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At least 73 records · Page 4

Effects of Impact Damage in Midplane Asymmetric Sandwich Composites

Several structural sandwich composites arc in service on military and commercial aerospace vehicles, however, these components have been limited to secondary structures partly because the impact damage and damage tolerance of these composites have not been extensively characterized. To improve durability, safety, and life cycle performance of PMCs while reducing maintenance costs, combined analysis, and test methods that provide a means of predicting critical engineering properties after impact damage of the structure, must be developed. A key enabling technology here is the establishment of the correlation between the impact test results conducted in the laboratory and the mechanics-based phenomenological solutions. This research was undertaken to investigate the compression and flexural properties following low velocity impact of a nomex/phenolic honeycomb core, fiberglass/epoxy facesheet, midplane asymmetric sandwich composite. One facesheet (thin side) was composed of two plies of the fiberglass/epoxy (0/90), while the other facesheet (thick side) was composed of four plies (0/90/0/90) of fiberglass/epoxy. Due to the differences in facesheet thickness, impact damage was separately induced on the thick side as well as the thin side. The compression and flexural strength properties for each damage arrangement were compared using different levels of impact energy ranging from 0 to 452 Joules. In all cases, higher impact energy resulted in decreased compression and flexural strength. Impact on the thin side showed slightly more retention of compression strength at low impact levels, whereas higher residual compressive strength was observed from impact on the thick side at higher impact levels. Different facesheet thicknesses or midplane asymmetry, played an important role in the flexural strength, however, low velocity impact on the both the thick and thin fiberglass/epoxy facesheet side showed an almost linear loss of flexural strength to saturation.

Meador, Michael↗

Digital Twin Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derate while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Passenger comfort technology for system decision making

Decisions requiring passenger comfort technology were shown to depend on: the relationship between comfort and other factors (e.g., cost, urgency, alternate modes) in traveler acceptance of the systems, serving a selected market require technology to quantify effects of comfort versus offsetting factors in system acceptance. Public predict the maximum percentage of travelers who willingly accept the overall comfort of any trip ride. One or the other of these technology requirements apply to decisions on system design, operation and maintenance.

Conner, D. W.↗

Verification and validation of developed short-term forecasting models

Recent advancements in machine learning (ML) and artificial intelligence (AI) technologies provide an opportunity for leveraging data-driven algorithms to predict future nuclear power plant (NPP) operating conditions by using recorded plant process data. Successfully implementing these models can lead to cost-reducing, conditioned-based predictive maintenance through optimized maintenance schedules and a reduction of unnecessary maintenance activities. This report discusses the verification and validation of short-term forecasting processes (i.e., data cleaning, feature selection, model optimization, and forecasting) developed in previous reports. The verification and validation (V&V) process demonstrates the expected precision and accuracy when the ML model encounters new datasets from different systems. Shapley additive explanations were used as the primary means of feature selection across these different data set. Individual models were trained for each data set, then validated through a cross-validation procedure. In this report, two different ML models were tasked to predict variables from three different plant process data sets with varying prediction horizons. The results indicate that support vector regression (SVR) outperformed long short-term memory (LSTM) neural networks in regard to each data set and each prediction horizon in this study, but further tuning and optimization could improve long short-term memory results. However, each forecasting model showed reduced performance as the prediction horizon was extended from 1 hour to 1 day ahead. Research is ongoing to evaluate the optimal input variable space, which is based on a given set of process parameters, to further improve forecasting accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Coherent Doppler Laser Radar: Technology Development and Applications

NASA's Marshall Space Flight Center has been investigating, developing, and applying coherent Doppler laser radar technology for over 30 years. These efforts have included the first wind measurement in 1967, the first airborne flights in 1972, the first airborne wind field mapping in 1981, and the first measurement of hurricane eyewall winds in 1998. A parallel effort at MSFC since 1982 has been the study, modeling and technology development for a space-based global wind measurement system. These endeavors to date have resulted in compact, robust, eyesafe lidars at 2 micron wavelength based on solid-state laser technology; in a factor of 6 volume reduction in near diffraction limited, space-qualifiable telescopes; in sophisticated airborne scanners with full platform motion subtraction; in local oscillator lasers capable of rapid tuning of 25 GHz for removal of relative laser radar to target velocities over a 25 km/s range; in performance prediction theory and simulations that have been validated experimentally; and in extensive field campaign experience. We have also begun efforts to dramatically improve the fundamental photon efficiency of the laser radar, to demonstrate advanced lower mass laser radar telescopes and scanners; to develop laser and laser radar system alignment maintenance technologies; and to greatly improve the electrical efficiency, cooling technique, and robustness of the pulsed laser. This coherent Doppler laser radar technology is suitable for high resolution, high accuracy wind mapping; for aerosol and cloud measurement; for Differential Absorption Lidar (DIAL) measurements of atmospheric and trace gases; for hard target range and velocity measurement; and for hard target vibration spectra measurement. It is also suitable for a number of aircraft operations applications such as clear air turbulence (CAT) detection; dangerous wind shear (microburst) detection; airspeed, angle of attack, and sideslip measurement; and fuel savings through headwind minimization. In addition to the airborne and space platforms, a coherent Doppler laser radar system in an unmanned aerial vehicle (UAV) could provide battlefield weather and target identification.

