Optimal power flow: a bibliographic survey II. Non-deterministic and hybrid methods

Energy Technology Data Exchange (ETDEWEB)

Frank, Stephen [Colorado School of Mines, Department of Electrical Engineering and Computer Science, Golden, CO (United States); Steponavice, Ingrida [Univ. of Jyvaskyla, Dept. of Mathematical Information Technology, Agora (Finland); Rebennack, Steffen [Colorado School of Mines, Division of Economics and Business, Golden, CO (United States)

2012-09-15

Over the past half-century, optimal power flow (OPF) has become one of the most important and widely studied nonlinear optimization problems. In general, OPF seeks to optimize the operation of electric power generation, transmission, and distribution networks subject to system constraints and control limits. Within this framework, however, there is an extremely wide variety of OPF formulations and solution methods. Moreover, the nature of OPF continues to evolve due to modern electricity markets and renewable resource integration. In this two-part survey, we survey both the classical and recent OPF literature in order to provide a sound context for the state of the art in OPF formulation and solution methods. The survey contributes a comprehensive discussion of specific optimization techniques that have been applied to OPF, with an emphasis on the advantages, disadvantages, and computational characteristics of each. Part I of the survey provides an introduction and surveys the deterministic optimization methods that have been applied to OPF. Part II of the survey (this article) examines the recent trend towards stochastic, or non-deterministic, search techniques and hybrid methods for OPF. (orig.)

Deterministic absorbed dose estimation in computed tomography using a discrete ordinates method

International Nuclear Information System (INIS)

Norris, Edward T.; Liu, Xin; Hsieh, Jiang

2015-01-01

Purpose: Organ dose estimation for a patient undergoing computed tomography (CT) scanning is very important. Although Monte Carlo methods are considered gold-standard in patient dose estimation, the computation time required is formidable for routine clinical calculations. Here, the authors instigate a deterministic method for estimating an absorbed dose more efficiently. Methods: Compared with current Monte Carlo methods, a more efficient approach to estimating the absorbed dose is to solve the linear Boltzmann equation numerically. In this study, an axial CT scan was modeled with a software package, Denovo, which solved the linear Boltzmann equation using the discrete ordinates method. The CT scanning configuration included 16 x-ray source positions, beam collimators, flat filters, and bowtie filters. The phantom was the standard 32 cm CT dose index (CTDI) phantom. Four different Denovo simulations were performed with different simulation parameters, including the number of quadrature sets and the order of Legendre polynomial expansions. A Monte Carlo simulation was also performed for benchmarking the Denovo simulations. A quantitative comparison was made of the simulation results obtained by the Denovo and the Monte Carlo methods. Results: The difference in the simulation results of the discrete ordinates method and those of the Monte Carlo methods was found to be small, with a root-mean-square difference of around 2.4%. It was found that the discrete ordinates method, with a higher order of Legendre polynomial expansions, underestimated the absorbed dose near the center of the phantom (i.e., low dose region). Simulations of the quadrature set 8 and the first order of the Legendre polynomial expansions proved to be the most efficient computation method in the authors’ study. The single-thread computation time of the deterministic simulation of the quadrature set 8 and the first order of the Legendre polynomial expansions was 21 min on a personal computer

Flow injection analysis simulations and diffusion coefficient determination by stochastic and deterministic optimization methods.

Science.gov (United States)

Kucza, Witold

2013-07-25

Stochastic and deterministic simulations of dispersion in cylindrical channels on the Poiseuille flow have been presented. The random walk (stochastic) and the uniform dispersion (deterministic) models have been used for computations of flow injection analysis responses. These methods coupled with the genetic algorithm and the Levenberg-Marquardt optimization methods, respectively, have been applied for determination of diffusion coefficients. The diffusion coefficients of fluorescein sodium, potassium hexacyanoferrate and potassium dichromate have been determined by means of the presented methods and FIA responses that are available in literature. The best-fit results agree with each other and with experimental data thus validating both presented approaches. Copyright © 2013 The Author. Published by Elsevier B.V. All rights reserved.

Developments based on stochastic and determinist methods for studying complex nuclear systems; Developpements utilisant des methodes stochastiques et deterministes pour l'analyse de systemes nucleaires complexes

Energy Technology Data Exchange (ETDEWEB)

Giffard, F X

2000-05-19

In the field of reactor and fuel cycle physics, particle transport plays and important role. Neutronic design, operation and evaluation calculations of nuclear system make use of large and powerful computer codes. However, current limitations in terms of computer resources make it necessary to introduce simplifications and approximations in order to keep calculation time and cost within reasonable limits. Two different types of methods are available in these codes. The first one is the deterministic method, which is applicable in most practical cases but requires approximations. The other method is the Monte Carlo method, which does not make these approximations but which generally requires exceedingly long running times. The main motivation of this work is to investigate the possibility of a combined use of the two methods in such a way as to retain their advantages while avoiding their drawbacks. Our work has mainly focused on the speed-up of 3-D continuous energy Monte Carlo calculations (TRIPOLI-4 code) by means of an optimized biasing scheme derived from importance maps obtained from the deterministic code ERANOS. The application of this method to two different practical shielding-type problems has demonstrated its efficiency: speed-up factors of 100 have been reached. In addition, the method offers the advantage of being easily implemented as it is not very to the choice of the importance mesh grid. It has also been demonstrated that significant speed-ups can be achieved by this method in the case of coupled neutron-gamma transport problems, provided that the interdependence of the neutron and photon importance maps is taken into account. Complementary studies are necessary to tackle a problem brought out by this work, namely undesirable jumps in the Monte Carlo variance estimates. (author)

2D deterministic radiation transport with the discontinuous finite element method

International Nuclear Information System (INIS)

Kershaw, D.; Harte, J.

1993-01-01

This report provides a complete description of the analytic and discretized equations for 2D deterministic radiation transport. This computational model has been checked against a wide variety of analytic test problems and found to give excellent results. We make extensive use of the discontinuous finite element method

A DETERMINISTIC METHOD FOR TRANSIENT, THREE-DIMENSIONAL NUETRON TRANSPORT

International Nuclear Information System (INIS)

S. GOLUOGLU, C. BENTLEY, R. DEMEGLIO, M. DUNN, K. NORTON, R. PEVEY I.SUSLOV AND H.L. DODDS

1998-01-01

A deterministic method for solving the time-dependent, three-dimensional Boltzmam transport equation with explicit representation of delayed neutrons has been developed and evaluated. The methodology used in this study for the time variable of the neutron flux is known as the improved quasi-static (IQS) method. The position, energy, and angle-dependent neutron flux is computed deterministically by using the three-dimensional discrete ordinates code TORT. This paper briefly describes the methodology and selected results. The code developed at the University of Tennessee based on this methodology is called TDTORT. TDTORT can be used to model transients involving voided and/or strongly absorbing regions that require transport theory for accuracy. This code can also be used to model either small high-leakage systems, such as space reactors, or asymmetric control rod movements. TDTORT can model step, ramp, step followed by another step, and step followed by ramp type perturbations. It can also model columnwise rod movement can also be modeled. A special case of columnwise rod movement in a three-dimensional model of a boiling water reactor (BWR) with simple adiabatic feedback is also included. TDTORT is verified through several transient one-dimensional, two-dimensional, and three-dimensional benchmark problems. The results show that the transport methodology and corresponding code developed in this work have sufficient accuracy and speed for computing the dynamic behavior of complex multidimensional neutronic systems

Developments based on stochastic and determinist methods for studying complex nuclear systems; Developpements utilisant des methodes stochastiques et deterministes pour l'analyse de systemes nucleaires complexes

Energy Technology Data Exchange (ETDEWEB)

Giffard, F.X

2000-05-19

In the field of reactor and fuel cycle physics, particle transport plays and important role. Neutronic design, operation and evaluation calculations of nuclear system make use of large and powerful computer codes. However, current limitations in terms of computer resources make it necessary to introduce simplifications and approximations in order to keep calculation time and cost within reasonable limits. Two different types of methods are available in these codes. The first one is the deterministic method, which is applicable in most practical cases but requires approximations. The other method is the Monte Carlo method, which does not make these approximations but which generally requires exceedingly long running times. The main motivation of this work is to investigate the possibility of a combined use of the two methods in such a way as to retain their advantages while avoiding their drawbacks. Our work has mainly focused on the speed-up of 3-D continuous energy Monte Carlo calculations (TRIPOLI-4 code) by means of an optimized biasing scheme derived from importance maps obtained from the deterministic code ERANOS. The application of this method to two different practical shielding-type problems has demonstrated its efficiency: speed-up factors of 100 have been reached. In addition, the method offers the advantage of being easily implemented as it is not very to the choice of the importance mesh grid. It has also been demonstrated that significant speed-ups can be achieved by this method in the case of coupled neutron-gamma transport problems, provided that the interdependence of the neutron and photon importance maps is taken into account. Complementary studies are necessary to tackle a problem brought out by this work, namely undesirable jumps in the Monte Carlo variance estimates. (author)

Deterministic and fuzzy-based methods to evaluate community resilience

Science.gov (United States)

Kammouh, Omar; Noori, Ali Zamani; Taurino, Veronica; Mahin, Stephen A.; Cimellaro, Gian Paolo

2018-04-01

Community resilience is becoming a growing concern for authorities and decision makers. This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework. PEOPLES is a multi-layered framework that defines community resilience using seven dimensions. Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator's performance. The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community. The second method exploits a knowledge-based fuzzy modeling for its implementation. This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis. The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community. The paper also introduces an open source online tool in which the first method is implemented. A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.

Theory and application of deterministic multidimensional pointwise energy lattice physics methods

International Nuclear Information System (INIS)

Zerkle, M.L.

1999-01-01

The theory and application of deterministic, multidimensional, pointwise energy lattice physics methods are discussed. These methods may be used to solve the neutron transport equation in multidimensional geometries using near-continuous energy detail to calculate equivalent few-group diffusion theory constants that rigorously account for spatial and spectral self-shielding effects. A dual energy resolution slowing down algorithm is described which reduces the computer memory and disk storage requirements for the slowing down calculation. Results are presented for a 2D BWR pin cell depletion benchmark problem

Deterministic Method for Obtaining Nominal and Uncertainty Models of CD Drives

DEFF Research Database (Denmark)

Vidal, Enrique Sanchez; Stoustrup, Jakob; Andersen, Palle

2002-01-01

In this paper a deterministic method for obtaining the nominal and uncertainty models of the focus loop in a CD-player is presented based on parameter identification and measurements in the focus loop of 12 actual CD drives that differ by having worst-case behaviors with respect to various...... properties. The method provides a systematic way to derive a nominal average model as well as a structures multiplicative input uncertainty model, and it is demonstrated how to apply mu-theory to design a controller based on the models obtained that meets certain robust performance criteria....

A critical evaluation of deterministic methods in size optimisation of reliable and cost effective standalone hybrid renewable energy systems

International Nuclear Information System (INIS)

Maheri, Alireza

2014-01-01

Reliability of a hybrid renewable energy system (HRES) strongly depends on various uncertainties affecting the amount of power produced by the system. In the design of systems subject to uncertainties, both deterministic and nondeterministic design approaches can be adopted. In a deterministic design approach, the designer considers the presence of uncertainties and incorporates them indirectly into the design by applying safety factors. It is assumed that, by employing suitable safety factors and considering worst-case-scenarios, reliable systems can be designed. In fact, the multi-objective optimisation problem with two objectives of reliability and cost is reduced to a single-objective optimisation problem with the objective of cost only. In this paper the competence of deterministic design methods in size optimisation of reliable standalone wind–PV–battery, wind–PV–diesel and wind–PV–battery–diesel configurations is examined. For each configuration, first, using different values of safety factors, the optimal size of the system components which minimises the system cost is found deterministically. Then, for each case, using a Monte Carlo simulation, the effect of safety factors on the reliability and the cost are investigated. In performing reliability analysis, several reliability measures, namely, unmet load, blackout durations (total, maximum and average) and mean time between failures are considered. It is shown that the traditional methods of considering the effect of uncertainties in deterministic designs such as design for an autonomy period and employing safety factors have either little or unpredictable impact on the actual reliability of the designed wind–PV–battery configuration. In the case of wind–PV–diesel and wind–PV–battery–diesel configurations it is shown that, while using a high-enough margin of safety in sizing diesel generator leads to reliable systems, the optimum value for this margin of safety leading to a

Comparison of deterministic and stochastic methods for time-dependent Wigner simulations

Energy Technology Data Exchange (ETDEWEB)

Shao, Sihong, E-mail: sihong@math.pku.edu.cn [LMAM and School of Mathematical Sciences, Peking University, Beijing 100871 (China); Sellier, Jean Michel, E-mail: jeanmichel.sellier@parallel.bas.bg [IICT, Bulgarian Academy of Sciences, Acad. G. Bonchev str. 25A, 1113 Sofia (Bulgaria)

2015-11-01

Recently a Monte Carlo method based on signed particles for time-dependent simulations of the Wigner equation has been proposed. While it has been thoroughly validated against physical benchmarks, no technical study about its numerical accuracy has been performed. To this end, this paper presents the first step towards the construction of firm mathematical foundations for the signed particle Wigner Monte Carlo method. An initial investigation is performed by means of comparisons with a cell average spectral element method, which is a highly accurate deterministic method and utilized to provide reference solutions. Several different numerical tests involving the time-dependent evolution of a quantum wave-packet are performed and discussed in deep details. In particular, this allows us to depict a set of crucial criteria for the signed particle Wigner Monte Carlo method to achieve a satisfactory accuracy.

Deterministic methods in radiation transport. A compilation of papers presented February 4--5, 1992

Energy Technology Data Exchange (ETDEWEB)

Rice, A.F.; Roussin, R.W. [eds.

1992-06-01

The Seminar on Deterministic Methods in Radiation Transport was held February 4--5, 1992, in Oak Ridge, Tennessee. Eleven presentations were made and the full papers are published in this report, along with three that were submitted but not given orally. These papers represent a good overview of the state of the art in the deterministic solution of radiation transport problems for a variety of applications of current interest to the Radiation Shielding Information Center user community.

Deterministic methods in radiation transport. A compilation of papers presented February 4-5, 1992

Energy Technology Data Exchange (ETDEWEB)

Rice, A. F.; Roussin, R. W. [eds.

1992-06-01

The Seminar on Deterministic Methods in Radiation Transport was held February 4--5, 1992, in Oak Ridge, Tennessee. Eleven presentations were made and the full papers are published in this report, along with three that were submitted but not given orally. These papers represent a good overview of the state of the art in the deterministic solution of radiation transport problems for a variety of applications of current interest to the Radiation Shielding Information Center user community.

Developments based on stochastic and determinist methods for studying complex nuclear systems

International Nuclear Information System (INIS)

Giffard, F.X.

2000-01-01

In the field of reactor and fuel cycle physics, particle transport plays and important role. Neutronic design, operation and evaluation calculations of nuclear system make use of large and powerful computer codes. However, current limitations in terms of computer resources make it necessary to introduce simplifications and approximations in order to keep calculation time and cost within reasonable limits. Two different types of methods are available in these codes. The first one is the deterministic method, which is applicable in most practical cases but requires approximations. The other method is the Monte Carlo method, which does not make these approximations but which generally requires exceedingly long running times. The main motivation of this work is to investigate the possibility of a combined use of the two methods in such a way as to retain their advantages while avoiding their drawbacks. Our work has mainly focused on the speed-up of 3-D continuous energy Monte Carlo calculations (TRIPOLI-4 code) by means of an optimized biasing scheme derived from importance maps obtained from the deterministic code ERANOS. The application of this method to two different practical shielding-type problems has demonstrated its efficiency: speed-up factors of 100 have been reached. In addition, the method offers the advantage of being easily implemented as it is not very to the choice of the importance mesh grid. It has also been demonstrated that significant speed-ups can be achieved by this method in the case of coupled neutron-gamma transport problems, provided that the interdependence of the neutron and photon importance maps is taken into account. Complementary studies are necessary to tackle a problem brought out by this work, namely undesirable jumps in the Monte Carlo variance estimates. (author)

Deterministic methods for multi-control fuel loading optimization

Science.gov (United States)

Rahman, Fariz B. Abdul

We have developed a multi-control fuel loading optimization code for pressurized water reactors based on deterministic methods. The objective is to flatten the fuel burnup profile, which maximizes overall energy production. The optimal control problem is formulated using the method of Lagrange multipliers and the direct adjoining approach for treatment of the inequality power peaking constraint. The optimality conditions are derived for a multi-dimensional multi-group optimal control problem via calculus of variations. Due to the Hamiltonian having a linear control, our optimal control problem is solved using the gradient method to minimize the Hamiltonian and a Newton step formulation to obtain the optimal control. We are able to satisfy the power peaking constraint during depletion with the control at beginning of cycle (BOC) by building the proper burnup path forward in time and utilizing the adjoint burnup to propagate the information back to the BOC. Our test results show that we are able to achieve our objective and satisfy the power peaking constraint during depletion using either the fissile enrichment or burnable poison as the control. Our fuel loading designs show an increase of 7.8 equivalent full power days (EFPDs) in cycle length compared with 517.4 EFPDs for the AP600 first cycle.

Development and application of a new deterministic method for calculating computer model result uncertainties

International Nuclear Information System (INIS)

Maerker, R.E.; Worley, B.A.

1989-01-01

Interest in research into the field of uncertainty analysis has recently been stimulated as a result of a need in high-level waste repository design assessment for uncertainty information in the form of response complementary cumulative distribution functions (CCDFs) to show compliance with regulatory requirements. The solution to this problem must obviously rely on the analysis of computer code models, which, however, employ parameters that can have large uncertainties. The motivation for the research presented in this paper is a search for a method involving a deterministic uncertainty analysis approach that could serve as an improvement over those methods that make exclusive use of statistical techniques. A deterministic uncertainty analysis (DUA) approach based on the use of first derivative information is the method studied in the present procedure. The present method has been applied to a high-level nuclear waste repository problem involving use of the codes ORIGEN2, SAS, and BRINETEMP in series, and the resulting CDF of a BRINETEMP result of interest is compared with that obtained through a completely statistical analysis

Biomedical applications of two- and three-dimensional deterministic radiation transport methods

International Nuclear Information System (INIS)

Nigg, D.W.

1992-01-01

Multidimensional deterministic radiation transport methods are routinely used in support of the Boron Neutron Capture Therapy (BNCT) Program at the Idaho National Engineering Laboratory (INEL). Typical applications of two-dimensional discrete-ordinates methods include neutron filter design, as well as phantom dosimetry. The epithermal-neutron filter for BNCT that is currently available at the Brookhaven Medical Research Reactor (BMRR) was designed using such methods. Good agreement between calculated and measured neutron fluxes was observed for this filter. Three-dimensional discrete-ordinates calculations are used routinely for dose-distribution calculations in three-dimensional phantoms placed in the BMRR beam, as well as for treatment planning verification for live canine subjects. Again, good agreement between calculated and measured neutron fluxes and dose levels is obtained

Extended method of moments for deterministic analysis of stochastic multistable neurodynamical systems

International Nuclear Information System (INIS)

Deco, Gustavo; Marti, Daniel

2007-01-01

The analysis of transitions in stochastic neurodynamical systems is essential to understand the computational principles that underlie those perceptual and cognitive processes involving multistable phenomena, like decision making and bistable perception. To investigate the role of noise in a multistable neurodynamical system described by coupled differential equations, one usually considers numerical simulations, which are time consuming because of the need for sufficiently many trials to capture the statistics of the influence of the fluctuations on that system. An alternative analytical approach involves the derivation of deterministic differential equations for the moments of the distribution of the activity of the neuronal populations. However, the application of the method of moments is restricted by the assumption that the distribution of the state variables of the system takes on a unimodal Gaussian shape. We extend in this paper the classical moments method to the case of bimodal distribution of the state variables, such that a reduced system of deterministic coupled differential equations can be derived for the desired regime of multistability

Extended method of moments for deterministic analysis of stochastic multistable neurodynamical systems

Science.gov (United States)

Deco, Gustavo; Martí, Daniel

2007-03-01

The analysis of transitions in stochastic neurodynamical systems is essential to understand the computational principles that underlie those perceptual and cognitive processes involving multistable phenomena, like decision making and bistable perception. To investigate the role of noise in a multistable neurodynamical system described by coupled differential equations, one usually considers numerical simulations, which are time consuming because of the need for sufficiently many trials to capture the statistics of the influence of the fluctuations on that system. An alternative analytical approach involves the derivation of deterministic differential equations for the moments of the distribution of the activity of the neuronal populations. However, the application of the method of moments is restricted by the assumption that the distribution of the state variables of the system takes on a unimodal Gaussian shape. We extend in this paper the classical moments method to the case of bimodal distribution of the state variables, such that a reduced system of deterministic coupled differential equations can be derived for the desired regime of multistability.

Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method.

Science.gov (United States)

Yin, Shen; Gao, Huijun; Qiu, Jianbin; Kaynak, Okyay

2017-11-01

Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve this problem, a just-in-time learning-based data-driven (JITL-DD) fault detection method for nonlinear processes with deterministic disturbances is proposed in this paper. JITL-DD employs JITL scheme for process description with local model structures to cope with processes dynamics and nonlinearity. The proposed method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection. Two nonlinear systems, i.e., a numerical example and a sewage treatment process benchmark, are employed to show the effectiveness of the proposed method.

Buildup factors for multilayer shieldings in deterministic methods and their comparison with Monte Carlo

International Nuclear Information System (INIS)

Listjak, M.; Slavik, O.; Kubovcova, D.; Vermeersch, F.

2008-01-01

In general there are two ways how to calculate effective doses. The first way is by use of deterministic methods like point kernel method which is implemented in Visiplan or Microshield. These kind of calculations are very fast, but they are not very convenient for a complex geometry with shielding composed of more then one material in meaning of result precision. In spite of this that programs are sufficient for ALARA optimisation calculations. On other side there are Monte Carlo methods which can be used for calculations. This way of calculation is quite precise in comparison with reality but calculation time is usually very large. Deterministic method like programs have one disadvantage -usually there is option to choose buildup factor (BUF) only for one material in multilayer stratified slabs shielding calculation problems even if shielding is composed from different materials. In literature there are proposed different formulas for multilayer BUF approximation. Aim of this paper was to examine these different formulas and their comparison with MCNP calculations. At first ware compared results of Visiplan and Microshield. Simple geometry was modelled - point source behind single and double slab shielding. For Build-up calculations was chosen Geometric Progression method (feature of the newest version of Visiplan) because there are lower deviations in comparison with Taylor fitting. (authors)

Buildup factors for multilayer shieldings in deterministic methods and their comparison with Monte Carlo

International Nuclear Information System (INIS)

Listjak, M.; Slavik, O.; Kubovcova, D.; Vermeersch, F.

2009-01-01

In general there are two ways how to calculate effective doses. The first way is by use of deterministic methods like point kernel method which is implemented in Visiplan or Microshield. These kind of calculations are very fast, but they are not very convenient for a complex geometry with shielding composed of more then one material in meaning of result precision. In spite of this that programs are sufficient for ALARA optimisation calculations. On other side there are Monte Carlo methods which can be used for calculations. This way of calculation is quite precise in comparison with reality but calculation time is usually very large. Deterministic method like programs have one disadvantage -usually there is option to choose buildup factor (BUF) only for one material in multilayer stratified slabs shielding calculation problems even if shielding is composed from different materials. In literature there are proposed different formulas for multilayer BUF approximation. Aim of this paper was to examine these different formulas and their comparison with MCNP calculations. At first ware compared results of Visiplan and Microshield. Simple geometry was modelled - point source behind single and double slab shielding. For Build-up calculations was chosen Geometric Progression method (feature of the newest version of Visiplan) because there are lower deviations in comparison with Taylor fitting. (authors)

Convergence studies of deterministic methods for LWR explicit reflector methodology

International Nuclear Information System (INIS)

Canepa, S.; Hursin, M.; Ferroukhi, H.; Pautz, A.

2013-01-01

The standard approach in modem 3-D core simulators, employed either for steady-state or transient simulations, is to use Albedo coefficients or explicit reflectors at the core axial and radial boundaries. In the latter approach, few-group homogenized nuclear data are a priori produced with lattice transport codes using 2-D reflector models. Recently, the explicit reflector methodology of the deterministic CASMO-4/SIMULATE-3 code system was identified to potentially constitute one of the main sources of errors for core analyses of the Swiss operating LWRs, which are all belonging to GII design. Considering that some of the new GIII designs will rely on very different reflector concepts, a review and assessment of the reflector methodology for various LWR designs appeared as relevant. Therefore, the purpose of this paper is to first recall the concepts of the explicit reflector modelling approach as employed by CASMO/SIMULATE. Then, for selected reflector configurations representative of both GII and GUI designs, a benchmarking of the few-group nuclear data produced with the deterministic lattice code CASMO-4 and its successor CASMO-5, is conducted. On this basis, a convergence study with regards to geometrical requirements when using deterministic methods with 2-D homogenous models is conducted and the effect on the downstream 3-D core analysis accuracy is evaluated for a typical GII deflector design in order to assess the results against available plant measurements. (authors)

A Study on Efficiency Improvement of the Hybrid Monte Carlo/Deterministic Method for Global Transport Problems

International Nuclear Information System (INIS)

Kim, Jong Woo; Woo, Myeong Hyeon; Kim, Jae Hyun; Kim, Do Hyun; Shin, Chang Ho; Kim, Jong Kyung

2017-01-01

In this study hybrid Monte Carlo/Deterministic method is explained for radiation transport analysis in global system. FW-CADIS methodology construct the weight window parameter and it useful at most global MC calculation. However, Due to the assumption that a particle is scored at a tally, less particles are transported to the periphery of mesh tallies. For compensation this space-dependency, we modified the module in the ADVANTG code to add the proposed method. We solved the simple test problem for comparing with result from FW-CADIS methodology, it was confirmed that a uniform statistical error was secured as intended. In the future, it will be added more practical problems. It might be useful to perform radiation transport analysis using the Hybrid Monte Carlo/Deterministic method in global transport problems.

Methods and models in mathematical biology deterministic and stochastic approaches

CERN Document Server

Müller, Johannes

2015-01-01

This book developed from classes in mathematical biology taught by the authors over several years at the Technische Universität München. The main themes are modeling principles, mathematical principles for the analysis of these models, and model-based analysis of data. The key topics of modern biomathematics are covered: ecology, epidemiology, biochemistry, regulatory networks, neuronal networks, and population genetics. A variety of mathematical methods are introduced, ranging from ordinary and partial differential equations to stochastic graph theory and  branching processes. A special emphasis is placed on the interplay between stochastic and deterministic models.

Frequency domain fatigue damage estimation methods suitable for deterministic load spectra

Energy Technology Data Exchange (ETDEWEB)

Henderson, A.R.; Patel, M.H. [University Coll., Dept. of Mechanical Engineering, London (United Kingdom)

2000-07-01

The evaluation of fatigue damage due to load spectra, directly in the frequency domain, is a complex phenomena but with the benefit of significant computation time savings. Various formulae have been suggested but have usually relating to a specific application only. The Dirlik method is the exception and is applicable to general cases of continuous stochastic spectra. This paper describes three approaches for evaluating discrete deterministic load spectra generated by the floating wind turbine model developed the UCL/RAL research project. (Author)

Neutronics comparative analysis of plate-type research reactor using deterministic and stochastic methods

International Nuclear Information System (INIS)

Liu, Shichang; Wang, Guanbo; Wu, Gaochen; Wang, Kan

2015-01-01

Highlights: • DRAGON and DONJON are applied and verified in calculations of research reactors. • Continuous-energy Monte Carlo calculations by RMC are chosen as the references. • “ECCO” option of DRAGON is suitable for the calculations of research reactors. • Manual modifications of cross-sections are not necessary with DRAGON and DONJON. • DRAGON and DONJON agree well with RMC if appropriate treatments are applied. - Abstract: Simulation of the behavior of the plate-type research reactors such as JRR-3M and CARR poses a challenge for traditional neutronics calculation tools and schemes for power reactors, due to the characteristics of complex geometry, highly heterogeneity and large leakage of the research reactors. Two different theoretical approaches, the deterministic and the stochastic methods, are used for the neutronics analysis of the JRR-3M plate-type research reactor in this paper. For the deterministic method the neutronics codes DRAGON and DONJON are used, while the continuous-energy Monte Carlo code RMC (Reactor Monte Carlo code) is employed for the stochastic approach. The goal of this research is to examine the capability of the deterministic code system DRAGON and DONJON to reliably simulate the research reactors. The results indicate that the DRAGON and DONJON code system agrees well with the continuous-energy Monte Carlo simulation on both k eff and flux distributions if the appropriate treatments (such as the ECCO option) are applied

A deterministic alternative to the full configuration interaction quantum Monte Carlo method

Energy Technology Data Exchange (ETDEWEB)

Tubman, Norm M.; Lee, Joonho; Takeshita, Tyler Y.; Head-Gordon, Martin; Whaley, K. Birgitta [University of California, Berkeley, Berkeley, California 94720 (United States)

2016-07-28

Development of exponentially scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, is a useful algorithm that allows exact diagonalization through stochastically sampling determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, along with a stochastic projected wave function, to find the important parts of Hilbert space. However, the stochastic representation of the wave function is not required to search Hilbert space efficiently, and here we describe a highly efficient deterministic method that can achieve chemical accuracy for a wide range of systems, including the difficult Cr{sub 2} molecule. We demonstrate for systems like Cr{sub 2} that such calculations can be performed in just a few cpu hours which makes it one of the most efficient and accurate methods that can attain chemical accuracy for strongly correlated systems. In addition our method also allows efficient calculation of excited state energies, which we illustrate with benchmark results for the excited states of C{sub 2}.

Deterministic and stochastic methods of calculation of polarization characteristics of radiation in natural environment

Science.gov (United States)

Strelkov, S. A.; Sushkevich, T. A.; Maksakova, S. V.

2017-11-01

We are talking about russian achievements of the world level in the theory of radiation transfer, taking into account its polarization in natural media and the current scientific potential developing in Russia, which adequately provides the methodological basis for theoretically-calculated research of radiation processes and radiation fields in natural media using supercomputers and mass parallelism. A new version of the matrix transfer operator is proposed for solving problems of polarized radiation transfer in heterogeneous media by the method of influence functions, when deterministic and stochastic methods can be combined.

A plateau–valley separation method for textured surfaces with a deterministic pattern

DEFF Research Database (Denmark)

Godi, Alessandro; Kühle, Anders; De Chiffre, Leonardo

2014-01-01

The effective characterization of textured surfaces presenting a deterministic pattern of lubricant reservoirs is an issue with which many researchers are nowadays struggling. Existing standards are not suitable for the characterization of such surfaces, providing at times values without physical...... meaning. A new method based on the separation between the plateau and valley regions is hereby presented allowing independent functional analyses of the detected features. The determination of a proper threshold between plateaus and valleys is the first step of a procedure resulting in an efficient...

Burnup-dependent core neutronics analysis of plate-type research reactor using deterministic and stochastic methods

International Nuclear Information System (INIS)

Liu, Shichang; Wang, Guanbo; Liang, Jingang; Wu, Gaochen; Wang, Kan

2015-01-01

Highlights: • DRAGON & DONJON were applied in burnup calculations of plate-type research reactors. • Continuous-energy Monte Carlo burnup calculations by RMC were chosen as references. • Comparisons of keff, isotopic densities and power distribution were performed. • Reasons leading to discrepancies between two different approaches were analyzed. • DRAGON & DONJON is capable of burnup calculations with appropriate treatments. - Abstract: The burnup-dependent core neutronics analysis of the plate-type research reactors such as JRR-3M poses a challenge for traditional neutronics calculational tools and schemes for power reactors, due to the characteristics of complex geometry, highly heterogeneity, large leakage and the particular neutron spectrum of the research reactors. Two different theoretical approaches, the deterministic and the stochastic methods, are used for the burnup-dependent core neutronics analysis of the JRR-3M plate-type research reactor in this paper. For the deterministic method the neutronics codes DRAGON & DONJON are used, while the continuous-energy Monte Carlo code RMC (Reactor Monte Carlo code) is employed for the stochastic one. In the first stage, the homogenizations of few-group cross sections by DRAGON and the full core diffusion calculations by DONJON have been verified by comparing with the detailed Monte Carlo simulations. In the second stage, the burnup-dependent calculations of both assembly level and the full core level were carried out, to examine the capability of the deterministic code system DRAGON & DONJON to reliably simulate the burnup-dependent behavior of research reactors. The results indicate that both RMC and DRAGON & DONJON code system are capable of burnup-dependent neutronics analysis of research reactors, provided that appropriate treatments are applied in both assembly and core levels for the deterministic codes

Risk-based and deterministic regulation

International Nuclear Information System (INIS)

Fischer, L.E.; Brown, N.W.

1995-07-01

Both risk-based and deterministic methods are used for regulating the nuclear industry to protect the public safety and health from undue risk. The deterministic method is one where performance standards are specified for each kind of nuclear system or facility. The deterministic performance standards address normal operations and design basis events which include transient and accident conditions. The risk-based method uses probabilistic risk assessment methods to supplement the deterministic one by (1) addressing all possible events (including those beyond the design basis events), (2) using a systematic, logical process for identifying and evaluating accidents, and (3) considering alternative means to reduce accident frequency and/or consequences. Although both deterministic and risk-based methods have been successfully applied, there is need for a better understanding of their applications and supportive roles. This paper describes the relationship between the two methods and how they are used to develop and assess regulations in the nuclear industry. Preliminary guidance is suggested for determining the need for using risk based methods to supplement deterministic ones. However, it is recommended that more detailed guidance and criteria be developed for this purpose

Classification of Underlying Causes of Power Quality Disturbances: Deterministic versus Statistical Methods

Directory of Open Access Journals (Sweden)

Emmanouil Styvaktakis

2007-01-01

Full Text Available This paper presents the two main types of classification methods for power quality disturbances based on underlying causes: deterministic classification, giving an expert system as an example, and statistical classification, with support vector machines (a novel method as an example. An expert system is suitable when one has limited amount of data and sufficient power system expert knowledge; however, its application requires a set of threshold values. Statistical methods are suitable when large amount of data is available for training. Two important issues to guarantee the effectiveness of a classifier, data segmentation, and feature extraction are discussed. Segmentation of a sequence of data recording is preprocessing to partition the data into segments each representing a duration containing either an event or a transition between two events. Extraction of features is applied to each segment individually. Some useful features and their effectiveness are then discussed. Some experimental results are included for demonstrating the effectiveness of both systems. Finally, conclusions are given together with the discussion of some future research directions.

Separation of Stochastic and Deterministic Information from Seismological Time Series with Nonlinear Dynamics and Maximum Entropy Methods

International Nuclear Information System (INIS)

Gutierrez, Rafael M.; Useche, Gina M.; Buitrago, Elias

2007-01-01

We present a procedure developed to detect stochastic and deterministic information contained in empirical time series, useful to characterize and make models of different aspects of complex phenomena represented by such data. This procedure is applied to a seismological time series to obtain new information to study and understand geological phenomena. We use concepts and methods from nonlinear dynamics and maximum entropy. The mentioned method allows an optimal analysis of the available information

Method to deterministically study photonic nanostructures in different experimental instruments.

Science.gov (United States)

Husken, B H; Woldering, L A; Blum, C; Vos, W L

2009-01-01

We describe an experimental method to recover a single, deterministically fabricated nanostructure in various experimental instruments without the use of artificially fabricated markers, with the aim to study photonic structures. Therefore, a detailed map of the spatial surroundings of the nanostructure is made during the fabrication of the structure. These maps are made using a series of micrographs with successively decreasing magnifications. The graphs reveal intrinsic and characteristic geometric features that can subsequently be used in different setups to act as markers. As an illustration, we probe surface cavities with radii of 65 nm on a silica opal photonic crystal with various setups: a focused ion beam workstation; a scanning electron microscope (SEM); a wide field optical microscope and a confocal microscope. We use cross-correlation techniques to recover a small area imaged with the SEM in a large area photographed with the optical microscope, which provides a possible avenue to automatic searching. We show how both structural and optical reflectivity data can be obtained from one and the same nanostructure. Since our approach does not use artificial grids or markers, it is of particular interest for samples whose structure is not known a priori, like samples created solely by self-assembly. In addition, our method is not restricted to conducting samples.

Studies of criticality Monte Carlo method convergence: use of a deterministic calculation and automated detection of the transient

International Nuclear Information System (INIS)

Jinaphanh, A.

2012-01-01

Monte Carlo criticality calculation allows to estimate the effective multiplication factor as well as local quantities such as local reaction rates. Some configurations presenting weak neutronic coupling (high burn up profile, complete reactor core,...) may induce biased estimations for k eff or reaction rates. In order to improve robustness of the iterative Monte Carlo methods, a coupling with a deterministic code was studied. An adjoint flux is obtained by a deterministic calculation and then used in the Monte Carlo. The initial guess is then automated, the sampling of fission sites is modified and the random walk of neutrons is modified using splitting and russian roulette strategies. An automated convergence detection method has been developed. It locates and suppresses the transient due to the initialization in an output series, applied here to k eff and Shannon entropy. It relies on modeling stationary series by an order 1 auto regressive process and applying statistical tests based on a Student Bridge statistics. This method can easily be extended to every output of an iterative Monte Carlo. Methods developed in this thesis are tested on different test cases. (author)

Stochastic optimization methods

CERN Document Server

Marti, Kurt

2005-01-01

Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.

Deterministic sensitivity analysis of two-phase flow systems: forward and adjoint methods. Final report

International Nuclear Information System (INIS)

Cacuci, D.G.

1984-07-01

This report presents a self-contained mathematical formalism for deterministic sensitivity analysis of two-phase flow systems, a detailed application to sensitivity analysis of the homogeneous equilibrium model of two-phase flow, and a representative application to sensitivity analysis of a model (simulating pump-trip-type accidents in BWRs) where a transition between single phase and two phase occurs. The rigor and generality of this sensitivity analysis formalism stem from the use of Gateaux (G-) differentials. This report highlights the major aspects of deterministic (forward and adjoint) sensitivity analysis, including derivation of the forward sensitivity equations, derivation of sensitivity expressions in terms of adjoint functions, explicit construction of the adjoint system satisfied by these adjoint functions, determination of the characteristics of this adjoint system, and demonstration that these characteristics are the same as those of the original quasilinear two-phase flow equations. This proves that whenever the original two-phase flow problem is solvable, the adjoint system is also solvable and, in principle, the same numerical methods can be used to solve both the original and adjoint equations

A data analysis method for identifying deterministic components of stable and unstable time-delayed systems with colored noise

Energy Technology Data Exchange (ETDEWEB)

Patanarapeelert, K. [Faculty of Science, Department of Mathematics, Mahidol University, Rama VI Road, Bangkok 10400 (Thailand); Frank, T.D. [Institute for Theoretical Physics, University of Muenster, Wilhelm-Klemm-Str. 9, 48149 Muenster (Germany)]. E-mail: tdfrank@uni-muenster.de; Friedrich, R. [Institute for Theoretical Physics, University of Muenster, Wilhelm-Klemm-Str. 9, 48149 Muenster (Germany); Beek, P.J. [Faculty of Human Movement Sciences and Institute for Fundamental and Clinical Human Movement Sciences, Vrije Universiteit, Van der Boechorststraat 9, 1081 BT Amsterdam (Netherlands); Tang, I.M. [Faculty of Science, Department of Physics, Mahidol University, Rama VI Road, Bangkok 10400 (Thailand)

2006-12-18

A method is proposed to identify deterministic components of stable and unstable time-delayed systems subjected to noise sources with finite correlation times (colored noise). Both neutral and retarded delay systems are considered. For vanishing correlation times it is shown how to determine their noise amplitudes by minimizing appropriately defined Kullback measures. The method is illustrated by applying it to simulated data from stochastic time-delayed systems representing delay-induced bifurcations, postural sway and ship rolling.

Direct deterministic method for neutronics analysis and computation of asymptotic burnup distribution in a recirculating pebble-bed reactor

International Nuclear Information System (INIS)

Terry, W.K.; Gougar, H.D.; Ougouag, A.M.

2002-01-01

A new deterministic method has been developed for the neutronics analysis of a pebble-bed reactor (PBR). The method accounts for the flow of pebbles explicitly and couples the flow to the neutronics. The method allows modeling of once-through cycles as well as cycles in which pebbles are recirculated through the core an arbitrary number of times. This new work is distinguished from older methods by the systematically semi-analytical approach it takes. In particular, whereas older methods use the finite-difference approach (or an equivalent one) for the discretization and the solution of the burnup equation, the present work integrates the relevant differential equation analytically in discrete and complementary sub-domains of the reactor. Like some of the finite-difference codes, the new method obtains the asymptotic fuel-loading pattern directly, without modeling any intermediate loading pattern. This is a significant advantage for the design and optimization of the asymptotic fuel-loading pattern. The new method is capable of modeling directly both the once-through-then-out fuel cycle and the pebble recirculating fuel cycle. Although it currently includes a finite-difference neutronics solver, the new method has been implemented into a modular code that incorporates the framework for the future coupling to an efficient solver such as a nodal method and to modern cross section preparation capabilities. In its current state, the deterministic method presented here is capable of quick and efficient design and optimization calculations for the in-core PBR fuel cycle. The method can also be used as a practical 'scoping' tool. It could, for example, be applied to determine the potential of the PBR for resisting nuclear-weapons proliferation and to optimize proliferation-resistant features. However, the purpose of this paper is to show that the method itself is viable. Refinements to the code are under way, with the objective of producing a powerful reactor physics

An assessment of dietary exposure to glyphosate using refined deterministic and probabilistic methods.

Science.gov (United States)

Stephenson, C L; Harris, C A

2016-09-01

Glyphosate is a herbicide used to control broad-leaved weeds. Some uses of glyphosate in crop production can lead to residues of the active substance and related metabolites in food. This paper uses data on residue levels, processing information and consumption patterns, to assess theoretical lifetime dietary exposure to glyphosate. Initial estimates were made assuming exposure to the highest permitted residue levels in foods. These intakes were then refined using median residue levels from trials, processing information, and monitoring data to achieve a more realistic estimate of exposure. Estimates were made using deterministic and probabilistic methods. Exposures were compared to the acceptable daily intake (ADI)-the amount of a substance that can be consumed daily without an appreciable health risk. Refined deterministic intakes for all consumers were at or below 2.1% of the ADI. Variations were due to cultural differences in consumption patterns and the level of aggregation of the dietary information in calculation models, which allows refinements for processing. Probabilistic exposure estimates ranged from 0.03% to 0.90% of the ADI, depending on whether optimistic or pessimistic assumptions were made in the calculations. Additional refinements would be possible if further data on processing and from residues monitoring programmes were available. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrated Deterministic-Probabilistic Safety Assessment Methodologies

Energy Technology Data Exchange (ETDEWEB)

Kudinov, P.; Vorobyev, Y.; Sanchez-Perea, M.; Queral, C.; Jimenez Varas, G.; Rebollo, M. J.; Mena, L.; Gomez-Magin, J.

2014-02-01

IDPSA (Integrated Deterministic-Probabilistic Safety Assessment) is a family of methods which use tightly coupled probabilistic and deterministic approaches to address respective sources of uncertainties, enabling Risk informed decision making in a consistent manner. The starting point of the IDPSA framework is that safety justification must be based on the coupling of deterministic (consequences) and probabilistic (frequency) considerations to address the mutual interactions between stochastic disturbances (e.g. failures of the equipment, human actions, stochastic physical phenomena) and deterministic response of the plant (i.e. transients). This paper gives a general overview of some IDPSA methods as well as some possible applications to PWR safety analyses. (Author)

The dialectical thinking about deterministic and probabilistic safety analysis

International Nuclear Information System (INIS)

Qian Yongbai; Tong Jiejuan; Zhang Zuoyi; He Xuhong

2005-01-01

There are two methods in designing and analysing the safety performance of a nuclear power plant, the traditional deterministic method and the probabilistic method. To date, the design of nuclear power plant is based on the deterministic method. It has been proved in practice that the deterministic method is effective on current nuclear power plant. However, the probabilistic method (Probabilistic Safety Assessment - PSA) considers a much wider range of faults, takes an integrated look at the plant as a whole, and uses realistic criteria for the performance of the systems and constructions of the plant. PSA can be seen, in principle, to provide a broader and realistic perspective on safety issues than the deterministic approaches. In this paper, the historical origins and development trend of above two methods are reviewed and summarized in brief. Based on the discussion of two application cases - one is the changes to specific design provisions of the general design criteria (GDC) and the other is the risk-informed categorization of structure, system and component, it can be concluded that the deterministic method and probabilistic method are dialectical and unified, and that they are being merged into each other gradually, and being used in coordination. (authors)

Transmission power control in WSNs : from deterministic to cognitive methods

NARCIS (Netherlands)

Chincoli, M.; Liotta, A.; Gravina, R.; Palau, C.E.; Manso, M.; Liotta, A.; Fortino, G.

2018-01-01

Communications in Wireless Sensor Networks (WSNs) are affected by dynamic environments, variable signal fluctuations and interference. Thus, prompt actions are necessary to achieve dependable communications and meet Quality of Service (QoS) requirements. To this end, the deterministic algorithms

STOCHASTIC METHODS IN RISK ANALYSIS

Directory of Open Access Journals (Sweden)

Vladimíra OSADSKÁ

2017-06-01

Full Text Available In this paper, we review basic stochastic methods which can be used to extend state-of-the-art deterministic analytical methods for risk analysis. We can conclude that the standard deterministic analytical methods highly depend on the practical experience and knowledge of the evaluator and therefore, the stochastic methods should be introduced. The new risk analysis methods should consider the uncertainties in input values. We present how large is the impact on the results of the analysis solving practical example of FMECA with uncertainties modelled using Monte Carlo sampling.

Deterministic alternatives to the full configuration interaction quantum Monte Carlo method for strongly correlated systems

Science.gov (United States)

Tubman, Norm; Whaley, Birgitta

The development of exponential scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, allows exact diagonalization through stochastically sampling of determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, together with a stochastic projected wave function, which are used to explore the important parts of Hilbert space. However, a stochastic representation of the wave function is not required to search Hilbert space efficiently and new deterministic approaches have recently been shown to efficiently find the important parts of determinant space. We shall discuss the technique of Adaptive Sampling Configuration Interaction (ASCI) and the related heat-bath Configuration Interaction approach for ground state and excited state simulations. We will present several applications for strongly correlated Hamiltonians. This work was supported through the Scientific Discovery through Advanced Computing (SciDAC) program funded by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences.

Quantifying diffusion MRI tractography of the corticospinal tract in brain tumors with deterministic and probabilistic methods.

Science.gov (United States)

Bucci, Monica; Mandelli, Maria Luisa; Berman, Jeffrey I; Amirbekian, Bagrat; Nguyen, Christopher; Berger, Mitchel S; Henry, Roland G

2013-01-01

sensitivity (79%) as determined from cortical IES compared to deterministic q-ball (50%), probabilistic DTI (36%), and deterministic DTI (10%). The sensitivity using the q-ball algorithm (65%) was significantly higher than using DTI (23%) (p probabilistic algorithms (58%) were more sensitive than deterministic approaches (30%) (p = 0.003). Probabilistic q-ball fiber tracks had the smallest offset to the subcortical stimulation sites. The offsets between diffusion fiber tracks and subcortical IES sites were increased significantly for those cases where the diffusion fiber tracks were visibly thinner than expected. There was perfect concordance between the subcortical IES function (e.g. hand stimulation) and the cortical connection of the nearest diffusion fiber track (e.g. upper extremity cortex). This study highlights the tremendous utility of intraoperative stimulation sites to provide a gold standard from which to evaluate diffusion MRI fiber tracking methods and has provided an object standard for evaluation of different diffusion models and approaches to fiber tracking. The probabilistic q-ball fiber tractography was significantly better than DTI methods in terms of sensitivity and accuracy of the course through the white matter. The commonly used DTI fiber tracking approach was shown to have very poor sensitivity (as low as 10% for deterministic DTI fiber tracking) for delineation of the lateral aspects of the corticospinal tract in our study. Effects of the tumor/edema resulted in significantly larger offsets between the subcortical IES and the preoperative fiber tracks. The provided data show that probabilistic HARDI tractography is the most objective and reproducible analysis but given the small sample and number of stimulation points a generalization about our results should be given with caution. Indeed our results inform the capabilities of preoperative diffusion fiber tracking and indicate that such data should be used carefully when making pre-surgical and

Development of a consistent Monte Carlo-deterministic transport methodology based on the method of characteristics and MCNP5

International Nuclear Information System (INIS)

Karriem, Z.; Ivanov, K.; Zamonsky, O.

2011-01-01

This paper presents work that has been performed to develop an integrated Monte Carlo- Deterministic transport methodology in which the two methods make use of exactly the same general geometry and multigroup nuclear data. The envisioned application of this methodology is in reactor lattice physics methods development and shielding calculations. The methodology will be based on the Method of Long Characteristics (MOC) and the Monte Carlo N-Particle Transport code MCNP5. Important initial developments pertaining to ray tracing and the development of an MOC flux solver for the proposed methodology are described. Results showing the viability of the methodology are presented for two 2-D general geometry transport problems. The essential developments presented is the use of MCNP as geometry construction and ray tracing tool for the MOC, verification of the ray tracing indexing scheme that was developed to represent the MCNP geometry in the MOC and the verification of the prototype 2-D MOC flux solver. (author)

Comparison of Monte Carlo method and deterministic method for neutron transport calculation

International Nuclear Information System (INIS)

Mori, Takamasa; Nakagawa, Masayuki

1987-01-01

The report outlines major features of the Monte Carlo method by citing various applications of the method and techniques used for Monte Carlo codes. Major areas of its application include analysis of measurements on fast critical assemblies, nuclear fusion reactor neutronics analysis, criticality safety analysis, evaluation by VIM code, and calculation for shielding. Major techniques used for Monte Carlo codes include the random walk method, geometric expression method (combinatorial geometry, 1, 2, 4-th degree surface and lattice geometry), nuclear data expression, evaluation method (track length, collision, analog (absorption), surface crossing, point), and dispersion reduction (Russian roulette, splitting, exponential transform, importance sampling, corrected sampling). Major features of the Monte Carlo method are as follows: 1) neutron source distribution and systems of complex geometry can be simulated accurately, 2) physical quantities such as neutron flux in a place, on a surface or at a point can be evaluated, and 3) calculation requires less time. (Nogami, K.)

Forward and Inverse Modeling of Self-potential. A Tomography of Groundwater Flow and Comparison Between Deterministic and Stochastic Inversion Methods

Science.gov (United States)

Quintero-Chavarria, E.; Ochoa Gutierrez, L. H.

2016-12-01

Applications of the Self-potential Method in the fields of Hydrogeology and Environmental Sciences have had significant developments during the last two decades with a strong use on groundwater flows identification. Although only few authors deal with the forward problem's solution -especially in geophysics literature- different inversion procedures are currently being developed but in most cases they are compared with unconventional groundwater velocity fields and restricted to structured meshes. This research solves the forward problem based on the finite element method using the St. Venant's Principle to transform a point dipole, which is the field generated by a single vector, into a distribution of electrical monopoles. Then, two simple aquifer models were generated with specific boundary conditions and head potentials, velocity fields and electric potentials in the medium were computed. With the model's surface electric potential, the inverse problem is solved to retrieve the source of electric potential (vector field associated to groundwater flow) using deterministic and stochastic approaches. The first approach was carried out by implementing a Tikhonov regularization with a stabilized operator adapted to the finite element mesh while for the second a hierarchical Bayesian model based on Markov chain Monte Carlo (McMC) and Markov Random Fields (MRF) was constructed. For all implemented methods, the result between the direct and inverse models was contrasted in two ways: 1) shape and distribution of the vector field, and 2) magnitude's histogram. Finally, it was concluded that inversion procedures are improved when the velocity field's behavior is considered, thus, the deterministic method is more suitable for unconfined aquifers than confined ones. McMC has restricted applications and requires a lot of information (particularly in potentials fields) while MRF has a remarkable response especially when dealing with confined aquifers.

Feasibility of a Monte Carlo-deterministic hybrid method for fast reactor analysis

Energy Technology Data Exchange (ETDEWEB)

Heo, W.; Kim, W.; Kim, Y. [Korea Advanced Institute of Science and Technology - KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701 (Korea, Republic of); Yun, S. [Korea Atomic Energy Research Institute - KAERI, 989-111 Daedeok-daero, Yuseong-gu, Daejeon, 305-353 (Korea, Republic of)

2013-07-01

A Monte Carlo and deterministic hybrid method is investigated for the analysis of fast reactors in this paper. Effective multi-group cross sections data are generated using a collision estimator in the MCNP5. A high order Legendre scattering cross section data generation module was added into the MCNP5 code. Both cross section data generated from MCNP5 and TRANSX/TWODANT using the homogeneous core model were compared, and were applied to DIF3D code for fast reactor core analysis of a 300 MWe SFR TRU burner core. For this analysis, 9 groups macroscopic-wise data was used. In this paper, a hybrid calculation MCNP5/DIF3D was used to analyze the core model. The cross section data was generated using MCNP5. The k{sub eff} and core power distribution were calculated using the 54 triangle FDM code DIF3D. A whole core calculation of the heterogeneous core model using the MCNP5 was selected as a reference. In terms of the k{sub eff}, 9-group MCNP5/DIF3D has a discrepancy of -154 pcm from the reference solution, 9-group TRANSX/TWODANT/DIF3D analysis gives -1070 pcm discrepancy. (authors)

Deterministic sensitivity and uncertainty analysis for large-scale computer models

International Nuclear Information System (INIS)

Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.

