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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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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

A Flexible Evolvable Architecture for Constellation Mission Systems User Applications

While simulating a complex set of repair tasks to be performed by EVA crewmembers on an upcoming mission, flight controllers and astronauts determine that the repair will take much longer than originally anticipated. All equipment in the vicinity of the worksite must be powered off to maintain a safe environment for the astronauts. Because heater power will be unavailable, several critical components will now be at risk of freezing and permanent damage. If an impending thermal violation is detected, Mission Control will have very limited time to react. Therefore, flight controllers must not only modify their procedures to account for these risks, they must also incorporate into their displays outputs from thermal models, alternate temperature measurements, new alarm limits, and emergency power-on commands to enable the detection and response to freezing conditions. Current software for mission control systems makes scenarios like this difficult to address. Given the time frame for modifying software, operations teams are left with labor-intensive operational workarounds as their only options. NASA Ames Research Center (ARC) and NASA Johnson Space Center (JSC) are collaborating on the development of a flexible software system for mission operations that will enable greater user flexibility than has been available to date. Using composable software, end users in the scenario described above could recompose procedures and command and control displays to allow flight controllers to monitor temperature measurements, identify time-critical conditions, and execute the procedures required to respond to these conditions before flight hardware is permanently damaged.

Trimble, Jay P.↗
DOE OSTI2021

Multimessenger Gamma-Ray and Neutrino Coincidence Alerts Using HAWC and IceCube Subthreshold Data

The High Altitude Water Cerenkov (HAWC) and IceCube observatories, through the Astrophysical Multimessenger Observatory Network (AMON) framework, have developed a multimessenger joint search for extragalactic astrophysical sources. This analysis looks for sources that emit both cosmic neutrinos and gamma rays that are produced in photohadronic or hadronic interactions. The AMON system is running continuously, receiving subthreshold data (i.e., data that are not suited on their own to do astrophysical searches) from HAWC and IceCube, and combining them in real time. Here we present the analysis algorithm, as well as results from archival data collected between 2015 June and 2018 August, with a total live time of 3.0 yr. During this period we found two coincident events that have a false-alarm rate (FAR) of <1 coincidence yr -1 , consistent with the background expectations. The real-time implementation of the analysis in the AMON system began on 2019 November 20 and issues alerts to the community through the Gamma-ray Coordinates Network with an FAR threshold of <4 coincidences yr -1 .

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1988

Artificial intelligence applied to process signal analysis

Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

Corsberg, Dan↗
NASA NTRS1981

Traveling-wave maser, closed cycle refrigerator automation

At the present time all traveling-wave maser and closed-cycle refrigerator system (TWM-CCR) and their power supply and helium compressor assemblies are operated manually. Many man-hours are required of highly trained and experienced operators, resulting in high operator cost. Of greater importance are the problems of unpredictable failure and long downtimes. Since field performance is not monitored, system degradation is detected only when it has progressed to the point of catastrophic failure. Without the aid of performance histories, failure diagnosis is arduous and slow. Rational and functional requirements for the TWM-CCR Automation project are the following: (1) to improve reliability and reduce downtime by providing unattended monitor and control, alarm and fault location, failure prediction and self-corrective action; (2) to reduce operator cost by providing automatic tuning and cooldown procedures; and (3) to improve system operations and development by providing the needed engineering data.

Mcneil, J. A.↗
NASA NTRS1991

Calculation of aerosol backscatter from airborne continuous wave focused CO2 Doppler lidar measurements. II - Algorithm performance

This paper examines the performance of the Rothermel et al. (1991) algorithm for calculating aerosol backscatter coefficients from measurements by an airborne continuous wave focused CO2 Doppler lidar by using the algorithm to analyze measurements by the Laser True Airspeed System. The results show that, under optimum signal conditions, backscatter signals are detected unambiguously and the aerosol backscatter coefficients are determined accurately. However, under marginal or subthreshold conditions under which the system sensitivity is degraded, noise can be mistaken for signals. As determined from parametric studies, the 'false-alarm' rate under these conditions depends on the size of the search window and the SNR threshold for valid signals.

