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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

FY24 Task 5: Leachate Disposition

Directly feeding sludge solids to the high-level waste (HLW) Waste Treatment Plant represents an alternative flowsheet seeking to initiate sludge processing as soon as possible. Key processing functions previously captured during baseline pretreatment operations include leaching and washing prior to solids concentration. These operations should be considered in the potential direct feed flowsheets to maximize waste feed loading, minimize HLW volume, and mitigate corrosion challenges associated with vitrification of high phosphate and fluoride concentrations. Additionally, single-shell tank (SST) retrievals and waste transfers to double-shell tanks (DSTs) in a direct feed flowsheet would likely also benefit from some level of leaching, washing, and solids concentration in order to reduce DST space and mission duration. These operations could occur in a new facility or potentially in available DSTs. If washing and leaching are utilized, an effective disposition pathway for the wash water and leachate solutions are needed. Three target species that benefit significantly from leaching and washing are phosphate, fluoride and aluminum. Phosphate (PO 4 3- ) and fluoride (F - ) can contribute substantially to the amount of carrier fluid needed for dissolution, and the resulting volume of liquid generated. Disposition of this retrieval solution should be evaluated in order to prevent crystallization of these anions throughout system processing. Since there is a high probability that any retrieval solutions will be at or near their PO 4 3- and F - solubility limits, evaporation or blending with a high Na supernate (>3.5 M) is not recommended for the wash water streams without a method to remove precipitants prior to solution disposal. Additionally, aluminum present in the southeast quadrant of the Hanford site represents roughly 60% of the waste solids in the initial processing tanks. These aluminum solids are in the form of gibbsite (Al(OH) 3 ) and can pose significant challenges for processing due to the fast-settling times and high solids loading associated with these materials. Easily remediated by caustic addition to the solids, these wash solutions could be processed through crystalline silicotitanate (CST) ion exchange columns to prepare the supernate solutions for disposition. The current target for feed conditions to the Low Activity Waste (LAW) melter are waste streams that contain nominally 5-6 M Na. Fractions within the tanks contain upwards of 0.2 M phosphate and fluoride in solution at 3.5 M Na. Concentrating these solutions above 5 M Na would result in an exceedance of the solubility limits, and potential for uncontrolled precipitation of the phosphate and fluoride crystal material. The resulting crystalline salt material is typically sodium fluoride phosphate, also referred to as natrophosphate (Na 7 FPO 4 ·19H 2 O). Salt phases are of importance in tank waste due to their chemical reactivity, which can result in precipitation, dissolution, or transformation, impacting any downstream processes (Bolling et al. 2020, Russell, Snow, and Peterson 2010). Salt generation and precipitation could pose challenges by causing system plugging and melter corrosion if left in the supernate stream, or limit sodium molarity of the supernate that would be accepted without incident in waste operations. To understand the impact of this salt generation, the crystallization of natrophosphate in multiple simulant feed matrices was studied to understand the implications of various tank waste supernate chemistries. Three matrices were examined: high PO 4 3- /low F - , low PO 4 3- /high F - , and an average matrix. Subsequent testing was performed with the average matrix with the inclusion of CsNO 3 , and a final run with the average matrix including CsNO 3 and a 137 Cs spike for tracer purposes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Project Final Report - Advanced Oxygen Separation from Air Using a Novel Mixed Matrix Membrane

