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Results for “correlation 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.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

The nature of isostasy on the moon - How big a Pratt-fall for Airy models

The correlation between topographic elevation and the major element chemistry of the lunar surface in non-mare regions suggest that a Pratt-type isostatic mechanism may be important in the lunar highlands. Pratt isostasy involves compensation of greater elevation by lower crustal density. Computation of the bulk density from surface chemistry and normative mineralogy, followed by comparisons between calculated density and surface height, is suggested as a means of testing the applicability of the Pratt isostatic model to the moon. A Pratt-type lunar crustal model requires much smaller variations in lunar crustal thickness than those necessitated by a constant-density (Airy) isostatic model. Mechanisms to produce a crust regionally heterogeneous in composition early in lunar differentiation are also required for Pratt isostasy.

Solomon, S. C.↗
DOE OSTI2025

Boosting efficiency and reducing graph reliance: Basis adaptation integration in Bayesian multi-fidelity networks

The computational cost of high-fidelity numerical models makes outer-loop analysis, which requires repeated interrogation of the model such as uncertainty quantification, computationally demanding. Multi-fidelity methods, which construct a surrogate model using data from an ensemble of models of varying cost and accuracy, can substantially reduce the cost of outer-loop analysis. However, these methods can be difficult to apply when the model ensemble does not admit a clear hierarchy a priori and the correlations between models are low. Consequently, in this paper, we present a multi-fidelity method that leverages dimension reduction to enhance the correlation between models, thereby reducing the amount of data needed to train a surrogate from an unordered ensemble of models. Our method utilizes basis adaptation to build low-dimensional polynomial chaos expansions of each model and employs Multi-fidelity Networks to encode the relationships among models. We show that the resulting method exhibit two notable advantages over its counterpart: (1) enhanced accuracy (both reduced bias and variance); and (2) reduced dependency on the graph structure encoding relationships among models. We demonstrate the approach on an analytical test problem and a challenging finite element model for a spent nuclear fuel. Our method produces a surrogate model that is significantly more accurate than either a single-fidelity surrogate or a multi-fidelity surrogate constructed without basis adaptation.

42 ENGINEERING↗
NASA NTRS1983

A theoretical model study of observed correlations between whistler mode waves and energetic electron precipitation events in the magnetosphere

A recently extended test particle computer model of the gyroresonance wave-particle interaction in the magnetosphere is applied to previously reported cases of observed correlations between whistler mode waves and ionospheric responses to particle precipitation. Three different ionospheric effects, namely, X-ray bursts, photoemissions, and D region perturbations, all correlated with VLF waves and believed to be caused by precipitated particles, are considered. The precipitation flux level, the pulse shape, and the associated time delays are computed for the parameters relevant to each case and are compared with values deduced from the data. The results demonstrate that the existing theoretical model can be useful for interpreting experimental results of this kind. Furthermore, the model results and observations, used together, provide a basis for additional diagnostics of the various parameters of the cold and energetic particle distributions in the magnetosphere. For example, when applied to the observed photoemission case (Helliwell et al., 1980) the model results imply that the trapped energetic particle distribution function at the time could be modeled as proportional to E exp -n/2 with n about 3.5 to 6, where E is the particle energy.

Chang, H. C.↗
NASA NTRS1973

A fission gas release correlation for uranium nitride fuel pins

A model was developed to predict fission gas releases from UN fuel pins clad with various materials. The model was correlated with total release data obtained by different experimentors, over a range of fuel temperatures primarily between 1250 and 1660 K, and fuel burnups up to 4.6 percent. In the model, fission gas is transported by diffusion mechanisms to the grain boundaries where the volume grows and eventually interconnects with the outside surface of the fuel. The within grain diffusion coefficients are found from fission gas release rate data obtained using a sweep gas facility.

