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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Smart Sensor Demonstration Payload

Sensors are a critical element to any monitoring, control, and evaluation processes such as those needed to support ground based testing for rocket engine test. Sensor applications involve tens to thousands of sensors; their reliable performance is critical to achieving overall system goals. Many figures of merit are used to describe and evaluate sensor characteristics; for example, sensitivity and linearity. In addition, sensor selection must satisfy many trade-offs among system engineering (SE) requirements to best integrate sensors into complex systems [1]. These SE trades include the familiar constraints of power, signal conditioning, cabling, reliability, and mass, and now include considerations such as spectrum allocation and interference for wireless sensors. Our group at NASA s John C. Stennis Space Center (SSC) works in the broad area of integrated systems health management (ISHM). Core ISHM technologies include smart and intelligent sensors, anomaly detection, root cause analysis, prognosis, and interfaces to operators and other system elements [2]. Sensor technologies are the base fabric that feed data and health information to higher layers. Cost-effective operation of the complement of test stands benefits from technologies and methodologies that contribute to reductions in labor costs, improvements in efficiency, reductions in turn-around times, improved reliability, and other measures. ISHM is an active area of development at SSC because it offers the potential to achieve many of those operational goals [3-5].

Schmalzel, John↗
DOE OSTI2024

Utilizing highly scattered light for intelligence through aerosols

A method for modeling light transport through a scattering medium prior to being incident on a detector and a corresponding system is disclosed. The method determines the effects of scattering and absorption caused by particles as a function of the density, size, and refractive index of the particles, as well as the wavelength of the light source. Based on the determined scattering and absorption coefficients, the signal incident on the detector may be calculated. The calculation may also be inverted such that based upon the detected signal, an object may be detected, and its location in the scattering medium may be estimated.

Bentz, Brian Z.↗
DOE OSTI2025

Intelligent Triggers for Rare Event Detection in Liquid Argon Detectors

Next-generation neutrino experiments like SBND and DUNE rely on Liquid Argon Time Projection Chambers (LArTPCs), which produce exceptionally detailed data at high volume. Capturing rare or unexpected events in real-time is a major challenge. Our project explores the use of machine learning, specifically autoencoder-based anomaly detection, to identify unusual activity directly from raw detector signals. Inspired by successes at the CMS experiment, we demonstrate that such methods can be adapted to LArTPCs and show promising results in both simulated studies and early steps toward real-time hardware deployment. This approach could open new avenues for detecting signals from physics beyond the Standard Model.

Chung, Seokju [Columbia U. (main)]↗
NASA NTRS1983

The Berkeley parasitic SETI program

Parasitic programs for the Search for Extraterrestrial Intelligence (SETI), carried out concurrently with conventional radio astronomical observing programs, can be an attractive and cost-effective means of exploring the large multidimensional search space intrinsic to this effort. A microprocessor-based automated SETI acquisition system is described which searches for, and records, spectra of narrowband signals in the IF band of an observatory receiver. Data taken with this system over 35 days at the Hat Creek Radio Observatory at 1612 MHz are discussed. Out of approximately 100,000 spectra processed during this period, 4000 were identified by the system as containing narrowband signals and were recorded. Subsequent analysis indicates that over 3900 of these are due to local RF contamination. The remainder are undergoing further investigation.

Bowyer, S.↗
NASA NTRS1987

Hierarchical control of intelligent machines applied to space station telerobots

A hierarchical architecture is described which supports space station telerobots in a variety of modes. The system is divided into three hierarchies: task decomposition, world model, and sensory processing. Goals at each level of the task decomposition hierarchy are divided both spatially and temporally into simpler commands for the next lower level. This decomposition is repeated until, at the lowest level, the drive signals to the robot actuators are generated. To accomplish its goals, task decomposition modules must often use information stored in the world model. The purpose of the sensory system is to update the world model as rapidly as possible to keep the model in registration with the physical world. The architecture of the entire control system hierarchy and how it can be applied to space telerobot applications are discussed.

Albus, J. S.↗
NASA NTRS1989

Intelligent Network Management and Functional Cerebellum Synthesis

Transdisciplinary modeling of the cerebellum across histology, physiology, and network engineering provides preliminary results at three organization levels: input/output links to central nervous system networks; links between the six neuron populations in the cerebellum; and computation among the neurons of the populations. Older models probably underestimated the importance and role of climbing fiber input which seems to supply write as well as read signals, not just to Purkinje but also to basket and stellate neurons. The well-known mossy fiber-granule cell-Golgi cell system should also respond to inputs originating from climbing fibers. Corticonuclear microcomplexing might be aided by stellate and basket computation and associate processing. Technological and scientific implications of the proposed cerebellum model are discussed.

Loebner, Egon E.↗
NASA NTRS1996

Spectral imaging applications: Remote sensing, environmental monitoring, medicine, military operations, factory automation and manufacturing

This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.

