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NASA Extreme Environment Mission Operations (NEEMO)

Introduction: NASA is preparing to land the first woman and first person of color on the Moon within the next decade, and ensuring the success of these missions will depend on our preparation on the ground in multiple ground-based lunar environment analogs. To achieve this, NASA has used full mission class analogs, of which NASA Extreme Environment Mission Operations (NEEMO) is the longest continuously running example. Discussion: NEEMO is NASA’s long-standing undersea high-fidelity spaceflight mission analog. It focuses on exploration science, EVA techniques and tools, and maturing ISS IVA flight hardware and operations concepts. NEEMO crews are composed of groups of US and International Partner (IP) astronauts, engineers and scientists who live, work and explore in a challenging environment analogous to the environment experienced currently on ISS and what is expected for future deep space exploration destinations. NEEMO missions are conducted at Aquarius Reef Base (ARB), which includes a shore base in Tavernier, FL, and the world's only undersea research station, the Aquarius habitat, which is located 5.4 miles (9 kilometers) off Key Largo in the Florida Keys National Marine Sanctuary. ARB is owned and operated by Florida International University (FIU). Aquarius was selected due to its remote and extreme location and its ability to provide the unique isolation and risk factors that spaceflight presents. NEEMO missions allow for evaluations of end-to-end EVA and Science exploration concepts of operations with a crew that is in situ in a true extreme environment. They also allow for evaluations of flight hardware and ops tools that are either pondered or destined for ISS or Gateway in the near future. NEEMO missions feature flight-like interactions between the crew and a Mission Control Center (MCC )and Science Team, which in turn allows evaluation of mission and science operations decision making and communications techniques. One reason NEEMO missions are of such high fidelity is that so many of the participants are experienced human space flight end operators. The majority of crewmembers are trained astronauts, and many of the MCC operators have credentials as current or former certified ISS MCC operators (e.g., CapCom, EVA Officer, etc.). Mission products are generated daily by the ground team and are modeled on ISS products (but modified as needed). A planning team manages the constantly evolving mission timelines in response to the ever-changing constraints and opportunities. During NEEMO missions, suited EVA crewmembers (using diving helmets) have clear voice communications with each other, the habitat, and the MCC and Science Team back on shore. Each EVA crewmember also sends helmet cam video to the habitat and MCC and Science Teams. Appropriate communications latencies are inserted for the destination being simulated as well. NEEMO missions are made possible by a broad collaboration of participants. Astronauts from all of the ISS partner agencies are eligible for crew assignment. Often the crew includes a NASA scientist, doctor or engineer with a particular skill to contribute. Sometimes crewmembers come from external entities–generally institutes or universities. Objectives come from a wide variety of sources as well, from within NASA, IPs, government agencies, academia, commercial companies and research institutes. A typical NEEMO mission is a collaboration between at least 5 NASA centers. To date, 23 NEEMO missions have been conducted since 2001, and NEEMO 24 is planned for 2022. Conclusion: NEEMO is a high-fidelity mission analog conducted in an extreme subsea environment. It features experienced end-operators in human spaceflight, from the astronaut crewmembers to key personnel staffing Mission Control. Acknowledgments: The authors wish to thank FIU and NASA’s HEO SEI/Strategic Analysis and Exploration Integration and Science Directorate organizations for the continued support that makes the NEEMO Project possible.

M L Reagan↗

Extreme Environment Hot Fire Durability of Post-Processed Additively Manufactured GRCop-Alloy Combustion Chambers in LOX/Hydrogen and LOX/Methane

