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At least 1,063 records · Page 59

Atomically Dispersed Reduced Graphene Aerogel-Supported Iridium Catalyst with an Iridium Loading of 14.8 wt %

Atomically dispersed iridium complexes were anchored on a reduced graphene aerogel (rGA) by the reaction of Ir(CO) 2 (acac) [acac = acetonylacetonato] with oxygen-containing groups on the rGA. Characterization by X-ray absorption, infrared, and X-ray photoelectron spectroscopies and atomic resolution aberration-corrected scanning transmission electron microscopy demonstrates atomically dispersed iridium, at the remarkably high loading of 14.8 wt %. The rGA support offers sites for metal bonding comparable to those of metal oxides, but with the advantages of high density and a relatively high degree of uniformity, as indicated by the same turnover frequencies for catalytic hydrogenation of ethylene at low and high iridium loadings. We note the atomic dispersion at a high metal loading—and the high density of catalytic sites per unit of reactor volume, a key criterion for practical catalysts—set this catalyst apart from those reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High speed synchrotron x-ray phase contrast imaging of dynamic material response to split Hopkinson bar loading

The successful process of amalgamating both the time-resolved imaging capabilities present at the Advanced Photon Source beamline 32ID-B and the proficiency of high-rate loading offered by the split Hopkinson or Kolsky compression/tension bar apparatus is discussed and verification of system effectiveness is expressed via dynamic experiments on various material systems. Single particle sand interaction along with glass cracking during dynamic compression, and fiber-epoxy interfacial failure, ligament-bone debonding, and single-crystal silicon fragmentation due to dynamic tension, were imaged with 0.5 {mu}s temporal resolution and {mu}m-level spatial resolution. Synchrotron x-ray phase contrast imaging of said material systems being loaded with the Kolsky bar apparatus demonstratively depicts the effectiveness of the novel union between these two powerful techniques, thereby allowing for in situ analysis of the interior of the material system during high-rate loading for a variety of applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Using a cold radiometer to measure heat loads and survey heat leaks

We have developed an inexpensive cold radiometer for use in thermal/vacuum chambers to measure heat loads, characterize emissivity and specularity of surfaces and to survey areas to evaluate stray heat loads. We report here the results of two such tests for the James Webb Space Telescope to measure heat loads and effective emissivities of 2 major pieces of optical ground support equipment that will be used in upcoming thermal vacuum testing of the Telescope.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Damage mechanisms in PBT-GF30 under thermo-mechanical cyclic loading

The scope of this paper is the investigation of damage mechanisms at microscopic scale on a short glass fiber reinforced polybutylene terephthalate (PBT-GF30) under thermo-mechanical cyclic loading. In addition the principal mechanisms are verified through micro mechanical FE models. In order to investigate the fatigue behavior of the material both isothermal strain controlled fatigue (ISCF) tests at three different temperatures and thermo-mechanical fatigue (TMF) tests were conducted on plain and notched specimens, manufactured by injection molding. The goal of the work is to determine the damage mechanisms occurring under TMF conditions and to compare them with the mechanisms occurring under ISCF. For this reason fracture surfaces of TMF and ISCF samples loaded at different temperature levels were analyzed using scanning electron microscopy. Furthermore, specimens that failed under TMF were examined on microsections revealing insight into both crack initiation and crack propagation. The findings of this investigation give valuable information about the main damage mechanisms of PBT-GF30 under TMF loading and serve as basis for the development of a TMF life estimation methodology.

36 MATERIALS SCIENCE↗

The Rehbinder effect in iron during giga-cycle fatigue loading

The influence of the adsorptive strength reduction effect (the Rehbinder effect) on the fatigue life of pure iron under the giga-cycle loading regime was investigated. Specimens were loaded by an ultrasonic testing machine with a frequency of 20 kHz in air and in contact with eutectic alloy of gallium with tin and indium. A significant (by several orders of magnitude) worsening of the life-time of iron in contact with a molten metal as compared with tests in air was established. The liquid metal penetrates into the material to a depth of 200 μm to the center of a fatigue crack. The mechanism of the fatigue crack initiation in the giga-cycle regime of loading in contact with a surfactant is differing: the crack is formed on the surface of the specimen rather than within it as is the case for air. Based on the electron and optical microscopy data for the fracture surface, it can be concluded that exactly the change in the crack initiation mechanism reduces the fatigue life of iron in contact with a liquid metal because the initiated crack propagates regardless of the surfactant.

