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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Thermal Analysis Of The NASA Integrated Vehicle Health Monitoring Experiment Technology For X-Vehicles (NITEX)

The purpose of this project was to perform a thermal analysis for the NASA Integrated Vehicle Health Monitoring (IVHM) Technology Experiment for X-vehicles (NITEX). This electronics package monitors vehicle sensor information in flight and downlinks vehicle health summary information via telemetry. The experiment will be tested on the X-34 in an unpressurized compartment, in the vicinity of one of the vehicle's liquid oxygen tanks. The transient temperature profile for the electronics package has been determined using finite element analysis for possible mission profiles that will most likely expose the package to the most extreme hot and cold environmental conditions. From the analyses, it was determined that temperature limits for the electronics would be exceeded for the worst case cold environment mission profile. The finite element model used for the analyses was modified to examine the use of insulation to address this problem. Recommendations for insulating the experiment for the cold environment are presented, and were analyzed to determine their effect on a nominal mission profile.

Hegab, Hisham E.↗
NASA NTRS2002

Thermal Analysis of the NASA Integrated Vehicle Health Monitoring Experiment Technology for X-Vehicles (NITEX)

The purpose of this project was to perform a thermal analysis for the NASA Integrated Vehicle Health Monitoring (IVHM) Technology Experiment for X-vehicles (NITEX). This electronics package monitors vehicle sensor information in flight and downlinks vehicle health summary information via telemetry. The experiment will be tested on the X-34 in an unpressurized compartment, in the vicinity of one of the vehicle's liquid oxygen tanks. The transient temperature profile for the electronics package has been determined using finite element analysis for possible mission profiles that will most likely expose the package to the most extreme hot and cold environmental conditions. From the analyses, it was determined that temperature limits for the electronics would be exceeded for the worst case cold environment mission profile. The finite element model used for the analyses was modified to examine the use of insulation to address this problem. Recommendations for insulating the experiment for the cold environment are presented, and were analyzed to determine their effect on a nominal mission profile.

Hegab, Hisham E.↗
NASA NTRS2014

A Battery Health Monitoring Framework for Planetary Rovers

Batteries have seen an increased use in electric ground and air vehicles for commercial, military, and space applications as the primary energy source. An important aspect of using batteries in such contexts is battery health monitoring. Batteries must be carefully monitored such that the battery health can be determined, and end of discharge and end of usable life events may be accurately predicted. For planetary rovers, battery health estimation and prediction is critical to mission planning and decision-making. We develop a model-based approach utilizing computaitonally efficient and accurate electrochemistry models of batteries. An unscented Kalman filter yields state estimates, which are then used to predict the future behavior of the batteries and, specifically, end of discharge. The prediction algorithm accounts for possible future power demands on the rover batteries in order to provide meaningful results and an accurate representation of prediction uncertainty. The framework is demonstrated on a set of lithium-ion batteries powering a rover at NASA.

prediction↗
NASA NTRS1990

Annual Health Monitoring Conference for Space Propulsion Systems, 2nd, Cincinnati, OH, Nov. 14, 15, 1990, Proceedings

This conference discusses health management systems for liquid rocket engines, signal processing of spectroscopic data for engine diagnostic applications, real-time diagnostics of the reusable rocket engine using on-line system identification, and nonlinear parameter estimation for rocket engine health monitoring. Plume diagnostics are considered including discussion on preliminary plume diagnostics on the SSME using video digitization techniques and baseline plume emmissions. The development of a Fabry-Perot Interferometer for rocket engine plumes is also considered. The topic of computational modeling is also discussed, addressing such topics as probabalistic dynamics of material loss in the SSME turbomachinery, state-variable modelling of fluid-dynamics processes, and a model for the SSME high pressure oxidizer turbopump shaft seal system. A discussion of sensor development includes the topics of sensor development for the rocket engine condition monitoring system and the heat flux measurements in SSME turbine blade tester.

Source record↗
NASA NTRS2013

Evaluation of a Microwave Blade Tip Clearance Sensor for Propulsion Health Monitoring

The NASA Glenn Research Center has investigated a microwave blade tip clearance system for the structural health monitoring of gas turbine engines. This presentation describes the sensors and the experiments that have been conducted to evaluate their performance along with future plans for their use on an engine ground test.

