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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 127 records · Page 7

A machine independent expert system for diagnosing environmentally induced spacecraft anomalies

A new rule-based, machine independent analytical tool for diagnosing spacecraft anomalies, the EnviroNET expert system, was developed. Expert systems provide an effective method for storing knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms which allow approximate reasoning and inference, and the ability to attack problems not rigidly defines. The EviroNET expert system knowledge base currently contains over two hundred rules, and links to databases which include past environmental data, satellite data, and previous known anomalies. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose.

Rolincik, Mark J.↗

Development and Testing of High Surface Area Iridium Anodes for Molten Oxide Electrolysis

Processing of lunar regolith into oxygen for habitat and propulsion is needed to support future space missions. Direct electrochemical reduction of molten regolith is an attractive method of processing, because no additional chemical reagents are needed. The electrochemical processing of molten oxides requires high surface area, inert anodes. Such electrodes need to be structurally robust at elevated temperatures (1400-1600 C), be resistant to thermal shock, have good electrical conductivity, be resistant to attack by molten oxide (silicate), be electrochemically stable and support high current density. Iridium with its high melting point, good oxidation resistance, superior high temperature strength and ductility is the most promising candidate for anodes in high temperature electrochemical processes. Several innovative concepts for manufacturing such anodes by electrodeposition of iridium from molten salt electrolyte (EL-Form process) were evaluated. Iridium electrodeposition to form of complex shape components and coating was investigated. Iridium coated graphite, porous iridium structure and solid iridium anodes were fabricated. Testing of electroformed iridium anodes shows no visible degradation. The result of development, manufacturing and testing of high surface, inert iridium anodes will be presented.

Shchetkovskiy, Anatoliy↗

Development and Testing of High Surface Area Iridium Anodes for Molten Oxide Electrolysis

Processing of lunar regolith into oxygen for habitat and propulsion is needed to support future space missions. Direct electrochemical reduction of molten regolith is an attractive method of processing, because no additional chemical reagents are needed. The electrochemical processing of molten oxides requires high surface area, inert anodes. Such electrodes need to be structurally robust at elevated temperatures (1400-1600?C), be resistant to thermal shock, have good electrical conductivity, be resistant to attack by molten oxide (silicate), be electrochemically stable and support high current density. Iridium with its high melting point, good oxidation resistance, superior high temperature strength and ductility is the most promising candidate for anodes in high temperature electrochemical processes. Several innovative concepts for manufacturing such anodes by electrodeposition of iridium from molten salt electrolyte (EL-Form? process) were evaluated. Iridium electrodeposition to form of complex shape components and coating was investigated. Iridium coated graphite, porous iridium structure and solid iridium anodes were fabricated. Testing of electroformed iridium anodes shows no visible degradation. The result of development, manufacturing and testing of high surface, inert iridium anodes will be presented.

Shchetkovskiy, Anatoliy↗

Water Security: Trends, Capabilities, and Research Directions to Secure Water Infrastructure

Water and wastewater sector is target rich and resource poor ~153k water utilities, serve 80% of US population ~16k publicly-owned wastewater systems in the US serve 75% of the population Need scalable solutions to fit small and medium to large systems Federal attention to critical infrastructure continues to grow – particularly in the water sector Increase in water sector incidents and threats for large scale disruption – particularly by nation-state actors and their proxies EPA is the SRMA DHS CISA focuses on critical infrastructure protection across sectors They must work together to secure WWW systems Research capabilities to enable secure water systems Current and future threats Resilience – natural disasters, accidents, cyber-physical attacks

