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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Plasma processes in the inner coma

The physical processes that determine the plasma behavior in the inner coma region of active comets are reviewed. Results of observations of the plasma and fields inside the cometopause of Comets Halley and Giacobini-Zinner by instruments on board several spacecraft are presented. Several plasma populations are found to exist in the inner coma. The characteristics of a particular population are largely determined by how far upstream the population was created. All particle populations in the inner coma are strongly affected by collisional processes, such as charge-transfer, ion-neutral chemistry, ion-neutral friction, and thermal cooling. Plasma processes, in the form of magnetohydrodynamics, are also important in the inner coma.

Cravens, T. E.↗
NASA NTRS2002

Convective Systems during the South China Sea Monsoon Onset and Post-Onset Simulated by a Cloud Resolving Model Using SCSMEX Data

South China Sea Monsoon Experiment (SCSMEX, 1998), one of several major TRMM field experiments, has successfully obtained a wealth of information and observational data on the summer monsoon onset and evolution in the South China Sea region. The primary goal of the experiment is to provide a better understanding of the key physical processes for the onset and maintenance of the monsoon over Southeast Asia and southern China leading to improved predictions. In this paper, our objective is to investigate the major physical and microphysical processes involved in the convective systems that developed during the onset and post-onset of the South China Sea monsoon - for both the similarities and differences between these two phases. There are two episodes simulated in this study, one of the onset period (May 18-26, 1998) and one of the post-onset period (June 2-11, 1998). The focus of this paper is to study four major aspects between these two different episodes. First, characteristics of rainfall such as rainfall amount and occurrence in the convective and stratiform regions are investigated, as well as the propagation of convective systems. The numerical precipitation fields are also validated against both the TRMM Microwave Imager (TMI) soundings and Precipitation Radar (PR) observations. Second, the domain-averaged heat and moisture budgets are analyzed to comprehend the essential roles played by physical processes such as the large-scale forcing and latent heat flux. Third, the microphysical processes associated with warm rain or ice are also closely examined during these two episodes. Finally, vertical distributions of Q1 and Q2 budgets are presented to perform a detailed discussion on the energy and moisture cascade in the vertical direction.

Shie, C.-L.↗
DOE OSTI2026

A hybrid Penman-Monteith and machine learning model for simulating evapotranspiration and its components

Integrating physical processes with machine learning has advanced evapotranspiration (ET) simulation, yet most hybrid models fail to partition total ET into its components: soil evaporation (E) and vegetation transpiration (T). This study introduces Residual Neural Network–Penman–Monteith (RNN-PM), a novel hybrid dual-source ET model designed to overcome this limitation. The model synergizes the physically-based Penman–Monteith framework with three specialized residual neural networks trained to estimate key conductance parameters (canopy conductance, soil surface conductance, and aerodynamic conductance). Furthermore this explicit parameterization allows for the direct partitioning of total ET. Validation at National Ecological Observatory Network (NEON) flux sites using high-frequency partitioned E and T shows that RNN-PM reliably reproduces ET and the transpiration fraction (T/ET). For ET, the model achieves an average Kling–Gupta efficiency (KGE) of 0.89 and a root-mean-square error (RMSE) of 0.55 mm/day; for T/ET, the KGE is 0.87 with an RMSE of 0.06. Furthermore, RNN-PM demonstrates robust generalization, accurately simulating ET and its components well beyond the initial training dataset, even under extreme climatic conditions. This study extended the analysis by comparing the RNN-PM model with seven established dual-source ET models. The results indicate that RNN-PM outperforms both conventional machine learning models and purely physical process-based models in simulating ET components in most cases. Among the purely physical process-based dual-source models, those based on surface temperature decomposition showed improved performance as the leaf area index (LAI) decreased when evaluated against high-frequency ET component datasets. In contrast, the performance of conductance-based dual-source models declined with decreasing LAI. Although purely machine learning-based models can produce relatively accurate simulations of ET components, they often exhibit limited generalization capability, an issue that the RNN-PM model effectively overcomes. Ultimately, the RNN-PM model represents a significant advance in simulating ET components, offering a novel and scalable approach for improving the representation of land–atmosphere interactions in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Experimental and simulation study of target biasing effects on plasma transport in linear plasma device MPS-LD

