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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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NASA NTRS2020

Southern Bhutan Ecological Forecasting Project Summary - Modeling Asian Elephant (Elephas Maximus) Habitat Suitability along the Southern Bhutan Border with NASA Earth Observations

Asian elephants (Elephas maximus) are a flagship species essential for the functioning of forest ecosystems, and they also have cultural significance in Bhutan. Elephants receive the highest legal protection as listed under Schedule I of the Bhutan Forests and Nature Conservation Act, 1995. Yet, they face threats of extinction due to poaching for ivory as well as the loss and fragmentation of their habitat. Due to the recent clearing of forests and the growing populations in these areas, there has been an increase in incidents of human-elephant conflict. These conflicts have been detrimental to farmer’s annual harvests and livelihoods and have led to retaliatory killing and injury of elephants in southern Bhutan. The DEVELOP Southern Bhutan Ecological Forecasting team partnered with the Bhutan Foundation and Bhutan Tiger Center to help address this problem. The team integrated NASA Earth observations, including Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and the Shuttle Radar Topography Mission (SRTM) to acquire information on land cover change and elephant habitat suitability along the southern border of Bhutan. The team utilized Esri ArcGIS Pro and Software for Assisted Habitat Modeling (SAHM) for data analysis, modeling, and visualization. The team used elephant occurrence data and environmental variables to model current habitat suitability for migrating elephant populations. This analysis provided partners with maps to inform decisions about the placement and conservation of elephant corridors and helped build their capacity to use satellite data for future studies and project planning.

DEVELOP Project Summary↗
NASA NTRS2022

A Multimodel Investigation of Asian Summer Monsoon UTLS Transport Over the Western Pacific

The Asian summer monsoon (ASM) as a chemical transport system is investigated using a suite of models in preparation for an airborne field campaign over the Western Pacific. Results show that the dynamical process of anticyclone eddy shedding in the upper troposphere rapidly transports convectively uplifted Asian boundary layer air masses to the upper troposphere and lower stratosphere over the Western Pacific. The models show that the transported air masses contain significantly enhanced aerosol loading and a complex chemical mixture of trace gases that are relevant to ozone chemistry. The chemical forecast models consistently predict the occurrence of the shedding events, but the predicted concentrations of transported trace gases and aerosols often differ between models. The airborne measurements to be obtained in the field campaign are expected to help reduce the model uncertainties. Furthermore, the large-scale seasonal chemical structure of the monsoon system is obtained from modeled carbon monoxide, a tracer of the convective transport of pollutants, which provides a new perspective of the ASM circulation, complementing the dynamical characterization of the monsoon.

Laura L. Pan↗
DOE OSTI2024

Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0

Abstract. Wildfires are becoming an increasing challenge to the sustainability of boreal peatland (BP) ecosystems and can alter the stability of boreal carbon storage. However, predicting the occurrence of rare and extreme BP fires proves to be challenging, and gaining a quantitative understanding of the factors, both natural and anthropogenic, inducing BP fires remains elusive. Here, we quantified the predictability of BP fires and their primary controlling factors from 1997 to 2015 using a two-step correcting machine learning (ML) framework that combines multiple ML classifiers, regression models, and an error-correcting technique. We found that (1) the adopted oversampling algorithm effectively addressed the unbalanced data and improved the recall rate by 26.88 %–48.62 % when using multiple datasets, and the error-correcting technique tackled the overestimation of fire sizes during fire seasons; (2) nonparametric models outperformed parametric models in predicting fire occurrences, and the random forest machine learning model performed the best, with the area under the receiver operating characteristic curve ranging from 0.83 to 0.93 across multiple fire datasets; and (3) four sets of factor-control simulations consistently indicated the dominant role of temperature, air dryness, and climate extreme (i.e., frost) for boreal peatland fires, overriding the effects of precipitation, wind speed, and human activities. Our findings demonstrate the efficiency and accuracy of ML techniques in predicting rare and extreme fire events and disentangle the primary factors determining BP fires, which are critical for predicting future fire risks under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their explanatory power is limited and uncertainties remain as to their relative contributions. Recent results show that the annual count of hours where evapotranspiration (ET) is larger than its 95th percentile is strongly correlated with the annual variability of ET and gross primary production (GPP) in an ecosystem model. This suggests that the occurrence of favorable conditions has a strong influence on the annual carbon budget. Here we analyzed data from eight forest sites of the AmeriFlux network with at least 7 years of continuous measurements. We show that for ET and the carbon fluxes GPP, ecosystem respiration (RE), and net ecosystem production, counting the “most active hours/days” (i.e., hours/days when the flux exceeds a high percentile) correlates well with the respective annual sums, with correlation coefficients generally larger than 0.8. Phenological transitions have much weaker explanatory power. By exploiting the relationship between most active hours and interannual variability, we classify hours as most active or less active and largely explain interannual variability in ecosystem fluxes, particularly for GPP and RE. Our results suggest that a better understanding and modeling of the occurrence of large values in high-frequency ecosystem fluxes will result in a better understanding of interannual variability of these fluxes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Evaluation and modeling of the topographic effect on the spectral response from NADIR pointing sensors

