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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
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Implications of using MERRA-2 cloud water in aerosol wet scavenging for Pb-210 surface concentrations and vertical profiles in GEOS-Chem

Precipitation scavenging is the dominant loss process for a whole suite of aerosols but model parameterizations of this process are highly uncertain, substantially contributing to large uncertainties in the simulated loadings and radiative forcing of aerosols. Lead-210 (210Pb, radioactive half-life of 22.3 years) is produced by radioactive decay of soil-emitted gaseous 222Rn. It attaches to ambient submicron aerosols and is subject to precipitation scavenging processes. Liu et al. [2001] estimated the global mean lifetime of tropospheric 210Pb aerosols to be ~9 days using the GEOS-Chem model. Luo et al. [2019, 2020] provided an option to use MERRA-2 cloud water in the model aerosol scavenging scheme. In this study, we examine the impact of this revision on 210Pb simulations and compare results with climatological observations of 210Pb surface and UT/LS concentrations, as well as aircraft profile measurements from eleven NASA field missions.

Bo Zhang↗
DOE OSTI2018

Impacts of Aerosol Dry Deposition on Black Carbon Spatial Distributions and Radiative Effects in the Community Atmosphere Model CAM5

Dry deposition is a vital process affecting the lifetime and spatial distributions of atmospheric aerosols. Black carbon (BC) plays an important role in the Earth’s climate. To explore the sensitivity of modeled BC spatial distributions to particle dry deposition treatments, the scheme of Petroff & Zhang (2010) (PZ10) is implemented into the Community Atmospheric Model version 5 (CAM5), and model simulations using PZ10 are compared with the one using the default scheme of Zhang et al. (2001) (Z01). The PZ10 scheme suggests much lower dry deposition velocities than Z01 for fine particles in Aitken, primary carbon, and accumulation modes, resulting in 73.0% lower of global mean BC dry deposition fluxes and 23.2% higher of global mean BC column burdens. CAM5 with PZ10 increases modeled BC concentrations at all altitudes and latitudes compared to Z01, which improves the agreement with observations of BC profiles in the lower troposphere in the Arctic. It also helps the simulation of surface BC concentrations in high-latitudes remote regions and its seasonality in the Arctic. Yet, PZ10 slightly exacerbates the overestimation of modeled BC concentrations in the middle and upper troposphere, which might be due to model uncertainties in other aerosol physical and chemical processes. The global annual mean radiative effects due to aerosol-radiation interactions (REari) and aerosol-cloud interactions (REaci) of BC from the CAM5 experiment using Z01 are 0.61±0.007 and -0.11±0.02 W m -2 , respectively, compared to slightly larger REari (0.75±0.01 W m -2 ) and REaci (-0.14±0.02 W m -2 ) from CAM5 using PZ10.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

17 WIND ENERGY↗
DOE OSTI2024

A Comprehensive Analysis of Uncertainties in Warm-Rain Parameterizations in Climate Models Based on In Situ Measurements

Abstract Because of the coarse grid size of Earth system models (ESMs), representing warm-rain processes in ESMs is a challenging task involving multiple sources of uncertainty. Previous studies evaluated warm-rain parameterizations mainly according to their performance in emulating collision–coalescence rates for local droplet populations over a short period of a few seconds. The representativeness of these local process rates comes into question when applied in ESMs for grid sizes on the order of 100 km and time steps on the order of 20–30 min. We evaluate several widely used warm-rain parameterizations in ESM application scenarios. In the comparison of local and instantaneous autoconversion rates, the two parameterization schemes based on numerical fitting to stochastic collection equation (SCE) results perform best. However, because of Jessen’s inequality, their performance deteriorates when grid-mean, instead of locally resolved, cloud properties are used in their simulations. In contrast, the effect of Jessen’s inequality partly cancels the overestimation problem of two semianalytical schemes, leading to an improvement in the ESM-like comparison. In the assessment of uncertainty due to the large time step of ESMs, it is found that the rainwater tendency simulated by the SCE is roughly linear for time steps smaller than 10 min, but the nonlinearity effect becomes significant for larger time steps, leading to errors up to a factor of 4 for a time step of 20 min. After considering all uncertainties, the grid-mean and time-averaged rainwater tendency based on the parameterization schemes is mostly within a factor of 4 of the local benchmark results simulated by SCE.

