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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 181 records · Page 10

Irreversible wave-mean flow interactions in a mechanistic model of the stratosphere

A wave-1 minor warming is simulated in a mechanistic, global, primitive equation model. The modification of the zonal flow by the rearrangement of potential vorticity on a middle stratopheric isentrope is compared in a fully nonlinear model and in a model with only one wave and the zonal flow (a quasi-linear model). The permanent rearrangement of potential vorticity during the wave episode is more intense and more localized meridionally in the fully nonlinear model, which is able to capture the process of planetary wave breaking in some detail. Additional experiments reveal that the differences between the quasi-linear and nonlinear models persist for a broad range of wave amplitudes, and that the quasi-linear model can qualitatively reproduce the modification of the zonal flow by the wave when the diffusive dissipation of the wave is enhanced. These results are discussed in the context of the theory of barotropic Rossby waves in shear flows, and in comparison with recent numerical simulations of the middle atmosphere.

Robinson, Walter A.↗

Modeling dynamically coupled fluid-duct systems with finite line elements

Structural analysis of piping systems, especially dynamic analysis, typically considers the duct structure and the contained fluid column separately. Coupling of these two systems, however, forms a new dynamic system with characteristics not necessarily described by the superposition of the two component system's characteristics. Methods for modeling the two coupled components simultaneously using finite line elements are presented. Techniques for general duct intersections, area or direction changes, long radius bends, hydraulic losses, and hydraulic impedances are discussed. An example problem and results involving time transients are presented. Additionally, a program to enhance post-processing of line element models is discussed.

Saxon, J. B.↗

TPSAS-NF1676L-33873-DND

NOAA's National Air Quality Forecasting Capability (NAQFC) model provides 48-hour forecast of surface ozone and other atmospheric constituents serving as the nation's key tool actively used by regulatory professionals in assessing air quality events and the issuance of public air quality alerts. NAQFC incorporates input meteorology from North American Mesoscale Model (NAM) at 12 km horizontal resolution that is coupled to the Community Multi-scale Air Quality Model (CMAQ) to predict emissions, tropospheric gas and aerosol chemistry, and related deposition and removal processes. The NAQFC forecast simulations contain 35 steps in altitude, with about one third of these in a typical afternoon daytime boundary layer (0-1.5 km). While several studies have been conducted comparing NAQFC predictions to surface observations, investigations comparing the vertical distribution to observations remain limited. Vertical comparisons are needed in order to fully assess forecast model behavior and atmospheric mixing conditions leading to the formation of ozone at the surface. The Tropospheric Ozone Lidar Network (TOLNet) instruments provide a unique observational capability in this regard, as ozone vertical measurements can be directly compared to models, such as NAQFC, and provide additional insight into atmospheric processes and enhance forecast capabilities. In this study, we utilize multiple TOLNet lidar observations obtained during the Ozone Water Land Environmental Transition Studies (OWLETS-2017 & OWLETS-2018) and the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) to compare with NAQFC vertical predictions of ozone. These campaigns took place at different coastal locations along the US East coast with each campaign having multiple TOLNet lidars present, providing a unique opportunity to examine vertical structure of ozone in regions with complex water-land boundaries. Preliminary comparison results will be presented on ozone temporal and vertical differences between NAQFC and the TOLNet lidars along with example case studies to illustrate insights into boundary layer and surface processes of trace gases.

