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209 records · Page 12

Environmentally Compatible Vapor-Phase Corrosion Inhibitor for Space Shuttle Hardware

USA-SRB Element is responsible for the assembly and refurbishment of the non-motor components of the SRB as part of Space Shuttle. Thrust Vector Control (TVC) frames structurally support components of the TVC system located in the aft skirt of the SRB. TVC frames are exposed to the seacoast environment after refurbishment and, also, to seawater immersion after splashdown, and during tow-back to CCAFS-Hangar AF refurbishment facilities. During refurbishment operations it was found that numerous TVC frames were experiencing internal corrosion and coating failures, both from salt air and seawater intrusions. Inspectors using borescopes would visually examine the internal cavities of the complicated aluminum alloy welded tubular structure. It was very difficult for inspectors to examine cavity corners and tubing intersections and particularly, to determine the extent of the corrosion and coating anomalies. Physical access to TVC frame internal cavities for corrosion removal and coating repair was virtually impossible, and an improved method using a Liquid (water based) Vapor-phase Corrosion Inhibitor (LVCI) for preventing initiation of new corrosion, and mitigating and/or stopping existing corrosion growth was recommended in lieu of hazardous paint solvents and high VOC/solvent based corrosion inhibitors. In addition, the borescopic inspection method used to detect corrosion, and/or coating anomalies had severe limitations because of part geometry, and an improved non-destructive inspection (NDI) method using Neutron Radiography (N-Ray) was also recommended.

Novak, Howard L.↗

Environmentally Compatible Vapor-Phase Corrosion Inhibitor for Space Shuttle Hardware

USA-SRB Element is responsible for the assembly and refurbishment of the non-motor components of the SRB as part of Space Shuttle. Thrust Vector Control (TVC) frames structurally support components of the TVC system located in the aft skirt of the SRB. TVC frames are exposed to the seacoast environment after refurbishment and, also, to seawater immersion after splashdown, and during tow-back to CCAFS-Hangar AF refurbishment facilities. During refurbishment operations it was found that numerous TVC frames were experiencing internal corrosion and coating failures, both from salt air and seawater intrusions. Inspectors using borescopes would visually examine the internal cavities of the complicated aluminum alloy welded tubular structure. It was very difficult for inspectors to examine cavity corners and tubing intersections and particularly, to determine the extent of the corrosion and coating anomalies. Physical access to TVC frame internal cavities for corrosion removal and coating repair was virtually impossible, and an improved method using a Liquid (water based) Vapor-phase Corrosion Inhibitor (LVCI) for preventing initiation of new corrosion, and mitigating and/or stopping existing corrosion growth was recommended in lieu of hazardous paint solvents and high VOC / solvent based corrosion inhibitors. In addition, the borescopic inspection method used to detect corrosion, and/or coating anomalies had severe limitations because of part geometry, and an improved non-destructive inspection (NDI) method using Neutron Radiography (N-Ray) was also recommended.

Novak, Howard L.↗

Environmentally Compatible Vapor-Phase Corrosion Inhibitor for Space Shuttle Hardware

USA-SRB Element is responsible for the assembly and refurbishment of the non-motor components of the SRB as part of Space Shuttle. Thrust Vector Control (TVC) frames structurally support components of the TVC system located in the aft skirt of the SRB (Solid Rocket Booster). TVC frames are exposed to the seacoast environment after refurbishment and, also, to seawater immersion after splashdown, and during tow-back to CCAFS-Hangar AF refurbishment facilities. During refurbishment operations it was found that numerous TVC frames were experiencing internal corrosion and coating failures, both from salt air and seawater intrusions. Inspectors using borescopes would visually examine the internal cavities of the complicated aluminum alloy welded tubular structure. It was very difficult for inspectors to examine cavity corners and tubing intersections and particularly. to determine the extent of the corrosion and coating anomalies. Physical access to TVC frame internal cavities for corrosion removal and coating repair was virtually impossible, and an improved method using a Liquid (water based) Vapor-phase Corrosion Inhibitor (LVCI) for preventing initiation of new corrosion, and mitigating and/or stopping existing corrosion growth was recommended in lieu of hazardous paint solvents and high VOC/solvent based corrosion inhibitors. In addition, the borescopic inspection method used to detect corrosion, and/or coating anomalies had severe limitations because of part geometry, and an improved non-destructive inspection (NDI) method using Neutron Radiography (N-Ray) was also recommended.

