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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 55 records · Page 3

Quantifying Emergent Fluid Dynamics Using Reynolds-Interpolated Fluid Reduced-order Models

Fluid reduced-order models (ROMs) which capture the flow physics within the problem's physical domain are usually constrained in accuracy to only the parameter points, e.g. Reynolds and Mach numbers, at which reference data was provided. Interpolation-focused quantity-of-interest ROMs are often structured differently and fail to provide flow volume data with the same quality - if at all. In this paper, techniques which reside at the intersection of these two ROM schools - flow physics ROMs which can be interpolated within a parameter space of interest - are explored. Using a combination of existing and novel techniques, emergent physics are identified using a fluid ROM at parameter points which are not provided in the ROM's training data.

uncertainty quantification↗

Analysis of a parallelized nonlinear elliptic boundary value problem solver with application to reacting flows

A parallelized finite difference code based on the Newton method for systems of nonlinear elliptic boundary value problems in two dimensions is analyzed in terms of computational complexity and parallel efficiency. An approximate cost function depending on 15 dimensionless parameters is derived for algorithms based on stripwise and boxwise decompositions of the domain and a one-to-one assignment of the strip or box subdomains to processors. The sensitivity of the cost functions to the parameters is explored in regions of parameter space corresponding to model small-order systems with inexpensive function evaluations and also a coupled system of nineteen equations with very expensive function evaluations. The algorithm was implemented on the Intel Hypercube, and some experimental results for the model problems with stripwise decompositions are presented and compared with the theory. In the context of computational combustion problems, multiprocessors of either message-passing or shared-memory type may be employed with stripwise decompositions to realize speedup of O(n), where n is mesh resolution in one direction, for reasonable n.

Keyes, David E.↗

On the Role of Friction and Particle Size Distribution in Granular Packings

Packing of particles in a disordered arrangement has tremendous significance in both condensed matter physics and engineering applications. The last three decades have seen remarkable progress in our understanding of the physics of granular packings that has been largely facilitated by a rapid growth in the power of modern computers. Although granular packings are ubiquitous in diverse natural settings, from clogging of powders in hoppers to the crowding of living cells, a significant motivation for modeling granular packings has emerged from a proposal that the transition from a fluid-like state to a solid-like state of a granular material upon increasing volume fraction, called jamming, is intimately related to the origins of glass transition in thermal systems. As such, a majority of modeling efforts have focused on the jamming behavior of an idealized granular material: frictionless, monodisperse sphere. While such studies have illuminated the rich physics of jamming, granular materials in nature and engineering practice are rarely frictionless or monodisperse. The analogous research on the packing of these ‘real-world’ granular materials is still not fully developed. Besides requiring the exploration of a huge parameter space, three key computational considerations have inhibited their modeling: (i) traditional computational methods are not adept at simulating mechanically-stable packings of frictional particles near the jamming transition; (ii) standard algorithms of contact detection in discrete element methods are impractical to simulate granular packings with a wide distribution of particle sizes; (iii) a lack of well-established contact mechanics models of friction that can accurately reproduce experimental data. This chapter will review the latest computational advances to simulate the jamming of size-dispersed frictional particles, and describe the rich microstructural diversity that emerges in their packings.

granular↗

Parametric Analysis of a Hover Test Vehicle using Advanced Test Generation and Data Analysis

Large complex aerospace systems are generally validated in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. This is due to the large parameter space, and complex, highly coupled nonlinear nature of the different systems that contribute to the performance of the aerospace system. We have addressed the factors deterring such an analysis by applying a combination of technologies to the area of flight envelop assessment. We utilize n-factor (2,3) combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. The data generated is automatically analyzed through a combination of unsupervised learning using a Bayesian multivariate clustering technique (AutoBayes) and supervised learning of critical parameter ranges using the machine-learning tool TAR3, a treatment learner. Covariance analysis with scatter plots and likelihood contours are used to visualize correlations between simulation parameters and simulation results, a task that requires tool support, especially for large and complex models. We present results of simulation experiments for a cold-gas-powered hover test vehicle.

Gundy-Burlet, Karen↗

Tool Support for Parametric Analysis of Large Software Simulation Systems

The analysis of large and complex parameterized software systems, e.g., systems simulation in aerospace, is very complicated and time-consuming due to the large parameter space, and the complex, highly coupled nonlinear nature of the different system components. Thus, such systems are generally validated only in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. We have addressed the factors deterring such an analysis with a tool to support envelope assessment: we utilize a combination of advanced Monte Carlo generation with n-factor combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. Additional test-cases, automatically generated from models (e.g., UML, Simulink, Stateflow) improve the coverage. The distributed test runs of the software system produce vast amounts of data, making manual analysis impossible. Our tool automatically analyzes the generated data through a combination of unsupervised Bayesian clustering techniques (AutoBayes) and supervised learning of critical parameter ranges using the treatment learner TAR3. The tool has been developed around the Trick simulation environment, which is widely used within NASA. We will present this tool with a GN&C (Guidance, Navigation and Control) simulation of a small satellite system.

