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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

A methodology to compute the critical current limit in Nb3Sn magnets

Numerous experiments have shown that the loads applied to Nb3Sn strands and cables can reduce their critical current. Experiments, performed on uniaxially loaded strands, allowed to define clear laws to describe the evolution of the critical surface as a function of the applied current, field, temperature and strain. It is, however, still unclear how these laws can be applied to superconducting magnets. The present paper proposes a methodology to estimate the critical current and temperature margin reduction on superconducting magnets due to stress on the superconducting material. The methodology is tested on the MQXF magnets, a quadrupole developed for the High Luminosity LHC project, and successfully validated by comparing computed strain with data from strain gauge measurements. Overall, results suggested that, because of the stresses arising in winding during assembly, cool-down and powering, the current limit of the magnet is lower than the expected short sample limit, and that the most critical region does not coincide with the peak field location.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

5G Enabled Energy Innovation: Advanced Wireless Networks for Science (Workshop Report)

Rapidly expanding, new telecommunications infrastructure based on 5G technologies will disrupt and transform how we design, build, operate, and optimize scientific infrastructure and the experiments and services enabled by that infrastructure, from continental-scale sensor networks to centralized scientific user facilities, from intelligent Internet of Things devices to supercomputers. Concurrently, 5G will introduce, or exacerbate, challenges related to protecting infrastructure and associated scientific data as well as to fully leveraging opportunities related to expanded infrastructure scale and complexity. The U.S. Department of Energy (DOE) Office of Science operates scientific infrastructure, supporting some of the nation’s most advanced intellectual discoveries, spanning the country and including 30 world-class user facilities from supercomputers to accelerators. Along with field experiments and remote observatories, every aspect of DOE’s scientific enterprise will be affected by 5G, which amounts to a complete renovation of the underpinnings of the nation’s information infrastructure. In this report we explore the scientific opportunities and new research challenges associated with 5G, ranging from scalability to heterogeneity to cybersecurity. The rapid commercial deployment of 5G opens the opportunity to rethink and reinvent DOE’s scientific infrastructure and experimentation, from intelligent sensor networks at unprecedented scales to a digital continuum of cyberinfrastructure spanning low-power sensors, high-performance computing embedded within and at the edge of the network, and DOE’s large-scale user instrument and computing facilities. New programming paradigms, workflow and data frameworks, and AI-based system design, operation, and autonomous adaptation and optimization will be necessary in order to exploit these new opportunities. Field deployments and centralized scientific instruments can also be revolutionized, moving (without traditional performance penalties) from wired to wireless connectivity for data and control systems, improving flexibility, and opening new sensing modalities, including the use of the 5G electromagnetic spectrum itself as an environmental probe. For DOE science, in contrast to commercial 5G applications and settings, devices will be deployed in extreme environments such as cryogenically cooled instrument control systems and in remote settings with harsh conditions, requiring the design of new materials for RF communication and edge processing to operate in these regimes. Concurrently, 5G infrastructure comprises both hardware and sophisticated software systems - currently closed and proprietary. The cybersecurity challenges to 5G-empowered reinvention mirror the complexity and variety of new 5G features, from virtualization to private network slices to ubiquitous access. Research is also needed in order to accelerate the development of secure and open 5G software infrastructure, reducing reliance on hardware and software produced outside the United States and providing the transparency and rigorous evaluation and testing afforded through open software. Twelve broad research thrusts are laid out in four chapters, with a companion fifth chapter (and three additional research thrusts) underscoring the needs and opportunities for an aggressive testbed program co-designed by networking experts and scientists involved in the 15 research thrusts. The urgency of undertaking this research is fueled by a global, accelerating deployment of new telecommunications infrastructure that is designed for entertainment and commercial applications - barely scratching the surface of what 5G can do to extend U.S. leadership in scientific discovery.

