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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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Bioelectrochemical energy conversion, discussing applications for toxic material identification, powering cardiac pacemakers and electric power generation
A Hybrid Optoelectronic Neural Object Recognition System (HONORS), is disclosed, comprising two major building blocks: (1) an advanced grayscale optical correlator (OC) and (2) a massively parallel three-dimensional neural-processor. The optical correlator, with its inherent advantages in parallel processing and shift invariance, is used for target of interest (TOI) detection and segmentation. The three-dimensional neural-processor, with its robust neural learning capability, is used for target classification and identification. The hybrid optoelectronic neural object recognition system, with its powerful combination of optical processing and neural networks, enables real-time, large frame, automatic target recognition (ATR).
The space station module power management and distribution (SSM/PMAD) breadboard models power distribution and management, including scheduling, load prioritization, and a fault detection, identification, and recovery (FDIR) system within a Space Station Freedom habitation or laboratory module. This 120 VDC system is capable of distributing up to 30 kW of power among more than 25 loads. In addition to the power distribution hardware, the system includes computer control through a hierarchy of processes. The lowest level consists of fast, simple (from a computing standpoint) switchgear that is capable of quickly safing the system. At the next level are local load center processors, (LLP's) which execute load scheduling, perform redundant switching, and shed loads which use more than scheduled power. Above the LLP's are three cooperating artificial intelligence (AI) systems which manage load prioritizations, load scheduling, load shedding, and fault recovery and management. Recent upgrades to hardware and modifications to software at both the LLP and AI system levels promise a drastic increase in speed, a significant increase in functionality and reliability, and potential for further examination of advanced automation techniques. The background, SSM/PMAD, interface to the Lewis Research Center test bed, the large autonomous spacecraft electrical power system, and future plans are discussed.
This paper describes analytical methods used in verification of large DC power systems with applications to the International Space Station (ISS). Large DC power systems contain many switching power converters with negative resistor characteristics. The ISS power system presents numerous challenges with respect to system stability such as complex sources and undefined loads. The Space Station program has developed impedance specifications for sources and loads. The overall approach to system stability consists of specific hardware requirements coupled with extensive system analysis and testing. Testing of large complex distributed power systems is not practical due to size and complexity of the system. Computer modeling has been extensively used to develop hardware specifications as well as to identify system configurations for lab testing. The statistical method of Design of Experiments (DoE) is used as an analysis tool for verification of these large systems. DOE reduces the number of computer runs which are necessary to analyze the performance of a complex power system consisting of hundreds of DC/DC converters. DoE also provides valuable information about the effect of changes in system parameters on the performance of the system. DoE provides information about various operating scenarios and identification of the ones with potential for instability. In this paper we will describe how we have used computer modeling to analyze a large DC power system. A brief description of DoE is given. Examples using applications of DoE to analysis and verification of the ISS power system are provided.
Energy conservation is a key issue in design optimization of Advanced Life Support Systems (ALSS) for long-term space missions. By considering designs for conservation at the system level, energy saving opportunities arise that would otherwise go unnoticed. This paper builds on a steady-state investigation of system-level waste heat reuse in an ALSS with a low degree of crop growth for a Mars mission. In past studies, such a system has been defined in terms of technology types, hot and cold stream identification and stream energy content. The maximum steady-state potential for power and cooling savings within the system was computed via the Pinch Method. In this paper, several practical issues are considered for achieving a pragmatic estimate of total system savings in terms of equivalent system mass (ESM), rather than savings solely in terms of power and cooling. In this paper, more realistic ESM savings are computed by considering heat transfer inefficiencies during material transfer. An estimate of the steady-state mass, volume and crewtime requirements associated with heat exchange equipment is made by considering heat exchange equipment material type and configuration, stream flow characteristics and associated energy losses during the heat exchange process. Also, previously estimated power and cooling savings are adjusted to reflect the impact of such energy losses. This paper goes one step further than the traditional Pinch Method of considering waste heat reuse in heat exchangers to include ESM savings that occur with direct reuse of a stream. For example, rather than exchanging heat between crop growth lamp cooling air and air going to a clothes dryer, air used to cool crop lamps might be reused directly for clothes drying purposes. When thermodynamically feasible, such an approach may increase ESM savings by minimizing the mass, volume and crewtime requirements associated with stream routing equipment.