A field experiment, using a hand-held radiometer, was designed and conducted to assess a simple theoretical incidence model for simulating the topographic effect of a uniform sand surface. Seven data sets were taken to compare effects of solar elevation and azimuth encountered at different times of year. Analysis of these data showed considerable variation in radiance values for different slope angles and aspects and that these values varied considerably with changes in solar elevation and azimuth. The field measured variations in spectral response were found to have generally strong correlations with the theoretical model. The reason for the occurrence of lower correlations are given and methods for improving the model are suggested. A model to simulate LANDSAT sensor response was applied to two subsets of the field data to establish the magnitude of the topographic effect on satellite data.

Holben, B. N.↗
DOE OSTI2022

Using Direct Numerical Simulation of Pore-Level Events to Improve Pore-Network Models for Prediction of Residual Trapping of CO2

Direct numerical simulation and pore-network modeling are common approaches to study the physics of two-phase flow through natural rocks. For assessment of the long-term performance of geological sequestration of CO 2 , it is important to model the full drainage-imbibition cycle to provide an accurate estimate of the trapped CO 2 . While direct numerical simulation using pore geometry from micro-CT rock images accurately models two-phase flow physics, it is computationally prohibitive for large rock volumes. On the other hand, pore-network modeling on networks extracted from micro-CT rock images is computationally efficient but utilizes simplified physics in idealized geometric pore elements. This study uses the lattice-Boltzmann method for direct numerical simulation of CO 2 -brine flow in idealized pore elements to develop a new set of pore-level flow models for the pore-body filling and snap-off events in pore-network modeling of imbibition. Lattice-Boltzmann simulations are conducted on typical idealized pore-network configurations, and the interface evolution and local capillary pressure are evaluated to develop modified equations of local threshold capillary pressure of pore elements as a function of shape factor and other geometrical parameters. The modified equations are then incorporated into a quasi-static pore-network flow solver. The modified model is applied on extracted pore-network of sandstone samples, and saturation of residual trapped CO 2 is computed for a drainage-imbibition cycle. The modified model yields different statistics of pore-level events compared with the original model; in particular, the occurrence of snap-off in pore-throats is reduced resulting in a more frontal displacement pattern along the main injection direction. Compared to the original model, the modified model is in closer agreement with the residual trapped CO 2 obtained from core flow experiments and direct numerical simulation.

Kohanpur, Amir H.↗
NASA NTRS2005

A Rapid Approach to Modeling Species-Habitat Relationships

A growing number of species require conservation or management efforts. Success of these activities requires knowledge of the species' occurrence pattern. Species-habitat models developed from GIS data sources are commonly used to predict species occurrence but commonly used data sources are often developed for purposes other than predicting species occurrence and are of inappropriate scale and the techniques used to extract predictor variables are often time consuming and cannot be repeated easily and thus cannot efficiently reflect changing conditions. We used digital orthophotographs and a grid cell classification scheme to develop an efficient technique to extract predictor variables. We combined our classification scheme with a priori hypothesis development using expert knowledge and a previously published habitat suitability index and used an objective model selection procedure to choose candidate models. We were able to classify a large area (57,000 ha) in a fraction of the time that would be required to map vegetation and were able to test models at varying scales using a windowing process. Interpretation of the selected models confirmed existing knowledge of factors important to Florida scrub-jay habitat occupancy. The potential uses and advantages of using a grid cell classification scheme in conjunction with expert knowledge or an habitat suitability index (HSI) and an objective model selection procedure are discussed.

