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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 505 records · Page 28

Permanent magnets composed of high temperature superconductors

A study of persistent, trapped magnetic field has been pursued with high-temperature superconducting (HTS) materials. The main effort is to study the feasibility of utilization of HTS to fabricate magnets for various devices. The trapped field, when not in saturation, is proportional to the applied field. Thus, it should be possible to replicate complicated field configurations with melt-textured YBa2Cu3O7 (MT-Y123) material, bypassing the need for HTS wires. Presently, materials have been developed from which magnets of 1.5 T, at 77 K, can be fabricated. Much higher field is available at lower operating temperature. Stability of a few percent per year is readily attainable. Results of studies on prototype motors and minimagnets are reported.

Weinstein, Roy↗

Effects of H 2 O 2 Concentration on Formation of Uranyl Peroxide Species Probed by Dissolution of Uranium Nitride and Uranium Dioxide

Dissolution of uranium materials in alkaline aqueous conditions containing H 2 O 2 results in uranyl peroxide species in solution, including anionic uranyl peroxide cage clusters. Uranyl peroxide cage clusters are generally highly soluble in water, where they persist as aqueous macroanions. Previous studies indicate that uranyl cluster speciation and dissolution of uranium materials is impacted by the concentration of alkali metal in solution, but in these studies, high concentrations of H 2 O 2 were used. Herein, the role of hydrogen peroxide concentration is examined relative to the dissolution of powdered UN and UO 2 . Lower initial H 2 O 2 concentrations reduce dissolution of UO 2 and UN and tend to produce simple (small) uranyl peroxide species rather the highly soluble uranyl peroxide clusters. H 2 O 2 availability will have implications for uranyl speciation and solubility where spent nuclear fuel is in contact with water and where alkaline peroxide conditions are used in dissolution of nuclear material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CPS Testbed Architectures for WAMPAC using Industrial Substation and Control Center Platforms and Attack-Defense Evaluation

Advanced persistent threats and cyberattacks can impact wide-area monitoring, protection, and control (WAMPAC) system operation. Many cyber-physical system (CPS) testbeds have been developed for attack-defense experimentation and attack-resiliency tools evaluation for WAMPAC, but they are limited to a simulation-and-emulation based environment. This paper presents a quasi-realistic CPS attack-defense testbed-based framework for WAMPAC applications using the industrial substation and control center platforms such as eTerra integrated with the hardware-in-the-loop CPS smart grid testbed available at Iowa State University. The proposed framework includes various combinations of industry-grade substation and control center platforms, communication topologies, real-time digital simulators, and a novel cyber-physical distributed intrusion-and-anomaly detection system (D-IADS) for WAMPAC applications. The D-IADS includes a master at the control center and geographically distributed sensor devices at each substation. Each D-IADS sensor deployed at a substation or control center network monitors ingress and egress traffic, detect intrusions, and dispatch alerts to the D-IADS master. The D-IADS master centrally monitors and analyze the alerts and controls D-IADS sensors. We considered an EMP60 synthetic CPS grid as a case study to demonstrate the framework and proposed D-IADS for WAMPAC applications against cyberattack vectors such as Man-in-the-Middle DNP3 attack, denial-of-service, and data-integrity attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Machine learning-enabled model-data integration for predicting subsurface water storage

Subsurface water storage (SWS) is a key variable of the climate system and a storage component for precipitation and radiation anomalies, inducing persistence in the climate system. It plays a critical role in climate-change projections and can mitigate the impacts of climate change on ecosystems. However, because of the difficult accessibility of the underground, hydrologic properties and dynamics of SWS are poorly known. Direct observations of SWS are limited, and accurate incorporation of SWS dynamics into Earth system land models remains challenging. We propose a machine learning-enabled model-data integration framework to improve the SWS prediction at local to conus scales in a changing climate by leveraging all the available observation and simulation resources, as well as to inform the model development and guide the observation collection. The accurate prediction will enable an optimal decision of water management and land use and improve the ecosystem's resilience to the climate change.

