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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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At least 73 records · Page 4

Leveraging Existing Assets for Long Duration Energy Storage

Increased renewables penetration to electrical grid is necessary to reduce overall emissions from the electrical power generation sector. Nonetheless, its integration creates challenges to grid operators who must match the power being generated by intermittent renewables and other traditional energy sources with the demand from consumers, while ensuring the reliability and power quality for the entire system. Energy storage has been proposed as an alternative to natural gas peaking plants and a form to deliver excess renewable energy generation at times of peak demand. For energy storage to provide benefits to end customers (energy consumers), it must be reliable, efficient, and cost effective. The Illinois Sustainable Technology Center (ISTC), one of the surveys that integrate the Prairie Research Institute (PRI), aims to develop a Center for Energy Storage at Existing Assets (CESEA) at UIUC with the participation of Waste Pressure Corp and Ecotek Engineering USA LLC. CESEA will focus on LDES systems that can integrate to existing infrastructure in a manner that reduces the initial capital expenditure and demonstrates the ability to repurpose fossil assets that would otherwise become stranded, to serve the energy transition. CESEA aims to leverage UIUC’s unique facilities to validate LDES systems performance at a relevant operating environment. UIUC’s facilities include a 85-MW combined heat and power (CHP) power plant, two (2) solar PV plants totaling over 18 MWdc of installed capacity, an electrical grid along with a substation at transmission and distribution voltages, a 22-mile gas pipeline network operating at two pressure levels, along with steam and chilled water distribution networks. The new LDES systems will connect to the existing UIUC grid through a new test electrical station, which will have the capacity to accommodate additional connections to test new devices and technologies as part of future CESEA R&D activities. The test electrical station will contain meters, instrumentation, and controls to accurately capture data and allow optimization of control algorithms. CESEA will initially focus on technologies that: i) utilize existing equipment or facilities to perform at least one of the process steps in LDES (charging, storage, or discharging), ii) leverage mature or commercially available components or controls, iii) show potential for cost-leadership in 10+ hour storage at a commercial scale. Initial technologies that were identified to meet these criteria include Compressed Gas Energy Storage (CGES), and TES. CGES stores electricity by raising the pressure of a compressible gas inside a control volume and converting the stored energy to electricity via expansion-generation. CGES is a generalization of CAES that covers any working gas (not just air). A successful CGES demo will help to circumvent many challenges faced by CAES (long development times due to site prospecting, high cost of compression and storage, heat recovery management, etc.) by: 1) utilizing existing infrastructure (compressors, pipelines, underground storage or pressure vessels) used in the transportation and storage of industrial gases for LDES charging and storage; 2) deploying over sites already-developed for industrial applications with minor additional work; 3) leveraging the price structure of commercial industrial gas to cover the costs of electricity used during charging. A previous DOE-sponsored conceptual study (DE-FE-0032018) estimated the levelized cost of energy of a 1.1 MW / 17 MWh CGES system at $0.08/kWh, with a commercial 10x scale system cost estimated at <$0.04/kWh (Giardinella, 2022). The pilot-sized system was estimated to avoid up to 2693 tons of CO2/year.

25 ENERGY STORAGE↗

Ripple-Type Control for Enhancing Resilience of Networked Physical Systems

Distributed control agents have been advocated as an effective means for improving the resiliency of our physical infrastructures under unexpected events. Purely local control has been shown to be insufficient, centralized optimal resource allocation approaches can be slow. In this context, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physical system and are allowed to communicate with peers over a “hotline” communication network. According to this protocol, agents act on local readings unless their control resources have been depleted, in which case they send a beacon for assistance to peer agents. Our ripple-type scheme triggers communication locally only for the agents with saturated resources and it is proved to converge. Moreover, under a monotonicity assumption on the underlying physical law coupling control outputs to inputs, the devised control is proved to converge to a configuration satisfying safe operational constraints. The assumption is shown to hold for voltage control in electric power systems and pressure control in water distribution networks. Numerical tests corroborate the efficacy of the novel scheme.

distributed control↗

Ripple-Type Control for Enhancing Resilience of Networked Physical Systems: Preprint

