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At least 271 records · Page 15

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗

Aspects of Spodumene Lithium Extraction Techniques

Lithium (Li), a leading cathode material in rechargeable Li-ion batteries, is vital to modern energy storage technology, establishing it as one of the most impactful and strategical elements. Given the surge in the electric car market, it is crucial to improve lithium recovery from its rich mineral deposits using the most effective extraction technique. In recent years, both industry and academia have shown significant interest in Li recovery from various Li-bearing minerals. Of these, only extraction from spodumene has established a reliable industrial production of Li salts. The current approaches for cracking of the naturally occurring, stable α-spodumene structure into a more open structure—β-spodumene—involve the so-called decrepitation process that takes place at extreme temperatures of ~1100 °C. This conversion is necessary, as β-spodumene is more susceptible to chemical attacks facilitating Li extraction. In the last several decades, many techniques have been demonstrated and patented to process hard-rock mineral spodumene. The objective of this review is to present a thorough analysis of significant findings and the enhancement of process flowsheets over time that can be useful for both research endeavors and industrial process improvements. The review focuses on the following techniques: acid methods, alkali methods, carbonate roasting/autoclaving methods, sulfuric acid roasting/autoclaving methods, chlorinating methods, and mechanochemical activation. Recently, microwaves (MWs), as an energy source, have been employed to transform α-spodumene into β-spodumene. Considering its energy-efficient and short-duration aspects, the review discusses the interaction mechanism of MWs with solids, MW-assisted decrepitation, and Li extraction efficiencies. Finally, the merits and/or disadvantages, challenges, and prospects of the processes are summarized.

25 ENERGY STORAGE↗

Preparation of a uranium monocarbide anode and electrochemical characterization in molten LiCl-KCl-UCl 3

Porous uranium carbide (UC) pellets possessing moderate electrical conductivity were synthesized by reaction of UO 2 with graphite at temperatures up to 1550°C under rough vacuum. Conversions as high as 98% were achieved at soak times of 2-4 hours. The electrochemistry of the UC pellets in molten LiCl-KCl-6.5 wt% UCl 3 was explored using a variety of techniques including DC polarization methods, cyclic voltammetry, chronopotentiometry and bulk electrolysis. Here, the electrode reaction for anodic dissolution was found to be kinetically controlled by dissociation of UC to a transition state complex that was hypothesized to consist of a uranium atom partially complexed by chloride ions. Precise measurements of current efficiencies using chronopotentiometry indicated upper limits of 90.9 ± 3.4% and 98.3 +1.7/-3.7% for anode and cathode, respectively, when operating at anodic overpotentials near +300 mV. Bulk electrolysis of a UC pellet performed by passing 98% of the theoretical charge resulted in nearly complete recovery of its uranium content as highly pure metal at the cathode.

36 MATERIALS SCIENCE↗

Precursor Analysis Report: Blackmatter Ransomware Attack on New Cooperative 2021

The BlackMatter Ransomware Attack on New Cooperative 2021 Precursor Analysis Report leverages publicly available information about the New Cooperative cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. The BlackMatter ransomware was first identified in July 2021 and is reported to have infected more than 50 corporations around the world. , The Iowa-based grain cooperative, New Cooperative, was impacted by the BlackMatter ransomware on or before 18 September 2021. The adversary likely resided on New Cooperative’s networks for 15 days prior to encrypting its network and demanding New Cooperative pay $5.9 million in ransom by 25 September to unlock systems and prevent 1 terabyte (TB) of sensitive data from being publicly released. It is not clear if New Cooperative paid the ransom. The full impact of the ransomware attack is not known; however, according to New Cooperative’s general manager, the attack caused the company’s automated processes to revert back to processes used in the 1970s. , As of 6 October, only 50 percent of New Cooperative’s operations were utilizing automated processes. The company took eight weeks to rebuild the entire network and information technology (IT) systems from the ground up, which puts the date of fully recovery around 13 November. Researchers and analysts identified 20 unique techniques utilized during the attack with a total of 404 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Seventeen of the identified techniques used during the New Cooperative cyber attack were precursors to the triggering event. Analysis identified 360 observables associated with these precursor techniques, 284 of which were assessed to have an increased likelihood of being perceived in the 15 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Electrodialysis: An effective methodology to purify the leachate of spent Li-ion batteries

