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At least 217 records · Page 12

EV Stock and Load Forecasting for HECO [Slides]

This presentation covers the work completed for the HECO Forecasting Department for the Electric Vehicle Stock and Load Forecast for Integrated Grid Planning project. This project uses a suite of detailed analytical tools developed by the National Laboratory of the Rockies, including TEMPO and EVI-Pro, to develop future scenarios to 2050 of county-level electric vehicle adoption and associated annual hourly charging load profiles for the state of Hawaii.

33 ADVANCED PROPULSION SYSTEMS↗

FIREFLY: heat load and particle exhaust approximations for rapid evaluation of divertor designs

The divertor in a magnetic confinement fusion reactor is an essential component for power dissipation and particle removal. The FIREFLY package for rapid evaluation of divertor designs is presented as an extension of the FLARE code for field line reconstruction from a flux tube mesh. First, divertor loads are approximated with a simplified heat transport model. Neutralized particles are then sampled from the resulting load distribution, and the EIRENE code is used to track molecules and atoms in a plasma background while accounting for dissociation, charge exchange and ionization. Particles are removed on pumping surfaces in order to estimate the exhaust efficiency for a given divertor geometry. Optimization of the divertor geometry for more efficient particle exhaust is explored by using W7-X as an example, and the sensitivity to model parameters for the plasma background in the proxy calculations is evaluated.

mesh generation, magnetic field lines, scrape-off ↗

A Fast, Accurate Prediction for System-Wide Damage Due to Dynamic Wind Loading

The complex relationship between photovoltaic (PV) hardware configurations, overall system dynamics, and turbulent aerodynamic phenomena generates highly unsteady, non-uniform loads that can lead to damaging instabilities. These effects may result in glass breakage, cell cracking, and structural failures in frames and mounting systems, even under moderate wind conditions. Addressing industry concerns about premature system failures in field conditions deemed survivable, our research aims to develop a fast and accurate predictive model for system damage. This model integrates configurable hardware choices with advanced simulation tools to represent the overall system-specific dynamics effectively. Using this model, we predict responses under varying weather conditions and hardware setups, translating these predictions into pre-trained surrogate models capable of accurately identifying failure risks and rapidly testing new system hardening measures. In this presentation, we will showcase preliminary results in capturing system dynamics through our customizable library of PV hardware configurations. Additionally, we will highlight how these new tools build upon PVade's established wind load modeling capabilities and foster the development of advanced AI/ML surrogates for improving system robustness.

97 MATHEMATICS AND COMPUTING↗

Distributed Wind for Industrial Loads

Industrial loads have significant energy resilience requirements, which is one reason distributed wind may be a good option to help provide generation for these facilities. This fact sheet provides an overview of industrial load energy and resilience needs, and discusses why distributed wind may be a good option to provide onsite power for these facilities.

17 WIND ENERGY↗

Plug Load Management Through Occupant Engagement at Washington State University

To decrease costs and improve building occupant safety, Washington State University (WSU) began planning a plug load management campaign in 2020, with implementation beginning in 2021. This case study describes the campaign's goals, approach, and results over the past 5 years, ultimately showing that occupant- and behavior-focused strategies can meaningfully reduce plug load energy use while improving health and safety.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Adaptive Control for Load-Following of Boiling Water Reactors Part I: Linear Systems and Fully-Observable Dynamics

Automation control is a key strategy to improve the economic competitiveness of nuclear power plants. Not only does it help reduce operational costs, but it also extends the value proposition of these plants to nontraditional markets, including unattended operations in remote villages and space. However, the dynamics of the operating environments of nuclear reactors are subject to changes over time, and there are no widely adopted methods to ensure that the automation strategy will remain effective over the extended durations required for these applications. Adaptive control is a discipline that offers the possibility to accommodate such changes online. However, it relies on mathematical assumptions that must be respected to ensure robustness and reliability. In this work, we derive an adaptive control formulation for linear systems in which all states are observable and apply it to an instance of load-follow operation for Boiling Water Reactors. We assumed uncertainty in two factors: the temperature coefficient and the control rod worth, both of which are affected over time by the evolution of the nuclear reactor core environment. With an arbitrary penalty factor of 5, we found that the mean absolute and integral time absolute errors can be reduced by more than 90%, underscoring the strength of adaptive control. To extend the application to more challenges, different uncertainties and load-follow trajectories, as well as new formulations that include non-linearity and partial observability, are currently being developed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Volcano‐like Activity Trends in Au@Pd Catalysts: The Role of Pd Loading and Nanoparticle Size