Distributed control agents have been advocated as an effective means for improving the resiliency of our physical in-frastructures under unexpected events. While purely local control has been shown to be insufficient, centralized optimal resource allocation approaches can be slow. In this context, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physicalsystem and are allowed to communicate with peers over a 'hot-line' communication network. According to this protocol, agents act upon on local readings unless their control resources have been depleted, in which case they send a beacon for assistance to peer agents. Our ripple-type scheme triggers communication locally only for the agents with saturated resources, and is proved to converge. Moreover, under a monotonicity assumption on the underlying physical law coupling control outputs to inputs, the devised control is proved to converge to a configuration satisfying safe operational constraints. The assumption is shown to hold for voltage control in electric power systems and pressure control in water distribution networks. Numerical tests on both networks corroborate the efficacy of the novel scheme.

distributed control↗

Integrated Energy-Water Data for Cross-Sector Resilience

This white paper focuses on the “energy-for-water” domain, addressing the urgent need for integrated, empirical data to support regional management, benchmarking, and research on improving efficiency and developing technologies for water and wastewater management systems. The costs and energy required for the supply, treatment, and distribution of water and wastewater lack a standard data collection mechanism and centralized database or storage infrastructure, limiting data-driven decision-making across interdependent infrastructure systems.

42 ENGINEERING↗

Digital Twin Applications in the Water Sector: A Review

As cities develop and resource demands rise, the water sector faces crucial challenges to deliver reliable, sustainable, and efficient services. Digital Twins (DTs), virtual replicas of physical systems, offer a promising tool to transform how we manage water infrastructure. Originally developed in the aerospace industry, DTs are now gaining traction in the water sector, enabling real-time monitoring, simulation, and predictive control of water and wastewater treatment, collection and distribution networks, and water reclamation and reuse systems. While still emerging in the water sector, DTs have shown potential to enhance operational efficiency, reduce environmental impacts, and support smarter, more resilient water management. This review study provides a comprehensive overview of current DT applications in the water sector, highlighting successful case studies, technical challenges, and knowledge gaps. It also explores how DTs can help bridge the water–energy nexus by optimizing resources utilized across interconnected systems. By synthesizing recent advances and identifying future research directions, this paper illustrates how DTs can play a central role in building sustainable, adaptive, and digitally-enabled water infrastructure.

digital twin↗

Identifying schools at high-risk for elevated lead in drinking water using only publicly available data

Estimating the risk of lead contamination of schools' drinking water at the State level is a complex, important, and unexplored challenge. Variable water quality among water systems and changes in water chemistry during distribution affect lead dissolution rates from pipes and fittings. In addition, the locations of lead-bearing plumbing materials are uncertain. We tested the capability of six machine learning models to predict the likelihood of lead contamination of drinking water at the schools' taps using only publicly available datasets. The predictive features used in the models correspond to those with a proven correlation to the dominant, but commonly unavailable, factors that govern lead leaching: the presence of lead-bearing plumbing materials and water quality conducive to lead corrosion. By combining water chemistry data from public reports, socioeconomic information from the US census, and spatial features using Geographic Information Systems, we trained and tested models to estimate the likelihood of lead contaminated tap water in over 8,000 schools across California and Massachusetts. Our best-performing model was a Random Forest, with a 10-fold cross validation score of 0.88 for Massachusetts and 0.78 for California using the average Area Under the Receiver Operating Characteristic Curve (ROC AUC) metric. The model was then used to assign a lead leaching risk category to half of the schools across California (the other half was used for training). There was good agreement between the modeled risk categories and the actual lead leaching outcomes for every school; however, the model overestimated the lead leaching risk in up to 17% of the schools. This model is the first of its kind to offer a tool to predict the risk of lead leaching in schools at the State level. Further use of this model can help deploy limited resources more effectively to prevent childhood lead exposure from school drinking water.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Physically Realistic Estimates of Electric Water Heater Demand Response Resource

