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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Shock Radiation Tests for Saturn and Uranus Entry Probes

This paper describes a test series in the Electric Arc Shock Tube at NASA Ames Research Center with the objective of quantifying shock-layer radiative heating magnitudes for future probe entries into Saturn and Uranus atmospheres. Normal shock waves are measured in Hydrogen-Helium mixtures (89:11 by volume) at freestream pressures between 13-66 Pa (0.1-0.5 Torr) and velocities from 20-30 kms. No shock layer radiation is detected within measurement limits below 25 kms, a finding consistent with predictions for Uranus entries. Between 25-30 kms, radiance is quantified from the Vacuum Ultraviolet through Near Infrared, with focus on the Lyman-a and Balmer series lines of Hydrogen. Shock profiles are analyzed for electron number density and electronic state distribution. The shocks do not equilibrate over several cm, and in many cases the state distributions are non-Boltzmann. Radiation data are compared to simulations of Decadal Survey entries for Saturn and shown to be as much as 8x lower than predicted with the Boltzmann radiation model. Radiance is observed in front of the shock layer, the characteristics of which match the expected diffusion length.

Hydrogen↗
DOE OSTI2021

A New Approach to Predict Hydrogeological Parameters Using Shear Waves from the Multichannel Analysis of Surface Waves Method

For near-surface contaminant characterization, the accurate prediction of hydrogeological parameters in anisotropic and heterogeneous environments has been a challenge since the last decades. However, recent advances in near-surface geophysics have facilitated the use of geophysical data for hydrogeological characterization in the last few years. A pseudo 3-D high resolution P-wave shallow seismic reflection survey was performed at the P Reactor Area, Savannah River Site, South Carolina in order to delineate and predict migration pathways of a large contaminant plume including trichloroethylene. This contaminant plume originates from the northwest section of the reactor facility that is located within the Upper Atlantic Coastal Plain. The data were collected with 40 Hz geophones, an accelerated weight-drop as seismic source and 1 m receiver spacing with near- and far-offsets of 0.5 and 119.5 m, respectively. In such areas with near-surface contaminants, a detailed subsurface characterization of the vadose zone hydraulic parameters is very important. Indeed, an inexpensive method of deriving such parameters by the use of seismic reflection surveys is beneficial, and our approach uses the relationship between seismic velocity and hydrogeological parameters together with empirical observations relating porosity to permeability and hydraulic conductivity. Shear wave velocity ( V s ) profiles were estimated from surface wave dispersion analysis of the seismic reflection data and were subsequently used to derive hydraulic parameters such as porosity, permeability, and hydraulic conductivity. Additional geophysical data including core samples, vertical seismic profiling, surface electrical resistivity tomography, natural gamma and electrical resistivity logs allowed for a robust assessment of the validity and geological significance of the estimated V s and hydrogeological models. The results demonstrate the usefulness of this approach for the upper 15 m of shallow unconsolidated sediments even though the survey design parameters were not optimal for surface wave analysis due to the higher than desired frequency geophones.

Engineering↗
NASA NTRS1998

Global tropospheric ozone investigations

Ozone (O3) is one of the most important trace gases in the troposphere, and it is responsible for influencing many critical chemical and radiative processes. Ozone contributes to the formation of the hydroxyl radical (OH), which is central to most chemical reactions in the lower atmosphere, and it absorbs UV, visible, and infrared radiation which affects the energy budget and atmospheric temperatures. In addition, O3 can be used as a tracer of atmospheric pollution and stratosphere troposphere exchange. At elevated concentrations, O3 can also produce detrimental biological and human health effects. The US National Research Council (NRC) Board on Sustainable Development reviewed the US Global Change Research Program (USGCRP) [NRC, 1995], and it identified tropospheric chemistry as one of the high priority areas for the USGCRP in the next decade. The NRC identified the following specific challenges in tropospheric chemistry. Although we understand the reason for the high levels of 03 over several regions of the world, we need to better establish the distribution of O3 in the troposphere in order to document and understand the changes in the abundance of global tropospheric O3. This information is needed to quantify the contribution of O3 to the Earth' s radiative balance and to understand potential impacts on the health of the biosphere. Having recognized the importance of particles in the chemistry of the stratosphere, we must determine how aerosols and clouds affect the chemical processes in the troposphere. This understanding is essential to predict the chemical composition of the atmosphere and to assess the resulting forcing effects in the climate system. We must determine if the self-cleansing chemistry of the atmosphere is changing as a result of human activities. This information is required to predict the rate at which pollutants are removed from the atmosphere. Over nearly two decades, airborne Differential Absorption Lidar (DIAL) systems have been used in over fifteen major field experiments conducted all over the world to address important atmospheric processes affecting the amount and distribution of 03 and aerosols across the troposphere. This paper discusses some of these wide-ranging field experiments and their results and presents a direction for future global studies of O3 and aerosols from space.

