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DOE OSTI2024

Electrification Analysis: Container Ports' Cargo Handling Equipment

This one-page highlight details the key takeaways from a project that utilized NREL's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline, the Electrification Analysis of Container Ports' Cargo Handling Equipment project. This project created a scalable solution to model energy demand per shipping container moved (kWh/TEU) for an all-electric cargo handling equipment fleet located at a maritime port. The model allows stakeholders to understand energy demand at each electric vehicle (EV) equipment level and is easily scalable to container demand and EV adoption rate projections.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Systems and methods for data analytics for virtual energy audits and value capture assessment of buildings

A system may provide virtual energy audits of one or more target buildings. The system may retrieve weather data and energy usage data specific to a given target building from a weather server and a utility server, respectively. The system may store predefined building characteristics corresponding to the given target building in local memory. Based on the weather data, energy usage data, and/or predefined building characteristics, the system may generate one or more building markers that characterize the energy usage and efficiency of the given target building. Building efficiency diagnostics and energy conservation prognostics may be generated based on the building markers and may be sent by the system to be displayed via a user interface of a client device. The energy conservation prognostics may include one or more energy conservation measure recommendations and corresponding predicted cost/energy savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Dark Energy Survey Year 3 results: Cosmology from cosmic shear and robustness to data calibration

This work, together with its companion paper, Secco, Samuroff et al., presents the Dark Energy Survey Year 3 cosmic shear measurements and cosmological constraints based on an analysis of over 100 million source galaxies. With the data spanning 4143 deg 2 on the sky, divided into four redshift bins, we produce the highest significance measurement of cosmic shear to date, with a signal-to-noise of 40. We conduct a blind analysis in the context of the ΛCDM model and find a 3% constraint of the clustering amplitude, S 8 ≡ σ 8 (Ω m /0.3) 0.5 = 0.759$^{+0.025}_{-0.023}$. A ΛCDM-Optimized analysis, which safely includes smaller scale information, yields a 2% precision measurement of S 8 = 0.772$^{+0.018}_{-0.017}$ that is consistent with the fiducial case. The two low-redshift measurements are statistically consistent with the Planck Cosmic Microwave Background result, however, both recovered S 8 values are lower than the high-redshift prediction by 2.3σ and 2.1σ (ρ-values of 0.02 and 0.05), respectively. The measurements are shown to be internally consistent across redshift bins, angular scales and correlation functions. The analysis is demonstrated to be robust to calibration systematics, with the S 8 posterior consistent when varying the choice of redshift calibration sample, the modeling of redshift uncertainty and methodology. Similarly, we find that the corrections included to account for the blending of galaxies shifts our best-fit S 8 by 0.5σ without incurring a substantial increase in uncertainty. We examine the limiting factors for the precision of the cosmological constraints and find observational systematics to be subdominant to the modeling of astrophysics. Specifically, we identify the uncertainties in modeling baryonic effects and intrinsic alignments as the limiting systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Combining Dark Energy Survey Science Verification data with near-infrared data from the ESO VISTA Hemisphere Survey

We present the combination of optical data from the Science Verification phase of the Dark Energy Survey (DES) with near-infrared (NIR) data from the European Southern Observatory VISTA Hemisphere Survey (VHS). The deep optical detections from DES are used to extract fluxes and associated errors from the shallower VHS data. Joint seven-band ( grizYJK ) photometric catalogues are produced in a single 3 sq-deg dedicated camera field centred at 02h26m-04d36m where the availability of ancillary multiwavelength photometry and spectroscopy allows us to test the data quality. Dual photometry increases the number of DES galaxies with measured VHS fluxes by a factor of ~4.5 relative to a simple catalogue level matching and results in a ~1.5 mag increase in the 80 per cent completeness limit of the NIR data. Almost 70 per cent of DES sources have useful NIR flux measurements in this initial catalogue. Photometric redshifts are estimated for a subset of galaxies with spectroscopic redshifts and initial results, although currently limited by small number statistics, indicate that the VHS data can help reduce the photometric redshift scatter at both z < 0.5 and z > 1. We present example DES+VHS colour selection criteria for high-redshift luminous red galaxies (LRGs) at z ~ 0.7 as well as luminous quasars. Using spectroscopic observations in this field we show that the additional VHS fluxes enable a cleaner selection of both populations with <10 per cent contamination from galactic stars in the case of spectroscopically confirmed quasars and <0.5 per cent contamination from galactic stars in the case of spectroscopically confirmed LRGs. The combined DES+VHS data set, which will eventually cover almost 5000 sq-deg, will therefore enable a range of new science and be ideally suited for target selection for future wide-field spectroscopic surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Mass and galaxy distributions of four massive galaxy clusters from Dark Energy Survey Science Verification data

