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At least 145 records · Page 8

Distributed parameter modeling of the structural dynamics of the Solar Array Flight Experiment

A distributed-parameter model of the structural dynamics of the space-shuttle-deployed Solar Array Flight Experiment is developed and used to produce estimates of the modal frequencies and mode shapes. A lumped parameter version of the distributed model is used to estimate model characteristics by analyzing the measured responses of 32 targets. To make the modeling more tenable, a distributed parameter system is used to reduce the number of unknown parameters, a modified Newton-Raphson technique is used for rapid convergence, and a parallel processing supercomputer is used for more efficient computation. The performances of computers with a high-speed serial processor and with a high-speed parallel processor are compared. The best results are obtained with the modeling approach in which maximum likelihood estimation is applied to distributed parameter models.

Taylor, L. W., Jr.↗

Efficient First-Order Algorithms for Large-Scale, Non-Smooth Maximum Entropy Models with Application to Wildfire Science

Maximum entropy (MaxEnt) models are a class of statistical models that use the maximum entropy principle to estimate probability distributions from data. Due to the size of modern data sets, MaxEnt models need efficient optimization algorithms to scale well for big data applications. State-of-the-art algorithms for MaxEnt models, however, were not originally designed to handle big data sets; these algorithms either rely on technical devices that may yield unreliable numerical results, scale poorly, or require smoothness assumptions that many practical MaxEnt models lack. In this paper, we present novel optimization algorithms that overcome the shortcomings of state-of-the-art algorithms for training large-scale, non-smooth MaxEnt models. Our proposed first-order algorithms leverage the Kullback–Leibler divergence to train large-scale and non-smooth MaxEnt models efficiently. For MaxEnt models with discrete probability distribution of n elements built from samples, each containing m features, the stepsize parameter estimation and iterations in our algorithms scale on the order of O(mn) operations and can be trivially parallelized. Moreover, the strong ℓ1 convexity of the Kullback–Leibler divergence allows for larger stepsize parameters, thereby speeding up the convergence rate of our algorithms. To illustrate the efficiency of our novel algorithms, we consider the problem of estimating probabilities of fire occurrences as a function of ecological features in the Western US MTBS-Interagency wildfire data set. Our numerical results show that our algorithms outperform the state of the art by one order of magnitude and yield results that agree with physical models of wildfire occurrence and previous statistical analyses of wildfire drivers.

Physics↗

Robot Acting on Moving Bodies (RAMBO): Interaction with tumbling objects

Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Davis, Larry S.↗

Robot acting on moving bodies (RAMBO): Preliminary results

A robot system called RAMBO is being developed. It is equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a moving object. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations nearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enchancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows the use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using parametric cubic splines between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Davis, Larry S.↗

Commercial Low-Earth Orbit Destination (CLD) Capabilities of Interest and Resource Needs

The Commercial Low Earth Orbit (LEO) Development Program team has been working with NASA and the International Space Station (ISS) National Lab (NL) stakeholders to identify capabilities of interest to both conduct research/technology demonstrations and estimate the resources that will be needed from Commercial LEO Destinations (CLDs). Through a series of one-on-one and working group meetings with users/stakeholders, hardware items of interest to the user community were identified and converted into capabilities (e.g., centrifugation, microscope, pressure chamber, etc.). In parallel, resources needed to operate the research equipment (e.g., crew time, number of experiments, volume, etc.) were estimated in order for the CLD providers to better understand NASA’s potential future service requirements. The capabilities and the resources included in this White Paper do not represent NASA requirements. Instead, they constitute a preliminary set of potential capability and resource needs collated to guide CLD providers in appropriately sizing and outfitting their CLD designs. NASA is requesting feedback from industry on how these capabilities and resources align with their own needs as well as those of their non-NASA customers. Information on how the capabilities/resources impact the CLD designs is also requested. After assessing industry’s feedback to this white paper, NASA plans to issue a preliminary set of requirements for review.

