Search NASA⌕ Search

SEARCH · Search NASA

Results for “configuration management”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Development of Efficient Process for Manufacturing of Thermoplastic Composites with Tailored Properties (CRADA 511)

This is a collaborative effort between Battelle Memorial Institute as manager and operator of Pacific Northwest National Laboratory (PNNL) and ESI North America Inc. (“ESI” or “Participant”) to apply computation and data analytics to the challenge of light weighting with a focus on the battery enclosures of electric vehicles (EVs). EVs use heavy batteries to increase range and power. A complex-shaped battery enclosure is required to meet a host of challenging performance requirements. The ability to virtually develop composite parts such as battery enclosure with tailored properties to meet required performance will be highly valuable to the automotive industry. However, efficient simulation of composite-manufacturing processes remains a challenging issue since simulation involves multiscale models in space and time, highly non-linear and anisotropic behavior, strongly coupled multi-physics, and complex geometries. This work will advance the state of the art by reducing the computational burden of composite optimization by using simulation data from a limited number of configurations off-line and then developing a reduced order model (ROM) using data analytics and machine learning (ML). Develop a data driven approach to link features of the material and manufacturing processes to the mechanical properties of thermoplastic composite parts.

42 ENGINEERING↗
DOE OSTI2020

Analysis of Hydrology and Interim Measure Performance in the Chromium Plume at Los Alamos National Laboratory - 20498

Hexavalent chromium, Cr(VI), is present in the regional aquifer beneath Los Alamos National Laboratory (LANL) at concentrations greater than the New Mexico groundwater standard (50 ppb). The source of the Cr is blowdown from a power plant where potassium dichromate was used as a corrosion inhibitor from 1956 to 1972. Blowdown comingled with effluent from another source and migrated approximately 3 miles down a canyon, primarily as surface flow, until reaching an alluvial infiltration zone. The infiltrating water moved vertically through a thick (approximately 900 ft), complex stratigraphic sequence of unsaturated tuffs, basalt, and unconsolidated alluvial deposits. Horizontal transport also took place within spatially limited perched groundwater horizons in the vadose zone (VZ). Breakthrough at the regional aquifer water table is thought to have occurred in multiple hydraulic windows or 'drip points' located approximately 3 miles from the initial release site at the power plant. The regional aquifer is highly heterogeneous and anisotropic, and displays unconfined behavior in an upper zone and confined behavior at depth. The Cr(VI) contamination has so far remained confined to the upper approximately 25 m of the aquifer. The ambient hydraulic gradient in the regional aquifer is toward the east/southeast, but the water table is extremely flat in the Cr plume area compared to surrounding areas. There is some local variability in flow direction, potentially related to effects of seasonal pumping from nearby Los Alamos county water-supply wells, which draw from the regional aquifer several hundred feet below the water table. An interim measure (IM) is currently operating at the site to achieve hydraulic control of plume migration using a series of extraction wells, ion-exchange treatment, and injection along the downgradient portion of the plume. The migration of Cr contamination in the aquifer has been previously evaluated using a calibrated probabilistic numerical model, which has also been used to design the spatial configuration of extraction and injection wells for the IM, and to identify locations for monitoring wells. The model is built using the Finite Element Heat and Mass (FEHM) transfer code, and the Model Analysis and Decision Support (MADS) software is used for analyses. To date, the portion of the IM system that has operated in a continuous manner has been very effective at hydraulic control. Modifications to the flow field associated with the influence of IM pumping and injection are evaluated here, with modeling constraints to be provided by recent observations of tracers injected into both monitoring wells and IM injection wells, as well as opportunistic observations of geochemical signatures of treated ion-exchange effluent injected into IM injection wells. The tracer and geochemical data provide insights into modified flow directions within the Cr plume area that cannot be otherwise obtained. Results of the modeling work are being used to inform adaptive management of IM operations and will be a valuable tool for development and refinement of long-term remediation strategies. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Salt Hydrate Eutectic Thermal Energy Storage for Building Thermal Regulation (Final Technical Report)