Schumann, Johann↗

Design Considerations for a Dedicated Gravity Recovery Satellite Mission Consisting of Two Pairs of Satellites

Future satellite missions dedicated to measuring time-variable gravity will need to address the concern of temporal aliasing errors; i.e., errors due to high-frequency mass variations. These errors have been shown to be a limiting error source for future missions with improved sensors. One method of reducing them is to fly multiple satellite pairs, thus increasing the sampling frequency of the mission. While one could imagine a system architecture consisting of dozens of satellite pairs, this paper explores the more economically feasible option of optimizing the orbits of two pairs of satellites. While the search space for this problem is infinite by nature, steps have been made to reduce it via proper assumptions regarding some parameters and a large number of numerical simulations exploring appropriate ranges for other parameters. A search space originally consisting of 15 variables is reduced to two variables with the utmost impact on mission performance: the repeat period of both pairs of satellites (shown to be near-optimal when they are equal to each other), as well as the inclination of one of the satellite pairs (the other pair is assumed to be in a polar orbit). To arrive at this conclusion, we assume circular orbits, repeat groundtracks for both pairs of satellites, a 100-km inter-satellite separation distance, and a minimum allowable operational satellite altitude of 290 km based on a projected 10-year mission lifetime. Given the scientific objectives of determining time-variable hydrology, ice mass variations, and ocean bottom pressure signals with higher spatial resolution, we find that an optimal architecture consists of a polar pair of satellites coupled with a pair inclined at 72deg, both in 13-day repeating orbits. This architecture provides a 67% reduction in error over one pair of satellites, in addition to reducing the longitudinal striping to such a level that minimal post-processing is required, permitting a substantial increase in the spatial resolution of the gravity field products. It should be emphasized that given different sets of scientific objectives for the mission, or a different minimum allowable satellite altitude, different architectures might be selected.

Wiese, D. N.↗

Trade Space Analyses: Balancing Crew and Mission Design Parameters

In 2020, the Associate Administrator for Human Exploration and Operations and the Agency’s Federated Board requested an assessment to develop a methodology for trade space analysis comparing crew size for Mars missions against mission design parameters. The NASA Engineering and Safety Center (NESC) conducted an assessment to develop a methodology for systematic, repeatable trade space analysis for crew size and developed an initial set of human performance models and a list of candidate crew tasks for NASA’s first mission to Mars. This report contains the results of the NESC assessment.

Humans to Mars↗

High-Contrast Near-Infrared Imaging Polarimetry of the Protoplanetary Disk around RY Tau

We present near-infrared coronagraphic imaging polarimetry of RY Tau. The scattered light in the circumstellar environment was imaged at H-band at a high resolution (approx. 0.05) for the first time, using Subaru-HiCIAO. The observed polarized intensity (PI) distribution shows a butterfly-like distribution of bright emission with an angular scale similar to the disk observed at millimeter wavelengths. This distribution is offset toward the blueshifted jet, indicating the presence of a geometrically thick disk or a remnant envelope, and therefore the earliest stage of the Class II evolutionary phase. We perform comparisons between the observed PI distribution and disk models with: (1) full radiative transfer code, using the spectral energy distribution (SED) to constrain the disk parameters; and (2) monochromatic simulations of scattered light which explore a wide range of parameters space to constrain the disk and dust parameters. We show that these models cannot consistently explain the observed PI distribution, SED, and the viewing angle inferred by millimeter interferometry. We suggest that the scattered light in the near-infrared is associated with an optically thin and geometrically thick layer above the disk surface, with the surface responsible for the infrared SED. Half of the scattered light and thermal radiation in this layer illuminates the disk surface, and this process may significantly affect the thermal structure of the disk.

protoplanetary disks↗

Hybrid Fuel Coupling in a Pulsed Z-Pinch Rocket Engine

The work presented here sought to explore a portion of the parameter space of a hybrid nuclear fuel in regards to ignition and burn by analyzing the effect of initial geometry and thermodynamic conditions. The authors performed 0D power balance and 1D burn wave calculations to determine temperature progression and energy production for defined initial conditions. Geometries examined are representative of concept fuels for a Pulsed Fission-Fusion (PuFF) engine. This work focuses on lithium deuteride and uranium 235 for the fuel since these are seen as leading candidates for PuFF. Presented below is a power balance illustrating a reduction in the energy and density required to breakeven of hybrid fuels in comparison with fusion fuels. Also the impact of fusion and fissile fuel quantities upon initial energies is presented. One can see that the initial energy required to breakeven in a hybrid cylindrical nuclear fuel decreases with decreasing fissile liner thickness, decreasing fusion fuel core radius, and increasing compression ratio of the fusion fuel.

