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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Noachian Impact Ejecta on Murray Ridge and Pre-impact Rocks on Wdowiak Ridge, Endeavour Crater, Mars: Opportunity Observations

Mars Exploration Rover Opportunity has been exploring Meridiani Planum since January 2004, and has completed 4227% of its primary mission. Opportunity has been investigating the geology of the rim of 22 km diameter Endeavour crater, first on the Cape York segment and now on Cape Tribulation. The outcrops are divided York; (ii) the Shoemaker fm, impact breccias representing ejecta from the crater; into three formations: (i) the lower Matijevic fm, a pre-impact lithology on Cape and (iii) the upper Grasberg fm, a post-impact deposit that drapes the lower portions of the eroded rim segments. On the Cape Tribulation segment Opportunity has been studying the rocks on Murray Ridge, with a brief sojourn to Wdowiak Ridge west of the rim segment. team member Thomas Wdowiak, who died in 2013.) One region of Murray Ridge has distinctive CRISM spectral characteristics indicating the presence of a small concentration of aluminous smectite based on a 2.2 micron Al-OH combination band (hereafter, the Al-OH region).

Mittlefehldt, D. W.↗
NASA NTRS2017

Radiative Impacts of Further Arctic Sea Ice Melt: Using past Observations to Inform Future Climate Impacts

The Arctic region has seen dramatic changes over the past several decades, from polar amplification of global temperature rise to ecosystem changes to the decline of the sea ice. While there has been much speculation as to when the world will see an ice-free Arctic, the radiative impacts of an eventual disappearance of the Arctic sea ice are likely to be significant regardless of the timing. Using CERES radiation and microwave satellite sea ice data, Pistone et al (2014) estimated the radiative forcing due to albedo changes associated with the Arctic sea ice retreat over the 30 years of the satellite data record. In this study, we found that the Arctic Ocean saw a decrease in all-sky albedo of 4% (from 52% to 48%), for an estimated increase in solar heating of 6.4 W/m(exp 2) between 1979 and 2011, or 0.21 W/m(exp 2) when averaged over the globe. This value is substantial--approximately 25% as large as the forcing due to the change in CO2 during the same period. Here we update and expand upon this previous work and use the CERES broadband shortwave observations to explore the radiative impacts of a transition to completely ice-free Arctic Ocean. We estimate the annually-averaged Arctic Ocean planetary albedo under ice-free and cloud-free conditions to be 14% over the region, or approximately 25% lower in absolute terms than the Arctic Ocean cloud-free albedo in 1979. However, the question of all-sky conditions (i.e. including the effects of clouds) introduces a new level of complexity. We explore several cloud scenarios and the resultant impact on albedo. In each of these cases, the estimated forcing is not uniformly distributed throughout the year. We describe the relative contributions of ice loss by month as well as the spatial distributions of the resulting changes in absorbed solar energy. The seasonal timing and location—in addition to magnitude—of the altered solar absorption may have significant implications for atmospheric and ocean dynamics in the Arctic and at lower latitudes; this observationally-based estimate of the large-scale characteristics of an ice-free Arctic thus provides a valuable tool to complement and validate model-based assessments of future climate.

Pistone, K.↗
NASA NTRS2019

PDC19 Impact Exercise: Probabilistic Asteroid Impact Risk Assessment

Probabilistic Asteroid Impact Risk (PAIR) - PDC (Planetary Defense Conference) 2019 Hypothetical Exercise, NASA Ames, Asteroid Threat Assessment Project (ATAP) - Characterization Summary and Updates: Assessment date: 19 April 2027; Impact date: 29 April 2027 (10 days); Earth impact probability: 100 percent, New York Area; Diameter (meters): 60 plus or minus 10 (1 minus sigma), range 26–93; Energy: mean 11 megatons, range 650 kilotons to 46 megatons; Type: S class, remaining chunk of disrupted contact binary. Risk Summary: Affected population: mean 2.4 million, range zero to 10.2 million; Likely airburst at approximately16 kilometers altitude (8 to 29 kilometers); Blast overpressure is primary hazard; Damage out to approximately 70 kilometers if larger, lower burst; Little-to-no damage if burst is small and high.