The addition of palladium (Pd) to preformed gold nanoparticles (Au NPs) enables the formation of core‐shell structures with enhanced catalytic performance in oxidation reactions. However, predicting the precise palladium content required to achieve maximum catalytic activity remains difficult based on current understanding. Herein, Pd was systematically introduced onto titania‐supported Au NPs (2, 6, and 10 nm) to evaluate their performance in benzyl alcohol oxidation. A volcano‐like trend in catalytic activity was observed, where activity increased with Pd addition, peaked, and then declined. The Pd loading required for maximum activity depended on Au NP size: ≈40 at% Pd/Au for 2.6 nm, ≈20 at% Pd/Au for 6.4 nm, and ≈12.5 at% Pd/Au for 10.6 nm. For Au NPs > 6 nm, peak activity aligned with monolayer Pd coverage, while for smaller NPs (2–3 nm), optimal Pd content was below monolayer predictions. X‐ray absorption spectroscopy revealed a core‐shell structure at low Pd content, but higher Pd loadings led to Pd diffusion into the Au core. This structural transformation likely caused activity decline, indicating that AuPd alloying negatively impacts catalysis. These results highlight that core‐shell Au@Pd catalysts outperform AuPd alloys and provide crucial insights for designing highly active bimetallic catalysts.

X-ray absorption spectroscopy↗

Biocatalytic Carboxylic Acid Reduction and Transamination in Cell‐Free Lysates at High Substrate Loading

Chemoselective reduction of stable carboxylic acids to reactive aldehydes is of interest across many industries. While carboxylic acid reductases (CARs) are promising biocatalysts for this chemistry, poor chemoselectivity and low yield are commonly obtained when using less expensive crude lysate preparations and prerequisite ATP and NADPH regeneration systems. Here, in this work, we developed a highly chemoselective multienzyme cascade featuring a CAR and an ω-transaminase (TA) in crude lysate format, with conversion of the dicarboxylic acid terephthalic acid (TPA) into the diamine para -xylylenediamine (pXDA) as the model chemistry. We improved chemoselectivity for pXDA using engineered aldehyde-stabilizing Escherichia coli strains, though desired product yields remained modest. We next found that CAR activity was limited at high substrate loadings and overcame this bottleneck by modulating the ratio of polyphosphate (polyP 6 ) to Mg 2+ , enabling volumetric scaling and increased substrate loading up to 50 mM TPA. We then showcased the portability of this platform across substrates, resulting in the synthesis of four other high-value amines from carboxylate precursors. The combination of high carboxyl group turnover, up to 93.5 mM under the tested conditions, and the simplicity of crude enzyme preparation is a promising platform for sustainable functional group interconversion.

60 APPLIED LIFE SCIENCES↗

Interpreting test temperature and loading rate effects on the fracture toughness of polymer-metal interfaces via time–temperature superposition

Here, in this letter, we present interfacial fracture toughness data for a polymer-metal interface where tests were conducted at various test temperatures T and loading rates $\dot{δ}$. An adhesively bonded asymmetric double cantilever beam (ADCB) specimen was utilized to measure toughness. ADCB specimens were created by bonding a thinner, upper adherend to a thicker, lower adherend (both 6061 T6 aluminum) using a thin layer of epoxy adhesive, such that the crack propagated along the interface between the thinner adherend and the epoxy layer. The specimens were tested at T from 25 to 65 °C and $\dot{δ}$ from 0.002 to 0.2 mm/s. The measured interfacial toughness Γ increased as both T and $\dot{δ}$ increased. For an ADCB specimen loaded at a constant $\dot{δ}$, the energy release rate G increases as the crack length a increases. For this reason, we defined rate effects in terms of the rate of change in the energy release rate $\dot{G}$. Although not rigorously correct, a formal application of time–temperature superposition (TTS) analysis to the Γ data provided useful insights on the observed dependencies. In the TTS-shifted data, Γ decreased and then increased for monotonically increasing $\dot{G}$. Thus, the TTS analysis suggests that there is a minimum value of Γ. This minimum value could be used to define a lower bound in Γ when designing critical engineering applications that are subjected to T and $\dot{δ}$ excursions.

36 MATERIALS SCIENCE↗

Microgrid design and multi-year dispatch optimization under climate-informed load and renewable resource uncertainty

Microgrids are an increasingly popular solution to provide energy resilience in response to increasing grid dependency and the growing impacts of climate change on grid operations. However, existing microgrid models do not currently consider the uncertain and long-term impacts of climate change when determining a set of design and operational decisions to minimize long-term costs or meet a resilience threshold. In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. Additionally, we develop a two-stage stochastic programming extension of an existing microgrid design and dispatch optimization model to obtain uncertainty-informed and climate-resilient energy system decisions that minimizes long-term costs. Use of sample average approximation to validate our two case studies illustrates that the proposed methodology produces high-quality solutions that add resilience to systems with existing backup generation while reducing expected long-term costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quantification of [MTBD][beti] loading and its effects on Pt/HSC electrode performance in hydrogen fuel cells

