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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Marshall Space Flight Center Ground Systems Development and Integration

Ground Systems Development and Integration performs a variety of tasks in support of the Mission Operations Laboratory (MOL) and other Center and Agency projects. These tasks include various systems engineering processes such as performing system requirements development, system architecture design, integration, verification and validation, software development, and sustaining engineering of mission operations systems that has evolved the Huntsville Operations Support Center (HOSC) into a leader in remote operations for current and future NASA space projects. The group is also responsible for developing and managing telemetry and command configuration and calibration databases. Personnel are responsible for maintaining and enhancing their disciplinary skills in the areas of project management, software engineering, software development, software process improvement, telecommunications, networking, and systems management. Domain expertise in the ground systems area is also maintained and includes detailed proficiency in the areas of real-time telemetry systems, command systems, voice, video, data networks, and mission planning systems.

Wade, Gina↗
NASA NTRS1987

Intelligent robotic tracker

An intelligent tracker capable of robotic applications requiring guidance and control of platforms, robotic arms, and end effectors has been developed. This packaged system capable of supervised autonomous robotic functions is partitioned into a multiple processor/parallel processing configuration. The system currently interfaces to cameras but has the capability to also use three-dimensional inputs from scanning laser rangers. The inputs are fed into an image processing and tracking section where the camera inputs are conditioned for the multiple tracker algorithms. An executive section monitors the image processing and tracker outputs and performs all the control and decision processes. The present architecture of the system is presented with discussion of its evolutionary growth for space applications. An autonomous rendezvous demonstration of this system was performed last year. More realistic demonstrations in planning are discussed.

Otaguro, W. S.↗
DOE OSTI2022

An in-situ conductometric apparatus for physicochemical characterization of solutions and in-line monitoring of separation processes at elevated temperatures and pressures

Specific conductance and frequency-dependent resistance (impedance) data are widely utilized for understanding the physicochemical characteristics of aqueous and non-aqueous fluids and for evaluating the performance of chemical processes. However, the implementation of such an in-situ probe in high-temperature and high-pressure environments is not trivial. This work provides a description of both the hardware and software associated with implementing a parallel-type in-situ electrochemical sensor. The sensor can be used for in-line monitoring of thermal desalination processes and for impedance measurements in fluids at high temperature and pressure. Further, a comparison between the experimental measurements on the specific conductance in aqueous sodium chloride solutions and the conductance model demonstrate that the methodology yields reasonable agreement with both the model and literature data. A combination of hardware components, a software-based correction for experimental artifacts, and computational fluid dynamics (CFD) calculations used in this work provide a sound basis for implementing such in-situ electrochemical sensors to measure frequency-dependent resistance spectra.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Efficient Anomaly Detection Driven By Different Machine Learning Architectures And Models

The rapid growth and ubiquitous adoption of the internet and cyber-physical systems (CPS) have fundamentally transformed modern communication, work, and human-system interactions. While networks now form the backbone of critical digital ecosystems, enabling seamless data transmission across diverse, interconnected systems, this increased connectivity also expands the attack surface, making real-time detection of network intrusions and anomalies a pressing challenge. Detecting unusual activities within network infrastructure requires advanced data traffic analysis to differentiate between legitimate and malicious interactions. Traditional approaches to network anomaly detectionâ??such as rule-based and signature-based systemsâ??often depend on predefined patterns to identify known anomalies, limiting their effectiveness against emerging, stealthy, or previously unseen threats. These conventional methods suffer from high false alarm rates and fail to adapt to the ever-evolving nature of network traffic, particularly in large-scale, decentralized environments where data volume, velocity, and variety are constantly increasing. This dissertation presents artificial intelligence (AI)-driven approaches to anomaly detection that leverage graphics processing unit (GPU)-enabled high-performance computing (HPC) platforms for processing massive network traffic data and monitoring the components of cyber-physical systems (CPS) for potentially hazardous conditions. The research advances several key contributions: (1) Designing efficient machine learning techniques for CPS condition monitoring and anomaly detection; (2) enabling federated learning (FL) frameworks that enable distributed detection while preserving data privacy and system resilience; (3) exploring graph-based methodologies combining graph neural networks (GNN) and graph machine learning (ML) approaches for the Internet of Things (IoT) and automotive network security, and (4) performing distributed edge computing optimizations that integrate FL with scalable technologies for reduced communication overhead. Through extensive experiments, these methodologies demonstrate that complex anomaly detection and condition monitoring tasks can be achieved while balancing computational efficiency and detection accuracy through fine-grained network information processing. The frameworks developed in this research establish a robust foundation for network anomaly detection, providing scalable, adaptive, and privacy-preserving solutions for safeguarding CPS and IoT networks in an increasingly interconnected digital landscape. The practical implications of these research findings are significant, as they can inform the development of next-generation network security systems and contribute to the protection of critical infrastructure against sophisticated cyber attacks.

