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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Scattering through a straight quantum waveguide with combined boundary conditions

Scattering through a straight two-dimensional quantum waveguide R×(0,d) with Dirichlet boundary conditions on (R{sub −}{sup *}×(y=0))∪(R{sub +}{sup *}×(y=d)) and Neumann boundary condition on (R{sub −}{sup *}×(y=d))∪(R{sub +}{sup *}×(y=0)) is considered using stationary scattering theory. The existence of a matching conditions solution at x = 0 is proved. The use of stationary scattering theory is justified showing its relation to the wave packets motion. As an illustration, the matching conditions are also solved numerically and the transition probabilities are shown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Growth condition dependence of photoluminescence polarization in (100) GaAs/AlGaAs quantum wells at room temperature

We conducted systematic measurements on the carrier lifetime (τ{sub c}), spin relaxation time (τ{sub s}), and circular polarization of photoluminescence (P{sub circ}) in (100) GaAs/AlGaAs multiple quantum wells grown by molecular beam epitaxy (MBE). The τ{sub c} values are strongly affected by MBE growth conditions (0.4–9 ns), whereas the τ{sub s} are almost constant at about 0.13 ns. The result suggests that spin detection efficiency [τ{sub s}/(τ{sub c} + τ{sub s})], which is expected to be proportional to a steady-state P{sub circ}, is largely dependent on growth condition. We confirmed that the P{sub circ} has similar dependence on growth condition to those of τ{sub s}/(τ{sub c} + τ{sub s}) values. The study thus indicates that choosing the appropriate growth condition of the QW is indispensable for obtaining a high P{sub circ} from a spin-polarized light-emitting diode (spin-LED)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Boundary conditions at the walls with thermionic electron emission in two temperature modeling of “thermal” plasmas

In this paper, we propose new boundary conditions for the electric potential, the electron energy equation, and the energy equation for heavy particles (ions and neutrals) at the hot walls with thermionic electron emission for two-temperature thermal arc models. The derived boundary conditions assume that the walls are made from refractory metals and, consequently, the erosion of the wall is small and can be neglected. In these boundary conditions, the plasma sheath formed at the electrode is viewed as the interface between the plasma and the wall. The derived boundary conditions allow the calculation of the heat flux to the walls from the plasma. This allows the calculation of the thermionic electron current that makes the model of electrode-plasma interaction self-consistent.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

The inverse problem of recovering the source in a parabolic equation under a condition of nonlocal observation

We study the inverse problem for a parabolic equation of recovering the source, that is, the right-hand side F(x,t)=h(x,t)f(x), where the function f(x) is unknown. To find f(x), along with the initial and boundary conditions, we also introduce an additional condition of nonlocal observation of the form ∫{sub 0}{sup T}u(x,t) dμ(t)=χ(x). We prove the Fredholm property for the problem stated in this way, and obtain sufficient conditions for the existence and uniqueness of a solution. These conditions are of the form of readily verifiable inequalities and put no restrictions on the value of T>0 or the diameter of the domain Ω under consideration. The proof uses a priori estimates and the qualitative properties of solutions of initial-boundary value problems for parabolic equations. Bibliography: 40 titles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Cable Condition Monitoring Strategy for Safe and Reliable Plant Operation

Electrical cables provide essential functions, such as delivery of power or instrumentation signals for monitoring systems. Most cables installed in industrial applications are constructed with organic polymer insulations that can become brittle, crack, or degrade over time from exposure to harsh environmental conditions, such as elevated temperatures, moisture, vibration, mechanical shock, and radiation. This paper describes an overall strategy for assessing the health and managing the aging of cables during the operating life of an industrial facility. This strategy involves performing condition assessments and monitoring of electrical cables using both in situ and laboratory testing techniques. It includes in situ testing to identify anomalies in the circuits, such as degraded terminations, splices, connections, and degraded sections of cable insulation, as well as as-found evaluations to determine the current condition of installed cables. Furthermore, these cable condition evaluations provide important information about the current state of the cable circuits. Moreover, the test results can be used to trend/monitor age-related degradation and estimate the remaining useful life of installed cables.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Visualization of R410A Flow Boiling Inside Horizontal Smooth Tubes under Diabatic Conditions

