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DOE OSTI2026

Uncertainty guided online ensemble for non-stationary data streams in fusion science

Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior with distribution drifts, resulted by both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with such non-stationary data streams. Online learning techniques have been leveraged in other domains, however it has been largely unexplored for fusion applications. In this paper, we investigate online learning for continuous adaptation to drifting data streams in the prediction of Toroidal Field (TF) coils deflection at the DIII-D fusion facility. We further address the short-term performance degradation inherent to standard online learning, which arises because ground truth is unavailable at prediction time. To mitigate this issue, we propose an uncertainty-guided online ensemble framework. The method leverages the Deep Gaussian Process Approximation (DGPA) for calibrated uncertainty estimation and uses these uncertainty measures to guide a meta-algorithm that aggregates predictions from learners trained over different historical horizons. Our results show that online learning reduces prediction error by 80% compared to a static model. The online ensemble and the proposed uncertainty-guided ensemble further reduce error by approximately 6%, and 10% respectively, relative to standard single-model online learning, while also providing calibrated uncertainty estimates to support operational decision-making.

AI↗

DOE OSTI2022

Synchronous High-frequency Distributed Readout For Edge Processing At The Fermilab Main Injector And Recycler

The Main Injector (MI) was commissioned using data acquisition systems developed for the Fermilab Main Ring in the 1980s. New VME-based instrumentation was commissioned in 2006 for beam loss monitors (BLM)[2], which provided a more systematic study of the machine and improved displays of routine operation. However, current projects are demanding more data and at a faster rate from this aging hardware. One such project, Real-time Edge AI for Distributed Systems (READS), requires the high-frequency, low-latency collection of synchronized BLM readings from around the approximately two-mile accelerator complex. Significant work has been done to develop new hardware to monitor the VME backplane and broadcast BLM measurements over Ethernet, while not disrupting the existing operations critical functions of the BLM system. This paper will detail the design, implementation, and testing of this parallel data pathway.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

EOS at the Fermilab LHC Physics Center(LPC)

The Fermilab CMS LPC center has operated an EOS instance since initial testing began in June 2012, transitioning to production storage in 2013 with an initial capacity of 600\,TB. Today, the system provides approximately 16\,PB of storage to support the 4{,}500-core LPC user analysis cluster, which serves several hundred active CMS users at any given time. In this talk, we will provide an update on our system setup and outline near-term plans for the CMS LPC production EOS system. We will share operational experiences from running our EOS system over the past year. Additionally, we will briefly discuss our recent efforts within the Fermilab Disk Evolution Project to consider the future architecture of HEP data storage at Fermilab for the HL-LHC era.

Wu, Yujun↗

DOE OSTI2026

EOS at the Fermilab LHC Physics Center(LPC)

Wu, Yujun↗

DOE OSTI2020

ATLAS data quality operations and performance for 2015–2018 data-taking

The ATLAS detector at the Large Hadron Collider reads out particle collision data from over 100 million electronic channels at a rate of approximately $100$ kHz, with a recording rate for physics events of approximately 1 kHz. Before being certified for physics analysis at computer centres worldwide, the data must be scrutinised to ensure they are clean from any hardware or software related issues that may compromise their integrity. Prompt identification of these issues permits fast action to investigate, correct and potentially prevent future such problems that could render the data unusable. This is achieved through the monitoring of detector-level quantities and reconstructed collision event characteristics at key stages of the data processing chain. This paper presents the monitoring and assessment procedures in place at ATLAS during 2015-2018 data-taking. Through the continuous improvement of operational procedures, ATLAS achieved a high data quality efficiency, with 95.6% of the recorded proton-proton collision data collected at $\sqrt{s}=13$ TeV certified for physics analysis.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Numerical simulation of a relativistic magnetron using a fluid electron model