Extreme environment survivability of metal additive manufactured (AM) GRCop-alloy thrust chambers has been demonstrated in different bi-propellants at near stoichiometric and even oxygen rich combustion. GRCop-alloy chambers tested at NASA Marshall Space Flight Center (MSFC) have accumulated over 26,000 seconds of hot fire duration and over 500 starts. These chambers are produced using an AM process called laser powder bed fusion (L-PBF). A major feature of this process is high wall surface roughness which can be customized in post processing to leverage various performance advantages. Post-processing can include heat treatment, final machining, polishing, and welding and is key to hardware survivability in extreme environments. Surface finish enhancement techniques were applied to the hot wall and coolant channels to reduce the overall total heat load to the chamber walls. Performance optimization of various thrust class TCA’s is a strategic technology goal of NASA MSFC. Three different chamber geometries using cryogenic methane and de-ionized water as coolants were hot fire tested to obtain their life cycle, pressure drop, and heat load performances. Several 1.2K lbf LOX/H2 chambers, 1K lbf LOX/CH4 chambers, and 7K lbf LOX/CH4 chambers were tested. All post-processed configurations performed remarkably well when subjected to extreme hot fire test conditions. Streaking and blanching due to localized oxygen rich conditions were observed on some test articles in their as-built surface finish state. However, this is actually a function of the injector mixing and only serves to further establish the durability of L-PBF GRCop-alloy thrust chambers. Several different polishing techniques were applied to the hot wall and integrated coolant channels prior to hot fire testing and their performances assessed. Overall, AM produced GRCop chambers are extremely reliable, durable, and customizable to the desired performance metrics.

grcop↗

Future Changes in Snowpack, Snowmelt, and Runoff Potential Extremes Over North America

Snowpack and snowmelt-driven extreme events (e.g., floods) have large societal consequences including infrastructure failures. However, it is not well understood how projected changes in the snow-related extremes differ across North America. Using dynamically downscaled regional climate model (RCM) simulations, we found that the magnitudes of extreme snow water equivalent, snowmelt, and runoff potential (RP; snowmelt plus precipitation) decrease by 72%, 73%, and 45%, respectively, over the continental United States and southern Canada but increase by up to 8%, 53%, and 41% in Alaska and northern Canada by the late 21st century. In California and the Pacific Northwest, there is a notable increase in extreme RP by 21% contrary to a decrease in snowmelt by 31% by the late century. These regions could be vulnerable to larger rain-on-snow floods in a warmer climate. Regions with a large variability among RCM ensembles are identified, which require further investigation to reduce the regional uncertainties.

Eunsang Cho↗

Compound High Temperature and Low Chlorophyll Extremes in the Ocean Over the Satellite Period

Ocean extreme events severely impact marine organisms and ecosystems. Of particular concern are compoundevents, i.e., when conditions are extreme for multiple potential ocean ecosystem stressors such as temperature and chlorophyll.Yet, little is known about the occurrence, intensity and duration of such compound high temperature (aka marine heatwaves -MHWs) and low chlorophyll (LChl) extreme events, whether their distributions have changed in the past decades and what thepotential drivers are. Here we use satellite-based sea surface temperature and chlorophyll concentration estimates to provide a5first assessment of such compound extreme events. We reveal hotspots of compound MHW and LChl events in the equatorialPacific, along the boundaries of the subtropical gyres, in the northern Indian Ocean, and around Antarctica. In these regions,compound events that typically last one week occur three to seven times more often than expected under the assumption ofindependence between MHWs and LChl events. The occurrence of compound MHW and LChl events varies on seasonalto interannual timescales. At the seasonal timescale, most compound events occur in summer in both hemispheres. At the10interannual timescale, the frequency of compound MHW and LChl events is strongly modulated by large-scale modes of naturalclimate variability such as the El Niño-Southern Oscillation, whose positive phase is associated with increased compoundevent occurrence in the eastern equatorial Pacific and in the Indian Ocean by a factor of up to four. Our results provide a firstunderstanding of where, when and why compound MHW and LChl events occur. Further studies are needed to identify theexact physical and biological drivers of these potentially harmful events in the ocean and their evolution under global warming.

