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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Hydrate failure in ITZ governs concrete strength: A micro-to-macro validated engineering mechanics model

Ever since the early days of Féret (1892) and Abrams (1919), concrete research has targeted at relating concrete composition to uniaxial compressive strength. While these activities were mainly characterized by empirical fitting functions, we here take a more fundamental approach based on continuum micromechanics. The loading applied at the concrete level, is first concentrated (''downscaled'') to maximum stresses related to cement paste volumes which are directly adjacent to the aggregates, i.e. to the interfacial transition zones (ITZ). These maximum stresses are further ''downscaled'' to the micron-sized hydrates, in terms of higher-order stress averages. The latter enter a Drucker-Prager failure criterion with material constants derived from nanoindentation tests. The model is successfully validated across the hydrate-to-concrete scales. Strength magnitude is governed by ITZ stress concentrations, and the water-to-cement ratio is its dominant mixture design parameter.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An improved detailed chemical kinetic model for C3-C4 linear and iso-alcohols and their blends with gasoline at engine-relevant conditions

Propanol and butanol isomers have received significant research attention as promising fuel additives or neat biofuels. Robust chemical kinetic models are needed that can provide accurate and efficient predictions of combustion performance across a wide range of engine relevant conditions. Herein, this study seeks to improve the understanding of ignition and combustion behavior of pure C3-C4 linear and iso-alcohols, and their blends with gasoline at engine-relevant conditions. In this work, a kinetic model with improved thermochemistry and reaction kinetics was developed based on recent theoretical calculations of H-atom abstraction and peroxy radical reaction rates. Kinetic model validations are reported, and the current model reproduces the ignition delay times of the C3 and C4 alcohols well. Variations in reactivity over a wide range of temperatures and other operating conditions are also well predicted by the current model. Recent ignition delay time measurements from a rapid compression machine of neat iso-propanol and iso-butanol [Cheng et al., Proc. Combust Inst. (2020)] and blends with a research grade gasoline [Goldsborough et al., Proc. Combust Inst. (2020)] at elevated pressure (20–40 bar) and intermediate temperatures (780–950 K) were used to demonstrate the accuracy of the current kinetic model at conditions relevant to boosted spark-ignition engines. The effects of alcohol blending with gasoline on the autoignition behavior are discussed. The current model captures the suppression of reactivity in the low-temperature and negative-temperature-coefficient (NTC) region when either isopropanol and isobutanol are added to a research grade gasoline. Sensitivity and reaction flux analysis were performed to provide insights into the relevant fuel chemistry of the C3-C4 alcohols.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Robust Machine Learning Inference from X-ray Absorption Near Edge Spectra through Featurization

X-ray absorption spectroscopy (XAS) is a commonly employed technique for characterizing functional materials. In particular, X-ray absorption near edge spectra (XANES) encode local coordination and electronic information, and machine learning approaches to extract this information are of significant interest. To date, most ML approaches for XANES have primarily focused on using the raw spectral intensities as input, overlooking the potential benefits of incorporating spectral transformations and dimensionality reduction techniques into ML predictions. Here, in this work, we focused on systematically comparing the impact of different featurization methods on the performance of ML models for XAS analysis. We evaluated the classification and regression capabilities of these models on computed data sets and validated their performance on previously unseen experimental data sets. Our analysis revealed an intriguing discovery: the cumulative distribution function feature achieves both high prediction accuracy and exceptional transferability. This remarkably robust performance can be attributed to its tolerance to horizontal shifts in the spectra, which is crucial when validating models using experimental data. While this work exclusively focuses on XANES analysis, we anticipate that the methodology presented here will hold promise as a versatile asset to the broader spectroscopy community.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling and experimental validation of dynamical effects in Bragg coherent x-ray diffractive imaging of finite crystals

Bragg coherent diffractive imaging (BCDI) is a noninvasive microscopy technique that can visualize the shape and internal lattice deviations of crystals with nanoscale spatial resolution and picometer deformation sensitivity. Its strain imaging capability relies on Fourier transform–based iterative phase retrieval algorithms, which are mostly developed under the kinematical approximation. Such approximation prohibits the application of BCDI on larger crystals, which are commonly seen in most emerging functional materials. Understanding the dynamical effect in BCDI, as well as developing a validated method for modeling BCDI at the dynamical diffraction limit, is crucial for applying BCDI to hierarchical systems that contain micron-sized crystals and grains. Thus we report a comparative study on the impact of dynamical diffraction effects by comparing the reconstruction results from two measurements of the same crystal. Forward simulation is implemented to show subtle changes of interference fringes in the diffraction pattern due to the dynamical diffraction, and is compared directly with the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Six Machine-Learning Methods for Predicting Hospital-Stay Duration for Patients with Sepsis: A Comparative Study

