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Development of a Numerical Model of Hypervelocity Impact into a Pressurized Composite Overwrapped Pressure Vessel

As the outlook for space exploration becomes more ambitious and spacecraft travel deeper into space than ever before, it is increasingly important that propulsion systems perform reliably within the space environment. The increased reliability compels designers to increase design margin at the expense of system mass, which contrasts with the need to limit vehicle mass to maximize payload. Such are the factors that motivate the integration of high specific strength composite materials in the construction of pressure vessels commonly referred to as composite overwrapped pressure vessels (COPV). The COPV consists of a metallic liner for the inner shell of the COPV that is stiff, negates fluid permeation and serves as the anchor for composite laminates or filaments, but the liner itself cannot contain the stresses from the pressurant it contains. The compo-site-fiber reinforced polymer (CFRP) is wound around the liner using a combination of hoop (circumferential) and helical orientations. Careful consideration of wrap orientation allows the composite to evenly bear structural loading and creates the COPV's characteristic high strength to weight ratio. As the CFRP overwrap carries most of the stresses induced by pressurization, damage to the overwrap can affect mission duration, mission success and potentially cause loss-of-vehicle/loss-of-crew. For this reason, it is critical to establish a fundamental understanding of the mechanisms involved in the failure of a stressed composite such as that of the COPV. One of the greatest external threats to the integrity of a spacecraft's COPV is an impact from the meteoroid and orbital debris environments (MMOD). These impacts, even from submillimeter particles, generate extremely high stress states in the CFRP that can damage numerous fibers. As a result of this possibility, initial assumptions in survivability analysis for some human-rated NASA space-craft have assumed that any alteration of the vessel due to impact is considered a catastrophic failure. This assumption is conservative and made due to lack of knowledge on the level of allow-able damage to the composite overwrap that can be sustained and still allow successful completion of the mission. To quantify the allowable damage level to the composite overwrap involves assessing stress redistribution following damage as well as evaluating possible time-dependent mechanisms involved in the COPV response to an impact event. Limited published work in this subject has shown that COPV can withstand at least some level of damage due to high energy impacts. These observations have been confirmed and expanded upon in recent experimental research performed by NASA. This research has demonstrated that there is not only robustness in a COPV to compensate for CFRP damage, but has also identified two significant failure modes for pressurized COPV. The lowest threshold failure mode involves the perforation of the vessel, and the highest threshold failure mode is the catastrophic rupture. While both of these failure modes mean a loss of the COPV, system robustness affords some tolerance to the venting as opposed to the more catastrophic rupture. As a consequence, it is necessary to understand the conditions that result in the transition between these failure modes. The aforementioned experimental research has been performed in both the unpressurized and pressurized condition to identify the damage level that triggered the failure thresh-old. This COPV test program was sponsored by the NASA Engineering and Safety Center (NESC), and tests were performed at NASA White Sands Test Facility (WSTF). Planning and coordination were provided by NASA JSC Hypervelocity Impact Technology (HVIT) group, and the COPVs were provided by the ISS Program. Unpressurized testing has been conducted at the pressure of the vacuum test chamber, while, the pressurized testing has been conducted at 290 +/- 10 bar (4,200  100 psi) using nitrogen as the pressurizing gas, which corresponds to the design pressure for the target COPV. In this research, spherical aluminum projectiles with varying diameter has been chosen as the impactor. For the unpressurized COPV, the dependence of penetration up to the dependence of hole size in the liner has been obtained as a function of impact conditions. For the pressurized research, the dependence of penetration up to rupture has been obtained as a function of im-pact conditions. Two representative post-test photographs of the failed COPV's from a nor-mal impact into the COPV surface are shown in Fig. 1. These images display the dramatic difference between failure modes, venting (Fig. 1a) and rupture (Fig. 1b). For venting, liner perforation, severed composite fibers/tows and ply delamination are commonly observed damage characteristics of this COPV failure mode. In the case of rupture, the COPV typically experienced a separation of its domed regions and severe break-up of the cylindrical region. Fully understanding the transition from venting to rupture experimentally is costly and potentially unachievable for conditions that cannot be generated in the laboratory. These shortcomings have motivated the performance of three-dimensional numerical simulations to expand the existing experimental database. These simulations have been carried out with the nonlinear-structural-dynamics, analysis-tool, CTH. A typical pressure contour plot from an impact simulation of an entire COPV is shown in Fig. 2. To generate the COPV stress state without initiating a shock wave, the pressure in the simulated COPV is ramped up to the final pressure over a millisecond prior to impact of the projectile with nitrogen gas. Figure 2a shows the system in this initial condition. After one millisecond, a projectile is initiated into the simulation and impacts the COPV. Figure 2b shows the system after this impact. In the figure, the onset of venting is represented as the change in pressure (μbar), red to green, at the perforation site. Also seen in the figure is the eroded projectile that had passed into the COPV vessel with the generated shock wave in the pressurant propagating just ahead of the material. In this paper, pertinent experimental details and the development of the material constitutive models necessary for this work along with the efforts to validate their use are dis-cussed. The simulation results are presented and compared with the NASA experimental observations. While work is on-going from this effort, early observations pertinent to the failure threshold are presented.