High surface area carbon-supported platinum catalysts (Pt/HSC) are widely used in polymer electrolyte membrane fuel cells but often suffer from limited proton and oxygen transport within porous domains. To address these challenges, we integrate the ionic liquid [MTBD][beti] into Pt/HSC catalyst layers using two deposition methods-one-pot and sequential deposition-to tune IL distribution within micropores and mesopores. A combination of ex situ and in operando techniques were employed to elucidate electrode structure-performance relationships across a range of IL loadings. Sequential deposition achieved more efficient pore filling and higher IL retention at lower IL:C ratios, enabling enhanced proton conductivity and protection of active sites. Compared to the IL-free Pt/HSC, IL-modified electrodes demonstrated up to 28% improvement in mass activity and enhanced high-current-density performance under low relative humidity, while maintaining comparable performance under humidified conditions. Electrochemical impedance spectroscopy and CO displacement experiments reveal that improvements are linked to reduced ionic resistance and lower sulfonate adsorption on Pt sites, rather than changes in electrochemical surface area. However, excessive IL loading leads to mass transport losses. These results highlight the importance of selective pore filling and efficient IL distribution in achieving kinetic gains without compromising ionic and gas transport.

08 HYDROGEN↗

Unsteady aerodynamic loads on pitching aerofoils represented by Gaussian body force distributions

The actuator line model (ALM) is an approach commonly used to represent lifting and dragging devices like wings and blades in large-eddy simulations (LES). The crux of the ALM is the projection of the actuator point forces onto the LES grid by means of a Gaussian regularisation kernel. The minimum width of the kernel is constrained by the grid size; however, for most practical applications like LES of wind turbines, this value is an order of magnitude larger than the optimal value that maximises accuracy. This discrepancy motivated the development of corrections for the actuator line, which, however, neglect the effect of unsteady spanwise shed vorticity. In this work we develop a model for the impact of spanwise shed vorticity on the unsteady loading of an aerofoil modelled as a Gaussian body force distribution, where the model is applicable within the regime of unsteady attached flow. The model solution is derived both in the time and frequency domain and features an explicit dependence on the Gaussian kernel width. We verify the model with ALM-LES for both pitch steps and periodic pitching. The model solution is compared with Theodorsen theory and validated with both computational fluid dynamics using body fitted grids and experiment. It is concluded that the optimal kernel width for unsteady aerodynamics is approximately 40 % of the chord. The ALM is able to predict the magnitude of the unsteady loading up to a reduced frequency of 𝑘 ≈ 0.2.

17 WIND ENERGY↗

Predicted Fracture Tendency of Naturally Occurring Aluminum Surface Coatings under Tensile Loading

Naturally occurring coatings on aluminum metal, such as its oxide or hydroxide, serve to protect the material from corrosion. Understanding the conditions under which these coatings mechanically fail is therefore expected to be an important aspect of predictive models for aluminum component lifetimes. To this end, we develop and apply a molecular dynamics (MD) modeling framework for conducting tension tests that is capable of isolating factors governing the mechanical strength as a function of coating chemistry, defect morphology, and variables associated with the loading path. We consider two representative materials, including γ-Al 2 O 3 and γ-Al(OH) 3 (i.e., oxide and hydroxide), both of which form readily as aluminum surface coatings. Our results indicate that defects have a significant bearing on the strength of aluminum oxide, with grain boundaries serving to reduce the strain at failure from ε zz = 0.300 to 0.219, relative to perfect single crystal. Our simulations also predict that porosity lowers the elastic stiffness and yield strength of the oxide. Relative to perfect crystal, we find porosity factors of 5%, 10% and 20% decrease the yield stress by 26%, 36% and 53%, respectively. MD predicts that perfect hydroxide and oxide single crystal have respective strains at failure of 0.08 and 0.31 under tensile uniaxial strain loading, and that the corresponding yield stresses are respectively 1.6 and 11.1 GPa. These data indicate that the hydroxide is substantially more susceptible to mechanical failure than the oxide. Our results, coupled with literature findings that indicate hot and humid conditions favor formation of hydroxide and defective oxide coatings, indicate the potential for a complicated dependence of aluminum corrosion susceptibility and stress corrosion cracking on aging history.

