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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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NASA NTRS1990

The He I 10830 line in Arcturus produced by stochastic shocks

An investigation is conducted as to whether strong shocks produced in time-dependent stochastic wave models can explain the formation of the He I 10830 line in a cool giant star like Arcturus. The exploratory research is based on the work of Cuntz (1987) who found that stochastic waves lead to overtaking and merging of shocks producing occasionally very strong shocks with temperatures larger than 40,000 K in the postshock regions.

Cuntz, Manfred↗

NASA NTRS2007

Parallel-Processing Software for Correlating Stereo Images

A computer program implements parallel- processing algorithms for cor relating images of terrain acquired by stereoscopic pairs of digital stereo cameras on an exploratory robotic vehicle (e.g., a Mars rove r). Such correlations are used to create three-dimensional computatio nal models of the terrain for navigation. In this program, the scene viewed by the cameras is segmented into subimages. Each subimage is assigned to one of a number of central processing units (CPUs) opera ting simultaneously.

Klimeck, Gerhard↗

NASA NTRS2014

High-Resolution Spectroscopy of the Lunar Sodium Exosphere

We have applied high-resolution Fabry-Perot spectroscopy to the study of the lunar sodium exosphere for the study of exospheric effective temperature and velocity variations. Observing from the National Solar Observatory McMath-Pierce Telescope, we used a dual-etalon Fabry-Perot spectrometer with a resolving power of 180,000 to measure line widths and Doppler shifts of the sodium D2 (5889.95 Å) emission line. Our field of view was 360 km, and measurements were made in equatorial and polar regions from 500 km to 3500 km off the limb. Data were obtained from full moon to 3 days following full moon (waning phase) in March 2009. Measured Doppler line widths within 1100 km of the sunlit east and south lunar limbs for observations between 5 and 40 deg lunar phase imply effective temperatures ranging between 3260 +/- 190 and 1000 +/- 135 K. Preliminary line center analysis indicates velocity displacements between different locations off the lunar limb ranging between 100 and 600 m/s from the lunar rest velocity with a precision of +/-20 to +/-50 m/s depending on brightness. Based on the success of these exploratory observations, an extensive program has been initiated that is expected to constrain lunar atmospheric and surface-process modeling and help quantify source and escape mechanisms.

Lunar↗

NASA NTRS2015

Climate Model Diagnostic Analyzer

The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

cloud computing↗

DOE OSTI2021

One of These Things IS Like the Other: Pursuing a New Taxonomy of Industry for Improved Energy System Modeling

Industrial processes drive the exchange of materials, energy, and currency throughout the economy. These processes are powered by electricity and direct combustion, with variation in their operation even within the same industry. This heterogeneity makes it difficult for large models, including the National Energy Modeling System (US), to project their energy use while remaining tractable. Decarbonization and ensuing changes to the energy system require changes to industrial processes while offering opportunities for process innovation, but the extent and nature of changes are difficult to model with current classification schemes and corresponding data. The North American Industrial Classification (NAICS) is an economic taxonomy of industries, but its categories are less meaningful from an energy and material flow perspective. For example, a facility that makes steel from iron ore in a blast furnace/basic oxygen furnace is categorized under the same NAICS code as a facility that makes steel from scrap in an electric arc furnace despite the scale, use of recycled scrap versus iron ore, and energy use differences in the two facility types. Exploratory analysis is performed on a large dataset used for plant-level energy assessment in order to detect clusters that can aid in better modeling of industry for energy analysis in an evolving system with breakthrough technologies.

28 EE - Advanced Manufacturing Office (EE-5A)↗

DOE OSTI2024

Dynamic modeling studies of basin-scale pressure interference and CO 2 plume evolution in multi-well geologic CO 2 storage

This research employs numerical modeling to analyze how CO 2 plumes and pressure fronts evolve when CO 2 is injected into a single storage formation from multiple projects located in proximity. Here, this analysis also evaluates the extent to which injection well spacing alleviates pressure buildup in the absence of active pressure management tactics. The simulation approach was based on a single, homogenous saline aquifer in which CO 2 injection occurs under a one-injector baseline case and several multi-well cases where well spacing varies. Analysis results show that the extent of pressure buildup is in the range of tens or a few hundreds of kilometers and contingent upon the defining pressure buildup demarcating the front edge. For the geological setting evaluated in this paper, our analysis suggests that without active basin pressure management strategies, commercial-scale projects would likely need to be sited far apart to avoid pressure interference from one another. Analysis results show the radius of CO 2 plume varies approximately from 2 to 3 km from injection wells (each injecting 1 Mt/year for 30 years) depending on cases and modeling parameters assumed. Given the pressure interference, this paper thus draws attention to the importance of greater coordination among storage operators and regulatory stakeholders. Because this analysis assumes a very specific geologic setting, this exploratory analysis bears further investigations across other geologic scenarios.

