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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Optimal Planning and Operation of Multi-Frequency HVac Transmission Systems

Low-frequency high-voltage alternating-current (LF-HVac) transmission scheme has been recently proposed as an alternative solution to conventional 50/60-Hz HVac and high-voltage direct-current (HVdc) schemes for bulk power transfer. This paper proposes an optimal planning and operation for loss minimization in a multi-frequency HVac transmission system. In such a system, conventional HVac and LF-HVac grids are interconnected using back-to-back (BTB) converters. The dependence of system MW losses on converter dispatch as well as the operating voltage and frequency in the LF-HVac is discussed and compared with that of HVdc transmission. Based on the results of the loss analysis, multi-objective optimization formulations for both planning and operation stages are proposed. The planning phase decides a suitable voltage level for the LF-HVac grid, while the operation phase determines the optimal operating frequency and power dispatch of BTB converters, generators, and shunt capacitors. A solution approach that effectively handles the variations of transmission line parameters with the rated voltage and operating frequency in the LF-HVac grid is proposed. The proposed solutions of the planning and operation stages are evaluated using a multi-frequency HVac system. The results show a significant loss reduction and improved voltage regulation during a 24-hour simulation.

Nguyen, Quan H.↗
DOE OSTI2013

Design optimization of MR-compatible rotating anode x-ray tubes for stable operation

Purpose: Hybrid x-ray/MR systems can enhance the diagnosis and treatment of endovascular, cardiac, and neurologic disorders by using the complementary advantages of both modalities for image guidance during interventional procedures. Conventional rotating anode x-ray tubes fail near an MR imaging system, since MR fringe fields create eddy currents in the metal rotor which cause a reduction in the rotation speed of the x-ray tube motor. A new x-ray tube motor prototype has been designed and built to be operated close to a magnet. To ensure the stability and safety of the motor operation, dynamic characteristics must be analyzed to identify possible modes of mechanical failure. In this study a 3D finite element method (FEM) model was developed in order to explore possible modifications, and to optimize the motor design. The FEM provides a valuable tool that permits testing and evaluation using numerical simulation instead of building multiple prototypes.Methods: Two experimental approaches were used to measure resonance characteristics: the first obtained the angular speed curves of the x-ray tube motor employing an angle encoder; the second measured the power spectrum using a spectrum analyzer, in which the large amplitude of peaks indicates large vibrations. An estimate of the bearing stiffness is required to generate an accurate FEM model of motor operation. This stiffness depends on both the bearing geometry and adjacent structures (e.g., the number of balls, clearances, preload, etc.) in an assembly, and is therefore unknown. This parameter was set by matching the FEM results to measurements carried out with the anode attached to the motor, and verified by comparing FEM predictions and measurements with the anode removed. The validated FEM model was then used to sweep through design parameters [bearing stiffness (1×10{sup 5}–5×10{sup 7} N/m), shaft diameter (0.372–0.625 in.), rotor diameter (2.4–2.9 in.), and total length of motor (5.66–7.36 in.)] to increase the fundamental frequency past the operating range at 50 Hz.Results: The first large vibration during the prototype motor operation was obtained at 21.64±0.68 Hz in the power spectrum. An abrupt decrease in acceleration occurred at 21.5 Hz due to struggling against the resonance vibrations. A bearing stiffness of 1.2×10{sup 5} N/m in the FEM simulation was used to obtain a critical speed of 21.4 Hz providing 1.1% error. This bearing stiffness value and the 3D model were then confirmed by the experiments with the anode removed, demonstrating an agreement within 6.4% between simulation results and measurements. A calculated first critical frequency (fundamental frequency) of 68.5 Hz was obtained by increasing the bearing stiffness to 1×10{sup 7} N/m and increasing the shaft diameter by 68.0%. Reducing the number of bearings in the design permits decreasing the total length of the motor by 1.7 in., and results in a fundamental frequency of 68.3 Hz in concert with additional changes (shaft diameter of 0.625 in., rotor diameter of 2.4 in., and bearing stiffness of 1×10{sup 6} N/m).Conclusions: An FEM model of the x-ray tube motor has been implemented and experimentally validated. A fundamental frequency above the operational rotation speed can be achieved through modification of multiple design parameters, which allows the motor to operate stably and safely in the MR environment during the repeated acceleration/deceleration cycles required for an interventional procedure. The validated 3D FEM model can now be used to investigate trade-offs between generated torque, maximum speed, and motor inertia to further optimize motor design.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Learning Nonlinear Reduced Models from Data with Operator Inference

