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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Enhancements to the RAVEN code in FY16

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN has currently reached a good level of maturity in terms of deployed state-of-art and advanced capabilities. The main subject of this report is to show the activities that have been recently accomplished: • Implementation of ensemble modeling for time-series, and • initial implementation of model validation for surrogate models, and • advanced visualization capability for topology based data analysis The development of ensemble modeling for time-series has been performed in order to begin tackling the needs of those RISMC applications that need to communicate 1-Dimensional information (e.g. power histories, etc.) among different models. In this document the implementation details and an application example is reported. The second subject of this report is about the initial development of methods, within the RAVEN framework, to assess the validity of the predictive capabilities of surrogate models. Indeed, after the construction of a surrogate tight to a certain physical model, it is crucial to assess the goodness of its representation, in order to be confident with its prediction. In this initial activity, a cross-validation technique has been employed. This report will highlight the implementation details and proof its correct implementation by an application example. The final subject of this report is about the implementation of advanced visualization capability in RAVEN, for interactive data analysis. Indeed, RAVEN offers several post-processing capabilities that can structurally decompose data extracted from experimental results offering both data clustering/partitioning and dimensionality reduction techniques. A disadvantage of the workflow available in RAVEN is that it treats these as black box operations and the user is expected to know specific information about their data including the number of partitions to expect in some cases or the “correct” parameter settings for a particular algorithm. In order to overcome this limitation, it has been added an interactive user interface that can be run in RAVEN to explore different parameter settings on the fly specifically for the topological post-processor and allows the user to explore the data interactively. The design of this user interface is generalizable to other algorithms and can be used as a model to generate more dynamic and user-friendly visualization capabilities within RAVEN.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Expanded Use of ISOCS Characterization Techniques for WIPP Certification at the Idaho Clean-up Project - 19623

The Advanced Mixed Waste Treatment Project (AMWTP) has been retrieving, treating, characterizing, and shipping legacy Transuranic (TRU) waste for disposal since 2003 as part of the overall Idaho Cleanup Project (ICP) in support of the US Department of Energy. As the ICP has progressed, over 700 containers have been identified that cannot be successfully assayed using the current suite of non-destructive assay (NDA) instruments. To meet this challenge, Fluor Idaho, LLC, and Mirion Technologies (formerly Canberra Industries) have teamed to deploy the In-Situ Object Counting System (ISOCS) to supplement the current NDA capabilities. ISOCS has long been used in various radioactive waste management applications, but never has the ISOCS ability to perform intrinsic efficiency modeling of discrete waste containers been employed to characterize and certify TRU waste for disposal at the Waste Isolation Pilot Plant (WIPP), near Carlsbad, New Mexico. Since the primary disposal facility for this waste is the WIPP, the characterization processes for determining the quantity of radioactive material entrained in the waste are subject to WIPP Waste Acceptance Criteria (WAC) quality requirements and associated performance criteria. Until now, the Carlsbad Field Office (CBFO) WIPP-certified NDA equipment has utilized pre-defined efficiency calibrations for fixed geometries. However, due to the radioactive material content, activity levels, waste stream matrix, and/or the geometries of various size drums, boxes and other-odd-shaped containers or container integrity issues, it may not be suitable to characterize these containers with any of the existing WIPP-certified NDA equipment located at the AMWTP. Therefore, advanced technologies are needed to complete characterization of these problematic waste containers. The July 5, 2016 release of the WIPP WAC, DOE/WIPP-02-3122, Revision 8.0, Appendix A, 'Radioassay Requirements for Transuranic Waste,' was expanded to include several newer concepts such as American Society for Testing and Materials (ASTM) approved methods for efficiency-based calibrations and the use of mathematical computer modeling techniques for calibration. This change prompted AMWTP to pursue obtaining WIPP certification authority for expanded ISOCS techniques to deal with the remaining challenging waste containers and the development and implementation of Mirion's Figures of Merit (FOM) evaluations. These vital FOM evaluations enhance the ISOCS's modeling capabilities by optimizing the dynamic efficiency calibration for each object and reducing the assay's Total Measurement Uncertainty (TMU) budget. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Crystal structure of the chloroplast RNA editing factor MORF2