Linear plasma devices (LPDs) are important experimental platforms for investigating plasma–material interactions (PMI). In PMI experiments, it has been found that applying a target bias not only effectively modifies the incident ion energy, but also induces significant changes in the electron density and electron temperature, whereby the evolution of these plasma parameters is primarily governed by plasma transport processes. However, at present, the physical process and mechanism underlying such bias-induced variations remain unclear. In this work, biasing experiments under argon plasma discharge conditions were first carried out on the MPS-LD device. For the corresponding experiments, an electric potential model was newly developed based on the BOUT++ LPD module, enabling self-consistent simulations of plasma transport under biased conditions. Numerical simulations were then performed to reproduce the experimental results and to validate the accuracy of the proposed model. Finally, by combining experimental measurements with numerical simulations, a bias-voltage scan was performed to investigate how the electron density and electron temperature vary with the bias voltage (U bias ). The results show that applying negative bias decreases the target electron density (n e,T ) while increasing the target electron temperature (T e,T ). In contrast, positive bias increases both n e,T and T e,T ; however, at high positive bias, n e,T first reaches a maximum and subsequently decreases with further increases in U bias . The underlying physical mechanisms are analyzed using particle flux, momentum, and energy conservation. It indicates that the applied bias regulates the parallel electric field, thereby changing ion and electron velocities, and consequently affecting the electron density. At high positive bias, the ion velocity is further influenced by ion viscosity, leading to the reversal in n e,T . Meanwhile, the enhanced parallel electric field drives stronger currents, significantly increasing ion–electron frictional work and converting the input bias power into electron energy, which raises the electron temperature. In conclusion, these results contribute to a deeper understanding of the effects and mechanisms of biasing on plasma transport in the MPS-LD device.

BOUT++ simulation↗
NASA NTRS2016

Aerosol Complexity and Implications for Predictability and Short-Term Forecasting

There are clear NWP and climate impacts from including aerosol radiative and cloud interactions. Changes in dynamics and cloud fields affect aerosol lifecycle, plume height, long-range transport, overall forcing of the climate system, etc. Inclusion of aerosols in NWP systems has benefit to surface field biases (e.g., T2m, U10m). Including aerosol affects has impact on analysis increments and can have statistically significant impacts on, e.g., tropical cyclogenesis. Above points are made especially with respect to aerosol radiative interactions, but aerosol-cloud interaction is a bigger signal on the global system. Many of these impacts are realized even in models with relatively simple (bulk) aerosol schemes (approx.10 -20 tracers). Simple schemes though imply simple representation of aerosol absorption and importantly for aerosol-cloud interaction particle-size distribution. Even so, more complex schemes exhibit a lot of diversity between different models, with issues such as size selection both for emitted particles and for modes. Prospects for complex sectional schemes to tune modal (and even bulk) schemes toward better selection of size representation. I think this is a ripe topic for more research -Systematic documentation of benefits of no vs. climatological vs. interactive (direct and then direct+indirect) aerosols. Document aerosol impact on analysis increments, inclusion in NWP data assimilation operator -Further refinement of baseline assumptions in model design (e.g., absorption, particle size distribution). Did not get into model resolution and interplay of other physical processes with aerosols (e.g., moist physics, obviously important), chemistry

Predictability↗
NASA NTRS1981

Solar Corona Explorer: A mission for the physical diagnosis of the solar corona

Mission objectives and spacecraft requirements for the Solar Corona Explorer (SCE), a proposed free flying, unmanned solar research craft to be tenatively launched in 1987, were defined. The SCE's purpose is to investigate structure, dynamics and evolution of the corona, globally and in the required physical detail, to study the close coupling between the inner corona and the heliosphere. Investigative objectives are: (1) to understand the corona as the source of varying interplanetary plasma and of varying solar X-ray and extreme ultraviolet fluxes; (2) to develop the capabilities to model the corona with sufficient precision to forecast the Earth's variable environment in space, on the scales from weeks to years; (3) to develop an understanding of the physical processes that determine the dynamics and physical state of the coronal plasma, particularly acceleration processes; and (4) to develop insight and test theory on the Sun applicable to stellar coronae and winds, and in particular, to understand why cool stars put such a large fraction of their energy into X-rays. Considered related factors are: (1) duration of the mission; (2) onboard measuring instrumentation; (3) ground support equipment and procedures; and (4) programs of interpretation and modeling.