36 MATERIALS SCIENCE↗

Dual Impacts of Space Heating Electrification and Climate Change Increase Uncertainties in Peak Load Behavior and Grid Capacity Requirements in Texas

Around 60% of households in Texas currently rely on electricity for space heating. As decarbonization efforts increase, non‐electrified households could adopt electric heat pumps, significantly increasing peak (highest) electricity demand in winter. Simultaneously, anthropogenic climate change is expected to increase temperatures, the potential for summer heat waves, and associated electricity demand for cooling. Uncertainty regarding the timing and magnitude of these concurrent changes raises questions about how they will jointly affect the seasonality of peak demand, firm capacity requirements, and grid reliability. This study investigates the net effects of residential space heating electrification and climate change on long‐term demand patterns and load shedding potential, using climate change projections, a predictive load model, and a direct current optimal power flow (DCOPF) model of the Texas grid. Results show that full electrification of residential space heating by replacing existing fossil fuel use with higher efficiency heat pumps could significantly improve reliability under hotter futures. Less efficient heat pumps may result in more severe winter peaking events and increased reliability risks. As heating electrification intensifies, system planners will need to balance the potential for greater resource adequacy risk caused by shifts in seasonal peaking behavior alongside the benefits (improved efficiency and reductions in emissions).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Rational design of high-performance low-loading oxygen reduction catalysts for alkaline fuel cells

The lack of mechanistic understanding and catalyst design principles for alkaline electrolytes, especially for the sluggish oxygen reduction reaction, has impeded the advancement of alkaline fuel cells. Here, in this study, we propose a modified volcano plot and apply this rationale to strategically design Pt nanosheets with PdH x nanosheets substrates. This catalyst exhibited high stability with a specific activity of 1.71 mA cm −2 at 0.95 V versus the reversible hydrogen electrode, surpassing the benchmark of Pt/C by 49-fold. Spectroscopic, electrochemical and electron microscopic characterizations revealed that such performance enhancement originated from tensile-strained Pt{111} facets, improving oxidative stability and suppressing carbon corrosion. In fuel cell testing, the catalyst enabled a peak power density of 1.67 W cm −2 with a loading of 10 µg PGM Cathode cm −2 . Further optimization delivered a peak power density of 21.7 W mg −1 PGM Cathode+Anode with a total specific catalyst cost US$\$$1.27 kW −1 , surpassing the US Department of Energy’s Pt group metal loading and cost targets. This study provides valuable insights into catalyst design for the alkaline oxygen reduction reaction.

36 MATERIALS SCIENCE↗

3D printing of architected sulfur cathodes with dual-site atomic catalysts for accelerated polysulfide kinetics and Li-ion transport in high areal-loading lithium–sulfur batteries

The practical deployment of lithium–sulfur batteries (LSBs) is hindered by fundamental limitations in conventional slurry-cast cathodes, including poor sulfur utilization, sluggish ion transport, and low areal capacity, particularly in thick electrodes required for high energy density. To address these challenges, we present direct ink writing (DIW) as an additive manufacturing strategy to fabricate advanced current-collector-free, 3D-printed sulfur cathodes (3DP S@CoNi-DSACs/NC) with hierarchically porous architectures that enhance lithium-ion diffusion, promote electrolyte penetration, and reduce interfacial resistance. The synergistic effects of Co/Ni dual-atom sites accelerate redox kinetics and mitigate polysulfide shuttling. As a result, the optimized 3DP cathode with a sulfur loading of 5.4 mg cm −2 demonstrated excellent rate capability, delivering a high reversible capacity of 1041.4 mAh g −1 at 1C with 85.5% capacity retention after 1000 cycles, significantly outperforming its cast counterpart. Remarkably, even at a higher sulfur loading of 8.1 mg cm −2 , the 3DP cathode maintains outstanding performance, achieving a discharge capacity of 1538.4 mAh g −1 and an areal capacity of 12.5 mAh cm −2 at 0.1C. This study not only demonstrates the functional integration of catalytically active materials into 3D printable sulfur cathode architectures but also offers a scalable and transformative platform for building high-performance LSBs beyond conventional electrode manufacturing methods.

3D electrode↗

Excessive charge, beam loading, and impedance collapse thresholds for a velvet emitter

Excess emission has been observed from velvet cathodes with total emission times >150 ns. In this diode experiment, we produce a sub-relativistic electron beam with the ability to consistently change γ from 1.2 to 1.5 and β = 0.5–0.75. Electron emission in this particular diode geometry requires electric fields >40 kV/cm. The current increases at steady rates >0.05 A/ns after the head of the pulse, indicating an expansion of the emission surface and reduction in the effective AK gap. Small transients of excess emission (or arcs) are consistently observed for current pulses exceeding 150 ns. The excess emission results in beam loaded levels ≥10 kV on the diode voltage. The effects described here are compounded as diode voltage is increased. The principal objective of these experiments is to quantify electric field emission thresholds, current ramps, excess emission delays, effective beam loading, and impedance collapse.

43 PARTICLE ACCELERATORS↗