Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Input Sensitivity”

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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Form-factor dependence of neutrino-nucleus cross sections using microscopic methods

To achieve its design goals, the next generation of neutrino-oscillation accelerator experiments requires percent-level predictions of neutrino-nucleus cross sections supplemented by robust estimates of the theoretical uncertainties involved. The latter arise from both approximations in solving the nuclear many-body problem and in the determination of the single- and few-nucleon quantities taken as input by many-body methods. To gauge the sensitivity of realistic nuclear many body methods to these few-nucleon quantities, we compute flux-averaged double-differential cross sections using the Green’s function Monte Carlo and spectral function methods as well as different parameterizations of the nucleon axial form factors based on either deuterium bubble-chamber data or lattice quantum chromodynamics calculations. The cross-section results are compared with available experimental data from the MiniBooNE and T2K collaborations. We also discuss the uncertainties associated with N → Δ transition form factors that enter the two-body current operator. We quantify the relations between neutrino-nucleus cross section and nucleon form factor uncertainties. These relations enable us to determine the form factor precision targets required to achieve a given cross-section precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Efficient mapping between void shapes and stress fields using Deep Convolutional Neural Networks with sparse data

Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.

surrogate modeling; convolutional neural networks;↗
DOE OSTI2017

Regression with Small Data Sets: A Case Study using Code Surrogates in Additive Manufacturing

There has been an increasing interest in recent years in the mining of massive data sets whose sizes are measured in terabytes. While it is easy to collect such large data sets in some application domains, there are others where collecting even a single data point can be very expensive, so the resulting data sets have only tens or hundreds of samples. For example, when complex computer simulations are used to understand a scientific phenomenon, we want to run the simulation for many different values of the input parameters and analyze the resulting output. The data set relating the simulation inputs and outputs is typically quite small, especially when each run of the simulation is expensive. However, regression techniques can still be used on such data sets to build an inexpensive \surrogate" that could provide an approximate output for a given set of inputs. A good surrogate can be very useful in sensitivity analysis, uncertainty analysis, and in designing experiments. In this paper, we compare different regression techniques to determine how well they predict melt-pool characteristics in the problem domain of additive manufacturing. Our analysis indicates that some of the commonly used regression methods do perform quite well even on small data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Neutrino Physics with SNO+

SNO+ is a neutrino experiment with a broad physics program, the primary goal being a search for the phenomenon of neutrinoless double beta decay, a process possible only if the neutrino is its own antiparticle, or a "Majorana" fermion. Such a discovery would substantially alter our understanding of particle physics, including introducing the need for a non-Higgs mechanism for generating particle mass, and place constraints on the as-yet-unknown neutrino mass scale. SNO+ will also detect neutrinos from the solar core, furthering our understanding of the fusion cycles that power the sun, and antineutrinos produced inside the Earth (geoneutrinos), which will enable a better understanding of heat production beneath the Earth's surface. We will continually monitor for neutrinos from nearby supernovae, which, if detected, could allow us to better understand the role of neutrinos in stellar core collapse, and potentially to determine the unknown neutrino mass hierarchy. With such a broad physics program, SNO+ has great potential both to advance our understanding of neutrinos, and to use neutrinos to understand the formation and behavior of our Universe. This report describes a targeted plan of optical calibrations of the SNO+ detector, with the goal of measuring and monitoring the PMT optical response independently of liquid scintillator properties. To this end we describe the design, construction, and operation of a source of Cherenkov light for deployment in SNO+. Successful deployment in the initial light water phase is described, demonstrating the capabilities of this calibration mechanism. The results of this work form a critical input to the SNO+ detector model, directly impacting the sensitivity of all SNO+ physics results. Also described is significant work on detector commissioning, DAQ and operations, the implementation of calibration efforts in multiple physics analyses, involvement in all levels of analysis activities, and leadership in SNO+ science.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Modeling the Cost of CO2 Saline Storage on a Regional and National Level

This poster presents the results of using the FECM/NETL CO2 Saline Storage Cost Model (CO2_S_COM) to evaluate the cost of saline storage in potential storage formations in the lower 48 U.S. states. Costs were calculated for 314 saline storage formations in the CO2_S_COM geologic property database. These results were used to generate national and regional cost-supply curves. In addition, a sensitivity analysis was performed that quantified how modifying several input variables in CO2_S_COM affected the costs. Poster presented (virtual) at the 2024 AGU Conference, December 9-13, 2024, Washington, D.C.