This article presents a novel approach to visualize the flow boiling in round tubes under “diabatic conditions”. In the visualization test section, a 3D printed round tube is placed inside a glass tube with secondary fluid at a higher temperature flowing in the annulus between the two tubes thus providing diabatic conditions. Experimental work was conducted for evaporating R410A flow in a horizontal smooth round tube with the inner diameter of 6.3 mm. Compared to the traditional adiabatic visualization technique, the more realistic evaporative condition is simulated and the developing evaporation process is captured. New insights for the flow behavior at low vapor quality are brought by this diabatic method. The vapor plug occurs at very low vapor quality, and this is attributed to the coalescence of bubbles generated on the heated tube wall. For the intermittent flow, liquid slug triggered by Kelvin–Helmholtz instability affects the nucleation on the tube wall. It brings the fresh liquid to rewet the dry surface and activate the nucleation sites. Finally, heat flux condition affects the heat transfer mechanisms during the flow boiling, and the heat transfer through the nucleate boiling mechanism increases as the heat flux increases.

3D printed↗
DOE OSTI2024

Robust errant beam prognostics with conditional modeling for particle accelerators

Abstract Particle accelerators are complex and comprise thousands of components, with many pieces of equipment running at their peak power. Consequently, they can fault and abort operations for numerous reasons, lowering efficiency and science output. To avoid these faults, we apply anomaly detection techniques to predict unusual behavior and perform preemptive actions to improve the total availability. Supervised machine learning (ML) techniques such as siamese neural network models can outperform the often-used unsupervised or semi-supervised approaches for anomaly detection by leveraging the label information. One of the challenges specific to anomaly detection for particle accelerators is the data’s variability due to accelerator configuration changes within a production run of several months. ML models fail at providing accurate predictions when data changes due to changes in the configuration. To address this challenge, we include the configuration settings into our models and training to improve the results. Beam configurations are used as a conditional input for the model to learn any cross-correlation between the data from different conditions and retain its performance. We employ conditional siamese neural network (CSNN) models and conditional variational auto encoder (CVAE) models to predict errant beam pulses at the spallation neutron source under different system configurations and compare their performance. We demonstrate that CSNNs outperform CVAEs in our application.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Order conditions for nonlinearly partitioned Runge-Kutta methods

Recently, a new class of nonlinearly partitioned Runge–Kutta (NPRK) methods was proposed for nonlinearly partitioned systems of autonomous ordinary differential equations y' = F(y, y). The target class of problems are those in which different scales, stiffnesses, or physics are coupled in a nonlinear way, wherein the desired partition cannot be written in a classical additive or component-wise fashion. Here we use a rooted-tree analysis to derive full-order conditions for NPRKM methods, where M denotes the number of nonlinear partitions. Due to the nonlinear coupling and thereby the mixed product differentials, it turns out that the standard node-colored rooted tree analysis used in analyzing ODE integrators does not naturally apply. Instead we develop a new edge-colored rooted-tree framework to address the nonlinear coupling. The resulting order conditions are enumerated, are provided directly for up to fourth order with M = 2 and third order with M = 3, and are related to existing order conditions of additive and partitioned RK methods. We conclude with an example that shows how the nonlinear order conditions can be used to obtain an embedded estimate of the state-dependent nonlinear coupling strength in a dynamical system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Final Technical Report Recovery Act: Online Nonintrusive Condition Monitoring and Fault Detection for Wind Turbines

