Microgrid resilience: A holistic approach for assessing threats, identifying vulnerabilities, and designing corresponding mitigation strategies
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Mishra, Sakshi (ORCID:0000000252028676)↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Combined Raman and Turbidity Probe for Real-Time Analysis of Variable Turbidity Streams
We know that real-time and in situ process monitoring is a powerful tool that can empower operators of hazardous processes to better understand and control their chemical systems without increased risk to themselves. However, applying monitoring techniques to complex chemical processes can face challenges. An example of this is the application of optical spectroscopy, otherwise capable of providing detailed chemical composition information, to processes exhibiting variable turbidity. Here, details on a novel combined Raman spectroscopy and turbidimetry probe are discussed. Furthermore, the analytical approach to accurately account for both Raman signal and turbidity while quantifying chemical targets is detailed. Through leveraging Raman and turbidity data simultaneously collected from the combined probe within chemometric models, accurate quantification of multiple chemical targets can be achieved under conditions of variable concentrations and turbidity.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection
The US Western Interconnection is facing unprecedented challenges in the form of less predictable peak demand, increasingly diverse generating resources, and fast-growing loads due to the onset of artificial intelligence, hyperscale computing, and electrification. Projecting where future generation may be developed is critical to maintaining a robust and resilient electric grid under this mounting uncertainty and variability. Using an integrated multisectoral, multiscale modeling framework that links a human-Earth systems model, an hourly load model, a geospatial power plant siting model, and an hourly grid operations model, we evaluate the power plant landscape evolution under eight alternative futures between 2020 and 2055. These futures represent a wide but plausible range of atmospheric conditions, emissions constraints, and economic, technological, and population growth assumptions. We find that local-level development can vary substantially both by generation type and capacity buildout across these futures. Specific regions of the Western Interconnection are projected to see large amounts of capacity development regardless of the future scenario. We additionally determine that projected power plant locations are more heavily influenced by the cost to interconnect to the electric grid than the locational energy value.
Mongird, Kendall↗
Rate capability and Ragone plots for phase change thermal energy storage
Phase change materials can improve the efficiency of energy systems by time shifting or reducing peak thermal loads. The value of a phase change material is defined by its energy and power density—the total available storage capacity and the speed at which it can be accessed. These are influenced by material properties but cannot be defined with these properties alone. In this work, we show the close link between energy and power density by developing thermal rate capability and Ragone plots, a framework widely used to describe the trade-off between energy and power in electrochemical storage systems (that is, batteries). Our results elucidate how material properties, geometry and operating conditions influence the performance of phase change thermal storage. This research sets a clear framework for comparing thermal storage materials and devices and can be used by researchers and designers to increase clean energy use with storage.
25 ENERGY STORAGE↗
Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions
High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.
Prantikos, Konstantinos [Argonne National Laborato↗
Addressing Human and Organizational Factors in Nuclear Industry Modernization: A Sociotechnically Based Strategic Framework
The modernization of nuclear power plants will require an advanced concept of operations, involving an integrated set of tightly coupled systems in which all stakeholders act in a coordinated manner. For this modernization effort to be enabled, we developed a human and organizational factors approach based on a broad sociotechnical framework. Starting from core human factors principles, we conducted a literature review of the methods and approaches relevant to the modernization problem. These included not only core disciplines such as cognitive systems engineering, systems theoretic accident modeling and processes, human systems integration, resilience engineering, and macroergonomics but also related topics of safety culture and organizational change. From this literature, we developed a conceptual framework centered around the work system with its four interacting components: people, technology, process, and governance. In an effective work system, these four components are jointly optimized according to three systems criteria: efficiency, effectiveness, and safety. System failure may result from excessive emphasis on any one criterion. The actual work of attaining joint optimization in a given work system can be accomplished by utilizing three high-level functions: knowledge elicitation, knowledge representation, and cross-functional integration. Finally, we illustrated the utility of this approach by applying it to practical problems and case studies.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Enhancing ZnO nanowire gas sensors using Au/Fe 2 O 3 hybrid nanoparticle decoration
