Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Average model”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

Zonally averaged thermal balance and stability models for nitrogen polar caps on Triton

Voyager four-color imaging data of Triton are analyzed to calculate the bolometric hemispheric albedo as a function of latitude and longitude. Zonal averages of these data have been incorporated into a thermal balance model involving insolation, reradiation, and latent heat of sublimation of N2 ice for the surface. The current average bolometric albedo of Triton's polar caps is 0.8, implying an effective temperature of 34.2 K and a surface pressure of N2 of 1.6 microbar for unit emissivity. This pressure is an order of magnitude lower than the surface pressure of 18 microbar inferred from Voyager data (Broadfoot et al., 1989; Conrath et al., 1989), a discrepancy that can be reconciled if the emissivity of the N2 on Triton's surface is 0.66. The model predicts that Triton's surface north of 15 deg N latitude is experiencing deposition of N2 frosts, as are the bright portions of the south polar cap near the equator. This result explains why the south cap covers nearly the entire southern hemisphere of Triton.

Stansberry, John A.↗

Producing Evaluation-quality 239 Pu Average Prompt Fission Neutron Multiplicities using a Correlated Fission Model

An evaluation of the average prompt fission neutron multiplicity, $\bar{ν}_p$, of 239 Pu(n,f) is shown. This evaluation includes (a) the correlated fission model CGMF, and (b) a detailed analysis of past and recently published experimental data. Using CGMF-calculated $\bar{ν}_p$ as prior enables to link, through the use of evaluated model input parameters, $\bar{ν}_p$ to other fission observables such as the prompt fission neutron spectrum (PFNS), preneutron emission fission yields as a function of mass, and the average total kinetic energy of the fragments. These evaluated parameters produce realistic predictions of many fission observables, while the evaluated $\bar{ν}_p$ agrees well (χ 2 ≈ 1) with data. Moreover, with the new evaluated $\bar{ν}_p$, the effective neutron multiplication factor of fast Pu ICSBEP critical assemblies are predicted with a mean bias of 58 pcm compared to 18 pcm with ENDF/B-VIII.0, when paired with a new 239 Pu PFNS and fission cross section. Due to these encouraging validation results, the evaluated $\bar{ν}_p$ is currently part of a release candidate for the 239 Pu ENDF/B-VIII.1 file. Hence, a correlated fission model was used for the first time for evaluating $\bar{ν}_p$ that is of evaluation quality. This is an important step towards consistent evaluations of prompt fission observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Digital spectral estimation and modeling of Space Shuttle flight data

Application of the digital signal processing technique of autoregressive-moving-average (ARMA) modeling to the estimation of power spectra and shock spectra from Space Shuttle lift-off flight accelerograms is described in this paper. The background for application to ARMA of lift-off accelerograms which are non-stationary in nature is exemplified through a step-by-step discussion of actual numerical results. Included is a discussion of pertinent mathematical background for the ARMA approximations. Potential areas for application of ARMA modeling in payload integration activities are suggested.

Spanos, P. D.↗

Lunar highland rock types: Their implications for impact-induced fractionation

Lunar rocks may be classified into three major groups: (1) coarse-grained igneous rocks, (2) fine-grained igneous rocks, and (3) breccias. Group 1 is interpreted as primitive lunar crustal rocks that display various degrees of crushing and/or annealing. Group 2 is interpreted as volcanic rocks. Group 3 is interpreted as resulting from impacts on the lunar surface and is subdivided on the basis of matrix textures into fragmental breccias, crystalline breccias that have been annealed, and crystalline breccias with igneous matrices. A synthesis of the data concerning lunar highlands polymict breccias compels the prediction that the breccias should have homogeneous matrices from rock to rock within regions of the highlands of limited size where impact mixing has been efficient and extensive. But the returned breccias, even from one landing site, display a wide range in composition. This incompatibility between prediction and observation is a paradox that may be resolved by a process that acts after impact mixing to cause a differentiation of the breccia compositions. Partial melting of the local average crustal composition (as modeled by the average soil composition for each site) and separation of melt and residue in ejecta and/or fall-back blankets are compatible with the reviewed data and may resolve the paradox.

Phinney, W. C.↗

Ground-based observations of equatorial thermosphere dynamics with a Fabry-Perot interferometer

Fabry-Perot determinations of thermospheric temperatures from 630.0 nm nightglow line width measurements were carried out for the period April to August, 1983. The nightly variation of the thermospheric temperature measured on 53 nights is compared with MSIS model predictions and found to agree occasionally with the model but, on the average, to exceed model predictions by approximately 180 K. The largest differences, 400 to 500 K occur during strongly increasing geomagnetic activity. Significant differences occur both during high geomagnetic/low solar activity and during low geomagnetic/high solar activity.

