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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 1,315 records · Page 73

Relationship of roof falls in underground coal mines to fractures mapped on ERTS-1 imagery

ERTS imagery is of unique value for mapping of certain fractures that are not identifiable on aircraft imagery. Because color infrared and ERTS imagery complement each other both sources of data were used to map fractures in western Indiana and eastern Illinois. In the Kings Station Mine, Gibson County, Indiana, most roof falls reported had occurred in areas where mapped fractures were closely spaced and intersecting. Using this information as a basis for extrapolation, roof fall hazard maps were prepared for other mine sites. Various coal resources programs related to energy and environment also were conducted.

Wier, C. E.↗

Solar energy system economic evaluation: Fern Tunkhannock, Tunkhannock, Pennsylvania

The economic performance of an Operational Test Site (OTS) is described. The long term economic performance of the system at its installation site and extrapolation to four additional selected locations to demonstrate the viability of the design over a broad range of environmental and economic conditions is reported. Topics discussed are: system description, study approach, economic analysis and system optimization, and technical and economical results of analysis. Data for the economic analysis are generated through evaluation of the OTS. The simulation is based on the technical results of the seasonal report simulation. In addition localized and standard economic parameters are used for economic analysis.

Source record↗

Horizon Missions Technology Study

The purpose of the HMT Study was to develop and demonstrate a systematic methodology for identifying and evaluating innovative technology concepts offering revolutionary, breadkthrough-type capabilities for advanced space missions and for assessing their potential mission impact. The methodology is based on identifying the new functional, operational and technology capabilities needed by hypothetical 'Horizon' space missions that have performance requirements that cannot be met, even by extrapolating known space technologies. Nineteen Horizon Missions were selected to represent a collective vision of advanced space missions of the mid-21st century. The missions typically would occur beyond the lifetime of current or planned space assets. The HM methodology and supporting data base may be used for advanced technology planning, advanced mission planning and multidisciplinary studies and analyses.

Anderson, John L.↗

Characterization of Laptop Fires in Spacecraft

An accidental fire involving the Lithium-Ion (Li-ion) battery in a laptop computer is one of the most likely fire scenarios on-board a spacecraft. These fires can occur from a defect in the battery that worsens with time, over-charging the battery and leading to failure or accidental damage caused by thermal runaway. While this is a relatively likely fire scenario, very little is known about the how a laptop computer fire would impact a sealed spacecraft. The heat release would likely cause a pressure rise, possibly exceeding the pressure limit of the vehicle and causing a relief valve to open. The combustion products from the fire could pose a short-term and long-term health hazard to the crew and the fire itself could cause injury to the crew and damage to the spacecraft. Despite the hazard posed by a laptop fire, there is little quantitative data on the fire size, heat release and toxic product formation. This paper presents the results of initial attempts to quantify the fire resulting from a failed laptop fire tested at the NASA White Sands Test Facility (WSTF). The data from the testing is useful to attempt to determine the fire size and characteristics such as maximum heat release rate, total heat release, maximum temperatures and fire duration are determined. Using existing models and correlations for fires, the measured fire characteristics are extrapolated to laptop fires on a vehicle the approximate size of the Orion spacecraft.

Padilla, Rosa E.↗

Towards a program of record of inland water quality: Exploiting present and heritage multispectral sensors for maximum information extraction

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This research exploits recent advancements in bio-optical modeling, cloud computing, and machine learning to enhance our capacity to leverage present and heritage satellite data. Recent research suggests that sensors with low spectral resolution, such as Sentinel 2 and Landsat missions, contain enough hidden spectral variation which can be exploited using data-driven approaches. The availability of three decades of archival imagery will open doors to discover global trends of eutrophication and increased cyanobacteria dominance and provide valuable insight to the development of predictive methodologies. Preliminary efforts in synthetic emulation of global natural inland waters will be discussed and contextualized against satellite radiometric measurement uncertainty, satellite data product uncertainties and causal signal ambiguity over the visible wavelength range, supported by high quality field and image data for selected inland aquatic sites. Insights on water quality estimation via data-driven machine learning models versus matrix inversions will be discussed, and how we can exploit spectral-spatial relationships in high spatial resolution data. A cross-sensor synergistic approach with detailed uncertainty analysis based on optical water types, will allow for unprecedented global snapshots of fine scale ecological dynamics of inland waters.