International Space Station↗

A provably stable numerical method for the anisotropic diffusion equation in confined magnetic fields

We present a novel numerical method for solving the anisotropic diffusion equation in magnetic fields confined to a periodic box which is accurate and provably stable. We derive energy estimates of the solution of the continuous initial boundary value problem. A discrete formulation is presented using operator splitting in time with the summation by parts finite difference approximation of spatial derivatives for the perpendicular diffusion operator. Weak penalty procedures are derived for implementing both boundary conditions and parallel diffusion operator obtained by field line tracing. We prove that the fully-discrete approximation is unconditionally stable. Discrete energy estimates are shown to match the continuous energy estimate given the correct choice of penalty parameters. A nonlinear penalty parameter is shown to provide an effective method for tuning the parallel diffusion penalty and significantly minimises rounding errors. Several numerical experiments, using manufactured solutions, the “NIMROD benchmark” problem and a single island problem, are presented to verify numerical accuracy, convergence, and asymptotic preserving properties of the method. Finally, we present a magnetic field with chaotic regions and islands and show the contours of the anisotropic diffusion equation reproduce key features in the field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Exploration of the Theoretical Physical Capacity of the John F. Kennedy International Airport Runway System

A design study was completed to explore the theoretical physical capacity (TPC) of the John F. Kennedy International Airport (KJFK) runway system for a northflow configuration assuming impedance-free (to throughput) air traffic control functionality. Individual runways were modeled using an agent-based, airspace simulation tool, the Airspace Concept Evaluation System (ACES), with all runways conducting both departures and arrivals on a first-come first-served (FCFS) scheduling basis. A realistic future flight schedule was expanded to 3.5 times the traffic level of a selected baseline day, September 26, 2006, to provide a steady overdemand state for KJFK runways. Rules constraining departure and arrival operations were defined to reflect physical limits beyond which safe operations could no longer be assumed. Safety buffers to account for all sources of operational variability were not included in the TPC estimate. Visual approaches were assumed for all arrivals to minimize inter-arrival spacing. Parallel runway operations were assumed to be independent based on lateral spacing distances. Resulting time intervals between successive airport operations were primarily constrained by same-runway and then by intersecting-runway spacing requirements. The resulting physical runway capacity approximates a theoretical limit that cannot be exceeded without modifying runway interaction assumptions. Comparison with current KJFK operational limits for a north-flow runway configuration indicates a substantial throughput gap of approximately 48%. This gap may be further analyzed to determine which part may be feasibly bridged through the deployment of advanced systems and procedures, and which part cannot, because it is either impossible or not cost-effective to control. Advanced systems for bridging the throughput gap may be conceptualized and simulated using this same experimental setup to estimate the level of gap closure achieved.

Neitzke, Kurt W.↗

Update on Parallel Process Execution in the Next Generation System Analysis Model (NGSAM)

As of the end of 2022, it is estimated that over 90,000 metric tons of heavy metal (MTHM) of spent nuclear fuel (SNF) were stored at various commercial nuclear power reactor sites (both operating and shutdown) across the United States [1]. The Office of Storage and Transportation within the U.S. Department of Energy’s Office of Nuclear Energy is planning for the transportation, storage, and eventual disposal of SNF and high-level radioactive waste (HLW). To aid in this effort and inform decision-makers about the backend of the spent fuel cycle, systems analysis tools capable of analyzing the various options with respect to SNF and HLW management are being used as well as continuously improved to meet the evolving needs of the program. System analysts typically use these tools to vary underlying assumptions (shipping rates, available facilities, start dates, interim storage capacity, etc.) and study the associated system implications such as timing for clearing sites of SNF, various cost elements, transportation infrastructure acquisition needs, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Effects of wave damping and finite perpendicular scale on three-dimensional Alfvén wave parametric decay in low-beta plasmas