99 - GENERAL AND MISCELLANEOUS↗

WAMS-Based HVDC Damping Control for Cyber Attack Defense

Owing to the fast and large power regulating the capacity of the HVDC system, the wide-area measurement system (WAMS) based high voltage direct current (HVDC) system has been regarded as a prospective solution to deal with the low-frequency oscillation issue. However, due to the vulnerability of the WAMS communication, WAMS based HVDC system control can be a prime target of malicious penetrations that could lead to disastrous events. To remediate this adverse effect, an improved WAMS based HVDC damping control framework is proposed in this paper. First, a lightweight network named Attack Shuffle convolutional neural Networks (ASNet) is proposed to learn the characteristics of cyber attacks. Then, a model-free-based cyber attack defense framework is introduced to quickly identify the attack types based on the continuous wavelet transform and ASNet. Additionally, an improved control framework of the WAMS and HVDC-based wide-area power oscillation damping control (WH-PODC) is developed to provide different response control for mitigation of the impact of cyber attacks. Finally, the performance of the proposed WH-PODC control framework is evaluated with real PMU data in multiple scenarios in RTDS, where the results indicate that the response intensity can be kept under multiple types of cyber attacks while providing similar effectiveness in oscillation suppression to conventional controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Detection of False Data Injection Attacks in Battery Stacks Using Input Noise-Aware Nonlinear State Estimation and Cumulative Sum Algorithms

Grid-scale battery energy storage systems (BESSs) are vulnerable to false data injection attacks (FDIAs), which could be used to disrupt state of charge (SoC) estimation. Inaccurate SoC estimation has negative impacts on system availability, reliability, safety, and the cost of operation. In this article a combination of a Cumulative Sum (CUSUM) algorithm and an improved input noise-aware extended Kalman filter (INAEKF) is proposed for the detection and identification of FDIAs in the voltage and current sensors of a battery stack. The series-connected stack is represented by equivalent circuit models, the SoC is modeled with a charge reservoir model and the states are estimated using the INAEKF. Further, the root mean squared error of the states’ estimation by the modified INAEKF was found to be superior to the traditional EKF. By employing the INAEKF, this article addresses the research gap that many state estimators make asymmetrical assumptions about the noise corrupting the system. Additionally, the INAEKF estimates the input allowing for the identification of FDIA, which many alternative methods are unable to achieve. The proposed algorithm was able to detect attacks in the voltage and current sensors in 99.16% of test cases, with no false positives. Utilizing the INAEKF compared to the standard EKF allowed for the identification of FDIA in the input of the system in 98.43% of test cases.

25 ENERGY STORAGE↗

Adversarial Attacks on Deep Neural Network-based Power System Event Classification Models

Online event classification is essential to strengthening the reliability of the power transmission system. Recently, deep learning based methods have achieved great success in numerous domains such as computer vision and natural language processing. Researchers began to adopt deep learning based methods to solve the power system event identification problem and achieved effective results. However, these previous works do not consider that deep learning models are vulnerable to adversarial attacks, potentially influencing real-world applications' reliability. In this paper, we adopt several adversarial attack mechanisms by adding tailored noise signal to the input Phasor Measurement Units (PMU) time series and make the deep learning model misclassify the power system event. This numerical study discloses that current state-of-the-art deep learning based power system event classifiers are extremely vulnerable to adversarial attacks, which may jeopardize the reliability of the power transmission system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Model Deformation and Optical Angle of Attack Measurement System in the NASA Ames Unitary Plan Wind Tunnel

Both AoA and MDM measurements can be made using an optical system that relies on photogrammetry. Optical measurements are being requested by customers in wind tunnels with increasing frequency due to their non-intrusive nature and recent hardware and software advances that allow measurements to become near real time. The NASA Ames Research Center Unitary Plan Wind Tunnel is currently developing a system based on photogrammetry to measure model deformation and model angle of attack. This paper describes the new system, its development, its use on recent tests and plans to further develop the system.

flow visualization↗

Adaptive anomaly detection for identifying attacks in cyber-physical systems: A systematic literature review

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods, which focus on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks, with an emphasis on fast data processing and model adaptation. AAD has been researched extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on current research in this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS from 2013 to November 2023. We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our findings show that most studies addressed either model adaptation or data processing, but rarely both simultaneously. This indicates a research gap in fully adaptive solutions. We also categorize algorithms, datasets, and attack characteristics, and summarize strengths and weaknesses across the literature. Our review provides a structured and accessible reference for researchers and practitioners, offering insights into key trends and highlighting limitations in current approaches. Finally, we outline several future research directions, including the need for integrated real-time processing and adaptive learning, explainability, and uncertainty quantification in AAD for CPS.