We measure the weak lensing masses and galaxy distributions of four massive galaxy clusters observed during the Science Verification phase of the Dark Energy Survey (DES). This pathfinder study is meant to (1) validate the Dark Energy Camera (DECam) imager for the task of measuring weak lensing shapes, and (2) utilize DECam's large field of view to map out the clusters and their environments over 90 arcmin. We conduct a series of rigorous tests on astrometry, photometry, image quality, point spread function (PSF) modelling, and shear measurement accuracy to single out flaws in the data and also to identify the optimal data processing steps and parameters. We find Science Verification data from DECam to be suitable for the lensing analysis described in this paper. The PSF is generally well behaved, but the modelling is rendered difficult by a flux-dependent PSF width and ellipticity. We employ photometric redshifts to distinguish between foreground and background galaxies, and a red-sequence cluster finder to provide cluster richness estimates and cluster-galaxy distributions. By fitting Navarro-Frenk-White profiles to the clusters in this study, we determine weak lensing masses that are in agreement with previous work. For Abell 3261, we provide the first estimates of redshift, weak lensing mass, and richness. In addition, the cluster-galaxy distributions indicate the presence of filamentary structures attached to 1E 0657-56 and RXC J2248.7-4431, stretching out as far as 1. (approximately 20 Mpc), showcasing the potential of DECam and DES for detailed studies of degree-scale features on the sky.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

Wireless Sensor Network for Improving the Energy Efficiency of Data Centers

Data centers occupy less than 2% of the federally owned portfolio under the jurisdiction, custody or control of the U.S. General Services Administration (GSA), but represent nearly 5% of the agency’s overall energy budget. Assuming that energy use in GSA’s data centers tracks with industry averages, GSA can anticipate that data center energy use will grow at an annual rate of 15%, a doubling of energy use every five years.1 In fact, energy is the single largest operating expense for most data centers. Improving the energy performance of data center systems supports progress toward meeting federally mandated greenhouse gas emission-reduction goals, while reducing operating and energy costs and allowing for greater flexibility in future expansion by eliminating the need to provide additional power and cooling. Studies sponsored by the U.S. Department of Energy (DOE) and the U.S. Environmental Protection Agency (EPA) have shown that energy use can be reduced by 25% through implementation of best practices and commercially available technologies. The present study evaluated the effectiveness of a strategy to cost- effectively improve the efficiency of data center cooling, which is the single largest non-IT load. The technology that was evaluated consists of a network of wireless sensors—including branch circuit power monitors, temperature sensors, humidity sensors, and pressure sensors, along with an integrated software product to help analyze the collected data. The technology itself does not save energy; however, its information collection and analysis features enable users to understand operating conditions and identify problem areas. In addition, data obtained by this technology can be input into assessment tools that can identify additional best practice measures. Energy savings result from the implementation of the best practices. The study was conducted to validate the premise that providing data center operators with detailed, real- time measurement of environmental parameters and power consumption enables them to establish baseline performance, discover areas of sub-optimal performance, and identify concrete opportunities for improvement.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2012

Campbell Creek Research Homes (FY 2012 Annual Performance Report)