42 ENGINEERING↗

NASA NTRS1974

Exploratory tests of a simple aero-mechanical ride comfort system for lightly loaded aircraft

Some exploratory wind tunnel and radio-controlled free-flight tests were made with a small high-wing airplane model (1.23m wing span) to study the concept of a simple aero mechanical system intended to alleviate gust loads and improve ride comfort of lightly loaded aircraft. The system consisted essentially of the outer portions of each wing being hinged in the chordwise direction and connected directly to the wing flaps using internal counter weights to provide neutral mass balance. When the wing experienced a change in velocity or angle of attack, the movable wing panels, acting as sensors and flap actuators, deflected in response to the changes in lift on the wing. The corresponding movements of the interconnected flaps tended to reduce the changes in the wing lift.

Hewes, D. E.↗

NASA NTRS1987

Predicting Spacecraft Trajectories

Calculations include drag, nonsphericity, and other perturbations. Artificial Satellite Analysis Program (ASAP) is general orbit-prediction program that incorporates sufficient orbit-modeling accuracy for mission design, maneuver analysis, and mission planning. Suitable for studying planetary orbit missions with spacecraft trajectories of exploratory (mapping) nature. Sample data included for study of drift cycle of geosynchronous station, strategy for mapping Venus by radar, frozen orbit about Mars, and repeat-ground-trace orbit. ASAP written in FORTRAN 77.

Kwok, J.↗

NASA NTRS1999

Meteorology of the Southern Global Plume: African and South American Fires Pollute the South Pacific

An immense global plume of CO meanders widely around the world in the Southern Hemisphere. It arises over Southern America and Africa and flows eastward. The first emissions are in tropical Brazil, and the plume circulates around the world to South America again. The plume was largely unexpected until there were aircraft studies made in NASA's Pacific Exploratory Mission - Tropics (Part A). This paper describes the meteorology of the Global Plume, as our simulation, with a synoptic model adapted to global transport, reveals it with a tracer-CO simulation. The observations and their simulation require a particular set of conditions of pollutant accumulation, cumulonimbus venting with required strengths at a narrow range of altitude. Additionally, a particular subtropical conduction region, over the Indian Ocean, Australia, and the westeRNmost South Pacific, relatively free of storms, appears to be a key part of the mechanism. These conclusions are the results of a synoptic reconstruction of the PEMT-A period, September- October, 1996.

Guo, Z.↗

DOE OSTI2025

Modeling and Simulation of Fuel Dispersal During the Loss-of-Coolant Accident

This document is the compilation of the milestone portion to a larger end of project NEUP report. The executive summary of the modeling portion is provided below: In the event of cladding rupture during a postulated LOCA in a pressurized water reactor, fuel particles, along with fission gases, can be expelled into the reactor core from the fractured fuel rod, a phenomenon referred to as fuel dispersal. The initial stage of fuel dispersal is strongly influenced by the high-pressure ejection of fuel fragments, the size and geometry of the ruptured cladding, and the depressurization history of the fuel rod during the postulated LOCA transient. Depending on the location of the burst orifice relative to the quench front, the dispersal event represents an intricate three-phase flow and heat transfer phenomenon, where high-temperature fuel particles carried by the fission gases interact with the coolant within the narrow subchannels of the fuel assemblies, inducing localized phase change. Given the unique multiphysics nature of this phenomena, the current study develops a dedicated computational framework to predict the mass distribution and cooling of dispersing fuel particles, facilitating post-accident assessment and management of the fuel assemblies. Considering the scale of nuclear reactor applications, a continuum three-fluid model is proposed for simulating the transport of solids within the reactor core. With high-temperature fuel fragments within the liquid media, nucleation sites inducing phase changes are dispersed within the flow domain. Coupled with the fact that the transient dispersal event occurs on different time scales than other three-phase flow applications, this study derives a time-averaged three-fluid flow model without losing generality. The assumptions regarding the continuum treatment of the solid phase and the modeling of fuel dispersal behavior are incorporated to simplify the governing equations and derive applicable closure relations. The computational validation of the model was conducted using adiabatic experimental results obtained from ongoing research at Oregon State University, focusing on characterizing fuel dispersal behavior during simulated LOCA conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched the probability density functions reported in experimental studies. The transport of fuel particles within a scaled 5 × 5 lattice of a pressurized-water reactor rod bundle geometry was modeled through a two-fluid Eulerian framework. The required boundary conditions were evaluated from the fuel performance code BISON in a postulated large-break LOCA scenario. The modeling framework considered solid fuel particles as granular matter, interacting with the gaseous dry steam phase and fission gases through the governing interfacial momentum exchange between the participating fluids. The simulation results provided the volume fraction of the solids obtained at the bottom surface of the enclosing tank geometry. Postulated LOCA leading to fuel dispersal phenomena involves the strong coupling between fuel thermomechanics, cladding deformation, thermal-hydraulics, and fuel particle transport. Incorporation of such a strong coupling in numerical simulation is performed by coupling the multiphysics solvers. In the case of fuel dispersal, a strong coupled simulation can be performed by coupling the BISON code for fuel performance, the TRACE code for system-level thermal hydraulics, and fuel particle transport in Multiphysics Object-Oriented Simulation Environment (MOOSE). For such intricate infrastructure, the MOOSE Framework eases the data transfer between codes. The recent version of MOOSE has incorporated the Navier-Stokes module for the fluid flow. An exploratory exercise was done to gain familiarity with finite volume capabilities in the MOOSE framework to incorporate the Spalart-Allmaras (SA) turbulence model. New finite-volume and auxiliary kernels were introduced to assemble the SA transport equation, compute turbulent viscosity, and evaluate wall distance and diagnostic turbulence terms, fully integrated with existing Navier-Stokes modules. A turbulent lid-driven cavity at a Reynolds number of approximately 10,000 is used for verification. MOOSE shows the robust solver convergence and produces the turbulent features. But it underpredicts the velocity profile and turbulent quantities, emphasizing the need to develop improved SA near-wall treatments (e.g., low-Re corrections or wall functions) as a key direction for future work.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2002

