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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Impact of mineral precipitation on flow and mixing in porous media determined by microcomputed tomography and MRI

Here, precipitation reactions in porous media influence transport properties of the environment and can control advective and dispersive transport. In subsurface environments, mixing of saline groundwater or injected solutions for remediation with fresh groundwater can induce supersaturation of constituents and drive precipitation reactions. Magnetic resonance imaging (MRI) and micro-computed tomography (µ-CT) were employed as complimentary techniques to evaluate advection, dispersion and formation of precipitate in a 3D porous media flow cell. Two parallel fluids were flowed concentrically through the porous media under two flow rate conditions with Na 2 CO 3 and CaCl 2 in the inner and outer fluids, respectively. Upon mixing, calcium carbonate became supersaturated and formed a precipitate at the interface of the two fluids. Spatial maps of changing local velocity fields and dispersion in the flow cell were generated from MRI, while high resolution imaging of the precipitate formed in the porous media was achieved via µ-CT imaging. Formation of a precipitate layer minimized dispersive and advective transport between the two fluids and the shape of the precipitation was influenced by the flow rate condition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

The Role of Convective Gustiness in Reducing Seasonal Precipitation Biases in the Tropical West Pacific

Abstract Precipitation is an important climate quantity that is critically relevant to society. In spite of intense efforts, significant precipitation biases remain in most climate models. One pervasive and persistent bias found in many general circulation models occurs in the Tropical West Pacific where northern hemisphere summer‐time precipitation is often underestimated compared to observations. Using the DOE‐E3SM model, the inclusion of a missing process, convective gustiness, is shown to reduce those biases through a net increase in surface evaporation. Gustiness in surface wind fields is assumed to arise empirically in proportion to the intensity of convective precipitation. The increased evaporation can be treated as an increase in the moist static energy forcing into the atmosphere. A Normalized Gross Moist Stability (NGMS) framework (which characterizes the relationship between convective forcing and convective response) is used to explore the processes responsible for the precipitation bias, and the impact of the gustiness parameterization in reducing that bias. Because the NGMS of the Tropical West Pacific is less than unity in the E3SMv1 model, the increase in energy forcing amplifies the increase in precipitation to exceed that of the evaporative flux. Convective gustiness favors increased precipitation in regions where the resolved surface winds are weak and convection is present.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Observing System Simulations for the AOS Mission

The Earth System Observatory (ESO) is NASA’s response to the recommendations of the 2017 Earth Sciences Decadal Survey conducted by the US National Academy of Sciences, Engineering and Medicine. The ESO is being conceived as a set of fully integrated missions addressing 4 main Earth science focus areas including aerosols, clouds, convection and precipitation (jointly re-ferred to as AOS, the Atmosphere Observing System). ESO ground breaking observations will provide critical measurements to address societally relevant problems in climate change, natural hazard mitiga-tion, fighting forest fires, and improving real-time agricultural processes. A critical element of the AOS observing strategy is to make extensive use of new passive and active sen-sors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. In order to achieve maximum benefit, all these observations need to be integrated into comprehensive observing and modeling/data assimilation systems. Such an approach requires compre-hensive model-data synthesis capabilities that needs to be conceived in conjunction with the space-based and suborbital components of AOS. In this presentation we will summarize the major science goals of AOS including cloud feedbacks, at-mospheric convection, emphasizing aerosol processes and aerosol radiative effects, and the synergistic aspects of clouds-precipitation-aerosol interactions. We will describe examples of the observing system simulation capabilities being developed for AOS, including global storm resolving nature runs, detailed instrument and retrieval simulators, as well as fast retrieval emulators for instrumenting climate models. This simulation environment, being developed under NASA’s open-source science initiative, will permit us to explore how AOS data will be used across space and time to better initialize forecasts and train modeling systems, and to infuse models and data assimilation systems with AOS data, well before launch.

