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DOE OSTI2025

Recent results from MicroBooNE

Modelling and reconstructing neutrino-nucleus scattering is difficult, but it is crucial to do it precisely to enable next-generation oscillation measurements. Liquid argon time projection chambers (LArTPCs), such as MicroBooNE, can be the tool for this job as they are excellent precision neutrino detectors with their ability to produce detailed three-dimensional interaction images and precise energy and spatial resolution. MicroBooNE currently possesses the world's largest neutrino-argon scattering data set collected over five years using the BNB and NuMI neutrino beams at Fermilab. The experiment has performed measurements over a broad range of physics topics including neutrino argon cross sections, searches for BSM physics, and investigations of the MiniBooNE LEE excess. Many of these measurements are essential for improving the modelling of nuclear effects for both MicroBooNE and future LArTPC neutrino experiments, such as DUNE. This talk will give an overview of recent MicroBooNE results, the analysis techniques that enable them, and prospects for future measurements.

Parkinson, Holly B. [U. Edinburgh (main)] (ORCID:0↗

DOE OSTI2024

High-Fidelity Modeling of a Type-5 Wind Turbine Gearbox (Intern Technical Presentation) (Poster)

Type-5 wind turbines are unique in their use of a permanent magnet synchronous generator, as well as their use of a hydraulic torque converter. This architecture presents an opportunity to provide steady and grid-ready energy without the need for a power converter. With infrastructure continuity and reliability being an important topic amongst renewable energies, researchers have been prompted to further investigate the benefits of type-5 turbines’ unique electromechanical configuration on stable electricity generation. Researchers involved in the WindSG project, SG standing for synchronous generator, are aiming to model a type-5 turbine using Real Time Digital Simulation (RTDS) to evaluate its efficacy in the grid. RSCAD, the software run on the RTDS, comes pre-loaded with electrical and electromechanical components to help simulate electrical generation and grid conditions. However, within this repertoire there is a lack of a component to represent a gearbox with high-fidelity. Within RSCAD’s case studies, the gearbox is often represented simply by a gear ratio value. This presented the task of developing a high-fidelity gearbox model in RSCAD for use in the larger RTDS type-5 wind turbine model. This presentation describes a method of developing a lumped parameter mathematical model to represent a planetary-parallel-parallel gearbox in RSCAD for use in RTDS.

17 WIND ENERGY↗

DOE OSTI2021

Evaluate the impact of sensor accuracy on model performance in data-driven building fault detection and diagnostics using Monte Carlo simulation

The performance of data-driven fault detection and diagnostics (FDD) is heavily dependent on sensors. However, sensor inaccuracy and sensor faults are pervasive in building operation: inaccurate and missing sensor readings deteriorate FDD performance; sensor inaccuracy will also affect the selection of sensor for data-driven FDD in the model training process, which is another key factor of data-driven FDD performance. Sensor accuracy and sensor selection individually are well-studied research topics in this field, but the impact of sensor accuracy on sensor selection and its further impact on FDD performance has not been evaluated and quantified. In this paper, we developed a novel analysis methodology that comprehensively evaluates sensor fault on sensor selection and FDD accuracy. Monte Carlo simulation is applied to deal with multiple stochastic sensor inaccuracy and provide probabilistic analysis results of the impact of sensor inaccuracy on sensor selection and FDD accuracy. This methodology focuses on the net impact of fault states across a full sensor set. The developed methodology can be used for the early-stage sensor design and operation-stage sensor maintenance. Furthermore, a case study is conducted to demonstrate the analysis methodology using a commercial building model crated to Flexible Research Platform located at Oak Ridge National Laboratory, USA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Master Services Agreement - Flexible Feeder/Distribution System Support: Cooperative Research and Development (Final Report)

PGE will engage NREL on a broad range of projects related to the integration of distributed energy resources (DERs) into the utility's operations. This portfolio of work could include projects focused on DER adoption models, advanced distribution management system (ADMS) and distributed energy management system (DERMS) design, DER dispatch strategy development, and DER valuation framework development. Additional topics could include long-term energy planning, renewable energy, energy efficiency and demand-side management. As well as technology evaluations and design guidance for building retrofits and new construction projects, energy and energy infrastructure planning, policies, and markets (and their analysis), energy storage, energy security and resilience (including energy system-related cybersecurity), transportation and mobility, technology integration analysis. Additionally, other assistance as requested by PGE consistent with NREL’s expertise.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2011

Shortwave absorptance in a tropical cloudy atmosphere: Reconciling calculations and observations

