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At least 307 records · Page 17

Preliminary design of a helium cryogenic system for SAND detector at LBNF-DUNE near site

The Long-Baseline Neutrino Facility (LBNF) is providing a helium cryogenic system to support the superconducting solenoid magnet of the System for on-Axis Neutrino Detection (SAND) for the Deep Underground Neutrino Experiment (DUNE) Near Site at Fermilab in Batavia, IL. The design started in 2020 and construction is set to begin in the mid 2020‘s.The helium cryogenic system primarily consists of a helium refrigerator system, distribution valve boxes, vacuum-jacketed helium and nitrogen transfer lines, warm gaseous helium transfer system, instruments and control system, and gaseous helium storage tanks. It is designed to provide supercritical helium at around 3 bara and 5 K with expansion from 3 to 1.2 bara in the SAND cryostat and 70K forced cold gas helium to cool the thermal shields of the SAND cryostat. The SAND superconductive magnet is indirectly cooled through a liquid helium thermosiphon cycle. A pair of 3 kA leads is cooled by the gas helium vaporized from the liquid helium reservoir in the cryostat turret. The helium system will share the liquid nitrogen tank and liquid nitrogen phase separator with the Near Site Liquid Argon system. The helium recycle compressor system, GHe tanks and LN2 tank will be located on the Surface. The cryogenic facilities including refrigerator cold box, valve boxes and LN2 phase separator will be located on the shaft cryo-mezzanine in the underground cavern. The shaft connecting surface and cavern is more than 60 meter deep. The helium vacuum-jacketed transfer line between the cold box and the SAND magnet is more than 50 meter long. This paper presents the preliminary design of the helium cryogenic system including the design scheme, process flow diagram, heat load estimates, layout plan and so on.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Optimizing Management of Persistent Data Structures in High-Performance Analytics

Large-scale data analytics workflows ingest massive input data into various data structures, including graphs and key-value datastores. These data structures undergo multiple transformations and computations and are typically reused in incremental and iterative analytics workflows. Persisting in-memory views of these data structures enables reusing them beyond the scope of a single program run while avoiding repetitive raw data ingestion overheads. Memory-mapped I/O enables persisting in-memory data structures without data serialization and deserialization overheads. However, memory-mapped I/O lacks the key feature of persisting consistent snapshots of these data structures for incremental ingestion and processing. The obstacles to efficient virtual memory snapshots using memory-mapped I/O include background writebacks outside the application’s control, and the significantly high storage footprint of such snapshots. To address these limitations, we present Privateer, a memory and storage management tool that enables storage-efficient virtual memory snapshotting while also optimizing snapshot I/O performance. Here, we integrated Privateer into Metall, a state-of-the-art persistent memory allocator for C++, and the Lightning Memory-Mapped Database (LMDB), a widely-used key-value datastore in data analytics and machine learning. Privateer optimized application performance by 1.22× when storing data structure snapshots to node-local storage, and up to 16.7× when storing snapshots to a parallel file system. Privateer also optimizes storage efficiency of incremental data structure snapshots by up to 11× using data deduplication and compression.

Computer science↗

Linking Plant and Microbial Traits to Soil Carbon for Reliable and Resilient Bioenergy Systems

Bioenergy systems in the United States offer a dual opportunity to supply renewable feedstocks while enhancing ecosystem services such as hydrologic regulation, erosion control, and soil carbon (C) storage. National assessments highlight the potential to grow perennial energy crops to improve soil function and ecosystem resilience. Realizing this potential requires understanding the ecological mechanisms that govern how C is added, transformed, and stabilized in soils. Plant traits determine the quantity, depth, and chemistry of organic inputs, while microbial processes—including carbon use efficiency, necromass formation, and trophic interactions—mediate their transformation and partitioning among soil carbon pools. These biological pathways are shaped by soil physical and chemical properties, including aggregation, texture, and mineralogy, and by environmental drivers such as temperature, moisture, and disturbance, leading to context-dependent outcomes across landscapes. Management practices that diversify feedstocks, minimize disturbance, and maintain soil cover can promote both biomass production and C retention, while microbial amendments and rhizosphere engineering offer emerging, but often context-dependent, tools to optimize plant–microbe interactions. Trade-offs between biomass yield and soil carbon storage may arise when systems favor rapid aboveground productivity at the expense of belowground inputs and microbial processing, underscoring the importance of trait combinations that support both functions. Advances in monitoring, reporting, and verification—spanning precision agriculture, remote sensing, and biosensing—are improving predictive capacity through microbial-explicit process models and model–experiment (ModEx) frameworks. By connecting soil, plant, and microbial processes with advances in modeling and biosensing, this review outlines research priorities focused on trait-based parameterization and ModEx integration. These priorities will support the design of bioenergy systems that are both reliable and resilient, enhancing renewable energy production and ecosystem sustainability.