Lu, Dan↗

Characterizing organic carbon dynamics during biostimulation of a uranium contaminated field site

Uranium contamination of groundwater remains a pressing problem at many former uranium mining and milling operations, such as the Rifle, Integrated Field Research Challenge (IFRC) site. Biostimulation of the subsurface with an organic carbon source such as acetate, followed by the microbially-induced reductive precipitation of uranium has been proposed as an effective remediation strategy. While uranium bioreduction has been studied in several field experiments, the transformation and fate of injected carbon remains poorly understood. This study evaluated the impact of added organic carbon on the long-term biogeochemical attenuation of uranium in the subsurface of a former mill tailings site. Fluorescence and ultraviolet–visible absorbance analyses were used together with dissolved organic carbon (DOC) measurements to track organic carbon dynamics during and post-biostimulation of the 2011 Rifle IFRC experiment. An electron mass balance was performed on well CD01 to account for any unidentified carbon sinks. Measured DOC values increased to 1.76 mM-C during biostimulation, and to 3.18 mM-C post-biostimulation over background DOC values of 0.3–0.4 mM-C. Elevated DOC levels persisted for 90 days after acetate injections ceased. The electron mass balance revealed that assumed electron acceptors would not account for the total amount of acetate consumed. Excitation–emission matrices showed an increase in signals associated with soluble microbial products, during biostimulation, which disappeared post-biostimulation despite an increase in total DOC. Specific ultraviolet absorbance analyses, indicated that DOC present post-biostimulation is less aromatic in nature, compared to background DOC. Furthermore, our results suggest that microbes convert injected acetate into a form of solid phase organic matter that may be available to sustain iron reduction post-stimulation.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Hematologic Toxicity in Patients Treated With Postprostatectomy Whole-Pelvis Irradiation With Different Intensity Modulated Radiation Therapy Techniques Is Not Negligible and Is Prolonged: Preliminary Results of a Longitudinal, Observational Study

Purpose: To address the thus-far poorly investigated severity and duration of hematologic toxicity from whole-pelvis radiation therapy (WPRT) in a cohort of chemo-naïve patients treated with postprostatectomy radiation therapy including WPRT with different intensity modulated radiation therapy (IMRT) techniques, doses, and fractionations. Methods and Materials: This analysis pertains to 125 patients (70 from a pilot study and 55 from an observational protocol) for whom 1 baseline and at least 3 subsequent blood samples (median 6), obtained at irradiation midpoint and end, and thereafter at 3, 6, and 12 months, were available. Patients were treated with adjuvant (n=73) or salvage intent; static-field IMRT (n=19); volumetric modulated arc therapy (n=60) or helical Tomotherapy (n=46); and conventional (n=39) or moderately hypofractionated (median 2.35 Gy per fraction, n=86) regimens. The median 2-Gy equivalent dose (EQD2) to the prostatic bed was 70.4 Gy with a lymph-nodal planning target volume of 50.2 Gy. Clinical and dosimetric data were collected. Results: Both leukopenia and thrombocytopenia were significant (median nadir count 65% and 67% of baseline, respectively), with leukopenia also persisting (1-year median count 75% of baseline). Lymphopenia was the major contributor to the severity and 1-year persistence of leukopenia; all patients developed acute grade ≥1 lymphopenia (61% and 26% grade 2 and ≥3, respectively), whereas 1-year grade ≥2 lymphopenia was still present in 16%. In addition to an independent predictive role of corresponding baseline values, multivariable analyses highlighted that higher EQD2 doses to lymph nodal planning target volume increased risk of acute neutropenia and hypofractionation for acute thrombocytopenia. Of note, patients of older age were at higher risk for acute grade 2 lymphopenia, and interestingly, increased risk of grade >2 lymphopenia for those who smoked at least one year. No role for different IMRT techniques indicated. Conclusions: Leukopenia and lymphopenia after postprostatectomy WPRT were found to be less negligible and more prolonged than expected. A number of radiation-related and clinical factors favoring hematologic toxicity, whose awareness may be crucial when prescribing WPRT, in particular if concomitant to chemotherapy, were identified.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Patterns and controls on island‐wide aboveground biomass accumulation in second‐growth forests of Puerto Rico