Rothermel, Jeffry↗
DOE OSTI2024

Direct Air Capture and Utilization System (DACUS): FEED Study of CarbonCapture Inc. DAC and CarbonCure Utilization Technologies Using United States Steel’s Gary Works Plant Waste Heat

The effects of climate change are drastically perceived through the alarming rates of severe events such as flooding, hurricanes, wildfires, global temperature rise, sea-level rise, and ocean acidification etc., which has prompted the nations across the globe to control & reduce greenhouse gas (GHG) emissions, by massive adoption of electric vehicles, switching to renewal energy sources and promoting sustainable green products. However, recent climate studies have shown that such efforts will not be enough to keep the global temperature rising under 1.5° Celsius by the year 2050, which lead to the development of multiple Direct Air Capture (DAC) technologies. A DAC system extracts CO2 directly from the atmosphere, which is either stored underground for long term or utilized in other processes. The DACUS proposed at U.S. Steel Corporation’s Gary Works Plant in Gary, Indiana, will include an innovative DAC technology from CarbonCapture Inc. (CCI), which will be collocated and powered by waste heat from the steel plant to capture CO2 from ambient air, and CarbonCure CO2 utilization technology- which is a commercial technology that is already installed and in use by early adopters in more than 150 concrete mixing plants across North America and Asia. The University of Illinois at Urbana Champaign spearheaded this Front-End Engineering Design (FEED) study project, which was funded by US Department of Energy (DOE), aimed at designing a state-of-the art DACU system that can remove minimum of 5,000 tonne/year net CO2 from air (based on cradle-to-gate LCA) and converting the captured CO2 into low carbon intensity products. The off takers of the low Carbon product produced by the DACUS have also been identified near the steel plant in the Indiana, Illinois & Wisconsin Region. This creates a full CO2 value chain and provides a means to assess the impact of this holistic approach on job creation, regional economic impact, and environmental justice. DACUS is a promising new technology for reducing greenhouse gas in the atmosphere. Operation costs are minimized by locating CCI’s innovative DAC collector at United States Steel's Gary Works site where waste heat is utilized. Carbon emissions are minimized in CO2 transportation. The captured CO2 will be permanently sequestered in concrete used as construction material. This DOE funded FEED study demonstrates a full CO2 value chain for a DACU system, supported by an industrial facility. If this project were constructed, it would have a very positive and lasting impact on both the environment and the community.

42 ENGINEERING↗
NASA NTRS1989

Spacelab system analysis: The modified free access protocol: An access protocol for communication systems with periodic and Poisson traffic

The protocol definition and terminal hardware for the modified free access protocol, a communications protocol similar to Ethernet, are developed. A MFA protocol simulator and a CSMA/CD math model are also developed. The protocol is tailored to communication systems where the total traffic may be divided into scheduled traffic and Poisson traffic. The scheduled traffic should occur on a periodic basis but may occur after a given event such as a request for data from a large number of stations. The Poisson traffic will include alarms and other random traffic. The purpose of the protocol is to guarantee that scheduled packets will be delivered without collision. This is required in many control and data collection systems. The protocol uses standard Ethernet hardware and software requiring minimum modifications to an existing system. The modification to the protocol only affects the Ethernet transmission privileges and does not effect the Ethernet receiver.

Ingels, Frank↗
NASA NTRS2006

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Kobayashi, Takahisa↗
NASA NTRS2010

Robust Fault Detection and Isolation for Stochastic Systems

This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.

George, Jemin↗
NASA NTRS1998

Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants

Control of air contaminants is a crucial factor in the safety considerations of crewed space flight. Indoor air quality needs to be closely monitored during long range missions such as a Mars mission, and also on large complex space structures such as the International Space Station. This work mainly pertains to the detection and simulation of air contaminants in the space station, though much of the work is easily extended to buildings, and issues of ventilation systems. Here we propose a method with which to track the presence of contaminants using an accurate physical model, and also develop a robust procedure that would raise alarms when certain tolerance levels are exceeded. A part of this research concerns the modeling of air flow inside a spacecraft, and the consequent dispersal pattern of contaminants. Our objective is to also monitor the contaminants on-line, so we develop a state estimation procedure that makes use of the measurements from a sensor system and determines an optimal estimate of the contamination in the system as a function of time and space. The real-time optimal estimates in turn are used to detect faults in the system and also offer diagnoses as to their sources. This work is concerned with the monitoring of air contaminants aboard future generation spacecraft and seeks to satisfy NASA's requirements as outlined in their Strategic Plan document (Technology Development Requirements, 1996).

