Recent developments of discrete material optimization of laminated composite structures
Lund, Erik; Sørensen, Rene
2015-01-01
This work will give a quick summary of recent developments of the Discrete Material Optimization approach for structural optimization of laminated composite structures. This approach can be seen as a multi-material topology optimization approach for selecting the best ply material and number...... of plies in a laminated composite structure. The conceptual combinatorial design problem is relaxed to a continuous problem such that well-established gradient based optimization techniques can be applied, and the optimization problem is solved on basis of interpolation schemes with penalization...
Quasicanonical structure of optimal control in constrained discrete systems
Sieniutycz, S.
2003-06-01
This paper considers discrete processes governed by difference rather than differential equations for the state transformation. The basic question asked is if and when Hamiltonian canonical structures are possible in optimal discrete systems. Considering constrained discrete control, general optimization algorithms are derived that constitute suitable theoretical and computational tools when evaluating extremum properties of constrained physical models. The mathematical basis of the general theory is the Bellman method of dynamic programming (DP) and its extension in the form of the so-called Carathéodory-Boltyanski (CB) stage criterion which allows a variation of the terminal state that is otherwise fixed in the Bellman's method. Two relatively unknown, powerful optimization algorithms are obtained: an unconventional discrete formalism of optimization based on a Hamiltonian for multistage systems with unconstrained intervals of holdup time, and the time interval constrained extension of the formalism. These results are general; namely, one arrives at: the discrete canonical Hamilton equations, maximum principles, and (at the continuous limit of processes with free intervals of time) the classical Hamilton-Jacobi theory along with all basic results of variational calculus. Vast spectrum of applications of the theory is briefly discussed.
Parker, R Gary
1988-01-01
This book treats the fundamental issues and algorithmic strategies emerging as the core of the discipline of discrete optimization in a comprehensive and rigorous fashion. Following an introductory chapter on computational complexity, the basic algorithmic results for the two major models of polynomial algorithms are introduced--models using matroids and linear programming. Further chapters treat the major non-polynomial algorithms: branch-and-bound and cutting planes. The text concludes with a chapter on heuristic algorithms.Several appendixes are included which review the fundamental ideas o
Henrichsen, Søren Randrup; Lindgaard, Esben; Lund, Erik
2015-01-01
Robust buckling optimal design of laminated composite structures is conducted in this work. Optimal designs are obtained by considering geometric imperfections in the optimization procedure. Discrete Material Optimization is applied to obtain optimal laminate designs. The optimal geometric...... imperfection is represented by the “worst” shape imperfection. The two optimization problems are combined through the recurrence optimization. Hereby the imperfection sensitivity of the considered structures can be studied. The recurrence optimization is demonstrated through a U-profile and a cylindrical panel...... example. The imperfection sensitivity of the optimized structure decreases during the recurrence optimization for both examples, hence robust buckling optimal structures are designed....
Topology and layout optimization of discrete and continuum structures
Bendsoe, Martin P.; Kikuchi, Noboru
1993-01-01
The basic features of the ground structure method for truss structure an continuum problems are described. Problems with a large number of potential structural elements are considered using the compliance of the structure as the objective function. The design problem is the minimization of compliance for a given structural weight, and the design variables for truss problems are the cross-sectional areas of the individual truss members, while for continuum problems they are the variable densities of material in each of the elements of the FEM discretization. It is shown how homogenization theory can be applied to provide a relation between material density and the effective material properties of a periodic medium with a known microstructure of material and voids.
Optimal Topology Design of Discrete Structures Resisting Degradation Effects
Achtziger, W.; Bendsøe, Martin P.
1999-01-01
In this technical note we treat the problem of finding the optimal topology of a truss, so that stiffness after degradation is maximized. It is shown that for the problem setting at hand, the optimal topology has uniform relative degradation in all bars and the topology is unchanged from the topo...
Lund, Erik
2017-01-01
This work extends the Discrete Material and Thickness Optimization approach to structural optimization problems where strength considerations in the form of failure criteria are taken into account for laminated composite structures. It takes offset in the density approaches applied for stress...... constrained topology optimization of single-material problems and develops formulations for multi-material topology optimization problems applied for laminated composite structures. The method can be applied for both stress- and strain-based failure criteria. The large number of local constraints is reduced...
State transformations and Hamiltonian structures for optimal control in discrete systems
Sieniutycz, S.
2006-04-01
Preserving usual definition of Hamiltonian H as the scalar product of rates and generalized momenta we investigate two basic classes of discrete optimal control processes governed by the difference rather than differential equations for the state transformation. The first class, linear in the time interval θ, secures the constancy of optimal H and satisfies a discrete Hamilton-Jacobi equation. The second class, nonlinear in θ, does not assure the constancy of optimal H and satisfies only a relationship that may be regarded as an equation of Hamilton-Jacobi type. The basic question asked is if and when Hamilton's canonical structures emerge in optimal discrete systems. For a constrained discrete control, general optimization algorithms are derived that constitute powerful theoretical and computational tools when evaluating extremum properties of constrained physical systems. The mathematical basis is Bellman's method of dynamic programming (DP) and its extension in the form of the so-called Carathéodory-Boltyanski (CB) stage optimality criterion which allows a variation of the terminal state that is otherwise fixed in Bellman's method. For systems with unconstrained intervals of the holdup time θ two powerful optimization algorithms are obtained: an unconventional discrete algorithm with a constant H and its counterpart for models nonlinear in θ. We also present the time-interval-constrained extension of the second algorithm. The results are general; namely, one arrives at: discrete canonical equations of Hamilton, maximum principles, and (at the continuous limit of processes with free intervals of time) the classical Hamilton-Jacobi theory, along with basic results of variational calculus. A vast spectrum of applications and an example are briefly discussed with particular attention paid to models nonlinear in the time interval θ.
Discrete particle swarm optimization for identifying community structures in signed social networks.
Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng
2014-10-01
Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.
DMTO – a method for Discrete Material and Thickness Optimization of laminated composite structures
Sørensen, Søren Nørgaard; Sørensen, Rene; Lund, Erik
2014-01-01
This paper presents a gradient based topology optimization method for Discrete Material and Thickness Optimization of laminated composite structures, labelled the DMTOmethod. The capabilities of the proposed method are demonstrated on mass minimization, subject to constraints on the structural...... criteria; buckling load factors, eigenfrequencies, and limited displacements. Furthermore, common design guidelines or rules, referred to as manufacturing constraints, are included explicitly in the optimization problem as series of linear inequalities. The material selection and thickness variation...... to manufacturability. The results will thus give insight into the relation between potential weight saving and design complexity. The results show that the DMTO method is capable of solving the problems robustly with only few intermediate valued design variables....
Lin, Albert; Fu, Sze-Ming; Chung, Yen-Kai; Lai, Shih-Yun; Tseng, Chi-Wei
2013-01-14
Surface plasmon enhancement has been proposed as a way to achieve higher absorption for thin-film photovoltaics, where surface plasmon polariton(SPP) and localized surface plasmon (LSP) are shown to provide dense near field and far field light scattering. Here it is shown that controlled far-field light scattering can be achieved using successive coupling between surface plasmonic (SP) nano-particles. Through genetic algorithm (GA) optimization, energy transfer between discrete nano-particles (ETDNP) is identified, which enhances solar cell efficiency. The optimized energy transfer structure acts like lumped-element transmission line and can properly alter the direction of photon flow. Increased in-plane component of wavevector is thus achieved and photon path length is extended. In addition, Wood-Rayleigh anomaly, at which transmission minimum occurs, is avoided through GA optimization. Optimized energy transfer structure provides 46.95% improvement over baseline planar cell. It achieves larger angular scattering capability compared to conventional surface plasmon polariton back reflector structure and index-guided structure due to SP energy transfer through mode coupling. Via SP mediated energy transfer, an alternative way to control the light flow inside thin-film is proposed, which can be more efficient than conventional index-guided mode using total internal reflection (TIR).
Discrete Optimization of Internal Part Structure via SLM Unit Structure-Performance Database
Li Tang
2018-01-01
Full Text Available The structural optimization of the internal structure of parts based on three-dimensional (3D printing has been recognized as being important in the field of mechanical design. The purpose of this paper is to present a creation of a unit structure-performance database based on the selective laser melting (SLM, which contains various structural units with different functions and records their structure and performance characteristics so that we can optimize the internal structure of parts directly, according to the database. The method of creating the unit structure-performance database was introduced in this paper and several structural units of the unit structure-performance database were introduced. The bow structure unit was used to show how to create the structure-performance database of the unit as an example. Some samples of the bow structure unit were designed and manufactured by SLM. These samples were tested in the WDW-100 compression testing machine to obtain their performance characteristics. After this, the paper collected all data regarding unit structure parameters, weight, performance characteristics, and other data; and, established a complete set of data from the bow structure unit for the unit structure-performance database. Furthermore, an aircraft part was reconstructed conveniently to be more lightweight according to the unit structure-performance database. Its weight was reduced by 36.8% when compared with the original structure, while the strength far exceeded the requirements.
Models and Methods for Structural Topology Optimization with Discrete Design Variables
Stolpe, Mathias
in the conceptual design phase to find innovative designs. The strength of topology optimization is the capability of determining both the optimal shape and the topology of the structure. In some cases also the optimal material properties can be determined. Optimal structural design problems are modeled...... such as bridges, airplanes, wind turbines, cars, etc. Topology optimization is a collection of theory, mathematical models, and numerical methods and is often used in the conceptual design phase to find innovative designs. The strength of topology optimization is the capability of determining both the optimal......Structural topology optimization is a multi-disciplinary research field covering optimal design of load carrying mechanical structures such as bridges, airplanes, wind turbines, cars, etc. Topology optimization is a collection of theory, mathematical models, and numerical methods and is often used...
Discrete computational structures
Korfhage, Robert R
1974-01-01
Discrete Computational Structures describes discrete mathematical concepts that are important to computing, covering necessary mathematical fundamentals, computer representation of sets, graph theory, storage minimization, and bandwidth. The book also explains conceptual framework (Gorn trees, searching, subroutines) and directed graphs (flowcharts, critical paths, information network). The text discusses algebra particularly as it applies to concentrates on semigroups, groups, lattices, propositional calculus, including a new tabular method of Boolean function minimization. The text emphasize
Luo, Biao; Liu, Derong; Wu, Huai-Ning
2018-06-01
Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.
Systematization of Accurate Discrete Optimization Methods
V. A. Ovchinnikov
2015-01-01
Full Text Available The object of study of this paper is to define accurate methods for solving combinatorial optimization problems of structural synthesis. The aim of the work is to systemize the exact methods of discrete optimization and define their applicability to solve practical problems.The article presents the analysis, generalization and systematization of classical methods and algorithms described in the educational and scientific literature.As a result of research a systematic presentation of combinatorial methods for discrete optimization described in various sources is given, their capabilities are described and properties of the tasks to be solved using the appropriate methods are specified.
Henrichsen, Søren Randrup; Lindgaard, Esben; Lund, Erik
2015-01-01
Robust design of laminated composite structures is considered in this work. Because laminated composite structures are often thin walled, buckling failure can occur prior to material failure, making it desirable to maximize the buckling load. However, as a structure always contains imperfections...... and “worst” shape imperfection optimizations to design robust composite structures. The approach is demonstrated on an U-profile where the imperfection sensitivity is monitored, and based on the example it can be concluded that robust designs can be obtained....
Discrete-time optimal control and games on large intervals
Zaslavski, Alexander J
2017-01-01
Devoted to the structure of approximate solutions of discrete-time optimal control problems and approximate solutions of dynamic discrete-time two-player zero-sum games, this book presents results on properties of approximate solutions in an interval that is independent lengthwise, for all sufficiently large intervals. Results concerning the so-called turnpike property of optimal control problems and zero-sum games in the regions close to the endpoints of the time intervals are the main focus of this book. The description of the structure of approximate solutions on sufficiently large intervals and its stability will interest graduate students and mathematicians in optimal control and game theory, engineering, and economics. This book begins with a brief overview and moves on to analyze the structure of approximate solutions of autonomous nonconcave discrete-time optimal control Lagrange problems.Next the structures of approximate solutions of autonomous discrete-time optimal control problems that are discret...
Handbook on modelling for discrete optimization
Pitsoulis, Leonidas; Williams, H
2006-01-01
The primary objective underlying the Handbook on Modelling for Discrete Optimization is to demonstrate and detail the pervasive nature of Discrete Optimization. While its applications cut across an incredibly wide range of activities, many of the applications are only known to specialists. It is the aim of this handbook to correct this. It has long been recognized that "modelling" is a critically important mathematical activity in designing algorithms for solving these discrete optimization problems. Nevertheless solving the resultant models is also often far from straightforward. In recent years it has become possible to solve many large-scale discrete optimization problems. However, some problems remain a challenge, even though advances in mathematical methods, hardware, and software technology have pushed the frontiers forward. This handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It will be done in an academic handbook treatment...
Discrete optimization in architecture extremely modular systems
Zawidzki, Machi
2017-01-01
This book is comprised of two parts, both of which explore modular systems: Pipe-Z (PZ) and Truss-Z (TZ), respectively. It presents several methods of creating PZ and TZ structures subjected to discrete optimization. The algorithms presented employ graph-theoretic and heuristic methods. The underlying idea of both systems is to create free-form structures using the minimal number of types of modular elements. PZ is more conceptual, as it forms single-branch mathematical knots with a single type of module. Conversely, TZ is a skeletal system for creating free-form pedestrian ramps and ramp networks among any number of terminals in space. In physical space, TZ uses two types of modules that are mirror reflections of each other. The optimization criteria discussed include: the minimal number of units, maximal adherence to the given guide paths, etc.
Discrete geometric structures for architecture
Pottmann, Helmut
2010-01-01
. The talk will provide an overview of recent progress in this field, with a particular focus on discrete geometric structures. Most of these result from practical requirements on segmenting a freeform shape into planar panels and on the physical realization
Optimization strategies for discrete multi-material stiffness optimization
Hvejsel, Christian Frier; Lund, Erik; Stolpe, Mathias
2011-01-01
Design of composite laminated lay-ups are formulated as discrete multi-material selection problems. The design problem can be modeled as a non-convex mixed-integer optimization problem. Such problems are in general only solvable to global optimality for small to moderate sized problems. To attack...... which numerically confirm the sought properties of the new scheme in terms of convergence to a discrete solution....
Thermodynamic framework for discrete optimal control in multiphase flow systems
Sieniutycz, Stanislaw
1999-08-01
Bellman's method of dynamic programming is used to synthesize diverse optimization approaches to active (work producing) and inactive (entropy generating) multiphase flow systems. Thermal machines, optimally controlled unit operations, nonlinear heat conduction, spontaneous relaxation processes, and self-propagating wave fronts are all shown to satisfy a discrete Hamilton-Jacobi-Bellman equation and a corresponding discrete optimization algorithm of Pontryagin's type, with the maximum principle for a Hamiltonian. The extremal structures are always canonical. A common unifying criterion is set for all considered systems, which is the criterion of a minimum generated entropy. It is shown that constraints can modify the entropy functionals in a different way for each group of the processes considered; thus the resulting structures of these functionals may differ significantly. Practical conclusions are formulated regarding the energy savings and energy policy in optimally controlled systems.
Meshes optimized for discrete exterior calculus (DEC).
Mousley, Sarah C. [Univ. of Illinois, Urbana-Champaign, IL (United States); Deakin, Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Knupp, Patrick [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mitchell, Scott A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-12-01
We study the optimization of an energy function used by the meshing community to measure and improve mesh quality. This energy is non-traditional because it is dependent on both the primal triangulation and its dual Voronoi (power) diagram. The energy is a measure of the mesh's quality for usage in Discrete Exterior Calculus (DEC), a method for numerically solving PDEs. In DEC, the PDE domain is triangulated and this mesh is used to obtain discrete approximations of the continuous operators in the PDE. The energy of a mesh gives an upper bound on the error of the discrete diagonal approximation of the Hodge star operator. In practice, one begins with an initial mesh and then makes adjustments to produce a mesh of lower energy. However, we have discovered several shortcomings in directly optimizing this energy, e.g. its non-convexity, and we show that the search for an optimized mesh may lead to mesh inversion (malformed triangles). We propose a new energy function to address some of these issues.
MacBain, Keith M
2009-01-01
Intends to supplement the engineer's box of analysis and design tools making optimization as commonplace as the finite element method in the engineering workplace. This title introduces structural optimization and the methods of nonlinear programming such as Lagrange multipliers, Kuhn-Tucker conditions, and calculus of variations.
Discrete geometric structures for architecture
Pottmann, Helmut
2010-06-13
The emergence of freeform structures in contemporary architecture raises numerous challenging research problems, most of which are related to the actual fabrication and are a rich source of research topics in geometry and geometric computing. The talk will provide an overview of recent progress in this field, with a particular focus on discrete geometric structures. Most of these result from practical requirements on segmenting a freeform shape into planar panels and on the physical realization of supporting beams and nodes. A study of quadrilateral meshes with planar faces reveals beautiful relations to discrete differential geometry. In particular, we discuss meshes which discretize the network of principal curvature lines. Conical meshes are among these meshes; they possess conical offset meshes at a constant face/face distance, which in turn leads to a supporting beam layout with so-called torsion free nodes. This work can be generalized to a variety of multilayer structures and laid the ground for an adapted curvature theory for these meshes. There are also efforts on segmenting surfaces into planar hexagonal panels. Though these are less constrained than planar quadrilateral panels, this problem is still waiting for an elegant solution. Inspired by freeform designs in architecture which involve circles and spheres, we present a new kind of triangle mesh whose faces\\' in-circles form a packing, i.e., the in-circles of two triangles with a common edge have the same contact point on that edge. These "circle packing (CP) meshes" exhibit an aesthetic balance of shape and size of their faces. They are closely tied to sphere packings on surfaces and to various remarkable structures and patterns which are of interest in art, architecture, and design. CP meshes constitute a new link between architectural freeform design and computational conformal geometry. Recently, certain timber structures motivated us to study discrete patterns of geodesics on surfaces. This
Finite Volumes Discretization of Topology Optimization Problems
Evgrafov, Anton; Gregersen, Misha Marie; Sørensen, Mads Peter
, FVMs represent a standard method of discretization within engineering communities dealing with computational uid dy- namics, transport, and convection-reaction problems. Among various avours of FVMs, cell based approaches, where all variables are associated only with cell centers, are particularly...... computations is done using nite element methods (FEMs). Despite some limited recent eorts [1, 2], we have only started to develop our understanding of the interplay between the control in the coecients and FVMs. Recent advances in discrete functional analysis allow us to analyze convergence of FVM...... of the induced parametrization of the design space that allows optimization algorithms to eciently explore it, and the ease of integration with existing computational codes in a variety of application areas, the simplicity and eciency of sensitivity analyses|all stemming from the use of the same grid throughout...
Discrete optimization in architecture architectural & urban layout
Zawidzki, Machi
2016-01-01
This book presents three projects that demonstrate the fundamental problems of architectural design and urban composition – the layout design, evaluation and optimization. Part I describes the functional layout design of a residential building, and an evaluation of the quality of a town square (plaza). The algorithm for the functional layout design is based on backtracking using a constraint satisfaction approach combined with coarse grid discretization. The algorithm for the town square evaluation is based on geometrical properties derived directly from its plan. Part II introduces a crowd-simulation application for the analysis of escape routes on floor plans, and optimization of a floor plan for smooth crowd flow. The algorithms presented employ agent-based modeling and cellular automata.
Integrals of Motion for Discrete-Time Optimal Control Problems
Torres, Delfim F. M.
2003-01-01
We obtain a discrete time analog of E. Noether's theorem in Optimal Control, asserting that integrals of motion associated to the discrete time Pontryagin Maximum Principle can be computed from the quasi-invariance properties of the discrete time Lagrangian and discrete time control system. As corollaries, results for first-order and higher-order discrete problems of the calculus of variations are obtained.
Truss topology optimization with discrete design variables by outer approximation
Stolpe, Mathias
2015-01-01
Several variants of an outer approximation method are proposed to solve truss topology optimization problems with discrete design variables to proven global optimality. The objective is to minimize the volume of the structure while satisfying constraints on the global stiffness of the structure...... for classical outer approximation approaches applied to optimal design problems. A set of two- and three-dimensional benchmark problems are solved and the numerical results suggest that the proposed approaches are competitive with other special-purpose global optimization methods for the considered class...... under the applied loads. We extend the natural problem formulation by adding redundant force variables and force equilibrium constraints. This guarantees that the designs suggested by the relaxed master problems are capable of carrying the applied loads, a property which is generally not satisfied...
Search Parameter Optimization for Discrete, Bayesian, and Continuous Search Algorithms
2017-09-01
NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS SEARCH PARAMETER OPTIMIZATION FOR DISCRETE , BAYESIAN, AND CONTINUOUS SEARCH ALGORITHMS by...to 09-22-2017 4. TITLE AND SUBTITLE SEARCH PARAMETER OPTIMIZATION FOR DISCRETE , BAYESIAN, AND CON- TINUOUS SEARCH ALGORITHMS 5. FUNDING NUMBERS 6...simple search and rescue acts to prosecuting aerial/surface/submersible targets on mission. This research looks at varying the known discrete and
On the application of Discrete Time Optimal Control Concepts to ...
On the application of Discrete Time Optimal Control Concepts to Economic Problems. ... Journal of the Nigerian Association of Mathematical Physics ... Abstract. An extension of the use of the maximum principle to solve Discrete-time Optimal Control Problems (DTOCP), in which the state equations are in the form of general ...
Sørensen, Søren Nørgaard; Lund, Erik
2012-01-01
This work concerns a novel large-scale multi-material topology optimization method for simultaneous determination of the optimum variable integer thickness and fiber orientation throughout laminate structures with fixed outer geometries while adhering to certain manufacturing constraints....... The conceptual combinatorial/integer problem is relaxed to a continuous problem and solved on basis of the so-called Discrete Material Optimization method, explicitly including the manufacturing constraints as linear constraints....
Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.
Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang
2017-11-01
Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.
In-plane material continuity for the discrete material optimization method
Sørensen, Rene; Lund, Erik
2015-01-01
When performing discrete material optimization of laminated composite structures, the variation of the in-plane material continuity is typically governed by the size of the finite element discretization. For a fine mesh, this can lead to designs that cannot be manufactured due to the complexity...
Quadratic Term Structure Models in Discrete Time
Marco Realdon
2006-01-01
This paper extends the results on quadratic term structure models in continuos time to the discrete time setting. The continuos time setting can be seen as a special case of the discrete time one. Recursive closed form solutions for zero coupon bonds are provided even in the presence of multiple correlated underlying factors. Pricing bond options requires simple integration. Model parameters may well be time dependent without scuppering such tractability. Model estimation does not require a r...
Achtziger, Wolfgang; Stolpe, Mathias
2007-01-01
this problem is well-studied for continuous bar areas, we consider in this study the case of discrete areas. This problem is of major practical relevance if the truss must be built from pre-produced bars with given areas. As a special case, we consider the design problem for a single available bar area, i.......e., a 0/1 problem. In contrast to the heuristic methods considered in many other approaches, our goal is to compute guaranteed globally optimal structures. This is done by a branch-and-bound method for which convergence can be proven. In this branch-and-bound framework, lower bounds of the optimal......-integer problems. The main intention of this paper is to provide optimal solutions for single and multiple load benchmark examples, which can be used for testing and validating other methods or heuristics for the treatment of this discrete topology design problem....
Galerkin v. discrete-optimal projection in nonlinear model reduction
Carlberg, Kevin Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Barone, Matthew Franklin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Antil, Harbir [George Mason Univ., Fairfax, VA (United States)
2015-04-01
Discrete-optimal model-reduction techniques such as the Gauss{Newton with Approximated Tensors (GNAT) method have shown promise, as they have generated stable, accurate solutions for large-scale turbulent, compressible ow problems where standard Galerkin techniques have failed. However, there has been limited comparative analysis of the two approaches. This is due in part to difficulties arising from the fact that Galerkin techniques perform projection at the time-continuous level, while discrete-optimal techniques do so at the time-discrete level. This work provides a detailed theoretical and experimental comparison of the two techniques for two common classes of time integrators: linear multistep schemes and Runge{Kutta schemes. We present a number of new ndings, including conditions under which the discrete-optimal ROM has a time-continuous representation, conditions under which the two techniques are equivalent, and time-discrete error bounds for the two approaches. Perhaps most surprisingly, we demonstrate both theoretically and experimentally that decreasing the time step does not necessarily decrease the error for the discrete-optimal ROM; instead, the time step should be `matched' to the spectral content of the reduced basis. In numerical experiments carried out on a turbulent compressible- ow problem with over one million unknowns, we show that increasing the time step to an intermediate value decreases both the error and the simulation time of the discrete-optimal reduced-order model by an order of magnitude.
Intelligent discrete particle swarm optimization for multiprocessor task scheduling problem
S Sarathambekai
2017-03-01
Full Text Available Discrete particle swarm optimization is one of the most recently developed population-based meta-heuristic optimization algorithm in swarm intelligence that can be used in any discrete optimization problems. This article presents a discrete particle swarm optimization algorithm to efficiently schedule the tasks in the heterogeneous multiprocessor systems. All the optimization algorithms share a common algorithmic step, namely population initialization. It plays a significant role because it can affect the convergence speed and also the quality of the final solution. The random initialization is the most commonly used method in majority of the evolutionary algorithms to generate solutions in the initial population. The initial good quality solutions can facilitate the algorithm to locate the optimal solution or else it may prevent the algorithm from finding the optimal solution. Intelligence should be incorporated to generate the initial population in order to avoid the premature convergence. This article presents a discrete particle swarm optimization algorithm, which incorporates opposition-based technique to generate initial population and greedy algorithm to balance the load of the processors. Make span, flow time, and reliability cost are three different measures used to evaluate the efficiency of the proposed discrete particle swarm optimization algorithm for scheduling independent tasks in distributed systems. Computational simulations are done based on a set of benchmark instances to assess the performance of the proposed algorithm.
Discrete-continuous analysis of optimal equipment replacement
YATSENKO, Yuri; HRITONENKO, Natali
2008-01-01
In Operations Research, the equipment replacement process is usually modeled in discrete time. The optimal replacement strategies are found from discrete (or integer) programming problems, well known for their analytic and computational complexity. An alternative approach is represented by continuous-time vintage capital models that explicitly involve the equipment lifetime and are described by nonlinear integral equations. Then the optimal replacement is determined via the opt...
Discrete-time inverse optimal control for nonlinear systems
Sanchez, Edgar N
2013-01-01
Discrete-Time Inverse Optimal Control for Nonlinear Systems proposes a novel inverse optimal control scheme for stabilization and trajectory tracking of discrete-time nonlinear systems. This avoids the need to solve the associated Hamilton-Jacobi-Bellman equation and minimizes a cost functional, resulting in a more efficient controller. Design More Efficient Controllers for Stabilization and Trajectory Tracking of Discrete-Time Nonlinear Systems The book presents two approaches for controller synthesis: the first based on passivity theory and the second on a control Lyapunov function (CLF). Th
Comments on `A discrete optimal control problem for descriptor systems'
Ravn, Hans
1990-01-01
In the above-mentioned work (see ibid., vol.34, p.177-81 (1989)), necessary and sufficient optimality conditions are derived for a discrete-time optimal problem, as well as other specific cases of implicit and explicit dynamic systems. The commenter corrects a mistake and demonstrates that there ......In the above-mentioned work (see ibid., vol.34, p.177-81 (1989)), necessary and sufficient optimality conditions are derived for a discrete-time optimal problem, as well as other specific cases of implicit and explicit dynamic systems. The commenter corrects a mistake and demonstrates...
Discrete Biogeography Based Optimization for Feature Selection in Molecular Signatures.
Liu, Bo; Tian, Meihong; Zhang, Chunhua; Li, Xiangtao
2015-04-01
Biomarker discovery from high-dimensional data is a complex task in the development of efficient cancer diagnoses and classification. However, these data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a discrete biogeography based optimization is proposed to select the good subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the fisher-markov selector is used to choose fixed number of gene data. Secondly, to make biogeography based optimization suitable for the feature selection problem; discrete migration model and discrete mutation model are proposed to balance the exploration and exploitation ability. Then, discrete biogeography based optimization, as we called DBBO, is proposed by integrating discrete migration model and discrete mutation model. Finally, the DBBO method is used for feature selection, and three classifiers are used as the classifier with the 10 fold cross-validation method. In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on four breast cancer dataset benchmarks. Comparison with genetic algorithm, particle swarm optimization, differential evolution algorithm and hybrid biogeography based optimization, experimental results demonstrate that the proposed method is better or at least comparable with previous method from literature when considering the quality of the solutions obtained. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Engineering applications of discrete-time optimal control
Vidal, Rene Victor Valqui; Ravn, Hans V.
1990-01-01
Many problems of design and operation of engineering systems can be formulated as optimal control problems where time has been discretisized. This is also true even if 'time' is not involved in the formulation of the problem, but rather another one-dimensional parameter. This paper gives a review...... of some well-known and new results in discrete time optimal control methods applicable to practical problem solving within engineering. Emphasis is placed on dynamic programming, the classical maximum principle and generalized versions of the maximum principle for optimal control of discrete time systems...
Optimization of Operations Resources via Discrete Event Simulation Modeling
Joshi, B.; Morris, D.; White, N.; Unal, R.
1996-01-01
The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.
Optimal weights for circle fitting with discrete granular data
Chernov, N.; Kolganova, E.; Ososkov, G.
1995-01-01
The problem of the data approximation measured along a circle by modern detectors in high energy physics, as for example, RICH (Ring Imaging Cherenkov) is considered. Such detectors having the discrete cell structure register the energy dissipation produced by a passing elementary particle not in a single point, but in several adjacent cells where all this energy is distributed. The presence of background hits makes inapplicable circle fitting methods based on the least square fit due to their noise sensitivity. In this paper it's shown that the efficient way to overcome these problems of the curve fitting is the robust fitting technique based on a reweighted least square method with optimally chosen weights, obtained by the use of maximum likelihood estimates. Results of numerical experiments are given proving the high efficiency of the suggested method. 9 refs., 5 figs., 1 tab
Augmented Lagrangian Method For Discretized Optimal Control ...
In this paper, we are concerned with one-dimensional time invariant optimal control problem, whose objective function is quadratic and the dynamical system is a differential equation with initial condition .Since most real life problems are nonlinear and their analytical solutions are not readily available, we resolve to ...
Optimal Robust Fault Detection for Linear Discrete Time Systems
Nike Liu
2008-01-01
Full Text Available This paper considers robust fault-detection problems for linear discrete time systems. It is shown that the optimal robust detection filters for several well-recognized robust fault-detection problems, such as ℋ−/ℋ∞, ℋ2/ℋ∞, and ℋ∞/ℋ∞ problems, are the same and can be obtained by solving a standard algebraic Riccati equation. Optimal filters are also derived for many other optimization criteria and it is shown that some well-studied and seeming-sensible optimization criteria for fault-detection filter design could lead to (optimal but useless fault-detection filters.
Discrete structures in F-theory compactifications
Till, Oskar
2016-05-04
In this thesis we study global properties of F-theory compactifications on elliptically and genus-one fibered Calabi-Yau varieties. This is motivated by phenomenological considerations as well as by the need for a deeper understanding of the set of consistent F-theory vacua. The global geometric features arise from discrete and arithmetic structures in the torus fiber and can be studied in detail for fibrations over generic bases. In the case of elliptic fibrations we study the role of the torsion subgroup of the Mordell-Weil group of sections in four dimensional compactifications. We show how the existence of a torsional section restricts the admissible matter representations in the theory. This is shown to be equivalent to inducing a non-trivial fundamental group of the gauge group. Compactifying F-theory on genus-one fibrations with multisections gives rise to discrete selection rules. In field theory the discrete symmetry is a broken U(1) symmetry. In the geometry the higgsing corresponds to a conifold transition. We explain in detail the origin of the discrete symmetry from two different M-theory phases and put the result into the context of torsion homology. Finally we systematically construct consistent gauge fluxes on genus-one fibrations and show that these induce an anomaly free chiral spectrum.
Discrete Optimization in Chemical Space Reference Manual
2012-10-01
includes instructions on setting up constrained optimizations of substitutional frameworks and the full application programming interface ( API ) necessary...space size • bool space size computed • ulong bits • bool bits computed • string Nam 4.26.1 Detailed Description This class provides the API that...1, 0) 1102 (O, 0, 1.4, -3, 120, -2, 180) 1103 (C, 1, 1.5, 0, 120, -3, -30(150)) 1104 (H, 2, 1.1, 1, 109.47, 0,180) 1105 (H, 2, 1.1, 1, 109.47, 3, 120
Discrete stochastic processes and optimal filtering
Bertein, Jean-Claude
2012-01-01
Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which ar
Modified Discrete Grey Wolf Optimizer Algorithm for Multilevel Image Thresholding
Linguo Li
2017-01-01
Full Text Available The computation of image segmentation has become more complicated with the increasing number of thresholds, and the option and application of the thresholds in image thresholding fields have become an NP problem at the same time. The paper puts forward the modified discrete grey wolf optimizer algorithm (MDGWO, which improves on the optimal solution updating mechanism of the search agent by the weights. Taking Kapur’s entropy as the optimized function and based on the discreteness of threshold in image segmentation, the paper firstly discretizes the grey wolf optimizer (GWO and then proposes a new attack strategy by using the weight coefficient to replace the search formula for optimal solution used in the original algorithm. The experimental results show that MDGWO can search out the optimal thresholds efficiently and precisely, which are very close to the result examined by exhaustive searches. In comparison with the electromagnetism optimization (EMO, the differential evolution (DE, the Artifical Bee Colony (ABC, and the classical GWO, it is concluded that MDGWO has advantages over the latter four in terms of image segmentation quality and objective function values and their stability.
Heuristic Optimization for the Discrete Virtual Power Plant Dispatch Problem
Petersen, Mette Kirschmeyer; Hansen, Lars Henrik; Bendtsen, Jan Dimon
2014-01-01
We consider a Virtual Power Plant, which is given the task of dispatching a fluctuating power supply to a portfolio of flexible consumers. The flexible consumers are modeled as discrete batch processes, and the associated optimization problem is denoted the Discrete Virtual Power Plant Dispatch...... Problem. First NP-completeness of the Discrete Virtual Power Plant Dispatch Problem is proved formally. We then proceed to develop tailored versions of the meta-heuristic algorithms Hill Climber and Greedy Randomized Adaptive Search Procedure (GRASP). The algorithms are tuned and tested on portfolios...... of varying sizes. We find that all the tailored algorithms perform satisfactorily in the sense that they are able to find sub-optimal, but usable, solutions to very large problems (on the order of 10 5 units) at computation times on the scale of just 10 seconds, which is far beyond the capabilities...
Discrete optimization in architecture building envelope
Zawidzki, Machi
2017-01-01
This book explores the extremely modular systems that meet two criteria: they allow the creation of structurally sound free-form structures, and they are comprised of as few types of modules as possible. Divided into two parts, it presents Pipe-Z (PZ) and Truss-Z (TZ) systems. PZ is more fundamental and forms spatial mathematical knots by assembling one type of unit (PZM). The shape of PZ is controlled by relative twists of a sequence of congruent PZMs. TZ is a skeletal system for creating free-form pedestrian ramps and ramp networks among any number of terminals in space. TZ structures are composed of four variations of a single basic unit subjected to affine transformations (mirror reflection, rotation and combination of both). .
Design and fabrication of topologically optimized structures;
Feringa, Jelle; Søndergaard, Asbjørn
2012-01-01
Integral structural optimization and fabrication seeks the synthesis of two original approaches; that of topological optimization (TO) and robotic hotwire cutting (HWC) (Mcgee 2011). TO allows for the reduction of up to 70% of the volume of concrete to support a given structure (Sondergaard...... & Dombernowsky 2011). A strength of the method is that it allows to come up with structural designs that lie beyond the grasp of traditional means of design. A design space is a discretized volume, delimiting where the optimization will take place. The number of cells used to discretize the design space thus...
A discrete optimization method for nuclear fuel management
Argaud, J.P.
1993-01-01
Nuclear fuel management can be seen as a large discrete optimization problem under constraints, and optimization methods on such problems are numerically costly. After an introduction of the main aspects of nuclear fuel management, this paper presents a new way to treat the combinatorial problem by using information included in the gradient of optimized cost function. A new search process idea is to choose, by direct observation of the gradient, the more interesting changes in fuel loading patterns. An example is then developed to illustrate an operating mode of the method. Finally, connections with classical simulated annealing and genetic algorithms are described as an attempt to improve search processes. 16 refs., 2 figs
Integrable structure in discrete shell membrane theory.
Schief, W K
2014-05-08
We present natural discrete analogues of two integrable classes of shell membranes. By construction, these discrete shell membranes are in equilibrium with respect to suitably chosen internal stresses and external forces. The integrability of the underlying equilibrium equations is proved by relating the geometry of the discrete shell membranes to discrete O surface theory. We establish connections with generalized barycentric coordinates and nine-point centres and identify a discrete version of the classical Gauss equation of surface theory.
Yue Wu
2017-01-01
Full Text Available Firefly Algorithm (FA, for short is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly, development of structural topology optimization method and the basic principle of standard FA are introduced in detail. Then, in order to apply the algorithm to optimization problems with discrete variables, the initial positions of fireflies and the position updating formula are discretized. By embedding the random-weight and enhancing the attractiveness, the performance of this algorithm is improved, and thus an Improved Firefly Algorithm (IFA, for short is proposed. Furthermore, using size variables which are capable of including topology variables and size and topology optimization for trusses with discrete variables is formulated based on the Ground Structure Approach. The essential techniques of variable elastic modulus technology and geometric construction analysis are applied in the structural analysis process. Subsequently, an optimization method for the size and topological design of trusses based on the IFA is introduced. Finally, two numerical examples are shown to verify the feasibility and efficiency of the proposed method by comparing with different deterministic methods.
Discrete Haar transform and protein structure.
Morosetti, S
1997-12-01
The discrete Haar transform of the sequence of the backbone dihedral angles (phi and psi) was performed over a set of X-ray protein structures of high resolution from the Brookhaven Protein Data Bank. Afterwards, the new dihedral angles were calculated by the inverse transform, using a growing number of Haar functions, from the lower to the higher degree. New structures were obtained using these dihedral angles, with standard values for bond lengths and angles, and with omega = 0 degree. The reconstructed structures were compared with the experimental ones, and analyzed by visual inspection and statistical analysis. When half of the Haar coefficients were used, all the reconstructed structures were not yet collapsed to a tertiary folding, but they showed yet realized most of the secondary motifs. These results indicate a substantial separation of structural information in the space of Haar transform, with the secondary structural information mainly present in the Haar coefficients of lower degrees, and the tertiary one present in the higher degree coefficients. Because of this separation, the representation of the folded structures in the space of Haar transform seems a promising candidate to encompass the problem of premature convergence in genetic algorithms.
Discrete size optimization of steel trusses using a refined big bang-big crunch algorithm
Hasançebi, O.; Kazemzadeh Azad, S.
2014-01-01
This article presents a methodology that provides a method for design optimization of steel truss structures based on a refined big bang-big crunch (BB-BC) algorithm. It is shown that a standard formulation of the BB-BC algorithm occasionally falls short of producing acceptable solutions to problems from discrete size optimum design of steel trusses. A reformulation of the algorithm is proposed and implemented for design optimization of various discrete truss structures according to American Institute of Steel Construction Allowable Stress Design (AISC-ASD) specifications. Furthermore, the performance of the proposed BB-BC algorithm is compared to its standard version as well as other well-known metaheuristic techniques. The numerical results confirm the efficiency of the proposed algorithm in practical design optimization of truss structures.
Sur, Chiranjib; Shukla, Anupam
2018-03-01
Bacteria Foraging Optimisation Algorithm is a collective behaviour-based meta-heuristics searching depending on the social influence of the bacteria co-agents in the search space of the problem. The algorithm faces tremendous hindrance in terms of its application for discrete problems and graph-based problems due to biased mathematical modelling and dynamic structure of the algorithm. This had been the key factor to revive and introduce the discrete form called Discrete Bacteria Foraging Optimisation (DBFO) Algorithm for discrete problems which exceeds the number of continuous domain problems represented by mathematical and numerical equations in real life. In this work, we have mainly simulated a graph-based road multi-objective optimisation problem and have discussed the prospect of its utilisation in other similar optimisation problems and graph-based problems. The various solution representations that can be handled by this DBFO has also been discussed. The implications and dynamics of the various parameters used in the DBFO are illustrated from the point view of the problems and has been a combination of both exploration and exploitation. The result of DBFO has been compared with Ant Colony Optimisation and Intelligent Water Drops Algorithms. Important features of DBFO are that the bacteria agents do not depend on the local heuristic information but estimates new exploration schemes depending upon the previous experience and covered path analysis. This makes the algorithm better in combination generation for graph-based problems and combination generation for NP hard problems.
Thuburn, J.; Woollings, T.J.
2005-01-01
Accurate representation of different kinds of wave motion is essential for numerical models of the atmosphere, but is sensitive to details of the discretization. In this paper, numerical dispersion relations are computed for different vertical discretizations of the compressible Euler equations and compared with the analytical dispersion relation. A height coordinate, an isentropic coordinate, and a terrain-following mass-based coordinate are considered, and, for each of these, different choices of prognostic variables and grid staggerings are considered. The discretizations are categorized according to whether their dispersion relations are optimal, are near optimal, have a single zero-frequency computational mode, or are problematic in other ways. Some general understanding of the factors that affect the numerical dispersion properties is obtained: heuristic arguments concerning the normal mode structures, and the amount of averaging and coarse differencing in the finite difference scheme, are shown to be useful guides to which configurations will be optimal; the number of degrees of freedom in the discretization is shown to be an accurate guide to the existence of computational modes; there is only minor sensitivity to whether the equations for thermodynamic variables are discretized in advective form or flux form; and an accurate representation of acoustic modes is found to be a prerequisite for accurate representation of inertia-gravity modes, which, in turn, is found to be a prerequisite for accurate representation of Rossby modes
Fast and Epsilon-Optimal Discretized Pursuit Learning Automata.
Zhang, JunQi; Wang, Cheng; Zhou, MengChu
2015-10-01
Learning automata (LA) are powerful tools for reinforcement learning. A discretized pursuit LA is the most popular one among them. During an iteration its operation consists of three basic phases: 1) selecting the next action; 2) finding the optimal estimated action; and 3) updating the state probability. However, when the number of actions is large, the learning becomes extremely slow because there are too many updates to be made at each iteration. The increased updates are mostly from phases 1 and 3. A new fast discretized pursuit LA with assured ε -optimality is proposed to perform both phases 1 and 3 with the computational complexity independent of the number of actions. Apart from its low computational complexity, it achieves faster convergence speed than the classical one when operating in stationary environments. This paper can promote the applications of LA toward the large-scale-action oriented area that requires efficient reinforcement learning tools with assured ε -optimality, fast convergence speed, and low computational complexity for each iteration.
Discrete Tomography and Imaging of Polycrystalline Structures
Alpers, Andreas
High resolution transmission electron microscopy is commonly considered as the standard application for discrete tomography. While this has yet to be technically realized, new applications with a similar flavor have emerged in materials science. In our group at Ris� DTU (Denmark's National...... Laboratory for Sustainable Energy), for instance, we study polycrystalline materials via synchrotron X-ray diffraction. Several reconstruction problems arise, most of them exhibit inherently discrete aspects. In this talk I want to give a concise mathematical introduction to some of these reconstruction...... problems. Special focus is on their relationship to classical discrete tomography. Several open mathematical questions will be mentioned along the way....
A stochastic discrete optimization model for designing container terminal facilities
Zukhruf, Febri; Frazila, Russ Bona; Burhani, Jzolanda Tsavalista
2017-11-01
As uncertainty essentially affect the total transportation cost, it remains important in the container terminal that incorporates several modes and transshipments process. This paper then presents a stochastic discrete optimization model for designing the container terminal, which involves the decision of facilities improvement action. The container terminal operation model is constructed by accounting the variation of demand and facilities performance. In addition, for illustrating the conflicting issue that practically raises in the terminal operation, the model also takes into account the possible increment delay of facilities due to the increasing number of equipment, especially the container truck. Those variations expectantly reflect the uncertainty issue in the container terminal operation. A Monte Carlo simulation is invoked to propagate the variations by following the observed distribution. The problem is constructed within the framework of the combinatorial optimization problem for investigating the optimal decision of facilities improvement. A new variant of glow-worm swarm optimization (GSO) is thus proposed for solving the optimization, which is rarely explored in the transportation field. The model applicability is tested by considering the actual characteristics of the container terminal.
