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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

A study of frontal dynamics with application to the Australian summertime 'cool change'

The dynamics of frontal evolution is examined in terms of the Australian summertime cool change using a two-dimensional numerical model. The model is synthesized from observational data on surface cold fronts obtained during the Australian Cold Fronts Research Program, and the model develops a quasi-steady surface cold front during the 24 hours of integration. The characteristics of this model are compared with those of a kinematic model; it is observed that the features of the two models correspond. The two-dimensional and kinematic models are also compared with a 24-hour prediction of the cold front of February 1983 using the three-dimensional nested-grid model of the Australian Numerical Meteorology Research Center, developed by Gauntlett et al. (1984). Good correlation between these models is detected.

Reeder, Michael J.↗
DOE OSTI2022

Bayesian model updating with finite element vs surrogate models: Application to a miter gate structural system

Bayesian finite element (FE) model updating using direct model evaluations of large-scale high-fidelity FE models is extremely computationally expensive. Surrogate models can be used as fast emulators of FE models to accelerate the model calibration process. The physics/mechanics-based FE models are still the underpinning behind the surrogate models. Here, this paper evaluates the loss in accuracy and the gain in computational time while performing Bayesian model updating by using surrogate model evaluations compared to using direct FE model evaluations. This evaluation is crucial before entirely relying on surrogate models in model updating for structural health monitoring (SHM) and damage prognosis (DP) purposes. This paper also demonstrates Bayesian updating and surrogate model construction of large-scale high-fidelity FE models of infrastructure systems. In this regard, the miter gate structural system is considered as the testbed structure. Three predominant damage modes (loss of contact between gate and wall, loss of thickness due to corrosion, and loss of tension in the diagonal rods) are considered for model updating purposes. Bayesian model updating is performed using direct FE evaluations by leveraging parallel computing. Two types of surrogates, namely polynomial chaos expansion (PCE) and Gaussian process regression (GPR), are developed for the miter gate. Model updating is performed again using the trained surrogate models, and the updating results are compared with their counterparts obtained using the direct FE evaluation results. The posterior distribution of the FE model parameters obtained using the trained surrogates are sufficiently accurate with respect to the posterior obtained utilizing the direct FE evaluations. In addition, an approximate 4-fold decrease in the computational time was observed when using surrogate model evaluations instead of direct FE evaluations for model updating.

42 ENGINEERING↗
NASA NTRS2013

Challenges in Quantifying Pliocene Terrestrial Warming Revealed by Data-Model Discord

Comparing simulations of key warm periods in Earth history with contemporaneous geological proxy data is a useful approach for evaluating the ability of climate models to simulate warm, high-CO2 climates that are unprecedented in the more recent past. Here we use a global data set of confidence-assessed, proxy-based temperature estimates and biome reconstructions to assess the ability of eight models to simulate warm terrestrial climates of the Pliocene epoch. The Late Pliocene, 3.6-2.6 million years ago, is an accessible geological interval to understand climate processes of a warmer world4. We show that model-predicted surface air temperatures reveal a substantial cold bias in the Northern Hemisphere. Particularly strong data-model mismatches in mean annual temperatures (up to 18 C) exist in northern Russia. Our model sensitivity tests identify insufficient temporal constraints hampering the accurate configuration of model boundary conditions as an important factor impacting on data- model discrepancies. We conclude that to allow a more robust evaluation of the ability of present climate models to predict warm climates, future Pliocene data-model comparison studies should focus on orbitally defined time slices.