1988-01-01

The fields of sensitivity and uncertainty analysis have traditionally been dominated by statistical techniques when large-scale modeling codes are being analyzed. These methods are able to estimate sensitivities, generate response surfaces, and estimate response probability distributions given the input parameter probability distributions. Because the statistical methods are computationally costly, they are usually applied only to problems with relatively small parameter sets. Deterministic methods, on the other hand, are very efficient and can handle large data sets, but generally require simpler models because of the considerable programming effort required for their implementation. The first part of this paper reports on the development and availability of two systems, GRESS and ADGEN, that make use of computer calculus compilers to automate the implementation of deterministic sensitivity analysis capability into existing computer models. This automation removes the traditional limitation of deterministic sensitivity methods. This second part of the paper describes a deterministic uncertainty analysis method (DUA) that uses derivative information as a basis to propagate parameter probability distributions to obtain result probability distributions. This paper is applicable to low-level radioactive waste disposal system performance assessment

Seismic Hazard Assessment for a Characteristic Earthquake Scenario: Probabilistic-Deterministic Method

Science.gov (United States)

mouloud, Hamidatou

2016-04-01

The objective of this paper is to analyze the seismic activity and the statistical treatment of seismicity catalog the Constantine region between 1357 and 2014 with 7007 seismic event. Our research is a contribution to improving the seismic risk management by evaluating the seismic hazard in the North-East Algeria. In the present study, Earthquake hazard maps for the Constantine region are calculated. Probabilistic seismic hazard analysis (PSHA) is classically performed through the Cornell approach by using a uniform earthquake distribution over the source area and a given magnitude range. This study aims at extending the PSHA approach to the case of a characteristic earthquake scenario associated with an active fault. The approach integrates PSHA with a high-frequency deterministic technique for the prediction of peak and spectral ground motion parameters in a characteristic earthquake. The method is based on the site-dependent evaluation of the probability of exceedance for the chosen strong-motion parameter. We proposed five sismotectonique zones. Four steps are necessary: (i) identification of potential sources of future earthquakes, (ii) assessment of their geological, geophysical and geometric, (iii) identification of the attenuation pattern of seismic motion, (iv) calculation of the hazard at a site and finally (v) hazard mapping for a region. In this study, the procedure of the earthquake hazard evaluation recently developed by Kijko and Sellevoll (1992) is used to estimate seismic hazard parameters in the northern part of Algeria.

GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method

International Nuclear Information System (INIS)

Gong Chunye; Liu Jie; Chi Lihua; Huang Haowei; Fang Jingyue; Gong Zhenghu

2011-01-01

Graphics Processing Unit (GPU), originally developed for real-time, high-definition 3D graphics in computer games, now provides great faculty in solving scientific applications. The basis of particle transport simulation is the time-dependent, multi-group, inhomogeneous Boltzmann transport equation. The numerical solution to the Boltzmann equation involves the discrete ordinates (S n ) method and the procedure of source iteration. In this paper, we present a GPU accelerated simulation of one energy group time-independent deterministic discrete ordinates particle transport in 3D Cartesian geometry (Sweep3D). The performance of the GPU simulations are reported with the simulations of vacuum boundary condition. The discussion of the relative advantages and disadvantages of the GPU implementation, the simulation on multi GPUs, the programming effort and code portability are also reported. The results show that the overall performance speedup of one NVIDIA Tesla M2050 GPU ranges from 2.56 compared with one Intel Xeon X5670 chip to 8.14 compared with one Intel Core Q6600 chip for no flux fixup. The simulation with flux fixup on one M2050 is 1.23 times faster than on one X5670.

GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method

Science.gov (United States)

Gong, Chunye; Liu, Jie; Chi, Lihua; Huang, Haowei; Fang, Jingyue; Gong, Zhenghu

2011-07-01

Graphics Processing Unit (GPU), originally developed for real-time, high-definition 3D graphics in computer games, now provides great faculty in solving scientific applications. The basis of particle transport simulation is the time-dependent, multi-group, inhomogeneous Boltzmann transport equation. The numerical solution to the Boltzmann equation involves the discrete ordinates ( Sn) method and the procedure of source iteration. In this paper, we present a GPU accelerated simulation of one energy group time-independent deterministic discrete ordinates particle transport in 3D Cartesian geometry (Sweep3D). The performance of the GPU simulations are reported with the simulations of vacuum boundary condition. The discussion of the relative advantages and disadvantages of the GPU implementation, the simulation on multi GPUs, the programming effort and code portability are also reported. The results show that the overall performance speedup of one NVIDIA Tesla M2050 GPU ranges from 2.56 compared with one Intel Xeon X5670 chip to 8.14 compared with one Intel Core Q6600 chip for no flux fixup. The simulation with flux fixup on one M2050 is 1.23 times faster than on one X5670.

Non deterministic methods for charged particle transport

International Nuclear Information System (INIS)

Besnard, D.C.; Buresi, E.; Hermeline, F.; Wagon, F.

1985-04-01

The coupling of Monte-Carlo methods for solving Fokker Planck equation with ICF inertial confinement fusion codes requires them to be economical and to preserve gross conservation properties. Besides, the presence in FPE Fokker-Planck equation of diffusion terms due to collisions between test particles and the background plasma challenges standard M.C. (Monte-Carlo) techniques if this phenomenon is dominant. We address these problems through the use of a fixed mesh in phase space which allows us to handle highly variable sources, avoiding any Russian Roulette for lowering the size of the sample. Also on this mesh are solved diffusion equations obtained from a splitting of FPE. Any non linear diffusion terms of FPE can be handled in this manner. Another method, also presented here is to use a direct particle method for solving the full FPE

Review of Hybrid (Deterministic/Monte Carlo) Radiation Transport Methods, Codes, and Applications at Oak Ridge National Laboratory

International Nuclear Information System (INIS)

Wagner, John C.; Peplow, Douglas E.; Mosher, Scott W.; Evans, Thomas M.

2010-01-01

This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods and codes used at the Oak Ridge National Laboratory and examples of their application for increasing the efficiency of real-world, fixed-source Monte Carlo analyses. The two principal hybrid methods are (1) Consistent Adjoint Driven Importance Sampling (CADIS) for optimization of a localized detector (tally) region (e.g., flux, dose, or reaction rate at a particular location) and (2) Forward Weighted CADIS (FW-CADIS) for optimizing distributions (e.g., mesh tallies over all or part of the problem space) or multiple localized detector regions (e.g., simultaneous optimization of two or more localized tally regions). The two methods have been implemented and automated in both the MAVRIC sequence of SCALE 6 and ADVANTG, a code that works with the MCNP code. As implemented, the methods utilize the results of approximate, fast-running 3-D discrete ordinates transport calculations (with the Denovo code) to generate consistent space- and energy-dependent source and transport (weight windows) biasing parameters. These methods and codes have been applied to many relevant and challenging problems, including calculations of PWR ex-core thermal detector response, dose rates throughout an entire PWR facility, site boundary dose from arrays of commercial spent fuel storage casks, radiation fields for criticality accident alarm system placement, and detector response for special nuclear material detection scenarios and nuclear well-logging tools. Substantial computational speed-ups, generally O(10 2-4 ), have been realized for all applications to date. This paper provides a brief review of the methods, their implementation, results of their application, and current development activities, as well as a considerable list of references for readers seeking more information about the methods and/or their applications.

Review of Hybrid (Deterministic/Monte Carlo) Radiation Transport Methods, Codes, and Applications at Oak Ridge National Laboratory

International Nuclear Information System (INIS)

Wagner, John C.; Peplow, Douglas E.; Mosher, Scott W.; Evans, Thomas M.

2010-01-01

This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods and codes used at the Oak Ridge National Laboratory and examples of their application for increasing the efficiency of real-world, fixed-source Monte Carlo analyses. The two principal hybrid methods are (1) Consistent Adjoint Driven Importance Sampling (CADIS) for optimization of a localized detector (tally) region (e.g., flux, dose, or reaction rate at a particular location) and (2) Forward Weighted CADIS (FW-CADIS) for optimizing distributions (e.g., mesh tallies over all or part of the problem space) or multiple localized detector regions (e.g., simultaneous optimization of two or more localized tally regions). The two methods have been implemented and automated in both the MAVRIC sequence of SCALE 6 and ADVANTG, a code that works with the MCNP code. As implemented, the methods utilize the results of approximate, fast-running 3-D discrete ordinates transport calculations (with the Denovo code) to generate consistent space- and energy-dependent source and transport (weight windows) biasing parameters. These methods and codes have been applied to many relevant and challenging problems, including calculations of PWR ex-core thermal detector response, dose rates throughout an entire PWR facility, site boundary dose from arrays of commercial spent fuel storage casks, radiation fields for criticality accident alarm system placement, and detector response for special nuclear material detection scenarios and nuclear well-logging tools. Substantial computational speed-ups, generally O(102-4), have been realized for all applications to date. This paper provides a brief review of the methods, their implementation, results of their application, and current development activities, as well as a considerable list of references for readers seeking more information about the methods and/or their applications.

Review of hybrid (deterministic/Monte Carlo) radiation transport methods, codes, and applications at Oak Ridge National Laboratory

International Nuclear Information System (INIS)

Wagner, J.C.; Peplow, D.E.; Mosher, S.W.; Evans, T.M.

2010-01-01

This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods and codes used at the Oak Ridge National Laboratory and examples of their application for increasing the efficiency of real-world, fixed-source Monte Carlo analyses. The two principal hybrid methods are (1) Consistent Adjoint Driven Importance Sampling (CADIS) for optimization of a localized detector (tally) region (e.g., flux, dose, or reaction rate at a particular location) and (2) Forward Weighted CADIS (FW-CADIS) for optimizing distributions (e.g., mesh tallies over all or part of the problem space) or multiple localized detector regions (e.g., simultaneous optimization of two or more localized tally regions). The two methods have been implemented and automated in both the MAVRIC sequence of SCALE 6 and ADVANTG, a code that works with the MCNP code. As implemented, the methods utilize the results of approximate, fast-running 3-D discrete ordinates transport calculations (with the Denovo code) to generate consistent space- and energy-dependent source and transport (weight windows) biasing parameters. These methods and codes have been applied to many relevant and challenging problems, including calculations of PWR ex-core thermal detector response, dose rates throughout an entire PWR facility, site boundary dose from arrays of commercial spent fuel storage casks, radiation fields for criticality accident alarm system placement, and detector response for special nuclear material detection scenarios and nuclear well-logging tools. Substantial computational speed-ups, generally O(10 2-4 ), have been realized for all applications to date. This paper provides a brief review of the methods, their implementation, results of their application, and current development activities, as well as a considerable list of references for readers seeking more information about the methods and/or their applications. (author)

A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths.

Science.gov (United States)

Olariu, Victor; Manesso, Erica; Peterson, Carsten

2017-06-01

Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis-Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its interactions would open up the possibility of swiftly identifying cell states and computing optimal paths, including those of cell reprogramming, thereby avoiding exhaustive trial-and-error simulations with rate equations for different parameter sets. It turns out that sigmoidal rate equations do have approximate free energy associations. With this replacement of rate equations, we develop a deterministic method for estimating the free energy surfaces of systems of interacting genes at different noise levels or temperatures. Once such free energy landscape estimates have been established, we adapt a shortest path algorithm to determine optimal routes in the landscapes. We explore the method on three circuits for haematopoiesis and embryonic stem cell development for commitment and reprogramming scenarios and illustrate how the method can be used to determine sequential steps for onsets of external factors, essential for efficient reprogramming.

Probabilistic methods for physics

International Nuclear Information System (INIS)

Cirier, G

2013-01-01

We present an asymptotic method giving a probability of presence of the iterated spots of R d by a polynomial function f. We use the well-known Perron Frobenius operator (PF) that lets certain sets and measure invariant by f. Probabilistic solutions can exist for the deterministic iteration. If the theoretical result is already known, here we quantify these probabilities. This approach seems interesting to use for computing situations when the deterministic methods don't run. Among the examined applications, are asymptotic solutions of Lorenz, Navier-Stokes or Hamilton's equations. In this approach, linearity induces many difficult problems, all of whom we have not yet resolved.

Computational methods working group

International Nuclear Information System (INIS)

Gabriel, T.A.

1997-09-01

During the Cold Moderator Workshop several working groups were established including one to discuss calculational methods. The charge for this working group was to identify problems in theory, data, program execution, etc., and to suggest solutions considering both deterministic and stochastic methods including acceleration procedures.

Spent Fuel Pool Dose Rate Calculations Using Point Kernel and Hybrid Deterministic-Stochastic Shielding Methods

International Nuclear Information System (INIS)

Matijevic, M.; Grgic, D.; Jecmenica, R.

2016-01-01

This paper presents comparison of the Krsko Power Plant simplified Spent Fuel Pool (SFP) dose rates using different computational shielding methodologies. The analysis was performed to estimate limiting gamma dose rates on wall mounted level instrumentation in case of significant loss of cooling water. The SFP was represented with simple homogenized cylinders (point kernel and Monte Carlo (MC)) or cuboids (MC) using uranium, iron, water, and dry-air as bulk region materials. The pool is divided on the old and new section where the old one has three additional subsections representing fuel assemblies (FAs) with different burnup/cooling time (60 days, 1 year and 5 years). The new section represents the FAs with the cooling time of 10 years. The time dependent fuel assembly isotopic composition was calculated using ORIGEN2 code applied to the depletion of one of the fuel assemblies present in the pool (AC-29). The source used in Microshield calculation is based on imported isotopic activities. The time dependent photon spectra with total source intensity from Microshield multigroup point kernel calculations was then prepared for two hybrid deterministic-stochastic sequences. One is based on SCALE/MAVRIC (Monaco and Denovo) methodology and another uses Monte Carlo code MCNP6.1.1b and ADVANTG3.0.1. code. Even though this model is a fairly simple one, the layers of shielding materials are thick enough to pose a significant shielding problem for MC method without the use of effective variance reduction (VR) technique. For that purpose the ADVANTG code was used to generate VR parameters (SB cards in SDEF and WWINP file) for MCNP fixed-source calculation using continuous energy transport. ADVATNG employs a deterministic forward-adjoint transport solver Denovo which implements CADIS/FW-CADIS methodology. Denovo implements a structured, Cartesian-grid SN solver based on the Koch-Baker-Alcouffe parallel transport sweep algorithm across x-y domain blocks. This was first

Deterministic flows of order-parameters in stochastic processes of quantum Monte Carlo method

International Nuclear Information System (INIS)

Inoue, Jun-ichi

2010-01-01

In terms of the stochastic process of quantum-mechanical version of Markov chain Monte Carlo method (the MCMC), we analytically derive macroscopically deterministic flow equations of order parameters such as spontaneous magnetization in infinite-range (d(= ∞)-dimensional) quantum spin systems. By means of the Trotter decomposition, we consider the transition probability of Glauber-type dynamics of microscopic states for the corresponding (d + 1)-dimensional classical system. Under the static approximation, differential equations with respect to macroscopic order parameters are explicitly obtained from the master equation that describes the microscopic-law. In the steady state, we show that the equations are identical to the saddle point equations for the equilibrium state of the same system. The equation for the dynamical Ising model is recovered in the classical limit. We also check the validity of the static approximation by making use of computer simulations for finite size systems and discuss several possible extensions of our approach to disordered spin systems for statistical-mechanical informatics. Especially, we shall use our procedure to evaluate the decoding process of Bayesian image restoration. With the assistance of the concept of dynamical replica theory (the DRT), we derive the zero-temperature flow equation of image restoration measure showing some 'non-monotonic' behaviour in its time evolution.

Deterministic hazard quotients (HQs): Heading down the wrong road

International Nuclear Information System (INIS)

Wilde, L.; Hunter, C.; Simpson, J.

1995-01-01

The use of deterministic hazard quotients (HQs) in ecological risk assessment is common as a screening method in remediation of brownfield sites dominated by total petroleum hydrocarbon (TPH) contamination. An HQ ≥ 1 indicates further risk evaluation is needed, but an HQ ≤ 1 generally excludes a site from further evaluation. Is the predicted hazard known with such certainty that differences of 10% (0.1) do not affect the ability to exclude or include a site from further evaluation? Current screening methods do not quantify uncertainty associated with HQs. To account for uncertainty in the HQ, exposure point concentrations (EPCs) or ecological benchmark values (EBVs) are conservatively biased. To increase understanding of the uncertainty associated with HQs, EPCs (measured and modeled) and toxicity EBVs were evaluated using a conservative deterministic HQ method. The evaluation was then repeated using a probabilistic (stochastic) method. The probabilistic method used data distributions for EPCs and EBVs to generate HQs with measurements of associated uncertainty. Sensitivity analyses were used to identify the most important factors significantly influencing risk determination. Understanding uncertainty associated with HQ methods gives risk managers a more powerful tool than deterministic approaches

Distinguishing deterministic and noise components in ELM time series

International Nuclear Information System (INIS)

Zvejnieks, G.; Kuzovkov, V.N

2004-01-01

Full text: One of the main problems in the preliminary data analysis is distinguishing the deterministic and noise components in the experimental signals. For example, in plasma physics the question arises analyzing edge localized modes (ELMs): is observed ELM behavior governed by a complicate deterministic chaos or just by random processes. We have developed methodology based on financial engineering principles, which allows us to distinguish deterministic and noise components. We extended the linear auto regression method (AR) by including the non-linearity (NAR method). As a starting point we have chosen the nonlinearity in the polynomial form, however, the NAR method can be extended to any other type of non-linear functions. The best polynomial model describing the experimental ELM time series was selected using Bayesian Information Criterion (BIC). With this method we have analyzed type I ELM behavior in a subset of ASDEX Upgrade shots. Obtained results indicate that a linear AR model can describe the ELM behavior. In turn, it means that type I ELM behavior is of a relaxation or random type

Radiation transport calculation methods in BNCT

International Nuclear Information System (INIS)

Koivunoro, H.; Seppaelae, T.; Savolainen, S.

2000-01-01

Boron neutron capture therapy (BNCT) is used as a radiotherapy for malignant brain tumours. Radiation dose distribution is necessary to determine individually for each patient. Radiation transport and dose distribution calculations in BNCT are more complicated than in conventional radiotherapy. Total dose in BNCT consists of several different dose components. The most important dose component for tumour control is therapeutic boron dose D B . The other dose components are gamma dose D g , incident fast neutron dose D f ast n and nitrogen dose D N . Total dose is a weighted sum of the dose components. Calculation of neutron and photon flux is a complex problem and requires numerical methods, i.e. deterministic or stochastic simulation methods. Deterministic methods are based on the numerical solution of Boltzmann transport equation. Such are discrete ordinates (SN) and spherical harmonics (PN) methods. The stochastic simulation method for calculation of radiation transport is known as Monte Carlo method. In the deterministic methods the spatial geometry is partitioned into mesh elements. In SN method angular integrals of the transport equation are replaced with weighted sums over a set of discrete angular directions. Flux is calculated iteratively for all these mesh elements and for each discrete direction. Discrete ordinates transport codes used in the dosimetric calculations are ANISN, DORT and TORT. In PN method a Legendre expansion for angular flux is used instead of discrete direction fluxes, land the angular dependency comes a property of vector function space itself. Thus, only spatial iterations are required for resulting equations. A novel radiation transport code based on PN method and tree-multigrid technique (TMG) has been developed at VTT (Technical Research Centre of Finland). Monte Carlo method solves the radiation transport by randomly selecting neutrons and photons from a prespecified boundary source and following the histories of selected particles

Deterministic chaotic dynamics of Raba River flow (Polish Carpathian Mountains)

Science.gov (United States)

Kędra, Mariola

2014-02-01

Is the underlying dynamics of river flow random or deterministic? If it is deterministic, is it deterministic chaotic? This issue is still controversial. The application of several independent methods, techniques and tools for studying daily river flow data gives consistent, reliable and clear-cut results to the question. The outcomes point out that the investigated discharge dynamics is not random but deterministic. Moreover, the results completely confirm the nonlinear deterministic chaotic nature of the studied process. The research was conducted on daily discharge from two selected gauging stations of the mountain river in southern Poland, the Raba River.

Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology.

Science.gov (United States)

Schaff, James C; Gao, Fei; Li, Ye; Novak, Igor L; Slepchenko, Boris M

2016-12-01

Hybrid deterministic-stochastic methods provide an efficient alternative to a fully stochastic treatment of models which include components with disparate levels of stochasticity. However, general-purpose hybrid solvers for spatially resolved simulations of reaction-diffusion systems are not widely available. Here we describe fundamentals of a general-purpose spatial hybrid method. The method generates realizations of a spatially inhomogeneous hybrid system by appropriately integrating capabilities of a deterministic partial differential equation solver with a popular particle-based stochastic simulator, Smoldyn. Rigorous validation of the algorithm is detailed, using a simple model of calcium 'sparks' as a testbed. The solver is then applied to a deterministic-stochastic model of spontaneous emergence of cell polarity. The approach is general enough to be implemented within biologist-friendly software frameworks such as Virtual Cell.

Deterministic methods to solve the integral transport equation in neutronic

International Nuclear Information System (INIS)

Warin, X.

1993-11-01

We present a synthesis of the methods used to solve the integral transport equation in neutronic. This formulation is above all used to compute solutions in 2D in heterogeneous assemblies. Three kinds of methods are described: - the collision probability method; - the interface current method; - the current coupling collision probability method. These methods don't seem to be the most effective in 3D. (author). 9 figs

When to conduct probabilistic linkage vs. deterministic linkage? A simulation study.

Science.gov (United States)

Zhu, Ying; Matsuyama, Yutaka; Ohashi, Yasuo; Setoguchi, Soko

2015-08-01

When unique identifiers are unavailable, successful record linkage depends greatly on data quality and types of variables available. While probabilistic linkage theoretically captures more true matches than deterministic linkage by allowing imperfection in identifiers, studies have shown inconclusive results likely due to variations in data quality, implementation of linkage methodology and validation method. The simulation study aimed to understand data characteristics that affect the performance of probabilistic vs. deterministic linkage. We created ninety-six scenarios that represent real-life situations using non-unique identifiers. We systematically introduced a range of discriminative power, rate of missing and error, and file size to increase linkage patterns and difficulties. We assessed the performance difference of linkage methods using standard validity measures and computation time. Across scenarios, deterministic linkage showed advantage in PPV while probabilistic linkage showed advantage in sensitivity. Probabilistic linkage uniformly outperformed deterministic linkage as the former generated linkages with better trade-off between sensitivity and PPV regardless of data quality. However, with low rate of missing and error in data, deterministic linkage performed not significantly worse. The implementation of deterministic linkage in SAS took less than 1min, and probabilistic linkage took 2min to 2h depending on file size. Our simulation study demonstrated that the intrinsic rate of missing and error of linkage variables was key to choosing between linkage methods. In general, probabilistic linkage was a better choice, but for exceptionally good quality data (<5% error), deterministic linkage was a more resource efficient choice. Copyright © 2015 Elsevier Inc. All rights reserved.

Learning to Act: Qualitative Learning of Deterministic Action Models

DEFF Research Database (Denmark)

Bolander, Thomas; Gierasimczuk, Nina

2017-01-01

In this article we study learnability of fully observable, universally applicable action models of dynamic epistemic logic. We introduce a framework for actions seen as sets of transitions between propositional states and we relate them to their dynamic epistemic logic representations as action...... in the limit (inconclusive convergence to the right action model). We show that deterministic actions are finitely identifiable, while arbitrary (non-deterministic) actions require more learning power—they are identifiable in the limit. We then move on to a particular learning method, i.e. learning via update......, which proceeds via restriction of a space of events within a learning-specific action model. We show how this method can be adapted to learn conditional and unconditional deterministic action models. We propose update learning mechanisms for the afore mentioned classes of actions and analyse...

Deterministic uncertainty analysis

International Nuclear Information System (INIS)

Worley, B.A.

1987-12-01

This paper presents a deterministic uncertainty analysis (DUA) method for calculating uncertainties that has the potential to significantly reduce the number of computer runs compared to conventional statistical analysis. The method is based upon the availability of derivative and sensitivity data such as that calculated using the well known direct or adjoint sensitivity analysis techniques. Formation of response surfaces using derivative data and the propagation of input probability distributions are discussed relative to their role in the DUA method. A sample problem that models the flow of water through a borehole is used as a basis to compare the cumulative distribution function of the flow rate as calculated by the standard statistical methods and the DUA method. Propogation of uncertainties by the DUA method is compared for ten cases in which the number of reference model runs was varied from one to ten. The DUA method gives a more accurate representation of the true cumulative distribution of the flow rate based upon as few as two model executions compared to fifty model executions using a statistical approach. 16 refs., 4 figs., 5 tabs

Lectures on Monte Carlo methods

CERN Document Server

Madras, Neal

2001-01-01

Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati

Probabilistic evaluation method of stability of ground and slope considering spatial randomness of soil properties

International Nuclear Information System (INIS)

Ohtori, Yasuki

2004-01-01

In the JEAG4601-1987 (Japan Electric Association Guide for earthquake resistance design), either the conventional deterministic method or probabilistic method is used for evaluating the stability of ground foundations and surrounding slopes in nuclear power plants. The deterministic method, in which the soil properties of 'mean ± coefficient x standard deviation' is adopted for the calculations, is generally used in the design stage to data. On the other hand, the probabilistic method, in which the soil properties assume to have probabilistic distributions, is stated as a future method. The deterministic method facilitates the evaluation, however, it is necessary to clarify the relation with the probabilistic method. In this paper, the relationship between the deterministic and the probabilistic methods are investigated. To do that, a simple model that can take into account the dynamic effect of structures and a simplified method for accounting the spatial randomness are proposed and used for the studies. As the results of studies, it is found that the strength of soil properties is most importation factor for the stability of ground structures and the probability below the safety factor evaluated with the soil properties of mean -1.0 x standard deviation' by the deterministic method is of much lower. (author)

Evaluation of the streaming-matrix method for discrete-ordinates duct-streaming calculations

International Nuclear Information System (INIS)

Clark, B.A.; Urban, W.T.; Dudziak, D.J.

1983-01-01

A new deterministic streaming technique called the Streaming Matrix Hybrid Method (SMHM) is applied to two realistic duct-shielding problems. The results are compared to standard discrete-ordinates and Monte Carlo calculations. The SMHM shows promise as an alternative deterministic streaming method to standard discrete-ordinates

The Random Ray Method for neutral particle transport

Energy Technology Data Exchange (ETDEWEB)

Tramm, John R., E-mail: jtramm@mit.edu [Massachusetts Institute of Technology, Department of Nuclear Science Engineering, 77 Massachusetts Avenue, 24-107, Cambridge, MA 02139 (United States); Argonne National Laboratory, Mathematics and Computer Science Department 9700 S Cass Ave, Argonne, IL 60439 (United States); Smith, Kord S., E-mail: kord@mit.edu [Massachusetts Institute of Technology, Department of Nuclear Science Engineering, 77 Massachusetts Avenue, 24-107, Cambridge, MA 02139 (United States); Forget, Benoit, E-mail: bforget@mit.edu [Massachusetts Institute of Technology, Department of Nuclear Science Engineering, 77 Massachusetts Avenue, 24-107, Cambridge, MA 02139 (United States); Siegel, Andrew R., E-mail: siegela@mcs.anl.gov [Argonne National Laboratory, Mathematics and Computer Science Department 9700 S Cass Ave, Argonne, IL 60439 (United States)

2017-08-01

A new approach to solving partial differential equations (PDEs) based on the method of characteristics (MOC) is presented. The Random Ray Method (TRRM) uses a stochastic rather than deterministic discretization of characteristic tracks to integrate the phase space of a problem. TRRM is potentially applicable in a number of transport simulation fields where long characteristic methods are used, such as neutron transport and gamma ray transport in reactor physics as well as radiative transfer in astrophysics. In this study, TRRM is developed and then tested on a series of exemplar reactor physics benchmark problems. The results show extreme improvements in memory efficiency compared to deterministic MOC methods, while also reducing algorithmic complexity, allowing for a sparser computational grid to be used while maintaining accuracy.

The Random Ray Method for neutral particle transport

International Nuclear Information System (INIS)

Tramm, John R.; Smith, Kord S.; Forget, Benoit; Siegel, Andrew R.

2017-01-01

A new approach to solving partial differential equations (PDEs) based on the method of characteristics (MOC) is presented. The Random Ray Method (TRRM) uses a stochastic rather than deterministic discretization of characteristic tracks to integrate the phase space of a problem. TRRM is potentially applicable in a number of transport simulation fields where long characteristic methods are used, such as neutron transport and gamma ray transport in reactor physics as well as radiative transfer in astrophysics. In this study, TRRM is developed and then tested on a series of exemplar reactor physics benchmark problems. The results show extreme improvements in memory efficiency compared to deterministic MOC methods, while also reducing algorithmic complexity, allowing for a sparser computational grid to be used while maintaining accuracy.

An incident flux expansion transport theory method suitable for coupling to diffusion theory methods in hexagonal geometry

International Nuclear Information System (INIS)

Hayward, Robert M.; Rahnema, Farzad; Zhang, Dingkang

2013-01-01

Highlights: ► A new hybrid stochastic–deterministic transport theory method to couple with diffusion theory. ► The method is implemented in 2D hexagonal geometry. ► The new method produces excellent results when compared with Monte Carlo reference solutions. ► The method is fast, solving all test cases in less than 12 s. - Abstract: A new hybrid stochastic–deterministic transport theory method, which is designed to couple with diffusion theory, is presented. The new method is an extension of the incident flux response expansion method, and it combines the speed of diffusion theory with the accuracy of transport theory. With ease of use in mind, the new method is derived in such a way that it can be implemented with only minimal modifications to an existing diffusion theory method. A new angular expansion, which is necessary for the diffusion theory coupling, is developed in 2D and 3D. The method is implemented in 2D hexagonal geometry, and an HTTR benchmark problem is used to test its accuracy in a standalone configuration. It is found that the new method produces excellent results (with average relative error in partial current less than 0.033%) when compared with Monte Carlo reference solutions. Furthermore, the method is fast, solving all test cases in less than 12 s

Simulation of photonic waveguides with deterministic aperiodic nanostructures for biosensing

DEFF Research Database (Denmark)

Neustock, Lars Thorben; Paulsen, Moritz; Jahns, Sabrina

2016-01-01

Photonic waveguides with deterministic aperiodic corrugations offer rich spectral characteristics under surface-normal illumination. The finite-element method (FEM), the finite-difference time-domain (FDTD) method and a rigorous coupled wave algorithm (RCWA) are compared for computing the near...

Weighted particle method for solving the Boltzmann equation

International Nuclear Information System (INIS)

Tohyama, M.; Suraud, E.

1990-01-01

We propose a new, deterministic, method of solution of the nuclear Boltzmann equation. In this Weighted Particle Method two-body collisions are treated by a Master equation for an occupation probability of each numerical particle. We apply the method to the quadrupole motion of 12 C. A comparison with usual stochastic methods is made. Advantages and disadvantages of the Weighted Particle Method are discussed

Impulse response identification with deterministic inputs using non-parametric methods

International Nuclear Information System (INIS)

Bhargava, U.K.; Kashyap, R.L.; Goodman, D.M.

1985-01-01

This paper addresses the problem of impulse response identification using non-parametric methods. Although the techniques developed herein apply to the truncated, untruncated, and the circulant models, we focus on the truncated model which is useful in certain applications. Two methods of impulse response identification will be presented. The first is based on the minimization of the C/sub L/ Statistic, which is an estimate of the mean-square prediction error; the second is a Bayesian approach. For both of these methods, we consider the effects of using both the identity matrix and the Laplacian matrix as weights on the energy in the impulse response. In addition, we present a method for estimating the effective length of the impulse response. Estimating the length is particularly important in the truncated case. Finally, we develop a method for estimating the noise variance at the output. Often, prior information on the noise variance is not available, and a good estimate is crucial to the success of estimating the impulse response with a nonparametric technique

Deterministic and probabilistic approach to safety analysis

International Nuclear Information System (INIS)

Heuser, F.W.

1980-01-01

The examples discussed in this paper show that reliability analysis methods fairly well can be applied in order to interpret deterministic safety criteria in quantitative terms. For further improved extension of applied reliability analysis it has turned out that the influence of operational and control systems and of component protection devices should be considered with the aid of reliability analysis methods in detail. Of course, an extension of probabilistic analysis must be accompanied by further development of the methods and a broadening of the data base. (orig.)

Solution Methods for Structures with Random Properties Subject to Random Excitation

DEFF Research Database (Denmark)

Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.

This paper deals with the lower order statistical moments of the response of structures with random stiffness and random damping properties subject to random excitation. The arising stochastic differential equations (SDE) with random coefficients are solved by two methods, a second order...... the SDE with random coefficients with deterministic initial conditions to an equivalent nonlinear SDE with deterministic coefficient and random initial conditions. In both methods, the statistical moment equations are used. Hierarchy of statistical moments in the markovian approach is closed...... by the cumulant neglect closure method applied at the fourth order level....

The stochastic energy-Casimir method

Science.gov (United States)

Arnaudon, Alexis; Ganaba, Nader; Holm, Darryl D.

2018-04-01

In this paper, we extend the energy-Casimir stability method for deterministic Lie-Poisson Hamiltonian systems to provide sufficient conditions for stability in probability of stochastic dynamical systems with symmetries. We illustrate this theory with classical examples of coadjoint motion, including the rigid body, the heavy top, and the compressible Euler equation in two dimensions. The main result is that stable deterministic equilibria remain stable in probability up to a certain stopping time that depends on the amplitude of the noise for finite-dimensional systems and on the amplitude of the spatial derivative of the noise for infinite-dimensional systems. xml:lang="fr"

Solution of Dendritic Growth in Steel by the Novel Point Automata Method

International Nuclear Information System (INIS)

Lorbiecka, A Z; Šarler, B

2012-01-01

The aim of this paper is the simulation of dendritic growth in steel in two dimensions by a coupled deterministic continuum mechanics heat and species transfer model and a stochastic localized phase change kinetics model taking into account the undercooling, curvature, kinetic, and thermodynamic anisotropy. The stochastic model receives temperature and concentration information from the deterministic model and the deterministic heat, and species diffusion equations receive the solid fraction information from the stochastic model. The heat and species transfer models are solved on a regular grid by the standard explicit Finite Difference Method (FDM). The phase-change kinetics model is solved by a novel Point Automata (PA) approach. The PA method was developed [1] in order to circumvent the mesh anisotropy problem, associated with the classical Cellular Automata (CA) method. The PA approach is established on randomly distributed points and neighbourhood configuration, similar as appears in meshless methods. A comparison of the PA and CA methods is shown. It is demonstrated that the results with the new PA method are not sensitive to the crystallographic orientations of the dendrite.

Statistically qualified neuro-analytic failure detection method and system

Science.gov (United States)

Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

2002-03-02

An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

Deterministic analyses of severe accident issues

International Nuclear Information System (INIS)

Dua, S.S.; Moody, F.J.; Muralidharan, R.; Claassen, L.B.

2004-01-01

Severe accidents in light water reactors involve complex physical phenomena. In the past there has been a heavy reliance on simple assumptions regarding physical phenomena alongside of probability methods to evaluate risks associated with severe accidents. Recently GE has developed realistic methodologies that permit deterministic evaluations of severe accident progression and of some of the associated phenomena in the case of Boiling Water Reactors (BWRs). These deterministic analyses indicate that with appropriate system modifications, and operator actions, core damage can be prevented in most cases. Furthermore, in cases where core-melt is postulated, containment failure can either be prevented or significantly delayed to allow sufficient time for recovery actions to mitigate severe accidents

Non-Deterministic, Non-Traditional Methods (NDNTM)

Science.gov (United States)

Cruse, Thomas A.; Chamis, Christos C. (Technical Monitor)

2001-01-01

The review effort identified research opportunities related to the use of nondeterministic, nontraditional methods to support aerospace design. The scope of the study was restricted to structural design rather than other areas such as control system design. Thus, the observations and conclusions are limited by that scope. The review identified a number of key results. The results include the potential for NASA/AF collaboration in the area of a design environment for advanced space access vehicles. The following key points set the context and delineate the key results. The Principal Investigator's (PI's) context for this study derived from participation as a Panel Member in the Air Force Scientific Advisory Board (AF/SAB) Summer Study Panel on 'Whither Hypersonics?' A key message from the Summer Study effort was a perceived need for a national program for a space access vehicle whose operating characteristics of cost, availability, deployability, and reliability most closely match the NASA 3rd Generation Reusable Launch Vehicle (RLV). The Panel urged the AF to make a significant joint commitment to such a program just as soon as the AF defined specific requirements for space access consistent with the AF Aerospace Vision 2020. The review brought home a concurrent need for a national vehicle design environment. Engineering design system technology is at a time point from which a revolution as significant as that brought about by the finite element method is possible, this one focusing on information integration on a scale that far surpasses current design environments. The study therefore fully supported the concept, if not some of the details of the Intelligent Synthesis Environment (ISE). It became abundantly clear during this study that the government (AF, NASA) and industry are not moving in the same direction in this regard, in fact each is moving in its own direction. NASA/ISE is not yet in an effective leadership position in this regard. However, NASA does

A method for deterministic statistical downscaling of daily precipitation at a monsoonal site in Eastern China

Science.gov (United States)

Liu, Yonghe; Feng, Jinming; Liu, Xiu; Zhao, Yadi

2017-12-01

Statistical downscaling (SD) is a method that acquires the local information required for hydrological impact assessment from large-scale atmospheric variables. Very few statistical and deterministic downscaling models for daily precipitation have been conducted for local sites influenced by the East Asian monsoon. In this study, SD models were constructed by selecting the best predictors and using generalized linear models (GLMs) for Feixian, a site in the Yishu River Basin and Shandong Province. By calculating and mapping Spearman rank correlation coefficients between the gridded standardized values of five large-scale variables and daily observed precipitation, different cyclonic circulation patterns were found for monsoonal precipitation in summer (June-September) and winter (November-December and January-March); the values of the gridded boxes with the highest absolute correlations for observed precipitation were selected as predictors. Data for predictors and predictands covered the period 1979-2015, and different calibration and validation periods were divided when fitting and validating the models. Meanwhile, the bootstrap method was also used to fit the GLM. All the above thorough validations indicated that the models were robust and not sensitive to different samples or different periods. Pearson's correlations between downscaled and observed precipitation (logarithmically transformed) on a daily scale reached 0.54-0.57 in summer and 0.56-0.61 in winter, and the Nash-Sutcliffe efficiency between downscaled and observed precipitation reached 0.1 in summer and 0.41 in winter. The downscaled precipitation partially reflected exact variations in winter and main trends in summer for total interannual precipitation. For the number of wet days, both winter and summer models were able to reflect interannual variations. Other comparisons were also made in this study. These results demonstrated that when downscaling, it is appropriate to combine a correlation

Assessment of seismic margin calculation methods

International Nuclear Information System (INIS)

Kennedy, R.P.; Murray, R.C.; Ravindra, M.K.; Reed, J.W.; Stevenson, J.D.

1989-03-01

Seismic margin review of nuclear power plants requires that the High Confidence of Low Probability of Failure (HCLPF) capacity be calculated for certain components. The candidate methods for calculating the HCLPF capacity as recommended by the Expert Panel on Quantification of Seismic Margins are the Conservative Deterministic Failure Margin (CDFM) method and the Fragility Analysis (FA) method. The present study evaluated these two methods using some representative components in order to provide further guidance in conducting seismic margin reviews. It is concluded that either of the two methods could be used for calculating HCLPF capacities. 21 refs., 9 figs., 6 tabs

Landslide prediction using combined deterministic and probabilistic methods in hilly area of Mt. Medvednica in Zagreb City, Croatia

Science.gov (United States)

Wang, Chunxiang; Watanabe, Naoki; Marui, Hideaki

2013-04-01

The hilly slopes of Mt. Medvednica are stretched in the northwestern part of Zagreb City, Croatia, and extend to approximately 180km2. In this area, landslides, e.g. Kostanjek landslide and Črešnjevec landslide, have brought damage to many houses, roads, farmlands, grassland and etc. Therefore, it is necessary to predict the potential landslides and to enhance landslide inventory for hazard mitigation and security management of local society in this area. We combined deterministic method and probabilistic method to assess potential landslides including their locations, size and sliding surfaces. Firstly, this study area is divided into several slope units that have similar topographic and geological characteristics using the hydrology analysis tool in ArcGIS. Then, a GIS-based modified three-dimensional Hovland's method for slope stability analysis system is developed to identify the sliding surface and corresponding three-dimensional safety factor for each slope unit. Each sliding surface is assumed to be the lower part of each ellipsoid. The direction of inclination of the ellipsoid is considered to be the same as the main dip direction of the slope unit. The center point of the ellipsoid is randomly set to the center point of a grid cell in the slope unit. The minimum three-dimensional safety factor and corresponding critical sliding surface are also obtained for each slope unit. Thirdly, since a single value of safety factor is insufficient to evaluate the slope stability of a slope unit, the ratio of the number of calculation cases in which the three-dimensional safety factor values less than 1.0 to the total number of trial calculation is defined as the failure probability of the slope unit. If the failure probability is more than 80%, the slope unit is distinguished as 'unstable' from other slope units and the landslide hazard can be mapped for the whole study area.

A Numerical Simulation for a Deterministic Compartmental ...

African Journals Online (AJOL)

In this work, an earlier deterministic mathematical model of HIV/AIDS is revisited and numerical solutions obtained using Eulers numerical method. Using hypothetical values for the parameters, a program was written in VISUAL BASIC programming language to generate series for the system of difference equations from the ...

Chaotic transitions in deterministic and stochastic dynamical systems applications of Melnikov processes in engineering, physics, and neuroscience

CERN Document Server

Simiu, Emil

2002-01-01

The classical Melnikov method provides information on the behavior of deterministic planar systems that may exhibit transitions, i.e. escapes from and captures into preferred regions of phase space. This book develops a unified treatment of deterministic and stochastic systems that extends the applicability of the Melnikov method to physically realizable stochastic planar systems with additive, state-dependent, white, colored, or dichotomous noise. The extended Melnikov method yields the novel result that motions with transitions are chaotic regardless of whether the excitation is deterministic or stochastic. It explains the role in the occurrence of transitions of the characteristics of the system and its deterministic or stochastic excitation, and is a powerful modeling and identification tool. The book is designed primarily for readers interested in applications. The level of preparation required corresponds to the equivalent of a first-year graduate course in applied mathematics. No previous exposure to d...

Probabilistic Analysis Methods for Hybrid Ventilation

DEFF Research Database (Denmark)

Brohus, Henrik; Frier, Christian; Heiselberg, Per

This paper discusses a general approach for the application of probabilistic analysis methods in the design of ventilation systems. The aims and scope of probabilistic versus deterministic methods are addressed with special emphasis on hybrid ventilation systems. A preliminary application...... of stochastic differential equations is presented comprising a general heat balance for an arbitrary number of loads and zones in a building to determine the thermal behaviour under random conditions....

Comparison of probabilistic and deterministic fiber tracking of cranial nerves.

Science.gov (United States)

Zolal, Amir; Sobottka, Stephan B; Podlesek, Dino; Linn, Jennifer; Rieger, Bernhard; Juratli, Tareq A; Schackert, Gabriele; Kitzler, Hagen H

2017-09-01

OBJECTIVE The depiction of cranial nerves (CNs) using diffusion tensor imaging (DTI) is of great interest in skull base tumor surgery and DTI used with deterministic tracking methods has been reported previously. However, there are still no good methods usable for the elimination of noise from the resulting depictions. The authors have hypothesized that probabilistic tracking could lead to more accurate results, because it more efficiently extracts information from the underlying data. Moreover, the authors have adapted a previously described technique for noise elimination using gradual threshold increases to probabilistic tracking. To evaluate the utility of this new approach, a comparison is provided with this work between the gradual threshold increase method in probabilistic and deterministic tracking of CNs. METHODS Both tracking methods were used to depict CNs II, III, V, and the VII+VIII bundle. Depiction of 240 CNs was attempted with each of the above methods in 30 healthy subjects, which were obtained from 2 public databases: the Kirby repository (KR) and Human Connectome Project (HCP). Elimination of erroneous fibers was attempted by gradually increasing the respective thresholds (fractional anisotropy [FA] and probabilistic index of connectivity [PICo]). The results were compared with predefined ground truth images based on corresponding anatomical scans. Two label overlap measures (false-positive error and Dice similarity coefficient) were used to evaluate the success of both methods in depicting the CN. Moreover, the differences between these parameters obtained from the KR and HCP (with higher angular resolution) databases were evaluated. Additionally, visualization of 10 CNs in 5 clinical cases was attempted with both methods and evaluated by comparing the depictions with intraoperative findings. RESULTS Maximum Dice similarity coefficients were significantly higher with probabilistic tracking (p cranial nerves. Probabilistic tracking with a gradual

Contribution to the solution of the multigroup Boltzmann equation by the determinist methods and the Monte Carlo method; Contribution a la resolution de l`equation de Bolztmann en multigroupe par les methodes deterministes et Monte-Carlo

Energy Technology Data Exchange (ETDEWEB)

Li, M

1998-08-01

In this thesis, two methods for solving the multigroup Boltzmann equation have been studied: the interface-current method and the Monte Carlo method. A new version of interface-current (IC) method has been develop in the TDT code at SERMA, where the currents of interface are represented by piecewise constant functions in the solid angle space. The convergence of this method to the collision probability (CP) method has been tested. Since the tracking technique is used for both the IC and CP methods, it is necessary to normalize he collision probabilities obtained by this technique. Several methods for this object have been studied and implemented in our code, we have compared their performances and chosen the best one as the standard choice. The transfer matrix treatment has been a long-standing difficulty for the multigroup Monte Carlo method: when the cross-sections are converted into multigroup form, important negative parts will appear in the angular transfer laws represented by low-order Legendre polynomials. Several methods based on the preservation of the first moments, such as the discrete angles methods and the equally-probable step function method, have been studied and implemented in the TRIMARAN-II code. Since none of these codes has been satisfactory, a new method, the non equally-probably step function method, has been proposed and realized in our code. The comparisons for these methods have been done in several aspects: the preservation of the moments required, the calculation of a criticality problem and the calculation of a neutron-transfer in water problem. The results have showed that the new method is the best one in all these comparisons, and we have proposed that it should be a standard choice for the multigroup transfer matrix. (author) 76 refs.

Precision production: enabling deterministic throughput for precision aspheres with MRF

Science.gov (United States)

Maloney, Chris; Entezarian, Navid; Dumas, Paul

2017-10-01

Aspherical lenses offer advantages over spherical optics by improving image quality or reducing the number of elements necessary in an optical system. Aspheres are no longer being used exclusively by high-end optical systems but are now replacing spherical optics in many applications. The need for a method of production-manufacturing of precision aspheres has emerged and is part of the reason that the optics industry is shifting away from artisan-based techniques towards more deterministic methods. Not only does Magnetorheological Finishing (MRF) empower deterministic figure correction for the most demanding aspheres but it also enables deterministic and efficient throughput for series production of aspheres. The Q-flex MRF platform is designed to support batch production in a simple and user friendly manner. Thorlabs routinely utilizes the advancements of this platform and has provided results from using MRF to finish a batch of aspheres as a case study. We have developed an analysis notebook to evaluate necessary specifications for implementing quality control metrics. MRF brings confidence to optical manufacturing by ensuring high throughput for batch processing of aspheres.

Deterministic bound for avionics switched networks according to networking features using network calculus

Directory of Open Access Journals (Sweden)

Feng HE

2017-12-01

Full Text Available The state of the art avionics system adopts switched networks for airborne communications. A major concern in the design of the networks is the end-to-end guarantee ability. Analytic methods have been developed to compute the worst-case delays according to the detailed configurations of flows and networks within avionics context, such as network calculus and trajectory approach. It still lacks a relevant method to make a rapid performance estimation according to some typically switched networking features, such as networking scale, bandwidth utilization and average flow rate. The goal of this paper is to establish a deterministic upper bound analysis method by using these networking features instead of the complete network configurations. Two deterministic upper bounds are proposed from network calculus perspective: one is for a basic estimation, and another just shows the benefits from grouping strategy. Besides, a mathematic expression for grouping ability is established based on the concept of network connecting degree, which illustrates the possibly minimal grouping benefit. For a fully connected network with 4 switches and 12 end systems, the grouping ability coming from grouping strategy is 15–20%, which just coincides with the statistical data (18–22% from the actual grouping advantage. Compared with the complete network calculus analysis method for individual flows, the effectiveness of the two deterministic upper bounds is no less than 38% even with remarkably varied packet lengths. Finally, the paper illustrates the design process for an industrial Avionics Full DupleX switched Ethernet (AFDX networking case according to the two deterministic upper bounds and shows that a better control for network connecting, when designing a switched network, can improve the worst-case delays dramatically. Keywords: Deterministic bound, Grouping ability, Network calculus, Networking features, Switched networks

Using MCBEND for neutron or gamma-ray deterministic calculations

Science.gov (United States)

Geoff, Dobson; Adam, Bird; Brendan, Tollit; Paul, Smith

2017-09-01

MCBEND 11 is the latest version of the general radiation transport Monte Carlo code from AMEC Foster Wheeler's ANSWERS® Software Service. MCBEND is well established in the UK shielding community for radiation shielding and dosimetry assessments. MCBEND supports a number of acceleration techniques, for example the use of an importance map in conjunction with Splitting/Russian Roulette. MCBEND has a well established automated tool to generate this importance map, commonly referred to as the MAGIC module using a diffusion adjoint solution. This method is fully integrated with the MCBEND geometry and material specification, and can easily be run as part of a normal MCBEND calculation. An often overlooked feature of MCBEND is the ability to use this method for forward scoping calculations, which can be run as a very quick deterministic method. Additionally, the development of the Visual Workshop environment for results display provides new capabilities for the use of the forward calculation as a productivity tool. In this paper, we illustrate the use of the combination of the old and new in order to provide an enhanced analysis capability. We also explore the use of more advanced deterministic methods for scoping calculations used in conjunction with MCBEND, with a view to providing a suite of methods to accompany the main Monte Carlo solver.

Probabilistic structural analysis methods for space transportation propulsion systems

Science.gov (United States)

Chamis, C. C.; Moore, N.; Anis, C.; Newell, J.; Nagpal, V.; Singhal, S.

1991-01-01

Information on probabilistic structural analysis methods for space propulsion systems is given in viewgraph form. Information is given on deterministic certification methods, probability of failure, component response analysis, stress responses for 2nd stage turbine blades, Space Shuttle Main Engine (SSME) structural durability, and program plans. .

Present status of reactor physics in the United States and Japan-II. 1. Deterministic Transport Methods for Reactor Analysis

International Nuclear Information System (INIS)

Adams, Marvin L.

2001-01-01

We discuss deterministic transport methods used today in neutronic analysis of nuclear reactors. This discussion is not exhaustive; our goal is to provide an overview of the methods that are most widely used for analyzing light water reactors (LWRs) and that (in our opinion) hold the most promise for the future. The current practice of LWR analysis involves the following steps: 1. Evaluate cross sections from measurements and models. 2. Obtain weighted-average cross sections over dozens to hundreds of energy intervals; the result is a 'fine-group' cross-section set. 3. [Optional] Modify the fine-group set: Further collapse it using information specific to your class of reactors and/or alter parameters so that computations better agree with experiments. The result is a 'many-group library'. 4. Perform pin cell transport calculations (usually one-dimensional cylindrical); use the results to collapse the many-group library to a medium-group set, and/or spatially average the cross sections over the pin cells. 5. Perform assembly-level transport calculations with the medium-group set. It is becoming common practice to use essentially exact geometry (no pin cell homogenization). It may soon become common to skip step 4 and use the many-group library. The output is a library of few-group cross sections, spatially averaged over the assembly, parameterized to cover the full range of operating conditions. 6. Perform full-core calculations with few-group diffusion theory that contains significant homogenizations and limited transport corrections. We discuss steps 4, 5, and 6 and focus mainly on step 5. One cannot review a large topic in a short summary without simplifying reality, omitting important details, and neglecting some methods that deserve attention; for this we apologize in advance. (author)

Corticospinal MRI tractography in space-occupying brain lesions by diffusion tensor and kurtosis imaging methods

Energy Technology Data Exchange (ETDEWEB)

Leote, Joao [epartment of Neurosurgery, Hospital Garcia de Orta, Almada (Portugal); Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisboa (Portugal); Nunes, Rita; Cerqueira, Luis; Ferreira, Hugo Alexandre [Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisboa (Portugal)

2015-05-18

Recently, DKI-based tractography has been developed, showing improved crossing-fiber resolution in comparison to deterministic DTI-based tractography in healthy subjects. In this work, DTI and DKI-based tractography methods were compared regarding the assessment of the corticospinal tract in patients presenting space-occupying brain lesions near cortical motor areas. Nine patients (4 males) aged 23 to 62 years old, with space-occupying brain lesions (e.g. tumors) were studied for pre-surgical planning using a 1.5T MRI scanner and a 12-channel head coil. In 5 patients diffusion data was acquired along 64 directions and in 4 patients along 32 directions both with b-values 0, 1000 and 2000 s/mm2. Corticospinal tracts were estimated using deterministic DTI and DKI methods and also using probabilistic DTI. The superior cerebellar peduncles and the motor cortical areas, ipsilateral and contralateral to the lesions, were used as seed regions-of-interest for fiber tracking. Tracts courses and volumes were documented and compared between methods. Results showed that it was possible to estimate fiber tracts using deterministic DTI and DKI methods in 8/9 patients, and using the probabilistic DTI method in all patients. Overall, it was observed that DKI-based tractography showed more voluminous fiber tracts than when using deterministic DTI. The DKI method also showed curvilinear fibers mainly above lesions margins, which were not visible with deterministic DTI in 5 patients. Similar tracts were observed when using probabilistic DTI in 3 of those patients. Results suggest that the DKI method contribute with additional information about the corticospinal tract course in comparison with the DTI method, especially with subcortical lesions and near lesions’ margins. Therefore, this study suggests that DKI-based tractography could be useful in MRI and hybrid PET-MRI pre-surgical planning protocols for improved corticospinal tract evaluation.