Morgan, David [NETL]↗
DOE OSTI2025

Dose Exceedance Distance Sensitivity Based on Parametric Uncertainty

Sandia National Laboratories (SNL) collaborated with the US Nuclear Regulatory Commission's (NRC) Office of Nuclear Security and Incident Response (NSIR) and Office of Nuclear Regulatory Research (RES) to investigate the reasonable variability in the estimation of dose exceedance distances. SNL performed calculations using the MACCS code to elucidate the sensitivity of dose exceedance distances to variations in user input parameters.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Evaluation of obstacle modelling approaches for resource assessment and small wind turbine siting: case study in the northern Netherlands

Abstract. Growth in adoption of distributed wind turbines for energy generation is significantly impacted by challenges associated with siting and accurate estimation of the wind resource. Small turbines, at hub heights of 40 m or less, are greatly impacted by terrestrial obstacles such as built structures and vegetation that can cause complex wake effects. While some progress in high-fidelity complex fluid dynamics (CFD) models has increased the potential accuracy for modelling the impacts of obstacles on turbulent wind flow, these models are too computationally expensive for practical siting and resource assessment applications. To understand the efficacy of available models in situ, this study evaluates classic and commonly used methods alongside new state-of-the-art lower-order models derived from CFD simulations and machine learning approaches. This evaluation is conducted using a subset of an extensive original dataset of measurements from more than 300 operational wind turbines in the northern Netherlands. The results show that data-driven methods (e.g. machine learning and statistical modelling) are most effective at predicting production at real sites with an average error in annual energy production of 2.5 %. When sufficient data may not be available de novo to support these data-driven approaches, models derived from high-fidelity simulations show promise and reliably outperform classic methods. On average these models have 6.3 %–11.5 % error compared with 26 % for classic methods and 27 % baseline error for reanalysis data without obstacle correction. While more performant on average, these methods are also sensitive to the quality of obstacle descriptions and reanalysis inputs.

17 WIND ENERGY↗
NASA NTRS1974

NASTRAN variance analysis and plotting of HBDY elements

The NASTRAN Thermal Analyzer has been intended to do variance analysis and plot the thermal boundary elements. The objective of the variance analysis addition is to assess the sensitivity of temperature variances resulting from uncertainties inherent in input parameters for heat conduction analysis. The plotting capability provides the ability to check the geometry (location, size and orientation) of the boundary elements of a model in relation to the conduction elements. Variance analysis is the study of uncertainties of the computed results as a function of uncertainties of the input data. To study this problem using NASTRAN, a solution is made for both the expected values of all inputs, plus another solution for each uncertain variable. A variance analysis module subtracts the results to form derivatives, and then can determine the expected deviations of output quantities.

Harder, R. L.↗
NASA NTRS1974

A spark gap switching system for gasdynamic facilities

A spark gap switching system has been developed to coordinate the discharge of a 300 kJ capacitor bank with the high speed flow of helium in a shock tube driver. The trigger system includes a flow transducer, a pulse forming circuit, a high voltage spark generator, and four heavy duty spark gaps that can carry total peak currents greater than 1.5 million A. A glow gauge flow transducer sensitive to small gas density changes was used whose input power and signal output can withstand high voltage fluctuations. This switching system is of use with gasdynamic discharge devices requiring a minimum number of switches.

Leibowitz, L. P.↗
NASA NTRS1981

Density of the mantle of Mars

The range of zero pressure densities of the Martian mantle which are compatible with the mean density and moment of inertia factor of Mars has been explored by: (1) considering the full range of plausible core compositions and densities, and (2) investigating the sensitivity of computed mantle densities to uncertainties in the input parameters. Ni, Fe, Fe3O4, and FeS cores were considered; corresponding zero pressure mantle densities range from 3.47 to 3.41 g/cu cm. Uncertainty in the mantle density of about 0.04 g/cu cm for the Fe core model and about 0.05 g/cu cm for the FeS core model results from uncertainties in the input parameters. The zero pressure density of the Martian mantle is estimated to be 3.44 plus or minus 0.06 g/cu cm.

Goettel, K. A.↗
NASA NTRS1983

Silicon solar cell process development, fabrication and analysis

Measurements of minority carrier diffusion lengths were made on the small mesa diodes from HEM Si and SILSO Si. The results were consistent with previous Voc and Isc measurements. Only the medium grain SILSO had a distinct advantage for the non grain boundary diodes. Substantial variations were observed for the HEM ingot 4141C. Also a quantitatively scaled light spot scan was being developed for localized diffusion length measurements in polycrystalline silicon solar cells. A change to a more monochromatic input for the light spot scan results in greater sensitivity and in principle, quantitative measurement of local material qualities is now possible.

Leung, D. C.↗
NASA NTRS1985

Model predictions of ozone changes

The predictions of several one-dimensional models were examined for a number of prescribed scenarios in steady-state or time-dependent approximations. A small number of two-dimensional steady-state calculations for a limited number of scenarios were compared with the results of one-dimensional models. The sensitivity of the calculated predictions to the values of input parameters were examined in order to assess recognized uncertainties in these predictions.

