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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Hands-Free Transcranial Color Doppler Probe

Current transcranial color Doppler (TCD) transducer probes are bulky and difficult to move in tiny increments to search and optimize TCD signals. This invention provides miniature motions of a TCD transducer probe to optimize TCD signals. The mechanical probe uses a spherical bearing in guiding and locating the tilting crystal face. The lateral motion of the crystal face as it tilts across the full range of motion was achieved by minimizing the distance between the pivot location and the crystal face. The smallest commonly available metal spherical bearing was used with an outer diameter of 12 mm, a 3-mm tall retaining ring, and 5-mm overall height. Small geared motors were used that would provide sufficient power in a very compact package. After confirming the validity of the basic positioning concept, optimization design loops were completed to yield the final design. A parallel motor configuration was used to minimize the amount of space wasted inside the probe case while minimizing the overall case dimensions. The distance from the front edge of the crystal to the edge of the case was also minimized to allow positioning of the probe very close to the ear on the temporal lobe. The mechanical probe is able to achieve a +/-20deg tip and tilt with smooth repeatable action in a very compact package. The enclosed probe is about 7 cm long, 4 cm wide, and 1.8 cm tall. The device is compact, hands-free, and can be adjusted via an innovative touchscreen. Positioning of the probe to the head is performed via conventional transducer gels and pillows. This device is amendable to having advanced software, which could intelligently focus and optimize the TCD signal.

Chin, Robert↗
NASA NTRS1993

Evolution of a high-performance storage system based on magnetic tape instrumentation recorders

In order to provide transparent access to data in network computing environments, high performance storage systems are getting smarter as well as faster. Magnetic tape instrumentation recorders contain an increasing amount of intelligence in the form of software and firmware that manages the processes of capturing input signals and data, putting them on media and then reproducing or playing them back. Such intelligence makes them better recorders, ideally suited for applications requiring the high-speed capture and playback of large streams of signals or data. In order to make recorders better storage systems, intelligence is also being added to provide appropriate computer and network interfaces along with services that enable them to interoperate with host computers or network client and server entities. Thus, recorders are evolving into high-performance storage systems that become an integral part of a shared information system. Data tape has embarked on a program with the Caltech sponsored Concurrent Supercomputer Consortium to develop a smart mass storage system. Working within the framework of the emerging IEEE Mass Storage System Reference Model, a high-performance storage system that works with the STX File Server to provide storage services for the Intel Touchstone Delta Supercomputer is being built. Our objective is to provide the required high storage capacity and transfer rate to support grand challenge applications, such as global climate modeling.

Peters, Bruce↗
NASA NTRS1995

Improved Noise-Power Estimators Based On Order Statistics

Technique based on order statistics enables design of improved noise-power estimators. In original intended application, noise-power estimators part of microwave-signal-processing system of Search for Extraterrestrial Intelligence project. Involves limiting dynamic range of value to be estimated; making it possible to achieve performance of order-statistical estimator with simple algorithms and equipment and with only one pass over input data. Technique also applicable to other signal-detection systems and to image-detection systems required to exhibit constant false-alarm rates.

Zimmerman, George A.↗
NASA NTRS1972

Asynchronous sampling of speech with some vocoder experimental results

The method of asynchronously sampling speech is based upon the derivatives of the acoustical speech signal. The following results are apparent from experiments to date: (1) It is possible to represent speech by a string of pulses of uniform amplitude, where the only information contained in the string is the spacing of the pulses in time; (2) the string of pulses may be produced in a simple analog manner; (3) the first derivative of the original speech waveform is the most important for the encoding process; (4) the resulting pulse train can be utilized to control an acoustical signal production system to regenerate the intelligence of the original speech.

Babcock, M. L.↗
NASA NTRS1976

System for imposing directional stability on a rocket-propelled vehicle

An improved system for use in imposing directional stability on a rocket-propelled vehicle is described. The system includes a pivotally supported engine-mounting platform, a gimbal ring mounted on the platform and adapted to pivotally support a rocket engine and an hydraulic actuator connected to the platform for imparting selected pivotal motion. An accelerometer and a signal comparator circuit for providing error intelligence indicative of aberration in vehicle acceleration is included along with an actuator control circuit connected with the actuator and responsive to error intelligence for imparting pivotal motion to the platform. Relocation of the engine's thrust vector is thus achieved for imparting directional stability to the vehicle.