The absorption of shortwave (SW) by clouds is a topic surrounded by contradictory reports and controversy. Some studies have shown large discrepancies between observed SW absorption and absorption predicted by models, while others have found no significant dfference. In this study, values of column SW absorptance obtained by combining collocated top-of atmosphere (TOA) and surface observations at an island site in the Tropical Western Pacific are compared to radiative transfer model (RTM) output. To compensate for the field of view difference between satellite and surface instruments, the surface data are averaged over time. Scatterplots and statistical measures show that there is a signficant discrepancy between models and observations with the RTMs apparently underestimating SW absorptance. In previous observational studies showing highly enhanced absorption compared to models, the slope of a linear fit to d*TOA/dT (the derivative of TOA albedo with respect to transmittance) was used to quantify cloud SW absorption while non-linearity of d*TOA/dT was interpreted as a sign of sampling issues. Here, the models produce a steeper slope (about -0.9) than observations (-0.6 to -0.8), indicating that models predict too little cloud SW absorption. However, when the surface observations are averaged over a longer period, their slope grows steeper and the root mean square di*erence between linear and quadratic fits to d*TOA/dT is reduced. This implies that insufficient averaging of surface data contributes to the observed SW absorption discrepancy. Reexamination of the observational data using the difference between cloud fraction estimated from satellite and surface measurements as an estimate of field of view mismatch supports this hypothesis. High mea sured absorptance values are shown to correspond to occasions of large field of view mismatch. When such data are excluded, the difference between the linear and quadratic fits is reduced and the slope of the best fit line becomes steeper. We conclude that averaging surface data over three hours or less is not always sufficient to eliminate sampling issues. However, the possibility that shortcomings of the RTMs contribute to the discrepancy in SW absorption values cannot be excluded.

58 GEOSCIENCES↗

DOE OSTI2018

Mean precipitation change from a deepening troposphere

Global climate models robustly predict that global mean precipitation should increase at roughly 2–3% K - 1 , but the origin of these values is not well understood. Here we develop a simple theory to help explain these values. This theory combines the well-known radiative constraint on precipitation, which says that condensation heating from precipitation is balanced by the net radiative cooling of the free troposphere, with an invariance of radiative cooling profiles when expressed in temperature coordinates. These two constraints yield a picture in which mean precipitation is controlled primarily by the depth of the troposphere, when measured in temperature coordinates. We develop this theory in idealized simulations of radiative–convective equilibrium and also demonstrate its applicability to global climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Feebly-interacting particles: FIPs 2020 workshop report

With the establishment and maturation of the experimental programs searching for new physics with sizeable couplings at the LHC, there is an increasing interest in the broader particle and astrophysics community for exploring the physics of light and feebly-interacting particles as a paradigm complementary to a New Physics sector at the TeV scale and beyond. FIPs 2020 has been the first workshop fully dedicated to the physics of feebly-interacting particles and was held virtually from 31 August to 4 September 2020. The workshop has gathered together experts from collider, beam dump, fixed target experiments, as well as from astrophysics, axions/ALPs searches, current/future neutrino experiments, and dark matter direct detection communities to discuss progress in experimental searches and underlying theory models for FIPs physics, and to enhance the cross-fertilisation across different fields. FIPs 2020 has been complemented by the topical workshop “Physics Beyond Colliders meets theory”, held at CERN from 7 June to 9 June 2020. This document presents the summary of the talks presented at the workshops and the outcome of the subsequent discussions held immediately after. It aims to provide a clear picture of this blooming field and proposes a few recommendations for the next round of experimental results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2011

Effects of Combustion-Induced Vortex Breakdown on Flashback Limits of Syngas-Fueled Gas Turbine Combustors