The penetration of wind power has increased greatly over the last decade in the United States and across the world. The U.S. wind power industry installed 1,118 MW of new capacity in the first quarter of 2011 alone and entered the second quarter with another 5,600 MW under construction. By 2030, wind energy is expected to provide 20% of the U.S. electricity needs. As the number of wind turbines continues to grow, the need for effective condition monitoring and fault detection (CMFD) systems becomes increasingly important [3]. Online CMFD is an effective means of not only improving the reliability, capacity factor, and lifetime, but it also reduces the downtime, energy loss, and operation and maintenance (O&M) of wind turbines. The goal of this project is to develop novel online nonintrusive CMFD technologies for wind turbines. The proposed technologies use only the current measurements that have been used by the control and protection system of a wind turbine generator (WTG); no additional sensors or data acquisition devices are needed. Current signals are reliable and easily accessible from the ground without intruding on the wind turbine generators (WTGs) that are situated on high towers and installed in remote areas. Therefore, current-based CMFD techniques have great economic benefits and the potential to be adopted by the wind energy industry. Specifically, the following objectives and results have been achieved in this project: (1) Analyzed the effects of faults in a WTG on the generator currents of the WTG operating at variable rotating speed conditions from the perspective of amplitude and frequency modulations of the current measurements; (2) Developed effective amplitude and frequency demodulation methods for appropriate signal conditioning of the current measurements to improve the accuracy and reliability of wind turbine CMFD; (3) Developed a 1P-invariant power spectrum density (PSD) method for effective signature extraction of wind turbine faults with characteristic frequencies in the current or current demodulated signals, where 1P stands for the shaft rotating frequency of a WTG; (4) Developed a wavelet filter for effective signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (5) Developed an effective adaptive noise cancellation method as an alternative to the wavelet filter method for signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (6) Developed a statistical analysis-based impulse detection method for effective fault signature extraction and evaluation of WTGs based on the 1P-invariant PSD of the current or current demodulated signals; (7) Validated the proposed current-based wind turbine CMFD technologies through extensive computer simulations and experiments for small direct-drive WTGs without gearboxes; and (8) Showed, through extensive experiments for small direct-drive WTGs, that the performance of the proposed current-based wind turbine CMFD technologies is comparable to traditional vibration-based methods. The proposed technologies have been successfully applied for detection of major failures in blades, shafts, bearings, and generators of small direct-drive WTGs. The proposed technologies can be easily integrated into existing wind turbine control, protection, and monitoring systems and can be implemented remotely from the wind turbines being monitored. The proposed technologies provide an alternative to vibration-sensor-based CMFD. This will reduce the cost and hardware complexity of wind turbine CMFD systems. The proposed technologies can also be combined with vibration-sensor-based methods to improve the accuracy and reliability of wind turbine CMFD systems. When there are problems with sensors, the proposed technologies will ensure proper CMFD for the wind turbines, including their sensing systems. In conclusion, the proposed technologies offer an effective means to achieve condition-based smart maintenance for wind turbines and have a great potential to be adopted by the wind energy industry due to their almost no-cost, nonintrusive features. Although only validated for small direct-drive wind turbines without gearboxes, the proposed technologies are also applicable for CMFD of large-size wind turbines with and without gearboxes. However, additional investigations are recommended in order to apply the proposed technologies to those large-size wind turbines.

17 WIND ENERGY↗
DOE OSTI2016

Rate Theory Modeling and Simulation of Silicide Fuel at LWR Conditions

As a promising candidate for the accident tolerant fuel (ATF) used in light water reactors (LWRs), the fuel performance of uranium silicide (U 3 Si 2 ) at LWR conditions needs to be well understood. In this report, rate theory model was developed based on existing experimental data and density functional theory (DFT) calculations so as to predict the fission gas behavior in U 3 Si 2 at LWR conditions. The fission gas behavior of U 3 Si 2 can be divided into three temperature regimes. During steady-state operation, the majority of the fission gas stays in intragranular bubbles, whereas the dominance of intergranular bubbles and fission gas release only occurs beyond 1000 K. The steady-state rate theory model was also used as reference to establish a gaseous swelling correlation of U 3 Si 2 for the BISON code. Meanwhile, the overpressurized bubble model was also developed so that the fission gas behavior at LOCA can be simulated. LOCA simulation showed that intragranular bubbles are still dominant after a 70 second LOCA, resulting in a controllable gaseous swelling. The fission gas behavior of U 3 Si 2 at LWR conditions is benign according to the rate theory prediction at both steady-state and LOCA conditions, which provides important references to the qualification of U 3 Si 2 as a LWR fuel material with excellent fuel performance and enhanced accident tolerance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 1