Highlights: • Crystal structure of MORF2 is determined at 2.4 Å. • MORF2 forms dimer through hydrophobic interaction. • Dimerization interface of MORF2 overlaps with its PPR interacting site. • A dimer-to-monomer transition is implicated for MORF2's role in RNA editing. RNA editing is a post-transcription process that alters the genetic information on RNA molecules. In plastids and mitochondria of flowering plants, the multiple organellar RNA editing factors (MORFs) interact with the PLS-type pentatricopeptide repeat (PPR) proteins and participate in RNA editing of cytidine-to-uridine conversion. The PPR proteins recognize cytidine targets around the editing sites, and the MORF proteins modulate the RNA-binding activity of the PPR proteins. Here, we report the structure of the Arabidopsis thaliana chloroplast MORF2 at 2.4 Å resolution. The structure, adopting typical MORF-box fold as observed in mitochondrial MORF1 and chloroplast MORF9, reveals an MORF1-like dimerization mode. The difference between the two dimerization modes can be attributed to F157 (corresponding F162 in MORF1 and W160 in MORF9), which causes a 60° shift upon dimerization. This observation, together with the PPR–MORF2 model, suggests a dimer-to-monomer transition during RNA editosome formation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Measure this, not that: Optimizing the cost and model-based information content of measurements

Model-based design of experiments (MBDoE) is a powerful framework for selecting and calibrating science-based mathematical models from data. Here, this work extends popular MBDoE workflows by proposing a convex mixed integer (non)linear programming (MINLP) to optimize the selection of measurements. The solver MindtPy is modified to support calculating the D-optimality objective and its gradient via an external package, scipy, using the grey-box module in Pyomo. The new approach is demonstrated in two case studies: estimating highly correlated kinetics from a batch reactor and estimating transport parameters in a large-scale rotary packed bed for CO 2 capture. Both case studies show how examining the Pareto optimal trade-offs between information content measured by A- and D-optimality versus measurement budget offers practical guidance for selecting measurements for scientific experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

THREE NEW ECLIPSING WHITE-DWARF-M-DWARF BINARIES DISCOVERED IN A SEARCH FOR TRANSITING PLANETS AROUND M-DWARFS

We present three new eclipsing white-dwarf/M-dwarf binary systems discovered during a search for transiting planets around M-dwarfs. Unlike most known eclipsing systems of this type, the optical and infrared emission is dominated by the M-dwarf components, and the systems have optical colors and discovery light curves consistent with being Jupiter-radius transiting planets around early M-dwarfs. We detail the PTF/M-dwarf transiting planet survey, part of the Palomar Transient Factory (PTF). We present a graphics processing unit (GPU)-based box-least-squares search for transits that runs approximately 8 Multiplication-Sign faster than similar algorithms implemented on general purpose systems. For the discovered systems, we decompose low-resolution spectra of the systems into white-dwarf and M-dwarf components, and use radial velocity measurements and cooling models to estimate masses and radii for the white dwarfs. The systems are compact, with periods between 0.35 and 0.45 days and semimajor axes of approximately 2 R{sub Sun} (0.01 AU). The M-dwarfs have masses of approximately 0.35 M{sub Sun }, and the white dwarfs have hydrogen-rich atmospheres with temperatures of around 8000 K and have masses of approximately 0.5 M{sub Sun }. We use the Robo-AO laser guide star adaptive optics system to tentatively identify one of the objects as a triple system. We also use high-cadence photometry to put an upper limit on the white-dwarf radius of 0.025 R{sub Sun} (95% confidence) in one of the systems. Accounting for our detection efficiency and geometric factors, we estimate that 0.08%{sub -0.05%}{sup +0.10%} (90% confidence) of M-dwarfs are in these short-period, post-common-envelope white-dwarf/M-dwarf binaries where the optical light is dominated by the M-dwarf. The lack of detections at shorter periods, despite near-100% detection efficiency for such systems, suggests that binaries including these relatively low-temperature white dwarfs are preferentially found at relatively large orbital radii. Similar eclipsing binary systems can have arbitrarily small eclipse depths in red bands and generate plausible small-planet-transit light curves. As such, these systems are a source of false positives for M-dwarf transiting planet searches. We present several ways to rapidly distinguish these binaries from transiting planet systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Low-mass Exoplanet Candidate Detected by K2 Transiting the Praesepe M Dwarf JS 183

