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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Impact of Cirrus Crystal Shape on Solar Spectral Irradiance: A Case Study for Subtropical Cirrus

Profiles of in situ measurements of ice crystal size distribution of subtropical cirrus were used to calculate solar spectral irradiances above and below the clouds. Spheres and nonspherical ice crystal habits (columns, hollows, plates, bullets, and aggregates) were assumed in the calculations. The simulation results were compared to irradiance measurements from the NASA Solar Spectral Flux Radiometer. The microphysical and radiation data were collected by three aircraft during CRYSTAL-FACE. Two cirrus cases (optical thickness of about 1 and 7) from two mission dates (26 and 23 July 2002) were investigated in detail. The measured downwelling and upwelling irradiance spectra above the cirrus could mostly be reproduced by the radiation model to within +/- 5-10% for most ice crystal habits. Below the cirrus the simulations disagreed with the measured irradiances due to surface albedo variability along the flight track, and nonoptimal colocation between the microphysical and irradiance measurements. The impact of shape characteristics of the crystals was important for the reflected irradiances above the optically thin cirrus, especially for small solar zenith angles, because in this case single-scattering dominated the solar radiation field. For the cirrus of moderate optical thickness the enhanced multiple scattering tended to diminish particular shape features caused by nonspherical single-scattering. Within the ice absorption bands the shape-related differences in the absorption characteristics of the individual nonspherical ice crystals were amplified if multiple scattering prevailed. Furthermore, it was found that below the cloud the shape sensitivity of the downwelling irradiance spectra is larger compared to the nonsphericity effects on reflected irradiances above the cirrus. Finally, it was shown that the calculated cirrus solar radiative forcing could vary by as much as 26% depending on the ice crystal habit.

Wendisch, Manfred↗
NASA NTRS1985

A survey of major east coast snowstorms, 1960-1983. Part 2: Case studies of eighteen storms

Snowfall, surface and upper air charts, and available satellite images are presented for eighteen major East Coast snowstorms that occurred between 1960 and 1983. The charts and descriptions of key fields are provided so that students, weather forecasters, and researchers alike can visualize how a large sample of major winter cyclones form and intensify. Although there are noted similarities in certain aspects of the surface and upper tropospheric development of the storms, significant case-to-case variability precludes the ability to effectively composite these weather systems.

Kocin, P. J.↗
NASA NTRS1983

Case study of the March 24, 1976 Elton, Louisiana tornado using satellite infrared imagery, Doppler sounder, rawinsonde, and radar observations

The Elton, Louisiana tornado on March 24, 1976 has been studied using GOES digital infrared data for the growth and collapse of the cloud top, the temperature-height relationship and air mass instability from rawinsonde data, gravity waves from Doppler sounder records, and radar summaries from storm activity during the three-hour time period immediately preceding the touchdown of the tornado. In this case, the overshooting turret collapsed 30 minutes before the tornado touchdown as the eastward moving cloud reached Elton, Louisiana. Results show that the gravity waves were excited by the enhanced convection of the storm penetrating through the tropopause in the 2.5 hour time period before the tornado touched down.

Hung, R. J.↗
NASA NTRS2020

Comparison of Surface Fluxes Derived from CYGNSS and Simulated by WRF Model: An MJO Case Study

