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At least 1,279 records · Page 71

Climate Influences on Capacity Expansion Planning with Application to the Western U.S

Electric power system planners utilize a variety of planning tools to inform decisions concerning generation and transmission additions to the electric grid, the need for operational changes, and to evaluate potential stressors on the system. Numerous factors contribute to the planning process including projected fuel and technology costs, policy and load profiles. There is also a growing recognition of the interdependency of the electric grid with other natural and engineered systems. Here we explore how future climate change and hydropower operability might influence decisions related to electricity capacity expansion planning and operations. To do so we assemble a multi-model framework. Specifically, water resource modeling is used to simulate climate impacts on future water supply for thermoelectric and hydropower generation. Separately, temperature impacts on electricity load are evaluated. Together, these climate factors spatially constrain a capacity expansion model that projects generation and transmission additions to the grid. The projected new capacity-builds are then evaluated on their operations, reliability, and cost under average and extreme climate conditions using production cost modeling. This coupled framework is demonstrated on the electric grid in the Western U.S., supporting capacity expansion planning by WECC, the North American Electric Reliability Corporation (NERC) regional entity responsible for reliability assurance of the Western Interconnection. This region was selected in part because the West is unique in that it has high potential for renewable penetrations and is experiencing large retirements/displacements of baseload resources, primarily coal, leading to possible operational challenges in terms of changing resource mix and the need for resource flexibility. Toward this challenge, planning scenarios encompass a range of alternative energy, climate and drought futures. In this context we explore answers to two strategic questions: 1) How does changing climate influence electricity expansion planning (generation and transmission) and future operations, including type and capacity of new builds, system reliability, cost and environmental impacts? 2) How does the representation of hydropower in the modeling framework influence the evaluation of bulk power system operations? Results indicate that climate has a measurable influence on recommendations concerning the capacity, type and location of new generation and transmission additions, with up to 17 GW additional capacity needed by 2038 to meet peak loads (~6.6% increase over capacity-builds based on historical climate). The extent of additional infrastructure needs is strongly influenced by future water availability for hydropower and the potential deployment of demand response technologies. Systems designed for future climate conditions were found to maintain high system reliability under a range of electricity and water availability scenarios (including significant drought), with minimal system curtailments. Additional capacity needs due to higher load tend to increase cumulative 20-year investment and operating costs by $\$$5-$\$$17 billion and generation costs increase by 9 to 19%. Finally, changing the representation of hydropower flexibility has a relatively small influence on capacity expansion in the Western Interconnection through 2038, but hydropower flexibility impacts generation costs to a similar extent as climate.

13 HYDRO ENERGY↗

Real-Time Science Decisioning During High Tempo-High Intensity Mission Operations and the Role of Analogs

Introduction: NASA’s VIPER mission presents a unique operational paradigm within the history of robotic spaceflight. The proximity of the Moon to the Earth and the terrain elements (surface characteristics, light/shadow dynamics, communication links) of the lunar South Polar landing site create unprecedented operational conditions between these two planetary bodies. Apollo era lunar science and exploration included humans in situ to operate instruments and assimilate observational inputs in real-time. Previous lunar orbital missions have worked to operational timescales, e.g., decisional timelines and communication exchanges, that were weeks in length. Mars rover missions have worked to operational timescales, e.g., decisional timelines and communication exchanges between Mars and Earth, that were hours, days, and weeks in length. In the case of the VIPER mission, our operational decisioning for rover driving and instrument commanding will be compressed to minute-scale timeframes. These operational conditions directly impact the manner and speed with which the VIPER Science Team (VST) is required to synthesize and analyze data and produce timely science-driven decisions throughout surface mission operations. The VST shall provide mission enhancing scientific input to guide rover traverse planning and drill site confirmation and selection throughout surface operations. Further, the VST input will be of vital importance to the mission’s ability to maximize science return and to meet broader NASA objectives for future lunar in-situ resource utilization (ISRU)and exploration activities. The VST co-located in the Mission Science Center (MSC) will be responsive to the tactical operational cadence of the Mission Operations Center (MOC) and will provide further strategic and Long-Term Planning (LTP) guidance to the mission. The VIPER Science Operations & Integration(SO&I)team has developed an architecture that is focused on the infusion of science-decisioning into the operational framework and execution cadence of VIPER. NASA analog research has played a significant role in the construction of the VIPER science operations systems. As an example, the SO&I team has led analog missions that have focused on bringing together expertise in the sciences (natural, applied and social) and in operations in service of learning how to build and hold together interdisciplinary work environments and what tools are needed to support high tempo, high intensity integrated decisioning. These experiences have provided an essential foundation of knowledge to the VIPER team. Those analogs that specifically influenced the VIPER science operations construct were identified through a process of comparative analysis to prioritize those that offered relevance in whole or in part, and those that did not. The analog research output that provided extensibility to the VIPER science operations architecture included remote teams of humans and robots in cooperation (synchronous and asynchronous) with simulated earthbound systems, engineering and science teams, and the integrated assembly of tools that supported scientific analysis and data synthesis and provided infrastructure for the remote testing framework. Analogs which included real-time data monitoring, synthesis, visualization and access in a democratized and operationalized manner were of particular interest to the development of the VIPER MSC toolset both in terms of the technology and the processes used to develop the supporting infrastructure. We anticipate that each subsequent mission to the lunar south pole, whether with robots or humans, will be able to optimize science and exploration return by evolving strategies to infuse real-time collaborative science-decisioning. Furthermore, these efforts will result in a foundation for science operations development in support of human-robotic exploration of deep space and Mars. NASA analogs can continue to provide the opportunity to prepare, test and iterate on the operational concepts and tools that will support these ever-expanding space exploration efforts. Our presentation will include an overview of the VIPER Science Operations & Integration development process and specifics on what aspects of analog research have had a significant impact on our work systems.