42 ENGINEERING↗

Sci-Thur AM: YIS – 04: Stopping power-to-Cherenkov power ratios and beam quality specification for clinical Cherenkov emission dosimetry of electrons: beam-specific effects and experimental validation

Purpose: To advance towards clinical Cherenkov emission (CE)-based dosimetry by investigating beam-specific effects on Monte Carlo-calculated electron-beam stopping power-to-CE power ratios (SCRs), addressing electron beam quality specification in terms of CE, and validating simulations with measurements. Methods: The EGSnrc user code SPRRZnrc, used to calculate Spencer-Attix stopping-power ratios, was modified to instead calculate SCRs. SCRs were calculated for 6- to 22-MeV clinical electron beams from Varian TrueBeam, Clinac 21EX, and Clinac 2100C/D accelerators. Experiments were performed with a 20-MeV electron beam from a Varian TrueBeam accelerator, using a diffraction grating spectrometer with optical fiber input and a cooled back-illuminated CCD. A fluorophore was dissolved in the water to remove CE signal anisotropy. Results: It was found that angular spread of the incident beam has little effect on the SCR (≤ 0.3% at d{sub max}), while both the electron spectrum and photon contamination increase the SCR at shallow depths and decrease it at large depths. A universal data fit of R{sub 50} in terms of C{sub 50} (50% CE depth) revealed a strong linear dependence (R{sup 2} > 0.9999). The SCR was fit with a Burns-type equation (R{sup 2} = 0.9974, NRMSD = 0.5%). Below-threshold incident radiation was found to have minimal effect on beam quality specification (< 0.1%). Experiments and simulations were in good agreement. Conclusions: Our findings confirm the feasibility of the proposed CE dosimetry method, contingent on computation of SCRs from additional accelerators and on further experimental validation. This work constitutes an important step towards clinical high-resolution out-of-beam CE dosimetry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance characterization of metal-supported solid-oxide fuel cell stacks at elevated pressure

Here, in this paper, we present results on performance characterization of solid oxide fuel cell stacks at elevated pressures up to 6 bar a . Stacks are designed and built by Ceres Power, Ltd., and are rated at 1- and 5- kW e . Fuel streams include H 2 / N 2 mixtures, synthetic natural-gas reformate, and simulated anode tail-gas recycle. Elevated operating pressure serves to increase stack electrochemical performance, with the most-pronounced gains found up to 4 bar a . Pressurized operation reduces the extent of methane conversion, promoting more-uniform internal reforming and cooling within the stack. Such cooling is critical at higher-current conditions. A previously developed one dimensional computational stack model is used to provide insight into stack operation. Pressurization is found to slightly increase internal thermal gradients, while promoting more-uniform reactant-concentration profiles across the cell, reducing the likelihood of local fuel starvation. The high fuel dilution brought by anode recycle can modestly decrease stack performance; however, this decrease is recovered through elevated-pressure operation at 3 bar a . Anode recycle further promotes compositional uniformity across the cell. These results reflect that pressurized operation can promote stack performance, while potentially promoting long-term stack durability through uniformity in stack environmental conditions.

25 ENERGY STORAGE↗

Multiphysics Co-Optimization Design and Analysis of Double-Side Cooled Silicon Carbide-Based Power Module: Preprint

With the rapid growth of Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs), much more rigorous design targets have been set for automotive power electronics, including high power density, high reliability, and low cost. Novel power module and inverter technologies based on wide bandgap (WEG) semiconductors have been developed to meet these design targets, while providing optimal power semiconductor operating temperature and promising thermomechanical performance. Compared with conventional cooling techniques which are normally applied only on one side of power module, double-side cooling approach is now believed to be the solution to enable high power density and low thermal resistance of WEG semiconductor-based power electronics. In this work, we develop a three-phase power module that is double-sided cooled using dielectric fluid jet impingement. In each phase, four silicon carbide (SiC) power semiconductors are bonded to copper busbars without electrical insulation layers. A finite element analysis (FEA) model is created for thermal and thermomechanical analysis. Based on FEA modeling results, we select particular dimensions for a parametric study to optimize thermal and mechanical performance. Using a multi-objective genetic algorithm (MOGA)-based optimization method, we have minimized the maximum junction temperature and thermal stresses within the power module. The multiphysics co-optimization approach has enabled an efficient design process of power modules with greatly reduced computational cost, as compared to conventional processes that rely on exhaustive numerical simulations and iterations.

