Garcia-Pareja, S. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' Carlos Haya' , Avda. Carlos Haya, s/n, E-29010 Malaga (Spain)], E-mail: garciapareja@gmail.com; Vilches, M. [Servicio de Fisica y Proteccion Radiologica, Hospital Regional Universitario ' Virgen de las Nieves' , Avda. de las Fuerzas Armadas, 2, E-18014 Granada (Spain); Lallena, A.M. [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)
2007-09-21
The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool.
Garcia-Pareja, S.; Vilches, M.; Lallena, A.M.
2007-01-01
The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool
Jing, Yaqi; Meng, Qinghao, E-mail: qh-meng@tju.edu.cn; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen [Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)
2014-05-15
An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively.
Jing, Yaqi; Meng, Qinghao; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen
2014-01-01
An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively
Linearization Method and Linear Complexity
Tanaka, Hidema
We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N(≅2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.
Reduction of Linear Programming to Linear Approximation
Vaserstein, Leonid N.
2006-01-01
It is well known that every Chebyshev linear approximation problem can be reduced to a linear program. In this paper we show that conversely every linear program can be reduced to a Chebyshev linear approximation problem.
Nam Lyong Kang
2013-07-01
Full Text Available The projection-reduction method introduced by the present authors is known to give a validated theory for optical transitions in the systems of electrons interacting with phonons. In this work, using this method, we derive the linear and first order nonlinear optical conductivites for an electron-impurity system and examine whether the expressions faithfully satisfy the quantum mechanical philosophy, in the same way as for the electron-phonon systems. The result shows that the Fermi distribution function for electrons, energy denominators, and electron-impurity coupling factors are contained properly in organized manners along with absorption of photons for each electron transition process in the final expressions. Furthermore, the result is shown to be represented properly by schematic diagrams, as in the formulation of electron-phonon interaction. Therefore, in conclusion, we claim that this method can be applied in modeling optical transitions of electrons interacting with both impurities and phonons.
Bhattacharya, S.; Maiti, R.; Saha, S.; Das, A. C.; Mondal, S.; Ray, S. K.; Bhaktha, S. B. N.; Datta, P. K.
2016-04-01
Graphene Oxide (GO) has been prepared by modified Hummers method and it has been reduced using an IR bulb (800-2000 nm). Both as grown GO and reduced graphene oxide (RGO) have been characterized using Raman spectroscopy and X-ray photoelectron spectroscopy (XPS). Raman spectra shows well documented Dband and G-band for both the samples while blue shift of G-band confirms chemical functionalization of graphene with different oxygen functional group. The XPS result shows that the as-prepared GO contains 52% of sp2 hybridized carbon due to the C=C bonds and 33% of carbon atoms due to the C-O bonds. As for RGO, increment of the atomic % of the sp2 hybridized carbon atom to 83% and rapid decrease in atomic % of C=O bonds confirm an efficient reduction with infrared radiation. UV-Visible absorption spectrum also confirms increment of conjugation with increased reduction. Non-linear optical properties of both GO and RGO are measured using single beam open aperture Z-Scan technique in femtosecond regime. Intensity dependent nonlinear phenomena are observed. Depending upon the intensity, both saturable absorption and two photon absorption contribute to the non-linearity of both the samples. Saturation dominates at low intensity (~ 127 GW/cm2) while two photon absorption become prominent at higher intensities (from 217 GW/cm2 to 302 GW/cm2). We have calculated the two-photon absorption co-efficient and saturation intensity for both the samples. The value of two photon absorption co-efficient (for GO~ 0.0022-0.0037 cm/GW and for RGO~ 0.0128-0.0143 cm/GW) and the saturation intensity (for GO~57 GW/cm2 and for RGO~ 194GW/cm2) is increased with reduction. Increase in two photon absorption coefficient with increasing intensity can also suggest that there may be multi-photon absorption is taking place.
Andersson, Pher G
2008-01-01
With its comprehensive overview of modern reduction methods, this book features high quality contributions allowing readers to find reliable solutions quickly and easily. The monograph treats the reduction of carbonyles, alkenes, imines and alkynes, as well as reductive aminations and cross and heck couplings, before finishing off with sections on kinetic resolutions and hydrogenolysis. An indispensable lab companion for every chemist.
Explorative methods in linear models
Høskuldsson, Agnar
2004-01-01
The author has developed the H-method of mathematical modeling that builds up the model by parts, where each part is optimized with respect to prediction. Besides providing with better predictions than traditional methods, these methods provide with graphic procedures for analyzing different feat...... features in data. These graphic methods extend the well-known methods and results of Principal Component Analysis to any linear model. Here the graphic procedures are applied to linear regression and Ridge Regression....
Andersen, O. Krogh
1975-01-01
of Korringa-Kohn-Rostoker, linear-combination-of-atomic-orbitals, and cellular methods; the secular matrix is linear in energy, the overlap integrals factorize as potential parameters and structure constants, the latter are canonical in the sense that they neither depend on the energy nor the cell volume...
Linear Methods for Image Interpolation
Pascal Getreuer
2011-01-01
We discuss linear methods for interpolation, including nearest neighbor, bilinear, bicubic, splines, and sinc interpolation. We focus on separable interpolation, so most of what is said applies to one-dimensional interpolation as well as N-dimensional separable interpolation.
Optimal control linear quadratic methods
Anderson, Brian D O
2007-01-01
This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the material.The three-part treatment begins with the basic theory of the linear regulator/tracker for time-invariant and time-varying systems. The Hamilton-Jacobi equation is introduced using the Principle of Optimality, and the infinite-time problem is considered. The second part outlines the
Variational linear algebraic equations method
Moiseiwitsch, B.L.
1982-01-01
A modification of the linear algebraic equations method is described which ensures a variational bound on the phaseshifts for potentials having a definite sign at all points. The method is illustrated by the elastic scattering of s-wave electrons by the static field of atomic hydrogen. (author)
Noise Reduction with Optimal Variable Span Linear Filters
Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll
2016-01-01
In this paper, the problem of noise reduction is addressed as a linear filtering problem in a novel way by using concepts from subspace-based enhancement methods, resulting in variable span linear filters. This is done by forming the filter coefficients as linear combinations of a number...... included in forming the filter. Using these concepts, a number of different filter designs are considered, like minimum distortion, Wiener, maximum SNR, and tradeoff filters. Interestingly, all these can be expressed as special cases of variable span filters. We also derive expressions for the speech...... demonstrate the advantages and properties of the variable span filter designs, and their potential performance gain compared to widely used speech enhancement methods....
Bayes linear statistics, theory & methods
Goldstein, Michael
2007-01-01
Bayesian methods combine information available from data with any prior information available from expert knowledge. The Bayes linear approach follows this path, offering a quantitative structure for expressing beliefs, and systematic methods for adjusting these beliefs, given observational data. The methodology differs from the full Bayesian methodology in that it establishes simpler approaches to belief specification and analysis based around expectation judgements. Bayes Linear Statistics presents an authoritative account of this approach, explaining the foundations, theory, methodology, and practicalities of this important field. The text provides a thorough coverage of Bayes linear analysis, from the development of the basic language to the collection of algebraic results needed for efficient implementation, with detailed practical examples. The book covers:The importance of partial prior specifications for complex problems where it is difficult to supply a meaningful full prior probability specification...
Supervised linear dimensionality reduction with robust margins for object recognition
Dornaika, F.; Assoum, A.
2013-01-01
Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.
Linear Methods for Image Interpolation
Pascal Getreuer
2011-09-01
Full Text Available We discuss linear methods for interpolation, including nearest neighbor, bilinear, bicubic, splines, and sinc interpolation. We focus on separable interpolation, so most of what is said applies to one-dimensional interpolation as well as N-dimensional separable interpolation.
Linear Algebraic Method for Non-Linear Map Analysis
Yu, L.; Nash, B.
2009-01-01
We present a newly developed method to analyze some non-linear dynamics problems such as the Henon map using a matrix analysis method from linear algebra. Choosing the Henon map as an example, we analyze the spectral structure, the tune-amplitude dependence, the variation of tune and amplitude during the particle motion, etc., using the method of Jordan decomposition which is widely used in conventional linear algebra.
A linear iterative unfolding method
László, András
2012-01-01
A frequently faced task in experimental physics is to measure the probability distribution of some quantity. Often this quantity to be measured is smeared by a non-ideal detector response or by some physical process. The procedure of removing this smearing effect from the measured distribution is called unfolding, and is a delicate problem in signal processing, due to the well-known numerical ill behavior of this task. Various methods were invented which, given some assumptions on the initial probability distribution, try to regularize the unfolding problem. Most of these methods definitely introduce bias into the estimate of the initial probability distribution. We propose a linear iterative method (motivated by the Neumann series / Landweber iteration known in functional analysis), which has the advantage that no assumptions on the initial probability distribution is needed, and the only regularization parameter is the stopping order of the iteration, which can be used to choose the best compromise between the introduced bias and the propagated statistical and systematic errors. The method is consistent: 'binwise' convergence to the initial probability distribution is proved in absence of measurement errors under a quite general condition on the response function. This condition holds for practical applications such as convolutions, calorimeter response functions, momentum reconstruction response functions based on tracking in magnetic field etc. In presence of measurement errors, explicit formulae for the propagation of the three important error terms is provided: bias error (distance from the unknown to-be-reconstructed initial distribution at a finite iteration order), statistical error, and systematic error. A trade-off between these three error terms can be used to define an optimal iteration stopping criterion, and the errors can be estimated there. We provide a numerical C library for the implementation of the method, which incorporates automatic
Interior-Point Methods for Linear Programming: A Review
Singh, J. N.; Singh, D.
2002-01-01
The paper reviews some recent advances in interior-point methods for linear programming and indicates directions in which future progress can be made. Most of the interior-point methods belong to any of three categories: affine-scaling methods, potential reduction methods and central path methods. These methods are discussed together with…
Robust methods for data reduction
Farcomeni, Alessio
2015-01-01
Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy
Reduction of Linear Functional Systems using Fuhrmann's Equivalence
Mohamed S. Boudellioua
2016-11-01
Full Text Available Functional systems arise in the treatment of systems of partial differential equations, delay-differential equations, multidimensional equations, etc. The problem of reducing a linear functional system to a system containing fewer equations and unknowns was first studied by Serre. Finding an equivalent presentation of a linear functional system containing fewer equations and fewer unknowns can generally simplify both the study of the structural properties of the linear functional system and of different numerical analysis issues, and it can sometimes help in solving the linear functional system. In this paper, Fuhrmann's equivalence is used to present a constructive result on the reduction of under-determined linear functional systems to a single equation involving a single unknown. This equivalence transformation has been studied by a number of authors and has been shown to play an important role in the theory of linear functional systems.
H∞ /H2 model reduction through dilated linear matrix inequalities
Adegas, Fabiano Daher; Stoustrup, Jakob
2012-01-01
This paper presents sufficient dilated linear matrix inequalities (LMI) conditions to the $H_{infty}$ and $H_{2}$ model reduction problem. A special structure of the auxiliary (slack) variables allows the original model of order $n$ to be reduced to an order $r=n/s$ where $n,r,s in field{N}$. Arb......This paper presents sufficient dilated linear matrix inequalities (LMI) conditions to the $H_{infty}$ and $H_{2}$ model reduction problem. A special structure of the auxiliary (slack) variables allows the original model of order $n$ to be reduced to an order $r=n/s$ where $n,r,s in field...
One-loop dimensional reduction of the linear σ model
Malbouisson, A.P.C.; Silva-Neto, M.B.; Svaiter, N.F.
1997-05-01
We perform the dimensional reduction of the linear σ model at one-loop level. The effective of the reduced theory obtained from the integration over the nonzero Matsubara frequencies is exhibited. Thermal mass and coupling constant renormalization constants are given, as well as the thermal renormalization group which controls the dependence of the counterterms on the temperature. We also recover, for the reduced theory, the vacuum instability of the model for large N. (author)
Dose reduction using a dynamic, piecewise-linear attenuator
Hsieh, Scott S., E-mail: sshsieh@stanford.edu [Department of Radiology, Stanford University, Stanford, California 94305 and Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States); Fleischmann, Dominik [Department of Radiology, Stanford University, Stanford, California 94305 (United States); Pelc, Norbert J. [Department of Radiology, Stanford University, Stanford, California 94305 and Department of Bioengineering, Stanford University, Stanford, California 94305 (United States)
2014-02-15
Purpose: The authors recently proposed a dynamic, prepatient x-ray attenuator capable of producing a piecewise-linear attenuation profile customized to each patient and viewing angle. This attenuator was intended to reduce scatter-to-primary ratio (SPR), dynamic range, and dose by redistributing flux. In this work the authors tested the ability of the attenuator to reduce dose and SPR in simulations. Methods: The authors selected four clinical applications, including routine full field-of-view scans of the thorax and abdomen, and targeted reconstruction tasks for an abdominal aortic aneurysm and the pancreas. Raw data were estimated by forward projection of the image volume datasets. The dynamic attenuator was controlled to reduce dose while maintaining peak variance by solving a convex optimization problem, assuminga priori knowledge of the patient anatomy. In targeted reconstruction tasks, the noise in specific regions was given increased weighting. A system with a standard attenuator (or “bowtie filter”) was used as a reference, and used either convex optimized tube current modulation (TCM) or a standard TCM heuristic. The noise of the scan was determined analytically while the dose was estimated using Monte Carlo simulations. Scatter was also estimated using Monte Carlo simulations. The sensitivity of the dynamic attenuator to patient centering was also examined by shifting the abdomen in 2 cm intervals. Results: Compared to a reference system with optimized TCM, use of the dynamic attenuator reduced dose by about 30% in routine scans and 50% in targeted scans. Compared to the TCM heuristics which are typically used withouta priori knowledge, the dose reduction is about 50% for routine scans. The dynamic attenuator gives the ability to redistribute noise and variance and produces more uniform noise profiles than systems with a conventional bowtie filter. The SPR was also modestly reduced by 10% in the thorax and 24% in the abdomen. Imaging with the dynamic
State Space Reduction of Linear Processes using Control Flow Reconstruction
van de Pol, Jan Cornelis; Timmer, Mark
2009-01-01
We present a new method for fighting the state space explosion of process algebraic specifications, by performing static analysis on an intermediate format: linear process equations (LPEs). Our method consists of two steps: (1) we reconstruct the LPE's control flow, detecting control flow parameters
State Space Reduction of Linear Processes Using Control Flow Reconstruction
van de Pol, Jan Cornelis; Timmer, Mark; Liu, Zhiming; Ravn, Anders P.
2009-01-01
We present a new method for fighting the state space explosion of process algebraic specifications, by performing static analysis on an intermediate format: linear process equations (LPEs). Our method consists of two steps: (1) we reconstruct the LPE's control flow, detecting control flow parameters
Kyung-Hun Shin
2017-05-01
Full Text Available The shape of the magnet is essential to the performance of a slotless permanent magnet linear synchronous machine (PMLSM because it is directly related to desirable machine performance. This paper presents a reduction in the thrust ripple of a PMLSM through the use of arc-shaped magnets based on electromagnetic field theory. The magnetic field solutions were obtained by considering end effect using a magnetic vector potential and two-dimensional Cartesian coordinate system. The analytical solution of each subdomain (PM, air-gap, coil, and end region is derived, and the field solution is obtained by applying the boundary and interface conditions between the subdomains. In particular, an analytical method was derived for the instantaneous thrust and thrust ripple reduction of a PMLSM with arc-shaped magnets. In order to demonstrate the validity of the analytical results, the back electromotive force results of a finite element analysis and experiment on the manufactured prototype model were compared. The optimal point for thrust ripple minimization is suggested.
Two linearization methods for atmospheric remote sensing
Doicu, A.; Trautmann, T.
2009-01-01
We present two linearization methods for a pseudo-spherical atmosphere and general viewing geometries. The first approach is based on an analytical linearization of the discrete ordinate method with matrix exponential and incorporates two models for matrix exponential calculation: the matrix eigenvalue method and the Pade approximation. The second method referred to as the forward-adjoint approach is based on the adjoint radiative transfer for a pseudo-spherical atmosphere. We provide a compact description of the proposed methods as well as a numerical analysis of their accuracy and efficiency.
Applications of the reduction method
Zimmermann, W.
1987-01-01
A renoramalizable model of quantum field theory involving several independent coupling parameters, λ 0 , ..., λ n and a normalization mass K is considered. If the model involves massive particles a formulation of the renormalization group should be used in which the β-functions are independent of the masses. The aim of the reduction method is to reduce the model to a description in terms of a single coupling parameter. Although the reduction method does not work for the gauge couplings it leads to reasonable mass constraints if applied to the Yukawa and the Higgs couplings. The underlying idea is that - whatever the fundamental interaction if going to be - eventually there is only one coupling which determines all parameters of the standard model. However, one should be skeptical about numerical results in the standard model. For the standard model is only an effective theory, its β-functions are only approximate and change on their lowest order coefficients may have large effects on the reduction solutions
Sparsity Prevention Pivoting Method for Linear Programming
Li, Peiqiang; Li, Qiyuan; Li, Canbing
2018-01-01
When the simplex algorithm is used to calculate a linear programming problem, if the matrix is a sparse matrix, it will be possible to lead to many zero-length calculation steps, and even iterative cycle will appear. To deal with the problem, a new pivoting method is proposed in this paper....... The principle of this method is avoided choosing the row which the value of the element in the b vector is zero as the row of the pivot element to make the matrix in linear programming density and ensure that most subsequent steps will improve the value of the objective function. One step following...... this principle is inserted to reselect the pivot element in the existing linear programming algorithm. Both the conditions for inserting this step and the maximum number of allowed insertion steps are determined. In the case study, taking several numbers of linear programming problems as examples, the results...
Sparsity Prevention Pivoting Method for Linear Programming
Li, Peiqiang; Li, Qiyuan; Li, Canbing
2018-01-01
. The principle of this method is avoided choosing the row which the value of the element in the b vector is zero as the row of the pivot element to make the matrix in linear programming density and ensure that most subsequent steps will improve the value of the objective function. One step following......When the simplex algorithm is used to calculate a linear programming problem, if the matrix is a sparse matrix, it will be possible to lead to many zero-length calculation steps, and even iterative cycle will appear. To deal with the problem, a new pivoting method is proposed in this paper...... this principle is inserted to reselect the pivot element in the existing linear programming algorithm. Both the conditions for inserting this step and the maximum number of allowed insertion steps are determined. In the case study, taking several numbers of linear programming problems as examples, the results...
The linearization method in hydrodynamical stability theory
Yudovich, V I
1989-01-01
This book presents the theory of the linearization method as applied to the problem of steady-state and periodic motions of continuous media. The author proves infinite-dimensional analogues of Lyapunov's theorems on stability, instability, and conditional stability for a large class of continuous media. In addition, semigroup properties for the linearized Navier-Stokes equations in the case of an incompressible fluid are studied, and coercivity inequalities and completeness of a system of small oscillations are proved.
Non-linear M -sequences Generation Method
Z. R. Garifullina
2011-06-01
Full Text Available The article deals with a new method for modeling a pseudorandom number generator based on R-blocks. The gist of the method is the replacement of a multi digit XOR element by a stochastic adder in a parallel binary linear feedback shift register scheme.
Uzawa method for fuzzy linear system
Ke Wang
2013-01-01
An Uzawa method is presented for solving fuzzy linear systems whose coefficient matrix is crisp and the right-hand side column is arbitrary fuzzy number vector. The explicit iterative scheme is given. The convergence is analyzed with convergence theorems and the optimal parameter is obtained. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.
The simplex method of linear programming
Ficken, Frederick A
1961-01-01
This concise but detailed and thorough treatment discusses the rudiments of the well-known simplex method for solving optimization problems in linear programming. Geared toward undergraduate students, the approach offers sufficient material for readers without a strong background in linear algebra. Many different kinds of problems further enrich the presentation. The text begins with examinations of the allocation problem, matrix notation for dual problems, feasibility, and theorems on duality and existence. Subsequent chapters address convex sets and boundedness, the prepared problem and boun
Preface: Introductory Remarks: Linear Scaling Methods
Bowler, D. R.; Fattebert, J.-L.; Gillan, M. J.; Haynes, P. D.; Skylaris, C.-K.
2008-07-01
It has been just over twenty years since the publication of the seminal paper on molecular dynamics with ab initio methods by Car and Parrinello [1], and the contribution of density functional theory (DFT) and the related techniques to physics, chemistry, materials science, earth science and biochemistry has been huge. Nevertheless, significant improvements are still being made to the performance of these standard techniques; recent work suggests that speed improvements of one or even two orders of magnitude are possible [2]. One of the areas where major progress has long been expected is in O(N), or linear scaling, DFT, in which the computer effort is proportional to the number of atoms. Linear scaling DFT methods have been in development for over ten years [3] but we are now in an exciting period where more and more research groups are working on these methods. Naturally there is a strong and continuing effort to improve the efficiency of the methods and to make them more robust. But there is also a growing ambition to apply them to challenging real-life problems. This special issue contains papers submitted following the CECAM Workshop 'Linear-scaling ab initio calculations: applications and future directions', held in Lyon from 3-6 September 2007. A noteworthy feature of the workshop is that it included a significant number of presentations involving real applications of O(N) methods, as well as work to extend O(N) methods into areas of greater accuracy (correlated wavefunction methods, quantum Monte Carlo, TDDFT) and large scale computer architectures. As well as explicitly linear scaling methods, the conference included presentations on techniques designed to accelerate and improve the efficiency of standard (that is non-linear-scaling) methods; this highlights the important question of crossover—that is, at what size of system does it become more efficient to use a linear-scaling method? As well as fundamental algorithmic questions, this brings up
Bohr, H.; Roy Chowdhury, A.
1984-10-01
The hidden symmetries in various integrable models are derived by applying a newly developed method that uses the Riemann-Hilbert transform in a Zsub(N)-reduction of the linearization systems. The method is extended to linearization systems with higher algebras and with supersymmetry. (author)
Polarized atomic orbitals for linear scaling methods
Berghold, Gerd; Parrinello, Michele; Hutter, Jürg
2002-02-01
We present a modified version of the polarized atomic orbital (PAO) method [M. S. Lee and M. Head-Gordon, J. Chem. Phys. 107, 9085 (1997)] to construct minimal basis sets optimized in the molecular environment. The minimal basis set derives its flexibility from the fact that it is formed as a linear combination of a larger set of atomic orbitals. This approach significantly reduces the number of independent variables to be determined during a calculation, while retaining most of the essential chemistry resulting from the admixture of higher angular momentum functions. Furthermore, we combine the PAO method with linear scaling algorithms. We use the Chebyshev polynomial expansion method, the conjugate gradient density matrix search, and the canonical purification of the density matrix. The combined scheme overcomes one of the major drawbacks of standard approaches for large nonorthogonal basis sets, namely numerical instabilities resulting from ill-conditioned overlap matrices. We find that the condition number of the PAO overlap matrix is independent from the condition number of the underlying extended basis set, and consequently no numerical instabilities are encountered. Various applications are shown to confirm this conclusion and to compare the performance of the PAO method with extended basis-set calculations.
A HYBRID TECHNIQUE FOR PAPR REDUCTION OF OFDM USING DHT PRECODING WITH PIECEWISE LINEAR COMPANDING
Thammana Ajay
2016-06-01
Full Text Available Orthogonal Frequency Division Multiplexing (OFDM is a fascinating approach for wireless communication applications which require huge amount of data rates. However, OFDM signal suffers from its large Peak-to-Average Power Ratio (PAPR, which results in significant distortion while passing through a nonlinear device, such as a transmitter high power amplifier (HPA. Due to this high PAPR, the complexity of HPA as well as DAC also increases. For the reduction of PAPR in OFDM many techniques are available. Among them companding is an attractive low complexity technique for the OFDM signal’s PAPR reduction. Recently, a piecewise linear companding technique is recommended aiming at minimizing companding distortion. In this paper, a collective piecewise linear companding approach with Discrete Hartley Transform (DHT method is expected to reduce peak-to-average of OFDM to a great extent. Simulation results shows that this new proposed method obtains significant PAPR reduction while maintaining improved performance in the Bit Error Rate (BER and Power Spectral Density (PSD compared to piecewise linear companding method.
Simultaneous Balancing and Model Reduction of Switched Linear Systems
Monshizadeh, Nima; Trentelman, Hendrikus; Camlibel, M.K.
2011-01-01
In this paper, first, balanced truncation of linear systems is revisited. Then, simultaneous balancing of multiple linear systems is investigated. Necessary and sufficient conditions are introduced to identify the case where simultaneous balancing is possible. The validity of these conditions is not
New nonlinear methods for linear transport calculations
Adams, M.L.
1993-01-01
We present a new family of methods for the numerical solution of the linear transport equation. With these methods an iteration consists of an 'S N sweep' followed by an 'S 2 -like' calculation. We show, by analysis as well as numerical results, that iterative convergence is always rapid. We show that this rapid convergence does not depend on a consistent discretization of the S 2 -like equations - they can be discretized independently from the S N equations. We show further that independent discretizations can offer significant advantages over consistent ones. In particular, we find that in a wide range of problems, an accurate discretization of the S 2 -like equation can be combined with a crude discretization of the S N equations to produce an accurate S N answer. We demonstrate this by analysis as well as numerical results. (orig.)
Simultaneous Balancing and Model Reduction of Switched Linear Systems
Monshizadeh, Nima; Trentelman, Hendrikus; Camlibel, M.K.
2011-01-01
In this paper, first, balanced truncation of linear systems is revisited. Then, simultaneous balancing of multiple linear systems is investigated. Necessary and sufficient conditions are introduced to identify the case where simultaneous balancing is possible. The validity of these conditions is not limited to a certain type of balancing, and they are applicable for different types of balancing corresponding to different equations, like Lyapunov or Riccati equations. The results obtained are ...
Noise Reduction of Measurement Data using Linear Digital Filters
Hitzmann B.
2007-12-01
Full Text Available In this paper Butterworth, Chebyshev (Type I and II and Elliptic digital filters are designed for signal noise reduction. On-line data measurements of substrate concentration from E. coli fed-batch cultivation process are used. Application of the designed filters leads to a successful noise reduction of on-line glucose measurements. The digital filters presented here are simple, easy to implement and effective - the used filters allow for a smart compromise between signal information and noise corruption.
Reduction of Under-Determined Linear Systems by Sparce Block Matrix Technique
Tarp-Johansen, Niels Jacob; Poulsen, Peter Noe; Damkilde, Lars
1996-01-01
numerical stability of the aforementioned reduction. Moreover the coefficient matrix for the equilibrium equations is typically very sparse. The objective is to deal efficiently with the full pivoting reduction of sparse rectangular matrices using a dynamic storage scheme based on the block matrix concept.......Under-determined linear equation systems occur in different engineering applications. In structural engineering they typically appear when applying the force method. As an example one could mention limit load analysis based on The Lower Bound Theorem. In this application there is a set of under......-determined equilibrium equation restrictions in an LP-problem. A significant reduction of computer time spent on solving the LP-problem is achieved if the equilib rium equations are reduced before going into the optimization procedure. Experience has shown that for some structures one must apply full pivoting to ensure...
On the reduction of the degree of linear differential operators
Bobieński, Marcin; Gavrilov, Lubomir
2011-01-01
Let L be a linear differential operator with coefficients in some differential field k of characteristic zero with algebraically closed field of constants. Let k a be the algebraic closure of k. For a solution y 0 , Ly 0 = 0, we determine the linear differential operator of minimal degree L-tilde and coefficients in k a , such that L-tilde y 0 =0. This result is then applied to some Picard–Fuchs equations which appear in the study of perturbations of plane polynomial vector fields of Lotka–Volterra type
Graphical reduction of reaction networks by linear elimination of species
Saez Cornellana, Meritxell; Wiuf, Carsten; Feliu, Elisenda
2017-01-01
We give a graphically based procedure to reduce a reaction network to a smaller reaction network with fewer species after linear elimination of a set of noninteracting species. We give a description of the reduced reaction network, its kinetics and conservations laws, and explore properties...
Optimal angle reduction - a behavioral approach to linear system appromixation
Roorda, B.; Weiland, S.
2001-01-01
We investigate the problem of optimal state reduction under minimization of the angle between system behaviors. The angle is defined in a worst-case sense, as the largest angle that can occur between a system trajectory and its optimal approximation in the reduced-order model. This problem is
Generalized Time-Limited Balanced Reduction Method
Shaker, Hamid Reza; Shaker, Fatemeh
2013-01-01
In this paper, a new method for model reduction of bilinear systems is presented. The proposed technique is from the family of gramian-based model reduction methods. The method uses time-interval generalized gramians in the reduction procedure rather than the ordinary generalized gramians...... and in such a way it improves the accuracy of the approximation within the time-interval which the method is applied. The time-interval generalized gramians are the solutions to the generalized time-interval Lyapunov equations. The conditions for these equations to be solvable are derived and an algorithm...
Applicabilities of ship emission reduction methods
Guleryuz, Adem [ARGEMAN Research Group, Marine Division (Turkey)], email: ademg@argeman.org; Kilic, Alper [Istanbul Technical University, Maritime Faculty, Marine Engineering Department (Turkey)], email: enviromarineacademic@yahoo.com
2011-07-01
Ships, with their high consumption of fossil fuels to power their engines, are significant air polluters. Emission reduction methods therefore need to be implemented and the aim of this paper is to assess the advantages and disadvantages of each emissions reduction method. Benefits of the different methods are compared, with their disadvantages and requirements, to determine the applicability of such solutions. The methods studied herein are direct water injection, humid air motor, sea water scrubbing, diesel particulate filter, selected catalytic reduction, design of engine components, exhaust gas recirculation and engine replacement. Results of the study showed that the usefulness of each emissions reduction method depends on the particular case and that an evaluation should be carried out for each ship. This study pointed out that methods to reduce ship emissions are available but that their applicability depends on each case.
PAPR reduction in FBMC using an ACE-based linear programming optimization
van der Neut, Nuan; Maharaj, Bodhaswar TJ; de Lange, Frederick; González, Gustavo J.; Gregorio, Fernando; Cousseau, Juan
2014-12-01
This paper presents four novel techniques for peak-to-average power ratio (PAPR) reduction in filter bank multicarrier (FBMC) modulation systems. The approach extends on current PAPR reduction active constellation extension (ACE) methods, as used in orthogonal frequency division multiplexing (OFDM), to an FBMC implementation as the main contribution. The four techniques introduced can be split up into two: linear programming optimization ACE-based techniques and smart gradient-project (SGP) ACE techniques. The linear programming (LP)-based techniques compensate for the symbol overlaps by utilizing a frame-based approach and provide a theoretical upper bound on achievable performance for the overlapping ACE techniques. The overlapping ACE techniques on the other hand can handle symbol by symbol processing. Furthermore, as a result of FBMC properties, the proposed techniques do not require side information transmission. The PAPR performance of the techniques is shown to match, or in some cases improve, on current PAPR techniques for FBMC. Initial analysis of the computational complexity of the SGP techniques indicates that the complexity issues with PAPR reduction in FBMC implementations can be addressed. The out-of-band interference introduced by the techniques is investigated. As a result, it is shown that the interference can be compensated for, whilst still maintaining decent PAPR performance. Additional results are also provided by means of a study of the PAPR reduction of the proposed techniques at a fixed clipping probability. The bit error rate (BER) degradation is investigated to ensure that the trade-off in terms of BER degradation is not too severe. As illustrated by exhaustive simulations, the SGP ACE-based technique proposed are ideal candidates for practical implementation in systems employing the low-complexity polyphase implementation of FBMC modulators. The methods are shown to offer significant PAPR reduction and increase the feasibility of FBMC as
Studying the method of linearization of exponential calibration curves
Bunzh, Z.A.
1989-01-01
The results of study of the method for linearization of exponential calibration curves are given. The calibration technique and comparison of the proposed method with piecewise-linear approximation and power series expansion, are given
A logic circuit for solving linear function by digital method
Ma Yonghe
1986-01-01
A mathematical method for determining the linear relation of physical quantity with rediation intensity is described. A logic circuit has been designed for solving linear function by digital method. Some applications and the circuit function are discussed
Methods in half-linear asymptotic theory
Řehák, Pavel
2016-01-01
Roč. 2016, Č. 267 (2016), s. 1-27 ISSN 1072-6691 Institutional support: RVO:67985840 Keywords : half-linear differential equation * nonoscillatory solution * regular variation Subject RIV: BA - General Mathematics Impact factor: 0.954, year: 2016 http://ejde.math.txstate.edu/Volumes/2016/267/abstr.html
Accelerated Cyclic Reduction: A Distributed-Memory Fast Solver for Structured Linear Systems
Chávez, Gustavo
2017-12-15
We present Accelerated Cyclic Reduction (ACR), a distributed-memory fast solver for rank-compressible block tridiagonal linear systems arising from the discretization of elliptic operators, developed here for three dimensions. Algorithmic synergies between Cyclic Reduction and hierarchical matrix arithmetic operations result in a solver that has O(kNlogN(logN+k2)) arithmetic complexity and O(k Nlog N) memory footprint, where N is the number of degrees of freedom and k is the rank of a block in the hierarchical approximation, and which exhibits substantial concurrency. We provide a baseline for performance and applicability by comparing with the multifrontal method with and without hierarchical semi-separable matrices, with algebraic multigrid and with the classic cyclic reduction method. Over a set of large-scale elliptic systems with features of nonsymmetry and indefiniteness, the robustness of the direct solvers extends beyond that of the multigrid solver, and relative to the multifrontal approach ACR has lower or comparable execution time and size of the factors, with substantially lower numerical ranks. ACR exhibits good strong and weak scaling in a distributed context and, as with any direct solver, is advantageous for problems that require the solution of multiple right-hand sides. Numerical experiments show that the rank k patterns are of O(1) for the Poisson equation and of O(n) for the indefinite Helmholtz equation. The solver is ideal in situations where low-accuracy solutions are sufficient, or otherwise as a preconditioner within an iterative method.
Accelerated Cyclic Reduction: A Distributed-Memory Fast Solver for Structured Linear Systems
Chá vez, Gustavo; Turkiyyah, George; Zampini, Stefano; Ltaief, Hatem; Keyes, David E.
2017-01-01
We present Accelerated Cyclic Reduction (ACR), a distributed-memory fast solver for rank-compressible block tridiagonal linear systems arising from the discretization of elliptic operators, developed here for three dimensions. Algorithmic synergies between Cyclic Reduction and hierarchical matrix arithmetic operations result in a solver that has O(kNlogN(logN+k2)) arithmetic complexity and O(k Nlog N) memory footprint, where N is the number of degrees of freedom and k is the rank of a block in the hierarchical approximation, and which exhibits substantial concurrency. We provide a baseline for performance and applicability by comparing with the multifrontal method with and without hierarchical semi-separable matrices, with algebraic multigrid and with the classic cyclic reduction method. Over a set of large-scale elliptic systems with features of nonsymmetry and indefiniteness, the robustness of the direct solvers extends beyond that of the multigrid solver, and relative to the multifrontal approach ACR has lower or comparable execution time and size of the factors, with substantially lower numerical ranks. ACR exhibits good strong and weak scaling in a distributed context and, as with any direct solver, is advantageous for problems that require the solution of multiple right-hand sides. Numerical experiments show that the rank k patterns are of O(1) for the Poisson equation and of O(n) for the indefinite Helmholtz equation. The solver is ideal in situations where low-accuracy solutions are sufficient, or otherwise as a preconditioner within an iterative method.
Methods in half-linear asymptotic theory
Pavel Rehak
2016-10-01
Full Text Available We study the asymptotic behavior of eventually positive solutions of the second-order half-linear differential equation $$ (r(t|y'|^{\\alpha-1}\\hbox{sgn} y''=p(t|y|^{\\alpha-1}\\hbox{sgn} y, $$ where r(t and p(t are positive continuous functions on $[a,\\infty$, $\\alpha\\in(1,\\infty$. The aim of this article is twofold. On the one hand, we show applications of a wide variety of tools, like the Karamata theory of regular variation, the de Haan theory, the Riccati technique, comparison theorems, the reciprocity principle, a certain transformation of dependent variable, and principal solutions. On the other hand, we solve open problems posed in the literature and generalize existing results. Most of our observations are new also in the linear case.
A Novel Four-Dimensional Energy-Saving and Emission-Reduction System and Its Linear Feedback Control
Minggang Wang
2012-01-01
Full Text Available This paper reports a new four-dimensional energy-saving and emission-reduction chaotic system. The system is obtained in accordance with the complicated relationship between energy saving and emission reduction, carbon emission, economic growth, and new energy development. The dynamics behavior of the system will be analyzed by means of Lyapunov exponents and equilibrium points. Linear feedback control methods are used to suppress chaos to unstable equilibrium. Numerical simulations are presented to show these results.
Reactor power reduction system and method
Bruno, S.J.; Dunn, S.A.; Raber, M.
1978-01-01
A method of operating a nuclear power reactor is disclosed which enables an accelerated power reduction of the reactor without completely shutting the reactor down. The method includes monitoring the incidents which, upon their occurrence, would require an accelerated power reduction in order to maintain the reactor in a safe operation mode; calculating the power reduction required on the occurrence of such an incident; determining a control rod insertion sequence for the normal operation of the reactor, said sequence being chosen to optimize reactor power capability; selecting the number of control rods necessary to respond to the accelerated power reduction demand, said selection being made according to a priority determined by said control rod insertion sequence; and inserting said selected control rods into the reactor core. 11 claims, 13 figures
Torque ripple reduction of brushless DC motor based on adaptive input-output feedback linearization.
Shirvani Boroujeni, M; Markadeh, G R Arab; Soltani, J
2017-09-01
Torque ripple reduction of Brushless DC Motors (BLDCs) is an interesting subject in variable speed AC drives. In this paper at first, a mathematical expression for torque ripple harmonics is obtained. Then for a non-ideal BLDC motor with known harmonic contents of back-EMF, calculation of desired reference current amplitudes, which are required to eliminate some selected harmonics of torque ripple, are reviewed. In order to inject the reference harmonic currents to the motor windings, an Adaptive Input-Output Feedback Linearization (AIOFBL) control is proposed, which generates the reference voltages for three phases voltage source inverter in stationary reference frame. Experimental results are presented to show the capability and validity of the proposed control method and are compared with the vector control in Multi-Reference Frame (MRF) and Pseudo-Vector Control (P-VC) method results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Convergence of hybrid methods for solving non-linear partial ...
This paper is concerned with the numerical solution and convergence analysis of non-linear partial differential equations using a hybrid method. The solution technique involves discretizing the non-linear system of PDE to obtain a corresponding non-linear system of algebraic difference equations to be solved at each time ...
Yi-hua Zhong
2013-01-01
Full Text Available Recently, various methods have been developed for solving linear programming problems with fuzzy number, such as simplex method and dual simplex method. But their computational complexities are exponential, which is not satisfactory for solving large-scale fuzzy linear programming problems, especially in the engineering field. A new method which can solve large-scale fuzzy number linear programming problems is presented in this paper, which is named a revised interior point method. Its idea is similar to that of interior point method used for solving linear programming problems in crisp environment before, but its feasible direction and step size are chosen by using trapezoidal fuzzy numbers, linear ranking function, fuzzy vector, and their operations, and its end condition is involved in linear ranking function. Their correctness and rationality are proved. Moreover, choice of the initial interior point and some factors influencing the results of this method are also discussed and analyzed. The result of algorithm analysis and example study that shows proper safety factor parameter, accuracy parameter, and initial interior point of this method may reduce iterations and they can be selected easily according to the actual needs. Finally, the method proposed in this paper is an alternative method for solving fuzzy number linear programming problems.
A Proposed Method for Solving Fuzzy System of Linear Equations
Reza Kargar
2014-01-01
Full Text Available This paper proposes a new method for solving fuzzy system of linear equations with crisp coefficients matrix and fuzzy or interval right hand side. Some conditions for the existence of a fuzzy or interval solution of m×n linear system are derived and also a practical algorithm is introduced in detail. The method is based on linear programming problem. Finally the applicability of the proposed method is illustrated by some numerical examples.
Mathematical methods linear algebra normed spaces distributions integration
Korevaar, Jacob
1968-01-01
Mathematical Methods, Volume I: Linear Algebra, Normed Spaces, Distributions, Integration focuses on advanced mathematical tools used in applications and the basic concepts of algebra, normed spaces, integration, and distributions.The publication first offers information on algebraic theory of vector spaces and introduction to functional analysis. Discussions focus on linear transformations and functionals, rectangular matrices, systems of linear equations, eigenvalue problems, use of eigenvectors and generalized eigenvectors in the representation of linear operators, metric and normed vector
Active sound reduction system and method
2016-01-01
The present invention refers to an active sound reduction system and method for attenuation of sound emitted by a primary sound source, especially for attenuation of snoring sounds emitted by a human being. This system comprises a primary sound source, at least one speaker as a secondary sound
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the
Dimension Reduction and Discretization in Stochastic Problems by Regression Method
Ditlevsen, Ove Dalager
1996-01-01
The chapter mainly deals with dimension reduction and field discretizations based directly on the concept of linear regression. Several examples of interesting applications in stochastic mechanics are also given.Keywords: Random fields discretization, Linear regression, Stochastic interpolation, ...
A feasible DY conjugate gradient method for linear equality constraints
LI, Can
2017-09-01
In this paper, we propose a feasible conjugate gradient method for solving linear equality constrained optimization problem. The method is an extension of the Dai-Yuan conjugate gradient method proposed by Dai and Yuan to linear equality constrained optimization problem. It can be applied to solve large linear equality constrained problem due to lower storage requirement. An attractive property of the method is that the generated direction is always feasible and descent direction. Under mild conditions, the global convergence of the proposed method with exact line search is established. Numerical experiments are also given which show the efficiency of the method.
Reductive methods for isotopic labeling of antibiotics
Champney, W.S.
1989-01-01
Methods for the reductive methylation of the amino groups of eight different antibiotics using 3 HCOH or H 14 COH are presented. The reductive labeling of an additional seven antibiotics by NaB 3 H 4 is also described. The specific activity of the methyl-labeled drugs was determined by a phosphocellulose paper binding assay. Two quantitative assays for these compounds based on the reactivity of the antibiotic amino groups with fluorescamine and of the aldehyde and ketone groups with 2,4-dinitrophenylhydrazine are also presented. Data on the cellular uptake and ribosome binding of these labeled compounds are also presented
Fast linear method of illumination classification
Cooper, Ted J.; Baqai, Farhan A.
2003-01-01
We present a simple method for estimating the scene illuminant for images obtained by a Digital Still Camera (DSC). The proposed method utilizes basis vectors obtained from known memory color reflectance to identify the memory color objects in the image. Once the memory color pixels are identified, we use the ratios of the red/green and blue/green to determine the most likely illuminant in the image. The critical part of the method is to estimate the smallest set of basis vectors that closely represent the memory color reflectances. Basis vectors obtained from both Principal Component Analysis (PCA) and Independent Component Analysis (ICA) are used. We will show that only two ICA basis vectors are needed to get an acceptable estimate.
Strong-stability-preserving additive linear multistep methods
Hadjimichael, Yiannis
2018-02-20
The analysis of strong-stability-preserving (SSP) linear multistep methods is extended to semi-discretized problems for which different terms on the right-hand side satisfy different forward Euler (or circle) conditions. Optimal perturbed and additive monotonicity-preserving linear multistep methods are studied in the context of such problems. Optimal perturbed methods attain larger monotonicity-preserving step sizes when the different forward Euler conditions are taken into account. On the other hand, we show that optimal SSP additive methods achieve a monotonicity-preserving step-size restriction no better than that of the corresponding nonadditive SSP linear multistep methods.
Approximate Method for Solving the Linear Fuzzy Delay Differential Equations
S. Narayanamoorthy
2015-01-01
Full Text Available We propose an algorithm of the approximate method to solve linear fuzzy delay differential equations using Adomian decomposition method. The detailed algorithm of the approach is provided. The approximate solution is compared with the exact solution to confirm the validity and efficiency of the method to handle linear fuzzy delay differential equation. To show this proper features of this proposed method, numerical example is illustrated.
Usuda, Takashi; Kobayashi, Naoki; Takeda, Sunao; Kotake, Yoshifumi
2010-01-01
We have developed the non-invasive blood pressure monitor which can measure the blood pressure quickly and robustly. This monitor combines two measurement mode: the linear inflation and the linear deflation. On the inflation mode, we realized a faster measurement with rapid inflation rate. On the deflation mode, we realized a robust noise reduction. When there is neither noise nor arrhythmia, the inflation mode incorporated on this monitor provides precise, quick and comfortable measurement. Once the inflation mode fails to calculate appropriate blood pressure due to body movement or arrhythmia, then the monitor switches automatically to the deflation mode and measure blood pressure by using digital signal processing as wavelet analysis, filter bank, filter combined with FFT and Inverse FFT. The inflation mode succeeded 2440 measurements out of 3099 measurements (79%) in an operating room and a rehabilitation room. The new designed blood pressure monitor provides the fastest measurement for patient with normal circulation and robust measurement for patients with body movement or severe arrhythmia. Also this fast measurement method provides comfortableness for patients.
Effective linear two-body method for many-body problems in atomic and nuclear physics
Kim, Y.E.; Zubarev, A.L.
2000-01-01
We present an equivalent linear two-body method for the many body problem, which is based on an approximate reduction of the many-body Schroedinger equation by the use of a variational principle. The method is applied to several problems in atomic and nuclear physics. (author)
Non-linear programming method in optimization of fast reactors
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.)