bioenergy systems↗

5G Securely Energized and Resilient: (5G-SER) (Final Report)

NREL's work on 5G integration with physical power systems (versus simulated systems demonstrated in task 3) under 5G-Securely Energized and Resilient (5G-SER) achieved a major milestone in with the completion of Task 4 activities. After many months (6+) of planning and development along with scaling challenges along the way, a full 5G end-to-end network with physical hardware components (physical inverter, physical power panel, physical battery, etc.) was deployed in a containerized environment. In parallel, a distributed controls architecture for a microgrid powering 5G resources was also successfully modified from its previous instantiation for a simulated environment to work with these physical components. These accomplishments set the stage to use newly setup 5G technology with physical microgrid components to test the feasibility of 5G wireless with physical systems to enable resilient communications between controls and distributed solar and storage resources while exploring ways to configure 5G components to survive power disturbances. The results detailed in the report below show that even utilizing physical components, 5G wireless systems were able to provide resilient results that were similar to the results from the simulated environment Task 3).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reinforcement Learning for In-Spill Optimization of the Mu2e Resonant Extraction: Compensating Non-Stationarity

We present design considerations and challenges for the fast machine learning component of a third-order resonant beam extraction regulation system being commissioned to deliver steady beam rates to the mu2e experiment at Fermilab. Dedicated quadrupoles drive the tune toward the 29/3 resonance each spill, extracting beam at kV multiwire septa. The overall Spill Regulation System consists of (1) a “slow” process using ~100-spill averages to adjust the base quad ramp infrequently, (2) a feedforward harmonic content compensator, and (3) the “fast” ML agent reacting during each ongoing spill with on-the-fly additive corrections to the sum of (1) and (2). We have demonstrated improved beam-rate steadying for a fast ML agent compared to a PID controller using a quasi-physical spill simulation, and demonstrated distillation of that simulation into a predictive surrogate model. Current work includes a data-and-training pipeline to generate data-aware surrogates with real-world dynamics, even as the dynamics shift unpredictably. The surrogates are to act as RL environments against which to train our fast ML control agents before deploying them on FPGA in the live system. Further current efforts focus on modeling and controlling beam loss around the storage ring, understanding additional available hardware inputs to the model, and the interplay of these with beam-steadying performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modular scalable power conversion

A cascaded architecture composed of interconnected blocks that are each designed to process constant power and eliminate bulk energy storage are provided. Further, local controls within each block natively achieve both block- and system-level aims, making the system modular and scalable. Further methods of providing power conversion using such interconnected clocks are also provided.

Maksimovic, Dragan↗

Methane Emissions Produced by Pneumatic Devices and Produced Water Tanks on Natural Gas Wellsites

In recent years, more scrutiny has been placed on the release of greenhouse gasses (GHGs) by the oil and gas industry in North America as climate concerns increase. In the coming years, stricter regulations proposed by the Environmental Protection Agency (EPA) concerning the release of GHGs will further direct attention to GHG emissions quantification, modeling, and overall reduction. Active natural gas wellsites employ production equipment that routinely emits methane during normal operation. Production equipment often includes, but is not limited to, gas production units (GPUs), pneumatic controllers (PCs) and actuators powered by produced natural gas, and produced water storage tanks. This work details direct methane emission measurements taken at active natural gas wellsites originating from intermittent pneumatic controllers and produced water storage tanks. Efforts to model methane flows originating from these sources are also detailed, and those results are compared to direct measurement. The direct methane emissions measurement campaign collected flow data from two active dry wellsites in the Marcellus shale region. These measurement campaigns captured, in total, several weeks of continuous data from these sites. Data included multiple pneumatic device vent flowrate channels, a single channel monitoring total emissions vented from the produced water storage tanks, and corresponding site weather data. Periodic composition measurements were taken from flows vented from produced water tanks. Computational modeling efforts attempted to mimic a given site’s methane emissions behavior given limited input parameters. Direct measurement data and simulation data yielded, through reduction and analysis, apparent methane emissions factors, statistics on pneumatic device actuation events, important relationships between GPU parameters and pneumatic device actuation events, produced water storage tank vent flows and flow compositions, and parameters most contributing to the magnitude and frequency of these fugitive methane emissions. Measurements, considering data from a 72hr period, produced PC emissions factors from 0.008 to 0.03 SCFH per device with an average device emitting 0.026 SCFH at the first site. The second site produced PC emissions factors spanning from 0.05 to 25.47 SCFH with an average device emitting 1.93 SCFH not including the 25.47 SCFH device, which was assumed to be malfunctioning. Two unique water tank emission measurements were made, 618 g CH4 per hour and 32.6 g CH4 per hour. On a water basis, the water tank emissions factors were 0.66 and 0.042 kg CH4 per bbl of water, respectively.