Weinstein, M. B.↗
NASA NTRS2019

Diagnosing Bias in Modeled Soil Moisture/runoff Coefficient Correlation Using the SMAP Level 4 Soil Moisture Product

The physical parameterization of key processes in land surface models (LSMs) remains uncertain, and new techniques are required to evaluate LSM accuracy over coarse spatial scales. Given the role of soil moisture in the partitioning of surface water fluxes (between infiltration, runoff and evapotranspiration), surface soil moisture (SSM) estimates represent an important observational benchmark for such evaluations. Here, we apply SSM estimates from the NASA Soil Moisture Active Passive Level 4 product (SMAP_L4) to diagnose bias in the coupling between SSM and surface runoff for multiple Noah-Multiple Physics (Noah-MP) LSM parameterization cases. Results demonstrate that Noah-MP surface runoff parameterizations often underestimate the coupling strength between pre-storm SSM and the event-scale runoff coefficient (RC; defined as the ratio between event-scale streamflow and precipitation volumes). This bias squanders RC information contained in pre-storm SSM and reduces RC estimation skill. Such bias can be quantified against an observational benchmark calculated using streamflow observations and SMAP_L4 SSM and applied to explain a substantial fraction of the observed basin-to-basin (and case-to-case) variability in the skill of event-scale Noah-MP RC estimates. Based on this concept, a novel case selection strategy for ungauged basins is introduced and demonstrated to successfully identify poorly performing Noah-MP parameterization cases.

SSM↗
DOE OSTI2026

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗
NASA NTRS1974

Analysis of spread multi-jet VTOL aircraft in hover

An investigation of vertical takeoff and landing aircraft lift losses in hover was conducted to evaluate a method for a simplified test technique. Three flat plate models were tested to determine their usefulness in predicting hover characteristics by comparing results between plate and three-dimensional models. Data obtained for the plate models were correlated to three-dimensional results by the application of a geometrical equivalent height correction factor. The correlation of plate and tunnel models indicated that lift losses in ground effect were essentially independent of the efflux characteristics for the engine simulators.

Albang, L. F.↗
NASA NTRS2007

Numerical Modeling of Propellant Boil-Off in a Cryogenic Storage Tank

A numerical model to predict boil-off of stored propellant in large spherical cryogenic tanks has been developed. Accurate prediction of tank boil-off rates for different thermal insulation systems was the goal of this collaboration effort. The Generalized Fluid System Simulation Program, integrating flow analysis and conjugate heat transfer for solving complex fluid system problems, was used to create the model. Calculation of tank boil-off rate requires simultaneous simulation of heat transfer processes among liquid propellant, vapor ullage space, and tank structure. The reference tank for the boil-off model was the 850,000 gallon liquid hydrogen tank at Launch Complex 39B (LC- 39B) at Kennedy Space Center, which is under study for future infrastructure improvements to support the Constellation program. The methodology employed in the numerical model was validated using a sub-scale model and tank. Experimental test data from a 1/15th scale version of the LC-39B tank using both liquid hydrogen and liquid nitrogen were used to anchor the analytical predictions of the sub-scale model. Favorable correlations between sub-scale model and experimental test data have provided confidence in full-scale tank boil-off predictions. These methods are now being used in the preliminary design for other cases including future launch vehicles

Majumdar, A. K.↗
NASA NTRS2018

Accounting for Static and Dynamic Open Water in the Modeling of SMAP Brightness Temperatures over Peatlands

Hydrological change in peatlands due to anthropogenic disturbance and global warming can release enormous amounts of greenhouse gas emissions. Passive microwave satellite observations are an opportunity to globally monitor these changes. Abundant static and dynamic open water surfaces in peatlands strongly affect observed brightness temperatures (Tb). Here, we account for these contributions in radiative transfer modeling using NASA's Goddard Earth Observing System Model version 5 (GEOS-5) static open water mask and, for the dynamic open water fraction, the simulated inundated area using a version of the GEOS-5 Catchment land surface model that has been modified for peatland areas (PEAT-CLSM). Modeled Tb is compared against two years of SMAP L-band Tb. Preliminary results indicate: (i) a bias reduction when including the static open water fraction in a simple RTM mixing model, and ii) significantly improved correlation between modeled and observed Tb when using land surface output from PEAT-CLSM instead of the operational CLSM.

