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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Impact of model predictive control-enabled home energy management on large-scale distribution systems with photovoltaics

Residential customers use more than one-quarter of the electricity in the world. Optimally managing home energy consumption is an effective way of easing the operational challenges facing the electric grid with increasing solar photovoltaics (PV). This paper studies the impact of the future proliferation of home energy management systems (HEMS) in the presence of PV on large-scale distribution systems. First, we present a stochastic HEMS model that minimizes residential customers' thermal discomfort and energy costs under uncertainty. The HEMS model schedules the optimal operations of residential appliances in the presence of PV within a mixed-integer linear programming-based model predictive control framework that links the proposed HEMS to a quasi-steady-state time-series simulation tool. Additionally, extensive simulations are conducted for a stand-alone residential home using two tariff structures and for 1977 homes on an 8,500-node distribution feeder. Simulation results quantify the impact of the future proliferation of HEMS on the large-scale distribution system with PV.

14 SOLAR ENERGY↗
DOE OSTI2021

Modeling the impact of COVID-19 on air quality in southern California: implications for future control policies

Abstract. In response to the coronavirus disease of 2019 (COVID-19), California issued statewide stay-at-home orders, bringing about abrupt and dramatic reductions in air pollutant emissions. This crisis offers us an unprecedented opportunity to evaluate the effectiveness of emission reductions in terms of air quality. Here we use the Weather Research and Forecasting model with Chemistry (WRF-Chem) in combination with surface observations to study the impact of the COVID-19 lockdown measures on air quality in southern California. Based on activity level statistics and satellite observations, we estimate the sectoral emission changes during the lockdown. Due to the reduced emissions, the population-weighted concentrations of fine particulate matter (PM2.5) decrease by 15 % in southern California. The emission reductions contribute 68 % of the PM2.5 concentration decrease before and after the lockdown, while meteorology variations contribute the remaining 32 %. Among all chemical compositions, the PM2.5 concentration decrease due to emission reductions is dominated by nitrate and primary components. For O3 concentrations, the emission reductions cause a decrease in rural areas but an increase in urban areas; the increase can be offset by a 70 % emission reduction in anthropogenic volatile organic compounds (VOCs). These findings suggest that a strengthened control on primary PM2.5 emissions and a well-balanced control on nitrogen oxides and VOC emissions are needed to effectively and sustainably alleviate PM2.5 and O3 pollution in southern California.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Microphysical properties of atmospheric soot and organic particles: measurements, modeling, and impacts

Atmospheric soot and organic particles from fossil fuel combustion and biomass burning modify Earth’s climate through their interactions with solar radiation and through modifications of cloud properties by acting as cloud condensation nuclei and ice nucleating particles. Recent advancements in understanding their individual properties and microscopic composition have led to heightened interest in their microphysical properties. This review article provides an overview of current advanced microscopic measurements and offers insights into future avenues for studying microphysical properties of these particles. To quantify soot morphology and ageing, fractal dimension ( D f ) is a commonly employed quantitative metric which allows to characterize morphologies of soot aggregates and their modifications in relation to ageing factors like internal mixing state, core-shell structures, phase, and composition heterogeneity. Models have been developed to incorporate D f and mixing diversity metrics of aged soot particles, enabling quantitative assessment of their optical absorption and radiative forcing effects. The microphysical properties of soot and organic particles are complex and they are influenced by particle sources, ageing process, and meteorological conditions. Furthermore, soluble organic particles exhibit diverse forms and can engage in liquid–liquid phase separation with sulfate and nitrate components. Primary carbonaceous particles such as tar balls and soot warrant further attention due to their strong light absorbing properties, presence of toxic organic constituents, and small size, which can impact human health. Future research needs include both atmospheric measurements and modeling approaches, focusing on changes in the mixing structures of soot and organic particle ensembles, their effects on climate dynamics and human health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

