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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 37 records · Page 2

Innovative laser-based methods for monitoring fuel retention in ITER

This paper addresses the challenge of tritium inventory management in ITER and future fusion reactors, highlighting the importance of accurate tritium measurement and its spatial distribution within the vacuum vessel. Given ITER’s operational constraints, especially the limit on tritium retention, precise measurement is essential for both safety and regulatory compliance. To tackle these questions, the paper presents the T-monitor diagnostic system developed by Forschungszentrum Jülich, which uses Laser-Induced Desorption (LID) in combination with Diagnostic Residual Gas Analysis (DRGA) to measure hydrogen isotope concentrations on the surface of divertor tiles. The system integrates a high-power laser, advanced optical components, and a Fast Scanning Mirror Unit (FSMU) for accurate laser spot positioning with rapid response. Designed to measure in situ tritium retention, the diagnostic provides high-resolution spatial mapping, vital for evaluating detritiation strategies. The laser heating process increases the divertor surface temperature to 1600 K within the laser spot, promoting hydrogen isotope desorption. Accurate measurements require the precise control of laser parameters, including pulse duration and spot size, with a target relative accuracy of 20%. The optical design includes both in-vessel and ex-vessel components, such as durable high-reflectivity mirrors made of gold and copper, selected not only for their infrared performance but also for their transmission of visible wavelengths for observation purposes. To protect optical components from contamination, a pneumatic shutter is used.

Hydrogen isotopes

Internal Electrostatic Discharge Monitor - IESDM

A document discusses an innovation designed to effectively monitor dielectric charging in spacecraft components to measure the potential for discharge in order to prevent damage from internal electrostatic discharge (IESD). High-energy electrons penetrate the structural materials and shielding of a spacecraft and then stop inside dielectrics and keep accumulating. Those deposited charges generate an electric field. If the electric field becomes higher than the breakdown threshold (approx. =2 x 10(exp 5) V/cm), discharge occurs. This monitor measures potentials as a function of dielectric depth. Differentiation of potential with respect to the depth yields electric field. Direct measurement of the depth profile of the potential in a dielectric makes real-time electronic field evaluation possible without simulations. The IESDM has been designed to emulate a multi-layer circuit board, to insert very thin metallic layers between the dielectric layers. The conductors serve as diagnostic monitoring locations to measure the deposited electron-charge and the charge dynamics. Measurement of the time-dependent potential of the metal layers provides information on the amount of charge deposited in the dielectrics and the movement of that charge with time (dynamics).

Kim, Wousik

Rocket-Plume Spectroscopy Simulation for Hydrocarbon-Fueled Rocket Engines

The UV-Vis spectroscopic system for plume diagnostics monitors rocket engine health by using several analytical tools developed at Stennis Space Center (SSC), including the rocket plume spectroscopy simulation code (RPSSC), to identify and quantify the alloys from the metallic elements observed in engine plumes. Because the hydrocarbon-fueled rocket engine is likely to contain C2, CO, CH, CN, and NO in addition to OH and H2O, the relevant electronic bands of these molecules in the spectral range of 300 to 850 nm in the RPSSC have been included. SSC incorporated several enhancements and modifications to the original line-by-line spectral simulation computer program implemented for plume spectral data analysis and quantification in 1994. These changes made the program applicable to the Space Shuttle Main Engine (SSME) and the Diagnostic Testbed Facility Thruster (DTFT) exhaust plume spectral data. Modifications included updating the molecular and spectral parameters for OH, adding spectral parameter input files optimized for the 10 elements of interest in the spectral range from 320 to 430 nm and linking the output to graphing and analysis packages. Additionally, the ability to handle the non-uniform wavelength interval at which the spectral computations are made was added. This allowed a precise superposition of wavelengths at which the spectral measurements have been made with the wavelengths at which the spectral computations are done by using the line-by-line (LBL) code. To account for hydrocarbon combustion products in the plume, which might interfere with detection and quantification of metallic elements in the spectral region of 300 to 850 nm, the spectroscopic code has been enhanced to include the carbon-based combustion species of C2, CO, and CH. In addition, CN and NO have spectral bands in 300 to 850 nm and, while these molecules are not direct products of hydrocarbon-oxygen combustion systems, they can show up if nitrogen or a nitrogen compound is present as an impurity in the propellants and/or these can form in the boundary layer as a result of interaction of the hot plume with the atmosphere during the ground testing of engines. Ten additional electronic band systems of these five molecules have been included into the code. A comprehensive literature search was conducted to obtain the most accurate values for the molecular and the spectral parameters, including Franck-Cordon factors and electronic transition moments for all ten band systems. For each elemental transition in the RPSSC, six spectral parameters - Doppler broadened line width at half-height, pressure-broadened line width at half-height, electronic multiplicity of the upper state, electronic term energy of the upper state, Einstein transition probability coefficient, and the atomic line center - are required. Input files have been created for ten elements of Ni, Fe, Cr, Co, Cu, Ca, Mn, Al, Ag, and Pd, which retain only relatively moderate to strong transitions in 300 to 430 nm spectral range for each element. The number of transitions in the input files is 68 for Ni; 148 for Fe; 6 for Cr; 87 for Co; 1 for Ca; 3 for Mn; 2 each for Cu, Al, and Ag; and 11 for Pd.