D S S Lim↗

Insights into Designing an Efficient and Reliable Microwave-Assisted Methane Dehydroaromatization Process: Effect of Microwave Absorber on Catalyst Performance

Microwave-assisted methane dehydroaromatization has the potential to address challenges of traditional dehydroaromatization reactions. However, catalysts for microwave-enhanced reaction systems require effective coupling of fields with the catalyst to produce heat and reach reaction temperatures. Here, this work presents an in-depth understanding of the effect of the addition of silicon carbide as a microwave absorber on catalyst performance among other variables, the viability of the microwave reactor configuration, and insights into designing an effective and reliable microwave-based methane dehydroaromatization process. The effect of other parameters including temperature, weight hourly space velocity, role of microwave absorber, and methane concentration during microwave-assisted methane dehydroaromatization reaction are studied. Mo/ZSM-5 was found to suffer from low permittivity and nonuniform heating under microwave conditions. Mixing silicon carbide powder as a microwave absorber with the catalyst was found to provide more uniform heating. When assessing the catalytic performance of the mixture, it was found that higher methane partial pressures at 2000 cc/g cat .h and a temperature range of 500-600°C produced the highest amount of benzene. The formation of graphitic carbon on the spent catalyst increased with temperature, gas-solid contact period, and methane concentration, which resulted in higher methane conversion and benzene selectivity. The study indicates that under microwave heating the presence of localized carbon enhanced catalyst life by coupling with microwave energy, leading to localized heating, and improving benzene selectivity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genomes and metagenome assemblies

Iron is a micronutrient for nearly all life on Earth. It can be used as an electron donor and electron acceptor by iron-oxidizing and iron-reducing microorganisms and is used in a variety of biological processes, including photosynthesis and respiration. While it is the fourth most abundant metal in the Earth’s crust, iron is often limiting for growth in oxic environments because it is readily oxidized and precipitated. Much of our understanding of how microorganisms compete for and utilize iron is based on laboratory experiments. However, the advent of next-generation sequencing and surge in publicly available sequence data has made it possible to probe the structure and function of microbial communities in the environment. To bridge the gap between our understanding of iron acquisition, iron redox cycling, iron storage, and magnetosome formation in model microorganisms and the plethora of sequence data available from environmental studies, we have created a comprehensive database of hidden Markov models (HMMs) based on genes related to iron acquisition, storage, and reduction/oxidation in Bacteria and Archaea. Along with this database, we present FeGenie, a bioinformatics tool that accepts genome and metagenome assemblies as input and uses our comprehensive HMM database to annotate provided datasets with respect to iron-related genes and gene neighborhood. An important contribution of this tool is the efficient identification of genes involved in iron oxidation and dissimilatory iron reduction, which have been largely overlooked by standard annotation pipelines. We validated FeGenie against a selected set of 28 isolate genomes and showcase its utility in exploring iron genes present in 27 metagenomes, 4 isolate genomes from human oral biofilms, and 17 genomes from candidate organisms, including members of the candidate phyla radiation. We show that FeGenie accurately identifies iron genes in isolates. Furthermore, analysis of metagenomes using FeGenie demonstrates that the iron gene repertoire and abundance of each environment is correlated with iron richness. While this tool will not replace the reliability of culture-dependent analyses of microbial physiology, it provides reliable predictions derived from the most up-to-date genetic markers. FeGenie’s database will be maintained and continually updated as new genes are discovered.