High Temperature↗

Evaluation of Extreme Soil Moisture Patterns over the Sahel during the 2020 Growing Season

The African Sahel is an ecologically and climatically sensitive region, and thus is a valuable test case for examination of climate extremes. Above-average rainfall during the 2020 growing season (June-October) led to flooding in the West, Central and East Sahel, with implications for infrastructure, agriculture and disease outbreaks. In this study, we evaluate soil moisture patterns in the region during 2020 to assess and quantify the extremeness of the event. The primary tool is the NASA Soil Moisture Active Passive (SMAP) Level 4 surface soil moisture data. Daily, monthly, and seasonal anomalies are computed relative to SMAP’s long-term mean (2015-2021). Additional comparisons are made with longer-time-series data sets, including surface soil moisture from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2(MERRA-2; 1981-present) and precipitation from the African Rainfall Climatology, Version 2 (ARC2; 1983-present).Possible drivers of the extreme wet event are examined, including potential links to the concurrent 2020-21 La Niña event. Finally, we explore the connections between the extreme soil moisture and vector-borne disease outbreaks in the region in2020, namely, Rift Valley Fever in Mauritania and Chikungunya in Chad.

Soil Moisture↗

Cryobotics: Extreme Cold Environment Testing

The extreme cold environment test chamber was designed to conduct research in cryobotics; an area of study that focuses on robotic systems and rotating machinery operating in extreme cold environments including Earth, low Earth orbit, Mars, Moon, asteroids, Solar orbit, planetary orbit, or those encountered during travel among these destinations. The test chamber incorporates a modular dynamometer, consisting of a variety of brakes, torque sensors and motors to be easily interchanged between tests. Each test employs a unique test profile that incorporates different setpoints of applied torques and velocities for a given period or number of revolutions. The modularity of the dynamometer setup allows for any combination of motor, gearbox to be tested. The chamber has been used to run tests for various projects including Bulk Metallic Glass Gears (BMGG), Volatiles Investigating Polar Exploration Rover (VIPER), Intelligent Payload Experiment (IPEX), and Pilot Excavator. Various upgrades have been made to the extreme cold environment test chamber for the use of cryobotic research. These upgrades greatly increased the autonomous capabilities of the test set up by providing redundancies in the hardware and software. The redundancies were primarily added to protect the integrity of the cryohead. A new strapping and insulation method was performed to create the thermal conductive path from the actuators to the cryohead. The software was upgraded to include temperature setpoint control, further increasing the autonomous capabilities of the test. This paper goes into detail regarding the upgrades made to the extreme cold environment test chamber, as well as highlights the results from a COLDArm acceptance test.

Jonathan Drew Smith↗

Changing Intensity of Hydroclimatic Extreme Events Revealed by GRACE and GRACE-FO

Distortion of the water cycle, particularly of its extremes (droughts and pluvials), will be among the most conspicuous consequences of climate change. We applied a novel approach with terrestrial water storage observations from the GRACE and GRACE-FO satellites to delineate and characterize 1,056 extreme events during 2002-2021. Dwarfing all other events was an ongoing pluvial that began in 2019 and engulfed central Africa. Total intensity of extreme events was strongly correlated with global mean temperature, more so than with the El Nino Southern Oscillation or other climate indicators, suggesting that continued warming of the planet will cause more frequent, more severe, longer, and/or larger droughts and pluvials. In three regions, including a vast swath extending from southern Europe to southwestern China, the ratio of wet to dry extreme events decreased substantially over the study period, while the opposite was true in two regions, including sub-Saharan Africa from 5°N to 20°N.

Climate change↗

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. Our ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

artificial intelligence↗

Performance of Convection-Permitting and Convection-Parameterized Models in Reproducing the Extreme Precipitation Intensity Relationship with Surface Conditions

Here, this study investigates the warm-season extreme precipitation–temperature scaling relationship in CONUS404, a convection-permitting (4 km) Weather Research and Forecasting (WRF) Model simulation over the conterminous United States for the past four decades, and compares it with the WRF-Thermodynamic Global Warming (WRF-TGW) historical simulation at a coarser resolution (12 km) using parameterized convection. We also analyze the NCEP stage IV and NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) datasets as observational benchmarks. We examine how extreme precipitation intensity (EPI) varies with temperature and saturation deficit over representative regions based on hourly data. The stage IV and IMERG data show a similar pattern of EPI variation with temperature and saturation deficit, except that the EPI peak is lower in IMERG than in stage IV. Under dry and hot conditions, EPI decreases too rapidly with elevated saturation deficit in both CONUS404 and WRF-TGW compared to observations, but the performance of CONUS404 is superior to WRF-TGW. When the near-surface atmosphere is saturated or close to saturated, both CONUS404 and WRF-TGW produce higher peak values of EPI relative to the observational references; IMERG exhibits scaling rates close to the Clausius–Clapeyron (C–C) relationship, while CONUS404, WRF-TGW, and stage IV all demonstrate super-C–C scaling behaviors. Despite marked warming over the past four decades, in both CONUS404 and WRF-TGW, the scaling relationship between EPI and temperature in a saturated atmosphere remains stable and robust. This indicates a strong potential for the EPI–temperature scaling rate under saturation to be used as an emergent constraint in reducing uncertainties of future extreme precipitation projection.