Kavaya, Michael J.↗

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Prognostics for Ground Support Systems: Case Study on Pneumatic Valves

Prognostics technologies determine the health (or damage) state of a component or sub-system, and make end of life (EOL) and remaining useful life (RUL) predictions. Such information enables system operators to make informed maintenance decisions and streamline operational and mission-level activities. We develop a model-based prognostics methodology for pneumatic valves used in ground support equipment for cryogenic propellant loading operations. These valves are used to control the flow of propellant, so failures may have a significant impact on launch availability. Therefore, correctly predicting when valves will fail enables timely maintenance that avoids launch delays and aborts. The approach utilizes mathematical models describing the underlying physics of valve degradation, and, employing the particle filtering algorithm for joint state-parameter estimation, determines the health state of the valve and the rate of damage progression, from which EOL and RUL predictions are made. We develop a prototype user interface for valve prognostics, and demonstrate the prognostics approach using historical pneumatic valve data from the Space Shuttle refueling system.

Daigle, Matthew↗

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable optimized scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins (DTs) are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. DTs for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. A DT’s goal is to provide additional insights by combining and interpreting various sources of information for preventative maintenance scheduling optimization or early fault detection. DTs for condition monitoring are projected to be valuable for meeting requirements under 10 CFR 50.55a, “Codes and Standards,” and 10 CFR 50.65, “Requirements for Monitoring the Effectiveness of Maintenance at Nuclear Power Plants”. However, DT technologies are still under significant development, and the process for developing a DT for condition monitoring has not been formalized. Therefore, in this work, we present an initial framework for developing a DT, discuss and review the various challenges and considerations for DT deployment, and identify the opportunities that a DT can improve. The presented framework is intended to help developers formulate a strategy when approaching DT development for condition monitoring. In conclusion, a DT use case for a reactor coolant pump is presented to demonstrate the proposed framework.

advanced sensor instrumentation↗

Economic Analysis of Condition-Monitoring-Based Predictive Maintenance in Power Plants under Market Elasticity

Condition-monitoring-based predictive maintenance can increase the power plant availability by preventing forced outages. However, the actual on-stream time depends on market elasticity and dynamics, which are affected by cost and penetration of other power generation technologies. This paper develops a systematic approach for the economic analysis of investment in condition monitoring technologies with due consideration of market elasticity. Focus is on corrosion monitoring in coal-fired power plants (CFFPs) since corrosion in high-temperature coal-fired boilers is a leading cause of equipment failure. Investment in sensor networks for measuring corrosion and operating conditions like metal temperature and concentrations of O 2 and SO 2 is investigated. The unscented Kalman filter is used to estimate corrosion in the waterwall section of the boiler under multiple sensor networks. Electricity produced by CFPPs in the future in the U.S. due to changes in availability under market elasticity is studied. Sensitivity of the incremental net present value to factors like the number, type, and cost of sensors is analyzed.

Electrochemistry↗

Space tug point design study. Volume 4: Program requirements

A study was conducted to determine the configuration of a space tug and to predict the performance parameters. The program plans and planning data generated in support of the tug development program are presented. The preliminary plans and supporting planning data emphasize the following requirements: (1) maintenance and refurbishment, (2) technology development, (3) production, (4) test facilities, (5) quality control, and (6) scheduling.

Source record↗

Fault Management Technology Maturation for NASA's Constellation Program

This slide presentation reviews the maturation of fault management technology in preparation for the Constellation Program. There is a review of the Space Shuttle Main Engine (SSME) and a discussion of a couple of incidents with the shuttle main engine and tanking that indicated the necessity for predictive maintenance. Included is a review of the planned Ares I-X Ground Diagnostic Prototype (GDP) and further information about detection and isolation of faults using Testability Engineering and Maintenance System (TEAMS). Another system that being readied for use that detects anomalies, the Inductive Monitoring System (IMS). The IMS automatically learns how the system behaves and alerts operations it the current behavior is anomalous. The comparison of STS-83 and STS-107 (i.e., the Columbia accident) is shown as an example of the anomaly detection capabilities.

