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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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Advanced Composition Explorer (ACE) satellite measurements of the galactic cosmic ray flux and correlation with the Climax Neutron Monitor count over Solar Cycle 23 are used to update the Badhwar O'Neill Galactic Cosmic Ray (GCR) model.
Method for determining orbit of Explorer VI SATELLITE - test of dynamic model atmospheres
The goal of the NASA HPCC Remote Exploration and Experimentation (REE) Project is to transfer commercial supercomputing technology into space.
Operations and support (O&S) costs for human spaceflight have not received the same attention in the cost estimating community as have development costs. This is unfortunate as O&S costs typically comprise a majority of life-cycle costs (LCC) in such programs as the International Space Station (ISS) and the now-cancelled Constellation Program. Recognizing this, the Constellation Program and NASA HQs supported the development of an O&S cost model specifically for human spaceflight. This model, known as the Exploration Architectures Operations Cost Model (ExAOCM), provided the operations cost estimates for a variety of alternative human missions to the moon, Mars, and Near-Earth Objects (NEOs) in architectural studies. ExAOCM is philosophically based on the DoD Architecture Framework (DoDAF) concepts of operational nodes, systems, operational functions, and milestones. This paper presents some of the historical background surrounding the development of the model, and discusses the underlying structure, its unusual user interface, and lastly, previous examples of its use in the aforementioned architectural studies.
In the explore the systematic construction of kinetic models from in silico reaction data for the decomposition of nitromethane. Our models are constructed in a computationally affordable manner by using reactions discovered through accelerated molecular dynamics simulations using the ReaxFF reactive force field. The reaction paths are then optimized to determine reaction rate parameters. We introduce a reaction barrier correction scheme that combines accurate thermochemical data from density functional theory with ReaxFF minimal energy paths. We validate our models across different thermodynamic regimes, showing predictions of gas phase CO and NO concentrations and high-pressure induction times that are similar to experimental data. The kinetic models are analyzed to find fundamental decomposition reactions in different thermodynamic regimes.
Ozone amounts observed at high Northern latitudes in late winter and early spring have been relatively very low in four of the last six years. On the face of it, this decline appears similar to that observed in the Antarctic in the mid-1980s in spite of the fact that the abundance of stratospheric chlorine is currently steady or decreasing. In order to predict the extent to which this change represents a trend, and to understand what combination of factors produces the low ozone, we need to accurately simulate these observations with models. In this presentation, we focus on the winter of 1999-2000, which exhibited some of the lowest ozone ever recorded in the Northern hemisphere. It also contained the largest-ever assembled set of atmospheric measurements and modeling activities in the SAGE III Ozone Loss and Validation Experiment/Third European Stratospheric Experiment on Ozone (SOLVE/THESEO). We use SOLVE/THESEO observations in comparison with the Goddard 3-D global model of stratospheric chemistry and transport to explore the model's capability to simulate the evolution of ozone and other species through the winter. We will discuss advective transport and mixing, chlorine activation, and denitrification, which are key processes to accurately simulating wintertime ozone. Preliminary results show that, although the model tracer transport and chlorine activation compare relatively well with observations, the magnitude of observed ozone loss is difficult to achieve in the model. Calculated ozone loss is sensitive to denitrification, which presents a major challenge to parameterization in a global model. Simulation requirements and uncertainties will be evaluated.
This paper will discuss the system modeling for two nearly identical spacecrafts, Mars Exploration Rovers; Spirit and Opportunity.
Transit spectroscopy of terrestrial planets around nearby M dwarfs will be a primary goal of space missions in coming decades. Three-dimensional climate modeling has shown that slow-synchronous rotating terrestrial planets may develop thick clouds at the substellar point, increasing the albedo. For M dwarfs with T(eff)>3000 K, such planets at the inner habitable zone (IHZ) have been shown to retain moist greenhouse conditions, with enhanced stratospheric water vapor ( fH2O>10(exp −3)) and low Earth-like surface temperatures. However, M dwarfs also possess strong UV activity, which may effectively photolyze stratospheric H2O. Prior modeling efforts have not included the impact of high stellar UV activity on the H2O. Here, we employ a 1D photochemical model with varied stellar UV, to assess whether H2O destruction driven by high stellar UV would affect its detectability in transmission spectroscopy. Temperature and water vapor profiles are taken from published 3D climate model simulations for an IHZ Earth-sized planet around a 3300 K M dwarf with an N2–H2O atmosphere; they serve as self-consistent input profiles for the 1D model. We explore additional chemical complexity within the 1D model by introducing other species into the atmosphere. We find that as long as the atmosphere is well-mixed up to 1 mbar, UV activity appears to not impact detectability of H2O in the transmission spectrum. The strongest H2O features occur in the James Webb Space Telescope MIRI instrument wavelength range and are comparable to the estimated systematic noise floor of ∼50 ppm.