Atmosphere↗

Modeling the impact of extreme summer drought on conventional and renewable generation capacity: Methods and a case study on the Eastern U.S. power system

Across recent years, there has been a growing prevalence of extreme weather events throughout the United States, posing significant challenges to the reliable and resilient operation of power systems. Specifically, summer droughts threaten to severely reduce available generation capacity to meet regional electricity demand, potentially leading to power outages. This underscores the importance of accurate resource adequacy (RA) assessment to ensure the reliable operation of the nation’s energy infrastructure. Accurately evaluating the usable capacity of regional generation fleets is a challenging undertaking due to the intricate interactions between power systems and hydro-climatic systems. Here, this paper proposes a systematic and analytical framework to evaluate the impacts of extreme summer drought events on the available capacity of various generating technologies, incorporating both meteorological and hydrologic factors. The framework provides detailed plant-level capacity derating models for hydroelectric, thermoelectric, and renewable power plants, facilitating evaluations with high temporal and spatial resolution. The application of the proposed impact assessment framework to the 2025 generation fleet of the real-world power system within the PJM and SERC regions of the United States yields insightful results. By analyzing the daily usable capacity of 6,055 at-risk generators across the study region, it shows that the summer capacity deration is most significant for hydroelectric and once-through thermal power plants, followed by recirculating thermal power plants and combustion turbines. In the event of the recurrence of the 2007 southeastern summer drought event in the near future, the generation fleet could experience a substantial reduction in available capacity, estimated at approximately 8.5 GW, compared to typical summer conditions. The sensitivity analysis reveals that the usable capacity of the generation fleet would suffer an even more significant decrease under conditions of increasingly severe summer droughts. The proposed approach and the findings of this study provide valuable methodologies and insights, empowering stakeholders to bolster the resilience of power systems against the potentially devastating effects of future extreme drought events.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Thiohalorhabdus methylotropha sp. nov., an extremely halophilic autotrophic methylotiotroph from hypersaline lakes

So far, there have been no reports of trimethylamine (TMA)-utilizing extremely halophilic microorganisms in hypersaline habitats. Our aerobic enrichments at 4 M total Na + with 5 mM TMA inoculated with surface sediments from hypersaline soda (at pH 9.5) or chloride-sulfate (at pH 7) lakes in southwestern Siberia were successful only for the latter. The initial enrichment included both bacteria and haloarchaea but only the bacterial component was able to grow as a pure culture with TMA. Strain Cl-TMA forms a new-species lineage within the genus Thiohalorhabdus which includes extremely halophilic and obligate lithoautotrophic sulfur-oxidizing gammaproteobacteria. Cl-TMA can grow methyloautotrophically utilizing TMA, dimethylamine (DMA) and methanol (MeOH) as the electron donors or chemolithoautotrophically with thiosulfate. Mixotrophic growth was also observed with the three methyl compounds and thiosulfate. Carbon is assimilated autotrophically via the Calvin-Benson-Basham pathway. Unlike the type species of Thiohalorhabdus, T. denitrificans , Cl-TMA was incapable of anaerobic growth via denitrification. The isolate belongs to extreme halophiles growing between 2.5 and 5 M NaCl with an optimum at 3–3.5 M. Genome analysis identified two gene clusters coding for PQQ-dependent methanol dehydrogenases (MxaFI and XoxF), four homologues of the formaldehyde activating enzymes (Faes), a TMA/DMA oxidation locus, and two cluster of genes encoding an N-methylglutamate dehydrogenase pathway (NMGP) for methylamine oxidation. The first steps of C 1 -subtrate conversions are followed by the tetrahydrofolate (THF)-linked and tetrahydromethanopterin (H4MPT)-linked formaldehyde oxidation pathways and two formate dehydrogenases. All of those signatures of methylotrophy were absent in T. denitrificans . In contrast, genes for two key sulfur oxidation enzymes, thiosulfate dehydrogenase TsdAB and sulfide dehydrogenase FccAB, that are present in the type species are missing in Cl-TMA. Thiosulfate is oxidized to sulfate by a combination of an incomplete Sox cycle and an sHdr system. Strain Cl-TMA T (JCM 35977 = UQM 41915) is proposed to be classified as Thiohalorhabdus methylotrophus sp. nov.

