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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Melt Pond Conditions on Declining Arctic Sea Ice Over 1979-2016: Model Development, Validation, and Results

A melt pond (MP) distribution equation has been developed and incorporated into the Marginal Ice-Zone Modeling and Assimilation System to simulate Arctic MPs and sea ice over 1979-2016. The equation differs from previous MP models and yet benefits from previous studies for MP parameterizations as well as a range of observations for model calibration. Model results show higher magnitude of MP volume per unit ice area and area fraction in most of the Canada Basin and the East Siberian Sea and lower magnitude in the central Arctic. This is consistent with Moderate Resolution Imaging Spectroradiometer observations, evaluated with Measurements of Earth Data for Environmental Analysis (MEDEA) data, and closely related to top ice melt per unit ice area. The model simulates a decrease in the total Arctic sea ice volume and area, owing to a strong increase in bottom and lateral ice melt. The sea ice decline leads to a strong decrease in the total MP volume and area. However, the Arctic-averaged MP volume per unit ice area and area fraction show weak, statistically insignificant downward trends, which is linked to the fact that MP water drainage per unit ice area is increasing. It is also linked to the fact that MP volume and area decrease relatively faster than ice area. This suggests that overall the actual MP conditions on ice have changed little in the past decades as the ice cover is retreating in response to Arctic warming, thus consistent with the Moderate Resolution Imaging Spectroradiometer observations that show no clear trend in MP area fraction over 2000-2011.

sea ice↗
DOE OSTI2017

Initial Verification and Validation Assessment for VERA

The Virtual Environment for Reactor Applications (VERA) code suite is assessed in terms of capability and credibility against the Consortium for Advanced Simulation of Light Water Reactors (CASL) Verification and Validation Plan (presented herein) in the context of three selected challenge problems: CRUD-Induced Power Shift (CIPS), Departure from Nucleate Boiling (DNB), and Pellet-Clad Interaction (PCI). Capability refers to evidence of required functionality for capturing phenomena of interest while capability refers to the evidence that provides confidence in the calculated results. For this assessment, each challenge problem defines a set of phenomenological requirements against which the VERA software is assessed. This approach, in turn, enables the focused assessment of only those capabilities relevant to the challenge problem. The evaluation of VERA against the challenge problem requirements represents a capability assessment. The mechanism for assessment is the Sandia-developed Predictive Capability Maturity Model (PCMM) that, for this assessment, evaluates VERA on 8 major criteria: (1) Representation and Geometric Fidelity, (2) Physics and Material Model Fidelity, (3) Software Quality Assurance and Engineering, (4) Code Verification, (5) Solution Verification, (6) Separate Effects Model Validation, (7) Integral Effects Model Validation, and (8) Uncertainty Quantification. For each attribute, a maturity score from zero to three is assigned in the context of each challenge problem. The evaluation of these eight elements constitutes the credibility assessment for VERA.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Updated Verification and Validation Assessment for VERA

The Virtual Environment for Reactor Applications (VERA) code suite is assessed in terms of capability and credibility against the Consortium for Advanced Simulation of Light Water Reactors (CASL) Verification and Validation Plan (presented herein) in the context of three selected challenge problems: CRUD-Induced Power Shift (CIPS), Departure from Nucleate Boiling (DNB), and Pellet-Clad Interaction (PCI). Capability refers to evidence of required functionality for capturing phenomena of interest while credibility refers to the evidence that provides confidence in the calculated results. For this assessment, each challenge problem defines a set of phenomenological requirements against which the VERA software is assessed. This approach, in turn, enables the focused assessment of only those capabilities relevant to the challenge problem. The evaluation of VERA against the challenge problem requirements represents a capability assessment. The mechanism for assessment is the Sandia-developed Predictive Capability Maturity Model (PCMM) that, for this assessment, evaluates VERA on 8 major criteria: (1) Representation and Geometric Fidelity, (2) Physics and Material Model Fidelity, (3) Software Quality Assurance and Engineering, (4) Code Verification, (5) Solution Verification, (6) Separate Effects Model Validation, (7) Integral Effects Model Validation, and (8) Uncertainty Quantification. For each attribute, a maturity score from zero to three is assigned in the context of each challenge problem. The evaluation of these eight elements constitutes the credibility assessment for VERA.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Updated Verification and Validation Assessment for VERA