Abstract Understanding the heterogeneity of biomass accumulation in second‐growth tropical forests following land use abandonment is important for informing ecosystem carbon models and forest restoration efforts. There is an urgent need for a broad sample of second‐growth forests to enhance our knowledge of carbon accumulation in human‐dominated landscapes, especially for older forests. Puerto Rico has predominantly second‐growth forests, ranging in age from approximately 25 to more than 80 years. We used an island‐wide sample of airborne lidar from the NASA Goddard Lidar, Hyperspectral, and Thermal (G‐LiHT) Airborne Imager collected on March 2017, forest inventory data, and data on forest age, precipitation, soils, and land use to estimate aboveground biomass stocks in moist and wet, second‐growth tropical forests. Biomass accumulation rates in Puerto Rico were lower, on average, than in other Neotropical forests. Median biomass across >16,700 ha of older second‐growth forests was 105 Mg ha −1 , and sampled biomass rarely surpassed 250 Mg ha −1 . Differences in biomass by age were large and persistent across different substrates and land uses, with a plateau in the pattern of island‐wide biomass accumulation after about 33 years. A spatial regression model showed that multiple factors were related to biomass accumulation, including time since abandonment, geologic substrate, past land use as coffee or pasture, precipitation, topographic wetness index, and slope. Our findings have important consequences for the total carbon storage and expected climate mitigation benefits of large‐scale reforestation efforts, and highlight the value of airborne lidar for quantifying biomass variability in complex tropical landscapes. Abstract in Spanish is available with online material.

54 ENVIRONMENTAL SCIENCES↗

Improved Modeling Tools Development for High Penetration Solar

One of the significant objectives of the High Penetration solar research is to help the DOE understand, anticipate, and minimize grid operation impacts as more solar resources are added to the electric power system. For Task 2.2, an effective, reliable approach to predicting solar energy availability for energy generation forecasts using the University of California, San Diego (UCSD) Sky Imager technology has been demonstrated. Granular cloud and ramp forecasts for the next 5 to 20 minutes over an area of 10 square miles were developed. Sky images taken every 30 seconds are processed to determine cloud locations and cloud motion vectors yielding future cloud shadow locations respective to distributed generation or utility solar power plants in the area. The performance of the method depends on cloud characteristics. On days with more advective cloud conditions, the developed method outperforms persistence forecasts by up to 30% (based on mean absolute error). On days with dynamic conditions, the method performs worse than persistence. Sky Imagers hold promise for ramp forecasting and ramp mitigation in conjunction with inverter controls and energy storage. The pre-commercial Sky Imager solar forecasting algorithm was documented with licensing information and was a Sunshot website highlight.

14 SOLAR ENERGY↗

Plant Growth Study: Growth of Three Plant Species in 100-OL-1 Operable Unit Soils

Soil contamination from historical application of lead arsenate pesticides persists in the 100-OL-1 Operable Unit (OU) of the U.S. Department of Energy’s Hanford Site in Benton County, Washington. A remedial investigation used a portable X-ray fluorescence analyzer to estimate and map the concentrations of metals in surface soil in the 133 decision units comprising the OU. There is variability in lead and arsenic concentrations among the non-contiguous decision units, and an incomplete understanding of the ecological and human risks from soil contamination. While general screening criteria for lead are reported in literature, limited information is available on the impacts of heavy metals on site-specific plant and animal life. To address this information gap, a study on plant growth in Hanford soils was conducted using native bluegrass (Poa secunda), invasive cheatgrass (Bromus tectorum), and buttercrunch lettuce (Lactuca sativa). The latter is included because it is a common species used in plant growth studies. Soil samples were collected from a single general location within the 100-OL-1 OU, prepared, and categorized as having low, medium, or high concentrations of lead and arsenic, with the high concentration soil having concentrations of up to 3,400 and 790 mg/kg lead and arsenic, respectively. Additionally, a synthetic soil was prepared and used as a control, in accordance with standard plant growth protocols. Fifty-four seeds of each plant species were planted in each of the four soil types following the procedure outlined by the Washington State Department of Ecology. Germination rates and biomass measurements were recorded for 20 days. Both bluegrass and lettuce germination rates appeared to be reduced at the highest lead and arsenic concentrations (Pb: 3400 mg/kg, As: 790 mg/kg), while cheatgrass germination rates were unaffected. Total biomass for all species appeared to be related to the relative concentrations of lead and arsenic in the soil. Results of this growth study agree reasonably well with previous Hanford Site plant growth studies and provide additional data for assessing ecological risk at the Hanford Site.

