Search NASA⌕ Search

SEARCH · Search NASA

Results for “matching complex”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

A Low-Cost and Low-Risk Testbed for Control Design of Launch Vehicles and Landing Systems

This research seeks to bridge the gap between the simulation/theory and the flight-testing phases of control algorithmdesign for launch vehicles (LVs) and landing systems (LSs). Thispaper reviews contemporary testbeds for LV and LS control sys-tem design with an emphasis on reducing costs and risks. Also, anew low-cost and low-risk testbed utilizing a quadcopter, flexibleinverted pendulum, and a hanging pendulum is proposed. It is shown that the planar dynamic response of this proposed testbedcan match the planar dynamic response of an LV. As mission objectives for frequent cislunar and interplanetary travel become more complex, the algorithms that control LVs and LSs need to become more advanced to ensure mission safety and success. These control systems are slow to mature because it is difficult to perform experiments in an environment relevant to the mission in a safe and cost-effective manner. A solution to this problem frequently leveraged in the aviation andsatellite industries involves mimicking the dynamic response ofthe vehicle with a test platform that is low-cost and low-risk.

William J Elke III↗

Research at NASA's NFAC wind tunnels

The National Full-Scale Aerodynamics Complex (NFAC) is a unique combination of wind tunnels that allow the testing of aerodynamic and dynamic models at full or large scale. It can even accommodate actual aircraft with their engines running. Maintaining full-scale Reynolds numbers and testing with surface irregularities, protuberances, and control surface gaps that either closely match the full-scale or indeed are those of the full-scale aircraft help produce test data that accurately predict what can be expected from future flight investigations. This complex has grown from the venerable 40- by 80-ft wind tunnel that has served for over 40 years helping researchers obtain data to better understand the aerodynamics of a wide range of aircraft from helicopters to the space shuttle. A recent modification to the tunnel expanded its maximum speed capabilities, added a new 80- by 120-ft test section and provided extensive acoustic treatment. The modification is certain to make the NFAC an even more useful facility for NASA's ongoing research activities. A brief background is presented on the original facility and the kind of testing that has been accomplished using it through the years. A summary of the modification project and the measured capabilities of the two test sections is followed by a review of recent testing activities and of research projected for the future.

Edenborough, H. Kipling↗

Uncertainty quantification for misspecified machine learned interatomic potentials

The use of high-dimensional regression techniques from machine learning has significantly improved the quantitative accuracy of interatomic potentials. Atomic simulations can now plausibly target quantitative predictions in a variety of settings, which has brought renewed interest in robust means to quantify uncertainties. In many practical settings where model complexity is constrained (e.g., due to performance considerations), misspecification — the inability of any one choice of model parameters to exactly match all training data — is a key contributor to errors that is often disregarded. Here, we employ a recent misspecification-aware regression technique to quantify parameter uncertainties, which is then propagated to a broad range of phase and defect properties in tungsten. The propagation is performed through both brute-force resampling and implicit Taylor expansion. The propagated misspecification uncertainties robustly quantify and bound errors on a broad range of material properties. We demonstrate application to recent foundational machine learning interatomic potentials, accurately predicting and bounding errors in MACE-MPA-0 energy predictions across the diverse materials project database.

36 MATERIALS SCIENCE↗

MaNGA 8313-1901: Gas Accretion Observed in a Blue Compact Dwarf Galaxy?

Gas accretion is an important process in the evolution of galaxies, but it has limited direct observational evidences. In this paper, we report the detection of a possible ongoing gas accretion event in a blue compact dwarf (BCD) galaxy, MaNGA 8313-1901, observed by the Mapping Nearby Galaxies and Apache Point Observatory (MaNGA) program. This galaxy has a distinct off-centered blue clump to the northeast (the NE clump) that shows low metallicity and enhanced star formation. The kinematics of the gas in the NE clump also seems to be detached from the host BCD galaxy. Together with the metallicity drop of the NE clump, it suggests that the NE clump likely has an external origin, such as gas accretion or galaxy interaction, rather than an internal origin, such as an H II complex in the disk. After removing the underlying host component, we find that the spectrum of the "pure" clump can match very well with a modeled spectrum containing a stellar population of the young stars (≤7 Myr) only. This may imply that the galaxy is experiencing an accretion of cold gas, instead of a merger event involving galaxies with significant preexisting old stars. We also find signs of another clump (the SW clump) at the southwest corner of the host galaxy, and the two clumps may share the same origin of gas accretion.

