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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

An uncertainty visualization framework for large-scale cardiovascular flow simulations: A case study on aortic stenosis

We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated on a patient-specific stenosed aorta. The framework combines EasyVVUQ for parameter sampling with large-eddy simulation turbulence modeling in HemeLB, and executes ensembles on the Frontier exascale supercomputer. Spatially resolved metrics, including entropy and isosurface-crossing probability, are used to map uncertainty in pressure and wall shear stress fields directly onto vascular geometries. Two sources of model variability are examined: inlet peak velocity and the Smagorinsky constant. Inlet velocity variation produces high uncertainty downstream of the stenosis where turbulence develops, while upstream regions remain stable. Smagorinsky constant variation has little effect on the large-scale pressure field but increases WSS uncertainty in localized high-shear regions. In both cases, the stenotic throat manifests low entropy, indicative of robust identification of elevated WSS. By linking quantitative UQ measures to three-dimensional anatomy, the framework improves interpretability over conventional 1D UQ plots and supports clinically relevant decision-making, with broad applicability to vascular flow problems requiring both accuracy and spatial insight.

Hemodynamics↗
DOE OSTI2022

Life cycle assessment of utilizing freshly cut urban wood: A case study

Large amounts of urban wood resources are generated through tree removals in urban areas. Therefore, there is a growing interest to improve the environmental performance of the urban wood supply chain by quantifying the environmental impacts of creating high-value products from urban tree removals to enhance its utilization. By surveying existing urban wood utilization operations for primary data in two major cities: Baltimore, Maryland, and Milwaukee, Wisconsin, a new life cycle inventory (LCI) dataset per m 3 of dry urban hardwood lumber and live edge slabs was created. Incorporating the new LCI data into life cycle assessment method, the total global warming (GW) impact of converting urban trees to kiln-dried lumber was estimated to be 122 kg CO 2 eq and 336 kg CO 2 eq per m 3 of lumber produced for Baltimore and Milwaukee, respectively. In both cases, the total environmental impact of the product was dominated by the conversion of urban trees to kiln dried lumber at the sawmill processing stage. Using scenario analysis for the source of heat generation used in kiln (force) drying wood, substituting wood fuel from coproducts for natural gas in a boiler for Milwaukee resulted in a substantial reduction in fossil-derived GW impact. Urban and traditional hardwood lumber production follow similar GW impact trajectories over their life-cycle stages with the lumber processing stage having the highest environmental impacts for both. Finally, increasing the overall lumber yield and decreasing kiln (force) drying would substantially improve the environmental performance of urban hardwood lumber and help make it comparable to traditional lumber.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

The 27-28 October 1986 FIRE cirrus case study: Meteorology and clouds

Detailed descriptions of the rawinsonde resolved meteorological conditions (3 hourly soundings) associated with a succession of five distinct mesoscale cirrus cloud regimes, that were intensively observed over a 36 hour period, are given. The synoptic scale systems in which these features were embedded are described and a brief overview of the experiment is given. Regional analyses of the static stability structure and vertical motion are presented and interpreted with respect to the characteristics of the corresponding cloud fields as deduced from satellite and lidar observations. The cloud fields exhibited a high degree of persistent mesoscale organization on scales of 20 to 500 km reflecting corresponding scales of dynamic and thermodynamic structure/variability as on the synoptic scale. Cloud generation was usually confined to layers less than 1 km deep (typically 0.5 km in depth) and cellular organization was evident in most cases irrespective of the thermal stratification. Multilayered development was prevalent (2 to 3 layers) and was associated with vertical structure of the temperature and moisture fields resulting primarily from vertical gradients in horizontal advection.

Starr, David↗
DOE OSTI2023

How an Autonomous Offshore Power System Can Transform the Ocean Economy - A Hypothetical Case Study Utilizing an Autonomous Offshore Power System in Northern Lights Carbon Capture and Storage Project

An Autonomous Offshore Power System (AOPS) provides in-situ power, energy storage, real-time data and communications support, asset management, and other capabilities at sea. It has applications for all offshore industries: energy, defense and security, aquaculture, science and research, and communications. Furthermore, this paper highlights how an AOPS can reduce cost, complexity, and carbon-intensity for existing offshore operations and enable new capabilities for offshore industry leaders. This new AOPS technology has two primary advantages. First, it unlocks the autonomous, electric future of the ocean economy via ‘local’ power generation and energy storage, in addition to real-time connection to the data cloud. Second, it helps enable a material change in the global energy mix through cost-effective, reliable generation and storage technology for use cases including mobile/static data-gathering and reporting systems, operating equipment, and charging networks for uncrewed surface vessels. AOPS technology will help transform the ocean economy, and thus has implications for offshore industry leaders as they push to reduce costs today and make an autonomous and decarbonized future possible.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Risk to ecological resources following remediation can be due mainly to increased resource value of successful restoration: A case study from the Department of Energy's Hanford Site