Salzmann, Ulrich↗
DOE OSTI2022

Chemical mixture exposure patterns and obesity among U.S. adults in NHANES 2005–2012

The effect of chemical exposure on obesity has raised great concerns. Real-world chemical exposure always imposes mixture impacts, however their exposure patterns and the corresponding associations with obesity have not been fully evaluated. To discover obesity-related mixed chemical exposure patterns in the general U.S. population. Sparse Decompositional Regression (SDR), a model adapted from sparse representation learning technique, was developed to identify exposure patterns of chemical mixtures with exclusion (non-targeted model) and inclusion (targeted model) of health outcomes. We assessed the relationships between the identified chemical mixture patterns and obesity-related indexes. We also conducted a comprehensive evaluation of this SDR model by comparing to the existing models, including generalized linear regression model (GLM), principal component analysis (PCA), and Bayesian kernel machine regression (BKMR). Eight core exposure patterns were identified using the non-targeted SDR model. Patterns of high levels of MEP, high levels of naphthalene metabolites (ΣOH-Nap), and a pattern of high exposure levels of MCOP, MCNP, and MCPP were positively associated with obesity. Patterns of high levels of BP3, and a pattern of higher mixed levels of MPB, PPB, and MEP were found to have negative associations. Associations were strengthened using the targeted SDR model. In the single chemical analysis by GLM, BP3, MBP, PPB, MCOP, and MCNP showed significant associations with obesity or body indexes. The SDR model exceeded the performance of PCA in pattern identification. Both SDR and BKMR identified a positive contribution of ΣOH-Nap and MCOP, as well as a negative contribution of BP3 and PPB to obesity. Our study identified five core exposure patterns of chemical mixtures significantly associated with obesity using the newly developed SDR model. The SDR model could open a new avenue for assessing health effects of environmental mixture contaminants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Optimal assignment for the single-household shared autonomous vehicle problem

Autonomous vehicles have the potential to transform the way people are transported. While driverless technology may mean fewer vehicles are required to transport people to and from their daily activities, such changes may result in increased congestion or total miles traveled. In this study, we solve the single-household shared autonomous vehicle problem to identify cost-optimal routings of vehicles throughout the day. Such a tool will be useful for consumers seeking to minimize cost and for regulators seeking to understand and predict how people may behave in different scenarios. Here, we provide a thorough literature review and construct a mixed-integer linear program to minimize the daily travel cost of a household attending a given set of activities. Since solution time is a determinant for applicability of such a model, we present the model in a component-wise fashion. This approach allows us to understand which features most affect the problem complexity and solution time. We note that modeling carpooling is the feature that most increases time to find an optimal solution, and we therefore propose a novel modeling technique for carpooling two people. We illustrate the performance of our model by comparing it with other models from the literature and note that our model can solve significantly larger problem instances and in a time that is short enough to facilitate real-time scheduling. We also highlight the utility of our model for regulators, who can use it to analyze quickly produced optimal routes under different cost/tax scenarios.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Prediction of Redox Potentials for Ac, Th, and Pa in Aqueous Solution

Density functional theory in conjunction with small core pseudopotentials and the associated basis sets was used to calculate potentials for multiple redox couples, covering a range of oxidation states for Ac (0 to III), Th (0 to IV), and Pa (0 to V) in aqueous solution. Solvation effects were incorporated using a supermolecule-continuum approach, with 30 water molecules representing two solvation shells, and the COSMO and SMD implicit solvation models. The calculated geometries for Ac(III), Th(IV), and Pa(V) were in reasonable agreement with the available experimental data. Using the COSMO model with the B3LYP functional, the calculated redox potentials were within ± 0.2 V from experiment for most redox couples. Several pathways were explored for the Pa(V/IV) redox couple for different forms of Pa(V) and Pa(IV). Most Pa(V/IV) redox couples have very similar potentials, ranging from 0 to -0.4 V up to a pH of 1.4. At pH = 1.4, the potentials shift to values that are more negative than -0.7 V, reflecting the growing unfavorable nature of the redox process at higher pH levels. The calculated values for An(III/II) potentials were consistent with prior estimates and the available experimental data. The predicted redox potentials for An(II/I) were highly negative, as expected. For An(I/0) potentials, Th and Pa exhibited positive values, contrasting with the negative values calculated for Ac. Furthermore, the An +m /An(0) potentials agreed better with the experimental data when using the COSMO solvation model as compared to the SMD model.

Chemical calculations↗
DOE OSTI2025

How are Heterogeneous Nucleation Rate Observations Influenced by Instrument Resolution?