Novak, Howard L.↗

Quantitative Measurement of Oxygen in Microgravity Combustion

A low-gravity environment, in space or in ground-based facilities such as drop towers, provides a unique setting for studying combustion mechanisms. Understanding the physical phenomena controlling the ignition and spread of flames in microgravity has importance for space safety as well as for better characterization of dynamical and chemical combustion processes which are normally masked by buoyancy and other gravity-related effects. Due to restrictions associated with performing measurements in reduced gravity, diagnostic methods which have been applied to microgravity combustion studies have generally been limited to capture of flame emissions on film or video, laser Schlieren imaging and (intrusive) temperature measurements using thermocouples. Given the development of detailed theoretical models, more sophisticated diagnostic methods are needed to provide the kind of quantitative data necessary to characterize the properties of microgravity combustion processes as well as provide accurate feedback to improve the predictive capabilities of the models. When the demands of space flight are considered, the need for improved diagnostic systems which are rugged, compact, reliable, and operate at low power becomes apparent. The objective of this research is twofold. First, we want to develop a better understanding of the relative roles of diffusion and reaction of oxygen in microgravity combustion. As the primary oxidizer species, oxygen plays a major role in controlling the observed properties of flames, including flame front speed (in solid or liquid flames), extinguishment characteristics, flame size and flame temperature. The second objective is to develop better diagnostics based on diode laser absorption which can be of real value in both microgravity combustion research and as a sensor on-board Spacelab as either an air quality monitor or as part of a fire detection system. In our prior microgravity work, an eight line-of-sight fiber optic system measured water vapor mole fractions in the NASA Lewis 2.2-sec Drop Tower. In that system, the laser and all electronics resided at the top of the drop tower and was connected via a fiber optic cable to the rig, on which a 'pitch and catch' set of fiber collimating lenses were used to transmit the laser beam across a jet diffusion flame. This system required eight independent detection/demodulation units and had poor spatial resolution. This research builds on this earlier work, resulting in an improved capability for quantitative, nonintrusive measurement of major combustion species. A vertical cavity surface-emitting diode laser (VCSEL) and a continuous spatial scanning method permit the measurement of temporal and spatial profiles of the concentrations and temperatures of molecular oxygen. High detection sensitivity is achieved with wavelength modulation spectroscopy (WMS). One-g experiments are performed using a slot diffusion flame. Microgravity measurements on a solid fuel (cellulose sheet) system are planned for the NASA Lewis 2.2-second Drop Tower Facility.

Silver, Joel A.↗

Model-Based Diagnostics and Mitigation of Cyber Threats

The report summarizes key tasks performed to develop a toolkit for detecting cyber-attack events in instrumentation and control (I&C) systems of nuclear power plants. The toolkit connects the state-of-the-art GPWR Simulator with the RELAP5 code providing best-estimate nuclear steam supply system (NSSS) analyses, via the application programming interface (API), and allows users to introduce potential cyber-attack scenarios into power plant operational simulation. This summary for the project reflects topical reports submitted during the project as well as a journal paper published in 2022. The focus areas of the summary include: (1) modeling I&C systems for the AP1000 Generation III+ nuclear plant and GPWR simulator, (2) simulation and monitoring of plant response to cyber-attack events, (3) API structure for the toolkit interfacing the GPWR simulator and RELAP5 code, and (4) restructuring of the three-loop NSSS software of GPWR to model the two-loop AP1000 structure. Discussed in some details are (a) the attack tree analysis assessing the susceptibility of the AP1000 I&C system, resulting in reactor trips, in terms of the attack possibility and component sensitivity and (b) realistic estimation of the time to steam generator trip due to cyber-intrusions in the GPWR Simulator. Finally, sample demonstrations of the cyber-security tool kit, in the form of the GPWR-RELAP5 API, are summarized.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