Several nations are faced with the need to remediate large contaminated sites following World War II, the Cold War, and abandoned industrial sites, and to return them to productive land uses. In the United States, the Department of Energy (DOE) has the largest cleanup challenge, and its Hanford Site in the state of Washington has the most extensive and most expensive cleanup task. Ideally, the risk to ecological resources on remediation sites is evaluated before, during, and after remediation, and the risk from, or damage to, ecological resources from contaminants should be lower following remediation. In this paper, we report the risk to ecological resources before, during, and as a consequence of remediation on contaminated units requiring cleanup, and then examine the causes for changes in risk by evaluating 56 cleanup evaluation units (EUs) at the Hanford Site. In this case, remediation includes a restoration phase. In general, the risk to ecological and eco-cultural resources is currently not discernible or low at most contaminated units, increases during remediation, and decreases thereafter. Remediation often causes physical disruption to ecosystems as it reduces the risk from exposure to contaminants. Most new remediation projects at the Hanford Site include ecological restoration. Ecological restoration results in the potential for the presence of higher quality resources after remediation than currently exists on these contaminated lands and facilities. Although counter-intuitive, our evaluation of the risk to ecological resources following remediation indicated that a significant percentage of units (61%) will be at increased risk in the post-remediation period. This increased risk is due to DOE's successful remediation and restoration that results in a higher percent of native vegetation and higher ecological value on the sites in the post-remediation period than before. These newly-created resources can then be at risk from post-remediation activities. Risks to these new higher quality resources include the potential for spread of invasive species and of noxious grasses used in previous cleanup actions, disruption of ecosystems (including those with state or federally listed species and unique ecosystems), compaction of soil, use of pesticides to control invasive species, and the eventual need for continued monitoring activities. Thus, by greatly improving the existing habitat and health of eco-receptors, and maintaining habitat corridors between high quality habitats, the ecological resources in the post-remediated units are at risk unless care is taken to protect them. Many of the negative effects of both remediation and future monitoring (or other future land uses) can be avoided by planning and management early in the remediation process. We suggest DOE and other agencies convene a panel of managers, remediation scientists, regulators, environmental and ecological scientists, Native Americans, economists, and the public to develop a generic list of performance metrics for the restoration phase of remediation, including evaluation of success, which could be applied across the DOE complex.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A case study of denoising microseismic data in the Farnsworth, TX CO 2 EOR site

As geologic carbon sequestration projects begin to be funded with a higher degree of frequency, microseismic monitoring will become more necessary to establish caprock integrity and induced seismicity risk. The Farnsworth, TX site, which hosts enhanced oil recovery operations, provides an ideal laboratory to test essential components of microseismic monitoring such as surface station placement, denoising, and different autopicker methods. We find that despite careful optimization, the surface station placement at the Farnsworth site was insufficient given the high level of background noise from the industrial operations at the oil field. Thus, we use only borehole geophone data in our processing. Two denoising techniques were examined: the DeepDenoiser and the continuous wavelet transform. The continuous wavelet transform was shown to be a valuable tool in converting between raw waveforms to processed denoised waveforms for microseismic monitoring. In the case of the noisy waveforms, only ten detections are found, compared with 90 in the denoised data for a two-hour window. The DeepDenoiser suffered from the fact that the training data was regional earthquake data. In addition, the PhaseNet machine-learning autopicker was applied to both the noisy and the denoised data, and this algorithm detected thousands of more arrivals in the data denoised with the continuous wavelet transform technique.

58 GEOSCIENCES↗
DOE OSTI2025

Hierarchical Resilience Planning for Networked Microgrids: A Case Study of Puerto Rico

Microgrids can be designed to enhance the energy resilience of communities and critical infrastructures, such as hospitals, data centers, and communication networks, which are vulnerable to frequent weather-related disruption. Coordinating multiple microgrids in a network can leverage the geographical diversity of load and generation resources while enabling resilient and cost-effective planning of the distribution system. Designing a networked microgrid is complex, involving intricate technical assessment, cost-benefit analysis, site-specific requirements, and the evaluation of existing resources. Therefore, this paper proposes a hierarchical resilience planning framework and performs an extensive techno-economic analysis for the design of a networked microgrid. Hierarchical resilience planning involves technology sizing at an individual community level to meet the critical load and satisfy resilience criteria, and resource optimization at networked microgrid level to provide a higher level of resilience and energy adequacy. A real-world case of Puerto Rico's cooperative microgrid “Microrred de la Montaña” is investigated considering localized electricity tariffs, site-specific demand profiles, solar generation, and existing hydro resources. Multiple optimization scenarios are developed based on the resiliency requirement to estimate the capacity of solar photovoltaic and battery energy storage (BES) to be installed at each substation. The results provide the optimal sizing for individual community and networked microgrid to withstand 1day and 3-day outages along with the criteria for critical load.

