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At least 973 records · Page 54

Formation of turing patterns in strongly magnetized electric discharges

Abstract Pattern formation and self-organization in many biological and non-biological systems can be explained through Turing’s activator-inhibitor model. Here we show how this model can be employed to describe the formation of filamentary structures in a low-pressure electric discharge exposed to a strong magnetic field. Theoretical investigation reveals that the fluid equations describing a magnetized plasma can be rearranged to take the mathematical form of Turing’s activator-inhibitor model. Numerical simulations based on the equations derived from this approach could reproduce the various patterns observed in the experiments. Also, it is shown that a density imbalance between electrons and ions exists in the bulk of the magnetized plasma that generates an electric field structure transverse to the applied magnetic field. This electric field is responsible for the stability of the filamentary patterns in the magnetized plasma over time scales much longer than the characteristic time scales of the electric discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Exploring the Potential of Residual Impurities in Germanium Detectors for MeV-Scale Dark Matter Detection

Abstract The direct detection of MeV-scale dark matter (DM) particles hinges on achieving an exceptionally low-energy detection threshold. Germanium (Ge) detectors, meticulously tailored with precise impurity compositions, hold the potential to enhance sensitivity to energy levels below the sub-electronvolt (sub-eV) range. This study explores the behavior of residual impurities inherent to Ge detectors at helium temperatures, unveiling a captivating freeze-out phenomenon leading to the formation of excited localized states known as dipole states. Using compelling evidence from relative capacitance measurements obtained from two detectors, we elucidate the transition of impurity atoms from free charge states to these dipole states as the temperature drops from 11 to 6.5 K. Our investigation comprehensively covers the intricate formation of these dipole states in bothn-type andp-type impurities. Furthermore, we shed light on the electric field generated by these dipole states, revealing their ability to trap charges and facilitate the creation of cluster dipole states. Confirming findings from previous measurements, we establish that these excited dipole states exhibit a binding energy of less than 10 meV, offering an exceptionally low detection threshold for MeV-scale DM. Building upon this concept, we propose the development of a 1-kg Ge detector with internal charge amplification—an innovative approach poised to surpass electrical noise and enable the detection of MeV-scale DM with unprecedented sensitivity.

Physics↗

Harnessing Ocean Thermal Gradients Using Thermoelectric Based Submersibles for Ocean Power Applications

The urgent need for energy solutions in marine environments has accelerated the development of innovative technologies capable of leveraging natural resources for power generation. This study introduces a buoyancy-driven submersible system designed to harness ocean thermal gradients using thermoelectric generators (TEGs) and phase change materials (PCMs). The technology aims to provide autonomous power to offshore aquaculture farms, unmanned underwater vehicles (UUVs), offshore platform illumination, and ocean sensors, significantly reducing dependence on fossil fuels. Ocean thermal gradients, especially prevalent in mid-latitude regions, exhibit temperature differences between surface and deep waters ranging from 7 degrees Celsius to 30 degrees Celsius depending on seasonal variations. The proposed submersible technology utilizes TEGs to convert thermal energy from these gradients into electrical power, generating between 0.2 and 0.5 watts, while PCMs are employed to store and regulate this energy, ensuring a stable and continuous power supply. The buoyancy-driven mechanism of the submersible enhances its capability to navigate through varying depths, optimizing its exposure to different thermal gradients and maximizing energy harvesting. The performance of this submersible system is analyzed through detailed thermodynamic assessments and computational fluid dynamics (CFD) modeling focused on heat transfer. These analyzes consider real-world ocean temperature profiles and seek to refine the interaction between TEGs and PCMs to optimize energy extraction. The evaluation encompasses several key performance metrics, including power output and energy efficiency. Results confirm the potential of this innovative technology to provide a continuous and reliable power source for marine applications. By demonstrating the feasibility of using ocean thermal gradients for energy generation, this study contributes to the broader efforts of innovation in energy technologies for harsh, remote marine environments. The implementation of such promises is significant advancements in the autonomy of marine operations. The ongoing research will further investigate scalability ensuring that the system can be effectively adapted to various marine settings and operational demands.