Inland↗

Computational Assessment of the Opening Mode Facesheet-to-Core Fracture Toughness of a Thin-Gage Facesheet Sandwich Structure

The single-cantilevered beam test (SCB) is currently being considered for standardization for measuring the opening mode fracture toughness of sandwich structures subjected to facesheet-to-core separation. At present, the Area method is considered the benchmark method for determining energy required to propagate the crack. This method is problematic since it requires periodic unloading and cannot be evaluated instantaneously. Therefore, a method is needed to accurately and instantaneously calculate opening mode fracture toughness. In previous work, SCB tests with thin-gauge facesheets were performed to compare the J-integral approach to data reduction methods including the Modified Beam Theory (MBT) and the Area method. Large deviations (over 10%) in the calculated fracture toughness were observed between the J-integral and MBT for large displacements. In this study, a simulated SCB experiment using a virtual crackclosure technique was performed to assess the previously observed discrepancies. The predicted load displacement response, the predicted angle at the load application point, and the predicted crack growth results are in good agreement (within 5%) with the corresponding experimental data. Using the predicted load and angles, the predicted J-integral is in good agreement (within 10%) with the experimentally obtained solution. Using the MBT approach, the previously observed deviations in the fracture toughness were determined to be associated with the empirical extrapolation procedure to estimate the crack-root rotation correction from nonlinear compliance curves. The nonlinear compliance is determined to be associated with large displacement effects observed within the predicted and experimental results.

Sandwich Composite↗

Experimental Studies and Energy Modeling for Evaluating Performance of Various Deep Wall Retrofits

The Pacific Northwest National Laboratory, Oak Ridge National Laboratory, and the University of Minnesota conducted a three-year, multipart study on residential retrofit wall assemblies. The project, which was funded by the U.S. Department of Energy’s Building Technology Office, aimed to compare a range of residential wall retrofit systems that prioritized affordability, durability, and energy savings potential. The research team identified, constructed, tested, simulated, and analyzed the feasibility and economics of 16 wall retrofit assemblies (14 test configurations and two baseline configurations) that can be applied to the exterior side of existing walls (either with or without the existing cladding). The 16 wall assemblies were installed in an in-situ laboratory environment, to evaluate the ease of construction and study the thermal and hygrothermal performance of the walls. This paper presents the methodology used to evaluate the thermal performance of the walls and discusses the energy modeling results of the study. The results from the experiments were used to calibrate a THERM model of each wall assembly, which was then applied to a whole building using the EnergyPlus 8.6 simulation engine. A residential prototype building was used to extrapolate whole-building energy savings in each U.S. climate zone. To capture the conditions of the largest number of homes in the United States, the most frequent building characteristics (e.g., attic insulation level, window specifications, foundation insulation, etc.) were extracted from ResStock data and applied to the prototype model. Results from the energy modeling showed that the climate zones with the highest potential for retrofit savings are those which are heating-dominated (i.e., Cold and Very Cold climate designations). In these climate zones, heating and cooling energy savings due to the wall retrofits alone ranged from 21.5% to 38.2%.

Nagda, Harshil↗

Calibration of CDM-Based Creep Constitutive Model Using Accelerated Creep Test (ACT) Data