This review discusses Operator Inference, a nonintrusive reduced modeling approach that incorporates physical governing equations by defining a structured polynomial form for the reduced model, and then learns the corresponding reduced operators from simulated training data. The polynomial model form of Operator Inference is sufficiently expressive to cover a wide range of nonlinear dynamics found in fluid mechanics and other fields of science and engineering, while still providing efficient reduced model computations. The learning steps of Operator Inference are rooted in classical projection-based model reduction; thus, some of the rich theory of model reduction can be applied to models learned with Operator Inference. This connection to projection-based model reduction theory offers a pathway toward deriving error estimates and gaining insights to improve predictions. Furthermore, through formulations of Operator Inference that preserve Hamiltonian and other structures, important physical properties such as energy conservation can be guaranteed in the predictions of the reduced model beyond the training horizon. This review illustrates key computational steps of Operator Inference through a large-scale combustion example.

Mechanics↗
DOE OSTI2025

On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling [SWR-25-20]

Code repository for the experiments performed in the paper: On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling (https://doi.org/10.1017/eds.2025.11) Overall, our work investigates the zero-shot downscaling potential of neural operators. To summarize, our contributions are: 1. We provide a comparative analysis based on two challenging weather downscaling problems, between various neural operator and non-neural-operator methods with large upsampling factors (e.g., 8x and 15x) and fine grid resolutions (e.g., 2 km × 2 km wind speed). 2. We examine whether neural operator layers provide unique advantages when testing downscaling models on upsampling factors higher than those seen during training, i.e., zero-shot downscaling. Our results instead show the surprising success of an approach that combines a powerful transformer-based model with a parameter-free interpolation step at zero-shot weather downscaling. 3. We find that this Swin-Transformer-based approach mostly outperforms all neural operator models in terms of average error metrics, whereas an enhanced super-resolution generative adversarial network (ESRGAN)-based approach is better than most models in capturing the physics of the system, and suggests their use in future work as strong baselines. However, these approaches still do not capture variations at smaller spatial scales well, including the physical characteristics of turbulence in the HR data. This suggests a potential for improvement in transformer or GAN-based methods and neural-operator-based methods for zero-shot weather downscaling.

Sinha, Saumya [National Renewable Energy Laborator↗
DOE OSTI2020

Feasibility of Operating a Heavy-Duty Battery Electric Truck Fleet for Drayage Applications

Vehicle fleet electrification is regarded as one major pathway toward achieving energy independence and reducing air pollution and greenhouse gas emissions. Compared to light-duty and medium-duty vehicles, electrification of heavy-duty vehicles, especially Class 8 trucks, is more challenging owing to the battery size required to attain the driving range necessary for their operating goals. As drayage trucks generally have a limited daily mileage, return to a home base every night, and spend a large amount of time creeping and idling, drayage operation has been the first targeted application for Class 8 electric trucks. The feasibility of operating battery electric drayage trucks at the individual vehicle level has recently been demonstrated. However, questions remain as to whether these trucks are capable of meeting the needs of typical drayage operation at the fleet level. Here we present a feasibility analysis of operating an electric truck fleet based on real-world operation data of a diesel drayage operator in Southern California. Second-by-second activity data collected from 20 trucks in the fleet were used to estimate the corresponding electric energy consumption and the state of charge of the battery using a microscopic electric energy consumption model. An algorithm for generating tours of drayage activity from the collected data was developed and implemented. Multiple scenarios with different battery charging and truck scheduling assumptions were analyzed. The results show that 85% of the tours could be served by electric trucks if there is opportunity for charging at the home base during the time gap between consecutive tours.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

CRADA Final Report For CRADA NO. CR-12-006 [Operation and Testing of an SO 2 -depolarized Electrolyzer (SDE) for the Purpose of Hydrogen and Sulfuric Acid Production]