ADVANCED PROPULSION SYSTEMS↗

Technoeconomic Design Optimization for Fast Reactors. Part I: Workflow Development and Case Study for Small LFR District Energy Application

The nuclear industry is developing small reactor designs that can target a variety of deployment locations and energy products. Smaller nuclear designs have traditionally struggled to handle the steep trade-offs between size and cost that have historically incentivized large reactors. This motivates computational optimization of small reactors to minimize costs and quantify the trade-off between size and cost. In this paper, the cost/size trade-off for a small fast reactor is derived using a multi-objective genetic algorithm optimization, with steady-state, transient, and cost analysis of the fast reactor being performed. Specifically, the method is demonstrated on a small 10- to 120-MW(thermal) U-Pu-Zr–fueled lead-cooled fast reactor with a 10-year core life for district energy applications, which can have a thermal load compatible with this range. The results reinforced that fast reactor cores at the lower end of this power range suffer cost penalties due to critical mass considerations. It was found that high power density cores with strong reactivity swings and many control rods were favored over designing to minimize reactivity swing. Furthermore, this contrasts with some traditional configurations designed using engineering judgment and demonstrates that optimizers can find nontraditional but realistic solutions, along with demonstrating the value of incorporating cost functions into whole-reactor design optimization.

Fast reactor↗

High-Fidelity CFD Simulation of Mixed Convection and Forced Convection in a Pebble Bed Test Reactor Core

The Hermes low-power [35-MW(thermal)] reactor will be built and operated by Kairos Power LLC (KP) to demonstrate its fluoride salt-cooled high-temperature reactor (FHR) technology. In the KP FHR, the reactor core is composed of randomly packed pebbles with TRISO fuel particles inside with FLiBe flow upward through the core acting as a coolant. Previous numerical and experimental studies have been limited to either a small-size bed or to a lack of detailed measurements for heat transfer. Here, to address the lack of high-fidelity heat transfer data in a real-size FHR core, in this study, we simulated a pebble bed core with 34 374 pebbles randomly packed, similar to the Hermes reactor's size. The core radius was 14 times that of the pebble diameter, while the core height was 45 times. In this work, we were particularly interested in a mixed convection regime, where buoyancy is important. Therefore, we performed several large-eddy simulations at different Reynolds numbers (160 to 1000) with gravitational force included. The spectral element computational fluid dynamics code NekRS with graphics processing unit acceleration was used for this study. The low-Mach number approximation was applied to address property changes in the FLiBe and to account for buoyancy. A pure hexahedral mesh with 60 million elements was generated by the Voronoi cell method. At the polynomial order of 5, the total degrees of freedom was 7.5 billion. The developed case in this work is the first of its kind in terms of size and complexity. The local numerical data across the domain were obtained and compared with empirical correlations. After examining the data, we found the following conclusions. For pressure drop, the Reger correlation predicted less than a 5% error. On the other hand, for heat transfer, the Wakao correlation outperformed the others. Based on our findings, we recommend the use of the Wakao correlation for the Nusselt number calculation, and for pressure drop, the KTA (Kerntechnischer Ausschuss) correclation, among the available experimental correlations. In conclusion, the Reger direct numerical simulation-driven correlation for pressure drops should also be considered, given its best agreement with our calculations.