13 - HYDRO ENERGY↗
NASA NTRS2012

The Geometric Factor of Electrostatic Plasma Analyzers: A Case Study from the Fast Plasma Investigation for the Magnetospheric Multiscale mission

We report our findings comparing the geometric factor (GF) as determined from simulations and laboratory measurements of the new Dual Electron Spectrometer (DES) being developed at NASA Goddard Space Flight Center as part of the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission. Particle simulations are increasingly playing an essential role in the design and calibration of electrostatic analyzers, facilitating the identification and mitigation of the many sources of systematic error present in laboratory calibration. While equations for laboratory measurement of the Geometric Factpr (GF) have been described in the literature, these are not directly applicable to simulation since the two are carried out under substantially different assumptions and conditions, making direct comparison very challenging. Starting from first principles, we derive generalized expressions for the determination of the GF in simulation and laboratory, and discuss how we have estimated errors in both cases. Finally, we apply these equations to the new DES instrument and show that the results agree within errors. Thus we show that the techniques presented here will produce consistent results between laboratory and simulation, and present the first description of the performance of the new DES instrument in the literature.

Magnetospheric Multiscale Mission↗
NASA NTRS2000

Design-Filter Selection for H2 Control of Microgravity Isolation Systems: A Single-Degree-of-Freedom Case Study

Many microgravity space-science experiments require active vibration isolation, to attain suitably low levels of background acceleration for useful experimental results. The design of state-space controllers by optimal control methods requires judicious choices of frequency-weighting design filters. Kinematic coupling among states greatly clouds designer intuition in the choices of these filters, and the masking effects of the state observations cloud the process further. Recent research into the practical application of H2 synthesis methods to such problems, indicates that certain steps can lead to state frequency-weighting design-filter choices with substantially improved promise of usefulness, even in the face of these difficulties. In choosing these filters on the states, one considers their relationships to corresponding design filters on appropriate pseudo-sensitivity- and pseudo-complementary-sensitivity functions. This paper investigates the application of these considerations to a single-degree-of-freedom microgravity vibration-isolation test case. Significant observations that were noted during the design process are presented. along with explanations based on the existent theory for such problems.

Hampton, R. David↗
NASA NTRS2004

What Multilevel Parallel Programs do when you are not Watching: A Performance Analysis Case Study Comparing MPI/OpenMP, MLP, and Nested OpenMP

With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors, parallel programming techniques have evolved that support parallelism beyond a single level. When comparing the performance of applications based on different programming paradigms, it is important to differentiate between the influence of the programming model itself and other factors, such as implementation specific behavior of the operating system (OS) or architectural issues. Rewriting-a large scientific application in order to employ a new programming paradigms is usually a time consuming and error prone task. Before embarking on such an endeavor it is important to determine that there is really a gain that would not be possible with the current implementation. A detailed performance analysis is crucial to clarify these issues. The multilevel programming paradigms considered in this study are hybrid MPI/OpenMP, MLP, and nested OpenMP. The hybrid MPI/OpenMP approach is based on using MPI [7] for the coarse grained parallelization and OpenMP [9] for fine grained loop level parallelism. The MPI programming paradigm assumes a private address space for each process. Data is transferred by explicitly exchanging messages via calls to the MPI library. This model was originally designed for distributed memory architectures but is also suitable for shared memory systems. The second paradigm under consideration is MLP which was developed by Taft. The approach is similar to MPi/OpenMP, using a mix of coarse grain process level parallelization and loop level OpenMP parallelization. As it is the case with MPI, a private address space is assumed for each process. The MLP approach was developed for ccNUMA architectures and explicitly takes advantage of the availability of shared memory. A shared memory arena which is accessible by all processes is required. Communication is done by reading from and writing to the shared memory.

