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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DECOVALEX-2023: Task C Final Report

The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1983

Simultaneous elastic and photoelastic calibration of birefringent orthotropic model materials

Transmission photoelastic analysis of composite models has been shown in recent years to be a viable stress analysis method for composite structures. However, difficulties in the fabrication of the model materials require the development of efficient mechanical and optical calibration procedures. In this paper, the methods for measuring elastic and photoelastic constants of composites are briefly reviewed. Then a new method, utilizing a relatively small calibration specimen, is described. In this method, electrical resistance strain gauges are mounted at selected points of a half-plane model and photoelastic measurements and strain readings are simultaneously taken. The data are processed by a least-squares procedure to yield the elastic and photoelastic constants. Comparison of results obtained by the proposed method with the results from conventional tests shows good agreement.

Prabhakaran, R.↗
DOE OSTI2026

TCAD-Machine Learning Enabled TID Compact Model Development for Commercial SiC MOSFET

We propose a TCAD (Technology Computer Aided Design)-machine learning coupled approach that combines a TCAD tool (Charon), optimization/uncertainty quantification tool (Dakota), surrogate models, and Bayesian learning capabilities. The coupling approach is used for accurate modeling and calibration of total ionizing dose (TID) induced threshold voltage (V th ) shifts in Commercial-Off-The-Shelf (COTS) semiconductor devices and to develop physics-informed TID compact models. This versatile approach is applied to model the TID effect in an exemplar COTS 3.3 kV SiC power MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor). With the Charon-Dakota coupling, we can determine key device geometry and doping values based on device physics, which are difficult to obtain or not available for COTS devices but important for TCAD simulation; additionally, we can efficiently generate thousands of simulation results in a large parameter space, which makes it possible to develop data-driven surrogate models and perform Bayesian calibration. Utilizing the full tool-coupling approach, we achieve calibrated TCAD simulation models that accurately capture the average TID-induced V th shifts behavior with total doses and V th shifts saturation at high doses as observed in experimental data. More importantly, the calibrated TCAD simulations are obtained with determined TID model parameters (e.g., hole trap density and capture cross section) values that contain well quantified uncertainties. Furthermore, we can isolate and quantify the noises that are not captured by the TCAD models but exist in the measured data due to measurements and devices variabilities. Lastly, the calibrated surrogate models are used to develop physics-informed TID compact models. The method is generalizable to other devices and/or radiation conditions with few modifications and can provide well-determined uncertainties.

COTS↗
DOE OSTI2024

A Multiscale Inelastic Internal State Variable Corrosion Model

We present a corrosion internal state variable (ISV) damage model based upon the integrated computational materials engineering (ICME) hierarchical multiscale paradigm. Structure–property experiments for magnesium alloys were used where the only inputs were the volume fractions of each element of the periodic table. This macroscale ISV corrosion model finds its basis in Horstemeyer’s mechanical damage model, which includes three separate ISVs for damage nucleation, growth, and coalescence, as well as Walton’s inclusion of corrosion, which introduces five new ISVs for pit nucleation, growth, and coalescence, along with general corrosion and intergranular corrosion. While Walton’s corrosion ISVs are phenomenological in nature, herein we develop a multiscale physical basis for the corrosion ISVs. The parameters for the macroscale corrosion ISVs were garnered from the mesoscale Butler–Volmer equations. Pure magnesium with differing amounts of aluminum were used in corrosion tests to exemplify the different pitting, general corrosion, and intergranular corrosion rates, and the macroscale ISV model was calibrated with said data, in which the only inputs to the model are the volume percentages of the elements magnesium and aluminum. Although magnesium alloys were used to motivate and calibrate the model, the model is abstract enough to possibly capture other material systems as well.

Chemistry↗
NASA NTRS1991

A calibration of solar envelope models using the frequencies of intermediate-degree solar acoustic oscillations

The frequency dependence of the phase shift, which arises from the reflection of internal acoustic waves (p-modes) at the outer solar layers, can be determined from the accurately measured frequencies of intermediate-degree p-modes. This dependence is sensitive to the complicated structure of the outer solar layers, down to the depth of the second ionization zone of helium. It can be used to calibrate solar envelope models. The results of the direct tests of a variety of solar envelope models using the phase shift inferred from the solar oscillation frequencies are reported.