Meriwether, J. W., Jr.↗

Optimal firing rate estimation

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

NASA Discipline Neuroscience↗

Regionally applicable angular reflectance models

Determination of the angular variation of the reflected radiance field in order to infer the reflected component of the Earth radiation budget from medium or narrow field of view radiometer measurements is discussed. An average angular model applicable at 250 to 1000 km is presented and evaluated. The nature of the convergence of the radiance patterns to the regional means is also discussed. Radiances measured during summer Monex 1979, from Hudson Bay to Saudi Arabia, were averaged and then normalized by multiplying by pi and dividing by the scene-averaged reflected flux density. This casts the model into the inverse of the bidirectional reflectance normalization coefficient, which has the value of unity for an isotropic surface. The reflected component of the Earth's radiation budget is inferred to an accuracy of about 2.5%.

Davis, J. M.↗

In-depth analysis of solar models with high-metallicity abundances and updated opacity tables

Context. As a result of the high-quality constraints available for the Sun, we are able to carry out detailed combined analyses using neutrino, spectroscopic, and helioseismic observations. These studies lay the ground for future improvements of the key physical components of solar and stellar models because ingredients such as the equation of state, the radiative opacities, or the prescriptions for macroscopic transport processes of chemicals are then used to study other stars in the Universe. Aims. We study the existing degeneracies in solar models using the recent high-metallicity spectroscopic abundances by comparing them to helioseismic and neutrino data and discuss the effect on their properties of changes in the micro and macro physical ingredients. Methods. We carried out a detailed study of solar models computed with a high-metallicity composition from the literature based on averaged 3D models that were claimed to resolve the solar modelling problem. We compared these models to helioseismic and neutrino constraints. Results. The properties of the solar models are significantly affected by the use of the recent OPLIB opacity tables and the inclusion of macroscopic transport. The properties of the standard solar models computed using the OPAL opacities are similar to those for which the OP opacities were used. We show that a modification of the temperature gradient just below the base of the convective zone is required to remove the discrepancies in solar models, particularly in the presence of macroscopic mixing. This can be simulated by a localised increase in the opacity of a few percent. Conclusions. We conclude that the existing degeneracies and issues in solar modelling are not removed by using an increase in the solar metallicity, in contradiction to what has been suggested in the recent literature. Therefore, standard solar models cannot be used as an argument for a high-metallicity composition. While further work is required to improve solar models, we note that direct helioseismic inversions indicate a low metallicity in the convective envelope, in agreement with spectroscopic analyses based on full 3D models.

74 ATOMIC AND MOLECULAR PHYSICS↗

A semi-analytic theory for the motion of a close-earth artificial satellite with drag

A semi-analytic method is used to estimate the decay history/lifetime and to generate orbital ephemeris for close-earth satellites perturbed by the atmospheric drag and earth oblateness due to the spherical harmonics J2, J3, and J4. The theory maintains efficiency through the application of the theory of a method of averaging and employs sufficient numerical emphasis to include a rather sophisticated atmospheric density model. The averaged drag effects with respect to mean anomaly are evaluated by a Gauss-Legendre quadrature while the averaged variational equations of motion are integrated numerically with automatic step size and error control.

Liu, J. J. F.↗

Greenhouse Gas Emissions and Decarbonization Potential of Global Fired Clay Brick Production

Fired clay bricks (FCBs) are a dominant building material globally due to their low cost and simplicity of production, especially in low- and middle-income countries. With a projected rising housing demand, commensurate growth in brick demand is anticipated, the production of which could result in significant greenhouse gas (GHG) emissions. Robust models are needed to estimate brick demand and emissions to systematically address decarbonization pathways. Few sources report production values; hence, we present two novel proxy models: (i) a consumption prediction model, relying on country-specific clay extraction data, dynamic building stock modeling, and average material intensity use allowing for projections to 2050; and (ii) a GHG emissions model, using literature-based data and production technology-specific inputs. Based on these models, the current global FCB consumption is estimated as 2.18 Gt annually, resulting in approximately 500 million tCO2e (1% of current global GHG emissions). If unaddressed, this fraction could increase to 3.5-5% in 2050 considering a moderate SSP 2-4.5 climate change mitigation scenario. Consequently, we explored three potential decarbonization pathways: (i) improving energy efficiency; (ii) shifting production to best practices; and (iii) replacing half of FCB demand with hollow concrete blocks, resulting in 27%, 49%, and 51% reduction in GHG emissions, respectively.