Ravi Kanth, A.S.V.; Aruna, K.
2009-01-01
In this paper, we propose a reliable algorithm to develop exact and approximate solutions for the linear and nonlinear Schroedinger equations. The approach rest mainly on two-dimensional differential transform method which is one of the approximate methods. The method can easily be applied to many linear and nonlinear problems and is capable of reducing the size of computational work. Exact solutions can also be achieved by the known forms of the series solutions. Several illustrative examples are given to demonstrate the effectiveness of the present method.
Application of the simplex method of linear programming model to ...
This work discussed how the simplex method of linear programming could be used to maximize the profit of any business firm using Saclux Paint Company as a case study. It equally elucidated the effect variation in the optimal result obtained from linear programming model, will have on any given firm. It was demonstrated ...
Strong-stability-preserving additive linear multistep methods
Hadjimichael, Yiannis; Ketcheson, David I.
2018-01-01
The analysis of strong-stability-preserving (SSP) linear multistep methods is extended to semi-discretized problems for which different terms on the right-hand side satisfy different forward Euler (or circle) conditions. Optimal perturbed
Direct Linear Transformation Method for Three-Dimensional Cinematography
Shapiro, Robert
1978-01-01
The ability of Direct Linear Transformation Method for three-dimensional cinematography to locate points in space was shown to meet the accuracy requirements associated with research on human movement. (JD)
Computation of Optimal Monotonicity Preserving General Linear Methods
Ketcheson, David I.
2009-07-01
Monotonicity preserving numerical methods for ordinary differential equations prevent the growth of propagated errors and preserve convex boundedness properties of the solution. We formulate the problem of finding optimal monotonicity preserving general linear methods for linear autonomous equations, and propose an efficient algorithm for its solution. This algorithm reliably finds optimal methods even among classes involving very high order accuracy and that use many steps and/or stages. The optimality of some recently proposed methods is verified, and many more efficient methods are found. We use similar algorithms to find optimal strong stability preserving linear multistep methods of both explicit and implicit type, including methods for hyperbolic PDEs that use downwind-biased operators.
Linear regression methods a ccording to objective functions
Yasemin Sisman; Sebahattin Bektas
2012-01-01
The aim of the study is to explain the parameter estimation methods and the regression analysis. The simple linear regressionmethods grouped according to the objective function are introduced. The numerical solution is achieved for the simple linear regressionmethods according to objective function of Least Squares and theLeast Absolute Value adjustment methods. The success of the appliedmethods is analyzed using their objective function values.
Efficient decomposition and linearization methods for the stochastic transportation problem
Holmberg, K.
1993-01-01
The stochastic transportation problem can be formulated as a convex transportation problem with nonlinear objective function and linear constraints. We compare several different methods based on decomposition techniques and linearization techniques for this problem, trying to find the most efficient method or combination of methods. We discuss and test a separable programming approach, the Frank-Wolfe method with and without modifications, the new technique of mean value cross decomposition and the more well known Lagrangian relaxation with subgradient optimization, as well as combinations of these approaches. Computational tests are presented, indicating that some new combination methods are quite efficient for large scale problems. (authors) (27 refs.)
A method for evaluating dynamical friction in linear ball bearings.
Fujii, Yusaku; Maru, Koichi; Jin, Tao; Yupapin, Preecha P; Mitatha, Somsak
2010-01-01
A method is proposed for evaluating the dynamical friction of linear bearings, whose motion is not perfectly linear due to some play in its internal mechanism. In this method, the moving part of a linear bearing is made to move freely, and the force acting on the moving part is measured as the inertial force given by the product of its mass and the acceleration of its centre of gravity. To evaluate the acceleration of its centre of gravity, the acceleration of two different points on it is measured using a dual-axis optical interferometer.
Hybrid Method for Solving Inventory Problems with a Linear ...
Osagiede and Omosigho (2004) proposed a direct search method for identifying the number of replenishment when the demand pattern is linearly increasing. The main computational task in this direct search method was associated with finding the optimal number of replenishments. To accelerate the use of this method, the ...
Runge-Kutta Methods for Linear Ordinary Differential Equations
Zingg, David W.; Chisholm, Todd T.
1997-01-01
Three new Runge-Kutta methods are presented for numerical integration of systems of linear inhomogeneous ordinary differential equations (ODES) with constant coefficients. Such ODEs arise in the numerical solution of the partial differential equations governing linear wave phenomena. The restriction to linear ODEs with constant coefficients reduces the number of conditions which the coefficients of the Runge-Kutta method must satisfy. This freedom is used to develop methods which are more efficient than conventional Runge-Kutta methods. A fourth-order method is presented which uses only two memory locations per dependent variable, while the classical fourth-order Runge-Kutta method uses three. This method is an excellent choice for simulations of linear wave phenomena if memory is a primary concern. In addition, fifth- and sixth-order methods are presented which require five and six stages, respectively, one fewer than their conventional counterparts, and are therefore more efficient. These methods are an excellent option for use with high-order spatial discretizations.
Wei, Peng; Sridhar, Banavar; Chen, Neil Yi-Nan; Sun, Dengfent
2012-01-01
A class of strategies has been proposed to reduce contrail formation in the United States airspace. A 3D grid based on weather data and the cruising altitude level of aircraft is adjusted to avoid the persistent contrail potential area with the consideration to fuel-efficiency. In this paper, the authors introduce a contrail avoidance strategy on 3D grid by considering additional operationally feasible constraints from an air traffic controller's aspect. First, shifting too many aircraft to the same cruising level will make the miles-in-trail at this level smaller than the safety separation threshold. Furthermore, the high density of aircraft at one cruising level may exceed the workload for the traffic controller. Therefore, in our new model we restrict the number of total aircraft at each level. Second, the aircraft count variation for successive intervals cannot be too drastic since the workload to manage climbing/descending aircraft is much larger than managing cruising aircraft. The contrail reduction is formulated as an integer-programming problem and the problem is shown to have the property of total unimodularity. Solving the corresponding relaxed linear programming with the simplex method provides an optimal and integral solution to the problem. Simulation results are provided to illustrate the methodology.
Generalization of the linear algebraic method to three dimensions
Lynch, D.L.; Schneider, B.I.
1991-01-01
We present a numerical method for the solution of the Lippmann-Schwinger equation for electron-molecule collisions. By performing a three-dimensional numerical quadrature, this approach avoids both a basis-set representation of the wave function and a partial-wave expansion of the scattering potential. The resulting linear equations, analogous in form to the one-dimensional linear algebraic method, are solved with the direct iteration-variation method. Several numerical examples are presented. The prospect for using this numerical quadrature scheme for electron-polyatomic molecules is discussed
QUADRO: A SUPERVISED DIMENSION REDUCTION METHOD VIA RAYLEIGH QUOTIENT OPTIMIZATION.
Fan, Jianqing; Ke, Zheng Tracy; Liu, Han; Xia, Lucy
We propose a novel Rayleigh quotient based sparse quadratic dimension reduction method-named QUADRO (Quadratic Dimension Reduction via Rayleigh Optimization)-for analyzing high-dimensional data. Unlike in the linear setting where Rayleigh quotient optimization coincides with classification, these two problems are very different under nonlinear settings. In this paper, we clarify this difference and show that Rayleigh quotient optimization may be of independent scientific interests. One major challenge of Rayleigh quotient optimization is that the variance of quadratic statistics involves all fourth cross-moments of predictors, which are infeasible to compute for high-dimensional applications and may accumulate too many stochastic errors. This issue is resolved by considering a family of elliptical models. Moreover, for heavy-tail distributions, robust estimates of mean vectors and covariance matrices are employed to guarantee uniform convergence in estimating non-polynomially many parameters, even though only the fourth moments are assumed. Methodologically, QUADRO is based on elliptical models which allow us to formulate the Rayleigh quotient maximization as a convex optimization problem. Computationally, we propose an efficient linearized augmented Lagrangian method to solve the constrained optimization problem. Theoretically, we provide explicit rates of convergence in terms of Rayleigh quotient under both Gaussian and general elliptical models. Thorough numerical results on both synthetic and real datasets are also provided to back up our theoretical results.
Comments on new iterative methods for solving linear systems
Wang Ke
2017-06-01
Full Text Available Some new iterative methods were presented by Du, Zheng and Wang for solving linear systems in [3], where it is shown that the new methods, comparing to the classical Jacobi or Gauss-Seidel method, can be applied to more systems and have faster convergence. This note shows that their methods are suitable for more matrices than positive matrices which the authors suggested through further analysis and numerical examples.
The Induced Dimension Reduction method applied to convection-diffusion-reaction problems
Astudillo, R.; Van Gijzen, M.B.
2016-01-01
Discretization of (linearized) convection-diffusion-reaction problems yields a large and sparse non symmetric linear system of equations, Ax = b. (1) In this work, we compare the computational behavior of the Induced Dimension Reduction method (IDR(s)) [10], with other short-recurrences Krylov
The induced dimension reduction method applied to convection-diffusion-reaction problems
Astudillo Rengifo, R.A.; van Gijzen, M.B.
2016-01-01
Discretization of (linearized) convection-diusion-reaction problems yields
a large and sparse non symmetric linear system of equations,
Ax = b: (1)
In this work, we compare the computational behavior of the Induced Dimension
Reduction method (IDR(s)) [10], with other
New Implicit General Linear Method | Ibrahim | Journal of the ...
A New implicit general linear method is designed for the numerical olution of stiff differential Equations. The coefficients matrix is derived from the stability function. The method combines the single-implicitness or diagonal implicitness with property that the first two rows are implicit and third and fourth row are explicit.
Linearly convergent stochastic heavy ball method for minimizing generalization error
Loizou, Nicolas; Richtarik, Peter
2017-01-01
In this work we establish the first linear convergence result for the stochastic heavy ball method. The method performs SGD steps with a fixed stepsize, amended by a heavy ball momentum term. In the analysis, we focus on minimizing the expected loss
Sodium flow rate measurement method of annular linear induction pump
Araseki, Hideo
2011-01-01
This report describes a method for measuring sodium flow rate of annular linear induction pumps arranged in parallel and its verification result obtained through an experiment and a numerical analysis. In the method, the leaked magnetic field is measured with measuring coils at the stator end on the outlet side and is correlated with the sodium flow rate. The experimental data and the numerical result indicate that the leaked magnetic field at the stator edge keeps almost constant when the sodium flow rate changes and that the leaked magnetic field change arising from the flow rate change is small compared with the overall leaked magnetic field. It is shown that the correlation between the leaked magnetic field and the sodium flow rate is almost linear due to this feature of the leaked magnetic field, which indicates the applicability of the method to small-scale annular linear induction pumps. (author)
EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.
Lian, Yao; Ge, Meng; Pan, Xian-Ming
2014-12-19
B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task. In this work, based on the antigen's primary sequence information, a novel linear B-cell epitope prediction model was developed using the multiple linear regression (MLR). A 10-fold cross-validation test on a large non-redundant dataset was performed to evaluate the performance of our model. To alleviate the problem caused by the noise of negative dataset, 300 experiments utilizing 300 sub-datasets were performed. We achieved overall sensitivity of 81.8%, precision of 64.1% and area under the receiver operating characteristic curve (AUC) of 0.728. We have presented a reliable method for the identification of linear B cell epitope using antigen's primary sequence information. Moreover, a web server EPMLR has been developed for linear B-cell epitope prediction: http://www.bioinfo.tsinghua.edu.cn/epitope/EPMLR/ .
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2014-01-01
In the paper, three frequently used operation optimisation methods are examined with respect to their impact on operation management of the combined utility technologies for electric power and DH (district heating) of eastern Denmark. The investigation focusses on individual plant operation...... differences and differences between the solution found by each optimisation method. One of the investigated approaches utilises LP (linear programming) for optimisation, one uses LP with binary operation constraints, while the third approach uses NLP (non-linear programming). The LP model is used...... as a benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. Compared to the reference, the use of binary integer variables, increases operation...
On a linear method in bootstrap confidence intervals
Andrea Pallini
2007-10-01
Full Text Available A linear method for the construction of asymptotic bootstrap confidence intervals is proposed. We approximate asymptotically pivotal and non-pivotal quantities, which are smooth functions of means of n independent and identically distributed random variables, by using a sum of n independent smooth functions of the same analytical form. Errors are of order Op(n-3/2 and Op(n-2, respectively. The linear method allows a straightforward approximation of bootstrap cumulants, by considering the set of n independent smooth functions as an original random sample to be resampled with replacement.
Relaxation Methods for Strictly Convex Regularizations of Piecewise Linear Programs
Kiwiel, K. C.
1998-01-01
We give an algorithm for minimizing the sum of a strictly convex function and a convex piecewise linear function. It extends several dual coordinate ascent methods for large-scale linearly constrained problems that occur in entropy maximization, quadratic programming, and network flows. In particular, it may solve exact penalty versions of such (possibly inconsistent) problems, and subproblems of bundle methods for nondifferentiable optimization. It is simple, can exploit sparsity, and in certain cases is highly parallelizable. Its global convergence is established in the recent framework of B -functions (generalized Bregman functions)
Sanjuan, J.; Nofrarias, M.
2018-04-01
Laser Interferometer Space Antenna (LISA) Pathfinder is a mission to test the technology enabling gravitational wave detection in space and to demonstrate that sub-femto-g free fall levels are possible. To do so, the distance between two free falling test masses is measured to unprecedented sensitivity by means of laser interferometry. Temperature fluctuations are one of the noise sources limiting the free fall accuracy and the interferometer performance and need to be known at the ˜10 μK Hz-1/2 level in the sub-millihertz frequency range in order to validate the noise models for the future space-based gravitational wave detector LISA. The temperature measurement subsystem on LISA Pathfinder is in charge of monitoring the thermal environment at key locations with noise levels of 7.5 μK Hz-1/2 at the sub-millihertz. However, its performance worsens by one to two orders of magnitude when slowly changing temperatures are measured due to errors introduced by analog-to-digital converter non-linearities. In this paper, we present a method to reduce this effect by data post-processing. The method is applied to experimental data available from on-ground validation tests to demonstrate its performance and the potential benefit for in-flight data. The analog-to-digital converter effects are reduced by a factor between three and six in the frequencies where the errors play an important role. An average 2.7 fold noise reduction is demonstrated in the 0.3 mHz-2 mHz band.
Size reduction of high- and low-moisture corn stalks by linear knife grid system
Igathinathane, C. [Agricultural and Biological Engineering Department, 130 Creelman Street, Mississippi State University, Mississippi State, Mississippi 39762 (United States); Womac, A.R. [Department of Biosystems Engineering and Soil Science, 2506 E. J. Chapman Drive, The University of Tennessee, Knoxville, Tennessee 37996 (United States); Sokhansanj, S. [Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, P. O. Box 2008, Tennessee 37831 (United States); Narayan, S. [First American Scientific Company, 100 Park Royal South West Vancouver, British Columbia, V7T 1A2 (Canada)
2009-04-15
High- and low-moisture corn stalks were tested using a linear knife grid size reduction device developed for first-stage size reduction. The device was used in conjunction with a universal test machine that quantified shearing stress and energy characteristics for forcing a bed of corn stalks through a grid of sharp knives. No published engineering performance data for corn stover with similar devices are available to optimize performance; however, commercial knife grid systems exist for forage size reduction. From the force-displacement data, mean and maximum ultimate shear stresses, cumulative and peak mass-based cutting energies for corn stalks, and mean new surface area-based cutting energies were determined from 4-5 refill runs at two moisture contents (78.8% and 11.3% wet basis), three knife grid spacings (25.4, 50.8, and 101.6 mm), and three bed depths (50.8, 101.6, and 152.4 mm). In general, the results indicated that peak failure load, ultimate shear stress, and cutting energy values varied directly with bed depth and inversely with knife grid spacing. Mean separation analysis established that high- and low-moisture conditions and bed depths {>=} 101.6 mm did not differ significantly (P < 0.05) for ultimate stress and cutting energy values, but knife grid spacing were significantly different. Linear knife grid cutting energy requirements for both moisture conditions of corn stalks were much smaller than reported cutting energy requirements. Ultimate shear stress and cutting energy results of this research should aid the engineering design of commercial scale linear knife gird size reduction equipment for various biomass feedstocks. (author)
Lattice Boltzmann methods for global linear instability analysis
Pérez, José Miguel; Aguilar, Alfonso; Theofilis, Vassilis
2017-12-01
Modal global linear instability analysis is performed using, for the first time ever, the lattice Boltzmann method (LBM) to analyze incompressible flows with two and three inhomogeneous spatial directions. Four linearization models have been implemented in order to recover the linearized Navier-Stokes equations in the incompressible limit. Two of those models employ the single relaxation time and have been proposed previously in the literature as linearization of the collision operator of the lattice Boltzmann equation. Two additional models are derived herein for the first time by linearizing the local equilibrium probability distribution function. Instability analysis results are obtained in three benchmark problems, two in closed geometries and one in open flow, namely the square and cubic lid-driven cavity flow and flow in the wake of the circular cylinder. Comparisons with results delivered by classic spectral element methods verify the accuracy of the proposed new methodologies and point potential limitations particular to the LBM approach. The known issue of appearance of numerical instabilities when the SRT model is used in direct numerical simulations employing the LBM is shown to be reflected in a spurious global eigenmode when the SRT model is used in the instability analysis. Although this mode is absent in the multiple relaxation times model, other spurious instabilities can also arise and are documented herein. Areas of potential improvements in order to make the proposed methodology competitive with established approaches for global instability analysis are discussed.
The Embedding Method for Linear Partial Differential Equations
The recently suggested embedding method to solve linear boundary value problems is here extended to cover situations where the domain of interest is unbounded or multiply connected. The extensions involve the use of complete sets of exterior and interior eigenfunctions on canonical domains. Applications to typical ...
Preconditioned Iterative Methods for Solving Weighted Linear Least Squares Problems
Bru, R.; Marín, J.; Mas, J.; Tůma, Miroslav
2014-01-01
Roč. 36, č. 4 (2014), A2002-A2022 ISSN 1064-8275 Institutional support: RVO:67985807 Keywords : preconditioned iterative methods * incomplete decompositions * approximate inverses * linear least squares Subject RIV: BA - General Mathematics Impact factor: 1.854, year: 2014
A General Linear Method for Equating with Small Samples
Albano, Anthony D.
2015-01-01
Research on equating with small samples has shown that methods with stronger assumptions and fewer statistical estimates can lead to decreased error in the estimated equating function. This article introduces a new approach to linear observed-score equating, one which provides flexible control over how form difficulty is assumed versus estimated…
Sodium flow rate measurement method of annular linear induction pumps
Araseki, Hideo; Kirillov, Igor R.; Preslitsky, Gennady V.
2012-01-01
Highlights: ► We found a new method of flow rate monitoring of electromagnetic pump. ► The method is very simple and does not require a large space. ► The method was verified with an experiment and a numerical analysis. ► The experimental data and the numerical results are in good agreement. - Abstract: The present paper proposes a method for measuring sodium flow rate of annular linear induction pumps. The feature of the method lies in measuring the leaked magnetic field with measuring coils near the stator end on the outlet side and in correlating it with the sodium flow rate. This method is verified through an experiment and a numerical analysis. The data obtained in the experiment reveals that the correlation between the leaked magnetic field and the sodium flow rate is almost linear. The result of the numerical analysis agrees with the experimental data. The present method will be particularly effective to sodium flow rate monitoring of each one of plural annular linear induction pumps arranged in parallel in a vessel which forms a large-scale pump unit.
Linearly convergent stochastic heavy ball method for minimizing generalization error
Loizou, Nicolas
2017-10-30
In this work we establish the first linear convergence result for the stochastic heavy ball method. The method performs SGD steps with a fixed stepsize, amended by a heavy ball momentum term. In the analysis, we focus on minimizing the expected loss and not on finite-sum minimization, which is typically a much harder problem. While in the analysis we constrain ourselves to quadratic loss, the overall objective is not necessarily strongly convex.
Linear algebraic methods applied to intensity modulated radiation therapy.
Crooks, S M; Xing, L
2001-10-01
Methods of linear algebra are applied to the choice of beam weights for intensity modulated radiation therapy (IMRT). It is shown that the physical interpretation of the beam weights, target homogeneity and ratios of deposited energy can be given in terms of matrix equations and quadratic forms. The methodology of fitting using linear algebra as applied to IMRT is examined. Results are compared with IMRT plans that had been prepared using a commercially available IMRT treatment planning system and previously delivered to cancer patients.
Linear density response function in the projector augmented wave method
Yan, Jun; Mortensen, Jens Jørgen; Jacobsen, Karsten Wedel
2011-01-01
We present an implementation of the linear density response function within the projector-augmented wave method with applications to the linear optical and dielectric properties of both solids, surfaces, and interfaces. The response function is represented in plane waves while the single...... functions of Si, C, SiC, AlP, and GaAs compare well with previous calculations. While optical properties of semiconductors, in particular excitonic effects, are generally not well described by ALDA, we obtain excellent agreement with experiments for the surface loss function of graphene and the Mg(0001...
An extended GS method for dense linear systems
Niki, Hiroshi; Kohno, Toshiyuki; Abe, Kuniyoshi
2009-09-01
Davey and Rosindale [K. Davey, I. Rosindale, An iterative solution scheme for systems of boundary element equations, Internat. J. Numer. Methods Engrg. 37 (1994) 1399-1411] derived the GSOR method, which uses an upper triangular matrix [Omega] in order to solve dense linear systems. By applying functional analysis, the authors presented an expression for the optimum [Omega]. Moreover, Davey and Bounds [K. Davey, S. Bounds, A generalized SOR method for dense linear systems of boundary element equations, SIAM J. Comput. 19 (1998) 953-967] also introduced further interesting results. In this note, we employ a matrix analysis approach to investigate these schemes, and derive theorems that compare these schemes with existing preconditioners for dense linear systems. We show that the convergence rate of the Gauss-Seidel method with preconditioner PG is superior to that of the GSOR method. Moreover, we define some splittings associated with the iterative schemes. Some numerical examples are reported to confirm the theoretical analysis. We show that the EGS method with preconditioner produces an extremely small spectral radius in comparison with the other schemes considered.
Preliminary comparison of different reduction methods of graphene
The reduction of graphene oxide (GO) is a promising route to bulk produce graphene-based sheets. Different reduction processes result in reduced graphene oxide (RGO) with different properties. In this paper three reduction methods, chemical, thermal and electrochemical reduction, were compared on three aspects ...
Solution methods for large systems of linear equations in BACCHUS
Homann, C.; Dorr, B.
1993-05-01
The computer programme BACCHUS is used to describe steady state and transient thermal-hydraulic behaviour of a coolant in a fuel element with intact geometry in a fast breeder reactor. In such computer programmes generally large systems of linear equations with sparse matrices of coefficients, resulting from discretization of coolant conservation equations, must be solved thousands of times giving rise to large demands of main storage and CPU time. Direct and iterative solution methods of the systems of linear equations, available in BACCHUS, are described, giving theoretical details and experience with their use in the programme. Besides use of a method of lines, a Runge-Kutta-method, for solution of the partial differential equation is outlined. (orig.) [de
Linear finite element method for one-dimensional diffusion problems
Brandao, Michele A.; Dominguez, Dany S.; Iglesias, Susana M., E-mail: micheleabrandao@gmail.com, E-mail: dany@labbi.uesc.br, E-mail: smiglesias@uesc.br [Universidade Estadual de Santa Cruz (LCC/DCET/UESC), Ilheus, BA (Brazil). Departamento de Ciencias Exatas e Tecnologicas. Laboratorio de Computacao Cientifica
2011-07-01
We describe in this paper the fundamentals of Linear Finite Element Method (LFEM) applied to one-speed diffusion problems in slab geometry. We present the mathematical formulation to solve eigenvalue and fixed source problems. First, we discretized a calculus domain using a finite set of elements. At this point, we obtain the spatial balance equations for zero order and first order spatial moments inside each element. Then, we introduce the linear auxiliary equations to approximate neutron flux and current inside the element and architect a numerical scheme to obtain the solution. We offer numerical results for fixed source typical model problems to illustrate the method's accuracy for coarse-mesh calculations in homogeneous and heterogeneous domains. Also, we compare the accuracy and computational performance of LFEM formulation with conventional Finite Difference Method (FDM). (author)
Marrero, Juan Carlos; Padrón, Edith; Rodríguez-Olmos, Miguel
2012-01-01
This paper addresses the problem of developing an extension of the Marsden–Weinstein reduction process to symplectic-like Lie algebroids, and in particular to the case of the canonical cover of a fiberwise linear Poisson structure, whose reduction process is the analog to cotangent bundle reduction in the context of Lie algebroids. Dedicated to the memory of Jerrold E Marsden (paper)
The Water-Induced Linear Reduction Gas Diffusivity Model Extended to Three Pore Regions
Chamindu, T. K. K. Deepagoda; de Jonge, Lis Wollesen; Kawamoto, Ken
2015-01-01
. Characterization of soil functional pore structure is an essential prerequisite to understand key gas transport processes in variably saturated soils in relation to soil ecosystems, climate, and environmental services. In this study, the water-induced linear reduction (WLR) soil gas diffusivity model originally...... gas diffusivity from moist to dry conditions across differently structured porous media, including narrow soil size fractions, perforated plastic blocks, fractured limestone, peaty soils, aggregated volcanic ash soils, and particulate substrates for Earth- or space-based applications. The new Cip...
Linear-scaling quantum mechanical methods for excited states.
Yam, ChiYung; Zhang, Qing; Wang, Fan; Chen, GuanHua
2012-05-21
The poor scaling of many existing quantum mechanical methods with respect to the system size hinders their applications to large systems. In this tutorial review, we focus on latest research on linear-scaling or O(N) quantum mechanical methods for excited states. Based on the locality of quantum mechanical systems, O(N) quantum mechanical methods for excited states are comprised of two categories, the time-domain and frequency-domain methods. The former solves the dynamics of the electronic systems in real time while the latter involves direct evaluation of electronic response in the frequency-domain. The localized density matrix (LDM) method is the first and most mature linear-scaling quantum mechanical method for excited states. It has been implemented in time- and frequency-domains. The O(N) time-domain methods also include the approach that solves the time-dependent Kohn-Sham (TDKS) equation using the non-orthogonal localized molecular orbitals (NOLMOs). Besides the frequency-domain LDM method, other O(N) frequency-domain methods have been proposed and implemented at the first-principles level. Except one-dimensional or quasi-one-dimensional systems, the O(N) frequency-domain methods are often not applicable to resonant responses because of the convergence problem. For linear response, the most efficient O(N) first-principles method is found to be the LDM method with Chebyshev expansion for time integration. For off-resonant response (including nonlinear properties) at a specific frequency, the frequency-domain methods with iterative solvers are quite efficient and thus practical. For nonlinear response, both on-resonance and off-resonance, the time-domain methods can be used, however, as the time-domain first-principles methods are quite expensive, time-domain O(N) semi-empirical methods are often the practical choice. Compared to the O(N) frequency-domain methods, the O(N) time-domain methods for excited states are much more mature and numerically stable, and
Galerkin projection methods for solving multiple related linear systems
Chan, T.F.; Ng, M.; Wan, W.L.
1996-12-31
We consider using Galerkin projection methods for solving multiple related linear systems A{sup (i)}x{sup (i)} = b{sup (i)} for 1 {le} i {le} s, where A{sup (i)} and b{sup (i)} are different in general. We start with the special case where A{sup (i)} = A and A is symmetric positive definite. The method generates a Krylov subspace from a set of direction vectors obtained by solving one of the systems, called the seed system, by the CG method and then projects the residuals of other systems orthogonally onto the generated Krylov subspace to get the approximate solutions. The whole process is repeated with another unsolved system as a seed until all the systems are solved. We observe in practice a super-convergence behaviour of the CG process of the seed system when compared with the usual CG process. We also observe that only a small number of restarts is required to solve all the systems if the right-hand sides are close to each other. These two features together make the method particularly effective. In this talk, we give theoretical proof to justify these observations. Furthermore, we combine the advantages of this method and the block CG method and propose a block extension of this single seed method. The above procedure can actually be modified for solving multiple linear systems A{sup (i)}x{sup (i)} = b{sup (i)}, where A{sup (i)} are now different. We can also extend the previous analytical results to this more general case. Applications of this method to multiple related linear systems arising from image restoration and recursive least squares computations are considered as examples.
Murakami, H.; Hirai, T.; Nakata, M.; Kobori, T.; Mizukoshi, K.; Takenaka, Y.; Miyagawa, N.
1989-01-01
Many of the equipment systems of nuclear power plants contain a number of non-linearities, such as gap and friction, due to their mechanical functions. It is desirable to take such non-linearities into account appropriately for the evaluation of the aseismic soundness. However, in usual design works, linear analysis method with rough assumptions is applied from engineering point of view. An equivalent linearization method is considered to be one of the effective analytical techniques to evaluate non-linear responses, provided that errors to a certain extent are tolerated, because it has greater simplicity in analysis and economization in computing time than non-linear analysis. The objective of this paper is to investigate the applicability of the equivalent linearization method to evaluate the maximum earthquake response of equipment systems such as the CANDU Fuelling Machine which has multiple non- linearities
Deterministic operations research models and methods in linear optimization
Rader, David J
2013-01-01
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations resear
Linear modeling of turbulent skin-friction reduction due to spanwise wall motion
Duque-Daza, Carlos; Baig, Mirza; Lockerby, Duncan; Chernyshenko, Sergei; Davies, Christopher; University of Warwick Team; Imperial College Team; Cardiff University Team
2012-11-01
We present a study on the effect of streamwise-travelling waves of spanwise wall velocity on the growth of near-wall turbulent streaks using a linearized formulation of the Navier-Stokes equations. The changes in streak amplification due to the travelling waves induced by the wall velocity are compared to published results of direct numerical simulation (DNS) predictions of the turbulent skin-friction reduction over a range of parameters; a clear correlation between these two sets of results is observed. Additional linearized simulations but at a much higher Reynolds numbers, more relevant to aerospace applications, produce results that show no marked differences to those obtained at low Reynolds number. It is also observed that a close correlation exists between DNS data of drag reduction and a very simple characteristic of the ``generalized'' Stokes layer generated by the streamwise-travelling waves. Carlos.Duque-Daza@warwick.ac.uk - School of Engineering, University of Warwick, Coventry CV4 7AL, UK caduqued@unal.edu.co - Department of Mechanical and Mechatronics Engineering, Universidad Nacional de Colombia.
Optimal overlapping of waveform relaxation method for linear differential equations
Yamada, Susumu; Ozawa, Kazufumi
2000-01-01
Waveform relaxation (WR) method is extremely suitable for solving large systems of ordinary differential equations (ODEs) on parallel computers, but the convergence of the method is generally slow. In order to accelerate the convergence, the methods which decouple the system into many subsystems with overlaps some of the components between the adjacent subsystems have been proposed. The methods, in general, converge much faster than the ones without overlapping, but the computational cost per iteration becomes larger due to the increase of the dimension of each subsystem. In this research, the convergence of the WR method for solving constant coefficients linear ODEs is investigated and the strategy to determine the number of overlapped components which minimizes the cost of the parallel computations is proposed. Numerical experiments on an SR2201 parallel computer show that the estimated number of the overlapped components by the proposed strategy is reasonable. (author)
A Lagrangian meshfree method applied to linear and nonlinear elasticity.
Walker, Wade A
2017-01-01
The repeated replacement method (RRM) is a Lagrangian meshfree method which we have previously applied to the Euler equations for compressible fluid flow. In this paper we present new enhancements to RRM, and we apply the enhanced method to both linear and nonlinear elasticity. We compare the results of ten test problems to those of analytic solvers, to demonstrate that RRM can successfully simulate these elastic systems without many of the requirements of traditional numerical methods such as numerical derivatives, equation system solvers, or Riemann solvers. We also show the relationship between error and computational effort for RRM on these systems, and compare RRM to other methods to highlight its strengths and weaknesses. And to further explain the two elastic equations used in the paper, we demonstrate the mathematical procedure used to create Riemann and Sedov-Taylor solvers for them, and detail the numerical techniques needed to embody those solvers in code.
van Manen's method and reduction in a phenomenological hermeneutic study.
Heinonen, Kristiina
2015-03-01
To describe van Manen's method and concept of reduction in a study that used a phenomenological hermeneutic approach. Nurse researchers have used van Manen's method in different ways. Participants' lifeworlds are described in depth, but descriptions of reduction have been brief. The literature and knowledge review and manual search of research articles. Databases Web Science, PubMed, CINAHL and PsycINFO, without applying a time period, to identify uses of van Manen's method. This paper shows how van Manen's method has been used in nursing research and gives some examples of van Manen's reduction. Reduction enables us to conduct in-depth phenomenological hermeneutic research and understand people's lifeworlds. As there are many variations in adapting reduction, it is complex and confusing. This paper contributes to the discussion of phenomenology, hermeneutic study and reduction. It opens up reduction as a method for researchers to exploit.
Exact solution of some linear matrix equations using algebraic methods
Djaferis, T. E.; Mitter, S. K.
1977-01-01
A study is done of solution methods for Linear Matrix Equations including Lyapunov's equation, using methods of modern algebra. The emphasis is on the use of finite algebraic procedures which are easily implemented on a digital computer and which lead to an explicit solution to the problem. The action f sub BA is introduced a Basic Lemma is proven. The equation PA + BP = -C as well as the Lyapunov equation are analyzed. Algorithms are given for the solution of the Lyapunov and comment is given on its arithmetic complexity. The equation P - A'PA = Q is studied and numerical examples are given.
Lyubetsky, Vassily; Gershgorin, Roman; Gorbunov, Konstantin
2017-12-06
Chromosome structure is a very limited model of the genome including the information about its chromosomes such as their linear or circular organization, the order of genes on them, and the DNA strand encoding a gene. Gene lengths, nucleotide composition, and intergenic regions are ignored. Although highly incomplete, such structure can be used in many cases, e.g., to reconstruct phylogeny and evolutionary events, to identify gene synteny, regulatory elements and promoters (considering highly conserved elements), etc. Three problems are considered; all assume unequal gene content and the presence of gene paralogs. The distance problem is to determine the minimum number of operations required to transform one chromosome structure into another and the corresponding transformation itself including the identification of paralogs in two structures. We use the DCJ model which is one of the most studied combinatorial rearrangement models. Double-, sesqui-, and single-operations as well as deletion and insertion of a chromosome region are considered in the model; the single ones comprise cut and join. In the reconstruction problem, a phylogenetic tree with chromosome structures in the leaves is given. It is necessary to assign the structures to inner nodes of the tree to minimize the sum of distances between terminal structures of each edge and to identify the mutual paralogs in a fairly large set of structures. A linear algorithm is known for the distance problem without paralogs, while the presence of paralogs makes it NP-hard. If paralogs are allowed but the insertion and deletion operations are missing (and special constraints are imposed), the reduction of the distance problem to integer linear programming is known. Apparently, the reconstruction problem is NP-hard even in the absence of paralogs. The problem of contigs is to find the optimal arrangements for each given set of contigs, which also includes the mutual identification of paralogs. We proved that these
Eko Rudi Iswanto; Eric Yee
2016-01-01
Within the framework of identifying NPP sites, site surveys are performed in West Bangka (WB), Bangka-Belitung Island Province. Ground response analysis of a potential site has been carried out using peak strain profiles and peak ground acceleration. The objective of this research is to compare Equivalent Linear (EQL) and Non Linear (NL) methods of ground response analysis on the selected NPP site (West Bangka) using Deep Soil software. Equivalent linear method is widely used because requires soil data in simple way and short time of computational process. On the other hand, non linear method is capable of representing the actual soil behaviour by considering non linear soil parameter. The results showed that EQL method has similar trends to NL method. At surface layer, the acceleration values for EQL and NL methods are resulted as 0.425 g and 0.375 g respectively. NL method is more reliable in capturing higher frequencies of spectral acceleration compared to EQL method. (author)
Linear augmented plane wave method for self-consistent calculations
Takeda, T.; Kuebler, J.
1979-01-01
O.K. Andersen has recently introduced a linear augmented plane wave method (LAPW) for the calculation of electronic structure that was shown to be computationally fast. A more general formulation of an LAPW method is presented here. It makes use of a freely disposable number of eigenfunctions of the radial Schroedinger equation. These eigenfunctions can be selected in a self-consistent way. The present formulation also results in a computationally fast method. It is shown that Andersen's LAPW is obtained in a special limit from the present formulation. Self-consistent test calculations for copper show the present method to be remarkably accurate. As an application, scalar-relativistic self-consistent calculations are presented for the band structure of FCC lanthanum. (author)
Uranium manufacturing process employing the electrolytic reduction method
Oda, Yoshio; Kazuhare, Manabu; Morimoto, Takeshi.
1986-01-01
The present invention related to a uranium manufacturing process that employs the electrolytic reduction method, but particularly to a uranium manufacturing process that employs an electrolytic reduction method requiring low voltage. The process, in which uranium is obtained by means of the electrolytic method and with uranyl acid as the raw material, is prior art
M. ZANGIABADI; H. R. MALEKI
2007-01-01
In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...
Revisiting the O(3) non-linear sigma model and its Pohlmeyer reduction
Pastras, Georgios [NCSR ' ' Demokritos' ' , Institute of Nuclear and Particle Physics, Attiki (Greece)
2018-01-15
It is well known that sigma models in symmetric spaces accept equivalent descriptions in terms of integrable systems, such as the sine-Gordon equation, through Pohlmeyer reduction. In this paper, we study the mapping between known solutions of the Euclidean O(3) non-linear sigma model, such as instantons, merons and elliptic solutions that interpolate between the latter, and solutions of the Pohlmeyer reduced theory, namely the sinh-Gordon equation. It turns out that instantons do not have a counterpart, merons correspond to the ground state, while the class of elliptic solutions is characterized by a two to one correspondence between solutions in the two descriptions. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Non linear optical investigations of silver nanoparticles synthesised by curcumin reduction
Dhanya, N. P.
2017-11-01
Metal nanoparticles have considerable applications in assorted fields like medicine, biology, photonics, metallurgy etc. Optical applications of Silver nanoparticles are of significant interest among researchers nowadays. In this paper, we report a single step chemical reduction of silver nanoparticles with Curcumin both as a reducing and stabilising agent at room temperature. Structural, plasmonic and non linear optical properties of the prepared nanoparticles are explored using Scanning Electron Microscope, Transmission Electron Microscope, UV absorption spectrometry, Spectroflurometry and Z scan. UV-Vis absorption studies affirm the Surface Plasmon Resonance (SPR) absorption and spectroflurometric studies announce the emission spectrum of the prepared silvernanoparticles at 520 nm. SEM and TEM images uphold the existence of uniform sized, spherical silvernanoparticles. Nonlinear optical studies are accomplished with the open aperture z scan technique in the nanosecond regime. The nonlinearity is in virtue of saturable absorption, two-photon absorption and excited state absorption. The marked nonlinearity and optical limiting of the Curcumin reduced silvernanoparticles enhances its photonic applications.
An improved partial bundle method for linearly constrained minimax problems
Chunming Tang
2016-02-01
Full Text Available In this paper, we propose an improved partial bundle method for solving linearly constrained minimax problems. In order to reduce the number of component function evaluations, we utilize a partial cutting-planes model to substitute for the traditional one. At each iteration, only one quadratic programming subproblem needs to be solved to obtain a new trial point. An improved descent test criterion is introduced to simplify the algorithm. The method produces a sequence of feasible trial points, and ensures that the objective function is monotonically decreasing on the sequence of stability centers. Global convergence of the algorithm is established. Moreover, we utilize the subgradient aggregation strategy to control the size of the bundle and therefore overcome the difficulty of computation and storage. Finally, some preliminary numerical results show that the proposed method is effective.
Electrostatic Discharge Current Linear Approach and Circuit Design Method
Pavlos K. Katsivelis
2010-11-01
Full Text Available The Electrostatic Discharge phenomenon is a great threat to all electronic devices and ICs. An electric charge passing rapidly from a charged body to another can seriously harm the last one. However, there is a lack in a linear mathematical approach which will make it possible to design a circuit capable of producing such a sophisticated current waveform. The commonly accepted Electrostatic Discharge current waveform is the one set by the IEC 61000-4-2. However, the over-simplified circuit included in the same standard is incapable of producing such a waveform. Treating the Electrostatic Discharge current waveform of the IEC 61000-4-2 as reference, an approximation method, based on Prony’s method, is developed and applied in order to obtain a linear system’s response. Considering a known input, a method to design a circuit, able to generate this ESD current waveform in presented. The circuit synthesis assumes ideal active elements. A simulation is carried out using the PSpice software.
Discrete linear canonical transform computation by adaptive method.
Zhang, Feng; Tao, Ran; Wang, Yue
2013-07-29
The linear canonical transform (LCT) describes the effect of quadratic phase systems on a wavefield and generalizes many optical transforms. In this paper, the computation method for the discrete LCT using the adaptive least-mean-square (LMS) algorithm is presented. The computation approaches of the block-based discrete LCT and the stream-based discrete LCT using the LMS algorithm are derived, and the implementation structures of these approaches by the adaptive filter system are considered. The proposed computation approaches have the inherent parallel structures which make them suitable for efficient VLSI implementations, and are robust to the propagation of possible errors in the computation process.
Alternating direction transport sweeps for linear discontinuous SN method
Yavuz, M.; Aykanat, C.
1993-01-01
The performance of Alternating Direction Transport Sweep (ADTS) method is investigated for spatially differenced Linear Discontinuous S N (LD-S N ) problems on a MIMD multicomputer, Intel IPSC/2. The method consists of dividing a transport problem spatially into sub-problems, assigning each sub-problem to a separate processor. Then, the problem is solved by performing transport sweeps iterating on the scattering source and interface fluxes between the sub-problems. In each processor, the order of transport sweeps is scheduled such that a processor completing its computation in a quadrant of a transport sweep is able to use the most recent information (exiting fluxes of neighboring processor) as its incoming fluxes to start the next quadrant calculation. Implementation of this method on the Intel IPSC/2 multicomputer displays significant speedups over the one-processor method. Also, the performance of the method is compared with those reported previously for the Diamond Differenced S N (DD-S N ) method. Our experimental experience illustrates that the parallel performance of both the ADTS LD- and DD-S N methods is the same. (orig.)
Drag reduction of a car model by linear genetic programming control
Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien
2017-08-01
We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.
Assessment of metal artifact reduction methods in pelvic CT
Abdoli, Mehrsima [Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX (Netherlands); Mehranian, Abolfazl [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211 (Switzerland); Ailianou, Angeliki; Becker, Minerva [Division of Radiology, Geneva University Hospital, Geneva CH-1211 (Switzerland); Zaidi, Habib, E-mail: habib.zaidi@hcuge.ch [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211 (Switzerland); Geneva Neuroscience Center, Geneva University, Geneva CH-1205 (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen 9700 RB (Netherlands)
2016-04-15
Purpose: Metal artifact reduction (MAR) produces images with improved quality potentially leading to confident and reliable clinical diagnosis and therapy planning. In this work, the authors evaluate the performance of five MAR techniques for the assessment of computed tomography images of patients with hip prostheses. Methods: Five MAR algorithms were evaluated using simulation and clinical studies. The algorithms included one-dimensional linear interpolation (LI) of the corrupted projection bins in the sinogram, two-dimensional interpolation (2D), a normalized metal artifact reduction (NMAR) technique, a metal deletion technique, and a maximum a posteriori completion (MAPC) approach. The algorithms were applied to ten simulated datasets as well as 30 clinical studies of patients with metallic hip implants. Qualitative evaluations were performed by two blinded experienced radiologists who ranked overall artifact severity and pelvic organ recognition for each algorithm by assigning scores from zero to five (zero indicating totally obscured organs with no structures identifiable and five indicating recognition with high confidence). Results: Simulation studies revealed that 2D, NMAR, and MAPC techniques performed almost equally well in all regions. LI falls behind the other approaches in terms of reducing dark streaking artifacts as well as preserving unaffected regions (p < 0.05). Visual assessment of clinical datasets revealed the superiority of NMAR and MAPC in the evaluated pelvic organs and in terms of overall image quality. Conclusions: Overall, all methods, except LI, performed equally well in artifact-free regions. Considering both clinical and simulation studies, 2D, NMAR, and MAPC seem to outperform the other techniques.
Pole-shape optimization of permanent-magnet linear synchronous motor for reduction of thrust ripple
Tavana, Nariman Roshandel, E-mail: nroshandel@ee.iust.ac.i [Department of Electrical Engineering, Iran University of Science and Technology, Narmak, Tehran 16846-13114 (Iran, Islamic Republic of); Shoulaie, Abbas, E-mail: shoulaie@iust.ac.i [Department of Electrical Engineering, Iran University of Science and Technology, Narmak, Tehran 16846-13114 (Iran, Islamic Republic of)
2011-01-15
In this paper, we have used magnet arc shaping technique in order to improve the performance of permanent-magnet linear synchronous motor (PMLSM). At first, a detailed analytical modeling based on Maxwell equations is presented for the analysis and design of PMLSM with the arc-shaped magnetic poles (ASMPs). Then the accuracy of presented method is verified by finite-element method. Very close agreement between the analytical and finite-element results shows the effectiveness of the proposed method. Finally, a magnet shape design is carried out based on the analytical method to enhance the motor developed thrust. Pertinent evaluations on the optimal design performance demonstrate that shape optimization leads to a design with extra low thrust ripple.