54 ENVIRONMENTAL SCIENCES↗

Snow ALbedo eVOlution (SALVO) Campaign Snow Depth and Related Surface Properties from April - June, 2024 in Utqiagivk, AK

Detailed transects of snow depths and related measurements were made with a magnaprobe along fixed lines in Utqiagvik, AK. The operator measures snow depth by plunging a rod with a sliding basket into the snow and pressing a trigger. At this point, the data logger records the distance between the tip of the rod and the height of the basket, the measurement number, the time, and the geographic location of the measurement. To measure snow depth, the rod tip must be placed at the snow-ground or snow-sea ice interface. The interface can be hard or soft; in the latter case, it is possible to “over-probe”, producing a snow depth that is too high. At times, the probe was also used to measure the depths of other interfaces within the snowpack (for example, the depth to persistent ice lenses) or the water depths of ponds atop the tundra or sea ice. When these alternative depth measurements were made, the operator recorded the location, measurement number, and composition of the alternative depth measurement in a field notebook. The data logger on the probe stores several thousand points. Data is downloaded to a computer at the end of a day or several days. Probes: We used 2 magnaprobes identified as GEO1 and GEODEL with the following serial numbers: S/N 20240416 (GEO1) and S/N P48066 (GEODEL). Note : There are three data levels available with this dataset: b3, b4, and a6. New users of these data are strongly encouraged to use the level a6 or b4 data.

54 ENVIRONMENTAL SCIENCES↗

Real-Time CME Forecasting Using HMI Active-Region Magnetograms and Flare History

We have recently developed a method of predicting an active region s probability of producing a CME, an X-class Flare, an M-class Flare, or a Solar Energetic Particle Event from a free-energy proxy measured from SOHO/MDI line-of-sight magnetograms. This year we have added three major improvements to our forecast tool: 1) Transition from MDI magnetogram to SDO/HMI magnetogram allowing us near-real-time forecasts, 2) Automation of acquisition and measurement of HMI magnetograms giving us near-real-time forecasts (no older than 2 hours), and 3) Determination of how to improve forecast by using the active region s previous flare history in combination with its free-energy proxy. HMI was turned on in May 2010 and MDI was turned off in April 2011. Using the overlap period, we have calibrated HMI to yield what MDI would measure. This is important since the value of the free-energy proxy used for our forecast is resolution dependent, and the forecasts are made from results of a 1996-2004 database of MDI observations. With near-real-time magnetograms from HMI, near-real-time forecasts are now possible. We have augmented the code so that it continually acquires and measures new magnetograms as they become available online, and updates the whole-sun forecast from the coming day. The next planned improvement is to use an active region s previous flare history, in conjunction with its free-energy proxy, to forecast the active region s event rate. It has long been known that active regions that have produced flares in the past are likely to produce flares in the future, and that active regions that are nonpotential (have large free-energy) are more likely to produce flares in the future. This year we have determined that persistence of flaring is not just a reflection of an active region s free energy. In other words, after controlling for free energy, we have found that active regions that have flared recently are more likely to flare in the future.

Falconer, David↗

Machine-Learning-Driven, Site-Specific Weather Forecasting for Grid-Interactive Efficient Buildings: Preprint

Emerging grid-interactive efficient buildings (GEBs) have great potential to provide much-needed demand flexibility to electric grids while fulfilling their own control targets by co-optimizing smart appliances, solar photovoltaics, electric vehicles, and energy storage at buildings. To enable the optimal operation of GEBs, site-specific weather information—such as temperature, solar irradiance, relative humidity, and wind speed—is crucial; however, this information is generally unavailable or expensive to obtain. This paper develops advanced machine learning methods to provide precise weather forecasts for individual building sites using readily available weather station data. Support vector regression and artificial neural networks have been employed to learn the spatiotemporal correlations between the weather conditions at nearby weather stations and the individual building site. The proposed site-specific weather forecasting methods have been validated using 1-year actual weather measurement data collected in the Denver metro area. Results show that the developed machine-learning-driven methods can accurately forecast the temperature at the target building site 1 hour ahead with mean absolute error less than 0.72°C and a 48% improvement over the persistence method. Site-specific weather forecasts will improve the understanding of the microclimate effect and its impact on building energy consumption. This information will drive efficiency upgrades and adjustments of building control strategies to improve energy savings and increase flexibility in building loads.