The Campbell Creek project is funded and managed by the Tennessee Valley Authority (TVA) Technology Innovation, Energy Efficiency, Power Delivery and Utilization Office. Technical support is provided under contract by the Oak Ridge National Laboratory (ORNL) and the Electric Power Research Institute (EPRI). The project was designed to determine the relative energy efficiency of typical new home construction, energy efficiency retrofitting of existing homes, and high-performance new homes built from the ground up for energy efficiency. This project will compare three houses that represented the current construction practices: a base case (Builder House—CC1); a modified house that could represent a major energy-efficient retrofit (Retrofit House—CC2); and a house constructed from the ground up to be a high-performance home (High Performance House—CC3). To enable a valid comparison, it was necessary to simulate occupancy in all three houses and heavily monitor the structural components and the energy usage by component. All three houses are two story, slab on grade, framed construction. CC1 and CC2 are approximately 2,400 ft 2 . CC3 has a pantry option, primarily used as a mechanical equipment room, that adds approximately 100 ft 2 . All three houses are all-electric (with the exception of a gas log fireplace that is not used during the testing) and use air-source heat pumps for heating and cooling. The three homes are located in Knoxville in the Campbell Creek Subdivision. CC1 and CC2 are next door to each other and CC3 is across the street and a couple of houses down. The energy data collected will be used to determine the benefits of retrofit packages and high-performance new home packages. There are over 300 channels of continuous energy performance and thermal comfort data collection in the houses (100 for each house). The data will also be used to evaluate the impact of energy-efficient upgrades on the envelope, mechanical equipment, and demand-response options. Each retrofit will be evaluated incrementally, by both short-term measurements and computer modeling, using a calibrated model. This report is intended to document the comprehensive testing, data analysis, research, and findings within the January 2011 through October 2012 timeframe at the Campbell Creek research houses. The following sections will provide an in-depth assessment of the technology progression in each of the three research houses. A detailed assessment and evaluation of the energy performance of technologies tested will also be provided. Finally, lessons learned and concluding remarks will be highlighted.

Annual Report↗

DOE OSTI2025

Artificial Intelligence for Enhancing Multiscale Analysis: Buildings Focus

This project aims to develop multi-scale building energy data, potentially improving the representation of the U.S. buildings sector in GCAM-USA, an U.S.-focused human-energy-Earth systems model. Existing building energy datasets are typically limited to national or regional levels, which constrains the ability of models to capture fine-scale human-energy-Earth systems interactions and reduces their relevance for decision-making on issues such as energy security, resilience, and energy planning. By leveraging AI and advanced data integration methods, this work fuses multiple existing datasets to enhance the physical and geographic representation of both residential and commercial building energy use. So far, progress includes processing residential building data, designing the data structure for commercial buildings, and testing AI approaches for integrating datasets and addressing spatial-temporal gaps. This effort can not only advances GCAM-USA’s capability in modeling the buildings sector but also supports broader DOE missions, such as developing digital testbeds, enhancing grid resilience analysis, and improving building–energy system modeling at decision-relevant scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Performance Demonstration of an Occupancy Sensor-enabled Integrated Solution for Commercial Buildings

Traditionally, a single-loop fixed-gain controller is applied to supply fan (SF) and cooling coil (CC) valve controls while a fixed-damper position control is applied to outdoor air (OA) damper control at air handling units (AHUs) in commercial buildings. With the increasing application of occupancy sensors, the information generated by occupancy sensors is applied to not only reduce the electricity loads from lighting and controllable plug loads, but also reset OA intake and minimum supply airflow setpoints. Meanwhile, these intermittent operation actions greatly elevate the dynamics of AHU systems, which may introduce unstable SF and CC valve operations and inaccurate OA flow control at AHUs and consequently degrade maximum energy efficiency gains. With virtual fan and valve flow meter technologies, two advanced controls, including cascade control and gain scheduling control, can be implemented on both the SF and CC valve, and an advanced control using a virtual OA flow meter can be implemented on OA damper integrated with occupancy sensors. The goal of this project is to demonstrate the savings, cost, and performance of an integrated solution that integrates the three advanced HVAC controls with occupancy sensors to allow accurate and stable AHU operations in real buildings. The project objectives are to: 1) develop and validate an advance SF control algorithm; 2) develop and validate an advanced CC valve control algorithm; 3) validate an algorithm to implement a virtual OA flow meter; and 4) demonstrate the savings, cost, and performance of the integrated solution in real buildings. The technical approaches are to: 1) select a test system at the University of Oklahoma; 2) develop and implement the algorithms of advanced SF and CC valve controls and validate the performance; 3) develop and implement the advanced OA control using a virtual OA flow meter and validate the performance; 4) demonstrate the savings, cost, and performance of the proposed integrated solution with and without three advanced HVAC controls; and 5) disseminate the project results through publications and presentations. For the SF control, both the gain scheduling and cascade controls can improve the fan energy performance by reducing the fan power during the transient period and the fan control performance at lower speeds by reducing fan speed variation. Moreover, the gain scheduling control provides a simple and low-cost solution and is recommended. The fan power savings can reach 30% in a transient period. For the CC valve control, the gain scheduling control can considerably reduce the supply air temperature oscillation range and frequency under both higher and lower load conditions and the control valve response is much more stable. As a result, the gain scheduling control is recommended. The projected pump energy consumption can be reduced by 68.5%. With the developed virtual OA flow meter, the OA can be accurately controlled at its setpoint, which is determined based on the actual number of occupants in the building provided by occupancy sensors. The RMSE of the proposed OA control is 15.9 L/s. The energy data shows that the fan power and CC cooling energy were significantly reduced. On the other hand, the energy savings majorly results from the occupancy sensors and the energy savings by the advanced HVAC controls is minimal because that the controllers in the test AHU were tuned with very slow response. An annual technical savings potential is estimated as 0.5 quads in the commercial sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2013