Ramirez, W. Fred↗
NASA NTRS2003

Aircraft signal definition for flight safety system monitoring system

A system and method compares combinations of vehicle variable values against known combinations of potentially dangerous vehicle input signal values. Alarms and error messages are selectively generated based on such comparisons. An aircraft signal definition is provided to enable definition and monitoring of sets of aircraft input signals to customize such signals for different aircraft. The input signals are compared against known combinations of potentially dangerous values by operational software and hardware of a monitoring function. The aircraft signal definition is created using a text editor or custom application. A compiler receives the aircraft signal definition to generate a binary file that comprises the definition of all the input signals used by the monitoring function. The binary file also contains logic that specifies how the inputs are to be interpreted. The file is then loaded into the monitor function, where it is validated and used to continuously monitor the condition of the aircraft.

Gibbs, Michael↗
NASA NTRS1982

Design of analytical failure detection using secondary observers

The problem of designing analytical failure-detection systems (FDS) for sensors and actuators, using observers, is addressed. The use of observers in FDS is related to the examination of the n-dimensional observer error vector which carries the necessary information on possible failures. The problem is that in practical systems, in which only some of the components of the state vector are measured, one has access only to the m-dimensional observer-output error vector, with m or = to n. In order to cope with these cases, a secondary observer is synthesized to reconstruct the entire observer-error vector from the observer output error vector. This approach leads toward the design of highly sensitive and reliable FDS, with the possibility of obtaining a unique fingerprint for every possible failure. In order to keep the observer's (or Kalman filter) false-alarm rate under a certain specified value, it is necessary to have an acceptable matching between the observer (or Kalman filter) models and the system parameters. A previously developed adaptive observer algorithm is used to maintain the desired system-observer model matching, despite initial mismatching or system parameter variations. Conditions for convergence for the adaptive process are obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors, while accurate and fast parameter identification, in both deterministic and stochastic cases, is obtained.

Sisar, M.↗
NASA NTRS1993

Intelligent neuroprocessors for in-situ launch vehicle propulsion systems health management

Efficacy of existing on-board propulsion systems health management systems (HMS) are severely impacted by computational limitations (e.g., low sampling rates); paradigmatic limitations (e.g., low-fidelity logic/parameter redlining only, false alarms due to noisy/corrupted sensor signatures, preprogrammed diagnostics only); and telemetry bandwidth limitations on space/ground interactions. Ultra-compact/light, adaptive neural networks with massively parallel, asynchronous, fast reconfigurable and fault-tolerant information processing properties have already demonstrated significant potential for inflight diagnostic analyses and resource allocation with reduced ground dependence. In particular, they can automatically exploit correlation effects across multiple sensor streams (plume analyzer, flow meters, vibration detectors, etc.) so as to detect anomaly signatures that cannot be determined from the exploitation of single sensor. Furthermore, neural networks have already demonstrated the potential for impacting real-time fault recovery in vehicle subsystems by adaptively regulating combustion mixture/power subsystems and optimizing resource utilization under degraded conditions. A class of high-performance neuroprocessors, developed at JPL, that have demonstrated potential for next-generation HMS for a family of space transportation vehicles envisioned for the next few decades, including HLLV, NLS, and space shuttle is presented. Of fundamental interest are intelligent neuroprocessors for real-time plume analysis, optimizing combustion mixture-ratio, and feedback to hydraulic, pneumatic control systems. This class includes concurrently asynchronous reprogrammable, nonvolatile, analog neural processors with high speed, high bandwidth electronic/optical I/O interfaced, with special emphasis on NASA's unique requirements in terms of performance, reliability, ultra-high density ultra-compactness, ultra-light weight devices, radiation hardened devices, power stringency, and long life terms.