Timothy Berkoff↗

Chemical Reaction and Flow Modeling in Fullerene and Nanotube Production

The development of processes to produce fullerenes and carbon nanotubes has largely been empirical. Fullerenes were first discovered in the soot produced by laser ablation of graphite [1]and then in the soot of electric arc evaporated carbon. Techniques and conditions for producing larger and larger quantities of fullerenes depended mainly on trial and error empirical variations of these processes, with attempts to scale them up by using larger electrodes and targets and higher power. Various concepts of how fullerenes and carbon nanotubes were formed were put forth, but very little was done based on chemical kinetics of the reactions. This was mainly due to the complex mixture of species and complex nature of conditions in the reactors. Temperatures in the reactors varied from several thousand degrees Kelvin down to near room temperature. There are hundreds of species possible, ranging from atomic carbon to large clusters of carbonaceous soot, and metallic catalyst atoms to metal clusters, to complexes of metals and carbon. Most of the chemical kinetics of the reactions and the thermodynamic properties of clusters and complexes have only been approximated. In addition, flow conditions in the reactors are transient or unsteady, and three dimensional, with steep spatial gradients of temperature and species concentrations. All these factors make computational simulations of reactors very complex and challenging. This article addresses the development of the chemical reaction involved in fullerene production and extends this to production of carbon nanotubes by the laser ablation/oven process and by the electric arc evaporation process. In addition, the high-pressure carbon monoxide (HiPco) process is discussed. The article is in several parts. The first one addresses the thermochemical aspects of modeling; and considers the development of chemical rate equations, estimates of reaction rates, and thermodynamic properties where they are available. The second part addresses modeling of the arc process for fullerene and carbon nanotube production using O-D, 1-D and 2-D fluid flow models. The third part addresses simulations of the pulsed laser ablation process using time-dependent techniques in 2-D, and a steady state 2-D simulation of a continuous laser ablation process. The fourth part addresses steady state modeling in O-D and 2-D of the HiPco process. In each of the simulations, there is a variety of simplifications that are made that enable one to concentrate on one aspect or another of the process. There are simplifications that can be made to the chemical reaction models , e.g. reduction in number of species by lumping some of them together in a representative species. Other simulations are carried out by eliminating the chemistry altogether in order to concentrate on the fluid dynamics. When solving problems with a large number of species in more than one spatial dimension, it is almost imperative that the problem be decoupled by solving for the fluid dynamics to find the fluid motion and temperature history of "particles" of fluid moving through a reactor. Then one can solve the chemical rate equations with complex chemistry following the temperature and pressure history. One difficulty is that often mixing with an ambient gas is involved. Therefore, one needs to take dilution and mixing into account. This changes the ratio of carbon species to background gas. Commercially available codes may have no provision for including dilution as part of the input. One must the write special solvers for including dilution in decoupled problems. The article addresses both ful1erene production and single-walled carbon nanotube (SWNT) production. There are at least two schemes or concepts of SWNT growth. This article will only address growth in the gas phase by carbon and catalyst cluster growth and SW T formation by the addition of carbon. There are other models that conceive of SWNT growth as a phase separation process from clusters me up carbon and metal catalyst, with the carbon precipitating from the cluster as it cools. We will not deal with that concept in this article. Further research is needed to determine the rates at which these composite clusters form, evaporate, and segregate.

Scott, Carl D.↗

Augmenting Topic Finding in the NASA Aviation Safety Reporting System using Topic Modeling

Context: The NASA Aviation and Safety Reporting System (ASRS) provides various publications to the aviation community (including individual anonymous reports, Callback, Database Search Requests, Directline, and Alerting Messages). Key to these publications are the timely processing of new reports, which is currently done mostly manually by ASRS staff, and which the volume increases yearly. Aim: We investigate whether existing topic modelling techniques are suitable to ease some of the manual effort, and to enhance it with additional visual cues regarding the process of grouping, sense making and labeling incoming (and previous) reports. Method: We evaluate the applicability of WarpLDA topic modelling results combined with three visualization tools, the first two of which have been extended by us in this work for ASRS: Termite, TopicFlow, and LDAVis. Based on the identified limitations in these tools, we propose a methodology for improving them, and evaluate their outputs using ASRS as our test dataset. Results: The user interfaces of Termite, Topicflow and LDAVis were found insufficient for sense-making of the narratives. Moreover, concerns regarding the stability of results due to the inherent randomness of topic modelling, and the lack of a measurable approach for evaluation against the existing ASRS manual workflow were also noted. Conclusion: While many tools to topic modeling and visualization have been proposed, more work is necessary before they can be applied in practical situations to improve existing manual workflows. The methodology presented and applied in this work contribute towards this effort.

ASRS↗

Regional scale hydrology with a new land surface processes model

Through the CaPE Hydrometeorology Project, we have developed an understanding of some of the unique data quality issues involved in assimilating data of disparate types for regional-scale hydrologic modeling within a GIS framework. Among others, the issues addressed here include the development of adequate validation of the surface water budget, implementation of the STATSGO soil data set, and implementation of a remote sensing-derived landcover data set to account for surface heterogeneity. A model of land surface processes has been developed and used in studies of the sensitivity of surface fluxes and runoff to soil and landcover characterization. Results of these experiments have raised many questions about how to treat the scale-dependence of land surface-atmosphere interactions on spatial and temporal variability. In light of these questions, additional modifications are being considered for the Marshall Land Surface Processes Model. It is anticipated that these techniques can be tested and applied in conjunction with GCIP activities over regional scales.