Browell, Edward V.↗
NASA NTRS1991

Turbulent separated flow past a backward-facing step: A critical evaluation of two-equation turbulence models

The ability of two-equation models to accurately predict separated flows is analyzed from a combined theoretical and computational standpoint. Turbulent flow past a backward facing step is chosen as a test case in an effort to resolve the variety of conflicting results that were published during the past decade concerning the performance of two-equation models. It is found that the errors in the reported predictions of the k-epsilon model have two major origins: (1) numerical problems arising from inadequate resolution, and (2) inaccurate predictions for normal Reynolds stress differences arising from the use of an isotropic eddy viscosity. Inadequacies in near wall modelling play a substantially smaller role. Detailed calculations are presented which strongly indicate the standard k-epsilon model - when modified with an independently calibrated anisotropic eddy viscosity - can yield surprisingly good predictions for the backstep problem.

Thangam, S.↗
NASA NTRS1992

Turbulent flow past a backward-facing step - A critical evaluation of two-equation models

The ability of two-equation models to accurately predict separated flows is analyzed from a combined theoretical and computational standpoint. Turbulent flow past a backward facing step is chosen as a test case in an effort to resolve the variety of conflicting results that were published during the past decade concerning the performance of two-equation models. It is found that the errors in the reported predictions of the k-epsilon model have two major origins: (1) numerical problems arising from inadequate resolution, and (2) inaccurate predictions for normal Reynolds stress differences arising from the use of an isotropic eddy viscosity. Inadequacies in near wall modelling play a substantially smaller role. Detailed calculations are presented which strongly indicate the standard k-epsilon model - when modified with an independently calibrated anisotropic eddy viscosity - can yield surprisingly good predictions for the backstep problem.

Thangam, S.↗
NASA NTRS2004

Radicals and Reservoirs in the GMI Chemistry and Transport Model: Comparison to Measurements

The most important use of atmospheric chemistry and transport models is to predict the future composition of the atmosphere. The amounts of gases like chlorofluorcarbons, methyl bromide, nitrous oxide and methane are changing and the stratospheric ozone layer will change because these gases are changing. Methyl bromide, nitrous oxide and methane all have natural sources, and also change because of human activity. Chlorofluorcarbons are man-made gases; these are known to decrease stratospheric ozone and future production is banned. They are long-lived gases, and many decades will pass before they are insignificant in the atmosphere. The models are used to predict changes in ozone and other gases; this is a straightforward application. The models must be also tested using observations for the present day atmosphere. This is a challenging task, because the model contains more than 50 species and more than 150 chemical reactions. Data from satellites, ground stations, aircraft and balloons are used to evaluate the model. Different models that are used in international assessments produce different results; in the most recent assessment some predict that ozone will return to 1980 levels by 2025 and others predict that this will not happen until 2050. Since all the parts of the models are conceptually the same, there must be differences in implementation that produce these differences, This work takes a single model, two different sets of winds and temperatures, and repeats the same prediction for the future. Here we compare the results for these two simulations with many observations. The purpose is to identify differences in the model results for the present atmosphere that will lead to different predictions. This sort of controlled comparison will reduce uncertainty in the predictions for stratospheric ozone.

