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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The Relationship Between Catalyst and Solvent in Hydrogenation via Condensed Phase Heterogeneous Catalysis

To understand a system is to understand its components and their sum. Cascading interactions between catalyst, solvent, and reagent create a complex web of influences when heterogeneous catalysis meets the condensed phase. Due to the importance of heterogeneous catalysis in chemical manufacturing, and the present and growing potential of condensed phase chemistries, the understanding of these interactions is of paramount importance. To develop condensed phase heterogeneous catalysis, the field needs to develop understanding of the role of solvent in heterogeneous catalytic hydrogenation. While no small feat, fields such as biofuel and petroleum refining have established certain applicable generalities that can bridge the knowledge gap in emerging technologies such as integrated carbon capture and conversion to materials (IC 3 M). In this review, we thoughtfully probe the current paradigm of condensed phase catalysis by challenging the idea that catalyst and solvent are independent reaction design choices. Challenges such as lack of experimental stability studies and poor resolution on our conceptualization of the condensed phase environment are discussed. Parameters such as viscosity and the dielectric constant, and their role on reaction activity and stability are explored. Knowledge gained from established biomass and petroleum processes is discussed and used to anticipate behavior in novel processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Optimization Simulations for a Gamma-Ray Calibration Standard for a Cyclic Neutron Activation Analysis Pneumatic System at the Penn State Breazeale Reactor

For new experimental setups, the initial testing and calibrations can be expensive and time consuming without prior optimization. However, these issues can be mitigated using realistic modeling and simulation studies of the proposed system a priori. Specifically, an experiment can be performed virtually using realistic simulations and the expected results evaluated to inform adjustments of the experimental setup to achieve optimum results. At the Penn State Breazeale Reactor, a new pneumatic transfer system has been developed for the detection and characterization of short-lived fission fragments to enhance and complement existing nuclear data. The system accomplishes this task by transporting samples cyclically between an assortment of gamma-ray/neutron detectors and the reactor-core vicinity with sub-second transit times. The measured neutron flux paired with simulations of detector response using Geant4 and a custom module for estimating cascade summing effects and corrections were used to select sample-material masses for system characterization. With the optimized sample masses, an experimental counting plan for characterizing the repeatability of the newly developed pneumatic system was developed. Finally, the predictions made with these simulations allowed for optimization of the irradiation sample characteristics and gamma-ray detection system.

cyclic neutron activation, gamma-ray spectroscopy↗
DOE OSTI2025

Angular Correlation Date Measurements with the GeRMAC system

Advanced modeling and simulation efforts have improved at Idaho National Laboratory in recent years with a solid foundation of experimental results. Current computational methods represent significant modeling capabilities but are limited by the accuracy and availability of nuclear data. The creation of pre- and post-processing software tools to address these limitations is fundamental to the improvement of nuclear science modeling capacities. One aspect of predictive modeling tools deals with gamma-rays emitted from radionuclides, including fissile or fissionable material, fission products, or activation products, produced in reactor experiments or other neutron environments. The resulting radionuclides decay in unique ways, providing complications upon measurement as a result of random and cascade, or true, coincidence summing. These effects are not easily quantified during modeling efforts of gamma-ray source terms., The germanium rotational measurements for angular correlation (GeRMAC) system was built to quantify the relative angles for gamma rays emitted by radionuclides of interest to investigate true coincidence, or cascade, summing as well as the nuclear energy levels of decay schemes of interest. Proof of concept studies utilize a series of laboratory check sources to provide validity, and it will soon be used to perform the same measurements for fission products of interest. The resulting data can be used to implement into a Monte Carlo code, such as Geant4, to provide more precise gamma-ray source terms following irradiations of materials.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2016

A Solar-Pumped Fluorescence Model for Line-By-Line Emission Intensities in the B-X, A-X, and X-X Band Systems of 12C14N