03 NATURAL GAS↗

Ballistic Ejection of Microdroplets from Overpacked Interfacial Assemblies

Spontaneous emulsification, resulting from the assembly and accumulation of surfactants at liquid–liquid interfaces, is an interfacial instability where microdroplets are generated and diffusively spread from the interface until complete emulsification. Here, it is shown that an external magnetic field can modulate the assembly of paramagnetic nanoparticle surfactants (NPSs) at liquid–liquid interfaces to trigger an oversaturation in the areal density of the NPSs at the interface, as evidenced by a marked reduction in the interfacial tension, γ, and corroborated with a magnetostatic continuum theory. Despite the significant reduction in γ, the presence of the magnetic field does not cause stable interfaces to become unstable. Upon rapid removal of the field, however, an explosive ejection of a plume of microdroplets from the surface occurs, a dynamical interfacial instability which is termed explosive emulsification. Further, this explosive event rapidly reduces the areal density of the NPSs to its pre-field level, stabilizing the interface. The ability to externally suppress or trigger the explosive emulsification and controlled generation of tens of thousands of microdroplets, uncovers an efficient energy storage and release process, that has potential applications for controlled and directed delivery of chemicals and remotely controlled soft microrobots, taking advantage of the ferromagnetic nature of the microdroplets.

36 MATERIALS SCIENCE↗

SolarPlus Optimizer: Integrated Control of Solar, Batteries, and Flexible Loads for Small Commercial Buildings

Building-level microgrids may be a key strategy to unlock the combined potential of flexible loads, renewable generation, and energy storage. However, few software options exist for integrated control of building loads and other distributed energy resources at this scale. The commercial software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice. The SolarPlus Optimizer (SPO) is an open-source building-level microgrid control platform that uses Model Predictive Control to optimize both building loads and behind-the-meter energy storage to reduce energy bills and increase demand flexibility. This paper evaluates the capabilities of SPO in a small commercial building in Northern California under multiple electricity tariffs and demand response scenarios. Comparing SPO operation with an emulated battery and baseline operation employing a commercial optimization service, SPO reduced electricity bills by an estimated 7.3% in summer, 3.2% in spring, and 3.7% in winter. In a “load shape” scenario meant to counter the “duck curve”, SPO achieved 71% fewer violations from the load signal than the baseline control method. During a three hour long load shed event, SPO reduced cooling and refrigeration load by 38%. This research shows significant potential to provide load flexibility for building-level microgrids for this type of control systems. Finally, the paper discusses the future direction of research on open-source control systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Testing of Participant's Power Electronics Component for Circuit Performance and Efficiency (CRADA Final Report)

The "Solar SEED Smart Controller is a charge control device to condition solar power to load voltage with or without Battery (also called a "DC Power Platform") invented by David Gibbs and T4D Labs Inc. T4D Inc. and the SEED Smart Controller invention were selected for American Made Challenges Solar Prize, which includes voucher for NREL to provide technical assistance.

14 SOLAR ENERGY↗

Comparative and Cost Analysis of a Novel Predictive Power Ramp Rate Control Method: A Case Study in a PV Power Plant in Puerto Rico

One of the most important aspects that need to be addressed to increase solar energy penetration is the power ramp-rate control. In weak grids such as the one found in Puerto Rico, it is important to smooth power fluctuations caused by the intermittence of passing clouds. In this work, a novel power ramp-rate control strategy is proposed. Additionally, a comparison with some of the most common power ramp-rate control methods is performed using a proposed model and real solar radiation data from the Coto Laurel photovoltaic power plant located in Ponce, Puerto Rico. The proposed model was validated using one-year real data from Coto Laurel. The power ramp-rate control methods were compared in real-time simulations using the OP5700 from Opal-RT Technologies considering power ramp rate fluctuations, power ramp-rate violations, fluctuations in the state-of-charge, among other indicators. Moreover, the proposed power ramp-rate control strategy, called predictive dynamic smoothing was explained and compared. Results indicate that the predictive dynamic smoothing produced a considerably reduced Levelized Cost of Storage compared to other power ramp-rate control methods and provided a higher lifetime expectancy for lithium batteries.