Douglas, Anne R.↗
DOE OSTI2022

A guideline to document occupant behavior models for advanced building controls

The availability of computational power, and a wealth of data from sensors have boosted the development of model-based predictive control for smart and effective control of advanced buildings in the last decade. More recently occupant-behavior models have been developed for including people in the building control loops. However, while important objectives of scientific research are reproducibility and replicability of results, not all information is available from published documents. Therefore, the aim of this paper is to propose a guideline for a thorough and standardized occupant-behavior model documentation. For that purpose, the literature screening for the existing occupant behavior models in building control was conducted, and the occupant behavior modeling processes were studied to extract practices and gaps for each of the following phases: problem statement, data collection, and preprocessing, model development, model evaluation, and model implementation. Here, the literature screening pointed out that the current state-of-the-art on model documentation shows little unification, which poses a particular burden for the model application and replication in field studies. In addition to the standardized model documentation, this work presented a model-evaluation schema that enabled benchmarking of different models in field settings as well as the recommendations on how OB models are integrated with the building system.

Building control↗
NASA NTRS2010

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Koster, Randal↗
DOE OSTI2022

A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

Real-Time UAV Trajectory Prediction for Safety Monitoring in Low-Altitude Airspace

The rising number of small unmanned aerial vehicles (UAVs) expected in the next decade will enable a new series of commercial, service, and military operations in low altitude airspace as well as above densely populated areas. These operations may include on-demand delivery, medical transportation services, law enforcement operations, traffic surveillance and many more. Such unprecedented scenarios create the need for robust, efficient ways to monitor the UAV state in time to guarantee safety and mitigate contingencies throughout the operations. This work proposes a generalized monitoring and prediction methodology that utilizes realtime measurements of an autonomous UAV following a series of way-points. Two different methods, based on sinusoidal acceleration profiles and high-order splines, are utilized to generate the predicted path. The monitoring approach includes dynamic trajectory re-planning in the event of unexpected detour or hovering of the UAV during flight. It can be further extended to different vehicle types, to quantify uncertainty affecting the state variables, e.g., aerodynamic and other environmental effects, and can also be implemented to prognosticate safety-critical metrics which depend on the estimated flight path and required thrust. The proposed framework is implemented on a simplified, scalable UAV modeling and control system traversing 3D trajectories. Results presented include examples of real-time predictions of the UAV trajectories during flight and a critical analysis of the proposed scenarios under uncertainty constraints.

UAV trajectory prognosis↗
NASA NTRSDate not supplied

High Temperature Material Property Data and Challenges to Thermal Process Model Predictions and In-Situ/Ex-Situ Measurements for Metallic Additive Manufacturing

Understanding and predicting performance properties of parts produced by metallic additive manufacturing has improved significantly over the past decade; however, difficult to measure material properties and process outcomes continue to be challenges. The qualification or certification of aerospace parts require extensive measures to quantify variable part properties in order to buy down the risk of component failure. The variability, inherent to the additive manufacturing, process adds unwanted uncertainty in the production of load critical structural components. Process modeling has proven valuable in providing predictions and context for understanding outcomes of the additive manufacturing process; however, these physically informed process models require material properties at temperatures that are difficult to measure and rarely available. Further, calibrating or validating such models is difficult because the process itself is challenging to measure. This talk will explore some of the challenges resulting from difficult to acquire input data by relating thermal process model predictions to in-situ and ex-situ optical microscopy measurements.