Adaptation↗

Nacelle/pylon interference study on a 1/17th-scale, twin-engine, low-wing transport model

NASA-Langley has conducted wind tunnel tests of a twin-engine, low-wing transport aircraft configuration with 10.8-aspect ratio supercritical wing, in order to ascertain and compare the wing/nacelle interference effects of through-flow nacelled simulating 'superfan' very high bypass ratio (BPR=20) turbofans and current-technology (BPR=6) turbofans. Measurements of model forces and moments have been obtained, together with extensive external static pressure measurement on the model's wings, nacelles, and pylons in the Mach 0.5-0.8 range, at angles of attack in the -4 to +8 deg range. The superfan nacelles exhibit a significant advantage over current-technology turbofan nacelles, when the superfan's SFC gains are taken into account.

Pendergraft, Odis C., Jr.↗

Identification of Intraday False Data Injection Attack on DER Dispatch Signals

The urgent need for the decarbonization of power grids has accelerated the integration of renewable energy. Concurrently, increasing distributed energy resources (DER) and advanced metering infrastructure (AMI) have transformed the power grids into a more sophisticated cyber-physical system with numerous communication devices. While these transitions provide economic and environmental value, they also impose increased risk of cyber attacks and operation al challenges. This paper investigates the vulnerabilit y of the power grids with high renewable penetration against an intraday false data injection (FDI) attack on DER dispatch signals and proposes a kernel support vector regression (SVR) based detection model as a countermeasure. The intraday FDI attack scenario and the detection model are demonstrated in a numerical experiment using the HCE 187-bus test system.

Kim, Jip↗

Reviewing clinical considerations and guideline recommendations of C1 inhibitor prophylaxis for hereditary angioedema

Abstract Background Hereditary angioedema (HAE), a rare disease that is characterized by painful and recurring non‐allergic swelling episodes, is caused by the deficiency or dysfunction of C1 inhibitor (C1INH) protein. A comprehensive HAE management plan may require long‐term prophylaxis (LTP) in addition to on‐demand treatment to help “normalize” patients' lives so that they may fully engage in work, school, family, and leisure activities. Aim The main objective of this narrative review is to provide an overview of updated guideline recommendations specific to LTP of HAE and discuss clinical considerations and pharmacologic management options, with a focus on C1INH. Materials and Methods The authors reviewed relevant HAE literature for current recommendations regarding LTP and the role of C1NH. Results Acute HAE attacks are treated with on‐demand medication; however, there is a consensus that LTP should routinely be considered for risk reduction and prevention of future episodes. The 2017 World Allergy Organization/European Academy of Allergy and Clinical Immunology guidelines recommend that all patients with HAE be evaluated for LTP routinely and the 2020 HAE Association (HAEA) guidelines emphasize that the decision to use LTP should not be based on rigid criteria, but rather should be based on individual patient needs. Both guidelines recommend C1INH as first‐line/preferred therapy for LTP in a range of patient types including adults, children/adolescents, and pregnant/lactating patients. The HAEA also recommends the kallikrein inhibitor, lanadelumab, as a first‐line option for LTP. HAE pathway‐specific agents for LTP have not been associated with notable safety concerns. Discussion Plasma‐derived C1INH has been available for 40+ years in Europe and impacts multiple targets within the HAE pathway. C1INH has been used for on‐demand treatment and LTP. A subcutaneous formulation of plasma‐derived C1INH is approved for LTP and produces functional C1INH activity levels consistently above the threshold needed for protection from HAE attacks. Other pathway‐specific options for LTP include the plasma kallikrein inhibitors, lanadelumab‐flyo and berotralstat, approved for adults and pediatric patients aged ≥12 years. C1INH is approved for adults and pediatric patients aged ≥6 years. Conclusion Assessing the need for LTP is vital in the ongoing dialogue between clinicians and patients, as both disease‐related factors and patient preferences may change over time. Among available options for LTP, plasma‐derived C1INH is the broadly recommended first‐line option for LTP in patients with HAE, including pregnant/lactating women and pediatric patients (≥6 years).

