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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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42 records · Page 3

Mesh-Based Entry Vehicle and Explosive Debris Re-Contact Probability Modeling

The risk to a crewed vehicle arising from potential re-contact with fragments from an explosive breakup of any jettisoned spacecraft segments during entry has long sought to be quantified. However, great difficulty lies in efficiently capturing the potential locations of each fragment and their collective threat to the vehicle. The method presented in this paper addresses this problem by using a stochastic approach that discretizes simulated debris pieces into volumetric cells, and then assesses strike probabilities accordingly. Combining spatial debris density and relative velocity between the debris and the entry vehicle, the strike probability can be calculated from the integral of the debris flux inside each cell over time. Using this technique it is possible to assess the risk to an entry vehicle along an entire trajectory as it separates from the jettisoned segment. By decoupling the fragment trajectories from that of the entry vehicle, multiple potential separation maneuvers can then be evaluated rapidly to provide an assessment of the best strategy to mitigate the re-contact risk.

McPherson, Mark A.↗

Mitigating Extremist Maritime Threats to Radiological Material Transport Vessels

The 21st century has experienced a rise in the threat of global radicalism and extremist organizations, and there has been oft-reported interest from these groups in obtaining or exploiting radiological materials. The threat of extremists acquiring radiological materials while in transit or sabotaging a transport vessel carrying materials at sea is one that requires increased attention. Transport is already one of the most vulnerable times for any cargo but including the difficulties in securing a large ship on the open ocean makes oceanic transport of radiological materials a space of elevated vulnerability for sabotage, theft, or other attacks. The risks of violent extremist attacks on trade ships and trading routes are serious, as shipping routes sustain the global economy, but an attack on a radiological transport vessel could be a magnitude worse, impacting national and international security. While radicalists have largely remained on land in the past due to minimal maritime expertise or inability to project power out of their immediate vicinity, the world has witnessed past attacks on ships such as the USS Cole and the MV Limburg and it is likely only a matter of time before groups extend further into the sea and engage in more maritime campaigns against material transport vessels. This paper suggests methods for increasing safety and security on oceanic transport voyages through behavioral science principles and insider threat recognition training, as well as a better understanding of adversarial and extremist psychology. By providing transport personnel with the knowledge and support to identify and respond to unique maritime threats by extremists, these principles and training suggestions should advance and increase security on the high seas.

Kinney, Justin↗

Autonomous System Subversion Tactics: Prototypes and Recommended Countermeasures

One of the fielding requirements for Advanced and Small Modular Reactors (AR/SMR) is the ability to support remote and autonomous operations. Autonomous Control Systems (ACS) are found on platforms such as Autonomous Space Vehicles, Cruise Missiles, and advanced driver-assistance systems. Each of these ACS implementations depends upon a set of decision support subsystems responsible for supporting Autonomous Mission Managers (names vary based upon field and author preferences). These Autonomous Mission Managers receive inputs from system sensors (e.g., LIDAR collection from an automobile travelling down a street; transients from a nuclear reactor), and perform a set of classifications (e.g., Red Traffic Light; Small Pedestrian at 10m; Load Rejection; Single Coolant Pump Trip), and then use these classifications in combination with recommendation algorithms to achieve platform goals (e.g., Stop the Vehicle at the Traffic Light, Avoid the Small Pedestrian; Trip the Reactor to prevent a Safety Event). The design, implementation, and fielding of an ACS capability will alter the cyber-attack surface such that existing risk management plans will need to be updated to include how to protect and defend against data-science and decision-support-system attack classes. These attack classes would include protection of the design and training environments where algorithm selection and testing and training data would be obvious attack vectors. These attack classes would also require an informed set of detection and response procedures to identify anomalous behaviors and document best practices for anomaly assessment and vulnerability mitigation and remediation. Last year we published a Cyber Threat Assessment Methodology for Autonomous and Remote Operations for AR/SMRs along with a companion publication on Cyber Attack and Defense Use Cases. The focus of the methodology was on describing and enumerating ACS processes, components, and functions such that security engineers could: evaluate subversion options against the target; identify threat actor attributes and capabilities derived from each subversion option; and identify security controls and response countermeasures. The Use Cases document offered detailed methodology examples including an assessment of a Military Base SMR, an Autonomous System Decision Loop, and implementation of AR/SMR Machine Learning algorithms. Our proposal at the end of last year was to focus on implementation of subversion prototypes related to the last Use Case area: AR/SMR Machine Learning (ML) Algorithms. We included six attack scenarios in our Use Cases paper: a Poisoning Attack against ML functions implemented using an FPGA; a Trojaning Attack against ML classifiers exploiting the excitability of Nuclear Engineers; a Backdooring Attack against ML Training environments to ensure persistence of an attack vector; a False Positive Evasion Attack against multi-factor Access Control Systems using clever inputs; an Inference Attack against ML models by an Insider with access to the Operational environment; and an Adversarial Reprogramming Attack against a Material Access Control Video Surveillance System. At the beginning of this year these six attack scenarios were provided to our research teams at Georgia Tech and Idaho State University and each team successfully implemented a subversion attack against a ML implementation to include transient misclassifications. While this is a notable outcome from this type of research, this paper offers the reader insight into not only how to structure and execute these types of attacks, but into the thought process behind how the researcher investigated the problem space, performed initial algorithm implementation, and the trial-and-error behind arriving at the successful subversion prototypes. We include in this paper a set of associated Scenarios on how these subversion prototypes could be implemented and an initial set of guidance for AR/SMR architects, Nuclear Regulators, and Cyber Defenders to implement awareness and defense capabilities into their current operational portfolios.