Exploring ν{sub τ}−ν{sub s} mixing with cascade events in DeepCore

The atmospheric neutrino data collected by the IceCube experiment and its low-energy extension DeepCore provide a unique opportunity to probe the neutrino sector of the Standard Model. In the low energy range the experiment have observed neutrino oscillations, and the high energy data are especially sensitive to signatures of new physics in the neutrino sector. In this context, we previously demonstrated the unmatched potential of the experiment to reveal the existence of light sterile neutrinos. The studies are routinely performed in the simplest 3+1 model concentrating on disappearance of muon neutrinos of TeV energy as a result of their mixing with a sterile neutrino. We here extend this analysis to include cascade events that are secondary electromagnetic and hadronic showers produced by neutrinos of all flavors. We find that it is possible to probe the complete parameter space of 3+1 model, including the poorly constrained mixing of the sterile neutrino to tau neutrinos. We show that ν{sub τ}−ν{sub s} mixing results into a unique signature in the data that will allow IceCube to obtain constraints well below the current upper limits.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

The Benefits of Creating a Cross-Country Data Framework for Energy Efficiency

As manufacturers now sell a similar range of consumer electronics and home appliances to major markets around the world, the task of identifying a product?s energy efficiency rating has usually been the responsibility of each country and its respective government agency. This has led to a multitude of energy efficiency testing procedures, ratings, and certifications, resulting in disparate data being captured on identical products. Furthermore, lack of consistent product identification criteria means product energy performance is not easily connected to relevant information about the product such as market availability, price or real world energy consumption. This paper presents a new data standard for reporting energy performance and related product information that can be adopted internationally. To inform the development of this standard, we explore the existing energy efficiency market data for the two example products of TVs and Room Air Conditioners. This paper discusses current/future use cases of appliance level energy efficiency data across all stakeholders, including consumers, retailers/manufacturers, global standards organizations, third party service providers, and regulatory agencies. It also explains the key benefits of moving to a common international data framework for energy efficiency, such as: 1) a centralized product information repository for comparing energy use, ratings/certifications, and pricing data 2) improved access to relevant consumer electronics and appliance data to facilitate new policy development and harmonization across markets 3) enablement of retailers and other third parties to embed actionable energy efficiency information as part of the consumer experience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2013

Benefits of creating a cross-country data framework for energy efficiency

As manufacturers now sell a similar range of consumer electronics and home appliances to major markets around the world, the task of identifying a product’s energy efficiency rating has usually been the responsibility of each country and its respective government agency. This has led to a multitude of energy efficiency testing procedures, ratings, and certifications, resulting in disparate data being captured on identical products. Furthermore, lack of consistent product identification criteria means product energy performance is not easily connected to relevant information about the product such as market availability, price or real world energy consumption. This paper presents a new data standard for reporting energy performance and related product information that can be adopted internationally. To inform the development of this standard, we explore the existing energy efficiency market data for the two example products of TVs and Room Air Conditioners. This paper discusses current/future use cases of appliance level energy efficiency data across all stakeholders, including consumers, retailers/manufacturers, global standards organizations, third party service providers, and regulatory agencies. It also explains the key benefits of moving to a common international data framework for energy efficiency, such as: 1) a centralized product information repository for comparing energy use, ratings/certifications, and pricing data 2) improved access to relevant consumer electronics and appliance data to facilitate new policy development and harmonization across markets 3) enablement of retailers and other third parties to embed actionable energy efficiency information as part of the consumer experience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Creating an Energy Intelligent Campus: Data Integration Challenges and Solutions at a Large Research Campus

