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At least 127 records · Page 7

Optimization-Inspired Pin-Fin Array for Supercritical Carbon Dioxide Recuperator

Additively manufactured heat exchangers are one possible route to cost-effective sCO 2 power cycles. In this paper, experimental results are obtained for two helical pin fin tubes that were designed following parametric optimization of the fin array. Neither the numerical optimization nor the experimental testing have been previously reported in the literature. The two tube designs were, (1) the optimization inspired design, and (2) the optimization-inspired design with a fin diameter increased by a factor of 2. To characterize the print, the designs were scanned using X-ray computed tomography to measure feature sizes and heat transfer area. The optimization was conducted in a commercial, computational fluid dynamics code. The code solved the Reynolds Averaged Navier-Stokes (RANS) and energy equations with turbulence closure provided by the shear stress transport (SST) k-ω model. In the experiments, the Nusselt number augmentation was measured using the Wilson plot technique and the friction factor was determined with mass flow and pressure drop measurements. The experimental testing indicated that the optimization-inspired design had a friction factor that was four times less than the baseline tube design at equal Nusselt number. Additionally, the optimization-inspired design had a 14% improvement in Nusselt number, at equal friction factor, relative to the best performing computational fluid dynamics (CFD) trial points. Tube design (2), with the larger diameter pin fins, had similar performance, within experimental error, as the tube with the smaller diameter pin fins (1). Both tubes achieved overall fin array efficiencies near 1. A performance factor, V/V 0 , equal to the volume of the enhanced heat exchanger divided by the volume of the baseline (no-fins) heat exchanger, is recommended to quantify internal cooling performance. In conclusion, the experimental shell and tube heat exchanger, using the additively manufactured tube, is competitive with printed circuit heat exchangers in its pressure drop class and could be further improved by optimizing a shell-and-tube heat exchanger utilizing this heat transfer enhancement feature.

42 ENGINEERING↗

An Operations and Maintenance Roadmap for U.S. Offshore Wind: Enabling a Cost-Effective and Sustainable U.S. Offshore Wind Energy Industry Through Innovative Operations and Maintenance

The United States is currently targeting 30GW of offshore wind to be installed by 2030, and 150GW by 2050. Even considering future turbine sizes, this represents thousands of new turbines installed in a diverse set of environments, each with their unique design, installation, and maintenance challenges. While much can be learned from European and Asian experience with offshore wind over the past two decades, it is important to understand the unique circumstances of the U.S. This document explores operations and maintenance of offshore wind energy, specific to the U.S. and attempts to lay out a roadmap for needed activities to ensure reliability of future installations. The roadmap was informed through dozens of interviews with a wide cross-section of the industry, including representatives from OEMs, owner/operators, service companies, certification agencies, service providers, and researchers. The roadmap first describes the problem by component - blades, drivetrain and nacelle, structures and foundations, and electrical systems - through a look at current practices and opportunities for improvement in the areas of Failure Mode Analysis and Mitigation; Monitoring, Sensing, and Inspection; and Maintenance Execution. Crosscutting areas of Digitalization, Robotics and Automation, Prognostics and Health Management and O&M Optimization, Experimentation and Demonstration, Standardization, and Design Optimization Considering Reliability and O&M are then discussed. Finally, the roadmap summarizes all of these topics with recommendations for short (1-3 years), medium (4-7 years), and long term (8-12 years) activities, with a description of needed public and private sector contributions.

17 WIND ENERGY↗

De novo design of high-affinity binders of bioactive helical peptides

Many peptide hormones form an α-helix on binding their receptors, and sensitive methods for their detection could contribute to better clinical management of disease. De novo protein design can now generate binders with high affinity and specificity to structured proteins. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.