Thermal energy storage is anticipated to play an important role in developing the power grid of the future - a power grid that meets increasing demands of users, is resistant to disruptions, but also allows for greater penetration of renewable resources. Specifically, thermal energy storage materials can be integrated into HVAC systems and building envelopes, where they can be used to shift power demands for building climate control from periods of peak demand to periods of low demand. Phase change materials (PCMs) are compelling as low-cost, high energy density thermal energy storage materials for building thermal management. However, there is a lack of high performance low-cost PCMs within the specific temperature ranges which would most effectively allow for power load shifting. Inorganic salt hydrates represent a promising class of PCMs, but their inherent limitations cause them to be currently unavailable for reliable building applications. The overarching goals of this research effort are to: 1) Discover low-cost, high volumetric density salt hydrate eutectic PCMs to store low-quality heat (10 to 40 °C); 2) Introduce a high thermal conductivity matrix to reduce the time constant for energy storage to ~0.1 to 1 hr, incorporate nucleation catalysts to decrease undercooling, and utilize microencapsulation and shape stabilization approaches, minimizing moisture loss/gain, mitigating phase separation, and maintaining stable melting behavior over the lifetime of the compounds; 3) Evaluate the impact these systems have on peak load shifting, and the potential for overall energy savings under different climatic scenarios and building configurations. These goals will be achieved by an integrated research program consisting of six cohesive research subtasks: 1) Materials discovery of eutectic salt hydrate PCMs by using computationally predicted thermodynamic equilibria, coupled with high-throughput experimental validation, 2) Rapid experimental screening of nucleation catalysts identified through robust computational databases, 3) Embedding salt hydrate PCM into a low cost and scalable high conductivity matrix, 4) Microencapsulation of salt hydrate microspheres using hybrid inorganic-polymer microencapsulation approach, 5) Shape stabilization by thermoreversible salt hydrate salogels, and 6) Analysis of end-use using thermal simulations, and characterization of mock-up energy storage finished components.

25 ENERGY STORAGE↗
DOE OSTI2022

Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)

Abstract. A new sea ice dynamical core, the Discrete Element Model for Sea Ice (DEMSI), is under development for use in coupled Earth system models. DEMSI is based on the discrete element method, which models collections of ice floes as interacting Lagrangian particles. In basin-scale sea ice simulations the Lagrangian motion results in significant convergence and ridging, which requires periodic remapping of sea ice variables from a deformed particle configuration back to an undeformed initial distribution. At the resolution required for Earth system models we cannot resolve individual sea ice floes, so we adopt the sub-grid-scale thickness distribution used in continuum sea ice models. This choice leads to a series of hierarchical tracers depending on ice fractional area or concentration that must be remapped consistently. The circular discrete elements employed in DEMSI help improve the computational efficiency at the cost of increased complexity in the effective element area definitions for sea ice cover that are required for the accurate enforcement of conservation. An additional challenge is the accurate remapping of element values along the ice edge, the location of which varies due to the Lagrangian motion of the particles. In this paper we describe a particle-to-particle remapping approach based on well-established geometric remapping ideas that enforces conservation, bounds preservation, and compatibility between associated tracer quantities, while also robustly managing remapping at the ice edge. One element of the remapping algorithm is a novel optimization-based flux correction that enforces concentration bounds in the case of nonuniform motion. We demonstrate the accuracy and utility of the algorithm in a series of numerical test cases.

58 GEOSCIENCES↗
DOE OSTI2020

Reliability of emergency and standby diesel generators: Impact on energy resiliency solutions

Emergency diesel generators are the most common form of backup power for critical loads when the grid fails and are most often deployed as stand-alone generators (<2000 kW) tied to individual buildings for hospitals, emergency services, military bases, ports, airports, industries, and commercial facilities. Understanding the finite reliability of emergency diesel generators during continuous operation is critical for energy planners, managers, and end-users. A new analysis of two large non-public emergency diesel generator operational data sets shows that commonly used reliability metrics are inadequate to predict the performance during a grid outage. Additional metrics addressing the likelihood of an emergency diesel generator to be available at the time an outage starts, successfully start and carry load, and constantly run for the duration of the outage are needed to predict the continuous run-time reliability of emergency diesel generators during a grid outage. This is the first analysis of the reliability of modern generators that follow standard maintenance protocols commonly used for backup power and these new metrics are shown to be dependent on the level of emergency diesel generator maintenance with values that can vary by more than an order of magnitude. Even using the new metrics for well-maintained emergency diesel generators, the analysis shows that the single emergency diesel generators configurations are only 80% likely to provide power for the duration of a two-week grid outage.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2022