Mixed Convection↗

Assessment of Modeling and Simulation Technical Gaps in Safety Analysis of High Burnup Accident-Tolerant Fuels

The United States nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs), and it can be achieved more economically by using a risk-informed ecosystem, such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development activities to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: The deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety, and; The development of advanced applications that enable cost-effective plant operation. As part of the RISA Pathway, the Enhanced Resilient Plant (ERP) project refers to an NPP where safety is improved by implementing various measures, such as accident-tolerant fuels (ATF), diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, incorporation of augmented or new passive cooling systems, and utilization of advanced battery technologies. The objective of the ERP research is to use novel methods and computational tools to enhance existing reactors’ safety while reducing operational costs. Many U.S. utilities are targeting implementation of ATFs instead of traditional fuel in the near future since ATFs offer benefits in terms of improved performance and cost savings. The robust properties of ATF make it possible to extend the refueling cycle from 18 to 24 months in addition to the opportunity to use less of fuel. Extensive safety assessments are required to support regulatory requirements and obtain the approvals to use ATFs and the ERP project support the industry by developing novel effective methodologies for safety evaluations. In this project, the technical gaps in the modeling and simulation of the high burnup (HBU) ATF were assessed in terms of the fuel cladding behavior during the postulated accident events. The issues were identified in modeling the cladding deformation, the hydrodynamic change due to cladding deformation and the critical heat flux (CHF). The RELAP5-3D cladding deformation model was assessed by multiple verification tests and validation with the instrumented fuel assembly (IFA) experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Direct numerical simulation of reactor two-phase flows enabled by high-performance computing

Nuclear reactor two-phase flows remain a great engineering challenge, where the high-resolution two-phase flow database which can inform practical model development is still sparse due to the extreme reactor operation conditions and measurement difficulties. Owing to the rapid growth of computing power, the direct numerical simulation (DNS) is enjoying a renewed interest in investigating the related flow problems. A combination between DNS and an interface tracking method can provide a unique opportunity to study two-phase flows based on first principles calculations. More importantly, state-of-the-art high-performance computing (HPC) facilities are helping unlock this great potential. This paper reviews the recent research progress of two-phase flow DNS related to reactor applications. The progress in large-scale bubbly flow DNS has been focused not only on the sheer size of those simulations in terms of resolved Reynolds number, but also on the associated advanced modeling and analysis techniques. Specifically, the current areas of active research include modeling of sub-cooled boiling, bubble coalescence, as well as the advanced post-processing toolkit for bubbly flow simulations in reactor geometries. A novel bubble tracking method has been developed to track the evolution of bubbles in two-phase bubbly flow. Also, spectral analysis of DNS database in different geometries has been performed to investigate the modulation of the energy spectrum slope due to bubble-induced turbulence. In addition, the single-and two-phase analysis results are presented for turbulent flows within the pressurized water reactor (PWR) core geometries. The related simulations are possible to carry out only with the world leading HPC platforms. Furthermore, these simulations are allowing more complex turbulence model development and validation for use in 3D multiphase computational fluid dynamics (M-CFD) codes.

97 MATHEMATICS AND COMPUTING↗

Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions

High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.

Prantikos, Konstantinos [Argonne National Laborato↗

Initial assessment of metallurgical interaction of clad/base metal systems

Molten Salt Reactors (MSRs), both liquid fuel and sold fuel (e.g., the fluoride salt-cooled high temperature reactors, FHR’s) offer several advantages relative to conventional, water-cooled nuclear power systems. However, currently approved ASME structural materials have not been optimized for use in molten salt environments and demonstrating materials performance in molten salts is challenging. Toward the goal of enabling MSR designs, corrosion resistant claddings offer an attractive solution to help mitigate corrosion concerns and enable the use of approved ASME materials. This report assesses metals and alloys that may be effective as corrosion resistant cladding with select structural alloys. The structural alloys of interest are capable of use at high temperatures ≥600°C for times ≥100,000 hours. Potential cladding alloys were assessed based on their corrosion resistance in both chloride and fluoride based salts, physical properties, mechanical properties, nuclear performance, and resistance to environmental-assisted cracking. Additionally both thermodynamic and kinetic computational modeling were used to assess interactions between the base metal and the cladding. Results to date have identified three candidate alloy systems that help enable MSR designs; nickel, molybdenum, and tungsten based claddings. This report discusses pros and cons of each class of cladding and outlines future work to develop these base metal / clad systems into industrial products suitable for use in commercial nuclear power systems.