In conventional creep testing (CCT) a specimen is subject to constant load and temperature for a long-duration until creep rupture occurs. Conventional testing can be costly when considering the number of experiments needed to characterize the creep response of a material over a range of stress and temperature. To predict long-term creep-rupture properties, the time-temperature-stress superposition principle (TTSSP) approach has been employed where stress and/or temperature is applied at an elevated level; the result of which are extrapolated down to low stress and/or temperature conditions. These methods have been successful in predicting minimum-creep-strain-rate (MCSR) and stress-rupture (SR) but suffer from an inability to predict the creep deformation curve or account for changes in deformation mechanisms or aging that occurs at long-duration. An accelerated technique, termed the Stepped isostress method (SSM) allows the accelerated testing of materials to determine their creep deformation response. Unlike TTSSP tests, the SSM test employs a single specimen where the stress is periodically step increased until rupture. The SSM creep deformation curve is processed (time and strain shifted) to produce an accelerated creep deformation curve that represent the creep deformation curve at the initial stress level in SSM. A processing procedure for metals has yet to be developed. The research objective of this study is to develop a processing procedure for SSM test data using a creep-damage constitutive model. Triplicate SSM tests were conducted on Ni-based superalloy Inconel 718 at 650°C with stress being periodically increased until rupture. Triplicate CCT tests were conducted at the initial stress level of the SSM tests. The Sine-hyperbolic (Sinh) creep-damage model was employed in this study. The Sinh creep-damage constitutive model is based on coupled creep strain rate and damage evolution equations; where both rates are dependent on the current state of damage. Calibration is two-step: analytical and numerical optimization. Each stepped creep deformation curve is tackled quasi-analytically to determine MCSR and SR related material constants and accumulated damage. The damage accumulated at the end of each step was then passed onto subsequent steps to calibrate the MCSR, rupture prediction, and damage evolution. Numerical optimization was applied to optimize model constants involved in the creep strain constitutive equations in order to generate best-fitted Sinh creep deformation curves. The Sinh model predictions were compared to the SSM and CCT data. The Sinh model satisfactorily predicts the SSM data and thus the calibrated material constants provides a good estimate of rupture found in the CCT data. Calibration using SSM data reduces the number of tests needed to calibrate a model; significantly reducing costs. A single SSM test replaces numerous creep tests at different stresses.

36 MATERIALS SCIENCE↗

Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states

We report molecular-orbital-based machine learning (MOB-ML) provides a general framework for the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. The application of Nesbet’s theorem makes it possible to recast a typical extrapolation task, training on correlation energies for small molecules and predicting correlation energies for large molecules, into an interpolation task based on the properties of orbital pairs. We demonstrate the importance of preserving physical constraints, including invariance conditions and size consistency, when generating the input for the machine learning model. Numerical improvements are demonstrated for different datasets covering total and relative energies for thermally accessible organic and transition-metal containing molecules, non-covalent interactions, and transition-state energies. MOB-ML requires training data from only 1% of the QM7b-T dataset (i.e., only 70 organic molecules with seven and fewer heavy atoms) to predict the total energy of the remaining 99% of this dataset with sub-kcal/mol accuracy. This MOB-ML model is significantly more accurate than other methods when transferred to a dataset comprising of 13 heavy atom molecules, exhibiting no loss of accuracy on a size intensive (i.e., per-electron) basis. It is shown that MOB-ML also works well for extrapolating to transition-state structures, predicting the barrier region for malonaldehyde intramolecular proton-transfer to within 0.35 kcal/mol when only trained on reactant/product-like structures. Finally, the use of the Gaussian process variance enables an active learning strategy for extending the MOB-ML model to new regions of chemical space with minimal effort. We demonstrate this active learning strategy by extending a QM7b-T model to describe non-covalent interactions in the protein backbone–backbone interaction dataset to an accuracy of 0.28 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computer mapping of turbidity and circulation patterns in Saginaw Bay, Michigan from LANDSAT data

The author has identified the following significant results. LANDSAT was used as a basis for producing geometrically-corrected, color-coded imagery of turbidity and circulation patterns in Saginaw Bay, Michigan (Lake Huron). This imagery shows nine discrete categories of turbidity, as indicated by nine Secchi depths between 0.3 and 3.3 meters. The categorized imagery provided an economical basis for extrapolating water quality parameters from point samples to unsample areas. LANDSAT furnished a synoptic view of water mass boundaries that no amount of ground sampling or monitoring could provide.