The electrification of transportation and the transition of society towards low or net-zero carbon emissions has led to a skyrocketing global demand for Li-ion batteries. After a service life of three to ten years, Li-ion batteries have less than 80 % of their initial capacities and draw near to the end of their lives for practical utilization. Due to potential supply chain shortages and the value embodied in Li-ion batteries, it is imperative to recycle them, to recover the materials, and to improve the circularity and the sustinability of the industry. How to cost-effectively purify spent batteries while reducing time, energy, and waste emissions is a challenge faced by Li-ion battery recyclers. The first electrochemical membrane reactor reported in our group hasa high selectivity towards lower Cu 2+ , Al 3+ and Fe 3+ ions (<5 ppm) and retains >95% of the Ni 2+ , Co 2+ and Mn 2+ ions in the leachate. An advanced electrochemical membrane reactor was developed in this study. Further, not only does the new reactor have the same selectivity as the original reactor, but other advantages including a faster leachate processing rate (up to 10X faster). The advanced reactor can also directly generate acid at the anode side; eliminating the reactor restoration step. The prominent advantages that this electrodialysis technology has over chemical-precipitation methods include: (1) ion recovery efficiencies do not diminish after removing the impurities, Ni 2+ , Co 2+ and Mn 2+ , even at a higher initial Ni 2+ ion concentrations; in comparison, chemical precipitation has Ni 2+ , Co 2+ and Mn 2+ ion recovery efficiencies reduced significantly when the initial Ni 2+ , Co 2+ and Mn 2+ ion concentrations increase. (2) electrodialysis does not change the concentrations of Ni 2+ , Co 2+ and Mn 2+ ions significantly, but chemical precipitation could reduce Ni 2+ and Co 2+ ions to less than half of their initial values. Through electro-dialyzing the leachate, the H 2 evolution reaction mechanism was found to switch from the Volmer-acid Heyrovsky mechanism to the Volmer-alkaline Heyrovsky mechanism at a pH of around 3.7.

25 ENERGY STORAGE↗

Real-Time Partitioning of Diurnal Stem CO 2 Efflux into Local Stem Respiration and Xylem Transport Processes

The apparent respiratory quotient (ARQ) of tree stems, defined as the ratio of net stem CO 2 efflux (E S_CO2 ) to net stem O 2 influx (E S_O2 ), offers insights into the balance between local respiratory CO 2 production and CO 2 transported via the xylem. Traditional static chamber methods for measuring ARQ can introduce artifacts and obscure natural diurnal variations. Here, we employed an open flow-through stem chamber with ambient air coupled with cavity ring-down spectrometry, which uses the molecular properties of CO 2 and O 2 molecules to continuously measure E S_CO2 , E S_O2 , and ARQ, at the base of a California cherry tree (Prunus ilicifolia) during the 2024 growing season. Measurements across three stem chambers over 3–11-day periods revealed strong correlations between E S_CO2 and E S_O2 and mean ARQ values ranging from 1.3 to 2.9, far exceeding previous reports. Two distinct diurnal ARQ patterns were observed: daytime suppression with nighttime recovery, and a morning peak followed by gradual decline. Partitioning E S_CO2 into local respiration and xylem-transported CO 2 indicated that the latter can dominate when ARQ exceeds 2.0. Furthermore, transported CO 2 exhibited a higher temperature sensitivity than local respiration, with both processes showing declining temperature sensitivity above 20 °C. These findings underscore the need to differentiate stem CO 2 flux components to improve our understanding of whole-tree carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental and numerical investigation of fracture conductivity between non-smooth rock surfaces with and without proppant

