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The Relative, Correlation Based Magnitude Detection Capability at the North Korean Test Site using an IMS Array
Abstract Not Provided
Youngs-Type Material Strength Model in the Besnard-Harlow-Rauenzahn Turbulence Equations
Youngs [AWE Report Number 96/96, 1992] has augmented a two-phase turbulence model to account for material strength. Here we adapt the model of Youngs to the turbulence model for the mixture developed by Besnard, Harlow, and Rauenzahn [LANL Report LA-10911, 1987].
GPU Acceleration of Mean Free Path Based Kernel Density Estimators in Monte Carlo Neutronics Simulations with Curvilinear Geometries
KDEs show potential reducing variance for global solutions (flux, reaction rates) when compared to histogram solutions.
Introduction to Control Theory. Part 2. Laplace Transforms and Linear Systems
Presentation for summer students. Start by considering linear differential equations, and how to solve them. The Laplace Transform is a great tool for solving linear differential equations.
Introduction to Control Theory. Part 3. State Space, Stability, and Lyapunov Functions
Presentation to summer students.
In-Situ Visualization Experiments with ParaView Cinema in RAGE
A previous paper described some numerical experiments performed using the ParaView/Catalyst in-situ visualization infrastructure deployed in the Los Alamos RAGE radiation-hydrodynamics code to produce images from a running large scale 3D ICF simulation. One challenge of the in-situ approach apparent in these experiments was the difficulty of choosing parameters likes isosurface values for the visualizations to be produced from the running simulation without the benefit of prior knowledge of the simulation results and the resultant cost of recomputing in-situ generated images when parameters are chosen suboptimally. A proposed method of addressing this difficulty is to simply render multiple images at runtime with a range of possible parameter values to produce a large database of images and to provide the user with a tool for managing the resulting database of imagery. Recently, ParaView/Catalyst has been extended to include such a capability via the so-called Cinema framework. Here I describe some initial experiments with the first delivery of Cinema and make some recommendations for future extensions of Cinema’s capabilities.
Electricity Capacity Expansion Modeling, Analysis, and Visualization. A Summary of High-Renewable Modeling Experience for China
Mathematical and computational models are widely used for the analysis and design of both physical and financial systems. Modeling the electric grid is of particular importance to China for three reasons. First, power-sector assets are expensive and long-lived, and they are critical to any country's development. China's electric load, transmission, and other energy-related infrastructure are expected to continue to grow rapidly; therefore it is crucial to understand and help plan for the future in which those assets will operate (NDRC ERI 2015). Second, China has dramatically increased its deployment of renewable energy (RE), and is likely to continue further accelerating such deployment over the coming decades. Careful planning and assessment of the various aspects (technical, economic, social, and political) of integrating a large amount of renewables on the grid is required. Third, companies need the tools to develop a strategy for their own involvement in the power market China is now developing, and to enable a possible transition to an efficient and high RE future.
RELAP-7 Theory Manual
This document summarizes the physical models and mathematical formulations used in the RELAP-7 code.
Linear Solvers Overview
This document presents an overview of various mathematical solvers.
Electricity Capacity Expansion Modeling, Analysis, and Visualization: A Summary of High-Renewable Modeling Experiences (Chinese Translation)
This is the Chinese translation of NREL/TP-6A20-64831. Mathematical and computational models are widely used for the analysis and design of both physical and financial systems. Modeling the electric grid is of particular importance to China for three reasons. First, power-sector assets are expensive and long-lived, and they are critical to any country's development. China's electric load, transmission, and other energy-related infrastructure are expected to continue to grow rapidly; therefore it is crucial to understand and help plan for the future in which those assets will operate. Second, China has dramatically increased its deployment of renewable energy (RE), and is likely to continue further accelerating such deployment over the coming decades. Careful planning and assessment of the various aspects (technical, economic, social, and political) of integrating a large amount of renewables on the grid is required. Third, companies need the tools to develop a strategy for their own involvement in the power market China is now developing, and to enable a possible transition to an efficient and high RE future.