Due to continuing global energy market trends, driven heavily by the abundant preserves of natural gas, there is an immediate need to reduce costs associated with operation and maintenance (O&M) for the current domestic nuclear power industry and for future reactor developments. This is to ensure that nuclear power generation remains an economically competitive and viable option in the energy market. O&M costs include labor-intensive preventive maintenance (PM) programs, which involve manually-performed inspection, calibration, testing, and maintenance of plant assets at periodic frequency and time-based replacement of assets, irrespective of their condition. This has resulted in an expensive, labor-centric business model to achieve high capacity factors. Fortunately, there are technologies (advanced sensors, data analytics, and risk assessment methodologies) that can enable the transition from a labor-centric business model to a technology-centric business model. The technology-centric business model will result in a significant reduction of PM activities, laying the foundation for real-time condition assessment of plant assets, reducing overall labor and part costs. To enable this transition, PKMJ Technical Services LLC is partnering with the U.S. Department of Energy’s Idaho National Laboratory (operated by the Battelle Energy Alliance, LLC) and the Public Services Enterprise Group (PSEG) Nuclear, LLC in the Integrated Risk-Informed Condition-Based Maintenance Capability and Automated Platform Project. In this report, the configuration of a digital cloud platform using Microsoft Azure is discussed, data from the PSEG Salem Nuclear Generating Station Units 1 & 2 are imported into a digital cloud platform, and the data is used for an evaluation of several key areas: cost impact analysis, risk-informed model development, and preventive maintenance strategy optimization. First, the cost impact analysis reviews which plant assets are potential good candidates for condition-based monitoring. Next, INL utilized the data in their local environment to develop the risk-informed model; which provides estimates of failure rates and probability of failures of assets based upon their past performance. The developed model is performed on assets selected from the cost impact analysis. Lastly, engineers assess the preventive maintenance strategy for the selected assets at PSEG against maintenance strategies in the nuclear industry for similar assets to potentially identify acceptable justification for the extension of current maintenance frequencies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Wind Turbine Gearbox Condition Monitoring Vibration Analysis Benchmarking Datasets

Wind turbine condition monitoring (CM) can potentially help the wind industry reduce turbine downtime and operation and maintenance (O&M) cost. NREL CM research has investigated various condition-monitoring techniques such as acoustic emission (AE specifically stress wave), vibration, electrical signature, lubricant and debris monitoring based on the Gearbox Reliability Collaborative dynamometer and field tests, and other test turbines and resources accessible by NREL. During the past several years, NREL CM research has shown that there are very few validation and verification efforts on commercial wind turbine CM systems. One of the reasons might be limited benchmarking datasets accessible by stakeholders. To fill this gap, NREL executed a data collection effort. The targeted users of these datasets include those investigating vibration-based wind turbine CM research, evaluating commercially available vibration-based CM systems, or testing prototyped vibration-based CM systems. NREL collected data from a healthy and a damaged gearbox of the same design tested by the GRC. Vibration data were collected by accelerometers along with high-speed shaft RPM signals during the dynamometer testing. The healthy gearbox was only tested in the dynamometer. The damaged gearbox was first tested in the dynamometer and later sent to a wind farm close to NREL for field testing. In the field test, it experienced two loss-of-oil events that damaged its internal bearings and gear elements. The gearbox was brought back to NREL and it was retested in the dynamometer with CM systems deployed under controlled loading conditions that would not cause catastrophic failure of the gearbox. The objective of releasing these datasets to the public along with information about the real damage that occurred to the damaged gearbox is to provide the wind industry with some benchmarking datasets. These datasets will benefit research, development, validation, verification, and advancement of vibration-based wind condition-monitoring techniques. By accessing this data you acknowledge the terms outlined in the "License Information" document. Please contract Shawn Sheng (NREL) if you have any questions on the data or would like to collaborate on publications based on the datasets.

Array↗
DOE OSTI2020

An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions

Wind profiling by Doppler lidar is common practice and highly useful in a wide range of applications. Airborne Doppler lidar can provide additional insights relative to ground-based systems by allowing for spatially distributed and targeted measurements. Providing a link between theory and measurement, a first large eddy simulation (LES)-based airborne Doppler lidar simulator (ADLS) has been developed. Simulated measurements are conducted based on LES wind fields, considering the coordinate and geometric transformations applicable to real-world measurements. The ADLS provides added value as the input truth used to create the measurements is known exactly, which is nearly impossible in real-world situations. Thus, valuable insight can be gained into measurement system characteristics as well as retrieval strategies. As an example application, airborne Doppler lidar wind profiling is investigated using the ADLS. For commonly used airborne velocity azimuth display (AVAD) techniques, flow homogeneity is assumed throughout the retrieval volume, a condition which is violated in turbulent boundary layer flow. Assuming an ideal measurement system, the ADLS allows to isolate and evaluate the error in wind profiling which occurs due to the violation of the flow homogeneity assumption. Overall, the ADLS demonstrates that wind profiling is possible in turbulent wind field conditions with reasonable errors (root mean squared error of 0.36 m s –1 for wind speed when using a commonly used system setup and retrieval strategy for the conditions investigated). Nevertheless, flow inhomogeneity, e.g., due to boundary layer turbulence, can cause an important contribution to wind profiling error and is non-negligible. Results suggest that airborne Doppler lidar wind profiling at low wind speeds (<5 m s –1 ) can be biased, if conducted in regions of inhomogeneous flow conditions.