We report the discovery of a repeating photometric signal from a low-mass member of the Praesepe open cluster that we interpret as a Neptune-sized transiting planet. The star is JS 183 (HSHJ 163, EPIC 211916756), with T {sub eff} = 3325 ± 100 K, M {sub *} = 0.44 ± 0.04 M {sub ⊙}, R {sub *} = 0.44 ± 0.03 R {sub ⊙}, and logg{sub ∗} = 4.82±0.06. The planet has an orbital period of 10.134588 days and a radius of R {sub P} = 0.32 ± 0.02 R {sub J}. Since the star is faint at V = 16.5 and J = 13.3, we are unable to obtain a measured radial velocity orbit, but we can constrain the companion mass to below about 1.7 M {sub J}, and thus well below the planetary boundary. JS 183b (since designated as K2-95b) is the second transiting planet found with K2 that resides in a several-hundred-megayear open cluster; both planets orbit mid-M dwarf stars and are approximately Neptune sized. With a well-determined stellar density from the planetary transit, and with an independently known metallicity from its cluster membership, JS 183 provides a particularly valuable test of stellar models at the fully convective boundary. We find that JS 183 is the lowest-density transit host known at the fully convective boundary, and that its very low density is consistent with current models of stars just above the fully convective boundary but in tension with the models just below the fully convective boundary.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2006

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗
DOE OSTI2018

MODAL FREQUENCY TRACKING: Performance Analysis on Noisy Experimental Ground Test Data

Mechanical devices operating in an environment contaminated by noise, uncertainties, and extraneous disturbances lead to low signal-to-noise-ratios creating an extremely challenging signal processing problem—especially for on-line, realtime, in-flight application. In this report, we discuss a model-based approach to incorporate physical device features into a dynamic structure that can be used to perform on-line tracking of modal frequencies. The approach we take, after pre-processing the raw measurement data, is to obtain a representation of the structural device under test that captures its underlying response to a suite of excitations and operating conditions. One approach is to apply modern system identification techniques based on stochastic subspace methods capable of both: (1) identifying the underlying black-box structure enabling the extraction of structural modes that can be used for analysis; and (2) modal tracking under continued vibrational excitation as in a real-time, in-flight like environment. The vibrational signature of the structural device is measured directly using a suite of tri-axial accelerometers characterizing a multiple input/multiple output (MIMO) dynamic system. In this analysis, we have 15 tri-axial accelerometer measurements or 45 total output channels along with a single excitation also measured with a tri-axial accelerometer providing a 3-input system for processing. We initially describe the experiment and then briefly develop the necessary background in stochastic subspace realization, discuss the algorithm and apply it to the isolated structural device, first, characterized by the set of noisy MIMO accelerometer measurements extracting the modal model from the data (subspace identification), extract the unique modal frequencies (modal coordinate transformation), track their evolution (real-time tracker) to evaluate the overall performance of the processor. Next we evaluate processor performance when the structural device is incorporated into a flight vehicle for further performance analysis. We summarize the results and predict performance.

