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At least 1,279 records · Page 71

Nuclear's Role in the U.S. Electricity System: A Multi-Model Inter-Comparison Analysis

Multiple capacity expansion models (CEMs) for the U.S. power system represent the balance of options among generation, transmission, and storage assets that can satisfy electric loads, operating and planning reserves, and policy requirements. These models are typically set up to find the least-cost portfolio of assets that meet specified requirements, and model decisions can include both investments in new, and retirement of existing, resources. The scenarios explored by CEMs can help inform strategies for meeting future electricity and energy needs under a range of future conditions. However, projections can differ between models, sometimes dramatically, for a seemingly similar scenario. Differences in model coverage, structure, and input assumptions contribute to the range of model outcomes. Understanding what drives the biggest differences in model outputs improves model insights and provides context for interpreting results. This summary presents analysis that was performed through a forum of analysts who own, update, and apply CEMs, as well as nuclear experts from national laboratories, industry, and the research community. The following sections describe methods, results, and findings from an original, innovative inter-model comparison that provides insights into what drives the greatest differences in nuclear retirement and deployment projections across models and a range of technology, market, and policy conditions.

capacity expansion model↗

Crushing behaviors of unidirectional carbon fiber reinforced plastic composites under dynamic bending and axial crushing loading

The dynamic crushing characteristics of unidirectional carbon fiber reinforced plastic composites under two loading types, dynamic three-point bending and axial crushing, are investigated by experiment and finite element simulation. Hat section samples with two different layup orientations are tested at various impact velocities to investigate its effects. The experiment results show that delamination plays a critical role in dynamic bending deformation. Different layup orientations lead to similar crushing bending behaviors, but remarkable variations in delamination pattern evolutions. In contrast, layup orientation exerts more significant effects on failure modes and energy absorption in axial crushing. A finite element model with multiple layers of thick shell element and cohesive element is established, and simulations are performed for both dynamic three-point bending and axial crushing. The model can capture the crushing behaviors in the two loading types reasonably well. The damage evolution and energy absorption through various mechanisms at different loading conditions are discussed.

42 ENGINEERING↗

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗

Coolant Density and Control Blade History Effects in Extended BWR Burnup Credit

Oak Ridge National Laboratory and the US Nuclear Regulatory Commission have initiated a multiyear project to investigate the application of burnup credit (BUC) for boiling water reactor (BWR) fuel in storage and transportation casks. This project includes two phases. The first phase investigates the applicability of peak reactivity methods currently used for spent fuel pools to spent fuel storage and transportation casks and the validation of reactivity (k eff ) calculations and predicted spent fuel compositions. The second phase focuses on extending BUC beyond peak reactivity. This paper documents work performed to date investigating some aspects of extended BUC. (The technical basis for application of peak reactivity methods to BWR fuel in storage and transportation systems is presented in a companion paper.) Two reactor operating parameters are being evaluated to establish an adequate basis for extended BWR BUC: (1) the effect of axial void profile and (2) the effect of control blade utilization during operation. A detailed analysis of core simulator data for one cycle of a modern operating BWR plant was performed to determine the range of void profiles and the variability of the profile experienced during irradiation. Although a single cycle does not provide complete data, the data obtained are sufficient to determine the primary effects and to identify conservative modeling approaches. These data were used in a study of the effect of axial void profile. The first stage of the study was determination of the necessary moderator density temporal fidelity in depletion modeling. After the required temporal fidelity was established, multiple void profiles were used to examine the effect on cask reactivity. The results of these studies are being used to develop recommendations for conservatively modeling the void profile effects for BWR depletion calculations. The second operational parameter studied was control blade history. Control blades are inserted in various locations and at varying degrees during BWR operation based on the core loading pattern. When present during depletion, control blades harden the neutron spectrum locally because they displace the moderator and absorb thermal neutrons. The investigation of the effect of control blades on post operational cask reactivity is documented herein, as is the effect of multiple (continuous and intermittent) exposure periods with control blades inserted. The coupled effects of control blade presence on power density, void profile, or burnup profile will be addressed in future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Coolant density and control blade history effects in extended BWR burnup credit - 14494

