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Results for “comparative modeling”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

The use of antioptimization to compare alternative structural models

Structural models are usually tested by comparing their response with that of a reference structure (an actual structure or a more refined model) to a limited number of arbitrary loads. This test is not always reliable because the loads are arbitrary. An antioptimization-based method is proposed to test structural models. This method compares a structural model with a reference model or an actual structure under the worst loading case that maximizes the error in the model. Specifically, the method identifies the loading case that maximizes the difference between the responses of two models of the same structure using optimization. This method can be used to design experiments in order to validate a structural model. It can also be applied to identify damage in a structure by determining the load that maximizes the difference in the behavior of the damaged and the intact structure. The proposed method is illustrated by applying it to a plate and an automotive structure.

Gangadharan, S. N.↗
NASA NTRS2011

Evaluation of Arctic Sea Ice Thickness Simulated by AOMIP Models

We compare results from six AOMIP model simulations with estimates of sea ice thickness obtained from ICESat, moored and submarine-based upward looking sensors, airborne electromagnetic measurements and drill holes. Our goal is to find patterns of model performance to guide model improvement. The satellite data is pan-arctic from 2004-2008, ice-draft data is from moored instruments in Fram Strait, the Greenland Sea and the Beaufort Sea from 1992-2008 and from submarines from 1975-2000. The drill hole data are from the Laptev and East Siberian marginal seas from 1982-1986 and from coastal stations from 1998-2009. While there are important caveats when comparing modeled results with measurements from different platforms and time periods such as these, the models agree well with moored ULS data. In general, the AOMIP models underestimate the thickness of measured ice thicker than about 2 m and overestimate thickness of ice thinner than 2 m. The simulated results are poor over the fast ice and marginal seas of the Siberian shelves. Averaging over all observational data sets, the better correlations and smaller differences from observed thickness are from the ECCO2 and UW models.

Johnson, Mark↗
DOE OSTI2022

A time‐varying formulation of the curled wake model within the FAST.Farm framework

Abstract In this article, we present a time‐varying formulation of the curled wake model that we implemented in FAST.Farm. The curled wake model, originally developed for steady‐state conditions, is used to produce realistic wake profiles behind a wind turbine in yawed (or skewed) conditions. We begin by introducing the key elements of the FAST.Farm framework. Then, after briefly summarizing the original wake dynamics formulation of FAST.Farm based on a polar wake profile, we present the new time‐varying formulation of the curled wake model, compare the two, and highlight the differences with the original curled wake model. After discussing some implementation details, we present different applications with increasing levels of complexity: single turbine with uniform and turbulent inflow, fixed and transient yaw, and multiple turbines. We verify our results using the original FAST.Farm implementation and large‐eddy simulations. The results with the new curled wake model are improved compared to the original implementation, as they include cross‐flow velocities and wake asymmetry. Yet, large‐eddy simulation results show a more pronounced lateral convection of the wake and a stronger concentration of vorticity at the top vortex. The new curled wake implementation in FAST.Farm should enable the calculation of not only generator power but also wind turbine structural loads for applications involving intentional or unintentional skewed flow and wind‐farm control involving wake steering.

17 WIND ENERGY↗
DOE OSTI2020

A Comprehensive Monte Carlo Framework for Jet-Quenching

This article presents the motivation for developing a comprehensive modeling framework in which different models and parameter inputs can be compared and evaluated for a large range of jet-quenching observables measured in relativistic heavy-ion collisions at RHIC and the LHC. Here, the concept of a framework is discussed within the context of recent efforts by the JET Collaboration, the authors of JEWEL, and the JETSCAPE collaborations. The framework ingredients for each of these approaches is presented with a sample of important results from each. The role of advanced statistical tools in comparing models to data is also discussed, along with the need for a more detailed accounting of correlated errors in experimental results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Urban Land Surface Effects on Summertime Clouds and Moist Convection in Houston Under Different Synoptic Conditions

Urban landscapes modify cloud formation and convection through complex thermodynamic and aerodynamic processes; however, their influence under different synoptic regimes remains poorly understood. This study investigates the impact of the Houston metropolitan area on summertime cloud cover and convective cell characteristics using a combination of satellite observations, radar data, and high-resolution process-based modeling. We isolate urban effects by comparing model simulations with realistic urban land cover against hypothetical scenarios where all urban areas are replaced by rural vegetation. Results reveal that Houston's land cover consistently enhances cloud fraction and convective activity relative to surrounding rural areas, altered by large-scale meteorological forcing. Under weakly forced conditions, enhanced surface heat flux primarily contributes to driving low-level convergence and vertical ascent, leading to over 8% cloud fraction increase between 2 and 6 km over the city. Under strongly forced conditions, urban influences manifest differently depending on cloud type. For non-convective clouds, the city acts as a barrier that decelerates and lifts moist southerly inflow, increasing low cloud cover over the urban core, while decreasing it downwind the city. For convective clouds, both synoptic ascent and urbanization modulate moisture redistribution and cloud structure, producing modest cloud enhancement over the city and slight suppression over the downwind area. Urbanization exerts small changes in the intensity of the convective cells; however, it significantly decreases their duration and traveling distance. This work highlights the importance of accounting for land surface heterogeneity in modeling clouds and precipitation and demonstrates that urban impacts on clouds are highly regime-dependent.