The enhancement of fracture conductivity is vital for the efficient recovery of subsurface resources, such as geothermal energy and petroleum hydrocarbons. Proppants, granular materials injected into hydraulic fractures to maintain their conductivity, have been studied primarily in the context of smooth fractures (i.e., fractures between smooth rock surfaces). However, non-smooth fractures (i.e., fractures between rough rock surfaces) are common in geoenergy reservoirs and thus require further investigations. In this study, we conducted laboratory measurements of fracture conductivity on shale slabs with non-smooth surfaces and carried out numerical simulation using the lattice Boltzmann (LB) method, which aimed to investigate the conductivity of non-smooth fractures with and without proppants placement. When ceramic proppant with an areal concentration of 2 lb/ft 2 was placed in the fracture, the conductivity was enhanced by roughly 3-8 times compared to fractures without proppant. In fractures with proppant, gas-measured conductivity was higher than that measured with water due to proppant embedment caused by water. The experiments demonstrate the advantages of using proppant in fractures, even if the rock surface roughness can provide certain fracture conductivity via the self-propping mechanism. For fractures without proppants, high rock surface roughness is not necessarily favorable for enhancing fracture conductivity because the self-propping mechanism requires shear slip along the fracture surface. If there is no shear slip, high rock surface roughness can cause a detrimental effect on the fracture conductivity due to the interlocking effect. Utilizing advanced experimental equipment and LB modeling, this research explores the interplays between proppant placement, fracture geometry, and stress conditions to develop a comprehensive understanding of the productivity in non-smooth fractures. Further, the outcomes of this investigation indicate the importance of creating fractures with surface roughness during hydraulic fracturing and will contribute to the development of more efficient stimulation techniques for subsurface energy extraction.

15 GEOTHERMAL ENERGY↗

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption↗

Sensing at the Nanoscale Using Nitrogen-Vacancy Centers in Diamond: A Model for a Quantum Pressure Sensor

The sensing of stress under harsh environmental conditions with high resolution has critical importance for a range of applications including earth’s subsurface scanning, geological CO2 storage monitoring, and mineral and resource recovery. Using a first-principles density functional theory (DFT) approach combined with the theoretical modelling of the low-energy Hamiltonian, here, we investigate a novel approach to detect unprecedented levels of pressure by taking advantage of the solid-state electronic spin of nitrogen-vacancy (NV) centers in diamond. We computationally explore the effect of strain on the defect band edges and band gaps by varying the lattice parameters of a diamond supercell hosting a single NV center. A low-energy Hamiltonian is developed that includes the effect of stress on the energy level of a ±1 spin manifold at the ground state. By quantifying the energy level shift and split, we predict pressure sensing of up to 0.3 MPa/Hz using the experimentally measured spin dephasing time. We show the superiority of the quantum sensing approach over traditional optical sensing techniques by discussing our results from DFT and theoretical modelling for the frequency shift per unit pressure. Importantly, we propose a quantum manometer that could be useful to measure earth’s subsurface vibrations as well as for pressure detection and monitoring in high-temperature superconductivity studies and in material sciences. Our results open avenues for the development of a sensing technology with high sensitivity and resolution under extreme pressure limits that potentially has a wider applicability than the existing pressure sensing technologies.

36 MATERIALS SCIENCE↗

Utilization of Ultrasonication as a Method of Reducing Organic and Inorganic Contamination in Post‐Consumer Plastic Film Waste

Post-consumer plastic film waste often carries organic and inorganic contaminants that challenge recycling processes and affect the quality of recycled products. An effective contaminant removal procedure through washing such single-used plastic films (SUPFs) can address environmental and waste management concerns. This study compares the efficiency of different washing techniques in reducing SUPF contamination. To evaluate the efficacy of each washing technique, film samples collected from material recovery facilities are individually exposed to friction, ultrasonic-assisted, and a combination of both washes. Thermal analysis indicates that the polymers' melting temperature, crystallization temperature, and crystallinity remain unaffected by the washing methods, demonstrating method aptness. Confocal laser scanning microscope images show that washing results in a cleaner sample surface. 91% ash reduction during the combined wash treatment indicates a high method efficiency compared to the individual friction and ultrasonic wash procedures. This is further validated by reducing characteristic contaminant IR bands (3600–3000, 1750–1600, and 1100–1000 cm −1 ). Elements of concern such as Cd, Cr, Hg, and Pb in SUPFs after each washing technique applied conform with regulations (<100 ppm) for packaging products. This research shows the novel ultrasonic washing reduces more contamination than friction with shorter wash times and no surfactants.