OCEANFILMS (Organic Compounds from Ecosystems to Aerosols: Natural Films and Interfaces via Langmuir Molecular Surfactants) sea spray organic aerosol emissions – implementation in a global climate model and impacts on clouds

Sea spray aerosol is one of the major sources of atmospheric particulate matter globally. It has increasingly been recognized that organic matter derived from ocean biological precursors contributes significantly to the composition of submicron sea spray and may modify sea spray aerosol impacts on clouds and climate. This paper describes the implementation of the OCEANFILMS (Organic Compounds from Ecosystems to Aerosols: Natural Films and Interfaces via Langmuir Molecular Surfactants) parameterization for sea spray organic aerosol emissions in a global Earth system model, the Energy Exascale Earth System Model (E3SM). OCEANFILMS is a physically based model that links sea spray chemistry with ocean biogeochemistry using a Langmuir partitioning approach. We describe the implementation details of OCEANFILMS within E3SM, compare simulated aerosol fields with observations, and investigate impacts on simulated clouds and climate. Four sensitivity cases are tested, in which organic emissions either strictly add to or strictly replace sea salt emissions (in mass and number) and are either fully internally or fully externally mixed with sea salt. The simulation with internally mixed, added organics agrees reasonably well with observed seasonal cycles of organic matter in marine aerosol and has been selected as the default configuration of the E3SM. In this configuration, sea spray organic aerosol contributes an additional source of cloud condensation nuclei, adding up to 30 cm -3 to Southern Ocean boundary-layer cloud condensation nuclei concentrations (supersaturation = 0.1 %). The addition of this new aerosol source strengthens shortwave radiative cooling by clouds by -0.36 W m -2 in the global annual mean and contributes more than -3.5 W m -2 to summertime zonal mean cloud forcing in the Southern Ocean, with maximum zonal mean impacts of about -4 W m -2 around 50–60°S. This is consistent with a previous top-down, satellite-based empirical estimate of the radiative forcing by sea spray organic aerosol over the Southern Ocean. Through its mechanistic approach, OCEANFILMS offers a path towards improved understanding of the feedbacks between ocean biology, sea spray organic matter, and climate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Community-Informed Urban Flood Modeling for Impact Mitigation

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

Baltimore MD↗
DOE OSTI2025

Modeling the impact of extreme weather events and future climate on the radiologically contaminated sites of Enewetak Atoll

Enewetak Atoll underwent 43 historical nuclear tests from 1948 to 1958, including the first hydrogen bomb test, resulting in a substantial nuclear material fallout contaminating the Atoll and the lagoon waters. The radionuclide fallout material deposited in lagoon sediments and land soil will remain for decades to come. With intensifying climate and extreme weather events, the possibility of redistribution of deposited radionuclide material has become a great concern. This study uses a numerical modeling approach to estimate the potential elevated radionuclide concentrations that can be distributed during storm events under current and future climates. We simulated three historical storm scenarios that are most likely to impact Atoll’s environment and remobilize the radionuclide-bound sediments. WRF-ARW was used to reconstruct these storm scenarios under current year (2015) and future year (2090) climates. Storm-induced ocean hydrodynamics conditions were generated using FVCOM. FVCOM-ICM was externally coupled to simulate the fate and transport of radionuclides. Given that the 239 Pu is the largest inventory of the lagoon and Atoll islands, the model results show the highest average 239 Pu concentration that an island may be exposed to is 3.25E-4 Bq/m 3 (becquerel per cubic meters), which is an increase of 84 times the average baseline/existing 239 Pu concentration without the storm conditions. The overall increase in 239 Pu average over all the islands of Atoll is about 20 folds relative to the baseline concentration. Despite the high relative increase ratios, the significantly low activity concentrations may not pose an immediate exposure risk. However, due to the limitations of the study and uncertainties/biases in the historical data used, further research supported by field surveys to better characterize the current contamination level may be needed to make more accurate predictions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Modeling Weather Impact on Ground Delay Programs

