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At least 973 records · Page 54

Binary Black Hole Late Inspiral: Simulations for Gravitational Wave Observations

Coalescing binary black hole mergers are expected to be the strongest gravitational wave sources for ground-based interferometers, such as the LIGO, VIRGO, and GEO600, as well as the spacebased interferometer LISA. Until recently it has been impossible to reliably derive the predictions of General Relativity for the final merger stage, which takes place in the strong-field regime. Recent progress in numerical relativity simulations is, however, revolutionizing our understanding of these systems. We examine here the specific case of merging equal-mass Schwarzschild black holes in detail, presenting new simulations in which the black holes start in the late inspiral stage on orbits with very low eccentricity and evolve for approximately 1200M through approximately 7 orbits before merging. We study the accuracy and consistency of our simulations and the resulting gravitational waveforms, which encompass approximately 14 cycles before merger, and highlight the importance of using frequency (rather than time) to set the physical reference when comparing models. Matching our results to PN calculations for the earlier parts of the inspiral provides a combined waveform with less than half a cycle of accumulated phase error through the entire coalescence. Using this waveform, we calculate signal-to-noise ratios (SNRs) for iLIGO, adLIGO, and LISA, highlighting the contributions from the late-inspiral and merger-ringdown parts of the waveform which can now be simulated numerically. Contour plots of SNR as a function of z and M show that adLIGO can achieve SNR 2 10 for some IMBBHs out to z approximately equals 1, and that LISA can see MBBHs in the range 3 x 10(exp 4) approximately < M/Mo approximately < 10(exp 7) at SNR > 100 out to the earliest epochs of structure formation at z > 15.

Baker, John G.↗

Automatic Hazard Detection for Landers

Unmanned planetary landers to date have landed 'blind'; that is, without the benefit of onboard landing hazard detection and avoidance systems. This constrains landing site selection to very benign terrain,which in turn constrains the scientific agenda of missions. The state of the art Entry, Descent, and Landing (EDL) technology can land a spacecraft on Mars somewhere within a 20-100km landing ellipse.Landing ellipses are very likely to contain hazards such as craters, discontinuities, steep slopes, and large rocks, than can cause mission-fatal damage. We briefly review sensor options for landing hazard detection and identify a perception approach based on stereo vision and shadow analysis that addresses the broadest set of missions. Our approach fuses stereo vision and monocular shadow-based rock detection to maximize spacecraft safety. We summarize performance models for slope estimation and rock detection within this approach and validate those models experimentally. Instantiating our model of rock detection reliability for Mars predicts that this approach can reduce the probability of failed landing by at least a factor of 4 in any given terrain. We also describe a rock detector/mapper applied to large-high-resolution images from the Mars Reconnaissance Orbiter (MRO) for landing site characterization and selection for Mars missions.

hazard detection↗

Notes on Accuracy of Finite-Volume Discretization Schemes on Irregular Grids

Truncation-error analysis is a reliable tool in predicting convergence rates of discretization errors on regular smooth grids. However, it is often misleading in application to finite-volume discretization schemes on irregular (e.g., unstructured) grids. Convergence of truncation errors severely degrades on general irregular grids; a design-order convergence can be achieved only on grids with a certain degree of geometric regularity. Such degradation of truncation-error convergence does not necessarily imply a lower-order convergence of discretization errors. In these notes, irregular-grid computations demonstrate that the design-order discretization-error convergence can be achieved even when truncation errors exhibit a lower-order convergence or, in some cases, do not converge at all.

Diskin, Boris↗

United Space Alliance LLC Parachute Refurbishment Facility Model

The Parachute Refurbishment Facility Model was created to reflect the flow of hardware through the facility using anticipated start and delivery times from a project level IV schedule. Distributions for task times were built using historical build data for SFOC work and new data generated for CLV/ARES task times. The model currently processes 633 line items from 14 SFOC builds for flight readiness, 16 SFOC builds returning from flight for defoul, wash, and dry operations, 12 builds for CLV manufacturing operations, and 1 ARES 1X build. Modeling the planned workflow through the PRF is providing a reliable way to predict the capability of the facility as well as the manpower resource need. Creating a real world process allows for real world problems to be identified and potential workarounds to be implemented in a safe, simulated world before taking it to the next step, implementation in the real world.

