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At least 271 records · Page 15

Micromobility Integrated Transit and Infrastructure for Efficiency (MITIE)

Nearly omnipresent in many cities of all sizes across the United States, micromobility vehicles-e-scooters, manual bicycles, e-bicycles, and larger seated electric scooters-are notably missing from SMART Mobility research. This project aims to expand the spectrum of modes currently being researched within SMART Mobility by exploring micromobility as an important tool toward meeting energy-efficient mobility goals. It expands on findings from SMART Mobility 1.0 that revealed preferences to reduce transportation-related expenses through use of a network of mobility-as-a-service (MaaS) and other shared mobility options, and builds on findings from a 2019 Vehicle Technology Analysis Program (VTAP) funded micromobility project conducted by our team. We will explore multiple facets of micromobility, including behavior and decision-making, the integration of micromobility within transportation infrastructure, energy estimates, and operations. Guiding research questions include: 1) what are the potential energy savings from low, medium, and high market penetration of micromobility (in passenger, multimodal, and freight domains)? 2) which scenarios for micromobility use and related enablement of increased public transit use should be modeled/considered in the SMART 2.0 Workflow? 3) to what degree can micromobility supplement/complement transit system operations? 4) what are people's preferences towards micromobility? How do preferences vary across various sociodemographic segments? How can this knowledge inform operations? 5) what are optimal strategies to attain high user adoption and shift users toward more energy-efficient mode choices in terms of micromobility operation? How do these strategies affect energy savings, person-miles traveled, lifecycle energy use, and adoption rates? These questions will be addressed through applied research in five project emphasis areas: 1) energy estimates of micromobility for Workflow scenarios: Expand and refine previous micromobility work to augment the Workflow approaches to modeling urban travel; 2) multimodal connection with transit: Utilizing Mobility-Energy Productivity (MEP) tools to evaluate multimodal travel patterns enabled by micromobility, including assessing how to reduce barriers of inequity of access to mobility options and destinations; 3) mode choice, induced demand, and infrastructure: Understanding the mode shift induced through micromobility to inform energy impact analysis; 4) energy optimization of micromobility operations: Identification of micromobility operations parameters and development of operations scenarios to better understand present-day micromobility operations for integration into the Workflow, in partnership with BEAM and POLARIS modeling teams; 5) micro-freight: Characterize the current state of micro-freight activities, including energy effects and geospatial analyses, to inform Workflow.

ADVANCED PROPULSION SYSTEMS↗

Thermo-economic analysis of a solid oxide fuel cell-gas turbine hybrid with commercial off-the-shelf gas turbine

The thermodynamic and economic performance of a natural gas-fueled solid oxide fuel cell (SOFC)-gas turbine (GT) hybrid system with a commercial off-the-shelf GT is investigated. Until today, commercial GTs are primarily engineered for the direct use of energy dense fuels, such as natural gas, and the integration of commercial GTs into a SOFC-GT hybrid remains challenging. In this work technically feasible and economically viable GT operating modes are identified to gauge the technology’s competitiveness on the free market. Steady state, full load operating conditions were established for various GT operating modes: I) constant spool speed operation, II) variable spool speed operation and III) partially closed compressor inlet guide vanes. For each GT operating mode, the performance was investigated over a range of SOFC fuel utilization factors, while considering physical constraints inside the SOFC, such as local temperature gradients in flow direction as well as overall cell temperature differences. The results of the thermodynamic evaluation served as inputs for the economic analysis of the SOFC-GT hybrid power plant. The results show that the integration of an off-the-shelf GT not only results in a significant derating of the GT, but also substantially impacts the SOFC operation, the main power producer in this SOFC-GT hybrid. To maximize the SOFC power output it is desirable operate the GT in a region of high air mass flow rates and low pressure ratios, which increases the number of stacks that can be accommodated and reduces the SOFC cooling requirement. The lowest costs of electricity are obtained at constant spool speed operation, while the highest efficiencies are reached at variable spool speed operation. Critical for the integration of off-the-shelf GTs, which historically have been designed for natural gas, is the surge margin. The largest surge margins are obtained by closing the compressor inlet guide vanes. Furthermore, higher SOFC fuel utilization factors are shown to increase the surge margin as the turbine firing temperature is decreased.