59 BASIC BIOLOGICAL SCIENCES↗

Thermomechanical analysis and modeling of a high-temperature light trapping planar cavity solar receiver

The development of durable particle-based high-temperature solar receivers is critical for advancing concentrating solar-thermal (CST) technologies to enable high-efficiency power generation and industrial process heat. Here, this study presents a computational framework to evaluate the thermomechanical performance of a proposed enclosed light-trapping planar cavity receiver designed for particle-based thermal energy systems. The receiver incorporates absorptive cavities and fluidized particle-bed channels to enhance heat capture and reduce thermal losses. Finite element analysis (FEA) is employed to assess stress, strain, and creep-fatigue behavior under concentrated solar flux using realistic thermal boundary conditions derived from coupled system models and experimental assembly parameters. The analysis investigates the influence of particle-to-wall heat transfer coefficients (HTC) ranging from 800 to 1800 W/m 2 .K on the thermomechanical response of six candidate high-temperature alloys: Alloy 740H, Alloy 282, Alloy 617, 316H, Alloy 230, and 800H. Results show that increasing HTC reduces thermal gradients, leading to lower stresses and strains and extended minimum predicted creep life. While all materials satisfy fatigue life requirements under the investigated conditions, significant differences in creep resistance are observed. Alloy 740H consistently exhibits the longest minimum predicted creep life and the most favorable durability margins, followed by Alloy 282, with the remaining materials showing reduced creep resistance under identical loading. The reported creep lives are conservative lower-bound estimates intended for comparative material evaluation. This framework highlights the critical roles of material selection and geometry optimization in improving mechanical durability and reliability of solar-thermal receivers, forming a foundation for future experimental validation and design optimization.

14 SOLAR ENERGY↗

Combining the synergistic control capabilities of modeling and experiments: Illustration of finding a minimum-time quantum objective

A common way to manipulate a quantum system, for example spins or artificial atoms, is to use properly tailored control pulses. In order to accomplish quantum information tasks before coherence is lost, it is crucial to implement the control in the shortest possible time. Here we report the near time-optimal preparation of a Bell state with fidelity higher than 99% in an NMR experiment, which is feasible by combining the synergistic capabilities of modeling and experiments operating in tandem. In this work, the pulses preparing the Bell state are found by experiments that are recursively assisted with a gradient-based optimization algorithm working with a model. Thus, we exploit the interplay between model-based numerical optimal design and experimental-based learning control. Utilizing the balanced synergism between the dual approaches, as dictated by the case specific capabilities of each approach, should have broad applications for accelerating the search for optimal quantum controls.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sustainable Li-ion anode material from Fe-catalyzed graphitization of paper waste

We report a novel method for the conversion of paper towel waste to biographite anode material is developed and optimized for use in Li-ion batteries. The surge in demand for Li-ion battery anode materials coupled with the unsustainable and inefficient methods of producing battery-grade graphite necessitate alternative carbon feedstocks and graphitization technologies. Paper waste (PW) is identified as a suitable carbon feedstock for iron-catalyzed graphitization due to its sustainability, low cost, low ash content, and ample supply for the intended end use. A Box Behnken experimental design for statistical optimization is pursued for untreated and pre-carbonized PW with factors of temperature (1100-1300 °C), hold time (1-5 h), and iron catalyst loading (0.5-1.5x fixed carbon content) with biographite crystal size as the primary response variable. Temperature and iron catalyst loading are found to be significant factors, whereas hold time is found to be insignificant. Reversible capacities of the biographite anodes are found to be 340-355 mAh g-1 with 99% capacity retention over 100 cycles, indicating good electrochemical performance relative to commercial graphite anodes. The initial Coulombic efficiency of untreated and pre-carbonized biographites, however, are 77% and 75%, respectively, suggesting parasitic reactions including electrolyte decomposition.

25 ENERGY STORAGE↗

High-efficiency solar thermophotovoltaic system using a nanostructure-based selective emitter

Herein, we present the design, fabrication, optimization, and experimental results of a high-efficiency planar solar thermophotovoltaic (STPV) system utilizing a micro-textured absorber and a nanostructure multilayer metal-dielectric coated selective emitter fabricated on a tungsten (W) substrate. Light absorptance of more than 90% was achieved at visible and near-infrared wavelengths using the microtextured absorbing surface. The nanostructure selective emitter consists of two thin-film optical coatings of silicon nitride (Si3N4) and a layer of W in between to increase the surface emissivity in spectral regimes matching the quantum efficiency of the thermophotovoltaic (TPV) cells. Gallium antimonide (GaSb)-based TPV cells are used in our STPV design. The experiment was conducted at different operating temperatures using a high-power continuous wave laser diode stack as a simulated source of concentrated incident radiation. Our experimental setup measured a maximum electrical output power density of 1.71 W/cm 2 at 1676 K STPV temperature, and the overall power conversion efficiency of 8.4% after normalizing the output power density to the emitter area. This is the highest STPV system efficiency reported so far for any experimental STPV device. The incident optical laser power on the absorber side was 131 W. This is equivalent to a solar concentration factor of ~2100, which is within the practical limit and readily achievable with Fresnel lens setup.