36 MATERIALS SCIENCE↗

Strength of concrete structures under dynamic loading

The use of elastic supports is one the efficient methods of decreasing the dynamic loading. The paper describes the influence of elastic supports on the stress-strain state of steel concrete structures exposed to one-time dynamic loading resulting in failure. Oblique bending beams on elastic supports and their elastic, elastoplastic, and elastoplastic consolidation behavior are considered in this paper. For numerical calculations the developed computer program is used based on the finite element method. Research findings prove high efficiency of elastic supports under dynamic loading conditions. The most effective behavior of elastic supports is demonstrated at the elastoplastic stage. A good agreement is observed between the theoretical and experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Simulation of the NuScale SMR and Investigation of the Effect of Load-Following on Component Lifetimes

The NuScale SMR has been modelled using the Virtual Environment for Reactor Applications (VERA) multiphysics environment and the results compared with the publicly reported data in the Design Certification Application (DCA). The results show an excellent agreement for the compared axial and radial power distributions, temperature coefficients of reactivity, boron and control rod worths, and fast neutron flux. This NuScale model is then used to investigate the effect of different operational modes on reactor components to determine how flexible load-following operation may affect control rod and reactor pressure vessel (RPV) lifetimes. The control rod degradation is confirmed to primarily affect the silver-indium-cadmium (AIC) rod tip. The degradation rate is observed to follow a non-linear function of core power level where the increase in degradation decreases with insertion depth. For the variation in core power levels expected with current load-following schemes, the total control rod degradation is found to be mild, at 5-10% of usable life per cycle for a reactor operating at <80% power. Nonetheless, this enables load following strategies to be confirmed and/or modified to ensure that control rods do not need to be replaced during the 60+ year life of the reactor. The RPV degradation was found to be almost directly proportional to the core power level and was not overly sensitive to flux shape perturbations. Future work is planned using these damage functions to optimize operation over multiple NuScale SMR units and develop strategies for prognostics and health management.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Load Forecasting Based Distribution System Network Reconfiguration -- A Distributed Data-Driven Approach

In this paper, a short-term load forecasting approach based network reconfiguration is proposed in a parallel manner. Specifically, a support vector regression (SVR) based short-term load forecasting approach is designed to provide an accurate load prediction and benefit the network reconfiguration. Because of the nonconvexity of the three-phase balanced optimal power flow, a second-order cone program (SOCP) based approach is used to relax the optimal power flow problem. Then, the alternating direction method of multipliers (ADMM) is used to compute the optimal power flow in distributed manner. Considering the limited number of the switches and the increasing computation capability, the proposed network reconfiguration is solved in a parallel way. The numerical results demonstrate the feasible and effectiveness of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An 802pW 93% Peak Efficiency Buck Converter with 5.5×10 6 Dynamic Range Featuring Fast DVFS and Asynchronous Load-Transient Control

Here this paper presents a buck converter with sub-nW quiescent power, high efficiency, and a wide dynamic range for ultra-low-power (ULP) IoT SoCs. To optimize the SoC power consumption, the buck converter supports fast dynamic voltage and frequency scaling (DVFS) and enables fast load-transient response (FLTR) through asynchronous control. In addition, the buck converter is fully self-contained with all features integrated on chip including a proposed adaptive deadtime controller. Fabricated in 65nm CMOS, measurement results show the buck converter has an 802pW quiescent power at 1.5V input voltage and a 93% peak efficiency. The measured dynamic range is from 0.5nW to 2.75mW, which is over 6 orders of magnitude. The measured voltage droop is 54mV for a 45nA-to-1mA load current step thanks to the asynchronous load-transient detector. The buck converter achieves the highest efficiency and widest dynamic range among all the state-of-the-art sub-nW switching voltage regulators, which makes it well suited for power management in ULP SoCs.