Johnston, H. S.↗
NASA NTRS1989

Three-dimensional linear instability modeling of the cloud level Venus atmosphere

Based on the success of several two-dimensional (latitude, longitude) linear barotropic instability models at matching some of the observed characteristics of the cloud level, polar region of the Venus atmosphere, a more realistic, linear, three-dimensional (height, latitude and longitude) model has been developed to further test the hypothesis that the observed features can be described by linear instability theory. The approach taken is to vary the model input parameters to see whether it is possible to produce modes that resemble the observations of wave activity and to compare those input parameters with other observations of the mean state. Sensitivity studies show that in addition to a well-documented dependence on the mean zonal wind, the growth and propagation of unstable modes depends on the latitude variation of the mean temperature (and hence static stability). These studies have led to the specification of a model basic state wind and temperature field that produces modes which are matched to observations of spatial structure, preferred wavenumber and phase speed of the polar disturbances. Wavenumber 2 is found to have the shortest growth time and unlike the two-dimensional results, wavenumbers 1-3 share a nearly common period of about 3 days. The derived basic state has a temperature field that is quite similar to Pioneer Venus observations; however, in some regions the model basic state wind field departs from cyclostrophic values based on temperature observations.

Elson, Lee S.↗
NASA NTRS2001

Implementing a Nitrogen-Based Model for Autotrophic Respiration Using Satellite and Field Observations

The rate of carbon accumulation by terrestrial plant communities in a process-level, mechanistic modeling is the difference of the rate of gross photosynthesis by a canopy (A(sub g)) and autotrophic respiration (R) of the stand. Observations for different biomes often show that R to be a large and variable fraction of A(sub g), ca. 35% to 75%, although other studies suggest the ratio of R and A(sub g) to be less variable. Here, R has been calculated according to the two compartment model as being the sum of maintenance and growth components. The maintenance respiration of foliage and living fine roots for different biomes has been determined objectively from observed nitrogen content of these organs. The sapwood maintenance respiration is based on pipe theory, and checked against an independently derived equation considering sapwood biomass and its maintenance coefficient. The growth respiration has been calculated from the difference of A(sub g) and maintenance respiration. The A(sub g) is obtained as the product of biome-specific radiation use efficiency for gross photosynthesis under unstressed conditions and intercepted photosynthetically active radiation, and adjusted for stress. Calculations have been done using satellite and ground observations for 36 consecutive months (1987-1989) over large contiguous areas (ca. 10(exp 5) sq km) of boreal forests, crop land, temperate deciduous forest, temperate grassland, tropical deciduous forest, tropical evergreen forest, tropical savanna, and tundra. The ratio of annual respiration and gross photosynthesis, (R/A(sub g)), is found to be 0.5-0.6 for temperate and cold adopted biome areas, but somewhat higher for tropical biome areas (0.6-0.7). Interannual variation of the fluxes is found to be generally less than 15%. Calculated fluxes are compared with observations and several previous estimates. Results of sensitivity analysis are presented for uncertainties in parameterization and input data. It is found that uncertainty in determining maintenance respiration for tropical biomes is such that R/A(sub g) for these biomes could be similar to that for temperate biomes.

Choudhury, Bhaskar J.↗
NASA NTRS2005

Probabilistic Analysis Techniques Applied to Complex Spacecraft Power System Modeling

Electric power system performance predictions are critical to spacecraft, such as the International Space Station (ISS), to ensure that sufficient power is available to support all the spacecraft s power needs. In the case of the ISS power system, analyses to date have been deterministic, meaning that each analysis produces a single-valued result for power capability because of the complexity and large size of the model. As a result, the deterministic ISS analyses did not account for the sensitivity of the power capability to uncertainties in model input variables. Over the last 10 years, the NASA Glenn Research Center has developed advanced, computationally fast, probabilistic analysis techniques and successfully applied them to large (thousands of nodes) complex structural analysis models. These same techniques were recently applied to large, complex ISS power system models. This new application enables probabilistic power analyses that account for input uncertainties and produce results that include variations caused by these uncertainties. Specifically, N&R Engineering, under contract to NASA, integrated these advanced probabilistic techniques with Glenn s internationally recognized ISS power system model, System Power Analysis for Capability Evaluation (SPACE).

Hojnicki, Jeffrey S.↗
NASA NTRS2006

The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global Precipitation Estimates at Fine Scales

The TRMM Multi-satellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining multiple precipitation estimates from satellites, as well as gauge analyses where feasible, at fine scales (0.25 degrees x 0.25 degrees and 3-hourly). It is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The data set covers the latitude band 50 degrees N-S for the period 1998 to the delayed present. Early validation results are as follows: The TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate dependent low bias due to lack of sensitivity to low precipitation rates in one of the input products (based on AMSU-B). At finer scales the TMPA is successful at approximately reproducing the surface-observation-based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other fine-scale estimators. Examples are provided of a flood event and diurnal cycle determination.

Huffman, George J.↗