Arlindo da Silva↗
DOE OSTI2022

Combined Effect of the Wegener–Bergeron–Findeisen Mechanism and Large Eddies on Microphysics of Mixed-Phase Stratiform Clouds

Abstract The process of glaciation in mixed-phase stratiform clouds was investigated by a novel Lagrangian–Eulerian model (LEM) in which thousands of adjoining Lagrangian parcels moved within a turbulent-like velocity field with statistical parameters typical of the Arctic boundary layer. We used detailed bin microphysics to describe the condensation/evaporation processes in each parcel, in which droplets, aerosols, and ice particles were described using size distributions of 500 mass bins. The model also calculated aerosol mass inside droplets and ice particles. Gravitational sedimentation of droplets and ice particles was also accounted for. Assuming that droplet freezing is the primary source of ice particles, the Arctic clouds observed in Indirect and Semi-Direct Aerosol Campaign (ISDAC) were successfully simulated. The model showed that at a low ice particle concentration typical of ISDAC, large vortices (eddies) led to a quasi-stationary regime, in which mixed-phase St existed for a long time. The large eddies controlled the water partitioning in the mixed-phase clouds. Droplets formed and grew in updrafts, typically reaching the cloud top, and evaporated in downdrafts. Ice particles grew in updrafts and downdrafts. The Wegener–Bergeron–Findeisen (WBF) mechanism was efficient in downdrafts and some parts of updrafts, depending on ice concentration and vertical velocity. At low ice concentrations, the effect of ice on the phase partitioning was negligible. In this regime, liquid droplets were found near the cloud top, whereas ice particles precipitated through the cloud base. When ice concentration exceeded about 10 L −1 , the WBF mechanism led to glaciation of almost the entire cloud, with the exception of narrow cloud regions associated with strong updrafts. At ice particle concentrations of a few tens per liter, the oscillatory regime took place due to the ice–liquid interaction. The microphysical structure of mixed-phase St forms as a combined effect of cloud dynamics (large eddies) and the WBF mechanism.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Develop a weather-aware climate model to understand and predict extremes and associated power outages and renewable energy shortages with uncertainty-aware and physics-informed machine learning

Focal Area(s): The focus area is predictive modeling through the use of AI techniques and AI-derived model components with a particular emphasis on extreme weather in Atmospheric Science and power outages and shortages in Energy Science. Science Challenge: Predicting weather extremes (e.g., heavy precipitation, strong wind, and large hailstones), and weather-related power system outages and shortages can mitigate economic losses, save lives, support renewables integration, and improve power system resiliency. However, currently, the poor reliability and large uncertainty associated with the weather extreme prediction in the current climate models make the problem intractable. The key challenges are: (1) physical factors like green-house gases (GHGs), aerosols, and land use and land cover (LULC) can significantly impact extreme storms, but the understanding of these impacts is limited, particularly globally; (2) the convective permitting resolutions needed to model severe convective storms and their impacts are computationally prohibitive with global climate models (GCMs); (3) interactions between weather extremes and power system outages are complex and subject to great uncertainty. Current outage prediction models are short lead (~ 3 days), which do not allow for long-time planning of energy production and distribution. Moreover, we have limited capacity to predict weather events leading to sustained shortages in a renewable-energy-dominated power system. These challenges drive motivation for mechanistic understanding and reliable and efficient predictive modeling of extremes and their impacts from the sub-seasonal to long term projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Significantly Promoting the Thermal Conductivity and Machinability of Negative Thermal Expansion Alloy via In Situ Precipitation of Copper Networks

Rapid advancements in electronic devices yield an urgent demand for high-performance electronic packaging materials with high thermal conductivity, low thermal expansion, and great mechanical properties. However, it is a great challenge for current design philosophies to fulfill all the requirements simultaneously. Here, an effective strategy is proposed for significantly promoting the thermal conductivity and machinability of negative thermal expansion alloy (Zr,Nb)Fe 2 through eutectic precipitation of copper networks. The eutectic dual-phase alloy exhibits an isotropic chips-matched thermal expansion coefficient and a thermal conductivity enhancement exceeding 200% compared with (Zr,Nb)Fe 2 , along with an ultimate compressive strength of 550 MPa. The addition of copper reorganizes the composition of (Zr,Nb)Fe 2 , which smooths the magnetic transition and shifts it toward higher temperature, resulting in linear low thermal expansion in a wide temperature range. The highly fine eutectic copper lamellae construct high thermal conductivity networks within (Zr,Nb)Fe 2 , serving as highways for heat transfer electrons and phonons. The in situ forming of eutectic copper lamellae also facilitates the mechanical properties by enhancing interfacial bonding and bearing additional stress after yielding of (Zr,Nb)Fe 2 . This work provides a novel strategy for promoting thermal conductivity and mechanical properties of negative thermal expansion alloys via eutectic precipitation of copper networks.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Formation and redox reactivity of ferrihydrite-organic carbon-calcium co-precipitates