Esser, Valerie↗

Stability and Control CFD Investigations of a Generic 53 Degree Swept UCAV Configuration

NATO STO Task Group AVT-201 on "Extended Assessment of Reliable Stability & Control Prediction Methods for NATO Air Vehicles" is studying various computational approaches to predict stability and control parameters for aircraft undergoing non-linear flight conditions. This paper contributes an assessment through correlations with wind tunnel data for the state of aerodynamic predictive capability of time-accurate RANS methodology on the group's focus configuration, a 53deg swept and twisted lambda wing UCAV, undergoing a variety of roll, pitch, and yaw motions. The vehicle aerodynamics is dominated by the complex non-linear physics of round leading-edge vortex flow separation. Correlations with experimental data are made for static longitudinal/lateral sweeps, and at varying frequencies of prescribed roll/pitch/yaw sinusoidal motion for the vehicle operating with and without control surfaces. The data and the derived understanding should prove useful to the AVT-201 team and other researchers who are developing techniques for augmenting flight simulation models from low-speed CFD predictions of aircraft traversing non-linear regions of a flight envelope.

Frink, Neal T.↗

Verification of Pointing Constraints for the Dawn Spacecraft

NASA's Dawn spacecraft, an ion-thrust science mission to Vesta and Ceres, has numerous pointing constraints critical for safe operation. Onboard software automatically chooses target attitudes but enforces only a simplified constraint set at slew endpoints. Onboard fault-protection also uses simplified constraints, and violations can result in safing events that dramatically consume mission margins for missed thrust. Lastly, for funding reasons the operations team is lean, forcing the development of month-long command sequences. These factors place a premium on reliable maneuver design, prediction, and verification against pointing constraints. This paper presents Slewth, a ground tool built to address these concerns.

Vanelli, C. Anthony↗

Diagnostic Reasoning using Prognostic Information for Unmanned Aerial Systems

With increasing popularity of unmanned aircraft, continuous monitoring of their systems, software, and health status is becoming more and more important to ensure safe, correct, and efficient operation and fulfillment of missions. The paper presents integration of prognosis models and prognostic information with the R2U2 (REALIZABLE, RESPONSIVE, and UNOBTRUSIVE Unit) monitoring and diagnosis framework. This integration makes available statistically reliable health information predictions of the future at a much earlier time to enable autonomous decision making. The prognostic information can be used in the R2U2 model to improve diagnostic accuracy and enable decisions to be made at the present time to deal with events in the future. This will be an advancement over the current state of the art, where temporal logic observers can only do such valuation at the end of the time interval. Usefulness and effectiveness of this integrated diagnostics and prognostics framework was demonstrated using simulation experiments with the NASA Dragon Eye electric unmanned aircraft.

Diagnostics↗

Successful Completion of the JWST OGSE2 Cryogenic Test at JSC Chamber-A While Managing Numerous Challenges

The James Webb Space Telescope (JWST) Optical Telescope Element (OTE) assembly is the largest optically stable infrared-optimized telescope currently being manufactured and assembled, and scheduled for launch in 2018. The JWST OTE, including the primary mirrors, secondary mirror, and the Aft Optics Subsystems (AOS) are designed to be passively cooled and operate at near 45 degrees Kelvin. Due to the size of its large sunshield in relation to existing test facilities, JWST cannot be optically or thermally tested as a complete observatory-level system at flight temperatures. As a result, the telescope portion along with its instrument complement will be tested as a single unit very late in the program, and on the program schedule critical path. To mitigate schedule risks, a set of 'pathfinder' cryogenic tests will be performed to reduce program risks by demonstrating the optical testing capabilities of the facility, characterizing telescope thermal performance, and allowing project personnel to learn valuable testing lessons off-line. This paper describes the 'pathfinder' cryogenic test program, focusing on the recently completed second test in the series called the Optical Ground Support Equipment 2 (OGSE2) test. The JWST OGSE2 was successfully completed within the allocated project schedule while faced with numerous conflicting thermal requirements during cool-down to the final cryogenic operational temperatures, and during warm-up after the cryo-stable optical tests. The challenges include developing a pre-test cool-down and warm-up profiles without a reliable method to predict the thermal behaviors in a rarified helium environment, and managing the test article hardware safety driven by the project Limits and Constraints (L&C's). Furthermore, OGSE2 test included the time critical Aft Optics Subsystem (AOS), a part of the flight Optical Telescope Element that would need to be placed back in the overall telescope assembly integrations. The OGSE2 test requirements included the strict adherence of the project contamination controls due to the presence of the contamination sensitive flight optical elements. The test operations required close coordination of numerous personnel while they being exposed and trained for the 'final' combined OTE and instrument cryo-test in 2017. This paper will also encompass the OGSE2 thermal data look-back review.