Tejwani, Gopal D.

Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection

The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. Data curation is a time-consuming process for a large volume of data, making it challenging and expensive to deploy data analytics platforms in new environments. Transfer learning (TL) mechanisms promise to mitigate data sparsity and model complexity by utilizing pre-trained models for a new task. Despite the triumph of TL in fields like computer vision and natural language processing, efforts on complex ST models for anomaly detection (AD) applications are limited. In this study, we present the potential of TL within the context of high-dimensional ST AD with a hybrid autoencoder architecture, incorporating convolutional, graph, and recurrent neural networks. Motivated by the need for improved model accuracy and robustness, particularly in scenarios with limited training data on systems with thousands of sensors, this research investigates the transferability of models trained on different sections of the Hadron Calorimeter of the Compact Muon Solenoid experiment at CERN. The key contributions of the study include exploring TL’s potential and limitations within the context of encoder and decoder networks, revealing insights into model initialization and training configurations that enhance performance while substantially reducing trainable parameters and mitigating data contamination effects.

47 OTHER INSTRUMENTATION

The git based ATLAS data acquisition configuration service in LHC Run 3

The ATLAS experiment at the LHC at CERN uses a large, distributed trigger and data acquisition system composed of many computing nodes, networks, and hardware modules. Its configuration service is used to provide descriptions of control, monitoring, diagnostic, recovery, dataflow and data quality configurations, interconnections, and parameters for modules, chips, and channels of various online systems, detectors, and the whole ATLAS experiment. Those descriptions have historically been stored in more than one thousand interconnected XML files, which are updated by various experts many times per day. Maintaining error-free and consistent sets of such files and providing reliable and fast access to current and historical configurations is a major challenge. This paper gives details of the configuration service upgrade on the modern Git version control system backend for LHC Run 3 and its exploitation experience. It may be interesting for developers using human-readable file formats, where consistency of the files, performance, access control, traceability of modifications, and effective archiving are key requirements.

Soloviev, Igor [Univ. of California, Irvine, CA (U

Breathing metabolic simulator.

Description of a device for simulation of the human breathing and metabolic parameters required for the evaluation of respiratory diagnostic, monitoring, support and resuscitation equipment. The remotely controlled device allows wide variations in breathing rate and depth, breath velocity contour, oxygen uptake and carbon dioxide release to simulate conditions from sleep to hard work, with respiration exchange ratios ranging from hypoventilation to hyperventilation. It also reduces the cost of prolonged testing when simulation chambers with human subjects require three shifts of crews and standby physicians. Several block diagrams of the device and subsystems are given.

Bartlett, R. G., Jr.

Breathing metabolic simulator

A description is given of an automatic computer controlled second generation breathing metabolic simulator (BMS). The simulator is used for evaluating and testing respiratory diagnostic, monitoring, support, and resuscitation equipment. Any desired sequence of metabolic activities can be simulated on the device for up to 15 hours. The computer monitors test procedures and provides printouts of test results.

Bartlett, R. G., Jr.

Algorithms for the Automated Power Systems Management

The system breadboard for the demonstration of Automated Power Systems Management (APSM) functions has been designed, fabricated, and is in the final stages of verification and testing. APSM functions fall into categories of fault detection and correction, commanding system and subsystem test and diagnoses, relay position monitoring, data acquisition and processing, and power management. All these functions are accomplished through software residing in 8-bit microprocessors dedicated to each group of Viking Orbiter power breadboard subassemblies and a 16-bit microprocessor serving as the central processor for the power system. This paper describes key monitoring, diagnostic, and control algorithms used in the APSM breadboard.

Moser, R. L.