This report describes a summary of the findings of the project. The technical work was divided into three activities: 1) technoeconomic analysis; 2) membrane component development (support layer, selective layer development, and gutter layer formulation); and 3) hollow fiber formation. The technoeconomic analysis includes operating, capital, and materials costs of an oxygen enrichment system with 1-3 stages. The analysis concluded that the desired gas quality (90-95% O2) cannot be reached with a single stage. The triple stage system yielded the best overall product quality at lower membrane performance levels but with the highest cost. For the membrane development activities, functionalized nanodiamonds have been shown to slightly improve membrane formation behaviors and gas permeability performance. For example, support layers based on polysulfone-nanodiamond composites have been formed that increase the material’s O2 permeability by over a factor of 150, however, at the cost of selectivity that suggests a change in transport mechanism. Furthermore, nanodiamonds have been found to improve membrane durability. Improvements in selective and gutter layers also have been accomplished. An additional accomplishment is the demonstration of phase inversion of polysulfone-nanodiamond composites that ensures that hollow fiber formation can be performed. Finally, the interfaces between support, gutter, and selective layers were briefly examined and the resulting membrane material consisting of all three layers gave good performance in an O2 separation from N2. The three-layer prototype membrane gave permeability of 29.2-32.2 Barrers, which equates to permeance of approximately 290-320 GPU, which is lower than the TEA informed goal of 500 GPU. O2/N2 selectivity ranged from 5.2-6.2, which is consistent with the less costly two-stage implementation of the technology. In summary, new materials have been developed for O2 concentration from air and are well-suited to a hollow fiber format.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Digital Analytics, Causal Knowledge Acquisition and Reasoning for Technical Language Processing

Complex engineering systems such as nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) data elements that contain information on the status of components, assets, and systems. Some of this information is textual in form and can be found in documents such as incident reports (IRs) and work orders (WOs). Analyses of textual data in current NPPs-using natural language processing (NLP) methods-have been expanded over the last decade, and it is only recently that the true potential of such analyses has emerged. So far, applications of NLP methods have mostly been limited to classification and prediction, the goal being to identify the nature of the textual element (e.g., safety or non-safety related). Here, we target a more complex problem: automatically extracting knowledge from a textual element in order to assist system engineers in conducting system health assessments. Knowledge extraction is a very broad concept, and its definition may vary depending on the application context. Our methods are a blend of both rule-based and machine learning (ML) algorithms. For our purposes, knowledge extraction means identifying the systems or assets mentioned in a given textual element, as well as the type of event described (e.g., component failure or maintenance activity). In addition, we want to capture details such as measured quantities and the temporal/cause-effect relations between events. In this tool, we also demonstrate how textual data elements are preprocessed in order to handle typos, acronyms, and abbreviations. One main feature of these methods is that they are not based solely on data, but are in fact model-based. In other words, they also rely on MBSE models that are designed to capture-from a functional point of view-the architecture of the systems/assets under consideration. The main purpose of such models is to digitally emulate system engineers' knowledge of system and asset architecture and to identify dependencies among systems, assets, and components. Provided these models, analyses of textual and numeric ER data can be performed by first identifying the OPM model elements to which the ER data elements are referring. The relationships between ER data elements are then identified by checking for any temporal or logical dependencies.

Mandelli, Diego [Idaho National Laboratory (INL), ↗
DOE OSTI2023

Sustainable and Green Production of Nanostructured Cellulose by a 2-Step Mechano-Enzymatic Process

Nanostructured cellulose (NC) represents an emerging sustainable biomaterial for diverse biotechnological applications; however, its production requires hazardous chemicals that render the process ecologically unfriendly. Using commercial plant-derived cellulose, an innovative strategy for NC production based on the combination of mechanical and enzymatic approaches was proposed as a sustainable alternative to conventional chemical procedures. After ball milling, the average length of the fibers was reduced by one order of magnitude (down to 10–20 μm) and the crystallinity index decreased from 0.54 to 0.07–0.18. Moreover, a 60 min ball milling pre-treatment followed by 3 h Cellic Ctec2 enzymatic hydrolysis led to NC production (15% yield). Analysis of the structural features of NC obtained by the mechano-enzymatic process revealed that the diameters of the obtained cellulose fibrils and particles were in the range of 200–500 nm and approximately 50 nm, respectively. Interestingly, the film-forming property on polyethylene (coating ≅ 2 μm thickness) was successfully demonstrated and a significant reduction (18%) of the oxygen transmission rate was obtained. Altogether, these findings demonstrated that nanostructured cellulose could be successfully produced using a novel, cheap, and rapid 2-step physico-enzymatic process that provides a potential green and sustainable route that could be exploitable in future biorefineries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