The Virtual Environment for Reactor Applications (VERA) code suite is assessed in terms of capability and credibility against the Consortium for Advanced Simulation of Light Water Reactors (CASL) Verification and Validation Plan (presented herein) in the context of three selected challenge problems: CRUD-Induced Power Shift (CIPS), Departure from Nucleate Boiling (DNB), and Pellet-Clad Interaction (PCI). Capability refers to evidence of required functionality for capturing phenomena of interest while credibility refers to the evidence that provides confidence in the calculated results. For this assessment, each challenge problem defines a set of phenomenological requirements against which the VERA software is assessed. This approach, in turn, enables the focused assessment of only those capabilities relevant to the challenge problem. The evaluation of VERA against the challenge problem requirements represents a capability assessment. The mechanism for assessment is the Sandia-developed Predictive Capability Maturity Model (PCMM) that, for this assessment, evaluates VERA on 8 major criteria: (1) Representation and Geometric Fidelity, (2) Physics and Material Model Fidelity, (3) Software Quality Assurance and Engineering, (4) Code Verification, (5) Solution Verification, (6) Separate Effects Model Validation, (7) Integral Effects Model Validation, and (8) Uncertainty Quantification. For each attribute, a maturity score from zero to three is assigned in the context of each challenge problem. The evaluation of these eight elements constitutes the credibility assessment for VERA.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2005

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

MCKissick, Burnell T.↗
DOE OSTI2015

Mathematical modeling to validate on-line CO 2 measurements as a metric for cellulolytic biofilm activity in continuous-flow bioreactors

A mathematical model for the growth of thin Clostridium thermocellum biofilms on cellulose sheets with penetration from the surface into the interior fiber matrix is formulated in this paper, and used to assess the potential of CO 2 on-line measurements for activity of cellulolytic biofilms. The biofilm growth model is linked to a product formation model. It includes the processes of carbon substrate consumption, biofilm growth, biofilm upkeep, and carbon dioxide production. The mathematical description leads to a system of ordinary differential equations that is simple enough to lend itself to qualitative analysis, yet complex enough to capture the essential features of the system. Numerical fitting of the model against experimental data showed excellent quantitative agreement. Finally, the model substantiates the utility of on-line CO 2 measurements as indicator of cellulose substrate colonization and consumption, which may be useful for reporting bioreactor performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Dispersive shell pellet injection modeling and validation for DIII-D disruption mitigation

Dispersive shell pellet injection for disruption mitigation on the DIII-D tokamak is modeled with the 3D MHD code NIMROD. The simulations attempt to reproduce as closely as possible a pellet velocity scan that was performed on the DIII-D tokamak [Hollmann, et al., Phys. Rev. Lett. 122, 65001 (2019)]. This scan involved injecting a hollow diamond shell filled with boron dust that is released in the core of the plasma. Trends that are reproduced in the simulation include improved mitigation, reduced plasma current spike amplitude, and increased likelihood of hot-tail runaway electron production with increased pellet speed. The simulations provide additional physics insight into these findings. Limitations of the present model and requirements for a predictive model are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Validating predictive models for fast ion profile relaxation in burning plasmas

The redistribution and potential loss of energetic particles due to MHD modes can limit the performance of fusion plasmas by reducing the plasma heating rate. In this work, we present validation studies of the 1.5D critical gradient model (CGM) for Alfvén eigenmode (AE) induced EP transport in NSTX and DIII-D neutral beam heated plasmas. In previous comparisons with a single DIII-D L-mode case, the CGM model was found to be responsible for 75% of measured AE induced neutron deficit [1]. A fully kinetic HINST is used to compute mode stability for the non-perturbative version of CGM (or nCGM). We have found that AEs show strong local instability drive up to $\gamma /\omega \sim 20\%$ violating assumptions of perturbative approaches used in NOVA-K code. Lastly, we demonstrate that both models agree with each other and both underestimate the neutron deficit measured in DIII-D shot by approximately a factor of 2.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2005

The contribution of CEOP data to the understanding and modeling of monsoon systems

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validating models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Similar validation projects in other monsoon regions are being started. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of key components of the convective,and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variability, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

Lau, William K. M.↗
DOE OSTI2026

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan↗
DOE OSTI2024

Summary of FY2024 Experimental Results to Support Development of New Inelastic Material Models and Validation of Section III, Division 5, Class A Design Rules

To address the data gap crucial for updating existing viscoplastic constitutive material models for the Class A materials in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section III, Division 5, High Temperature Reactors (ASME, 2023) for inelastic design analysis, Oak Ridge National Laboratory (ORNL) conducted experimental studies on Alloy 800H and Alloy 617 across a range of temperatures up to their maximum temperature limits in Section III, Division 5. The studies aim to characterize the materials' deformation behavior under both strain-controlled mechanical cyclic loading and thermal cycling conditions. This report summarizes ORNL's FY 2024 experimental findings on Alloy 800H and Alloy 617, focusing on pure fatigue tests, cyclic stress-strain curves, thermomechanical fatigue experiments, and verification of the high temperature cyclic damage summation design rules.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Thermal aging modeling and validation on the Mo-containing Fe-Cr-Ni alloys

