Ruszczynski, Andrzej
2011-01-01
Optimization is one of the most important areas of modern applied mathematics, with applications in fields from engineering and economics to finance, statistics, management science, and medicine. While many books have addressed its various aspects, Nonlinear Optimization is the first comprehensive treatment that will allow graduate students and researchers to understand its modern ideas, principles, and methods within a reasonable time, but without sacrificing mathematical precision. Andrzej Ruszczynski, a leading expert in the optimization of nonlinear stochastic systems, integrates the theory and the methods of nonlinear optimization in a unified, clear, and mathematically rigorous fashion, with detailed and easy-to-follow proofs illustrated by numerous examples and figures. The book covers convex analysis, the theory of optimality conditions, duality theory, and numerical methods for solving unconstrained and constrained optimization problems. It addresses not only classical material but also modern top...
NR-code: Nonlinear reconstruction code
Yu, Yu; Pen, Ue-Li; Zhu, Hong-Ming
2018-04-01
NR-code applies nonlinear reconstruction to the dark matter density field in redshift space and solves for the nonlinear mapping from the initial Lagrangian positions to the final redshift space positions; this reverses the large-scale bulk flows and improves the precision measurement of the baryon acoustic oscillations (BAO) scale.
Nonlinear optimal control theory
Berkovitz, Leonard David
2012-01-01
Nonlinear Optimal Control Theory presents a deep, wide-ranging introduction to the mathematical theory of the optimal control of processes governed by ordinary differential equations and certain types of differential equations with memory. Many examples illustrate the mathematical issues that need to be addressed when using optimal control techniques in diverse areas. Drawing on classroom-tested material from Purdue University and North Carolina State University, the book gives a unified account of bounded state problems governed by ordinary, integrodifferential, and delay systems. It also dis
Optimal codes as Tanner codes with cyclic component codes
DEFF Research Database (Denmark)
Høholdt, Tom; Pinero, Fernando; Zeng, Peng
2014-01-01
In this article we study a class of graph codes with cyclic code component codes as affine variety codes. Within this class of Tanner codes we find some optimal binary codes. We use a particular subgraph of the point-line incidence plane of A(2,q) as the Tanner graph, and we are able to describe ...
Iterative nonlinear unfolding code: TWOGO
International Nuclear Information System (INIS)
Hajnal, F.
1981-03-01
a new iterative unfolding code, TWOGO, was developed to analyze Bonner sphere neutron measurements. The code includes two different unfolding schemes which alternate on successive iterations. The iterative process can be terminated either when the ratio of the coefficient of variations in terms of the measured and calculated responses is unity, or when the percentage difference between the measured and evaluated sphere responses is less than the average measurement error. The code was extensively tested with various known spectra and real multisphere neutron measurements which were performed inside the containments of pressurized water reactors
Methods for Large-Scale Nonlinear Optimization.
1980-05-01
STANFORD, CALIFORNIA 94305 METHODS FOR LARGE-SCALE NONLINEAR OPTIMIZATION by Philip E. Gill, Waiter Murray, I Michael A. Saunden, and Masgaret H. Wright...typical iteration can be partitioned so that where B is an m X m basise matrix. This partition effectively divides the vari- ables into three classes... attention is given to the standard of the coding or the documentation. A much better way of obtaining mathematical software is from a software library
Interactive Nonlinear Multiobjective Optimization Methods
Miettinen, Kaisa; Hakanen, Jussi; Podkopaev, Dmitry
2016-01-01
An overview of interactive methods for solving nonlinear multiobjective optimization problems is given. In interactive methods, the decision maker progressively provides preference information so that the most satisfactory Pareto optimal solution can be found for her or his. The basic features of several methods are introduced and some theoretical results are provided. In addition, references to modifications and applications as well as to other methods are indicated. As the...
Induction technology optimization code
International Nuclear Information System (INIS)
Caporaso, G.J.; Brooks, A.L.; Kirbie, H.C.
1992-01-01
A code has been developed to evaluate relative costs of induction accelerator driver systems for relativistic klystrons. The code incorporates beam generation, transport and pulsed power system constraints to provide an integrated design tool. The code generates an injector/accelerator combination which satisfies the top level requirements and all system constraints once a small number of design choices have been specified (rise time of the injector voltage and aspect ratio of the ferrite induction cores, for example). The code calculates dimensions of accelerator mechanical assemblies and values of all electrical components. Cost factors for machined parts, raw materials and components are applied to yield a total system cost. These costs are then plotted as a function of the two design choices to enable selection of an optimum design based on various criteria. (Author) 11 refs., 3 figs
Nonlinear Optimization with Financial Applications
Bartholomew-Biggs, Michael
2005-01-01
The book introduces the key ideas behind practical nonlinear optimization. Computational finance - an increasingly popular area of mathematics degree programs - is combined here with the study of an important class of numerical techniques. The financial content of the book is designed to be relevant and interesting to specialists. However, this material - which occupies about one-third of the text - is also sufficiently accessible to allow the book to be used on optimization courses of a more general nature. The essentials of most currently popular algorithms are described, and their performan
An Optimal Linear Coding for Index Coding Problem
Pezeshkpour, Pouya
2015-01-01
An optimal linear coding solution for index coding problem is established. Instead of network coding approach by focus on graph theoric and algebraic methods a linear coding program for solving both unicast and groupcast index coding problem is presented. The coding is proved to be the optimal solution from the linear perspective and can be easily utilize for any number of messages. The importance of this work is lying mostly on the usage of the presented coding in the groupcast index coding ...
Formal Proofs for Nonlinear Optimization
Directory of Open Access Journals (Sweden)
Victor Magron
2015-01-01
Full Text Available We present a formally verified global optimization framework. Given a semialgebraic or transcendental function f and a compact semialgebraic domain K, we use the nonlinear maxplus template approximation algorithm to provide a certified lower bound of f over K.This method allows to bound in a modular way some of the constituents of f by suprema of quadratic forms with a well chosen curvature. Thus, we reduce the initial goal to a hierarchy of semialgebraic optimization problems, solved by sums of squares relaxations. Our implementation tool interleaves semialgebraic approximations with sums of squares witnesses to form certificates. It is interfaced with Coq and thus benefits from the trusted arithmetic available inside the proof assistant. This feature is used to produce, from the certificates, both valid underestimators and lower bounds for each approximated constituent.The application range for such a tool is widespread; for instance Hales' proof of Kepler's conjecture yields thousands of multivariate transcendental inequalities. We illustrate the performance of our formal framework on some of these inequalities as well as on examples from the global optimization literature.
ROTAX: a nonlinear optimization program by axes rotation method
International Nuclear Information System (INIS)
Suzuki, Tadakazu
1977-09-01
A nonlinear optimization program employing the axes rotation method has been developed for solving nonlinear problems subject to nonlinear inequality constraints and its stability and convergence efficiency were examined. The axes rotation method is a direct search of the optimum point by rotating the orthogonal coordinate system in a direction giving the minimum objective. The searching direction is rotated freely in multi-dimensional space, so the method is effective for the problems represented with the contours having deep curved valleys. In application of the axes rotation method to the optimization problems subject to nonlinear inequality constraints, an improved version of R.R. Allran and S.E.J. Johnsen's method is used, which deals with a new objective function composed of the original objective and a penalty term to consider the inequality constraints. The program is incorporated in optimization code system SCOOP. (auth.)
Introduction to Nonlinear and Global Optimization
Hendrix, E.M.T.; Tóth, B.
2010-01-01
This self-contained text provides a solid introduction to global and nonlinear optimization, providing students of mathematics and interdisciplinary sciences with a strong foundation in applied optimization techniques. The book offers a unique hands-on and critical approach to applied optimization
Scaling Optimization of the SIESTA MHD Code
Seal, Sudip; Hirshman, Steven; Perumalla, Kalyan
2013-10-01
SIESTA is a parallel three-dimensional plasma equilibrium code capable of resolving magnetic islands at high spatial resolutions for toroidal plasmas. Originally designed to exploit small-scale parallelism, SIESTA has now been scaled to execute efficiently over several thousands of processors P. This scaling improvement was accomplished with minimal intrusion to the execution flow of the original version. First, the efficiency of the iterative solutions was improved by integrating the parallel tridiagonal block solver code BCYCLIC. Krylov-space generation in GMRES was then accelerated using a customized parallel matrix-vector multiplication algorithm. Novel parallel Hessian generation algorithms were integrated and memory access latencies were dramatically reduced through loop nest optimizations and data layout rearrangement. These optimizations sped up equilibria calculations by factors of 30-50. It is possible to compute solutions with granularity N/P near unity on extremely fine radial meshes (N > 1024 points). Grid separation in SIESTA, which manifests itself primarily in the resonant components of the pressure far from rational surfaces, is strongly suppressed by finer meshes. Large problem sizes of up to 300 K simultaneous non-linear coupled equations have been solved on the NERSC supercomputers. Work supported by U.S. DOE under Contract DE-AC05-00OR22725 with UT-Battelle, LLC.
Progress on DART code optimization
International Nuclear Information System (INIS)
Taboada, Horacio; Solis, Diego; Rest, Jeffrey
1999-01-01
This work consists about the progress made on the design and development of a new optimized version of DART code (DART-P), a mechanistic computer model for the performance calculation and assessment of aluminum dispersion fuel. It is part of a collaboration agreement between CNEA and ANL in the area of Low Enriched Uranium Advanced Fuels. It is held by the Implementation Arrangement for Technical Exchange and Cooperation in the Area of Peaceful Uses of Nuclear Energy, signed on October 16, 1997 between US DOE and the National Atomic Energy Commission of the Argentine Republic. DART optimization is a biannual program; it is operative since February 8, 1999 and has the following goals: 1. Design and develop a new DART calculation kernel for implementation within a parallel processing architecture. 2. Design and develop new user-friendly I/O routines to be resident on Personal Computer (PC)/WorkStation (WS) platform. 2.1. The new input interface will be designed and developed by means of a Visual interface, able to guide the user in the construction of the problem to be analyzed with the aid of a new database (described in item 3, below). The new I/O interface will include input data check controls in order to avoid corrupted input data. 2.2. The new output interface will be designed and developed by means of graphical tools, able to translate numeric data output into 'on line' graphic information. 3. Design and develop a new irradiated materials database, to be resident on PC/WS platform, so as to facilitate the analysis of the behavior of different fuel and meat compositions with DART-P. Currently, a different version of DART is used for oxide, silicide, and advanced alloy fuels. 4. Develop rigorous general inspection algorithms in order to provide valuable DART-P benchmarks. 5. Design and develop new models, such as superplasticity, elastoplastic feedback, improved models for the calculation of fuel deformation and the evolution of the fuel microstructure for
Optimization for nonlinear inverse problem
International Nuclear Information System (INIS)
Boyadzhiev, G.; Brandmayr, E.; Pinat, T.; Panza, G.F.
2007-06-01
The nonlinear inversion of geophysical data in general does not yield a unique solution, but a single model, representing the investigated field, is preferred for an easy geological interpretation of the observations. The analyzed region is constituted by a number of sub-regions where the multi-valued nonlinear inversion is applied, which leads to a multi-valued solution. Therefore, combining the values of the solution in each sub-region, many acceptable models are obtained for the entire region and this complicates the geological interpretation of geophysical investigations. In this paper are presented new methodologies, capable to select one model, among all acceptable ones, that satisfies different criteria of smoothness in the explored space of solutions. In this work we focus on the non-linear inversion of surface waves dispersion curves, which gives structural models of shear-wave velocity versus depth, but the basic concepts have a general validity. (author)
Structural optimization for nonlinear dynamic response
DEFF Research Database (Denmark)
Dou, Suguang; Strachan, B. Scott; Shaw, Steven W.
2015-01-01
by a single vibrating mode, or by a pair of internally resonant modes. The approach combines techniques from nonlinear dynamics, computational mechanics and optimization, and it allows one to relate the geometric and material properties of structural elements to terms in the normal form for a given resonance......Much is known about the nonlinear resonant response of mechanical systems, but methods for the systematic design of structures that optimize aspects of these responses have received little attention. Progress in this area is particularly important in the area of micro-systems, where nonlinear...... resonant behaviour is being used for a variety of applications in sensing and signal conditioning. In this work, we describe a computational method that provides a systematic means for manipulating and optimizing features of nonlinear resonant responses of mechanical structures that are described...
Some optimizations of the animal code
International Nuclear Information System (INIS)
Fletcher, W.T.
1975-01-01
Optimizing techniques were performed on a version of the ANIMAL code (MALAD1B) at the source-code (FORTRAN) level. Sample optimizing techniques and operations used in MALADOP--the optimized version of the code--are presented, along with a critique of some standard CDC 7600 optimizing techniques. The statistical analysis of total CPU time required for MALADOP and MALAD1B shows a run-time saving of 174 msec (almost 3 percent) in the code MALADOP during one time step
Nonlinear Krylov acceleration of reacting flow codes
Energy Technology Data Exchange (ETDEWEB)
Kumar, S.; Rawat, R.; Smith, P.; Pernice, M. [Univ. of Utah, Salt Lake City, UT (United States)
1996-12-31
We are working on computational simulations of three-dimensional reactive flows in applications encompassing a broad range of chemical engineering problems. Examples of such processes are coal (pulverized and fluidized bed) and gas combustion, petroleum processing (cracking), and metallurgical operations such as smelting. These simulations involve an interplay of various physical and chemical factors such as fluid dynamics with turbulence, convective and radiative heat transfer, multiphase effects such as fluid-particle and particle-particle interactions, and chemical reaction. The governing equations resulting from modeling these processes are highly nonlinear and strongly coupled, thereby rendering their solution by traditional iterative methods (such as nonlinear line Gauss-Seidel methods) very difficult and sometimes impossible. Hence we are exploring the use of nonlinear Krylov techniques (such as CMRES and Bi-CGSTAB) to accelerate and stabilize the existing solver. This strategy allows us to take advantage of the problem-definition capabilities of the existing solver. The overall approach amounts to using the SIMPLE (Semi-Implicit Method for Pressure-Linked Equations) method and its variants as nonlinear preconditioners for the nonlinear Krylov method. We have also adapted a backtracking approach for inexact Newton methods to damp the Newton step in the nonlinear Krylov method. This will be a report on work in progress. Preliminary results with nonlinear GMRES have been very encouraging: in many cases the number of line Gauss-Seidel sweeps has been reduced by about a factor of 5, and increased robustness of the underlying solver has also been observed.
Iterative optimization of quantum error correcting codes
International Nuclear Information System (INIS)
Reimpell, M.; Werner, R.F.
2005-01-01
We introduce a convergent iterative algorithm for finding the optimal coding and decoding operations for an arbitrary noisy quantum channel. This algorithm does not require any error syndrome to be corrected completely, and hence also finds codes outside the usual Knill-Laflamme definition of error correcting codes. The iteration is shown to improve the figure of merit 'channel fidelity' in every step
Nonlinear analysis approximation theory, optimization and applications
2014-01-01
Many of our daily-life problems can be written in the form of an optimization problem. Therefore, solution methods are needed to solve such problems. Due to the complexity of the problems, it is not always easy to find the exact solution. However, approximate solutions can be found. The theory of the best approximation is applicable in a variety of problems arising in nonlinear functional analysis and optimization. This book highlights interesting aspects of nonlinear analysis and optimization together with many applications in the areas of physical and social sciences including engineering. It is immensely helpful for young graduates and researchers who are pursuing research in this field, as it provides abundant research resources for researchers and post-doctoral fellows. This will be a valuable addition to the library of anyone who works in the field of applied mathematics, economics and engineering.
International Nuclear Information System (INIS)
Suzuki, Tadakazu
1979-11-01
Thirty two programs for linear and nonlinear optimization problems with or without constraints have been developed or incorporated, and their stability, convergence and efficiency have been examined. On the basis of these evaluations, the first version of the optimization code system SCOOP-I has been completed. The SCOOP-I is designed to be an efficient, reliable, useful and also flexible system for general applications. The system enables one to find global optimization point for a wide class of problems by selecting the most appropriate optimization method built in it. (author)
Linear and nonlinear verification of gyrokinetic microstability codes
Bravenec, R. V.; Candy, J.; Barnes, M.; Holland, C.
2011-12-01
Verification of nonlinear microstability codes is a necessary step before comparisons or predictions of turbulent transport in toroidal devices can be justified. By verification we mean demonstrating that a code correctly solves the mathematical model upon which it is based. Some degree of verification can be accomplished indirectly from analytical instability threshold conditions, nonlinear saturation estimates, etc., for relatively simple plasmas. However, verification for experimentally relevant plasma conditions and physics is beyond the realm of analytical treatment and must rely on code-to-code comparisons, i.e., benchmarking. The premise is that the codes are verified for a given problem or set of parameters if they all agree within a specified tolerance. True verification requires comparisons for a number of plasma conditions, e.g., different devices, discharges, times, and radii. Running the codes and keeping track of linear and nonlinear inputs and results for all conditions could be prohibitive unless there was some degree of automation. We have written software to do just this and have formulated a metric for assessing agreement of nonlinear simulations. We present comparisons, both linear and nonlinear, between the gyrokinetic codes GYRO [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] and GS2 [W. Dorland, F. Jenko, M. Kotschenreuther, and B. N. Rogers, Phys. Rev. Lett. 85, 5579 (2000)]. We do so at the mid-radius for the same discharge as in earlier work [C. Holland, A. E. White, G. R. McKee, M. W. Shafer, J. Candy, R. E. Waltz, L. Schmitz, and G. R. Tynan, Phys. Plasmas 16, 052301 (2009)]. The comparisons include electromagnetic fluctuations, passing and trapped electrons, plasma shaping, one kinetic impurity, and finite Debye-length effects. Results neglecting and including electron collisions (Lorentz model) are presented. We find that the linear frequencies with or without collisions agree well between codes, as do the time averages of
Optimal Codes for the Burst Erasure Channel
Hamkins, Jon
2010-01-01
Deep space communications over noisy channels lead to certain packets that are not decodable. These packets leave gaps, or bursts of erasures, in the data stream. Burst erasure correcting codes overcome this problem. These are forward erasure correcting codes that allow one to recover the missing gaps of data. Much of the recent work on this topic concentrated on Low-Density Parity-Check (LDPC) codes. These are more complicated to encode and decode than Single Parity Check (SPC) codes or Reed-Solomon (RS) codes, and so far have not been able to achieve the theoretical limit for burst erasure protection. A block interleaved maximum distance separable (MDS) code (e.g., an SPC or RS code) offers near-optimal burst erasure protection, in the sense that no other scheme of equal total transmission length and code rate could improve the guaranteed correctible burst erasure length by more than one symbol. The optimality does not depend on the length of the code, i.e., a short MDS code block interleaved to a given length would perform as well as a longer MDS code interleaved to the same overall length. As a result, this approach offers lower decoding complexity with better burst erasure protection compared to other recent designs for the burst erasure channel (e.g., LDPC codes). A limitation of the design is its lack of robustness to channels that have impairments other than burst erasures (e.g., additive white Gaussian noise), making its application best suited for correcting data erasures in layers above the physical layer. The efficiency of a burst erasure code is the length of its burst erasure correction capability divided by the theoretical upper limit on this length. The inefficiency is one minus the efficiency. The illustration compares the inefficiency of interleaved RS codes to Quasi-Cyclic (QC) LDPC codes, Euclidean Geometry (EG) LDPC codes, extended Irregular Repeat Accumulate (eIRA) codes, array codes, and random LDPC codes previously proposed for burst erasure
Optimal interference code based on machine learning
Qian, Ye; Chen, Qian; Hu, Xiaobo; Cao, Ercong; Qian, Weixian; Gu, Guohua
2016-10-01
In this paper, we analyze the characteristics of pseudo-random code, by the case of m sequence. Depending on the description of coding theory, we introduce the jamming methods. We simulate the interference effect or probability model by the means of MATLAB to consolidate. In accordance with the length of decoding time the adversary spends, we find out the optimal formula and optimal coefficients based on machine learning, then we get the new optimal interference code. First, when it comes to the phase of recognition, this study judges the effect of interference by the way of simulating the length of time over the decoding period of laser seeker. Then, we use laser active deception jamming simulate interference process in the tracking phase in the next block. In this study we choose the method of laser active deception jamming. In order to improve the performance of the interference, this paper simulates the model by MATLAB software. We find out the least number of pulse intervals which must be received, then we can make the conclusion that the precise interval number of the laser pointer for m sequence encoding. In order to find the shortest space, we make the choice of the greatest common divisor method. Then, combining with the coding regularity that has been found before, we restore pulse interval of pseudo-random code, which has been already received. Finally, we can control the time period of laser interference, get the optimal interference code, and also increase the probability of interference as well.
Optimal non-linear health insurance.
Blomqvist, A
1997-06-01
Most theoretical and empirical work on efficient health insurance has been based on models with linear insurance schedules (a constant co-insurance parameter). In this paper, dynamic optimization techniques are used to analyse the properties of optimal non-linear insurance schedules in a model similar to one originally considered by Spence and Zeckhauser (American Economic Review, 1971, 61, 380-387) and reminiscent of those that have been used in the literature on optimal income taxation. The results of a preliminary numerical example suggest that the welfare losses from the implicit subsidy to employer-financed health insurance under US tax law may be a good deal smaller than previously estimated using linear models.
Optimal patch code design via device characterization
Wu, Wencheng; Dalal, Edul N.
2012-01-01
In many color measurement applications, such as those for color calibration and profiling, "patch code" has been used successfully for job identification and automation to reduce operator errors. A patch code is similar to a barcode, but is intended primarily for use in measurement devices that cannot read barcodes due to limited spatial resolution, such as spectrophotometers. There is an inherent tradeoff between decoding robustness and the number of code levels available for encoding. Previous methods have attempted to address this tradeoff, but those solutions have been sub-optimal. In this paper, we propose a method to design optimal patch codes via device characterization. The tradeoff between decoding robustness and the number of available code levels is optimized in terms of printing and measurement efforts, and decoding robustness against noises from the printing and measurement devices. Effort is drastically reduced relative to previous methods because print-and-measure is minimized through modeling and the use of existing printer profiles. Decoding robustness is improved by distributing the code levels in CIE Lab space rather than in CMYK space.
Optimization of nonlinear wave function parameters
International Nuclear Information System (INIS)
Shepard, R.; Minkoff, M.; Chemistry
2006-01-01
An energy-based optimization method is presented for our recently developed nonlinear wave function expansion form for electronic wave functions. This expansion form is based on spin eigenfunctions, using the graphical unitary group approach (GUGA). The wave function is expanded in a basis of product functions, allowing application to closed-shell and open-shell systems and to ground and excited electronic states. Each product basis function is itself a multiconfigurational function that depends on a relatively small number of nonlinear parameters called arc factors. The energy-based optimization is formulated in terms of analytic arc factor gradients and orbital-level Hamiltonian matrices that correspond to a specific kind of uncontraction of each of the product basis functions. These orbital-level Hamiltonian matrices give an intuitive representation of the energy in terms of disjoint subsets of the arc factors, they provide for an efficient computation of gradients of the energy with respect to the arc factors, and they allow optimal arc factors to be determined in closed form for subspaces of the full variation problem. Timings for energy and arc factor gradient computations involving expansion spaces of > 10 24 configuration state functions are reported. Preliminary convergence studies and molecular dissociation curves are presented for some small molecules
Optimized reversible binary-coded decimal adders
DEFF Research Database (Denmark)
Thomsen, Michael Kirkedal; Glück, Robert
2008-01-01
Abstract Babu and Chowdhury [H.M.H. Babu, A.R. Chowdhury, Design of a compact reversible binary coded decimal adder circuit, Journal of Systems Architecture 52 (5) (2006) 272-282] recently proposed, in this journal, a reversible adder for binary-coded decimals. This paper corrects and optimizes...... their design. The optimized 1-decimal BCD full-adder, a 13 × 13 reversible logic circuit, is faster, and has lower circuit cost and less garbage bits. It can be used to build a fast reversible m-decimal BCD full-adder that has a delay of only m + 17 low-power reversible CMOS gates. For a 32-decimal (128-bit....... Keywords: Reversible logic circuit; Full-adder; Half-adder; Parallel adder; Binary-coded decimal; Application of reversible logic synthesis...
The history and development of nonlinear stellar pulsation codes
International Nuclear Information System (INIS)
Davis, C.G.
1987-01-01
This review is limited to the history and development of nonlinear stellar pulsation codes and methods. The narrative includes examples of practical interest in the application of these numerical methods to problems in stellar pulsation such as Cepheid mass discrepancy, the delineation of the RR Lyrae instability strip, and the question of the development of double-mode pulsation as observed in Cepheids, RR Lyrae and other variable stars. 15 refs
A nonlinear resistive MHD-code in cylindrical geometry
International Nuclear Information System (INIS)
Jakoby, A.
1987-11-01
A computer code has been developed which solves the full compressible resistive magnetohydrodynamic (MHD) equations in cylindrical geometry. The variables are expanded in Fourier series in the poloidal and axial directions while finite differences are used in the radial direction. The time advance is accomplished by using a semi-implicit predictor-corrector-scheme. Applications to the ideal m=1 ideal kink saturation in the nonlinear regime and the subsequent decay of the singular current layer due to resistivity are presented. (orig.)
Gradient-based optimization in nonlinear structural dynamics
DEFF Research Database (Denmark)
Dou, Suguang
The intrinsic nonlinearity of mechanical structures can give rise to rich nonlinear dynamics. Recently, nonlinear dynamics of micro-mechanical structures have contributed to developing new Micro-Electro-Mechanical Systems (MEMS), for example, atomic force microscope, passive frequency divider......, frequency stabilization, and disk resonator gyroscope. For advanced design of these structures, it is of considerable value to extend current optimization in linear structural dynamics into nonlinear structural dynamics. In this thesis, we present a framework for modelling, analysis, characterization......, and optimization of nonlinear structural dynamics. In the modelling, nonlinear finite elements are used. In the analysis, nonlinear frequency response and nonlinear normal modes are calculated based on a harmonic balance method with higher-order harmonics. In the characterization, nonlinear modal coupling...
COMPARISON OF NONLINEAR DYNAMICS OPTIMIZATION METHODS FOR APS-U
Energy Technology Data Exchange (ETDEWEB)
Sun, Y.; Borland, Michael
2017-06-25
Many different objectives and genetic algorithms have been proposed for storage ring nonlinear dynamics performance optimization. These optimization objectives include nonlinear chromaticities and driving/detuning terms, on-momentum and off-momentum dynamic acceptance, chromatic detuning, local momentum acceptance, variation of transverse invariant, Touschek lifetime, etc. In this paper, the effectiveness of several different optimization methods and objectives are compared for the nonlinear beam dynamics optimization of the Advanced Photon Source upgrade (APS-U) lattice. The optimized solutions from these different methods are preliminarily compared in terms of the dynamic acceptance, local momentum acceptance, chromatic detuning, and other performance measures.
Nonlinearity Analysis and Parameters Optimization for an Inductive Angle Sensor
Directory of Open Access Journals (Sweden)
Lin Ye
2014-02-01
Full Text Available Using the finite element method (FEM and particle swarm optimization (PSO, a nonlinearity analysis based on parameter optimization is proposed to design an inductive angle sensor. Due to the structure complexity of the sensor, understanding the influences of structure parameters on the nonlinearity errors is a critical step in designing an effective sensor. Key parameters are selected for the design based on the parameters’ effects on the nonlinearity errors. The finite element method and particle swarm optimization are combined for the sensor design to get the minimal nonlinearity error. In the simulation, the nonlinearity error of the optimized sensor is 0.053% in the angle range from −60° to 60°. A prototype sensor is manufactured and measured experimentally, and the experimental nonlinearity error is 0.081% in the angle range from −60° to 60°.
Constellation labeling optimization for bit-interleaved coded APSK
Xiang, Xingyu; Mo, Zijian; Wang, Zhonghai; Pham, Khanh; Blasch, Erik; Chen, Genshe
2016-05-01
This paper investigates the constellation and mapping optimization for amplitude phase shift keying (APSK) modulation, which is deployed in Digital Video Broadcasting Satellite - Second Generation (DVB-S2) and Digital Video Broadcasting - Satellite services to Handhelds (DVB-SH) broadcasting standards due to its merits of power and spectral efficiency together with the robustness against nonlinear distortion. The mapping optimization is performed for 32-APSK according to combined cost functions related to Euclidean distance and mutual information. A Binary switching algorithm and its modified version are used to minimize the cost function and the estimated error between the original and received data. The optimized constellation mapping is tested by combining DVB-S2 standard Low-Density Parity-Check (LDPC) codes in both Bit-Interleaved Coded Modulation (BICM) and BICM with iterative decoding (BICM-ID) systems. The simulated results validate the proposed constellation labeling optimization scheme which yields better performance against conventional 32-APSK constellation defined in DVB-S2 standard.
Nonlinear optimal perturbations in a curved pipe
Rinaldi, Enrico; Canton, Jacopo; Marin, Oana; Schanen, Michel; Schlatter, Philipp
2017-11-01
We investigate the effect of curvature on transition to turbulence in pipes by comparing optimal perturbations of finite amplitude that maximise their energy growth in a toroidal geometry to the ones calculated in the absence of curvature. Our interest is motivated by the fact that even small curvatures, of the order of d =Rpipe /Rtorus art numerical algorithms, capable of tackling the optimisation problem on large computational domains, coupled to a high-order spectral-element code, which is used to perform direct numerical simulations (DNS) of the full Navier-Stokes and their adjoint equations. Results are compared to the corresponding states in straight pipes and differences in their structure and evolution are discussed. Furthermore, the newly calculated initial conditions are used to identify coherent flow structures that are compared to the ones observed in recent DNS of weakly turbulent and relaminarising flows in the same toroidal geometry.
Optimizing Extender Code for NCSX Analyses
International Nuclear Information System (INIS)
Richman, M.; Ethier, S.; Pomphrey, N.
2008-01-01
Extender is a parallel C++ code for calculating the magnetic field in the vacuum region of a stellarator. The code was optimized for speed and augmented with tools to maintain a specialized NetCDF database. Two parallel algorithms were examined. An even-block work-distribution scheme was comparable in performance to a master-slave scheme. Large speedup factors were achieved by representing the plasma surface with a spline rather than Fourier series. The accuracy of this representation and the resulting calculations relied on the density of the spline mesh. The Fortran 90 module db access was written to make it easy to store Extender output in a manageable database. New or updated data can be added to existing databases. A generalized PBS job script handles the generation of a database from scratch
Topology optimization of nonlinear optical devices
DEFF Research Database (Denmark)
Jensen, Jakob Søndergaard
2011-01-01
This paper considers the design of nonlinear photonic devices. The nonlinearity stems from a nonlinear material model with a permittivity that depends on the local time-averaged intensity of the electric field. A finite element model is developed for time-harmonic wave propagation and an incremen......This paper considers the design of nonlinear photonic devices. The nonlinearity stems from a nonlinear material model with a permittivity that depends on the local time-averaged intensity of the electric field. A finite element model is developed for time-harmonic wave propagation...... limiter. Here, air, a linear and a nonlinear material are distributed so that the wave transmission displays a strong sensitivity to the amplitude of the incoming wave....
Continuous nonlinear optimization for engineering applications in GAMS technology
Andrei, Neculai
2017-01-01
This book presents the theoretical details and computational performances of algorithms used for solving continuous nonlinear optimization applications imbedded in GAMS. Aimed toward scientists and graduate students who utilize optimization methods to model and solve problems in mathematical programming, operations research, business, engineering, and industry, this book enables readers with a background in nonlinear optimization and linear algebra to use GAMS technology to understand and utilize its important capabilities to optimize algorithms for modeling and solving complex, large-scale, continuous nonlinear optimization problems or applications. Beginning with an overview of constrained nonlinear optimization methods, this book moves on to illustrate key aspects of mathematical modeling through modeling technologies based on algebraically oriented modeling languages. Next, the main feature of GAMS, an algebraically oriented language that allows for high-level algebraic representation of mathematical opti...
Code Differentiation for Hydrodynamic Model Optimization
Energy Technology Data Exchange (ETDEWEB)
Henninger, R.J.; Maudlin, P.J.
1999-06-27
Use of a hydrodynamics code for experimental data fitting purposes (an optimization problem) requires information about how a computed result changes when the model parameters change. These so-called sensitivities provide the gradient that determines the search direction for modifying the parameters to find an optimal result. Here, the authors apply code-based automatic differentiation (AD) techniques applied in the forward and adjoint modes to two problems with 12 parameters to obtain these gradients and compare the computational efficiency and accuracy of the various methods. They fit the pressure trace from a one-dimensional flyer-plate experiment and examine the accuracy for a two-dimensional jet-formation problem. For the flyer-plate experiment, the adjoint mode requires similar or less computer time than the forward methods. Additional parameters will not change the adjoint mode run time appreciably, which is a distinct advantage for this method. Obtaining ''accurate'' sensitivities for the j et problem parameters remains problematic.
On a Highly Nonlinear Self-Obstacle Optimal Control Problem
Energy Technology Data Exchange (ETDEWEB)
Di Donato, Daniela, E-mail: daniela.didonato@unitn.it [University of Trento, Department of Mathematics (Italy); Mugnai, Dimitri, E-mail: dimitri.mugnai@unipg.it [Università di Perugia, Dipartimento di Matematica e Informatica (Italy)
2015-10-15
We consider a non-quadratic optimal control problem associated to a nonlinear elliptic variational inequality, where the obstacle is the control itself. We show that, fixed a desired profile, there exists an optimal solution which is not far from it. Detailed characterizations of the optimal solution are given, also in terms of approximating problems.
Parallel Nonlinear Optimization for Astrodynamic Navigation, Phase I
National Aeronautics and Space Administration — CU Aerospace proposes the development of a new parallel nonlinear program (NLP) solver software package. NLPs allow the solution of complex optimization problems,...
A Nonlinear Fuel Optimal Reaction Jet Control Law
National Research Council Canada - National Science Library
Breitfeller, Eric
2002-01-01
We derive a nonlinear fuel optimal attitude control system (ACS) that drives the final state to the desired state according to a cost function that weights the final state angular error relative to the angular rate error...
Optimization of nonlinear controller with an enhanced biogeography approach
Directory of Open Access Journals (Sweden)
Mohammed Salem
2014-07-01
Full Text Available This paper is dedicated to the optimization of nonlinear controllers basing of an enhanced Biogeography Based Optimization (BBO approach. Indeed, The BBO is combined to a predator and prey model where several predators are used with introduction of a modified migration operator to increase the diversification along the optimization process so as to avoid local optima and reach the optimal solution quickly. The proposed approach is used in tuning the gains of PID controller for nonlinear systems. Simulations are carried out over a Mass spring damper and an inverted pendulum and has given remarkable results when compared to genetic algorithm and BBO.
Directory of Open Access Journals (Sweden)
Jinmyoung Seok
2015-07-01
Full Text Available In this article, we are interested in singularly perturbed nonlinear elliptic problems involving a fractional Laplacian. Under a class of nonlinearity which is believed to be almost optimal, we construct a positive solution which exhibits multiple spikes near any given local minimum components of an exterior potential of the problem.
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
Optimal, Reliability-Based Code Calibration
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2002-01-01
Reliability based code calibration is considered in this paper. It is described how the results of FORM based reliability analysis may be related to the partial safety factors and characteristic values. The code calibration problem is presented in a decision theoretical form and it is discussed how...... of reliability based code calibration of LRFD based design codes....
Investigation of Navier-Stokes Code Verification and Design Optimization
Vaidyanathan, Rajkumar
2004-01-01
With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization
C code generation applied to nonlinear model predictive control for an artificial pancreas
DEFF Research Database (Denmark)
Boiroux, Dimitri; Jørgensen, John Bagterp
2017-01-01
This paper presents a method to generate C code from MATLAB code applied to a nonlinear model predictive control (NMPC) algorithm. The C code generation uses the MATLAB Coder Toolbox. It can drastically reduce the time required for development compared to a manual porting of code from MATLAB to C...
Non-binary Hybrid LDPC Codes: Structure, Decoding and Optimization
Sassatelli, Lucile; Declercq, David
2007-01-01
In this paper, we propose to study and optimize a very general class of LDPC codes whose variable nodes belong to finite sets with different orders. We named this class of codes Hybrid LDPC codes. Although efficient optimization techniques exist for binary LDPC codes and more recently for non-binary LDPC codes, they both exhibit drawbacks due to different reasons. Our goal is to capitalize on the advantages of both families by building codes with binary (or small finite set order) and non-bin...
A Linearized Relaxing Algorithm for the Specific Nonlinear Optimization Problem
Directory of Open Access Journals (Sweden)
Mio Horai
2016-01-01
Full Text Available We propose a new method for the specific nonlinear and nonconvex global optimization problem by using a linear relaxation technique. To simplify the specific nonlinear and nonconvex optimization problem, we transform the problem to the lower linear relaxation form, and we solve the linear relaxation optimization problem by the Branch and Bound Algorithm. Under some reasonable assumptions, the global convergence of the algorithm is certified for the problem. Numerical results show that this method is more efficient than the previous methods.
Optimal Nonlinear Filter for INS Alignment
Institute of Scientific and Technical Information of China (English)
赵瑞; 顾启泰
2002-01-01
All the methods to handle the inertial navigation system (INS) alignment were sub-optimal in the past. In this paper, particle filtering (PF) as an optimal method is used for solving the problem of INS alignment. A sub-optimal two-step filtering algorithm is presented to improve the real-time performance of PF. The approach combines particle filtering with Kalman filtering (KF). Simulation results illustrate the superior performance of these approaches when compared with extended Kalman filtering (EKF).
Galerkin approximations of nonlinear optimal control problems in Hilbert spaces
Directory of Open Access Journals (Sweden)
Mickael D. Chekroun
2017-07-01
Full Text Available Nonlinear optimal control problems in Hilbert spaces are considered for which we derive approximation theorems for Galerkin approximations. Approximation theorems are available in the literature. The originality of our approach relies on the identification of a set of natural assumptions that allows us to deal with a broad class of nonlinear evolution equations and cost functionals for which we derive convergence of the value functions associated with the optimal control problem of the Galerkin approximations. This convergence result holds for a broad class of nonlinear control strategies as well. In particular, we show that the framework applies to the optimal control of semilinear heat equations posed on a general compact manifold without boundary. The framework is then shown to apply to geoengineering and mitigation of greenhouse gas emissions formulated here in terms of optimal control of energy balance climate models posed on the sphere $\\mathbb{S}^2$.
Introduction to the theory of nonlinear optimization
Jahn, Johannes
2007-01-01
This book serves as an introductory text to optimization theory in normed spaces. The topics of this book are existence results, various differentiability notions together with optimality conditions, the contingent cone, a generalization of the Lagrange multiplier rule, duality theory, extended semidefinite optimization, and the investigation of linear quadratic and time minimal control problems. This textbook presents fundamentals with particular emphasis on the application to problems in the calculus of variations, approximation and optimal control theory. The reader is expected to have a ba
Performance of Different OCDMA Codes with FWM and XPM Nonlinear Effects
Rana, Shivani; Gupta, Amit
2017-08-01
In this paper, 1 Gb/s non-linear optical code division multiple access system have been simulated and modeled. To reduce multiple user interference multi-diagonal (MD) code which possesses the property of having zero cross-correlation have been deployed. The MD code shows better results than Walsh-Hadamard and multi-weight code under the nonlinear effect of four-wave mixing (FWM) and cross-phase modulation (XPM). The simulation results reveal that effect of FWM reduces when MD codes are employed as compared to other codes.
THE OPTIMAL CONTROL IN THE MODELOF NETWORK SECURITY FROM MALICIOUS CODE
Directory of Open Access Journals (Sweden)
2016-01-01
Full Text Available The paper deals with a mathematical model of network security. The model is described in terms of the nonlinear optimal control. As a criterion of the control problem quality the price of the summary damage inflicted by the harmful codes is chosen, under additional restriction: the number of recovered nodes is maximized. The Pontryagin maximum principle for construction of the optimal decisions is formulated. The number of switching points of the optimal control is found. The explicit form of optimal control is given using the Lagrange multipliers method.
Nonlinear demodulation and channel coding in EBPSK scheme.
Chen, Xianqing; Wu, Lenan
2012-01-01
The extended binary phase shift keying (EBPSK) is an efficient modulation technique, and a special impacting filter (SIF) is used in its demodulator to improve the bit error rate (BER) performance. However, the conventional threshold decision cannot achieve the optimum performance, and the SIF brings more difficulty in obtaining the posterior probability for LDPC decoding. In this paper, we concentrate not only on reducing the BER of demodulation, but also on providing accurate posterior probability estimates (PPEs). A new approach for the nonlinear demodulation based on the support vector machine (SVM) classifier is introduced. The SVM method which selects only a few sampling points from the filter output was used for getting PPEs. The simulation results show that the accurate posterior probability can be obtained with this method and the BER performance can be improved significantly by applying LDPC codes. Moreover, we analyzed the effect of getting the posterior probability with different methods and different sampling rates. We show that there are more advantages of the SVM method under bad condition and it is less sensitive to the sampling rate than other methods. Thus, SVM is an effective method for EBPSK demodulation and getting posterior probability for LDPC decoding.
A new optimization algotithm with application to nonlinear MPC
Directory of Open Access Journals (Sweden)
Frode Martinsen
2005-01-01
Full Text Available This paper investigates application of SQP optimization algorithm to nonlinear model predictive control. It considers feasible vs. infeasible path methods, sequential vs. simultaneous methods and reduced vs full space methods. A new optimization algorithm coined rFOPT which remains feasibile with respect to inequality constraints is introduced. The suitable choices between these various strategies are assessed informally through a small CSTR case study. The case study also considers the effect various discretization methods have on the optimization problem.
Optimal beamforming in MIMO systems with HPA nonlinearity
Qi, Jian
2010-09-01
In this paper, multiple-input multiple-output (MIMO) transmit beamforming (TB) systems under the consideration of nonlinear high-power amplifiers (HPAs) are investigated. The optimal beamforming scheme, with the optimal beamforming weight vector and combining vector, is proposed for MIMO systems with HPA nonlinearity. The performance of the proposed MIMO beamforming scheme in the presence of HPA nonlinearity is evaluated in terms of average symbol error probability (SEP), outage probability and system capacity, considering transmission over uncorrelated quasi-static frequency-flat Rayleigh fading channels. Numerical results are provided and show the effects of several system parameters, namely, parameters of nonlinear HPA, numbers of transmit and receive antennas, and modulation order of phase-shift keying (PSK), on performance. ©2010 IEEE.
Optimal beamforming in MIMO systems with HPA nonlinearity
Qi, Jian; Aissa, Sonia
2010-01-01
In this paper, multiple-input multiple-output (MIMO) transmit beamforming (TB) systems under the consideration of nonlinear high-power amplifiers (HPAs) are investigated. The optimal beamforming scheme, with the optimal beamforming weight vector and combining vector, is proposed for MIMO systems with HPA nonlinearity. The performance of the proposed MIMO beamforming scheme in the presence of HPA nonlinearity is evaluated in terms of average symbol error probability (SEP), outage probability and system capacity, considering transmission over uncorrelated quasi-static frequency-flat Rayleigh fading channels. Numerical results are provided and show the effects of several system parameters, namely, parameters of nonlinear HPA, numbers of transmit and receive antennas, and modulation order of phase-shift keying (PSK), on performance. ©2010 IEEE.
Non-linear programming method in optimization of fast reactors
International Nuclear Information System (INIS)
Pavelesku, M.; Dumitresku, Kh.; Adam, S.
1975-01-01
Application of the non-linear programming methods on optimization of nuclear materials distribution in fast reactor is discussed. The programming task composition is made on the basis of the reactor calculation dependent on the fuel distribution strategy. As an illustration of this method application the solution of simple example is given. Solution of the non-linear program is done on the basis of the numerical method SUMT. (I.T.)
Optimal Reliability-Based Code Calibration
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Kroon, I. B.; Faber, Michael Havbro
1994-01-01
Calibration of partial safety factors is considered in general, including classes of structures where no code exists beforehand. The partial safety factors are determined such that the difference between the reliability for the different structures in the class considered and a target reliability...... level is minimized. Code calibration on a decision theoretical basis is also considered and it is shown how target reliability indices can be calibrated. Results from code calibration for rubble mound breakwater designs are shown....
Optimal super dense coding over memory channels
Shadman, Zahra; Kampermann, Hermann; Macchiavello, Chiara; Bruß, Dagmar
2011-01-01
We study the super dense coding capacity in the presence of quantum channels with correlated noise. We investigate both the cases of unitary and non-unitary encoding. Pauli channels for arbitrary dimensions are treated explicitly. The super dense coding capacity for some special channels and resource states is derived for unitary encoding. We also provide an example of a memory channel where non-unitary encoding leads to an improvement in the super dense coding capacity.
Efficient topology optimization in MATLAB using 88 lines of code
DEFF Research Database (Denmark)
Andreassen, Erik; Clausen, Anders; Schevenels, Mattias
2011-01-01
The paper presents an efficient 88 line MATLAB code for topology optimization. It has been developed using the 99 line code presented by Sigmund (Struct Multidisc Optim 21(2):120–127, 2001) as a starting point. The original code has been extended by a density filter, and a considerable improvemen...... of the basic code to include recent PDE-based and black-and-white projection filtering methods. The complete 88 line code is included as an appendix and can be downloaded from the web site www.topopt.dtu.dk....
Conference on High Performance Software for Nonlinear Optimization
Murli, Almerico; Pardalos, Panos; Toraldo, Gerardo
1998-01-01
This book contains a selection of papers presented at the conference on High Performance Software for Nonlinear Optimization (HPSN097) which was held in Ischia, Italy, in June 1997. The rapid progress of computer technologies, including new parallel architec tures, has stimulated a large amount of research devoted to building software environments and defining algorithms able to fully exploit this new computa tional power. In some sense, numerical analysis has to conform itself to the new tools. The impact of parallel computing in nonlinear optimization, which had a slow start at the beginning, seems now to increase at a fast rate, and it is reasonable to expect an even greater acceleration in the future. As with the first HPSNO conference, the goal of the HPSN097 conference was to supply a broad overview of the more recent developments and trends in nonlinear optimization, emphasizing the algorithmic and high performance software aspects. Bringing together new computational methodologies with theoretical...
Optimization under uncertainty of parallel nonlinear energy sinks
Boroson, Ethan; Missoum, Samy; Mattei, Pierre-Olivier; Vergez, Christophe
2017-04-01
Nonlinear Energy Sinks (NESs) are a promising technique for passively reducing the amplitude of vibrations. Through nonlinear stiffness properties, a NES is able to passively and irreversibly absorb energy. Unlike the traditional Tuned Mass Damper (TMD), NESs do not require a specific tuning and absorb energy over a wider range of frequencies. Nevertheless, they are still only efficient over a limited range of excitations. In order to mitigate this limitation and maximize the efficiency range, this work investigates the optimization of multiple NESs configured in parallel. It is well known that the efficiency of a NES is extremely sensitive to small perturbations in loading conditions or design parameters. In fact, the efficiency of a NES has been shown to be nearly discontinuous in the neighborhood of its activation threshold. For this reason, uncertainties must be taken into account in the design optimization of NESs. In addition, the discontinuities require a specific treatment during the optimization process. In this work, the objective of the optimization is to maximize the expected value of the efficiency of NESs in parallel. The optimization algorithm is able to tackle design variables with uncertainty (e.g., nonlinear stiffness coefficients) as well as aleatory variables such as the initial velocity of the main system. The optimal design of several parallel NES configurations for maximum mean efficiency is investigated. Specifically, NES nonlinear stiffness properties, considered random design variables, are optimized for cases with 1, 2, 3, 4, 5, and 10 NESs in parallel. The distributions of efficiency for the optimal parallel configurations are compared to distributions of efficiencies of non-optimized NESs. It is observed that the optimization enables a sharp increase in the mean value of efficiency while reducing the corresponding variance, thus leading to more robust NES designs.
Using Peephole Optimization on Intermediate Code
Tanenbaum, A.S.; van Staveren, H.; Stevenson, J.W.
1982-01-01
Many portable compilers generate an intermediate code that is subsequently translated into the target machine's assembly language. In this paper a stack-machine-based intermediate code suitable for algebraic languages (e.g., PASCAL, C, FORTRAN) and most byte-addressed mini- and microcomputers is
Approaches to the Optimal Nonlinear Analysis of Microcalorimeter Pulses
Fowler, J. W.; Pappas, C. G.; Alpert, B. K.; Doriese, W. B.; O'Neil, G. C.; Ullom, J. N.; Swetz, D. S.
2018-03-01
We consider how to analyze microcalorimeter pulses for quantities that are nonlinear in the data, while preserving the signal-to-noise advantages of linear optimal filtering. We successfully apply our chosen approach to compute the electrothermal feedback energy deficit (the "Joule energy") of a pulse, which has been proposed as a linear estimator of the deposited photon energy.
New preconditioned conjugate gradient algorithms for nonlinear unconstrained optimization problems
International Nuclear Information System (INIS)
Al-Bayati, A.; Al-Asadi, N.
1997-01-01
This paper presents two new predilection conjugate gradient algorithms for nonlinear unconstrained optimization problems and examines their computational performance. Computational experience shows that the new proposed algorithms generally imp lone the efficiency of Nazareth's [13] preconditioned conjugate gradient algorithm. (authors). 16 refs., 1 tab
Coded aperture optimization using Monte Carlo simulations
International Nuclear Information System (INIS)
Martineau, A.; Rocchisani, J.M.; Moretti, J.L.
2010-01-01
Coded apertures using Uniformly Redundant Arrays (URA) have been unsuccessfully evaluated for two-dimensional and three-dimensional imaging in Nuclear Medicine. The images reconstructed from coded projections contain artifacts and suffer from poor spatial resolution in the longitudinal direction. We introduce a Maximum-Likelihood Expectation-Maximization (MLEM) algorithm for three-dimensional coded aperture imaging which uses a projection matrix calculated by Monte Carlo simulations. The aim of the algorithm is to reduce artifacts and improve the three-dimensional spatial resolution in the reconstructed images. Firstly, we present the validation of GATE (Geant4 Application for Emission Tomography) for Monte Carlo simulations of a coded mask installed on a clinical gamma camera. The coded mask modelling was validated by comparison between experimental and simulated data in terms of energy spectra, sensitivity and spatial resolution. In the second part of the study, we use the validated model to calculate the projection matrix with Monte Carlo simulations. A three-dimensional thyroid phantom study was performed to compare the performance of the three-dimensional MLEM reconstruction with conventional correlation method. The results indicate that the artifacts are reduced and three-dimensional spatial resolution is improved with the Monte Carlo-based MLEM reconstruction.
Optimization Specifications for CUDA Code Restructuring Tool
Khan, Ayaz
2017-01-01
and convert it into an optimized CUDA kernel with user directives in a configuration file for guiding the compiler. RTCUDA also allows transparent invocation of the most optimized external math libraries like cuSparse and cuBLAS enabling efficient design
Route Monopolie and Optimal Nonlinear Pricing
Tournut, Jacques
2003-01-01
To cope with air traffic growth and congested airports, two solutions are apparent on the supply side: 1) use larger aircraft in the hub and spoke system; or 2) develop new routes through secondary airports. An enlarged route system through secondary airports may increase the proportion of route monopolies in the air transport market.The monopoly optimal non linear pricing policy is well known in the case of one dimension (one instrument, one characteristic) but not in the case of several dimensions. This paper explores the robustness of the one dimensional screening model with respect to increasing the number of instruments and the number of characteristics. The objective of this paper is then to link and fill the gap in both literatures. One of the merits of the screening model has been to show that a great varieD" of economic questions (non linear pricing, product line choice, auction design, income taxation, regulation...) could be handled within the same framework.VCe study a case of non linear pricing (2 instruments (2 routes on which the airline pro_ddes customers with services), 2 characteristics (demand of services on these routes) and two values per characteristic (low and high demand of services on these routes)) and we show that none of the conclusions of the one dimensional analysis remain valid. In particular, upward incentive compatibility constraint may be binding at the optimum. As a consequence, they may be distortion at the top of the distribution. In addition to this, we show that the optimal solution often requires a kind of form of bundling, we explain explicitly distortions and show that it is sometimes optimal for the monopolist to only produce one good (instead of two) or to exclude some buyers from the market. Actually, this means that the monopolist cannot fully apply his monopoly power and is better off selling both goods independently.We then define all the possible solutions in the case of a quadratic cost function for a uniform
Nonlinear spike-and-slab sparse coding for interpretable image encoding.
Directory of Open Access Journals (Sweden)
Jacquelyn A Shelton
Full Text Available Sparse coding is a popular approach to model natural images but has faced two main challenges: modelling low-level image components (such as edge-like structures and their occlusions and modelling varying pixel intensities. Traditionally, images are modelled as a sparse linear superposition of dictionary elements, where the probabilistic view of this problem is that the coefficients follow a Laplace or Cauchy prior distribution. We propose a novel model that instead uses a spike-and-slab prior and nonlinear combination of components. With the prior, our model can easily represent exact zeros for e.g. the absence of an image component, such as an edge, and a distribution over non-zero pixel intensities. With the nonlinearity (the nonlinear max combination rule, the idea is to target occlusions; dictionary elements correspond to image components that can occlude each other. There are major consequences of the model assumptions made by both (nonlinear approaches, thus the main goal of this paper is to isolate and highlight differences between them. Parameter optimization is analytically and computationally intractable in our model, thus as a main contribution we design an exact Gibbs sampler for efficient inference which we can apply to higher dimensional data using latent variable preselection. Results on natural and artificial occlusion-rich data with controlled forms of sparse structure show that our model can extract a sparse set of edge-like components that closely match the generating process, which we refer to as interpretable components. Furthermore, the sparseness of the solution closely follows the ground-truth number of components/edges in the images. The linear model did not learn such edge-like components with any level of sparsity. This suggests that our model can adaptively well-approximate and characterize the meaningful generation process.