79 ASTRONOMY AND ASTROPHYSICS↗

Task-dependent color discrimination

When color video displays are used in time-critical applications (e.g., head-up displays, video control panels), the observer must discriminate among briefly presented targets seen within a complex spatial scene. Color-discrimination threshold are compared by using two tasks. In one task the observer makes color matches between two halves of a continuously displayed bipartite field. In a second task the observer detects a color target in a set of briefly presented objects. The data from both tasks are well summarized by ellipsoidal isosensitivity contours. The fitted ellipsoids differ both in their size, which indicates an absolute sensitivity difference, and orientation, which indicates a relative sensitivity difference.

Poirson, Allen B.↗

Bayesian Approach for Reliability Assessment of Sunshield Deployment on JWST

Deployable subsystems are essential to mission success of most spacecraft. These subsystems enable critical functions including power, communications and thermal control. The loss of any of these functions will generally result in loss of the mission. These subsystems and their components often consist of unique designs and applications, for which various standardized data sources are not applicable for estimating reliability and for assessing risks. In this study, a Bayesian approach for reliability estimation of spacecraft deployment was developed for this purpose. This approach was then applied to the James Webb Space Telescope (JWST) Sunshield subsystem, a unique design intended for thermal control of the observatory's telescope and science instruments. In order to collect the prior information on deployable systems, detailed studies of "heritage information", were conducted extending over 45 years of spacecraft launches. The NASA Goddard Space Flight Center (GSFC) Spacecraft Operational Anomaly and Reporting System (SOARS) data were then used to estimate the parameters of the conjugative beta prior distribution for anomaly and failure occurrence, as the most consistent set of available data and that could be matched to launch histories. This allows for an emperical Bayesian prediction for the risk of an anomaly occurrence of the complex Sunshield deployment, with credibility limits, using prior deployment data and test information.

Kaminskiy, Mark P.↗

Advanced Colloids Experiment (ACE) Science Overview

The Advanced Colloids Experiment is being conducted on the International Space Station (ISS) using the Light Microscopy Module (LMM) in the Fluids Integrated Rack (FIR). Work to date will be discussed and future plans and opportunities will be highlighted. The LMM is a microscope facility designed to allow scientists to process, manipulate, and characterize colloidal samples in micro-gravity where the absence of gravitational settling and particle jamming enables scientists to study such things as:a.The role that disordered and ordered-packing of spheres play in the phase diagram and equation of state of hard sphere systems,b.crystal nucleation and growth, growth instabilities, and the glass transition, c.gelation and phase separation of colloid polymer mixtures,d.crystallization of colloidal binary alloys,e.competition between crystallization and phase separation,f.effects of anisotropy and specific interactions on packing, aggregation, frustration and crystallization,g.effects of specific reversible and irreversible interactions mediated in the first case by hybridization of complementary DNA strands attached to separate colloidal particles,h.Lock and key interactions between colloids with dimples and spheres which match the size and shape of the dimples,i.finding the phase diagrams of isotropic and interacting particles,j.new techniques for complex self-assembly including scenarios for self-replication, k.critical Casimir forces,l.biology (real and model systems) in microgravity,m.etc. By adding additional microscopy capabilities to the existing LMM, NASA will increase the tools available for scientists that fly experiments on the ISS enabling scientists to observe directly what is happening at the particle level. Presently, theories are needed to bridge the gap between what is being observed (at a macroscopic level when photographing samples) with what is happening at a particle (or microscopic) level. What is happening at a microscopic level will be directly accessible with the availability of the Light Microscopy Module (LMM) on ISS. To meet these goals, the ACE experiment is being built-up in stages, with the availability of confocal microscopy being the ultimate objective. Supported by NASAs Physical Sciences Research Program, ESAESTEC, and the authors respective governments.