Meteorology & Atmospheric Sciences↗
DOE OSTI2016

Biosecurity through Public Health System Design.

We applied modeling and simulation to examine the real-world tradeoffs between developingcountry public-health improvement and the need to improve the identification, tracking, and security of agents with bio-weapons potential. Traditionally, the international community has applied facility-focused strategies for improving biosecurity and biosafety. This work examines how system-level assessments and improvements can foster biosecurity and biosafety. We modeled medical laboratory resources and capabilities to identify scenarios where biosurveillance goals are transparently aligned with public health needs, and resource are distributed in a way that maximizes their ability to serve patients while minimizing security a nd safety risks. Our modeling platform simulates key processes involved in healthcare system operation, such as sample collection, transport, and analysis at medical laboratories. The research reported here extends the prior art by provided two key compone nts for comparative performance assessment: a model of patient interaction dynamics, and the capability to perform uncertainty quantification. In addition, we have outlined a process for incorporating quantitative biosecurity and biosafety risk measures. Two test problems were used to exercise these research products examine (a) Systemic effects of technological innovation and (b) Right -sizing of laboratory networks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

ARM Cloud-Aerosol-Precipitation Experiment (ACAPEX) Field Campaign Report

The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility’s ARM Cloud-Aerosol-Precipitation Experiment (ACAPEX) field campaign contributes to CalWater 2015, a multi-agency field campaign that aims to improve understanding of atmospheric rivers and aerosol sources and transport that influence cloud and precipitation processes. The ultimate goal is to reduce uncertainties in weather predictions and climate projections of droughts and floods in California. With the DOE G-1 aircraft and ARM Mobile Facility 2 (AMF2) well equipped for making aerosol and cloud measurements, ACAPEX focuses specifically on understanding how aerosols from local pollution and long-range transport affect the amount and phase of precipitation associated with atmospheric rivers. ACAPEX took place between January 12, 2015 and March 8, 2015 as part of CalWater 2015, which included four aircraft (DOE G-1, National Oceanic and Atmospheric Administration [NOAA] G-IV and P-3, and National Aeronautics and Space Administration [NASA] ER-2), the NOAA research ship Ron Brown, carrying onboard the AMF2, National Science Foundation (NSF)-sponsored aerosol and precipitation measurements at Bodega Bay, and the California Department of Water Resources extreme precipitation network.

aerosol transport↗
DOE OSTI2022

Mechanisms of woody-plant mortality under rising drought, CO 2 and vapour pressure deficit

Drought-associated woody plant mortality may have increased over the past several decades, and is projected to increase in the future, impacting terrestrial climate forcing, biodiversity, and resource availability. The mechanisms underlying such mortality, however, are debated owing to interactions between multiple drivers and mechanisms. In this work, we synthesize knowledge of drought-related tree mortality under a warming and drying atmosphere with rising atmospheric CO 2 . Drought-associated mortality results from the depletion of pools of water and carbon within a plant and declines in their fluxes relative to demand by living tissues. These pools and fluxes are interdependent and underlay plant defenses against biotic agents. Death via failure to maintain a positive water balance is particularly dependent on soil-to-root conductance, capacitance, vulnerability to hydraulic failure, cuticular water losses, and dehydration tolerance, all of which could be exacerbated by reduced carbon supply rates to support cellular survival e.g. the carbon starvation process. The depletion of plant water and carbon pools accelerates under rising vapor pressure deficit; however, increasing CO 2 can mitigate these impacts. Advancing knowledge and reducing predictive uncertainties requires studies that integrate carbon, water, and defensive processes, and utilize a range of experimental and modeling approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

