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NASA NTRS2010

Performance and Stability Analyses of Rocket Thrust Chambers with Oxygen/Methane Propellants

Liquid rocket engines using oxygen and methane propellants are being considered by the National Aeronautics and Space Administration (NASA) for future in-space vehicles. This propellant combination has not been previously used in flight-qualified engine systems developed by NASA, so limited test data and analysis results are available at this stage of early development. As part of activities for the Propulsion and Cryogenic Advanced Development (PCAD) project funded under the Exploration Technology Development Program, the NASA Marshall Space Flight Center (MSFC) has been evaluating capability to model combustion performance and stability for oxygen and methane propellants. This activity has been proceeding for about two years and this paper is a summary of results to date. Hot-fire test results of oxygen/methane propellant rocket engine combustion devices for the modeling investigations have come from several sources, including multi-element injector tests with gaseous methane from the 1980s, single element tests with gaseous methane funded through the Constellation University Institutes Program, and multi-element injector tests with both gaseous and liquid methane conducted at the NASA MSFC funded by PCAD. For the latter, test results of both impinging and coaxial element injectors using liquid oxygen and liquid methane propellants are included. Configurations were modeled with two one-dimensional liquid rocket combustion analysis codes, the Rocket Combustor Interactive Design and Analysis code and the Coaxial Injector Combustion Model. Special effort was focused on how these codes can be used to model combustion and performance with oxygen/methane propellants a priori, and what anchoring or calibrating features need to be applied, improved or developed in the future. Low frequency combustion instability (chug) occurred, with frequencies ranging from 150 to 250 Hz, with several multi-element injectors with liquid/liquid propellants, and was modeled using techniques from Wenzel and Szuch. High-frequency combustion instability also occurred at the first tangential (1T) mode, at about 4500 Hz, with several multi-element injectors with liquid/liquid propellants. Analyses of the transverse mode instability were conducted by evaluating injector resonances and empirical methods developed by Hewitt.

Hulka, James R.↗

NASA NTRS1980

Development of advanced avionics systems applicable to terminal-configured vehicles

A technique to add the time constraint to the automatic descent feature of the existing L-1011 aircraft Flight Management System (FMS) was developed. Software modifications were incorporated in the FMS computer program and the results checked by lab simulation and on a series of eleven test flights. An arrival time dispersion (2 sigma) of 19 seconds was achieved. The 4 D descent technique can be integrated with the time-based metering method of air traffic control. Substantial reductions in delays at today's busy airports should result.

Heimbold, R. L.↗

NASA NTRS1982

Development and operating characteristics of an advanced two-stage combustor

Results are presented from an experimental program aimed at optimizing the features of an advanced two-stage combustor that currently is being developed as part of the National Aeronautics and Space Administration/Pratt & Whitney Aircraft Energy Efficient Engine program. The combustor is designed to meet stringent goals for performance, emissions, durability and operational characteristics. An overview of the design selection process in light of these goals is discussed. Combustor rig test results, which highlight the techniques used to reduce emissions, development of the pilot and main power zone fuel injection systems, and methods of achieving efficient fuel staging, are presented.

Greene, W.↗

NASA NTRS1971

Supporting research and technology

The development of definition of the modular space station is discussed. The modular approach was evaluated, the requirements were defined, and program definition and design were accomplished. The features of the program which significantly affect the initial development and early operating costs were identified and their impacts on the program were assessed. Specifications of various systems and components are included.

Source record↗

NASA NTRS1973

A comparison of land-use determinations using data from ERTS-1 and high altitude aircraft

A manual interpretation of ERTS-1 MSS system corrected imagery has been performed on a study area within the Houston Area Test Site to classify land use using the Level 1 categories proposed by the Department of the Interior. The two types of imagery used included: (1) black and white transparencies of each band enlarged to a scale of approximately 1:250,000 and (2) color transparencies composited from the computer compatible tapes using the film recorder on a multispectral data analysis station. The results of this interpretation have been compared with the 1970 land use inventory of HATS which was compiled using color ektachrome imagery from high altitude aircraft (scale 1:120,000). Urban data from the same scene was also analyzed using a computer-aided (clustering) technique. The resulting clusters, representing areas of similar content, were compared with existing land use patterns in Houston. A technique was developed to correlate the spectral clusters to specific urban features on aircraft imagery by the location of specific, high contrast objects in particular resolution elements. It was concluded that ERTS-1 data could be used to develop Level 1 and many Level 2 land use categories for regional inventories and perhaps to some degree on a local level.

