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At least 793 records · Page 44

Engineering Company Recognized for Advanced Use of Lighting Sensors and Controls - Case Study: IMEG Corp, IL

This case study describes the implementation of several emerging lighting techniques at the new Chicago offices of IMEG Corp, an engineering and design consulting firm. IMEG collaborated with Pacific Northwest National Lab as part of a study to better understand the physiological and psychological impacts of advanced lighting strategies on occupant comfort, well-being, and energy savings. The project was recognized as part of DOE's Integrated Lighting Campaign.

integrated lighting, lighting, controls, tunable, ↗

Prediction of non-intuitive metabolic targets with bayesian metabolic control analysis to improve 3-hydroxypropionic acid production in Aspergillus niger

Development of efficient bioconversion processes is limited by the ability to predictably improve metabolic flux. Here we deployed Bayesian Metabolic Control Analysis as a platform to integrate multi-omics data with metabolic modeling and evaluated its ability to predict genetic interventions that improve metabolic flux. Global Metabolomics and proteomics data was collected from 17 Aspergillus niger strains engineered to produce the platform biochemical 3-hydroxypropionic acid from which seven actional genetic interventions were predicted from significant flux control coefficients. Of the suggested genetic interventions, two were present within the intuitively designed strains used for training (malonic semialdehyde dehydrogenase and pyruvate carboxylase) while five predicted targets were present within non-intuitive areas of the metabolic network including 5-formyltetrahydrofolate deformylase and four mitochondrial enzymes, alcohol dehydrogenase, succinyl-CoA ligase, aspartate aminotransferase, and malate dehydrogenase. Six of the targets were validated in the highest performing 3-HP strain used for multi-omics data generation which contained a prior disruption of the highest scoring target malonic semialdehyde dehydrogenase. Predicted directional perturbation of five of the six tested targets significantly improved titer and rate of 3-HP production and two significantly improved yield. The greatest improvements were observed following disruption of the non-intuitive target succinyl-CoA ligase which increased titer by 39% and yield by 29% (to 20.4 g/L 3-HP and 0.31 g 3-HP/g glucose) over the strains used for training. This study demonstrates the utility of Bayesian Metabolic Control Analysis and highlights the ability to predict meaningful genetic targets in unexpected areas of metabolism to improve engineered strains for bioconversion.

3-hydroxypropionic acid↗

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

CRADA Final Report: Open Microgrid Platform

Current microgrid control technology is mostly proprietary, expensive, and inflexible. An open-source, vendor-neutral, publish-subscribe controller will significantly lower the barrier to entry for new technologies and market entrants: inverter, battery, and load control manufacturers; cloud and services providers; and energy aggregators. An OpenFMB controller can significantly reduce the acquisition, integration, and ongoing operating and maintenance costs and increase revenue opportunities for energy producers and consumers. It allows distributed energy resource (DER) owners to replace individual DER components as richer-function, lower-cost devices become available or to incorporate new forecast and optimization algorithms as they are developed. A standard, secure, full-function DER field controller will also provide a low-cost means for grid operators to effectively manage the variability and uncertainty of solar photovoltaics (PV). Under the terms of this CRADA, ORNL has worked with Open Energy Solutions (OES) to advance the transition of ORNL’s existing open-source microgrid controller into a platform geared toward mainstream implementation. Using a more prevalent and memory-safe programming language, Rust, OES has converted ORNL’s current generation on-grid optimization into an application more suitable for industry use. The results of the ported optimization were analyzed by inputting the same arguments in both the current-generation and next-generation optimizers and verifying that the results were equivalent.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery

Future scientific discoveries will rely on flexible ecosystems that incorporate modern scientific instruments, high performance computing resources, parallel distributed data storage, and performant networks across multiple, independent facilities. In addition to connecting physical resources, such an ecosystem presents many challenges in logistics and accessibility, especially in orchestrating computations and experiments that span across leadership computing systems and experimental instruments. Past efforts have typically been application-specific or limited to interfaces for computing resources. This paper proposes a general framework for integrating computation resources and instrument operations, addressing challenges in code development/execution, data staging and collection, software stack, control mechanisms, resource authorization and governance, and hardware integration. We also describe a demonstration use case wherein a Bayesian optimization algorithm running on an edge computing resource guides a scanning probe microscope to autonomously and intelligently characterize a material sample. This science edge ecosystem framework will provide a blueprint for federating multi-institutional, disparate resources and orchestrating scientific workflows across them to enable next-generation discoveries.