JWST OGSE2 Cryogenic Test↗

An Electron Backscatter Diffraction (EBSD)-Based Automated Tool for Ceramic Capacitor Grain Size Analysis

Ceramic capacitors continue to be recurring problem parts for NASA, despite best efforts to screen out potential defects and failures through environmental and electrical testing and nondestructive inspection techniques such as acoustic microscopy. The physical properties of ceramic capacitors necessitates thin dielectric layers capable of withstanding significant electric fields. Any defects in those ceramic layers can result in reduced insulation resistance failure modes including short circuit failures, so the quality and consistency of the dielectric material is critical. The size of the individual ceramic grains in the dielectric material is a critical parameter. However, judging “grain size” is not so simple—in a single capacitor there can be wide variation in grain sizes observed. It is theorized that by studying the grain size distributions of “known good” and “known bad” lots of capacitors, some conclusions could be drawn that would allow us to better predict to the reliability of future lots based on grain size distributions. The initial goal of this effort was to find or develop an automated tool that could inspect a capacitor and return grain size distribution results.

Robert Hodson↗

From Research to Reality -- Challenges and Opportunities in Complex System Design

The scope and scale of our interconnected society requires that we view the world through a complex system lens, where numerous parts interact, and emergent behaviors are the norm. Understanding complex systems is critical for decision-making and policy development in domains such as ecological systems, financial markets, supply chains, and global transportation systems, where decision-makers need reliable information to predict the impact of decisions that may play out over decades. Traditional approaches to the research that produces this information are often insufficient, where hypotheses are tested in an isolated environment, and where the results may not carry over to the integrated system. There are a multitude of advancements in system engineering, artificial intelligence, and test and evaluation that are emerging to meet the challenge. Approaches such as agile development, model-based system engineering, design of experiments, large language models, and formal ontologies are providing ways to manage complexity and increase our collective ability to make the changes that we want to see in the world. In this talk I will provide a few examples related to the architecture of the National Airspace System (NAS), where we have investigated the use of large language models, basic formal ontology, and applied category theory to help researchers and system engineers be more effective in this complex design space. Bio: Dr. Ian Levitt’s current research focus is on the complex evolution of the National Airspace System. Prior to joining NASA in 2020, he was with the FAA leading international standards and national laboratory development for the agency. Dr. Levitt earned his PhD in mathematics from Rutgers University in 2009. His mission is to promote a healthy and continuous transformation of society through open information and cooperation.

Ian Levitt↗

Fault Diagnosis of Power Components with Reliability Assessment in Extraterrestrial Microgrids

This research investigates the possible failures caused by aging and other environmental and external factors that could significantly impact the performance of extraterrestrial power systems. Additionally, it presents a reliability assessment model for the space microgrid based on fault tree analysis (FTA). The reliability assessment model developed in this paper represents a tool that can be used by engineers to harden the system design for operational and economic benefits. To improve the reliability of the system, this work provides a broad review of the different fault detection and diagnosis (FDD) algorithms used for power microgrids and space applications. Using data sets from the Habitat Simulator developed through the NASA-funded Resilient Extraterrestrial Habitat Institute, this paper compares the applicability and accuracy of the different FDD methods. The primary FDD approach proposed and assessed in this work is based on the Markov reliability model. It predicts and detects future faults in the space microgrids by using past data samples and categorizing them into different classes. Data-driven-based models such as artificial neural networks are also investigated, tested, and evaluated using simulation data sets. According to the simulation results and the broad FDD algorithm comparison, this study provides the crew or maintenance engineers with a clear methodology to detect and localize power system failures.

