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Book Quantification and Reduction of the Uncertainty in Mass Balance Models by Monte Carlo Analysis of Prior Data

Download or read book Quantification and Reduction of the Uncertainty in Mass Balance Models by Monte Carlo Analysis of Prior Data written by and published by . This book was released on 1991 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: The general objective of this workshop is to investigate and discuss methods by which uncertainties in mass balance models for toxics in the Great Lakes may be reduced. As described by the workshop prospectus, this paper is focused on problems of reducing (and quantifying) uncertainty as they relate to ''in situ field observations/system response measurements for the establishment of initial conditions, boundary conditions, calibration/confirmation data sets, and model post-audit data sets.'' I have taken this description to refer not only to the evaluation of uncertainty in the field observations themselves, but also to the uncertainty associated the analyses of in situ observations as they interact in the overall modeling process. Thus, I will be concerned here with quantification and reduction of uncertainty both (1) as they may be applied to descriptions of the system that is being modeled and (2) as they may be associated with model simulations.

Book Scientific and Technical Aerospace Reports

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1992 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Energy Research Abstracts

Download or read book Energy Research Abstracts written by and published by . This book was released on 1992 with total page 886 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Government reports annual index

Download or read book Government reports annual index written by and published by . This book was released on 199? with total page 1114 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Detailed Technical Plan for the Great Lakes Environmental Research Laboratory

Download or read book Detailed Technical Plan for the Great Lakes Environmental Research Laboratory written by Great Lakes Environmental Research Laboratory and published by . This book was released on 1980 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Winter Waterfront   Year round Use in Metropolitan Toronto

Download or read book Winter Waterfront Year round Use in Metropolitan Toronto written by Xenia Klinger and published by . This book was released on 1991 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Correlations in Monte Carlo Eigenvalue Simulations

Download or read book Correlations in Monte Carlo Eigenvalue Simulations written by Jilang Miao and published by . This book was released on 2018 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods have mostly been used as a benchmark tool for other transport and diffusion methods in nuclear reactor analysis. One important feature of Monte Carlo calculations is the report of the variance of the estimators as a measure of uncertainty. In the current production codes, the assumption of independence of neutron generations in Monte Carlo eigenvalue simulations leads to the oversimplified estimate of the uncertainty of tallies. The correlation of tallies between neutron generations can make reported uncertainty underestimated by a factor of 8 in assembly size tallies in a typical LWR. This work analyzes the variance/uncertainty convergence rate in Monte Carlo eigenvalue simulations and develops different methods to properly report the variance. To correct the underestimated variance as a post-processing step, a simple correction factor can be calculated from the correlation coefficients estimated from a sufficient number of active generations and fitted to decreasing exponentials. If the variance convergence rate is needed before or during the simulation to optimize the run strategy (number of generations and neutrons per generation), a discrete model can be constructed from the inactive generations that can predict the correlation behavior of the original problem. Since it is not efficient to perform variance correction to all tallies on all problems, a simple correlation indicator is also developed to quickly determine the potential impact of correlations on a given tally in a given problem. This can help decide if more complicated correction analysis or the use of independent simulations should be used to calculate the true variance. Run strategy to reduce correlations is also investigated by introducing the notion of delayed neutrons. A predictive model for the new source update scheme was developed to help identify optimal delayed neutron parameters before implementing in OpenMC. Optimal run strategies in terms of delayed bank size, frequency of delayed bank sampling and true simulation costs are proposed.

Book Probabilistic Machine Learning for Finance and Investing

Download or read book Probabilistic Machine Learning for Finance and Investing written by Deepak K. Kanungo and published by "O'Reilly Media, Inc.". This book was released on 2023-08-14 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether based on academic theories or discovered empirically by humans and machines, all financial models are at the mercy of modeling errors that can be mitigated but not eliminated. Probabilistic ML technologies are based on a simple and intuitive definition of probability and the rigorous calculus of probability theory. Unlike conventional AI systems, probabilistic machine learning (ML) systems treat errors and uncertainties as features, not bugs. They quantify uncertainty generated from inexact model inputs and outputs as probability distributions, not point estimates. Most importantly, these systems are capable of forewarning us when their inferences and predictions are no longer useful in the current market environment. These ML systems provide realistic support for financial decision-making and risk management in the face of uncertainty and incomplete information. Probabilistic ML is the next generation ML framework and technology for AI-powered financial and investing systems for many reasons. They are generative ensembles that learn continually from small and noisy financial datasets while seamlessly enabling probabilistic inference, prediction and counterfactual reasoning. By moving away from flawed statistical methodologies (and a restrictive conventional view of probability as a limiting frequency), you can embrace an intuitive view of probability as logic within an axiomatic statistical framework that comprehensively and successfully quantifies uncertainty. This book shows you why and how to make that transition.

