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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Finite-difference simulation and visualization of elastodynamics in time-evolving generalized curvilinear coordinates

Modeling and simulation of free and forced structural vibrations is essential to an overall structural health monitoring capability. In the various embodiments, a first principles finite-difference approach is adopted in modeling a structural subsystem such as a mechanical gear by solving elastodynamic equations in generalized curvilinear coordinates. Such a capability to generate a dynamic structural response is widely applicable in a variety of structural health monitoring systems. This capability (1) will lead to an understanding of the dynamic behavior of a structural system and hence its improved design, (2) will generate a sufficiently large space of normal and damage solutions that can be used by machine learning algorithms to detect anomalous system behavior and achieve a system design optimization and (3) will lead to an optimal sensor placement strategy, based on the identification of local stress maxima all over the domain.

Kaul, Upender K.↗
NASA NTRS2010

Smart Sensors Assess Structural Health

NASA frequently inspects launch vehicles, fuel tanks, and other components for structural damage. To perform quick evaluation and monitoring, the Agency pursues the development of structural health monitoring systems. In 2001, Acellent Technologies Inc., of Sunnyvale, California, received Small Business Innovation Research (SBIR) funding from Marshall Space Flight Center to develop a hybrid Stanford Multi-Actuator Receiver Transduction (SMART) Layer for aerospace vehicles and structures. As a result, Acellent expanded the technology's capability and now sells it to aerospace and automotive companies; construction, energy, and utility companies; and the defense, space, transportation, and energy industries for structural condition monitoring, damage detection, crack growth monitoring, and other applications.

Source record↗
NASA NTRS2011

NASA Tech Briefs, January 2011

The topics include: 1) Distributed Aerodynamic Sensing and Processing Toolbox; 2) Collaborative Supervised Learning for Sensor Networks; 3) Hazard Detection Software for Lunar Landing; 4) Onboard Nonlinear Engine Sensor and Component Fault Diagnosis and Isolation Scheme; 5) Network-Capable Application Process and Wireless Intelligent Sensors for ISHM; 6) Interface Supports Multiple Broadcast Transceivers for Flight Applications; 7) FPGA Sequencer for Radar Altimeter Applications; 8) Miniature Sapphire Acoustic Resonator - MSAR; 9) Process-Hardened, Multi-Analyte Sensor for Characterizing Rocket Plume Constituents; 10) SAD5 Stereo Correlation Line-Striping in an FPGA; 11) Hybrid Composite Cryogenic Tank Structure; 12) Nanoscale Deformable Optics; 13) Reliability-Based Design Optimization of a Composite Airframe Component; 14) Zinc Oxide Nanowire Interphase for Enhanced Lightweight Polymer Fiber Composites; 15) Plasma Igniter for Reliable Ignition of Combustion in Rocket Engines; 16) Wire Test Grip Fixture; 17) A Sub-Hertz, Low-Frequency Vibration Isolation Platform; 18) Carbon Nanofibers Synthesized on Selective Substrates for Nonvolatile Memory and 3D Electronics; 19) Nanoparticle/Polymer Nanocomposite Bond Coat or Coating; 20) High-Resolution Wind Measurements for Offshore Wind Energy Development; 21) Spring Tire; 22) Marsviewer 2008; 23) Mission Services Evolution Center Message Bus; 24) Major Constituents Analysis for the Vehicle Cabin Atmosphere Monitor; 25) Astronaut Health Participant Summary Application; 26) Adaption of the AMDIS Method to Flight Status on the VCAM Instrument; 27) Natural Language Interface for Safety Certification of Safety-Critical Software; 28) Cryogenic Caging for Science Instrumentation; 29) Wide-Range Neutron Detector for Space Nuclear Applications; 30) In Situ Guided Wave Structural Health Monitoring System; 31) Multiplexed Energy Coupler for Rotating Equipment; 32) Attitude Estimation in Fractionated Spacecraft Cluster Systems; 33) Full Piezoelectric Multilayer-Stacked Hybrid Actuation/Transduction Systems; 34) Active Flow Effectors for Noise and Separation Control; 35) Method and System for Temporal Filtering in Video Compression Systems; 36) Apparatus for Measuring Total Emissivity of Small, Low-Emissivity Samples; 37) Multiple-Zone Diffractive Optic Element for Laser Ranging Applications; 38) Simplified Architecture for Precise Aiming of a Deep-Space Communication Laser Transceiver; 39) Two-Photon-Absorption Scheme for Optical Beam Tracking; 40) High-Sensitivity, Broad-Range Vacuum Gauge Using Nanotubes for Micromachined Cavities; 41) Wide-Field Optic for Autonomous Acquisition of Laser Link; 42) Extracting Zero-Gravity Surface Figure of a Mirror; 43) Modeling Electromagnetic Scattering From Complex Inhomogeneous Objects; 44) Visual Object Recognition and Tracking of Tools; 45) Method for Implementing Optical Phase Adjustment; 46) Visual SLAM Using Variance Grid Maps; 47) Rapid Calculation of Spacecraft Trajectories Using Efficient Taylor Series Integration; 48) Efficient Kriging Algorithms; 49) Predicting Spacecraft Trajectories by the WeavEncke Method; 50) An Augmentation of G-Guidance Algorithms; 51) Comparison of Aircraft Icing Growth Assessment Software; 52) Silicon-Germanium Voltage-Controlled Oscillator at 105 GHz; 53) Estimation of Coriolis Force and Torque Acting on Ares-1; 54) Null Lens Assembly for X-Ray Mirror Segments; and 55) High-Precision Pulse Generator.