Thermodynamics of intermetallic phases in Fe-rich Fe-Cr-Ni-Mo alloys is critical knowledge to understand thermal aging effect on the phase stability of Mo-containing austenitic steels, which subsequently facilitates alloy design/improvement and degradation mitigation of these materials for reactor applications. Among the intermetallic phases, Chi (χ), Laves, and Sigma (σ) are often of concern because of their tendency to cause embrittlement of the materials. The focus of this study is thermal stability of the Chi and Laves phases as they were less studied compared to the Sigma phase. Coupled with thermodynamic modeling, thermal stability of intermetallic phases in Mo containing Fe-Cr-Ni alloys was investigated at 1000, 850 and 700°C for different annealing times. The morphologies, compositions and crystal structures of the precipitates of the intermetallic phases were carefully examined by scanning electron microscopy, electron probe microanalysis, X-ray diffraction, and transmission electron microscopy. Three key findings resulted from this study. First, the Chi phase is stable at high temperature, and with decreasing temperature it transforms into the Laves phase that is stable at low temperature. Secondly, Cr, Mo, Ni are soluble in both the Chi and Laves phases, with the solubility of Mo playing a major role in the relative stability of the intermetallic phases. Thirdly, in situ transformation from Chi phase to Laves phase was directly observed, which increased the local strain field, generated dislocations in the intermetallic phases, and altered the precipitate phase orientation relationship with the austenitic matrix. The thermodynamic models that were developed and validated were then applied to evaluating the effect of Mo on the thermal stability of intermetallic phases in type 316 and NF709 stainless steels.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mass measurement of 27 P to constrain type-I x-ray burst models and validate the isobaric multiplet mass equation for the $A = 27, T = \frac{3}{2}$ isospin quartet

Background: Light curves are the primary observable of type-I x-ray bursts. Computational x-ray burst models must match simulations to observed light curves. Most of the error in simulated curves comes from uncertainties in rp process reaction rates, which can be reduced via precision mass measurements of neutron-deficient isotopes in the rp process path. Purpose: Perform a precise atomic mass measurement of 27 P. Use this new measurement to calculate rp process reaction rates and input these rates into an x-ray burst model to reduce simulated light curve uncertainty. Use the mass measurement of 27 P to validate the isobaric multiplet mass equation (IMME) for the A = 27 T = 3/2 isospin quartet which 27 P belongs to. Method: High-precision Penning trap mass spectrometry utilizing the time-of-flight ion cyclotron resonance technique was used to determine the atomic mass of 27 P. The MESA code (Modules for Experiments in Stellar Astrophysics) was then used to simulate x-ray bursts using a one-dimensional multizone model to produce updated light curves. Results: The mass excess of 27 P was measured to be –670.7(6) keV, a 14-fold precision increase over the mass reported in the 2020 Atomic Mass Evaluation (AME2020). The 26 Si(p, $γ$) 27 P– 27 P($γ$, p) 26 Si rate equilibrium has been determined to a higher precision based on the precision mass measurement of 27 P. x-ray burst light curves were produced with the MESA code using the new reaction rates. Changes in the mass of 27 P seem to have minimal effect on light curves, even in burster systems tailored to maximize impact. Conclusion: The mass of 27 P does not play a significant role in x-ray burst light curves. It is important to understand that more advanced models do not just provide more precise results, but often qualitatively different ones. This result brings us a step closer to being able to extract stellar parameters from individual x-ray burst observations. In addition, the IMME has been validated for the A = 27, T = 3/2 quartet. The normal quadratic form of the IMME using the latest data yields a reduced $χ$ 2 of 2.9. Finally, the cubic term required to generate an exact fit to the latest data matches theoretical attempts to predict this term.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2000