Oak Ridge National Laboratory and the US Nuclear Regulatory Commission have initiated a multiyear project to investigate the application of burnup credit (BUC) for boiling water reactor (BWR) fuel in storage and transportation casks. This project includes two phases. The first phase investigates the applicability of peak reactivity methods currently used for spent fuel pools to spent fuel storage and transportation casks and the validation of reactivity (k{sub eff}) calculations and predicted spent fuel compositions. The second phase focuses on extending BUC beyond peak reactivity. This paper documents work performed to date investigating some aspects of extended BUC. The technical basis for application of peak reactivity methods to BWR fuel in storage and transportation systems is presented in a companion paper. Two reactor operating parameters are being evaluated to establish an adequate basis for extended BWR BUC: (1) the effect of axial void profile and (2) the effect of control blade utilization during operation. A detailed analysis of core simulator data for one cycle of a modern operating BWR plant was performed to determine the range of void profiles and the variability of the profile experienced during irradiation. Although a single cycle does not provide complete data, the data obtained are sufficient to determine the primary effects and to identify conservative modeling approaches. These data were used in a study of the effect of axial void profile. The first stage of the study was determination of the necessary moderator density temporal fidelity in depletion modeling. After the required temporal fidelity was established, multiple void profiles were used to examine the effect on cask reactivity. The results of these studies are being used to develop recommendations for conservatively modeling the void profile effects for BWR depletion calculations. The second operational parameter studied was control blade history. Control blades are inserted in various locations and at varying degrees during BWR operation based on the core loading pattern. When present during depletion, control blades harden the neutron spectrum locally because they displace the moderator and absorb thermal neutrons. The investigation of the effect of control blades on post operational cask reactivity is documented herein, as is the effect of multiple (continuous and intermittent) exposure periods with control blades inserted. The coupled effects of control blade presence on power density, void profile, or burnup profile will be addressed in future work. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Efficient electrochemical CO 2 conversion powered by renewable energy

Here, the catalytic conversion of CO 2 into industrially relevant chemicals is one strategy for mitigating greenhouse gas emissions. Along these lines, electrochemical CO 2 conversion technologies are attractive because they can operate with high reaction rates at ambient conditions. However, electrochemical systems require electricity, and CO 2 conversion processes must integrate with carbon-free, renewable-energy sources to be viable on larger scales. We utilize Au 25 nanoclusters as renewably powered CO 2 conversion electrocatalysts with CO 2 → CO reaction rates between 400 and 800 L of CO 2 per gram of catalytic metal per hour and product selectivities between 80 and 95%. These performance metrics correspond to conversion rates approaching 0.8–1.6 kg of CO 2 per gram of catalytic metal per hour. We also present data showing CO 2 conversion rates and product selectivity strongly depend on catalyst loading. Optimized systems demonstrate stable operation and reaction turnover numbers (TONs) approaching 6 × 10 6 mol CO 2 molcatalyst–1 during a multiday (36 hours total hours) CO 2 electrolysis experiment containing multiple start/stop cycles. TONs between 1 × 10 6 and 4 × 10 6 molCO 2 molcatalyst–1 were obtained when our system was powered by consumer-grade renewable-energy sources. Daytime photovoltaic-powered CO 2 conversion was demonstrated for 12 h and we mimicked low-light or nighttime operation for 24 h with a solar-rechargeable battery. This proof-of-principle study provides some of the initial performance data necessary for assessing the scalability and technical viability of electrochemical CO 2 conversion technologies. Specifically, we show the following: (1) all electrochemical CO 2 conversion systems will produce a net increase in CO 2 emissions if they do not integrate with renewable-energy sources, (2) catalyst loading vs activity trends can be used to tune process rates and product distributions, and (3) state-of-the-art renewable-energy technologies are sufficient to power larger-scale, tonne per day CO 2 conversion systems.