17 WIND ENERGY↗
NASA NTRS2012

Survival of B. Horneckiae Spores Under Ground-simulated Space Conditions

To prevent forward contamination and maintain the scientific integrity of future life detection missions, it is important to characterize and attempt to eliminate terrestrial microorganisms associated with exploratory spacecraft and landing vehicles. Among the organisms isolated from spacecraft-associated habitats, spore-forming microbes are highly resistant to various physical and chemical conditions, which include ionizing and UV radiation, desiccation and oxidative stress, and the harsh environment of outer space or planetary surfaces. Recently a radiation resistant, spore forming bacterial isolate, Bacillus horneckiae, was isolated from a clean room of the Kennedy Space Center where the Phoenix spacecraft was assembled. The exceptionally high tolerance of extreme conditions demonstrated by sporeforming bacteria highlighted the need to assess the viability of these microbes in situ (in real) space. The proposed BOSS (Biofilm Organisms Surfing Space) project aims to understand the mechanisms by which biofilm forming organisms, such as B. horneckiae, will potentially be able to withstand harsh space conditions. As previously stated, the spore producing ability of these species gives them increased survivability to harsh conditions. Some of the spores will have the protective exosporium layer artificially removed before the test to determine if the existence of this layer significantly changes the survivability during the mission. In preparation for that experiment, we analyzed spores which were exposed during a ground simulation, the EXPOSE R2 Biofilm Organisms Surfing Space (BOSS). Previous to exposure, spores were deposited onto spacecraft grade aluminum coupons in a spore suspension calculated to contain between 10(exp 7) and 10(exp 8) spores. This precursor series will be used to establish a baseline survivability function for comparison with the future flight tests during EXPOSE-R. For each coupon, a 10% polyvinyl alcohol (PVA) film was applied and peeled from the coupon to recover the spores. One hundred μl of sterile 10% PVA was applied to the surface of the coupon and allowed to dry for 1 hour at 37 C. The films were then removed using sterile scalpel and forceps and placed into a glass test tube containing 2 milliliters of sterile deionized water. The PVA film process was then repeated on each coupon one additional time to ensure recovery of the majority of spores. The second PVA film was added in the same glass tube as in the previous round. If the spores remained 100% viable, the test tubes should now contain between 5 X 10(exp 6) and 5 X 10(exp 7) spores per millimeter; however, it is expected that some loss of viability has occurred. In order to assess this loss, the number of colony forming, viable spores was counted. To count the colony forming units (CFUs), the spore containing solution was diluted in a process of 10-fold serial dilution by mixing successive solutions in a 100 microliter spore suspension to 900 microliter deionized H2O ratio. A sample dilution series revealed that 10(exp -3) and 10(exp -4) concentrations would be necessary for an accurate CFU count to be taken. For those two concentrations, a spread on a TSA plate was prepared and incubated at 32 C. For the samples exposed to UV radiation, the cell survivability was too low to establish a count from 100 microliter spread plating. Instead, no dilutions were performed and the entire 2 milliliter spore suspension was plated and incubated at 32 C. The plate's CFU counts were taken at 24 hours and 48 hours from the time of plating. At the end of the CFU counting the total surviving spores in each sample were calculated based on the number of CFUs that were observed per 100 microliters, or per 2 milliliters for the UV irradiated samples. The results of these calculations are shown in Figures 1 and 2.

cleanroom↗
NASA NTRS2020

INVESTIGATING THE FEASIBILITY AND STABILITY FOR MODELING ACOUSTIC WAVE SCATTERING USING A TIME-DOMAIN BOUNDARY INTEGRAL EQUATION WITH IMPEDANCE BOUNDARY CONDITION