Over the past several years, Savannah River National Laboratory (SRNL) has led a team of collaborators under the Department of Energy’s (DOE) nuclear hydrogen production program to develop the Hybrid Sulfur (HyS) Process. HyS is a 2-step water-splitting process consisting of high temperature decomposition of sulfuric acid to generate SO 2 , followed by the electrolysis of aqueous SO 2 to generate hydrogen and sulfuric acid. The latter is fed back into the high temperature reactor. SRNL designed and built an SO 2 -depolarized electrolyzer (SDE) and a test facility. Over 40 SDE’s were tested using different catalysts, membranes and other components. SRNL demonstrated that an SDE could be operated continuously for approximately 200 hours under certain conditions without buildup of sulfur at the SDE’s cathode, thus solving a key technical problem with SDE technology. Air Products and Chemicals, Inc. (APCI) is a major supplier of hydrogen production systems, and they have proprietary technology that could benefit from the SDE developed by SRNS, or some improved version thereof. However, to demonstrate that SRNL’s SDE is a truly viable approach to the electrolyzer design, continuous operation for far greater periods of time than 200 hours must be demonstrated, and the electrolyzer must be scaled up to greater hydrogen production capacities. SRNL and Air Products entered into a Cooperative Research and Development Agreement with the objective of demonstrating the effectiveness of the SDE for hydrogen and sulfuric acid production and to demonstrate long-term continuous operation so as to dramatically increase the confidence in the SDE design for commercial operation. SRNL prepared a detailed technical report documenting previous SDE development, including the current SDE design and operating conditions that led to the 200-hour sulfurfree testing. SRNL refurbished its single cell SDE test facility and qualified the equipment for continuous operation. A new membrane electrode assembly (MEA) was fabricated and installed in the single cell electrolyzer (60 cm 2 active cell area). Shakedown testing was conducted, and several modifications were made to the test facility equipment. Seven different MEAs were used during testing. Beginning on May 20, 2013, SRNL was able to test the SDE continuously for 1200 hours, including 1000 hours under power to generate hydrogen at an average rate of 10.8 liters per hour. The SDE was not removed or repaired during the 50-day test and was successfully restarted after each shutdown. The test was intentionally stopped after 1200 hours (1000 hours of hydrogen production) due to funding constraints. Post-test examination of the MEA using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Microanalysis (EDAX) showed no elemental sulfur deposits or sulfur layer inside the cell, thus successfully achieving the test goals. The results demonstrated that the SDE could be operated for extended periods without major performance degradation or the buildup of sulfur inside the MEA. Air Products conducted an assessment of the economic viability of the SDE based on the “as tested” design. The results indicated that the SDE faces significant economic obstacles in its current state. Further development and scale-up are necessary before the SDE is ready for commercialization.

08 HYDROGEN↗
DOE OSTI2014

A Framework for Adaptable Operating and Runtime Systems

The emergence of new classes of HPC systems where performance improvement is enabled by Moore’s Law for technology is manifest through multi-core-based architectures including specialized GPU structures. Operating systems were originally designed for control of uniprocessor systems. By the 1980s multiprogramming, virtual memory, and network interconnection were integral services incorporated as part of most modern computers. HPC operating systems were primarily derivatives of the Unix model with Linux dominating the Top-500 list. The use of Linux for commodity clusters was first pioneered by the NASA Beowulf Project. However, the rapid increase in number of cores to achieve performance gain through technology advances has exposed the limitations of POSIX general-purpose operating systems in scaling and efficiency. This project was undertaken through the leadership of Sandia National Laboratories and in partnership of the University of New Mexico to investigate the alternative of composable lightweight kernels on scalable HPC architectures to achieve superior performance for a wide range of applications. The use of composable operating systems is intended to provide a minimalist set of services specifically required by a given application to preclude overheads and operational uncertainties (“OS noise”) that have been demonstrated to degrade efficiency and operational consistency. This project was undertaken as an exploration to investigate possible strategies and methods for composable lightweight kernel operating systems towards support for extreme scale systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.

17 WIND ENERGY↗
DOE OSTI2014

Acquisition of Kerr Dam and Establishment of a Wholesale Power Generation Corporation to Operate It: Hiring of Power market Coordinator and Staff Engineer (Final Report)