Perkins, H.↗
NASA NTRS2001

Virtual Instrumentation for a Fiber-Optics-Based Artificial Nerve

A LabView-based computer interface for fiber-optic artificial nerves has been devised as a Masters thesis project. This project involves the use of outputs from wavelength multiplexed optical fiber sensors (artificial nerves), which are capable of producing dense optical data outputs for physical measurements. The potential advantages of using optical fiber sensors for sensory function restoration is the fact that well defined WDM-modulated signals can be transmitted to and from the sensing region allowing networked units to replace low-level nerve functions for persons desirous of "intelligent artificial limbs." Various FO sensors can be designed with high sensitivity and the ability to be interfaced with a wide range of devices including miniature shielded electrical conversion units. Our Virtual Instrument (VI) interface software package was developed using LabView's "Laboratory Virtual Instrument Engineering Workbench" package. The virtual instrument has been configured to arrange and encode the data to develop an intelligent response in the form of encoded digitized signal outputs. The architectural layout of our nervous system is such that different touch stimuli from different artificial fiber-optic nerve points correspond to gratings of a distinct resonant wavelength and physical location along the optical fiber. Thus, when an automated, tunable diode laser sends scans, the wavelength spectrum of the artificial nerve, it triggers responses that are encoded with different touch stimuli by way wavelength shifts in the reflected Bragg resonances. The reflected light is detected and a resulting analog signal is fed into ADC1 board and DAQ card. Finally, the software has been written such that the experimenter is able to set the response range during data acquisition.

Lyons, Donald R.↗
NASA NTRS2007

Miniature Intelligent Sensor Module

An electronic unit denoted the Miniature Intelligent Sensor Module performs sensor-signal-conditioning functions and local processing of sensor data. The unit includes four channels of analog input/output circuitry, a processor, volatile and nonvolatile memory, and two Ethernet communication ports, all housed in a weathertight enclosure. The unit accepts AC or DC power. The analog inputs provide programmable gain, offset, and filtering as well as shunt calibration and auto-zeroing. Analog outputs include sine, square, and triangular waves having programmable frequencies and amplitudes, as well as programmable amplitude DC. One innovative aspect of the design of this unit is the integration of a relatively powerful processor and large amount of memory along with the sensor-signalconditioning circuitry so that sophisticated computer programs can be used to acquire and analyze sensor data and estimate and track the health of the overall sensor-data-acquisition system of which the unit is a part. The unit includes calibration, zeroing, and signalfeedback circuitry to facilitate health monitoring. The processor is also integrated with programmable logic circuitry in such a manner as to simplify and enhance acquisition of data and generation of analog outputs. A notable unique feature of the unit is a cold-junction compensation circuit in the back shell of a sensor connector. This circuit makes it possible to use Ktype thermocouples without compromising a housing seal. Replicas of this unit may prove useful in industrial and manufacturing settings - especially in such large outdoor facilities as refineries. Two features can be expected to simplify installation: the weathertight housings should make it possible to mount the units near sensors, and the Ethernet communication capability of the units should facilitate establishment of communication connections for the units.

Beech, Russell S.↗
DOE OSTI2026

Using Explainable Artificial Intelligence to Predict Perovskite Solar Cell Electrical Metastability from Operando Photoluminescence Images in Accelerated Stress Testing