42 ENGINEERING↗

The Design and Evaluation of Zero Trust Architecture for Electric Vehicle Charging Infrastructure: EVs @ Scale Series on EV Charging Station Cybersecurity

Implementing a zero trust architecture can significantly bolster the security of electric vehicle (EV) charging infrastructure. EV charging infrastructure includes numerous networked interfaces, each of which can present potential vulnerabilities. When these vulnerabilities are exploited, they can compromise the entire system, leading to severe operational and security risks. Zero trust is a security model that operates on the principle of "never trust, always verify," which helps manage the attack surface and limit the scope of any potential compromises. Fundamentally, this model ensures that no entity, whether inside or outside the network, is trusted by default. The design principles of zero trust include continuous verification, strict deny-by-default access controls, and micro-segmentation. Continuous verification ensures that every request is thoroughly checked, regardless of its origin. Strict access controls enforce the principle of least privilege, allowing users and devices only the minimum necessary access to perform their functions. Micro-segmentation involves dividing the network into smaller, isolated segments to prevent lateral movement in case of a breach. In the context of EV charging infrastructure, zero trust can be implemented through various strategies. For example, multi-factor authentication (MFA) can be required for engineers to access the management interfaces and control systems of charging stations. Real-time monitoring and analysis of network traffic can help detect and respond to anomalies. Systems that do not need to communicate with each other can be micro-segmented to enhance security. All communications should adhere to predefined policies to be permitted. Additionally, encrypting communications can protect sensitive information exchanged between chargers and management systems. This paper presents a zero trust architecture specifically designed for EV charging infrastructure. Implementing zero trust not only mitigates risks but also builds a resilient infrastructure capable of withstanding and quickly recovering from cyber threats. The architecture addresses six defined security objectives. A comprehensive test plan is developed to assess the architecture against these objectives, and the results of the evaluation are reported. This approach is essential for maintaining the reliability and integrity of EV charging services in an increasingly interconnected and vulnerable digital landscape. This is the first in a planned series of papers exploring the implementation of zero trust in EV charging infrastructure. Each paper will delve into different aspects and applications of zero trust, highlighting how various work processes and requirements can lead to distinct architectural designs. These architectures will be tailored to address specific security challenges and operational needs within the EV charging ecosystem, ensuring a robust and adaptable security framework.