passive microwave↗
NASA NTRS2013

Bulk Insolation Models as Predictors for Locations for High Lunar Hydrogen Concentrations

In this study we consider the bulk effects of surface illumination on topography (insolation) and the possible thermodynamic effects on the Moon's hydrogen budget. Insolation is important as one of the dominant loss processes governing distributions of hydrogen volatiles on the Earth, Mars and most recently Mercury. We evaluated three types of high latitude > 65 deg., illumination models that were derived from the Lunar Observing Laser Altimetry (LOLA) digital elevation models (DEM)'s. These models reflect varying accounts of solar flux interactions with the Moon's near-surface. We correlate these models with orbital collimated epithermal neutron measurements made by the Lunar Exploration Neutron Detector (LEND). LEND's measurements derive the Moon's spatial distributions of hydrogen concentration. To perform this analysis we transformed the topographic model into an insolation model described by two variables as each pixels 1) slope and 2) slope angular orientation with respect to the pole. We then decomposed the illumination models and epithermal maps as a function of the insolation model and correlate the datasets.

Hydrogen Concentrations↗
NASA NTRS2016

Comparison of Spatial Correlation Parameters between Full and Model Scale Launch Vehicles

The current vibro-acoustic analysis tools require specific spatial correlation parameters as input to define the liftoff acoustic environment experienced by the launch vehicle. Until recently these parameters have not been very well defined. A comprehensive set of spatial correlation data were obtained during a scale model acoustic test conducted in 2014. From these spatial correlation data, several parameters were calculated: the decay coefficient, the diffuse to propagating ratio, and the angle of incidence. Spatial correlation data were also collected on the EFT-1 flight of the Delta IV vehicle which launched on December 5th, 2014. A comparison of the spatial correlation parameters from full scale and model scale data will be presented.

Kenny, Jeremy↗
NASA NTRS1975

On the modeling of the scalar correlations necessary to construct a second-order closure description of turbulent reacting flows

A tentative scheme is proposed for constructing second-order closure models of turbulent reacting flows, with particular reference to mixing processes in turbulent diffusion flows. The model is based on the concepts of typical structure and typical eddy, and treats various hypothetical turbulent flame situations, including the time dependence of species mass fractions passing a point in the flame, the most typical occurrence of species mass fractions, and the case of a rather bizarre typical eddy which shows the effects of nonmixedness.

Donaldson, C. DUP.↗
NASA NTRS2001

Error Estimation of An Ensemble Statistical Seasonal Precipitation Prediction Model

This NASA Technical Memorandum describes an optimal ensemble canonical correlation forecasting model for seasonal precipitation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. Since new CCA scheme is derived for continuous fields of predictor and predictand, an area-factor is automatically included. Thus our model is an improvement of the spectral CCA scheme of Barnett and Preisendorfer. The improvements include (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States (US) precipitation field. The predictor is the sea surface temperature (SST). The US Climate Prediction Center's reconstructed SST is used as the predictor's historical data. The US National Center for Environmental Prediction's optimally interpolated precipitation (1951-2000) is used as the predictand's historical data. Our forecast experiments show that the new ensemble canonical correlation scheme renders a reasonable forecasting skill. For example, when using September-October-November SST to predict the next season December-January-February precipitation, the spatial pattern correlation between the observed and predicted are positive in 46 years among the 50 years of experiments. The positive correlations are close to or greater than 0.4 in 29 years, which indicates excellent performance of the forecasting model. The forecasting skill can be further enhanced when several predictors are used.