36 MATERIALS SCIENCE↗

Turbulence modeling of free shear layers for high performance aircraft

In many flowfield computations, accuracy of the turbulence model employed is frequently a limiting factor in the overall accuracy of the computation. This is particularly true for complex flowfields such as those around full aircraft configurations. Free shear layers such as wakes, impinging jets (in V/STOL applications), and mixing layers over cavities are often part of these flowfields. Although flowfields have been computed for full aircraft, the memory and CPU requirements for these computations are often excessive. Additional computer power is required for multidisciplinary computations such as coupled fluid dynamics and conduction heat transfer analysis. Massively parallel computers show promise in alleviating this situation, and the purpose of this effort was to adapt and optimize CFD codes to these new machines. The objective of this research effort was to compute the flowfield and heat transfer for a two-dimensional jet impinging normally on a cool plate. The results of this research effort were summarized in an AIAA paper titled 'Parallel Implementation of the k-epsilon Turbulence Model'. Appendix A contains the full paper.

Sondak, Douglas↗

COMSOL Results for the Nominal Steady-State Operation of the Proposed 95-MW LEU Silicide Core for HFIR Conversion

Engineering design studies are being performed to determine the feasibility of converting the High Flux Isotope Reactor (HFIR) from highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel at Oak Ridge National Laboratory. This activity is sponsored by the Office of Reactor Conversion and Uranium Supply (ORCUS) under the auspices of the US Department of Energy National Nuclear Security Administration’s Office of Material Management and Minimization. HFIR is a very high flux, pressurized, light water–cooled and moderated, flux trap–type research reactor with a core made of involute shaped U 3 O 8 /Al cermet fuel plates and coolant channels. HFIR currently operates at a thermal power of 85 MW and supports key national and international missions in neutron scattering, isotope production, materials/fuels irradiation, neutron activation analysis, gamma irradiation, and neutrino research. Advanced multiphysics computational fluid dynamics models have been developed in the COMSOL Multiphysics software to simulate the steady-state operating conditions for the proposed low-and high-density LEU U 3 Si 2 -Al (uranium silicide dispersion) fuel designs. The COMSOL models for HFIR inner and outer fuel element models incorporate various essential inputs and physics such as spatially dependent nuclear heat deposition, multilayer heat conduction, conjugate heat transfer, turbulent flows (using Reynolds-averaged Navier Stokes turbulence models), structural mechanics (thermal–structural interactions and fuel swelling), and oxide layer build-up. This report presents the best-estimate thermal hydraulics results for the low- and high-density optimized silicide LEU core designs at 95 MW steady-state nominal operation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

HPC Annual Report 2017

Sandia National Laboratories has a long history of significant contributions to the high performance community and industry. Our innovative computer architectures allowed the United States to become the first to break the teraFLOP barrier—propelling us to the international spotlight. Our advanced simulation and modeling capabilities have been integral in high consequence US operations such as Operation Burnt Frost. Strong partnerships with industry leaders, such as Cray, Inc. and Goodyear, have enabled them to leverage our high performance computing (HPC) capabilities to gain a tremendous competitive edge in the marketplace. As part of our continuing commitment to providing modern computing infrastructure and systems in support of Sandia missions, we made a major investment in expanding Building 725 to serve as the new home of HPC systems at Sandia. Work is expected to be completed in 2018 and will result in a modern facility of approximately 15,000 square feet of computer center space. The facility will be ready to house the newest National Nuclear Security Administration/Advanced Simulation and Computing (NNSA/ASC) Prototype platform being acquired by Sandia, with delivery in late 2019 or early 2020. This new system will enable continuing advances by Sandia science and engineering staff in the areas of operating system R&D, operation cost effectiveness (power and innovative cooling technologies), user environment and application code performance.