Sepsis is a life-threatening medical condition that, if not treated promptly, can result in tissue damage, organ failure, and death. According to the Centers for Disease Control, about 270,000 individuals die of sepsis in the US each year. Further, sepsis expenditures accounted for 13% of total US hospital costs in 2013, totaling more than $24 billion. Our project objectives were to determine if Machine Learning algorithms could reliably predict hospital stay duration for patients with sepsis. The data set we used has been de-identified and is freely available through the BupaR package. The data includes 1050 cases, 15214 events, and 16 types of actions related to sepsis patient care. First, we used process mining to determine how long each patient was in the hospital. Using BupaR’s functions, we created several process model graphs. These process models depict the movement of patients at a hospital and provide duration data for each patent case. Second, we identified outlier data and created two dataset versions: one with and one without outliers. We then applied the following analysis methods: Linear Regression, Random Forest, K-Nearest Neighbors, Neural Networks, XGBoost, and lightGBM. We compared the model validations for the six machine learning models using the same data-splitting method. We found that the XGBoost model had the best prediction accuracy of 73.9 percent for cases with outliers, and 79 percent for cases without outliers. We also found that the lightGBM model had the lowest mean absolute error between prediction and actual duration in days with 3.66 days for the case with outliers, and 2.4 days for the case without outliers. These two models outperformed the other four models. This work will be enhanced in the future by exploring new prediction algorithms and comparing them with the results of this study.

Chen, Lingtao↗
DOE OSTI2021

TRANSIENT THERMAL MODELING OF THE HIGH BURNUP DEMONSTRATION RESEARCH PROJECT CASK USING STAR-CCM+ AND COBRA-SFS

The Department of Energy in collaboration with the Electric Power Research Institute is in the process of conducting the High Burnup Demonstration Project. Where the objective is to characterize the performance of high-burnup fuel in long term storage. As part of this demonstration, a TN-32B dry storage cask was instrumented and loaded with spent nuclear fuel at North Anna Nuclear Generating Station in November 2017. The project cask provides a unique opportunity to gain information on spent fuel and cask performance from an in-service operational system. The cask was instrumented with thermocouples inside of the fuel assemblies, then loaded and dried using normal procedures. After the drying process a thermal soak period where the cask was left indoors was used to obtain steady temperatures for model comparison along with surface temperatures. This paper details thermal modeling validation work that was done to model both the steady state and transient cases. Two modeling tools were used to predict temperatures in the cask. The general purpose CFD and heat transfer code STAR-CCM+ was used with both a detailed pin-by-pin model was used along with a more efficient k-effective simplification. The other code is COBRA-SFS, a purpose-built detailed thermal modeling tool developed and maintained at PNNL. Results from all the modeling tools were compared blind to the test data. Each model utilized general design information and compared reasonably well to the blind steady state data using convection and surface temperature boundary conditions. Post-test adjustments were later made to better reflect the “as built” conditions of the cask. Based on lessons learned from the steady state analysis the vacuum drying process was modeled in both codes. Utilizing the measured loading conditions the transient models were able to compare very well with the measured data. Overall the project showed an ability to model spent fuel storage conditions very well and future work is planned to generalize the methodology used for vacuum drying.

Thermal Analysis, Spent Fuel, Dry Storage↗
DOE OSTI2018

Research and Development in Fire Science

FM Global Technologies LLC and the Fire Science and Technology Department at Sandia National Laboratories have undertaken a Cooperative Research and Development Agreement (CRADA) to perform joint research and development in fire science. The objective of this work is to provide significant technical advances for the prevention and mitigation of high consequence fires. These advances will be accomplished through the acquisition of new, high-quality data for discovery of controlling mechanisms and model validation, formulation of new theories to describe fire behavior, and the development and validation of analytical and numerical fire models to predict fire hazard and mitigation system performance. These advances are expected to provide measurable improvements in fire safety by decreasing fire-related losses of life and property.