Metal halide perovskite (MHP) solar cells exhibit a metastable response to bias governed by coupled ionic–electronic processes, complicating the conventional reciprocity relation between luminescence intensity and device open-circuit voltage (V oc ). This limits the use of luminescence as a diagnostic for device screening or accelerated stress testing, motivating new approaches that can interpret photoluminescence (PL) signals under nonequilibrium conditions. From the artificial intelligence perspective, we develop an explainable deep learning framework that integrates convolutional neural networks (CNN), long short-term memory (LSTM) layers, and an attention mechanism to learn spatiotemporal features from operando photoluminescence PL image sequences. The model achieves a mean absolute error of ±0.027 V in predicting open-circuit voltage transients and reduces extreme-tail errors by up to 78% compared to physics-based reciprocity calculations. Gradient-weighted Class Activation Mapping (Grad-CAM) provides interpretability by highlighting physically meaningful regions such as electrode edges and emergent defect features. From the engineering application perspective, this framework enables accurate, contactless prediction of device V oc and identification of degradation-relevant features during accelerated aging of perovskite solar cells. This approach demonstrates how explainable AI can enhance operando diagnostics and reliability analysis in photovoltaic devices under nonequilibrium conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms

Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
NASA NTRS1994

Multichannel spatial auditory display for speech communications

A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degrees azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degrees azimuth positions.

NASA Discipline Space Human Factors↗
NASA NTRS1994

Multichannel Spatial Auditory Display for Speed Communications

A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplifiedhead-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degree azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degree azimuth positions.

Begault, Durand R.↗
DOE OSTI2025

Broadband unidirectional visible imaging using wafer-scale nano-fabrication of multi-layer diffractive optical processors

We present a broadband and polarization-insensitive unidirectional imager that operates at the visible part of the spectrum, where image formation occurs in one direction, while in the opposite direction, it is blocked. This approach is enabled by deep learning-driven diffractive optical design with wafer-scale nano-fabrication using high-purity fused silica to ensure optical transparency and thermal stability. Our design achieves unidirectional imaging across three visible wavelengths (covering red, green, and blue parts of the spectrum), and we experimentally validated this broadband unidirectional imager by creating high-fidelity images in the forward direction and generating weak, distorted output patterns in the backward direction, in alignment with our numerical simulations. This work demonstrates wafer-scale production of diffractive optical processors, featuring 16 levels of nanoscale phase features distributed across two axially aligned diffractive layers for visible unidirectional imaging. This approach facilitates mass-scale production of ~0.5 billion nanoscale phase features per wafer, supporting high-throughput manufacturing of hundreds to thousands of multi-layer diffractive processors suitable for large apertures and parallel processing of multiple tasks. Beyond broadband unidirectional imaging in the visible spectrum, this study establishes a pathway for artificial-intelligence-enabled diffractive optics with versatile applications, signaling a new era in optical device functionality with industrial-level, massively scalable fabrication.

36 MATERIALS SCIENCE↗
NASA NTRS1978

A digital audio/video interleaving system

A method of interleaving an audio signal with its associated video signal for simultaneous transmission or recording, and the subsequent separation of the two signals, is described. Comparisons are made between the new audio signal interleaving system and the Skylab Pam audio/video interleaving system, pointing out improvements gained by using the digital audio/video interleaving system. It was found that the digital technique is the simplest, most effective and most reliable method for interleaving audio and/or other types of data into the video signal for the Shuttle Orbiter application. Details of the design of a multiplexer capable of accommodating two basic data channels, each consisting of a single 31.5-kb/s digital bit stream are given. An adaptive slope delta modulation system is introduced to digitize audio signals, producing a high immunity of work intelligibility to channel errors, primarily due to the robust nature of the delta-modulation algorithm.

Richards, R. W.↗
NASA NTRS2002

Multipoint sensing by intelligent collectives

Many remote sensing applications require that multiple sensors collect data simultaneously at spatially distributed locations and their information combined in order to characterize the phenomena of interest. Several basic classes of such multipoint measurement systems may be identified. For each, centralized methods exist for combining the raw data from the various sensors. However, recent advancements have given rise to small, integrated nodes comprised of one or more miniaturized sensors, processor, wireless communications capability and power supplies. Collections of these may be deployed and self-organized into intelligent sensor networks capable of performing cooperative signal processing locally, thereby providing substantial benefits.

multipoint measurement sensor networks↗
DOE OSTI2024

Safe Operations at Roadway Junctions: Intelligent Roadway Infrastructure as Functional Interlocking