Multiscale Path Metrics for the Analysis of Discrete Geometric Structures
2017-11-30
Report: Multiscale Path Metrics for the Analysis of Discrete Geometric Structures The views, opinions and/or findings contained in this report are those...Analysis of Discrete Geometric Structures Report Term: 0-Other Email: tomasi@cs.duke.edu Distribution Statement: 1-Approved for public release
Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.
Wei, Qinglai; Li, Benkai; Song, Ruizhuo
2018-04-01
In this paper, a generalized policy iteration (GPI) algorithm with approximation errors is developed for solving infinite horizon optimal control problems for nonlinear systems. The developed stable GPI algorithm provides a general structure of discrete-time iterative adaptive dynamic programming algorithms, by which most of the discrete-time reinforcement learning algorithms can be described using the GPI structure. It is for the first time that approximation errors are explicitly considered in the GPI algorithm. The properties of the stable GPI algorithm with approximation errors are analyzed. The admissibility of the approximate iterative control law can be guaranteed if the approximation errors satisfy the admissibility criteria. The convergence of the developed algorithm is established, which shows that the iterative value function is convergent to a finite neighborhood of the optimal performance index function, if the approximate errors satisfy the convergence criterion. Finally, numerical examples and comparisons are presented.
Maruno, Ken-ichi; Biondini, Gino
2004-01-01
We present a class of solutions of the two-dimensional Toda lattice equation, its fully discrete analogue and its ultra-discrete limit. These solutions demonstrate the existence of soliton resonance and web-like structure in discrete integrable systems such as differential-difference equations, difference equations and cellular automata (ultra-discrete equations)
A Global Network Alignment Method Using Discrete Particle Swarm Optimization.
Huang, Jiaxiang; Gong, Maoguo; Ma, Lijia
2016-10-19
Molecular interactions data increase exponentially with the advance of biotechnology. This makes it possible and necessary to comparatively analyse the different data at a network level. Global network alignment is an important network comparison approach to identify conserved subnetworks and get insight into evolutionary relationship across species. Network alignment which is analogous to subgraph isomorphism is known to be an NP-hard problem. In this paper, we introduce a novel heuristic Particle-Swarm-Optimization based Network Aligner (PSONA), which optimizes a weighted global alignment model considering both protein sequence similarity and interaction conservations. The particle statuses and status updating rules are redefined in a discrete form by using permutation. A seed-and-extend strategy is employed to guide the searching for the superior alignment. The proposed initialization method "seeds" matches with high sequence similarity into the alignment, which guarantees the functional coherence of the mapping nodes. A greedy local search method is designed as the "extension" procedure to iteratively optimize the edge conservations. PSONA is compared with several state-of-art methods on ten network pairs combined by five species. The experimental results demonstrate that the proposed aligner can map the proteins with high functional coherence and can be used as a booster to effectively refine the well-studied aligners.
Prolongation Structure of Semi-discrete Nonlinear Evolution Equations
Bai Yongqiang; Wu Ke; Zhao Weizhong; Guo Hanying
2007-01-01
Based on noncommutative differential calculus, we present a theory of prolongation structure for semi-discrete nonlinear evolution equations. As an illustrative example, a semi-discrete model of the nonlinear Schroedinger equation is discussed in terms of this theory and the corresponding Lax pairs are also given.
Rasmussen, Marie-Louise Højlund; Stolpe, Mathias
2008-01-01
the physics, and the cuts (Combinatorial Benders’ and projected Chvátal–Gomory) come from an understanding of the particular mathematical structure of the reformulation. The impact of a stronger representation is investigated on several truss topology optimization problems in two and three dimensions.......The subject of this article is solving discrete truss topology optimization problems with local stress and displacement constraints to global optimum. We consider a formulation based on the Simultaneous ANalysis and Design (SAND) approach. This intrinsically non-convex problem is reformulated...
Discretization model for nonlinear dynamic analysis of three dimensional structures
Hayashi, Y.
1982-12-01
A discretization model for nonlinear dynamic analysis of three dimensional structures is presented. The discretization is achieved through a three dimensional spring-mass system and the dynamic response obtained by direct integration of the equations of motion using central diferences. First the viability of the model is verified through the analysis of homogeneous linear structures and then its performance in the analysis of structures subjected to impulsive or impact loads, taking into account both geometrical and physical nonlinearities is evaluated. (Author) [pt
Seslija, Marko; van der Schaft, Arjan; Scherpen, Jacquelien M.A.
This paper addresses the issue of structure-preserving discretization of open distributed-parameter systems with Hamiltonian dynamics. Employing the formalism of discrete exterior calculus, we introduce a simplicial Dirac structure as a discrete analogue of the Stokes-Dirac structure and demonstrate
Seslija, Marko; Scherpen, Jacquelien M.A.; van der Schaft, Arjan
2011-01-01
This paper addresses the issue of structure-preserving discretization of open distributed-parameter systems with Hamiltonian dynamics. Employing the formalism of discrete exterior calculus, we introduce simplicial Dirac structures as discrete analogues of the Stokes-Dirac structure and demonstrate
Discrete ternary particle swarm optimization for area optimization of MPRM circuits
Yu Haizhen; Wang Pengjun; Wang Disheng; Zhang Huihong
2013-01-01
Having the advantage of simplicity, robustness and low computational costs, the particle swarm optimization (PSO) algorithm is a powerful evolutionary computation tool for synthesis and optimization of Reed-Muller logic based circuits. Exploring discrete PSO and probabilistic transition rules, the discrete ternary particle swarm optimization (DTPSO) is proposed for mixed polarity Reed-Muller (MPRM) circuits. According to the characteristics of mixed polarity OR/XNOR expression, a tabular technique is improved, and it is applied in the polarity conversion of MPRM functions. DTPSO is introduced to search the best polarity for an area of MPRM circuits by building parameter mapping relationships between particles and polarities. The computational results show that the proposed DTPSO outperforms the reported method using maxterm conversion starting from POS Boolean functions. The average saving in the number of terms is about 11.5%; the algorithm is quite efficient in terms of CPU time and achieves 12.2% improvement on average. (semiconductor integrated circuits)
In-plane Material Filters for the Discrete Material Optimization Method
Sørensen, Rene; Lund, Erik
2015-01-01
, because the projection filter is a non-linear function of the design variables, the projected variables have to be re-scaled in a final so-called normalization filter. This is done to prevent the optimizer in creating superior, but non-physical pseudo-materials. The method is demonstrated on a series......This paper presents in-plane material filters for the Discrete Material Optimization method used for optimizing laminated composite structures. The filters make it possible for engineers to specify a minimum length scale which governs the minimum size of areas with constant material continuity....... Consequently, engineers can target the available production methods, and thereby increase its manufacturability while the optimizer is free to determine which material to apply together with an optimum location, shape, and size of these areas with constant material continuity. By doing so, engineers no longer...
Li, Zejing
2012-01-01
This dissertation is mainly devoted to the research of two problems - the continuous-time portfolio optimization in different Wishart models and the effects of discrete rebalancing on portfolio wealth distribution and optimal portfolio strategy.
On some fundamental properties of structural topology optimization problems
Stolpe, Mathias
2010-01-01
We study some fundamental mathematical properties of discretized structural topology optimization problems. Either compliance is minimized with an upper bound on the volume of the structure, or volume is minimized with an upper bound on the compliance. The design variables are either continuous o....... The presented examples can be used as teaching material in graduate and undergraduate courses on structural topology optimization....
Discrete bat algorithm for optimal problem of permutation flow shop scheduling.
Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang
2014-01-01
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem.
Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling
Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang
2014-01-01
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220
Stochastic Finite Elements in Reliability-Based Structural Optimization
Sørensen, John Dalsgaard; Engelund, S.
1995-01-01
Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...... to optimization variables can be performed. A computer implementation is described and an illustrative example is given....
Fundamental structures of algebra and discrete mathematics
Foldes, Stephan
2011-01-01
Introduces and clarifies the basic theories of 12 structural concepts, offering a fundamental theory of groups, rings and other algebraic structures. Identifies essentials and describes interrelationships between particular theories. Selected classical theorems and results relevant to current research are proved rigorously within the theory of each structure. Throughout the text the reader is frequently prompted to perform integrated exercises of verification and to explore examples.
Fushing Hsieh
2016-11-01
Full Text Available Discrete combinatorial optimization problems in real world are typically defined via an ensemble of potentially high dimensional measurements pertaining to all subjects of a system under study. We point out that such a data ensemble in fact embeds with system's information content that is not directly used in defining the combinatorial optimization problems. Can machine learning algorithms extract such information content and make combinatorial optimizing tasks more efficient? Would such algorithmic computations bring new perspectives into this classic topic of Applied Mathematics and Theoretical Computer Science? We show that answers to both questions are positive. One key reason is due to permutation invariance. That is, the data ensemble of subjects' measurement vectors is permutation invariant when it is represented through a subject-vs-measurement matrix. An unsupervised machine learning algorithm, called Data Mechanics (DM, is applied to find optimal permutations on row and column axes such that the permuted matrix reveals coupled deterministic and stochastic structures as the system's information content. The deterministic structures are shown to facilitate geometry-based divide-and-conquer scheme that helps optimizing task, while stochastic structures are used to generate an ensemble of mimicries retaining the deterministic structures, and then reveal the robustness pertaining to the original version of optimal solution. Two simulated systems, Assignment problem and Traveling Salesman problem, are considered. Beyond demonstrating computational advantages and intrinsic robustness in the two systems, we propose brand new robust optimal solutions. We believe such robust versions of optimal solutions are potentially more realistic and practical in real world settings.
Uher, Vojtěch; Gajdoš, Petr; Radecký, Michal; Snášel, Václav
2016-01-01
The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.
Shen-yan Chen
2015-01-01
Full Text Available This paper presents an Improved Genetic Algorithm with Two-Level Approximation (IGATA to minimize truss weight by simultaneously optimizing size, shape, and topology variables. On the basis of a previously presented truss sizing/topology optimization method based on two-level approximation and genetic algorithm (GA, a new method for adding shape variables is presented, in which the nodal positions are corresponding to a set of coordinate lists. A uniform optimization model including size/shape/topology variables is established. First, a first-level approximate problem is constructed to transform the original implicit problem to an explicit problem. To solve this explicit problem which involves size/shape/topology variables, GA is used to optimize individuals which include discrete topology variables and shape variables. When calculating the fitness value of each member in the current generation, a second-level approximation method is used to optimize the continuous size variables. With the introduction of shape variables, the original optimization algorithm was improved in individual coding strategy as well as GA execution techniques. Meanwhile, the update strategy of the first-level approximation problem was also improved. The results of numerical examples show that the proposed method is effective in dealing with the three kinds of design variables simultaneously, and the required computational cost for structural analysis is quite small.
Discrete and Continuous Optimization Based on Hierarchical Artificial Bee Colony Optimizer
Lianbo Ma
2014-01-01
Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization (HABC, to tackle complex high-dimensional problems. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operator is applied to enhance the global search ability between species. Experiments are conducted on a set of 20 continuous and discrete benchmark problems. The experimental results demonstrate remarkable performance of the HABC algorithm when compared with other six evolutionary algorithms.
N. M. Okasha
2016-04-01
Full Text Available In this paper, an approach for conducting a Reliability-Based Design Optimization (RBDO of truss structures with linked-discrete design variables is proposed. The sections of the truss members are selected from the AISC standard tables and thus the design variables that represent the properties of each section are linked. Latin hypercube sampling is used in the evaluation of the structural reliability. The improved firefly algorithm is used for the optimization solution process. It was found that in order to use the improved firefly algorithm for efficiently solving problems of reliability-based design optimization with linked-discrete design variables; it needs to be modified as proposed in this paper to accelerate its convergence.
Optimization of stochastic discrete systems and control on complex networks computational networks
Lozovanu, Dmitrii
2014-01-01
This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors' new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book's final chapter is devoted to finite horizon stochastic con...
Optimal Design of Composite Structures Under Manufacturing Constraints
Marmaras, Konstantinos
algorithms to perform the global optimization. The efficiency of the proposed models is examined on a set of well–defined discrete multi material and thickness optimization problems originating from the literature. The inclusion of manufacturing limitations along with structural considerations in the early...... mixed integer 0–1 programming problems. The manufacturing constraints have been treated by developing explicit models with favorable properties. In this thesis we have developed and implemented special purpose global optimization methods and heuristic techniques for solving this class of problems......This thesis considers discrete multi material and thickness optimization of laminated composite structures including local failure criteria and manufacturing constraints. Our models closely follow an immediate extension of the Discrete Material Optimization scheme, which allows simultaneous...
Peculiar symmetry structure of some known discrete nonautonomous equations
Garifullin, R N; Habibullin, I T; Yamilov, R I
2015-01-01
We study the generalized symmetry structure of three known discrete nonautonomous equations. One of them is the semidiscrete dressing chain of Shabat. Two others are completely discrete equations defined on the square lattice. The first one is a discrete analogue of the dressing chain introduced by Levi and Yamilov. The second one is a nonautonomous generalization of the potential discrete KdV equation or, in other words, the H1 equation of the well-known Adler−Bobenko−Suris list. We demonstrate that these equations have generalized symmetries in both directions if and only if their coefficients, depending on the discrete variables, are periodic. The order of the simplest generalized symmetry in at least one direction depends on the period and may be arbitrarily high. We substantiate this picture by some theorems in the case of small periods. In case of an arbitrarily large period, we show that it is possible to construct two hierarchies of generalized symmetries and conservation laws. The same picture should take place in case of any nonautonomous equation of the Adler−Bobenko−Suris list. (paper)
Stochastic Finite Elements in Reliability-Based Structural Optimization
Sørensen, John Dalsgaard; Engelund, S.
Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...
Continuous versus discrete structures II -- Discrete Hamiltonian systems and Helmholtz conditions
Cresson, Jacky; Pierret, Frédéric
2015-01-01
We define discrete Hamiltonian systems in the framework of discrete embeddings. An explicit comparison with previous attempts is given. We then solve the discrete Helmholtz's inverse problem for the discrete calculus of variation in the Hamiltonian setting. Several applications are discussed.
Munoz, Eduardo; Stolpe, Mathias; Bendsøe, Martin P.
2009-01-01
in any discrete angle optimization design, or material selection problems. The mathematical modeling of this problem is more general than the one of standard topology optimization. When considering only two material candidates with a considerable difference in stiffness, it corresponds exactly...... to a topology optimization problem. The problem is modeled as a discrete design problem coming from a finite element discretization of the continuum problem. This discretization is made of shell or plate elements. For each element (selection domain), only one of the material candidates must be selected...... of the relaxed master problem and the current best compliance (weight) found get close enough with respect to certain tolerance. The method is investigated by computational means, using the finite element method to solve the analysis problems, and a commercial branch and cut method for solving the relaxed master...
Dynamic Optimization of a Polymer Flooding Process Based on Implicit Discrete Maximum Principle
Yang Lei
2012-01-01
Full Text Available Polymer flooding is one of the most important technologies for enhanced oil recovery (EOR. In this paper, an optimal control model of distributed parameter systems (DPSs for polymer injection strategies is established, which involves the performance index as maximum of the profit, the governing equations as the fluid flow equations of polymer flooding, and some inequality constraints as polymer concentration and injection amount limitation. The optimal control model is discretized by full implicit finite-difference method. To cope with the discrete optimal control problem (OCP, the necessary conditions for optimality are obtained through application of the calculus of variations and Pontryagin’s discrete maximum principle. A modified gradient method with new adjoint construction is proposed for the computation of optimal injection strategies. The numerical results of an example illustrate the effectiveness of the proposed method.
Discrete Discriminant analysis based on tree-structured graphical models
Perez de la Cruz, Gonzalo; Eslava, Guillermina
The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant a...... analysis based on tree{structured graphical models is a simple nonlinear method competitive with, and sometimes superior to, other well{known linear methods like those assuming mutual independence between variables and linear logistic regression.......The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant...
Robust Structured Control Design via LMI Optimization
Adegas, Fabiano Daher; Stoustrup, Jakob
2011-01-01
This paper presents a new procedure for discrete-time robust structured control design. Parameter-dependent nonconvex conditions for stabilizable and induced L2-norm performance controllers are solved by an iterative linear matrix inequalities (LMI) optimization. A wide class of controller...... structures including decentralized of any order, ﬁxed-order dynamic output feedback, static output feedback can be designed robust to polytopic uncertainties. Stability is proven by a parameter-dependent Lyapunov function. Numerical examples on robust stability margins shows that the proposed procedure can...
Structural Optimization with Reliability Constraints
Sørensen, John Dalsgaard; Thoft-Christensen, Palle
1986-01-01
During the last 25 years considerable progress has been made in the fields of structural optimization and structural reliability theory. In classical deterministic structural optimization all variables are assumed to be deterministic. Due to the unpredictability of loads and strengths of actual......]. In this paper we consider only structures which can be modelled as systems of elasto-plastic elements, e.g. frame and truss structures. In section 2 a method to evaluate the reliability of such structural systems is presented. Based on a probabilistic point of view a modern structural optimization problem...... is formulated in section 3. The formulation is a natural extension of the commonly used formulations in determinstic structural optimization. The mathematical form of the optimization problem is briefly discussed. In section 4 two new optimization procedures especially designed for the reliability...
Papagiannis, P.; Azariadis, P.; Papanikos, P.
2017-10-01
Footwear is subject to bending and torsion deformations that affect comfort perception. Following review of Finite Element Analysis studies of sole rigidity and comfort, a three-dimensional, linear multi-material finite element sole model for quasi-static bending and torsion simulation, overcoming boundary and optimisation limitations, is described. Common footwear materials properties and boundary conditions from gait biomechanics are used. The use of normalised strain energy for product benchmarking is demonstrated along with comfort level determination through strain energy density stratification. Sensitivity of strain energy against material thickness is greater for bending than for torsion, with results of both deformations showing positive correlation. Optimization for a targeted performance level and given layer thickness is demonstrated with bending simulations sufficing for overall comfort assessment. An algorithm for comfort optimization w.r.t. bending is presented, based on a discrete approach with thickness values set in line with practical manufacturing accuracy. This work illustrates the potential of the developed finite element analysis applications to offer viable and proven aids to modern footwear sole design assessment and optimization.
Giga-Voxel Structural Optimization
Aage, Niels; Andreassen, Erik; Lazarov, Boyan Stefanov
2017-01-01
The optimal topology of large structural systems has until now been concerned with the design of individual parts and not that of complete assemblies. However, due to recent advances in numerical algorithms tailored for large scale structural optimization this limitation can now be circumvented....... In this work we present several examplesdisplaying how high resolution topology optimization can be used to obtain new, as well as already known, insight within the field of structural optimization. To demonstrate the capabilities of the developed framework we apply it to the design of the supporting structure...... topology optimization provides new insight and possible weight savings forfuture aircraft designs....
Smolensky, Paul; Goldrick, Matthew; Mathis, Donald
2014-08-01
Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The framework we introduce here, Gradient Symbol Processing, characterizes the emergence of grammatical macrostructure from the Parallel Distributed Processing microstructure (McClelland, Rumelhart, & The PDP Research Group, 1986) of language processing. The mental representations that emerge, Distributed Symbol Systems, have both combinatorial and gradient structure. They are processed through Subsymbolic Optimization-Quantization, in which an optimization process favoring representations that satisfy well-formedness constraints operates in parallel with a distributed quantization process favoring discrete symbolic structures. We apply a particular instantiation of this framework, λ-Diffusion Theory, to phonological production. Simulations of the resulting model suggest that Gradient Symbol Processing offers a way to unify accounts of grammatical competence with both discrete and continuous patterns in language performance. Copyright © 2013 Cognitive Science Society, Inc.
Sampled-data and discrete-time H2 optimal control
Trentelman, Harry L.; Stoorvogel, Anton A.
1993-01-01
This paper deals with the sampled-data H2 optimal control problem. Given a linear time-invariant continuous-time system, the problem of minimizing the H2 performance over all sampled-data controllers with a fixed sampling period can be reduced to a pure discrete-time H2 optimal control problem. This
Discrete Geometry Toolkit for Shape Optimization, Phase II
National Aeronautics and Space Administration — Simulation-based design optimization has been steadily maturing over the past two decades, but not without its own unique and persistent challenges. The proposed...
Achtziger, Wolfgang; Stolpe, Mathias
2009-01-01
we use the theory developed in Part I to design a convergent nonlinear branch-and-bound method tailored to solve large-scale instances of the original discrete problem. The problem formulation and the needed theoretical results from Part I are repeated such that this paper is self-contained. We focus...... the largest discrete topology design problems solved by means of global optimization....
On the (non-)optimality of Michell structures
Sigmund, Ole; Aage, Niels; Andreassen, Erik
2016-01-01
Optimal analytical Michell frame structures have been extensively used as benchmark examples in topology optimization, including truss, frame, homogenization, density and level-set based approaches. However, as we will point out, partly the interpretation of Michell’s structural continua...... as discrete frame structures is not accurate and partly, it turns out that limiting structural topology to frame-like structures is a rather severe design restriction and results in structures that are quite far from being stiffness optimal. The paper discusses the interpretation of Michell’s theory...... in the context of numerical topology optimization and compares various topology optimization results obtained with the frame restriction to cases with no design restrictions. For all examples considered, the true stiffness optimal structures are composed of sheets (2D) or closed-walled shell structures (3D...
Park, Nam-Gyu; Kim, Kyoung-Joo; Kim, Kyoung-Hong; Suh, Jung-Min
2013-01-01
Highlights: ► An identification method of the optimal stiffness matrix for a fuel assembly structure is discussed. ► The least squares optimization method is introduced, and a closed form solution of the problem is derived. ► The method can be expanded to the system with the limited number of modes. ► Identification error due to the perturbed mode shape matrix is analyzed. ► Verification examples show that the proposed procedure leads to a reliable solution. -- Abstract: A reactor core structural model which is used to evaluate the structural integrity of the core contains nuclear fuel assembly models. Since the reactor core consists of many nuclear fuel assemblies, the use of a refined fuel assembly model leads to a considerable amount of computing time for performing nonlinear analyses such as the prediction of seismic induced vibration behaviors. The computational time could be reduced by replacing the detailed fuel assembly model with a simplified model that has fewer degrees of freedom, but the dynamic characteristics of the detailed model must be maintained in the simplified model. Such a model based on an optimal design method is proposed in this paper. That is, when a mass matrix and a mode shape matrix are given, the optimal stiffness matrix of a discrete fuel assembly model can be estimated by applying the least squares minimization method. The verification of the method is completed by comparing test results and simulation results. This paper shows that the simplified model's dynamic behaviors are quite similar to experimental results and that the suggested method is suitable for identifying reliable mathematical model for fuel assemblies
Discrete Model for the Structure and Strength of Cementitious Materials
Balopoulos, Victor D.; Archontas, Nikolaos; Pantazopoulou, Stavroula J.
2017-12-01
Cementitious materials are characterized by brittle behavior in direct tension and by transverse dilatation (due to microcracking) under compression. Microcracking causes increasingly larger transverse strains and a phenomenological Poisson's ratio that gradually increases to about ν =0.5 and beyond, at the limit point in compression. This behavior is due to the underlying structure of cementitious pastes which is simulated here with a discrete physical model. The computational model is generic, assembled from a statistically generated, continuous network of flaky dendrites consisting of cement hydrates that emanate from partially hydrated cement grains. In the actual amorphous material, the dendrites constitute the solid phase of the cement gel and interconnect to provide the strength and stiffness against load. The idealized dendrite solid is loaded in compression and tension to compute values for strength and Poisson's effects. Parametric studies are conducted, to calibrate the statistical parameters of the discrete model with the physical and mechanical characteristics of the material, so that the familiar experimental trends may be reproduced. The model provides a framework for the study of the mechanical behavior of the material under various states of stress and strain and can be used to model the effects of additives (e.g., fibers) that may be explicitly simulated in the discrete structure.
Notes on qubit phase space and discrete symplectic structures
Livine, Etera R
2010-01-01
We start from Wootter's construction of discrete phase spaces and Wigner functions for qubits and more generally for finite-dimensional Hilbert spaces. We look at this framework from a non-commutative space perspective and we focus on the Moyal product and the differential calculus on these discrete phase spaces. In particular, the qubit phase space provides the simplest example of a four-point non-commutative phase space. We give an explicit expression of the Moyal bracket as a differential operator. We then compare the quantum dynamics encoded by the Moyal bracket to the classical dynamics: we show that the classical Poisson bracket does not satisfy the Jacobi identity thus leaving the Moyal bracket as the only consistent symplectic structure. We finally generalize our analysis to Hilbert spaces of prime dimensions d and their associated d x d phase spaces.
Optimal Investment in Structured Bonds
Jessen, Pernille; Jørgensen, Peter Løchte
The paper examines the role of structured bonds in the optimal portfolio of a small retail investor. We consider the typical structured bond essentially repacking an exotic option and a zero coupon bond, i.e. an investment with portfolio insurance. The optimal portfolio is found when the investment...
Continuous and Discrete-Time Optimal Controls for an Isolated Signalized Intersection
Jiyuan Tan
2017-01-01
Full Text Available A classical control problem for an isolated oversaturated intersection is revisited with a focus on the optimal control policy to minimize total delay. The difference and connection between existing continuous-time planning models and recently proposed discrete-time planning models are studied. A gradient descent algorithm is proposed to convert the optimal control plan of the continuous-time model to the plan of the discrete-time model in many cases. Analytic proof and numerical tests for the algorithm are also presented. The findings shed light on the links between two kinds of models.
Bitencourt, Ana Carla P; Prudente, Frederico V; Vianna, Jose David M
2007-01-01
We propose a new numerically optimized discrete variable representation using eigenstates of diabatic Hamiltonians. This procedure provides an efficient method to solve non-adiabatic coupling problems since the generated basis sets take into account information on the diabatic potentials. The method is applied to the B 1 Σ + - D' 1 Σ + Rydberg-valence predissociation interaction in the CO molecule. Here we give an account of the discrete variable representation and present the procedure for the calculation of its optimized version, which we apply to obtain the total photodissociation cross sections of the CO molecule
A Novel adaptative Discrete Cuckoo Search Algorithm for parameter optimization in computer vision
loubna benchikhi
2017-10-01
Full Text Available Computer vision applications require choosing operators and their parameters, in order to provide the best outcomes. Often, the users quarry on expert knowledge and must experiment many combinations to find manually the best one. As performance, time and accuracy are important, it is necessary to automate parameter optimization at least for crucial operators. In this paper, a novel approach based on an adaptive discrete cuckoo search algorithm (ADCS is proposed. It automates the process of algorithms’ setting and provides optimal parameters for vision applications. This work reconsiders a discretization problem to adapt the cuckoo search algorithm and presents the procedure of parameter optimization. Some experiments on real examples and comparisons to other metaheuristic-based approaches: particle swarm optimization (PSO, reinforcement learning (RL and ant colony optimization (ACO show the efficiency of this novel method.
Guaranteed Discrete Energy Optimization on Large Protein Design Problems.
Simoncini, David; Allouche, David; de Givry, Simon; Delmas, Céline; Barbe, Sophie; Schiex, Thomas
2015-12-08
In Computational Protein Design (CPD), assuming a rigid backbone and amino-acid rotamer library, the problem of finding a sequence with an optimal conformation is NP-hard. In this paper, using Dunbrack's rotamer library and Talaris2014 decomposable energy function, we use an exact deterministic method combining branch and bound, arc consistency, and tree-decomposition to provenly identify the global minimum energy sequence-conformation on full-redesign problems, defining search spaces of size up to 10(234). This is achieved on a single core of a standard computing server, requiring a maximum of 66GB RAM. A variant of the algorithm is able to exhaustively enumerate all sequence-conformations within an energy threshold of the optimum. These proven optimal solutions are then used to evaluate the frequencies and amplitudes, in energy and sequence, at which an existing CPD-dedicated simulated annealing implementation may miss the optimum on these full redesign problems. The probability of finding an optimum drops close to 0 very quickly. In the worst case, despite 1,000 repeats, the annealing algorithm remained more than 1 Rosetta unit away from the optimum, leading to design sequences that could differ from the optimal sequence by more than 30% of their amino acids.
Berthe, P.M.
2013-01-01
In the context of nuclear waste repositories, we consider the numerical discretization of the non stationary convection diffusion equation. Discontinuous physical parameters and heterogeneous space and time scales lead us to use different space and time discretizations in different parts of the domain. In this work, we choose the discrete duality finite volume (DDFV) scheme and the discontinuous Galerkin scheme in time, coupled by an optimized Schwarz waveform relaxation (OSWR) domain decomposition method, because this allows the use of non-conforming space-time meshes. The main difficulty lies in finding an upwind discretization of the convective flux which remains local to a sub-domain and such that the multi domain scheme is equivalent to the mono domain one. These difficulties are first dealt with in the one-dimensional context, where different discretizations are studied. The chosen scheme introduces a hybrid unknown on the cell interfaces. The idea of up winding with respect to this hybrid unknown is extended to the DDFV scheme in the two-dimensional setting. The well-posedness of the scheme and of an equivalent multi domain scheme is shown. The latter is solved by an OSWR algorithm, the convergence of which is proved. The optimized parameters in the Robin transmission conditions are obtained by studying the continuous or discrete convergence rates. Several test-cases, one of which inspired by nuclear waste repositories, illustrate these results. (author) [fr
A discrete optimization method for nuclear fuel management
Argaud, J.P.
1993-04-01
Nuclear loading pattern elaboration can be seen as a combinational optimization problem of tremendous size and with non-linear cost-functions, and search are always numerically expensive. After a brief introduction of the main aspects of nuclear fuel management, this paper presents a new idea to treat the combinational problem by using informations included in the gradient of a cost function. The method is to choose, by direct observation of the gradient, the more interesting changes in fuel loading patterns. An example is then developed to illustrate an operating mode of the method, and finally, connections with simulated annealing and genetic algorithms are described as an attempt to improve search processes
Implementing size-optimal discrete neural networks require analog circuitry
Beiu, V.
1998-12-01
This paper starts by overviewing results dealing with the approximation capabilities of neural networks, as well as bounds on the size of threshold gate circuits. Based on a constructive solution for Kolmogorov`s superpositions the authors show that implementing Boolean functions can be done using neurons having an identity transfer function. Because in this case the size of the network is minimized, it follows that size-optimal solutions for implementing Boolean functions can be obtained using analog circuitry. Conclusions and several comments on the required precision are ending the paper.
Truss optimization with discrete design variables: a critical review
Stolpe, Mathias
2016-01-01
problems. This, and other, observations lead to a set of recommended research tasks and objectives to bring the field forward. The development of a publicly available benchmark library is urgently needed to support development and assessment of existing and new heuristics and methods. Combined...... methods and meta heuristics. The field has experienced a shift in focus from deterministic methods to meta heuristics, i.e. stochastic search methods. Based on the reported numerical results it is however not possible to conclude that this shift has improved the competences to solve application relevant...... with this effort, it is recommended that the field begins to use modern methods such as performance profiles for fair and accurate comparison of optimization methods. Finally, theoretical results are rare in this field. This means that most recent methods and heuristics are not supported by mathematical theory...
A discrete optimization method for nuclear fuel management
Argaud, J.P.
1993-04-01
Nuclear loading pattern elaboration can be seen as a combinational optimization problem, of tremendous size and with non-linear cost-functions, and search are always numerically expensive. After a brief introduction of the main aspects of nuclear fuel management, this note presents a new idea to treat the combinational problem by using informations included in the gradient of a cost function. The method is to choose, by direct observation of the gradient, the more interesting changes in fuel loading patterns. An example is then developed to illustrate an operating mode of the method, and finally, connections with simulated annealing and genetic algorithms are described as an attempt to improve search processes. (author). 1 fig., 16 refs
Ising Processing Units: Potential and Challenges for Discrete Optimization
Coffrin, Carleton James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nagarajan, Harsha [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bent, Russell Whitford [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-07-05
The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, presents new opportunities for hybrid-optimization algorithms that leverage these kinds of specialized hardware. In this work, we propose the idea of an Ising processing unit as a computational abstraction for these emerging tools. Challenges involved in using and bench- marking these devices are presented, and open-source software tools are proposed to address some of these challenges. The proposed benchmarking tools and methodology are demonstrated by conducting a baseline study of established solution methods to a D-Wave 2X adiabatic quantum computer, one example of a commercially available Ising processing unit.
Optimally segmented magnetic structures
Insinga, Andrea Roberto; Bahl, Christian; Bjørk, Rasmus
We present a semi-analytical algorithm for magnet design problems, which calculates the optimal way to subdivide a given design region into uniformly magnetized segments.The availability of powerful rare-earth magnetic materials such as Nd-Fe-B has broadened the range of applications of permanent...... is not available.We will illustrate the results for magnet design problems from different areas, such as electric motors/generators (as the example in the picture), beam focusing for particle accelerators and magnetic refrigeration devices.......We present a semi-analytical algorithm for magnet design problems, which calculates the optimal way to subdivide a given design region into uniformly magnetized segments.The availability of powerful rare-earth magnetic materials such as Nd-Fe-B has broadened the range of applications of permanent...... magnets[1][2]. However, the powerful rare-earth magnets are generally expensive, so both the scientific and industrial communities have devoted a lot of effort into developing suitable design methods. Even so, many magnet optimization algorithms either are based on heuristic approaches[3...
Optimization of Laminated Composite Structures
Henrichsen, Søren Randrup
of the contributions of the PhD project are included in the second part of the thesis. Paper A presents a framework for free material optimization where commercially available finite element analysis software is used as analysis tool. Robust buckling optimization of laminated composite structures by including...... allows for a higher degree of tailoring of the resulting material. To enable better utilization of the composite materials, optimum design procedures can be used to assist the engineer. This PhD thesis is focused on developing numerical methods for optimization of laminated composite structures...... nonlinear analysis of structures, buckling and post-buckling analysis of structures, and formulations for optimization of structures considering stiffness, buckling, and post-buckling criteria. Lastly, descriptions, main findings, and conclusions of the papers are presented. The papers forming the basis...
Wu, Yue; Li, Q.; Hu, Qingjie; Borgart, A.
2017-01-01
Firefly Algorithm (FA, for short) is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly,
BEST-4, Fuel Cycle and Cost Optimization for Discrete Power Levels
1973-01-01
1 - Nature of physical problem solved: Determination of optimal power strategy for a fuel cycle, for discrete power levels and n temporal stages, taking into account replacement energy costs and de-rating. 2 - Method of solution: Dynamic programming. 3 - Restrictions on the complexity of the problem: Restrictions may arise from number of power levels and temporal stages, due to machine limitations
Ponslet, E.R.; Eldred, M.S. [Sandia National Labs., Albuquerque, NM (United States). Structural Dynamics Dept.
1996-05-17
An analytical and experimental study is conducted to investigate the effect of isolator locations on the effectiveness of vibration isolation systems. The study uses isolators with fixed properties and evaluates potential improvements to the isolation system that can be achieved by optimizing isolator locations. Because the available locations for the isolators are discrete in this application, a Genetic Algorithm (GA) is used as the optimization method. The system is modeled in MATLAB{trademark} and coupled with the GA available in the DAKOTA optimization toolkit under development at Sandia National Laboratories. Design constraints dictated by hardware and experimental limitations are implemented through penalty function techniques. A series of GA runs reveal difficulties in the search on this heavily constrained, multimodal, discrete problem. However, the GA runs provide a variety of optimized designs with predicted performance from 30 to 70 times better than a baseline configuration. An alternate approach is also tested on this problem: it uses continuous optimization, followed by rounding of the solution to neighboring discrete configurations. Results show that this approach leads to either infeasible or poor designs. Finally, a number of optimized designs obtained from the GA searches are tested in the laboratory and compared to the baseline design. These experimental results show a 7 to 46 times improvement in vibration isolation from the baseline configuration.
Optimal Priority Structure, Capital Structure, and Investment
Dirk Hackbarth; David C. Mauer
2012-01-01
We study the interaction between financing and investment decisions in a dynamic model, where the firm has multiple debt issues and equityholders choose the timing of investment. Jointly optimal capital and priority structures can virtually eliminate investment distortions because debt priority serves as a dynamically optimal contract. Examining the relative efficiency of priority rules observed in practice, we develop several predictions about how firms adjust their priority structure in res...
Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming
2016-07-14
Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.
Design of an optimal preview controller for linear discrete-time descriptor systems with state delay
Cao, Mengjuan; Liao, Fucheng
2015-04-01
In this paper, the linear discrete-time descriptor system with state delay is studied, and a design method for an optimal preview controller is proposed. First, by using the discrete lifting technique, the original system is transformed into a general descriptor system without state delay in form. Then, taking advantage of the first-order forward difference operator, we construct a descriptor augmented error system, including the state vectors of the lifted system, error vectors, and desired target signals. Rigorous mathematical proofs are given for the regularity, stabilisability, causal controllability, and causal observability of the descriptor augmented error system. Based on these, the optimal preview controller with preview feedforward compensation for the original system is obtained by using the standard optimal regulator theory of the descriptor system. The effectiveness of the proposed method is shown by numerical simulation.
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.
Optimization methods in structural design
Rothwell, Alan
2017-01-01
This book offers an introduction to numerical optimization methods in structural design. Employing a readily accessible and compact format, the book presents an overview of optimization methods, and equips readers to properly set up optimization problems and interpret the results. A ‘how-to-do-it’ approach is followed throughout, with less emphasis at this stage on mathematical derivations. The book features spreadsheet programs provided in Microsoft Excel, which allow readers to experience optimization ‘hands-on.’ Examples covered include truss structures, columns, beams, reinforced shell structures, stiffened panels and composite laminates. For the last three, a review of relevant analysis methods is included. Exercises, with solutions where appropriate, are also included with each chapter. The book offers a valuable resource for engineering students at the upper undergraduate and postgraduate level, as well as others in the industry and elsewhere who are new to these highly practical techniques.Whi...
Optimal control of LQR for discrete time-varying systems with input delays
Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng
2018-04-01
In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.
The choice of optimal Discrete Interaction Approximation to the kinetic integral for ocean waves
V. G. Polnikov
2003-01-01
Full Text Available A lot of discrete configurations for the four-wave nonlinear interaction processes have been calculated and tested by the method proposed earlier in the frame of the concept of Fast Discrete Interaction Approximation to the Hasselmann's kinetic integral (Polnikov and Farina, 2002. It was found that there are several simple configurations, which are more efficient than the one proposed originally in Hasselmann et al. (1985. Finally, the optimal multiple Discrete Interaction Approximation (DIA to the kinetic integral for deep-water waves was found. Wave spectrum features have been intercompared for a number of different configurations of DIA, applied to a long-time solution of kinetic equation. On the basis of this intercomparison the better efficiency of the configurations proposed was confirmed. Certain recommendations were given for implementation of new approximations to the wave forecast practice.
Multi-Material Design Optimization of Composite Structures
Hvejsel, Christian Frier
properties. The modeling encompasses discrete orientationing of orthotropic materials, selection between different distinct materials as well as removal of material representing holes in the structure within a unified parametrization. The direct generalization of two-phase topology optimization to any number...... of a relaxation-based search heuristic that accelerates a Generalized Benders' Decomposition technique for global optimization and enables the solution of medium-scale problems to global optimality. Improvements in the ability to solve larger problems to global optimality are found and potentially further...... improvements may be obtained with this technique in combination with cheaper heuristics....
Mengjuan Cao
2014-01-01
Full Text Available The linear discrete-time descriptor noncausal multirate system is considered for the presentation of a new design approach for optimal preview control. First, according to the characteristics of causal controllability and causal observability, the descriptor noncausal system is constructed into a descriptor causal closed-loop system. Second, by using the characteristics of the causal system and elementary transformation, the descriptor causal closed-loop system is transformed into a normal system. Then, taking advantage of the discrete lifting technique, the normal multirate system is converted to a single-rate system. By making use of the standard preview control method, we construct the descriptor augmented error system. The quadratic performance index for the multirate system is given, which can be changed into one for the single-rate system. In addition, a new single-rate system is obtained, the optimal control law of which is given. Returning to the original system, the optimal preview controller for linear discrete-time descriptor noncausal multirate systems is derived. The stabilizability and detectability of the lifted single-rate system are discussed in detail. The optimal preview control design techniques are illustrated by simulation results for a simple example.
Yu Fajun
2008-01-01
In [W.X. Ma, J. Phys. A: Math. Theor. 40 (2007) 15055], Prof. Ma gave a beautiful result (a discrete variational identity). In this Letter, based on a discrete block matrix spectral problem, a new hierarchy of Lax integrable lattice equations with four potentials is derived. By using of the discrete variational identity, we obtain Hamiltonian structure of the discrete soliton equation hierarchy. Finally, an integrable coupling system of the soliton equation hierarchy and its Hamiltonian structure are obtained through the discrete variational identity
Yu Fajun [College of Maths and Systematic Science, Shenyang Normal University, Shenyang 110034 (China)], E-mail: yufajun888@163.com
2008-06-09
In [W.X. Ma, J. Phys. A: Math. Theor. 40 (2007) 15055], Prof. Ma gave a beautiful result (a discrete variational identity). In this Letter, based on a discrete block matrix spectral problem, a new hierarchy of Lax integrable lattice equations with four potentials is derived. By using of the discrete variational identity, we obtain Hamiltonian structure of the discrete soliton equation hierarchy. Finally, an integrable coupling system of the soliton equation hierarchy and its Hamiltonian structure are obtained through the discrete variational identity.
Topology optimization for coated structures
Clausen, Anders; Andreassen, Erik; Sigmund, Ole
2015-01-01
This paper presents new results within the design of three-dimensional (3D) coated structures using topology optimization.The work is an extension of a recently published two-dimensional (2D) method for including coatedstructures into the minimum compliance topology optimization problem. The high...... level of control over key parameters demonstrated for the 2D model can likewise be achieved in 3D. The effectiveness of the approach isdemonstrated with numerical examples, which for the 3D problems have been solved using a parallel topology optimization implementation based on the PETSc toolkit....
Spinors in euclidean field theory, complex structures and discrete symmetries
Wetterich, C.
2011-01-01
We discuss fermions for arbitrary dimensions and signature of the metric, with special emphasis on euclidean space. Generalized Majorana spinors are defined for d=2,3,4,8,9mod8, independently of the signature. These objects permit a consistent analytic continuation of Majorana spinors in Minkowski space to euclidean signature. Compatibility of charge conjugation with complex conjugation requires for euclidean signature a new complex structure which involves a reflection in euclidean time. The possible complex structures for Minkowski and euclidean signature can be understood in terms of a modulo two periodicity in the signature. The concepts of a real action and hermitean observables depend on the choice of the complex structure. For a real action the expectation values of all hermitean multi-fermion observables are real. This holds for arbitrary signature, including euclidean space. In particular, a chemical potential is compatible with a real action for the euclidean theory. We also discuss the discrete symmetries of parity, time reversal and charge conjugation for arbitrary dimension and signature.
Optimization and anti-optimization of structures under uncertainty
Elishakoff, Isaac; Ohsaki, Makoto
2010-01-01
The volume presents a collaboration between internationally recognized experts on anti-optimization and structural optimization, and summarizes various novel ideas, methodologies and results studied over 20 years...
A Framework for the Optimization of Discrete-Event Simulation Models
Joshi, B. D.; Unal, R.; White, N. H.; Morris, W. D.
1996-01-01
With the growing use of computer modeling and simulation, in all aspects of engineering, the scope of traditional optimization has to be extended to include simulation models. Some unique aspects have to be addressed while optimizing via stochastic simulation models. The optimization procedure has to explicitly account for the randomness inherent in the stochastic measures predicted by the model. This paper outlines a general purpose framework for optimization of terminating discrete-event simulation models. The methodology combines a chance constraint approach for problem formulation, together with standard statistical estimation and analyses techniques. The applicability of the optimization framework is illustrated by minimizing the operation and support resources of a launch vehicle, through a simulation model.
The continuous 1.5D terrain guarding problem: Discretization, optimal solutions, and PTAS
Stephan Friedrichs
2016-05-01
Full Text Available In the NP-hard continuous 1.5D Terrain Guarding Problem (TGP we are given an $x$-monotone chain of line segments in $R^2$ (the terrain $T$, and ask for the minimum number of guards (located anywhere on $T$ required to guard all of $T$. We construct guard candidate and witness sets $G, W \\subset T$ of polynomial size such that any feasible (optimal guard cover $G^* \\subseteq G$ for $W$ is also feasible (optimal for the continuous TGP. This discretization allows us to: (1 settle NP-completeness for the continuous TGP; (2 provide a Polynomial Time Approximation Scheme (PTAS for the continuous TGP using the PTAS for the discrete TGP by Gibson et al.; (3 formulate the continuous TGP as an Integer Linear Program (IP. Furthermore, we propose several filtering techniques reducing the size of our discretization, allowing us to devise an efficient IP-based algorithm that reliably provides optimal guard placements for terrains with up to $10^6$ vertices within minutes on a standard desktop computer.