Development of non-linear vibration analysis code for CANDU fuelling machine
International Nuclear Information System (INIS)
Murakami, Hajime; Hirai, Takeshi; Horikoshi, Kiyomi; Mizukoshi, Kaoru; Takenaka, Yasuo; Suzuki, Norio.
1988-01-01
This paper describes the development of a non-linear, dynamic analysis code for the CANDU 600 fuelling machine (F-M), which includes a number of non-linearities such as gap with or without Coulomb friction, special multi-linear spring connections, etc. The capabilities and features of the code and the mathematical treatment for the non-linearities are explained. The modeling and numerical methodology for the non-linearities employed in the code are verified experimentally. Finally, the simulation analyses for the full-scale F-M vibration testing are carried out, and the applicability of the code to such multi-degree of freedom systems as F-M is demonstrated. (author)
Optimization Specifications for CUDA Code Restructuring Tool
Khan, Ayaz
2017-03-13
In this work we have developed a restructuring software tool (RT-CUDA) following the proposed optimization specifications to bridge the gap between high-level languages and the machine dependent CUDA environment. RT-CUDA takes a C program and convert it into an optimized CUDA kernel with user directives in a configuration file for guiding the compiler. RTCUDA also allows transparent invocation of the most optimized external math libraries like cuSparse and cuBLAS enabling efficient design of linear algebra solvers. We expect RT-CUDA to be needed by many KSA industries dealing with science and engineering simulation on massively parallel computers like NVIDIA GPUs.
Nonlinear adaptive optimization of biomass productivity in continuous bioreactors
Energy Technology Data Exchange (ETDEWEB)
Sauvaire, P; Mellichamp, D A; Agrawal, P [California Univ., Santa Barbara, CA (United States). Dept. of Chemical and Nuclear Engineering
1991-11-01
A novel on-line adaptive optimization algorithm is developed and applied to continuous biological reactors. The algorithm makes use of a simple nonlinear estimation model that relates either the cell-mass productivity or the cell-mass concentration to the dilution rate. On-line estimation is used to recursively identify the parameters in the nonlinear process model and to periodically calculate and steer the bioreactor to the dilution rate that yields optimum cell-mass productivity. Thus, the algorithm does not require an accurate process model, locates the optimum dilution rate online, and maintains the bioreactors at this optimum condition at all times. The features of the proposed new algorithm are compared with those of other adaptive optimization techniques presented in the literature. A detailed simulation study using three different microbial system models was conducted to illustrate the performance of the optimization algorithms. (orig.).
ARC Code TI: Optimal Alarm System Design and Implementation
National Aeronautics and Space Administration — An optimal alarm system can robustly predict a level-crossing event that is specified over a fixed prediction horizon. The code contained in this packages provides...
VVER-440 loading patterns optimization using ATHENA code
International Nuclear Information System (INIS)
Katovsky, K.; Sustek, J.; Bajgl, J.; Cada, R.
2009-01-01
In this paper the Czech optimization state-of-the-art, new code system development goals and OPAL optimization system are briefly mentioned. The algorithms, maths, present status and future developments of the ATHENA code are described. A calculation exercise of the Dukovany NPP cycles, on increased power using ATHENA, starting with on-coming 24th cycle (303 FPD) continuing with 25th (322 FPD), and 26th (336 FPD); for all cycles K R ≤1.54 is presented
Optimizing the ATLAS code with different profilers
Kama, S; The ATLAS collaboration
2013-01-01
After the current maintenance period, the LHC will provide higher energy collisions with increased luminosity. In order to keep up with these higher rates, ATLAS software needs to speed up substantially. However, ATLAS code is composed of approximately 4M lines, written by many different programmers with different backgrounds, which makes code optimisation a challenge. To help with this effort different profiling tools and techniques are being used. These include well known tools, such as the Valgrind suite and Intel Amplifier; less common tools like PIN, PAPI, and GOODA; as well as techniques such as library interposing. In this talk we will mainly focus on PIN tools and GOODA. PIN is a dynamic binary instrumentation tool which can obtain statistics such as call counts, instruction counts and interrogate functions' arguments. It has been used to obtain CLHEP Matrix profiles, operations and vector sizes for linear algebra calculations which has provided the insight necessary to achieve significant performance...
Optimization of Particle-in-Cell Codes on RISC Processors
Decyk, Viktor K.; Karmesin, Steve Roy; Boer, Aeint de; Liewer, Paulette C.
1996-01-01
General strategies are developed to optimize particle-cell-codes written in Fortran for RISC processors which are commonly used on massively parallel computers. These strategies include data reorganization to improve cache utilization and code reorganization to improve efficiency of arithmetic pipelines.
Adaptive RD Optimized Hybrid Sound Coding
Schijndel, N.H. van; Bensa, J.; Christensen, M.G.; Colomes, C.; Edler, B.; Heusdens, R.; Jensen, J.; Jensen, S.H.; Kleijn, W.B.; Kot, V.; Kövesi, B.; Lindblom, J.; Massaloux, D.; Niamut, O.A.; Nordén, F.; Plasberg, J.H.; Vafin, R.; Virette, D.; Wübbolt, O.
2008-01-01
Traditionally, sound codecs have been developed with a particular application in mind, their performance being optimized for specific types of input signals, such as speech or audio (music), and application constraints, such as low bit rate, high quality, or low delay. There is, however, an
New Exact Penalty Functions for Nonlinear Constrained Optimization Problems
Directory of Open Access Journals (Sweden)
Bingzhuang Liu
2014-01-01
Full Text Available For two kinds of nonlinear constrained optimization problems, we propose two simple penalty functions, respectively, by augmenting the dimension of the primal problem with a variable that controls the weight of the penalty terms. Both of the penalty functions enjoy improved smoothness. Under mild conditions, it can be proved that our penalty functions are both exact in the sense that local minimizers of the associated penalty problem are precisely the local minimizers of the original constrained problem.
Nonlinear to Linear Elastic Code Coupling in 2-D Axisymmetric Media.
Energy Technology Data Exchange (ETDEWEB)
Preston, Leiph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-08-01
Explosions within the earth nonlinearly deform the local media, but at typical seismological observation distances, the seismic waves can be considered linear. Although nonlinear algorithms can simulate explosions in the very near field well, these codes are computationally expensive and inaccurate at propagating these signals to great distances. A linearized wave propagation code, coupled to a nonlinear code, provides an efficient mechanism to both accurately simulate the explosion itself and to propagate these signals to distant receivers. To this end we have coupled Sandia's nonlinear simulation algorithm CTH to a linearized elastic wave propagation code for 2-D axisymmetric media (axiElasti) by passing information from the nonlinear to the linear code via time-varying boundary conditions. In this report, we first develop the 2-D axisymmetric elastic wave equations in cylindrical coordinates. Next we show how we design the time-varying boundary conditions passing information from CTH to axiElasti, and finally we demonstrate the coupling code via a simple study of the elastic radius.
Italian electricity supply contracts optimization: ECO computer code
International Nuclear Information System (INIS)
Napoli, G.; Savelli, D.
1993-01-01
The ECO (Electrical Contract Optimization) code written in the Microsoft WINDOWS 3.1 language can be handled with a 286 PC and a minimum of RAM. It consists of four modules, one for the calculation of ENEL (Italian National Electricity Board) tariffs, one for contractual time-of-use tariffs optimization, a table of tariff coefficients, and a module for monthly power consumption calculations based on annual load diagrams. The optimization code was developed by ENEA (Italian Agency for New Technology, Energy and the Environment) to help Italian industrial firms comply with new and complex national electricity supply contractual regulations and tariffs. In addition to helping industrial firms determine optimum contractual arrangements, the code also assists them in optimizing their choice of equipment and production cycles
SPORTS - a simple non-linear thermalhydraulic stability code
International Nuclear Information System (INIS)
Chatoorgoon, V.
1986-01-01
A simple code, called SPORTS, has been developed for two-phase stability studies. A novel method of solution of the finite difference equations was deviced and incorporated, and many of the approximations that are common in other stability codes are avoided. SPORTS is believed to be accurate and efficient, as small and large time-steps are permitted, and hence suitable for micro-computers. (orig.)
Hierarchical optimal control of large-scale nonlinear chemical processes.
Ramezani, Mohammad Hossein; Sadati, Nasser
2009-01-01
In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear chemical stirred tank reactor (CSTR), where its solution is also compared with the ones obtained using the centralized approach. The simulation results show the efficiency and the capability of the proposed hierarchical approach, in finding the optimal solution, over the centralized method.
Optimal analytic method for the nonlinear Hasegawa-Mima equation
Baxter, Mathew; Van Gorder, Robert A.; Vajravelu, Kuppalapalle
2014-05-01
The Hasegawa-Mima equation is a nonlinear partial differential equation that describes the electric potential due to a drift wave in a plasma. In the present paper, we apply the method of homotopy analysis to a slightly more general Hasegawa-Mima equation, which accounts for hyper-viscous damping or viscous dissipation. First, we outline the method for the general initial/boundary value problem over a compact rectangular spatial domain. We use a two-stage method, where both the convergence control parameter and the auxiliary linear operator are optimally selected to minimize the residual error due to the approximation. To do the latter, we consider a family of operators parameterized by a constant which gives the decay rate of the solutions. After outlining the general method, we consider a number of concrete examples in order to demonstrate the utility of this approach. The results enable us to study properties of the initial/boundary value problem for the generalized Hasegawa-Mima equation. In several cases considered, we are able to obtain solutions with extremely small residual errors after relatively few iterations are computed (residual errors on the order of 10-15 are found in multiple cases after only three iterations). The results demonstrate that selecting a parameterized auxiliary linear operator can be extremely useful for minimizing residual errors when used concurrently with the optimal homotopy analysis method, suggesting that this approach can prove useful for a number of nonlinear partial differential equations arising in physics and nonlinear mechanics.
Spin glasses and nonlinear constraints in portfolio optimization
Energy Technology Data Exchange (ETDEWEB)
Andrecut, M., E-mail: mircea.andrecut@gmail.com
2014-01-17
We discuss the portfolio optimization problem with the obligatory deposits constraint. Recently it has been shown that as a consequence of this nonlinear constraint, the solution consists of an exponentially large number of optimal portfolios, completely different from each other, and extremely sensitive to any changes in the input parameters of the problem, making the concept of rational decision making questionable. Here we reformulate the problem using a quadratic obligatory deposits constraint, and we show that from the physics point of view, finding an optimal portfolio amounts to calculating the mean-field magnetizations of a random Ising model with the constraint of a constant magnetization norm. We show that the model reduces to an eigenproblem, with 2N solutions, where N is the number of assets defining the portfolio. Also, in order to illustrate our results, we present a detailed numerical example of a portfolio of several risky common stocks traded on the Nasdaq Market.
Spin glasses and nonlinear constraints in portfolio optimization
International Nuclear Information System (INIS)
Andrecut, M.
2014-01-01
We discuss the portfolio optimization problem with the obligatory deposits constraint. Recently it has been shown that as a consequence of this nonlinear constraint, the solution consists of an exponentially large number of optimal portfolios, completely different from each other, and extremely sensitive to any changes in the input parameters of the problem, making the concept of rational decision making questionable. Here we reformulate the problem using a quadratic obligatory deposits constraint, and we show that from the physics point of view, finding an optimal portfolio amounts to calculating the mean-field magnetizations of a random Ising model with the constraint of a constant magnetization norm. We show that the model reduces to an eigenproblem, with 2N solutions, where N is the number of assets defining the portfolio. Also, in order to illustrate our results, we present a detailed numerical example of a portfolio of several risky common stocks traded on the Nasdaq Market.
Stiffness design of geometrically nonlinear structures using topology optimization
DEFF Research Database (Denmark)
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...
Recent developments in KTF. Code optimization and improved numerics
International Nuclear Information System (INIS)
Jimenez, Javier; Avramova, Maria; Sanchez, Victor Hugo; Ivanov, Kostadin
2012-01-01
The rapid increase of computer power in the last decade facilitated the development of high fidelity simulations in nuclear engineering allowing a more realistic and accurate optimization as well as safety assessment of reactor cores and power plants compared to the legacy codes. Thermal hydraulic subchannel codes together with time dependent neutron transport codes are the options of choice for an accurate prediction of local safety parameters. Moreover, fast running codes with the best physical models are needed for high fidelity coupled thermal hydraulic / neutron kinetic solutions. Hence at KIT, different subchannel codes such as SUBCHANFLOW and KTF are being improved, validated and coupled with different neutron kinetics solutions. KTF is a subchannel code developed for best-estimate analysis of both Pressurized Water Reactor (PWR) and BWR. It is based on the Pennsylvania State University (PSU) version of COBRA-TF (Coolant Boling in Rod Arrays Two Fluids) named CTF. In this paper, the investigations devoted to the enhancement of the code numeric and informatics structure are presented and discussed. By some examples the gain on code speed-up will be demonstrated and finally an outlook of further activities concentrated on the code improvements will be given. (orig.)
Recent developments in KTF. Code optimization and improved numerics
Energy Technology Data Exchange (ETDEWEB)
Jimenez, Javier; Avramova, Maria; Sanchez, Victor Hugo; Ivanov, Kostadin [Karlsruhe Institute of Technology (KIT) (Germany). Inst. for Neutron Physics and Reactor Technology (INR)
2012-11-01
The rapid increase of computer power in the last decade facilitated the development of high fidelity simulations in nuclear engineering allowing a more realistic and accurate optimization as well as safety assessment of reactor cores and power plants compared to the legacy codes. Thermal hydraulic subchannel codes together with time dependent neutron transport codes are the options of choice for an accurate prediction of local safety parameters. Moreover, fast running codes with the best physical models are needed for high fidelity coupled thermal hydraulic / neutron kinetic solutions. Hence at KIT, different subchannel codes such as SUBCHANFLOW and KTF are being improved, validated and coupled with different neutron kinetics solutions. KTF is a subchannel code developed for best-estimate analysis of both Pressurized Water Reactor (PWR) and BWR. It is based on the Pennsylvania State University (PSU) version of COBRA-TF (Coolant Boling in Rod Arrays Two Fluids) named CTF. In this paper, the investigations devoted to the enhancement of the code numeric and informatics structure are presented and discussed. By some examples the gain on code speed-up will be demonstrated and finally an outlook of further activities concentrated on the code improvements will be given. (orig.)
Optimized iterative decoding method for TPC coded CPM
Ma, Yanmin; Lai, Penghui; Wang, Shilian; Xie, Shunqin; Zhang, Wei
2018-05-01
Turbo Product Code (TPC) coded Continuous Phase Modulation (CPM) system (TPC-CPM) has been widely used in aeronautical telemetry and satellite communication. This paper mainly investigates the improvement and optimization on the TPC-CPM system. We first add the interleaver and deinterleaver to the TPC-CPM system, and then establish an iterative system to iteratively decode. However, the improved system has a poor convergence ability. To overcome this issue, we use the Extrinsic Information Transfer (EXIT) analysis to find the optimal factors for the system. The experiments show our method is efficient to improve the convergence performance.
Software exorcism a handbook for debugging and optimizing legacy code
Blunden, Bill
2013-01-01
Software Exorcism: A Handbook for Debugging and Optimizing Legacy Code takes an unflinching, no bulls and look at behavioral problems in the software engineering industry, shedding much-needed light on the social forces that make it difficult for programmers to do their job. Do you have a co-worker who perpetually writes bad code that you are forced to clean up? This is your book. While there are plenty of books on the market that cover debugging and short-term workarounds for bad code, Reverend Bill Blunden takes a revolutionary step beyond them by bringing our atten
On A Nonlinear Generalization of Sparse Coding and Dictionary Learning.
Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba
2013-01-01
Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝ d , and the dictionary is learned from the training data using the vector space structure of ℝ d and its Euclidean L 2 -metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis.
An hp symplectic pseudospectral method for nonlinear optimal control
Peng, Haijun; Wang, Xinwei; Li, Mingwu; Chen, Biaosong
2017-01-01
An adaptive symplectic pseudospectral method based on the dual variational principle is proposed and is successfully applied to solving nonlinear optimal control problems in this paper. The proposed method satisfies the first order necessary conditions of continuous optimal control problems, also the symplectic property of the original continuous Hamiltonian system is preserved. The original optimal control problem is transferred into a set of nonlinear equations which can be solved easily by Newton-Raphson iterations, and the Jacobian matrix is found to be sparse and symmetric. The proposed method, on one hand, exhibits exponent convergence rates when the number of collocation points are increasing with the fixed number of sub-intervals; on the other hand, exhibits linear convergence rates when the number of sub-intervals is increasing with the fixed number of collocation points. Furthermore, combining with the hp method based on the residual error of dynamic constraints, the proposed method can achieve given precisions in a few iterations. Five examples highlight the high precision and high computational efficiency of the proposed method.
Global Optimization of Nonlinear Blend-Scheduling Problems
Directory of Open Access Journals (Sweden)
Pedro A. Castillo Castillo
2017-04-01
Full Text Available The scheduling of gasoline-blending operations is an important problem in the oil refining industry. This problem not only exhibits the combinatorial nature that is intrinsic to scheduling problems, but also non-convex nonlinear behavior, due to the blending of various materials with different quality properties. In this work, a global optimization algorithm is proposed to solve a previously published continuous-time mixed-integer nonlinear scheduling model for gasoline blending. The model includes blend recipe optimization, the distribution problem, and several important operational features and constraints. The algorithm employs piecewise McCormick relaxation (PMCR and normalized multiparametric disaggregation technique (NMDT to compute estimates of the global optimum. These techniques partition the domain of one of the variables in a bilinear term and generate convex relaxations for each partition. By increasing the number of partitions and reducing the domain of the variables, the algorithm is able to refine the estimates of the global solution. The algorithm is compared to two commercial global solvers and two heuristic methods by solving four examples from the literature. Results show that the proposed global optimization algorithm performs on par with commercial solvers but is not as fast as heuristic approaches.
Simulation-based optimal Bayesian experimental design for nonlinear systems
Huan, Xun
2013-01-01
The optimal selection of experimental conditions is essential to maximizing the value of data for inference and prediction, particularly in situations where experiments are time-consuming and expensive to conduct. We propose a general mathematical framework and an algorithmic approach for optimal experimental design with nonlinear simulation-based models; in particular, we focus on finding sets of experiments that provide the most information about targeted sets of parameters.Our framework employs a Bayesian statistical setting, which provides a foundation for inference from noisy, indirect, and incomplete data, and a natural mechanism for incorporating heterogeneous sources of information. An objective function is constructed from information theoretic measures, reflecting expected information gain from proposed combinations of experiments. Polynomial chaos approximations and a two-stage Monte Carlo sampling method are used to evaluate the expected information gain. Stochastic approximation algorithms are then used to make optimization feasible in computationally intensive and high-dimensional settings. These algorithms are demonstrated on model problems and on nonlinear parameter inference problems arising in detailed combustion kinetics. © 2012 Elsevier Inc.
Non-linear theory of elasticity and optimal design
Ratner, LW
2003-01-01
In order to select an optimal structure among possible similar structures, one needs to compare the elastic behavior of the structures. A new criterion that describes elastic behavior is the rate of change of deformation. Using this criterion, the safe dimensions of a structure that are required by the stress distributed in a structure can be calculated. The new non-linear theory of elasticity allows one to determine the actual individual limit of elasticity/failure of a structure using a simple non-destructive method of measurement of deformation on the model of a structure while presently it
Nonlinear Chance Constrained Problems: Optimality Conditions, Regularization and Solvers
Czech Academy of Sciences Publication Activity Database
Adam, Lukáš; Branda, Martin
2016-01-01
Roč. 170, č. 2 (2016), s. 419-436 ISSN 0022-3239 R&D Projects: GA ČR GA15-00735S Institutional support: RVO:67985556 Keywords : Chance constrained programming * Optimality conditions * Regularization * Algorithms * Free MATLAB codes Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.289, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/adam-0460909.pdf
A Fast Optimization Method for General Binary Code Learning.
Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng
2016-09-22
Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.
Optimal and efficient decoding of concatenated quantum block codes
International Nuclear Information System (INIS)
Poulin, David
2006-01-01
We consider the problem of optimally decoding a quantum error correction code--that is, to find the optimal recovery procedure given the outcomes of partial ''check'' measurements on the system. In general, this problem is NP hard. However, we demonstrate that for concatenated block codes, the optimal decoding can be efficiently computed using a message-passing algorithm. We compare the performance of the message-passing algorithm to that of the widespread blockwise hard decoding technique. Our Monte Carlo results using the five-qubit and Steane's code on a depolarizing channel demonstrate significant advantages of the message-passing algorithms in two respects: (i) Optimal decoding increases by as much as 94% the error threshold below which the error correction procedure can be used to reliably send information over a noisy channel; and (ii) for noise levels below these thresholds, the probability of error after optimal decoding is suppressed at a significantly higher rate, leading to a substantial reduction of the error correction overhead
Non-linear and signal energy optimal asymptotic filter design
Directory of Open Access Journals (Sweden)
Josef Hrusak
2003-10-01
Full Text Available The paper studies some connections between the main results of the well known Wiener-Kalman-Bucy stochastic approach to filtering problems based mainly on the linear stochastic estimation theory and emphasizing the optimality aspects of the achieved results and the classical deterministic frequency domain linear filters such as Chebyshev, Butterworth, Bessel, etc. A new non-stochastic but not necessarily deterministic (possibly non-linear alternative approach called asymptotic filtering based mainly on the concepts of signal power, signal energy and a system equivalence relation plays an important role in the presentation. Filtering error invariance and convergence aspects are emphasized in the approach. It is shown that introducing the signal power as the quantitative measure of energy dissipation makes it possible to achieve reasonable results from the optimality point of view as well. The property of structural energy dissipativeness is one of the most important and fundamental features of resulting filters. Therefore, it is natural to call them asymptotic filters. The notion of the asymptotic filter is carried in the paper as a proper tool in order to unify stochastic and non-stochastic, linear and nonlinear approaches to signal filtering.
Optimal Nonlinear Pricing, Bundling Commodities and Contingent Services
International Nuclear Information System (INIS)
Podesta, Marion; Poudou, Jean-Christophe
2008-01-01
In this paper, we propose to analyze optimal nonlinear pricing when a firm offers in a bundle a commodity and a contingent service. The paper studies a mechanism design where all private information can be captured in a single scalar variable in a monopoly context. We show that to propose the package for commodity and service is less costly for the consumer, the firm has lower consumers' rent than the situation where it sells their good and contingent service under an independent pricing strategy. In fact, the possibility to use price discrimination via the supply of package is dominated by the fact that it is costly for the consumer to sign two contracts. Bundling energy and a contingent service is a profitable strategy for a energetician monopoly practising optimal nonlinear tariff. We show that the rates of the energy and the contingent service depend to the optional character of the contingent service and depend to the degree of complementarity between commodities and services. (authors)
International Nuclear Information System (INIS)
Maldonado, G.I.; Turinsky, P.J.
1995-01-01
The determination of the family of optimum core loading patterns for pressurized water reactors (PWRs) involves the assessment of the core attributes for thousands of candidate loading patterns. For this reason, the computational capability to efficiently and accurately evaluate a reactor core's eigenvalue and power distribution versus burnup using a nodal diffusion generalized perturbation theory (GPT) model is developed. The GPT model is derived from the forward nonlinear iterative nodal expansion method (NEM) to explicitly enable the preservation of the finite difference matrix structure. This key feature considerably simplifies the mathematical formulation of NEM GPT and results in reduced memory storage and CPU time requirements versus the traditional response-matrix approach to NEM. In addition, a treatment within NEM GPT can account for localized nonlinear feedbacks, such as that due to fission product buildup and thermal-hydraulic effects. When compared with a standard nonlinear iterative NEM forward flux solve with feedbacks, the NEM GPT model can execute between 8 and 12 times faster. These developments are implemented within the PWR in-core nuclear fuel management optimization code FORMOSA-P, combining the robustness of its adaptive simulated annealing stochastic optimization algorithm with an NEM GPT neutronics model that efficiently and accurately evaluates core attributes associated with objective functions and constraints of candidate loading patterns
Optimized Method for Generating and Acquiring GPS Gold Codes
Directory of Open Access Journals (Sweden)
Khaled Rouabah
2015-01-01
Full Text Available We propose a simpler and faster Gold codes generator, which can be efficiently initialized to any desired code, with a minimum delay. Its principle consists of generating only one sequence (code number 1 from which we can produce all the other different signal codes. This is realized by simply shifting this sequence by different delays that are judiciously determined by using the bicorrelation function characteristics. This is in contrast to the classical Linear Feedback Shift Register (LFSR based Gold codes generator that requires, in addition to the shift process, a significant number of logic XOR gates and a phase selector to change the code. The presence of all these logic XOR gates in classical LFSR based Gold codes generator provokes the consumption of an additional time in the generation and acquisition processes. In addition to its simplicity and its rapidity, the proposed architecture, due to the total absence of XOR gates, has fewer resources than the conventional Gold generator and can thus be produced at lower cost. The Digital Signal Processing (DSP implementations have shown that the proposed architecture presents a solution for acquiring Global Positioning System (GPS satellites signals optimally and in a parallel way.
Photon attenuation correction technique in SPECT based on nonlinear optimization
International Nuclear Information System (INIS)
Suzuki, Shigehito; Wakabayashi, Misato; Okuyama, Keiichi; Kuwamura, Susumu
1998-01-01
Photon attenuation correction in SPECT was made using a nonlinear optimization theory, in which an optimum image is searched so that the sum of square errors between observed and reprojected projection data is minimized. This correction technique consists of optimization and step-width algorithms, which determine at each iteration a pixel-by-pixel directional value of search and its step-width, respectively. We used the conjugate gradient and quasi-Newton methods as the optimization algorithm, and Curry rule and the quadratic function method as the step-width algorithm. Statistical fluctuations in the corrected image due to statistical noise in the emission projection data grew as the iteration increased, depending on the combination of optimization and step-width algorithms. To suppress them, smoothing for directional values was introduced. Computer experiments and clinical applications showed a pronounced reduction in statistical fluctuations of the corrected image for all combinations. Combinations using the conjugate gradient method were superior in noise characteristic and computation time. The use of that method with the quadratic function method was optimum if noise property was regarded as important. (author)
Directory of Open Access Journals (Sweden)
Pinter Stephen Z
2007-01-01
Full Text Available Transmitter nonlinearity has been a major issue in many scenarios: cellular wireless systems have high power RF amplifier (HPA nonlinearity at the base station; satellite downlinks have nonlinear TWT amplifiers in the satellite transponder and multipath conditions in the ground station; and radio-over-fiber (ROF systems consist of a nonlinear optical link followed by a wireless channel. In many cases, the nonlinearity is simply ignored if there is no out-of-band emission. This results in poor BER performance. In this paper we propose a new technique to estimate the linear part of the wireless downlink in the presence of a nonlinearity using Walsh codes; Walsh codes are commonly used in CDMA downlinks. Furthermore, we show that equalizer performance is significantly improved by taking into account the presence of the nonlinearity during channel estimation. This is shown by using a regular decision feedback equalizer (DFE with both wireless and RF amplifier noise. We perform estimation in a multiuser CDMA communication system where all users transmit their signal simultaneously. Correlation analysis is applied to identify the channel impulse response (CIR and the derivation of key correlation relationships is shown. A difficulty with using Walsh codes in terms of their correlations (compared to PN sequences is then presented, as well as a discussion on how to overcome it. Numerical evaluations show a good estimation of the linear system with 54 users in the downlink and a signal-to-noise ratio (SNR of 25 dB. Bit error rate (BER simulations of the proposed identification and equalization algorithms show a BER of achieved at an SNR of dB.
Optimization of the particle pusher in a diode simulation code
International Nuclear Information System (INIS)
Theimer, M.M.; Quintenz, J.P.
1979-09-01
The particle pusher in Sandia's particle-in-cell diode simulation code has been rewritten to reduce the required run time of a typical simulation. The resulting new version of the code has been found to run up to three times as fast as the original with comparable accuracy. The cost of this optimization was an increase in storage requirements of about 15%. The new version has also been written to run efficiently on a CRAY-1 computing system. Steps taken to affect this reduced run time are described. Various test cases are detailed
Liu, Tao; Djordjevic, Ivan B
2014-12-29
In this paper, we first describe an optimal signal constellation design algorithm suitable for the coherent optical channels dominated by the linear phase noise. Then, we modify this algorithm to be suitable for the nonlinear phase noise dominated channels. In optimization procedure, the proposed algorithm uses the cumulative log-likelihood function instead of the Euclidian distance. Further, an LDPC coded modulation scheme is proposed to be used in combination with signal constellations obtained by proposed algorithm. Monte Carlo simulations indicate that the LDPC-coded modulation schemes employing the new constellation sets, obtained by our new signal constellation design algorithm, outperform corresponding QAM constellations significantly in terms of transmission distance and have better nonlinearity tolerance.
Robust and fast nonlinear optimization of diffusion MRI microstructure models.
Harms, R L; Fritz, F J; Tobisch, A; Goebel, R; Roebroeck, A
2017-07-15
Advances in biophysical multi-compartment modeling for diffusion MRI (dMRI) have gained popularity because of greater specificity than DTI in relating the dMRI signal to underlying cellular microstructure. A large range of these diffusion microstructure models have been developed and each of the popular models comes with its own, often different, optimization algorithm, noise model and initialization strategy to estimate its parameter maps. Since data fit, accuracy and precision is hard to verify, this creates additional challenges to comparability and generalization of results from diffusion microstructure models. In addition, non-linear optimization is computationally expensive leading to very long run times, which can be prohibitive in large group or population studies. In this technical note we investigate the performance of several optimization algorithms and initialization strategies over a few of the most popular diffusion microstructure models, including NODDI and CHARMED. We evaluate whether a single well performing optimization approach exists that could be applied to many models and would equate both run time and fit aspects. All models, algorithms and strategies were implemented on the Graphics Processing Unit (GPU) to remove run time constraints, with which we achieve whole brain dataset fits in seconds to minutes. We then evaluated fit, accuracy, precision and run time for different models of differing complexity against three common optimization algorithms and three parameter initialization strategies. Variability of the achieved quality of fit in actual data was evaluated on ten subjects of each of two population studies with a different acquisition protocol. We find that optimization algorithms and multi-step optimization approaches have a considerable influence on performance and stability over subjects and over acquisition protocols. The gradient-free Powell conjugate-direction algorithm was found to outperform other common algorithms in terms of
Optimal perturbations for nonlinear systems using graph-based optimal transport
Grover, Piyush; Elamvazhuthi, Karthik
2018-06-01
We formulate and solve a class of finite-time transport and mixing problems in the set-oriented framework. The aim is to obtain optimal discrete-time perturbations in nonlinear dynamical systems to transport a specified initial measure on the phase space to a final measure in finite time. The measure is propagated under system dynamics in between the perturbations via the associated transfer operator. Each perturbation is described by a deterministic map in the measure space that implements a version of Monge-Kantorovich optimal transport with quadratic cost. Hence, the optimal solution minimizes a sum of quadratic costs on phase space transport due to the perturbations applied at specified times. The action of the transport map is approximated by a continuous pseudo-time flow on a graph, resulting in a tractable convex optimization problem. This problem is solved via state-of-the-art solvers to global optimality. We apply this algorithm to a problem of transport between measures supported on two disjoint almost-invariant sets in a chaotic fluid system, and to a finite-time optimal mixing problem by choosing the final measure to be uniform. In both cases, the optimal perturbations are found to exploit the phase space structures, such as lobe dynamics, leading to efficient global transport. As the time-horizon of the problem is increased, the optimal perturbations become increasingly localized. Hence, by combining the transfer operator approach with ideas from the theory of optimal mass transportation, we obtain a discrete-time graph-based algorithm for optimal transport and mixing in nonlinear systems.
Numerical computation of molecular integrals via optimized (vectorized) FORTRAN code
International Nuclear Information System (INIS)
Scott, T.C.; Grant, I.P.; Saunders, V.R.
1997-01-01
The calculation of molecular properties based on quantum mechanics is an area of fundamental research whose horizons have always been determined by the power of state-of-the-art computers. A computational bottleneck is the numerical calculation of the required molecular integrals to sufficient precision. Herein, we present a method for the rapid numerical evaluation of molecular integrals using optimized FORTRAN code generated by Maple. The method is based on the exploitation of common intermediates and the optimization can be adjusted to both serial and vectorized computations. (orig.)
Nonlinear Burn Control and Operating Point Optimization in ITER
Boyer, Mark; Schuster, Eugenio
2013-10-01
Control of the fusion power through regulation of the plasma density and temperature will be essential for achieving and maintaining desired operating points in fusion reactors and burning plasma experiments like ITER. In this work, a volume averaged model for the evolution of the density of energy, deuterium and tritium fuel ions, alpha-particles, and impurity ions is used to synthesize a multi-input multi-output nonlinear feedback controller for stabilizing and modulating the burn condition. Adaptive control techniques are used to account for uncertainty in model parameters, including particle confinement times and recycling rates. The control approach makes use of the different possible methods for altering the fusion power, including adjusting the temperature through auxiliary heating, modulating the density and isotopic mix through fueling, and altering the impurity density through impurity injection. Furthermore, a model-based optimization scheme is proposed to drive the system as close as possible to desired fusion power and temperature references. Constraints are considered in the optimization scheme to ensure that, for example, density and beta limits are avoided, and that optimal operation is achieved even when actuators reach saturation. Supported by the NSF CAREER award program (ECCS-0645086).
Cooperative optimization and their application in LDPC codes
Chen, Ke; Rong, Jian; Zhong, Xiaochun
2008-10-01
Cooperative optimization is a new way for finding global optima of complicated functions of many variables. The proposed algorithm is a class of message passing algorithms and has solid theory foundations. It can achieve good coding gains over the sum-product algorithm for LDPC codes. For (6561, 4096) LDPC codes, the proposed algorithm can achieve 2.0 dB gains over the sum-product algorithm at BER of 4×10-7. The decoding complexity of the proposed algorithm is lower than the sum-product algorithm can do; furthermore, the former can achieve much lower error floor than the latter can do after the Eb / No is higher than 1.8 dB.
Fundamentals of an Optimal Multirate Subband Coding of Cyclostationary Signals
Directory of Open Access Journals (Sweden)
D. Kula
2000-06-01
Full Text Available A consistent theory of optimal subband coding of zero mean wide-sense cyclostationary signals, with N-periodic statistics, is presented in this article. An M-channel orthonormal uniform filter bank, employing N-periodic analysis and synthesis filters, is used while an average variance condition is applied to evaluate the output distortion. In three lemmas and final theorem, the necessity of decorrelation of blocked subband signals and requirement of specific ordering of power spectral densities are proven.
Iterative optimization of performance libraries by hierarchical division of codes
International Nuclear Information System (INIS)
Donadio, S.
2007-09-01
The increasing complexity of hardware features incorporated in modern processors makes high performance code generation very challenging. Library generators such as ATLAS, FFTW and SPIRAL overcome this issue by empirically searching in the space of possible program versions for the one that performs the best. This thesis explores fully automatic solution to adapt a compute-intensive application to the target architecture. By mimicking complex sequences of transformations useful to optimize real codes, we show that generative programming is a practical tool to implement a new hierarchical compilation approach for the generation of high performance code relying on the use of state-of-the-art compilers. As opposed to ATLAS, this approach is not application-dependant but can be applied to fairly generic loop structures. Our approach relies on the decomposition of the original loop nest into simpler kernels. These kernels are much simpler to optimize and furthermore, using such codes makes the performance trade off problem much simpler to express and to solve. Finally, we propose a new approach for the generation of performance libraries based on this decomposition method. We show that our method generates high-performance libraries, in particular for BLAS. (author)
ARSTEC, Nonlinear Optimization Program Using Random Search Method
International Nuclear Information System (INIS)
Rasmuson, D. M.; Marshall, N. H.
1979-01-01
1 - Description of problem or function: The ARSTEC program was written to solve nonlinear, mixed integer, optimization problems. An example of such a problem in the nuclear industry is the allocation of redundant parts in the design of a nuclear power plant to minimize plant unavailability. 2 - Method of solution: The technique used in ARSTEC is the adaptive random search method. The search is started from an arbitrary point in the search region and every time a point that improves the objective function is found, the search region is centered at that new point. 3 - Restrictions on the complexity of the problem: Presently, the maximum number of independent variables allowed is 10. This can be changed by increasing the dimension of the arrays
Robust C subroutines for non-linear optimization
DEFF Research Database (Denmark)
Brock, Pernille; Madsen, Kaj; Nielsen, Hans Bruun
2004-01-01
This report presents a package of robust and easy-to-use C subroutines for solving unconstrained and constrained non-linear optimization problems. The intention is that the routines should use the currently best algorithms available. All routines have standardized calls, and the user does not have...... by changing 1 to 0. The present report is a new and updated version of a previous report NI-91-03 with the same title, [16]. Both the previous and the present report describe a collection of subroutines, which have been translated from Fortran to C. The reason for writing the present report is that some...... of the C subroutines have been replaced by more effective and robust versions translated from the original Fortran subroutines to C by the Bandler Group, see [1]. Also the test examples have been modi ed to some extent. For a description of the original Fortran subroutines see the report [17]. The software...
Robust Homography Estimation Based on Nonlinear Least Squares Optimization
Directory of Open Access Journals (Sweden)
Wei Mou
2014-01-01
Full Text Available The homography between image pairs is normally estimated by minimizing a suitable cost function given 2D keypoint correspondences. The correspondences are typically established using descriptor distance of keypoints. However, the correspondences are often incorrect due to ambiguous descriptors which can introduce errors into following homography computing step. There have been numerous attempts to filter out these erroneous correspondences, but it is unlikely to always achieve perfect matching. To deal with this problem, we propose a nonlinear least squares optimization approach to compute homography such that false matches have no or little effect on computed homography. Unlike normal homography computation algorithms, our method formulates not only the keypoints’ geometric relationship but also their descriptor similarity into cost function. Moreover, the cost function is parametrized in such a way that incorrect correspondences can be simultaneously identified while the homography is computed. Experiments show that the proposed approach can perform well even with the presence of a large number of outliers.
Simulation of nonlinear propagation of biomedical ultrasound using PZFlex and the KZK Texas code
Qiao, Shan; Jackson, Edward; Coussios, Constantin-C.; Cleveland, Robin
2015-10-01
In biomedical ultrasound nonlinear acoustics can be important in both diagnostic and therapeutic applications and robust simulations tools are needed in the design process but also for day-to-day use such as treatment planning. For most biomedical application the ultrasound sources generate focused sound beams of finite amplitude. The KZK equation is a common model as it accounts for nonlinearity, absorption and paraxial diffraction and there are a number of solvers available, primarily developed by research groups. We compare the predictions of the KZK Texas code (a finite-difference time-domain algorithm) to an FEM-based commercial software, PZFlex. PZFlex solves the continuity equation and momentum conservation equation with a correction for nonlinearity in the equation of state incorporated using an incrementally linear, 2nd order accurate, explicit algorithm in time domain. Nonlinear ultrasound beams from two transducers driven at 1 MHz and 3.3 MHz respectively were simulated by both the KZK Texas code and PZFlex, and the pressure field was also measured by a fibre-optic hydrophone to validate the models. Further simulations were carried out a wide range of frequencies. The comparisons showed good agreement for the fundamental frequency for PZFlex, the KZK Texas code and the experiments. For the harmonic components, the KZK Texas code was in good agreement with measurements but PZFlex underestimated the amplitude: 32% for the 2nd harmonic and 66% for the 3rd harmonic. The underestimation of harmonics by PZFlex was more significant when the fundamental frequency increased. Furthermore non-physical oscillations in the axial profile of harmonics occurred in the PZFlex results when the amplitudes were relatively low. These results suggest that careful benchmarking of nonlinear simulations is important.
Simulation of nonlinear propagation of biomedical ultrasound using PZFlex and the KZK Texas code
Energy Technology Data Exchange (ETDEWEB)
Qiao, Shan, E-mail: shan.qiao@eng.ox.ac.uk; Jackson, Edward; Coussios, Constantin-C; Cleveland, Robin [Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford (United Kingdom)
2015-10-28
In biomedical ultrasound nonlinear acoustics can be important in both diagnostic and therapeutic applications and robust simulations tools are needed in the design process but also for day-to-day use such as treatment planning. For most biomedical application the ultrasound sources generate focused sound beams of finite amplitude. The KZK equation is a common model as it accounts for nonlinearity, absorption and paraxial diffraction and there are a number of solvers available, primarily developed by research groups. We compare the predictions of the KZK Texas code (a finite-difference time-domain algorithm) to an FEM-based commercial software, PZFlex. PZFlex solves the continuity equation and momentum conservation equation with a correction for nonlinearity in the equation of state incorporated using an incrementally linear, 2nd order accurate, explicit algorithm in time domain. Nonlinear ultrasound beams from two transducers driven at 1 MHz and 3.3 MHz respectively were simulated by both the KZK Texas code and PZFlex, and the pressure field was also measured by a fibre-optic hydrophone to validate the models. Further simulations were carried out a wide range of frequencies. The comparisons showed good agreement for the fundamental frequency for PZFlex, the KZK Texas code and the experiments. For the harmonic components, the KZK Texas code was in good agreement with measurements but PZFlex underestimated the amplitude: 32% for the 2nd harmonic and 66% for the 3rd harmonic. The underestimation of harmonics by PZFlex was more significant when the fundamental frequency increased. Furthermore non-physical oscillations in the axial profile of harmonics occurred in the PZFlex results when the amplitudes were relatively low. These results suggest that careful benchmarking of nonlinear simulations is important.
Simulation of nonlinear propagation of biomedical ultrasound using PZFlex and the KZK Texas code
International Nuclear Information System (INIS)
Qiao, Shan; Jackson, Edward; Coussios, Constantin-C; Cleveland, Robin
2015-01-01
In biomedical ultrasound nonlinear acoustics can be important in both diagnostic and therapeutic applications and robust simulations tools are needed in the design process but also for day-to-day use such as treatment planning. For most biomedical application the ultrasound sources generate focused sound beams of finite amplitude. The KZK equation is a common model as it accounts for nonlinearity, absorption and paraxial diffraction and there are a number of solvers available, primarily developed by research groups. We compare the predictions of the KZK Texas code (a finite-difference time-domain algorithm) to an FEM-based commercial software, PZFlex. PZFlex solves the continuity equation and momentum conservation equation with a correction for nonlinearity in the equation of state incorporated using an incrementally linear, 2nd order accurate, explicit algorithm in time domain. Nonlinear ultrasound beams from two transducers driven at 1 MHz and 3.3 MHz respectively were simulated by both the KZK Texas code and PZFlex, and the pressure field was also measured by a fibre-optic hydrophone to validate the models. Further simulations were carried out a wide range of frequencies. The comparisons showed good agreement for the fundamental frequency for PZFlex, the KZK Texas code and the experiments. For the harmonic components, the KZK Texas code was in good agreement with measurements but PZFlex underestimated the amplitude: 32% for the 2nd harmonic and 66% for the 3rd harmonic. The underestimation of harmonics by PZFlex was more significant when the fundamental frequency increased. Furthermore non-physical oscillations in the axial profile of harmonics occurred in the PZFlex results when the amplitudes were relatively low. These results suggest that careful benchmarking of nonlinear simulations is important
Energy Technology Data Exchange (ETDEWEB)
Liu, Z. X., E-mail: zxliu316@ipp.ac.cn; Xia, T. Y.; Liu, S. C.; Ding, S. Y. [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Xu, X. Q.; Joseph, I.; Meyer, W. H. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Gao, X.; Xu, G. S.; Shao, L. M.; Li, G. Q.; Li, J. G. [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China)
2014-09-15
Experimental measurements of edge localized modes (ELMs) observed on the EAST experiment are compared to linear and nonlinear theoretical simulations of peeling-ballooning modes using the BOUT++ code. Simulations predict that the dominant toroidal mode number of the ELM instability becomes larger for lower current, which is consistent with the mode structure captured with visible light using an optical CCD camera. The poloidal mode number of the simulated pressure perturbation shows good agreement with the filamentary structure observed by the camera. The nonlinear simulation is also consistent with the experimentally measured energy loss during an ELM crash and with the radial speed of ELM effluxes measured using a gas puffing imaging diagnostic.
Imtiaz, Waqas A.; Ilyas, M.; Khan, Yousaf
2016-11-01
This paper propose a new code to optimize the performance of spectral amplitude coding-optical code division multiple access (SAC-OCDMA) system. The unique two-matrix structure of the proposed enhanced multi diagonal (EMD) code and effective correlation properties, between intended and interfering subscribers, significantly elevates the performance of SAC-OCDMA system by negating multiple access interference (MAI) and associated phase induce intensity noise (PIIN). Performance of SAC-OCDMA system based on the proposed code is thoroughly analyzed for two detection techniques through analytic and simulation analysis by referring to bit error rate (BER), signal to noise ratio (SNR) and eye patterns at the receiving end. It is shown that EMD code while using SDD technique provides high transmission capacity, reduces the receiver complexity, and provides better performance as compared to complementary subtraction detection (CSD) technique. Furthermore, analysis shows that, for a minimum acceptable BER of 10-9 , the proposed system supports 64 subscribers at data rates of up to 2 Gbps for both up-down link transmission.
On Optimal Policies for Network-Coded Cooperation
DEFF Research Database (Denmark)
Khamfroush, Hana; Roetter, Daniel Enrique Lucani; Pahlevani, Peyman
2015-01-01
Network-coded cooperative communication (NC-CC) has been proposed and evaluated as a powerful technology that can provide a better quality of service in the next-generation wireless systems, e.g., D2D communications. Previous contributions have focused on performance evaluation of NC-CC scenarios...... rather than searching for optimal policies that can minimize the total cost of reliable packet transmission. We break from this trend by initially analyzing the optimal design of NC-CC for a wireless network with one source, two receivers, and half-duplex erasure channels. The problem is modeled...... as a special case of Markov decision process (MDP), which is called stochastic shortest path (SSP), and is solved for any field size, arbitrary number of packets, and arbitrary erasure probabilities of the channels. The proposed MDP solution results in an optimal transmission policy per time slot, and we use...
Random mask optimization for fast neutron coded aperture imaging
Energy Technology Data Exchange (ETDEWEB)
McMillan, Kyle [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Univ. of California, Los Angeles, CA (United States); Marleau, Peter [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Brubaker, Erik [Sandia National Lab. (SNL-CA), Livermore, CA (United States)
2015-05-01
In coded aperture imaging, one of the most important factors determining the quality of reconstructed images is the choice of mask/aperture pattern. In many applications, uniformly redundant arrays (URAs) are widely accepted as the optimal mask pattern. Under ideal conditions, thin and highly opaque masks, URA patterns are mathematically constructed to provide artifact-free reconstruction however, the number of URAs for a chosen number of mask elements is limited and when highly penetrating particles such as fast neutrons and high-energy gamma-rays are being imaged, the optimum is seldom achieved. In this case more robust mask patterns that provide better reconstructed image quality may exist. Through the use of heuristic optimization methods and maximum likelihood expectation maximization (MLEM) image reconstruction, we show that for both point and extended neutron sources a random mask pattern can be optimized to provide better image quality than that of a URA.
NOTICONA--a nonlinear time-domain computer code of two-phase natural circulation instability
International Nuclear Information System (INIS)
Su Guanghui; Guo Yujun; Zhang Jinling; Qiu Shuizheng; Jia Dounan; Yu Zhenwan
1997-10-01
A microcomputer code, NOTICONA, is developed, which is used for non-linear analysing the two-phase natural circulation systems. The mathematical model of the code includes point source neutron-kinetic model, the feedback of reactivity model, single-phase and two-phase flow model, heat transfer model in different conditions, associated model, etc. NOTICONA is compared with experiments, and its correctness and accuracy are proved. Using NOTICONA, the density wave oscillation (type I) of the 5 MW Test Heating Reactor are calculated, and the marginal stability boundary is obtained
Development of a 3D non-linear implicit MHD code
International Nuclear Information System (INIS)
Nicolas, T.; Ichiguchi, K.
2016-06-01
This paper details the on-going development of a 3D non-linear implicit MHD code, which aims at making possible large scale simulations of the non-linear phase of the interchange mode. The goal of the paper is to explain the rationale behind the choices made along the development, and the technical difficulties encountered. At the present stage, the development of the code has not been completed yet. Most of the discussion is concerned with the first approach, which utilizes cartesian coordinates in the poloidal plane. This approach shows serious difficulties in writing the preconditioner, closely related to the choice of coordinates. A second approach, based on curvilinear coordinates, also faced significant difficulties, which are detailed. The third and last approach explored involves unstructured tetrahedral grids, and indicates the possibility to solve the problem. The issue to domain meshing is addressed. (author)
Nonlinear FE Analysis for PCCV 1/4 Model using NUCAS Code
International Nuclear Information System (INIS)
Lee, Hong-Pyo; Song, Young-Chul; Choun, Young Sun
2007-01-01
During the several years, ultimate pressure analysis as well as failure mode evaluations of containment building in nuclear power plant have been carried out in KAERI. In this point of view, the program NUCAS (NUclear Containment Analysis System) code, which is FE (Finite Element) program with the sole purpose of evaluating ultimate pressure capacity of PSC containment building, was developed to predict nonlinear behavior. The main objective of this paper is to verify the performance of the program's solid element
Design and optimization of carbon-nanotube-material/dielectric hybrid nonlinear optical waveguides
International Nuclear Information System (INIS)
Zhao, Xin; Zheng, Zheng; Lu, Zhiting; Zhu, Jinsong; Zhou, Tao
2011-01-01
The nonlinear optical characteristics of highly nonlinear waveguides utilizing carbon nanotube composite materials are investigated theoretically. The extremely high nonlinearity and relatively high loss of the carbon nanotube materials are shown to greatly affect the performance of such waveguides for nonlinear optical applications, in contrast to waveguides using conventional nonlinear materials. Different configurations based on applying the carbon nanotube materials to the popular ridge and buried waveguides are thoroughly studied, and the optimal geometries are derived through simulations. It is shown that, though the nonlinear coefficient is often huge for these waveguides, the loss characteristics can significantly limit the maximum achievable accumulated nonlinearity, e.g. the maximum nonlinear phase shift. Our results suggest that SOI-based high-index-contrast, carbon nanotube cladding waveguides, rather than the currently demonstrated low-contrast waveguides, could hold the promise of achieving significantly higher accumulated nonlinearity
BWROPT: A multi-cycle BWR fuel cycle optimization code
Energy Technology Data Exchange (ETDEWEB)
Ottinger, Keith E.; Maldonado, G. Ivan, E-mail: Ivan.Maldonado@utk.edu
2015-09-15
Highlights: • A multi-cycle BWR fuel cycle optimization algorithm is presented. • New fuel inventory and core loading pattern determination. • The parallel simulated annealing algorithm was used for the optimization. • Variable sampling probabilities were compared to constant sampling probabilities. - Abstract: A new computer code for performing BWR in-core and out-of-core fuel cycle optimization for multiple cycles simultaneously has been developed. Parallel simulated annealing (PSA) is used to optimize the new fuel inventory and placement of new and reload fuel for each cycle considered. Several algorithm improvements were implemented and evaluated. The most significant of these are variable sampling probabilities and sampling new fuel types from an ordered array. A heuristic control rod pattern (CRP) search algorithm was also implemented, which is useful for single CRP determinations, however, this feature requires significant computational resources and is currently not practical for use in a full multi-cycle optimization. The PSA algorithm was demonstrated to be capable of significant objective function reduction and finding candidate loading patterns without constraint violations. The use of variable sampling probabilities was shown to reduce runtime while producing better results compared to using constant sampling probabilities. Sampling new fuel types from an ordered array was shown to have a mixed effect compared to random new fuel type sampling, whereby using both random and ordered sampling produced better results but required longer runtimes.
Optimized nonlinear inversion of surface-wave dispersion data
International Nuclear Information System (INIS)
Raykova, Reneta B.
2014-01-01
A new code for inversion of surface wave dispersion data is developed to obtain Earth’s crustal and upper mantle velocity structure. The author developed Optimized Non–Linear Inversion ( ONLI ) software, based on Monte-Carlo search. The values of S–wave velocity VS and thickness h for a number of horizontal homogeneous layers are parameterized. Velocity of P–wave VP and density ρ of relevant layers are calculated by empirical or theoretical relations. ONLI explores parameters space in two modes, selective and full search, and the main innovation of software is evaluation of tested models. Theoretical dispersion curves are calculated if tested model satisfied specific conditions only, reducing considerably the computation time. A number of tests explored impact of parameterization and proved the ability of ONLI approach to deal successfully with non–uniqueness of inversion problem. Key words: Earth’s structure, surface–wave dispersion, non–linear inversion, software
International Nuclear Information System (INIS)
Khan, Mohd Shariq; Lee, Moonyong
2013-01-01
The particle swarm paradigm is employed to optimize single mixed refrigerant natural gas liquefaction process. Liquefaction design involves multivariable problem solving and non-optimal execution of these variables can waste energy and contribute to process irreversibilities. Design optimization requires these variables to be optimized simultaneously; minimizing the compression energy requirement is selected as the optimization objective. Liquefaction is modeled using Honeywell UniSim Design ™ and the resulting rigorous model is connected with the particle swarm paradigm coded in MATLAB. Design constraints are folded into the objective function using the penalty function method. Optimization successfully improved efficiency by reducing the compression energy requirement by ca. 10% compared with the base case. -- Highlights: ► The particle swarm paradigm (PSP) is employed for design optimization of SMR NG liquefaction process. ► Rigorous SMR process model based on UniSim is connected with PSP coded in MATLAB. ► Stochastic features of PSP give more confidence in the optimality of complex nonlinear problems. ► Optimization with PSP notably improves energy efficiency of the SMR process.