This study focuses on ocean surface fluxes, mainly the latent heat flux, and their impact on MJO propagation and associated precipitation structures over the Indian Ocean and Maritime Continent. The Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) model is used to simulate two MJO events during the 2017-2018 season: the December 10 - January 20, 2017 case, which maintained its strong precipitation signal over the Maritime Continent, and the March 1 - 20, 2018 case, which was weaker and did not propagate through the Maritime Continent. Both simulated MJO events show positive biases in surface rainfall compared with GPM IMERG data. During the MJO suppressed phase, the simulations rain more often than the observations. During the active phase, the westward propagating precipitation structures are more organized and much stronger compared with the observations, sometimes forming westward propagating cyclones that weakened the eastward precipitation signals. Two aspects of the surface flux interactions are investigated: the impact of the domain mean surface fluxes, and the impact of storm scale circulations and their interactions with local surface fluxes. Both aspects affect water vapor budget, atmosphere instability and mean flow, through which convection initiation, organization, and propagation are influenced. Model sensitivity tests with different radiation, microphysics, PBL schemes and nudging schemes indicate that in the control simulations, higher SST and surface fluxes, especially during the suppressed period, are the main reason of rainfall overestimation compared with IMERG data. The strong westward propagating signals are caused by both increased atmosphere instability and reduced mean wind shear. Unfortunately, the small differences in mean SST and surface fluxes between different model sensitivity tests are all within the satellite observation error margin, and cannot be directly corroborated by observations. One of the advantages of CYGNSS satellites is that they observe ocean surface wind and heat fluxes underneath strong rainfall events such as the convective systems associated with MJO active phases. Currently we are comparing CYGNSS level 2 surface fluxes retrievals and the model simulations in order to better understand the second aspect of the MJO and surface fluxes interactions, and how this affects MJO strengths and propagations. The interactive atmosphere-ocean-wave model also provides cases that directly comparing satellite observables (the bistatic radar cross section) and the model simulations (through CYGNSS satellite simulator). These discrepancies are more prominent in coupled ocean simulations, mainly due to higher SST and enhanced surface fluxes.

Li, Xiaowen↗
DOE OSTI2023

Sensor Incipient Fault Impacts on Building Energy Performance: A Case Study on a Multi-Zone Commercial Building

Existing studies show sensor faults/error could double building energy consumption and carbon emissions compared with the baseline. Those studies assume that the sensor error is fixed or constant. However, sensor faults are incipient in real conditions and there were extremely limited studies investigating the incipient sensor fault impacts systematically. This study filled in this research gap by studying time-developing sensor fault impacts to rule-based controls on a 10-zone office building. The control sequences for variable air volume boxes (VAV) with an air handling unit (AHU) system were selected based on ASHRAE Guideline 36-2018: High-Performance Sequences of Operation for HVAC Systems. Large-scale simulations on cloud were conducted (3600 cases) through stochastic approach. Results show (1) The site energy differences could go –3.3% lower or 18.1% higher, compared with baseline. (2) The heating energy differences could go –66.5% lower or 314.4% higher, compared with baseline. (3) The cooling energy differences could go –11.5% lower or 65.0% higher, compared with baseline. (4) The fan energy differences could go 0.15% lower or 6.9% higher, compared with baseline.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2017

On the Impact of Granularity of Space-Based Urban CO2 Emissions in Urban Atmospheric Inversions: A Case Study for Indianapolis, IN

Quantifying greenhouse gas (GHG) emissions from cities is a key challenge towards effective emissions management. An inversion analysis from the INdianapolis FLUX experiment (INFLUX) project, as the first of its kind, has achieved a top-down emission estimate for a single city using CO2 data collected by the dense tower network deployed across the city. However, city-level emission data, used as a priori emissions, are also a key component in the atmospheric inversion framework. Currently, fine-grained emission inventories (EIs) able to resolve GHG city emissions at high spatial resolution, are only available for few major cities across the globe. Following the INFLUX inversion case with a global 1x1 km ODIAC fossil fuel CO2 emission dataset, we further improved the ODIAC emission field and examined its utility as a prior for the city scale inversion. We disaggregated the 1x1 km ODIAC non-point source emissions using geospatial datasets such as the global road network data and satellite-data driven surface imperviousness data to a 3030 m resolution. We assessed the impact of the improved emission field on the inversion result, relative to priors in previous studies (Hestia and ODIAC). The posterior total emission estimate (5.1 MtC/yr) remains statistically similar to the previous estimate with ODIAC (5.3 MtC/yr). However, the distribution of the flux corrections was very close to those of Hestia inversion and the model-observation mismatches were significantly reduced both in forward and inverse runs, even without hourly temporal changes in emissions. EIs reported by cities often do not have estimates of spatial extents. Thus, emission disaggregation is a required step when verifying those reported emissions using atmospheric models. Our approach offers gridded emission estimates for global cities that could serves as a prior for inversion, even without locally reported EIs in a systematic way to support city-level Measuring, Reporting and Verification (MRV) practice implementation.