Olsson, Josefine A↗

Issues related to waveform computations for radar altimeter applications

An algorithm has been developed to model the average return power waveforms available from general radar altimeter systems, such as the Multimode Airborne Radar Altimeter (MARA) system operated at NASA Goddard Space Flight Center - Wallops Flight Facility. The algorithm is based on a convolutional model comprised of three functions: the average flat surface impulse response (FSIR), the radar system point target response (PTR), and the height pdf of the specular points on the sea surface. The FSIR is modified to account for the asymmetric antenna beam used by the MARA system, and then certain properties of this modified SIR are exploited to obtain closed-form expressions that can be rapidly evaluated. An FFT convolution routine is used to further speed up the computations. The result is an algorithm that can be used to study the effects of pointing errors in surface measurements.

Newkirk, Michael H.↗

Large Eddy Simulation of Low-Reynolds-Number Turbulent Flow of Low-Prandtl-Number Fluid in a Tight Lattice Bundle for Assessment of Reynolds-Averaged Navier-Stokes Turbulence Model

The MARVEL (Microreactor Applications Research Validation and Evaluation) microreactor utilizes natural circulation as core cooling mechanism and liquid metal as a primary coolant. Moreover, the reactor core has a pitch-to-diameter ratio of 1.056, which is considered a tight lattice configuration. Numerous studies have widely reported that Reynolds-Averaged Navier-Stokes (RANS) turbulence models inaccurately predict heat transfer in liquid metals and fail to capture flow pulsations that can occur within tight lattices, leading to further inaccuracies in simulation results. Therefore, evaluating the accuracy of RANS turbulence models in the thermal-hydraulic analysis of the MARVEL microreactor core is crucial for assessing reactor safety. In this study, a Large Eddy Simulation (LES) of the MARVEL microreactor core subchannel was conducted and compared with a RANS simulation to evaluate the accuracies and conservatism of the RANS model. The flow pulsation in a tight lattice predicted by LES enhanced the heat transfer, whereas the RANS model underpredicted it. Consequently, the RANS model predicted the peak cladding temperature higher than the LES model, but the discrepancy between the two approaches was not significant due to the good thermal characteristics of the liquid metal. It can be concluded that the steady-state RANS model is effective for the thermal analysis of liquid-metal-cooled MARVEL microreactor core and can provide conservative predictions from a safety analysis perspective.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Three dimensional model calculations of the global dispersion of high speed aircraft exhaust and implications for stratospheric ozone loss

Two-dimensional (zonally averaged) photochemical models are commonly used for calculations of ozone changes due to various perturbations. These include calculating the ozone change expected as a result of change in the lower stratospheric composition due to the exhaust of a fleet of supersonic aircraft flying in the lower stratosphere. However, zonal asymmetries are anticipated to be important to this sort of calculation. The aircraft are expected to be restricted from flying over land at supersonic speed due to sonic booms, thus the pollutant source will not be zonally symmetric. There is loss of pollutant through stratosphere/troposphere exchange, but these processes are spatially and temporally inhomogeneous. Asymmetry in the pollutant distribution contributes to the uncertainty in the ozone changes calculated with two dimensional models. Pollutant distributions for integrations of at least 1 year of continuous pollutant emissions along flight corridors are calculated using a three dimensional chemistry and transport model. These distributions indicate the importance of asymmetry in the pollutant distributions to evaluation of the impact of stratospheric aircraft on ozone. The implications of such pollutant asymmetries to assessment calculations are discussed, considering both homogeneous and heterogeneous reactions.

Douglass, Anne R.↗

AERMOD Screening Dispersion Factors for INL Facilities

This engineering calculations and analysis report (ECAR) documents the calculation of screening level air dispersion factors (DFs) for use in identifying Idaho National Laboratory (INL) air pollutant sources that would not be of concern relative to state of Idaho Department of Environmental Quality (DEQ) significant impact levels for toxic air pollutants (IDAPA 2020). A DF (in units of s/m 3 ) is the maximum time-averaged model-predicted air concentration (g/m 3 ) at an ambient-air receptor location divided by a unit source release or emission rate (1 g/s). DFs were calculated for a generic pollutant released from facilities at the INL Site and the Idaho Falls Research Education Campus (REC) using the Environmental Protection Agency (EPA)-recommended AERMOD air-dispersion model (EPA 2019a) and site-specific meteorological data. The use of AERMOD for air quality analyses is specified by EPA in Appendix W of 40 CFR Part 51, Guideline on Air Quality Models, and by DEQ in their air modeling guidance (DEQ 2013). DFs were calculated for 1-hour, 3 hour, 8-hour, 24-hour, monthly, and annual averaging times.