Validation of an All-Pressure Fluid Drop Model: Heptane Fluid Drops in Nitrogen

Despite the fact that supercritical fluids occur both in nature and in industrial situations, the fundamentals of their behavior is poorly understood because supercritical fluids combine the characteristics of both liquids and gases, and therefore their behavior is not intuitive. There are several specific reasons for the lack of understanding: First, data from (mostly optical) measurements can be very misleading because regions of high density thus observed are frequently identified with liquids. A common misconception is that if in an experiment one can optically identify "drops" and "ligaments", the observed fluid must be in a liquid state. This inference is incorrect because in fact optical measurements detect any large change (i.e. gradients) in density. Thus, the density ratio may be well below Omicron(10(exp 3)) that characterizes its liquid/gas value, but the measurement will still identify a change in the index of refraction providing that the change is sudden (steep gradients). As shown by simulations of supercritical fluids, under certain conditions the density gradients may remain large during the supercritical binary fluids mixing, thus making them optically identifiable. Therefore, there is no inconsistency between the optical observation of high density regions and the fluids being in a supercritical state. A second misconception is that because a fluid has a liquid-like density, it is appropriate to model it as a liquid. However, such fluids may have liquid-like densities while their transport properties differ from those of a liquid. Considering that the critical pressure of most fuel hydrocarbons used in Diesel and gas turbine engines is in the range of 1.5 - 3 MPa, and the fact that the maximum pressure attained in these engines is about 6 Mps, it is clear that the fuel in the combustion chamber will experience both subcritical and supercritical conditions. Studies of drop behavior over a wide range of pressures were performed in the past, however none of these studies identified the crucial differences between the subcritical and supercritical behavior. In fact, in two of these studies, it was found that the subcritical and supercritical behavior is similar as the drop diameter decreased according to the classical d(exp 2)-law over a wide range of pressures and drop diameters. The present study is devoted to the exploration of differences in fluid-behavior characteristics under subcritical and supercritical conditions in the particular case of heptane fluid drops in nitrogen; these substances were selected because of the availability of experimental observations for model validation.

Harstad, K.↗
DOE OSTI2016

Computer Aided Battery Engineering Consortium

A multi-national lab collaborative team was assembled that includes experts from academia and industry to enhance recently developed Computer-Aided Battery Engineering for Electric Drive Vehicles (CAEBAT)-II battery crush modeling tools and to develop microstructure models for electrode design - both computationally efficient. Task 1. The new Multi-Scale Multi-Domain model framework (GH-MSMD) provides 100x to 1,000x computation speed-up in battery electrochemical/thermal simulation while retaining modularity of particles and electrode-, cell-, and pack-level domains. The increased speed enables direct use of the full model in parameter identification. Task 2. Mechanical-electrochemical-thermal (MECT) models for mechanical abuse simulation were simultaneously coupled, enabling simultaneous modeling of electrochemical reactions during the short circuit, when necessary. The interactions between mechanical failure and battery cell performance were studied, and the flexibility of the model for various batteries structures and loading conditions was improved. Model validation is ongoing to compare with test data from Sandia National Laboratories. The ABDT tool was established in ANSYS. Task 3. Microstructural modeling was conducted to enhance next-generation electrode designs. This 3- year project will validate models for a variety of electrodes, complementing Advanced Battery Research programs. Prototype tools have been developed for electrochemical simulation and geometric reconstruction.

25 ENERGY STORAGE↗
DOE OSTI2020

Perturbation theory for modeling galaxy bias: validation with simulations of the Dark Energy Survey

We describe perturbation theory (PT) models of galaxy bias for applications to photometric galaxy surveys. We model the galaxy-galaxy and galaxy-matter correlation functions in configuration space and validate against measurements from mock catalogs designed for the Dark Energy Survey (DES). We find that an effective PT model with five galaxy bias parameters provides a good description of the 3D correlation functions above scales of 4 Mpc/$h$ and $z < 1$. Our tests show that at the projected precision of the DES-Year 3 analysis, two of the non-linear bias parameters can be fixed to their co-evolution values, and a third (the $k^2$ term for higher derivative bias) set to zero. The agreement is typically at the 2 percent level over scales of interest, which is the statistical uncertainty of our simulation measurements. To achieve this level of agreement, our {\it fiducial} model requires using the full non-linear matter power spectrum (rather than the 1-loop PT one). We also measure the relationship between the non-linear and linear bias parameters and compare them to their expected co-evolution values. We use these tests to motivate the galaxy bias model and scale cuts for the cosmological analysis of the Dark Energy Survey; our conclusions are generally applicable to all photometric surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

A vorticity dynamics based model for the turbulent dissipation: Model development and validation

A new model dissipation rate equation is proposed based on the dynamic equation of the mean-square vorticity fluctuation for large Reynolds number turbulence. The advantage of working with the vorticity fluctuation equation is that the physical meanings of the terms in this equation are more clear than those in the dissipation rate equation. Hence, the model development based on the vorticity fluctuation equation is more straightforward. The resulting form of the model equation is consistent with the spectral energy cascade analysis introduced by Lumley. The proposed model dissipation rate equation is numerically well behaved and can be applied to any level of turbulence modeling. It is applied to a realizable eddy viscosity model. Flows that are examined include: rotating homogeneous shear flows; free shear flows; a channel flow and flat plate boundary layers with and without pressure gradients; and backward facing step separated flows. In most cases, the present model predictions show considerable improvement over the standard kappa-epsilon model.

Shih, Tsan-Hsing↗