Waterman, Robert D.↗

Orbit transfer rocket engine technology program

An advanced near term (1990's) space-based Orbit Transfer Vehicle Engine (OTVE) system was designed, and the technologies applicable to its construction, maintenance, and operations were developed under Tasks A through F of the Orbit Transfer Rocket Engine Technology Program. Task A was a reporting task. In Task B, promising OTV turbomachinery technologies were explored: two stage partial admission turbines, high velocity ratio diffusing crossovers, soft wear ring seals, advanced bearing concepts, and a rotordynamic analysis. In Task C, a ribbed combustor design was developed. Possible rib and channel geometries were chosen analytically. Rib candidates were hot air tested and laser velocimeter boundary layer analyses were conducted. A channel geometry was also chosen on the basis of laser velocimeter data. To verify the predicted heat enhancement effects, a ribbed calorimeter spool was hot fire tested. Under Task D, the optimum expander cycle engine thrust, performance and envelope were established for a set of OTV missions. Optimal nozzle contours and quick disconnects for modularity were developed. Failure Modes and Effects Analyses, maintenance and reliability studies and component study results were incorporated into the engine system. Parametric trades on engine thrust, mixture ratio, and area ratio were also generated. A control system and the health monitoring and maintenance operations necessary for a space-based engine were outlined in Task E. In addition, combustor wall thickness measuring devices and a fiberoptic shaft monitor were developed. These monitoring devices were incorporated into preflight engine readiness checkout procedures. In Task F, the Integrated Component Evaluator (I.C.E.) was used to demonstrate performance and operational characteristics of an advanced expander cycle engine system and its component technologies. Sub-system checkouts and a system blowdown were performed. Short transitions were then made into main combustor ignition and main stage operation.

Gustafson, N. B.↗

Coating Development for GRCop-84 Liners for Reusable Launch Vehicles Aided by Modeling Studies

The design of the next generation of reusable launch vehicles calls for using GRCop-84 copper alloy liners based on a composition invented at the NASA Glenn Research Center. Despite its considerable advantage over other copper alloys, it is expected that GRCop-84 will suffer from environmental degradation depending on the type of rocket fuels used and on thermomechanical fatigue. Applying protective coatings on GRCop-84 substrates can minimize or eliminate many of these problems and extend the operational life of the combustion liner. This could increase component reliability, shorten depot maintenance turnaround times, and lower operating costs. Therefore, Glenn is actively pursuing the development of advanced coatings technology for GRCop-84 liners. Technology is being developed in four major areas: (1) new metallic coating compositions, (2) application techniques, (3) test methods, and (4) life prediction design methodology using finite element analysis. The role of finite element analysis in guiding the coating effort is discussed in this report. Thermal analyses were performed at Glenn for different combinations of top- and bondcoat compositions to determine the temperature variation across the coated cross section with the thickness of the top coat. These calculations were conducted for simulated LH2/LO2 booster engine conditions assuming that the bond coat had a constant thickness of 50 m. The preceding graphs show the predicted temperatures at the outer surface of the top coat (hot wall), at the top-coat/bond-coat interface, at the bond-coat/GRCop-84 interface, and at the GRCop-84 cold wall as a function of top-coat thickness for Cu- 26(wt%)Cr top coat (top graph), Ni-17(wt%)Cr-6%Al-0.5%Y top coat and Cu-26%Cr bond coat, and NiAl top coat and Ni bond coat. In all cases, the temperature of the top coat at the hot wall increased with increasing top-coat thickness and with corresponding decreases in the temperatures at the two interfaces and the cold wall. These temperatures are not acutely sensitive to the thermal conductivity of the top coat when it exceeds 25 and 50 W/m/K for low and high heat flux engines. This observation is significant for two reasons. First, several different top-coat compositions can be evaluated as potential protective coatings without loss in the heat-transfer efficiency of the coated system. Second, materials with thermal conductivities less than the critical values of 25 or 50 W/m/K are more likely to act as thermal barrier coatings. The deposition of overlay coatings on GRCop-84 substrates results in the development of residual stresses. The presence of these residual stresses influences the probability of coating spallation, the thermal cycling life, and the fatigue properties of the coated substrate during use. Since it is important to understand how these stresses develop during the vacuum-plasma-spraying coating deposition process, the nature and magnitudes of the cool-down residual stresses were calculated and compared with experimentally determined values across the coated cross section of a disk specimen. The calculations were conducted assuming that the specimen cools down to room temperature from vacuum plasma-spraying temperatures of either 250 or 650 C. The effects of coating the substrate with and without grit blasting were also theoretically examined. The final graph compares the predicted and the experimental results for a GRCop-84 disk coated with about a 50- m-thick Ni bond coat and a 75- to 100- m NiAl top coat, where the curves for NASA-2 assume the presence of a prior residual stress generated by grit blasting under conditions similar to the experimental situation. The predicted cool-down in-plane stresses were compressive in both the NiAl top coat and the Ni bond coat. They were also compressive in the substrate to a depth of about 0.25 mm from the Ni/GRCop-84 interface when the vacuum-plasma-spraying temperature was low. However, using a higher plasma spraying temperaturs likely to leave the substrate under a small tensile stress to counter the compressive stresses in the bond and top coats because of the relaxation of residual stresses generated in the substrate during the grit blasting of its surface prior to spraying. These results suggest that the NiAl and Ni coatings are unlikely to spall after spraying as confirmed by the microstructural observations shown in the following photomicrograph of an as-sprayed specimen. Finally, it is noted that the calculated and experimental results are not in complete agreement, which indicates that both the experimental and modeling techniques need further refinement.