59 BASIC BIOLOGICAL SCIENCES↗

Control, Fault Management, and Grid Support Functionality of an MV AC-DC Solid State Transformer based EV Extreme Fast Charging Station

Electric vehicles (EVs) have become increasingly popular in recent times while revolutionizing the consumer and commercial transportation market. The development of charging infrastructure has become one of the priorities for increasing the adoption of EVs. Extreme fast charging (XFC) technology can reduce the so-called ’range anxiety’ of consumers as they significantly reduce the charging time. With the advent of wide band-gap (WBG) power devices and improvement in power electronic converters, medium voltage (MV) solid state transformer (SST) based XFC system has the potential to replace the traditional XFC stations because of the lower footprint, ease of installation, enhanced control feature, and better system efficiency. The control system design is one of the critical aspects of the SST development process. Careful consideration and detailed analysis are required to find out suitable control method for the SST based on its topology among different centralized and decentralized control architectures. Also, the control parameters selection and potential improvement to the transient response of the controller ought to be investigated. Another major concern of the SST is different types of internal fault which reduces the overall reliability of the XFC system. As a result, designing a robust protection system is essential. Among different fault modes, open circuit switch faults have received significant attention as an active research area because of their likelihood and severe effects on converters. Therefore, the power stages used in the XFC system require functional and accurate open circuit switch fault management methods. An equally significant aspect of this SST based XFC is its compatibility in a microgrid where there is no synchronous generator present. When the grid is not available, the XFC SSTs can provide grid forming capability and continue supplying the critical loads in islanded mode. The transition between grid connected and islanded mode, especially the grid resynchronization process has to be carefully performed for the safety of the microgrid components. The challenges posed by the aforementioned issues have inspired the work done in this dissertation. Here, a 13.2 kV, 1 MVA, AC/DC SST for the XFC system is examined and a comparative analysis is conducted to select the control architecture based on feasibility of implementation and performance. A detailed control parameter design process is demonstrated considering the sensor dynamics and delay. The selected decentralized control method is augmented by introducing a novel sensor-less load current feedforward method to provide better voltage regulation at the DC bus during a change of load. Next, in the fault management section, a hierarchical failure mode effect analysis (FMEA) is proposed to enable a systematic design of the internal fault protection of the XFC SST as there are limited examples in the literature regarding the analysis of the safety and design of the protection of a power electronic converter system. Novel open circuit switch fault management methods for the converters in the system are presented. Finally, XFC SST based MV microgrid operations in grid connected mode and islanded mode are explored. A secondary control method for grid resynchronization is presented and a design process of control parameters is shown to ensure the stability of the secondary voltage and frequency regulation.

30 DIRECT ENERGY CONVERSION↗

Contaminant Migration Modeling to Support the In Situ Decommissioning of Hardened Nuclear Facilities - 20215

The decommissioning of hardened nuclear facilities provides a unique challenge in balancing current worker dose with exposure to future receptors and media. In situ decommissioning (ISD) is a cost-effective and safe option for the closure of such facilities but requires a detailed understanding of the threat that radioactive and hazardous constituents remaining in the facilities pose to groundwater and surrounding surface water. The Savannah River Site (SRS) extensively employs contaminant migration models within the decommissioning process to develop site-specific removal, grouting, and monitoring strategies in support of safe and effective final end states of nuclear facilities. This work discusses the use of contaminant migration modeling in the ISD process at SRS, including specific examples from the closure of P-Reactor and R-Reactor, Building 235-F, F-Canyon and F/H Laboratory Complex. Migration models developed during the closure of P-Reactor and R-Reactor were divided into four source areas: the reactor vessel, the process area, the disassembly basin, and the purification wing. Each source area was assigned a specific inventory and migration pathway and was then subject to varying hypothetical removal, capping, and grouting schemes. Modeling indicated that groundwater Maximum Concentration Limits (MCLs) might be exceeded if no action was taken for eleven and ten constituents of concern (COCs) at P-Reactor and R-Reactor, respectively. These exceedances could occur in as few as 200 to 500 years. Alternatively, the migration modeling demonstrated that the selected ISD actions reduced contaminant mobility which allowed for significant radioactive decay and resulted in fewer predicted exceedances of groundwater MCLs (five COCs for P-Reactor; eight COCs for R-Reactor). In response to the modeling results for P-Reactor and R-Reactor, effectiveness monitoring programs were developed to target contaminants, specific to each reactor, that may migrate to groundwater. Contaminant migration modeling also revealed that roof collapse was a large factor in the release of COCs to the environment, giving rise to roof improvements, and an inspection and vegetation control program to ensure roof stability over time. Contaminant migration modeling is also aiding in the closure planning for hardened facilities in F Area. Building 235-F housed the Actinide Billet Line, which produced Np-237 billets for irradiation in SRS reactors, and the Plutonium Fuel Form (PuFF) facility that produced Pu-238 heat sources for the space program. As a result of these missions, areas within Building 235-F contain considerable residual amounts of both Pu-238 and Np-237. Contaminant migration modeling of Building 235-F was originally performed in 2012 to identify the feasibility of ISD and the amount of radioactive material removal required to prevent the exceedance of groundwater MCLs. The original model indicated that a 60% reduction in the PuFF facility Pu-238 inventory could keep groundwater concentrations below standards, while Np-237 did not pose a threat to groundwater. However, updates to the model with an emphasis on source impact pathways revealed that, due to the orientation of the source areas relative to groundwater flow, no amount of reasonable removal of Pu-238 would keep groundwater concentrations below MCLs and that Np-237 could be a large contributor to localized MCL exceedances. With this insight, the refined 2019 model is being used to assist in the development of grouting plans specific to each facility source area, where bentonite may be utilized to slow the migration of Pu-238 and its daughter products from the PuFF facility and a reducing grout may decrease Np-237 transport by ensuring the nuclide remains in the less mobile +IV oxidation state. The beginning phases of contaminant migration modeling are underway for F-Canyon and associated facilities using lessons learned from the Reactors and Building 235-F. A contaminant migration pathway, similar to the pathway used for the reactor vessels, is being developed for the hot and warm canyons. The F-Canyon inventories are being spatially refined to identify specific and localized source zones, comparable to Building 235-F, that may impact groundwater. Contaminant migration modeling provides vital input within the ISD process, from facility investigation to post closure effectiveness monitoring, making it a valuable tool in the development of safe and effective end states for hardened nuclear facilities at SRS. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Demonstration of a Novel Technology to Manage Electricity Demand in Grid-Independent Military Microgrids