Somnath, Suhas↗

Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI-XFC)

Increasing vehicle electrification will require extensive use of extreme fast charging (XFC), especially for larger vehicles. Uncoordinated XFC can create grid challenges, particularly at the distribution level. Two strategies can support widespread XFC: gold-plate the grid (i.e., upgrade all systems to enable worst-case, fully coincident loads) or use integrated planning to codesign a smart system based on advanced controls that leverage load flexibility and distributed energy resources. With the right design and control, XFC can simultaneously support both mobility and grid operations. Fully realizing the potential of XFC, however, will require unprecedented coordination among the charging infrastructure, grid, and vehicles. GEMINI-XFC combines high-fidelity grid and transport modeling at an unprecedented level of resolution and codesigns a smart system based on advanced controls that leverage load flexibility and distributed energy resources to optimize the integration of extreme fast charging (XFC) across a full regional scale with individual customer resolution.

ADVANCED PROPULSION SYSTEMS↗

Hardware-Based Demonstration of Temperature Control Functions for Reactor Systems

Establishing autonomy in reactor control systems has become essential for the expansion of nuclear technologies. Thermal regulation in particular remains crucial for maintaining stable operation and ensuring the integrity of fuel. To alleviate public skepticism of the safety of nuclear reactors, demonstrating control over this key factor is pivotal. Utilizing electric heat pads to simulate the heat released in a reactor core, thermocouples for temperature monitoring, and an Arduino micro programmable logic controller (PLC) for control, a hardware-based demonstration of a reactor heating system validates the efficacy of reactor control over this key parameter. To improve precision, a proportional-integral-derivative (PID) algorithm was implemented in the heating control loop to ensure meticulous control of reactor functions. In addition, the integration of this physical system with a digital simulator tool such as RELAP5-3D establishes a foundation for a comprehensive testing environment. This allows for a refinement of temperature control under various simulated reactor conditions, bringing another layer of reliability to the operation of the system. By facilitating a physical demonstration of reactor thermal management and control strategies, this project provides a foundation for expanded testing and educational outreach. Ultimately, this system advances the broader goal of demonstrating the safety and viability of autonomous reactor operations, contributing to public trust and future reactor deployment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Quantum Computing in Next-Generation Transportation Optimization

We explore how quantum computing (QC) can advance transportation optimization, with a focus on two high-impact areas: traffic signal control and vehicle electrification with grid integration. As transportation systems grow in complexity, classical optimization methods increasingly struggle to deliver scalable and efficient solutions, particularly for real-time, data-rich environments. This work identifies key challenges within these two domains where QC may offer advantages, particularly in handling combinatorial decision spaces and dynamic constraints. We begin by outlining the limitations of classical approaches for traffic signal control optimization and electric vehicle charging coordination, highlighting where computational limitations arise. Previous quantum formulations are presented and new formulations are proposed to demonstrate how emerging quantum algorithms, including quantum annealing and the Quantum Approximation Optimization Algorithm, could be leveraged to reformulate and address these problems. We also evaluate the suitability of current quantum hardware and discuss recent trends that indicate when QC may become a viable tool for transportation applications. While acknowledging the present limitations of QC technologies, this poster emphasizes the importance of preparing quantum-compatible models today. By reviewing and establishing formulations that align with the strengths of quantum algorithms, researchers and practitioners can better position themselves to take advantage of QC advancements as they occur. This work aims to provide a practical, forward-looking perspective on the near-term potential of quantum computing in transportation optimization.

33 ADVANCED PROPULSION SYSTEMS↗

Data-Enhanced Hierarchical Control to Improve Distribution Voltage with Extremely High PV Penetration

Dynamic, scalable, and interoperable control paradigms are required to enable efficient, secure, reliable, and resilient distribution grid operations with widespread grid integration of renewable energy resources. This paper presents our recent research on developing a novel, holistic, data-enhanced hierarchical control architecture that addresses the formidable challenges faced by emerging distribution grids with increasing penetrations of distributed energy resources. The proposed architecture integrates centralized monitoring and control with distributed grid-edge control and thus effectively deals with multi-spatiotemporal dynamics existing in the grid. Simulation results are provided to demonstrate the effectiveness of the proposed control architecture.