Scheduled arriving aircraft demand may exceed airport arrival capacity when there is abnormal weather at an airport. In such situations, Federal Aviation Administration (FAA) institutes ground-delay programs (GDP) to delay flights before they depart from their originating airports. Efficient GDP planning depends on the accuracy of prediction of airport capacity and demand in the presence of uncertainties in weather forecast. This paper presents a study of the impact of dynamic airport surface weather on GDPs. Using the National Traffic Management Log, effect of weather conditions on the characteristics of GDP events at selected busy airports is investigated. Two machine learning methods are used to generate models that map the airport operational conditions and weather information to issued GDP parameters and results of validation tests are described.

Wang, Yao↗
DOE OSTI2025

Modeling the impact of smoke from prescribed fire on road visibility

Prescribed fires are planned to achieve conservation and fuel reduction objectives while minimizing smoke ground concentration to limit health impacts and road visibility impairment. Prescribed burns cannot indeed be conducted if those hazards are not within predefined limits. This paper proposes a new framework to evaluate road visibility that overcomes the limitation of the state of the art model, VSMOKE. The framework leverages the fast-running framework QUIC-Fire/QUIC-SMOKE to capture fire and smoke dynamics, and the timing and duration of hazardous conditions on the road network close to the burn unit (within 50–100 km). The paper presents parametric study using a real burn plot at Fort Stewart (GA, USA), under hypothetical wind conditions to understand the interplay between buoyancy and smoke dilution. Here, results showed that faster winds caused fire escape while slower winds did not achieve a complete burn. Furthermore, faster winds featured brief road visibility reduction below braking distance.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

The Impact of Model Configuration and Large-Scale, Upper-Level Forcing on CRM- Simulated Convective Systems

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D, see a brief review by Tao 2003). Only recently have 3D experiments been performed for multi-day periods for tropical cloud systems with large horizontal domains at the National Center for Atmospheric Research, at NOAA GFDL, at the U. K. Met. Office, at Colorado State University and at NASA Goddard Space Flight Center (Tao 2003). At Goddard, a 3D Goddard Cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE (December 19-27, 1992), GATE (September 1-7, 1974), SCSMEX (June 2-11, 1998), ARM (June 26-30, 1997) and KWAJEX (August 7-13, August 18-21, and August 29-September 12, 1999) using a 512 by 512 km domain (with 2-km resolution). The results indicate that surface precipitation and latent heating profiles are similar between the 2D and 3D GCE model simulations. However, there are difference in radiation, surface fluxes and precipitation characteristics. The 2D GCE model was used to perform a long-term integration on ARM/GCSS case 4 (22 days at the ARM Southern Great Plains site in March 2000). Preliminary results showed a large temperature bias in the upper troposphere that had not been seen in previous tropical cases. The major objectives of this paper are: (1) to determine the sensitivities to model configuration (i.e., 2D in west-east, south-north or 3D), (2) to identify the differences and similarities in the organization and entrainment rates of convection between 2D- and 3D-simulated ARM cloud systems, and (3) assess the impact of upper tropospheric forcing on tropical and ARM case 4 cases.

Tao, W.-K.↗
NASA NTRS2004

The Impact of Model Configuration and Large-Scale, Upper-Level Forcing on CRM-Simulated Convective Systems