Source record↗
NASA NTRS2011

Model-Based Diagnostics for Propellant Loading Systems

The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are necessary to quickly identify when a fault occurs, so that recovery actions can be taken or an abort procedure can be initiated. Model-based diagnosis solutions, established using an in-depth analysis and understanding of the underlying physical processes, offer the advanced capability to quickly detect and isolate faults, identify their severity, and predict their effects on system performance. We develop a physics-based model of a cryogenic propellant loading system, which describes the complex dynamics of liquid hydrogen filling from a storage tank to an external vehicle tank, as well as the influence of different faults on this process. The model takes into account the main physical processes such as highly nonequilibrium condensation and evaporation of the hydrogen vapor, pressurization, and also the dynamics of liquid hydrogen and vapor flows inside the system in the presence of helium gas. Since the model incorporates multiple faults in the system, it provides a suitable framework for model-based diagnostics and prognostics algorithms. Using this model, we analyze the effects of faults on the system, derive symbolic fault signatures for the purposes of fault isolation, and perform fault identification using a particle filter approach. We demonstrate the detection, isolation, and identification of a number of faults using simulation-based experiments.

Daigle, Matthew John↗
NASA NTRS1982

Rayleigh, Raman and particulate scattering

Analysis of the visible and near infrared spectra of planetary atmospheres and the multiple scattering of photons within the atmosphere are discussed. Photons detected within the spectral region are solar photons which were scattered by the gas and particles in the planetary atmosphere. An example is given for the incident and emitted fluxes for a hypothetical planet with an effective temperature of 100 K. The absorption spectrum of the planetary atmosphere is discussed in terms of the various scattering processes photons undergo within the atmosphere. Three different physical processes are considered. Rayleigh scattering and Raman scattering by the gas molecules, and scattering by any cloud or dust aerosol particles in the atmosphere. The physics of each of these processes is examined.

Cochran, W. D.↗
NASA NTRS1987

NASA's solar maximum mission: A look at a new Sun

As part of the ongoing process of trying to understand the physical processes at work in the Sun, the Solar Maximum Mission (SMM) spacecraft was launched on February 14, 1980, near the height of the solar cycle, to enable the solar physics community to examine, in more physically meaningful detail than ever before, the most violent aspect of solar activity: flares. The scientific products of SMM are substantial: by 1986, over 400 papers based on SMM observations and their interpretations had appeared in scientific journals. More important than such numerical measures of success is the significance of the science that has come from SMM. The following topics, the Sun as a star, solar flares, and the active solar atmosphere, as well as other findings of SMM investigators are described. The instruments on the SMM are also described.

Gurman, Joseph B.↗
DOE OSTI2024

Debunking common myths in coastal circulation modeling

Despite tremendous progress in algorithm development, computational efficiency and transition into operations over the past two decades, coastal modeling still lacks scientific rigor due to proliferation of many ‘gray’ areas related to various modeling choices made by modelers. Here, in this paper, we propose some guiding principles for the modeling community to improve performance, and we also debunk commonly held myths that make the coastal modeling lack rigor. Using our own experience in developing seamless cross-scale unstructured-grid based models for the past two decades, we describe in unprecedented detail the end-to-end modeling process (i.e., from digital elevation models (DEMs) to mesh generation to post analysis), and demonstrate that defensible modeling is within reach for any end user by following three guiding principles: (1) Bathymetry is a first order forcing in coastal domains and thus should be respected in all aspects of modeling; (2) Oceanographic processes are driven across multiple spatial scales and so models should enable appropriate resolution as needed; and (3) Model assessment should focus on physical processes. Through qualitative and quantitative model assessments, we demonstrate the fundamental role played by bathymetry/topography as embedded in DEMs in making the results defensible, which is unfortunately glossed over in many modeling studies. Focusing on process-based assessment simplifies the calibration process. A major conclusion of this work is that model developers and operators should maximize the scientific rigor for in silico oceanography by avoiding some common pitfalls that rely on error compensation at the expense of representation of physical system processes. We present some best practice procedures for defensive and trustworthy numerical modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Assessment of Oceanographic Conditions during the North Atlantic EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) Field Campaign

