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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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The time- and frequency-domain properties of the orthogonal binomial sequences are presented. It is shown that these sequences, or digital filters based on them, can be generated using adders and delay elements only. The frequency-domain behavior of these nonrecursive binomial filters suggests a number of applications as low-pass Gaussian filters or as inexpensive bandpass filters.
Unsteady lifting-line theory is developed for a flexible unswept wing of large aspect ratio oscillating at low frequency in inviscid incompressible flow. The theory is formulated in terms of the acceleration potential and treated by the method of matched asymptotic expansions. The wing displacements are prescribed and the pressure field, airloads, and unsteady induced downwash are obtained in closed form. Sample numerical calculations are presented. The present work identifies and resolves errors in the unsteady lifting-line theory of James and points out a limitation in that of Van Holten. Comparison of the results of Reissner's approximate unsteady lifting-surface theory with those of the present work shows favorable agreement. The present work thus provides some formal justification for Reissner's ad hoc theory. For engineering purposes, the region of applicability of the theory in the reduced frequency-aspect ratio domain is identified approximately and found to cover most cases of practical interest.
This paper presents the necessary conditions for solving Chebyshev minimax (or maximax) problems with bounded control. The jump conditions obtained are applicable to problems with single or multiple maxima. By using Contensou domain of maneuverability, it is shown that when the maxima are isolated single points the control is generally continuous at the jump point in the minimax problems and discontinuous in the maximax problems in which the first time derivative of the maximax function contains the control variable. The theory is applied to the problem of maximizing the flight radius in a closed circuit glide of a hypervelocity vehicle and to a maximax optimal control problem in which the control appears explicitly with the first time derivative of the maximax function.
At NASA Goddard, the role of the command management system (CMS) is to transform general requests for spacecraft opeerations into detailed operational plans to be uplinked to the spacecraft. The CMS is part of the NASA Data System which entails the downlink of science and engineering data from NASA near-earth satellites to the user, and the uplink of command and control data to the spacecraft. Presently, it takes one to three years, with meetings once or twice a week, to determine functional requirements for CMS software design. As an alternative approach to the present technique of developing CMS software functional requirements, an expert system prototype was developed to aid in this function. Specifically, the knowledge base was formulated through interactions with domain experts, and was then linked to an existing expert system application generator called 'Knowledge Engineering System (Version 1.3).' Knowledge base development focused on four major steps: (1) develop the problem-oriented attribute hierachy; (2) determine the knowledge management approach; (3) encode the knowledge base; and (4) validate, test, certify, and evaluate the knowledge base and the expert system prototype as a whole. Backcasting was accomplished for validating and testing the expert system prototype. Knowledge refinement, evaluation, and implementation procedures of the expert system prototype were then transacted.
We present a novel time-domain method for the detection of faulty bearings that has direct applicability to monitoring the health of the turbo pumps on the Space Shuttle Main Engine. A feed-forward neural network was trained to detect modelled roller bearing faults on the basis of the periodicity of impact pulse trains. The network's performance was dependent upon the number of pulses in the network's input window and the signal-to-noise ratio of the input signal. To test the model's validity, we fit the model's parameters to an actual vibration signal generated by a faulty roller element bearing and applied the network trained on this model to detect faults in actual vibration data. When this network was tested on the actual vibration data, it correctly identified the vibration signal as a fault condition 76 percent of the time.
The aspects of nonlinear behavior of a finite length liquid column is investigated with an emphasis on bridge dynamics. The primary objectives are to determine the nonlinear corrections to the interface shape of a naturally oscillating finite length liquid column and to determine the nonlinear corrections to the oscillation frequencies for various modes of oscillation. Application of the Lindstedt-Poincare expansion in conjunction with the domain perturbation techniques results in an hierarchical system of equations.
In the control center, raw telemetry data is received for storage, display, and analysis. This raw data must be combined and manipulated in various ways by mathematical computations to facilitate analysis, provide diversified fault detection mechanisms, and enhance display readability. A development tool called the Graphical Computation Builder (GCB) has been implemented which provides flight controllers with the capability to implement computations for use in the control center. The GCB provides a language that contains both general programming constructs and language elements specifically tailored for the control center environment. The GCB concept allows staff who are not skilled in computer programming to author and maintain computer programs. The GCB user is isolated from the details of external subsystem interfaces and has access to high-level functions such as matrix operators, trigonometric functions, and unit conversion macros. The GCB provides a high level of feedback during computation development that improves upon the often cryptic errors produced by computer language compilers. An equivalent need can be identified in the industrial data acquisition and process control domain: that of an integrated graphical development tool tailored to the application to hide the operating system, computer language, and data acquisition interface details. The GCB features a modular design which makes it suitable for technology transfer without significant rework. Control center-specific language elements can be replaced by elements specific to industrial process control.