Source record↗
NASA NTRS2009

Shuttle Wing Leading Edge Root Cause NDE Team Findings and Implementation of Quantitative Flash Infrared Thermography

Comparison metrics can be established to reliably and repeatedly establish the health of the joggle region of the Orbiter Wing Leading Edge reinforced carbon carbon (RCC) panels. Using these metrics can greatly reduced the man hours needed to perform, wing leading edge scanning for service induced damage. These time savings have allowed for more thorough inspections to be preformed in the necessary areas with out affecting orbiter flow schedule. Using specialized local inspections allows for a larger margin of safety by allowing for more complete characterizations of panel defects. The presence of the t-seal during thermographic inspection can have adverse masking affects on ability properly characterize defects that exist in the joggle region of the RCC panels. This masking affect dictates the final specialized inspection should be preformed with the t-seal removed. Removal of the t-seal and use of the higher magnification optics has lead to the most effective and repeatable inspection method for characterizing and tracking defects in the wing leading edge. Through this study some inadequacies in the main health monitoring system for the orbiter wing leading edge have been identified and corrected. The use of metrics and local specialized inspection have lead to a greatly increased reliability and repeatable inspection of the shuttle wing leading edge.

Burke, Eric R.↗
NASA NTRS2014

Emerging Needs for Pervasive Passive Wireless Sensor Networks on Aerospace Vehicles

NASA is investigating passive wireless sensor technology to reduce instrumentation mass and volume in ground testing, air flight, and space exploration applications. Vehicle health monitoring systems (VHMS) are desired on all aerospace programs to ensure the safety of the crew and the vehicles. Pervasive passive wireless sensor networks facilitate VHMS on aerospace vehicles. Future wireless sensor networks on board aerospace vehicles will be heterogeneous and will require active and passive network systems. Since much has been published on active wireless sensor networks, this work will focus on the need for passive wireless sensor networks on aerospace vehicles. Several passive wireless technologies such as microelectromechanical systems MEMS, SAW, backscatter, and chipless RFID techniques, have all shown potential to meet the pervasive sensing needs for aerospace VHMS applications. A SAW VHMS application will be presented. In addition, application areas including ground testing, hypersonic aircraft and spacecraft will be explored along with some of the harsh environments found in aerospace applications.