High-Efficiency Modular SiC-based Power-Converter for Flexible-CHP Systems with Stability-Enhanced Grid-Support Functions

This project seeks to develop a modular, scalable MV power converter featuring stability-enhanced grid-support functions for future grid-interface applications in flexible combined heat and power (F-CHP) cogeneration plants, being fully compliant with the IEEE Standard 1547, category B—for operation in local areas with high aggregated distributed energy resource (DER) penetration, and also with the IEEE standard for the specification of microgrid controllers, namely IEEE Std 2030.7, with the goal to enable F-CHP systems for both microgrid and standalone applications. Further, the proposed converter will use a modular circuit topology, the MMC, which is scalable both in voltage and current by interconnecting power-cell building blocks, thus flexibly suiting the needs of F-CHP systems in the 1–20 MWe range. Furthermore, the use of 10 kV SiC MOSFET devices will minimize the number of power-cells needed to operate in 2–13.8 kV MV distribution systems, but more importantly, they will render feasible a power conversion efficiency > 98 %, and a power density > 10 kW/l. This is highly relevant given that these are two key performance metrics that will further increase the value of F-CHP systems by shortening the time required to recover their investment costs.

14 SOLAR ENERGY↗
DOE OSTI2020

Damaged Fuel in the United States

Over the years of commercial nuclear power plant operations in the United States (U.S.), many fuel assemblies have lost the capability to perform all of their desired functions. These assemblies have lost the capability to be handled, stored, or transported to meet regulations resulting in them being classified as damaged fuel. The causes of these failed assemblies are diverse and plant-specific. The majority of these failed assemblies are contained in a damaged fuel can that will be used in conjunction with a storage and/or transportation system. The storage and transportation systems have a limit on how many slots can be filled with damaged fuel cans. A damaged fuel can is generally a stainless steel container that confines damaged SNF and is closed on its end by screened openings. These screened openings allow gaseous and liquid media to escape but minimize the dispersal of gross particulate material. Out of an abundance of caution a few reactors have loaded high burnup fuel into damaged fuel cans. Damaged fuel is not licensed for storage or transport in the U.S., because the regulations for storage and transport do not specify exactly how to classify damaged fuel. Instead the regulations license/certify packages that specify approved contents. Damaged fuel must be included in the approved contents to be a viable option. In many cases damaged SNF is encapsulated in a damaged fuel can to ensure it can confine gross fuel particles, debris, and or damaged assemblies to a known volume within a loaded cask. This damaged fuel can may then be utilized in the same way as an assembly in a storage and transportation design system. Some storage cask systems utilize top and bottom plugs to confine debris in damaged fuel. The most recent domestic documentation on damaged SNF was performed by the U.S. Energy Information Administration (EIA) and used data from U.S. reactors concluding in June 30th 2013 to produce Form GC-859, “Nuclear Fuel Data Survey”. Based on this form there were 136,821 boiling water reactor (BWR) spent nuclear fuel (SNF) assemblies and 104,647 pressurized water reactor (PWR) SNF assemblies for a total of 241,468 SNF assemblies in the U.S. Out of these 241,468 SNF assemblies, 4,521 assemblies were classified as failed. Some assemblies were also disassembled and the fuel rods or pieces of fuel rods were combined together to make a consolidated assembly. A consolidated assembly may include damaged fuel, or it could have been consolidated as part of a demonstration project. The GC-859 data includes 2,550 consolidated assemblies containing between 0 and 264 whole fuel rods. These consolidated assemblies could be placed in single assembly canisters and stored in the spent fuel pool. For dry storage and transportation, a single assembly canister is generally placed in a damaged fuel can. In addition to the consolidated assemblies, 2,391 uncanistered fuel rod pieces exist, which were removed from 494 assemblies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Development of Novel Materials for Direct Air Capture of CO 2 : MIL-101(Cr)-Amine Sorbents Evaluation Under Realistic Direct Air Capture Conditions (Final Report)