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D, see a brief review by Tao 2003). Only recently have 3D experiments been performed for multi-day periods for tropical cloud systems with large horizontal domains at the National Center for Atmospheric Research, at NOAA GFDL, at the U. K. Met. Office, at Colorado State University and at NASA Goddard Space Flight Center (Tao 2003). At Goddard, a 3D Goddard Cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE (December 19-27, 1992), GATE (September 1-7, 1974), SCSMEX (June 2-11, 1998), ARM (June 26-30, 1997) and KWAJEX (August 7-13, August 18-21, and August 29-September 12, 1999) using a 512 km domain (with 2-kilometer resolution). The results indicate that surface precipitation and latent heating profiles are similar between the 2D and 3D GCE model simulations. However, there are difference in radiation, surface fluxes and precipitation characteristics. The 2D GCE model was used to perform a long-term integration on ARM/GCSS case 4 (22 days at the ARM southern Great Plains site in March 2000). Preliminary results showed a large temperature bias in the upper troposphere that had not been seen in previous tropical cases. The major objectives of this paper are: (1) to determine the sensitivities to model configuration (ie., 2D in west-east, south-north or 3D), (2) to identify the differences and similarities in the organization and entrainment rates of convection between 2D- and 3D-simulated ARM cloud systems, and (3) assess the impact of upper tropospheric forcing on tropical and ARM case 4 cases.

Tao, W.-K.↗
DOE OSTI2021

Multi-cyclone analysis and machine learning model implications of cyclone effects on forests

Past studies of cyclones (hurricanes, typhoons, tropical cyclones) disturbance showed that meteorological, topographical, and biological factors affect the patterns of forest disturbance intensity but left open the extent to which these findings were representative across different global cyclone regions. Using remote sensing data and machine learning models, we examined how these factors change over spatial scales and assessed their consistency across four major cyclones: Katrina (August 2005), Rita (September 2005), Yasi (February 2011), and María (September 2017). Our results revealed that the factors which best explained forest disturbance intensity pattern varied across these regions. Wind speed and precipitation were the dominant factors contributing to the variation in impacts of Katrina; terrain features, especially elevation, explained most of the variation in disturbance intensity of Rita; pre-disturbance vegetation condition was significant predictors of effects of Yasi; these factors played equal roles in explaining the disturbance intensity variation of María. A 40 m/s (144 km/h) wind speed threshold was proposed to split low- and high-level forest disturbance intensity. Other than wind speed, few generalizations can be made on features across multiple regions. We built several generalized hurricane impact models, which worked well with the test data from cyclones used for model development (R 2 = 0.89). However, these models did not have good predictions on other cyclones, such as Michael (October 2018) and Laura (August 2020). This study showed that each cyclone interacted with the landscape in a unique way and the challenges remained in building a generalized cyclone impact model.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Popigai Impact Structure Modeling: Morphology and Worldwide Ejecta

The approx. 100 km in diameter, 35.7 0.2 Ma old Popigai structure [1], northern Siberia (Russia), is the best-preserved of the large terrestrial complex crater structures containing a central-peak ring [2- 4]. Although remotely located, the excellent outcrops, large number of drill cores, and wealth of geochemical data make Popigai ideal for the general study of the cratering processes. It is most famous for its impact-diamonds [2,5]. Popigai is the best candidate for the source crater of the worldwide late Eocene ejecta [6,7].

Ivanov, B. A.↗
DOE OSTI2020

Impact of ocean model resolution on understanding the delayed warming of the Southern Ocean

Abstract Currently available historical climate change simulations indicate a relatively delayed Southern Ocean warming, particularly poleward of the Antarctic Circumpolar Current (ACC) compared much of the rest of the globe. However, even this simulated delayed warming is inconsistent with observational estimates which show a cooling trend poleward of the ACC for the period 1979–2014. A fully coupled model run at two resolutions, i.e. ocean eddy parameterized and ocean eddy resolving, driven by historical and fixed CO2 concentration is used to investigate forced trends south of the ACC. We analyze the 1961–2005 Southern Ocean surface and upper ocean temperatures trends simulated by the model and observational estimates to understand the observed trends in the SO. At both resolutions, the models successfully reproduce the observed warming response for the northern flank of the ACC. The eddy resolving simulations, however, are able to reproduce the observed near Antarctic cooling in contrast to the eddy parameterized simulation which shows a warming trend. The cause of this inconsistency between the observations and the ocean eddy parameterized climate models is still a matter of debate, and we show here results that suggest resolved ocean meso-scale processes may be an integral part of capturing the observed trends in the Southern Ocean.