Microgravity Biology Research↗

Ultra-Stable Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (5STAR)

The Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) combines airborne sun tracking and sky scanning with diffraction spectroscopy to improve knowledge of atmospheric constituents and their links to airpollution and climate. Direct beam hyperspectral measurement of optical depth improves retrievals of gas constituentsand determination of aerosol properties. Sky scanning enhances retrievals of aerosol type and size distribution.Hyperspectral cloud-transmitted radiance measurements enable the retrieval of cloud properties from below clouds.These measurements tighten the closure between satellite and ground-based measurements. 4STAR incorporates amodular sun-tracking sky-scanning optical head with optical fiber signal transmission to rack mounted spectrometers,permitting miniaturization of the external optical tracking head, and future detector evolution.4STAR has supported a broad range of flight experiments since it was first flown in 2010. This experience provides thebasis for a series of improvements directed toward reducing measurement uncertainty and calibration complexity, andexpanding future measurement capabilities, to be incorporated into a new 5STAR instrument. A 9-channel photodioderadiometer with AERONET-matched bandpass filters will be incorporated to improve calibration stability. A wide dynamic range tracking camera will provide a high precision solar position tracking signal as well as an image of sky conditions around the solar axis. An ultrasonic window cleaning system design will be tested. A UV spectrometer tailored for formaldehyde and SO2 gas retrievals will be added to the spectrometer enclosure. Finally, expansion capability for a 4 channel polarized radiometer to measure the Stokes polarization vector of sky light will be incorporated. This paper presents initial progress on this next-generation 5STAR instrument.

atmosphere↗

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific applications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application-level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher prediction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific ap- plications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Net- works (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate band- widths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer perfor- mance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application- level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher pre- diction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗

Complex refractive index of Martian dust - Mariner 9 ultraviolet observations

Mariner 9 ultraviolet spectrometer observations of the 1971 dust clouds obscuring the surface of Mars have been analyzed by matching the observed dust phase function with Mie scattering calculations for size distributions of homogeneous and isotropic material. Preliminary results indicate an effective particle radius of not less than 0.2. The real component of the index of refraction is not less than 1.8 at both 268 and 305 nm; corresponding values for the imagery component are 0.02 and 0.01. These values are consistent with those found by Mead (1970) for the visible and near-visible wavelengths. The refractive index and the absorption coefficient increase rapidly with decreasing wavelength in going from the visible to the ultraviolet, indicating the presence of an ultraviolet absorption band which may shield organisms from ultraviolet irradiation.

Pang, K.↗

Online Learning of Effective Turbine Wind Speed in Wind Farms

To develop better wind farm controllers that can meet more complex objectives, methods of modeling the wind turbine wakes at low computational expense are needed. Gaussian process (GP) regression offers a computationally inexpensive framework for learning complex functions from noisy measurements with very few datapoints. In this work, an online learning approach is presented to learn the rotor-averaged wind velocity at downstream wind turbines with GPs, using the available datastream of wind field measurements and wind turbine control set-points. This framework can readily be integrated into model-based controls methods because the model a) is updated online at low computational expense, b) assumes a mathematically favorable Gaussian form, and c) explicitly quantifies the stochastic nature of the wake field so that the trade-off between exploration and exploitation, and the uncertainty in the prediction, can be utilized. We show that a GP-learned model can match true values with errors within 0.5% on average, with as few as 5 training data points.

Gaussian process↗

Complex refractive index of Martian dust - Wavelength dependence and composition

The size distribution and complex refractive index of Martian dust-cloud particles observed in 1971 with the Mariner 9 UV spectrometer are determined by matching the observed single-scattering albedo and phase function with Mie-scattering calculations for size distributions of spheres. Values of phase function times single-scattering albedo are presented for 12 wavelength intervals in the range from 190 to 350 nm, and best-fit values are obtained for the absorption index. It is found that the absorption index of the dust particles increases with decreasing wavelength from 350 to about 210 nm and then drops off shortward of 210 nm, with a structural shoulder occurring in the absorption spectrum between 240 and 250 nm. A search for a candidate material that can explain the strong UV absorption yields TiO2, whose anatase polymorph has an absorption spectrum matching that of the Martian dust. The TiO2 content of the dust particles is estimated to be a few percent or less.