A Physics Exploratory Experiment on Plasma Liner Formation

Momentum flux for imploding a target plasma in magnetized target fusion (MTF) may be delivered by an array of plasma guns launching plasma jets that would merge to form an imploding plasma shell (liner). In this paper, we examine what would be a worthwhile experiment to do in order to explore the dynamics of merging plasma jets to form a plasma liner as a first step in establishing an experimental database for plasma-jets driven magnetized target fusion (PJETS-MTF). Using past experience in fusion energy research as a model, we envisage a four-phase program to advance the art of PJETS-MTF to fusion breakeven Q is approximately 1). The experiment (PLX (Plasma Liner Physics Exploratory Experiment)) described in this paper serves as Phase I of this four-phase program. The logic underlying the selection of the experimental parameters is presented. The experiment consists of using twelve plasma guns arranged in a circle, launching plasma jets towards the center of a vacuum chamber. The velocity of the plasma jets chosen is 200 km/s, and each jet is to carry a mass of 0.2 mg - 0.4 mg. A candidate plasma accelerator for launching these jets consists of a coaxial plasma gun of the Marshall type.

Thio, Y. C. Francis↗

NASA NTRS2003

Active State Model for Autonomous Systems

The concept of the active state model (ASM) is an architecture for the development of advanced integrated fault-detection-and-isolation (FDI) systems for robotic land vehicles, pilotless aircraft, exploratory spacecraft, or other complex engineering systems that will be capable of autonomous operation. An FDI system based on the ASM concept would not only provide traditional diagnostic capabilities, but also integrate the FDI system under a unified framework and provide mechanism for sharing of information between FDI subsystems to fully assess the overall health of the system. The ASM concept begins with definitions borrowed from psychology, wherein a system is regarded as active when it possesses self-image, self-awareness, and an ability to make decisions itself, such that it is able to perform purposeful motions and other transitions with some degree of autonomy from the environment. For an engineering system, self-image would manifest itself as the ability to determine nominal values of sensor data by use of a mathematical model of itself, and selfawareness would manifest itself as the ability to relate sensor data to their nominal values. The ASM for such a system may start with the closed-loop control dynamics that describe the evolution of state variables. As soon as this model was supplemented with nominal values of sensor data, it would possess self-image. The ability to process the current sensor data and compare them with the nominal values would represent self-awareness. On the basis of self-image and self-awareness, the ASM provides the capability for self-identification, detection of abnormalities, and self-diagnosis.

Park, Han↗

NASA NTRS1979

Exploratory study of the influence of wing leading-edge modifications on the spin characteristics of a low-wing single-engine general aviation airplane

A wide variety of model and airplane tests were conducted to explore the effects of wing leading-edge modifications on the stalling and spinning characteristics of a low-wing general aviation research airplane configuration. The results presented herein discuss the effects of leading-edge airfoil modifications applied to the full wing span and to partial-span locations. The results obtained in the study indicate that the wing modifications can produce large effects (both favorable or unfavorable) on spin resistance, developed spin characteristics, and spin recovery.