This manuscript presents an overview of NASA’s EXport Processes in the Ocean from Remote Sensing 2021 Field Campaign in the North Atlantic (EXPORTS NA) and provides quantitative and dynamical descriptions of the physical processes modulating water transformations during the study. A major programmatic goal was to conduct the sampling in a Lagrangian mode so that ocean ecological and biogeochemical changes can be observed independent from physical advective processes. To accomplish this goal, EXPORTS NA conducted a multi-ship, multi-asset field sampling program within a retentive, anticyclonic mode water eddy. Beneath depths of ∼100 m, Lagrangian sampling assets remained within the eddy core waters (ECWs) throughout the experiment, demonstrating that the ECWs within the mode water eddy were retentive. However, strong westerly winds from four storm events deepened the mixed layer (ML) of the surface core waters (SCWs) above the eddy’s mode water core by 25-40 m and exchanged some of the SCWs with surface waters outside of the eddy via Ekman transport. Estimates of flushing times ranged from 5-8 days, with surface exchange fractions ranging from 20-75% and were consistent with particle tracking advected by combined geostrophic and Ekman velocities. The relative contributions of horizontal and vertical advection on changes in ECW tracers depended on the horizontal and vertical gradients of that tracer. For example, horizontal advection played a large role in ECW salinity fluxes, while vertical entrainment played a larger role in the fluxes of nutrients into SCW ML. Each storm injected nutrients and low oxygen waters into the ML, after which the surface ocean ecosystem responded by reducing nutrient concentrations and increasing %O2 saturation levels. Overall, ECW values of chlorophyll and POC were the largest at the onset of the field program and decreased throughout the campaign. The analysis presented provides a physical oceanographic context for the many measurements made during the EXPORTS NA field campaign while illustrating the many challenges of conducting a production-flux experiment, even in a Lagrangian frame, and the inherent uncertainties of interpreting biological carbon pump observations that were collected in a Eulerian frame of reference.

oceanography↗
NASA NTRS2019

The Physics of Accretion Onto Highly Magnetized Neutron Stars

Studying the physical processes occurring in the region just above the magnetic polesof strongly magnetized, accreting binary neutron stars is essential to our understanding of stellarand binary system evolution. Perhaps more importantly, it provides us with a natural laboratoryfor studying the physics of high temperature and density plasmas exposed to extreme radiation,gravitational, and magnetic fields. Observations over the past decade have shed new light on themanner in which plasma falling at near the speed of light onto a neutron star surface is halted. Recentadvances in modeling these processes have resulted in direct measurement of the magnetic fieldsand plasma properties. On the other hand, numerous physical processes have been identified thatchallenge our current picture of how the accretion process onto neutron stars works. Observationand theory are our essential tools in this regime because the extreme conditions cannot be duplicatedon Earth. This white paper gives an overview of the current theory, the outstanding theoreticaland observational challenges, and the importance of addressing them in contemporary astrophysicsresearch.

Wolff, Michael T.↗
DOE OSTI2026

DAMSA Experiment Conceptual Design White Paper

DAMSA (DArk Messenger Searches at an Accelerator) is a novel short-baseline accelerator experiment aimed at probing short-lived physics processes, including searches for evidence of a dark sector of particle physics and well-motivated Standard Model signals. Motivated by open questions in neutrino physics and the absence of conclusive evidence for conventional weakly interacting massive particles, DAMSA targets MeV-to-sub-GeV dark-sector messengers with feeble couplings that can be produced in abundance at the PIP-II LINAC. By employing an ultra-short baseline of order one meter, DAMSA is uniquely positioned to overcome the beam-dump "ceiling" that limits sensitivity to promptly decaying particles in longer-baseline experiments. The conceptual design emphasizes a beam-dump production scheme combined with a compact detector optimized for rare decays while mitigating intense neutron-induced backgrounds inherent to high-power proton beams. To validate the experimental strategy and detector technologies, the Little DAMSA Path-Finder (LDPF) proof-of-concept experiment is proposed, focusing on axion-like particles decaying to two photons and operating with 300 MeV electron beams at FAST. Successful realization of LDPF will establish the feasibility of the DAMSA approach, enabling a broad and powerful program to explore short-lived new physics and precision Standard Model processes in a previously inaccessible regime. This conceptual design document outlines the technical details of DAMSA's physics goals, the beam facility proposals, key experimental challenges and how to overcome them, and the proposed experimental staging campaigns.