Marfo, William↗
DOE OSTI2022

Unveiling the influence of selective-area-regrowth interfaces on local electronic properties of GaN p-n junctions for efficient power devices

Here, we report correlated nanoscale mapping of the structure, composition, and properties of regrown GaN p-n junctions to identify how etching and non-planar regrowth processes limit diode performance via the introduction of unintentional dopants and defect states. p-GaN was selectively regrown in n-GaN trenches with SiO 2 masks of variable mask-to-trench-width ratio. Dilute Al layers were periodically introduced during regrowth as markers of the growth interface. Correlated nanoscale mapping of doping, conductivity, and dopant complexes was achieved with atom probe tomography (APT), scanning spreading resistance microscopy (SSRM), and cathodoluminescence (CL) spectroscopy, respectively. The Al marker layers, detected by APT, enabled reconstruction of the faceted growth interface and correlation of the dopant concentration with position and time. The p-GaN growth rate is proportional to the mask-to-trench width ratio while the dopant incorporation rate is invariant. At trench edges, magnesium incorporation is suppressed, and oxygen incorporation enhanced, due to preferential incorporation on the semi-polar growth surface, leading to compensation and less abrupt p-n junctions; the SiO 2 mask is a source of oxygen. Residual etch damage below the regrowth interface induces n-type and p-type conductivity, creating leakage pathways. The non-uniform Mg incorporation is driven by crystal anisotropy and is thus inherent to non-planar regrowth, but can be mitigated by engineering the regrowth interface and process parameters. The unprecedented integration of spatially resolved mapping of dopants, impurities, conductivity, and carrier type is a powerful approach to discriminating distinct factors that limit the performance of regrown diodes, enabling the rational optimization of process and device design.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Nanotip Carpets as Antireflection Surfaces

Carpet-like random arrays of metal-coated silicon nanotips have been shown to be effective as antireflection surfaces. Now undergoing development for incorporation into Sun sensors that would provide guidance for robotic exploratory vehicles on Mars, nanotip carpets of this type could also have many uses on Earth as antireflection surfaces in instruments that handle or detect ultraviolet, visible, or infrared light. In the original Sun-sensor application, what is required is an array of 50-micron-diameter apertures on what is otherwise an opaque, minimally reflective surface, as needed to implement a miniature multiple-pinhole camera. The process for fabrication of an antireflection nanotip carpet for this application (see Figure 1) includes, and goes somewhat beyond, the process described in A New Process for Fabricating Random Silicon Nanotips (NPO-40123), NASA Tech Briefs, Vol. 28, No. 1 (November 2004), page 62. In the first step, which is not part of the previously reported process, photolithography is performed to deposit etch masks to define the 50-micron apertures on a silicon substrate. In the second step, which is part of the previously reported process, the non-masked silicon area between the apertures is subjected to reactive ion etching (RIE) under a special combination of conditions that results in the growth of fluorine-based compounds in randomly distributed formations, known in the art as "polymer RIE grass," that have dimensions of the order of microns. The polymer RIE grass formations serve as microscopic etch masks during the next step, in which deep reactive ion etching (DRIE) is performed. What remains after DRIE is the carpet of nano - tips, which are high-aspect-ratio peaks, the tips of which have radii of the order of nanometers. Next, the nanotip array is evaporatively coated with Cr/Au to enhance the absorption of light (more specifically, infrared light in the Sun-sensor application). The photoresist etch masks protecting the apertures are then removed by dipping the substrate into acetone. Finally, for the Sun-sensor application, the back surface of the substrate is coated with a 57-nm-thick layer of Cr for attenuation of sunlight.