Taylor, Brian↗

Hybrid Fuel Coupling in a Pulsed Z-Pinch Rocket Engine

The work presented here sought to explore a portion of the parameter space of a hybrid nuclear fuel in regards to ignition and burn by analyzing the effect of initial geometry and thermodynamic conditions. The authors performed 0D power balance and 1D burn wave calculations to determine temperature progression and energy production for defined initial conditions. Geometries examined are representative of concept fuels for a Pulsed Fission-Fusion (PuFF) engine. This work focuses on lithium deuteride and uranium 235 for the fuel since these are seen as leading candidates for PuFF. Presented below is a power balance illustrating a reduction in the energy and density required to breakeven of hybrid fuels in comparison with fusion fuels. Also the impact of fusion and fissile fuel quantities upon initial energies is presented. One can see that the initial energy required to breakeven in a hybrid cylindrical nuclear fuel decreases with decreasing fissile liner thickness, decreasing fusion fuel core radius, and increasing compression ratio of the fusion fuel.

Taylor, Brian↗

Development of a Data Fusion Methodology for Lineload Aerodynamic Databases for a Launch Vehicle during Liftoff and Transition

The need for databases for the distributed loading on launch vehicles during the early portion of flight necessitates the use of expensive computational flows in regimes where wake effects dominate. While also being expensive, this is a regime that computational tools tend to historically have problems simulating accurately. To help tackle this problem, a method of data fusion to combine computational results to wind tunnel derived force and moment data is developed. Using this method, significant reduction in computational costs and increases in confidence of the final product is possible and has been used to generate several databases for the Space Launch System (SLS) at NASA. While the full details of database generation are not part of this work, the crucial method at its core is developed here. Two SLS geometries are used throughout the work to demonstrate the techniques. These are two of the larger geometries and represent both planned crewed missions to the Moon as well as potential cargo missions to deep space. The method uses principal component analysis (PCA) to generate a reduced ordered model (ROM) to help fill in the full parameter space. Other similar techniques are explored, but were not found to have a significant result on the predictions of the ROM. Because the full number of components are kept to generate the model, this lack of difference is expected. This method is then extended to ensure that predicted surfaces match trusted force and moment data derived from wind tunnel testing. This extension is done by setting up a constrained optimization problem in order to minimize the deviation from the surface resolved computational data while still integrating to the desired values. When generating the constrained optimization problem, a weighting factor to balance these competing needs is introduced. The work compares previously introduced weighting terms from similar work to the proposed terms and shows that the previously used terms do not have as desirable behavior in this flow regime. This method is then expanded by developing a technique to incorporate uncertainty quantification into the developed data fusion methodology. This expansion takes a two pronged approach. One examines transferring the uncertainties in the force and moment database and characterizes how those adjustments change the predicted lineloads. The second looks at model form error and looks how rebuilding the model using slightly different data changes the predictions. These two terms are then combined in order to create an uncertainty model that takes both effects into account. The limitations of the proposed methods is then discussed as well as possible techniques to address these shortcomings.

Launch Vehicles↗

Mapping the Capabilities and Attributes of Solid Oxide Electrochemical Systems to Human Spaceflight Needs

NASA is sponsoring the development of a solid oxide electrochemical oxygen separation and compression system. This system is capable of extracting oxygen from a process stream of spacecraft cabin air, and compressing it to >27,000 kPa without mechanical compressors. Process temperatures are >650C, but the materials in contact with the oxygen do not burn. The system is called eCOG-C, Electrochemical Oxygen Generator and Compressor. A system capable of producing high pressure, high purity oxygen may have application as a method of recharging space suit oxygen tanks during human exploration missions. This paper describes the key performance parameters of a space suit oxygen tank recharge system, and places the key performance parameters of eCOG-c in the context of other methods of space suit oxygen tank recharge. This paper compares the eCOG-c configuration to an earlier electrochemical oxygen generator that has been prototyped and tested. Areas of emphasis for eCOG-C development are listed and described.