EIs↗
NASA NTRSDate not supplied

Dermatitis During Spaceflight Associated With HSV-1 Reactivation- A Case Study

Human alpha herpesviruses herpes simplex virus (HSV-1 or -2) and varicella zoster virus (VZV) establish latency in various cranial nerve ganglia, and often reactivate in response to stress-associated immune system dysregulation. Reactivation of Epstein Barr Virus (EBV), VZV, HSV-1 and Cytomegalovirus (CMV) is typically asymptomatic during spaceflight, though live/infectious virus has been recovered and the shedding rate increases with mission duration. The risk of clinical disease, therefore, may increase for astronauts assigned to extended missions (>180 days). Here, we report for the first time, a case of HSV-1 skin rash (dermatitis) occurring during a long duration spaceflight. The astronaut reported persistent dermatitis during flight, which was treated onboard with oral antihistamines and topical/oral steroids. No HSV-1 DNA was detected in 6-month pre-mission saliva samples, but on flight day 82, a saliva and rash swab both yielded 4.8 copies/ng DNA and 5.3×104 copies/ng DNA, respectively. Post-mission saliva samples continued to have high infectious HSV-1 load (1.67×107 copies/ng DNA). HSV-1 from both rash and saliva samples had 99.4% genotype homology. Additional physiological monitoring, including stress biomarkers (cortisol, dehydroepiandrosterone (DHEA), and salivary amylase), immune markers (adaptive regulatory and inflammatory plasma cytokines) and biochemical profile markers including vitamin/mineral status and bone metabolism are also presented for this case. These data highlight an atypical presentation of HSV-1 during spaceflight and underscore the importance of viral screening during clinical evaluations of in-flight dermatitis, to determine viral etiology and guide treatment.

Herpes, Viral Reactivation, Spaceflight, Dermatiti↗
NASA NTRS2008

Irrigation Requirement Estimation using MODIS Vegetation Indices and Inverse Biophysical Modeling; A Case Study for Oran, Algeria

Human demand for food influences the water cycle through diversion and extraction of fresh water needed to support agriculture. Future population growth and economic development alone will substantially increase water demand and much of it for agricultural uses. For many semi-arid lands, socio-economic shifts are likely to exacerbate changes in climate as a driver of future water supply and demand. For these areas in particular, where the balance between water supply and demand is fragile, variations in regional climate can have potentially predictable effect on agricultural production. Satellite data and biophysically-based models provide a powerful method to quantify the interactions between local climate, plant growth and water resource requirements. In irrigated agricultural lands, satellite observations indicate high vegetation density while the precipitation amount indicates otherwise. This inconsistency between the observed precipitation and the observed canopy leaf density triggers the possibility that the observed high leaf density is due to an alternate source of water, irrigation. We explore an inverse process approach using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), climatological data, and the NASA's Simple Biosphere model, SiB2, to quantitatively assess water demand in a semi-arid agricultural land by constraining the carbon and water cycles modeled under both equilibrium (balance between vegetation and prevailing local climate) and nonequilibrium (water added through irrigation) conditions. We postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. We added water using two distribution methods: The first method adds water on top of the canopy and is a proxy for the traditional spray irrigation. The second method allows water to be applied directly into the soil layer and serves as proxy for drip irrigation. Our approach indicates that over the study site, for the month of July, spray irrigation resulted in an irrigation amount of about 1.4 mm per occurrence with an average frequency of occurrence of 24.6 hours. The simulated total monthly irrigation for July was 34.85 mm. In contrast, the drip irrigation resulted in less frequent irrigation events with an average water requirement about 57% less than that simulated during the spray irrigation case. The efficiency of the drip irrigation method rests on its reduction of the canopy interception loss compared to the spray irrigation method. When compared to a country-wide average estimate of irrigation water use, our numbers are quite low. We would have to revise the reported country level estimates downward to 17% or less