We present a new quantitative model for detailed solar-pumped fluorescent emission of the main isotopologue of CN. The derived fluorescence efficiencies permit estimation and interpretation of ro-vibrational infrared line intensities of CN in exospheres exposed to solar (or stellar) radiation. Our g-factors are applicable to astronomical observations of CN extending from infrared to optical wavelengths, and we compare them with previous calculations in the literature. The new model enables extraction of rotational temperature, column abundance, and production rate from astronomical observations of CN in the inner coma of comets. Our model accounts for excitation and de-excitation of rotational levels in the ground vibrational state by collisions, solar excitation to the A(sup 2)Pi(sub I) and B(sup 2)Sum(sup +) electronically excited states followed by cascade to ro-vibrational levels of X(sup 2)Sum(sup +), and direct solar infrared pumping of ro-vibrational levels in the X(sup 2)Sum(sup +) state. The model uses advanced solar spectra acquired at high spectral resolution at the relevant infrared and optical wavelengths and considers the heliocentric radial velocity of the comet (the Swings effect) when assessing the exciting solar flux for a given transition. We present model predictions for the variation of fluorescence rates with rotational temperature and heliocentric radial velocity. Furthermore, we test our fluorescence model by comparing predicted and measured line-by-line intensities for X(sup 2)Sum(sup +) (1-0) in comet C/2014 Q2 (Lovejoy), thereby identifying multiple emission lines observed at IR wavelengths.

Emission↗
NASA NTRS1993

Inertial transfers in the helical decomposition

The directions of the triadic energy transfers assumed in a previous paper agree with the spectral closures, in a similarity range, if the exponent of the power-law energy spectrum is less than unity. The helical interactions showing a strong local energy transfer when the triad is nonlocal, sum up to a reverse cascade unless the spectrum falls off faster than a -7/3 power of the wave number. The energy cascades from each type of helical interaction are calculated for a -5/3 inertial range using the eddy damped quasinormal Markovian model. One type of interaction is responsible for 86 percent of the cascade. The contributions of the two classes of helical interactions to the subgrid-scale eddy viscosity are presented, together with the contributions from the forward and reverse cascading interactions. An application of the assumption on the triadic energy transfers to turbulence under rapid rotation gives a simple argument for the tendency toward nonlinear two-dimensionalization of the flow.

Waleffe, Fabian↗
NASA NTRS2005

Initial Kernel Timing Using a Simple PIM Performance Model

This presentation will describe some initial results of paper-and-pencil studies of 4 or 5 application kernels applied to a processor-in-memory (PIM) system roughly similar to the Cascade Lightweight Processor (LWP). The application kernels are: * Linked list traversal * Sun of leaf nodes on a tree * Bitonic sort * Vector sum * Gaussian elimination The intent of this work is to guide and validate work on the Cascade project in the areas of compilers, simulators, and languages. We will first discuss the generic PIM structure. Then, we will explain the concepts needed to program a parallel PIM system (locality, threads, parcels). Next, we will present a simple PIM performance model that will be used in the remainder of the presentation. For each kernel, we will then present a set of codes, including codes for a single PIM node, and codes for multiple PIM nodes that move data to threads and move threads to data. These codes are written at a fairly low level, between assembly and C, but much closer to C than to assembly. For each code, we will present some hand-drafted timing forecasts, based on the simple PIM performance model. Finally, we will conclude by discussing what we have learned from this work, including what programming styles seem to work best, from the point-of-view of both expressiveness and performance.

BRIEFING CHARTS↗
NASA NTRS1985

LPM effect and primary energy estimations

The distortion of the electron cascade development under LPM effects is now admitted; it consists of an increase of depth of showers origin, of shower maximum T sum max, a decrease of the number of particles at maximum N sub max and results in a flattening and a widening of the cascade transition curve. Connected with the influence of multiple Coulomb scattering on basic electromagnetic processes (bremsstrahlung, pair production), this effect appears at high energy with a threshold dependent on the density of the medium (more than 10 TeV for lead, more than 10 sup 6 TeV in air). Consequently, the electromagnetic components of hadron induced showers in lead and EAS in air calculated for the same hadronic cascades in the different alternative, including or not the LPM effect are examined here.