Garcia, M. A.↗

Study of atmospheric parameters measurements using MM-wave radar in synergy with LITE-2

The Lidar In-Space Technology Experiment, (LITE), has been developed, designed, and built by NASA Langley Research Center, to be flown on the space shuttle 'Discovery' on September 9, 1994. Lidar, which stands for light detecting and ranging, is a radar system that uses short pulses of laser light instead of radio waves in the case of the common radar. This space-based lidar offers atmospheric measurements of stratospheric and tropospheric aerosols, the planetary boundary layer, cloud top heights, and atmospheric temperature and density in the 10-40 km altitude range. A study is being done on the use, advantages, and limitations of a millimeterwave radar to be utilized in synergy with the Lidar system, for the LITE-2 experiment to be flown on a future space shuttle mission. The lower atmospheric attenuation, compared to infrared and optical frequencies, permits the millimeter-wave signals to penetrate through the clouds and measure multi-layered clouds, cloud thickness, and cloud-base height. These measurements would provide a useful input to radiation computations used in the operational numerical weather prediction models, and for forecasting. High power levels, optimum modulation, data processing, and high antenna gain are used to increase the operating range, while space environment, radar tradeoffs, and power availability are considered. Preliminary, numerical calculations are made, using the specifications of an experimental system constructed at Georgia Tech. The noncoherent 94 GHz millimeter-wave radar system has a pulsed output with peak value of 1 kW. The backscatter cross section of the particles to be measured, that are present in the volume covered by the beam footprint, is also studied.

Andrawis, Madeleine Y.↗

Calibration of the Geosar Dual Frequency Interferometric SAR

GeoSAR is an airborne, interferometric Synthetic Aperture Radar (INSAR) system for terrain mapping, currently under development by a consortium including NASA's Jet Propulsion Laboratory (JPL), Calgis, Inc., and the California Department of Conservation (CalDOC) with funding provided by the Topographic Engineering Center (TEC) of the U.S. Army Corps of Engineers and the Defense Advanced Research Projects Agency (DARPA). The radar simultaneously maps swaths on both sides of the aircraft at two frequencies, X-Band and P-Band. For the P-Band system, data is collected for two across track interferometric baselines and at the crossed polarization. The aircraft position and attitude are measured using two Honeywell Embedded GPS Inertial Navigation Units (EGI) and an Ashtech Z12 GPS receiver. The mechanical orientation and position of the antennas are actively measured using a Laser Baseline Metrology System (LBMS). In the GeoSAR motion measurement software, these data are optimally combined with data from a nearby ground station using Ashtech PNAV software to produce the position, orientation, and baseline information are used to process the dual frequency radar data. Proper calibration of the GeoSAR system is essential to obtaining digital elevation models (DEMS) with the required sub-meter level planimetric and vertical accuracies. Calibration begins with the determination of the yaw and pitch biases for the two EGI units. Common range delays are determined for each mode, along with differential time and phase delays between channels. Because the antennas are measured by the LBMS, baseline calibration consists primarily of measuring a constant offset between mechanical center and the electrical phase center of the antennas. A phase screen, an offset to the interferometric phase difference which is a function of absolute phase, is applied to the interferometric data to compensate for multipath and leakage. Calibration parameters are calculated for each of the ten processing modes, each of the operational bandwidths (80 and 160 MHZ), and each aircraft altitude. In this talk we will discuss the layout calibration sites, the synthesis of data from multiple flights to improve the calibration, methods for determining time and phase delays, and techniques for determining radiometric and polarimetric quantities. We will describe how calibration quantities are incorporated into the processor and pre-processor. We will demonstrate our techniques applied to GeoSar data and assess the stability and accuracy of the calibration. This will be compared to the modeled performance determined from calibrating the output of a point target simulator. The details of baseline determination and phase screen calculation are covered in related talks.