Lundelius, M. A.↗

DOE OSTI2013

Improving Site-Specific Radiological Performance Assessments - 13431

An improved approach is presented for conducting complete and defensible radiological site-specific performance assessments (PAs) to support radioactive waste disposal decisions. The basic tenets of PA were initiated some thirty years ago, focusing on geologic disposals and evaluating compliance with regulations. Some of these regulations were inherently probabilistic (i.e., addressing uncertainty in a quantitative fashion), such as the containment requirements of the U.S. Environmental Protection Agency's (EPA's) 40 CFR 191, Environmental Radiation Protection Standards for Management and Disposal of Spent Nuclear Fuel, High-Level and Transuranic Radioactive Wastes, Chap. 191.13 [1]. Methods of analysis were developed to meet those requirements, but at their core early PAs used 'conservative' parameter values and modeling approaches. This limited the utility of such PAs to compliance evaluation, and did little to inform decisions about optimizing disposal, closure and long-term monitoring and maintenance, or, in general, maintaining doses 'as low as reasonably achievable' (ALARA). This basic approach to PA development in the United States was employed essentially unchanged through the end of the 20. century, principally by the U.S. Department of Energy (DOE). Performance assessments developed in support of private radioactive waste disposal operations, regulated by the U.S. Nuclear Regulatory Commission (NRC) and its agreement states, were typically not as sophisticated. Discussion of new approaches to PA is timely, since at the time of this writing, the DOE is in the midst of revising its Order 435.1, Radioactive Waste Management [2], and the NRC is revising 10 CFR 61, Licensing Requirements for Land Disposal of Radioactive Waste [3]. Over the previous decade, theoretical developments and improved computational technology have provided the foundation for integrating decision analysis (DA) concepts and objective-focused thinking, plus a Bayesian approach to probabilistic modeling and risk analysis, to guide improvements in PA. This decision-making approach, [4, 5, 6] provides a transparent formal framework for using a value- or objective-focused approach to decision-making. DA, as an analytical means to implement structured decision making, provides a context for both understanding how uncertainty affects decisions and for targeting uncertainty reduction. The proposed DA approach improves defensibility and transparency of decision-making. The DA approach is fully consistent with the need to perform realistic modeling (rather than conservative modeling), including evaluation of site-specific factors. Instead of using generic stylized scenarios for radionuclide fate and transport and for human exposures to radionuclides, site-specific scenarios better represent the advantages and disadvantages of alternative disposal sites or engineered designs, thus clarifying their differences as well as providing a sound basis for evaluation of site performance. The full DA approach to PA is described, from explicitly incorporating societal values through stakeholder involvement to model building. Model building involves scoping by considering features, events, processes, and exposure scenarios (FEPSs), development of a conceptual site model (CSM), translation into numerical models and subsequent computation, and model evaluation. These are implemented in a cycle of uncertainty analysis, sensitivity analysis and value of information analysis so that uncertainty can be reduced until sufficient confidence is gained in the decisions to be made. This includes the traditional focus on hydrogeological processes, but also places emphasis on other FEPSs such as biotically-induced transport and human exposure phenomena. The significance of human exposure scenarios is emphasized by modifying the traditional acronym 'FEPs' to include them, hence 'FEPSs'. The radioactive waste community is also recognizing that disposal sites are to be considered a national (or even global) resource. As such, there is a pressing need to optimize their utility within the constraints of protecting human health and the environment. Failing to do so will result in the need for additional sites or options for storing radioactive waste temporarily, assuming a continued need for radioactive waste disposal. Optimization should be performed using DA, including economic analysis, invoked if necessary through the ALARA process. The economic analysis must recognize the cost of implementation (disposal design, closure, maintenance, etc.), and intra- and inter-generational equity in order to ensure that the best possible radioactive waste management decisions are made for the protection of both current and future generations. In most cases this requires consideration of population or collective risk. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1989

Structural zooming research and development of an interactive computer graphical interface for stress analysis of cracks