30 DIRECT ENERGY CONVERSION↗

Constructing Highly Porous Low Iridium Anode Catalysts Via Dealloying for Proton Exchange Membrane Water Electrolyzers

Iridium (Ir) is the most active and durable anode catalyst for the oxygen evolution reaction (OER) for proton exchange membrane water electrolyzers (PEMWEs). However, their large-scale applications are hindered by high costs and scarcity of Ir. Lowering Ir loadings below 1.0 mgcm -2 causes significantly reduced PEMWE performance and durability. Therefore, developing efficient low Ir-based catalysts is critical to widely commercializing PEMWEs. Herein, an approach is presented for designing porous Ir metal aerogel (MA) catalysts via chemically dealloying IrCu alloys. In this study, the unique hierarchical pore structures and multiple channels of the Ir MA catalyst significantly increase electrochemical surface area (ECSA) and enhance OER activity compared to conventional Ir black catalysts, providing an effective solution to design low-Ir catalysts with improved Ir utilization and enhanced stability. An optimized membrane electrode assembly (MEA) with an Ir loading of 0.5 mg Ir cm -2 generated 2.0 A cm -2 at 1.79 V, higher than the Ir black at a loading of 2.0 mg Ir cm -2 (1.63 A cm -2 ). The low-Ir MEA demonstrated an acceptable decay rate of ≈40 µV h -1 during durability tests at 0.5 (>1200 h) and 2.0 A cm -2 (400 h), outperforming the commercial Ir-based MEA (175 µV h -1 at 2.0 mg Ir cm -2 ).

36 MATERIALS SCIENCE↗

Speed Variation Based Power Regulation Concept for Dynamic Wireless Charging

On-road wireless charging of electric vehicles (EVs) in-motion could potentially reduce range anxiety or battery size with wide-spread deployment. The planning and implementation of such systems are greatly complicated due to their susceptibility to load variation inherent to traffic flow. Here, this paper proposes a method for derisking the potential for traffic slowdowns by compensating for reduced vehicle speed and investigates how implementation may affect system performance. A load modeling case study is presented at 200kW for a mile of high-speed roadway employing speed-based power regulation with results indicating average power usage and maximum car hosting capability can be reduced by 20% and increased by 30% respectively. An 85kHz power electronics model is developed based on designs and prototypes for an 11kW, 190m airgap static system and a 200kW dynamic wireless track. The simulation is validated in the 11kW experimental prototype and modified for 200kW operation to compare with simulated performance. Sensitivity studies are performed in MATLAB/Simulink to evaluate how parameters influence system performance and confirm the capability to reduce output power and maintain efficiency at 11 and 200kW. The static 11kW experimental system operates at 93.6% efficiency and multiple options exist to reduce power while maintaining efficiency greater than 90%. The capability to dynamically modify power output from WPT coils, in an experimentally validated simulation, enables techniques to significantly mitigate load variability due to reductions in vehicle speed.