Compiler design handbook optimizations and machine code generation
Srikant, YN
2003-01-01
The widespread use of object-oriented languages and Internet security concerns are just the beginning. Add embedded systems, multiple memory banks, highly pipelined units operating in parallel, and a host of other advances and it becomes clear that current and future computer architectures pose immense challenges to compiler designers-challenges that already exceed the capabilities of traditional compilation techniques. The Compiler Design Handbook: Optimizations and Machine Code Generation is designed to help you meet those challenges. Written by top researchers and designers from around the
Gunnels, John; Lee, Jon; Margulies, Susan
2010-01-01
We provide a first demonstration of the idea that matrix-based algorithms for nonlinear combinatorial optimization problems can be efficiently implemented. Such algorithms were mainly conceived by theoretical computer scientists for proving efficiency. We are able to demonstrate the practicality of our approach by developing an implementation on a massively parallel architecture, and exploiting scalable and efficient parallel implementations of algorithms for ultra high-precision linear algebra. Additionally, we have delineated and implemented the necessary algorithmic and coding changes required in order to address problems several orders of magnitude larger, dealing with the limits of scalability from memory footprint, computational efficiency, reliability, and interconnect perspectives. © Springer and Mathematical Programming Society 2010.
Gunnels, John
2010-06-01
We provide a first demonstration of the idea that matrix-based algorithms for nonlinear combinatorial optimization problems can be efficiently implemented. Such algorithms were mainly conceived by theoretical computer scientists for proving efficiency. We are able to demonstrate the practicality of our approach by developing an implementation on a massively parallel architecture, and exploiting scalable and efficient parallel implementations of algorithms for ultra high-precision linear algebra. Additionally, we have delineated and implemented the necessary algorithmic and coding changes required in order to address problems several orders of magnitude larger, dealing with the limits of scalability from memory footprint, computational efficiency, reliability, and interconnect perspectives. © Springer and Mathematical Programming Society 2010.
A Study on the Analysis and Optimal Control of Nonlinear Systems via Walsh Function
Energy Technology Data Exchange (ETDEWEB)
Kim, Jin Tae; Kim, Tai Hoon; Ahn, Doo Soo [Sungkyunkwan University (Korea); Lee, Myung Kyu [Kyungsung University (Korea)
2000-07-01
This paper presents the new adaptive optimal scheme for the nonlinear systems, which is based on the Picard's iterative approximation and fast Walsh transform. It is well known that the Walsh function approach method is very difficult to apply for the analysis and optimal control of nonlinear systems. However, these problems can be easily solved by the improvement of the previous adaptive optimal scheme. The proposes method is easily applicable to the analysis and optimal control of nonlinear systems. (author). 15 refs., 6 figs., 1 tab.
A nonlinear optimal control approach for chaotic finance dynamics
Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.
2017-11-01
A new nonlinear optimal control approach is proposed for stabilization of the dynamics of a chaotic finance model. The dynamic model of the financial system, which expresses interaction between the interest rate, the investment demand, the price exponent and the profit margin, undergoes approximate linearization round local operating points. These local equilibria are defined at each iteration of the control algorithm and consist of the present value of the systems state vector and the last value of the control inputs vector that was exerted on it. The approximate linearization makes use of Taylor series expansion and of the computation of the associated Jacobian matrices. The truncation of higher order terms in the Taylor series expansion is considered to be a modelling error that is compensated by the robustness of the control loop. As the control algorithm runs, the temporary equilibrium is shifted towards the reference trajectory and finally converges to it. The control method needs to compute an H-infinity feedback control law at each iteration, and requires the repetitive solution of an algebraic Riccati equation. Through Lyapunov stability analysis it is shown that an H-infinity tracking performance criterion holds for the control loop. This implies elevated robustness against model approximations and external perturbations. Moreover, under moderate conditions the global asymptotic stability of the control loop is proven.
FEAST: a two-dimensional non-linear finite element code for calculating stresses
International Nuclear Information System (INIS)
Tayal, M.
1986-06-01
The computer code FEAST calculates stresses, strains, and displacements. The code is two-dimensional. That is, either plane or axisymmetric calculations can be done. The code models elastic, plastic, creep, and thermal strains and stresses. Cracking can also be simulated. The finite element method is used to solve equations describing the following fundamental laws of mechanics: equilibrium; compatibility; constitutive relations; yield criterion; and flow rule. FEAST combines several unique features that permit large time-steps in even severely non-linear situations. The features include a special formulation for permitting many finite elements to simultaneously cross the boundary from elastic to plastic behaviour; accomodation of large drops in yield-strength due to changes in local temperature and a three-step predictor-corrector method for plastic analyses. These features reduce computing costs. Comparisons against twenty analytical solutions and against experimental measurements show that predictions of FEAST are generally accurate to ± 5%
Optimization and Validation of the Developed Uranium Isotopic Analysis Code
Energy Technology Data Exchange (ETDEWEB)
Kim, J. H.; Kang, M. Y.; Kim, Jinhyeong; Choi, H. D. [Seoul National Univ., Seoul (Korea, Republic of)
2014-10-15
γ-ray spectroscopy is a representative non-destructive assay for nuclear material, and less time-consuming and less expensive than the destructive analysis method. The destructive technique is more precise than NDA technique, however, there is some correction algorithm which can improve the performance of γ-spectroscopy. For this reason, an analysis code for uranium isotopic analysis is developed by Applied Nuclear Physics Group in Seoul National University. Overlapped γ- and x-ray peaks in the 89-101 keV X{sub α}-region are fitted with Gaussian and Lorentzian distribution peak functions, tail and background functions. In this study, optimizations for the full-energy peak efficiency calibration and fitting parameters of peak tail and background are performed, and validated with 24 hour acquisition of CRM uranium samples. The optimization of peak tail and background parameters are performed with the validation by using CRM uranium samples. The analysis performance is improved in HEU samples, but more optimization of fitting parameters is required in LEU sample analysis. In the future, the optimization research about the fitting parameters with various type of uranium samples will be performed. {sup 234}U isotopic analysis algorithms and correction algorithms (coincidence effect, self-attenuation effect) will be developed.
Turbine Airfoil Optimization Using Quasi-3D Analysis Codes
Directory of Open Access Journals (Sweden)
Sanjay Goel
2009-01-01
Full Text Available A new approach to optimize the geometry of a turbine airfoil by simultaneously designing multiple 2D sections of the airfoil is presented in this paper. The complexity of 3D geometry modeling is circumvented by generating multiple 2D airfoil sections and constraining their geometry in the radial direction using first- and second-order polynomials that ensure smoothness in the radial direction. The flow fields of candidate geometries obtained during optimization are evaluated using a quasi-3D, inviscid, CFD analysis code. An inviscid flow solver is used to reduce the execution time of the analysis. Multiple evaluation criteria based on the Mach number profile obtained from the analysis of each airfoil cross-section are used for computing a quality metric. A key contribution of the paper is the development of metrics that emulate the perception of the human designer in visually evaluating the Mach Number distribution. A mathematical representation of the evaluation criteria coupled with a parametric geometry generator enables the use of formal optimization techniques in the design. The proposed approach is implemented in the optimal design of a low-pressure turbine nozzle.
International Nuclear Information System (INIS)
Halimi, B.; Suh, Kune Y.
2012-01-01
Highlights: ► A nonlinearity characteristic compensation is proposed of the steam turbine control valve. ► A steady state and transient analyzer is developed of Ulchin Units 3 and 4 OPR1000 nuclear plants. ► MARS code and Matlab Simulink are used to verify the compensation concept. ► The results show the concept can compensate for the nonlinearity characteristic very well. - Abstract: Steam turbine control valves play a pivotal role in regulating the output power of the turbine in a commercial power plant. They thus have to be operated linearly to be run by an automatic control system. Unfortunately, the control valve has inherently nonlinearity characteristics. The flow increases more significantly near the closed end than near the open end of the stem travel given the valve position signal. The steam flow should nonetheless be proportional to the final desired quantity, output power, of the turbine to obtain a linear operation. This paper presents the valve engineering linked analysis (VELA) for nonlinearity characteristic compensation of the steam turbine control valve by using a linked two existing commercial software. The Multi-dimensional Analysis of Reactor Safety (MARS) code and Matlab Simulink have been selected for VELA to develop a steady state and transient analyzer of Ulchin Units 3 and 4 powered by the Optimized Power Reactor 1000 MWe (OPR1000). MARS is capable of modeling a wide range of systems from single pipes to full nuclear power plants. As one of standard nuclear power plant thermal hydraulic analysis software tools, MARS simulates the primary and secondary sides of the nuclear power plant. To simulate the electric power flow part, Matlab Simulink is chosen as the standard analysis software. Matlab Simulink having an interactive environment to model analyzes and simulates a wide variety of engineering dynamic systems including multimachine power systems. Based on the MARS code result, Matlab Simulink analyzes the power flow of the
Meyn, Larry A.
2018-01-01
One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its use
NonLinear Parallel OPtimization Tool, Phase I
National Aeronautics and Space Administration — CU Aerospace, in partnership with the University of Illinois propose the further development of a new sparse nonlinear programming architecture that exploits...
GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling
International Nuclear Information System (INIS)
Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas
2015-01-01
Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and
Directory of Open Access Journals (Sweden)
Guo-Qiang Zeng
2014-01-01
Full Text Available As a novel evolutionary optimization method, extremal optimization (EO has been successfully applied to a variety of combinatorial optimization problems. However, the applications of EO in continuous optimization problems are relatively rare. This paper proposes an improved real-coded population-based EO method (IRPEO for continuous unconstrained optimization problems. The key operations of IRPEO include generation of real-coded random initial population, evaluation of individual and population fitness, selection of bad elements according to power-law probability distribution, generation of new population based on uniform random mutation, and updating the population by accepting the new population unconditionally. The experimental results on 10 benchmark test functions with the dimension N=30 have shown that IRPEO is competitive or even better than the recently reported various genetic algorithm (GA versions with different mutation operations in terms of simplicity, effectiveness, and efficiency. Furthermore, the superiority of IRPEO to other evolutionary algorithms such as original population-based EO, particle swarm optimization (PSO, and the hybrid PSO-EO is also demonstrated by the experimental results on some benchmark functions.
A NEW CODE FOR NONLINEAR FORCE-FREE FIELD EXTRAPOLATION OF THE GLOBAL CORONA
International Nuclear Information System (INIS)
Jiang Chaowei; Feng Xueshang; Xiang Changqing
2012-01-01
Reliable measurements of the solar magnetic field are still restricted to the photosphere, and our present knowledge of the three-dimensional coronal magnetic field is largely based on extrapolations from photospheric magnetograms using physical models, e.g., the nonlinear force-free field (NLFFF) model that is usually adopted. Most of the currently available NLFFF codes have been developed with computational volume such as a Cartesian box or a spherical wedge, while a global full-sphere extrapolation is still under development. A high-performance global extrapolation code is in particular urgently needed considering that the Solar Dynamics Observatory can provide a full-disk magnetogram with resolution up to 4096 × 4096. In this work, we present a new parallelized code for global NLFFF extrapolation with the photosphere magnetogram as input. The method is based on the magnetohydrodynamics relaxation approach, the CESE-MHD numerical scheme, and a Yin-Yang spherical grid that is used to overcome the polar problems of the standard spherical grid. The code is validated by two full-sphere force-free solutions from Low and Lou's semi-analytic force-free field model. The code shows high accuracy and fast convergence, and can be ready for future practical application if combined with an adaptive mesh refinement technique.
Directory of Open Access Journals (Sweden)
Akemi Gálvez
2013-01-01
Full Text Available Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor’s method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently.
ABAQUS/EPGEN - a general purpose finite element code with emphasis on nonlinear applications
International Nuclear Information System (INIS)
Hibbitt, H.D.
1984-01-01
The article contains a summary description of ABAQUS, a finite element program designed for general use in nonlinear as well as linear structural problems, in the context of its application to nuclear structural integrity analysis. The article begins with a discussion of the design criteria and methods upon which the code development has been based. The engineering modelling capabilities, currently implemented in the program - elements, constitutive models and analysis procedures - are then described. Finally, a few demonstration examples are presented, to illustrate some of the program's features that are of interest in structural integrity analysis associated with nuclear power plants. (orig.)
Computer codes for three dimensional mass transport with non-linear sorption
International Nuclear Information System (INIS)
Noy, D.J.
1985-03-01
The report describes the mathematical background and data input to finite element programs for three dimensional mass transport in a porous medium. The transport equations are developed and sorption processes are included in a general way so that non-linear equilibrium relations can be introduced. The programs are described and a guide given to the construction of the required input data sets. Concluding remarks indicate that the calculations require substantial computer resources and suggest that comprehensive preliminary analysis with lower dimensional codes would be important in the assessment of field data. (author)
CENTAR code for extended nonlinear transient analysis of extraterrestrial reactor systems
International Nuclear Information System (INIS)
Nassersharif, B.; Peer, J.S.; DeHart, M.D.
1987-01-01
Current interest in the application of nuclear reactor-driven power systems to space missions has generated a need for a systems simulation code to model and analyze space reactor systems; such a code has been initiated at Texas A and M, and the first version is nearing completion; release was anticipated in the fall of 1987. This code, named CENTAR (Code for Extended Nonlinear Transient Analysis of Extraterrestrial Reactor Systems), is designed specifically for space systems and is highly vectorizable. CENTAR is composed of several specialized modules. A fluids module is used to model fluid behavior throughout the system. A wall heat transfer module models the heat transfer characteristics of all walls, insulation, and structure around the system. A fuel element thermal analysis module is used to predict the temperature behavior and heat transfer characteristics of the reactor fuel rods. A kinetics module uses a six-group point kinetics formulation to model reactivity feedback and control and the ANS 5.1 decay-heat curve to model shutdown decay-heat production. A pump module models the behavior of thermoelectric-electromagnetic pumps, and a heat exchanger module models not only thermal effects in thermoelectric heat exchangers, but also predicts electrical power production for a given configuration. Finally, an accumulator module models coolant expansion/contraction accumulators
Optimized parallel convolutions for non-linear fluid models of tokamak ηi turbulence
International Nuclear Information System (INIS)
Milovich, J.L.; Tomaschke, G.; Kerbel, G.D.
1993-01-01
Non-linear computational fluid models of plasma turbulence based on spectral methods typically spend a large fraction of the total computing time evaluating convolutions. Usually these convolutions arise from an explicit or semi implicit treatment of the convective non-linearities in the problem. Often the principal convective velocity is perpendicular to magnetic field lines allowing a reduction of the convolution to two dimensions in an appropriate geometry, but beyond this, different models vary widely in the particulars of which mode amplitudes are selectively evolved to get the most efficient representation of the turbulence. As the number of modes in the problem, N, increases, the amount of computation required for this part of the evolution algorithm then scales as N 2 /timestep for a direct or analytic method and N ln N/timestep for a pseudospectral method. The constants of proportionality depend on the particulars of mode selection and determine the size problem for which the method will perform equally. For large enough N, the pseudospectral method performance is always superior, though some problems do not require correspondingly high resolution. Further, the Courant condition for numerical stability requires that the timestep size must decrease proportionately as N increases, thus accentuating the need to have fast methods for larger N problems. The authors have developed a package for the Cray system which performs these convolutions for a rather arbitrary mode selection scheme using either method. The package is highly optimized using a combination of macro and microtasking techniques, as well as vectorization and in some cases assembly coded routines. Parts of the package have also been developed and optimized for the CM200 and CM5 system. Performance comparisons with respect to problem size, parallelization, selection schemes and architecture are presented
A novel neutron energy spectrum unfolding code using particle swarm optimization
International Nuclear Information System (INIS)
Shahabinejad, H.; Sohrabpour, M.
2017-01-01
A novel neutron Spectrum Deconvolution using Particle Swarm Optimization (SDPSO) code has been developed to unfold the neutron spectrum from a pulse height distribution and a response matrix. The Particle Swarm Optimization (PSO) imitates the bird flocks social behavior to solve complex optimization problems. The results of the SDPSO code have been compared with those of the standard spectra and recently published Two-steps Genetic Algorithm Spectrum Unfolding (TGASU) code. The TGASU code have been previously compared with the other codes such as MAXED, GRAVEL, FERDOR and GAMCD and shown to be more accurate than the previous codes. The results of the SDPSO code have been demonstrated to match well with those of the TGASU code for both under determined and over-determined problems. In addition the SDPSO has been shown to be nearly two times faster than the TGASU code. - Highlights: • Introducing a novel method for neutron spectrum unfolding. • Implementation of a particle swarm optimization code for neutron unfolding. • Comparing results of the PSO code with those of recently published TGASU code. • Match results of the PSO code with those of TGASU code. • Greater convergence rate of implemented PSO code than TGASU code.
Nonlinear dynamic simulation of optimal depletion of crude oil in the lower 48 United States
International Nuclear Information System (INIS)
Ruth, M.; Cleveland, C.J.
1993-01-01
This study combines the economic theory of optimal resource use with econometric estimates of demand and supply parameters to develop a nonlinear dynamic model of crude oil exploration, development, and production in the lower 48 United States. The model is simulated with the graphical programming language STELLA, for the years 1985 to 2020. The procedure encourages use of economic theory and econometrics in combination with nonlinear dynamic simulation to enhance our understanding of complex interactions present in models of optimal resource use. (author)
A three-dimensional computer code for the nonlinear dynamic response of an HTGR core
International Nuclear Information System (INIS)
Subudhi, M.; Lasker, L.; Koplik, B.; Curreri, J.; Goradia, H.
1979-01-01
A three-dimensional dynamic code has been developed to determine the nonlinear response of an HTGR core. The HTGR core consists of several thousands of hexagonal core blocks. These are arranged in layers stacked together. Each layer contains many core blocks surrounded on their outer periphery by reflector blocks. The entire assembly is contained within a prestressed concrete reactor vessel. Gaps exist between adjacent blocks in any horizontal plane. Each core block in a given layer is connected to the blocks directly above and below it via three dowell pins. The present analytical study is directed towards an investigation of the nonlinear response of the reactor core blocks in the event of a seismic occurrence. The computer code is developed for a specific mathematical model which represents a vertical arrangement of layers of blocks. This comprises a 'block module' of core elements which would be obtained by cutting a cylindrical portion consisting of seven fuel blocks per layer. It is anticipated that a number of such modules properly arranged could represent the entire core. Hence, the predicted response of this module would exhibit the response characteristics of the core. (orig.)
Three-dimensional computer code for the nonlinear dynamic response of an HTGR core
International Nuclear Information System (INIS)
Subudhi, M.; Lasker, L.; Koplik, B.; Curreri, J.; Goradia, H.
1979-01-01
A three-dimensional dynamic code has been developed to determine the nonlinear response of an HTGR core. The HTGR core consists of several thousands of hexagonal core blocks. These are arranged inlayers stacked together. Each layer contains many core blocks surrounded on their outer periphery by reflector blocks. The entire assembly is contained within a prestressed concrete reactor vessel. Gaps exist between adjacent blocks in any horizontal plane. Each core block in a given layer is connected to the blocks directly above and below it via three dowell pins. The present analystical study is directed towards an invesstigation of the nonlinear response of the reactor core blocks in the event of a seismic occurrence. The computer code is developed for a specific mathemtical model which represents a vertical arrangement of layers of blocks. This comprises a block module of core elements which would be obtained by cutting a cylindrical portion consisting of seven fuel blocks per layer. It is anticipated that a number of such modules properly arranged could represent the entire core. Hence, the predicted response of this module would exhibit the response characteristics of the core
Optimization of lift gas allocation in a gas lifted oil field as non-linear optimization problem
Directory of Open Access Journals (Sweden)
Roshan Sharma
2012-01-01
Full Text Available Proper allocation and distribution of lift gas is necessary for maximizing total oil production from a field with gas lifted oil wells. When the supply of the lift gas is limited, the total available gas should be optimally distributed among the oil wells of the field such that the total production of oil from the field is maximized. This paper describes a non-linear optimization problem with constraints associated with the optimal distribution of the lift gas. A non-linear objective function is developed using a simple dynamic model of the oil field where the decision variables represent the lift gas flow rate set points of each oil well of the field. The lift gas optimization problem is solved using the emph'fmincon' solver found in MATLAB. As an alternative and for verification, hill climbing method is utilized for solving the optimization problem. Using both of these methods, it has been shown that after optimization, the total oil production is increased by about 4. For multiple oil wells sharing lift gas from a common source, a cascade control strategy along with a nonlinear steady state optimizer behaves as a self-optimizing control structure when the total supply of lift gas is assumed to be the only input disturbance present in the process. Simulation results show that repeated optimization performed after the first time optimization under the presence of the input disturbance has no effect in the total oil production.
Distributed Optimization for a Class of Nonlinear Multiagent Systems With Disturbance Rejection.
Wang, Xinghu; Hong, Yiguang; Ji, Haibo
2016-07-01
The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the internal model approach, we propose a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree. We prove that the proposed design can solve the exact optimization problem with rejecting disturbances.
Optimization of the FAST ICRF antenna using TOPICA code
International Nuclear Information System (INIS)
Sorba, M.; Milanesio, D.; Maggiora, R.; Tuccillo, A.
2010-01-01
Ion Cyclotron Resonance Heating is one of the most important auxiliary heating systems in most plasma confinement experiments. Because of this, the need for very accurate design of ion cyclotron (IC) launchers has dramatically grown in recent years. Furthermore, a reliable simulation tool is a crucial request in the successful design of these antennas, since full testing is impossible outside experiments. One of the most advanced and validated simulation codes is TOPICA, which offers the possibility to handle the geometrical level of detail of a real antenna in front of an accurately described plasma scenario. Adopting this essential tool made possible to reach a refined design of ion cyclotron radio frequency antenna for the FAST (Fusion Advanced Studies Torus) experiment . Starting from a streamlined antenna model and then following well-defined refinement procedures, an optimized launcher design in terms of power delivered to plasma has been finally achieved. The computer-assisted geometry refinements allowed an increase in the performances of the antenna and notably in power handling: the extent of the gained improvements were not experienced in the past, essentially due to the absence of predictive tools capable of analyzing the detailed effects of antenna geometry in plasma facing conditions. Thus, with the help of TOPICA code, it has been possible to comply with the FAST experiment requirements in terms of vacuum chamber constraints and power delivered to plasma. Once an antenna geometry was optimized with a reference plasma profile, the analysis of the performances of the launcher has been extended with respect to two plasma scenarios. Exploiting all TOPICA features, it has been possible to predict the behavior of the launcher in real operating conditions, for instance varying the position of the separatrix surface. In order to fulfil the analysis of the FAST IC antenna, the study of the RF potentials, which depend on the parallel electric field computation
Optimized Min-Sum Decoding Algorithm for Low Density Parity Check Codes
Mohammad Rakibul Islam; Dewan Siam Shafiullah; Muhammad Mostafa Amir Faisal; Imran Rahman
2011-01-01
Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the sam...
Estimation of dynamic reactivity using an H∞ optimal filter with a nonlinear term
International Nuclear Information System (INIS)
Suzuki, Katsuo; Watanabe, Koiti
1996-01-01
A method of nonlinear filtering is applied to the problem of estimating the dynamic reactivity of a nonlinear reactor system. The nonlinear filtering algorithm developed is a simple modification of a linear H ∞ optimal filter with a nonlinear feedback loop added. The linear filter is designed on the basis of a linearized dynamical system model that consists of linearized point reactor kinetic equations and a reactivity state equation driven by a fictitious signal. The latter is artificially introduced to deal with the reactivity as a state variable. The results of the computer simulation show that the nonlinear filtering algorithm can be applied to estimate the dynamic reactivity of the nonlinear reactor system, even under relatively large reactivity disturbances
Optimal Control Problems for Nonlinear Variational Evolution Inequalities
Directory of Open Access Journals (Sweden)
Eun-Young Ju
2013-01-01
Full Text Available We deal with optimal control problems governed by semilinear parabolic type equations and in particular described by variational inequalities. We will also characterize the optimal controls by giving necessary conditions for optimality by proving the Gâteaux differentiability of solution mapping on control variables.
Phenotypic Graphs and Evolution Unfold the Standard Genetic Code as the Optimal
Zamudio, Gabriel S.; José, Marco V.
2018-03-01
In this work, we explicitly consider the evolution of the Standard Genetic Code (SGC) by assuming two evolutionary stages, to wit, the primeval RNY code and two intermediate codes in between. We used network theory and graph theory to measure the connectivity of each phenotypic graph. The connectivity values are compared to the values of the codes under different randomization scenarios. An error-correcting optimal code is one in which the algebraic connectivity is minimized. We show that the SGC is optimal in regard to its robustness and error-tolerance when compared to all random codes under different assumptions.
A Realistic Model under which the Genetic Code is Optimal
Buhrman, H.; van der Gulik, P.T.S.; Klau, G.W.; Schaffner, C.; Speijer, D.; Stougie, L.
2013-01-01
The genetic code has a high level of error robustness. Using values of hydrophobicity scales as a proxy for amino acid character, and the mean square measure as a function quantifying error robustness, a value can be obtained for a genetic code which reflects the error robustness of that code. By
NonLinear Parallel OPtimization Tool, Phase II
National Aeronautics and Space Administration — The technological advancement proposed is a novel large-scale Noninear Parallel OPtimization Tool (NLPAROPT). This software package will eliminate the computational...
Wavefront optimized nonlinear microscopy of ex vivo human retinas
Gualda, Emilio J.; Bueno, Juan M.; Artal, Pablo
2010-03-01
A multiphoton microscope incorporating a Hartmann-Shack (HS) wavefront sensor to control the ultrafast laser beam's wavefront aberrations has been developed. This instrument allowed us to investigate the impact of the laser beam aberrations on two-photon autofluorescence imaging of human retinal tissues. We demonstrated that nonlinear microscopy images are improved when laser beam aberrations are minimized by realigning the laser system cavity while wavefront controlling. Nonlinear signals from several human retinal anatomical features have been detected for the first time, without the need of fixation or staining procedures. Beyond the improved image quality, this approach reduces the required excitation power levels, minimizing the side effects of phototoxicity within the imaged sample. In particular, this may be important to study the physiology and function of the healthy and diseased retina.
Self-optimizing robust nonlinear model predictive control
Lazar, M.; Heemels, W.P.M.H.; Jokic, A.; Thoma, M.; Allgöwer, F.; Morari, M.
2009-01-01
This paper presents a novel method for designing robust MPC schemes that are self-optimizing in terms of disturbance attenuation. The method employs convex control Lyapunov functions and disturbance bounds to optimize robustness of the closed-loop system on-line, at each sampling instant - a unique
Engineering application of in-core fuel management optimization code with CSA algorithm
Energy Technology Data Exchange (ETDEWEB)
Liu, Zhihong; Hu, Yongming [INET, Tsinghua university, Beijing 100084 (China)
2009-06-15
PWR in-core loading (reloading) pattern optimization is a complex combined problem. An excellent fuel management optimization code can greatly improve the efficiency of core reloading design, and bring economic and safety benefits. Today many optimization codes with experiences or searching algorithms (such as SA, GA, ANN, ACO) have been developed, while how to improve their searching efficiency and engineering usability still needs further research. CSA (Characteristic Statistic Algorithm) is a global optimization algorithm with high efficiency developed by our team. The performance of CSA has been proved on many problems (such as Traveling Salesman Problems). The idea of CSA is to induce searching direction by the statistic distribution of characteristic values. This algorithm is quite suitable for fuel management optimization. Optimization code with CSA has been developed and was used on many core models. The research in this paper is to improve the engineering usability of CSA code according to all the actual engineering requirements. Many new improvements have been completed in this code, such as: 1. Considering the asymmetry of burn-up in one assembly, the rotation of each assembly is considered as new optimization variables in this code. 2. Worth of control rods must satisfy the given constraint, so some relative modifications are added into optimization code. 3. To deal with the combination of alternate cycles, multi-cycle optimization is considered in this code. 4. To confirm the accuracy of optimization results, many identifications of the physics calculation module in this code have been done, and the parameters of optimization schemes are checked by SCIENCE code. The improved optimization code with CSA has been used on Qinshan nuclear plant of China. The reloading of cycle 7, 8, 9 (12 months, no burnable poisons) and the 18 months equilibrium cycle (with burnable poisons) reloading are optimized. At last, many optimized schemes are found by CSA code
Non-Linear Transaction Costs Inclusion in Mean-Variance Optimization
Directory of Open Access Journals (Sweden)
Christian Johannes Zimmer
2005-12-01
Full Text Available In this article we propose a new way to include transaction costs into a mean-variance portfolio optimization. We consider brokerage fees, bid/ask spread and the market impact of the trade. A pragmatic algorithm is proposed, which approximates the optimal portfolio, and we can show that is converges in the absence of restrictions. Using Brazilian financial market data we compare our approximation algorithm with the results of a non-linear optimizer.
Greedy vs. L1 convex optimization in sparse coding
DEFF Research Database (Denmark)
Ren, Huamin; Pan, Hong; Olsen, Søren Ingvor
2015-01-01
Sparse representation has been applied successfully in many image analysis applications, including abnormal event detection, in which a baseline is to learn a dictionary from the training data and detect anomalies from its sparse codes. During this procedure, sparse codes which can be achieved...... solutions. Considering the property of abnormal event detection, i.e., only normal videos are used as training data due to practical reasons, effective codes in classification application may not perform well in abnormality detection. Therefore, we compare the sparse codes and comprehensively evaluate...... their performance from various aspects to better understand their applicability, including computation time, reconstruction error, sparsity, detection...
Novel Area Optimization in FPGA Implementation Using Efficient VHDL Code
Directory of Open Access Journals (Sweden)
. Zulfikar
2012-10-01
Full Text Available A new novel method for area efficiency in FPGA implementation is presented. The method is realized through flexibility and wide capability of VHDL coding. This method exposes the arithmetic operations such as addition, subtraction and others. The design technique aim to reduce occupies area for multi stages circuits by selecting suitable range of all value involved in every step of calculations. Conventional and efficient VHDL coding methods are presented and the synthesis result is compared. The VHDL code which limits range of integer values is occupies less area than the one which is not. This VHDL coding method is suitable for multi stage circuits.
Novel Area Optimization in FPGA Implementation Using Efficient VHDL Code
Directory of Open Access Journals (Sweden)
Zulfikar .
2015-05-01
Full Text Available A new novel method for area efficiency in FPGA implementation is presented. The method is realized through flexibility and wide capability of VHDL coding. This method exposes the arithmetic operations such as addition, subtraction and others. The design technique aim to reduce occupies area for multi stages circuits by selecting suitable range of all value involved in every step of calculations. Conventional and efficient VHDL coding methods are presented and the synthesis result is compared. The VHDL code which limits range of integer values is occupies less area than the one which is not. This VHDL coding method is suitable for multi stage circuits.
QR code-based non-linear image encryption using Shearlet transform and spiral phase transform
Kumar, Ravi; Bhaduri, Basanta; Hennelly, Bryan
2018-02-01
In this paper, we propose a new quick response (QR) code-based non-linear technique for image encryption using Shearlet transform (ST) and spiral phase transform. The input image is first converted into a QR code and then scrambled using the Arnold transform. The scrambled image is then decomposed into five coefficients using the ST and the first Shearlet coefficient, C1 is interchanged with a security key before performing the inverse ST. The output after inverse ST is then modulated with a random phase mask and further spiral phase transformed to get the final encrypted image. The first coefficient, C1 is used as a private key for decryption. The sensitivity of the security keys is analysed in terms of correlation coefficient and peak signal-to noise ratio. The robustness of the scheme is also checked against various attacks such as noise, occlusion and special attacks. Numerical simulation results are shown in support of the proposed technique and an optoelectronic set-up for encryption is also proposed.
Generalized rank weights of reducible codes, optimal cases and related properties
DEFF Research Database (Denmark)
Martinez Peñas, Umberto
2018-01-01
in network coding. In this paper, we study their security behavior against information leakage on networks when applied as coset coding schemes, giving the following main results: 1) we give lower and upper bounds on their generalized rank weights (GRWs), which measure worst case information leakage...... to the wire tapper; 2) we find new parameters for which these codes are MRD (meaning that their first GRW is optimal) and use the previous bounds to estimate their higher GRWs; 3) we show that all linear (over the extension field) codes, whose GRWs are all optimal for fixed packet and code sizes but varying...... length are reducible codes up to rank equivalence; and 4) we show that the information leaked to a wire tapper when using reducible codes is often much less than the worst case given by their (optimal in some cases) GRWs. We conclude with some secondary related properties: conditions to be rank...
Optimization of hardening/softening behavior of plane frame structures using nonlinear normal modes
DEFF Research Database (Denmark)
Dou, Suguang; Jensen, Jakob Søndergaard
2016-01-01
Devices that exploit essential nonlinear behavior such as hardening/softening and inter-modal coupling effects are increasingly used in engineering and fundamental studies. Based on nonlinear normal modes, we present a gradient-based structural optimization method for tailoring the hardening...... involving plane frame structures where the hardening/softening behavior is qualitatively and quantitatively tuned by simple changes in the geometry of the structures....
International Nuclear Information System (INIS)
Maldonado, G.I.; Turinsky, P.J.; Kropaczek, D.J.
1993-01-01
The computational capability of efficiently and accurately evaluate reactor core attributes (i.e., k eff and power distributions as a function of cycle burnup) utilizing a second-order accurate advanced nodal Generalized Perturbation Theory (GPT) model has been developed. The GPT model is derived from the forward non-linear iterative Nodal Expansion Method (NEM) strategy, thereby extending its inherent savings in memory storage and high computational efficiency to also encompass GPT via the preservation of the finite-difference matrix structure. The above development was easily implemented into the existing coarse-mesh finite-difference GPT-based in-core fuel management optimization code FORMOSA-P, thus combining the proven robustness of its adaptive Simulated Annealing (SA) multiple-objective optimization algorithm with a high-fidelity NEM GPT neutronics model to produce a powerful computational tool used to generate families of near-optimum loading patterns for PWRs. (orig.)
A Nonlinear GMRES Optimization Algorithm for Canonical Tensor Decomposition
De Sterck, Hans
2011-01-01
A new algorithm is presented for computing a canonical rank-R tensor approximation that has minimal distance to a given tensor in the Frobenius norm, where the canonical rank-R tensor consists of the sum of R rank-one components. Each iteration of the method consists of three steps. In the first step, a tentative new iterate is generated by a stand-alone one-step process, for which we use alternating least squares (ALS). In the second step, an accelerated iterate is generated by a nonlinear g...
Simulation-based optimal Bayesian experimental design for nonlinear systems
Huan, Xun; Marzouk, Youssef M.
2013-01-01
The optimal selection of experimental conditions is essential to maximizing the value of data for inference and prediction, particularly in situations where experiments are time-consuming and expensive to conduct. We propose a general mathematical
Nonlinear Multidimensional Assignment Problems Efficient Conic Optimization Methods and Applications
2015-06-24
WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Arizona State University School of Mathematical & Statistical Sciences 901 S...SUPPLEMENTARY NOTES 14. ABSTRACT The major goals of this project were completed: the exact solution of previously unsolved challenging combinatorial optimization... combinatorial optimization problem, the Directional Sensor Problem, was solved in two ways. First, heuristically in an engineering fashion and second, exactly
Optimal Near-Hitless Network Failure Recovery Using Diversity Coding
Avci, Serhat Nazim
2013-01-01
Link failures in wide area networks are common and cause significant data losses. Mesh-based protection schemes offer high capacity efficiency but they are slow, require complex signaling, and instable. Diversity coding is a proactive coding-based recovery technique which offers near-hitless (sub-ms) restoration with a competitive spare capacity…
Differentially Encoded LDPC CodesÃ¢Â€Â”Part II: General Case and Code Optimization
Directory of Open Access Journals (Sweden)
Jing Li (Tiffany
2008-04-01
Full Text Available This two-part series of papers studies the theory and practice of differentially encoded low-density parity-check (DE-LDPC codes, especially in the context of noncoherent detection. Part I showed that a special class of DE-LDPC codes, product accumulate codes, perform very well with both coherent and noncoherent detections. The analysis here reveals that a conventional LDPC code, however, is not fitful for differential coding and does not, in general, deliver a desirable performance when detected noncoherently. Through extrinsic information transfer (EXIT analysis and a modified Ã¢Â€Âœconvergence-constraintÃ¢Â€Â density evolution (DE method developed here, we provide a characterization of the type of LDPC degree profiles that work in harmony with differential detection (or a recursive inner code in general, and demonstrate how to optimize these LDPC codes. The convergence-constraint method provides a useful extension to the conventional Ã¢Â€Âœthreshold-constraintÃ¢Â€Â method, and can match an outer LDPC code to any given inner code with the imperfectness of the inner decoder taken into consideration.
Directory of Open Access Journals (Sweden)
Shaolong Chen
2016-01-01
Full Text Available Parameter estimation is an important problem in nonlinear system modeling and control. Through constructing an appropriate fitness function, parameter estimation of system could be converted to a multidimensional parameter optimization problem. As a novel swarm intelligence algorithm, chicken swarm optimization (CSO has attracted much attention owing to its good global convergence and robustness. In this paper, a method based on improved boundary chicken swarm optimization (IBCSO is proposed for parameter estimation of nonlinear systems, demonstrated and tested by Lorenz system and a coupling motor system. Furthermore, we have analyzed the influence of time series on the estimation accuracy. Computer simulation results show it is feasible and with desirable performance for parameter estimation of nonlinear systems.
Optimization Formulations for the Maximum Nonlinear Buckling Load of Composite Structures
DEFF Research Database (Denmark)
Lindgaard, Esben; Lund, Erik
2011-01-01
This paper focuses on criterion functions for gradient based optimization of the buckling load of laminated composite structures considering different types of buckling behaviour. A local criterion is developed, and is, together with a range of local and global criterion functions from literature......, benchmarked on a number of numerical examples of laminated composite structures for the maximization of the buckling load considering fiber angle design variables. The optimization formulations are based on either linear or geometrically nonlinear analysis and formulated as mathematical programming problems...... solved using gradient based techniques. The developed local criterion is formulated such it captures nonlinear effects upon loading and proves useful for both analysis purposes and as a criterion for use in nonlinear buckling optimization. © 2010 Springer-Verlag....
Lan, C. Edward; Ge, Fuying
1989-01-01
Control system design for general nonlinear flight dynamic models is considered through numerical simulation. The design is accomplished through a numerical optimizer coupled with analysis of flight dynamic equations. The general flight dynamic equations are numerically integrated and dynamic characteristics are then identified from the dynamic response. The design variables are determined iteratively by the optimizer to optimize a prescribed objective function which is related to desired dynamic characteristics. Generality of the method allows nonlinear effects to aerodynamics and dynamic coupling to be considered in the design process. To demonstrate the method, nonlinear simulation models for an F-5A and an F-16 configurations are used to design dampers to satisfy specifications on flying qualities and control systems to prevent departure. The results indicate that the present method is simple in formulation and effective in satisfying the design objectives.
Qiao, Shan; Jackson, Edward; Coussios, Constantin C; Cleveland, Robin O
2016-09-01
Nonlinear acoustics plays an important role in both diagnostic and therapeutic applications of biomedical ultrasound and a number of research and commercial software packages are available. In this manuscript, predictions of two solvers available in a commercial software package, pzflex, one using the finite-element-method (FEM) and the other a pseudo-spectral method, spectralflex, are compared with measurements and the Khokhlov-Zabolotskaya-Kuznetsov (KZK) Texas code (a finite-difference time-domain algorithm). The pzflex methods solve the continuity equation, momentum equation and equation of state where they account for nonlinearity to second order whereas the KZK code solves a nonlinear wave equation with a paraxial approximation for diffraction. Measurements of the field from a single element 3.3 MHz focused transducer were compared with the simulations and there was good agreement for the fundamental frequency and the harmonics; however the FEM pzflex solver incurred a high computational cost to achieve equivalent accuracy. In addition, pzflex results exhibited non-physical oscillations in the spatial distribution of harmonics when the amplitudes were relatively low. It was found that spectralflex was able to accurately capture the nonlinear fields at reasonable computational cost. These results emphasize the need to benchmark nonlinear simulations before using codes as predictive tools.
Complex fluid network optimization and control integrative design based on nonlinear dynamic model
International Nuclear Information System (INIS)
Sui, Jinxue; Yang, Li; Hu, Yunan
2016-01-01
In view of distribution according to complex fluid network’s needs, this paper proposed one optimization computation method of the nonlinear programming mathematical model based on genetic algorithm. The simulation result shows that the overall energy consumption of the optimized fluid network has a decrease obviously. The control model of the fluid network is established based on nonlinear dynamics. We design the control law based on feedback linearization, take the optimal value by genetic algorithm as the simulation data, can also solve the branch resistance under the optimal value. These resistances can provide technical support and reference for fluid network design and construction, so can realize complex fluid network optimization and control integration design.
Stupishin, L. U.; Nikitin, K. E.; Kolesnikov, A. G.
2018-02-01
The article is concerned with a methodology of optimal design of geometrically nonlinear (flexible) shells of revolution of minimum weight with strength, stability and strain constraints. The problem of optimal design with constraints is reduced to the problem of unconstrained minimization using the penalty functions method. Stress-strain state of shell is determined within the geometrically nonlinear deformation theory. A special feature of the methodology is the use of a mixed finite-element formulation based on the Galerkin method. Test problems for determining the optimal form and thickness distribution of a shell of minimum weight are considered. The validity of the results obtained using the developed methodology is analyzed, and the efficiency of various optimization algorithms is compared to solve the set problem. The developed methodology has demonstrated the possibility and accuracy of finding the optimal solution.
Galerkin v. discrete-optimal projection in nonlinear model reduction
Energy Technology Data Exchange (ETDEWEB)
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.
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.
Optimal control of nonlinear continuous-time systems in strict-feedback form.
Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani
2015-10-01
This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.
Efficacy of Code Optimization on Cache-based Processors
VanderWijngaart, Rob F.; Chancellor, Marisa K. (Technical Monitor)
1997-01-01
The current common wisdom in the U.S. is that the powerful, cost-effective supercomputers of tomorrow will be based on commodity (RISC) micro-processors with cache memories. Already, most distributed systems in the world use such hardware as building blocks. This shift away from vector supercomputers and towards cache-based systems has brought about a change in programming paradigm, even when ignoring issues of parallelism. Vector machines require inner-loop independence and regular, non-pathological memory strides (usually this means: non-power-of-two strides) to allow efficient vectorization of array operations. Cache-based systems require spatial and temporal locality of data, so that data once read from main memory and stored in high-speed cache memory is used optimally before being written back to main memory. This means that the most cache-friendly array operations are those that feature zero or unit stride, so that each unit of data read from main memory (a cache line) contains information for the next iteration in the loop. Moreover, loops ought to be 'fat', meaning that as many operations as possible are performed on cache data-provided instruction caches do not overflow and enough registers are available. If unit stride is not possible, for example because of some data dependency, then care must be taken to avoid pathological strides, just ads on vector computers. For cache-based systems the issues are more complex, due to the effects of associativity and of non-unit block (cache line) size. But there is more to the story. Most modern micro-processors are superscalar, which means that they can issue several (arithmetic) instructions per clock cycle, provided that there are enough independent instructions in the loop body. This is another argument for providing fat loop bodies. With these restrictions, it appears fairly straightforward to produce code that will run efficiently on any cache-based system. It can be argued that although some of the important
Nonlinear Non-convex Optimization of Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Kallesøe, Carsten; Leth, John-Josef
2013-01-01
Pressure management in water supply systems is an effective way to reduce the leakage in a system. In this paper, the pressure management and the reduction of power consumption of a water supply system is formulated as an optimization problem. The problem is to minimize the power consumption in p....... They can be used for a general hydraulic networks to optimize the leakage and energy consumption and to satisfy the demands at the end-users. The results in this paper show that the power consumption of the pumps is reduced.......Pressure management in water supply systems is an effective way to reduce the leakage in a system. In this paper, the pressure management and the reduction of power consumption of a water supply system is formulated as an optimization problem. The problem is to minimize the power consumption...
DEFF Research Database (Denmark)
Yoon, Gil Ho; Joung, Young Soo; Kim, Yoon Young
2005-01-01
The topology design optimization of “three-dimensional geometrically-nonlinear” continuum structures is still a difficult problem not only because of its problem size but also the occurrence of unstable continuum finite elements during the design optimization. To overcome this difficulty, the ele......) stiffness matrix of continuum finite elements. Therefore, any finite element code, including commercial codes, can be readily used for the ECP implementation. The key ideas and characteristics of these methods will be presented in this paper....
Optimal Control Of Nonlinear Wave Energy Point Converters
DEFF Research Database (Denmark)
Nielsen, Søren R.K.; Zhou, Qiang; Kramer, Morten
2013-01-01
idea behind the control strategy is to enforce the stationary velocity response of the absorber into phase with the wave excitation force at any time. The controller is optimal under monochromatic wave excitation. It is demonstrated that the devised causal controller, in plane irregular sea states...
Nonlinear Dynamic Analysis and Optimization of Closed-Form Planetary Gear System
Directory of Open Access Journals (Sweden)
Qilin Huang
2013-01-01
Full Text Available A nonlinear purely rotational dynamic model of a multistage closed-form planetary gear set formed by two simple planetary stages is proposed in this study. The model includes time-varying mesh stiffness, excitation fluctuation and gear backlash nonlinearities. The nonlinear differential equations of motion are solved numerically using variable step-size Runge-Kutta. In order to obtain function expression of optimization objective, the nonlinear differential equations of motion are solved analytically using harmonic balance method (HBM. Based on the analytical solution of dynamic equations, the optimization mathematical model which aims at minimizing the vibration displacement of the low-speed carrier and the total mass of the gear transmission system is established. The optimization toolbox in MATLAB program is adopted to obtain the optimal solution. A case is studied to demonstrate the effectiveness of the dynamic model and the optimization method. The results show that the dynamic properties of the closed-form planetary gear transmission system have been improved and the total mass of the gear set has been decreased significantly.
Novel Area Optimization in FPGA Implementation Using Efficient VHDL Code
Zulfikar, Z
2012-01-01
A new novel method for area efficiency in FPGA implementation is presented. The method is realized through flexibility and wide capability of VHDL coding. This method exposes the arithmetic operations such as addition, subtraction and others. The design technique aim to reduce occupies area for multi stages circuits by selecting suitable range of all value involved in every step of calculations. Conventional and efficient VHDL coding methods are presented and the synthesis result is compared....
Dattoli, Giuseppe
2005-01-01
The coherent synchrotron radiation (CSR) is one of the main problems limiting the performance of high intensity electron accelerators. A code devoted to the analysis of this type of problems should be fast and reliable: conditions that are usually hardly achieved at the same time. In the past, codes based on Lie algebraic techniques have been very efficient to treat transport problem in accelerators. The extension of these method to the non-linear case is ideally suited to treat CSR instability problems. We report on the development of a numerical code, based on the solution of the Vlasov equation, with the inclusion of non-linear contribution due to wake field effects. The proposed solution method exploits an algebraic technique, using exponential operators implemented numerically in C++. We show that the integration procedure is capable of reproducing the onset of an instability and effects associated with bunching mechanisms leading to the growth of the instability itself. In addition, parametric studies a...
Optimal control of dissipative nonlinear dynamical systems with triggers of coupled singularities
International Nuclear Information System (INIS)
Hedrih, K
2008-01-01
This paper analyses the controllability of motion of nonconservative nonlinear dynamical systems in which triggers of coupled singularities exist or appear. It is shown that the phase plane method is useful for the analysis of nonlinear dynamics of nonconservative systems with one degree of freedom of control strategies and also shows the way it can be used for controlling the relative motion in rheonomic systems having equivalent scleronomic conservative or nonconservative system For the system with one generalized coordinate described by nonlinear differential equation of nonlinear dynamics with trigger of coupled singularities, the functions of system potential energy and conservative force must satisfy some conditions defined by a Theorem on the existence of a trigger of coupled singularities and the separatrix in the form of 'an open a spiral form' of number eight. Task of the defined dynamical nonconservative system optimal control is: by using controlling force acting to the system, transfer initial state of the nonlinear dynamics of the system into the final state of the nonlinear dynamics in the minimal time for that optimal control task
Optimal control of dissipative nonlinear dynamical systems with triggers of coupled singularities
Stevanović Hedrih, K.
2008-02-01
This paper analyses the controllability of motion of nonconservative nonlinear dynamical systems in which triggers of coupled singularities exist or appear. It is shown that the phase plane method is useful for the analysis of nonlinear dynamics of nonconservative systems with one degree of freedom of control strategies and also shows the way it can be used for controlling the relative motion in rheonomic systems having equivalent scleronomic conservative or nonconservative system For the system with one generalized coordinate described by nonlinear differential equation of nonlinear dynamics with trigger of coupled singularities, the functions of system potential energy and conservative force must satisfy some conditions defined by a Theorem on the existence of a trigger of coupled singularities and the separatrix in the form of "an open a spiral form" of number eight. Task of the defined dynamical nonconservative system optimal control is: by using controlling force acting to the system, transfer initial state of the nonlinear dynamics of the system into the final state of the nonlinear dynamics in the minimal time for that optimal control task
Optimization of CW Fiber Lasers With Strong Nonlinear Cavity Dynamics
Shtyrina, O. V.; Efremov, S. A.; Yarutkina, I. A.; Skidin, A. S.; Fedoruk, M. P.
2018-04-01
In present work the equation for the saturated gain is derived from one-level gain equations describing the energy evolution inside the laser cavity. It is shown how to derive the parameters of the mathematical model from the experimental results. The numerically-estimated energy and spectrum of the signal are in good agreement with the experiment. Also, the optimization of the output energy is performed for a given set of model parameters.
Kim, Seongho; Li, Lang
2014-02-01
The statistical identifiability of nonlinear pharmacokinetic (PK) models with the Michaelis-Menten (MM) kinetic equation is considered using a global optimization approach, which is particle swarm optimization (PSO). If a model is statistically non-identifiable, the conventional derivative-based estimation approach is often terminated earlier without converging, due to the singularity. To circumvent this difficulty, we develop a derivative-free global optimization algorithm by combining PSO with a derivative-free local optimization algorithm to improve the rate of convergence of PSO. We further propose an efficient approach to not only checking the convergence of estimation but also detecting the identifiability of nonlinear PK models. PK simulation studies demonstrate that the convergence and identifiability of the PK model can be detected efficiently through the proposed approach. The proposed approach is then applied to clinical PK data along with a two-compartmental model. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.
Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping
2018-06-01
This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.
RCLED Optimization and Nonlinearity Compensation in a Polymer Optical Fiber DMT System
Directory of Open Access Journals (Sweden)
Pu Miao
2016-09-01
Full Text Available In polymer optical fiber (POF systems, the nonlinear transfer function of the resonant cavity light emitting diode (RCLED drastically degrades the communication performance. After investigating the characteristics of the RCLED nonlinear behavior, an improved digital look-up-table (LUT pre-distorter, based on an adaptive iterative algorithm, is proposed. Additionally, the system parameters, including the bias current, the average electrical power, the LUT size and the step factor are also jointly optimized to achieve a trade-off between the system linearity, reliability and the computational complexity. With the proposed methodology, both the operating point and efficiency of RCLED are enhanced. Moreover, in the practical 50 m POF communication system with the discrete multi-tone (DMT modulation, the bit error rate performance is improved by over 12 dB when RCLED is operating in the nonlinear region. Therefore, the proposed pre-distorter can both resist the nonlinearity and improve the operating point of RCLED.
Directory of Open Access Journals (Sweden)
B. Shank
2014-11-01
Full Text Available We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs connected to quasiparticle (qp traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.
Directory of Open Access Journals (Sweden)
Sie Long Kek
2015-01-01
Full Text Available A computational approach is proposed for solving the discrete time nonlinear stochastic optimal control problem. Our aim is to obtain the optimal output solution of the original optimal control problem through solving the simplified model-based optimal control problem iteratively. In our approach, the adjusted parameters are introduced into the model used such that the differences between the real system and the model used can be computed. Particularly, system optimization and parameter estimation are integrated interactively. On the other hand, the output is measured from the real plant and is fed back into the parameter estimation problem to establish a matching scheme. During the calculation procedure, the iterative solution is updated in order to approximate the true optimal solution of the original optimal control problem despite model-reality differences. For illustration, a wastewater treatment problem is studied and the results show the efficiency of the approach proposed.