Wilson, William C.↗
NASA NTRS2013

Investigation of Gearbox Vibration Transmission Paths on Gear Condition Indicator Performance

Helicopter health monitoring systems use vibration signatures generated from damaged components to identify transmission faults. For damaged gears, these signatures relate to changes in dynamics due to the meshing of the damaged tooth. These signatures, referred to as condition indicators (CI), can perform differently when measured on different systems, such as a component test rig, or a full-scale transmission test stand, or an aircraft. These differences can result from dissimilarities in systems design and environment under dynamic operating conditions. The static structure can also filter the response between the vibration source and the accelerometer, when the accelerometer is installed on the housing. To assess the utility of static vibration transfer paths for predicting gear CI performance, measurements were taken on the NASA Glenn Spiral Bevel Gear Fatigue Test Rig. The vibration measurements were taken to determine the effect of torque, accelerometer location and gearbox design on accelerometer response. Measurements were taken at the housing and compared while impacting the gear set near mesh. These impacts were made at gear mesh to simulate gear meshing dynamics. Data measured on a helicopter gearbox installed in a static fixture were also compared to the test rig. The behavior of the structure under static conditions was also compared to CI values calculated under dynamic conditions. Results indicate that static vibration transfer path measurements can provide some insight into spiral bevel gear CI performance by identifying structural characteristics unique to each system that can affect specific CI response.

Dempsey, Paula J.↗
NASA NTRS2015

Composite Cryotank Technologies and Development 2.4 and 5.5M out of Autoclave Tank Test Results

The Composite Cryotank Technologies and Demonstration (CCTD) project substantially matured composite, cryogenic propellant tank technology. The project involved the design, analysis, fabrication, and testing of large-scale (2.4-m-diameter precursor and 5.5-m-diameter) composite cryotanks. Design features included a one-piece wall design that minimized tank weight, a Y-joint that incorporated an engineered material to alleviate stress concentration under combined loading, and a fluted core cylindrical section that inherently allows for venting and purging. The tanks used out-of-autoclave (OoA) cured graphite/epoxy material and processes to enable large (up to 10-m-diameter) cryotank fabrication, and thin-ply prepreg to minimize hydrogen permeation through tank walls. Both tanks were fabricated at Boeing using automated fiber placement on breakdown tooling. A fluted core skirt that efficiently carried axial loads and enabled hydrogen purging was included on the 5.5-m-diameter tank. Ultrasonic inspection was performed, and a structural health monitoring system was installed to identify any impact damage during ground processing. The precursor and 5.5-m-diameter tanks were tested in custom test fixtures at the National Aeronautics and Space Administration Marshall Space Flight Center. The testing, which consisted of a sequence of pressure and thermal cycles using liquid hydrogen, was successfully concluded and obtained valuable structural, thermal, and permeation performance data. This technology can be applied to a variety of aircraft and spacecraft applications that would benefit from 30 to 40% weight savings and substantial cost savings compared to aluminum lithium tanks.

Jackson, Justin R.↗
NASA NTRS2015

Computational Modeling and Experimental Characterization of Martensitic Transformations in Nicoal for Self-Sensing Materials

Fundamental changes to aero-vehicle management require the utilization of automated health monitoring of vehicle structural components. A novel method is the use of self-sensing materials, which contain embedded sensory particles (SP). SPs are micron-sized pieces of shape-memory alloy that undergo transformation when the local strain reaches a prescribed threshold. The transformation is a result of a spontaneous rearrangement of the atoms in the crystal lattice under intensified stress near damaged locations, generating acoustic waves of a specific spectrum that can be detected by a suitably placed sensor. The sensitivity of the method depends on the strength of the emitted signal and its propagation through the material. To study the transition behavior of the sensory particle inside a metal matrix under load, a simulation approach based on a coupled atomistic-continuum model is used. The simulation results indicate a strong dependence of the particle's pseudoelastic response on its crystallographic orientation with respect to the loading direction and suggest possible ways of optimizing particle sensitivity. The technology of embedded sensory particles will serve as the key element in an autonomous structural health monitoring system that will constantly monitor for damage initiation in service, which will enable quick detection of unforeseen damage initiation in real-time and during onground inspections.