Operating Strategies for Dispatchable PEM Electrolyzers that Enable Low-Cost Hydrogen Production

Hydrogen is a pathway to enabling decarbonization across multiple economic sectors that cannot be directly decarbonized with electricity including heat for industrial operations, medium- and heavy-duty transportation applications, long-duration energy storage, and as a feedstock for chemical synthesis. Producing hydrogen at low costs and carbon footprint is likely essential to economically decarbonize these otherwise "hard to decarbonize" sectors. Low-temperature polymer electrolyte membrane (PEM) electrolysis produces hydrogen from water and electricity and is a rapidly developing pathway towards making hydrogen at the scales required for decarbonization applications. The levelized cost of electrolytic hydrogen is dependent on the capital cost, efficiency, and durability of the electrolyzer system as well as the price of electricity supplied to the electrolyzer and the annual utilization of the electrolyzer (capacity factor). Electricity price and capacity factor depend on the source of energy that the system uses and impact other economic factors. Electricity price and capacity factor and the connections between other aspects of hydrogen production via PEM electrolyzers are the focus of this work. PEM electrolyzers have conventionally been operated at high capacity factors using electricity purchased from utilities with a constant price throughout the year. To achieve lower effective electricity prices, recent work has investigated opportunities for electrolyzers to purchase electricity in wholesale markets, where the cost of electricity varies hourly. This option can lead to lower electricity costs when the electrolyzer is a controllable load that ramps up and down rapidly and turns on and off frequently. This configuration and operating strategy capitalizes on times of low wholesale electricity prices and results in lower hydrogen levelized costs than constant operation due to reduced electricity costs even though the reduced capacity factor increases the cost of recovering the capital investment. Cycling on and off frequently also has implications for electrolyzer durability. An electrolyzer configuration where it is directly connected to renewable generation such as wind or solar, only running when the generator is producing energy, has similar implications on operating strategy, hydrogen levelized cost, capacity factor, and durability. This work provides insight into the relationships between dispatchable electrolyzer operating strategies and the cost of producing hydrogen from these systems, outlining strategies and opportunities to minimize production costs while minimizing operations that are likely to negatively impact system durability and efficiency. We find strategies that minimize electrolyzer cycling and the resulting durability impacts while increasing the hydrogen levelized cost only slightly above the minimum. We also find opportunities for batteries to minimize the number of cycles in systems directly connected to renewable generation. These findings outline key opportunities for future electrolyzer deployments and the synergistic benefits between electrolyzers and increased deployment of renewable energy generation like wind and solar. They also inform research and development that is reducing electrolyzer capital cost while managing durability impacts.

electricity markets↗
DOE OSTI2021

A Review of Existing and Emerging Methods for Lithium Detection and Characterization in Li-Ion and Li-Metal Batteries

Whether attempting to eliminate parasitic Li metal plating on graphite (and other Li-ion anodes) or enabling stable, uniform Li metal formation in ‘anode-free’ Li battery configurations, the detection and characterization (morphology, microstructure, chemistry) of Li that cannot be reversibly cycled is essential to understand the behavior and degradation of rechargeable batteries. In this review, various approaches used to detect and characterize the formation of Li in batteries are discussed. Each technique has its unique set of advantages and limitations, and works towards solving only part of the full puzzle of battery degradation. Going forward, multimodal characterization holds the most promise towards addressing two pressing concerns in the implementation of the next generation of batteries in the transportation sector (viz. reducing recharging times and increasing the available capacity per recharge without sacrificing cycle life). Such characterizations involve combining several techniques (experimental- and/or modeling-based) in order to exploit their respective advantages and allow a more comprehensive view of cell degradation and the role of Li metal formation in it. Additionally, it is also discussed which individual techniques, or combinations thereof, can be implemented in real-world battery management systems on-board electric vehicles for early detection of potential battery degradation that would lead to failure.