Optimization of piezoelectric cantilever energy harvesters including non-linear effects
International Nuclear Information System (INIS)
Patel, R; McWilliam, S; Popov, A A
2014-01-01
This paper proposes a versatile non-linear model for predicting piezoelectric energy harvester performance. The presented model includes (i) material non-linearity, for both substrate and piezoelectric layers, and (ii) geometric non-linearity incorporated by assuming inextensibility and accurately representing beam curvature. The addition of a sub-model, which utilizes the transfer matrix method to predict eigenfrequencies and eigenvectors for segmented beams, allows for accurate optimization of piezoelectric layer coverage. A validation of the overall theoretical model is performed through experimental testing on both uniform and non-uniform samples manufactured in-house. For the harvester composition used in this work, the magnitude of material non-linearity exhibited by the piezoelectric layer is 35 times greater than that of the substrate layer. It is also observed that material non-linearity, responsible for reductions in resonant frequency with increases in base acceleration, is dominant over geometric non-linearity for standard piezoelectric harvesting devices. Finally, over the tested range, energy loss due to damping is found to increase in a quasi-linear fashion with base acceleration. During an optimization study on piezoelectric layer coverage, results from the developed model were compared with those from a linear model. Unbiased comparisons between harvesters were realized by using devices with identical natural frequencies—created by adjusting the device substrate thickness. Results from three studies, each with a different assumption on mechanical damping variations, are presented. Findings showed that, depending on damping variation, a non-linear model is essential for such optimization studies with each model predicting vastly differing optimum configurations. (paper)
PRONTO3D users` instructions: A transient dynamic code for nonlinear structural analysis
Energy Technology Data Exchange (ETDEWEB)
Attaway, S.W.; Mello, F.J.; Heinstein, M.W.; Swegle, J.W.; Ratner, J.A. [Sandia National Labs., Albuquerque, NM (United States); Zadoks, R.I. [Univ. of Texas, El Paso, TX (United States)
1998-06-01
This report provides an updated set of users` instructions for PRONTO3D. PRONTO3D is a three-dimensional, transient, solid dynamics code for analyzing large deformations of highly nonlinear materials subjected to extremely high strain rates. This Lagrangian finite element program uses an explicit time integration operator to integrate the equations of motion. Eight-node, uniform strain, hexahedral elements and four-node, quadrilateral, uniform strain shells are used in the finite element formulation. An adaptive time step control algorithm is used to improve stability and performance in plasticity problems. Hourglass distortions can be eliminated without disturbing the finite element solution using either the Flanagan-Belytschko hourglass control scheme or an assumed strain hourglass control scheme. All constitutive models in PRONTO3D are cast in an unrotated configuration defined using the rotation determined from the polar decomposition of the deformation gradient. A robust contact algorithm allows for the impact and interaction of deforming contact surfaces of quite general geometry. The Smooth Particle Hydrodynamics method has been embedded into PRONTO3D using the contact algorithm to couple it with the finite element method.
Santos, José; Monteagudo, Angel
2011-02-21
As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical genetic code was measured taking into account the harmful consequences resulting from point mutations leading to the replacement of one amino acid for another. There are two basic theories to measure the level of optimization: the statistical approach, which compares the canonical genetic code with many randomly generated alternative ones, and the engineering approach, which compares the canonical code with the best possible alternative. Here we used a genetic algorithm to search for better adapted hypothetical codes and as a method to guess the difficulty in finding such alternative codes, allowing to clearly situate the canonical code in the fitness landscape. This novel proposal of the use of evolutionary computing provides a new perspective in the open debate between the use of the statistical approach, which postulates that the genetic code conserves amino acid properties far better than expected from a random code, and the engineering approach, which tends to indicate that the canonical genetic code is still far from optimal. We used two models of hypothetical codes: one that reflects the known examples of codon reassignment and the model most used in the two approaches which reflects the current genetic code translation table. Although the standard code is far from a possible optimum considering both models, when the more realistic model of the codon reassignments was used, the evolutionary algorithm had more difficulty to overcome the efficiency of the canonical genetic code. Simulated evolution clearly reveals that the canonical genetic code is far from optimal regarding its optimization. Nevertheless, the efficiency of the canonical code increases when mistranslations are taken into account with the two models, as indicated by the fact that the best possible codes show the patterns of the
Directory of Open Access Journals (Sweden)
Monteagudo Ángel
2011-02-01
Full Text Available Abstract Background As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical genetic code was measured taking into account the harmful consequences resulting from point mutations leading to the replacement of one amino acid for another. There are two basic theories to measure the level of optimization: the statistical approach, which compares the canonical genetic code with many randomly generated alternative ones, and the engineering approach, which compares the canonical code with the best possible alternative. Results Here we used a genetic algorithm to search for better adapted hypothetical codes and as a method to guess the difficulty in finding such alternative codes, allowing to clearly situate the canonical code in the fitness landscape. This novel proposal of the use of evolutionary computing provides a new perspective in the open debate between the use of the statistical approach, which postulates that the genetic code conserves amino acid properties far better than expected from a random code, and the engineering approach, which tends to indicate that the canonical genetic code is still far from optimal. We used two models of hypothetical codes: one that reflects the known examples of codon reassignment and the model most used in the two approaches which reflects the current genetic code translation table. Although the standard code is far from a possible optimum considering both models, when the more realistic model of the codon reassignments was used, the evolutionary algorithm had more difficulty to overcome the efficiency of the canonical genetic code. Conclusions Simulated evolution clearly reveals that the canonical genetic code is far from optimal regarding its optimization. Nevertheless, the efficiency of the canonical code increases when mistranslations are taken into account with the two models, as indicated by the
Optimized Wavelength-Tuned Nonlinear Frequency Conversion Using a Liquid Crystal Clad Waveguide
Stephen, Mark A. (Inventor)
2018-01-01
An optimized wavelength-tuned nonlinear frequency conversion process using a liquid crystal clad waveguide. The process includes implanting ions on a top surface of a lithium niobate crystal to form an ion implanted lithium niobate layer. The process also includes utilizing a tunable refractive index of a liquid crystal to rapidly change an effective index of the lithium niobate crystal.
Nonlinear Thermodynamic Analysis and Optimization of a Carnot Engine Cycle
Directory of Open Access Journals (Sweden)
Michel Feidt
2016-06-01
Full Text Available As part of the efforts to unify the various branches of Irreversible Thermodynamics, the proposed work reconsiders the approach of the Carnot engine taking into account the finite physical dimensions (heat transfer conductances and the finite speed of the piston. The models introduce the irreversibility of the engine by two methods involving different constraints. The first method introduces the irreversibility by a so-called irreversibility ratio in the entropy balance applied to the cycle, while in the second method it is emphasized by the entropy generation rate. Various forms of heat transfer laws are analyzed, but most of the results are given for the case of the linear law. Also, individual cases are studied and reported in order to provide a simple analytical form of the results. The engine model developed allowed a formal optimization using the calculus of variations.
RAID-6 reed-solomon codes with asymptotically optimal arithmetic complexities
Lin, Sian-Jheng; Alloum, Amira; Al-Naffouri, Tareq Y.
2016-01-01
present a configuration of the factors of the second-parity formula, such that the arithmetic complexity can reach the optimal complexity bound when the code length approaches infinity. In the proposed approach, the intermediate data used for the first
Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai
2013-09-01
In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.
Yang, Xiong; Liu, Derong; Wang, Ding
2014-03-01
In this paper, an adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem of constrained-input continuous-time nonlinear systems in the presence of nonlinearities with unknown structures. Two different types of neural networks (NNs) are employed to approximate the Hamilton-Jacobi-Bellman equation. That is, an recurrent NN is constructed to identify the unknown dynamical system, and two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal cost, respectively. Based on this framework, the action NN and the critic NN are tuned simultaneously, without the requirement for the knowledge of system drift dynamics. Moreover, by using Lyapunov's direct method, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. To demonstrate the effectiveness of the present approach, simulation results are illustrated.
Biferale, L.; Mantovani, F.; Pivanti, M.; Pozzati, F.; Sbragaglia, M.; Schifano, S.F.; Toschi, F.; Tripiccione, R.
2011-01-01
We develop a Lattice Boltzmann code for computational fluid-dynamics and optimize it for massively parallel systems based on multi-core processors. Our code describes 2D multi-phase compressible flows. We analyze the performance bottlenecks that we find as we gradually expose a larger fraction of
PlayNCool: Opportunistic Network Coding for Local Optimization of Routing in Wireless Mesh Networks
DEFF Research Database (Denmark)
Pahlevani, Peyman; Roetter, Daniel Enrique Lucani; Pedersen, Morten Videbæk
2013-01-01
This paper introduces PlayNCool, an opportunistic protocol with local optimization based on network coding to increase the throughput of a wireless mesh network (WMN). PlayNCool aims to enhance current routing protocols by (i) allowing random linear network coding transmissions end-to-end, (ii) r...
International Nuclear Information System (INIS)
Huang, Xiaobiao; Safranek, James
2014-01-01
Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications
Energy Technology Data Exchange (ETDEWEB)
Huang, Xiaobiao, E-mail: xiahuang@slac.stanford.edu; Safranek, James
2014-09-01
Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.
Directory of Open Access Journals (Sweden)
Xiao-Fang Zhong
2017-12-01
Full Text Available The irregular wave disturbance attenuation problem for jacket-type offshore platforms involving the nonlinear characteristics is studied. The main contribution is that a digital-control-based approximation of optimal wave disturbances attenuation controller (AOWDAC is proposed based on iteration control theory, which consists of a feedback item of offshore state, a feedforward item of wave force and a nonlinear compensated component with iterative sequences. More specifically, by discussing the discrete model of nonlinear offshore platform subject to wave forces generated from the Joint North Sea Wave Project (JONSWAP wave spectrum and linearized wave theory, the original wave disturbances attenuation problem is formulated as the nonlinear two-point-boundary-value (TPBV problem. By introducing two vector sequences of system states and nonlinear compensated item, the solution of introduced nonlinear TPBV problem is obtained. Then, a numerical algorithm is designed to realize the feasibility of AOWDAC based on the deviation of performance index between the adjacent iteration processes. Finally, applied the proposed AOWDAC to a jacket-type offshore platform in Bohai Bay, the vibration amplitudes of the displacement and the velocity, and the required energy consumption can be reduced significantly.
International Nuclear Information System (INIS)
Frolov, A.M.
1986-01-01
The problem of exact variational calculations of few-particle systems in the exponential basis of the relative coordinates using nonlinear parameters is studied. The techniques of stepwise optimization and global chaos of nonlinear parameters are used to calculate the S and P states of homonuclear muonic molecules with an error of no more than +0.001 eV. The global-chaos technique also has proved to be successful in the case of the nuclear systems 3 H and 3 He
Narayanan, Vignesh; Jagannathan, Sarangapani
2017-06-08
This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.
Energy Technology Data Exchange (ETDEWEB)
Haverkort, J.W. [Centrum Wiskunde & Informatica, P.O. Box 94079, 1090 GB Amsterdam (Netherlands); Dutch Institute for Fundamental Energy Research, P.O. Box 6336, 5600 HH Eindhoven (Netherlands); Blank, H.J. de [Dutch Institute for Fundamental Energy Research, P.O. Box 6336, 5600 HH Eindhoven (Netherlands); Huysmans, G.T.A. [ITER Organization, Route de Vinon sur Verdon, 13115 Saint Paul Lez Durance (France); Pratt, J. [Dutch Institute for Fundamental Energy Research, P.O. Box 6336, 5600 HH Eindhoven (Netherlands); Koren, B., E-mail: b.koren@tue.nl [Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands)
2016-07-01
Numerical simulations form an indispensable tool to understand the behavior of a hot plasma that is created inside a tokamak for providing nuclear fusion energy. Various aspects of tokamak plasmas have been successfully studied through the reduced magnetohydrodynamic (MHD) model. The need for more complete modeling through the full MHD equations is addressed here. Our computational method is presented along with measures against possible problems regarding pollution, stability, and regularity. The problem of ensuring continuity of solutions in the center of a polar grid is addressed in the context of a finite element discretization of the full MHD equations. A rigorous and generally applicable solution is proposed here. Useful analytical test cases are devised to verify the correct implementation of the momentum and induction equation, the hyperdiffusive terms, and the accuracy with which highly anisotropic diffusion can be simulated. A striking observation is that highly anisotropic diffusion can be treated with the same order of accuracy as isotropic diffusion, even on non-aligned grids, as long as these grids are generated with sufficient care. This property is shown to be associated with our use of a magnetic vector potential to describe the magnetic field. Several well-known instabilities are simulated to demonstrate the capabilities of the new method. The linear growth rate of an internal kink mode and a tearing mode are benchmarked against the results of a linear MHD code. The evolution of a tearing mode and the resulting magnetic islands are simulated well into the nonlinear regime. The results are compared with predictions from the reduced MHD model. Finally, a simulation of a ballooning mode illustrates the possibility to use our method as an ideal MHD method without the need to add any physical dissipation.
Optimal quantum error correcting codes from absolutely maximally entangled states
Raissi, Zahra; Gogolin, Christian; Riera, Arnau; Acín, Antonio
2018-02-01
Absolutely maximally entangled (AME) states are pure multi-partite generalizations of the bipartite maximally entangled states with the property that all reduced states of at most half the system size are in the maximally mixed state. AME states are of interest for multipartite teleportation and quantum secret sharing and have recently found new applications in the context of high-energy physics in toy models realizing the AdS/CFT-correspondence. We work out in detail the connection between AME states of minimal support and classical maximum distance separable (MDS) error correcting codes and, in particular, provide explicit closed form expressions for AME states of n parties with local dimension \
International Nuclear Information System (INIS)
Heighway, E.A.
1980-07-01
A second order beam transport design code with parametric optimization is described. The code analyzes the transport of charged particle beams through a user defined magnet system. The magnet system parameters are varied (within user defined limits) until the properties of the transported beam and/or the system transport matrix match those properties requested by the user. The code uses matrix formalism to represent the transport elements and optimization is achieved using the variable metric method. Any constraints that can be expressed algebraically may be included by the user as part of his design. Instruction in the use of the program is given. (auth)
Yang, Xiong; He, Haibo
2018-05-26
In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying an array of optimal control laws of auxiliary subsystems. We also prove that this feedback controller ensures a specified cost function to achieve optimality. Then, under the framework of adaptive critic designs, we use critic networks to solve the Hamilton-Jacobi-Bellman equations associated with auxiliary subsystem optimal control laws. The critic network weights are tuned through the gradient descent method combined with an additional stabilizing term. By using the newly established weight tuning rules, we no longer need the initial admissible control condition. In addition, we demonstrate that all signals in the closed-loop auxiliary subsystems are stable in the sense of uniform ultimate boundedness by using classic Lyapunov techniques. Finally, we provide an interconnected nonlinear plant to validate the present control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Huang, C.-H.; Li, J.-X.
2006-01-01
A non-linear optimal control algorithm is examined in this study for the diffusion process of semiconductor materials. The purpose of this algorithm is to estimate an optimal control function such that the homogeneity of the concentration can be controlled during the diffusion process and the diffusion-induced stresses for the semiconductor materials can thus be reduced. The validation of this optimal control analysis utilizing the conjugate gradient method of minimization is analysed by using numerical experiments. Three different diffusion processing times are given and the corresponding optimal control functions are to be determined. Results show that the diffusion time can be shortened significantly by applying the optimal control function at the boundary and the homogeneity of the concentration is also guaranteed. This control function can be obtained within a very short CPU time on a Pentium III 600 MHz PC
Optimization of Thermal Object Nonlinear Control Systems by Energy Efficiency Criterion.
Velichkin, Vladimir A.; Zavyalov, Vladimir A.
2018-03-01
This article presents the results of thermal object functioning control analysis (heat exchanger, dryer, heat treatment chamber, etc.). The results were used to determine a mathematical model of the generalized thermal control object. The appropriate optimality criterion was chosen to make the control more energy-efficient. The mathematical programming task was formulated based on the chosen optimality criterion, control object mathematical model and technological constraints. The “maximum energy efficiency” criterion helped avoid solving a system of nonlinear differential equations and solve the formulated problem of mathematical programming in an analytical way. It should be noted that in the case under review the search for optimal control and optimal trajectory reduces to solving an algebraic system of equations. In addition, it is shown that the optimal trajectory does not depend on the dynamic characteristics of the control object.
Simplex sliding mode control for nonlinear uncertain systems via chaos optimization
International Nuclear Information System (INIS)
Lu, Zhao; Shieh, Leang-San; Chen, Guanrong; Coleman, Norman P.
2005-01-01
As an emerging effective approach to nonlinear robust control, simplex sliding mode control demonstrates some attractive features not possessed by the conventional sliding mode control method, from both theoretical and practical points of view. However, no systematic approach is currently available for computing the simplex control vectors in nonlinear sliding mode control. In this paper, chaos-based optimization is exploited so as to develop a systematic approach to seeking the simplex control vectors; particularly, the flexibility of simplex control is enhanced by making the simplex control vectors dependent on the Euclidean norm of the sliding vector rather than being constant, which result in both reduction of the chattering and speedup of the convergence. Computer simulation on a nonlinear uncertain system is given to illustrate the effectiveness of the proposed control method
State and parameter estimation in nonlinear systems as an optimal tracking problem
International Nuclear Information System (INIS)
Creveling, Daniel R.; Gill, Philip E.; Abarbanel, Henry D.I.
2008-01-01
In verifying and validating models of nonlinear processes it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, we present a framework for connecting a data signal with a model in a way that minimizes the required coupling yet allows the estimation of unknown parameters in the model. The need to evaluate unknown parameters in models of nonlinear physical, biophysical, and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. Our approach builds on existing work that uses synchronization as a tool for parameter estimation. We address some of the critical issues in that work and provide a practical framework for finding an accurate solution. In particular, we show the equivalence of this problem to that of tracking within an optimal control framework. This equivalence allows the application of powerful numerical methods that provide robust practical tools for model development and validation
Characterization and Optimization of LDPC Codes for the 2-User Gaussian Multiple Access Channel
Directory of Open Access Journals (Sweden)
Declercq David
2007-01-01
Full Text Available We address the problem of designing good LDPC codes for the Gaussian multiple access channel (MAC. The framework we choose is to design multiuser LDPC codes with joint belief propagation decoding on the joint graph of the 2-user case. Our main result compared to existing work is to express analytically EXIT functions of the multiuser decoder with two different approximations of the density evolution. This allows us to propose a very simple linear programming optimization for the complicated problem of LDPC code design with joint multiuser decoding. The stability condition for our case is derived and used in the optimization constraints. The codes that we obtain for the 2-user case are quite good for various rates, especially if we consider the very simple optimization procedure.
Optimizing fusion PIC code performance at scale on Cori Phase 2
Energy Technology Data Exchange (ETDEWEB)
Koskela, T. S.; Deslippe, J.
2017-07-23
In this paper we present the results of optimizing the performance of the gyrokinetic full-f fusion PIC code XGC1 on the Cori Phase Two Knights Landing system. The code has undergone substantial development to enable the use of vector instructions in its most expensive kernels within the NERSC Exascale Science Applications Program. We study the single-node performance of the code on an absolute scale using the roofline methodology to guide optimization efforts. We have obtained 2x speedups in single node performance due to enabling vectorization and performing memory layout optimizations. On multiple nodes, the code is shown to scale well up to 4000 nodes, near half the size of the machine. We discuss some communication bottlenecks that were identified and resolved during the work.
Development of a graphical interface computer code for reactor fuel reloading optimization
International Nuclear Information System (INIS)
Do Quang Binh; Nguyen Phuoc Lan; Bui Xuan Huy
2007-01-01
This report represents the results of the project performed in 2007. The aim of this project is to develop a graphical interface computer code that allows refueling engineers to design fuel reloading patterns for research reactor using simulated graphical model of reactor core. Besides, this code can perform refueling optimization calculations based on genetic algorithms as well as simulated annealing. The computer code was verified based on a sample problem, which relies on operational and experimental data of Dalat research reactor. This code can play a significant role in in-core fuel management practice at nuclear research reactor centers and in training. (author)
Product code optimization for determinate state LDPC decoding in robust image transmission.
Thomos, Nikolaos; Boulgouris, Nikolaos V; Strintzis, Michael G
2006-08-01
We propose a novel scheme for error-resilient image transmission. The proposed scheme employs a product coder consisting of low-density parity check (LDPC) codes and Reed-Solomon codes in order to deal effectively with bit errors. The efficiency of the proposed scheme is based on the exploitation of determinate symbols in Tanner graph decoding of LDPC codes and a novel product code optimization technique based on error estimation. Experimental evaluation demonstrates the superiority of the proposed system in comparison to recent state-of-the-art techniques for image transmission.
International Nuclear Information System (INIS)
Saviz, M R
2015-01-01
In this paper a nonlinear approach to studying the vibration characteristic of laminated composite plate with surface-bonded piezoelectric layer/patch is formulated, based on the Green Lagrange type of strain–displacements relations, by incorporating higher-order terms arising from nonlinear relations of kinematics into mathematical formulations. The equations of motion are obtained through the energy method, based on Lagrange equations and by using higher-order shear deformation theories with von Karman–type nonlinearities, so that transverse shear strains vanish at the top and bottom surfaces of the plate. An isoparametric finite element model is provided to model the nonlinear dynamics of the smart plate with piezoelectric layer/ patch. Different boundary conditions are investigated. Optimal locations of piezoelectric patches are found using a genetic algorithm to maximize spatial controllability/observability and considering the effect of residual modes to reduce spillover effect. Active attenuation of vibration of laminated composite plate is achieved through an optimal control law with inequality constraint, which is related to the maximum and minimum values of allowable voltage in the piezoelectric elements. To keep the voltages of actuator pairs in an allowable limit, the Pontryagin’s minimum principle is implemented in a system with multi-inequality constraint of control inputs. The results are compared with similar ones, proving the accuracy of the model especially for the structures undergoing large deformations. The convergence is studied and nonlinear frequencies are obtained for different thickness ratios. The structural coupling between plate and piezoelectric actuators is analyzed. Some examples with new features are presented, indicating that the piezo-patches significantly improve the damping characteristics of the plate for suppressing the geometrically nonlinear transient vibrations. (paper)
Quo vadis code optimization in high energy physics
International Nuclear Information System (INIS)
Jarp, S.
1994-01-01
Although performance tuning and optimization can be considered less critical than in the past, there are still many High Energy Physics (HEP) applications and application domains that can profit from such an undertaking. In CERN's CORE (Centrally Operated RISC Environment) where all major RISC vendors are present, this implies an understanding of the various computer architectures, instruction sets and performance analysis tools from each of these vendors. This paper discusses some initial observations after having evaluated the situation and makes some recommendations for further progress
International Nuclear Information System (INIS)
Xu Ruirui; Chen Tianlun; Gao Chengfeng
2006-01-01
Nonlinear time series prediction is studied by using an improved least squares support vector machine (LS-SVM) regression based on chaotic mutation evolutionary programming (CMEP) approach for parameter optimization. We analyze how the prediction error varies with different parameters (σ, γ) in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.
Stabilization of Hypersonic Boundary Layers by Linear and Nonlinear Optimal Perturbations
Paredes, Pedro; Choudhari, Meelan M.; Li, Fei
2017-01-01
The effect of stationary, finite-amplitude, linear and nonlinear optimal perturbations on the modal disturbance growth in a Mach 6 axisymmetric flow over a 7 deg. half-angle cone with 0:126 mm nose radius and 0:305 m length is investigated. The freestream parameters (M = 6, Re(exp 1) = 18 x 10(exp. 6) /m) are selected to match the flow conditions of a previous experiment in the VKI H3 hypersonic tunnel. Plane-marching parabolized stability equations are used in conjunction with a partial-differential equation based planar eigenvalue analysis to characterize the boundary layer instability in the presence of azimuthally periodic streaks. The streaks are observed to stabilize nominally planar Mack mode instabilities, although oblique Mack mode and first-mode disturbances are destabilized. Experimentally measured transition onset in the absence of any streaks correlates with an amplification factor of N = 6 for the planar Mack modes. For high enough streak amplitudes, the transition threshold of N = 6 is not reached by the Mack mode instabilities within the length of the cone; however, subharmonic first-mode instabilities, which are destabilized by the presence of the streaks, do reach N = 6 near the end of the cone. The highest stabilization is observed at streak amplitudes of approximately 20 percent of the freestream velocity. Because the use of initial disturbance profiles based on linear optimal growth theory may yield suboptimal control in the context of nonlinear streaks, the computational predictions are extended to nonlinear optimal growth theory. Results show that by using nonlinearly optimal perturbation leads to slightly enhanced stabilization of plane Mack mode disturbances as well as reduced destabilization of subharmonic first-mode disturbances.
Study on Rail Profile Optimization Based on the Nonlinear Relationship between Profile and Wear Rate
Directory of Open Access Journals (Sweden)
Jianxi Wang
2017-01-01
Full Text Available This paper proposes a rail profile optimization method that takes account of wear rate within design cycle so as to minimize rail wear at the curve in heavy haul railway and extend the service life of rail. Taking rail wear rate as the object function, the vertical coordinate of rail profile at range optimization as independent variable, and the geometric characteristics and grinding depth of rail profile as constraint conditions, the support vector machine regression theory was used to fit the nonlinear relationship between rail profile and its wear rate. Then, the profile optimization model was built. Based on the optimization principle of genetic algorithm, the profile optimization model was solved to achieve the optimal rail profile. A multibody dynamics model was used to check the dynamic performance of carriage running on optimal rail profile. The result showed that the average relative error of support vector machine regression model remained less than 10% after a number of training processes. The dynamic performance of carriage running on optimized rail profile met the requirements on safety index and stability. The wear rate of optimized profile was lower than that of standard profile by 5.8%; the allowable carrying gross weight increased by 12.7%.
Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks
DEFF Research Database (Denmark)
Heide, J; Zhang, Qi; Fitzek, F H P
2013-01-01
This work studies how to select optimal code parameters of Random Linear Network Coding (RLNC) in Wireless Sensor Networks (WSNs). With Rateless Deluge [1] the authors proposed to apply Network Coding (NC) for Over-the-Air Programming (OAP) in WSNs, and demonstrated that with NC a significant...... reduction in the number of transmitted packets can be achieved. However, NC introduces additional computations and potentially a non-negligible transmission overhead, both of which depend on the chosen coding parameters. Therefore it is necessary to consider the trade-off that these coding parameters...... present in order to obtain the lowest energy consumption per transmitted bit. This problem is analyzed and suitable coding parameters are determined for the popular Tmote Sky platform. Compared to the use of traditional RLNC, these parameters enable a reduction in the energy spent per bit which grows...
Energy Technology Data Exchange (ETDEWEB)
Kwak, Noh Sung; Lee, Jongsoo [Yonsei University, Seoul (Korea, Republic of)
2016-01-15
The present study aims to implement a new selection method and a novel crossover operation in a real-coded genetic algorithm. The proposed selection method facilitates the establishment of a successively evolved population by combining several subpopulations: an elitist subpopulation, an off-spring subpopulation and a mutated subpopulation. A probabilistic crossover is performed based on the measure of probabilistic distance between the individuals. The concept of ‘allowance’ is suggested to describe the level of variance in the crossover operation. A number of nonlinear/non-convex functions and engineering optimization problems are explored to verify the capacities of the proposed strategies. The results are compared with those obtained from other genetic and nature-inspired algorithms.
Demonstration of Automatically-Generated Adjoint Code for Use in Aerodynamic Shape Optimization
Green, Lawrence; Carle, Alan; Fagan, Mike
1999-01-01
Gradient-based optimization requires accurate derivatives of the objective function and constraints. These gradients may have previously been obtained by manual differentiation of analysis codes, symbolic manipulators, finite-difference approximations, or existing automatic differentiation (AD) tools such as ADIFOR (Automatic Differentiation in FORTRAN). Each of these methods has certain deficiencies, particularly when applied to complex, coupled analyses with many design variables. Recently, a new AD tool called ADJIFOR (Automatic Adjoint Generation in FORTRAN), based upon ADIFOR, was developed and demonstrated. Whereas ADIFOR implements forward-mode (direct) differentiation throughout an analysis program to obtain exact derivatives via the chain rule of calculus, ADJIFOR implements the reverse-mode counterpart of the chain rule to obtain exact adjoint form derivatives from FORTRAN code. Automatically-generated adjoint versions of the widely-used CFL3D computational fluid dynamics (CFD) code and an algebraic wing grid generation code were obtained with just a few hours processing time using the ADJIFOR tool. The codes were verified for accuracy and were shown to compute the exact gradient of the wing lift-to-drag ratio, with respect to any number of shape parameters, in about the time required for 7 to 20 function evaluations. The codes have now been executed on various computers with typical memory and disk space for problems with up to 129 x 65 x 33 grid points, and for hundreds to thousands of independent variables. These adjoint codes are now used in a gradient-based aerodynamic shape optimization problem for a swept, tapered wing. For each design iteration, the optimization package constructs an approximate, linear optimization problem, based upon the current objective function, constraints, and gradient values. The optimizer subroutines are called within a design loop employing the approximate linear problem until an optimum shape is found, the design loop
Application of the optimal homotopy asymptotic method to nonlinear Bingham fluid dampers
Directory of Open Access Journals (Sweden)
Marinca Vasile
2017-10-01
Full Text Available Dynamic response time is an important feature for determining the performance of magnetorheological (MR dampers in practical civil engineering applications. The objective of this paper is to show how to use the Optimal Homotopy Asymptotic Method (OHAM to give approximate analytical solutions of the nonlinear differential equation of a modified Bingham model with non-viscous exponential damping. Our procedure does not depend upon small parameters and provides us with a convenient way to optimally control the convergence of the approximate solutions. OHAM is very efficient in practice for ensuring very rapid convergence of the solution after only one iteration and with a small number of steps.
Application of the optimal homotopy asymptotic method to nonlinear Bingham fluid dampers
Marinca, Vasile; Ene, Remus-Daniel; Bereteu, Liviu
2017-10-01
Dynamic response time is an important feature for determining the performance of magnetorheological (MR) dampers in practical civil engineering applications. The objective of this paper is to show how to use the Optimal Homotopy Asymptotic Method (OHAM) to give approximate analytical solutions of the nonlinear differential equation of a modified Bingham model with non-viscous exponential damping. Our procedure does not depend upon small parameters and provides us with a convenient way to optimally control the convergence of the approximate solutions. OHAM is very efficient in practice for ensuring very rapid convergence of the solution after only one iteration and with a small number of steps.
The optimization of the nonlinear parameters in the transcorrelated method: the hydrogen molecule
International Nuclear Information System (INIS)
Huggett, J.P.; Armour, E.A.G.
1976-01-01
The nonlinear parameters in a transcorrelated calculation of the groundstate energy and wavefunction of the hydrogen molecule are optimized using the method of Boys and Handy (Proc. R. Soc. A.; 309:195 and 209, 310:43 and 63, 311:309 (1969)). The method gives quite accurate results in all cases and in some cases the results are highly accurate. This is the first time the method has been applied to the optimization of a term in the correlation function which depends linearly on the interelectronic distance. (author)
Optimal Control of Nonlinear Hydraulic Networks in the Presence of Disturbance
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Leth, John-Josef; Kallesøe, Carsten
2014-01-01
Water leakage is an important component of water loss. Many methods have emerged from urban water supply systems for leakage control, but it still remains a challenge in many countries. Pressure management is an effective way to reduce the leakage in a system. It can also reduce the power...... consumption. To this end, an optimal control strategy is proposed in this paper. In the water supply system model, the hydraulic resistance of the valve is estimated by the real data from a water supply system and it is considered to be a disturbance. The method which is used to solve the nonlinear optimal...
Efficacy of Code Optimization on Cache-Based Processors
VanderWijngaart, Rob F.; Saphir, William C.; Chancellor, Marisa K. (Technical Monitor)
1997-01-01
In this paper a number of techniques for improving the cache performance of a representative piece of numerical software is presented. Target machines are popular processors from several vendors: MIPS R5000 (SGI Indy), MIPS R8000 (SGI PowerChallenge), MIPS R10000 (SGI Origin), DEC Alpha EV4 + EV5 (Cray T3D & T3E), IBM RS6000 (SP Wide-node), Intel PentiumPro (Ames' Whitney), Sun UltraSparc (NERSC's NOW). The optimizations all attempt to increase the locality of memory accesses. But they meet with rather varied and often counterintuitive success on the different computing platforms. We conclude that it may be genuinely impossible to obtain portable performance on the current generation of cache-based machines. At the least, it appears that the performance of modern commodity processors cannot be described with parameters defining the cache alone.
Athaudage, Chandranath R. N.; Bradley, Alan B.; Lech, Margaret
2003-12-01
A dynamic programming-based optimization strategy for a temporal decomposition (TD) model of speech and its application to low-rate speech coding in storage and broadcasting is presented. In previous work with the spectral stability-based event localizing (SBEL) TD algorithm, the event localization was performed based on a spectral stability criterion. Although this approach gave reasonably good results, there was no assurance on the optimality of the event locations. In the present work, we have optimized the event localizing task using a dynamic programming-based optimization strategy. Simulation results show that an improved TD model accuracy can be achieved. A methodology of incorporating the optimized TD algorithm within the standard MELP speech coder for the efficient compression of speech spectral information is also presented. The performance evaluation results revealed that the proposed speech coding scheme achieves 50%-60% compression of speech spectral information with negligible degradation in the decoded speech quality.
Acoustic wave focusing in complex media using Nonlinear Time Reversal coded signal processing
Czech Academy of Sciences Publication Activity Database
Dos Santos, S.; Dvořáková, Zuzana; Lints, M.; Kůs, V.; Salupere, A.; Převorovský, Zdeněk
2014-01-01
Roč. 19, č. 12 (2014) ISSN 1435-4934. [European Conference on Non-Destructive Testing (ECNDT 2014) /11./. Praha, 06.10.2014-10.10.2014] Institutional support: RVO:61388998 Keywords : ultrasonic testing (UT) * signal processing * TR- NEWS * nonlinear time reversal * NDT * nonlinear acoustics Subject RIV: BI - Acoustics http://www.ndt.net/events/ECNDT2014/app/content/Slides/590_DosSantos_Rev1.pdf
Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang
2017-11-01
The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.
Game-Theoretic Rate-Distortion-Complexity Optimization of High Efficiency Video Coding
DEFF Research Database (Denmark)
Ukhanova, Ann; Milani, Simone; Forchhammer, Søren
2013-01-01
profiles in order to tailor the computational load to the different hardware and power-supply resources of devices. In this work, we focus on optimizing the quantization parameter and partition depth in HEVC via a game-theoretic approach. The proposed rate control strategy alone provides 0.2 dB improvement......This paper presents an algorithm for rate-distortioncomplexity optimization for the emerging High Efficiency Video Coding (HEVC) standard, whose high computational requirements urge the need for low-complexity optimization algorithms. Optimization approaches need to specify different complexity...
Power Optimization of Wireless Media Systems With Space-Time Block Codes
Yousefi'zadeh, Homayoun; Jafarkhani, Hamid; Moshfeghi, Mehran
2004-01-01
We present analytical and numerical solutions to the problem of power control in wireless media systems with multiple antennas. We formulate a set of optimization problems aimed at minimizing total power consumption of wireless media systems subject to a given level of QoS and an available bit rate. Our formulation takes in to consideration the power consumption related to source coding, channel coding, and transmission of multiple-transmit antennas. In our study, we consider Gauss-Markov and...
Gottlieb, Sigal
2015-04-10
High order spatial discretizations with monotonicity properties are often desirable for the solution of hyperbolic PDEs. These methods can advantageously be coupled with high order strong stability preserving time discretizations. The search for high order strong stability time-stepping methods with large allowable strong stability coefficient has been an active area of research over the last two decades. This research has shown that explicit SSP Runge-Kutta methods exist only up to fourth order. However, if we restrict ourselves to solving only linear autonomous problems, the order conditions simplify and this order barrier is lifted: explicit SSP Runge-Kutta methods of any linear order exist. These methods reduce to second order when applied to nonlinear problems. In the current work we aim to find explicit SSP Runge-Kutta methods with large allowable time-step, that feature high linear order and simultaneously have the optimal fourth order nonlinear order. These methods have strong stability coefficients that approach those of the linear methods as the number of stages and the linear order is increased. This work shows that when a high linear order method is desired, it may still be worthwhile to use methods with higher nonlinear order.
Directory of Open Access Journals (Sweden)
Patrick Piprek
2018-02-01
Full Text Available This paper presents an approach to model a ski jumper as a multi-body system for an optimal control application. The modeling is based on the constrained Newton-Euler-Equations. Within this paper the complete multi-body modeling methodology as well as the musculoskeletal modeling is considered. For the musculoskeletal modeling and its incorporation in the optimization model, we choose a nonlinear dynamic inversion control approach. This approach uses the muscle models as nonlinear reference models and links them to the ski jumper movement by a control law. This strategy yields a linearized input-output behavior, which makes the optimal control problem easier to solve. The resulting model of the ski jumper can then be used for trajectory optimization whose results are compared to literature jumps. Ultimately, this enables the jumper to get a very detailed feedback of the flight. To achieve the maximal jump length, exact positioning of his body with respect to the air can be displayed.
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.
DEFF Research Database (Denmark)
Rahman, Imadur Mohamed; Marchetti, Nicola; Fitzek, Frank
2005-01-01
(SIC) receiver where the detection is done on subcarrier by sub-carrier basis based on both Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) nulling criterion for the system. In terms of Frame Error Rate (FER), MMSE based SIC receiver performs better than all other receivers compared......In this work, we have analyzed a joint spatial diversity and multiplexing transmission structure for MIMO-OFDM system, where Orthogonal Space-Frequency Block Coding (OSFBC) is used across all spatial multiplexing branches. We have derived a BLAST-like non-linear Successive Interference Cancellation...... in this paper. We have found that a linear two-stage receiver for the proposed system [1] performs very close to the non-linear receiver studied in this work. Finally, we compared the system performance in spatially correlated scenario. It is found that higher amount of spatial correlation at the transmitter...
Differentially Encoded LDPC Codes—Part II: General Case and Code Optimization
Directory of Open Access Journals (Sweden)
Li (Tiffany Jing
2008-01-01
Full Text Available This two-part series of papers studies the theory and practice of differentially encoded low-density parity-check (DE-LDPC codes, especially in the context of noncoherent detection. Part I showed that a special class of DE-LDPC codes, product accumulate codes, perform very well with both coherent and noncoherent detections. The analysis here reveals that a conventional LDPC code, however, is not fitful for differential coding and does not, in general, deliver a desirable performance when detected noncoherently. Through extrinsic information transfer (EXIT analysis and a modified "convergence-constraint" density evolution (DE method developed here, we provide a characterization of the type of LDPC degree profiles that work in harmony with differential detection (or a recursive inner code in general, and demonstrate how to optimize these LDPC codes. The convergence-constraint method provides a useful extension to the conventional "threshold-constraint" method, and can match an outer LDPC code to any given inner code with the imperfectness of the inner decoder taken into consideration.
Spectral-Amplitude-Coded OCDMA Optimized for a Realistic FBG Frequency Response
Penon, Julien; El-Sahn, Ziad A.; Rusch, Leslie A.; Larochelle, Sophie
2007-05-01
We develop a methodology for numerical optimization of fiber Bragg grating frequency response to maximize the achievable capacity of a spectral-amplitude-coded optical code-division multiple-access (SAC-OCDMA) system. The optimal encoders are realized, and we experimentally demonstrate an incoherent SAC-OCDMA system with seven simultaneous users. We report a bit error rate (BER) of 2.7 x 10-8 at 622 Mb/s for a fully loaded network (seven users) using a 9.6-nm optical band. We achieve error-free transmission (BER < 1 x 10-9) for up to five simultaneous users.
Robust Optimization Using Supremum of the Objective Function for Nonlinear Programming Problems
International Nuclear Information System (INIS)
Lee, Se Jung; Park, Gyung Jin
2014-01-01
In the robust optimization field, the robustness of the objective function emphasizes an insensitive design. In general, the robustness of the objective function can be achieved by reducing the change of the objective function with respect to the variation of the design variables and parameters. However, in conventional methods, when an insensitive design is emphasized, the performance of the objective function can be deteriorated. Besides, if the numbers of the design variables are increased, the numerical cost is quite high in robust optimization for nonlinear programming problems. In this research, the robustness index for the objective function and a process of robust optimization are proposed. Moreover, a method using the supremum of linearized functions is also proposed to reduce the computational cost. Mathematical examples are solved for the verification of the proposed method and the results are compared with those from the conventional methods. The proposed approach improves the performance of the objective function and its efficiency
Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm
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V. Rajinikanth
2012-01-01
Full Text Available An enhanced bacteria foraging optimization (EBFO algorithm-based Proportional + integral + derivative (PID controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.
International Nuclear Information System (INIS)
Tian Shunqiang; Liu Guimin; Hou Jie; Chen Guangling; Wan Chenglan; Li Haohu
2009-01-01
In this paper, we present a rule to improve the nonlinear solution with frequency map analysis (FMA), and without frequently revisiting the optimization algorithm. Two aspects of FMA are emphasized. The first one is the tune shift with amplitude, which can be used to improve the solution of harmonic sextupoles, and thus obtain a large dynamic aperture. The second one is the tune diffusion rate, which can be used to select a quiet tune. Application of these ideas is carried out in the storage ring of the Shanghai Synchrotron Radiation Facility (SSRF), and the detailed processes, as well as better solutions, are presented in this paper. Discussions about the nonlinear behaviors of off-momentum particles are also presented. (authors)
Esfandiari, Kasra; Abdollahi, Farzaneh; Talebi, Heidar Ali
2017-09-01
In this paper, an identifier-critic structure is introduced to find an online near-optimal controller for continuous-time nonaffine nonlinear systems having saturated control signal. By employing two Neural Networks (NNs), the solution of Hamilton-Jacobi-Bellman (HJB) equation associated with the cost function is derived without requiring a priori knowledge about system dynamics. Weights of the identifier and critic NNs are tuned online and simultaneously such that unknown terms are approximated accurately and the control signal is kept between the saturation bounds. The convergence of NNs' weights, identification error, and system states is guaranteed using Lyapunov's direct method. Finally, simulation results are performed on two nonlinear systems to confirm the effectiveness of the proposed control strategy. Copyright © 2017 Elsevier Ltd. All rights reserved.
Todo, Y.; Berk, H. L.; Breizman, B. N.
2012-03-01
A hybrid simulation code for nonlinear magnetohydrodynamics (MHD) and energetic-particle dynamics has been extended to simulate recurrent bursts of Alfvén eigenmodes by implementing the energetic-particle source, collisions and losses. The Alfvén eigenmode bursts with synchronization of multiple modes and beam ion losses at each burst are successfully simulated with nonlinear MHD effects for the physics condition similar to a reduced simulation for a TFTR experiment (Wong et al 1991 Phys. Rev. Lett. 66 1874, Todo et al 2003 Phys. Plasmas 10 2888). It is demonstrated with a comparison between nonlinear MHD and linear MHD simulation results that the nonlinear MHD effects significantly reduce both the saturation amplitude of the Alfvén eigenmodes and the beam ion losses. Two types of time evolution are found depending on the MHD dissipation coefficients, namely viscosity, resistivity and diffusivity. The Alfvén eigenmode bursts take place for higher dissipation coefficients with roughly 10% drop in stored beam energy and the maximum amplitude of the dominant magnetic fluctuation harmonic δBm/n/B ~ 5 × 10-3 at the mode peak location inside the plasma. Quadratic dependence of beam ion loss rate on magnetic fluctuation amplitude is found for the bursting evolution in the nonlinear MHD simulation. For lower dissipation coefficients, the amplitude of the Alfvén eigenmodes is at steady levels δBm/n/B ~ 2 × 10-3 and the beam ion losses take place continuously. The beam ion pressure profiles are similar among the different dissipation coefficients, and the stored beam energy is higher for higher dissipation coefficients.
Nuclear-thermal-coupled optimization code for the fusion breeding blanket conceptual design
International Nuclear Information System (INIS)
Li, Jia; Jiang, Kecheng; Zhang, Xiaokang; Nie, Xingchen; Zhu, Qinjun; Liu, Songlin
2016-01-01
Highlights: • A nuclear-thermal-coupled predesign code has been developed for optimizing the radial build arrangement of fusion breeding blanket. • Coupling module aims at speeding up the efficiency of design progress by coupling the neutronics calculation code with the thermal-hydraulic analysis code. • Radial build optimization algorithm aims at optimal arrangement of breeding blanket considering one or multiple specified objectives subject to the design criteria such as material temperature limit and available TBR. - Abstract: Fusion breeding blanket as one of the key in-vessel components performs the functions of breeding the tritium, removing the nuclear heat and heat flux from plasma chamber as well as acting as part of shielding system. The radial build design which determines the arrangement of function zones and material properties on the radial direction is the basis of the detailed design of fusion breeding blanket. For facilitating the radial build design, this study aims for developing a pre-design code to optimize the radial build of blanket with considering the performance of nuclear and thermal-hydraulic simultaneously. Two main features of this code are: (1) Coupling of the neutronics analysis with the thermal-hydraulic analysis to speed up the analysis progress; (2) preliminary optimization algorithm using one or multiple specified objectives subject to the design criteria in the form of constrains imposed on design variables and performance parameters within the possible engineering ranges. This pre-design code has been applied to the conceptual design of water-cooled ceramic breeding blanket in project of China fusion engineering testing reactor (CFETR).
Nuclear-thermal-coupled optimization code for the fusion breeding blanket conceptual design
Energy Technology Data Exchange (ETDEWEB)
Li, Jia, E-mail: lijia@ustc.edu.cn [School of Nuclear Science and Technology, University of Science and Technology of China, Hefei 230027, Anhui (China); Jiang, Kecheng; Zhang, Xiaokang [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031, Anhui (China); Nie, Xingchen [School of Nuclear Science and Technology, University of Science and Technology of China, Hefei 230027, Anhui (China); Zhu, Qinjun; Liu, Songlin [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031, Anhui (China)
2016-12-15
Highlights: • A nuclear-thermal-coupled predesign code has been developed for optimizing the radial build arrangement of fusion breeding blanket. • Coupling module aims at speeding up the efficiency of design progress by coupling the neutronics calculation code with the thermal-hydraulic analysis code. • Radial build optimization algorithm aims at optimal arrangement of breeding blanket considering one or multiple specified objectives subject to the design criteria such as material temperature limit and available TBR. - Abstract: Fusion breeding blanket as one of the key in-vessel components performs the functions of breeding the tritium, removing the nuclear heat and heat flux from plasma chamber as well as acting as part of shielding system. The radial build design which determines the arrangement of function zones and material properties on the radial direction is the basis of the detailed design of fusion breeding blanket. For facilitating the radial build design, this study aims for developing a pre-design code to optimize the radial build of blanket with considering the performance of nuclear and thermal-hydraulic simultaneously. Two main features of this code are: (1) Coupling of the neutronics analysis with the thermal-hydraulic analysis to speed up the analysis progress; (2) preliminary optimization algorithm using one or multiple specified objectives subject to the design criteria in the form of constrains imposed on design variables and performance parameters within the possible engineering ranges. This pre-design code has been applied to the conceptual design of water-cooled ceramic breeding blanket in project of China fusion engineering testing reactor (CFETR).
Pasekov, V P
2013-03-01
The paper considers the problems in the adaptive evolution of life-history traits for individuals in the nonlinear Leslie model of age-structured population. The possibility to predict adaptation results as the values of organism's traits (properties) that provide for the maximum of a certain function of traits (optimization criterion) is studied. An ideal criterion of this type is Darwinian fitness as a characteristic of success of an individual's life history. Criticism of the optimization approach is associated with the fact that it does not take into account the changes in the environmental conditions (in a broad sense) caused by evolution, thereby leading to losses in the adequacy of the criterion. In addition, the justification for this criterion under stationary conditions is not usually rigorous. It has been suggested to overcome these objections in terms of the adaptive dynamics theory using the concept of invasive fitness. The reasons are given that favor the application of the average number of offspring for an individual, R(L), as an optimization criterion in the nonlinear Leslie model. According to the theory of quantitative genetics, the selection for fertility (that is, for a set of correlated quantitative traits determined by both multiple loci and the environment) leads to an increase in R(L). In terms of adaptive dynamics, the maximum R(L) corresponds to the evolutionary stability and, in certain cases, convergent stability of the values for traits. The search for evolutionarily stable values on the background of limited resources for reproduction is a problem of linear programming.
The Effect of Slot-Code Optimization in Warehouse Order Picking
Directory of Open Access Journals (Sweden)
Andrea Fumi
2013-07-01
most appropriate material handling resource configuration. Building on previous work on the effect of slot-code optimization on travel times in single/dual command cycles, the authors broaden the scope to include the most general picking case, thus widening the range of applicability and realising former suggestions for future research.
Alghamdi, Amal Mohammed
2012-04-01
Clawpack, a conservation laws package implemented in Fortran, and its Python-based version, PyClaw, are existing tools providing nonlinear wave propagation solvers that use state of the art finite volume methods. Simulations using those tools can have extensive computational requirements to provide accurate results. Therefore, a number of tools, such as BearClaw and MPIClaw, have been developed based on Clawpack to achieve significant speedup by exploiting parallel architectures. However, none of them has been shown to scale on a large number of cores. Furthermore, these tools, implemented in Fortran, achieve parallelization by inserting parallelization logic and MPI standard routines throughout the serial code in a non modular manner. Our contribution in this thesis research is three-fold. First, we demonstrate an advantageous use case of Python in implementing easy-to-use modular extensible scalable scientific software tools by developing an implementation of a parallelization framework, PetClaw, for PyClaw using the well-known Portable Extensible Toolkit for Scientific Computation, PETSc, through its Python wrapper petsc4py. Second, we demonstrate the possibility of getting acceptable Python code performance when compared to Fortran performance after introducing a number of serial optimizations to the Python code including integrating Clawpack Fortran kernels into PyClaw for low-level computationally intensive parts of the code. As a result of those optimizations, the Python overhead in PetClaw for a shallow water application is only 12 percent when compared to the corresponding Fortran Clawpack application. Third, we provide a demonstration of PetClaw scalability on up to the entirety of Shaheen; a 16-rack Blue Gene/P IBM supercomputer that comprises 65,536 cores and located at King Abdullah University of Science and Technology (KAUST). The PetClaw solver achieved above 0.98 weak scaling efficiency for an Euler application on the whole machine excluding the
RAID-6 reed-solomon codes with asymptotically optimal arithmetic complexities
Lin, Sian-Jheng
2016-12-24
In computer storage, RAID 6 is a level of RAID that can tolerate two failed drives. When RAID-6 is implemented by Reed-Solomon (RS) codes, the penalty of the writing performance is on the field multiplications in the second parity. In this paper, we present a configuration of the factors of the second-parity formula, such that the arithmetic complexity can reach the optimal complexity bound when the code length approaches infinity. In the proposed approach, the intermediate data used for the first parity is also utilized to calculate the second parity. To the best of our knowledge, this is the first approach supporting the RAID-6 RS codes to approach the optimal arithmetic complexity.
An Optimal Homotopy Asymptotic Approach Applied to Nonlinear MHD Jeffery-Hamel Flow
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Vasile Marinca
2011-01-01
Full Text Available A simple and effective procedure is employed to propose a new analytic approximate solution for nonlinear MHD Jeffery-Hamel flow. This technique called the Optimal Homotopy Asymptotic Method (OHAM does not depend upon any small/large parameters and provides us with a convenient way to control the convergence of the solution. The examples given in this paper lead to the conclusion that the accuracy of the obtained results is growing along with increasing the number of constants in the auxiliary function, which are determined using a computer technique. The results obtained through the proposed method are in very good agreement with the numerical results.
Global stability, periodic solutions, and optimal control in a nonlinear differential delay model
Directory of Open Access Journals (Sweden)
Anatoli F. Ivanov
2010-09-01
Full Text Available A nonlinear differential equation with delay serving as a mathematical model of several applied problems is considered. Sufficient conditions for the global asymptotic stability and for the existence of periodic solutions are given. Two particular applications are treated in detail. The first one is a blood cell production model by Mackey, for which new periodicity criteria are derived. The second application is a modified economic model with delay due to Ramsey. An optimization problem for a maximal consumption is stated and solved for the latter.
DEFF Research Database (Denmark)
Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2015-01-01
In this paper, we compare the performance of an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) to a linear tracking Model Predictive Controller (MPC) for a spray drying plant. We find in this simulation study, that the economic performance of the two controllers are almost...... equal. We evaluate the economic performance with an industrially recorded disturbance scenario, where unmeasured disturbances and model mismatch are present. The state of the spray dryer, used in the E-NMPC and MPC, is estimated using Kalman Filters with noise covariances estimated by a maximum...
Krasilenko, Vladimir G.; Nikolsky, Alexander I.; Lazarev, Alexander A.; Lazareva, Maria V.
2008-03-01
In the paper the actuality of neurophysiologically motivated neuron arrays with flexibly programmable functions and operations with possibility to select required accuracy and type of nonlinear transformation and learning are shown. We consider neurons design and simulation results of multichannel spatio-time algebraic accumulation - integration of optical signals. Advantages for nonlinear transformation and summation - integration are shown. The offered circuits are simple and can have intellectual properties such as learning and adaptation. The integrator-neuron is based on CMOS current mirrors and comparators. The performance: consumable power - 100...500 μW, signal period- 0.1...1ms, input optical signals power - 0.2...20 μW time delays - less 1μs, the number of optical signals - 2...10, integration time - 10...100 of signal periods, accuracy or integration error - about 1%. Various modifications of the neuron-integrators with improved performance and for different applications are considered in the paper.