The overarching goal of this project is to evaluate the CO 2 adsorption properties of a small family of metal-organic framework (MOFs) materials functionalized with amines at sub-ambient conditions. Our goal is to develop capabilities to measure CO 2 adsorption at conditions more relevant to the weather of the planet. For this purpose, Georgia Tech is constructing a “sub-ambient adsorption facility” in partnership with ZCP Sorbent Development, LLC, aimed specifically at rapidly and deeply characterizing the performance of DAC candidate materials in this important operational range (adsorption at -20 to 20 °C and RH of 0-100%). Here, we use the sub-ambient lab instrumentation designed or adapted to study the behavior of the pristine metal organic framework (MOF) MIL-101(Cr) and the MOF in the presence of amines ranging from small molecules (e.g. TREN, tris(2-aminoethylamine)) to oligomers (e.g. PEI, poly(ethyleneimine)). Any DAC sorbent must be amenable to deployment in practical contactors for gas-solid contacting (traditional pellet-based fixed beds are impossible at scale). To this end, we developed and tested these DAC materials in the forms of composite polymer/MOF fibers and custom 3D-printed monolith structures containing MOF DAC sorbents. The proposed studies advance these materials from technology readiness level (TRL) 2 to TRL 3.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Evolution of micro-pores in Ni–Cr alloys via molten salt dealloying

Porous materials with high specific surface area, high porosity, and high electrical conductivity are promising materials for functional applications, including catalysis, sensing, and energy storage. Molten salt dealloying was recently demonstrated in microwires as an alternative method to fabricate porous structures. The method takes advantage of the selective dissolution process introduced by impurities often observed in molten salt corrosion. This work further investigates molten salt dealloying in bulk Ni–20Cr alloy in both KCl–MgCl 2 and KCl–NaCl salts at 700 °C, using scanning electron microscopy, energy dispersive spectroscopy, and X-ray diffraction (XRD), as well as synchrotron X-ray nano-tomography. Micro-sized pores with irregular shapes and sizes ranging from sub-micron to several microns and ligaments formed during the process, while the molten salt dealloying was found to progress several microns into the bulk materials within 1–16 h, a relatively short reaction time, enhancing the practicality of using the method for synthesis. The ligament size increased from ~ 0.7 μm to ~ 1.3 μm in KCl–MgCl 2 from 1 to 16 h due to coarsening, while remaining ~ 0.4 μm in KCl–NaCl during 16 h of exposure. The XRD analysis shows that the corrosion occurred primarily near the surface of the bulk sample, and Cr 2 O 3 was identified as a corrosion product when the reaction was conducted in an air environment (controlled amount sealed in capillaries); thus surface oxides are likely to slow the morphological coarsening rate by hindering the surface diffusion in the dealloyed structure. 3D-connected pores and grain boundary corrosion were visualized by synchrotron X-ray nano-tomography. This study provides insights into the morphological and chemical evolution of molten salt dealloying in bulk materials, with a connection to molten salt corrosion concerns in the design of next-generation nuclear and solar energy power plants.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.

Preconditioner, Nonlinear, Porous media, Multiphas↗
DOE OSTI2024

Transportation and Systems Analysis Collaborations in Support of a Federal Consolidated Interim Storage Facility