Space Experiments with Particle Accelerators (SEPAC)

The purpose of Space Experiments with Particle Accelerators (SEPAC) on the Atmospheric Laboratory for Applications and Science (ATLAS 1) mission, is to carry out active and interactive experiments on and in the earth's ionosphere, atmosphere, and magnetosphere. The instruments to be used are an electron beam accelerator (EBA), plasma contactor, and associated instruments the purpose of which is to perform diagnostic, monitoring, and general data taking functions. Four major classes of investigations are to be performed by SEPAC. They are: beam plasma physics, beam-atmosphere interactions, the use of modulated electron beams as transmitting antennas, and the use of electron beams for remote sensing of electric and magnetic fields. The first class consists mainly of onboard plasma physics experiments to measure the effects of phenomena in the vicinity of the shuttle. The last three are concerned with remote effects and are supported by other ATLAS 1 investigations as well as by ground-based observations.

Obayashi, Tatsuzo

NASA CSTI Earth-to-orbit propulsion R/T program overview

The topics presented are covered in viewgraph form. The programmatic objectives are to develop and validate technology, design tools, and methodologies needed for the development of a new generation of lower cost, operationally-efficient, long-life, highly reliable ETO propulsion systems. The technical objectives are: (1) high quality, low cost, inspectable manufacturing; (2) safe shutdown to fault tolerance operations for safety; (3) condition monitoring diagnostics for maintainability; (4) automatic servicing and checkout for ground operations; (5) max commensurate with life for performance; and full flow, combined cycle for advanced cycles.

Moses, James L.

Model-based reasoning for power system management using KATE and the SSM/PMAD

The overall goal of this research effort has been the development of a software system which automates tasks related to monitoring and controlling electrical power distribution in spacecraft electrical power systems. The resulting software system is called the Intelligent Power Controller (IPC). The specific tasks performed by the IPC include continuous monitoring of the flow of power from a source to a set of loads, fast detection of anomalous behavior indicating a fault to one of the components of the distribution systems, generation of diagnosis (explanation) of anomalous behavior, isolation of faulty object from remainder of system, and maintenance of flow of power to critical loads and systems (e.g. life-support) despite fault conditions being present (recovery). The IPC system has evolved out of KATE (Knowledge-based Autonomous Test Engineer), developed at NASA-KSC. KATE consists of a set of software tools for developing and applying structure and behavior models to monitoring, diagnostic, and control applications.

Morris, Robert A.

Knowledge base rule partitioning design for CLIPS

This describes a knowledge base (KB) partitioning approach to solve the problem of real-time performance using the CLIPS AI shell when containing large numbers of rules and facts. This work is funded under the joint USAF/NASA Advanced Launch System (ALS) Program as applied research in expert systems to perform vehicle checkout for real-time controller and diagnostic monitoring tasks. The Expert System advanced development project (ADP-2302) main objective is to provide robust systems responding to new data frames of 0.1 to 1.0 second intervals. The intelligent system control must be performed within the specified real-time window, in order to meet the demands of the given application. Partitioning the KB reduces the complexity of the inferencing Rete net at any given time. This reduced complexity improves performance but without undo impacts during load and unload cycles. The second objective is to produce highly reliable intelligent systems. This requires simple and automated approaches to the KB verification & validation task. Partitioning the KB reduces rule interaction complexity overall. Reduced interaction simplifies the V&V testing necessary by focusing attention only on individual areas of interest. Many systems require a robustness that involves a large number of rules, most of which are mutually exclusive under different phases or conditions. The ideal solution is to control the knowledge base by loading rules that directly apply for that condition, while stripping out all rules and facts that are not used during that cycle. The practical approach is to cluster rules and facts into associated 'blocks'. A simple approach has been designed to control the addition and deletion of 'blocks' of rules and facts, while allowing real-time operations to run freely. Timing tests for real-time performance for specific machines under R/T operating systems have not been completed but are planned as part of the analysis process to validate the design.

Mainardi, Joseph D.

Protein Crystal Movements and Fluid Flows During Microgravity Growth

The growth of protein crystals suitable for X-ray crystal structure analysis is an important topic. The methods of protein crystal growth are under increasing study whereby different methods are being compared via diagnostic monitoring including Charge Coupled Device (CCD) video and interferometry. The quality (perfection) of protein crystals is now being evaluated by mosaicity analysis (rocking curves) and X-ray topographic images as well as the diffraction resolution limit and overall data quality. Choice of a liquid-liquid linear crystal growth geometry and microgravity can yield a spatial stability of growing crystals and fluid, as seen in protein crystallization experiments on the unmanned platform EURICA. A review is given here of existing results and experience over several microgravity missions. The results include CCD video as well as interferometry during the mission, followed, on return to earth, by rocking curve experiments and full X-ray data collection on LMS and earth control lysozyme crystals. Diffraction data recorded from LMS and ground control apocrustacyanin C(sub 1) crystals are also described.