This project aimed at supporting one key component of a major multi-step undertaking on the part of the CSKT: the acquisition of the Kerr Hydroelectric project and its subsequent operation as a wholesale power generation facility. This project provided support to kick-start the development of the organizational structure to acquire and operate the facility by acquiring critical expertise necessary for the acquisition by funding in part two key personnel for the first two years of the four-year organizational development process. These individuals provided the Tribes with expert knowledge in the highly specialized areas of resource balancing, power marketing, and hydro-engineering; essential prerequisites to the Tribes' ability to build an organization for the operation of the Kerr Project and to securing financial backing for the acquisition. Goals achieved: • Establishing an efficient and economic conveyance process, and transition plans • Establishing an efficient and effective Tribal wholesale power generation corporation to manage the plant, balance the resources, and market the power from the Kerr Project. The success of this project, which is essential to the Tribes' acquisition of the Kerr Hydroelectric facility, helps to address poverty and unemployment among Tribal members by generating a number of highly skilled and specialized, high-paying Tribal member jobs and providing a stream of income from power sales that will be used for Tribal economic development. Objectives achieved: The project supported the position of Power Plant Operations and Maintenance engineer and power marketing coordinator positions. These are key, in part, to the Tribes' successful acquisition and operation of the facility because they will enable to the Tribes to gain the very specialized expertise required to operate a large wholesale power generation facility. Specific objectives include: Objective 1: Hire a power marketing coordinator to develop and coordinate the appropriate power marketing strategy for the sale of power generated by the operation of Kerr Dam. Objective 2: Hire a staff engineer.

13 HYDRO ENERGY↗
DOE OSTI2016

Stochastic Methods Applied to Power System Operations with Renewable Energy: A Review

Renewable energy resources have been rapidly integrated into power systems in many parts of the world, contributing to a cleaner and more sustainable supply of electricity. Wind and solar resources also introduce new challenges for system operations and planning in terms of economics and reliability because of their variability and uncertainty. Operational strategies based on stochastic optimization have been developed recently to address these challenges. In general terms, these stochastic strategies either embed uncertainties into the scheduling formulations (e.g., the unit commitment [UC] problem) in probabilistic forms or develop more appropriate operating reserve strategies to take advantage of advanced forecasting techniques. Other approaches to address uncertainty are also proposed, where operational feasibility is ensured within an uncertainty set of forecasting intervals. In this report, a comprehensive review is conducted to present the state of the art through Spring 2015 in the area of stochastic methods applied to power system operations with high penetration of renewable energy. Chapters 1 and 2 give a brief introduction and overview of power system and electricity market operations, as well as the impact of renewable energy and how this impact is typically considered in modeling tools. Chapter 3 reviews relevant literature on operating reserves and specifically probabilistic methods to estimate the need for system reserve requirements. Chapter 4 looks at stochastic programming formulations of the UC and economic dispatch (ED) problems, highlighting benefits reported in the literature as well as recent industry developments. Chapter 5 briefly introduces alternative formulations of UC under uncertainty, such as robust, chance-constrained, and interval programming. Finally, in Chapter 6, we conclude with the main observations from our review and important directions for future work.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Department of Energy Operational Readiness Review for the Waste Isolation Pilot Plant

The U.S. Department of Energy (DOE) has completed an Operational Readiness Review (ORR) for the restart of Contact Handled (CH) waste emplacement at the Waste Isolation Pilot Plant (WIPP) located near Carlsbad, New Mexico. The ORR team assessed the readiness of Nuclear Waste Partnership, LLC (NWP) to manage and perform receipt through CH waste emplacement, and associated waste handling and management activities, including the ability of the National TRU Program (NTP) to evaluate the waste currently stored at the WIPP site against the revised and enhanced Waste Acceptance Criteria (WAC). Field work for this review began on November 14, 2015 and was completed on November 30, 2016. The DOE ORR was conducted in accordance with the Department of Energy Operational Readiness Review Implementation Plan for the Waste Isolation Pilot Plant, dated November 8, 2016, and DOE Order 425.1D, Verification of Readiness to Start Up or Restart Nuclear Facilities. The review activities included personnel interviews, record reviews, direct observation of operations and maintenance demonstrations, and observation of multiple operational and emergency drills/exercises. The DOE ORR also evaluated the adequacy of the contractor’s ORR (CORR) and the readiness of the DOE Carlsbad field Office (CBFO) to oversee the startup and execution of CH waste emplacement activities at the WIPP facility. The WIPP facility is categorized as a Hazard Category 2 DOE Nonreactor Nuclear Facility for all surface and Underground (UG) operations per DOE-STD-1027-92, Hazard Categorization and Accident Analysis Techniques for Compliance with DOE Order 5480.23, Nuclear Safety Analysis Reports. In addition, the WIPP experienced two events in February, 2014 that resulted in Accident Investigations being performed in accordance with the requirements of DOE Order 225.1B, Accident Investigations. Based upon the results of the accident investigations and hazard categorization of the facility, the team placed significant emphasis on the following areas: fire protection, emergency preparedness, radiological protection, nuclear safety, and operations. The identification of specific focus areas was not intended to diminish the importance of other areas of the review, but to ensure that these areas received a particularly thorough and in-depth evaluation due to their significance with respect to the safe operation of the facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

nPINNs: nonlocal Physics-Informed Neural Networks for a parametrized nonlocal universal Laplacian operator. Algorithms and Applications