Road maintenance optimization through a discrete-time semi-Markov decision process
Zhang Xueqing; Gao Hui
2012-01-01
Optimization models are necessary for efficient and cost-effective maintenance of a road network. In this regard, road deterioration is commonly modeled as a discrete-time Markov process such that an optimal maintenance policy can be obtained based on the Markov decision process, or as a renewal process such that an optimal maintenance policy can be obtained based on the renewal theory. However, the discrete-time Markov process cannot capture the real time at which the state transits while the renewal process considers only one state and one maintenance action. In this paper, road deterioration is modeled as a semi-Markov process in which the state transition has the Markov property and the holding time in each state is assumed to follow a discrete Weibull distribution. Based on this semi-Markov process, linear programming models are formulated for both infinite and finite planning horizons in order to derive optimal maintenance policies to minimize the life-cycle cost of a road network. A hypothetical road network is used to illustrate the application of the proposed optimization models. The results indicate that these linear programming models are practical for the maintenance of a road network having a large number of road segments and that they are convenient to incorporate various constraints on the decision process, for example, performance requirements and available budgets. Although the optimal maintenance policies obtained for the road network are randomized stationary policies, the extent of this randomness in decision making is limited. The maintenance actions are deterministic for most states and the randomness in selecting actions occurs only for a few states.
Jung, B. K.; Cho, J. R.; Jeong, W. B.
2015-01-01
The position of vibration sensors influences the modal identification quality of flexible structures for a given number of sensors, and the quality of modal identification is usually estimated in terms of correlation between the natural modes using the modal assurance criterion (MAC). The sensor placement optimization is characterized by the fact that the design variables are not continuous but discrete, implying that the conventional sensitivity-driven optimization methods are not applicable. In this context, this paper presents the application of genetic algorithm to the sensor placement optimization for improving the modal identification quality of flexible structures. A discrete-type optimization problem using genetic algorithm is formulated by defining the sensor positions and the MAC as the design variables and the objective function, respectively. The proposed GA-based evolutionary optimization method is validated through the numerical experiment with a rectangular plate, and its excellence is verified from the comparison with the cases using different modal correlation measures.
Reza Sirjani
2017-09-01
Full Text Available Currently, many wind farms exist throughout the world and, in some cases, supply a significant portion of energy to networks. However, numerous uncertainties remain with respect to the amount of energy generated by wind turbines and other sophisticated operational aspects, such as voltage and reactive power management, which requires further development and consideration. To fix the problem of poor reactive power compensation in wind farms, optimal capacitor placement has been proposed in existing wind farms as a simple and relatively inexpensive method. However, the use of induction generators, transformers, and additional capacitors represent potential problems for the harmonics of a system and therefore must be taken into account at wind farms. The optimal location and size of capacitors at buses of an 80-MW wind farm were determined according to modelled wind speed, system equivalent circuits, and harmonics in order to minimize energy losses, optimize reactive power and reduce the management costs. The discrete version of the lightning search algorithm (DLSA is a powerful and flexible nature-inspired optimization technique that was developed and implemented herein for optimal capacitor placement in wind farms. The obtained results are compared with the results of the genetic algorithm (GA and the discrete harmony search algorithm (DHSA.
The Structural Optimization System CAOS
Rasmussen, John
1990-01-01
CAOS is a system for structural shape optimization. It is closely integrated in a Computer Aided Design environment and controlled entirely from the CAD-system AutoCAD. The mathematical foundation of the system is briefly presented and a description of the CAD-integration strategy is given together...
Poursalehi, N.; Zolfaghari, A.; Minuchehr, A.
2015-01-01
Highlights: • An advanced version of firefly algorithm, EDFA, is proposed for the core pattern optimization problem. • The movement of each firefly toward the best firefly with a dynamic probability is the major improvement of EDFA. • LPO results represent the faster convergence and better performance of EDFA in comparison to CFA and DFA. - Abstract: Inspired by fireflies behavior in nature, a firefly algorithm has been developed for solving optimization problems. In this approach, each firefly movement is based on absorption of the other one. For enhancing the performance of firefly algorithm in the optimization process of nuclear reactor loading pattern optimization (LPO), we introduce a new variant of firefly algorithm, i.e. Effective Discrete Firefly Algorithm (EDFA). In EDFA, a new behavior is the movement of fireflies to current global best position with a dynamic probability, i.e. the movement of each firefly can be determined to be toward the brighter or brightest firefly’s position in any iteration of the algorithm. In this paper, our optimization objectives for the LPO are the maximization of K eff along with the minimization of the power peaking factor (PPF). In order to represent the increase of convergence speed of EDFA, basic firefly algorithms including the continuous firefly algorithm (CFA) and the discrete firefly algorithm (DFA) also have been implemented. Loading pattern optimization results of two well-known problems confirm better performance of EDFA in obtaining nearly optimized fuel arrangements in comparison to CFA and DFA. All in all, we can suggest applying the EDFA to other optimization problems of nuclear engineering field in order to investigate its performance in gaining considered objectives
Ram Verma
2016-02-01
Full Text Available This paper deals with mainly establishing numerous sets of generalized second order paramertic sufficient optimality conditions for a semiinfinite discrete minmax fractional programming problem, while the results on semiinfinite discrete minmax fractional programming problem achieved based on some partitioning schemes under various types of generalized second order univexity assumptions.
Protein Structure Refinement by Optimization
Carlsen, Martin
on whether the three-dimensional structure of a homologous sequence is known. Whether or not a protein model can be used for industrial purposes depends on the quality of the predicted structure. A model can be used to design a drug when the quality is high. The overall goal of this project is to assess...... that correlates maximally to a native-decoy distance. The main contribution of this thesis is methods developed for analyzing the performance of metrically trained knowledge-based potentials and for optimizing their performance while making them less dependent on the decoy set used to define them. We focus...... being at-least a local minimum of the potential. To address how far the current functional form of the potential is from an ideal potential we present two methods for finding the optimal metrically trained potential that simultaneous has a number of native structures as a local minimum. Our results...
Henryk Josiński
2014-01-01
Full Text Available This paper introduces an expanded version of the Invasive Weed Optimization algorithm (exIWO distinguished by the hybrid strategy of the search space exploration proposed by the authors. The algorithm is evaluated by solving three well-known optimization problems: minimization of numerical functions, feature selection, and the Mona Lisa TSP Challenge as one of the instances of the traveling salesman problem. The achieved results are compared with analogous outcomes produced by other optimization methods reported in the literature.
Discrete variational methods and their application to electronic structures
Ellis, D.E.
1987-01-01
Some general concepts concerning Discrete Variational methods are developed and applied to problems of determination of eletronic spectra, charge densities and bonding of free molecules, surface-chemisorbed species and bulk solids. (M.W.O.) [pt
Evaluation of a proposed optimization method for discrete-event simulation models
Alexandre Ferreira de Pinho
2012-12-01
Full Text Available Optimization methods combined with computer-based simulation have been utilized in a wide range of manufacturing applications. However, in terms of current technology, these methods exhibit low performance levels which are only able to manipulate a single decision variable at a time. Thus, the objective of this article is to evaluate a proposed optimization method for discrete-event simulation models based on genetic algorithms which exhibits more efficiency in relation to computational time when compared to software packages on the market. It should be emphasized that the variable's response quality will not be altered; that is, the proposed method will maintain the solutions' effectiveness. Thus, the study draws a comparison between the proposed method and that of a simulation instrument already available on the market and has been examined in academic literature. Conclusions are presented, confirming the proposed optimization method's efficiency.
Optimization of structures and components
Muñoz-Rojas, Pablo Andrés
2013-01-01
Written by an international group of active researchers in the field, this volume presents innovative formulations and applied procedures for sensitivity analysis and structural design optimization. Eight chapters discuss subjects ranging from recent developments in the determination and application of topological gradients, to the use of evolutionary algorithms and meta-models to solve practical engineering problems. With such a comprehensive set of contributions, the book is a valuable source of information for graduate students and researchers entering or working in the matter.
Stochastic search in structural optimization - Genetic algorithms and simulated annealing
Hajela, Prabhat
1993-01-01
An account is given of illustrative applications of genetic algorithms and simulated annealing methods in structural optimization. The advantages of such stochastic search methods over traditional mathematical programming strategies are emphasized; it is noted that these methods offer a significantly higher probability of locating the global optimum in a multimodal design space. Both genetic-search and simulated annealing can be effectively used in problems with a mix of continuous, discrete, and integer design variables.
Global optimization of truss topology with discrete bar areas—Part I: Theory of relaxed problems
Achtziger, Wolfgang; Stolpe, Mathias
2008-01-01
the case of discrete areas. This problem is of major practical relevance if the truss must be built from pre-produced bars with given areas. As a special case, we consider the design problem for a single bar area, i.e., a 0/1-problem. In contrast to heuristic methods considered in other approaches, Part I....... The main issue of the paper and of the approach lies in the fact that the relaxed nonlinear optimization problem can be formulated as a quadratic program (QP). Here the paper generalizes and extends the available theory from the literature. Although the Hessian of this QP is indefinite, it is possible...
Retrieving quasi-phase-matching structure with discrete layer-peeling method
Zhang, Q. W.; Zeng, Xianglong; Wang, M.
2012-01-01
An approach to reconstruct a quasi-phase-matching grating by using a discrete layer-peeling algorithm is presented. Experimentally measured output spectra of Solc-type filters, based on uniform and chirped QPM structures, are used in the discrete layer-peeling algorithm. The reconstructed QPM...
Delay-area trade-off for MPRM circuits based on hybrid discrete particle swarm optimization
Jiang Zhidi; Wang Zhenhai; Wang Pengjun
2013-01-01
Polarity optimization for mixed polarity Reed—Muller (MPRM) circuits is a combinatorial issue. Based on the study on discrete particle swarm optimization (DPSO) and mixed polarity, the corresponding relation between particle and mixed polarity is established, and the delay-area trade-off of large-scale MPRM circuits is proposed. Firstly, mutation operation and elitist strategy in genetic algorithm are incorporated into DPSO to further develop a hybrid DPSO (HDPSO). Then the best polarity for delay and area trade-off is searched for large-scale MPRM circuits by combining the HDPSO and a delay estimation model. Finally, the proposed algorithm is testified by MCNC Benchmarks. Experimental results show that HDPSO achieves a better convergence than DPSO in terms of search capability for large-scale MPRM circuits. (semiconductor integrated circuits)
LQR-Based Optimal Distributed Cooperative Design for Linear Discrete-Time Multiagent Systems.
Zhang, Huaguang; Feng, Tao; Liang, Hongjing; Luo, Yanhong
2017-03-01
In this paper, a novel linear quadratic regulator (LQR)-based optimal distributed cooperative design method is developed for synchronization control of general linear discrete-time multiagent systems on a fixed, directed graph. Sufficient conditions are derived for synchronization, which restrict the graph eigenvalues into a bounded circular region in the complex plane. The synchronizing speed issue is also considered, and it turns out that the synchronizing region reduces as the synchronizing speed becomes faster. To obtain more desirable synchronizing capacity, the weighting matrices are selected by sufficiently utilizing the guaranteed gain margin of the optimal regulators. Based on the developed LQR-based cooperative design framework, an approximate dynamic programming technique is successfully introduced to overcome the (partially or completely) model-free cooperative design for linear multiagent systems. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design methods.
Yu, Chaoyin; Yuan, Zhengwu; Wu, Yuanfeng
2017-10-01
Hyperspectral image unmixing is an important part of hyperspectral data analysis. The mixed pixel decomposition consists of two steps, endmember (the unique signatures of pure ground components) extraction and abundance (the proportion of each endmember in each pixel) estimation. Recently, a Discrete Particle Swarm Optimization algorithm (DPSO) was proposed for accurately extract endmembers with high optimal performance. However, the DPSO algorithm shows very high computational complexity, which makes the endmember extraction procedure very time consuming for hyperspectral image unmixing. Thus, in this paper, the DPSO endmember extraction algorithm was parallelized, implemented on the CUDA (GPU K20) platform, and evaluated by real hyperspectral remote sensing data. The experimental results show that with increasing the number of particles the parallelized version obtained much higher computing efficiency while maintain the same endmember exaction accuracy.
Xiaofeng Lv
2018-01-01
Full Text Available Sensor data-based test selection optimization is the basis for designing a test work, which ensures that the system is tested under the constraint of the conventional indexes such as fault detection rate (FDR and fault isolation rate (FIR. From the perspective of equipment maintenance support, the ambiguity isolation has a significant effect on the result of test selection. In this paper, an improved test selection optimization model is proposed by considering the ambiguity degree of fault isolation. In the new model, the fault test dependency matrix is adopted to model the correlation between the system fault and the test group. The objective function of the proposed model is minimizing the test cost with the constraint of FDR and FIR. The improved chaotic discrete particle swarm optimization (PSO algorithm is adopted to solve the improved test selection optimization model. The new test selection optimization model is more consistent with real complicated engineering systems. The experimental result verifies the effectiveness of the proposed method.
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
Reliability-Based Optimization in Structural Engineering
Enevoldsen, I.; Sørensen, John Dalsgaard
1994-01-01
In this paper reliability-based optimization problems in structural engineering are formulated on the basis of the classical decision theory. Several formulations are presented: Reliability-based optimal design of structural systems with component or systems reliability constraints, reliability...
Stolpe, Mathias; Bendsøe, Martin P.
2007-01-01
This paper present some initial results pertaining to a search for globally optimal solutions to a challenging benchmark example proposed by Zhou and Rozvany. This means that we are dealing with global optimization of the classical single load minimum compliance topology design problem with a fixed...... finite element discretization and with discrete design variables. Global optimality is achieved by the implementation of some specially constructed convergent nonlinear branch and cut methods, based on the use of natural relaxations and by applying strengthening constraints (linear valid inequalities...
Stolpe, Mathias; Bendsøe, Martin P.
2007-01-01
This paper present some initial results pertaining to a search for globally optimal solutions to a challenging benchmark example proposed by Zhou and Rozvany. This means that we are dealing with global optimization of the classical single load minimum compliance topology design problem with a fixed...... finite element discretization and with discrete design variables. Global optimality is achieved by the implementation of some specially constructed convergent nonlinear branch and cut methods, based on the use of natural relaxations and by applying strengthening constraints (linear valid inequalities......) and cuts....
Hong-Zhong Huang
2012-02-01
Full Text Available Various uncertainties are inevitable in complex engineered systems and must be carefully treated in design activities. Reliability-Based Multidisciplinary Design Optimization (RBMDO has been receiving increasing attention in the past decades to facilitate designing fully coupled systems but also achieving a desired reliability considering uncertainty. In this paper, a new formulation of multidisciplinary design optimization, namely RFCDV (random/fuzzy/continuous/discrete variables Multidisciplinary Design Optimization (RFCDV-MDO, is developed within the framework of Sequential Optimization and Reliability Assessment (SORA to deal with multidisciplinary design problems in which both aleatory and epistemic uncertainties are present. In addition, a hybrid discrete-continuous algorithm is put forth to efficiently solve problems where both discrete and continuous design variables exist. The effectiveness and computational efficiency of the proposed method are demonstrated via a mathematical problem and a pressure vessel design problem.
Zhang, Qing; Beard, Daniel A; Schlick, Tamar
2003-12-01
Salt-mediated electrostatics interactions play an essential role in biomolecular structures and dynamics. Because macromolecular systems modeled at atomic resolution contain thousands of solute atoms, the electrostatic computations constitute an expensive part of the force and energy calculations. Implicit solvent models are one way to simplify the model and associated calculations, but they are generally used in combination with standard atomic models for the solute. To approximate electrostatics interactions in models on the polymer level (e.g., supercoiled DNA) that are simulated over long times (e.g., milliseconds) using Brownian dynamics, Beard and Schlick have developed the DiSCO (Discrete Surface Charge Optimization) algorithm. DiSCO represents a macromolecular complex by a few hundred discrete charges on a surface enclosing the system modeled by the Debye-Hückel (screened Coulombic) approximation to the Poisson-Boltzmann equation, and treats the salt solution as continuum solvation. DiSCO can represent the nucleosome core particle (>12,000 atoms), for example, by 353 discrete surface charges distributed on the surfaces of a large disk for the nucleosome core particle and a slender cylinder for the histone tail; the charges are optimized with respect to the Poisson-Boltzmann solution for the electric field, yielding a approximately 5.5% residual. Because regular surfaces enclosing macromolecules are not sufficiently general and may be suboptimal for certain systems, we develop a general method to construct irregular models tailored to the geometry of macromolecules. We also compare charge optimization based on both the electric field and electrostatic potential refinement. Results indicate that irregular surfaces can lead to a more accurate approximation (lower residuals), and the refinement in terms of the electric field is more robust. We also show that surface smoothing for irregular models is important, that the charge optimization (by the TNPACK
Smolensky, Paul; Goldrick, Matthew; Mathis, Donald
2014-01-01
Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The…
Geometric Structure-Preserving Discretization Schemes for Nonlinear Elasticity
2015-08-13
sufficient conditions for the compatibility of displacement gradient and the existence of stress functions on non-contractible bodies. The main...conditions. 15. SUBJECT TERMS geometric theory for nonlinear elasticity, discrete exterior calculus 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...complex allows one to readily derive the necessary and sufficient conditions for the compatibility of displacement gradient and the existence of stress
Reliability-Based Optimization of Structural Elements
Sørensen, John Dalsgaard
In this paper structural elements from an optimization point of view are considered, i.e. only the geometry of a structural element is optimized. Reliability modelling of the structural element is discussed both from an element point of view and from a system point of view. The optimization...
Na Lin
2017-03-01
Full Text Available In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS2Os, which extend the single population particle swarm optimization (PSO algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS2O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS2O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm’s performance. Then PS2O is used for solving the radio frequency identification (RFID network planning (RNP problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.
Hybrid discrete PSO and OPF approach for optimization of biomass fueled micro-scale energy system
Gómez-González, M.; López, A.; Jurado, F.
2013-01-01
Highlights: ► Method to determine the optimal location and size of biomass power plants. ► The proposed approach is a hybrid of PSO algorithm and optimal power flow. ► Comparison among the proposed algorithm and other methods. ► Computational costs are enough lower than that required for exhaustive search. - Abstract: This paper addresses generation of electricity in the specific aspect of finding the best location and sizing of biomass fueled gas micro-turbine power plants, taking into account the variables involved in the problem, such as the local distribution of biomass resources, biomass transportation and extraction costs, operation and maintenance costs, power losses costs, network operation costs, and technical constraints. In this paper a hybrid method is introduced employing discrete particle swarm optimization and optimal power flow. The approach can be applied to search the best sites and capacities to connect biomass fueled gas micro-turbine power systems in a distribution network among a large number of potential combinations and considering the technical constraints of the network. A fair comparison among the proposed algorithm and other methods is performed.
Lin, Na; Chen, Hanning; Jing, Shikai; Liu, Fang; Liang, Xiaodan
2017-03-01
In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS 2 Os, which extend the single population particle swarm optimization (PSO) algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS 2 O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS 2 O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm's performance. Then PS 2 O is used for solving the radio frequency identification (RFID) network planning (RNP) problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.
Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.
Kiumarsi, Bahare; Lewis, Frank L
2015-01-01
This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.
Reliability-based optimization of engineering structures
Sørensen, John Dalsgaard
2008-01-01
The theoretical basis for reliability-based structural optimization within the framework of Bayesian statistical decision theory is briefly described. Reliability-based cost benefit problems are formulated and exemplitied with structural optimization. The basic reliability-based optimization...... problems are generalized to the following extensions: interactive optimization, inspection and repair costs, systematic reconstruction, re-assessment of existing structures. Illustrative examples are presented including a simple introductory example, a decision problem related to bridge re...
Discrete Optimal Multirate Techniques for Excitation Controller Design of a Synchronous Machine
D. I. Pappas
2016-02-01
Full Text Available An optimal control strategy based on Two-Point-Multirate Controllers (TPMRCs, is used to design a desirable excitation controller of a hydrogenerator system, in order to enhance its dynamic stability characteristics. In the TPMRCs based scheme, the control is constrained to a certain piecewise constant signal, while each of the controlled plant outputs is detected many times over a fundamental sampling period T0. On the basis on this strategy, the original problem is reduced to an associate discrete-time linear quadratic (LQ regulation problem for the performance index with cross product terms, for which a fictitious static state feedback controller is needed to be computed. Simulation results for the actual 117 MVA synchronous generator with conventional exciter supplying line to an infinite grid show the effectiveness of the proposed method which has a quite satisfactory performance.
Optimal maintenance policy for a system subject to damage in a discrete time process
Chien, Yu-Hung; Sheu, Shey-Huei; Zhang, Zhe George
2012-01-01
Consider a system operating over n discrete time periods (n=1, 2, …). Each operation period causes a random amount of damage to the system which accumulates over time periods. The system fails when the cumulative damage exceeds a failure level ζ and a corrective maintenance (CM) action is immediately taken. To prevent such a failure, a preventive maintenance (PM) may be performed. In an operation period without a CM or PM, a regular maintenance (RM) is conducted at the end of that period to maintain the operation of the system. We propose a maintenance policy which prescribes a PM when the accumulated damage exceeds a pre-specified level δ ( ⁎ and N ⁎ and discuss some useful properties about them. It has been shown that a δ-based PM outperforms a N-based PM in terms of cost minimization. Numerical examples are presented to demonstrate the optimization of this class of maintenance policies.
Hu, Xiao-Bing; Wang, Ming; Di Paolo, Ezequiel
2013-06-01
Searching the Pareto front for multiobjective optimization problems usually involves the use of a population-based search algorithm or of a deterministic method with a set of different single aggregate objective functions. The results are, in fact, only approximations of the real Pareto front. In this paper, we propose a new deterministic approach capable of fully determining the real Pareto front for those discrete problems for which it is possible to construct optimization algorithms to find the k best solutions to each of the single-objective problems. To this end, two theoretical conditions are given to guarantee the finding of the actual Pareto front rather than its approximation. Then, a general methodology for designing a deterministic search procedure is proposed. A case study is conducted, where by following the general methodology, a ripple-spreading algorithm is designed to calculate the complete exact Pareto front for multiobjective route optimization. When compared with traditional Pareto front search methods, the obvious advantage of the proposed approach is its unique capability of finding the complete Pareto front. This is illustrated by the simulation results in terms of both solution quality and computational efficiency.
Structural and Topology Optimization of Complex Civil Engineering Structures
Hald, Frederik; Kirkegaard, Poul Henning; Andersen, Lars Vabbersgaard
2013-01-01
This paper shows the use of topology optimization for finding an optimized form for civil engineering structures. Today topology optimization and shape optimization have been integrated in several commercial finite element codes. Here, the topology of two complex civil engineering structures...
New non-structured discretizations for fluid flows with reinforced incompressibility
Heib, S.
2003-01-01
This work deals with the discretization of Stokes and Navier-Stokes equations modeling the flow of incompressible fluids on 2-D or 3-D non-structured meshes. Triangles and tetrahedrons are used for 2-D and 3-D meshes, respectively. The developments and calculations are performed with the code Priceles (fast CEA-EdF industrial platform for large Eddy simulation). This code allows to perform simulations both on structured and non-structured meshes. A finite-volume resolution method is used: a finite difference volume (FDV) method is used for the structured meshes and a finite element volume (FEV) method is used for the non-structured meshes. The finite element used in the beginning of this work has several defects. Starting from this situation, the discretization is improved by adding modifications to this element and the new elements introduced are analyzed theoretically. In parallel to these analyses, the new discretizations are implemented in order to test them numerically and to confirm the theoretical analyses. The first chapter presents the physical and mathematical modeling used in this work. The second chapter treats of the discretization of Stokes equations and presents the FEV resolution method. Chapter 3 presents a first attempt of improvement of this finite element and leads to the proposal of a new element which is presented in details. The problem encountered with the new discretization leads to a modification presented in chapter 4. This new discretization gives all the expected convergence results and sometimes shows super-convergence properties. Chapter 5 deals with the study and discretization of the Navier-Stokes equations. The study of the filtered Navier-Stokes equations, used for large Eddy simulations, requires to give a particular attention to the discretization of the diffusive terms. Then, the convective terms are considered. The effects of the convective terms in the initial discretization and in the improved method are compared. The use of
Reliability and optimization of structural systems
Thoft-Christensen, P.
1987-01-01
The proceedings contain 28 papers presented at the 1st working conference. The working conference was organized by the IFIP Working Group 7.5. The proceedings also include 4 papers which were submitted, but for various reasons not presented at the working conference. The working conference was attended by 50 participants from 18 countries. The conference was the first scientific meeting of the new IFIP Working Group 7.5 on 'Reliability and Optimization of Structural Systems'. The purpose of the Working Group 7.5 is to promote modern structural system optimization and reliability theory, to advance international cooperation in the field of structural system optimization and reliability theory, to stimulate research, development and application of structural system optimization and reliability theory, to further the dissemination and exchange of information on reliability and optimization of structural system optimization and reliability theory, and to encourage education in structural system optimization and reliability theory. (orig./HP)
Discrete-State Simulated Annealing For Traveling-Wave Tube Slow-Wave Circuit Optimization
Wilson, Jeffrey D.; Bulson, Brian A.; Kory, Carol L.; Williams, W. Dan (Technical Monitor)
2001-01-01
Algorithms based on the global optimization technique of simulated annealing (SA) have proven useful in designing traveling-wave tube (TWT) slow-wave circuits for high RF power efficiency. The characteristic of SA that enables it to determine a globally optimized solution is its ability to accept non-improving moves in a controlled manner. In the initial stages of the optimization, the algorithm moves freely through configuration space, accepting most of the proposed designs. This freedom of movement allows non-intuitive designs to be explored rather than restricting the optimization to local improvement upon the initial configuration. As the optimization proceeds, the rate of acceptance of non-improving moves is gradually reduced until the algorithm converges to the optimized solution. The rate at which the freedom of movement is decreased is known as the annealing or cooling schedule of the SA algorithm. The main disadvantage of SA is that there is not a rigorous theoretical foundation for determining the parameters of the cooling schedule. The choice of these parameters is highly problem dependent and the designer needs to experiment in order to determine values that will provide a good optimization in a reasonable amount of computational time. This experimentation can absorb a large amount of time especially when the algorithm is being applied to a new type of design. In order to eliminate this disadvantage, a variation of SA known as discrete-state simulated annealing (DSSA), was recently developed. DSSA provides the theoretical foundation for a generic cooling schedule which is problem independent, Results of similar quality to SA can be obtained, but without the extra computational time required to tune the cooling parameters. Two algorithm variations based on DSSA were developed and programmed into a Microsoft Excel spreadsheet graphical user interface (GUI) to the two-dimensional nonlinear multisignal helix traveling-wave amplifier analysis program TWA3
Fermion Systems in Discrete Space-Time Exemplifying the Spontaneous Generation of a Causal Structure
Diethert, A.; Finster, F.; Schiefeneder, D.
As toy models for space-time at the Planck scale, we consider examples of fermion systems in discrete space-time which are composed of one or two particles defined on two up to nine space-time points. We study the self-organization of the particles as described by a variational principle both analytically and numerically. We find an effect of spontaneous symmetry breaking which leads to the emergence of a discrete causal structure.
Intelligent structural optimization: Concept, Model and Methods
Lu, Dagang; Wang, Guangyuan; Peng, Zhang
2002-01-01
Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented
GUO Han-Ying,; LI Yu-Qi; WU Ke1; WANG Shi-Kun
2002-01-01
In this first paper of a series, we study the difference discrete variational principle in the framework of multi-parameter differential approach by regarding the forward difference as an entire geometric object in view of noncommutative differential geometry. Regarding the difference as an entire geometric object, the difference discrete version of Legendre transformation can be introduced. By virtue of this variational principle, we can discretely deal with the variation problems in both the Lagrangian and Hamiltonian formalisms to get difference discrete Euler-Lagrange equations and canonical ones for the difference discrete versions of the classical mechanics and classical field theory.
Kubatko, Ethan J.; Yeager, Benjamin A.; Ketcheson, David I.
2013-01-01
Discontinuous Galerkin (DG) spatial discretizations are often used in a method-of-lines approach with explicit strong-stability-preserving (SSP) Runge–Kutta (RK) time steppers for the numerical solution of hyperbolic conservation laws. The time steps that are employed in this type of approach must satisfy Courant–Friedrichs–Lewy stability constraints that are dependent on both the region of absolute stability and the SSP coefficient of the RK method. While existing SSPRK methods have been optimized with respect to the latter, it is in fact the former that gives rise to stricter constraints on the time step in the case of RKDG stability. Therefore, in this work, we present the development of new “DG-optimized” SSPRK methods with stability regions that have been specifically designed to maximize the stable time step size for RKDG methods of a given order in one space dimension. These new methods represent the best available RKDG methods in terms of computational efficiency, with significant improvements over methods using existing SSPRK time steppers that have been optimized with respect to SSP coefficients. Second-, third-, and fourth-order methods with up to eight stages are presented, and their stability properties are verified through application to numerical test cases.
Hao Yin
2014-01-01
Full Text Available For SLA-aware service composition problem (SSC, an optimization model for this algorithm is built, and a hybrid multiobjective discrete particle swarm optimization algorithm (HMDPSO is also proposed in this paper. According to the characteristic of this problem, a particle updating strategy is designed by introducing crossover operator. In order to restrain particle swarm’s premature convergence and increase its global search capacity, the swarm diversity indicator is introduced and a particle mutation strategy is proposed to increase the swarm diversity. To accelerate the process of obtaining the feasible particle position, a local search strategy based on constraint domination is proposed and incorporated into the proposed algorithm. At last, some parameters in the algorithm HMDPSO are analyzed and set with relative proper values, and then the algorithm HMDPSO and the algorithm HMDPSO+ incorporated by local search strategy are compared with the recently proposed related algorithms on different scale cases. The results show that algorithm HMDPSO+ can solve the SSC problem more effectively.
Kubatko, Ethan J.
2013-10-29
Discontinuous Galerkin (DG) spatial discretizations are often used in a method-of-lines approach with explicit strong-stability-preserving (SSP) Runge–Kutta (RK) time steppers for the numerical solution of hyperbolic conservation laws. The time steps that are employed in this type of approach must satisfy Courant–Friedrichs–Lewy stability constraints that are dependent on both the region of absolute stability and the SSP coefficient of the RK method. While existing SSPRK methods have been optimized with respect to the latter, it is in fact the former that gives rise to stricter constraints on the time step in the case of RKDG stability. Therefore, in this work, we present the development of new “DG-optimized” SSPRK methods with stability regions that have been specifically designed to maximize the stable time step size for RKDG methods of a given order in one space dimension. These new methods represent the best available RKDG methods in terms of computational efficiency, with significant improvements over methods using existing SSPRK time steppers that have been optimized with respect to SSP coefficients. Second-, third-, and fourth-order methods with up to eight stages are presented, and their stability properties are verified through application to numerical test cases.
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.
Optimally segmented permanent magnet structures
Insinga, Andrea Roberto; Bjørk, Rasmus; Smith, Anders
2016-01-01
We present an optimization approach which can be employed to calculate the globally optimal segmentation of a two-dimensional magnetic system into uniformly magnetized pieces. For each segment the algorithm calculates the optimal shape and the optimal direction of the remanent flux density vector......, with respect to a linear objective functional. We illustrate the approach with results for magnet design problems from different areas, such as a permanent magnet electric motor, a beam focusing quadrupole magnet for particle accelerators and a rotary device for magnetic refrigeration....
Discrete symmetries and the complex structure of Calabi-Yau manifolds
Ross, G.G.
1988-01-01
We show how the discrete symmetries, which may be present after Calabi-Yau compactification for specific choices of the complex structure, extend to the h 2,1 moduli - the scalar fields whose vacuum expectation values determine the complex structure. This allows us to determine much about the coupling of the moduli and hence the energetically favoured complex structure. The discrete symmetry transformation properties of the moduli are worked out in detail for a three-generation Calabi-Yau model and it is shown how minimization of the effective potential involving these fields selects the complex structure which leaves unbroken a set of discrete symmetries. The phenomenological implications of the symmetries are briefly discussed. (orig.)
Structure Preserving Spatial Discretization of a 1-D Piezoelectric Timoshenko Beam
Voss, T.; Scherpen, J. M. A.
2011-01-01
In this paper we show how to spatially discretize a distributed model of a piezoelectric beam representing the dynamics of an inflatable space reflector in port-Hamiltonian (pH) form. This model can then be used to design a controller for the shape of the inflatable structure. Inflatable structures
Density perturbations due to the inhomogeneous discrete spatial structure of space-time
Wolf, C.
1998-01-01
For the case that space-time permits an inhomogeneous discrete spatial structure due to varying gravitational fields or a foam-like structure of space-time, it is demonstrated that thermodynamic reasoning implies that matter-density perturbations will arise in the early universe
Optimization of mechanical structures using particle swarm optimization
Leite, Victor C.; Schirru, Roberto
2015-01-01
Several optimization problems are dealed with the particle swarm optimization (PSO) algorithm, there is a wide kind of optimization problems, it may be applications related to logistics or the reload of nuclear reactors. This paper discusses the use of the PSO in the treatment of problems related to mechanical structure optimization. The geometry and material characteristics of mechanical components are important for the proper functioning and performance of the systems were they are applied, particularly to the nuclear field. Calculations related to mechanical aspects are all made using ANSYS, while the PSO is programed in MATLAB. (author)
Optimization of mechanical structures using particle swarm optimization
Leite, Victor C.; Schirru, Roberto, E-mail: victor.coppo.leite@lmp.ufrj.br [Coordenacao dos Programas de Pos-Graduacao em Engenharia (LMP/PEN/COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Lab. de Monitoracao de Processos
2015-07-01
Several optimization problems are dealed with the particle swarm optimization (PSO) algorithm, there is a wide kind of optimization problems, it may be applications related to logistics or the reload of nuclear reactors. This paper discusses the use of the PSO in the treatment of problems related to mechanical structure optimization. The geometry and material characteristics of mechanical components are important for the proper functioning and performance of the systems were they are applied, particularly to the nuclear field. Calculations related to mechanical aspects are all made using ANSYS, while the PSO is programed in MATLAB. (author)
Methodology of shell structure reinforcement layout optimization
Szafrański, Tomasz; Małachowski, Jerzy; Damaziak, Krzysztof
2018-01-01
This paper presents an optimization process of a reinforced shell diffuser intended for a small wind turbine (rated power of 3 kW). The diffuser structure consists of multiple reinforcement and metal skin. This kind of structure is suitable for optimization in terms of selection of reinforcement density, stringers cross sections, sheet thickness, etc. The optimisation approach assumes the reduction of the amount of work to be done between the optimization process and the final product design. The proposed optimization methodology is based on application of a genetic algorithm to generate the optimal reinforcement layout. The obtained results are the basis for modifying the existing Small Wind Turbine (SWT) design.
Energy group structure determination using particle swarm optimization
Yi, Ce; Sjoden, Glenn
2013-01-01
Highlights: ► Particle swarm optimization is applied to determine broad group structure. ► A graph representation of the broad group structure problem is introduced. ► The approach is tested on a fuel-pin model. - Abstract: Multi-group theory is widely applied for the energy domain discretization when solving the Linear Boltzmann Equation. To reduce the computational cost, fine group cross libraries are often down-sampled into broad group cross section libraries. Cross section data collapsing generally involves two steps: Firstly, the broad group structure has to be determined; secondly, a weighting scheme is used to evaluate the broad cross section library based on the fine group cross section data and the broad group structure. A common scheme is to average the fine group cross section weighted by the fine group flux. Cross section collapsing techniques have been intensively researched. However, most studies use a pre-determined group structure, open based on experience, to divide the neutron energy spectrum into thermal, epi-thermal, fast, etc. energy range. In this paper, a swarm intelligence algorithm, particle swarm optimization (PSO), is applied to optimize the broad group structure. A graph representation of the broad group structure determination problem is introduced. And the swarm intelligence algorithm is used to solve the graph model. The effectiveness of the approach is demonstrated using a fuel-pin model
Optimal design of lossy bandgap structures
Jensen, Jakob Søndergaard
2004-01-01
The method of topology optimization is used to design structures for wave propagation with one lossy material component. Optimized designs for scalar elastic waves are presented for mininimum wave transmission as well as for maximum wave energy dissipation. The structures that are obtained...... are of the 1D or 2D bandgap type depending on the objective and the material parameters....
Efficient Reanalysis Procedures in Structural Topology Optimization
Amir, Oded
This thesis examines efficient solution procedures for the structural analysis problem within topology optimization. The research is motivated by the observation that when the nested approach to structural optimization is applied, most of the computational effort is invested in repeated solutions...... on approximate reanalysis. For cases where memory limitations require the utilization of iterative equation solvers, we suggest efficient procedures based on alternative termination criteria for such solvers. These approaches are tested on two- and three-dimensional topology optimization problems including...
A multi-fidelity analysis selection method using a constrained discrete optimization formulation
Stults, Ian C.
uncertainty present in analyses with 4 or fewer input variables could be effectively quantified using a strategic distribution creation method; if more than 4 input variables exist, a Frontier Finding Particle Swarm Optimization should instead be used. Once model uncertainty in contributing analysis code choices has been quantified, a selection method is required to determine which of these choices should be used in simulations. Because much of the selection done for engineering problems is driven by the physics of the problem, these are poor candidate problems for testing the true fitness of a candidate selection method. Specifically moderate and high dimensional problems' variability can often be reduced to only a few dimensions and scalability often cannot be easily addressed. For these reasons a simple academic function was created for the uncertainty quantification, and a canonical form of the Fidelity Selection Problem (FSP) was created. Fifteen best- and worst-case scenarios were identified in an effort to challenge the candidate selection methods both with respect to the characteristics of the tradeoff between time cost and model uncertainty and with respect to the stringency of the constraints and problem dimensionality. The results from this experiment show that a Genetic Algorithm (GA) was able to consistently find the correct answer, but under certain circumstances, a discrete form of Particle Swarm Optimization (PSO) was able to find the correct answer more quickly. To better illustrate how the uncertainty quantification and discrete optimization might be conducted for a "real world" problem, an illustrative example was conducted using gas turbine engines.
Discrete PSO algorithm based optimization of transmission lines loading in TNEP problem
Shayeghi, H.; Mahdavi, M.; Bagheri, A.
2010-01-01
Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e. expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using discrete particle swarm optimization (DPSO) algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. The proposed idea has been tested on the Garvers network and an actual transmission network of the Azerbaijan regional electric company, Iran, and the results are compared with the decimal codification genetic algorithm (DCGA) technique. The results evaluation shows that the network will possess maximum efficiency economically. Also, it is shown that precision and convergence speed of the proposed DPSO based method for the solution of the STNEP problem is superior to DCGA approach.
Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng
2016-01-01
Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.
A Discrete Fruit Fly Optimization Algorithm for the Traveling Salesman Problem.
Zi-Bin Jiang
Full Text Available The fruit fly optimization algorithm (FOA is a newly developed bio-inspired algorithm. The continuous variant version of FOA has been proven to be a powerful evolutionary approach to determining the optima of a numerical function on a continuous definition domain. In this study, a discrete FOA (DFOA is developed and applied to the traveling salesman problem (TSP, a common combinatorial problem. In the DFOA, the TSP tour is represented by an ordering of city indices, and the bio-inspired meta-heuristic search processes are executed with two elaborately designed main procedures: the smelling and tasting processes. In the smelling process, an effective crossover operator is used by the fruit fly group to search for the neighbors of the best-known swarm location. During the tasting process, an edge intersection elimination (EXE operator is designed to improve the neighbors of the non-optimum food location in order to enhance the exploration performance of the DFOA. In addition, benchmark instances from the TSPLIB are classified in order to test the searching ability of the proposed algorithm. Furthermore, the effectiveness of the proposed DFOA is compared to that of other meta-heuristic algorithms. The results indicate that the proposed DFOA can be effectively used to solve TSPs, especially large-scale problems.
Structure of the discrete Dirac vacuum in the sigma + omega model
Miller, L.D.
1989-01-01
The sigma + omega model potentials imply that any moderate to large nucleus should have thousands of discrete negative-energy nucleon states. Theoretical predictions of structure in this discrete island of the nuclear Dirac sea are presented in this paper. This structure is related to the spectral functions that will emerge in high energy electron- and hardon-induced reactions on nuclei. These high-energy reaction studies should supplement our understanding of the saturation mechanism of the sigma + omega model. They could also identify the threshold for observable quantum chromo-dynamics (QCD) effects in nuclei
V. A. Baturin
2017-03-01
Full Text Available An optimal control problem for discrete systems is considered. A method of successive improvements along with its modernization based on the expansion of the main structures of the core algorithm about the parameter is suggested. The idea of the method is based on local approximation of attainability set, which is described by the zeros of the Bellman function in the special problem of optimal control. The essence of the problem is as follows: from the end point of the phase is required to find a path that minimizes functional deviations of the norm from the initial state. If the initial point belongs to the attainability set of the original controlled system, the value of the Bellman function equal to zero, otherwise the value of the Bellman function is greater than zero. For this special task Bellman equation is considered. The support approximation and Bellman equation are selected. The Bellman function is approximated by quadratic terms. Along the allowable trajectory, this approximation gives nothing, because Bellman function and its expansion coefficients are zero. We used a special trick: an additional variable is introduced, which characterizes the degree of deviation of the system from the initial state, thus it is obtained expanded original chain. For the new variable initial nonzero conditions is selected, thus obtained trajectory is lying outside attainability set and relevant Bellman function is greater than zero, which allows it to hold a non-trivial approximation. As a result of these procedures algorithms of successive improvements is designed. Conditions for relaxation algorithms and conditions for the necessary conditions of optimality are also obtained.
Electronic Structure of Au25 Clusters: Between Discrete and Continuous
Katsiev, Khabiboulakh
2016-07-15
Here, an approach based on synchrotron resonant photoemission is emplyed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states at the vicinity of the Fermi level. These observations are supported by DFT studies.
Electronic Structure of Au25 Clusters: Between Discrete and Continuous
Katsiev, Khabiboulakh; Lozova, Nataliya; Wang, Lu; Katla, Saikrishna; Li, Ruipeng; Mei, Wai Ning; Skrabalak, Sara; Challa, Challa; Losovyj, Yaroslav
2016-01-01
Here, an approach based on synchrotron resonant photoemission is emplyed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states at the vicinity of the Fermi level. These observations are supported by DFT studies.
Reliability Based Optimization of Structural Systems
Sørensen, John Dalsgaard
1987-01-01
The optimization problem to design structural systems such that the reliability is satisfactory during the whole lifetime of the structure is considered in this paper. Some of the quantities modelling the loads and the strength of the structure are modelled as random variables. The reliability...... is estimated using first. order reliability methods ( FORM ). The design problem is formulated as the optimization problem to minimize a given cost function such that the reliability of the single elements satisfies given requirements or such that the systems reliability satisfies a given requirement....... For these optimization problems it is described how a sensitivity analysis can be performed. Next, new optimization procedures to solve the optimization problems are presented. Two of these procedures solve the system reliability based optimization problem sequentially using quasi-analytical derivatives. Finally...
STRUCTURE OPTIMIZATION OF RESERVATION BY PRECISE QUADRATIC REGULARIZATION
KOSOLAP A. I.
2015-11-01
Full Text Available The problem of optimization of the structure of systems redundancy elements. Such problems arise in the design of complex systems. To improve the reliability of operation of such systems of its elements are duplicated. This increases system cost and improves its reliability. When optimizing these systems is maximized probability of failure of the entire system while limiting its cost or the cost is minimized for a given probability of failure-free operation. A mathematical model of the problem is a discrete backup multiextremal. To search for the global extremum of currently used methods of Lagrange multipliers, coordinate descent, dynamic programming, random search. These methods guarantee a just and local solutions are used in the backup tasks of small dimension. In the work for solving redundancy uses a new method for accurate quadratic regularization. This method allows you to convert the original discrete problem to the maximization of multi vector norm on a convex set. This means that the diversity of the tasks given to the problem of redundancy maximize vector norm on a convex set. To solve the problem, a reformed straightdual interior point methods. Currently, it is the best method for local optimization of nonlinear problems. Transformed the task includes a new auxiliary variable, which is determined by dichotomy. There have been numerous comparative numerical experiments in problems with the number of redundant subsystems to one hundred. These experiments confirm the effectiveness of the method of precise quadratic regularization for solving problems of redundancy.
