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Recent advancements of reactor Monte Carlo code RMC

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Recent advancements of reactor Monte Carlo code RMC

Physics of Reactors 2016: Unifying Theory and Experiments in the 21st Century, PHYSOR 2016

作者： Wang, Kan Liang, Jin-Gang Liu, Shichang Shang, Xiaotong Fan, Xiao Qiu, Yishu Yexin, Ouwen Yang, Feng Wu, Gaochen Shen, Qicang Wang, Gang Li, Wanlin Yuan, Yuan Tang, Xiao Cai, Yun Li, Quan Wu, Qu Yu, Ganglin Yu, Jiankai Chen, Zonghuan She, Ding Li, Zeguang Li, Songyang Chen, Yixue Yu, Hui Quan, Guoping Li, Linsen Chai, Xiaoming Qiang, Shenglong Lv, Huanwen Yao, Dong Li, Qing Xu, Qi Shen, Huayun Department of Engineering Physics Tsinghua University Beijing China Shanghai Nuclear Engineering Design Institute Shanghai China China Nuclear Power Engineering Corporation Beijing China Institute of Nuclear and New Energy Technology Tsinghua University Beijing China State Nuclear Power Technology Company Beijing China Nuclear Power Institute of China Chengdu Sichuan China Beijing Applied Physics and Computational Mathematics Beijing China

ISBN: (纸本)9781510825734

This paper is to summarize the recent advancements of Reactor Monte Carlo code RMC. The capability of shielding calculations and improved variance reduction techniques have been developed in RMC code. A hybrid message-passing and shared-memory approach has been implemented in RMC, fully utilizing the available computing resources. A new merging strategy based on the virtual mesh was proposed and investigated for large scale burnup problems of stochastic media. The adjoint superhistory method was proposed for sensitivity analysis. A subchannel module (RMC-TH) is embedded inside the RMC in order to consider the thermal-hydraulic feedback. The inline equilibrium Xenon method has been implemented in RMC to solve the problem of numerical Xenon oscillation. Integrated parallel methods which include data decomposition and spatial domain decomposition are investigated based on RMC, to handle the memory problem in full core detailed burnup calculations.

关键词： Stochastic systems

Divergence based learning vector quantization

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Divergence based learning vector quantization

18th European Symposium on Artificial Neural Networks, computational Intelligence and Machine Learning, ESANN 2010

作者： Mwebaze, E. Schneider, P. Schleif, F.-M. Haase, S. Villmann, T. Biehl, M. Makerere Univ P.O. Box 7062 Kampala Uganda Johann Bernoulli Inst. for Mathematics and Computer Science Univ. of Groningen P. O. Box 407 9700AK Groningen Netherlands Computational Intelligence Group University of Leipzig Semmelweisstr. 10 04103 Leipzig Germany Department of MPI University of Applied Sciences Technikumplatz 17 09648 Mittweida Germany

ISBN: (纸本)2930307102

We suggest the use of alternative distance measures for similarity based classification in Learning Vector Quantization. Divergences can be employed whenever the data consists of non-negative normalized features, which is the case for, e.g., spectral data or histograms. As examples, we derive gradient based training algorithms in the framework of Generalized Learning Vector Quantization based on the so-called Cauchy-Schwarz divergence and a non-symmetric Renyi divergence. As a first test we apply the methods to two different biomedical data sets and compare with the use of standard Euclidean distance.

关键词： Vector quantization

Varycoef: An R package for gaussian process-based spatially varying coefficient models

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arXiv 2021年

作者： Dambon, Jakob A. Sigrist, Fabio Furrer, Reinhard Institute of Financial Services Zug Lucerne School of Business Lucerne University of Applied Sciences and Arts Suurstoffi 1 Rotkreuz6343 Switzerland Department of Mathematics Department of Computational Sciences Faculty of Science University of Zurich Winterthurerstr. 190 Zurich8057 Switzerland Department of Mathematics Faculty of Science University of Zurich Winterthurerstr. 190 Zurich8057 Switzerland

Gaussian processes (GPs) are well-known tools for modeling dependent data with applications in spatial statistics, time series analysis, or econometrics. In this article, we present the R package varycoef that implements estimation, prediction, and variable selection of linear models with spatially varying coefficients (SVC) defined by GPs, so called GP-based SVC models. Such models offer a high degree of flexibility while being relatively easy to interpret. Using varycoef, we show versatile applications of (spatially) varying coefficient models on spatial and time series data. This includes model and coefficient estimation with predictions and variable selection. The package uses state-of-the-art computational statistics techniques like parallelization, model-based optimization, and covariance tapering. This allows the user to work with (S)VC models in a computationally efficient manner, i.e., model estimation on large data sets is possible in a feasible amount of time. © 2021, CC BY.