Heterojunctions are an important strategy for designing high performance electrical sensor materials and related devices. Herein, a new type of metal-semiconductor hybrid nanoparticle has been successfully used to remarkably sensitize the surface of ZnO nanowires for detecting NO 2 with high responses over a broad temperature window ranging from room temperature to 600 °C. These hybrid nanoparticles are comprised of iron oxide nanowires with well dispersed single crystalline Au nanoparticles. The hybrid nanoparticle decorated ZnO nanowires have achieved a giant response, as high as 74 500 toward NO 2 gas, about 42 times that of Au decorated ZnO nanowire sensors. This dramatic enhancement may be attributed to the efficient charge transfer across the Au–Fe 2 O 3 Schottky and Fe 2 O 3 –ZnO semiconductor heterojunction interfaces. Due to the incorporation of thermally-stable Fe 2 O 3 nanoparticles as the support of Au nanoparticles, the working temperature of nanowire sensors was successfully extended to higher temperatures, with an increase of 200 °C, from 400 °C to 600 °C. Such a combination of semiconductor heterojunction and semiconductor-metal Schottky contact presents a new strategy for designing high performance electrical sensors with high sensitivity, stability, selectivity, and wide operation temperature window, which are potentially suitable for advanced energy systems such as automotive engines and power plants.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
OpenSAMPL: An Open Source Library for Timing and Synchronization Measurements and Analytics
Today's power grid operators are implementing timing and synchronization solutions that provide resilience to Global Navigation Satellite System (GNSS) vulnerabilities. These vendor-specific solutions often come with additional software applications that are designed to monitor that vendor's synchronization performance data. However, resilient timing architectures often resulting in multi-vendor solutions, including approaches that blend terrestrial clocks with space-based subscription services. In such an environment, collecting, analyzing, and visualizing data from a variety of sources within a single platform was heretofore not possible. To address this need, the US Department of Energy's Center for Alternative Synchronization and Timing (CAST) developed OpenSAMPL, the Open Synchronized Analytics and Monitoring Platform, an open-source Python framework for processing, loading, and observing clock measurement data from distributed devices. OpenSAMPL enables the ingestion of diverse clock-probe sources into a scalable time-series database and applies robust analytics. OpenSAMPL currently supports two vendor data pipelines, and will be extended to more in the near future, enabling seamless monitoring of a variety of timing and synchronization devices in a common environment.
Grant, Josh [ORNL] (ORCID:0000000163475060)↗
Second ARM Mobile Facility (AMF2) Aerosol Observing System (AOS) Instrument Handbook
The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s second mobile facility (AMF2) Aerosol Observing System, designated AOS02, entered service in October of 2010 at Steamboat Springs, Colorado for the Storm Peak Laboratory Cloud Property Validation Experiment (StormVEx). The Aerosol Observing S ystem is meant to be a standalone, autonomous, aerosol sampling system. It requires only power, 208 or 440 VAC 1φ, and an internet connection to be operational. The physical structure is a standard-sized shipping container, 20 feet long by 8 feet wide. Inside, the walls, ceiling, and floors are insulated using >3.5” of spray polyurethane foam with an R-value of 6.2/inch of insulation. The interior walls, floor, and ceiling are lined with ¾” plywood for durability and have integrated unistrut for mounting equipment.
54 ENVIRONMENTAL SCIENCES↗
Individual Electro-Hydraulic Drives for Off-Road Vehicles (Final Report)
This document constitutes the final report of the project titled “Individual Electro-Hydraulic Drives for Off-Road Vehicles” (DOE award # DE-EE0008334). The project started May 1st 2018 and ended May 31st 2022. There were three budget periods (BPs) that, considering no-cost extension made throughout the project, had following periods: BP1 – Preliminary design: 05/01/2018 – 07/31/2019; BP2 – Initial implementation: 08/01/2019 – 01/31/2021; BP3 – Technology demonstration: 02/01/2021 – 05/31/2022. The main objective of the project was to develop and demonstrate an electro-hydraulic technology that, with respect to current state of the art solutions for off-road vehicles, can: 1. Lower power consumption of the fluid power system up to 70%; 2. Reduce noise emissions and vibration; 3. Allow for zero emission operation of the vehicle (engine off operation); 4. Enable “smart actuators” operating as modern “plug & play” elements with integrated control and self-diagnostic functions.