A system is described with specific examples for identifying and selecting advanced technologies for use with the Space Station Freedom (SSF) that positively impact capabilities and costs. Emerging advanced technologies should be compared with SSF technological needs and selected according to an optimal combination of readiness, development risks/costs, performance requirements, and crew safety. The selected technologies should be planned to the extent that the technology continues advancing to the point of readiness in a manner consistent with the objectives and timeframe of the SSF program. An SSF Advanced Studies component is described that worked to advance critical emergent technologies including advanced heat rejection, closed air-loops, high-efficiency space-power systems, and advanced power storage. The efforts can lead to the identification of crucial parameters such as performance degradation, lifetime, growth, and area that are relevant to the SSF overall objectives.
The Cardiovascular Alterations Team is conducting studies of hemodynamic regulation and susceptibility to arrhythmias resulting from sixteen days of simulated microgravity exposure. In these studies very intensive measurements are made during a short duration of bed rest. In this collaborative effort are making many of the same measurements, however much less frequently, on subjects who are exposed to a much longer duration of simulated microgravity. Alterations in cardiovascular regulation and function that occur during and after space flight have been reported. These alterations are manifested, for example, by reduced orthostatic tolerance upon reentry to the earth's gravity from space. However, the precise physiologic mechanisms responsible for these alterations remain to be fully elucidated. Perhaps, as a result, effective countermeasures have yet to be developed. In addition, numerous reports from the past 30 years suggest that the incidence of ventricular arrhythmias among astronauts is increased during space flight. However, the effects of space flight and the associated physiologic stresses on cardiac conduction processes are not known, and an increase in cardiac susceptibility to arrhythmias has never been quantified. In this project we are applying the most powerful technologies available to determine, in a ground-based study of long duration space flight, the mechanisms by which space flight affects cardiovascular function, and then on the basis of an understanding of these mechanisms to develop rational and specific countermeasures. To this end we are conducting a collaborative project with the Bone Demineralization/Calcium Metabolism Team of the National Space Biomedical Research Institute (NSBRI). The Bone Team is conducting bed rest studies in human subjects lasting 17 weeks, which provides a unique opportunity to study the effects of long duration microgravity exposure on the human cardiovascular system. We are applying a number of powerful new methods to these long term bed rest subjects, including cardiovascular system identification (CSI), microvolt level T wave alternans analysis, and cardiac magnetic resonance imaging to assess non-invasively the effects of simulated long duration space flight on the cardiovascular system.
This paper investigates the utility of the Hilbert-Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert-Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert-Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this paper is to demonstrate the potential applications of the Hilbert-Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized/online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F/A-18 Active Aeroelastic Wing aircraft, an Aerostructures Test Wing, and pitch-plunge simulation.
This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation.
Data readily available from the literature were used to make an initial comparison of the health and safety risks of a fission power system with fuel reprocessing; a combined-cycle coal power system with a low-Btu gasifier and open-cycle gas turbine; a central-station, terrestrial, solar photovoltaic power system; the satellite power system; and a first-generation fusion system. The assessment approach consists of the identification of health and safety issues in each phase of the energy cycle from raw material extraction through electrical generation, waste disposal, and system deactivation; quantitative or qualitative evaluation of impact severity; and the rating of each issue with regard to known or potential impact level and level of uncertainty.
Why don t you use MEMS? is one of the most common questions posed to navigation systems engineers designing inertial navigation solutions in the modern era. The question stems from a general understanding that great strides have been made in terrestrial MEMS accelerometers and attitude rate sensors in terms of accuracy, mass, and power. Yet, when compared on a unit-to-unit basis, MEMS devices do not provide comparable performance (accuracy) to navigation grade sensors. This paper will propose a paradigm shift where the comparison in performance is between multiple MEMS devices and a single navigation grade sensor. The concept is that systematically, a sufficient number of MEMS sensors may mathematically provide comparable performance to a single navigation grade device and be competitive in terms power and mass allocations when viewed on a systems level. The implication is that both inertial navigation system design and fault detection, identification, and recovery could benefit from a system of MEMS devices in the same way that swarm sensing has benefited Earth observation and astronomy. A survey of the state of the art in inertial sensor accuracy scaled by mass and power will be provided to show the specific error in MEMS and navigation graded devices, a mathematical comparison of multi-unit to single-unit sensor errors will be developed, and preliminary applications to Constellation vehicles will be explored.