International Workshop on Comparing Ice Nucleation Measuring Systems 2014

The relationship of ambient aerosol particles to the formation of ice-containing clouds is one of the largest uncertainties in understanding the Earth’s climate. The uncertainty is due to several poorly understood processes and measurements including, but not limited to: (1) the microphysics of how particles nucleate ice, (2) the number of ice forming particles as a function of atmospheric properties such as temperature and relative humidity, (3) the atmospheric distribution of ice forming particles and (4) the role of anthropogenic activities in producing or changing the behavior of ice forming particles. The ways in which ice forming particles can impact climate is also multi-faceted. More ice forming particles can lead to clouds with more ice crystals and different optical properties than clouds with less ice forming particles. More effective ice forming particles can lead to ice at higher temperature and/or lower saturation, resulting in clouds at lower altitude or latitude which also changes the Earth’s radiative balance. Ice nucleation also initiates most of the Earth’s precipitation, even in the mid- and low-latitudes, since cloud-top temperatures are often below freezing. The limited measurements and lack of understanding directly translates to restrictions in our ability to model atmospheric ice formation and project changes into the future. The importance of ice nucleation research is further exemplified by Figure 1 which shows the publications per decade and citations per year on the topic of ice nucleation [DeMott et al., 2011]. After a lull at the end of the last century, there has been a dramatic increase in both publications and citations related to ice nucleation; this directly corresponds to the importance of ice nucleation on the Earth’s climate and the uncertainty in this area noted by the Solomon [2007].

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Perturbed Physics Ensemble Simulations of Cirrus on the Cloud System-resolving Scale

In this study, the effect of uncertainties in the parameterization of ice microphysical processes and initial conditions on the variability of cirrus microphysical and radiative properties are investigated in a series of cloud system-resolving perturbed physics ensemble (PPE) and initial condition ensemble (ICE) simulations. Three cirrus cases representative of mid-latitude, subtropical and tropical cirrus are examined. It is found that the variability in cirrus properties induced by perturbing uncertain parameters in ice microphysics parameterizations outweighs the variability induced by perturbing the initial conditions in midlatitude and subtropical cirrus. However, in tropical anvil cirrus the variability in the PPE and ICE simulations is about the same order of magnitude. The cirrus properties showing the largest sensitivity are ice water content (IWC) and cloud thickness whereas the averaged high cloud cover is only marginally affected. Changes in cirrus ice water path and outgoing longwave radiation are controlled primarily by changes in IWC and cloud thickness but not by changes is the averaged high cloud cover. The change in the vertical distribution of cloud fraction and cloud thickness is caused by changes in cirrus cloud base whereas cloud top is not sensitive to either perturbed physics or perturbed initial conditions. In all cirrus cases, the top three parameters controlling the microphysical variability and radiative impact of cirrus clouds are ice fall speeds, ice autoconversion size thresholds and heterogeneous ice nucleation. Changes in the ice deposition coefficient do not affect the ice water path and outgoing longwave radiation. Similarly, changes in the number concentration of aerosols available for homogeneous freezing have virtually no effect on the microphysical and radiative properties of midlatitude and subtropical cirrus but only little impact on tropical anvil cirrus. Overall, the sensitivity of cirrus microphysical and radiative properties to uncertainties in ice microphysics is largest for midlatitude cirrus and smallest for tropical anvil cirrus.

cirrus↗
DOE OSTI2016

System Modeling Techniques for PRA P-200

Course Objectives: Build PRA modeling and analysis skills – Event tree and fault tree model development – Dependent failures and common cause modeling – Component failure mechanisms, Improve understanding of quantification process, Improve ability to extract key results from a PRA, Greater familiarity with PRA goals and process, and Aleatory (stochastic) versus Epistemic (state of knowledge) uncertainty

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

The spectroscopic foundation of radiative forcing of climate by carbon dioxide

The radiative forcing (RF) of carbon dioxide (CO 2 ) is the leading contribution to climate change from anthropogenic activities. Calculating CO 2 RF requires detailed knowledge of spectral line parameters for thousands of infrared absorption lines. A reliable spectroscopic characterization of CO 2 forcing is critical to scientific and policy assessments of present climate and climate change. Our results show that CO 2 RF in a variety of atmospheres is remarkably insensitive to known uncertainties in the three main CO 2 spectroscopic parameters: the line shapes, line strengths, and half widths. We specifically examine uncertainty in RF due to line mixing as this process is critical in determining line shapes in the far wings of CO 2 absorption lines. RF computed with a Voigt line shape is also examined. Overall, the spectroscopic uncertainty in present-day CO 2 RF is less than 1%, indicating a robust foundation in our understanding of how rising CO 2 warms the climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