42 ENGINEERING↗
DOE OSTI2018

The interaction between XBP1 and eNOS contributes to endothelial cell migration

Highlights: • Wound in EC monolayer induced XBP1 splicing, which was involved in EC migration. • XBP1s increased NOS3 mRNA stability via down-regulating microRNA miR-24. • ENOS was involved in EC migration via forming a complex with AKT and XBP1s. The X-box binding protein 1 (XBP1) is a pivotal transcription factor in the endoplasmic reticulum stress response. Our previous studies have proven that XBP1 is involved in vascular endothelial growth factor (VEGF)-mediated endothelial cell (EC) proliferation and angiogenesis. In this study, we used EC monolayer wound healing, tube formation and transwell migration models to explore the role of XBP1splicing in EC migration. We found that scratching on EC monolayer triggered XBP1splicing, which was attenuated by the presence of SU5416and LY294002, suggesting that VEGF signalling pathways may be involved. Over-expression of the spliced XBP1 (XBP1s) via Ad-XBP1s gene transfer increased while knockdown of IRE1αor XBP1 by ShRNA lentivirus suppressed EC migration. Over-expression of XBP1s up-regulated the nitric oxide synthase 3 (NOS3)mRNA through the 3’UTR-mediated stabilisation and increased eNOS protein translation. Further experiments demonstrated that miR-24 participated in the XBP1s-induced eNOSup-regulation and EC migration. Further co-IP and immunofluorescence staining assays revealed that protein kinase B (Akt), eNOS andXBP1s form a complex, resulting in Akt and eNOS nucleus relocation. These results suggest that XBP1 splicing can regulate eNOS expression and cellular location, leading to EC migration and therefore contributing to wound healing and angiogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗
DOE OSTI2015

Thermally averaged collision strengths for extreme-ultraviolet line of Fe ix

Collision strengths and thermally averaged collision strengths for a large number of extreme-ultraviolet lines of Fe ix arising by electron impact have been reported. The thermally averaged collision strengths are calculated at electron temperatures in the range 10{sup 4}–10{sup 7} K for the 122,043 forbidden and allowed transitions between the 370 fine-structure levels. The atomic parameters for Fe ix play an important role in modeling of various astrophysical plasmas, including especially the solar corona. The B-spline Breit–Pauli R-matrix method has been used in the calculation of collision strengths. The target wave functions and transition probabilities have been determined by combining the multiconfiguration Hartree–Fock method with the B-spline box-based multichannel expansions. We have included 370 fine-structure levels of Fe ix in the energy region up to 3s{sup 2}3p{sup 5}5s states. The close-coupling expansion includes levels of the 3s{sup 2}3p{sup 6}, 3s{sup 2}3p{sup 5}3d,4l,5s, 3s3p{sup 6}3d,4s,4p, 3s{sup 2}3p{sup 4}3d{sup 2}, 3s3p{sup 5}3d{sup 2} configurations and some low-lying levels of the 3s{sup 2}3p{sup 3}3d{sup 3} configuration in our collision strengths and transition probabilities calculations. There is a good agreement with the previous R-matrix collision strength calculations by Storey et al. and Del Zanna et al. for transitions between the lowest 17 levels of the 3s{sup 2}3p{sup 6}, 3s{sup 2}3p{sup 5}3d, and 3s3p{sup 6}3d configurations, especially for electron temperatures log T(K) ≥ 5.0. The transitions between the first 17 levels are dominated by Rydberg series of resonances converging to the levels of the 3s{sup 2}3p{sup 4}3d{sup 2} configuration. The present results and the calculation of Del Zanna et al. show significant differences for many weaker forbidden and intercombination transitions with thermally averaged collision strengths smaller than 0.01.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