Carter, Geoffrey M.↗
DOE OSTI2019

On the long-term migration of uranyl in bentonite barrier for high-level radioactive waste repositories: The effect of different host rocks

Repositories for high level radioactive waste hosted in argillite or granite with bentonite backfill are the two disposal concepts that been extensively studied. A general perception is that granite has very low sorption capacity and therefore is disadvantageous in retarding the migration of radionuclides in comparison with argillite. However, when there is bentonite backfill, does the sorption capacity of granite really matter for the migration of radionuclides? How different host rocks would affect the migration of U(VI) through the bentonite backfill of an engineered barrier system (EBS), and which properties of the host rocks cause those differences in migration, given that migration of radionuclides is a critical measure in assessing the performance of a repository? Here we present two coupled thermal, hydrological, and chemical models for the transport of U(VI), each with an identical setup except for the type of host rock (argillite vs granite rock). Comparisons between our models show that the different host rocks exert their influence on migration of U(VI) via regulating the chemical conditions in the bentonite, which affect the concentration of U(VI) at the source and the adsorption of U(VI) in the bentonite. The key chemical conditions are pH, Ca + , and HCO 3 - concentration in pore-water, which are strongly affected by soluble carbonate minerals. Our models also show the occurrence of illitization (dissolution of smectite and precipitation of illite) in the bentonite, which affects the migration of U(VI) through changing pH and the quantity of adsorbents. Although generalization of current model results for granite and argillite should be done carefully, the simulations highlight the importance of pore-water chemistry in host rock, as well as bentonite-host rock interactions, when assessing the performance of a repository. In comparison to properties such as thermal conductivity, permeability, and adsorption capacity, properties that have been studied intensively, the pore-water chemistry of host rocks deserve equal or even more attention because of its strong influence on radionuclide migration.

58 GEOSCIENCES↗
DOE OSTI2015

On the impact of temperatures up to 200°C in clay repositories with bentonite engineer barrier systems: A study with coupled thermal, hydrological, chemical, and mechanical modeling

One of the most important design variables for a geological nuclear waste repository is the temperature limit up to which the engineered barrier system (EBS) and the natural geologic environment can be exposed. Up to now, almost all design concepts that involve bentonite-backfilled emplacement tunnels have chosen a maximum allowable temperature of about 100°C. Such a choice is largely based on the consideration that in clay-based materials illitization and the associated mechanical changes in the bentonite (and perhaps the clay host rock) could affect the barrier attributes of the EBS. However, existing experimental and modeling studies on the occurrence of illitization and related performance impacts are not conclusive, in part because the relevant couplings between the thermal, hydrological, chemical, and mechanical (THMC) processes have not been fully represented in the models. This work presents a fully coupled THMC simulation of a nuclear waste repository in a clay formation with a bentonite-backfilled EBS for 1000 years. Two scenarios were simulated for comparison: a case in which the temperature in the bentonite near the waste canister can reach about 200°C and a case in which the temperature in the bentonite near the waste canister peaks at about 100°C. The model simulations demonstrate some degree of illitization in both the bentonite buffer and the surrounding clay formation. Other chemical alterations include the dissolution of K-feldspar and calcite, and precipitation of quartz, chlorite, and kaolinite. In general, illitization in the bentonite and the clay formation is enhanced at higher temperature. However, the quantity of illitization is affected by many chemical factors and therefore varies a great deal. The most important chemical factors are the concentration of K in the pore water as well as the abundance and dissolution rate of K-feldspar; less important ones are the concentration of sodium and the quartz precipitation rate. In our modeling scenarios, the calculated decrease in smectite volume fraction in bentonite ranges from 1 to 8% of the initial volume fraction of smectite in the 100°C scenario and 1–27% in the 200°C scenario. Chemical changes in the 200°C scenario could also lead to a reduction in swelling stress up to 15–18% whereas those in the 100°C scenario result in about 14–15% reduction in swelling stress for the base case scenario. Model results also show that the 200°C scenario results in a much higher total stress than the 100°C scenario, mostly due to thermal pressurization. While cautions should be taken regarding the model results due to some limitations in the models, the modeling work is illustrative in light of the relative importance of different processes occurring in EBS bentonite and clay formation at higher than 100°C conditions, and could be of greater use when site specific data are available.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Advancing cloud lifecycle representation in numerical models using innovative analysis methods that bridge arm observations over a breadth of scales