Engineering problems sometimes involve the numerical solution of boundary value problems over domains containing geometric feature with widely varying scales. Often, a detailed solution is required at one or more of these features. Small details in large structures may have profound effects upon global performance. Conversely, large-scale conditions may effect local performance. Many man-hours and CPU-hours are currently spent in modeling such problems. With the structural zooming technique, it is now possible to design an integrated program which allows the analyst to interactively focus upon a small region of interest, to modify the local geometry, and then to obtain highly accurate responses in that region which reflect both the properties of the overall structure and the local detail. A boundary integral equation analysis program, called BOAST, was recently developed for the stress analysis of cracks. This program can accurately analyze two-dimensional linear elastic fracture mechanics problems with far less computational effort than existing finite element codes. An interactive computer graphical interface to BOAST was written. The graphical interface would have several requirements: it would be menu-driven, with mouse input; all aspects of input would be entered graphically; the results of a BOAST analysis would be displayed pictorially but also the user would be able to probe interactively to get numerical values of displacement and stress at desired locations within the analysis domain; the entire procedure would be integrated into a single, easy to use package; and it would be written using calls to the graphic package called HOOPS. The program is nearing completion. All of the preprocessing features are working satisfactorily and were debugged. The postprocessing features are under development, and rudimentary postprocessing should be available by the end of the summer. The program was developed and run on a VAX workstation, and must be ported to the SUN workstation. This activity is currently underway.

Gerstle, Walter↗

DOE OSTI2022

Development of Integrated Thermal Fluids Modeling Capability for MSRs

The DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad class of light-water and advanced reactor concepts. The research and development approach under thermal fluids technical area synergistically combines three length and time scales in a hierarchal multi-scale approach. To demonstrate the feasibility and capabilities of a multi-scale thermal fluids capability using these codes, a key joint effort has been pursued to develop an integrated system-and engineering-scale thermal fluids analysis capability with the MOOSE-based codes, through integration of SAM and Pronghorn, both based on the MOOSE framework. This report summarizes the progress in developing an integrated system- and engineering-scale thermal fluids analysis capability based on SAM and Pronghorn for molten salt reactors (MSRs), which gained significant interest in recently years. Two coupling approaches were studied, i.e. separate domain or domain-segregated coupling approach and the domain-overlapping approach. A series of coupled multi-physics models have been developed for a common reference molten salt fast reactor (MSFR) concept, ranging from standalone SAM system model to integrated SAM-Pronghorn-Griffin models. Both the steady state and the transient simulations are performed to the state-of-the-art simulation capabilities of NEAMS software suite in MSFR system applications. This report also covers further development and testing of the gas transport model in SAM for MSR modeling support. The presence of noncondensable gas in MSR systems would have strong impacts on fission gas removal and transport of noble metals throughout the system. Fission products removed through the off-gas system can also impact reactivity and can act as an additional point of heat removal. To ensure that the gas transport model is adequately tested, the supported modeling capabilities and features of SAM were identified, and a suite of tests were developed to test the model for each identified feature. Validation and UQ testing were also performed for the model and demonstrated that the buoyancy term, which was originally developed using non-salt/helium gas experimental data, can capture the experimental gas bubble velocity and diameter to within experimental and code uncertainty. An existing MSRE model was also modified in this work to include the gas transport model and to demonstrate the gas model behavior for realistic conditions of interest.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1997

Least-Squares Spectral Element Solutions to the CAA Workshop Benchmark Problems

This paper presents computed results for some of the CAA benchmark problems via the acoustic solver developed at Rocketdyne CFD Technology Center under the corporate agreement between Boeing North American, Inc. and NASA for the Aerospace Industry Technology Program. The calculations are considered as benchmark testing of the functionality, accuracy, and performance of the solver. Results of these computations demonstrate that the solver is capable of solving the propagation of aeroacoustic signals. Testing of sound generation and on more realistic problems is now pursued for the industrial applications of this solver. Numerical calculations were performed for the second problem of Category 1 of the current workshop problems for an acoustic pulse scattered from a rigid circular cylinder, and for two of the first CAA workshop problems, i. e., the first problem of Category 1 for the propagation of a linear wave and the first problem of Category 4 for an acoustic pulse reflected from a rigid wall in a uniform flow of Mach 0.5. The aim for including the last two problems in this workshop is to test the effectiveness of some boundary conditions set up in the solver. Numerical results of the last two benchmark problems have been compared with their corresponding exact solutions and the comparisons are excellent. This demonstrates the high fidelity of the solver in handling wave propagation problems. This feature lends the method quite attractive in developing a computational acoustic solver for calculating the aero/hydrodynamic noise in a violent flow environment.