NSRD-16: Computational Capability to Substantiate DOE-HDBk-3010 Data

Safety basis analysts throughout the U.S. Department of Energy (DOE) complex rely heavily on the information provided in the DOE Handbook, DOE-HDBK-3010, Airborne Release Fractions/Rates and Respirable Fractions for Nonreactor Nuclear Facilities, to determine radionuclide source terms from postulated accident scenarios. In calculating source terms, analysts tend to use the DOE Handbook's bounding values on airborne release fractions (ARFs) and respirable fractions (RFs) for various categories of insults (representing potential accident release categories). This is typically due to both time constraints and the avoidance of regulatory critique. Unfortunately, these bounding ARFs/RFs represent extremely conservative values. Moreover, they were derived from very limited small-scale bench/laboratory experiments and/or from engineered judgment. Thus, the basis for the data may not be representative of the actual unique accident conditions and configurations being evaluated. The goal of this research is to develop a more accurate and defensible method to determine bounding values for the DOE Handbook using state-of-art multi-physics-based computer codes. This enables us to better understand the fundamental physics and phenomena associated with the types of accidents in the handbook. In this fourth year, we improved existing computational capabilities to better model fragmentation situations to capture small fragments during an impact accident. In addition, we have provided additional new information for various sections of Chapters 4 and 5 of the Handbook on free fall powders and impacts of solids, and have provided the damage ratio simulations for containers (7A drum and standard waste box) for various drops and impact scenarios. Thus, this work provides a low-cost method to establish physics-justified safety bounds by considering specific geometries and conditions that may not have been previously measured and/or are too costly to perform during an experiment.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1986

Grain dynamics in zero gravity

The dynamics of granular materials has proved difficult to model, primarily because of the complications arising from inelastic losses, friction, packing, and the effect of many grains being in contact simultaneously. The kinetic model of granular systems is similar to the kinetic theory of gases, except that collisional energy losses are always present in the former and must be treated explicity. Few granular materials on Earth are describable by this limiting model, since gravity tends to collapse the grains into a high density state where Coulombic friction effects are dominant. The planned Space Station offers an unusual opportunity to test the kinetic grain model and to explore its predictions. Without gravity, the regime of low interparticle velocities (where an elastic description of the collision is still valid) can be investigated. This will allow for direct interpretation by dynamical computer simulations as well as by the kinetic theory. The dynamics of spherical grains inside a clear box would be examined. Results would be compared with the predictions of the kinetic theory and computer simulations.

Werner, B. T.↗
NASA NTRS1991

Simulation of deep one- and two-dimensional redshift surveys

It is shown that slice or pencil-beam redshift surveys of galaxies can be simulated in a box with nonequal sides. This method saves a lot of computer time and memory while providing essentially the same results as from whole-cube simulations. A 2457.6/h Mpc-long rod (out to a redshift z = 0.58 in two opposite directions) is simulated using the standard biased cold dark matter model as an example to mimic the recent deep pencil-beam surveys by Broadhurst et al. (1990). The structures (spikes) seen in these simulated samples occur when the narrow pencil-beam pierces walls, filaments, and clusters appearing randomly along the line-of-sight. A statistical test for goodness of fit to a periodic lattice has been applied to the observations and the simulations. It is found that the statistical significance level (P = 15.4 percent) is not strong enough to reject the null hypothesis that the observations and the simulations were drawn at random from the same set.

Park, Changbom↗
NASA NTRS2001

Some Advanced Concepts in Discrete Aerodynamic Sensitivity Analysis

An efficient incremental-iterative approach for differentiating advanced flow codes is successfully demonstrated on a 2D inviscid model problem. The method employs the reverse-mode capability of the automatic- differentiation software tool ADIFOR 3.0, and is proven to yield accurate first-order aerodynamic sensitivity derivatives. A substantial reduction in CPU time and computer memory is demonstrated in comparison with results from a straight-forward, black-box reverse- mode application of ADIFOR 3.0 to the same flow code. An ADIFOR-assisted procedure for accurate second-order aerodynamic sensitivity derivatives is successfully verified on an inviscid transonic lifting airfoil example problem. The method requires that first-order derivatives are calculated first using both the forward (direct) and reverse (adjoint) procedures; then, a very efficient non-iterative calculation of all second-order derivatives can be accomplished. Accurate second derivatives (i.e., the complete Hessian matrices) of lift, wave-drag, and pitching-moment coefficients are calculated with respect to geometric- shape, angle-of-attack, and freestream Mach number