Complexation with minerals plays a critical role in regulating the stability of organic matter. The presence of cations is assumed to be important for the complexation between organic matter and minerals, but there is still limited direct analysis for the formation and reactivity of mineral-organic matter-cation ternary complexes, as well as governing factors for the fate of minerals and organic matter in the complexes. In order to close this knowledge gap, we investigated the formation and reactivity of ferrihydrite (Fh)-organic carbon (OC)-calcium (Ca) ternary co-precipitates. We performed microbial anaerobic Fe reduction using Shewanella putrefaciens CN32 on synthesized Fh-OC-Ca co-precipitates and characterized OC and Fe minerals using various spectroscopic and wet chemistry techniques. We discovered that Ca incorporated into the co-precipitate was a function of OC/iron (Fe) ratio, but OC incorporation was not impacted by the Ca content. During the reduction, the presence of Ca favored the formation of green rust but decreased the formation of magnetite and siderite in co-precipitates with high OC content. The reduction of Fe and reductive release of Fe-bound OC were controlled primarily by the C/Fe ratio, rather than Ca/Fe ratio. Phenolic OC was preferentially released or degraded during the reduction compared to aromatic and carboxylic OC. Collectively, C/Ca incorporation data, Fe K-edge extended X-ray absorption fine structure (EXAFS) analysis for co-precipitates before and after reduction, and the reductive release of Ca and OC suggest the formation of Fh-OC-Ca ternary co-precipitates, likely with OC as bridges. The reduction of Fe and reductive release of OC were primarily controlled by the C/Fe ratio, whereas the presence of Ca affected the mineral phase transformation for Fh during the reduction of Fe. Thus, our results provide novel understanding for the formation and reactivity of Ca-based ternary co-precipitates, which can be valuable for building up process-based models for cycles of carbon and metals.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Assessing Malaria Risks in Greater Mekong Subregion based on Environmental Parameters

At 4,200 km, the Mekong River is the tenth longest river in the world. It directly and indirectly influences the lives of hundreds of millions of inhabitants in its basin. The riparian countries - Thailand, Myanmar, Cambodia, Laos, Vietnam, and a small part of China - form the Greater Mekong Subregion (GMS). This geographical region has the misfortune of being the world's epicenter of falciparum malaria, which is the most severe form of malaria caused by Plasmodium falciparum. Depending on the country, approximately 50 to 90% of all malaria cases are due to this species. In the Malaria Modeling and Surveillance Project, we have been developing techniques to enhance public health s decision capability for malaria risk assessments and controls. The main objectives are: 1) identifying the potential breeding sites for major vector species; 2) implementing a malaria transmission model to identify the key factors that sustain or intensify malaria transmission; and 3) implementing a risk algorithm to predict the occurrence of malaria and its transmission intensity. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Socioeconomic factors that may influence malaria transmissions will also be incorporated into the predictive models.

Kiang, Richard↗
DOE OSTI2023

Implicit learning of convective organization explains precipitation stochasticity

Accurate prediction of precipitation intensity is crucial for both human and natural systems, especially in a warming climate more prone to extreme precipitation. Yet, climate models fail to accurately predict precipitation intensity, particularly extremes. One missing piece of information in traditional climate model parameterizations is subgrid-scale cloud structure and organization, which affects precipitation intensity and stochasticity at coarse resolution. Here, using global storm-resolving simulations and machine learning, we show that, by implicitly learning subgrid organization, we can accurately predict precipitation variability and stochasticity with a low-dimensional set of latent variables. Using a neural network to parameterize coarse-grained precipitation, we find that the overall behavior of precipitation is reasonably predictable using large-scale quantities only; however, the neural network cannot predict the variability of precipitation (R 2 ~ 0.45) and underestimates precipitation extremes. The performance is significantly improved when the network is informed by our organization metric, correctly predicting precipitation extremes and spatial variability (R 2 ~ 0.9). The organization metric is implicitly learned by training the algorithm on a high-resolution precipitable water field, encoding the degree of subgrid organization. The organization metric shows large hysteresis, emphasizing the role of memory created by subgrid-scale structures. We demonstrate that this organization metric can be predicted as a simple memory process from information available at the previous time steps. These findings stress the role of organization and memory in accurate prediction of precipitation intensity and extremes and the necessity of parameterizing subgrid-scale convective organization in climate models to better project future changes of water cycle and extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The Midlatitude Continental Convective Clouds Experiment (MC3E)