Bae, Youngsam↗
DOE OSTI2023

Convoluted filtering for process cycle modeling

Principles of materials science and engineering, physics, mathematics, and information science are used to extract knowledge and insights from the process-structure–property-performance relationships hidden in materials data. The process-structure modeling can be accelerated without loss of interpretability, with artificial intelligence tools that mimic the salient features of the process and process-structure relations. In this work, a novel convoluted model-filtering technique was exploited to build and successfully train the Convoluted Filter (CoFi) artifacts for Fe-based alloy heat treatment cycles. The artifacts were pre-trained to filter out deep models that change the surrogate microstructure state after the heat treatment at ambient conditions. Direct representation of the thermal cycle features within knowledge Graph facilitated development of meaningful data models for microstructure evolution, which reduce overfitting to limited datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An AI-accelerated pathway for reproducible and stable halide perovskites

Halide perovskites (HPs) have remarkable optoelectronic properties, and in the last decade their photovoltaic power conversion efficiency and light-emitting diode efficiency have skyrocketed. Despite the surge in research on these burgeoning materials, two key challenges in the field remain: material irreproducibility and instability. Their behavior is especially dynamic in response to environmental stressors, due to complex interactions with the perovskite crystal lattice. Here, in this review, we survey the latest achievements in HP materials research accomplished with the assistance of artificial intelligence (AI), through the implementation of automated experimentation and machine learning (ML) data analysis. Automated synthesis and characterization tackle problems with material irreproducibility by systematically controlling parameters with very high precision, creating massive datasets, and allowing methodical comparisons from which unbiased conclusions can be drawn. AI can reveal otherwise unnoticed trends, inform future experiments with the highest potential information gain, and forecast future performance. The review concludes with a forward viewpoint of how human-assisted closed-loop laboratories and shared databases allow halide perovskite materials’ processing, properties, and performance to be potentially optimized with AI, accelerating the development of highly reproducible and stable optoelectronic devices.

Hering, Abigail R. [Univ. of California, Davis, CA↗
DOE OSTI2018

Investigation of GaN-on-GaN vertical p - n diode with regrown p -GaN by metalorganic chemical vapor deposition

Here, to mimic selective-area doping, p -GaN was regrown on an etched GaN surface on GaN substrates by metalorganic chemical vapor deposition. Vertical GaN-on-GaN p - n diodes were fabricated to investigate the effects of the etch-then-regrowth process on device performance. The crystal quality of the sample after each epitaxial step was characterized by X-ray diffraction, where the etch-then-regrowth process led to a very slight increase in edge dislocations. A regrowth interfacial layer was clearly shown by transmission electron microscopy. Strong electroluminescence was observed with three emission peaks at 2.2 eV, 2.8 eV and 3.0 eV, respectively. The forward current density increased slightly with the increasing temperature, while the reverse current density was almost temperature independent indicating tunneling as the reverse transport mechanism. This result is very similar to the reported Zener tunnel diode comprising a high doping profile at the junction interface. High levels of silicon and oxygen concentrations were observed at the regrowth interface with a distribution width of ~100 nm. This work provides valuable information of p -GaN regrowth and regrown GaN p - n diodes, which can serve as an important reference for developing selective doping for advanced GaN power electronics for high voltage and high power applications.

42 ENGINEERING↗
DOE OSTI2021

Development of Low-cost Magnetocaloric Materials - CRADA 446

The overall goal of the project is to develop a faster heat-treatment process to produce low-cost high-performance magnetocaloric materials (MCM) for magnetic refrigeration technology. This research is in support of DOE-Fuel Cell Technology Office’s efforts to develop energy-efficient magnetic refrigeration technology for hydrogen liquefaction. Magnetic refrigeration offers a lower-cost and more energy-efficient alternative to traditional compression-based refrigeration technologies for liquefaction of gaseous hydrogen. Thus, PNNL is working with its industrial partner who is engaged in discovery, development and commercialization of low-cost high-performance MCM for use in magnetic refrigeration systems. Currently used MCM are typically a mixture of rare-earth and other elements. These are made in small batches and often need to be annealed for long durations, ranging from days to weeks, to obtain a good performance. Such extremely long heat-treatments add to the overall cost and increase the lead time to market of the commercial product. Therefore, this project will use recently developed innovative heat-treatment techniques at PNNL to shorten the annealing times and enhance the performance and lower the processing cost of MCM.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sorbent Based Post-Combustion CO 2 Slipstream Testing