Laymon, Charles↗

Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms

Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗

Solar Concentrator Demonstrator for Lunar Regolith Processing

NASA at the Marshall Space Flight Center (MSFC) is building a portable inflatable solar concentrator ground demonstrator for use in testing in-situ resource utilization (ISRU) lunar regolith processing methods. Of primary interest is the production of oxygen as a propellant oxidizer and for life support. There are various processes being proposed for the in-situ reduction of the lunar regolith, the leading processes are hydrogen reduction, carbothermal reduction and vapor phase pyrolysis. The concentrator system being built at MSFC could support demonstrations of all of these processes. The system consists of a light inflatable concentrator that will capture sunlight and focus it onto a receiver inside a vacuum chamber. Inflatable concentrators are good for space based applications due to their low weight and dense packaging at launch. The hexapod design allows the spot size to be increased to reduce the power density if needed for the process being demonstrated. In addition to the hardware development, a comprehensive simulation model is being developed and will be verified and validated using the system hardware. The model will allow for the evaluation of different lunar locations and operational scenarios for the lunar regolith processing with a high confidence in the predicted results.

Fikes, John C.↗

Understanding the causes of satellite–model discrepancies in aerosol–cloud interactions using near-LES simulations of marine boundary layer clouds

Aerosol–cloud interactions (ACI) remain the largest source of uncertainty in model estimates of anthropogenic radiative forcing, primarily because of deficiencies in representing aerosol–cloud microphysical processes that lead to inconsistent cloud liquid water path (LWP) responses to aerosol perturbations between observations and models. To investigate this discrepancy, we conducted a series of large-eddy-scale simulations driven by realistic meteorology over the eastern North Atlantic, and evaluated LWP susceptibility, precipitation processes, and boundary layer thermodynamics using satellite and ground-based observations. Simulated LWP responses show a strong dependence on cloud state. Non-precipitating thin clouds exhibit a modest LWP decrease with increasing cloud droplet number concentration (N d ), consistent in sign but weaker in magnitude than satellite estimates, reflecting enhanced turbulent mixing and evaporation. The largest model-observation discrepancy occurs in non-precipitating thick clouds, where simulated LWP susceptibilities are strongly positive (+0.32) while observations indicate large negative values (−0.69). This discrepancy stems from excessive precipitation driven by underestimated entrainment, overly active accretion, and overly broad drop-size distributions in polluted conditions. While our high-resolution setup mitigates the excessive drizzling common in coarser models and captures key regime transitions, these biases persist – highlighting that improved parameterizations of cloud-top processes, precipitation, and aerosol effects are needed beyond simply increasing model resolution. Additionally, misrepresented moisture inversions in reanalysis introduce a moist bias in cloud-top relative humidity, further amplifying positive LWP susceptibility. Our results also suggest that large negative N d –LWP relationships in observations may reflect internal cloud processes rather than true ACI effects.

Aerosol-cloud interaction↗

Fidelity Analysis of Sampled Imaging Systems

Many modeling, simulation and performance analysis studies of sampled imaging systems are inherently incomplete because they are conditioned on a discrete-input, discrete-output model that only accounts for blurring during image acquisition and additive noise. For those sampled imaging systems where the effects of digital image acquisition, digital filtering and reconstruction are significant, the modeling, simulation and performance analysis should be based on a more comprehensive continuous-input, discrete-processing, continuous-output end-to-end model. This more comprehensive model should properly account for the low-pass filtering effects of image acquisition prior to sampling, the potentially important noiselike effects of the aliasing caused by sampling, additive noise due to device electronics and quantization, the generally high-boost filtering effects of digital processing, and the low-pass filtering effects of image reconstruction. This model should not, however, be so complex as to preclude significant mathematical analysis, particularly the mean-square (fidelity) type of analysis so common in linear system theory. We demonstrate that, although the mathematics of such a model is more complex, the increase in complexity is not so great as to prevent a complete fidelity-metric analysis at both the component level and at the end-to-end system level: that is, computable mean-square-based fidelity metrics are developed by which both component-level and system-level performance can be quantified. In addition, we demonstrate that system performance can be assessed qualitatively by visualizing the output image as the sum of three component images, each of which relates to a corresponding fidelity metric. The cascaded, or filtered, component accounts for the end-to-end system filtering of image acquisition, digital processing, and image reconstruction; the random noise component accounts for additive random noise, modulated by digital processing and image reconstruction filtering; and the aliased noise component accounts for the frequency folding effect of sampling, modulated by digital processing and image reconstruction filtering.

