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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Shallow Cumulus in WRF Parameterizations Evaluated against LASSO Large-Eddy Simulations

Abstract Representation of shallow cumulus is a challenge for mesoscale numerical weather prediction models. These cloud fields have important effects on temperature, solar irradiance, convective initiation, and pollutant transport, among other processes. Recent improvements to physics schemes available in the Weather Research and Forecasting (WRF) Model aim to improve representation of shallow cumulus, in particular over land. The DOE LES ARM Symbiotic Simulation and Observation Workflow (LASSO) project provides several cases that we use here to test the new physics improvements. The LASSO cases use multiple large-scale forcings to drive large-eddy simulations (LES), and the LES output is easily compared to output from WRF single-column simulations driven with the same initial conditions and forcings. The new Mellor–Yamada–Nakanishi–Niino (MYNN) eddy diffusivity mass-flux (EDMF) boundary layer and shallow cloud scheme produces clouds with timing, liquid water path (LWP), and cloud fraction that agree well with LES over a wide range of those variables. Here we examine those variables and test the scheme’s sensitivity to perturbations of a few key parameters. We also discuss the challenges and uncertainties of single-column tests. The older, simpler total energy mass-flux (TEMF) scheme is included for comparison, and its tuning is improved. This is the first published use of the LASSO cases for parameterization development, and the first published study to use such a large number of cases with varying cloud amount. This is also the first study to use a more precise combined infrared and microwave retrieval of LWP to evaluate modeled clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Quantum Approach for Implementing Fixed-Point Arithmetic in Solving Ordinary Differential Equations

Differential equations (DEs) serve as fundamental tools in mathematical modeling across scientific disciplines, yet classical numerical solvers face limitations with large-scale or computationally intensive problems. This study explores a quantum-inspired approach to solving DEs, combining quantum- inspired techniques with classical methods. It focuses on fixed- point arithmetic on quantum circuits, utilizing basic quantum gates to manipulate DE solutions. We expand upon the techniques introduced by Zanger et al. [Quantum, 5, 502 (2021)] by offering a precise computation for a fixed-point signed multiplication scheme, while also presenting a quantum circuit capable of executing the fixed-point division algorithm. We demonstrate the feasibility of our approach through the simulation of a linear Ordinary Differential Equation (ODE), where initial conditions and parameters are encoded into quantum circuits using fixed- point representation. By executing sequences of quantum gates mimicking numerical integration steps, we obtain approximate solutions to the ODE with specified fixed-point precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A Quantum Approach for Implementing Fixed-Point Arithmetic in Solving Ordinary Differential Equations

Differential equations (DEs) serve as fundamental tools in mathematical modeling across scientific disciplines, yet classical numerical solvers face limitations with large-scale or computationally intensive problems. This study explores a quantum-inspired approach to solving DEs, combining quantum-inspired techniques with classical methods. It focuses on fixed-point arithmetic on quantum circuits, utilizing basic quantum gates to manipulate DE solutions. We expand upon the techniques introduced by Zanger et al. [Quantum, 5, 502 (2021)] by offering a precise computation for a fixed-point signed multiplication scheme, while also presenting a quantum circuit capable of executing the fixed-point division algorithm. We demonstrate the feasibility of our approach through the simulation of a linear Ordinary Differential Equation (ODE), where initial conditions and parameters are encoded into quantum circuits using fixed-point representation. By executing sequences of quantum gates mimicking numerical integration steps, we obtain approximate solutions to the ODE with specified fixed-point precision.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Management of Digital Equipment in Preproduction by Means of Uniform Numeric Control Language

The requirements on preproduction and the control software for various digital machining systems (numerically controlled machine tools, robot manipulators, additive manufacturing equipment) in flexible production are considered. By analysis of existing programming languages for digital equipment, UNCL (Uniform Numeric Control Language) has been developed for standard representation of control commands. The use of UNCL in verifying program operation on a machining simulator is considered. Software for the translation of control programs (specified in CLDATA formats and in ISO code) to the invariant format of the universal language is described. The postprocessing of control software from the universal language into programs in commonly used digital control systems is also considered.