Wheeler, Lorien↗
DOE OSTI2024

Simulated plant-mediated oxygen input has strong impacts on fine-scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands

Methane (CH 4 ) emissions from wetland ecosystems are controlled by redox conditions in the soil, which are currently underrepresented in Earth system models. Plant-mediated radial oxygen loss (ROL) can increase soil O 2 availability, affect local redox conditions, and cause heterogeneous distribution of redox-sensitive chemical species at the root scale, which would affect CH 4 emissions integrated over larger scales. In this study, we used a subsurface geochemical simulator (PFLOTRAN) to quantify the effects of incorporating either spatially homogeneous ROL or more complex heterogeneous ROL on model predictions of porewater solute concentration depth profiles (dissolved organic carbon, methane, sulfate, sulfide) and column integrated CH 4 fluxes for a tidal coastal wetland. From the heterogeneous ROL simulation, we obtained 18% higher column averaged CH 4 concentration at the rooting zone but 5% lower total CH 4 flux compared to simulations of the homogeneous ROL or without ROL. This difference is because lower CH 4 concentrations occurred in the same rhizosphere volume that was directly connected with plant-mediated transport of CH 4 from the rooting zone to the atmosphere. Sensitivity analysis indicated that the impacts of heterogeneous ROL on model predictions of porewater oxygen and sulfide concentrations will be more important under conditions of higher ROL fluxes or more heterogeneous root distribution (lower root densities). Despite the small impact on predicted CH 4 emissions, the simulated ROL drastically reduced porewater concentrations of sulfide, an effective phytotoxin, indicating that incorporating ROL combined with sulfur cycling into ecosystem models could potentially improve predictions of plant productivity in coastal wetland ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multiscale Effects Masked the Impact of the COVID-19 Pandemic on Electricity Demand in the United States

Shelter-in-place orders and business closures related to COVID-19 changed the hourly profile of electricity demand and created an unprecedented source of uncertainty for the grid. The potential for continued shifts in electricity profiles has implications for electricity sector investment and operating decisions that maintain reserve margins and provide grid reliability. This study reveals that understanding this uncertainty requires an understanding of the underlying drivers at the customer-class scale. This paper utilizes three datasets to compare the impacts of COVID-19 on electricity consumption across a range of spatiotemporal and customer scales. At the utility/customer-class scale, COVID-19-induced shutdowns in the spring of 2020 shifted weekday residential load profiles to resemble weekend profiles from previous years. Total commercial loads declined, but the commercial diurnal load profile was unchanged. With only total loads available at the balancing authority scale, the apparent impact of COVID-19 was smaller during the summer due in part to phased re-opening and spatial variability in re-opening, but there were still clear variations once total loads were broken down zonally. Monthly data at the state scale showed an increase in state-level residential electricity sales, a decrease in commercial sales, and a small net decrease in total sales in most states from April-August 2020. Analyses that focus on total load or a single scale may miss important changes that become apparent when the load is broken down regionally or by customer class.

COVID-19, electricity demand, multiscale, Commonwe↗
DOE OSTI2024

Implementation of new mixture rules has a substantial impact on combustion predictions for H 2 and NH 3