42 ENGINEERING↗

Efficient Parallelization of Irregular Applications on GPU Architectures

With the enlarging computation capacity of general Graphics Processing Units (GPUs), leveraging GPUs to accelerate parallel applications has become a critical topic in academia and industry. However, a wide range of irregular applications with the computation-/memory-intensive nature cannot easily achieve high GPU utilization. The challenges mainly involve the following aspects: first, data dependence leads to coarse-grained kernel and inefficient parallelism; second, heavy GPU memory usage may cause frequent memory evictions and extra overhead of I/O; third, specific computation patterns produce memory redundancies; last, workload balance and data reusability conjunctly benefit the overall performance, but there may exist a dynamic trade-off between them. Targeting these challenges, this dissertation proposes multiple optimizations to accelerate two real-world applications: many-body correlation functions to simulate nuclear physics in a large-scale scientific system; the other is the eALS-based matrix factorization recommendation system. To accelerate the calculations of many-body correlation functions, this dissertation presents three frameworks in GPU memory management and multi-GPU scheduling. Firstly, an optimized systematic GPU memory management framework, MemHC, utilizes a series of new memory reduction designs in GPU memory allocation, CPU/GPU communications, and GPU memory oversubscription. Secondly, an enhanced multi-GPU scheduling framework, MICCO, particularly by taking both data dimension (e.g., data reuse and data eviction) and computation dimension into account. MICCO designs a heuristic scheduling algorithm and a machine learning-based regression model to generate the optimal settings of a proposed new concept to manage the trade-off. Thirdly, a locality-aware multi-GPU scheduling framework. This scheduler leverages pipeline batch generation with a looking-ahead strategy by building local dependency graphs for memory transfer reduction and better data reuse, achieving up to 79.92% memory cost reduction and 1.67x speedup. To parallelize the eALS-based recommendation system, this dissertation proposes an efficient CPU/GPU heterogeneous recommendation system, HEALS. HEALS employs newly designed architecture-adaptive data formats to achieve load balance and good data locality on CPU and GPU. To mitigate the data dependence, HEALS presents a CPU/GPU collaboration model for both task parallelism and data parallelism with multiple kernel computation optimizations. In summary, this dissertation efficiently accelerates two typical irregular applications on GPUs by building four frameworks, including CPU/GPU collaboration, GPU memory management, and multi-GPU scheduling.

Wang, Qihan↗

Method for Estimating Operational Loads on Aerospace Structures Using Span-Wisely Distributed Surface Strains

This report presents a new method for estimating operational loads (bending moments, shear loads, and torques) acting on slender aerospace structures using distributed surface strains (unidirectional strains). The surface strain-sensing stations are to be evenly distributed along each span-wise strain-sensing line. A depth-wise cross section of the structure along each strain-sensing line can then be considered as an imaginary embedded beam. The embedded beam was first evenly divided into multiple small domains with domain junctures matching the strain-sensing stations. The new method is comprised of two steps. The first step is to determine the structure stiffness (bending or torsion) using surface strains obtained from a simple bending (or torsion) loading case, for which the applied bending moment (or torque) is known. The second step is to use the strain-determined structural stiffness (bending or torsion), and a new set of surface strains induced by any other loading case to calculate the associated operational loads (bending moments, shear loads, or torques). Performance of the new method for estimating operational loads was studied in light of finite-element analyses of several example structures subjected to different loading conditions. The new method for estimating operational loads was found to be fairly accurate, and is very promising for applications to the flight load monitoring of flying vehicles with slender wings.

Ko, William L.↗

A novel framework for hosting capacity analysis with spatio-temporal probabilistic voltage sensitivity analysis

Smart grids are envisioned to accommodate high penetration of distributed photovoltaic (PV) generation, which may cause adverse grid impacts in terms of voltage violations. Therefore, PV Hosting capacity is being used as a planning tool to determine the maximum PV installation capacity that causes the first voltage violation and above which would require infrastructure upgrades. Additionally, traditional methods of Hosting capacity analysis are scenario based and computationally complex as they rely on iterative load flow algorithms that require investigating a large number of scenarios for accurate assessment of PV impacts. Therefore, this paper presents a computationally efficient analytical approach to compute the probability distribution of voltage change due to random behavior of randomly located multiple distributed PVs. The proposed approach is based on Spatio-temporal probabilistic voltage sensitivity analysis that exploits both spatial and temporal uncertainties associated with PV injections. Thereafter, the derived distribution is used to quantify voltage violations for various PV penetration levels and subsequently determine the hosting capacity of the system without the need to examine large number of scenarios. Results of the proposed framework are validated via conventional load flow based simulation approach on the IEEE 37 and IEEE 123 node test systems.