The Midlatitude Continental Convective Clouds Experiment (MC3E), a field program jointly led by the U.S. Department of Energy’s Atmospheric Radiation Measurement program and the NASA Global Precipitation Measurement (GPM) Mission, was conducted in south-central Oklahoma during April – May 2011. MC3E science objectives were motivated by the need to improve understanding of midlatitude continental convective cloud system lifecycles, microphysics, and GPM precipitation retrieval algorithms. To achieve these objectives a multi-scale surface- and aircraft-based in situ and remote sensing observing strategy was employed. A variety of cloud and precipitation events were sampled during the MC3E, of which results from three deep convective events are highlighted. Vertical structure, air motions, precipitation drop-size distributions and ice properties were retrieved from multi-wavelength radar, profiler, and aircraft observations for an MCS on 11 May. Aircraft observations for another MCS observed on 20 May were used to test agreement between observed radar reflectivities and those calculated with forward-modeled reflectivity and microwave brightness temperatures using in situ particle size distributions and ice water content. Multi-platform observations of a supercell that occurred on 23 May allowed for an integrated analysis of kinematic and microphysical interactions. A core updraft of 25 ms-1 supported growth of hail and large rain drops. Data collected during the MC3E campaign is being used in a number of current and ongoing research projects and is available through the DOE ARM and NASA data archives.

Jensen, Mark P.↗
DOE OSTI2021

Lagged Wetland CH 4 Flux Response in a Historically Wet Year

While a stimulating effect of plant primary productivity on soil carbon dioxide (CO 2 ) emissions has been well documented, links between gross primary productivity (GPP) and wetland methane (CH 4 ) emissions are less well investigated. Determination of the influence of primary productivity on wetland CH 4 emissions (FCH 4 ) is complicated by confounding influences of water table level and temperature on CH 4 production, which also vary seasonally. Here, in this work, we evaluate the link between preceding GPP and subsequent FCH 4 at two fens in Wisconsin using eddy covariance flux towers, Lost Creek (US-Los) and Allequash Creek (US-ALQ). Both wetlands are mosaics of forested and shrub wetlands, with US-Los being larger in scale and having a more open canopy. Co-located sites with multi-year observations of flux, hydrology, and meteorology provide an opportunity to measure and compare lag effects on FCH4 without interference due to differing climate. Daily average FCH4 from US-Los reached a maximum of 47.7 ηmol CH 4 m -2 s -1 during the study period, while US-ALQ was more than double at 117.9 ηmol CH 4 m -2 s -1 . The lagged influence of GPP on temperature-normalized FCH4 (T air -FCH 4 ) was weaker and more delayed in a year with anomalously high precipitation than a following drier year at both sites. FCH 4 at US-ALQ was lower coincident with higher stream discharge in the wet year (2019), potentially due to soil gas flushing during high precipitation events and lower water temperatures. Better understanding of the lagged influence of GPP on FCH 4 due to this study has implications for climate modeling and more accurate carbon budgeting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Legacies of precipitation influence primary production in Panicum virgatum

Precipitation is a key driver of primary production worldwide, but primary production does not always track year-to-year variation in precipitation linearly. Instead, plant responses to changes in precipitation may exhibit time lags, or legacies of past precipitation. Legacies can be driven by multiple mechanisms, including persistent changes in plant physiological and morphological traits and changes to the physical environment, such as plant access to soil water. Here, we used three precipitation manipulation experiments in central Texas, USA to evaluate the magnitude, duration, and potential mechanisms driving precipitation legacies on aboveground primary production of the perennial C 4 grass, Panicum virgatum. Specifically, we performed a rainout shelter study, where eight genotypes grew under different precipitation regimes; a transplant study, where plants that had previously grown in a rainout shelter under different precipitation regimes were moved to a common environment; and a mesocosm study, where the effect of swapping precipitation regime was examined with a single genotype. Across these experiments, plants previously grown under wet conditions generally performed better than expected when exposed to drought. Panicum virgatum exhibited stronger productivity legacies of past wet years on current-year responses to drought than of past dry years on current-year responses to wet conditions. Additionally, previous year tiller counts, a proxy for meristem availability, were important in determining legacy effects on aboveground production. As climate changes and precipitation extremes—both dry and wet—become more common, these results suggest that populations of P. virgatum may become less resilient.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Effect of V and Ta on the precipitation behavior of 12%Cr reduced activation ferrite/martensite steel