14 SOLAR ENERGY↗

Dissimilar Material Joining via Interlocking Metasurfaces

Background The integration of dissimilar materials poses a significant challenge in engineering, necessitating innovative solutions for robust and reliable joining. Interlocking metasurfaces (ILMs) are a new joining technology comprising arrays of autogenous features patterned across two surfaces that interlock to form robust structural joints. Objective Here, this study elucidates the factors influencing the tensile performance of ILM joints formed between dissimilar materials. Methods We employed parametric optimization to identify optimal unit cell geometries for maximal yield strength based on the hypothesis that the elastic tensile properties of the materials are the primary determinants of tensile performance. Experimental validation was performed by mechanically testing the theorized optimal ILM geometry and a range of ILM geometries to capture the overall behavior trends of joints between two additively manufactured polymers, VeroPureWhite (VW) and RGDA8430-DM (8430). Results Experimental validation of optimized designs revealed that additional factors, e.g. flexural strength and localized plasticity, also strongly influenced the tensile performance of T-slot ILMs joining dissimilar materials. The proposed optimal design remained the best performer. Conclusions This study demonstrates the viability of ILMs as a joining method for dissimilar materials. ILMs can join dissimilar materials with no loss in joint yield strength compared to joints composed solely of the weaker of the two constitutive materials. ILMs demonstrated their potential as a versatile and effective joining technology in diverse engineering applications.

Elbrecht, Benjamin James [Sandia National Laborato↗

Predicting the onset of metal-insulator transitions in transition metal oxides-A first step in designing neuromorphic devices.

Several transition metal oxides, including La1-xSrxCoO3, are promising materials to realize resistive switching devices for neuromorphic applications, as they can undergo a metal-to-insulator transition (MIT) upon small perturbations to their electronic structure. Here, we focus on the MIT induced by varying the oxygen vacancy concentration, and we propose a model to predict the required electrical bias, based on three fundamental quantities: the vacancy formation energy, the permanent polarization in the material, and its dielectric constant. We obtain these quantities using first-principles electronic structure calculations, and we discuss strategies to minimize the electrical bias which may be adopted experimentally to design and optimize neuromorphic devices.

Zhang, Shenli↗

End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml

In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx radiofrequency system-on-chip field-programmable gate arrays (FPGAs), we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes the hls4ml package and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python application programming interfaces. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA lookup table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.

42 ENGINEERING↗

Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks [Slides]

This presentation discusses Nuclear Criticality Safety (NCS) and how designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear experiments. The presentation poses the question of how this analysis can be performed and states that the answer lies in matching new nuclear experiments with existing benchmark experiments using similarity metrics. By increasing the criticality safety of the application in this work, higher mass limits could be used in PF-4 operations. Additionally, the presentation discusses MCNP6.2®, Whisper-1.1, the software that can be used in this analysis. Also discussed is the fact that International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks rarely match new nuclear applications and that there are significant differences in given set of materials and/or geometry. If there are no benchmarks that match the application, the presentation discusses the possibility of creating new benchmarks. In conclusion, this work presents a Gaussian process (GP) optimization scheme that was used to generate new benchmarks with the highest sensitivity-based similarity metrics to user-defined nuclear applications. The Gaussian process optimization successfully designed 3 new experimental benchmarks that were highly correlated to the application of interest and had k eff values near critical. Optimization over c k,i-r has shown that investigating specific isotope reactions for different applications is crucial to designing benchmark experiments. Partial contribution from Pu dominates c k similarity metric. Future work includes testing new stand-alone similarity metrics or new combinations of similarity metrics as the design criterion of this optimization – design criterion is application dependent.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Integrated Heat Exchanger-Phase Change Material Thermal Energy Storage System