36 MATERIALS SCIENCE↗

Optimal, Reliable Building-Integrated Energy Storage (Cooperative Research and Development Final Report)

The team will advance the commercial readiness of behind-the-meter (BTM) energy storage (ES) systems by employing health-conscious controls that guarantee lifetime and optimize the ES system's value stream when integrated with onsite renewable energy generation. Specifically, the team will develop ES controls that increase the net present value (NPV) of photovoltaics (PV) by 50% in markets where net-metering policies are being replaced by variable electricity pricing structures. The team will also reduce the risk of achieving a 10-year ES warranty lifetime by at least one order of magnitude. The successful two-year project will develop the controls and system enabling Eaton to commercialize the technology by 2021. The developments achieved through this project may enable wide scale adoption of stationary energy storage benefitting the public.

25 ENERGY STORAGE↗

Heat pump water heater enhanced with phase change materials thermal energy storage: Modeling study

A promising solution to improve the first hour rating (FHR) of a heat pump water heater (HPWH) involves employing a secondary tank which contains phase change material (PCM) capsules. To better understand the influence of PCM thermal storage on the HPWH operational performance, a dynamic model was developed to simulate and analyze the behavior of a newly developed HPWH technology that incorporates PCM storage into a standard HPWH to optimize key parameters such as the uniform energy factor and FHR. Mathematical models of several key components of the proposed HPWH-PCM integrated thermal energy storage (TES) system, e.g., water heater tank, PCM TES tank, evaporator, compressor, and expansion valve, have been elaborated. Also, a model-based control co-simulation platform was developed to integrate a embed PCM storage HPWH dynamic model with a control model for better supporting control design, analysis, verification, and validation. The model accuracy has been validated through comparing simulation results with lab test results, with a mean average percentage error of <5.5% for most of the selected performance variables. In addition, using the developed co-simulation platform, the demand response control strategy was studied to evaluate the load flexibility of the combined HPWH-PCM storage system by shifting system power usage to outside of the 3.5 h peak load period.

25 ENERGY STORAGE↗

Risk Considerations of Transitioning CO2-EOR Field to CO2 storage Field: Case Study

In the United States (U.S.), carbon dioxide (CO2) injection wells at EOR sites are currently regulated as Class II wells under the U.S. Environmental Protection Agency’s (EPA) Underground Injection Control (UIC) program while dedicated geological CO2 storage (GCS) wells are considered Class VI wells. A CO2-EOR facility considering a transitioning from tertiary oil recovery to injecting CO2 for the primary purpose of long-term storage is required to obtain a Class VI permit where this transition poses an increased risk to underground sources of drinking water. This study considers how transitioning operations from CO2-EOR to storage can impact reservoir plume and pressure transient in the storage envelope, and how these changes could impact area of review and potential unwanted fluid migration. We developed a case study to assess subsurface response and leakage risks associated with a representative, hypothetical operation in a carbonate reservoir. This reservoir transitions from tertiary hydrocarbon recovery to dedicated GCS. Reservoir simulations were run for a set of credible CO2-EOR scenarios to estimate distributions of fluids phases and pressures throughout the model domain after CO2 flooding as well as forecasting the behavior of the reservoir after the transition to a dedicated storage phase. The evolutions from all simulated scenarios were used as the basis for leakage risk quantification using the National Risk Assessment Partnership’s Open-Source Integrated Assessment Model (NRAP-Open-IAM) with a novel reduced-order model to estimate time-dependent leakage of CO2, brine, and hydrocarbon fluids through potentially leaky wells. Results include a description of reservoir response, an estimate of the areal extent that could potentially be impacted by leakage to underground sources of drinking water, and estimates of the magnitude of potential leakage. Considerations for dedicated storage injection well selection, injectivity, and injection scheme performance and potential leakage risk are presented, with implications for risk assessment of well transition discussed. This study presents a risk-based workflow for the Class II to Class VI well transition. Integrating credible numerical simulation of viable CO2-EOR to dedicated CO2 storage with quantitative risk assessment tools, such as the NRAP-Open-IAM, will provide a valuable means to devise operational scenarios and inform decision-making related to storage benefit, leakage risk, and liability. Presented at the SPE/AAPG/SEG Carbon Capture Utilization and Storage Conference in Houston, TX, March 11-13, 2024.