59 BASIC BIOLOGICAL SCIENCES↗

Extreme Temperature Cryptography Based On Nitrogen-Incorporated Ultrananocrystalline Diamond

Physical entropy sources that remain stable under extreme temperatures are essential for cryptography in emerging technological frontiers in deep space exploration, geothermal energy harvesting, and nuclear energy. However, conventional semiconductor platforms fail to generate stable and reliable cryptographic keys above 200 degrees C due to performance degradation. Here, we report a diamond-based cryptographic primitive that exploits the defect-rich sp 2 -bonded grain boundary network in nitrogen-incorporated ultrananocrystalline diamond (n-UNCD) film as a robust entropy source to generate cryptographic keys that remain operationally stable even after enduring extreme temperatures of 700 degrees C for 54 h while also surviving thermal cycling between room temperature and 700 degrees C for 48 h. The strength of the generated keys is assessed through several cryptographic metrics such as bit uniformity, entropy, hamming distances, and correlation coefficients, all of which are found to be near their respective ideal values. Moreover, the generated keys pass the NIST SP 800 and SP 800-90B tests and are also resilient to supply bias variations and a regression-based machine learning attack model based on the Fourier series. The robustness of the keys is attributed to the better thermal stability and chemical inertness of the n-UNCD film. This is supported by high-resolution energy-dispersive X-ray spectroscopy (EDS), which shows no significant lateral diffusion of metal atoms into the n-UNCD layer, and by Raman spectroscopy, which reveals no significant changes in the bonding configuration of the n-UNCD structure. Our findings highlight the remarkable potential of n-UNCD film for extreme environment cryptography by expanding the operational limits of conventional hardware security platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique

Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R 2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.

54 ENVIRONMENTAL SCIENCES↗

Future Changes in Midwest Extreme Precipitation Depend on Storm Type

Midwestern U.S. extreme precipitation is associated with multiple storm types including mesoscale convective systems (MCSs) and/or training thunderstorms, tropical cyclone (TC) remnants, and winter storms. Anthropogenic warming is expected to increase climatological precipitation globally, however, there may be little correspondence with regional storm-based changes. Furthermore, uncertainty remains in precipitation-temperature scaling due to use of convective parameterization in most global models. In this study, we investigated historically impactful extreme precipitation events from multiple types of Midwest storms using the Weather Research and Forecasting model at convection-permitting resolution. We simulated five-member ensembles of historical hindcasts and experiments representing the storms in the future using the pseudo-global warming method. We found that future precipitation changes depend on storm type, with increases near Clausius-Clapeyron (CC) for winter storms, no consensus for MCSs and/or training thunderstorms, and sub-CC increases for TC remnants. This research highlights the importance of considering storm type in future extreme precipitation projections.