This research was conducted by the National Renewable Energy Laboratory (NREL) in collaboration with the S&C Electric Inc. through funding provided by the ESTCP. The project demonstrates use of cybersecure Automated Demand Response (ADR) technology to effectively manage microgrid loads during grid-independent, also known as "islanded," operation. When military microgrids become isolated from the main electrical grid, they are required to balance electricity supply and demand locally. Given that local generation may be constrained, the prevailing strategy involves shedding all but the most critical loads by tripping smart circuit breakers, which then necessitate manual resetting. This approach is generally implemented at the building level, which means that the buildings with mission-critical activities are exempt from load management and remain fully powered, whereas those deemed non-critical can experience a complete loss of service. In this research we developed a method that allows building automation systems to selectively control their assets in response to load shedding request from a microgrid controller, avoiding total loss of service in contrast to the conventional control approach. A commercial OpenADR client server by GridFabric is used for communication between the microgrid controller and the building management system (BMS). The microgrid controller monitors both generation capacity and various assets within the microgrid and issues a demand reduction request when necessary. This request is communicated to the OpenADR server via Modbus. Upon receiving the request, the OpenADR server forwards it to the BMS utilizing the OpenADR protocol. The BMS is pre-configured with various levels of load reduction strategies based on the controllable assets available, allowing for a nuanced approach to demand reduction. Both lab and field tests were performed that considered load shedding needed to achieve closed transition into island mode and to accommodate changing loads and power source availability while islanded. A commercial microgrid controller was used for these tests with normal programming within the expected constraints of the system capabilities. That is, the solution did not require any specialized modification to the code base of the controller. Given the latency of the round-trip communication path between the microgrid controller and the various devices involved with the load shed processes, there are certain scenarios for which the demonstrated solution are appropriate and some which are not. The methods described in this report can be used for load shedding/restoration during transitions between islanded and grid-tied modes of operation, as well as accommodating normal variations in load and the need to remove a power source from operation for maintenance. These methods should not be used for scenarios that require load shedding within a second or two such as sudden and unanticipated significant load increases or loss of power sources through equipment faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Thermochemical Properties of a Water-Soluble Zr(IV)-Flavonolate Complex for Fluoride Sensing