33 ADVANCED PROPULSION SYSTEMS↗
Water & Energy Interdependencies Across Economic Sectors of the United States
The motivation of the Integrated Water Power Resilience Project is to identify and develop opportunities for improving resilience in the water and power sectors through coordinated planning, investment, and operations and thereby provide benefits to power and water utilities, consumers, and the environment. Water and power systems are interdependent, subject to many of the same natural and manmade hazards, and are critical for the well-being of communities and society. Because of the interconnectedness of water and power systems, there are substantial economic, social, and environmental benefits to co-managing the market sectors for resilience instead of managing them separately. To support this initiative and future research in this area, a county level water and energy flow dataset was developed to build, calculate, and visualize interconnections in water and energy between various sectors. This report presents county and regional water and energy visualizations across nine economic sectors of the United States: agriculture, commercial, electricity generation, industrial, mining, public water supply, residential, transportation, and wastewater treatment.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Oak Ridge National Laboratory's Strategic Research and Development Insights for Digital Twins
Oak Ridge National Laboratory (ORNL) is pleased to provide our response to the NITRD RFI on Digital Twins Research and Development. Digital twins are virtual representations of physical systems, leveraging real-time data to simulate and predict behaviors. ORNL is advancing digital twin technology across various disciplines, including neutron scattering, networking, science ecosystems, supercomputing, secure facilities, mobility technologies, materials design and discovery, power systems, fusion reactors, biological sciences, and earth observation. These efforts aim to enhance scientific research, operational efficiency, and decision-making processes. ORNL facilities, such as the High Flux Isotope Reactor (HFIR), Grid-C, Spallation Neutron Source (SNS), and Oak Ridge Leadership Computing Facility (OLCF), provide the infrastructure to develop and demonstrate these digital twin technologies. In this document, we lay out key challenges, research gaps, and future opportunities based on our experience with digital twins that aim to serve as useful contributions towards a National Digital Twins R&D Strategic Plan. In the remaining document, we address nine of the thirteen topic areas specified in the RFI.
97 MATHEMATICS AND COMPUTING↗
Pulse charging system
A system, method, and apparatus for pulsed charging applications comprises a bulk capacitor operably connected to a power source, an inductor connected to the bulk capacitor with a charge switch, a pulse capacitor connected to the inductor, a freewheeling diode connecting a point between the charge switch and the inductor to a point after the pulse capacitor, a second diode connecting the inductor to the pulse capacitor, and a pulse switch connecting the pulse capacitor to a load.
42 ENGINEERING↗
Addressing Human and Organizational Factors In Nuclear Industry Modernization: A Sociotechnically-Based Strategic Framework
The modernization of nuclear power plants will require an advanced concept of operations, involving an integrated set of tightly coupled systems in which all stakeholders act in a coordinated manner. For this modernization effort to be enabled, we developed a human and organizational factors approach, based on a broad sociotechnical framework. Starting from core human factors principles, we conducted a literature review of the methods and approaches relevant to the modernization problem. These included core disciplines such as cognitive systems engineering, systems theoretic accident modeling and processes (STAMP), human systems integration, resilience engineering, and macroergonomics but also related topics of safety culture and organizational change. From this literature, we developed a conceptual framework centered around the work system with its four interacting components: people, technology, process, and governance. In an effective work system, these four components are jointly optimized according to three systems criteria: efficiency, effectiveness, and safety. System failure may result from excessive emphasis on any one criterion. The actual work of attaining joint optimization in a given work system can be accomplished by utilizing three high level functions: knowledge elicitation, knowledge representation, and cross-functional integration. We illustrated the utility of this approach by applying it to practical problems and case studies. The complete report is available in [1]; this paper is a description of our approach and report contents.
99 GENERAL AND MISCELLANEOUS↗
Integrated solid-state rapid thermo-cycling system
Techniques, systems, and devices are disclosed for implementing a portable lab system for PCR testing. The portable lab system comprises a thermal cycling device including a first well and a second well to receive samples to be thermally cycled, a thermoelectric cooling (TEC) element coupled to the first well and the second well, and a controller to control operation of the TEC element. The portable lab system further includes an electronic interface including a power interface to supply power to the TEC element and the controller of the thermal cycling device to allow the TEC element to transfer energy from the first well to the second well when current flows through the TEC element in a first direction, and from the second well to the first well when current flows through the TEC element in a second direction, and a data interface to collect data from the controller.