Rich, well-organized building performance and energy consumption data enable a host of analytic capabilities for building owners and operators, from basic energy benchmarking to detailed fault detection and system optimization. Unfortunately, data integration for building control systems is challenging and costly in any setting. Large portfolios of buildings--campuses, cities, and corporate portfolios--experience these integration challenges most acutely. These large portfolios often have a wide array of control systems, including multiple vendors and nonstandard communication protocols. They typically have complex information technology (IT) networks and cybersecurity requirements and may integrate distributed energy resources into their infrastructure. Although the challenges are significant, the integration of control system data has the potential to provide proportionally greater value for these organizations through portfolio-scale analytics, comprehensive demand management, and asset performance visibility. As a large research campus, the National Renewable Energy Laboratory (NREL) experiences significant data integration challenges. To meet them, NREL has developed an architecture for effective data collection, integration, and analysis, providing a comprehensive view of data integration based on functional layers. The architecture is being evaluated on the NREL campus through deployment of three pilot implementations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Unifying leptogenesis, dark matter and high-energy neutrinos with right-handed neutrino mixing via Higgs portal

We revisit a model in which neutrino masses and mixing are described by a two right-handed (RH) neutrino seesaw scenario, implying a strictly hierarchical light neutrino spectrum. A third decoupled RH neutrino, N{sub DM} with mass M{sub DM}, plays the role of cold dark matter (DM) and is produced by the mixing with a source RH neutrino, N{sub S} with mass M{sub S}, induced by Higgs portal interactions. The same interactions are also responsible for N{sub DM} decays. We discuss in detail the constraints coming from DM abundance and stability conditions showing that in the hierarchical case, for M{sub DM}≫M{sub S}, there is an allowed window on M{sub DM} values necessarily implying a contribution, from DM decays, to the high-energy neutrino flux recently detected by IceCube. We also show how the model can explain the matter-antimatter asymmetry of the Universe via leptogenesis in the quasi-degenerate limit. In this case, the DM mass should be within the range 300 GeV ≲M{sub S}<M{sub DM}≲ 10 PeV. We discuss the specific properties of this high-energy neutrino flux and show the predicted event spectrum for two exemplary cases. Although DM decays, with a relatively hard spectrum, cannot account for all the IceCube high-energy data, we illustrate how this extra source of high-energy neutrinos could reasonably explain some potential features in the observed spectrum. In this way, this represents a unified scenario for leptogenesis and DM that could be tested during the next years with more high-energy neutrino events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Opacities of singly and doubly ionized neodymium and uranium for kilonova emission modeling

ABSTRACT Even though the electromagnetic counterpart AT2017gfo to the binary neutron star merger GW170817 is powered by the radioactive decay of r-process nuclei, only few tentative identifications of light r-process elements have been made so far. One of the major limitations for the identification of heavy nuclei is incomplete or missing atomic data. While substantial progress has been made on lanthanide atomic data over the last few years, for actinides there has been less emphasis, with the first complete set of opacity data only recently published. We perform atomic structure calculations of neodymium (Z = 60) as well as the corresponding actinide uranium (Z = 92). Using two different codes [flexible atomic code (fac) and hartree–fock-relativistic (hfr)] for the calculation of the atomic data, we investigate the accuracy of the calculated data (energy levels and electric dipole transitions) and their effect on kilonova opacities. For the fac calculations, we optimize the local central potential and the number of included configurations and use a dedicated calibration technique to improve the agreement between theoretical and available experimental atomic energy levels (AELs). For ions with vast amounts of experimental data available, the presented opacities agree quite well with previous estimations. On the other hand, the optimization and calibration method cannot be used for ions with only few available AELs. For these cases, where no experimental nor benchmarked calculations are available, a large spread in the opacities estimated from the atomic data obtained with the various atomic structure codes is observed. We find that the opacity of uranium is almost double the neodymium opacity.