Discrete-time Calogero-Moser system and Lagrangian 1-form structure
Yoo-Kong, Sikarin; Lobb, Sarah; Nijhoff, Frank
2011-01-01
We study the Lagrange formalism of the (rational) Calogero-Moser (CM) system, both in discrete time and continuous time, as a first example of a Lagrangian 1-form structure in the sense of the recent paper (Lobb and Nijhoff 2009 J. Phys. A: Math. Theor.42 454013). The discrete-time model of the CM system was established some time ago arising as a pole reduction of a semi-discrete version of the Kadomtsev-Petviashvili (KP) equation, and was shown to lead to an exactly integrable correspondence (multivalued map). In this paper, we present the full KP solution based on the commutativity of the discrete-time flows in the two discrete KP variables. The compatibility of the corresponding Lax matrices is shown to lead directly to the relevant closure relation on the level of the Lagrangians. Performing successive continuum limits on both the level of the KP equation and the level of the CM system, we establish the proper Lagrangian 1-form structure for the continuum case of the CM model. We use the example of the three-particle case to elucidate the implementation of the novel least-action principle, which was presented in Lobb and Nijhoff (2009), for the simpler case of Lagrangian 1-forms. (paper)
Santosa, B.; Siswanto, N.; Fiqihesa
2018-04-01
This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution
Yu, Xue; Chen, Wei-Neng; Gu, Tianlong; Zhang, Huaxiang; Yuan, Huaqiang; Kwong, Sam; Zhang, Jun
2017-08-07
This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.
Maria CAPCELEA
2015-12-01
Full Text Available Este elaborat şi argumentat teoretic un algoritm eficient pentru determinarea strategiilor optime staţionare în proble-mele stocastice de control optimal discret cu perioada de dirijare infinită, definite pe reţele decizionale cu multiple clase recurente, în care este aplicat criteriul de optimizare a combinaţiei convexe a costurilor medii în clasele recurente. Sunt examinate probleme în care costurile de tranziţie între stările sistemului dinamic şi probabilităţile de tranziţie, definite în stările necontrolabile, sunt constante independente de timp. Algoritmul elaborat este bazat pe modelul de programare liniară pentru determinarea strategiilor optime în problemele de control definite pe reţele decizionale perfecte [3,4].AN ALGORITHM FOR DETERMINING STATIONARY OPTIMAL STRATEGIES FOR STOCHASTIC DISCRETE OPTIMAL CONTROL PROBLEMS DEFINED ON NETWORKS WITH MULTIPLE RECURRENT CLASSESAn efficient algorithm for determining optimal stationary strategies for the stochastic discrete optimal control problems with infinite time horizon is developed and theoretically justified. The problems are defined on decision networks with multiple recurrent classes. The average costs convex combination optimization criterion is applied. We examine problems in which the costs of transitions between the states of the dynamic system and transition probabilities, defined on the uncontrollable states, are constants independent on time. The algorithm is based on the linear programming model developed for determining optimal strategies in control problems defined on perfect decision networks [3,4].
Optimal reinforcing of reticular structures Optimal reinforcing of reticular structures
Juan Santiago Mejía
2006-12-01
Full Text Available This article presents an application of Genetic Algorithms (GA and Finite Element Analysis (FEA to solve a structural optimisation problem on reticular plastic structures. Structural optimisation is used to modify the original shape by placing reinforcements at optimum locations. As a result, a reduction in the maximum stress by 14,70% for a structure with a final volume increase of 8,36% was achieved. This procedure solves the structural optimisation problem by adjusting the original mold and thereby avoiding the re-construction of a new one.Este artículo presenta una aplicación de Algoritmos Genéticos (GA y Análisis por Elementos Finitos (FEA a la solución de un problema de optimización estructural en estructuras reticulares plásticas. Optimización estructurales usada para modificar la forma original colocando refuerzos en posiciones óptimas. Como resultado se obtuvo una reducción en el esfuerzo máximo de 14,70% para una estructura cuyo volumen original aumento en 8,36%. Este procedimiento soluciona el problema de optimización estructural ajustando el molde original y evitando la manufactura de un nuevo molde.
Optimal Investment in Structured Bonds
Jessen, Pernille; Jørgensen, Peter Løchte
2012-01-01
of the article is to provide possible explanations for the puzzle of why small retail investors hold structured bonds. The investment universe consists of a stock index, a risk-free bank account, and a structured bond containing an option written on another index. We apply expected utility maximization...
Structural Optimization based on the Concept of First Order Analysis
Shinji, Nishiwaki; Hidekazu, Nishigaki; Yasuaki, Tsurumi; Yoshio, Kojima; Noboru, Kikuchi
2002-01-01
Computer Aided Engineering (CAE) has been successfully utilized in mechanical industries such as the automotive industry. It is, however, difficult for most mechanical design engineers to directly use CAE due to the sophisticated nature of the operations involved. In order to mitigate this problem, a new type of CAE, First Order Analysis (FOA) has been proposed. This paper presents the outcome of research concerning the development of a structural topology optimization methodology within FOA. This optimization method is constructed based on discrete and function-oriented elements such as beam and panel elements, and sequential convex programming. In addition, examples are provided to show the utility of the methodology presented here for mechanical design engineers
Hamiltonian structures and integrability for a discrete coupled KdV-type equation hierarchy
Zhao Haiqiong; Zhu Zuonong; Zhang Jingli
2011-01-01
Coupled Korteweg-de Vries (KdV) systems have many important physical applications. By considering a 4 × 4 spectral problem, we derive a discrete coupled KdV-type equation hierarchy. Our hierarchy includes the coupled Volterra system proposed by Lou et al. (e-print arXiv: 0711.0420) as the first member which is a discrete version of the coupled KdV equation. We also investigate the integrability in the Liouville sense and the multi-Hamiltonian structures for the obtained hierarchy. (authors)
Topology optimization for simplified structural fire safety
Madsen, Søren; Lange, Nis P.; Giuliani, Luisa
2016-01-01
Topology optimization is applied in an idealized structural fire safety model, where the minimum compliance problem is constrained by temperature-controlled structural degradation. The constraint ensures a certain structural stiffness after a prescribed time. As this time period is extended......, resulting optimized topologies tend to become thicker or introduce redundant members that can take over when structural parts near the origin of the fire lose their load carrying capability. Hence, the structural degradation model acts as an erosion operator on the topology and indirectly enforces a minimum...
Topology optimization of hyperelastic structures using a level set method
Chen, Feifei; Wang, Yiqiang; Wang, Michael Yu; Zhang, Y. F.
2017-12-01
Soft rubberlike materials, due to their inherent compliance, are finding widespread implementation in a variety of applications ranging from assistive wearable technologies to soft material robots. Structural design of such soft and rubbery materials necessitates the consideration of large nonlinear deformations and hyperelastic material models to accurately predict their mechanical behaviour. In this paper, we present an effective level set-based topology optimization method for the design of hyperelastic structures that undergo large deformations. The method incorporates both geometric and material nonlinearities where the strain and stress measures are defined within the total Lagrange framework and the hyperelasticity is characterized by the widely-adopted Mooney-Rivlin material model. A shape sensitivity analysis is carried out, in the strict sense of the material derivative, where the high-order terms involving the displacement gradient are retained to ensure the descent direction. As the design velocity enters into the shape derivative in terms of its gradient and divergence terms, we develop a discrete velocity selection strategy. The whole optimization implementation undergoes a two-step process, where the linear optimization is first performed and its optimized solution serves as the initial design for the subsequent nonlinear optimization. It turns out that this operation could efficiently alleviate the numerical instability and facilitate the optimization process. To demonstrate the validity and effectiveness of the proposed method, three compliance minimization problems are studied and their optimized solutions present significant mechanical benefits of incorporating the nonlinearities, in terms of remarkable enhancement in not only the structural stiffness but also the critical buckling load.
Phononic band gap structures as optimal designs
Jensen, Jakob Søndergaard; Sigmund, Ole
2003-01-01
In this paper we use topology optimization to design phononic band gap structures. We consider 2D structures subjected to periodic loading and obtain the distribution of two materials with high contrast in material properties that gives the minimal vibrational response of the structure. Both in...
Modelling Dowel Action of Discrete Reinforcing Bars in Cracked Concrete Structures
Kwan, A. K. H.; Ng, P. L.; Lam, J. Y. K.
2010-01-01
Dowel action is one of the component actions for shear force transfer in cracked reinforced concrete. In finite element analysis of concrete structures, the use of discrete representation of reinforcing bars is considered advantageous over the smeared representation due to the relative ease of modelling the bond-slip behaviour. However, there is very limited research on how to simulate the dowel action of discrete reinforcing bars. Herein, a numerical model for dowel action of discrete reinforcing bars crossing cracks in concrete is developed. The model features the derivation of dowel stiffness matrix based on beam-on-elastic-foundation theory and the direct assemblage of dowel stiffness into the concrete element stiffness matrices. The dowel action model is incorporated in a nonlinear finite element programme with secant stiffness formulation. Deep beams tested in the literature are analysed and it is found that the incorporation of dowel action model improves the accuracy of analysis.
Ray, Jaideep; Lefantzi, Sophia; Najm, Habib N.; Kennedy, Christopher A.
2006-01-01
Block-structured adaptively refined meshes (SAMR) strive for efficient resolution of partial differential equations (PDEs) solved on large computational domains by clustering mesh points only where required by large gradients. Previous work has indicated that fourth-order convergence can be achieved on such meshes by using a suitable combination of high-order discretizations, interpolations, and filters and can deliver significant computational savings over conventional second-order methods at engineering error tolerances. In this paper, we explore the interactions between the errors introduced by discretizations, interpolations and filters. We develop general expressions for high-order discretizations, interpolations, and filters, in multiple dimensions, using a Fourier approach, facilitating the high-order SAMR implementation. We derive a formulation for the necessary interpolation order for given discretization and derivative orders. We also illustrate this order relationship empirically using one and two-dimensional model problems on refined meshes. We study the observed increase in accuracy with increasing interpolation order. We also examine the empirically observed order of convergence, as the effective resolution of the mesh is increased by successively adding levels of refinement, with different orders of discretization, interpolation, or filtering.
Strategies for Optimal Design of Structural Systems
Enevoldsen, I.; Sørensen, John Dalsgaard
1992-01-01
Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...
Zakary, Omar; Rachik, Mostafa; Elmouki, Ilias
2017-08-01
First, we devise in this paper, a multi-regions discrete-time model which describes the spatial-temporal spread of an epidemic which starts from one region and enters to regions which are connected with their neighbors by any kind of anthropological movement. We suppose homogeneous Susceptible-Infected-Removed (SIR) populations, and we consider in our simulations, a grid of colored cells, which represents the whole domain affected by the epidemic while each cell can represent a sub-domain or region. Second, in order to minimize the number of infected individuals in one region, we propose an optimal control approach based on a travel-blocking vicinity strategy which aims to control only one cell by restricting movements of infected people coming from all neighboring cells. Thus, we show the influence of the optimal control approach on the controlled cell. We should also note that the cellular modeling approach we propose here, can also describes infection dynamics of regions which are not necessarily attached one to an other, even if no empty space can be viewed between cells. The theoretical method we follow for the characterization of the travel-locking optimal controls, is based on a discrete version of Pontryagin's maximum principle while the numerical approach applied to the multi-points boundary value problems we obtain here, is based on discrete progressive-regressive iterative schemes. We illustrate our modeling and control approaches by giving an example of 100 regions.
Abdulaal, Ahmed; Moghaddass, Ramin; Asfour, Shihab
2017-01-01
Highlights: •Two-stage model links discrete-optimization to real-time system dynamics operation. •The solutions obtained are non-dominated Pareto optimal solutions. •Computationally efficient GA solver through customized chromosome coding. •Modest to considerable savings are achieved depending on the consumer’s preference. -- Abstract: In the wake of today’s highly dynamic and competitive energy markets, optimal dispatching of energy sources requires effective demand responsiveness. Suppliers have adopted a dynamic pricing strategy in efforts to control the downstream demand. This method however requires consumer awareness, flexibility, and timely responsiveness. While residential activities are more flexible and schedulable, larger commercial consumers remain an obstacle due to the impacts on industrial performance. This paper combines methods from quadratic, stochastic, and evolutionary programming with multi-objective optimization and continuous simulation, to propose a two-stage discrete-continuous multi-objective load optimization (DiCoMoLoOp) autonomous approach for industrial consumer demand response (DR). Stage 1 defines discrete-event load shifting targets. Accordingly, controllable loads are continuously optimized in stage 2 while considering the consumer’s utility. Utility functions, which measure the loads’ time value to the consumer, are derived and weights are assigned through an analytical hierarchy process (AHP). The method is demonstrated for an industrial building model using real data. The proposed method integrates with building energy management system and solves in real-time with autonomous and instantaneous load shifting in the hour-ahead energy price (HAP) market. The simulation shows the occasional existence of multiple load management options on the Pareto frontier. Finally, the computed savings, based on the simulation analysis with real consumption, climate, and price data, ranged from modest to considerable amounts
Optimized Parallel Discrete Event Simulation (PDES) for High Performance Computing (HPC) Clusters
Abu-Ghazaleh, Nael
2005-01-01
The aim of this project was to study the communication subsystem performance of state of the art optimistic simulator Synchronous Parallel Environment for Emulation and Discrete-Event Simulation (SPEEDES...
Chen, Jian; Matuttis, Hans-Georg
2013-02-01
We report our experiences with the optimization and parallelization of a discrete element code for convex polyhedra on multi-core machines and introduce a novel variant of the sort-and-sweep neighborhood algorithm. While in theory the whole code in itself parallelizes ideally, in practice the results on different architectures with different compilers and performance measurement tools depend very much on the particle number and optimization of the code. After difficulties with the interpretation of the data for speedup and efficiency are overcome, respectable parallelization speedups could be obtained.
Craft, David
2010-10-01
A discrete set of points and their convex combinations can serve as a sparse representation of the Pareto surface in multiple objective convex optimization. We develop a method to evaluate the quality of such a representation, and show by example that in multiple objective radiotherapy planning, the number of Pareto optimal solutions needed to represent Pareto surfaces of up to five dimensions grows at most linearly with the number of objectives. The method described is also applicable to the representation of convex sets. Copyright © 2009 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Optimization of Perfect Absorbers with Multilayer Structures
Li Voti, Roberto
2018-02-01
We study wide-angle and broadband perfect absorbers with compact multilayer structures made of a sequence of ITO and TiN layers deposited onto a silver thick layer. An optimization procedure is introduced for searching the optimal thicknesses of the layers so as to design a perfect broadband absorber from 400 nm to 750 nm, for a wide range of angles of incidence from 0{°} to 50{°}, for both polarizations and with a low emissivity in the mid-infrared. We eventually compare the performances of several optimal structures that can be very promising for solar thermal energy harvesting and collectors.
Variable ordering structures in vector optimization
Eichfelder, Gabriele
2014-01-01
This book provides an introduction to vector optimization with variable ordering structures, i.e., to optimization problems with a vector-valued objective function where the elements in the objective space are compared based on a variable ordering structure: instead of a partial ordering defined by a convex cone, we see a whole family of convex cones, one attached to each element of the objective space. The book starts by presenting several applications that have recently sparked new interest in these optimization problems, and goes on to discuss fundamentals and important results on a wide ra
Structural optimization of free-form reciprocal structures
Parigi, Dario
2014-01-01
This paper presents an optimization algorithm for the design of structurally efficient free-form reciprocal structures. Because of the geometric complexity of reciprocal structures, only a few structural studies have been carried out so far, and we have a limited knowledge of the relation between...
The optimal design of UAV wing structure
Długosz, Adam; Klimek, Wiktor
2018-01-01
The paper presents an optimal design of UAV wing, made of composite materials. The aim of the optimization is to improve strength and stiffness together with reduction of the weight of the structure. Three different types of functionals, which depend on stress, stiffness and the total mass are defined. The paper presents an application of the in-house implementation of the evolutionary multi-objective algorithm in optimization of the UAV wing structure. Values of the functionals are calculated on the basis of results obtained from numerical simulations. Numerical FEM model, consisting of different composite materials is created. Adequacy of the numerical model is verified by results obtained from the experiment, performed on a tensile testing machine. Examples of multi-objective optimization by means of Pareto-optimal set of solutions are presented.
Inferring network structure in non-normal and mixed discrete-continuous genomic data.
Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran
2018-03-01
Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. © 2017, The International Biometric Society.
Computing optimal interfacial structure of modulated phases
Xu, Jie; Wang, Chu; Shi, An-Chang; Zhang, Pingwen
2016-01-01
We propose a general framework of computing interfacial structures between two modulated phases. Specifically we propose to use a computational box consisting of two half spaces, each occupied by a modulated phase with given position and orientation. The boundary conditions and basis functions are chosen to be commensurate with the bulk structures. It is observed that the ordered nature of modulated structures stabilizes the interface, which enables us to obtain optimal interfacial structures...
Ellington, Roni; Wachira, James; Nkwanta, Asamoah
2010-01-01
The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems.
Ellington, Roni; Wachira, James
2010-01-01
The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems. PMID:20810968
Donado-Garzon, L. D.; Pardo, Y.
2013-12-01
Fractured media are very heterogeneous systems where occur complex physical and chemical processes to model. One of the possible approaches to conceptualize this type of massifs is the Discrete Fracture Network (DFN). Donado et al., modeled flow and transport in a granitic batholith based on this approach and found good fitting with hydraulic and tracer tests, but the computational cost was excessive due to a gigantic amount of elements to model. We present in this work a methodology based on percolation theory for reducing the number of elements and in consequence, to reduce the bandwidth of the conductance matrix and the execution time of each network. DFN poses as an excellent representation of all the set of fractures of the media, but not all the fractures of the media are part of the conductive network. Percolation theory is used to identify which nodes or fractures are not conductive, based on the occupation probability or percolation threshold. In a fractured system, connectivity determines the flow pattern in the fractured rock mass. This volume of fluid is driven through connection paths formed by the fractures, when the permeability of the rock is negligible compared to the fractures. In a population of distributed fractures, each of this that has no intersection with any connected fracture do not contribute to generate a flow field. This algorithm also permits us to erase these elements however they are water conducting and hence, refine even more the backbone of the network. We used 100 different generations of DFN that were optimized in this study using percolation theory. In each of the networks calibrate hydrodynamic parameters as hydraulic conductivity and specific storage coefficient, for each of the five families of fractures, yielding a total of 10 parameters to estimate, at each generation. Since the effects of the distribution of fault orientation changes the value of the percolation threshold, but not the universal laws of classical
Topology optimization for submerged buoyant structures
Picelli, R.; van Dijk, R.; Vicente, W.M.; Pavanello, R.; Langelaar, M.; van Keulen, A.
2017-01-01
This paper presents an evolutionary structural topology optimization method for the design of completely submerged buoyant modules with design-dependent fluid pressure loading. This type of structure is used to support offshore rig installation and pipeline transportation at all water depths. The
Optimization of Large-Scale Structural Systems
Jensen, F. M.
solutions to small problems with one or two variables to the optimization of large structures such as bridges, ships and offshore structures. The methods used for salving these problems have evolved from being classical differential calculus and calculus of variation to very advanced numerical techniques...
Optimal Capital Structure for Insurance Companies
Laeven, R.J.A.; Perotti, E.C.
2010-01-01
This paper analyzes the capital structure decision that insurance companies face. A structural microeconomic model is constructed and solved by means of dynamic optimization. The model allows for a careful analysis of various aspects pertaining to the basic economic trade-off between increasing the
Vanderbei, Robert J., E-mail: rvdb@princeton.edu [Princeton University, Department of Operations Research and Financial Engineering (United States); P Latin-Small-Letter-Dotless-I nar, Mustafa C., E-mail: mustafap@bilkent.edu.tr [Bilkent University, Department of Industrial Engineering (Turkey); Bozkaya, Efe B. [Sabanc Latin-Small-Letter-Dotless-I University, Faculty of Administrative Sciences (Turkey)
2013-02-15
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
Vanderbei, Robert J.; Pınar, Mustafa Ç.; Bozkaya, Efe B.
2013-01-01
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
Li, Chunlong; Zhou, Jianzhong; Ouyang, Shuo; Ding, Xiaoling; Chen, Lu
2014-01-01
Highlights: • Optimization of large-scale hydropower system in the Yangtze River basin. • Improved decomposition–coordination and discrete differential dynamic programming. • Generating initial solution randomly to reduce generation time. • Proposing relative coefficient for more power generation. • Proposing adaptive bias corridor technology to enhance convergence speed. - Abstract: With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize these systems. Optimization of large-scale hydropower system (OLHS), which is to determine water discharges or water levels of overall hydro plants for maximizing total power generation when subjecting to lots of constrains, is a high dimensional, nonlinear and coupling complex problem. In order to solve the OLHS problem effectively, an improved decomposition–coordination and discrete differential dynamic programming (IDC–DDDP) method is proposed in this paper. A strategy that initial solution is generated randomly is adopted to reduce generation time. Meanwhile, a relative coefficient based on maximum output capacity is proposed for more power generation. Moreover, an adaptive bias corridor technology is proposed to enhance convergence speed. The proposed method is applied to long-term optimal dispatches of large-scale hydropower system (LHS) in the Yangtze River basin. Compared to other methods, IDC–DDDP has competitive performances in not only total power generation but also convergence speed, which provides a new method to solve the OLHS problem
Discrete Self-Similarity in Interfacial Hydrodynamics and the Formation of Iterated Structures.
Dallaston, Michael C; Fontelos, Marco A; Tseluiko, Dmitri; Kalliadasis, Serafim
2018-01-19
The formation of iterated structures, such as satellite and subsatellite drops, filaments, and bubbles, is a common feature in interfacial hydrodynamics. Here we undertake a computational and theoretical study of their origin in the case of thin films of viscous fluids that are destabilized by long-range molecular or other forces. We demonstrate that iterated structures appear as a consequence of discrete self-similarity, where certain patterns repeat themselves, subject to rescaling, periodically in a logarithmic time scale. The result is an infinite sequence of ridges and filaments with similarity properties. The character of these discretely self-similar solutions as the result of a Hopf bifurcation from ordinarily self-similar solutions is also described.
Structural Design Optimization On Thermally Induced Vibration
Gu, Yuanxian; Chen, Biaosong; Zhang, Hongwu; Zhao, Guozhong
2002-01-01
The numerical method of design optimization for structural thermally induced vibration is originally studied in this paper and implemented in application software JIFEX. The direct and adjoint methods of sensitivity analysis for thermal induced vibration coupled with both linear and nonlinear transient heat conduction is firstly proposed. Based on the finite element method, the structural linear dynamics is treated simultaneously with coupled linear and nonlinear transient heat structural linear dynamics is treated simultaneously with coupled linear and nonlinear transient heat conduction. In the thermal analysis model, the nonlinear heat conduction considered is result from the radiation and temperature-dependent materials. The sensitivity analysis of transient linear and nonlinear heat conduction is performed with the precise time integration method. And then, the sensitivity analysis of structural transient dynamics is performed by the Newmark method. Both the direct method and the adjoint method are employed to derive the sensitivity equations of thermal vibration, and there are two adjoint vectors of structure and heat conduction respectively. The coupling effect of heat conduction on thermal vibration in the sensitivity analysis is particularly investigated. With coupling sensitivity analysis, the optimization model is constructed and solved by the sequential linear programming or sequential quadratic programming algorithm. The methods proposed have been implemented in the application software JIFEX of structural design optimization, and numerical examples are given to illustrate the methods and usage of structural design optimization on thermally induced vibration
Kalb, Guyonne; Kühnle, Daniel; Scott, Anthony; Cheng, Terence Chai; Jeon, Sung-Hee
2015-01-01
Few papers examine the pecuniary and non-pecuniary determinants of doctors' labour supply despite substantial predicted shortages in many OECD countries. We contribute to the literature by applying both a structural discrete choice and a reduced-form approach. Using detailed survey data for Australian physicians, we examine how these different modelling approaches affect estimated wage elasticities at the intensive margin. We show that all modelling approaches predict small negative wage elas...
Introductory discrete mathematics
Balakrishnan, V K
2010-01-01
This concise text offers an introduction to discrete mathematics for undergraduate students in computer science and mathematics. Mathematics educators consider it vital that their students be exposed to a course in discrete methods that introduces them to combinatorial mathematics and to algebraic and logical structures focusing on the interplay between computer science and mathematics. The present volume emphasizes combinatorics, graph theory with applications to some stand network optimization problems, and algorithms to solve these problems.Chapters 0-3 cover fundamental operations involv
Norman Josephy
2011-01-01
Full Text Available We present a method of optimal hedging and pricing of equity-linked life insurance products in an incomplete discrete-time financial market. A pure endowment life insurance contract with guarantee is used as an example. The financial market incompleteness is caused by the assumption that the underlying risky asset price ratios are distributed in a compact interval, generalizing the assumptions of multinomial incomplete market models. For a range of initial hedging capitals for the embedded financial option, we numerically solve an optimal hedging problem and determine a risk-return profile of each optimal non-self-financing hedging strategy. The fair price of the insurance contract is determined according to the insurer's risk-return preferences. Illustrative numerical results of testing our algorithm on hypothetical insurance contracts are documented. A discussion and a test of a hedging strategy recalibration technique for long-term contracts are presented.
Naz, Rehana
2018-01-01
Pontrygin-type maximum principle is extended for the present value Hamiltonian systems and current value Hamiltonian systems of nonlinear difference equations for uniform time step $h$. A new method termed as a discrete time current value Hamiltonian method is established for the construction of first integrals for current value Hamiltonian systems of ordinary difference equations arising in Economic growth theory.
Structural optimization for nonlinear dynamic response
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...
Optimization of C20 isomers structure
Ndjaka, J.M.B.; Charlier, J.C.
2001-07-01
We have performed geometry optimization of various possible planar and three-dimensional C 20 geometries. The planar structures considered include a linear chain, a monoclinic ring, and a bicyclic bow tie; while the three-dimensional geometric; consisted of a bowl or corranulene structure and a fullerene cage. In agreement with Wang et al MP2's calculations, our results predict the corranulene bowl to be the lowest energy structure. From the ground state geometry to the highest energy, considered C 20 structures, listed in increasing energy, are bowl, cage, bow tie, ring and chain. For the ring and bow tie isomers, the shape of the optimized structure deviates from that of the initial configuration; while the shape of the optimised bowl, cage and chain remain unchanged. (author)
Chen, J.-D.
2007-01-01
In this paper, the robust control problem of output dynamic observer-based control for a class of uncertain neutral systems with discrete and distributed time delays is considered. Linear matrix inequality (LMI) optimization approach is used to design the new output dynamic observer-based controls. Three classes of observer-based controls are proposed and the maximal perturbed bound is given. Based on the results of this paper, the constraint of matrix equality is not necessary for designing the observer-based controls. Finally, a numerical example is given to illustrate the usefulness of the proposed method
Continuum and discrete approach in modeling biofilm development and structure: a review.
Mattei, M R; Frunzo, L; D'Acunto, B; Pechaud, Y; Pirozzi, F; Esposito, G
2018-03-01
The scientific community has recognized that almost 99% of the microbial life on earth is represented by biofilms. Considering the impacts of their sessile lifestyle on both natural and human activities, extensive experimental activity has been carried out to understand how biofilms grow and interact with the environment. Many mathematical models have also been developed to simulate and elucidate the main processes characterizing the biofilm growth. Two main mathematical approaches for biomass representation can be distinguished: continuum and discrete. This review is aimed at exploring the main characteristics of each approach. Continuum models can simulate the biofilm processes in a quantitative and deterministic way. However, they require a multidimensional formulation to take into account the biofilm spatial heterogeneity, which makes the models quite complicated, requiring significant computational effort. Discrete models are more recent and can represent the typical multidimensional structural heterogeneity of biofilm reflecting the experimental expectations, but they generate computational results including elements of randomness and introduce stochastic effects into the solutions.
Park, K. C.; Belvin, W. Keith
1990-01-01
A general form for the first-order representation of the continuous second-order linear structural-dynamics equations is introduced to derive a corresponding form of first-order continuous Kalman filtering equations. Time integration of the resulting equations is carried out via a set of linear multistep integration formulas. It is shown that a judicious combined selection of computational paths and the undetermined matrices introduced in the general form of the first-order linear structural systems leads to a class of second-order discrete Kalman filtering equations involving only symmetric sparse N x N solution matrices.
Newton-type method for the variational discretization of topology optimization problems
Evgrafov, Anton
2013-01-01
We present a locally quadratically convergent optimization algorithm for solving topology optimization problems. The distinguishing feature of the algorithm is to treat the design as a smooth function of the state and not vice versa as in the traditional nested approach to topology optimization, ...
Modeling, Analysis, and Optimization Issues for Large Space Structures
Pinson, L. D. (Compiler); Amos, A. K. (Compiler); Venkayya, V. B. (Compiler)
1983-01-01
Topics concerning the modeling, analysis, and optimization of large space structures are discussed including structure-control interaction, structural and structural dynamics modeling, thermal analysis, testing, and design.
Finite approximations in discrete-time stochastic control quantized models and asymptotic optimality
Saldi, Naci; Yüksel, Serdar
2018-01-01
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems. This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original mo...
Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control
Hansen, Anders Hedegaard; Asmussen, Magnus Færing; Bech, Michael Møller
2017-01-01
For Discrete Displacement Cylinder (DDC) drives the control task lies in choosing force level. Hence, which force level to apply and thereby which pressure level each cylinder chambers shall be connected to. The DDC system is inherently a force system why often a force reference is generated...... and compared to a PID like tracking controller combined with a FSA. The results indicate that the energy efficiency of position tracking DDC systems may be improved significantly by using the MPC algorithm....
Design and volume optimization of space structures
Jiang, Caigui
2017-07-21
We study the design and optimization of statically sound and materially efficient space structures constructed by connected beams. We propose a systematic computational framework for the design of space structures that incorporates static soundness, approximation of reference surfaces, boundary alignment, and geometric regularity. To tackle this challenging problem, we first jointly optimize node positions and connectivity through a nonlinear continuous optimization algorithm. Next, with fixed nodes and connectivity, we formulate the assignment of beam cross sections as a mixed-integer programming problem with a bilinear objective function and quadratic constraints. We solve this problem with a novel and practical alternating direction method based on linear programming relaxation. The capability and efficiency of the algorithms and the computational framework are validated by a variety of examples and comparisons.
Design and volume optimization of space structures
Jiang, Caigui; Tang, Chengcheng; Seidel, Hans-Peter; Wonka, Peter
2017-01-01
We study the design and optimization of statically sound and materially efficient space structures constructed by connected beams. We propose a systematic computational framework for the design of space structures that incorporates static soundness, approximation of reference surfaces, boundary alignment, and geometric regularity. To tackle this challenging problem, we first jointly optimize node positions and connectivity through a nonlinear continuous optimization algorithm. Next, with fixed nodes and connectivity, we formulate the assignment of beam cross sections as a mixed-integer programming problem with a bilinear objective function and quadratic constraints. We solve this problem with a novel and practical alternating direction method based on linear programming relaxation. The capability and efficiency of the algorithms and the computational framework are validated by a variety of examples and comparisons.
Strength optimized designs of thermoelastic structures
Pedersen, Pauli; Pedersen, Niels Leergaard
2010-01-01
For thermoelastic structures the same optimal design does not simultaneously lead to minimum compliance and maximum strength. Compliance may be a questionable objective and focus for the present paper is on the important aspect of strength, quantified as minimization of the maximum von Mises stre...... loads are appended....
Kim, Jae Hwan; Park, Soon Ho; Na, Man Gyun
2014-01-01
Highlights: • A model predictive controller for load-following operation was developed. • Genetic algorithm optimizes the five nonlinear discrete control rod speeds. • The boron concentration is adjusted with automatic adjustment logic. • The proposed controller reflects the realistic control rod drive mechanism movement. • The performance was confirmed to be satisfactory by simulation from BOC to EOC. - Abstract: Currently, most existing nuclear power plants alter the reactor power by adjusting the boron concentration in the coolant because it has a smaller effect on the reactor power distribution. Frequent control rod movements for load-following operation induce xenon-oscillation. Therefore, a controller that can subdue this phenomenon effectively is needed. At an APR1400 nuclear power plant which is a pressurized water reactor (PWR), the reactor power is controlled automatically using a Reactor Regulating System (RRS) but the power distribution is controlled manually by operators. Therefore, for APR+ nuclear power plants which is an improved version of APR1400 nuclear reactor, a new concept of a reactor controller is needed to control both the reactor power and power distribution automatically. The model predictive control (MPC) method is applicable to multiple-input multiple-output control, and can be applied for complex and nonlinear systems, such as the nuclear power plants. In this study, an MPC controller was developed by applying a genetic algorithm to optimize the discrete control rod speeds and by reflecting the realistic movement of the control rod drive mechanism that moves at only five discrete speeds. The performance of the proposed controller was confirmed to be satisfactory by simulating the load-following operation of an APR+ nuclear power plant through interface with KISPAC-1D code
Weak form of Stokes-Dirac structures and geometric discretization of port-Hamiltonian systems
Kotyczka, Paul; Maschke, Bernhard; Lefèvre, Laurent
2018-05-01
We present the mixed Galerkin discretization of distributed parameter port-Hamiltonian systems. On the prototypical example of hyperbolic systems of two conservation laws in arbitrary spatial dimension, we derive the main contributions: (i) A weak formulation of the underlying geometric (Stokes-Dirac) structure with a segmented boundary according to the causality of the boundary ports. (ii) The geometric approximation of the Stokes-Dirac structure by a finite-dimensional Dirac structure is realized using a mixed Galerkin approach and power-preserving linear maps, which define minimal discrete power variables. (iii) With a consistent approximation of the Hamiltonian, we obtain finite-dimensional port-Hamiltonian state space models. By the degrees of freedom in the power-preserving maps, the resulting family of structure-preserving schemes allows for trade-offs between centered approximations and upwinding. We illustrate the method on the example of Whitney finite elements on a 2D simplicial triangulation and compare the eigenvalue approximation in 1D with a related approach.
Alberto Pascual-García
2009-03-01
Full Text Available Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications
Sørensen, Søren N.; Stolpe, Mathias
2015-01-01
rate. The capabilities of the method and the effect of active versus inactive manufacturing constraints are demonstrated on several numerical examples of limited size, involving at most 320 binary variables. Most examples are solved to guaranteed global optimality and may constitute benchmark examples...... but is, however, convex in the original mixed binary nested form. Convexity is the foremost important property of optimization problems, and the proposed method can guarantee the global or near-global optimal solution; unlike most topology optimization methods. The material selection is limited...... for popular topology optimization methods and heuristics based on solving sequences of non-convex problems. The results will among others demonstrate that the difficulty of the posed problem is highly dependent upon the composition of the constitutive properties of the material candidates....
Simultaneous topology optimization of structures and supports
Buhl, Thomas
2002-01-01
supported areas. The method is applied to compliance minimization and mechanism design. In the case of mechanism design, the large displacements of the mechanism are modelled using geometrically nonlinear FE-analysis. Examples with minimization of the compliance demonstrate the effects of using variable......The purpose of this paper is to demonstrate a method for and the benefits of simultaneously designing structure and support distribution using topology optimization. The support conditions are included in the topology optimization by introducing, a new set of design variables that represents...... cost of supports in a design domain. Other examples show that more efficient mechanisms are obtained by introducing the support conditions in the topology optimization problem....
Furihata, Daisuke
2010-01-01
Nonlinear Partial Differential Equations (PDEs) have become increasingly important in the description of physical phenomena. Unlike Ordinary Differential Equations, PDEs can be used to effectively model multidimensional systems. The methods put forward in Discrete Variational Derivative Method concentrate on a new class of ""structure-preserving numerical equations"" which improves the qualitative behaviour of the PDE solutions and allows for stable computing. The authors have also taken care to present their methods in an accessible manner, which means that the book will be useful to engineer
Optimal Structural Reliability of Offshore Wind Turbines
Sørensen, John Dalsgaard; Tarp-Johansen, N.J.
2005-01-01
The main failure modes of modern large wind turbines are fatigue failure of wings, hub, shaft and main tower, local buckling of main tower, and failure of the foundation. This paper considers reliability-based optimal design of wind turbines. Compared to onshore wind turbines and building...... structures, humans spent little time in the vicinity of offshore wind turbines and the probability of human injury during storm conditions is small. Further environmental pollution will also in general be small in case of failure. One could therefore argue that the reliability level of offshore wind turbines...... can be lower than for onshore wind turbines and other civil engineering structures and can be assessed by reliability-based cost-optimization. Specifically this paper considers the main tower and foundation. Both fatigue and ultimate strength failure modes are included. Different formulations...
Discrete Teaching-learning-based optimization Algorithm for Traveling Salesman Problems
Wu Lehui
2017-01-01
Full Text Available In this paper, a discrete variant of TLBO (DTLBO is proposed for solving the traveling salesman problem (TSP. In the proposed method, an effective learner representation scheme is redefined based on the characteristics of TSP problem. Moreover, all learners are randomly divided into several sub-swarms with equal amounts of learners so as to increase the diversity of population and reduce the probability of being trapped in local optimum. In each sub-swarm, the new positions of learners in the teaching phase and the learning phase are generated by the crossover operation, the legality detection and mutation operation, and then the offspring learners are determined based on greedy selection. Finally, to verify the performance of the proposed algorithm, benchmark TSP problems are examined and the results indicate that DTLBO is effective compared with other algorithms used for TSP problems.
Optimal resonant control of flexible structures
Krenk, Steen; Høgsberg, Jan Becker
2009-01-01
When introducing a resonant controller for a particular vibration mode in a structure this mode splits into two. A design principle is developed for resonant control based oil equal damping of these two modes. First the design principle is developed for control of a system with a single degree...... of freedom, and then it is extended to multi-mode structures. A root locus analysis of the controlled single-mode structure identifies the equal modal damping property as a condition oil the linear and Cubic terms of the characteristic equation. Particular solutions for filtered displacement feedback...... and filtered acceleration feedback are developed by combining the root locus analysis with optimal properties of the displacement amplification frequency curve. The results are then extended to multi-mode structures by including a quasi-static representation of the background modes in the equations...
Song Huang
2016-01-01
Full Text Available The fuzzy processing time occasionally exists in job shop scheduling problem of flexible manufacturing system. To deal with fuzzy processing time, fuzzy flexible job shop model was established in several papers and has attracted numerous researchers’ attention recently. In our research, an improved version of discrete particle swarm optimization (IDPSO is designed to solve flexible job shop scheduling problem with fuzzy processing time (FJSPF. In IDPSO, heuristic initial methods based on triangular fuzzy number are developed, and a combination of six initial methods is applied to initialize machine assignment and random method is used to initialize operation sequence. Then, some simple and effective discrete operators are employed to update particle’s position and generate new particles. In order to guide the particles effectively, we extend global best position to a set with several global best positions. Finally, experiments are designed to investigate the impact of four parameters in IDPSO by Taguchi method, and IDPSO is tested on five instances and compared with some state-of-the-art algorithms. The experimental results show that the proposed algorithm can obtain better solutions for FJSPF and is more competitive than the compared algorithms.
A conceptual modeling framework for discrete event simulation using hierarchical control structures
Furian, N.; O’Sullivan, M.; Walker, C.; Vössner, S.; Neubacher, D.
2015-01-01
Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM’s applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models’ system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example. PMID:26778940
A conceptual modeling framework for discrete event simulation using hierarchical control structures.
Furian, N; O'Sullivan, M; Walker, C; Vössner, S; Neubacher, D
2015-08-01
Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM's applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models' system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example.
Optimization and anti-optimization of structures under uncertainty
Elishakoff, Isaac; Ohsaki, Makoto
2010-01-01
.... The necessity of anti-optimization approach is first demonstrated, then the anti-optimization techniques are applied to static, dynamic and buckling problems, thus covering the broadest possible set of applications...
Guo, H. Y.; Li, Y. Q.; Wu, K.; Wang, S. K.
2001-01-01
We study the difference discrete variational principle in the framework of multi-parameter differential approach by regarding the forward difference as an entire geometric object in view of noncomutative differential geometry. By virtue of this variational principle, we get the difference discrete Euler-Lagrange equations and canonical ones for the difference discrete versions of the classical mechanics and classical field theory. We also explore the difference discrete versions for the Euler...
Performance-based shape optimization of continuum structures
Liang Qingquan
2010-01-01
This paper presents a performance-based optimization (PBO) method for optimal shape design of continuum structures with stiffness constraints. Performance-based design concepts are incorporated in the shape optimization theory to achieve optimal designs. In the PBO method, the traditional shape optimization problem of minimizing the weight of a continuum structure with displacement or mean compliance constraints is transformed to the problem of maximizing the performance of the structure. The optimal shape of a continuum structure is obtained by gradually eliminating inefficient finite elements from the structure until its performance is maximized. Performance indices are employed to monitor the performance of optimized shapes in an optimization process. Performance-based optimality criteria are incorporated in the PBO method to identify the optimum from the optimization process. The PBO method is used to produce optimal shapes of plane stress continuum structures and plates in bending. Benchmark numerical results are provided to demonstrate the effectiveness of the PBO method for generating the maximum stiffness shape design of continuum structures. It is shown that the PBO method developed overcomes the limitations of traditional shape optimization methods in optimal design of continuum structures. Performance-based optimality criteria presented can be incorporated in any shape and topology optimization methods to obtain optimal designs of continuum structures.
Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints
Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.
2018-01-01
Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.
Guo, Song; Liu, Chunhua; Zhou, Peng; Li, Yanling
2016-01-01
Tyrosine sulfation is one of the ubiquitous protein posttranslational modifications, where some sulfate groups are added to the tyrosine residues. It plays significant roles in various physiological processes in eukaryotic cells. To explore the molecular mechanism of tyrosine sulfation, one of the prerequisites is to correctly identify possible protein tyrosine sulfation residues. In this paper, a novel method was presented to predict protein tyrosine sulfation residues from primary sequences. By means of informative feature construction and elaborate feature selection and parameter optimization scheme, the proposed predictor achieved promising results and outperformed many other state-of-the-art predictors. Using the optimal features subset, the proposed method achieved mean MCC of 94.41% on the benchmark dataset, and a MCC of 90.09% on the independent dataset. The experimental performance indicated that our new proposed method could be effective in identifying the important protein posttranslational modifications and the feature selection scheme would be powerful in protein functional residues prediction research fields.
Bai, Yunru; Baleanu, Dumitru; Wu, Guo-Cheng
2018-06-01
We investigate a class of generalized differential optimization problems driven by the Caputo derivative. Existence of weak Carathe ´odory solution is proved by using Weierstrass existence theorem, fixed point theorem and Filippov implicit function lemma etc. Then a numerical approximation algorithm is introduced, and a convergence theorem is established. Finally, a nonlinear programming problem constrained by the fractional differential equation is illustrated and the results verify the validity of the algorithm.
ON DISCRETE STRUCTURE OF GEOLOGIC MEDIUM AND CONTINUAL APPROACH TO MODELING ITS MOVEMENTS
Sh. A. Mukhamediev
2016-01-01
Full Text Available This paper discusses the structure of a geologic medium represented by accessible lithified rocks and provides an overview of methods used to describe its movements. Two basic opinions are considered in the framework of the discussion: (1 an initially homogeneous and continuous geologic medium acquires the structure composed of blocks in the process of the geologic medium’s deformation/destruction/degradation, and (2 a geologic medium is composed of blocks (and often has hierarchic, active, energy-saturated features, and the continuity model is thus not valid for describing the geologic medium’s deformation. Proponents of the first point of view actively apply the standard or modified continuum model of a solid deformed body (SDB in estimations of the stress-strain state, but the input parameters of this model do not contain any information on discreteness in principle. Authors who support the second opinion, either explicitly or implicitly assume that the block structure of the geologic medium, which is detectable by geological methods, makes a direct and unambiguous impact on all other mechanical properties of the geologic medium and, above all, on the nature of its movements.Based on results obtained by interpreting the data collected in our long-term field studies of rock fracturing, mathematical processing of GPS-measurements, and theoretical models, we agree with the concept of the geologic medium’s block structure, but argue that the geologic block-structure property is not acquired but congenital. Regarding sedimentary rocks, it means that the discrete structure has been already embodied in the rock before sediment lithification, regardless of the intensity of macroscopic deformations. A discrete structure is the form of the geologic medium existence and a cause of the congenital anisotropy of the geologic medium’s strength characteristics. Due to subsequent deformation of the geologic medium, some elements of the structure can
A simple boundary element formulation for shape optimization of 2D continuous structures
Luciano Mendes Bezerra; Jarbas de Carvalho Santos Junior; Arlindo Pires Lopes; Andre Luiz; Souza, A.C.