42 ENGINEERING↗

The Technical and Economic Potential of the H2@Scale Hydrogen Concept within the United States

The U.S. energy system is evolving as society and technologies change. Renewable electricity generation - especially from wind and solar - is growing rapidly, and alternative energy sources are being developed and implemented across the residential, commercial, transportation, and industrial sectors to take advantage of their cost, security, and health benefits. Systemic changes present numerous challenges to grid resiliency and energy affordability, creating a need for synergistic solutions that satisfy multiple applications while yielding system-wide cost and emissions benefits. One such solution is an integrated hydrogen energy system. This is the focus of H2@Scale - a U.S. Department of Energy (DOE) initiative led by the Office of Energy Efficiency and Renewable Energy’s Hydrogen and Fuel Technologies Office. H2@Scale brings together stakeholders to advance affordable hydrogen production, transport, storage, and utilization in multiple energy sectors. The H2@Scale concept involves hydrogen as an energy intermediate. Hydrogen can be produced from various conventional and renewable energy sources including as a responsive load on the electric grid. Hydrogen has many current applications and many more potential applications, such as energy for transportation - used directly in fuel cell electric vehicles (FCEVs), as a feedstock for synthetic fuels, and to upgrade oil and biomass - feedstock for industry (e.g., for ammonia production, metals refining, and other end uses), heat for industry and buildings, and electricity storage. Owing to its flexibility and fungibility, a hydrogen intermediate could link energy sources that have surplus availability to markets that require energy or chemical feedstocks, benefiting both. This document builds upon a growing body of analyses of hydrogen as an energy intermediate by reporting the results from our initial analysis of the potential impacts of the H2@Scale vision by the mid-21 st century for the 48 contiguous U.S. states. Previous estimates have been based on expert elicitation and focused on hydrogen demands. We build upon them, first, by estimating hydrogen’s serviceable consumption potential for possible hydrogen applications and the technical potential for producing hydrogen from various resources. We define the serviceable consumption potential as the quantity of hydrogen that would be consumed to serve the portion of the market that could be captured without considering economics (i.e., if the price of hydrogen were $0/kg over an extended period); thus, it can be considered an upper bound for the size of the market. We define the technical potential as the resource potential constrained by real-world geography and system performance, but not by economics. We then compare the cumulative serviceable consumption potential with the technical potential of a number of possible sources. Second, we estimate economic potential: the quantity of hydrogen at an equilibrium price at which suppliers are willing to sell and consumers are willing to buy the same quantity of hydrogen. We believe this method provides a deeper understanding than was available in the previous analyses. We develop economic potentials for multiple scenarios across various market and technology-advancement assumptions.

08 HYDROGEN↗

Lightweight Deployable Mirrors with Tensegrity Supports

The upper part of Figure 1 shows a small-scale prototype of a developmental class of lightweight, deployable structures that would support panels in precise alignments. In this case, the panel is hexagonal and supports disks that represent segments of a primary mirror of a large telescope. The lower part of Figure 1 shows a complete conceptual structure containing multiple hexagonal panels that hold mirror segments. The structures of this class are of the tensegrity type, which was invented five decades ago by artist Kenneth Snelson. A tensegrity structure consists of momentfree compression members (struts) and tension members (cables). The structures of this particular developmental class are intended primarily as means to erect large segmented primary mirrors of astronomical telescopes or large radio antennas in outer space. Other classes of tensegrity structures could also be designed for terrestrial use as towers, masts, and supports for general structural panels. An important product of the present development effort is the engineering practice of building a lightweight, deployable structure as an assembly of tensegrity modules like the one shown in Figure 2. This module comprises two octahedral tensegrity subunits that are mirror images of each other joined at their plane of mirror symmetry. In this case, the plane of mirror symmetry is both the upper plane of the lower subunit and the lower plane of the upper subunit, and is delineated by the midheight triangle in Figure 2. In the configuration assumed by the module to balance static forces under mild loading, the upper and lower planes of each sub-unit are rotated about 30 , relative to each other, about the long (vertical) axis of the structure. Larger structures can be assembled by joining multiple modules like this one at their sides or ends. When the module is compressed axially (vertically), the first-order effect is an increase in the rotation angle, but by virtue of the mirror arrangement, the net first-order rotation between the uppermost and lowermost planes is zero. The need to have zero net rotation between these planes under all loading conditions in a typical practical structure is what prompts the use of the mirror configuration. Force and moment loadings other than simple axial compression produce only second-order deformations through strains in the struts and cables.