Challenges and Successes of Solving Binary Quadratic Programming Benchmarks on the DW2X QPU
This presentation discusses some of the challenges and successes of the quantitative benchmarking efforts performed at LANL.
Contextual Multi-armed Bandits under Feature Uncertainty
We study contextual multi-armed bandit problems under linear realizability on rewards and uncertainty (or noise) on features. For the case of identical noise on features across actions, we propose an algorithm, coined NLinRel, having O(T⁷/₈(log(dT)+K√d)) regret bound for T rounds, K actions, and d-dimensional feature vectors. Next, for the case of non-identical noise, we observe that popular linear hypotheses including NLinRel are impossible to achieve such sub-linear regret. Instead, under assumption of Gaussian feature vectors, we prove that a greedy algorithm has O(T²/₃√log d)regret bound with respect to the optimal linear hypothesis. Utilizing our theoretical understanding on the Gaussian case, we also design a practical variant of NLinRel, coined Universal-NLinRel, for arbitrary feature distributions. It first runs NLinRel for finding the ‘true’ coefficient vector using feature uncertainties and then adjust it to minimize its regret using the statistical feature information. We justify the performance of Universal-NLinRel on both synthetic and real-world datasets.
PowerModels.jl a Brief Introduction
This is a description of powermodels.jl for power network optimization.
Fast Approximate Union Volume in High Dimensions with Line Samples
The classical problem of calculating the volume of the union of d-dimensional balls is known as "Union Volume." We present line-sampling approximation algorithms for Union Volume. Our methods may be extended to other Boolean operations, such as setminus; or to other shapes, such as hyper-rectangles. The deterministic, exact approaches for Union Volume do not scale well to high dimensions. However, we adapt several of these exact approaches to approximation algorithms based on sampling. We perform local sampling within each ball using lines. We have several variations, depending on how the overlapping volume is partitioned, and depending on whether radial, axis-aligned, or other line patterns are used. Our variations fall within the family of Monte Carlo sampling, and hence have about the same theoretical convergence rate, 1 /$\sqrt{M}$, where M is the number of samples. In our limited experiments, line-sampling proved more accurate per unit work than point samples, because a line sample provides more information, and the analytic equation for a sphere makes the calculation almost as fast. We performed a limited empirical study of the efficiency of these variations. We suggest a more extensive study for future work. We speculate that different ball arrangements, differentiated by the distribution of overlaps in terms of volume and degree, will benefit the most from patterns of line samples that preferentially capture those overlaps. Acknowledgement We thank Karl Bringman for explaining his BF-ApproxUnion (ApproxUnion) algorithm [3] to us. We thank Josiah Manson for pointing out that spoke darts oversample the center and we might get a better answer by uniform sampling. We thank Vijay Natarajan for suggesting random chord sampling. The authors are grateful to Brian Adams, Keith Dalbey, and Vicente Romero for useful technical discussions. This work was sponsored by the Laboratory Directed Research and Development (LDRD) Program at Sandia National Laboratories. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (ASCR), Applied Mathematics Program. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.
Grid Modernization Initiative Peer Review: Extreme Event Modeling 1.4.17 [Slides]
Abstract not provided.
Design, analysis and numerical experiments for the virtual element p and hp approximations of elliptic eigenvalue problems
We discuss the p- and the hp-versions of the virtual element method for the approximation of the eigenvalues of elliptic operators with a potential term on polygonal meshes. An application of this model is provided by the Schr¨odinger equation with a pseudo-potential term. We present in details the analysis of the p-version of the method, proving the exponential convergence in the case of analytic eigenfunctions. The theoretical results are supplied with a wide set of experiments. We also show numerically that, in the case of eigenfunctions with finite Sobolev regularity, an exponential approximation of the eigenvalues in terms of the cubic root of the number of degrees of freedom can be obtained by employing hp-refinements. Importantly, the geometric flexibility of polygonal meshes is exploited in the construction of the hp-spaces.