Afifi, Ahmed; Nakaguchi, Toshiya; Tsumura, Norimichi
2010-03-01
In many medical applications, the automatic segmentation of deformable organs from medical images is indispensable and its accuracy is of a special interest. However, the automatic segmentation of these organs is a challenging task according to its complex shape. Moreover, the medical images usually have noise, clutter, or occlusion and considering the image information only often leads to meager image segmentation. In this paper, we propose a fully automated technique for the segmentation of deformable organs from medical images. In this technique, the segmentation is performed by fitting a nonlinear shape model with pre-segmented images. The kernel principle component analysis (KPCA) is utilized to capture the complex organs deformation and to construct the nonlinear shape model. The presegmentation is carried out by labeling each pixel according to its high level texture features extracted using the overcomplete wavelet packet decomposition. Furthermore, to guarantee an accurate fitting between the nonlinear model and the pre-segmented images, the particle swarm optimization (PSO) algorithm is employed to adapt the model parameters for the novel images. In this paper, we demonstrate the competence of proposed technique by implementing it to the liver segmentation from computed tomography (CT) scans of different patients.
Linear and nonlinear market correlations: Characterizing financial crises and portfolio optimization
Haluszczynski, Alexander; Laut, Ingo; Modest, Heike; Räth, Christoph
2017-12-01
Pearson correlation and mutual information-based complex networks of the day-to-day returns of U.S. S&P500 stocks between 1985 and 2015 have been constructed to investigate the mutual dependencies of the stocks and their nature. We show that both networks detect qualitative differences especially during (recent) turbulent market periods, thus indicating strongly fluctuating interconnections between the stocks of different companies in changing economic environments. A measure for the strength of nonlinear dependencies is derived using surrogate data and leads to interesting observations during periods of financial market crises. In contrast to the expectation that dependencies reduce mainly to linear correlations during crises, we show that (at least in the 2008 crisis) nonlinear effects are significantly increasing. It turns out that the concept of centrality within a network could potentially be used as some kind of an early warning indicator for abnormal market behavior as we demonstrate with the example of the 2008 subprime mortgage crisis. Finally, we apply a Markowitz mean variance portfolio optimization and integrate the measure of nonlinear dependencies to scale the investment exposure. This leads to significant outperformance as compared to a fully invested portfolio.
Optimizing optical nonlinearities in GaInAs/AlInAs quantum cascade lasers
Directory of Open Access Journals (Sweden)
Gajić Aleksandra D.
2014-01-01
Full Text Available Regardless of the huge advances made in the design and fabrication of mid-infrared and terahertz quantum cascade lasers, success in accessing the ~3-4 mm region of the electromagnetic spectrum has remained limited. This fact has brought about the need to exploit resonant intersubband transitions as powerful nonlinear oscillators, consequently enabling the occurrence of large nonlinear optical susceptibilities as a means of reaching desired wavelengths. In this work, we present a computational model developed for the optimization of second-order optical nonlinearities in In0.53Ga0.47As/Al0.48In0.52As quantum cascade laser structures based on the implementation of the Genetic algorithm. The carrier transport and the power output of the structure were calculated by self-consistent solutions to the system of rate equations for carriers and photons. Both stimulated and simultaneous double-photon absorption processes occurring between the second harmonic generation-relevant levels are incorporated into rate equations and the material-dependent effective mass and band non-parabolicity are taken into account, as well. The developed method is quite general and can be applied to any higher order effect which requires the inclusion of the photon density equation. [Projekat Ministarstva nauke Republike Srbije, br. III 45010
Economic Optimization of Spray Dryer Operation using Nonlinear Model Predictive Control
DEFF Research Database (Denmark)
Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2014-01-01
In this paper we investigate an economically optimizing Nonlinear Model Predictive Control (E-NMPC) for a spray drying process. By simulation we evaluate the economic potential of this E-NMPC compared to a conventional PID based control strategy. Spray drying is the preferred process to reduce...... the water content for many liquid foodstuffs and produces a free flowing powder. The main challenge in controlling the spray drying process is to meet the residual moisture specifications and avoid that the powder sticks to the chamber walls of the spray dryer. We present a model for a spray dryer that has...... been validated on experimental data from a pilot plant. We use this model for simulation as well as for prediction in the E-NMPC. The E-NMPC is designed with hard input constraints and soft output constraints. The open-loop optimal control problem in the E-NMPC is solved using the single...
Directory of Open Access Journals (Sweden)
Bingyong Yan
2015-01-01
Full Text Available A robust fault detection scheme for a class of nonlinear systems with uncertainty is proposed. The proposed approach utilizes robust control theory and parameter optimization algorithm to design the gain matrix of fault tracking approximator (FTA for fault detection. The gain matrix of FTA is designed to minimize the effects of system uncertainty on residual signals while maximizing the effects of system faults on residual signals. The design of the gain matrix of FTA takes into account the robustness of residual signals to system uncertainty and sensitivity of residual signals to system faults simultaneously, which leads to a multiobjective optimization problem. Then, the detectability of system faults is rigorously analyzed by investigating the threshold of residual signals. Finally, simulation results are provided to show the validity and applicability of the proposed approach.
DEFF Research Database (Denmark)
Petersen, Lars Norbert; Jørgensen, John Bagterp; Rawlings, James B.
2015-01-01
In this paper, we develop an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) for a complete spray drying plant with multiple stages. In the E-NMPC the initial state is estimated by an extended Kalman Filter (EKF) with noise covariances estimated by an autocovariance least...... squares method (ALS). We present a model for the spray drying plant and use this model for simulation as well as for prediction in the E-NMPC. The open-loop optimal control problem in the E-NMPC is solved using the single-shooting method combined with a quasi-Newton Sequential Quadratic programming (SQP......) algorithm and the adjoint method for computation of gradients. We evaluate the economic performance when unmeasured disturbances are present. By simulation, we demonstrate that the E-NMPC improves the profit of spray drying by 17% compared to conventional PI control....
Robust non-gradient C subroutines for non-linear optimization
DEFF Research Database (Denmark)
Brock, Pernille; Madsen, Kaj; Nielsen, Hans Bruun
2004-01-01
This report presents a package of robust and easy-to-use C subroutines for solving unconstrained and constrained non-linear optimization problems, where gradient information is not required. The intention is that the routines should use the currently best algorithms available. All routines have...... subroutines are obtained by changing 0 to 1. The present report is a new and updated version of a previous report NI-91-04 with the title Non-gradient c Subroutines for Non- Linear Optimization, [16]. Both the previous and the present report describe a collection of subroutines, which have been translated...... from Fortran to C. The reason for writing the present report is that some of the C subroutines have been replaced by more e ective and robust versions translated from the original Fortran subroutines to C by the Bandler Group, see [1]. Also the test examples have been modified to some extent...
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Yutong Liu
2012-01-01
Full Text Available Purpose. To develop a technique to automate landmark selection for point-based interpolating transformations for nonlinear medical image registration. Materials and Methods. Interpolating transformations were calculated from homologous point landmarks on the source (image to be transformed and target (reference image. Point landmarks are placed at regular intervals on contours of anatomical features, and their positions are optimized along the contour surface by a function composed of curvature similarity and displacements of the homologous landmarks. The method was evaluated in two cases (=5 each. In one, MRI was registered to histological sections; in the second, geometric distortions in EPI MRI were corrected. Normalized mutual information and target registration error were calculated to compare the registration accuracy of the automatically and manually generated landmarks. Results. Statistical analyses demonstrated significant improvement (<0.05 in registration accuracy by landmark optimization in most data sets and trends towards improvement (<0.1 in others as compared to manual landmark selection.
International Nuclear Information System (INIS)
Ramani, D.T.
1977-01-01
The 'INTRANS' system is a general purpose computer code, designed to perform linear and non-linear structural stress and deflection analysis of impacting or non-impacting nuclear reactor internals components coupled with reactor vessel, shield building and external as well as internal gapped spring support system. This paper describes in general a unique computational procedure for evaluating the dynamic response of reactor internals, descretised as beam and lumped mass structural system and subjected to external transient loads such as seismic and LOCA time-history forces. The computational procedure is outlined in the INTRANS code, which computes component flexibilities of a discrete lumped mass planar model of reactor internals by idealising an assemblage of finite elements consisting of linear elastic beams with bending, torsional and shear stiffnesses interacted with external or internal linear as well as non-linear multi-gapped spring support system. The method of analysis is based on the displacement method and the code uses the fourth-order Runge-Kutta numerical integration technique as a basis for solution of dynamic equilibrium equations of motion for the system. During the computing process, the dynamic response of each lumped mass is calculated at specific instant of time using well-known step-by-step procedure. At any instant of time then, the transient dynamic motions of the system are held stationary and based on the predicted motions and internal forces of the previous instant. From which complete response at any time-step of interest may then be computed. Using this iterative process, the relationship between motions and internal forces is satisfied step by step throughout the time interval
Thrust generation by a heaving flexible foil: Resonance, nonlinearities, and optimality
Paraz, Florine; Schouveiler, Lionel; Eloy, Christophe
2016-01-01
Flexibility of marine animal fins has been thought to enhance swimming performance. However, despite numerous experimental and numerical studies on flapping flexible foils, there is still no clear understanding of the effect of flexibility and flapping amplitude on thrust generation and swimming efficiency. Here, to address this question, we combine experiments on a model system and a weakly nonlinear analysis. Experiments consist in immersing a flexible rectangular plate in a uniform flow and forcing this plate into a heaving motion at its leading edge. A complementary theoretical model is developed assuming a two-dimensional inviscid problem. In this model, nonlinear effects are taken into account by considering a transverse resistive drag. Under these hypotheses, a modal decomposition of the system motion allows us to predict the plate response amplitude and the generated thrust, as a function of the forcing amplitude and frequency. We show that this model can correctly predict the experimental data on plate kinematic response and thrust generation, as well as other data found in the literature. We also discuss the question of efficiency in the context of bio-inspired propulsion. Using the proposed model, we show that the optimal propeller for a given thrust and a given swimming speed is achieved when the actuating frequency is tuned to a resonance of the system, and when the optimal forcing amplitude scales as the square root of the required thrust.
Mathematical modeling of zika virus disease with nonlinear incidence and optimal control
Goswami, Naba Kumar; Srivastav, Akhil Kumar; Ghosh, Mini; Shanmukha, B.
2018-04-01
The Zika virus was first discovered in a rhesus monkey in the Zika Forest of Uganda in 1947, and it was isolated from humans in Nigeria in 1952. Zika virus disease is primarily a mosquito-borne disease, which is transmitted to human primarily through the bite of an infected Aedes species mosquito. However, there is documented evidence of sexual transmission of this disease too. In this paper, a nonlinear mathematical model for Zika virus by considering nonlinear incidence is formulated and analyzed. The equilibria and the basic reproduction number (R0) of the model are found. The stability of the different equilibria of the model is discussed in detail. When the basic reproduction number R0 1, we have endemic equilibrium which is locally stable under some restriction on parameters. Further this model is extended to optimal control model and is analyzed by using Pontryagin’s Maximum Principle. It has been observed that optimal control plays a significant role in reducing the number of zika infectives. Finally, numerical simulation is performed to illustrate the analytical findings.
Nonlinear Optimization-Based Device-Free Localization with Outlier Link Rejection
Directory of Open Access Journals (Sweden)
Wendong Xiao
2015-04-01
Full Text Available Device-free localization (DFL is an emerging wireless technique for estimating the location of target that does not have any attached electronic device. It has found extensive use in Smart City applications such as healthcare at home and hospitals, location-based services at smart spaces, city emergency response and infrastructure security. In DFL, wireless devices are used as sensors that can sense the target by transmitting and receiving wireless signals collaboratively. Many DFL systems are implemented based on received signal strength (RSS measurements and the location of the target is estimated by detecting the changes of the RSS measurements of the wireless links. Due to the uncertainty of the wireless channel, certain links may be seriously polluted and result in erroneous detection. In this paper, we propose a novel nonlinear optimization approach with outlier link rejection (NOOLR for RSS-based DFL. It consists of three key strategies, including: (1 affected link identification by differential RSS detection; (2 outlier link rejection via geometrical positional relationship among links; (3 target location estimation by formulating and solving a nonlinear optimization problem. Experimental results demonstrate that NOOLR is robust to the fluctuation of the wireless signals with superior localization accuracy compared with the existing Radio Tomographic Imaging (RTI approach.
Nonlinear Multiuser Receiver for Optimized Chaos-Based DS-CDMA Systems
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S. Shaerbaf
2011-09-01
Full Text Available Chaos based communications have drawn increasing attention over the past years. Chaotic signals are derived from non-linear dynamic systems. They are aperiodic, broadband and deterministic signals that appear random in the time domain. Because of these properties, chaotic signals have been proposed to generate spreading sequences for wide-band secure communication recently. Like conventional DS-CDMA systems, chaos-based CDMA systems suffer from multi-user interference (MUI due to other users transmitting in the cell. In this paper, we propose a novel method based on radial basis function (RBF for both blind and non-blind multiuser detection in chaos-based DS-CDMA systems. We also propose a new method for optimizing generation of binary chaotic sequences using Genetic Algorithm. Simulation results show that our proposed nonlinear receiver with optimized chaotic sequences outperforms in comparison to other conventional detectors such as a single-user detector, decorrelating detector and minimum mean square error detector, particularly for under-loaded CDMA condition, which the number of active users is less than processing gain.
Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks
Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.
2011-01-01
In this paper, we propose a scheme for the optimal allocation of power, source coding rate, and channel coding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network. The optimization is quality-driven, i.e. the received quality of the video that is transmitted by the nodes is optimized. The scheme takes into account the fact that the sensor nodes may be imaging scenes with varying levels of motion. Nodes that image low-motion scenes will require a lower source coding rate, so they will be able to allocate a greater portion of the total available bit rate to channel coding. Stronger channel coding will mean that such nodes will be able to transmit at lower power. This will both increase battery life and reduce interference to other nodes. Two optimization criteria are considered. One that minimizes the average video distortion of the nodes and one that minimizes the maximum distortion among the nodes. The transmission powers are allowed to take continuous values, whereas the source and channel coding rates can assume only discrete values. Thus, the resulting optimization problem lies in the field of mixed-integer optimization tasks and is solved using Particle Swarm Optimization. Our experimental results show the importance of considering the characteristics of the video sequences when determining the transmission power, source coding rate and channel coding rate for the nodes of the visual sensor network.
Final Report A Multi-Language Environment For Programmable Code Optimization and Empirical Tuning
Energy Technology Data Exchange (ETDEWEB)
Yi, Qing [Univ. of Colorado, Colorado Springs, CO (United States); Whaley, Richard Clint [Univ. of Texas, San Antonio, TX (United States); Qasem, Apan [Texas State Univ., San Marcos, TX (United States); Quinlan, Daniel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2013-11-23
This report summarizes our effort and results of building an integrated optimization environment to effectively combine the programmable control and the empirical tuning of source-to-source compiler optimizations within the framework of multiple existing languages, specifically C, C++, and Fortran. The environment contains two main components: the ROSE analysis engine, which is based on the ROSE C/C++/Fortran2003 source-to-source compiler developed by Co-PI Dr.Quinlan et. al at DOE/LLNL, and the POET transformation engine, which is based on an interpreted program transformation language developed by Dr. Yi at University of Texas at San Antonio (UTSA). The ROSE analysis engine performs advanced compiler analysis, identifies profitable code transformations, and then produces output in POET, a language designed to provide programmable control of compiler optimizations to application developers and to support the parameterization of architecture-sensitive optimizations so that their configurations can be empirically tuned later. This POET output can then be ported to different machines together with the user application, where a POET-based search engine empirically reconfigures the parameterized optimizations until satisfactory performance is found. Computational specialists can write POET scripts to directly control the optimization of their code. Application developers can interact with ROSE to obtain optimization feedback as well as provide domain-specific knowledge and high-level optimization strategies. The optimization environment is expected to support different levels of automation and programmer intervention, from fully-automated tuning to semi-automated development and to manual programmable control.
Imaging of human tooth using ultrasound based chirp-coded nonlinear time reversal acoustics
Czech Academy of Sciences Publication Activity Database
Dos Santos, S.; Převorovský, Zdeněk
2011-01-01
Roč. 51, č. 6 (2011), s. 667-674 ISSN 0041-624X Institutional research plan: CEZ:AV0Z20760514 Keywords : TR-NEWS * chirp-coded excitation * echodentography * ultrasonic imaging Subject RIV: BI - Acoustics Impact factor: 1.838, year: 2011 http://www.sciencedirect.com/science/article/pii/S0041624X11000229
Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P
2015-11-01
This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu
2016-01-01
An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.
Energy Technology Data Exchange (ETDEWEB)
Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Drohmann, Martin [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Tuminaro, Raymond S. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Computational Mathematics; Boggs, Paul T. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Ray, Jaideep [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; van Bloemen Waanders, Bart Gustaaf [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Optimization and Uncertainty Estimation
2014-10-01
-model errors. This enables ROMs to be rigorously incorporated in uncertainty-quantification settings, as the error model can be treated as a source of epistemic uncertainty. This work was completed as part of a Truman Fellowship appointment. We note that much additional work was performed as part of the Fellowship. One salient project is the development of the Trilinos-based model-reduction software module Razor , which is currently bundled with the Albany PDE code and currently allows nonlinear reduced-order models to be constructed for any application supported in Albany. Other important projects include the following: 1. ROMES-equipped ROMs for Bayesian inference: K. Carlberg, M. Drohmann, F. Lu (Lawrence Berkeley National Laboratory), M. Morzfeld (Lawrence Berkeley National Laboratory). 2. ROM-enabled Krylov-subspace recycling: K. Carlberg, V. Forstall (University of Maryland), P. Tsuji, R. Tuminaro. 3. A pseudo balanced POD method using only dual snapshots: K. Carlberg, M. Sarovar. 4. An analysis of discrete v. continuous optimality in nonlinear model reduction: K. Carlberg, M. Barone, H. Antil (George Mason University). Journal articles for these projects are in progress at the time of this writing.
Yang, Xinyu; Xu, Guoai; Li, Qi; Guo, Yanhui; Zhang, Miao
2017-01-01
Authorship attribution is to identify the most likely author of a given sample among a set of candidate known authors. It can be not only applied to discover the original author of plain text, such as novels, blogs, emails, posts etc., but also used to identify source code programmers. Authorship attribution of source code is required in diverse applications, ranging from malicious code tracking to solving authorship dispute or software plagiarism detection. This paper aims to propose a new method to identify the programmer of Java source code samples with a higher accuracy. To this end, it first introduces back propagation (BP) neural network based on particle swarm optimization (PSO) into authorship attribution of source code. It begins by computing a set of defined feature metrics, including lexical and layout metrics, structure and syntax metrics, totally 19 dimensions. Then these metrics are input to neural network for supervised learning, the weights of which are output by PSO and BP hybrid algorithm. The effectiveness of the proposed method is evaluated on a collected dataset with 3,022 Java files belong to 40 authors. Experiment results show that the proposed method achieves 91.060% accuracy. And a comparison with previous work on authorship attribution of source code for Java language illustrates that this proposed method outperforms others overall, also with an acceptable overhead.
The SWAN/NPSOL code system for multivariable multiconstraint shield optimization
International Nuclear Information System (INIS)
Watkins, E.F.; Greenspan, E.
1995-01-01
SWAN is a useful code for optimization of source-driven systems, i.e., systems for which the neutron and photon distribution is the solution of the inhomogeneous transport equation. Over the years, SWAN has been applied to the optimization of a variety of nuclear systems, such as minimizing the thickness of fusion reactor blankets and shields, the weight of space reactor shields, the cost for an ICF target chamber shield, and the background radiation for explosive detection systems and maximizing the beam quality for boron neutron capture therapy applications. However, SWAN's optimization module can handle up to a single constraint and was inefficient in handling problems with many variables. The purpose of this work is to upgrade SWAN's optimization capability
φq-field theory for portfolio optimization: “fat tails” and nonlinear correlations
Sornette, D.; Simonetti, P.; Andersen, J. V.
2000-08-01
Physics and finance are both fundamentally based on the theory of random walks (and their generalizations to higher dimensions) and on the collective behavior of large numbers of correlated variables. The archetype examplifying this situation in finance is the portfolio optimization problem in which one desires to diversify on a set of possibly dependent assets to optimize the return and minimize the risks. The standard mean-variance solution introduced by Markovitz and its subsequent developments is basically a mean-field Gaussian solution. It has severe limitations for practical applications due to the strongly non-Gaussian structure of distributions and the nonlinear dependence between assets. Here, we present in details a general analytical characterization of the distribution of returns for a portfolio constituted of assets whose returns are described by an arbitrary joint multivariate distribution. In this goal, we introduce a non-linear transformation that maps the returns onto Gaussian variables whose covariance matrix provides a new measure of dependence between the non-normal returns, generalizing the covariance matrix into a nonlinear covariance matrix. This nonlinear covariance matrix is chiseled to the specific fat tail structure of the underlying marginal distributions, thus ensuring stability and good conditioning. The portfolio distribution is then obtained as the solution of a mapping to a so-called φq field theory in particle physics, of which we offer an extensive treatment using Feynman diagrammatic techniques and large deviation theory, that we illustrate in details for multivariate Weibull distributions. The interaction (non-mean field) structure in this field theory is a direct consequence of the non-Gaussian nature of the distribution of asset price returns. We find that minimizing the portfolio variance (i.e. the relatively “small” risks) may often increase the large risks, as measured by higher normalized cumulants. Extensive
Zhao, Hui; Wei, Jingxuan
2014-09-01
The key to the concept of tunable wavefront coding lies in detachable phase masks. Ojeda-Castaneda et al. (Progress in Electronics Research Symposium Proceedings, Cambridge, USA, July 5-8, 2010) described a typical design in which two components with cosinusoidal phase variation operate together to make defocus sensitivity tunable. The present study proposes an improved design and makes three contributions: (1) A mathematical derivation based on the stationary phase method explains why the detachable phase mask of Ojeda-Castaneda et al. tunes the defocus sensitivity. (2) The mathematical derivations show that the effective bandwidth wavefront coded imaging system is also tunable by making each component of the detachable phase mask move asymmetrically. An improved Fisher information-based optimization procedure was also designed to ascertain the optimal mask parameters corresponding to specific bandwidth. (3) Possible applications of the tunable bandwidth are demonstrated by simulated imaging.
User's manual for the BNW-II optimization code for dry/wet-cooled power plants
International Nuclear Information System (INIS)
Braun, D.J.; Bamberger, J.A.; Braun, D.J.; Faletti, D.W.; Wiles, L.E.
1978-05-01
The User's Manual describes how to operate BNW-II, a computer code developed by the Pacific Northwest Laboratory (PNL) as a part of its activities under the Department of Energy (DOE) Dry Cooling Enhancement Program. The computer program offers a comprehensive method of evaluating the cost savings potential of dry/wet-cooled heat rejection systems. Going beyond simple ''figure-of-merit'' cooling tower optimization, this method includes such items as the cost of annual replacement capacity, and the optimum split between plant scale-up and replacement capacity, as well as the purchase and operating costs of all major heat rejection components. Hence the BNW-II code is a useful tool for determining potential cost savings of new dry/wet surfaces, new piping, or other components as part of an optimized system for a dry/wet-cooled plant
Directory of Open Access Journals (Sweden)
Carlos Pozo
Full Text Available Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study
Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Sorribas, Albert; Jiménez, Laureano
2012-01-01
Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the
[Symbol: see text]2 Optimized predictive image coding with [Symbol: see text]∞ bound.
Chuah, Sceuchin; Dumitrescu, Sorina; Wu, Xiaolin
2013-12-01
In many scientific, medical, and defense applications of image/video compression, an [Symbol: see text]∞ error bound is required. However, pure[Symbol: see text]∞-optimized image coding, colloquially known as near-lossless image coding, is prone to structured errors such as contours and speckles if the bit rate is not sufficiently high; moreover, most of the previous [Symbol: see text]∞-based image coding methods suffer from poor rate control. In contrast, the [Symbol: see text]2 error metric aims for average fidelity and hence preserves the subtlety of smooth waveforms better than the ∞ error metric and it offers fine granularity in rate control, but pure [Symbol: see text]2-based image coding methods (e.g., JPEG 2000) cannot bound individual errors as the [Symbol: see text]∞-based methods can. This paper presents a new compression approach to retain the benefits and circumvent the pitfalls of the two error metrics. A common approach of near-lossless image coding is to embed into a DPCM prediction loop a uniform scalar quantizer of residual errors. The said uniform scalar quantizer is replaced, in the proposed new approach, by a set of context-based [Symbol: see text]2-optimized quantizers. The optimization criterion is to minimize a weighted sum of the [Symbol: see text]2 distortion and the entropy while maintaining a strict [Symbol: see text]∞ error bound. The resulting method obtains good rate-distortion performance in both [Symbol: see text]2 and [Symbol: see text]∞ metrics and also increases the rate granularity. Compared with JPEG 2000, the new method not only guarantees lower [Symbol: see text]∞ error for all bit rates, but also it achieves higher PSNR for relatively high bit rates.
International Nuclear Information System (INIS)
Tayal, M.
1987-01-01
Structures often operate at elevated temperatures. Temperature calculations are needed so that the design can accommodate thermally induced stresses and material changes. A finite element computer called FEAT has been developed to calculate temperatures in solids of arbitrary shapes. FEAT solves the classical equation for steady state conduction of heat. The solution is obtained for two-dimensional (plane or axisymmetric) or for three-dimensional problems. Gap elements are use to simulate interfaces between neighbouring surfaces. The code can model: conduction; internal generation of heat; prescribed convection to a heat sink; prescribed temperatures at boundaries; prescribed heat fluxes on some surfaces; and temperature-dependence of material properties like thermal conductivity. The user has a option of specifying the detailed variation of thermal conductivity with temperature. For convenience to the nuclear fuel industry, the user can also opt for pre-coded values of thermal conductivity, which are obtained from the MATPRO data base (sponsored by the U.S. Nuclear Regulatory Commission). The finite element method makes FEAT versatile, and enables it to accurately accommodate complex geometries. The optional link to MATPRO makes it convenient for the nuclear fuel industry to use FEAT, without loss of generality. Special numerical techniques make the code inexpensive to run, for the type of material non-linearities often encounter in the analysis of nuclear fuel. The code, however, is general, and can be used for other components of the reactor, or even for non-nuclear systems. The predictions of FEAT have been compared against several analytical solutions. The agreement is usually better than 5%. Thermocouple measurements show that the FEAT predictions are consistent with measured changes in temperatures in simulated pressure tubes. FEAT was also found to predict well, the axial variations in temperatures in the end-pellets(UO 2 ) of two fuel elements irradiated
Taylor, Ellen Meredith
Weighted essentially non-oscillatory (WENO) methods have been developed to simultaneously provide robust shock-capturing in compressible fluid flow and avoid excessive damping of fine-scale flow features such as turbulence. This is accomplished by constructing multiple candidate numerical stencils that adaptively combine so as to provide high order of accuracy and high bandwidth-resolving efficiency in continuous flow regions while averting instability-provoking interpolation across discontinuities. Under certain conditions in compressible turbulence, however, numerical dissipation remains unacceptably high even after optimization of the linear optimal stencil combination that dominates in smooth regions. The remaining nonlinear error arises from two primary sources: (i) the smoothness measurement that governs the application of adaptation away from the optimal stencil and (ii) the numerical properties of individual candidate stencils that govern numerical accuracy when adaptation engages. In this work, both of these sources are investigated, and corrective modifications to the WENO methodology are proposed and evaluated. Excessive nonlinear error due to the first source is alleviated through two separately considered procedures appended to the standard smoothness measurement technique that are designated the "relative smoothness limiter" and the "relative total variation limiter." In theory, appropriate values of their associated parameters should be insensitive to flow configuration, thereby sidestepping the prospect of costly parameter tuning; and this expectation of broad effectiveness is assessed in direct numerical simulations (DNS) of one-dimensional inviscid test problems, three-dimensional compressible isotropic turbulence of varying Reynolds and turbulent Mach numbers, and shock/isotropic-turbulence interaction (SITI). In the process, tools for efficiently comparing WENO adaptation behavior in smooth versus shock-containing regions are developed. The
Nonlinear dynamics of laser systems with elements of a chaos: Advanced computational code
Buyadzhi, V. V.; Glushkov, A. V.; Khetselius, O. Yu; Kuznetsova, A. A.; Buyadzhi, A. A.; Prepelitsa, G. P.; Ternovsky, V. B.
2017-10-01
A general, uniform chaos-geometric computational approach to analysis, modelling and prediction of the non-linear dynamics of quantum and laser systems (laser and quantum generators system etc) with elements of the deterministic chaos is briefly presented. The approach is based on using the advanced generalized techniques such as the wavelet analysis, multi-fractal formalism, mutual information approach, correlation integral analysis, false nearest neighbour algorithm, the Lyapunov’s exponents analysis, and surrogate data method, prediction models etc There are firstly presented the numerical data on the topological and dynamical invariants (in particular, the correlation, embedding, Kaplan-York dimensions, the Lyapunov’s exponents, Kolmogorov’s entropy and other parameters) for laser system (the semiconductor GaAs/GaAlAs laser with a retarded feedback) dynamics in a chaotic and hyperchaotic regimes.
Cosmological N-body simulations with a tree code - Fluctuations in the linear and nonlinear regimes
International Nuclear Information System (INIS)
Suginohara, Tatsushi; Suto, Yasushi; Bouchet, F.R.; Hernquist, L.
1991-01-01
The evolution of gravitational systems is studied numerically in a cosmological context using a hierarchical tree algorithm with fully periodic boundary conditions. The simulations employ 262,144 particles, which are initially distributed according to scale-free power spectra. The subsequent evolution is followed in both flat and open universes. With this large number of particles, the discretized system can accurately model the linear phase. It is shown that the dynamics in the nonlinear regime depends on both the spectral index n and the density parameter Omega. In Omega = 1 universes, the evolution of the two-point correlation function Xi agrees well with similarity solutions for Xi greater than about 100 but its slope is steeper in open models with the same n. 28 refs
International Nuclear Information System (INIS)
Luehrmann, L.; Noseck, U.
1996-03-01
While the verification report on CHET1 primarily focused on aspects such as the correctness of algorithms with respect to the modeling of advection, dispersion and diffusion, the report in hand is intended to primarily deal with nonlinear sorption and numerical sorption modeling. Another aspect discussed is the correct treatment of decay within established radioactive decay chains. First, the physical fundamentals are explained of the processes determining the radionuclide transport in the cap rock, and hence are the basis of the program discussed. The numeric algorithms the CHET2 code is based are explained, showing the details of realisation and the function of the various defaults and corrections. The iterative coupling of transport and sorption computation is illustrated by means of a program flowchart. Furthermore, the actvities for verification of the program are explained, as well as qualitative effects of computations assuming concentration-dependent sorption. The computation of the decay within decay chains is verified, and application programming using nonlinear sorption isotherms as well as the entire process of transport calculations with CHET2 are shown. (orig./DG) [de
Directory of Open Access Journals (Sweden)
Zhen Chen
2016-01-01
Full Text Available Accelerated degradation test (ADT has been widely used to assess highly reliable products’ lifetime. To conduct an ADT, an appropriate degradation model and test plan should be determined in advance. Although many historical studies have proposed quite a few models, there is still room for improvement. Hence we propose a Nonlinear Generalized Wiener Process (NGWP model with consideration of the effects of stress level, product-to-product variability, and measurement errors for a higher estimation accuracy and a wider range of use. Then under the constraints of sample size, test duration, and test cost, the plans of constant-stress ADT (CSADT with multiple stress levels based on the NGWP are designed by minimizing the asymptotic variance of the reliability estimation of the products under normal operation conditions. An optimization algorithm is developed to determine the optimal stress levels, the number of units allocated to each level, inspection frequency, and measurement times simultaneously. In addition, a comparison based on degradation data of LEDs is made to show better goodness-of-fit of the NGWP than that of other models. Finally, optimal two-level and three-level CSADT plans under various constraints and a detailed sensitivity analysis are demonstrated through examples in this paper.
Distributed Optimal Consensus Control for Nonlinear Multiagent System With Unknown Dynamic.
Zhang, Jilie; Zhang, Huaguang; Feng, Tao
2017-08-01
This paper focuses on the distributed optimal cooperative control for continuous-time nonlinear multiagent systems (MASs) with completely unknown dynamics via adaptive dynamic programming (ADP) technology. By introducing predesigned extra compensators, the augmented neighborhood error systems are derived, which successfully circumvents the system knowledge requirement for ADP. It is revealed that the optimal consensus protocols actually work as the solutions of the MAS differential game. Policy iteration algorithm is adopted, and it is theoretically proved that the iterative value function sequence strictly converges to the solution of the coupled Hamilton-Jacobi-Bellman equation. Based on this point, a novel online iterative scheme is proposed, which runs based on the data sampled from the augmented system and the gradient of the value function. Neural networks are employed to implement the algorithm and the weights are updated, in the least-square sense, to the ideal value, which yields approximated optimal consensus protocols. Finally, a numerical example is given to illustrate the effectiveness of the proposed scheme.
Stabilization of business cycles of finance agents using nonlinear optimal control
Rigatos, G.; Siano, P.; Ghosh, T.; Sarno, D.
2017-11-01
Stabilization of the business cycles of interconnected finance agents is performed with the use of a new nonlinear optimal control method. First, the dynamics of the interacting finance agents and of the associated business cycles is described by a modeled of coupled nonlinear oscillators. Next, this dynamic model undergoes approximate linearization round a temporary operating point which is defined by the present value of the system's state vector and the last value of the control inputs vector that was exerted on it. The linearization procedure is based on Taylor series expansion of the dynamic model and on the computation of Jacobian matrices. The modelling error, which is due to the truncation of higher-order terms in the Taylor series expansion is considered as a disturbance which is compensated by the robustness of the control loop. Next, for the linearized model of the interacting finance agents, an H-infinity feedback controller is designed. The computation of the feedback control gain requires the solution of an algebraic Riccati equation at each iteration of the control algorithm. Through Lyapunov stability analysis it is proven that the control scheme satisfies an H-infinity tracking performance criterion, which signifies elevated robustness against modelling uncertainty and external perturbations. Moreover, under moderate conditions the global asymptotic stability features of the control loop are proven.
Liolios, A
2003-01-01
The paper presents a new numerical approach for a non-linear optimal control problem arising in earthquake civil engineering. This problem concerns the elastoplastic softening-fracturing unilateral contact between neighbouring buildings during earthquakes when Coulomb friction is taken into account under second-order instabilizing effects. So, the earthquake response of the adjacent structures can appear instabilities and chaotic behaviour. The problem formulation presented here leads to a set of equations and inequalities, which is equivalent to a dynamic hemivariational inequality in the way introduced by Panagiotopoulos [Hemivariational Inequalities. Applications in Mechanics and Engineering, Springer-Verlag, Berlin, 1993]. The numerical procedure is based on an incremental problem formulation and on a double discretization, in space by the finite element method and in time by the Wilson-theta method. The generally non-convex constitutive contact laws are piecewise linearized, and in each time-step a non-c...
Dynamics and optimal control of a non-linear epidemic model with relapse and cure
Lahrouz, A.; El Mahjour, H.; Settati, A.; Bernoussi, A.
2018-04-01
In this work, we introduce the basic reproduction number R0 for a general epidemic model with graded cure, relapse and nonlinear incidence rate in a non-constant population size. We established that the disease free-equilibrium state Ef is globally asymptotically exponentially stable if R0 1, we proved that the system model has at least one endemic state Ee. Then, by means of an appropriate Lyapunov function, we showed that Ee is unique and globally asymptotically stable under some acceptable biological conditions. On the other hand, we use two types of control to reduce the number of infectious individuals. The optimality system is formulated and solved numerically using a Gauss-Seidel-like implicit finite-difference method.
Nonlinear optimization method of ship floating condition calculation in wave based on vector
Ding, Ning; Yu, Jian-xing
2014-08-01
Ship floating condition in regular waves is calculated. New equations controlling any ship's floating condition are proposed by use of the vector operation. This form is a nonlinear optimization problem which can be solved using the penalty function method with constant coefficients. And the solving process is accelerated by dichotomy. During the solving process, the ship's displacement and buoyant centre have been calculated by the integration of the ship surface according to the waterline. The ship surface is described using an accumulative chord length theory in order to determine the displacement, the buoyancy center and the waterline. The draught forming the waterline at each station can be found out by calculating the intersection of the ship surface and the wave surface. The results of an example indicate that this method is exact and efficient. It can calculate the ship floating condition in regular waves as well as simplify the calculation and improve the computational efficiency and the precision of results.
Non-linear heat transfer computer code by finite element method
International Nuclear Information System (INIS)
Nagato, Kotaro; Takikawa, Noboru
1977-01-01
The computer code THETA-2D for the calculation of temperature distribution by the two-dimensional finite element method was made for the analysis of heat transfer in a high temperature structure. Numerical experiment was performed for the numerical integration of the differential equation of heat conduction. The Runge-Kutta method of the numerical experiment produced an unstable solution. A stable solution was obtained by the β method with the β value of 0.35. In high temperature structures, the radiative heat transfer can not be neglected. To introduce a term of the radiative heat transfer, a functional neglecting the radiative heat transfer was derived at first. Then, the radiative term was added after the discretion by variation method. Five model calculations were carried out by the computer code. Calculation of steady heat conduction was performed. When estimated initial temperature is 1,000 degree C, reasonable heat blance was obtained. In case of steady-unsteady temperature calculation, the time integral by THETA-2D turned out to be under-estimation for enthalpy change. With a one-dimensional model, the temperature distribution in a structure, in which heat conductivity is dependent on temperature, was calculated. Calculation with a model which has a void inside was performed. Finally, model calculation for a complex system was carried out. (Kato, T.)
Martini, William R.
1989-01-01
A FORTRAN computer code is described that could be used to design and optimize a free-displacer, free-piston Stirling engine similar to the RE-1000 engine made by Sunpower. The code contains options for specifying displacer and power piston motion or for allowing these motions to be calculated by a force balance. The engine load may be a dashpot, inertial compressor, hydraulic pump or linear alternator. Cycle analysis may be done by isothermal analysis or adiabatic analysis. Adiabatic analysis may be done using the Martini moving gas node analysis or the Rios second-order Runge-Kutta analysis. Flow loss and heat loss equations are included. Graphical display of engine motions and pressures and temperatures are included. Programming for optimizing up to 15 independent dimensions is included. Sample performance results are shown for both specified and unconstrained piston motions; these results are shown as generated by each of the two Martini analyses. Two sample optimization searches are shown using specified piston motion isothermal analysis. One is for three adjustable input and one is for four. Also, two optimization searches for calculated piston motion are presented for three and for four adjustable inputs. The effect of leakage is evaluated. Suggestions for further work are given.
Kumar, Ravi; Bhaduri, Basanta; Nishchal, Naveen K.
2018-01-01
In this study, we propose a quick response (QR) code based nonlinear optical image encryption technique using spiral phase transform (SPT), equal modulus decomposition (EMD) and singular value decomposition (SVD). First, the primary image is converted into a QR code and then multiplied with a spiral phase mask (SPM). Next, the product is spiral phase transformed with particular spiral phase function, and further, the EMD is performed on the output of SPT, which results into two complex images, Z 1 and Z 2. Among these, Z 1 is further Fresnel propagated with distance d, and Z 2 is reserved as a decryption key. Afterwards, SVD is performed on Fresnel propagated output to get three decomposed matrices i.e. one diagonal matrix and two unitary matrices. The two unitary matrices are modulated with two different SPMs and then, the inverse SVD is performed using the diagonal matrix and modulated unitary matrices to get the final encrypted image. Numerical simulation results confirm the validity and effectiveness of the proposed technique. The proposed technique is robust against noise attack, specific attack, and brutal force attack. Simulation results are presented in support of the proposed idea.
Pozo, Carlos; Marín-Sanguino, Alberto; Alves, Rui; Guillén-Gosálbez, Gonzalo; Jiménez, Laureano; Sorribas, Albert
2011-08-25
Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.
Directory of Open Access Journals (Sweden)
Sorribas Albert
2011-08-01
Full Text Available Abstract Background Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.
Zhang, Liping; Zheng, Yanling; Wang, Kai; Zhang, Xueliang; Zheng, Yujian
2014-06-01
In this paper, by using a particle swarm optimization algorithm to solve the optimal parameter estimation problem, an improved Nash nonlinear grey Bernoulli model termed PSO-NNGBM(1,1) is proposed. To test the forecasting performance, the optimized model is applied for forecasting the incidence of hepatitis B in Xinjiang, China. Four models, traditional GM(1,1), grey Verhulst model (GVM), original nonlinear grey Bernoulli model (NGBM(1,1)) and Holt-Winters exponential smoothing method, are also established for comparison with the proposed model under the criteria of mean absolute percentage error and root mean square percent error. The prediction results show that the optimized NNGBM(1,1) model is more accurate and performs better than the traditional GM(1,1), GVM, NGBM(1,1) and Holt-Winters exponential smoothing method. Copyright © 2014. Published by Elsevier Ltd.
A nuclear reload optimization approach using a real coded genetic algorithm with random keys
International Nuclear Information System (INIS)
Lima, Alan M.M. de; Schirru, Roberto; Medeiros, Jose A.C.C.
2009-01-01
The fuel reload of a Pressurized Water Reactor is made whenever the burn up of the fuel assemblies in the nucleus of the reactor reaches a certain value such that it is not more possible to maintain a critical reactor producing energy at nominal power. The problem of fuel reload optimization consists on determining the positioning of the fuel assemblies within the nucleus of the reactor in an optimized way to minimize the cost benefit relationship of fuel assemblies cost per maximum burn up, and also satisfying symmetry and safety restrictions. The fuel reload optimization problem difficulty grows exponentially with the number of fuel assemblies in the nucleus of the reactor. During decades the fuel reload optimization problem was solved manually by experts that used their knowledge and experience to build configurations of the reactor nucleus, and testing them to verify if safety restrictions of the plant are satisfied. To reduce this burden, several optimization techniques have been used, included the binary code genetic algorithm. In this work we show the use of a real valued coded approach of the genetic algorithm, with different recombination methods, together with a transformation mechanism called random keys, to transform the real values of the genes of each chromosome in a combination of discrete fuel assemblies for evaluation of the reload optimization. Four different recombination methods were tested: discrete recombination, intermediate recombination, linear recombination and extended linear recombination. For each of the 4 recombination methods 10 different tests using different seeds for the random number generator were conducted 10 generating, totaling 40 tests. The results of the application of the genetic algorithm are shown with formulation of real numbers for the problem of the nuclear reload of the plant Angra 1 type PWR. Since the best results in the literature for this problem were found by the parallel PSO we will it use for comparison
Directory of Open Access Journals (Sweden)
Valérian Mannoni
2004-09-01
Full Text Available This paper deals with optimized channel coding for OFDM transmissions (COFDM over frequency-selective channels using irregular low-density parity-check (LDPC codes. Firstly, we introduce a new characterization of the LDPC code irregularity called Ã‚Â“irregularity profile.Ã‚Â” Then, using this parameterization, we derive a new criterion based on the minimization of the transmission bit error probability to design an irregular LDPC code suited to the frequency selectivity of the channel. The optimization of this criterion is done using the Gaussian approximation technique. Simulations illustrate the good performance of our approach for different transmission channels.
International Nuclear Information System (INIS)
Lu, Peng; Zhou, Jianzhong; Wang, Chao; Qiao, Qi; Mo, Li
2015-01-01
Highlights: • STHGS problem is decomposed into two parallel sub-problems of UC and ELD. • Binary coded BCO is used to solve UC sub-problem with 0–1 discrete variables. • Real coded BCO is used to solve ELD sub-problem with continuous variables. • Some heuristic repairing strategies are designed to handle various constraints. • The STHGS of Xiluodu and Xiangjiaba cascade stations is solved by IB-RBCO. - Abstract: Short-term hydro generation scheduling (STHGS) of cascade hydropower stations is a typical nonlinear mixed integer optimization problem to minimize the total water consumption while simultaneously meeting the grid requirements and other hydraulic and electrical constraints. In this paper, STHGS problem is decomposed into two parallel sub-problems of unit commitment (UC) and economic load dispatch (ELD), and the methodology of improved binary-real coded bee colony optimization (IB-RBCO) algorithm is proposed to solve them. Firstly, the improved binary coded BCO is used to solve the UC sub-problem with 0–1 discrete variables, and the heuristic repairing strategy for unit state constrains is applied to generate the feasible unit commitment schedule. Then, the improved real coded BCO is used to solve the ELD sub-problem with continuous variables, and an effective method is introduced to handle various unit operation constraints. Especially, the new updating strategy of DE/best/2/bin method with dynamic parameter control mechanism is applied to real coded BCO to improve the search ability of IB-RBCO. Finally, to verify the feasibility and effectiveness of the proposed IB-RBCO method, it is applied to solve the STHGS problem of Xiluodu and Xiangjiaba cascaded hydropower stations, and the simulating results are compared with other intelligence algorithms. The simulation results demonstrate that the proposed IB-RBCO method can get higher-quality solutions with less water consumption and shorter calculating time when facing the complex STHGS problem
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Alrijadjis .
2014-12-01
Full Text Available The proportional integral derivative (PID controllers have been widely used in most process control systems for a long time. However, it is a very important problem how to choose PID parameters, because these parameters give a great influence on the control performance. Especially, it is difficult to tune these parameters for nonlinear systems. In this paper, a new modified particle swarm optimization (PSO is presented to search for optimal PID parameters for such system. The proposed algorithm is to modify constriction coefficient which is nonlinearly decreased time-varying for improving the final accuracy and the convergence speed of PSO. To validate the control performance of the proposed method, a typical nonlinear system control, a continuous stirred tank reactor (CSTR process, is illustrated. The results testify that a new modified PSO algorithm can perform well in the nonlinear PID control system design in term of lesser overshoot, rise-time, settling-time, IAE and ISE. Keywords: PID controller, Particle Swarm Optimization (PSO,constriction factor, nonlinear system.
Energy Technology Data Exchange (ETDEWEB)
Serkez, Svitozar; Kocharyan, Vitali; Saldin, Evgeni; Zagorodnov, Igor [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Geloni, Gianluca [European XFEL GmbH, Hamburg (Germany)
2013-09-15
We demonstrate that the output radiation characteristics of the European XFEL sources at nominal operation point can be easily made significantly better than what is currently reported in the TDRs of scientific instruments and X-ray optics. In fact, the output SASE characteristics of the baseline European XFEL have been previously optimized assuming uniform undulators at a nominal operating point of 5 kA peak current, without considering the potential of undulator tapering in the SASE regime. In order to illustrate this point, we analyze the case of an electron bunch with nominal parameters. Based on start-to-end simulations, we demonstrate that nonlinear undulator tapering allows one to achieve up to a tenfold increase in peak power and photon spectral density in the conventional SASE regime, without modification to the baseline design. The FEL code Genesis has been extensively used for these studies. In order to increase our confidence in simulation results, we cross-checked outcomes by reproducing simulations in the deep nonlinear SASE regime with tapered undulator using the code ALICE.
Multiple Description Coding Based on Optimized Redundancy Removal for 3D Depth Map
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Sen Han
2016-06-01
Full Text Available Multiple description (MD coding is a promising alternative for the robust transmission of information over error-prone channels. In 3D image technology, the depth map represents the distance between the camera and objects in the scene. Using the depth map combined with the existing multiview image, it can be efficient to synthesize images of any virtual viewpoint position, which can display more realistic 3D scenes. Differently from the conventional 2D texture image, the depth map contains a lot of spatial redundancy information, which is not necessary for view synthesis, but may result in the waste of compressed bits, especially when using MD coding for robust transmission. In this paper, we focus on the redundancy removal of MD coding based on the DCT (discrete cosine transform domain. In view of the characteristics of DCT coefficients, at the encoder, a Lagrange optimization approach is designed to determine the amounts of high frequency coefficients in the DCT domain to be removed. It is noted considering the low computing complexity that the entropy is adopted to estimate the bit rate in the optimization. Furthermore, at the decoder, adaptive zero-padding is applied to reconstruct the depth map when some information is lost. The experimental results have shown that compared to the corresponding scheme, the proposed method demonstrates better rate central and side distortion performance.
The SWAN-SCALE code for the optimization of critical systems
International Nuclear Information System (INIS)
Greenspan, E.; Karni, Y.; Regev, D.; Petrie, L.M.
1999-01-01
The SWAN optimization code was recently developed to identify the maximum value of k eff for a given mass of fissile material when in combination with other specified materials. The optimization process is iterative; in each iteration SWAN varies the zone-dependent concentration of the system constituents. This change is guided by the equal volume replacement effectiveness functions (EVREF) that SWAN generates using first-order perturbation theory. Previously, SWAN did not have provisions to account for the effect of the composition changes on neutron cross-section resonance self-shielding; it used the cross sections corresponding to the initial system composition. In support of the US Department of Energy Nuclear Criticality Safety Program, the authors recently removed the limitation on resonance self-shielding by coupling SWAN with the SCALE code package. The purpose of this paper is to briefly describe the resulting SWAN-SCALE code and to illustrate the effect that neutron cross-section self-shielding could have on the maximum k eff and on the corresponding system composition
Zhang, Ridong; Tao, Jili; Lu, Renquan; Jin, Qibing
2018-02-01
Modeling of distributed parameter systems is difficult because of their nonlinearity and infinite-dimensional characteristics. Based on principal component analysis (PCA), a hybrid modeling strategy that consists of a decoupled linear autoregressive exogenous (ARX) model and a nonlinear radial basis function (RBF) neural network model are proposed. The spatial-temporal output is first divided into a few dominant spatial basis functions and finite-dimensional temporal series by PCA. Then, a decoupled ARX model is designed to model the linear dynamics of the dominant modes of the time series. The nonlinear residual part is subsequently parameterized by RBFs, where genetic algorithm is utilized to optimize their hidden layer structure and the parameters. Finally, the nonlinear spatial-temporal dynamic system is obtained after the time/space reconstruction. Simulation results of a catalytic rod and a heat conduction equation demonstrate the effectiveness of the proposed strategy compared to several other methods.
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.
Calibration of Mine Ventilation Network Models Using the Non-Linear Optimization Algorithm
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Guang Xu
2017-12-01
Full Text Available Effective ventilation planning is vital to underground mining. To ensure stable operation of the ventilation system and to avoid airflow disorder, mine ventilation network (MVN models have been widely used in simulating and optimizing the mine ventilation system. However, one of the challenges for MVN model simulation is that the simulated airflow distribution results do not match the measured data. To solve this problem, a simple and effective calibration method is proposed based on the non-linear optimization algorithm. The calibrated model not only makes simulated airflow distribution results in accordance with the on-site measured data, but also controls the errors of other parameters within a minimum range. The proposed method was then applied to calibrate an MVN model in a real case, which is built based on ventilation survey results and Ventsim software. Finally, airflow simulation experiments are carried out respectively using data before and after calibration, whose results were compared and analyzed. This showed that the simulated airflows in the calibrated model agreed much better to the ventilation survey data, which verifies the effectiveness of calibrating method.
Lin, Chao; Shen, Xueju; Hua, Binbin; Wang, Zhisong
2015-10-01
We demonstrate the feasibility of three dimensional (3D) polarization multiplexing by optimizing a single vectorial beam using a multiple-signal window multiple-plane (MSW-MP) phase retrieval algorithm. Original messages represented with multiple quick response (QR) codes are first partitioned into a series of subblocks. Then, each subblock is marked with a specific polarization state and randomly distributed in 3D space with both longitudinal and transversal adjustable freedoms. A generalized 3D polarization mapping protocol is established to generate a 3D polarization key. Finally, multiple-QR code is encrypted into one phase only mask and one polarization only mask based on the modified Gerchberg-Saxton (GS) algorithm. We take the polarization mask as the cyphertext and the phase only mask as additional dimension of key. Only when both the phase key and 3D polarization key are correct, original messages can be recovered. We verify our proposal with both simulation and experiment evidences.
Rosenberg, D. E.; Alafifi, A.
2016-12-01
Water resources systems analysis often focuses on finding optimal solutions. Yet an optimal solution is optimal only for the modelled issues and managers often seek near-optimal alternatives that address un-modelled objectives, preferences, limits, uncertainties, and other issues. Early on, Modelling to Generate Alternatives (MGA) formalized near-optimal as the region comprising the original problem constraints plus a new constraint that allowed performance within a specified tolerance of the optimal objective function value. MGA identified a few maximally-different alternatives from the near-optimal region. Subsequent work applied Markov Chain Monte Carlo (MCMC) sampling to generate a larger number of alternatives that span the near-optimal region of linear problems or select portions for non-linear problems. We extend the MCMC Hit-And-Run method to generate alternatives that span the full extent of the near-optimal region for non-linear, non-convex problems. First, start at a feasible hit point within the near-optimal region, then run a random distance in a random direction to a new hit point. Next, repeat until generating the desired number of alternatives. The key step at each iterate is to run a random distance along the line in the specified direction to a new hit point. If linear equity constraints exist, we construct an orthogonal basis and use a null space transformation to confine hits and runs to a lower-dimensional space. Linear inequity constraints define the convex bounds on the line that runs through the current hit point in the specified direction. We then use slice sampling to identify a new hit point along the line within bounds defined by the non-linear inequity constraints. This technique is computationally efficient compared to prior near-optimal alternative generation techniques such MGA, MCMC Metropolis-Hastings, evolutionary, or firefly algorithms because search at each iteration is confined to the hit line, the algorithm can move in one
A nonlinear optimal control approach to stabilization of a macroeconomic development model
Rigatos, G.; Siano, P.; Ghosh, T.; Sarno, D.