PFLOTRAN-SIP: A PFLOTRAN Module for Simulating Spectral-Induced Polarization of Electrical Impedance Data

Spectral induced polarization (SIP) is a non-intrusive geophysical method that collects chargeability information (the ability of a material to retain charge) in the time domain or its phase shift in the frequency domain. Although SIP is a temporal method, it cannot measure the dynamics of flow and solute/species transport in the subsurface over long times (i.e., 10–100 s of years). Data collected with the SIP technique need to be coupled with fluid flow and reactive-transport models in order to capture long-term dynamics. To address this challenge, PFLOTRAN-SIP was built to couple SIP data to fluid flow and solute transport processes. Specifically, this framework couples the subsurface flow and transport simulator PFLOTRAN and geoelectrical simulator E4D without sacrificing computational performance. PFLOTRAN solves the coupled flow and solute-transport process models in order to estimate solute concentrations, which were used in Archie’s model to compute bulk electrical conductivities at near-zero frequency. These bulk electrical conductivities were modified while using the Cole–Cole model to account for frequency dependence. Using the estimated frequency-dependent bulk conductivities, E4D simulated the real and complex electrical potential signals for selected frequencies for SIP. These frequency-dependent bulk conductivities contain information that is relevant to geochemical changes in the system. This study demonstrated that the PFLOTRAN-SIP framework is able to detect the presence of a tracer in the subsurface. SIP offers a significant benefit over ERT in the form of greater information content. It provided multiple datasets at different frequencies that better constrained the tracer distribution in the subsurface. Consequently, this framework allows for practitioners of environmental hydrogeophysics and biogeophysics to monitor the subsurface with improved resolution.

54 ENVIRONMENTAL SCIENCES↗

Field Evaluations of Sampling, Interviewing, and Flight Tracking of NASA's Low Boom Flight Demonstrator Aircraft