42 ENGINEERING↗

Tradeoffs in single stage drift step recovery diode generator design

A high-voltage generator of nanosecond pulses utilizing a drift step recovery diode (DSRD) as an opening switch in the compression section is designed to operate at peak voltages of 4 kV and repetition rates of 2 MHz in burst mode at reduced voltages. The generator is used to perform empirical studies on the output metrics of a DSRD generator with a focus on matching the circuit of the reverse current loop parameters and DSRD to the load. The dynamic impedance introduced by nonlinear elements in the DSRD was investigated with respect to the driving circuit by varying the number of DSRDs connected in series. Experimental results indicate that optimization of the driving circuit for the DSRD is key to minimizing losses and achieving optimal pulse compression. Furthermore, the results also indicate trends in DSRD performance as larger storage inductances and longer pumping times are used, limiting the pulse compression capabilities of a single stage DSRD generator.

Electrical properties and parameters↗

Mapping Critical Vulnerabilities in Natural Gas Pipeline Systems through Network Centrality and GIS Analytics

Natural gas plays a central role in the US energy landscape, providing 43% of electricity generation in 2023. Its exclusive recovery ability on pipelines for transmission underscores the importance of understanding the disruption recovery ability of this infrastructure. This study employs a network-based analytical framework integrating geographic information systems (GIS) with multiple centrality measures—betweenness, closeness, degree, and eigenvector—to pinpoint key segments and evaluate the structural robustness of the national pipeline network. Pipelines are grouped by System ID and Operator ID to capture variations across organizational and physical structures. The analysis reveals uneven patterns of network influence, where certain pipelines function as critical connectors or dominant hubs. Spatial mapping highlights geographic dependencies and potential chokepoints, offering a clear view of where targeted risk prevention measures would be most effective. The findings provide practical guidance for prioritizing maintenance, enhancing system robustness, and mitigating risks to ensure a stable and secure energy supply. Future research will expand the framework to incorporate dynamic operational data and real-time network behavior.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗

Performance and economic viability assessment of a novel CO 2 adsorbent for manufacturing and integration with coal power plants

Here, this study assesses the performance and economic feasibility of a novel CO 2 adsorbent for post-combustion capture in DOE/NETL’s 650 MWnet SubC PC power plant (case B11B). Bench-scale tests showed an initial adsorption capacity of 16.3 wt%, which decreased to 12.1 wt% after 41 adsorption–desorption cycles due to induced particle aggregation by over-humidification. With a conservative adsorption capacity of 8.8 wt% and 695 adsorption–desorption cycles, an adsorbent replenishment rate of 10 tonnes/h is necessary to capture 90% of CO 2 . The breakeven sale price of the adsorbent produced at this rate is $\$$1,293/tonne, which is 40 to 80 times lower than prices for K 2 CO 3 adsorbents reported in the literature (e.g., K 2 CO 3 /TiO 2 , K 2 CO 3 /ZrO 2 ) while providing better capture performances. Sensitivity analysis reveals that increasing the plant production rate from 10 to 40 tonnes/h reduces the sale price by 8%. The study also compares the CO 2 capture cost to Cansolv, an integrated solvent-based technology. The novel adsorbent requires 2.4 GJ/tonne of CO 2 for regeneration, lower than Cansolv’s 2.7 GJ/tonne. With conservative performance estimates, the capture cost is $\$$54/tonne of CO 2 , slightly higher than Cansolv’s $\$$45/tonne. To achieve lower or comparable capture costs to Cansolv, the adsorbent should meet one of the following conditions at a commercial scale: minimum 950 cycles, 16 wt% capture capacity, 50% of the adsorbent recovery, or a reduced cost to $\$$646/tonne by upscaling the manufactury to 75 tonnes/h.

01 COAL, LIGNITE, AND PEAT↗

Dominance of Particulate Mercury in Stream Transport and Rapid Watershed Recovery from Wildfires in Northern California, USA