An approach to numerically modeling relativistic magnetrons, in which the electrons are represented with a relativistic fluid, is described. A principal effect in the operation of a magnetron is space-charge-limited (SCL) emission of electrons from the cathode. We have developed an approximate SCL emission boundary condition for the fluid electron model. This boundary condition prescribes the flux of electrons as a function of the normal component of the electric field on the boundary. Here we show the results of a benchmarking activity that applies the fluid SCL boundary condition to the one-dimensional Child–Langmuir diode problem and a canonical two-dimensional diode problem. Simulation results for a two-dimensional A6 magnetron are then presented. Computed bunching of the electron cloud occurs and coincides with significant microwave power generation. Numerical convergence of the solution is considered. Sharp gradients in the solution quantities at the diocotron resonance, spanning an interval of three to four grid cells in the most well-resolved case, are present and likely affect convergence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI1991

Physical and Operational Status of the Photovoltaic Systems in the Municipality of Pinotepa de Don Luis, Oaxaca, One Year after Their Installation [Estado fisico y operativo de los sistemas fotovoltaicos en el municipio de Pinotepa de Don Luis, Oaxaca un ano despues de su instalacion]

In November 1990, an inspection visit was made to the residential lighting photovoltaic systems that had been installed approximately one year before in the rural communities of the Municipality of Pinotepa de Don Luis, in the State of Oaxaca. The main purpose of the visit was to evaluate the physical and operational status of these systems. The systems typically consist of a photovoltaic module with a capacity of 30 or 35 Watts, an automotive type battery, an indicator of the status of charge of the battery, 3 fluorescent lamps and the corresponding installation, including cables, connection or outlet box and switches. It can be seen that the systems are in good physical condition and do not show any signs of intentionally caused damage. However, the incidence of failures is higher than what had been expected; therefore the operational status of these systems is considered to be below a level that could be accepted, with a tendency to getting worse. The main problem that has been detected is the lack of automatic charge controllers. This problem has caused other important failures. Serious deficiencies were appreciated in the installations, which show evidence of the poor workmanship of the installers. The lack of system standardization is evident, both regarding the components and the installation. As a consequence, there are technical factors which indicate that the installed systems will keep deteriorating at a rate faster than normal, and will stop operating in a short time unless urgent preventive and corrective measures are taken. The attitude of the users with respect to the systems is generally positive. However, there are elements that make the correct operation and maintenance of these systems a very difficult task. The users did not receive any training regarding the best way to operate and take care of their systems, nor any other information in relation to their technical limitations.

14 SOLAR ENERGY↗

DOE OSTI2020

Evaluation of Steam Cycle Upgrades to Improve the Competitiveness of U.S. Coal Power Plants (Final Scientific / Technical Report)