Boggon, Titus J.

Risk Assessment System

FEAT, a software system for evaluating risks, was developed by Lockheed and later enhanced under NASA funding. FEAT uses directed graph - or digraph - models to provide information on cause and effect if a set of failure events occurs. James Miller, the program designer at Lockheed, formed DiGraphics, Inc. to market the software that has evolved from FEAT. The Diquest Analyzer, the company's flagship product, assists product designers in identifying the redundancies and weaknesses of a system. The software has applications in the chemical industry for risk assessment, design evaluation, and change management. Additional markets have been found in operations monitoring diagnostics and training of new personnel.

Source record

Sensor Data Distribution With Robustness and Reliability: Toward Distributed Components Model

In planetary surface exploration mission, sensor data distribution is required in many aspects, for example, in navigation, scheduling, planning, monitoring, diagnostics, and automation of the field tasks. The challenge is to distribute such data in the robust and reliable way so that we can minimize the errors caused by miscalculations, and misjudgments that based on the error data input in the mission. The ad-hoc wireless network on planetary surface is not constantly connected because of the nature of the rough terrain and lack of permanent establishments on the surface. There are some disconnected moments that the computation nodes will re-associate with different repeaters or access points until connections are reestablished. Such a nature requires our sensor data distribution software robust and reliable with ability to tolerant disconnected moments. This paper presents a distributed components model as a framework to accomplish such tasks. The software is written in Java and utilized the available Java Message Services schema and the Boss implementation. The results of field experimentations show that the model is very effective in completing the tasks.

Alena, Richard L.

Carbon Nanotube Based Nanotechnology for NASA Mission Needs and Societal Applications

Carbon nanotubes (CNT) exhibit extraordinary mechanical properties and unique electronic properties and therefore, have received much attention for more than a decade now for a variety of applications ranging from nanoelectronics, composites to meeting needs in energy, environmental and other sectors. In this talk, we focus on some near term potential of CNT applications for both NASA and other Agency/societal needs. The most promising and successful application to date is a nano chem sensor at TRL 6 that uses a 16-256 sensor array in the construction of an electronic nose. Pristine, doped, functionalized and metal-loaded SWCNTs are used as conducting materials to provide chemical variation across the individual elements of the sensor array. This miniaturized sensor has been incorporated in an iPhone for homeland security applications. Gases and vapors relevant to leak detection in crew vehicles, biomedical, mining, chemical threats, industrial spills and others have been demonstrated. SWCNTs also respond to radiation exposure via a change in conductivity and therefore, a similar strategy is being pursued to construct a radiation nose to identify radiation sources (gamma, protons, neutrons, X-ray, etc.) with their energy levels. Carbon nanofibers (CNFs) grown using plasma enhanced CVD typically are vertical, individual, freestanding structures and therefore, are ideal for construction of nanoelectrodes. A nanoelectrode array (NEA) can be the basis for an affinity-based biosensor to meet the needs in applications such as lab-on-a-chip, environmental monitoring, cancer diagnostics, biothreat monitoring, water and food safety and others. A couple of demonstrations including detection of e-coli and ricin will be discussed. The NEA is also useful for implantation in the brain for deep brain stimulation and neuroengineering applications. Miniaturization of payload such as science instrumentation and power sources is critical to reduce launch costs. High current density (greater than 100 mA/per square centimeters) field emission capabilities of CNTs can be exploited for construction of electron gun for electron microscopy and X-ray tubes for spectrometers and baggage screening. A CNT pillar array configuration has been demonstrated, not only meeting the high current density needs but more importantly providing long term emitter stability. Finally, supercapacitors hold the promise to combine the high energy density of a battery with the high power density of capacitors. Traditional graphite electrodes have not delivered this promise yet. A novel design and processing approach using MWCNTs has shown a record 550 F/g capacitance along with significant device endurance. This supercapacitor is suitable for railgun launch application for NASA, powering rovers and robots, consumer electronics and future hybrid vehicles.

Li, Jing

Modeling for Battery Prognostics

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient, and is of suitable accuracy for reliable EOD prediction in a variety of operational profiles. The model can be considered an electrochemical engineering model, but unlike most such models found in the literature, certain approximations are done that allow to retain computational efficiency for online implementation of the model. Although the focus here is on Li-ion batteries, the model is quite general and can be applied to different chemistries through a change of model parameter values. Progress on model development, providing model validation results and EOD prediction results is being presented.

Prognostics