The U.S. Department of Energy’s Integrated Waste Management (IWM) program under the Office of Nuclear Energy is planning for the future transportation, storage, and eventual disposal of spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from nuclear power plant sites across the United States. To better enable informed decision-making regarding the back end of the nuclear fuel cycle, the IWM program has been sponsoring the development and application of system analysis tools capable of analyzing various options for managing SNF and HLW. With these tools, integrated waste management system (IWMS) architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analyses and assessments typically use these modeling and simulation tools to investigate implications of changes in various assumptions and parameters such as acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, start and stop dates of facilities, etc. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation toolkit that is used for a system-level simulation and analysis focused on SNF management in the United States. An analyst using NGSAM has the ability to define several factors like the number of storage facilities, capacity at each facility, transportation schedules, shipment rates, and other conditions. NGSAM’s primary purpose is to provide a system analyst with capabilities to model the IWMS and gain insights into SNF and HLW management alternatives including the impact of system choices, associated cost estimates, and development of integrated yet flexible approaches. IWM is also developing the Stakeholder Tool for Assessing Radioactive Transportation (START). START is a web-based geospatial tool developed to provide visualization and initial evaluation of transportation options associated with future SNF and HLW shipment planning and operations. This includes characterizing safety, economic, and environmental conditions on and in proximity to shipment origins as well as along prospective transportation routes. Information from the START tool can be presented/shared as maps, graphics, geospatial files, and tabular form to enable easy data representation and export functionality. The system analysis, NGSAM, and START teams had been working closely for several years before formalizing this collaboration. START provides the SNF routing information for use in NGSAM. System analysts use the NGSAM tool to generate results (schedule, costs, infrastructure acquisitions, shipment rates, etc.). Subject-matter experts and system analysts work together to inform how NGSAM should model the waste management system. Specifically, this paper discusses the collaborations between the system analysis, NGSAM, and START teams and their accomplishments over the past year. Some examples of these efforts include calibrating and adding data to the START output files to meet NGSAM needs, gaining a better understanding of START data used in NGSAM, as well as how updates in START data could result in an improved NGSAM analysis. Detailed examples of various tasks that have been performed by the team will be discussed in the full paper. Continued efforts in this direction are expected in the coming years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Transportation and System Analysis Collaborations in Support of a Federal Consolidated Interim Storage Facility

The U.S. Department of Energy’s Integrated Waste Management (IWM) program under the Office of Nuclear Energy is planning for the future transportation, storage, and eventual disposal of spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from nuclear power plant and waste custodian sites across the United States. To better enable informed decision-making regarding the back end of the nuclear fuel cycle, the IWM program has been sponsoring the development and application of system analysis tools capable of analyzing various options for managing SNF and HLW. With these tools, integrated waste management system (IWMS) architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analyses and assessments typically use these modeling and simulation tools to investigate implications of changes in various assumptions and parameters such as acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, start and stop dates of facilities, etc. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation toolkit that is used for a system-level simulation and analysis focused on SNF management in the United States. NGSAM’s primary purpose is to provide a system analyst with capabilities to model the IWMS and gain insights into SNF and HLW management alternatives including the impact of system choices, associated cost estimates, and development of integrated yet flexible approaches. An analyst using NGSAM can define several factors like the number of storage facilities, capacity at each facility, transportation schedules, shipment rates, and other conditions. IWM is also developing the Stakeholder Tool for Assessing Radioactive Transportation (START). START is a web-based geospatial tool developed to provide the visualization and initial evaluation of transportation options associated with future SNF and HLW shipment planning and operations. This includes characterizing safety, economic, and environmental conditions at and in proximity to shipment origins as well as along prospective transportation routes. Information from the START tool can be presented/shared as maps, graphics, geospatial files, and tabular form to enable easy data representation and export functionality. The system analysis, NGSAM, and START teams have been working closely for several years before formalizing this collaboration. START provides the SNF transportation routing information for use in NGSAM. System analysts use the NGSAM tool to generate results (schedule, costs, infrastructure acquisitions, shipment rates, etc.). Subject-matter experts and system analysts work together to inform how NGSAM should model the waste management system. Specifically, this paper discusses the collaborations between the system analysis, NGSAM, and START teams and their accomplishments over the past year. Some examples of these efforts include calibrating and adding data to the START output files to meet NGSAM needs, gaining a better understanding of START data used in NGSAM as well as how updates in START data could result in an improved NGSAM analysis. Detailed examples of various tasks that have been performed by the team will be discussed in the full paper. Continued efforts in this direction are expected in the coming years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A Cybersecurity Threat Profile for a Connected Lighting System

