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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Summer mean and extreme precipitation over the Mid-Atlantic region: climatological characteristics and contributions from different precipitation types

Based on a long-term observational dataset from the tracking of mesoscale convective systems (MCSs), isolated deep convection (IDC), and tropical cyclones (TCs), we examine the climatological characteristics of summer mean and extreme precipitation during 2004 – 2017 and their respective contributions from MCS, IDC, TC, and non-convective (NC) systems and the local vs. remote influence of MCS and IDC over the MAR. On average, MCS, IDC, TC, and NC contribute 22%, 29%, 4%, and 45% to the total summer mean precipitation in the region. While MCS and TC precipitation primarily occurs in the coastal areas east of the Appalachian Mountains, IDC precipitation is more concentrated in the southern MAR and near the mountain windward slopes. Each summer, ~41 MCSs with an average lifetime of 19.6 hours influence the MAR, with 80% initiated outside and traveling on average 10 hours to the region. Around 13 MCSs initiated in the Great Plains and Midwest propagate across the Appalachian Mountains and contribute 20-40% to summer MCS precipitation in the central Mid-Atlantic coastal areas. In contrast, more than 2000 IDCs with an average lifetime of 2.0 hours influence the MAR each summer, and 77% are initiated locally. MCS, IDC, TC, and NC contribute 31% (30%), 26% (31%), 18% (7%), and 26% (32%) to the top 1% (5%) extreme daily precipitation, respectively. Considering extreme hourly precipitation, however, the IDC contributions increase to 41% (top 1%) and 38% (top 5%) due to the shorter duration of IDC events than the other precipitation types.

Li, Jianfeng↗
DOE OSTI2019

A Framework to Delineate Precipitation-Runoff Regimes: Precipitation vs. Snowpack in the Western U.S.

We propose a framework to classify precipitation events accompanied by snow process (precipitation-and-snow, or PAS events) into five regimes, based on the relative contributions of snowpack change and precipitation amount to the runoff response. This framework is applied to a regional climate simulation over the western U.S. to reveal the regions where snow process plays important roles. Over the western U.S., PAS events account for 50-90% of all the precipitation events. About 60-80% of PAS events feature snow accumulation, but snow melting frequently happens in high-elevation areas. Compared with snow accumulation events, snow melting events have a more limited spatial distribution. Different regimes peak in different months between early winter and late spring. Lastly, the impact of atmospheric rivers is investigated. Although accounting for only 2% of the grid-scale precipitation events, atmospheric rivers trigger significant snowmelt and contribute to 20% and 11% of light and heavy snow melting events, respectively.

Chen, Xiaodong↗
DOE OSTI2015

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21 month (April 2009-December 2010) comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1- 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from at Graciosa are being compared with short-range forecasts made a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.

clouds↗
NASA NTRS2019

Integrated Multi-Satellite Evaluation for the Global Precipitation Measurement: Impact of Precipitation Types on Spaceborne Precipitation Estimation

Integrated multi-sensor assessment is proposed as a novel approach to advance satellite precipitation validation in order to provide users and algorithm developers with an assessment adequately coping with the varying performances of merged satellite precipitation estimates. Gridded precipitation rates retrieved from space sensors with quasi-global coverage feed numerous applications ranging from water budget studies to forecasting natural hazards caused by extreme events. Characterizing the error structure of satellite precipitation products is recognized as a major issue for the usefulness of these estimates. The Global Precipitation Measurement (GPM) mission aims at unifying precipitation measurements from a constellation of low-earth orbiting (LEO) sensors with various capabilities to detect, classify and quantify precipitation. They are used in combination with geostationary observations to provide gridded precipitation accumulations. The GPM Core Observatory satellite serves as a calibration reference for consistent precipitation retrieval algorithms across the constellation. The propagation of QPE uncertainty from LEO active/passive microwave (PMW) precipitation estimates to gridded QPE is addressed in this study, by focusing on the impact of precipitation typology on QPE from the Level-2 GPM Core Observatory Dual-frequency Precipitation Radar (DPR) to the Microwave Imager (GMI) to Level-3 IMERG precipitation over the Conterminous U.S. A high-resolution surface precipitation used as a consistent reference across scales is derived from the ground radar-based Multi-Radar/Multi-Sensor. While the error structure of the DPR, GMI and subsequent IMERG is complex because of the interaction of various error factors, systematic biases related to precipitation typology are consistently quantified across products. These biases display similar features across Level-2 and Level-3, highlighting the need to better resolve precipitation typology from space and the room for improvement in global-scale precipitation estimates. The integrated analysis and framework proposed herein applies more generally to precipitation estimates from sensors and error sources affecting low-earth orbiting satellites and derived gridded products.