High-Temperature Sapphire Pressure Sensors for Harsh Environments

The project aimed to develop and characterize an optical pressure sensor capable of withstanding high temperatures, up to 1000 °C. Survivability in harsh environments was enabled using sapphire for both the substrate and the optical fibers, therefore mitigating thermal expansion mismatch. Such material cannot be machined through conventional microfabrication techniques, and unique additive and subtractive methods had to be studied and implemented. Subtractive methods included laser-machining the sapphire substrate using a picosecond laser machining tool. At first, the parameters of importance were theoretically and experimentally evaluated such that the fluence, the pulse spacing, and the number of passes were found to strongly influence the laser ablation process. A simulation tool was designed to predict the final pattern when inputting a set of parameters and a profile. This model was complemented with laser ablation material physics models and Bayesian uncertainty analysis for one dimensional and three dimensional ablation processes. An additive process called thermocompression bonding was studied in order to seal the diaphragm substrate to the back cavity. At first, bonding strength using this technique was examined using the chevron-notch method that allow to determine the fracture toughness of this bond. This parameter is independent of the geometry used and therefore can be extended to other geometries used in actual sensor bonding. A theoretical and experimental study of internal damage caused by the laser micromachining of the sapphire material was carried out. The research identified enhanced strength and fracture toughness along laser ablated surfaces. This was determined using bend bar specimens and Vicker’s microindentations. Softening of the plasticity behavior (as indicated by nanoindentation experiments) was also investigated using finite deformation plasticity modeling via a contact mechanics finite element simulation. Good correlations between experiments and the model were achieved to determine material parameters that can be used in future MEMS based sensor design and modeling to minimize sensor failure loads. The enhanced strength and fracture toughness was determined to be due to compressive residual stress near laser ablated surfaces. This was confirmed through x-ray spectra taken along different crystal structure planes in combination and Bayesian uncertainty analysis. The Bayesian analysis inferred the entire residual strain tensor (six components) and the residual stress tensor. The results illustrated compressive in-plane stress was the most likely cause of enhanced strength and toughness after laser machining. Due to major equipment failures, a parallel route for fabricating the sensor was taken, using commercially available sapphire removal method (subtractive) and ceramic adhesive bonding (additive). The fully-packaged sensor utilized laser micromachining for the sapphire substrate fabrication and was comprised only of high-temperature-compatible materials. Calibration tests of the sensor in both room-temperature and high-temperature plane-wave tubes showed good linearity and consistent frequency response, in the tested frequency range. The sensor also showed good thermal stability in tests up to 300 °C, proving the fiber-optic lever and its packaging process to be a promising approach for high-temperature measurements. The calibration from 23 °C to 300 °C gave a raw sensitivity of 3.9 × 10 -7 V/Pa and a normalized sensitivity of 9.8 × 10 -8 Pa -1 which were consistent within the temperature range. The sensor had a resonance at 16.3 kHz and a flat band (±3 dB) up to 10.3 kHz. The noise floor of the sensor at 1 kHz was 316 nV/Hz 1/2 , resulting in a MDP of 0.8 Pa. Previously, diaphragm delamination due to CTE mismatch was found at 500 °C, causing packaging failure. Unfortunately high temperature validation in hot jet environment could not be made in time. In the future, it is suggested that the two sapphire substrates be bonded by thermal compression bonding with an intermediate platinum layer instead of using an alumina-based adhesive, and therefore achieve higher temperature capacity up to 1000 °C.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Photocatalysis and Photoelectrocatalysis Methods of Nitrogen Reduction for Sustainable Ammonia Synthesis