Bourdeau, M. F.↗
NASA NTRS1988

Real time pipelined system for forming the sum of products in the processing of video data

A 3-by-3 convolver utilizes 9 binary arithmetic units connected in cascade for multiplying 12-bit binary pixel values P sub i which are positive or two's complement binary numbers by 5-bit magnitide (plus sign) weights W sub i which may be positive or negative. The weights are stored in registers including the sign bits. For a negative weight, the one's complement of the pixel value to be multiplied is formed at each unit by a bank of 17 exclusive or gates G sub i under control of the sign of the corresponding weight W sub i, and a correction is made by adding the sum of the absolute values of all the negative weights for each 3-by-3 kernel. Since this correction value remains constant as long as the weights are constant, it can be precomputed and stored in a register as a value to be added to the product PW of the first arithmetic unit.

Wilcox, Brian↗
NASA NTRS1999

Fidelity Analysis of Sampled Imaging Systems

Many modeling, simulation and performance analysis studies of sampled imaging systems are inherently incomplete because they are conditioned on a discrete-input, discrete-output model that only accounts for blurring during image acquisition and additive noise. For those sampled imaging systems where the effects of digital image acquisition, digital filtering and reconstruction are significant, the modeling, simulation and performance analysis should be based on a more comprehensive continuous-input, discrete-processing, continuous-output end-to-end model. This more comprehensive model should properly account for the low-pass filtering effects of image acquisition prior to sampling, the potentially important noiselike effects of the aliasing caused by sampling, additive noise due to device electronics and quantization, the generally high-boost filtering effects of digital processing, and the low-pass filtering effects of image reconstruction. This model should not, however, be so complex as to preclude significant mathematical analysis, particularly the mean-square (fidelity) type of analysis so common in linear system theory. We demonstrate that, although the mathematics of such a model is more complex, the increase in complexity is not so great as to prevent a complete fidelity-metric analysis at both the component level and at the end-to-end system level: that is, computable mean-square-based fidelity metrics are developed by which both component-level and system-level performance can be quantified. In addition, we demonstrate that system performance can be assessed qualitatively by visualizing the output image as the sum of three component images, each of which relates to a corresponding fidelity metric. The cascaded, or filtered, component accounts for the end-to-end system filtering of image acquisition, digital processing, and image reconstruction; the random noise component accounts for additive random noise, modulated by digital processing and image reconstruction filtering; and the aliased noise component accounts for the frequency folding effect of sampling, modulated by digital processing and image reconstruction filtering.

Park, Stephen K.↗
DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation: Preprint

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

Bayesian structural time series↗
DOE OSTI2023

Gaussian process hydrodynamics

Abstract We present a Gaussian process (GP) approach, called Gaussian process hydrodynamics (GPH) for approximating the solution to the Euler and Navier-Stokes (NS) equations. Similar to smoothed particle hydrodynamics (SPH), GPH is a Lagrangian particle-based approach that involves the tracking of a finite number of particles transported by a flow. However, these particles do not represent mollified particles of matter but carry discrete/partial information about the continuous flow. Closure is achieved by placing a divergence-free GP prior ξ on the velocity field and conditioning it on the vorticity at the particle locations. Known physics (e.g., the Richardson cascade and velocity increment power laws) is incorporated into the GP prior by using physics-informed additive kernels. This is equivalent to expressing ξ as a sum of independent GPs ξ l , which we call modes, acting at different scales (each mode ξ l self-activates to represent the formation of eddies at the corresponding scales). This approach enables a quantitative analysis of the Richardson cascade through the analysis of the activation of these modes, and enables us to analyze coarse-grain turbulence statistically rather than deterministically. Because GPH is formulated by using the vorticity equations, it does not require solving a pressure equation. By enforcing incompressibility and fluid-structure boundary conditions through the selection of a kernel, GPH requires significantly fewer particles than SPH. Because GPH has a natural probabilistic interpretation, the numerical results come with uncertainty estimates, enabling their incorporation into an uncertainty quantification (UQ) pipeline and adding/removing particles (quanta of information) in an adapted manner. The proposed approach is suitable for analysis because it inherits the complexity of state-of-the-art solvers for dense kernel matrices and results in a natural definition of turbulence as information loss. Numerical experiments support the importance of selecting physics-informed kernels and illustrate the major impact of such kernels on the accuracy and stability. Because the proposed approach uses a Bayesian interpretation, it naturally enables data assimilation and predictions and estimations by mixing simulation data and experimental data.