Rogers, R. H.↗

Lessons Learned in Employing Data Analytics to Predict Oxidation Kinetics and Spallation Behavior of High-Temperature NiCr-Based Alloys

Machine learning (ML) can offer many advantages in predicting material properties over traditional materials development methods based solely on limited experimental investigations or physical-based simulations with the capability to reduce development cost, risk, and time. However, so far, limited efforts have been made to predict alloy oxidation kinetics and spallation behavior via ML due to the lack of consistently measured and sufficient experimental data and the inherent complexity in oxidation behavior of multicomponent high-temperature alloys. A previous study reported the ability of ML to predict oxidation kinetics of NiCr-based alloys as a function of alloy composition and operating conditions. Here, the performance of a ML model in predicting rate constants and spallation probability was evaluated in light of the roles of the data distribution of the experimental dataset (data analytics), the alloy composition, the exposure environment and the chosen oxidation approach to extracting kinetic values from the measured mass changes (but using either a simple parabolic law or a statistical cyclic oxidation model). Potential strategies to improve the predictions and enhance the extrapolative capability of the previously trained model will be discussed.

36 MATERIALS SCIENCE↗

Evolution of recurrent solar wind structures between 14 AU and the termination shock

The solar wind conditions observed from Voyager 2 at approximately 14 AU are extrapolated to the region of the outer heliosphere bounded by the termination shock, using an MHD simulation model. Results from two simulation studies are presented for two sets of nearly recurrent solar wind interaction regions, with initial conditions generated from plasma and magnetic field data observed on March 1984 at 13.8 AU, and on November 1984 at 15.4, respectively. Each simulation describes an idealized recurrent solar wind structure in the supersonic region of the outer heliosphere out to the termination shock far beyond the present reaches of the Pioneer and Voyager spacecraft. It is shown that a collision between the forward shock and the reverse shock occurs approximately every 40 AU. When a forward shock interacts with the termination shock, the latter is weakened and moves outward; the termination shock is strengthened and moves inward when a reverse shock interacts with it.

Whang, Y. C.↗

Atmospheric sulfur hexafluoride - Sources, sinks and greenhouse warming

An estimate is obtained of worldwide production of SF6, from which a global emission rate is derived and extrapolated for the next 20 years. The atmospheric lifetime of SF6 is then estimated based on a known mechanism (e.g., photolysis and atmospheric oxidation) and/or on the mass balance method. Finally, the radiative forcing of SF6 is calculated based on recent laboratory IR absorption data, and the expected warming over the time period 1950-2010 is computed for several emission scenarios. Calculations showed that SF6 is 3 times more effective as a greenhouse gas compared to CFC 11 on a per-molecule basis. However, based on projected emission scenarios, the expected warming from SF6 through 2010 is small (0.004 C), compared to the warming from CO2 and other trace gases (0.8 C).

Ko, Malcolm K. W.↗

Galaxy Cluster Gas Mass Fractions From Sunyaev-Zel'dovich Effect Measurement: Constraints on Omega_M

Using sensitive centimeter-wave receivers mounted on the Owens Valley Radio Observatory and Berkeley-Illinois-Maryland-Association millimeter arrays, we have obtained interferometric measurements of the Sunyaev-Zei'dovich (SZ) effect toward massive galaxy clusters. We use the SZ data to determine the pressure distribution of the cluster gas and, in combination with published X-ray temperatures, to infer the gas mass and total gravitational mass of 18 clusters. The gas mass fraction, f~g, is calculated for each cluster, and is extrapolated to the fiducial radius r_{500} using the results of numerical simulations. The mean f_g within r_{500} is 0.081 + 0.009 - 0.011/(h_{100} (statistical uncertainty at 68% confidence level, assuming OmegaM=0.3, OmegaL=0.7). We discuss possible sources of systematic errors in the mean f 9 measurement. We derive an upper limit for OmegaM from this sample under the assumption that the mass composition of clusters within r_{500} reflects the universal mass composition: Omega_M h <Omega_B/f_g.The gas mass f on cosmology through the angular diameter distance and the r_{500} correction factors. For a flat universe (Omegal, = 1 - OmegaM) and h=0.7, we find the measured gas mass fractions are consistent with OmegaM less than 0.40, at 68% confidence. Including estimates of the baryons contained in galaxies and the baryons which failed to become bound during the cluster formation process, we find OmegaM\approximately 0.25.