Pole-shape optimization of permanent-magnet linear synchronous motor for reduction of thrust ripple
Tavana, Nariman Roshandel; Shoulaie, Abbas
2011-01-01
In this paper, we have used magnet arc shaping technique in order to improve the performance of permanent-magnet linear synchronous motor (PMLSM). At first, a detailed analytical modeling based on Maxwell equations is presented for the analysis and design of PMLSM with the arc-shaped magnetic poles (ASMPs). Then the accuracy of presented method is verified by finite-element method. Very close agreement between the analytical and finite-element results shows the effectiveness of the proposed method. Finally, a magnet shape design is carried out based on the analytical method to enhance the motor developed thrust. Pertinent evaluations on the optimal design performance demonstrate that shape optimization leads to a design with extra low thrust ripple.
Deep Learning Methods for Improved Decoding of Linear Codes
Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair
2018-02-01
The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.
Linear source approximation scheme for method of characteristics
Tang Chuntao
2011-01-01
Method of characteristics (MOC) for solving neutron transport equation based on unstructured mesh has already become one of the fundamental methods for lattice calculation of nuclear design code system. However, most of MOC codes are developed with flat source approximation called step characteristics (SC) scheme, which is another basic assumption for MOC. A linear source (LS) characteristics scheme and its corresponding modification for negative source distribution were proposed. The OECD/NEA C5G7-MOX 2D benchmark and a self-defined BWR mini-core problem were employed to validate the new LS module of PEACH code. Numerical results indicate that the proposed LS scheme employs less memory and computational time compared with SC scheme at the same accuracy. (authors)
Adaptive discontinuous Galerkin methods for non-linear reactive flows
Uzunca, Murat
2016-01-01
The focus of this monograph is the development of space-time adaptive methods to solve the convection/reaction dominated non-stationary semi-linear advection diffusion reaction (ADR) equations with internal/boundary layers in an accurate and efficient way. After introducing the ADR equations and discontinuous Galerkin discretization, robust residual-based a posteriori error estimators in space and time are derived. The elliptic reconstruction technique is then utilized to derive the a posteriori error bounds for the fully discrete system and to obtain optimal orders of convergence. As coupled surface and subsurface flow over large space and time scales is described by (ADR) equation the methods described in this book are of high importance in many areas of Geosciences including oil and gas recovery, groundwater contamination and sustainable use of groundwater resources, storing greenhouse gases or radioactive waste in the subsurface.
Linear feature selection in texture analysis - A PLS based method
Marques, Joselene; Igel, Christian; Lillholm, Martin
2013-01-01
We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... and considering all CV groups, the methods selected 36 % of the original features available. The diagnosis evaluation reached a generalization area-under-the-ROC curve of 0.92, which was higher than established cartilage-based markers known to relate to OA diagnosis....
An Augmented Lagrangian Method for the Optimal H∞ Model Order Reduction Problem
Hongli Yang
2017-01-01
Full Text Available This paper treats the computational method of the optimal H∞ model order reduction (MOR problem of linear time-invariant (LTI systems. Optimal solution of MOR problem of LTI systems can be obtained by solving the LMIs feasibility coupling with a rank inequality constraint, which makes the solutions much harder to be obtained. In this paper, we show that the rank inequality constraint can be formulated as a linear rank function equality constraint. Properties of the linear rank function are discussed. We present an iterative algorithm based on augmented Lagrangian method by replacing the rank inequality with the linear rank function. Convergence analysis of the algorithm is given, which is distinct to the now available heuristic methods. Numerical experiments for the MOR problems of continuous LTI system illustrate the practicality of our method.
Reduction Method for Active Distribution Networks
Raboni, Pietro; Chen, Zhe
2013-01-01
On-line security assessment is traditionally performed by Transmission System Operators at the transmission level, ignoring the effective response of distributed generators and small loads. On the other hand the required computation time and amount of real time data for including Distribution...... Networks also would be too large. In this paper an adaptive aggregation method for subsystems with power electronic interfaced generators and voltage dependant loads is proposed. With this tool may be relatively easier including distribution networks into security assessment. The method is validated...... by comparing the results obtained in PSCAD® with the detailed network model and with the reduced one. Moreover the control schemes of a wind turbine and a photovoltaic plant included in the detailed network model are described....
End effect braking force reduction in high-speed single-sided linear induction machine
Shiri, Abbas; Shoulaie, Abbas
2012-01-01
Highlights: ► A new analytical equation to model the end effect braking force of SLIM is derived. ► Equations for efficiency, power factor and output thrust are analytically derived. ► The effect of design variables on the performance of the motor is analyzed. ► An optimization method is employed to minimize the end effect braking force (EEBF). ► The results show that EEBF is minimized by appropriate selection of motor parameters. - Abstract: Linear induction motors have been widely employed in industry because of their simple structure and low construction cost. However, they suffer from low efficiency and power factor. In addition, existence of so called end effect influences their performance especially in high speeds. The end effect deteriorates the performance of the motor by producing braking force. So, in this paper, by using Duncan equivalent circuit model, a new analytical equation is proposed to model end effect braking force. Employing the proposed equation and considering all phenomena involved in the single-sided linear induction motor, a simple design procedure is presented and the effect of different design variables on the performance of the motor is analyzed. A multi-objective optimization method based on genetic algorithm is introduced to maximize efficiency and power factor, as well as to minimize the end effect braking force, simultaneously. Finally, to validate the optimization results, 2D finite element method is employed.
Non linear permanent magnets modelling with the finite element method
Chavanne, J.; Meunier, G.; Sabonnadiere, J.C.
1989-01-01
In order to perform the calculation of permanent magnets with the finite element method, it is necessary to take into account the anisotropic behaviour of hard magnetic materials (Ferrites, NdFeB, SmCo5). In linear cases, the permeability of permanent magnets is a tensor. This one is fully described with the permeabilities parallel and perpendicular to the easy axis of the magnet. In non linear cases, the model uses a texture function which represents the distribution of the local easy axis of the cristallytes of the magnet. This function allows a good representation of the angular dependance of the coercitive field of the magnet. As a result, it is possible to express the magnetic induction B and the tensor as functions of the field and the texture parameter. This model has been implemented in the software FLUX3D where the tensor is used for the Newton-Raphson procedure. 3D demagnetization of a ferrite magnet by a NdFeB magnet is a suitable representative example. They analyze the results obtained for an ideally oriented ferrite magnet and a real one using a measured texture parameter
Reduction method of exhaust gas quantity
Ono, Y.; Morishita, K.
1975-02-08
A cleaning method for automobile exhaust through contact with sintered oxide semiconductors consisting of tin, antimony, manganese, and palladium oxides is discussed. This device has a much higher efficiency and lasts longer than any similar device developed previously consisting of oxides of iron, manganese cobalt, nickel, aluminum, and other rare earth metals. This sintered oxide semiconductor device is composed of: tin oxide: 30 wt ratio, tin hydrogen oxide: 30 wt ratio, antimony oxide: 2 wt ratio, manganese chloride: 2 wt ratio, palladium chloride: 1 wt ratio, carbon powder: 4 wt ratio, and ammonium carbonate: 10 wt ratio, for example. This device converts 100 percent of carbon monoxide into carbon dioxide at 350 C. This compound provides oxygen to CO at higher temperatures and absorbs oxygen from air at normal temperatures. There is no effect on efficiency.
Linear Strength Vortex Panel Method for NACA 4412 Airfoil
Liu, Han
2018-03-01
The objective of this article is to formulate numerical models for two-dimensional potential flow over the NACA 4412 Airfoil using linear vortex panel methods. By satisfying the no penetration boundary condition and Kutta condition, the circulation density on each boundary points (end point of every panel) are obtained and according to which, surface pressure distribution and lift coefficients of the airfoil are predicted and validated by Xfoil, an interactive program for the design and analysis of airfoil. The sensitivity of results to the number of panels is also investigated in the end, which shows that the results are sensitive to the number of panels when panel number ranges from 10 to 160. With the increasing panel number (N>160), the results become relatively insensitive to it.
Grotti, Marco; Abelmoschi, Maria Luisa; Soggia, Francesco; Tiberiade, Christian; Frache, Roberto
2000-12-01
The multivariate effects of Na, K, Mg and Ca as nitrates on the electrothermal atomisation of manganese, cadmium and iron were studied by multiple linear regression modelling. Since the models proved to efficiently predict the effects of the considered matrix elements in a wide range of concentrations, they were applied to correct the interferences occurring in the determination of trace elements in seawater after pre-concentration of the analytes. In order to obtain a statistically significant number of samples, a large volume of the certified seawater reference materials CASS-3 and NASS-3 was treated with Chelex-100 resin; then, the chelating resin was separated from the solution, divided into several sub-samples, each of them was eluted with nitric acid and analysed by electrothermal atomic absorption spectrometry (for trace element determinations) and inductively coupled plasma optical emission spectrometry (for matrix element determinations). To minimise any other systematic error besides that due to matrix effects, accuracy of the pre-concentration step and contamination levels of the procedure were checked by inductively coupled plasma mass spectrometric measurements. Analytical results obtained by applying the multiple linear regression models were compared with those obtained with other calibration methods, such as external calibration using acid-based standards, external calibration using matrix-matched standards and the analyte addition technique. Empirical models proved to efficiently reduce interferences occurring in the analysis of real samples, allowing an improvement of accuracy better than for other calibration methods.
A reduction method for phase equilibrium calculations with cubic equations of state
D. V. Nichita
2006-09-01
Full Text Available In this work we propose a new reduction method for phase equilibrium calculations using a general form of cubic equations of state (CEOS. The energy term in the CEOS is a quadratic form, which is diagonalized by applying a linear transformation. The number of the reduction parameters is related to the rank of the matrix C with elements (1-Cij, where Cij denotes the binary interaction parameters (BIPs. The dimensionality of the problem depends only on the number of reduction parameters, and is independent of the number of components in the mixture.
Giuliano de Oliveira Freitas
2013-10-01
Full Text Available PURPOSE: To determine linear regression models between Alpins descriptive indices and Thibos astigmatic power vectors (APV, assessing the validity and strength of such correlations. METHODS: This case series prospectively assessed 62 eyes of 31 consecutive cataract patients with preoperative corneal astigmatism between 0.75 and 2.50 diopters in both eyes. Patients were randomly assorted among two phacoemulsification groups: one assigned to receive AcrySof®Toric intraocular lens (IOL in both eyes and another assigned to have AcrySof Natural IOL associated with limbal relaxing incisions, also in both eyes. All patients were reevaluated postoperatively at 6 months, when refractive astigmatism analysis was performed using both Alpins and Thibos methods. The ratio between Thibos postoperative APV and preoperative APV (APVratio and its linear regression to Alpins percentage of success of astigmatic surgery, percentage of astigmatism corrected and percentage of astigmatism reduction at the intended axis were assessed. RESULTS: Significant negative correlation between the ratio of post- and preoperative Thibos APVratio and Alpins percentage of success (%Success was found (Spearman's ρ=-0.93; linear regression is given by the following equation: %Success = (-APVratio + 1.00x100. CONCLUSION: The linear regression we found between APVratio and %Success permits a validated mathematical inference concerning the overall success of astigmatic surgery.
A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.
Röhl, Annika; Bockmayr, Alexander
2017-01-03
Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.
Preliminary comparison of different reduction methods of graphene ...
diverse applications and developing a simple, green, and efficient method for the mass production of ... properties of graphene have driven the search to find methods ... Chemical reduction of GO sheets has been performed with ... efficient method for the mass production of graphene. 2. ... temperature was raised to 35.
Lithographic linear motor, lithographic apparatus, and device manufacturing method
2006-01-01
A linear motor having a high driving force, high efficiency and low normal force comprises two opposed magnet tracks and an armature comprising three open coil sets. The linear motor may be used to drive a stage, such as, for example, a mask or wafer stage, in a lithographic apparatus.
Mathematical and Numerical Methods for Non-linear Beam Dynamics
Herr, W
2014-01-01
Non-linear effects in accelerator physics are important for both successful operation of accelerators and during the design stage. Since both of these aspects are closely related, they will be treated together in this overview. Some of the most important aspects are well described by methods established in other areas of physics and mathematics. The treatment will be focused on the problems in accelerators used for particle physics experiments. Although the main emphasis will be on accelerator physics issues, some of the aspects of more general interest will be discussed. In particular, we demonstrate that in recent years a framework has been built to handle the complex problems in a consistent form, technically superior and conceptually simpler than the traditional techniques. The need to understand the stability of particle beams has substantially contributed to the development of new techniques and is an important source of examples which can be verified experimentally. Unfortunately, the documentation of these developments is often poor or even unpublished, in many cases only available as lectures or conference proceedings
Xing, Yafei; Macq, Benoit
2017-11-01
With the emergence of clinical prototypes and first patient acquisitions for proton therapy, the research on prompt gamma imaging is aiming at making most use of the prompt gamma data for in vivo estimation of any shift from expected Bragg peak (BP). The simple problem of matching the measured prompt gamma profile of each pencil beam with a reference simulation from the treatment plan is actually made complex by uncertainties which can translate into distortions during treatment. We will illustrate this challenge and demonstrate the robustness of a predictive linear model we proposed for BP shift estimation based on principal component analysis (PCA) method. It considered the first clinical knife-edge slit camera design in use with anthropomorphic phantom CT data. Particularly, 4115 error scenarios were simulated for the learning model. PCA was applied to the training input randomly chosen from 500 scenarios for eliminating data collinearities. A total variance of 99.95% was used for representing the testing input from 3615 scenarios. This model improved the BP shift estimation by an average of 63+/-19% in a range between -2.5% and 86%, comparing to our previous profile shift (PS) method. The robustness of our method was demonstrated by a comparative study conducted by applying 1000 times Poisson noise to each profile. 67% cases obtained by the learning model had lower prediction errors than those obtained by PS method. The estimation accuracy ranged between 0.31 +/- 0.22 mm and 1.84 +/- 8.98 mm for the learning model, while for PS method it ranged between 0.3 +/- 0.25 mm and 20.71 +/- 8.38 mm.
Linearized versus non-linear inverse methods for seismic localization of underground sources
Oh, Geok Lian; Jacobsen, Finn
2013-01-01
The problem of localization of underground sources from seismic measurements detected by several geophones located on the ground surface is addressed. Two main approaches to the solution of the problem are considered: a beamforming approach that is derived from the linearized inversion problem, a...
Ho, Yuh-Shan
2006-01-01
A comparison was made of the linear least-squares method and a trial-and-error non-linear method of the widely used pseudo-second-order kinetic model for the sorption of cadmium onto ground-up tree fern. Four pseudo-second-order kinetic linear equations are discussed. Kinetic parameters obtained from the four kinetic linear equations using the linear method differed but they were the same when using the non-linear method. A type 1 pseudo-second-order linear kinetic model has the highest coefficient of determination. Results show that the non-linear method may be a better way to obtain the desired parameters.
Extension of the linear nodal method to large concrete building calculations
Childs, R.L.; Rhoades, W.A.
1985-01-01
The implementation of the linear nodal method in the TORT code is described, and the results of a mesh refinement study to test the effectiveness of the linear nodal and weighted diamond difference methods available in TORT are presented
Method and apparatus of highly linear optical modulation
DeRose, Christopher; Watts, Michael R.
2016-05-03
In a new optical intensity modulator, a nonlinear change in refractive index is used to balance the nonlinearities in the optical transfer function in a way that leads to highly linear optical intensity modulation.
Jovanović Jelena
2016-02-01
Full Text Available A cost-effective method for resolution increase of a two-stage piecewise linear analog-to-digital converter used for sensor linearization is proposed in this paper. In both conversion stages flash analog-to-digital converters are employed. Resolution increase by one bit per conversion stage is performed by introducing one additional comparator in front of each of two flash analog-to-digital converters, while the converters’ resolutions remain the same. As a result, the number of employed comparators, as well as the circuit complexity and the power consumption originating from employed comparators are for almost 50 % lower in comparison to the same parameters referring to the linearization circuit of the conventional design and of the same resolution. Since the number of employed comparators is significantly reduced according to the proposed method, special modifications of the linearization circuit are needed in order to properly adjust reference voltages of employed comparators.
Analysis of Drag Reduction Methods and Mechanisms of Turbulent
Gu Yunqing
2017-01-01
Full Text Available Turbulent flow is a difficult issue in fluid dynamics, the rules of which have not been totally revealed up to now. Fluid in turbulent state will result in a greater frictional force, which must consume great energy. Therefore, it is not only an important influence in saving energy and improving energy utilization rate but also an extensive application prospect in many fields, such as ship domain and aerospace. Firstly, bionic drag reduction technology is reviewed and is a hot research issue now, the drag reduction mechanism of body surface structure is analyzed, such as sharks, earthworms, and dolphins. Besides, we make a thorough study of drag reduction characteristics and mechanisms of microgrooved surface and compliant wall. Then, the relevant drag reduction technologies and mechanisms are discussed, focusing on the microbubbles, the vibrant flexible wall, the coating, the polymer drag reduction additives, superhydrophobic surface, jet surface, traveling wave surface drag reduction, and the composite drag reduction methods. Finally, applications and advancements of the drag reduction technology in turbulence are prospected.
A non-linear dimension reduction methodology for generating data-driven stochastic input models
Ganapathysubramanian, Baskar; Zabaras, Nicholas
2008-06-01
Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space Rn. An isometric mapping F from M to a low-dimensional, compact, connected set A⊂Rd(d≪n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low
A non-linear dimension reduction methodology for generating data-driven stochastic input models
Ganapathysubramanian, Baskar; Zabaras, Nicholas
2008-01-01
Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R n . An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R d (d<< n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology
Algebraic coarsening methods for linear and nonlinear PDE and systems
McWilliams, J C
2000-01-01
In [l] Brandt describes a general approach for algebraic coarsening. Given fine-grid equations and a prescribed relaxation method, an approach is presented for defining both the coarse-grid variables and the coarse-grid equations corresponding to these variables. Although, these two tasks are not necessarily related (and, indeed, are often performed independently and with distinct techniques) in the approaches of [1] both revolve around the same underlying observation. To determine whether a given set of coarse-grid variables is appropriate it is suggested that one should employ compatible relaxation. This is a generalization of so-called F-relaxation (e.g., [2]). Suppose that the coarse-grid variables are defined as a subset of the fine-grid variables. Then, F-relaxation simply means relaxing only the F-variables (i.e., fine-grid variables that do not correspond to coarse-grid variables), while leaving the remaining fine-grid variables (C-variables) unchanged. The generalization of compatible relaxation is in allowing the coarse-grid variables to be defined differently, say as linear combinations of fine-grid variables, or even nondeterministically (see examples in [1]). For the present summary it suffices to consider the simple case. The central observation regarding the set of coarse-grid variables is the following [1]: Observation 1--A general measure for the quality of the set of coarse-grid variables is the convergence rate of compatible relaxation. The conclusion is that a necessary condition for efficient multigrid solution (e.g., with convergence rates independent of problem size) is that the compatible-relaxation convergence be bounded away from 1, independently of the number of variables. This is often a sufficient condition, provided that the coarse-grid equations are sufficiently accurate. Therefore, it is suggested in [1] that the convergence rate of compatible relaxation should be used as a criterion for choosing and evaluating the set of coarse
METHODS OF REDUCTION OF FREE PHENOL CONTENT IN PHENOLIC FOAM
Bruyako Mikhail Gerasimovich
2012-12-01
method aimed at reduction of toxicity of phenolic foams consists in the introduction of a composite mixture of chelate compounds. Raw materials applied in the production of phenolic foams include polymers FRB-1A and VAG-3. The aforementioned materials are used to produce foams FRP-1. Introduction of 1% aluminum fluoride leads to the 40% reduction of the free phenol content in the foam. Introduction of crystalline zinc chloride accelerates the foaming and curing of phenolic foams. The technology that contemplates the introduction of zeolites into the mixture includes pre-mixing with FRB -1A and subsequent mixing with VAG-3; thereafter, the composition is poured into the form, in which the process of foaming is initiated. The content of free phenol was identified using the method of UV spectroscopy. The objective of the research was to develop methods of reduction of the free phenol content in the phenolic foam.
An implementation analysis of the linear discontinuous finite element method
Becker, T. L.
2013-01-01
This paper provides an implementation analysis of the linear discontinuous finite element method (LD-FEM) that spans the space of (l, x, y, z). A practical implementation of LD includes 1) selecting a computationally efficient algorithm to solve the 4 x 4 matrix system Ax = b that describes the angular flux in a mesh element, and 2) choosing how to store the data used to construct the matrix A and the vector b to either reduce memory consumption or increase computational speed. To analyze the first of these, three algorithms were selected to solve the 4 x 4 matrix equation: Cramer's rule, a streamlined implementation of Gaussian elimination, and LAPACK's Gaussian elimination subroutine dgesv. The results indicate that Cramer's rule and the streamlined Gaussian elimination algorithm perform nearly equivalently and outperform LAPACK's implementation of Gaussian elimination by a factor of 2. To analyze the second implementation detail, three formulations of the discretized LD-FEM equations were provided for implementation in a transport solver: 1) a low-memory formulation, which relies heavily on 'on-the-fly' calculations and less on the storage of pre-computed data, 2) a high-memory formulation, which pre-computes much of the data used to construct A and b, and 3) a reduced-memory formulation, which lies between the low - and high-memory formulations. These three formulations were assessed in the Jaguar transport solver based on relative memory footprint and computational speed for increasing mesh size and quadrature order. The results indicated that the memory savings of the low-memory formulation were not sufficient to warrant its implementation. The high-memory formulation resulted in a significant speed advantage over the reduced-memory option (10-50%), but also resulted in a proportional increase in memory consumption (5-45%) for increasing quadrature order and mesh count; therefore, the practitioner should weigh the system memory constraints against any
An implementation analysis of the linear discontinuous finite element method
Becker, T. L. [Bechtel Marine Propulsion Corporation, Knolls Atomic Power Laboratory, P.O. Box 1072, Schenectady, NY 12301-1072 (United States)
2013-07-01
This paper provides an implementation analysis of the linear discontinuous finite element method (LD-FEM) that spans the space of (l, x, y, z). A practical implementation of LD includes 1) selecting a computationally efficient algorithm to solve the 4 x 4 matrix system Ax = b that describes the angular flux in a mesh element, and 2) choosing how to store the data used to construct the matrix A and the vector b to either reduce memory consumption or increase computational speed. To analyze the first of these, three algorithms were selected to solve the 4 x 4 matrix equation: Cramer's rule, a streamlined implementation of Gaussian elimination, and LAPACK's Gaussian elimination subroutine dgesv. The results indicate that Cramer's rule and the streamlined Gaussian elimination algorithm perform nearly equivalently and outperform LAPACK's implementation of Gaussian elimination by a factor of 2. To analyze the second implementation detail, three formulations of the discretized LD-FEM equations were provided for implementation in a transport solver: 1) a low-memory formulation, which relies heavily on 'on-the-fly' calculations and less on the storage of pre-computed data, 2) a high-memory formulation, which pre-computes much of the data used to construct A and b, and 3) a reduced-memory formulation, which lies between the low - and high-memory formulations. These three formulations were assessed in the Jaguar transport solver based on relative memory footprint and computational speed for increasing mesh size and quadrature order. The results indicated that the memory savings of the low-memory formulation were not sufficient to warrant its implementation. The high-memory formulation resulted in a significant speed advantage over the reduced-memory option (10-50%), but also resulted in a proportional increase in memory consumption (5-45%) for increasing quadrature order and mesh count; therefore, the practitioner should weigh the system memory
Vibration of carbon nanotubes with defects: order reduction methods
Hudson, Robert B.; Sinha, Alok
2018-03-01
Order reduction methods are widely used to reduce computational effort when calculating the impact of defects on the vibrational properties of nearly periodic structures in engineering applications, such as a gas-turbine bladed disc. However, despite obvious similarities these techniques have not yet been adapted for use in analysing atomic structures with inevitable defects. Two order reduction techniques, modal domain analysis and modified modal domain analysis, are successfully used in this paper to examine the changes in vibrational frequencies, mode shapes and mode localization caused by defects in carbon nanotubes. The defects considered are isotope defects and Stone-Wales defects, though the methods described can be extended to other defects.
Proposal of Realization Restricted Quantum Game with Linear Optic Method
Zhao Haijun; Fang Ximing
2006-01-01
We present a quantum game with the restricted strategic space and its realization with linear optical system, which can be played by two players who are separated remotely. This game can also be realized on any other quantum computers. We find that the constraint brings some interesting properties that are useful for making game models.
Improved Methods for Pitch Synchronous Linear Prediction Analysis of Speech
劉, 麗清
2015-01-01
Linear prediction (LP) analysis has been applied to speech system over the last few decades. LP technique is well-suited for speech analysis due to its ability to model speech production process approximately. Hence LP analysis has been widely used for speech enhancement, low-bit-rate speech coding in cellular telephony, speech recognition, characteristic parameter extraction (vocal tract resonances frequencies, fundamental frequency called pitch) and so on. However, the performance of the co...
A general method for enclosing solutions of interval linear equations
Rohn, Jiří
2012-01-01
Roč. 6, č. 4 (2012), s. 709-717 ISSN 1862-4472 R&D Projects: GA ČR GA201/09/1957; GA ČR GC201/08/J020 Institutional research plan: CEZ:AV0Z10300504 Keywords : interval linear equations * solution set * enclosure * absolute value inequality Subject RIV: BA - General Mathematics Impact factor: 1.654, year: 2012
Locally linear approximation for Kernel methods : the Railway Kernel
Muñoz, Alberto; González, Javier
2008-01-01
In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel. In this way, we avoid potential problems due to the use of a general purpose kernel, like the RBF kernel, as the high dimension of the induced feature space. As a consequence, following our methodology the number of support vectors is much lower and, therefore, the generalization capab...
On symmetry reduction and exact solutions of the linear one-dimensional Schroedinger equation
Barannik, L.L.
1996-01-01
Symmetry reduction of the Schroedinger equation with potential is carried out on subalgebras of the Lie algebra which is the direct sum of the special Galilei algebra and one-dimensional algebra. Some new exact solutions are obtained
Second derivative continuous linear multistep methods for the ...
step methods (LMM), with properties that embed the characteristics of LMM and hybrid methods. This paper gives a continuous reformulation of the Enright [5] second derivative methods. The motivation lies in the fact that the new formulation ...
Method of dimensionality reduction in contact mechanics and friction
Popov, Valentin L
2015-01-01
This book describes for the first time a simulation method for the fast calculation of contact properties and friction between rough surfaces in a complete form. In contrast to existing simulation methods, the method of dimensionality reduction (MDR) is based on the exact mapping of various types of three-dimensional contact problems onto contacts of one-dimensional foundations. Within the confines of MDR, not only are three dimensional systems reduced to one-dimensional, but also the resulting degrees of freedom are independent from another. Therefore, MDR results in an enormous reduction of the development time for the numerical implementation of contact problems as well as the direct computation time and can ultimately assume a similar role in tribology as FEM has in structure mechanics or CFD methods, in hydrodynamics. Furthermore, it substantially simplifies analytical calculation and presents a sort of “pocket book edition” of the entirety contact mechanics. Measurements of the rheology of bodies in...
Leapfrog variants of iterative methods for linear algebra equations
Saylor, Paul E.
1988-01-01
Two iterative methods are considered, Richardson's method and a general second order method. For both methods, a variant of the method is derived for which only even numbered iterates are computed. The variant is called a leapfrog method. Comparisons between the conventional form of the methods and the leapfrog form are made under the assumption that the number of unknowns is large. In the case of Richardson's method, it is possible to express the final iterate in terms of only the initial approximation, a variant of the iteration called the grand-leap method. In the case of the grand-leap variant, a set of parameters is required. An algorithm is presented to compute these parameters that is related to algorithms to compute the weights and abscissas for Gaussian quadrature. General algorithms to implement the leapfrog and grand-leap methods are presented. Algorithms for the important special case of the Chebyshev method are also given.
Generalized linear mixed models modern concepts, methods and applications
Stroup, Walter W
2012-01-01
PART I The Big PictureModeling BasicsWhat Is a Model?Two Model Forms: Model Equation and Probability DistributionTypes of Model EffectsWriting Models in Matrix FormSummary: Essential Elements for a Complete Statement of the ModelDesign MattersIntroductory Ideas for Translating Design and Objectives into ModelsDescribing ""Data Architecture"" to Facilitate Model SpecificationFrom Plot Plan to Linear PredictorDistribution MattersMore Complex Example: Multiple Factors with Different Units of ReplicationSetting the StageGoals for Inference with Models: OverviewBasic Tools of InferenceIssue I: Data
Fast Reduction Method in Dominance-Based Information Systems
Li, Yan; Zhou, Qinghua; Wen, Yongchuan
2018-01-01
In real world applications, there are often some data with continuous values or preference-ordered values. Rough sets based on dominance relations can effectively deal with these kinds of data. Attribute reduction can be done in the framework of dominance-relation based approach to better extract decision rules. However, the computational cost of the dominance classes greatly affects the efficiency of attribute reduction and rule extraction. This paper presents an efficient method of computing dominance classes, and further compares it with traditional method with increasing attributes and samples. Experiments on UCI data sets show that the proposed algorithm obviously improves the efficiency of the traditional method, especially for large-scale data.
Variance reduction methods applied to deep-penetration problems
Cramer, S.N.
1984-01-01
All deep-penetration Monte Carlo calculations require variance reduction methods. Before beginning with a detailed approach to these methods, several general comments concerning deep-penetration calculations by Monte Carlo, the associated variance reduction, and the similarities and differences of these with regard to non-deep-penetration problems will be addressed. The experienced practitioner of Monte Carlo methods will easily find exceptions to any of these generalities, but it is felt that these comments will aid the novice in understanding some of the basic ideas and nomenclature. Also, from a practical point of view, the discussions and developments presented are oriented toward use of the computer codes which are presented in segments of this Monte Carlo course
Reduced order methods for modeling and computational reduction
Rozza, Gianluigi
2014-01-01
This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics. Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This...
One testing method of dynamic linearity of an accelerometer
Lei Jing-Yu
2015-01-01
Full Text Available To effectively test dynamic linearity of an accelerometer over a wide rang of 104 g to about 20 × 104g, one published patent technology is first experimentally verified and analysed, and its deficient is presented, then based on stress wave propagation theory on the thin long bar, the relation between the strain signal and the corresponding acceleration signal is obtained, one special link of two coaxial projectile is developed. These two coaxial metal cylinders (inner cylinder and circular tube are used as projectiles, to prevent their mutual slip inside the gun barrel during movement, the one end of two projectiles is always fastened by small screws. Ti6-AL4-V bar with diameter of 30 mm is used to propagate loading stress pulse. The resultant compression wave can be measured by the strain gauges on the bar, and a half –sine strain pulse is obtained. The measuring accelerometer is attached on the other end of the bar by a vacuum clamp. In this clamp, the accelerometer only bear compression wave, the reflected tension pulse make the accelerometer off the bar. Using this system, dynamic linearity measurement of accelerometer can be easily tested in wider range of acceleration values. And a really measuring results are presented.
Griebler, C; Slezak, D
2001-01-01
A new method to determine microbial (bacterial and fungal) activity in various freshwater habitats is described. Based on microbial reduction of dimethyl sulfoxide (DMSO) to dimethyl sulfide (DMS), our DMSO reduction method allows measurement of the respiratory activity in interstitial water, as well as in the water column. DMSO is added to water samples at a concentration (0.75% [vol/vol] or 106 mM) high enough to compete with other naturally occurring electron acceptors, as determined with oxygen and nitrate, without stimulating or inhibiting microbial activity. Addition of NaN(3), KCN, and formaldehyde, as well as autoclaving, inhibited the production of DMS, which proves that the reduction of DMSO is a biotic process. DMSO reduction is readily detectable via the formation of DMS even at low microbial activities. All water samples showed significant DMSO reduction over several hours. Microbially reduced DMSO is recovered in the form of DMS from water samples by a purge and trap system and is quantified by gas chromatography and detection with a flame photometric detector. The DMSO reduction method was compared with other methods commonly used for assessment of microbial activity. DMSO reduction activity correlated well with bacterial production in predator-free batch cultures. Cell-production-specific DMSO reduction rates did not differ significantly in batch cultures with different nutrient regimes but were different in different growth phases. Overall, a cell-production-specific DMSO reduction rate of 1.26 x 10(-17) +/- 0. 12 x 10(-17) mol of DMS per produced cell (mean +/- standard error; R(2) = 0.78) was calculated. We suggest that the relationship of DMSO reduction rates to thymidine and leucine incorporation is linear (the R(2) values ranged from 0.783 to 0.944), whereas there is an exponential relationship between DMSO reduction rates and glucose uptake, as well as incorporation (the R(2) values ranged from 0.821 to 0.931). Based on our results, we
Approximate inverse preconditioning of iterative methods for nonsymmetric linear systems
Benzi, M. [Universita di Bologna (Italy); Tuma, M. [Inst. of Computer Sciences, Prague (Czech Republic)
1996-12-31
A method for computing an incomplete factorization of the inverse of a nonsymmetric matrix A is presented. The resulting factorized sparse approximate inverse is used as a preconditioner in the iterative solution of Ax = b by Krylov subspace methods.
Alam, I; Morgan, J; Baxter, J; Lewis, M J
2009-01-01
'scaling' or 'collective response' across the multiple autonomic modulators of heart rate. The multifractal method appears to be a more sensitive measure of integrated cardiac autonomic function than linear methods for these patients
A simple finite element method for linear hyperbolic problems
Mu, Lin; Ye, Xiu
2017-01-01
Here, we introduce a simple finite element method for solving first order hyperbolic equations with easy implementation and analysis. Our new method, with a symmetric, positive definite system, is designed to use discontinuous approximations on finite element partitions consisting of arbitrary shape of polygons/polyhedra. Error estimate is established. Extensive numerical examples are tested that demonstrate the robustness and flexibility of the method.
Metal artifact reduction method using metal streaks image subtraction
Pua, Rizza D.; Cho, Seung Ryong
2014-01-01
Many studies have been dedicated for metal artifact reduction (MAR); however, the methods are successful to varying degrees depending on situations. Sinogram in-painting, filtering, iterative method are some of the major categories of MAR. Each has its own merits and weaknesses. A combination of these methods or hybrid methods have also been developed to make use of the different benefits of two techniques and minimize the unfavorable results. Our method focuses on the in-paitning approach and a hybrid MAR described by Xia et al. Although in-painting scheme is an effective technique in reducing the primary metal artifacts, a major drawback is the reintroduction of new artifacts that can be caused by an inaccurate interpolation process. Furthermore, combining the segmented metal image to the corrected nonmetal image in the final step of a conventional inpainting approach causes an issue of incorrect metal pixel values. Our proposed method begins with a sinogram in-painting approach and ends with an image-based metal artifact reduction scheme. This work provides a simple, yet effective solution for reducing metal artifacts and acquiring the original metal pixel information. The proposed method demonstrated its effectiveness in a simulation setting. The proposed method showed image quality that is comparable to the standard MAR; however, quantitatively more accurate than the standard MAR
Review of noise reduction methods for centrifugal fans
Neise, W.
1981-11-01
Several methods for the reduction of centrifugal fan noise are presented, the most of which are aimed at a lower blade passage frequency level. The methods are grouped into five categories: casing modifications to increase the distance between impeller and cutoff, the introduction of a phase shift of the source pressure fluctuations, impeller modifications, radial clearance between impeller eye and inlet nozzle, and acoustical measures. Resonators mounted at the cutoff of centrifugal fans appear to be a highly efficient and simple means of reducing the blade passage tone, and the method can be used for new fan construction and existing installations without affecting the aerodynamic performance of the fan.
Dimension reduction methods for microarray data: a review
Rabia Aziz
2017-03-01
Full Text Available Dimension reduction has become inevitable for pre-processing of high dimensional data. “Gene expression microarray data” is an instance of such high dimensional data. Gene expression microarray data displays the maximum number of genes (features simultaneously at a molecular level with a very small number of samples. The copious numbers of genes are usually provided to a learning algorithm for producing a complete characterization of the classification task. However, most of the times the majority of the genes are irrelevant or redundant to the learning task. It will deteriorate the learning accuracy and training speed as well as lead to the problem of overfitting. Thus, dimension reduction of microarray data is a crucial preprocessing step for prediction and classification of disease. Various feature selection and feature extraction techniques have been proposed in the literature to identify the genes, that have direct impact on the various machine learning algorithms for classification and eliminate the remaining ones. This paper describes the taxonomy of dimension reduction methods with their characteristics, evaluation criteria, advantages and disadvantages. It also presents a review of numerous dimension reduction approaches for microarray data, mainly those methods that have been proposed over the past few years.
Nonlinear dimensionality reduction methods for synthetic biology biobricks' visualization.
Yang, Jiaoyun; Wang, Haipeng; Ding, Huitong; An, Ning; Alterovitz, Gil
2017-01-19
Visualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately labeled data, etc. As crowdsourcing-based synthetic biology databases face similar data quality issues, we propose to visualize biobricks to tackle them. However, existing dimensionality reduction methods could not be directly applied on biobricks datasets. Hereby, we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and Laplacian Eigenmaps. By extracting biobricks from synthetic biology database Registry of Standard Biological Parts, six combinations of various types of biobricks are tested. The visualization graphs illustrate discriminated biobricks and inappropriately labeled biobricks. Clustering algorithm K-means is adopted to quantify the reduction results. The average clustering accuracy for Isomap and Laplacian Eigenmaps are 0.857 and 0.844, respectively. Besides, Laplacian Eigenmaps is 5 times faster than Isomap, and its visualization graph is more concentrated to discriminate biobricks. By combining normalized edit distance with Isomap and Laplacian Eigenmaps, synthetic biology biobircks are successfully visualized in two dimensional space. Various types of biobricks could be discriminated and inappropriately labeled biobricks could be determined, which could help to assess crowdsourcing-based synthetic biology databases' quality, and make biobricks selection.
Speckle reduction methods in laser-based picture projectors
Akram, M. Nadeem; Chen, Xuyuan
2016-02-01
Laser sources have been promised for many years to be better light sources as compared to traditional lamps or light-emitting diodes (LEDs) for projectors, which enable projectors having wide colour gamut for vivid image, super brightness and high contrast for the best picture quality, long lifetime for maintain free operation, mercury free, and low power consumption for green environment. A major technology obstacle in using lasers for projection has been the speckle noise caused by to the coherent nature of the lasers. For speckle reduction, current state of the art solutions apply moving parts with large physical space demand. Solutions beyond the state of the art need to be developed such as integrated optical components, hybrid MOEMS devices, and active phase modulators for compact speckle reduction. In this article, major methods reported in the literature for the speckle reduction in laser projectors are presented and explained. With the advancement in semiconductor lasers with largely reduced cost for the red, green and the blue primary colours, and the developed methods for their speckle reduction, it is hoped that the lasers will be widely utilized in different projector applications in the near future.
Linear and kernel methods for multi- and hypervariate change detection
Nielsen, Allan Aasbjerg; Canty, Morton J.
2010-01-01
. Principal component analysis (PCA) as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (which are nonlinear), may further enhance change signals relative to no-change background. The kernel versions are based on a dual...... formulation, also termed Q-mode analysis, in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution......, also known as the kernel trick, these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of the kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component...
Linear and kernel methods for multivariate change detection
Canty, Morton J.; Nielsen, Allan Aasbjerg
2012-01-01
), as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (nonlinear), may further enhance change signals relative to no-change background. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric...... normalization, and kernel PCA/MAF/MNF transformations are presented that function as transparent and fully integrated extensions of the ENVI remote sensing image analysis environment. The train/test approach to kernel PCA is evaluated against a Hebbian learning procedure. Matlab code is also available...... that allows fast data exploration and experimentation with smaller datasets. New, multiresolution versions of IR-MAD that accelerate convergence and that further reduce no-change background noise are introduced. Computationally expensive matrix diagonalization and kernel image projections are programmed...
Oscillatory Reduction in Option Pricing Formula Using Shifted Poisson and Linear Approximation
Rachmawati Ro’fah Nur
2014-03-01
Full Text Available Option is one of derivative instruments that can help investors improve their expected return and minimize the risks. However, the Black-Scholes formula is generally used in determining the price of the option does not involve skewness factor and it is difficult to apply in computing process because it produces oscillation for the skewness values close to zero. In this paper, we construct option pricing formula that involve skewness by modified Black-Scholes formula using Shifted Poisson model and transformed it into the form of a Linear Approximation in the complete market to reduce the oscillation. The results are Linear Approximation formula can predict the price of an option with very accurate and successfully reduce the oscillations in the calculation processes.
Thrust Reduction of Magnetic Levitation Vehicle Driven by Long Stator Linear Synchronous Motor
Wan-Tsun Tseng
2013-01-01
Full Text Available The propulsion technology of long stator linear synchronous motors is used to drive high-speed maglev trains. The linear synchronous motor stator is divided into sections placed on guideway. The electric power supplies to stator sections in which the train just passes in change-step mode for long-distance operation. However, a thrust drop will be caused by change-step machinery for driving magnetic vehicle. According to the train speed and vehicle data, the change-step mode has three types of operation, namely premature commutation, simultaneous commutation, and late commutation. Each type of operation has a different thrust drop which can be affected by several parameters such as jerk, running speed, motor section length, and vehicle data. This paper focuses on determining the thrust drop of the change-step mode. The study results of this paper can be used to improve the operation system of high-speed maglev trains.
Iterative methods for dose reduction and image enhancement in tomography
Miao, Jianwei; Fahimian, Benjamin Pooya
2012-09-18
A system and method for creating a three dimensional cross sectional image of an object by the reconstruction of its projections that have been iteratively refined through modification in object space and Fourier space is disclosed. The invention provides systems and methods for use with any tomographic imaging system that reconstructs an object from its projections. In one embodiment, the invention presents a method to eliminate interpolations present in conventional tomography. The method has been experimentally shown to provide higher resolution and improved image quality parameters over existing approaches. A primary benefit of the method is radiation dose reduction since the invention can produce an image of a desired quality with a fewer number projections than seen with conventional methods.
Sanz, Luis; Alonso, Juan Antonio
2017-12-01
In this work we develop approximate aggregation techniques in the context of slow-fast linear population models governed by stochastic differential equations and apply the results to the treatment of populations with spatial heterogeneity. Approximate aggregation techniques allow one to transform a complex system involving many coupled variables and in which there are processes with different time scales, by a simpler reduced model with a fewer number of 'global' variables, in such a way that the dynamics of the former can be approximated by that of the latter. In our model we contemplate a linear fast deterministic process together with a linear slow process in which the parameters are affected by additive noise, and give conditions for the solutions corresponding to positive initial conditions to remain positive for all times. By letting the fast process reach equilibrium we build a reduced system with a lesser number of variables, and provide results relating the asymptotic behaviour of the first- and second-order moments of the population vector for the original and the reduced system. The general technique is illustrated by analysing a multiregional stochastic system in which dispersal is deterministic and the rate growth of the populations in each patch is affected by additive noise.
On some properties of the block linear multi-step methods | Chollom ...
The convergence, stability and order of Block linear Multistep methods have been determined in the past based on individual members of the block. In this paper, methods are proposed to examine the properties of the entire block. Some Block Linear Multistep methods have been considered, their convergence, stability and ...
Krylov subspace methods for solving large unsymmetric linear systems
Saad, Y.
1981-01-01
Some algorithms based upon a projection process onto the Krylov subspace K/sub m/ = Span(r 0 , Ar 0 ,...,A/sup m/-1r 0 ) are developed, generalizing the method of conjugate gradients to unsymmetric systems. These methods are extensions of Arnoldi's algorithm for solving eigenvalue problems. The convergence is analyzed in terms of the distance of the solution to the subspace K/sub m/ and some error bounds are established showing, in particular, a similarity with the conjugate gradient method (for symmetric matrices) when the eigenvalues are real. Several numerical experiments are described and discussed
Lubna Moin
2009-04-01
Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and
Noise reduction methods for nucleic acid and macromolecule sequencing
Schuller, Ivan K.; Di Ventra, Massimiliano; Balatsky, Alexander
2018-05-08
Methods, systems, and devices are disclosed for processing macromolecule sequencing data with substantial noise reduction. In one aspect, a method for reducing noise in a sequential measurement of a macromolecule comprising serial subunits includes cross-correlating multiple measured signals of a physical property of subunits of interest of the macromolecule, the multiple measured signals including the time data associated with the measurement of the signal, to remove or at least reduce signal noise that is not in the same frequency and in phase with the systematic signal contribution of the measured signals.
Method for validating radiobiological samples using a linear accelerator
Brengues, Muriel; Liu, David; Korn, Ronald; Zenhausern, Frederic
2014-01-01
There is an immediate need for rapid triage of the population in case of a large scale exposure to ionizing radiation. Knowing the dose absorbed by the body will allow clinicians to administer medical treatment for the best chance of recovery for the victim. In addition, today's radiotherapy treatment could benefit from additional information regarding the patient's sensitivity to radiation before starting the treatment. As of today, there is no system in place to respond to this demand. This paper will describe specific procedures to mimic the effects of human exposure to ionizing radiation creating the tools for optimization of administered radiation dosimetry for radiotherapy and/or to estimate the doses of radiation received accidentally during a radiation event that could pose a danger to the public. In order to obtain irradiated biological samples to study ionizing radiation absorbed by the body, we performed ex-vivo irradiation of human blood samples using the linear accelerator (LINAC). The LINAC was implemented and calibrated for irradiating human whole blood samples. To test the calibration, a 2 Gy test run was successfully performed on a tube filled with water with an accuracy of 3% in dose distribution. To validate our technique the blood samples were ex-vivo irradiated and the results were analyzed using a gene expression assay to follow the effect of the ionizing irradiation by characterizing dose responsive biomarkers from radiobiological assays. The response of 5 genes was monitored resulting in expression increase with the dose of radiation received. The blood samples treated with the LINAC can provide effective irradiated blood samples suitable for molecular profiling to validate radiobiological measurements via the gene-expression based biodosimetry tools. (orig.)