TDA Research, Inc. has developed a low-cost sorbent (alkalized alumina) based technology for post-combustion CO 2 capture. The sorbent runs in an isothermal process for adsorption and regeneration. Neither temperature swing nor pressure swing is needed. TDA designed a system which operated 10 fixed beds to simulate a moving bed process. The flow pattern was optimized to minimize the steam usage for regeneration. An excellent sorbent (Batch 1) was also developed with collaboration with our partner. The sorbent degraded after long term operation. We developed a reprocessing procedure, which can be conducted in situ, to restore the sorbent capture capacity as the fresh sorbent after running for about 1250 hours. The reprocessing extended the sorbent longevity significantly. TDA designed a pilot unit (40’ x 32’ x 11.5’), processing flue gas equivalent to 0.5 MW of power generation. It had 10 beds and each bed could hold 1.75 m 3 of sorbent. We worked with Springs Fabrication, Inc. to complete the construction of the pilot unit. It was then shipped and installed at NCCC. The pilot unit was kept running in 24-hour mode when the flue gas and steam were available. It could run automatically without operator on site. Parametric and long-term (2 months) tests were carried out successfully. The results showed that TDA’s process can achieve 90% capture and 95% CO 2 purity for both coal and NG flue gases. For coal flue gas, the system reached performance target when processing up to 0.62 MW flue gas, 24% higher than the design capacity. Thus, capital cost could be saved on the reactors and sorbent. The strip air flow was designed to be 0.25 of that of the flue gas. The test data showed the strip/flue ratio can be reduced to as little as 0.18, which saves the power consumption for the strip air blower. The pressure drop was found to be lower than what the empirical equation calculated. The sorbent still had 91.7% of original capacity after 3-month test. With the data from the pilot test, we updated the TEA. For a 550-MW e supercritical coal fired power plant with CO 2 capture, the capture cost for TDA’s process is $34.9/tonne CO 2 captured, which meets DOE’s goal of $40/tonne and is 17.1% less than the DOE baseline Case 12. Therefore, TDA’s process has a good potential for commercialization.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1980

Design of a massively parallel processor

The massively parallel processor (MPP) system is designed to process satellite imagery at high rates. A large number (16,384) of processing elements (PE's) are configured in a square array. For optimum performance on operands of arbitrary length, processing is performed in a bit-serial manner. On 8-bit integer data, addition can occur at 6553 million operations per second (MOPS) and multiplication at 1861 MOPS. On 32-bit floating-point data, addition can occur at 430 MOPS and multiplication at 216 MOPS.

Batcher, K. E.↗
NASA NTRS1989

Parallel asynchronous systems and image processing algorithms

A new hardware approach to implementation of image processing algorithms is described. The approach is based on silicon devices which would permit an independent analog processing channel to be dedicated to evey pixel. A laminar architecture consisting of a stack of planar arrays of the device would form a two-dimensional array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuronlike asynchronous pulse coded form through the laminar processor. Such systems would integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The research is aimed at implementation of algorithms, such as the intensity dependent summation algorithm and pyramid processing structures, which are motivated by the operation of natural vision systems. Implementation of natural vision algorithms would benefit from the use of neuronlike information coding and the laminar, 2-D parallel, vision system type architecture. Besides providing a neural network framework for implementation of natural vision algorithms, a 2-D parallel approach could eliminate the serial bottleneck of conventional processing systems. Conversion to serial format would occur only after raw intensity data has been substantially processed. An interesting challenge arises from the fact that the mathematical formulation of natural vision algorithms does not specify the means of implementation, so that hardware implementation poses intriguing questions involving vision science.