"Why don't you use MEMS?" is of the most common questions posed to navigation systems engineers designing inertial navigation solutions in the modern era. The question stems from a general understanding that great strides have been made in terrestrial MEMS accelerometers and attitude rate sensors in terms of accuracy, mass, and power. Yet, when compared on a unit-to-unit basis, MEMS devices do not provide comparable performance (accuracy) to navigation grade sensors in several key metrics. This paper will propose a paradigm shift where the comparison in performance is between multiple MEMS devices and a single navigation grade sensor. The concept is that systematically, a sufficient number of MEMS sensors may mathematically provide comparable performance to a single navigation grade device and be competitive in terms power and mass allocations when viewed on a systems level. The implication is that both inertial navigation system design and fault detection, identification, and recovery could benefit from a system of MEMS devices in the same way that swarm sensing has benefited Earth observation and astronomy. A survey of the state of the art in inertial sensor accuracy scaled by mass and power will be provided to show the scaled error in MEMS and navigation graded devices, a mathematical comparison of multi-unit to single-unit sensor errors will be developed, and preliminary application to an Orion lunar skip atmospheric entry trajectory will be explored.
The objective is to develop a real time fault monitoring and diagnosis knowledge-based system (KBS) for space power systems which can save costly operational manpower and can achieve more reliable space power system operation. The proposed KBS was developed using the Autonomously Managed Power System (AMPS) test facility currently installed at NASA Marshall Space Flight Center (MSFC), but the basic approach taken for this project could be applicable for other space power systems. The proposed KBS is entitled Autonomously Managed Power-System Extendible Real-time Expert System (AMPERES). In Phase 1 the emphasis was put on the design of the overall KBS, the identification of the basic research required, the initial performance of the research, and the development of a prototype KBS. In Phase 2, emphasis is put on the completion of the research initiated in Phase 1, and the enhancement of the prototype KBS developed in Phase 1. This enhancement is intended to achieve a working real time KBS incorporated with the NASA space power system test facilities. Three major research areas were identified and progress was made in each area. These areas are real time data acquisition and its supporting data structure; sensor value validations; development of inference scheme for effective fault monitoring and diagnosis, and its supporting knowledge representation scheme.
The 6 ft. by 6 ft. thermal vacuum chamber (TVAC), housed in Building 1250 at the NASA Langley Research Center (LaRC), and managed by the Systems Integration and Test Branch within the Engineering Directorate, has undergone several significant modifications to increase testing capability, safety, and quality of measurements of articles under environmental test. Significant modifications include: a new nitrogen thermal conditioning unit for controlling shroud temperatures from -150degC to +150degC; two horizontal auxiliary cold plates for independent temperature control from -150degC to +200degC; a suite of contamination monitoring sensors for outgassing measurements and species identification; signal and power feed-throughs; new pressure gauges; and a new data acquisition and control commanding system including safety interlocks. This presentation will provide a general overview of the LaRC 6 ft. by 6 ft. TVAC chamber, an overview of the new technical capabilities, and illustrate each upgrade in detail, in terms of mechanical design and predicted performance. Additionally, an overview of the scope of tests currently being performed in the chamber will be documented, and sensor plots from tests will be provided to show chamber temperature and pressure performance with actual flight hardware under test.
High performance aircraft are, by their very nature, often required to undergo maneuvers involving high angles of attack. Under these conditions unsteady vortices emanating from the wing and the fuselage will impinge on the twin fins (required for directional stability) causing excessive buffet loads, in some circumstances, to be applied to the aircraft. These loads result in oscillatory stresses, which may cause significant amounts of fatigue damage. Active control is a possible solution to this important problem. A full-scale test was carried out on an F/A-18 fuselage and fins using piezoceramic actuators to control the vibrations. Buffet loads were simulated using very powerful electromagnetic shakers. The first phase of this test was concerned with the open loop system identification whereas the second stage involved implementing linear time invariant control laws. This paper looks at some of the problems encountered as well as the corresponding solutions and some results. It is expected that flight trials of a similar control system to alleviate buffet will occur as early as 2001.