Deterministic Graphical Games Revisited

DEFF Research Database (Denmark)

Andersson, Klas Olof Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro

2012-01-01

Starting from Zermelo’s classical formal treatment of chess, we trace through history the analysis of two-player win/lose/draw games with perfect information and potentially infinite play. Such chess-like games have appeared in many different research communities, and methods for solving them......, such as retrograde analysis, have been rediscovered independently. We then revisit Washburn’s deterministic graphical games (DGGs), a natural generalization of chess-like games to arbitrary zero-sum payoffs. We study the complexity of solving DGGs and obtain an almost-linear time comparison-based algorithm...

Deterministic prediction of surface wind speed variations

Directory of Open Access Journals (Sweden)

G. V. Drisya

2014-11-01

Full Text Available Accurate prediction of wind speed is an important aspect of various tasks related to wind energy management such as wind turbine predictive control and wind power scheduling. The most typical characteristic of wind speed data is its persistent temporal variations. Most of the techniques reported in the literature for prediction of wind speed and power are based on statistical methods or probabilistic distribution of wind speed data. In this paper we demonstrate that deterministic forecasting methods can make accurate short-term predictions of wind speed using past data, at locations where the wind dynamics exhibit chaotic behaviour. The predictions are remarkably accurate up to 1 h with a normalised RMSE (root mean square error of less than 0.02 and reasonably accurate up to 3 h with an error of less than 0.06. Repeated application of these methods at 234 different geographical locations for predicting wind speeds at 30-day intervals for 3 years reveals that the accuracy of prediction is more or less the same across all locations and time periods. Comparison of the results with f-ARIMA model predictions shows that the deterministic models with suitable parameters are capable of returning improved prediction accuracy and capturing the dynamical variations of the actual time series more faithfully. These methods are simple and computationally efficient and require only records of past data for making short-term wind speed forecasts within practically tolerable margin of errors.

Inherent Conservatism in Deterministic Quasi-Static Structural Analysis

Science.gov (United States)

Verderaime, V.

1997-01-01

The cause of the long-suspected excessive conservatism in the prevailing structural deterministic safety factor has been identified as an inherent violation of the error propagation laws when reducing statistical data to deterministic values and then combining them algebraically through successive structural computational processes. These errors are restricted to the applied stress computations, and because mean and variations of the tolerance limit format are added, the errors are positive, serially cumulative, and excessively conservative. Reliability methods circumvent these errors and provide more efficient and uniform safe structures. The document is a tutorial on the deficiencies and nature of the current safety factor and of its improvement and transition to absolute reliability.

A Deterministic Annealing Approach to Clustering AIRS Data

Science.gov (United States)

Guillaume, Alexandre; Braverman, Amy; Ruzmaikin, Alexander

2012-01-01

We will examine the validity of means and standard deviations as a basis for climate data products. We will explore the conditions under which these two simple statistics are inadequate summaries of the underlying empirical probability distributions by contrasting them with a nonparametric, method called Deterministic Annealing technique

Dual ant colony operational modal analysis parameter estimation method

Science.gov (United States)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

STOCHASTIC GRADIENT METHODS FOR UNCONSTRAINED OPTIMIZATION

Directory of Open Access Journals (Sweden)

Nataša Krejić

2014-12-01

Full Text Available This papers presents an overview of gradient based methods for minimization of noisy functions. It is assumed that the objective functions is either given with error terms of stochastic nature or given as the mathematical expectation. Such problems arise in the context of simulation based optimization. The focus of this presentation is on the gradient based Stochastic Approximation and Sample Average Approximation methods. The concept of stochastic gradient approximation of the true gradient can be successfully extended to deterministic problems. Methods of this kind are presented for the data fitting and machine learning problems.

Using MCBEND for neutron or gamma-ray deterministic calculations

Directory of Open Access Journals (Sweden)

Geoff Dobson

2017-01-01

Full Text Available MCBEND 11 is the latest version of the general radiation transport Monte Carlo code from AMEC Foster Wheeler’s ANSWERS® Software Service. MCBEND is well established in the UK shielding community for radiation shielding and dosimetry assessments. MCBEND supports a number of acceleration techniques, for example the use of an importance map in conjunction with Splitting/Russian Roulette. MCBEND has a well established automated tool to generate this importance map, commonly referred to as the MAGIC module using a diffusion adjoint solution. This method is fully integrated with the MCBEND geometry and material specification, and can easily be run as part of a normal MCBEND calculation. An often overlooked feature of MCBEND is the ability to use this method for forward scoping calculations, which can be run as a very quick deterministic method. Additionally, the development of the Visual Workshop environment for results display provides new capabilities for the use of the forward calculation as a productivity tool. In this paper, we illustrate the use of the combination of the old and new in order to provide an enhanced analysis capability. We also explore the use of more advanced deterministic methods for scoping calculations used in conjunction with MCBEND, with a view to providing a suite of methods to accompany the main Monte Carlo solver.

Cheap arbitrary high order methods for single integrand SDEs

DEFF Research Database (Denmark)

Debrabant, Kristian; Kværnø, Anne

2017-01-01

For a particular class of Stratonovich SDE problems, here denoted as single integrand SDEs, we prove that by applying a deterministic Runge-Kutta method of order $p_d$ we obtain methods converging in the mean-square and weak sense with order $\\lfloor p_d/2\\rfloor$. The reason is that the B-series...

Methods for designing building envelope components prepared for repair and maintenance

DEFF Research Database (Denmark)

Rudbeck, Claus Christian

2000-01-01

the deterministic and probabilistic approach. Based on an investigation of the data-requirement, user-friendliness and supposed accuracy (the accuracy of the different methods has not been evaluated due to the absence of field data) the method which combines the deterministic factor method with statistical...... to be prepared for repair and maintenance. Both of these components are insulation systems for flat roofs and low slope roofs; components where repair or replacement is very expensive if the roofing material fails in its function. The principle of both roofing insulation systems is that the insulation can...... of issues which are specified below:Further development of methods for designing building envelope components prepared for repair and maintenance, and ways of tracking and predicting performance through time once the components have been designed, implemented in a building design and built...

Comparison of construction algorithms for minimal, acyclic, deterministic, finite-state automata from sets of strings

NARCIS (Netherlands)

Daciuk, J; Champarnaud, JM; Maurel, D

2003-01-01

This paper compares various methods for constructing minimal, deterministic, acyclic, finite-state automata (recognizers) from sets of words. Incremental, semi-incremental, and non-incremental methods have been implemented and evaluated.

Fluid-Induced Vibration Analysis for Reactor Internals Using Computational FSI Method

Energy Technology Data Exchange (ETDEWEB)

Moon, Jong Sung; Yi, Kun Woo; Sung, Ki Kwang; Im, In Young; Choi, Taek Sang [KEPCO E and C, Daejeon (Korea, Republic of)

2013-10-15

This paper introduces a fluid-induced vibration analysis method which calculates the response of the RVI to both deterministic and random loads at once and utilizes more realistic pressure distribution using the computational Fluid Structure Interaction (FSI) method. As addressed above, the FIV analysis for the RVI was carried out using the computational FSI method. This method calculates the response to deterministic and random turbulence loads at once. This method is also a simple and integrative method to get structural dynamic responses of reactor internals to various flow-induced loads. Because the analysis of this paper omitted the bypass flow region and Inner Barrel Assembly (IBA) due to the limitation of computer resources, it is necessary to find an effective way to consider all regions in the RV for the FIV analysis in the future. Reactor coolant flow makes Reactor Vessel Internals (RVI) vibrate and may affect the structural integrity of them. U. S. NRC Regulatory Guide 1.20 requires the Comprehensive Vibration Assessment Program (CVAP) to verify the structural integrity of the RVI for Fluid-Induced Vibration (FIV). The hydraulic forces on the RVI of OPR1000 and APR1400 were computed from the hydraulic formulas and the CVAP measurements in Palo Verde Unit 1 and Yonggwang Unit 4 for the structural vibration analyses. In this method, the hydraulic forces were divided into deterministic and random turbulence loads and were used for the excitation forces of the separate structural analyses. These forces are applied to the finite element model and the responses to them were combined into the resultant stresses.

A method for statistical steady state thermal analysis of reactor cores

International Nuclear Information System (INIS)

Whetton, P.A.

1980-01-01

This paper presents a method for performing a statistical steady state thermal analysis of a reactor core. The technique is only outlined here since detailed thermal equations are dependent on the core geometry. The method has been applied to a pressurised water reactor core and the results are presented for illustration purposes. Random hypothetical cores are generated using the Monte-Carlo method. The technique shows that by splitting the parameters into two types, denoted core-wise and in-core, the Monte Carlo method may be used inexpensively. The idea of using extremal statistics to characterise the low probability events (i.e. the tails of a distribution) is introduced together with a method of forming the final probability distribution. After establishing an acceptable probability of exceeding a thermal design criterion, the final probability distribution may be used to determine the corresponding thermal response value. If statistical and deterministic (i.e. conservative) thermal response values are compared, information on the degree of pessimism in the deterministic method of analysis may be inferred and the restrictive performance limitations imposed by this method relieved. (orig.)

Efficient improvement of nuclear power plant safety by reorganization of risk-informed safety importance evaluation methods for piping welded portions

Energy Technology Data Exchange (ETDEWEB)

Irie, Takashi; Hanafusa, Hidemitsu; Suyama, Takeshi [Institute of Nuclear Safety System, Inc., Mihama, Fukui (Japan); Morota, Hidetsugu; Kojima, Sigeo; Mizuno, Yoshinobu [Computer Software Development Co., Ltd., Tokyo (Japan)

2002-09-01

In this work, risk information was used to evaluate the safety importance of piping welded portions which were important for plant operation and maintenance of nuclear power plants. There are two types of risk-informed safety importance evaluation methods, namely the ASME method and the EPRI method. Since both methods have advantages and disadvantages, elements of each method were combined and reorganized. Considerations included whether the degradation mechanisms would be objectively evaluated and whether plant safety would be efficiently improved. The most objective and efficient method was as follows. Piping failure potential is quantitatively and objectively evaluated for failure with probabilistic fracture mechanics (PFM) and for other degradation mechanisms with empirical failure rates, and conditional core damage probability (CCDP) is calculated with PSA. This method reduces the inspected segment numbers to 1/4 of the deterministic method and increases the ratio of risk, which is covered by the inspected segments, to total risk from 80% of the deterministic method to 95%. Piping inspection numbers decreased for safety injection systems that were required the inspections by the deterministic method. Piping inspections were required for part of main feed water and main steam systems that were not required the inspections by the deterministic method. (author)

Progress in nuclear well logging modeling using deterministic transport codes

International Nuclear Information System (INIS)

Kodeli, I.; Aldama, D.L.; Maucec, M.; Trkov, A.

2002-01-01

Further studies in continuation of the work presented in 2001 in Portoroz were performed in order to study and improve the performances, precission and domain of application of the deterministic transport codes with respect to the oil well logging analysis. These codes are in particular expected to complement the Monte Carlo solutions, since they can provide a detailed particle flux distribution in the whole geometry in a very reasonable CPU time. Real-time calculation can be envisaged. The performances of deterministic transport methods were compared to those of the Monte Carlo method. IRTMBA generic benchmark was analysed using the codes MCNP-4C and DORT/TORT. Centric as well as excentric casings were considered using 14 MeV point neutron source and NaI scintillation detectors. Neutron and gamma spectra were compared at two detector positions.(author)

Deterministic automata for extended regular expressions

Directory of Open Access Journals (Sweden)

Syzdykov Mirzakhmet

2017-12-01

Full Text Available In this work we present the algorithms to produce deterministic finite automaton (DFA for extended operators in regular expressions like intersection, subtraction and complement. The method like “overriding” of the source NFA(NFA not defined with subset construction rules is used. The past work described only the algorithm for AND-operator (or intersection of regular languages; in this paper the construction for the MINUS-operator (and complement is shown.

Deterministic ion beam material adding technology for high-precision optical surfaces.

Science.gov (United States)

Liao, Wenlin; Dai, Yifan; Xie, Xuhui; Zhou, Lin

2013-02-20

Although ion beam figuring (IBF) provides a highly deterministic method for the precision figuring of optical components, several problems still need to be addressed, such as the limited correcting capability for mid-to-high spatial frequency surface errors and low machining efficiency for pit defects on surfaces. We propose a figuring method named deterministic ion beam material adding (IBA) technology to solve those problems in IBF. The current deterministic optical figuring mechanism, which is dedicated to removing local protuberances on optical surfaces, is enriched and developed by the IBA technology. Compared with IBF, this method can realize the uniform convergence of surface errors, where the particle transferring effect generated in the IBA process can effectively correct the mid-to-high spatial frequency errors. In addition, IBA can rapidly correct the pit defects on the surface and greatly improve the machining efficiency of the figuring process. The verification experiments are accomplished on our experimental installation to validate the feasibility of the IBA method. First, a fused silica sample with a rectangular pit defect is figured by using IBA. Through two iterations within only 47.5 min, this highly steep pit is effectively corrected, and the surface error is improved from the original 24.69 nm root mean square (RMS) to the final 3.68 nm RMS. Then another experiment is carried out to demonstrate the correcting capability of IBA for mid-to-high spatial frequency surface errors, and the final results indicate that the surface accuracy and surface quality can be simultaneously improved.

Bayesian analysis of deterministic and stochastic prisoner's dilemma games

Directory of Open Access Journals (Sweden)

Howard Kunreuther

2009-08-01

Full Text Available This paper compares the behavior of individuals playing a classic two-person deterministic prisoner's dilemma (PD game with choice data obtained from repeated interdependent security prisoner's dilemma games with varying probabilities of loss and the ability to learn (or not learn about the actions of one's counterpart, an area of recent interest in experimental economics. This novel data set, from a series of controlled laboratory experiments, is analyzed using Bayesian hierarchical methods, the first application of such methods in this research domain. We find that individuals are much more likely to be cooperative when payoffs are deterministic than when the outcomes are probabilistic. A key factor explaining this difference is that subjects in a stochastic PD game respond not just to what their counterparts did but also to whether or not they suffered a loss. These findings are interpreted in the context of behavioral theories of commitment, altruism and reciprocity. The work provides a linkage between Bayesian statistics, experimental economics, and consumer psychology.

Deterministic transfer of two-dimensional materials by all-dry viscoelastic stamping

International Nuclear Information System (INIS)

Castellanos-Gomez, Andres; Buscema, Michele; Molenaar, Rianda; Singh, Vibhor; Janssen, Laurens; Van der Zant, Herre S J; Steele, Gary A

2014-01-01

The deterministic transfer of two-dimensional crystals constitutes a crucial step towards the fabrication of heterostructures based on the artificial stacking of two-dimensional materials. Moreover, controlling the positioning of two-dimensional crystals facilitates their integration in complex devices, which enables the exploration of novel applications and the discovery of new phenomena in these materials. To date, deterministic transfer methods rely on the use of sacrificial polymer layers and wet chemistry to some extent. Here, we develop an all-dry transfer method that relies on viscoelastic stamps and does not employ any wet chemistry step. This is found to be very advantageous to freely suspend these materials as there are no capillary forces involved in the process. Moreover, the whole fabrication process is quick, efficient, clean and it can be performed with high yield. (letter)

Sequential optimization and reliability assessment method for metal forming processes

International Nuclear Information System (INIS)

Sahai, Atul; Schramm, Uwe; Buranathiti, Thaweepat; Chen Wei; Cao Jian; Xia, Cedric Z.

2004-01-01

Uncertainty is inevitable in any design process. The uncertainty could be due to the variations in geometry of the part, material properties or due to the lack of knowledge about the phenomena being modeled itself. Deterministic design optimization does not take uncertainty into account and worst case scenario assumptions lead to vastly over conservative design. Probabilistic design, such as reliability-based design and robust design, offers tools for making robust and reliable decisions under the presence of uncertainty in the design process. Probabilistic design optimization often involves double-loop procedure for optimization and iterative probabilistic assessment. This results in high computational demand. The high computational demand can be reduced by replacing computationally intensive simulation models with less costly surrogate models and by employing Sequential Optimization and reliability assessment (SORA) method. The SORA method uses a single-loop strategy with a series of cycles of deterministic optimization and reliability assessment. The deterministic optimization and reliability assessment is decoupled in each cycle. This leads to quick improvement of design from one cycle to other and increase in computational efficiency. This paper demonstrates the effectiveness of Sequential Optimization and Reliability Assessment (SORA) method when applied to designing a sheet metal flanging process. Surrogate models are used as less costly approximations to the computationally expensive Finite Element simulations

Condensation and homogenization of cross sections for the deterministic transport codes with Monte Carlo method: Application to the GEN IV fast neutron reactors

International Nuclear Information System (INIS)

Cai, Li

2014-01-01

In the framework of the Generation IV reactors neutronic research, new core calculation tools are implemented in the code system APOLLO3 for the deterministic part. These calculation methods are based on the discretization concept of nuclear energy data (named multi-group and are generally produced by deterministic codes) and should be validated and qualified with respect to some Monte-Carlo reference calculations. This thesis aims to develop an alternative technique of producing multi-group nuclear properties by a Monte-Carlo code (TRIPOLI-4). At first, after having tested the existing homogenization and condensation functionalities with better precision obtained nowadays, some inconsistencies are revealed. Several new multi-group parameters estimators are developed and validated for TRIPOLI-4 code with the aid of itself, since it has the possibility to use the multi-group constants in a core calculation. Secondly, the scattering anisotropy effect which is necessary for handling neutron leakage case is studied. A correction technique concerning the diagonal line of the first order moment of the scattering matrix is proposed. This is named the IGSC technique and is based on the usage of an approximate current which is introduced by Todorova. An improvement of this IGSC technique is then presented for the geometries which hold an important heterogeneity property. This improvement uses a more accurate current quantity which is the projection on the abscissa X. The later current can represent the real situation better but is limited to 1D geometries. Finally, a B1 leakage model is implemented in the TRIPOLI-4 code for generating multi-group cross sections with a fundamental mode based critical spectrum. This leakage model is analyzed and validated rigorously by the comparison with other codes: Serpent and ECCO, as well as an analytical case.The whole development work introduced in TRIPOLI-4 code allows producing multi-group constants which can then be used in the core

Methods for design flood estimation in South Africa

African Journals Online (AJOL)

2012-07-04

Jul 4, 2012 ... 1970s and are in need of updating with more than 40 years of additional data ... This paper reviews methods used for design flood estimation in South Africa and .... transposition of past experience, or a deterministic approach,.

The State of Deterministic Thinking among Mothers of Autistic Children

Directory of Open Access Journals (Sweden)

Mehrnoush Esbati

2011-10-01

Full Text Available Objectives: The purpose of the present study was to investigate the effectiveness of cognitive-behavior education on decreasing deterministic thinking in mothers of children with autism spectrum disorders. Methods: Participants were 24 mothers of autistic children who were referred to counseling centers of Tehran and their children’s disorder had been diagnosed at least by a psychiatrist and a counselor. They were randomly selected and assigned into control and experimental groups. Measurement tool was Deterministic Thinking Questionnaire and both groups answered it before and after education and the answers were analyzed by analysis of covariance. Results: The results indicated that cognitive-behavior education decreased deterministic thinking among mothers of autistic children, it decreased four sub scale of deterministic thinking: interaction with others, absolute thinking, prediction of future, and negative events (P<0.05 as well. Discussions: By learning cognitive and behavioral techniques, parents of children with autism can reach higher level of psychological well-being and it is likely that these cognitive-behavioral skills would have a positive impact on general life satisfaction of mothers of children with autism.

A contribution Monte Carlo method

International Nuclear Information System (INIS)

Aboughantous, C.H.

1994-01-01

A Contribution Monte Carlo method is developed and successfully applied to a sample deep-penetration shielding problem. The random walk is simulated in most of its parts as in conventional Monte Carlo methods. The probability density functions (pdf's) are expressed in terms of spherical harmonics and are continuous functions in direction cosine and azimuthal angle variables as well as in position coordinates; the energy is discretized in the multigroup approximation. The transport pdf is an unusual exponential kernel strongly dependent on the incident and emergent directions and energies and on the position of the collision site. The method produces the same results obtained with the deterministic method with a very small standard deviation, with as little as 1,000 Contribution particles in both analog and nonabsorption biasing modes and with only a few minutes CPU time

A simple method for estimating the convection- dispersion equation ...

African Journals Online (AJOL)

Jane

2011-08-31

Aug 31, 2011 ... approach of modeling solute transport in porous media uses the deterministic ... Methods of estimating CDE transport parameters can be divided into statistical ..... diffusion-type model for longitudinal mixing of fluids in flow.

Joint Parametric Fault Diagnosis and State Estimation Using KF-ML Method

DEFF Research Database (Denmark)

Sun, Zhen; Yang, Zhenyu

2014-01-01

The paper proposes a new method for a kind of parametric fault online diagnosis with state estimation jointly. The considered fault affects not only the deterministic part of the system but also the random circumstance. The proposed method first applies Kalman Filter (KF) and Maximum Likelihood (...

Deterministic Earthquake Hazard Assessment by Public Agencies in California

Science.gov (United States)

Mualchin, L.

2005-12-01

Even in its short recorded history, California has experienced a number of damaging earthquakes that have resulted in new codes and other legislation for public safety. In particular, the 1971 San Fernando earthquake produced some of the most lasting results such as the Hospital Safety Act, the Strong Motion Instrumentation Program, the Alquist-Priolo Special Studies Zone Act, and the California Department of Transportation (Caltrans') fault-based deterministic seismic hazard (DSH) map. The latter product provides values for earthquake ground motions based on Maximum Credible Earthquakes (MCEs), defined as the largest earthquakes that can reasonably be expected on faults in the current tectonic regime. For surface fault rupture displacement hazards, detailed study of the same faults apply. Originally, hospital, dam, and other critical facilities used seismic design criteria based on deterministic seismic hazard analyses (DSHA). However, probabilistic methods grew and took hold by introducing earthquake design criteria based on time factors and quantifying "uncertainties", by procedures such as logic trees. These probabilistic seismic hazard analyses (PSHA) ignored the DSH approach. Some agencies were influenced to adopt only the PSHA method. However, deficiencies in the PSHA method are becoming recognized, and the use of the method is now becoming a focus of strong debate. Caltrans is in the process of producing the fourth edition of its DSH map. The reason for preferring the DSH method is that Caltrans believes it is more realistic than the probabilistic method for assessing earthquake hazards that may affect critical facilities, and is the best available method for insuring public safety. Its time-invariant values help to produce robust design criteria that are soundly based on physical evidence. And it is the method for which there is the least opportunity for unwelcome surprises.

Bearing-only SLAM: comparison between probabilistic and deterministic methods

OpenAIRE

Joly , Cyril; Rives , Patrick

2008-01-01

This work deals with the problem of simultaneous localization and mapping (SLAM). Classical methods for solving the SLAM problem are based on the Extended Kalman Filter (EKF-SLAM) or particle filter (FastSLAM). These kinds of algorithms allow on-line solving but could be inconsistent. In this report, the above-mentioned algorithms are not studied but global ones. Global approaches need all measurements from the initial step to the final step in order to compute the trajectory of the robot and...

Process identification method based on the Z transformation; Methode d'identification de processus par la transformation en Z

Energy Technology Data Exchange (ETDEWEB)

Zwingelstein, G [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1968-07-01

A simple method is described for identifying the transfer function of a linear retard-less system, based on the inversion of the Z transformation of the transmittance using a computer. It is assumed in this study that the signals at the entrance and at the exit of the circuit considered are of the deterministic type. The study includes: the theoretical principle of the inversion of the Z transformation, details about programming simulation, and identification of filters whose degrees vary from the first to the fifth order. (authors) [French] On decrit une methode simple d'identification de fonction de transfert d'un systeme lineaire sans retard, qui repose sur l'inversion de la transformee en Z de la transmittance a l'aide d'un calculateur. On suppose dans cette etude, que les signaux a l'entree et a la sortie du circuit considere sont de type deterministe. L'etude comporte: le principe theorique de l'inversion de la transformation en Z, les details de la programmation, la simulation et l'identification de filtres dont le degre varie du premier au cinquieme ordre. (auteurs)

Use and application of 'best estimate plus uncertainty' methods. A regulatory view

International Nuclear Information System (INIS)

Mendizabal, Rafael; Pelayo, Fernando

2013-01-01

Regulatory environment is characterized by its prevention to change. Any move has to be solidly founded. Application in licensing of Best Estimate Plus Uncertainty (BEPU) methods is not an exception. Typically a fully deterministic approach as described in IAEA SSG-2 is used for design bases accident analyses in current Nuclear Power Plants. In recent years the use of BEPU methodologies is gaining favor in the nuclear technology community as a way to optimize design and operation while preserving full compliance with applicable regulation. This paper has its focus on the regulatory relevance of the use of BEPU in licensing practices. A regulatory analysis describing the rationale of the evolution from classic deterministic methods to BEPU as well as a selected set of topics around the implications of the use of BEPU methods is shown. To finalize some conclusions and thoughts of possible further developments of these methods are drawn. (authors)

Finite element random vibration method for soil-structure interaction analysis

International Nuclear Information System (INIS)

Romo-Organista, M.P.; Lysmer, J.; Seed, H.B.

1977-01-01

The authors present a method in which the seismic environment is defined directly in terms of the given design response spectrum. Response spectra cannot be used directly for random analysis, thus using extreme value theory a new procedure has been developed for converting the design response spectrum into a design power spectrum. This procedure is reversible and can also be used to compute response spectra the distribution of which can be expressed in terms of Confidence limits. Knowing the design power spctrum the resulting output power spectra and their statistical distribution can be computed by a response analysis of the soil-structure system in the frequency domain. Due to the complexity of soil structure systems, this is most conveniently done by the finite element method. Having obtained the power spectra for all motions in the system, these spectra can be used to determine other statistical information about the response such as maximum accelerations, stresses, bending moments, etc, all with appropriate confidence limits. This type of information is actually more useful for design than corresponding deterministic values. The authors have developed a computer program, PLUSH, which can perform the above procedures. Results obtained by the new method are in excellent agreement with the results of corresponding deterministic analysis. Furthermore, the probabilistic results can be obtained at a fraction of the cost of deterministic results

Uniform distribution and quasi-Monte Carlo methods discrepancy, integration and applications

CERN Document Server

Kritzer, Peter; Pillichshammer, Friedrich; Winterhof, Arne

2014-01-01

The survey articles in this book focus on number theoretic point constructions, uniform distribution theory, and quasi-Monte Carlo methods. As deterministic versions of the Monte Carlo method, quasi-Monte Carlo rules enjoy increasing popularity, with many fruitful applications in mathematical practice, as for example in finance, computer graphics, and biology.

Reliability-based design optimization using a generalized subset simulation method and posterior approximation

Science.gov (United States)

Ma, Yuan-Zhuo; Li, Hong-Shuang; Yao, Wei-Xing

2018-05-01

The evaluation of the probabilistic constraints in reliability-based design optimization (RBDO) problems has always been significant and challenging work, which strongly affects the performance of RBDO methods. This article deals with RBDO problems using a recently developed generalized subset simulation (GSS) method and a posterior approximation approach. The posterior approximation approach is used to transform all the probabilistic constraints into ordinary constraints as in deterministic optimization. The assessment of multiple failure probabilities required by the posterior approximation approach is achieved by GSS in a single run at all supporting points, which are selected by a proper experimental design scheme combining Sobol' sequences and Bucher's design. Sequentially, the transformed deterministic design optimization problem can be solved by optimization algorithms, for example, the sequential quadratic programming method. Three optimization problems are used to demonstrate the efficiency and accuracy of the proposed method.

Resolution of the neutron transport equation by a three-dimensional least square method

International Nuclear Information System (INIS)

Varin, Elisabeth

2001-01-01

The knowledge of space and time distribution of neutrons with a certain energy or speed allows the exploitation and control of a nuclear reactor and the assessment of the irradiation dose about an irradiated nuclear fuel storage site. The neutron density is described by a transport equation. The objective of this research thesis is to develop a software for the resolution of this stationary equation in a three-dimensional Cartesian domain by means of a deterministic method. After a presentation of the transport equation, the author gives an overview of the different deterministic resolution approaches, identifies their benefits and drawbacks, and discusses the choice of the Ressel method. The least square method is precisely described and then applied. Numerical benchmarks are reported for validation purposes

A deterministic width function model

Directory of Open Access Journals (Sweden)

C. E. Puente

2003-01-01

Full Text Available Use of a deterministic fractal-multifractal (FM geometric method to model width functions of natural river networks, as derived distributions of simple multifractal measures via fractal interpolating functions, is reported. It is first demonstrated that the FM procedure may be used to simulate natural width functions, preserving their most relevant features like their overall shape and texture and their observed power-law scaling on their power spectra. It is then shown, via two natural river networks (Racoon and Brushy creeks in the United States, that the FM approach may also be used to closely approximate existing width functions.

Nonlinear deterministic structures and the randomness of protein sequences

CERN Document Server

Huang Yan Zhao

2003-01-01

To clarify the randomness of protein sequences, we make a detailed analysis of a set of typical protein sequences representing each structural classes by using nonlinear prediction method. No deterministic structures are found in these protein sequences and this implies that they behave as random sequences. We also give an explanation to the controversial results obtained in previous investigations.

Proteus-MOC: A 3D deterministic solver incorporating 2D method of characteristics

International Nuclear Information System (INIS)

Marin-Lafleche, A.; Smith, M. A.; Lee, C.

2013-01-01

A new transport solution methodology was developed by combining the two-dimensional method of characteristics with the discontinuous Galerkin method for the treatment of the axial variable. The method, which can be applied to arbitrary extruded geometries, was implemented in PROTEUS-MOC and includes parallelization in group, angle, plane, and space using a top level GMRES linear algebra solver. Verification tests were performed to show accuracy and stability of the method with the increased number of angular directions and mesh elements. Good scalability with parallelism in angle and axial planes is displayed. (authors)

Proteus-MOC: A 3D deterministic solver incorporating 2D method of characteristics

Energy Technology Data Exchange (ETDEWEB)

Marin-Lafleche, A.; Smith, M. A.; Lee, C. [Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, IL 60439 (United States)

2013-07-01

A new transport solution methodology was developed by combining the two-dimensional method of characteristics with the discontinuous Galerkin method for the treatment of the axial variable. The method, which can be applied to arbitrary extruded geometries, was implemented in PROTEUS-MOC and includes parallelization in group, angle, plane, and space using a top level GMRES linear algebra solver. Verification tests were performed to show accuracy and stability of the method with the increased number of angular directions and mesh elements. Good scalability with parallelism in angle and axial planes is displayed. (authors)

Influence of wind energy forecast in deterministic and probabilistic sizing of reserves

Energy Technology Data Exchange (ETDEWEB)

Gil, A.; Torre, M. de la; Dominguez, T.; Rivas, R. [Red Electrica de Espana (REE), Madrid (Spain). Dept. Centro de Control Electrico

2010-07-01

One of the challenges in large-scale wind energy integration in electrical systems is coping with wind forecast uncertainties at the time of sizing generation reserves. These reserves must be sized large enough so that they don't compromise security of supply or the balance of the system, but economic efficiency must be also kept in mind. This paper describes two methods of sizing spinning reserves taking into account wind forecast uncertainties, deterministic using a probabilistic wind forecast and probabilistic using stochastic variables. The deterministic method calculates the spinning reserve needed by adding components each of them in order to overcome one single uncertainty: demand errors, the biggest thermal generation loss and wind forecast errors. The probabilistic method assumes that demand forecast errors, short-term thermal group unavailability and wind forecast errors are independent stochastic variables and calculates the probability density function of the three variables combined. These methods are being used in the case of the Spanish peninsular system, in which wind energy accounted for 14% of the total electrical energy produced in the year 2009 and is one of the systems in the world with the highest wind penetration levels. (orig.)

Reliable method for fission source convergence of Monte Carlo criticality calculation with Wielandt's method

International Nuclear Information System (INIS)

Yamamoto, Toshihiro; Miyoshi, Yoshinori

2004-01-01

A new algorithm of Monte Carlo criticality calculations for implementing Wielandt's method, which is one of acceleration techniques for deterministic source iteration methods, is developed, and the algorithm can be successfully implemented into MCNP code. In this algorithm, part of fission neutrons emitted during random walk processes are tracked within the current cycle, and thus a fission source distribution used in the next cycle spread more widely. Applying this method intensifies a neutron interaction effect even in a loosely-coupled array where conventional Monte Carlo criticality methods have difficulties, and a converged fission source distribution can be obtained with fewer cycles. Computing time spent for one cycle, however, increases because of tracking fission neutrons within the current cycle, which eventually results in an increase of total computing time up to convergence. In addition, statistical fluctuations of a fission source distribution in a cycle are worsened by applying Wielandt's method to Monte Carlo criticality calculations. However, since a fission source convergence is attained with fewer source iterations, a reliable determination of convergence can easily be made even in a system with a slow convergence. This acceleration method is expected to contribute to prevention of incorrect Monte Carlo criticality calculations. (author)

Risk-Informed SSCs Categorization: Elicitation Method of Expert's Opinion

International Nuclear Information System (INIS)

Hwang, Mee Jeong; Yang, Joon Eon; Kim, Kil Yoo

2005-01-01

The regulations have been performing by deterministic way since nuclear power plants have been operating. However, some SSCs identified as safety-significance by deterministic way, were turned out to be low or non safety-significant and some SSCs identified as non-safety significance were turned out to be high safety-significant according to the results of PSA. Considering these risk insights, Regulatory Guide 1.174 and 10CFR50.69 were drawn up, and we can re-categorize the SSCs according to their safety significance. Therefore, a study and an interest about the risk-informed SSCs re-categorization and treatment has been continued. The objective of this regulatory initiative is to adjust the scope of equipment subject to special regulatory treatment to better focus licensee and regulatory attention and resources on equipment that has safety significance. Current most regulations define the plant equipment necessary to meet deterministic regulatory basis as 'safety-related.' This equipment is subject to special treatment regulations. Other plant equipment is categorized as 'non-safety related,' and is not subject to a select number of special treatment requirement or a subset of those requirement. However, risk information is not a magic tool making a decision but a supporting tool to categorize SSCs. This is because only small parts of a plant are modeled in PSA model. Thus, engineering and deterministic judgments are also used for risk-informed SSCs categorization, and expert opinion elicitation is very important for risk-informed SSCs categorization. Therefore, we need a rational method to elicit the expert's opinions, and in this study, we developed a systematic method for expert elicitation to categorize the nuclear power plants' SSCs. Current states for SSCs categorization of the USA and the existing methods for expert elicitation were surveyed and more systematic way eliciting the expert opinions and combining was developed. To validate the developed method

Deterministic and Probabilistic Analysis of NPP Communication Bridge Resistance Due to Extreme Loads

Directory of Open Access Journals (Sweden)

Králik Juraj

2014-12-01

Full Text Available This paper presents the experiences from the deterministic and probability analysis of the reliability of communication bridge structure resistance due to extreme loads - wind and earthquake. On the example of the steel bridge between two NPP buildings is considered the efficiency of the bracing systems. The advantages and disadvantages of the deterministic and probabilistic analysis of the structure resistance are discussed. The advantages of the utilization the LHS method to analyze the safety and reliability of the structures is presented

Testing serial dependence by Random-shuffle surrogates and the Wayland method

Energy Technology Data Exchange (ETDEWEB)

Hirata, Yoshito [Department of Mathematical Informatics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Aihara Complexity Modelling Project, ERATO, JST (Japan); Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)], E-mail: yoshito@sat.t.u-tokyo.ac.jp; Horai, Shunsuke [Aihara Complexity Modelling Project, ERATO, JST (Japan); Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Suzuki, Hideyuki [Department of Mathematical Informatics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Aihara, Kazuyuki [Department of Mathematical Informatics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Aihara Complexity Modelling Project, ERATO, JST (Japan); Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)

2007-10-22

Given time series, a primary concern is existence of serial dependence and determinism. They are often tested with Random-shuffle surrogates, which totally break serial dependence, and the Wayland method. Since the statistic of the Wayland method fundamentally shows a smaller value for a more deterministic time series, for real-world data, we usually expect that the statistic for the original data is smaller than or equal to those of Random-shuffle surrogates. However, we show herewith an opposite result with wind data in high time resolution. We argue that this puzzling phenomenon can be produced by observational or dynamical noise, both of which may be produced by a low-dimensional deterministic system. Thus the one-sided test is dangerous.

Testing serial dependence by Random-shuffle surrogates and the Wayland method

International Nuclear Information System (INIS)

Hirata, Yoshito; Horai, Shunsuke; Suzuki, Hideyuki; Aihara, Kazuyuki

2007-01-01

Given time series, a primary concern is existence of serial dependence and determinism. They are often tested with Random-shuffle surrogates, which totally break serial dependence, and the Wayland method. Since the statistic of the Wayland method fundamentally shows a smaller value for a more deterministic time series, for real-world data, we usually expect that the statistic for the original data is smaller than or equal to those of Random-shuffle surrogates. However, we show herewith an opposite result with wind data in high time resolution. We argue that this puzzling phenomenon can be produced by observational or dynamical noise, both of which may be produced by a low-dimensional deterministic system. Thus the one-sided test is dangerous

Over-deterministic method: The influence of rounding numbers on the accuracy of the values of williams’ expansion terms

Czech Academy of Sciences Publication Activity Database

Růžička, V.; Malíková, Lucie; Seitl, Stanislav

2017-01-01

Roč. 11, č. 42 (2017), s. 128-135 ISSN 1971-8993 R&D Projects: GA ČR GA17-01589S Institutional support: RVO:68081723 Keywords : Over-deterministic * Fracture mechanics * Rounding numbers * Stress field * Williams’ expansion Subject RIV: JL - Materials Fatigue, Friction Mechanics OBOR OECD: Audio engineering, reliability analysis

Generalized outcome-based strategy classification: comparing deterministic and probabilistic choice models.

Science.gov (United States)

Hilbig, Benjamin E; Moshagen, Morten

2014-12-01

Model comparisons are a vital tool for disentangling which of several strategies a decision maker may have used--that is, which cognitive processes may have governed observable choice behavior. However, previous methodological approaches have been limited to models (i.e., decision strategies) with deterministic choice rules. As such, psychologically plausible choice models--such as evidence-accumulation and connectionist models--that entail probabilistic choice predictions could not be considered appropriately. To overcome this limitation, we propose a generalization of Bröder and Schiffer's (Journal of Behavioral Decision Making, 19, 361-380, 2003) choice-based classification method, relying on (1) parametric order constraints in the multinomial processing tree framework to implement probabilistic models and (2) minimum description length for model comparison. The advantages of the generalized approach are demonstrated through recovery simulations and an experiment. In explaining previous methods and our generalization, we maintain a nontechnical focus--so as to provide a practical guide for comparing both deterministic and probabilistic choice models.

Determination of axial diffusion coefficients by the Monte-Carlo method

International Nuclear Information System (INIS)

Milgram, M.

1994-01-01

A simple method to calculate the homogenized diffusion coefficient for a lattice cell using Monte-Carlo techniques is demonstrated. The method relies on modelling a finite reactor volume to induce a curvature in the flux distribution, and then follows a large number of histories to obtain sufficient statistics for a meaningful result. The goal is to determine the diffusion coefficient with sufficient accuracy to test approximate methods built into deterministic lattice codes. Numerical results are given. (author). 4 refs., 8 figs

SU-C-BRC-03: Development of a Novel Strategy for On-Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy

Energy Technology Data Exchange (ETDEWEB)

Yang, Y M; Bush, K; Han, B; Xing, L [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA (United States)

2016-06-15

Purpose: Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed. Methods: Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) method that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms. Results: We achieved <1% agreement between deterministic and MC calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region. Conclusion: Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high

SU-C-BRC-03: Development of a Novel Strategy for On-Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy

International Nuclear Information System (INIS)

Yang, Y M; Bush, K; Han, B; Xing, L

2016-01-01

Purpose: Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed. Methods: Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) method that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms. Results: We achieved <1% agreement between deterministic and MC calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region. Conclusion: Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high

Nano transfer and nanoreplication using deterministically grown sacrificial nanotemplates

Science.gov (United States)

Melechko, Anatoli V [Oak Ridge, TN; McKnight, Timothy E [Greenback, TN; Guillorn, Michael A [Ithaca, NY; Ilic, Bojan [Ithaca, NY; Merkulov, Vladimir I [Knoxville, TX; Doktycz, Mitchel J [Knoxville, TN; Lowndes, Douglas H [Knoxville, TN; Simpson, Michael L [Knoxville, TN

2012-03-27

Methods, manufactures, machines and compositions are described for nanotransfer and nanoreplication using deterministically grown sacrificial nanotemplates. An apparatus, includes a substrate and a nanoconduit material coupled to a surface of the substrate. The substrate defines an aperture and the nanoconduit material defines a nanoconduit that is i) contiguous with the aperture and ii) aligned substantially non-parallel to a plane defined by the surface of the substrate.

Deterministic computation of functional integrals

International Nuclear Information System (INIS)

Lobanov, Yu.Yu.

1995-09-01

A new method of numerical integration in functional spaces is described. This method is based on the rigorous definition of a functional integral in complete separable metric space and on the use of approximation formulas which we constructed for this kind of integral. The method is applicable to solution of some partial differential equations and to calculation of various characteristics in quantum physics. No preliminary discretization of space and time is required in this method, as well as no simplifying assumptions like semi-classical, mean field approximations, collective excitations, introduction of ''short-time'' propagators, etc are necessary in our approach. The constructed approximation formulas satisfy the condition of being exact on a given class of functionals, namely polynomial functionals of a given degree. The employment of these formulas replaces the evaluation of a functional integral by computation of the ''ordinary'' (Riemannian) integral of a low dimension, thus allowing to use the more preferable deterministic algorithms (normally - Gaussian quadratures) in computations rather than traditional stochastic (Monte Carlo) methods which are commonly used for solution of the problem under consideration. The results of application of the method to computation of the Green function of the Schroedinger equation in imaginary time as well as the study of some models of Euclidean quantum mechanics are presented. The comparison with results of other authors shows that our method gives significant (by an order of magnitude) economy of computer time and memory versus other known methods while providing the results with the same or better accuracy. The funcitonal measure of the Gaussian type is considered and some of its particular cases, namely conditional Wiener measure in quantum statistical mechanics and functional measure in a Schwartz distribution space in two-dimensional quantum field theory are studied in detail. Numerical examples demonstrating the

Deterministic sensitivity and uncertainty analysis for large-scale computer models

International Nuclear Information System (INIS)

Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.

1988-01-01

This paper presents a comprehensive approach to sensitivity and uncertainty analysis of large-scale computer models that is analytic (deterministic) in principle and that is firmly based on the model equations. The theory and application of two systems based upon computer calculus, GRESS and ADGEN, are discussed relative to their role in calculating model derivatives and sensitivities without a prohibitive initial manpower investment. Storage and computational requirements for these two systems are compared for a gradient-enhanced version of the PRESTO-II computer model. A Deterministic Uncertainty Analysis (DUA) method that retains the characteristics of analytically computing result uncertainties based upon parameter probability distributions is then introduced and results from recent studies are shown. 29 refs., 4 figs., 1 tab

An Adjoint State Method for Three-Dimensional Transmission Traveltime Tomography Using First-Arrivals

Science.gov (United States)

2006-01-30

detail next. 3.2 Fast Sweeping Method for Equation (1) The fast sweeping method was originated in Boue and Dupis [5], its first PDE formulation was in...Geophysics, 50:903–923, 1985. [5] M. Boue and P. Dupuis. Markov chain approximations for deterministic control prob- lems with affine dynamics and

Precursor analyses - The use of deterministic and PSA based methods in the event investigation process at nuclear power plants

International Nuclear Information System (INIS)

2004-09-01

The efficient feedback of operating experience (OE) is a valuable source of information for improving the safety and reliability of nuclear power plants (NPPs). It is therefore essential to collect information on abnormal events from both internal and external sources. Internal operating experience is analysed to obtain a complete understanding of an event and of its safety implications. Corrective or improvement measures may then be developed, prioritized and implemented in the plant if considered appropriate. Information from external events may also be analysed in order to learn lessons from others' experience and prevent similar occurrences at our own plant. The traditional ways of investigating operational events have been predominantly qualitative. In recent years, a PSA-based method called probabilistic precursor event analysis has been developed, used and applied on a significant scale in many places for a number of plants. The method enables a quantitative estimation of the safety significance of operational events to be incorporated. The purpose of this report is to outline a synergistic process that makes more effective use of operating experience event information by combining the insights and knowledge gained from both approaches, traditional deterministic event investigation and PSA-based event analysis. The PSA-based view on operational events and PSA-based event analysis can support the process of operational event analysis at the following stages of the operational event investigation: (1) Initial screening stage. (It introduces an element of quantitative analysis into the selection process. Quantitative analysis of the safety significance of nuclear plant events can be a very useful measure when it comes to selecting internal and external operating experience information for its relevance.) (2) In-depth analysis. (PSA based event evaluation provides a quantitative measure for judging the significance of operational events, contributors to

Deterministic and Probabilistic Serviceability Assessment of Footbridge Vibrations due to a Single Walker Crossing

Directory of Open Access Journals (Sweden)

Cristoforo Demartino

2018-01-01

Full Text Available This paper presents a numerical study on the deterministic and probabilistic serviceability assessment of footbridge vibrations due to a single walker crossing. The dynamic response of the footbridge is analyzed by means of modal analysis, considering only the first lateral and vertical modes. Single span footbridges with uniform mass distribution are considered, with different values of the span length, natural frequencies, mass, and structural damping and with different support conditions. The load induced by a single walker crossing the footbridge is modeled as a moving sinusoidal force either in the lateral or in the vertical direction. The variability of the characteristics of the load induced by walkers is modeled using probability distributions taken from the literature defining a Standard Population of walkers. Deterministic and probabilistic approaches were adopted to assess the peak response. Based on the results of the simulations, deterministic and probabilistic vibration serviceability assessment methods are proposed, not requiring numerical analyses. Finally, an example of the application of the proposed method to a truss steel footbridge is presented. The results highlight the advantages of the probabilistic procedure in terms of reliability quantification.

Deterministic Graphical Games Revisited

DEFF Research Database (Denmark)

Andersson, Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro

2008-01-01

We revisit the deterministic graphical games of Washburn. A deterministic graphical game can be described as a simple stochastic game (a notion due to Anne Condon), except that we allow arbitrary real payoffs but disallow moves of chance. We study the complexity of solving deterministic graphical...... games and obtain an almost-linear time comparison-based algorithm for computing an equilibrium of such a game. The existence of a linear time comparison-based algorithm remains an open problem....

Deterministic and probabilistic approach to determine seismic risk of nuclear power plants; a practical example

International Nuclear Information System (INIS)

Soriano Pena, A.; Lopez Arroyo, A.; Roesset, J.M.

1976-01-01

The probabilistic and deterministic approaches for calculating the seismic risk of nuclear power plants are both applied to a particular case in Southern Spain. The results obtained by both methods, when varying the input data, are presented and some conclusions drawn in relation to the applicability of the methods, their reliability and their sensitivity to change

Numerical method for two phase flow with a unstable interface

International Nuclear Information System (INIS)

Glimm, J.; Marchesin, D.; McBryan, O.

1981-01-01

The random choice method is used to compute the oil-water interface for two dimensional porous media equations. The equations used are a pair of coupled equations; the (elliptic) pressure equation and the (hyperbolic) saturation equation. The equations do not include the dispersive capillary pressure term and the computation does not introduce numerical diffusion. The method resolves saturation discontinuities sharply. The main conclusion of this paper is that the random choice is a correct numerical procedure for this problem even in the highly fingered case. Two methods of inducing fingers are considered: deterministically, through choice of Cauchy data and heterogeneity, through maximizing the randomness of the random choice method

Forward-weighted CADIS method for variance reduction of Monte Carlo calculations of distributions and multiple localized quantities

International Nuclear Information System (INIS)

Wagner, J. C.; Blakeman, E. D.; Peplow, D. E.

2009-01-01

This paper presents a new hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is a variation on the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for some time to very effectively improve the efficiency of Monte Carlo calculations of localized quantities, e.g., flux, dose, or reaction rate at a specific location. The basis of this method is the development of an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space- and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain approximately uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented in the ADVANTG/MCNP framework and has been fully automated within the MAVRIC sequence of SCALE 6. Results of the application of the method to enabling the calculation of dose rates throughout an entire full-scale pressurized-water reactor facility are presented and discussed. (authors)

Deterministic global optimization an introduction to the diagonal approach

CERN Document Server

Sergeyev, Yaroslav D

2017-01-01

This book begins with a concentrated introduction into deterministic global optimization and moves forward to present new original results from the authors who are well known experts in the field. Multiextremal continuous problems that have an unknown structure with Lipschitz objective functions and functions having the first Lipschitz derivatives defined over hyperintervals are examined. A class of algorithms using several Lipschitz constants is introduced which has its origins in the DIRECT (DIviding RECTangles) method. This new class is based on an efficient strategy that is applied for the search domain partitioning. In addition a survey on derivative free methods and methods using the first derivatives is given for both one-dimensional and multi-dimensional cases. Non-smooth and smooth minorants and acceleration techniques that can speed up several classes of global optimization methods with examples of applications and problems arising in numerical testing of global optimization algorithms are discussed...

Height-Deterministic Pushdown Automata

DEFF Research Database (Denmark)

Nowotka, Dirk; Srba, Jiri

2007-01-01

We define the notion of height-deterministic pushdown automata, a model where for any given input string the stack heights during any (nondeterministic) computation on the input are a priori fixed. Different subclasses of height-deterministic pushdown automata, strictly containing the class...... of regular languages and still closed under boolean language operations, are considered. Several of such language classes have been described in the literature. Here, we suggest a natural and intuitive model that subsumes all the formalisms proposed so far by employing height-deterministic pushdown automata...

A hybrid multiscale kinetic Monte Carlo method for simulation of copper electrodeposition

International Nuclear Information System (INIS)

Zheng Zheming; Stephens, Ryan M.; Braatz, Richard D.; Alkire, Richard C.; Petzold, Linda R.

2008-01-01

A hybrid multiscale kinetic Monte Carlo (HMKMC) method for speeding up the simulation of copper electrodeposition is presented. The fast diffusion events are simulated deterministically with a heterogeneous diffusion model which considers site-blocking effects of additives. Chemical reactions are simulated by an accelerated (tau-leaping) method for discrete stochastic simulation which adaptively selects exact discrete stochastic simulation for the appropriate reaction whenever that is necessary. The HMKMC method is seen to be accurate and highly efficient

Probabilistic safety analysis : a new nuclear power plants licensing method

International Nuclear Information System (INIS)

Oliveira, L.F.S. de.

1982-04-01

After a brief retrospect of the application of Probabilistic Safety Analysis in the nuclear field, the basic differences between the deterministic licensing method, currently in use, and the probabilistic method are explained. Next, the two main proposals (by the AIF and the ACRS) concerning the establishment of the so-called quantitative safety goals (or simply 'safety goals') are separately presented and afterwards compared in their most fundamental aspects. Finally, some recent applications and future possibilities are discussed. (Author) [pt

Prospects in deterministic three dimensional whole-core transport calculations

International Nuclear Information System (INIS)

Sanchez, Richard

2012-01-01

The point we made in this paper is that, although detailed and precise three-dimensional (3D) whole-core transport calculations may be obtained in the future with massively parallel computers, they would have an application to only some of the problems of the nuclear industry, more precisely those regarding multiphysics or for methodology validation or nuclear safety calculations. On the other hand, typical design reactor cycle calculations comprising many one-point core calculations can have very strict constraints in computing time and will not directly benefit from the advances in computations in large scale computers. Consequently, in this paper we review some of the deterministic 3D transport methods which in the very near future may have potential for industrial applications and, even with low-order approximations such as a low resolution in energy, might represent an advantage as compared with present industrial methodology, for which one of the main approximations is due to power reconstruction. These methods comprise the response-matrix method and methods based on the two-dimensional (2D) method of characteristics, such as the fusion method.

Risk-Informed SSCs Categorization: Elicitation Method of Expert's Opinion

Energy Technology Data Exchange (ETDEWEB)

Hwang, Mee Jeong; Yang, Joon Eon; Kim, Kil Yoo

2005-01-15

The regulations have been performing by deterministic way since nuclear power plants have been operating. However, some SSCs identified as safety-significance by deterministic way, were turned out to be low or non safety-significant and some SSCs identified as non-safety significance were turned out to be high safety-significant according to the results of PSA. Considering these risk insights, Regulatory Guide 1.174 and 10CFR50.69 were drawn up, and we can re-categorize the SSCs according to their safety significance. Therefore, a study and an interest about the risk-informed SSCs re-categorization and treatment has been continued. The objective of this regulatory initiative is to adjust the scope of equipment subject to special regulatory treatment to better focus licensee and regulatory attention and resources on equipment that has safety significance. Current most regulations define the plant equipment necessary to meet deterministic regulatory basis as 'safety-related.' This equipment is subject to special treatment regulations. Other plant equipment is categorized as 'non-safety related,' and is not subject to a select number of special treatment requirement or a subset of those requirement. However, risk information is not a magic tool making a decision but a supporting tool to categorize SSCs. This is because only small parts of a plant are modeled in PSA model. Thus, engineering and deterministic judgments are also used for risk-informed SSCs categorization, and expert opinion elicitation is very important for risk-informed SSCs categorization. Therefore, we need a rational method to elicit the expert's opinions, and in this study, we developed a systematic method for expert elicitation to categorize the nuclear power plants' SSCs. Current states for SSCs categorization of the USA and the existing methods for expert elicitation were surveyed and more systematic way eliciting the expert opinions and combining was developed. To

Top-down fabrication of plasmonic nanostructures for deterministic coupling to single quantum emitters

NARCIS (Netherlands)

Pfaff, W.; Vos, A.; Hanson, R.