Jost, Gabriele↗
NASA NTRS2023

Dragonfly: A Case Study in Dynamic Stability Characterization

Next decade, the Dragonfly probe will enter Titan’s atmosphere on a mission to explore and characterize its unique and complex organic chemistry. In contrast to Mars entry missions, where the challenge is to slow down in its tenuous atmosphere before impacting the surface, Titan’s thick atmosphere provides generous drag. However, Titan has its own unique EDL challenges. Among these challenges is the long time (on the order of 90 minutes!) the vehicle will need to descend unguided through flow regimes where blunt-body entry probes are known to be dynamically unstable. This elongated timeline, both prior to drogue parachute deployment, and during the ensuing descent, has the potential to allow adverse dynamic instability properties to produce large amplitude oscillations in angle-of-attack. This, in-turn may lead to non-compliance in vehicle attitude requirements for EDL events such as parachute deployment, and lander release, or in the most extreme case, tumbling of the aeroshell and near-assured loss of mission.

EDL↗
NASA NTRS2023

Dragonfly: A Case Study in Dynamic Stability Characterization

Next decade, the Dragonfly probe will enter Titan’s atmosphere on a mission to explore and characterize its unique and complex organic chemistry. In contrast to Mars entry missions, where the challenge is to slow down in its tenuous atmosphere before impacting the surface, Titan’s thick atmosphere provides generous drag. However, Titan has its own unique EDL challenges. Among these challenges is the long time (on the order of 90 minutes!) the vehicle will need to descend unguided through flow regimes where blunt-body entry probes are known to be dynamically unstable. This elongated timeline, both prior to drogue parachute deployment, and during the ensuing descent, has the potential to allow adverse dynamic instability properties to produce large amplitude oscillations in angle-of-attack. This, in-turn may lead to non-compliance in vehicle attitude requirements for EDL events such as parachute deployment, and lander release, or in the most extreme case, tumbling of the aeroshell and near-assured loss of mission.

EDL↗
DOE OSTI2023

Evaluating Production Implications of Pressure Maintenance in Unconventional Oil and Gas Wells using a Machine Learning Modeling Approach: Case Study in the Permian Basin

This study implements the proprietary machine learning-based model (model) developed under the 2022 study titled “Evaluating the Impact of Proprietary Oil & Gas Data on Machine Learning Model Performance Using a Quasi-Experimental Analytical Approach” for forecasting unconventional oil and gas production using well data from the Permian Basin. The model, developed using an exclusive dataset that includes time series production data from an operator in the Permian Basin, is designed to jointly predict daily oil, gas, and water production for horizontal wells as a function of bottomhole pressure drawdown, spatial placement across the study domain, and well-completion attributes. In this study, the model was explicitly applied to explore its utility to evaluate the impact of varying drawdown strategies on the production forecast of a well in the Permian Basin dataset. Managing pressure drawdown has been identified as a way to improve estimated ultimate recovery (EUR) from unconventional shale wells due to the stress-dependent nature of fractures in shale reservoirs. Research has shown that applying a lower pressure drawdown helps to maintain the reservoir conductivity, resulting in higher productivity over the life of a well. Historic bottomhole pressure data from the well over time was used as a benchmark from which to set more and less aggressive pressure decline rates as bounding modeling cases. All pressure decline rates/strategies were forecasted over 5 years, and the model was used to generate oil, water, and gas prediction over the same timeframe. This report presents the results from the production forecast and discusses potential operational and economic implications, with contrasting perspectives between well productivity and profitability given typical oil and gas economics and the volatility in the oil and gas market.

02 PETROLEUM↗
NASA NTRS2000

Case Study of Solar Wind and IMF Influence on Ionospheric Outflow

We examine ionospheric outflows in the high attitude magnetospheric polar cap during the POLAR satellite's apogee on 04/19/96 using the TIDE instrument. The pass has a fairly constant flux of H+ which is similar to many other passes, but there is a large amount of O+ present. The elevated levels of O+ may be due both to the geophysical conditions during the apogee pass (Kp=5) and prior to the pass. When the outflows for many high altitude polar cap passes are analyzed the O+ density correlates well with the dynamic pressure. There are several aspects of this pass which are interesting besides the abundance of O+ relative to H+. In this pass both the H+ and O+ outflow velocity correlate with both the solar wind speed and Interplanetary Magnetic Field (IMF) Bx. The geophysical conditions are such that the solar wind speed and IMF Bx are highly correlated with each other. For this case the dynamic pressure of the solar wind is fairly constant and has an average value of about 2.5 nPa which is typical for the solar wind, but the average solar wind speed is about 695 km/s which is greater than 450 km/s which is typical for the solar wind at I AU. The ion outflow measurements themselves are interrelated. The H+ density and parallel speed are anticorrelated which results in the constant flux. The 0+ density does not have as large of a anticorrelation with its parallel speed as H+ does with its parallel speed.