Abstract Ammonia (NH 3 ) is one of the essential chemicals as a fertilizer and as a starting reagent for various chemicals with a production expectation of 200 million tonnes for 2018. With the development of renewable energy technologies such as hydrogen fuel cells, hydrogen also has emerged as an innovative clean energy source. Ammonia is a suitable hydrogen fuel carrier since a molecule of ammonia can carry up to three atoms of hydrogen. Recently, photochemical synthesis via nitrogen reduction has gained considerable attention as a sustainable method for the production of ammonia. The performance of the photoreduction of nitrogen lies in the developments of the photocatalysts and photoelectrocatalysts. Therefore, it is essential to understand the fundamentals of nitrogen reduction processes along with apprehending the challenges that limit the progress of catalysts. In this review, the basic understanding of photoreduction of nitrogen is highlighted, emphasizing on the challenges and effective methods to control defects, structures, and morphologies of materials for the catalyst development. The methods for ammonia detection and uncertainties in calculating the efficiency of the photochemical process are also addressed.

Ithisuphalap, Kemakorn↗
DOE OSTI2014

β-decay spectroscopy for the r-process nucleosynthesis

Series of decay spectroscopy experiments, utilizing of high-purity Ge detectors and double-sided silicon-strip detectors, have been conducted to harvest the decay properties of very exotic nuclei relevant to the r-process nucleosynthesis at the RIBF. The decay properties such as β-decay half-lives, low-lying states, β-delayed neutron emissions, isomeric states, and possibly Q{sub β} of the very neutron-rich nuclei are to be measured to give significant constraints in the uncertainties of nuclear properties for the r-process nucleosynthesis. Recent results of βγ spectroscopy study using in-flight fission of {sup 238}U-beam will be presented together with our future perspectives.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A Fortran–Python interface for integrating machine learning parameterization into earth system models

Abstract. Parameterizations in earth system models (ESMs) are subject to biases and uncertainties arising from subjective empirical assumptions and incomplete understanding of the underlying physical processes. Recently, the growing representational capability of machine learning (ML) in solving complex problems has spawned immense interests in climate science applications. Specifically, ML-based parameterizations have been developed to represent convection, radiation, and microphysics processes in ESMs by learning from observations or high-resolution simulations, which have the potential to improve the accuracies and alleviate the uncertainties. Previous works have developed some surrogate models for these processes using ML. These surrogate models need to be coupled with the dynamical core of ESMs to investigate the effectiveness and their performance in a coupled system. In this study, we present a novel Fortran–Python interface designed to seamlessly integrate ML parameterizations into ESMs. This interface showcases high versatility by supporting popular ML frameworks like PyTorch, TensorFlow, and scikit-learn. We demonstrate the interface's modularity and reusability through two cases: an ML trigger function for convection parameterization and an ML wildfire model. We conduct a comprehensive evaluation of memory usage and computational overhead resulting from the integration of Python codes into the Fortran ESMs. By leveraging this flexible interface, ML parameterizations can be effectively developed, tested, and integrated into ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Fortran-Python Interface for Integrating Machine Learning Parameterization into Earth System Models

Parameterizations in Earth System Models (ESMs) are subject to biases and uncertainties arising from subjective empirical assumptions and incomplete understanding of the underlying physical processes. Recently, the growing representational capability of machine learning (ML) in solving complex problems has spawned immense interests in climate science applications. Specifically, ML-based parameterizations have been developed to represent convection, radiation and microphysics processes in ESMs by learning from observations or high-resolution simulations, which have the potential to improve the accuracies and alleviate the uncertainties. Previous works have developed some surrogate models for these processes using ML. These surrogate models need to be coupled with the dynamical core of ESMs to investigate the effectiveness and their performance in a coupled system. In this study, we present a novel Fortran-Python interface designed to seamlessly integrate ML parameterizations into ESMs. This interface showcases high versatility by supporting popular ML frameworks like PyTorch, TensorFlow, and Scikit-learn. We demonstrate the interface's modularity and reusability through two cases: a ML trigger function for convection parameterization and a ML wildfire model. We conduct a comprehensive evaluation of memory usage and computational overhead resulting from the integration of Python codes into the Fortran ESMs. By leveraging this flexible interface, ML parameterizations can be effectively developed, tested, and integrated into ESMs.

54 ENVIRONMENTAL SCIENCES↗