59 BASIC BIOLOGICAL SCIENCES↗
Two-Tower Quantum Matrix Chain Multiplication: Trading Qubits for Depth
Matrix chain multiplication -- computing $\mathcal{W} = M^{(0)}\cdots M^{(K-1)}$ where $M^{(k)} \in \mathbb{R}^{P_k \times P_{k+1}}$-- arises in scientific computing, machine learning, and graph analysis. Despite the importance of this problem, for chains of distinct matrices, the classical number of operations grows linearly with the chain length $K$ and polynomially in the matrix dimensions. We present \emph{Two-Tower Matrix Multiplication}, a quantum subroutine that encodes the product $\mathcal{W}$ of the $K$ matrices into a quantum state in circuit depth $\mathcal{O}(\max_{k} \mathrm{polylog} (P_k P_{k+1}))$, which is independent of~$K$ within the QRAM-based state-preparation model, whereas the qubit count is $\mathcal{O}\bigl(\sum_{k} \log P_k \bigr)$; the total gate count remains linear in $K$, so the gain is in the circuit depth. The construction interleaves state-preparation operators across two layers; within each layer, all operators act on disjoint registers and execute in parallel. This subroutine can be specialized for the chain-vector case, which computes the product of $K-1$ matrices applied to a vector. We prove the correctness of the subroutine for all $K$ and provide two implementations using the Qiskit and QCLAB frameworks. The subroutine is applicable to any downstream quantum algorithm that operates on a matrix encoded in the statevector, including norm estimation, graph-matrix powers, linear system solving, and quantum machine learning kernels.
Antonioli, Giacomo [Pisa U.] (ORCID:00090000668703↗
Frequency Analysis of Solar PV Power to Enable Optimal Building Load Control
In this paper, we present a flexibility estimation mechanism for buildings’ thermostatically controlled loads (TCLs) to enable the distribution level consumption of the majority of solar photovoltaic (PV) generation by local building TCLs. The local consumption of PV generation provides several advantages to the grid operation as well as the consumers, such as reducing the stress on the distribution network, minimizing voltage fluctuations and two-way power flows in the distribution network, and reducing the required battery storage capacity for PV integration. This would result in increasing the solar PV generation penetration levels. The aims of this study are twofold. First, spectral (frequency) analyses of solar PV power generation together with the power consumption of multiple building TCLs (such as heating, ventilation, and air conditioning (HVAC) systems, water heaters, and refrigerators) are performed. These analyses define the bandwidth over which these TCLs can operate and also describe the PV generation frequency bandwidth. Such spectral analyses, in frequency domain, can help identify the flexible components of PV generation that can be consumed by the various TCLs through optimal building load utilization. Second, a quadratic optimization problem based on model predictive control is formulated to allow consuming most of the low and medium frequency content of the PV power locally by building TCLs, while maintaining occupants’ comfort and TCLs’ physical constraints. The solution to the proposed optimization problem is achieved using optimal control strategies. Numerical results show that most of the low and medium frequency content of the PV generation can be consumed locally by building TCLs. The remaining high-frequency content of the PV generation can then be stored/offset using energy storage systems.
14 SOLAR ENERGY↗
Experimental Validation of a Modular All-Electric Power Take-Off Topology for Wave Energy Converter Enabling Marine Renewable Energy Interconnection
Power electronic converters are an enabling technology for the emerging marine energy applications, such as using ocean waves to produce electricity. This paper outlines the power take-off system and its key components used in a wave energy converter offering modularity and scalability to generate power efficiently. The proposed power take-off system was implemented based on a modular multilevel converter and could be deployed to convert any alternating current electrical energy to a different alternating current for interconnection to grid or non-grid applications. Examples of widespread deployment are supplying electricity to coastal communities or producing clean drinking water. The analysis using both the simulation tests and laboratory experiments verified the design objectives and basic functionality of the developed power take-off system. An acceptable response using a field programmable gate array-based controlled laboratory testbench was achieved, complying with guidelines specified in the prevalent industry standards. Seamless operation during steady-state and transients for the studied wave energy converter was achieved as supported by the obtained results. The key findings of this work were experimentally examined under different load conditions, direct current bus voltage fluctuations, and generator speed–torque regulation. The ability of the power take-off system to generate high-power quality of the waveforms, e.g., against adhering to the IEEE 519-2022 standard for total harmonic distortion limits, is also confirmed.
Engineering↗