Experimental measurements of the heterogeneous nucleation rate rely on counting the number of nuclei with time. However, the size of a thermodynamically stable nucleus is often a few nanometers in diameter and is below the resolution of most (in situ) measurement techniques that provide a statistically valid sample. Due to the finite resolution of the instruments and analysis methods, it is challenging to capture the incipient nuclei and the subsequent evolution of nuclei density over time. In this work, we demonstrate the impact of instrument resolution on observed nuclei densities by comparing numerical modeling with experimental results. Further, to achieve this, we implemented heterogeneous nucleation within the pore-scale reactive transport modeling framework using classical nucleation theory (CNT). We compared the modeling results with nucleation rates measured using X-ray nanotomography (XnT) and evaluated how these impact the apparent values of the prefactor and interfacial energy based on CNT and the crystal growth rate. Specifically, we applied a resolution threshold (artificial resolution limit) in the model during nuclei counting to resemble an experimental resolution, ranging from 15 to 500 nm. The findings reveal that the instrument resolution significantly impacts the apparent prefactor and interfacial energy. Both apparent prefactor and interfacial energy decrease with a decrease in the instrument resolution. While deviation in the prefactor due to resolution is anticipated, those in the interfacial energy are unexpected. The approach described here allows one to correct apparent nucleation rates that depend on the instrument’s resolution to derive “intrinsic” CNT parameters for the prefactor and interfacial energy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

AMOC Variability in Climate Models and Its Dependence on the Mean State

Abstract Understanding internal variability of the climate system is critical when isolating internal and anthropogenically forced signals. Here, we investigate the modes of Atlantic Meridional Overturning Circulation ( AMOC ) variability using perturbation experiments with the Institut Pierre‐Simon Laplace's (IPSL) coupled model and compare them to Coupled Model Intercomparison Project Phase 6 (CMIP6) pre‐industrial control simulations. We identify two characteristic modes of variability—decadal‐to‐multidecadal ( DMD var ) and centennial ( CEN var ). The former is driven largely by temperature anomalies in the subpolar North Atlantic, while the latter is driven by salinity in the western subpolar North Atlantic. The amplitude of each mode scales linearly with the mean AMOC strength in the IPSL experiments. The DMD var amplitude correlates well with the AMOC mean strength across CMIP6 models, while the CEN var mode does not. These findings suggest that the strength of DMD var depends robustly on the North Atlantic mean state, while the CEN var mode may be model‐dependent.

Ferster, Brady S. [LOCEAN‐IPSL Sorbonne Université↗
DOE OSTI2022

Mixed stochastic-deterministic time-dependent density functional theory: application to stopping power of warm dense carbon

Warm dense matter (WDM) describes an intermediate phase, between condensed matter and classical plasmas, found in natural and man-made systems. In a laboratory setting, WDM is often created dynamically. It is typically laser or pulse-power generated and can be difficult to characterize experimentally. Measuring the energy loss of high energy ions, caused by a WDM target, is both a promising diagnostic and of fundamental importance to inertial confinement fusion research. However, electron coupling, degeneracy, and quantum effects limit the accuracy of easily calculable kinetic models for stopping power, while high temperatures make the traditional tools of condensed matter, e.g. time-dependent density functional theory (TD-DFT), often intractable. In this study, we have developed a mixed stochastic-deterministic approach to TD-DFT which provides more efficient computation while maintaining the required precision for model discrimination. Recently, this approach showed significant improvement compared to models when compared to experimental energy loss measurements in WDM carbon. Here, we describe this approach and demonstrate its application to warm dense carbon stopping across a range of projectile velocities. We compare direct stopping-power calculation to approaches based on combining homogeneous electron gas response with bound electrons, with parameters extracted from our TD-DFT calculations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