Complex-forming reactions comprise a substantial fraction of all important combustion reactions and are central to combustion behavior. Despite being often called “pressure-dependent” reactions, their rate constants depend on not only the pressure but also the composition. While modern combustion codes allow arbitrarily high accuracy in treating pressure dependence, recent work has consistently demonstrated dramatic failures of essentially all available treatments of mixture dependence. In situations where mixture dependence is treated at all, it is inevitably treated through specification of pressure-dependent rate constants for a set of pure bath gases, which are then combined to estimate the rate constant in a mixture via a “mixture rule.” While there had been a generally unquestioning confidence in these mixture rules, they had, in reality, been scarcely tested until the last decade, when comparisons against master equation calculations revealed order-of-magnitude errors for important pressure-dependent reactions. New mixture rules, based on the reduced pressure, have recently been proposed and shown to reproduce master equation calculations for broad classes of complex-forming reactions very accurately. Here, in this work, we present an implementation of one such new mixture rule (“LMR-R”) in Cantera and then use it to enable simulations that use new high-accuracy ab initio data for individual bath gases (for the first time, since codes previously could not accommodate the complex bath gas dependence). Demonstrations focus on combustion of H 2 and NH 3 , where (1) high-accuracy ab initio data are available and (2) the impact is expected to be large due to the high fractions of efficient colliders (e.g., H 2 O and NH 3 ) in the burned and unburned gases. Indeed, we find the impact of this treatment to be substantial and may explain previous modeling difficulties for these important carbon-free fuels, particularly for NH 3 , whose extraordinarily high third-body efficiency (~20) is often omitted from kinetic models.

Ammonia↗
DOE OSTI2025

Getting brighter: Impacts of improved day-ahead solar forecasts in high-solar, high-storage electricity systems

This paper analyzes the impacts of improved day-ahead solar forecasts on costs and dispatch in the solar-rich Southeast U.S. It uses an optimized high-solar, high-storage resource portfolio in which solar generation capacity accounts for 45 % of total installed capacity (34 %–36 % of generation) and energy storage capacity (43 GW) is equivalent to 33 % of peak demand. In a base scenario, improved day-ahead solar forecasts reduce production costs by $\$87$ million per year ($\$0.13$ per MWh load, $2023$$). This level of savings is within the range or lower than earlier studies of solar forecast improvements at lower levels of solar generation (<25 % of total generation). In this study, solar expansion was accompanied by two important sources of flexibility for managing solar forecast error: energy storage and day-ahead solar curtailment. Furthermore, the analysis finds that regional coordination complements day-ahead solar forecast improvements while natural gas commitment flexibility is a substitute for forecast improvements, as the improved solar forecast leads to sub-optimal commitment of thermal units. Day-ahead solar forecast improvements reduce reserves required to manage forecast error by 30 %. Fewer reserves to manage large, infrequent solar forecast errors could be an important benefit of improved solar forecasts.

14 SOLAR ENERGY↗
DOE OSTI2021

Characterizing Impacts of Storage Faults on HPC Applications: A methodology and insights

In recent years, the increasing complexity in scientific simulations and emerging demands for training heavy artificial intelligence models require massive and fast data accesses, which urges high-performance computing (HPC) platforms to equip with more advanced storage infrastructures such as solid-state disks (SSDs). While SSDs offer high-performance I/O, it remains unclear about the reliability challenges faced by the HPC applications under the SSD-related failures, in particular, failures resulting in data corruptions. The goal of this paper is to understand the impact of SSD-related data corruptions on the behaviors of complex HPC applications. To this end, we propose FFIS, a FUSE-based fault injection framework that systematically introduces storage faults into the application layer to model the errors originated from SSDs. FFIS is able to plant different I/O related faults into the data returned from underlying file systems, which also enables the investigation on the error resilience characteristics of the scientific file format for the first time. We demonstrate the use of FFIS with three representative real HPC applications, show how each application reacts to the data corruptions, and provide insights on the error resilience of the widely-adopted HDF5 file format for the HPC applications.

Fang, Bo↗
DOE OSTI2023

Impact of Detailed Parameter Modeling of Open-Cycle Gas Turbines on Production Cost Simulation: Preprint

Flexible resources are increasingly important as variable renewable energy deployment in the power system increases. Although many systems are transitioning away from fossil fuels, open-cycle gas turbines are likely to play an important balancing role for some time, thus requiring accurate modeling of their operational parameters. This paper explores the impact of detailed representation of three operational parameters - start- up costs, run-up rates, and forced outage rates - in the production cost model of a system as it adopts higher levels of wind and solar. Using PLEXOS simulations of the NREL-118 bus test system, the study examines how more detailed parameter modeling affects outcomes such as the number of start-ups and shutdowns, ramping and total generation costs for open-cycle gas turbines, as renewable energy levels increase. The results suggest the value of detailed parameter modeling and continued research on combustion turbines' ability to provide flexibility.