Liu, Ye [Pacific Northwest National Laboratory (PN↗
DOE OSTI2022

Plasma thermal transport with a generalized 8-moment distribution function

Moment equations that model plasma transport require an ansatz distribution function to close the system of equations. The resulting transport is sensitive to the specific closure used, and several options have been proposed in the literature. Two different 8-moment distribution functions can be generalized to form a single-parameter family of distribution functions. The transport coefficients resulting from this generalized distribution function can be expressed in terms of this free parameter. This provides the flexibility of matching the 8-moment model to some validating result at a given magnetization value, such as Braginskii’s transport, or the more recent results of Davies et al. [Physics of Plasma, 28, 012305 (2021)]. Here, this process can be thought of as solving for the 8-moment distribution function that matches the value of a transport coefficient given by a Chapman-Enskog expansion, while retaining the improved physical properties, such as finite propagation speeds and time dependence which belong to the hyperbolic moment models. Since the presented generalized distribution function only has a single free parameter, only a single transport coefficient can be matched at a time. However, this generalization process may be extended to provide multiple free parameters. The focus of this Brief Communication is on the dramatically improved thermal conductivity of the proposed model compared to the two base moment models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The physiological basis for estimating photosynthesis from Chl>em>a fluorescence

We report solar-induced Chl fluorescence (SIF) offers the potential to curb large uncertainties in the estimation of photosynthesis across biomes and climates, and at different spatiotemporal scales. However, it remains unclear how SIF should be used to mechanistically estimate photosynthesis. In this study, we built a quantitative framework for the estimation of photosynthesis, based on a mechanistic light reaction model with the Chla fluorescence of Photosystem II (SIFPSII) as an input (MLR-SIF). Utilizing 29 C 3 and C 4 plant species that are representative of major plant biomes across the globe, we confirmed the validity of this framework at the leaf level. The MLR-SIF model is capable of accurately reproducing photosynthesis for all C 3 and C 4 species under diverse light, temperature, and CO 2 conditions. We further tested the robustness of the MLR-SIF model using Monte Carlo simulations, and found that photosynthesis estimates were much less sensitive to parameter uncertainties relative to the conventional Farquhar, von Caemmerer, Berry (FvCB) model because of the additional independent information contained in SIF PSII . Once inferred from direct observables of SIF, SIF PSII provides ‘parameter savings’ to the MLR-SIF model, compared to the mechanistically equivalent FvCB model, and thus avoids the uncertainties arising as a result of imperfect model parameterization. Our findings set the stage for future efforts to employ SIF mechanistically to improve photosynthesis estimates across a variety of scales, functional groups, and environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Weak-Form Latent Space Dynamics Identification

This software showcases the enhanced capabilities of the Latent Space Dynamics Identification (LaSDI) algorithm through the application of the weak form, resulting in WLaSDI. WLaSDI first compresses the data, then projects it onto test functions, and subsequently learns the local latent space models. Notably, WLaSDI demonstrates significantly improved robustness to noise. Using weak-form equation learning techniques, WLaSDI achieves local latent space modeling. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form ensures robust and precise latent space recovery, enabling fast, robust, and accurate simulations. We demonstrate the efficacy of WLaSDI against LaSDI using several common benchmark examples, including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in 1D inviscid Burgers' simulations with up to 100% Gaussian white noise, WLaSDI maintains relative errors consistently below 6%, whereas LaSDI errors can exceed 10,000%. Similarly, in radial advection simulations, WLaSDI keeps relative errors below 16%, compared to potential errors of up to 10,000% with LaSDI. Additionally, WLaSDI achieves significant speedups, such as a 140X speedup in 1D Burgers' simulations compared to the corresponding full order model.

Choi, Youngsoo↗
DOE OSTI2019

What Drives Upper-Ocean Temperature Variability in Coupled Climate Models and Observations?