Pamiatnykh, A. A.↗
DOE OSTI2026

Building Energy Analysis of Manufactured and Multifamily Housing Types in Juneau, Alaska

This report details the results of building energy modeling analysis evaluating the potential energy savings, economic outcomes, and grid-level electricity reduction associated with cold climate air source heat pump (ccASHP) adoption across multifamily and manufactured housing (MMFH) building typologies in the City and Borough of Juneau (CBJ). Three building archetypes were evaluated: multifamily 4-plex apartments, multifamily 8-plex apartments, and manufactured housing units. Building energy models were developed using OpenStudio-HPXML and calibrated to actual utility consumption data and local meteorological data from the Juneau International Airport weather station using an automated calibration tool following the BPI-2400-S-2015 v.2 standard for model calibration. Occupant behaviors present the greatest variability in successful calibrations. Calibrated models were benchmarked against a baseline electric resistance heating condition, with the selected ccASHP modeled as the retrofit condition and typical meteorological year weather data for all results generation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2010

Calibration Designs for Non-Monolithic Wind Tunnel Force Balances

This research paper investigates current experimental designs and regression models for calibrating internal wind tunnel force balances of non-monolithic design. Such calibration methods are necessary for this class of balance because it has an electrical response that is dependent upon the sign of the applied forces and moments. This dependency gives rise to discontinuities in the response surfaces that are not easily modeled using traditional response surface methodologies. An analysis of current recommended calibration models is shown to lead to correlated response model terms. Alternative modeling methods are explored which feature orthogonal or near-orthogonal terms.

Wind tunnel models↗
DOE OSTI2026

AWSD Reactive Burn Model for the HMX‐Based High Explosive LX‐04

An Arrhenius–Wescott–Stewart–Davis (AWSD) reactive burn model is applied to describe shock initiation and detonation properties of the HMX-based high explosive LX-04. The parameters in the model are calibrated to data from multiple sources. The thermodynamic equations of state used in the model are calibrated to a combination of thermochemical calculations for HMX and LX-04 as well as experimentally-measured cylinder expansion results for LX-04. The kinetic parameters are calibrated to velocity data from gas gun experiments performed using EDC-32—a high explosive with the same chemical composition as LX-04 but different structural properties, and scaled rate stick data for PBX 9012. The AWSD model is shown to accurately describe the shock initiation and propagation of LX-04. Very good agreement is observed between the available experimental data and the AWSD model output. The presented results constitute an accurate LX-04 reactive burn model for use in engineering-scale models and simulations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Bayesian calibration of stochastic agent based model via random forest

SAND2024-11403O The Bayesian Calibration of Stochastic Agent-based Model via Random Forest is a code that was developed in concurrence with an article by the same name that was written for a journal. The code reproduces simulation results and plots from the article. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2024

Modeling the Effects of Artificial Drainage on Agriculture-Dominated Watersheds Using a Fully Distributed Integrated Hydrology Model

In agriculture-dominated watersheds where natural drainage is poor, agricultural ditches (narrow engineered channels) and tile drains (perforated pipes) are widely employed to enhance surface and subsurface drainage, respectively. Despite their relatively small scale, these features exert substantial control over the hydro-biogeochemical function of watersheds and their effects need to be represented in the models. We introduce a novel strategy to incorporate the effects of artificial agricultural drainage into a fully distributed basin-scale integrated surface-subsurface hydrology models. In our approach, narrow agriculture ditches for surface drainage are resolved efficiently using ditch-aligned computational meshes that are hydrologically conditioned to ensure connectivity in the stream/ditch network. For tile drainage in the subsurface, we use the physically based Hooghoudt's drainage equation as a subgrid model and route the water drained through tiles to the nearest ditch. Without site-specific calibration, this model reproduced observed streamflow in the Portage River Watershed (>1,000 km 2 ) as recorded by a USGS gauge with good accuracy (normalized KGE = 0.81) and outperformed a calibrated SWAT model (normalized KGE = 0.68). Numerical experiments confirm that artificial drainage reduces surface inundations and effectively controls the water table. At the watershed scale, artificial drainage increases baseflow but has little effect on watershed discharges above the 90th percentile. The strong physical underpinnings and reduced need for calibration allow us to study the impacts of artificial drainage on distributed hydrological response in terms of fluxes and states and provide a platform for investigating watershed-scale nutrient transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Multi‐Model Ensembles in Ecosystem Modeling: Challenges and Best Practices for Decision‐Making