25 ENERGY STORAGE↗

Tritium generation, release, and retention from in-core fluoride salt irradiations

Further understanding of tritium transport mechanisms in the combined molten fluoride salt and graphite environment is necessary for the design and licensing of a Fluoride-Salt-Cooled High-Temperature Reactor (FHR). The three in-core fluoride salt irradiations completed at the Massachusetts Institute of Technology Reactor (MITR) are a useful parallel for studying transport phenomena expected in a FHR environment. During the irradiations, evolution of tritium from the flibe salt was monitored and compared to the calculated total generation rate. A difference of 22 ± 10% between the integrated calculated tritium generation rate and the total release was measured for the third MITR irradiation (FS-3). The fraction of tritium which was not released from the salt could be explained by tritium retention in graphite. Additionally, for post irradiation examination, a thermal desorption furnace was used to heat nuclear graphite samples in order to release and measure retained tritium. The desorption analysis in this work utilized seven subsections of graphite from the second salt irradiation (FS-2); three from a disc of IG-110U and four from ARB matrix graphite. Observed desorption versus temperature as well as total tritium content in the samples after irradiation indicate that the graphites were not volumetrically saturated with tritium, but rather tritium retention was likely limited to the near-surface region. Measurements of the samples resulted in 2.90 ± 0.29 μCi/mm 2 of tritium retained by IG-110U and 1.83 ± 0.31 μCi/mm 2 for ARB during the 300 h FS-2 in-core irradiation. Based on the desorption measurements, the estimated total tritium retention in graphite from the FS-2 samples is consistent with the tritium release measurements from the FS-3 experiment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network

Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.

09 BIOMASS FUELS↗

High Efficiency OLED Light Engine

LED Specialists has accomplished the program objective in designing a high efficiency OLED light engine combining high-performance OLED panels in the 5W-8W range. We achieved our goal by using an Active-Clamp Flyback circuit topology using state-of-the-art electronics. Evaluation testing of our second-generation prototype PC board has demonstrated an efficiency rating of 93% and dimming capability between 100% and 5% of OLED brightness. A reliability analysis of the design shows it to have a predicted Mean Time Between Failures (MTBF) of approximately 1,000,000 hours.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Cross-Code Verification of Neutronics Analysis Tools at INL Applied for 238 Pu Production in the Advanced Test Reactor

Here, analyses are completed for experiments prior to experiment irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). Various codes are used to qualify all experiments planned for insertion in the reactor, thereby ensuring that all safety and programmatic requirements are satisfied preirradiation. Among the common experiment analysis tools at INL are MCNP5 coupled to ORIGEN2 (MOPY) and MC21. MOPY uses MCNP5 for transport calculations along with calculations for fluxes and select reaction rates, and then ORIGEN2 handles the step-by-step and postirradiation depletion. MC21 handles all in-reactor transport and step-by-step, during-irradiation, depletion calculations, and then ORIGEN (SCALE 6.2.3) is used for decay and dose calculations postirradiation. The MOPY results, along with those obtained via two variations of the MC21 model, were compared in terms of 238 Pu production in the ATR’s H10 position. For the MOPY model, the MC21 model utilizing the HELIOS-based fission product (FP) library, and the MC21 model utilizing the expanded 1300 FP library, the during-cycle irradiation in-core heating results were sufficiently equivalent; however, the MOPY model and the MC21 model with the HELIOS library showed some differences relating to the respective FP libraries. Ultimately, the MC21 model with a 1300 FP library produced the most consistent results throughout the cycle, whereas the MC21 model that utilized the (smaller) HELIOS library was able to handle during-irradiation analysis but lacked certain short-lived FPs that significantly contributed to the total decay heat at shutdown. MOPY, on the other hand, was found to overpredict fission gas production, as a result of limitations in the ORIGEN2 code.

ATR↗

PERSIANN Dynamic Infrared–Rain Rate Model (PDIR) for High-Resolution, Real-Time Satellite Precipitation Estimation

Precipitation measurements with high spatiotemporal resolution are a vital input for hydrometeorological and water resources studies; decision-making in disaster management; and weather, climate, and hydrological forecasting. Moreover, real-time precipitation estimation with high precision is pivotal for the monitoring and managing of catastrophic hydroclimate disasters such as flash floods, which frequently transpire after extreme rainfall. While algorithms that exclusively use satellite infrared data as input are attractive owing to their rich spatiotemporal resolution and near-instantaneous availability, their sole reliance on cloud-top brightness temperature (T b ) readings causes underestimates in wet regions and overestimates in dry regions—this is especially evident over the western contiguous United States (CONUS). We introduce an algorithm, the Precipitation Estimations from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain rate model (PDIR), which utilizes climatological data to construct a dynamic (i.e., laterally shifting) T b –rain rate relationship that has several notable advantages over other quantitative precipitation-estimation algorithms and noteworthy skill over the western CONUS. Validation of PDIR over the western CONUS shows a promising degree of skill, notably at the annual scale, where it performs well in comparison to other satellite-based products. Analysis of two extreme landfalling atmospheric rivers show that solely IR-based PDIR performs reasonably well compared to other IR- and PMW-based satellite rainfall products, marking its potential to be effective in real-time monitoring of extreme storms. This research suggests that IR-based algorithms that contain the spatiotemporal richness and near-instantaneous availability needed for rapid natural hazards response may soon contain the skill needed for hydrologic and water resource applications.