16 TIDAL AND WAVE POWER↗

Small Hydropower Interconnections: Small Hydropower in the United States

Small hydropower projects, which we define as generators below 20 MW in capacity have been the predominant source of hydropower growth over the past decade and create the most cost-effective and environmentally permissible avenues for new hydropower installation in the United States (DOE 2016; Johnson et al. 2018). Small hydropower developers across the United States have found that interconnecting these projects with the grid can be challenging due to unexpected costs and schedule overruns. Understanding the interconnection challenges and improving the process may allow more small hydropower projects to be successful. Noting these challenges, the U.S. Department of Energy Water Power Technologies Office enlisted Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) to investigate the small hydropower interconnection landscape across the United States. To begin to analyze the existing interconnection processes and challenges facing small hydropower, the state of small hydropower development in the U.S. must first be described to understand the characteristics of the industry. The first in a series, this paper presents the state of small hydropower projects in the U.S. to describe their type, location, and size based on data extracted from the HydroSource database (ORNL 2020). The following papers in the series will detail the variety of state interconnection processes to connect power generators with the grid (“Small Hydropower Interconnections: State Interconnection Processes”), analyze these interconnection processes (“Small Hydropower Interconnections: Analysis of Interconnection Processes”), and present best practices in interconnection processes (“Small Hydropower Interconnections: Best Practices”) that will help overcome barriers to future small hydropower development.

13 HYDRO ENERGY↗

Electric Grid Visualization: Hourly Renewable Generation, Load, Unserved Load, and Locational Marginal Prices during a Heatwave

Visualization of hourly solar and wind generation, load, unserved load, and locational marginal energy prices in the western United States during a July 22-28 heatwave event in 2018, 2058, and 2098. In addition to hourly time series data of each of the parameters, choropleth maps showing the hourly value for each balancing authority are provided.

Climate Change↗

Framework for optimization of long-term, multi-period investment planning of integrated urban energy systems

In order to achieve stringent greenhouse gas emission reductions, a transition of our entire energy system from fossil to renewable resources needs to be designed. Such an energy transition brings two main challenges: most renewables generate variable electric energy, yet most demand is currently not electric (carrier mismatch) and does not always manifest at the same time as supply (temporal mismatch). Integrating multiple energy infrastructures can address both challenges by using the synergy between different energy carriers; building on existing infrastructure, while allowing a robust and flexible integration of the new. This paper proposes an optimization framework for long-term, multi-period investment planning of urban energy systems in an integrated manner. We formulate it as a mixed-integer linear program, combining a capacitated facility location with a multi-dimensional, capacitated network design problem. It includes generation and network expansion planning as well as interconnections between networks and storage infrastructure for each energy system. It can incorporate pathway effects like techno-economic developments, policy measures, and weather variations. The intended use is to support urban decision makers with long-term investment planning, though it can be tailored to fit other geographical or temporal scales. We demonstrate the model using two cases based on an average city in The Netherlands, which wants to reduce its CO 2 -emissions with 95% by 2050. In the first case, we include explicit carbon-emission constraints to study the effects of the carrier mismatch. In the second case, we implement interannual weather variations to analyze the temporal mismatch. The results give valuable insights into the energy transition design strategy for urban decision makers. They also show the future potential, as well as the computational challenges of the optimization framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributed Energy Resource Management Systems: Preserving Customer Privacy through K-Anonymity

The smart grid represents the next generation of electricity distribution systems that utilizes recent technological innovations. It uses digital communication between its components and entities to attain more automation, self-sufficiency, and reliability. One of the many concerns in smart grid digital communication discussions is the possibility of violating customers’ privacy. Violating customers’ privacy imposes a significant barrier as smart grid desirable attributes are tightly tied to customers’ participation. Employing privacy models can address concerns regarding information privacy in smart grid digital communication. In this work, we provide an approach to utilizing K-anonymity to ensure data within the system excludes Personally Identifiable Information. Results suggest that a dynamically generated generalization hierarchy minimizes information loss incurred by the anonymization process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

State-of-the-art short-term electricity market operation with solar generation: A review

With the accelerating penetration of solar energy in energy systems, market operations concerning the solar-associated intermittency are widely discussed. How to correctly model the solar generation in the market and solve the uncertainty-based operation problems call for solutions. Unlike other renewable resources, solar power can be more easily applied to the demand side through behind-the-meter installations in a distributed manner with significant future extensibility. The corresponding operational rules in the markets are largely being revised. Over the past two decades, with the development of deregulated power markets, numerous studies related to uncertainty-based market operations tend to transform the market from a deterministic and centralized framework to a stochastic and decentralized one. As the relevant literature is most recent, this paper reviews their contributions to electricity market operations with solar integration and underlines the research directions of this topic and ongoing industry practices. A thorough review of the electricity markets worldwide with solar energy is provided. A variety of proposed mathematical solutions to the problem are also addressed.