Prognostics is an engineering discipline that focuses on estimation of the health state of a component and the prediction of its remaining useful life (RUL) before failure. Health state estimation is based on actual conditions and it is fundamental for the prediction of RUL under anticipated future usage. Failure of electronic devices is of great concern as future aircraft will see an increase of electronics to drive and control safety-critical equipment throughout the aircraft. Therefore, development of prognostics solutions for electronics is of key importance. This paper presents an accelerated aging system for gate-controlled power transistors. This system allows for the understanding of the effects of failure mechanisms, and the identification of leading indicators of failure which are essential in the development of physics-based degradation models and RUL prediction. In particular, this system isolates electrical overstress from thermal overstress. Also, this system allows for a precise control of internal temperatures, enabling the exploration of intrinsic failure mechanisms not related to the device packaging. By controlling the temperature within safe operation levels of the device, accelerated aging is induced by electrical overstress only, avoiding the generation of thermal cycles. The temperature is controlled by active thermal-electric units. Several electrical and thermal signals are measured in-situ and recorded for further analysis in the identification of leading indicators of failures. This system, therefore, provides a unique capability in the exploration of different failure mechanisms and the identification of precursors of failure that can be used to provide a health management solution for electronic devices.
This work describes the scaling and design attributes of Nested Hall Thrusters (NHT) with extremely large operational envelopes, including a wide range of throttleability in power and specific impulse at high efficiency (>50%). NHTs have the potential to provide the game changing performance, powerprocessing capabilities, and cost effectiveness required to enable missions that cannot otherwise be accomplished. NHTs were first identified in the electric propulsion community as a path to 100- kW class thrusters for human missions. This study aimed to identify the performance capabilities NHTs can provide for NASA robotic and human missions, with an emphasis on 10-kW class thrusters well-suited for robotic exploration. A key outcome of this work has been the identification of NHTs as nearly constant-efficiency devices over large power throttling ratios, especially in direct-drive power systems. NHT systems sized for robotic solar system exploration are predicted to be capable of high-efficiency operation over nearly their entire power throttling range. A traditional Annular Hall Thruster (AHT) consists of a single annular discharge chamber where the propellant is ionized and accelerated. In an NHT, multiple annular channels are concentrically stacked. The channels can be operated in unison or individually depending on the available power or required performance. When throttling an AHT, performance must be sacrificed since a single channel cannot satisfy the diverse design attributes needed to maintain high thrust efficiency. NHTs can satisfy these requirements by varying which channels are operated and thereby offer significant benefits in terms of thruster performance, especially under deep power throttling conditions where the efficiency of an AHT suffers since a single channel can only operate efficiently (>50%) over a narrow power throttling ratio (3:1). Designs for 10-kW class NHTs were developed and compared with AHT systems. Power processing systems were considered using either traditional Power Processing Units (PPU) or Direct Drive Units (DDU). In a PPU-based system, power from the solar arrays is transformed from the low voltage of the arrays to the high voltage needed by the thruster. In a DDU-based system, power from the solar arrays is fed to the thruster without conversion. DDU-based systems are attractive for their simplicity since they eliminate the most complex and expensive part of the propulsion system. The results point to the strong potential of NHTs operating with either PPUs or DDUs to benefit robotic and human missions through their unprecedented power and specific impulse throttling capabilities. NHTs coupled to traditional PPUs are predicted to offer high-efficiency (>50%) power throttling ratios 320% greater than present capabilities, while NHTs with direct-drive power systems (DDU) could exceed existing capabilities by 340%. Because the NHT-DDU approach is implicitly low-cost, NHT-DDU technology has the potential to radically reduce the cost of SEP-enabled NASA missions while simultaneously enabling unprecedented performance capability.
A multi-input multi-output system identification technique is used to obtain linearized point models of the Space Shuttle Main Engine (SSME) at five different operating conditions (power levels) from the engine firing data. This study demonstrates that the open-loop dynamics of the SSME can be successfully modeled from the engine firing data. The identified linear models may be used for fault detection studies and control system design and development.