Understanding Research and Development (R&D) enterprise relationships and processes at a governance level is not a simple task, but valuable decision-making insight and evaluation capabilities can be gained from their exploration through computer simulations. This paper discusses current Modeling and Simulation (M&S) methods, addressing their applicability to R&D enterprise governance. Specifically, the authors analyze advantages and disadvantages of the four methodologies used most often by M&S practitioners: System Dynamics (SO), Discrete Event Simulation (DES), Agent Based Modeling (ABM), and formal Analytic Methods (AM) for modeling systems at the governance level. Moreover, the paper describes nesting models using a multi-method approach. Guidance is provided to those seeking to employ modeling techniques in an R&D enterprise for the purposes of understanding enterprise governance. Further, an example is modeled and explored for potential insight. The paper concludes with recommendations regarding opportunities for concentration of future work in modeling and simulating R&D governance relationships and processes.
The recently developed collisional radiative (CR) models for neutral xenon (Xe I) and singly charged xenon ion (Xe II) described by Chaplin et al. in the paper "Insights from Collisional-Radiative Models of Neutral and Singly-Ionized Xenon in Hall Thrusters" also submitted to the 2021 AIAA Propulsion and Energy Forum are more thoroughly investigated. Comparisons between the existing and recently developed JPL Xe I CR models are done and reasons for discrepancies between the two models are explored. An experiment to validate the Xe II CR model is carried out in the anode region of the UCLA Plasma interactions facility. The Xe II CR model is applied to measured xenon ion emission line intensities to determine electron temperature and density. Spatial resolution of these optical measurements is obtained through an Abel inversion for direct comparison to Langmuir probe results. Although the measured electron densities were on the order of $10^{17}$ m$^{-3}$ and the Xe II CR model is most suitable for use with densities above $10^{18}$ m$^{-3}$ due to the strong dependence of the line ratios on electron temperature in that regime, initial results from the validation experiment show reasonable agreements between the optical and Langmuir probe results. The 441 nm to 605 nm line ratio appears to have the most promise for non-intrusive electron temperature measurements with the Xe II CR model. Shortcomings of the Xe II CR model revealed in the validation experiment are to be explored further.
This paper proposes an engineering management model for NASA's future space exploration missions based on past experiences working with the International Partners of the International Space Station. The authors have over 25 years of combined experience working with the European Space Agency, Japan Aerospace Exploration Agency, Canadian Space Agency, Italian Space Agency, Russian Space Agency, and their respective contractors in the design, manufacturing, verification, and integration of their elements electric power system into the United States on-orbit segment. The perspective presented is one from a specific sub-system integration role and is offered so that the lessons learned from solving issues of technical and cultural nature may be taken into account during the formulation of international partnerships. Descriptions of the types of unique problems encountered relative to interactions between international partnerships are reviewed. Solutions to the problems are offered, taking into consideration the technical implications. Through the process of investigating each solution, the important and significant issues associated with working with international engineers and managers are outlined. Potential solutions are then characterized by proposing a set of specific methodologies to jointly develop spacecraft configurations that benefits all international participants, maximizes mission success and vehicle interoperability while minimizing cost.
The use of differential equations such as Eikonal, Hamilton-Jacobi and Poisson for the economical calculation of the nearest wall distance d, which is needed by some turbulence models, is explored. Modifications that could palliate some turbulence-modeling anomalies are also discussed. Economy is of especial value for deforming/adaptive grid problems. For these, ideally, d is repeatedly computed. It is shown that the Eikonal and Hamilton-Jacobi equations can be easy to implement when written in implicit (or iterated) advection and advection-diffusion equation analogous forms, respectively. These, like the Poisson Laplacian term, are commonly occurring in CFD solvers, allowing the re-use of efficient algorithms and code components. The use of the NASA CFL3D CFD program to solve the implicit Eikonal and Hamilton-Jacobi equations is explored. The re-formulated d equations are easy to implement, and are found to have robust convergence. For accurate Eikonal solutions, upwind metric differences are required. The Poisson approach is also found effective, and easiest to implement. Modified distances are not found to affect global outputs such as lift and drag significantly, at least in common situations such as airfoil flows.