14 SOLAR ENERGY↗

Polarization Selectivity of Aloof-Beam Electron Energy-Loss Spectroscopy in One-Dimensional ZnO Nanorods

Orientation-dependent electronic properties of wurtzite zinc oxide nanorods are characterized by aloof-beam electron energy-loss spectroscopy (EELS) carried out in a scanning transmission electron microscope (STEM). The two key crystal orientation differentiating transitions specific to the in-plane (13.0 eV) and out-of-plane (11.2 eV) directions with respect to the wurtzite structure are examined by first-principles density-functional theory calculations. We note some degree of orientation dependence at the onset of direct band gap transition near 3.4 eV. We demonstrate that good polarization selectivity can be achieved by placing the electron probe at different locations around the specimen with increasing impact parameter while keeping the beam-specimen orientation fixed. The observed results are qualitatively elucidated in terms of the perpendicular electric fields generated by the fast electron (60 kV) used in the microscope. The fact that good polarization selectivity can be achieved by aloof-beam EELS without the requirement of sample reorientation is an attractive aspect from the characterization method point of view in the STEM-EELS community.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Low-Temperature Geothermal Resources: Relevant Data and PFA Methods to Reduce Development Risk: Preprint

This project is part of a larger national effort focused on demonstrating the multi-faceted value of integrating low-temperature geothermal resources into national decarbonization strategies and community energy plans. Low-temperature geothermal resources are defined as reservoirs-natural or engineered-with temperatures < 150 degrees C. While the focus in the NREL effort is on geothermal heating and cooling (GHC), resources at the upper end of this temperature range can also be used for small-scale power generation. However, low-temperature geothermal resources have not been studied as extensively as higher-temperature geothermal resources. We identified three major classes of low-temperature geothermal play types: sedimentary basins, orogenic systems, and radiogenic systems. We developed workflows for evaluating the potential of these resources building off the Play Fairway Analysis (PFA) approach to de-risking geothermal exploration. This PFA-based approach to low-temperature geothermal resources includes: (1) identifying relevant data; (2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, economic criteria); (3) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and (4) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool. This project will facilitate future deployment of GHC by providing data, tools, and workflows applicable to low-temperature geothermal resources.

favorability maps↗

Low-Temperature Geothermal Resources: Relevant Data and PFA Methods to Reduce Development Risk

This project is part of a larger national effort focused on demonstrating the multi-faceted value of integrating low-temperature geothermal resources into national decarbonization strategies and community energy plans. Low-temperature geothermal resources are defined as reservoirs-natural or engineered-with temperatures < 150 degrees C. While the focus in the NREL effort is on geothermal heating and cooling (GHC), resources at the upper end of this temperature range can also be used for small-scale power generation. However, low-temperature geothermal resources have not been studied as extensively as higher-temperature geothermal resources. We identified three major classes of low-temperature geothermal play types: sedimentary basins, orogenic systems, and radiogenic systems. We developed workflows for evaluating the potential of these resources building off the Play Fairway Analysis (PFA) approach to de-risking geothermal exploration. This PFA-based approach to low-temperature geothermal resources includes: (1) identifying relevant data; (2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, economic criteria); (3) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and (4) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool. This project will facilitate future deployment of GHC by providing data, tools, and workflows applicable to low-temperature geothermal resources.

favorability maps↗

SMALL UNMANNED MARINE HYDROKINETIC PLATFORMS FOR POWER GENERATION IN COASTAL AND TIDAL WATERS

The feasibility and optimization of small unmanned mobile marine hydrokinetic (MHK) energy platforms for harvesting marine current energy in coastal and tidal waters are examined. A case study of a platform based on the use of a free-surface waterwheel (FSWW) mounted on an autonomous unmanned surface vehicle (USV) was conducted. Such platforms can serve as recharging stations for aerial drones (UAVs), enabling extension of the UAVs’ autonomous operating time. An unmanned MHK platform potentially meets this need with sustainable power harvested from water currents. For the case study, six different waterwheel configurations were field-tested in the Intracoastal Waterway of South Florida in support of determining the configuration that produced the most power. Required technologies for unmanned operations of the MHK platform were developed and tested. The data from the field-testing were analyzed to develop an empirical relation between the wheel’s theoretical hydrokinetic power produced and the mechanical power harnessed by the MHK platform with various waterwheel configurations during field-testing. The field data was also used to determine the electrical power generated by the FSWW configurations during field-testing. The study has led to the development of standardized testing procedures. The empirical relation is used to examine predicted power production through scaling up different physical aspects of the waterwheel.