Bounoua, L.↗
NASA NTRS2012

Modeling a Civil Event Case Study for Consequence Management Using the IMPRINT Forces Module

A critical challenge in the Consequence Management (CM) domain is the appropriate allocation of necessary and skilled military and civilian personnel and materiel resources in unexpected emergencies. To aid this process we used the Forces module in the Improved Performance Research Integration Tool (IMPRINT). This module enables analysts to enter personnel and equipment capabilities, prioritized schedules and numbers available, along with unexpected emergency requirements in order to assess force response requirements. Using a suspected terrorist threat on a college campus, we developed a test case model which exercised the capabilities of the module, including the scope and scale of operations. The model incorporates data from multiple sources, including daily schedules and frequency of events such as fire calls. Our preliminary results indicate that the model can predict potential decreases in civilian emergency response coverage due to an involved unplanned incident requiring significant portions of police, fire and civil responses teams.

Gacy, Marc↗
NASA NTRS1993

Terrestrial case studies of ilmenite exploration and lunar implications

The Space Exploration Initiative (SEI) includes space resource utilization as one of the four architectures to achieve U.S. goals in space. Space resource utilization will make use of lunar resources to support long term activities on the lunar surface. Lunar ilmenite and regolith are two of the materials that can be mined and processed for lunar oxygen production. During this investigation, several sources were reviewed to assess terrestrial exploration methods used for locating ilmenite resources. These sources included published reports on terrestrial ilmenite exploration methods, analytical methods, case histories, chemical and physical properties, and associations with other minerals. Using a terrestrial analog and considering the differences between terrestrial and lunar environmental conditions, rocks, and minerals, exploration methods and analytical instruments can be recommended for a lunar orbiter and lander for assessing lunar resources. Twelve terrestrial case histories were reviewed to gain insight into ilmenite exploration on the Moon. All exploration case histories follow the same pattern. They begin with a model, use remote geophysical techniques, define regional sampling sites from the model and geophysics, narrow down the area of exploration based on the preceding work, collect more samples and cores, and perform laboratory analyses of samples. An important part of this process is the collection of samples to determine the correctness of the model. Surface and core samples are collected in areas expected to contain both high and low concentration of the commodity to test the model. After samples are analyzed and the area of mineralization is defined, reserves are calculated to determine the cost/benefit ratio, the necessary capacity of the processing plant, and the life of the mine. The exploration methods used for locating terrestrial ilmenite resources are reviewed with respect to the petrology, chemistry, and mineral associations of the terrestrial and lunar environments.

Feldman, S. C.↗
NASA NTRS1994

A performance analysis method for distributed real-time robotic systems: A case study of remote teleoperation

Robot coordination and control systems for remote teleoperation applications are by necessity implemented on distributed computers. Modeling and performance analysis of these distributed robotic systems is difficult, but important for economic system design. Performance analysis methods originally developed for conventional distributed computer systems are often unsatisfactory for evaluating real-time systems. The paper introduces a formal model of distributed robotic control systems; and a performance analysis method, based on scheduling theory, which can handle concurrent hard-real-time response specifications. Use of the method is illustrated by a case of remote teleoperation which assesses the effect of communication delays and the allocation of robot control functions on control system hardware requirements.