Ecosystem models are increasingly central to the decision-making for environmental policy, conservation planning, and climate-related investments. Yet, the growing reliance on Multi-Model Ensembles (MMEs) of ecosystem models by practitioners and policymakers, sometimes under tight timelines and imperfect information, has frequently outpaced the scientific rigor required to ensure ensemble reliability. Here, MMEs refer to approaches that combine targeted predictions from multiple models with the expectation of improving robustness and quantifying predictive uncertainty. Poorly designed MMEs may create a false sense of confidence and lead to suboptimal policy and market decisions. This perspective argues that robust decision-making-relevant MMEs must be grounded on two pillars: (1) rigorous Model Intercomparison Projects (MIPs), which identify inter-model agreement and disagreement, characterize model uncertainties, and evaluate robustness with observationally based benchmarks—MIPs' diagnostic evaluation is so critical that it must be needed to drive MME's decision in model selection and weighting, especially when only a limited number of models available; and (2) co-design by both stakeholders and scientists to ensure that scenarios, metrics and uncertainty requirements provide decision-relevant information. Building upon the past success and lessons from the existing MIPs-MMEs efforts (e.g., climate/Earth system/crop), we derived the theoretical basis for MMEs, addressed their specific challenges in ecosystem modeling, and highlighted proper consideration of model numbers and diversity, risk of model inter-dependence, effective calibration of model parameters, possible overdue of some ecosystem model development, critical roles of open benchmark data across a wide range of conditions, and suggested use of Artificial Intelligence to support MIPs-MMEs. We highlighted the under-recognized opportunity for MIPs and MMEs to drive scientific progress and innovation through identifying better performing models, systematic benchmarking, feedback loops, and targeted model improvement. By following actionable best practice guidelines, MMEs can evolve from ad hoc aggregation of models into a trusted backbone of environmental policy and decision-making.

ecosystem modeling↗
DOE OSTI2024

Initial Alloy 709 constitutive models for use with the ASME design by inelastic analysis and EPP+SMT design methods

This report details a preliminary inelastic constitutive model describing the behavior of Alloy 709. This model will serve two purposes: (1) integration into Nonmandatory Appendix HBB-Z of the ASME Boiler & Pressure Vessel Code Section III, Division 5 and (2) extrapolating cyclic test data to difficult to measure conditions for formulating improved creep-fatigue design methods. For both applications, the model must accurately capture the material behavior across a wide range of temperatures and a variety of test conditions, both monotonic and cyclic. For this purpose we adopt a universal model form under consideration to standardize the description of high temperature constitutive models in the ASME Code. This report briefly restates that model form and how we calibrate the model against the test data, summarizes the test database, and validates the final, trained model by comparison to the experimental tests.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

CFD Validation Study of a Hypersonic Cone-Slice-Flap Configuration

Model validation is the process of determining the degree of accuracy between the real world and the model. The result of model validation can either be used to improve the model through calibration or quantify the model-form uncertainty. This work focuses on providing the model-form uncertainty through an area metric for a hypersonic cone-slice-flap geometry configuration given uncertainty in both the simulation and experimental data. A procedure will be presented that can give an accurate representation of the model-form uncertainty using a small number of high-fidelity runs. The work will also assess the impact between using different high-fidelity solvers and different turbulence models.The goal of performing this comparison is to provide a quantifiable measurement for the accuracy of each solver and turbulence model for this type of design. A low-fidelity analysis will also be performed to get a model-form uncertainty for the lower fidelity analysis. The two high-fidelty CFD solvers used are VULCAN-CFD and FUN3D and the low-fidelity results will come from Cart3D. The experimental data came from the 20-inch Mach 6Tunnel located at NASA Langley Research Center.

Laura M. White↗
NASA NTRSDate not supplied

CFD Validation Study of a Hypersonic Cone-Slice-Flap Configuration

Model validation is the process of determining the degree of accuracy between the real world and the model. The result of model validation can be used to either improve the model through calibration or quantify the model-form uncertainty. This work focuses on estimating the model-form uncertainty through an area metric for a hypersonic cone-slice-flap geometry configuration given the uncertainty in both the simulation and experimental data. A procedure that can give an accurate representation of the model-form uncertainty using a small number of high-fidelity runs is outlined. The work also assesses the impact of using different high-fidelity solvers and different turbulence models. The goal of performing this comparison is to provide a quantifiable measurement of the accuracy of each solver and turbulence model for this type of design. A low-fidelity analysis is also performed to get a model-form uncertainty for this type of analysis. The two high-fidelity CFD solvers used here are VULCAN-CFD and FUN3D, and the low-fidelity results comes from Cart3D.The experimental data comes from the 20-inch Mach 6 Tunnel located at NASA Langley Research Center. The work here shows that the models used tend to under-predict the drag and moment aerodynamic coefficients for this type of design leading to a model-form uncertainty estimate which can account for up to an 86% of the total uncertainty in the model predictions.