Rainfall↗
NASA NTRS2020

Integrated Multi-satellite Evaluation for the Global Precipitation Measurement: Impact of Precipitation Types on Spaceborne Precipitation Estimation

An integrated multi-sensor assessment is proposed as a novel approach to advance satellite precipitation validation in order to provide users and algorithm developers with an assessment adequately coping with the varying performances of merged satellite precipitation estimates. Gridded precipitation rates retrieved from space sensors with quasi-global coverage feed numerous applications ranging from water budget studies to forecasting natural hazards caused by extreme events. Characterizing the error structure of satellite precipitation products is recognized as a major issue for the usefulness of these estimates. The Global Precipitation Measurement (GPM) mission aims at unifying precipitation measurements from a constellation of low-earth orbiting (LEO) sensors with various capabilities to detect, classify and quantify precipitation. They are used in combination with geostationary observations to provide gridded precipitation accumulations. The GPM Core Obser­vatory satellite serves as a calibration reference for consistent precipitation retrieval algorithms across the constellation. The propagation of QPE uncertainty from LEO active/passive microwave (PMW) precipitation estimates to gridded QPE is addressed in this study, by focusing on the impact of precipitation typology on QPE from the Level-2 GPM Core Observatory Dual-frequency Precipitation Radar (DPR) to the Microwave Imager (GMI) to Level-3 IMERG precipitation over the Conterminous U.S. A high-resolution surface precipitation used as a consistent reference across scales is derived from the ground radar-based Multi-Radar/Multi­Sensor. While the error structure of the DPR, GMI and subsequent IMERG is complex because of the interaction of various error factors, systematic biases related to precipitation typology are consistently quantified across products. These biases display similar features across Level-2 and Level-3, highlighting the need to better resolve precipitation typology from space and the room for improvement in global­scale precipitation estimates. The integrated analysis and framework proposed herein applies more generally to precipitation estimates from sensors and error sources affecting low-earth orbiting satellites and derived gridded products.

Pierre-Emmanuel Kirstette↗
DOE OSTI2017

Solute mixing regulates heterogeneity of mineral precipitation in porous media

Here, synchrotron X-ray microtomography was used to track the spatiotemporal evolution of mineral precipitation and the consequent alteration of the pore structure. Column experiments were conducted by injecting CaCl 2 and NaHCO 3 solutions into granular porous media either as a premixed supersaturated solution (external mixing) or as separate solutions that mixed within the specimen (internal mixing). The two mixing modes produced distinct mineral growth patterns. While internal mixing promoted transverse heterogeneity with precipitation at the mixing zone, external mixing favored relatively homogeneous precipitation along the flow direction. The impact of precipitation on pore water flow and permeability was assessed via 3-D flow simulations, which indicated anisotropic permeability evolution for both mixing modes. Under both mixing modes, precipitation decreased the median pore size and increased the skewness of the pore size distribution. Such similar pore-scale evolution patterns suggest that the clogging of individual pores depends primarily on local supersaturation state and pore geometry.

42 ENGINEERING↗
DOE OSTI2017

Nanoparticle Precipitation in Irradiated and Annealed Ceria Doped with Metals for Emulation of Spent Fuels

Epsilon alloy precipitates have been observed with varied compositions and sizes in spent nuclear fuels, such as UO2. Presence of the inclusions, along with other oxide precipitates, gas bubbles and irradiation-induced structural defects, can significantly degrade the physical properties of the fuel. To predict fuel performance, a fundamental study of the precipitation processes is needed. This study uses ceria (CeO2) as a surrogate for UO2. Polycrystalline CeO2 films doped with Mo, Ru, Rh, Pd and Re (surrogate for Tc) were grown at 823 K using pulsed laser deposition, irradiated at 673 K with He+ ions, and subsequently annealed at higher temperatures. A number of methods, including transmission electron microscopy and atom probe tomography, were applied to characterize the samples. The results indicate that there is a uniform distribution of the doped metals in the as-grown CeO2 film. Pd particles of ~3 nm in size appear near dislocation edges after He+ ion irradiation to ~13 dpa. Thermal annealing at 1073 K in air leads to formation of precipitates with Mo and Pd around grain boundaries. Further annealing at 1373 K produces 70 nm sized precipitates with small grains at cavities.