42 ENGINEERING↗
DOE OSTI2024

Using MARCUS, MICRE, and COMBLE data to improve understanding and modeling of cloud, aerosol, and boundary layer processes at high-latitudes

Because it is believed general circulation (GCM) and numerical weather prediction (NWP) models underestimate shortwave radiation over the Southern Ocean (SO) due to inadequate representations of boundary layer (BL) and cloud processes, it is critical to improve our understanding of key aerosol, cloud, precipitation, and BL processes. Over the north Atlantic Ocean (NA), cold-air outbreaks are common, yet few studies of the aerosol and environmental controls of the associated convective BL clouds exist as needed to develop and evaluate GCM representations. Although processes cannot be observed, cloud and aerosol properties can be measured in-situ or remotely retrieved, which when combined with numerical simulations enable process level understanding required to improve model representations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

A Grobner Basis Solution for Lightning Ground Flash Fraction Retrieval

A Bayesian inversion method was previously introduced for retrieving the fraction of ground flashes in a set of flashes observed from a (low earth orbiting or geostationary) satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters, a scalar function was minimized by a numerical method. In order to improve this optimization, we introduce a Grobner basis solution to obtain analytic representations of the model parameters that serve as a refined initialization scheme to the numerical optimization. Using the Grobner basis, we show that there are exactly 2 solutions involving the first 3 moments of the (exponentially distributed) data. When the mean of the ground flash optical characteristic (e.g., such as the Maximum Group Area, MGA) is larger than that for cloud flashes, then a unique solution can be obtained.

Solakiewicz, Richard↗
NASA NTRS2011

Tests of the Grobner Basis Solution for Lightning Ground Flash Fraction Retrieval

Satellite lightning imagers such as the NASA Tropical Rainfall Measuring Mission Lightning Imaging Sensor (TRMM/LIS) and the future GOES-R Geostationary Lightning Mapper (GLM) are designed to detect total lightning (ground flashes + cloud flashes). However, there is a desire to discriminate ground flashes from cloud flashes from the vantage point of space since this would enhance the overall information content of the satellite lightning data and likely improve its operational and scientific applications (e.g., in severe weather warning, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method was previously introduced for retrieving the fraction of ground flashes in a set of flashes observed from a satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters (one of which is the ground flash fraction), a scalar function was minimized by a numerical method. In order to improve this optimization, a Grobner basis solution was introduced to obtain analytic representations of the model parameters that serve as a refined initialization scheme to the numerical optimization. In this study, we test the efficacy of the Grobner basis initialization using actual lightning imager measurements and ground flash truth derived from the national lightning network.

Koshak, William↗
DOE OSTI2017

Reflection and Transmission of Plane Electromagnetic Waves by a Geologic Layer.

Electric field and magnetic field reflection and transmission responses generated by a plane wave normally incident onto a finite - thickness geologic layer are mathematically derived and numerically evaluated. A thin layer with enhanced electric current conductivity and/or magnetic permeability is a reasonable geophysical representation of a hydraulic fracture inject ed with a high - contrast proppant pack. Both theory and numerics indicate that backward - and forward - scattered electromagnetic wavefields are potentially observable in a field experiment, despite the extreme thinness of a fracture compared to a typical low - frequency electromagnetic wavelength. The First Born Approximation (FBA) representation of layer scattering, significant for inversion studies, is shown to be accurate for a thin layer with mild medium parameter (i.e., conductivity, permeability, and per mittivity) contrasts with the surrounding homogeneous wholespace. However, FBA scattering theory breaks down for thick layers and strong parameter contrasts. ACKNOWLEDGEMENTS Sandia National Laboratories is a multi - mission laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy's National Nuclear Security Administration under contract DE - AC04 - 94AL85000. This research is conducted under the auspices of CRADA (Cooperative Research and Development Agreement) SC11/01780.00 between Carbo Ceramics Inc. and Sandia National Laboratories. The author acknowledges former Carbo R&D Vic e - President Mr. Chad Cannan and former SNL Geophysics Department manage r Ms. Amy Halloran for their interest i n and support of this work. Technical discussions with Project Manager and Principal Investigator Dr. Chester J. Weiss of the SNL Geophysics Department greatly benefited this work. Dr. Lewis C. Bartel, formerly with S NL and presently a consultant to Carbo Ceramics, provided many useful and intuitive insights, and is acknowledged as the originator of the concept underpinning a recent patent grant (Aldridge and Bartel, 2016) involving electromagnetic wave scattering.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

GASP Advancements With Symbolic Computations, Optimization, and Decoupled Numerical Methods