The local hole: a galaxy underdensity covering 90 per cent of sky to ≈200 Mpc

We investigate the ‘Local Hole’, an anomalous underdensity in the local galaxy environment, by extending our previous galaxy K-band number-redshift and number-magnitude counts to ≈90 per cent of the sky. Our redshift samples are taken from the 2MASS Redshift Survey (2MRS) and the 2M++ catalogues, limited to K < 11.5. We find that both surveys are in good agreement, showing an ≈21–22 per cent underdensity at z < 0.075 when compared to our homogeneous counts model that assumes the same luminosity function (LF) and other parameters as in our earlier papers. Using the Two Micron All Sky Survey (2MASS) for n(K) galaxy counts, we measure an underdensity relative to this model of 20±2 per cent at K < 11.5, which is consistent in both form and scale with the observed n(z) underdensity. To examine further the accuracy of the counts model, we compare its prediction for the fainter n(K) counts of the Galaxy and Mass Assembly (GAMA) survey. We further compare these data with a model assuming the parameters of a previous study where little evidence for the Local Hole was found. At 13 < K < 16, we find a significantly better fit for our galaxy counts model, arguing for our higher LF normalization. Although our implied underdensity of ≈20 per cent means local measurements of the Hubble Constant have been overestimated by ≈3 per cent, such a scale of underdensity is in tension with a global ΛCDM cosmology at an ≈3σ level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

FEM Analysis of Hybrid LTS/HTS Cos-Theta Dipole Magnet With Heterogeneous Cable Model

The Lawrence Berkeley National Laboratory (LBNL) and the National High Magnetic Field Laboratory (NHMFL) have published results on Bi-2212 superconductive magnets realized and tested in the canted cosine-theta and solenoid designs, respectively. Fermilab is now preparing for the assembly of the first Bi-2212 stress-managed cosine-theta insert magnet. The insert will be part of the first hybrid cosine-theta magnet made of Nb$_3$Sn outer layers within the US-MDP effort to reach a 20 T bore field. This paper presents the analytical analysis of the cosine-theta Nb$_3$Sn/Bi-2212 hybrid magnet. We report the parameters, logic, and implementation method of the 2D electromagnetic and mechanical FEM analysis of the LTS/HTS hybrid magnet. Results from a detailed heterogeneous model are compared to the homogeneous model implemented in the past. A Python code has been developed to simulate the current degradation due to stresses in the detail-modeled conductor areas. The current degradation has been introduced in the simulation dynamics for the HTS conductor as an iteration process, updating the input load of Lorentz forces of the energization at each step. The magnetic and mechanical analysis results of the 2D cosine-theta LTS/HTS dipole magnet have been described and analyzed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science

Abstract Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph‐based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these “knowledge graphs” (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open‐access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open‐source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object‐oriented classification and graph‐oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Calibration verification for stochastic agent-based disease spread models

Accurate disease spread modeling is crucial for identifying the severity of outbreaks and planning effective mitigation efforts. To be reliable when applied to new outbreaks, model calibration techniques must be robust. However, current methods frequently forgo calibration verification (a stand-alone process evaluating the calibration procedure) and instead use overall model validation (a process comparing calibrated model results to data) to check calibration processes, which may conceal errors in calibration. In this work, we develop a stochastic agent-based disease spread model to act as a testing environment as we test two calibration methods using simulation-based calibration, which is a synthetic data calibration verification method. The first calibration method is a Bayesian inference approach using an empirically-constructed likelihood and Markov chain Monte Carlo (MCMC) sampling, while the second method is a likelihood-free approach using approximate Bayesian computation (ABC). Simulation-based calibration suggests that there are challenges with the empirical likelihood calculation used in the first calibration method in this context. These issues are alleviated in the ABC approach. Despite these challenges, we note that the first calibration method performs well in a synthetic data model validation test similar to those common in disease spread modeling literature. We conclude that stand-alone calibration verification using synthetic data may benefit epidemiological researchers in identifying model calibration challenges that may be difficult to identify with other commonly used model validation techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Surrogate Model of Flexible Research Platform EnergyPlus Models to Enable Sensitivity Analysis