In anticipation of improved energy performance and cost savings, cities and building owners are increasingly considering “smart lighting initiatives” that aim to convert their collection of simple luminaires (i.e., lighting fixtures) into an intelligent connected lighting system (CLS) capable of remotely monitoring energy consumption and fault conditions, and possibly implementing adaptive lighting schemes. The U.S. Department of Energy (DOE) has set an national goal of tripling the energy efficiency and demand flexibility of the buildings sector by 2030, relative to 2020 levels 1. It is forecast that connected lighting systems can contribute to that goal by delivering 125 TWh of annual energy savings by 2035 2, equivalent to the annual output of 50 typical (500 MW) power plants. However, these energy savings and the DOE goal are put at significant risk if connected technologies are not adopted due to real or perceived cybersecurity concerns. Connected IoT devices such as these have historically been rife with vulnerabilities which sometimes put security considerations secondary to functionality and operability. What are the cybersecurity threats that will impact these systems, as formerly banal luminaires transition into intelligent connected devices that collect information about themselves, their surrounding environment, and possibly us? In this paper we analyze a threat profile performed on a fault-detection use case for streetlights. A threat profile establishes security requirements, justifies security measures, yields actionable controls, and effectively communicates risk to stakeholders. This effort provides critical information for making threat-based decisions to increase security at a reasonable cost, and can effectively be used by development teams, software architects, and managers to make cybersecurity a part of their ongoing culture of awareness, training, and prevention. This leads to more secure systems and better-understood security. On-premise, cloud, and hybrid architectures with different authentication mechanisms were modeled and later categorized using the Microsoft STRIDE framework. An analysis of the recommended controls for each threat was performed to determine which controls could and should be put in place by manufacturers or third-party suppliers, and which controls need to be left up the end-user to implement. Fifty-seven threats were identified. Among our key findings: (1) 65% (37/57) of the threats did not involve the luminaires, but rather the other components needed to communicate with and manage them; (2) 63% (36/57) of the threats could have been mitigated through manufacturer-implemented defensive techniques or “controls”; and (3) 23% (13/57) of the threats were dependent on the network configuration. Recommendations based on the results of this work are made to key stakeholder groups. Notably, lighting technology developers are advised to address all threats that can be reasonably controlled with baked-in technology solutions (e.g., encryption or authentication controls), and employ some form of secure supply chain management and tracking where other parts (e.g., sensors, microprocessors) of a luminaire must also be built and manufactured with the proper security controls in place. Developers should also review threats involving assets not developed in-house to understand how connectivity with other devices will affect their product during system operation and determine if a compensating control for a defense-in-depth strategy will be needed. Finally, those interested in deploying CLS should compare the differences between cloud and on-premise models to determine which is more suitable for their needs and the abilities of their security team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Determination of Location-Specific Solidification Cracking Susceptibility for a Mixed Dissimilar Alloy Processed by Wire-Arc Additive Manufacturing

Solidification cracking is a major obstacle when joining dissimilar alloys using additive manufacturing. In this work, location-specific solidification cracking susceptibility has been investigated using an integrated computational materials engineering (ICME) approach for a graded alloy formed by mixing P91 steel and Inconel 740H superalloy. An alloy mixture of 26 wt.% P91 and 74 wt.% Inconel 740H, with high configurational and total entropy, was fabricated using wire arc additive manufacturing. Microstructure characterization revealed intergranular solidification cracks in the FCC matrix, which increased in length along with the enrichment of Nb (~27 to 56 wt.%) and Cu (~87 wt.%) in the middle and top regions. DICTRA simulations to model location-specific solidification cracking susceptibility showed that the top region with the highest cooling rate (270 K/s) has the highest solidification cracking susceptibility in comparison with the middle and bottom regions. This is in good agreement with the experimentally observed varying crack length. From Scheil simulations, it was deduced that enrichment of Nb and Cu affected the solidification range as high as ~77%, in comparison with the matrix composition. The overall solidification cracking susceptibility and freezing range was highest for the 26 wt.% P91 alloy amongst the mixed compositions between P91 steel and 740H superalloy, proving that solidification characteristics play a major role in alloy design for additive manufacturing.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1999

Analysis of peg formation in cucumber seedlings grown on clinostats and in a microgravity (space) environment