12%Cr reduced activation ferrite/martensite steels are promising candidate materials for good corrosion and irradiation resistance used for supercritical water-cooled reactor cladding and in-core components. V and Ta are considered to have improved the creep strength of high Cr steels by precipitating as MX phase. In this paper, a series of trial products microalloyed with V and V–Ta are produced, and the microstructure is characterized after quenching at 1050 °C and tempering at 780 °C by using TEM method to investigate the effect of these elements on the precipitation behavior of 12%Cr reduced activation ferrite/martensite steel. The results from both the experimental observations and thermodynamic and kinetic calculations reveal that V and V–Ta can promote the stable MX precipitation instead of M{sub 2}X, thus increasing the volume fraction of M{sub 23}C{sub 6}. Two-phase separation behavior of the (Ta, V)(C, N) carbonitride into a Ta(V)C(N) phase and a V(Ta)N(C) phase in 12Cr3WVTa steel is observed and further discussed. - Highlights: • Microalloyed with V and V-Ta can promote the precipitation of MX instead of M{sub 2}X. • The presence of delta-ferrite in microstructure affects the morphology of MX. • Two-phase separation of MX carbonitride was observed in 12Cr3WVTa steel.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Precipitation of sigma and chi phases in δ-ferrite of Type 316FR weld metals

The decomposition behavior and kinetics of δ-ferrite are examined using aging treatments between 873 and 1073 K for Type 316FR stainless steel weld metals with different solidification modes (316FR AF, 316FR FA). The dominant precipitates are sigma, chi, and secondary austenite nucleated at δ-ferrite/austenite interfaces or in the interior of the ferrite grains. These precipitates consume all the ferrite during isothermal aging in both 316FR AF and FA weld metals. Differences in the precipitation behavior (precipitation initiation time and precipitation speed) between weld metals can be explained by i) the degree of Cr and Mo microsegregation within δ-ferrite or austenite near ferrite and ii) the nucleation sites induced due to the solidification mode (AF or FA), such as the ferrite amount. For both weld materials, a Johnson–Mehl-type equation can express the precipitation behavior of the sigma + chi phases and quantitatively predict the behavior at the service-exposure temperatures of a fast breed reactor. - Highlights: • Precipitation of σ and χ phase in Type 316FR welds (two solidification modes) • Different precipitation behaviors: precipitation initiation time and growth speed • Johnson-Mehl–type equation is the most applicable to the precipitation behaviors • Precipitation behaviors are predicted under service conditions of FBRs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Tansey_MICRE_AAD_lidar_cloud_and_precip_phase_V2.0_20160406_201601120

This data file contains retrievals of cloud-base and below-cloud precipitation phase base for the MICRE campaign. The retrieved base is largely based on AAD depolarization lidar measurements. BOM cloud radar (BASTA), ARM ceilometer, and U. Canterbury ceilometer data are used to locate cloud base and below-cloud precipitation. Details on the algorithm and analysis of results are given in Tansey et al. 2023 (submitted DOI: 10.22541/essoar.168394768.89694625/v1). The data is limited to the period 20160406 to 201601120 during which both AAD lidar data and BoM radar data was collected.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Impacts of precipitation variability on plant species and community water stress in a temperate deciduous forest in the central US

Variations in precipitation regimes can shift ecosystem structure and function by altering frequency, severity and timing of plant water stress. There is a need for predictively understanding impacts of precipitation regimes on plant water stress in relation to species water use strategies. Here we first formulated two complementary, physiologically-linked measures of precipitation variability (PV) - Precipitation Variability Index (PVI) and Average Recurrence Interval of Effective Precipitation (ARIEP). We then used nine-year continuous measurements of Predawn Leaf Water Potential Integral (PLWPI) in a central US forest to relate PVI and ARIEP to actual plant water availability and comparative water stress responses of six species with different capacities to regulate their internal water status. We found that PVI and ARIEP explained nearly all inter-annual variations in PLWPI for all species as well as for the community scaled from species measurements. The six species investigated showed differential sensitivities to variations in precipitation regimes. Their sensitivities were reflected more in the responses to PVI and ARIEP than to the mean precipitation rate. Further, they exhibited tradeoffs between responses to low and high PV. Finally, PVI and ARIEP were closely correlated with temporal integrals of positive temperature anomalies and vapor pressure deficit. We suggest that the comparative responses of plant species to PV are part of species-specific water use strategies in a plant community facing the uncertainty of fluctuating precipitation regimes. In conclusion, PVI and ARIEP should be adopted as key indices to quantify physiological drought and the ecological impacts of precipitation regimes in a changing climate.

54 ENVIRONMENTAL SCIENCES↗