2005-01-01
For the design of nuclear equipment like pressure vessels, steam generators, and pipelines, among others, it is very important to optimize the shape of the structural systems to withstand prescribed loads such as internal pressures and prescribed or limiting referential values such as stress or strain. In the literature, shape optimization of frame structural systems is commonly found but the same is not true for continuous structural systems. In this work, the Boundary Element Method (BEM) is applied to simple problems of shape optimization of 2D continuous structural systems. The proposed formulation is based on the BEM and on deterministic optimization methods of zero and first order such as Powell's, Conjugate Gradient, and BFGS methods. Optimal characterization for the geometric configuration of 2D structure is obtained with the minimization of an objective function. Such function is written in terms of referential values (such as loads, stresses, strains or deformations) prescribed at few points inside or at the boundary of the structure. The use of the BEM for shape optimization of continuous structures is attractive compared to other methods that discretized the whole continuous. Several numerical examples of the application of the proposed formulation to simple engineering problems are presented. (authors)
Sørensen, Rene; Lund, Erik
2015-01-01
This paper presents a new gradient based method for performing discrete material and thickness optimization of laminated composite structures. The novelty in the new method lies in the application of so-called casting constraints, or thickness filters in this context, to control the thickness...... variation throughout the laminate. The filters replace the layerwise density variables with a single continuous through-the-thickness design variable. Consequently, the filters eliminate the need for having explicit constraints for preventing intermediate void through the thickness of the laminate....... Therefore, the filters reduce both the number of constraints and design variables in the optimization problem. Based upon a continuous approximation of a unit step function, the thickness filters are capable of projecting discrete 0/1 values to the underlying layerwise or ”physical” density variables which...
Optimal community structure for social contagions
Su, Zhen; Wang, Wei; Li, Lixiang; Stanley, H. Eugene; Braunstein, Lidia A.
2018-05-01
Community structure is an important factor in the behavior of real-world networks because it strongly affects the stability and thus the phase transition order of the spreading dynamics. We here propose a reversible social contagion model of community networks that includes the factor of social reinforcement. In our model an individual adopts a social contagion when the number of received units of information exceeds its adoption threshold. We use mean-field approximation to describe our proposed model, and the results agree with numerical simulations. The numerical simulations and theoretical analyses both indicate that there is a first-order phase transition in the spreading dynamics, and that a hysteresis loop emerges in the system when there is a variety of initially adopted seeds. We find an optimal community structure that maximizes spreading dynamics. We also find a rich phase diagram with a triple point that separates the no-diffusion phase from the two diffusion phases.
Optimal State Estimation for Discrete-Time Markov Jump Systems with Missing Observations
Qing Sun
2014-01-01
Full Text Available This paper is concerned with the optimal linear estimation for a class of direct-time Markov jump systems with missing observations. An observer-based approach of fault detection and isolation (FDI is investigated as a detection mechanic of fault case. For systems with known information, a conditional prediction of observations is applied and fault observations are replaced and isolated; then, an FDI linear minimum mean square error estimation (LMMSE can be developed by comprehensive utilizing of the correct information offered by systems. A recursive equation of filtering based on the geometric arguments can be obtained. Meanwhile, a stability of the state estimator will be guaranteed under appropriate assumption.
IMA’s 2014-2015 Annual Thematic Program on Discrete Structures: Analysis and Applications
Madiman, Mokshay; Werner, Elisabeth
2017-01-01
This volume presents some of the research topics discussed at the 2014-2015 Annual Thematic Program Discrete Structures: Analysis and Applications at the Institute of Mathematics and its Applications during the Spring 2015 where geometric analysis, convex geometry and concentration phenomena were the focus. Leading experts have written surveys of research problems, making state of the art results more conveniently and widely available. The volume is organized into two parts. Part I contains those contributions that focus primarily on problems motivated by probability theory, while Part II contains those contributions that focus primarily on problems motivated by convex geometry and geometric analysis. This book will be of use to those who research convex geometry, geometric analysis and probability directly or apply such methods in other fields.
A Heuristic Design Information Sharing Framework for Hard Discrete Optimization Problems
Jacobson, Sheldon H
2007-01-01
.... This framework has been used to gain new insights into neighborhood structure designs that allow different neighborhood functions to share information when using the same heuristic applied to the same problem...
Estimations of impact strength on reinforced concrete structures by the discrete element method
Morikawa, H.; Kusano, N.; Koshika, N.; Aoyagi, T.; Hagiwara, Y.; Sawamoto, Y.
1993-01-01
There has been a rising interest in the response of reinforced concrete structures to impact loading, from the point of view in particular of disaster prevention at nuclear power facilities, and there is an urgent requirement for establishment of design methods against such type of loads. Structural damage on reinforced concrete structures under impact load includes local damage and global damage. The behavior of local damage, such as penetration into the structures, rear face scabbing, perforation, or spalling, has been difficult to estimate by numerical analysis, but over recent years research has advantaged and various analytical methods have been tried. The authors proposed a new approach for assessing local damage characteristics by applying the discrete element method (DEM), and verified that the behavior of a concrete slab suffering local damage may be qualitatively expressed. This was followed by the discussion of the quantitative evaluation of various constants used in the DEM analysis in reference. The authors apply the DEM to the simulation analysis of impact tests on reinforced concrete panels and analytical investigations are made on the local damage characteristics and response values that are difficult to assess through tests, in an attempt to evaluate the mechanism of local damage according to the hardness of the missiles
Advances in metaheuristic algorithms for optimal design of structures
Kaveh, A
2017-01-01
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...
Advances in metaheuristic algorithms for optimal design of structures
Kaveh, A
2014-01-01
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...
Chowdhury, Md Mukul
With the increased practice of modularization and prefabrication, the construction industry gained the benefits of quality management, improved completion time, reduced site disruption and vehicular traffic, and improved overall safety and security. Whereas industrialized construction methods, such as modular and manufactured buildings, have evolved over decades, core techniques used in prefabrication plants vary only slightly from those employed in traditional site-built construction. With a focus on energy and cost efficient modular construction, this research presents the development of a simulation, measurement and optimization system for energy consumption in the manufacturing process of modular construction. The system is based on Lean Six Sigma principles and loosely coupled system operation to identify the non-value adding tasks and possible causes of low energy efficiency. The proposed system will also include visualization functions for demonstration of energy consumption in modular construction. The benefits of implementing this system include a reduction in the energy consumption in production cost, decrease of energy cost in the production of lean-modular construction, and increase profit. In addition, the visualization functions will provide detailed information about energy efficiency and operation flexibility in modular construction. A case study is presented to validate the reliability of the system.
Stolpe, Mathias; Stidsen, Thomas K.
2007-01-01
In this paper, we present a hierarchical optimization method for finding feasible true 0-1 solutions to finite-element-based topology design problems. The topology design problems are initially modelled as non-convex mixed 0-1 programs. The hierarchical optimization method is applied to the problem...... and then successively refined as needed. At each level of design mesh refinement, a neighbourhood optimization method is used to treat the problem considered. The non-convex topology design problems are equivalently reformulated as convex all-quadratic mixed 0-1 programs. This reformulation enables the use of methods...... of minimizing the weight of a structure subject to displacement and local design-dependent stress constraints. The method iteratively treats a sequence of problems of increasing size of the same type as the original problem. The problems are defined on a design mesh which is initially coarse...
Topological Optimization of Continuum Structure based on ANSYS
Li Xue-ping
2017-01-01
Full Text Available Topology optimization is at the phase of structural concept design and the result of it is foundation for succeeding design, therefore, structural topology optimization is more important to engineering design. in this thesis, in order to seek the optimal structure shape of the winch’s mounting bracket of ROV simulator, topology optimization design of it by finite element analysis software ANSYS was carried out. the results show that the topology optimization method is an effective optimization method and indicate that the method is correct and effective, it has a certain engineering application prospect.
Le Dez, V; Lallemand, M [Ecole Nationale Superieure de Mecanique et d` Aerotechnique (ENSMA), 86 - Poitiers (France); Sakami, M; Charette, A [Quebec Univ., Chicoutimi, PQ (Canada). Dept. des Sciences Appliquees
1997-12-31
The description of an efficient method of radiant heat transfer field determination in a grey semi-transparent environment included in a 2-D polygonal cavity with surface boundaries that reflect the radiation in a purely diffusive manner is proposed, at the equilibrium and in radiation-conduction coupling situation. The technique uses simultaneously the finite-volume method in non-structured triangular mesh, the discrete ordinate method and the ray shooting method. The main mathematical developments and comparative results with the discrete ordinate method in orthogonal curvilinear coordinates are included. (J.S.) 10 refs.
Le Dez, V.; Lallemand, M. [Ecole Nationale Superieure de Mecanique et d`Aerotechnique (ENSMA), 86 - Poitiers (France); Sakami, M.; Charette, A. [Quebec Univ., Chicoutimi, PQ (Canada). Dept. des Sciences Appliquees
1996-12-31
The description of an efficient method of radiant heat transfer field determination in a grey semi-transparent environment included in a 2-D polygonal cavity with surface boundaries that reflect the radiation in a purely diffusive manner is proposed, at the equilibrium and in radiation-conduction coupling situation. The technique uses simultaneously the finite-volume method in non-structured triangular mesh, the discrete ordinate method and the ray shooting method. The main mathematical developments and comparative results with the discrete ordinate method in orthogonal curvilinear coordinates are included. (J.S.) 10 refs.
Optimal Stochastic Modeling and Control of Flexible Structures
1988-09-01
1.37] and McLane [1.18] considered multivariable systems and derived their optimal control characteristics. Kleinman, Gorman and Zaborsky considered...Leondes [1.72,1.73] studied various aspects of multivariable linear stochastic, discrete-time systems that are partly deterministic, and partly stochastic...June 1966. 1.8. A.V. Balaknishnan, Applied Functional Analaysis , 2nd ed., New York, N.Y.: Springer-Verlag, 1981 1.9. Peter S. Maybeck, Stochastic
Control of discrete-event systems with modular or distributed structure
Komenda, Jan; van Schuppen, J. H.
2007-01-01
Roč. 388, č. 3 (2007), s. 199-226 ISSN 0304-3975 R&D Projects: GA AV ČR(CZ) KJB100190609 Institutional research plan: CEZ:AV0Z10190503 Keywords : supervisory control * modular discrete-event system * distributed discrete-event system Subject RIV: BA - General Mathematics Impact factor: 0.735, year: 2007
Marchiolli, M.A.; Ruzzi, M.
2012-01-01
We propose a self-consistent theoretical framework for a wide class of physical systems characterized by a finite space of states which allows us, within several mathematical virtues, to construct a discrete version of the Weyl–Wigner–Moyal (WWM) formalism for finite-dimensional discrete phase spaces with toroidal topology. As a first and important application from this ab initio approach, we initially investigate the Robertson–Schrödinger (RS) uncertainty principle related to the discrete coordinate and momentum operators, as well as its implications for physical systems with periodic boundary conditions. The second interesting application is associated with a particular uncertainty principle inherent to the unitary operators, which is based on the Wiener–Khinchin theorem for signal processing. Furthermore, we also establish a modified discrete version for the well-known Heisenberg–Kennard–Robertson (HKR) uncertainty principle, which exhibits additional terms (or corrections) that resemble the generalized uncertainty principle (GUP) into the context of quantum gravity. The results obtained from this new algebraic approach touch on some fundamental questions inherent to quantum mechanics and certainly represent an object of future investigations in physics. - Highlights: ► We construct a discrete version of the Weyl–Wigner–Moyal formalism. ► Coherent states for finite-dimensional discrete phase spaces are established. ► Discrete coordinate and momentum operators are properly defined. ► Uncertainty principles depend on the topology of finite physical systems. ► Corrections for the discrete Heisenberg uncertainty relation are also obtained.
Liu, Tun-Dong; Fan, Tian-E [Center for Cloud Computing and Big Data, Department of Automation, Xiamen University, Xiamen 361005 (China); Shao, Gui-Fang, E-mail: gfshao@xmu.edu.cn [Center for Cloud Computing and Big Data, Department of Automation, Xiamen University, Xiamen 361005 (China); Zheng, Ji-Wen [Center for Cloud Computing and Big Data, Department of Automation, Xiamen University, Xiamen 361005 (China); Wen, Yu-Hua [Institute of Theoretical Physics and Astrophysics, Department of Physics, Xiamen University, Xiamen 361005 (China)
2014-08-14
Bimetallic nanoparticles, enclosed by high-index facets, have great catalytic activity and selectivity owing to the synergy effects of high-index facets and the electronic structures of alloy. In this paper, a discrete particle swarm optimization algorithm was employed to systematically investigate the structural stability and features of tetrahexahedral Pt-based bimetallic nanoparticles with high-index facets. Different Pt/Ag, Pt/Cu, Pt/Pd atom ratios and particle sizes were considered in this work. The simulation results reveal that these alloy nanoparticles exhibit considerably different structural characteristics. Pt–Ag nanoparticles tend to form Pt–Ag core–shell structure. Pt–Cu nanoparticles are preferred to take multi-shell structure with Cu on the outer surface while Pt–Pd nanoparticles present a mixing structure in the interior and Pd-dominated surface. Atomic distribution and bonding characteristics were applied to further characterize the structural features of Pt-based nanoparticles. This study provides an important insight into the structural stability and features of Pt-based nanoparticles with different alloys. - Highlights: • We explore the structural stability of Pt-based alloy NPs by a discrete PSO. • Our study discovers the different structural characteristics for Pt-based NPs. • Alloy composition and size have important effects on the surface segregation. • Our work shows strong phase separation for Pt–Ag NPs while weak for Pt–Pd NPs.
Liu, Tun-Dong; Fan, Tian-E; Shao, Gui-Fang; Zheng, Ji-Wen; Wen, Yu-Hua
2014-01-01
Bimetallic nanoparticles, enclosed by high-index facets, have great catalytic activity and selectivity owing to the synergy effects of high-index facets and the electronic structures of alloy. In this paper, a discrete particle swarm optimization algorithm was employed to systematically investigate the structural stability and features of tetrahexahedral Pt-based bimetallic nanoparticles with high-index facets. Different Pt/Ag, Pt/Cu, Pt/Pd atom ratios and particle sizes were considered in this work. The simulation results reveal that these alloy nanoparticles exhibit considerably different structural characteristics. Pt–Ag nanoparticles tend to form Pt–Ag core–shell structure. Pt–Cu nanoparticles are preferred to take multi-shell structure with Cu on the outer surface while Pt–Pd nanoparticles present a mixing structure in the interior and Pd-dominated surface. Atomic distribution and bonding characteristics were applied to further characterize the structural features of Pt-based nanoparticles. This study provides an important insight into the structural stability and features of Pt-based nanoparticles with different alloys. - Highlights: • We explore the structural stability of Pt-based alloy NPs by a discrete PSO. • Our study discovers the different structural characteristics for Pt-based NPs. • Alloy composition and size have important effects on the surface segregation. • Our work shows strong phase separation for Pt–Ag NPs while weak for Pt–Pd NPs
Min Jin
2014-01-01
Full Text Available There is recently a great deal of interest and excitement in understanding the role of inertia and acceleration in the motion equation of discrete particle swarm optimization (DPSO algorithms. It still remains unknown whether the inertia section should be abandoned and how to select the appropriate acceleration in order for DPSO to show the best convergence performance. Adopting channel assignment as a case study, this paper systematically conducts experimental filtering research on this issue. Compared with other channel assignment schemes, the proposed scheme and the selection of inertia and acceleration are verified to have the advantage to channel assignment in three respects of convergence rate, convergence speed, and the independency of the quality of initial solution. Furthermore, the experimental result implies that DSPO might have the best convergence performance when its motion equation includes an inertia section in a less medium weight, a bigger acceleration coefficient for global-search optimum, and a smaller acceleration coefficient for individual-search optimum.
Rousseau, J.
2009-07-01
That study focuses on concrete structures submitted to impact loading and is aimed at predicting local damage in the vicinity of an impact zone as well as the global response of the structure. The Discrete Element Method (DEM) seems particularly well suited in this context for modeling fractures. An identification process of DEM material parameters from macroscopic data (Young's modulus, compressive and tensile strength, fracture energy, etc.) will first be presented for the purpose of enhancing reproducibility and reliability of the simulation results with DE samples of various sizes. Then, a particular interaction, between concrete and steel elements, was developed for the simulation of reinforced concrete. The discrete elements method was validated on quasi-static and dynamic tests carried out on small samples of concrete and reinforced concrete. Finally, discrete elements were used to simulate impacts on reinforced concrete slabs in order to confront the results with experimental tests. The modeling of a large structure by means of DEM may lead to prohibitive computation times. A refined discretization becomes required in the vicinity of the impact, while the structure may be modeled using a coarse FE mesh further from the impact area, where the material behaves elastically. A coupled discrete-finite element approach is thus proposed: the impact zone is modeled by means of DE and elastic FE are used on the rest of the structure. An existing method for 3D finite elements was extended to shells. This new method was then validated on many quasi-static and dynamic tests. The proposed approach is then applied to an impact on a concrete structure in order to validate the coupled method and compare computation times. (author)
Optimization of Structural Topology in the High-Porosity Regime
Kohn, Robert
2004-01-01
...." Moreover there is a simple formula for the Hooke's law of a single-scale laminate. It reduces the task of structural optimization for minimum weight and maximal stiffness to a convex optimization specifically, a problem of semidefinite programming...
Topology optimization of fluid-structure-interaction problems in poroelasticity
Andreasen, Casper Schousboe; Sigmund, Ole
2013-01-01
This paper presents a method for applying topology optimization to fluid-structure interaction problems in saturated poroelastic media. The method relies on a multiple-scale method applied to periodic media. The resulting model couples the Stokes flow in the pores of the structure with the deform...... by topology optimization in order to optimize the performance of a shock absorber and test the pressure loading capabilities and optimization of an internally pressurized lid. © 2013 Published by Elsevier B.V....
Persistence versus extinction for a class of discrete-time structured population models.
Jin, Wen; Smith, Hal L; Thieme, Horst R
2016-03-01
We provide sharp conditions distinguishing persistence and extinction for a class of discrete-time dynamical systems on the positive cone of an ordered Banach space generated by a map which is the sum of a positive linear contraction A and a nonlinear perturbation G that is compact and differentiable at zero in the direction of the cone. Such maps arise as year-to-year projections of population age, stage, or size-structure distributions in population biology where typically A has to do with survival and individual development and G captures the effects of reproduction. The threshold distinguishing persistence and extinction is the principal eigenvalue of (II−A)(−1)G'(0) provided by the Krein-Rutman Theorem, and persistence is described in terms of associated eigenfunctionals. Our results significantly extend earlier persistence results of the last two authors which required more restrictive conditions on G. They are illustrated by application of the results to a plant model with a seed bank.
Generation of fractional acoustic vortex with a discrete Archimedean spiral structure plate
Jia, Yu-Rou; Wei, Qi; Wu, Da-Jian; Xu, Zheng; Liu, Xiao-Jun
2018-04-01
Artificial structure plates engraved with discrete Archimedean spiral slits have been well designed to achieve fractional acoustic vortices (FAVs). The phase and pressure field distributions of FAVs are investigated theoretically and demonstrated numerically. It is found that the phase singularities relating to the integer and fractional parts of the topological charge (TC) result in dark spots in the upper half of the pressure field profile and a low-intensity stripe in the lower half of the pressure field profile, respectively. The dynamic progress of the FAV is also discussed in detail as TC increases from 1 to 2. With increasing TC from 1 to 1.5, the splitting of the phase singularity leads to the deviation of the phase of the FAV from the integer case and hence a new phase singularity occurs. As TC m increases from 1.5 to 2, two phase singularities of the FAV approach together and finally merge as a new central phase singularity. We further perform an experiment based on the Schlieren method to demonstrate the generation of the FAV.
Rigid missiles impact on reinforced concrete structures: analysis by discrete element method
Shiu, W.J.
2008-10-01
The constructions likely to be subjected to some extreme loadings like reactor containment buildings have to be dimensioned accordingly. As a part of study of concrete structures, this thesis focuses on numerical modelling of rigid missile impacts against a rigid reinforced concrete slab. Based on some experiment tests data, an elasto-plastic-damaged constitutive law has been implanted into a discrete element numerical code. To calibrate certain parameters of the numerical model, some quasi static tests have been first simulated. Once the model calibration was done, some missile impact simulation tests have then been carried out. The numerical results are well agree with these provided by French Atomic Energy Agency (Cea) and the French Electrical power Company (EDF) in terms of the trajectory of the missile. We were able to show the need of a constitutive law taking into account the compaction behaviour of the concrete when the predictions of penetration and perforation of a thick slab was demanded. Finally, a parametric study confirmed that the numerical model can be used the way predictive as well as the empirical prediction law, while the first can provide additional significant mechanical description. (author)
Structural Optimization of non-Newtonian Microfluidics
Jensen, Kristian Ejlebjærg; Okkels, Fridolin
2011-01-01
We present results for topology optimization of a non-Newtonian rectifier described with a differential constitutive model. The results are novel in the sense that a differential constitutive model has not been combined with topology optimization previously. We find that it is necessary to apply...... optimization of fluids. We test the method on a microfluidic rectifier and find solutions topologically different from experimentally realized designs....
Integrated topology and shape optimization in structural design
Bremicker, M.; Chirehdast, M.; Kikuchi, N.; Papalambros, P. Y.
1990-01-01
Structural optimization procedures usually start from a given design topology and vary its proportions or boundary shapes to achieve optimality under various constraints. Two different categories of structural optimization are distinguished in the literature, namely sizing and shape optimization. A major restriction in both cases is that the design topology is considered fixed and given. Questions concerning the general layout of a design (such as whether a truss or a solid structure should be used) as well as more detailed topology features (e.g., the number and connectivities of bars in a truss or the number of holes in a solid) have to be resolved by design experience before formulating the structural optimization model. Design quality of an optimized structure still depends strongly on engineering intuition. This article presents a novel approach for initiating formal structural optimization at an earlier stage, where the design topology is rigorously generated in addition to selecting shape and size dimensions. A three-phase design process is discussed: an optimal initial topology is created by a homogenization method as a gray level image, which is then transformed to a realizable design using computer vision techniques; this design is then parameterized and treated in detail by sizing and shape optimization. A fully automated process is described for trusses. Optimization of two dimensional solid structures is also discussed. Several application-oriented examples illustrate the usefulness of the proposed methodology.
Global stability-based design optimization of truss structures using ...
Furthermore, a pure pareto-ranking based multi-objective optimization model is employed for the design optimization of the truss structure with multiple objectives. The computational performance of the optimization model is increased by implementing an island model into its evolutionary search mechanism. The proposed ...
Optimization and anti-optimization of structures under uncertainty
Elishakoff, Isaac; Ohsaki, Makoto
2010-01-01
..., architecture, civil, mechanical or ocean engineering, invariably adopt the either/or style. Namely, they devote themselves either to linear or to nonlinear analysis of the structure they are dealing with, they are engaged in analyzing it either in the elastic or in the inelastic range; they deal either with its static or with its dynamic behavior. Al...
Mathematical modeling and optimization of complex structures
Repin, Sergey; Tuovinen, Tero
2016-01-01
This volume contains selected papers in three closely related areas: mathematical modeling in mechanics, numerical analysis, and optimization methods. The papers are based upon talks presented on the International Conference for Mathematical Modeling and Optimization in Mechanics, held in Jyväskylä, Finland, March 6-7, 2014 dedicated to Prof. N. Banichuk on the occasion of his 70th birthday. The articles are written by well-known scientists working in computational mechanics and in optimization of complicated technical models. Also, the volume contains papers discussing the historical development, the state of the art, new ideas, and open problems arising in modern continuum mechanics and applied optimization problems. Several papers are concerned with mathematical problems in numerical analysis, which are also closely related to important mechanical models. The main topics treated include: * Computer simulation methods in mechanics, physics, and biology; * Variational problems and methods; minimiz...
Structural optimization of reinforced concrete container for radioactive wastes
Tamura, M.
1984-01-01
A structural optimization study of reinforced concrete container for transportation and disposal of the low level radioactive waste generated in Brazilian nuclear power plants. The code requires the structural integrity of these containers when subjected to fall from specified height, avoiding environmental contamination. The structural optimization allows material and transportation cost reduction by container wall thickness reduction. The structural analysis is performed by tridimensional mathematical model using finite element method. (Author) [pt
Kamihigashi, Takashi
2017-01-01
Given a sequence [Formula: see text] of measurable functions on a σ -finite measure space such that the integral of each [Formula: see text] as well as that of [Formula: see text] exists in [Formula: see text], we provide a sufficient condition for the following inequality to hold: [Formula: see text] Our condition is considerably weaker than sufficient conditions known in the literature such as uniform integrability (in the case of a finite measure) and equi-integrability. As an application, we obtain a new result on the existence of an optimal path for deterministic infinite-horizon optimization problems in discrete time.
An analytical method for optimal design of MR valve structures
Nguyen, Q H; Choi, S B; Lee, Y S; Han, M S
2009-01-01
This paper proposes an analytical methodology for the optimal design of a magnetorheological (MR) valve structure. The MR valve structure is constrained in a specific volume and the optimization problem identifies geometric dimensions of the valve structure that maximize the yield stress pressure drop of a MR valve or the yield stress damping force of a MR damper. In this paper, the single-coil and two-coil annular MR valve structures are considered. After describing the schematic configuration and operating principle of a typical MR valve and damper, a quasi-static model is derived based on the Bingham model of a MR fluid. The magnetic circuit of the valve and damper is then analyzed by applying Kirchoff's law and the magnetic flux conservation rule. Based on quasi-static modeling and magnetic circuit analysis, the optimization problem of the MR valve and damper is built. In order to reduce the computation load, the optimization problem is simplified and a procedure to obtain the optimal solution of the simplified optimization problem is presented. The optimal solution of the simplified optimization problem of the MR valve structure constrained in a specific volume is then obtained and compared with the solution of the original optimization problem and the optimal solution obtained from the finite element method
Filippov, E.S.
1976-01-01
In terms of a theory of liquid metals which is based upon a notion of spheric groups disintegrating according to the melting type a coordination number (K) for 22 metals is calculated from the type of packing in groups (Ksub(T)) and a computed statistical packing (Ksub(s.p.) = 6.5 - 4.5). The diffraction K is presented as a sum of Ksub(T) and Ksub(s.p.) groups. Packing type in Ksub(T) groups is established by experiments on density as a function of temperature, which has revealed the stage (discrete) nature of density changes. The ratio between the temperature of the beginning and termination of a stage is equal to the packing coefficient in a group (0.74; 0,68; 0.50). For densely packed groups at Tsub(m(it is shown that K)sub(l) = 0.74 Ksub(T + 0.26XKsub(s.p.) (if Ksub(T) = 12, Ksub(l) = 10.4). If the number of splitting stages (p) is less than three, then Ksub(l) = 0.74 2 Ksub(T) + 2(1 - 0.74 2 ) Ksub(s.p.) When Ksub(T) = 8 (for alkaline metals and iron), Ksub(l) = 9.5. It has been found for liquid inert groups that Ksub(l) = 8.7. Liquid Sn and Bi prove to be a mixture of densest cubic (d.c.) and volume-centred cubic (v.c.c.) groups. The fractions of each group have been calculated; Bi consists of 30% v.c.c. and 70% d.c., Sn of 54% d.c. and 46% v.c.c. grouops. The diffraction (total) K in liquid metals appears to be a parameter different from K in solid ones, being a function of structural components of the groups and packing of atoms between the groups, rather than a definite characteristic of liquid metals structure
Topology optimization of 3D shell structures with porous infill
Clausen, Anders; Andreassen, Erik; Sigmund, Ole
2017-01-01
This paper presents a 3D topology optimization approach for designing shell structures with a porous or void interior. It is shown that the resulting structures are significantly more robust towards load perturbations than completely solid structures optimized under the same conditions. The study...... indicates that the potential benefit of using porous structures is higher for lower total volume fractions. Compared to earlier work dealing with 2D topology optimization, we found several new effects in 3D problems. Most notably, the opportunity for designing closed shells significantly improves...
Isis Didier Lins
2009-04-01
Full Text Available This paper attempts to provide a more realistic approach to the characterization of system reliability when handling redundancy allocation problems: it considers repairable series-parallel systems comprised of components subjected to corrective maintenance actions with failure-repair cycles modeled by renewal processes. A multiobjective optimization approach is applied since increasing the number of redundancies not only enlarges system reliability but also its associated costs. Then a multiobjective genetic algorithm is coupled with discrete event simulation and its solutions present the compromise between system reliability and cost. Two examples are provided. In the first one, the proposed algorithm is validated by comparison with results obtained from a system devised as to allow for analytical solutions of the objective functions. The second case analyzes a repairable system subjected to perfect repairs. Results from both examples show that the proposed method can be a valuable tool for the decision maker when choosing the system design.Esse artigo utiliza uma abordagem mais realista para a caracterização da confiabilidade de sistemas em problemas de alocação de redundâncias: são considerados sistemas série-paralelo formados por componentes sujeitos a ações de manutenção corretiva com ciclos de falha-reparo modelados por processos de renovação. É aplicada uma abordagem de otimização multiobjetivo, pois o aumento de redundâncias eleva a confiabilidade do sistema e também os seus custos. Assim, um algoritmo genético multiobjetivo é integrado com simulação discreta de eventos e suas soluções apresentam o compromisso entre confiabilidade e custo do sistema. Dois exemplos são fornecidos. No primeiro, o algoritmo proposto é validado através da comparação com resultados obtidos de um sistema criado de forma a permitir soluções analíticas das funções-objetivo. No segundo, analisa-se um sistema reparável sujeito a
The Discreteness of Emotion Concepts: Categorical Structure in the Affective Circumplex.
Haslam, Nick
1995-01-01
Emotion concepts might be represented as distributed around a circumplex defined on bipolar dimensions of pleasure and arousal. Using an analog of categorical perception methodology, this study demonstrated a number of category boundaries that mark out discrete segments of the circumplex. Discriminability of emotion concepts was relatively weak…
Piil, Rune; Moelmer, Klaus
2007-01-01
By adjusting the tunneling couplings over longer than nearest-neighbor distances, it is possible in discrete lattice models to reproduce the properties of the lowest energy band of a real, continuous periodic potential. We propose to include such terms in problems with interacting particles, and we show that they have significant consequences for scattering and bound states of atom pairs in periodic potentials
Financial optimization of investments in maritime structures
Bischoff van Heemskerck, W.C.; Booy, N.
1969-01-01
The designing engineer often comes across the economic decision problem in which the "benefit" of a higher design criterion must be weighed against the "cost". Several methods have been developed to deal with this optimization problem; none of them, however, offer the possibility of introducing the
Optimal structural inference of signaling pathways from unordered and overlapping gene sets.
Acharya, Lipi R; Judeh, Thair; Wang, Guangdi; Zhu, Dongxiao
2012-02-15
A plethora of bioinformatics analysis has led to the discovery of numerous gene sets, which can be interpreted as discrete measurements emitted from latent signaling pathways. Their potential to infer signaling pathway structures, however, has not been sufficiently exploited. Existing methods accommodating discrete data do not explicitly consider signal cascading mechanisms that characterize a signaling pathway. Novel computational methods are thus needed to fully utilize gene sets and broaden the scope from focusing only on pairwise interactions to the more general cascading events in the inference of signaling pathway structures. We propose a gene set based simulated annealing (SA) algorithm for the reconstruction of signaling pathway structures. A signaling pathway structure is a directed graph containing up to a few hundred nodes and many overlapping signal cascades, where each cascade represents a chain of molecular interactions from the cell surface to the nucleus. Gene sets in our context refer to discrete sets of genes participating in signal cascades, the basic building blocks of a signaling pathway, with no prior information about gene orderings in the cascades. From a compendium of gene sets related to a pathway, SA aims to search for signal cascades that characterize the optimal signaling pathway structure. In the search process, the extent of overlap among signal cascades is used to measure the optimality of a structure. Throughout, we treat gene sets as random samples from a first-order Markov chain model. We evaluated the performance of SA in three case studies. In the first study conducted on 83 KEGG pathways, SA demonstrated a significantly better performance than Bayesian network methods. Since both SA and Bayesian network methods accommodate discrete data, use a 'search and score' network learning strategy and output a directed network, they can be compared in terms of performance and computational time. In the second study, we compared SA and
Integrated Reliability-Based Optimal Design of Structures
Sørensen, John Dalsgaard; Thoft-Christensen, Palle
1987-01-01
In conventional optimal design of structural systems the weight or the initial cost of the structure is usually used as objective function. Further, the constraints require that the stresses and/or strains at some critical points have to be less than some given values. Finally, all variables......-based optimal design is discussed. Next, an optimal inspection and repair strategy for existing structural systems is presented. An optimization problem is formulated , where the objective is to minimize the expected total future cost of inspection and repair subject to the constraint that the reliability...... value. The reliability can be measured from an element and/or a systems point of view. A number of methods to solve reliability-based optimization problems has been suggested, see e.g. Frangopol [I]. Murotsu et al. (2], Thoft-Christensen & Sørensen (3] and Sørensen (4). For structures where...
Optimal design of aperiodic, vertical silicon nanowire structures for photovoltaics.
Lin, Chenxi; Povinelli, Michelle L
2011-09-12
We design a partially aperiodic, vertically-aligned silicon nanowire array that maximizes photovoltaic absorption. The optimal structure is obtained using a random walk algorithm with transfer matrix method based electromagnetic forward solver. The optimal, aperiodic structure exhibits a 2.35 times enhancement in ultimate efficiency compared to its periodic counterpart. The spectral behavior mimics that of a periodic array with larger lattice constant. For our system, we find that randomly-selected, aperiodic structures invariably outperform the periodic array.
Structural Optimization of non-Newtonian Microfluidics
Jensen, Kristian Ejlebjærg
2013-01-01
Many of the biological fluids analyzed in Lab-on-a-Chip systems contain elastic components, which gives the fluids elastic character. Such fluids are said to be non-Newtonian or, more precisely, viscoelastic. They can give rise to exotic effects on the macroscale, which are never seen for fluids...... with components relying on viscoelastic effects, but the non-intuitive nature of these fluids complicates the design process. This thesis combines the method of topology optimization with differential constitutive equations, which govern the flow of viscoelastic fluids. The optimization method iteratively...... finite element package. The code is capable of calculating the viscoelastic flow in a benchmark geometry, and we hope that it will help newcomers as well as experienced researchers in the field of differential constitutive equations. v...
Optimal Vibration Control of Civil Engineering Structures
Thesbjerg, Leo
In designing large civil engineering structures, an important consideration is prospective dynamic loadings which may include earthquake ground motion, wind gusts, severe sea states and moving vehicles, rotating and reciprocating machinery and others. successful design of such structures requires...... providing for the safety and integrity of the structure, and in some cases also providing for a measure of comfort for the occupants during such loading which the structure and its occupants must endure. Due to these uncertainties, the civil engineering community has traditionally adopted a very...
Service life optimization and extension of structures
Hornet, P.; Venturini, V.; Persoz, M.; Debost-Eymard, I.; Meister, E.
1998-01-01
In order to justify its power plants safety which conditions their service life, EDF uses a deterministic approach until now. A probabilistic approach also exists which has a decisive advantage because it quantifies risk and makes it possible to optimize maintenance volume. The application of this approach is illustrated on the case of a reactor vessel; a coupling between the Code Aster tool and a probabilistic analysis software is necessary. (authors)
Topology optimization for acoustic-structure interaction problems
Yoon, Gil Ho; Jensen, Jakob Søndergaard; Sigmund, Ole
2006-01-01
We propose a gradient based topology optimization algorithm for acoustic-structure (vibro-acoustic) interaction problems without an explicit interfacing boundary representation. In acoustic-structure interaction problems, the pressure field and the displacement field are governed by the Helmholtz...... to subdomain interfaces evolving during the optimization process. In this paper, we propose to use a mixed finite element formulation with displacements and pressure as primary variables (u/p formulation) which eliminates the need for explicit boundary representation. In order to describe the Helmholtz......-dimensional acoustic-structure interaction problems are optimized to show the validity of the proposed method....
Combined shape and topology optimization of 3D structures
Christiansen, Asger Nyman; Bærentzen, Jakob Andreas; Nobel-Jørgensen, Morten
2015-01-01
We present a method for automatic generation of 3D models based on shape and topology optimization. The optimization procedure, or model generation process, is initialized by a set of boundary conditions, an objective function, constraints and an initial structure. Using this input, the method...... will automatically deform and change the topology of the initial structure such that the objective function is optimized subject to the specified constraints and boundary conditions. For example, this tool can be used to improve the stiffness of a structure before printing, reduce the amount of material needed...
Design and Optimization of a Turbine Intake Structure
P. Fošumpaur
2005-01-01
Full Text Available The appropriate design of the turbine intake structure of a hydropower plant is based on assumptions about its suitable function, and the design will increase the total efficiency of operation. This paper deals with optimal design of the turbine structure of run-of-river hydropower plants. The study focuses mainly on optimization of the hydropower plant location with respect to the original river banks, and on the optimal design of a separating pier between the weir and the power plant. The optimal design of the turbine intake was determined with the use of 2-D mathematical modelling. A case study is performed for the optimal design of a turbine intake structure on the Nemen river in Belarus.
An overview of optimization of structures subjected to transient loads
Kang, Byung Soo; Park, Gyung Jin
2005-01-01
Various aspects of structural optimization techniques under transient loads are extensively reviewed. The main themes of the paper are treatment of time dependent constraints, calculation of design sensitivity, and approximation. Each subject is reviewed with the corresponding papers that have been published since 1970s. The treatment of time dependent constraints in both the direct method and the transformation method is discussed. Two ways of calculating design sensitivity of a structure under transient loads are discussed-direct differentiation method and adjoint variable method. The approximation concept mainly focuses on response surface method in crashworthiness and local approximation with the intermediate variable. Especially, as an approximated optimization technique, equivalent static load method which takes advantage of the well-established static response optimization technique is introduced. And as an application area of dynamic response optimization technique, the structural optimization in flexible multibody dynamic system is reviewed in the viewpoint of the above three themes
Optimization of Reinforcement of RC Framed Structures
P. Štěpánek
2000-01-01
Full Text Available This paper presents the entire formulation of longitudinal reinforcement minimization in a concrete structure of known sections and shape under loading by the normal force and the bending moment. Constraint conditions are given by the conditions of structure reliability in accordance with the relevant codes for ultimate strength and applicability of the sections specified by a designer. Linearization of the non-linear function is described, and possibilities of applying algorithms of linear computing are discussed. The functioning of the process described is demonstrated on a plane frame structure design.
Optimal Investment in Age-Structured Goodwill
Silvia Faggian; Luca Grosset
2012-01-01
Segmentation is a core strategy in modern marketing, and age-specific segmentation based on the age of the consumers is very common in practice. Age-specific segmentation enables the change of the segments composition during time and can be studied only by means of dynamic advertising models. Here we assume that a firm wants to optimally promote and sell a single product in an age-segmented market and we model the awareness of this product using an infinite dimensional Nerlove-Arrow goodwill ...
Cellular Automata in Topology Optimization of Continuum Structures ...
In this paper, an optimization algorithm based on cellular automata (CA) is developed for topology optimization of continuum structures with shear and flexural behavior. The design domain is divided into small triangle elements and each cell is considered as a finite element. The stress analysis is performed by the Constant ...
Xiaojuan, Ou; Wei, Zhou; Jianguo, Yu
2005-01-01
In this paper, we pay our attention to the multiscale kalman algorithm based on correlation structure of the discrete wavelet coefficients for the restoration of the GPS common-view observation data...
DISCRETE MATHEMATICS/NUMBER THEORY
Mrs. Manju Devi*
2017-01-01
Discrete mathematics is the study of mathematical structures that are fundamentally discrete rather than continuous. In contrast to real numbers that have the property of varying "smoothly", the objects studied in discrete mathematics such as integers, graphs, and statements do not vary smoothly in this way, but have distinct, separated values. Discrete mathematics therefore excludes topics in "continuous mathematics" such as calculus and analysis. Discrete objects can often be enumerated by ...
A tutorial on fundamental model structures for railway timetable optimization
Harrod, Steven
2012-01-01
This guide explains the role of railway timetables relative to all other railway scheduling activities, and then presents four fundamental timetable formulations suitable for optimization. Timetabling models may be classified according to whether they explicitly model the track structure, and whe......This guide explains the role of railway timetables relative to all other railway scheduling activities, and then presents four fundamental timetable formulations suitable for optimization. Timetabling models may be classified according to whether they explicitly model the track structure...
Topology Optimization for Conceptual Design of Reinforced Concrete Structures
Amir, Oded; Bogomolny, Michael
2011-01-01
Design of reinforced concrete structures is governed by the nonlinear behavior of concrete and by its dierent strengths in tension and compression. The purpose of this article is to present a computational procedure for optimal conceptual design of reinforced concrete structures, based on topology...... must be consid- ered. Optimized distribution of material is achieved by introducing interpolation rules for both elastic and plastic material properties. Several numerical examples illustrate the capability and potential of the proposed procedure....
Optimizing the structure of Tetracyanoplatinate(II)
Dohn, Asmus Ougaard; Møller, Klaus Braagaard; Sauer, Stephan P. A.
2013-01-01
. For the C-N bond these trends are reversed and an order of magnitude smaller. With respect to the basis set dependence we observed that a triple zeta basis set with polarization functions gives in general sufﬁciently converged results, but while for the Pt-C bond it is advantageous to include extra diffuse......The geometry of tetracyanoplatinate(II) (TCP) has been optimized with density functional theory (DFT) calculations in order to compare different computational strategies. Two approximate scalar relativistic methods, i.e. the scalar zeroth-order regular approximation (ZORA) and non...... is almost quantitatively reproduced in the ZORA and ECP calculations. In addition, the effect of the exchange-correlation functional and one-electron basis set was studied by employing the two generalized gradient approximation (GGA) functionals, BLYP and PBE, as well as their hybrid version B3LYP and PBE0...
Design Optimization of Irregular Cellular Structure for Additive Manufacturing
Song, Guo-Hua; Jing, Shi-Kai; Zhao, Fang-Lei; Wang, Ye-Dong; Xing, Hao; Zhou, Jing-Tao
2017-09-01
Irregularcellular structurehas great potential to be considered in light-weight design field. However, the research on optimizing irregular cellular structures has not yet been reporteddue to the difficulties in their modeling technology. Based on the variable density topology optimization theory, an efficient method for optimizing the topology of irregular cellular structures fabricated through additive manufacturing processes is proposed. The proposed method utilizes tangent circles to automatically generate the main outline of irregular cellular structure. The topological layoutof each cellstructure is optimized using the relative density informationobtained from the proposed modified SIMP method. A mapping relationship between cell structure and relative densityelement is builtto determine the diameter of each cell structure. The results show that the irregular cellular structure can be optimized with the proposed method. The results of simulation and experimental test are similar for irregular cellular structure, which indicate that the maximum deformation value obtained using the modified Solid Isotropic Microstructures with Penalization (SIMP) approach is lower 5.4×10-5 mm than that using the SIMP approach under the same under the same external load. The proposed research provides the instruction to design the other irregular cellular structure.
Development and optimization of containment structure concepts
Reuter, H.R.; Whitcraft, J.S. Jr.
1976-01-01
The development of prestressed concrete containment structures for nuclear power plants designed, constructed, and tested by Bechtel Power Corporation has been divided into three general stages or generations. The distinctions that characterize these generations are: the shape of the dome, the number of buttresses, the size and arrangement of the post-tensioning tendons, and the design level of the prestressing forces. (author)
Design optimization of jacket structures for mass production
Sandal, Kasper
This thesis presents models and applications for structural optimization of jacket structures for offshore wind turbines. The motivation is that automatic design procedures can be used to obtain more cost efficient designs, and thus reduce the levelized cost of energy from offshore wind. A struct......This thesis presents models and applications for structural optimization of jacket structures for offshore wind turbines. The motivation is that automatic design procedures can be used to obtain more cost efficient designs, and thus reduce the levelized cost of energy from offshore wind....... A structural finite element model is developed specifically for the analysis and optimization of jacket structures. The model uses Timoshenko beam elements, and assumes thin walled tubular beams and a linear elastic structural response. The finite element model is implemented in a Matlab package called JADOP...... (Jacket Design Optimization), and the static and dynamic structural response is verified with the commercial finite element software Abaqus. A parametric mesh of the offshore wind turbine structure makes it relatively easy to represent various structures from the literature, as well as exploring...