Method for validating radiobiological samples using a linear accelerator.
Brengues, Muriel; Liu, David; Korn, Ronald; Zenhausern, Frederic
2014-04-29
There is an immediate need for rapid triage of the population in case of a large scale exposure to ionizing radiation. Knowing the dose absorbed by the body will allow clinicians to administer medical treatment for the best chance of recovery for the victim. In addition, today's radiotherapy treatment could benefit from additional information regarding the patient's sensitivity to radiation before starting the treatment. As of today, there is no system in place to respond to this demand. This paper will describe specific procedures to mimic the effects of human exposure to ionizing radiation creating the tools for optimization of administered radiation dosimetry for radiotherapy and/or to estimate the doses of radiation received accidentally during a radiation event that could pose a danger to the public. In order to obtain irradiated biological samples to study ionizing radiation absorbed by the body, we performed ex-vivo irradiation of human blood samples using the linear accelerator (LINAC). The LINAC was implemented and calibrated for irradiating human whole blood samples. To test the calibration, a 2 Gy test run was successfully performed on a tube filled with water with an accuracy of 3% in dose distribution. To validate our technique the blood samples were ex-vivo irradiated and the results were analyzed using a gene expression assay to follow the effect of the ionizing irradiation by characterizing dose responsive biomarkers from radiobiological assays. The response of 5 genes was monitored resulting in expression increase with the dose of radiation received. The blood samples treated with the LINAC can provide effective irradiated blood samples suitable for molecular profiling to validate radiobiological measurements via the gene-expression based biodosimetry tools.
Nonstandard Finite Difference Method Applied to a Linear Pharmacokinetics Model
Oluwaseun Egbelowo
2017-05-01
Full Text Available We extend the nonstandard finite difference method of solution to the study of pharmacokinetic–pharmacodynamic models. Pharmacokinetic (PK models are commonly used to predict drug concentrations that drive controlled intravenous (I.V. transfers (or infusion and oral transfers while pharmacokinetic and pharmacodynamic (PD interaction models are used to provide predictions of drug concentrations affecting the response of these clinical drugs. We structure a nonstandard finite difference (NSFD scheme for the relevant system of equations which models this pharamcokinetic process. We compare the results obtained to standard methods. The scheme is dynamically consistent and reliable in replicating complex dynamic properties of the relevant continuous models for varying step sizes. This study provides assistance in understanding the long-term behavior of the drug in the system, and validation of the efficiency of the nonstandard finite difference scheme as the method of choice.
Zhou G Tong
2007-01-01
Full Text Available Many modern communication signal formats, such as orthogonal frequency-division multiplexing (OFDM and code-division multiple access (CDMA, have high peak-to-average power ratios (PARs. A signal with a high PAR not only is vulnerable in the presence of nonlinear components such as power amplifiers (PAs, but also leads to low transmission power efficiency. Selected mapping (SLM and clipping are well-known PAR reduction techniques. We propose to combine SLM with threshold clipping and digital baseband predistortion to improve the overall efficiency of the transmission system. Testbed experiments demonstrate the effectiveness of the proposed approach.
Interpolation from Grid Lines: Linear, Transfinite and Weighted Method
Lindberg, Anne-Sofie Wessel; Jørgensen, Thomas Martini; Dahl, Vedrana Andersen
2017-01-01
When two sets of line scans are acquired orthogonal to each other, intensity values are known along the lines of a grid. To view these values as an image, intensities need to be interpolated at regularly spaced pixel positions. In this paper we evaluate three methods for interpolation from grid l...
Huffman and linear scanning methods with statistical language models.
Roark, Brian; Fried-Oken, Melanie; Gibbons, Chris
2015-03-01
Current scanning access methods for text generation in AAC devices are limited to relatively few options, most notably row/column variations within a matrix. We present Huffman scanning, a new method for applying statistical language models to binary-switch, static-grid typing AAC interfaces, and compare it to other scanning options under a variety of conditions. We present results for 16 adults without disabilities and one 36-year-old man with locked-in syndrome who presents with complex communication needs and uses AAC scanning devices for writing. Huffman scanning with a statistical language model yielded significant typing speedups for the 16 participants without disabilities versus any of the other methods tested, including two row/column scanning methods. A similar pattern of results was found with the individual with locked-in syndrome. Interestingly, faster typing speeds were obtained with Huffman scanning using a more leisurely scan rate than relatively fast individually calibrated scan rates. Overall, the results reported here demonstrate great promise for the usability of Huffman scanning as a faster alternative to row/column scanning.
Construction of extended exponential general linear methods 524 ...
This paper introduces a new approach for constructing higher order of EEGLM which have become very popular and novel due to its enviable stability properties. This paper also shows that methods 524 is stable with its characteristics root lies in a unit circle. Numerical experiments indicate that Extended Exponential ...
A fast method for linear waves based on geometrical optics
Stolk, C.C.
2009-01-01
We develop a fast method for solving the one-dimensional wave equation based on geometrical optics. From geometrical optics (e.g., Fourier integral operator theory or WKB approximation) it is known that high-frequency waves split into forward and backward propagating parts, each propagating with the
Numerical method for solving linear Fredholm fuzzy integral equations of the second kind
Abbasbandy, S. [Department of Mathematics, Imam Khomeini International University, P.O. Box 288, Ghazvin 34194 (Iran, Islamic Republic of)]. E-mail: saeid@abbasbandy.com; Babolian, E. [Faculty of Mathematical Sciences and Computer Engineering, Teacher Training University, Tehran 15618 (Iran, Islamic Republic of); Alavi, M. [Department of Mathematics, Arak Branch, Islamic Azad University, Arak 38135 (Iran, Islamic Republic of)
2007-01-15
In this paper we use parametric form of fuzzy number and convert a linear fuzzy Fredholm integral equation to two linear system of integral equation of the second kind in crisp case. We can use one of the numerical method such as Nystrom and find the approximation solution of the system and hence obtain an approximation for fuzzy solution of the linear fuzzy Fredholm integral equations of the second kind. The proposed method is illustrated by solving some numerical examples.
The intelligence of dual simplex method to solve linear fractional fuzzy transportation problem.
Narayanamoorthy, S; Kalyani, S
2015-01-01
An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.
The Intelligence of Dual Simplex Method to Solve Linear Fractional Fuzzy Transportation Problem
S. Narayanamoorthy
2015-01-01
Full Text Available An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.
New Cogging Torque Reduction Methods for Permanent Magnet Machine
Bahrim, F. S.; Sulaiman, E.; Kumar, R.; Jusoh, L. I.
2017-08-01
Permanent magnet type motors (PMs) especially permanent magnet synchronous motor (PMSM) are expanding its limbs in industrial application system and widely used in various applications. The key features of this machine include high power and torque density, extending speed range, high efficiency, better dynamic performance and good flux-weakening capability. Nevertheless, high in cogging torque, which may cause noise and vibration, is one of the threat of the machine performance. Therefore, with the aid of 3-D finite element analysis (FEA) and simulation using JMAG Designer, this paper proposed new method for cogging torque reduction. Based on the simulation, methods of combining the skewing with radial pole pairing method and skewing with axial pole pairing method reduces the cogging torque effect up to 71.86% and 65.69% simultaneously.
Experimental validation of a linear model for data reduction in chirp-pulse microwave CT.
Miyakawa, M; Orikasa, K; Bertero, M; Boccacci, P; Conte, F; Piana, M
2002-04-01
Chirp-pulse microwave computerized tomography (CP-MCT) is an imaging modality developed at the Department of Biocybernetics, University of Niigata (Niigata, Japan), which intends to reduce the microwave-tomography problem to an X-ray-like situation. We have recently shown that data acquisition in CP-MCT can be described in terms of a linear model derived from scattering theory. In this paper, we validate this model by showing that the theoretically computed response function is in good agreement with the one obtained from a regularized multiple deconvolution of three data sets measured with the prototype of CP-MCT. Furthermore, the reliability of the model as far as image restoration in concerned, is tested in the case of space-invariant conditions by considering the reconstruction of simple on-axis cylindrical phantoms.
Slot technique - an alternative method of scatter reduction in radiography
Panzer, W.; Widenmann, L.
1983-01-01
The most common method of scatter reduction in radiography is the use of an antiscatter grid. Its disadvantage is the absorption of a certain percentage of primary radiation in the lead strips of the grid and the fact that due to the limited thickness of the lead strips their scatter absorption is also limited. A possibility for avoiding this disadvantage is offered by the so-called slot technique, ie, the successive exposure of the subject with a narrow fan beam provided by slots in rather thick lead plates. The results of a comparison between grid and slot technique regarding dose to the patient, scatter reduction, image quality and the effect of automatic exposure control are reported. (author)
METHODS OF NOISE LEVEL REDUCTION OF DRIVE IN LATHES
Janusz ROGULA
2014-06-01
Full Text Available The aim of this work is method presentation to noise level reduction of fixed headstock of the lathe. It is connected with the causes finding of non-uniform work of lathe headstock, description of recent design and its analysis. Problem of the excessive noise level concern to near 35% of the lathes have been produced. In spite of lack of noise reduction possibility there were no system solution of problem. Design optimisation weren’t done after application the electric motor with inverter. New solution of electric motor control let to reduce number of gear wheels in lathe drive system. For this drive solution there weren’t made the analysis of drive particular parts influence on the noise generation.
Linear electron accelerator body and method of its manufacture
Landa, V.; Maresova, V.; Lucek, J.; Prusa, F.
1988-01-01
The accelerator body consists of a hollow casing made of a high electric conductivity metal. The inside is partitioned with a system of resonators. The resonator body is made of one piece of the same metal as the casing or a related one (e.g., copper -coper, silver-copper, copper-copper alloy). The accelerator body is manufactured using the cathodic process on the periphery of a system of metal partitions and negative models of resonator cavities fitted to a metal pin. The pin is then removed from the system and the soluble models of the cavities are dissolved in a solvent. The advantage of the design and the method of manufacture is that the result is a compact, perfectly tight body with a perfectly lustre surface. The casing wall can be very thin, which improves accelerator performance. The claimed method can also be used in manufacturing miniature accelerators. (E.J.). 1 fig
Non-linear methods for the quantification of cyclic motion
Quintana Duque, Juan Carlos
2016-01-01
Traditional methods of human motion analysis assume that fluctuations in cycles (e.g. gait motion) and repetitions (e.g. tennis shots) arise solely from noise. However, the fluctuations may have enough information to describe the properties of motion. Recently, the fluctuations in motion have been analysed based on the concepts of variability and stability, but they are not used uniformly. On the one hand, these concepts are often mixed in the existing literature, while on the other hand, the...
Linear facility location in three dimensions - Models and solution methods
Brimberg, Jack; Juel, Henrik; Schöbel, Anita
2002-01-01
We consider the problem of locating a line or a line segment in three-dimensional space, such that the sum of distances from the facility represented by the line (segment) to a given set of points is minimized. An example is planning the drilling of a mine shaft, with access to ore deposits through...... horizontal tunnels connecting the deposits and the shaft. Various models of the problem are developed and analyzed, and efficient solution methods are given....
Arcentales, Andres; Rivera, Patricio; Caminal, Pere; Voss, Andreas; Bayes-Genis, Antonio; Giraldo, Beatriz F
2016-08-01
Changes in the left ventricle function produce alternans in the hemodynamic and electric behavior of the cardiovascular system. A total of 49 cardiomyopathy patients have been studied based on the blood pressure signal (BP), and were classified according to the left ventricular ejection fraction (LVEF) in low risk (LR: LVEF>35%, 17 patients) and high risk (HR: LVEF≤35, 32 patients) groups. We propose to characterize these patients using a linear and a nonlinear methods, based on the spectral estimation and the recurrence plot, respectively. From BP signal, we extracted each systolic time interval (STI), upward systolic slope (BPsl), and the difference between systolic and diastolic BP, defined as pulse pressure (PP). After, the best subset of parameters were obtained through the sequential feature selection (SFS) method. According to the results, the best classification was obtained using a combination of linear and nonlinear features from STI and PP parameters. For STI, the best combination was obtained considering the frequency peak and the diagonal structures of RP, with an area under the curve (AUC) of 79%. The same results were obtained when comparing PP values. Consequently, the use of combined linear and nonlinear parameters could improve the risk stratification of cardiomyopathy patients.
Fundamental solution of the problem of linear programming and method of its determination
Petrunin, S. V.
1978-01-01
The idea of a fundamental solution to a problem in linear programming is introduced. A method of determining the fundamental solution and of applying this method to the solution of a problem in linear programming is proposed. Numerical examples are cited.
Carlberg, Kevin
2010-10-28
A Petrov-Galerkin projection method is proposed for reducing the dimension of a discrete non-linear static or dynamic computational model in view of enabling its processing in real time. The right reduced-order basis is chosen to be invariant and is constructed using the Proper Orthogonal Decomposition method. The left reduced-order basis is selected to minimize the two-norm of the residual arising at each Newton iteration. Thus, this basis is iteration-dependent, enables capturing of non-linearities, and leads to the globally convergent Gauss-Newton method. To avoid the significant computational cost of assembling the reduced-order operators, the residual and action of the Jacobian on the right reduced-order basis are each approximated by the product of an invariant, large-scale matrix, and an iteration-dependent, smaller one. The invariant matrix is computed using a data compression procedure that meets proposed consistency requirements. The iteration-dependent matrix is computed to enable the least-squares reconstruction of some entries of the approximated quantities. The results obtained for the solution of a turbulent flow problem and several non-linear structural dynamics problems highlight the merit of the proposed consistency requirements. They also demonstrate the potential of this method to significantly reduce the computational cost associated with high-dimensional non-linear models while retaining their accuracy. © 2010 John Wiley & Sons, Ltd.
Carlberg, Kevin; Bou-Mosleh, Charbel; Farhat, Charbel
2010-01-01
A Petrov-Galerkin projection method is proposed for reducing the dimension of a discrete non-linear static or dynamic computational model in view of enabling its processing in real time. The right reduced-order basis is chosen to be invariant and is constructed using the Proper Orthogonal Decomposition method. The left reduced-order basis is selected to minimize the two-norm of the residual arising at each Newton iteration. Thus, this basis is iteration-dependent, enables capturing of non-linearities, and leads to the globally convergent Gauss-Newton method. To avoid the significant computational cost of assembling the reduced-order operators, the residual and action of the Jacobian on the right reduced-order basis are each approximated by the product of an invariant, large-scale matrix, and an iteration-dependent, smaller one. The invariant matrix is computed using a data compression procedure that meets proposed consistency requirements. The iteration-dependent matrix is computed to enable the least-squares reconstruction of some entries of the approximated quantities. The results obtained for the solution of a turbulent flow problem and several non-linear structural dynamics problems highlight the merit of the proposed consistency requirements. They also demonstrate the potential of this method to significantly reduce the computational cost associated with high-dimensional non-linear models while retaining their accuracy. © 2010 John Wiley & Sons, Ltd.
Love, J.C.; Demas, J.N.
1983-01-01
The Foerster equation describes excited-state decay curves involving resonance intermolecular energy transfer. A linearized solution based on the phase-plane method has been developed. The new method is quick, insensitive to the fitting region, accurate, and precise
Strong Stability Preserving Explicit Linear Multistep Methods with Variable Step Size
Hadjimichael, Yiannis; Ketcheson, David I.; Loczi, Lajos; Né meth, Adriá n
2016-01-01
Strong stability preserving (SSP) methods are designed primarily for time integration of nonlinear hyperbolic PDEs, for which the permissible SSP step size varies from one step to the next. We develop the first SSP linear multistep methods (of order
Mohammad Almousa
2013-01-01
Full Text Available The aim of this study is to present the use of a semi analytical method called the optimal homotopy asymptotic method (OHAM for solving the linear Fredholm integral equations of the first kind. Three examples are discussed to show the ability of the method to solve the linear Fredholm integral equations of the first kind. The results indicated that the method is very effective and simple.
Mejlbro, Leif
1997-01-01
An alternative formula for the solution of linear differential equations of order n is suggested. When applicable, the suggested method requires fewer and simpler computations than the well-known method using Wronskians.......An alternative formula for the solution of linear differential equations of order n is suggested. When applicable, the suggested method requires fewer and simpler computations than the well-known method using Wronskians....
Liu Linqin
1991-01-01
The separation-combination method a new kind of analysis method of linear structures in remote sensing image interpretation is introduced taking northwestern Fujian as the example, its practical application is examined. The practice shows that application results not only reflect intensities of linear structures in overall directions at different locations, but also contribute to the zonation of linear structures and display their space distribution laws. Based on analyses of linear structures, it can provide more information concerning remote sensing on studies of regional mineralization laws and the guide to ore-finding combining with mineralization
Greenhouse effect gases: reduction challenges and accounting methods
Dumergues, Laurent
2012-01-01
In this article, the author first proposes an overview of strategic challenges related to the reduction of greenhouse gas emissions. He indicates and discusses the various economic consequences of climate change. These consequences can be environmental (issues ranging from a loss of biodiversity to agriculture), social (from climate refugees to tourism), and economic (from climate disasters to insurance). He focuses on the issue of energy (oil at the base of our economy, carbon contents) and discusses competition issues (an always more demanding regulation, and unavoidable practices). In the second part, he proposes an overview of methods of accounting of greenhouse effect gases, and discusses how to perform an emission inventory
A systematic way for the cost reduction of density fitting methods
Kállay, Mihály
2014-01-01
We present a simple approach for the reduction of the size of auxiliary basis sets used in methods exploiting the density fitting (resolution of identity) approximation for electron repulsion integrals. Starting out of the singular value decomposition of three-center two-electron integrals, new auxiliary functions are constructed as linear combinations of the original fitting functions. The new functions, which we term natural auxiliary functions (NAFs), are analogous to the natural orbitals widely used for the cost reduction of correlation methods. The use of the NAF basis enables the systematic truncation of the fitting basis, and thereby potentially the reduction of the computational expenses of the methods, though the scaling with the system size is not altered. The performance of the new approach has been tested for several quantum chemical methods. It is demonstrated that the most pronounced gain in computational efficiency can be expected for iterative models which scale quadratically with the size of the fitting basis set, such as the direct random phase approximation. The approach also has the promise of accelerating local correlation methods, for which the processing of three-center Coulomb integrals is a bottleneck
Kandel, Tanka P; Lærke, Poul Erik; Elsgaard, Lars
2016-01-01
One of the shortcomings of closed chamber methods for soil respiration (SR) measurements is the decreased CO2 diffusion rate from soil to chamber headspace that may occur due to increased chamber CO2 concentrations. This feedback on diffusion rate may lead to underestimation of pre-deployment flu......One of the shortcomings of closed chamber methods for soil respiration (SR) measurements is the decreased CO2 diffusion rate from soil to chamber headspace that may occur due to increased chamber CO2 concentrations. This feedback on diffusion rate may lead to underestimation of pre...... was placed on fixed collars, and CO2 concentration in the chamber headspace were recorded at 1-s intervals for 45 min. Fluxes were measured in different soil types (sandy, sandy loam and organic soils), and for various manipulations (tillage, rain and drought) and soil conditions (temperature and moisture......) to obtain a range of fluxes with different shapes of flux curves. The linear method provided more stable flux results during short enclosure times (few min) but underestimated initial fluxes by 15–300% after 45 min deployment time. Non-linear models reduced the underestimation as average underestimation...
Conjugate gradient type methods for linear systems with complex symmetric coefficient matrices
Freund, Roland
1989-01-01
We consider conjugate gradient type methods for the solution of large sparse linear system Ax equals b with complex symmetric coefficient matrices A equals A(T). Such linear systems arise in important applications, such as the numerical solution of the complex Helmholtz equation. Furthermore, most complex non-Hermitian linear systems which occur in practice are actually complex symmetric. We investigate conjugate gradient type iterations which are based on a variant of the nonsymmetric Lanczos algorithm for complex symmetric matrices. We propose a new approach with iterates defined by a quasi-minimal residual property. The resulting algorithm presents several advantages over the standard biconjugate gradient method. We also include some remarks on the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.
Solution of systems of linear algebraic equations by the method of summation of divergent series
Kirichenko, G.A.; Korovin, Ya.S.; Khisamutdinov, M.V.; Shmojlov, V.I.
2015-01-01
A method for solving systems of linear algebraic equations has been proposed on the basis on the summation of the corresponding continued fractions. The proposed algorithm for solving systems of linear algebraic equations is classified as direct algorithms providing an exact solution in a finite number of operations. Examples of solving systems of linear algebraic equations have been presented and the effectiveness of the algorithm has been estimated [ru
Yin haihua; Yao Zhigang
2014-01-01
This article describes the environmental impact assessment methods of the radiation generated by the runing. medical linear accelerator. The material and thickness of shielding wall and protective doors of the linear accelerator were already knew, therefore we can evaluate the radiation by the runing. medical linear accelerator whether or not in the normal range of national standard by calculating the annual effective radiation dose of the surrounding personnel suffered. (authors)
Chosen interval methods for solving linear interval systems with special type of matrix
Szyszka, Barbara
2013-10-01
The paper is devoted to chosen direct interval methods for solving linear interval systems with special type of matrix. This kind of matrix: band matrix with a parameter, from finite difference problem is obtained. Such linear systems occur while solving one dimensional wave equation (Partial Differential Equations of hyperbolic type) by using the central difference interval method of the second order. Interval methods are constructed so as the errors of method are enclosed in obtained results, therefore presented linear interval systems contain elements that determining the errors of difference method. The chosen direct algorithms have been applied for solving linear systems because they have no errors of method. All calculations were performed in floating-point interval arithmetic.
A Linear Birefringence Measurement Method for an Optical Fiber Current Sensor.
Xu, Shaoyi; Shao, Haiming; Li, Chuansheng; Xing, Fangfang; Wang, Yuqiao; Li, Wei
2017-07-03
In this work, a linear birefringence measurement method is proposed for an optical fiber current sensor (OFCS). First, the optical configuration of the measurement system is presented. Then, the elimination method of the effect of the azimuth angles between the sensing fiber and the two polarizers is demonstrated. Moreover, the relationship of the linear birefringence, the Faraday rotation angle and the final output is determined. On these bases, the multi-valued problem on the linear birefringence is simulated and its solution is illustrated when the linear birefringence is unknown. Finally, the experiments are conducted to prove the feasibility of the proposed method. When the numbers of turns of the sensing fiber in the OFCS are about 15, 19, 23, 27, 31, 35, and 39, the measured linear birefringence obtained by the proposed method are about 1.3577, 1.8425, 2.0983, 2.5914, 2.7891, 3.2003 and 3.5198 rad. Two typical methods provide the references for the proposed method. The proposed method is proven to be suitable for the linear birefringence measurement in the full range without the limitation that the linear birefringence must be smaller than π/2.
Refat Aljumily
2015-09-01
Full Text Available A few literary scholars have long claimed that Shakespeare did not write some of his best plays (history plays and tragedies and proposed at one time or another various suspect authorship candidates. Most modern-day scholars of Shakespeare have rejected this claim, arguing that strong evidence that Shakespeare wrote the plays and poems being his name appears on them as the author. This has caused and led to an ongoing scholarly academic debate for quite some long time. Stylometry is a fast-growing field often used to attribute authorship to anonymous or disputed texts. Stylometric attempts to resolve this literary puzzle have raised interesting questions over the past few years. The following paper contributes to “the Shakespeare authorship question” by using a mathematically-based methodology to examine the hypothesis that Shakespeare wrote all the disputed plays traditionally attributed to him. More specifically, the mathematically based methodology used here is based on Mean Proximity, as a linear hierarchical clustering method, and on Principal Components Analysis, as a non-hierarchical linear clustering method. It is also based, for the first time in the domain, on Self-Organizing Map U-Matrix and Voronoi Map, as non-linear clustering methods to cover the possibility that our data contains significant non-linearities. Vector Space Model (VSM is used to convert texts into vectors in a high dimensional space. The aim of which is to compare the degrees of similarity within and between limited samples of text (the disputed plays. The various works and plays assumed to have been written by Shakespeare and possible authors notably, Sir Francis Bacon, Christopher Marlowe, John Fletcher, and Thomas Kyd, where “similarity” is defined in terms of correlation/distance coefficient measure based on the frequency of usage profiles of function words, word bi-grams, and character triple-grams. The claim that Shakespeare authored all the disputed
Method of simulating dose reduction for digital radiographic systems
Baath, M.; Haakansson, M.; Tingberg, A.; Maansson, L. G.
2005-01-01
The optimisation of image quality vs. radiation dose is an important task in medical imaging. To obtain maximum validity of the optimisation, it must be based on clinical images. Images at different dose levels can then either be obtained by collecting patient images at the different dose levels sought to investigate - including additional exposures and permission from an ethical committee - or by manipulating images to simulate different dose levels. The aim of the present work was to develop a method of simulating dose reduction for digital radiographic systems. The method uses information about the detective quantum efficiency and noise power spectrum at the original and simulated dose levels to create an image containing filtered noise. When added to the original image this results in an image with noise which, in terms of frequency content, agrees with the noise present in an image collected at the simulated dose level. To increase the validity, the method takes local dose variations in the original image into account. The method was tested on a computed radiography system and was shown to produce images with noise behaviour similar to that of images actually collected at the simulated dose levels. The method can, therefore, be used to modify an image collected at one dose level so that it simulates an image of the same object collected at any lower dose level. (authors)
Tonogi, Morio; Yamane, Genyuki; Aoyagi, Yutaka; Hasegawa, Azusa; Mizoe, Junetsu; Tsujii, Hirohiko
2004-01-01
Reduction methods for irradiation on oral mucosa examined concerning in acute phase of the carbon ion radiotherapy for head and neck malignancies. We enforced a mechanical teeth and gingival cleaning as an Oral hearth care and gargled a polaprezinc with sodium alginate, and azulene- lidocaine with glycerin sodium as a oral linces before radiation. The response of the mucosal failure was reduced compare with no care group. In this Result, we considered that oral hearth care for prevention of infection, and mucosa protection by the drug was important factor. (author)
Libraries for spectrum identification: Method of normalized coordinates versus linear correlation
Ferrero, A.; Lucena, P.; Herrera, R.G.; Dona, A.; Fernandez-Reyes, R.; Laserna, J.J.
2008-01-01
In this work it is proposed that an easy solution based directly on linear algebra in order to obtain the relation between a spectrum and a spectrum base. This solution is based on the algebraic determination of an unknown spectrum coordinates with respect to a spectral library base. The identification capacity comparison between this algebraic method and the linear correlation method has been shown using experimental spectra of polymers. Unlike the linear correlation (where the presence of impurities may decrease the discrimination capacity), this method allows to detect quantitatively the existence of a mixture of several substances in a sample and, consequently, to beer in mind impurities for improving the identification
Infeasible Interior-Point Methods for Linear Optimization Based on Large Neighborhood
Asadi, A.R.; Roos, C.
2015-01-01
In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author.
Schmitt, M. A.; And Others
1994-01-01
Compares traditional manure application planning techniques calculated to meet agronomic nutrient needs on a field-by-field basis with plans developed using computer-assisted linear programming optimization methods. Linear programming provided the most economical and environmentally sound manure application strategy. (Contains 15 references.) (MDH)
Camporesi, Roberto
2011-01-01
We present an approach to the impulsive response method for solving linear constant-coefficient ordinary differential equations based on the factorization of the differential operator. The approach is elementary, we only assume a basic knowledge of calculus and linear algebra. In particular, we avoid the use of distribution theory, as well as of…
An Evaluation of Five Linear Equating Methods for the NEAT Design
Mroch, Andrew A.; Suh, Youngsuk; Kane, Michael T.; Ripkey, Douglas R.
2009-01-01
This study uses the results of two previous papers (Kane, Mroch, Suh, & Ripkey, this issue; Suh, Mroch, Kane, & Ripkey, this issue) and the literature on linear equating to evaluate five linear equating methods along several dimensions, including the plausibility of their assumptions and their levels of bias and root mean squared difference…
Genomic prediction based on data from three layer lines: a comparison between linear methods
Calus, M.P.L.; Huang, H.; Vereijken, J.; Visscher, J.; Napel, ten J.; Windig, J.J.
2014-01-01
Background The prediction accuracy of several linear genomic prediction models, which have previously been used for within-line genomic prediction, was evaluated for multi-line genomic prediction. Methods Compared to a conventional BLUP (best linear unbiased prediction) model using pedigree data, we
An introduction to fuzzy linear programming problems theory, methods and applications
Kaur, Jagdeep
2016-01-01
The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.
Improvement of linear reactivity methods and application to long range fuel management
Woehlke, R.A.; Quan, B.L.
1982-01-01
The original development of the linear reactivity theory assumes flat burnup, batch by batch. The validity of this assumption is explored using multicycle burnup data generated with a detailed 3-D SIMULATE model. The results show that the linear reactivity method can be improved by correcting for batchwise power sharing. The application of linear reactivity to long range fuel management is demonstrated in several examples. Correcting for batchwise power sharing improves the accuracy of the analysis. However, with regard to the sensitivity of fuel cost to changes in various parameters, the corrected and uncorrected linear reactivity theories give remarkably similar results
Reduction of aflatoxin in rice by different cooking methods.
Sani, Ali Mohamadi; Azizi, Eisa Gholampour; Salehi, Esmaeel Ataye; Rahimi, Khadije
2014-07-01
Rice (Oryza sativa Linn) is one of the basic diets in the north of Iran. The aim of present study was to detect total aflatoxin (AFT) in domestic and imported rice in Amol (in the north of Iran) and to evaluate the effect of different cooking methods on the levels of the toxin. For this purpose, 42 rice samples were collected from retail stores. The raw samples were analysed by enzyme-linked immunosorbent assay (ELISA) technique for toxin assessment and then submitted to two different cooking methods including traditional local method and in rice cooker. After treatment, AFT was determined. Results show that the average concentration of AFT in domestic and imported samples was 1.08 ± 0.02 and 1.89 ± 0.87 ppb, respectively, which is lower than national and European Union standards. The highest AFT reduction (24.8%) was observed when rice samples were cooked by rice cooker but the difference with local method was not statistically significant (p > 0.05). © The Author(s) 2012.
On Extended Exponential General Linear Methods PSQ with S>Q ...
This paper is concerned with the construction and Numerical Analysis of Extended Exponential General Linear Methods. These methods, in contrast to other methods in literatures, consider methods with the step greater than the stage order (S>Q).Numerical experiments in this study, indicate that Extended Exponential ...
Electric field control methods for foil coils in high-voltage linear actuators
Beek, van T.A.; Jansen, J.W.; Lomonova, E.A.
2015-01-01
This paper describes multiple electric field control methods for foil coils in high-voltage coreless linear actuators. The field control methods are evaluated using 2-D and 3-D boundary element methods. A comparison is presented between the field control methods and their ability to mitigate
Anderson, Carl A; McRae, Allan F; Visscher, Peter M
2006-07-01
Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.
Comparison of boundedness and monotonicity properties of one-leg and linear multistep methods
Mozartova, A.; Savostianov, I.; Hundsdorfer, W.
2015-01-01
© 2014 Elsevier B.V. All rights reserved. One-leg multistep methods have some advantage over linear multistep methods with respect to storage of the past results. In this paper boundedness and monotonicity properties with arbitrary (semi-)norms or convex functionals are analyzed for such multistep methods. The maximal stepsize coefficient for boundedness and monotonicity of a one-leg method is the same as for the associated linear multistep method when arbitrary starting values are considered. It will be shown, however, that combinations of one-leg methods and Runge-Kutta starting procedures may give very different stepsize coefficients for monotonicity than the linear multistep methods with the same starting procedures. Detailed results are presented for explicit two-step methods.
Comparison of boundedness and monotonicity properties of one-leg and linear multistep methods
Mozartova, A.
2015-05-01
© 2014 Elsevier B.V. All rights reserved. One-leg multistep methods have some advantage over linear multistep methods with respect to storage of the past results. In this paper boundedness and monotonicity properties with arbitrary (semi-)norms or convex functionals are analyzed for such multistep methods. The maximal stepsize coefficient for boundedness and monotonicity of a one-leg method is the same as for the associated linear multistep method when arbitrary starting values are considered. It will be shown, however, that combinations of one-leg methods and Runge-Kutta starting procedures may give very different stepsize coefficients for monotonicity than the linear multistep methods with the same starting procedures. Detailed results are presented for explicit two-step methods.
Wispy Prosthesis: A Novel Method in Denture Weight Reduction.
Anne, Gopinadh; Budeti, Sreedevi; Anche, Sampath Kumar; Zakkula, Srujana; Atla, Jyothi; Jyothula, Ravi Rakesh Dev; Appana, Krishna Chaitanya; Peddinti, Vijaya Kumar
2016-04-01
Stability and retention of the denture becomes at stake with the increase in weight of the denture prosthesis. As a consequence, different materials and methods have been introduced to overcome these issues but denture weight reduction still remains to be a cumbersome and strenuous procedure. To introduce a novel technique for the fabrication of denture prosthesis where in the weight of the denture will not affect the retention and stability of the denture. Four groups with a sample size of 10 each, were included where in one group was control and other three were study groups. The control group samples were made completely solid and the study group samples were packed with materials like bean balls, cellulose balls and polyacrylic fibers. The weight of all the samples of each study group was measured and compared with the control group. The observations were analyzed statistically by paired t-test. It was observed that the bean balls group produced a weight reduction of 31.3%, cellulose balls group 27.4% and polyacrylic fibers group 24.5% when compared to that of the control group. This novel technique will eliminate the problems that were associated in creating hollowness and at the same time will reduce the weight of the prosthesis and among all the study groups, bean balls group were found to reduce maximum weight of the prosthesis.
Ingel, R
1999-01-01
... (which require derivative information) interpolation functions as well as standard Lagrangian functions, which can be linear, quadratic or cubic, have been used to construct the interpolation windows...
Non-linear model reduction and control of molten carbonate fuel cell systems with internal reforming
Sheng, Min
2007-10-12
Currently, the process design of fuel cells and the development of control strategies is mainly based on heuristic methods. Fuel cell models are often too complex for control purposes, or they are developed for a specific type of fuel cell and valid only in a small range of operation conditions. The application of fuel cell models to controller design is still limited. Furthermore, suitable and simple-to-implement design strategies for fuel cell control remain an open area. There is thus a motivation for simplifying dynamic models for process control applications and for designing suitable control strategies for fuel cells. This is the main objective of this work. As an application example, the 250 kW industrial molten carbonate fuel cell (MCFC) system HotModule by MTU CFC Solutions, Germany is considered. A detailed dynamic two-dimensional spatially distributed cross-flow model of a MCFC from literature is taken as a starting point for the investigation. In Chapter 2, two simplified model versions are derived by incorporating additional physical assumptions. One of the simplified models is extended to a three-dimensional stack model to deal with physical and chemical phenomena in the stack. Simulations of the stack model are performed in Chapter 3 in order to calculate the mass and temperature distributions in the direction perpendicular to the electrode area. The other simplified model forms the basis for a low order reduced model that is derived in Chapter 4. The reduced-order model is constructed by application of the Karhunen-Loeve Galerkin method. The spatial temperature, concentration and potential profiles are approximated by a set of orthogonal time independent spatial basis functions. Problem specific basis functions are generated numerically from simulation data of the detailed reference model. The advantage of this approach is that a small number of basis functions suffices in order to approximate the solution of the detailed model very well. The
Møldrup, Per; Chamindu, T. K. K. Deepagoda; Hamamoto, S.
2013-01-01
The soil-gas diffusion is a primary driver of transport, reactions, emissions, and uptake of vadose zone gases, including oxygen, greenhouse gases, fumigants, and spilled volatile organics. The soil-gas diffusion coefficient, Dp, depends not only on soil moisture content, texture, and compaction...... but also on the local-scale variability of these. Different predictive models have been developed to estimate Dp in intact and repacked soil, but clear guidelines for model choice at a given soil state are lacking. In this study, the water-induced linear reduction (WLR) model for repacked soil is made...... air) in repacked soils containing between 0 and 54% clay. With Cm = 2.1, the SWLR model on average gave excellent predictions for 290 intact soils, performing well across soil depths, textures, and compactions (dry bulk densities). The SWLR model generally outperformed similar, simple Dp/Do models...
Saitou, Y.; Yonesu, A.; Shinohara, S.; Ignatenko, M. V.; Kasuya, N.; Kawaguchi, M.; Terasaka, K.; Nishijima, T.; Nagashima, Y.; Kawai, Y.; Yagi, M.; Itoh, S.-I.; Azumi, M.; Itoh, K.
2007-01-01
The importance of reducing the neutral density to reach strong drift wave turbulence is clarified from the results of the extended magnetohydrodynamics and Monte Carlo simulations in a linear magnetized plasma. An upper bound of the neutral density relating to the ion-neutral collision frequency for the excitation of drift wave instability is shown, and the necessary flow velocity to excite this instability is also estimated from the neutral distributions. Measurements of the Mach number and the electron density distributions using Mach probe in the large mirror device (LMD) of Kyushu University [S. Shinohara et al., Plasma Phys. Control. Fusion 37, 1015 (1995)] are reported as well. The obtained results show a controllability of the neutral density and provide the basis for neutral density reduction and a possibility to excite strong drift wave turbulence in the LMD
Mathematical Methods in Wave Propagation: Part 2--Non-Linear Wave Front Analysis
Jeffrey, Alan
1971-01-01
The paper presents applications and methods of analysis for non-linear hyperbolic partial differential equations. The paper is concluded by an account of wave front analysis as applied to the piston problem of gas dynamics. (JG)
A method for computing the stationary points of a function subject to linear equality constraints
Uko, U.L.
1989-09-01
We give a new method for the numerical calculation of stationary points of a function when it is subject to equality constraints. An application to the solution of linear equations is given, together with a numerical example. (author). 5 refs
Wang Wansheng; Li Shoufu; Wang Wenqiang
2009-01-01
In this paper, we show that under identical conditions which guarantee the contractivity of the theoretical solutions of general nonlinear NDDEs, the numerical solutions obtained by a class of linear multistep methods are also contractive.
Watabe, Hiroshi; Hatazawa, Jun; Ishiwata, Kiichi; Ido, Tatsuo; Itoh, Masatoshi; Iwata, Ren; Nakamura, Takashi; Takahashi, Toshihiro; Hatano, Kentaro
1995-01-01
The authors proposed a new method (Linearized method) to analyze neuroleptic ligand-receptor specific binding in a human brain using positron emission tomography (PET). They derived the linear equation to solve four rate constants, k 3 , k 4 , k 5 , k 6 from PET data. This method does not demand radioactivity curve in plasma as an input function to brain, and can do fast calculations in order to determine rate constants. They also tested Nonlinearized method including nonlinear equations which is conventional analysis using plasma radioactivity corrected for ligand metabolites as an input function. The authors applied these methods to evaluate dopamine D 2 receptor specific binding of [ 11 C] YM-09151-2. The value of B max /K d = k 3 k 4 obtained by Linearized method was 5.72 ± 3.1 which was consistent with the value of 5.78 ± 3.4 obtained by Nonlinearized method
Linear, Transﬁnite and Weighted Method for Interpolation from Grid Lines Applied to OCT Images
Lindberg, Anne-Sofie Wessel; Jørgensen, Thomas Martini; Dahl, Vedrana Andersen
2018-01-01
of a square grid, but are unknown inside each square. To view these values as an image, intensities need to be interpolated at regularly spaced pixel positions. In this paper we evaluate three methods for interpolation from grid lines: linear, transfinite and weighted. The linear method does not preserve...... and the stability of the linear method further away. An important parameter influencing the performance of the interpolation methods is the upsampling rate. We perform an extensive evaluation of the three interpolation methods across a range of upsampling rates. Our statistical analysis shows significant difference...... in the performance of the three methods. We find that the transfinite interpolation works well for small upsampling rates and the proposed weighted interpolation method performs very well for all upsampling rates typically used in practice. On the basis of these findings we propose an approach for combining two OCT...
Method for simulating dose reduction in digital mammography using the Anscombe transformation.
Borges, Lucas R; Oliveira, Helder C R de; Nunes, Polyana F; Bakic, Predrag R; Maidment, Andrew D A; Vieira, Marcelo A C
2016-06-01
This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose. The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the detective quantum efficiency. The scaling process takes into account the linearity of the system and the offset of the detector elements. The inserted noise is obtained by acquiring images of a flat-field phantom at the standard radiation dose and at the simulated dose. Using the Anscombe transformation, a relationship is created between the calculated noise mask and the scaled image, resulting in a clinical mammogram with the same noise and gray level characteristics as an image acquired at the lower-radiation dose. The performance of the proposed algorithm was validated using real images acquired with an anthropomorphic breast phantom at four different doses, with five exposures for each dose and 256 nonoverlapping ROIs extracted from each image and with uniform images. The authors simulated lower-dose images and compared these with the real images. The authors evaluated the similarity between the normalized noise power spectrum (NNPS) and power spectrum (PS) of simulated images and real images acquired with the same dose. The maximum relative error was less than 2.5% for every ROI. The added noise was also evaluated by measuring the local variance in the real and simulated images. The relative average error for the local variance was smaller than 1%. A new method is proposed for simulating dose reduction in clinical mammograms. In this method, the dependency between image noise and image signal is addressed using a novel application of the Anscombe transformation. NNPS, PS, and local noise
Elimination Voltammetry with Linear Scan as a New Detection Method for DNA Sensors
Rene Kizek
2005-11-01
Full Text Available The paper describes successful coupling of adsorptive transfer stripping (AdTS andelimination voltammetry with linear scan (EVLS for the resolution of reduction signals of cytosine (Cand adenine (A residues in hetero-oligodeoxynucleotides (ODNs. Short ODNs (9-mers and 20-merswere adsorbed from a small volume on a hanging mercury drop electrode (HMDE. After washing ofthe ODN-modified electrode by water and its transferring to an electrochemical cell, voltammetric curves were measured. The AdTS EVLS was able to determine of C/A ratio of ODNs through theelimination function conserving the diffusion current component and eliminating kinetic and chargingcurrent components. This function, which provides the elimination signal in a peak-counterpeak form,increased the current sensitivity for A and C resolution, and for the recognition of bases sequences inODN chains. Optimal conditions of elimination experiments such as pH, time of adsorption, and scanrate were found. The combination of EVLS with AdTS procedure can be considered as a newdetection method in a DNA sensor.
Dimensionality Reduction Methods: Comparative Analysis of methods PCA, PPCA and KPCA
Jorge Arroyo-Hernández
2016-01-01
Full Text Available The dimensionality reduction methods are algorithms mapping the set of data in subspaces derived from the original space, of fewer dimensions, that allow a description of the data at a lower cost. Due to their importance, they are widely used in processes associated with learning machine. This article presents a comparative analysis of PCA, PPCA and KPCA dimensionality reduction methods. A reconstruction experiment of worm-shape data was performed through structures of landmarks located in the body contour, with methods having different number of main components. The results showed that all methods can be seen as alternative processes. Nevertheless, thanks to the potential for analysis in the features space and the method for calculation of its preimage presented, KPCA offers a better method for recognition process and pattern extraction
Ai-Min Yang
2014-01-01
Full Text Available The local fractional Laplace variational iteration method was applied to solve the linear local fractional partial differential equations. The local fractional Laplace variational iteration method is coupled by the local fractional variational iteration method and Laplace transform. The nondifferentiable approximate solutions are obtained and their graphs are also shown.
Comparison results on preconditioned SOR-type iterative method for Z-matrices linear systems
Wang, Xue-Zhong; Huang, Ting-Zhu; Fu, Ying-Ding
2007-09-01
In this paper, we present some comparison theorems on preconditioned iterative method for solving Z-matrices linear systems, Comparison results show that the rate of convergence of the Gauss-Seidel-type method is faster than the rate of convergence of the SOR-type iterative method.
A Fifth Order Hybrid Linear Multistep method For the Direct Solution ...
A linear multistep hybrid method (LMHM)with continuous coefficients isconsidered and directly applied to solve third order initial and boundary value problems (IBVPs). The continuous method is used to obtain Multiple Finite Difference Methods (MFDMs) (each of order 5) which are combined as simultaneous numerical ...