Bhattarai, Prithak [Texas U., Arlington]↗
NASA NTRS1993

Arcjet space thrusters

Electrically powered arc jets which produce thrust at high specific impulse could provide a substantial cost reduction for orbital transfer and station keeping missions. There is currently a limited understanding of the complex, nonlinear interactions in the plasma propellant which has hindered the development of high efficiency arc jet thrusters by making it difficult to predict the effect of design changes and to interpret experimental results. A computational model developed at the University of Tennessee Space Institute (UTSI) to study laser powered thrusters and radio frequency gas heaters has been adapted to provide a tool to help understand the physical processes in arc jet thrusters. The approach is to include in the model those physical and chemical processes which appear to be important, and then to evaluate our judgement by the comparison of numerical simulations with experimental data. The results of this study have been presented at four technical conferences. The details of the work accomplished in this project are covered in the individual papers included in the appendix of this report. We present a brief description of the model covering its most important features followed by a summary of the effort.

Keefer, Dennis↗
NASA NTRS2015

Why Is Improvement of Earth System Models so Elusive? Challenges and Strategies from Dust Aerosol Modeling

Past decades have seen an accelerating increase in computing efficiency, while climate models are representing a rapidly widening set of physical processes. Yet simulations of some fundamental aspects of climate like precipitation or aerosol forcing remain highly uncertain and resistant to progress. Dust aerosol modeling of soil particles lofted by wind erosion has seen a similar conflict between increasing model sophistication and remaining uncertainty. Dust aerosols perturb the energy and water cycles by scattering radiation and acting as ice nuclei, while mediating atmospheric chemistry and marine photosynthesis (and thus the carbon cycle). These effects take place across scales from the dimensions of an ice crystal to the planetary-scale circulation that disperses dust far downwind of its parent soil. Representing this range leads to several modeling challenges. Should we limit complexity in our model, which consumes computer resources and inhibits interpretation? How do we decide if a process involving dust is worthy of inclusion within our model? Can we identify a minimal representation of a complex process that is efficient yet retains the physics relevant to climate? Answering these questions about the appropriate degree of representation is guided by model evaluation, which presents several more challenges. How do we proceed if the available observations do not directly constrain our process of interest? (This could result from competing processes that influence the observed variable and obscure the signature of our process of interest.) Examples will be presented from dust modeling, with lessons that might be more broadly applicable. The end result will either be clinical depression or there assuring promise of continued gainful employment as the community confronts these challenges.

Climate models↗
NASA NTRS1985

Experimental characterization of fatigue crack tip processes

Many analytical models have been proposed to describe the physical processes attendant to a fatigue crack tip, as well as the rate at which fatigue cracks grow. By applying advanced experimental methods (such as electron channeling, stereoimaging, and in-situ cyclic loading in an SEM) to a broad range of structural materials, it has been shown that it is possible to critically assess the physical assumptions incorporated into the models. Refinements in existing models and the development of new ones have resulted. New insights into materials' behavior are providing guidelines for improving the fatigue resistance of structural alloys. In the near future, even more advanced experimental methods, such as high temperature SEM stages and small angle neutron scattering, will be available to study creep/fatigue interactions in metals and ceramics.

Lankford, J.↗
NASA NTRS1990

Masking failures of multidimensional sensors (extended abstract)

When a computer monitors a physical process, the computer uses sensors to determine the values of the physical variables that represent the state of the process. A sensor can sometimes fail, however, and in the worst case report a value completely unrelated to the true physical value. The work described is motivated by a methodology for transforming a process control program that can not tolerate sensor failure into one that can. In this methodology, a reliable abstract sensor is created by combining information from several real sensors that measure the same physical value. To be useful, an abstract sensor must deliver reasonably accurate information at reasonable computational cost. Sensors are considered that deliver multidimensional values (e.g., location or velocity in three dimensions, or both temperature and pressure). Geometric techniques are used to derive upper bounds on abstract sensor accuracy and to develop efficient algorithms for implementing abstract sensors.

Chew, Paul↗