Laura M White↗
NASA NTRSDate not supplied

CFD Validation Study of a Hypersonic Cone-Slice-Flap Variable Geometry Configuration

Model validation is the process of determining the degree of accuracy between physical reality and the model. The result of model validation can either be used to improve the model through calibration or quantify the model-form uncertainty. This work focuses on providing the model-form uncertainty through an area metric for a hypersonic cone-slice-flap variable geometry configuration given uncertainty in both the simulation and experimental data. The research here compares two different turbulence models for the simulations. For a variable geometry, performing uncertainty quantification to capture the model-form uncertainty on every configuration is computationally challenging. This work lays out a procedure that can give an accurate representation of the model-form uncertainty using a small number of high-fidelity runs and many low-fidelity runs on multiple configurations. Running this comparison provides a quantifiable measurement for the accuracy of each turbulence model for this type of design. The high-fidelity CFD solver used was VULCAN-CFD and the low-fidelity results came from Cart3D. The experimental data came from the 20-Inch Mach 6 Tunnel located at NASA Langley Research Center. The present work showed that the using both the Spalart and Allamaras and Menter Shear-Stress Transport turbulence models overpredicted the drag and lift coefficient, while underpredicting the pitching moment coefficient. The model-form uncertainty estimate resulted in up to a 13.6% change in the total uncertainty for the drag coefficient, up to a 57.4% change in total uncertainty for the lift coefficient, and up to a 100% change in total uncertainty for the pitching moment coefficient.

Laura M. White↗
NASA NTRSDate not supplied

CFD Validation Study of a Hypersonic Cone-Slice-Flap Variable Geometry Configuration

Model validation is the process of determining the degree of accuracy between physical reality and the model. The result of model validation can either be used to improve the model through calibration or quantify the model-form uncertainty. This work focuses on providing the model-form uncertainty through an area metric for a hypersonic cone-slice-flap variable geometry configuration given uncertainty in both the simulation and experimental data. For a variable geometry, performing uncertainty quantification to capture the model-form uncertainty on every configuration is computationally challenging. This work lays out a procedure that can give an accurate representation of the model-form uncertainty using a small number of high-fidelity runs and many low-fidelity runs on multiple configurations. Running this comparison provides a quantifiable measurement for the accuracy of each turbulence model for this type of design. The high-fidelity CFD solver used was VULCAN-CFD and the low-fidelity results came from Cart3D. The experimental data came from the 20-Inch Mach 6 Tunnel located at NASA Langley Research Center. The present work showed that the turbulence simulation overpredicted the drag and lift coefficient, while underpredicting the pitching moment coefficient. The model-form uncertainty estimate resulted up to a 13.6% change in the total uncertainty for the drag coefficient, up to a 57.4% change in total uncertainty for the lift coefficient, and up to a 100% change in total uncertainty for the pitching moment coefficient.

Laura White↗
NASA NTRS2013

Hidden Connections between Regression Models of Strain-Gage Balance Calibration Data

Hidden connections between regression models of wind tunnel strain-gage balance calibration data are investigated. These connections become visible whenever balance calibration data is supplied in its design format and both the Iterative and Non-Iterative Method are used to process the data. First, it is shown how the regression coefficients of the fitted balance loads of a force balance can be approximated by using the corresponding regression coefficients of the fitted strain-gage outputs. Then, data from the manual calibration of the Ames MK40 six-component force balance is chosen to illustrate how estimates of the regression coefficients of the fitted balance loads can be obtained from the regression coefficients of the fitted strain-gage outputs. The study illustrates that load predictions obtained by applying the Iterative or the Non-Iterative Method originate from two related regression solutions of the balance calibration data as long as balance loads are given in the design format of the balance, gage outputs behave highly linear, strict statistical quality metrics are used to assess regression models of the data, and regression model term combinations of the fitted loads and gage outputs can be obtained by a simple variable exchange.

Ulbrich, Norbert↗
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↗