25 ENERGY STORAGE↗
DOE OSTI2022

Hydration-driven stabilization and volume collapse of grain boundaries in Mg2SiO4 forsterite predicted by first-principles simulations

Grain boundaries in mantle minerals are of critical importance to geophysical and geochemical processes of the Earth’s interior. One of the fundamental issues is to understand how the water (H 2 O) component influences the properties of grain boundaries in silicate materials. Here, we report the results of the structure and stability of several tilt grain boundaries in Mg 2 SiO 4 forsterite over the pressure range 0 to 15 GPa using density functional theory-based first-principles simulations. Here, the results suggest greater energetic stability and hydration-driven volume collapse (negative excess volume) at zero pressure for the majority of hydrous grain boundaries relative to the anhydrous (dry) ones. All the hydrous grain boundaries become increasingly favorable at elevated pressures as the calculated hydration enthalpy systematically decreases with increasing pressure. The hydrous components at the interfacial regions are predominantly in the hydroxyl form and, to a lesser extent, in the molecular H 2 O form. Their calculated ratio ranges from 1.6 to 8.7 among the different grain boundary configurations. Our structural analysis also reveals that the hydroxyls are bound to either both Mg and Si or to Mg only. In comparison, the molecular species are bound only to Mg sites. Besides direct oxygen-hydrogen bonding, intermolecular hydrogen bonding becomes important with compression. On the basis of our results, we suggest that local atomic rearrangements caused by dissociative adsorption of water facilitate efficient compaction of the boundary interfaces, which, in turn, results in greater relative stability of hydrous grain boundaries. This means that water prefers to be incorporated within the grain boundaries over the bulk of silicate materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Divertor Plasma Detachment Control Neural Network

DivControlNN is a state-of-the-art software tool that leverages advanced machine learning techniques to predict and control divertor plasma behavior in fusion reactors. Plasma, a highly energetic and electrically charged gas, requires meticulous management to protect reactor components and maintain optimal energy production. Conventional simulation methods, although extremely detailed, typically demand extensive computational time-making them unsuitable for real-time control scenarios. DivControlNN addresses this challenge by learning from tens of thousands of high-fidelity simulations, thereby creating a rapid surrogate model that can deliver near-instantaneous predictions. At the core of its functionality is a sophisticated technique known as latent space mapping, which condenses complex, high-dimensional plasma data into a compact, lower-dimensional representation. This streamlined representation enables the system to quickly forecast essential plasma properties and determine the precise conditions required for effective detachment. Detachment is a crucial process in which the plasma is cooled before reaching the divertor plates, thereby reducing heat loads and mitigating material erosion. In recent experiments conducted on the KSTAR tokamak in South Korea, DivControlNN successfully guided the detachment process without any fine-tuning-even when applied to a new tungsten divertor configuration. By achieving a computational speed-up of over one hundred million times compared to traditional simulation methods while maintaining low prediction errors, DivControlNN stands to significantly enhance real-time control and diagnostic capabilities in future fusion reactors. This breakthrough paves the way for safer, more reliable reactor operation and represents a major advancement toward realizing fusion energy as a practical, sustainable, and clean power source.

Xu, Xueqiao [Lawrence Livermore National Laborator↗
DOE OSTI2022

EJFAT: Towards Intelligent Compute Destination Load Balancing

To handle increased data flow, Jefferson Lab (JLab) is partnering with ESnet for development of an AI/ML directed compute work Load Balancer (LB) of UDP streamed data. The LB is FPGA based featuring dynamically configurable, low latency and high throughput destination address switching. The LB provides integration of edge and core computing to support JLab experimental programs, the Electron-Ion Collider, as well as data centers of the future. In the ESnet/JLab FPGA Accelerated Transport (EJFAT) initiative, the function of the LB Data Plane (DP) is to redirect data streams to selectable (but unknown to sender) destination hosts based on current worload and within that host to destination ports as a function of sub- stream id. This effects hierarchical scaling, first across compute machines for processing over a series of events and second, across ports so different data source sub-streams may be assigned to different processors for further parallelization. The LB Control Plane (CP) programs the DP using compute farm telemetry to direct and balance workloads across a compute cluster as the operating conditions require. While Proportional/Integrative/Derivative (PID) controllers are often seen in similar applications, here we investigate the feasibility of a Reinforcement Learning (RL) based schedule manager running in the CP to provide dynamic updates to the DP scheduling policy.