Gulati, S.↗
NASA NTRS2017

Flight Tests of a Remaining Flying Time Prediction System for Small Electric Aircraft in the Presence of Faults

This paper addresses the problem of building trust in the online prediction of a battery powered aircraft's remaining flying time. A series of flight tests is described that make use of a small electric powered unmanned aerial vehicle (eUAV) to verify the performance of the remaining flying time prediction algorithm. The estimate of remaining flying time is used to activate an alarm when the predicted remaining time is two minutes. This notifies the pilot to transition to the landing phase of the flight. A second alarm is activated when the battery charge falls below a specified limit threshold. This threshold is the point at which the battery energy reserve would no longer safely support two repeated aborted landing attempts. During the test series, the motor system is operated with the same predefined timed airspeed profile for each test. To test the robustness of the prediction, half of the tests were performed with, and half were performed without, a simulated powertrain fault. The pilot remotely engages a resistor bank at a specified time during the test flight to simulate a partial powertrain fault. The flying time prediction system is agnostic of the pilot's activation of the fault and must adapt to the vehicle's state. The time at which the limit threshold on battery charge is reached is then used to measure the accuracy of the remaining flying time predictions. Accuracy requirements for the alarms are considered and the results discussed.

Hogge, Edward F.↗
NASA NTRS1971

Sensitive gaseous hydrogen detection system

System utilizing new type hydrogen sensor has overall detection sensitivity and response speed higher than conventional hot-wire or hot-thermistor detectors. System measures concentrations of from 2 parts per million to 30 percent and is adaptable as leak detector and hazard alarm wherever hydrogen is used.

Macintyre, J. R.↗
NASA NTRS1990

Increased Fire and Toxic Contaminant Detection Responsibility by Use of Distributed, Aspirating Sensors

Viewgraphs of increased fire and toxic contaminant detection responsivity by use of distributed, aspirating sensors for space station are presented. Objectives of the concept described are (1) to enhance fire and toxic contaminant detection responsivity in habitable regions of space station; (2) to reduce system weight and complexity through centralized detector/monitor systems; (3) to increase fire signature information from selected locations in a space station module; and (4) to reduce false alarms.

Youngblood, Wallace W.↗
DOE OSTI2020

The Need for a Maximum Intensity Accident in ANS 8-Series Standards

Y-12 has installed one CAAS system under the ANS 8.3 framework as a safety significant system, and is in the process of designing, installing, and qualifying another. As a safety significant system, the Y-12 CAAS is required to demonstrate that it is able to perform its function and actuate an alarm when exposed to the radiation from both a Minimum Accident of Concern and a maximum intensity accident. The ANS 8-series standards do not present a maximum accident to be considered, nor do they specify dose rate tolerance requirements, leading CAAS vendors to potentially use other standards that provide inadequate criteria. A maximum intensity accident is proposed, and the effects of this accident on CAAS analysis and the vendor’s equipment qualification are discussed

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring

Abstract There is strong socio‐political support for offshore wind development in US territorial waters and construction is planned off several east coast states. Some of the planned development sites coincide with important habitat for critically endangered North Atlantic right whales. Both exclusion zones and passive acoustic monitoring are important tools for managing interactions between marine mammals and human activities. Understanding where animals are with respect to exclusion zones is important to avoid costly construction delays while minimizing the potential for negative impacts. Impact piling from construction of hundreds of offshore wind turbines likely require exclusion zones as large as 10 km. We have developed a three‐hydrophone passive acoustic monitoring system that provides bearing information along with marine mammal detections to allow for informed management decisions in real‐time. Multiple units form a monitoring system designed to determine whether marine mammal calls originate from inside or outside of an exclusion zone. In October 2021, we undertook a full system validation, with a focus on evaluating the detection range and bearing accuracy of the system with respect to right whale upcalls. Five units were deployed in Mid‐Atlantic waters and we played more than 3500 simulated right whale upcalls at known locations to characterize the detection function and bearing accuracy of each unit. The modelled results of the detection function error were then used to compare the effectiveness of a bearing‐based system to a single sensor that can only detect a signal but not ascertain directivity. Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. Simulations showed that incorporating bearing detections provide a substantial improvement in false alarm rates (6 to 12 times depending on number of units, placement and signal to noise conditions) for a small increase in the risk of missed detections inside of an exclusion zone (1%–3%). We show that the system can be used for monitoring exclusion zones and clearly highlight the value of including bearing estimation into exclusion zone monitoring plans while noting that placement and configuration of units should reflect anticipated ambient noise conditions.

17 WIND ENERGY↗