Chapine, Elaine↗

Megadroughts in the Common Era and the Anthropocene

Megadroughts, often lasting multiple decades, have caused major ecological and societal disturbances in the past. While most research has focused on megadroughts in North America, the concept has gained increased international attention in recent years. In this Review, we discuss shared causes and features of Common Era and future megadroughts. Paleoclimate reconstructions spanning the last 2,000 years document the occurrence of megadroughts on every continent, save Antarctica. Megadroughts are often linked to decadal variations in sea surface temperatures, with radiative forcing and land-atmosphere interactions acting as secondary factors. Anthropogenic climate change has already contributed to recent megadroughts in southwestern North America and Chile-Argentina and will likely increase future megadrought risk and severity in many regions. Notably, future megadroughts will be differentiated from past events through higher temperatures, which act as the main driver of increased risk, severity, and impacts. Major deficiencies in our understanding of natural and anthropogenic megadrought processes remain, however. These include 1) sparse high-resolution paleoclimate information over some regions, 2) incomplete representations of internal variability and land-surface processes in climate models, and 3) the undetermined capacity of water-resource management systems to manage megadrought impacts. Resolving these key uncertainties will be necessary to increase confidence in projections of future megadrought risk and resiliency planning.

Droughts↗

Enhanced Flight Dynamics Models with Aerodynamic Interference for Real-Time Simulation of VTOL Concept Vehicles

In an effort to establish common models to support the Advanced Air Mobility (AAM) community, NASA has designed a fleet of VTOL configuration reference models. Advanced Rotorcraft Technologies (ART) in cooperation with the NASA Ames Aeromechanics branch has developed FLIGHTLAB simulation models for several of these AAM VTOL concept vehicles. These simulation models are real-time capable while maintaining accurate flight dynamic characteristics with enhanced interference simulation by extracting important modeling parameters from Viscous Vortex Particle Method (VVPM). The focus of this paper is threefold. First, it introduces the simulation models developed and describes their modeling characteristics important to control and flight dynamics simulation. Second, the method for deriving the interference coefficients between model components such as rotors and wings is outlined. Implementation of the method for the lift+cruise and tiltwing models are discussed in detail. Third, the accuracy of the interference enhancement is assessed, with emphasis placed on the impacts to trim and flight dynamic characteristics. The interference enhancement method is further used to evaluate configuration design decisions by quantifying performance aspects of interference. This research effort culminated in simulation models for the AAM VTOL concept vehicles, with proper interference and real-time capability.

Flight Dynamics↗

An overview of data tools for representing and managing building information and performance data

Building information modeling (BIM) has been widely adopted for representing and exchanging building data across disciplines during building design and construction. However, BIM's use in the building operation phase is limited. With the increasing deployment of low-cost sensors and meters, as well as affordable digital storage and computing technologies, growing volumes of data have been collected from buildings, their energy services systems, and occupants. Such data are crucial to help decision makers understand what, how, and when energy is consumed in buildings—a critical step to improving building performance for energy efficiency, demand flexibility, and resilience. However, practical analyses and use of the collected data are very limited due to various reasons, including poor data quality, ad-hoc representation of data, and lack of data science skills. To unlock value from building data, there is a strong need for a toolchain to curate and represent building information and performance data in common standardized terminologies and schemas, to enable interoperability between tools and applications. This study selected and reviewed 24 data tools based on common use cases of data across the building life cycle, from design to construction, commissioning, operation, and retrofits. The selected data tools are grouped into three categories: (1) data dictionary or terminology, (2) data ontology and schemas, and (3) data platforms. The data are grouped into ten typologies covering most types of data collected in buildings. This study resulted in five main findings: (1) most data representation tools can represent their intended data typologies well, such as Green Button for smart meter data and Brick schema for metadata of sensors in buildings and HVAC systems, but none of the tools cover all ten types of data; (2) there is a need for data schemas to represent the basis of design data and metadata of occupant data; (3) standard terminologies such as those defined in BEDES are only adopted in a few data tools; (4) integrating data across various stages in the building life cycle remains a challenge; and (5) most data tools were developed and maintained by different parties for different purposes, their flexibility and interoperability can be improved to support broader use cases. Finally, recommendations for future research on building data tools are provided for the data and buildings community based on the FAIR principles to make data Findable, Accessible, Interoperable, and Reusable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Kirigami-Inspired Self-Assembly of 3D Structures