Lawrence, David↗
DOE OSTI2022

Evaluation of artificial neural network performance for classification of potato plants infected with potato virus Y using spectral data on multiple varieties and genotypes

Potato virus Y (Potyviridae, PVY) is a plant virus that poses a significant threat to potato producers on a global basis. The pathogen has disrupted seed potato supplies and negatively impacted yield and quality of commercial potato crops. The potato industry currently manages PVY infection levels via insecticide applications, regional seed certification programs that rely on field scouting to visually assess individual plants for infection status, and destructive and costly tissue sampling coupled with laboratory assays. Despite these efforts, PVY continues to confound potato industry stakeholders resulting in economic harm. Remote sensing and machine learning provide for the development of new tools to more accurately detect and spatially quantify PVY-infected plants versus the current state of the art. However, there is a need to understand how the occurrence of many different potato varieties impact the dynamics of developing models to detect potato plants impacted with PVY and their potential effectiveness. This study evaluates classification modelling outcomes using spectral datasets collected in different temporal and spatial environments (greenhouse and a production field) on multiple potato varieties consisting of labelled instances of plants infected with PVY and those not infected with the virus. A modelling framework was developed to support iterative modelling runs using artificial neural network (ANN) architectures configured as binary classifiers to develop sample populations to support statistical analysis on model performance using specific spectral subsets. When using spectral data to detect PVY-infected plants, ANN models achieved the highest mean accuracy of 0.894 on a single variety. Conversely, the same ANN model architecture only achieved a mean accuracy of 0.575 on a spectral data set representing 29 potato breeding lines. Additionally, statistical analysis indicates spectral regions including the red edge, near infrared and shortwave infrared contain more important spectral features for the ANN classifier introduced in this research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Subcritical Californium Source Drive Noise Analysis Measurements With Unreflected Uranium (93.15) Hydride

On July 6, 1989, subcritical californium source-driven noise analysis (CSDNA) measurements were performed with bare uranium hydride cylindrical assemblies at the Los Alamos National Laboratory Critical Experiments Facility in KIVA 1. Three configurations of ~7.5 cm radius-enriched (93.15 wt. % 235 U) uranium hydride with a density of ~10 g/cm 3 cylinders were assembled with uranium hydride heights of ~11, ~14, and ~16 cm. The uranium hydride (~2 and ~3 cm high) was in thin-welded stainless steel cans. The neutron multiplication factors obtained on-line from the measured ratios of spectral densities were 0.942 ± 0.002, 0.917 ± 0.003, and 0.867 ± 0.004 for uranium hydride heights of ~16, ~14, and ~11 cm., respectively. Neutron multiplication factors for these three configurations calculated by Los Alamos National Laboratory Monte Carlo methods were 0.952 ± 0.005, 0.922 ± 0.005, and 0.860 ± 0.005, all of which are in good agreement with the measurements. The break frequency noise analysis data could be fitted to obtain the prompt neutron decay constant at all subcritical states. Some data presented in this report are from notes that are not in the logbooks. A discussion of the two different point kinetics theories of the measurements that illustrated the deficiencies of the rigorous theory at low neutron multiplication factors (k eff < 0.80) is given in an Appendix. These measurements may be the only configuration of unreflected, highly enriched uranium hydride configuration assembled. The presence of hydrogen diluted the uranium density, decreasing the reactivity, but this is offset by slowing down the neutron energy to the energy ranges of higher-fission cross sections. Extrapolations to delayed critical indicate that adding one more 3 cm can and one more 2 cm can would result in the unreflected cylindrical system being slightly above critical with a critical mass of ~37 kg, which is considerably less than the critical mass of an unreflected and unmoderated highly enriched uranium metal sphere. An unreflected, highly enriched uranium hydride sphere would have a critical mass less than 37 kg.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Nanostructures for Electrical Energy Storage (NEES) (2020 Final Technical Report)