54 ENVIRONMENTAL SCIENCES↗

Interregional Electricity Transmission in the United States: Realized Savings and Opportunities for Increased Value, 2014 to 2023

Interregional electricity trade in the United States reduces total energy costs, but falls short of maximizing the economic potential of existing transmission infrastructure. This analysis of thirty-two U.S. electricity system interfaces crossing grid or market seams finds an average achieved cost savings of at least $1,226 million per year. This positive impact is offset by an average annual cost of uneconomic interchange of $551 million. Additional value of at least $238 million per year could be enabled by increasing utilization. Notably, uneconomic flows and low utilization rates can persist even when the price spread between regions is large. These conclusions are derived from historical (2014–2023) data on the magnitude and direction of interregional price spreads, the magnitude and direction of net energy transfers, and how these variables coincide, but do not account for all system constraints. These findings motivate the development and deployment of solutions that improve interregional transmission operations, in parallel with robust transmission infrastructure planning. JEL Classification: Q40 Energy: General

Q40 Energy: General↗

Physics-Based Limiter Redesign and Bit Performance Analysis at The Geysers

As part of a U.S. DOE Geothermal Technologies Office funding opportunity, Geysers Power Company, LLC (GPC), an indirect subsidiary of Calpine Corporation, partnered with Sandia National Labs, EGI at the University of Utah, and Texas A&M University to demonstrate increased drilling performance at The Geysers Geothermal Field. The performance target in the drilling demonstrations is at least a 25% improvement in rates of penetration, with increased footage on bottom for each bit coupled with increased bit life and time drilling. The project leverages advances in oil and gas drilling technologies including PDC bits, along with the physics-based limiter redesign techniques championed in drilling demonstrations conducted at the Utah FORGE geothermal site. The planned drilling demonstrations are being conducted as part of an existing drilling campaign intended to enhance reservoir utilization. The wells are typically drilled to the top of the reservoir with mud and then air-drilled to total depth (TD) through fractured zones at temperatures ≥ 450°F. A major goal of the project is to assess the effectiveness of implementing mechanical specific energy (MSE) and drilling dysfunction diagnosis and remediation in these challenging environments, as well as alternate rock reduction technologies. The first demonstration well has been completed, with 15 PDC bit runs in the 17.5”, 12.25” and 8.5” sections. Initial analysis shows ROP gains in all three sections, especially in the 17.5” and 12.25” sections, compared with conventional roller cone bit runs in the demonstration well and offset wells. However, in the 8.5” hole, wear and damage to the PDC bits resulted in relatively short bit runs. Analysis is underway to take advantage of the positive results and remediate the challenges. This paper provides updates on drilling activities conducted since the Phase 1 demonstration well at GDC-36 which was drilled from November 2023-January 2024. Additional analysis of the bit performance has been conducted. Furthermore, in subsequent wells drilled by GPC, PDC bits have been used extensively, building on the gains realized at GDC-36. GPC has continued to work with bit vendors to identify designs that last longer in the harsh, air-drilled 8.5” portions of the wells. Planning for the Phase 2 demonstration at Prati-44 is ongoing.