Dose rate reduction method for NMCA applied BWR plants
Nagase, Makoto; Aizawa, Motohiro; Ito, Tsuyoshi; Hosokawa, Hideyuki; Varela, Juan; Caine, Thomas
2012-09-01
BRAC (BWR Radiation Assessment and Control) dose rate is used as an indicator of the incorporation of activated corrosion by products into BWR recirculation piping, which is known to be a significant contributor to dose rate received by workers during refueling outages. In order to reduce radiation exposure of the workers during the outage, it is desirable to keep BRAC dose rates as low as possible. After HWC was adopted to reduce IGSCC, a BRAC dose rate increase was observed in many plants. As a countermeasure to these rapid dose rate increases under HWC conditions, Zn injection was widely adopted in United States and Europe resulting in a reduction of BRAC dose rates. However, BRAC dose rates in several plants remain high, prompting the industry to continue to investigate methods to achieve further reductions. In recent years a large portion of the BWR fleet has adopted NMCA (NobleChem TM ) to enhance the hydrogen injection effect to suppress SCC. After NMCA, especially OLNC (On-Line NobleChem TM ), BRAC dose rates were observed to decrease. In some OLNC applied BWR plants this reduction was observed year after year to reach a new reduced equilibrium level. This dose rate reduction trends suggest the potential dose reduction might be obtained by the combination of Pt and Zn injection. So, laboratory experiments and in-plant tests were carried out to evaluate the effect of Pt and Zn on Co-60 deposition behaviour. Firstly, laboratory experiments were conducted to study the effect of noble metal deposition on Co deposition on stainless steel surfaces. Polished type 316 stainless steel coupons were prepared and some of them were OLNC treated in the test loop before the Co deposition test. Water chemistry conditions to simulate HWC were as follows: Dissolved oxygen, hydrogen and hydrogen peroxide were below 5 ppb, 100 ppb and 0 ppb (no addition), respectively. Zn was injected to target a concentration of 5 ppb. The test was conducted up to 1500 hours at 553 K. Test
Krylov Subspace Methods for Complex Non-Hermitian Linear Systems. Thesis
Freund, Roland W.
1991-01-01
We consider Krylov subspace methods for the solution of large sparse linear systems Ax = b with complex non-Hermitian coefficient matrices. Such linear systems arise in important applications, such as inverse scattering, numerical solution of time-dependent Schrodinger equations, underwater acoustics, eddy current computations, numerical computations in quantum chromodynamics, and numerical conformal mapping. Typically, the resulting coefficient matrices A exhibit special structures, such as complex symmetry, or they are shifted Hermitian matrices. In this paper, we first describe a Krylov subspace approach with iterates defined by a quasi-minimal residual property, the QMR method, for solving general complex non-Hermitian linear systems. Then, we study special Krylov subspace methods designed for the two families of complex symmetric respectively shifted Hermitian linear systems. We also include some results concerning the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.
Development of pre-critical excore detector linear subchannel calibration method
Choi, Yoo Sun; Goo, Bon Seung; Cha, Kyun Ho; Lee, Chang Seop; Kim, Yong Hee; Ahn, Chul Soo; Kim, Man Soo
2001-01-01
The improved pre-critical excore detector linear subchannel calibration method has been developed to improve the applicability of pre-critical calibration method. The existing calibration method does not always guarantee the accuracy of pre-critical calibration because the calibration results of the previous cycle are not reflected into the current cycle calibration. The developed method has a desirable feature that calibration error would not be propagated in the following cycles since the calibration data determined in previous cycle is incorporated in the current cycle calibration. The pre-critical excore detector linear calibration is tested for YGN unit 3 and UCN unit 3 to evaluate its characteristics and accuracy
Guo, Sangang
2017-09-01
There are two stages in solving security-constrained unit commitment problems (SCUC) within Lagrangian framework: one is to obtain feasible units’ states (UC), the other is power economic dispatch (ED) for each unit. The accurate solution of ED is more important for enhancing the efficiency of the solution to SCUC for the fixed feasible units’ statues. Two novel methods named after Convex Combinatorial Coefficient Method and Power Increment Method respectively based on linear programming problem for solving ED are proposed by the piecewise linear approximation to the nonlinear convex fuel cost functions. Numerical testing results show that the methods are effective and efficient.
Multigrid for the Galerkin least squares method in linear elasticity: The pure displacement problem
Yoo, Jaechil [Univ. of Wisconsin, Madison, WI (United States)
1996-12-31
Franca and Stenberg developed several Galerkin least squares methods for the solution of the problem of linear elasticity. That work concerned itself only with the error estimates of the method. It did not address the related problem of finding effective methods for the solution of the associated linear systems. In this work, we prove the convergence of a multigrid (W-cycle) method. This multigrid is robust in that the convergence is uniform as the parameter, v, goes to 1/2 Computational experiments are included.
Camporesi, Roberto
2016-01-01
This book presents a method for solving linear ordinary differential equations based on the factorization of the differential operator. The approach for the case of constant coefficients is elementary, and only requires a basic knowledge of calculus and linear algebra. In particular, the book avoids the use of distribution theory, as well as the other more advanced approaches: Laplace transform, linear systems, the general theory of linear equations with variable coefficients and variation of parameters. The case of variable coefficients is addressed using Mammana’s result for the factorization of a real linear ordinary differential operator into a product of first-order (complex) factors, as well as a recent generalization of this result to the case of complex-valued coefficients.
A sparse grid based method for generative dimensionality reduction of high-dimensional data
Bohn, Bastian; Garcke, Jochen; Griebel, Michael
2016-03-01
Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.
An explicit method in non-linear soil-structure interaction
Kunar, R.R.
1981-01-01
The explicit method of analysis in the time domain is ideally suited for the solution of transient dynamic non-linear problems. Though the method is not new, its application to seismic soil-structure interaction is relatively new and deserving of public discussion. This paper describes the principles of the explicit approach in soil-structure interaction and it presents a simple algorithm that can be used in the development of explicit computer codes. The paper also discusses some of the practical considerations like non-reflecting boundaries and time steps. The practicality of the method is demonstrated using a computer code, PRESS, which is used to compare the treatment of strain-dependent properties using average strain levels over the whole time history (the equivalent linear method) and using the actual strain levels at every time step to modify the soil properties (non-linear method). (orig.)
Uniform irradiation using rotational-linear scanning method for narrow synchrotron radiation beam
Nariyama, N.; Ohnishi, S.; Odano, N.
2004-01-01
At SPring-8, photon intensity monitors for synchrotron radiation have been developed. Using these monitors, the responses of radiation detectors and dosimeters to monoenergetic photons can be measured. In most cases, uniform irradiation to the sample is necessary. Here, two scanning methods are proposed. One is an XZ-linear scanning method, which moves the sample simultaneously in both the X and Z direction, that is, in zigzag fashion. The other is a rotational-linear scanning method, which rotates the sample moving in the X direction. To investigate the validity of the two methods, thermoluminescent dosimeters were irradiated with a broad synchrotron-radiation beam, and the readings from the two methods were compared with that of the dosimeters fixed in the beam. The results for both scanning methods virtually agreed with that of the fixed method. The advantages of the rotational-linear scanning method are that low- and medium-dose irradiation is possible, uniformity is excellent and the load to the scanning equipment is light: hence, this method is superior to the XZ-linear scanning method for most applications. (author)
Method of local pointed function reduction of original shape in Fourier transformation
Dosch, H.; Slavyanov, S.Yu.
2002-01-01
The method for analytical reduction of the original shape in the one-dimensional Fourier transformation by the fourier image modulus is proposed. The basic concept of the method consists in the presentation of the model shape in the form of the local peak functions sum. The eigenfunctions, generated by the linear differential equations with the polynomial coefficients, are selected as the latter ones. This provides for the possibility of managing the Fourier transformation without numerical integration. This reduces the reverse task to the nonlinear regression with a small number of the evaluated parameters and to the numerical or asymptotic study on the model peak functions - the eigenfunctions of the differential tasks and their fourier images [ru
Ross S Williamson
2015-04-01
Full Text Available Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID, uses an information-theoretic quantity known as "single-spike information" to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex.
Numerical Methods for Solution of the Extended Linear Quadratic Control Problem
Jørgensen, John Bagterp; Frison, Gianluca; Gade-Nielsen, Nicolai Fog
2012-01-01
In this paper we present the extended linear quadratic control problem, its efficient solution, and a discussion of how it arises in the numerical solution of nonlinear model predictive control problems. The extended linear quadratic control problem is the optimal control problem corresponding...... to the Karush-Kuhn-Tucker system that constitute the majority of computational work in constrained nonlinear and linear model predictive control problems solved by efficient MPC-tailored interior-point and active-set algorithms. We state various methods of solving the extended linear quadratic control problem...... and discuss instances in which it arises. The methods discussed in the paper have been implemented in efficient C code for both CPUs and GPUs for a number of test examples....
Lu Li; Yang Yiren
2009-01-01
The responses and limit cycle flutter of a plate-type structure with cubic stiffness in viscous flow were studied. The continuous system was dispersed by utilizing Galerkin Method. The equivalent linearization concept was performed to predict the ranges of limit cycle flutter velocities. The coupled map of flutter amplitude-equivalent linear stiffness-critical velocity was used to analyze the stability of limit cycle flutter. The theoretical results agree well with the results of numerical integration, which indicates that the equivalent linearization concept is available to the analysis of limit cycle flutter of plate-type structure. (authors)
The JCMT Transient Survey: Data Reduction and Calibration Methods
Mairs, Steve; Lane, James [Department of Physics and Astronomy, University of Victoria, Victoria, BC, V8P 1A1 (Canada); Johnstone, Doug; Kirk, Helen [NRC Herzberg Astronomy and Astrophysics, 5071 West Saanich Road, Victoria, BC, V9E 2E7 (Canada); Lacaille, Kevin; Chapman, Scott [Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, B3H 4R2 (Canada); Bower, Geoffrey C. [Academia Sinica Institute of Astronomy and Astrophysics, 645 N. A‘ohōkū Place, Hilo, HI 96720 (United States); Bell, Graham S.; Graves, Sarah, E-mail: smairs@uvic.ca [East Asian Observatory, 660 North A‘ohōkū Place, University Park, Hilo, Hawaii 96720 (United States); Collaboration: JCMT Transient Team
2017-07-01
Though there has been a significant amount of work investigating the early stages of low-mass star formation in recent years, the evolution of the mass assembly rate onto the central protostar remains largely unconstrained. Examining in depth the variation in this rate is critical to understanding the physics of star formation. Instabilities in the outer and inner circumstellar disk can lead to episodic outbursts. Observing these brightness variations at infrared or submillimeter wavelengths constrains the current accretion models. The JCMT Transient Survey is a three-year project dedicated to studying the continuum variability of deeply embedded protostars in eight nearby star-forming regions at a one-month cadence. We use the SCUBA-2 instrument to simultaneously observe these regions at wavelengths of 450 and 850 μ m. In this paper, we present the data reduction techniques, image alignment procedures, and relative flux calibration methods for 850 μ m data. We compare the properties and locations of bright, compact emission sources fitted with Gaussians over time. Doing so, we achieve a spatial alignment of better than 1″ between the repeated observations and an uncertainty of 2%–3% in the relative peak brightness of significant, localized emission. This combination of imaging performance is unprecedented in ground-based, single-dish submillimeter observations. Finally, we identify a few sources that show possible and confirmed brightness variations. These sources will be closely monitored and presented in further detail in additional studies throughout the duration of the survey.
Hybrid CMS methods with model reduction for assembly of structures
Farhat, Charbel
1991-01-01
Future on-orbit structures will be designed and built in several stages, each with specific control requirements. Therefore there must be a methodology which can predict the dynamic characteristics of the assembled structure, based on the dynamic characteristics of the subassemblies and their interfaces. The methodology developed by CSC to address this issue is Hybrid Component Mode Synthesis (HCMS). HCMS distinguishes itself from standard component mode synthesis algorithms in the following features: (1) it does not require the subcomponents to have displacement compatible models, which makes it ideal for analyzing the deployment of heterogeneous flexible multibody systems, (2) it incorporates a second-level model reduction scheme at the interface, which makes it much faster than other algorithms and therefore suitable for control purposes, and (3) it does answer specific questions such as 'how does the global fundamental frequency vary if I change the physical parameters of substructure k by a specified amount?'. Because it is based on an energy principle rather than displacement compatibility, this methodology can also help the designer to define an assembly process. Current and future efforts are devoted to applying the HCMS method to design and analyze docking and berthing procedures in orbital construction.
The JCMT Transient Survey: Data Reduction and Calibration Methods
Mairs, Steve; Lane, James; Johnstone, Doug; Kirk, Helen; Lacaille, Kevin; Chapman, Scott; Bower, Geoffrey C.; Bell, Graham S.; Graves, Sarah
2017-01-01
Though there has been a significant amount of work investigating the early stages of low-mass star formation in recent years, the evolution of the mass assembly rate onto the central protostar remains largely unconstrained. Examining in depth the variation in this rate is critical to understanding the physics of star formation. Instabilities in the outer and inner circumstellar disk can lead to episodic outbursts. Observing these brightness variations at infrared or submillimeter wavelengths constrains the current accretion models. The JCMT Transient Survey is a three-year project dedicated to studying the continuum variability of deeply embedded protostars in eight nearby star-forming regions at a one-month cadence. We use the SCUBA-2 instrument to simultaneously observe these regions at wavelengths of 450 and 850 μ m. In this paper, we present the data reduction techniques, image alignment procedures, and relative flux calibration methods for 850 μ m data. We compare the properties and locations of bright, compact emission sources fitted with Gaussians over time. Doing so, we achieve a spatial alignment of better than 1″ between the repeated observations and an uncertainty of 2%–3% in the relative peak brightness of significant, localized emission. This combination of imaging performance is unprecedented in ground-based, single-dish submillimeter observations. Finally, we identify a few sources that show possible and confirmed brightness variations. These sources will be closely monitored and presented in further detail in additional studies throughout the duration of the survey.
New method for reduction of burning sulfur of coal
Lyutskanov, L.; Dushanov, D.
1998-01-01
The coal pyrolysis is key phase in the the pyrolysis-combustion cycle as it provides char for combustor. The behaviour of sulfur compounds during coal pyrolysis depends on factors as rank of coal, quantity of sulfur and sulfur forms distribution in the coal, quantity and kind of mineral matter and the process conditions. The mineral content of coal may inhibit or catalyze the formation of volatile sulfur compounds. The pyrolysis itself is a mean of removing inorganic and organic sulfur but anyway a portion of it remains in the char while the other moves into the tar and gas. The aim of this study was to determine an optimal reduction of burning sulfur at the coal pyrolysis by varying parametric conditions. The pyrolysis of different kinds of coal has been studied. The samples with size particles o C at atmospheric pressure and with a heating rate of 6-50 o C min -1 . They were treated with exhaust gas and nitrogen at an addition of steam and air. The char obtained remains up to 10 min at the final temperature. The char samples cool without a contact with air. Two methods of desulfurization-pyrolysis were studied - using 9-vertical tubular reactor and 9-horizontal turning reactor. The results obtained show that at all samples there is a decrease of burning sulfur with maximal removal efficiency 83%. For example at a pyrolysis of Maritsa Iztok lignite coal the burning sulfur is only 16% in comparison with the control sample. The remained is 90% sulfate, 10% organic and pyrite traces when a mixture 'exhaust gas-water stream-air' was used. The method of desulfurization by pyrolysis could be applied at different kinds of coal and different conditions. Char obtained as a clean product can be used for generating electric power. This innovation is in a stage of patenting
F. Grigoli; Simone Cesca; Torsten Dahm; L. Krieger
2012-01-01
Determining the relative orientation of the horizontal components of seismic sensors is a common problem that limits data analysis and interpretation for several acquisition setups, including linear arrays of geophones deployed in borehole installations or ocean bottom seismometers deployed at the seafloor. To solve this problem we propose a new inversion method based on a complex linear algebra approach. Relative orientation angles are retrieved by minimizing, in a least-squares sense, the l...
General methods for determining the linear stability of coronal magnetic fields
Craig, I. J. D.; Sneyd, A. D.; Mcclymont, A. N.
1988-01-01
A time integration of a linearized plasma equation of motion has been performed to calculate the ideal linear stability of arbitrary three-dimensional magnetic fields. The convergence rates of the explicit and implicit power methods employed are speeded up by using sequences of cyclic shifts. Growth rates are obtained for Gold-Hoyle force-free equilibria, and the corkscrew-kink instability is found to be very weak.
Non-linear shape functions over time in the space-time finite element method
Kacprzyk Zbigniew
2017-01-01
Full Text Available This work presents a generalisation of the space-time finite element method proposed by Kączkowski in his seminal of 1970’s and early 1980’s works. Kączkowski used linear shape functions in time. The recurrence formula obtained by Kączkowski was conditionally stable. In this paper, non-linear shape functions in time are proposed.
An algebraic method for system reduction of stationary Gaussian systems
D. Jibetean; J.H. van Schuppen (Jan)
2003-01-01
textabstractSystem identification for a particular approach reduces to system reduction, determining for a system with a high state-space dimension a system of low state-space dimension. For Gaussian systems the problem of system reduction is considered with the divergence rate criterion. The
Treating experimental data of inverse kinetic method by unitary linear regression analysis
Zhao Yusen; Chen Xiaoliang
2009-01-01
The theory of treating experimental data of inverse kinetic method by unitary linear regression analysis was described. Not only the reactivity, but also the effective neutron source intensity could be calculated by this method. Computer code was compiled base on the inverse kinetic method and unitary linear regression analysis. The data of zero power facility BFS-1 in Russia were processed and the results were compared. The results show that the reactivity and the effective neutron source intensity can be obtained correctly by treating experimental data of inverse kinetic method using unitary linear regression analysis and the precision of reactivity measurement is improved. The central element efficiency can be calculated by using the reactivity. The result also shows that the effect to reactivity measurement caused by external neutron source should be considered when the reactor power is low and the intensity of external neutron source is strong. (authors)
A Method of Calculating Motion Error in a Linear Motion Bearing Stage
Gyungho Khim
2015-01-01
Full Text Available We report a method of calculating the motion error of a linear motion bearing stage. The transfer function method, which exploits reaction forces of individual bearings, is effective for estimating motion errors; however, it requires the rail-form errors. This is not suitable for a linear motion bearing stage because obtaining the rail-form errors is not straightforward. In the method described here, we use the straightness errors of a bearing block to calculate the reaction forces on the bearing block. The reaction forces were compared with those of the transfer function method. Parallelism errors between two rails were considered, and the motion errors of the linear motion bearing stage were measured and compared with the results of the calculations, revealing good agreement.
A Method of Calculating Motion Error in a Linear Motion Bearing Stage
Khim, Gyungho; Park, Chun Hong; Oh, Jeong Seok
2015-01-01
We report a method of calculating the motion error of a linear motion bearing stage. The transfer function method, which exploits reaction forces of individual bearings, is effective for estimating motion errors; however, it requires the rail-form errors. This is not suitable for a linear motion bearing stage because obtaining the rail-form errors is not straightforward. In the method described here, we use the straightness errors of a bearing block to calculate the reaction forces on the bearing block. The reaction forces were compared with those of the transfer function method. Parallelism errors between two rails were considered, and the motion errors of the linear motion bearing stage were measured and compared with the results of the calculations, revealing good agreement. PMID:25705715
Ingel, R
1999-01-01
.... Projection operators are employed for the model reduction or condensation process. Interpolation is then introduced over a user defined frequency window, which can have real and imaginary boundaries and be quite large. Hermitian...
On a new iterative method for solving linear systems and comparison results
Jing, Yan-Fei; Huang, Ting-Zhu
2008-10-01
In Ujevic [A new iterative method for solving linear systems, Appl. Math. Comput. 179 (2006) 725-730], the author obtained a new iterative method for solving linear systems, which can be considered as a modification of the Gauss-Seidel method. In this paper, we show that this is a special case from a point of view of projection techniques. And a different approach is established, which is both theoretically and numerically proven to be better than (at least the same as) Ujevic's. As the presented numerical examples show, in most cases, the convergence rate is more than one and a half that of Ujevic.
Şuayip Yüzbaşı
2017-03-01
Full Text Available In this paper, we suggest a matrix method for obtaining the approximate solutions of the delay linear Fredholm integro-differential equations with constant coefficients using the shifted Legendre polynomials. The problem is considered with mixed conditions. Using the required matrix operations, the delay linear Fredholm integro-differential equation is transformed into a matrix equation. Additionally, error analysis for the method is presented using the residual function. Illustrative examples are given to demonstrate the efficiency of the method. The results obtained in this study are compared with the known results.
Methods of measurement of integral and differential linearity distortions of spectrometry sets
Fuan, Jacques; Grimont, Bernard; Marin, Roland; Richard, Jean-Pierre
1969-05-01
The objective of this document is to describe different measurement methods, and more particularly to present a software for the processing of obtained results in order to avoid interpretation by the investigator. In a first part, the authors define the parameters of integral and differential linearity, outlines their importance in measurements performed by spectrometry, and describe the use of these parameters. In the second part, they propose various methods of measurement of these linearity parameters, report experimental applications of these methods and compare the obtained results
Novel method of interpolation and extrapolation of functions by a linear initial value problem
Shatalov, M
2008-09-01
Full Text Available A novel method of function approximation using an initial value, linear, ordinary differential equation (ODE) is presented. The main advantage of this method is to obtain the approximation expressions in a closed form. This technique can be taught...
Jen-Yuan Chen
2014-01-01
Full Text Available Continuing from the works of Li et al. (2014, Li (2007, and Kincaid et al. (2000, we present more generalizations and modifications of iterative methods for solving large sparse symmetric and nonsymmetric indefinite systems of linear equations. We discuss a variety of iterative methods such as GMRES, MGMRES, MINRES, LQ-MINRES, QR MINRES, MMINRES, MGRES, and others.
Thompson, Russel L.
Homoscedasticity is an important assumption of linear regression. This paper explains what it is and why it is important to the researcher. Graphical and mathematical methods for testing the homoscedasticity assumption are demonstrated. Sources of homoscedasticity and types of homoscedasticity are discussed, and methods for correction are…
Experimental validation for calcul methods of structures having shock non-linearity
Brochard, D.; Buland, P.
1987-01-01
For the seismic analysis of non-linear structures, numerical methods have been developed which need to be validated on experimental results. The aim of this paper is to present the design method of a test program which results will be used for this purpose. Some applications to nuclear components will illustrate this presentation [fr
Calculation of U, Ra, Th and K contents in uranium ore by multiple linear regression method
Lin Chao; Chen Yingqiang; Zhang Qingwen; Tan Fuwen; Peng Guanghui
1991-01-01
A multiple linear regression method was used to compute γ spectra of uranium ore samples and to calculate contents of U, Ra, Th, and K. In comparison with the inverse matrix method, its advantage is that no standard samples of pure U, Ra, Th and K are needed for obtaining response coefficients
Engineered high expansion glass-ceramics having near linear thermal strain and methods thereof
Dai, Steve Xunhu; Rodriguez, Mark A.; Lyon, Nathanael L.
2018-01-30
The present invention relates to glass-ceramic compositions, as well as methods for forming such composition. In particular, the compositions include various polymorphs of silica that provide beneficial thermal expansion characteristics (e.g., a near linear thermal strain). Also described are methods of forming such compositions, as well as connectors including hermetic seals containing such compositions.
A block Krylov subspace time-exact solution method for linear ordinary differential equation systems
Bochev, Mikhail A.
2013-01-01
We propose a time-exact Krylov-subspace-based method for solving linear ordinary differential equation systems of the form $y'=-Ay+g(t)$ and $y"=-Ay+g(t)$, where $y(t)$ is the unknown function. The method consists of two stages. The first stage is an accurate piecewise polynomial approximation of
A study on linear and nonlinear Schrodinger equations by the variational iteration method
Wazwaz, Abdul-Majid
2008-01-01
In this work, we introduce a framework to obtain exact solutions to linear and nonlinear Schrodinger equations. The He's variational iteration method (VIM) is used for analytic treatment of these equations. Numerical examples are tested to show the pertinent features of this method
Hong, Ser Gi; Kim, Jong Woon; Lee, Young Ouk; Kim, Kyo Youn
2010-01-01
The subcell balance methods have been developed for one- and two-dimensional SN transport calculations. In this paper, a linear discontinuous expansion method using sub-cell balances (LDEM-SCB) is developed for neutral particle S N transport calculations in 3D unstructured geometrical problems. At present, this method is applied to the tetrahedral meshes. As the name means, this method assumes the linear distribution of the particle flux in each tetrahedral mesh and uses the balance equations for four sub-cells of each tetrahedral mesh to obtain the equations for the four sub-cell average fluxes which are unknowns. This method was implemented in the computer code MUST (Multi-group Unstructured geometry S N Transport). The numerical tests show that this method gives more robust solution than DFEM (Discontinuous Finite Element Method)
Strong Stability Preserving Explicit Linear Multistep Methods with Variable Step Size
Hadjimichael, Yiannis
2016-09-08
Strong stability preserving (SSP) methods are designed primarily for time integration of nonlinear hyperbolic PDEs, for which the permissible SSP step size varies from one step to the next. We develop the first SSP linear multistep methods (of order two and three) with variable step size, and prove their optimality, stability, and convergence. The choice of step size for multistep SSP methods is an interesting problem because the allowable step size depends on the SSP coefficient, which in turn depends on the chosen step sizes. The description of the methods includes an optimal step-size strategy. We prove sharp upper bounds on the allowable step size for explicit SSP linear multistep methods and show the existence of methods with arbitrarily high order of accuracy. The effectiveness of the methods is demonstrated through numerical examples.
Campoamor-Stursberg, R.
2018-03-01
A procedure for the construction of nonlinear realizations of Lie algebras in the context of Vessiot-Guldberg-Lie algebras of first-order systems of ordinary differential equations (ODEs) is proposed. The method is based on the reduction of invariants and projection of lowest-dimensional (irreducible) representations of Lie algebras. Applications to the description of parameterized first-order systems of ODEs related by contraction of Lie algebras are given. In particular, the kinematical Lie algebras in (2 + 1)- and (3 + 1)-dimensions are realized simultaneously as Vessiot-Guldberg-Lie algebras of parameterized nonlinear systems in R3 and R4, respectively.
A new method for the chemoselective reduction of aldehydes and ...
Department of Chemistry, Akdeniz University, 07058, Antalya, Turkey e-mail: ... Kinetics of reduction of aldehydes and ketones to corresponding alcohols were also examined and .... hol and unreducted ketone remain in organic phase. The.
A discrete homotopy perturbation method for non-linear Schrodinger equation
H. A. Wahab
2015-12-01
Full Text Available A general analysis is made by homotopy perturbation method while taking the advantages of the initial guess, appearance of the embedding parameter, different choices of the linear operator to the approximated solution to the non-linear Schrodinger equation. We are not dependent upon the Adomian polynomials and find the linear forms of the components without these calculations. The discretised forms of the nonlinear Schrodinger equation allow us whether to apply any numerical technique on the discritisation forms or proceed for perturbation solution of the problem. The discretised forms obtained by constructed homotopy provide the linear parts of the components of the solution series and hence a new discretised form is obtained. The general discretised form for the NLSE allows us to choose any initial guess and the solution in the closed form.
Analytical study of dynamic aperture for storage ring by using successive linearization method
Yang Jiancheng; Xia Jiawen; Wu Junxia; Xia Guoxing; Liu Wei; Yin Xuejun
2004-01-01
The determination of dynamic aperture is a critical issue in circular accelerator. In this paper, authors solved the equation of motion including non-linear forces by using successive linearization method and got a criterion for the determining of the dynamic aperture of the machine. Applying this criterion, a storage ring with FODO lattice has been studied. The results are agree well with the tracking results in a large range of linear turn (Q). The purpose is to improve our understanding of the mechanisms driving the particle motion in the presence of non-linear forces and got another mechanism driving instability of particle in storage ring-parametric resonance caused by 'fluctuating transfer matrices' at small amplification
A New Spectral Local Linearization Method for Nonlinear Boundary Layer Flow Problems
S. S. Motsa
2013-01-01
Full Text Available We propose a simple and efficient method for solving highly nonlinear systems of boundary layer flow problems with exponentially decaying profiles. The algorithm of the proposed method is based on an innovative idea of linearizing and decoupling the governing systems of equations and reducing them into a sequence of subsystems of differential equations which are solved using spectral collocation methods. The applicability of the proposed method, hereinafter referred to as the spectral local linearization method (SLLM, is tested on some well-known boundary layer flow equations. The numerical results presented in this investigation indicate that the proposed method, despite being easy to develop and numerically implement, is very robust in that it converges rapidly to yield accurate results and is more efficient in solving very large systems of nonlinear boundary value problems of the similarity variable boundary layer type. The accuracy and numerical stability of the SLLM can further be improved by using successive overrelaxation techniques.
Shang, Shang; Bai, Jing; Song, Xiaolei; Wang, Hongkai; Lau, Jaclyn
2007-01-01
Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based on a restart strategy, in order to take advantage of the two kinds of conjugate gradient methods and compensate for the disadvantages. A quadratic penalty method is adopted to gain a nonnegative constraint and reduce the illposedness of the problem. Simulation studies show that the presented algorithm is accurate, stable, and fast. It has a better performance than the conventional conjugate gradient-based reconstruction algorithms. It offers an effective approach to reconstruct fluorochrome information for FMT.
Hussein Abdel-jaber
2015-10-01
Full Text Available Congestion control is one of the hot research topics that helps maintain the performance of computer networks. This paper compares three Active Queue Management (AQM methods, namely, Adaptive Gentle Random Early Detection (Adaptive GRED, Random Early Dynamic Detection (REDD, and GRED Linear analytical model with respect to different performance measures. Adaptive GRED and REDD are implemented based on simulation, whereas GRED Linear is implemented as a discrete-time analytical model. Several performance measures are used to evaluate the effectiveness of the compared methods mainly mean queue length, throughput, average queueing delay, overflow packet loss probability, and packet dropping probability. The ultimate aim is to identify the method that offers the highest satisfactory performance in non-congestion or congestion scenarios. The first comparison results that are based on different packet arrival probability values show that GRED Linear provides better mean queue length; average queueing delay and packet overflow probability than Adaptive GRED and REDD methods in the presence of congestion. Further and using the same evaluation measures, Adaptive GRED offers a more satisfactory performance than REDD when heavy congestion is present. When the finite capacity of queue values varies the GRED Linear model provides the highest satisfactory performance with reference to mean queue length and average queueing delay and all the compared methods provide similar throughput performance. However, when the finite capacity value is large, the compared methods have similar results in regard to probabilities of both packet overflowing and packet dropping.
Bykova, L.N.; Chesnokova, O.Ya.; Orlova, M.V.
1995-01-01
The method for linearizing the potentiometric curves of precipitation titration is studied for its application in the determination of halide ions (Cl - , Br - , I - ) in dimethylacetamide, dimethylformamide, in which titration is complicated by additional equilibrium processes. It is found that the method of linearization permits the determination of the titrant volume at the end point of titration to high accuracy in the case of titration curves without a potential jump in the proximity of the equivalent point (5 x 10 -5 M). 3 refs., 2 figs., 3 tabs
Heinz Toparkus
2014-04-01
Full Text Available In this paper we consider first-order systems with constant coefficients for two real-valued functions of two real variables. This is both a problem in itself, as well as an alternative view of the classical linear partial differential equations of second order with constant coefficients. The classification of the systems is done using elementary methods of linear algebra. Each type presents its special canonical form in the associated characteristic coordinate system. Then you can formulate initial value problems in appropriate basic areas, and you can try to achieve a solution of these problems by means of transform methods.
Ikuno, Soichiro; Chen, Gong; Yamamoto, Susumu; Itoh, Taku; Abe, Kuniyoshi; Nakamura, Hiroaki
2016-01-01
Krylov subspace method and the variable preconditioned Krylov subspace method with communication avoiding technique for a linear system obtained from electromagnetic analysis are numerically investigated. In the k−skip Krylov method, the inner product calculations are expanded by Krylov basis, and the inner product calculations are transformed to the scholar operations. k−skip CG method is applied for the inner-loop solver of Variable Preconditioned Krylov subspace methods, and the converged solution of electromagnetic problem is obtained using the method. (author)
Gusriani, N.; Firdaniza
2018-03-01
The existence of outliers on multiple linear regression analysis causes the Gaussian assumption to be unfulfilled. If the Least Square method is forcedly used on these data, it will produce a model that cannot represent most data. For that, we need a robust regression method against outliers. This paper will compare the Minimum Covariance Determinant (MCD) method and the TELBS method on secondary data on the productivity of phytoplankton, which contains outliers. Based on the robust determinant coefficient value, MCD method produces a better model compared to TELBS method.
Salih Yalcinbas
2016-01-01
Full Text Available In this paper, a new collocation method based on the Fibonacci polynomials is introduced to solve the high-order linear Volterra integro-differential equations under the conditions. Numerical examples are included to demonstrate the applicability and validity of the proposed method and comparisons are made with the existing results. In addition, an error estimation based on the residual functions is presented for this method. The approximate solutions are improved by using this error estimation.
Measurements of linear attenuation coefficients of irregular shaped samples by two media method
Singh, Sukhpal; Kumar, Ashok; Thind, Kulwant Singh; Mudahar, Gurmel S.
2008-01-01
The linear attenuation coefficient values of regular and irregular shaped flyash materials have been measured without knowing the thickness of a sample using a new technique namely 'two media method'. These values have also been measured with a standard gamma ray transmission method and obtained theoretically with winXCOM computer code. From the comparison it is reported that the two media method has given accurate results of attenuation coefficients of flyash materials
A simple method for identifying parameter correlations in partially observed linear dynamic models.
Li, Pu; Vu, Quoc Dong
2015-12-14
Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a
Aytaç Korkmaz, Sevcan; Binol, Hamidullah
2018-03-01
Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.
Two new modified Gauss-Seidel methods for linear system with M-matrices
Zheng, Bing; Miao, Shu-Xin
2009-12-01
In 2002, H. Kotakemori et al. proposed the modified Gauss-Seidel (MGS) method for solving the linear system with the preconditioner [H. Kotakemori, K. Harada, M. Morimoto, H. Niki, A comparison theorem for the iterative method with the preconditioner () J. Comput. Appl. Math. 145 (2002) 373-378]. Since this preconditioner is constructed by only the largest element on each row of the upper triangular part of the coefficient matrix, the preconditioning effect is not observed on the nth row. In the present paper, to deal with this drawback, we propose two new preconditioners. The convergence and comparison theorems of the modified Gauss-Seidel methods with these two preconditioners for solving the linear system are established. The convergence rates of the new proposed preconditioned methods are compared. In addition, numerical experiments are used to show the effectiveness of the new MGS methods.
Comparative study of synthesis and reduction methods for graphene oxide
Alazmi, Amira; Rasul, Shahid; Patole, Shashikant P.; Da Costa, Pedro M. F. J.
2016-01-01
Graphene oxide (GO) and reduced graphene oxide (rGO) have congregated much interest as promising active materials for a variety of applications such as electrodes for supercapacitors. Yet, partially given the absence of comparative studies in synthesis methodologies, a lack of understanding persists on how to best tailor these materials. In this work, the effect of using different graphene oxidation-reduction strategies in the structure and chemistry of rGOs is systematically discussed. Two of the most popular oxidation routes in the literature were used to obtain GO. Subsequently, two sets of rGO powders were synthesised employing three different reduction routes, totalling six separate products. It is shown that the extension of the structural rearrangement in rGOs is not just dependent on the reduction step but also on the approach followed for the initial graphite oxidation.
Some variance reduction methods for numerical stochastic homogenization.
Blanc, X; Le Bris, C; Legoll, F
2016-04-28
We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).
Comparative study of synthesis and reduction methods for graphene oxide
Alazmi, Amira
2016-05-14
Graphene oxide (GO) and reduced graphene oxide (rGO) have congregated much interest as promising active materials for a variety of applications such as electrodes for supercapacitors. Yet, partially given the absence of comparative studies in synthesis methodologies, a lack of understanding persists on how to best tailor these materials. In this work, the effect of using different graphene oxidation-reduction strategies in the structure and chemistry of rGOs is systematically discussed. Two of the most popular oxidation routes in the literature were used to obtain GO. Subsequently, two sets of rGO powders were synthesised employing three different reduction routes, totalling six separate products. It is shown that the extension of the structural rearrangement in rGOs is not just dependent on the reduction step but also on the approach followed for the initial graphite oxidation.
Jimenez, J.C.
2009-06-01
Local Linearization (LL) methods conform a class of one-step explicit integrators for ODEs derived from the following primary and common strategy: the vector field of the differential equation is locally (piecewise) approximated through a first-order Taylor expansion at each time step, thus obtaining successive linear equations that are explicitly integrated. Hereafter, the LL approach may include some additional strategies to improve that basic affine approximation. Theoretical and practical results have shown that the LL integrators have a number of convenient properties. These include arbitrary order of convergence, A-stability, linearization preserving, regularity under quite general conditions, preservation of the dynamics of the exact solution around hyperbolic equilibrium points and periodic orbits, integration of stiff and high-dimensional equations, low computational cost, and others. In this paper, a review of the LL methods and their properties is presented. (author)
Paul, Sarbajit; Chang, Junghwan
2017-07-01
This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension.
Method for simulating dose reduction in digital mammography using the Anscombe transformation
Borges, Lucas R.; Oliveira, Helder C. R. de; Nunes, Polyana F.; Vieira, Marcelo A. C.; Bakic, Predrag R.; Maidment, Andrew D. A.
2016-01-01
Purpose: This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose. Methods: The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the detective quantum efficiency. The scaling process takes into account the linearity of the system and the offset of the detector elements. The inserted noise is obtained by acquiring images of a flat-field phantom at the standard radiation dose and at the simulated dose. Using the Anscombe transformation, a relationship is created between the calculated noise mask and the scaled image, resulting in a clinical mammogram with the same noise and gray level characteristics as an image acquired at the lower-radiation dose. Results: The performance of the proposed algorithm was validated using real images acquired with an anthropomorphic breast phantom at four different doses, with five exposures for each dose and 256 nonoverlapping ROIs extracted from each image and with uniform images. The authors simulated lower-dose images and compared these with the real images. The authors evaluated the similarity between the normalized noise power spectrum (NNPS) and power spectrum (PS) of simulated images and real images acquired with the same dose. The maximum relative error was less than 2.5% for every ROI. The added noise was also evaluated by measuring the local variance in the real and simulated images. The relative average error for the local variance was smaller than 1%. Conclusions: A new method is proposed for simulating dose reduction in clinical mammograms. In this method, the dependency between image noise and image signal is addressed using a novel application of the Anscombe
Method for simulating dose reduction in digital mammography using the Anscombe transformation
Borges, Lucas R., E-mail: lucas.rodrigues.borges@usp.br; Oliveira, Helder C. R. de; Nunes, Polyana F.; Vieira, Marcelo A. C. [Department of Electrical and Computer Engineering, São Carlos School of Engineering, University of São Paulo, 400 Trabalhador São-Carlense Avenue, São Carlos 13566-590 (Brazil); Bakic, Predrag R.; Maidment, Andrew D. A. [Department of Radiology, Hospital of the University of Pennsylvania, University of Pennsylvania, 3400 Spruce Street, Philadelphia, Pennsylvania 19104 (United States)
2016-06-15
Purpose: This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose. Methods: The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the detective quantum efficiency. The scaling process takes into account the linearity of the system and the offset of the detector elements. The inserted noise is obtained by acquiring images of a flat-field phantom at the standard radiation dose and at the simulated dose. Using the Anscombe transformation, a relationship is created between the calculated noise mask and the scaled image, resulting in a clinical mammogram with the same noise and gray level characteristics as an image acquired at the lower-radiation dose. Results: The performance of the proposed algorithm was validated using real images acquired with an anthropomorphic breast phantom at four different doses, with five exposures for each dose and 256 nonoverlapping ROIs extracted from each image and with uniform images. The authors simulated lower-dose images and compared these with the real images. The authors evaluated the similarity between the normalized noise power spectrum (NNPS) and power spectrum (PS) of simulated images and real images acquired with the same dose. The maximum relative error was less than 2.5% for every ROI. The added noise was also evaluated by measuring the local variance in the real and simulated images. The relative average error for the local variance was smaller than 1%. Conclusions: A new method is proposed for simulating dose reduction in clinical mammograms. In this method, the dependency between image noise and image signal is addressed using a novel application of the Anscombe
Comparison of different methods for the solution of sets of linear equations
Bilfinger, T.; Schmidt, F.
1978-06-01
The application of the conjugate-gradient methods as novel general iterative methods for the solution of sets of linear equations with symmetrical systems matrices led to this paper, where a comparison of these methods with the conventional differently accelerated Gauss-Seidel iteration was carried out. In additon, the direct Cholesky method was also included in the comparison. The studies referred mainly to memory requirement, computing time, speed of convergence, and accuracy of different conditions of the systems matrices, by which also the sensibility of the methods with respect to the influence of truncation errors may be recognized. (orig.) 891 RW [de
Robust fault detection of linear systems using a computationally efficient set-membership method
Tabatabaeipour, Mojtaba; Bak, Thomas
2014-01-01
In this paper, a computationally efficient set-membership method for robust fault detection of linear systems is proposed. The method computes an interval outer-approximation of the output of the system that is consistent with the model, the bounds on noise and disturbance, and the past measureme...... is trivially parallelizable. The method is demonstrated for fault detection of a hydraulic pitch actuator of a wind turbine. We show the effectiveness of the proposed method by comparing our results with two zonotope-based set-membership methods....
An overview of solution methods for multi-objective mixed integer linear programming programs
Andersen, Kim Allan; Stidsen, Thomas Riis
Multiple objective mixed integer linear programming (MOMIP) problems are notoriously hard to solve to optimality, i.e. finding the complete set of non-dominated solutions. We will give an overview of existing methods. Among those are interactive methods, the two phases method and enumeration...... methods. In particular we will discuss the existing branch and bound approaches for solving multiple objective integer programming problems. Despite the fact that branch and bound methods has been applied successfully to integer programming problems with one criterion only a few attempts has been made...
Rubin's CMS reduction method for general state-space models
Kraker, de A.; Campen, van D.H.
1996-01-01
In this paper the Rubin CMS procedure for the reduction and successive coupling of undamped structural subsystems with symmetric system matrices will be modified for the case of general damping. The final coordinate transformation is based on the use of complex (residual) flexibility modes,
A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants
Cooper, Paul D.
2010-01-01
A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…
Linear shrinkage test: justification for its reintroduction as a standard South African test method
Sampson, LR
2009-06-04
Full Text Available Several problems with the linear shrinkage test specified in Method A4 of the THM 1 1979 were addressed as part of this investigation in an effort to improve the alleged poor reproducibility of the test and justify its reintroduction into THM 1. A...
Fusco, D [Messina Univ. (Italy). Instituto de Matematica
1979-01-01
The paper is concerned with a three-dimensional theory of non-linear magnetosonic waves in a turbulent plasma. A perturbation method is used that allows a transport equation, like Burgers equation but with a variable coefficient to be obtained.
В.Т. Чемерис
2006-04-01
Full Text Available There is a method of simplified calculation and design parameters choice elaborated in this article with corresponding basing for the induction system of electron-beam sterilizer on the base of linear induction accelerator taking into account the parameters of magnetic material for production of cores and parameters of pulsed voltage.
The H-N method for solving linear transport equation: theory and application
Kaskas, A.; Gulecyuz, M.C.; Tezcan, C.
2002-01-01
The system of singular integral equation which is obtained from the integro-differential form of the linear transport equation as a result of Placzec lemma is solved. Application are given using the exit distributions and the infinite medium Green's function. The same theoretical results are also obtained with the use of the singular eigenfunction of the method of elementary solutions
Tuereci, R. Goekhan [Kirikkale Univ. (Turkey). Kirikkale Vocational School; Tuereci, D. [Ministry of Education, Ankara (Turkey). 75th year Anatolia High School
2017-11-15
One speed, time independent and homogeneous medium neutron transport equation is solved with the anisotropic scattering which includes both the linearly and the quadratically anisotropic scattering kernel. Having written Case's eigenfunctions and the orthogonality relations among of these eigenfunctions, slab albedo problem is investigated as numerically by using Modified F{sub N} method. Selected numerical results are presented in tables.
An Empirical Comparison of Five Linear Equating Methods for the NEAT Design
Suh, Youngsuk; Mroch, Andrew A.; Kane, Michael T.; Ripkey, Douglas R.
2009-01-01
In this study, a data base containing the responses of 40,000 candidates to 90 multiple-choice questions was used to mimic data sets for 50-item tests under the "nonequivalent groups with anchor test" (NEAT) design. Using these smaller data sets, we evaluated the performance of five linear equating methods for the NEAT design with five levels of…
A Revised Piecewise Linear Recursive Convolution FDTD Method for Magnetized Plasmas
Liu Song; Zhong Shuangying; Liu Shaobin
2005-01-01
The piecewise linear recursive convolution (PLRC) finite-different time-domain (FDTD) method improves accuracy over the original recursive convolution (RC) FDTD approach and current density convolution (JEC) but retains their advantages in speed and efficiency. This paper describes a revised piecewise linear recursive convolution PLRC-FDTD formulation for magnetized plasma which incorporates both anisotropy and frequency dispersion at the same time, enabling the transient analysis of magnetized plasma media. The technique is illustrated by numerical simulations of the reflection and transmission coefficients through a magnetized plasma layer. The results show that the revised PLRC-FDTD method has improved the accuracy over the original RC FDTD method and JEC FDTD method
Anderson, Carl A.; McRae, Allan F.; Visscher, Peter M.
2006-01-01
Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using...
Interior-Point Method for Non-Linear Non-Convex Optimization
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
Method for solving fully fuzzy linear programming problems using deviation degree measure
Haifang Cheng; Weilai Huang; Jianhu Cai
2013-01-01
A new ful y fuzzy linear programming (FFLP) prob-lem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crispδ-parametric linear programming (LP) problem. Giving the value of deviation degree in each constraint, the δ-fuzzy optimal so-lution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict: to improve the va-lues of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to il ustrate the proposed method.
Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.
Ying, Xiaoguo; Lin, Han; Hui, Guohua
2015-01-01
Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.
Yamasaki, Shinya; Tanaka, Kazuya; Kozai, Naofumi; Ohnuki, Toshihiko
2017-01-01
The reduction of uranium hexavalent (U(VI)) to tetravalent (U(IV)) is an important reaction because of the change in its mobility in the natural environment. Although the flavin mononucleotide (FMN) has acted as an electron shuttle for the U(VI) reduction in vivo system, which is called an electron mediator, only the rate constant for the electron transfer from FMN to U(VI) has been determined. This study examined the rate constant for the U(VI) reduction process by three flavin analogues (riboflavin, flavin mononucleotide, flavin adenine dinucleotide) to elucidate their substituent group effect on the U(VI) reduction rate by electrochemical methods. The formation of the U(IV) was monitored by UV-vis spectrometry at 660 nm during the constant potential electrolysis of the U(VI) solution in the presence of the mediator. The cyclic voltammograms indicated that the three flavin analogues behaved as electron mediator to reduce U(VI). The logarithmic rate constant for the U(VI) reduction was related to the standard redox potential of the mediators. This linear relationship indicated that the redox-active group of the mediator and the substituent group of the mediator dominate capability of the U(VI) reduction and its rate, respectively. The apparent reduction potential of U(VI) increased about 0.2 V in the presence of the mediators, which strongly suggests that the biological electron mediator makes the U(VI) reduction possible even under more oxidative conditions. - Highlights: • The rate constant for the U(VI) reduction by flavin analogues was determined. • The flavins showed a mediator effect on the U(VI) reduction. • The logarithmic rate constants for the U(VI) reduction was proportional to redox potential of the mediator. • The presence of the mediator increased about 0.2 V apparent redox potential of U(VI) to U(IV).
Restoring the missing features of the corrupted speech using linear interpolation methods
Rassem, Taha H.; Makbol, Nasrin M.; Hasan, Ali Muttaleb; Zaki, Siti Syazni Mohd; Girija, P. N.
2017-10-01
One of the main challenges in the Automatic Speech Recognition (ASR) is the noise. The performance of the ASR system reduces significantly if the speech is corrupted by noise. In spectrogram representation of a speech signal, after deleting low Signal to Noise Ratio (SNR) elements, the incomplete spectrogram is obtained. In this case, the speech recognizer should make modifications to the spectrogram in order to restore the missing elements, which is one direction. In another direction, speech recognizer should be able to restore the missing elements due to deleting low SNR elements before performing the recognition. This is can be done using different spectrogram reconstruction methods. In this paper, the geometrical spectrogram reconstruction methods suggested by some researchers are implemented as a toolbox. In these geometrical reconstruction methods, the linear interpolation along time or frequency methods are used to predict the missing elements between adjacent observed elements in the spectrogram. Moreover, a new linear interpolation method using time and frequency together is presented. The CMU Sphinx III software is used in the experiments to test the performance of the linear interpolation reconstruction method. The experiments are done under different conditions such as different lengths of the window and different lengths of utterances. Speech corpus consists of 20 males and 20 females; each one has two different utterances are used in the experiments. As a result, 80% recognition accuracy is achieved with 25% SNR ratio.
Sanchez, Richard.
1975-11-01
The Integral Transform Method for the neutron transport equation has been developed in last years by Asaoka and others. The method uses Fourier transform techniques in solving isotropic one-dimensional transport problems in homogeneous media. The method has been extended to linearly anisotropic transport in one-dimensional homogeneous media. Series expansions were also obtained using Hembd techniques for the new anisotropic matrix elements in cylindrical geometry. Carlvik spatial-spherical harmonics method was generalized to solve the same problem. By applying a relation between the isotropic and anisotropic one-dimensional kernels, it was demonstrated that anisotropic matrix elements can be calculated by a linear combination of a few isotropic matrix elements. This means in practice that the anisotropic problem of order N with the N+2 isotropic matrix for the plane and spherical geometries, and N+1 isotropic matrix for cylindrical geometries can be solved. A method of solving linearly anisotropic one-dimensional transport problems in homogeneous media was defined by applying Mika and Stankiewicz observations: isotropic matrix elements were computed by Hembd series and anisotropic matrix elements then calculated from recursive relations. The method has been applied to albedo and critical problems in cylindrical geometries. Finally, a number of results were computed with 12-digit accuracy for use as benchmarks [fr
Practical methods of dose reduction to the bladder wall
Smith, E.M.; Warner, G.G.
1976-01-01
The radiation dose to the bladder wall following the administration of radionuclides to patients can be reduced by a factor between 25 percent and 75 percent when the effective half-life for the radioactivity entering the urine is two hours or less. A significant but smaller reduction in dose to the gonads may also be achieved in situations where the major fraction of the administered activity is rapidly excreted in the urine. This reduction in dose is achieved by ensuring that the patient has between 50 and 150 ml of urine in his bladder when the radioactivity is injected, and is encouraged to void between one and two hours after the activity has been administered. The interrelationship of voiding schedule, effective half-life, initial urine volume, and demand urination has been analyzed in these studies. In addition, the significance of the rate of urine production and volume of urine in the bladder on the radiation dose to the bladder is demonstrated
Fuzzy Linear Regression for the Time Series Data which is Fuzzified with SMRGT Method
Seçil YALAZ
2016-10-01
Full Text Available Our work on regression and classification provides a new contribution to the analysis of time series used in many areas for years. Owing to the fact that convergence could not obtained with the methods used in autocorrelation fixing process faced with time series regression application, success is not met or fall into obligation of changing the models’ degree. Changing the models’ degree may not be desirable in every situation. In our study, recommended for these situations, time series data was fuzzified by using the simple membership function and fuzzy rule generation technique (SMRGT and to estimate future an equation has created by applying fuzzy least square regression (FLSR method which is a simple linear regression method to this data. Although SMRGT has success in determining the flow discharge in open channels and can be used confidently for flow discharge modeling in open canals, as well as in pipe flow with some modifications, there is no clue about that this technique is successful in fuzzy linear regression modeling. Therefore, in order to address the luck of such a modeling, a new hybrid model has been described within this study. In conclusion, to demonstrate our methods’ efficiency, classical linear regression for time series data and linear regression for fuzzy time series data were applied to two different data sets, and these two approaches performances were compared by using different measures.
A linear multiple balance method for discrete ordinates neutron transport equations
Park, Chang Je; Cho, Nam Zin
2000-01-01
A linear multiple balance method (LMB) is developed to provide more accurate and positive solutions for the discrete ordinates neutron transport equations. In this multiple balance approach, one mesh cell is divided into two subcells with quadratic approximation of angular flux distribution. Four multiple balance equations are used to relate center angular flux with average angular flux by Simpson's rule. From the analysis of spatial truncation error, the accuracy of the linear multiple balance scheme is ο(Δ 4 ) whereas that of diamond differencing is ο(Δ 2 ). To accelerate the linear multiple balance method, we also describe a simplified additive angular dependent rebalance factor scheme which combines a modified boundary projection acceleration scheme and the angular dependent rebalance factor acceleration schme. It is demonstrated, via fourier analysis of a simple model problem as well as numerical calculations, that the additive angular dependent rebalance factor acceleration scheme is unconditionally stable with spectral radius < 0.2069c (c being the scattering ration). The numerical results tested so far on slab-geometry discrete ordinates transport problems show that the solution method of linear multiple balance is effective and sufficiently efficient
Solutions of First-Order Volterra Type Linear Integrodifferential Equations by Collocation Method
Olumuyiwa A. Agbolade
2017-01-01
Full Text Available The numerical solutions of linear integrodifferential equations of Volterra type have been considered. Power series is used as the basis polynomial to approximate the solution of the problem. Furthermore, standard and Chebyshev-Gauss-Lobatto collocation points were, respectively, chosen to collocate the approximate solution. Numerical experiments are performed on some sample problems already solved by homotopy analysis method and finite difference methods. Comparison of the absolute error is obtained from the present method and those from aforementioned methods. It is also observed that the absolute errors obtained are very low establishing convergence and computational efficiency.
Exact solution to the Coulomb wave using the linearized phase-amplitude method
Shuji Kiyokawa
2015-08-01
Full Text Available The author shows that the amplitude equation from the phase-amplitude method of calculating continuum wave functions can be linearized into a 3rd-order differential equation. Using this linearized equation, in the case of the Coulomb potential, the author also shows that the amplitude function has an analytically exact solution represented by means of an irregular confluent hypergeometric function. Furthermore, it is shown that the exact solution for the Coulomb potential reproduces the wave function for free space expressed by the spherical Bessel function. The amplitude equation for the large component of the Dirac spinor is also shown to be the linearized 3rd-order differential equation.
A spectral analysis of the domain decomposed Monte Carlo method for linear systems
Slattery, S. R.; Wilson, P. P. H. [Engineering Physics Department, University of Wisconsin - Madison, 1500 Engineering Dr., Madison, WI 53706 (United States); Evans, T. M. [Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830 (United States)
2013-07-01
The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)
A spectral analysis of the domain decomposed Monte Carlo method for linear systems
Slattery, S. R.; Wilson, P. P. H.; Evans, T. M.
2013-01-01
The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)
Linear least-squares method for global luminescent oil film skin friction field analysis
Lee, Taekjin; Nonomura, Taku; Asai, Keisuke; Liu, Tianshu
2018-06-01
A data analysis method based on the linear least-squares (LLS) method was developed for the extraction of high-resolution skin friction fields from global luminescent oil film (GLOF) visualization images of a surface in an aerodynamic flow. In this method, the oil film thickness distribution and its spatiotemporal development are measured by detecting the luminescence intensity of the thin oil film. From the resulting set of GLOF images, the thin oil film equation is solved to obtain an ensemble-averaged (steady) skin friction field as an inverse problem. In this paper, the formulation of a discrete linear system of equations for the LLS method is described, and an error analysis is given to identify the main error sources and the relevant parameters. Simulations were conducted to evaluate the accuracy of the LLS method and the effects of the image patterns, image noise, and sample numbers on the results in comparison with the previous snapshot-solution-averaging (SSA) method. An experimental case is shown to enable the comparison of the results obtained using conventional oil flow visualization and those obtained using both the LLS and SSA methods. The overall results show that the LLS method is more reliable than the SSA method and the LLS method can yield a more detailed skin friction topology in an objective way.
Linearly decoupled energy-stable numerical methods for multi-component two-phase compressible flow
Kou, Jisheng
2017-12-06
In this paper, for the first time we propose two linear, decoupled, energy-stable numerical schemes for multi-component two-phase compressible flow with a realistic equation of state (e.g. Peng-Robinson equation of state). The methods are constructed based on the scalar auxiliary variable (SAV) approaches for Helmholtz free energy and the intermediate velocities that are designed to decouple the tight relationship between velocity and molar densities. The intermediate velocities are also involved in the discrete momentum equation to ensure a consistency relationship with the mass balance equations. Moreover, we propose a component-wise SAV approach for a multi-component fluid, which requires solving a sequence of linear, separate mass balance equations. We prove that the methods have the unconditional energy-dissipation feature. Numerical results are presented to verify the effectiveness of the proposed methods.
An Online Method for Interpolating Linear Parametric Reduced-Order Models
Amsallem, David; Farhat, Charbel
2011-01-01
A two-step online method is proposed for interpolating projection-based linear parametric reduced-order models (ROMs) in order to construct a new ROM for a new set of parameter values. The first step of this method transforms each precomputed ROM into a consistent set of generalized coordinates. The second step interpolates the associated linear operators on their appropriate matrix manifold. Real-time performance is achieved by precomputing inner products between the reduced-order bases underlying the precomputed ROMs. The proposed method is illustrated by applications in mechanical and aeronautical engineering. In particular, its robustness is demonstrated by its ability to handle the case where the sampled parameter set values exhibit a mode veering phenomenon. © 2011 Society for Industrial and Applied Mathematics.
Two media method for linear attenuation coefficient determination of irregular soil samples
Vici, Carlos Henrique Georges
2004-01-01
In several situations of nuclear applications, the knowledge of gamma-ray linear attenuation coefficient for irregular samples is necessary, such as in soil physics and geology. This work presents the validation of a methodology for the determination of the linear attenuation coefficient (μ) of irregular shape samples, in such a way that it is not necessary to know the thickness of the considered sample. With this methodology irregular soil samples (undeformed field samples) from Londrina region, north of Parana were studied. It was employed the two media method for the μ determination. It consists of the μ determination through the measurement of a gamma-ray beam attenuation by the sample sequentially immersed in two different media, with known and appropriately chosen attenuation coefficients. For comparison, the theoretical value of μ was calculated by the product of the mass attenuation coefficient, obtained by the WinXcom code, and the measured value of the density sample. This software employs the chemical composition of the samples and supplies a table of the mass attenuation coefficients versus the photon energy. To verify the validity of the two media method, compared with the simple gamma ray transmission method, regular pome stone samples were used. With these results for the attenuation coefficients and their respective deviations, it was possible to compare the two methods. In this way we concluded that the two media method is a good tool for the determination of the linear attenuation coefficient of irregular materials, particularly in the study of soils samples. (author)
Larsen, E.W.; Alcouffe, R.E.
1981-01-01
In this article a new linear characteristic (LC) spatial differencing scheme for the discrete ordinates equations in (x,y)-geometry is described and numerical comparisons are given with the diamond difference (DD) method. The LC method is more stable with mesh size and is generally much more accurate than the DD method on both fine and coarse meshes, for eigenvalue and deep penetration problems. The LC method is based on computations involving the exact solution of a cell problem which has spatially linear boundary conditions and interior source. The LC method is coupled to the diffusion synthetic acceleration (DSA) algorithm in that the linear variations of the source are determined in part by the results of the DSA calculation from the previous inner iteration. An inexpensive negative-flux fixup is used which has very little effect on the accuracy of the solution. The storage requirements for LC are essentially the same as that for DD, while the computational times for LC are generally less than twice the DD computational times for the same mesh. This increase in computational cost is offset if one computes LC solutions on somewhat coarser meshes than DD; the resulting LC solutions are still generally much more accurate than the DD solutions. (orig.) [de
A Golub-Kahan-type reduction method for matrix pairs
Hochstenbach, M.E.; Reichel, L.; Yu, X.
2015-01-01
We describe a novel method for reducing a pair of large matrices {A;B} to a pair of small matrices {H;K}. The method is an extension of Golub-Kahan bidiagonalization to matrix pairs, and simplifies to the latter method when B is the identity matrix. Applications to Tikhonov regularization of large
A Golub-Kahan-type reduction method for matrix pairs
Hochstenbach, M.E.; Reichel, L.; Yu, X.
2015-01-01
We describe a novel method for reducing a pair of large matrices {A,B} to a pair of small matrices {H,K}. The method is an extension of Golub–Kahan bidiagonalization to matrix pairs, and simplifies to the latter method when B is the identity matrix. Applications to Tikhonov regularization of large
The boomerang osteotomy -- a new method of reduction malarplasty.
Nakanishi, Yuji; Nagasao, Tomohisa; Shimizu, Yusuke; Miyamoto, Junpei; Kishi, Kazuo; Fukuta, Keizo
2012-05-01
To achieve optimal outcomes in reduction malarplasty, it is important to preserve the natural curvature of the cheek while reducing the zygoma prominence and the width of the midface. The present article introduces an effective technique that aims to achieve these purposes. Through an intraoral approach, boomerang-shaped bone incision lines are marked on the anterior aspect of the zygomatico-maxillary junction. The lines are placed medial to the most prominent part of the zygoma. The zygomatic arch is divided at its posterior part through a small incision made in the pre-auricular region. By performing these manoeuvres, a unit of bone-composed of a part of the zygoma body and zygomatic arch - is mobilised. The mobilised bone is shifted medially, reducing the width of the midface and making the zygoma region less prominent. After performing reduction malarplasty for 89 patients (10 males and 79 females) using this technique, clinical outcomes were evaluated. Outcomes of the treatment was optimal, with over 80% of the patients evaluating the results as excellent in terms of effectiveness in malar prominence, facial width and symmetry. Because the continuity of the main part of the zygoma body and zygomatic arch is preserved in our technique, medial transfer of the zygoma is enabled while preserving the natural curvature of the malar region and the superior-inferior position of the zygomatic arch. Because of these advantages, we recommend our technique as an effective technique of reduction malarplasty. Copyright © 2012 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.
Non-linear analysis of skew thin plate by finite difference method
Kim, Chi Kyung; Hwang, Myung Hwan
2012-01-01
This paper deals with a discrete analysis capability for predicting the geometrically nonlinear behavior of skew thin plate subjected to uniform pressure. The differential equations are discretized by means of the finite difference method which are used to determine the deflections and the in-plane stress functions of plates and reduced to several sets of linear algebraic simultaneous equations. For the geometrically non-linear, large deflection behavior of the plate, the non-linear plate theory is used for the analysis. An iterative scheme is employed to solve these quasi-linear algebraic equations. Several problems are solved which illustrate the potential of the method for predicting the finite deflection and stress. For increasing lateral pressures, the maximum principal tensile stress occurs at the center of the plate and migrates toward the corners as the load increases. It was deemed important to describe the locations of the maximum principal tensile stress as it occurs. The load-deflection relations and the maximum bending and membrane stresses for each case are presented and discussed
A method for fitting regression splines with varying polynomial order in the linear mixed model.
Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W
2006-02-15
The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.
Linear and nonlinear methods in modeling the aqueous solubility of organic compounds.
Catana, Cornel; Gao, Hua; Orrenius, Christian; Stouten, Pieter F W
2005-01-01
Solubility data for 930 diverse compounds have been analyzed using linear Partial Least Square (PLS) and nonlinear PLS methods, Continuum Regression (CR), and Neural Networks (NN). 1D and 2D descriptors from MOE package in combination with E-state or ISIS keys have been used. The best model was obtained using linear PLS for a combination between 22 MOE descriptors and 65 ISIS keys. It has a correlation coefficient (r2) of 0.935 and a root-mean-square error (RMSE) of 0.468 log molar solubility (log S(w)). The model validated on a test set of 177 compounds not included in the training set has r2 0.911 and RMSE 0.475 log S(w). The descriptors were ranked according to their importance, and at the top of the list have been found the 22 MOE descriptors. The CR model produced results as good as PLS, and because of the way in which cross-validation has been done it is expected to be a valuable tool in prediction besides PLS model. The statistics obtained using nonlinear methods did not surpass those got with linear ones. The good statistic obtained for linear PLS and CR recommends these models to be used in prediction when it is difficult or impossible to make experimental measurements, for virtual screening, combinatorial library design, and efficient leads optimization.
A Novel Method of Robust Trajectory Linearization Control Based on Disturbance Rejection
Xingling Shao
2014-01-01
Full Text Available A novel method of robust trajectory linearization control for a class of nonlinear systems with uncertainties based on disturbance rejection is proposed. Firstly, on the basis of trajectory linearization control (TLC method, a feedback linearization based control law is designed to transform the original tracking error dynamics to the canonical integral-chain form. To address the issue of reducing the influence made by uncertainties, with tracking error as input, linear extended state observer (LESO is constructed to estimate the tracking error vector, as well as the uncertainties in an integrated manner. Meanwhile, the boundedness of the estimated error is investigated by theoretical analysis. In addition, decoupled controller (which has the characteristic of well-tuning and simple form based on LESO is synthesized to realize the output tracking for closed-loop system. The closed-loop stability of the system under the proposed LESO-based control structure is established. Also, simulation results are presented to illustrate the effectiveness of the control strategy.
A Globally Convergent Matrix-Free Method for Constrained Equations and Its Linear Convergence Rate
Min Sun
2014-01-01
Full Text Available A matrix-free method for constrained equations is proposed, which is a combination of the well-known PRP (Polak-Ribière-Polyak conjugate gradient method and the famous hyperplane projection method. The new method is not only derivative-free, but also completely matrix-free, and consequently, it can be applied to solve large-scale constrained equations. We obtain global convergence of the new method without any differentiability requirement on the constrained equations. Compared with the existing gradient methods for solving such problem, the new method possesses linear convergence rate under standard conditions, and a relax factor γ is attached in the update step to accelerate convergence. Preliminary numerical results show that it is promising in practice.
A time-domain finite element model reduction method for viscoelastic linear and nonlinear systems
Antônio Marcos Gonçalves de Lima
Full Text Available AbstractMany authors have shown that the effective design of viscoelastic systems can be conveniently carried out by using modern mathematical models to represent the frequency- and temperature-dependent behavior of viscoelastic materials. However, in the quest for design procedures of real-word engineering structures, the large number of exact evaluations of the dynamic responses during iterative procedures, combined with the typically high dimensions of large finite element models, makes the numerical analysis very costly, sometimes unfeasible. It is especially true when the viscoelastic materials are used to reduce vibrations of nonlinear systems. As a matter of fact, which the resolution of the resulting nonlinear equations of motion with frequency- and temperature-dependent viscoelastic damping forces is an interesting, but hard-to-solve problem. Those difficulties motivate the present study, in which a time-domain condensation strategy of viscoelastic systems is addressed, where the viscoelastic behavior is modeled by using a four parameter fractional derivative model. After the discussion of various theoretical aspects, the exact and reduced time responses are calculated for a three-layer sandwich plate by considering nonlinear boundary conditions.
Sun, Lei; Jin, Hong-Yu; Tian, Run-Tao; Wang, Ming-Juan; Liu, Li-Na; Ye, Liu-Ping; Zuo, Tian-Tian; Ma, Shuang-Cheng
2017-01-01
Analysis of related substances in pharmaceutical chemicals and multi-components in traditional Chinese medicines needs bulk of reference substances to identify the chromatographic peaks accurately. But the reference substances are costly. Thus, the relative retention (RR) method has been widely adopted in pharmacopoeias and literatures for characterizing HPLC behaviors of those reference substances unavailable. The problem is it is difficult to reproduce the RR on different columns due to the error between measured retention time (t R ) and predicted t R in some cases. Therefore, it is useful to develop an alternative and simple method for prediction of t R accurately. In the present study, based on the thermodynamic theory of HPLC, a method named linear calibration using two reference substances (LCTRS) was proposed. The method includes three steps, procedure of two points prediction, procedure of validation by multiple points regression and sequential matching. The t R of compounds on a HPLC column can be calculated by standard retention time and linear relationship. The method was validated in two medicines on 30 columns. It was demonstrated that, LCTRS method is simple, but more accurate and more robust on different HPLC columns than RR method. Hence quality standards using LCTRS method are easy to reproduce in different laboratories with lower cost of reference substances.
Shuke, Noriyuki
1991-01-01
In hepatobiliary scintigraphy, kinetic model analysis, which provides kinetic parameters like hepatic extraction or excretion rate, have been done for quantitative evaluation of liver function. In this analysis, unknown model parameters are usually determined using nonlinear least square regression method (NLS method) where iterative calculation and initial estimate for unknown parameters are required. As a simple alternative to NLS method, direct integral linear least square regression method (DILS method), which can determine model parameters by a simple calculation without initial estimate, is proposed, and tested the applicability to analysis of hepatobiliary scintigraphy. In order to see whether DILS method could determine model parameters as good as NLS method, or to determine appropriate weight for DILS method, simulated theoretical data based on prefixed parameters were fitted to 1 compartment model using both DILS method with various weightings and NLS method. The parameter values obtained were then compared with prefixed values which were used for data generation. The effect of various weights on the error of parameter estimate was examined, and inverse of time was found to be the best weight to make the error minimum. When using this weight, DILS method could give parameter values close to those obtained by NLS method and both parameter values were very close to prefixed values. With appropriate weighting, the DILS method could provide reliable parameter estimate which is relatively insensitive to the data noise. In conclusion, the DILS method could be used as a simple alternative to NLS method, providing reliable parameter estimate. (author)
Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method
Desmal, Abdulla
2014-07-01
A contrast-source inversion scheme is proposed for microwave imaging of domains with sparse content. The scheme uses inexact Newton and linear shrinkage methods to account for the nonlinearity and ill-posedness of the electromagnetic inverse scattering problem, respectively. Thresholded shrinkage iterations are accelerated using a preconditioning technique. Additionally, during Newton iterations, the weight of the penalty term is reduced consistently with the quadratic convergence of the Newton method to increase accuracy and efficiency. Numerical results demonstrate the applicability of the proposed method.
A Projected Non-linear Conjugate Gradient Method for Interactive Inverse Kinematics
Engell-Nørregård, Morten; Erleben, Kenny
2009-01-01
Inverse kinematics is the problem of posing an articulated figure to obtain a wanted goal, without regarding inertia and forces. Joint limits are modeled as bounds on individual degrees of freedom, leading to a box-constrained optimization problem. We present A projected Non-linear Conjugate...... Gradient optimization method suitable for box-constrained optimization problems for inverse kinematics. We show application on inverse kinematics positioning of a human figure. Performance is measured and compared to a traditional Jacobian Transpose method. Visual quality of the developed method...
Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method
Desmal, Abdulla; Bagci, Hakan
2014-01-01
A contrast-source inversion scheme is proposed for microwave imaging of domains with sparse content. The scheme uses inexact Newton and linear shrinkage methods to account for the nonlinearity and ill-posedness of the electromagnetic inverse scattering problem, respectively. Thresholded shrinkage iterations are accelerated using a preconditioning technique. Additionally, during Newton iterations, the weight of the penalty term is reduced consistently with the quadratic convergence of the Newton method to increase accuracy and efficiency. Numerical results demonstrate the applicability of the proposed method.
Pseudoinverse preconditioners and iterative methods for large dense linear least-squares problems
Oskar Cahueñas
2013-05-01
Full Text Available We address the issue of approximating the pseudoinverse of the coefficient matrix for dynamically building preconditioning strategies for the numerical solution of large dense linear least-squares problems. The new preconditioning strategies are embedded into simple and well-known iterative schemes that avoid the use of the, usually ill-conditioned, normal equations. We analyze a scheme to approximate the pseudoinverse, based on Schulz iterative method, and also different iterative schemes, based on extensions of Richardson's method, and the conjugate gradient method, that are suitable for preconditioning strategies. We present preliminary numerical results to illustrate the advantages of the proposed schemes.
Linearized self-consistent quasiparticle GW method: Application to semiconductors and simple metals
Kutepov, A. L.
2017-01-01
We present a code implementing the linearized self-consistent quasiparticle GW method (QSGW) in the LAPW basis. Our approach is based on the linearization of the self-energy around zero frequency which differs it from the existing implementations of the QSGW method. The linearization allows us to use Matsubara frequencies instead of working on the real axis. This results in efficiency gains by switching to the imaginary time representation in the same way as in the space time method. The all electron LAPW basis set eliminates the need for pseudopotentials. We discuss the advantages of our approach, such as its N 3 scaling with the system size N, as well as its shortcomings. We apply our approach to study the electronic properties of selected semiconductors, insulators, and simple metals and show that our code produces the results very close to the previously published QSGW data. Our implementation is a good platform for further many body diagrammatic resummations such as the vertex-corrected GW approach and the GW+DMFT method.
Song, Xizi; Xu, Yanbin; Dong, Feng
2017-01-01
Electrical resistance tomography (ERT) is a promising measurement technique with important industrial and clinical applications. However, with limited effective measurements, it suffers from poor spatial resolution due to the ill-posedness of the inverse problem. Recently, there has been an increasing research interest in hybrid imaging techniques, utilizing couplings of physical modalities, because these techniques obtain much more effective measurement information and promise high resolution. Ultrasound modulated electrical impedance tomography (UMEIT) is one of the newly developed hybrid imaging techniques, which combines electric and acoustic modalities. A linearized image reconstruction method based on power density is proposed for UMEIT. The interior data, power density distribution, is adopted to reconstruct the conductivity distribution with the proposed image reconstruction method. At the same time, relating the power density change to the change in conductivity, the Jacobian matrix is employed to make the nonlinear problem into a linear one. The analytic formulation of this Jacobian matrix is derived and its effectiveness is also verified. In addition, different excitation patterns are tested and analyzed, and opposite excitation provides the best performance with the proposed method. Also, multiple power density distributions are combined to implement image reconstruction. Finally, image reconstruction is implemented with the linear back-projection (LBP) algorithm. Compared with ERT, with the proposed image reconstruction method, UMEIT can produce reconstructed images with higher quality and better quantitative evaluation results. (paper)
Yi Du
2017-03-01
Full Text Available C-core linear flux-switching permanent magnet (PM machines (LFSPMs are attracting more and more attention due to their advantages of simplicity and robustness of the secondary side, high power density and high torque density, in which both PMs and armature windings are housed in the primary side. The primary salient tooth wound with a concentrated winding consists of C-shaped iron core segments between which PMs are sandwiched and the magnetization directions of these PMs are adjacent and alternant in the horizontal direction. On the other hand, the secondary side is composed of a simple iron core with salient teeth so that it is very suitable for long stroke applications. However, the detent force of the C-core LFSPM machine is relatively high and the magnetic circuit is unbalanced due to the end effect. Thus, a new multiple additional tooth which consists of an active and a traditional passive additional tooth, is employed at each end side of the primary in this paper, so that the asymmetry due to end effect can be depressed and the detent force can be reduced by adjusting the passive additional tooth position. By using the finite element method, the characteristics and performances of the proposed machine are analyzed and verified.
A comparative study of two stochastic mode reduction methods
Stinis, Panagiotis
2005-09-01
We present a comparative study of two methods for thereduction of the dimensionality of a system of ordinary differentialequations that exhibits time-scale separation. Both methods lead to areduced system of stochastic differential equations. The novel feature ofthese methods is that they allow the use, in the reduced system, ofhigher order terms in the resolved variables. The first method, proposedby Majda, Timofeyev and Vanden-Eijnden, is based on an asymptoticstrategy developed by Kurtz. The second method is a short-memoryapproximation of the Mori-Zwanzig projection formalism of irreversiblestatistical mechanics, as proposed by Chorin, Hald and Kupferman. Wepresent conditions under which the reduced models arising from the twomethods should have similar predictive ability. We apply the two methodsto test cases that satisfy these conditions. The form of the reducedmodels and the numerical simulations show that the two methods havesimilar predictive ability as expected.
Chein-Shan Liu
2012-04-01
Full Text Available It is well known that the numerical algorithms of the steepest descent method (SDM, and the conjugate gradient method (CGM are effective for solving well-posed linear systems. However, they are vulnerable to noisy disturbance for solving ill-posed linear systems. We propose the modifications of SDM and CGM, namely the modified steepest descent method (MSDM, and the modified conjugate gradient method (MCGM. The starting point is an invariant manifold defined in terms of a minimum functional and a fictitious time-like variable; however, in the final stage we can derive a purely iterative algorithm including an acceleration parameter. Through the Hopf bifurcation, this parameter indeed plays a major role to switch the situation of slow convergence to a new situation that the functional is stepwisely decreased very fast. Several numerical examples are examined and compared with exact solutions, revealing that the new algorithms of MSDM and MCGM have good computational efficiency and accuracy, even for the highly ill-conditioned linear equations system with a large noise being imposed on the given data.
Leventis, Nicholas; Zhang, Guo-Hui; Rawashdeh, Abdel-Monem M.; Sotiriou-Leventis, Chariklia; Gray, Hugh R. (Technical Monitor)
2003-01-01
In analogy to 4-(para-substituted benzoyl)-N-methylpyridinium cations (1-X's), the title species (2-X's, -X = -OCH3, -CH3, -H, -Br, -COCH3, -NO2) undergo two reversible, well-separated (E(sub 1/2) greater than or equal to 650 mV) one-electron reductions. The effect of substitution on the reduction potentials of 2-X's is much weaker than the effect of the same substituents on 1-X's: the Hammett rho-values are 0.80 and 0.93 for the 1st- and 2nd-e reduction of 2-X's vs. 2.3 and 3.3 for the same reductions of 1-X's, respectively. Importantly, the nitro group of 2-NO2 undergoes reduction before the 2nd-e reduction of the 4-benzoylpyridinium system. These results suggest that the redox potentials of the 4-benzoylpyridinium system can be course-tuned via p-benzoyl substitution and fine-tuned via para-benzyl substitution. Introducing the recently derived substituent constant of the -NO2(sup)- group (sigma para-NO2(sup)- = -0.97) yields an excellent correlation for the 3rd-e reduction of 2- NO2 (corresponding to the reduction of the carbonyl group) with the 2nd-e reduction of the other 2-X's, and confirms the electron donating properties of -NO2(sup)-.
Linear programming models and methods of matrix games with payoffs of triangular fuzzy numbers
Li, Deng-Feng
2016-01-01
This book addresses two-person zero-sum finite games in which the payoffs in any situation are expressed with fuzzy numbers. The purpose of this book is to develop a suite of effective and efficient linear programming models and methods for solving matrix games with payoffs in fuzzy numbers. Divided into six chapters, it discusses the concepts of solutions of matrix games with payoffs of intervals, along with their linear programming models and methods. Furthermore, it is directly relevant to the research field of matrix games under uncertain economic management. The book offers a valuable resource for readers involved in theoretical research and practical applications from a range of different fields including game theory, operational research, management science, fuzzy mathematical programming, fuzzy mathematics, industrial engineering, business and social economics. .
Simple estimating method of damages of concrete gravity dam based on linear dynamic analysis
Sasaki, T.; Kanenawa, K.; Yamaguchi, Y. [Public Works Research Institute, Tsukuba, Ibaraki (Japan). Hydraulic Engineering Research Group
2004-07-01
Due to the occurrence of large earthquakes like the Kobe Earthquake in 1995, there is a strong need to verify seismic resistance of dams against much larger earthquake motions than those considered in the present design standard in Japan. Problems exist in using nonlinear analysis to evaluate the safety of dams including: that the influence which the set material properties have on the results of nonlinear analysis is large, and that the results of nonlinear analysis differ greatly according to the damage estimation models or analysis programs. This paper reports the evaluation indices based on a linear dynamic analysis method and the characteristics of the progress of cracks in concrete gravity dams with different shapes using a nonlinear dynamic analysis method. The study concludes that if simple linear dynamic analysis is appropriately conducted to estimate tensile stress at potential locations of initiating cracks, the damage due to cracks would be predicted roughly. 4 refs., 1 tab., 13 figs.
A Low-Complexity ESPRIT-Based DOA Estimation Method for Co-Prime Linear Arrays.
Sun, Fenggang; Gao, Bin; Chen, Lizhen; Lan, Peng
2016-08-25
The problem of direction-of-arrival (DOA) estimation is investigated for co-prime array, where the co-prime array consists of two uniform sparse linear subarrays with extended inter-element spacing. For each sparse subarray, true DOAs are mapped into several equivalent angles impinging on the traditional uniform linear array with half-wavelength spacing. Then, by applying the estimation of signal parameters via rotational invariance technique (ESPRIT), the equivalent DOAs are estimated, and the candidate DOAs are recovered according to the relationship among equivalent and true DOAs. Finally, the true DOAs are estimated by combining the results of the two subarrays. The proposed method achieves a better complexity-performance tradeoff as compared to other existing methods.
Acceleration of step and linear discontinuous schemes for the method of characteristics in DRAGON5
Alain Hébert
2017-09-01
Full Text Available The applicability of the algebraic collapsing acceleration (ACA technique to the method of characteristics (MOC in cases with scattering anisotropy and/or linear sources was investigated. Previously, the ACA was proven successful in cases with isotropic scattering and uniform (step sources. A presentation is first made of the MOC implementation, available in the DRAGON5 code. Two categories of schemes are available for integrating the propagation equations: (1 the first category is based on exact integration and leads to the classical step characteristics (SC and linear discontinuous characteristics (LDC schemes and (2 the second category leads to diamond differencing schemes of various orders in space. The acceleration of these MOC schemes using a combination of the generalized minimal residual [GMRES(m] method preconditioned with the ACA technique was focused on. Numerical results are provided for a two-dimensional (2D eight-symmetry pressurized water reactor (PWR assembly mockup in the context of the DRAGON5 code.
Stability of numerical method for semi-linear stochastic pantograph differential equations
Yu Zhang
2016-01-01
Full Text Available Abstract As a particular expression of stochastic delay differential equations, stochastic pantograph differential equations have been widely used in nonlinear dynamics, quantum mechanics, and electrodynamics. In this paper, we mainly study the stability of analytical solutions and numerical solutions of semi-linear stochastic pantograph differential equations. Some suitable conditions for the mean-square stability of an analytical solution are obtained. Then we proved the general mean-square stability of the exponential Euler method for a numerical solution of semi-linear stochastic pantograph differential equations, that is, if an analytical solution is stable, then the exponential Euler method applied to the system is mean-square stable for arbitrary step-size h > 0 $h>0$ . Numerical examples further illustrate the obtained theoretical results.
Projective-Dual Method for Solving Systems of Linear Equations with Nonnegative Variables
Ganin, B. V.; Golikov, A. I.; Evtushenko, Yu. G.
2018-02-01
In order to solve an underdetermined system of linear equations with nonnegative variables, the projection of a given point onto its solutions set is sought. The dual of this problem—the problem of unconstrained maximization of a piecewise-quadratic function—is solved by Newton's method. The problem of unconstrained optimization dual of the regularized problem of finding the projection onto the solution set of the system is considered. A connection of duality theory and Newton's method with some known algorithms of projecting onto a standard simplex is shown. On the example of taking into account the specifics of the constraints of the transport linear programming problem, the possibility to increase the efficiency of calculating the generalized Hessian matrix is demonstrated. Some examples of numerical calculations using MATLAB are presented.
Catalyst and method for reduction of nitrogen oxides
Ott, Kevin C [Los Alamos, NM
2008-05-27
A Selective Catalytic Reduction (SCR) catalyst was prepared by slurry coating ZSM-5 zeolite onto a cordierite monolith, then subliming an iron salt onto the zeolite, calcining the monolith, and then dipping the monolith either into an aqueous solution of manganese nitrate and cerium nitrate and then calcining, or by similar treatment with separate solutions of manganese nitrate and cerium nitrate. The supported catalyst containing iron, manganese, and cerium showed 80 percent conversion at 113 degrees Celsius of a feed gas containing nitrogen oxides having 4 parts NO to one part NO.sub.2, about one equivalent ammonia, and excess oxygen; conversion improved to 94 percent at 147 degrees Celsius. N.sub.2O was not detected (detection limit: 0.6 percent N.sub.2O).
Stochastic Least-Squares Petrov--Galerkin Method for Parameterized Linear Systems
Lee, Kookjin [Univ. of Maryland, College Park, MD (United States). Dept. of Computer Science; Carlberg, Kevin [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Elman, Howard C. [Univ. of Maryland, College Park, MD (United States). Dept. of Computer Science and Inst. for Advanced Computer Studies
2018-03-29
Here, we consider the numerical solution of parameterized linear systems where the system matrix, the solution, and the right-hand side are parameterized by a set of uncertain input parameters. We explore spectral methods in which the solutions are approximated in a chosen finite-dimensional subspace. It has been shown that the stochastic Galerkin projection technique fails to minimize any measure of the solution error. As a remedy for this, we propose a novel stochatic least-squares Petrov--Galerkin (LSPG) method. The proposed method is optimal in the sense that it produces the solution that minimizes a weighted $\\ell^2$-norm of the residual over all solutions in a given finite-dimensional subspace. Moreover, the method can be adapted to minimize the solution error in different weighted $\\ell^2$-norms by simply applying a weighting function within the least-squares formulation. In addition, a goal-oriented seminorm induced by an output quantity of interest can be minimized by defining a weighting function as a linear functional of the solution. We establish optimality and error bounds for the proposed method, and extensive numerical experiments show that the weighted LSPG method outperforms other spectral methods in minimizing corresponding target weighted norms.
Discussion on calculation method of overburden cover for radon reduction
Liang Jianlong; Zhou Xinghuo; Zhou Ju; Liu Huijuan
2010-01-01
The article collects a large number of experimental results from domestic researchers with regard to soil overburden experimental methods. Based on analyzing experimental results, some questions in determining requirements for overburden cover thickness, data processing method and negative intercept have been dis- cussed. (authors)
Xiangdong Liu
2016-05-01
Full Text Available A novel modular arc-linear flux-switching permanent-magnet motor (MAL-FSPM used for scanning system instead of reduction gearboxes and kinematic mechanisms is proposed and researched in this paper by the finite element method (FEM. The MAL-FSPM combines characteristics of flux-switching permanent-magnet motor and linear motor and can realize the direct driving and limited angular movement. Structure and operation principle of the MAL-FSPM are analyzed. Cogging torque model of the MAL-FSPM is established. The characteristics of cogging torque and torque ripple are investigated for: (1 distance (dend between left end of rotor and left end of stator is more than two rotor tooth pitch (τp; and (2 dend is less than two rotor tooth pitch. Cogging torque is an important component of torque ripple and the period ratio of the cogging torque to the back electromotive force (EMF equals one for the MAL-FSPM before optimization. In order to reduce the torque ripple as much as possible and affect the back EMF as little as possible, influence of period ratio of cogging torque to back EMF on rotor step skewing is investigated. Rotor tooth width and stator slot open width are optimized to increase the period ratio of cogging torque to back EMF. After the optimization, torque ripple is decreased by 79.8% for dend > τp and torque ripple is decreased by 49.7% for dend < τp. Finally, 3D FEM model is established to verify the 2D results.
2016-11-22
structure of the graph, we replace the ℓ1- norm by the nonconvex Capped -ℓ1 norm , and obtain the Generalized Capped -ℓ1 regularized logistic regression...X. M. Yuan. Linearized augmented lagrangian and alternating direction methods for nuclear norm minimization. Mathematics of Computation, 82(281):301...better approximations of ℓ0- norm theoretically and computationally beyond ℓ1- norm , for example, the compressive sensing (Xiao et al., 2011). The
James W. Hardin; Henrik Schmeidiche; Raymond J. Carroll
2003-01-01
This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). Discussion will include specified measurement error, measurement error estimated by replicate error-prone proxies, and measurement error estimated by instrumental variables. The discussion focuses on s...
An enhanced finite volume method to model 2D linear elastic structures
Suliman, Ridhwaan
2014-04-01
Full Text Available . Suliman) Preprint submitted to Applied Mathematical Modelling July 22, 2013 Keywords: finite volume, finite element, locking, error analysis 1. Introduction Since the 1960s, the finite element method has mainly been used for modelling the mechanics... formulation provides higher accuracy 2 for displacement solutions. It is well known that the linear finite element formulation suffers from sensitivity to element aspect ratio or shear locking when subjected to bend- ing [16]. Fallah [8] and Wheel [6] present...
Solution of second order linear fuzzy difference equation by Lagrange's multiplier method
Sankar Prasad Mondal
2016-06-01
Full Text Available In this paper we execute the solution procedure for second order linear fuzzy difference equation by Lagrange's multiplier method. In crisp sense the difference equation are easy to solve, but when we take in fuzzy sense it forms a system of difference equation which is not so easy to solve. By the help of Lagrange's multiplier we can solved it easily. The results are illustrated by two different numerical examples and followed by two applications.
Linear motion device and method for inserting and withdrawing control rods
Smith, J.E.
Disclosed is a linear motion device and more specifically a control rod drive mechanism (CRDM) for inserting and withdrawing control rods into a reactor core. The CRDM and method disclosed is capable of independently and sequentially positioning two sets of control rods with a single motor stator and rotor. The CRDM disclosed can control more than one control rod lead screw without incurring a substantial increase in the size of the mechanism.
Linearized self-consistent quasiparticle GW method: Application to semiconductors and simple metals
Kutepov, A. L.; Oudovenko, V. S.; Kotliar, G.
2017-10-01
We present a code implementing the linearized quasiparticle self-consistent GW method (LQSGW) in the LAPW basis. Our approach is based on the linearization of the self-energy around zero frequency which differs it from the existing implementations of the QSGW method. The linearization allows us to use Matsubara frequencies instead of working on the real axis. This results in efficiency gains by switching to the imaginary time representation in the same way as in the space time method. The all electron LAPW basis set eliminates the need for pseudopotentials. We discuss the advantages of our approach, such as its N3 scaling with the system size N, as well as its shortcomings. We apply our approach to study the electronic properties of selected semiconductors, insulators, and simple metals and show that our code produces the results very close to the previously published QSGW data. Our implementation is a good platform for further many body diagrammatic resummations such as the vertex-corrected GW approach and the GW+DMFT method. Program Files doi:http://dx.doi.org/10.17632/cpchkfty4w.1 Licensing provisions: GNU General Public License Programming language: Fortran 90 External routines/libraries: BLAS, LAPACK, MPI (optional) Nature of problem: Direct implementation of the GW method scales as N4 with the system size, which quickly becomes prohibitively time consuming even in the modern computers. Solution method: We implemented the GW approach using a method that switches between real space and momentum space representations. Some operations are faster in real space, whereas others are more computationally efficient in the reciprocal space. This makes our approach scale as N3. Restrictions: The limiting factor is usually the memory available in a computer. Using 10 GB/core of memory allows us to study the systems up to 15 atoms per unit cell.