Park, Stephen K.↗

Challenges in Laser Sintering of Melt-Processable Thermoset Imide Resin

Polymer Laser Sintering (LS) is an additive manufacturing technique that builds 3D models layer by layer using a laser to selectively melt cross sections in powdered polymeric materials, following sequential slices of the CAD model. LS generally uses thermoplastic polymeric powders, such as polyamides (i.e. Nylon), and the resultant 3D objects are often weaker in their strength compared to traditionally processed materials, due to the lack of polymer inter-chain connection in the z-direction. The objective of this project is to investigate the possibility of printing a melt-processable RTM370 imide resin powder terminated with reactive phenylethynyl groups by LS, followed by a postcure in order to promote additional crosslinking to achieve higher temperature (250-300 C) capability. A preliminary study to build tensile specimens by LS and the corresponding DSC and rheology study of RTM370 during LS process is presented.

Additive Manufacturing↗

A study of carbon monoxide distribution determinations for a global transport model

A system of programs which model the chemistry and transport of carbon monoxide and methane in the Earth's atmosphere on a global scale was installed onto the NASA-Langley central scientific computer network. This system, the GLOBAL system, consists of a user-friendly set of procedural files which allow for simplified pre-processing, execution, and post-processing for all program elements. The package includes procedures for obtaining the NMC meteorological data, calculating the vertical winds to satisfy mass conservation, determining the boundary layer, and executing the transport/chemical model for carbon monoxide. In addition, plotting, saving to tape, and reading from tape routines were developed. Final modifications to the subprograms for processing the input data for the transport/chemistry model have improved these data to more accurately reflect true atmospheric conditions. The transfer of the transport/chemistry model from the NCAR CRAY system to the NASA-Langley VPS-32 system was completed. The problems encountered during this process and their resolutions are discussed.

Peters, Leonard K.↗

The effect of an isotopic non-equilibrium plasma on electron temperature measurements

Electron temperatures determined by electrostatic probe, diffuse resonance, and radar backscatter techniques in an isotropic two temperature plasma are presented. Plasma models corresponding to the addition of a minor component of energetic electrons, and models corresponding to a process that cools a fraction of the ionospheric electrons are considered. The diffuse resonance temperature is found to lie between the probe and radar backscatter temperatures. The isotropic models corresponding to the addition of energetic electrons cannot support the reported discrepancies between radio wave and probe electron temperature measurements. Temperature differences similar to the observed differences can be produced by models with a fraction of the electrons at a temperature cooler than that of the main component of electrons.

Benson, R. F.↗

Effect of an isotropic nonequilibrium plasma on electron temperature measurements.

The electron temperatures that would be determined (using the conventional single-temperature analysis) by the electrostatic probe, the diffuse resonance, and the radar backscatter techniques in an isotropic two-temperature plasma are presented. Plasma models corresponding to the addition of a minor component of energetic electrons and models corresponding to a process that cools a fraction of the ionospheric electrons are considered. The diffuse resonance temperature is found to lie between the probe and radar backscatter temperatures. The isotropic models corresponding to the addition of energetic electrons cannot support the reported discrepancies between radio wave and probe electron temperature measurements. Temperature differences similar to the observed differences can be produced by models with a fraction of the electrons at a temperature cooler than that of the main component of electrons. These models, however, are difficult to explain in terms of present understanding of the ionospheric plasma.