14 SOLAR ENERGY↗

Volume III. DUNE far detector technical coordination

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay -- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume III of this TDR describes how the activities required to design, construct, fabricate, install, and commission the DUNE far detector modules are organized and managed. This volume details the organizational structures that will carry out and/or oversee the planned far detector activities safely, successfully, on time, and on budget. It presents overviews of the facilities, supporting infrastructure, and detectors for context, and it outlines the project-related functions and methodologies used by the DUNE technical coordination organization, focusing on the areas of integration engineering, technical reviews, quality assurance and control, and safety oversight. Because of its more advanced stage of development, functional examples presented in this volume focus primarily on the single-phase (SP) detector module.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Ligand-Guided Growth of Alloyed Shells on Intermetallic Seeds as a Route toward Multimetallic Nanocatalysts with Shape-Control

In this work, shape-controlled core@shell PdCu@PtCu nanoparticles (NPs) were synthesized by seed-mediated co-reduction. Specifically, cubic-shaped NPs were achieved by selecting tetraoctylammonium bromide (TOAB) and triphenylphosphine (TPP) as capping ligands. Their roles were investigated by incorporating independently each ligand into the reaction and analyzing the products by transmission electron microscopy (TEM). This analysis revealed that the quasi-spherical PdCu seeds acquired cubic shapes during the synthesis and directed shell deposition. This process was mediated by TPP, which was central to achieving monodisperse NPs with shape-control. The synthesis conditions were modified to tune both the thickness and composition of the shells. Evaluation of the NPs as catalysts for the electrooxidation of formic acid found that the NPs with the thinnest Pt-rich shells gave the highest specific activity, with the nanocubic shape also enhancing performance with respect to the spherical counterpart. These results highlight the benefits of integrating compositional, architectural, and shape-control all in one NP construct.

36 MATERIALS SCIENCE↗

Spatial quantum-interference landscapes of multi-site-controlled quantum dots coupled to extended photonic cavity modes

Abstract A compact platform to integrate emitters in a cavity-like support is to embed quantum dots (QDs) in a photonic crystal (PhC) structure, making them promising candidates for integrated quantum photonic circuits. The emission properties of QDs can be modified by tailored photonic structures, relying on the Purcell effect or strong light-matter interactions. However, the effects of photonic states on spatial features of exciton emissions in these systems are rarely explored. Such effect is difficult to access due to random positions of self-assembled QDs in PhC structures, and the fact that quantum well excitons’ wavefunctions resemble photonic states in a conventional distributed Bragg reflector cavity system. In this work, we instead observe a spatial signature of exciton emission using site-controlled QDs embedded in PhC cavities. In particular, we observe the detuning-dependent spatial repulsion of the QD exciton emissions by polarized imaging of the micro-photoluminescence, dependent on the controlled QD’s position in a spatially extended photonic pattern. The observed effect arises due to the quantum interference between QD decay channel in a spatially-extended cavity mode. Our findings suggest that integration of site-controlled QDs in tailored photonic structures can enable spatially distributed single-photon sources and photon switches.

Physics↗

Heterogeneous Multilayer Nanopores via Chemically Tuned Dielectric Breakdown for Single‐Molecule Sensing

Solid-state nanopores are powerful platforms for single-molecule sensing, yet their performance is often constrained by fabrication complexity, noise, and limited control over surface properties. Here we report a direct method to fabricate heterogeneous multilayer nanopores using chemically tuned controlled dielectric breakdown (CT-CDB). We integrate hBN, MoS 2 , or graphene atop a silicon nitride membrane to form five distinct bilayer and tri-layer architectures, with bare SiN x nanopore as a control. CT-CDB achieves pore formation reproducibly through material-stacks with high efficiency, good pore size control, and strong yield, validated by various characterizations. Transferrin protein translocation experiments, supported by simulations, reveal that multilayer configurations modulate protein conformations, ionic current blockade and dwell time distributions, reflecting combined effects of membrane type, interfacial chemistry, and local electric field gradients. A supervised machine learning framework is implemented to assist identifying multilayer structure effects embedded in signal signatures, with over 96% accuracy. This work presents a modular and scalable framework for functional nanopore engineering with complex structural integration, thereby expanding the potential of 2D materials in single-molecule sensing applications.