2013-01-01

Metal nanostructures can be used to harvest and guide the emission of single photon emitters on-chip via surface plasmon polaritons. In order to develop and characterize photonic devices based on emitter-plasmon hybrid structures, a deterministic and scalable fabrication method for such structures

Weak Second Order Explicit Stabilized Methods for Stiff Stochastic Differential Equations

KAUST Repository

Abdulle, Assyr

2013-01-01

We introduce a new family of explicit integrators for stiff Itô stochastic differential equations (SDEs) of weak order two. These numerical methods belong to the class of one-step stabilized methods with extended stability domains and do not suffer from the step size reduction faced by standard explicit methods. The family is based on the standard second order orthogonal Runge-Kutta-Chebyshev (ROCK2) methods for deterministic problems. The convergence, meansquare, and asymptotic stability properties of the methods are analyzed. Numerical experiments, including applications to nonlinear SDEs and parabolic stochastic partial differential equations are presented and confirm the theoretical results. © 2013 Society for Industrial and Applied Mathematics.

Deterministic global optimization algorithm based on outer approximation for the parameter estimation of nonlinear dynamic biological systems.

Science.gov (United States)

Miró, Anton; Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Egea, Jose A; Jiménez, Laureano

2012-05-10

The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are usually classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens. This work presents a deterministic outer approximation-based algorithm for the global optimization of dynamic problems arising in the parameter estimation of models of biological systems. Our approach, which offers a theoretical guarantee of convergence to global minimum, is based on reformulating the set of ordinary differential equations into an equivalent set of algebraic equations through the use of orthogonal collocation methods, giving rise to a nonconvex nonlinear programming (NLP) problem. This nonconvex NLP is decomposed into two hierarchical levels: a master mixed-integer linear programming problem (MILP) that provides a rigorous lower bound on the optimal solution, and a reduced-space slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied. The capabilities of our approach were tested in two benchmark problems, in which the performance of our algorithm was compared with that of the commercial global optimization package BARON. The proposed strategy produced near optimal solutions (i.e., within a desired tolerance) in a fraction of the CPU time required by BARON.

Deterministic behavioural models for concurrency

DEFF Research Database (Denmark)

Sassone, Vladimiro; Nielsen, Mogens; Winskel, Glynn

1993-01-01

This paper offers three candidates for a deterministic, noninterleaving, behaviour model which generalizes Hoare traces to the noninterleaving situation. The three models are all proved equivalent in the rather strong sense of being equivalent as categories. The models are: deterministic labelled...... event structures, generalized trace languages in which the independence relation is context-dependent, and deterministic languages of pomsets....

Hybrid and Parallel Domain-Decomposition Methods Development to Enable Monte Carlo for Reactor Analyses

International Nuclear Information System (INIS)

Wagner, John C.; Mosher, Scott W.; Evans, Thomas M.; Peplow, Douglas E.; Turner, John A.

2010-01-01

This paper describes code and methods development at the Oak Ridge National Laboratory focused on enabling high-fidelity, large-scale reactor analyses with Monte Carlo (MC). Current state-of-the-art tools and methods used to perform real commercial reactor analyses have several undesirable features, the most significant of which is the non-rigorous spatial decomposition scheme. Monte Carlo methods, which allow detailed and accurate modeling of the full geometry and are considered the gold standard for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the deterministic, multi-level spatial decomposition methodology in current practice. However, the prohibitive computational requirements associated with obtaining fully converged, system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. The goal of this research is to change this paradigm by enabling direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome are the slow, non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, our research has focused on the development and implementation of (1) a novel hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition (DD) algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The hybrid method development is based on an extension of the FW-CADIS method, which

Hybrid and parallel domain-decomposition methods development to enable Monte Carlo for reactor analyses

International Nuclear Information System (INIS)

Wagner, J.C.; Mosher, S.W.; Evans, T.M.; Peplow, D.E.; Turner, J.A.

2010-01-01

This paper describes code and methods development at the Oak Ridge National Laboratory focused on enabling high-fidelity, large-scale reactor analyses with Monte Carlo (MC). Current state-of-the-art tools and methods used to perform 'real' commercial reactor analyses have several undesirable features, the most significant of which is the non-rigorous spatial decomposition scheme. Monte Carlo methods, which allow detailed and accurate modeling of the full geometry and are considered the 'gold standard' for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the deterministic, multi-level spatial decomposition methodology in current practice. However, the prohibitive computational requirements associated with obtaining fully converged, system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. The goal of this research is to change this paradigm by enabling direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome are the slow, non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, our research has focused on the development and implementation of (1) a novel hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition (DD) algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The hybrid method development is based on an extension of the FW-CADIS method

Evaluation of Deterministic and Stochastic Components of Traffic Counts

Directory of Open Access Journals (Sweden)

Ivan Bošnjak

2012-10-01

Full Text Available Traffic counts or statistical evidence of the traffic processare often a characteristic of time-series data. In this paper fundamentalproblem of estimating deterministic and stochasticcomponents of a traffic process are considered, in the context of"generalised traffic modelling". Different methods for identificationand/or elimination of the trend and seasonal componentsare applied for concrete traffic counts. Further investigationsand applications of ARIMA models, Hilbert space formulationsand state-space representations are suggested.

The adaptation method in the Monte Carlo simulation for computed tomography

Energy Technology Data Exchange (ETDEWEB)

Lee, Hyoung Gun; Yoon, Chang Yeon; Lee, Won Ho [Dept. of Bio-convergence Engineering, Korea University, Seoul (Korea, Republic of); Cho, Seung Ryong [Dept. of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Park, Sung Ho [Dept. of Neurosurgery, Ulsan University Hospital, Ulsan (Korea, Republic of)

2015-06-15

The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT). To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA) and a human-like voxel phantom (KTMAN-2) (Los Alamos National Laboratory, Los Alamos, NM, USA). For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterations-assuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.

Deterministic and stochastic transport theories for the analysis of complex nuclear systems

International Nuclear Information System (INIS)

Giffard, F.X.

2000-01-01

In the field of reactor and fuel cycle physics, particle transport plays an important role. Neutronic design, operation and evaluation calculations of nuclear systems make use of large and powerful computer codes. However, current limitations in terms of computer resources make it necessary to introduce simplifications and approximations in order to keep calculation time and cost within reasonable limits. Two different types of methods are available in these codes. The first one is the deterministic method, which is applicable in most practical cases but requires approximations. The other method is the Monte Carlo method, which does not make these approximations but which generally requires exceedingly long running times. The main motivation of this work is to investigate the possibility of a combined use of the two methods in such a way as to retain their advantages while avoiding their drawbacks. Our work has mainly focused on the speed-up of 3-D continuous energy Monte Carlo calculations (TRIPOLI-4 code) by means of an optimized biasing scheme derived from importance maps obtained from the deterministic code ERANOS. The application of this method to two different practical shielding-type problems has demonstrated its efficiency: speed-up factors of 100 have been reached. In addition, the method offers the advantage of being easily implemented as it is not very sensitive to the choice of the importance mesh grid. It has also been demonstrated that significant speed-ups can be achieved by this method in the case of coupled neutron-gamma transport problems, provided that the interdependence of the neutron and photon importance maps is taken into account. Complementary studies are necessary to tackle a problem brought out by this work, namely undesirable jumps in the Monte Carlo variance estimates. (author)

Probabilistic Power Flow Method Considering Continuous and Discrete Variables

Directory of Open Access Journals (Sweden)

Xuexia Zhang

2017-04-01

Full Text Available This paper proposes a probabilistic power flow (PPF method considering continuous and discrete variables (continuous and discrete power flow, CDPF for power systems. The proposed method—based on the cumulant method (CM and multiple deterministic power flow (MDPF calculations—can deal with continuous variables such as wind power generation (WPG and loads, and discrete variables such as fuel cell generation (FCG. In this paper, continuous variables follow a normal distribution (loads or a non-normal distribution (WPG, and discrete variables follow a binomial distribution (FCG. Through testing on IEEE 14-bus and IEEE 118-bus power systems, the proposed method (CDPF has better accuracy compared with the CM, and higher efficiency compared with the Monte Carlo simulation method (MCSM.

Automated Controller Synthesis for non-Deterministic Piecewise-Affine Hybrid Systems

DEFF Research Database (Denmark)

Grunnet, Jacob Deleuran

formations. This thesis uses a hybrid systems model of a satellite formation with possible actuator faults as a motivating example for developing an automated control synthesis method for non-deterministic piecewise-affine hybrid systems (PAHS). The method does not only open an avenue for further research...... in fault tolerant satellite formation control, but can be used to synthesise controllers for a wide range of systems where external events can alter the system dynamics. The synthesis method relies on abstracting the hybrid system into a discrete game, finding a winning strategy for the game meeting...... game and linear optimisation solvers for controller refinement. To illustrate the efficacy of the method a reoccurring satellite formation example including actuator faults has been used. The end result is the application of PAHSCTRL on the example showing synthesis and simulation of a fault tolerant...

The development of the deterministic nonlinear PDEs in particle physics to stochastic case

Science.gov (United States)

Abdelrahman, Mahmoud A. E.; Sohaly, M. A.

2018-06-01

In the present work, accuracy method called, Riccati-Bernoulli Sub-ODE technique is used for solving the deterministic and stochastic case of the Phi-4 equation and the nonlinear Foam Drainage equation. Also, the control on the randomness input is studied for stability stochastic process solution.

Improving Deterministic Reserve Requirements for Security Constrained Unit Commitment and Scheduling Problems in Power Systems

Science.gov (United States)

Wang, Fengyu

Traditional deterministic reserve requirements rely on ad-hoc, rule of thumb methods to determine adequate reserve in order to ensure a reliable unit commitment. Since congestion and uncertainties exist in the system, both the quantity and the location of reserves are essential to ensure system reliability and market efficiency. The modeling of operating reserves in the existing deterministic reserve requirements acquire the operating reserves on a zonal basis and do not fully capture the impact of congestion. The purpose of a reserve zone is to ensure that operating reserves are spread across the network. Operating reserves are shared inside each reserve zone, but intra-zonal congestion may block the deliverability of operating reserves within a zone. Thus, improving reserve policies such as reserve zones may improve the location and deliverability of reserve. As more non-dispatchable renewable resources are integrated into the grid, it will become increasingly difficult to predict the transfer capabilities and the network congestion. At the same time, renewable resources require operators to acquire more operating reserves. With existing deterministic reserve requirements unable to ensure optimal reserve locations, the importance of reserve location and reserve deliverability will increase. While stochastic programming can be used to determine reserve by explicitly modelling uncertainties, there are still scalability as well as pricing issues. Therefore, new methods to improve existing deterministic reserve requirements are desired. One key barrier of improving existing deterministic reserve requirements is its potential market impacts. A metric, quality of service, is proposed in this thesis to evaluate the price signal and market impacts of proposed hourly reserve zones. Three main goals of this thesis are: 1) to develop a theoretical and mathematical model to better locate reserve while maintaining the deterministic unit commitment and economic dispatch

The Relation between Deterministic Thinking and Mental Health among Substance Abusers Involved in a Rehabilitation Program

Directory of Open Access Journals (Sweden)

Seyed Jalal Younesi

2015-06-01

Full Text Available Objective: The current research is to investigate the relation between deterministic thinking and mental health among drug abusers, in which the role of  cognitive distortions is considered and clarified by focusing on deterministic thinking. Methods: The present study is descriptive and correlative. All individuals with experience of drug abuse who had been referred to the Shafagh Rehabilitation center (Kahrizak were considered as the statistical population. 110 individuals who were addicted to drugs (stimulants and Methamphetamine were selected from this population by purposeful sampling to answer questionnaires about deterministic thinking and general health. For data analysis Pearson coefficient correlation and regression analysis was used. Results: The results showed that there is a positive and significant relationship between deterministic thinking and the lack of mental health at the statistical level [r=%22, P<0.05], which had the closest relation to deterministic thinking among the factors of mental health, such as anxiety and depression. It was found that the two factors of deterministic thinking which function as the strongest variables that predict the lack of mental health are: definitiveness in predicting tragic events and future anticipation. Discussion: It seems that drug abusers suffer from deterministic thinking when they are confronted with difficult situations, so they are more affected by depression and anxiety. This way of thinking may play a major role in impelling or restraining drug addiction.

Deterministic Approach to Detect Heart Sound Irregularities

Directory of Open Access Journals (Sweden)

Richard Mengko

2017-07-01

Full Text Available A new method to detect heart sound that does not require machine learning is proposed. The heart sound is a time series event which is generated by the heart mechanical system. From the analysis of heart sound S-transform and the understanding of how heart works, it can be deducted that each heart sound component has unique properties in terms of timing, frequency, and amplitude. Based on these facts, a deterministic method can be designed to identify each heart sound components. The recorded heart sound then can be printed with each component correctly labeled. This greatly help the physician to diagnose the heart problem. The result shows that most known heart sounds were successfully detected. There are some murmur cases where the detection failed. This can be improved by adding more heuristics including setting some initial parameters such as noise threshold accurately, taking into account the recording equipment and also the environmental condition. It is expected that this method can be integrated into an electronic stethoscope biomedical system.

A novel reliability evaluation method for large engineering systems

Directory of Open Access Journals (Sweden)

Reda Farag

2016-06-01

Full Text Available A novel reliability evaluation method for large nonlinear engineering systems excited by dynamic loading applied in time domain is presented. For this class of problems, the performance functions are expected to be function of time and implicit in nature. Available first- or second-order reliability method (FORM/SORM will be challenging to estimate reliability of such systems. Because of its inefficiency, the classical Monte Carlo simulation (MCS method also cannot be used for large nonlinear dynamic systems. In the proposed approach, only tens instead of hundreds or thousands of deterministic evaluations at intelligently selected points are used to extract the reliability information. A hybrid approach, consisting of the stochastic finite element method (SFEM developed by the author and his research team using FORM, response surface method (RSM, an interpolation scheme, and advanced factorial schemes, is proposed. The method is clarified with the help of several numerical examples.

Three-dimensional protein structure prediction: Methods and computational strategies.

Science.gov (United States)

Dorn, Márcio; E Silva, Mariel Barbachan; Buriol, Luciana S; Lamb, Luis C

2014-10-12

A long standing problem in structural bioinformatics is to determine the three-dimensional (3-D) structure of a protein when only a sequence of amino acid residues is given. Many computational methodologies and algorithms have been proposed as a solution to the 3-D Protein Structure Prediction (3-D-PSP) problem. These methods can be divided in four main classes: (a) first principle methods without database information; (b) first principle methods with database information; (c) fold recognition and threading methods; and (d) comparative modeling methods and sequence alignment strategies. Deterministic computational techniques, optimization techniques, data mining and machine learning approaches are typically used in the construction of computational solutions for the PSP problem. Our main goal with this work is to review the methods and computational strategies that are currently used in 3-D protein prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.

Safety margins in deterministic safety analysis

International Nuclear Information System (INIS)

Viktorov, A.

2011-01-01

The concept of safety margins has acquired certain prominence in the attempts to demonstrate quantitatively the level of the nuclear power plant safety by means of deterministic analysis, especially when considering impacts from plant ageing and discovery issues. A number of international or industry publications exist that discuss various applications and interpretations of safety margins. The objective of this presentation is to bring together and examine in some detail, from the regulatory point of view, the safety margins that relate to deterministic safety analysis. In this paper, definitions of various safety margins are presented and discussed along with the regulatory expectations for them. Interrelationships of analysis input and output parameters with corresponding limits are explored. It is shown that the overall safety margin is composed of several components each having different origins and potential uses; in particular, margins associated with analysis output parameters are contrasted with margins linked to the analysis input. While these are separate, it is possible to influence output margins through the analysis input, and analysis method. Preserving safety margins is tantamount to maintaining safety. At the same time, efficiency of operation requires optimization of safety margins taking into account various technical and regulatory considerations. For this, basic definitions and rules for safety margins must be first established. (author)

Pseudo-deterministic Algorithms

OpenAIRE

Goldwasser , Shafi

2012-01-01

International audience; In this talk we describe a new type of probabilistic algorithm which we call Bellagio Algorithms: a randomized algorithm which is guaranteed to run in expected polynomial time, and to produce a correct and unique solution with high probability. These algorithms are pseudo-deterministic: they can not be distinguished from deterministic algorithms in polynomial time by a probabilistic polynomial time observer with black box access to the algorithm. We show a necessary an...

Analysis of natural circulation BWR dynamics with stochastic and deterministic methods

International Nuclear Information System (INIS)

VanderHagen, T.H.; Van Dam, H.; Hoogenboom, J.E.; Kleiss, E.B.J.; Nissen, W.H.M.; Oosterkamp, W.J.

1986-01-01

Reactor kinetic, thermal hydraulic and total plant stability of a natural convection cooled BWR was studied using noise analysis and by evaluation of process responses to control rod steps and to steamflow control valve steps. An estimate of the fuel thermal time constant and an impression of the recirculation flow response to power variations was obtained. A sophisticated noise analysis method resulted in more insight into the fluctuations of the coolant velocity

Deterministic methods for the relativistic Vlasov-Maxwell equations and the Van Allen belts dynamics

International Nuclear Information System (INIS)

Le Bourdiec, S.

2007-03-01

Artificial satellites operate in an hostile radiation environment, the Van Allen radiation belts, which partly condition their reliability and their lifespan. In order to protect them, it is necessary to characterize the dynamics of the energetic electrons trapped in these radiation belts. This dynamics is essentially determined by the interactions between the energetic electrons and the existing electromagnetic waves. This work consisted in designing a numerical scheme to solve the equations modelling these interactions: the relativistic Vlasov-Maxwell system of equations. Our choice was directed towards methods of direct integration. We propose three new spectral methods for the momentum discretization: a Galerkin method and two collocation methods. All of them are based on scaled Hermite functions. The scaling factor is chosen in order to obtain the proper velocity resolution. We present in this thesis the discretization of the one-dimensional Vlasov-Poisson system and the numerical results obtained. Then we study the possible extensions of the methods to the complete relativistic problem. In order to reduce the computing time, parallelization and optimization of the algorithms were carried out. Finally, we present 1Dx-3Dv (mono-dimensional for x and three-dimensional for velocity) computations of Weibel and whistler instabilities with one or two electrons species. (author)

The deterministic optical alignment of the HERMES spectrograph

Science.gov (United States)

Gers, Luke; Staszak, Nicholas

2014-07-01

The High Efficiency and Resolution Multi Element Spectrograph (HERMES) is a four channel, VPH-grating spectrograph fed by two 400 fiber slit assemblies whose construction and commissioning has now been completed at the Anglo Australian Telescope (AAT). The size, weight, complexity, and scheduling constraints of the system necessitated that a fully integrated, deterministic, opto-mechanical alignment system be designed into the spectrograph before it was manufactured. This paper presents the principles about which the system was assembled and aligned, including the equipment and the metrology methods employed to complete the spectrograph integration.

An adaptive multi-element probabilistic collocation method for statistical EMC/EMI characterization

KAUST Repository

Yücel, Abdulkadir C.

2013-12-01

An adaptive multi-element probabilistic collocation (ME-PC) method for quantifying uncertainties in electromagnetic compatibility and interference phenomena involving electrically large, multi-scale, and complex platforms is presented. The method permits the efficient and accurate statistical characterization of observables (i.e., quantities of interest such as coupled voltages) that potentially vary rapidly and/or are discontinuous in the random variables (i.e., parameters that characterize uncertainty in a system\\'s geometry, configuration, or excitation). The method achieves its efficiency and accuracy by recursively and adaptively dividing the domain of the random variables into subdomains using as a guide the decay rate of relative error in a polynomial chaos expansion of the observables. While constructing local polynomial expansions on each subdomain, a fast integral-equation-based deterministic field-cable-circuit simulator is used to compute the observable values at the collocation/integration points determined by the adaptive ME-PC scheme. The adaptive ME-PC scheme requires far fewer (computationally costly) deterministic simulations than traditional polynomial chaos collocation and Monte Carlo methods for computing averages, standard deviations, and probability density functions of rapidly varying observables. The efficiency and accuracy of the method are demonstrated via its applications to the statistical characterization of voltages in shielded/unshielded microwave amplifiers and magnetic fields induced on car tire pressure sensors. © 2013 IEEE.

Research on reactor physics analysis method based on Monte Carlo homogenization

International Nuclear Information System (INIS)

Ye Zhimin; Zhang Peng

2014-01-01

In order to meet the demand of nuclear energy market in the future, many new concepts of nuclear energy systems has been put forward. The traditional deterministic neutronics analysis method has been challenged in two aspects: one is the ability of generic geometry processing; the other is the multi-spectrum applicability of the multigroup cross section libraries. Due to its strong geometry modeling capability and the application of continuous energy cross section libraries, the Monte Carlo method has been widely used in reactor physics calculations, and more and more researches on Monte Carlo method has been carried out. Neutronics-thermal hydraulics coupling analysis based on Monte Carlo method has been realized. However, it still faces the problems of long computation time and slow convergence which make it not applicable to the reactor core fuel management simulations. Drawn from the deterministic core analysis method, a new two-step core analysis scheme is proposed in this work. Firstly, Monte Carlo simulations are performed for assembly, and the assembly homogenized multi-group cross sections are tallied at the same time. Secondly, the core diffusion calculations can be done with these multigroup cross sections. The new scheme can achieve high efficiency while maintain acceptable precision, so it can be used as an effective tool for the design and analysis of innovative nuclear energy systems. Numeric tests have been done in this work to verify the new scheme. (authors)

Calculating complete and exact Pareto front for multiobjective optimization: a new deterministic approach for discrete problems.

Science.gov (United States)

Hu, Xiao-Bing; Wang, Ming; Di Paolo, Ezequiel

2013-06-01

Searching the Pareto front for multiobjective optimization problems usually involves the use of a population-based search algorithm or of a deterministic method with a set of different single aggregate objective functions. The results are, in fact, only approximations of the real Pareto front. In this paper, we propose a new deterministic approach capable of fully determining the real Pareto front for those discrete problems for which it is possible to construct optimization algorithms to find the k best solutions to each of the single-objective problems. To this end, two theoretical conditions are given to guarantee the finding of the actual Pareto front rather than its approximation. Then, a general methodology for designing a deterministic search procedure is proposed. A case study is conducted, where by following the general methodology, a ripple-spreading algorithm is designed to calculate the complete exact Pareto front for multiobjective route optimization. When compared with traditional Pareto front search methods, the obvious advantage of the proposed approach is its unique capability of finding the complete Pareto front. This is illustrated by the simulation results in terms of both solution quality and computational efficiency.

Geant4-related R&D for new particle transport methods

CERN Document Server

Augelli, M; Evans, T; Gargioni, E; Hauf, S; Kim, C H; Kuster, M; Pia, M G; Filho, P Queiroz; Quintieri, L; Saracco, P; Santos, D Souza; Weidenspointner, G; Zoglauer, A

2009-01-01

A R&D project has been launched in 2009 to address fundamental methods in radiation transport simulation and revisit Geant4 kernel design to cope with new experimental requirements. The project focuses on simulation at different scales in the same experimental environment: this set of problems requires new methods across the current boundaries of condensed-random-walk and discrete transport schemes. An exploration is also foreseen about exploiting and extending already existing Geant4 features to apply Monte Carlo and deterministic transport methods in the same simulation environment. An overview of this new R&D associated with Geant4 is presented, together with the first developments in progress.

A simplified method for random vibration analysis of structures with random parameters

International Nuclear Information System (INIS)

Ghienne, Martin; Blanzé, Claude

2016-01-01

Piezoelectric patches with adapted electrical circuits or viscoelastic dissipative materials are two solutions particularly adapted to reduce vibration of light structures. To accurately design these solutions, it is necessary to describe precisely the dynamical behaviour of the structure. It may quickly become computationally intensive to describe robustly this behaviour for a structure with nonlinear phenomena, such as contact or friction for bolted structures, and uncertain variations of its parameters. The aim of this work is to propose a non-intrusive reduced stochastic method to characterize robustly the vibrational response of a structure with random parameters. Our goal is to characterize the eigenspace of linear systems with dynamic properties considered as random variables. This method is based on a separation of random aspects from deterministic aspects and allows us to estimate the first central moments of each random eigenfrequency with a single deterministic finite elements computation. The method is applied to a frame with several Young's moduli modeled as random variables. This example could be expanded to a bolted structure including piezoelectric devices. The method needs to be enhanced when random eigenvalues are closely spaced. An indicator with no additional computational cost is proposed to characterize the ’’proximity” of two random eigenvalues. (paper)

Medical Data Probabilistic Analysis by Optical Computing Methods

Directory of Open Access Journals (Sweden)

Alexander LARKIN

2014-06-01

Full Text Available The purpose of this article to show the laser coherent photonics methods can be use for classification of medical information. It is shown that the holography methods can be used not only for work with images. Holographic methods can be used for processing of information provided in the universal multi-parametric form. It is shown that along with the usual correlation algorithm enable to realize a number of algorithms of classification: searching for a precedent, Hamming distance measurement, Bayes probability algorithm, deterministic and “correspondence” algorithms. Significantly, that preserves all advantages of holographic method – speed, two-dimension, record-breaking high capacity of memory, flexibility of data processing and representation of result, high radiation resistance in comparison with electronic equipment. For example is presented the result of solving one of the problems of medical diagnostics - a forecast of organism state after mass traumatic lesions.

Stochastic seismic floor response analysis method for various damping systems

International Nuclear Information System (INIS)

Kitada, Y.; Hattori, K.; Ogata, M.; Kanda, J.

1991-01-01

A study using the stochastic seismic response analysis method which is applicable for the estimation of floor response spectra is carried out. It is pointed out as a shortcoming in this stochastic seismic response analysis method, that the method tends to overestimate floor response spectra for low damping systems, e.g. 1% of the critical damping ratio. An investigation on the cause of the shortcoming is carried out and a number of improvements in this method were also made to the original method by taking correlation of successive peaks in a response time history into account. The application of the improved method to a typical BWR reactor building is carried out. The resultant floor response spectra are compared with those obtained by deterministic time history analysis. Floor response spectra estimated by the improved method consistently cover the response spectra obtained by the time history analysis for various damping ratios. (orig.)

SU-E-T-577: Commissioning of a Deterministic Algorithm for External Photon Beams

International Nuclear Information System (INIS)

Zhu, T; Finlay, J; Mesina, C; Liu, H

2014-01-01

Purpose: We report commissioning results for a deterministic algorithm for external photon beam treatment planning. A deterministic algorithm solves the radiation transport equations directly using a finite difference method, thus improve the accuracy of dose calculation, particularly under heterogeneous conditions with results similar to that of Monte Carlo (MC) simulation. Methods: Commissioning data for photon energies 6 – 15 MV includes the percentage depth dose (PDD) measured at SSD = 90 cm and output ratio in water (Spc), both normalized to 10 cm depth, for field sizes between 2 and 40 cm and depths between 0 and 40 cm. Off-axis ratio (OAR) for the same set of field sizes was used at 5 depths (dmax, 5, 10, 20, 30 cm). The final model was compared with the commissioning data as well as additional benchmark data. The benchmark data includes dose per MU determined for 17 points for SSD between 80 and 110 cm, depth between 5 and 20 cm, and lateral offset of up to 16.5 cm. Relative comparisons were made in a heterogeneous phantom made of cork and solid water. Results: Compared to the commissioning beam data, the agreement are generally better than 2% with large errors (up to 13%) observed in the buildup regions of the FDD and penumbra regions of the OAR profiles. The overall mean standard deviation is 0.04% when all data are taken into account. Compared to the benchmark data, the agreements are generally better than 2%. Relative comparison in heterogeneous phantom is in general better than 4%. Conclusion: A commercial deterministic algorithm was commissioned for megavoltage photon beams. In a homogeneous medium, the agreement between the algorithm and measurement at the benchmark points is generally better than 2%. The dose accuracy for a deterministic algorithm is better than a convolution algorithm in heterogeneous medium

Application of Deterministic and Probabilistic System Design Methods and Enhancements of Conceptual Design Tools for ERA Project

Science.gov (United States)

Mavris, Dimitri N.; Schutte, Jeff S.

2016-01-01

This report documents work done by the Aerospace Systems Design Lab (ASDL) at the Georgia Institute of Technology, Daniel Guggenheim School of Aerospace Engineering for the National Aeronautics and Space Administration, Aeronautics Research Mission Directorate, Integrated System Research Program, Environmentally Responsible Aviation (ERA) Project. This report was prepared under contract NNL12AA12C, "Application of Deterministic and Probabilistic System Design Methods and Enhancement of Conceptual Design Tools for ERA Project". The research within this report addressed the Environmentally Responsible Aviation (ERA) project goal stated in the NRA solicitation "to advance vehicle concepts and technologies that can simultaneously reduce fuel burn, noise, and emissions." To identify technology and vehicle solutions that simultaneously meet these three metrics requires the use of system-level analysis with the appropriate level of fidelity to quantify feasibility, benefits and degradations, and associated risk. In order to perform the system level analysis, the Environmental Design Space (EDS) [Kirby 2008, Schutte 2012a] environment developed by ASDL was used to model both conventional and unconventional configurations as well as to assess technologies from the ERA and N+2 timeframe portfolios. A well-established system design approach was used to perform aircraft conceptual design studies, including technology trade studies to identify technology portfolios capable of accomplishing the ERA project goal and to obtain accurate tradeoffs between performance, noise, and emissions. The ERA goal, shown in Figure 1, is to simultaneously achieve the N+2 benefits of a cumulative noise margin of 42 EPNdB relative to stage 4, a 75 percent reduction in LTO NOx emissions relative to CAEP 6 and a 50 percent reduction in fuel burn relative to the 2005 best in class aircraft. There were 5 research task associated with this research: 1) identify technology collectors, 2) model

Comparison study on cell calculation method of fast reactor

International Nuclear Information System (INIS)

Chiba, Gou

2002-10-01

Effective cross sections obtained by cell calculations are used in core calculations in current deterministic methods. Therefore, it is important to calculate the effective cross sections accurately and several methods have been proposed. In this study, some of the methods are compared to each other using a continuous energy Monte Carlo method as a reference. The result shows that the table look-up method used in Japan Nuclear Cycle Development Institute (JNC) sometimes has a difference over 10% in effective microscopic cross sections and be inferior to the sub-group method. The problem was overcome by introducing a new nuclear constant system developed in JNC, in which the ultra free energy group library is used. The system can also deal with resonance interaction effects between nuclides which are not able to be considered by other methods. In addition, a new method was proposed to calculate effective cross section accurately for power reactor fuel subassembly where the new nuclear constant system cannot be applied. This method uses the sub-group method and the ultra fine energy group collision probability method. The microscopic effective cross sections obtained by this method agree with the reference values within 5% difference. (author)

Deterministic calculation of the effective delayed neutron fraction without using the adjoint neutron flux - 299

International Nuclear Information System (INIS)

Talamo, A.; Gohar, Y.; Aliberti, G.; Zhong, Z.; Bournos, V.; Fokov, Y.; Kiyavitskaya, H.; Routkovskaya, C.; Serafimovich, I.

2010-01-01

In 1997, Bretscher calculated the effective delayed neutron fraction by the k-ratio method. The Bretscher's approach is based on calculating the multiplication factor of a nuclear reactor core with and without the contribution of delayed neutrons. The multiplication factor set by the delayed neutrons (the delayed multiplication factor) is obtained as the difference between the total and the prompt multiplication factors. Bretscher evaluated the effective delayed neutron fraction as the ratio between the delayed and total multiplication factors (therefore the method is often referred to as k-ratio method). In the present work, the k-ratio method is applied by deterministic nuclear codes. The ENDF/B nuclear data library of the fuel isotopes ( 238 U and 238 U) have been processed by the NJOY code with and without the delayed neutron data to prepare multigroup WIMSD nuclear data libraries for the DRAGON code. The DRAGON code has been used for preparing the PARTISN macroscopic cross sections. This calculation methodology has been applied to the YALINA-Thermal assembly of Belarus. The assembly has been modeled and analyzed using PARTISN code with 69 energy groups and 60 different material zones. The deterministic and Monte Carlo results for the effective delayed neutron fraction obtained by the k-ratio method agree very well. The results also agree with the values obtained by using the adjoint flux. (authors)

The concerted calculation of the BN-600 reactor for the deterministic and stochastic codes

Science.gov (United States)

Bogdanova, E. V.; Kuznetsov, A. N.

2017-01-01

The solution of the problem of increasing the safety of nuclear power plants implies the existence of complete and reliable information about the processes occurring in the core of a working reactor. Nowadays the Monte-Carlo method is the most general-purpose method used to calculate the neutron-physical characteristic of the reactor. But it is characterized by large time of calculation. Therefore, it may be useful to carry out coupled calculations with stochastic and deterministic codes. This article presents the results of research for possibility of combining stochastic and deterministic algorithms in calculation the reactor BN-600. This is only one part of the work, which was carried out in the framework of the graduation project at the NRC “Kurchatov Institute” in cooperation with S. S. Gorodkov and M. A. Kalugin. It is considering the 2-D layer of the BN-600 reactor core from the international benchmark test, published in the report IAEA-TECDOC-1623. Calculations of the reactor were performed with MCU code and then with a standard operative diffusion algorithm with constants taken from the Monte - Carlo computation. Macro cross-section, diffusion coefficients, the effective multiplication factor and the distribution of neutron flux and power were obtained in 15 energy groups. The reasonable agreement between stochastic and deterministic calculations of the BN-600 is observed.

Deterministic sensitivity analysis for the numerical simulation of contaminants transport; Analyse de sensibilite deterministe pour la simulation numerique du transfert de contaminants

Energy Technology Data Exchange (ETDEWEB)

Marchand, E

2007-12-15

The questions of safety and uncertainty are central to feasibility studies for an underground nuclear waste storage site, in particular the evaluation of uncertainties about safety indicators which are due to uncertainties concerning properties of the subsoil or of the contaminants. The global approach through probabilistic Monte Carlo methods gives good results, but it requires a large number of simulations. The deterministic method investigated here is complementary. Based on the Singular Value Decomposition of the derivative of the model, it gives only local information, but it is much less demanding in computing time. The flow model follows Darcy's law and the transport of radionuclides around the storage site follows a linear convection-diffusion equation. Manual and automatic differentiation are compared for these models using direct and adjoint modes. A comparative study of both probabilistic and deterministic approaches for the sensitivity analysis of fluxes of contaminants through outlet channels with respect to variations of input parameters is carried out with realistic data provided by ANDRA. Generic tools for sensitivity analysis and code coupling are developed in the Caml language. The user of these generic platforms has only to provide the specific part of the application in any language of his choice. We also present a study about two-phase air/water partially saturated flows in hydrogeology concerning the limitations of the Richards approximation and of the global pressure formulation used in petroleum engineering. (author)

Deterministic models for energy-loss straggling

International Nuclear Information System (INIS)

Prinja, A.K.; Gleicher, F.; Dunham, G.; Morel, J.E.

1999-01-01

Inelastic ion interactions with target electrons are dominated by extremely small energy transfers that are difficult to resolve numerically. The continuous-slowing-down (CSD) approximation is then commonly employed, which, however, only preserves the mean energy loss per collision through the stopping power, S(E) = ∫ 0 ∞ dEprime (E minus Eprime) σ s (E → Eprime). To accommodate energy loss straggling, a Gaussian distribution with the correct mean-squared energy loss (akin to a Fokker-Planck approximation in energy) is commonly used in continuous-energy Monte Carlo codes. Although this model has the unphysical feature that ions can be upscattered, it nevertheless yields accurate results. A multigroup model for energy loss straggling was recently presented for use in multigroup Monte Carlo codes or in deterministic codes that use multigroup data. The method has the advantage that the mean and mean-squared energy loss are preserved without unphysical upscatter and hence is computationally efficient. Results for energy spectra compared extremely well with Gaussian distributions under the idealized conditions for which the Gaussian may be considered to be exact. Here, the authors present more consistent comparisons by extending the method to accommodate upscatter and, further, compare both methods with exact solutions obtained from an analog Monte Carlo simulation, for a straight-ahead transport problem

Quantitative Methods in Supply Chain Management Models and Algorithms

CERN Document Server

Christou, Ioannis T

2012-01-01

Quantitative Methods in Supply Chain Management presents some of the most important methods and tools available for modeling and solving problems arising in the context of supply chain management. In the context of this book, “solving problems” usually means designing efficient algorithms for obtaining high-quality solutions. The first chapter is an extensive optimization review covering continuous unconstrained and constrained linear and nonlinear optimization algorithms, as well as dynamic programming and discrete optimization exact methods and heuristics. The second chapter presents time-series forecasting methods together with prediction market techniques for demand forecasting of new products and services. The third chapter details models and algorithms for planning and scheduling with an emphasis on production planning and personnel scheduling. The fourth chapter presents deterministic and stochastic models for inventory control with a detailed analysis on periodic review systems and algorithmic dev...

Hydraulic tomography of discrete networks of conduits and fractures in a karstic aquifer by using a deterministic inversion algorithm

Science.gov (United States)

Fischer, P.; Jardani, A.; Lecoq, N.

2018-02-01

In this paper, we present a novel inverse modeling method called Discrete Network Deterministic Inversion (DNDI) for mapping the geometry and property of the discrete network of conduits and fractures in the karstified aquifers. The DNDI algorithm is based on a coupled discrete-continuum concept to simulate numerically water flows in a model and a deterministic optimization algorithm to invert a set of observed piezometric data recorded during multiple pumping tests. In this method, the model is partioned in subspaces piloted by a set of parameters (matrix transmissivity, and geometry and equivalent transmissivity of the conduits) that are considered as unknown. In this way, the deterministic optimization process can iteratively correct the geometry of the network and the values of the properties, until it converges to a global network geometry in a solution model able to reproduce the set of data. An uncertainty analysis of this result can be performed from the maps of posterior uncertainties on the network geometry or on the property values. This method has been successfully tested for three different theoretical and simplified study cases with hydraulic responses data generated from hypothetical karstic models with an increasing complexity of the network geometry, and of the matrix heterogeneity.

Continuous energy Monte Carlo method based lattice homogeinzation

International Nuclear Information System (INIS)

Li Mancang; Yao Dong; Wang Kan

2014-01-01

Based on the Monte Carlo code MCNP, the continuous energy Monte Carlo multi-group constants generation code MCMC has been developed. The track length scheme has been used as the foundation of cross section generation. The scattering matrix and Legendre components require special techniques, and the scattering event method has been proposed to solve this problem. Three methods have been developed to calculate the diffusion coefficients for diffusion reactor core codes and the Legendre method has been applied in MCMC. To the satisfaction of the equivalence theory, the general equivalence theory (GET) and the superhomogenization method (SPH) have been applied to the Monte Carlo method based group constants. The super equivalence method (SPE) has been proposed to improve the equivalence. GET, SPH and SPE have been implemented into MCMC. The numerical results showed that generating the homogenization multi-group constants via Monte Carlo method overcomes the difficulties in geometry and treats energy in continuum, thus provides more accuracy parameters. Besides, the same code and data library can be used for a wide range of applications due to the versatility. The MCMC scheme can be seen as a potential alternative to the widely used deterministic lattice codes. (authors)

Monte Carlo burnup codes acceleration using the correlated sampling method

International Nuclear Information System (INIS)

Dieudonne, C.

2013-01-01

For several years, Monte Carlo burnup/depletion codes have appeared, which couple Monte Carlo codes to simulate the neutron transport to deterministic methods, which handle the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3-dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the Monte Carlo solver called at each time step. In this document we present an original methodology to avoid the repetitive and time-expensive Monte Carlo simulations, and to replace them by perturbation calculations: indeed the different burnup steps may be seen as perturbations of the isotopic concentration of an initial Monte Carlo simulation. In a first time we will present this method, and provide details on the perturbative technique used, namely the correlated sampling. In a second time we develop a theoretical model to study the features of the correlated sampling method to understand its effects on depletion calculations. In a third time the implementation of this method in the TRIPOLI-4 code will be discussed, as well as the precise calculation scheme used to bring important speed-up of the depletion calculation. We will begin to validate and optimize the perturbed depletion scheme with the calculation of a REP-like fuel cell depletion. Then this technique will be used to calculate the depletion of a REP-like assembly, studied at beginning of its cycle. After having validated the method with a reference calculation we will show that it can speed-up by nearly an order of magnitude standard Monte-Carlo depletion codes. (author) [fr

A robust and efficient stepwise regression method for building sparse polynomial chaos expansions

Energy Technology Data Exchange (ETDEWEB)

Abraham, Simon, E-mail: Simon.Abraham@ulb.ac.be [Vrije Universiteit Brussel (VUB), Department of Mechanical Engineering, Research Group Fluid Mechanics and Thermodynamics, Pleinlaan 2, 1050 Brussels (Belgium); Raisee, Mehrdad [School of Mechanical Engineering, College of Engineering, University of Tehran, P.O. Box: 11155-4563, Tehran (Iran, Islamic Republic of); Ghorbaniasl, Ghader; Contino, Francesco; Lacor, Chris [Vrije Universiteit Brussel (VUB), Department of Mechanical Engineering, Research Group Fluid Mechanics and Thermodynamics, Pleinlaan 2, 1050 Brussels (Belgium)

2017-03-01

Polynomial Chaos (PC) expansions are widely used in various engineering fields for quantifying uncertainties arising from uncertain parameters. The computational cost of classical PC solution schemes is unaffordable as the number of deterministic simulations to be calculated grows dramatically with the number of stochastic dimension. This considerably restricts the practical use of PC at the industrial level. A common approach to address such problems is to make use of sparse PC expansions. This paper presents a non-intrusive regression-based method for building sparse PC expansions. The most important PC contributions are detected sequentially through an automatic search procedure. The variable selection criterion is based on efficient tools relevant to probabilistic method. Two benchmark analytical functions are used to validate the proposed algorithm. The computational efficiency of the method is then illustrated by a more realistic CFD application, consisting of the non-deterministic flow around a transonic airfoil subject to geometrical uncertainties. To assess the performance of the developed methodology, a detailed comparison is made with the well established LAR-based selection technique. The results show that the developed sparse regression technique is able to identify the most significant PC contributions describing the problem. Moreover, the most important stochastic features are captured at a reduced computational cost compared to the LAR method. The results also demonstrate the superior robustness of the method by repeating the analyses using random experimental designs.

Performance Analysis of Combined Methods of Genetic Algorithm and K-Means Clustering in Determining the Value of Centroid

Science.gov (United States)

Adya Zizwan, Putra; Zarlis, Muhammad; Budhiarti Nababan, Erna

2017-12-01

The determination of Centroid on K-Means Algorithm directly affects the quality of the clustering results. Determination of centroid by using random numbers has many weaknesses. The GenClust algorithm that combines the use of Genetic Algorithms and K-Means uses a genetic algorithm to determine the centroid of each cluster. The use of the GenClust algorithm uses 50% chromosomes obtained through deterministic calculations and 50% is obtained from the generation of random numbers. This study will modify the use of the GenClust algorithm in which the chromosomes used are 100% obtained through deterministic calculations. The results of this study resulted in performance comparisons expressed in Mean Square Error influenced by centroid determination on K-Means method by using GenClust method, modified GenClust method and also classic K-Means.

Statistics of Monte Carlo methods used in radiation transport calculation

International Nuclear Information System (INIS)

Datta, D.

2009-01-01

Radiation transport calculation can be carried out by using either deterministic or statistical methods. Radiation transport calculation based on statistical methods is basic theme of the Monte Carlo methods. The aim of this lecture is to describe the fundamental statistics required to build the foundations of Monte Carlo technique for radiation transport calculation. Lecture note is organized in the following way. Section (1) will describe the introduction of Basic Monte Carlo and its classification towards the respective field. Section (2) will describe the random sampling methods, a key component of Monte Carlo radiation transport calculation, Section (3) will provide the statistical uncertainty of Monte Carlo estimates, Section (4) will describe in brief the importance of variance reduction techniques while sampling particles such as photon, or neutron in the process of radiation transport

The Role of Probabilistic Design Analysis Methods in Safety and Affordability

Science.gov (United States)

Safie, Fayssal M.

2016-01-01

For the last several years, NASA and its contractors have been working together to build space launch systems to commercialize space. Developing commercial affordable and safe launch systems becomes very important and requires a paradigm shift. This paradigm shift enforces the need for an integrated systems engineering environment where cost, safety, reliability, and performance need to be considered to optimize the launch system design. In such an environment, rule based and deterministic engineering design practices alone may not be sufficient to optimize margins and fault tolerance to reduce cost. As a result, introduction of Probabilistic Design Analysis (PDA) methods to support the current deterministic engineering design practices becomes a necessity to reduce cost without compromising reliability and safety. This paper discusses the importance of PDA methods in NASA's new commercial environment, their applications, and the key role they can play in designing reliable, safe, and affordable launch systems. More specifically, this paper discusses: 1) The involvement of NASA in PDA 2) Why PDA is needed 3) A PDA model structure 4) A PDA example application 5) PDA link to safety and affordability.

Deterministic simulation of first-order scattering in virtual X-ray imaging

Energy Technology Data Exchange (ETDEWEB)

Freud, N. E-mail: nicolas.freud@insa-lyon.fr; Duvauchelle, P.; Pistrui-Maximean, S.A.; Letang, J.-M.; Babot, D

2004-07-01

A deterministic algorithm is proposed to compute the contribution of first-order Compton- and Rayleigh-scattered radiation in X-ray imaging. This algorithm has been implemented in a simulation code named virtual X-ray imaging. The physical models chosen to account for photon scattering are the well-known form factor and incoherent scattering function approximations, which are recalled in this paper and whose limits of validity are briefly discussed. The proposed algorithm, based on a voxel discretization of the inspected object, is presented in detail, as well as its results in simple configurations, which are shown to converge when the sampling steps are chosen sufficiently small. Simple criteria for choosing correct sampling steps (voxel and pixel size) are established. The order of magnitude of the computation time necessary to simulate first-order scattering images amounts to hours with a PC architecture and can even be decreased down to minutes, if only a profile is computed (along a linear detector). Finally, the results obtained with the proposed algorithm are compared to the ones given by the Monte Carlo code Geant4 and found to be in excellent accordance, which constitutes a validation of our algorithm. The advantages and drawbacks of the proposed deterministic method versus the Monte Carlo method are briefly discussed.

A Solution Method for Linear and Geometrically Nonlinear MDOF Systems with Random Properties subject to Random Excitation

DEFF Research Database (Denmark)

Micaletti, R. C.; Cakmak, A. S.; Nielsen, Søren R. K.

structural properties. The resulting state-space formulation is a system of ordinary stochastic differential equations with random coefficient and deterministic initial conditions which are subsequently transformed into ordinary stochastic differential equations with deterministic coefficients and random......A method for computing the lower-order moments of randomly-excited multi-degree-of-freedom (MDOF) systems with random structural properties is proposed. The method is grounded in the techniques of stochastic calculus, utilizing a Markov diffusion process to model the structural system with random...... initial conditions. This transformation facilitates the derivation of differential equations which govern the evolution of the unconditional statistical moments of response. Primary consideration is given to linear systems and systems with odd polynomial nonlinearities, for in these cases...

A methodological framework applied to the choice of the best method in replacement of nuclear systems

International Nuclear Information System (INIS)

Vianna Filho, Alfredo Marques

2009-01-01

The economic equipment replacement problem is a central question in Nuclear Engineering. On the one hand, new equipment are more attractive given their best performance, better reliability, lower maintenance cost etc. New equipment, however, require a higher initial investment. On the other hand, old equipment represent the other way around, with lower performance, lower reliability and specially higher maintenance costs, but in contrast having lower financial and insurance costs. The weighting of all these costs can be made with deterministic and probabilistic methods applied to the study of equipment replacement. Two types of distinct problems will be examined, substitution imposed by the wearing and substitution imposed by the failures. In order to solve the problem of nuclear system substitution imposed by wearing, deterministic methods are discussed. In order to solve the problem of nuclear system substitution imposed by failures, probabilistic methods are discussed. The aim of this paper is to present a methodological framework to the choice of the most useful method applied in the problem of nuclear system substitution.(author)

Deterministic quantitative risk assessment development

Energy Technology Data Exchange (ETDEWEB)

Dawson, Jane; Colquhoun, Iain [PII Pipeline Solutions Business of GE Oil and Gas, Cramlington Northumberland (United Kingdom)

2009-07-01

Current risk assessment practice in pipeline integrity management is to use a semi-quantitative index-based or model based methodology. This approach has been found to be very flexible and provide useful results for identifying high risk areas and for prioritizing physical integrity assessments. However, as pipeline operators progressively adopt an operating strategy of continual risk reduction with a view to minimizing total expenditures within safety, environmental, and reliability constraints, the need for quantitative assessments of risk levels is becoming evident. Whereas reliability based quantitative risk assessments can be and are routinely carried out on a site-specific basis, they require significant amounts of quantitative data for the results to be meaningful. This need for detailed and reliable data tends to make these methods unwieldy for system-wide risk k assessment applications. This paper describes methods for estimating risk quantitatively through the calibration of semi-quantitative estimates to failure rates for peer pipeline systems. The methods involve the analysis of the failure rate distribution, and techniques for mapping the rate to the distribution of likelihoods available from currently available semi-quantitative programs. By applying point value probabilities to the failure rates, deterministic quantitative risk assessment (QRA) provides greater rigor and objectivity than can usually be achieved through the implementation of semi-quantitative risk assessment results. The method permits a fully quantitative approach or a mixture of QRA and semi-QRA to suit the operator's data availability and quality, and analysis needs. For example, consequence analysis can be quantitative or can address qualitative ranges for consequence categories. Likewise, failure likelihoods can be output as classical probabilities or as expected failure frequencies as required. (author)

An assessment of the acute dietary exposure to glyphosate using deterministic and probabilistic methods.

Science.gov (United States)

Stephenson, C L; Harris, C A; Clarke, R

2018-02-01

Use of glyphosate in crop production can lead to residues of the active substance and related metabolites in food. Glyphosate has never been considered acutely toxic; however, in 2015 the European Food Safety Authority (EFSA) proposed an acute reference dose (ARfD). This differs from the Joint FAO/WHO Meeting on Pesticide Residues (JMPR) who in 2016, in line with their existing position, concluded that an ARfD was not necessary for glyphosate. This paper makes a comprehensive assessment of short-term dietary exposure to glyphosate from potentially treated crops grown in the EU and imported third-country food sources. European Union and global deterministic models were used to make estimates of short-term dietary exposure (generally defined as up to 24 h). Estimates were refined using food-processing information, residues monitoring data, national dietary exposure models, and basic probabilistic approaches to estimating dietary exposure. Calculated exposures levels were compared to the ARfD, considered to be the amount of a substance that can be consumed in a single meal, or 24-h period, without appreciable health risk. Acute dietary intakes were Probabilistic exposure estimates showed that the acute intake on no person-days exceeded 10% of the ARfD, even for the pessimistic scenario.

A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography.

Science.gov (United States)

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.

Radiation transport methods for nuclear log assessment - an overview

International Nuclear Information System (INIS)

Badruzzaman, A.

1996-01-01

Methods of radiation transport have been applied to well-logging problems with nuclear sources since the early 1960s. Nuclear sondes are used in identifying rock compositions and fluid properties in reservoirs to predict the porosity and oil saturation. Early computational effort in nuclear logging used diffusion techniques. As computers became more powerful, deterministic transport methods and, finally, Monte Carlo methods were applied to solve these problems in three dimensions. Recently, the application has been extended to problems with a new generation of devices, including spectroscopic sondes that measure such quantities as the carbon/oxygen ratio to predict oil saturation and logging-while-drilling (LWD) sondes that take neutron and gamma measurements as they rotate in the borehole. These measurements present conditions that will be difficult to calibrate in the laboratory

Development of probabilistic fast reactor fuel design method

International Nuclear Information System (INIS)

Ozawa, Takayuki

1997-01-01

Under the current method of evaluating fuel robustness in FBR fuel rod design, a variety of uncertain quantities including fuel production tolerance and power density are estimated conservatively. In the future, in order to proceed with improvements in the FBR core's performance and optimize the fuel's specifications, a rationalization of fuel design tolerance is required. Among the measures aimed at realizing this rationalization, the introduction of a probabilistic fast reactor fuel design method is currently under consideration. I have developed a probabilistic fast reactor fuel design code named BORNFREE, in order to make use of this method in FBR fuel design. At the same time, I have carried out a trial calculation of the cladding stress using this code and made a study and an evaluation of the possibility of employing tolerance rationalization in fuel rod design. In this paper, I provide an outline description of BORNFREE and report the results of the above study and evaluation. After performing cladding stress trial calculations using the probabilistic method, I was able to confirm that this method promises more rational design evaluation results than the conventional deterministic method. (author)

Inferring hierarchical clustering structures by deterministic annealing

International Nuclear Information System (INIS)

Hofmann, T.; Buhmann, J.M.

1996-01-01

The unsupervised detection of hierarchical structures is a major topic in unsupervised learning and one of the key questions in data analysis and representation. We propose a novel algorithm for the problem of learning decision trees for data clustering and related problems. In contrast to many other methods based on successive tree growing and pruning, we propose an objective function for tree evaluation and we derive a non-greedy technique for tree growing. Applying the principles of maximum entropy and minimum cross entropy, a deterministic annealing algorithm is derived in a meanfield approximation. This technique allows us to canonically superimpose tree structures and to fit parameters to averaged or open-quote fuzzified close-quote trees

Deterministic SLIR model for tuberculosis disease mapping

Science.gov (United States)

Aziz, Nazrina; Diah, Ijlal Mohd; Ahmad, Nazihah; Kasim, Maznah Mat

2017-11-01

Tuberculosis (TB) occurs worldwide. It can be transmitted to others directly through air when active TB persons sneeze, cough or spit. In Malaysia, it was reported that TB cases had been recognized as one of the most infectious disease that lead to death. Disease mapping is one of the methods that can be used as the prevention strategies since it can displays clear picture for the high-low risk areas. Important thing that need to be considered when studying the disease occurrence is relative risk estimation. The transmission of TB disease is studied through mathematical model. Therefore, in this study, deterministic SLIR models are used to estimate relative risk for TB disease transmission.

Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy

Science.gov (United States)

Zelyak, O.; Fallone, B. G.; St-Aubin, J.

2018-01-01

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low-density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy

Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy.

Science.gov (United States)

Zelyak, O; Fallone, B G; St-Aubin, J

2017-12-14

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low-density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy

Sensitivity/uncertainty analysis of a borehole scenario comparing Latin Hypercube Sampling and deterministic sensitivity approaches

International Nuclear Information System (INIS)

Harper, W.V.; Gupta, S.K.

1983-10-01

A computer code was used to study steady-state flow for a hypothetical borehole scenario. The model consists of three coupled equations with only eight parameters and three dependent variables. This study focused on steady-state flow as the performance measure of interest. Two different approaches to sensitivity/uncertainty analysis were used on this code. One approach, based on Latin Hypercube Sampling (LHS), is a statistical sampling method, whereas, the second approach is based on the deterministic evaluation of sensitivities. The LHS technique is easy to apply and should work well for codes with a moderate number of parameters. Of deterministic techniques, the direct method is preferred when there are many performance measures of interest and a moderate number of parameters. The adjoint method is recommended when there are a limited number of performance measures and an unlimited number of parameters. This unlimited number of parameters capability can be extremely useful for finite element or finite difference codes with a large number of grid blocks. The Office of Nuclear Waste Isolation will use the technique most appropriate for an individual situation. For example, the adjoint method may be used to reduce the scope to a size that can be readily handled by a technique such as LHS. Other techniques for sensitivity/uncertainty analysis, e.g., kriging followed by conditional simulation, will be used also. 15 references, 4 figures, 9 tables

The COMET method in 3-D hexagonal geometry

International Nuclear Information System (INIS)

Connolly, K. J.; Rahnema, F.

2012-01-01

The hybrid stochastic-deterministic coarse mesh radiation transport (COMET) method developed at Georgia Tech now solves reactor core problems in 3-D hexagonal geometry. In this paper, the method is used to solve three preliminary test problems designed to challenge the method with steep flux gradients, high leakage, and strong asymmetry and heterogeneity in the core. The test problems are composed of blocks taken from a high temperature test reactor benchmark problem. As the method is still in development, these problems and their results are strictly preliminary. Results are compared to whole core Monte Carlo reference solutions in order to verify the method. Relative errors are on the order of 50 pcm in core eigenvalue, and mean relative error in pin fission density calculations is less than 1% in these difficult test cores. The method requires the one-time pre-computation of a response expansion coefficient library, which may be compiled in a comparable amount of time to a single whole core Monte Carlo calculation. After the library has been computed, COMET may solve any number of core configurations on the order of an hour, representing a significant gain in efficiency over other methods for whole core transport calculations. (authors)

Deterministic extraction from weak random sources

CERN Document Server

Gabizon, Ariel

2011-01-01

In this research monograph, the author constructs deterministic extractors for several types of sources, using a methodology of recycling randomness which enables increasing the output length of deterministic extractors to near optimal length.

The discrete cones methods for two-dimensional neutral particle transport problems with voids

International Nuclear Information System (INIS)

Watanabe, Y.; Maynard, C.W.

1983-01-01

One of the most widely applied deterministic methods for time-independent, two-dimensional neutron transport calculations is the discrete ordinates method (DSN). The DSN solution, however, fails to be accurate in a void due to the ray effect. In order to circumvent this drawback, the authors have been developing a novel approximation: the discrete cones method (DCN), where a group of particles in a cone are simultaneously traced instead of particles in discrete directions for the DSN method. Programs, which apply to the DSN method in a non-vacuum region and the DCN method in a void, have been written for transport calculations in X-Y coordinates. The solutions for test problems demonstrate mitigation of the ray effect in voids without loosing the computational efficiency of the DSN method

Streamflow disaggregation: a nonlinear deterministic approach

Directory of Open Access Journals (Sweden)

B. Sivakumar

2004-01-01

Full Text Available This study introduces a nonlinear deterministic approach for streamflow disaggregation. According to this approach, the streamflow transformation process from one scale to another is treated as a nonlinear deterministic process, rather than a stochastic process as generally assumed. The approach follows two important steps: (1 reconstruction of the scalar (streamflow series in a multi-dimensional phase-space for representing the transformation dynamics; and (2 use of a local approximation (nearest neighbor method for disaggregation. The approach is employed for streamflow disaggregation in the Mississippi River basin, USA. Data of successively doubled resolutions between daily and 16 days (i.e. daily, 2-day, 4-day, 8-day, and 16-day are studied, and disaggregations are attempted only between successive resolutions (i.e. 2-day to daily, 4-day to 2-day, 8-day to 4-day, and 16-day to 8-day. Comparisons between the disaggregated values and the actual values reveal excellent agreements for all the cases studied, indicating the suitability of the approach for streamflow disaggregation. A further insight into the results reveals that the best results are, in general, achieved for low embedding dimensions (2 or 3 and small number of neighbors (less than 50, suggesting possible presence of nonlinear determinism in the underlying transformation process. A decrease in accuracy with increasing disaggregation scale is also observed, a possible implication of the existence of a scaling regime in streamflow.

Development of a DNBR evaluation method for the CEA ejection accident in SMART core

Energy Technology Data Exchange (ETDEWEB)

Hwang, Dae Hyun; Yoo, Y. J.; In, W. K.; Chang, M. H. [Korea Atomic Energy Research Institute, Taejon (Korea)

1999-12-01

A methodology applicable to the analysis of the CEA ejection accident in SMART is developed for the evaluation of the fraction of fuel failure caused by DNB. The transient behavior of the core thermal-hydraulic conditions is calculated by the subchannel analysis code MATRA. The minimum DNBR during the accident is calculated by KRB-1 CHF correlation considering the 1/8 symmetry of hot assembly. The variation of hot assembly power during the accident is simulated by the LTC(Limiting transient Curve) which is determined from the analysis of power distribution data resulting from the three-dimensional core dynamics calculations. The initial condition of the accident is determined by considering LOC(Limiting Conditions for Operation) of SMART core. Two different methodologies for the evaluation of DNB failure rate are established; a deterministic method based on the DNB envelope, and a probabilistic method based on the DNB probability of each fuel rod. The methodology developed in this study is applied to the analysis of CEA ejection accident in the preliminary design core of SMART. As the result, the fractions of DNB fuel failure by the deterministic method and the probabilistic method are calculated as 38.7% and 7.8%, respectively. 16 refs., 16 figs., 5 tabs. (Author)

SCALE6 Hybrid Deterministic-Stochastic Shielding Methodology for PWR Containment Calculations

International Nuclear Information System (INIS)

Matijevic, Mario; Pevec, Dubravko; Trontl, Kresimir

2014-01-01

The capabilities and limitations of SCALE6/MAVRIC hybrid deterministic-stochastic shielding methodology (CADIS and FW-CADIS) are demonstrated when applied to a realistic deep penetration Monte Carlo (MC) shielding problem of full-scale PWR containment model. The ultimate goal of such automatic variance reduction (VR) techniques is to achieve acceptable precision for the MC simulation in reasonable time by preparation of phase-space VR parameters via deterministic transport theory methods (discrete ordinates SN) by generating space-energy mesh-based adjoint function distribution. The hybrid methodology generates VR parameters that work in tandem (biased source distribution and importance map) in automated fashion which is paramount step for MC simulation of complex models with fairly uniform mesh tally uncertainties. The aim in this paper was determination of neutron-gamma dose rate distribution (radiation field) over large portions of PWR containment phase-space with uniform MC uncertainties. The sources of ionizing radiation included fission neutrons and gammas (reactor core) and gammas from activated two-loop coolant. Special attention was given to focused adjoint source definition which gave improved MC statistics in selected materials and/or regions of complex model. We investigated benefits and differences of FW-CADIS over CADIS and manual (i.e. analog) MC simulation of particle transport. Computer memory consumption by deterministic part of hybrid methodology represents main obstacle when using meshes with millions of cells together with high SN/PN parameters, so optimization of control and numerical parameters of deterministic module plays important role for computer memory management. We investigated the possibility of using deterministic module (memory intense) with broad group library v7 2 7n19g opposed to fine group library v7 2 00n47g used with MC module to fully take effect of low energy particle transport and secondary gamma emission. Compared with

A stochastic collocation method for the second order wave equation with a discontinuous random speed

KAUST Repository

Motamed, Mohammad; Nobile, Fabio; Tempone, Raul

2012-01-01

In this paper we propose and analyze a stochastic collocation method for solving the second order wave equation with a random wave speed and subjected to deterministic boundary and initial conditions. The speed is piecewise smooth in the physical

A Riccati-Based Interior Point Method for Efficient Model Predictive Control of SISO Systems

DEFF Research Database (Denmark)

Hagdrup, Morten; Johansson, Rolf; Bagterp Jørgensen, John

2017-01-01

model parts separate. The controller is designed based on the deterministic model, while the Kalman filter results from the stochastic part. The controller is implemented as a primal-dual interior point (IP) method using Riccati recursion and the computational savings possible for SISO systems...

Jump probabilities in the non-Markovian quantum jump method

International Nuclear Information System (INIS)

Haerkoenen, Kari

2010-01-01

The dynamics of a non-Markovian open quantum system described by a general time-local master equation is studied. The propagation of the density operator is constructed in terms of two processes: (i) deterministic evolution and (ii) evolution of a probability density functional in the projective Hilbert space. The analysis provides a derivation for the jump probabilities used in the recently developed non-Markovian quantum jump (NMQJ) method (Piilo et al 2008 Phys. Rev. Lett. 100 180402).

Deterministic sensitivity analysis for the numerical simulation of contaminants transport

International Nuclear Information System (INIS)

Marchand, E.

2007-12-01

The questions of safety and uncertainty are central to feasibility studies for an underground nuclear waste storage site, in particular the evaluation of uncertainties about safety indicators which are due to uncertainties concerning properties of the subsoil or of the contaminants. The global approach through probabilistic Monte Carlo methods gives good results, but it requires a large number of simulations. The deterministic method investigated here is complementary. Based on the Singular Value Decomposition of the derivative of the model, it gives only local information, but it is much less demanding in computing time. The flow model follows Darcy's law and the transport of radionuclides around the storage site follows a linear convection-diffusion equation. Manual and automatic differentiation are compared for these models using direct and adjoint modes. A comparative study of both probabilistic and deterministic approaches for the sensitivity analysis of fluxes of contaminants through outlet channels with respect to variations of input parameters is carried out with realistic data provided by ANDRA. Generic tools for sensitivity analysis and code coupling are developed in the Caml language. The user of these generic platforms has only to provide the specific part of the application in any language of his choice. We also present a study about two-phase air/water partially saturated flows in hydrogeology concerning the limitations of the Richards approximation and of the global pressure formulation used in petroleum engineering. (author)

Deterministic nonlinear phase gates induced by a single qubit

Science.gov (United States)

Park, Kimin; Marek, Petr; Filip, Radim

2018-05-01

We propose deterministic realizations of nonlinear phase gates by repeating a finite sequence of non-commuting Rabi interactions between a harmonic oscillator and only a single two-level ancillary qubit. We show explicitly that the key nonclassical features of the ideal cubic phase gate and the quartic phase gate are generated in the harmonic oscillator faithfully by our method. We numerically analyzed the performance of our scheme under realistic imperfections of the oscillator and the two-level system. The methodology is extended further to higher-order nonlinear phase gates. This theoretical proposal completes the set of operations required for continuous-variable quantum computation.

Quantitative diffusion tensor deterministic and probabilistic fiber tractography in relapsing-remitting multiple sclerosis

International Nuclear Information System (INIS)

Hu Bing; Ye Binbin; Yang Yang; Zhu Kangshun; Kang Zhuang; Kuang Sichi; Luo Lin; Shan Hong

2011-01-01

Purpose: Our aim was to study the quantitative fiber tractography variations and patterns in patients with relapsing-remitting multiple sclerosis (RRMS) and to assess the correlation between quantitative fiber tractography and Expanded Disability Status Scale (EDSS). Material and methods: Twenty-eight patients with RRMS and 28 age-matched healthy volunteers underwent a diffusion tensor MR imaging study. Quantitative deterministic and probabilistic fiber tractography were generated in all subjects. And mean numbers of tracked lines and fiber density were counted. Paired-samples t tests were used to compare tracked lines and fiber density in RRMS patients with those in controls. Bivariate linear regression model was used to determine the relationship between quantitative fiber tractography and EDSS in RRMS. Results: Both deterministic and probabilistic tractography's tracked lines and fiber density in RRMS patients were less than those in controls (P < .001). Both deterministic and probabilistic tractography's tracked lines and fiber density were found negative correlations with EDSS in RRMS (P < .001). The fiber tract disruptions and reductions in RRMS were directly visualized on fiber tractography. Conclusion: Changes of white matter tracts can be detected by quantitative diffusion tensor fiber tractography, and correlate with clinical impairment in RRMS.

Probabilistic evaluation of fuel element performance by the combined use of a fast running simplistic and a detailed deterministic fuel performance code

International Nuclear Information System (INIS)

Misfeldt, I.

1980-01-01

A comprehensive evaluation of fuel element performance requires a probabilistic fuel code supported by a well bench-marked deterministic code. This paper presents an analysis of a SGHWR ramp experiment, where the probabilistic fuel code FRP is utilized in combination with the deterministic fuel models FFRS and SLEUTH/SEER. The statistical methods employed in FRP are Monte Carlo simulation or a low-order Taylor approximation. The fast-running simplistic fuel code FFRS is used for the deterministic simulations, whereas simulations with SLEUTH/SEER are used to verify the predictions of FFRS. The ramp test was performed with a SGHWR fuel element, where 9 of the 36 fuel pins failed. There seemed to be good agreement between the deterministic simulations and the experiment, but the statistical evaluation shows that the uncertainty on the important performance parameters is too large for this ''nice'' result. The analysis does therefore indicate a discrepancy between the experiment and the deterministic code predictions. Possible explanations for this disagreement are discussed. (author)

Evaluation of the risk associated with the storage of radioactive wastes. The deterministic approach

International Nuclear Information System (INIS)

Lewi, J.

1988-07-01

Radioactive waste storage facility safety depends on a certain number of barriers being placed between the waste and man. These barriers, certain of which are articial (the waste package and engineered barriers) and others are natural (geological formations), are of characteristics suited to the type of storage facility (surface storage or storage in deep geological formations). The combination of these different barriers provide protection for man, under all circumstances considered plausible. Justification, for the storage of given quantities of radionuclides, of the choice of the site, the artificial barriers and the overall storage architecture, is obtained by evaluation of the risk. It being this which provides a basis for determining the acceptability of the storage facility. One of the following two methods is normally used for evaluation of the risk: the deterministic method and the probabilistic method. This adress describes the deterministic method. This method is employed in France for the safety analysis of the projects and works of ANDRA, the national agency responsible for the management of radioactive waste. It should be remembered that in France, the La Manche surface storage centre for low and medium activity waste has been in existence since 1969, close to the reprocessing plant at La Hague and a second surface storage centre is to be commissioned around 1991 at Soulaines in centre of France (departement de l'Aube). Furthermore, geological surveying of four sites located in geological formations consisting of granite, schist, clay and salt were begun in 1987 for the selection in about three years time of a site for the creation of an underground laboratory. This could later be transformed, if safety is demonstrated, into a deep storage centre

Random 2D Composites and the Generalized Method of Schwarz

Directory of Open Access Journals (Sweden)

Vladimir Mityushev

2015-01-01

Full Text Available Two-phase composites with nonoverlapping inclusions randomly embedded in matrix are investigated. A straightforward approach is applied to estimate the effective properties of random 2D composites. First, deterministic boundary value problems are solved for all locations of inclusions, that is, for all events of the considered probabilistic space C by the generalized method of Schwarz. Second, the effective properties are calculated in analytical form and averaged over C. This method is related to the traditional method based on the average probabilistic values involving the n-point correlation functions. However, we avoid computation of the correlation functions and compute their weighted moments of high orders by an indirect method which does not address the correlation functions. The effective properties are exactly expressed through these moments. It is proved that the generalized method of Schwarz converges for an arbitrary multiply connected doubly periodic domain and for an arbitrary contrast parameter. The proposed method yields an algorithm which can be applied with symbolic computations. The Torquato-Milton parameter ζ1 is exactly written for circular inclusions.

A review of recent advances in the spherical harmonics expansion method for semiconductor device simulation.

Science.gov (United States)

Rupp, K; Jungemann, C; Hong, S-M; Bina, M; Grasser, T; Jüngel, A

The Boltzmann transport equation is commonly considered to be the best semi-classical description of carrier transport in semiconductors, providing precise information about the distribution of carriers with respect to time (one dimension), location (three dimensions), and momentum (three dimensions). However, numerical solutions for the seven-dimensional carrier distribution functions are very demanding. The most common solution approach is the stochastic Monte Carlo method, because the gigabytes of memory requirements of deterministic direct solution approaches has not been available until recently. As a remedy, the higher accuracy provided by solutions of the Boltzmann transport equation is often exchanged for lower computational expense by using simpler models based on macroscopic quantities such as carrier density and mean carrier velocity. Recent developments for the deterministic spherical harmonics expansion method have reduced the computational cost for solving the Boltzmann transport equation, enabling the computation of carrier distribution functions even for spatially three-dimensional device simulations within minutes to hours. We summarize recent progress for the spherical harmonics expansion method and show that small currents, reasonable execution times, and rare events such as low-frequency noise, which are all hard or even impossible to simulate with the established Monte Carlo method, can be handled in a straight-forward manner. The applicability of the method for important practical applications is demonstrated for noise simulation, small-signal analysis, hot-carrier degradation, and avalanche breakdown.

Deterministic methods for the relativistic Vlasov-Maxwell equations and the Van Allen belts dynamics; Methodes deterministes de resolution des equations de Vlasov-Maxwell relativistes en vue du calcul de la dynamique des ceintures de Van Allen

Energy Technology Data Exchange (ETDEWEB)

Le Bourdiec, S

2007-03-15

Artificial satellites operate in an hostile radiation environment, the Van Allen radiation belts, which partly condition their reliability and their lifespan. In order to protect them, it is necessary to characterize the dynamics of the energetic electrons trapped in these radiation belts. This dynamics is essentially determined by the interactions between the energetic electrons and the existing electromagnetic waves. This work consisted in designing a numerical scheme to solve the equations modelling these interactions: the relativistic Vlasov-Maxwell system of equations. Our choice was directed towards methods of direct integration. We propose three new spectral methods for the momentum discretization: a Galerkin method and two collocation methods. All of them are based on scaled Hermite functions. The scaling factor is chosen in order to obtain the proper velocity resolution. We present in this thesis the discretization of the one-dimensional Vlasov-Poisson system and the numerical results obtained. Then we study the possible extensions of the methods to the complete relativistic problem. In order to reduce the computing time, parallelization and optimization of the algorithms were carried out. Finally, we present 1Dx-3Dv (mono-dimensional for x and three-dimensional for velocity) computations of Weibel and whistler instabilities with one or two electrons species. (author)

Experimental aspects of deterministic secure quantum key distribution

Energy Technology Data Exchange (ETDEWEB)

Walenta, Nino; Korn, Dietmar; Puhlmann, Dirk; Felbinger, Timo; Hoffmann, Holger; Ostermeyer, Martin [Universitaet Potsdam (Germany). Institut fuer Physik; Bostroem, Kim [Universitaet Muenster (Germany)

2008-07-01

Most common protocols for quantum key distribution (QKD) use non-deterministic algorithms to establish a shared key. But deterministic implementations can allow for higher net key transfer rates and eavesdropping detection rates. The Ping-Pong coding scheme by Bostroem and Felbinger[1] employs deterministic information encoding in entangled states with its characteristic quantum channel from Bob to Alice and back to Bob. Based on a table-top implementation of this protocol with polarization-entangled photons fundamental advantages as well as practical issues like transmission losses, photon storage and requirements for progress towards longer transmission distances are discussed and compared to non-deterministic protocols. Modifications of common protocols towards a deterministic quantum key distribution are addressed.

Shutdown Dose Rate Analysis Using the Multi-Step CADIS Method

International Nuclear Information System (INIS)

Ibrahim, Ahmad M.; Peplow, Douglas E.; Peterson, Joshua L.; Grove, Robert E.

2015-01-01

The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid Monte Carlo (MC)/deterministic radiation transport method was proposed to speed up the shutdown dose rate (SDDR) neutron MC calculation using an importance function that represents the neutron importance to the final SDDR. This work applied the MS-CADIS method to the ITER SDDR benchmark problem. The MS-CADIS method was also used to calculate the SDDR uncertainty resulting from uncertainties in the MC neutron calculation and to determine the degree of undersampling in SDDR calculations because of the limited ability of the MC method to tally detailed spatial and energy distributions. The analysis that used the ITER benchmark problem compared the efficiency of the MS-CADIS method to the traditional approach of using global MC variance reduction techniques for speeding up SDDR neutron MC calculation. Compared to the standard Forward-Weighted-CADIS (FW-CADIS) method, the MS-CADIS method increased the efficiency of the SDDR neutron MC calculation by 69%. The MS-CADIS method also increased the fraction of nonzero scoring mesh tally elements in the space-energy regions of high importance to the final SDDR

Process identification method based on the Z transformation

International Nuclear Information System (INIS)

Zwingelstein, G.

1968-01-01

A simple method is described for identifying the transfer function of a linear retard-less system, based on the inversion of the Z transformation of the transmittance using a computer. It is assumed in this study that the signals at the entrance and at the exit of the circuit considered are of the deterministic type. The study includes: the theoretical principle of the inversion of the Z transformation, details about programming simulation, and identification of filters whose degrees vary from the first to the fifth order. (authors) [fr

Simulation of dose deposition in stereotactic synchrotron radiation therapy: a fast approach combining Monte Carlo and deterministic algorithms

Energy Technology Data Exchange (ETDEWEB)

Smekens, F; Freud, N; Letang, J M; Babot, D [CNDRI (Nondestructive Testing using Ionizing Radiations) Laboratory, INSA-Lyon, 69621 Villeurbanne Cedex (France); Adam, J-F; Elleaume, H; Esteve, F [INSERM U-836, Equipe 6 ' Rayonnement Synchrotron et Recherche Medicale' , Institut des Neurosciences de Grenoble (France); Ferrero, C; Bravin, A [European Synchrotron Radiation Facility, Grenoble (France)], E-mail: francois.smekens@insa-lyon.fr

2009-08-07

A hybrid approach, combining deterministic and Monte Carlo (MC) calculations, is proposed to compute the distribution of dose deposited during stereotactic synchrotron radiation therapy treatment. The proposed approach divides the computation into two parts: (i) the dose deposited by primary radiation (coming directly from the incident x-ray beam) is calculated in a deterministic way using ray casting techniques and energy-absorption coefficient tables and (ii) the dose deposited by secondary radiation (Rayleigh and Compton scattering, fluorescence) is computed using a hybrid algorithm combining MC and deterministic calculations. In the MC part, a small number of particle histories are simulated. Every time a scattering or fluorescence event takes place, a splitting mechanism is applied, so that multiple secondary photons are generated with a reduced weight. The secondary events are further processed in a deterministic way, using ray casting techniques. The whole simulation, carried out within the framework of the Monte Carlo code Geant4, is shown to converge towards the same results as the full MC simulation. The speed of convergence is found to depend notably on the splitting multiplicity, which can easily be optimized. To assess the performance of the proposed algorithm, we compare it to state-of-the-art MC simulations, accelerated by the track length estimator technique (TLE), considering a clinically realistic test case. It is found that the hybrid approach is significantly faster than the MC/TLE method. The gain in speed in a test case was about 25 for a constant precision. Therefore, this method appears to be suitable for treatment planning applications.

Deterministic Chaos in Radon Time Variation

International Nuclear Information System (INIS)

Planinic, J.; Vukovic, B.; Radolic, V.; Faj, Z.; Stanic, D.

2003-01-01

Radon concentrations were continuously measured outdoors, in living room and basement in 10-minute intervals for a month. The radon time series were analyzed by comparing algorithms to extract phase-space dynamical information. The application of fractal methods enabled to explore the chaotic nature of radon in the atmosphere. The computed fractal dimensions, such as Hurst exponent (H) from the rescaled range analysis, Lyapunov exponent (λ ) and attractor dimension, provided estimates of the degree of chaotic behavior. The obtained low values of the Hurst exponent (0< H<0.5) indicated anti-persistent behavior (non random changes) of the time series, but the positive values of the λ pointed out the grate sensitivity on initial conditions and appearing deterministic chaos by radon time variations. The calculated fractal dimensions of attractors indicated more influencing (meteorological) parameters on radon in the atmosphere. (author)

Radon time variations and deterministic chaos

Energy Technology Data Exchange (ETDEWEB)

Planinic, J. E-mail: planinic@pedos.hr; Vukovic, B.; Radolic, V

2004-07-01

Radon concentrations were continuously measured outdoors, in the living room and in the basement at 10 min intervals for a month. Radon time series were analyzed by comparing algorithms to extract phase space dynamical information. The application of fractal methods enabled exploration of the chaotic nature of radon in atmosphere. The computed fractal dimensions, such as the Hurst exponent (H) from the rescaled range analysis, Lyapunov exponent ({lambda}) and attractor dimension, provided estimates of the degree of chaotic behavior. The obtained low values of the Hurst exponent (0deterministic chaos that appeared due to radon time variations. The calculated fractal dimensions of attractors indicated more influencing (meteorological) parameters on radon in the atmosphere.

Radon time variations and deterministic chaos

International Nuclear Information System (INIS)

Planinic, J.; Vukovic, B.; Radolic, V.

2004-01-01

Radon concentrations were continuously measured outdoors, in the living room and in the basement at 10 min intervals for a month. Radon time series were analyzed by comparing algorithms to extract phase space dynamical information. The application of fractal methods enabled exploration of the chaotic nature of radon in atmosphere. The computed fractal dimensions, such as the Hurst exponent (H) from the rescaled range analysis, Lyapunov exponent (λ) and attractor dimension, provided estimates of the degree of chaotic behavior. The obtained low values of the Hurst exponent (0< H<0.5) indicated anti-persistent behavior (non-random changes) of the time series, but the positive values of λ pointed out the grate sensitivity on initial conditions and the deterministic chaos that appeared due to radon time variations. The calculated fractal dimensions of attractors indicated more influencing (meteorological) parameters on radon in the atmosphere

Solution of the inverse problem of polarimetry for deterministic objects on the base of incomplete Mueller matrices

CERN Document Server

Savenkov, S M

2002-01-01

Using the Mueller matrix representation in the basis of the matrices of amplitude and phase anisotropies, a generalized solution of the inverse problem of polarimetry for deterministic objects on the base of incomplete Mueller matrices, which have been measured by method of three input polarization, is obtained.

Solution of the inverse problem of polarimetry for deterministic objects on the base of incomplete Mueller matrices

International Nuclear Information System (INIS)

Savenkov, S.M.; Oberemok, Je.A.

2002-01-01

Using the Mueller matrix representation in the basis of the matrices of amplitude and phase anisotropies, a generalized solution of the inverse problem of polarimetry for deterministic objects on the base of incomplete Mueller matrices, which have been measured by method of three input polarization, is obtained

Application of Monte Carlo method for dose calculation in thyroid follicle

International Nuclear Information System (INIS)

Silva, Frank Sinatra Gomes da

2008-02-01

The Monte Carlo method is an important tool to simulate radioactive particles interaction with biologic medium. The principal advantage of the method when compared with deterministic methods is the ability to simulate a complex geometry. Several computational codes use the Monte Carlo method to simulate the particles transport and they have the capacity to simulate energy deposition in models of organs and/or tissues, as well models of cells of human body. Thus, the calculation of the absorbed dose to thyroid's follicles (compound of colloid and follicles' cells) have a fundamental importance to dosimetry, because these cells are radiosensitive due to ionizing radiation exposition, in particular, exposition due to radioisotopes of iodine, because a great amount of radioiodine may be released into the environment in case of a nuclear accidents. In this case, the goal of this work was use the code of particles transport MNCP4C to calculate absorbed doses in models of thyroid's follicles, for Auger electrons, internal conversion electrons and beta particles, by iodine-131 and short-lived iodines (131, 132, 133, 134 e 135), with diameters varying from 30 to 500 μm. The results obtained from simulation with the MCNP4C code shown an average percentage of the 25% of total absorbed dose by colloid to iodine- 131 and 75% to short-lived iodine's. For follicular cells, this percentage was of 13% to iodine-131 and 87% to short-lived iodine's. The contributions from particles with low energies, like Auger and internal conversion electrons should not be neglected, to assessment the absorbed dose in cellular level. Agglomerative hierarchical clustering was used to compare doses obtained by codes MCNP4C, EPOTRAN, EGS4 and by deterministic methods. (author)

Review of the Monte Carlo and deterministic codes in radiation protection and dosimetry

International Nuclear Information System (INIS)

Tagziria, H.

2000-02-01

Modelling a physical system can be carried out either stochastically or deterministically. An example of the former method is the Monte Carlo technique, in which statistically approximate methods are applied to exact models. No transport equation is solved as individual particles are simulated and some specific aspect (tally) of their average behaviour is recorded. The average behaviour of the physical system is then inferred using the central limit theorem. In contrast, deterministic codes use mathematically exact methods that are applied to approximate models to solve the transport equation for the average particle behaviour. The physical system is subdivided in boxes in the phase-space system and particles are followed from one box to the next. The smaller the boxes the better the approximations become. Although the Monte Carlo method has been used for centuries, its more recent manifestation has really emerged from the Manhattan project of the Word War II. Its invention is thought to be mainly due to Metropolis, Ulah (through his interest in poker), Fermi, von Neuman and Richtmeyer. Over the last 20 years or so, the Monte Carlo technique has become a powerful tool in radiation transport. This is due to users taking full advantage of richer cross section data, more powerful computers and Monte Carlo techniques for radiation transport, with high quality physics and better known source spectra. This method is a common sense approach to radiation transport and its success and popularity is quite often also due to necessity, because measurements are not always possible or affordable. In the Monte Carlo method, which is inherently realistic because nature is statistical, a more detailed physics is made possible by isolation of events while rather elaborate geometries can be modelled. Provided that the physics is correct, a simulation is exactly analogous to an experimenter counting particles. In contrast to the deterministic approach, however, a disadvantage of the

Review of the Monte Carlo and deterministic codes in radiation protection and dosimetry

Energy Technology Data Exchange (ETDEWEB)

Tagziria, H

2000-02-01

Modelling a physical system can be carried out either stochastically or deterministically. An example of the former method is the Monte Carlo technique, in which statistically approximate methods are applied to exact models. No transport equation is solved as individual particles are simulated and some specific aspect (tally) of their average behaviour is recorded. The average behaviour of the physical system is then inferred using the central limit theorem. In contrast, deterministic codes use mathematically exact methods that are applied to approximate models to solve the transport equation for the average particle behaviour. The physical system is subdivided in boxes in the phase-space system and particles are followed from one box to the next. The smaller the boxes the better the approximations become. Although the Monte Carlo method has been used for centuries, its more recent manifestation has really emerged from the Manhattan project of the Word War II. Its invention is thought to be mainly due to Metropolis, Ulah (through his interest in poker), Fermi, von Neuman andRichtmeyer. Over the last 20 years or so, the Monte Carlo technique has become a powerful tool in radiation transport. This is due to users taking full advantage of richer cross section data, more powerful computers and Monte Carlo techniques for radiation transport, with high quality physics and better known source spectra. This method is a common sense approach to radiation transport and its success and popularity is quite often also due to necessity, because measurements are not always possible or affordable. In the Monte Carlo method, which is inherently realistic because nature is statistical, a more detailed physics is made possible by isolation of events while rather elaborate geometries can be modelled. Provided that the physics is correct, a simulation is exactly analogous to an experimenter counting particles. In contrast to the deterministic approach, however, a disadvantage of the

Deterministic calculation of grey Dancoff factors in cluster cells with cylindrical outer boundaries

International Nuclear Information System (INIS)

Jenisch Rodrigues, L.; Tullio de Vilhena, M.

2008-01-01

In the present work, the WIMSD code routine PIJM is modified to compute deterministic Dancoff factors by the collision probability definition in general arrangements of partially absorbing fuel rods. Collision probabilities are calculated by an efficient integration scheme of the third-order Bickley functions, which considers each cell region separately. The effectiveness of the method is assessed by comparing grey Dancoff factors as calculated by PIJM, with those available in the literature by the Monte Carlo method, for the irregular geometry of the Canadian CANDU and CANFLEX assemblies. Dancoff factors at several different fuel pin positions are found in very good agreement with the literature results. (orig.)

Handbook of methods for risk-based analyses of technical specifications

International Nuclear Information System (INIS)

Samanta, P.K.; Kim, I.S.; Mankamo, T.; Vesely, W.E.

1994-12-01

Technical Specifications (TS) requirements for nuclear power plants define the Limiting Conditions for Operation (LCOs) and Surveillance Requirements (SRs) to assure safety during operation. In general, these requirements are based on deterministic analysis and engineering judgments. Experiences with plant operation indicate that some elements of the requirements are unnecessarily restrictive, while a few may not be conducive to safety. The US Nuclear Regulatory Commission (USNRC) Office of Research has sponsored research to develop systematic risk-based methods to improve various aspects of TS requirements. This handbook summarizes these risk-based methods. The scope of the handbook includes reliability and risk-based methods for evaluating allowed outage times (AOTs), scheduled or preventive maintenance, action statements requiring shutdown where shutdown risk may be substantial, surveillance test intervals (STIs), and management of plant configurations resulting from outages of systems, or components. For each topic, the handbook summarizes analytic methods with data needs, outlines the insights to be gained, lists additional references, and gives examples of evaluations

Handbook of methods for risk-based analyses of technical specifications

Energy Technology Data Exchange (ETDEWEB)

Samanta, P.K.; Kim, I.S. [Brookhaven National Lab., Upton, NY (United States); Mankamo, T. [Avaplan Oy, Espoo (Finland); Vesely, W.E. [Science Applications International Corp., Dublin, OH (United States)

1994-12-01

Technical Specifications (TS) requirements for nuclear power plants define the Limiting Conditions for Operation (LCOs) and Surveillance Requirements (SRs) to assure safety during operation. In general, these requirements are based on deterministic analysis and engineering judgments. Experiences with plant operation indicate that some elements of the requirements are unnecessarily restrictive, while a few may not be conducive to safety. The US Nuclear Regulatory Commission (USNRC) Office of Research has sponsored research to develop systematic risk-based methods to improve various aspects of TS requirements. This handbook summarizes these risk-based methods. The scope of the handbook includes reliability and risk-based methods for evaluating allowed outage times (AOTs), scheduled or preventive maintenance, action statements requiring shutdown where shutdown risk may be substantial, surveillance test intervals (STIs), and management of plant configurations resulting from outages of systems, or components. For each topic, the handbook summarizes analytic methods with data needs, outlines the insights to be gained, lists additional references, and gives examples of evaluations.

An Optimal Calibration Method for a MEMS Inertial Measurement Unit

Directory of Open Access Journals (Sweden)

Bin Fang

2014-02-01

Full Text Available An optimal calibration method for a micro-electro-mechanical inertial measurement unit (MIMU is presented in this paper. The accuracy of the MIMU is highly dependent on calibration to remove the deterministic errors of systematic errors, which also contain random errors. The overlapping Allan variance is applied to characterize the types of random error terms in the measurements. The calibration model includes package misalignment error, sensor-to-sensor misalignment error and bias, and a scale factor is built. The new concept of a calibration method, which includes a calibration scheme and a calibration algorithm, is proposed. The calibration scheme is designed by D-optimal and the calibration algorithm is deduced by a Kalman filter. In addition, the thermal calibration is investigated, as the bias and scale factor varied with temperature. The simulations and real tests verify the effectiveness of the proposed calibration method and show that it is better than the traditional method.

Robust Topology Optimization Based on Stochastic Collocation Methods under Loading Uncertainties

Directory of Open Access Journals (Sweden)

Qinghai Zhao

2015-01-01

Full Text Available A robust topology optimization (RTO approach with consideration of loading uncertainties is developed in this paper. The stochastic collocation method combined with full tensor product grid and Smolyak sparse grid transforms the robust formulation into a weighted multiple loading deterministic problem at the collocation points. The proposed approach is amenable to implementation in existing commercial topology optimization software package and thus feasible to practical engineering problems. Numerical examples of two- and three-dimensional topology optimization problems are provided to demonstrate the proposed RTO approach and its applications. The optimal topologies obtained from deterministic and robust topology optimization designs under tensor product grid and sparse grid with different levels are compared with one another to investigate the pros and cons of optimization algorithm on final topologies, and an extensive Monte Carlo simulation is also performed to verify the proposed approach.

Application of probabilistic methods for sizing of safety factors in studies on defect harm fullness

International Nuclear Information System (INIS)

Ardillon, E.; Pitner, P.

1996-01-01

The design rules that are currently under application in nuclear engineering recommend the use of deterministic analysis methods. Probabilistic methods allow the uncertainties inherent in input variables of the analytical model to be taken into account owing to data provided by operation feedback so as to better evaluate the link between the deterministic margins adopted and the actual risk level. In the Resistance R/Loading L elementary case where the variables are Gaussian, there is an explicit relation between the required safety level and the partial safety coefficients which affect each variable. In the complex case of a flawed pipe subjected to various modes of ruin where many random variables are not Gaussian, one can obtain implicit relations. These relations allow a certain flexibility when choosing the coefficients, which poses the problem of their optimum calibration. The choice of coefficients based upon the coordinates of the ''most probable failure point'' illustrates this approach. (authors). 7 refs., 5 figs., 2 tabs

A Comfort-Aware Energy Efficient HVAC System Based on the Subspace Identification Method

Directory of Open Access Journals (Sweden)

O. Tsakiridis

2016-01-01

Full Text Available A proactive heating method is presented aiming at reducing the energy consumption in a HVAC system while maintaining the thermal comfort of the occupants. The proposed technique fuses time predictions for the zones’ temperatures, based on a deterministic subspace identification method, and zones’ occupancy predictions, based on a mobility model, in a decision scheme that is capable of regulating the balance between the total energy consumed and the total discomfort cost. Simulation results for various occupation-mobility models demonstrate the efficiency of the proposed technique.

Study (Prediction of Main Pipes Break Rates in Water Distribution Systems Using Intelligent and Regression Methods

Directory of Open Access Journals (Sweden)

Massoud Tabesh

2011-07-01

Full Text Available Optimum operation of water distribution networks is one of the priorities of sustainable development of water resources, considering the issues of increasing efficiency and decreasing the water losses. One of the key subjects in optimum operational management of water distribution systems is preparing rehabilitation and replacement schemes, prediction of pipes break rate and evaluation of their reliability. Several approaches have been presented in recent years regarding prediction of pipe failure rates which each one requires especial data sets. Deterministic models based on age and deterministic multi variables and stochastic group modeling are examples of the solutions which relate pipe break rates to parameters like age, material and diameters. In this paper besides the mentioned parameters, more factors such as pipe depth and hydraulic pressures are considered as well. Then using multi variable regression method, intelligent approaches (Artificial neural network and neuro fuzzy models and Evolutionary polynomial Regression method (EPR pipe burst rate are predicted. To evaluate the results of different approaches, a case study is carried out in a part ofMashhadwater distribution network. The results show the capability and advantages of ANN and EPR methods to predict pipe break rates, in comparison with neuro fuzzy and multi-variable regression methods.

Method to assist conception of collimators in nuclear medicine

International Nuclear Information System (INIS)

Gantet, P.; Esquerre, J.P.; Danet, B.; Roux, G.; Guiraud, R.

1990-01-01

Designing a collimator should begin by an accurate computation of its performances in order to minimize the usual expensive and time consuming phase of trial and error. The authors briefly describe several methods currently used, and present a method of simulation of the percussional response of collimators. The computation takes into account the attenuation of photons by the collimator septas. An other benefit is its ability to be used whatever the geometric specifications of the collimator. The program computes spatial resolution, geometric efficiency, septal penetration, as well as slice thickness when the collimator is used with a SPECT device. The study presents the results concerning two collimators: a general purpose parallel hole commercially available and a focused parallel one dedicated to a single slice SPECT system. In conclusion, this deterministic method which takes attenuation into account for collimators performances computation should be useful tool to assist conception of new collimators in nuclear medicine [fr

Nodal deterministic simulation for problems of neutron shielding in multigroup formulation

International Nuclear Information System (INIS)

Baptista, Josue Costa; Heringer, Juan Diego dos Santos; Santos, Luiz Fernando Trindade; Alves Filho, Hermes

2013-01-01

In this paper, we propose the use of some computational tools, with the implementation of numerical methods SGF (Spectral Green's Function), making use of a deterministic model of transport of neutral particles in the study and analysis of a known and simplified problem of nuclear engineering, known in the literature as a problem of neutron shielding, considering the model with two energy groups. These simulations are performed in MatLab platform, version 7.0, and are presented and developed with the help of a Computer Simulator providing a friendly computer application for their utilities

A stochastic collocation method for the second order wave equation with a discontinuous random speed

KAUST Repository

Motamed, Mohammad

2012-08-31

In this paper we propose and analyze a stochastic collocation method for solving the second order wave equation with a random wave speed and subjected to deterministic boundary and initial conditions. The speed is piecewise smooth in the physical space and depends on a finite number of random variables. The numerical scheme consists of a finite difference or finite element method in the physical space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space. This approach leads to the solution of uncoupled deterministic problems as in the Monte Carlo method. We consider both full and sparse tensor product spaces of orthogonal polynomials. We provide a rigorous convergence analysis and demonstrate different types of convergence of the probability error with respect to the number of collocation points for full and sparse tensor product spaces and under some regularity assumptions on the data. In particular, we show that, unlike in elliptic and parabolic problems, the solution to hyperbolic problems is not in general analytic with respect to the random variables. Therefore, the rate of convergence may only be algebraic. An exponential/fast rate of convergence is still possible for some quantities of interest and for the wave solution with particular types of data. We present numerical examples, which confirm the analysis and show that the collocation method is a valid alternative to the more traditional Monte Carlo method for this class of problems. © 2012 Springer-Verlag.

A new method to consider human actions in the framework of a dynamic PSA

International Nuclear Information System (INIS)

Kloos, M.; Peschke, J.

2006-01-01

The variety of accident sequences to be considered in the framework of a PSA derives from mutual dependencies between the physical process, the behaviour of the technical system, human actions and stochastic influences along the time axis. Because the conventional PSA approach is not able to adequately account for these interactions, so-called probabilistic dynamics methods have been developed. They generally achieve a more realistic modelling of accident scenarios and a more realistic safety assessment. At GRS, the method MCDET - a combination of Monte Carlo Simulation und the Discrete Dynamic Event Tree method - was developed. The implementation of MCDET was supplemented by a so called Crew-Module which allows - together with a deterministic dynamics code - to simulate human actions as a dynamic process evolving over time in interaction with the system and process dynamics. The Crew-Module accounts for communications between crew members and for performance shaping factors like stress, knowledge or ergonomics. This paper presents the Crew- Module and gives an overview of the results which may be obtained from its combination with MCDET and a deterministic dynamics code. The emergency operating procedure 'Secondary Side Bleed and Feed' in a German PWR is selected as an illustrative application. (authors)

Application and problems of probability methods in technical safety assessment in the field of nuclear engineering and other technologies

International Nuclear Information System (INIS)

Heuser, F.W.

1980-01-01

On the basis of a deterministic safety concept that has been developed in nuclear engineering, approaches for a probabilistic interpretation of existing safety requirements and for a further risk assessment are described. The procedures in technical reliability analysis and its application in nuclear engineering are discussed. By the example of a reliability analysis for a reactor protection system the author discusses the question as to what extent methods of reliability analysis can be used to interpret deterministically derived safety requirements. The the author gives a survey of the current value and application of probabilistic reliability assessments in non-nuclear technology. The last part of this report deals with methods of risk analysis and its use for safety assessment in nuclear engineering. On the basis of WASH 1,400 the most important phases and tasks of research work in risk assessment are explained, showing the basic criteria and the methods to be applied in risk analysis. (orig./HSCH) [de

Extending the subspace hybrid method for eigenvalue problems in reactor physics calculation

International Nuclear Information System (INIS)

Zhang, Q.; Abdel-Khalik, H. S.

2013-01-01

This paper presents an innovative hybrid Monte-Carlo-Deterministic method denoted by the SUBSPACE method designed for improving the efficiency of hybrid methods for reactor analysis applications. The SUBSPACE method achieves its high computational efficiency by taking advantage of the existing correlations between desired responses. Recently, significant gains in computational efficiency have been demonstrated using this method for source driven problems. Within this work the mathematical theory behind the SUBSPACE method is introduced and extended to address core wide level k-eigenvalue problems. The method's efficiency is demonstrated based on a three-dimensional quarter-core problem, where responses are sought on the pin cell level. The SUBSPACE method is compared to the FW-CADIS method and is found to be more efficient for the utilized test problem because of the reason that the FW-CADIS method solves a forward eigenvalue problem and an adjoint fixed-source problem while the SUBSPACE method only solves an adjoint fixed-source problem. Based on the favorable results obtained here, we are confident that the applicability of Monte Carlo for large scale reactor analysis could be realized in the near future. (authors)

Summary of existing uncertainty methods

International Nuclear Information System (INIS)

Glaeser, Horst

2013-01-01

A summary of existing and most used uncertainty methods is presented, and the main features are compared. One of these methods is the order statistics method based on Wilks' formula. It is applied in safety research as well as in licensing. This method has been first proposed by GRS for use in deterministic safety analysis, and is now used by many organisations world-wide. Its advantage is that the number of potential uncertain input and output parameters is not limited to a small number. Such a limitation was necessary for the first demonstration of the Code Scaling Applicability Uncertainty Method (CSAU) by the United States Regulatory Commission (USNRC). They did not apply Wilks' formula in their statistical method propagating input uncertainties to obtain the uncertainty of a single output variable, like peak cladding temperature. A Phenomena Identification and Ranking Table (PIRT) was set up in order to limit the number of uncertain input parameters, and consequently, the number of calculations to be performed. Another purpose of such a PIRT process is to identify the most important physical phenomena which a computer code should be suitable to calculate. The validation of the code should be focused on the identified phenomena. Response surfaces are used in some applications replacing the computer code for performing a high number of calculations. The second well known uncertainty method is the Uncertainty Methodology Based on Accuracy Extrapolation (UMAE) and the follow-up method 'Code with the Capability of Internal Assessment of Uncertainty (CIAU)' developed by the University Pisa. Unlike the statistical approaches, the CIAU does compare experimental data with calculation results. It does not consider uncertain input parameters. Therefore, the CIAU is highly dependent on the experimental database. The accuracy gained from the comparison between experimental data and calculated results are extrapolated to obtain the uncertainty of the system code predictions

Design of deterministic interleaver for turbo codes

International Nuclear Information System (INIS)

Arif, M.A.; Sheikh, N.M.; Sheikh, A.U.H.

2008-01-01

The choice of suitable interleaver for turbo codes can improve the performance considerably. For long block lengths, random interleavers perform well, but for some applications it is desirable to keep the block length shorter to avoid latency. For such applications deterministic interleavers perform better. The performance and design of a deterministic interleaver for short frame turbo codes is considered in this paper. The main characteristic of this class of deterministic interleaver is that their algebraic design selects the best permutation generator such that the points in smaller subsets of the interleaved output are uniformly spread over the entire range of the information data frame. It is observed that the interleaver designed in this manner improves the minimum distance or reduces the multiplicity of first few spectral lines of minimum distance spectrum. Finally we introduce a circular shift in the permutation function to reduce the correlation between the parity bits corresponding to the original and interleaved data frames to improve the decoding capability of MAP (Maximum A Posteriori) probability decoder. Our solution to design a deterministic interleaver outperforms the semi-random interleavers and the deterministic interleavers reported in the literature. (author)

Nonlinear Boltzmann equation for the homogeneous isotropic case: Minimal deterministic Matlab program

Science.gov (United States)

Asinari, Pietro

2010-10-01

The homogeneous isotropic Boltzmann equation (HIBE) is a fundamental dynamic model for many applications in thermodynamics, econophysics and sociodynamics. Despite recent hardware improvements, the solution of the Boltzmann equation remains extremely challenging from the computational point of view, in particular by deterministic methods (free of stochastic noise). This work aims to improve a deterministic direct method recently proposed [V.V. Aristov, Kluwer Academic Publishers, 2001] for solving the HIBE with a generic collisional kernel and, in particular, for taking care of the late dynamics of the relaxation towards the equilibrium. Essentially (a) the original problem is reformulated in terms of particle kinetic energy (exact particle number and energy conservation during microscopic collisions) and (b) the computation of the relaxation rates is improved by the DVM-like correction, where DVM stands for Discrete Velocity Model (ensuring that the macroscopic conservation laws are exactly satisfied). Both these corrections make possible to derive very accurate reference solutions for this test case. Moreover this work aims to distribute an open-source program (called HOMISBOLTZ), which can be redistributed and/or modified for dealing with different applications, under the terms of the GNU General Public License. The program has been purposely designed in order to be minimal, not only with regards to the reduced number of lines (less than 1000), but also with regards to the coding style (as simple as possible). Program summaryProgram title: HOMISBOLTZ Catalogue identifier: AEGN_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGN_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License No. of lines in distributed program, including test data, etc.: 23 340 No. of bytes in distributed program, including test data, etc.: 7 635 236 Distribution format: tar

Handbook of methods for risk-based analysis of technical specifications

International Nuclear Information System (INIS)

Samanta, P.K.; Kim, I.S.; Mankamo, T.; Vesely, W.E.

1996-01-01

Technical Specifications (TS) requirements for nuclear power plants define the Limiting Conditions for Operations (LCOs) and Surveillance Requirements (SRs) to assure safety during operation. In general, these requirements are based on deterministic analyses and engineering judgments. Improvements in these requirements are facilitated by the availability of plant-specific Probabilistic Risk Assessments (PRAs). The US Nuclear Regulatory Commission (USNRC) Office of Research sponsored research to develop systematic, risk-based methods to improve various aspects of TS requirements. A handbook of methods summarizing such risk-based approaches has been completed in 1994. It is expected that this handbook will provide valuable input to NRC's present work in developing guidance for using PRA in risk-informed regulation. The handbook addresses reliability and risk-based methods for evaluating allowed outage times (AOTs), action statements requiring shutdown where shutdown risk may be substantial, surveillance test intervals (STIs), managing plant configurations, and scheduling maintenance

Contribution of the deterministic approach to the characterization of seismic input

International Nuclear Information System (INIS)

Panza, G.F.; Romanelli, F.; Vaccari, F.; Decanini, L.; Mollaioli, F.

1999-10-01

Traditional methods use either a deterministic or a probabilistic approach, based on empirically derived laws for ground motion attenuation. The realistic definition of seismic input can be performed by means of advanced modelling codes based on the modal summation technique. These codes and their extension to laterally heterogeneous structures allow us to accurately calculate synthetic signals, complete of body waves and of surface waves, corresponding to different source and anelastic structural models, taking into account the effect of local geological conditions. This deterministic approach is capable to address some aspects largely overlooked in the probabilistic approach: (a) the effect of crustal properties on attenuation are not neglected; (b) the ground motion parameters are derived from synthetic time histories. and not from overly simplified attenuation functions; (c) the resulting maps are in terms of design parameters directly, and do not require the adaptation of probabilistic maps to design ground motions; and (d) such maps address the issue of the deterministic definition of ground motion in a way which permits the generalization of design parameters to locations where there is little seismic history. The methodology has been applied to a large part of south-eastern Europe, in the framework of the EU-COPERNICUS project 'Quantitative Seismic Zoning of the Circum Pannonian Region'. Maps of various seismic hazard parameters numerically modelled, and whenever possible tested against observations, such as peak ground displacement, velocity and acceleration, of practical use for the design of earthquake-safe structures, have been produced. The results of a standard probabilistic approach are compared with the findings based on the deterministic approach. A good agreement is obtained except for the Vrancea (Romania) zone, where the attenuation relations used in the probabilistic approach seem to underestimate, mainly at large distances, the seismic hazard

Proving Non-Deterministic Computations in Agda

Directory of Open Access Journals (Sweden)

Sergio Antoy

2017-01-01

Full Text Available We investigate proving properties of Curry programs using Agda. First, we address the functional correctness of Curry functions that, apart from some syntactic and semantic differences, are in the intersection of the two languages. Second, we use Agda to model non-deterministic functions with two distinct and competitive approaches incorporating the non-determinism. The first approach eliminates non-determinism by considering the set of all non-deterministic values produced by an application. The second approach encodes every non-deterministic choice that the application could perform. We consider our initial experiment a success. Although proving properties of programs is a notoriously difficult task, the functional logic paradigm does not seem to add any significant layer of difficulty or complexity to the task.

Mathematical methods in elasticity imaging

CERN Document Server

Ammari, Habib; Garnier, Josselin; Kang, Hyeonbae; Lee, Hyundae; Wahab, Abdul

2015-01-01

This book is the first to comprehensively explore elasticity imaging and examines recent, important developments in asymptotic imaging, modeling, and analysis of deterministic and stochastic elastic wave propagation phenomena. It derives the best possible functional images for small inclusions and cracks within the context of stability and resolution, and introduces a topological derivative-based imaging framework for detecting elastic inclusions in the time-harmonic regime. For imaging extended elastic inclusions, accurate optimal control methodologies are designed and the effects of uncertainties of the geometric or physical parameters on stability and resolution properties are evaluated. In particular, the book shows how localized damage to a mechanical structure affects its dynamic characteristics, and how measured eigenparameters are linked to elastic inclusion or crack location, orientation, and size. Demonstrating a novel method for identifying, locating, and estimating inclusions and cracks in elastic...