Childress, Amy↗
DOE OSTI2020

SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1985

Multiple-scale turbulence closure modeling of confined recirculating flows

A multiple-scale turbulence closure scheme is developed for the numerical predictions of confined recirculating flows. This model is based on the multiple-time-scale concepts of Hanjalic et al. (1980) and takes into account the non-equilibrium spectra energy transfer mechanism. Problems concerning new formulation of energy transfer rate equations and subsequent model coefficient redefinition and energy spectrum partition are discussed. Comparisons are made with several experiments of internal recirculating flows for the purpose of model validation. Numerical results using the present model show significant improvement of predictive capability over that obtained with the single-scale k-epsilon model and show promising potential for complex turbulent flow predictions.

Chen, C. P.↗
NASA NTRS1996

Utilization of STRAT Data

One of the goals of the STRAT mission was to improve our understanding of transport in the stratosphere. We have used our coupled 2-D model to analyse transport between the tropics and midlatitudes using aircraft measurements of (CO2) and (N2O) made during the SPADE and ASHOE/MAESA campaigns (Boering et al. 1994) for model validation. We have further used the model to estimate errors in the experimental determination of the age of stratospheric air that arise from nonlinear increases of real tracers such as (CO2) and (SF6). The interpretation of measurements made during STRAT is still in progress. Most of the work performed under this contract has been described in the second year progress report, submitted in April of 1996. In the following, the research is summarized and some additional work that has become relevant in the meantime is described. We have developed an interactive model of the dynamics, chemistry and radiation of the stratosphere with partial support from this contract. The dynamics module integrates the primitive equations on a sphere. Lower boundary zonal winds and eddy geopotential heights are specified from observations. Chemistry and tracer transport are done in two dimensions. The chemistry model is a family model. Long lived species are transported and short lived species are determined in intervals of 5 to 10 days by assuming photochemical steady state. Full diurnal integrations with the fast species are performed periodically and diurnal coefficients, derived from the explicit integration are used to determine the steady state solution. Heating rates in the stratosphere are calculated from model ozone and the model temperatures and circulation fields are used in the chemistry transport module.

Source record↗
NASA NTRS2012

Utilizing Chamber Data for Developing and Validating Climate Change Models

Controlled environment chambers (e.g. growth chambers, SPAR chambers, or open-top chambers) are useful for measuring plant ecosystem responses to climatic variables and CO2 that affect plant water relations. However, data from chambers was found to overestimate responses of C fluxes to CO2 enrichment. Chamber data may be confounded by numerous artifacts (e.g. sidelighting, edge effects, increased temperature and VPD, etc) and this limits what can be measured accurately. Chambers can be used to measure canopy level energy balance under controlled conditions and plant transpiration responses to CO2 concentration can be elucidated. However, these measurements cannot be used directly in model development or validation. The response of stomatal conductance to CO2 will be the same as in the field, but the measured response must be recalculated in such a manner to account for differences in aerodynamic conductance, temperature and VPD between the chamber and the field.

Monje, Oscar↗
NASA NTRS2016

Crash Testing and Simulation of a Cessna 172 Aircraft: Pitch Down Impact Onto Soft Soil

During the summer of 2015, NASA Langley Research Center conducted three full-scale crash tests of Cessna 172 (C-172) aircraft at the NASA Langley Landing and Impact Research (LandIR) Facility. The first test represented a flare-to-stall emergency or hard landing onto a rigid surface. The second test, which is the focus of this paper, represented a controlled-flight-into-terrain (CFIT) with a nose-down pitch attitude of the aircraft, which impacted onto soft soil. The third test, also conducted onto soil, represented a CFIT with a nose-up pitch attitude of the aircraft, which resulted in a tail strike condition. These three crash tests were performed for the purpose of evaluating the performance of Emergency Locator Transmitters (ELTs) and to generate impact test data for model validation. LS-DYNA finite element models were generated to simulate the three test conditions. This paper describes the model development and presents test-analysis comparisons of acceleration and velocity time-histories, as well as a comparison of the time sequence of events for Test 2 onto soft soil.

Fasanella, Edwin L.↗
NASA NTRS2019

Near Field Probe Measurements in the Plume of a NEXT Ion Thruster

Due to the extremely long lifetime and ground testing complications, such as facility backpressure effects, modeling is a necessary tool for validating mission lifetime requirements. Both NASA's Glenn Research Center and Jet Propulsion Laboratory have developed lifetime validation models for the NEXT ion thruster. The largest uncertainties in these models are due to unknown plasma properties, such as plasma potential, that occur very near to the grid. Previous studies have made measurements in the mid to far field. Here, we make very near field measurements of the plasma properties in the ion beam within 0.1 thruster radii of the grid using various probes. Emissive and triple Langmuir probes are swept through the plume to spatially resolve plasma potential, electron temperature and ion density very near to the grid. The goal is to provide refined inputs to the lifetime modeling efforts and increase the accuracy of the models.