Dicarlo, D. J.↗

DOE OSTI2020

Modeling sediment diagenesis processes on riverbed to better quantify aquatic carbon fluxes and stocks in a small watershed of the Mid-Atlantic region

Background: Despite the widely recognized importance of aquatic processes for bridging gaps in the global carbon cycle, there is still a lack of understanding of the role of riverbed processes for carbon flows and stocks in aquatic environments. Here, we added a sediment diagenesis and sediment carbon (C) resuspension module into the SWAT-C model and tested it for simulating both particulate organic C (POC) and dissolved organic C (DOC) fluxes using 4 years of monthly observations (2014–2017) in the Tuckahoe watershed (TW) in the U.S. Mid-Atlantic region. Results: Sensitivity analyses show that parameters that regulate POC deposition in river networks are more sensitive than those that determine C resuspension from sediments. Further analyses indicate that allochthonous contributions to POC and DOC are about 36.6 and 46 kgC ha –1 year –1 , respectively, while autochthonous contributions are less than 0.72 kgC ha –1 year –1 for both POC and DOC (less than 2% of allochthonous sources). The net deposition of POC on the riverbed (i.e., 11.4 kgC ha –1 year –1 ) retained ca. 31% of terrestrial inputs of POC. In addition, average annual buried C was 0.34 kgC ha –1 year –1 , accounting for only 1% of terrestrial POC inputs or 3% of net POC deposition. The results indicate that about 79% of deposited organic C was converted to inorganic C (CH 4 and CO 2 ) in the sediment and eventually released into the overlying water column. Conclusion: This study serves as an exploratory study on estimation of C fluxes from terrestrial to aquatic environments at the watershed scale. We demonstrated capabilities of the SWAT-C model to simulate C cycling from uplands to riverine ecosystems and estimated C sinks and sources in aquatic environments. Overall, the results highlight the importance of including carbon cycle dynamics within the riverbed in order to accurately estimate aquatic carbon fluxes and stocks. The new capabilities of SWAT-C are expected to serve as a useful tool to account for those processes in watershed C balance assessment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗

DOE OSTI2023

Exploring fingerprints of ultrafast structural dynamics in molecular solutions with an X-ray laser

We apply ultrashort x-ray laser pulses to track optically excited structural dynamics of [Ir 2 (dimen) 4 ] 2+ molecules in solution. In our exploratory study we determine angular correlations in the scattered x-rays, which comprise a complex fingerprint of the ultrafast dynamics. Model-assisted analysis of the experimental correlation data allows us to elucidate various aspects of the photoinduced changes in the excited molecular ensembles. We unambiguously identify that in our experiment the photoinduced transition dipole moments in [Ir 2 (dimen) 4 ] 2+ molecules are oriented perpendicular to the Ir-Ir bond. The analysis also shows that the ground state conformer of [Ir 2 (dimen) 4 ] 2+ with a larger Ir–Ir distance is mostly responsible for the formation of the excited state. We also reveal that the ensemble of solute molecules can be characterized with a substantial structural heterogeneity due to solvent influence. In conclusion, the proposed x-ray correlation approach offers an alternative path for studies of ultrafast structural dynamics of molecular ensembles in the liquid and gas phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1997

Determination of Stress Intensity Factor Distributions for "Interface" Cracks in Incompressible, Dissimilar Materials

The present study was undertaken in order to develop test methods and procedures for measuring the variation of the stress intensity factor through the thickness in bimaterial specimens containing cracks within and parallel to the bond line using the frozen stress photoelastic method. Since stress freezing materials are incompressible above critical temperature, and since thick plates are to be employed which tend to produce a state of plane strain near the crack tip, the interface near tip fracture equations reduce to the classic form for homogeneous materials. Moreover, zero thickness interfaces do not exist when materials are bonded together. It was decided early on that it would be important to insure a uniform straight and accurate crack tip region through the thickness of the body to reduce scatter in the SIF distribution through the thickness. It was also observed that rubberlike materials which were desired to be modeled exhibited significant tip blunting prior to crack extension and that some blunting of the tip would provide a more realistic model. It should be noted that, in normal stress freezing photoelastic work, it is considered good practice to avoid utilizing data near bond lines in photoelastic models due to the bond line stresses which inevitably develop when two parts are bonded together. Thus, the present study involves certain exploratory aspects in deviating from standard practice in stress freezing work. With the above ideas in mind, several different test methods were investigated and are described in the following sections and appendices. The geometry selected for the program was a thick, edge cracked specimen containing a bond line.

Smith, C. W.↗

DOE OSTI2021

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