15 GEOTHERMAL ENERGY↗

Numerical Analysis of Novel Plate Type Heat Exchanger with Oval-Twisted Channels

The novel heat exchanger (HX) designs implementing geometrical and surface modification combinations are expected to perform better than traditional HX technologies. Applied enhancement techniques seek to achieve (1) higher overall heat transfer performance, (2) increased compactness, and (3) simplified or comparable manufacturability. One innovative enhancement technique is to generate swirling flow vortices induced by channel or tube twisting. The turbulence generated by the twisted cross-section greatly enhances the heat transfer rate with minimal increases in pressure drop. Plate-type HXs and Printed Circuit Heat Exchangers (PCHXs) are compact designs that achieve high heat transfer rates per unit volume by utilizing several small channels, which maximizes the heat transfer surface area between the hot and cold fluids. Currently, advanced manufacturing technologies enable the design and fabrication of compact-type units with complicated channel geometries to achieve the highest performance and meet the compactness criteria of innovative HX technology. The proposed HX design concept combines the compactness of plate-type HXs and twisted channels, which provide additional turbulence and flow swirl enhancement. The plate-type oval-twisted HX (PTOTHX) is a crossflow configuration, with 16 short channels on one side (for hot fluid) and 8 long channels on the perpendicular side (for cold fluid). The inlet plenums have flow guide vanes to redirect flow and produce uniformity across the various flow paths. The compact size and purportedly improved heat transfer performance of the PTOTHX investigated herein prove its viability in various applications. Some notable potential nuclear applications of the PTOTHX include reactor core, spent fuel cooling, and residual heat dissipation. To establish a reference case, circular channels (PTCHX) are also considered in the present study for comparison with (PTOTHX). This paper aims to outline the numerical analysis procedures for determining the viability of the PTOTHX by comparing its heat transfer performance with the PTCHX units. The computational study used STAR-CCM+, a commercial computational fluid dynamics (CFD) code. Sensitivity analysis and model selection studies are conducted to determine the appropriate mesh density and turbulence model to provide the reported results. Numerical analyses comparing the Nusselt number (Nu) of the PTOTHX design with a comparable HX unit, including a circular cross-section and no twisting (PTCHX), show an overall heat transfer performance increase of 29-55% for balanced flow and 29-59% for imbalanced flow. Oval-cross-sectional twisted channels induce swirling flow vortices, enhancing the working fluid's convective heat transfer capabilities.

25 ENERGY STORAGE↗

Heavy-Duty Nonroad Material Handler Electrification Part 1: Real-World Drive Cycle Development

Knowing a detailed operating cycle is critical for developing and testing equipment. Operating cycles can be separated by two clear distinctions: (1) regulatory or non-regulatory and (2) application at the engine-only or full machine level. The Environmental Protection Agency’s (EPA) Nonroad Transient Cycle (NRTC) may be a good representation of engine use in many types of equipment, but there is a gap in standardized and validated drive cycles specifically for nonroad material handlers. Lacking a standardized drive cycle makes it difficult to accurately benchmark machine performance and validate new powertrain technologies. The objective of this investigation is to illustrate the development of a custom drive cycle augmented with real-world customer use data that serves multiple purposes: (1) understand the range of operation and utilization that formulated inputs for electrified architecture analysis and (2) develop a repetitive and consistent maneuver to establish baseline energy consumption enabling equivalent comparison to future electrified prototype builds. This article presents a solution specifically for a 23-ton nonroad material handler in which material handling, machine transport, and extended idle were homologated to form representative short cycles defined by machine velocity and hydraulic cylinder position. The most intensive material handling short cycles had a load factor of 40% and an average fuel rate of 16 L/h. Combined with a visual aid, the short cycles exhibited low variability, having less than 5% root mean square (RMS) error in lift and reach position with respect to the average. The machine’s performance on these short cycles at the Advanced Power Systems Research Center (APSRC) was compared to results from two real-world customer locations operating the instrumented test machine in a cyclical manner, and for similar ground conditions were found to be comparable in fuel consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Document Management: A Focused Analysis on the Configuration Management Process at Y-12 National Security Complex

The configuration management process at Y-12 is a crucial process to ensure safe operations and compliance with Department of Energy (DOE) regulations and requirements. This process is evaluated utilizing systems-thinking methodology in order to understand the current operational flow, with the ultimate goal of building an easily understandable, representative model. This model offers insights on key areas of waste and provides a potential solution by modernizing rate limiting steps: a software implementation to update the traditional document management system and make it paperless. Stakeholders of the software implementation are identified in order to define characteristic requirements of an effective product and the anticipated benefit is evaluated. Ultimately, this project is an effort to increase the quality of life for all stakeholders, while improving the capacity, throughput, and effectiveness of a necessary process at Y-12.