Arthur, Neil↗
NASA NTRS2019

Near Field Probe Measurements in the Plume of a NEXT Ion Thruster

Due to the extremely long lifetime and ground testing complications, such as facility backpressure effects, modeling is a necessary tool for validating mission lifetime requirements. Both NASA's Glenn Research Center and Jet Propulsion Laboratory have developed lifetime validation models for the NEXT ion thruster. The largest uncertaintiesin these models are due to unknown plasma properties, such as fields plasma potential, that occur very near to the grid. Previous studies have made measurements in the mid to far field. Here, we make very near field measurements of the plasma properties in the ion beam within 0.1 thruster radii of the grid using various probes. Emissive and triple Lang-muir probes are swept through the plume to spatially resolve plasma potential, electron temperature and ion density very near to the grid. The goal is to provide refined inputs to the lifetime modeling efforts and increase the accuracy of the models.

Arthur, Neil A.↗
NASA NTRS2020

Space Launch System Mobile Launcher Modal Pretest Analysis

NASA is developing an expendable heavy lift launch vehicle capability, the Space Launch System, to support lunar and deep space exploration. To support this capability, an updated ground infrastructure is required including modifying an existing Mobile Launcher system. The Mobile Launcher is a very large heavy beam/truss steel structure designed to support the Space Launch System during its buildup and integration in the Vehicle Assembly Building, transportation from the Vehicle Assembly Building out to the launch pad, and provides the launch platform at the launch pad. The previous Saturn/Apollo and Space Shuttle programs had integrated vehicle ground vibration tests of their integrated launch vehicles performed with simulated free-free boundary conditions to experimentally anchor and validate structural and flight controls analysis models. For the Space Launch System program, the Mobile Launcher will be used as the modal test fixture for the ground vibration test of the first Space Launch System flight vehicle, Exploration Mission ? 1( now referred to as Artemis 1), programmatically referred to as the Integrated vehicle modal test. The Integrated vehicle modal test of the Exploration Mission - 1 integrated launch vehicle will have its core and second stages unfueled while mounted to the ML while inside the Vehicle Assembly Building, which is currently scheduled for the late spring or early summer of 2020. The Space Launch System program has implemented a building block approach for dynamic model validation. The modal test of the Mobile Launcher is an important part of this building block approach in supporting the integrated vehicle modal test since the Mobile Launcher will serve as a structurally dynamic test fixture whose modes will couple with the modes of the Exploration Mission ? 1 test vehicle. The Mobile Launcher modal test will further support understanding the structural dynamics of the Mobile Launcher and SLS during rollout to the launch pad, which will play a key role in better understanding and prediction of the rollout forces acting on the launch vehicle. The Mobile Launcher modal test is currently scheduled for the summer of 2019. Due to a very tight modal testing schedule, this Mobile Launcher modal pretest analysis has been performed to ensure there is a high likelihood of being able to successfully complete the modal test (i.e. identify the primary target modes) using the planned instrumentation, shakers, and excitation types. This paper will discuss this Mobile Launcher modal pretest analysis and the unique challenges faced due to the Mobile Launcher's size and weight, which are typically not faced when modal testing aerospace structures.