Self-assembly of 3D structures introduce an attractive and scalable route to realize reconfigurable and functionally capable mesoscale devices without human intervention. A common approach for achieving this is to utilize stimuli-responsive folding of hinged structures, which requires the integration of different materials and/or geometric arrangements along the hinges. It is also demonstrated that the inclusion of Kirigami cuts in planar, hingeless bilayer thin sheets can be used to produce complex 3D shapes in an on-demand manner. Nonlinear finite element models are developed to elucidate the mechanics of shape morphing in bilayer thin sheets and verify the predictions through swelling experiments of planar, millimeter-scaled PDMS (polydimethylsiloxane) bilayers in organic solvents. Building upon the mechanistic understandings, The transformation of Kirigami-cut simple bilayers into 3D shapes such as letters from the Roman alphabet (to make “ADVANCED FUNCTIONAL MATERIALS”) and open/closed polyhedral architectures is experimentally demonstrated. A possible application of the bilayers as tether-less optical metamaterials with dynamically tunable light transmission and reflection behaviors is also shown. As the proposed mechanistic design principles could be applied to a variety of materials, this research broadly contributes toward the development of smart, tetherless, and reconfigurable multifunctional systems.

36 MATERIALS SCIENCE↗

A Chromosome-Scale Genome Assembly of the Flax Rust Fungus Reveals the Two Unusually Large Effector Proteins, AvrM3 and AvrN

Rust fungi comprise thousands of species, many of which cause disease on important crop plants. The flax rust fungus Melampsora lini has been a model species for the genetic dissection of plant immunity since the 1940s; however, the highly fragmented and incomplete reference genome has so far hindered progress in effector gene discovery. Here, we generated a fully phased, chromosome-scale assembly of the two nuclear genomes of M. lini strain CH5, resolving an additional 320 Mbp of the sequence. The 482-Mbp dikaryotic genome is at least 79% repetitive, with a large proportion (approximately 40%) of the genome comprising young, highly similar transposable elements. The assembly resolves the known effector gene loci, some of which carry complex duplications that were collapsed in the previous assembly. Using a genetic map followed by manual correction of gene models, we identified the AvrM3 and AvrN genes, which encode unusually large fungal effector proteins and trigger defense responses when co-expressed with the corresponding resistance genes. We located the genes linked to the tetrapolar mating system on chromosomes 4 and 9, but in contrast to the cereal rusts that have one pheromone receptor gene per haplotype, in flax rust, three pheromone receptor genes were found, with two of them closely linked on one haplotype. Taken together, we show that a high-quality assembly is crucial for resolving complex gene loci, and given the increasing number of fungal effectors of large size, the commonly applied criterion for effector candidates of being small proteins needs to be reconsidered.

Melampsora↗

Clean energy technology pathways from research to commercialization: Policy and practice case studies

Clean energy research and development (R and D) leading to commercial technologies is vital to economic development, technology competitiveness, and reduced environmental impact. Over the past 30 years, such efforts have advanced technology performance and reduced cost by leveraging network effects and economies of scale. After demonstrating promise in applied R and D, successful clean energy and energy efficiency technologies are incorporated into an initial product sold by the private sector. Despite its importance, processes by which first commercialization occurs are difficult to generalize while capturing specific insights from practitioners in markets and technologies. This paper presents a policy-focused qualitative assessment of the first commercialization of four diverse energy technologies: thin film photovoltaics, wind turbine blades, dual-stage refrigeration evaporators, and fuel cells for material handling equipment. Each technology presents distinct value propositions, markets, and regulatory drivers. The case studies indicate three common characteristics of successful first commercialization for new energy technologies: 1) good fit between the technology, R&D infrastructure, and public-private partnership models; 2) high degree of alignment of government regulations and R&D priorities with market forces; and 3) compatibility between time scales required for R&D, product development, and opportunities. These findings may inform energy investment decision-making, maximize benefits from R&D, and advance the transition to a low-emission future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Estimation of pollen productivity and dispersal: How pollen assemblages in small lakes represent vegetation