Wallace, T. A.↗
NASA NTRS2017

Design, Manufacture and Test of Cryotank Components

On the composite cryotank technology development (CCTD) project, the Boeing Company built two cryotanks as a means of advancing technology and manufacturing readiness levels (TRL and MRL) and lowering the risk of fabricating full-scale fuel containment vessels.1 CCTD focused on upper stage extended duration applications where long term storage of propellants is required. The project involved the design, analysis, fabrication, and test of manufacturing demonstration units (MDU), a 2.4 m (precursor) and a 5.5 m composite cryotank. Key design features included one-piece wall construction to minimize overall weight (eliminating the need for a bellyband joint), 3-dimensionally (3D) reinforced y-joint material to alleviate stress concentrations at the tank to skirt interface and a purge-able fluted core skirt to carry high axial launch loads. The tanks were made with OoA curing pre-impregnated (prepreg) carbon/epoxy (C/E) slit-tape tow (STT) that contained thin micro-crack resistant plies in the tank wall center to impede permeation. The tanks were fabricated at Boeing's Seattle-based Advanced Development Center (ADC) using RAFP and multipiece break-down tooling. The tooling was designed and built by Janicki Industries (JI) at Sedro Woolley, Washington. Tank assemblage consisted of co-bonded dome covers, one-piece fluted core skirts and mechanical fastened cover/sump. Ultrasonic inspection was performed after every cure or bond and a structural health monitoring system (SHMS) was installed to identify potential impact damage events (in-process and/or during transportation). The tanks were low temperature tested at NASA's George C. Marshall Space Flight Center (MSFC) in Huntsville, Alabama. The testing, which consisted of a sequence of fill/drain pressure and thermal cycles using LH2, was successfully concluded in 2012 on the 2.4 m tank and in 2014 on the 5.5 m tank. Structural, thermal, and permeation performance data was obtained. 2 Critical design features and manufacturing advancements, which helped to validate 25% weight and 30% cost reduction projections, were matured. These advancements will help to guide future composite tank integration activities on next generation long duration aircraft and space launch vehicles. Because CCTD addressed innovative design features, heavy lift size scale-up, multipiece captured tooling, new generation automated material placement (AMP) equipment and OoA materials, this chapter should be of interest to educators, students and manufacturers of composite hardware and flight vehicles.

McCarville, Douglas A.↗
NASA NTRS2018

An Efficient Inverse Finite Element Method for Shape and Stress Sensing of Laminated Composite and Sandwich Plates and Shells

The inverse Finite Element Method (iFEM) is a revolutionary methodology for real-time reconstruction of full-field structural displacements and stresses in structures that are instrumented with strain sensors. This inverse problem is commonly referred to as shape and stress sensing, which is well-recognized as an enabling technology for structural health monitoring systems. In this study, an improved iFEM formulation is proposed for shape and stress sensing of laminated composite and sandwich plates and shells. The formulation includes the kinematics of a shear deformation plate theory known as Refined Zigzag Theory (RZT) as its baseline. The present iFEM formulation is based upon the minimization of a weighted-least-squares functional that uses the complete set of section strains of RZT. The improved iFEM methodology is applicable for shape and stress sensing of thin and moderately thick plate and shell structures involving a relatively small number of strain gauges. The main advantage of the current formulation is that highly accurate through-the-thickness distributions of displacements, strains, and stresses are attainable using an element based on simple C0-continuous displacement interpolation functions. A three-node inverseshell element, named i3-RZT, is developed. Two example problems are examined in detail: (1) a simply supported rectangular laminated composite plate and (2) a wedge structure with a hole near one of the clamped ends. For both problems, the experimental strain data are generated numerically by the direct finite element analysis using high-fidelity discretizations. These strains are then regarded as the experimental strains obtained from surface mounted strain gauges or embedded fiber Bragg grating (FBG) sensors. The numerical results demonstrate the superior capability and potential applicability of the i3- RZT/iFEM methodology for performing accurate shape and stress sensing of complex composite structures.

Kefal, Adnan↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗
NASA NTRS1981

Engine health monitoring: An advanced system

The advanced propulsion monitoring system is described. The system was developed in order to fulfill a growing need for effective engine health monitoring. This need is generated by military requirements for increased performance and efficiency in more complex propulsion systems, while maintaining or improving the cost to operate. This program represents a vital technological step in the advancement of the state of the art for monitoring systems in terms of reliability, flexibility, accuracy, and provision of user oriented results. It draws heavily on the technology and control theory developed for modern, complex, electronically controlled engines and utilizes engine information which is a by-product of such a system.