Mathematics↗
DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

bayesian structural time series↗
DOE OSTI2023

N-particle irreducible actions for stochastic fluids

We construct one- and two-particle irreducible (1PI and 2PI) effective actions for the stochastic fluid dynamics of a conserved density undergoing diffusive motion. We compute the 1PI action in one-loop order and the 2PI action in two-loop approximation. We derive a set of Schwinger-Dyson equations and regularize the resulting equations using Pauli-Villars fields. We numerically solve the Schwinger-Dyson equations for a non-critical fluid. We find that higher-loop effects summed by the Schwinger-Dyson renormalize the non-linear coupling. We also find indications of a diffuson-cascade, the appearance of n-loop correction with smaller and smaller exponential suppression.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Neutrino topology reconstruction at DUNE and applications to searches for dark matter annihilation in the Sun

We consider a new technique for neutrino energy and topology reconstruction at DUNE. In particular, we show that when the direction of the incoming neutrino is known, one can use the measured directions of the outgoing leptonic and hadronic particles to reconstruct poorly-measured quantities, such as the hadronic cascade energy. We show that this alternative technique yields an energy resolution which is comparable to current reconstruction methods which sum measured energies. As a proof of concept we apply this new reconstruction method to a search for dark matter annihilation in the Sun. We show that the use of directional information from both the leptonic and hadronic interaction products allows one to effectively reject backgrounds and isolate the signal, giving competitive sensitivities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Ratio method for estimating uncertainty in calculated gamma cascades

The assessment of uncertainty on deduced quantities obtained through both measurement and modeling must include contributions from both components. There are several methods to estimate the uncertainty due to modeling, such as the parametric uncertainty and that stemming from model bias. However, in the case where experimental data exists for partial cross sections, such as discrete gammas emitted in the de-excitation of the product nucleus following the reaction, the discrepancy between the measured and modeled gamma cascades provides more information and allows for uncertainty estimation that can account for all types of model and data uncertainty. This work presents a method for estimating that uncertainty, using ratios of gammas to get a measure of the accuracy of different parts of the modeled gamma cascade. The gamma with the lowest intensity uncertainty is shown to be the best for determining the channel cross section with realistic uncertainties, indicating that it should be used rather than the most intense gamma or a sum of gammas. In conclusion, this method provides both a simple procedure for calculating realistic uncertainties and identifies the best gamma for use in converting a set of measured partial gamma cross sections to the deduced total channel cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2004

Program Predicts Broadband Noise from a Turbofan Engine

Broadband Fan Noise Prediction System (BFaNS) is a computer program that, as its name indicates, predicts the broadband noise generated by the fan stage of a turbofan engine. This noise is the sum of (1) turbulent-inflow noise, which is caused by turbulence impinging on leading edges of the fan and the fan exit guide vane and (2) self noise, which is caused by turbulence convecting past the corresponding trailing edges. The user provides input data on the fan-blade, vane, and flow-path geometries and on the mean and turbulent components of the flow field. BFaNS then calculates the turbulent-inflow noise by use of D. B. Hanson's theory, which relates sound power to the inflow turbulence characteristics and the cascade geometry. Hanson s program, BBCASCADE, is incorporated into BFaNS, wherein it is applied to the rotor and stator in a stripwise manner. The spectra of upstream and downstream sound powers radiated by each strip are summed to obtain the total upstream and downstream sound-power spectra. The self-noise contributions are calculated by S. A. L. Glegg's theory, which is also applied in a stripwise manner. The current version of BFaNS is limited to fans with subsonic tip speeds.

Morin, Bruce L.↗