Shear Alfvén wave parametric decay instability (PDI) provides a potential path toward significant wave dissipation and plasma heating. However, fundamental questions regarding how PDI is excited in a realistic three-dimensional (3D) open system and how the finite perpendicular wave scale—as found in both laboratory and space plasmas—affects the excitation remain poorly understood. Here, we present the first 3D, open-boundary, hybrid kinetic-fluid simulations of kinetic Alfvén wave PDI in low-beta plasmas. Key findings are that the PDI excitation is strongly limited by the wave damping present, including electron–ion collisional damping (represented by a constant resistivity) and geometrical attenuation associated with the finite-scale Alfvén wave, and ion Landau damping of the child acoustic wave. The perpendicular wave scale alone, however, plays no discernible role: waves of different perpendicular scales exhibit similar instability excitation as long as the magnitude of the parallel ponderomotive force remains unchanged. These findings are corroborated by theoretical analysis and estimates. This new understanding of 3D kinetic Alfvén wave PDI physics is essential for laboratory study of the basic plasma process and may also aid future evaluation of the relevance/role of PDI in low-beta space plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MTUQ: a framework for estimating moment tensors, point forces, and their uncertainties

SUMMARY We introduce MTUQ, an open-source Python package for seismic source estimation and uncertainty quantification, emphasizing flexibility and operational scalability. MTUQ provides MPI-parallelized grid search and global optimization capabilities, compatibility with 1-D and 3-D Green’s function database formats, customizable data processing, C-accelerated waveform and first-motion polarity misfit functions, and utilities for plotting seismic waveforms and visualizing misfit and likelihood surfaces. Applicability to a range of full- and constrained-moment tensor, point force, and centroid inversion problems is possible via a documented application programming interface, accompanied by example scripts and integration tests. We demonstrate the software using three different types of seismic events: (1) a 2009 intraslab earthquake near Anchorage, Alaska; (2) an episode of the 2021 Barry Arm landslide in Alaska; and (3) the 2017 Democratic People’s Republic of Korea underground nuclear test. With these events, we illustrate the well-known complementary character of body waves, surface waves, and polarities for constraining source parameters. We also convey the distinct misfit patterns that arise from each individual data type, the importance of uncertainty quantification for detecting multimodal or otherwise poorly constrained solutions, and the software’s flexible, modular design.

58 GEOSCIENCES↗

Dependence of velocity fluctuations on solar wind speeds: A simple analysis with IPS method

A number of theoretical works have suggested that MHD plasma fluctuations in solar winds should play an important role particularly in the acceleration of high speed winds inside or near 0.1 AU from the sun. Since velocity fluctuations in solar winds are expected to be caused by the MHD plasma fluctuations, measurements of the velocity fluctuations give clues to reveal the acceleration process of solar winds. We made interplanetary scintillation (IPS) observations at the region out of 0.1 AU to investigate dependence of velocity fluctuations on flow speeds. For evaluating the velocity fluctuation of a flow, we selected the IPS data-set acquired at 2 separate antennas which located in the projected flow direction onto the baseline plane, and tried to compare skewness of the observed cross correlation function(CCF) with skewness of modeled CCFs in which velocity fluctuations were parametrized. The integration effect of IPS along a ray path was also taken into account in the estimation of modeled CCFs. Although this analysis method is significant to derive only parallel fluctuation components to the flow directions, preliminary analyses show following results: (1) High speed winds (Vsw greater than or equal to 500 km/s out of 0.3 AU) indicate enhancement of velocity fluctuations near 0.1 AU; and (2) Low speed winds (Vsw less than or equal to 400 Km/s out of 0.3 AU) indicate small velocity fluctuations at any distances.