Multiple grid integration studies have examined the value of demand response, including from water heaters, to bulk power systems. Common shortcomings of these studies include physically unrealistic assumptions. For example, studies often assume that all electric water heater load can be shed for up to an hour to provide capacity or contingency service, that all electric water heater load is shiftable, and that round-trip efficiencies for shifting service are 100%. Another issue is that simply summing up estimates of individual water heaters' flexibility bounds, an attractive idea for constructing the MW-scale resources necessary for direct inclusion in grid investment and operational models, can result in significant overestimates of actual resource, because, e.g., a water heater with the ability to reduce load may not be able sustain the reduction for as long as the aggregate model suggests is possible. This presentation demonstrates the impact of estimating the flexibility of electric water heaters with physically realistic models suitable for grid service analysis. Electric water heater flexibility representations are constructed based on ResStock simulations of New England. Specifically, we examine contingency resource (related to capacity, shed, and contingency reserve services) and energy shifting resource from electric resistance and heat pump water heaters. Different estimation methods are compared; and the surrogate models' event responses are validated against events directly simulated in EnergyPlus. We also demonstrate the impact of using electric water heaters for contingency reserves and energy shifting in detailed models of possible future ISO New England power systems.

building energy modeling↗

The future evolution of energy-water-agriculture interconnectivity across the US

Abstract Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the ‘Interconnectivity Magnitude Index’ and the ‘Interconnectivity Spread Index’. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Khan, Zarrar (ORCID:0000000281478553)↗

Preventing leaching from lead water pipes with electrochemistry: an exploratory study

Toxic levels of lead leaching from ageing water distribution infrastructure affect over 5000 public drinking water systems in the US. Pipe replacement, the most effective solution to this problem, is prohibitively expensive. Additionally, chemical conditioning of drinking water using orthophosphates, although cost-effective, does not quickly stop lead leaching once it has started. We propose a novel approach to stop lead leaching: to rapidly form an insoluble scale within lead pipes using an external power supply. We report on the feasibility of this approach by first anodizing lead coupons and lead pipes reclaimed from a local water distribution using a phosphate electrolyte and different potentials, pH values, and phosphate concentrations. We subsequently exposed these anodized lead coupons and pipes to synthetic tap water to evaluate their lead leaching rates. We found that polarizing lead coupons in the presence of a 0.05 M phosphate solution decreased lead leaching by up to a 100-fold, relative to leaching from polished bare lead. Similarly, polarizing the reclaimed lead pipes (with a preexisting scale) decreased lead leaching from an average of 36 ppb to 7 ppb. These results were observed when applying potentials that favor Pb(IV) formation, which resulted in the buildup of PbO 2 and Pb 5 (PO 4 ) 3 OH in both lead coupons and pipes. Our findings indicate that this novel technology has the potential to rapidly decrease equilibrium lead levels in tap water below the EPA action limit of 15 ppb, and thus deserves further exploration.

54 ENVIRONMENTAL SCIENCES↗

Cryogenic Considerations for Superconducting Magnet System Design for the Material Plasma Exposure eXperiment (MPEX)

The Material Plasma Exposure eXperiment (MPEX) has been proposed as a facility to address plasma material interaction knowledge gaps to qualify and develop materials and technologies that surround plasma environments for future fusion reactors. Utilizing different radio-frequency (rf) heating technologies, MPEX is a linear plasma device that will generate fusion reactor–like plasmas with energies and particle fluxes at the target materials with electron temperatures of 1 to 15 eV, electron densities of 10 20 to 10 21 m -3 , and ion fluxes greater than 10 24 m -2 s -1 . Starting with the MPEX requirements with respect to magnetic fields between 0.1 and 2.5 T and warm bores of either 0.65 m or 1.56 m, conceptual designs for a superconducting magnet system have been developed that utilize multiple NbTi windings distributed across seven cryostats to accommodate rf heating, water cooling, and vacuum systems needed for MPEX. While the cryogenic and magnet technologies relative to the field and space requirements are mature, the integration of these technologies across multiple cryostats presents several technical and logistical challenges. An analysis of the preferred refrigeration approach, modular recondensing liquid helium cryocoolers, was performed. Utilizing a design margin of a factor of two, this approach is feasible within the current design requirements for MPEX with some considerations related to its implementation within the thermal shields and the magnet subsystem geometries.