Detection of fluoride in water samples is critical for monitoring many chemical, environmental, and biological processes, however, these measurements often rely on costly instrumentation. Here, this situation has motivated the design of simple to use, fieldable fluoride sensors. Previously, a fluorometric sensor based on (EDTA)­Zr­(H 2 O) 2 (EDTA = ethylenediamine-N,N,N′,N′-tetraacetate) and 3-hydroxyflavone (FlvH) was reported for fluoride detection in ethanol-H 2 O mixtures. Herein, we report the synthesis and characterization of the previously proposed Zr­(IV)-flavonolate complex as the dimethylammonium salt, [(EDTA)­Zr­(Flv)]­[NMe 2 H 2 ] (Flv = 3-hydroxyflavonolate), and detail its utility for aqueous fluoride sensing. This species exhibits an intense blue fluorescence upon excitation with near-UV light (λ ex = 390 nm; λ em = 460 nm) that is quenched in the presence of NaF (100 mM acetate buffer, pH = 5) with good sensitivity (LOD = 20.9 nM; [F – ] from 10 –8 to 10 –4 M) under neat aqueous conditions. The equilibrium constant (K eq = 1.26 ± 0.00184 × 10 8 M –2 ) and free energy (Δ$G^°_{\textrm{rxn}}$ = –11.0 kcal mol –1 ) were determined under the conditions used for fluoride sensing, indicating a highly favorable reaction with F – in water. Finally, we developed paper-based sensing strips for qualitative fluoride sensing by immobilizing the sensor in a deposited gel enabling good selectivity and reduced interference due to slower ion diffusion.

aqueous chemistry↗

Computational Analysis of Different Sparging Systems and their Influence in the Fluid-Dynamic Behavior of Bubble Column Reactors

Bubble column bioreactors are being actively considered for gas fermentation applications, specifically for CO2 utilization, and sugars to fuels conversion. Their main advantages include good mass transfer without any moving parts and low-cost of operation and maintenance. However, the design and scale-up of such reactors is challenging specifically for carbon capture applications where a mixture of gases (e.g. CO2/CO/H2) with variable solubilities is used. The overall performance of scaled-up bioreactors (e.g., mass transfer rate) is largely affected by gas holdup, bubble size distribution (BSD), and multiphase hydrodynamics. We investigate the effect of gas sparger designs on the performance of these large-scale bioreactors using computational fluid dynamics simulations in this work, so as to improve CO2 conversion at scale. The gas distribution systems in bubble column reactors not only determines operational regime, but also affects the evolution of the BSD, which in turn influences interfacial mass transfer and ultimately the efficiency of the gas-liquid exchange process. In addition to the BSD, uniformity in gas sparging affects gas holdup and bubble residence time which constitute important metrics of performance in gas-liquid systems. In this work, we use computational models to simulate high fidelity representations of different sparger designs and their effect on the operation of a bubble column reactor. Four different types of spargers have been selected for the computational study (Fig. 1): ladder, multi-ring, single-ring and toroidal. Their effect on superficial velocity, gas holdup mixing efficiency, and BSD will be evaluated in this work. The model uses a multiphase Eulerian framework similar to [1] and include a composition of mixtures of H2/CO/CO2 gases, common in fermentation applications.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗

Statistical Considerations of Data Processing in Giovanni Online Tool

The GES DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni) is a web-based interface for the rapid visualization and analysis of gridded data from a number of remote sensing instruments. The GES DISC currently employs several Giovanni instances to analyze various products, such as Ocean-Giovanni for ocean products from SeaWiFS and MODIS-Aqua; TOMS & OM1 Giovanni for atmospheric chemical trace gases from TOMS and OMI, and MOVAS for aerosols from MODIS, etc. (http://giovanni.gsfc.nasa.gov) Foremost among the Giovanni statistical functions is data averaging. Two aspects of this function are addressed here. The first deals with the accuracy of averaging gridded mapped products vs. averaging from the ungridded Level 2 data. Some mapped products contain mean values only; others contain additional statistics, such as number of pixels (NP) for each grid, standard deviation, etc. Since NP varies spatially and temporally, averaging with or without weighting by NP will be different. In this paper, we address differences of various weighting algorithms for some datasets utilized in Giovanni. The second aspect is related to different averaging methods affecting data quality and interpretation for data with non-normal distribution. The present study demonstrates results of different spatial averaging methods using gridded SeaWiFS Level 3 mapped monthly chlorophyll a data. Spatial averages were calculated using three different methods: arithmetic mean (AVG), geometric mean (GEO), and maximum likelihood estimator (MLE). Biogeochemical data, such as chlorophyll a, are usually considered to have a log-normal distribution. The study determined that differences between methods tend to increase with increasing size of a selected coastal area, with no significant differences in most open oceans. The GEO method consistently produces values lower than AVG and MLE. The AVG method produces values larger than MLE in some cases, but smaller in other cases. Further studies indicated that significant differences between AVG and MLE methods occurred in coastal areas where data have large spatial variations and a log-bimodal distribution instead of log-normal distribution.