Jiang, Weilin↗
NASA NTRS2015

Global Precipitation Measurement (GPM) Mission: Precipitation Processing System (PPS) GPM Mission Gridded Text Products Provide Surface Precipitation Retrievals

In February 2015, the Global Precipitation Measurement (GPM) mission core satellite will complete its first year in space. The core satellite carries a conically scanning microwave imager called the GPM Microwave Imager (GMI), which also has 166 GHz and 183 GHz frequency channels. The GPM core satellite also carries a dual frequency radar (DPR) which operates at Ku frequency, similar to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar, and a new Ka frequency. The precipitation processing system (PPS) is producing swath-based instantaneous precipitation retrievals from GMI, both radars including a dual-frequency product, and a combined GMIDPR precipitation retrieval. These level 2 products are written in the HDF5 format and have many additional parameters beyond surface precipitation that are organized into appropriate groups. While these retrieval algorithms were developed prior to launch and are not optimal, these algorithms are producing very creditable retrievals. It is appropriate for a wide group of users to have access to the GPM retrievals. However, for researchers requiring only surface precipitation, these L2 swath products can appear to be very intimidating and they certainly do contain many more variables than the average researcher needs. Some researchers desire only surface retrievals stored in a simple easily accessible format. In response, PPS has begun to produce gridded text based products that contain just the most widely used variables for each instrument (surface rainfall rate, fraction liquid, fraction convective) in a single line for each grid box that contains one or more observations.This paper will describe the gridded data products that are being produced and provide an overview of their content. Currently two types of gridded products are being produced: (1) surface precipitation retrievals from the core satellite instruments GMI, DPR, and combined GMIDPR (2) surface precipitation retrievals for the partner constellation satellites. Both of these gridded products are generated for a.25 degree x.25 degree hourly grid, which are packaged into daily ASCII (American Standard Code for Information Interchange) files that can downloaded from the PPS FTP (File Transfer Protocol) site. To reduce the download size, the files are compressed using the gzip utility.This paper will focus on presenting high-level details about the gridded text product being generated from the instruments on the GPM core satellite. But summary information will also be presented about the partner radiometer gridded product. All retrievals for the partner radiometer are done using the GPROF2014 algorithmusing as input the PPS generated inter-calibrated 1C product for the radiometer.

precipitation↗
DOE OSTI2015

Precipitation in pores: A geochemical frontier

This article's purpose is to review some of the recent research in which geochemists have examined precipitation of solid phases in porous media, particularly in pores a few nanometers in diameter (nanopores). While this is a “review,” it is actually more forward-looking in that the list of things about this phenomenon that we do not know or cannot control at this time is likely longer than what we do know and can control. For example, there are three directly contradictory theories on how to predict how precipitation proceeds in a medium of varying pore size, as will be discussed below. The confusion on this subject likely stems from the complexity of the phenomenon itself: One can easily clog a porous medium by inducing a rapid, homogeneous precipitation directly from solution, or have limited precipitation occur that does not affect permeability or even porosity substantially. It is more difficult to engineer mineral precipitation in order to obtain a specific outcome, such as filling all available pore space over a targeted area for the purposes of contaminant sequestration. However, breakthrough discoveries could occur in the next five to ten years that enhance our ability to predict robustly and finely control precipitation in porous media by understanding how porosity and permeability evolve in response to system perturbations. These discoveries will likely stem (at least in part) from advances in our ability to 1) perform and interpret X-ray/neutron scattering experiments that reveal the extent of precipitation and its locales within porous media (Anovitz and Cole 2015, this volume), and 2) utilize increasingly powerful simulations to test concepts and models about the evolution of porosity and permeability as precipitation occurs (Steefel et al. 2015, this volume). A further important technique to isolate specific phenomena and understand reactivity is also microfluidics cell experiments that allow specific control of flow paths and fluid velocities (Yoon et al. 2012). An improved ability to synthesize idealized porous media will allow for tailored control of pore distributions, mineralogy and will allow more reproducible results. This in turn may allow us to isolate specific processes without the competing and obfuscatory effects that hinder generalization of observations when working with solely natural samples. It is likely that no one single experiment, or simulation technique will provide the key discoveries: to make substantive progress will require a collaborative effort to understand the interplay between fluid transport and geochemistry. Finally, where rock fracturing and elevated pressures are of concern, an understanding and capability to model geomechanical properties are necessary (Scherer 1999).