Pang, K.↗

A kinematic model for the evolution of the Gorda Plate

The magnetic lineation pattern produced by the Gorda Rise reflects a complex tectonic history marked by propagating ridges and nonrigid deformation of the Gorda plate. The Pacific-side lineation pattern is matched using a kinematic model which incorporates northward and southward propagating ridge segments and ridge rotation. By superimposing flexural-slip style deformation on the resulting Gorda-side lineations, and allowing convergent motion at the Mendocino Fracture Zone, the Gorda magnetic pattern is also successfully predicted. A similar model, but one which does not allow convergence at the Mendocino Fracture Zone, fails to produce the observed lineation pattern. Model predictions of the amount of material that would be 'obducted' at the Mendocino due to convergence between the Gorda and Pacific agree with bathymetric and density estimates of the amount of material located along the Mendocino Ridge.

Stoddard, Paul R.↗

The Navy/NASA Engine Program (NNEP89): Interfacing the program for the calculation of complex Chemical Equilibrium Compositions (CEC)

The NNEP is a general computer program for calculating aircraft engine performance. NNEP has been used extensively to calculate the design and off-design (matched) performance of a broad range of turbine engines, ranging from subsonic turboprops to variable cycle engines for supersonic transports. Recently, however, there has been increased interest in applications for which NNEP is not capable of simulating, such as the use of alternate fuels including cryogenic fuels and the inclusion of chemical dissociation effects at high temperatures. To overcome these limitations, NNEP was extended by including a general chemical equilibrium method. This permits consideration of any propellant system and the calculation of performance with dissociation effects. The new extended program is referred to as NNEP89.

Gordon, Sanford↗

235-F GoldSim Fate and Transport Model: Uncertainty Quantification

Building 235-F was configured with two missions in mind: Actinide Billet Line (ABL) and the fabrication of Pu-238 oxide for space program applications. ABL produced Np-237 billets for use in SRS reactors, whereas the design process, fabrication, and examination of Pu-238 oxide powder occurred within the following areas, respectively: Plutonium Experimental Facility (PEF), Plutonium Fuel Form (PuFF), and Old Metallography Lab (OML). By 1990 production ceased and by 2006 de-inventory occurred; however, assays have shown significant holdup remains within ABL and PuFF. As a result, 235-F is a Category 2 nuclear facility, with plans to undergo deactivation and decommission (D and D) via In-Situ Disposal (ISD). The purpose of this project is to ensure United States Environmental Protection Agency (USEPA) groundwater radiation maximum contaminant level (MCL) and dosage standards are met during the D and D of 235-F by quantifying uncertainty through probabilistic modeling and evaluation of various ISD alternatives. GoldSim is a dynamic modeling software package with a graphical, object-oriented interface capable of capturing the influence of complex system input variability on probabilistic system outcomes. A GoldSim stochastic fate and transport model for 235-F was developed and matched with a PORFLOW deterministic model to simulate probabilistic release and flow of radionuclides from ABL and PuFF into the vadose zone, the Upper Three Runs (UTR) Aquifer, and UTR Creek. The GoldSim model was used to probabilistically evaluate four ISD scenarios against USEPA groundwater radiation MCLs and dosage standards. The deterministic 235-F GoldSim fate and transport model continues to be refined to match the results of the PORFLOW deterministic model to ensure the model accurately represents radionuclide movement through the groundwater system. The stochastic variables that are utilized within the GoldSim model are founded on the most current data; a conservative perspective is taken where needed. Alignment with the PORFLOW deterministic model, coupled with input stochastic variability, allows the probabilistic 235-F GoldSim model to capture the conservative breadth of possible outcomes for radionuclide fate within this particular system. This ensures that the USEPA MCLs and dosage limits hold even in the worst case scenarios.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs

In simulation-based studies and analyses of epidemics, a major challenge lies in resolving the conflict between fidelity of models and the speed of their simulation. Another related challenge arises in dealing with the large number of what–if scenarios that need to be explored. Here, we describe new computational methods that together provide an approach to dealing with both challenges. A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. The mesoscopic approach offers the ability to incorporate complex compositions of multiple layers of dynamics even while retaining the potential for aggregate behaviors at varying levels. It also is an excellent match to the accelerator-based architectures of modern computing platforms in which graphical processing units (GPUs) can be exploited for fast simulation via the parallel execution mode of single instruction multiple thread (SIMT). The challenge of simulating a large number of scenarios is addressed via a method of sharing model state and computation across a tree of what–if scenarios that are localized, incremental changes to a large base simulation. A combination of the mesoscopic modeling approach and the incremental what–if scenario tree evaluation has been implemented in the software on modern GPUs. Synthetic simulation scenarios are presented to demonstrate the computational characteristics of our approach. Results from the experiments with large population data, including USA, UK, and India, illustrate the modeling methodology and computational performance on thousands of synthetically generated what–if scenarios. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what–if scenarios several orders of magnitude faster than the conventional methods.

97 MATHEMATICS AND COMPUTING↗

DECOVALEX-2023: Task E Final Report

This is the Task E final report for DECOVALEX-2023. Task E is focused on understanding thermal, two-phase hydrological, and mechanical (TH2M) processes, especially related to predicting brine migration in the excavation damaged zone around a heated excavation in salt. Salt is attractive as a disposal medium for radioactive waste because it is self-healing and is essentially impermeable and essentially non-porous in the far field (away from excavations). Investigation of the short-term (days to years) near-field (centimeters to tens of meters) behavior of salt is important for radioactive waste disposal because this early period strongly controls the amount of brine in a salt repository. Brine leads to corrosion of waste forms and waste packages, and possible dissolution of radionuclides with brine transport being a potential transport vector to the accessible environment. The main test case used in Task E is the ongoing Brine Availability Test in Salt (BATS) heater test located underground at the Waste Isolation Pilot Plant (WIPP) near Carlsbad, New Mexico, USA. The Task was divided into a series of Steps. Step 0 was an introduction to processes in salt, that included matching historical unheated brine inflow data from boreholes at WIPP and matching temperature observations during BATS heater test 1a. Step 1 included validation of models against a thermo-poroelastic analytical solution relevant to heated boreholes in salt, and two-phase flow around an excavation in salt. Step 2 required all the individual components covered in steps 0 and 1 to come together to match observed brine inflow behavior during the BATS 1a heater test. There were a range of approaches from the teams, from mechanistic to prescriptive. Given the uncertainties in the problem, some teams used one- or two-dimensional models of the processes, while other teams included more geometrical complexity in three-dimensional models. The key learning points from Task E have been: • Heat conduction through salt typically requires non-linear thermal conductivity (as a function of temperature), but most models do a good job matching observations, given appropriate adjustments to the applied power and some thermocouple locations. • Thermal pressurization requires coupled thermal-hydrological-mechanical (THM) responses that consider the thermal expansion of the fluid and solid phases. • Initialization of two-phase flow models around a borehole or excavation in salt are more realistically represented as “wetting up”, rather than “drying down” (i.e., the initial state after excavation is mostly dry, rather than mostly wet). • The BATS 1a heater test includes a significant release of brine after the end of heating, which requires a large increase in permeability to recreate. Task E has been a great learning experience for all the teams involved, and feedback from the modeling teams has led to changes in the design of follow-on BATS experiments, which are now ongoing underground at WIPP. There was a balance throughout the task between freedom to model phenomena how each team saw fit, and prescriptiveness in problem design to bring the modeling teams closer together to allow attribution of smaller differences between models to different modeling choices. The modeling approaches seem to go through two phases: an early phase of discovery or testing, and a later phase of refinement and improvement. In future modeling efforts, different field data could be used (e.g., BATS 2) and more time should be included in the processes for teams to make multiple model refinement or even significant changes to their conceptual model or setup, based on lessons learned from the modeling exercise.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