54 ENVIRONMENTAL SCIENCES↗

A Hybrid Dynamic/Steady-State Tool With Protection Simulation for Cascading-Outage Analysis of Extreme Events in Power Systems

The bulk electric power grid is subject to vulnerabilities from component outages, which in certain combinations (extreme events) might lead to cascading outages. Some of these outages can be severe enough to trigger brownouts and blackouts. Much is known about mitigating the first few failures near the beginning of a cascade, but there are few established methods and tools for directly analyzing the risks of cascading component outages over a longer time scale. Current power system tools have limited ability to perform detailed and accurate cascading-outage analysis, which could be computationally intensive. The Dynamic Contingency Analysis Tool (DCAT) enables power system planning engineers to more realistically assess the consequences of extreme contingencies and potential cascading events across their systems and interconnections. DCAT has several unique features: (i) detailed hybrid dynamic and steady-state analysis of power systems to mimic real-world cascading outages, (ii) detailed modeling of protection systems embedded in the dynamic simulation, (iii) simulation of corrective action after transients, (iv) simulation of islanding , and (v) high-performance computing capability to simulate a large number of contingencies in a reasonable time. DCAT outputs will help find technically sound solutions to reduce the risk of cascading outages. This paper provides details of DCAT methodology and shows its capabilities with extreme events on real-world cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Intelligent Manufacturing for Extreme Environments Conference Proceedings

The Intelligent Manufacturing for Extreme Environments (IMEE) workshop was held at the Center for Advanced Energy Studies (CAES) in Idaho Falls, Idaho, May 2–3, 2023, in support of the United States (U.S.) National Science Foundation (NSF) Established Program to Stimulate Competitive Research: Workshop Opportunities (EPSCoR-WO) program. This workshop featured keynote speakers, panels, and breakout sessions with 58 participants. Nuclear reactors need to operate under extreme service conditions, such as high temperatures, corrosive environments, and high-radiation doses. Hence, reactor components must be able to withstand those conditions. The participants envision a future where on demand manufacture of components for small modular reactors (SMRs), microreactors, and other advanced reactor designs are possible. In this future, regulatory bodies accept validated manufacturing processes and standardized feedstocks, thus eliminating the need for individual component testing. However, the necessary technologies and regulatory policies needed for this future do not exist today. Successful innovation would revolutionize the nuclear power sector, enable fast commercial development, create economic opportunities in the U.S., reduce the carbon footprint and associated risks, and promote a skilled and highly competitive workforce. The objective of the workshop was to convene world-class experts, researchers, educators, and students to identify gaps and envision solutions for five interrelated challenges for intelligent manufacturing in extreme environments. The key outcomes of the conference were: (1) to take the opportunity for researchers and educators to network and form collaborations; and (2) to produce a full report to inform policy-makers, industry, and the academic community of various challenges and opportunities in the nuclear energy sector.

36 MATERIALS SCIENCE↗

Final technical report for DE-SC0022255: Discovering Physically Meaningful Structures from Climate Extreme Data

The past two decades have witnessed natural disasters and extreme weather events that affect millions of people. At the same time, the data volume from high-resolution climate models, satellite, in-situ and ground-based measurements have substantially increased to petabyte scales. These new and readily accessible datasets create the previously missing pipeline required for scientific machine learning (ML) and therefore new opportunities for improved understanding and prediction capability of climate extreme events. This project developed a deep latent variable model framework to discover physically meaningful hidden structures from high-dimensional, spatiotemporal climate extreme data.

97 MATHEMATICS AND COMPUTING↗

Data Converters Performance at Extreme Temperatures

Space missions often require radiation and extreme-temperature hardened electronics to survive the harsh environments beyond earth's atmosphere. Traditional approaches to preserve electronics incorporate shielding, insulation and redundancy at the expense of power and weight. However, a novel way of bypassing these problems is the concept of evolutionary hardware. A reconfgurable device, consisting of several switches interconnected with analog/digital parts, is controlled by an evolutionary processor (EP). When the EP detects degradation in the circuit it sends signals to reconfgure the switches, thus forming a new circuit with the desired output. This concept has been developed since the mid-90s, but one problem remains - the EP cannot degrade substantially. For this reason, extensive testing at extreme temperatures (-180' to 120(deg)C) has been done on devices found on FPGA boards (taking the role of the EP) such as the Analog to Digital and the Digital to Analog Converter. Analysis of the results has shown that FPGA boards implementing EP with some compensation may be a practical solution to evolving circuits. This paper describes results on the tests of data converters at extreme temperatures.

evolvable hardware↗