58 GEOSCIENCES↗
DOE OSTI2021

Enhancing fatigue life by ductile-transformable multicomponent B2 precipitates in a high-entropy alloy

Catastrophic accidents caused by fatigue failures often occur in engineering structures. Thus, a fundamental understanding of cyclic-deformation and fatigue-failure mechanisms is critical for the development of fatigue-resistant structural materials. Here we report a high-entropy alloy with enhanced fatigue life by ductile-transformable multicomponent B2 precipitates. Its cyclic-deformation mechanisms are revealed by real-time in-situ neutron diffraction, transmission-electron microscopy, crystal-plasticity modeling, and Monte-Carlo simulations. Multiple cyclic-deformation mechanisms, including dislocation slips, precipitation strengthening, deformation twinning, and reversible martensitic phase transformation, are observed in the studied high-entropy alloy. Its improved fatigue performance at low strain amplitudes, i.e., the high fatigue-crack-initiation resistance, is attributed to the high elasticity, plastic deformability, and martensitic transformation of the B2-strengthening phase. This study shows that fatigue-resistant alloys can be developed by incorporating strengthening ductile-transformable multicomponent intermetallic phases.

36 MATERIALS SCIENCE↗
DOE OSTI2012

The role of precipitation size distributions in km-scale NWP simulations of intense precipitation: Evaluation of cloud properties and surface precipitation

We investigate the sensitivity of simulated cloud properties and surface precipitation to assumptions regarding the size distributions of the precipitating hydrometeors in a one-moment bulk microphysics scheme. Three sensitivity experiments were applied to two composites of 15 convective and 15 frontal stratiform intense precipitation events observed in a coastal midlatitude region (Belgium), which were evaluated against satellite-retrieved cloud properties and radar-rain-gauge derived surface precipitation. It is found that the cloud optical thickness distribution was well captured by all experiments, although a significant underestimation of cloudiness occurred in the convective composite. The cloud-top-pressure distribution was improved most by more realistic snow size distributions (including a temperature-dependent intercept parameter and non-spherical snow for the calculation of the slope parameter), due to increased snow depositional growth at high altitudes. Surface precipitation was far less sensitive to whether graupel or hail was chosen as the rimed ice species, as compared to previous idealized experiments. This smaller difference in sensitivity could be explained by the stronger updraught velocities and higher freezing levels in the idealized experiments compared to typical coastal midlatitude environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Effect of Phosphate on U(VI) Sorption to Montmorillonite: Ternary Complexation and Precipitation Barriers

Phosphate addition is a potential treatment method to lower the solubility of U(VI) in soil and groundwater systems by causing U(VI) phosphate precipitation as well as enhancing adsorption. Previous work has shown that iron oxide surfaces may facilitate the nucleation of U(VI) phosphate minerals and, that under weakly acidic conditions, phosphate also enhances U(VI) adsorption to such phases. Like iron oxides, clays are important reactive phases in the subsurface but little is known about the interaction of U(VI) and phosphate with these minerals. The effect of aqueous phosphate on U(VI) binding to Wyoming montmorillonite (SWy-2) in air-equilibrated systems was investigated. Equilibrium U(VI) uptake to montmorillonite was determined at pH 4, 6 and 8 at discrete initial phosphate concentrations between 0 and 100 μM. The observed behavior of U(VI) indicates a transition from adsorption to precipitation with increasing total uranium and phosphate concentrations at all pH values. At the highest phosphate concentration examined at each pH value, a barrier to U(VI) phosphate nucleation is observed. At lower concentrations, phosphate has no effect on macroscopic U(VI) adsorption. To assess the mechanisms of U(VI)-phosphate interactions on smectite surfaces, U(VI) speciation was investigated under selected conditions using laser-induced fluorescence spectroscopy (LIFS) and extended X-ray absorption fine-structure (EXAFS) spectroscopy. Samples above the precipitation threshold display EXAFS and LIFS spectral signatures consistent with the autunite family of U(VI) phosphate minerals. However, at lower U(VI) concentrations, changes in LIFS spectra upon phosphate addition suggest that U(VI)-phosphate ternary surface complexes form on the montmorillonite surface at pH 4 and 6 despite the lack of a macroscopic effect on adsorption. The speciation of solid-associated U(VI) below the precipitation threshold at pH 8 is dominated by U(VI)-carbonate surface complexes. This work reveals that ternary complexation may occur without a macroscopic signature, which is attributed to phosphate not appreciably binding to smectite in the absence of U(VI), with U(VI) surface complexes serving as the sole reactive surface sites for phosphate. This study shows that phosphate does not enhance U(VI) adsorption to smectite clay minerals, unlike oxide phases, and that a barrier to homogeneous nucleation of U(VI) phosphates was not affected by the presence of the smectite surface