Nanostructures for Electrical Energy Storage (NEES, www.efrc.umd.edu) was an Energy Frontier Research Center supported by the DOE Office of Science, Basic Energy Sciences, from 8/1/2009 to 7/31/2020. Led by the University of Maryland, NEES enjoyed extensive collaborations with its funded partners, including two DOE Laboratories and six universities. The NEES vision has been to reveal a set of scientific insights and design principles that can underpin a next-generation electrical energy storage approach, building on advances in nanoscale science and technology to achieve simultaneous high power and high energy over extended charge/discharge cycling. The vision is motivated by the recognition that scaling into the nano regime opens the door to new physical phenomena and that the tools enlisted in nanoscale research provide major new opportunities for the synthesis not only of materials at molecular scale but for structures at nano scale and above. NEES has translated this vision into its research program based on two observations. First, while the behavior of ions and electrons in electrolytes and in electrode materials is crucial to electrical energy storage (or more appropriately electrochemical energy storage), it is the transport of ion and electron charge between different structural components of a storage device that ultimately determine its performance. With it well recognized that the choice of electrode materials typically constrain ion transport kinetics as well as maximum ion concentration, the search for better electrode materials has been a primary driver of battery research. At the same time the synthesis of electrodes is typically based on aggregation of particles with varying size, shape, and orientation in the electrode. Together with the presence of additional materials to impart electrical conductivity and cohesion to the composite electrode, change in electrode materials is necessarily accompanied by structural changes at the nano/micro scale that are difficult to categorize and manage. From the beginning, NEES’ vision has been to create and study simpler, highly controlled spatial arrangements of known materials as battery components (electrodes, current collectors, and electrolyte) and to understand how design and structure above the molecular scale determines the energy storage performance available from known materials. Second, advances in nanoscience dramatically expanded the portfolio of synthesis methods, structural motifs, and new phenomena available for research. Some of these gave rapid access to new building blocks at the deep nanoscale (e.g., carbon nanotubes grown by self-assembly, nanoscale arrays formed by electrochemical self-alignment, monolayer films controlled by self-limiting reaction). Such advances served as the enabler for the NEES vision to be pursued experimentally through study of 3D structures created and controlled at the nano, micro, and meso scales. Here, we use meso as in the BES MESO Report, implying not only intermediate or varying length scales, but very much the way behavior is influenced by other factors including aggregation of nanocomponents at different densities and spatial configurations, statistical variations in the aggregates, hierarchical architectures in which they can be assembled, or local 3D configurations that result from the architectures. Over its life cycle, NEES has pursued two overarching goals: (1) to understand the scientific fundamentals of electrochemical storage from the nanoscale to the mesoscale; and (2) to create and learn from innovative, controlled, heterogeneous nanostructures, where such nanostructures can enable the first goal and serve as models for future paradigms in energy storage. Specific goals have included: Synthesize heterogeneous nanostructures comprised of multiple materials arranged in controlled fashion and characterize their behavior; Demonstrate and elucidate design principles for achieving simultaneous high power and high energy; Develop materials processes which enable precision control of thin layers and 3D structures; Investigate the impact of artificial interphases on electrode stability during ion insertion/deinsertion; Create dense arrays of nanostructures to understand how the architecture of these assemblies, along with nanostructure design, influences energy storage behavior at the mesoscale; Identify and understand the consequences of nanoconfinement and local inhomogeneities in 3D mesoscale arrays; Develop and apply computational models to stimulate, guide and interpret experiments.

25 ENERGY STORAGE↗
DOE OSTI2024

Intermediate Scale Test Platform Conceptual Design and Hybrid Resin Performance Evaluation Recommendations

Recent laboratory evaluations demonstrated that further testing of alternative hybrid resins is warranted for their potential use as part of the 200 West Area (200W) pump-and-treat (P&T) remedy. 200W P&T has been treating technetium (Tc) since 2012 and uranium (U) since 2015 via two separate ion exchange (IX) treatment units: a single treatment train (i.e., a three-vessel system) for the removal of uranium utilizing a gel strong base anion (SBA) exchange resin, Dowex 21K; and two parallel treatment trains for the removal technetium using a gel SBA resin, Purolite® A532E. While these resins have been removing these contaminants effectively, new hybrid resins can provide additional benefits of further optimizing the IX treatment unit capacities and addressing additional treatment needs (e.g., Cr(VI)) by removing multiple contaminants simultaneously and/or through specific design configurations. Some of these resins also demonstrated some level of removal for I-129 which would be significant for expansion of the P&T into the 200 East Area. This document provides design recommendations for an intermediate scale test platform (ISTP) to evaluate alternative hybrid IX resin performance under conditions approaching field scale and using 200W P&T process groundwater. Results from the ISTP will provide the technical basis required to inform alternative IX resin selection in future 200W P&T facility operations where the treatment of multiple contaminants of concern may be required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Minimizing grid energy consumption in wastewater treatment plants: Towards green energy solutions, water sustainability, and cleaner environment