Misawa, H.↗

Research on computer systems benchmarking

This grant addresses the topic of research on computer systems benchmarking and is more generally concerned with performance issues in computer systems. This report reviews work in those areas during the period of NASA support under this grant. The bulk of the work performed concerned benchmarking and analysis of CPUs, compilers, caches, and benchmark programs. The first part of this work concerned the issue of benchmark performance prediction. A new approach to benchmarking and machine characterization was reported, using a machine characterizer that measures the performance of a given system in terms of a Fortran abstract machine. Another report focused on analyzing compiler performance. The performance impact of optimization in the context of our methodology for CPU performance characterization was based on the abstract machine model. Benchmark programs are analyzed in another paper. A machine-independent model of program execution was developed to characterize both machine performance and program execution. By merging these machine and program characterizations, execution time can be estimated for arbitrary machine/program combinations. The work was continued into the domain of parallel and vector machines, including the issue of caches in vector processors and multiprocessors. All of the afore-mentioned accomplishments are more specifically summarized in this report, as well as those smaller in magnitude supported by this grant.

Smith, Alan Jay↗

Reconstruction of the 1997/1998 El Nino from TOPEX/POSEIDON and TOGA/TAO Data Using a Massively Parallel Pacific-Ocean Model and Ensemble Kalman Filter

Two massively parallel data assimilation systems in which the model forecast-error covariances are estimated from the distribution of an ensemble of model integrations are applied to the assimilation of 97-98 TOPEX/POSEIDON altimetry and TOGA/TAO temperature data into a Pacific basin version the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. in the first system, ensemble of model runs forced by an ensemble of atmospheric model simulations is used to calculate asymptotic error statistics. The data assimilation then occurs in the reduced phase space spanned by the corresponding leading empirical orthogonal functions. The second system is an ensemble Kalman filter in which new error statistics are computed during each assimilation cycle from the time-dependent ensemble distribution. The data assimilation experiments are conducted on NSIPP's 512-processor CRAY T3E. The two data assimilation systems are validated by withholding part of the data and quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The pros and cons of each system are discussed.

Keppenne, C. L.↗

Upflowing ionospheric ions in the auroral region

Observations of upflowing ionospheric ions are obtained nearly simultaneously by DE 1 and DE 2 over the nightside auroral regions. At low altitudes, the mean value of the net upward ion number flux is of the order of 10 exp 9/sq cm per sec. The ionosphere is predominantly O(+), and the flux of ions with energy greater than 5 eV is a very small fraction (less than 1 percent) of the total ion flux. At high altitudes, the upflowing ions are accelerated by a parallel electric field and heated (with characteristic energies of hundreds of electron volts). Comparing upflowing fluxes at high and low altitudes yields an estimated height of the bottom of the auroral acceleration region of 1400-1700 km for the region of peak potential drop. This low-altitude acceleration could either be from a parallel electric field or from perpendicular acceleration. The fluxes at the edges of the arc are mostly H(+) thus implying a higher-altitude base of the acceleration region at the edges where the potential drop is lower.

Lu, G.↗

Analyzing the Impact of Lunar Dust on Astronaut Health – an Update to the Risk Modeling

INTRODUCTION Lunar dust exposure is an unavoidable hazard during lunar surface operations. Given the large number of surface EVAs expected to be performed during Artemis missions, it is critical that the incidence and extent of symptoms resulting from contact with lunar dust be fully understood in order to accurately predict the resources needed to treat Artemis astronauts. The purpose of this study will be to gather the latest data regarding the risk of and severity of symptoms associated with lunar dust exposure and refine the estimates of the impact of lunar dust on astronaut health for PRA models, both those in operational use and those currently being developed. METHODS The latest data on the pathophysiologic effects of lunar dust on humans will be gathered by querying the peer-reviewed literature as well as NASA technical documents. This data will be supplemented with discussions with hardware designers regarding methods used to mitigate exposure to lunar dust during lunar surface operations. Taken together, this data will be used to refine both the estimates for exposure to lunar dust for astronauts inside and outside lunar habitats, as well as provide evidence to guide estimates for the percentage of astronauts who are exposed to lunar dust who will be symptomatic. RESULTS Querying the peer-reviewed literature and NASA technical documents will begin in October of 2024, with the goal of codifying this information by the end of October. In parallel, discussions will begin with hardware engineering teams, also in October. Using the evidence found will help refine the estimate for resources needed to treat astronauts who exhibit symptoms from lunar dust exposure. DISCUSSION Lunar dust exposure is expected to be a major risk for upcoming exploration missions that include a lunar surface interval. Until recently, most of the information to inform the risk associated with lunar dust exposure has come from anecdotal evidence from Apollo astronauts about their symptoms while on the lunar surface; however, this evidence is sparse. Newer studies are now coming out, looking at the impact of lunar dust on human physiology, including studies on effects to the immune system. Additionally, there are new engineering efforts to attempt to mitigate the exposure to lunar dust from the space suits of astronauts returning to the lunar habitat after surface operations. Thus, developing an updated risk assessment, based on our current understanding of human physiology and our current resources for risk mitigation, is prudent to best estimate overall human health and performance risk for future Artemis missions. This project will lead to an updated and more accurate assessment of the risk of lunar dust exposure for exploration missions and will therefore allow mission planners to more accurately predict resources needed for these exploration-class missions.