Reliability-Based Structural Optimization of Wave Energy Converters
Ambühl, Simon; Kramer, Morten; Sørensen, John Dalsgaard
2014-01-01
More and more wave energy converter (WEC) concepts are reaching prototype level. Once the prototype level is reached, the next step in order to further decrease the levelized cost of energy (LCOE) is optimizing the overall system with a focus on structural and maintenance (inspection) costs......, as well as on the harvested power from the waves. The target of a fully-developed WEC technology is not maximizing its power output, but minimizing the resulting LCOE. This paper presents a methodology to optimize the structural design of WECs based on a reliability-based optimization problem...
Topology optimization of structures and infill for additive manufacturing
Sigmund, Ole; Clausen, Anders; Groen, Jeroen Peter
Topology optimization (TO) [1] is a widely used tool for generating optimal structures for subsequent realization by additive manufacturing (AM) methods. TO is a numerical method that, based on iterated finite element analyses, gradient-based optimization algorithms and design parameterizations...... described by point clouds, delivers optimal but often rather complex topologies. As such, TO is a design method that takes full advantage of the large design freedom offered by AM technologies. Much recent effortin the TO community has been devoted to the development of algorithms that take manufacturing...... as a design gimmick to illustrate the capabilities of AM to mimic natural creations like honeycombs and bonestructure. Partly for manufacturing reasons, infill microstructure is often built as open-walled foam structures. However, as maybe unknown by many, open-walled microstructures are not optimal...
Interactive Reliability-Based Optimization of Structural Systems
Pedersen, Claus
In order to introduce the basic concepts within the field of reliability-based structural optimization problems, this chapter is devoted to a brief outline of the basic theories. Therefore, this chapter is of a more formal nature and used as a basis for the remaining parts of the thesis. In section...... 2.2 a general non-linear optimization problem and corresponding terminology are presented whereupon optimality conditions and the standard form of an iterative optimization algorithm are outlined. Subsequently, the special properties and characteristics concerning structural optimization problems...... are treated in section 2.3. With respect to the reliability evalutation, the basic theory behind a reliability analysis and estimation of probability of failure by the First-Order Reliability Method (FORM) and the iterative Rackwitz-Fiessler (RF) algorithm are considered in section 2.5 in which...
Singularities in Structural Optimization of the Ziegler Pendulum
O. N. Kirillov
2011-01-01
Full Text Available Structural optimization of non-conservative systems with respect to stability criteria is a research area with important applications in fluid-structure interactions, friction-induced instabilities, and civil engineering. In contrast to optimization of conservative systems where rigorously proven optimal solutions in buckling problems have been found, for nonconservative optimization problems only numerically optimized designs have been reported. The proof of optimality in non-conservative optimization problems is a mathematical challenge related to multiple eigenvalues, singularities in the stability domain, and non-convexity of the merit functional. We present here a study of optimal mass distribution in a classical Ziegler pendulum where local and global extrema can be found explicitly. In particular, for the undamped case, the two maxima of the critical flutter load correspond to a vanishing mass either in a joint or at the free end of the pendulum; in the minimum, the ratio of the masses is equal to the ratio of the stiffness coefficients. The role of the singularities on the stability boundary in the optimization is highlighted, and an extension to the damped case as well as to the case of higher degrees of freedom is discussed.
Conceptual optimization using genetic algorithms for tube in tube structures
Pârv, Bianca Roxana; Hulea, Radu; Mojolic, Cristian
2015-01-01
The purpose of this article is to optimize the tube in tube structural systems for tall buildings under the horizontal wind loads. It is well-known that the horizontal wind loads is the main criteria when choosing the structural system, the types and the dimensions of structural elements in the majority of tall buildings. Thus, the structural response of tall buildings under the horizontal wind loads will be analyzed for 40 story buildings and a total height of 120 meters; the horizontal dimensions will be 30m × 30m for the first two optimization problems and 15m × 15m for the third. The optimization problems will have the following as objective function the cross section area, as restrictions the displacement of the building< the admissible displacement (H/500), and as variables the cross section dimensions of the structural elements
Structural optimization via a design space hierarchy
Vanderplaats, G. N.
1976-01-01
Mathematical programming techniques provide a general approach to automated structural design. An iterative method is proposed in which design is treated as a hierarchy of subproblems, one being locally constrained and the other being locally unconstrained. It is assumed that the design space is locally convex in the case of good initial designs and that the objective and constraint functions are continuous, with continuous first derivatives. A general design algorithm is outlined for finding a move direction which will decrease the value of the objective function while maintaining a feasible design. The case of one-dimensional search in a two-variable design space is discussed. Possible applications are discussed. A major feature of the proposed algorithm is its application to problems which are inherently ill-conditioned, such as design of structures for optimum geometry.
Particle Swarm Optimization for Structural Design Problems
Hamit SARUHAN
2010-02-01
Full Text Available The aim of this paper is to employ the Particle Swarm Optimization (PSO technique to a mechanical engineering design problem which is minimizing the volume of a cantilevered beam subject to bending strength constraints. Mechanical engineering design problems are complex activities which are computing capability are more and more required. The most of these problems are solved by conventional mathematical programming techniques that require gradient information. These techniques have several drawbacks from which the main one is becoming trapped in local optima. As an alternative to gradient-based techniques, the PSO does not require the evaluation of gradients of the objective function. The PSO algorithm employs the generation of guided random positions when they search for the global optimum point. The PSO which is a nature inspired heuristics search technique imitates the social behavior of bird flocking. The results obtained by the PSO are compared with Mathematical Programming (MP. It is demonstrated that the PSO performed and obtained better convergence reliability on the global optimum point than the MP. Using the MP, the volume of 2961000 mm3 was obtained while the beam volume of 2945345 mm3 was obtained by the PSO.
A Comparative Study on Optimal Structural Dynamics Using Wavelet Functions
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.
On Optimal Shapes in Materials and Structures
Pedersen, Pauli
2000-01-01
In the micromechanics design of materials, as well as in the design of structural connections, the boundary shape plays an important role. The objective may be the stiffest design, the strongest design or just a design of uniform energy density along the shape. In an energy formulation it is proven...... that these three objectives have the same solution, at least within the limits of geometrical constraints, including the parametrization. Without involving stress/strain fields, the proof holds for 3D-problems, for power-law nonlinear elasticity and for anisotropic elasticity. To clarify the importance...
Thomas, Edward, E-mail: etjr@auburn.edu; Konopka, Uwe; Lynch, Brian; Adams, Stephen; LeBlanc, Spencer [Physics Department, Auburn University, Auburn, Alabama 36849 (United States); Merlino, Robert L. [Department of Physics and Astronomy, The University of Iowa, Iowa City, Iowa 52242 (United States); Rosenberg, Marlene [Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California 92093 (United States)
2015-11-15
Dusty plasmas have been studied in argon, radio frequency (rf) glow discharge plasmas at magnetic fields up to 2.5 T where the electrons and ions are strongly magnetized. Plasmas are generated between two parallel plate electrodes where the lower, powered electrode is solid and the upper electrode supports a dual mesh consisting of #24 brass and #30 aluminum wire cloth. In this experiment, we study the formation of imposed ordered structures and particle dynamics as a function of magnetic field. Through observations of trapped particles and the quasi-discrete (i.e., “hopping”) motion of particles between the trapping locations, it is possible to make a preliminary estimate of the potential structure that confines the particles to a grid structure in the plasma. This information is used to gain insight into the formation of the imposed grid pattern of the dust particles in the plasma.
Changwei Zhou
2017-02-01
Full Text Available In this article, the analytical homogenization method of periodic discrete media (HPDM and the numerical condensed wave finite element method (CWFEM are employed to study the longitudinal and transverse vibrations of framed structures. The valid frequency range of the HPDM is re-evaluated using the wave propagation feature identified by the CWFEM. The relative error of the wavenumber by the HPDM compared to that by the CWFEM is illustrated in functions of frequency and scale ratio. A parametric study on the thickness of the structure is carried out where the dispersion relation and the relative error are given for three different thicknesses. The dynamics of a finite structure such as natural frequency and forced response are also investigated using the HPDM and the CWFEM.
Homogenization of discrete media
Pradel, F.; Sab, K.
1998-01-01
Material such as granular media, beam assembly are easily seen as discrete media. They look like geometrical points linked together thanks to energetic expressions. Our purpose is to extend discrete kinematics to the one of an equivalent continuous material. First we explain how we build the localisation tool for periodic materials according to estimated continuum medium type (classical Cauchy, and Cosserat media). Once the bridge built between discrete and continuum media, we exhibit its application over two bidimensional beam assembly structures : the honey comb and a structural reinforced variation. The new behavior is then applied for the simple plan shear problem in a Cosserat continuum and compared with the real discrete solution. By the mean of this example, we establish the agreement of our new model with real structures. The exposed method has a longer range than mechanics and can be applied to every discrete problems like electromagnetism in which relationship between geometrical points can be summed up by an energetic function. (orig.)
Structural features that optimize high temperature superconductivity
Jorgensen, J.D.; Argonne Nat. Lab., IL; Hinks, D.G.; Argonne Nat. Lab., IL; Chmaissem, O.; Argonne Nat. Lab., IL; Argyriou, D.N.; Argonne Nat. Lab., IL; Mitchell, J.F.; Argonne Nat. Lab., IL; Dabrowski, B.
1996-01-01
Studies of a large number of compounds have provided a consistent picture of what structural features give rise to the highest T c 's in copper-oxide superconductors. For example, various defects can be introduced into the blocking layer to provide the optimum carrier concentration, but defects that form in or adjacent to the CuO 2 layers will lower T c and eventually destroy superconductivity. After these requirements are satisfied, the highest T c 's are observed for compounds (such as the HgBa 2 Ca n-1 Cu n O 2n+2+x family) that have flat and square CuO 2 planes and long apical Cu-O bonds. This conclusion is confirmed by the study of materials in which the flatness of the CuO 2 plane can be varied in a systematic way. In more recent work, attention has focused on how the structure can be modified, for example, by chemical substitution, to improve flux pinning properties. Two strategies are being investigated: (1) Increasing the coupling of pancake vortices to form vortex lines by shortening or ''metallizing'' the blocking layer; and (2) the formation of defects that pin flux. (orig.)
Shi, Zhongyuan; Dong, Tao
2015-01-01
Highlights: • A constructal thermohydraulic optimization was carried out. • The effect of manufacturing limit on the Pareto solution set was discussed. • The suitable constraints may differ from those on a quasi-continuous basis. - Abstract: A synthetic optimization is presented for the Pareto layouts of discrete heat sources (with uniform heat flux) flush mounted on a flat plate over which laminar flow serves for cooling purpose. The peak temperatures and the flow drag loss are minimizing simultaneously provided that the total heat dissipation rate and the plate length are held constant. The impact of the manufacturing limit, i.e. the minimum length of the heated or the adiabatic patch, on the optimum layout is discussed. The results in general comply with analytical deduction based on the constructal theory. However in a finite length scenario, geometric constraints on the adiabatic spacing differ from that fits the situation in which maximum heat transfer performance alone is to be achieved.
Nonlinear Shaping Architecture Designed with Using Evolutionary Structural Optimization Tools
Januszkiewicz, Krystyna; Banachowicz, Marta
2017-10-01
The paper explores the possibilities of using Structural Optimization Tools (ESO) digital tools in an integrated structural and architectural design in response to the current needs geared towards sustainability, combining ecological and economic efficiency. The first part of the paper defines the Evolutionary Structural Optimization tools, which were developed specifically for engineering purposes using finite element analysis as a framework. The development of ESO has led to several incarnations, which are all briefly discussed (Additive ESO, Bi-directional ESO, Extended ESO). The second part presents result of using these tools in structural and architectural design. Actual building projects which involve optimization as a part of the original design process will be presented (Crematorium in Kakamigahara Gifu, Japan, 2006 SANAA“s Learning Centre, EPFL in Lausanne, Switzerland 2008 among others). The conclusion emphasizes that the structural engineering and architectural design mean directing attention to the solutions which are used by Nature, designing works optimally shaped and forming their own environments. Architectural forms never constitute the optimum shape derived through a form-finding process driven only by structural optimization, but rather embody and integrate a multitude of parameters. It might be assumed that there is a similarity between these processes in nature and the presented design methods. Contemporary digital methods make the simulation of such processes possible, and thus enable us to refer back to the empirical methods of previous generations.
Training set optimization under population structure in genomic selection.
Isidro, Julio; Jannink, Jean-Luc; Akdemir, Deniz; Poland, Jesse; Heslot, Nicolas; Sorrells, Mark E
2015-01-01
Population structure must be evaluated before optimization of the training set population. Maximizing the phenotypic variance captured by the training set is important for optimal performance. The optimization of the training set (TRS) in genomic selection has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the coefficient of determination (CDmean), mean of predictor error variance (PEVmean), stratified CDmean (StratCDmean) and random sampling, were evaluated for prediction accuracy in the presence of different levels of population structure. In the presence of population structure, the most phenotypic variation captured by a sampling method in the TRS is desirable. The wheat dataset showed mild population structure, and CDmean and stratified CDmean methods showed the highest accuracies for all the traits except for test weight and heading date. The rice dataset had strong population structure and the approach based on stratified sampling showed the highest accuracies for all traits. In general, CDmean minimized the relationship between genotypes in the TRS, maximizing the relationship between TRS and the test set. This makes it suitable as an optimization criterion for long-term selection. Our results indicated that the best selection criterion used to optimize the TRS seems to depend on the interaction of trait architecture and population structure.
Multidisciplinary Design and Optimization Framework for Aircraft Box Structures
Van Dijk, R.E.C.; Zhao, X.; Wang, H.; Van Dalen, F.
2012-01-01
Competitive aircraft box structures are a perfect compromise between weight and price. The conceptual design process of these structures is a typical Multidisciplinary Design and Optimization effort, normally conducted by human engineers. The iterative nature of MDO turns development into a long and
Optimal Capital Structure: Reflections on Economic and Other Values
M.B.J. Schauten (Marc); J. Spronk (Jaap)
2006-01-01
textabstractDespite a vast literature on the capital structure of the firm there still is a big gap between theory and practice. Starting with the seminal work by Modigliani & Miller, much attention has been paid to the optimality of capital structure from the shareholders’ point of view. Over the
Optimization of an embedded rail structure using a numerical technique
Markine, V.L.; De Man, A.P.; Esveld, C.
2000-01-01
This paper presents several steps of a procedure for design of a railway track aiming at the development of optimal track structures under various predefined service and environmental conditions. The structural behavior of the track is analyzed using a finite element model in which the track and a
Studies of multiperiodic structures by means of circuits with discrete elements
Tran, D.T.
In modern linear accelerators, magnetrons, and travelling wave tubes, to reduce the beam loading effect and to reconcile the structure efficiency and its sensitiveness to mechanical errors, sophisticated structures are often designed by associating several elementary circuits. Because several pass-bands can interfere, the dispersion properties of such multiband structures were studied. Using matrix calculus and applying the positive real properties of impedance, the behavior of series-coupled and parallel-coupled structures is derived. Forms of dispersion curves of biperiodic, triperiodic structure, deflecting structure, interdigital structure, and others are discussed. Experimental work is presented on a few modern structures to illustrate the theoretical work. A new structure, derived from the organ pipe structure and proposed recently as a variable energy accelerating structure, is discussed, and interdigital structures are considered
Optimal Design of Composite Structures Under Manufacturing Constraints
Marmaras, Konstantinos
determination of the appropriate laminate thickness and the material choice in the structure. The optimal design problems that arise are stated as nonconvex mixed integer programming problems. We resort to different reformulation techniques to state the optimization problems as either linear or nonlinear convex....... The continuous relaxation of the mixed integer programming problems is being solved by an implementation of a primal–dual interior point method for nonlinear programming that updates the barrier parameter adaptively. The method is chosen for its excellent convergence properties and the ability of the method...... design phase results in structures with better structural performance reducing the need of manually post–processing the found designs....
Optimal Inspection and Maintenance Strategies for Structural Systems
Sommer, A. M.
The aim of this thesis is to give an overview of conventional and optimal reliability-based inspection and maintenance strategies and to examine for specific structures how the cost can be reduced and/or the safety can be improved by using optimal reliability-based inspection strategies....... For structures with several almost similar components it is suggested that individual inspection strategies should be determined for each component or a group of components based on the reliability of the actual component. The benefit of this procedure is assessed in connection with the structures considered....... Furthermore, in relation to the calculations performed the intention is to modify an existing program for determination of optimal inspection strategies. The main purpose of inspection and maintenance of structural systems is to prevent or delay damage or deterioration to protect people, environment...
Structure optimization and simulation analysis of the quartz micromachined gyroscope
Xuezhong Wu
2014-02-01
Full Text Available Structure optimization and simulation analysis of the quartz micromachined gyroscope are reported in this paper. The relationships between the structure parameters and the frequencies of work mode were analysed by finite element analysis. The structure parameters of the quartz micromachined gyroscope were optimized to reduce the difference between the frequencies of the drive mode and the sense mode. The simulation results were proved by testing the prototype gyroscope, which was fabricated by micro-electromechanical systems (MEMS technology. Therefore, the frequencies of the drive mode and the sense mode can match each other by the structure optimization and simulation analysis of the quartz micromachined gyroscope, which is helpful in the design of the high sensitivity quartz micromachined gyroscope.
Deterministic Design Optimization of Structures in OpenMDAO Framework
Coroneos, Rula M.; Pai, Shantaram S.
2012-01-01
Nonlinear programming algorithms play an important role in structural design optimization. Several such algorithms have been implemented in OpenMDAO framework developed at NASA Glenn Research Center (GRC). OpenMDAO is an open source engineering analysis framework, written in Python, for analyzing and solving Multi-Disciplinary Analysis and Optimization (MDAO) problems. It provides a number of solvers and optimizers, referred to as components and drivers, which users can leverage to build new tools and processes quickly and efficiently. Users may download, use, modify, and distribute the OpenMDAO software at no cost. This paper summarizes the process involved in analyzing and optimizing structural components by utilizing the framework s structural solvers and several gradient based optimizers along with a multi-objective genetic algorithm. For comparison purposes, the same structural components were analyzed and optimized using CometBoards, a NASA GRC developed code. The reliability and efficiency of the OpenMDAO framework was compared and reported in this report.
Alfvénic Dynamics and Fine Structuring of Discrete Auroral Arcs: Swarm and e-POP Observations
Miles, D.; Mann, I. R.; Pakhotin, I.; Burchill, J. K.; Howarth, A. D.; Knudsen, D. J.; Wallis, D. D.; Yau, A. W.; Lysak, R. L.
2017-12-01
The electrodynamics associated with dual discrete arc aurora with anti-parallel flow along the arcs were observed nearly simultaneously by the enhanced Polar Outflow Probe (e-POP) and the Swarm A and C spacecraft. Auroral imaging from e-POP reveal 1-10 km structuring of the arcs, which move and evolve on second timescales and confound the traditional single-spacecraft field-aligned current algorithms. High-cadence magnetic data from e-POP shows 1-10 Hz, presumably Alfvénic perturbations co-incident with and at the same scale size as the observed dynamic auroral fine structures. High-cadence electric and magnetic field data from Swarm A reveals non-stationary electrodynamics involving reflected and interfering Alfvén waves and signatures of modulation consistent with trapping in the Ionospheric Alfvén Resonator (IAR). Together, these observations suggest a role for Alfven waves, perhaps also the IAR, in discrete arc dynamics on 0.2 - 10s timescales and 1-10 km spatial scales.
Novel structures for Discrete Hartley Transform based on first-order moments
Xiong, Jun; Zheng, Wenjuan; Wang, Hao; Liu, Jianguo
2018-03-01
Discrete Hartley Transform (DHT) is an important tool in digital signal processing. In the present paper, the DHT is firstly transformed into the first-order moments-based form, then a new fast algorithm is proposed to calculate the first-order moments without multiplication. Based on the algorithm theory, the corresponding hardware architecture for DHT is proposed, which only contains shift operations and additions with no need for multipliers and large memory. To verify the availability and effectiveness, the proposed design is implemented with hardware description language and synthesized by Synopsys Design Compiler with 0.18-μm SMIC library. A series of experiments have proved that the proposed architecture has better performance in terms of the product of the hardware consumption and computation time.
Sørensen, John Aasted
2011-01-01
The objectives of Discrete Mathematics (IDISM2) are: The introduction of the mathematics needed for analysis, design and verification of discrete systems, including the application within programming languages for computer systems. Having passed the IDISM2 course, the student will be able...... to accomplish the following: -Understand and apply formal representations in discrete mathematics. -Understand and apply formal representations in problems within discrete mathematics. -Understand methods for solving problems in discrete mathematics. -Apply methods for solving problems in discrete mathematics......; construct a finite state machine for a given application. Apply these concepts to new problems. The teaching in Discrete Mathematics is a combination of sessions with lectures and students solving problems, either manually or by using Matlab. Furthermore a selection of projects must be solved and handed...
Structural features that optimize high temperature superconductivity
Jorgensen, J.D.; Hinks, D.G. Chmaissem, O.; Argyriou, D.N.; Mitchell, J.F. [Argonne National Lab., IL (United States); Dabrowski, B. [Northern Illinois Univ., De Kalb, IL (United States). Dept. of Physics
1996-01-01
For example, various defects can be introduced into the blocking layer to provide the optimum carrier concentration, but defects that form in or adjacent to the CuO{sub 2} layers will lower T{sub c} and eventually destroy superconductivity. After these requirements are satisfied, the highest T{sub c}`s are observed for compounds (such as the HgBa{sub 2}Ca{sub n-1}CuO{sub 2n{plus}2{plus}x} family) that have flat and square CuO{sub 2} planes and long apical Cu-O bonds. This conclusion is confirmed by the study of materials in which the flatness of the CuO{sub 2} plane can be varied in a systematic way. In more recent work, attention has focused on how the structure can be modified, for example, by chemical substitution, to improve flux pinning properties. Two strategies are being investigated: (1) Increasing the coupling of pancake vortices to form vortex-lines by shortening or ``metallizing`` the blocking layer; and (2) the formation of defects that pin flux.
Structural features that optimize high temperature superconductivity
Jorgensen, J.D.; Hinks, D.G. Chmaissem, O.; Argyriou, D.N.; Mitchell, J.F.; Dabrowski, B.
1996-01-01
For example, various defects can be introduced into the blocking layer to provide the optimum carrier concentration, but defects that form in or adjacent to the CuO 2 layers will lower T c and eventually destroy superconductivity. After these requirements are satisfied, the highest T c 's are observed for compounds (such as the HgBa 2 Ca n-1 CuO 2n+2+x family) that have flat and square CuO 2 planes and long apical Cu-O bonds. This conclusion is confirmed by the study of materials in which the flatness of the CuO 2 plane can be varied in a systematic way. In more recent work, attention has focused on how the structure can be modified, for example, by chemical substitution, to improve flux pinning properties. Two strategies are being investigated: (1) Increasing the coupling of pancake vortices to form vortex-lines by shortening or ''metallizing'' the blocking layer; and (2) the formation of defects that pin flux
Gradient-based optimization in nonlinear structural dynamics
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...
Optimal analysis of structures by concepts of symmetry and regularity
Kaveh, Ali
2013-01-01
Optimal analysis is defined as an analysis that creates and uses sparse, well-structured and well-conditioned matrices. The focus is on efficient methods for eigensolution of matrices involved in static, dynamic and stability analyses of symmetric and regular structures, or those general structures containing such components. Powerful tools are also developed for configuration processing, which is an important issue in the analysis and design of space structures and finite element models. Different mathematical concepts are combined to make the optimal analysis of structures feasible. Canonical forms from matrix algebra, product graphs from graph theory and symmetry groups from group theory are some of the concepts involved in the variety of efficient methods and algorithms presented. The algorithms elucidated in this book enable analysts to handle large-scale structural systems by lowering their computational cost, thus fulfilling the requirement for faster analysis and design of future complex systems. The ...
TLM modeling and system identification of optimized antenna structures
N. Fichtner
2008-05-01
Full Text Available The transmission line matrix (TLM method in conjunction with the genetic algorithm (GA is presented for the bandwidth optimization of a low profile patch antenna. The optimization routine is supplemented by a system identification (SI procedure. By the SI the model parameters of the structure are estimated which is used for a reduction of the total TLM simulation time. The SI utilizes a new stability criterion of the physical poles for the parameter extraction.
Choi, Youngmin; Chang, Hyunju; Lee, Jae Do [Korea Research Inst. of Chemical Technology, Taejon (Korea); Kim, Eunah; No, Kwangsoo [Korea Advanced Inst. of Science and Technology, Taejon (Korea)
2002-09-01
We use a first-principles discrete variational (DV)-X{alpha} method to investigate the electronic structure of chromium aluminum oxynitride. When nitrogen is substituted for oxygen in the Cr-Al-O system, the N2p level appears in the energy range between O2p and Cr3d levels. Consequently, the valence band of chromium aluminum oxynitride becomes broader and the band gap becomes smaller than that of chromium aluminum oxide, which is consistent with the photoelectron spectra for the valence band using X-ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS). We expect that this valence band structure of chromium aluminum oxynitride will modify the transmittance slope which is a requirement for photomask application. (author)
Choi, Youngmin; Chang, Hyunju; Lee, Jae Do; Kim, Eunah; No, Kwangsoo
2002-01-01
We use a first-principles discrete variational (DV)-Xα method to investigate the electronic structure of chromium aluminum oxynitride. When nitrogen is substituted for oxygen in the Cr-Al-O system, the N2p level appears in the energy range between O2p and Cr3d levels. Consequently, the valence band of chromium aluminum oxynitride becomes broader and the band gap becomes smaller than that of chromium aluminum oxide, which is consistent with the photoelectron spectra for the valence band using X-ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS). We expect that this valence band structure of chromium aluminum oxynitride will modify the transmittance slope which is a requirement for photomask application. (author)
Optimization of foam-filled bitubal structures for crashworthiness criteria
Zhang, Yong; Sun, Guangyong; Li, Guangyao; Luo, Zhen; Li, Qing
2012-01-01
Highlights: ► The paper aims to optimize foam-filled bitubal squared column for crashworthiness. ► It explores different formulations and configurations of design. ► The optimal foam-filled bitubal column is better than foam-filled monotubal column. ► The optimal foam-filled bitubal column is better than empty bitubal column. -- Abstract: Thin-walled structures have been widely used as key components in automobile and aerospace industry to improve the crashworthiness and safety of vehicles while maintaining overall light-weight. This paper aims to explore the design issue of thin-walled bitubal column structures filled with aluminum foam. As a relatively new filler material, aluminum foam can increase crashworthiness without sacrificing too much weight. To optimize crashworthiness of the foam-filled bitubal square column, the Kriging meta-modeling technique is adopted herein to formulate the objective and constraint functions. The genetic algorithm (GA) and Non-dominated Sorting Genetic Algorithm II (NSGA II) are used to seek the optimal solutions to the single and multiobjective optimization problems, respectively. To compare with other thin-walled configurations, the design optimization is also conducted for empty bitubal column and foam-filled monotubal column. The results demonstrate that the foam-filled bitubal configuration has more room to enhance the crashworthiness and can be an efficient energy absorber.
Xun Zhang
2014-01-01
Full Text Available Optimal sensor placement is a key issue in the structural health monitoring of large-scale structures. However, some aspects in existing approaches require improvement, such as the empirical and unreliable selection of mode and sensor numbers and time-consuming computation. A novel improved particle swarm optimization (IPSO algorithm is proposed to address these problems. The approach firstly employs the cumulative effective modal mass participation ratio to select mode number. Three strategies are then adopted to improve the PSO algorithm. Finally, the IPSO algorithm is utilized to determine the optimal sensors number and configurations. A case study of a latticed shell model is implemented to verify the feasibility of the proposed algorithm and four different PSO algorithms. The effective independence method is also taken as a contrast experiment. The comparison results show that the optimal placement schemes obtained by the PSO algorithms are valid, and the proposed IPSO algorithm has better enhancement in convergence speed and precision.
Optimization study on structural analyses for the J-PARC mercury target vessel
Guan, Wenhai; Wakai, Eiichi; Naoe, Takashi; Kogawa, Hiroyuki; Wakui, Takashi; Haga, Katsuhiro; Takada, Hiroshi; Futakawa, Masatoshi
2018-06-01
The spallation neutron source at the Japan Proton Accelerator Research Complex (J-PARC) mercury target vessel is used for various materials science studies, work is underway to achieve stable operation at 1 MW. This is very important for enhancing the structural integrity and durability of the target vessel, which is being developed for 1 MW operation. In the present study, to reduce thermal stress and relax stress concentrations more effectively in the existing target vessel in J-PARC, an optimization approach called the Taguchi method (TM) is applied to thermo-mechanical analysis. The ribs and their relative parameters, as well as the thickness of the mercury vessel and shrouds, were selected as important design parameters for this investigation. According to the analytical results of 18 model types designed using the TM, the optimal design was determined. It is characterized by discrete ribs and a thicker vessel wall than the current design. The maximum thermal stresses in the mercury vessel and the outer shroud were reduced by 14% and 15%, respectively. Furthermore, it was indicated that variations in rib width, left/right rib intervals, and shroud thickness could influence the maximum thermal stress performance. It is therefore concluded that the TM was useful for optimizing the structure of the target vessel and to reduce the thermal stress in a small number of calculation cases.
Portfolio optimization with structured products under return constraint
Baweja Meena
2015-01-01
Full Text Available A new approach for optimizing risk in a portfolio of financial instruments involving structured products is presented. This paper deals with a portfolio selection model which uses optimization methodology to minimize conditional Value-at-Risk (CVaR under return constraint. It focuses on minimizing CVaR rather than on minimizing value-at-Risk VaR, as portfolios with low CVaR necessarily have low VaR as well. We consider a simple investment problem where besides stocks and bonds, the investor can also include structured products into the investment portfolio. Due to possible intermediate payments from structured product, we have to deal with a re-investment problem modeled as a linear optimization problem.
Stiffness design of geometrically nonlinear structures using topology optimization
Buhl, Thomas; Pedersen, Claus B. Wittendorf; Sigmund, Ole
2000-01-01
of the objective functions are found with the adjoint method and the optimization problem is solved using the Method of Moving Asymptotes. A filtering scheme is used to obtain checkerboard-free and mesh-independent designs and a continuation approach improves convergence to efficient designs. Different objective......The paper deals with topology optimization of structures undergoing large deformations. The geometrically nonlinear behaviour of the structures are modelled using a total Lagrangian finite element formulation and the equilibrium is found using a Newton-Raphson iterative scheme. The sensitivities...... functions are tested. Minimizing compliance for a fixed load results in degenerated topologies which are very inefficient for smaller or larger loads. The problem of obtaining degenerated "optimal" topologies which only can support the design load is even more pronounced than for structures with linear...
Doo Ho Lee
Full Text Available This work studies the optimal pricing strategy in a discrete-time Geo/Geo/1 queuing system under the sojourn time-dependent reward. We consider two types of pricing schemes. The first one is called the ex-post payment scheme where the server charges a price that is proportional to the time a customer spends in the system, and the second one is called ex-ante payment scheme where the server charges a flat price for all services. In each pricing scheme, a departing customer receives the reward that is inversely proportional to his/her sojourn time. The server should make the optimal pricing decisions in order to maximize its expected profits per time unit in each pricing scheme. This work also investigates customer's equilibrium joining or balking behavior under server's optimal pricing strategy. Numerical experiments are also conducted to validate our analysis. Keywords: Optimal pricing, Equilibrium behavior, Geo/Geo/1 queue, Sojourn time-dependent reward
Optimization of extraordinary optical absorption in plasmonic and dielectric structures
Dühring, Maria Bayard; Sigmund, Ole
2013-01-01
Extraordinary optical absorption (EOA) can be obtained by plasmonic surface structuring. However, studies that compare the performance of these plasmonic devices with similar structured dielectric devices are rarely found in the literature. In this work we show different methods to enhance the EOA...... by optimizing the geometry of the surface structuring for both plasmonic and dielectric devices, and the optimized performances are compared. Two different problem types with periodic structures are considered. The first case shows that strips of silicon on a surface can increase the absorption in an underlying...... it is important to compare the absorption performance of plasmonic devices with similarly structured dielectric devices in order to find the best possible solution....
Ellington, Roni; Wachira, James; Nkwanta, Asamoah
2010-01-01
The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses…
Shao Gui-Fang; Zhu Meng; Shangguan Ya-Li; Li Wen-Ran; Zhang Can; Wang Wei-Wei; Li Ling
2017-01-01
Due to the dependence of the chemical and physical properties of the bimetallic nanoparticles (NPs) on their structures, a fundamental understanding of their structural characteristics is crucial for their syntheses and wide applications. In this article, a systematical atomic-level investigation of Au–Pd bimetallic NPs is conducted by using the improved particle swarm optimization (IPSO) with quantum correction Sutton–Chen potentials (Q-SC) at different Au/Pd ratios and different sizes. In the IPSO, the simulated annealing is introduced into the classical particle swarm optimization (PSO) to improve the effectiveness and reliability. In addition, the influences of initial structure, particle size and composition on structural stability and structural features are also studied. The simulation results reveal that the initial structures have little effects on the stable structures, but influence the converging rate greatly, and the convergence rate of the mixing initial structure is clearly faster than those of the core-shell and phase structures. We find that the Au–Pd NPs prefer the structures with Au-rich in the outer layers while Pd-rich in the inner ones. Especially, when the Au/Pd ratio is 6:4, the structure of the nanoparticle (NP) presents a standardized Pd core Au shell structure. (paper)
Optimization of morphing flaps based on fluid structure interaction modeling
Barlas, Athanasios; Akay, Busra
2018-01-01
This article describes the design optimization of morphing trailing edge flaps for wind turbines with ‘smart blades’. A high fidelity Fluid Structure Interaction (FSI) simulation framework is utilized, comprised of 2D Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) models....... A coupled aero-structural simulation of a 10% chordwise length morphing trailing edge flap for a 4 MW wind turbine rotor is carried out and response surfaces are produced with respect to the flap internal geometry design parameters for the design conditions. Surrogate model based optimization is applied...
Homogenization and structural topology optimization theory, practice and software
Hassani, Behrooz
1999-01-01
Structural topology optimization is a fast growing field that is finding numerous applications in automotive, aerospace and mechanical design processes. Homogenization is a mathematical theory with applications in several engineering problems that are governed by partial differential equations with rapidly oscillating coefficients Homogenization and Structural Topology Optimization brings the two concepts together and successfully bridges the previously overlooked gap between the mathematical theory and the practical implementation of the homogenization method. The book is presented in a unique self-teaching style that includes numerous illustrative examples, figures and detailed explanations of concepts. The text is divided into three parts which maintains the book's reader-friendly appeal.
Wilke, Jeremiah J [Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Kenny, Joseph P. [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)
2015-02-01
Discrete event simulation provides a powerful mechanism for designing and testing new extreme- scale programming models for high-performance computing. Rather than debug, run, and wait for results on an actual system, design can first iterate through a simulator. This is particularly useful when test beds cannot be used, i.e. to explore hardware or scales that do not yet exist or are inaccessible. Here we detail the macroscale components of the structural simulation toolkit (SST). Instead of depending on trace replay or state machines, the simulator is architected to execute real code on real software stacks. Our particular user-space threading framework allows massive scales to be simulated even on small clusters. The link between the discrete event core and the threading framework allows interesting performance metrics like call graphs to be collected from a simulated run. Performance analysis via simulation can thus become an important phase in extreme-scale programming model and runtime system design via the SST macroscale components.
Material Distribution Optimization for the Shell Aircraft Composite Structure
Shevtsov, S.; Zhilyaev, I.; Oganesyan, P.; Axenov, V.
2016-09-01
One of the main goal in aircraft structures designing isweight decreasing and stiffness increasing. Composite structures recently became popular in aircraft because of their mechanical properties and wide range of optimization possibilities.Weight distribution and lay-up are keys to creating lightweight stiff strictures. In this paperwe discuss optimization of specific structure that undergoes the non-uniform air pressure at the different flight conditions and reduce a level of noise caused by the airflowinduced vibrations at the constrained weight of the part. Initial model was created with CAD tool Siemens NX, finite element analysis and post processing were performed with COMSOL Multiphysicsr and MATLABr. Numerical solutions of the Reynolds averaged Navier-Stokes (RANS) equations supplemented by k-w turbulence model provide the spatial distributions of air pressure applied to the shell surface. At the formulation of optimization problem the global strain energy calculated within the optimized shell was assumed as the objective. Wall thickness has been changed using parametric approach by an initiation of auxiliary sphere with varied radius and coordinates of the center, which were the design variables. To avoid a local stress concentration, wall thickness increment was defined as smooth function on the shell surface dependent of auxiliary sphere position and size. Our study consists of multiple steps: CAD/CAE transformation of the model, determining wind pressure for different flow angles, optimizing wall thickness distribution for specific flow angles, designing a lay-up for optimal material distribution. The studied structure was improved in terms of maximum and average strain energy at the constrained expense ofweight growth. Developed methods and tools can be applied to wide range of shell-like structures made of multilayered quasi-isotropic laminates.
Improved hybrid optimization algorithm for 3D protein structure prediction.
Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang
2014-07-01
A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins.
Reliability-based optimal structural design by the decoupling approach
Royset, J.O.; Der Kiureghian, A.; Polak, E.
2001-01-01
A decoupling approach for solving optimal structural design problems involving reliability terms in the objective function, the constraint set or both is discussed and extended. The approach employs a reformulation of each problem, in which reliability terms are replaced by deterministic functions. The reformulated problems can be solved by existing semi-infinite optimization algorithms and computational reliability methods. It is shown that the reformulated problems produce solutions that are identical to those of the original problems when the limit-state functions defining the reliability problem are affine. For nonaffine limit-state functions, approximate solutions are obtained by solving series of reformulated problems. An important advantage of the approach is that the required reliability and optimization calculations are completely decoupled, thus allowing flexibility in the choice of the optimization algorithm and the reliability computation method
Protein structure prediction using bee colony optimization metaheuristic
Fonseca, Rasmus; Paluszewski, Martin; Winter, Pawel
2010-01-01
of the proteins structure, an energy potential and some optimization algorithm that ¿nds the structure with minimal energy. Bee Colony Optimization (BCO) is a relatively new approach to solving opti- mization problems based on the foraging behaviour of bees. Several variants of BCO have been suggested......Predicting the native structure of proteins is one of the most challenging problems in molecular biology. The goal is to determine the three-dimensional struc- ture from the one-dimensional amino acid sequence. De novo prediction algorithms seek to do this by developing a representation...... our BCO method to generate good solutions to the protein structure prediction problem. The results show that BCO generally ¿nds better solutions than simulated annealing which so far has been the metaheuristic of choice for this problem....
Global structural optimizations of surface systems with a genetic algorithm
Chuang, Feng-Chuan
2005-01-01
Global structural optimizations with a genetic algorithm were performed for atomic cluster and surface systems including aluminum atomic clusters, Si magic clusters on the Si(111) 7 x 7 surface, silicon high-index surfaces, and Ag-induced Si(111) reconstructions. First, the global structural optimizations of neutral aluminum clusters Al n (n up to 23) were performed using a genetic algorithm coupled with a tight-binding potential. Second, a genetic algorithm in combination with tight-binding and first-principles calculations were performed to study the structures of magic clusters on the Si(111) 7 x 7 surface. Extensive calculations show that the magic cluster observed in scanning tunneling microscopy (STM) experiments consist of eight Si atoms. Simulated STM images of the Si magic cluster exhibit a ring-like feature similar to STM experiments. Third, a genetic algorithm coupled with a highly optimized empirical potential were used to determine the lowest energy structure of high-index semiconductor surfaces. The lowest energy structures of Si(105) and Si(114) were determined successfully. The results of Si(105) and Si(114) are reported within the framework of highly optimized empirical potential and first-principles calculations. Finally, a genetic algorithm coupled with Si and Ag tight-binding potentials were used to search for Ag-induced Si(111) reconstructions at various Ag and Si coverages. The optimized structural models of √3 x √3, 3 x 1, and 5 x 2 phases were reported using first-principles calculations. A novel model is found to have lower surface energy than the proposed double-honeycomb chained (DHC) model both for Au/Si(111) 5 x 2 and Ag/Si(111) 5 x 2 systems
Protein diversity in discrete structures at the distal tip of the trypanosome flagellum
Varga, Vladimír; Moreira-Leite, F.; Portman, N.; Gull, K.
2017-01-01
Roč. 114, č. 32 (2017), E6546-E6555 ISSN 0027-8424 Institutional support: RVO:68378050 Keywords : flagellar distal end * trypanosome * flagella connector * axonemal capping structure * structure immunoprecipitation Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Cell biology Impact factor: 9.661, year: 2016
Crystal structure and solid-state properties of discrete hexa cationic ...
Subsequently, weight loss of 33% in two stages from 242 to 691◦C can be assigned to the decomposition of triazole ligands. 3.3 Description of the crystal structure. The solid-state structure of ZnT was unambiguously determined by the single crystal X-ray diffraction tech- nique (figures 2 and 3). Compound ZnT crystallizes in.
Gao Shujing; Chen Lansun
2005-01-01
In this paper, we propose an exploited single-species discrete model with stage structure for the dynamics in a fish population for which births occur in a single pulse once per time period. Using the stroboscopic map, we obtain an exact cycle of the system, and obtain the threshold conditions for its stability. Bifurcation diagrams are constructed with the birth rate as the bifurcation parameter, and these are observed to display complex dynamic behaviors, including chaotic bands with period windows, pitch-fork and tangent bifurcation. This suggests that birth pulse provides a natural period or cyclicity that makes the dynamical behavior more complex. Moreover, we show that the timing of harvesting has a strong impact on the persistence of the fish population, on the volume of mature fish stock and on the maximum annual-sustainable yield. An interesting result is obtained that, after the birth pulse, the earlier culling the mature fish, the larger harvest can tolerate
Optimal Inspection and Repair Strategies for Structural Systems
Sommer, A. M.; Nowak, A. S.; Thoft-Christensen, Palle
1992-01-01
and a design variable as optimization variables. A model for estimating the total expected costs for structural systems is given including the costs associated with the loss of individual structural members as well as the costs associated with the loss of at least one element of a particular group......A model for reliability-based repair and maintenance strategies of structural systems is described. The total expected costs in the lifetime of the structure are minimized with the number of inspections, the number and positions of the inspected points, the inspection efforts, the repair criteria...... of structural members and the costs associated with the simultaneous loss of all members of a specific group of structural members. The approach is based on the pre-posteriori analysis from the classical decision theory. Special emphasis is given to the problem of selecting the number of points in the structure...
Reliability-Based Structural Optimization of Wave Energy Converters
Simon Ambühl
2014-12-01
Full Text Available More and more wave energy converter (WEC concepts are reaching prototypelevel. Once the prototype level is reached, the next step in order to further decrease thelevelized cost of energy (LCOE is optimizing the overall system with a focus on structuraland maintenance (inspection costs, as well as on the harvested power from the waves.The target of a fully-developed WEC technology is not maximizing its power output,but minimizing the resulting LCOE. This paper presents a methodology to optimize thestructural design of WECs based on a reliability-based optimization problem and the intentto maximize the investor’s benefits by maximizing the difference between income (e.g., fromselling electricity and the expected expenses (e.g., structural building costs or failure costs.Furthermore, different development levels, like prototype or commercial devices, may havedifferent main objectives and will be located at different locations, as well as receive varioussubsidies. These points should be accounted for when performing structural optimizationsof WECs. An illustrative example on the gravity-based foundation of the Wavestar deviceis performed showing how structural design can be optimized taking target reliability levelsand different structural failure modes due to extreme loads into account.
Quasi-static structural optimization under the seismic loads
Choi, W. S.; Lee, K. M.; Kim, T. W.
2001-01-01
For preliminaries to optimization of SMART under the seismic loads, a quasi-static structural optimization for elastic structures under dynamic loads is presented. An equivalent static load (ESL) set is defined as a static load set, which generates the same displacement field as that from a dynamic load at a certain time. Multiple ESL sets calculated at all the time intervals are employed to represent the various states of the structure under the dynamic load. They can cover all the critical states that might happen at arbitrary times. The continuous characteristics of a dynamic load are considered by multiple static load sets. The calculated sets of ESLs are utilized as a multiple loading condition in the optimization process. A design cycle is defined as a circulated process between an analysis domain and a design domain. The analysis domain gives the loading condition needed in the design domain. The design domain gives a new updated design to be verified by the analysis domain in the next design cycle. The design cycles are iterated until the design converges. Structural optimization with dynamic loads is tangible by the proposed method. Standard example problems are solved to verify the validity of the method
Wind load modeling for topology optimization of continuum structures
Zakhama, R.; Abdalla, M.M.; Gürdal, Z.; Smaoui, H.