Suhung, Shen↗

Theoretical Insights into Reaction-Induced Transformation and Tuning of Catalytic Behavior in Heterogenous Catalysis

Reaction-induced transformations in heterogenous catalysis represent diverse phenomena that challenge traditional views of static catalyst surfaces. From surface adsorbate dynamics, atomic rearrangements, to composition and phase transitions, these processes reveal the profound differences between idealized model systems under ultrahigh vacuum and the complex, evolving interfaces that govern real catalytic behaviors under reaction conditions. Here, this perspective reviews recent theoretical efforts to provide atomic-level mechanistic insights into significant reaction-induced transformations and their impact on catalytic activity and selectivity. It underscores the need for an integrated framework that combines predictive simulations with operando characterization to uncover active sites and mechanisms under realistic operating conditions. Achieving this requires accelerating existing simulations to fully capture diverse reaction-induced surface dynamics, enabling scalable and accurate modeling of catalysts as condition-dependent, dynamically evolving systems. Such approaches are critical to bridge the gap between theory and practice, offering a pathway to more impactful and predictive catalyst design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Application of multi-criteria decision analysis techniques and decision support framework for informing select agent designation for agricultural animal pathogens

The United States Department of Agriculture (USDA), Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents and toxins (Select Agent List) that potentially threaten agricultural health and safety, the procedures governing the transfer of those agents, and training requirements for entities working with them. Every 2 years the USDA DASAT reviews the Select Agent List, using subject matter experts (SMEs) to perform an assessment and rank the agents. To assist the USDA DASAT biennial review process, we explored the applicability of multi-criteria decision analysis (MCDA) techniques and a Decision Support Framework (DSF) in a logic tree format to identify pathogens for consideration as select agents, applying the approach broadly to include non-select agents to evaluate its robustness and generality. We conducted a literature review of 41 pathogens against 21 criteria for assessing agricultural threat, economic impact, and bioterrorism risk and documented the findings to support this assessment. The most prominent data gaps were those for aerosol stability and animal infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. The MCDA analysis supported the intuitive sense that select agents should rank high on the relative risk scale when considering agricultural health consequences of a bioterrorism attack. However, comparing select agents with non-select agents indicated that there was not a clean break in scores to suggest thresholds for designating select agents, requiring subject matter expertise collectively to establish which analytical results were in good agreement to support the intended purpose in designating select agents. The DSF utilized a logic tree approach to identify pathogens that are of sufficiently low concern that they can be ruled out from consideration as a select agent. In contrast to the MCDA approach, the DSF rules out a pathogen if it fails to meet even one criteria threshold. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making.

60 APPLIED LIFE SCIENCES↗

eddy Users Manual

eddy is a collection of tools - nonlinear solvers, meshing, post-processing, visualization, optimization, etc. - for performing scale-resolving simulations of multi-physics applications. The framework is designed to enable advanced R&D on a variety of topics by leveraging a mature capability for scale resolving simulations, and simultaneously be an appropriate tool for application analysis and support. Currently, eddy is at a relatively low technical readiness level (TRL), and users and developers should maintain appropriate expectations. The technical details behind eddy are outlined in several publications which can be consulted for more information [1–10]. The solvers are built around an unstructured high-order capability, and heavily utilize the tensor product sum-factorization approach for efficiency. The unsteady formulation utilizes a fully implicit space-time approach with a matrix-free Newton- Krylov method. A primitive steady-state solver is available for testing purposes, but is not expected to converge for all but simple verification cases. The Navier-Stokes fluid solvers do not support either RANS or hybrid-RANS capability, only LES and wall-modeled LES approaches. All of the solvers within eddy support three modes of operation: a primal solve of the full nonlinear problem, and two linearization approaches of the primal solve - the ad joint and the tangent solution. Details on how to select and use these three modes are outlined in Sec. 3.

Murman, Scott M.↗

Minimizing Cr-Evaporation from Balance Of Plant Components By Utilizing Cost-Effective Alumina-Forming Austenitic Steels