Coon, D. D.↗
NASA NTRS1993

LOX/hydrocarbon rocket engine analytical design methodology development and validation. Volume 1: Executive summary and technical narrative

During the past three decades, an enormous amount of resources were expended in the design and development of Liquid Oxygen/Hydrocarbon and Hydrogen (LOX/HC and LOX/H2) rocket engines. A significant portion of these resources were used to develop and demonstrate the performance and combustion stability for each new engine. During these efforts, many analytical and empirical models were developed that characterize design parameters and combustion processes that influence performance and stability. Many of these models are suitable as design tools, but they have not been assembled into an industry-wide usable analytical design methodology. The objective of this program was to assemble existing performance and combustion stability models into a usable methodology capable of producing high performing and stable LOX/hydrocarbon and LOX/hydrogen propellant booster engines.

Pieper, Jerry L.↗
NASA NTRS1996

Investigation of ion-beam machining methods for replicated x-ray optics

The final figuring step in the fabrication of an optical component involves imparting a specified contour onto the surface. This can be expensive and time consuming step. The recent development of ion beam figuring provides a method for performing the figuring process with advantages over standard mechanical methods. Ion figuring has proven effective in figuring large optical components. The process of ion beam figuring removes material by transferring kinetic energy from impinging neutral particles. The process utilizes a Kaufman type ion source, where a plasma is generated in a discharge chamber by controlled electric potentials. Charged grids extract and accelerate ions from the chamber. The accelerated ions form a directional beam. A neutralizer outside the accelerator grids supplies electrons to the positive ion beam. It is necessary to neutralize the beam to prevent charging workpieces and to avoid bending the beam with extraneous electro-magnetic fields. When the directed beam strikes the workpiece, material sputters in a predicable manner. The amount and distribution of material sputtered is a function of the energy of the beam, material of the component, distance from the workpiece, and angle of incidence of the beam. The figuring method described here assumes a constant beam removal, so that the process can be represented by a convolution operation. A fixed beam energy maintains a constant sputtering rate. This temporally and spatially stable beam is held perpendicular to the workpiece at a fixed distance. For non-constant removal, corrections would be required to model the process as a convolution operation. Specific figures (contours) are achieved by rastering the beam over the workpiece at varying velocities. A unique deconvolution is performed, using series-derivative solution developed for the system, to determine these velocities.

Drueding, Thomas W.↗
NASA NTRS1998

Integrated Advanced Microwave Sounding Unit-A (AMSU-A). Performance Verification Reports: Final Comprehensive Performance Test Report, P/N: 1356006-1, S.N: 202/A2

This is the Performance Verification Report. the process specification establishes the requirements for the comprehensive performance test (CPT) and limited performance test (LPT) of the earth observing system advanced microwave sounding unit-A2 (EOS/AMSU-A2), referred to as the unit. The unit is defined on drawing 1356006.

Platt, R.↗
NASA NTRS2004

Active Flow Control on a Boundary-Layer-Ingesting Inlet

Boundary layer ingestion (BLI) is explored as means to improve overall system performance for Blended Wing Body configuration. The benefits of BLI for vehicle system performance benefit are assessed with a process derived from first principles suitable for highly-integrated propulsion systems. This performance evaluation process provides framework within which to assess the benefits of an integrated BLI inlet and lays the groundwork for higher-fidelity systems studies. The results of the system study show that BLI provides a significant improvement in vehicle performance if the inlet distortion can be controlled, thus encouraging the pursuit of active flow control (AFC) as a BLI enabling technology. The effectiveness of active flow control in reducing engine inlet distortion was assessed using a 6% scale model of a 30% BLI offset, diffusing inlet. The experiment was conducted in the NASA Langley Basic Aerodynamics Research Tunnel with a model inlet designed specifically for this type of testing. High mass flow pulsing actuators provided the active flow control. Measurements were made of the onset boundary layer, the duct surface static pressures, and the mass flow through the duct and the actuators. The distortion was determined by 120 total pressure measurements located at the aerodynamic interface plane. The test matrix was limited to a maximum freestream Mach number of 0.15 with scaled mass flows through the inlet for that condition. The data show that the pulsed actuation can reduce distortion from 29% to 4.6% as measured by the circumferential distortion descriptor DC60 using less than 1% of inlet mass flow. Closed loop control of the actuation was also demonstrated using a sidewall surface static pressure as the response sensor.

Gorton, Susan Althoff↗