Flörs, A. (ORCID:0000000320242819)↗

NASA NTRS1996

Determination of Small Animal Long Bone Properties Using Densitometry

Assessment of bone structural property changes due to loading regimens or pharmacological treatment typically requires destructive mechanical testing and sectioning. Our group has accurately and non-destructively estimated three dimensional cross-sectional areal properties (principal moments of inertia, Imax and Imin, and principal angle, Theta) of human cadaver long bones from pixel-by-pixel analysis of three non-coplanar densitometry scans. Because the scanner beam width is on the order of typical small animal diapbyseal diameters, applying this technique to high-resolution scans of rat long bones necessitates additional processing to minimize errors induced by beam smearing, such as dependence on sample orientation and overestimation of Imax and Imin. We hypothesized that these errors are correctable by digital image processing of the raw scan data. In all cases, four scans, using only the low energy data (Hologic QDR-1000W, small animal mode), are averaged to increase image signal-to-noise ratio. Raw scans are additionally processed by interpolation, deconvolution by a filter derived from scanner beam characteristics, and masking using a variable threshold based on image dynamic range. To assess accuracy, we scanned an aluminum step phantom at 12 orientations over a range of 180 deg about the longitudinal axis, in 15 deg increments. The phantom dimensions (2.5, 3.1, 3.8 mm x 4.4 mm; Imin/Imax: 0.33-0.74) were comparable to the dimensions of a rat femur which was also scanned. Cross-sectional properties were determined at 0.25 mm increments along the length of the phantom and femur. The table shows average error (+/- SD) from theory of Imax, Imin, and Theta) over the 12 orientations, calculated from raw and fully processed phantom images, as well as standard deviations about the mean for the femur scans. Processing of phantom scans increased agreement with theory, indicating improved accuracy. Smaller standard deviations with processing indicate increased precision and repeatability. Standard deviations for the femur are consistent with those of the phantom. We conclude that in conjunction with digital image enhancement, densitometry scans are suitable for non-destructive determination of areal properties of small animal bones of comparable size to our phantom, allowing prediction of Imax and Imin within 2.5% and Theta within a fraction of a degree. This method represents a considerable extension of current methods of analyzing bone tissue distribution in small animal bones.

Breit, Gregory A.↗

DOE OSTI2020

Assessing Current and Future Infrastructure Hazards

Project Objective Execute intelligent analytics via an advanced analytical framework, to assess the current state of offshore infrastructure, evaluate infrastructure life, and identify technologies to reduce infrastructure hazards, costs, and extend infrastructure life. Approach & Results thus Far• Build comprehensive dataset• Perform data-driven analytics to evaluate infrastructure integrity 1. Remaining lifespan 2. Likelihood of future risk• Apply data-driven advanced spatial, statistical, and Machine Learning (ML) models to quantify existing infrastructure integrity• Release data and models through a smart, online platform hosted by Energy Data eXchange (EDX)

Romeo, Lucy F.↗

DOE OSTI2019

Advancing Fusion with Machine Learning Research Needs Workshop

The pursuit of fusion energy has required extensive experimental and theoretical science activities to develop the knowledge needed that will enable design of successful fusion power plants. Even today, following decades of research in many key areas including plasma physics and material science, much remains to be learned to enable optimization of the tokamak or other paths to fusion energy. Data science methods from the fields of machine learning and artificial intelligence (ML/AI) offer opportunities for enabling or accelerating progress toward the realization of fusion energy by maximizing the amount and usefulness of information extracted from experimental and simulation output data. Jointly supported by the Department of Energy Offices of Fusion Energy Science (FES) and Advanced Scientific Computing Research (ASCR), a workshop was organized to identify Priority Research Opportunities (PRO’s) for application of ML/AI methods to enable accelerated solution of fusion problems. The resulting “Advancing Fusion with Machine Learning Research Needs Workshop,” held in Gaithersburg, MD, April 30 – May 2, 2019, brought together ~ 60 experts in fields spanning fusion science, data science, statistical inference and mathematics, machine learning, and artificial intelligence, along with DOE program managers and technical experts, to identify key PRO’s.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