97 MATHEMATICS AND COMPUTING↗

New High-Strength Ni-based Alloys for High Temperature Service in Liquid Fluoride Salt Environments

The ever-increasing demand for higher system thermal efficiency necessitates the operation of power generation cycles and heat conversion systems for chemical processes at progressively higher temperatures. As the system operating temperature increases, fewer and fewer materials are available with the required mechanical properties and environmental compatibility. This dearth of materials is particularly acute in structural applications at temperatures above 700°C in liquid Fluoride Salt Cooled High-Temperature Reactors (FHRs) and Concentrated Solar Power (CSP) systems where liquid fluoride and/or liquid chloride salts are used for their high thermal capacity and low thermal conductivity to store and transport heat. It has been shown that fluorides and chlorides can degrade the properties of the material used for storage and transport due to corrosive effects thus affecting the performance and lifetime characteristics. Thus, materials used for storage and transport for fluoride/chloride-salt must at the minimum have good compatibility with the salt by exhibiting low corrosion rates at the required temperatures. In addition, since many of the components will be subject to stresses in service, they need to have sufficient strength to resist plastic deformation, and the resistance to time dependent creep deformation at these temperatures, and stress levels. Achieving the combination of these properties required for higher temperatures is particularly challenging considering traditionally, the expected lifetime of some of the components used in these systems are from 30 years (CSP) to 80 years (FHRs). Although 316 stainless steel and associated redox corrosion reduction techniques are being considered for use in the first generational systems, use of 316SS is limited to operating temperatures up to ~ 650°C, thereby resulting in lower reactor efficiencies. Hastelloy ® N, developed at ORNL in the 1950s-60s for molten salt service is currently the leading candidate FHR structural alloy but has inadequate creep properties at high temperatures. Using a computationally-guided approach, Oak Ridge National Laboratory had developed new high strength alloys strengthened by γ’ precipitates (about 2X the strength of Hastelloy ® N) in small laboratory-scale heats that show good resistance to corrosion by fluorides and improved creep rupture life at temperatures up to 850°C (U.S. Patent Application No. 13/833,357 entitled “High Strength Alloys for High Temperature Service in Liquid-Salt Cooled Energy Systems”- granted U. S. Patent No. 9,540,714).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Magnetic Reconnection in High-Energy Density Laboratory Plasmas

This project involved theoretical research on radiative magnetic reconnection in High-Energy Density (HED) plasmas, with applications to laboratory laser-plasma experiments [on facilities like OMEGA (LLE) and NIF (LLNL)] and to astrophysical systems, such as accreting black hole coronae and magnetospheres of strongly magnetized neutron stars (magnetars and pulsars). Relativistic magnetic reconnection is a leading candidate mechanism for powering high-energy flares and persistent emission in various astrophysical systems.The extremely high energy density found in many of these systems dictates that reconnection should proceed in the radiative regime, where radiation back reaction on the electrons (and, if present, positrons), manifested, e.g., as radiative cooling and radiative drag on reconnection-driven bulk flows, plays an important role. Moreover, under some conditions, the energy of the emitted photons is so high that they can readily produce electron-positron pairs, e.g., in black-hole accretion disk coronae and in pulsar and magnetar magnetospheres. Due to recent rapid developments of experimental capabilities in HED physics, we can now for the first time seriously contemplate studying these exciting physical processes in the laboratory. This project investigated fundamental physics of magnetic reconnection in this novel regime, by performing several computational [using radiative particle-in-cell (PIC) simulations] and theoretical studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

HVAC load Disaggregation using Low-resolution Smart Meter Data

Traditional non-intrusive load monitoring (NILM) methods are effective for load disaggregation using high resolution smart meter data collected by power quality meters. However, smart meter data collected and stored by utilities are normally 15-, 30- or 60-minute in granularity, making most NILM methods ineffective. This paper presents a novel sequential energy disaggregation (SED) algorithm for extracting heating, ventilation, and air conditioning (HVAC) energy consumptions from residential and small commercial building loads using 30 min smart meter data. Large, infrequently-used loads are first detected and removed from the total building energy consumption. Then, base energy consumption curves, defined as the energy consumption without heating and cooling loads, are identified using the mild-day method. After that, the heating and cooling loads are extracted using an average value subtracting method. Simulation results with real data show that the proposed SED method is computationally efficient, simple to implement and robust in performance across different types of buildings.

Liang, Ming↗