A solid oxide fuel cell (SOFC) is a clean and efficient energy conversion device. The development of intermediate-temperature SOFCs has made it preferable to use metallic interconnects (MICs) to greatly reduce the cost and significantly increase the efficiency compared to ceramic interconnect materials. However, gaseous chromium species will evaporate from the chromium-containing layer formed on the surface of commonly used MICs and balance of plant (BoP) components. Volatile chromium species have been shown to form solid deposits which poison the cathodes of SOFCs, causing drastic cell performance degradation and thereby limiting commercialization. In order to alleviate the Cr poisoning and achieve long-term high performance of SOFC stacks, various Al 2 O 3 -forming austenitic (AFA) stainless steels applied at different temperatures are evaluated in this project. Based on our Phase I results (500 h operation), it is shown that on the AFAs, an alumina-based protective layer forms under high temperature that is invulnerable to water vapor effects and suppresses the diffusion of chromium and manganese which can prevent the generation of spinels on the alloy surface. Therefore, 310S, OC4 and OC5 at 800 °C and 625, OC11 and OC11LZ at 900 °C are selected to be tested in the Phase II long-term operation. From the results, we find that besides the lower Cr evaporation rates and better oxidation resistance of AFAs than benchmark alloys after short-term (500 h) operation, AFAs also possess the sturdy and compact alumina layer after a long-term operation (5000 h). A protective oxide layer is of great importance for the long-term high-temperature operation of structural materials. The high-temperature oxidation behavior of AFAs and commercial 310S and 625 alloys in Air + 10% H 2 O at 800 °C and 900 °C is systematically investigated. Severe breakaway oxidation and minor spallation are observed for the 310S and 625 after the long-term operation, while the AFAs show high oxidation resistance. It is found that the formation of a continuous alumina layer could greatly prevent the volatilization of chromium vapors. In addition, the corresponding evolving models are discussed. Chromium evaporation from BoP components in high-temperature environment could severely deteriorate the electrochemical performance of SOFC. Several methods were applied to evaluate the Cr evaporation rates of BoP after 500 h exposure at 800 °C to 900 °C in air with 10% H 2 O. An optimal method was designed to exclude the effect of silicon (Si) deposits from quartz tube and sodium (Na) deposits from the sodium carbonate on the oxidation process and the chemical interaction between Cr gaseous species and alumina tube which could provide further quantitative correlation of the evaporated Cr species quantities and degradation rates of SOFC. Based on the great performance of AFAs after long-term operation, AFAs are assembled with Anode-supported cells (ASC) to investigate the the Cr deposition of anode-supported cell under a constant current density of 0.5 A cm -2 at 800 °C with AFA alloys compared with commercial alloys. In addition, the anodic and cathodic processes are deconvoluted by distribution of relaxation times (DRT) method which are comprehensively discussed. It is found out that the voltage exhibited a slight decrease of 5.09 % and 1.54 % in the presence of OC11 and OC11LZA alloy, respectively. However, a considerable decrease of 22.14 % and 12.06 % was determined in the presence of 310S and 625 alloy, respectively. AFAs possessing the low-cost, low Cr evaporation rates and the high oxidation resistance will make it of great potential to replace the existing BoP components.

01 COAL, LIGNITE, AND PEAT↗

Surface Reorganization of Transition Metal Dichalcogenide Nanoflowers for Efficient Electrochemical Coenzyme Regeneration

In the past 20 years, enzymatic conversions have been intensely examined as a practical and environmentally friendly alternative to traditional organocatalytic conversions for chemicals and pharmaceutical intermediate production. Out of all commercial enzymes, more than one-fourth are oxidoreductases that operate in tandem with coenzymes, typically nicotinamide adenine dinucleotide (NADH) or nicotinamide adenine dinucleotide phosphate (NADPH). Enzymes utilize coenzymes as a source for electrons, protons, or holes. Unfortunately, coenzymes can be exorbitant; thus, recycling coenzymes is paramount to establishing a sustainable and affordable cell-free enzymatic catalyst system. Herein, cost-effective transition metal dichalcogenides (TMDCs), 2H-MoS 2 , 2H-WS 2 , and 2H-WSe 2 , were employed for the first time for direct electrochemical reduction of NAD + to the active form of the NADH (1,4-NADH). Of the three TMDCs, 2H-WSe 2 shows optimal activity, producing 1,4 NADH at a rate of 6.5 μmol cm –2 h –1 and a faradaic efficiency of 45% at -0.8 V vs Ag/AgCl. Interestingly, a self-induced surface reorganization process was identified, where the native surface oxide grown in the air was spontaneously removed in the electrochemical process, resulting in the activation of TMDCs.

36 MATERIALS SCIENCE↗

Thermochemical processes for CO 2 hydrogenation to fuels and chemicals: Challenges and opportunities

This manuscript discusses the potential use of CO 2 as a carbon and oxygen carrier to return it to the carbon life cycle in the form of fuels or chemicals via thermochemical catalytic pathways. Theoretically, CO 2 hydrogenation can form a variety of fuels and chemicals. Practically, however, the selectivity, conversion, operating range, and kinetic limitations and operational cost determine the end product. Because of their high value and versatility as a chemical or fuel, small olefins (i.e., C 2 H 4 ) and methanol are often considered as target species. Whether alcohol or olefin formation, CH 4 and CO are the nature’s primary choices of CO 2 conversion. They can be formed over a wide operating temperature, pressure, and CO 2 :H 2 ratios. They are often competitive carbon species in olefin or methanol formation steps. Although they are less valuable as end products, they can be used as intermediate species. Secondary processes of CO and CH 4 to form chemicals and fuels can increase the overall CO 2 hydrogenation yield. Independent of the choice of end product, CO 2 hydrogenation requires hydrogen. Pure hydrogen derived mostly from fossil fuels adds to the overall process cost and also increases the CO 2 emissions. Hydrogen produced from water electrolysis is a renewable green pathway but is limited by the process efficiency and cost. As an alternative to pure hydrogen, low-value, small chain paraffins are suggested as the hydrogen carriers. Carbon dioxide–assisted oxidative dehydrogenation of paraffins to olefins process is a direct pathway to olefin formation. The paper discusses these potential pathways for CO 2 utilization based on theoretical analysis and recent advances in academia and industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Schema Elements for Granta Annual Report: FY2024