D M Nusbaum↗

A meshless stochastic method for Poisson–Nernst–Planck equations

A plethora of biological, physical, and chemical phenomena involve transport of charged particles (ions). Its continuum-scale description relies on the Poisson–Nernst–Planck (PNP) system, which encapsulates the conservation of mass and charge. The numerical solution of these coupled partial differential equations is challenging and suffers from both the curse of dimensionality and difficulty in efficiently parallelizing. We present a novel particle-based framework to solve the full PNP system by simulating a drift–diffusion process with time- and space-varying drift. We leverage Green’s functions, kernel-independent fast multipole methods, and kernel density estimation to solve the PNP system in a meshless manner, capable of handling discontinuous initial states. The method is embarrassingly parallel, and the computational cost scales linearly with the number of particles and dimension. We use a series of numerical experiments to demonstrate both the method’s convergence with respect to the number of particles and computational cost vis-à-vis a traditional partial differential equation solver.

Chemistry↗

Collaborative Pose Estimation of An Unknown Target Using Multiple Spacecraft

A reliable method for pose estimation of an unknown and uncooperative space target using monocular vision remains an open problem. Vision-based pose determination can be challenging in case of unfavorable illumination, time-varying conditions due to rotational motion and relative orbit, and scale ambiguity resolution. To address these challenges, we propose a novel collaborative pose determination algorithm called Multi- Spacecraft Simultaneous Estimation of Pose and Shape algorithm or M-SEPS.Within M-SEPS, a team of chaser spacecraft, each equipped with a monocular camera, exchange information over a local network to jointly estimate the relative kinematic state of the target and its sparse shape landmarks. In this approach, each spacecraft processes its own images and observes particular target landmarks in parallel and in a distributed fashion. Then, the local network is exploited by the spacecraft to share their consensus proposals and aggregate them to achieve the joint estimate. We validate our algorithm using simulations of relative orbits and observations, captured by each chaser spacecraft. To the best of the authors’ knowledge, this is the first cooperative, vision-based algorithm for estimating the pose and shape of a space object for an arbitrary number of spacecraft.

Chung, Soon-Jo↗

Modified jet noise source model for twin-jet shielding analysis

An analytical method to estimate the influence that a jet of heated flow has on the noise emission from a parallel jet is presented. The shielding jet is modelled as a cylinder of constant cross-section in which the flow speed and temperature are uniform throughout. The jet noise emission is modelled by a point source with directivity imposed. The directivity term consists of: a self-noise term, a shear-noise term, and a convection factor. The self- and shear-noise terms each contain a basic directivity factor multiplying a spectral shape function. The various components are evaluated based on comparison with isothermal jet radiation experimental data. The modified source term is incorporated into the jet shielding model and compared to heated twin jet shielding data. The estimated spectra agree well except further downstream of the nozzle where peak of the noise spectrum estimated by the model lies approximately one octave below the experimental peak. The noise reduction estimated by the model agrees favorably with experiment in the near downstream region. This discrepancy is explained in terms of the shielding mechanism which is dominant far downstream.

Gerhold, C. H.↗