Environmental Molecular Sciences Laboratory↗
DOE OSTI2015

Deformation mechanisms in a precipitation-strengthened ferritic super alloy revealed by in situ neutron dffraction studies at elevated temperatures

The ferritic superalloy Fe–10Ni–6.5Al–10Cr–3.4Mo strengthened by ordered (Ni,Fe)AlB2-type precipitates is a candidate material for ultra-supercritical steam turbine applications above 923 K. Despite earlier success in improving its room-temperature ductility, the creep resistance of this material at high temperatures needs to be further improved, which requires a fundamental understanding of the high-temperature deformation mechanisms at the scales of individual phases and grains. In situ neutron diffraction has been utilized to investigate the lattice strain evolution and the microscopic load-sharing mechanisms during tensile deformation of this ferritic superalloy at elevated temperatures. Finite-element simulations based on the crystal plasticity theory are employed and compared with the experimental results, both qualitatively and quantitatively. Based on these interphase and intergranular load-partitioning studies, it is found that the deformation mechanisms change from dislocation slip to those related to dislocation climb, diffusional flow and possibly grain boundary sliding, below and above 873 K, respectively. Insights into microstructural design for enhancing creep resistance are also discussed.

nuclear (including radiation effects), defects, me↗
DOE OSTI2024

Improved Diagnosis of Precipitation Type with LightGBM Machine Learning

Abstract Existing precipitation-type algorithms have difficulty discerning the occurrence of freezing rain and ice pellets. These inherent biases are not only problematic in operational forecasting but also complicate the development of model-based precipitation-type climatologies. To address these issues, this paper introduces a novel light gradient-boosting machine (LightGBM)-based machine learning precipitation-type algorithm that utilizes reanalysis and surface observations. By comparing it with the Bourgouin precipitation-type algorithm as a baseline, we demonstrate that our algorithm improves the critical success index (CSI) for all examined precipitation types. Moreover, when compared with the precipitation-type diagnosis in reanalysis, our algorithm exhibits increased F1 scores for snow, freezing rain, and ice pellets. Subsequently, we utilize the algorithm to compute a freezing-rain climatology over the eastern United States. The resulting climatology pattern aligns well with observations; however, a significant mean bias is observed. We interpret this bias to be influenced by both the algorithm itself and assumptions regarding precipitation processes, which include biases associated with freezing drizzle, precipitation occurrence, and regional synoptic weather patterns. To mitigate the overall bias, we propose increasing the precipitation cutoff from 0.04 to 0.25 mm h −1 , as it better reflects the precision of precipitation observations. This adjustment yields a substantial reduction in the overall bias. Finally, given the strong performance of LightGBM in predicting mixed precipitation episodes, we anticipate that the algorithm can be effectively utilized in operational settings and for diagnosing precipitation types in climate model outputs. Significance Statement Freezing rain can have significant impacts on transportation and infrastructure, making accurate prediction of precipitation types crucial. In this study, we use a machine learning method known as LightGBM to predict precipitation types. We show that the new algorithm performs better than the existing methods for all precipitation types examined. Additionally, we compute a freezing-rain climatology over the eastern United States. Although the resulting climatology pattern corresponds well to observations, the algorithm overpredicts freezing-rain occurrence. We argue that this bias can be substantially reduced by increasing the precipitation cutoff from 0.04 to 0.25 mm h −1 . Overall, this work highlights the potential of the LightGBM algorithm for both weather forecasting and diagnosing precipitation types in climate models.

Meteorology & Atmospheric Sciences↗