Abstract Quantitative understanding of vegetation dynamics over timespans beyond a century remains limited. In this regard, the pollen‐based reconstruction of past vegetation enables unique research opportunities by quantifying changes in plant community compositions during hundreds to thousands of years. Critically, the methodological basis for most reconstruction approaches rests upon estimates of pollen productivity and dispersal. Previous studies, however, have reached contrasting conclusions concerning these estimates, which may be perceived to challenge the applicability and reliability of pollen‐based reconstruction. Here we show that conflicting estimates of pollen production and dispersal are, at least in part, artifacts of fixed assumptions of pollen dispersal and insufficient spatial resolution of vegetation data surrounding the pollen‐collecting lake. We implemented a Bayesian statistical model that related pollen assemblages in surface sediments of 33 small lakes (<2 ha) in the northeastern United States, with surrounding vegetation ranging from 10 1 to >10 5 m from the lake margin. Our analysis revealed three key insights. First, pollen productivity is largely conserved within taxa and across forest types. Second, when local (within a 1‐km radius) vegetation abundances are not considered, pollen‐source areas may be overestimated for some common taxa (Cupressaceae, Pinus , Quercus , and Tsuga ). Third, pollen dispersal mechanisms may differ between local and regional scales; this is missed by pollen‐dispersal models used in previous studies. These findings highlight the complex interactions between vegetation heterogeneity on the landscape and pollen dispersal. We suggest that, when estimating pollen productivity and dispersal, both detailed local and extended regional vegetation must be taken into account. Also, both deductive (mechanistic models) and inductive (statistical models) approaches are needed to better understand the emergent properties of pollen dispersal in heterogeneous landscapes.

54 ENVIRONMENTAL SCIENCES↗

Development of New g-function Data for Simulating a Novel Shallow Bore Ground Heat Exchanger

Geothermal heat pump (GHP), which is also referred as ground source heat pump, is the most energy-efficient technology for space heating and cooling. However, the application of GHP is hindered by its high initial cost, of which approximately 30% is for the ground heat exchanger (GHE). In recent years, researchers have developed different types of shallow bore ground heat exchangers (SBGHE) intending to reduce the cost of drilling. The ability to predict the thermal response of an SBGHE is critical for sizing SBGHE. While g-functions have been commonly used for predicting the thermal response of conventional vertical bore ground heat exchangers (VBGHE), they cannot be directly used for predicting the performance of SBGHE because they did not account for the impacts of the seasonal variation of the soil temperature along with the depth of an SBGHE. In addition, an SBGHE has a larger thermal mass within the borehole than the VBGHE due to the larger borehole diameter of SBGHE. This study develops new g-function data pairs for a new design of SBGHE, which is named Underground Thermal Battery (UTB). Impacts of the seasonal variation of soil temperature on the thermal response of UTB were accounted for by superposing a time-dependent soil temperature onto the g-functions calculated with a numerical model that assumes constant undisturbed soil temperature. The TOUGH program was used to predict the thermal response of several configurations involving multiple UTBs. The results indicate that the proposed methodology is appropriate to generate g-functions for the UTB, and the g-function value of UTB is much lower than that of VBGHE in the time range of 15 min to 1 year due to the large thermal mass and convection heat transfer within the UTB.

Shi, Liang↗

Mechanisms of Low-Level Jet Formation in the U.S. Mid-Atlantic Offshore

Low level jets (LLJs) in the atmosphere exhibit a local windspeed maximum inthe boundary layer and are commonly observed both over land and in coastal environments. Because LLJs present strong positive shear beneath the maximum (or "jet nose") and negative shear above the nose, they pose a challenge to future offshore wind technology through their impacts on turbine performance and wakes. Summertime LLJs in the Great Plains have been attributed to frictional decoupling triggering an inertial oscillation, whilecoastal LLJs in California or the North Sea have additional driving mechanisms such as baroclinic forcing. By comparison, LLJs in the coastal US Mid-Atlantic have received less attention, with conflicting evidence about the mechanism that triggers these high shear events. Motivated by future wind energy development in the region, this work elucidates the atmospheric mechanisms of LLJ formation in the US Mid-Atlantic. Using observational data from two floating LiDAR buoys deployed bythe New York State Energy Research and Development Authority in the NY Bight, we identify four sustained LLJ events whose windspeeds and directions are well predicted by a WRF simulation (Weather Research and Forecasting Model). From analysis of the WRF data, we find that the four case studies provide evidence of concurrent inertial oscillation, reduced vertical mixing, and baroclinicity. In addition, we use simple atmospheric dynamics and a single-column-model to compare the relative contribution of each of these mechanisms to triggering the LLJ. By improving understanding and predictability of coastal mid-Atlantic LLJs, this work reduces uncertaintiesof wind energy deployment in the region, aiding the US's transition toward renewable energy.