Zeiders, Glenn W.↗

Design and performance assessment of a dual-mode latent thermal storage integrated heat pump across multiple climate zones

The electrification of space cooling and heating systems risks overloading the existing electrical grid during peak hours. Heat pumps integrated with thermal energy storage (HP-TES) offer a promising solution by shifting peak loads to off-peak hours, reducing grid strains. This work presents the design and assessment of a dual-mode HP-TES that uses a single 22°C phase-change material (PCM) as a heat source or sink in heating and cooling modes, respectively. Performance assessment was conducted using Modelica-based transient models, and full-year simulations were conducted across eight US climate zones using typical weather data. Two HP-TES performance metrics: peak energy reduction and recharge energy increases, were defined by comparing HP-TES energy consumption with base HP peak consumptions. Annual heating demand reductions (40–65%) exceeded cooling demand reductions (15–20%) due to the elimination of peak-hour backup heating. Cooling mode recharge energy requirements (0–10%) were reduced in locations with lower summer nighttime temperatures, while heating recharge requirements were lower than the high base-peak energy demand from backup heating. Simplified rapid methods that were 10 7 times faster than annual simulations were developed to predict seasonal cooling and heating energy reductions, and recharge energy requirements, with maximum deviations of ±2.5% and ±3.5% points. These methods enabled rapid parametric studies that identified optimal location-specific PCM temperatures between 22°C and 27°C, highlighting the need to consider both discharge and recharge energy requirements to achieve sustainable, energy-efficient peak load shifting across various climate zones.

25 ENERGY STORAGE↗

Frequency, pressure and strain dependence of nonlinear elasticity in Berea Sandstone

Acoustoelasticity measurements in a sample of room dry Berea sandstone are conducted at various loading frequencies to explore the transition between the quasi-static ( f → 0) and dynamic (few kilohertz) nonlinear elastic response. We carry out these measurements at multiple confining pressures and perform a multivariate regression analysis to quantify the dependence of the harmonic content on strain amplitude, frequency, and pressure. The modulus softening (equivalent to the harmonic at 0f) increases by a factor 2–3 over 3 orders of magnitude increase in frequency. Harmonics at 2f, 4f, and 6f exhibit similar behaviors. In contrast, the harmonic at 1f appears frequency independent. This result corroborates previous studies showing that the nonlinear elasticity of rocks can be described with a minimum of two physical mechanisms. This study provides quantitative data that describes the rate dependency of nonlinear elasticity. Furthermore, these findings can be used to improve theories relating the macroscopic elastic response to microstructural features.

58 GEOSCIENCES↗

Post-extreme-event restoration using linear topological constraints and DER scheduling to enhance distribution system resilience

In this paper, a post-extreme-event restoration (PEER) algorithm is proposed to improve distribution system resilience. Linear topological constraints are proposed to ensure radial topology after N-k contingencies, possibly in multiple islands. The approach is made comprehensive by considering dispatchable distributed energy resources (DERs), non-dispatchable DERs, and demand responses, as well as on-load tap changers (OLTCs) and shunt capacitors. The goal is to minimize the accumulative expense caused by load reduction payment or penalty, as well as DER operation cost. As a result, the overall system will survive longer with higher resilience during an extreme event. To verify the effectiveness of the PEER algorithm, we proposed a resilience evaluation algorithm using Monte Carlo simulation (MCS) with reduced scenarios. This is based on a probabilistic model for generating random scenarios which consider the uncertainty of line faults and solar irradiance. Combined with the proposed PEER algorithm, this reduced-scenario MCS can evaluate the expected energy not served (EENS) which is an essential index for distribution system resilience. Case studies of the IEEE 33-bus and 123-bus test systems validate the proposed algorithm in reducing EENS.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Restructuring of the Lewis Acid Sites in Y-Modified Dealuminated Beta-Zeolite by Hydrothermal Treatment