The purpose of this study is to experimentally investigate the thermal performance of an innovative thermal energy storage (TES) system that combines the advantages of the phase-change material (PCM)/graphite foam latent heat TES medium developed at Argonne National Laboratory (Argonne) and the internally supported plate-fin (ISPE) cell architecture heat transfer fluid (HTF) flow channels developed at Brayton Energy (Brayton). Several essential tasks were accomplished: (1) Thermal property characterization. Thermal properties of the graphite foam were characterized, providing necessary data for experimental result analysis and numerical simulation. (2) Design and optimization of lab-scale test module. Based on Brayton’s full-scale heat exchanger (HX)-TES system, the experimental test module was designed, optimized, and fabricated. (3) Thermal performance testing and data analysis. Five cycle tests were successfully conducted—including one with approximately 3.5 psig of pressure applied to the diaphragms—to investigate the thermal performance of the experimental test module for charging and discharging. Temperature profiles were generated for each charging test and discharging test as a function of time. The temperature profiles clearly show three TES stages: sensible heat (temperature increase), latent heat (melting), and sensible heat (temperature increase) for the charging process. Similarly, the temperature profiles clearly show three thermal energy release stages: sensible heat (temperature decrease), latent heat (solidification), and sensible heat (temperature decrease). Melting and solidification of the PCM generally occurred in relatively narrow temperature ranges, indicated by the flattened temperature regions in the temperature profiles. These phase changes ranged approximately 3°C for melting and 3.5°C for solidification. The charging and discharging temperature profiles were similar for similar experimental parameter tests whether or not pressure was applied to the diaphragm to eliminate the gap between the HX surface and the TES subsystem. This indicates that the effect of a small gap between the HX surface and the TES subsystem is insignificant for charging and discharging. (4) Comparison of experimental data and simulation results. We compared the experimental data to the numerical simulation results. Numerical simulations were conducted by using the ANSYS FLUENT 2019 R3 commercial computational fluid dynamics software. The predicted phase-change times agreed reasonably well with those from the experimental data. In most cases, the estimated time differences between the relative phase changes were within 16%. The predicted start and end times for the charging process agreed well with those from the experimental data. However, the simulation results showed earlier start and end times than the experimental data for the discharging process. Overall, the experimental data and its comparison with the simulation predictions verified the technical viability of the integrated ISPF HX-PCM/graphite foam latent-heat TES system.

25 ENERGY STORAGE↗

Direction-optimizing Label Propagation Framework for Structure Detection in Graphs: Design, Implementation, and Experimental Analysis

Label Propagation is not only a well-known machine learning algorithm for classification but also an effective method for discovering communities and connected components in networks. We propose a new Direction-optimizing Label Propagation Algorithm (DOLPA) framework that enhances the performance of the standard Label Propagation Algorithm (LPA), increases its scalability, and extends its versatility and application scope. As a central feature, the DOLPA framework relies on the use of frontiers and alternates between label push and label pull operations to attain high performance. It is formulated in such a way that the same basic algorithm can be used for finding communities or connected components in graphs by only changing the objective function used. Additionally, DOLPA has parameters for tuning the processing order of vertices in a graph to reduce the number of edges visited and improve the quality of solution obtained. We present the design and implementation of the enhanced algorithm as well as our shared-memory parallelization of it using OpenMP. We also present an extensive experimental evaluation of our implementations using the LFR benchmark and real-world networks drawn from various domains. Compared with an implementation of LPA for community detection available in a widely used network analysis software, we achieve at most five times the F-Score while maintaining similar runtime for graphs with overlapping communities. We also compare DOLPA against an implementation of the Louvain method for community detection using the same LFR-graphs and show that DOLPA achieves about three times the F-Score at just 10% of the runtime. For connected component decomposition, our algorithm achieves orders of magnitude speedups over the basic LP-based algorithm on large-diameter graphs, up to 13.2× speedup over the Shiloach-Vishkin algorithm, and up to 1.6× speedup over Afforest on an Intel Xeon processor using 40 threads.