Research on probabilistic assessment method based on the corroded pipeline assessment criteria

International Nuclear Information System (INIS)

Zhang Guangli; Luo, Jinheng; Zhao Xinwei; Zhang Hua; Zhang Liang; Zhang Yi

2012-01-01

Pipeline integrity assessments are performed using conventional deterministic approaches, even though there are many uncertainties about the parameters in the pipeline integrity assessment. In this paper, a probabilistic assessment method is provided for the gas pipeline with corrosion defects based on the current corroded pipe evaluation criteria, and the failure probability of corroded pipelines due to the uncertainties of loadings, material property and measurement accuracy is estimated using Monte-Carlo technique. Furthermore, the sensitivity analysis approach is introduced to rank the influence of various random variables to the safety of pipeline. And the method to determine the critical defect size based on acceptable failure probability is proposed. Highlights: ► The folias factor in pipeline corrosion assessment methods was analyzed. ► The probabilistic method was applied in corrosion assessment methods. ► The influence of assessment variables to the reliability of pipeline was ranked. ► The acceptable failure probability was used to determine the critical defect size.

Offshore platforms and deterministic ice actions: Kashagan phase 2 development: North Caspian Sea.

Energy Technology Data Exchange (ETDEWEB)

Croasdale, Ken [KRCA, Calgary (Canada); Jordaan, Ian [Ian Jordaan and Associates, St John' s (Canada); Verlaan, Paul [Shell Development Kashagan, London (United Kingdom)

2011-07-01

The Kashagan development has to face the difficult conditions of the northern Caspian Sea. This paper investigated ice interaction scenarios and deterministic methods used on platform designs for the Kashagan development. The study presents first a review of the types of platforms in use and being designed for the Kashagan development. The various ice load scenarios and the structures used in each case are discussed. Vertical faced barriers, mobile drilling barges and sheet pile islands were used for the ice loads on vertical structures. Sloping faced barriers and islands of rock were used for the ice loads on sloping structures. Deterministic models such as the model in ISO 19906 were used to calculate the loads occurring with or without ice rubble in front of the structure. The results showed the importance of rubble build-up in front of wide structures in shallow water. Recommendations were provided for building efficient vertical and sloping faced barriers.

Application of perturbation theory methods to nuclear data uncertainty propagation using the collision probability method

International Nuclear Information System (INIS)

Sabouri, Pouya

2013-01-01

This thesis presents a comprehensive study of sensitivity/uncertainty analysis for reactor performance parameters (e.g. the k-effective) to the base nuclear data from which they are computed. The analysis starts at the fundamental step, the Evaluated Nuclear Data File and the uncertainties inherently associated with the data they contain, available in the form of variance/covariance matrices. We show that when a methodical and consistent computation of sensitivity is performed, conventional deterministic formalisms can be sufficient to propagate nuclear data uncertainties with the level of accuracy obtained by the most advanced tools, such as state-of-the-art Monte Carlo codes. By applying our developed methodology to three exercises proposed by the OECD (Uncertainty Analysis for Criticality Safety Assessment Benchmarks), we provide insights of the underlying physical phenomena associated with the used formalisms. (author)

Multiobjective anatomy-based dose optimization for HDR-brachytherapy with constraint free deterministic algorithms

International Nuclear Information System (INIS)

Milickovic, N.; Lahanas, M.; Papagiannopoulou, M.; Zamboglou, N.; Baltas, D.

2002-01-01

In high dose rate (HDR) brachytherapy, conventional dose optimization algorithms consider multiple objectives in the form of an aggregate function that transforms the multiobjective problem into a single-objective problem. As a result, there is a loss of information on the available alternative possible solutions. This method assumes that the treatment planner exactly understands the correlation between competing objectives and knows the physical constraints. This knowledge is provided by the Pareto trade-off set obtained by single-objective optimization algorithms with a repeated optimization with different importance vectors. A mapping technique avoids non-feasible solutions with negative dwell weights and allows the use of constraint free gradient-based deterministic algorithms. We compare various such algorithms and methods which could improve their performance. This finally allows us to generate a large number of solutions in a few minutes. We use objectives expressed in terms of dose variances obtained from a few hundred sampling points in the planning target volume (PTV) and in organs at risk (OAR). We compare two- to four-dimensional Pareto fronts obtained with the deterministic algorithms and with a fast-simulated annealing algorithm. For PTV-based objectives, due to the convex objective functions, the obtained solutions are global optimal. If OARs are included, then the solutions found are also global optimal, although local minima may be present as suggested. (author)

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

Science.gov (United States)

Oliveira, Sérgio C.; Zêzere, José L.; Lajas, Sara; Melo, Raquel

2017-07-01

Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km2) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.

Domain decomposition methods for the neutron diffusion problem

International Nuclear Information System (INIS)

Guerin, P.; Baudron, A. M.; Lautard, J. J.

2010-01-01

The neutronic simulation of a nuclear reactor core is performed using the neutron transport equation, and leads to an eigenvalue problem in the steady-state case. Among the deterministic resolution methods, simplified transport (SPN) or diffusion approximations are often used. The MINOS solver developed at CEA Saclay uses a mixed dual finite element method for the resolution of these problems. and has shown his efficiency. In order to take into account the heterogeneities of the geometry, a very fine mesh is generally required, and leads to expensive calculations for industrial applications. In order to take advantage of parallel computers, and to reduce the computing time and the local memory requirement, we propose here two domain decomposition methods based on the MINOS solver. The first approach is a component mode synthesis method on overlapping sub-domains: several Eigenmodes solutions of a local problem on each sub-domain are taken as basis functions used for the resolution of the global problem on the whole domain. The second approach is an iterative method based on a non-overlapping domain decomposition with Robin interface conditions. At each iteration, we solve the problem on each sub-domain with the interface conditions given by the solutions on the adjacent sub-domains estimated at the previous iteration. Numerical results on parallel computers are presented for the diffusion model on realistic 2D and 3D cores. (authors)

Method for Assessing Grid Frequency Deviation Due to Wind Power Fluctuation Based on “Time-Frequency Transformation”

DEFF Research Database (Denmark)

Jin, Lin; Yuan-zhang, Sun; Sørensen, Poul Ejnar

2012-01-01

published studies are based entirely on deterministic methodology. This paper presents a novel assessment method based on Time-Frequency Transformation to overcome shortcomings of existing methods. The main contribution of the paper is to propose a stochastic process simulation model which is a better...... alternative of the existing dynamic frequency deviation simulation model. In this way, the method takes the stochastic wind power fluctuation into full account so as to give a quantitative risk assessment of grid frequency deviation to grid operators, even without using any dynamic simulation tool. The case...

Acceleration of monte Carlo solution by conjugate gradient method

International Nuclear Information System (INIS)

Toshihisa, Yamamoto

2005-01-01

The conjugate gradient method (CG) was applied to accelerate Monte Carlo solutions in fixed source problems. The equilibrium model based formulation enables to use CG scheme as well as initial guess to maximize computational performance. This method is available to arbitrary geometry provided that the neutron source distribution in each subregion can be regarded as flat. Even if it is not the case, the method can still be used as a powerful tool to provide an initial guess very close to the converged solution. The major difference of Monte Carlo CG to deterministic CG is that residual error is estimated using Monte Carlo sampling, thus statistical error exists in the residual. This leads to a flow diagram specific to Monte Carlo-CG. Three pre-conditioners were proposed for CG scheme and the performance was compared with a simple 1-D slab heterogeneous test problem. One of them, Sparse-M option, showed an excellent performance in convergence. The performance per unit cost was improved by four times in the test problem. Although direct estimation of efficiency of the method is impossible mainly because of the strong problem-dependence of the optimized pre-conditioner in CG, the method seems to have efficient potential as a fast solution algorithm for Monte Carlo calculations. (author)

Deterministic Echo State Networks Based Stock Price Forecasting

Directory of Open Access Journals (Sweden)

Jingpei Dan

2014-01-01

Full Text Available Echo state networks (ESNs, as efficient and powerful computational models for approximating nonlinear dynamical systems, have been successfully applied in financial time series forecasting. Reservoir constructions in standard ESNs rely on trials and errors in real applications due to a series of randomized model building stages. A novel form of ESN with deterministically constructed reservoir is competitive with standard ESN by minimal complexity and possibility of optimizations for ESN specifications. In this paper, forecasting performances of deterministic ESNs are investigated in stock price prediction applications. The experiment results on two benchmark datasets (Shanghai Composite Index and S&P500 demonstrate that deterministic ESNs outperform standard ESN in both accuracy and efficiency, which indicate the prospect of deterministic ESNs for financial prediction.

Verification of statistical method CORN for modeling of microfuel in the case of high grain concentration

Energy Technology Data Exchange (ETDEWEB)

Chukbar, B. K., E-mail: bchukbar@mail.ru [National Research Center Kurchatov Institute (Russian Federation)

2015-12-15

Two methods of modeling a double-heterogeneity fuel are studied: the deterministic positioning and the statistical method CORN of the MCU software package. The effect of distribution of microfuel in a pebble bed on the calculation results is studied. The results of verification of the statistical method CORN for the cases of the microfuel concentration up to 170 cm{sup –3} in a pebble bed are presented. The admissibility of homogenization of the microfuel coating with the graphite matrix is studied. The dependence of the reactivity on the relative location of fuel and graphite spheres in a pebble bed is found.

Deterministic chaos in the pitting phenomena of passivable alloys

International Nuclear Information System (INIS)

Hoerle, Stephane

1998-01-01

It was shown that electrochemical noise recorded in stable pitting conditions exhibits deterministic (even chaotic) features. The occurrence of deterministic behaviors depend on the material/solution severity. Thus, electrolyte composition ([Cl - ]/[NO 3 - ] ratio, pH), passive film thickness or alloy composition can change the deterministic features. Only one pit is sufficient to observe deterministic behaviors. The electrochemical noise signals are non-stationary, which is a hint of a change with time in the pit behavior (propagation speed or mean). Modifications of electrolyte composition reveals transitions between random and deterministic behaviors. Spontaneous transitions between deterministic behaviors of different features (bifurcation) are also evidenced. Such bifurcations enlighten various routes to chaos. The routes to chaos and the features of chaotic signals allow to suggest the modeling (continuous and discontinuous models are proposed) of the electrochemical mechanisms inside a pit, that describe quite well the experimental behaviors and the effect of the various parameters. The analysis of the chaotic behaviors of a pit leads to a better understanding of propagation mechanisms and give tools for pit monitoring. (author) [fr

Earthquake Hazard Analysis Methods: A Review

Science.gov (United States)

Sari, A. M.; Fakhrurrozi, A.

2018-02-01

One of natural disasters that have significantly impacted on risks and damage is an earthquake. World countries such as China, Japan, and Indonesia are countries located on the active movement of continental plates with more frequent earthquake occurrence compared to other countries. Several methods of earthquake hazard analysis have been done, for example by analyzing seismic zone and earthquake hazard micro-zonation, by using Neo-Deterministic Seismic Hazard Analysis (N-DSHA) method, and by using Remote Sensing. In its application, it is necessary to review the effectiveness of each technique in advance. Considering the efficiency of time and the accuracy of data, remote sensing is used as a reference to the assess earthquake hazard accurately and quickly as it only takes a limited time required in the right decision-making shortly after the disaster. Exposed areas and possibly vulnerable areas due to earthquake hazards can be easily analyzed using remote sensing. Technological developments in remote sensing such as GeoEye-1 provide added value and excellence in the use of remote sensing as one of the methods in the assessment of earthquake risk and damage. Furthermore, the use of this technique is expected to be considered in designing policies for disaster management in particular and can reduce the risk of natural disasters such as earthquakes in Indonesia.

The deterministic prediction of failure of low pressure steam turbine disks

International Nuclear Information System (INIS)

Liu, Chun; Macdonald, D.D.

1993-01-01

Localized corrosion phenomena, including pitting corrosion, stress corrosion cracking, and corrosion fatigue, are the principal causes of corrosion-induced damage in electric power generating facilities and typically result in more than 50% of the unscheduled outages. Prediction of damage, so that repairs and inspections can be made during scheduled outages, could have an enormous impact on the economics of electric power generation. To date, prediction of corrosion damage has been made on the basis of empirical/statistical methods that have proven to be insufficiently robust and accurate to form the basis for the desired inspection/repair protocol. In this paper, we describe a deterministic method for predicting localized corrosion damage. We have used the method to illustrate how pitting corrosion initiates stress corrosion cracking (SCC) for low pressure steam turbine disks downstream of the Wilson line, where a thin condensed liquid layer exists on the steel disk surfaces. Our calculations show that the SCC initiation and propagation are sensitive to the oxygen content of the steam, the environment in the thin liquid condensed layer, and the stresses that the disk experiences in service

Calculation of neutron importance function in fissionable assemblies using Monte Carlo method

International Nuclear Information System (INIS)

Feghhi, S. A. H.; Afarideh, H.; Shahriari, M.

2007-01-01

The purpose of the present work is to develop an efficient solution method to calculate neutron importance function in fissionable assemblies for all criticality conditions, using Monte Carlo Method. The neutron importance function has a well important role in perturbation theory and reactor dynamic calculations. Usually this function can be determined by calculating adjoint flux through out solving the Adjoint weighted transport equation with deterministic methods. However, in complex geometries these calculations are very difficult. In this article, considering the capabilities of MCNP code in solving problems with complex geometries and its closeness to physical concepts, a comprehensive method based on physical concept of neutron importance has been introduced for calculating neutron importance function in sub-critical, critical and supercritical conditions. For this means a computer program has been developed. The results of the method has been benchmarked with ANISN code calculations in 1 and 2 group modes for simple geometries and their correctness has been approved for all three criticality conditions. Ultimately, the efficiency of the method for complex geometries has been shown by calculation of neutron importance in MNSR research reactor

Slope Stability Assessment Using Trigger Parameters and SINMAP Methods on Tamblingan-Buyan Ancient Mountain Area in Buleleng Regency, Bali

Directory of Open Access Journals (Sweden)

I Nengah Sinarta

2017-10-01

Full Text Available The mapping of soil movement was examined by comparing an extension of the deterministic Soil Stability Index Mapping (SINMAP method, and an overlay method with trigger parameters of soil movement. The SINMAP model used soil parameters in the form of the cohesion value (c, internal friction angle (φ, and hydraulic conductivity (ks for the prediction of soil movement based on the factor of safety (FS, while the indirect method used a literature review and field observations. The weightings of soil movement trigger parameters in assessments were based on natural physical aspects: (1 slope inclination = 30%; (2 rock weathering = 15%; (3 geological structure = 20%; (4 rainfall = 15%; (5 groundwater potential = 7%; (6 seismicity = 3%; and (7 vegetation = 10%. The research area was located in the Buleleng district, in particular in the ancient mountain area of Buyan-Tamblingan, in the Sukasada sub-district. The hazard mapping gave a high and very high hazard scale. The SINMAP model gave a validation accuracy of 14.29%, while the overlay method with seven trigger parameters produced an accuracy of 71.43%. Based on the analysis of the very high and high hazard class and the validation of the landslide occurrence points, the deterministic method using soil parameters and water absorption gave a much lower accuracy than the overlay method with a study of soil motion trigger parameters.

Minaret, a deterministic neutron transport solver for nuclear core calculations

Energy Technology Data Exchange (ETDEWEB)

Moller, J-Y.; Lautard, J-J., E-mail: jean-yves.moller@cea.fr, E-mail: jean-jacques.lautard@cea.fr [CEA - Centre de Saclay , Gif sur Yvette (France)

2011-07-01

We present here MINARET a deterministic transport solver for nuclear core calculations to solve the steady state Boltzmann equation. The code follows the multi-group formalism to discretize the energy variable. It uses discrete ordinate method to deal with the angular variable and a DGFEM to solve spatially the Boltzmann equation. The mesh is unstructured in 2D and semi-unstructured in 3D (cylindrical). Curved triangles can be used to fit the exact geometry. For the curved elements, two different sets of basis functions can be used. Transport solver is accelerated with a DSA method. Diffusion and SPN calculations are made possible by skipping the transport sweep in the source iteration. The transport calculations are parallelized with respect to the angular directions. Numerical results are presented for simple geometries and for the C5G7 Benchmark, JHR reactor and the ESFR (in 2D and 3D). Straight and curved finite element results are compared. (author)

Minaret, a deterministic neutron transport solver for nuclear core calculations

International Nuclear Information System (INIS)

Moller, J-Y.; Lautard, J-J.

2011-01-01

We present here MINARET a deterministic transport solver for nuclear core calculations to solve the steady state Boltzmann equation. The code follows the multi-group formalism to discretize the energy variable. It uses discrete ordinate method to deal with the angular variable and a DGFEM to solve spatially the Boltzmann equation. The mesh is unstructured in 2D and semi-unstructured in 3D (cylindrical). Curved triangles can be used to fit the exact geometry. For the curved elements, two different sets of basis functions can be used. Transport solver is accelerated with a DSA method. Diffusion and SPN calculations are made possible by skipping the transport sweep in the source iteration. The transport calculations are parallelized with respect to the angular directions. Numerical results are presented for simple geometries and for the C5G7 Benchmark, JHR reactor and the ESFR (in 2D and 3D). Straight and curved finite element results are compared. (author)

Linking mothers and infants within electronic health records: a comparison of deterministic and probabilistic algorithms.

Science.gov (United States)

Baldwin, Eric; Johnson, Karin; Berthoud, Heidi; Dublin, Sascha

2015-01-01

To compare probabilistic and deterministic algorithms for linking mothers and infants within electronic health records (EHRs) to support pregnancy outcomes research. The study population was women enrolled in Group Health (Washington State, USA) delivering a liveborn infant from 2001 through 2008 (N = 33,093 deliveries) and infant members born in these years. We linked women to infants by surname, address, and dates of birth and delivery using deterministic and probabilistic algorithms. In a subset previously linked using "gold standard" identifiers (N = 14,449), we assessed each approach's sensitivity and positive predictive value (PPV). For deliveries with no "gold standard" linkage (N = 18,644), we compared the algorithms' linkage proportions. We repeated our analyses in an independent test set of deliveries from 2009 through 2013. We reviewed medical records to validate a sample of pairs apparently linked by one algorithm but not the other (N = 51 or 1.4% of discordant pairs). In the 2001-2008 "gold standard" population, the probabilistic algorithm's sensitivity was 84.1% (95% CI, 83.5-84.7) and PPV 99.3% (99.1-99.4), while the deterministic algorithm had sensitivity 74.5% (73.8-75.2) and PPV 95.7% (95.4-96.0). In the test set, the probabilistic algorithm again had higher sensitivity and PPV. For deliveries in 2001-2008 with no "gold standard" linkage, the probabilistic algorithm found matched infants for 58.3% and the deterministic algorithm, 52.8%. On medical record review, 100% of linked pairs appeared valid. A probabilistic algorithm improved linkage proportion and accuracy compared to a deterministic algorithm. Better linkage methods can increase the value of EHRs for pregnancy outcomes research. Copyright © 2014 John Wiley & Sons, Ltd.

The probabilistic approach and the deterministic licensing procedure

International Nuclear Information System (INIS)

Fabian, H.; Feigel, A.; Gremm, O.

1984-01-01

If safety goals are given, the creativity of the engineers is necessary to transform the goals into actual safety measures. That is, safety goals are not sufficient for the derivation of a safety concept; the licensing process asks ''What does a safe plant look like.'' The answer connot be given by a probabilistic procedure, but need definite deterministic statements; the conclusion is, that the licensing process needs a deterministic approach. The probabilistic approach should be used in a complementary role in cases where deterministic criteria are not complete, not detailed enough or not consistent and additional arguments for decision making in connection with the adequacy of a specific measure are necessary. But also in these cases the probabilistic answer has to be transformed into a clear deterministic statement. (orig.)

Comparison of projection skills of deterministic ensemble methods using pseudo-simulation data generated from multivariate Gaussian distribution

Science.gov (United States)

Oh, Seok-Geun; Suh, Myoung-Seok

2017-07-01

The projection skills of five ensemble methods were analyzed according to simulation skills, training period, and ensemble members, using 198 sets of pseudo-simulation data (PSD) produced by random number generation assuming the simulated temperature of regional climate models. The PSD sets were classified into 18 categories according to the relative magnitude of bias, variance ratio, and correlation coefficient, where each category had 11 sets (including 1 truth set) with 50 samples. The ensemble methods used were as follows: equal weighted averaging without bias correction (EWA_NBC), EWA with bias correction (EWA_WBC), weighted ensemble averaging based on root mean square errors and correlation (WEA_RAC), WEA based on the Taylor score (WEA_Tay), and multivariate linear regression (Mul_Reg). The projection skills of the ensemble methods improved generally as compared with the best member for each category. However, their projection skills are significantly affected by the simulation skills of the ensemble member. The weighted ensemble methods showed better projection skills than non-weighted methods, in particular, for the PSD categories having systematic biases and various correlation coefficients. The EWA_NBC showed considerably lower projection skills than the other methods, in particular, for the PSD categories with systematic biases. Although Mul_Reg showed relatively good skills, it showed strong sensitivity to the PSD categories, training periods, and number of members. On the other hand, the WEA_Tay and WEA_RAC showed relatively superior skills in both the accuracy and reliability for all the sensitivity experiments. This indicates that WEA_Tay and WEA_RAC are applicable even for simulation data with systematic biases, a short training period, and a small number of ensemble members.

Multigrid methods for the computation of propagators in gauge fields

International Nuclear Information System (INIS)

Kalkreuter, T.

1992-11-01

In the present work generalizations of multigrid methods for propagators in gauge fields are investigated. We discuss proper averaging operations for bosons and for staggered fermions. An efficient algorithm for computing C numerically is presented. The averaging kernels C can be used not only in deterministic multigrid computations, but also in multigrid Monte Carlo simulations, and for the definition of block spins and blocked gauge fields in Monte Carlo renormalization group studies of gauge theories. Actual numerical computations of kernels and propagators are performed in compact four-dimensional SU(2) gauge fields. (orig./HSI)

Deterministic indexing for packed strings

DEFF Research Database (Denmark)

Bille, Philip; Gørtz, Inge Li; Skjoldjensen, Frederik Rye

2017-01-01

Given a string S of length n, the classic string indexing problem is to preprocess S into a compact data structure that supports efficient subsequent pattern queries. In the deterministic variant the goal is to solve the string indexing problem without any randomization (at preprocessing time...... or query time). In the packed variant the strings are stored with several character in a single word, giving us the opportunity to read multiple characters simultaneously. Our main result is a new string index in the deterministic and packed setting. Given a packed string S of length n over an alphabet σ...

SU-E-T-22: A Deterministic Solver of the Boltzmann-Fokker-Planck Equation for Dose Calculation

Energy Technology Data Exchange (ETDEWEB)

Hong, X; Gao, H [Shanghai Jiao Tong University, Shanghai, Shanghai (China); Paganetti, H [Massachusetts General Hospital, Boston, MA (United States)

2015-06-15

Purpose: The Boltzmann-Fokker-Planck equation (BFPE) accurately models the migration of photons/charged particles in tissues. While the Monte Carlo (MC) method is popular for solving BFPE in a statistical manner, we aim to develop a deterministic BFPE solver based on various state-of-art numerical acceleration techniques for rapid and accurate dose calculation. Methods: Our BFPE solver is based on the structured grid that is maximally parallelizable, with the discretization in energy, angle and space, and its cross section coefficients are derived or directly imported from the Geant4 database. The physical processes that are taken into account are Compton scattering, photoelectric effect, pair production for photons, and elastic scattering, ionization and bremsstrahlung for charged particles.While the spatial discretization is based on the diamond scheme, the angular discretization synergizes finite element method (FEM) and spherical harmonics (SH). Thus, SH is used to globally expand the scattering kernel and FFM is used to locally discretize the angular sphere. As a Result, this hybrid method (FEM-SH) is both accurate in dealing with forward-peaking scattering via FEM, and efficient for multi-energy-group computation via SH. In addition, FEM-SH enables the analytical integration in energy variable of delta scattering kernel for elastic scattering with reduced truncation error from the numerical integration based on the classic SH-based multi-energy-group method. Results: The accuracy of the proposed BFPE solver was benchmarked against Geant4 for photon dose calculation. In particular, FEM-SH had improved accuracy compared to FEM, while both were within 2% of the results obtained with Geant4. Conclusion: A deterministic solver of the Boltzmann-Fokker-Planck equation is developed for dose calculation, and benchmarked against Geant4. Xiang Hong and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang

Prediction of periodically correlated processes by wavelet transform and multivariate methods with applications to climatological data

Science.gov (United States)

Ghanbarzadeh, Mitra; Aminghafari, Mina

2015-05-01

This article studies the prediction of periodically correlated process using wavelet transform and multivariate methods with applications to climatological data. Periodically correlated processes can be reformulated as multivariate stationary processes. Considering this fact, two new prediction methods are proposed. In the first method, we use stepwise regression between the principal components of the multivariate stationary process and past wavelet coefficients of the process to get a prediction. In the second method, we propose its multivariate version without principal component analysis a priori. Also, we study a generalization of the prediction methods dealing with a deterministic trend using exponential smoothing. Finally, we illustrate the performance of the proposed methods on simulated and real climatological data (ozone amounts, flows of a river, solar radiation, and sea levels) compared with the multivariate autoregressive model. The proposed methods give good results as we expected.

Deterministic mean-variance-optimal consumption and investment

DEFF Research Database (Denmark)

Christiansen, Marcus; Steffensen, Mogens

2013-01-01

In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature that the consum......In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature...... that the consumption rate and the investment proportion are constrained to be deterministic processes. As a result we get rid of a series of unwanted features of the stochastic solution including diffusive consumption, satisfaction points and consistency problems. Deterministic strategies typically appear in unit......-linked life insurance contracts, where the life-cycle investment strategy is age dependent but wealth independent. We explain how optimal deterministic strategies can be found numerically and present an example from life insurance where we compare the optimal solution with suboptimal deterministic strategies...

Nuclear methods in medical physics

International Nuclear Information System (INIS)

Jeraj, R.

2003-01-01

A common ground for both, reactor and medical physics is a demand for high accuracy of particle transport calculations. In reactor physics, safe operation of nuclear power plants has been asking for high accuracy of calculation methods. Similarly, dose calculation in radiation therapy for cancer has been requesting high accuracy of transport methods to ensure adequate dosimetry. Common to both problems has always been a compromise between achievable accuracy and available computer power leading into a variety of calculation methods developed over the decades. On the other hand, differences of subjects (nuclear reactor vs. humans) and radiation types (neutron/photon vs. photon/electron or ions) are calling for very field-specific approach. Nevertheless, it is not uncommon to see drift of researches from one field to another. Several examples from both fields will be given with the aim to compare the problems, indicating their similarities and discussing their differences. As examples of reactor physics applications, both deterministic and Monte Carlo calculations will be presented for flux distributions of the VENUS and TRIGA Mark II benchmark. These problems will be paralleled to medical physics applications in linear accelerator radiation field determination and dose distribution calculations. Applicability of the adjoint/forward transport will be discussed in the light of both transport problems. Boron neutron capture therapy (BNCT) as an example of the close collaboration between the fields will be presented. At last, several other examples from medical physics, which can and cannot find corresponding problems in reactor physics, will be discussed (e.g., beam optimisation in inverse treatment planning, imaging applications). (author)

Linear dynamic analysis of arbitrary thin shells modal superposition by using finite element method

International Nuclear Information System (INIS)

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)

Deterministic chaos in the processor load

International Nuclear Information System (INIS)

Halbiniak, Zbigniew; Jozwiak, Ireneusz J.

2007-01-01

In this article we present the results of research whose purpose was to identify the phenomenon of deterministic chaos in the processor load. We analysed the time series of the processor load during efficiency tests of database software. Our research was done on a Sparc Alpha processor working on the UNIX Sun Solaris 5.7 operating system. The conducted analyses proved the presence of the deterministic chaos phenomenon in the processor load in this particular case

The complexity of interior point methods for solving discounted turn-based stochastic games

DEFF Research Database (Denmark)

Hansen, Thomas Dueholm; Ibsen-Jensen, Rasmus

2013-01-01

for general 2TBSGs. This implies that a number of interior point methods can be used to solve 2TBSGs. We consider two such algorithms: the unified interior point method of Kojima, Megiddo, Noma, and Yoshise, and the interior point potential reduction algorithm of Kojima, Megiddo, and Ye. The algorithms run...... states and discount factor γ we get κ=Θ(n(1−γ)2) , −δ=Θ(n√1−γ) , and 1/θ=Θ(n(1−γ)2) in the worst case. The lower bounds for κ, − δ, and 1/θ are all obtained using the same family of deterministic games....

Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

International Nuclear Information System (INIS)

Biondo, Elliott D.; Wilson, Paul P. H.

2017-01-01

In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation of an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 _± 5 • _1_0_"_4 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.

Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation.

Science.gov (United States)

Liu, Xiaofeng; Bai, Fang; Ouyang, Sisheng; Wang, Xicheng; Li, Honglin; Jiang, Hualiang

2009-03-31

Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105-112). Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 A to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 +/- 0.18 seconds per molecule) renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms other four multiple conformer generators in the case of

Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation

Directory of Open Access Journals (Sweden)

Li Honglin

2009-03-01

Full Text Available Abstract Background Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. Results The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105–112. Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 Å to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 ± 0.18 seconds per molecule renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. Conclusion On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms

The probabilistic method of WWER fuel rod strength estimation using the START-3 code

International Nuclear Information System (INIS)

Bibilashvili, Yu.K.; Medvedev, A.V.; Bogatyr, S.M.; Sokolov, F.F.; Khramtsov, M.V.

2001-01-01

During the last years probability methods of studying were widely used to determine the influence exerted by the geometry, technology and performance parameters of a fuel rod on the characteristics of its condition. Despite the diversity of probability methods their basis is formed by the simplest schema of the Monte-Carlo method (MC). This schema assumes a great number of the realizations of a random value and the statistical assessment of its characteristics. To generate random values, use is usually made of a pseudo-random number generator. The application of the quasi-random sequence elements in place of the latter substantially reduces the machine time since it promotes a quicker convergence of the method. Probability methods used to study the characteristics of a fuel rod condition can be considered to be an auxiliary means of deterministic calculations that allows the assessment of the conservatism degree of design calculations. (author)

Problems in radiation shielding calculations with Monte Carlo methods

International Nuclear Information System (INIS)

Ueki, Kohtaro

1985-01-01

The Monte Carlo method is a very useful tool for solving a large class of radiation transport problem. In contrast with deterministic method, geometric complexity is a much less significant problem for Monte Carlo calculations. However, the accuracy of Monte Carlo calculations is of course, limited by statistical error of the quantities to be estimated. In this report, we point out some typical problems to solve a large shielding system including radiation streaming. The Monte Carlo coupling technique was developed to settle such a shielding problem accurately. However, the variance of the Monte Carlo results using the coupling technique of which detectors were located outside the radiation streaming, was still not enough. So as to bring on more accurate results for the detectors located outside the streaming and also for a multi-legged-duct streaming problem, a practicable way of ''Prism Scattering technique'' is proposed in the study. (author)

Corrigendum to "Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy".

Science.gov (United States)

Zelyak, Oleksandr; Fallone, B Gino; St-Aubin, Joel

2018-03-12

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy

Forward-Weighted CADIS Method for Variance Reduction of Monte Carlo Reactor Analyses

International Nuclear Information System (INIS)

Wagner, John C.; Mosher, Scott W.

2010-01-01

Current state-of-the-art tools and methods used to perform 'real' commercial reactor analyses use high-fidelity transport codes to produce few-group parameters at the assembly level for use in low-order methods applied at the core level. Monte Carlo (MC) methods, which allow detailed and accurate modeling of the full geometry and energy details and are considered the 'gold standard' for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the several-decade-old methodology used in current practice. However, the prohibitive computational requirements associated with obtaining fully converged system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. A goal of current research at Oak Ridge National Laboratory (ORNL) is to change this paradigm by enabling the direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome is the slow non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, research has focused on development in the following two areas: (1) a hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The focus of this paper is limited to the first area mentioned above. It describes the FW-CADIS method applied to variance reduction of MC reactor analyses and provides initial results for calculating

Hooke–Jeeves Method-used Local Search in a Hybrid Global Optimization Algorithm

Directory of Open Access Journals (Sweden)

V. D. Sulimov

2014-01-01

Full Text Available Modern methods for optimization investigation of complex systems are based on development and updating the mathematical models of systems because of solving the appropriate inverse problems. Input data desirable for solution are obtained from the analysis of experimentally defined consecutive characteristics for a system or a process. Causal characteristics are the sought ones to which equation coefficients of mathematical models of object, limit conditions, etc. belong. The optimization approach is one of the main ones to solve the inverse problems. In the main case it is necessary to find a global extremum of not everywhere differentiable criterion function. Global optimization methods are widely used in problems of identification and computation diagnosis system as well as in optimal control, computing to-mography, image restoration, teaching the neuron networks, other intelligence technologies. Increasingly complicated systems of optimization observed during last decades lead to more complicated mathematical models, thereby making solution of appropriate extreme problems significantly more difficult. A great deal of practical applications may have the problem con-ditions, which can restrict modeling. As a consequence, in inverse problems the criterion functions can be not everywhere differentiable and noisy. Available noise means that calculat-ing the derivatives is difficult and unreliable. It results in using the optimization methods without calculating the derivatives.An efficiency of deterministic algorithms of global optimization is significantly restrict-ed by their dependence on the extreme problem dimension. When the number of variables is large they use the stochastic global optimization algorithms. As stochastic algorithms yield too expensive solutions, so this drawback restricts their applications. Developing hybrid algo-rithms that combine a stochastic algorithm for scanning the variable space with deterministic local search

A method for risk-informed safety significance categorization using the analytic hierarchy process and bayesian belief networks

International Nuclear Information System (INIS)

Ha, Jun Su; Seong, Poong Hyun

2004-01-01

A risk-informed safety significance categorization (RISSC) is to categorize structures, systems, or components (SSCs) of a nuclear power plant (NPP) into two or more groups, according to their safety significance using both probabilistic and deterministic insights. In the conventional methods for the RISSC, the SSCs are quantitatively categorized according to their importance measures for the initial categorization. The final decisions (categorizations) of SSCs, however, are qualitatively made by an expert panel through discussions and adjustments of opinions by using the probabilistic insights compiled in the initial categorization process and combining the probabilistic insights with the deterministic insights. Therefore, owing to the qualitative and linear decision-making process, the conventional methods have the demerits as follows: (1) they are very costly in terms of time and labor, (2) it is not easy to reach the final decision, when the opinions of the experts are in conflict and (3) they have an overlapping process due to the linear paradigm (the categorization is performed twice - first, by the engineers who propose the method, and second, by the expert panel). In this work, a method for RISSC using the analytic hierarchy process (AHP) and bayesian belief networks (BBN) is proposed to overcome the demerits of the conventional methods and to effectively arrive at a final decision (or categorization). By using the AHP and BBN, the expert panel takes part in the early stage of the categorization (that is, the quantification process) and the safety significance based on both probabilistic and deterministic insights is quantified. According to that safety significance, SSCs are quantitatively categorized into three categories such as high safety significant category (Hi), potentially safety significant category (Po), or low safety significant category (Lo). The proposed method was applied to the components such as CC-V073, CV-V530, and SI-V644 in Ulchin Unit

Study on critical effect in lattice homogenization via Monte Carlo method

International Nuclear Information System (INIS)

Li Mancang; Wang Kan; Yao Dong

2012-01-01

In contrast to the traditional deterministic lattice codes, generating the homogenization multigroup constants via Monte Carlo method overcomes the difficulties in geometry and treats energy in continuum. thus provides more accuracy parameters. An infinite lattice of identical symmetric motives is usually assumed when performing the homogenization. However, the finite size of a reactor is reality and it should influence the lattice calculation. In practice of the homogenization with Monte Carlo method, B N theory is applied to take the leakage effect into account. The fundamental mode with the buckling B is used as a measure of the finite size. The critical spectrum in the solution of 0-dimensional fine-group B 1 equations is used to correct the weighted spectrum for homogenization. A PWR prototype core is examined to verify that the presented method indeed generates few group constants effectively. In addition, a zero power physical experiment verification is performed. The results show that B N theory is adequate for leakage correction in the multigroup constants generation via Monte Carlo method. (authors)

Introducing Synchronisation in Deterministic Network Models

DEFF Research Database (Denmark)

Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens Frederik D.

2006-01-01

The paper addresses performance analysis for distributed real time systems through deterministic network modelling. Its main contribution is the introduction and analysis of models for synchronisation between tasks and/or network elements. Typical patterns of synchronisation are presented leading...... to the suggestion of suitable network models. An existing model for flow control is presented and an inherent weakness is revealed and remedied. Examples are given and numerically analysed through deterministic network modelling. Results are presented to highlight the properties of the suggested models...

Deterministic Compressed Sensing

Science.gov (United States)

2011-11-01

39 4.3 Digital Communications . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.4 Group Testing ...deterministic de - sign matrices. All bounds ignore the O() constants. . . . . . . . . . . 131 xvi List of Algorithms 1 Iterative Hard Thresholding Algorithm...sensing is information theoretically possible using any (2k, )-RIP sensing matrix . The following celebrated results of Candès, Romberg and Tao [54

Deterministic Mean-Field Ensemble Kalman Filtering

KAUST Repository

Law, Kody

2016-05-03

The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.

Deterministic Mean-Field Ensemble Kalman Filtering

KAUST Repository

Law, Kody; Tembine, Hamidou; Tempone, Raul

2016-01-01

The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.

Upgrading of analytical method of general sensitivity for feature evaluation of land disposal system. 3. Abstract of report on research entrusted by the Japan Nuclear Cycle Development Institute

International Nuclear Information System (INIS)

1999-02-01

In this research, a method to evaluate features of searching type system was analyzed statistically and deterministically by expanding it to nuclide transport in near-field host rocks. Here was described on abstract of methodology by summarizing fundamental concept on procedure and shadow-model of the feature evaluation based on investigation progress in last fiscal year, details on the nuclide transport in near-field host rocks and analytical method of sensitivity using this research, contents of statistical analysis using the shadow-model of nuclide transport, and summaries of contents and results on the deterministic analysis. (G.K.)

Probabilist methods applied to electric source problems in nuclear safety

International Nuclear Information System (INIS)

Carnino, A.; Llory, M.

1979-01-01

Nuclear Safety has frequently been asked to quantify safety margins and evaluate the hazard. In order to do so, the probabilist methods have proved to be the most promising. Without completely replacing determinist safety, they are now commonly used at the reliability or availability stages of systems as well as for determining the likely accidental sequences. In this paper an application linked to the problem of electric sources is described, whilst at the same time indicating the methods used. This is the calculation of the probable loss of all the electric sources of a pressurized water nuclear power station, the evaluation of the reliability of diesels by event trees of failures and the determination of accidental sequences which could be brought about by the 'total electric source loss' initiator and affect the installation or the environment [fr

Combining Different Privacy-Preserving Record Linkage Methods for Hospital Admission Data.

Science.gov (United States)

Stausberg, Jürgen; Waldenburger, Andreas; Borgs, Christian; Schnell, Rainer

2017-01-01

Record linkage (RL) is the process of identifying pairs of records that correspond to the same entity, for example the same patient. The basic approach assigns to each pair of records a similarity weight, and then determines a certain threshold, above which the two records are considered to be a match. Three different RL methods were applied under privacy-preserving conditions on hospital admission data: deterministic RL (DRL), probabilistic RL (PRL), and Bloom filters. The patient characteristics like names were one-way encrypted (DRL, PRL) or transformed to a cryptographic longterm key (Bloom filters). Based on one year of hospital admissions, the data set was split randomly in 30 thousand new and 1,5 million known patients. With the combination of the three RL-methods, a positive predictive value of 83 % (95 %-confidence interval 65 %-94 %) was attained. Thus, the application of the presented combination of RL-methods seem to be suited for other applications of population-based research.

Deterministic uncertainty analysis

International Nuclear Information System (INIS)

Worley, B.A.

1987-01-01

Uncertainties of computer results are of primary interest in applications such as high-level waste (HLW) repository performance assessment in which experimental validation is not possible or practical. This work presents an alternate deterministic approach for calculating uncertainties that has the potential to significantly reduce the number of computer runs required for conventional statistical analysis. 7 refs., 1 fig

Approximation and inference methods for stochastic biochemical kinetics—a tutorial review

International Nuclear Information System (INIS)

Schnoerr, David; Grima, Ramon; Sanguinetti, Guido

2017-01-01

Stochastic fluctuations of molecule numbers are ubiquitous in biological systems. Important examples include gene expression and enzymatic processes in living cells. Such systems are typically modelled as chemical reaction networks whose dynamics are governed by the chemical master equation. Despite its simple structure, no analytic solutions to the chemical master equation are known for most systems. Moreover, stochastic simulations are computationally expensive, making systematic analysis and statistical inference a challenging task. Consequently, significant effort has been spent in recent decades on the development of efficient approximation and inference methods. This article gives an introduction to basic modelling concepts as well as an overview of state of the art methods. First, we motivate and introduce deterministic and stochastic methods for modelling chemical networks, and give an overview of simulation and exact solution methods. Next, we discuss several approximation methods, including the chemical Langevin equation, the system size expansion, moment closure approximations, time-scale separation approximations and hybrid methods. We discuss their various properties and review recent advances and remaining challenges for these methods. We present a comparison of several of these methods by means of a numerical case study and highlight some of their respective advantages and disadvantages. Finally, we discuss the problem of inference from experimental data in the Bayesian framework and review recent methods developed the literature. In summary, this review gives a self-contained introduction to modelling, approximations and inference methods for stochastic chemical kinetics. (topical review)

Recognition of deterministic ETOL languages in logarithmic space

DEFF Research Database (Denmark)

Jones, Neil D.; Skyum, Sven

1977-01-01

It is shown that if G is a deterministic ETOL system, there is a nondeterministic log space algorithm to determine membership in L(G). Consequently, every deterministic ETOL language is recognizable in polynomial time. As a corollary, all context-free languages of finite index, and all Indian...

Pseudo-random number generator based on asymptotic deterministic randomness

Science.gov (United States)

Wang, Kai; Pei, Wenjiang; Xia, Haishan; Cheung, Yiu-ming

2008-06-01

A novel approach to generate the pseudorandom-bit sequence from the asymptotic deterministic randomness system is proposed in this Letter. We study the characteristic of multi-value correspondence of the asymptotic deterministic randomness constructed by the piecewise linear map and the noninvertible nonlinearity transform, and then give the discretized systems in the finite digitized state space. The statistic characteristics of the asymptotic deterministic randomness are investigated numerically, such as stationary probability density function and random-like behavior. Furthermore, we analyze the dynamics of the symbolic sequence. Both theoretical and experimental results show that the symbolic sequence of the asymptotic deterministic randomness possesses very good cryptographic properties, which improve the security of chaos based PRBGs and increase the resistance against entropy attacks and symbolic dynamics attacks.

Pseudo-random number generator based on asymptotic deterministic randomness

International Nuclear Information System (INIS)

Wang Kai; Pei Wenjiang; Xia Haishan; Cheung Yiuming

2008-01-01

A novel approach to generate the pseudorandom-bit sequence from the asymptotic deterministic randomness system is proposed in this Letter. We study the characteristic of multi-value correspondence of the asymptotic deterministic randomness constructed by the piecewise linear map and the noninvertible nonlinearity transform, and then give the discretized systems in the finite digitized state space. The statistic characteristics of the asymptotic deterministic randomness are investigated numerically, such as stationary probability density function and random-like behavior. Furthermore, we analyze the dynamics of the symbolic sequence. Both theoretical and experimental results show that the symbolic sequence of the asymptotic deterministic randomness possesses very good cryptographic properties, which improve the security of chaos based PRBGs and increase the resistance against entropy attacks and symbolic dynamics attacks

Deterministic calculations of radiation doses from brachytherapy seeds

International Nuclear Information System (INIS)

Reis, Sergio Carneiro dos; Vasconcelos, Vanderley de; Santos, Ana Maria Matildes dos

2009-01-01

Brachytherapy is used for treating certain types of cancer by inserting radioactive sources into tumours. CDTN/CNEN is developing brachytherapy seeds to be used mainly in prostate cancer treatment. Dose calculations play a very significant role in the characterization of the developed seeds. The current state-of-the-art of computation dosimetry relies on Monte Carlo methods using, for instance, MCNP codes. However, deterministic calculations have some advantages, as, for example, short computer time to find solutions. This paper presents a software developed to calculate doses in a two-dimensional space surrounding the seed, using a deterministic algorithm. The analysed seeds consist of capsules similar to IMC6711 (OncoSeed), that are commercially available. The exposure rates and absorbed doses are computed using the Sievert integral and the Meisberger third order polynomial, respectively. The software also allows the isodose visualization at the surface plan. The user can choose between four different radionuclides ( 192 Ir, 198 Au, 137 Cs and 60 Co). He also have to enter as input data: the exposure rate constant; the source activity; the active length of the source; the number of segments in which the source will be divided; the total source length; the source diameter; and the actual and effective source thickness. The computed results were benchmarked against results from literature and developed software will be used to support the characterization process of the source that is being developed at CDTN. The software was implemented using Borland Delphi in Windows environment and is an alternative to Monte Carlo based codes. (author)

The safety assessment of OPR-1000 nuclear power plant for station blackout accident applying the combined deterministic and probabilistic procedure

Energy Technology Data Exchange (ETDEWEB)

Kang, Dong Gu, E-mail: littlewing@kins.re.kr [Korea Institute of Nuclear Safety, 62 Gwahak-ro, Yuseong-gu, Daejeon 305-338 (Korea, Republic of); Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); Chang, Soon Heung [Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of)

2014-08-15

Highlights: • The combined deterministic and probabilistic procedure (CDPP) was proposed for safety assessment of the BDBAs. • The safety assessment of OPR-1000 nuclear power plant for SBO accident is performed by applying the CDPP. • By estimating the offsite power restoration time appropriately, the SBO risk is reevaluated. • It is concluded that the CDPP is applicable to safety assessment of BDBAs without significant erosion of the safety margin. - Abstract: Station blackout (SBO) is a typical beyond design basis accident (BDBA) and significant contributor to overall plant risk. The risk analysis of SBO could be important basis of rulemaking, accident mitigation strategy, etc. Recently, studies on the integrated approach of deterministic and probabilistic method for nuclear safety in nuclear power plants have been done, and among them, the combined deterministic and probabilistic procedure (CDPP) was proposed for safety assessment of the BDBAs. In the CDPP, the conditional exceedance probability obtained by the best estimate plus uncertainty method acts as go-between deterministic and probabilistic safety assessments, resulting in more reliable values of core damage frequency and conditional core damage probability. In this study, the safety assessment of OPR-1000 nuclear power plant for SBO accident was performed by applying the CDPP. It was confirmed that the SBO risk should be reevaluated by eliminating excessive conservatism in existing probabilistic safety assessment to meet the targeted core damage frequency and conditional core damage probability. By estimating the offsite power restoration time appropriately, the SBO risk was reevaluated, and it was finally confirmed that current OPR-1000 system lies in the acceptable risk against the SBO. In addition, it is concluded that the CDPP is applicable to safety assessment of BDBAs in nuclear power plants without significant erosion of the safety margin.

A New Equivalence Theory Method for Doubly Heterogeneous Fuel

International Nuclear Information System (INIS)

Choi, Sooyoung; Lee, Deokjung

2014-01-01

The unique characteristics cannot be handled easily by conventional computer code. A new methodology is being developed to treat resonance self-shielding in a doubly heterogeneous system. The method first homogenizes the material in the fuel compact region using an analytical approximation for the disadvantage factor based on equivalence theory. The disadvantage factor accounts for spatial self-shielding of the resonance flux within the fuel grains. The doubly-heterogeneous effects are accounted by using a modified definition of background cross section, which includes geometry parameters and the cross sections of both the fuel grain and fuel compact regions. For the verification, the new DH methodology was implemented in deterministic transport code TICTOC developed at UNIST which uses equivalence theory for resonance treatment and Method of Characteristics (MOC) for the ray tracing. In previous research, this new methodology was verified for several pin cell problems but further verification is required to confirm the validity of the methodology for various situations. Therefore, in this study, 9 cases for unit pin cell problems are designed and the accuracy of the new DH method is compared to the Monte Carlo code, McCARD. The new method for doubly-heterogeneous self-shielding using equivalence theory was summarized and calculation procedure was presented. The new methods use analytical expression for the disadvantage factor therefore additional complicated module is not required. The new method was verified for 9 pin cell models. As a result, TICTOC with the new DH method predicts the eigenvalues within about 200 pcm error compared with Monte Carlo results for the most of problems

Review of smoothing methods for enhancement of noisy data from heavy-duty LHD mining machines

Science.gov (United States)

Wodecki, Jacek; Michalak, Anna; Stefaniak, Paweł

2018-01-01

Appropriate analysis of data measured on heavy-duty mining machines is essential for processes monitoring, management and optimization. Some particular classes of machines, for example LHD (load-haul-dump) machines, hauling trucks, drilling/bolting machines etc. are characterized with cyclicity of operations. In those cases, identification of cycles and their segments or in other words - simply data segmentation is a key to evaluate their performance, which may be very useful from the management point of view, for example leading to introducing optimization to the process. However, in many cases such raw signals are contaminated with various artifacts, and in general are expected to be very noisy, which makes the segmentation task very difficult or even impossible. To deal with that problem, there is a need for efficient smoothing methods that will allow to retain informative trends in the signals while disregarding noises and other undesired non-deterministic components. In this paper authors present a review of various approaches to diagnostic data smoothing. Described methods can be used in a fast and efficient way, effectively cleaning the signals while preserving informative deterministic behaviour, that is a crucial to precise segmentation and other approaches to industrial data analysis.

Long term evolution of waste disposal sites: scenario selection and methods

International Nuclear Information System (INIS)

Peaudecerf, P.; Blanc, P.L.

1990-01-01

The safety analysis of long term radioactive waste disposal projects must take into account the evolution of the sites natural environment. The present paper aims at reassessing some questions relating to the methods and to some lack of knowledge which may appear when we try to forecast such evolutions and their results, and to some solutions that can be considered. We will particularly discuss the advantages and drawbacks of the deterministic approaches and the construction and working out of scenarios. The presentation is illustrated by reference to recent examples. 5 refs., 6 figs [fr

Electric field control of deterministic current-induced magnetization switching in a hybrid ferromagnetic/ferroelectric structure

Science.gov (United States)

Cai, Kaiming; Yang, Meiyin; Ju, Hailang; Wang, Sumei; Ji, Yang; Li, Baohe; Edmonds, Kevin William; Sheng, Yu; Zhang, Bao; Zhang, Nan; Liu, Shuai; Zheng, Houzhi; Wang, Kaiyou

2017-07-01

All-electrical and programmable manipulations of ferromagnetic bits are highly pursued for the aim of high integration and low energy consumption in modern information technology. Methods based on the spin-orbit torque switching in heavy metal/ferromagnet structures have been proposed with magnetic field, and are heading toward deterministic switching without external magnetic field. Here we demonstrate that an in-plane effective magnetic field can be induced by an electric field without breaking the symmetry of the structure of the thin film, and realize the deterministic magnetization switching in a hybrid ferromagnetic/ferroelectric structure with Pt/Co/Ni/Co/Pt layers on PMN-PT substrate. The effective magnetic field can be reversed by changing the direction of the applied electric field on the PMN-PT substrate, which fully replaces the controllability function of the external magnetic field. The electric field is found to generate an additional spin-orbit torque on the CoNiCo magnets, which is confirmed by macrospin calculations and micromagnetic simulations.

Equivalence relations between deterministic and quantum mechanical systems

International Nuclear Information System (INIS)

Hooft, G.

1988-01-01

Several quantum mechanical models are shown to be equivalent to certain deterministic systems because a basis can be found in terms of which the wave function does not spread. This suggests that apparently indeterministic behavior typical for a quantum mechanical world can be the result of locally deterministic laws of physics. We show how certain deterministic systems allow the construction of a Hilbert space and a Hamiltonian so that at long distance scales they may appear to behave as quantum field theories, including interactions but as yet no mass term. These observations are suggested to be useful for building theories at the Planck scale

Operational State Complexity of Deterministic Unranked Tree Automata

Directory of Open Access Journals (Sweden)

Xiaoxue Piao

2010-08-01

Full Text Available We consider the state complexity of basic operations on tree languages recognized by deterministic unranked tree automata. For the operations of union and intersection the upper and lower bounds of both weakly and strongly deterministic tree automata are obtained. For tree concatenation we establish a tight upper bound that is of a different order than the known state complexity of concatenation of regular string languages. We show that (n+1 ( (m+12^n-2^(n-1 -1 vertical states are sufficient, and necessary in the worst case, to recognize the concatenation of tree languages recognized by (strongly or weakly deterministic automata with, respectively, m and n vertical states.

Sensitivity analysis of the titan hybrid deterministic transport code for SPECT simulation

International Nuclear Information System (INIS)

Royston, Katherine K.; Haghighat, Alireza

2011-01-01

Single photon emission computed tomography (SPECT) has been traditionally simulated using Monte Carlo methods. The TITAN code is a hybrid deterministic transport code that has recently been applied to the simulation of a SPECT myocardial perfusion study. For modeling SPECT, the TITAN code uses a discrete ordinates method in the phantom region and a combined simplified ray-tracing algorithm with a fictitious angular quadrature technique to simulate the collimator and generate projection images. In this paper, we compare the results of an experiment with a physical phantom with predictions from the MCNP5 and TITAN codes. While the results of the two codes are in good agreement, they differ from the experimental data by ∼ 21%. In order to understand these large differences, we conduct a sensitivity study by examining the effect of different parameters including heart size, collimator position, collimator simulation parameter, and number of energy groups. (author)

Benchmarking of EPRI-cell epithermal methods with the point-energy discrete-ordinates code (OZMA)

International Nuclear Information System (INIS)

Williams, M.L.; Wright, R.Q.; Barhen, J.; Rothenstein, W.