30 DIRECT ENERGY CONVERSION↗

An automated multi-component gas adsorption system (MC GAS)

The knowledge gap on adsorption of complex mixtures in the literature relative to single component data represents a persistent obstacle to developing accurate process models for adsorption separations. The collection of mixed gas adsorption data is an imminent need for improved understanding of the behavior of adsorbent systems in these diverse adsorption applications. Current approaches to understanding mixture adsorption using predictive theories based on pure component adsorption experiments often fail to capture the behavior of more complex, non-ideal systems. In this work, we present an automated volumetric instrument for the measurement of mixed gas adsorption isotherms. This instrument was validated by comparison to other in-house instruments and data available in the literature, and the binary adsorption measurements were found to be thermodynamically consistent. The automation of this instrument allows for rapid collection of high-quality mixture adsorption data.

47 OTHER INSTRUMENTATION↗

Heavy Oil Polymer EOR in the Challenging Alaskan Arctic - It Works!

Under co-sponsorship of the US Department of Energy and Hilcorp Alaska LLC the first ever polymer field pilot commenced on 8/28/2018 in the Schrader Bluff heavy oil reservoir at the Milne Point Field on Alaska North Slope (ANS). The primary objective of the pilot is to prove the efficacy of polymer Enhanced Oil Recovery (EOR) to unlock the vast heavy oil resources on ANS. More than two and half years after startup, the polymer injection, supporting laboratory experiments and simulation studies steadily continue. The pilot started injecting hydrolyzed polyacrylamide (HPAM), at a concentration of 1,750 ppm to achieve a target viscosity of 45 cP, into the two horizontal injectors in the flood pattern. Production is monitored in the two horizontal producers. Based on laboratory measurements of polymer viscosity at reservoir conditions, the team decided to reduce polymer concentration to 1,200 ppm since July 2020 in an effort to control injection pressure and optimize polymer utilization. Quality control (QC) on the field ensures uniform polymer solution properties. Representative rock and fluid systems and test conditions are utilized in the corefloods on polymer retention, effect of injection water salinity, polymer loading, and their combinations on oil recovery. A history matched reservoir simulation model for forecasting oil recovery was developed on the basis of all the available field data. Field concerns related to the post-polymer breakthrough impact on flow assurance is addressed via specialized laboratory tests. Notwithstanding early operational disruptions and hydration issues, continuous polymer injection in both injectors has been achieved. To date, 950,000 lbs of polymer or 2 million barrels of polymer solution, equating to 13% of total pore volume (PV), has been placed in the flood pattern, serving as an effective indicator of adequate polymer injectivity. So far, the success of polymer EOR is evident from drastically reduced water cut in the producers, an estimated incremental 1,000 bopd over waterflood, and a favorable polymer utilization of 1.7 lbs/barrel of incremental oil. Polymer breakthrough was observed 26 months after the start of polymer injection. Main observations from corefloods are unusually high polymer retention values in some cases and a positive response to low salinity water. Although the heterogeneity in the flood pattern and exceptionally low water cut pose some challenges, persistent novel and justifiable simulation approaches have resulted in a robust history matched model. Experimental results on produced fluids treatment provide operational guidance for improved oil-water separation and mitigation of heater tube fouling. The ongoing success of the pilot is a key indicator of bringing the team ever closer to meeting the project’s primary objective. The encouraging results of the pilot is one of the drivers that has provided the impetus to apply polymer EOR throughout the Milne Point Field, which would increase oil recovery and extend the economic life of the Trans Alaska Pipeline System. The scientific knowledge, including the many lessons learned from this pilot also has referential value for other potential heavy oil EOR projects throughout the world. The collected data, operational lessons learned, and the overall success of the pilot are summarized in the paper.