Automated vehicle (AV) technology is quickly maturing, and the corresponding infrastructure systems that evaluate traffic and communicate to vehicles requires sophisticated sensing and perception technologies, referred to as intelligent roadway infrastructure (IRI), to complement emerging AV capabilities. IRI provides signals to vehicles, indicating right-of-way for vehicles and communicating to approaching AVs that no other vehicle is failing to yield. This capability, denoted as safety-affirmative signaling, provides a green light or a green arrow as appropriate and affirms through communication links to connected vehicles when it is safe to proceed. About 36% of collisions occur at intersections, with most occurring upon left turns (22.2%) or crossing over (12.6%), and only a small percentage (1.2%) while turning right at an intersection. Of all intersection crashes about half (52.5%) of those vehicles were traveling through a signalized intersection 2. Safety-affirmative signaling would guarantee safety of AV fleet vehicles, by providing the interlocking principle, a term from automated train control that only allows progression through a railway intersection after affirming no opportunity for a crash exists. IRI through safety-affirmative signaling would bring performance and safety to complex roadway intersections where AV transit fleet service is most needed, as well as safety benefits to traditional, non-automated vehicles and vulnerable road users. The implementation of IRI has functional, programmatic, and technical challenges. Research work performed at the National Renewable Energy Laboratory (NREL) in an integrative approach encapsulating these themes, and termed infrastructure perception and control (IPC) is motivated by improved performance (travel time), improved safety (reduced collisions), and improved energy efficiency (less fuel burned and minimized production of greenhouse gases). IPC is intended not only for roadway and intersection applications but also in extension to inform complementary buildings and grid systems to enable better co-management, as vehicles and their charging needs become increasingly integrated into the built environment. The NREL IPC project presents an open-source framework, architecture, and supporting technology to implement IRI, addressing critical issues such as fusion of data, reliability, standardization of data interfaces, and confidence of detection. The framework is informed by previous experience in U.S. Department of Defense research technology, specifically in the use of radar to detect, identify, and track aerial threats. These principles combined with multi-sensor fusion provides for a complete digital twin with known and measurable confidence and accuracy from which safety-affirmative signaling can be developed and deployed.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
NASA NTRS2015

Speech Intelligibility Advantages using an Acoustic Beamformer Display

A speech intelligibility test conforming to the Modified Rhyme Test of ANSI S3.2 "Method for Measuring the Intelligibility of Speech Over Communication Systems" was conducted using a prototype 12-channel acoustic beamformer system. The target speech material (signal) was identified against speech babble (noise), with calculated signal-noise ratios of 0, 5 and 10 dB. The signal was delivered at a fixed beam orientation of 135 deg (re 90 deg as the frontal direction of the array) and the noise at 135 deg (co-located) and 0 deg (separated). A significant improvement in intelligibility from 57% to 73% was found for spatial separation for the same signal-noise ratio (0 dB). Significant effects for improved intelligibility due to spatial separation were also found for higher signal-noise ratios (5 and 10 dB).

acoustic beamforming↗
NASA NTRS1993

Multi-channel spatial auditory display for speech communications

A spatial auditory display for multiple speech communications was developed at NASA-Ames Research Center. Input is spatialized by use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four letter call signs used by launch personnel at NASA, against diotic speech babble. Spatial positions at 30 deg azimuth increments were evaluated. The results from eight subjects showed a maximal intelligibility improvement of about 6 to 7 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.

Begault, Durand↗
NASA NTRS1991

Hidden Markov model analysis of force/torque information in telemanipulation

A model for the prediction and analysis of sensor information recorded during robotic performance of telemanipulation tasks is presented. The model uses the hidden Markov model to describe the task structure, the operator's or intelligent controller's goal structure, and the sensor signals. A methodology for constructing the model parameters based on engineering knowledge of the task is described. It is concluded that the model and its optimal state estimation algorithm, the Viterbi algorithm, are very succesful at the task of segmenting the data record into phases corresponding to subgoals of the task. The model provides a rich modeling structure within a statistical framework, which enables it to represent complex systems and be robust to real-world sensory signals.

Hannaford, Blake↗