In young cucumber seedlings, the peg is a polar out-growth of tissue that functions by snagging the seed coat, thereby freeing the cotyledons. Previous studies have indicated that peg formation is gravity dependent. In this study we analyzed peg formation in cucumber seedlings (Cucumis sativus L. cv Burpee Hybrid II) grown under conditions of normal gravity, microgravity, and simulated microgravity (clinostat rotation). Seeds were germinated on the ground, in clinostats and on board the space shuttle (STS 95) for 1-2 days, frozen and subsequently examined for their stage of development, degree of hook formation, number of pegs formed, and peg morphology. The frequency of peg formation in space grown seedlings was found to be nearly identical to that of clinostat grown seedlings and to differ from that of seedlings germinated under normal gravity only in a minority of cases; approximately 6% of the seedlings formed two pegs and nearly 2% of the seedlings lacked pegs, whereas such abnormalities did not occur in ground controls. The degree of hook formation was found to be less pronounced for space grown seedlings, compared to clinostat grown seedlings, indicating a greater degree of decoupling between peg formation and hook formation in space. Nonetheless, in all seedlings having single pegs and a hook, the peg was found to be positioned correctly on the inside of the hook, showing that there is coordinate development even in microgravity environments. Peg morphologies were altered in space grown samples, with the pegs having a blunt appearance and many pegs showing alterations in expansion, with the peg extending out over the edges of the seed coat and downwards. These phenotypes were not observed in clinostat or ground grown seedlings.

STS-95 Shuttle Project↗
DOE OSTI2022

Determining the bubble nucleation efficiency of low-energy nuclear recoils in superheated C 3 F 8 dark matter detectors

The bubble nucleation efficiency of low-energy nuclear recoils in superheated liquids plays a crucial role in interpreting results from direct searches for weakly interacting massive particle (WIMP) dark matter. Here, the PICO collaboration presents the results of the efficiencies for bubble nucleation from carbon and fluorine recoils in superheated C 3 F 8 from calibration data taken with five distinct neutron spectra at various thermodynamic thresholds ranging from 2.1 to 3.9 keV. Instead of assuming any particular functional forms for the nuclear recoil efficiency, a generalized piecewise linear model is proposed with systematic errors included as nuisance parameters to minimize model-introduced uncertainties. A Markov chain Monte Carlo routine is applied to sample the nuclear recoil efficiency for fluorine and carbon at 2.45 and 3.29 keV thermodynamic thresholds simultaneously. The nucleation efficiency for fluorine was found to be ≥ 50% for nuclear recoils of 3.3 keV (3.7 keV) at a thermodynamic Seitz threshold of 2.45 keV (3.29 keV), and for carbon the efficiency was found to be ≥ 50% for recoils of 10.6 keV (11.1 keV) at a threshold of 2.45 keV (3.29 keV). Simulated datasets are used to calculate a p value for the fit, confirming that the model used is compatible with the data. The fit paradigm is also assessed for potential systematic biases, which although small, are corrected for. Additional steps are performed to calculate the expected interaction rates of WIMPs in the PICO-60 detector, a requirement for calculating WIMP exclusion limits.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Need for advanced research reactors for the next-generation reactor physics, analysis tools, and technology

Full text of publication follows. There is an urgent need for design and deployment of advanced research and test reactors in support of design, licensing and operation of advanced power reactors and education of next generation nuclear workforce. Existing research reactors mostly were designed and constructed decades ago with the main objectives of training operators, performing reactor physics experiments, and educating nuclear engineers and scientists. There are already gaps and significant concern about future capabilities for the existing research reactor facilities to address modern instrumentation and/or flexible environments for: performing reactor physics studies for advanced designs which have significantly different core materials forms and compositions, reactor shapes and size; validation of advanced high-fidelity software; development of machine learning algorithms for enhancement of human-machine collaboration in support of reactor monitoring, operation and safeguards; and, effective education of the next-generation workforce. The authors will focus on the need for advanced research reactors to improve and validate fast and accurate simulation tools for high-fidelity modeling and analysis of nuclear reactors in support of their design, optimization, licensing, operation, and monitoring. In the past, simulation tools were limited to relatively coarse models using approximate methodologies that benefited from two main factors: i) allowance for large margins and tolerances; ii) ability to construct prototype (e.g., zero power) reactors for adjustment of approximate methodologies. The next generation reactors have to be designed mainly by using novel high-fidelity computational tools that are accurate and fast, and therefore can be used for parametric studies and uncertainty quantification. To sufficiently demonstrate the accuracy of these tools, advanced research reactors are needed. The authors argue the need for new computational paradigms such as the MRT (Multistage, Response- function Transport) methodology which has resulted in the development of the novel high-fidelity RAPID (Real-time Analysis for Particle-transport and In-situ Detection) code system. Such code systems have to be robust in modeling any complex system, and should be fast and accurate, henceforth their uncertainties can be quantified at reasonable costs. Again, advanced research reactors are needed for the validation of the fidelity and accuracy of new computational tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRSDate not supplied