NASA is exploring advancements in hybrid-electric propulsion concepts for aircraft design. A new analysis capability has been deployed at NASA’s Ames Research Center using a new mathematical modeling framework in Python that leverages symbolic representation of mathematical expressions, optimization-based problem formulations, and standalone numerical methods. This capability, called Gascon, has been verified against NASA’s General Aviation Synthesis Program (GASP) results for several vehicles that exercise the analysis capability for a variety of aircraft classes and engine models, including both turbofans and turboprops. We believe this capability will set the stage for more rapid development of novel aircraft models with more flexible design assessments using optimization, and more traceable analysis for reproducibility. Additionally, a novel Pareto optimization-based design space exploration that shows the trade between range flown and fuel burn by manipulating the thrust split during cruise for a true parallel hybrid aircraft was developed by leveraging the unique features of Gascon.

aircraft design↗
DOE OSTI2012

Controlled Nonlinear Stochastic Delay Equations: Part II: Approximations and Pipe-Flow Representations

This is the second part of a work dealing with key issues that have not been addressed in the modeling and numerical optimization of nonlinear stochastic delay systems. We consider new classes of models, such as those with nonlinear functions of several controls (such as products), each with is own delay, controlled random Poisson measure driving terms, admissions control with delayed retrials, and others. Part I was concerned with issues concerning the class of admissible controls and their approximations, since the classical definitions are inadequate for our models. This part is concerned with transportation equation representations and their approximations. Such representations of nonlinear stochastic delay models have been crucial in the development of numerical algorithms with much reduced memory and computational requirements. The representations for the new models are not obvious and are developed. They also provide a template for the adaptation of the Markov chain approximation numerical methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1976

Pines nonsingular gravitational potential derivation, description and implementation

An engineering interpretation of and some minor corrections to previously completed work on a uniform representation of the gravitational potential and its derivatives (with emphasis on avoiding the usual singularity at the pole) were presented. The physical meaning of the variables was explained, the derivation of results was separated into smaller parts for easier reading, some additional recurrence relations for the derived Legendre polynomials were included and compared, and a computer program implementing this formulation was presented. Numerical experiments have shown that the use of this representation, besides removing the singularity, substantially increases the speed of the computation.

Spencer, J. L.↗
NASA NTRS1976

Magnetic dynamo action in two-dimensional turbulent magneto-hydrodynamics

Two-dimensional magnetohydrodynamic turbulence is explored by means of numerical simulation. Previous analytical theory, based on non-dissipative constants of the motion in a truncated Fourier representation, is verified by following the evolution of highly non-equilibrium initial conditions numerically. Dynamo action (conversion of a significant fraction of turbulent kinetic energy into long-wavelength magnetic field energy) is observed. It is conjectured that in the presence of dissipation and external forcing, a dual cascade will be observed for zero-helicity situations. Energy will cascade to higher wave numbers simultaneously with a cascade of mean square vector potential to lower wave numbers, leading to an omni-directional magnetic energy spectrum which varies as 1/k 3 at lower wave numbers, simultaneously with a buildup of magnetic excitation at the lowest wave number of the system. Equipartition of kinetic and magnetic energies is expected at the highest wave numbers in the system.

Fyfe, D.↗
NASA NTRS1977

Magnetic dynamo action in two-dimensional turbulent magneto-hydrodynamics

Two-dimensional magnetohydrodynamic turbulence is explored by means of numerical simulation. Previous analytical theory, based on non-dissipative constants of the motion in a truncated Fourier representation, is verified by following the evolution of highly non-equilibrium initial conditions numerically. Dynamo action (conversion of a significant fraction of turbulent kinetic energy into long-wavelength magnetic field energy) is observed. It is conjectured that in the presence of dissipation and external forcing, a dual cascade will be observed for zero-helicity situations. Energy will cascade to higher wavenumbers simultaneously with a cascade of mean square vector potential to lower wavenumbers, leading to an omni-directional magnetic energy spectrum.