On the economical solution method for a system of linear algebraic equations
Jan Awrejcewicz
2004-01-01
Full Text Available The present work proposes a novel optimal and exact method of solving large systems of linear algebraic equations. In the approach under consideration, the solution of a system of algebraic linear equations is found as a point of intersection of hyperplanes, which needs a minimal amount of computer operating storage. Two examples are given. In the first example, the boundary value problem for a three-dimensional stationary heat transfer equation in a parallelepiped in ℝ3 is considered, where boundary value problems of first, second, or third order, or their combinations, are taken into account. The governing differential equations are reduced to algebraic ones with the help of the finite element and boundary element methods for different meshes applied. The obtained results are compared with known analytical solutions. The second example concerns computation of a nonhomogeneous shallow physically and geometrically nonlinear shell subject to transversal uniformly distributed load. The partial differential equations are reduced to a system of nonlinear algebraic equations with the error of O(hx12+hx22. The linearization process is realized through either Newton method or differentiation with respect to a parameter. In consequence, the relations of the boundary condition variations along the shell side and the conditions for the solution matching are reported.
Franklin, Timothy C; Granata, Kevin P; Madigan, Michael L; Hendricks, Scott L
2008-08-01
Linear stability methods were applied to a biomechanical model of the human musculoskeletal spine to investigate effects of reflex gain and reflex delay on stability. Equations of motion represented a dynamic 18 degrees-of-freedom rigid-body model with time-delayed reflexes. Optimal muscle activation levels were identified by minimizing metabolic power with the constraints of equilibrium and stability with zero reflex time delay. Muscle activation levels and associated muscle forces were used to find the delay margin, i.e., the maximum reflex delay for which the system was stable. Results demonstrated that stiffness due to antagonistic co-contraction necessary for stability declined with increased proportional reflex gain. Reflex delay limited the maximum acceptable proportional reflex gain, i.e., long reflex delay required smaller maximum reflex gain to avoid instability. As differential reflex gain increased, there was a small increase in acceptable reflex delay. However, differential reflex gain with values near intrinsic damping caused the delay margin to approach zero. Forward-dynamic simulations of the fully nonlinear time-delayed system verified the linear results. The linear methods accurately found the delay margin below which the nonlinear system was asymptotically stable. These methods may aid future investigations in the role of reflexes in musculoskeletal stability.
An Improved Method for Solving Multiobjective Integer Linear Fractional Programming Problem
Meriem Ait Mehdi
2014-01-01
Full Text Available We describe an improvement of Chergui and Moulaï’s method (2008 that generates the whole efficient set of a multiobjective integer linear fractional program based on the branch and cut concept. The general step of this method consists in optimizing (maximizing without loss of generality one of the fractional objective functions over a subset of the original continuous feasible set; then if necessary, a branching process is carried out until obtaining an integer feasible solution. At this stage, an efficient cut is built from the criteria’s growth directions in order to discard a part of the feasible domain containing only nonefficient solutions. Our contribution concerns firstly the optimization process where a linear program that we define later will be solved at each step rather than a fractional linear program. Secondly, local ideal and nadir points will be used as bounds to prune some branches leading to nonefficient solutions. The computational experiments show that the new method outperforms the old one in all the treated instances.
American Society for Testing and Materials. Philadelphia
1995-01-01
1.1 This test method covers the interferometric determination of linear thermal expansion of premelted glaze frits and fired ceramic whiteware materials at temperatures lower than 1000°C (1830°F). 1.2 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.
Massimiliano Ferraioli
2016-01-01
Full Text Available Although the most commonly used isolation systems exhibit nonlinear inelastic behaviour, the equivalent linear elastic analysis is commonly used in the design and assessment of seismic-isolated structures. The paper investigates if the linear elastic model is suitable for the analysis of a seismically isolated multiple building structure. To this aim, its computed responses were compared with those calculated by nonlinear dynamic analysis. A common base isolation plane connects the isolation bearings supporting the adjacent structures. In this situation, the conventional equivalent linear elastic analysis may have some problems of accuracy because this method is calibrated on single base-isolated structures. Moreover, the torsional characteristics of the combined system are significantly different from those of separate isolated buildings. A number of numerical simulations and parametric studies under earthquake excitations were performed. The accuracy of the dynamic response obtained by the equivalent linear elastic model was calculated by the magnitude of the error with respect to the corresponding response considering the nonlinear behaviour of the isolation system. The maximum displacements at the isolation level, the maximum interstorey drifts, and the peak absolute acceleration were selected as the most important response measures. The influence of mass eccentricity, torsion, and high-modes effects was finally investigated.
A simple and efficient electrochemical reductive method for ...
Administrator
This approach opens up a new, practical and green reducing method to prepare large- scale graphene. ... has the following significant advantages: (1) It is simple to operate. .... The authors thank the National High Technology Research.
Computerized simulation methods for dose reduction, in radiodiagnosis
Brochi, M.A.C.
1990-01-01
The present work presents computational methods that allow the simulation of any situation encountered in diagnostic radiology. Parameters of radiographic techniques that yield a standard radiographic image, previously chosen, and so could compare the dose of radiation absorbed by the patient is studied. Initially the method was tested on a simple system composed of 5.0 cm of water and 1.0 mm of aluminium and, after verifying experimentally its validity, it was applied in breast and arm fracture radiographs. It was observed that the choice of the filter material is not an important factor, because analogous behaviours were presented by aluminum, iron, copper, gadolinium, and other filters. A method of comparison of materials based on the spectral match is shown. Both the results given by this simulation method and the experimental measurements indicate an equivalence of brass and copper, both more efficient than aluminium, in terms of exposition time, but not of dose. (author)
Cost reduction by using budgeting via the Kaizen method
Dorina Budugan; Iuliana Georgescu
2009-01-01
In the current conditions, continuous improvement is one of the main issues faced by the manag-ers of organizations. The Japanese use the term kaizen to designate continuous improvement. Budgeting via the kaizen method explicitly integrates improvement throughout the period budgeted in the budget data. Budget explanation via the kaizen method refers, on the one hand, to budgeting for the purposes of continuously improving the number of work hours per product unit, and, on the other hand, to t...
An Improved Isotropic Periodic Sum Method That Uses Linear Combinations of Basis Potentials
Takahashi, Kazuaki Z.
2012-11-13
Isotropic periodic sum (IPS) is a technique that calculates long-range interactions differently than conventional lattice sum methods. The difference between IPS and lattice sum methods lies in the shape and distribution of remote images for long-range interaction calculations. The images used in lattice sum calculations are identical to those generated from periodic boundary conditions and are discretely positioned at lattice points in space. The images for IPS calculations are "imaginary", which means they do not explicitly exist in a simulation system and are distributed isotropically and periodically around each particle. Two different versions of the original IPS method exist. The IPSn method is applied to calculations for point charges, whereas the IPSp method calculates polar molecules. However, both IPSn and IPSp have their advantages and disadvantages in simulating bulk water or water-vapor interfacial systems. In bulk water systems, the cutoff radius effect of IPSn strongly affects the configuration, whereas IPSp does not provide adequate estimations of water-vapor interfacial systems unless very long cutoff radii are used. To extend the applicability of the IPS technique, an improved IPS method, which has better accuracy in both homogeneous and heterogeneous systems has been developed and named the linear-combination-based isotropic periodic sum (LIPS) method. This improved IPS method uses linear combinations of basis potentials. We performed molecular dynamics (MD) simulations of bulk water and water-vapor interfacial systems to evaluate the accuracy of the LIPS method. For bulk water systems, the LIPS method has better accuracy than IPSn in estimating thermodynamic and configurational properties without the countercharge assumption, which is used for IPSp. For water-vapor interfacial systems, LIPS has better accuracy than IPSp and properly estimates thermodynamic and configurational properties. In conclusion, the LIPS method can successfully estimate
An Improved Isotropic Periodic Sum Method That Uses Linear Combinations of Basis Potentials
Takahashi, Kazuaki Z.; Narumi, Tetsu; Suh, Donguk; Yasuoka, Kenji
2012-01-01
Isotropic periodic sum (IPS) is a technique that calculates long-range interactions differently than conventional lattice sum methods. The difference between IPS and lattice sum methods lies in the shape and distribution of remote images for long-range interaction calculations. The images used in lattice sum calculations are identical to those generated from periodic boundary conditions and are discretely positioned at lattice points in space. The images for IPS calculations are "imaginary", which means they do not explicitly exist in a simulation system and are distributed isotropically and periodically around each particle. Two different versions of the original IPS method exist. The IPSn method is applied to calculations for point charges, whereas the IPSp method calculates polar molecules. However, both IPSn and IPSp have their advantages and disadvantages in simulating bulk water or water-vapor interfacial systems. In bulk water systems, the cutoff radius effect of IPSn strongly affects the configuration, whereas IPSp does not provide adequate estimations of water-vapor interfacial systems unless very long cutoff radii are used. To extend the applicability of the IPS technique, an improved IPS method, which has better accuracy in both homogeneous and heterogeneous systems has been developed and named the linear-combination-based isotropic periodic sum (LIPS) method. This improved IPS method uses linear combinations of basis potentials. We performed molecular dynamics (MD) simulations of bulk water and water-vapor interfacial systems to evaluate the accuracy of the LIPS method. For bulk water systems, the LIPS method has better accuracy than IPSn in estimating thermodynamic and configurational properties without the countercharge assumption, which is used for IPSp. For water-vapor interfacial systems, LIPS has better accuracy than IPSp and properly estimates thermodynamic and configurational properties. In conclusion, the LIPS method can successfully estimate
One step linear reconstruction method for continuous wave diffuse optical tomography
Ukhrowiyah, N.; Yasin, M.
2017-09-01
The method one step linear reconstruction method for continuous wave diffuse optical tomography is proposed and demonstrated for polyvinyl chloride based material and breast phantom. Approximation which used in this method is selecting regulation coefficient and evaluating the difference between two states that corresponding to the data acquired without and with a change in optical properties. This method is used to recovery of optical parameters from measured boundary data of light propagation in the object. The research is demonstrated by simulation and experimental data. Numerical object is used to produce simulation data. Chloride based material and breast phantom sample is used to produce experimental data. Comparisons of results between experiment and simulation data are conducted to validate the proposed method. The results of the reconstruction image which is produced by the one step linear reconstruction method show that the image reconstruction almost same as the original object. This approach provides a means of imaging that is sensitive to changes in optical properties, which may be particularly useful for functional imaging used continuous wave diffuse optical tomography of early diagnosis of breast cancer.
Reduction of scour around bridge piers using a modified method for vortex reduction
Entesar A.S. EL-Ghorab
2013-09-01
Full Text Available The current study presents a modified method to reduce the scour depth in front of the bridge piers. The idea of this method is based on reducing the stagnation of the flow and vortex formation in front of the pier. Therefore, the pressure difference around the pier is used for driving the flow through an arrangement of openings in front and connected to the openings along the pier’s side. A test program was planned using an experimental flume at the Hydraulics Research Institute (HRI and three hundred thirty six runs were conducted. Three different pier shapes, circular, square, and rectangular, provided with different openings arrangement and vertical spacing are tested. This method showed that the scour depth is reduced by 45% and also the volume of the scoured material is decreased up to 64%. These results were obtained using opening diameter of 20% of the pier width (w and vertical spacing equals the pier width (w. Also, a dimensionless regression equation was developed based on the obtained results. These findings when implemented in the field can easily safeguard the bridge piers and dramatically reduce the maintenance efforts and costs as well as improve the hydraulic performance of the water structure.
A Posteriori Error Estimation for Finite Element Methods and Iterative Linear Solvers
Melboe, Hallgeir
2001-10-01
This thesis addresses a posteriori error estimation for finite element methods and iterative linear solvers. Adaptive finite element methods have gained a lot of popularity over the last decades due to their ability to produce accurate results with limited computer power. In these methods a posteriori error estimates play an essential role. Not only do they give information about how large the total error is, they also indicate which parts of the computational domain should be given a more sophisticated treatment in order to reduce the error. A posteriori error estimates are traditionally aimed at estimating the global error, but more recently so called goal oriented error estimators have been shown a lot of interest. The name reflects the fact that they estimate the error in user-defined local quantities. In this thesis the main focus is on global error estimators for highly stretched grids and goal oriented error estimators for flow problems on regular grids. Numerical methods for partial differential equations, such as finite element methods and other similar techniques, typically result in a linear system of equations that needs to be solved. Usually such systems are solved using some iterative procedure which due to a finite number of iterations introduces an additional error. Most such algorithms apply the residual in the stopping criterion, whereas the control of the actual error may be rather poor. A secondary focus in this thesis is on estimating the errors that are introduced during this last part of the solution procedure. The thesis contains new theoretical results regarding the behaviour of some well known, and a few new, a posteriori error estimators for finite element methods on anisotropic grids. Further, a goal oriented strategy for the computation of forces in flow problems is devised and investigated. Finally, an approach for estimating the actual errors associated with the iterative solution of linear systems of equations is suggested. (author)
A Robust Non-Gaussian Data Assimilation Method for Highly Non-Linear Models
Elias D. Nino-Ruiz
2018-03-01
Full Text Available In this paper, we propose an efficient EnKF implementation for non-Gaussian data assimilation based on Gaussian Mixture Models and Markov-Chain-Monte-Carlo (MCMC methods. The proposed method works as follows: based on an ensemble of model realizations, prior errors are estimated via a Gaussian Mixture density whose parameters are approximated by means of an Expectation Maximization method. Then, by using an iterative method, observation operators are linearized about current solutions and posterior modes are estimated via a MCMC implementation. The acceptance/rejection criterion is similar to that of the Metropolis-Hastings rule. Experimental tests are performed on the Lorenz 96 model. The results show that the proposed method can decrease prior errors by several order of magnitudes in a root-mean-square-error sense for nearly sparse or dense observational networks.
Incineration method for volume reduction and disposal of transuranic waste
Borham, B.M.
1985-01-01
The Process Experimental Pilot Plant (PREPP) at Idaho National Engineering Laboratory (INEL) is designed to process 7 TPD of transuranic (TRU) waste producing 8.5 TPD of cemented waste and 4100 ACFM of combustion gases with a volume reduction of up to 17:1. The waste and its container are shredded then fed to a rotary kiln heated to 1700 0 F, then cooled and classified by a trommel screen. The fine portion is mixed with a cement grout which is placed with the coarse portion in steel drums for disposal at the Waste Isolation Pilot Plant (WIPP). The kiln off-gas is reheated to 2000 0 F to destroy any remaining hydrocarbons and toxic volatiles. The gases are cooled and passed in a venturi scrubber to remove particulates and corrosive gases. The venturi off-gas is passed through a mist eliminator and is reheated to 50 0 F above the dew point prior to passing through a High Efficiency Particulate Air (HEPA) filter. The scrub solution is concentrated to 25% solids by an inertial filter. The sludge containing the combustion chemical contaminants is encapsulated with the residue of the incinerated waste
Noack, K.
1982-01-01
The perturbation source method may be a powerful Monte-Carlo means to calculate small effects in a particle field. In a preceding paper we have formulated this methos in inhomogeneous linear particle transport problems describing the particle fields by solutions of Fredholm integral equations and have derived formulae for the second moment of the difference event point estimator. In the present paper we analyse the general structure of its variance, point out the variance peculiarities, discuss the dependence on certain transport games and on generation procedures of the auxiliary particles and draw conclusions to improve this method
Method for the mechanical axis alignment of the linear induction accelerator
Li Hong; China Academy of Engineering Physics, Mianyang; Yao Jin; Liu Yunlong; Zhang Linwen; Deng Jianjun
2004-01-01
Accurate mechanical axis alignment is a basic requirement for assembling a linear induction accelerator (LIA). The total length of an LIA is usually over thirty or fifty meters, and it consists of many induction cells. By using a laser tracker a new method of mechanical axis alignment for LIA is established to achieve the high accuracy. This paper introduces the method and gives implementation step and point position measure errors of the mechanical axis alignment. During the alignment process a 55 m-long alignment control survey net is built, and the theoretic revision of the coordinate of the control survey net is presented. (authors)
Reproducing kernel method with Taylor expansion for linear Volterra integro-differential equations
Azizallah Alvandi
2017-06-01
Full Text Available This research aims of the present a new and single algorithm for linear integro-differential equations (LIDE. To apply the reproducing Hilbert kernel method, there is made an equivalent transformation by using Taylor series for solving LIDEs. Shown in series form is the analytical solution in the reproducing kernel space and the approximate solution $ u_{N} $ is constructed by truncating the series to $ N $ terms. It is easy to prove the convergence of $ u_{N} $ to the analytical solution. The numerical solutions from the proposed method indicate that this approach can be implemented easily which shows attractive features.
Nagy, D.L.; Dengler, J.; Ritter, G.
1988-01-01
A model-independent evaluation of the components of poorly resolved Moessbauer spectra based on a linear combination method is possible if there is a parameter as a function of which the shape of the individual components do not but their intensities do change and the dependence of the intensities on this parameter is known. The efficiency of the method is demonstrated on the example of low temperature magnetically split spectra of the high-T c superconductor YBa 2 (Cu 0.9 Fe 0 .1 ) 3 O 7-y . (author)
Linear dynamic analysis of arbitrary thin shells modal superposition by using finite element method
Goncalves Filho, O.J.A.
1978-11-01
The linear dynamic behaviour of arbitrary thin shells by the Finite Element Method is studied. Plane triangular elements with eighteen degrees of freedom each are used. The general equations of movement are obtained from the Hamilton Principle and solved by the Modal Superposition Method. The presence of a viscous type damping can be considered by means of percentages of the critical damping. An automatic computer program was developed to provide the vibratory properties and the dynamic response to several types of deterministic loadings, including temperature effects. The program was written in FORTRAN IV for the Burroughs B-6700 computer. (author)
Reduction Methods for Real-time Simulations in Hybrid Testing
Andersen, Sebastian
2016-01-01
Hybrid testing constitutes a cost-effective experimental full scale testing method. The method was introduced in the 1960's by Japanese researchers, as an alternative to conventional full scale testing and small scale material testing, such as shake table tests. The principle of the method...... is performed on a glass fibre reinforced polymer composite box girder. The test serves as a pilot test for prospective real-time tests on a wind turbine blade. The Taylor basis is implemented in the test, used to perform the numerical simulations. Despite of a number of introduced errors in the real...... is to divide a structure into a physical substructure and a numerical substructure, and couple these in a test. If the test is conducted in real-time it is referred to as real time hybrid testing. The hybrid testing concept has developed significantly since its introduction in the 1960', both with respect...
Shen, Junlin; Du, Xiangying; Guo, Daode; Cao, Lizhen; Gao, Yan; Bai, Mei; Li, Pengyu; Liu, Jiabin; Li, Kuncheng
2013-01-01
Purpose: To investigate the potential of noise-based tube current reduction method with iterative reconstruction to reduce radiation exposure while achieving consistent image quality in coronary CT angiography (CCTA). Materials and methods: 294 patients underwent CCTA on a 64-detector row CT equipped with iterative reconstruction. 102 patients with fixed tube current were assigned to Group 1, which was used to establish noise-based tube current modulation formulas, where tube current was modulated by the noise of test bolus image. 192 patients with noise-based tube current were randomly assigned to Group 2 and Group 3. Filtered back projection was applied for Group 2 and iterative reconstruction for Group 3. Qualitative image quality was assessed with a 5 point score. Image noise, signal intensity, volume CT dose index, and dose-length product were measured. Results: The noise-based tube current modulation formulas were established through regression analysis using image noise measurements in Group 1. Image noise was precisely maintained at the target value of 35.00 HU with small interquartile ranges for Group 2 (34.17–35.08 HU) and Group 3 (34.34–35.03 HU), while it was from 28.41 to 36.49 HU for Group 1. All images in the three groups were acceptable for diagnosis. A relative 14% and 41% reduction in effective dose for Group 2 and Group 3 were observed compared with Group 1. Conclusion: Adequate image quality could be maintained at a desired and consistent noise level with overall 14% dose reduction using noise-based tube current reduction method. The use of iterative reconstruction further achieved approximately 40% reduction in effective dose
A Bayes linear Bayes method for estimation of correlated event rates.
Quigley, John; Wilson, Kevin J; Walls, Lesley; Bedford, Tim
2013-12-01
Typically, full Bayesian estimation of correlated event rates can be computationally challenging since estimators are intractable. When estimation of event rates represents one activity within a larger modeling process, there is an incentive to develop more efficient inference than provided by a full Bayesian model. We develop a new subjective inference method for correlated event rates based on a Bayes linear Bayes model under the assumption that events are generated from a homogeneous Poisson process. To reduce the elicitation burden we introduce homogenization factors to the model and, as an alternative to a subjective prior, an empirical method using the method of moments is developed. Inference under the new method is compared against estimates obtained under a full Bayesian model, which takes a multivariate gamma prior, where the predictive and posterior distributions are derived in terms of well-known functions. The mathematical properties of both models are presented. A simulation study shows that the Bayes linear Bayes inference method and the full Bayesian model provide equally reliable estimates. An illustrative example, motivated by a problem of estimating correlated event rates across different users in a simple supply chain, shows how ignoring the correlation leads to biased estimation of event rates. © 2013 Society for Risk Analysis.
Thin Cloud Detection Method by Linear Combination Model of Cloud Image
Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.
2018-04-01
The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.
A linear complementarity method for the solution of vertical vehicle-track interaction
Zhang, Jian; Gao, Qiang; Wu, Feng; Zhong, Wan-Xie
2018-02-01
A new method is proposed for the solution of the vertical vehicle-track interaction including a separation between wheel and rail. The vehicle is modelled as a multi-body system using rigid bodies, and the track is treated as a three-layer beam model in which the rail is considered as an Euler-Bernoulli beam and both the sleepers and the ballast are represented by lumped masses. A linear complementarity formulation is directly established using a combination of the wheel-rail normal contact condition and the generalised-α method. This linear complementarity problem is solved using the Lemke algorithm, and the wheel-rail contact force can be obtained. Then the dynamic responses of the vehicle and the track are solved without iteration based on the generalised-α method. The same equations of motion for the vehicle and track are adopted at the different wheel-rail contact situations. This method can remove some restrictions, that is, time-dependent mass, damping and stiffness matrices of the coupled system, multiple equations of motion for the different contact situations and the effect of the contact stiffness. Numerical results demonstrate that the proposed method is effective for simulating the vehicle-track interaction including a separation between wheel and rail.
Ringing Artefact Reduction By An Efficient Likelihood Improvement Method
Fuderer, Miha
1989-10-01
In MR imaging, the extent of the acquired spatial frequencies of the object is necessarily finite. The resulting image shows artefacts caused by "truncation" of its Fourier components. These are known as Gibbs artefacts or ringing artefacts. These artefacts are particularly. visible when the time-saving reduced acquisition method is used, say, when scanning only the lowest 70% of the 256 data lines. Filtering the data results in loss of resolution. A method is described that estimates the high frequency data from the low-frequency data lines, with the likelihood of the image as criterion. It is a computationally very efficient method, since it requires practically only two extra Fourier transforms, in addition to the normal. reconstruction. The results of this method on MR images of human subjects are promising. Evaluations on a 70% acquisition image show about 20% decrease of the error energy after processing. "Error energy" is defined as the total power of the difference to a 256-data-lines reference image. The elimination of ringing artefacts then appears almost complete..
The iterative shrinkage method for impulsive noise reduction from images
Beygi, Sajjad; Kafashan, Mohammadmehdi; Bahrami, Hamid Reza; Mugler, Dale H
2012-01-01
In this paper, we present a novel scheme to compensate impulsive noise from images using the sparse shrinkage method. In this scheme, we assume the remaining noise after using a simple median filtering in place of corrupted pixels, found by boundary discriminative noise detection method, to be Gaussian additive noise. This assumption will later be verified by the means of simulation. Knowing that the pure image in the discrete wavelet transform (DWT) domain is a sparse vector, we define an optimization problem to minimize the l 0 -norm of the estimated image vector from the noisy one in the DWT domain. l 0 -norm makes the optimization problem a combinatorial optimization problem which is NP-hard to solve. To come up with a solution for our optimization problem, we convert the l 0 -norm problem to a continuous optimization problem which is then solved to find the estimated image with reduced noise. In the simulation and discussion part, the performance of our proposed method in reducing impulsive noise is compared to that of existing methods in the literature. We show that our proposed algorithm generally performs better in terms of both subjective and objective evaluations and is less complex. (paper)
Shi Jun
2015-02-01
Full Text Available Downward-looking Linear Array Synthetic Aperture Radar (LASAR has many potential applications in the topographic mapping, disaster monitoring and reconnaissance applications, especially in the mountainous area. However, limited by the sizes of platforms, its resolution in the linear array direction is always far lower than those in the range and azimuth directions. This disadvantage leads to the blurring of Three-Dimensional (3D images in the linear array direction, and restricts the application of LASAR. To date, the research on 3D SAR image enhancement has focused on the sparse recovery technique. In this case, the one-to-one mapping of Digital Elevation Model (DEM brakes down. To overcome this, an optimal DEM reconstruction method for LASAR based on the variational model is discussed in an effort to optimize the DEM and the associated scattering coefficient map, and to minimize the Mean Square Error (MSE. Using simulation experiments, it is found that the variational model is more suitable for DEM enhancement applications to all kinds of terrains compared with the Orthogonal Matching Pursuit (OMPand Least Absolute Shrinkage and Selection Operator (LASSO methods.
A METHOD FOR SELF-CALIBRATION IN SATELLITE WITH HIGH PRECISION OF SPACE LINEAR ARRAY CAMERA
W. Liu
2016-06-01
Full Text Available At present, the on-orbit calibration of the geometric parameters of a space surveying camera is usually processed by data from a ground calibration field after capturing the images. The entire process is very complicated and lengthy and cannot monitor and calibrate the geometric parameters in real time. On the basis of a large number of on-orbit calibrations, we found that owing to the influence of many factors, e.g., weather, it is often difficult to capture images of the ground calibration field. Thus, regular calibration using field data cannot be ensured. This article proposes a real time self-calibration method for a space linear array camera on a satellite using the optical auto collimation principle. A collimating light source and small matrix array CCD devices are installed inside the load system of the satellite; these use the same light path as the linear array camera. We can extract the location changes of the cross marks in the matrix array CCD to determine the real-time variations in the focal length and angle parameters of the linear array camera. The on-orbit status of the camera is rapidly obtained using this method. On one hand, the camera’s change regulation can be mastered accurately and the camera’s attitude can be adjusted in a timely manner to ensure optimal photography; in contrast, self-calibration of the camera aboard the satellite can be realized quickly, which improves the efficiency and reliability of photogrammetric processing.
Comments on the comparison of global methods for linear two-point boundary value problems
de Boor, C.; Swartz, B.
1977-01-01
A more careful count of the operations involved in solving the linear system associated with collocation of a two-point boundary value problem using a rough splines reverses results recently reported by others in this journal. In addition, it is observed that the use of the technique of ''condensation of parameters'' can decrease the computer storage required. Furthermore, the use of a particular highly localized basis can also reduce the setup time when the mesh is irregular. Finally, operation counts are roughly estimated for the solution of certain linear system associated with two competing collocation methods; namely, collocation with smooth splines and collocation of the equivalent first order system with continuous piecewise polynomials
Pilipchuk, L. A.; Pilipchuk, A. S.
2015-01-01
In this paper we propose the theory of decomposition, methods, technologies, applications and implementation in Wol-fram Mathematica for the constructing the solutions of the sparse linear systems. One of the applications is the Sensor Location Problem for the symmetric graph in the case when split ratios of some arc flows can be zeros. The objective of that application is to minimize the number of sensors that are assigned to the nodes. We obtain a sparse system of linear algebraic equations and research its matrix rank. Sparse systems of these types appear in generalized network flow programming problems in the form of restrictions and can be characterized as systems with a large sparse sub-matrix representing the embedded network structure
A Fast Condensing Method for Solution of Linear-Quadratic Control Problems
Frison, Gianluca; Jørgensen, John Bagterp
2013-01-01
consider a condensing (or state elimination) method to solve an extended version of the LQ control problem, and we show how to exploit the structure of this problem to both factorize the dense Hessian matrix and solve the system. Furthermore, we present two efficient implementations. The first......In both Active-Set (AS) and Interior-Point (IP) algorithms for Model Predictive Control (MPC), sub-problems in the form of linear-quadratic (LQ) control problems need to be solved at each iteration. The solution of these sub-problems is usually the main computational effort. In this paper we...... implementation is formally identical to the Riccati recursion based solver and has a computational complexity that is linear in the control horizon length and cubic in the number of states. The second implementation has a computational complexity that is quadratic in the control horizon length as well...
Pilipchuk, L. A., E-mail: pilipchik@bsu.by [Belarussian State University, 220030 Minsk, 4, Nezavisimosti avenue, Republic of Belarus (Belarus); Pilipchuk, A. S., E-mail: an.pilipchuk@gmail.com [The Natural Resources and Environmental Protestion Ministry of the Republic of Belarus, 220004 Minsk, 10 Kollektornaya Street, Republic of Belarus (Belarus)
2015-11-30
In this paper we propose the theory of decomposition, methods, technologies, applications and implementation in Wol-fram Mathematica for the constructing the solutions of the sparse linear systems. One of the applications is the Sensor Location Problem for the symmetric graph in the case when split ratios of some arc flows can be zeros. The objective of that application is to minimize the number of sensors that are assigned to the nodes. We obtain a sparse system of linear algebraic equations and research its matrix rank. Sparse systems of these types appear in generalized network flow programming problems in the form of restrictions and can be characterized as systems with a large sparse sub-matrix representing the embedded network structure.
KEELE, Minimization of Nonlinear Function with Linear Constraints, Variable Metric Method
Westley, G.W.
1975-01-01
1 - Description of problem or function: KEELE is a linearly constrained nonlinear programming algorithm for locating a local minimum of a function of n variables with the variables subject to linear equality and/or inequality constraints. 2 - Method of solution: A variable metric procedure is used where the direction of search at each iteration is obtained by multiplying the negative of the gradient vector by a positive definite matrix which approximates the inverse of the matrix of second partial derivatives associated with the function. 3 - Restrictions on the complexity of the problem: Array dimensions limit the number of variables to 20 and the number of constraints to 50. These can be changed by the user
Sensitivity-based virtual fields for the non-linear virtual fields method
Marek, Aleksander; Davis, Frances M.; Pierron, Fabrice
2017-09-01
The virtual fields method is an approach to inversely identify material parameters using full-field deformation data. In this manuscript, a new set of automatically-defined virtual fields for non-linear constitutive models has been proposed. These new sensitivity-based virtual fields reduce the influence of noise on the parameter identification. The sensitivity-based virtual fields were applied to a numerical example involving small strain plasticity; however, the general formulation derived for these virtual fields is applicable to any non-linear constitutive model. To quantify the improvement offered by these new virtual fields, they were compared with stiffness-based and manually defined virtual fields. The proposed sensitivity-based virtual fields were consistently able to identify plastic model parameters and outperform the stiffness-based and manually defined virtual fields when the data was corrupted by noise.
Qiu, J.; Khalloufi, S.; Martynenko, A.; Dalen, van G.; Schutyser, M.A.I.; Almeida-Rivera, C.
2015-01-01
Several experimental methods for measuring porosity, bulk density and volume reduction during drying of foodstuff are available. These methods include among others geometric dimension, volume displacement, mercury porosimeter, micro-CT, and NMR. However, data on their accuracy, sensitivity, and
Numerical comparison of robustness of some reduction methods in rough grids
Hou, Jiangyong; Sun, Shuyu; Chen, Zhangxin
2014-01-01
In this article, we present three nonsymmetric mixed hybrid RT 1 2 methods and compare with some recently developed reduction methods which are suitable for the single-phase Darcy flow problem with full anisotropic and highly heterogeneous
Controllable reductive method for synthesizing metal-containing particles
Moon, Ji-Won; Jung, Hyunsung; Phelps, Tommy Joe; Duty, Chad E.; Ivanov, Ilia N.; Joshi, Pooran Chandra; Jellison, Jr., Gerald Earle; Armstrong, Beth Louise; Smith, Sean Campbell; Rondinone, Adam Justin; Love, Lonnie J.
2018-03-06
The invention is directed to a method for producing metal-containing particles, the method comprising subjecting an aqueous solution comprising a metal salt, E.sub.h, lowering reducing agent, pH adjusting agent, and water to conditions that maintain the E.sub.h value of the solution within the bounds of an E.sub.h-pH stability field corresponding to the composition of the metal-containing particles to be produced, and producing said metal-containing particles in said aqueous solution at a selected E.sub.h value within the bounds of said E.sub.h-pH stability field. The invention is also directed to the resulting metal-containing particles as well as devices in which they are incorporated.
Reduction in requirements for allogeneic blood products: nonpharmacologic methods.
Hardy, J F; Bélisle, S; Janvier, G; Samama, M
1996-12-01
Various strategies have been proposed to decrease bleeding and allogeneic transfusion requirements during and after cardiac operations. This article attempts to document the usefulness, or lack thereof, of the nonpharmacologic methods available in clinical practice. Blood conservation methods were reviewed in chronologic order, as they become available to patients during the perisurgical period. The literature in support of or against each strategy was reexamined critically. Avoidance of preoperative anemia and adherence to published guidelines for the practice of transfusion are of paramount importance. Intraoperatively, tolerance of low hemoglobin concentrations and use of autologous blood (predonated or harvested before bypass) will reduce allogeneic transfusions. The usefulness of plateletpheresis and retransfusion of shed mediastinal fluid remains controversial. Intraoperatively and postoperatively, maintenance of normothermia contributes to improved hemostasis. Several approaches have been shown to be effective. An efficient combination of methods can reduce, and sometimes abolish, the need for allogeneic blood products after cardiac operations, inasmuch as all those involved in the care of cardiac surgical patients adhere thoughtfully to existing transfusion guidelines.
Sukhpreet Kaur Sidhu
2014-01-01
Full Text Available The drawbacks of the existing methods to obtain the fuzzy optimal solution of such linear programming problems, in which coefficients of the constraints are represented by real numbers and all the other parameters as well as variables are represented by symmetric trapezoidal fuzzy numbers, are pointed out, and to resolve these drawbacks, a new method (named as Mehar method is proposed for the same linear programming problems. Also, with the help of proposed Mehar method, a new method, much easy as compared to the existing methods, is proposed to deal with the sensitivity analysis of the same type of linear programming problems.
Dual linear structured support vector machine tracking method via scale correlation filter
Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen
2018-01-01
Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.
Sorokin, Vladislav; Thomsen, Jon Juel
2015-01-01
Parametrically excited systems appear in many fields of science and technology, intrinsically or imposed purposefully; e.g. spatially periodic structures represent an important class of such systems [4]. When the parametric excitation can be considered weak, classical asymptotic methods like...... the method of averaging [2] or multiple scales [6] can be applied. However, with many practically important applications this simplification is inadequate, e.g. with spatially periodic structures it restricts the possibility to affect their effective dynamic properties by a structural parameter modulation...... of considerable magnitude. Approximate methods based on Floquet theory [4] for analyzing problems involving parametric excitation, e.g. the classical Hill’s method of infinite determinants [3,4], can be employed also in cases of strong excitation; however, with Floquet theory being applicable only for linear...
Barari, Amin; Ganjavi, B.; Jeloudar, M. Ghanbari
2010-01-01
and fluid mechanics. Design/methodology/approach – Two new but powerful analytical methods, namely, He's VIM and HPM, are introduced to solve some boundary value problems in structural engineering and fluid mechanics. Findings – Analytical solutions often fit under classical perturbation methods. However......, as with other analytical techniques, certain limitations restrict the wide application of perturbation methods, most important of which is the dependence of these methods on the existence of a small parameter in the equation. Disappointingly, the majority of nonlinear problems have no small parameter at all......Purpose – In the last two decades with the rapid development of nonlinear science, there has appeared ever-increasing interest of scientists and engineers in the analytical techniques for nonlinear problems. This paper considers linear and nonlinear systems that are not only regarded as general...
General methods for alarm reduction; Larmsanering med generella metoder
Ahnlund, Jonas; Bergquist, Tord; Raaberg, Martin [Lund Univ. (Sweden). Dept. of Information Technology
2003-10-01
The information in the control rooms has increased due to the technological advances in process control. Large industries produce large data quantities, where some information is unnecessary or even incorrect. The operator needs support from an advanced and well-adjusted alarm system to be able to separate a real event from a minor disturbance. The alarms must be of assistance and not a nuisance. An enhanced alarm situation qualifies an increased efficiency with fewer production disturbances and an improved safety. Yet, it is still unusual that actions are taken to improve the situation. An alarm cleanup with general methods can shortly be described as taking advantage of the control systems built-in functions, the possibility to modify or create function blocks and fine-tune the settings in the alarm system. In this project, we make use of an intelligent software, Alarm Cleanup Toolbox, that simulate different signal processing methods and tries to find improved settings on all the signals in the process. This is a fast and cost-efficient way to improve the overall alarm situation, and lays a foundation for more advanced alarm systems. An alarm cleanup has been carried out at Flintraennan district heating plant in Malmoe, where various signal processing methods has been implemented in a parallel alarm system. This made it possible to compare the two systems under the same conditions. The result is very promising, and shows that a lot of improvements can be achieved with very little effort. An analysis of the alarm system at Vattenreningen (the water purification process) at Heleneholmsverket in Malmoe has been carried out. Alarm Cleanup Toolbox has, besides suggesting improved settings, also found logical errors in the alarm system. Here, no implementation was carried out and therefore the results are analytical, but they validate the efficiency of the general methods. The project has shown that an alarm cleanup with general methods is cost-efficient, and that the
Comparing performance of standard and iterative linear unmixing methods for hyperspectral signatures
Gault, Travis R.; Jansen, Melissa E.; DeCoster, Mallory E.; Jansing, E. David; Rodriguez, Benjamin M.
2016-05-01
Linear unmixing is a method of decomposing a mixed signature to determine the component materials that are present in sensor's field of view, along with the abundances at which they occur. Linear unmixing assumes that energy from the materials in the field of view is mixed in a linear fashion across the spectrum of interest. Traditional unmixing methods can take advantage of adjacent pixels in the decomposition algorithm, but is not the case for point sensors. This paper explores several iterative and non-iterative methods for linear unmixing, and examines their effectiveness at identifying the individual signatures that make up simulated single pixel mixed signatures, along with their corresponding abundances. The major hurdle addressed in the proposed method is that no neighboring pixel information is available for the spectral signature of interest. Testing is performed using two collections of spectral signatures from the Johns Hopkins University Applied Physics Laboratory's Signatures Database software (SigDB): a hand-selected small dataset of 25 distinct signatures from a larger dataset of approximately 1600 pure visible/near-infrared/short-wave-infrared (VIS/NIR/SWIR) spectra. Simulated spectra are created with three and four material mixtures randomly drawn from a dataset originating from SigDB, where the abundance of one material is swept in 10% increments from 10% to 90%with the abundances of the other materials equally divided amongst the remainder. For the smaller dataset of 25 signatures, all combinations of three or four materials are used to create simulated spectra, from which the accuracy of materials returned, as well as the correctness of the abundances, is compared to the inputs. The experiment is expanded to include the signatures from the larger dataset of almost 1600 signatures evaluated using a Monte Carlo scheme with 5000 draws of three or four materials to create the simulated mixed signatures. The spectral similarity of the inputs to the
da Silva, Claudia Pereira; Emídio, Elissandro Soares; de Marchi, Mary Rosa Rodrigues
2015-01-01
This paper describes the validation of a method consisting of solid-phase extraction followed by gas chromatography-tandem mass spectrometry for the analysis of the ultraviolet (UV) filters benzophenone-3, ethylhexyl salicylate, ethylhexyl methoxycinnamate and octocrylene. The method validation criteria included evaluation of selectivity, analytical curve, trueness, precision, limits of detection and limits of quantification. The non-weighted linear regression model has traditionally been used for calibration, but it is not necessarily the optimal model in all cases. Because the assumption of homoscedasticity was not met for the analytical data in this work, a weighted least squares linear regression was used for the calibration method. The evaluated analytical parameters were satisfactory for the analytes and showed recoveries at four fortification levels between 62% and 107%, with relative standard deviations less than 14%. The detection limits ranged from 7.6 to 24.1 ng L(-1). The proposed method was used to determine the amount of UV filters in water samples from water treatment plants in Araraquara and Jau in São Paulo, Brazil. Copyright © 2014 Elsevier B.V. All rights reserved.
APPLYING ROBUST RANKING METHOD IN TWO PHASE FUZZY OPTIMIZATION LINEAR PROGRAMMING PROBLEMS (FOLPP
Monalisha Pattnaik
2014-12-01
Full Text Available Background: This paper explores the solutions to the fuzzy optimization linear program problems (FOLPP where some parameters are fuzzy numbers. In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either probabilistic programming or multi-objective programming methods. Methods: In this paper, using the concept of comparison of fuzzy numbers, a very effective method is introduced for solving these problems. This paper extends linear programming based problem in fuzzy environment. With the problem assumptions, the optimal solution can still be theoretically solved using the two phase simplex based method in fuzzy environment. To handle the fuzzy decision variables can be initially generated and then solved and improved sequentially using the fuzzy decision approach by introducing robust ranking technique. Results and conclusions: The model is illustrated with an application and a post optimal analysis approach is obtained. The proposed procedure was programmed with MATLAB (R2009a version software for plotting the four dimensional slice diagram to the application. Finally, numerical example is presented to illustrate the effectiveness of the theoretical results, and to gain additional managerial insights.
Sergienko, I.V.; Golodnikov, A.N.
1984-01-01
This article applies the methods of decompositions, which are used to solve continuous linear problems, to integer and partially integer problems. The fall-vector method is used to solve the obtained coordinate problems. An algorithm of the fall-vector is described. The Kornai-Liptak decomposition principle is used to reduce the integer linear programming problem to integer linear programming problems of a smaller dimension and to a discrete coordinate problem with simple constraints
Evaluation of cost reduction method for manufacturing ODS ferritic claddings
Fujiwara, Masayuki; Mizuta, Shunji; Ukai, Shigeharu
2000-04-01
For evaluating the fast reactor system technology, it is important to evaluate the practical feasibility of ODS ferritic claddings, which is the most promising materials to attain the goal of high coolant temperature and more than 150 GWd/t. Based on the results of their technology development, mass production process with highly economically benefit as well as manufacturing cost estimation of ODS ferritic claddings were preliminarily conducted. From the view point of future utility scale, the cost for manufacturing mother tubes has a dominant factor in the total manufacturing cost. The method to reduce the cost of mother tube manufacturing was also preliminarily investigated. (author)
Non-linear triangle-based polynomial expansion nodal method for hexagonal core analysis
Cho, Jin Young; Cho, Byung Oh; Joo, Han Gyu; Zee, Sung Qunn; Park, Sang Yong
2000-09-01
This report is for the implementation of triangle-based polynomial expansion nodal (TPEN) method to MASTER code in conjunction with the coarse mesh finite difference(CMFD) framework for hexagonal core design and analysis. The TPEN method is a variation of the higher order polynomial expansion nodal (HOPEN) method that solves the multi-group neutron diffusion equation in the hexagonal-z geometry. In contrast with the HOPEN method, only two-dimensional intranodal expansion is considered in the TPEN method for a triangular domain. The axial dependence of the intranodal flux is incorporated separately here and it is determined by the nodal expansion method (NEM) for a hexagonal node. For the consistency of node geometry of the MASTER code which is based on hexagon, TPEN solver is coded to solve one hexagonal node which is composed of 6 triangular nodes directly with Gauss elimination scheme. To solve the CMFD linear system efficiently, stabilized bi-conjugate gradient(BiCG) algorithm and Wielandt eigenvalue shift method are adopted. And for the construction of the efficient preconditioner of BiCG algorithm, the incomplete LU(ILU) factorization scheme which has been widely used in two-dimensional problems is used. To apply the ILU factorization scheme to three-dimensional problem, a symmetric Gauss-Seidel Factorization scheme is used. In order to examine the accuracy of the TPEN solution, several eigenvalue benchmark problems and two transient problems, i.e., a realistic VVER1000 and VVER440 rod ejection benchmark problems, were solved and compared with respective references. The results of eigenvalue benchmark problems indicate that non-linear TPEN method is very accurate showing less than 15 pcm of eigenvalue errors and 1% of maximum power errors, and fast enough to solve the three-dimensional VVER-440 problem within 5 seconds on 733MHz PENTIUM-III. In the case of the transient problems, the non-linear TPEN method also shows good results within a few minute of
Liu, Ke; Chen, Xiaojing; Li, Limin; Chen, Huiling; Ruan, Xiukai; Liu, Wenbin
2015-02-09
The successive projections algorithm (SPA) is widely used to select variables for multiple linear regression (MLR) modeling. However, SPA used only once may not obtain all the useful information of the full spectra, because the number of selected variables cannot exceed the number of calibration samples in the SPA algorithm. Therefore, the SPA-MLR method risks the loss of useful information. To make a full use of the useful information in the spectra, a new method named "consensus SPA-MLR" (C-SPA-MLR) is proposed herein. This method is the combination of consensus strategy and SPA-MLR method. In the C-SPA-MLR method, SPA-MLR is used to construct member models with different subsets of variables, which are selected from the remaining variables iteratively. A consensus prediction is obtained by combining the predictions of the member models. The proposed method is evaluated by analyzing the near infrared (NIR) spectra of corn and diesel. The results of C-SPA-MLR method showed a better prediction performance compared with the SPA-MLR and full-spectra PLS methods. Moreover, these results could serve as a reference for combination the consensus strategy and other variable selection methods when analyzing NIR spectra and other spectroscopic techniques. Copyright © 2014 Elsevier B.V. All rights reserved.