99 GENERAL AND MISCELLANEOUS↗

Computational Modeling of Molten Salt Infiltration and Oxidation in Nuclear Graphite

Graphite is utilized as a moderator and reflector in advanced nuclear reactor designs due to its high thermal conductivity, neutron moderation properties, and resistance to radiation damage. However, its longterm performance and reliability are challenged by degradation mechanisms such as molten salt infiltration in molten salt reactors (MSRs) and oxidation in gas-cooled reactors (GCRs). These mechanisms can compromise the structural integrity and operational lifetime of graphite components, necessitating a more detailed assessment of their physical behavior. This report focuses on the development of computational models for molten salt infiltration and oxidation of graphite to aid the design and performance analysis of graphite components. For molten salt infiltration, a computational framework is developed that couples incompressible Navier-Stokes and phase-field model to simulate the penetration of molten salt into graphite?s interconnected pore structure. Initial model verification is performed using two-phase flows in two dimensions, demonstrating the models ability to capture fundamental physical behavior and agree with analytical solution. This framework is then applied to a realistic IG110 nuclear graphite , where a computed tomography extracted pore geometry is used to analyse the infiltration behavior of FLiNaK molten salt. This model provides insights into how the microstructure and other relevant parameters influence the transport pathways of molten salt into graphite, potentially offering a means to rapidly evaluate a graphite grade?s resistance to infiltration. For oxidation, the report details pore-scale mass and heat transport models, describing the diffusion of gases, reaction kinetics, and thermal effects. Additionally, this report highlights inconsistencies in the existing volume-averaged macroscopic model, particularly in upscaling of reaction kinetics and flux terms, and surface to volume transformations. These inconsistencies suggest that current formulations may not accurately capture the experimentally observed graphite oxidation process, highlighting the need for improved model development. This work advances the development of physics-based computational models for graphite degradation, contributing to improved predictive models for next-generation nuclear reactor designs. Future efforts will focus on refining the infiltration model to address non-physical behaviors and enhance its robustness. Additionally, for oxidation, further studies will employ the principles of volume averaging to rigorously derive the upscaled equations, potentially in collaboration with subject matter experts.

Computational Modeling of Molten Salt Infiltration↗

A model for closing the inviscid form of the average-passage equation system

A mathematical model is proposed for closing or mathematically completing the system of equations which describes the time average flow field through the blade passages of multistage turbomachinery. These equations referred to as the average passage equation system govern a conceptual model which has proven useful in turbomachinery aerodynamic design and analysis. The closure model is developed so as to insure a consistency between these equations and the axisymmetric through flow equations. The closure model was incorporated into a computer code for use in simulating the flow field about a high speed counter rotating propeller and a high speed fan stage. Results from these simulations are presented.

Adamczyk, J. J.↗

A model for closing the inviscid form of the average-passage equation system

A mathematical model is proposed for closing or mathematically completing the system of equations which describes the time average flow field through the blade passages of multistage turbomachinery. These equations referred to as the average passage equation system govern a conceptual model which has proven useful in turbomachinery aerodynamic design and analysis. The closure model is developed so as to insure a consistency between these equations and the axisymmetric through flow equations. The closure model was incorporated into a computer code for use in simulating the flow field about a high speed counter rotating propeller and a high speed fan stage. Results from these simulations are presented.

Adamczyk, J. J.↗

Gaussian Process Regression for Aggregate Baseline Load Forecasting

Demand response (DR) is one of the most effective ways to maintain the reliability and improve the flexibility of power systems. Accurate forecasts of baseline loads are essential for DR programs. In the era of big data, machine learning-based approaches present a unique opportunity for baseline load forecasting. Thus, this paper presents a machine learning-based approach using a relatively less explored algorithm, Gaussian process regression (GPR), to forecast aggregate baseline loads. As such, a dataset was generated using a set of EnergyPlus simulations. Using the generated dataset, a GPR-based forecasting model was developed. In addition, support vector regression (SVR)-, artificial neural network (ANN)-, and averaging-based models were developed as baseline models for comparison. These models were compared in terms of accuracy, simplicity, and integrity. The prediction performance of the models showed that the GPR-based model is more accurate and reliable than the others. Such high performance shows the potential of the GPR in baseline load forecasting. GPR, therefore, can be used for DR applications.

Amasyali, Kadir↗