Duckworth, Robert↗

Developing a Decision Support Engine to Enable Irrigation Modernization - Poster

Irrigation systems in the United States are some of the oldest continually utilized infrastructure in existence today, with some systems exceeding 100 years in age. They are operated to meet farming demands but are managed through a balance of varying influence: policies limiting water usage, stakeholder interests, and environmental impacts. Irrigation modernization is defined as a set of activities that update and improve existing irrigation systems, including, but not limited to improving water quantity, development of distributed energy resources for surrounding communities, ecosystem services, and improved agricultural yields. Modernizing an existing irrigation system can enable stakeholders to combat changing environmental and population demands but is difficult because the complexity involved in determining the potential benefits and consequences of irrigation modernization is high. We are combining a large amount of various geospatial, tabular, and temporal data with subject matter expertise into a decision support engine that will enable stakeholders to determine the benefits and consequences of irrigation modernization in their irrigation systems. A web-based GIS will allow the user to construct the modifications out of a palette of modernization options, which will be sent to the analytics engine for computations, and back to the web client for a graphical display and comparison of relevant metrics. Our development process involves four phases: 1) identify mechanisms of modernization, 2) identify data requirements, data streams, first principles and applicable algorithms necessary to quantify modernization mechanisms, 3) create ‘modules’ for each modernization mechanism, these modules will form the decision support engine, each capable of performing independently but can also inform other modules when needed, 4) Merge the decision support engine with a user interface, capable of ingesting user inputs and returning insights into the impacts of a modernization project as they relate to economic, environmental, monetary, and energy generation. Once complete, it is our intention that this tool will be fundamental in irrigation modernization projects, providing a strong analytical basis from which stakeholders can quickly make informed decisions regarding project development.

13 HYDRO ENERGY↗

OH density and water vapor concentration gradients during plasma-droplet interactions

Plasma-droplet interactions significantly promote the reactivity transfer of gas phase species from the plasma to the liquid phase. Nonetheless, experimental studies on the impact of droplet evaporation on reactive species generation in such systems remain scarce. We report the spatial distribution of water vapor and OH radical densities around a droplet (∼41 μm in diameter) in He and He-Ar plasma using laser-induced fluorescence. The results reveal a significant gradient in both water vapor and OH radical concentrations near the droplets. Mutiple droplets present in the plasma can lead to a significant accumulation of water vapor and even local quenching of the discharge. The findings are critical for developing a quantitative understanding of plasma-liquid interactions for a broad range of plasma-enabled applications in the liquid phase often involving OH radicals.

42 ENGINEERING↗

DERMS-RT (Distributed Energy Resource Management Solution using Real-Time Optimization) [SWR-20-46]

DERMS-RT provides a distributed energy resource management solution using real-time optimization to control different types of distributed energy resources (DERs) — such as rooftop PVs, battery energy storage systems, HVAC loads, electric water heater loads, and EV charging loads, and use these DERs to provide distribution voltage regulation and peak demand management services. The control approach implemented by DERM-RT is developed based on the real-time optimal power flow and distributed control previously developed by NREL researchers. The software codes are designed to provide modular DER management solution that can be easily applied to control heterogeneous DERs in distribution grids in coordination with centralized utility management systems. Also, DERMS-RT provides application programming interface (API) to extract useful grid model information from an open-source power system simulation software, use the information to solve the optimization problem, and apply the optimal set-points to the controlled DERs. In this way, DERMS-RT provides a plug-and-play function for implementing the real-time DER control on different utility system models, and it can be used as a simulation testbed to demonstrate the impact of real-time DER optimization on improving grid operations.

Ding, Fei↗

FALCON: Framework for Anomaly Detection in Industrial Control Systems

Industrial Control Systems (ICS) are used to control physical processes in critical infrastructure. These systems are used in a wide variety of operations such as water treatment, power generation and distribution, and manufacturing. While the safety and security of these systems are of serious concern, recent reports have shown an increase in targeted attacks aimed at manipulating physical processes to cause catastrophic consequences. This trend emphasizes the need for algorithms and tools that provide resilient and smart attack detection mechanisms to protect ICS. In this paper, we propose an anomaly detection framework for ICS based on a deep neural network. The proposed methodology uses dilated convolution and long short-term memory (LSTM) layers to learn temporal as well as long term dependencies within sensor and actuator data in an ICS. The sensor/actuator data are passed through a unique feature engineering pipeline where wavelet transformation is applied to the sensor signals to extract features that are fed into the model. Additionally, this paper explores four variations of supervised deep learning models, as well as an unsupervised support vector machine (SVM) model for this problem. The proposed framework is validated on Secure Water Treatment testbed results. This framework detects more attacks in a shorter period of time than previously published methods.