Granta: Materials Intelligence (Granta: MI) is a commercial database software distributed by Ansys, Inc. that is utilized by the Nuclear Security Enterprise (NSE) to organize and store relevant materials data. Lack of standard and well-documented database schema is the primary obstacle to an NSE materials data management solution, so the objective of this project is to create and document such a schema. In FY21, an approach for designing, documenting, and managing a standard database schema was described based on the creation of schema elements (collections of attributes used to describe particular aspects of the data) to be used as building blocks for creating various database tables without duplication. In FY22, these methods were applied through a multi-site collaboration to create and document the schema elements necessary to build a thermogravimetric analysis (TGA) testing table. In FY23 the schema was expanded to include elements for a differential scanning calorimetry (DSC) table, along with schema for supporting metadata tables including Instruments, Projects, Documents, and Testing Series. In FY24 the following progress was made, again through multi-site collaboration: • The existing schema elements were modified to accommodate thermomechanical analysis (TMA) data, and a table, Test Data: TMA, was created for managing TMA data. • The elements necessary for the following additive manufacturing (AM) data tables (directed at data specific to selective laser sintering AM technology) were created: • AM Builds • AM Processes • AM Part Designs • Built AM Parts • AM Feedstock Materials • AM Feedstock Material Batches • The elements necessary for creating a Calibrated Material Models table were created, and the Calibrated Material Models table was created. In FY25 the existing schema will be deployed on the production enterprise Granta instance on the enterprise secure network. Schema elements will be appended, and new elements created as necessary, to allow the creation of tables specifically to support materials testing, AM process development, and design and analysis for modernization programs.

36 MATERIALS SCIENCE↗

The SGI/Cray T3E: Experiences and Insights

The NASA Goddard Space Flight Center is home to the fifth most powerful supercomputer in the world, a 1024 processor SGI/Cray T3E-600. The original 512 processor system was placed at Goddard in March, 1997 as part of a cooperative agreement between the High Performance Computing and Communications Program's Earth and Space Sciences Project (ESS) and SGI/Cray Research. The goal of this system is to facilitate achievement of the Project milestones of 10, 50 and 100 GFLOPS sustained performance on selected Earth and space science application codes. The additional 512 processors were purchased in March, 1998 by the NASA Earth Science Enterprise for the NASA Seasonal to Interannual Prediction Project (NSIPP). These two "halves" still operate as a single system, and must satisfy the unique requirements of both aforementioned groups, as well as guest researchers from the Earth, space, microgravity, manned space flight and aeronautics communities. Few large scalable parallel systems are configured for capability computing, so models are hard to find. This unique environment has created a challenging system administration task, and has yielded some insights into the supercomputing needs of the various NASA Enterprises, as well as insights into the strengths and weaknesses of the T3E architecture and software. The T3E is a distributed memory system in which the processing elements (PE's) are connected by a low latency, high bandwidth bidirectional 3-D torus. Due to the focus on high speed communication between PE's, the T3E requires PE's to be allocated contiguously per job. Further, jobs will only execute on the user specified number of PE's and PE timesharing is possible but impractical. With a highly varied job mix in both size and runtime of jobs, the resulting scenario is PE fragmentation and an inability to achieve near 100% utilization. SGI/Cray has provided several scheduling and configuration tools to minimize the impact of fragmentation. These tools include PScheD (the political scheduler), GRM (the global resource manager) and NQE (the Network Queuing Environment). Features and impact of these tools will be discussed, as will resulting performance and utilization data. As a distributed memory system, the T3E is designed to be programmed through explicit message passing. Consequently, certain assumptions related to code design are made by the operating system (UNICOS/mk) and its scheduling tools. With the exception of HPF, which does run on the T3E, however poorly, alternative programming styles have the potential to impact the T3E in unexpected and undesirable ways. Several examples will be presented (preceeded with the disclaimer, "Don't try this at home! Violators will be prosecuted!")

Bernard, Lisa Hamet↗