Abstract A key question in climate modeling is to what extent sea surface temperature and upper-ocean heat content are driven passively by air–sea heat fluxes, as opposed to forcing by ocean dynamics. This paper investigates the question using a climate model at different resolutions, and observations, for monthly variability. At the grid scale in a high-resolution climate model with resolved mesoscale ocean eddies, ocean dynamics (i.e., ocean heat flux convergence) dominates upper 50 m heat content variability over most of the globe. For deeper depths of integration to 400 m, the heat content variability at the grid scale is almost totally controlled by ocean heat flux convergence. However, a strong dependence on spatial scale is found—for the upper 50 m of ocean, after smoothing the data to around 7°, air–sea heat fluxes, augmented by Ekman heat transports, dominate. For deeper depths of integration to 400 m, the transition scale becomes larger and is above 10° in western boundary currents. Comparison of climate model results with observations show that the small-scale influence of ocean intrinsic variability is well captured by the high-resolution model but is missing from a comparable model with parameterized ocean-eddy effects. In the deep tropics, ocean dynamics dominates in all cases and all scales. In the subtropical gyres at large scales, air–sea heat fluxes play the biggest role. In the midlatitudes, at large scales >10°, atmosphere-driven air–sea heat fluxes and Ekman heat transport variability are the dominant processes except in the western boundary currents for the 400 m heat content.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Modeling of vortex generated sound in solid propellant rocket motors

There is considerable evidence based on both full scale firings and cold flow simulations that hydrodynamically unstable shear flows in solid propellant rocket motors can lead to acoustic pressure fluctuations of significant amplitude. Although a comprehensive theoretical understanding of this problem does not yet exist, procedures were explored for generating useful analytical models describing the vortex shedding phenomenon and the mechanisms of coupling to the acoustic field in a rocket combustion chamber. Since combustion stability prediction procedures cannot be successful without incorporation of all acoustic gains and losses, it is clear that a vortex driving model comparable in quality to the analytical models currently employed to represent linear combustion instability must be formulated.

Flandro, G. A.↗
NASA NTRS2015

An Approach to Quantify Workload in a System of Agents

The role of humans in aviation and other domains continues to shift from manual control to automation monitoring. Studies have found that humans are often poorly suited for monitoring roles, and workload can easily spike in off-nominal situations. Current workload measurement tools, like NASA TLX, use human operators to assess their own workload after using a prototype system. Such measures are used late in the design process and can result in ex- pensive alterations when problems are discovered. Our goal in this work is to provide a quantitative workload measure for use early in the design process. We leverage research in human cognition to de ne metrics that can measure workload on belief-desire-intentions based multi-agent systems. These measures can alert designers to potential workload issues early in design. We demonstrate the utility of our approach by characterizing quantitative differences in the workload for a single pilot operations model compared to a traditional two pilot model.

Single Pilot Operations↗
NASA NTRS2017

Model-Based Thermal System Design Optimization for the James Webb Space Telescope

Spacecraft thermal model validation is normally performed by comparing model predictions with thermal test data and reducing their discrepancies to meet the mission requirements. Based on thermal engineering expertise, the model input parameters are adjusted to tune the model output response to the test data. The end result is not guaranteed to be the best solution in terms of reduced discrepancy and the process requires months to complete. A model-based methodology was developed to perform the validation process in a fully automated fashion and provide mathematical bases to the search for the optimal parameter set that minimizes the discrepancies between model and data. The methodology was successfully applied to several thermal subsystems of the James Webb Space Telescope (JWST). Global or quasiglobal optimal solutions were found and the total execution time of the model validation process was reduced to about two weeks. The model sensitivities to the parameters, which are required to solve the optimization problem, can be calculated automatically before the test begins and provide a library for sensitivity studies. This methodology represents a crucial commodity when testing complex, large-scale systems under time and budget constraints. Here, results for the JWST Core thermal system will be presented in detail.

Cataldo, Giuseppe↗
DOE OSTI2023

Rapid Spaceborne Mapping of Wildfire Retardant Drops for Active Wildfire Management

Aerial application of fire retardant is a critical tool for managing wildland fire spread. Retardant applications are carefully planned to maximize fire line effectiveness, improve firefighter safety, protect high-value resources and assets, and limit environmental impact. However, topography, wind, visibility, and aircraft orientation can lead to differences between planned drop locations and the actual placement of the retardant. Information on the precise placement and areal extent of the dropped retardant can provide wildland fire managers with key information to (1) adaptively manage event resources, (2) assess the effectiveness of retardant slowing or stopping fire spread, (3) document location in relation to ecologically sensitive areas; and perform or validate cost-accounting for drop services. This study uses Sentinel-2 satellite data and commonly used machine learning classifiers to test an automated approach for detecting and mapping retardant application. We show that a multiclass model (retardant, burned, unburned, and cloud artifact classes) outperforms a single-class retardant model and that image differencing (post-application minus pre-application) outperforms single-image models. Compared to the random forest and support vector machine, the gradient boosting model performed the best with an overall accuracy of 0.88 and an F1 Score of 0.76 for fire retardant, though results were comparable for all three models. Our approach maps the full areal extent of the dropped retardant within minutes of image availability, rather than linear representations currently mapped by aerial GPS surveys. The development of this capability allows for the rapid assessment of retardant effectiveness and documentation of placement in relation to sensitive environments.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Comparison of measurements and models in stratospheric polar vortex studies