2D materials↗

Distributed Control and Optimization of Virtual Inertia in Power Systems

The integration of renewable energy sources into power grids through inverter-based resources (IBRs) reduces system inertia, leading to faster frequency dynamics and potential grid instability. This paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources during system disturbances, enhancing both system stability and economic performance. Furthermore, we integrate this approach with the traditional inertia placement problem, demonstrating its suitability for existing frameworks. We validate its effectiveness in a 4-bus test system and a two-area 8-bus test system, showcasing its potential for scalable, dynamic inertia management in low-inertia grids.

Yadav, Ajay [ORNL] (ORCID:000000016111881X)↗

Evaluation of supply air temperature control performance with different control strategies at air handling units

Due to its nonlinear feature, supply air temperature control systems at air handling units using single-loop fixed gain control frequently suffer unstable response under dynamic conditions. This paper is aimed at identifying a more effective control strategy to stabilize the valve control and achieve desirable supply air temperature response under various operation conditions by evaluating three control strategies, cascade, gain scheduling and cascade plus gain scheduling controls. Firstly, a control-oriented model is developed and calibrated through open-loop tests. Then, the control issues with single-loop fixed gain control are evaluated through simulations and field tests, which indicates that the system has more aggressive response or becomes unstable under lower load conditions when the chilled-water flow rate is less than 0.1 L/s. Finally, three control strategies are proposed and evaluated. Further, the results reveal that all three proposed controls can achieve better robustness with the integral square error of supply air temperature decreased to 16%, 47% and 5%, respectively, under lower load condition. However, since high-frequency oscillation of the control valve occurs with cascade and cascade plus gain scheduling control, the gain scheduling control is recommended considering a trade-off among the supply air temperature response, valve lifetime and implementation complexity.

42 ENGINEERING↗

Numerical analysis of air dehumidification through electrospray-enhanced vortical flow cyclone separator

The dehumidification of air is a highly energy-intensive process, typically requiring vapor compression systems to cool the air significantly below its dew point temperature. Here, this study numerically investigates air dehumidification achieved by electrostatic and dielectrophoresis forces in a converging duct and centrifugal principles in cyclone separators. An electrospray was employed to energize water droplets, which then captured water vapor via dielectrophoresis. A novelty of the present study is the inclusion of a cyclone separator positioned downstream of the electrospray. This combination increased the dehumidification efficiency and controlled the flow of the condensate. By integrating electrospray technology and applying an electric field, this study examines the impact of particle separation efficiency, pressure drops, and cyclone performance on air dehumidification. The control parameters for air dehumidification were investigated. Three cyclones were modelled for airflow rates of 5 cubic feet per minute [cfm] (0.0024 m 3 /s), 38 cfm (0.0179 m 3 /s), and 200 cfm (0.094 m 3 /s). The results indicated air dehumidification was up to 5.7 % under environmental conditions, similar to those used to validate the CFD model. The degree of air dehumidification was primarily influenced by the electric charge acquired by the water droplets, their flight trajectory, and the vorticity intensity within the cyclone. Air dehumidification could increase by up to 13 % by increasing the number of droplets injected into the air stream, the flight time, and the electrical charge. The breakdown electric field strength threshold near the electrospray was a limiting factor for further enhancing dehumidification performance. This study examines the optimization of an electro-assisted dehumidification system that includes cyclone-based droplet separation through numerical analysis. The results provide insights into the design of energy-efficient air treatment technologies.

42 ENGINEERING↗

Regional Power System Black Start with Run-of-river Hydropower Plant and Battery Energy Storage

Battery energy storage systems (BESSs) are an important asset for power systems with high integration levels of renewable energy, and they can be controlled to provide various critical services to the power grid. This paper presents the real-world experience of using a megawatt-scale BESS with grid-following (GFL) and grid-forming (GFM) controls and a run-of-river (ROR) hydropower plant to restore a regional power system. To demonstrate this, we carry out power-hardware-in-the-loop experiments integrating an actual GFL- or GFM-controlled BESS and a load bank. Both the simulation and experimental results presented in this paper show the different roles of GFL- or GFM-controlled BESS in power system black starts. The results provide further insight for system operators on how GFL- or GFM-controlled BESS can enhance grid stability and how an ROR hydropower plant can be converted into a black-start-capable unit with the support of a small-capacity BESS. The results show that an ROR hydropower plant combined with a BESS has the potential of becoming one of enabling elements to perform bottom-up black-start schemes as opposed to conventional bottom-down method, thus enhancing the system resiliency and robustness.

24 POWER TRANSMISSION AND DISTRIBUTION↗