Singular perturbations introduction to system order reduction methods with applications
Shchepakina, Elena; Mortell, Michael P
2014-01-01
These lecture notes provide a fresh approach to investigating singularly perturbed systems using asymptotic and geometrical techniques. It gives many examples and step-by-step techniques, which will help beginners move to a more advanced level. Singularly perturbed systems appear naturally in the modelling of many processes that are characterized by slow and fast motions simultaneously, for example, in fluid dynamics and nonlinear mechanics. This book’s approach consists in separating out the slow motions of the system under investigation. The result is a reduced differential system of lesser order. However, it inherits the essential elements of the qualitative behaviour of the original system. Singular Perturbations differs from other literature on the subject due to its methods and wide range of applications. It is a valuable reference for specialists in the areas of applied mathematics, engineering, physics, biology, as well as advanced undergraduates for the earlier parts of the book, and graduate stude...
Adaptive Subband Filtering Method for MEMS Accelerometer Noise Reduction
Piotr PIETRZAK
2008-12-01
Full Text Available Silicon microaccelerometers can be considered as an alternative to high-priced piezoelectric sensors. Unfortunately, relatively high noise floor of commercially available MEMS (Micro-Electro-Mechanical Systems sensors limits the possibility of their usage in condition monitoring systems of rotating machines. The solution of this problem is the method of signal filtering described in the paper. It is based on adaptive subband filtering employing Adaptive Line Enhancer. For filter weights adaptation, two novel algorithms have been developed. They are based on the NLMS algorithm. Both of them significantly simplify its software and hardware implementation and accelerate the adaptation process. The paper also presents the software (Matlab and hardware (FPGA implementation of the proposed noise filter. In addition, the results of the performed tests are reported. They confirm high efficiency of the solution.
V. S. Zarubin
2015-01-01
Full Text Available The rational use of composites as structural materials, while perceiving the thermal and mechanical loads, to a large extent determined by their thermoelastic properties. From the presented review of works devoted to the analysis of thermoelastic characteristics of composites, it follows that the problem of estimating these characteristics is important. Among the thermoelastic properties of composites occupies an important place its temperature coefficient of linear expansion.Along with fiber composites are widely used in the technique of dispersion hardening composites, in which the role of inclusions carry particles of high-strength and high-modulus materials, including nanostructured elements. Typically, the dispersed particles have similar dimensions in all directions, which allows the shape of the particles in the first approximation the ball.In an article for the composite with isotropic spherical inclusions of a plurality of different materials by the self-produced design formulas relating the temperature coefficient of linear expansion with volume concentration of inclusions and their thermoelastic characteristics, as well as the thermoelastic properties of the matrix of the composite. Feature of the method is the self-accountability thermomechanical interaction of a single inclusion or matrix particles with a homogeneous isotropic medium having the desired temperature coefficient of linear expansion. Averaging over the volume of the composite arising from such interaction perturbation strain and stress in the inclusions and the matrix particles and makes it possible to obtain such calculation formulas.For the validation of the results of calculations of the temperature coefficient of linear expansion of the composite of this type used two-sided estimates that are based on the dual variational formulation of linear thermoelasticity problem in an inhomogeneous solid containing two alternative functional (such as Lagrange and Castigliano
Vossoughi, Mehrdad; Ayatollahi, S M T; Towhidi, Mina; Ketabchi, Farzaneh
2012-03-22
The summary measure approach (SMA) is sometimes the only applicable tool for the analysis of repeated measurements in medical research, especially when the number of measurements is relatively large. This study aimed to describe techniques based on summary measures for the analysis of linear trend repeated measures data and then to compare performances of SMA, linear mixed model (LMM), and unstructured multivariate approach (UMA). Practical guidelines based on the least squares regression slope and mean of response over time for each subject were provided to test time, group, and interaction effects. Through Monte Carlo simulation studies, the efficacy of SMA vs. LMM and traditional UMA, under different types of covariance structures, was illustrated. All the methods were also employed to analyze two real data examples. Based on the simulation and example results, it was found that the SMA completely dominated the traditional UMA and performed convincingly close to the best-fitting LMM in testing all the effects. However, the LMM was not often robust and led to non-sensible results when the covariance structure for errors was misspecified. The results emphasized discarding the UMA which often yielded extremely conservative inferences as to such data. It was shown that summary measure is a simple, safe and powerful approach in which the loss of efficiency compared to the best-fitting LMM was generally negligible. The SMA is recommended as the first choice to reliably analyze the linear trend data with a moderate to large number of measurements and/or small to moderate sample sizes.
Machine learning-based methods for prediction of linear B-cell epitopes.
Wang, Hsin-Wei; Pai, Tun-Wen
2014-01-01
B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.
Pinkerton, Steven D.; Chesson, Harrell W.; Crosby, Richard A.; Layde, Peter M.
2011-01-01
A mathematical model of HIV/sexually transmitted infections (STI) transmission was used to examine how linearity or nonlinearity in the relationship between the number of unprotected sex acts (or the number of sex partners) and the risk of acquiring HIV or a highly infectious STI (such as gonorrhea or chlamydia) affects the utility of sexual…
A New Class of Non-Linear, Finite-Volume Methods for Vlasov Simulation
Banks, J.W.; Hittinger, J.A.
2010-01-01
Methods for the numerical discretization of the Vlasov equation should efficiently use the phase space discretization and should introduce only enough numerical dissipation to promote stability and control oscillations. A new high-order, non-linear, finite-volume algorithm for the Vlasov equation that discretely conserves particle number and controls oscillations is presented. The method is fourth-order in space and time in well-resolved regions, but smoothly reduces to a third-order upwind scheme as features become poorly resolved. The new scheme is applied to several standard problems for the Vlasov-Poisson system, and the results are compared with those from other finite-volume approaches, including an artificial viscosity scheme and the Piecewise Parabolic Method. It is shown that the new scheme is able to control oscillations while preserving a higher degree of fidelity of the solution than the other approaches.
Chang Liyun; Ho, S.-Y.; Du, Y.-C.; Lin, C.-M.; Chen Tainsong
2007-01-01
The calibration of the gantry angle indicator is an important and basic quality assurance (QA) item for the radiotherapy linear accelerator. In this study, we propose a new and practical method, which uses only the digital level, V-film, and general solid phantoms. By taking the star shot only, we can accurately calculate the true gantry angle according to the geometry of the film setup. The results on our machine showed that the gantry angle was shifted by -0.11 deg. compared with the digital indicator, and the standard deviation was within 0.05 deg. This method can also be used for the simulator. In conclusion, this proposed method could be adopted as an annual QA item for mechanical QA of the accelerator
Zhang, Ling
2017-01-01
The main purpose of this paper is to investigate the strong convergence and exponential stability in mean square of the exponential Euler method to semi-linear stochastic delay differential equations (SLSDDEs). It is proved that the exponential Euler approximation solution converges to the analytic solution with the strong order [Formula: see text] to SLSDDEs. On the one hand, the classical stability theorem to SLSDDEs is given by the Lyapunov functions. However, in this paper we study the exponential stability in mean square of the exact solution to SLSDDEs by using the definition of logarithmic norm. On the other hand, the implicit Euler scheme to SLSDDEs is known to be exponentially stable in mean square for any step size. However, in this article we propose an explicit method to show that the exponential Euler method to SLSDDEs is proved to share the same stability for any step size by the property of logarithmic norm.
Adi, Wisnu Ari; Sukirman, Engkir; Winatapura, Didin S.
2000-01-01
Technique of critical current density measurement (Jc) of HTc bulk ceramic superconductor has been performed by using linear extrapolation with four-point probes method. The measurement of critical current density HTc bulk ceramic superconductor usually causes damage in contact resistance. In order to decrease this damage factor, we introduce extrapolation method. The extrapolating data show that the critical current density Jc for YBCO (123) and BSCCO (2212) at 77 K are 10,85(6) Amp.cm - 2 and 14,46(6) Amp.cm - 2, respectively. This technique is easier, simpler, and the use of the current flow is low, so it will not damage the contact resistance of the sample. We expect that the method can give a better solution for bulk superconductor application. Key words. : superconductor, critical temperature, and critical current density
Ling Zhang
2017-10-01
Full Text Available Abstract The main purpose of this paper is to investigate the strong convergence and exponential stability in mean square of the exponential Euler method to semi-linear stochastic delay differential equations (SLSDDEs. It is proved that the exponential Euler approximation solution converges to the analytic solution with the strong order 1 2 $\\frac{1}{2}$ to SLSDDEs. On the one hand, the classical stability theorem to SLSDDEs is given by the Lyapunov functions. However, in this paper we study the exponential stability in mean square of the exact solution to SLSDDEs by using the definition of logarithmic norm. On the other hand, the implicit Euler scheme to SLSDDEs is known to be exponentially stable in mean square for any step size. However, in this article we propose an explicit method to show that the exponential Euler method to SLSDDEs is proved to share the same stability for any step size by the property of logarithmic norm.
Standard test method for linear-elastic plane-strain fracture toughness KIc of metallic materials
American Society for Testing and Materials. Philadelphia
2009-01-01
1.1 This test method covers the determination of fracture toughness (KIc) of metallic materials under predominantly linear-elastic, plane-strain conditions using fatigue precracked specimens having a thickness of 1.6 mm (0.063 in.) or greater subjected to slowly, or in special (elective) cases rapidly, increasing crack-displacement force. Details of test apparatus, specimen configuration, and experimental procedure are given in the Annexes. Note 1—Plane-strain fracture toughness tests of thinner materials that are sufficiently brittle (see 7.1) can be made using other types of specimens (1). There is no standard test method for such thin materials. 1.2 This test method is divided into two parts. The first part gives general recommendations and requirements for KIc testing. The second part consists of Annexes that give specific information on displacement gage and loading fixture design, special requirements for individual specimen configurations, and detailed procedures for fatigue precracking. Additional a...
Kim, Jin Kyu; Kim, Dong Keon
2016-01-01
A common approach for dynamic analysis in current practice is based on a discrete time-integration scheme. This approach can be largely attributed to the absence of a true variational framework for initial value problems. To resolve this problem, a new stationary variational principle was recently established for single-degree-of-freedom oscillating systems using mixed variables, fractional derivatives and convolutions of convolutions. In this mixed convolved action, all the governing differential equations and initial conditions are recovered from the stationarity of a single functional action. Thus, the entire description of linear elastic dynamical systems is encapsulated. For its practical application to structural dynamics, this variational formalism is systemically extended to linear elastic multidegree- of-freedom systems in this study, and a corresponding weak form is numerically implemented via a quadratic temporal finite element method. The developed numerical method is symplectic and unconditionally stable with respect to a time step for the underlying conservative system. For the forced-damped vibration, a three-story shear building is used as an example to investigate the performance of the developed numerical method, which provides accurate results with good convergence characteristics
Integrated structural analysis tool using the linear matching method part 1 – Software development
Ure, James; Chen, Haofeng; Tipping, David
2014-01-01
A number of direct methods based upon the Linear Matching Method (LMM) framework have been developed to address structural integrity issues for components subjected to cyclic thermal and mechanical load conditions. This paper presents a new integrated structural analysis tool using the LMM framework for the assessment of load carrying capacity, shakedown limit, ratchet limit and steady state cyclic response of structures. First, the development of the LMM for the evaluation of design limits in plasticity is introduced. Second, preliminary considerations for the development of the LMM into a tool which can be used on a regular basis by engineers are discussed. After the re-structuring of the LMM subroutines for multiple central processing unit (CPU) solution, the LMM software tool for the assessment of design limits in plasticity is implemented by developing an Abaqus CAE plug-in with graphical user interfaces. Further demonstration of this new LMM analysis tool including practical application and verification is presented in an accompanying paper. - Highlights: • A new structural analysis tool using the Linear Matching Method (LMM) is developed. • The software tool is able to evaluate the design limits in plasticity. • Able to assess limit load, shakedown, ratchet limit and steady state cyclic response. • Re-structuring of the LMM subroutines for multiple CPU solution is conducted. • The software tool is implemented by developing an Abaqus CAE plug-in with GUI
Deriving the probability of a linear opinion pooling method being superior to a set of alternatives
Bolger, Donnacha; Houlding, Brett
2017-01-01
Linear opinion pools are a common method for combining a set of distinct opinions into a single succinct opinion, often to be used in a decision making task. In this paper we consider a method, termed the Plug-in approach, for determining the weights to be assigned in this linear pool, in a manner that can be deemed as rational in some sense, while incorporating multiple forms of learning over time into its process. The environment that we consider is one in which every source in the pool is herself a decision maker (DM), in contrast to the more common setting in which expert judgments are amalgamated for use by a single DM. We discuss a simulation study that was conducted to show the merits of our technique, and demonstrate how theoretical probabilistic arguments can be used to exactly quantify the probability of this technique being superior (in terms of a probability density metric) to a set of alternatives. Illustrations are given of simulated proportions converging to these true probabilities in a range of commonly used distributional cases. - Highlights: • A novel context for combination of expert opinion is provided. • A dynamic reliability assessment method is stated, justified by properties and a data study. • The theoretical grounding underlying the data-driven justification is explored. • We conclude with areas for expansion and further relevant research.
Arbitrary Lagrangian-Eulerian method for non-linear problems of geomechanics
Nazem, M; Carter, J P; Airey, D W
2010-01-01
In many geotechnical problems it is vital to consider the geometrical non-linearity caused by large deformation in order to capture a more realistic model of the true behaviour. The solutions so obtained should then be more accurate and reliable, which should ultimately lead to cheaper and safer design. The Arbitrary Lagrangian-Eulerian (ALE) method originated from fluid mechanics, but has now been well established for solving large deformation problems in geomechanics. This paper provides an overview of the ALE method and its challenges in tackling problems involving non-linearities due to material behaviour, large deformation, changing boundary conditions and time-dependency, including material rate effects and inertia effects in dynamic loading applications. Important aspects of ALE implementation into a finite element framework will also be discussed. This method is then employed to solve some interesting and challenging geotechnical problems such as the dynamic bearing capacity of footings on soft soils, consolidation of a soil layer under a footing, and the modelling of dynamic penetration of objects into soil layers.
Kim, Jin Kyu [School of Architecture and Architectural Engineering, Hanyang University, Ansan (Korea, Republic of); Kim, Dong Keon [Dept. of Architectural Engineering, Dong A University, Busan (Korea, Republic of)
2016-09-15
A common approach for dynamic analysis in current practice is based on a discrete time-integration scheme. This approach can be largely attributed to the absence of a true variational framework for initial value problems. To resolve this problem, a new stationary variational principle was recently established for single-degree-of-freedom oscillating systems using mixed variables, fractional derivatives and convolutions of convolutions. In this mixed convolved action, all the governing differential equations and initial conditions are recovered from the stationarity of a single functional action. Thus, the entire description of linear elastic dynamical systems is encapsulated. For its practical application to structural dynamics, this variational formalism is systemically extended to linear elastic multidegree- of-freedom systems in this study, and a corresponding weak form is numerically implemented via a quadratic temporal finite element method. The developed numerical method is symplectic and unconditionally stable with respect to a time step for the underlying conservative system. For the forced-damped vibration, a three-story shear building is used as an example to investigate the performance of the developed numerical method, which provides accurate results with good convergence characteristics.
Reactor Network Synthesis Using Coupled Genetic Algorithm with the Quasi-linear Programming Method
Soltani, H.; Shafiei, S.; Edraki, J.
2016-01-01
This research is an attempt to develop a new procedure for the synthesis of reactor networks (RNs) using a genetic algorithm (GA) coupled with the quasi-linear programming (LP) method. The GA is used to produce structural configuration, whereas continuous variables are handled using a quasi-LP formulation for finding the best objective function. Quasi-LP consists of LP together with a search loop to find the best reactor conversions (xi), as well as split and recycle ratios (yi). Quasi-LP rep...
Elongation cutoff technique armed with quantum fast multipole method for linear scaling.
Korchowiec, Jacek; Lewandowski, Jakub; Makowski, Marcin; Gu, Feng Long; Aoki, Yuriko
2009-11-30
A linear-scaling implementation of the elongation cutoff technique (ELG/C) that speeds up Hartree-Fock (HF) self-consistent field calculations is presented. The cutoff method avoids the known bottleneck of the conventional HF scheme, that is, diagonalization, because it operates within the low dimension subspace of the whole atomic orbital space. The efficiency of ELG/C is illustrated for two model systems. The obtained results indicate that the ELG/C is a very efficient sparse matrix algebra scheme. Copyright 2009 Wiley Periodicals, Inc.
Detection methods of pulsed X-rays for transmission tomography with a linear accelerator
Glasser, F.
1988-07-01
Appropriate detection methods are studied for the development of a high energy tomograph using a linear accelerator for nondestructive testing of bulky objects. The aim is the selection of detectors adapted to a pulsed X-ray source and with a good behavior under X-ray radiations of several MeV. Performance of semiconductors (HgI 2 , Cl doped CdTe, GaAs, Bi 12 Ge0 20 ) and a scintillator (Bi 4 Ge 3 0 12 ) are examined. A prototype tomograph gave images that show the validity of detectors for analysis of medium size equipment such as a concrete drum of 60 cm in diameter [fr
Face Hallucination with Linear Regression Model in Semi-Orthogonal Multilinear PCA Method
Asavaskulkiet, Krissada
2018-04-01
In this paper, we propose a new face hallucination technique, face images reconstruction in HSV color space with a semi-orthogonal multilinear principal component analysis method. This novel hallucination technique can perform directly from tensors via tensor-to-vector projection by imposing the orthogonality constraint in only one mode. In our experiments, we use facial images from FERET database to test our hallucination approach which is demonstrated by extensive experiments with high-quality hallucinated color faces. The experimental results assure clearly demonstrated that we can generate photorealistic color face images by using the SO-MPCA subspace with a linear regression model.
The evaluation of multi-element personal dosemeters using the linear programming method
Kragh, P.; Ambrosi, P.; Boehm, J.; Hilgers, G.
1996-01-01
Multi-element dosemeters are frequently used in individual monitoring. Each element can be regarded as an individual dosemeter with its own individual dose measurement value. In general, the individual dose values of one dosemeter vary according to the exposure conditions, i. e. the energy and angle of incidence of the radiation. The (final) dose measurement value of the personal dosemeter is calculated from the individual dose values by means of an evaluation algorithm. The best possible dose value, i.e. that of the smallest systematic (type B) uncertainty if the exposure conditions are changed in the dosemeter's rated range of use, is obtained by the method of linear programming. (author)
Faster Simulation Methods for the Non-Stationary Random Vibrations of Non-Linear MDOF Systems
Askar, A.; Köylüoglu, H. U.; Nielsen, Søren R. K.
subject to nonstationary Gaussian white noise excitation, as an alternative to conventional direct simulation methods. These alternative simulation procedures rely on an assumption of local Gaussianity during each time step. This assumption is tantamount to various linearizations of the equations....... Such a treatment offers higher rates of convergence, faster speed and higher accuracy. These procedures are compared to the direct Monte Carlo simulation procedure, which uses a fourth order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process...
Faster Simulation Methods for the Nonstationary Random Vibrations of Non-linear MDOF Systems
Askar, A.; Köylüo, U.; Nielsen, Søren R.K.
1996-01-01
subject to nonstationary Gaussian white noise excitation, as an alternative to conventional direct simulation methods. These alternative simulation procedures rely on an assumption of local Gaussianity during each time step. This assumption is tantamount to various linearizations of the equations....... Such a treatment offers higher rates of convergence, faster speed and higher accuracy. These procedures are compared to the direct Monte Carlo simulation procedure, which uses a fourth order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process...
A review of methods for experimentally determining linear optics in storage rings
Safranek, J.
1995-01-01
In order to maximize the brightness and provide sufficient dynamic aperture in synchrotron radiation storage rings, one must understand and control the linear optics. Control of the horizontal beta function and dispersion is important for minimizing the horizontal beam size. Control of the skew gradient distribution is important for minimizing the vertical size. In this paper, various methods for experimentally determining the optics in a storage ring will be reviewed. Recent work at the National Synchrotron Light Source X-Ray Ring will be presented as well as work done at laboratories worldwide
Multidimensional radiative transfer with multilevel atoms. II. The non-linear multigrid method.
Fabiani Bendicho, P.; Trujillo Bueno, J.; Auer, L.
1997-08-01
A new iterative method for solving non-LTE multilevel radiative transfer (RT) problems in 1D, 2D or 3D geometries is presented. The scheme obtains the self-consistent solution of the kinetic and RT equations at the cost of only a few (iteration (Brandt, 1977, Math. Comp. 31, 333; Hackbush, 1985, Multi-Grid Methods and Applications, springer-Verlag, Berlin), an efficient multilevel RT scheme based on Gauss-Seidel iterations (cf. Trujillo Bueno & Fabiani Bendicho, 1995ApJ...455..646T), and accurate short-characteristics formal solution techniques. By combining a valid stopping criterion with a nested-grid strategy a converged solution with the desired true error is automatically guaranteed. Contrary to the current operator splitting methods the very high convergence speed of the new RT method does not deteriorate when the grid spatial resolution is increased. With this non-linear multigrid method non-LTE problems discretized on N grid points are solved in O(N) operations. The nested multigrid RT method presented here is, thus, particularly attractive in complicated multilevel transfer problems where small grid-sizes are required. The properties of the method are analyzed both analytically and with illustrative multilevel calculations for Ca II in 1D and 2D schematic model atmospheres.
Clemens, M.; Weiland, T. [Technische Hochschule Darmstadt (Germany)
1996-12-31
In the field of computational electrodynamics the discretization of Maxwell`s equations using the Finite Integration Theory (FIT) yields very large, sparse, complex symmetric linear systems of equations. For this class of complex non-Hermitian systems a number of conjugate gradient-type algorithms is considered. The complex version of the biconjugate gradient (BiCG) method by Jacobs can be extended to a whole class of methods for complex-symmetric algorithms SCBiCG(T, n), which only require one matrix vector multiplication per iteration step. In this class the well-known conjugate orthogonal conjugate gradient (COCG) method for complex-symmetric systems corresponds to the case n = 0. The case n = 1 yields the BiCGCR method which corresponds to the conjugate residual algorithm for the real-valued case. These methods in combination with a minimal residual smoothing process are applied separately to practical 3D electro-quasistatical and eddy-current problems in electrodynamics. The practical performance of the SCBiCG methods is compared with other methods such as QMR and TFQMR.
Method for simulating dose reduction in digital mammography using the Anscombe transformation
Borges, Lucas R.; de Oliveira, Helder C. R.; Nunes, Polyana F.; Bakic, Predrag R.; Maidment, Andrew D. A.; Vieira, Marcelo A. C.
2016-01-01
Purpose: This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose. Methods: The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the d...
Godin, Bruno; Mayer, Frédéric; Agneessens, Richard; Gerin, Patrick; Dardenne, Pierre; Delfosse, Philippe; Delcarte, Jérôme
2015-01-01
The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models. Copyright © 2014 Elsevier Ltd. All rights reserved.
Linear and nonlinear dynamic analysis by boundary element method. Ph.D. Thesis, 1986 Final Report
Ahmad, Shahid
1991-01-01
An advanced implementation of the direct boundary element method (BEM) applicable to free-vibration, periodic (steady-state) vibration and linear and nonlinear transient dynamic problems involving two and three-dimensional isotropic solids of arbitrary shape is presented. Interior, exterior, and half-space problems can all be solved by the present formulation. For the free-vibration analysis, a new real variable BEM formulation is presented which solves the free-vibration problem in the form of algebraic equations (formed from the static kernels) and needs only surface discretization. In the area of time-domain transient analysis, the BEM is well suited because it gives an implicit formulation. Although the integral formulations are elegant, because of the complexity of the formulation it has never been implemented in exact form. In the present work, linear and nonlinear time domain transient analysis for three-dimensional solids has been implemented in a general and complete manner. The formulation and implementation of the nonlinear, transient, dynamic analysis presented here is the first ever in the field of boundary element analysis. Almost all the existing formulation of BEM in dynamics use the constant variation of the variables in space and time which is very unrealistic for engineering problems and, in some cases, it leads to unacceptably inaccurate results. In the present work, linear and quadratic isoparametric boundary elements are used for discretization of geometry and functional variations in space. In addition, higher order variations in time are used. These methods of analysis are applicable to piecewise-homogeneous materials, such that not only problems of the layered media and the soil-structure interaction can be analyzed but also a large problem can be solved by the usual sub-structuring technique. The analyses have been incorporated in a versatile, general-purpose computer program. Some numerical problems are solved and, through comparisons
Graf, Daniel; Beuerle, Matthias; Schurkus, Henry F; Luenser, Arne; Savasci, Gökcen; Ochsenfeld, Christian
2018-05-08
An efficient algorithm for calculating the random phase approximation (RPA) correlation energy is presented that is as accurate as the canonical molecular orbital resolution-of-the-identity RPA (RI-RPA) with the important advantage of an effective linear-scaling behavior (instead of quartic) for large systems due to a formulation in the local atomic orbital space. The high accuracy is achieved by utilizing optimized minimax integration schemes and the local Coulomb metric attenuated by the complementary error function for the RI approximation. The memory bottleneck of former atomic orbital (AO)-RI-RPA implementations ( Schurkus, H. F.; Ochsenfeld, C. J. Chem. Phys. 2016 , 144 , 031101 and Luenser, A.; Schurkus, H. F.; Ochsenfeld, C. J. Chem. Theory Comput. 2017 , 13 , 1647 - 1655 ) is addressed by precontraction of the large 3-center integral matrix with the Cholesky factors of the ground state density reducing the memory requirements of that matrix by a factor of [Formula: see text]. Furthermore, we present a parallel implementation of our method, which not only leads to faster RPA correlation energy calculations but also to a scalable decrease in memory requirements, opening the door for investigations of large molecules even on small- to medium-sized computing clusters. Although it is known that AO methods are highly efficient for extended systems, where sparsity allows for reaching the linear-scaling regime, we show that our work also extends the applicability when considering highly delocalized systems for which no linear scaling can be achieved. As an example, the interlayer distance of two covalent organic framework pore fragments (comprising 384 atoms in total) is analyzed.
Chunyan Han
2015-01-01
Full Text Available Based on the heteroclinic Shil’nikov theorem and switching control, a kind of multipiecewise linear chaotic system is constructed in this paper. Firstly, two fundamental linear systems are constructed via linearization of a chaotic system at its two equilibrium points. Secondly, a two-piecewise linear chaotic system which satisfies the Shil’nikov theorem is generated by constructing heteroclinic loop between equilibrium points of the two fundamental systems by switching control. Finally, another multipiecewise linear chaotic system that also satisfies the Shil’nikov theorem is obtained via alternate translation of the two fundamental linear systems and heteroclinic loop construction of adjacent equilibria for the multipiecewise linear system. Some basic dynamical characteristics, including divergence, Lyapunov exponents, and bifurcation diagrams of the constructed systems, are analyzed. Meanwhile, computer simulation and circuit design are used for the proposed chaotic systems, and they are demonstrated to be effective for the method of chaos anticontrol.
Using the fuzzy linear regression method to benchmark the energy efficiency of commercial buildings
Chung, William
2012-01-01
Highlights: ► Fuzzy linear regression method is used for developing benchmarking systems. ► The systems can be used to benchmark energy efficiency of commercial buildings. ► The resulting benchmarking model can be used by public users. ► The resulting benchmarking model can capture the fuzzy nature of input–output data. -- Abstract: Benchmarking systems from a sample of reference buildings need to be developed to conduct benchmarking processes for the energy efficiency of commercial buildings. However, not all benchmarking systems can be adopted by public users (i.e., other non-reference building owners) because of the different methods in developing such systems. An approach for benchmarking the energy efficiency of commercial buildings using statistical regression analysis to normalize other factors, such as management performance, was developed in a previous work. However, the field data given by experts can be regarded as a distribution of possibility. Thus, the previous work may not be adequate to handle such fuzzy input–output data. Consequently, a number of fuzzy structures cannot be fully captured by statistical regression analysis. This present paper proposes the use of fuzzy linear regression analysis to develop a benchmarking process, the resulting model of which can be used by public users. An illustrative example is given as well.
Carey, G.F.; Young, D.M.
1993-12-31
The program outlined here is directed to research on methods, algorithms, and software for distributed parallel supercomputers. Of particular interest are finite element methods and finite difference methods together with sparse iterative solution schemes for scientific and engineering computations of very large-scale systems. Both linear and nonlinear problems will be investigated. In the nonlinear case, applications with bifurcation to multiple solutions will be considered using continuation strategies. The parallelizable numerical methods of particular interest are a family of partitioning schemes embracing domain decomposition, element-by-element strategies, and multi-level techniques. The methods will be further developed incorporating parallel iterative solution algorithms with associated preconditioners in parallel computer software. The schemes will be implemented on distributed memory parallel architectures such as the CRAY MPP, Intel Paragon, the NCUBE3, and the Connection Machine. We will also consider other new architectures such as the Kendall-Square (KSQ) and proposed machines such as the TERA. The applications will focus on large-scale three-dimensional nonlinear flow and reservoir problems with strong convective transport contributions. These are legitimate grand challenge class computational fluid dynamics (CFD) problems of significant practical interest to DOE. The methods developed and algorithms will, however, be of wider interest.
An Application of Robust Method in Multiple Linear Regression Model toward Credit Card Debt
Amira Azmi, Nur; Saifullah Rusiman, Mohd; Khalid, Kamil; Roslan, Rozaini; Sufahani, Suliadi; Mohamad, Mahathir; Salleh, Rohayu Mohd; Hamzah, Nur Shamsidah Amir
2018-04-01
Credit card is a convenient alternative replaced cash or cheque, and it is essential component for electronic and internet commerce. In this study, the researchers attempt to determine the relationship and significance variables between credit card debt and demographic variables such as age, household income, education level, years with current employer, years at current address, debt to income ratio and other debt. The provided data covers 850 customers information. There are three methods that applied to the credit card debt data which are multiple linear regression (MLR) models, MLR models with least quartile difference (LQD) method and MLR models with mean absolute deviation method. After comparing among three methods, it is found that MLR model with LQD method became the best model with the lowest value of mean square error (MSE). According to the final model, it shows that the years with current employer, years at current address, household income in thousands and debt to income ratio are positively associated with the amount of credit debt. Meanwhile variables for age, level of education and other debt are negatively associated with amount of credit debt. This study may serve as a reference for the bank company by using robust methods, so that they could better understand their options and choice that is best aligned with their goals for inference regarding to the credit card debt.
The linearly scaling 3D fragment method for large scale electronic structure calculations
Zhao Zhengji [National Energy Research Scientific Computing Center (NERSC) (United States); Meza, Juan; Shan Hongzhang; Strohmaier, Erich; Bailey, David; Wang Linwang [Computational Research Division, Lawrence Berkeley National Laboratory (United States); Lee, Byounghak, E-mail: ZZhao@lbl.go [Physics Department, Texas State University (United States)
2009-07-01
The linearly scaling three-dimensional fragment (LS3DF) method is an O(N) ab initio electronic structure method for large-scale nano material simulations. It is a divide-and-conquer approach with a novel patching scheme that effectively cancels out the artificial boundary effects, which exist in all divide-and-conquer schemes. This method has made ab initio simulations of thousand-atom nanosystems feasible in a couple of hours, while retaining essentially the same accuracy as the direct calculation methods. The LS3DF method won the 2008 ACM Gordon Bell Prize for algorithm innovation. Our code has reached 442 Tflop/s running on 147,456 processors on the Cray XT5 (Jaguar) at OLCF, and has been run on 163,840 processors on the Blue Gene/P (Intrepid) at ALCF, and has been applied to a system containing 36,000 atoms. In this paper, we will present the recent parallel performance results of this code, and will apply the method to asymmetric CdSe/CdS core/shell nanorods, which have potential applications in electronic devices and solar cells.
The Inverse System Method Applied to the Derivation of Power System Non—linear Control Laws
DonghaiLI; XuezhiJIANG; 等
1997-01-01
The differential geometric method has been applied to a series of power system non-linear control problems effectively.However a set of differential equations must be solved for obtaining the required diffeomorphic transformation.Therefore the derivation of control laws is very complicated.In fact because of the specificity of power system models the required diffeomorphic transformation may be obtained directly,so it is unnecessary to solve a set of differential equations.In addition inverse system method is equivalent to differential geometric method in reality and not limited to affine nonlinear systems,Its physical meaning is able to be viewed directly and its deduction needs only algebraic operation and derivation,so control laws can be obtained easily and the application to engineering is very convenient.Authors of this paper take steam valving control of power system as a typical case to be studied.It is demonstrated that the control law deduced by inverse system method is just the same as one by differential geometric method.The conclusion will simplify the control law derivations of steam valving,excitation,converter and static var compensator by differential geometric method and may be suited to similar control problems in other areas.
Yager’s ranking method for solving the trapezoidal fuzzy number linear programming
Karyati; Wutsqa, D. U.; Insani, N.
2018-03-01
In the previous research, the authors have studied the fuzzy simplex method for trapezoidal fuzzy number linear programming based on the Maleki’s ranking function. We have found some theories related to the term conditions for the optimum solution of fuzzy simplex method, the fuzzy Big-M method, the fuzzy two-phase method, and the sensitivity analysis. In this research, we study about the fuzzy simplex method based on the other ranking function. It is called Yager's ranking function. In this case, we investigate the optimum term conditions. Based on the result of research, it is found that Yager’s ranking function is not like Maleki’s ranking function. Using the Yager’s function, the simplex method cannot work as well as when using the Maleki’s function. By using the Yager’s function, the value of the subtraction of two equal fuzzy numbers is not equal to zero. This condition makes the optimum table of the fuzzy simplex table is undetected. As a result, the simplified fuzzy simplex table becomes stopped and does not reach the optimum solution.
Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum Method
Younes Elahi
2014-01-01
Full Text Available We propose a new approach to optimizing portfolios to mean-variance-CVaR (MVC model. Although of several researches have studied the optimal MVC model of portfolio, the linear weighted sum method (LWSM was not implemented in the area. The aim of this paper is to investigate the optimal portfolio model based on MVC via LWSM. With this method, the solution of the MVC model of portfolio as the multiobjective problem is presented. In data analysis section, this approach in investing on two assets is investigated. An MVC model of the multiportfolio was implemented in MATLAB and tested on the presented problem. It is shown that, by using three objective functions, it helps the investors to manage their portfolio better and thereby minimize the risk and maximize the return of the portfolio. The main goal of this study is to modify the current models and simplify it by using LWSM to obtain better results.
Combined slope ratio analysis and linear-subtraction: An extension of the Pearce ratio method
De Waal, Sybrand A.
1996-07-01
A new technique, called combined slope ratio analysis, has been developed by extending the Pearce element ratio or conserved-denominator method (Pearce, 1968) to its logical conclusions. If two stoichiometric substances are mixed and certain chemical components are uniquely contained in either one of the two mixing substances, then by treating these unique components as conserved, the composition of the substance not containing the relevant component can be accurately calculated within the limits allowed by analytical and geological error. The calculated composition can then be subjected to rigorous statistical testing using the linear-subtraction method recently advanced by Woronow (1994). Application of combined slope ratio analysis to the rocks of the Uwekahuna Laccolith, Hawaii, USA, and the lavas of the 1959-summit eruption of Kilauea Volcano, Hawaii, USA, yields results that are consistent with field observations.
A Dynamic Linear Hashing Method for Redundancy Management in Train Ethernet Consist Network
Xiaobo Nie
2016-01-01
Full Text Available Massive transportation systems like trains are considered critical systems because they use the communication network to control essential subsystems on board. Critical system requires zero recovery time when a failure occurs in a communication network. The newly published IEC62439-3 defines the high-availability seamless redundancy protocol, which fulfills this requirement and ensures no frame loss in the presence of an error. This paper adopts these for train Ethernet consist network. The challenge is management of the circulating frames, capable of dealing with real-time processing requirements, fast switching times, high throughout, and deterministic behavior. The main contribution of this paper is the in-depth analysis it makes of network parameters imposed by the application of the protocols to train control and monitoring system (TCMS and the redundant circulating frames discarding method based on a dynamic linear hashing, using the fastest method in order to resolve all the issues that are dealt with.
Application of the method of continued fractions for electron scattering by linear molecules
Lee, M.-T.; Iga, I.; Fujimoto, M.M.; Lara, O.; Brasilia Univ., DF
1995-01-01
The method of continued fractions (MCF) of Horacek and Sasakawa is adapted for the first time to study low-energy electron scattering by linear molecules. Particularly, we have calculated the reactance K-matrices for an electron scattered by hydrogen molecule and hydrogen molecular ion as well as by a polar LiH molecule in the static-exchange level. For all the applications studied herein. the calculated physical quantities converge rapidly, even for a strongly polar molecule such as LiH, to the correct values and in most cases the convergence is monotonic. Our study suggests that the MCF could be an efficient method for studying electron-molecule scattering and also photoionization of molecules. (Author)
A new formulation of the linear sampling method: spatial resolution and post-processing
Piana, M; Aramini, R; Brignone, M; Coyle, J
2008-01-01
A new formulation of the linear sampling method is described, which requires the regularized solution of a single functional equation set in a direct sum of L 2 spaces. This new approach presents the following notable advantages: it is computationally more effective than the traditional implementation, since time consuming samplings of the Tikhonov minimum problem and of the generalized discrepancy equation are avoided; it allows a quantitative estimate of the spatial resolution achievable by the method; it facilitates a post-processing procedure for the optimal selection of the scatterer profile by means of edge detection techniques. The formulation is described in a two-dimensional framework and in the case of obstacle scattering, although generalizations to three dimensions and penetrable inhomogeneities are straightforward
A novel method to design sparse linear arrays for ultrasonic phased array.
Yang, Ping; Chen, Bin; Shi, Ke-Ren
2006-12-22
In ultrasonic phased array testing, a sparse array can increase the resolution by enlarging the aperture without adding system complexity. Designing a sparse array involves choosing the best or a better configuration from a large number of candidate arrays. We firstly designed sparse arrays by using a genetic algorithm, but found that the arrays have poor performance and poor consistency. So, a method based on the Minimum Redundancy Linear Array was then adopted. Some elements are determined by the minimum-redundancy array firstly in order to ensure spatial resolution and then a genetic algorithm is used to optimize the remaining elements. Sparse arrays designed by this method have much better performance and consistency compared to the arrays designed only by a genetic algorithm. Both simulation and experiment confirm the effectiveness.
The instantaneous linear motion information measurement method based on inertial sensors for ships
Yang, Xu; Huang, Jing; Gao, Chen; Quan, Wei; Li, Ming; Zhang, Yanshun
2018-05-01
Ship instantaneous line motion information is the important foundation for ship control, which needs to be measured accurately. For this purpose, an instantaneous line motion measurement method based on inertial sensors is put forward for ships. By introducing a half-fixed coordinate system to realize the separation between instantaneous line motion and ship master movement, the instantaneous line motion acceleration of ships can be obtained with higher accuracy. Then, the digital high-pass filter is applied to suppress the velocity error caused by the low frequency signal such as schuler period. Finally, the instantaneous linear motion displacement of ships can be measured accurately. Simulation experimental results show that the method is reliable and effective, and can realize the precise measurement of velocity and displacement of instantaneous line motion for ships.
Method for pulse to pulse dose reproducibility applied to electron linear accelerators
Ighigeanu, D.; Martin, D.; Oproiu, C.; Cirstea, E.; Craciun, G.
2002-01-01
An original method for obtaining programmed beam single shots and pulse trains with programmed pulse number, pulse repetition frequency, pulse duration and pulse dose is presented. It is particularly useful for automatic control of absorbed dose rate level, irradiation process control as well as in pulse radiolysis studies, single pulse dose measurement or for research experiments where pulse-to-pulse dose reproducibility is required. This method is applied to the electron linear accelerators, ALIN-10 of 6.23 MeV and 82 W and ALID-7, of 5.5 MeV and 670 W, built in NILPRP. In order to implement this method, the accelerator triggering system (ATS) consists of two branches: the gun branch and the magnetron branch. ATS, which synchronizes all the system units, delivers trigger pulses at a programmed repetition rate (up to 250 pulses/s) to the gun (80 kV, 10 A and 4 ms) and magnetron (45 kV, 100 A, and 4 ms).The accelerated electron beam existence is determined by the electron gun and magnetron pulses overlapping. The method consists in controlling the overlapping of pulses in order to deliver the beam in the desired sequence. This control is implemented by a discrete pulse position modulation of gun and/or magnetron pulses. The instabilities of the gun and magnetron transient regimes are avoided by operating the accelerator with no accelerated beam for a certain time. At the operator 'beam start' command, the ATS controls electron gun and magnetron pulses overlapping and the linac beam is generated. The pulse-to-pulse absorbed dose variation is thus considerably reduced. Programmed absorbed dose, irradiation time, beam pulse number or other external events may interrupt the coincidence between the gun and magnetron pulses. Slow absorbed dose variation is compensated by the control of the pulse duration and repetition frequency. Two methods are reported in the electron linear accelerators' development for obtaining the pulse to pulse dose reproducibility: the method
Knowledge Reduction Based on Divide and Conquer Method in Rough Set Theory
Feng Hu
2012-01-01
Full Text Available The divide and conquer method is a typical granular computing method using multiple levels of abstraction and granulations. So far, although some achievements based on divided and conquer method in the rough set theory have been acquired, the systematic methods for knowledge reduction based on divide and conquer method are still absent. In this paper, the knowledge reduction approaches based on divide and conquer method, under equivalence relation and under tolerance relation, are presented, respectively. After that, a systematic approach, named as the abstract process for knowledge reduction based on divide and conquer method in rough set theory, is proposed. Based on the presented approach, two algorithms for knowledge reduction, including an algorithm for attribute reduction and an algorithm for attribute value reduction, are presented. Some experimental evaluations are done to test the methods on uci data sets and KDDCUP99 data sets. The experimental results illustrate that the proposed approaches are efficient to process large data sets with good recognition rate, compared with KNN, SVM, C4.5, Naive Bayes, and CART.
Application of linear scheduling method (LSM) for nuclear power plant (NPP) construction
Kim, Woojoong; Ryu, Dongsoo; Jung, Youngsoo
2014-01-01
Highlights: • Mixed use of linear scheduling method with traditional CPM is suggested for NPP. • A methodology for selecting promising areas for LSM application is proposed. • A case-study is conducted to validate the proposed LSM selection methodology. • A case-study of reducing NPP construction duration by using LSM is introduced. - Abstract: According to a forecast, global energy demand is expected to increase by 56% from 2010 to 2040 (EIA, 2013). The nuclear power plant construction market is also growing with sharper competition. In nuclear power plant construction, scheduling is one of the most important functions due to its large size and complexity. Therefore, it is crucial to incorporate the ‘distinct characteristics of construction commodities and the complex characteristics of scheduling techniques’ (Jung and Woo, 2004) when selecting appropriate schedule control methods for nuclear power plant construction. However, among various types of construction scheduling techniques, the traditional critical path method (CPM) has been used most frequently in real-world practice. In this context, the purpose of this paper is to examine the viability and effectiveness of linear scheduling method (LSM) applications for specific areas in nuclear power plant construction. In order to identify the criteria for selecting scheduling techniques, the characteristics of CPM and LSM were compared and analyzed first through a literature review. Distinct characteristics of nuclear power plant construction were then explored by using a case project in order to develop a methodology to select effective areas of LSM application to nuclear power plant construction. Finally, promising areas for actual LSM application are suggested based on the proposed evaluation criteria and the case project. Findings and practical implications are discussed for further implementation
Application of linear scheduling method (LSM) for nuclear power plant (NPP) construction
Kim, Woojoong, E-mail: minidung@nate.com [Central Research Institute, Korea Hydro and Nuclear Power Co., Ltd, Daejeon 305-343 (Korea, Republic of); Ryu, Dongsoo, E-mail: energyboy@khnp.co.kr [Central Research Institute, Korea Hydro and Nuclear Power Co., Ltd, Daejeon 305-343 (Korea, Republic of); Jung, Youngsoo, E-mail: yjung97@mju.ac.kr [College of Architecture, Myongji University, Yongin 449-728 (Korea, Republic of)
2014-04-01
Highlights: • Mixed use of linear scheduling method with traditional CPM is suggested for NPP. • A methodology for selecting promising areas for LSM application is proposed. • A case-study is conducted to validate the proposed LSM selection methodology. • A case-study of reducing NPP construction duration by using LSM is introduced. - Abstract: According to a forecast, global energy demand is expected to increase by 56% from 2010 to 2040 (EIA, 2013). The nuclear power plant construction market is also growing with sharper competition. In nuclear power plant construction, scheduling is one of the most important functions due to its large size and complexity. Therefore, it is crucial to incorporate the ‘distinct characteristics of construction commodities and the complex characteristics of scheduling techniques’ (Jung and Woo, 2004) when selecting appropriate schedule control methods for nuclear power plant construction. However, among various types of construction scheduling techniques, the traditional critical path method (CPM) has been used most frequently in real-world practice. In this context, the purpose of this paper is to examine the viability and effectiveness of linear scheduling method (LSM) applications for specific areas in nuclear power plant construction. In order to identify the criteria for selecting scheduling techniques, the characteristics of CPM and LSM were compared and analyzed first through a literature review. Distinct characteristics of nuclear power plant construction were then explored by using a case project in order to develop a methodology to select effective areas of LSM application to nuclear power plant construction. Finally, promising areas for actual LSM application are suggested based on the proposed evaluation criteria and the case project. Findings and practical implications are discussed for further implementation.
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.