We generalize Harten's multiresolution representation to biorthogonal multiwavelets. Several variants are considered. For example, a given array of discrete point values is transformed to point values and derivatives or point 'values and cell averages'. Compact Hermite interpolation is used in the decomposition and reconstruction algorithm. The resulting basis functions that are symmetric or skewsymmetric, compact, and smooth with optimal order accuracy. Harten's approach has several advantages: the multiresolution scheme is inherently discrete, non-periodic boundary conditions are easy to implement, and the representation can be extended to unstructured grids in bounded domains. We demonstrate the compression features of the new mutliwavelets by application to variable scale piecewise smooth functions with jump discontinuities typical of numerical solutions of nonlinear hyperbolic conservation laws.
In an effort to expand the helicopter flight envelope, this analytical study proposes the concept of using high frequency blade pitch actuation to alleviate blade stall at high speed and/or high thrust flight conditions. The availability of high-frequency blade-mounted actuators has made this concept realizable. This study is carried out using the University of Maryland Advanced Rotorcraft Code (or UMARC), which employs state-of-the-art structural and aerodynamic modelings. The salient features of this code include the application of the finite element methods in both space and time domains, and the incorporation of an advanced unsteady aerodynamic and nonuniform inflow models. Preliminary results indicate that two-per-rev blade pitch control can reduce retreating blade stall for a rotor operating at high speed and high thrust flight condition. Current efforts concentrate on developing an automatic stall suppression system which employs a combination of higher harmonic blade pitch schedule.
In the Tui ine Branch of the Turbomachinery and Propulsion Systems Division, researching and developing efficient turbine aerothermodynamics technologies is the main objective. Creating effective turbines for jet engines is a process which, if based purely on physical experimental testing, would be extremely expensive. It is for this reason, and also for the reasons of speed and ease, that the Turbine Branch spends a large amount of effort working with simulations of turbines. Specifically, they focus their work on two main fields: Computational Field Dynamics (CFD), and Experimental data analysis. The experimental field involves comparing experimental results to simulated results, whereas the CFD field involves running these simulations. The simulations are applied to aerodynamics and heat transfer cases, for both steady and unsteady flow conditions. By and large this work is applied to the domain of flow and heat transfer in axial turbines. The main application used to run these heat flow simulations is GlennHT. This program, recently rewritten in FORTRAN 90, allows the user to input a job file which specifies all the necessary parameters needed to simulate flow through a user-defined grid. There are several other executables used as well, ranging in application from converting grid files to and from particular formats, to merging blocks in a connectivity file, to converting connectivity files to a GlennHT compatible format. All of these executables are run from the command line in a terminal; some of them have interactive prompts where the user must specify the files to be manipulated after the program starts, while others take all of their parameters from the command line. With this amount of variation comes a good deal of commands and formats to memorize, which can cause slower and less efficient work, as users may forget how to execute a certain program, or not remember the pathnames of the files they wish to use. Two years ago, steps were made to expedite this process with a graphical user interface (GUI) that combines the functionality of all the executables along with adding some new functionality, such as residuals graphing and boundary conditions creation. Upon my beginning here at Glenn, many parts of the GUI, which was developed in Java, were nonfunctional. There were also issues with cross-platforming, as systems in the branch were transitioning from Silicon Graphics (SGI) machines to Linux machines. My goals this summer are to finish the parts of the GUI that are not yet completed, fix parts that did not work correctly, expand the functionality to include other useful features, such as grid surface highlighting, and make the system compatible with both Linux and SGI. I will also be heavily testing the system and providing sufficient documentation on how to use the GUI, as no such documentation existed previously.
The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 900,000 reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 5,500 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides de-identified report information through the online ASRS Database at http://asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation \vill discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.