Leila Chebbo↗

Accomplishments and Mid-Year Performance Report: Wind Energy Program Fiscal Year 2020

Through transformative science and innovation, the U.S. Department of Energy's (DOE's) National Wind Technology Center (NWTC) at the National Renewable Energy Laboratory's (NREL's) Flatirons Campus helps lead the way to a sustainable energy future that powers America with significant levels of reliable, low-cost, and accessible wind energy. Since 1976, NREL has provided an ideal environment for the research and development (R&D) of advanced energy technologies through: Wind energy resource assessments, World-class research facilities, High-performance computing and modeling, Data and technology analysis, Manufacturing breakthroughs, Environmental analysis and wildlife conservation efforts, Education and training programs for a future workforce. These activities enable the innovations needed to advance U.S. wind systems, address market and deployment barriers, and drive down the cost of wind energy with more efficient, more reliable, and more predictable wind energy systems. This report provides an overview of the achievements NREL delivered on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners during the first and second quarters of Fiscal Year (FY) 2020.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Metabolism and heat dissipation during Apollo EVA periods

The extravehicular activity life support equipment, suit temperature control, metabolic rate measurement methods, and energy production are discussed. The Apollo crewmen were able to perform planned extravehicular activities and to extend them to the maximum time allowable without medical problems. The metabolic rates experienced during the lunar surface extravehicular activities were lower than conservative premission estimates. A manually controlled liquid cooling garment was effectively used to minimize fatigue and water loss from sweating during lunar surface extravehicular activities. Gas cooling was adequate during the short zero-g extravehicular activities performed from the command module. The prediction of EVA workloads became more reliable as inflight data was accumulated. The prediction of the average metabolic cost of an EVA was more reliable than the cost of an individual short-term task.

J.M. Waligora↗

Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

Duque, Earl P. N.↗

Polymorphism and melt in high-pressure tantalum. II. Orthorhombic phases

Continuing uncertainty in the high-pressure melt curves of bcc transition metals has spawned renewed research interest in the phase diagrams of these materials, with tantalum becoming an important prototype. Here, the present paper extends the quantum-based investigation of high- T, P polymorphism and melt in Ta that was begun in Paper I [Haskins et al., Phys. Rev. B 86, 224104 (2012)] on five candidate cubic and hexagonal structures (bcc, A15, fcc, hcp, and hex-ω) to here treat four promising orthorhombic structures (Pnma, Fddd, Pmma, and α-U). Using DFT-based MGPT multi-ion potentials that allow accurate MD simulations of large systems, we showed in Paper I that the mechanically unstable fcc, hcp, and hex-ω structures can only be stabilized at high- T , P by large anharmonic vibrational effects, requiring systems of ~500 atoms to produce size-independent melt curves and reliable calculations of thermodynamic stability. This reversed a previous small-cell quantum-simulation prediction of a high- T , P hex-ω phase. Subsequent DFT calculations have now suggested a more energetically favorable and mechanically stable Pnma structure, which again small-cell quantum simulations predict could be a high- T , P phase. Our present MGPT total-energy and phonon calculations show that not only Pnma, but all four orthorhombic structures considered here, are similarly energetically favorable, and that Fddd in addition to Pnma is mechanically stable at T = 0 up to 420 GPa. MGPT-MD simulations further reveal spontaneous temperature-induced Pnma → bcc and Fddd → bcc transformations at modest temperatures, peaking at ~1450 K near 100 GPa. At high temperatures near melt, we find T -dependent c / a and b / a axial ratios and large stabilizing anharmonicity present in all four orthorhombic structures. The anharmonicity drives significantly larger melt size effects, requiring systems of ~1000 – 4000 atoms to produce converged melt curves for reliable predictions of relative thermodynamic stability. In the large-cell limit, with ~40000 solid-phase atoms and accurate two-phase MGPT-MD melt simulation, we find that Pnma, Fddd and α-U have melt temperatures that are equal to bcc over small pressure ranges in the vicinity of 100 GPa, but that the orthorhombic melt temperatures never exceed bcc up to 420 GPa. This finding suggests that Pnma, Fddd, and α-U remain highly competitive metastable phases that could coexist with bcc and possibly be observed experimentally. Finally, to add additional insight into our results we have constructed global Helmholtz free energies for the A15, Pnma, and Fddd phases of Ta, complementing previous free energies obtained for the bcc, fcc, and liquid phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Predictive Models and Novel Accelerated Tests for the Reliability of Cell Metallization in Photovoltaic Modules (Final Report)