Elliott, H. A.↗
DOE OSTI2022

Initial Scoping Efforts for a Plant-Wide Digital Infrastructure Modernization Business Case Study

This research report describes the preparatory efforts to perform a BCA on an expanded set of digital upgrades envisioned for implementation at the Luminant?s Comanche Peak nuclear plant. It captures efforts to scope the digital upgrade effort to enable performance of the BCA. The final BCA will be the subject of a subsequent report. LWRS pilot research in this area is intended to enable this effort and to provide a roadmap to others to follow. INL appreciates the Luminant?s participation in this research.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2022

NASA Satellites and Data Fusion: A Case Study with Coral Reefs

As the world is experiencing a significant rise in both AI, Climate, and Space start-up companies, we are in a new wave of limitless innovation. NASA's statutory responsibility is to "provide for the widest practicable and appropriate dissemination of information concerning its activities and the results thereof." (51 U.S.C. § 20112) In particular, through machine learning, the public data drawn from NASA’s space assets can provide insights for addressing climate-related problems here on Earth. And many climate start-up companies can benefit from leveraging this data, either for proof of concepts or their own missions. In the Fall of 2021, several scientists from NASA and Coral Vita led a Practicum with the Georgia Institute of Technology Masters in Data Analytics program. The Practicum saw two teams of students develop and implement machine learning models to infer, from CALIPSO satellite imagery, vitality properties upon satellite pass. This kind of capability can lead to real-time mapping of coral health around the world, giving organization an understanding of where to prioritize reef reconstitution.. In this presentation, we will highlight this use case and discuss other concrete applications in which space data is used to solve problems here on Earth.

Earth Sciences↗
DOE OSTI2022

Seasonality and trade in hydro-heavy electricity markets: A case study with the West Africa Power Pool (WAPP)

Hydroelectric power plants account for 25% of West Africa's total installed capacity. In general, electricity generated by these plants is seasonal and intra-annual fluctuation has a considerable impact on electricity supply and cross-border electricity trade. We soft-linked a global hydrologic model to a multi-region capacity expansion and planning model for the West Africa Power Pool (WAPP) to examine the effects of seasonality in hydropower electricity generation on electricity trade, as well as the economic benefits of unconstrained cross-border electricity trade. We found that transitioning from rainy to dry season decreases hydroelectricity generation by an average of 40% in a normal year across the region. Between 2018 and 2050, satisfying the region's electricity demand will require significant capital investment; nevertheless, extending from current bilateral electricity trade agreements to a fully competitive cross-border electricity trade will result in net annual savings of $3 billion in 2015 USD. To achieve year-round energy security, countries should plan ahead and diversify their energy sources to ensure that supply reliability can be maintained in the case of lower supply during the dry season.

13 HYDRO ENERGY↗
DOE OSTI2022

Overcoming significant challenges in extracting off-stoichiometric thermodynamics using the compound energy formalism through complementary use of experimental and first principles data: A case study of Ba 1-x Sr x FeO 3-δ

The compound energy formalism (CEF) is a powerful framework to describe the thermodynamics of metal oxides as a function of off-stoichiometry, temperature, and composition. The thermodynamic properties are crucial materials design attributes in metal oxide-based oxygen-exchange chemical processes. Despite the richness of information an accurate CEF model provides, a method to determine a unique and accurate fit for oxygen exchange materials remains elusive. This contribution details a method for fitting the CEF model that overcomes the current fitting challenges through three innovations: 1) the combination of density functional theory calculations with experimental data decorrelates excess terms and delineates the enthalpic/entropic contributions to the Gibbs free energy; 2) a systematic determination of the important CEF model terms, removing thermodynamic predetermining human intervention; 3) a self-consistent solution of the starting oxygen offstoichiometry (δ 0 ) of thermogravimetric measurements. Thus, our method enables the reliable extraction of off-stoichiometric metal oxide thermodynamic properties and facilitates rapid materials compositional screening, and reliable process design of systems dependent on off-stoichiometric redox-active metal oxides. We apply this method to a Ba x Sr 1-x FeO 3-δ test case. We find by systematically examining the performance of the CEF model fit with and without each innovation that all three innovations are necessary for an accurate fit. We determined that reduction enthalpy is higher and more sensitive to off-stoichiometry when the Sr fraction is large (139.5 and 185.3 kJ/mol O 2 for SrFeO 3 at δ = 0 and δ = 0.5, respectively vs. nearly constant 83 kJ/mol O 2 for BaFeO 3 ). However, the reduction entropy is mostly insensitive to Sr fraction, but highly dependent on δ suggesting larger contributions in the non-configurational entropy parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