Anderson, John↗

Sign-OPT: A Query-Efficient Hard-label Adversarial Attack

We study the most practical problem setup for evaluating adversarial robustness of a machine learning system with limited access: the hard-label black-box attack setting for generating adversarial examples, where limited model queries are allowed and only the decision is provided to a queried data input. Several algorithms have been proposed for this problem but they typically require huge amount (>20,000) of queries for attacking one example. Among them, one of the state-of-the-art approaches (Cheng et al., 2019) showed that hard-label attack can be modeled as an optimization problem where the objective function can be evaluated by binary search with additional model queries, thereby a zeroth order optimization algorithm can be applied. In this paper, we adopt the same optimization formulation but propose to directly estimate the sign of gradient at any direction instead of the gradient itself, which enjoys the benefit of single query. Using this single query oracle for retrieving sign of directional derivative, we develop a novel query-efficient Sign-OPT approach for hard-label black-box attack. We provide a convergence analysis of the new algorithm and conduct experiments on several models on MNIST, CIFAR-10 and ImageNet. We find that Sign-OPT attack consistently requires 5X to 10X fewer queries when compared to the current state-of-the-art approaches, and usually converges to an adversarial example with smaller perturbation.

Cheng, Minhao↗

High temperature environmental effects on metals

The current status of knowledge and ability to predict high-temperature environmental attack of metals is reviewed with particular reference to the gas turbine engine. Environmental attack is caused by high temperatures, combustion products, and impurities. A schematic representation of life-limiting factors of turbine components shows that environmental attack can lead to very early failures. Attention is given to high-temperature oxidation with prevailing modes of oxidation attack, and to hot corrosion and other impurity effects. Erosion attack results from the direct mechanical removal of component material by impact of hard substances like ash, sand, or dirt. Solutions to hot-corrosion problems can be found semiempirically by using improved alloys or ceramics, protective surface coatings, additives to the engine environment, and air/fuel cleanup to eliminate detrimental impurities.

Grisaffe, S. J.↗

Comparative wind tunnel tests of NACA 23024 airfoils with several aileron and spoiler configurations

This paper reviews research efforts at Wichita State University sponsored by NASA Lewis Research Center to design and evaluate aerodynamic braking devices which will be smaller and lighter than full-chord blade pitch control. Devices evaluated include a variety of aileron configurations, and spoilers located at both trailing edge and near the leading edge. The paper discusses analytical modeling, wind tunnel tests, and for some configurations, full-scale rotor tests. Current designs have not provided adequate control power at high angles of attack (low tip-speed-ratios). The reasons for these limitations are discussed. Analysis and wind tunnel test data indicate that several options are available to the designer to provide aerodynamic slowdown without full-chord pitch control. Three options are suggested; adding venting in front of the control surface hingeline, using spoilers located near the leading edge, and using a two-piece control combining downward deflection inboard with upward deflection outboard.

Wentz, W. H., Jr.↗

A Review on Cybersecurity Vulnerabilities for Urban Air Mobility

Recent developments of high-powered unmanned aerial vehicles (UAVs) have allowed for urban air mobility (UAM) to become a reality. While the propulsive technology of these flying cars has almost reached an economic level, the infrastructure to allow for these vehicles to operate in an urban environment is still lacking. With numerous known vulnerabilities in UAVs and commercial aircraft, manufacturers have not addressed cybersecurity in the scope of urban air mobility. This paper presents a review of several known cybersecurity vulnerabilities and previous attacks associated with the core communication systems of UAVs and aircraft. Analyzing current solutions to each threat and incorporating early concepts for UAM, this paper then presents a basic framework featuring a blockchain-based PKI with secondary navigation systems to allow for the development of secure airspace.