Increasing the competitiveness of the existing pulverized-coal utility fleet in the United States may be achieved by decreasing heat rate, via increases in steam cycle efficiency through upgraded steam temperatures and use of latest technology available in steam turbine and blading design. The average net plant efficiency of the US coal-fired fleet is approximately 33% (HHV). Plant efficiency increases to approximately 41.4% (HHV) at 1,350°F (732°C) steam temperature. However, achieving these Advanced Ultra-Super Critical (AUSC) steam conditions requires the use of advanced high-temperature materials. While there has been a significant amount of DOE-funded materials R&D, most of the related design work has focused on new (greenfield) units, rather than on opportunities to retrofit this advanced technology to the existing utility fleet. If technology, based upon the advanced materials required for AUSC steam conditions, may be applied to the existing fleet, using an economically viable retrofit, a higher capacity factor can be expected as a result of the increased plant competitiveness. The Electric Power Research Institute (EPRI) was awarded a project by the US Department of Energy to examine the technical and economic feasibility of a series of steam cycle upgrades to the two most prevalent types of U.S. coal power plants: 2,400 psig (16.6 MPa) subcritical and 3,500 psig (24.1 MPa) supercritical pulverized coal units. The nine upgrade options that were originally being considered included increasing the main and reheat steam temperatures from 1,000°F (538°C) to 1,100°, 1,200°, and 1,350°F (593°C, 649°C, and 732°C) while holding the steam pressures constant at their original design values, and cases where just the main steam or reheat steam temperatures were increased. The objective was to minimize the modifications required to the existing power plant while still providing a significant improvement in heat rate. The upgrade options assumed that the boiler enclosure envelope remained unchanged from each base case, and that all applicable OEM design guidelines for normal commercial units were imposed. For the highest temperature supercritical case, an option of using a low-pressure molten salt loop to transfer heat from the furnace to the steam was examined. The first major task of the work scope was designed to examine the technical feasibility of various upgrade options, while the subsequent work determined economic viability of the technically feasible upgrade options. Prior to evaluating the effect of these increased temperatures, a “base case” model of a subcritical and supercritical PC boiler was created, which was used for comparative purposes. Upgrade options were evaluated at full-load, part-load and dynamic transient conditions. Once the technical feasibility of each upgrade option was evaluated, the economic value of the heat rate improvement of each feasible option was determined by detailed modeling of unit dispatch in several regional power markets. The dispatch model was used to estimate the amount of revenue from power sales the upgraded unit would receive in comparison to a non-upgraded version of the same power plant. As a parallel task to the dispatch analysis, the capital cost of implementing the upgrades was estimated. The capital cost estimates were then compared to the increased revenue estimated by the dispatch modeling to determine the economic attractiveness of each upgrade option. Several upgrade options were determined to be technically feasible. The net present value (NPV) of the costs for steam cycle upgrades considered in this study ranged from approximately $\$$111 to $\$$130 million. The economic modeling results show that the unit dispatch changes resulting from steam cycle upgrades are relatively small, due largely to heat rate (and operating cost) changes being relatively small. Additionally, the cost of each upgrade exceeds the net revenue increases associated with the upgrade case. Note that the breakeven values are higher for subcritical retrofits, but the capital costs for the subcritical upgrades are also slightly higher. In typical new pulverized coal plants, fuel accounts for approximately 25% of the cost of electricity (COE), while capital costs represent around 50% of the COE. Therefore, in order to improve the heat rate by 4% one can only afford to increase the capital cost by 2%, at the same cost of electricity. The conclusion of this study is that without a cost for emitting CO 2 , it will be difficult to pay for significant efficiency improvements on plants firing low cost coals.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Accelerating Hamiltonian Monte Carlo for Bayesian inference in neural networks and neural operators

Hamiltonian Monte Carlo (HMC) is a powerful and accurate method to sample from the posterior distribution in Bayesian inference. However, HMC techniques are computationally demanding for Bayesian neural networks due to the high dimensionality of the network’s parameter space and the non-convexity of their posterior distributions. Therefore, various approximation techniques, such as variational inference (VI) or stochastic gradient MCMC, are often employed to infer the posterior distribution of the network parameters. Such approximations introduce inaccuracies in the inferred distributions, resulting in unreliable uncertainty estimates. In this work, we propose a hybrid approach that combines inexpensive VI and accurate HMC methods to efficiently and accurately quantify uncertainties in neural networks and neural operators. The proposed approach leverages an initial VI training on the full network. We examine the influence of individual parameters on the prediction uncertainty, which shows that a large proportion of the parameters do not contribute substantially to uncertainty in the network predictions. This information is then used to significantly reduce the dimension of the parameter space, and HMC is performed only for the subset of network parameters that strongly influence prediction uncertainties. This yields a framework for accelerating the full batch HMC for posterior inference in neural networks. We demonstrate the efficiency and accuracy of the proposed framework on deep neural networks and operator networks, showing that inference can be performed for large networks with tens to hundreds of thousands of parameters. Finally, we show that this method can effectively learn surrogates for complex physical systems by modeling the operator that maps from upstream conditions to wall-pressure data on a cone in hypersonic flow.