Woike, Mark R.↗
NASA NTRS2016

Demonstration of a Packaged Capacitive Pressure Sensor System Suitable for Jet Turbofan Engine Health Monitoring

In this paper, the development and characterization of a packaged pressure sensor system suitable for jet engine health monitoring is demonstrated. The sensing system operates from 97 to 117 MHz over a pressure range from 0 to 350 psi and a temperature range from 25 to 500 deg. The sensing system consists of a Clapp-type oscillator that is fabricated on an alumina substrate and is comprised of a Cree SiC MESFET, MIM capacitors, a wire-wound inductor, chip resistors and a SiCN capacitive pressure sensor. The pressure sensor is located in the LC tank circuit of the oscillator so that a change in pressure causes a change in capacitance, thus changing the resonant frequency of the sensing system. The chip resistors, wire-wound inductors and MIM capacitors have all been characterized at temperature and operational frequency, and perform with less than 5% variance in electrical performance. The measured capacitive pressure sensing system agrees very well with simulated results. The packaged pressure sensing system is specifically designed to measure the pressure on a jet turbofan engine. The packaged system can be installed by way of borescope plug adaptor fitted to a borescope port exposed to the gas path of a turbofan engine.

Harsh environment↗
NASA NTRS2004

Inductive System Health Monitoring

The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS uses nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring method used by IMS and summarize some recent IMS results.

Iverson, David L.↗
DOE OSTI2025

Boiler Health Monitoring Using a Hybrid First Principles-Artificial Intelligence Model

Due to increased penetration of the intermittent renewables to the grid, pulverized coal (PC) plants are being forced to cycle their load frequently and rapidly, operate at low load condition for sustained period, and start up and shut down several hundred times in a year in the worst case. These severe operations are causing substantial damage to the boiler components compromising the reliability of PC plants. An online health monitoring tool can be instrumental in understanding the impacts of load-following and can eventually help PC plants to develop advanced process control strategies for improved flexibility without compromising safety nor reliability.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2017

Prognostics and Health Monitoring: Application to Electric Vehicles

As more and more autonomous electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of remaining useful life of the systemssubsystems, specifically the electrical powertrain. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle.Our research approach is to develop a system level health monitoring safety indicator either to the pilotautopilot for the electric vehicles which runs estimation and prediction algorithms to estimate remaining useful life of the vehicle e.g. determine state-of-charge in batteries. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

Prognostics↗
DOE OSTI2021

Structural Health Monitoring of Microreactor Safety Systems Using Convolutional Neural Networks

Microreactors, a class of modular reactors with net power output of less than 20 MWth, have innovative applications in nuclear and nonnuclear industries due to their portability, reliability, resilience, and high capacity factors. In order to operate microreactors on a wider scale, it is essential to bring down maintenance life-cycle costs while ensuring the integrity of operating such systems. Autonomous operations in microreactors using augmented digital-twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. Structural health monitoring (SHM) is a key component of nuclear DT frameworks. Artificial neural networks can be beneficial to detect degradation in the nuclear safety systems, such as piping equipment systems, by monitoring the sensor data obtained from the plant and its corresponding structures, systems and components. In this report, an SHM methodology is presented which uses convolutional neural networks to determine degraded locations and their corresponding degradation-severity levels at various locations of nuclear piping equipment systems. A simple pipe system, subjected to seismic loads, is selected to design the post-hazard SHM framework. The effectiveness of the proposed SHM methodology is demonstrated by obtaining high accuracy in detecting degraded locations as well as the severity levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2002

Structural Health Monitoring Sensor Development at NASA Langley Research Center

NASA is applying considerable effort on the development of sensor technology for structural health monitoring (SHM). This research is targeted toward increasing the safety and reliability of aerospace vehicles, while reducing operating and maintenance costs. Research programs are focused on applications to both aircraft and space vehicles. Sensor technologies under development span a wide range including fiber-optic sensing, active and passive acoustic sensors, electromagnetic sensors, wireless sensing systems, MEMS, and nanosensors. Because of their numerous advantages for aerospace applications, fiber-optic sensors are one of the leading candidates and are the major focus of this presentation. In addition, recent advances in active and passive acoustic sensing will also be discussed.

Prosser, W. H.↗
NASA NTRS1992

Orbit transfer rocket engine integrated control and health monitoring system technology readiness assessment

The objectives of this task were to: (1) estimate the technology readiness of an integrated control and health monitoring (ICHM) system for the Aerojet 7500 lbF Orbit Transfer Vehicle engine preliminary design assuming space based operations; and (2) estimate the remaining cost to advance this technology to a NASA defined 'readiness level 6' by 1996 wherein the technology has been demonstrated with a system validation model in a simulated environment. The work was accomplished through the conduct of four subtasks. In subtask 1 the minimally required functions for the control and monitoring system was specified. The elements required to perform these functions were specified in Subtask 2. In Subtask 3, the technology readiness level of each element was assessed. Finally, in Subtask 4, the development cost and schedule requirements were estimated for bringing each element to 'readiness level 6'.