33 ADVANCED PROPULSION SYSTEMS↗

Analysis of Solids Obtained from 201O, 201P, 202A, and 202B Contactors in the Salt Waste Processing Facility

In December 2022, Savannah River Mission Completion personnel recovered solids samples from four contractors (EXT-001, EXT-007, EXT-031, and EXT-040) employed at the Salt Waste Processing Facility (SWPF). These solids were submitted to Savannah River National Laboratory for analysis and characterization. This Technical Report outlines the analytical findings and observations associated with these samples and explores the potential source of solid generation within the SWPF. The following conclusions are offered as a result of this work: the light color solids recovered from EXT-007 are consistent with crystallized, soluble salt components (such as sodium nitrate, sodium hydroxide, and sodium carbonate), all of which can be easily re-dissolved in process water and do not represent a threat to SWPF CSSX processing. While the light solids from the top of EXT-040 were not analyzed, it is believed that they share similar characteristics to those recovered from EXT-007; The dark color solids recovered from EXT-001, EXT-031, and the inside of EXT-040 appear to be complex, consisting of several different types of solids: High concentrations of mercury (Hg, 40-75% by mass) partially present as elemental Hg are consistent with the precipitation of Hg 0 /Hg 2+ from disproportionation of Hg + species in pH swing conditions; Moderate concentrations of titanium (Ti) (2-7%, by mass) are also present, often co-located with Hg. This is consistent with co-precipitation, entrainment, and/or amalgamation of Ti and Hg; Moderate concentrations of iron (Fe) (1-3%, by mass) are observed in SWPF solids and are likely attributable to erosion of stainless-steel components within the CSSX process; Small concentrations of tungsten (W) and cobalt (Co) (<1%, by mass) are observed in SWPF solids. The presence of these solids is consistent with the erosion of components coated with W and Co (e.g., Stellite); Small concentrations of aluminum (Al) (<1%, by mass) are observed in the form of gibbsite and potentially sodium aluminosilicate. The presence of these compounds is likely attributable to the pH swing observed between the scrub and extraction cycles within the CSSX process. The following recommendations are made as a result of this work: Testing should be performed to determine the chemical drivers, process, and mechanism of Hg precipitation in CSSX processing. Special care should be taken to include titanium in tests to evaluate the potential for co-precipitation, entrainment, and amalgamation; Hg-mitigation options that would minimize or eliminate risks of Hg precipitation and solids accumulation (e.g., Hg-absorption techniques, ion exchange/adsorbents, flowsheet changes, etc.) should be assessed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Comparing the Earth Impact Flux from Comets and Near-Earth Asteroids

Long-period comets (LPC), defined here as those active comets with orbital periods greater than 200 years, are the most difficult objects to mitigate should one be found on an Earth threatening trajectory. The arrival of these objects from the distant Oort cloud cannot be predicted and the impact warning time would be measured in a few months - not years. At the distance of Jupiter, an inactive cometary nucleus with a diameter of one kilometer and a geometric albedo equal to 0.04 would have an apparent magnitude fainter than 25 near opposition and, hence would be well outside the detection capability of current NEO search telescopes. In general LPCs do not become active, and hence discoverable, until inside the orbit of Jupiter and it takes but nine months for a LPC to travel the distance from Jupiter's orbit to that of the Earth.Estimating the impact energy for long-period comets is particularly difficult because the sizes and masses of these objects are not well known. Their solid nuclei are hidden from ground-based telescopes by their gas and dust atmospheres and even when nearby spacecraft observations can determine a size and shape for a cometary nucleus, there are no direct determinations of any cometary mass or bulk density to date. However, a variety of indirect bulk density determinations consistently provide values below one gram per cubic centimeter, the value for water. From measurements made by the Deep Impact spacecraft during its encounter with comet Tempel 1 in July 2005, the bulk density was estimated to be 0.6 grams per cubic centimeter. The mean impact velocity of a LPC is about 51 km/s, three times the 17 km/s value for a typical near-Earth asteroid (NEA) so the impact energy for an LPC would be 9 times that of a NEA of similar mass. However, the bulk density of a comet (approx. 0.6 g/cu cm) is several times less than the density of a stony NEA (approx. 2.6 g/ cu cm) so for a LPC and a stony NEA of the same size, the LPC's impact energy would be about twice that of the NEA.To properly allocate the limited resources available for NEO surveys and physical characterization, it is important to understand the relative threat from long-period comets versus the threat posed by near-Earth asteroids.

near Earth objects↗