Urban Air Mobility↗

Support for Reactor Operators in Case of Cyber-Security Threats (NEUP Final Report)

Increasing use of digital technology in nuclear power plants (NPPs) poses cyber-security as a crucial threat to public safety and to continuous energy production. Cyber-security risks are comprised of complex known and unknown interactions between various entities, system vulnerabilities, network protocols, human users and malicious attacks. There is little understanding or research geared towards plant operators’ response under cyber-security threats and operational procedures to cope with such threats. This is particularly critical when a cyber-security event masquerades as a safety incident or an evolving accident. Instead of leading operators to the remediation of the accident, the masked cyber event may lead them to circumvent the safety mechanisms of the plant. Given these challenges, the objective of this project is to develop a tool to characterize abnormal NPP events as “cyber” or “safety” incidents, and to further develop this tool as a real-time operator aid to assist in response to the incident. This NEUP Final Report summarizes the research efforts towards the above goals and the results in the following three aspects. First, a methodology for classifying abnormal NPP events as cyber-attacks or safety incidents was developed. This provides the basis for responding to potential cyber-attacks. In this methodology, the causal relationships between various variables (i.e., physical variables, network variables, and control variables) for a nuclear system under consideration are modeled using dynamic Bayesian networks. Based on observations of certain variables (i.e., the evidence), inference is performed to identify the state of hidden variables, which helps indicate the occurrence of cyber-attacks or safety incidents. The proposed methodology was applied to the full scope NPP simulator system at The Ohio State University as a case study. The result shows that the proposed methodology is capable of distinguishing between cyber-attacks and safety incidents. Second, a game-theoretic approach for responding to cyber-attacks on nuclear power plants was developed. This is the second major goal of the project, and the method is used to recommend optimal responses to reactor operators in the case of cyber-attacks. We consider two cases in this research. In the first case, the interaction between the defender (i.e., the reactor operator) and the attacker is modeled as a two-player, nonzero-sum, Markov game with an infinite time horizon. In the second case, we consider a semi-Markov game between the defender and the attacker within a finite time horizon. The model in the second case enables us to consider the time sensitive response of the defender. In each case, the method for deriving the Nash equilibrium is developed. The Nash Equilibrium of the game provides the valid prediction of both players’ actions because no single player can benefit from unilaterally deviating from the equilibrium policy if the other player adheres to his/hers, hence it provides the best response of the defender to cyber-attacks. The proposed method in each case is demonstrated through a simplified benchmark digital feedwater control system. Third, a prototype display is developed to integrate the above information. The prototype display depicts the communication information to the operator and incorporates the cyber-security tool developed by the team into the interface. It consists of the regular display in current control rooms, as well as a panel used to indicate the occurrence of cyber-attacks or safety events and a panel used to guide the operator’s response to detected cyber-attacks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Artificial Intelligence for Digital Security and Protections

Proper functioning of nuclear power plants relies on a mix of well-regulated human and machine-driven workflows. This regulation supports nuclear safety through a series of processes and many of the tasks that support these processes have a repetitive nature that make artificial intelligence (AI) informed by machine learning (ML) a potential aid in a variety of tasks. AI is being evaluated for activities that include inspections, fuel processing, monitoring, and other activities. The introduction of any new technology presents a potential new attack vector. In the case of AI/ML, there are many attacks that have already been discovered and over time the attacks can be expected to follow the growth pattern observed in cyber security. While future planning is necessary, current efforts need to be established now to predict the threat emergence over the next year 10 years and mitigate potential threats. Based on these observations, AI/ML will need to become trustworthy, which corresponds to techniques and procedures that emphasize AI explainability along with resilience techniques to data, algorithms, models, and systems. This kind of system robustness is the foundation for defenses against AI/ML-specific attacks. Attempting to look forward and take a broad view of capabilities provides input to research roadmaps and the ability to distill vulnerabilities into specific use cases may provide greater assistance in understanding the technology benefits while introducing new risks. The impact of current and future AI in three areas—capabilities, challenges, and recovery strategies—represents an initial attempt at balancing both.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