From its location on the subtropics-midlatitude boundary, the Azores is influenced by both the subtropical high pressure and the midlatitude baroclinic storm regimes, and therefore experiences a wide range of cloud structures, from fair-weather scenes to stratocumulus sheets to deep convective systems. This project combined three types of data sets to study cloud variability in the Azores: a satellite analysis of cloud regimes, a reanalysis characterization of storminess, and a 19-month field campaign that occurred on Graciosa Island. Combined analysis of the three data sets provides a detailed picture of cloud variability and the respective dynamic influences, with emphasis on low clouds that constitute a major uncertainty source in climate model simulations. The satellite cloud regime analysis shows that the Azores cloud distribution is similar to the mean global distribution and can therefore be used to evaluate cloud simulation in global models. Regime analysis of low clouds shows that stratocumulus decks occur under the influence of the Azores high-pressure system, while shallow cumulus clouds are sustained by cold-air outbreaks, as revealed by their preference for post-frontal environments and northwesterly flows. An evaluation of CMIP5 climate model cloud regimes over the Azores shows that all models severely underpredict shallow cumulus clouds, while most models also underpredict the occurrence of stratocumulus cloud decks. It is demonstrated that carefully selected case studies can be related through regime analysis to climatological cloud distributions, and a methodology is suggested utilizing process-resolving model simulations of individual cases to better understand cloud-dynamics interactions and attempt to explain and correct climate model cloud deficiencies.

58 GEOSCIENCES↗
DOE OSTI2021

Mathematical analysis of laboratory microbial experiments demonstrating deterministic chaotic dynamics

Presented is a system of four ordinary differential equations and a mathematical analysis of microbiological experiments in a four-component chemostat—nutrient n, rods r, cocci c, and predators p. The analysis is consistent with the conclusion that previous experiments produced features of deterministic chaotic and classical dynamics depending on dilution rate. The surrogate model incorporates as much experimental detail as possible, but necessarily contains unmeasured parameters. The objective is to understand better the differences between model simulations and experimental results in complex microbial populations. The key methodology for simulation of chaotic dynamics, consistent with the measured dilution rate and microbial volume averages, was to cause the preference of p for r vs. c to vary with the r and c concentrations, to make r more competitive for nutrient than c, and to recycle some dying p biomass, leading to a modified version of the Monod kinetics model. Our mathematical model demonstrated that the occurrence of chaotic dynamics requires a predator, p, preference for r versus c to increase significantly with increases in r and c populations. Also included is a discussion of several generalizations of the existing model and a possible involvement of the minimum energy dissipation principle. This principle appears fundamental to thermodynamic systems including living systems. Several new experiments are suggested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A Dynamical and Statistical Characterization of U.S. Extreme Precipitation Events and Their Associated Large-Scale Meteorological Patterns

Abstract Regional patterns of extreme precipitation events occurring over the continental United States are identified via hierarchical cluster analysis of observed daily precipitation for the period 1950–2005. Six canonical extreme precipitation patterns (EPPs) are isolated for the boreal warm season and five for the cool season. The large-scale meteorological pattern (LMP) inducing each EPP is identified and used to create a “base function” for evaluating a climate model’s potential for accurately representing the different patterns of precipitation extremes. A parallel analysis of the Community Climate System Model, version 4 (CCSM4), reveals that the CCSM4 successfully captures the main U.S. EPPs for both the warm and cool seasons, albeit with varying degrees of accuracy. The model’s skill in simulating each EPP tends to be positively correlated with its capability in representing the associated LMP. Model bias in the occurrence frequency of a governing LMP is directly related to the frequency bias in the corresponding EPP. In addition, however, discrepancies are found between the CCSM4’s representation of LMPs and EPPs over regions such as the western United States and Midwest, where topographic precipitation influences and organized convection are prominent, respectively. In these cases, the model representation of finer-scale physical processes appears to be at least equally important compared to the LMPs in driving the occurrence of extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