Bayesian inference↗

DOE OSTI2026

Data-Driven Modeling and Correction of Vehicle Dynamics

We develop a data-driven framework for learning and correcting nonautonomous vehicle dynamics. Physics-based vehicle models are often simplified for tractability and therefore exhibit inherent model-form uncertainty, motivating the need for data-driven correction. Moreover, nonautonomous dynamics are governed by time-dependent control inputs, which pose challenges in learning predictive models directly from temporal snapshot data. To address these, we reformulate the vehicle dynamics via a local parameterization of the time-dependent inputs, yielding a modified system composed ofa sequence of local parametric dynamical systems. Here, we approximate these parametric systems using two complementary approaches. First, we employ the dimension reduction and interpolation in parameter space (DRIPS) methodology to construct efficient linear surrogate models, equipped with lifted observable spaces and manifold-based operator interpolation. This enables data-efficient learning of vehicle models whose dynamics admit accurate linear representations in the lifted spaces. Second, for more strongly nonlinear systems, we employ flow map learning (FML), a deep neural network (DNN) approach that approximates the parametric evolution map without requiring special treatment of nonlinearities. We further extend FML with a transfer-learning-based model correction procedure, enabling the correction of misspecified prior models using only a sparse set of high-fidelity or experimental measurements, without assuming a prescribed form for the correction term. Through a suite of numerical experiments on unicycle, simplified bicycle, and slip-based bicycle models, we demonstrate that DRIPS offers robust and highly data-efficient learning of nonautonomous vehicle dynamics, while FML provides expressive nonlinear modeling and effective correction of model-form errors under severe data scarcity.

data-driven modeling↗

DOE OSTI2023

Jet-veto resummation at N 3 LL p + NNLO in boson production processes

Vetoing energetic jet activity is a crucial tool for suppressing backgrounds and enabling new physics searches at the LHC, but the introduction of a veto scale can introduce large logarithms that may need to be resummed. We present an implementation of jet-veto resummation for color-singlet processes at the level of N 3 LL p matched to fixed-order NNLO predictions. Our public code MCFM allows for predictions of a single boson, such as Z/γ*, W ± or H, or with a pair of vector bosons, such as W + W – , W ± Z or ZZ. The implementation relies on recent calculations of the soft and beam functions in the presence of a jet veto over all rapidities, with jets defined using a sequential recombination algorithm with jet radius R. However one of the ingredients that is required to reach full N 3 LL accuracy is only known approximately, hence N 3 LL p . We describe in detail our formalism and compare with previous public codes that operate at the level of NNLL. Our higher-order predictions improve significantly upon NNLL calculations by reducing theoretical uncertainties. We demonstrate this by comparing our predictions with ATLAS and CMS results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Abatement of ionizing radiation for superconducting quantum devices

Ionizing radiation has been shown to reduce the performance of superconducting quantum circuits. In this report, we evaluate the expected contributions of different sources of ambient radioactivity for typical superconducting qubit experiment platforms. Our assessment of radioactivity inside a typical cryostat highlights the importance of selecting appropriate materials for the experiment components nearest to qubit devices, such as packaging and electrical interconnects. We present a shallow underground facility (30-meter water equivalent) to reduce the flux of cosmic rays and a lead shielded cryostat to abate the naturally occurring radiogenic gamma-ray flux in the laboratory environment. We predict that superconducting qubit devices operated in this facility could experience a reduced rate of correlated multi-qubit errors by a factor of approximately 20 relative to the rate in a typical above-ground, unshielded facility. Finally, we outline overall design improvements that would be required to further reduce the residual ionizing radiation rate, down to the limit of current generation direct detection dark matter experiments.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Lifetime study of the ColdADC for the Deep Underground Neutrino Experiment

ColdADC is a custom ASIC digitizer implemented in 65 nm CMOS technology using specialized techniques for long-term reliability in cryogenic environments. ColdADC was developed for use in the DUNE Far Detector complex, which will consist of four liquid argon time projection chambers. Each contains 17 kilotons liquid argon as the target material in order to measure neutrino oscillations. Approximately 40,000 ColdADC ASICs will be installed for DUNE in the first two large detectors and will be operated at cryogenic temperatures during the experiment without replacement. The lifetime of the ColdADC is a critical parameter affecting the data quality and physics sensitivity of the experiment. A measurement of the lifetime of the ColdADC was carried out, and the results shown in this paper assure orders of magnitude longer lifetime of the ColdADC than the planned operation time of the detectors.