42 ENGINEERING↗

Peak Load Management in Distribution Systems Using Legacy Utility Equipment and Distributed Energy Resources

The ability to perform peak load management in distribution systems has several benefits for utilities, including reduced demand charges and improved reliability, efficiency, and utilization of the network infrastructure. This paper demonstrates the coordinated operation of an advanced distribution management system (ADMS) and a distributed energy resource management system (DERMS) to achieve peak load management using a realistic laboratory test bed. A commercial ADMS reduces the peak demand by reducing system voltages using a dynamic voltage regulation (DVR) application. A prototype DERMS-based on real-time optimal power flow-controls distributed battery energy storage systems to further reduce the feeder power. Results from the experiments conducted using a model of a real distribution feeder show that the coordinated operation of the ADMS and DERMS is effective in accomplishing peak load management.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transfer Learning Trained LSTM Models for Household Load Profile Forecasting

Grid edge renewable energy resources, such as rooftop solar photovoltaics, closely interact with consumer load profiles. Therefore, forecasting future electricity demand, ideally at the individual household level, is indispensable. In this paper, we present a transfer learning enhanced household load profile forecasting method. First, we tune a long short-term memory forecasting model to perform day-ahead prediction of household electricity load profiles. Then we improve these individualized models using transfer learning, and we use k-means clustering to create optimal source data sets. We find average improvements of 4.38% (largest improvement of 10.71%) when the entire data set was used to train the source model and 2.45% (largest improvement of 11.57%) in the mean absolute error when households were first clustered and used to train separate source models for each cluster. We find that transfer learning with clustered data can effectively boost the forecasting performance of the LSTM models. We use realistic household power measurements for 148 real residential households in Austin, Texas.

deep learning↗

NO-LESS: Near optimal curtailment strategy selection for net load balancing in micro grids

The integration of renewable energy sources such as solar PVs into micro grids has increased in recent years. However, the intermittent and unpredictable nature of renewable energy generation makes supply uncertain, in turn requiring continuous net load balancing to ensure grid stability. One technique to achieve net load balancing is curtailment, however, selection of the optimal set of curtailment strategies to achieve a targeted curtailment is NP-hard. State-of-the-art curtailment selection techniques approach this problem by either developing computationally expensive optimal curtailment strategies or reduce accuracy to generate sub-optimal solutions quickly. In this work, we develop NO-LESS: a Near OptimaL CurtailmEnt Strategy Selection algorithm. NO-LESS is a novel Fully Polynomial Time Approximation Scheme (FPTAS) which determines bounded (near optimal) curtailment strategies in a small amount of time while simultaneously satisfying practical constraints on strategy switching overhead and curtailment fairness. We perform both theoretical analysis and practical evaluation to show that NO-LESS is a scalable solution for performing net load balancing through curtailment strategy selection in Micro Grids.

14 SOLAR ENERGY↗

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings

Smart buildings with net-load metering and control capabilities can provide valuable flexibility to grid operators. This article develops a novel approach for high-frequency, multiclass nonintrusive load monitoring (NILM) that enables effective net-load monitoring capabilities with minimal additional equipment and cost. Relative to existing NILM work, the proposed solution operates at a faster timescale, providing accurate multiclass state predictions for each 60-Hz ac cycle without relying on event-detection techniques. The approach is validated using a test bed with residential appliances and shown to have high accuracy, good generalization properties, and sufficient response time to support building grid-interactive control at fast timescales relevant to the provision of grid frequency support services.