1982-01-01

The purpose of the present study is to benchmark E-C resonance-shielding and cell-averaging methods against a rigorous deterministic solution on a fine-group level (approx. 30 groups between 1 eV and 5.5 keV). The benchmark code used is OZMA, which solves the space-dependent slowing-down equations using continuous-energy discrete ordinates or integral transport theory to produce fine-group cross sections. Results are given for three water-moderated lattices - a mixed oxide, a uranium method, and a tight-pitch high-conversion uranium oxide configuration. The latter two lattices were chosen because of the strong self shielding of the 238 U resonances

A combined deterministic and probabilistic procedure for safety assessment of components with cracks - Handbook.

Energy Technology Data Exchange (ETDEWEB)

Dillstroem, Peter; Bergman, Mats; Brickstad, Bjoern; Weilin Zang; Sattari-Far, Iradj; Andersson, Peder; Sund, Goeran; Dahlberg, Lars; Nilsson, Fred (Inspecta Technology AB, Stockholm (Sweden))

2008-07-01

SSM has supported research work for the further development of a previously developed procedure/handbook (SKI Report 99:49) for assessment of detected cracks and tolerance for defect analysis. During the operative use of the handbook it was identified needs to update the deterministic part of the procedure and to introduce a new probabilistic flaw evaluation procedure. Another identified need was a better description of the theoretical basis to the computer program. The principal aim of the project has been to update the deterministic part of the recently developed procedure and to introduce a new probabilistic flaw evaluation procedure. Other objectives of the project have been to validate the conservatism of the procedure, make the procedure well defined and easy to use and make the handbook that documents the procedure as complete as possible. The procedure/handbook and computer program ProSACC, Probabilistic Safety Assessment of Components with Cracks, has been extensively revised within this project. The major differences compared to the last revision are within the following areas: It is now possible to deal with a combination of deterministic and probabilistic data. It is possible to include J-controlled stable crack growth. The appendices on material data to be used for nuclear applications and on residual stresses are revised. A new deterministic safety evaluation system is included. The conservatism in the method for evaluation of the secondary stresses for ductile materials is reduced. A new geometry, a circular bar with a circumferential surface crack has been introduced. The results of this project will be of use to SSM in safety assessments of components with cracks and in assessments of the interval between the inspections of components in nuclear power plants

Handbook of methods for risk-based analysis of technical specification requirements

International Nuclear Information System (INIS)

Samanta, P.K.; Vesely, W.E.

1994-01-01

Technical Specifications (TS) requirements for nuclear power plants define the Limiting Conditions for Operation (LCOs) and Surveillance Requirements (SRs) to assure safety during operation. In general, these requirements were based on deterministic analysis and engineering judgments. Experiences with plant operation indicate that some elements of the requirements are unnecessarily restrictive, while others may not be conducive to safety. Improvements in these requirements are facilitated by the availability of plant specific Probabilistic Safety Assessments (PSAs). The use of risk and reliability-based methods to improve TS requirements has gained wide interest because these methods can: Quantitatively evaluate the risk and justify changes based on objective risk arguments; Provide a defensible basis for these requirements for regulatory applications. The US NRC Office of Research is sponsoring research to develop systematic risk-based methods to improve various aspects of TS requirements. The handbook of methods, which is being prepared, summarizes such risk-based methods. The scope of the handbook includes reliability and risk-based methods for evaluating allowed outage times (AOTs), action statements requiring shutdown where shutdown risk may be substantial, surveillance test intervals (STIs), defenses against common-cause failures, managing plant configurations, and scheduling maintenances. For each topic, the handbook summarizes methods of analysis and data needs, outlines the insights to be gained, lists additional references, and presents examples of evaluations

Handbook of methods for risk-based analysis of Technical Specification requirements

International Nuclear Information System (INIS)

Samanta, P.K.; Vesely, W.E.

1993-01-01

Technical Specifications (TS) requirements for nuclear power plants define the Limiting Conditions for Operation (LCOs) and Surveillance Requirements (SRs) to assure safety during operation. In general, these requirements were based on deterministic analysis and engineering judgments. Experiences with plant operation indicate that some elements of the requirements are unnecessarily restrictive, while others may not be conducive to safety. Improvements in these requirements are facilitated by the availability of plant specific Probabilistic Safety Assessments (PSAs). The use of risk and reliability-based methods to improve TS requirements has gained wide interest because these methods can: quantitatively evaluate the risk impact and justify changes based on objective risk arguments. Provide a defensible basis for these requirements for regulatory applications. The United States Nuclear Regulatory Commission (USNRC) Office of Research is sponsoring research to develop systematic risk-based methods to improve various aspects of TS requirements. The handbook of methods, which is being prepared, summarizes such risk-based methods. The scope of the handbook includes reliability and risk-based methods for evaluating allowed outage times (AOTs), action statements requiring shutdown where shutdown risk may be substantial, surveillance test intervals (STIs), defenses against common-cause failures, managing plant configurations, and scheduling maintenances. For each topic, the handbook summarizes methods of analysis and data needs, outlines the insights to be gained, lists additional references, and presents examples of evaluations

Probabilistic methods in fire-risk analysis

International Nuclear Information System (INIS)

Brandyberry, M.D.

1989-01-01

The first part of this work outlines a method for assessing the frequency of ignition of a consumer product in a building and shows how the method would be used in an example scenario utilizing upholstered furniture as the product and radiant auxiliary heating devices (electric heaters, wood stoves) as the ignition source. Deterministic thermal models of the heat-transport processes are coupled with parameter uncertainty analysis of the models and with a probabilistic analysis of the events involved in a typical scenario. This leads to a distribution for the frequency of ignition for the product. In second part, fire-risk analysis as currently used in nuclear plants is outlines along with a discussion of the relevant uncertainties. The use of the computer code COMPBRN is discussed for use in the fire-growth analysis along with the use of response-surface methodology to quantify uncertainties in the code's use. Generalized response surfaces are developed for temperature versus time for a cable tray, as well as a surface for the hot gas layer temperature and depth for a room of arbitrary geometry within a typical nuclear power plant compartment. These surfaces are then used to simulate the cable tray damage time in a compartment fire experiment

A study on the fatigue life prediction of tire belt-layers using probabilistic method

International Nuclear Information System (INIS)

Lee, Dong Woo; Park, Jong Sang; Lee, Tae Won; Kim, Seong Rae; Sung, Ki Deug; Huh, Sun Chul

2013-01-01

Tire belt separation failure is occurred by internal cracks generated in *1 and *2 belt layers and by its growth. And belt failure seriously affects tire endurance. Therefore, to improve the tire endurance, it is necessary to analyze tire crack growth behavior and predict fatigue life. Generally, the prediction of tire endurance is performed by the experimental method using tire test machine. But it takes much cost and time to perform experiment. In this paper, to predict tire fatigue life, we applied deterministic fracture mechanics approach, based on finite element analysis. Also, probabilistic analysis method based on statistics using Monte Carlo simulation is presented. Above mentioned two methods include a global-local finite element analysis to provide the detail necessary to model explicitly an internal crack and calculate the J-integral for tire life prediction.

Stochastic Modeling and Deterministic Limit of Catalytic Surface Processes

DEFF Research Database (Denmark)

Starke, Jens; Reichert, Christian; Eiswirth, Markus

2007-01-01

Three levels of modeling, microscopic, mesoscopic and macroscopic are discussed for the CO oxidation on low-index platinum single crystal surfaces. The introduced models on the microscopic and mesoscopic level are stochastic while the model on the macroscopic level is deterministic. It can......, such that in contrast to the microscopic model the spatial resolution is reduced. The derivation of deterministic limit equations is in correspondence with the successful description of experiments under low-pressure conditions by deterministic reaction-diffusion equations while for intermediate pressures phenomena...

A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs

Directory of Open Access Journals (Sweden)

Jooyong Yi

2013-09-01

Full Text Available Backtracking (i.e., reverse execution helps the user of a debugger to naturally think backwards along the execution path of a program, and thinking backwards makes it easy to locate the origin of a bug. So far backtracking has been implemented mostly by state saving or by checkpointing. These implementations, however, inherently do not scale. Meanwhile, a more recent backtracking method based on reverse-code generation seems promising because executing reverse code can restore the previous states of a program without state saving. In the literature, there can be found two methods that generate reverse code: (a static reverse-code generation that pre-generates reverse code through static analysis before starting a debugging session, and (b dynamic reverse-code generation that generates reverse code by applying dynamic analysis on the fly during a debugging session. In particular, we espoused the latter one in our previous work to accommodate non-determinism of a program caused by e.g., multi-threading. To demonstrate the usefulness of our dynamic reverse-code generation, this article presents a case study of various backtracking methods including ours. We compare the memory usage of various backtracking methods in a simple but nontrivial example, a bounded-buffer program. In the case of non-deterministic programs such as this bounded-buffer program, our dynamic reverse-code generation outperforms the existing backtracking methods in terms of memory efficiency.

RBE for deterministic effects

International Nuclear Information System (INIS)

1990-01-01

In the present report, data on RBE values for effects in tissues of experimental animals and man are analysed to assess whether for specific tissues the present dose limits or annual limits of intake based on Q values, are adequate to prevent deterministic effects. (author)

Application of QMC methods to PDEs with random coefficients : a survey of analysis and implementation

KAUST Repository

Kuo, Frances

2016-01-05

In this talk I will provide a survey of recent research efforts on the application of quasi-Monte Carlo (QMC) methods to PDEs with random coefficients. Such PDE problems occur in the area of uncertainty quantification. In recent years many papers have been written on this topic using a variety of methods. QMC methods are relatively new to this application area. I will consider different models for the randomness (uniform versus lognormal) and contrast different QMC algorithms (single-level versus multilevel, first order versus higher order, deterministic versus randomized). I will give a summary of the QMC error analysis and proof techniques in a unified view, and provide a practical guide to the software for constructing QMC points tailored to the PDE problems.

Probabilistic and deterministic soil structure interaction analysis including ground motion incoherency effects

International Nuclear Information System (INIS)

Elkhoraibi, T.; Hashemi, A.; Ostadan, F.

2014-01-01

input motions obtained from Probabilistic Seismic Hazard Analysis (PSHA) and the site response analysis is conducted with simulated soil profiles and accompanying soil nonlinearity curves. The deterministic approach utilizes three strain-compatible soil profiles (Lower Bound (LB), Best Estimate (BE) and Upper Bound (UB)) determined based on the variation of strain-compatible soil profiles obtained from the probabilistic site response analysis and uses SSI analysis to determine a conservative estimate of the required response as the envelope of the SSI results from LB, BE and UB soil cases. In contrast, the probabilistic SSI analysis propagates the uncertainty in the soil and structural properties and provides rigorous estimates for the statistical distribution of the response parameters of interest. The engineering demand parameters considered are the story drifts and ISRS at key locations in the example structure. The results from the deterministic and probabilistic approaches, with and without ground motion incoherency effects, are compared and discussed. Recommendations are made regarding the efficient use of statistical methods in probabilistic SSI analysis and the use of such results in Integrated Soil-Structure Fragility Analysis (ISSFA) and performance-based design

Probabilistic and deterministic soil structure interaction analysis including ground motion incoherency effects

Energy Technology Data Exchange (ETDEWEB)

Elkhoraibi, T., E-mail: telkhora@bechtel.com; Hashemi, A.; Ostadan, F.

2014-04-01

input motions obtained from Probabilistic Seismic Hazard Analysis (PSHA) and the site response analysis is conducted with simulated soil profiles and accompanying soil nonlinearity curves. The deterministic approach utilizes three strain-compatible soil profiles (Lower Bound (LB), Best Estimate (BE) and Upper Bound (UB)) determined based on the variation of strain-compatible soil profiles obtained from the probabilistic site response analysis and uses SSI analysis to determine a conservative estimate of the required response as the envelope of the SSI results from LB, BE and UB soil cases. In contrast, the probabilistic SSI analysis propagates the uncertainty in the soil and structural properties and provides rigorous estimates for the statistical distribution of the response parameters of interest. The engineering demand parameters considered are the story drifts and ISRS at key locations in the example structure. The results from the deterministic and probabilistic approaches, with and without ground motion incoherency effects, are compared and discussed. Recommendations are made regarding the efficient use of statistical methods in probabilistic SSI analysis and the use of such results in Integrated Soil-Structure Fragility Analysis (ISSFA) and performance-based design.

Implementation of the quasi-static method for neutron transport

International Nuclear Information System (INIS)

Alcaro, Fabio; Dulla, Sandra; Ravetto, Piero; Le Tellier, Romain; Suteau, Christophe

2011-01-01

The study of the dynamic behavior of next generation nuclear reactors is a fundamental aspect for safety and reliability assessments. Despite the growing performances of modern computers, the full solution of the neutron Boltzmann equation in the time domain is still an impracticable task, thus several approximate dynamic models have been proposed for the simulation of nuclear reactor transients; the quasi-static method represents the standard tool currently adopted for the space-time solution of neutron transport problems. All the practical applications of this method that have been proposed contain a major limit, consisting in the use of isotropic quantities, such as scalar fluxes and isotropic external neutron sources, being the only data structures available in most deterministic transport codes. The loss of the angular information produces both inaccuracies in the solution of the kinetic model and the inconsistency of the quasi-static method itself. The present paper is devoted to the implementation of a consistent quasi-static method. The computational platform developed by CEA in Cadarache has been used for the creation of a kinetic package to be coupled with the existing SNATCH solver, a discrete-ordinate multi-dimensional neutron transport solver, employed for the solution of the steady-state Boltzmann equation. The work aims at highlighting the effects of the angular treatment of the neutron flux on the transient analysis, comparing the results with those produced by the previous implementations of the quasi-static method. (author)

Calculation of neutron importance function in fissionable assemblies using Monte Carlo method

International Nuclear Information System (INIS)

Feghhi, S.A.H.; Shahriari, M.; Afarideh, H.

2007-01-01

The purpose of the present work is to develop an efficient solution method for the calculation of neutron importance function in fissionable assemblies for all criticality conditions, based on Monte Carlo calculations. The neutron importance function has an important role in perturbation theory and reactor dynamic calculations. Usually this function can be determined by calculating the adjoint flux while solving the adjoint weighted transport equation based on deterministic methods. However, in complex geometries these calculations are very complicated. In this article, considering the capabilities of MCNP code in solving problems with complex geometries and its closeness to physical concepts, a comprehensive method based on the physical concept of neutron importance has been introduced for calculating the neutron importance function in sub-critical, critical and super-critical conditions. For this propose a computer program has been developed. The results of the method have been benchmarked with ANISN code calculations in 1 and 2 group modes for simple geometries. The correctness of these results has been confirmed for all three criticality conditions. Finally, the efficiency of the method for complex geometries has been shown by the calculation of neutron importance in Miniature Neutron Source Reactor (MNSR) research reactor

Numerical functional integration method for studying the properties of the physical vacuum

International Nuclear Information System (INIS)

Lobanov, Yu.Yu.

1998-01-01

The new approach to investigate the physical vacuum in quantum theories including its nonperturbative topological structure is discussed. This approach is based on the representation of the matrix element of the evolution operator in Euclidean metrics in a form of the functional integral with a certain measure in the corresponding space and on the use of approximation formulas which we constructed for this kind of integral. No preliminary discretization of space and time is required, as well as no simplifying assumptions like semiclassical approximation, collective excitations, introduction of ''short-time'' propagators, etc. are necessary in this approach. The method allows to use the more preferable deterministic algorithms instead of the traditional stochastic technique. It has been proven that our approach has important advantages over the other known methods, including the higher efficiency of computations. Examples of application of the method to the numerical study of some potential nuclear models and to the computation of the topological susceptibility and the θ-vacua energy are presented. (author)

Approximation of the Monte Carlo Sampling Method for Reliability Analysis of Structures

Directory of Open Access Journals (Sweden)

Mahdi Shadab Far

2016-01-01

Full Text Available Structural load types, on the one hand, and structural capacity to withstand these loads, on the other hand, are of a probabilistic nature as they cannot be calculated and presented in a fully deterministic way. As such, the past few decades have witnessed the development of numerous probabilistic approaches towards the analysis and design of structures. Among the conventional methods used to assess structural reliability, the Monte Carlo sampling method has proved to be very convenient and efficient. However, it does suffer from certain disadvantages, the biggest one being the requirement of a very large number of samples to handle small probabilities, leading to a high computational cost. In this paper, a simple algorithm was proposed to estimate low failure probabilities using a small number of samples in conjunction with the Monte Carlo method. This revised approach was then presented in a step-by-step flowchart, for the purpose of easy programming and implementation.

Linear–Quadratic Mean-Field-Type Games: A Direct Method

Directory of Open Access Journals (Sweden)

Tyrone E. Duncan

2018-02-01

Full Text Available In this work, a multi-person mean-field-type game is formulated and solved that is described by a linear jump-diffusion system of mean-field type and a quadratic cost functional involving the second moments, the square of the expected value of the state, and the control actions of all decision-makers. We propose a direct method to solve the game, team, and bargaining problems. This solution approach does not require solving the Bellman–Kolmogorov equations or backward–forward stochastic differential equations of Pontryagin’s type. The proposed method can be easily implemented by beginners and engineers who are new to the emerging field of mean-field-type game theory. The optimal strategies for decision-makers are shown to be in a state-and-mean-field feedback form. The optimal strategies are given explicitly as a sum of the well-known linear state-feedback strategy for the associated deterministic linear–quadratic game problem and a mean-field feedback term. The equilibrium cost of the decision-makers are explicitly derived using a simple direct method. Moreover, the equilibrium cost is a weighted sum of the initial variance and an integral of a weighted variance of the diffusion and the jump process. Finally, the method is used to compute global optimum strategies as well as saddle point strategies and Nash bargaining solution in state-and-mean-field feedback form.

Matrix-based system reliability method and applications to bridge networks

International Nuclear Information System (INIS)

Kang, W.-H.; Song Junho; Gardoni, Paolo

2008-01-01

Using a matrix-based system reliability (MSR) method, one can estimate the probabilities of complex system events by simple matrix calculations. Unlike existing system reliability methods whose complexity depends highly on that of the system event, the MSR method describes any general system event in a simple matrix form and therefore provides a more convenient way of handling the system event and estimating its probability. Even in the case where one has incomplete information on the component probabilities and/or the statistical dependence thereof, the matrix-based framework enables us to estimate the narrowest bounds on the system failure probability by linear programming. This paper presents the MSR method and applies it to a transportation network consisting of bridge structures. The seismic failure probabilities of bridges are estimated by use of the predictive fragility curves developed by a Bayesian methodology based on experimental data and existing deterministic models of the seismic capacity and demand. Using the MSR method, the probability of disconnection between each city/county and a critical facility is estimated. The probability mass function of the number of failed bridges is computed as well. In order to quantify the relative importance of bridges, the MSR method is used to compute the conditional probabilities of bridge failures given that there is at least one city disconnected from the critical facility. The bounds on the probability of disconnection are also obtained for cases with incomplete information

CSL model checking of deterministic and stochastic Petri nets

NARCIS (Netherlands)

Martinez Verdugo, J.M.; Haverkort, Boudewijn R.H.M.; German, R.; Heindl, A.

2006-01-01

Deterministic and Stochastic Petri Nets (DSPNs) are a widely used high-level formalism for modeling discrete-event systems where events may occur either without consuming time, after a deterministic time, or after an exponentially distributed time. The underlying process dened by DSPNs, under

The cointegrated vector autoregressive model with general deterministic terms

DEFF Research Database (Denmark)

Johansen, Søren; Nielsen, Morten Ørregaard

2017-01-01

In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model X(t)=Z(t) Y(t), where Z(t) belongs to a large class...... of deterministic regressors and Y(t) is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended...... model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are X 2 -distributed....

The cointegrated vector autoregressive model with general deterministic terms

DEFF Research Database (Denmark)

Johansen, Søren; Nielsen, Morten Ørregaard

In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model X(t)= Z(t) + Y(t), where Z(t) belongs to a large class...... of deterministic regressors and Y(t) is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended...... model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are khi squared distributed....

A semi-Lagrangian transport method for kinetic problems with application to dense-to-dilute polydisperse reacting spray flows

Energy Technology Data Exchange (ETDEWEB)

Doisneau, François, E-mail: fdoisne@sandia.gov; Arienti, Marco, E-mail: marient@sandia.gov; Oefelein, Joseph C., E-mail: oefelei@sandia.gov

2017-01-15

For sprays, as described by a kinetic disperse phase model strongly coupled to the Navier–Stokes equations, the resolution strategy is constrained by accuracy objectives, robustness needs, and the computing architecture. In order to leverage the good properties of the Eulerian formalism, we introduce a deterministic particle-based numerical method to solve transport in physical space, which is simple to adapt to the many types of closures and moment systems. The method is inspired by the semi-Lagrangian schemes, developed for Gas Dynamics. We show how semi-Lagrangian formulations are relevant for a disperse phase far from equilibrium and where the particle–particle coupling barely influences the transport; i.e., when particle pressure is negligible. The particle behavior is indeed close to free streaming. The new method uses the assumption of parcel transport and avoids to compute fluxes and their limiters, which makes it robust. It is a deterministic resolution method so that it does not require efforts on statistical convergence, noise control, or post-processing. All couplings are done among data under the form of Eulerian fields, which allows one to use efficient algorithms and to anticipate the computational load. This makes the method both accurate and efficient in the context of parallel computing. After a complete verification of the new transport method on various academic test cases, we demonstrate the overall strategy's ability to solve a strongly-coupled liquid jet with fine spatial resolution and we apply it to the case of high-fidelity Large Eddy Simulation of a dense spray flow. A fuel spray is simulated after atomization at Diesel engine combustion chamber conditions. The large, parallel, strongly coupled computation proves the efficiency of the method for dense, polydisperse, reacting spray flows.

Novel Parallel Numerical Methods for Radiation and Neutron Transport

International Nuclear Information System (INIS)

Brown, P N

2001-01-01

In many of the multiphysics simulations performed at LLNL, transport calculations can take up 30 to 50% of the total run time. If Monte Carlo methods are used, the percentage can be as high as 80%. Thus, a significant core competence in the formulation, software implementation, and solution of the numerical problems arising in transport modeling is essential to Laboratory and DOE research. In this project, we worked on developing scalable solution methods for the equations that model the transport of photons and neutrons through materials. Our goal was to reduce the transport solve time in these simulations by means of more advanced numerical methods and their parallel implementations. These methods must be scalable, that is, the time to solution must remain constant as the problem size grows and additional computer resources are used. For iterative methods, scalability requires that (1) the number of iterations to reach convergence is independent of problem size, and (2) that the computational cost grows linearly with problem size. We focused on deterministic approaches to transport, building on our earlier work in which we performed a new, detailed analysis of some existing transport methods and developed new approaches. The Boltzmann equation (the underlying equation to be solved) and various solution methods have been developed over many years. Consequently, many laboratory codes are based on these methods, which are in some cases decades old. For the transport of x-rays through partially ionized plasmas in local thermodynamic equilibrium, the transport equation is coupled to nonlinear diffusion equations for the electron and ion temperatures via the highly nonlinear Planck function. We investigated the suitability of traditional-solution approaches to transport on terascale architectures and also designed new scalable algorithms; in some cases, we investigated hybrid approaches that combined both

The Global Optimal Algorithm of Reliable Path Finding Problem Based on Backtracking Method

Directory of Open Access Journals (Sweden)

Liang Shen

2017-01-01

Full Text Available There is a growing interest in finding a global optimal path in transportation networks particularly when the network suffers from unexpected disturbance. This paper studies the problem of finding a global optimal path to guarantee a given probability of arriving on time in a network with uncertainty, in which the travel time is stochastic instead of deterministic. Traditional path finding methods based on least expected travel time cannot capture the network user’s risk-taking behaviors in path finding. To overcome such limitation, the reliable path finding algorithms have been proposed but the convergence of global optimum is seldom addressed in the literature. This paper integrates the K-shortest path algorithm into Backtracking method to propose a new path finding algorithm under uncertainty. The global optimum of the proposed method can be guaranteed. Numerical examples are conducted to demonstrate the correctness and efficiency of the proposed algorithm.

Parametrical Method for Determining Optimal Ship Carrying Capacity and Performance of Handling Equipment

Directory of Open Access Journals (Sweden)

Michalski Jan P.

2016-04-01

Full Text Available The paper presents a method of evaluating the optimal value of the cargo ships deadweight and the coupled optimal value of cargo handling capacity. The method may be useful at the stage of establishing the main owners requirements concerning the ship design parameters as well as for choosing a proper second hand ship for a given transportation task. The deadweight and the capacity are determined on the basis of a selected economic measure of the transport effectiveness of ship – the Required Freight Rate. The mathematical model of the problem is of a deterministic character and the simplifying assumptions are justified for ships operating in the liner trade. The assumptions are so selected that solution of the problem is obtained in analytical closed form. The presented method can be useful for application in the preliminary ship design or in the simulation of pre-investment transportation task studies.

Adaptive algorithms for a self-shielding wavelet-based Galerkin method

International Nuclear Information System (INIS)

Fournier, D.; Le Tellier, R.

2009-01-01

The treatment of the energy variable in deterministic neutron transport methods is based on a multigroup discretization, considering the flux and cross-sections to be constant within a group. In this case, a self-shielding calculation is mandatory to correct sections of resonant isotopes. In this paper, a different approach based on a finite element discretization on a wavelet basis is used. We propose adaptive algorithms constructed from error estimates. Such an approach is applied to within-group scattering source iterations. A first implementation is presented in the special case of the fine structure equation for an infinite homogeneous medium. Extension to spatially-dependent cases is discussed. (authors)

Deterministic Safety Analysis for Nuclear Power Plants. Specific Safety Guide (Russian Edition)

International Nuclear Information System (INIS)

2014-01-01

The objective of this Safety Guide is to provide harmonized guidance to designers, operators, regulators and providers of technical support on deterministic safety analysis for nuclear power plants. It provides information on the utilization of the results of such analysis for safety and reliability improvements. The Safety Guide addresses conservative, best estimate and uncertainty evaluation approaches to deterministic safety analysis and is applicable to current and future designs. Contents: 1. Introduction; 2. Grouping of initiating events and associated transients relating to plant states; 3. Deterministic safety analysis and acceptance criteria; 4. Conservative deterministic safety analysis; 5. Best estimate plus uncertainty analysis; 6. Verification and validation of computer codes; 7. Relation of deterministic safety analysis to engineering aspects of safety and probabilistic safety analysis; 8. Application of deterministic safety analysis; 9. Source term evaluation for operational states and accident conditions; References

Activity modes selection for project crashing through deterministic simulation

Directory of Open Access Journals (Sweden)

Ashok Mohanty

2011-12-01

Full Text Available Purpose: The time-cost trade-off problem addressed by CPM-based analytical approaches, assume unlimited resources and the existence of a continuous time-cost function. However, given the discrete nature of most resources, the activities can often be crashed only stepwise. Activity crashing for discrete time-cost function is also known as the activity modes selection problem in the project management. This problem is known to be NP-hard. Sophisticated optimization techniques such as Dynamic Programming, Integer Programming, Genetic Algorithm, Ant Colony Optimization have been used for finding efficient solution to activity modes selection problem. The paper presents a simple method that can provide efficient solution to activity modes selection problem for project crashing.Design/methodology/approach: Simulation based method implemented on electronic spreadsheet to determine activity modes for project crashing. The method is illustrated with the help of an example.Findings: The paper shows that a simple approach based on simple heuristic and deterministic simulation can give good result comparable to sophisticated optimization techniques.Research limitations/implications: The simulation based crashing method presented in this paper is developed to return satisfactory solutions but not necessarily an optimal solution.Practical implications: The use of spreadsheets for solving the Management Science and Operations Research problems make the techniques more accessible to practitioners. Spreadsheets provide a natural interface for model building, are easy to use in terms of inputs, solutions and report generation, and allow users to perform what-if analysis.Originality/value: The paper presents the application of simulation implemented on a spreadsheet to determine efficient solution to discrete time cost tradeoff problem.

Reliability analysis of PWR thermohydraulic design by the Monte Carlo method

International Nuclear Information System (INIS)

Silva Junior, H.C. da; Berthoud, J.S.; Carajilescov, P.

1977-01-01

The operating power level of a PWR is limited by the occurence of DNB. Without affecting the safety and performance of the reactor, it is possible to admit failure of a certain number of core channels. The thermohydraulic design, however, is affect by a great number of uncertainties of deterministic or statistical nature. In the present work, the Monte Carlo method is applied to yield the probability that a number F of channels submitted to boiling crises will not exceed a number F* previously given. This probability is obtained as function of the reactor power level. (Author) [pt

A Deterministic Approach to Earthquake Prediction

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Vittorio Sgrigna

2012-01-01

Full Text Available The paper aims at giving suggestions for a deterministic approach to investigate possible earthquake prediction and warning. A fundamental contribution can come by observations and physical modeling of earthquake precursors aiming at seeing in perspective the phenomenon earthquake within the framework of a unified theory able to explain the causes of its genesis, and the dynamics, rheology, and microphysics of its preparation, occurrence, postseismic relaxation, and interseismic phases. Studies based on combined ground and space observations of earthquake precursors are essential to address the issue. Unfortunately, up to now, what is lacking is the demonstration of a causal relationship (with explained physical processes and looking for a correlation between data gathered simultaneously and continuously by space observations and ground-based measurements. In doing this, modern and/or new methods and technologies have to be adopted to try to solve the problem. Coordinated space- and ground-based observations imply available test sites on the Earth surface to correlate ground data, collected by appropriate networks of instruments, with space ones detected on board of Low-Earth-Orbit (LEO satellites. Moreover, a new strong theoretical scientific effort is necessary to try to understand the physics of the earthquake.

Deterministic dense coding with partially entangled states

Science.gov (United States)

Mozes, Shay; Oppenheim, Jonathan; Reznik, Benni

2005-01-01

The utilization of a d -level partially entangled state, shared by two parties wishing to communicate classical information without errors over a noiseless quantum channel, is discussed. We analytically construct deterministic dense coding schemes for certain classes of nonmaximally entangled states, and numerically obtain schemes in the general case. We study the dependency of the maximal alphabet size of such schemes on the partially entangled state shared by the two parties. Surprisingly, for d>2 it is possible to have deterministic dense coding with less than one ebit. In this case the number of alphabet letters that can be communicated by a single particle is between d and 2d . In general, we numerically find that the maximal alphabet size is any integer in the range [d,d2] with the possible exception of d2-1 . We also find that states with less entanglement can have a greater deterministic communication capacity than other more entangled states.

Development and Investigation of Reactivity Measurement Methods in Subcritical Cores

Energy Technology Data Exchange (ETDEWEB)

Wright, Johanna

2005-05-01

Subcriticality measurements during core loading and in future accelerator driven systems have a clear safety relevance. In this thesis two subcriticality methods are treated: the Feynman-alpha and the source modulation method. The Feynman-alpha method is a technique to determine the reactivity from the relative variance of the detector counts during a measurement period. The period length is varied to get the full time dependence of the variance-to-mean. The corresponding theoretical formula was known only with stationary sources. In this thesis, due to its relevance for novel reactivity measurement methods, the Feynman-alpha formulae for pulsed sources for both the stochastic and the deterministic cases are treated. Formulae neglecting as well as including the delayed neutrons are derived. The formulae neglecting delayed neutrons are experimentally verified with quite good agreement. The second reactivity measurement technique investigated in this thesis is the so-called source modulation technique. The theory of the method was elaborated on the assumption of point kinetics, but in practice the method will be applied by using the signal from a single local neutron detector. Applicability of the method therefore assumes point kinetic behaviour of the core. Hence, first the conditions of the point kinetic behaviour of subcritical cores was investigated. After that the performance of the source modulation technique in the general case as well as and in the limit of exact point kinetic behaviour was examined. We obtained the unexpected result that the method has a finite, non-negligible error even in the limit of point kinetic behaviour, and a substantial error in the operation range of future accelerator driven subcritical reactors (ADS). In practice therefore the method needs to be calibrated by some other method for on-line applications.

Development and Investigation of Reactivity Measurement Methods in Subcritical Cores

International Nuclear Information System (INIS)

Wright, Johanna

2005-05-01

Subcriticality measurements during core loading and in future accelerator driven systems have a clear safety relevance. In this thesis two subcriticality methods are treated: the Feynman-alpha and the source modulation method. The Feynman-alpha method is a technique to determine the reactivity from the relative variance of the detector counts during a measurement period. The period length is varied to get the full time dependence of the variance-to-mean. The corresponding theoretical formula was known only with stationary sources. In this thesis, due to its relevance for novel reactivity measurement methods, the Feynman-alpha formulae for pulsed sources for both the stochastic and the deterministic cases are treated. Formulae neglecting as well as including the delayed neutrons are derived. The formulae neglecting delayed neutrons are experimentally verified with quite good agreement. The second reactivity measurement technique investigated in this thesis is the so-called source modulation technique. The theory of the method was elaborated on the assumption of point kinetics, but in practice the method will be applied by using the signal from a single local neutron detector. Applicability of the method therefore assumes point kinetic behaviour of the core. Hence, first the conditions of the point kinetic behaviour of subcritical cores was investigated. After that the performance of the source modulation technique in the general case as well as and in the limit of exact point kinetic behaviour was examined. We obtained the unexpected result that the method has a finite, non-negligible error even in the limit of point kinetic behaviour, and a substantial error in the operation range of future accelerator driven subcritical reactors (ADS). In practice therefore the method needs to be calibrated by some other method for on-line applications

Optimal Deterministic Investment Strategies for Insurers

Directory of Open Access Journals (Sweden)

Ulrich Rieder

2013-11-01

Full Text Available We consider an insurance company whose risk reserve is given by a Brownian motion with drift and which is able to invest the money into a Black–Scholes financial market. As optimization criteria, we treat mean-variance problems, problems with other risk measures, exponential utility and the probability of ruin. Following recent research, we assume that investment strategies have to be deterministic. This leads to deterministic control problems, which are quite easy to solve. Moreover, it turns out that there are some interesting links between the optimal investment strategies of these problems. Finally, we also show that this approach works in the Lévy process framework.

Implementation of the Master Curve method in ProSACC

Energy Technology Data Exchange (ETDEWEB)

Feilitzen, Carl von; Sattari-Far, Iradj [Inspecta Technology AB, Stockholm (Sweden)

2012-03-15

Cleavage fracture toughness data display normally large amount of statistical scatter in the transition region. The cleavage toughness data in this region is specimen size-dependent, and should be treated statistically rather than deterministically. Master Curve methodology is a procedure for mechanical testing and statistical analysis of fracture toughness of ferritic steels in the transition region. The methodology accounts for temperature and size dependence of fracture toughness. Using the Master Curve methodology for evaluation of the fracture toughness in the transition region releases the overconservatism that has been observed in using the ASME-KIC curve. One main advantage of using the Master Curve methodology is possibility to use small Charpy-size specimens to determine fracture toughness. Detailed description of the Master Curve methodology is given by Sattari-Far and Wallin [2005). ProSACC is a suitable program in using for structural integrity assessments of components containing crack like defects and for defect tolerance analysis. The program gives possibilities to conduct assessments based on deterministic or probabilistic grounds. The method utilized in ProSACC is based on the R6-method developed at Nuclear Electric plc, Milne et al [1988]. The basic assumption in this method is that fracture in a cracked body can be described by two parameters Kr and Lr. The parameter Kr is the ratio between the stress intensity factor and the fracture toughness of the material. The parameter Lr is the ratio between applied load and the plastic limit load of the structure. The ProSACC assessment results are therefore highly dependent on the applied fracture toughness value in the assessment. In this work, the main options of the Master Curve methodology are implemented in the ProSACC program. Different options in evaluating Master Curve fracture toughness from standard fracture toughness testing data or impact testing data are considered. In addition, the

Implementation of the Master Curve method in ProSACC

International Nuclear Information System (INIS)

Feilitzen, Carl von; Sattari-Far, Iradj

2012-03-01

Cleavage fracture toughness data display normally large amount of statistical scatter in the transition region. The cleavage toughness data in this region is specimen size-dependent, and should be treated statistically rather than deterministically. Master Curve methodology is a procedure for mechanical testing and statistical analysis of fracture toughness of ferritic steels in the transition region. The methodology accounts for temperature and size dependence of fracture toughness. Using the Master Curve methodology for evaluation of the fracture toughness in the transition region releases the overconservatism that has been observed in using the ASME-KIC curve. One main advantage of using the Master Curve methodology is possibility to use small Charpy-size specimens to determine fracture toughness. Detailed description of the Master Curve methodology is given by Sattari-Far and Wallin [2005). ProSACC is a suitable program in using for structural integrity assessments of components containing crack like defects and for defect tolerance analysis. The program gives possibilities to conduct assessments based on deterministic or probabilistic grounds. The method utilized in ProSACC is based on the R6-method developed at Nuclear Electric plc, Milne et al [1988]. The basic assumption in this method is that fracture in a cracked body can be described by two parameters Kr and Lr. The parameter Kr is the ratio between the stress intensity factor and the fracture toughness of the material. The parameter Lr is the ratio between applied load and the plastic limit load of the structure. The ProSACC assessment results are therefore highly dependent on the applied fracture toughness value in the assessment. In this work, the main options of the Master Curve methodology are implemented in the ProSACC program. Different options in evaluating Master Curve fracture toughness from standard fracture toughness testing data or impact testing data are considered. In addition, the

Analysis of pinching in deterministic particle separation

Science.gov (United States)

Risbud, Sumedh; Luo, Mingxiang; Frechette, Joelle; Drazer, German

2011-11-01

We investigate the problem of spherical particles vertically settling parallel to Y-axis (under gravity), through a pinching gap created by an obstacle (spherical or cylindrical, center at the origin) and a wall (normal to X axis), to uncover the physics governing microfluidic separation techniques such as deterministic lateral displacement and pinched flow fractionation: (1) theoretically, by linearly superimposing the resistances offered by the wall and the obstacle separately, (2) computationally, using the lattice Boltzmann method for particulate systems and (3) experimentally, by conducting macroscopic experiments. Both, theory and simulations, show that for a given initial separation between the particle centre and the Y-axis, presence of a wall pushes the particles closer to the obstacle, than its absence. Experimentally, this is expected to result in an early onset of the short-range repulsive forces caused by solid-solid contact. We indeed observe such an early onset, which we quantify by measuring the asymmetry in the trajectories of the spherical particles around the obstacle. This work is partially supported by the National Science Foundation Grant Nos. CBET- 0731032, CMMI-0748094, and CBET-0954840.

Relationship of Deterministic Thinking With Loneliness and Depression in the Elderly

Directory of Open Access Journals (Sweden)

Mehdi Sharifi

2017-12-01

Conclusion According to the results, it can be said that deterministic thinking has a significant relationship with depression and sense of loneliness in older adults. So, deterministic thinking acts as a predictor of depression and sense of loneliness in older adults. Therefore, psychological interventions for challenging cognitive distortion of deterministic thinking and attention to mental health in older adult are very important. 

Neo-Deterministic and Probabilistic Seismic Hazard Assessments: a Comparative Analysis

Science.gov (United States)

Peresan, Antonella; Magrin, Andrea; Nekrasova, Anastasia; Kossobokov, Vladimir; Panza, Giuliano F.

2016-04-01

Objective testing is the key issue towards any reliable seismic hazard assessment (SHA). Different earthquake hazard maps must demonstrate their capability in anticipating ground shaking from future strong earthquakes before an appropriate use for different purposes - such as engineering design, insurance, and emergency management. Quantitative assessment of maps performances is an essential step also in scientific process of their revision and possible improvement. Cross-checking of probabilistic models with available observations and independent physics based models is recognized as major validation procedure. The existing maps from the classical probabilistic seismic hazard analysis (PSHA), as well as those from the neo-deterministic analysis (NDSHA), which have been already developed for several regions worldwide (including Italy, India and North Africa), are considered to exemplify the possibilities of the cross-comparative analysis in spotting out limits and advantages of different methods. Where the data permit, a comparative analysis versus the documented seismic activity observed in reality is carried out, showing how available observations about past earthquakes can contribute to assess performances of the different methods. Neo-deterministic refers to a scenario-based approach, which allows for consideration of a wide range of possible earthquake sources as the starting point for scenarios constructed via full waveforms modeling. The method does not make use of empirical attenuation models (i.e. Ground Motion Prediction Equations, GMPE) and naturally supplies realistic time series of ground shaking (i.e. complete synthetic seismograms), readily applicable to complete engineering analysis and other mitigation actions. The standard NDSHA maps provide reliable envelope estimates of maximum seismic ground motion from a wide set of possible scenario earthquakes, including the largest deterministically or historically defined credible earthquake. In addition

Nuclear data uncertainties propagation methods in Boltzmann/Bateman coupled problems: Application to reactivity in MTR

International Nuclear Information System (INIS)

Frosio, Thomas; Bonaccorsi, Thomas; Blaise, Patrick

2016-01-01

Highlights: • Hybrid methods are developed for uncertainty propagation. • These methods take into account the flux perturbation in the coupled problem. • We show that OAT and MC methods give coherent results, except for Pearson correlations. • Local sensitivity analysis is performed. - Abstract: A novel method has been developed to calculate sensitivity coefficients in coupled Boltzmann/Bateman problem for nuclear data (ND) uncertainties propagation on the reactivity. Different uncertainty propagation methodologies, such as One-At-a-Time (OAT) and hybrid Monte-Carlo/deterministic methods have been tested and are discussed on an actual example of ND uncertainty problem on a Material Testing Reactor (MTR) benchmark. Those methods, unlike total Monte Carlo (MC) sampling for uncertainty propagation and quantification (UQ), allow obtaining sensitivity coefficients, as well as Bravais–Pearson correlations values between Boltzmann and Bateman, during the depletion calculation for global neutronics parameters such as the effective multiplication coefficient. The methodologies are compared to a pure MC sampling method, usually considered as the “reference” method. It is shown that methodologies can seriously underestimate propagated variances, when Bravais–Pearson correlations on ND are not taken into account in the UQ process.

Identification of metabolic system parameters using global optimization methods

Directory of Open Access Journals (Sweden)

Gatzke Edward P

2006-01-01

Full Text Available Abstract Background The problem of estimating the parameters of dynamic models of complex biological systems from time series data is becoming increasingly important. Methods and results Particular consideration is given to metabolic systems that are formulated as Generalized Mass Action (GMA models. The estimation problem is posed as a global optimization task, for which novel techniques can be applied to determine the best set of parameter values given the measured responses of the biological system. The challenge is that this task is nonconvex. Nonetheless, deterministic optimization techniques can be used to find a global solution that best reconciles the model parameters and measurements. Specifically, the paper employs branch-and-bound principles to identify the best set of model parameters from observed time course data and illustrates this method with an existing model of the fermentation pathway in Saccharomyces cerevisiae. This is a relatively simple yet representative system with five dependent states and a total of 19 unknown parameters of which the values are to be determined. Conclusion The efficacy of the branch-and-reduce algorithm is illustrated by the S. cerevisiae example. The method described in this paper is likely to be widely applicable in the dynamic modeling of metabolic networks.

Novel hybrid Monte Carlo/deterministic technique for shutdown dose rate analyses of fusion energy systems

International Nuclear Information System (INIS)

Ibrahim, Ahmad M.; Peplow, Douglas E.; Peterson, Joshua L.; Grove, Robert E.

2014-01-01

Highlights: •Develop the novel Multi-Step CADIS (MS-CADIS) hybrid Monte Carlo/deterministic method for multi-step shielding analyses. •Accurately calculate shutdown dose rates using full-scale Monte Carlo models of fusion energy systems. •Demonstrate the dramatic efficiency improvement of the MS-CADIS method for the rigorous two step calculations of the shutdown dose rate in fusion reactors. -- Abstract: The rigorous 2-step (R2S) computational system uses three-dimensional Monte Carlo transport simulations to calculate the shutdown dose rate (SDDR) in fusion reactors. Accurate full-scale R2S calculations are impractical in fusion reactors because they require calculating space- and energy-dependent neutron fluxes everywhere inside the reactor. The use of global Monte Carlo variance reduction techniques was suggested for accelerating the R2S neutron transport calculation. However, the prohibitive computational costs of these approaches, which increase with the problem size and amount of shielding materials, inhibit their ability to accurately predict the SDDR in fusion energy systems using full-scale modeling of an entire fusion plant. This paper describes a novel hybrid Monte Carlo/deterministic methodology that uses the Consistent Adjoint Driven Importance Sampling (CADIS) method but focuses on multi-step shielding calculations. The Multi-Step CADIS (MS-CADIS) methodology speeds up the R2S neutron Monte Carlo calculation using an importance function that represents the neutron importance to the final SDDR. Using a simplified example, preliminary results showed that the use of MS-CADIS enhanced the efficiency of the neutron Monte Carlo simulation of an SDDR calculation by a factor of 550 compared to standard global variance reduction techniques, and that the efficiency enhancement compared to analog Monte Carlo is higher than a factor of 10,000

Deterministic influences exceed dispersal effects on hydrologically-connected microbiomes: Deterministic assembly of hyporheic microbiomes

Energy Technology Data Exchange (ETDEWEB)

Graham, Emily B. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Crump, Alex R. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Resch, Charles T. [Geochemistry Department, Pacific Northwest National Laboratory, Richland WA USA; Fansler, Sarah [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Arntzen, Evan [Environmental Compliance and Emergency Preparation, Pacific Northwest National Laboratory, Richland WA USA; Kennedy, David W. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Fredrickson, Jim K. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Stegen, James C. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA

2017-03-28

Subsurface zones of groundwater and surface water mixing (hyporheic zones) are regions of enhanced rates of biogeochemical cycling, yet ecological processes governing hyporheic microbiome composition and function through space and time remain unknown. We sampled attached and planktonic microbiomes in the Columbia River hyporheic zone across seasonal hydrologic change, and employed statistical null models to infer mechanisms generating temporal changes in microbiomes within three hydrologically-connected, physicochemically-distinct geographic zones (inland, nearshore, river). We reveal that microbiomes remain dissimilar through time across all zones and habitat types (attached vs. planktonic) and that deterministic assembly processes regulate microbiome composition in all data subsets. The consistent presence of heterotrophic taxa and members of the Planctomycetes-Verrucomicrobia-Chlamydiae (PVC) superphylum nonetheless suggests common selective pressures for physiologies represented in these groups. Further, co-occurrence networks were used to provide insight into taxa most affected by deterministic assembly processes. We identified network clusters to represent groups of organisms that correlated with seasonal and physicochemical change. Extended network analyses identified keystone taxa within each cluster that we propose are central in microbiome composition and function. Finally, the abundance of one network cluster of nearshore organisms exhibited a seasonal shift from heterotrophic to autotrophic metabolisms and correlated with microbial metabolism, possibly indicating an ecological role for these organisms as foundational species in driving biogeochemical reactions within the hyporheic zone. Taken together, our research demonstrates a predominant role for deterministic assembly across highly-connected environments and provides insight into niche dynamics associated with seasonal changes in hyporheic microbiome composition and metabolism.

A new Monte Carlo method for neutron noise calculations in the frequency domain

International Nuclear Information System (INIS)

Rouchon, Amélie; Zoia, Andrea; Sanchez, Richard

2017-01-01

Neutron noise equations, which are obtained by assuming small perturbations of macroscopic cross sections around a steady-state neutron field and by subsequently taking the Fourier transform in the frequency domain, have been usually solved by analytical techniques or by resorting to diffusion theory. A stochastic approach has been recently proposed in the literature by using particles with complex-valued weights and by applying a weight cancellation technique. We develop a new Monte Carlo algorithm that solves the transport neutron noise equations in the frequency domain. The stochastic method presented here relies on a modified collision operator and does not need any weight cancellation technique. In this paper, both Monte Carlo methods are compared with deterministic methods (diffusion in a slab geometry and transport in a simplified rod model) for several noise frequencies and for isotropic and anisotropic noise sources. Our stochastic method shows better performances in the frequency region of interest and is easier to implement because it relies upon the conventional algorithm for fixed-source problems.

Efficient Deterministic Finite Automata Minimization Based on Backward Depth Information.

Science.gov (United States)

Liu, Desheng; Huang, Zhiping; Zhang, Yimeng; Guo, Xiaojun; Su, Shaojing

2016-01-01

Obtaining a minimal automaton is a fundamental issue in the theory and practical implementation of deterministic finite automatons (DFAs). A minimization algorithm is presented in this paper that consists of two main phases. In the first phase, the backward depth information is built, and the state set of the DFA is partitioned into many blocks. In the second phase, the state set is refined using a hash table. The minimization algorithm has a lower time complexity O(n) than a naive comparison of transitions O(n2). Few states need to be refined by the hash table, because most states have been partitioned by the backward depth information in the coarse partition. This method achieves greater generality than previous methods because building the backward depth information is independent of the topological complexity of the DFA. The proposed algorithm can be applied not only to the minimization of acyclic automata or simple cyclic automata, but also to automata with high topological complexity. Overall, the proposal has three advantages: lower time complexity, greater generality, and scalability. A comparison to Hopcroft's algorithm demonstrates experimentally that the algorithm runs faster than traditional algorithms.

Understanding advanced statistical methods

CERN Document Server

Westfall, Peter

2013-01-01

Introduction: Probability, Statistics, and ScienceReality, Nature, Science, and ModelsStatistical Processes: Nature, Design and Measurement, and DataModelsDeterministic ModelsVariabilityParametersPurely Probabilistic Statistical ModelsStatistical Models with Both Deterministic and Probabilistic ComponentsStatistical InferenceGood and Bad ModelsUses of Probability ModelsRandom Variables and Their Probability DistributionsIntroductionTypes of Random Variables: Nominal, Ordinal, and ContinuousDiscrete Probability Distribution FunctionsContinuous Probability Distribution FunctionsSome Calculus-Derivatives and Least SquaresMore Calculus-Integrals and Cumulative Distribution FunctionsProbability Calculation and SimulationIntroductionAnalytic Calculations, Discrete and Continuous CasesSimulation-Based ApproximationGenerating Random NumbersIdentifying DistributionsIntroductionIdentifying Distributions from Theory AloneUsing Data: Estimating Distributions via the HistogramQuantiles: Theoretical and Data-Based Estimate...

Determination of the double angular and energy differential gamma-ray albedo by using the Monte Carlo method

International Nuclear Information System (INIS)

Miss, J.

1998-06-01

The goal of this thesis was to study comprehensively photons energy and angular distributions of backscattered radiations. In general, this relation is described by the concept to the backscattered factor or doubly differential albedo. This concept is useful to study the particle propagation into the air space by simple or multiple reflections on materials There are two principal treatments to solve numerically this problem: the deterministic and probabilistic methods. We showed that deterministic methods furnish unsatisfactory results: that's why we choice to develop a new gamma ray albedo estimator in the code TRIPOLI14 (three dimensional Monte Carlo code). So, we have been able to compute an important data base of doubly differential albedos. A physical analysis of these data showed that albedos can be simply described by parameter functions. These parameters were obtained by fitting the albedos of the data base over a complete range of incident and reflected energy and direction. So, we produced a very smaller data base of functions coefficients, instead of storing all the values of the doubly differential spectrum. It is so easy to make every albedo by linear interpolations on the coefficient of the new library. (author)

Deterministic hydrodynamics: Taking blood apart

Science.gov (United States)

Davis, John A.; Inglis, David W.; Morton, Keith J.; Lawrence, David A.; Huang, Lotien R.; Chou, Stephen Y.; Sturm, James C.; Austin, Robert H.

2006-10-01

We show the fractionation of whole blood components and isolation of blood plasma with no dilution by using a continuous-flow deterministic array that separates blood components by their hydrodynamic size, independent of their mass. We use the technology we developed of deterministic arrays which separate white blood cells, red blood cells, and platelets from blood plasma at flow velocities of 1,000 μm/sec and volume rates up to 1 μl/min. We verified by flow cytometry that an array using focused injection removed 100% of the lymphocytes and monocytes from the main red blood cell and platelet stream. Using a second design, we demonstrated the separation of blood plasma from the blood cells (white, red, and platelets) with virtually no dilution of the plasma and no cellular contamination of the plasma. cells | plasma | separation | microfabrication

Aboveground and belowground arthropods experience different relative influences of stochastic versus deterministic community assembly processes following disturbance

Directory of Open Access Journals (Sweden)

Scott Ferrenberg

2016-10-01

Full Text Available Background Understanding patterns of biodiversity is a longstanding challenge in ecology. Similar to other biotic groups, arthropod community structure can be shaped by deterministic and stochastic processes, with limited understanding of what moderates the relative influence of these processes. Disturbances have been noted to alter the relative influence of deterministic and stochastic processes on community assembly in various study systems, implicating ecological disturbances as a potential moderator of these forces. Methods Using a disturbance gradient along a 5-year chronosequence of insect-induced tree mortality in a subalpine forest of the southern Rocky Mountains, Colorado, USA, we examined changes in community structure and relative influences of deterministic and stochastic processes in the assembly of aboveground (surface and litter-active species and belowground (species active in organic and mineral soil layers arthropod communities. Arthropods were sampled for all years of the chronosequence via pitfall traps (aboveground community and modified Winkler funnels (belowground community and sorted to morphospecies. Community structure of both communities were assessed via comparisons of morphospecies abundance, diversity, and composition. Assembly processes were inferred from a mixture of linear models and matrix correlations testing for community associations with environmental properties, and from null-deviation models comparing observed vs. expected levels of species turnover (Beta diversity among samples. Results Tree mortality altered community structure in both aboveground and belowground arthropod communities, but null models suggested that aboveground communities experienced greater relative influences of deterministic processes, while the relative influence of stochastic processes increased for belowground communities. Additionally, Mantel tests and linear regression models revealed significant associations between the

Aboveground and belowground arthropods experience different relative influences of stochastic versus deterministic community assembly processes following disturbance

Science.gov (United States)

Martinez, Alexander S.; Faist, Akasha M.