2017-11-01
A nonlinear optimal (H-infinity) control approach is proposed for the problem of stabilization of the dynamics of a macroeconomic development model that is known as the Grossman-Helpman model of endogenous product cycles. The dynamics of the macroeconomic development model is divided in two parts. The first one describes economic activities in a developed country and the second part describes variation of economic activities in a country under development which tries to modify its production so as to serve the needs of the developed country. The article shows that through control of the macroeconomic model of the developed country, one can finally control the dynamics of the economy in the country under development. The control method through which this is achieved is the nonlinear H-infinity control. The macroeconomic model for the country under development undergoes approximate linearization round a temporary operating point. This is defined at each time instant by the present value of the system's state vector and the last value of the control input vector that was exerted on it. The linearization is based on Taylor series expansion and the computation of the associated Jacobian matrices. For the linearized model an H-infinity feedback controller is computed. The controller's gain is calculated by solving an algebraic Riccati equation at each iteration of the control method. The asymptotic stability of the control approach is proven through Lyapunov analysis. This assures that the state variables of the macroeconomic model of the country under development will finally converge to the designated reference values.
Memetic Algorithms to Solve a Global Nonlinear Optimization Problem. A Review
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M. K. Sakharov
2015-01-01
Full Text Available In recent decades, evolutionary algorithms have proven themselves as the powerful optimization techniques of search engine. Their popularity is due to the fact that they are easy to implement and can be used in all areas, since they are based on the idea of universal evolution. For example, in the problems of a large number of local optima, the traditional optimization methods, usually, fail in finding the global optimum. To solve such problems using a variety of stochastic methods, in particular, the so-called population-based algorithms, which are a kind of evolutionary methods. The main disadvantage of this class of methods is their slow convergence to the exact solution in the neighborhood of the global optimum, as these methods incapable to use the local information about the landscape of the function. This often limits their use in largescale real-world problems where the computation time is a critical factor.One of the promising directions in the field of modern evolutionary computation are memetic algorithms, which can be regarded as a combination of population search of the global optimum and local procedures for verifying solutions, which gives a synergistic effect. In the context of memetic algorithms, the meme is an implementation of the local optimization method to refine solution in the search.The concept of memetic algorithms provides ample opportunities for the development of various modifications of these algorithms, which can vary the frequency of the local search, the conditions of its end, and so on. The practically significant memetic algorithm modifications involve the simultaneous use of different memes. Such algorithms are called multi-memetic.The paper gives statement of the global problem of nonlinear unconstrained optimization, describes the most promising areas of AI modifications, including hybridization and metaoptimization. The main content of the work is the classification and review of existing varieties of
Two-dimensional core calculation research for fuel management optimization based on CPACT code
International Nuclear Information System (INIS)
Chen Xiaosong; Peng Lianghui; Gang Zhi
2013-01-01
Fuel management optimization process requires rapid assessment for the core layout program, and the commonly used methods include two-dimensional diffusion nodal method, perturbation method, neural network method and etc. A two-dimensional loading patterns evaluation code was developed based on the three-dimensional LWR diffusion calculation program CPACT. Axial buckling introduced to simulate the axial leakage was searched in sub-burnup sections to correct the two-dimensional core diffusion calculation results. Meanwhile, in order to get better accuracy, the weight equivalent volume method of the control rod assembly cross-section was improved. (authors)
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.
User's manual for the BNW-II optimization code for dry/wet-cooled power plants
Energy Technology Data Exchange (ETDEWEB)
Braun, D.J.; Bamberger, J.A.; Braun, D.J.; Faletti, D.W.; Wiles, L.E.
1978-05-01
This volume provides a listing of the BNW-II dry/wet ammonia heat rejection optimization code and is an appendix to Volume I which gives a narrative description of the code's algorithms as well as logic, input and output information.
DEFF Research Database (Denmark)
Misaridis, Thanasis; Jensen, Jørgen Arendt
1999-01-01
This paper presents a coded excitation imaging system based on a predistorted FM excitation and a digital compression filter designed for medical ultrasonic applications, in order to preserve both axial resolution and contrast. In radars, optimal Chebyshev windows efficiently weight a nearly...... as with pulse excitation (about 1.5 lambda), depending on the filter design criteria. The axial sidelobes are below -40 dB, which is the noise level of the measuring imaging system. The proposed excitation/compression scheme shows good overall performance and stability to the frequency shift due to attenuation...... be removed by weighting. We show that by using a predistorted chirp with amplitude or phase shaping for amplitude ripple reduction and a correlation filter that accounts for the transducer's natural frequency weighting, output sidelobe levels of -35 to -40 dB are directly obtained. When an optimized filter...
An Order Coding Genetic Algorithm to Optimize Fuel Reloads in a Nuclear Boiling Water Reactor
International Nuclear Information System (INIS)
Ortiz, Juan Jose; Requena, Ignacio
2004-01-01
A genetic algorithm is used to optimize the nuclear fuel reload for a boiling water reactor, and an order coding is proposed for the chromosomes and appropriate crossover and mutation operators. The fitness function was designed so that the genetic algorithm creates fuel reloads that, on one hand, satisfy the constrictions for the radial power peaking factor, the minimum critical power ratio, and the maximum linear heat generation rate while optimizing the effective multiplication factor at the beginning and end of the cycle. To find the values of these variables, a neural network trained with the behavior of a reactor simulator was used to predict them. The computation time is therefore greatly decreased in the search process. We validated this method with data from five cycles of the Laguna Verde Nuclear Power Plant in Mexico
DEFF Research Database (Denmark)
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...
DEFF Research Database (Denmark)
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....
Directory of Open Access Journals (Sweden)
Y. W. Sun
2013-08-01
Full Text Available In this paper, we present an optimized analysis algorithm for non-dispersive infrared (NDIR to in situ monitor stack emissions. The proposed algorithm simultaneously compensates for nonlinear absorption and cross interference among different gases. We present a mathematical derivation for the measurement error caused by variations in interference coefficients when nonlinear absorption occurs. The proposed algorithm is derived from a classical one and uses interference functions to quantify cross interference. The interference functions vary proportionally with the nonlinear absorption. Thus, interference coefficients among different gases can be modeled by the interference functions whether gases are characterized by linear or nonlinear absorption. In this study, the simultaneous analysis of two components (CO2 and CO serves as an example for the validation of the proposed algorithm. The interference functions in this case can be obtained by least-squares fitting with third-order polynomials. Experiments show that the results of cross interference correction are improved significantly by utilizing the fitted interference functions when nonlinear absorptions occur. The dynamic measurement ranges of CO2 and CO are improved by about a factor of 1.8 and 3.5, respectively. A commercial analyzer with high accuracy was used to validate the CO and CO2 measurements derived from the NDIR analyzer prototype in which the new algorithm was embedded. The comparison of the two analyzers show that the prototype works well both within the linear and nonlinear ranges.
Outage Analysis and Optimization of SWIPT in Network-Coded Two-Way Relay Networks
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Ruihong Jiang
2017-01-01
Full Text Available This paper investigates the outage performance of simultaneous wireless information and power transfer (SWIPT in network-coded two-way relay systems, where a relay first harvests energy from the signals transmitted by two sources and then uses the harvested energy to forward the received information to the two sources. We consider two transmission protocols, power splitting two-way relay (PS-TWR and time switching two-way relay (TS-TWR protocols. We present two explicit expressions for the system outage probability of the two protocols and further derive approximate expressions for them in high and low SNR cases. To explore the system performance limits, two optimization problems are formulated to minimize the system outage probability. Since the problems are nonconvex and have no known solution methods, a genetic algorithm- (GA- based algorithm is designed. Numerical and simulation results validate our theoretical analysis. It is shown that, by jointly optimizing the time assignment and SWIPT receiver parameters, a great performance gain can be achieved for both PS-TWR and TS-TWR. Moreover, the optimized PS-TWR always outperforms the optimized TS-TWR in terms of outage performance. Additionally, the effects of parameters including relay location and transmit powers are also discussed, which provide some insights for the SWIPT-enabled two-way relay networks.
International Nuclear Information System (INIS)
Frolov, A.M.
1986-01-01
Exact variational calculations are treated for few-particle systems in the exponential basis of relative coordinates using nonlinear parameters. The methods of step-by-step optimization and global chaos of nonlinear parameters are applied to calculate the S and P states of ppμ, ddμ, ttμ homonuclear mesomolecules within the error ≤±0.001 eV. The global chaos method turned out to be well applicable to nuclear 3 H and 3 He systems
Energy Technology Data Exchange (ETDEWEB)
Frolov, A M
1986-09-01
Exact variational calculations are treated for few-particle systems in the exponential basis of relative coordinates using nonlinear parameters. The methods of step-by-step optimization and global chaos of nonlinear parameters are applied to calculate the S and P states of pp..mu.., dd..mu.., tt..mu.. homonuclear mesomolecules within the error less than or equal to+-0.001 eV. The global chaos method turned out to be well applicable to nuclear /sup 3/H and /sup 3/He systems.
Numerical optimization of the ramp-down phase with the RAPTOR code
Teplukhina, Anna; Sauter, Olivier; Felici, Federico; The Tcv Team; The ASDEX-Upgrade Team; The Eurofusion Mst1 Team
2017-10-01
The ramp-down optimization goal in this work is defined as the fastest possible decrease of a plasma current while avoiding any disruptions caused by reaching physical or technical limits. Numerical simulations and preliminary experiments on TCV and AUG have shown that a fast decrease of plasma elongation and an adequate timing of the H-L transition during current ramp-down can help to avoid reaching high values of the plasma internal inductance. The RAPTOR code (F. Felici et al., 2012 PPCF 54; F. Felici, 2011 EPFL PhD thesis), developed for real-time plasma control, has been used for an optimization problem solving. Recently the transport model has been extended to include the ion temperature and electron density transport equations in addition to the electron temperature and current density transport equations, increasing the physical applications of the code. The gradient-based models for the transport coefficients (O. Sauter et al., 2014 PPCF 21; D. Kim et al., 2016 PPCF 58) have been implemented to RAPTOR and tested during this work. Simulations of the AUG and TCV entire plasma discharges will be presented. See the author list of S. Coda et al., Nucl. Fusion 57 2017 102011.
SPEXTRA: Optimal extraction code for long-slit spectra in crowded fields
Sarkisyan, A. N.; Vinokurov, A. S.; Solovieva, Yu. N.; Sholukhova, O. N.; Kostenkov, A. E.; Fabrika, S. N.
2017-10-01
We present a code for the optimal extraction of long-slit 2D spectra in crowded stellar fields. Its main advantage and difference from the existing spectrum extraction codes is the presence of a graphical user interface (GUI) and a convenient visualization system of data and extraction parameters. On the whole, the package is designed to study stars in crowded fields of nearby galaxies and star clusters in galaxies. Apart from the spectrum extraction for several stars which are closely located or superimposed, it allows the spectra of objects to be extracted with subtraction of superimposed nebulae of different shapes and different degrees of ionization. The package can also be used to study single stars in the case of a strong background. In the current version, the optimal extraction of 2D spectra with an aperture and the Gaussian function as PSF (point spread function) is proposed. In the future, the package will be supplemented with the possibility to build a PSF based on a Moffat function. We present the details of GUI, illustrate main features of the package, and show results of extraction of the several interesting spectra of objects from different telescopes.
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.
Tutcuoglu, A.; Majidi, C.
2014-12-01
Using principles of damped harmonic oscillation with continuous media, we examine electrostatic energy harvesting with a "soft-matter" array of dielectric elastomer (DE) transducers. The array is composed of infinitely thin and deformable electrodes separated by layers of insulating elastomer. During vibration, it deforms longitudinally, resulting in a change in the capacitance and electrical enthalpy of the charged electrodes. Depending on the phase of electrostatic loading, the DE array can function as either an actuator that amplifies small vibrations or a generator that converts these external excitations into electrical power. Both cases are addressed with a comprehensive theory that accounts for the influence of viscoelasticity, dielectric breakdown, and electromechanical coupling induced by Maxwell stress. In the case of a linearized Kelvin-Voigt model of the dielectric, we obtain a closed-form estimate for the electrical power output and a scaling law for DE generator design. For the complete nonlinear model, we obtain the optimal electrostatic voltage input for maximum electrical power output.
Kong, Liang; Gu, Zexu; Li, Tao; Wu, Junjie; Hu, Kaijin; Liu, Yanpu; Zhou, Hongzhi; Liu, Baolin
2009-01-01
A nonlinear finite element method was applied to examine the effects of implant diameter and length on the maximum von Mises stresses in the jaw, and to evaluate the maximum displacement of the implant-abutment complex in immediate-loading models. The implant diameter (D) ranged from 3.0 to 5.0 mm and implant length (L) ranged from 6.0 to 16.0 mm. The results showed that the maximum von Mises stress in cortical bone was decreased by 65.8% under a buccolingual load with an increase in D. In cancellous bone, it was decreased by 71.5% under an axial load with an increase in L. The maximum displacement in the implant-abutment complex decreased by 64.8% under a buccolingual load with an increase in D. The implant was found to be more sensitive to L than to D under axial loads, while D played a more important role in enhancing its stability under buccolingual loads. When D exceeded 4.0 mm and L exceeded 11.0 mm, both minimum stress and displacement were obtained. Therefore, these dimensions were the optimal biomechanical selections for immediate-loading implants in type B/2 bone.
The nurse scheduling problem: a goal programming and nonlinear optimization approaches
Hakim, L.; Bakhtiar, T.; Jaharuddin
2017-01-01
Nurses scheduling is an activity of allocating nurses to conduct a set of tasks at certain room at a hospital or health centre within a certain period. One of obstacles in the nurse scheduling is the lack of resources in order to fulfil the needs of the hospital. Nurse scheduling which is undertaken manually will be at risk of not fulfilling some nursing rules set by the hospital. Therefore, this study aimed to perform scheduling models that satisfy all the specific rules set by the management of Bogor State Hospital. We have developed three models to overcome the scheduling needs. Model 1 is designed to schedule nurses who are solely assigned to a certain inpatient unit and Model 2 is constructed to manage nurses who are assigned to an inpatient room as well as at Polyclinic room as conjunct nurses. As the assignment of nurses on each shift is uneven, then we propose Model 3 to minimize the variance of the workload in order to achieve equitable assignment on every shift. The first two models are formulated in goal programming framework, while the last model is in nonlinear optimization form.
International Nuclear Information System (INIS)
Liolios, A.A.; Boglou, A.K.
2003-01-01
The paper presents a new numerical approach for a non-linear optimal control problem arising in earthquake civil engineering. This problem concerns the elastoplastic softening-fracturing unilateral contact between neighbouring buildings during earthquakes when Coulomb friction is taken into account under second-order instabilizing effects. So, the earthquake response of the adjacent structures can appear instabilities and chaotic behaviour. The problem formulation presented here leads to a set of equations and inequalities, which is equivalent to a dynamic hemivariational inequality in the way introduced by Panagiotopoulos [Hemivariational Inequalities. Applications in Mechanics and Engineering, Springer-Verlag, Berlin, 1993]. The numerical procedure is based on an incremental problem formulation and on a double discretization, in space by the finite element method and in time by the Wilson-θ method. The generally non-convex constitutive contact laws are piecewise linearized, and in each time-step a non-convex linear complementarity problem is solved with a reduced number of unknowns
Hariharan, M; Sindhu, R; Vijean, Vikneswaran; Yazid, Haniza; Nadarajaw, Thiyagar; Yaacob, Sazali; Polat, Kemal
2018-03-01
Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition and autism, etc.) of an infant and therefore suited for early diagnosis. In this work, combination of wavelet packet based features and Improved Binary Dragonfly Optimization based feature selection method was proposed to classify the different types of infant cry signals. Cry signals from 2 different databases were utilized. First database contains 507 cry samples of normal (N), 340 cry samples of asphyxia (A), 879 cry samples of deaf (D), 350 cry samples of hungry (H) and 192 cry samples of pain (P). Second database contains 513 cry samples of jaundice (J), 531 samples of premature (Prem) and 45 samples of normal (N). Wavelet packet transform based energy and non-linear entropies (496 features), Linear Predictive Coding (LPC) based cepstral features (56 features), Mel-frequency Cepstral Coefficients (MFCCs) were extracted (16 features). The combined feature set consists of 568 features. To overcome the curse of dimensionality issue, improved binary dragonfly optimization algorithm (IBDFO) was proposed to select the most salient attributes or features. Finally, Extreme Learning Machine (ELM) kernel classifier was used to classify the different types of infant cry signals using all the features and highly informative features as well. Several experiments of two-class and multi-class classification of cry signals were conducted. In binary or two-class experiments, maximum accuracy of 90.18% for H Vs P, 100% for A Vs N, 100% for D Vs N and 97.61% J Vs Prem was achieved using the features selected (only 204 features out of 568) by IBDFO. For the classification of multiple cry signals (multi-class problem), the selected features could differentiate between three classes (N, A & D) with the accuracy of 100% and seven classes with the accuracy of 97.62%. The experimental
Energy Technology Data Exchange (ETDEWEB)
Lima, Alan M.M. de; Freire, Fernando S.; Nicolau, Andressa S.; Schirru, Roberto, E-mail: alan@lmp.ufrj.br, E-mail: andressa@lmp.ufrj.br, E-mail: schirru@lmp.ufrj.br, E-mail: ffreire@eletronuclear.gov.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (PEN/COPPE/UFRJ), Rio de Janeiro, RJ (Brazil); Eletrobras Termonuclear S.A. (ELETRONUCLEAR), Rio de Janeiro, RJ (Brazil)
2017-11-01
The Nuclear reload of a Pressurized Water Reactor (PWR) occurs whenever the burning of the fuel elements can no longer maintain the criticality of the reactor, that is, it cannot maintain the Nuclear power plant operates within its nominal power. Nuclear reactor reload optimization problem consists of finding a loading pattern of fuel assemblies in the reactor core in order to minimize the cost/benefit ratio, trying to obtain maximum power generation with a minimum of cost, since in all reloads an average of one third of the new fuel elements are purchased. This loading pattern must also satisfy constraints of symmetry and security. In practice, it consists of the placing 121 fuel elements in 121 core positions, in the case of the Angra 1 Brazilian Nuclear Power Plant (NPP), making this new arrangement provide the best cost/benefit ratio. It is an extremely complex problem, since it has around 1% of great places. A core of 121 fuel elements has approximately 10{sup 13} combinations and 10{sup 11} great locations. With this number of possible combinations it is impossible to test all, in order to choose the best. In this work a system called ACO-GENES is proposed in order to optimization the Nuclear Reactor Reload Problem. ACO is successfully used in combination problems, and it is expected that ACO-GENES will show a robust optimization system, since in addition to optimizing ACO, it allows important prior knowledge such as K infinite, burn, etc. After optimization by ACO-GENES, the best results will be validated by a licensed reactor physics code and will be compared with the actual results of the cycle. (author)
International Nuclear Information System (INIS)
Lima, Alan M.M. de; Freire, Fernando S.; Nicolau, Andressa S.; Schirru, Roberto
2017-01-01
The Nuclear reload of a Pressurized Water Reactor (PWR) occurs whenever the burning of the fuel elements can no longer maintain the criticality of the reactor, that is, it cannot maintain the Nuclear power plant operates within its nominal power. Nuclear reactor reload optimization problem consists of finding a loading pattern of fuel assemblies in the reactor core in order to minimize the cost/benefit ratio, trying to obtain maximum power generation with a minimum of cost, since in all reloads an average of one third of the new fuel elements are purchased. This loading pattern must also satisfy constraints of symmetry and security. In practice, it consists of the placing 121 fuel elements in 121 core positions, in the case of the Angra 1 Brazilian Nuclear Power Plant (NPP), making this new arrangement provide the best cost/benefit ratio. It is an extremely complex problem, since it has around 1% of great places. A core of 121 fuel elements has approximately 10"1"3 combinations and 10"1"1 great locations. With this number of possible combinations it is impossible to test all, in order to choose the best. In this work a system called ACO-GENES is proposed in order to optimization the Nuclear Reactor Reload Problem. ACO is successfully used in combination problems, and it is expected that ACO-GENES will show a robust optimization system, since in addition to optimizing ACO, it allows important prior knowledge such as K infinite, burn, etc. After optimization by ACO-GENES, the best results will be validated by a licensed reactor physics code and will be compared with the actual results of the cycle. (author)
A finite element code for electric motor design
Campbell, C. Warren
1994-01-01
FEMOT is a finite element program for solving the nonlinear magnetostatic problem. This version uses nonlinear, Newton first order elements. The code can be used for electric motor design and analysis. FEMOT can be embedded within an optimization code that will vary nodal coordinates to optimize the motor design. The output from FEMOT can be used to determine motor back EMF, torque, cogging, and magnet saturation. It will run on a PC and will be available to anyone who wants to use it.
International Nuclear Information System (INIS)
Chang, Ying-Pin
2010-01-01
A particle-swarm optimization method with nonlinear time-varying evolution (PSO-NTVE) is employed in determining the tilt angle of photovoltaic (PV) modules in Taiwan. The objective is to maximize the output electrical energy of the modules. In this study, seven Taiwanese cities were selected for analysis. First, the sun's position at any time and location was predicted by the mathematical procedure of Julian dating, and then the solar irradiation was obtained at each site under a clear sky. By combining the temperature effect, the PSO-NTVE method is adopted to calculate the optimal tilt angles for fixed south-facing PV modules. In this method, the parameters are determined by using matrix experiments with an orthogonal array, in which a minimal number of experiments have an effect that approximates the full factorial experiments. Statistical error analysis was performed to compare the results between the four PSO methods and experimental results. Hengchun city in which the minimum total error value of 6.12% the reasons for the weather more stability and less building shade. A comparison of the measurement results in electrical energy between the four PSO methods and the PV modules set a six tilt angles. Obviously four types of PSO methods simulation of electrical energy value from 231.12 kWh/m 2 for Taipei to 233.81 kWh/m 2 for Hengchun greater than the measurement values from 224.71 kWh/m 2 for Taichung to 228.47 kWh/m 2 for Hengchun by PV module which is due to instability caused by climate change. Finally, the results show that the annual optimal angle for the Taipei area is 18.16 o ; for Taichung, 17.3 o ; for Tainan, 16.15 o ; for Kaosiung, 15.79 o ; for Hengchung, 15.17 o ; for Hualian, 17.16 o ; and for Taitung, 15.94 o . It is evident that the authorized Industrial Technology Research Institute (ITRI) recommends that tilt angle of 23.5 o was not an appropriate use of Taiwan's seven cities. PV modules with the installation of the tilt angle should be
Yang, Qin; Zou, Hong-Yan; Zhang, Yan; Tang, Li-Juan; Shen, Guo-Li; Jiang, Jian-Hui; Yu, Ru-Qin
2016-01-15
Most of the proteins locate more than one organelle in a cell. Unmixing the localization patterns of proteins is critical for understanding the protein functions and other vital cellular processes. Herein, non-linear machine learning technique is proposed for the first time upon protein pattern unmixing. Variable-weighted support vector machine (VW-SVM) is a demonstrated robust modeling technique with flexible and rational variable selection. As optimized by a global stochastic optimization technique, particle swarm optimization (PSO) algorithm, it makes VW-SVM to be an adaptive parameter-free method for automated unmixing of protein subcellular patterns. Results obtained by pattern unmixing of a set of fluorescence microscope images of cells indicate VW-SVM as optimized by PSO is able to extract useful pattern features by optimally rescaling each variable for non-linear SVM modeling, consequently leading to improved performances in multiplex protein pattern unmixing compared with conventional SVM and other exiting pattern unmixing methods. Copyright © 2015 Elsevier B.V. All rights reserved.
Miró, Anton; Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Egea, Jose A; Jiménez, Laureano
2012-05-10
The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are usually classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens. This work presents a deterministic outer approximation-based algorithm for the global optimization of dynamic problems arising in the parameter estimation of models of biological systems. Our approach, which offers a theoretical guarantee of convergence to global minimum, is based on reformulating the set of ordinary differential equations into an equivalent set of algebraic equations through the use of orthogonal collocation methods, giving rise to a nonconvex nonlinear programming (NLP) problem. This nonconvex NLP is decomposed into two hierarchical levels: a master mixed-integer linear programming problem (MILP) that provides a rigorous lower bound on the optimal solution, and a reduced-space slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied. The capabilities of our approach were tested in two benchmark problems, in which the performance of our algorithm was compared with that of the commercial global optimization package BARON. The proposed strategy produced near optimal solutions (i.e., within a desired tolerance) in a fraction of the CPU time required by BARON.
Optimization of Nonlinear Figure-of-Merits of Integrated Power MOSFETs in Partial SOI Process
DEFF Research Database (Denmark)
Fan, Lin; Jørgensen, Ivan Harald Holger; Knott, Arnold
2016-01-01
State-of-the-art power semiconductor industry uses figure-of-merits (FOMs) for technology-to-technology and/or device-to-device comparisons. However, the existing FOMs are fundamentally nonlinear due to the nonlinearities of the parameters such as the gate charge and the output charge versus...
Adaptive Optimizing Nonlinear Control Design for an Over-actuated Aircraft Model
Van Oort, E.R.; Sonneveldt, L.; Chu, Q.P.; Mulder, J.A.
2011-01-01
In this paper nonlinear adaptive flight control laws based on the backstepping approach are proposed which are applicable to over-actuated nonlinear systems. Instead of solving the control allocation exactly, update laws for the desired control effector signals are defined such that they converge to
OPT13B and OPTIM4 - computer codes for optical model calculations
International Nuclear Information System (INIS)
Pal, S.; Srivastava, D.K.; Mukhopadhyay, S.; Ganguly, N.K.
1975-01-01
OPT13B is a computer code in FORTRAN for optical model calculations with automatic search. A summary of different formulae used for computation is given. Numerical methods are discussed. The 'search' technique followed to obtain the set of optical model parameters which produce best fit to experimental data in a least-square sense is also discussed. Different subroutines of the program are briefly described. Input-output specifications are given in detail. A modified version of OPT13B specifications are given in detail. A modified version of OPT13B is OPTIM4. It can be used for optical model calculations where the form factors of different parts of the optical potential are known point by point. A brief description of the modifications is given. (author)
Directory of Open Access Journals (Sweden)
Jens G. Balchen
1984-10-01
Full Text Available The problem of systematic derivation of a quasi-dynamic optimal control strategy for a non-linear dynamic process based upon a non-quadratic objective function is investigated. The wellknown LQG-control algorithm does not lead to an optimal solution when the process disturbances have non-zero mean. The relationships between the proposed control algorithm and LQG-control are presented. The problem of how to constrain process variables by means of 'penalty' - terms in the objective function is dealt with separately.
Directory of Open Access Journals (Sweden)
Jing Lei
2013-01-01
Full Text Available The paper considers the problem of variable structure control for nonlinear systems with uncertainty and time delays under persistent disturbance by using the optimal sliding mode surface approach. Through functional transformation, the original time-delay system is transformed into a delay-free one. The approximating sequence method is applied to solve the nonlinear optimal sliding mode surface problem which is reduced to a linear two-point boundary value problem of approximating sequences. The optimal sliding mode surface is obtained from the convergent solutions by solving a Riccati equation, a Sylvester equation, and the state and adjoint vector differential equations of approximating sequences. Then, the variable structure disturbance rejection control is presented by adopting an exponential trending law, where the state and control memory terms are designed to compensate the state and control delays, a feedforward control term is designed to reject the disturbance, and an adjoint compensator is designed to compensate the effects generated by the nonlinearity and the uncertainty. Furthermore, an observer is constructed to make the feedforward term physically realizable, and thus the dynamical observer-based dynamical variable structure disturbance rejection control law is produced. Finally, simulations are demonstrated to verify the effectiveness of the presented controller and the simplicity of the proposed approach.
El-Khoury, O.; Kim, C.; Shafieezadeh, A.; Hur, J. E.; Heo, G. H.
2015-06-01
This study performs a series of numerical simulations and shake-table experiments to design and assess the performance of a nonlinear clipped feedback control algorithm based on optimal polynomial control (OPC) to mitigate the response of a two-span bridge equipped with a magnetorheological (MR) damper. As an extended conventional linear quadratic regulator, OPC provides more flexibility in the control design and further enhances system performance. The challenges encountered in this case are (1) the linearization of the nonlinear behavior of various components and (2) the selection of the weighting matrices in the objective function of OPC. The first challenge is addressed by using stochastic linearization which replaces the nonlinear portion of the system behavior with an equivalent linear time-invariant model considering the stochasticity in the excitation. Furthermore, a genetic algorithm is employed to find optimal weighting matrices for the control design. The input current to the MR damper installed between adjacent spans is determined using a clipped stochastic optimal polynomial control algorithm. The performance of the controlled system is assessed through a set of shake-table experiments for far-field and near-field ground motions. The proposed method showed considerable improvements over passive cases especially for the far-field ground motion.
International Nuclear Information System (INIS)
El-Khoury, O; Shafieezadeh, A; Hur, J E; Kim, C; Heo, G H
2015-01-01
This study performs a series of numerical simulations and shake-table experiments to design and assess the performance of a nonlinear clipped feedback control algorithm based on optimal polynomial control (OPC) to mitigate the response of a two-span bridge equipped with a magnetorheological (MR) damper. As an extended conventional linear quadratic regulator, OPC provides more flexibility in the control design and further enhances system performance. The challenges encountered in this case are (1) the linearization of the nonlinear behavior of various components and (2) the selection of the weighting matrices in the objective function of OPC. The first challenge is addressed by using stochastic linearization which replaces the nonlinear portion of the system behavior with an equivalent linear time-invariant model considering the stochasticity in the excitation. Furthermore, a genetic algorithm is employed to find optimal weighting matrices for the control design. The input current to the MR damper installed between adjacent spans is determined using a clipped stochastic optimal polynomial control algorithm. The performance of the controlled system is assessed through a set of shake-table experiments for far-field and near-field ground motions. The proposed method showed considerable improvements over passive cases especially for the far-field ground motion. (paper)
Solution of optimization problems by means of the CASTEM 2000 computer code
International Nuclear Information System (INIS)
Charras, Th.; Millard, A.; Verpeaux, P.
1991-01-01
In the nuclear industry, it can be necessary to use robots for operation in contaminated environment. Most of the time, positioning of some parts of the robot must be very accurate, which highly depends on the structural (mass and stiffness) properties of its various components. Therefore, there is a need for a 'best' design, which is a compromise between technical (mechanical properties) and economical (material quantities, design and manufacturing cost) matters. This is precisely the aim of optimization techniques, in the frame of structural analysis. A general statement of this problem could be as follows: find the set of parameters which leads to the minimum of a given function, and satisfies some constraints. For example, in the case of a robot component, the parameters can be some geometrical data (plate thickness, ...), the function can be the weight and the constraints can consist in design criteria like a given stiffness and in some manufacturing technological constraints (minimum available thickness, etc). For nuclear industry purposes, a robust method was chosen and implemented in the new generation computer code CASTEM 2000. The solution of the optimum design problem is obtained by solving a sequence of convex subproblems, in which the various functions (the function to minimize and the constraints) are transformed by convex linearization. The method has been programmed in the case of continuous as well as discrete variables. According to the highly modular architecture of the CASTEM 2000 code, only one new operation had to be introduced: the solution of a sub problem with convex linearized functions, which is achieved by means of a conjugate gradient technique. All other operations were already available in the code, and the overall optimum design is realized by means of the Gibiane language. An example of application will be presented to illustrate the possibilities of the method. (author)
Core design optimization by integration of a fast 3-D nodal code in a heuristic search procedure
Energy Technology Data Exchange (ETDEWEB)
Geemert, R. van; Leege, P.F.A. de; Hoogenboom, J.E.; Quist, A.J. [Delft University of Technology, NL-2629 JB Delft (Netherlands)
1998-07-01
An automated design tool is being developed for the Hoger Onderwijs Reactor (HOR) in Delft, the Netherlands, which is a 2 MWth swimming-pool type research reactor. As a black box evaluator, the 3-D nodal code SILWER, which up to now has been used only for evaluation of predetermined core designs, is integrated in the core optimization procedure. SILWER is a part of PSl's ELCOS package and features optional additional thermal-hydraulic, control rods and xenon poisoning calculations. This allows for fast and accurate evaluation of different core designs during the optimization search. Special attention is paid to handling the in- and output files for SILWER such that no adjustment of the code itself is required for its integration in the optimization programme. The optimization objective, the safety and operation constraints, as well as the optimization procedure, are discussed. (author)
Core design optimization by integration of a fast 3-D nodal code in a heuristic search procedure
International Nuclear Information System (INIS)
Geemert, R. van; Leege, P.F.A. de; Hoogenboom, J.E.; Quist, A.J.
1998-01-01
An automated design tool is being developed for the Hoger Onderwijs Reactor (HOR) in Delft, the Netherlands, which is a 2 MWth swimming-pool type research reactor. As a black box evaluator, the 3-D nodal code SILWER, which up to now has been used only for evaluation of predetermined core designs, is integrated in the core optimization procedure. SILWER is a part of PSl's ELCOS package and features optional additional thermal-hydraulic, control rods and xenon poisoning calculations. This allows for fast and accurate evaluation of different core designs during the optimization search. Special attention is paid to handling the in- and output files for SILWER such that no adjustment of the code itself is required for its integration in the optimization programme. The optimization objective, the safety and operation constraints, as well as the optimization procedure, are discussed. (author)
Development of hydraulic analysis code for optimizing thermo-chemical is process reactors
International Nuclear Information System (INIS)
Terada, Atsuhiko; Hino, Ryutaro; Hirayama, Toshio; Nakajima, Norihiro; Sugiyama, Hitoshi
2007-01-01
The Japan Atomic Energy Agency has been conducting study on thermochemical IS process for water splitting hydrogen production. Based on the test results and know-how obtained through the bench-scale test, a pilot test plant, which has a hydrogen production performance of 30 Nm 3 /h, is being designed conceptually as the next step of the IS process development. In design of the IS pilot plant, it is important to make chemical reactors compact with high performance from the viewpoint of plant cost reduction. A new hydraulic analytical code has been developed for optimizing mixing performance of multi-phase flow involving chemical reactions especially in the Bunsen reactor. Complex flow pattern with gas-liquid chemical interaction involving flow instability will be characterized in the Bunsen reactor. Preliminary analytical results obtained with above mentioned code, especially flow patterns induced by swirling flow agreed well with that measured by water experiments, which showed vortex breakdown pattern in a simplified Bunsen reactor. (author)
The role of stochasticity in an information-optimal neural population code
International Nuclear Information System (INIS)
Stocks, N G; Nikitin, A P; McDonnell, M D; Morse, R P
2009-01-01
In this paper we consider the optimisation of Shannon mutual information (MI) in the context of two model neural systems. The first is a stochastic pooling network (population) of McCulloch-Pitts (MP) type neurons (logical threshold units) subject to stochastic forcing; the second is (in a rate coding paradigm) a population of neurons that each displays Poisson statistics (the so called 'Poisson neuron'). The mutual information is optimised as a function of a parameter that characterises the 'noise level'-in the MP array this parameter is the standard deviation of the noise; in the population of Poisson neurons it is the window length used to determine the spike count. In both systems we find that the emergent neural architecture and, hence, code that maximises the MI is strongly influenced by the noise level. Low noise levels leads to a heterogeneous distribution of neural parameters (diversity), whereas, medium to high noise levels result in the clustering of neural parameters into distinct groups that can be interpreted as subpopulations. In both cases the number of subpopulations increases with a decrease in noise level. Our results suggest that subpopulations are a generic feature of an information optimal neural population.
The role of stochasticity in an information-optimal neural population code
Energy Technology Data Exchange (ETDEWEB)
Stocks, N G; Nikitin, A P [School of Engineering, University of Warwick, Coventry CV4 7AL (United Kingdom); McDonnell, M D [Institute for Telecommunications Research, University of South Australia, SA 5095 (Australia); Morse, R P, E-mail: n.g.stocks@warwick.ac.u [School of Life and Health Sciences, Aston University, Birmingham B4 7ET (United Kingdom)
2009-12-01
In this paper we consider the optimisation of Shannon mutual information (MI) in the context of two model neural systems. The first is a stochastic pooling network (population) of McCulloch-Pitts (MP) type neurons (logical threshold units) subject to stochastic forcing; the second is (in a rate coding paradigm) a population of neurons that each displays Poisson statistics (the so called 'Poisson neuron'). The mutual information is optimised as a function of a parameter that characterises the 'noise level'-in the MP array this parameter is the standard deviation of the noise; in the population of Poisson neurons it is the window length used to determine the spike count. In both systems we find that the emergent neural architecture and, hence, code that maximises the MI is strongly influenced by the noise level. Low noise levels leads to a heterogeneous distribution of neural parameters (diversity), whereas, medium to high noise levels result in the clustering of neural parameters into distinct groups that can be interpreted as subpopulations. In both cases the number of subpopulations increases with a decrease in noise level. Our results suggest that subpopulations are a generic feature of an information optimal neural population.
Ramezanpour, H R; Setayeshi, S; Akbari, M E
2011-01-01
Determining the optimal and effective scheme for administrating the chemotherapy agents in breast cancer is the main goal of this scientific research. The most important issue here is the amount of drug or radiation administrated in chemotherapy and radiotherapy for increasing patient's survival. This is because in these cases, the therapy not only kills the tumor cells, but also kills some of the healthy tissues and causes serious damages. In this paper we investigate optimal drug scheduling effect for breast cancer model which consist of nonlinear ordinary differential time-delay equations. In this paper, a mathematical model of breast cancer tumors is discussed and then optimal control theory is applied to find out the optimal drug adjustment as an input control of system. Finally we use Sensitivity Approach (SA) to solve the optimal control problem. The goal of this paper is to determine optimal and effective scheme for administering the chemotherapy agent, so that the tumor is eradicated, while the immune systems remains above a suitable level. Simulation results confirm the effectiveness of our proposed procedure. In this paper a new scheme is proposed to design a therapy protocol for chemotherapy in Breast Cancer. In contrast to traditional pulse drug delivery, a continuous process is offered and optimized, according to the optimal control theory for time-delay systems.
Performance of a Nonlinear Real-Time Optimal Control System for HEVs/PHEVs during Car Following
Directory of Open Access Journals (Sweden)
Kaijiang Yu
2014-01-01
Full Text Available This paper presents a real-time optimal control approach for the energy management problem of hybrid electric vehicles (HEVs and plug-in hybrid electric vehicles (PHEVs with slope information during car following. The new features of this study are as follows. First, the proposed method can optimize the engine operating points and the driving profile simultaneously. Second, the proposed method gives the freedom of vehicle spacing between the preceding vehicle and the host vehicle. Third, using the HEV/PHEV property, the desired battery state of charge is designed according to the road slopes for better recuperation of free braking energy. Fourth, all of the vehicle operating modes engine charge, electric vehicle, motor assist and electric continuously variable transmission, and regenerative braking, can be realized using the proposed real-time optimal control approach. Computer simulation results are shown among the nonlinear real-time optimal control approach and the ADVISOR rule-based approach. The conclusion is that the nonlinear real-time optimal control approach is effective for the energy management problem of the HEV/PHEV system during car following.
International Nuclear Information System (INIS)
Zhang, Jianyun; Liu, Pei; Zhou, Zhe; Ma, Linwei; Li, Zheng; Ni, Weidou
2014-01-01
Highlights: • Integration of heat streams with HRSG in a polygeneration system is studied. • A mixed-integer nonlinear programming model is proposed to optimize heat network. • Operating parameters and heat network configuration are optimized simultaneously. • The optimized heat network highly depends on the HRSG type and model specification. - Abstract: A large number of heat flows at various temperature and pressure levels exist in a polygeneration plant which co-produces electricity and chemical products. Integration of these external heat flows in a heat recovery steam generator (HRSG) has great potential to further enhance energy efficiency of such a plant; however, it is a challenging problem arising from the large design space of heat exchanger network. In this paper, a mixed-integer nonlinear programming model is developed for the design optimization of a HRSG with consideration of all alternative matches between the HRSG and external heat flows. This model is applied to four polygeneration cases with different HRSG types, and results indicate that the optimized heat network mainly depends on the HRSG type and the model specification
International Nuclear Information System (INIS)
Jaafar, Hazriq Izzuan; Ali, Nursabillilah Mohd; Selamat, Nur Asmiza; Kassim, Anuar Mohamed; Mohamed, Z; Abidin, Amar Faiz Zainal; Jamian, J J
2013-01-01
This paper presents development of an optimal PID and PD controllers for controlling the nonlinear gantry crane system. The proposed Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is adopted in obtaining five optimal controller gains. The optimal gains are tested on a control structure that combines PID and PD controllers to examine system responses including trolley displacement and payload oscillation. The dynamic model of gantry crane system is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of system in terms of settling time (Ts), steady state error (SSE) and overshoot (OS). This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the various desired position
Directory of Open Access Journals (Sweden)
Ray Richard Paul
2015-09-01
Full Text Available Geotechnical and structural engineers are faced with a difficult task when their designs interact with each other. For complex projects, this is more the norm than the exception. In order to help bridge that gap, a method for modeling the behavior of a foundation using a simple elasto-plastic subgrade reaction was developed. The method uses an optimization technique to position 4-6 springs along a pile foundation to produce similar load deflection characteristics that were modeled by more sophisticated geotechnical finite element software. The methodology uses an Excel spreadsheet for accepting user input and delivering an optimized subgrade spring stiffness, yield, and position along the pile. In this way, the behavior developed from the geotechnical software can be transferred to the structural analysis software. The optimization is achieved through the solver add-in within Excel. Additionally, a beam on a nonlinear elastic foundation model is used to compute deflections of the optimized subgrade reaction configuration.
Zhu, Yuanheng; Zhao, Dongbin; Yang, Xiong; Zhang, Qichao
2018-02-01
Sum of squares (SOS) polynomials have provided a computationally tractable way to deal with inequality constraints appearing in many control problems. It can also act as an approximator in the framework of adaptive dynamic programming. In this paper, an approximate solution to the optimal control of polynomial nonlinear systems is proposed. Under a given attenuation coefficient, the Hamilton-Jacobi-Isaacs equation is relaxed to an optimization problem with a set of inequalities. After applying the policy iteration technique and constraining inequalities to SOS, the optimization problem is divided into a sequence of feasible semidefinite programming problems. With the converged solution, the attenuation coefficient is further minimized to a lower value. After iterations, approximate solutions to the smallest -gain and the associated optimal controller are obtained. Four examples are employed to verify the effectiveness of the proposed algorithm.
Language Recognition via Sparse Coding
2016-09-08
explanation is that sparse coding can achieve a near-optimal approximation of much complicated nonlinear relationship through local and piecewise linear...training examples, where x(i) ∈ RN is the ith example in the batch. Optionally, X can be normalized and whitened before sparse coding for better result...normalized input vectors are then ZCA- whitened [20]. Em- pirically, we choose ZCA- whitening over PCA- whitening , and there is no dimensionality reduction
An optimized cosine-modulated nonuniform filter bank design for subband coding of ECG signal
Directory of Open Access Journals (Sweden)
A. Kumar
2015-07-01
Full Text Available A simple iterative technique for the design of nonuniform cosine modulated filter banks (CMFBS is presented in this paper. The proposed technique employs a single parameter for optimization. The nonuniform cosine modulated filter banks are derived by merging the adjacent filters of uniform cosine modulated filter banks. The prototype filter is designed with the aid of different adjustable window functions such as Kaiser, Cosh and Exponential, and by using the constrained equiripple finite impulse response (FIR digital filter design technique. In this method, either cut off frequency or passband edge frequency is varied in order to adjust the filter coefficients so that reconstruction error could be optimized/minimized to zero. Performance and effectiveness of the proposed method in terms of peak reconstruction error (PRE, aliasing distortion (AD, computational (CPU time, and number of iteration (NOI have been shown through the numerical examples and comparative studies. Finally, the technique is exploited for the subband coding of electrocardiogram (ECG and speech signals.
Stereoscopic Visual Attention-Based Regional Bit Allocation Optimization for Multiview Video Coding
Directory of Open Access Journals (Sweden)
Dai Qionghai
2010-01-01
Full Text Available We propose a Stereoscopic Visual Attention- (SVA- based regional bit allocation optimization for Multiview Video Coding (MVC by the exploiting visual redundancies from human perceptions. We propose a novel SVA model, where multiple perceptual stimuli including depth, motion, intensity, color, and orientation contrast are utilized, to simulate the visual attention mechanisms of human visual system with stereoscopic perception. Then, a semantic region-of-interest (ROI is extracted based on the saliency maps of SVA. Both objective and subjective evaluations of extracted ROIs indicated that the proposed SVA model based on ROI extraction scheme outperforms the schemes only using spatial or/and temporal visual attention clues. Finally, by using the extracted SVA-based ROIs, a regional bit allocation optimization scheme is presented to allocate more bits on SVA-based ROIs for high image quality and fewer bits on background regions for efficient compression purpose. Experimental results on MVC show that the proposed regional bit allocation algorithm can achieve over % bit-rate saving while maintaining the subjective image quality. Meanwhile, the image quality of ROIs is improved by dB at the cost of insensitive image quality degradation of the background image.
Stilp, Christian E.; Kluender, Keith R.
2012-01-01
To the extent that sensorineural systems are efficient, redundancy should be extracted to optimize transmission of information, but perceptual evidence for this has been limited. Stilp and colleagues recently reported efficient coding of robust correlation (r = .97) among complex acoustic attributes (attack/decay, spectral shape) in novel sounds. Discrimination of sounds orthogonal to the correlation was initially inferior but later comparable to that of sounds obeying the correlation. These effects were attenuated for less-correlated stimuli (r = .54) for reasons that are unclear. Here, statistical properties of correlation among acoustic attributes essential for perceptual organization are investigated. Overall, simple strength of the principal correlation is inadequate to predict listener performance. Initial superiority of discrimination for statistically consistent sound pairs was relatively insensitive to decreased physical acoustic/psychoacoustic range of evidence supporting the correlation, and to more frequent presentations of the same orthogonal test pairs. However, increased range supporting an orthogonal dimension has substantial effects upon perceptual organization. Connectionist simulations and Eigenvalues from closed-form calculations of principal components analysis (PCA) reveal that perceptual organization is near-optimally weighted to shared versus unshared covariance in experienced sound distributions. Implications of reduced perceptual dimensionality for speech perception and plausible neural substrates are discussed. PMID:22292057
Directory of Open Access Journals (Sweden)
A. A. Kovylin
2013-01-01
Full Text Available The article describes the problem of searching for binary pseudo-random sequences with quasi-ideal autocorrelation function, which are to be used in contemporary communication systems, including mobile and wireless data transfer interfaces. In the synthesis of binary sequences sets, the target set is manning them based on the minimax criterion by which a sequence is considered to be optimal according to the intended application. In the course of the research the optimal sequences with order of up to 52 were obtained; the analysis of Run Length Encoding was carried out. The analysis showed regularities in the distribution of series number of different lengths in the codes that are optimal on the chosen criteria, which would make it possible to optimize the searching process for such codes in the future.
International Nuclear Information System (INIS)
Gao Fei; Gao Hongrui; Li Zhuoqiu; Tong Hengqing; Lee, Ju-Jang
2009-01-01
It is well known that set of unstable periodic orbits (UPOs) can be thought of as the skeleton for the dynamics. However, detecting UPOs of nonlinear map is one of the most challenging problems of nonlinear science in both numerical computations and experimental measures. In this paper, a new method is proposed to detect the UPOs in a non-Lyapunov way. Firstly three special techniques are added to quantum-behaved particle swarm optimization (QPSO), a novel mbest particle, contracting the searching space self-adaptively and boundaries restriction (NCB), then the new method NCB-QPSO is proposed. It can maintain an effective search mechanism with fine equilibrium between exploitation and exploration. Secondly, the problems of detecting the UPOs are converted into a non-negative functions' minimization through a proper translation in a non-Lyapunov way. Thirdly the simulations to 6 benchmark optimization problems and different high order UPOs of 5 classic nonlinear maps are done by the proposed method. And the results show that NCB-QPSO is a successful method in detecting the UPOs, and it has the advantages of fast convergence, high precision and robustness.
DEFF Research Database (Denmark)
Mirzadeh, Kiavash; Martinez, Virginia; Toddo, Stephen
2015-01-01
are poorly expressed even when they are codon-optimized and expressed from vectors with powerful genetic elements. In this study, we show that poor expression can be caused by certain nucleotide sequences (e.g., cloning scars) at the junction between the vector and the coding sequence. Since these sequences...
Nonlinear H∞ Optimal Control Scheme for an Underwater Vehicle with Regional Function Formulation
Directory of Open Access Journals (Sweden)
Zool H. Ismail
2013-01-01
Full Text Available A conventional region control technique cannot meet the demands for an accurate tracking performance in view of its inability to accommodate highly nonlinear system dynamics, imprecise hydrodynamic coefficients, and external disturbances. In this paper, a robust technique is presented for an Autonomous Underwater Vehicle (AUV with region tracking function. Within this control scheme, nonlinear H∞ and region based control schemes are used. A Lyapunov-like function is presented for stability analysis of the proposed control law. Numerical simulations are presented to demonstrate the performance of the proposed tracking control of the AUV. It is shown that the proposed control law is robust against parameter uncertainties, external disturbances, and nonlinearities and it leads to uniform ultimate boundedness of the region tracking error.
Błażej, Paweł; Wnȩtrzak, Małgorzata; Mackiewicz, Paweł
2016-12-01
One of theories explaining the present structure of canonical genetic code assumes that it was optimized to minimize harmful effects of amino acid replacements resulting from nucleotide substitutions and translational errors. A way to testify this concept is to find the optimal code under given criteria and compare it with the canonical genetic code. Unfortunately, the huge number of possible alternatives makes it impossible to find the optimal code using exhaustive methods in sensible time. Therefore, heuristic methods should be applied to search the space of possible solutions. Evolutionary algorithms (EA) seem to be ones of such promising approaches. This class of methods is founded both on mutation and crossover operators, which are responsible for creating and maintaining the diversity of candidate solutions. These operators possess dissimilar characteristics and consequently play different roles in the process of finding the best solutions under given criteria. Therefore, the effective searching for the potential solutions can be improved by applying both of them, especially when these operators are devised specifically for a given problem. To study this subject, we analyze the effectiveness of algorithms for various combinations of mutation and crossover probabilities under three models of the genetic code assuming different restrictions on its structure. To achieve that, we adapt the position based crossover operator for the most restricted model and develop a new type of crossover operator for the more general models. The applied fitness function describes costs of amino acid replacement regarding their polarity. Our results indicate that the usage of crossover operators can significantly improve the quality of the solutions. Moreover, the simulations with the crossover operator optimize the fitness function in the smaller number of generations than simulations without this operator. The optimal genetic codes without restrictions on their structure
Performance Modeling and Optimization of a High Energy CollidingBeam Simulation Code
Energy Technology Data Exchange (ETDEWEB)
Shan, Hongzhang; Strohmaier, Erich; Qiang, Ji; Bailey, David H.; Yelick, Kathy
2006-06-01
An accurate modeling of the beam-beam interaction is essential to maximizing the luminosity in existing and future colliders. BeamBeam3D was the first parallel code that can be used to study this interaction fully self-consistently on high-performance computing platforms. Various all-to-all personalized communication (AAPC) algorithms dominate its communication patterns, for which we developed a sequence of performance models using a series of micro-benchmarks. We find that for SMP based systems the most important performance constraint is node-adapter contention, while for 3D-Torus topologies good performance models are not possible without considering link contention. The best average model prediction error is very low on SMP based systems with of 3% to 7%. On torus based systems errors of 29% are higher but optimized performance can again be predicted within 8% in some cases. These excellent results across five different systems indicate that this methodology for performance modeling can be applied to a large class of algorithms.
Performance Modeling and Optimization of a High Energy Colliding Beam Simulation Code
International Nuclear Information System (INIS)
Shan, Hongzhang; Strohmaier, Erich; Qiang, Ji; Bailey, David H.; Yelick, Kathy
2006-01-01
An accurate modeling of the beam-beam interaction is essential to maximizing the luminosity in existing and future colliders. BeamBeam3D was the first parallel code that can be used to study this interaction fully self-consistently on high-performance computing platforms. Various all-to-all personalized communication (AAPC) algorithms dominate its communication patterns, for which we developed a sequence of performance models using a series of micro-benchmarks. We find that for SMP based systems the most important performance constraint is node-adapter contention, while for 3D-Torus topologies good performance models are not possible without considering link contention. The best average model prediction error is very low on SMP based systems with of 3% to 7%. On torus based systems errors of 29% are higher but optimized performance can again be predicted within 8% in some cases. These excellent results across five different systems indicate that this methodology for performance modeling can be applied to a large class of algorithms
Optimization of the Monte Carlo code for modeling of photon migration in tissue.
Zołek, Norbert S; Liebert, Adam; Maniewski, Roman
2006-10-01
The Monte Carlo method is frequently used to simulate light transport in turbid media because of its simplicity and flexibility, allowing to analyze complicated geometrical structures. Monte Carlo simulations are, however, time consuming because of the necessity to track the paths of individual photons. The time consuming computation is mainly associated with the calculation of the logarithmic and trigonometric functions as well as the generation of pseudo-random numbers. In this paper, the Monte Carlo algorithm was developed and optimized, by approximation of the logarithmic and trigonometric functions. The approximations were based on polynomial and rational functions, and the errors of these approximations are less than 1% of the values of the original functions. The proposed algorithm was verified by simulations of the time-resolved reflectance at several source-detector separations. The results of the calculation using the approximated algorithm were compared with those of the Monte Carlo simulations obtained with an exact computation of the logarithm and trigonometric functions as well as with the solution of the diffusion equation. The errors of the moments of the simulated distributions of times of flight of photons (total number of photons, mean time of flight and variance) are less than 2% for a range of optical properties, typical of living tissues. The proposed approximated algorithm allows to speed up the Monte Carlo simulations by a factor of 4. The developed code can be used on parallel machines, allowing for further acceleration.