关键词： Gaussian distribution

CEMRACS 2017: numerical probabilistic approach to MFG

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arXiv 2018年

作者： Angiuli, Andrea Graves, Christy V. Li, Houzhi Chassagneux, Jean-François Delarue, François Carmona, René Department of Statistics and Applied Probability University of California Santa Barbara Program in Applied and Computational Mathematics Princeton University Laboratoire de Probabilités Modélisation et Statistiques Université Paris Diderot Laboratoire Jean-Alexandre Dieudonné Université de Nice Sophia-Antipolis Operations Research and Financial Engineering Bendheim Center for Finance Princeton University

This project investigates numerical methods for solving fully coupled forward-backward stochastic differential equations (FBSDEs) of McKean-Vlasov type. Having numerical solvers for such mean field FBSDEs is of interest because of the potential application of these equations to optimization problems over a large population, say for instance mean field games (MFG) and optimal mean field control problems. Theory for this kind of problems has met with great success since the early works on mean field games by Lasry and Lions, see [27], and by Huang, Caines, and Malhamé, see [24]. Generally speaking, the purpose is to understand the continuum limit of optimizers or of equilibria (say in Nash sense) as the number of underlying players tends to infinity. When approached from the probabilistic viewpoint, solutions to these control problems (or games) can be described by coupled mean field FBSDEs, meaning that the coefficients depend upon the own marginal laws of the solution. In this note, we detail two methods for solving such FBSDEs which we implement and apply to five benchmark problems. The first method uses a tree structure to represent the pathwise laws of the solution, whereas the second method uses a grid discretization to represent the time marginal laws of the solutions. Both are based on a Picard scheme;importantly, we combine each of them with a generic continuation method that permits to extend the time horizon (or equivalently the coupling strength between the two equations) for which the Picard iteration converges. Copyright © 2018, The Authors. All rights reserved.

关键词： Numerical methods

Extended virtual detector theory including quantum interferences

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arXiv 2020年

作者： Xu, Rui-Hua Wang, Xu Eberly, J.H. Institute of Applied Physics and Computational Mathematics Beijing100094 China Graduate School China Academy of Engineering Physics Beijing100193 China Department of Physics and Astronomy University of Rochester RochesterNY14627 United States

We extend our earlier "virtual detector" method [X. Wang, J. Tian, and J. H. Eberly, Phys. Rev. Lett. 110, 243001 (2013)], a hybrid quantum mechanical and classical trajectory method, to include phases in the classical trajectories. Effects of quantum interferences, lost in the earlier method, are restored. The obtained photoelectron momentum distributions agree well with the corresponding numerical solutions of the time-dependent Schrödinger equation. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum interference devices

Quantum Chaos of a Kicked Particle in an Infinite Potential Well

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Physical Review Letters 1999年第21期82卷 4224-4224页

作者： Bambi Hu Baowen Li Jie Liu Yan Gu Department of Physics and Centre for Nonlinear Studies Hong Kong Baptist University Hong Kong China Department of Physics University of Houston Texas 77204-5506 Institute of Applied Physics and Computational Mathematics P.O. Box 8009 Beijing 100088 China Center for Fundamental Physics University of Science and Technology of China Hefei China

We study quantum chaos in a non-KAM system exemplified by a particle in an infinite potential well subject to a periodic kicking force. For a small perturbation K, the classical phase space displays a stochastic web structure, and the diffusion coefficient scales as D∝K2.5. However, in the large K regime, D∝K2. Quantum mechanically, we observe that the level spacing statistics of the quasieigenenergies changes from Poisson to Wigner distribution as K increases. The quasieigenstates are power-law localized for small K and extended for large K. Possible experimental realization of this model is also discussed.