An overview will be given of recent studies comparing model results with observations of stratospheric meteorological and trace gas fields, focusing on the polar vortex during winter. Studies comparing process-oriented (e.g., stability) model, mechanistic (i.e., forced lower boundary near the tropopause) model and general circulation model (GCM) simulations of the dynamics of the polar winter stratosphere with analyzed or assimilated meteorological datasets are reviewed.

modeling↗
NASA NTRS2015

Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

simulation↗
DOE OSTI2023

Soil Respiration Responses to Throughfall Exclusion Are Decoupled From Changes in Soil Moisture for Four Tropical Forests, Suggesting Processes for Ecosystem Models

Abstract Climatic drying is predicted for many tropical forests yet models remain poorly parameterized for these ecosystems, hampering predictions of forest‐climate interactions. We applied an integrated model–experiment approach, parameterizing an ecosystem model with tropical forest observational data and comparing model predictions to a field drying manipulation. We hypothesized that drying suppresses soil CO 2 fluxes (i.e., respiration) in relatively dry tropical forests but increases CO 2 fluxes in wetter tropical forests by alleviating anaerobiosis. We measured soil CO 2 fluxes during wet‐dry cycles from 2015 to 2022 in four Panamanian forests that vary in rainfall and soil fertility. Measured soil CO 2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in lower soil moisture optima for respiration than previously modeled. We then parameterized the model using field data and the new moisture‐respiration response functions. The updated model predicted increased soil CO 2 fluxes with drying in wetter and fertile forests and suppressed fluxes in drier, infertile forests. In contrast to model predictions, a chronic throughfall exclusion experiment initially suppressed soil respiration across forests, with sustained suppression for four years in the wettest forest only (−28% ± 4% during the dry season). In the fertile forest, drying eventually elevated CO 2 fluxes over this period (+75% ± 28% during the late wet season). The unexpected negative drying effect in the wettest, infertile forest could have resulted from reduced vertical flushing of nutrients into soils. Including hydro‐nutrient interactions in ecosystem models could improve predictions of tropical forest‐climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

HYSPLIT/MACCS Atmospheric Dispersion Model Technical Documentation and Benchmark Analysis

The nuclear accident consequence analysis code MACCS has traditionally modeled dispersion during downwind transport using a Gaussian plume segment model. MACCS is designed to estimate consequence measures such as air concentrations and ground depositions, radiological doses, and health and economic impacts on a statistical basis over the course of a year to produce annualaveraged output measures. The objective of this work is to supplement the Gaussian atmospheric transport and diffusion (ATD) model currently in MACCS with a new option using the HYSPLIT model. HYSPLIT/MACCS coupling has been implemented, with HYSPLIT as an alternative ATD option. The subsequent calculations in MACCS use the HYSPLIT-generated air concentration, and ground deposition values to calculate the same range of output quantities (dose, health effects, risks, etc.) that can be generated when using the MACCS Gaussian ATD model. Based on the results from the verification test cases, the implementation of the HYSPLIT/MACCS coupling is confirmed. This report contains technical details of the HYSPLIT/MACCS coupling and presents a benchmark analysis using the HYSPLIT/MACCS coupling system. The benchmark analysis, which involves running specific scenarios and sensitivity studies designed to examine how the results generated by the traditional MACCS Gaussian plume segment model compare to the new, higher fidelity HYSPLIT/MACCS modeling option, demonstrates the modeling results that can be obtained by using this new option. The comparisons provided herein can also help decision-makers evaluate the potential benefit of using results based on higher fidelity modeling with the additional computational burden needed to perform the calculations. Three sensitivity studies to investigate the potential impact of alternative modeling options, regarding 1) input meteorological data set, 2) method to estimate stability class, and 3) plume dispersion model for larger distances, on consequence results were also performed. The results of these analyses are provided and discussed in this report.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Multistep modeling of protein structure: application to bungarotoxin

Modelling of bungarotoxin in atomic details is presented in this article. The model-building procedure utilizes the low-resolution crystal coordinates of the c-alpha atoms of bungarotoxin, sequence homology within the neurotoxin family, as well as high-resolution x-ray diffraction data of cobratoxin and erabutoxin. Our model-building procedure involves: (a) principles of comparative modelling, (b) embedding procedures of distance geometry, and (c) use of molecular mechanics for optimizing packing. The model is not only consistent with the c-alpha coordinates of crystal structure, but also agrees with solution conformational features of the triple-stranded beta sheet as observed by NOE measurements.

NASA Discipline Exobiology↗