Dyson, R. J. E.↗
NASA NTRS2015

Evaluation of the Accuracy of Astroskin as a Behavioral Health Self-Monitoring System for Spaceflight

In space, there is a need to monitor astronauts' vital signs and assess their readiness to perform specific tasks during a mission. Currently, NASA does not have the capability to noninvasively monitor crew for extended periods of time. The Canadian Space Agency is working with the Psychophysiology Lab at NASA ARC to determine if the Astroskin could be used as a solution to this problem. Astroskin, a commercially available garment with built-in biosensors, can be comfortably worn under clothing or a spacesuit and relay information to the crewman's own mobile device. Data can also be sent wirelessly to the on-board Exploration Medical System. To determine if Astroskin meets requirements for health monitoring, it must first be validated in spaceflight analog environments. In the current study Astroskin data will be compared to traditional biomedical instrument measures of electrocardiography (ECG), respiration rate, and systolic blood pressure. The data will be recorded during Autogenic Feedback Training Exercise (AFTE), which is a type of physiological self-regulation training designed for astronauts. The data will also be recorded during simulations of the Orion spacecraft re-entry. The results to date suggest that Astroskin is a suitable ambulatory monitoring system that allows astronauts to self-diagnose and self-regulate adverse autonomic nervous system responses to sustained exposure to microgravity of spaceflight.

biomedical↗
NASA NTRS2001

A Model-based Health Monitoring and Diagnostic System for the UH-60 Helicopter

Model-based reasoning techniques hold much promise in providing comprehensive monitoring and diagnostics capabilities for complex systems. We are exploring the use of one of these techniques, which utilizes multi-signal modeling and the TEAMS-RT real-time diagnostic engine, on the UH-60 Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) flight research aircraft. We focus on the engine and transmission systems, and acquire sensor data across the 1553 bus as well as by direct analog-to-digital conversion from sensors to the QHuMS (Qualtech health and usage monitoring system) computer. The QHuMS computer uses commercially available components and is rack-mounted in the RASCAL facility. A multi-signal model of the transmission and engine subsystems enables studies of system testability and analysis of the degree of fault isolation available with various instrumentation suites. The model and examples of these analyses will be described and the data architectures enumerated. Flight tests of this system will validate the data architecture and provide real-time flight profiles to be further analyzed in the laboratory.

Patterson-Hine, Ann↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments.

Iverson, David L.↗
NASA NTRS2019

Acoustic Emission-Based Health Monitoring of Space Launch System Structures

This report documents the technical accomplishments of the project, “Acoustic Emission- Based Health Monitoring of Space Launch System Structures,” sponsored by the National Aeronautics and Space Administration (Award No. NNM13AA12G). As the project title suggests, the goal of the project was to develop a structural health monitoring (SHM) system for Space Launch System (SLS) vehicles based on acoustic emission (AE) or AE-like signals. Such a system will enhance SLS reliability by identifying the damage locations and type of damage when the damage is initiated. This SHM system would also lead to reduced maintenance costs by enabling ground support equipment to inspect only SLS elements or parts that are likely to be damaged. Finally, it will facilitate lean designs that meet tolerance levels specified by barely detectable damage. By avoiding excess conservatism in this manner, this SHM system will further reduce manufacturing costs of SLS vehicles.

Adams, D. O.↗
NASA NTRS2013

High Temperatures Health Monitoring of the Condensed Water Height in Steam Pipe Systems

Ultrasonic probes were designed, fabricated and tested for high temperature health monitoring system. The goal of this work was to develop the health monitoring system that can determine the height level of the condensed water through the pipe wall at high temperature up to 250 deg while accounting for the effects of surface perturbation. Among different ultrasonic probe designs, 2.25 MHz probes with air backed configuration provide satisfactory results in terms of sensitivity, receiving reflections from the target through the pipe wall. A series of tests were performed using the air-backed probes under irregular conditions, such as surface perturbation and surface disturbance at elevated temperature, to qualify the developed ultrasonic system. The results demonstrate that the fabricated air-backed probes combined with advanced signal processing techniques offer the capability of health monitoring of steam pipe under various operating conditions.

High Temperatures (HT)↗