Frequency and intensity of wildfires are expected to increase due to climate change, especially in areas with a long summer drought. Forests are a major sink for the global pollutant mercury (Hg), and fluvial transport of Hg from recently burned watersheds has not been widely investigated. Here, we examined two years of fluvial transport of Hg and its speciation (total Hg, methyl-Hg, particulate, and dissolved forms) under storm events and baseflow in two recently burned watersheds with different burned proportions and one nonburned reference watershed in the Coastal Ranges of northern California. We examined postfire storm-event transport of Hg and its methylated form (methyl-Hg), addressed the importance of the “initial runoff pulse” to postfire Hg fluvial transport and its predominant association with suspended solids, and elucidated potential sources of Hg exports from the burned landscapes using geochemical indicators, which suggested that ash materials were likely the significant sources of particulates in the first high-flow season postfire but not subsequently. The maximum total suspended solid and total Hg levels in the “first pulse” at the severely burned watershed were 442 and 46 times higher, respectively, than those at the reference watershed. Stream suspended solid and Hg levels declined substantially in the burned watersheds after just a few months of rainfall likely due to the rapid regrowth of vegetation commonly observed in postfire landscapes, implying that the wildfire effects on immediate Hg inputs from the burned landscape are at most transient in nature.

54 ENVIRONMENTAL SCIENCES↗

Optimal experimental design using eigenvalue-based criteria with Pyomo.DoE

New developments in automated optimal experimental design within the PSE+ software ecosystem. Advancements in user experience (to reduce the time taken to perform optimal experiment design) and computational capabilities (allowing more diverse experimental design) are shown with an example relevant to critical minerals and materials. Also, a small tutorial on science-based optimal experimental design and novel contributions therein are presented.

97 MATHEMATICS AND COMPUTING↗

Post-Release Survivorship in a New Population of Blanding's Turtles Established Using Headstarted and Directly Released Turtles

Blanding’s Turtles are facing a variety of anthropogenic threats that decrease population viability. We initiated a project to establish a new population of Blanding’s Turtles on a National Wildlife Refuge in Massachusetts using hatchlings obtained from a nearby robust donor population. We released 440 head-started individuals and 401 directly-released hatchlings between 2007–2013 and conducted multiple years of post-release monitoring via aquatic trapping to estimate survival. Between 2014–2021 we released an additional 824 head-started and 433 directly-released individuals and conducted one year of aquatic trapping in 2021 to estimate population size. First year post-release survival of head-started turtles was six times that of directly-released hatchlings (0.72 vs. 0.12, respectively), but annual survival of both groups was 0.78–0.90 in subsequent years. Only 19% of turtles released at <60 mm carapace length (CL) were subsequently recaptured compared to 60% of those released at ≥60 mm CL, supporting 60 mm CL as a target minimum release size. The mean population estimates using two different study designs were 164 and 202, with 91 individuals encountered. Now that turtles released early in the project are approaching reproductive maturity, we recommend resampling and expanding trapping efforts to include more wetlands to assess long-term survival, abundance, and distribution of Blanding’s Turtles in this newly established population. Furthermore, our results, combined with other evaluations of head-starting across the species’ range, add credence to the use of head-starting as a population recovery tool for Blanding’s Turtles.

59 BASIC BIOLOGICAL SCIENCES↗

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Non-destructive electrochemical diagnosis of failure mechanisms in aqueous zinc batteries

The early detection of secondary reactions that affect the life and performance of zinc manganese oxide batteries requires a shift from conventional time-consuming and often destructive procedures to rapid lifetime-predictive techniques. In this work, an electrochemical approach is employed to elucidate independent signatures for four common types of failure mechanisms in zinc manganese dioxide (Zn||MnO2) batteries—namely, the loss of zinc inventory, the loss of active material at the cathode, electrolyte depletion, and increased cell impedance. Our findings, specific to coin cell configurations, reveal that each induced failure mechanism can be distinctively modeled and identified based on responses from the rest voltage and columbic-efficiency data for prompt detection. For instance, electrolyte depletion response manifests a distinctive abrupt (>80 %) decrease in columbic efficiency (CE) and charge-rest voltage (Vc) while the discharge-rest voltage remained constant at ~1.3 V. Furthermore, electrolyte rejuvenation of the cell increased the CE to >95 % and restored Vc from ~0.3 to >1.7 V. Recovery experiments and reference performance tests demonstrated consistency between electrochemical descriptors and their associated failure mechanisms. Further, the outcomes of this work provide valuable insights and data models for some of the dominant failure mechanisms present in zinc manganese battery chemistries, which are beneficial to accelerated early-lifetime diagnosis and advancement of Zn batteries development.

25 ENERGY STORAGE↗