None, None↗

Elucidation of Local Ordering and Atomic-Scale Structure in Polymer-Derived SiOC

Silicon oxycarbide (SiOC) is a versatile ceramic material with tunable microstructure and compositions that can be modulated through precursor chemistry and processing conditions. Though there are several noteworthy uses of SiOC across a range of application spaces, the difficulties in elucidating the short- to medium-range order within these materials have limited the maturation of strategies to precisely control SiC x O 4–x compositions for user-tailored applications. In this contribution, we implement a range of synchrotron scattering and spectroscopy methods coupled with stochastic modeling techniques to elucidate changes in local chemistry and structure associated with the pyrolysis of a commercially available SiOC polymer precursor. Stochastic modeling approaches provide valuable insights into decoupling local Si–O and Si–C environments while confirming predominate heterogeneous phases in materials. Using pyrolysis temperatures between 250 to 800 °C results in a heterogeneous material predominately composed of SiOC and amorphous SiO 2 domains. At 1100 °C, redistribution of Si–C pairs in the SiOC network and Si–O from the SiO 2 domains create a more ordered SiOC phase with local cubic SiC-like ordering. In addition, residual carbon leads to a detectable carbon phases at 1100 °C that persist at higher temperatures. These efforts address the difficulties of obtaining atomic-scale insights into the local structure and nanoscale heterogeneities in SiOC, providing pathways toward establishing structure–property relationships for future materials development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The seasonal climate niche predicts phenology and distribution of an ephemeral annual plant, Mollugo verticillata

Many short-lived species complete their life cycles during brief seasonal windows of favourable environmental conditions. Such species may persist in the face of climate warming by migration to track their seasonal climate niche in space and/or by phenological shifts to track favourable conditions in time within the year. To describe the seasonal climate niche of the short-lived annual Mollugo verticillata in California, we used data from herbarium specimens and historic climate records to estimate environmental conditions at the location, month and year of each collection. We used these data in a MaxEnt framework to construct a seasonal species distribution model (SDM) of the species’ climate niche within the total climate space available across all seasons and locations in California. The model provides fine-scale spatial and temporal predictions of habitat suitability, predicting both where and when the species should be observed. We compared the predictions of the model to those from a conventional SDM based on mean annual climate data. Both models showed that M. verticillata is limited to warm environments within California. However, the seasonal SDM also predicted phenology by mapping climate suitability across the state for each month of the year. Mollugo verticillata is limited to warm months, and its seasonal climate niche shifts in space across California in the course of the year. We used the seasonal SDM to map the predicted future species distribution for each month of the year under three warming scenarios. The species is predicted to expand its range and occur earlier in the year in most locations; in the warmest locations, seasonal suitability is predicted to decline in the warmest months, which may result in bimodal phenology with a mid-summer gap. Synthesis. We developed a novel species distribution model using herbarium records and monthly weather data, which predicts not only where a short-lived species should be found but also when during the year it is predicted to occur in those areas. Furthermore, this model can be used to predict how climate change will affect the species distribution in space as well as seasonal phenology across the landscape.

54 ENVIRONMENTAL SCIENCES↗

Advanced Reactor Cyber Analysis and Development Environment (ARCADE) for System-Level Design Analysis

Cybersecurity is a persistent concern to the safety and security of Nuclear Power Plants (NPPs), but has lacked data-driven, evidence-based research. Rigorous cybersecurity analysis is critical for the licensing of advanced reactors using a performance-based approach. One tool that enables cybersecurity analysis is modeling and simulation. The nuclear industry makes extensive use of modeling and simulation throughout the decision process but lacks a method to incorporate cybersecurity analysis with existing models. To meet this need, the Advanced Reactor Cyber Analysis and Development Environment (ARCADE) was developed. ARCADE is a suite of publicly available tools that can be used to develop emulations of industrial control system devices and networks and integrate those emulations with physics simulators. This integration of cyber emulations and physics models enables rigorous cyber-physical analysis of cyber-attacks on NPP systems. This report provides an overview of key considerations for using ARCADE with existing physics models and demonstrates ARCADE’s capabilities for cybersecurity analysis. Using a model of the Small Modular Advanced High Temperature Reactor (SmAHTR), ARCADE was able to determine the sensitivity of the primary heat exchangers (PHX) to coordinated cyber-attacks. The analysis determined that while the PHX’s failures cause disruption to the reactor, they did not cause any safety limits to be exceeded because of the plant design, including passive safety features. Further development of ARCADE will enable rigorous, repeatable, and automated cyber-physical analysis of advanced reactor control systems. These efforts will also help reduce regulatory uncertainty by presenting similar types of cybersecurity analyses in a common format, driving standard approaches and reporting.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