Environmental Sciences & Ecology↗
DOE OSTI2025

Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts

Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here, in this work, we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.

catalytic mechanisms↗
DOE OSTI2020

Impact of Model Resolution on Tropical Cyclone Simulation Using the HighResMIP–PRIMAVERA Multimodel Ensemble

A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ~0.5 to ~0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modeling the Impact of Riparian Hollows on River Corridor Nitrogen Exports

Recent studies in snowmelt-dominated catchments have documented changes in nitrogen (N) retention over time, such as declines in watershed exports of N, though there is a limited understanding of the controlling processes driving these trends. Working in the mountainous headwater East River Colorado watershed, we explored the effects of riparian hollows as N-cycling hotspots and as important small-scale controls on observed watershed trends. Using a modeling-based approach informed by remote sensing and in situ observations, we simulated the N-retention capacity of riparian hollows with seasonal and yearly hydrobiogeochemical perturbations imposed as drivers. We then implemented a scaling approach to quantify the relative contribution of riparian hollows to the total river corridor N budget. We found that riparian hollows primarily serve as N sinks, with N-transformation rates significantly limited by periods of enhanced groundwater upwelling and promoted at the onset of rainfall events. Given these observed hydrologic controls, we expect that the nitrate ( NO 3 - ) sink capacity of riparian hollows will increase in magnitude with future climatic perturbations, specifically the shift to more frequent rainfall events and fewer snowmelt events, as projected for many mountainous headwater catchments. Our current estimates suggest that while riparian hollows provision ~5–20% of NO 3 - to the river network, they functionally act as inhibitors to upland NO 3 - reaching the stream. Our work linking transient hydrological conditions to numerical biogeochemical simulations is an important step in assessing N-retaining features relative to the watershed N budget and better understanding the role of small-scale features within watersheds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development: Executive summary

A cross impact model of the U.S. telecommunications system was developed. For this model, it was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impacts). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics, throughout the telecommunications system.

Martino, J. P.↗
NASA NTRS2010

Modeling the Impact of Space Suit Components and Anthropometry on the Center of Mass of a Seated Crewmember

The Crew Impact Attenuation System (CIAS) is the energy-absorbing strut concept that dampens Orion Crew Exploration Vehicle (CEV) landing loads to levels sustainable by the crew. Significant COM variations across suited crew configurations would amplify the inertial effects of the pallet and potentially create unacceptable crew loading during launch and landing. The objective of this study was to obtain data needed for dynamic simulation models by quantifying the effects of posture, suit components, and the expected range of anthropometry on the COM of a seated individual. Several elements are required for the COM calculation of a suited human in a seated position: anthropometry, body segment mass, suit component mass, suit component location relative to the body, and joint angles defining the seated posture. Three-dimensional (3D) human body models, suit mass data, and vector calculus were utilized to compute the COM positions for 12 boundary manikins in two different seated postures. The analysis focused on two objectives: (1) quantify how much the wholebody COM varied from the smallest to largest subject and (2) quantify the effects of the suit components on the overall COM in each seat configuration. The location of the anterior-posterior COM varied across all boundary manikins by about 7 cm, and the vertical COM varied by approximately 9 to 10 cm. The mediolateral COM varied by 1.2 cm from the midline sagittal plane for both seat configurations. The suit components caused an anterior shift of the total COM by approximately 2 cm and a shift to the right along the mediolateral axis of 0.4 cm for both seat configurations. When the seat configuration was in the standard posture the suited vertical COM shifted inferiorly by as much as 1 cm, whereas in the CEV posture the vertical COM had no appreciable change. These general differences were due to the high proportion of suit mass located in the boots and lower legs and their corresponding distance from the body COM, as well as to the prevalence of suit components on the right side of the body.

Blackledge, Christopher↗