2010-01-01
Topology optimization of two and three dimensional structures subject to dead and wind loading is considered. The wind loading is introduced into the formulation by using standard expressions for the drag force, and a strategy is devised so that wind pressure is ignored where there is no surface
Multiscale topology optimization of solid and fluid structures
Andreasen, Casper Schousboe
This thesis considers the application of the topology optimization method to multiscale problems, specifically the fluid-structure interaction problem. By multiple-scale methods the governing equations, the Navier-Cauchy and the incompressible Navier-Stokes equations are expanded and separated...
A practical multiscale approach for optimization of structural damping
Andreassen, Erik; Jensen, Jakob Søndergaard
2016-01-01
A simple and practical multiscale approach suitable for topology optimization of structural damping in a component ready for additive manufacturing is presented.The approach consists of two steps: First, the homogenized loss factor of a two-phase material is maximized. This is done in order...
Technology of Structural Optimization for Subsidiary in Enterprise ...
pc
2018-03-05
Mar 5, 2018 ... structure optimization for technical registration of enterprise energy resources. ... some apartments, metering of energy resources that consumed in different ... connected to existing wireless subnets of an information net in .... connection reasonabilit y (rates)*. 1. Room No1 Name1. Resides at the zone of.
Topology Optimization of Continuum Structures with Local Stress Constraints
Duysinx, Pierre; Bendsøe, Martin P
1998-01-01
We introduce an extension of current technologies for topology optimization of continuum structures which allows for treating local stress criteria. We first consider relevant stress criteria for porous composite materials, initially by studying the stress states of the so-called rank 2 layered m...
Liu, Lei; Wang, Zhanshan; Zhang, Huaguang
2018-04-01
This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.
Sizing optimization of skeletal structures using teaching-learning based optimization
Vedat Toğan
2017-03-01
Full Text Available Teaching Learning Based Optimization (TLBO is one of the non-traditional techniques to simulate natural phenomena into a numerical algorithm. TLBO mimics teaching learning process occurring between a teacher and students in a classroom. A parameter named as teaching factor, TF, seems to be the only tuning parameter in TLBO. Although the value of the teaching factor, TF, is determined by an equation, the value of 1 or 2 has been used by the researchers for TF. This study intends to explore the effect of the variation of teaching factor TF on the performances of TLBO. This effect is demonstrated in solving structural optimization problems including truss and frame structures under the stress and displacement constraints. The results indicate that the variation of TF in the TLBO process does not change the results obtained at the end of the optimization procedure when the computational cost of TLBO is ignored.
Ferreira, Rodrigo B; Coelli, Fernando C; Pereira, Wagner C A; Almeida, Renan M V R
2008-12-01
This study used the discrete-events computer simulation methodology to model a large hospital surgical centre (SC), in order to analyse the impact of increases in the number of post-anaesthetic beds (PABs), of changes in surgical room scheduling strategies and of increases in surgery numbers. The used inputs were: number of surgeries per day, type of surgical room scheduling, anaesthesia and surgery duration, surgical teams' specialty and number of PABs, and the main outputs were: number of surgeries per day, surgical rooms' use rate and blocking rate, surgical teams' use rate, patients' blocking rate, surgery delays (minutes) and the occurrence of postponed surgeries. Two basic strategies were implemented: in the first strategy, the number of PABs was increased under two assumptions: (a) following the scheduling plan actually used by the hospital (the 'rigid' scheduling - surgical rooms were previously assigned and assignments could not be changed) and (b) following a 'flexible' scheduling (surgical rooms, when available, could be freely used by any surgical team). In the second, the same analysis was performed, increasing the number of patients (up to the system 'feasible maximum') but fixing the number of PABs, in order to evaluate the impact of the number of patients over surgery delays. It was observed that the introduction of a flexible scheduling/increase in PABs would lead to a significant improvement in the SC productivity.
ON DISCRETE STRUCTURE OF GEOLOGIC MEDIUM AND CONTINUAL APPROACH TO MODELING ITS MOVEMENTS
Sh. A. Mukhamediev
2016-01-01
This paper discusses the structure of a geologic medium represented by accessible lithified rocks and provides an overview of methods used to describe its movements. Two basic opinions are considered in the framework of the discussion: (1) an initially homogeneous and continuous geologic medium acquires the structure composed of blocks in the process of the geologic medium’s deformation/destruction/degradation, and (2) a geologic medium is composed of blocks (and often has hierarchic, active,...
ACT Payload Shroud Structural Concept Analysis and Optimization
Zalewski, Bart B.; Bednarcyk, Brett A.
2010-01-01
Aerospace structural applications demand a weight efficient design to perform in a cost effective manner. This is particularly true for launch vehicle structures, where weight is the dominant design driver. The design process typically requires many iterations to ensure that a satisfactory minimum weight has been obtained. Although metallic structures can be weight efficient, composite structures can provide additional weight savings due to their lower density and additional design flexibility. This work presents structural analysis and weight optimization of a composite payload shroud for NASA s Ares V heavy lift vehicle. Two concepts, which were previously determined to be efficient for such a structure are evaluated: a hat stiffened/corrugated panel and a fiber reinforced foam sandwich panel. A composite structural optimization code, HyperSizer, is used to optimize the panel geometry, composite material ply orientations, and sandwich core material. HyperSizer enables an efficient evaluation of thousands of potential designs versus multiple strength and stability-based failure criteria across multiple load cases. HyperSizer sizing process uses a global finite element model to obtain element forces, which are statistically processed to arrive at panel-level design-to loads. These loads are then used to analyze each candidate panel design. A near optimum design is selected as the one with the lowest weight that also provides all positive margins of safety. The stiffness of each newly sized panel or beam component is taken into account in the subsequent finite element analysis. Iteration of analysis/optimization is performed to ensure a converged design. Sizing results for the hat stiffened panel concept and the fiber reinforced foam sandwich concept are presented.
Sørensen, John Aasted
2011-01-01
; construct a finite state machine for a given application. Apply these concepts to new problems. The teaching in Discrete Mathematics is a combination of sessions with lectures and students solving problems, either manually or by using Matlab. Furthermore a selection of projects must be solved and handed...... to accomplish the following: -Understand and apply formal representations in discrete mathematics. -Understand and apply formal representations in problems within discrete mathematics. -Understand methods for solving problems in discrete mathematics. -Apply methods for solving problems in discrete mathematics...... to new problems. Relations and functions: Define a product set; define and apply equivalence relations; construct and apply functions. Apply these concepts to new problems. Natural numbers and induction: Define the natural numbers; apply the principle of induction to verify a selection of properties...
Busch, Peter Andre; Zinner Henriksen, Helle
2018-01-01
discretion is suggested to reduce this footprint by influencing or replacing their discretionary practices using ICT. What is less researched is whether digital discretion can cause changes in public policy outcomes, and under what conditions such changes can occur. Using the concept of public service values......This study reviews 44 peer-reviewed articles on digital discretion published in the period from 1998 to January 2017. Street-level bureaucrats have traditionally had a wide ability to exercise discretion stirring debate since they can add their personal footprint on public policies. Digital......, we suggest that digital discretion can strengthen ethical and democratic values but weaken professional and relational values. Furthermore, we conclude that contextual factors such as considerations made by policy makers on the macro-level and the degree of professionalization of street...
Design optimization and uncertainty analysis of SMA morphing structures
Oehler, S D; Hartl, D J; Lopez, R; Malak, R J; Lagoudas, D C
2012-01-01
The continuing implementation of shape memory alloys (SMAs) as lightweight solid-state actuators in morphing structures has now motivated research into finding optimized designs for use in aerospace control systems. This work proposes methods that use iterative analysis techniques to determine optimized designs for morphing aerostructures and consider the impact of uncertainty in model variables on the solution. A combination of commercially available and custom coded tools is utilized. ModelCenter, a suite of optimization algorithms and simulation process management tools, is coupled with the Abaqus finite element analysis suite and a custom SMA constitutive model to assess morphing structure designs in an automated fashion. The chosen case study involves determining the optimized configuration of a morphing aerostructure assembly that includes SMA flexures. This is accomplished by altering design inputs representing the placement of active components to minimize a specified cost function. An uncertainty analysis is also conducted using design of experiment methods to determine the sensitivity of the solution to a set of uncertainty variables. This second study demonstrates the effective use of Monte Carlo techniques to simulate the variance of model variables representing the inherent uncertainty in component fabrication processes. This paper outlines the modeling tools used to execute each case study, details the procedures for constructing the optimization problem and uncertainty analysis, and highlights the results from both studies. (paper)
Reliability-Based Optimal Design for Very Large Floating Structure
ZHANG Shu-hua(张淑华); FUJIKUBO Masahiko
2003-01-01
Costs and losses induced by possible future extreme environmental conditions and difficulties in repairing post-yielding damage strongly suggest the need for proper consideration in design rather than just life loss prevention. This can be addressed through the development of design methodology that balances the initial cost of the very large floating structure (VLFS) against the expected potential losses resulting from future extreme wave-induced structural damage. Here, the development of a methodology for determining optimal, cost-effective design will be presented and applied to a VLFS located in the Tokyo bay. Optimal design criteria are determined based on the total expected life-cycle cost and acceptable damage probability and curvature of the structure, and a set of sizes of the structure are obtained. The methodology and applications require expressions of the initial cost and the expected life-cycle damage cost as functions of the optimal design variables. This study includes the methodology, total life-cycle cost function, structural damage modeling, and reliability analysis.
Genetic algorithms for optimal design and control of adaptive structures
Ribeiro, R; Dias-Rodrigues, J; Vaz, M
2000-01-01
Future High Energy Physics experiments require the use of light and stable structures to support their most precise radiation detection elements. These large structures must be light, highly stable, stiff and radiation tolerant in an environment where external vibrations, high radiation levels, material aging, temperature and humidity gradients are not negligible. Unforeseen factors and the unknown result of the coupling of environmental conditions, together with external vibrations, may affect the position stability of the detectors and their support structures compromising their physics performance. Careful optimization of static and dynamic behavior must be an essential part of the engineering design. Genetic Algorithms ( GA) belong to the group of probabilistic algorithms, combining elements of direct and stochastic search. They are more robust than existing directed search methods with the advantage of maintaining a population of potential solutions. There is a class of optimization problems for which Ge...
Hiermaier, Stefan
2007-01-01
Required reading for those in the relevant areas of work, this book examines the testing and modeling of materials and structures under dynamic loading conditions.Readers get an in-depth analysis of the current mathematical modeling and simulation tools available for a variety of materials, alongside discussions of the benefits and limitations these tools pose in industrial design.The models discussed are also available in commercial codes such as LS-DYNA and AOTODYN.Following a logical and well organized structure, this volume uniquely combines experimental procedures with numerical simulatio
Hernán Darío Vargas Cardona
2015-07-01
Full Text Available Identification of brain signals from microelectrode recordings (MER is a key procedure during deep brain stimulation (DBS applied in Parkinson’s disease patients. The main purpose of this research work is to identify with high accuracy a brain structure called subthalamic nucleus (STN, since it is the target structure where the DBS achieves the best therapeutic results. To do this, we present an approach for optimal representation of MER signals through method of frames. We obtain coefficients that minimize the Euclidean norm of order two. From optimal coefficients, we extract some features from signals combining the wavelet packet and cosine dictionaries. For a comparison frame with the state of the art, we also process the signals using the discrete wavelet transform (DWT with several mother functions. We validate the proposed methodology in a real data base. We employ simple supervised machine learning algorithms, as the K-Nearest Neighbors classifier (K-NN, a linear Bayesian classifier (LDC and a quadratic Bayesian classifier (QDC. Classification results obtained with the proposed method improves significantly the performance of the DWT. We achieve a positive identification of the STN superior to 97,6%. Identification outcomes achieved by the MOF are highly accurate, as we can potentially get a false positive rate of less than 2% during the DBS.
Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut
2016-05-16
Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.
Physico-Chemical and Structural Interpretation of Discrete Derivative Indices on N-Tuples Atoms
Martínez-Santiago, Oscar; Marrero-Ponce, Yovani; Barigye, Stephen J.; Le Thi Thu, Huong; Torres, F. Javier; Zambrano, Cesar H.; Muñiz Olite, Jorge L.; Cruz-Monteagudo, Maykel; Vivas-Reyes, Ricardo; Vázquez Infante, Liliana; Artiles Martínez, Luis M.
2016-01-01
This report examines the interpretation of the Graph Derivative Indices (GDIs) from three different perspectives (i.e., in structural, steric and electronic terms). It is found that the individual vertex frequencies may be expressed in terms of the geometrical and electronic reactivity of the atoms and bonds, respectively. On the other hand, it is demonstrated that the GDIs are sensitive to progressive structural modifications in terms of: size, ramifications, electronic richness, conjugation effects and molecular symmetry. Moreover, it is observed that the GDIs quantify the interaction capacity among molecules and codify information on the activation entropy. A structure property relationship study reveals that there exists a direct correspondence between the individual frequencies of atoms and Hückel’s Free Valence, as well as between the atomic GDIs and the chemical shift in NMR, which collectively validates the theory that these indices codify steric and electronic information of the atoms in a molecule. Taking in consideration the regularity and coherence found in experiments performed with the GDIs, it is possible to say that GDIs possess plausible interpretation in structural and physicochemical terms. PMID:27240357
Physico-Chemical and Structural Interpretation of Discrete Derivative Indices on N-Tuples Atoms
Oscar Martínez-Santiago
2016-05-01
Full Text Available This report examines the interpretation of the Graph Derivative Indices (GDIs from three different perspectives (i.e., in structural, steric and electronic terms. It is found that the individual vertex frequencies may be expressed in terms of the geometrical and electronic reactivity of the atoms and bonds, respectively. On the other hand, it is demonstrated that the GDIs are sensitive to progressive structural modifications in terms of: size, ramifications, electronic richness, conjugation effects and molecular symmetry. Moreover, it is observed that the GDIs quantify the interaction capacity among molecules and codify information on the activation entropy. A structure property relationship study reveals that there exists a direct correspondence between the individual frequencies of atoms and Hückel’s Free Valence, as well as between the atomic GDIs and the chemical shift in NMR, which collectively validates the theory that these indices codify steric and electronic information of the atoms in a molecule. Taking in consideration the regularity and coherence found in experiments performed with the GDIs, it is possible to say that GDIs possess plausible interpretation in structural and physicochemical terms.
Robust structural optimization using Gauss-type quadrature formula
Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei
2009-01-01
In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the Tensor Product Quadrature (TPQ) formula and the Univariate Dimension Reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.
Robust structural optimization using Gauss-type quadrature formula
Lee, Sang Hoon; Seo, Ki Seog [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Chen, Shikui; Chen, Wei [Northwestern University, Illinois (United States)
2009-07-01
In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the Tensor Product Quadrature (TPQ) formula and the Univariate Dimension Reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.
Robust Structural Optimization Using Gauss-type Quadrature Formula
Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2009-08-15
In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the tensor product quadrature (TPQ) formula and the univariate dimension reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.
Robust Structural Optimization Using Gauss-type Quadrature Formula
Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei
2009-01-01
In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the tensor product quadrature (TPQ) formula and the univariate dimension reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty
Discrete variational Hamiltonian mechanics
Lall, S; West, M
2006-01-01
The main contribution of this paper is to present a canonical choice of a Hamiltonian theory corresponding to the theory of discrete Lagrangian mechanics. We make use of Lagrange duality and follow a path parallel to that used for construction of the Pontryagin principle in optimal control theory. We use duality results regarding sensitivity and separability to show the relationship between generating functions and symplectic integrators. We also discuss connections to optimal control theory and numerical algorithms
Self-similarities of periodic structures for a discrete model of a two-gene system
Souza, S.L.T. de; Lima, A.A.; Caldas, I.L.; Medrano-T, R.O.; Guimarães-Filho, Z.O.
2012-01-01
We report self-similar properties of periodic structures remarkably organized in the two-parameter space for a two-gene system, described by two-dimensional symmetric map. The map consists of difference equations derived from the chemical reactions for gene expression and regulation. We characterize the system by using Lyapunov exponents and isoperiodic diagrams identifying periodic windows, denominated Arnold tongues and shrimp-shaped structures. Period-adding sequences are observed for both periodic windows. We also identify Fibonacci-type series and Golden ratio for Arnold tongues, and period multiple-of-three windows for shrimps. -- Highlights: ► The existence of noticeable periodic windows has been reported recently for several nonlinear systems. ► The periodic window distributions appear highly organized in two-parameter space. ► We characterize self-similar properties of Arnold tongues and shrimps for a two-gene model. ► We determine the period of the Arnold tongues recognizing a Fibonacci-type sequence. ► We explore self-similar features of the shrimps identifying multiple period-three structures.
Dynamic soil-structure interaction analysis based on discretized Green function
Muto, K.; Kobayashi, T.; Nakahara, M.
1983-01-01
In the seismic design of massive and rigid structure such as a nuclear reactor building, it is important to evaluate the dynamic interaction effect between soil and structure. The authors developed an advanced and practical method to evaluate the interaction effect between the soil which is considered to be semi-infinite elastic medium, and the structure in which flexibility is considered. In this report, this method is applied to a seismic analysis of the full size BWR Mark I type reactor building. For horizontal input earthquake, the vibrational degrees of freedom shall be considered both horizontal and vertical as the rocking response occurs because of the overturning moment caused by the building's horizontal response. The results of earthquake response analysis show that the floors deform in-place and the response acceleration at the center of the floor is larger than that of at the side wall. The response spectra also differ each other even if on the same floor because of the in-place deformation of the floor slab. It means that in analytical modeling of the reactor building, multi-stick model considering deformation of floor slab is required instead of single-stick model. The ratio of the peak acceleration response of the roof floor to the input earthquake is about 2.5. (orig./HP)
Self-similarities of periodic structures for a discrete model of a two-gene system
Souza, S.L.T. de, E-mail: thomaz@ufsj.edu.br [Departamento de Física e Matemática, Universidade Federal de São João del-Rei, Ouro Branco, MG (Brazil); Lima, A.A. [Escola de Farmácia, Universidade Federal de Ouro Preto, Ouro Preto, MG (Brazil); Caldas, I.L. [Instituto de Física, Universidade de São Paulo, São Paulo, SP (Brazil); Medrano-T, R.O. [Departamento de Ciências Exatas e da Terra, Universidade Federal de São Paulo, Diadema, SP (Brazil); Guimarães-Filho, Z.O. [Aix-Marseille Univ., CNRS PIIM UMR6633, International Institute for Fusion Science, Marseille (France)
2012-03-12
We report self-similar properties of periodic structures remarkably organized in the two-parameter space for a two-gene system, described by two-dimensional symmetric map. The map consists of difference equations derived from the chemical reactions for gene expression and regulation. We characterize the system by using Lyapunov exponents and isoperiodic diagrams identifying periodic windows, denominated Arnold tongues and shrimp-shaped structures. Period-adding sequences are observed for both periodic windows. We also identify Fibonacci-type series and Golden ratio for Arnold tongues, and period multiple-of-three windows for shrimps. -- Highlights: ► The existence of noticeable periodic windows has been reported recently for several nonlinear systems. ► The periodic window distributions appear highly organized in two-parameter space. ► We characterize self-similar properties of Arnold tongues and shrimps for a two-gene model. ► We determine the period of the Arnold tongues recognizing a Fibonacci-type sequence. ► We explore self-similar features of the shrimps identifying multiple period-three structures.
Utilization of Flexible Airspace Structure in Flight Efficiency Optimization
Tomislav Mihetec
2013-04-01
Full Text Available With increasing air traffic demand in the Pan-European airspace there is a need for optimizing the use of the airspace structure (civilian and military in a manner that would satisfy the requirements of civil and military users. In the area of Europe with the highest levels of air traffic (Core area 32% of the volume of airspace above FL 195 is shared by both civil and military users. Until the introduction of the concept of flexible use of airspace, flexible airspace structures were 24 hours per day unavailable for commercial air transport. Flexible use of airspace concept provides a substantial level of dynamic airspace management by the usage of conditional routes. This paper analyses underutilization of resources, flexible airspace structures in the Pan-European airspace, especially in the south-eastern part of the traffic flows (East South Axis, reducing the efficiency of flight operations, as result of delegating the flexible structures to military users. Based on previous analysis, utilization model for flexible use of airspace is developed (scenarios with defined airspace structure. The model is based on the temporal, vertical, and modular airspace sectorisation parameters in order to optimize flight efficiency. The presented model brings significant improvement in flight efficiency (in terms of reduced flight distance for air carriers that planned to fly through the selected flexible airspace structure (LI_RST-49.
Optimal simultaneous superpositioning of multiple structures with missing data.
Theobald, Douglas L; Steindel, Phillip A
2012-08-01
Superpositioning is an essential technique in structural biology that facilitates the comparison and analysis of conformational differences among topologically similar structures. Performing a superposition requires a one-to-one correspondence, or alignment, of the point sets in the different structures. However, in practice, some points are usually 'missing' from several structures, for example, when the alignment contains gaps. Current superposition methods deal with missing data simply by superpositioning a subset of points that are shared among all the structures. This practice is inefficient, as it ignores important data, and it fails to satisfy the common least-squares criterion. In the extreme, disregarding missing positions prohibits the calculation of a superposition altogether. Here, we present a general solution for determining an optimal superposition when some of the data are missing. We use the expectation-maximization algorithm, a classic statistical technique for dealing with incomplete data, to find both maximum-likelihood solutions and the optimal least-squares solution as a special case. The methods presented here are implemented in THESEUS 2.0, a program for superpositioning macromolecular structures. ANSI C source code and selected compiled binaries for various computing platforms are freely available under the GNU open source license from http://www.theseus3d.org. dtheobald@brandeis.edu Supplementary data are available at Bioinformatics online.
M. Christobel
2015-01-01
Full Text Available One of the most significant and the topmost parameters in the real world computing environment is energy. Minimizing energy imposes benefits like reduction in power consumption, decrease in cooling rates of the computing processors, provision of a green environment, and so forth. In fact, computation time and energy are directly proportional to each other and the minimization of computation time may yield a cost effective energy consumption. Proficient scheduling of Bag-of-Tasks in the grid environment ravages in minimum computation time. In this paper, a novel discrete particle swarm optimization (DPSO algorithm based on the particle’s best position (pbDPSO and global best position (gbDPSO is adopted to find the global optimal solution for higher dimensions. This novel DPSO yields better schedule with minimum computation time compared to Earliest Deadline First (EDF and First Come First Serve (FCFS algorithms which comparably reduces energy. Other scheduling parameters, such as job completion ratio and lateness, are also calculated and compared with EDF and FCFS. An energy improvement of up to 28% was obtained when Makespan Conservative Energy Reduction (MCER and Dynamic Voltage Scaling (DVS were used in the proposed DPSO algorithm.
Christobel, M.; Tamil Selvi, S.; Benedict, Shajulin
2015-01-01
One of the most significant and the topmost parameters in the real world computing environment is energy. Minimizing energy imposes benefits like reduction in power consumption, decrease in cooling rates of the computing processors, provision of a green environment, and so forth. In fact, computation time and energy are directly proportional to each other and the minimization of computation time may yield a cost effective energy consumption. Proficient scheduling of Bag-of-Tasks in the grid environment ravages in minimum computation time. In this paper, a novel discrete particle swarm optimization (DPSO) algorithm based on the particle's best position (pbDPSO) and global best position (gbDPSO) is adopted to find the global optimal solution for higher dimensions. This novel DPSO yields better schedule with minimum computation time compared to Earliest Deadline First (EDF) and First Come First Serve (FCFS) algorithms which comparably reduces energy. Other scheduling parameters, such as job completion ratio and lateness, are also calculated and compared with EDF and FCFS. An energy improvement of up to 28% was obtained when Makespan Conservative Energy Reduction (MCER) and Dynamic Voltage Scaling (DVS) were used in the proposed DPSO algorithm. PMID:26075296
Fast optimization of statistical potentials for structurally constrained phylogenetic models
Rodrigue Nicolas
2009-09-01
Full Text Available Abstract Background Statistical approaches for protein design are relevant in the field of molecular evolutionary studies. In recent years, new, so-called structurally constrained (SC models of protein-coding sequence evolution have been proposed, which use statistical potentials to assess sequence-structure compatibility. In a previous work, we defined a statistical framework for optimizing knowledge-based potentials especially suited to SC models. Our method used the maximum likelihood principle and provided what we call the joint potentials. However, the method required numerical estimations by the use of computationally heavy Markov Chain Monte Carlo sampling algorithms. Results Here, we develop an alternative optimization procedure, based on a leave-one-out argument coupled to fast gradient descent algorithms. We assess that the leave-one-out potential yields very similar results to the joint approach developed previously, both in terms of the resulting potential parameters, and by Bayes factor evaluation in a phylogenetic context. On the other hand, the leave-one-out approach results in a considerable computational benefit (up to a 1,000 fold decrease in computational time for the optimization procedure. Conclusion Due to its computational speed, the optimization method we propose offers an attractive alternative for the design and empirical evaluation of alternative forms of potentials, using large data sets and high-dimensional parameterizations.
Shock aurora: Field-aligned discrete structures moving along the dawnside oval
Zhou, Xiaoyan; Haerendel, Gerhard; Moen, Jøran I.; Trondsen, Espen; Clausen, Lasse; Strangeway, Robert J.; Lybekk, Bjørn; Lorentzen, Dag A.
2017-03-01
Generated by interplanetary shocks or solar wind pressure pulses, shock aurora has transient, global, and dynamic significances and provides a direct manifestation of the solar wind-magnetosphere-ionosphere interaction. As a part of a series of studies of the shock aurora, this paper focuses on the interaction at the morning magnetopause and its auroral manifestation at 06 magnetic local time, where the velocity and magnetic field shears dominate the interaction. Flow shears can generate wave-like structures inside a viscous boundary layer or even larger-scale vortices. These structures couple to the ionosphere via quasi-static field-aligned currents or via kinetic Alfvén waves. Potential drops along field-aligned filaments may be generated accelerating electrons to form auroral manifestations of the structures. A shock aurora event at dawnside is used to test this scenario. The findings include moving auroral streaks/rays that have a vertical profile from red (at 250 km altitude) to purple (at 100 km). The streaks moved antisunward along the poleward boundary of the oval at an ionospheric speed of 3 km s-1. It was mapped to the magnetopause flank at 133 km s-1, which was consistent with the observed speed of the magnetopause surface waves generated by the Kelvin-Helmholtz instability. The calculated field-aligned potential drop using Haerendel's analytic model was 5 kV that reasonably explained the observations. The results support the above scenario and reveal that magnetic and velocity shears at the flanks of the magnetospause may be the main cause of the fast moving shock aurora streaks.
Fedrigo, Melissa; Newnham, Glenn J.; Coops, Nicholas C.; Culvenor, Darius S.; Bolton, Douglas K.; Nitschke, Craig R.
2018-02-01
Light detection and ranging (lidar) data have been increasingly used for forest classification due to its ability to penetrate the forest canopy and provide detail about the structure of the lower strata. In this study we demonstrate forest classification approaches using airborne lidar data as inputs to random forest and linear unmixing classification algorithms. Our results demonstrated that both random forest and linear unmixing models identified a distribution of rainforest and eucalypt stands that was comparable to existing ecological vegetation class (EVC) maps based primarily on manual interpretation of high resolution aerial imagery. Rainforest stands were also identified in the region that have not previously been identified in the EVC maps. The transition between stand types was better characterised by the random forest modelling approach. In contrast, the linear unmixing model placed greater emphasis on field plots selected as endmembers which may not have captured the variability in stand structure within a single stand type. The random forest model had the highest overall accuracy (84%) and Cohen's kappa coefficient (0.62). However, the classification accuracy was only marginally better than linear unmixing. The random forest model was applied to a region in the Central Highlands of south-eastern Australia to produce maps of stand type probability, including areas of transition (the 'ecotone') between rainforest and eucalypt forest. The resulting map provided a detailed delineation of forest classes, which specifically recognised the coalescing of stand types at the landscape scale. This represents a key step towards mapping the structural and spatial complexity of these ecosystems, which is important for both their management and conservation.
Problem statement for optimal design of steel structures
Ginzburg Aleksandr Vital'evich
2014-07-01
task it can be offered to use informational technologies and opportunities of automated systems. For this purpose it is necessary to develop the automated system of steel designs, allowing to consider some criteria of optimality and a wide range of the restrictions for steel structural designs. This will allow to accelerate projection process, to reduce labor input of a designer and essentially increase the quality of design solutions for steel designs.
Hybrid Optimization in the Design of Reciprocal Structures
Parigi, Dario; Kirkegaard, Poul Henning; Sassone, Mario
2012-01-01
that explore the global domain of solutions as genetic algorithms (GAs). The benchmark tests show that when the control on the topology is required the best result is obtained by a hybrid approach that combines the global search of the GA with the local search of a GB algorithm. The optimization method......The paper presents a method to generate the geometry of reciprocal structures by means of a hybrid optimization procedure. The geometry of reciprocal structures where elements are sitting on the top or in the bottom of each other is extremely difficult to predict because of the non....... In this paper it is shown that the geometrically compatible position of the elements could be determined by local search algorithm gradient-based (GB). However the control on which bar sit on the top or in the bottom at each connection can be regarded as a topological problem and require the use of algorithms...
Matthew J. Clement
2012-01-01
Full Text Available Mustached bats, Pteronotus parnellii, are highly social and vocal. Individuals of this species roost in tight clusters, and emit an acoustically rich repertoire of calls whose behavioral significance is largely unknown. We recorded their social and vocal behaviors within a colony housed under semi-natural conditions. We also quantified the spatial spread of each bat’s roosting location and discovered that this was relatively fixed and roughly confined to an individual’s body width. The spatial precision in roosting was accompanied by an equally remarkable match between specific vocalizations and well-timed, discrete, identifiable postures/behaviors, as revealed by logistic regression analysis. The bodily behaviors included crouching, marking, yawning, nipping, flicking, fighting, kissing, inspecting, and fly-bys. Two echolocation-like calls were used to maintain spacing in the colony, two noisy broadband calls were emitted during fights, two tonal calls conveyed fear, and another tonal call signaled appeasement. Overall, the results establish that mustached bats exhibit complex social interactions common to other social mammals. The correspondence of relatively low frequency and noisy, broadband calls with aggression, and of tonal, high frequency calls with fear supports Morton’s Motivation-Structure hypothesis, and establishes a link between motivation and the acoustic structure of social calls emitted by mustached bats.
Sørensen, John Aasted
2010-01-01
The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Spring 2010 Ectent: 5 ects Class size: 18......The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Spring 2010 Ectent: 5 ects Class size: 18...
Sørensen, John Aasted
2010-01-01
The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Autumn 2010 Ectent: 5 ects Class size: 15......The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Autumn 2010 Ectent: 5 ects Class size: 15...
A Low Cost Structurally Optimized Design for Diverse Filter Types
Kazmi, Majida; Aziz, Arshad; Akhtar, Pervez; Ikram, Nassar
2016-01-01
A wide range of image processing applications deploys two dimensional (2D)-filters for performing diversified tasks such as image enhancement, edge detection, noise suppression, multi scale decomposition and compression etc. All of these tasks require multiple type of 2D-filters simultaneously to acquire the desired results. The resource hungry conventional approach is not a viable option for implementing these computationally intensive 2D-filters especially in a resource constraint environment. Thus it calls for optimized solutions. Mostly the optimization of these filters are based on exploiting structural properties. A common shortcoming of all previously reported optimized approaches is their restricted applicability only for a specific filter type. These narrow scoped solutions completely disregard the versatility attribute of advanced image processing applications and in turn offset their effectiveness while implementing a complete application. This paper presents an efficient framework which exploits the structural properties of 2D-filters for effectually reducing its computational cost along with an added advantage of versatility for supporting diverse filter types. A composite symmetric filter structure is introduced which exploits the identities of quadrant and circular T-symmetries in two distinct filter regions simultaneously. These T-symmetries effectually reduce the number of filter coefficients and consequently its multipliers count. The proposed framework at the same time empowers this composite filter structure with additional capabilities of realizing all of its Ψ-symmetry based subtypes and also its special asymmetric filters case. The two-fold optimized framework thus reduces filter computational cost up to 75% as compared to the conventional approach as well as its versatility attribute not only supports diverse filter types but also offers further cost reduction via resource sharing for sequential implementation of diversified image
MICRONEEDLE STRUCTURE DESIGN AND OPTIMIZATION USING GENETIC ALGORITHM
N. A. ISMAIL; S. C. NEOH; N. SABANI; B. N. TAIB
2015-01-01
This paper presents a Genetic Algorithm (GA) based microneedle design and analysis. GA is an evolutionary optimization technique that mimics the natural biological evolution. The design of microneedle structure considers the shape of microneedle, material used, size of the array, the base of microneedle, the lumen base, the height of microneedle, the height of the lumen, and the height of the drug container or reservoir. The GA is executed in conjunction with ANSYS simulation system to assess...
Structural analysis and optimization procedure of the TFTR device substructure
Driesen, G.
1975-10-01
A structural evaluation of the TFTR device substructure is performed in order to verify the feasibility of the proposed design concept as well as to establish a design optimization procedure for minimizing the material and fabrication cost of the substructure members. A preliminary evaluation of the seismic capability is also presented. The design concept on which the analysis is based is consistent with that described in the Conceptual Design Status Briefing report dated June 18, 1975
Topology optimization of coated structures and material interface problems
Clausen, Anders; Aage, Niels; Sigmund, Ole
2015-01-01
This paper presents a novel method for including coated structures and prescribed material interface properties into the minimum compliance topology optimization problem. Several elements of the method are applicable to a broader range of interface problems. The approach extends the standard SIMP......-step filtering/projection approach. The modeled coating thickness is derived analytically, and the coating is shown to be accurately controlled and applied in a highly uniform manner over the structure. An alternative interpretation of the model is to perform single-material design for additive manufacturing...
Structure optimization of CFB reactor for moderate temperature FGD
Li, Yuan; Zhang, Jie; Zheng, Kai; You, Changfu [Tsinghua Univ., Beijing (China). Dept. of Thermal Engineering; Ministry of Education, Beijing (China). Key Lab. for Thermal Science and Power Engineering
2013-07-01
The gas velocity distribution, sorbent particle concentration distribution and particle residence time in circulating fluidized bed (CFB) reactors for moderate temperature flue gas desulfurization (FGD) have significant influence on the desulfurization efficiency and the sorbent calcium conversion ratio for sulfur reaction. Experimental and numerical methods were used to investigate the influence of the key reactor structures, including the reactor outlet structure, internal structure, feed port and circulating port, on the gas velocity distribution, sorbent particle concentration distribution and particle residence time. Experimental results showed that the desulfurization efficiency increased 5-10% when the internal structure was added in the CFB reactor. Numerical analysis results showed that the particle residence time of the feed particles with the average diameter of 89 and 9 {mu}m increased 40% and 17% respectively, and the particle residence time of the circulating particles with the average diameter of 116 {mu}m increased 28% after reactor structure optimization. The particle concentration distribution also improved significantly, which was good for improving the contact efficiency between the sorbent particles and SO{sub 2}. In addition, the optimization guidelines were proposed to further increase the desulfurization efficiency and the sorbent calcium conversion ratio.
Targeted Structural Optimization with Additive Manufacturing of Metals
Burt, Adam; Hull, Patrick
2015-01-01
The recent advances in additive manufacturing (AM) of metals have now improved the state-of-the-art such that traditionally non-producible parts can be readily produced in a cost-effective way. Because of these advances in manufacturing technology, structural optimization techniques are well positioned to supplement and advance this new technology. The goal of this project is to develop a structural design, analysis, and optimization framework combined with AM to significantly light-weight the interior of metallic structures while maintaining the selected structural properties of the original solid. This is a new state-of-the-art capability to significantly reduce mass, while maintaining the structural integrity of the original design, something that can only be done with AM. In addition, this framework will couple the design, analysis, and fabrication process, meaning that what has been designed directly represents the produced part, thus closing the loop on the design cycle and removing human iteration between design and fabrication. This fundamental concept has applications from light-weighting launch vehicle components to in situ resource fabrication.
Structural Optimization of Triboelectric Nanogenerator for Harvesting Water Wave Energy.
Jiang, Tao; Zhang, Li Min; Chen, Xiangyu; Han, Chang Bao; Tang, Wei; Zhang, Chi; Xu, Liang; Wang, Zhong Lin
2015-12-22
Ocean waves are one of the most abundant energy sources on earth, but harvesting such energy is rather challenging due to various limitations of current technologies. Recently, networks formed by triboelectric nanogenerator (TENG) have been proposed as a promising technology for harvesting water wave energy. In this work, a basic unit for the TENG network was studied and optimized, which has a box structure composed of walls made of TENG composed of a wavy-structured Cu-Kapton-Cu film and two FEP thin films, with a metal ball enclosed inside. By combination of the theoretical calculations and experimental studies, the output performances of the TENG unit were investigated for various structural parameters, such as the size, mass, or number of the metal balls. From the viewpoint of theory, the output characteristics of TENG during its collision with the ball were numerically calculated by the finite element method and interpolation method, and there exists an optimum ball size or mass to reach maximized output power and electric energy. Moreover, the theoretical results were well verified by the experimental tests. The present work could provide guidance for structural optimization of wavy-structured TENGs for effectively harvesting water wave energy toward the dream of large-scale blue energy.
Optimal neural networks for protein-structure prediction
Head-Gordon, T.; Stillinger, F.H.
1993-01-01
The successful application of neural-network algorithms for prediction of protein structure is stymied by three problem areas: the sparsity of the database of known protein structures, poorly devised network architectures which make the input-output mapping opaque, and a global optimization problem in the multiple-minima space of the network variables. We present a simplified polypeptide model residing in two dimensions with only two amino-acid types, A and B, which allows the determination of the global energy structure for all possible sequences of pentamer, hexamer, and heptamer lengths. This model simplicity allows us to compile a complete structural database and to devise neural networks that reproduce the tertiary structure of all sequences with absolute accuracy and with the smallest number of network variables. These optimal networks reveal that the three problem areas are convoluted, but that thoughtful network designs can actually deconvolute these detrimental traits to provide network algorithms that genuinely impact on the ability of the network to generalize or learn the desired mappings. Furthermore, the two-dimensional polypeptide model shows sufficient chemical complexity so that transfer of neural-network technology to more realistic three-dimensional proteins is evident
Two new discrete integrable systems
Chen Xiao-Hong; Zhang Hong-Qing
2013-01-01
In this paper, we focus on the construction of new (1+1)-dimensional discrete integrable systems according to a subalgebra of loop algebra Ã 1 . By designing two new (1+1)-dimensional discrete spectral problems, two new discrete integrable systems are obtained, namely, a 2-field lattice hierarchy and a 3-field lattice hierarchy. When deriving the two new discrete integrable systems, we find the generalized relativistic Toda lattice hierarchy and the generalized modified Toda lattice hierarchy. Moreover, we also obtain the Hamiltonian structures of the two lattice hierarchies by means of the discrete trace identity
An expert system for integrated structural analysis and design optimization for aerospace structures
1992-04-01
The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and
Approximate Schur complement preconditioning of the lowest order nodal discretizations
Moulton, J.D.; Ascher, U.M. [Univ. of British Columbia, Vancouver, British Columbia (Canada); Morel, J.E. [Los Alamos National Lab., NM (United States)
1996-12-31
Particular classes of nodal methods and mixed hybrid finite element methods lead to equivalent, robust and accurate discretizations of 2nd order elliptic PDEs. However, widespread popularity of these discretizations has been hindered by the awkward linear systems which result. The present work exploits this awkwardness, which provides a natural partitioning of the linear system, by defining two optimal preconditioners based on approximate Schur complements. Central to the optimal performance of these preconditioners is their sparsity structure which is compatible with Dendy`s black box multigrid code.
Prinz, Jan-Hendrik; Chodera, John D; Pande, Vijay S; Swope, William C; Smith, Jeremy C; Noé, Frank
2011-06-28
Parallel tempering (PT) molecular dynamics simulations have been extensively investigated as a means of efficient sampling of the configurations of biomolecular systems. Recent work has demonstrated how the short physical trajectories generated in PT simulations of biomolecules can be used to construct the Markov models describing biomolecular dynamics at each simulated temperature. While this approach describes the temperature-dependent kinetics, it does not make optimal use of all available PT data, instead estimating the rates at a given temperature using only data from that temperature. This can be problematic, as some relevant transitions or states may not be sufficiently sampled at the temperature of interest, but might be readily sampled at nearby temperatures. Further, the comparison of temperature-dependent properties can suffer from the false assumption that data collected from different temperatures are uncorrelated. We propose here a strategy in which, by a simple modification of the PT protocol, the harvested trajectories can be reweighted, permitting data from all temperatures to contribute to the estimated kinetic model. The method reduces the statistical uncertainty in the kinetic model relative to the single temperature approach and provides estimates of transition probabilities even for transitions not observed at the temperature of interest. Further, the method allows the kinetics to be estimated at temperatures other than those at which simulations were run. We illustrate this method by applying it to the generation of a Markov model of the conformational dynamics of the solvated terminally blocked alanine peptide.
Improving the Dynamic Characteristics of Body-in-White Structure Using Structural Optimization
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.
Optimal ground motion intensity measure for long-period structures
Guan, Minsheng; Du, Hongbiao; Zeng, Qingli; Cui, Jie; Jiang, Haibo
2015-01-01
This paper aims to select the most appropriate ground motion intensity measure (IM) that is used in selecting earthquake records for the dynamic time history analysis of long-period structures. For this purpose, six reinforced concrete frame-core wall structures, designed according to modern seismic codes, are studied through dynamic time history analyses with a set of twelve selected earthquake records. Twelve IMs and two types of seismic damage indices, namely, the maximum seismic response-based and energy-based parameters, are chosen as the examined indices. Selection criteria such as correlation, efficiency, and proficiency are considered in the selection process. The optimal IM is identified by means of a comprehensive evaluation using a large number of data of correlation, efficiency, and proficiency coefficients. Numerical results illustrate that peak ground velocity is the optimal one for long-period structures and peak ground displacement is also a close contender. As compared to previous reports, the spectral-correlated parameters can only be taken as moderate IMs. Moreover, the widely used peak ground acceleration in the current seismic codes is considered inappropriate for long-period structures. (paper)
Unimodal optimal passive electromechanical damping of elastic structures
Ben Mekki, O; Bourquin, F; Merliot, E; Maceri, F
2013-01-01
In this paper, a new electromechanical damper is presented and used, made of a pendulum oscillating around an alternator axis and connected by a gear to the vibrating structure. In this way, the mechanical energy of the oscillating mass can be transformed into electrical energy to be dissipated when the alternator is branched on a resistor. This damping device is intrinsically non-linear, and the problem of the optimal parameters and of the best placement of this damper on the structure is studied. The optimality criterion chosen here is the maximum exponential time decay rate (ETDR) of the structural response. This criterion leads to new design formulas. The case of a bridge under construction is considered and the analytical results are compared with experimental ones, obtained on a mock-up made of a vertical tower connected to a free-end horizontal beam, to simulate the behavior of a cable-stayed bridge during the erection phase. Up to three electromechanical dampers are placed in order to study the multi-modal damping. The satisfactory agreement between the theoretical model and the experiments suggests that a multi-modal passive damping of electromagnetic type could be effective on lightweight flexible structures, when dampers are suitably placed. (paper)
Venter, Gerhard; Sobieszczanski-Sobieski Jaroslaw
2002-01-01
The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of the algorithm, Results of numerical experiments for both continuous and discrete applications are presented in the paper. The results indicate that the particle swarm optimization algorithm does locate the constrained minimum design in continuous applications with very good precision, albeit at a much higher computational cost than that of a typical gradient based optimizer. However, the true potential of particle swarm optimization is primarily in applications with discrete and/or discontinuous functions and variables. Additionally, particle swarm optimization has the potential of efficient computation with very large numbers of concurrently operating processors.
Integrated Multidisciplinary Constrained Optimization of Offshore Support Structures
Haghi, Rad; Molenaar, David P; Ashuri, Turaj; Van der Valk, Paul L C
2014-01-01
In the current offshore wind turbine support structure design method, the tower and foundation, which form the support structure are designed separately by the turbine and foundation designer. This method yields a suboptimal design and it results in a heavy, overdesigned and expensive support structure. This paper presents an integrated multidisciplinary approach to design the tower and foundation simultaneously. Aerodynamics, hydrodynamics, structure and soil mechanics are the modeled disciplines to capture the full dynamic behavior of the foundation and tower under different environmental conditions. The objective function to be minimized is the mass of the support structure. The model includes various design constraints: local and global buckling, modal frequencies, and fatigue damage along different stations of the structure. To show the usefulness of the method, an existing SWT-3.6-107 offshore wind turbine where its tower and foundation are designed separately is used as a case study. The result of the integrated multidisciplinary design optimization shows 12.1% reduction in the mass of the support structure, while satisfying all the design constraints
The maintenance optimization of structural components in nuclear power plants
Bryla, P.; Ardorino, F.; Aufort, P.; Jacquot, J.P.; Magne, L.; Pitner, P.; Verite, B.; Villain, B.; Monnier, B.