Achieving fine control over the dispersion of supported platinum nanoparticles (Pt) is a promising avenue to enhancing their catalytic activity and selectivity. Experimental observations suggest that exposing ceria-supported Pt nanoparticles to O 2 at 500 °C promotes their dispersion into smaller particles and eventually single atoms. The exact role of oxygen in this process is not yet well understood. Past density functional theory studies of ceria-supported Pt have typically narrowed their scope to single atoms and clusters of a few atoms. Herein, we combine several approaches and types of models in a consistent atomistic framework to evaluate the relative stability of ceria-supported Pt as a function of the degree of oxidation of Pt and of the particle size, ranging from single atoms to nanoparticles 1.5 nm of diameter. Finally, we find that the largest nanoparticles remain the thermodynamically most stable species on the lowest energy facet of ceria even under oxidizing conditions, suggesting that stronger adsorption sites are required to stabilize smaller clusters and single atoms and promote oxidative dispersion.
Determining collective variables (CVs) for conformational transitions is crucial to understanding their dynamics and targeting them in enhanced sampling simulations. Often, CVs are proposed based on intuition or prior knowledge of a system. However, the problem of systematically determining a proper reaction coordinate (RC) for a specific process in terms of a set of putative CVs can be achieved using committor analysis (CA). Identifying essential degrees of freedom that govern such transitions using CA remains elusive because of the high dimensionality of the conformational space. Various schemes exist to leverage the power of machine learning (ML) to extract an RC from CA. Here, we extend these studies and compare the ability of 17 different ML schemes to identify accurate RCs associated with conformational transitions. We tested these methods on an alanine dipeptide in vacuum and on a sarcosine dipeptoid in an implicit solvent. Our comparison revealed that the light gradient boosting machine method outperforms other methods. In order to extract key features from the models, we employed Shapley Additive exPlanations analysis and compared its interpretation with the “feature importance” approach. For the alanine dipeptide, our methodology identifies ϕ and θ dihedrals as essential degrees of freedom in the C7ax to C7eq transition. For the sarcosine dipeptoid system, the dihedrals ψ and ω are the most important for the cisαD to transαD transition. We further argue that analysis of the full dynamical pathway, and not just endpoint states, is essential for identifying key degrees of freedom governing transitions.
The circular economy (CE) tackles environmental and resource scarcity issues by maximizing value retention in the economy. The concept implies design strategies such as reducing the use of materials or improving products’ durability and end-of-life (EOL) strategies, for example, reusing products and components and recycling materials. With an estimated 80 million tons of global cumulative EOL photovoltaic (PV) modules, applying CE principles to the PV industry could alleviate resource scarcity issues while also providing economic benefits. However, transitioning to a CE may imply changes in organizations and consumer behaviors. In this context, assessment of CE strategies may require accounting for behavioral change, a requirement that methods from complex system science such as agent-based modeling meet. Thus, this paper uses an agent-based modeling (ABM) approach to study circularity in the photovoltaics supply chain. Four types of agents are represented in the ABM: PV owners, installers, recyclers, and manufacturers. Moreover, five possible EOL options – including three CE strategies – are modeled. Departing from traditional techno-economic analysis, the model includes techno-economic factors as well as social factors to model EOL management decisions. Results show that each dollar decrease in the recycling fees improves the recycling rate by roughly 1.1%. However, excluding social factors underestimates the effect that lower recycling prices have on material circularity.
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The experience and advancement of Structural dynamics testing for space system applications at the Langley Research Center of the National Aeronautics and Space Administration (NASA) over the past four decades is reviewed. This experience began in the 1960's with the development of a technology base using a variety of physical models to explore dynamic phenomena and to develop reliable analytical modeling capability for space systems. It continued through the 1970's and 80's with the development of rapid, computer-aided test techniques, the testing of low-natural frequency, gravity-sensitive systems, the testing of integrated structures with active flexible motion control, and orbital flight measurements, It extended into the 1990's where advanced computerized system identification methods were developed for estimating the dynamic states of complex, lightweight, flexible aerospace systems, The scope of discussion in this paper includes ground and flight tests and summarizes lessons learned in both successes and failures.