Lefebvre, D. R.↗
NASA NTRS2018

Extreme Air Pollution Events in Hokkaido, Japan Traced Back to Early Snowmelt and Large-Scale Wildfires Over East Eurasia: Case Studies

To identify the unusual climate conditions and their connections to air pollutions in a remote area due to wildfires, we examine three anomalous large-scale wildfires in May 2003, April 2008, and July 2014 over East Eurasia, as well as how products of those wildfires reached an urban city, Sapporo, in the northern part of Japan (Hokkaido), significantly affecting the air quality. NASA's MERRA-2 (the Modern-Era Retrospective analysis for Research and Applications, Version 2) aerosol re-analysis data closely reproduced the PM2.5 variations in Sapporo for the case of smoke arrival inJuly 2014. Results show that all three cases featured unusually early snowmelt in East Eurasia, accompanied by warmer and drier surface conditions in the months leading to the fires, inducing long-lasting soil dryness and producing environmental conditions conductive to active wildfires. Due to prevailing anomalous synoptic-scale atmospheric motions, smoke from those fires eventually reached a remote area, Hokkaido, and worsened the air quality in Sapporo. In futurestudies, continuous monitoring of the timing of Eurasian snowmelt and the air quality from the source regions to remote regions, coupled with the analysis of atmospheric and surface conditions, may be essential in more accurately predicting the effects of wildfires on air quality.

MERRA-2↗
DOE OSTI2024

Profitability, Scalability and Optimized Siting for Waste-to-Energy Supply Chains: A Case Study on Hydrothermal Liquefaction

Waste-to-Energy (WtE) conversion technologies have the potential to simultaneously reduce waste volumes, treatment-related emissions, and carbon intensity while producing valuable energy services. However, questions remain regarding under which conditions emerging WtE technologies are feasible to deploy. In this project, we develop an optimized siting method for WtE technologies to assess cost-effective WtE processor locations, throughput scales, and profitability. We apply the model using Hydrothermal Liquefaction (HTL) as an example WtE technology. We develop calibrated capital and operating expense cost curves based on literature data to study the techno-economic characteristics of WtE supply chains. Prior to solving the siting optimization, we analyze the model parameters to describe organic waste management system behavior under four different HTL deployment configurations: Co-Processing, where HTL plants send biocrude to existing conventional refineries via assumed pipelines; Co-Location, where biorefineries are co-located with HTL plants; and two alternative Standalone Biorefining cases, where distributed HTL plants transport biocrude intermediate via either assumed pipelines or trucking to centralized biorefineries. We also define and apply several feedstock gate fee calculations, representing different revenue distribution options, to investigate how bioproduct value could impact WtE supply chain economics in terms of waste producer and processor profit or cost reduction.

09 BIOMASS FUELS↗
DOE OSTI2021

Learning with Delayed Rewards—A Case Study on Inverse Defect Design in 2D Materials

Defect dynamics in materials are of central importance to a broad range of technologies from catalysis to energy storage systems to microelectronics. Material functionality depends strongly on the nature and organization of defects-their arrangements often involve intermediate or transient states that present a high barrier for transformation. The lack of knowledge of these intermediate states and the presence of this energy barrier presents a serious challenge for inverse defect design, especially for gradient-based approaches. Here, we present a reinforcement learning (RL) [Monte Carlo Tree Search (MCTS)] based on delayed rewards that allow for efficient search of the defect configurational space and allows us to identify optimal defect arrangements in low-dimensional materials. Using a representative case of two-dimensional MoS 2 , we demonstrate that the use of delayed rewards allows us to efficiently sample the defect configurational space and overcome the energy barrier for a wide range of defect concentrations (from 1.5 to 8% S vacancies)-the system evolves from an initial randomly distributed S vacancies to one with extended S line defects consistent with previous experimental studies. Detailed analysis in the feature space allows us to identify the optimal pathways for this defect transformation and arrangement. Comparison with other global optimization schemes like genetic algorithms suggests that the MCTS with delayed rewards takes fewer evaluations and arrives at a better quality of the solution. The implications of the various sampled defect configurations on the 2H to 1T phase transitions in MoS 2 are discussed. In this study, we introduce a RL strategy employing delayed rewards that can accelerate the inverse design of defects in materials for achieving targeted functionality.