Reducing aircraft noise is a major objective in the field of computational aeroacoustics. When designing next generation quiet and environmentally friendly aircraft, it is important to be able to accurately and efficiently predict the acoustic scattering by an aircraft body from a given noise source. Acoustic liners are an effective tool for aircraft noise reduction and are characterized by a frequency-dependent impedance. Converted into the time-domain using Fourier transforms, an impedance boundary condition can be used to simulate the acoustic wave scattering by geometric bodies treated with acoustic liners. This work considers using either an impedance or an admittance (inverse of impedance) boundary condition to allow for acoustic scattering problems to be modeled with geometries consisting of both un-lined and lined surfaces. Three acoustic liner models are discussed: the Extended Helmholtz Resonator Model, the Three-Parameter Impedance Model, and the Broadband Impedance Model. In both the Helmholtz and Three-Parameter models, liner impedance is specified at a given frequency, whereas the Broadband model allows for the investigation of multiple frequencies simultaneously. The impedance and admittance boundary conditions for acoustic liners are derived for each model and coupled with a time-domain boundary integral equation. The scattering solution is obtained iteratively using a boundary element method with constant spatial and third-order temporal basis functions. Time-domain boundary integral equations are unfortunately prone to numerical instabilities due to resonant frequencies resulting from non-trivial solutions in the interior domain. When reformulated with the Burton-Miller method, the instabilities are eliminated. Using a Burton-Miller reformulation, the stability of the boundary element method assuming a liner boundary condition is assessed using eigenvalue analysis. The stability of each liner model is discussed, and it is shown that the Three-Parameter and Broadband models are sufficient for modeling an acoustic liner on the surface of scattering bodies. The Helmholtz model demonstrates strict limitations for stability, whereas the Three-Parameter and Broadband models are stable for most cases. Also included in this work is an assessment of the spatial accuracy of the time-domain boundary element method with respect to the surface element basis functions, as well as a performance study of the numerical algorithm.

computational mathematics↗
NASA NTRSDate not supplied

An Extension of the Truncated Ingard-Myers Impedance Boundary Condition for High Mach Number Grazing Flows

The Ingard-Myers impedance boundary condition is widely recognized to be prone to hydrodynamic Kelvin-Helmholtz-type instability, primarily due to its use of a vortex sheet to model the flow at the boundary. Recently, a stabilized approximation of the Ingard-Myers condition, called the Truncated Ingard-Myers Impedance Boundary Condition (TIMIBC), has been introduced. This approximation offers a good representation of the Ingard-Myers condition for grazing flows characterized by low to mid subsonic Mach numbers. This paper explores an extension of the TIMIBC, referred to as TIMIBC-ext, designed for liners in grazing flows with high subsonic Mach numbers. The TIMIBC-ext introduces a tunable parameter and demonstrates that by judiciously selecting the parameter value, the accuracy of the TIMIBC can be improved for either upstream or downstream propagating waves in grazing flows with high subsonic Mach numbers. Consequently, the TIMIBC-ext represents an enhancement to the TIMIBC when the location of the source relative to the liner (upstream or downstream) is known. Time domain implementations of the TIMIBC-ext are also provided, employing a multipole expansion model for the impedance function. A numerical example is provided to assess the performance of the TIMIBC-ext, comparing computational results with measurements from a recent set of measurements in the NASA Langley Grazing Flow Impedance Tube.

time domain acoustic scattering↗
DOE OSTI2012

Online Condition Monitoring to Enable Extended Operation of Nuclear Power Plants

Safe, secure, and economic operation of nuclear power plants will remain of strategic significance. New and improved monitoring will likely have increased significance in the post-Fukushima world. Prior to Fukushima, many activities were already underway globally to facilitate operation of nuclear power plants beyond their initial licensing periods. Decisions to shut down a nuclear power plant are mostly driven by economic considerations. Online condition monitoring is a means to improve both the safety and economics of extending the operating lifetimes of nuclear power plants, enabling adoption of proactive aging management. With regard to active components (e.g., pumps, valves, motors, etc.), significant experience in other industries has been leveraged to build the science base to support adoption for online condition-based maintenance and proactive aging management in the nuclear industry. Many of the research needs are associated with enabling proactive management of aging in passive components (e.g., pipes, vessels, cables, containment structures, etc.). This paper provides an overview of online condition monitoring for the nuclear power industry with an emphasis on passive components. Following the overview, several technology/knowledge gaps are identified, which require addressing to facilitate widespread online condition monitoring of passive components.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