27 ARPA - Advanced Research Projects Agency-Energy↗

A Hydrogen Load Modeling Method for Integrated Hydrogen Energy System Planning

The integrated hydrogen energy system incorporates hydrogen energy into the power grid, which has been recognized as a promising option for reaching a 100% renewable electricity supply. It can make a profit because the hydrogen produced can be sold as fuel or used to generate electricity for grid services. In this paper, we develop a planning model for the integrated hydrogen energy system that considers the uncertainty of the load demand, the renewable energy generation, and the market prices. To calculate the hydrogen load, we simulate the refueling operations at a hydrogen fueling station over the course of one day and generate representative load profiles with K-means clustering. Moreover, the long-term profitability of the integrated system under both current and future conditions is validated in 10-year planning results.

grid service↗

A Data-Driven Framework for Residential Electric Vehicle Charging Load Profile Generation

Residential electric vehicle charging load profile is indispensable to achieve reliable control strategies for mitigating negative effects on power distribution system due to emerging electrified transportation. This paper introduces a data-driven framework of charging load profile generation for residential plug-in electric vehicles. Real world historical residential charging behavior data is utilized to construct empirical charging decision making model by using machine learning algorithm. A multiple channels method with kernel density estimation is proposed to construct probability density functions for estimating charging duration based on parking duration. A generation algorithm considering parking time and travel demand dependency is introduced to generate residential charging behaviors. This framework is extensible to generate various charging load profiles and simulate varied residential charging scenarios under different number of households and charging rates. This will be crucial for designing and validating residential charging control strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Frequency Restoration of Grid-Forming Inverters in Pulse Load and Plug-in Events

This article presents a restoration technique using grid-forming inverters in an islanded microgrid during pulse load and plug-in events. In a microgrid powered by droop-controlled inverters, frequency is the variable that is accessible to all inverters for adjusting their power contributions. The problem is that the microgrid frequency deviates from its nominal value after a load change. The presented method enables the inverters to restore the frequency to the nominal value and regulate their bus voltage amplitudes. The frequency and voltage restorations are performed without communication while achieving the desired power-sharing between grid-forming inverters. The restoration is activated after detecting any active or reactive power changes. In this article, the dynamic model of an inverter equipped with enabled restoration paths is developed to verify the stability of the inverter controller under various conditions. The frequency and voltage restorations are examined during pulse load and plug-in events. Furthermore, this study is performed using a laboratory-scale islanded microgrid powered by two 208 V, 60 Hz, 5 kVA inverters.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Effects of Photovoltaic Module Materials and Design on Module Deformation Under Load

Quasi-static structural finite-element models of an aluminum-framed crystalline silicon photovoltaic module and a glass-glass thin-film module were constructed and validated against experimental measurements of deflection under uniform pressure loading. Specific practices in the computational representation of module assembly were identified as influential to matching experimental deflection observations. Additionally, parametric analyses using Latin hypercube sampling were performed to propagate input uncertainties related to module materials, dimensions, and tolerances into uncertainties in simulated deflection. Sensitivity analyses were performed on the uncertainty quantification datasets using linear correlation coefficients and variance-based sensitivity indices to elucidate key parameters influencing module deformation. Results identified edge tape and adhesive material properties as being strongly correlated to module deflection, suggesting that optimization of these materials could yield module stiffness gains at par with the conventionally structural parameters, such as glass thickness. This exercise verifies the applicability of finite-element models for accurately predicting mechanical behavior of solar modules and demonstrates a workflow for model-based parametric uncertainty quantification and sensitivity analysis. Finally, applications of this capability include the assessment of field environment loads, derivation of representative loading conditions for reduced-scale testing, and module design optimization, among others.

42 ENGINEERING↗

Solar Cell Metallization Wear is Sensitive to Loading Frequency

Here, we performed cyclic loading of photovoltaic laminates with precracked silicon cells to explore if and how loading frequency and contact pressure influence the ensuing gridline wear-out process. A measurement of parallel resistance across cracked gridlines on a laminated cell coupon was used as the metric for gridline electrical contact degradation. A statistical analysis of variance (ANOVA) analysis of the experimental results discerned that loading frequency is a more significant factor than contact pressure for gridline degradation.

14 SOLAR ENERGY↗