Bickford, R. L.↗
DOE OSTI2025

Self-Sensing Composites via an Embedded 3D-Printed PVDF-MoS 2 Nanosensor for Structural Health Monitoring

Carbon fiber (CF)-reinforced epoxy composites are widely used in vehicle applications, where early damage detection is crucial for reliability and safety. To address this need, we developed a self-sensing epoxy/CF composite by embedding a PVDF-MoS 2 nanosensor via an embedded 3D printing method. By harnessing the intrinsic curing kinetics of epoxy, we tailored its rheological properties to optimize the embedded printing process, enabling precise and reliable support for sensor filaments without compromising the composite’s structural and functional integrity. Through comprehensive rheological and kinetic analysis, we established a quantitative relationship among curing temperature, conversion rate, and resulting yield modulus─defining a narrow processing window essential for successful sensor integration. Specifically, we identified that an epoxy yield modulus range of 180–294 Pa and a conversion rate below 10% are critical to support the PVDF-MoS 2 filament architecture. Here, this embedded 3D printing method produces complex and multimaterial PVDF-MoS 2 sensors within an epoxy matrix with minimal deformation and reduced postprocessing, which is scalable and adaptable for industrial applications. Under cyclic loading, the embedded sensors exhibited stable signals under constant loads and increased voltage signals in response to crack formation (17–35% higher) and catastrophic failure (1 order of magnitude higher), effectively capturing structural changes in real time. This study demonstrates the potential of PVDF-MoS 2 nanocomposite sensor materials for real-time structural health monitoring in epoxy–CF composite systems, enabling early detection of defects and stress anomalies, significantly reducing the risk of unexpected failures, and enhancing structural reliability.

PVDF-MoS2 sensor↗
NASA NTRS2003

Proof-of-Concept Application of Impedance-Based Health Monitoring on Space Shuttle Ground Structures

Many of the structures responsible for the launch, ground systems and support operations of the space shuttle are still being used well past their nominal expected design life. This has led to an increased interest in monitoring these structures in order to decrease the risk of eventual breakdown or structural failure. One monitoring method, which has shown promising results for such applications, is the impedance-based structural health monitoring technique. This paper presents results from proof-of-concept tests on the launch pad's orbiter access arm bolted connection, solid rocket booster hold down post, mobile launch platform heat shield and crawler transporter bearing. Modification for future tests are suggested.

Peairs, Daniel M.↗
NASA NTRS2017

The Potential for Health Monitoring in Expandable Space Modules: The Bigelow Expandable Activity Module on the ISS

Expandable modules for use in space and on the Moon or Mars offer a great opportunity for volume and mass savings in future space exploration missions. This type of module can be compressed into a relatively small shape on the ground, allowing them to fit into space vehicles with a smaller cargo/fairing size than a traditional solid, metallic structure based module would allow. In April 2016, the Bigelow Expandable Activity Module (BEAM) was berthed to the International Space Station (ISS). BEAM is the first human-rated expandable habitat/module to be deployed and crewed in space. BEAM is a NASA managed ISS payload project in partnership with Bigelow Aerospace. BEAM is intended to stay attached to ISS for an operational period of 2 years to help advance the technology readiness for future expandable modules. BEAM has been instrumented with a suite of space flight certified sensors systems which will help characterize the module's performance for thermal, radiation shielding and impact monitoring against potential Micro Meteoroid/Orbital Debris (MM/OD) providing fundamental information on the BEAM environment for potential health monitoring requirements and capabilities. This paper will provide an overview of how the sensors/instrumentation systems were developed, tested, installed and an overview of the current sensor system operations. It will also discuss how the MM/OD impact detection system referred to as the Distributed Impact Detection System (DIDS) data is being processed and reviewed on the ground by the principle investigators.

Wells, Nathan D.↗
NASA NTRS2016

Health Monitoring of a Planetary Rover Using Hybrid Particle Petri Nets

This paper focuses on the application of a Petri Net-based diagnosis method on a planetary rover prototype.The diagnosis is performed by using a model-based method in the context of health management of hybrid systems.In system health management, the diagnosis task aims at determining the current health state of a system and the fault occurrences that lead to this state. The Hybrid Particle Petri Nets (HPPN) formalism is used to model hybrid systems behavior and degradation, and to define the generation of diagnosers to monitor the health states of such systems under uncertainty. At any time, the HPPN-based diagnoser provides the current diagnosis represented by a distribution of beliefs over the health states. The health monitoring methodology is demonstrated on the K11 rover. A hybrid model of the K11 is proposed and experimental results show that the approach is robust to real system data and constraints.

health monitoring↗