economic dispatch↗
DOE OSTI2022

Impact of Timing in the Design Process on Students’ Application of Design for Additive Manufacturing Heuristics

The goal of this work is to study the way student designers use design for additive manufacturing (DfAM) rules or heuristics. It can be challenging for novice designers to create successful designs for additive manufacturing (AM), due to its recent surge in popularity and lack of formal education or training. A study was carried out to investigate the way novices apply DfAM heuristics when they receive them at different points in the design process. A design problem was presented to students, and three different groups of student participants were given a lecture on DfAM heuristics at three different points in the design process: before the initial design, between the initial design and redesign, and after the redesign. The novelty and quality of each of the resulting designs were evaluated. Results indicate that although the DfAM heuristics lecture had no impact on the overall quality of the designs generated, participants who were given the heuristics lecture after the initial design session produced designs that were better-suited for 3D printing in the second phase of the design activity. However, receiving this additional information appears to prevent students from creatively iterating upon their initial designs, as participants who received heuristic information between the design sessions experienced a decrease in novelty between the two sessions. Additionally, receiving the heuristics lecture increased all students’ perceptions of their ability to perform DfAM-related tasks. Furthermore, these results validate the practicality of design heuristics in lecture form as AM training tools while also emphasizing the importance of iteration in the design process.

computer-aided design↗
DOE OSTI2024

Response of Graphite to Dynamic Loading and Hypervelocity Jet Impacts

The compressive strengths of three varieties of high purity graphite, PCEA, NBG-18, and NBG-25, as well as the depth of penetration of small-scale charges into these materials was experimentally determined. These grades are similar in density, ranging from 1.80 – 1.85 g/cc, and nominal apparent porosity, ranging from 18% to 20%, but provide a wide range in maximum grain or particle size from 10s to 1000s of µm. Two very different manufacturing methods are also represented; PCEA is extruded while NBG-18 and NBG-25 are iso-molded. The quasistatic and dynamic strengths of each grade were determined on a load frame and split-Hopkinson pressure bar, respectively. The depth of penetration (DOP) of two small-scale shaped charges, the Teledyne RP-1 and RP-4, was determined against graphite. The global response of the RP-4 impacts was markedly different as the PCEA samples remained intact while all the NBG-25 samples split into 2 or 3 pieces after the jet penetration had completed. However, for all tests, the trusted DOPs fell within 2 cm. Preliminary hydrocode modeling of the penetration events used existing models that were not designed for graphite. The results can be tuned to reasonably reproduce the DOP, but the wound channel geometry is not reproduced well. A model designed for graphite would need to represent graphite’s non-linear and energy dissipation characteristics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Emissions and Energy Impacts of the Inflation Reduction Act

If goals set under the Paris Agreement are met, the world may hold warming well below 2 degrees C (1); however, parties are not on track to deliver these commitments (2), increasing focus on policy implementation to close the gap between ambition and action. Recently, the US government passed its most prominent piece of climate legislation to date - the Inflation Reduction Act of 2022 (IRA) - designed to invest in a wide range of programs that, among other provisions, incentivize clean energy and carbon management, encourage electrification and efficiency measures, reduce methane emissions, promote domestic supply chains, and address environmental justice concerns (3). IRA's scope and complexity make modeling important to understand impacts on emissions and energy systems. We leverage results from nine independent, state-of-the-art models to examine potential implications of key IRA provisions, showing economy-wide emissions reductions between 43 and 48% below 2005 levels by 2035.

electricity↗
DOE OSTI2023

Understanding the Computing and Analysis Needs for Resiliency of Power Systems from Severe Weather Impacts