Taylor, Arthur C., III↗
NASA NTRS2001

Quantitative risk assessment system (QRAS)

A quantitative risk assessment system (QRAS) builds a risk model of a system for which risk of failure is being assessed, then analyzes the risk of the system corresponding to the risk model. The QRAS performs sensitivity analysis of the risk model by altering fundamental components and quantifications built into the risk model, then re-analyzes the risk of the system using the modifications. More particularly, the risk model is built by building a hierarchy, creating a mission timeline, quantifying failure modes, and building/editing event sequence diagrams. Multiplicities, dependencies, and redundancies of the system are included in the risk model. For analysis runs, a fixed baseline is first constructed and stored. This baseline contains the lowest level scenarios, preserved in event tree structure. The analysis runs, at any level of the hierarchy and below, access this baseline for risk quantitative computation as well as ranking of particular risks. A standalone Tool Box capability exists, allowing the user to store application programs within QRAS.

Weinstock, Robert M↗
NASA NTRS2014

Implementation and Initial Validation of a 100-Kilowatt Class Nested-Channel Hall Thruster

The X3 is a 100-kilowatt class nested-channel Hall thruster developed by the Plasmadynamics and Electric Propulsion Laboratory at the University of Michigan in collaboration with the Air Force Research Laboratory and NASA. The cathode, magnetic circuit, boron nitride channel rings, and anodes all required specific design considerations during thruster development, and thermal modeling was used to properly account for thermal growth in material selection and component design. A number of facility upgrades were required at the University of Michigan to facilitate operation of the X3. These upgrades included a re-worked propellant feed system, a completely redesigned power and telemetry break-out box, and numerous updates to thruster handling equipment. The X3 was tested on xenon propellant at two current densities, 37% and 73% of the nominal design value. It was operated to a maximum steady-state discharge power of 60.8 kilowatts. The tests presented here served as an initial validation of thruster operation. Thruster behavior was monitored with telemetry, photography and high-speed current probes. The photography showed a uniform plume throughout testing. At constant current density, reductions in mass flow rate of 18% and 26% were observed in the three-channel operating configuration as compared to the superposition of each channel running individually. The high-speed current probes showed that the thruster was stable at all operating points and that the channels influence each other when more than one is operating simultaneously. Additionally, the ratio of peak-to-peak AC-coupled discharge current oscillations to mean discharge current did not exceed 51% for any operating points reported here, and did not exceed 17% at the higher current density.

High Power↗
NASA NTRS2017

CFD Simulations of the IHF Arc-Jet Flow: Compression-Pad/Separation Bolt Wedge Tests

This paper reports computational analyses in support of two wedge tests in a high enthalpy arc-jet facility at NASA Ames Research Center. These tests were conducted using two different wedge models, each placed in a free jet downstream of a corresponding different conical nozzle in the Ames 60-MW Interaction Heating Facility. Each panel test article included a metallic separation bolt imbedded in Orion compression-pad and heatshield materials, resulting in a circular protuberance over a flat plate. The protuberances produce complex model flowfields, containing shock-shock and shock-boundary layer interactions, and multiple augmented heating regions on the test plate. As part of the test calibration runs, surface pressure and heat flux measurements on water-cooled calibration plates integrated with the wedge models were also obtained. Surface heating distributions on the test articles as well as arc-jet test environment parameters for each test configuration are obtained through computational fluid dynamics simulations, consistent with the facility and calibration measurements. The present analysis comprises simulations of the nonequilibrium flowfield in the facility nozzle, test box, and flowfield over test articles, and comparisons with the measured calibration data.

CFD↗