The first year’s effort identified sampling and interviewing as the principal risks to assessment of prompt reactions to overflights producing low-amplitude sonic booms. It also 1) established the utility of geo-information system-based route planning for LBFD flight missions, 2) developed and demonstrated a prototype of a geographically-distributed, Internet-enabled instrumentation system capable of wide-area tracking of LBFD aircraft in near-real time. The latter system permits synchronizing the conduct of interviews in multiple overflown communities with arrival times of shock waves at interviewing sites; and of measuring, archiving, and processing their acoustic signatures. Means were also recommended for constructing representative, telephone-based samples of eligible respondents living in households within carpet boom corridors adjacent to LBFD flight tracks, and for conducting interviews with cross-sectional (independent) samples of such respondents about their prompt reactions to exposure to low-amplitude sonic booms. A detailed study design was prepared and accepted by NASA for a set of single-contact attempt telephone interviews with a nationally representative sample of households. The study design focused on testing automated and live agent interview completion rates obtainable without callbacks. A minimal (two monitoring station) version of the aircraft tracking system was built and installed near a civil airport in a successful demonstration of the system’s ability to detect and track aircraft movements. The field exercise also demonstrated the ability of the system to capture the acoustic emissions of departing aircraft, and to serve aircraft position and sound level information to remote, geographically-distributed analysts in near-real time. Upon approval of OMB and IRB of the detailed study plan, a stratified, nationally representative sample of landline and wireless telephone-subscribing households was constructed. A total of 12,734 telephone interview contact attempts of the sort required by a straightforward cross-sectional study design were then made. These contact attempts demonstrated the impracticality of conducting a time-critical, cross-sectional study of prompt community response to low-amplitude sonic booms by means of “independent” (single contact attempt per respondent for each LBFD flight mission) telephone samples of respondents. The observed interview completion rates for these single telephone contact attempts were so low (~ 1% to 3% for automated and live agent interviews, respectively) that: 1) the representativeness of collected opinions would be susceptible to intuitive challenge as inadequate, even absent conclusive evidence of non-representativeness. Refuting challenges to representativeness would have to demonstrate that the composition of the actual sample did not differ from that of the target population, a task that is tantamount to proving a negative; 2) the information required to refute allegations of non-representativeness would require a questionnaire considerably lengthier than that required simply to determine the prevalence of boom-induced startle and annoyance. Such a questionnaire would have to inquire about potentially sensitive and intrusive matters, including respondents’ age, gender, education, employment, home ownership, income, ethnicity, family size, and other demographic factors; and 3) unreasonable numbers of attempts would be required to re-contact households with unsuccessful initial contact attempts, given the limited time available for doing so. For example, if about 500 completed interviews were desired in a supersonically overflown community, approximately 50,000 automated interview attempts would have to be made within ten to fifteen minutes of each LBFD overflight. Such large numbers of contact attempts could well exceed the numbers of households available for interview in areas of similar boom exposure levels in some communities near LBFD flight tracks. Such large numbers of interviews could be cost-effectively undertaken only by means of automated (i.e., outgoing interactive voice response) interviewing, a data collection method ill-suited for complex and sensitive questionnaire items. The infeasibility of independent sampling for evaluating prompt responses to LBFD overflights in a cross-sectional study is due in large part to simple non-response: that is, potential respondents – particularly those contacted on wireless telephones – refusing to answer calls with unfamiliar caller IDs. It is also due in part, however, to 1) the lack of time to attempt to contact the same respondent more than once within a few minutes after the arrival of a shock wave at the respondent’s location; and 2) the need to place calls during weekday/daytime hours, when response rates are notably lower than during evenings and weekends. Despite the poor interview completion rates achieved under the above constraints, cross sectional assessments of delayed reactions to LBFD overflights could still be feasible, if multiple attempts could be made to contact respondents during evening and weekend time periods, over extended time periods. Detailed plans for a longitudinal (panel) sample were developed as an alternative to a cross sectional sample design.

Fidell, Sanford↗

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗

Rotor blade imbalance fault detection for variable-speed marine current turbines via generator power signal analysis

Marine hydrokinetic (MHK) turbines extract renewable energy from oceanic environments. However, due to the harsh conditions that these turbines operate in, system performance naturally degrades over time. Thus, ensuring efficient condition-based maintenance is imperative towards guaranteeing reliable operation and reduced costs for marine hydrokinetic power. This work proposes a novel framework aimed at identifying and classifying the severity of rotor blade pitch imbalance faults experienced by marine current turbines (MCTs). In the framework, a Continuous Morlet Wavelet Transform (CMWT) is first utilized to acquire the wavelet coefficients encompassed within the 1P frequency range of the turbine's rotor shaft. From these coefficients, several statistical indices are tabulated into a six-dimensional feature space. Next, Principle Component Analysis (PCA) is employed on the resulting feature space for dimensionality reduction, and then the application of a K-Nearest Neighbor (KNN) machine learning algorithm is utilized for fault detection and severity classification. The effectiveness of the proposed framework is validated using a high-fidelity MCT numerical simulation platform, where results demonstrate that the presence of a pitch imbalance fault can be accurately detected 100% of the time and correctly classified based upon severity more than 97% of the time.