1997-10-01
An optimization process, called 'OMF-Structures', is developed by Electricite de France (EDF) in order to extend the current 'OMF' Reliability Centered Maintenance to piping structural components. The Auxiliary Feedwater System of a 900 MW French nuclear plant has been studied in order to lay the foundations of the method. This paper presents the currently proposed principles of the process. The principles of the OMF-Structures process include 'Risk-Based Inspection' concepts within an RCM process. Two main phases are identified: The purpose of the first phase is to select the risk-significant failure modes and associated elements. This phase consists of two major steps: potential consequences evaluation and reliability performance evaluation. The second phase consists of the definition of preventive maintenance programs for piping elements that are associated with risk-significant failure modes. (author)
Structure Optimization of Safety Investment of Petrochemical Port Enterprises
Zhiqiang Hou
2017-01-01
Full Text Available Safety investment is an essential guarantee to identify and manage potential security problems in petrochemical port enterprises. The reasonability of safety investment structure determines overall security risks in an enterprise. Based on the definition of risks, combining Cobb-Douglas production function with FTA probability model, and taking Gompertz curve model as the constraint condition, structure optimization model of safety investment is built in order to minimize risks and work out the safety investment structure of petrochemical port enterprises. According to the case study, the calculations indicate that safety investment in corporate management presents a larger growth rate than past years and that unsafe act of human being is the main factor accounting for the greatest probability of occurrence, which is consistent with previous accident investigation results as well as enterprise reality. This testifies that the model is effective and that the results can guide the allocation of safety investment of petrochemical port enterprises scientifically.
Lian, Jijian; He, Longjun; Ma, Bin; Peng, Wenxiang; Li, Huokun
2013-01-01
Research on optimal sensor placement (OSP) has become very important due to the need to obtain effective testing results with limited testing resources in health monitoring. In this study, a new methodology is proposed to select the best sensor locations for large structures. First, a novel fitness function derived from the nearest neighbour index is proposed to overcome the drawbacks of the effective independence method for OSP for large structures. This method maximizes the contribution of each sensor to modal observability and simultaneously avoids the redundancy of information between the selected degrees of freedom. A hybrid algorithm combining the improved discrete particle swarm optimization (DPSO) with the clonal selection algorithm is then implemented to optimize the proposed fitness function effectively. Finally, the proposed method is applied to an arch dam for performance verification. The results show that the proposed hybrid swarm intelligence algorithm outperforms a genetic algorithm with decimal two-dimension array encoding and DPSO in the capability of global optimization. The new fitness function is advantageous in terms of sensor distribution and ensuring a well-conditioned information matrix and orthogonality of modes, indicating that this method may be used to provide guidance for OSP in various large structures. (paper)
A database structure for radiological optimization analyses of decommissioning operations
Zeevaert, T.; Van de Walle, B.
1995-09-01
The structure of a database for decommissioning experiences is described. Radiological optimization is a major radiation protection principle in practices and interventions, involving radiological protection factors, economic costs, social factors. An important lack of knowledge with respect to these factors exists in the domain of the decommissioning of nuclear power plants, due to the low number of decommissioning operations already performed. Moreover, decommissioning takes place only once for a installation. Tasks, techniques, and procedures are in most cases rather specific, limiting the use of past experiences in the radiological optimization analyses of new decommissioning operations. Therefore, it is important that relevant data or information be acquired from decommissioning experiences. These data have to be stored in a database in a way they can be used efficiently in ALARA analyses of future decommissioning activities
Decentralized Optimization for a Novel Control Structure of HVAC System
Shiqiang Wang
2016-01-01
Full Text Available A decentralized control structure is introduced into the heating, ventilation, and air conditioning (HVAC system to solve the high maintenance and labor cost problem in actual engineering. Based on this new control system, a decentralized optimization method is presented for sensor fault repair and optimal group control of HVAC equipment. Convergence property of the novel method is theoretically analyzed considering both convex and nonconvex systems with constraints. In this decentralized control system, traditional device is fitted with a control chip such that it becomes a smart device. The smart device can communicate and operate collaboratively with the other devices to accomplish some designated tasks. The effectiveness of the presented method is verified by simulations and hardware tests.
Optimization of SMA layers in composite structures to enhance damping
Haghdoust, P.; Cinquemani, S.; Lecis, N.; Bassani, P.
2016-04-01
The performance of lightweight structures can be severely affected by vibration. New design concepts leading to lightweight, slender structural components can increase the vulnerability of the components to failure due to excessive vibration. The intelligent approach to address the problem would be the use of materials which are more capable in dissipating the energy due to their high value of loss factor. Among the different materials available to achieve damping, much attention has been attached to the use of shape memory alloys (SMAs) because of their unique microstructure, leading to good damping capacity. This work describes the design and optimization of a hybrid layered composite structure for the passive suppression of flexural vibrations in slender and light structures. Embedding the SMA layers in composite structure allows to combine different properties: the lightness of the base composite (e.g. fiber glass), the mechanical strength of the insert of metallic material and the relevant damping properties of SMA, in the martensitic phase. In particular, we put our attention on embedding the CuZnAl in the form of thin sheet in a layered composite made by glass fiber reinforced epoxy. By appropriately positioning of the SMA sheets so that they are subjected to the maximum curvature, the damping of the hybrid system can be considerably enhanced. Accordingly analytical method for evaluating the energy dissipation of the thin sheets with different shapes and patterns is developed and is followed by a shape optimization based on genetic algorithm. Eventually different configurations of the hybrid beam structure with different patterns of SMA layer are proposed and compared in the term of damping capacity.
Hu, Weifei; Park, Dohyun; Choi, DongHoon
2013-12-01
A composite blade structure for a 2 MW horizontal axis wind turbine is optimally designed. Design requirements are simultaneously minimizing material cost and blade weight while satisfying the constraints on stress ratio, tip deflection, fatigue life and laminate layup requirements. The stress ratio and tip deflection under extreme gust loads and the fatigue life under a stochastic normal wind load are evaluated. A blade element wind load model is proposed to explain the wind pressure difference due to blade height change during rotor rotation. For fatigue life evaluation, the stress result of an implicit nonlinear dynamic analysis under a time-varying fluctuating wind is converted to the histograms of mean and amplitude of maximum stress ratio using the rainflow counting algorithm Miner's rule is employed to predict the fatigue life. After integrating and automating the whole analysis procedure an evolutionary algorithm is used to solve the discrete optimization problem.
Blumer-Schuette, Sara E; Alahuhta, Markus; Conway, Jonathan M; Lee, Laura L; Zurawski, Jeffrey V; Giannone, Richard J; Hettich, Robert L; Lunin, Vladimir V; Himmel, Michael E; Kelly, Robert M
2015-04-24
A variety of catalytic and noncatalytic protein domains are deployed by select microorganisms to deconstruct lignocellulose. These extracellular proteins are used to attach to, modify, and hydrolyze the complex polysaccharides present in plant cell walls. Cellulolytic enzymes, often containing carbohydrate-binding modules, are key to this process; however, these enzymes are not solely responsible for attachment. Few mechanisms of attachment have been discovered among bacteria that do not form large polypeptide structures, called cellulosomes, to deconstruct biomass. In this study, bioinformatics and proteomics analyses identified unique, discrete, hypothetical proteins ("tāpirins," origin from Māori: to join), not directly associated with cellulases, that mediate attachment to cellulose by species in the noncellulosomal, extremely thermophilic bacterial genus Caldicellulosiruptor. Two tāpirin genes are located directly downstream of a type IV pilus operon in strongly cellulolytic members of the genus, whereas homologs are absent from the weakly cellulolytic Caldicellulosiruptor species. Based on their amino acid sequence, tāpirins are specific to these extreme thermophiles. Tāpirins are also unusual in that they share no detectable protein domain signatures with known polysaccharide-binding proteins. Adsorption isotherm and trans vivo analyses demonstrated the carbohydrate-binding module-like affinity of the tāpirins for cellulose. Crystallization of a cellulose-binding truncation from one tāpirin indicated that these proteins form a long β-helix core with a shielded hydrophobic face. Furthermore, they are structurally unique and define a new class of polysaccharide adhesins. Strongly cellulolytic Caldicellulosiruptor species employ tāpirins to complement substrate-binding proteins from the ATP-binding cassette transporters and multidomain extracellular and S-layer-associated glycoside hydrolases to process the carbohydrate content of lignocellulose.
Caltagirone, Jean-Paul
2014-01-01
This book presents the fundamental principles of mechanics to re-establish the equations of Discrete Mechanics. It introduces physics and thermodynamics associated to the physical modeling. The development and the complementarity of sciences lead to review today the old concepts that were the basis for the development of continuum mechanics. The differential geometry is used to review the conservation laws of mechanics. For instance, this formalism requires a different location of vector and scalar quantities in space. The equations of Discrete Mechanics form a system of equations where the H
Lee, T.D.
1985-01-01
This paper reviews the role of time throughout all phases of mechanics: classical mechanics, non-relativistic quantum mechanics, and relativistic quantum theory. As an example of the relativistic quantum field theory, the case of a massless scalar field interacting with an arbitrary external current is discussed. The comparison between the new discrete theory and the usual continuum formalism is presented. An example is given of a two-dimensional random lattice and its duel. The author notes that there is no evidence that the discrete mechanics is more appropriate than the usual continuum mechanics
Ding, Yi; Goel, Lalit; Wang, Peng
2012-01-01
cost of the system will also increase. The reserve structure of a MSS should be determined based on striking a balance between the required reliability and the reserve cost. The objective of reserve management for a MSS is to schedule the reserve at the minimum system reserve cost while maintaining......Electric power generating systems are typical examples of multi-state systems (MSS). Sufficient reserve is critically important for maintaining generating system reliabilities. The reliability of a system can be increased by increasing the reserve capacity, noting that at the same time the reserve...... the required level of supply reliability to its customers. In previous research, Genetic Algorithm (GA) has been used to solve most reliability optimization problems. However, the GA is not very computationally efficient in some cases. In this chapter a new heuristic optimization technique—the particle swarm...
Seifbarghy, Mehdi; Kalani, Masoud Mirzaei; Hemmati, Mojtaba
2016-03-01
This paper formulates a two-echelon single-producer multi-buyer supply chain model, while a single product is produced and transported to the buyers by the producer. The producer and the buyers apply vendor-managed inventory mode of operation. It is assumed that the producer applies economic production quantity policy, which implies a constant production rate at the producer. The operational parameters of each buyer are sales quantity, sales price and production rate. Channel profit of the supply chain and contract price between the producer and each buyer is determined based on the values of the operational parameters. Since the model belongs to nonlinear integer programs, we use a discrete particle swarm optimization algorithm (DPSO) to solve the addressed problem; however, the performance of the DPSO is compared utilizing two well-known heuristics, namely genetic algorithm and simulated annealing. A number of examples are provided to verify the model and assess the performance of the proposed heuristics. Experimental results indicate that DPSO outperforms the rival heuristics, with respect to some comparison metrics.
Reliability analysis of large scaled structures by optimization technique
Ishikawa, N.; Mihara, T.; Iizuka, M.
1987-01-01
This paper presents a reliability analysis based on the optimization technique using PNET (Probabilistic Network Evaluation Technique) method for the highly redundant structures having a large number of collapse modes. This approach makes the best use of the merit of the optimization technique in which the idea of PNET method is used. The analytical process involves the minimization of safety index of the representative mode, subjected to satisfaction of the mechanism condition and of the positive external work. The procedure entails the sequential performance of a series of the NLP (Nonlinear Programming) problems, where the correlation condition as the idea of PNET method pertaining to the representative mode is taken as an additional constraint to the next analysis. Upon succeeding iterations, the final analysis is achieved when a collapse probability at the subsequent mode is extremely less than the value at the 1st mode. The approximate collapse probability of the structure is defined as the sum of the collapse probabilities of the representative modes classified by the extent of correlation. Then, in order to confirm the validity of the proposed method, the conventional Monte Carlo simulation is also revised by using the collapse load analysis. Finally, two fairly large structures were analyzed to illustrate the scope and application of the approach. (orig./HP)
Structural parameter optimization design for Halbach permanent maglev rail
Guo, F.; Tang, Y.; Ren, L.; Li, J.
2010-01-01
Maglev rail is an important part of the magnetic levitation launch system. Reducing the manufacturing cost of magnetic levitation rail is the key problem for the development of magnetic levitation launch system. The Halbach permanent array has an advantage that the fundamental spatial field is cancelled on one side of the array while the field on the other side is enhanced. So this array used in the design of high temperature superconducting permanent maglev rail could improve the surface magnetic field and the levitation force. In order to make the best use of Nd-Fe-B (NdFeB) material and reduce the cost of maglev rail, the effect of the rail's structural parameters on levitation force and the utilization rate of NdFeB material are analyzed. The optimal ranges of these structural parameters are obtained. The mutual impact of these parameters is also discussed. The optimization method of these structure parameters is proposed at the end of this paper.
Structural parameter optimization design for Halbach permanent maglev rail
Guo, F., E-mail: guofang19830119@163.co [R and D Center of Applied Superconductivity, Huazhong University of Science and Technology, Wuhan 430074 (China); Tang, Y.; Ren, L.; Li, J. [R and D Center of Applied Superconductivity, Huazhong University of Science and Technology, Wuhan 430074 (China)
2010-11-01
Maglev rail is an important part of the magnetic levitation launch system. Reducing the manufacturing cost of magnetic levitation rail is the key problem for the development of magnetic levitation launch system. The Halbach permanent array has an advantage that the fundamental spatial field is cancelled on one side of the array while the field on the other side is enhanced. So this array used in the design of high temperature superconducting permanent maglev rail could improve the surface magnetic field and the levitation force. In order to make the best use of Nd-Fe-B (NdFeB) material and reduce the cost of maglev rail, the effect of the rail's structural parameters on levitation force and the utilization rate of NdFeB material are analyzed. The optimal ranges of these structural parameters are obtained. The mutual impact of these parameters is also discussed. The optimization method of these structure parameters is proposed at the end of this paper.
The PDB_REDO server for macromolecular structure model optimization
Robbie P. Joosten
2014-07-01
Full Text Available The refinement and validation of a crystallographic structure model is the last step before the coordinates and the associated data are submitted to the Protein Data Bank (PDB. The success of the refinement procedure is typically assessed by validating the models against geometrical criteria and the diffraction data, and is an important step in ensuring the quality of the PDB public archive [Read et al. (2011, Structure, 19, 1395–1412]. The PDB_REDO procedure aims for `constructive validation', aspiring to consistent and optimal refinement parameterization and pro-active model rebuilding, not only correcting errors but striving for optimal interpretation of the electron density. A web server for PDB_REDO has been implemented, allowing thorough, consistent and fully automated optimization of the refinement procedure in REFMAC and partial model rebuilding. The goal of the web server is to help practicing crystallographers to improve their model prior to submission to the PDB. For this, additional steps were implemented in the PDB_REDO pipeline, both in the refinement procedure, e.g. testing of resolution limits and k-fold cross-validation for small test sets, and as new validation criteria, e.g. the density-fit metrics implemented in EDSTATS and ligand validation as implemented in YASARA. Innovative ways to present the refinement and validation results to the user are also described, which together with auto-generated Coot scripts can guide users to subsequent model inspection and improvement. It is demonstrated that using the server can lead to substantial improvement of structure models before they are submitted to the PDB.
Comparison of optimization methods for electronic-structure calculations
Garner, J.; Das, S.G.; Min, B.I.; Woodward, C.; Benedek, R.
1989-01-01
The performance of several local-optimization methods for calculating electronic structure is compared. The fictitious first-order equation of motion proposed by Williams and Soler is integrated numerically by three procedures: simple finite-difference integration, approximate analytical integration (the Williams-Soler algorithm), and the Born perturbation series. These techniques are applied to a model problem for which exact solutions are known, the Mathieu equation. The Williams-Soler algorithm and the second Born approximation converge equally rapidly, but the former involves considerably less computational effort and gives a more accurate converged solution. Application of the method of conjugate gradients to the Mathieu equation is discussed
Topology Optimization of Vehicle Body Structure for Improved Ride & Handling
Lövgren, Sebastian; Norberg, Emil
2011-01-01
Ride and handling are important areas for safety and improved vehicle control during driving. To meet the demands on ride and handling a number of measures can be taken. This master thesis work has focused on the early design phase. At the early phases of design, the level of details is low and the design freedom is big. By introducing a tool to support the early vehicle body design, the potential of finding more efficient structures increases. In this study, topology optimization of a vehicl...
Homogenization of discrete media
Pradel, F.; Sab, K. [CERAM-ENPC, Marne-la-Vallee (France)
1998-11-01
Material such as granular media, beam assembly are easily seen as discrete media. They look like geometrical points linked together thanks to energetic expressions. Our purpose is to extend discrete kinematics to the one of an equivalent continuous material. First we explain how we build the localisation tool for periodic materials according to estimated continuum medium type (classical Cauchy, and Cosserat media). Once the bridge built between discrete and continuum media, we exhibit its application over two bidimensional beam assembly structures : the honey comb and a structural reinforced variation. The new behavior is then applied for the simple plan shear problem in a Cosserat continuum and compared with the real discrete solution. By the mean of this example, we establish the agreement of our new model with real structures. The exposed method has a longer range than mechanics and can be applied to every discrete problems like electromagnetism in which relationship between geometrical points can be summed up by an energetic function. (orig.) 7 refs.
Multivariable controller for discrete stochastic amplitude-constrained systems
Hannu T. Toivonen
1983-04-01
Full Text Available A sub-optimal multivariable controller for discrete stochastic amplitude-constrained systems is presented. In the approach the regulator structure is restricted to the class of linear saturated feedback laws. The stationary covariances of the controlled system are evaluated by approximating the stationary probability distribution of the state by a gaussian distribution. An algorithm for minimizing a quadratic loss function is given, and examples are presented to illustrate the performance of the sub-optimal controller.
Clustering methods for the optimization of atomic cluster structure
Bagattini, Francesco; Schoen, Fabio; Tigli, Luca
2018-04-01
In this paper, we propose a revised global optimization method and apply it to large scale cluster conformation problems. In the 1990s, the so-called clustering methods were considered among the most efficient general purpose global optimization techniques; however, their usage has quickly declined in recent years, mainly due to the inherent difficulties of clustering approaches in large dimensional spaces. Inspired from the machine learning literature, we redesigned clustering methods in order to deal with molecular structures in a reduced feature space. Our aim is to show that by suitably choosing a good set of geometrical features coupled with a very efficient descent method, an effective optimization tool is obtained which is capable of finding, with a very high success rate, all known putative optima for medium size clusters without any prior information, both for Lennard-Jones and Morse potentials. The main result is that, beyond being a reliable approach, the proposed method, based on the idea of starting a computationally expensive deep local search only when it seems worth doing so, is capable of saving a huge amount of searches with respect to an analogous algorithm which does not employ a clustering phase. In this paper, we are not claiming the superiority of the proposed method compared to specific, refined, state-of-the-art procedures, but rather indicating a quite straightforward way to save local searches by means of a clustering scheme working in a reduced variable space, which might prove useful when included in many modern methods.
Optimal control of large space structures via generalized inverse matrix
Nguyen, Charles C.; Fang, Xiaowen
1987-01-01
Independent Modal Space Control (IMSC) is a control scheme that decouples the space structure into n independent second-order subsystems according to n controlled modes and controls each mode independently. It is well-known that the IMSC eliminates control and observation spillover caused when the conventional coupled modal control scheme is employed. The independent control of each mode requires that the number of actuators be equal to the number of modelled modes, which is very high for a faithful modeling of large space structures. A control scheme is proposed that allows one to use a reduced number of actuators to control all modeled modes suboptimally. In particular, the method of generalized inverse matrices is employed to implement the actuators such that the eigenvalues of the closed-loop system are as closed as possible to those specified by the optimal IMSC. Computer simulation of the proposed control scheme on a simply supported beam is given.
Approaches of Russian oil companies to optimal capital structure
Ishuk, T.; Ulyanova, O.; Savchitz, V.
2015-11-01
Oil companies play a vital role in Russian economy. Demand for hydrocarbon products will be increasing for the nearest decades simultaneously with the population growth and social needs. Change of raw-material orientation of Russian economy and the transition to the innovative way of the development do not exclude the development of oil industry in future. Moreover, society believes that this sector must bring the Russian economy on to the road of innovative development due to neo-industrialization. To achieve this, the government power as well as capital management of companies are required. To make their optimal capital structure, it is necessary to minimize the capital cost, decrease definite risks under existing limits, and maximize profitability. The capital structure analysis of Russian and foreign oil companies shows different approaches, reasons, as well as conditions and, consequently, equity capital and debt capital relationship and their cost, which demands the effective capital management strategy.
Automatic design optimization tool for passive structural control systems
Mojolic, Cristian; Hulea, Radu; Parv, Bianca Roxana
2017-07-01
The present paper proposes an automatic dynamic process in order to find the parameters of the seismic isolation systems applied to large span structures. Three seismic isolation solutions are proposed for the model of the new Slatina Sport Hall. The first case uses friction pendulum system (FP), the second one uses High Damping Rubber Bearing (HDRB) and Lead Rubber Bearings, while (LRB) are used for the last case of isolation. The placement of the isolation level is at the top end of the roof supporting columns. The aim is to calculate the parameters of each isolation system so that the whole's structure first vibration periods is the one desired by the user. The model is computed with the use of SAP2000 software. In order to find the best solution for the optimization problem, an optimization process based on Genetic Algorithms (GA) has been developed in Matlab. With the use of the API (Application Programming Interface) libraries a two way link is created between the two programs in order to exchange results and link parameters. The main goal is to find the best seismic isolation method for each desired modal period so that the bending moment on the supporting columns should be minimum.
Adaptive symbiotic organisms search (SOS algorithm for structural design optimization
Ghanshyam G. Tejani
2016-07-01
Full Text Available The symbiotic organisms search (SOS algorithm is an effective metaheuristic developed in 2014, which mimics the symbiotic relationship among the living beings, such as mutualism, commensalism, and parasitism, to survive in the ecosystem. In this study, three modified versions of the SOS algorithm are proposed by introducing adaptive benefit factors in the basic SOS algorithm to improve its efficiency. The basic SOS algorithm only considers benefit factors, whereas the proposed variants of the SOS algorithm, consider effective combinations of adaptive benefit factors and benefit factors to study their competence to lay down a good balance between exploration and exploitation of the search space. The proposed algorithms are tested to suit its applications to the engineering structures subjected to dynamic excitation, which may lead to undesirable vibrations. Structure optimization problems become more challenging if the shape and size variables are taken into account along with the frequency. To check the feasibility and effectiveness of the proposed algorithms, six different planar and space trusses are subjected to experimental analysis. The results obtained using the proposed methods are compared with those obtained using other optimization methods well established in the literature. The results reveal that the adaptive SOS algorithm is more reliable and efficient than the basic SOS algorithm and other state-of-the-art algorithms.
Optimal Design of HGV Front Structure for Pedestrian Safety
Ramli, Faiz Redza; Yamazaki, Koetsu
This paper addresses a pedestrian safety design of front structure of Heavy Goods Vehicle (HGV) by two concepts; firstly by equipping a lower bumper stiffener structure under the front bumper and secondly by putting an airbag in front of the HGV front panel. In this study, HGV-pedestrian collision accident was simulated by the crash analysis solver MADYMO environment, where the HGV model with the speed of 20 km/h was collided with an adult male and with an adult female pedestrian, respectively. The bumper and lower bumper stiffener were varied their positions, while the airbag was adjusted the vent hole size and the position of airbag in front of front panel vertically. The pedestrian injuries that can be sustained during the simulation impact were limited at the critical body parts of head, chest, upper leg; an injury criteria of Head Injury Criterion (HIC), Thorax Cumulative 3ms Acceleration (C3ms) and peak loads of femur, respectively. Because of various parameters and constraints of initial conditions and injury thresholds, a multi-objective optimization design problem considered these main injury criterion is solved in order to achieve the best solution for this study. The results of optimized design parameters for each cases and conditions were obtained and the possibilities of the proposed concept were discussed.
MICRONEEDLE STRUCTURE DESIGN AND OPTIMIZATION USING GENETIC ALGORITHM
N. A. ISMAIL
2015-07-01
Full Text Available This paper presents a Genetic Algorithm (GA based microneedle design and analysis. GA is an evolutionary optimization technique that mimics the natural biological evolution. The design of microneedle structure considers the shape of microneedle, material used, size of the array, the base of microneedle, the lumen base, the height of microneedle, the height of the lumen, and the height of the drug container or reservoir. The GA is executed in conjunction with ANSYS simulation system to assess the design specifications. The GA uses three operators which are reproduction, crossover and mutation to manipulate the genetic composition of the population. In this research, the microneedle is designed to meet a number of significant specifications such as nodal displacement, strain energy, equivalent stress and flow rate of the fluid / drug that flow through its channel / lumen. A comparison study is conducted to investigate the design of microneedle structure with and without the implementation of GA model. The results showed that GA is able to optimize the design parameters of microneedle and is capable to achieve the required specifications with better performance.
Overconfidence, Managerial Optimism, and the Determinants of Capital Structure
Alexandre di Miceli da Silveira
2008-12-01
Full Text Available This research examines the determinants of the capital structure of firms introducing a behavioral perspective that has received little attention in corporate finance literature. The following central hypothesis emerges from a set of recently developed theories: firms managed by optimistic and/or overconfident people will choose more levered financing structures than others, ceteris paribus. We propose different proxies for optimism/overconfidence, based on the manager’s status as an entrepreneur or non-entrepreneur, an idea that is supported by theories and solid empirical evidence, as well as on the pattern of ownership of the firm’s shares by its manager. The study also includes potential determinants of capital structure used in earlier research. We use a sample of Brazilian firms listed in the Sao Paulo Stock Exchange (Bovespa in the years 1998 to 2003. The empirical analysis suggests that the proxies for the referred cognitive biases are important determinants of capital structure. We also found as relevant explanatory variables: profitability, size, dividend payment and tangibility, as well as some indicators that capture the firms’ corporate governance standards. These results suggest that behavioral approaches based on human psychology research can offer relevant contributions to the understanding of corporate decision making.
HuaZhi, Zhou; ZhiJin, Wang
2017-11-01
The intersection element is an important part of the helicopter subfloor structure. In order to improve the crashworthiness properties, the floor and the skin of the intersection element are replaced with foldcore sandwich structures. Foldcore is a kind of high-energy absorption structure. Compared with original structure, the new intersection element shows better buffering capacity and energy-absorption capacity. To reduce structure’s mass while maintaining the crashworthiness requirements satisfied, optimization of the intersection element geometric parameters is conducted. An optimization method using NSGA-II and Anisotropic Kriging is used. A significant CPU time saving can be obtained by replacing numerical model with Anisotropic Kriging surrogate model. The operation allows 17.15% reduce of the intersection element mass.
Discrete Exterior Calculus Discretization of Incompressible Navier-Stokes Equations
Mohamed, Mamdouh S.
2017-05-23
A conservative discretization of incompressible Navier-Stokes equations over surface simplicial meshes is developed using discrete exterior calculus (DEC). Numerical experiments for flows over surfaces reveal a second order accuracy for the developed scheme when using structured-triangular meshes, and first order accuracy otherwise. The mimetic character of many of the DEC operators provides exact conservation of both mass and vorticity, in addition to superior kinetic energy conservation. The employment of barycentric Hodge star allows the discretization to admit arbitrary simplicial meshes. The discretization scheme is presented along with various numerical test cases demonstrating its main characteristics.
Optimizing enactment of nursing roles: redesigning care processes and structures
Jackson K
2014-02-01
Full Text Available Karen Jackson,1 Deborah E White,2 Jeanne Besner,1 Jill M Norris21Health Systems and Workforce Research Unit, Alberta Health Services, Calgary, Alberta, Canada; 2Faculty of Nursing, University of Calgary, Calgary, Alberta, CanadaBackground: Effective and efficient use of nursing human resources is critical. The Nursing Role Effectiveness Model conceptualizes nursing practice in terms of key clinical role accountabilities and has the potential to inform redesign efforts. The aims of this study were to develop, implement, and evaluate a job redesign intended to optimize the enactment of registered nurse (RN clinical role accountabilities.Methods: A job redesign was developed and implemented in a single medical patient care unit, the redesign unit. A mixed-methods design was used to evaluate the job redesign; a second medical patient care unit served as a control unit. Data from administrative databases, observations, interviews, and demographic surveys were collected pre-redesign (November 2005 and post-redesign (October 2007.Results: Several existing unit structures and processes (eg, model of care delivery influenced RNs' ability to optimally enact their role accountabilities. Redesign efforts were hampered by contextual issues, including organizational alignment, leadership, and timing. Overall, optimized enactment of RN role accountabilities and improvements to patient outcomes did not occur, yet this was predictable, given that the redesign was not successful. Although the results were disappointing, much was learned about job redesign.Conclusion: Potential exists to improve the utilization of nursing providers by situating nurses' work in a clinical role accountability framework and attending to a clear organizational vision and well-articulated strategic plan that is championed by leaders at all levels of the organization. Health care leaders require a clear understanding of nurses' role accountabilities, support in managing change, and
Advances in discrete differential geometry
2016-01-01
This is one of the first books on a newly emerging field of discrete differential geometry and an excellent way to access this exciting area. It surveys the fascinating connections between discrete models in differential geometry and complex analysis, integrable systems and applications in computer graphics. The authors take a closer look at discrete models in differential geometry and dynamical systems. Their curves are polygonal, surfaces are made from triangles and quadrilaterals, and time is discrete. Nevertheless, the difference between the corresponding smooth curves, surfaces and classical dynamical systems with continuous time can hardly be seen. This is the paradigm of structure-preserving discretizations. Current advances in this field are stimulated to a large extent by its relevance for computer graphics and mathematical physics. This book is written by specialists working together on a common research project. It is about differential geometry and dynamical systems, smooth and discrete theories, ...
Optimal structure of fault-tolerant software systems
Levitin, Gregory
2005-01-01
This paper considers software systems consisting of fault-tolerant components. These components are built from functionally equivalent but independently developed versions characterized by different reliability and execution time. Because of hardware resource constraints, the number of versions that can run simultaneously is limited. The expected system execution time and its reliability (defined as probability of obtaining the correct output within a specified time) strictly depend on parameters of software versions and sequence of their execution. The system structure optimization problem is formulated in which one has to choose software versions for each component and find the sequence of their execution in order to achieve the greatest system reliability subject to cost constraints. The versions are to be chosen from a list of available products. Each version is characterized by its reliability, execution time and cost. The suggested optimization procedure is based on an algorithm for determining system execution time distribution that uses the moment generating function approach and on the genetic algorithm. Both N-version programming and the recovery block scheme are considered within a universal model. Illustrated example is presented
A Cultural Algorithm for Optimal Design of Truss Structures
Shahin Jalili
Full Text Available Abstract A cultural algorithm was utilized in this study to solve optimal design of truss structures problem achieving minimum weight objective under stress and deflection constraints. The algorithm is inspired by principles of human social evolution. It simulates the social interaction between the peoples and their beliefs in a belief space. Cultural Algorithm (CA utilizes the belief space and population space which affects each other based on acceptance and influence functions. The belief space of CA consists of different knowledge components. In this paper, only situational and normative knowledge components are used within the belief space. The performance of the method is demonstrated through four benchmark design examples. Comparison of the obtained results with those of some previous studies demonstrates the efficiency of this algorithm.
Wetting on micro-structured surfaces: modelling and optimization
Cavalli, Andrea
-patterns, and suggests that there is a balance between optimal wetting properties and mechanical robustness of the microposts. We subsequently analyse liquid spreading on surfaces patterned with slanted microposts. Such a geometry induces unidirectional liquid spreading, as observed in several recent experiments. Our...... liquid spreading and spontaneous drop removal on superhydrophobic surfaces. We do this by applying different numerical techniques, suited for the specific topic. We first consider superhydrophobicity, a condition of extreme water repellency associated with very large static contact angles and low roll......The present thesis deals with the wetting of micro-structured surfaces by various fluids, and its goal is to elucidate different aspects of this complex interaction. In this work we address some of the most relevant topics in this field such as superhydrophobicity, oleophobicity, unidirectional...
Modeling and Structural Optimization of Solid Oxide Fuel Cells
Panagakos, Grigorios
energy basket of solutions. In this project, consulting role was also undertaken by researchers at National Center for Sustainable Energy, Risø and more specifically by Dr. Martin Søgaard, Dr. Henrik Frandsen and Dr. Peter Vang Hendriksen (team leader). The other approach is based on attacking......, such as the tortuosity and the porosity of the material, for preselected micro-structures. Furthermore, we apply optimization techniques to lead this ASR to minimization. This work has been the fruit of collaboration with Professor Sossina Haile at the California Institute of Technology (Caltech) and with assistant...... Professor Francesco Ciucci at the Hong Kong University of Science and Technology (HKUST). As a complementary in this modeling work, we have also developed other activities, leading to either already accepted, submitted or soon to be submitted publications. These additional to the main focus directions, have...
Opportunities of Optimization in Administrative Structures for Efficient Management
Venelin Terziev
2017-12-01
Full Text Available Current paper presents studies on the administrative structures in order to optimize the activities and the overall management through the example of the Bulgarian Commission for Protection against Discrimination. It aims at establishing duplicate functions in the organization under study. The main tasks in the analysis are related to the display of the basic findings and conclusions for the strongest sides and the fields for improvement regarding the relevance, the effectiveness and the efficiency of the administration of the Commission for Protection against Discrimination in Bulgaria. The following areas are thoroughly and critically analyzed: relevance of the functions and efficiency of the activity. As a result of the study a Strategy for Organizational Development and a Training Plan have been drafted.
Structural optimization of the Halbach array PM rim thrust motor
Cao, Haichuan; Chen, Weihu
2018-05-01
The Rim-driven Thruster (RDT) integrates the thrust motor and the propeller, which can effectively reduce the space occupied by the propulsion system, improve the propulsion efficiency, and thus has important research value and broad market prospects. The Halbach Permanent Magnet Rim Thrust Motor (HPMRTM) can improve the torque density of the propulsion motor by utilizing the unilateral magnetic field of the Halbach array. In this paper, the numerical method is used to study the electromagnetic performance of the motor under different Halbach array parameters. The relationship between motor parameters such as air-gap flux density, electromagnetic torque and Halbach array parameters is obtained, and then the motor structure is optimized. By comparing with Common Permanent Magnet RTM, the advantages of HPMRTM are verified.
Design of an X-band accelerating structure using a newly developed structural optimization procedure
Huang, Xiaoxia [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Fang, Wencheng; Gu, Qiang [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China); Zhao, Zhentang, E-mail: zhaozhentang@sinap.ac.cn [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China); University of Chinese Academy of Sciences, Beijing 100049 (China)
2017-05-11
An X-band high gradient accelerating structure is a challenging technology for implementation in advanced electron linear accelerator facilities. The present work discusses the design of an X-band accelerating structure for dedicated application to a compact hard X-ray free electron laser facility at the Shanghai Institute of Applied Physics, and numerous design optimizations are conducted with consideration for radio frequency (RF) breakdown, RF efficiency, short-range wakefields, and dipole/quadrupole field modes, to ensure good beam quality and a high accelerating gradient. The designed X-band accelerating structure is a constant gradient structure with a 4π/5 operating mode and input and output dual-feed couplers in a racetrack shape. The design process employs a newly developed effective optimization procedure for optimization of the X-band accelerating structure. In addition, the specific design of couplers providing high beam quality by eliminating dipole field components and reducing quadrupole field components is discussed in detail.
Van Aardt, JAN
2012-07-01
Full Text Available The goals of the study were to (i) determine if there is a direct relationship between waveform LiDAR intensity-by-height and discrete return frequency-by-height (do the distributions match?) and (ii) assess the impact of scale (does...
Design optimization of embedded ultrasonic transducers for concrete structures assessment.
Dumoulin, Cédric; Deraemaeker, Arnaud
2017-08-01
In the last decades, the field of structural health monitoring and damage detection has been intensively explored. Active vibration techniques allow to excite structures at high frequency vibrations which are sensitive to small damage. Piezoelectric PZT transducers are perfect candidates for such testing due to their small size, low cost and large bandwidth. Current ultrasonic systems are based on external piezoelectric transducers which need to be placed on two faces of the concrete specimen. The limited accessibility of in-service structures makes such an arrangement often impractical. An alternative is to embed permanently low-cost transducers inside the structure. Such types of transducers have been applied successfully for the in-situ estimation of the P-wave velocity in fresh concrete, and for crack monitoring. Up to now, the design of such transducers was essentially based on trial and error, or in a few cases, on the limitation of the acoustic impedance mismatch between the PZT and concrete. In the present study, we explore the working principles of embedded piezoelectric transducers which are found to be significantly different from external transducers. One of the major challenges concerning embedded transducers is to produce very low cost transducers. We show that a practical way to achieve this imperative is to consider the radial mode of actuation of bulk PZT elements. This is done by developing a simple finite element model of a piezoelectric transducer embedded in an infinite medium. The model is coupled with a multi-objective genetic algorithm which is used to design specific ultrasonic embedded transducers both for hard and fresh concrete monitoring. The results show the efficiency of the approach and a few designs are proposed which are optimal for hard concrete, fresh concrete, or both, in a given frequency band of interest. Copyright © 2017 Elsevier B.V. All rights reserved.
Managerial instrument for didactic staff structure optimization for Distance Learning
Gavrus Cristina
2017-01-01
Full Text Available Distance learning is a modern system for providing educational services and is relatively new in Romania, if related to the date of its emergence in Europe. More and more active working people are interested in this form of education, paying of course a special attention to its quality. It is quite difficult to appraise the quality of educational programs but several instruments and criteria have been developed over time. The present paper proposes an original mathematical instrument that is aiming at human resources, this type of resources being considered extremely important in case of providing educational service. The number of teachers is crucial for a distance learning program study, because the didactic staff must cover a number of didactic classes that take place on weekends. Concretely, this paper is focused on finding an algorithm that allows the didactic staff structure optimization. For accomplishing this objective, two managerial instruments were use. One of them is mathematical linear programing technique, that develops a mathematical model for didactic staff structure and the other one is WinQSB software package that tests the mathematical model.
Optimal optical communication terminal structure for maximizing the link budget
Huang, Jian; Jiang, Dagang; Deng, Ke; Zhang, Peng
2015-02-01
Ordinary inter-satellite optical includes at least three optical paths for acquisition, tracking and communication, the three optical paths work simultaneously and share the received power. An optimal structure of inter-satellite optical communication terminal with single working optical path at each of working stages of acquisition and communication is introduced. A space optical switch based on frustrated total internal reflection effect is applied to switch the received laser power between the acquisition sensor and the communication sensor between the stages of acquisition and communication, this is named as power fusion which means power is transferred for shutting down unused optical path. For the stages of tracking and communication, a multiple cells sensor is used to accomplish the operation of tracking while communication, this is named as function fusion which means accomplishing multiple functions by one device to reduce the redundant optical paths. For optical communication terminal with single working path structure, the total received laser power would be detected by one sensor for each different stages of acquisition, tracking and communication, the link budget would be maximized, and this design would help to enlarge the system tolerance and reduce the acquisition time.
Management of a stage-structured insect pest: an application of approximate optimization.
Hackett, Sean C; Bonsall, Michael B
2018-06-01
Ecological decision problems frequently require the optimization of a sequence of actions over time where actions may have both immediate and downstream effects. Dynamic programming can solve such problems only if the dimensionality is sufficiently low. Approximate dynamic programming (ADP) provides a suite of methods applicable to problems of arbitrary complexity at the expense of guaranteed optimality. The most easily generalized method is the look-ahead policy: a brute-force algorithm that identifies reasonable actions by constructing and solving a series of temporally truncated approximations of the full problem over a defined planning horizon. We develop and apply this approach to a pest management problem inspired by the Mediterranean fruit fly, Ceratitis capitata. The model aims to minimize the cumulative costs of management actions and medfly-induced losses over a single 16-week season. The medfly population is stage-structured and grows continuously while management decisions are made at discrete, weekly intervals. For each week, the model chooses between inaction, insecticide application, or one of six sterile insect release ratios. Look-ahead policy performance is evaluated over a range of planning horizons, two levels of crop susceptibility to medfly and three levels of pesticide persistence. In all cases, the actions proposed by the look-ahead policy are contrasted to those of a myopic policy that minimizes costs over only the current week. We find that look-ahead policies always out-performed a myopic policy and decision quality is sensitive to the temporal distribution of costs relative to the planning horizon: it is beneficial to extend the planning horizon when it excludes pertinent costs. However, longer planning horizons may reduce decision quality when major costs are resolved imminently. ADP methods such as the look-ahead-policy-based approach developed here render questions intractable to dynamic programming amenable to inference but should be
Sousa, Sergio H.G. de; Madeira, Marcelo G. [Halliburton Servicos Ltda., Rio de Janeiro, RJ (Brazil)
2008-07-01
In the classical operations research arena, there is the notion that the search for optimized solutions in continuous solution spaces is easier than on discrete solution spaces, even when the latter is a subset of the first. On the upstream oil industry, there is an additional complexity in the optimization problems because there usually are no analytical expressions for the objective function, which require some form of simulation in order to be evaluated. Thus, the use of meta heuristic optimizers like scatter search, tabu search and genetic algorithms is common. In this meta heuristic context, there are advantages in transforming continuous solution spaces in equivalent discrete ones; the goal to do so usually is to speed up the search for optimized solutions. However, these advantages can be masked when the problem has restrictions formed by linear combinations of its decision variables. In order to study these aspects of meta heuristic optimization, two optimization problems are proposed and solved with both continuous and discrete solution spaces: assisted history matching and injection rates optimization. Both cases operate on a model of the Wytch Farm onshore oil filed located in England. (author)
Topology optimization of radio frequency and microwave structures
Aage, Niels
in this thesis, concerns the optimization of devices for wireless energy transfer via strongly coupled magnetic resonators. A single design problem is considered to demonstrate proof of concept. The resulting design illustrates the possibilities of the optimization method, but also reveals its numerical...... of efficient antennas and power supplies. A topology optimization methodology is proposed based on a design parameterization which incorporates the skin effect. The numerical optimization procedure is implemented in Matlab, for 2D problems, and in a parallel C++ optimization framework, for 3D design problems...... formalism, a two step optimization procedure is presented. This scheme is applied to the design and optimization of a hemispherical sub-wavelength antenna. The optimized antenna configuration displayed a ratio of radiated power to input power in excess of 99 %. The third, and last, design problem considered...
On CAD-integrated Structural Topology and Design Optimization
Olhoff, Niels; Bendsøe, M.P.; Rasmussen, John
1991-01-01
Concepts underlying an interactive CAD-based engineering design optimization system are developed, and methods of optimizing the topology, shape and sizing of mechanical components are presented. These methods are integrated in the system, and the method for determining the optimal topology is used...
Eremin, Yu. A.; Sveshnikov, A. G.
2018-04-01
The discrete source method is used to develop and implement a mathematical model for solving the problem of scattering electromagnetic waves by a three-dimensional plasmonic scatterer with nonlocal effects taken into account. Numerical results are presented whereby the features of the scattering properties of plasmonic particles with allowance for nonlocal effects are demonstrated depending on the direction and polarization of the incident wave.
Infill Optimization for Additive Manufacturing-Approaching Bone-Like Porous Structures.
Wu, Jun; Aage, Niels; Westermann, Rudiger; Sigmund, Ole
2018-02-01
Porous structures such as trabecular bone are widely seen in nature. These structures are lightweight and exhibit strong mechanical properties. In this paper, we present a method to generate bone-like porous structures as lightweight infill for additive manufacturing. Our method builds upon and extends voxel-wise topology optimization. In particular, for the purpose of generating sparse yet stable structures distributed in the interior of a given shape, we propose upper bounds on the localized material volume in the proximity of each voxel in the design domain. We then aggregate the local per-voxel constraints by their p-norm into an equivalent global constraint, in order to facilitate an efficient optimization process. Implemented on a high-resolution topology optimization framework, our results demonstrate mechanically optimized, detailed porous structures which mimic those found in nature. We further show variants of the optimized structures subject to different design specifications, and we analyze the optimality and robustness of the obtained structures.