John Graf↗

The Impacts of Cabin Atmosphere Quality Standards and Control Loads on Atmosphere Revitalization Process Design

Maintaining the cabin atmosphere’s pressure, composition, and quality within specified parameters is a necessity for successful crewed space exploration missions. A properly maintained environment minimizes health impacts on the occupants and maximizes their comfort. The challenge is to accomplish this outcome economically. The insight gained during the International Space Station’s (ISS) operational lifetime is driving toward more challenging cabin atmospheric quality standards for future exploration missions. At the same time, the metabolic loads are increasing to accommodate a broader crew body size range and more rigorous exercise protocols to mitigate health effects associated with long duration microgravity exposure. Compounding this situation is new process equipment for handling trash and waste that may vent contaminants into the cabin. The limits placed on the cabin atmospheric quality parameters combined with the contaminant load define the design space for the atmosphere revitalization (AR) subsystem technologies to be deployed aboard the spacecraft. The impacts of changes to cabin atmospheric quality standards and contamination loads are evaluated and implications to future crewed exploration missions are explored.

Perry, Jay L.↗

International Docking Standard (IDSS) Interface Definition Document (IDD) : Revision - E

This International Docking System Standard (IDSS) Interface Definition Document (IDD) is the result of a collaboration by the International Space Station membership to establish a standard docking interface to enable on-orbit crew rescue operations and joint collaborative endeavors utilizing different spacecraft. This IDSS IDD details the physical geometric mating interface and design loads requirements. The physical geometric interface requirements must be strictly followed to ensure physical spacecraft mating compatibility. This includes both defined components and areas that are void of components. The IDD also identifies common design parameters as identified in section 3.0, e.g., docking initial conditions and vehicle mass properties. This information represents a recommended set of design values enveloping a broad set of design reference missions and conditions, which if accommodated in the docking system design, increases the probability of successful docking between different spacecraft. This IDD does not address operational procedures or off-nominal situations, nor does it dictate implementation or design features behind the mating interface. It is the responsibility of the spacecraft developer to perform all hardware verification and validation, and to perform final docking analyses to ensure the needed docking performance and to develop the final certification loads for their application. While there are many other critical requirements needed in the development of a docking system such as fault tolerance, reliability, and environments (e.g. vibration, etc.), it is not the intent of the IDSS IDD to mandate all of these requirements; these requirements must be addressed as part of the specific developer's unique program, spacecraft and mission needs. This approach allows designers the flexibility to design and build docking mechanisms to their unique program needs and requirements. The purpose of the IDSS IDD is to provide basic common design parameters to allow developers to independently design compatible docking systems. The IDSS is intended for uses ranging from crewed to autonomous space vehicles, and from Low Earth Orbit (LEO) to deep-space exploration missions.The purpose of the IDSS IDD is to provide basic common design parameters to allow developers to independently design compatible docking systems. The IDSS is intended for uses ranging from crewed to autonomous space vehicles, and from Low Earth Orbit (LEO) to deep-space exploration missions. The purpose of the IDSS IDD is to provide basic common design parameters to allow developers to independently design compatible docking systems. The IDSS is intended for uses ranging from crewed to autonomous space vehicles, and from Low Earth Orbit (LEO) to deep-space exploration missions.

docking↗

An Extensible Perturbed Parameter Ensemble for the Community Atmosphere Model Version 6

This paper documents the methodology and preliminary results from a Perturbed Parameter Ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2-CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations are analyzed and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks. The use of various emulators is explored in the multi- dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that using PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2-CAM6 PPE is publicly available, and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g. coupling to the land surface).

Machine learning↗

Evolution and Control of 2219 Aluminum Microstructural Features Through Electron Beam Freeform Fabrication

The layer-additive nature of the electron beam freeform fabrication (EBF3) process results in a tortuous thermal path producing complex microstructures including: small homogeneous equiaxed grains; dendritic growth contained within larger grains; and/or pervasive dendritic formation in the interpass regions of the deposits. Several process control variables contribute to the formation of these different microstructures, including translation speed, wire feed rate, beam current and accelerating voltage. In electron beam processing, higher accelerating voltages embed the energy deeper below the surface of the substrate. Two EBF3 systems have been established at NASA Langley, one with a low-voltage (10-30kV) and the other a high-voltage (30-60 kV) electron beam gun. Aluminum alloy 2219 was processed over a range of different variables to explore the design space and correlate the resultant microstructures with the processing parameters. This report is specifically exploring the impact of accelerating voltage. Of particular interest is correlating energy to the resultant material characteristics to determine the potential of achieving microstructural control through precise management of the heat flux and cooling rates during deposition.

Taminger, Karen M.↗