International Nuclear Information System (INIS)
Dattoli, G.; Schiavi, A.; Migliorati, M.
2006-03-01
The coherent synchrotron radiation (CSR) is one of the main problems limiting the performance of high intensity electron accelerators. The complexity of the physical mechanisms underlying the onset of instabilities due to CSR demands for accurate descriptions, capable of including the large number of features of an actual accelerating device. A code devoted to the analysis of this type of problems should be fast and reliable, conditions that are usually hardly achieved at the same rime. In the past, codes based on Lie algebraic techniques , have been very efficient to treat transport problems in accelerators. The extension of these methods to the non-linear case is ideally suited to treat CSR instability problems. We report on the development of a numerical code, based on the solution of the Vlasov equation, with the inclusion of non-linear contribution due to wake field effects. The proposed solution method exploits an algebraic technique, using exponential operators. We show that the integration procedure is capable of reproducing the onset of an instability and the effects associated with bunching mechanisms leading to the growth of the instability itself. In addition, considerations on the threshold of the instability are also developed [it
International Nuclear Information System (INIS)
Dattoli, G.; Migliorati, M.; Schiavi, A.
2007-01-01
The coherent synchrotron radiation (CSR) is one of the main problems limiting the performance of high-intensity electron accelerators. The complexity of the physical mechanisms underlying the onset of instabilities due to CSR demands for accurate descriptions, capable of including the large number of features of an actual accelerating device. A code devoted to the analysis of these types of problems should be fast and reliable, conditions that are usually hardly achieved at the same time. In the past, codes based on Lie algebraic techniques have been very efficient to treat transport problems in accelerators. The extension of these methods to the non-linear case is ideally suited to treat CSR instability problems. We report on the development of a numerical code, based on the solution of the Vlasov equation, with the inclusion of non-linear contribution due to wake field effects. The proposed solution method exploits an algebraic technique that uses the exponential operators. We show that the integration procedure is capable of reproducing the onset of instability and the effects associated with bunching mechanisms leading to the growth of the instability itself. In addition, considerations on the threshold of the instability are also developed
Scott, Robert C.; Perry, Boyd, III; Pototzky, Anthony S.
1991-01-01
This paper describes and illustrates two matched-filter-theory based schemes for obtaining maximized and time-correlated gust-loads for a nonlinear airplane. The first scheme is computationally fast because it uses a simple one-dimensional search procedure to obtain its answers. The second scheme is computationally slow because it uses a more complex multidimensional search procedure to obtain its answers, but it consistently provides slightly higher maximum loads than the first scheme. Both schemes are illustrated with numerical examples involving a nonlinear control system.
Chang, Chau-Lyan
2003-01-01
During the past two decades, our understanding of laminar-turbulent transition flow physics has advanced significantly owing to, in a large part, the NASA program support such as the National Aerospace Plane (NASP), High-speed Civil Transport (HSCT), and Advanced Subsonic Technology (AST). Experimental, theoretical, as well as computational efforts on various issues such as receptivity and linear and nonlinear evolution of instability waves take part in broadening our knowledge base for this intricate flow phenomenon. Despite all these advances, transition prediction remains a nontrivial task for engineers due to the lack of a widely available, robust, and efficient prediction tool. The design and development of the LASTRAC code is aimed at providing one such engineering tool that is easy to use and yet capable of dealing with a broad range of transition related issues. LASTRAC was written from scratch based on the state-of-the-art numerical methods for stability analysis and modem software technologies. At low fidelity, it allows users to perform linear stability analysis and N-factor transition correlation for a broad range of flow regimes and configurations by using either the linear stability theory (LST) or linear parabolized stability equations (LPSE) method. At high fidelity, users may use nonlinear PSE to track finite-amplitude disturbances until the skin friction rise. Coupled with the built-in receptivity model that is currently under development, the nonlinear PSE method offers a synergistic approach to predict transition onset for a given disturbance environment based on first principles. This paper describes the governing equations, numerical methods, code development, and case studies for the current release of LASTRAC. Practical applications of LASTRAC are demonstrated for linear stability calculations, N-factor transition correlation, non-linear breakdown simulations, and controls of stationary crossflow instability in supersonic swept wing boundary
Non-Linear Multi-Physics Analysis and Multi-Objective Optimization in Electroheating Applications
Czech Academy of Sciences Publication Activity Database
di Barba, P.; Doležel, Ivo; Mognaschi, M. E.; Savini, A.; Karban, P.
2014-01-01
Roč. 50, č. 2 (2014), s. 7016604-7016604 ISSN 0018-9464 Institutional support: RVO:61388998 Keywords : coupled multi-physics problems * finite element method * non-linear equations Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 1.386, year: 2014
International Nuclear Information System (INIS)
1983-04-01
VISCOT is a non-linear, transient, thermal-stress finite-element code designed to determine the viscoelastic, fiscoplastic, or elastoplastic deformation of a rock mass due to mechanical and thermal loading. The numerical solution of the nonlinear incremental equilibrium equations within VISCOT is performed by using an explicit Euler time-stepping scheme. The rock mass may be modeled as a viscoplastic or viscoelastic material. The viscoplastic material model can be described by a Tresca, von Mises, Drucker-Prager or Mohr-Coulomb yield criteria (with or without strain hardening) with an associated flow rule which can be a power or an exponential law. The viscoelastic material model within VISCOT is a temperature- and stress-dependent law which has been developed specifically for salt rock masses by Pfeifle, Mellegard and Senseny in ONWI-314 topical report (1981). Site specific parameters for this creep law at the Richton, Permian, Paradox and Vacherie salt sites have been calculated and are given in ONWI-314 topical report (1981). A major application of VISCOT (in conjunction with a SCEPTER heat transfer code such as DOT) is the thermomechanical analysis of a rock mass such as salt in which significant time-dependent nonlinear deformations are expected to occur. Such problems include room- and canister-scale studies during the excavation, operation, and long-term post-closure stages in a salt repository. In Section 1.5 of this document the code custodianship and control is described along with the status of verification, validation and peer review of this report
Zou, Rui; Riverson, John; Liu, Yong; Murphy, Ryan; Sim, Youn
2015-03-01
Integrated continuous simulation-optimization models can be effective predictors of a process-based responses for cost-benefit optimization of best management practices (BMPs) selection and placement. However, practical application of simulation-optimization model is computationally prohibitive for large-scale systems. This study proposes an enhanced Nonlinearity Interval Mapping Scheme (NIMS) to solve large-scale watershed simulation-optimization problems several orders of magnitude faster than other commonly used algorithms. An efficient interval response coefficient (IRC) derivation method was incorporated into the NIMS framework to overcome a computational bottleneck. The proposed algorithm was evaluated using a case study watershed in the Los Angeles County Flood Control District. Using a continuous simulation watershed/stream-transport model, Loading Simulation Program in C++ (LSPC), three nested in-stream compliance points (CP)—each with multiple Total Maximum Daily Loads (TMDL) targets—were selected to derive optimal treatment levels for each of the 28 subwatersheds, so that the TMDL targets at all the CP were met with the lowest possible BMP implementation cost. Genetic Algorithm (GA) and NIMS were both applied and compared. The results showed that the NIMS took 11 iterations (about 11 min) to complete with the resulting optimal solution having a total cost of 67.2 million, while each of the multiple GA executions took 21-38 days to reach near optimal solutions. The best solution obtained among all the GA executions compared had a minimized cost of 67.7 million—marginally higher, but approximately equal to that of the NIMS solution. The results highlight the utility for decision making in large-scale watershed simulation-optimization formulations.
Energy Technology Data Exchange (ETDEWEB)
Kurosu, K [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Department of Medical Physics ' Engineering, Osaka University Graduate School of Medicine, Osaka (Japan); Takashina, M; Koizumi, M [Department of Medical Physics ' Engineering, Osaka University Graduate School of Medicine, Osaka (Japan); Das, I; Moskvin, V [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN (United States)
2014-06-01
Purpose: Monte Carlo codes are becoming important tools for proton beam dosimetry. However, the relationships between the customizing parameters and percentage depth dose (PDD) of GATE and PHITS codes have not been reported which are studied for PDD and proton range compared to the FLUKA code and the experimental data. Methods: The beam delivery system of the Indiana University Health Proton Therapy Center was modeled for the uniform scanning beam in FLUKA and transferred identically into GATE and PHITS. This computational model was built from the blue print and validated with the commissioning data. Three parameters evaluated are the maximum step size, cut off energy and physical and transport model. The dependence of the PDDs on the customizing parameters was compared with the published results of previous studies. Results: The optimal parameters for the simulation of the whole beam delivery system were defined by referring to the calculation results obtained with each parameter. Although the PDDs from FLUKA and the experimental data show a good agreement, those of GATE and PHITS obtained with our optimal parameters show a minor discrepancy. The measured proton range R90 was 269.37 mm, compared to the calculated range of 269.63 mm, 268.96 mm, and 270.85 mm with FLUKA, GATE and PHITS, respectively. Conclusion: We evaluated the dependence of the results for PDDs obtained with GATE and PHITS Monte Carlo generalpurpose codes on the customizing parameters by using the whole computational model of the treatment nozzle. The optimal parameters for the simulation were then defined by referring to the calculation results. The physical model, particle transport mechanics and the different geometrybased descriptions need accurate customization in three simulation codes to agree with experimental data for artifact-free Monte Carlo simulation. This study was supported by Grants-in Aid for Cancer Research (H22-3rd Term Cancer Control-General-043) from the Ministry of Health
International Nuclear Information System (INIS)
Wang Rubin; Yu Wei
2005-01-01
In this paper, we investigate how the population of neuronal oscillators deals with information and the dynamic evolution of neural coding when the external stimulation acts on it. Numerically computing method is used to describe the evolution process of neural coding in three-dimensioned space. The numerical result proves that only the suitable stimulation can change the coupling structure and plasticity of neurons
Optimization of Coding of AR Sources for Transmission Across Channels with Loss
DEFF Research Database (Denmark)
Arildsen, Thomas
Source coding concerns the representation of information in a source signal using as few bits as possible. In the case of lossy source coding, it is the encoding of a source signal using the fewest possible bits at a given distortion or, at the lowest possible distortion given a specified bit rate....... Channel coding is usually applied in combination with source coding to ensure reliable transmission of the (source coded) information at the maximal rate across a channel given the properties of this channel. In this thesis, we consider the coding of auto-regressive (AR) sources which are sources that can...... compared to the case where the encoder is unaware of channel loss. We finally provide an extensive overview of cross-layer communication issues which are important to consider due to the fact that the proposed algorithm interacts with the source coding and exploits channel-related information typically...
Cerveau, Nicolas; Jackson, Daniel J
2016-12-09
Next-generation sequencing (NGS) technologies are arguably the most revolutionary technical development to join the list of tools available to molecular biologists since PCR. For researchers working with nonconventional model organisms one major problem with the currently dominant NGS platform (Illumina) stems from the obligatory fragmentation of nucleic acid material that occurs prior to sequencing during library preparation. This step creates a significant bioinformatic challenge for accurate de novo assembly of novel transcriptome data. This challenge becomes apparent when a variety of modern assembly tools (of which there is no shortage) are applied to the same raw NGS dataset. With the same assembly parameters these tools can generate markedly different assembly outputs. In this study we present an approach that generates an optimized consensus de novo assembly of eukaryotic coding transcriptomes. This approach does not represent a new assembler, rather it combines the outputs of a variety of established assembly packages, and removes redundancy via a series of clustering steps. We test and validate our approach using Illumina datasets from six phylogenetically diverse eukaryotes (three metazoans, two plants and a yeast) and two simulated datasets derived from metazoan reference genome annotations. All of these datasets were assembled using three currently popular assembly packages (CLC, Trinity and IDBA-tran). In addition, we experimentally demonstrate that transcripts unique to one particular assembly package are likely to be bioinformatic artefacts. For all eight datasets our pipeline generates more concise transcriptomes that in fact possess more unique annotatable protein domains than any of the three individual assemblers we employed. Another measure of assembly completeness (using the purpose built BUSCO databases) also confirmed that our approach yields more information. Our approach yields coding transcriptome assemblies that are more likely to be
Directory of Open Access Journals (Sweden)
R. Kotteeswaran
2014-01-01
Full Text Available A Multiobjective Particle Swarm Optimization (MOPSO algorithm is proposed to fine-tune the baseline PI controller parameters of Alstom gasifier. The existing baseline PI controller is not able to meet the performance requirements of Alstom gasifier for sinusoidal pressure disturbance at 0% load. This is considered the major drawback of controller design. A best optimal solution for Alstom gasifier is obtained from a set of nondominated solutions using MOPSO algorithm. Performance of gasifier is investigated at all load conditions. The controller with optimized controller parameters meets all the performance requirements at 0%, 50%, and 100% load conditions. The investigations are also extended for variations in coal quality, which shows an improved stability of the gasifier over a wide range of coal quality variations.
International Nuclear Information System (INIS)
Huang Hai-Ping
2015-01-01
The statistical physics properties of low-density parity-check codes for the binary symmetric channel are investigated as a spin glass problem with multi-spin interactions and quenched random fields by the cavity method. By evaluating the entropy function at the Nishimori temperature, we find that irregular constructions with heterogeneous degree distribution of check (bit) nodes have higher decoding thresholds compared to regular counterparts with homogeneous degree distribution. We also show that the instability of the mean-field calculation takes place only after the entropy crisis, suggesting the presence of a frozen glassy phase at low temperatures. When no prior knowledge of channel noise is assumed (searching for the ground state), we find that a reinforced strategy on normal belief propagation will boost the decoding threshold to a higher value than the normal belief propagation. This value is close to the dynamical transition where all local search heuristics fail to identify the true message (codeword or the ferromagnetic state). After the dynamical transition, the number of metastable states with larger energy density (than the ferromagnetic state) becomes exponentially numerous. When the noise level of the transmission channel approaches the static transition point, there starts to exist exponentially numerous codewords sharing the identical ferromagnetic energy. (condensed matter: electronic structure, electrical, magnetic, and optical properties)
Directory of Open Access Journals (Sweden)
Ying Chen
2018-03-01
Full Text Available Rate-distortion optimization (RDO plays an essential role in substantially enhancing the coding efficiency. Currently, rate-distortion optimized mode decision is widely used in scalable video coding (SVC. Among all the possible coding modes, it aims to select the one which has the best trade-off between bitrate and compression distortion. Specifically, this tradeoff is tuned through the choice of the Lagrange multiplier. Despite the prevalence of conventional method for Lagrange multiplier selection in hybrid video coding, the underlying formulation is not applicable to 3-D wavelet-based SVC where the explicit values of the quantization step are not available, with on consideration of the content features of input signal. In this paper, an efficient content adaptive Lagrange multiplier selection algorithm is proposed in the context of RDO for 3-D wavelet-based SVC targeting quality scalability. Our contributions are two-fold. First, we introduce a novel weighting method, which takes account of the mutual information, gradient per pixel, and texture homogeneity to measure the temporal subband characteristics after applying the motion-compensated temporal filtering (MCTF technique. Second, based on the proposed subband weighting factor model, we derive the optimal Lagrange multiplier. Experimental results demonstrate that the proposed algorithm enables more satisfactory video quality with negligible additional computational complexity.
Directory of Open Access Journals (Sweden)
Irwin Yousept
2010-07-01
Full Text Available An optimal control problem arising in the context of 3D electromagnetic induction heating is investigated. The state equation is given by a quasilinear stationary heat equation coupled with a semilinear time harmonic eddy current equation. The temperature-dependent electrical conductivity and the presence of pointwise inequality state-constraints represent the main challenge of the paper. In the first part of the paper, the existence and regularity of the state are addressed. The second part of the paper deals with the analysis of the corresponding linearized equation. Some suffcient conditions are presented which guarantee thesolvability of the linearized system. The final part of the paper is concerned with the optimal control. The aim of the optimization is to find the optimal voltage such that a desired temperature can be achieved optimally. The corresponding first-order necessary optimality condition is presented.
International Nuclear Information System (INIS)
Jeong, J. H.; Lee, K. L.
2016-01-01
The wire spacer has important roles to avoid collisions between adjacent rods, to mitigate a vortex induced vibration, and to enhance convective heat transfer by wire spacer induced secondary flow. Many experimental and numerical works has been conducted to understand the thermal-hydraulics of the wire-wrapped fuel bundles. There has been enormous growth in computing capability. Recently, a huge increase of computer power allows to three-dimensional simulation of thermal-hydraulics of wire-wrapped fuel bundles. In this study, the geometry optimization methodology with RANS based in-house CFD (Computational Fluid Dynamics) code has been successfully developed in air condition. In order to apply the developed methodology to fuel assembly, GGI (General Grid Interface) function is developed for in-house CFD code. Furthermore, three-dimensional flow fields calculated with in-house CFD code are compared with those calculated with general purpose commercial CFD solver, CFX. The geometry optimization methodology with RANS based in-house CFD code has been successfully developed in air condition. In order to apply the developed methodology to fuel assembly, GGI function is developed for in-house CFD code as same as CFX. Even though both analyses are conducted with same computational meshes, numerical error due to GGI function locally occurred in only CFX solver around rod surface and boundary region between inner fluid region and outer fluid region.
Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chain
Energy Technology Data Exchange (ETDEWEB)
Catalao, J.P.S.; Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)
2010-08-15
This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain. We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to earlier studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas. Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper. Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement. (author)
Interior-Point Method for Non-Linear Non-Convex Optimization
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan
2004-01-01
Roč. 11, č. 5-6 (2004), s. 431-453 ISSN 1070-5325 R&D Projects: GA AV ČR IAA1030103 Institutional research plan: CEZ:AV0Z1030915 Keywords : non-linear programming * interior point methods * indefinite systems * indefinite preconditioners * preconditioned conjugate gradient method * merit functions * algorithms * computational experiments Subject RIV: BA - General Mathematics Impact factor: 0.727, year: 2004
Non-linear optimization of track layouts in loop-sorting-systems
DEFF Research Database (Denmark)
Sørensen, Søren Emil; Hansen, Michael R.; Ebbesen, Morten K.
2013-01-01
Optimization used for enhancing geometric structures iswell known. Applying obstacles to the shape optimization problemis on the other hand not very common. It requires a fast contact search algorithmand an exact continuous formulation to solve the problem robustly. This paper focuses on combining...
Directory of Open Access Journals (Sweden)
Shuai Zeng
2013-01-01
Full Text Available With the development of wireless technologies, mobile communication applies more and more extensively in the various walks of life. The social network of both fixed and mobile users can be seen as networked agent system. At present, kinds of devices and access network technology are widely used. Different users in this networked agent system may need different coding rates multimedia data due to their heterogeneous demand. This paper proposes a distributed flow rate control algorithm to optimize multimedia data transmission of the networked agent system with the coexisting various coding rates. In this proposed algorithm, transmission path and upload bandwidth of different coding rate data between source node, fixed and mobile nodes are appropriately arranged and controlled. On the one hand, this algorithm can provide user nodes with differentiated coding rate data and corresponding flow rate. On the other hand, it makes the different coding rate data and user nodes networked, which realizes the sharing of upload bandwidth of user nodes which require different coding rate data. The study conducts mathematical modeling on the proposed algorithm and compares the system that adopts the proposed algorithm with the existing system based on the simulation experiment and mathematical analysis. The results show that the system that adopts the proposed algorithm achieves higher upload bandwidth utilization of user nodes and lower upload bandwidth consumption of source node.
Directory of Open Access Journals (Sweden)
M. Pattnaik
2013-08-01
Full Text Available In this paper the concept of fuzzy Non-Linear Programming Technique is applied to solve an economic order quantity (EOQ model under restricted space. Since various types of uncertainties and imprecision are inherent in real inventory problems they are classically modeled using the approaches from the probability theory. However, there are uncertainties that cannot be appropriately treated by usual probabilistic models. The questions how to define inventory optimization tasks in such environment how to interpret optimal solutions arise. This paper allows the modification of the Single item EOQ model in presence of fuzzy decision making process where demand is related to the unit price and the setup cost varies with the quantity produced/Purchased. This paper considers the modification of objective function and storage area in the presence of imprecisely estimated parameters. The model is developed for the problem by employing different modeling approaches over an infinite planning horizon. It incorporates all concepts of a fuzzy arithmetic approach, the quantity ordered and the demand per unit compares both fuzzy non linear and other models. Investigation of the properties of an optimal solution allows developing an algorithm whose validity is illustrated through an example problem and ugh MATLAB (R2009a version software, the two and three dimensional diagrams are represented to the application. Sensitivity analysis of the optimal solution is also studied with respect to changes in different parameter values and to draw managerial insights of the decision problem.
Code Samples Used for Complexity and Control
Ivancevic, Vladimir G.; Reid, Darryn J.
2015-11-01
The following sections are included: * MathematicaⓇ Code * Generic Chaotic Simulator * Vector Differential Operators * NLS Explorer * 2C++ Code * C++ Lambda Functions for Real Calculus * Accelerometer Data Processor * Simple Predictor-Corrector Integrator * Solving the BVP with the Shooting Method * Linear Hyperbolic PDE Solver * Linear Elliptic PDE Solver * Method of Lines for a Set of the NLS Equations * C# Code * Iterative Equation Solver * Simulated Annealing: A Function Minimum * Simple Nonlinear Dynamics * Nonlinear Pendulum Simulator * Lagrangian Dynamics Simulator * Complex-Valued Crowd Attractor Dynamics * Freeform Fortran Code * Lorenz Attractor Simulator * Complex Lorenz Attractor * Simple SGE Soliton * Complex Signal Presentation * Gaussian Wave Packet * Hermitian Matrices * Euclidean L2-Norm * Vector/Matrix Operations * Plain C-Code: Levenberg-Marquardt Optimizer * Free Basic Code: 2D Crowd Dynamics with 3000 Agents
Malas, Tareq M.
2016-07-21
Understanding and optimizing the properties of solar cells is becoming a key issue in the search for alternatives to nuclear and fossil energy sources. A theoretical analysis via numerical simulations involves solving Maxwell\\'s Equations in discretized form and typically requires substantial computing effort. We start from a hybrid-parallel (MPI+OpenMP) production code that implements the Time Harmonic Inverse Iteration Method (THIIM) with Finite-Difference Frequency Domain (FDFD) discretization. Although this algorithm has the characteristics of a strongly bandwidth-bound stencil update scheme, it is significantly different from the popular stencil types that have been exhaustively studied in the high performance computing literature to date. We apply a recently developed stencil optimization technique, multicore wavefront diamond tiling with multi-dimensional cache block sharing, and describe in detail the peculiarities that need to be considered due to the special stencil structure. Concurrency in updating the components of the electric and magnetic fields provides an additional level of parallelism. The dependence of the cache size requirement of the optimized code on the blocking parameters is modeled accurately, and an auto-tuner searches for optimal configurations in the remaining parameter space. We were able to completely decouple the execution from the memory bandwidth bottleneck, accelerating the implementation by a factor of three to four compared to an optimal implementation with pure spatial blocking on an 18-core Intel Haswell CPU.
User's manual for the BNW-II optimization code for dry/wet-cooled power plants
Energy Technology Data Exchange (ETDEWEB)
Braun, D.J.; Bamberger, J.A.; Braun, D.J.; Faletti, D.W.; Wiles, L.E.
1978-05-01
The User's Manual describes how to operate BNW-II, a computer code developed by the Pacific Northwest Laboratory (PNL) as a part of its activities under the Department of Energy (DOE) Dry Cooling Enhancement Program. The computer program offers a comprehensive method of evaluating the cost savings potential of dry/wet-cooled heat rejection systems. Going beyond simple ''figure-of-merit'' cooling tower optimization, this method includes such items as the cost of annual replacement capacity, and the optimum split between plant scale-up and replacement capacity, as well as the purchase and operating costs of all major heat rejection components. Hence the BNW-II code is a useful tool for determining potential cost savings of new dry/wet surfaces, new piping, or other components as part of an optimized system for a dry/wet-cooled plant.
An integer optimization algorithm for robust identification of non-linear gene regulatory networks
Directory of Open Access Journals (Sweden)
Chemmangattuvalappil Nishanth
2012-09-01
Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters
Optimal Operation of Industrial Batch Crystallizers : A Nonlinear Model-based Control Approach
Mesbah, A.
2010-01-01
Batch crystallization is extensively employed in the chemical, pharmaceutical, and food industries to separate and purify high value-added chemical substances. Despite their widespread application, optimal operation of batch crystallizers is particularly challenging. The difficulties primarily
Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue
2018-02-03
One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C /2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C /2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi's model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments.
Accuracy improvement of SPACE code using the optimization for CHF subroutine
International Nuclear Information System (INIS)
Yang, Chang Keun; Kim, Yo Han; Park, Jong Eun; Ha, Sang Jun
2010-01-01
Typically, a subroutine to calculate the CHF (Critical Heat Flux) is loaded in code for safety analysis of nuclear power plant. CHF subroutine calculates CHF phenomenon using arbitrary condition (Temperature, pressure, flow rate, power, etc). When safety analysis for nuclear power plant is performed using major factor, CHF parameter is one of the most important factor. But the subroutines used in most codes, such as Biasi method, etc., estimate some different values from experimental data. Most CHF subroutines in the codes could predict only in their specification area, such as pressure, mass flow, void fraction, etc. Even though the most accurate CHF subroutine is used in the high quality nuclear safety analysis code, it is not assured that the valued predicted values by the subroutine are acceptable out of their application area. To overcome this hardship, various approaches to estimate the CHF have been examined during the code developing stage of SPACE. And the six sigma technique was adopted for the examination as mentioned this study. The objective of this study is to improvement of CHF prediction accuracy for nuclear power plant safety analysis code using the CHF database and Six Sigma technique. Through the study, it was concluded that the six sigma technique was useful to quantify the deviation of prediction values to experimental data and the implemented CHF prediction method in SPACE code had well-predict capabilities compared with those from other methods
Welter, David E.; Doherty, John E.; Hunt, Randall J.; Muffels, Christopher T.; Tonkin, Matthew J.; Schreuder, Willem A.
2012-01-01
An object-oriented parameter estimation code was developed to incorporate benefits of object-oriented programming techniques for solving large parameter estimation modeling problems. The code is written in C++ and is a formulation and expansion of the algorithms included in PEST, a widely used parameter estimation code written in Fortran. The new code is called PEST++ and is designed to lower the barriers of entry for users and developers while providing efficient algorithms that can accommodate large, highly parameterized problems. This effort has focused on (1) implementing the most popular features of PEST in a fashion that is easy for novice or experienced modelers to use and (2) creating a software design that is easy to extend; that is, this effort provides a documented object-oriented framework designed from the ground up to be modular and extensible. In addition, all PEST++ source code and its associated libraries, as well as the general run manager source code, have been integrated in the Microsoft Visual Studio® 2010 integrated development environment. The PEST++ code is designed to provide a foundation for an open-source development environment capable of producing robust and efficient parameter estimation tools for the environmental modeling community into the future.
Optimizing BAO measurements with non-linear transformations of the Lyman-α forest
Energy Technology Data Exchange (ETDEWEB)
Wang, Xinkang; Font-Ribera, Andreu; Seljak, Uroš, E-mail: xinkang.wang@berkeley.edu, E-mail: afont@lbl.gov, E-mail: useljak@berkeley.edu [Department of Physics, University of California, South Hall Rd, Berkeley (United States)
2015-04-01
We explore the effect of applying a non-linear transformation to the Lyman-α forest transmitted flux F=e{sup −τ} and the ability of analytic models to predict the resulting clustering amplitude. Both the large-scale bias of the transformed field (signal) and the amplitude of small scale fluctuations (noise) can be arbitrarily modified, but we were unable to find a transformation that increases significantly the signal-to-noise ratio on large scales using Taylor expansion up to the third order. In particular, however, we achieve a 33% improvement in signal to noise for Gaussianized field in transverse direction. On the other hand, we explore an analytic model for the large-scale biasing of the Lyα forest, and present an extension of this model to describe the biasing of the transformed fields. Using hydrodynamic simulations we show that the model works best to describe the biasing with respect to velocity gradients, but is less successful in predicting the biasing with respect to large-scale density fluctuations, especially for very nonlinear transformations.
Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.
2010-01-01
Structural design generated by traditional method, optimization method and the stochastic design concept are compared. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions were produced by all the three methods. The variation in the weight calculated by the methods was modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliabilitytraced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.
Directory of Open Access Journals (Sweden)
Steven J. Schrodi
2017-01-01
Full Text Available Diagnostic codes within electronic health record systems can vary widely in accuracy. It has been noted that the number of instances of a particular diagnostic code monotonically increases with the accuracy of disease phenotype classification. As a growing number of health system databases become linked with genomic data, it is critically important to understand the effect of this misclassification on the power of genetic association studies. Here, I investigate the impact of this diagnostic code misclassification on the power of genetic association studies with the aim to better inform experimental designs using health informatics data. The trade-off between (i reduced misclassification rates from utilizing additional instances of a diagnostic code per individual and (ii the resulting smaller sample size is explored, and general rules are presented to improve experimental designs.
Padhi, Radhakant; Unnikrishnan, Nishant; Wang, Xiaohua; Balakrishnan, S N
2006-12-01
Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the "Single Network Adaptive Critic (SNAC)" is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.
2016-08-24
to the seven-qubit Steane code [29] and also represents the smallest instance of a 2D topological color code [30]. Since the realized quantum error...Quantum Computations on a Topologically Encoded Qubit, Science 345, 302 (2014). [17] M. Cramer, M. B. Plenio, S. T. Flammia, R. Somma, D. Gross, S. D...Memory, J. Math . Phys. (N.Y.) 43, 4452 (2002). [20] B. M. Terhal, Quantum Error Correction for Quantum Memories, Rev. Mod. Phys. 87, 307 (2015). [21] D
Performance Evaluation of a Novel Optimization Sequential Algorithm (SeQ Code for FTTH Network
Directory of Open Access Journals (Sweden)
Fazlina C.A.S.
2017-01-01
Full Text Available The SeQ codes has advantages, such as variable cross-correlation property at any given number of users and weights, as well as effectively suppressed the impacts of phase induced intensity noise (PIIN and multiple access interference (MAI cancellation property. The result revealed, at system performance analysis of BER = 10-09, the SeQ code capable to achieved 1 Gbps up to 60 km.
Computational Modelling and Optimal Control of Ebola Virus Disease with non-Linear Incidence Rate
Takaidza, I.; Makinde, O. D.; Okosun, O. K.
2017-03-01
The 2014 Ebola outbreak in West Africa has exposed the need to connect modellers and those with relevant data as pivotal to better understanding of how the disease spreads and quantifying the effects of possible interventions. In this paper, we model and analyse the Ebola virus disease with non-linear incidence rate. The epidemic model created is used to describe how the Ebola virus could potentially evolve in a population. We perform an uncertainty analysis of the basic reproductive number R 0 to quantify its sensitivity to other disease-related parameters. We also analyse the sensitivity of the final epidemic size to the time control interventions (education, vaccination, quarantine and safe handling) and provide the cost effective combination of the interventions.
Energy Technology Data Exchange (ETDEWEB)
Kurosu, Keita [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN 46202 (United States); Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871 (Japan); Department of Radiology, Osaka University Hospital, Suita, Osaka 565-0871 (Japan); Das, Indra J. [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN 46202 (United States); Moskvin, Vadim P. [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN 46202 (United States); Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, TN 38105 (United States)
2016-01-15
Spot scanning, owing to its superior dose-shaping capability, provides unsurpassed dose conformity, in particular for complex targets. However, the robustness of the delivered dose distribution and prescription has to be verified. Monte Carlo (MC) simulation has the potential to generate significant advantages for high-precise particle therapy, especially for medium containing inhomogeneities. However, the inherent choice of computational parameters in MC simulation codes of GATE, PHITS and FLUKA that is observed for uniform scanning proton beam needs to be evaluated. This means that the relationship between the effect of input parameters and the calculation results should be carefully scrutinized. The objective of this study was, therefore, to determine the optimal parameters for the spot scanning proton beam for both GATE and PHITS codes by using data from FLUKA simulation as a reference. The proton beam scanning system of the Indiana University Health Proton Therapy Center was modeled in FLUKA, and the geometry was subsequently and identically transferred to GATE and PHITS. Although the beam transport is managed by spot scanning system, the spot location is always set at the center of a water phantom of 600 × 600 × 300 mm{sup 3}, which is placed after the treatment nozzle. The percentage depth dose (PDD) is computed along the central axis using 0.5 × 0.5 × 0.5 mm{sup 3} voxels in the water phantom. The PDDs and the proton ranges obtained with several computational parameters are then compared to those of FLUKA, and optimal parameters are determined from the accuracy of the proton range, suppressed dose deviation, and computational time minimization. Our results indicate that the optimized parameters are different from those for uniform scanning, suggesting that the gold standard for setting computational parameters for any proton therapy application cannot be determined consistently since the impact of setting parameters depends on the proton irradiation
International Nuclear Information System (INIS)
Kurosu, Keita; Das, Indra J.; Moskvin, Vadim P.
2016-01-01
Spot scanning, owing to its superior dose-shaping capability, provides unsurpassed dose conformity, in particular for complex targets. However, the robustness of the delivered dose distribution and prescription has to be verified. Monte Carlo (MC) simulation has the potential to generate significant advantages for high-precise particle therapy, especially for medium containing inhomogeneities. However, the inherent choice of computational parameters in MC simulation codes of GATE, PHITS and FLUKA that is observed for uniform scanning proton beam needs to be evaluated. This means that the relationship between the effect of input parameters and the calculation results should be carefully scrutinized. The objective of this study was, therefore, to determine the optimal parameters for the spot scanning proton beam for both GATE and PHITS codes by using data from FLUKA simulation as a reference. The proton beam scanning system of the Indiana University Health Proton Therapy Center was modeled in FLUKA, and the geometry was subsequently and identically transferred to GATE and PHITS. Although the beam transport is managed by spot scanning system, the spot location is always set at the center of a water phantom of 600 × 600 × 300 mm 3 , which is placed after the treatment nozzle. The percentage depth dose (PDD) is computed along the central axis using 0.5 × 0.5 × 0.5 mm 3 voxels in the water phantom. The PDDs and the proton ranges obtained with several computational parameters are then compared to those of FLUKA, and optimal parameters are determined from the accuracy of the proton range, suppressed dose deviation, and computational time minimization. Our results indicate that the optimized parameters are different from those for uniform scanning, suggesting that the gold standard for setting computational parameters for any proton therapy application cannot be determined consistently since the impact of setting parameters depends on the proton irradiation technique
International Nuclear Information System (INIS)
Binh, Do Quang; Huy, Ngo Quang; Hai, Nguyen Hoang
2014-01-01
This paper presents a new approach based on a binary mixed integer coded genetic algorithm in conjunction with the weighted sum method for multi-objective optimization of fuel loading patterns for nuclear research reactors. The proposed genetic algorithm works with two types of chromosomes: binary and integer chromosomes, and consists of two types of genetic operators: one working on binary chromosomes and the other working on integer chromosomes. The algorithm automatically searches for the most suitable weighting factors of the weighting function and the optimal fuel loading patterns in the search process. Illustrative calculations are implemented for a research reactor type TRIGA MARK II loaded with the Russian VVR-M2 fuels. Results show that the proposed genetic algorithm can successfully search for both the best weighting factors and a set of approximate optimal loading patterns that maximize the effective multiplication factor and minimize the power peaking factor while satisfying operational and safety constraints for the research reactor.
Energy Technology Data Exchange (ETDEWEB)
Binh, Do Quang [University of Technical Education Ho Chi Minh City (Viet Nam); Huy, Ngo Quang [University of Industry Ho Chi Minh City (Viet Nam); Hai, Nguyen Hoang [Centre for Research and Development of Radiation Technology, Ho Chi Minh City (Viet Nam)
2014-12-15
This paper presents a new approach based on a binary mixed integer coded genetic algorithm in conjunction with the weighted sum method for multi-objective optimization of fuel loading patterns for nuclear research reactors. The proposed genetic algorithm works with two types of chromosomes: binary and integer chromosomes, and consists of two types of genetic operators: one working on binary chromosomes and the other working on integer chromosomes. The algorithm automatically searches for the most suitable weighting factors of the weighting function and the optimal fuel loading patterns in the search process. Illustrative calculations are implemented for a research reactor type TRIGA MARK II loaded with the Russian VVR-M2 fuels. Results show that the proposed genetic algorithm can successfully search for both the best weighting factors and a set of approximate optimal loading patterns that maximize the effective multiplication factor and minimize the power peaking factor while satisfying operational and safety constraints for the research reactor.
Flexible aluminum tubes and a least square multi-objective non-linear optimization scheme
International Nuclear Information System (INIS)
Endelt, Benny; Nielsen, Karl Brian; Olsen, Soeren
2004-01-01
The automotive industry currently uses rubber hoses as the media carrier between e.g. the radiator and the engine, and the basic idea is to replace the rubber hoses with flexible aluminum tubes.A good quality is defined through several quality measurements, i.e. in the current case the key objective is to produce a flexible convolution through optimization of the tool geometry, but the process should also be stable, and the process stability is evaluated through Forming Limit Diagrams. Typically the defined objectives are conflicting, i.e. the optimized configuration represents therefore a trade-off between the individual objectives, in this case flexibility versus process stability.The optimization problem is solved through iteratively minimizing the object function. A second-order least square scheme is used for the approximation of the quadratic model, and the change in the design parameters is evaluated through the trust region scheme and box constraints are introduced within the trust region framework. Furthermore, the object function is minimized by applying the non-monotone scheme, and the trust region subproblem is solved by applying the Cholesky factorization scheme.An optimal bell shaped geometry is identified and the design is verified experimentally
Wang, Danshi; Zhang, Min; Cai, Zhongle; Cui, Yue; Li, Ze; Han, Huanhuan; Fu, Meixia; Luo, Bin
2016-06-01
An effective machine learning algorithm, the support vector machine (SVM), is presented in the context of a coherent optical transmission system. As a classifier, the SVM can create nonlinear decision boundaries to mitigate the distortions caused by nonlinear phase noise (NLPN). Without any prior information or heuristic assumptions, the SVM can learn and capture the link properties from only a few training data. Compared with the maximum likelihood estimation (MLE) algorithm, a lower bit-error rate (BER) is achieved by the SVM for a given launch power; moreover, the launch power dynamic range (LPDR) is increased by 3.3 dBm for 8 phase-shift keying (8 PSK), 1.2 dBm for QPSK, and 0.3 dBm for BPSK. The maximum transmission distance corresponding to a BER of 1 ×10-3 is increased by 480 km for the case of 8 PSK. The larger launch power range and longer transmission distance improve the tolerance to amplitude and phase noise, which demonstrates the feasibility of the SVM in digital signal processing for M-PSK formats. Meanwhile, in order to apply the SVM method to 16 quadratic amplitude modulation (16 QAM) detection, we propose a parameter optimization scheme. By utilizing a cross-validation and grid-search techniques, the optimal parameters of SVM can be selected, thus leading to the LPDR improvement by 2.8 dBm. Additionally, we demonstrate that the SVM is also effective in combating the laser phase noise combined with the inphase and quadrature (I/Q) modulator imperfections, but the improvement is insignificant for the linear noise and separate I/Q imbalance. The computational complexity of SVM is also discussed. The relatively low complexity makes it possible for SVM to implement the real-time processing.
International Nuclear Information System (INIS)
Tunstall, J.N.
1975-05-01
The General Productivity Code is a FORTRAN IV computer program for the IBM System 360. With its model of the productivity of gaseous diffusion cascades, the program is used to determine optimum cascade performance based on specified operating conditions and to aid in the calculation of optimum operating conditions for a complex of diffusion cascades. This documentation of the program is directed primarily to programmers who will be responsible for updating the code as requested by the users. It is also intended to be an aid in training new Productivity Code users and to serve as a general reference manual. Elements of the mathematical model, the input data requirements, the definitions of the various tasks (Instructions) that can be performed, and a detailed description of most FORTRAN variables and program subroutines are presented. A sample problem is also included. (auth)
Darazi, R.; Gouze, A.; Macq, B.
2009-01-01
Reproducing a natural and real scene as we see in the real world everyday is becoming more and more popular. Stereoscopic and multi-view techniques are used for this end. However due to the fact that more information are displayed requires supporting technologies such as digital compression to ensure the storage and transmission of the sequences. In this paper, a new scheme for stereo image coding is proposed. The original left and right images are jointly coded. The main idea is to optimally exploit the existing correlation between the two images. This is done by the design of an efficient transform that reduces the existing redundancy in the stereo image pair. This approach was inspired by Lifting Scheme (LS). The novelty in our work is that the prediction step is been replaced by an hybrid step that consists in disparity compensation followed by luminance correction and an optimized prediction step. The proposed scheme can be used for lossless and for lossy coding. Experimental results show improvement in terms of performance and complexity compared to recently proposed methods.
Optimal nonlinear information processing capacity in delay-based reservoir computers
Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo
2015-09-01
Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature.
Directory of Open Access Journals (Sweden)
Quan Zheng
2015-12-01
Full Text Available In this paper, a family of Steffensen-type methods of optimal order of convergence with two parameters is constructed by direct Newtonian interpolation. It satisfies the conjecture proposed by Kung and Traub (J. Assoc. Comput. Math. 1974, 21, 634–651 that an iterative method based on m evaluations per iteration without memory would arrive at the optimal convergence of order 2m-1 . Furthermore, the family of Steffensen-type methods of super convergence is suggested by using arithmetic expressions for the parameters with memory but no additional new evaluation of the function. Their error equations, asymptotic convergence constants and convergence orders are obtained. Finally, they are compared with related root-finding methods in the numerical examples.
Optimal bounds and extremal trajectories for time averages in nonlinear dynamical systems
Tobasco, Ian; Goluskin, David; Doering, Charles R.
2018-02-01
For any quantity of interest in a system governed by ordinary differential equations, it is natural to seek the largest (or smallest) long-time average among solution trajectories, as well as the extremal trajectories themselves. Upper bounds on time averages can be proved a priori using auxiliary functions, the optimal choice of which is a convex optimization problem. We prove that the problems of finding maximal trajectories and minimal auxiliary functions are strongly dual. Thus, auxiliary functions provide arbitrarily sharp upper bounds on time averages. Moreover, any nearly minimal auxiliary function provides phase space volumes in which all nearly maximal trajectories are guaranteed to lie. For polynomial equations, auxiliary functions can be constructed by semidefinite programming, which we illustrate using the Lorenz system.
Nonlinear Dynamic in an Ecological System with Impulsive Effect and Optimal Foraging
Directory of Open Access Journals (Sweden)
Min Zhao
2014-01-01
Full Text Available The population dynamics of a three-species ecological system with impulsive effect are investigated. Using the theories of impulsive equations and small-amplitude perturbation scales, the conditions for the system to be permanent when the number of predators released is less than some critical value can be obtained. Furthermore, because the predator in the system follows the predictions of optimal foraging theory, it follows that optimal foraging promotes species coexistence. In particular, the less beneficial prey can support the predator alone when the more beneficial prey goes extinct. Moreover, the influences of the impulsive effect and optimal foraging on inherent oscillations are studied using simulation, which reveals rich dynamic behaviors such as period-halving bifurcations, a chaotic band, a periodic window, and chaotic crises. In addition, the largest Lyapunov exponent and the power spectra of the strange attractor, which can help analyze the chaotic dynamic behavior of the model, are investigated. This information will be useful for studying the dynamic complexity of ecosystems.
Evaluating optimal CNR as a preset criteria for nonlinear moidal blending of dual energy CT data
Holmes, D. R., III; Apel, A.; Fletcher, J. G.; Guimaraes, L. S.; Eusemann, C. E.; Robb, R. A.
2009-02-01
Nonlinear blending of dual-energy CT data is available on current scanners. Selection of the blending parameters can be time-consuming and challenging. The purpose of this study was to determine if the Contrast-To-Noise Ratio (CNR) may be used ti automatic select of blending parameters. A Bovine liver was built with six syringes filled with varying concentrations of CT contrast yielding six 140kV HU levels (15, 47, 64, 79, 116, and 145). The phantom was scanned using 95 mAs @ 140kV and 404mAs @ 80 kV. The 80 and 140 kV datasets were blended using a modified sigmoid (moidal) function which requires two parameters - level and width. Every combination of moidal level and width was applied to the data, and the CNR was calculated as (mean(syringe ROI) - mean(liver ROI)) / STD(water). The maximum CNR was determined for each of the 6 HU levels. Pairs of blended images were presented in a blind manner to observers. Nine comparisons for each of the 6 HU settings were made by a staff radiologist, a resident, and a physicist. For each comparison, the observer selected the more "visually appealing" image. Outcomes from the study were compared using the Fisher Sign Test statistic. Analysis by observer showed a statistical (penergy CT data may provide consistency across radiologists and facilitate the clinical review process.
DEFF Research Database (Denmark)
Zhou, Dao; Blaabjerg, Frede; Lau, Mogens
2015-01-01
. In order to fulfill the modern grid codes, over-excited reactive power injection will further reduce the lifetime of the rotor-side converter. In this paper, the additional stress of the power semiconductor due to the reactive power injection is firstly evaluated in terms of modulation index...
Power Allocation Optimization: Linear Precoding Adapted to NB-LDPC Coded MIMO Transmission
Directory of Open Access Journals (Sweden)
Tarek Chehade
2015-01-01
Full Text Available In multiple-input multiple-output (MIMO transmission systems, the channel state information (CSI at the transmitter can be used to add linear precoding to the transmitted signals in order to improve the performance and the reliability of the transmission system. This paper investigates how to properly join precoded closed-loop MIMO systems and nonbinary low density parity check (NB-LDPC. The q elements in the Galois field, GF(q, are directly mapped to q transmit symbol vectors. This allows NB-LDPC codes to perfectly fit with a MIMO precoding scheme, unlike binary LDPC codes. The new transmission model is detailed and studied for several linear precoders and various designed LDPC codes. We show that NB-LDPC codes are particularly well suited to be jointly used with precoding schemes based on the maximization of the minimum Euclidean distance (max-dmin criterion. These results are theoretically supported by extrinsic information transfer (EXIT analysis and are confirmed by numerical simulations.
Directory of Open Access Journals (Sweden)
Zhi-Ren Tsai
2013-01-01
Full Text Available A tracking problem, time-delay, uncertainty and stability analysis of a predictive control system are considered. The predictive control design is based on the input and output of neural plant model (NPM, and a recursive fuzzy predictive tracker has scaling factors which limit the value zone of measured data and cause the tuned parameters to converge to obtain a robust control performance. To improve the further control performance, the proposed random-local-optimization design (RLO for a model/controller uses offline initialization to obtain a near global optimal model/controller. Other issues are the considerations of modeling error, input-delay, sampling distortion, cost, greater flexibility, and highly reliable digital products of the model-based controller for the continuous-time (CT nonlinear system. They are solved by a recommended two-stage control design with the first-stage (offline RLO and second-stage (online adaptive steps. A theorizing method is then put forward to replace the sensitivity calculation, which reduces the calculation of Jacobin matrices of the back-propagation (BP method. Finally, the feedforward input of reference signals helps the digital fuzzy controller improve the control performance, and the technique works to control the CT systems precisely.
Xu, Y; Li, N
2014-09-01
Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator-prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework.
International Nuclear Information System (INIS)
Xu, Y; Li, N
2014-01-01
Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator–prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework. (paper)
Directory of Open Access Journals (Sweden)
Farong Kou
2018-01-01
Full Text Available In order to coordinate the damping performance and energy regenerative performance of energy regenerative suspension, this paper proposes a structure of a vehicle semi-active energy regenerative suspension with an electro-hydraulic actuator (EHA. In light of the proposed concept, a specific energy regenerative scheme is designed and a mechanical properties test is carried out. Based on the test results, the parameter identification for the system model is conducted using a recursive least squares algorithm. On the basis of the system principle, the nonlinear model of the semi-active energy regenerative suspension with an EHA is built. Meanwhile, linear-quadratic-Gaussian control strategy of the system is designed. Then, the influence of the main parameters of the EHA on the damping performance and energy regenerative performance of the suspension is analyzed. Finally, the main parameters of the EHA are optimized via the genetic algorithm. The test results show that when a sinusoidal is input at the frequency of 2 Hz and the amplitude of 30 mm, the spring mass acceleration root meam square value of the optimized EHA semi-active energy regenerative suspension is reduced by 22.23% and the energy regenerative power RMS value is increased by 40.51%, which means that while meeting the requirements of vehicle ride comfort and driving safety, the energy regenerative performance is improved significantly.
Application of Flow and Transport Optimization Codes to Groundwater Pump and Treat Systems- VOLUME 2
National Research Council Canada - National Science Library
Minsker, Barbara
2004-01-01
.... Recent studies completed by the EPA and the Navy indicate that the majority of pump and treat systems are not operating as designed, have unachievable or undefined goals, and have not been optimized since installation...
Energy Technology Data Exchange (ETDEWEB)
Kudryashov, Nikolay A.; Shilnikov, Kirill E. [National Research Nuclear University MEPhI, Department of Applied Mathematics, Moscow (Russian Federation)
2016-06-08
Numerical computation of the three dimensional problem of the freezing interface propagation during the cryosurgery coupled with the multi-objective optimization methods is used in order to improve the efficiency and safety of the cryosurgery operations performing. Prostate cancer treatment and cutaneous cryosurgery are considered. The heat transfer in soft tissue during the thermal exposure to low temperature is described by the Pennes bioheat model and is coupled with an enthalpy method for blurred phase change computations. The finite volume method combined with the control volume approximation of the heat fluxes is applied for the cryosurgery numerical modeling on the tumor tissue of a quite arbitrary shape. The flux relaxation approach is used for the stability improvement of the explicit finite difference schemes. The method of the additional heating elements mounting is studied as an approach to control the cellular necrosis front propagation. Whereas the undestucted tumor tissue and destucted healthy tissue volumes are considered as objective functions, the locations of additional heating elements in cutaneous cryosurgery and cryotips in prostate cancer cryotreatment are considered as objective variables in multi-objective problem. The quasi-gradient method is proposed for the searching of the Pareto front segments as the multi-objective optimization problem solutions.
Yu, Xuefei; Lin, Liangzhuo; Shen, Jie; Chen, Zhi; Jian, Jun; Li, Bin; Xin, Sherman Xuegang
2018-01-01
The mean amplitude of glycemic excursions (MAGE) is an essential index for glycemic variability assessment, which is treated as a key reference for blood glucose controlling at clinic. However, the traditional "ruler and pencil" manual method for the calculation of MAGE is time-consuming and prone to error due to the huge data size, making the development of robust computer-aided program an urgent requirement. Although several software products are available instead of manual calculation, poor agreement among them is reported. Therefore, more studies are required in this field. In this paper, we developed a mathematical algorithm based on integer nonlinear programming. Following the proposed mathematical method, an open-code computer program named MAGECAA v1.0 was developed and validated. The results of the statistical analysis indicated that the developed program was robust compared to the manual method. The agreement among the developed program and currently available popular software is satisfied, indicating that the worry about the disagreement among different software products is not necessary. The open-code programmable algorithm is an extra resource for those peers who are interested in the related study on methodology in the future.
Directory of Open Access Journals (Sweden)
Sukhinov Alexander
2017-01-01
Full Text Available One of the practically important tasks of hydrophysics for sea coastal systems is the problem of modeling and forecasting bottom sediment transportation. A number of problems connected to ship safety traffic, water medium condition near the coastal line etc. depends on forecasting bottom deposit transportation under natural and technogenic influences. Coastal systems are characterized by a complicated form of coastline - the presence of long, narrow and curvilinear peninsulas and bays. Water currents and waves near the beach are strongly depend on complicated coastal line and in turn, exert on the bottom sediment transportation near the shore. The use of rectangular grids in the construction of discrete models leads to significant errors in both the specification of boundary conditions and in the modeling of hydrophysical processes in the coastal zone. In this paper, we consider the construction of a finite-element approximation of the initial-boundary value problem for the spatially two-dimensional linearized equation of sediment transportation using optimal boundary-adaptive grid. First, the linearization of a spatially two-dimensional nonlinear parabolic equation on the time grid is performed-when the coefficients of the equation that are nonlinearly dependent on the bottom relief function are set on the previous time layer, and the corresponding initial conditions are used on the first time layer. The algorithm for constructing the grid is based on the procedure for minimizing the generalized Dirichlet functional. On the constructed grid, finite element approximation using bilinear basis functions is performed, which completes the construction of a discrete model for the given problem. The using of curvilinear boundary adaptive grids leads to decreasing of total grid number in 5-20 times and respectively the total modeling time and/or it allows to improve modeling accuracy.
Analysis and Optimization of Sparse Random Linear Network Coding for Reliable Multicast Services
DEFF Research Database (Denmark)
Tassi, Andrea; Chatzigeorgiou, Ioannis; Roetter, Daniel Enrique Lucani
2016-01-01
Point-to-multipoint communications are expected to play a pivotal role in next-generation networks. This paper refers to a cellular system transmitting layered multicast services to a multicast group of users. Reliability of communications is ensured via different random linear network coding (RLNC......) techniques. We deal with a fundamental problem: the computational complexity of the RLNC decoder. The higher the number of decoding operations is, the more the user's computational overhead grows and, consequently, the faster the battery of mobile devices drains. By referring to several sparse RLNC...... techniques, and without any assumption on the implementation of the RLNC decoder in use, we provide an efficient way to characterize the performance of users targeted by ultra-reliable layered multicast services. The proposed modeling allows to efficiently derive the average number of coded packet...