atmospheric boundary layers↗

Atomic layer deposition of nanofilms on porous polymer substrates: Strategies for success

Atomic layer deposition (ALD) is a versatile technique for engineering the surfaces of porous polymers, imbuing the flexible, high-surface-area substrates with inorganic and hybrid material properties. Previously reported enhancements include fouling resistance, electrical conductance, thermal stability, photocatalytic activity, hydrophilicity, and oleophilicity. However, there are many poorly understood phenomena that introduce challenges in applying ALD to porous polymers. In this paper, we address five common challenges and ways to overcome them: (1) entrapped precursor, (2) embrittlement, (3) film fracture, (4) deformation, and (5) pore collapse. These challenges are often interrelated and can exacerbate one another. To investigate these phenomena, we applied various ALD chemistries to porous polymers including polyethersulfone, polysulfone, polyvinylidene fluoride, and polycarbonate track-etched membranes. Reaction-diffusion modeling revealed why certain precursors and processing conditions result in embrittling subsurface material growth, entrapment of unreacted precursors, and nongrowth. We quantify the limits of ALD processing temperatures that are dictated by thermal expansion mismatch and can lead to fractured ALD films. The results herein allow us to make recommendations to avoid, mitigate, or overcome the difficulties encountered when performing ALD and plasma-enhanced ALD on porous polymers. We intend this article to serve as a “lessons learned” guide informed by previous experience to provide a better understanding of the difficulties and limitations of ALD on porous polymers and knowledge-based guidelines for successful depositions. This knowledge can accelerate future research and help experimentalists navigate and troubleshoot as they expose porous polymers to reactive precursor vapors.

36 MATERIALS SCIENCE↗

A Grand Challenge "Uncertainty Project" to Accelerate Advances in Earth System Predictability: AI-Enabled Concepts and Applications

This proposal is emerging from GISS ModelE3 ESM development in the area of cloud physics, so we begin with an example of research needs/gaps from that work. Here, some of our greatest development concerns arise where we lack fundamental process-level understanding, as in ice formation. Namely, it is currently unclear what is the main process that is forming the majority of ice crystals in commonly occurring convection, apparently via secondary ice production at warm temperatures. We are keenly awaiting laboratory data for candidate mechanisms, which is not yet in hand to crucially establish their efficiency. Our progress is also hampered by a lack of uncertainty characterization in currently available measurements of ice crystal number size distributions. Furthermore, the same multiplication process may be responsible for a majority of ice crystals in many extratropical mixed-phase clouds, whose variable representation in CMIP6 ESMs may be a leading cause of differences in cloud phase feedback and ECS. Yet we have been required to deliver an ESM with the cloud physics knowledge at hand. The proposed grand challenge project is AI-enabled via application of machine learning (ML) to climate model and observational data streams (focal area 3), and applications include AI-guided observing system design and model/component/parameterization selection (areas 1 and 2). The project is structurally agnostic as to whether model or observing system components use AI approaches or not, but uncertainties must be estimated and propagatable in both.

58 GEOSCIENCES↗

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

System modeling for grid-interactive efficient building applications

Despite the abundance of research applications of system modeling in grid-interactive efficient buildings (GEBs), the transfer of those applications to real-world practices is still in its early stages. This is partially due to the lack of a summary on how system modeling should be established for a given application of GEBs. Here, we fill this gap by providing an extensive survey of the literature on system modeling for different GEBs that have been produced in the past decade. This survey involves over 300 relevant journal articles from the building community, the power system community, and the society of control. Specifically, we first identified key requirements of system modeling for GEBs based on various types of applications discussed in those publications. We then summarized the system modeling applications from those publications, in terms of their assumptions, modeling approach, and simulation. After that, we analyzed different assumptions made for various applications, the extent to which those modeling approaches satisfied the key requirements, and how those approaches can be scaled up for large-scale applications, which are quite common in GEBs. In addition, we gave insights on how to use system modeling for different applications in GEBs. At the end, we provided recommended directions for future studies to fully unleash the potentials of system modeling to support GEBs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The role of international collaboration in the United States geologic disposal research program