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A Differential Effect Approach to Partial Identification of Treatment Effects

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arXiv 2023年

作者： Chen, Kan Wang, Bingkai Small, Dylan S. Graduate Group of Applied Mathematics and Computational Science School of Arts and Sciences University of Pennsylvania PhiladelphiaPA United States Department of Statistics and Data Science The Wharton School University of Pennsylvania PhiladelphiaPA United States

We consider identification and inference for the average treatment effect and heterogeneous treatment effect conditional on observable covariates in the presence of unmeasured confounding. Since point identification of these treatment effects is not achievable without strong assumptions, we obtain bounds on these treatment effects by leveraging differential effects, a tool that allows for using a second treatment to learn the effect of the first treatment. The differential effect is the effect of using one treatment in lieu of the other. We provide conditions under which differential treatment effects can be used to point identify or partially identify treatment effects. Under these conditions, we develop a flexible and easy-to-implement semi-parametric framework to estimate bounds and leverage a two-stage approach to conduct statistical inference on effects of interest. The proposed method is examined through a simulation study and a case study that investigates the effect of smoking on the blood level of cadmium using the National Health and Nutrition Examination Survey. © 2023, CC BY.

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Density Functional Theory Study on Organic Dye Sensitizers Containing Bis-dimethylfluorenyl Amino Benzofuran

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Chinese Journal of Chemical Physics 2009年第5期22卷 489-496,I0001页

作者： Cai-rong Zhang Zi-jiang Liu Yu-hong Chen Jun Ma Hong-shan Chen Mei-ling Zhang State Key Laboratory of Gansu Advanced Non-ferrous Metal Materials Lanzhou University of Technology Lanzhou 730050 China Department of Applied Physics Lanzhou University of Technology Lanzhou 730050 China Institute of Applied Physics and Computational Mathematics Beefing 100088 China Institute of Electronic Information Science and Technology Lanzhou City Universiy Lanzhou 730070 China College of Physics and Electronic Engineering Northwest Normal University Lanzhou 730070 China

The geometries, electronic structures, polarizabilities and hyperpolarizabilities, as well as the UV-Vis spectra of the two organic dye sensitizers containing bis-dimethylfluorenyl amino benzofuran were studied via density functional theory （DFT） and time-dependent DFT. The features of electronic absorption spectra were assigned on account of the agreement between the experiment and the calculations. The absorption bands in visible region are related to photoinduced electron transfer processes, and the dimethylfluorenyl amino benzo[b]furan groups are major chromophore that contributed to the sensitization of photo-to-current conversion. The role of vinylene group in geometry, electronic structure and spectra property is analyzed according to the comparative study of the dyes.

关键词： Dye sensitizer Electronic structure Density functional theory Absorptionspectra

A non-Gaussian spatio-temporal model for daily wind speeds based on a multivariate skew-t distribution

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arXiv 2017年

作者： Tagle, Felipe Castruccio, Stefano Crippa, Paola Genton, Marc G. Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre DameIN46556 United States Department of Civil and Environmental Engineering and Earth Sciences University of Notre Dame Notre DameIN46556 United States Statistics Program King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

Facing increasing domestic energy consumption from population growth and industrialization, Saudi Arabia is aiming to reduce its reliance on fossil fuels and to broaden its energy mix by expanding investment in renewable energy sources, including wind energy. A preliminary task in the development of wind energy infrastructure is the assessment of wind energy potential, a key aspect of which is the characterization of its spatio-temporal behavior. In this study we examine the impact of internal climate variability on seasonal wind power density uctuations over Saudi Arabia using 30 simulations from the Large Ensemble Project (LENS) developed at the National Center for Atmospheric Research. Furthermore, a spatio-temporal model for daily wind speed is proposed with neighbor-based cross-temporal dependence, and a multivariate skewt distribution to capture the spatial patterns of higher order moments. The model can be used to generate synthetic time series over the entire spatial domain that adequately reproduce the internal variability of the LENS dataset. Copyright © 2017, The Authors. All rights reserved.

关键词： Wind power