Raj, Sai V.↗

Vibration Monitoring Techniques Applied to Detect Damage in Rotating Disks

Rotor health monitoring and online damage detection are increasingly gaining the interest of the manufacturers of aircraft engines. This is primarily due to the need for improved safety during operation as well as the need for lower maintenance costs. Applied techniques for detecting damage in and monitoring the health of rotors are essential for engine safety, reliability, and life prediction. The goals of engine safety are addressed within the NASA-sponsored Aviation Safety Program (AvSP). AvSP provides research and technology products needed to help the Federal Aviation Administration and the aerospace industry improve aviation safety. The Nondestructive Evaluation Group at the NASA Glenn Research Center is addressing propulsion health management and the development of propulsion-system-specific technologies intended to detect potential failures prior to catastrophe.

Gyekenyesi, Andrew L.↗

Design of an orbital debris radar ground demonstration

A breadboard radar system is being designed and tested at NASA Johnson for dealing with the space debris problem that could present a growing threat to Space Station Freedom. The major design problems are due to the small radar cross section of such debris (below -30 dBm2), the high closing velocities of the particles with respect to the Space Station (10 km/sec and higher), and the stringent weight, power-consumption, maintenance, and reliability constraints on spaceborne systems. Consideration is given to the preliminary implementation of a ground demonstration radar for testing concepts, technologies, and performance envelopes for application to the space-borne debris detection and tracking radar. Simulation results and techniques developed for predicting system performance and for evaluating antenna parameters are given. The design process of the electronically steered phased array antenna is briefly described, and block diagrams for the implementation of the radar system are given.

Paz, I.↗

Monitoring System for Storm Readiness and Recovery of Test Facilities: Integrated System Health Management (ISHM) Approach

Severe weather events are likely occurrences on the Mississippi Gulf Coast. It is important to rapidly diagnose and mitigate the effects of storms on Stennis Space Center's rocket engine test complex to avoid delays to critical test article programs, reduce costs, and maintain safety. An Integrated Systems Health Management (ISHM) approach and technologies are employed to integrate environmental (weather) monitoring, structural modeling, and the suite of available facility instrumentation to provide information for readiness before storms, rapid initial damage assessment to guide mitigation planning, and then support on-going assurance as repairs are effected and finally support recertification. The system is denominated Katrina Storm Monitoring System (KStorMS). Integrated Systems Health Management (ISHM) describes a comprehensive set of capabilities that provide insight into the behavior the health of a system. Knowing the status of a system allows decision makers to effectively plan and execute their mission. For example, early insight into component degradation and impending failures provides more time to develop work around strategies and more effectively plan for maintenance. Failures of system elements generally occur over time. Information extracted from sensor data, combined with system-wide knowledge bases and methods for information extraction and fusion, inference, and decision making, can be used to detect incipient failures. If failures do occur, it is critical to detect and isolate them, and suggest an appropriate course of action. ISHM enables determining the condition (health) of every element in a complex system-of-systems or SoS (detect anomalies, diagnose causes, predict future anomalies), and provide data, information, and knowledge (DIaK) to control systems for safe and effective operation. ISHM capability is achieved by using a wide range of technologies that enable anomaly detection, diagnostics, prognostics, and advise for control: (1) anomaly detection algorithms and strategies, (2) fusion of DIaK for anomaly detection (model-based, numerical, statistical, empirical, expert-based, qualitative, etc.), (3) diagnostics/prognostics strategies and methods, (4) user interface, (5) advanced control strategies, (6) integration architectures/frameworks, (7) embedding of intelligence. Many of these technologies are mature, and they are being used in the KStorMS. The paper will describe the design, implementation, and operation of the KStorMS; and discuss further evolution to support other needs such as condition-based maintenance (CBM).

Figueroa, Fernando↗

A software technology evaluation program

A set of quantitative approaches is presented for evaluating software development methods and tools. The basic idea is to generate a set of goals which are refined into quantifiable questions which specify metrics to be collected on the software development and maintenance process and product. These metrics can be used to characterize, evaluate, predict, and motivate. They can be used in an active as well as passive way by learning form analyzing the data and improving the methods and tools based upon what is learned from that analysis. Several examples were given representing each of the different approaches to evaluation. The cost of the approaches varied inversely with the level of confidence in the interpretation of the results.

Novaes-Card, David N.↗