Abstract. More than a decade ago, the United States disposal program discontinued all research activities focused on the unsaturated fractured tuff formation at Yucca Mountain as the geologic disposal site for spent fuel and high-level radioactive waste. A new research and development (R&D) program was initiated to provide a sound technical basis for alternative disposal options across clay, crystalline, and salt rocks. The goals of this broad program were (and still are) to (1) increase confidence in the robustness of generic disposal concepts, (2) develop the science and engineering tools needed to support disposal concept implementation, and (3) conduct R&D on the direct disposal of existing dual-purpose (storage and transportation) canisters. Recognizing the benefits of international collaboration toward the common goal of safely and efficiently managing the back end of the nuclear fuel cycle, the program emphasized international cooperation as an effective strategy for sharing information and knowledge. In a multi-laboratory effort coordinated by Lawrence Berkeley National Laboratory, the United States Department of Energy (DOE) program established formal and informal cooperation partnerships with several international initiatives and institutions and developed a number of collaborative R&D activities in important research areas, such as engineered barrier integrity, near-field perturbations, radionuclide transport, performance assessment, and methods for characterization and monitoring of engineered and natural barriers. This presentation gives an overview of these R&D activities, with a specific focus on activities that improve our current understanding of the coupled thermal–hydrological–mechanical–chemical (THMC) processes occurring in engineered and natural barriers. We start with a brief review of selected international collaboration initiatives and then describe a few specific collaboration projects. We focus specifically on such studies that use experimental data sets provided by international research cooperation for joint modeling work to increase confidence in performance-relevant predictions of coupled processes. Overall, the focus on international collaboration has allowed deep engagement of US researchers with the international waste management R&D community in terms of best practices, new scientific advances, state-of-the-art simulation tools, new monitoring and performance confirmation approaches, and lessons learned. The joint R&D with international researchers, worldwide sharing of knowledge and experience, and access to relevant data and experiments from a variety of host rocks have helped our researchers to significantly improve their understanding of the current technical basis for disposal in a range of potential host rock environments. International collaboration also provides ample opportunity for training and educating junior staff that are well suited to move the United States disposal research program forward into the next decades, a promising avenue for developing a next-generation workforce of disposal scientists.

Birkholzer, Jens T.↗

Comparisons Between the Distributions of Dust and Combustion Aerosols in MERRA-2, FLEXPART and CALIPSO and Implications for Deposition Freezing Over Wintertime Siberia

Aerosol distributions have a potentially large influence on climate-relevant cloud properties but can be difficult to observe over the Arctic given pervasive cloudiness, long polar nights, data paucity over remote regions, and periodic diamond dust events that satellites can misclassify as aerosol. We compared Arctic 2008–2015 mineral dust and combustion aerosol distributions from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis products, and the FLEXible PARTicle (FLEXPART) dispersion model. Based on coincident, seasonal Atmospheric Infrared Sounder (AIRS) Arctic satellite meteorological data, diamond dust may occur up to 60 % of the time in winter, but it hardly ever occurs in summer. In its absence, MERRA-2 and FLEXPART each predict the vertical and horizontal distribution of large-scale patterns in combustion aerosols with relatively high confidence (Kendall tau rank correlation > 0.6), although a sizable amount of variability is still unaccounted for. They do the same for dust, except in conditions conducive to diamond dust formation where CALIPSO is likely misclassifying diamond dust as mineral dust and near the surface (< ∼ 2 km) where FLEXPART may be overpredicting local dust emissions. Comparisons to ground data suggest that MERRA-2 Arctic dust concentrations can be improved by the addition of local dust sources. All three products predicted that wintertime dust and combustion aerosols occur most frequently over the same Siberian regions where diamond dust is most common in the winter. This suggests that dust aerosol impacts on ice phase processes may be particularly high over Siberia, although further wintertime model validation with non-CALIPSO observations is needed. This assessment paves the way for applying the model-based aerosol simulations to a range of regional-scale Arctic aerosol–cloud interaction studies with greater confidence.

MERRA-2↗