97 MATHEMATICS AND COMPUTING↗

Response Surface Methodology As a New Approach for Finding Optimal MALDI Matrix Spraying Parameters for Mass Spectrometry Imaging

Automated spraying devices have become ubiquitous in laboratories employing matrixassisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), in part because they permit control of a number of matrix application parameters that can easily be reproduced for intra- and interlaboratory studies. Determining the optimal parameters for MALDI matrix application, such as temperature, flow rate, spraying velocity, number of spraying cycles, and solvent composition for matrix application, is critical for obtaining high-quality MALDI-MSI data. However, there are no established approaches for optimizing these multiple parameters simultaneously. Instead optimization is performed iteratively (i.e., one parameter at a time), which is time consuming and can lead to overall non-optimal settings. In this report, we demonstrate the use a novel experimental design and the response surface methodology to optimize five parameters of MALDI matrix application using a robotic sprayer. Thirtytwo combinations of MALDI matrix spraying conditions were tested, which allowed us to elucidate relationships between each of the application parameters as determined by MALDI-MS (specifically, using a 15 Tesla Fourier transform ion cyclotron resonance mass spectrometer). As such, we were able to determine the optimal automated spraying parameters that minimized signal de-localization and enabled high MALDI sensitivity. We envision this optimization strategy can be utilized for other MALDI-MSI applications, tissue types, and matrix application approaches.

60 APPLIED LIFE SCIENCES↗

Potential benefits and optimization of cool-coated office buildings: A case study in Chongqing, China

Increasing envelope facet albedos considerably reduces solar heat gain, thus yielding building cooling energy savings. Few studies have explored the potential benefits of utilizing cool coatings on building envelopes (“cool-coated buildings”) based on life-cycle cost analysis. A holistic approach integrating the field testing, building energy simulation, and a 20-year life-cycle-based optimization was developed to explore cool-coated building performance and the maximum net savings of optimal building envelope retrofit and design. Experimental results showed that applying cool coatings to a west wall of an office building in Chongqing, China reduced its exterior surface temperature by up to 9.3 °C in summer. Additionally, simulation results showed that in Chongqing, making the roof and walls cool could reduce annual HVAC electricity use by up to 11.9% in old buildings (with poorly insulated envelopes) and up to 5.9% in new buildings. Retrofitting old buildings with a cool roof provided the net savings per modified area with present values up to 42.8 CNY/m2; retrofitting a new building with a cool roof or cool walls was not cost-effective. Optimizing both envelope insulation and envelope albedo can achieve 5.6 times the net savings of optimizing the insulation only, and 1.6 times that of optimizing albedo only.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Utilization of the CW magnetrons as coherent RF sources for superconducting RF accelerators

CW magnetrons designed and optimized for industrial heaters, driven by an injection-locking signal, were suggested to power Superconducting RF (SRF) cavities. However, the CW magnetrons, which are regenerative generators, are intended to operate in self-excitation mode, so, for reliable starting they use a large regenerative gain, causing a large regenerative instability in operation. Thus, power supply ripple, even shot noise, etc., lead to multiple sidebands forming a quasi-continuous noise spectrum at the carrier frequency. Therefore, in the traditionally used mode of operation and control, such magnetrons are inapplicable for powering high Q-factor SRF cavities. A new approach to operation and control of CW magnetrons considering non-stationary processes during start-up and operation makes it possible to find a mode of almost coherent RF generation of tubes with a significant reduction in regenerative instability and noise and increased efficiency. In our work is presented substantiation for the newly developed mode with an analysis of the new approach based on experimental results. •In this article, for the first time, non-stationary, regenerative processes are considered during the start-up and operation of CW magnetrons for powering high-Q superconducting RF cavities.•An analytical study, confirmed by experiments, showed that the traditionally used modes of starting and operating CW magnetrons are not suitable for powering high-Q superconducting RF cavities.•In fact, to make CW magnetrons suitable for such cavities, the physics of starting and operating CW magnetrons must be changed. This has been demonstrated in our work.•In developing the Stimulated Coherent Generation Mode [NIM A 980 (2020) 164366], we have shown the suitability of this mode for starting and operating CW magnetrons for high-Q superconducting RF cavities.•Analytical analysis, verified experimentally, substantiates in our article the suitability of the “Mode of stimulated coherent generation” of CW magnetrons for powering high-Q superconducting cavities in pulsed and continuous modes.

43 PARTICLE ACCELERATORS↗