Shen, Samuel S. P.↗
NASA NTRS1985

SSME structural dynamic model development, phase 2

A set of test correlated mathematical models of the SSME High Pressure Oxygen Turbopump (HPOTP) housing and rotor assembly was produced. New analysis methods within the EISI/EAL and SPAR systems were investigated and runstreams for future use were developed. The LOX pump models have undergone extensive modification since the first phase of this effort was completed. The rotor assembly from the original model was abandoned and a new, more detailed model constructed. A description of the new rotor math model is presented. Also, the pump housing model was continually modified as additional test data have become available. This model is documented along with measured test results. Many of the more advanced features of the EAL/SPAR finite element analysis system were exercised. These included the cyclic symmetry option, the macro-element procedures, and the fluid analysis capability. In addition, a new tool was developed that allows an automated analysis of a disjoint structure in terms of its component modes. A complete description of the implementation of the Craig-Bampton method is given along with two worked examples.

Foley, M. J.↗
NASA NTRS2014

Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

radioisotope power system↗
NASA NTRS1997

The Influence of Correlated Crustal Signals in Modelling the Main Geomagnetic Field

Algorithms used in geomagnetic main-field modelling have for the most part treated the noise in the field measurements as if it were white. A major component of the noise consists of the field due to magnetization in the crust and it has been realized for some time that such signals are highly correlated at satellite altitude. Hence approximation by white noise, while of undoubted utility, is of unknown validity. In this paper we study two plausible statistical models for the crustal magnetization, in which the magnetization is a realization of a stationary, isotropic, random process. At a typical satellite altitude the associated fields exhibit significant correlation over ranges as great as 15 deg. or more, which introduces off-diagonal elements into the covariance matrix, elements that have usually been neglected in modelling procedures. Dealing with a full covariance matrix for a large data set would present a formidable computational challenge, but fortunately most of the entries in the covariance matrix are so small that they can be replaced by zeros. The resultant matrix comprises only about 3 per cent non-zero entries and thus we can take advantage of efficient sparse matrix techniques to solve the numerical system. We construct several main-field models based on vertical-component data from a selected 5 deg. by 5 deg. data set derived from the Magsat mission. Models with and without off-diagonal terms are compared.

Rygaard-Hjalsted, C.↗
NASA NTRS1975

A study of noise source location on a model scale augmentor wing using correlation techniques

An experimental investigation, conducted on a model-scale augmentor wing to identify the sources of far-field noise, is examined. The measurement procedure followed in the investigation involved the cross-correlation of far field sound pressures with fluctuating pressures on the surface of the augmentor flap and shroud. In addition pressures on the surfaces of the augmentor were cross-correlated. The results are interpreted as showing that the surface pressure fluctuations are mainly aerodynamic in character and are convected in the downstream direction with a velocity which is dependent on the jet exhaust velocity. However the far field sound levels in the mid and high frequency ranges are dominated by jet noise. There is an indication that in the low frequency range trailing edge noise, associated with interaction of the jet flow and the flap trailing edge, plays a significant role in the radiated sound field.

Wilby, J. F.↗
DOE OSTI2025

Steam generator model design parameter sensitivity study for small modular reactor system

Here, this study focuses on design parameter sensitivity studies pertaining to several Once-Through Steam Generator (OTSG) model cases both with and without a riser using python and advanced risk assessment and optimization tool, i.e. Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), to support a Small Modular Reactor (SMR) system. The presented Steam Generator (SG) python-based model is a mathematical representation of a steam-generating unit for a Pressurized Water Reactor (PWR)-type SMR system, including fluid flow and heat transfer equations, models, and correlations. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system, such as the Heat Transfer Coefficient (HTC), Reynolds number, Nusselt number, and heat transfer performance. Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in the input parameters. By using RAVEN, detailed design parametric sensitivity studies. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10 % relative changes) for 600 samples. The analysis results give valuable insights into SG system performance, and provide justification for further research and development such as optimized sensor placement, design verification, validation, and optimization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