National Defense↗
NASA NTRS2007

Smart Sensor Node Development, Testing and Implementation for Rocket Propulsion Systems

Successful design and implementation of an Integrated System Health Management (ISHM) approach for rocket propulsion systems requires the capability improve the reliability of complex systems by detecting and diagnosing problems. One of the critical elements in the ISHM is an intelligent sensor node for data acquisition that meets specific requirements for rocket motor testing including accuracy, sample rate and size/weight. Traditional data acquisition systems are calibrated in a controlled environment and guaranteed to perform bounded by their tested conditions. In a real world ISHM system, the data acquisition and signal conditioning needs to function in an uncontrolled environment. Development and testing of this sensor node focuses on a design with the ability to self check in order to extend calibration times, report internal faults and drifts and notify the overall system when the data acquisition is not performing as it should. All of this will be designed within a system that is flexible, requiring little re-design to be deployed on a wide variety of systems. Progress in this design and initial testing of prototype units will be reported.

Mengers, Timothy R.↗
NASA NTRS1989

Interface For Fault-Tolerant Control System

Interface unit and controller emulator developed for research on electronic helicopter-flight-control systems equipped with artificial intelligence. Interface unit interrupt-driven system designed to link microprocessor-based, quadruply-redundant, asynchronous, ultra-reliable, fault-tolerant control system (controller) with electronic servocontrol unit that controls set of hydraulic actuators. Receives digital feedforward messages from, and transmits digital feedback messages to, controller through differential signal lines or fiber-optic cables (thus far only differential signal lines have been used). Analog signals transmitted to and from servocontrol unit via coaxial cables.

Shaver, Charles↗
NASA NTRS2012

Intelligent Data Visualization for Cross-Checking Spacecraft System Diagnosis

Any reasoning system is fallible, so crew members and flight controllers must be able to cross-check automated diagnoses of spacecraft or habitat problems by considering alternate diagnoses and analyzing related evidence. Cross-checking improves diagnostic accuracy because people can apply information processing heuristics, pattern recognition techniques, and reasoning methods that the automated diagnostic system may not possess. Over time, cross-checking also enables crew members to become comfortable with how the diagnostic reasoning system performs, so the system can earn the crew s trust. We developed intelligent data visualization software that helps users cross-check automated diagnoses of system faults more effectively. The user interface displays scrollable arrays of timelines and time-series graphs, which are tightly integrated with an interactive, color-coded system schematic to show important spatial-temporal data patterns. Signal processing and rule-based diagnostic reasoning automatically identify alternate hypotheses and data patterns that support or rebut the original and alternate diagnoses. A color-coded matrix display summarizes the supporting or rebutting evidence for each diagnosis, and a drill-down capability enables crew members to quickly view graphs and timelines of the underlying data. This system demonstrates that modest amounts of diagnostic reasoning, combined with interactive, information-dense data visualizations, can accelerate system diagnosis and cross-checking.

Ong, James C.↗
NASA NTRS1972

Quantization noise in digital speech

The amount of quantization noise generated in a digital-to-analog converter is dependent on the number of bits or quantization levels used to digitize the analog signal in the analog-to-digital converter. The minimum number of quantization levels and the minimum sample rate were derived for a digital voice channel. A sample rate of 6000 samples per second and lowpass filters with a 3 db cutoff of 2400 Hz are required for 100 percent sentence intelligibility. Consonant sounds are the first speech components to be degraded by quantization noise. A compression amplifier can be used to increase the weighting of the consonant sound amplitudes in the analog-to-digital converter. An expansion network must be installed at the output of the digital-to-analog converter to restore the original weighting of the consonant sounds. This technique results in 100 percent sentence intelligibility for a sample rate of 5000 samples per second, eight quantization levels, and lowpass filters with a 3 db cutoff of 2000 Hz.

Schmidt, O. L.↗
DOE OSTI2026

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
NASA NTRS1980

A bimodal search strategy for SETI

The search strategy and resultant observational plan which was developed to carry out a comprehensive Search for Extraterrestrial Intelligence (SETI) over that portion of the electromagnetic spectrum known as the terrestrial microwave window is described. The limiting sensitivity achieved was parameterized and calculated for Deep Space Network antennas as well as several radio astronomy observatories. A brief description of the instrumentation to be employed in the search and the classes of signals to be looked for is given. One observational goal is to survey the entire sky over a wide range of frequency to a relatively constant flux level. This survey ensures that all potential life sites are observed to some limiting equivalent isotropic radiated power depending upon their distance. A second goal is to survey a set of potential transmission sites selected a priori to be especially promising, achieving very high sensitivity over a smaller range of frequency.