Process Model↗
NASA NTRS1997

Comparisons of Solar Wind Coupling Parameters with Auroral Energy Deposition Rates

Measurement of the global rate of energy deposition in the ionosphere via auroral particle precipitation is one of the primary goals of the Polar UVI program and is an important component of the ISTP program. The instantaneous rate of energy deposition for the entire month of January 1997 has been calculated by applying models to the UVI images and is presented by Fillingim et al. In this session. A number of parameters that predict the rate of coupling of solar wind energy into the magnetosphere have been proposed in the last few decades. Some of these parameters, such as the epsilon parameter of Perrault and Akasofu, depend on the instantaneous values in the solar wind. Other parameters depend on the integrated values of solar wind parameters, especially IMF Bz, e.g. applied flux which predicts the net transfer of magnetic flux to the tail. While these parameters have often been used successfully with substorm studies, their validity in terms of global energy input has not yet been ascertained, largely because data such as that supplied by the ISTP program was lacking. We have calculated these and other energy coupling parameters for January 1997 using solar wind data provided by WIND and other solar wind monitors. The rates of energy input predicted by these parameters are compared to those measured through UVI data and correlations are sought. Whether these parameters are better at providing an instantaneous rate of energy input or an average input over some time period is addressed. We also study if either type of parameter may provide better correlations if a time delay is introduced; if so, this time delay may provide a characteristic time for energy transport in the coupled solar wind-magnetosphere-ionosphere system.

Elsen, R.↗
NASA NTRSDate not supplied

Enabling in-time Prognostics with Surrogate Modeling through Physics-enhanced Dynamic Mode Decomposition Method

Computational models provide essential quantitative tools for assessing and predicting the health and performance of physical systems. However, high-fidelity models are rarely used in real-time operations or large optimization loops, due to their time-intensive nature. A common approach to improving computational efficiency of prognosis is to employ surrogate models. Such models can significantly decrease computation time for some accuracy loss. In this context, use of Dynamic Mode Decomposition (DMD) is proposed to generate surrogate models for lithium-ion (Li-ion) battery discharge. DMD has been suggested and used successfully in the area of fluid dynamics for over a decade, but it has not been applied to the PHM domain, where far-ahead prediction of nonlinear behavior is crucial to propagate faults or predict Remaining Useful Life (RUL). For Li-ion battery health management, the standard application of DMD using only the observable quantities of interest was unable to capture the nonlinear discharge of batteries exhibited in lab testing. The Koopman theory, however, provides a mechanism to tradeoff low dimensional nonlinear models with high-dimensional linear ones in a DMD framework, by augmenting nonlinear state variables into the system representation. In this way, DMD allows for configurable simulation accuracy dependent on the dimensionality of the Koopman operator. For battery health management, we augmented the observable variables with the hidden states of a higher-fidelity physics model to build the DMD surrogate. In comparison to a high-fidelity model, the surrogate improved computational efficiency with only a minimal loss of accuracy, and enabled long-term prognostics horizons. A generalized method for this was implemented in the prog models python package.

prognostics and health management↗
DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term experiments

Climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (<10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Halogenated PETN derivatives: interplay between physical and chemical factors in explosive sensitivity

Determining the factors that influence and can help predict energetic material sensitivity has long been a challenge in the explosives community. Decades of literature reports identify a multitude of factors both chemical and physical that influence explosive sensitivity; however no unifying theory has been observed. Recent work by our team has demonstrated that the kinetics of “trigger linkages” (i.e., the weakest bonds in the energetic material) showed strong correlations with experimental drop hammer impact sensitivity. These correlations suggest that the simple kinetics of the first bonds to break are good indicators for the reactivity observed in simple handling sensitivity tests. Herein we report the synthesis of derivatives of the explosive pentaerythritol tetranitrate (PETN) in which one, two or three of the nitrate ester functional groups are substituted with an inert group. Experimental and computational studies show that explosive sensitivity correlates well with Q (heat of explosion), due to the change in the number of trigger linkages removed from the starting material. In addition, this correlation appears more significant than other observed chemical or physical effects imparted on the material by different inert functional groups, such as heat of formation, heat of explosion, heat capacity, oxygen balance, and the crystal structure of the material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Sequential versus Simultaneous Aging of EPDM Nuclear Cable Insulation Subjected to Elevated Temperature and Gamma Radiation