Akers, James C.↗
NASA NTRS2020

Space Launch System Mobile Launcher Modal Pretest Analysis

NASA is developing an expendable heavy lift launch vehicle capability, the Space Launch System, to support lunar and deep space exploration. To support this capability, an updated ground infrastructure is required including modifying an existing Mobile Launcher system. The Mobile Launcher is a very large heavy beam/truss steel structure designed to support the Space Launch System during its buildup and integration in the Vehicle Assembly Building, transportation from the Vehicle Assembly Building out to the launch pad, and provides the launch platform at the launch pad. The previous Saturn/Apollo and Space Shuttle programs had integrated vehicle ground vibration tests of their integrated launch vehicles performed with simulated free-free boundary conditions to experimentally anchor and validate structural and flight controls analysis models. For the Space Launch System program, the Mobile Launcher will be used as the modal test fixture for the ground vibration test of the first Space Launch System flight vehicle, Artemis 1, programmatically referred to as the integrated vehicle modal test. The integrated vehicle modal test of the Artemis 1 integrated launch vehicle will have its core and second stages unfueled while mounted to the Mobile Launcher while inside the Vehicle Assembly Building, which is currently scheduled for the summer of 2020. The Space Launch System program has implemented a building block approach for dynamic model validation. The modal test of the Mobile Launcher is an important part of this building block approach in supporting the integrated vehicle modal test since the Mobile Launcher will serve as a structurally dynamic test fixture whose modes will couple with the modes of the Artemis 1 integrated vehicle. The Mobile Launcher modal test will further support understanding the structural dynamics of the Mobile Launcher and Space Launch System during rollout to the launch pad, which will play a key role in better understanding and prediction of the rollout forces acting on the launch vehicle. The Mobile Launcher modal test is currently scheduled for the summer of 2019. Due to a very tight modal testing schedule, this independent Mobile Launcher modal pretest analysis has been performed to ensure there is a high likelihood of successfully completing the modal test (i.e. identify the primary target modes) using the planned instrumentation, shakers, and excitation types. This paper will discuss this Mobile Launcher modal pretest analysis for its three test configurations and the unique challenges faced due to the Mobile Launcher’s size and weight, which are typically not faced when modal testing aerospace structures.

Akers, James C.↗
NASA NTRSDate not supplied

A Summary of Recent SBIR and STTR Projects in Support of Cryogenic Fluid Management Modeling

Over the last five years, NASA has invested in development of sub-models to improve the current capabilities of Computational Fluid Dynamics (CFD) codes utilized for cryogenic fluid management (CFM) predictions. The goal is for the submodels to be modular so that they can easily be implemented into NASA’s CFD codes such as ANSYS Fluent, Siemens STAR-CCM+, and Streamline Numerics Loci-Stream. These technologies are being developed through Small Business Innovative Research (SBIR) and Small Business Technology Transfer (STTR) contracts under the CFM subtopic solicitation and funded by the CFM Portfolio Project. All contracts presented include cryogenic experiments to enable model validation. A sub-grid boiling model has been developed by Combustion Research and Flow Technology Inc. and Massachusetts Institute of Technology for cryogenic line chilldown predictions and has completed Phase III. A spray chill-and-fill model for cryogenic tankage is being developed by Combustion Research and Flow Technology Inc. and University of Connecticut and is currently in Phase II. Last, film condensation modeling to support cryogenic liquefaction was progressed through a Phase I contract with Combustion Research and Flow Technology Inc. and University of Connecticut. A summary of accomplishments for each contract is presented.

cryogenics↗
DOE OSTI2018

Modulating factors of hydrologic exchanges in a large-scale river reach: Insights from three-dimensional computational fluid dynamics simulations

Hyporheic exchange is a critical mechanism shaping hydrological and biogeochemical processes along a river corridor. Recent studies on quantifying the hyporheic exchange were mostly limited to local scales due to field inaccessibility, computational demand, and complexity of geomorphology and subsurface geology. Surface flow conditions and subsurface physical properties are well known factors on modulating the hyporheic exchange, but quantitative understanding of their impacts on the strength and direction of hyporheic exchanges at reach scales is absent. In this study, a high resolution computational fluid dynamics (CFD) model that couples surface and subsurface flow and transport is employed to simulate hyporheic exchanges in a 7-km long reach along the main-stem of the Columbia River. Assuming that the hyporheic exchange does not affect surface water flow conditions due to its negligible magnitude compared to the volume and velocity of river water, we developed a one-way coupled surface and subsurface water flow model using the commercial CFD software STAR-CCM+. The model integrates the Reynolds-averaged Navier-Stokes (RANS) equation solver with a realizable k-e two-layer turbulence model, a two-layer all y^+ wall treatment, and the volume of fluid (VOF) method, and is used to simulate hyporheic exchanges by tracking the free water-air interface as well as flow in the river and the subsurface porous media. The model is validated against measurements from acoustic Doppler current profiler (ADCP) in the stream water and hyporheic fluxes derived from a set of temperature profilers installed across the riverbed. The validated model is then employed to systematically investigate how hyporheic exchanges are influenced by surface water fluid dynamics strongly regulated by upstream dam operations, as well as subsurface structures (e.g. thickness of riverbed and subsurface formation layers) and hydrogeological properties (e.g. permeability). The results suggest that the thickness of riverbed alluvium layer is the dominant factor for reach-scale hyporheic exchanges, followed by the alluvium permeability, the depth of the underlying impermeable layer, and the assumption of hydrostatic pressure.

Bao, Jie↗