In this paper, we discuss the scheduling capability of APGEN (Activity Plan Generator), a multi-mission planning application that is part of the NASA AMMOS (Advanced Multi- Mission Operations System), and how APGEN scheduling evolved over its applications to specific Space Missions. Our analysis identifies two major reasons for the successful application of APGEN scheduling to real problems: an expressive DSL (Domain-Specific Language) for formulating scheduling algorithms, and a well-defined process for enlisting the help of auxiliary modeling tools in providing high-fidelity, system-level simulations of the combined spacecraft and ground support system.
The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 million reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.
The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 M reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.
Operations engineering teams interact with complex data systems to make technical decisions that ensure the operational efficacy of their missions. To support these decision-making tasks, which may require elastic prioritization of goals dependent on changing conditions, custom analytics tools are often developed. We were asked to develop such a tool by a team at the NASA Jet Propulsion Laboratory, where rover telecom operators make decisions based on models predicting how much data rovers can transfer from the surface of Mars. Through research, design, implementation, and informal evaluation of our new tool, we developed principles to inform the design of visual analytics systems in operations contexts. We offer these principles as a step towards understanding the complex task of designing these systems. The principles we present are applicable to designers and developers tasked with building analytics systems in domains that face complex operations challenges such as scheduling, routing, and logistics.
Neuromorphic processors are designed to execute Deep Neural Networks (DNNs) at very high speed using only a fraction of the electrical power needed to run a DNN on a traditional CPU or GPU. This unique capability makes Neuromorphic processors a prime candidate for space systems, where advanced computational tasks like image analysis, depth map reconstruction, or rover control need to be executed in a power-starved environment. In contrast to the growing number of applications of Neuromorphic processors in smart phones, the automotive and robotics domain, the space environment is unforgiving because of extreme temperatures and high levels of radiation. Any space system, operating beyond LEO requires computing hardware that is resilient against radiation effects. However, Neuromorphic processors have not yet been designed or tested for their radiation tolerance. In this report, we consider traditional methods of detection of radiation events and mitigation via redundancy and gauge their effectiveness on DNNs. In contrast to traditional flight software, however, neural networks represent a statistical algorithm, which might affect its resilience against radiation events. We will focus on the analysis of the tolerance of DNNs with respect to radiation events and discuss techniques to detect radiation hits using on-chip triple modular redundancy (TMR) on an Intel Loihi neuromorphic processor and to mitigate radiation damage. We describe an architecture for on-chip TMR for the Intel Loihi and present results of initial experiments.
We propose an application of molecular information theory to analyze the folding of single domain proteins. We analyze results from various areas of protein science, such as sequence-based potentials, reduced amino acid alphabets, backbone configurational entropy, secondary structure content, residue burial layers, and mutational studies of protein stability changes. We found that the average information contained in the sequences of evolved proteins is very close to the average information needed to specify a fold ~2.2 ± 0.3 bits/(site operation). The effective alphabet size in evolved proteins equals the effective number of conformations of a residue in the compact unfolded state at around 5. We calculated an energy-to-information conversion efficiency upon folding of around 50%, lower than the theoretical limit of 70%, but much higher than human built macroscopic machines. We propose a simple mapping between molecular information theory and energy landscape theory and explore the connections between sequence evolution, configurational entropy and the energetics of protein folding.
Assurance cases are being increasingly acknowledged as away to build trust in complex systems with autonomous capabilities. An assurance case is a comprehensive, defensible, and valid justification that a system will function as intended for a specific mission and operating environment. Formal verification is often reserved for the most critical components of such systems. However, formal verification tools are often complex, and their usage is subject to many constraints and contextual dependencies. This can raise challenges both for performing the verification as well as reflecting the verification results appropriately in the assurance case, especially for non-expert users of the verification tool. To address these challenges, we present a tool-supported methodology for integrating formal verification results in an assurance case by capturing key verification method information in a rigorously constructed assurance case. In particular, we capture the tool specification in terms of its inputs, outputs, and assurance constraints as assumptions over inputs and guarantees provided over its outputs. The tool specification is parametrized over the inputs and outputs to both guide the intended application of the tool, as well as to check that the tool has been applied following the stated assumptions and that the guarantees hold. We define a generic tool assurance argument pattern that enables integration of the verification results in the assurance case by allowing custom refinement and automated instantiation for each tool use. We demonstrate our methodology on two formal verification tools and their applications to the verification of neural network properties for the aircraft domain.