McKinney, Adriana↗

New Insights into the Charge-Transfer-to-Solvent Spectrum of Aqueous Iodide: Surface versus Bulk

Liquid phase charge-transfer-to-solvent (CTTS) transitions are important, as they serve as photochemical routes to solvated electrons. Here in this work, broadband deep-ultraviolet electronic sum frequency generation (DUV-ESFG) and two-photon absorption (2PA) spectroscopic techniques were used to assign and compare the nature of the aqueous iodide CTTS excitations at the air/water interface and in bulk solution. In the one-photon absorption (1PA) spectrum, excitation to the 6s Rydberg-like orbital (5p → 6s) gives rise to a pair of spin–orbit split iodine states, 2 P 3/2 and 2 P 1/2 . In the 2PA spectra, the lower-energy 2 P 3/2 peak is absent and the observed 2PA peak, which is ~0.14 eV blue-shifted relative to the upper 2 P 1/2 CTTS peak seen in 1PA, arises from 5p → 6p electronic promotion. The band observed in the ESFG spectrum is attributed to mixing of excited states involving 5p → 6p and 5p → 6s promotions caused by both vibronic coupling and the external electric field generated by asymmetric interfacial solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning

Proton exchange membrane fuel cells, consuming hydrogen and oxygen to generate clean electricity and water, suffer acute liquid water challenges. Accurate liquid water modelling is inherently challenging due to the multi-phase, multi-component, reactive dynamics within multi-scale, multi-layered porous media. In addition, currently inadequate imaging and modelling capabilities are limiting simulations to small areas (<1 mm 2 ) or simplified architectures. Herein, an advancement in water modelling is achieved using X-ray micro-computed tomography, deep learned super-resolution, multi-label segmentation, and direct multi-phase simulation. The resulting image is the most resolved domain (16 mm 2 with 700 nm voxel resolution) and the largest direct multi-phase flow simulation of a fuel cell. This generalisable approach unveils multi-scale water clustering and transport mechanisms over large dry and flooded areas in the gas diffusion layer and flow fields, paving the way for next generation proton exchange membrane fuel cells with optimised structures and wettabilities.

25 ENERGY STORAGE↗

A Reduced-Order Model of a Nuclear Power Plant with Thermal Power Dispatch

This paper presents reduced-order modeling of thermal power dispatch (TPD) from a pressurized water reactor (PWR) for providing heat to nearby heat consuming industrial processes that seek to take advantage of nuclear heat to reduce carbon emissions. The reactor model includes the neutronics of the reactor core, thermal–hydraulics of the primary coolant cycle, and a three-lump model of the steam generator (SG). The secondary coolant cycle is represented with quasi-steady state mass and energy balance equations. The secondary cycle consists of a steam extraction system, high-pressure and low-pressure turbines, moisture separator and reheater, high-pressure and low-pressure feedwater heaters, deaerator, feedwater and condensate pumps, and a condenser. The steam produced by the SG is distributed between the turbines and the extraction steam line (XSL) that delivers steam to nearby industrial processes, such as production of clean hydrogen. The reduced-order simulator is verified by comparing predictions with results from separate validated steady-state and transient full-scope PWR simulators for TPD levels between 0% and 70% of the rated reactor power. All simulators indicate that the flow rate of steam in the main steam line and turbine systems decrease with increasing TPD, which causes a reduction in PWR electric power generation. The results are analyzed to assess the impact of TPD on system efficiency and feedwater flow control. Due to the simplicity of the proposed reduced-order model, it can be scaled to represent a PWR of any size with a few parametric changes. In the future, the proposed reduced-order model will be integrated into a power system model in a digital real-time simulator (DRTS) and physical hardware-in-the-loop simulations.