Yttrium-modified dealuminated Betazeolite (Y-BEA) represents a type of Lewis acid zeolite that has gained attention for its potential to efficiently catalyze the conversion of biomass-derived oxygenates. The structure of the Y active sites and their dynamics during biomass conversion reactions, which normally involve substantial amounts of water, necessitate thorough investigation for the rational design of more active and stable catalysts. Here, we conducted a study where a series of Y-BEA catalysts with different yttrium loadings (1–7 wt.%) were subjected to hydrothermal treatment (450 °C, 20% water) and investigated for their structural and catalytic activity changes through a combination of multiple characterizations and kinetic measurements. The number of acid sites of Y-BEA decreased without a change in acid strength following the hydrothermal treatment, which was confirmed by the results of acid site titration, infrared spectroscopy of probe molecules, and kinetic measurements for probe reactions (acetone aldol condensation). Structural analysis using X-ray diffraction (XRD), specific surface area measurement, X-ray absorption spectroscopy (XAS), and X-ray photoelectron spectroscopy (XPS) demonstrated that both the zeolite structure and the isolation status of the Y site remain intact after hydrothermal treatment. Further, the Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) spectra, thermogravimetric analysis (TGA), and operando 1 H and 29 Si magic-angle spinning (MAS) nuclear magnetic resonance (NMR) revealed the dehydroxylation of Y-BEA induced by hydration-rearrangement-condensation restructuring during the high-temperature steam treatment. Dehydroxylation affects the structure of Y sites by reducing their vicinal silanol sites. In conclusion, this conversion of Lewis acidic Y sites into nonacidic sites is the primary factor behind the change in acid site quantity and catalytic activity on Y-BEA.

36 MATERIALS SCIENCE↗

Design and Validation of a High-Throughput Reductive Catalytic Fractionation Method

Reductive catalytic fractionation (RCF) is a promising method to extract and depolymerize lignin from biomass, and bench-scale studies have enabled considerable progress in the past decade. RCF experiments are typically conducted in pressurized batch reactors with volumes ranging between 50 and 1000 mL, limiting the throughput of these experiments to one to six reactions per day for an individual researcher. Here, we report a high-throughput RCF (HTP-RCF) method in which batch RCF reactions are conducted in 1 mL wells machined directly into Hastelloy reactor plates. The plate reactors can seal high pressures produced by organic solvents by vertically stacking multiple reactor plates, leading to a compact and modular system capable of performing 240 reactions per experiment. Using this setup, we screened solvent mixtures and catalyst loadings for hydrogen-free RCF using 50 mg poplar and 0.5 mL reaction solvent. The system of 1:1 isopropanol/methanol showed optimal monomer yields and selectivity to 4-propyl substituted monomers, and validation reactions using 75 mL batch reactors produced identical monomer yields. To accommodate the low material loadings, we then developed a workup procedure for parallel filtration, washing, and drying of samples and a 1H nuclear magnetic resonance spectroscopy method to measure the RCF oil yield without performing liquid-liquid extraction. As a demonstration of this experimental pipeline, 50 unique switchgrass samples were screened in RCF reactions in the HTP-RCF system, revealing a wide range of monomer yields (21-36%), S/G ratios (0.41-0.93), and oil yields (40-75%). These results were successfully validated by repeating RCF reactions in 75 mL batch reactors for a subset of samples. We anticipate that this approach can be used to rapidly screen substrates, catalysts, and reaction conditions in high-pressure batch reactions with higher throughput than standard batch reactors.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