Lin, Wen H.↗

NASA NTRS1995

T/BEST: Technology Benefit Estimator Select Features and Applications

A Technology Benefit Estimator (T/BEST) system has been developed to provide a formal method to assess advanced aerospace technologies and quantify the benefit contributions for prioritization. An open-ended, modular approach is used to allow for upgrade and insertion of advanced technology modules. T/BEST's software framework, beginner-to-expert operation, interface architecture, and key analysis modules are discussed. In this paper, selected features and applications of T/BEST are demonstrated. Sample cases pertaining to structural analysis of titanium and composite blades are presented. The performance of hot and cold composite fan blades is also discussed. The cost required to manufacture titanium and composite fan blades is estimated.

Generazio, Edward R.↗

DOE OSTI2013

Tile-Based Fisher-Ratio Software for Improved Feature Selection Analysis of Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry Data

Two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC – TOFMS) is a highly capable instrumental platform that produces complex and information-rich multi-dimensional chemical data. The complex data can be overwhelming, especially when many samples (of various sample classes) are analyzed with multiple injections for each sample. Thus, the data must be analyzed in such a way to extract the most meaningful information. The pixel-based and peak table-based algorithmic use of Fisher ratios has been used successfully in the past to reduce the multi-dimensional data down to those chemical compounds that are changing between classes relative to those that are not (i.e., chemical feature selection). We report on the initial development of a computationally fast novel tile-based Fisher-ratio software that addresses challenges due to 2D retention time misalignment without explicitly aligning the data, which is a problem for both pixel-based and peak table- based methods. Concurrently, the tile-based Fisher-ratio software maximizes the sensitivity contrast of true positives against a background of potential false positives and noise. To study this software, eight compounds, plus one internal standard, were spiked into diesel at various concentrations. The tile-based F-ratio software was able to discover all spiked analytes, within the complex diesel sample matrix with thousands of potential false positives, in each possible concentration comparison, even at the lowest absolute spiked analyte concentration ratio of 1.06.

chemometrics↗

DOE OSTI2023

Middleware for a Heterogeneous CAV Fleet

This paper introduces CAN to ROS, a model-based code generation tool used in development, testing, and deployment of a heterogeneous fleet of vehicles with robotic sensing in ROS. Code generation supports two main features: (1) self-configuration for deployment in a heterogeneous vehicle fleet, and (2) quick iteration for testing and development of reading vehicle sensors and robotic control. This tool features the ability to detect the vehicle it is in and regenerate and rebuild itself at runtime to provide the proper two-way bridge between ROS and the sensed on-board vehicle sensor network. Code generation relies on a per-model defined JSON to map a CAN database (DBC) to the desired ROS topic names and message types. The live ROS publishing of CAN messages allows for instant feedback, and the code regeneration allows for adjustments in DBC or vehicle JSON to iteratively hone in on new vehicle signals. Generated ROS nodes are written in C++ for runtime use in lightweight embedded computers. This has been tested in vehicles from three different Original Equipment Manufacturers (OEMs), and can be extended to support a wide array of vehicles. By using a unifying ROS specification, a heterogeneous set of vehicles can be unified into a fleet with abstracted model-specific details; this opens the door for developing cross-model software applications for vehicle control, connected vehicle applications, or fleet monitoring systems.

42 ENGINEERING↗

NASA NTRS1999

Integrated Computational System for Aerodynamic Steering and Visualization

In February of 1994, an effort from the Fluid Dynamics and Information Sciences Divisions at NASA Ames Research Center with McDonnel Douglas Aerospace Company and Stanford University was initiated to develop, demonstrate, validate and disseminate automated software for numerical aerodynamic simulation. The goal of the initiative was to develop a tri-discipline approach encompassing CFD, Intelligent Systems, and Automated Flow Feature Recognition to improve the utility of CFD in the design cycle. This approach would then be represented through an intelligent computational system which could accept an engineer's definition of a problem and construct an optimal and reliable CFD solution. Stanford University's role focused on developing technologies that advance visualization capabilities for analysis of CFD data, extract specific flow features useful for the design process, and compare CFD data with experimental data. During the years 1995-1997, Stanford University focused on developing techniques in the area of tensor visualization and flow feature extraction. Software libraries were created enabling feature extraction and exploration of tensor fields. As a proof of concept, a prototype system called the Integrated Computational System (ICS) was developed to demonstrate CFD design cycle. The current research effort focuses on finding a quantitative comparison of general vector fields based on topological features. Since the method relies on topological information, grid matching and vector alignment is not needed in the comparison. This is often a problem with many data comparison techniques. In addition, since only topology based information is stored and compared for each field, there is a significant compression of information that enables large databases to be quickly searched. This report will (1) briefly review the technologies developed during 1995-1997 (2) describe current technologies in the area of comparison techniques, (4) describe the theory of our new method researched during the grant year (5) summarize a few of the results and finally (6) discuss work within the last 6 months that are direct extensions from the grant.