2016-01-01

Background Understanding patterns of biodiversity is a longstanding challenge in ecology. Similar to other biotic groups, arthropod community structure can be shaped by deterministic and stochastic processes, with limited understanding of what moderates the relative influence of these processes. Disturbances have been noted to alter the relative influence of deterministic and stochastic processes on community assembly in various study systems, implicating ecological disturbances as a potential moderator of these forces. Methods Using a disturbance gradient along a 5-year chronosequence of insect-induced tree mortality in a subalpine forest of the southern Rocky Mountains, Colorado, USA, we examined changes in community structure and relative influences of deterministic and stochastic processes in the assembly of aboveground (surface and litter-active species) and belowground (species active in organic and mineral soil layers) arthropod communities. Arthropods were sampled for all years of the chronosequence via pitfall traps (aboveground community) and modified Winkler funnels (belowground community) and sorted to morphospecies. Community structure of both communities were assessed via comparisons of morphospecies abundance, diversity, and composition. Assembly processes were inferred from a mixture of linear models and matrix correlations testing for community associations with environmental properties, and from null-deviation models comparing observed vs. expected levels of species turnover (Beta diversity) among samples. Results Tree mortality altered community structure in both aboveground and belowground arthropod communities, but null models suggested that aboveground communities experienced greater relative influences of deterministic processes, while the relative influence of stochastic processes increased for belowground communities. Additionally, Mantel tests and linear regression models revealed significant associations between the aboveground arthropod

A probabilistic design method for LMFBR fuel rods

International Nuclear Information System (INIS)

Peck, S.O.; Lovejoy, W.S.

1977-01-01

Fuel rod performance analyses for design purposes are dependent upon material properties, dimensions, and loads that are statistical in nature. Conventional design practice accounts for the uncertainties in relevant parameters by designing to a 'safety factor', set so as to assure safe operation. Arbitrary assignment of these safety factors, based upon a number of 'worst case' assumptions, may result in costly over-design. Probabilistic design methods provide a systematic way to reflect the uncertainties in design parameters. PECS-III is a computer code which employs Monte Carlo techniques to generate the probability density and distribution functions for time-to-failure and cumulative damage for sealed plenum LMFBR fuel rods on a single rod or whole core basis. In Monte Carlo analyses, a deterministic model (that maps single-valued inputs into single-valued outputs) is coupled to a statistical 'driver'. Uncertainties in the input are reflected by assigning probability densities to the input parameters. Dependent input variables are considered multivariate normal. Independent input variables may be arbitrarily distributed. Sample values are drawn from these input densities, and a complete analysis is done by the deterministic model to generate a sample point in the output distribution. This process is repeated many times, and the number of times each output value occurs is accumulated. The probability that some measure of rod performance will fall within given limits is estimated by the relative frequency with which the Monte Carlo samples fall within tho

Hybrid Methods for Muon Accelerator Simulations with Ionization Cooling

Energy Technology Data Exchange (ETDEWEB)

Kunz, Josiah [Anderson U.; Snopok, Pavel [Fermilab; Berz, Martin [Michigan State U.; Makino, Kyoko [Michigan State U.

2018-03-28

Muon ionization cooling involves passing particles through solid or liquid absorbers. Careful simulations are required to design muon cooling channels. New features have been developed for inclusion in the transfer map code COSY Infinity to follow the distribution of charged particles through matter. To study the passage of muons through material, the transfer map approach alone is not sufficient. The interplay of beam optics and atomic processes must be studied by a hybrid transfer map--Monte-Carlo approach in which transfer map methods describe the deterministic behavior of the particles, and Monte-Carlo methods are used to provide corrections accounting for the stochastic nature of scattering and straggling of particles. The advantage of the new approach is that the vast majority of the dynamics are represented by fast application of the high-order transfer map of an entire element and accumulated stochastic effects. The gains in speed are expected to simplify the optimization of cooling channels which is usually computationally demanding. Progress on the development of the required algorithms and their application to modeling muon ionization cooling channels is reported.

Safety assessment of a shallow foundation using the random finite element method

Science.gov (United States)

Zaskórski, Łukasz; Puła, Wojciech

2015-04-01

A complex structure of soil and its random character are reasons why soil modeling is a cumbersome task. Heterogeneity of soil has to be considered even within a homogenous layer of soil. Therefore an estimation of shear strength parameters of soil for the purposes of a geotechnical analysis causes many problems. In applicable standards (Eurocode 7) there is not presented any explicit method of an evaluation of characteristic values of soil parameters. Only general guidelines can be found how these values should be estimated. Hence many approaches of an assessment of characteristic values of soil parameters are presented in literature and can be applied in practice. In this paper, the reliability assessment of a shallow strip footing was conducted using a reliability index β. Therefore some approaches of an estimation of characteristic values of soil properties were compared by evaluating values of reliability index β which can be achieved by applying each of them. Method of Orr and Breysse, Duncan's method, Schneider's method, Schneider's method concerning influence of fluctuation scales and method included in Eurocode 7 were examined. Design values of the bearing capacity based on these approaches were referred to the stochastic bearing capacity estimated by the random finite element method (RFEM). Design values of the bearing capacity were conducted for various widths and depths of a foundation in conjunction with design approaches DA defined in Eurocode. RFEM was presented by Griffiths and Fenton (1993). It combines deterministic finite element method, random field theory and Monte Carlo simulations. Random field theory allows to consider a random character of soil parameters within a homogenous layer of soil. For this purpose a soil property is considered as a separate random variable in every element of a mesh in the finite element method with proper correlation structure between points of given area. RFEM was applied to estimate which theoretical

A Comparative Study on the Refueling Simulation Method for a CANDU Reactor

Energy Technology Data Exchange (ETDEWEB)

Do, Quang Binh; Choi, Hang Bok; Roh, Gyu Hong [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

2006-07-01

The Canada deuterium uranium (CANDU) reactor calculation is typically performed by the RFSP code to obtain the power distribution upon a refueling. In order to assess the equilibrium behavior of the CANDU reactor, a few methods were suggested for a selection of the refueling channel. For example, an automatic refueling channel selection method (AUTOREFUEL) and a deterministic method (GENOVA) were developed, which were based on a reactor's operation experience and the generalized perturbation theory, respectively. Both programs were designed to keep the zone controller unit (ZCU) water level within a reasonable range during a continuous refueling simulation. However, a global optimization of the refueling simulation, that includes constraints on the discharge burn-up, maximum channel power (MCP), maximum bundle power (MBP), channel power peaking factor (CPPF) and the ZCU water level, was not achieved. In this study, an evolutionary algorithm, which is indeed a hybrid method based on the genetic algorithm, the elitism strategy and the heuristic rules for a multi-cycle and multi-objective optimization of the refueling simulation has been developed for the CANDU reactor. This paper presents the optimization model of the genetic algorithm and compares the results with those obtained by other simulation methods.

Processing multiphoton states through operation on a single photon: Methods and applications

International Nuclear Information System (INIS)

Lin Qing; He Bing; Bergou, Janos A.; Ren, Yuhang

2009-01-01

Multiphoton states are widely applied in quantum information technology. By the methods presented in this paper, the structure of a multiphoton state in the form of multiple single-photon qubit products can be mapped to a single-photon qudit, which could also be in a separable product with other photons. This makes possible the manipulation of such multiphoton states by processing single-photon states. The optical realization of unknown qubit discrimination [B. He, J. A. Bergou, and Y.-H. Ren, Phys. Rev. A 76, 032301 (2007)] is simplified with the transformation methods. Another application is the construction of quantum logic gates, where the inverse transformations back to the input state spaces are also necessary. We especially show that the modified setups to implement the transformations can realize the deterministic multicontrol gates (including Toffoli gate) operating directly on the products of single-photon qubits.

Performance of particle in cell methods on highly concurrent computational architectures

International Nuclear Information System (INIS)

Adams, M.F.; Ethier, S.; Wichmann, N.

2009-01-01

Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson's equation or more generally Maxwell's equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores.

Performance of particle in cell methods on highly concurrent computational architectures

International Nuclear Information System (INIS)

Adams, M F; Ethier, S; Wichmann, N

2007-01-01

Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson's equation or more generally Maxwell's equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores

Chaos emerging in soil failure patterns observed during tillage: Normalized deterministic nonlinear prediction (NDNP) and its application.

Science.gov (United States)

Sakai, Kenshi; Upadhyaya, Shrinivasa K; Andrade-Sanchez, Pedro; Sviridova, Nina V

2017-03-01

Real-world processes are often combinations of deterministic and stochastic processes. Soil failure observed during farm tillage is one example of this phenomenon. In this paper, we investigated the nonlinear features of soil failure patterns in a farm tillage process. We demonstrate emerging determinism in soil failure patterns from stochastic processes under specific soil conditions. We normalized the deterministic nonlinear prediction considering autocorrelation and propose it as a robust way of extracting a nonlinear dynamical system from noise contaminated motion. Soil is a typical granular material. The results obtained here are expected to be applicable to granular materials in general. From a global scale to nano scale, the granular material is featured in seismology, geotechnology, soil mechanics, and particle technology. The results and discussions presented here are applicable in these wide research areas. The proposed method and our findings are useful with respect to the application of nonlinear dynamics to investigate complex motions generated from granular materials.

Evaluation of methods used for the direct generation of response spectra

International Nuclear Information System (INIS)

Mayers, R.L.; Muraki, T.; Jones, L.R.; Donikian, R.

1983-01-01

The paper presents an alternate methodology by which seismic in-structure response spectra may be generated directly from either ground or floor excitation spectra. The method is based upon stochastic concepts and utilizes the modal superposition solution. The philosophy of the method is based upon the notion that the evaluation of 'peak' response in uncertain excitation environments is only meaningful in a probabilistic sense. This interpretation of response spectra facilitates the generation of in-structure spectra for any non-exceedance probability (NEP). The method is validated by comparisons with a set of deterministic time-history analyses with three example models: an eleven-story building model, a containment structure stick model, and a floor mounted control panel, subjected to ten input spectrum compatible acceleration time-histories. A significant finding resulting from these examples is that the time-history method portrayed substantial variation in the resulting in-structure spectra, and therefore is unreliable for the generation of spectra. It is shown that the average of the time-history generated spectra can be estimated by the direct generation procedure, and reliable spectra may be generated for 85 NEP levels. The methodology presented herein is shown to be valid for both primary and secondary systems. Also included in the paper, is a review of the stochastic methods proposed by Singh and Der Kiureghian et. al., and the Fourier transform method proposed by Scanlan et al. (orig./HP)

Deterministic and stochastic CTMC models from Zika disease transmission

Science.gov (United States)

Zevika, Mona; Soewono, Edy

2018-03-01

Zika infection is one of the most important mosquito-borne diseases in the world. Zika virus (ZIKV) is transmitted by many Aedes-type mosquitoes including Aedes aegypti. Pregnant women with the Zika virus are at risk of having a fetus or infant with a congenital defect and suffering from microcephaly. Here, we formulate a Zika disease transmission model using two approaches, a deterministic model and a continuous-time Markov chain stochastic model. The basic reproduction ratio is constructed from a deterministic model. Meanwhile, the CTMC stochastic model yields an estimate of the probability of extinction and outbreaks of Zika disease. Dynamical simulations and analysis of the disease transmission are shown for the deterministic and stochastic models.

Multi-Index Monte Carlo and stochastic collocation methods for random PDEs

KAUST Repository

Nobile, Fabio; Haji Ali, Abdul Lateef; Tamellini, Lorenzo; Tempone, Raul

2016-01-01

In this talk we consider the problem of computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a finite or countable sequence of terms in a suitable expansion. We describe and analyze a Multi-Index Monte Carlo (MIMC) and a Multi-Index Stochastic Collocation method (MISC). the former is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using firstorder differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2). On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that in the optimal case the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally effective. We finally show the effectiveness of MIMC and MISC with some computational tests, including tests with a infinite countable number of random parameters.

Multi-Index Monte Carlo and stochastic collocation methods for random PDEs

KAUST Repository

Nobile, Fabio

2016-01-09

In this talk we consider the problem of computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a finite or countable sequence of terms in a suitable expansion. We describe and analyze a Multi-Index Monte Carlo (MIMC) and a Multi-Index Stochastic Collocation method (MISC). the former is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using firstorder differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2). On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that in the optimal case the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally effective. We finally show the effectiveness of MIMC and MISC with some computational tests, including tests with a infinite countable number of random parameters.

Simplified Probabilistic Analysis of Settlement of Cyclically Loaded Soil Stratum by Point Estimate Method

Science.gov (United States)

Przewłócki, Jarosław; Górski, Jarosław; Świdziński, Waldemar

2016-12-01

The paper deals with the probabilistic analysis of the settlement of a non-cohesive soil layer subjected to cyclic loading. Originally, the settlement assessment is based on a deterministic compaction model, which requires integration of a set of differential equations. However, with the use of the Bessel functions, the settlement of a soil stratum can be calculated by a simplified algorithm. The compaction model parameters were determined for soil samples taken from subsoil near the Izmit Bay, Turkey. The computations were performed for various sets of random variables. The point estimate method was applied, and the results were verified by the Monte Carlo method. The outcome leads to a conclusion that can be useful in the prediction of soil settlement under seismic loading.

ICRP (1991) and deterministic effects

International Nuclear Information System (INIS)

Mole, R.H.

1992-01-01

A critical review of ICRP Publication 60 (1991) shows that considerable revisions are needed in both language and thinking about deterministic effects (DE). ICRP (1991) makes a welcome and clear distinction between change, caused by irradiation; damage, some degree of deleterious change, for example to cells, but not necessarily deleterious to the exposed individual; harm, clinically observable deleterious effects expressed in individuals or their descendants; and detriment, a complex concept combining the probability, severity and time of expression of harm (para42). (All added emphases come from the author.) Unfortunately these distinctions are not carried through into the discussion of deterministic effects (DE) and two important terms are left undefined. Presumably effect may refer to change, damage, harm or detriment, according to context. Clinically observable is also undefined although its meaning is crucial to any consideration of DE since DE are defined as causing observable harm (para 20). (Author)

Reliability Estimation of the Pultrusion Process Using the First-Order Reliability Method (FORM)

DEFF Research Database (Denmark)

Baran, Ismet; Tutum, Cem Celal; Hattel, Jesper Henri

2013-01-01

In the present study the reliability estimation of the pultrusion process of a flat plate is analyzed by using the first order reliability method (FORM). The implementation of the numerical process model is validated by comparing the deterministic temperature and cure degree profiles...... with corresponding analyses in the literature. The centerline degree of cure at the exit (CDOCE) being less than a critical value and the maximum composite temperature (Tmax) during the process being greater than a critical temperature are selected as the limit state functions (LSFs) for the FORM. The cumulative...

ADAPTIVE METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS VIA NATURAL EMBEDDINGS AND REJECTION SAMPLING WITH MEMORY.

Science.gov (United States)

Rackauckas, Christopher; Nie, Qing

2017-01-01

Adaptive time-stepping with high-order embedded Runge-Kutta pairs and rejection sampling provides efficient approaches for solving differential equations. While many such methods exist for solving deterministic systems, little progress has been made for stochastic variants. One challenge in developing adaptive methods for stochastic differential equations (SDEs) is the construction of embedded schemes with direct error estimates. We present a new class of embedded stochastic Runge-Kutta (SRK) methods with strong order 1.5 which have a natural embedding of strong order 1.0 methods. This allows for the derivation of an error estimate which requires no additional function evaluations. Next we derive a general method to reject the time steps without losing information about the future Brownian path termed Rejection Sampling with Memory (RSwM). This method utilizes a stack data structure to do rejection sampling, costing only a few floating point calculations. We show numerically that the methods generate statistically-correct and tolerance-controlled solutions. Lastly, we show that this form of adaptivity can be applied to systems of equations, and demonstrate that it solves a stiff biological model 12.28x faster than common fixed timestep algorithms. Our approach only requires the solution to a bridging problem and thus lends itself to natural generalizations beyond SDEs.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas

2017-12-27

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas; Richtarik, Peter

2017-01-01

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Parameter estimation for stiff deterministic dynamical systems via ensemble Kalman filter

International Nuclear Information System (INIS)

Arnold, Andrea; Calvetti, Daniela; Somersalo, Erkki

2014-01-01

A commonly encountered problem in numerous areas of applications is to estimate the unknown coefficients of a dynamical system from direct or indirect observations at discrete times of some of the components of the state vector. A related problem is to estimate unobserved components of the state. An egregious example of such a problem is provided by metabolic models, in which the numerous model parameters and the concentrations of the metabolites in tissue are to be estimated from concentration data in the blood. A popular method for addressing similar questions in stochastic and turbulent dynamics is the ensemble Kalman filter (EnKF), a particle-based filtering method that generalizes classical Kalman filtering. In this work, we adapt the EnKF algorithm for deterministic systems in which the numerical approximation error is interpreted as a stochastic drift with variance based on classical error estimates of numerical integrators. This approach, which is particularly suitable for stiff systems where the stiffness may depend on the parameters, allows us to effectively exploit the parallel nature of particle methods. Moreover, we demonstrate how spatial prior information about the state vector, which helps the stability of the computed solution, can be incorporated into the filter. The viability of the approach is shown by computed examples, including a metabolic system modeling an ischemic episode in skeletal muscle, with a high number of unknown parameters. (paper)

Bayesian flood forecasting methods: A review

Science.gov (United States)

Han, Shasha; Coulibaly, Paulin

2017-08-01

Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been

Cryptology transmitted message protection from deterministic chaos up to optical vortices

CERN Document Server

Izmailov, Igor; Romanov, Ilia; Smolskiy, Sergey

2016-01-01

This book presents methods to improve information security for protected communication. It combines and applies interdisciplinary scientific engineering concepts, including cryptography, chaos theory, nonlinear and singular optics, radio-electronics and self-changing artificial systems. It also introduces additional ways to improve information security using optical vortices as information carriers and self-controlled nonlinearity, with nonlinearity playing a key "evolving" role. The proposed solutions allow the universal phenomenon of deterministic chaos to be discussed in the context of information security problems on the basis of examples of both electronic and optical systems. Further, the book presents the vortex detector and communication systems and describes mathematical models of the chaos oscillator as a coder in the synchronous chaotic communication and appropriate decoders, demonstrating their efficiency both analytically and experimentally. Lastly it discusses the cryptologic features of analyze...

Charge sharing in multi-electrode devices for deterministic doping studied by IBIC

International Nuclear Information System (INIS)

Jong, L.M.; Newnham, J.N.; Yang, C.; Van Donkelaar, J.A.; Hudson, F.E.; Dzurak, A.S.; Jamieson, D.N.

2011-01-01

Following a single ion strike in a semiconductor device the induced charge distribution changes rapidly with time and space. This phenomenon has important applications to the sensing of ionizing radiation with applications as diverse as deterministic doping in semiconductor devices to radiation dosimetry. We have developed a new method for the investigation of this phenomenon by using a nuclear microprobe and the technique of Ion Beam Induced Charge (IBIC) applied to a specially configured sub-100 μm scale silicon device fitted with two independent surface electrodes coupled to independent data acquisition systems. The separation between the electrodes is comparable to the range of the 2 MeV He ions used in our experiments. This system allows us to integrate the total charge induced in the device by summing the signals from the independent electrodes and to measure the sharing of charge between the electrodes as a function of the ion strike location as a nuclear microprobe beam is scanned over the sensitive region of the device. It was found that for a given ion strike location the charge sharing between the electrodes allowed the beam-strike location to be determined to higher precision than the probe resolution. This result has potential application to the development of a deterministic doping technique where counted ion implantation is used to fabricate devices that exploit the quantum mechanical attributes of the implanted ions.

Validation of The Deterministic Diffusion Method For The Neutronic Calculations of Thermal Research Reactors of TRIGA-Type Using The Wisdom-IAEA-69 Nuclear Data Library

International Nuclear Information System (INIS)

Hussein, H.M.; Sakr, A.M.; Amin, E.H.

2011-01-01

The objective of this paper is to assess the suitability and the accuracy of the deterministic diffusion method for the neutronic calculations of the TRIGA type research reactors in proposed condensed energy spectra of five and seven groups with one and three thermal groups respectively, using the calculational line: WIMSD-IAEA-69 nuclear data library/ WIMSD-5B lattice and cell calculations code/ CITVAP v3.1 core calculations code. Firstly, The assessment goes through analyzing the integral parameters - k e ff, ρ 238 , σ 235 , σ 238 , and C * - of the TRX and BAPL benchmark lattices and comparison with experimental and previous reference results using other ENDLs at the full energy spectra, which show good agreement with the references at both spectra. Secondly, evaluation of the 3D nuclear characteristics of three different cores of the TRR-1/M1 TRIGA Mark- III Thai research reactor, using the CITVAP v3.1 code and macroscopic cross-section libraries generated using the WIMSD-5B code at the proposed energy spectra separately. The results include the excess reactivities and the worth of control rods, which were compared with previous Monte Carlo results and experimental values, that show good agreement with the references at both energy spectra, albeit better accuracies are shown with the five groups spectrum. The results also includes neutron flux distributions which are settled for future comparisons with other calculational techniques, even, they are comparable to reactors and fuels of the same type. The study reflects the adequacy of using the pre-stated calculational line at the condensed energy spectra for evaluation of the neutronic parameters of the TRIGA type reactors, and future comparisons of the un-benchmarked results could assure this result for wider range of neutronics or safety-related parameters

Fragility assessment method of Concrete Wall Subjected to Impact Loading

International Nuclear Information System (INIS)

Hahm, Daegi; Shin, Sang Shup; Choi, In-Kil

2014-01-01

These studies have been aimed to verify and ensure the safety of the targeted walls and structures especially in the viewpoint of the deterministic approach. However, recently, the regulation and the assessment of the safety of the nuclear power plants (NPPs) against to an aircraft impact are strongly encouraged to adopt a probabilistic approach, i.e., the probabilistic risk assessment of an aircraft impact. In Korea, research to develop aircraft impact risk quantification technology was initiated in 2012 by Korea Atomic Energy Research Institute (KAERI). In this paper, for the one example of the probabilistic safety assessment approach, a method to estimate the failure probability and fragility of concrete wall subjected to impact loading caused by missiles or engine parts of aircrafts will be introduced. This method and the corresponding results will be used for the total technical roadmap and the procedure to assess the aircraft impact risk (Fig.1). A method and corresponding results of the estimation of the failure probability and fragility for a concrete wall subjected to impact loadings caused by missiles or engine parts of aircrafts was introduced. The detailed information of the target concrete wall in NPP, and the example aircraft engine model is considered safeguard information (SGI), and is not contained in this paper

Dynamic model based on Bayesian method for energy security assessment

International Nuclear Information System (INIS)

Augutis, Juozas; Krikštolaitis, Ričardas; Pečiulytė, Sigita; Žutautaitė, Inga

2015-01-01

Highlights: • Methodology for dynamic indicator model construction and forecasting of indicators. • Application of dynamic indicator model for energy system development scenarios. • Expert judgement involvement using Bayesian method. - Abstract: The methodology for the dynamic indicator model construction and forecasting of indicators for the assessment of energy security level is presented in this article. An indicator is a special index, which provides numerical values to important factors for the investigated area. In real life, models of different processes take into account various factors that are time-dependent and dependent on each other. Thus, it is advisable to construct a dynamic model in order to describe these dependences. The energy security indicators are used as factors in the dynamic model. Usually, the values of indicators are obtained from statistical data. The developed dynamic model enables to forecast indicators’ variation taking into account changes in system configuration. The energy system development is usually based on a new object construction. Since the parameters of changes of the new system are not exactly known, information about their influences on indicators could not be involved in the model by deterministic methods. Thus, dynamic indicators’ model based on historical data is adjusted by probabilistic model with the influence of new factors on indicators using the Bayesian method

Multi-objective Optimization Strategies Using Adjoint Method and Game Theory in Aerodynamics

Science.gov (United States)

Tang, Zhili

2006-08-01

There are currently three different game strategies originated in economics: (1) Cooperative games (Pareto front), (2) Competitive games (Nash game) and (3) Hierarchical games (Stackelberg game). Each game achieves different equilibria with different performance, and their players play different roles in the games. Here, we introduced game concept into aerodynamic design, and combined it with adjoint method to solve multi-criteria aerodynamic optimization problems. The performance distinction of the equilibria of these three game strategies was investigated by numerical experiments. We computed Pareto front, Nash and Stackelberg equilibria of the same optimization problem with two conflicting and hierarchical targets under different parameterizations by using the deterministic optimization method. The numerical results show clearly that all the equilibria solutions are inferior to the Pareto front. Non-dominated Pareto front solutions are obtained, however the CPU cost to capture a set of solutions makes the Pareto front an expensive tool to the designer.

Multi-objective optimization strategies using adjoint method and game theory in aerodynamics

Institute of Scientific and Technical Information of China (English)

Zhili Tang

2006-01-01

There are currently three different game strategies originated in economics:(1) Cooperative games (Pareto front),(2)Competitive games (Nash game) and (3)Hierarchical games (Stackelberg game).Each game achieves different equilibria with different performance,and their players play different roles in the games.Here,we introduced game concept into aerodynamic design, and combined it with adjoint method to solve multicriteria aerodynamic optimization problems.The performance distinction of the equilibria of these three game strategies was investigated by numerical experiments.We computed Pareto front, Nash and Stackelberg equilibria of the same optimization problem with two conflicting and hierarchical targets under different parameterizations by using the deterministic optimization method.The numerical results show clearly that all the equilibria solutions are inferior to the Pareto front.Non-dominated Pareto front solutions are obtained,however the CPU cost to capture a set of solutions makes the Pareto front an expensive tool to the designer.

Nonlinear Markov processes: Deterministic case

International Nuclear Information System (INIS)

Frank, T.D.

2008-01-01

Deterministic Markov processes that exhibit nonlinear transition mechanisms for probability densities are studied. In this context, the following issues are addressed: Markov property, conditional probability densities, propagation of probability densities, multistability in terms of multiple stationary distributions, stability analysis of stationary distributions, and basin of attraction of stationary distribution

Deterministic nonlinear systems a short course

CERN Document Server

Anishchenko, Vadim S; Strelkova, Galina I

2014-01-01

This text is a short yet complete course on nonlinear dynamics of deterministic systems. Conceived as a modular set of 15 concise lectures it reflects the many years of teaching experience by the authors. The lectures treat in turn the fundamental aspects of the theory of dynamical systems, aspects of stability and bifurcations, the theory of deterministic chaos and attractor dimensions, as well as the elements of the theory of Poincare recurrences.Particular attention is paid to the analysis of the generation of periodic, quasiperiodic and chaotic self-sustained oscillations and to the issue of synchronization in such systems.  This book is aimed at graduate students and non-specialist researchers with a background in physics, applied mathematics and engineering wishing to enter this exciting field of research.

Dynamic optimization deterministic and stochastic models

CERN Document Server

Hinderer, Karl; Stieglitz, Michael

2016-01-01

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

KAUST Repository

Babuška, Ivo; Nobile, Fabio; Tempone, Raul

2010-01-01

This work proposes and analyzes a stochastic collocation method for solving elliptic partial differential equations with random coefficients and forcing terms. These input data are assumed to depend on a finite number of random variables. The method consists of a Galerkin approximation in space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space, and naturally leads to the solution of uncoupled deterministic problems as in the Monte Carlo approach. It treats easily a wide range of situations, such as input data that depend nonlinearly on the random variables, diffusivity coefficients with unbounded second moments, and random variables that are correlated or even unbounded. We provide a rigorous convergence analysis and demonstrate exponential convergence of the “probability error” with respect to the number of Gauss points in each direction of the probability space, under some regularity assumptions on the random input data. Numerical examples show the effectiveness of the method. Finally, we include a section with developments posterior to the original publication of this work. There we review sparse grid stochastic collocation methods, which are effective collocation strategies for problems that depend on a moderately large number of random variables.

Failure analysis of the cement mantle in total hip arthroplasty with an efficient probabilistic method.

Science.gov (United States)

Kaymaz, Irfan; Bayrak, Ozgu; Karsan, Orhan; Celik, Ayhan; Alsaran, Akgun

2014-04-01

Accurate prediction of long-term behaviour of cemented hip implants is very important not only for patient comfort but also for elimination of any revision operation due to failure of implants. Therefore, a more realistic computer model was generated and then used for both deterministic and probabilistic analyses of the hip implant in this study. The deterministic failure analysis was carried out for the most common failure states of the cement mantle. On the other hand, most of the design parameters of the cemented hip are inherently uncertain quantities. Therefore, the probabilistic failure analysis was also carried out considering the fatigue failure of the cement mantle since it is the most critical failure state. However, the probabilistic analysis generally requires large amount of time; thus, a response surface method proposed in this study was used to reduce the computation time for the analysis of the cemented hip implant. The results demonstrate that using an efficient probabilistic approach can significantly reduce the computation time for the failure probability of the cement from several hours to minutes. The results also show that even the deterministic failure analyses do not indicate any failure of the cement mantle with high safety factors, the probabilistic analysis predicts the failure probability of the cement mantle as 8%, which must be considered during the evaluation of the success of the cemented hip implants.

New methods for solving a vertex p-center problem with uncertain demand-weighted distance: A real case study

Directory of Open Access Journals (Sweden)

Javad Nematian

2015-04-01

Full Text Available Vertex and p-center problems are two well-known types of the center problem. In this paper, a p-center problem with uncertain demand-weighted distance will be introduced in which the demands are considered as fuzzy random variables (FRVs and the objective of the problem is to minimize the maximum distance between a node and its nearest facility. Then, by introducing new methods, the proposed problem is converted to deterministic integer programming (IP problems where these methods will be obtained through the implementation of the possibility theory and fuzzy random chance-constrained programming (FRCCP. Finally, the proposed methods are applied for locating bicycle stations in the city of Tabriz in Iran as a real case study. The computational results of our study show that these methods can be implemented for the center problem with uncertain frameworks.

Flood risk assessment in France: comparison of extreme flood estimation methods (EXTRAFLO project, Task 7)

Science.gov (United States)

Garavaglia, F.; Paquet, E.; Lang, M.; Renard, B.; Arnaud, P.; Aubert, Y.; Carre, J.

2013-12-01

In flood risk assessment the methods can be divided in two families: deterministic methods and probabilistic methods. In the French hydrologic community the probabilistic methods are historically preferred to the deterministic ones. Presently a French research project named EXTRAFLO (RiskNat Program of the French National Research Agency, https://extraflo.cemagref.fr) deals with the design values for extreme rainfall and floods. The object of this project is to carry out a comparison of the main methods used in France for estimating extreme values of rainfall and floods, to obtain a better grasp of their respective fields of application. In this framework we present the results of Task 7 of EXTRAFLO project. Focusing on French watersheds, we compare the main extreme flood estimation methods used in French background: (i) standard flood frequency analysis (Gumbel and GEV distribution), (ii) regional flood frequency analysis (regional Gumbel and GEV distribution), (iii) local and regional flood frequency analysis improved by historical information (Naulet et al., 2005), (iv) simplify probabilistic method based on rainfall information (i.e. Gradex method (CFGB, 1994), Agregee method (Margoum, 1992) and Speed method (Cayla, 1995)), (v) flood frequency analysis by continuous simulation approach and based on rainfall information (i.e. Schadex method (Paquet et al., 2013, Garavaglia et al., 2010), Shyreg method (Lavabre et al., 2003)) and (vi) multifractal approach. The main result of this comparative study is that probabilistic methods based on additional information (i.e. regional, historical and rainfall information) provide better estimations than the standard flood frequency analysis. Another interesting result is that, the differences between the various extreme flood quantile estimations of compared methods increase with return period, staying relatively moderate up to 100-years return levels. Results and discussions are here illustrated throughout with the example

Towards automatic global error control: Computable weak error expansion for the tau-leap method

KAUST Repository

Karlsson, Peer Jesper; Tempone, Raul

2011-01-01

This work develops novel error expansions with computable leading order terms for the global weak error in the tau-leap discretization of pure jump processes arising in kinetic Monte Carlo models. Accurate computable a posteriori error approximations are the basis for adaptive algorithms, a fundamental tool for numerical simulation of both deterministic and stochastic dynamical systems. These pure jump processes are simulated either by the tau-leap method, or by exact simulation, also referred to as dynamic Monte Carlo, the Gillespie Algorithm or the Stochastic Simulation Slgorithm. Two types of estimates are presented: an a priori estimate for the relative error that gives a comparison between the work for the two methods depending on the propensity regime, and an a posteriori estimate with computable leading order term. © de Gruyter 2011.

SU-G-TeP1-15: Toward a Novel GPU Accelerated Deterministic Solution to the Linear Boltzmann Transport Equation

Energy Technology Data Exchange (ETDEWEB)

Yang, R [University of Alberta, Edmonton, AB (Canada); Fallone, B [University of Alberta, Edmonton, AB (Canada); Cross Cancer Institute, Edmonton, AB (Canada); MagnetTx Oncology Solutions, Edmonton, AB (Canada); St Aubin, J [University of Alberta, Edmonton, AB (Canada); Cross Cancer Institute, Edmonton, AB (Canada)

2016-06-15

Purpose: To develop a Graphic Processor Unit (GPU) accelerated deterministic solution to the Linear Boltzmann Transport Equation (LBTE) for accurate dose calculations in radiotherapy (RT). A deterministic solution yields the potential for major speed improvements due to the sparse matrix-vector and vector-vector multiplications and would thus be of benefit to RT. Methods: In order to leverage the massively parallel architecture of GPUs, the first order LBTE was reformulated as a second order self-adjoint equation using the Least Squares Finite Element Method (LSFEM). This produces a symmetric positive-definite matrix which is efficiently solved using a parallelized conjugate gradient (CG) solver. The LSFEM formalism is applied in space, discrete ordinates is applied in angle, and the Multigroup method is applied in energy. The final linear system of equations produced is tightly coupled in space and angle. Our code written in CUDA-C was benchmarked on an Nvidia GeForce TITAN-X GPU against an Intel i7-6700K CPU. A spatial mesh of 30,950 tetrahedral elements was used with an S4 angular approximation. Results: To avoid repeating a full computationally intensive finite element matrix assembly at each Multigroup energy, a novel mapping algorithm was developed which minimized the operations required at each energy. Additionally, a parallelized memory mapping for the kronecker product between the sparse spatial and angular matrices, including Dirichlet boundary conditions, was created. Atomicity is preserved by graph-coloring overlapping nodes into separate kernel launches. The one-time mapping calculations for matrix assembly, kronecker product, and boundary condition application took 452±1ms on GPU. Matrix assembly for 16 energy groups took 556±3s on CPU, and 358±2ms on GPU using the mappings developed. The CG solver took 93±1s on CPU, and 468±2ms on GPU. Conclusion: Three computationally intensive subroutines in deterministically solving the LBTE have been

Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

Directory of Open Access Journals (Sweden)

I. Kioutsioukis

2016-12-01

Full Text Available Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism. Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3, nitrogen dioxide (NO2 and particulate matter (PM10. Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII. The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint

Quantum deterministic key distribution protocols based on the authenticated entanglement channel

International Nuclear Information System (INIS)

Zhou Nanrun; Wang Lijun; Ding Jie; Gong Lihua

2010-01-01

Based on the quantum entanglement channel, two secure quantum deterministic key distribution (QDKD) protocols are proposed. Unlike quantum random key distribution (QRKD) protocols, the proposed QDKD protocols can distribute the deterministic key securely, which is of significant importance in the field of key management. The security of the proposed QDKD protocols is analyzed in detail using information theory. It is shown that the proposed QDKD protocols can safely and effectively hand over the deterministic key to the specific receiver and their physical implementation is feasible with current technology.

Quantum deterministic key distribution protocols based on the authenticated entanglement channel

Energy Technology Data Exchange (ETDEWEB)

Zhou Nanrun; Wang Lijun; Ding Jie; Gong Lihua [Department of Electronic Information Engineering, Nanchang University, Nanchang 330031 (China)], E-mail: znr21@163.com, E-mail: znr21@hotmail.com

2010-04-15

Based on the quantum entanglement channel, two secure quantum deterministic key distribution (QDKD) protocols are proposed. Unlike quantum random key distribution (QRKD) protocols, the proposed QDKD protocols can distribute the deterministic key securely, which is of significant importance in the field of key management. The security of the proposed QDKD protocols is analyzed in detail using information theory. It is shown that the proposed QDKD protocols can safely and effectively hand over the deterministic key to the specific receiver and their physical implementation is feasible with current technology.

Is the Multigrid Method Fault Tolerant? The Two-Grid Case

Energy Technology Data Exchange (ETDEWEB)

Ainsworth, Mark [Brown Univ., Providence, RI (United States). Division of Applied Mathematics; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division; Glusa, Christian [Brown Univ., Providence, RI (United States). Division of Applied Mathematics

2016-06-30

The predicted reduced resiliency of next-generation high performance computers means that it will become necessary to take into account the effects of randomly occurring faults on numerical methods. Further, in the event of a hard fault occurring, a decision has to be made as to what remedial action should be taken in order to resume the execution of the algorithm. The action that is chosen can have a dramatic effect on the performance and characteristics of the scheme. Ideally, the resulting algorithm should be subjected to the same kind of mathematical analysis that was applied to the original, deterministic variant. The purpose of this work is to provide an analysis of the behaviour of the multigrid algorithm in the presence of faults. Multigrid is arguably the method of choice for the solution of large-scale linear algebra problems arising from discretization of partial differential equations and it is of considerable importance to anticipate its behaviour on an exascale machine. The analysis of resilience of algorithms is in its infancy and the current work is perhaps the first to provide a mathematical model for faults and analyse the behaviour of a state-of-the-art algorithm under the model. It is shown that the Two Grid Method fails to be resilient to faults. Attention is then turned to identifying the minimal necessary remedial action required to restore the rate of convergence to that enjoyed by the ideal fault-free method.

A comparative study of track reconstruction methods in the context of CMS physics

International Nuclear Information System (INIS)

Winkler, M.

2002-05-01

This thesis deals mainly with the problem of reconstructing the tracks of charged particles from the measurements recorded by the CMS Tracker, in particular with track fitting. The task of the track fit is to use the available information (the subsets of hits belonging to the track of a particle found by a track finder) in a statistically optimal way for the estimation of the track parameters and the associated errors. Due to the high track multiplicity at LHC and the large background of noise hits, combinatorial methods such as the Kalman filter may have problems in the association of hits to tracks, and their results will be biased in the case of wrong hits assigned to a track. Recently developped non-linear, adaptive methods such as the deterministic annealing filter and the multi track filter try to solve the assignment problem during the track fit, by determining an assignment probability of a hit to a track. The methods are studied in the CMS Tracker using various event topologies. (author)

A Method to Select Software Test Cases in Consideration of Past Input Sequence

International Nuclear Information System (INIS)

Kim, Hee Eun; Kim, Bo Gyung; Kang, Hyun Gook

2015-01-01

In the Korea Nuclear I and C Systems (KNICS) project, the software for the fully-digitalized reactor protection system (RPS) was developed under a strict procedure. Even though the behavior of the software is deterministic, the randomness of input sequence produces probabilistic behavior of software. A software failure occurs when some inputs to the software occur and interact with the internal state of the digital system to trigger a fault that was introduced into the software during the software lifecycle. In this paper, the method to select test set for software failure probability estimation is suggested. This test set reflects past input sequence of software, which covers all possible cases. In this study, the method to select test cases for software failure probability quantification was suggested. To obtain profile of paired state variables, relationships of the variables need to be considered. The effect of input from human operator also have to be considered. As an example, test set of PZR-PR-Lo-Trip logic was examined. This method provides framework for selecting test cases of safety-critical software

Advanced methods on the evaluation of design earthquake motions for important power constructions

International Nuclear Information System (INIS)

Higashi, Sadanori; Shiba, Yoshiaki; Sato, Hiroaki; Sato, Yusuke; Nakajima, Masato; Sakai, Michiya; Sato, Kiyotaka

2009-01-01

In this report, we compiled advanced methods on the evaluation of design earthquake motions for important power constructions such as nuclear power, thermal power, and hydroelectric power facilities. For the nuclear and hydroelectric power facilities, we developed an inversion method of broad-band (0.1-5Hz) source process and obtained valid results from applying the method to the 2007 Niigata-ken Chuetsu-oki earthquake (M6.8). We have also improved our modeling techniques of thick sedimentary layered structure such as the S-wave velocity modeling by using microtremor array measurement and the frequency dependent damping factor with a lower limit. For seismic isolation design for nuclear power facilities, we proposed a design pseudo-velocity response spectrum. For the thermal power facilities, we performed three-dimensional numerical simulation of Kanto Basin for a prediction relation of long-period ground motion. We also proposed the introduction of probabilistic approach into the deterministic evaluation flow of design earthquake motions and evaluated the effect of a great earthquake with a short return period on the seismic hazard in Miyagi Prefecture, Japan. (author)

Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem.

Science.gov (United States)

Schilde, M; Doerner, K F; Hartl, R F

2014-10-01

In urban areas, logistic transportation operations often run into problems because travel speeds change, depending on the current traffic situation. If not accounted for, time-dependent and stochastic travel speeds frequently lead to missed time windows and thus poorer service. Especially in the case of passenger transportation, it often leads to excessive passenger ride times as well. Therefore, time-dependent and stochastic influences on travel speeds are relevant for finding feasible and reliable solutions. This study considers the effect of exploiting statistical information available about historical accidents, using stochastic solution approaches for the dynamic dial-a-ride problem (dynamic DARP). The authors propose two pairs of metaheuristic solution approaches, each consisting of a deterministic method (average time-dependent travel speeds for planning) and its corresponding stochastic version (exploiting stochastic information while planning). The results, using test instances with up to 762 requests based on a real-world road network, show that in certain conditions, exploiting stochastic information about travel speeds leads to significant improvements over deterministic approaches.

Piecewise deterministic processes in biological models

CERN Document Server

Rudnicki, Ryszard

2017-01-01

This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models. Further, it presents examples of biological phenomena, such as gene activity and population growth, where different types of PDMPs appear: continuous time Markov chains, deterministic processes with jumps, processes with switching dynamics, and point processes. Subsequent chapters present the necessary tools from the theory of stochastic processes and semigroups of linear operators, as well as theoretical results concerning the long-time behaviour of stochastic semigroups induced by PDMPs and their applications to biological models. As such, the book offers a valuable resource for mathematicians and biologists alike. The first group will find new biological models that lead to interesting and often new mathematical questions, while the second can observe how to include seemingly disparate biological processes into a unified mathematical theory, and...

Deterministic geologic processes and stochastic modeling

International Nuclear Information System (INIS)

Rautman, C.A.; Flint, A.L.

1992-01-01

This paper reports that recent outcrop sampling at Yucca Mountain, Nevada, has produced significant new information regarding the distribution of physical properties at the site of a potential high-level nuclear waste repository. consideration of the spatial variability indicates that her are a number of widespread deterministic geologic features at the site that have important implications for numerical modeling of such performance aspects as ground water flow and radionuclide transport. Because the geologic processes responsible for formation of Yucca Mountain are relatively well understood and operate on a more-or-less regional scale, understanding of these processes can be used in modeling the physical properties and performance of the site. Information reflecting these deterministic geologic processes may be incorporated into the modeling program explicitly using geostatistical concepts such as soft information, or implicitly, through the adoption of a particular approach to modeling

Coupling finite elements and reliability methods - application to safety evaluation of pressurized water reactor vessels

International Nuclear Information System (INIS)

Pitner, P.; Venturini, V.

1995-02-01

When reliability studies are extended form deterministic calculations in mechanics, it is necessary to take into account input parameters variabilities which are linked to the different sources of uncertainty. Integrals must then be calculated to evaluate the failure risk. This can be performed either by simulation methods, or by approximations ones (FORM/SORM). Model in mechanics often require to perform calculation codes. These ones must then be coupled with the reliability calculations. Theses codes can involve large calculation times when they are invoked numerous times during simulations sequences or in complex iterative procedures. Response surface method gives an approximation of the real response from a reduced number of points for which the finite element code is run. Thus, when it is combined with FORM/SORM methods, a coupling can be carried out which gives results in a reasonable calculation time. An application of response surface method to mechanics reliability coupling for a mechanical model which calls for a finite element code is presented. It corresponds to a probabilistic fracture mechanics study of a pressurized water reactor vessel. (authors). 5 refs., 3 figs

Understanding deterministic diffusion by correlated random walks

International Nuclear Information System (INIS)

Klages, R.; Korabel, N.

2002-01-01

Low-dimensional periodic arrays of scatterers with a moving point particle are ideal models for studying deterministic diffusion. For such systems the diffusion coefficient is typically an irregular function under variation of a control parameter. Here we propose a systematic scheme of how to approximate deterministic diffusion coefficients of this kind in terms of correlated random walks. We apply this approach to two simple examples which are a one-dimensional map on the line and the periodic Lorentz gas. Starting from suitable Green-Kubo formulae we evaluate hierarchies of approximations for their parameter-dependent diffusion coefficients. These approximations converge exactly yielding a straightforward interpretation of the structure of these irregular diffusion coefficients in terms of dynamical correlations. (author)

Deterministic one-way simulation of two-way, real-time cellular automata and its related problems

Energy Technology Data Exchange (ETDEWEB)

Umeo, H; Morita, K; Sugata, K

1982-06-13

The authors show that for any deterministic two-way, real-time cellular automaton, m, there exists a deterministic one-way cellular automation which can simulate m in twice real-time. Moreover the authors present a new type of deterministic one-way cellular automata, called circular cellular automata, which are computationally equivalent to deterministic two-way cellular automata. 7 references.

"The Theory was Beautiful Indeed": Rise, Fall and Circulation of Maximizing Methods in Population Genetics (1930-1980).

Science.gov (United States)

Grodwohl, Jean-Baptiste

2017-08-01

Describing the theoretical population geneticists of the 1960s, Joseph Felsenstein reminisced: "our central obsession was finding out what function evolution would try to maximize. Population geneticists used to think, following Sewall Wright, that mean relative fitness, W, would be maximized by natural selection" (Felsenstein 2000). The present paper describes the genesis, diffusion and fall of this "obsession", by giving a biography of the mean fitness function in population genetics. This modeling method devised by Sewall Wright in the 1930s found its heyday in the late 1950s and early 1960s, in the wake of Motoo Kimura's and Richard Lewontin's works. It seemed a reliable guide in the mathematical study of deterministic effects (the study of natural selection in populations of infinite size, with no drift), leading to powerful generalizations presenting law-like properties. Progress in population genetics theory, it then seemed, would come from the application of this method to the study of systems with several genes. This ambition came to a halt in the context of the influential objections made by the Australian mathematician Patrick Moran in 1963. These objections triggered a controversy between mathematically- and biologically-inclined geneticists, with affected both the formal standards and the aims of population genetics as a science. Over the course of the 1960s, the mean fitness method withered with the ambition of developing the deterministic theory. The mathematical theory became increasingly complex. Kimura re-focused his modeling work on the theory of random processes; as a result of his computer simulations, Lewontin became the staunchest critic of maximizing principles in evolutionary biology. The mean fitness method then migrated to other research areas, being refashioned and used in evolutionary quantitative genetics and behavioral ecology.

An Analysis on the Characteristic of Multi-response CADIS Method for the Monte Carlo Radiation Shielding Calculation

International Nuclear Information System (INIS)

Kim, Do Hyun; Shin, Chang Ho; Kim, Song Hyun

2014-01-01

It uses the deterministic method to calculate adjoint fluxes for the decision of the parameters used in the variance reductions. This is called as hybrid Monte Carlo method. The CADIS method, however, has a limitation to reduce the stochastic errors of all responses. The Forward Weighted CADIS (FW-CADIS) was introduced to solve this problem. To reduce the overall stochastic errors of the responses, the forward flux is used. In the previous study, the Multi-Response CADIS (MR-CAIDS) method was derived for minimizing sum of each squared relative error. In this study, the characteristic of the MR-CADIS method was evaluated and compared with the FW-CADIS method. In this study, how the CADIS, FW-CADIS, and MR-CADIS methods are applied to optimize and decide the parameters used in the variance reduction techniques was analyzed. The MR-CADIS Method uses a technique that the sum of squared relative error in each tally region was minimized to achieve uniform uncertainty. To compare the simulation efficiency of the methods, a simple shielding problem was evaluated. Using FW-CADIS method, it was evaluated that the average of the relative errors was minimized; however, MR-CADIS method gives a lowest variance of the relative errors. Analysis shows that, MR-CADIS method can efficiently and uniformly reduce the relative error of the plural response problem than FW-CADIS method

Stability and accuracy of 3D neutron transport simulations using the 2D/1D method in MPACT

International Nuclear Information System (INIS)

Collins, Benjamin; Stimpson, Shane; Kelley, Blake W.; Young, Mitchell T.H.; Kochunas, Brendan; Graham, Aaron; Larsen, Edward W.; Downar, Thomas; Godfrey, Andrew

2016-01-01

A consistent “2D/1D” neutron transport method is derived from the 3D Boltzmann transport equation, to calculate fuel-pin-resolved neutron fluxes for realistic full-core Pressurized Water Reactor (PWR) problems. The 2D/1D method employs the Method of Characteristics to discretize the radial variables and a lower order transport solution to discretize the axial variable. This paper describes the theory of the 2D/1D method and its implementation in the MPACT code, which has become the whole-core deterministic neutron transport solver for the Consortium for Advanced Simulations of Light Water Reactors (CASL) core simulator VERA-CS. Several applications have been performed on both leadership-class and industry-class computing clusters. Results are presented for whole-core solutions of the Watts Bar Nuclear Power Station Unit 1 and compared to both continuous-energy Monte Carlo results and plant data.

Stability and accuracy of 3D neutron transport simulations using the 2D/1D method in MPACT

Energy Technology Data Exchange (ETDEWEB)

Collins, Benjamin, E-mail: collinsbs@ornl.gov [Oak Ridge National Laboratory, One Bethel Valley Rd., Oak Ridge, TN 37831 (United States); Stimpson, Shane, E-mail: stimpsonsg@ornl.gov [Oak Ridge National Laboratory, One Bethel Valley Rd., Oak Ridge, TN 37831 (United States); Kelley, Blake W., E-mail: kelleybl@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Young, Mitchell T.H., E-mail: youngmit@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Kochunas, Brendan, E-mail: bkochuna@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Graham, Aaron, E-mail: aarograh@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Larsen, Edward W., E-mail: edlarsen@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Downar, Thomas, E-mail: downar@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Godfrey, Andrew, E-mail: godfreyat@ornl.gov [Oak Ridge National Laboratory, One Bethel Valley Rd., Oak Ridge, TN 37831 (United States)

2016-12-01

A consistent “2D/1D” neutron transport method is derived from the 3D Boltzmann transport equation, to calculate fuel-pin-resolved neutron fluxes for realistic full-core Pressurized Water Reactor (PWR) problems. The 2D/1D method employs the Method of Characteristics to discretize the radial variables and a lower order transport solution to discretize the axial variable. This paper describes the theory of the 2D/1D method and its implementation in the MPACT code, which has become the whole-core deterministic neutron transport solver for the Consortium for Advanced Simulations of Light Water Reactors (CASL) core simulator VERA-CS. Several applications have been performed on both leadership-class and industry-class computing clusters. Results are presented for whole-core solutions of the Watts Bar Nuclear Power Station Unit 1 and compared to both continuous-energy Monte Carlo results and plant data.

Monte Carlo Finite Volume Element Methods for the Convection-Diffusion Equation with a Random Diffusion Coefficient

Directory of Open Access Journals (Sweden)

Qian Zhang

2014-01-01

Full Text Available The paper presents a framework for the construction of Monte Carlo finite volume element method (MCFVEM for the convection-diffusion equation with a random diffusion coefficient, which is described as a random field. We first approximate the continuous stochastic field by a finite number of random variables via the Karhunen-Loève expansion and transform the initial stochastic problem into a deterministic one with a parameter in high dimensions. Then we generate independent identically distributed approximations of the solution by sampling the coefficient of the equation and employing finite volume element variational formulation. Finally the Monte Carlo (MC method is used to compute corresponding sample averages. Statistic error is estimated analytically and experimentally. A quasi-Monte Carlo (QMC technique with Sobol sequences is also used to accelerate convergence, and experiments indicate that it can improve the efficiency of the Monte Carlo method.

New Hybrid Monte Carlo methods for efficient sampling. From physics to biology and statistics

International Nuclear Information System (INIS)

Akhmatskaya, Elena; Reich, Sebastian

2011-01-01

We introduce a class of novel hybrid methods for detailed simulations of large complex systems in physics, biology, materials science and statistics. These generalized shadow Hybrid Monte Carlo (GSHMC) methods combine the advantages of stochastic and deterministic simulation techniques. They utilize a partial momentum update to retain some of the dynamical information, employ modified Hamiltonians to overcome exponential performance degradation with the system’s size and make use of multi-scale nature of complex systems. Variants of GSHMCs were developed for atomistic simulation, particle simulation and statistics: GSHMC (thermodynamically consistent implementation of constant-temperature molecular dynamics), MTS-GSHMC (multiple-time-stepping GSHMC), meso-GSHMC (Metropolis corrected dissipative particle dynamics (DPD) method), and a generalized shadow Hamiltonian Monte Carlo, GSHmMC (a GSHMC for statistical simulations). All of these are compatible with other enhanced sampling techniques and suitable for massively parallel computing allowing for a range of multi-level parallel strategies. A brief description of the GSHMC approach, examples of its application on high performance computers and comparison with other existing techniques are given. Our approach is shown to resolve such problems as resonance instabilities of the MTS methods and non-preservation of thermodynamic equilibrium properties in DPD, and to outperform known methods in sampling efficiency by an order of magnitude. (author)