Grego, Laura↗

Galaxy Cluster Gas Mass Fractions From Sunyaev-Zeldovich Effect Measurements: Constraints on Omega(M)

Using sensitive centimeter-wave receivers mounted on the Owens Valley Radio Observatory and Berkeley-Illinois-Maryland-Association millimeter arrays, we have obtained interferometric measurements of the Sunyaev-Zeldovich(SZ) effect toward massive galaxy clusters. We use the SZ data to determine the pressure distribution of the cluster gas and, in combination with published X-ray temperatures, to infer the gas mass and total gravitational mass of 18 clusters. The gas mass fraction, f(g), is calculated for each cluster and is extrapolated to the fiducial radius r(500) using the results of numerical simulations. The mean f(g) within r(500) is 0.081(+ 0.009 / - 0.011) per h(100) (statistical uncertainty at 68% confidence level, assuming Omega(M) = 0.3, Omega(Lambda) = 0.7). We discuss possible sources of systematic errors in the mean f(sub g) measurement. We derive an upper limit for Omega(M) from this sample under the assumption that the mass composition of clusters within r(500) reflects the universal mass composition: Omega(M)h is less than or equal to Omega(B)/f(g). The gas mass fractions depend on cosmology through the angular diameter distance and the r(500) correction factors. For a flat universe (Omega(Lambda) is identical with 1 - Omega(M)) and h = 0.7, we find the measured gas mass fractions are consistent with Omega(M) is less than 0.40, at 68% confidence. Including estimates of the baryons contained in galaxies and the baryons which failed to become bound during the cluster formation process, we find Omega(M) is approximately equal to 0.25.

Grego, Laura↗

Nuclear Safeguards: Feature Extraction for Machine Learning Enrichment Analysis of UF 6 Cylinders

With the increasing international interest in using nuclear material as sources of energy, comes the growing concern that we may see an increase in proliferation threats. Uranium hexafluoride (UF 6 ) is used in the nuclear fuel cycle for uranium enrichment. Inspectors from the International Atomic Energy Agency (IAEA) monitor the enrichment levels of UF 6 stored in transportation cylinders, to ensure the enrichments match that of a facility operator’s declarations. However, only a characteristic subset of UF 6 cylinders can be measured by inspectors from the IAEA during these inspections. In turn, the inspector may not identify a cylinder whose enrichment levels do not match the facility declarations. Therefore, our team attempts to develop a machine learning network that could determine the enrichment percentage of cylinders as they enter and exit facilities. The machine learning model must be robust against spectral variations due to factors that are internal and external to the UF 6 cylinder. Such factors include but are not limited to the speed and distance of the moving vehicle, cylinder type, cylinder orientation, and fill level. Many features in the spectral continuum can be used to identify and correct for some of these variations. As a consequence, the model must extract numerous features in the continuum. We investigate new approaches in continuum subtraction to verify enrichment percentage: interpolation and extrapolation of lines at the notable characteristic spectral peaks. It was determined that there was no clear answer on which method proved superior, therefore the decision was made to implement both new methods into the current codebase. We currently rely on synthetic training and testing data to analyze the results and fine tune our models but hope to test the system on measured data soon.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Comparison of single crack propagation in lunar analogue glass and the failure strength of rocks

New data of crack propagation in lunar analogue glass provides important input for the construction of deformation maps (maps which delineate the rates and principal means of material deformation under various environmental conditions) applicable to the lunar crust. Comparison of single crack propagation data obtained on flat plates of glass and failure strength data obtained on fine grained rock samples show that single crack propagation velocities are directly related to the failure strength of rocks. The chemical reaction between water and silicon-oxygen bonds at the crack tip seems to be of first order. This greatly simplifies extrapolation to low partial pressures of H2O

Soga, N.↗

Non-urban mobile radio market demand forecast

A national nonmetropolitan land mobile traffic model for 1990-2000 addresses user classes, density classes, traffic mix statistics, distance distribution, geographic distribution, price elasticity, and service quality elasticity. Traffic demands for business, special industrial, and police were determined on the basis of surveys in 73 randomly selected nonurban counties. The selected services represent 69% of total demand. The results were extrapolated to all services in the non-SMSA areas of the contiguous United States. Radiotelephone services were considered separately. Total non-SMSA mobile radio demand (one way) estimates are given. General functional requirements include: hand portability, privacy, reduction of blind spots, two way data transmission, position location, slow scan imagery.

Castruccio, P. A.↗