This letter report describes the surrogate models developed from the EnergyPlus model of Oak Ridge National Laboratory’s Flexible Research Platform. Two data-driven black-box models were developed, and the outputs of the surrogate models were compared with the EnergyPlus model. The two models developed are a multilayer perceptron deep learning model, and a long short-term memory (LSTM) neural network model. The three factors for selecting the black-box models are scalability, computation time, and accuracy. A total of 107 input variables were the dominant variables in determining the outputs of building energy consumptions and thermal comfort. A total of 54 output variables were identified as the prediction targets, including the system- and zone-level outputs. The large set of the simulation cases were generated by integrating sensor errors into an emulator based on EnergyPlus and Python EMS, which includes advanced control sequences from ASHRAE Guideline 36-2018: High-Performance Sequences of Operation. The surrogate models were developed based on a set of large-scale simulation runs (i.e., 4,000 runs) on a cloud platform. The comparison analysis shows that the two black-box models had good accuracy for predicting new outputs for sensitivity analysis using the root mean square error metric. As a next step, the developed surrogate models will be used to perform sensitivity analysis for different sensor impacts (e.g., sensor types, sensor locations).

42 ENGINEERING↗
NASA NTRS1975

Orbital maneuvering engine feed system coupled stability investigation

A digital computer model used to analyze and predict engine feed system coupled instabilities over a frequency range of 10 to 1000 Hz was developed and verified. The analytical approach to modeling the feed system hydrodynamics, combustion dynamics, chamber dynamics, and overall engineering model structure is described and the governing equations in each of the technical areas are presented. This is followed by a description of the generalized computer model, including formulation of the discrete subprograms and their integration into an overall engineering model structure. The operation and capabilities of the engineering model were verified by comparing the model's theoretical predictions with experimental data from an OMS-type engine with a known feed system/engine chugging history.

Kahn, D. R.↗
NASA NTRS1975

Interpretation of the X-ray spectra of solar active regions

This paper presents a review of recent analytical studies of the coronal X-ray spectrum below 25 A. The techniques used to compute the theoretical coronal spectrum, and the currently available atomic rate constant data are reviewed first. Spectroscopic techniques which have been proposed for the determination of coronal temperature and density structure, and the results derived from their application to coronal spectra are also reviewed. A number of coronal models based on X-ray observations have been developed recently, and the coronal temperature structure and composition predicted by these models is discussed, and compared with models of the corona and transition region derived from studies of the solar EUV spectrum.

Walker, A. B. C., Jr.↗
NASA NTRS1979

Synthesis of a control model for a liquid nitrogen cooled, closed circuit, cryogenic nitrogen wind tunnel and its validation

The details of the efforts to synthesize a control-compatible multivariable model of a liquid nitrogen cooled, gaseous nitrogen operated, closed circuit, cryogenic pressure tunnel are presented. The synthesized model was transformed into a real-time cryogenic tunnel simulator, and this model is validated by comparing the model responses to the actual tunnel responses of the 0.3 m transonic cryogenic tunnel, using the quasi-steady-state and the transient responses of the model and the tunnel. The global nature of the simple, explicit, lumped multivariable model of a closed circuit cryogenic tunnel is demonstrated.

Balakrishna, S.↗
NASA NTRS1982

Models of climate cycles recorded in Martian polar layered deposits

Mars polar deposit accumulation models are used to predict the sequences of layer thicknesses. Continuous deposition and climate-modulated deposition models are compared, and two physical models of the latter type are developed in detail. In addition to examining the sensitivity of the sequence of layer thicknesses to model type and threshold, parallels with terrestrial ocean margin deposition are drawn with a view to better understanding the effects of a prolonged interval of nondeposition on stratigraphy and the modification of the central polar stratigraphy by scarp margin effects. When the threshold for deposition lies in the midrange with respect to excursions of the climate function, deposition occurs about half of the time, and there is only a slight modulation of the layer thickness. When the threshold for deposition is high, deposition occurs only a small fraction of the total time, and groups of layers form which are separated from other groups by long periods of nondeposition.

Cutts, J. A.↗