Physics-informed neural networks (PINNs) are effective in solving inverse problems based on differential and integro-differential equations with sparse, noisy, unstructured, and multifidelity data. PINNs incorporate all available information, including governing equations (reflecting physical laws), initial-boundary conditions, and observations of quantities of interest, into a loss function to be minimized, thus recasting the original problem into an optimization problem. In this paper, we extend PINNs to parameter and function inference for integral equations such as nonlocal Poisson and nonlocal turbulence models, and we refer to them as nonlocal PINNs (nPINNs). The contribution of the paper is three-fold. First, we propose a unified nonlocal Laplace operator, which converges to the classical Laplacian as one of the operator parameters, the nonlocal interaction radius δ goes to zero, and to the fractional Laplacian as δ goes to infinity. This universal operator forms a super-set of classical Laplacian and fractional Laplacian operators and, thus, has the potential to fit a broad spectrum of data sets. We provide theoretical convergence rates with respect to δ and verify them via numerical experiments. Second, we use nPINNs to estimate the two parameters, δ and α, characterizing the kernel of the unified operator. The strong non-convexity of the loss function yielding multiple (good) local minima reveals the occurrence of the operator mimicking phenomenon, that is, different pairs of estimated parameters could produce multiple solutions of comparable accuracy. Third, we propose another nonlocal operator with spatially variable order α(γ), which is more suitable for modeling turbulent Couette flow. Our results show that nPINNs can jointly infer this function as well as δ. More importantly, these parameters exhibit a universal behavior with respect to the Reynolds number, a finding that contributes to our understanding of nonlocal interactions in wall-bounded turbulence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Analysis of Tempered Fractional Operators

Tempered fractional operators are useful in models for subsurface transport and diffusion due to their ability to capture anomalous diffusion: a behavior which the classical partial differential equation models cannot describe. We analyze tempered fractional operators within the nonlocal vector calculus framework in order to assimilate them to the rigorous mathematical structure developed for nonlocal models. First, we show they are special instances of generalized nonlocal operators in correspondence of a proper choice of nonlocal kernels. Then, we work towards showing tempered fractional operators are equivalent to truncated fractional operators. These truncated operators are useful because they are less computationally intensive than the tempered operators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Analysis of Tempered Fractional Operators

Tempered fractional operators provide an improved predictive capability for modeling anomalous effects that cannot be captured by standard partial differential equations. These effects include subdiffusion and superdiffusion (i.e. the mean square displacement in a diffusion process is proportional to a fractional power of the time), that often occur in, e.g., geoscience and hydrology. We analyze tempered fractional operators within the nonlocal vector calculus framework in order to assimilate them to the rigorous mathematical structure developed for nonlocal models. First, we show they are special instances of generalized nonlocal operators by means of a proper choice of the nonlocal kernel. Then, we present a plan for showing tempered fractional operators are equivalent to truncated fractional operators. These truncated operators are useful because they are less computationally intensive than the tempered operators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