Book Government Reports Announcements   Index

Download or read book Government Reports Announcements Index written by and published by . This book was released on 1996 with total page 1428 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling

Download or read book Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling written by José Eduardo Souza De Cursi and published by Springer Nature. This book was released on 2020-08-19 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings book discusses state-of-the-art research on uncertainty quantification in mechanical engineering, including statistical data concerning the entries and parameters of a system to produce statistical data on the outputs of the system. It is based on papers presented at Uncertainties 2020, a workshop organized on behalf of the Scientific Committee on Uncertainty in Mechanics (Mécanique et Incertain) of the AFM (French Society of Mechanical Sciences), the Scientific Committee on Stochastic Modeling and Uncertainty Quantification of the ABCM (Brazilian Society of Mechanical Sciences) and the SBMAC (Brazilian Society of Applied Mathematics).

Book FEFLOW

    Book Details:
  • Author : Hans-Jörg G. Diersch
  • Publisher : Springer Science & Business Media
  • Release : 2013-11-22
  • ISBN : 364238739X
  • Pages : 1018 pages

Download or read book FEFLOW written by Hans-Jörg G. Diersch and published by Springer Science & Business Media. This book was released on 2013-11-22 with total page 1018 pages. Available in PDF, EPUB and Kindle. Book excerpt: FEFLOW is an acronym of Finite Element subsurface FLOW simulation system and solves the governing flow, mass and heat transport equations in porous and fractured media by a multidimensional finite element method for complex geometric and parametric situations including variable fluid density, variable saturation, free surface(s), multispecies reaction kinetics, non-isothermal flow and multidiffusive effects. FEFLOW comprises theoretical work, modeling experiences and simulation practice from a period of about 40 years. In this light, the main objective of the present book is to share this achieved level of modeling with all required details of the physical and numerical background with the reader. The book is intended to put advanced theoretical and numerical methods into the hands of modeling practitioners and scientists. It starts with a more general theory for all relevant flow and transport phenomena on the basis of the continuum approach, systematically develops the basic framework for important classes of problems (e.g., multiphase/multispecies non-isothermal flow and transport phenomena, discrete features, aquifer-averaged equations, geothermal processes), introduces finite-element techniques for solving the basic balance equations, in detail discusses advanced numerical algorithms for the resulting nonlinear and linear problems and completes with a number of benchmarks, applications and exercises to illustrate the different types of problems and ways to tackle them successfully (e.g., flow and seepage problems, unsaturated-saturated flow, advective-diffusion transport, saltwater intrusion, geothermal and thermohaline flow).

Book Uncertainty Quantification

Download or read book Uncertainty Quantification written by Christian Soize and published by Springer. This book was released on 2017-04-24 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses in parametric uncertainties, and non-parametric uncertainties with applications from the structural dynamics and vibroacoustics of complex mechanical systems, from micromechanics and multiscale mechanics of heterogeneous materials. Resulting from a course developed by the author, the book begins with a description of the fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification. It proceeds with a well carried out description of some basic and advanced methods for constructing stochastic models of uncertainties, paying particular attention to the problem of calibrating and identifying a stochastic model of uncertainty when experimental data is available. This book is intended to be a graduate-level textbook for students as well as professionals interested in the theory, computation, and applications of risk and prediction in science and engineering fields.

Book Uncertainty Quantification and Model Calibration

Download or read book Uncertainty Quantification and Model Calibration written by Jan Peter Hessling and published by BoD – Books on Demand. This book was released on 2017-07-05 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.

Book Uncertainty Quantification in Multiscale Materials Modeling

Download or read book Uncertainty Quantification in Multiscale Materials Modeling written by Yan Wang and published by Woodhead Publishing Limited. This book was released on 2020-03-12 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.

Book Uncertainty Quantification for Maxwell  s Equations Using Stochastic Collocation and Model Order Reduction

Download or read book Uncertainty Quantification for Maxwell s Equations Using Stochastic Collocation and Model Order Reduction written by Peter Benner and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Modeling and simulation are important for the design process of new semiconductor structures. Difficulties proceed from shrinking structures, increasing working frequencies, and uncertainties of materials and geometries. Therefore, we consider the time-harmonic Maxwell\'s equations for the simulation of a coplanar waveguide with uncertain material parameters. To analyze the uncertainty of the system, we use stochastic collocation with Stroud and sparse grid points. The results are compared to a Monte Carlo simulation. Both methods rely on repetitive runs of a deterministic solver. Hence, we compute a reduced model by means of proper orthogonal decomposition to reduce the computational cost. The Monte Carlo simulation and the stochastic collocation are both applied to the full and the reduced model. All results are compared concerning accuracy and computation time.