Liu, Guoxiang↗

Impact of Quaternary Pumped Storage Hydropower on Frequency Response of U.S. Western Interconnection with High Renewable Penetrations

As renewable penetration increases in the United States, maintaining stability and reliability of low-inertia power grid by providing sufficient frequency control capability becomes a challenge. Advanced pumped storage hydro technologies (APSH) will be expected to play an important role for future grid as not only an energy supplier, but also as an ancillary services provider. This paper studies the impact of using quaternary pumped storage hydropower (Q-PSH), as one of the newly proposed APSH technology, to provide primary frequency response. To quantify the impact of Q-PSH on frequency response of the U.S. Western Interconnection, a user-defined dynamic model of Q-PSH is developed on the GE Positive Sequence Load Flow (PSLF) platform and is implemented in a set of detailed U.S. Western Electricity Coordination Council (WECC) planning cases in which renewable penetration levels are 20%, 40%, 60% and 80%. Simulation results show that Q-PSH can help improve frequency nadir and settling frequency comparing to the conventional PSH.

frequency response↗

Evaluation of Communication Issues in Primal-Dual-Based Distributed Energy Resource Management Systems (DERMS)

With the increasing adoption of distributed energy resources (DERs) in distribution networks, DERMS is becoming an attractive option to coordinate the control of DERs, especially primal-dual-based DERMS which is a well-developed class of them. In order to help lower the uncertainty in commercializing them, we evaluate and find the upper limits of severity for some common issues that can occur within the communication systems on which a primal-dual-based DERMS relies on; these include packet losses, link failures, and delays. This information can help a DERMS operator decide on the specifications for the communication infrastructure it will invest in for the DERMS. Our evaluation is based on numerical simulations of a real-world feeder with around 2,000 nodes and a DERMS that controls 163 PV generators and 140 energy storage batteries. In general, we found that the DERMS becomes less resistant to communication issues as the information flows closer to the DERs implementing the controllable power injections.

communication delay↗

Evaluation of Communication Issues in Primal-Dual-Based Distributed Energy Resource Management Systems (DERMS): Preprint

With the increasing adoption of distributed energy resources (DERs) in distribution networks, DERMS is becoming an attractive option to coordinate the control of DERs, especially primal-dual-based DERMS which is a well-developed class of them. In order to help lower the uncertainty in commercializing them, we evaluate and find the upper limits of severity for some common issues that can occur within the communication systems on which a primal-dual-based DERMS relies on; these include packet losses, link failures, and delays. This information can help a DERMS operator decide on the specifications for the communication infrastructure it will invest in for the DERMS. Our evaluation is based on numerical simulations of a real-world feeder with around 2,000 nodes and a DERMS that controls 163 PV generators and 140 energy storage batteries. In general, we found that the DERMS becomes less resistant to communication issues as the information flows closer to the DERs implementing the controllable power injections.

communication delay↗

Impact of Quaternary-Pumped Storage Hydropower on Frequency Response of U.S. Western Interconnection with High Renewable Penetrations: Preprint

As renewable penetration increases in the United States, maintaining stability and reliability of low-inertia power grid by providing sufficient frequency control capability becomes a challenge. Advanced pumped storage hydro technologies (APSH) will be expected to play an important role for future grid as not only an energy supplier, but also as an ancillary services provider. This paper studies the impact of using quaternary pumped storage hydropower (Q-PSH), as one of the newly proposed APSH technology, to provide primary frequency response. To quantify the impact of Q-PSH on frequency response of the U.S. Western Interconnection, a user-defined dynamic model of Q-PSH is developed on the GE Positive Sequence Load Flow (PSLF) platform and is implemented in a set of detailed U.S. Western Electricity Coordination Council (WECC) planning cases in which renewable penetration levels are 20%, 40%, 60% and 80%. Simulation results show that Q-PSH can help improve frequency nadir and settling frequency comparing to the conventional PSH.

frequency response↗