As the frequency and intensity of severe weather has increased, its effect on the electric grid has manifested in the form of significantly more and larger outages in the United States. This has become especially true for regions that were previously isolated from weather extremes. In this paper, we analyze the weather impacts on the electric power grid across a variety of weather conditions, draw correlations, and provide practical insights into the operational state of these systems. High resolution computational modeling of specific meteorological variables, computational approaches to solving power system models under these conditions, and the types of resiliency needs are highlighted as goal-oriented computing approaches are being built to address grid resiliency needs. An example analysis correlating outages to 1km day-ahead weather from two historical winter storms, calculated on a large cluster using a combination of interpolated and extrapolated inputs from multiple instrumented sites to workflows that produce primary meteorological outputs, is shown as initial proof of concept.

analysis↗
DOE OSTI2021

Potassium-Containing α-MnO 2 Nanotubes: The Impact of Hollow Regions on Electrochemistry

α-MnO 2 type materials have been studied as electrode materials in rechargeable batteries and electrocatalysts due to their 2 × 2 tunneled crystal structures capable of accommodating cations and their tunable physiochemical properties. In this study, we deliberately synthesized K + containing α-MnO 2 (K 0.9 Mn 8 O 16 ) hollow nanotubes varying the dimensions of the hollow regions and level of surface defects. The K 0.9 Mn 8 O 16 nanotube material samples have similar crystallinity, thermal stability, and average Mn oxidation state. Oxygen surface defects in the hollow regions were revealed through detailed studies using electron energy loss spectroscopy. The impact of the hollow regions and associated surface defects on the electrochemistry of K x Mn 8 O 16 were investigated using cyclic voltammetry, galvanostatic intermittent titration technique, and galvanostatic cycling. The K 0.9 Mn 8 O 16 nanotubes with a large hollow region (~30 nm) and higher level of surface defects show higher apparent lithium ion diffusion coefficients and lower polarization compared to the nanotubes with a small hollow region (~10 nm). In-situ lithiation demonstrated that the dimensions of the nanotube walls expanded, but the hollow region did not change in size as result of lithiation. Furthermore, this research demonstrates that tuning particle architecture and surface defects can positively impact functional behavior of electrochemical storage materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Dataset for scientific paper "Simulated plant‑mediated oxygen input has strong impacts on fine‑scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands", a modeling study based on field observation at the tidal salt marshes of the Parker River Estuary, Massachusetts, United States

This dataset is the raw and processed data for the paper "Simulated plant ‑ mediated oxygen input has strong impacts on fine ‑ scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands". This study investigated how plant-mediated oxygen input affects subsurface biogeochemical reactions of organic carbon degradation and the resulting methane emissions of coastal wetlands by model simulation. We used the subsurface geochemical simulator PFLOTRAN for the modeling, which produced the simulated changes in porewater chemical substances and methane emissions over 10 days under different scenarios of plant-mediated oxygen input.Specifically, this dataset contains: 1) the input files for PFLOTRAN of all simulation runs conducted in this study. Those files are with an extension of ".in", containing information of the biogeochemical reaction network (stoichiometry, reaction rate, Monod constants, etc), fluid flow rate and oxygen concentration in the fluid which together simulated the plant-mediated oxygen input, the configuration of artificial reactions that simulated the methane fluxes, etc. The PFLOTRAN input files are text files, which can be opened by NotePad, but running these input files will require proper installation of PFLOTRAN (instruction: https://documentation.pflotran.org/user_guide/how_to/installation/installation.html). 2) the raw and processed model output from PFLOTRAN of all simulation runs, and 3) the python scripts used to process the raw model output, including random allocation of root cells, converting raw data into organized formats, calculating the methane fluxes based on the model output, data visualization, etc. The raw and processed model output from PFLOTRAN are in .spydata format, which can be viewed with Python. and 3) the python scripts for data processing and analysis are programming scripts, which can be opened with Python.This modeling work, in particular the model parameterization of root density and initial conditions of porewater concentrations of biogeochemical substances, was based on field measurements at the salt marsh of the Upper Parker River Estuary, Massachusetts, United States.

54 ENVIRONMENTAL SCIENCES↗