97 - MATHEMATICS AND COMPUTING↗

Shedding light on U.S. small and midsize data centers: Exploring insights from the CBECS survey

As demand for digital services accelerates, the energy and environmental footprint of data centers faces increasing scrutiny. While hyperscale cloud facilities have driven efficiency gains, small and midsize U.S. data centers remain a critical yet underexamined segment with significant untapped potential for energy savings. This study leverages data from the Commercial Buildings Energy Consumption Survey (CBECS) to analyze trends in server stocks, computing customers, cooling system adoption and efficiency, and geospatial distribution from 2012 to 2018. Findings reveal a sharp decline in small and midsize data centers, from 1.764 million to 1.398 million, with server counts dropping from 5.177 million to 4.262 million—aligning with the broader shift toward cloud computing. More than 40 % of servers in small data centers and 55 % in midsize data centers are housed in office buildings, and over half of all servers are concentrated in climate zones 5A (cold), 3A (mixed-humid), and 4A (mixed-humid), with the highest densities in metropolitan hubs. While direct expansion units remain the dominant cooling system, a clear transition toward more energy-efficient solutions, particularly air economizers, is evident. By integrating server and cooling system distributions, we estimate Power Usage Effectiveness (PUE) and Water Usage Effectiveness (WUE) for U.S. data centers by size and year. Results show that midsize data centers are more energy-efficient but more water-intensive due to the widespread use of water-cooled chillers. These findings highlight the trade-offs in cooling system selection and provide a critical foundation for policies aimed at enhancing efficiency in an evolving data center landscape.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Coupling Thermal-Hydraulics with Reactor Pressure Vessel Fracture Models

Because of the importance of maintaining the integrity of the reactor pressure vessel (RPV) in light-water reactors, significant effort has been devoted over the last several decades to understand the potential failure mechanisms, characterize how material properties evolve due to environmental conditions, and develop tools to assess the probability of fracture in aged RPVs during potential transient events. One important aspect of this problem that has not yet been fully addressed is the effects of nonuniform cooling on the RPV inner wall due to the way low-temperature water injected into the primary coolant system is distributed within the RPV during potential loss-of-coolant accident transients. Colder temperatures are expected in the regions near the inlets, causing a “cold-plume” effect. Rapid cooling of the RPV wall increases the likelihood of fracture initiation, and localized cooling due to cold-plume effects could potentially exacerbate this problem. The Grizzly code can perform a three-dimensional simulation of the RPV thermomechanical response as well as the probabilistic assessment of fracture for a population of pre-existing flaws, which is necessary to account for spatial variations in coolant temperature. This report documents a first effort to couple Grizzly RPV fracture models with computational fluid dynamics models performed using the Cardinal code, which allows for a realistic representation of the temperature distribution. This report demonstrates this coupling approach on two test cases: a simplified proof-of-concept scenario and a realistic small-break loss-of-coolant accident scenario. In both cases, the effects of the spatially varying temperature are evident; although, because the small-break loss-of-coolant accident scenario was far from challenging the RPV’s margins, it is still inconclusive how important cold-plume effects are in realistic accident scenarios. However, this effort represents an important step toward performing realistic analyses to determine to what extent spatially nonuniform cooling might affect RPV integrity under more aggressive accident scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper presents the analysis which help visualize the DER impact on the grid, identify the challenges and provides an insight into the new distribution management and control needs to enable reliable and resilient grid operations.

behind-the-meter↗

SULI End of Summer Presentation

This presentation made on Power Point is a brief summary of my work enhancing the Supervisory Control and Data Acquisition (SCADA) architecture for Idaho National Lab’s Critical Infrastructure Test Range Complex (CITRC). This work was part of an on-going project to create a digital twin of CITRC that will be implemented for resiliency research. Resiliency is growing more important as extreme weather, aging infrastructure, and increasing load all exert stress on the United States power grid. This presentation highlights how I documented the existing devices and data flow on site and then updated specific device settings to better support the needs of the project. It also examines future use of this data in the digital twin data warehouse (DeepLynx), and future Artificial Intelligence and Advanced Distribution Management System applications. It will be presented to the B751 Water and Energy Systems Analysis group at INL during my last week.

24 - POWER TRANSMISSION AND DISTRIBUTION↗