On the occurrence of fast neutrino flavor conversions in multidimensional supernova models

The dense neutrino medium in a core-collapse supernova or a neutron-star merger event can experience fast flavor conversions on time/distance scales that are much smaller than those of vacuum oscillations. It is believed that fast neutrino flavor transformation occurs in the region where the angular distributions of ν e and v¯ e cross each other. We present the first study of this crossing phenomenon and the fast neutrino flavor conversions in multidimensional (multi-D) supernova models. We examine the neutrino distributions obtained by solving the Boltzmann transport equation for several fixed profiles which are representative snapshots taken from separate 2D and 3D supernova simulations with an 11.2 M ⊙ progenitor model. Our research shows that the spherically asymmetric patterns of the ν e and v¯ e fluxes in multi-D models can assist the appearance of the crossing between the ν e and v¯ e angular distributions. In the models that we have studied, there exist unstable neutrino oscillation modes in and beyond the neutrino decoupling region which have amplitude growth rates as large as an e-fold per nanosecond. Here, this finding can have important consequences for the explosion mechanism, nucleosynthesis, and neutrino signals of core-collapse supernovae.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

Combustion modeling in internal combustion engines

The fundamental assumptions of the Blizard and Keck combustion model for internal combustion engines are examined and a generalization of that model is derived. The most significant feature of the model is that it permits the occurrence of unburned hydrocarbons in the thermodynamic-kinetic modeling of exhaust gases. The general formulas are evaluated in two specific cases that are likely to be significant in the applications of the model.

Zeleznik, F. J.↗
DOE OSTI2023

Quantifying conditional probabilities of fish-turbine encounters and impacts

Tidal turbines are one source of marine renewable energy but development of tidal power is hampered by uncertainties in fish-turbine interaction impacts. Current knowledge gaps exist in efforts to quantify risks, as empirical data and modeling studies have characterized components of fish approach and interaction with turbines, but a comprehensive model that quantifies conditional occurrence probabilities of fish approaching and then interacting with a turbine in sequential steps is lacking. We combined empirical acoustic density measurements of Pacific herring ( Clupea pallasii ) and when data limited, published probabilities in an impact probability model that includes approach, entrainment, interactions, and avoidance of fish with axial or cross-flow tidal turbines. Interaction impacts include fish collisions with stationary turbine components, blade strikes by rotating blades, and/or a collision followed by a blade strike. Impact probabilities for collision followed by a blade strike were lowest with estimates ranging from 0.0000242 to 0.0678, and highest for blade strike ranging from 0.000261 to 0.40. Maximum probabilities occurred for a cross-flow turbine at night with no active or passive avoidance. Estimates were lowest when probabilities were conditional on sequential events, and when active and passive avoidance was included for an axial-flow turbine during the day. As expected, conditional probabilities were typically lower than analogous independent events and literature values. Estimating impact probabilities for Pacific herring in Admiralty Inlet, Washington, United States for two device types illustrates utilization of existing data and simultaneously identifies data gaps needed to fully calculate empirical-based probabilities for any site-species combination.

collision risk↗
DOE OSTI2020

Dynamic Restoration Strategy for Distribution System Resilience Enhancement

In electric power distribution systems, distributed energy resources (DERs) can act as controllable power sources and support utility operators to minimize power outages after extreme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influences of extreme events and the capabilities of DERs are dynamic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/dis-turbance information and the availability of DERs. In this paper, we propose a new dynamic restoration strategy for distribution systems to enhance system resilience against potential hazards. An efficient reconfiguration algorithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER operation set points based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

distributed energy resources (DERs)↗
NASA NTRS2009

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

Duda, David P.↗
NASA NTRS1973

Analysis of electrical contact occurrences between rolling surface with application to elastohydrodynamic lubrication

A mathematical model enabling the relation of electrical contact occurrences between rolling surfaces to the mean thickness of an elastohydrodynamic lubricant film is discussed. A previous development by other authors is shown to contain an error invalidating their results. Some potentially useful approximations are developed for the case when the lubricant film is large with respect to the surface roughness. Complete solutions that are valid for all film thicknesses are not yet available.

Sidik, S. M.↗