Electrical cables are integral to power, control, and instrumentation systems within nuclear power plants (NPPs). Exposure of cable systems within nuclear containment to elevated temperatures and gamma radiation during decades-long operation of NPPs can lead to degradation of cable polymeric insulation. Prediction of nuclear cable insulation degradation is complicated as thermal and radiation stress are not additive. In this work, we explore the relative effects of simultaneous and sequential thermal and gamma irradiation on the aging of ethylene-propylene-diene (EPDM) elastomer insulation to better understand realistic scenarios of cable insulation degradation. Cable insulation samples of EPDM were subjected to up to 320 kGy of gamma radiation at a dose rate of 300 Gy/hr in two heating scenarios: (1) simultaneously aged samples were heated at 150°C during irradiation and (2) sequentially aged samples were heated at 150°C for designated durations followed by corresponding periods of irradiation at ambient temperature. The mass, tensile elongation at break, and carbonyl index were assessed to quantify aging of the polymers. The simultaneous aging scenario was found to the more severe of the two for EPDM insulation degradation.

ethylene-propylene-diene elastomer, EPDM, nuclear ↗
DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs

This submission aimed to assess differences in short-term step warming manipulations and long-term chronic response to climate change in Alaskan ecosystems. Briefly, climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.The model used in the current study is available publicly (https://github.com/jinyun1tang/ECOSYS), and the current submission contains the python/ matlab codes for analyzing output from the model (includng a readme file to explain the codes). The benchmark data, also enclosed, was collected from a range of published and publicly available sources (extracted using GRABIT: https://www.mathworks.com/matlabcentral/fileexchange/7173-grabit). These sources describe warming induced changes in tundra/ boreal ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Sulfur, Chlorine and Fluorine Degassing and Atmospheric Loading by the Roza eruption, Columbia River Basalt Group, Washington

In this study we attempt to quantify the amount of S, Cl and F released by the 1300 cu km Roza member (approximately 14.7 Ma) of the Columbia River Basalt Group, which was produced by a moderate-size flood basalt eruption in the mid-Miocene. Our results are the first indication of the potential atmospheric SO2 yield from a flood basalt eruption, and indicate the mechanism by which flood basalt eruptions may have seriously affected the environment. Glass inclusions in phenocrysts and quenched glass in products from various stages of the eruption were analyzed for concentrations of S, Cl and F and major elements. Glass inclusions contain 1965 +/- 110 ppm S, 295 +/- 65 ppm Cl and 1310 +/- 110 ppm F. Groundmass glass of Roza dike selvages contains considerably lower concentrations: 1110 +/- 90 ppm S, 245 +/- 30 ppm Cl and 1020 +/- 25 ppm F. Scoria clasts from near vent deposits contain 665 +/- 75 ppm S, 175 +/- 5 ppm Cl and 950 +/- 20 ppm F, and the groundmass glass of lava selvages contains 520 +/- 30 ppm S, 190 +/- 30 ppm Cl and 890 +/- 55 ppm F. In crystalline lava, the concentrations are 195 ppm S, 100 ppm Cl and 830 ppm F. Volatile element concentrations in these samples represent the progress of degassing through the eruption and can be used to estimate the potential amount of the volatiles S, Cl and F released by the magma into the atmosphere, as well as to evaluate the amount liberated by various phases of the eruption. The total amount of volatiles released by the Roza eruption is estimated to have been approximately 12,420 MtSO2, approximately 710 MtHCI and approximately 1780 MtHF. The Roza magma liberated approximately 9620 MtSO, (77% of the total volatile mass released), approximately 400 MtHCI (56%) and approximately 1450 MtHF (81%) at the vents and lofted by the eruption columns to altitudes of 7-13 km. Degassing of the lava is estimated to have released an additional approximately 2810 MtSO2, approximately 310 MtHCI and approximately 330 MtHF. The Roza eruption is likely to have lasted for approximately 10 years, indicating an annual H2SO4-mass loading of approximately 1800 Mt. Thus, the atmospheric perturbations associated with the Roza eruption may have been of the magnitude predicted for a severe "nuclear" or "volcanic" winter, but lasting up to a decade or more.

Thordarson, Th.↗