Front-end electronics for detector readout↗

DOE OSTI2024

Stochastic Maxwell-Bloch equations for modeling amplified spontaneous emission

An approach for studying atom-radiation interaction has been developed, associating quantum operators with stochastic variables governed by discrete Heisenberg equations. This framework models general multilevel atomic systems using the paraxial approximation in both single- and multipass configurations. Simulation results for x-ray laser oscillators with parameters of interest are presented. Finally, the stochastic model is efficient to solve, as the required computational resources scale linearly with the number of emitters, and it may be applicable to various other quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous- enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗

DOE OSTI2025

DESIGN ISSUES AND QUALIFICATION OF HYDROFORMED DOUBLE WALLED EXPANSION JOINTS IN VACUUM SERVICE

The Vacuum Auxiliary System for ITER is devoted to pumping out, venting, and purging the vacuum volumes of the tokamak. Over 5000 clients including the cryostat and vacuum vessel, at 8500 m3 and 1400 m3 respectively, are serviced by approximately 150 pumping stations through 6 km of pipework. The piping and functions provided to the clients include component operation, routing of potentially tritiated gases, and timely leak localization. Expansion joints are used to reduce loadings on pumps and piping stresses but also to qualify in-line components having low allowable design loads. The ITER project utilizes vacuum valves that are not designed to withstand typical piping system loadings and require detailed design and evaluation. Loading scenarios prescribed by governing system specifications must be considered. To maintain allowable design loads for components and to keep piping stresses below code requirements, double walled hydroformed expansion joints have been employed in the design. These are not standard items and require custom fabrication. Installation space constraints and adjacent pipe support attachment location availability at ITER limit standard expansion joint installation guidelines provided by the Expasion Joint Manufacturers Association (EJMA). Careful consideration must be given to the analysis model to ensure proper function and life expectancy of the component. These considerations include accurate accounting of thrust forces, thermal movements, seismic accelerations, equipment and building differential displacements. In addition to displacements, the process internal, external, and interspace pressures affect the qualification and selection of the double walled expansion joints. The calculation results shall confirm that deflections, forces, and moments are reasonable for the size and type required for the system’s demands as evaluated against the manufacturer’s design.

Clark, Forrest [ORNL] (ORCID:0009000678106843)↗

DOE OSTI2020

Savannah River Site Composite Analysis (FY2019 Annual Review)

The Savannah River Site (SRS) is a Department of Energy (DOE) site encompassing approximately 310 square miles in South Carolina. It is bounded on the southwest by the Savannah River (SR) and is situated approximately 12 miles south of Aiken, South Carolina, and 15 miles southeast of Augusta, Georgia. Construction of and subsequent operations at the SRS began in 1951 under the direction of the Atomic Energy Commission. The primary mission of the SRS was to produce tritium and plutonium for the national nuclear weapons complex. Between 1953 and 1955, SRS brought five reactors and various support facilities into operation in support of its primary mission. Support facilities included two chemical separations plants, a heavy water extraction plant, a nuclear fuel and target fabrication facility, a tritium extraction facility and waste management facilities. With the declining need for a large nuclear weapons stockpile since the end of the Cold War, many SRS facilities no longer produce or process nuclear materials. All reactors were shut down by 1993. However, the SRS Tritium Extraction Facility continues to supply DOE with tritium. Additionally, operations at the K-Area Complex currently provide interim safe storage for much of DOE’s excess plutonium (Pu) and high enriched uranium, in a building which formerly housed K Reactor. As the SRS mission has changed, many surplus facilities are being dispositioned safely and economically. SRS has completed extensive decommissioning activities in D-Area, M-Area, P-Area, R-Area, and T-Area, with groundwater (GW) remediation ongoing. High-level waste tanks continue to be emptied and closed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Intelligent System Partitioning for Agent-Based Security Constrained Optimal Power Flow

This project developed scalable, computationally efficient algorithms to solve realistic large-scale power system optimization problems as part of a larger series of competitions run by ARPA-E. These problems are important because the secure and reliable operation of the power grid, especially under increased uncertainty and variability, is growing increasingly challenging. The economic feasibility of the proposed methods developed by our team is quite low, considering it’s a purely software-based solution to operate power grids more efficiently. The technical effectiveness, as evidenced by our performance in the competition, balances heuristics and approximations to provide a tradeoff between speed and accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