Stochastic optimization of GeantV code by use of genetic algorithms
Amadio, G.; Apostolakis, J.; Bandieramonte, M.; Behera, S. P.; Brun, R.; Canal, P.; Carminati, F.; Cosmo, G.; Duhem, L.; Elvira, D.; Folger, G.; Gheata, A.; Gheata, M.; Goulas, I.; Hariri, F.; Jun, S. Y.; Konstantinov, D.; Kumawat, H.; Ivantchenko, V.; Lima, G.; Nikitina, T.; Novak, M.; Pokorski, W.; Ribon, A.; Seghal, R.; Shadura, O.; Vallecorsa, S.; Wenzel, S.
2017-10-01
GeantV is a complex system based on the interaction of different modules needed for detector simulation, which include transport of particles in fields, physics models simulating their interactions with matter and a geometrical modeler library for describing the detector and locating the particles and computing the path length to the current volume boundary. The GeantV project is recasting the classical simulation approach to get maximum benefit from SIMD/MIMD computational architectures and highly massive parallel systems. This involves finding the appropriate balance between several aspects influencing computational performance (floating-point performance, usage of off-chip memory bandwidth, specification of cache hierarchy, etc.) and handling a large number of program parameters that have to be optimized to achieve the best simulation throughput. This optimization task can be treated as a black-box optimization problem, which requires searching the optimum set of parameters using only point-wise function evaluations. The goal of this study is to provide a mechanism for optimizing complex systems (high energy physics particle transport simulations) with the help of genetic algorithms and evolution strategies as tuning procedures for massive parallel simulations. One of the described approaches is based on introducing a specific multivariate analysis operator that could be used in case of resource expensive or time consuming evaluations of fitness functions, in order to speed-up the convergence of the black-box optimization problem.
Equilibrium optimization code OPEQ and results of applying it to HT-7U
International Nuclear Information System (INIS)
Zha Xuejun; Zhu Sizheng; Yu Qingquan
2003-01-01
The plasma equilibrium configuration has a strong impact on the confinement and MHD stability in tokamaks. For designing a tokamak device, it is an important issue to determine the sites and currents of poloidal coils which have some constraint conditions from physics and engineering with a prescribed equilibrium shape of the plasma. In this paper, an effective method based on multi-variables equilibrium optimization is given. The method can optimize poloidal coils when the previously prescribed plasma parameters are treated as an object function. We apply it to HT-7U equilibrium calculation, and obtain good results
Wei, Qinglai; Song, Ruizhuo; Yan, Pengfei
2016-02-01
This paper is concerned with a new data-driven zero-sum neuro-optimal control problem for continuous-time unknown nonlinear systems with disturbance. According to the input-output data of the nonlinear system, an effective recurrent neural network is introduced to reconstruct the dynamics of the nonlinear system. Considering the system disturbance as a control input, a two-player zero-sum optimal control problem is established. Adaptive dynamic programming (ADP) is developed to obtain the optimal control under the worst case of the disturbance. Three single-layer neural networks, including one critic and two action networks, are employed to approximate the performance index function, the optimal control law, and the disturbance, respectively, for facilitating the implementation of the ADP method. Convergence properties of the ADP method are developed to show that the system state will converge to a finite neighborhood of the equilibrium. The weight matrices of the critic and the two action networks are also convergent to finite neighborhoods of their optimal ones. Finally, the simulation results will show the effectiveness of the developed data-driven ADP methods.
Innovation of genetic algorithm code GenA for WWER fuel loading optimization
International Nuclear Information System (INIS)
Sustek, J.
2005-01-01
One of the stochastic search techniques - genetic algorithms - was recently used for optimization of arrangement of fuel assemblies (FA) in core of reactors WWER-440 and WWER-1000. Basic algorithm was modified by incorporation of SPEA scheme. Both were enhanced and some results are presented (Authors)
Suzuki, Taiji; Aihara, Kazuyuki
2013-09-01
These days prostate cancer is one of the most common types of malignant neoplasm in men. Androgen ablation therapy (hormone therapy) has been shown to be effective for advanced prostate cancer. However, continuous hormone therapy often causes recurrence. This results from the progression of androgen-dependent cancer cells to androgen-independent cancer cells during the continuous hormone therapy. One possible method to prevent the progression to the androgen-independent state is intermittent androgen suppression (IAS) therapy, which ceases dosing intermittently. In this paper, we propose two methods to estimate the dynamics of prostate cancer, and investigate the IAS therapy from the viewpoint of optimality. The two methods that we propose for dynamics estimation are a variational Bayesian method for a piecewise affine (PWA) system and a Gaussian process regression method. We apply the proposed methods to real clinical data and compare their predictive performances. Then, using the estimated dynamics of prostate cancer, we observe how prostate cancer behaves for various dosing schedules. It can be seen that the conventional IAS therapy is a way of imposing high cost for dosing while keeping the prostate cancer in a safe state. We would like to dedicate this paper to the memory of Professor Luigi M. Ricciardi. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
Corbetta, Matteo; Sbarufatti, Claudio; Giglio, Marco; Todd, Michael D.
2018-05-01
The present work critically analyzes the probabilistic definition of dynamic state-space models subject to Bayesian filters used for monitoring and predicting monotonic degradation processes. The study focuses on the selection of the random process, often called process noise, which is a key perturbation source in the evolution equation of particle filtering. Despite the large number of applications of particle filtering predicting structural degradation, the adequacy of the picked process noise has not been investigated. This paper reviews existing process noise models that are typically embedded in particle filters dedicated to monitoring and predicting structural damage caused by fatigue, which is monotonic in nature. The analysis emphasizes that existing formulations of the process noise can jeopardize the performance of the filter in terms of state estimation and remaining life prediction (i.e., damage prognosis). This paper subsequently proposes an optimal and unbiased process noise model and a list of requirements that the stochastic model must satisfy to guarantee high prognostic performance. These requirements are useful for future and further implementations of particle filtering for monotonic system dynamics. The validity of the new process noise formulation is assessed against experimental fatigue crack growth data from a full-scale aeronautical structure using dedicated performance metrics.
Sapenov, Yerzhan
2017-07-06
In this paper, an optical wireless multiple-input multiple-output communication system employing intensity-modulation direct-detection is considered. The performance of direct current offset space-time block codes (DC-STBC) is studied in terms of pairwise error probability (PEP). It is shown that among the class of DC-STBCs, the worst case PEP corresponding to the minimum distance between two codewords is minimized by repetition coding (RC), under both electrical and optical individual power constraints. It follows that among all DC-STBCs, RC is optimal in terms of worst-case PEP for static channels and also for varying channels under any turbulence statistics. This result agrees with previously published numerical results showing the superiority of RC in such systems. It also agrees with previously published analytic results on this topic under log-normal turbulence and further extends it to arbitrary turbulence statistics. This shows the redundancy of the time-dimension of the DC-STBC in this system. This result is further extended to sum power constraints with static and turbulent channels, where it is also shown that the time dimension is redundant, and the optimal DC-STBC has a spatial beamforming structure. Numerical results are provided to demonstrate the difference in performance for systems with different numbers of receiving apertures and different throughput.
International Nuclear Information System (INIS)
Ballon P, C. I.; Quispe V, N. Y.; Vega R, J. L. J.
2017-10-01
The computational simulation to obtain the X-ray spectrum in the range of radio-diagnosis, allows a study and advance knowledge of the transport process of X-rays in the interaction with matter using the Monte Carlo method. With the obtaining of the X-ray spectra we can know the dose that the patient receives when he undergoes a radiographic study or CT, improving the quality of the obtained image. The objective of the present work was to implement and optimize the open source Penelope (Monte Carlo code for the simulation of the transport of electrons and photons in the matter) 2008 version programming extra code in functional language F, managing to double the processing speed, thus reducing the simulation time spent and errors when optimizing the software initially programmed in Fortran 77. The results were compared with those of Penelope, obtaining a good concordance. We also simulated the obtaining of a Pdd curve (depth dose profile) for a Theratron Equinox cobalt-60 teletherapy device, also validating the software implemented for high energies. (Author)
Lee, Dongyul; Lee, Chaewoo
2014-01-01
The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.
Directory of Open Access Journals (Sweden)
Dongyul Lee
2014-01-01
Full Text Available The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC with adaptive modulation and coding (AMC provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.
Low-complexity BCH codes with optimized interleavers for DQPSK systems with laser phase noise
DEFF Research Database (Denmark)
Leong, Miu Yoong; Larsen, Knud J.; Jacobsen, Gunnar
2017-01-01
The presence of high phase noise in addition to additive white Gaussian noise in coherent optical systems affects the performance of forward error correction (FEC) schemes. In this paper, we propose a simple scheme for such systems, using block interleavers and binary Bose...... simulations. For a target post-FEC BER of 10−6, codes selected using our method result in BERs around 3× target and achieve the target with around 0.2 dB extra signal-to-noise ratio....
SEJITS: embedded specializers to turn patterns-based designs into optimized parallel code
CERN. Geneva
2012-01-01
All software should be parallel software. This is natural result of the transition to a many core world. For a small fraction of the world's programmers (efficiency programmers), this is not a problem. They enjoy mapping algorithms onto the details of a particular system and are well served by low level languages and OpenMP, MPI, or OpenCL. Most programmers, however, are "domain specialists" who write code. They are too busy working in their domain of choice (such as physics) to master the intricacies of each computer they use. How do we make these programmers productive without giving up performance? We have been working with a team at UC Berkeley's ParLab to address this problem. The key is a clear software architecture expressed in terms of design patterns that exposes the concurrency in a problem. The resulting code is written using a patterns-based framework within a high level, productivity language (such as Python). Then a separate system is used by a small group o...
Zhao, Hui; Li, Yingcai
2010-01-10
In two papers [Proc. SPIE 4471, 272-280 (2001) and Appl. Opt. 43, 2709-2721 (2004)], a logarithmic phase mask was proposed and proved to be effective in extending the depth of field; however, according to our research, this mask is not that perfect because the corresponding defocused modulation transfer function has large oscillations in the low-frequency region, even when the mask is optimized. So, in a previously published paper [Opt. Lett. 33, 1171-1173 (2008)], we proposed an improved logarithmic phase mask by making a small modification. The new mask can not only eliminate the drawbacks to a certain extent but can also be even less sensitive to focus errors according to Fisher information criteria. However, the performance comparison was carried out with the modified mask not being optimized, which was not reasonable. In this manuscript, we optimize the modified logarithmic phase mask first before analyzing its performance and more convincing results have been obtained based on the analysis of several frequently used metrics.
Energy Technology Data Exchange (ETDEWEB)
Taleei, R; Qin, N; Jiang, S [UT Southwestern Medical Center, Dallas, TX (United States); Peeler, C [UT MD Anderson Cancer Center, Houston, TX (United States); Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)
2016-06-15
Purpose: Biological treatment plan optimization is of great interest for proton therapy. It requires extensive Monte Carlo (MC) simulations to compute physical dose and biological quantities. Recently, a gPMC package was developed for rapid MC dose calculations on a GPU platform. This work investigated its suitability for proton therapy biological optimization in terms of accuracy and efficiency. Methods: We performed simulations of a proton pencil beam with energies of 75, 150 and 225 MeV in a homogeneous water phantom using gPMC and FLUKA. Physical dose and energy spectra for each ion type on the central beam axis were scored. Relative Biological Effectiveness (RBE) was calculated using repair-misrepair-fixation model. Microdosimetry calculations were performed using Monte Carlo Damage Simulation (MCDS). Results: Ranges computed by the two codes agreed within 1 mm. Physical dose difference was less than 2.5 % at the Bragg peak. RBE-weighted dose agreed within 5 % at the Bragg peak. Differences in microdosimetric quantities such as dose average lineal energy transfer and specific energy were < 10%. The simulation time per source particle with FLUKA was 0.0018 sec, while gPMC was ∼ 600 times faster. Conclusion: Physical dose computed by FLUKA and gPMC were in a good agreement. The RBE differences along the central axis were small, and RBE-weighted dose difference was found to be acceptable. The combined accuracy and efficiency makes gPMC suitable for proton therapy biological optimization.
MagRad: A code to optimize the operation of superconducting magnets in a radiation environment
International Nuclear Information System (INIS)
Yeaw, C.T.
1995-01-01
A powerful computational tool, called MagRad, has been developed which optimizes magnet design for operation in radiation fields. Specifically, MagRad has been used for the analysis and design modification of the cable-in-conduit conductors of the TF magnet systems in fusion reactor designs. Since the TF magnets must operate in a radiation environment which damages the material components of the conductor and degrades their performance, the optimization of conductor design must account not only for start-up magnet performance, but also shut-down performance. The degradation in performance consists primarily of three effects: reduced stability margin of the conductor; a transition out of the well-cooled operating regime; and an increased maximum quench temperature attained in the conductor. Full analysis of the magnet performance over the lifetime of the reactor includes: radiation damage to the conductor, stability, protection, steady state heat removal, shielding effectiveness, optimal annealing schedules, and finally costing of the magnet and reactor. Free variables include primary and secondary conductor geometric and compositional parameters, as well as fusion reactor parameters. A means of dealing with the radiation damage to the conductor, namely high temperature superconductor anneals, is proposed, examined, and demonstrated to be both technically feasible and cost effective. Additionally, two relevant reactor designs (ITER CDA and ARIES-II/IV) have been analyzed. Upon addition of pure copper strands to the cable, the ITER CDA TF magnet design was found to be marginally acceptable, although much room for both performance improvement and cost reduction exists. A cost reduction of 10-15% of the capital cost of the reactor can be achieved by adopting a suitable superconductor annealing schedule. In both of these reactor analyses, the performance predictive capability of MagRad and its associated costing techniques have been demonstrated
International Nuclear Information System (INIS)
Salko, Robert K.; Schmidt, Rodney C.; Avramova, Maria N.
2015-01-01
Highlights: • COBRA-TF was adopted by the Consortium for Advanced Simulation of LWRs. • We have improved code performance to support running large-scale LWR simulations. • Code optimization has led to reductions in execution time and memory usage. • An MPI parallelization has reduced full-core simulation time from days to minutes. - Abstract: This paper describes major improvements to the computational infrastructure of the CTF subchannel code so that full-core, pincell-resolved (i.e., one computational subchannel per real bundle flow channel) simulations can now be performed in much shorter run-times, either in stand-alone mode or as part of coupled-code multi-physics calculations. These improvements support the goals of the Department Of Energy Consortium for Advanced Simulation of Light Water Reactors (CASL) Energy Innovation Hub to develop high fidelity multi-physics simulation tools for nuclear energy design and analysis. A set of serial code optimizations—including fixing computational inefficiencies, optimizing the numerical approach, and making smarter data storage choices—are first described and shown to reduce both execution time and memory usage by about a factor of ten. Next, a “single program multiple data” parallelization strategy targeting distributed memory “multiple instruction multiple data” platforms utilizing domain decomposition is presented. In this approach, data communication between processors is accomplished by inserting standard Message-Passing Interface (MPI) calls at strategic points in the code. The domain decomposition approach implemented assigns one MPI process to each fuel assembly, with each domain being represented by its own CTF input file. The creation of CTF input files, both for serial and parallel runs, is also fully automated through use of a pressurized water reactor (PWR) pre-processor utility that uses a greatly simplified set of user input compared with the traditional CTF input. To run CTF in
Energy Technology Data Exchange (ETDEWEB)
Kirtman, Bernard [Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106 (United States); Springborg, Michael [Physical and Theoretical Chemistry, University of Saarland, 66123 Saarbrücken (Germany); Rérat, Michel [Equipe de Chimie Physique, IPREM UMR5254, Université de Pau et des Pays de l' Adour, 64000 Pau (France); Ferrero, Mauro; Lacivita, Valentina; Dovesi, Roberto [Departimeno di Chimica, IFM, Università di Torino and NIS - Nanostructure Interfaces and Surfaces - Centre of Excellence, Via P. Giuria 7, 10125 Torino (Italy); Orlando, Roberto [Departimento di Scienze e Tecnologie Avanzati, Università del Piemonte Orientale, Viale T. Michel 11, 15121 Alessandria (Italy)
2015-01-22
An implementation of the vector potential approach (VPA) for treating the response of infinite periodic systems to static and dynamic electric fields has been initiated within the CRYSTAL code. The VPA method is based on the solution of a time-dependent Hartree-Fock or Kohn-Sham equation for the crystal orbitals wherein the usual scalar potential, that describes interaction with the field, is replaced by the vector potential. This equation may be solved either by perturbation theory or by finite field methods. With some modification all the computational procedures of molecular ab initio quantum chemistry can be adapted for periodic systems. Accessible properties include the linear and nonlinear responses of both the nuclei and the electrons. The programming of static field pure electronic (hyper)polarizabilities has been successfully tested. Dynamic electronic (hyper)polarizabilities, as well as infrared and Raman intensities, are in progress while the addition of finite fields for calculation of vibrational (hyper)polarizabilities, through nuclear relaxation procedures, will begin shortly.
Sommariva, C.; Nardon, E.; Beyer, P.; Hoelzl, M.; Huijsmans, G. T. A.; van Vugt, D.; Contributors, JET
2018-01-01
In order to contribute to the understanding of runaway electron generation mechanisms during tokamak disruptions, a test particle tracker is introduced in the JOREK 3D non-linear MHD code, able to compute both full and guiding center relativistic orbits. Tests of the module show good conservation of the invariants of motion and consistency between full orbit and guiding center solutions. A first application is presented where test electron confinement properties are investigated in a massive gas injection-triggered disruption simulation in JET-like geometry. It is found that electron populations initialised before the thermal quench (TQ) are typically not fully deconfined in spite of the global stochasticity of the magnetic field during the TQ. The fraction of ‘survivors’ decreases from a few tens down to a few tenths of percent as the electron energy varies from 1 keV to 10 MeV. The underlying mechanism for electron ‘survival’ is the prompt reformation of closed magnetic surfaces at the plasma core and, to a smaller extent, the subsequent reappearance of a magnetic surface at the edge. It is also found that electrons are less deconfined at 10 MeV than at 1 MeV, which appears consistent with a phase averaging effect due to orbit shifts at high energy.
Flow analysis and port optimization of geRotor pump using commercial CFD code
Energy Technology Data Exchange (ETDEWEB)
Kim, Byung Jo; Seong, Seung Hak; Yoon, Soon Hyun [Pusan National Univ., Pusan (Korea, Republic of)
2005-07-01
GeRotor pump is widely used in the automotive industry for fuel lift, injection, engine oil lubrication, and also in transmission systems. The CFD study of the pump, which is characterized by transient flow with moving rotor boundaries, has been performed to obtain the most optimum shape of the inlet/outlet port of the pump. Various shapes of the port have been tested to investigate how they affect flow rates and fluctuations. Based on the parametric study, an optimum shape has been determined for the maximum flow rate and minimum fluctuations. The result has been confirmed by experiments. For the optimization, Taguchi method has been adapted. The groove shape has been found to be the most important factor among the selected several parameters related to flow rate and fluctuations.
Optimal coding-decoding for systems controlled via a communication channel
Yi-wei, Feng; Guo, Ge
2013-12-01
In this article, we study the problem of controlling plants over a signal-to-noise ratio (SNR) constrained communication channel. Different from previous research, this article emphasises the importance of the actual channel model and coder/decoder in the study of network performance. Our major objectives include coder/decoder design for an additive white Gaussian noise (AWGN) channel with both standard network configuration and Youla parameter network architecture. We find that the optimal coder and decoder can be realised for different network configuration. The results are useful in determining the minimum channel capacity needed in order to stabilise plants over communication channels. The coder/decoder obtained can be used to analyse the effect of uncertainty on the channel capacity. An illustrative example is provided to show the effectiveness of the results.
Zhao, Hui; Li, Yingcai
2010-08-01
In a previous Letter [Opt. Lett. 33, 1171 (2008)], we proposed an improved logarithmic phase mask by making modifications to the original one designed by Sherif. However, further studies in another paper [Appl. Opt. 49, 229 (2010)] show that even when the Sherif mask and the improved one are optimized, their corresponding defocused modulation transfer functions (MTFs) are still not stable with respect to focus errors. So, by further modifying their phase profiles, we design another two logarithmic phase masks that exhibit more stable defocused MTF. However, with the defocus-induced phase effect considered, we find that the performance of the two masks proposed in this Letter is better than the Sherif mask, but worse than our previously proposed phase mask, according to the Hilbert space angle.
ActiWiz – optimizing your nuclide inventory at proton accelerators with a computer code
Vincke, Helmut
2014-01-01
When operating an accelerator one always faces unwanted, but inevitable beam losses. These result in activation of adjacent material, which in turn has an obvious impact on safety and handling constraints. One of the key parameters responsible for activation is the chemical composition of the material which often can be optimized in that respect. In order to facilitate this task also for non-expert users the ActiWiz software has been developed at CERN. Based on a large amount of generic FLUKA Monte Carlo simulations the software applies a specifically developed risk assessment model to provide support to decision makers especially during the design phase as well as common operational work in the domain of radiation protection.
Oh, Jihoon; Chae, Jeong-Ho
2018-04-01
Although heart rate variability (HRV) may be a crucial marker of mental health, how it is related to positive psychological factors (i.e. attitude to life and positive thinking) is largely unknown. Here we investigated the correlation of HRV linear and nonlinear dynamics with psychological scales that measured degree of optimism and happiness in patients with anxiety disorders. Results showed that low- to high-frequency HRV ratio (LF/HF) was increased and the HRV HF parameter was decreased in subjects who were more optimistic and who felt happier in daily living. Nonlinear analysis also showed that HRV dispersion and regulation were significantly correlated with the subjects' optimism and purpose in life. Our findings showed that HRV properties might be related to degree of optimistic perspectives on life and suggests that HRV markers of autonomic nervous system function could reflect positive human mind states.
International Nuclear Information System (INIS)
Sekiguchi, Miho; Nakajima, Teruyuki
2008-01-01
The gas absorption process scheme in the broadband radiative transfer code 'mstrn8', which is used to calculate atmospheric radiative transfer efficiently in a general circulation model, is improved. Three major improvements are made. The first is an update of the database of line absorption parameters and the continuum absorption model. The second is a change to the definition of the selection rule for gas absorption used to choose which absorption bands to include. The last is an upgrade of the optimization method used to decrease the number of quadrature points used for numerical integration in the correlated k-distribution approach, thereby realizing higher computational efficiency without losing accuracy. The new radiation package termed 'mstrnX' computes radiation fluxes and heating rates with errors less than 0.6 W/m 2 and 0.3 K/day, respectively, through the troposphere and the lower stratosphere for any standard AFGL atmospheres. A serious cold bias problem of an atmospheric general circulation model using the ancestor code 'mstrn8' is almost solved by the upgrade to 'mstrnX'
Energy Technology Data Exchange (ETDEWEB)
Welsch, Dominic Markus
2010-03-10
The High-Energy Storage Ring (HESR) is part of the upcoming Facility for Antiproton and Ion Research (FAIR) which is planned as a major extension to the present facility of the Helmholtzzentrum fuer Schwerionenforschung (GSI) in Darmstadt. The HESR will provide antiprotons in the momentum range from 1.5 to 15 GeV/c for the internal target experiment PANDA. The demanding requirements of PANDA in terms of beam quality and luminosity together with a limited production rate of antiprotons call for a long beam life time and a minimum of beam loss. Therefore, an effective closed orbit correction and a sufficiently large dynamic aperture of the HESR are crucial. With this thesis I present my work on both of these topics. The expected misalignments of beam guiding magnets have been estimated and used to simulate the closed orbit in the HESR. A closed orbit correction scheme has been developed for different ion optical settings of the HESR and numerical simulations have been performed to validate the scheme. The proposed closed orbit correction method which uses the orbit response matrix has been benchmarked at the Cooler Synchrotron COSY of the Forschungszentrum Juelich. A chromaticity correction scheme for the HESR consisting of sextupole magnets has been developed to reduce tune spread and thus to minimize the emittance growth caused by betatron resonances. The chromaticity correction scheme has been optimized through dynamic aperture calculations. The estimated field errors of the HESR dipole and quadrupole magnets have been included in the non-linear beam dynamics studies. Investigations concerning their optimization have been carried out. The ion optical settings of the HESR have been improved using dynamic aperture calculations and the technique of frequency map analysis. The related diffusion coefficient was also used to predict long-term stability based on short-term particle tracking. With a reasonable reduction of the quadrupole magnets field errors and a
International Nuclear Information System (INIS)
Bouzid, M.; Benkherouf, H.; Benzadi, K.
2011-01-01
In this paper, we propose a stochastic joint source-channel scheme developed for efficient and robust encoding of spectral speech LSF parameters. The encoding system, named LSF-SSCOVQ-RC, is an LSF encoding scheme based on a reduced complexity stochastic split vector quantizer optimized for noisy channel. For transmissions over noisy channel, we will show first that our LSF-SSCOVQ-RC encoder outperforms the conventional LSF encoder designed by the split vector quantizer. After that, we applied the LSF-SSCOVQ-RC encoder (with weighted distance) for the robust encoding of LSF parameters of the 2.4 Kbits/s MELP speech coder operating over a noisy/noiseless channel. The simulation results will show that the proposed LSF encoder, incorporated in the MELP, ensure better performances than the original MELP MSVQ of 25 bits/frame; especially when the transmission channel is highly disturbed. Indeed, we will show that the LSF-SSCOVQ-RC yields significant improvement to the LSFs encoding performances by ensuring reliable transmissions over noisy channel.
Energy Technology Data Exchange (ETDEWEB)
Hwang, Jong Rok; Oh, Seung Jong [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)
2013-10-15
In this study, we examined optimum operator actions to mitigate extended SBO using MARS code. Particularly, this paper focuses on analyzing outside core cooling water injection scenario, and aimed to develop optimal extended SBO procedure. Supplying outside emergency cooling water is the key feature of flexible strategy in extended SBO situation. An optimum strategy to maintain core cooling is developed for typical extended SBO. MARS APR1400 best estimate model was used to find optimal procedure. Also RCP seal leakage effect was considered importantly. Recent Fukushima accident shows the importance of mitigation capability against extended SBO scenarios. In Korea, all nuclear power plants incorporated various measures against Fukushima-like events. For APR1400 NPP, outside connectors are installed to inject cooling water using fire trucks or portable pumps. Using these connectors, outside cooling water can be provided to reactor, steam generators (SG), containment spray system, and spent fuel pool. In U. S., similar approach is chosen to provide a diverse and flexible means to prevent fuel damage (core and SFP) in external event conditions resulting in extended loss of AC power and loss of ultimate heat sink. Hence, hardware necessary to cope with extended SBO is already available for APR1400. However, considering the complex and stressful condition encountered by operators during extended SBO, it is important to develop guidelines/procedures to best cope with the event.
Energy Technology Data Exchange (ETDEWEB)
Delbecq, J.M
1999-07-01
The Aster code is a 2D or 3D finite-element calculation code for structures developed by the R and D direction of Electricite de France (EdF). This dossier presents a complete overview of the characteristics and uses of the Aster code: introduction of version 4; the context of Aster (organisation of the code development, versions, systems and interfaces, development tools, quality assurance, independent validation); static mechanics (linear thermo-elasticity, Euler buckling, cables, Zarka-Casier method); non-linear mechanics (materials behaviour, big deformations, specific loads, unloading and loss of load proportionality indicators, global algorithm, contact and friction); rupture mechanics (G energy restitution level, restitution level in thermo-elasto-plasticity, 3D local energy restitution level, KI and KII stress intensity factors, calculation of limit loads for structures), specific treatments (fatigue, rupture, wear, error estimation); meshes and models (mesh generation, modeling, loads and boundary conditions, links between different modeling processes, resolution of linear systems, display of results etc..); vibration mechanics (modal and harmonic analysis, dynamics with shocks, direct transient dynamics, seismic analysis and aleatory dynamics, non-linear dynamics, dynamical sub-structuring); fluid-structure interactions (internal acoustics, mass, rigidity and damping); linear and non-linear thermal analysis; steels and metal industry (structure transformations); coupled problems (internal chaining, internal thermo-hydro-mechanical coupling, chaining with other codes); products and services. (J.S.)
Yan, Zhiqiang; Jerabkova, Tereza; Kroupa, Pavel
2017-11-01
Here we present a full description of the integrated galaxy-wide initial mass function (IGIMF) theory in terms of the optimal sampling and compare it with available observations. Optimal sampling is the method we use to discretize the IMF deterministically into stellar masses. Evidence indicates that nature may be closer to deterministic sampling as observations suggest a smaller scatter of various relevant observables than random sampling would give, which may result from a high level of self-regulation during the star formation process. We document the variation of IGIMFs under various assumptions. The results of the IGIMF theory are consistent with the empirical relation between the total mass of a star cluster and the mass of its most massive star, and the empirical relation between the star formation rate (SFR) of a galaxy and the mass of its most massive cluster. Particularly, we note a natural agreement with the empirical relation between the IMF power-law index and the SFR of a galaxy. The IGIMF also results in a relation between the SFR of a galaxy and the mass of its most massive star such that, if there were no binaries, galaxies with SFR first time, we show optimally sampled galaxy-wide IMFs (OSGIMF) that mimic the IGIMF with an additional serrated feature. Finally, a Python module, GalIMF, is provided allowing the calculation of the IGIMF and OSGIMF dependent on the galaxy-wide SFR and metallicity. A copy of the python code model is available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/607/A126
International Nuclear Information System (INIS)
Lenain, Roland
2015-01-01
This thesis is devoted to the implementation of a domain decomposition method applied to the neutron transport equation. The objective of this work is to access high-fidelity deterministic solutions to properly handle heterogeneities located in nuclear reactor cores, for problems' size ranging from color-sets of assemblies to large reactor cores configurations in 2D and 3D. The innovative algorithm developed during the thesis intends to optimize the use of parallelism and memory. The approach also aims to minimize the influence of the parallel implementation on the performances. These goals match the needs of APOLLO3 project, developed at CEA and supported by EDF and AREVA, which must be a portable code (no optimization on a specific architecture) in order to achieve best estimate modeling with resources ranging from personal computer to compute cluster available for engineers analyses. The proposed algorithm is a Parallel Multigroup-Block Jacobi one. Each sub-domain is considered as a multi-group fixed-source problem with volume-sources (fission) and surface-sources (interface flux between the sub-domains). The multi-group problem is solved in each sub-domain and a single communication of the interface flux is required at each power iteration. The spectral radius of the resolution algorithm is made similar to the one of a classical resolution algorithm with a nonlinear diffusion acceleration method: the well-known Coarse Mesh Finite Difference. In this way an ideal scalability is achievable when the calculation is parallelized. The memory organization, taking advantage of shared memory parallelism, optimizes the resources by avoiding redundant copies of the data shared between the sub-domains. Distributed memory architectures are made available by a hybrid parallel method that combines both paradigms of shared memory parallelism and distributed memory parallelism. For large problems, these architectures provide a greater number of processors and the amount of
Bizon, Nicu; Mahdavi Tabatabaei, Naser
2014-01-01
This book explains and analyzes the dynamic performance of linear and nonlinear systems, particularly for Power Systems including Hybrid Power Sources. Offers a detailed description of system stability using state space energy conservation principle, and more.
International Nuclear Information System (INIS)
Fonville, Judith M.; Bylesjoe, Max; Coen, Muireann; Nicholson, Jeremy K.; Holmes, Elaine; Lindon, John C.; Rantalainen, Mattias
2011-01-01
Highlights: → Non-linear modeling of metabonomic data using K-OPLS. → automated optimization of the kernel parameter by simulated annealing. → K-OPLS provides improved prediction performance for exemplar spectral data sets. → software implementation available for R and Matlab under GPL v2 license. - Abstract: Linear multivariate projection methods are frequently applied for predictive modeling of spectroscopic data in metabonomic studies. The OPLS method is a commonly used computational procedure for characterizing spectral metabonomic data, largely due to its favorable model interpretation properties providing separate descriptions of predictive variation and response-orthogonal structured noise. However, when the relationship between descriptor variables and the response is non-linear, conventional linear models will perform sub-optimally. In this study we have evaluated to what extent a non-linear model, kernel-based orthogonal projections to latent structures (K-OPLS), can provide enhanced predictive performance compared to the linear OPLS model. Just like its linear counterpart, K-OPLS provides separate model components for predictive variation and response-orthogonal structured noise. The improved model interpretation by this separate modeling is a property unique to K-OPLS in comparison to other kernel-based models. Simulated annealing (SA) was used for effective and automated optimization of the kernel-function parameter in K-OPLS (SA-K-OPLS). Our results reveal that the non-linear K-OPLS model provides improved prediction performance in three separate metabonomic data sets compared to the linear OPLS model. We also demonstrate how response-orthogonal K-OPLS components provide valuable biological interpretation of model and data. The metabonomic data sets were acquired using proton Nuclear Magnetic Resonance (NMR) spectroscopy, and include a study of the liver toxin galactosamine, a study of the nephrotoxin mercuric chloride and a study of
Directory of Open Access Journals (Sweden)
Toly Chen
2012-01-01
Full Text Available A nonlinear programming and artificial neural network approach is presented in this study to optimize the performance of a job dispatching rule in a wafer fabrication factory. The proposed methodology fuses two existing rules and constructs a nonlinear programming model to choose the best values of parameters in the two rules by dynamically maximizing the standard deviation of the slack, which has been shown to benefit scheduling performance by several studies. In addition, a more effective approach is also applied to estimate the remaining cycle time of a job, which is empirically shown to be conducive to the scheduling performance. The efficacy of the proposed methodology was validated with a simulated case; evidence was found to support its effectiveness. We also suggested several directions in which it can be exploited in the future.
Rapid assessment of nonlinear optical propagation effects in dielectrics
Hoyo, J. Del; de La Cruz, A. Ruiz; Grace, E.; Ferrer, A.; Siegel, J.; Pasquazi, A.; Assanto, G.; Solis, J.
2015-01-01
Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process.
Hecht-Nielsen, Robert
1997-04-01
A new universal one-chart smooth manifold model for vector information sources is introduced. Natural coordinates (a particular type of chart) for such data manifolds are then defined. Uniformly quantized natural coordinates form an optimal vector quantization code for a general vector source. Replicator neural networks (a specialized type of multilayer perceptron with three hidden layers) are the introduced. As properly configured examples of replicator networks approach minimum mean squared error (e.g., via training and architecture adjustment using randomly chosen vectors from the source), these networks automatically develop a mapping which, in the limit, produces natural coordinates for arbitrary source vectors. The new concept of removable noise (a noise model applicable to a wide variety of real-world noise processes) is then discussed. Replicator neural networks, when configured to approach minimum mean squared reconstruction error (e.g., via training and architecture adjustment on randomly chosen examples from a vector source, each with randomly chosen additive removable noise contamination), in the limit eliminate removable noise and produce natural coordinates for the data vector portions of the noise-corrupted source vectors. Consideration regarding selection of the dimension of a data manifold source model and the training/configuration of replicator neural networks are discussed.
International Nuclear Information System (INIS)
Taboada, Horacio; Solis, Diego
1999-01-01
DART (Dispersion Analysis Research Tool) calculation and assessment program is a thermomechanical computer model developed by Dr. J. Rest of Argonne National Laboratory, USA. This program is the only mechanistic model available to assure the performance of low-enriched oxided-based dispersion fuels, dispersion of siliciures and uranium intermetallics in aluminum matrix for research reactors. The program predicts fission-products induced swelling (especially gases), fuel behavior during fabrication porosity closing, macroscopical changes in diameter of rods or width of plates and tubes produced by fuel deformation, degradation of thermal conductivity of fuel dispersion owing to irradiation and fuel restructuring because of Al-fuel reaction, amorphization and recrystallization. (author)
Energy Technology Data Exchange (ETDEWEB)
Deslippe, Jack; da Jornada, Felipe H.; Vigil-Fowler, Derek; Barnes, Taylor; Wichmann, Nathan; Raman, Karthik; Sasanka, Ruchira; Louie, Steven G.
2016-10-06
We profile and optimize calculations performed with the BerkeleyGW code on the Xeon-Phi architecture. BerkeleyGW depends both on hand-tuned critical kernels as well as on BLAS and FFT libraries. We describe the optimization process and performance improvements achieved. We discuss a layered parallelization strategy to take advantage of vector, thread and node-level parallelism. We discuss locality changes (including the consequence of the lack of L3 cache) and effective use of the on-package high-bandwidth memory. We show preliminary results on Knights-Landing including a roofline study of code performance before and after a number of optimizations. We find that the GW method is particularly well-suited for many-core architectures due to the ability to exploit a large amount of parallelism over plane-wave components, band-pairs, and frequencies.
Cai, Yao; Hu, Huasi; Pan, Ziheng; Hu, Guang; Zhang, Tao
2018-05-17
To optimize the shield for neutrons and gamma rays compact and lightweight, a method combining the structure and components together was established employing genetic algorithms and MCNP code. As a typical case, the fission energy spectrum of 235 U which mixed neutrons and gamma rays was adopted in this study. Six types of materials were presented and optimized by the method. Spherical geometry was adopted in the optimization after checking the geometry effect. Simulations have made to verify the reliability of the optimization method and the efficiency of the optimized materials. To compare the materials visually and conveniently, the volume and weight needed to build a shield are employed. The results showed that, the composite multilayer material has the best performance. Copyright © 2018 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Kurosu, Keita [Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871 (Japan); Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871 (Japan); Takashina, Masaaki; Koizumi, Masahiko [Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871 (Japan); Das, Indra J. [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN 46202 (United States); Moskvin, Vadim P., E-mail: vadim.p.moskvin@gmail.com [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN 46202 (United States)
2014-10-01
Although three general-purpose Monte Carlo (MC) simulation tools: Geant4, FLUKA and PHITS have been used extensively, differences in calculation results have been reported. The major causes are the implementation of the physical model, preset value of the ionization potential or definition of the maximum step size. In order to achieve artifact free MC simulation, an optimized parameters list for each simulation system is required. Several authors have already proposed the optimized lists, but those studies were performed with a simple system such as only a water phantom. Since particle beams have a transport, interaction and electromagnetic processes during beam delivery, establishment of an optimized parameters-list for whole beam delivery system is therefore of major importance. The purpose of this study was to determine the optimized parameters list for GATE and PHITS using proton treatment nozzle computational model. The simulation was performed with the broad scanning proton beam. The influences of the customizing parameters on the percentage depth dose (PDD) profile and the proton range were investigated by comparison with the result of FLUKA, and then the optimal parameters were determined. The PDD profile and the proton range obtained from our optimized parameters list showed different characteristics from the results obtained with simple system. This led to the conclusion that the physical model, particle transport mechanics and different geometry-based descriptions need accurate customization in planning computational experiments for artifact-free MC simulation.
International Nuclear Information System (INIS)
Kurosu, Keita; Takashina, Masaaki; Koizumi, Masahiko; Das, Indra J.; Moskvin, Vadim P.
2014-01-01
Although three general-purpose Monte Carlo (MC) simulation tools: Geant4, FLUKA and PHITS have been used extensively, differences in calculation results have been reported. The major causes are the implementation of the physical model, preset value of the ionization potential or definition of the maximum step size. In order to achieve artifact free MC simulation, an optimized parameters list for each simulation system is required. Several authors have already proposed the optimized lists, but those studies were performed with a simple system such as only a water phantom. Since particle beams have a transport, interaction and electromagnetic processes during beam delivery, establishment of an optimized parameters-list for whole beam delivery system is therefore of major importance. The purpose of this study was to determine the optimized parameters list for GATE and PHITS using proton treatment nozzle computational model. The simulation was performed with the broad scanning proton beam. The influences of the customizing parameters on the percentage depth dose (PDD) profile and the proton range were investigated by comparison with the result of FLUKA, and then the optimal parameters were determined. The PDD profile and the proton range obtained from our optimized parameters list showed different characteristics from the results obtained with simple system. This led to the conclusion that the physical model, particle transport mechanics and different geometry-based descriptions need accurate customization in planning computational experiments for artifact-free MC simulation
Vector Network Coding Algorithms
Ebrahimi, Javad; Fragouli, Christina
2010-01-01
We develop new algebraic algorithms for scalar and vector network coding. In vector network coding, the source multicasts information by transmitting vectors of length L, while intermediate nodes process and combine their incoming packets by multiplying them with L x L coding matrices that play a similar role as coding c in scalar coding. Our algorithms for scalar network jointly optimize the employed field size while selecting the coding coefficients. Similarly, for vector coding, our algori...
Zaghian, Maryam; Cao, Wenhua; Liu, Wei; Kardar, Laleh; Randeniya, Sharmalee; Mohan, Radhe; Lim, Gino
2017-03-01
Robust optimization of intensity-modulated proton therapy (IMPT) takes uncertainties into account during spot weight optimization and leads to dose distributions that are resilient to uncertainties. Previous studies demonstrated benefits of linear programming (LP) for IMPT in terms of delivery efficiency by considerably reducing the number of spots required for the same quality of plans. However, a reduction in the number of spots may lead to loss of robustness. The purpose of this study was to evaluate and compare the performance in terms of plan quality and robustness of two robust optimization approaches using LP and nonlinear programming (NLP) models. The so-called "worst case dose" and "minmax" robust optimization approaches and conventional planning target volume (PTV)-based optimization approach were applied to designing IMPT plans for five patients: two with prostate cancer, one with skull-based cancer, and two with head and neck cancer. For each approach, both LP and NLP models were used. Thus, for each case, six sets of IMPT plans were generated and assessed: LP-PTV-based, NLP-PTV-based, LP-worst case dose, NLP-worst case dose, LP-minmax, and NLP-minmax. The four robust optimization methods behaved differently from patient to patient, and no method emerged as superior to the others in terms of nominal plan quality and robustness against uncertainties. The plans generated using LP-based robust optimization were more robust regarding patient setup and range uncertainties than were those generated using NLP-based robust optimization for the prostate cancer patients. However, the robustness of plans generated using NLP-based methods was superior for the skull-based and head and neck cancer patients. Overall, LP-based methods were suitable for the less challenging cancer cases in which all uncertainty scenarios were able to satisfy tight dose constraints, while NLP performed better in more difficult cases in which most uncertainty scenarios were hard to meet
International Nuclear Information System (INIS)
Jiang, He; Dong, Yao
2016-01-01
Highlights: • Eclat data mining algorithm is used to determine the possible predictors. • Support vector machine is converted into a ridge regularization problem. • Hard penalty selects the number of radial basis functions to simply the structure. • Glowworm swarm optimization is utilized to determine the optimal parameters. - Abstract: For a portion of the power which is generated by grid connected photovoltaic installations, an effective solar irradiation forecasting approach must be crucial to ensure the quality and the security of power grid. This paper develops and investigates a novel model to forecast 30 daily global solar radiation at four given locations of the United States. Eclat data mining algorithm is first presented to discover association rules between solar radiation and several meteorological factors laying a theoretical foundation for these correlative factors as input vectors. An effective and innovative intelligent optimization model based on nonlinear support vector machine and hard penalty function is proposed to forecast solar radiation by converting support vector machine into a regularization problem with ridge penalty, adding a hard penalty function to select the number of radial basis functions, and using glowworm swarm optimization algorithm to determine the optimal parameters of the model. In order to illustrate our validity of the proposed method, the datasets at four sites of the United States are split to into training data and test data, separately. The experiment results reveal that the proposed model delivers the best forecasting performances comparing with other competitors.
Nonlinear Approaches in Engineering Applications
Jazar, Reza
2012-01-01
Nonlinear Approaches in Engineering Applications focuses on nonlinear phenomena that are common in the engineering field. The nonlinear approaches described in this book provide a sound theoretical base and practical tools to design and analyze engineering systems with high efficiency and accuracy and with less energy and downtime. Presented here are nonlinear approaches in areas such as dynamic systems, optimal control and approaches in nonlinear dynamics and acoustics. Coverage encompasses a wide range of applications and fields including mathematical modeling and nonlinear behavior as applied to microresonators, nanotechnologies, nonlinear behavior in soil erosion,nonlinear population dynamics, and optimization in reducing vibration and noise as well as vibration in triple-walled carbon nanotubes. This book also: Provides a complete introduction to nonlinear behavior of systems and the advantages of nonlinearity as a tool for solving engineering problems Includes applications and examples drawn from the el...
International Nuclear Information System (INIS)
Jannati Isfahani, A.; Shokrani, P.; Raisali, Gh.
2010-01-01
Ophthalmic plaque radiotherapy using I-125 radioactive seeds in removable episcleral plaques is often used in management of ophthalmic tumors. Radioactive seeds are fixed in a gold bowl-shaped plaque and the plaque is sutured to the scleral surface corresponding to the base of the intraocular tumor. This treatment allows for a localized radiation dose delivery to the tumor with a minimum target dose of 85 Gy. The goal of this study was to develop a Monte Carlo simulation method for treatment planning optimization of the COMS and USC eye plaques. Material and Methods: The MCNP4C code was used to simulate three plaques: COMS-12mm, COMS-20mm, and USC ≠9 with I-125 seeds. Calculation of dose was performed in a spherical water phantom (radius 12 mm) using a 3D matrix with a size of 12 voxels in each dimension. Each voxel contained a sphere of radius 1 mm. Results: Dose profiles were calculated for each plaque. Isodose lines were created in 2 planes normal to the axes of the plaque, at the base of the tumor and at the level of the 85 Gy isodose in a 7 day treatment. Discussion and Conclusion: This study shows that it is necessary to consider the following tumor properties in design or selection of an eye plaque: the diameter of tumor base, its thickness and geometric shape, and the tumor location with respect to normal critical structures. The plaque diameter is selected by considering the tumor diameter. Tumor thickness is considered when selecting the seed parameters such as their number, activity and distribution. Finally, tumor shape and its location control the design of following parameters: the shape and material of the plaque and the need for collimation.
International Nuclear Information System (INIS)
Ishigami, Tsutomu; Oyama, Kazuo
1989-09-01
This report presents a new method to support selection of off-site protective action in nuclear reactor accidents, and provides a user's manual of a computer code system, PRASMA, developed using the method. The PRASMA code system gives several candidates of protective action zones of evacuation, sheltering and no action based on the multiobjective optimization method, which requires objective functions and decision variables. We have assigned population risks of fatality, injury and cost as the objective functions, and distance from a nuclear power plant characterizing the above three protective action zones as the decision variables. (author)
Performance optimization of PM-16QAM transmission system enabled by real-time self-adaptive coding.
Qu, Zhen; Li, Yao; Mo, Weiyang; Yang, Mingwei; Zhu, Shengxiang; Kilper, Daniel C; Djordjevic, Ivan B
2017-10-15
We experimentally demonstrate self-adaptive coded 5×100 Gb/s WDM polarization multiplexed 16 quadrature amplitude modulation transmission over a 100 km fiber link, which is enabled by a real-time control plane. The real-time optical signal-to-noise ratio (OSNR) is measured using an optical performance monitoring device. The OSNR measurement is processed and fed back using control plane logic and messaging to the transmitter side for code adaptation, where the binary data are adaptively encoded with three types of low-density parity-check (LDPC) codes with code rates of 0.8, 0.75, and 0.7 of large girth. The total code-adaptation latency is measured to be 2273 ms. Compared with transmission without adaptation, average net capacity improvements of 102%, 36%, and 7.5% are obtained, respectively, by adaptive LDPC coding.
Energy Technology Data Exchange (ETDEWEB)
Moen, C.D.; Spence, P.A.; Meza, J.C.; Plantenga, T.D.
1996-12-31
Automatic differentiation is applied to the optimal design of microelectronic manufacturing equipment. The performance of nonlinear, least-squares optimization methods is compared between numerical and analytical gradient approaches. The optimization calculations are performed by running large finite-element codes in an object-oriented optimization environment. The Adifor automatic differentiation tool is used to generate analytic derivatives for the finite-element codes. The performance results support previous observations that automatic differentiation becomes beneficial as the number of optimization parameters increases. The increase in speed, relative to numerical differences, has a limited value and results are reported for two different analysis codes.
International Nuclear Information System (INIS)
Trejos, Sorayda; Barrera, John Fredy; Torroba, Roberto
2015-01-01
We present for the first time an optical encrypting–decrypting protocol for recovering messages without speckle noise. This is a digital holographic technique using a 2f scheme to process QR codes entries. In the procedure, letters used to compose eventual messages are individually converted into a QR code, and then each QR code is divided into portions. Through a holographic technique, we store each processed portion. After filtering and repositioning, we add all processed data to create a single pack, thus simplifying the handling and recovery of multiple QR code images, representing the first multiplexing procedure applied to processed QR codes. All QR codes are recovered in a single step and in the same plane, showing neither cross-talk nor noise problems as in other methods. Experiments have been conducted using an interferometric configuration and comparisons between unprocessed and recovered QR codes have been performed, showing differences between them due to the involved processing. Recovered QR codes can be successfully scanned, thanks to their noise tolerance. Finally, the appropriate sequence in the scanning of the recovered QR codes brings a noiseless retrieved message. Additionally, to procure maximum security, the multiplexed pack could be multiplied by a digital diffuser as to encrypt it. The encrypted pack is easily decoded by multiplying the multiplexing with the complex conjugate of the diffuser. As it is a digital operation, no noise is added. Therefore, this technique is threefold robust, involving multiplexing, encryption, and the need of a sequence to retrieve the outcome. (paper)
Trejos, Sorayda; Fredy Barrera, John; Torroba, Roberto
2015-08-01
We present for the first time an optical encrypting-decrypting protocol for recovering messages without speckle noise. This is a digital holographic technique using a 2f scheme to process QR codes entries. In the procedure, letters used to compose eventual messages are individually converted into a QR code, and then each QR code is divided into portions. Through a holographic technique, we store each processed portion. After filtering and repositioning, we add all processed data to create a single pack, thus simplifying the handling and recovery of multiple QR code images, representing the first multiplexing procedure applied to processed QR codes. All QR codes are recovered in a single step and in the same plane, showing neither cross-talk nor noise problems as in other methods. Experiments have been conducted using an interferometric configuration and comparisons between unprocessed and recovered QR codes have been performed, showing differences between them due to the involved processing. Recovered QR codes can be successfully scanned, thanks to their noise tolerance. Finally, the appropriate sequence in the scanning of the recovered QR codes brings a noiseless retrieved message. Additionally, to procure maximum security, the multiplexed pack could be multiplied by a digital diffuser as to encrypt it. The encrypted pack is easily decoded by multiplying the multiplexing with the complex conjugate of the diffuser. As it is a digital operation, no noise is added. Therefore, this technique is threefold robust, involving multiplexing, encryption, and the need of a sequence to retrieve the outcome.
DEFF Research Database (Denmark)
Ghoreishi, Newsha; Sørensen, Jan Corfixen; Jørgensen, Bo Nørregaard
2015-01-01
Non-trivial real world decision-making processes usually involve multiple parties having potentially conflicting interests over a set of issues. State-of-the-art multi-objective evolutionary algorithms (MOEA) are well known to solve this class of complex real-world problems. In this paper, we...... compare the performance of state-of-the-art multi-objective evolutionary algorithms to solve a non-linear multi-objective multi-issue optimisation problem found in Greenhouse climate control. The chosen algorithms in the study includes NSGAII, eNSGAII, eMOEA, PAES, PESAII and SPEAII. The performance...... of all aforementioned algorithms is assessed and compared using performance indicators to evaluate proximity, diversity and consistency. Our insights to this comparative study enhanced our understanding of MOEAs performance in order to solve a non-linear complex climate control problem. The empirical...
Directory of Open Access Journals (Sweden)
Qian Xie
2016-07-01
Full Text Available This paper pays attention to magnetic flux linkage optimization of a direct-driven surface-mounted permanent magnet synchronous generator (D-SPMSG. A new compact representation of the D-SPMSG nonlinear dynamic differential equations to reduce system parameters is established. Furthermore, the nonlinear dynamic characteristics of new D-SPMSG equations in the process of varying magnetic flux linkage are considered, which are illustrated by Lyapunov exponent spectrums, phase orbits, Poincaré maps, time waveforms and bifurcation diagrams, and the magnetic flux linkage stable region of D-SPMSG is acquired concurrently. Based on the above modeling and analyses, a novel method of magnetic flux linkage optimization is presented. In addition, a 2 MW D-SPMSG 2D/3D model is designed by ANSYS software according to the practical design requirements. Finally, five cases of D-SPMSG models with different magnetic flux linkages are simulated by using the finite element analysis (FEA method. The nephograms of magnetic flux density are agreement with theoretical analysis, which both confirm the correctness and effectiveness of the proposed approach.
Energy Technology Data Exchange (ETDEWEB)
Dellin, T.A.; Fish, M.J.; Yang, C.L.
1981-08-01
DELSOL2 is a revised and substantially extended version of the DELSOL computer program for calculating collector field performance and layout, and optimal system design for solar thermal central receiver plants. The code consists of a detailed model of the optical performance, a simpler model of the non-optical performance, an algorithm for field layout, and a searching algorithm to find the best system design. The latter two features are coupled to a cost model of central receiver components and an economic model for calculating energy costs. The code can handle flat, focused and/or canted heliostats, and external cylindrical, multi-aperture cavity, and flat plate receivers. The program optimizes the tower height, receiver size, field layout, heliostat spacings, and tower position at user specified power levels subject to flux limits on the receiver and land constraints for field layout. The advantages of speed and accuracy characteristic of Version I are maintained in DELSOL2.