42 ENGINEERING↗

Use of Unmanned Aerial Systems for Post-closure Waste Site Maintenance and Surveillance - 20143

The P- and R-Area Reactor buildings, located at SRS near Aiken, SC, were in-situ decommissioned by grouting below-grade portions of the buildings and demolishing some above-grade structures to grade level. Other reactor building structures were left above-grade and sealed to prevent human or animal access. Because the above grade-structures are expected to continue in their present state for hundreds of years, the condition of the building roofs is critical to mitigate rainwater intrusion. For this reason, building roof areas were strengthened with high strength concrete to ensure the long-term integrity of the roof structure. Periodic inspections of the roof structures are required to ensure that the roofs are functioning properly and to identify damage areas. The traditional method of inspecting closed reactor buildings requires the use of a helicopter and photographer to generate photographs and videos for review. This method proved sufficient but lacked the resolution and clarity that is required for a thorough inspection of the building structure. Fortunately, the Savannah River National Laboratory (SRNL) has established a Small Unmanned Aircraft System (sUAS) program using commercially available and custom-built remote-controlled aircraft. EC and ACP contacted the SRNL program to evaluate whether the sUAS technology could be employed for periodic reactor building inspections. The sUAS can fly within a few meters of the reactor buildings and hover, allowing for a more thorough aerial inspection. The initial sUAS inspection of the P-Area Reactor building was completed in February 2018 and at the R-Area Reactor building in August 2018 and were successful in providing higher resolution photos and videos. The sUAS inspections also revealed that vegetation had begun to grow on the roofs that could potentially damage the structure integrity. SRNL partnered with Virginia Polytechnic Institute and State University to build a custom heavy lift sUAS that could be equipped with herbicides to remotely treat the vegetative growth. Herbicides were successfully applied to the R-Area Reactor building roof using the custom sUAS in September 2018. The use of unmanned aircraft systems at SRS to perform aerial inspections and herbicide treatment in otherwise inaccessible areas has proven to be an efficient and cost-effective technology that provides high value, increases knowledge of facility conditions, and provides for early detection of damage. Periodic inspections of the reactor building roofs using sUAS technology are performed safely, efficiently, and at a significant cost and schedule savings while reducing emissions, noise, and fossil fuel use. The use of sUAS equipment for building inspections and herbicide application at SRS is unique within the DOE complex. The goal of SRS is to apply this remote technology to other waste unit operations and maintenance activities in the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations

Integration of Information and Communication Technology (ICT) in modern smart grids (SGs) offers many advantages including the use of renewables and an effective way to protect, control and monitor the energy transmission and distribution. To reach an optimal operation of future energy systems, availability, integrity and confidentiality of data should be guaranteed. Research on the cyber-physical security of electrical substations based on IEC 61850 is still at an early stage. In the present work, we first model the network traffic data in electrical substations, then, we present a statistical Anomaly Detection (AD) method to detect Denial of Service (DoS) attacks against the Generic Object Oriented Substation Event (GOOSE) network communication. According to interpretations on the self-similarity and the Long-Range Dependency (LRD) of the data, an Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) model was shown to describe well the GOOSE communication in the substation process network. Based on this ARFIMA-model and in view of cyber-physical security, an effective model-based AD method is developed and analyzed. Two variants of the statistical AD considering statistical hypothesis testing based on the Generalized Likelihood Ratio Test (GLRT) and the cumulative sum (CUSUM) are presented to detect flooding attacks that might affect the availability of the data. Our work presents a novel AD method, with two different variants, tailored to the specific features of the GOOSE traffic in IEC 61850 substations. The statistical AD is capable of detecting anomalies at unknown change times under the realistic assumption of unknown model parameters. The performance of both variants of the AD method is validated and assessed using data collected from a simulation case study. We perform several Monte-Carlo simulations under different noise variances. The detection delay is provided for each detector and it represents the number of discrete time samples after which an anomaly is detected. In fact, our statistical AD method with both variants (CUSUM and GLRT) has around half the false positive rate and a smaller detection delay when compared with two of the closest works found in the literature. Our AD approach based on the GLRT detector has the smallest false positive rate among all considered approaches. Whereas, our AD approach based on the CUSUM test has the lowest false negative rate thus the best detection rate. Depending on the requirements as well as the costs of false alarms or missed anomalies, both variants of our statistical detection method can be used and are further analyzed using composite detection metrics.

IEC 61850 electrical substations↗