Hesselink, Lambertus↗

DOE OSTI2016

Optimal Power Flow for Distribution Systems under Uncertain Forecasts

The paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) pertinent linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative bounds that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption↗

NASA NTRS1992

SPIKE: Application for ASTRO-D mission planning

SPIKE is a mission planning software system developed by a team of programmers at the STScI for use with the Hubble Space Telescope (HST). SPIKE has been developed for the purpose of automating observatory scheduling to increase the effective utilization and ultimately, scientific return from orbiting telescopes. High-level scheduling strategies using both rule-based and neural network approaches have been incorporated. Graphical displays of activities, constraints, and schedules are an important feature of the system. Although SPIKE was originally developed for the HST, it can be used for other astronomy missions including ground-based observatories. One of the missions that has decided to use SPIKE is ASTRO-D, a Japanese X-ray satellite for which the U.S. is providing a part of the scientific payload. Scheduled to fly in Feb. 1993, its four telescopes will focus X-rays over a wide energy range onto CCD's and imaging gas proportional counters. ASTRO-D will be the first X-ray imaging mission operating over the 0.5-12 keV band with high energy resolution. This combination of capabilities will enable a varied and exciting program of astronomical research to be carried out. ASTRO-D is expected to observe 5 to 20 objects per day and a total of several thousands per year. This requires the implementation of an efficient planning and scheduling system which SPIKE can provide. Although the version of SPIKE that will be used for ASTRO-D mission is almost identical to that used for the HST, there are a few differences. For example, ASTRO-D will use two ground stations for data downlinks, instead of the TDRSS system for data transmission. As a consequence ASTRO-D is constrained by limited on-board data storage capacity to schedule high data-rate observations during periods of frequent high bit rate observations accordingly. We will demonstrate the ASTRO-D version of SPIKE to show what SPIKE can provide and how efficiently it creates an observational schedule.

Isobe, T.↗

NASA NTRS2004

Feature-Identification and Data-Compression Software

A report discusses the continuing development of Windows Interface for Nominal Displacement Selection (WINDS), a computer program for automated analysis of images of the Sun and planets acquired by scientific instruments aboard spacecraft. WINDS is intended to afford capabilities for identification of features, measurement of displacements and velocities, analysis of terrain and of atmospheres, and synthesis of animation sequences of images of terrains and atmospheres from small sets of samples by use of velocity-based interpolation. A major element of WINDS will be a nonlinear correlator capable of tracking small features in complex image sequences. For dynamic image sequences, the correlator will enable compression of data by factors >100. In processing image data, WINDS will take account of such factors as texture in image data, rotation of features during measurement intervals, effects of viewing and solar illumination angles, and vertical structures of atmospheres. WINDS will also take account of positions, aiming directions, and fields of view of cameras to determine three-dimensional feature structures by use of triangulation and stereoscopic analysis techniques.

Jong, Eric De↗

DOE OSTI2024

Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility

One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materials tailored for specific applications. However, realizing this vision requires both providing detailed uncertainty quantification (model prediction errors and domain of applicability) and making models readily usable. At present, it is common practice in the community to assess ML model performance only in terms of prediction accuracy (e.g. mean absolute error), while neglecting detailed uncertainty quantification and robust model accessibility and usability. Here, we demonstrate a practical method for realizing both uncertainty and accessibility features with a large set of models. We develop random forest ML models for 33 materials properties spanning an array of data sources (computational and experimental) and property types (electrical, mechanical, thermodynamic, etc). All models have calibrated ensemble error bars to quantify prediction uncertainty and domain of applicability guidance enabled by kernel-density-estimate-based feature distance measures. All data and models are publicly hosted on the Garden-AI infrastructure, which provides an easy-to-use, persistent interface for model dissemination that permits models to be invoked with only a few lines of Python code. We demonstrate the power of this approach by using our models to conduct a fully ML-based materials discovery exercise to search for new stable, highly active perovskite oxide catalyst materials.

domain of applicability↗