08 HYDROGEN↗

Comparison of temporal resolution selection approaches in energy systems models

Capacity expansion models for the power sector are used to project future decisions over the coming decades by simulating investment and operation decisions for the use of electricity. Due to model performance constraints, these models typically do not explicitly simulate every hour within a year, but instead simulate representative time segments (groups of hours). This paper evaluates different approaches for selecting time segments across three methods: sequential, categorical, and clustering, across a wide range of time-segment quantities, for a total of 204 temporal profiles. To measure the performance of each profile's ability to accurately represent data, the root-mean-square-error of each profile's time segments are compared to the data's original hourly data. The temporal alignment across regions is also measured (i.e., how often windy days align across regions). Different spatial resolutions were applied for a subset of the temporal selection methods to investigate the impact spatial resolution has on performance. This paper provides a framework for measuring the value of different temporal selection methods and of adding more granular data to energy system models. Overall, multi-criteria clustering yields the lowest root-mean-square-error across all datasets evaluated and provides a holistic view of the intertwined relationships between renewable generation and electricity demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods

The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) is supporting the Geothermal Heating and Cooling Geospatial Datasets and Analysis project conducted by the National Renewable Energy Laboratory (NREL) as part of a broader effort to demonstrate the multi-faceted value of integrating geothermal power and geothermal heating and cooling (GHC) technologies into national decarbonization plans and community energy plans. Currently, there is a need to establish baseline low-temperature geothermal resource datasets and evaluate methods for deploying these technologies to provide the basis for supporting private sector investment. This project is focused on collecting baseline datasets, updating conceptual models, and creating Play Fairway Analysis (PFA) workflows for low-temperature (<150 degrees Celsius) geothermal resources of different geothermal play types (i.e., sedimentary basin, orogenic belts, and radiogenic geothermal play types) that could be used for geothermal heating and cooling (GHC), combined heat and power (CHP), and other geothermal direct uses (GDU) applications. Low-temperature geothermal resources are defined as reservoirs - natural or engineered - with temperatures <150 degrees Celsius. While the focus in the NREL effort is on GHC, resources at the upper end of this temperature range can also be used for small-scale power generation. This project does not include Ground Source Heat Pumps (GSHPs) technologies because they can be effectively developed almost anywhere. Low-temperature geothermal resources have not been studied as extensively as higher- to medium-temperature geothermal resources, but there is recent interest in improving understanding of these types of resources with an uptick of interest in geothermal technologies for decarbonizing heating and cooling systems. In addition, Enhanced Geothermal Systems (EGS) and other emerging technologies for exploiting petrothermal resources have opened the possibility of utilizing deep sedimentary basin systems, where porous media provide permeability and high temperatures can be reached at great depths. This project takes the approach of classifying low- temperature geothermal resources by geothermal play type (GPT). We defined and characterized three major classes of low-temperature GPT: sedimentary basins, orogenic systems, and radiogenic systems. We develop methodologies for evaluating and analyzing the potential for these resources building off the PFA approach to de-risking geothermal exploration and characterization. The proposed PFA approach for low-temperature geothermal resources includes: 1) identifying relevant data (e.g., datasets such bottom-hole temperatures from oil and gas wells, heat flow data, Quaternary faults and stress field data, geophysical data, etc.); 2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, and economic criteria); 3) uncertainty quantification; 4) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and 5) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool (RSAT). This project should facilitate future deployment of GHC, CHP, and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources. Increased deployment of GHC and GDU will help achieve national and local decarbonization goals.

15 GEOTHERMAL ENERGY↗

Non-Reciprocity, Metastability, and Dynamic Reconfiguration in Co-Assembly of Active and Passive Particles

Living organisms often exhibit non-reciprocal interactions where the forces acting on the objects are not equal in magnitude or opposite in direction. The combination of reciprocal and non-reciprocal interactions between synthetic building blocks remains largely unexplored. Here, out-of-equilibrium assemblies of non-motile isotropic passive and metal-patched motile active particles are formed by overlapping bulk interactions with directed self-propulsion. An external alternating current (AC) electric field generates concurrent dipolar and induced-charge electrophoretic forces between the particles which are evaluated using microscopy. The interaction force measurements allow to determine the degree of reciprocity in interactions, which is tunable by designing the active particle and its trajectory. While linearly-propelled active particles evade assembly with passive particles, helically propelled active particles form active-passive clusters with dynamic reconfiguration and long-lived metastability. Large clusters display programmable fluctuations and reconfigurability by controlling the fraction of active particles. The study establishes principles of integrating reciprocal and non-reciprocal interactions in guided colloidal assembly of reconfigurable metastable structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