Spaceflight Autonomous Multigenerational Microbial Sequencer in Support of Plant-Growth Systems

The CubeSat platform has proven successful in obtaining meaningful life science information when biological payloads are incorporated. Examples include: 1) the first-ever CubeSat with a biological payload, GeneSat-1, which demonstrated decreased growth rates for flight samples of Escherichia coli in low Earth orbit (Parra et al. 2008); 2) PharmaSat, demonstrated that Saccharomyces cerevisiae in the microgravity environment exhibits a significant level of metabolic activity even at high doses of applied antifungal (Ricco et al. 2011); 3) O/OREOS, which used Bacillus subtilis(bacteria) to demonstrate for the first time that microorganisms can be loaded in a dried, dormant form and then rehydrated and grown in orbit months after launch (Nicholson et al. 2011; Ehrenfreund et al. 2014; 4) the SporeSat payload, which investigated Ceratopteris richardii(fern spores) using lab-on-a-chip devices (BioCDs) and minicentrifuges to produce artificial gravitational forces in ground studies (Park et al. 2017), with demonstration of the BioCD and minicentrifuge in space; 5) EcAMSat, the first CubeSat to be directly deployed from the ISS for an experiment assessing antibiotic resistance of E. coli in the microgravity environment (Padgen et al. 2020); 6) BioSentinel, exposed a culture of yeast to galactic cosmic radiation (GCR) and solar particle events while in heliocentric orbit to measure the rate of double-strand-break repair using DNA-repair-deficient mutants. This effort measures the metabolic parameters of yeast in a deep-space environment compared to Earth ambient conditions using a 3-color LED detection system (Ricco et al. 2020; Padgen et al. 2021). We aim to expand this list to include a Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS). SAMMS will allow for the genome level understanding of changes in growth and metabolic activity for any organism. While microbes are suitable for early studies in our proposed platform because of their small size, small and relatively less-complicated genomes, fast generation times, and relevance to life support systems; multicellular organisms can similarly be evaluated for their genetic response to the spaceflight environment. The Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) will enable autonomous sequencing of biological samples in plant production units, cislunar orbit and on the lunar surface to examine spaceflight effects (ie. radiation, altered gravity, reduced pressures) on plant and microbial genomes.On this team a Kennedy Space Center (KSC) space crop production and water systems microbiologist/molecular biologist works with a Johnson Space Center (JSC) International Space Station (ISS) microbial sequencing expert and an Ames Research Center (ARC) CubeSat Engineering team to convert an automated Oxford Nanopore librarypreparation and sequencing method to a fluidic CubeSat payload system. The Oxford Nanopore MinION sequencing platform has proven successful in the spaceflight environment onboard the ISS (Stahl-Rommel et al. 2021). Further long-duration spaceflight and exposure to high levels of radiation will cause genotypic effects in biological organisms that may affect their function. Monitoring the adaption of a population to the spaceflight environment and any subsequent beneficial mutations will allow for the harnessing of organisms best suited for use in life support systems. This will ensure that the selected life support-essential microorganisms maintain their intended specified function over generations of culturing in the relevant spaceflight environment without becoming hazardous to crew or spacecraft systems.

Aubrie E Orourke↗