42 ENGINEERING↗

Optimization of metal-supported solid oxide electrolysis cells with infiltrated catalysts

We report metal-supported solid oxide electrolysis cells (MS-SOECs) are being developed for steam-to-hydrogen electrolysis, especially for utilization of dynamic or intermittent electrical power from renewable sources. Various aspects of the electrocatalyst processing and composition, and metal support structure were explored. Catalyst materials, infiltration temperature and infiltration cycles were optimized for high performance and durability. Numerous catalyst materials were screened for both oxygen and steam electrodes. The oxygen catalyst had moderate impact on both initial cell performance and durability. Reducing Ni content in the steam electrode had little effect on durability, but reduced initial performance. Ex-situ XRD analysis and cell assessment of catalyst infiltration temperature revealed that the optimal range is 750–850 °C. The best cell performance and durability was achieved with LSCF-SDC oxygen electrocatalyst and SDC-Ni (60:40 vol%) steam electrocatalyst infiltrated 11 times at 800 °C and operated at 700 °C. At low steam content, a significant mass transport limitation on the steam side results in limiting current behavior. Thinner and more porous metal supports were implemented, and found to improve steam mass transport at low steam content, relevant for SOECs operating under high H 2 recycle rate or high steam utilization.

08 HYDROGEN↗

Practical Considerations for Understanding Surface Reaction Mechanisms Involved in Heterogeneous Catalysis

Acquiring useful knowledge about the active site(s) of a catalyst, nature of reactant–catalyst interactions, nature of reactive intermediates, rate-determining step, reaction rate orders that affect various process parameters, and reaction mechanism as a whole is exceedingly challenging. This is especially true in the case of heterogeneous catalysts due to the complexity of the nature of surface active sites and their nonstatic behavior. Here, we present our perspective on differentiating between various surface reaction mechanisms in light of pioneering studies by leaders in the field, with the aim of clarifying some of the confusion associated with these complex mechanisms, especially the Eley–Rideal mechanism. Using bibliometric analysis, we identify and discuss the following four reactions that most commonly invoke the Eley– Rideal mechanism: H 2 activation, CO oxidation, esterification of alcohols by acids, and selective catalytic reduction (SCR) of NO x with NH 3 . Our analysis of studies utilizing well-suited experimental and computational methodologies for differentiating surface reaction mechanisms suggests that the above-mentioned four reactions do not occur via the Eley–Rideal mechanism. Instead, each reaction occurs via the Langmuir–Hinshelwood mechanism with nonidealities present. Lastly, we highlight practical considerations regarding select experimental (characterization methods and differential kinetics) and computational modeling that we believe can provide useful insights to accurately discern between the various possible reaction mechanisms in heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗

COVIDScholar: An automated COVID-19 research aggregation and analysis platform

The ongoing COVID-19 pandemic produced far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community’s COVID-19 response lead to the emergence of new research at the remarkable rate of more than 250 papers published per day. This posed a challenge for the scientific community as traditional methods of engagement with the literature were strained by the volume of new research being produced. Meanwhile, the urgency of response lead to an increasingly prominent role for preprint servers and a diffusion of relevant research through many channels simultaneously. These factors created a need for new tools to change the way scientific literature is organized and found by researchers. With this challenge in mind, we present an overview of COVIDScholar https://covidscholar.org/, an automated knowledge portal which utilizes natural language processing (NLP) that was built to meet these urgent needs. The search interface for this corpus of more than 260,000 research articles, patents, and clinical trials served more than 33,000 users at an average of 2,000 monthly active users and a peak of more than 8,600 weekly active users in the summer of 2020. Additionally, we include an analysis of trends in COVID-19 research over the course of the pandemic with a particular focus on the first 10 months, which represents a unique period of rapid worldwide shift in scientific attention.

60 APPLIED LIFE SCIENCES↗

Proxy quality control of biomass particles using thermogravimetric analysis and Gaussian process regression models

Abstract The temperature experienced by reactants during preparation in a reactor is a key component in determining the yield and homogeneity of usable chemical products such as biomass particles. Thermocouples with sensors can be used to monitor spatial temperature gradients within reactors but these sensors are often too expensive and/or invasive. The present work proposes a strategy to identify optimal machine learning models to infer the maximum effective temperature experienced by particles during oxidative biomass torrefaction using key thermochemical combustion parameters. The maximum rate of weight loss, the corresponding temperature, and fixed carbon content on a dry‐ash‐free basis are used as literature‐based predictor variables obtained from thermogravimetric analysis. The evaluation of 24 machine‐learning models using the standard tenfold cross‐validation method suggests that the exponential Gaussian process regression (GPR) model is the most effective, followed by other GPR models. These high‐performing GPR models were also utilized to predict the effective preparation temperature distribution of reactor‐produced biomass particles under eight conditions of varying residence time and air‐to‐biomass ratio. The effective preparation temperature and residence time of individual biomass particles were then encoded into the torrefaction severity factor and used to estimate the energy yield of the reactor output as a novel quality control method. © 2023 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