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

Modeling and Energy Analysis of Refrigeration Systems in Supermarkets: A Case Study

Refrigeration systems are the single largest consumer of electricity in supermarkets, accounting for approximately 40–60% of total store electricity use. As supermarkets face increasing pressures to improve efficiency and reduce operational costs, understanding the energy performance of refrigeration systems in supermarkets has become essential. In this paper, we investigate the energy performance and patterns of the refrigeration system using field measurements in one supermarket. The compressor coefficient of performance (COP) averaged 4.5 during nighttime steady-state operation, providing a practical efficiency benchmark. We develop simple physical-based load models for the display cases in the supermarket, where the refrigeration system uses R404A. The results show the display case models achieve a good agreement with measured data, validating its utility for energy estimation during unoccupied hours. Finally, the analysis reveals several challenges of data collection systems for refrigeration systems in the supermarket industry as well.

Chen, Yimin [ORNL] (ORCID:0000000338181655)↗
DOE OSTI2024

Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources: A Case Study on Federated Fine-Tuning of LLaMA 2

Federated learning enables multiple data owners to collaboratively train robust machine learning models without transferring large or sensitive local datasets by only sharing the parameters of the locally trained models. Here, in this article, we elaborate on the design of our Advanced Privacy-Preserving Federated Learning (APPFL) framework, which streamlines end-to-end secure and reliable federated learning experiments across cloud computing facilities and high-performance computing resources by leveraging Globus Compute, a distributed function as a service platform, and Amazon Web Services. We further demonstrate the use case of APPFL in fine-tuning an LLaMA 2 7B model using several cloud resources and supercomputers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Fossil Fuel Transitions Framework: Case Studies of the Decision-Making Process for Energy and Economic Development Pathways

Each community is unique, and transitions must be tailored to local and national contexts, with recognition that access to financing is a key differentiator between wealthy and low-to-middle income countries. This analysis examines six community fossil fuel transitions in two different country contexts to provide insights on inclusive processes and decision-making criteria that bring forth positive outcomes for the communities. In both the United States and Chile, a coordination mechanism is established across government agencies and the importance of stakeholder engagement is recognized. In many cases, the government, local community groups, and electric utility or industry players have a critical role in transition planning and support.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Modeling, analysis, and optimization of complex nuclear processes and facilities via computational methods: The HALEU process case study

Improving and adapting industrial systems to timely meet changing programmatic and market demands is an important goal to achieve, including when operating and maintaining complex nuclear processes and facilities. However, changes to these complex systems are costly, particularly when they are already in place and bounded to stringent requirements and constraints such as when handling radioactive material and contaminated equipment. These conditions often exist when treating spent nuclear fuel remotely within shielded nuclear radiation chambers, commonly referred as hot cells, to condition nuclear material and/or fabricate products for utilization in other nuclear enterprises such as in the manufacture of advanced nuclear fuel. The illustrative case considered here is the production of high assay low enriched uranium (HALEU) products supporting the deployment of advanced nuclear reactors. For the HALEU program, resources invested were and are being systematically analyzed so that these investments are maximized in a facility that is nearly 60 years old. A methodology that has effectively enabled optimized and improvements in the Spent Fuel Treatment (SFT) program, and consequently the HALEU program, involves discrete event simulation as addressed in this article. Here, the quantification of multiple productivity metrics, including material processing rates, cycle times, bottlenecks, number of material transfers as well as equipment, workstation, and material handling utilization, has resulted in a myriad of diverse discoveries and data-informed decisions regarding process layout and constituent, labor levels and schedules, selection of new process units, storage needs, and other critical process configurations. This article describes such a computational capability being applied for decision-making, illustrates its application to an actual process and program, provides illustrative results, and argues how computational methods for the modeling, analysis, and optimization of complex processes and facilities does lead to informed decisions derived from data and not only from intuition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