US Department of Energy, Office of Science High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory's (ORNL's) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable computational ecosystems; creating innovative solutions for high performance computing (HPC) needs; and managing risks, safety, and security associated with operating some of the most powerful computers in the world. The results can be seen in the cutting-edge science conducted by users and the praise from the research community. Calendar year (CY) 2019 was a big year as OLCF staff ran five world-class resources (the leadershipclass computers Titan and Summit, the large analysis cluster called Eos, and the massive parallel filesystems called Atlas and Alpine)) and also began power and cooling upgrades for a 2021 exascale system called Frontier. While continuing exceptional operation of Titan, Eos, and Rhea, the OLCF released the Summit supercomputer for production on January 1, 2019. Summit debuted as the most capable and efficient system in its class and has been recognized as the most powerful system in the world for its performance on both the high performance linpack (HPL) and conjugate gradient (HPCG) benchmark applications since June 2018 according to TOP500. Summit represents the culmination of a multiyear effort between the OLCF, IBM, NVIDIA, and Mellanox to deliver a system that is unmatched for modeling, simulation, data analysis, and learning. To hit the ground running with science-ready applications on day one, application teams worked closely with the OLCF through the Center for Accelerated Application Readiness (CAAR) program for years in advance of the Summit deployment. CY 2019 was filled with outstanding results and accomplishments: a very high rating from users on overall satisfaction for the sixth year in a row; a tremendous amount of core-hours delivered to researchers from two leadership-class systems; and success in delivering on the allocation split of roughly 60%, 30%, and 10% of core-hours offered for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE), Advanced Scientific Computing Research Leadership Computing Challenge (ALCC), and Director's Discretionary (DD) programs, respectively (see Operational Performance section). These accomplishments, coupled with the high utilization rates (overall and capability usage), represent the fulfillment of the promise of both leadership-class machines: efficient facilitation of leadership-class computational applications. Table ES.1 presents a summary of the 2019 OLCF metric targets and the associated results. More information can be found in the Operational Performance section for each OLCF resource. The scientific accomplishments of OLCF users are a strong indication of long-term operational success, with publications this year in such notable journals and publications as Nature, Nature Physics, Nature Plants, Physical Review X, Journal of the American Physical Society, Cell, Nano Letters, and Trends in Biotechnology. Crucial domain-specific discoveries facilitated by resources at the OLCF are described in the High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility (OAR) Strategic Results section. For example, researchers used Summit to pinpoint and understand the production of proteins from genetic information, including mutations and the functional expression of disease (Section 8.2).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Optical Engine Lockout System Design and Operation

Engine run days in the Diesel Combustion and Fuel Effects Lab are hectic. The long mental lists that must be kept by engine operators, paired with the tight time constraints between experiments, can cause operational issues that may be dangerous to personnel and/or cause damage to test equipment. Until now, a paper sign has been used to warn operators not to motor the engine when a foreign object has been placed inside of it. Unfortunately, this simple administrative control has failed in the past, motivating this effort to develop an improved system. The lockout system described in this document introduces an engineering control that, when activated, actually prevents the engine from being motored. The new system consists of a primary and a secondary control panel. Prior to an operator placing a foreign object into the cylinder, they press a button on the secondary control panel near the engine. This breaks the interlock circuit for the engine dynamometer and activates LEDs on both control panels to notify operators that a foreign object is present within the engine cylinder. Once the work is done and all foreign objects have been removed from the combustion chamber, two operators must be present to disable the system by simultaneously pressing the buttons on the primary and secondary control panels. Requiring a second operator to disable the system increases accountability and reduces the likelihood of potentially costly mistakes.

42 ENGINEERING↗
DOE OSTI2019

Performance of Gather/Scatter Operations

In this paper we describe the performance of two operations, gather and scatter. The operations we describe are simplified versions of those used in the implementation of sparse matrix libraries such as sparse-blas. Similar operations can also be found in benchmarks such as HPCG. Gather and scatter operations are memory load and store operations that are related to other memory operations such as Stream Triad and DAXPY, but have an additional dependence between memory loads that affects performance. We describe how the operations behave on current technology and identify features that enhance their performance. However, our description of hardware is general rather than specific to a single architecture.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Enhancing the Operational Resilience of Advanced Reactors with Digital Twins by Recurrent Neural Networks

Because of a lack of operational data and uncertainty in evaluation model for abnormal and accident scenarios, the established operating procedures can be biased in characterizing the reactor states and ensuring operational resilience. To reduce uncertainty associated with actual plant conditions, digital twin (DT) technology is suggested to support operator’s decision-making by effectively extracting and using knowledge of the current and future plant states from the knowledge base. This study first builds a knowledge base based on the characterization of issue space and the simulation tool. Next, this study discusses diagnosis and prognosis DTs for enhancing operational resilience by recovering the complete states of reactors and by predicting the future reactor behaviors. Finally, the decision-making module of the control system can determine the optimal control strategy that meets operational goals during loss-of-flow scenarios. To demonstrate and evaluate the DTs capability for supporting the operations of nuclear reactors, this study develops and assesses both the diagnosis and prognosis DTs in a nearly autonomous management and control system for an Experimental Breeder Reactor-II simulator during different loss-of-flow scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