Gulkis, S.↗
NASA NTRS1992

Reflections - The Microwave Observing Project is prologue

NASA's Microwave Observing Project (MOP) for searching for extraterrestrial intelligence is reviewed to demonstrate its significance and need for international support. Attention is given to the analytical aspects of the probability of successful detection based on the number of stars searched. Array sizes for MOP are considered to determine the number of stars that could potentially be covered, and it is shown that signals can only be detected within 100 light years of earth. Design issues are discussed in the light of the need for balanced equipment that equally treats signal transmission and reception. The cost of the optimal array and worldwide interest in SETI activities are used as the basis for an argument that the MOP project should be multinational.

Oliver, Bernard M.↗
NASA NTRS2006

Semiautonomous Avionics-and-Sensors System for a UAV

Unmanned Aerial Vehicles (UAVs) autonomous or remotely controlled pilotless aircraft have been recently thrust into the spotlight for military applications, for homeland security, and as test beds for research. In addition to these functions, there are many space applications in which lightweight, inexpensive, small UAVS can be used e.g., to determine the chemical composition and other qualities of the atmospheres of remote planets. Moreover, on Earth, such UAVs can be used to obtain information about weather in various regions; in particular, they can be used to analyze wide-band acoustic signals to aid in determining the complex dynamics of movement of hurricanes. The Advanced Sensors and Electronics group at Langley Research Center has developed an inexpensive, small, integrated avionics-and-sensors system to be installed in a UAV that serves two purposes. The first purpose is to provide flight data to an AI (Artificial Intelligence) controller as part of an autonomous flight-control system. The second purpose is to store data from a subsystem of distributed MEMS (microelectromechanical systems) sensors. Examples of these MEMS sensors include humidity, temperature, and acoustic sensors, plus chemical sensors for detecting various vapors and other gases in the environment. The critical sensors used for flight control are a differential- pressure sensor that is part of an apparatus for determining airspeed, an absolute-pressure sensor for determining altitude, three orthogonal accelerometers for determining tilt and acceleration, and three orthogonal angular-rate detectors (gyroscopes). By using these eight sensors, it is possible to determine the orientation, height, speed, and rates of roll, pitch, and yaw of the UAV. This avionics-and-sensors system is shown in the figure. During the last few years, there has been rapid growth and advancement in the technological disciplines of MEMS, of onboard artificial-intelligence systems, and of smaller, faster, and smarter wireless telemetry systems. The major attraction of MEMS lies in orders-of-magnitude reductions of power requirements relative to traditional electronic components that perform equivalent functions. In addition, the compactness of MEMS, relative to functionally equivalent traditional electronics systems, makes MEMS attractive for UAV applications. Recent advances in MEMS have made it possible to produce pressure, acceleration, humidity, and temperature sensors having masses in subgram range and possessing sensitivities and accuracies comparable to those of larger devices.

Shams, Qamar↗
NASA NTRS2002

Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification

When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle. The system uses only gyro signals to detect and identify hard, abrupt, single and multiple jet on- and off-failures. Faults are detected within one second and identified within one to five accords,

Wilson, Edward↗
NASA NTRS2005

Small Vocabulary Recognition Using Surface Electromyography in an Acoustically Harsh Environment

This paper presents results of electromyographic-based (EMG-based) speech recognition on a small vocabulary of 15 English words. The work was motivated in part by a desire to mitigate the effects of high acoustic noise on speech intelligibility in communication systems used by first responders. Both an off-line and a real-time system were constructed. Data were collected from a single male subject wearing a fireghter's self-contained breathing apparatus. A single channel of EMG data was used, collected via surface sensors at a rate of 104 samples/s. The signal processing core consisted of an activity detector, a feature extractor, and a neural network classifier. In the off-line phase, 150 examples of each word were collected from the subject. Generalization testing, conducted using bootstrapping, produced an overall average correct classification rate on the 15 words of 74%, with a 95% confidence interval of [71%, 77%]. Once the classifier was trained, the subject used the real-time system to communicate and to control a robotic device. The real-time system was tested with the subject exposed to an ambient noise level of approximately 95 decibels.

Betts, Bradley J.↗
NASA NTRS1996

The NIST Real-Time Control System (RCS): A Reference Model Architecture for Computational Intelligence

The Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades defines a reference model architecture for design and analysis of complex intelligent control systems. The RCS architecture consists of a hierarchically layered set of functional processing modules connected by a network of communication pathways. The primary distinguishing feature of the layers is the bandwidth of the control loops. The characteristic bandwidth of each level is determined by the spatial and temporal integration window of filters, the temporal frequency of signals and events, the spatial frequency of patterns, and the planning horizon and granularity of the planners that operate at each level. At each level, tasks are decomposed into sequential subtasks, to be performed by cooperating sets of subordinate agents. At each level, signals from sensors are filtered and correlated with spatial and temporal features that are relevant to the control function being implemented at that level.

Albus, James S.↗