Wastewater treatment plants (WWTPs) consume significant amount of energy to sustain their operation. From this point, the current study aims to enhance the capacity of these facilities to meet their energy needs by integrating renewable energy sources. The study focused on the investigation of two primary solar energy systems in As Samra WWTP in Jordan. The first system combines parabolic trough collectors (PTCs) with thermal energy storage (TES). This system primarily serves to fulfill the thermal energy demands of the plant by reducing the demands from boiler units, which allows more biogas for electricity generation. The second system is a photovoltaic (PV) system with Lithium-Ion batteries, which directly produces electricity that will be used to cover part of the electrical energy demands of plant. To assess the optimal configuration, two distinct scenarios have been formulated and compared to the current case scenario (SC#1). The first scenario focuses on maximizing the net present value (NPV) and minimizing the levelized cost of electricity (LCOE). The second scenario is centred on minimizing the levelized cost of heat (LCOH). The findings indicate that both scenarios succeeded in reducing the reliance on the grid to a value that reach 1 %. Moreover, they both reduced biogas percentage in energy production from 88 % to approximately 65 % through the integration of the PV system. In terms of thermal demand, SC#2 reduced the reliance on biogas boiler units from 100 % to 25 %, while SC#3 achieved an even more impressive reduction to just 8 %. The best LCOE value was attained in SC#2, at 0.0895 USD/kWh, with an NPV of 10.54 million USD. Conversely, SC# 3 yielded an LCOH value of 0.0432 USD/kWh th compared to 0.0534 USD/kWh th USD for SC#2. In conclusion, despite their relatively high capital and operating costs, SC#2 and SC#3 managed to substantially decrease the annual electricity expenditure from approximately 2 million USD to 86,000 USD and 0 USD, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Open Building Operating System: An Open-Source Grid Responsive Control Platform for Buildings

Grid-interactive efficient buildings (GEBs) with flexible loads are a promising method to decarbonize buildings, shift loads during peak hours, and lower energy use and electricity costs. Despite the promising benefits of GEBs, automation systems that manage flexible loads in response to energy prices or other grid signals are still uncommon in small and medium commercial buildings. Recent literature demonstrates such control solutions, but they often rely on custom integrations lacking the tools and drivers needed for scalability. To address these gaps, our team has created a fully open-source software stack capable of integrating heterogeneous flexible building loads and implementing integrated portable control applications called the Open Building Operating System (OpenBOS). The software can be deployed over existing control architecture with a small capital cost. OpenBOS leverages semantic models, which have been the subject of recent investigations to facilitate application portability. The use of semantic data reduces the labor and expense required to deploy and update smart control applications, increasing scalability. In this paper, the semantic modeling schema "Brick" was used, but the proposed approach can also be applied to ASHRAE standard 223P, when released. This paper describes the methodology and software components of OpenBOS and demonstrates its functionality with a rule-based demand flexibility control application configured using a semantic model. This application was tested at a real building in NY that uses a dual-fuel heating system made up of five ductless heat pump mini-splits and a central furnace serving a single zone. The demonstration reduced electricity costs at the site by 27%, demand during a shed event by 49%, and furnace usage by 35%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Status of the International Criticality Safety Benchmark Evaluation Project

The International Criticality Safety Benchmark Evaluation Project (ICSBEP) has continued its work generating evaluations of new and historical criticality benchmark experiments since the last update to the nuclear criticality safety community at the 11th International Conference on Nuclear Criticality Safety (ICNC 2019) in Paris, France. Three additional versions of the ICSBEP Handbook have been published since that update, and the Technical Review Group (TRG) held two in-person (in 2019 and 2023) and three virtual (2020 and 2021) meetings to review and approve additional benchmarks. The 2019 edition of the ICSBEP Handbook included five new evaluations with 79 new configurations, the 2020 version of the ICSBEP Handbook contained five new evaluations totaling 76 new configurations, and the 2021 version of the ICSBEP handbook contained five new evaluations with a total of 57 different configurations. The ICSBEP TRG met in October and December 2021, to review benchmarks for potential inclusion in the 2022 ICSBEP Handbook, with seven evaluations receiving provisional approval pending resolution of review group comments. Final comment resolution for some of these evaluations is currently underway and handbook publication should be completed soon. The ICSBEP TRG met again in person in April 2023 to review benchmarks for the 2023 ICSBEP Handbook, provisionally approving 7 new evaluations. The ICSBEP continues to deliver high-quality, peer reviewed evaluations of experiments relevant to the nuclear criticality safety community.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