Benson, R. F.↗

Electromagnetic Dissociation Cross Sections for High LET Fragments

Nuclear interaction cross sections are used in space radiation transport codes to calculate the probability of fragment emission in high energy nucleus-nucleus collisions. Strong interactions usually dominate in these collisions, but electromagnetic (EM) interactions can also sometimes be important. Strong interactions typically occur when the projectile nucleus hits a target nucleus, with a small impact parameter. For impact parameters larger than the sum of the nuclear radii, EM reactions dominate and the process is called electromagnetic dissociation (EMD) if one of the nuclei undergo fragmentation. Previous models of EMD have been used to calculate single proton (p) production, single neutron (n) production or light ion production, where a light ion is defined as an isotope of hydrogen (H) or helium (He), such as a deuteron (2H), a triton (3H), a helion (3He) or an alpha particle (4He). A new model is described which can also account for multiple nucleon production, such as 2p, 2n, 1p1n, 2p1n, 2p2n, etc. in addition to light ion production. Such processes are important to include for the following reasons. Consider, for example, the EMD reaction 56Fe + Al --> 52Cr + X + Al, for a 56Fe projectile impacting Al, which produces the high linear energy transfer (LET) fragment 52Cr. In this reaction, the most probable particles representing X are either 2p2n or 4He. Therefore, production of the high LET fragment 52Cr, must include the multiple nucleon production of 2p2n in addition to the light ion production of 4He. Previous models, such as the NUCFRG3 model, could only account for the 4He production process in this reaction and could not account for 2p2n. The new EMD model presented in this work accounts for both the light ion and multiple nucleon processes, and is therefore able to correctly account for the production of high LET products such as 52Cr. The model will be described and calculations will be presented that show the importance of light ion and multiple nucleon production. The work will also show that EMD reactions contribute most to those fragments with the highest LET.

Norbury, John↗

Two stochastic models useful in petroleum exploration

A model of the petroleum exploration process that tests empirically the hypothesis that at an early stage in the exploration of a basin, the process behaves like sampling without replacement is proposed along with a model of the spatial distribution of petroleum reserviors that conforms to observed facts. In developing the model of discovery, the following topics are discussed: probabilitistic proportionality, likelihood function, and maximum likelihood estimation. In addition, the spatial model is described, which is defined as a stochastic process generating values of a sequence or random variables in a way that simulates the frequency distribution of areal extent, the geographic location, and shape of oil deposits

Kaufman, G. M.↗

Advanced waste management technology evaluation

The purpose of this program is to evaluate the feasibility of steam reforming spacecraft wastes into simple recyclable inorganic salts, carbon dioxide and water. Model waste compounds included cellulose, urea, methionine, Igapon TC-42, and high density polyethylenes. These are compounds found in urine, feces, hygiene water, etc. The gasification and steam reforming process used the addition of heat and low quantities of oxygen to oxidize and reduce the model compounds.The studied reactions were aimed at recovery of inorganic residues that can be recycled into a closed biologic system. Results indicate that even at very low concentrations of oxygen (less than 3%) the formation of a carbonaceous residue was suppressed. The use of a nickel/cobalt reforming catalyst at reaction temperature of 1600 degrees yielded an efficient destruction of the organic effluents, including methane and ammonia. Additionally, the reforming process with nickel/cobalt catalyst diminished the noxious odors associated with butyric acid, methionine and plastics.

Couch, H.↗

A quality-agnostic combinatoric cost estimation model for large-format directed energy deposition metal additive manufacturing

Directed energy deposition (DED) additive manufacturing (AM) processes are amenable to synergistic combination into multi-process AM systems due to similar requirements for automation and energy sources. This work analyzes the economic performance of such DED AM systems from a quality-agnostic combinatoric standpoint with a model that calculates lowest-cost system combinations based on part geometry and process performance metrics. Common DED AM systems research focuses on a single process and does not consider the process, system, and application in the context of all possible system combinations (e.g., the combined set of process selection(s), motion system(s), and process hardware), leading to limited applicability of the resulting DED AM systems to cost-sensitive components such as those found in energy generation applications. The model developed herein incorporates the capital, material, and energy costs associated with DED AM system combinations into a predictive tool for estimating part and system cost, the output of which is intended to guide deployment of finite research and development resources towards DED AM system combinations with the lowest costs and greatest likelihood of economic impact. The DED AM systems identified by this framework may enable domestic production of the large conventionally cast and forged components necessary for energy generation.

Shanafield, Alexandra [ORNL]↗