Fyfe, D.↗
DOE OSTI2021

An Introduction to Word Embeddings and Language Models

Language models have advanced at a phenomenal pace over the past decade. This document provides a short introduction to terminology, word embeddings (aka low-dimensional representations), and popular large-scale language models (LMs). Word embeddings are used to represent words as numerical vectors and are context-independent, meaning a word can only have a single representation (e.g., club can only be club sandwich, not golf club ). Language models can determine the probability of a given sequence of words occurring in a sentence and can provide context to distinguish between words and phrases that sound similar. LMs are context-dependent (e.g., club can be club sandwich or golf club ) and largely fall in two main classes – autoregressive and autoencoding models. Autoregressive models are pretrained on the classic language modeling task: guess the next token having read all the previous ones. Those models can be fine-tuned and achieve great results on many tasks, the most natural application is text generation. A typical example of such models is GPT, but others include GPT-2, GPT-3, CTLR, TRANSFORMER-XL, REFORMER, XLNET. Autoencoding models are pretrained by corrupting the input tokens in some way and trying to reconstruct the original sentence. They can be fine-tuned and achieve great results on many tasks such as text generation, but their most natural application is sentence classification or token classification. A typical example of such models is BERT, but others include ROBERTA, ALBERT, XML, XML-ROBERTA, FLAUBERT AND LONGFORMER.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

On the equivalence of dynamically orthogonal and bi-orthogonal methods: Theory and numerical simulations

The Karhunen–Lòeve (KL) decomposition provides a low-dimensional representation for random fields as it is optimal in the mean square sense. Although for many stochastic systems of practical interest, described by stochastic partial differential equations (SPDEs), solutions possess this low-dimensional character, they also have a strongly time-dependent form and to this end a fixed-in-time basis may not describe the solution in an efficient way. Motivated by this limitation of standard KL expansion, Sapsis and Lermusiaux (2009) [26] developed the dynamically orthogonal (DO) field equations which allow for the simultaneous evolution of both the spatial basis where uncertainty ‘lives’ but also the stochastic characteristics of uncertainty. Recently, Cheng et al. (2013) [28] introduced an alternative approach, the bi-orthogonal (BO) method, which performs the exact same tasks, i.e. it evolves the spatial basis and the stochastic characteristics of uncertainty. In the current work we examine the relation of the two approaches and we prove theoretically and illustrate numerically their equivalence, in the sense that one method is an exact reformulation of the other. We show this by deriving a linear and invertible transformation matrix described by a matrix differential equation that connects the BO and the DO solutions. We also examine a pathology of the BO equations that occurs when two eigenvalues of the solution cross, resulting in an instantaneous, infinite-speed, internal rotation of the computed spatial basis. We demonstrate that despite the instantaneous duration of the singularity this has important implications on the numerical performance of the BO approach. On the other hand, it is observed that the BO is more stable in nonlinear problems involving a relatively large number of modes. Several examples, linear and nonlinear, are presented to illustrate the DO and BO methods as well as their equivalence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud top occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals

A new method for fast evaluation of high dimensional integrals arising in quantum mechanics is proposed. Here, the method is based on sparse approximation of a high dimensional function followed by a low-rank compression. In the first step, we interpret the high dimensional integrand as a tensor in a suitable tensor product space and determine its entries by a compressed sensing based algorithm using only a few function evaluations. Secondly, we implement a rank reduction strategy to compress this tensor in a suitable low-rank tensor format using standard tensor compression tools. This allows representing a high dimensional integrand function as a small sum of products of low dimensional functions. Finally, a low dimensional Gauss–Hermite quadrature rule is used to integrate this low-rank representation, thus alleviating the curse of dimensionality. Finally, numerical tests on synthetic functions, as well as on energy correction integrals for water and formaldehyde molecules demonstrate the efficiency of this method using very few function evaluations as compared to other integration strategies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Value of abstraction in performance assessment – When is a higher level of detail necessary?

In this study, different approaches in performance assessment (PA) of the long-term safety of a repository for radioactive waste were examined. This investigation was carried out as part of the DECOVALEX-2023 project, an international collaborative effort for research and model comparison. One specific task of the DECOVALEX-2023 project was the Salt Performance Assessment Modelling task (Salt PA), which aimed at comparing various models and methods employed in the performance assessment of deep geological repositories in salt. In the context of the Salt PA task, three distinct teams from SNL (United States), Quintessa Ltd (United Kingdom), and GRS (Germany) examined the consequences of employing different levels of abstractions when modelling the repository's geometry and implementing various features and processes, using the example of a simple hypothetical repository structure in domal salt. Each team applied their own tools: PFLOTRAN (SNL), QPAC (Quintessa) and LOPOS (GRS). These differ essentially regarding numerical concept and degree of detail in the representation of the underlying physical processes. The discussion focused on when simplifications can be appropriately applied and what consequences result from them. Furthermore, it was explored when and if a higher level of fidelity in geometry or physical processes is required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