Studies of metallization corrosion m photovoltaics have mainly been limited to comparisons of modules placed in accelerated chambers to fielded modules [1]. Damp Heat accelerated tests and phenomenological equations [2] are used to assess metallization corrosion without understanding the effect of UV light and temperature and humidity cycles on encapsulant adhesion degradation. The roles of encapsulant in-and out-diffusions of moisture and encapsulant impurities are important. Furthermore, few photovoltaic metallization corrosion studies included the role of bias and leakage currents, which are crucial in the electrochemical reaction of metallization. Leakage currents can highly accelerate the corrosion mechanism and are important to include in the studies of corrosion. In our research plan, we will address the following gaps in the PV community's understanding of metallization corrosion: (1) metallization corrosion with bias, humidity, and impurities in the encapsulant or metallization; (2) humidity diffusion through fresh and degraded encapsulants; and (3) comparison of model predictions with outdoor field modules and SunPower's extensive data for its back-contact and front-contact fleets [2] along with NREL's store of >20 year old modules. Our goal is to build models and accelerated tests to predict long term degradation of metallization corrosion of photovoltaic modules in the field. Our studies will include metals used in c-Si solar cells (Cu, Ag, and Al) and commonly used encapsulants (EV A (ethylene vinyl acetate), TPO (thermoplastic olefin), and silicone).

14 SOLAR ENERGY↗

Combining Data with Physical Knowledge for Uncertainty Quantification in Certification and Reliability Analysis

Unifying empirical data with predictive models can enable engineering cost-savings through certification by analysis and reliability-based design. Both concepts require rigorous uncertainty quantification (UQ) and robust understanding and treatment of relevant physics. Combining sampling-based UQ algorithms with high-fidelity simulations creates a computational bottleneck that is often alleviated through the use of machine learning (ML). ML can be used to create computationally efficient surrogates for simulations of complex or high-dimensional physical interactions (e.g., multi-phase interactions associated with melt pools in laser powder bed fusion or spatially-dependent material properties in functionally graded materials). However, negative side effects of ML may include a lack of interpretability and negative correlation between event rarity and simulation accuracy due to a lack of training data. As such, it is important to infuse ML algorithms with physics-based guardrails to provide confidence in their predictions. This talk will provide a brief review of recent NASA research at this intersection of physics-based simulation, ML, and UQ with a focus on certification and reliability analysis.

uncertainty quantification↗

Digital Twinning and Predictive Modeling of Traffic for Safe, Efficient, and Reliable Intersections

Over the last decade, the advances in connected and autonomous vehicles (CAVs) have far surpassed the technological realm of transportation infrastructure. There is a growing need to have a technologically commensurate transportation infrastructure to enable safe and reliable movement of goods and people. The recent creation of Advanced Research Projects Agency - Infrastructure (ARPA-I) through the Infrastructure Investment and Jobs Act by the U.S. Department of Transportation (USDOT) has further amplified the need to revolutionize the transportation infrastructure system in the US. This need is perhaps felt most at traffic intersections, as more than 50 percent of the combined total of fatal and injury crashes occur at or near intersections. The proposed concept of Infrastructure Perception and Control (IPC) is aimed at bridging this technological gap by building a real-time digital twin of traffic by fusing detections from sensors installed at the intersection. This digital twin can then empower a wide variety of applications such as smart traffic signals or infrastructure-to-everything (I2X) communications. Smart signaling can help avoid crashes through early-prediction, while I2X can augment the CAV sensors under uncertain driving conditions and provide connected vehicles (CVs) with traffic information they can use to optimize their travel.

connected vehicles↗