Turbine combustors of advanced power systems have goals to achieve very low pollutants emissions, fuel variability, and fuel flexibility. Future generation gas turbine combustors should tolerate fuel compositions ranging from natural gas to a broad range of syngas without sacrificing operational advantages and low emission characteristics. Additionally, current designs of advanced turbine combustors use various degrees of swirl and lean premixing for stabilizing flames and controlling high temperature NOx formation zones. However, issues of fuel variability and NOx control through premixing also bring a number of concerns, especially combustor flashback and flame blowout. Flashback is a combustion condition at which the flame propagates upstream against the gas stream into the burner tube. Flashback is a critical issue for premixed combustor designs, because it not only causes serious hardware damages but also increases pollutant emissions. In swirl stabilized lean premixed turbine combustors onset of flashback may occur due to (i) boundary layer flame propagation (critical velocity gradient), (ii) turbulent flame propagation in core flow, (iii) combustion instabilities, and (iv) upstream flame propagation induced by combustion induced vortex breakdown (CIVB). Flashback due to first two foregoing mechanisms is a topic of classical interest and has been studied extensively. Generally, analytical theories and experimental determinations of laminar and turbulent burning velocities model these mechanisms with sufficient precision for design usages. However, the swirling flow complicates the flashback processes in premixed combustions and the first two mechanisms inadequately describe the flashback propensity of most practical combustor designs. The presence of hydrogen in syngas significantly increases the potential for flashback. Due to high laminar burning velocity and low lean flammability limit, hydrogen tends to shift the combustor operating conditions towards flashback regime. Even a small amount of hydrogen in a fuel blend triggers the onset of flashback by altering the kinetics and thermophysical characteristics of the mixture. Additionally, the presence of hydrogen in the fuel mixture modifies the response of the flame to the global effects of stretch and preferential diffusion. Despite its immense importance in fuel flexible combustor design, little is known about the magnitude of fuel effects on CIVB induced flashback mechanism. Hence, this project investigates the effects of syngas compositions on flashback resulting from combustion induced vortex breakdown. The project uses controlled experiments and parametric modeling to understand the velocity field and flame interaction leading to CIVB driven flashback.

03 NATURAL GAS↗

DOE OSTI2014

A white paper: The Cornell-BNL FFAG-ERL Test Accelerator

This white paper describes a project that promises to propel high-power, high-brightness electron beam science and applications to an exciting new level. The collaborative effort between Brookhaven and Cornell will be a model for future projects between universities and national lab, taking advantage of the expertise and resources of both to investigate new topics in a timely and cost-effective manner.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

InSPIRE 2.0 (Final Technical Report)

Co-locating solar projects and agriculture can provide mutual benefits to local farmers (e.g., dual revenue streams, increased yields from pollinator services, irrigation reductions) and to the solar projects (e.g., reduced timeline/costs for installation and O&M, expanded market, increased PV efficiency from a cooler, vegetated microclimate). While prior work sought to demonstrate the feasibility of agricultural co-location (or "agrivoltaic") opportunities, there is a fundamental gap in data available to developers, landowners, and state agencies that prevents widespread deployment of these mutually beneficial practices. This project addressed this gap by (1) establishing a stakeholder research working group composed of multi-sector industry leaders and academics to provide guidance and assist with outreach; (2) undertaking targeted field-based research projects evaluating solar and agriculture co-location tradeoffs; (3) conducting analysis and modeling studies that complement the field-based research; and (4) developing a data portal to consolidate all data on this topic in one location.

14 SOLAR ENERGY↗

DOE OSTI2023

Time–Concentration Superposition for Linear Viscoelasticity of Polymer Solutions

The concentration dependence of linear viscoelastic properties of polymer solutions is a well-studied topic in polymer physics. Dynamic scaling theories allow qualitative predictions of polymer solution rheology, but quantitative predictions are still limited to model polymers. Meanwhile, the scaling properties of non-model polymer solutions must be determined experimentally. In present paper, the time–concentration superposition (TCS) of experimental data is shown to be a robust procedure for studying the concentration scaling properties of binary and ternary polymer solutions. TCS can not only identify whether power law scaling may exist or not, and over which concentration range, but also unambiguously estimate the concentration scaling exponents of linear viscoelastic properties for a range of non-model polymer solutions.

42 ENGINEERING↗

DOE OSTI2013

The DOE s In-Plant Training (INPLT) Model to Promote Energy Efficiency in the Industrial Sector

In-Plant Training (INPLT) is a new model for developing energy efficiency expertise within the US manufacturing companies participating in the U.S. Department of Energy s (DOE s) Better Buildings, Better Plants Program-a nationwide initiative to drive a 25% reduction in industrial energy intensity in 10 years. INPLTs are designed to fill a market niche by providing hands on training in a real world manufacturing plant environment. Through INPLTs, participants from multiple manufacturing plants, supply chains, utilities, and other external stakeholders learn how to conduct energy assessments, use energy analysis tools to analyze energy saving opportunities, develop energy management systems, and implement energy savings projects. Typical INPLT events are led by DOE-certified Energy Experts and range from 2-4 days. Topics discussed include: identification of cross-cutting or system specific opportunities; introduction to ISO 50001 Energy Management Systems; and energy project implementation and replication. This model is flexible, and can be tailored to suit the needs of specific industries. The INPLTs are a significant departure from the traditional single plant energy assessment model previously employed by DOE. INPLTs shift the focus from the concept of a single-plant s energy profile to a broader focus on training and capacity building among multiple industrial participants. The objective is to enable trainees to identify, quantify, implement and replicate future energy saving projects without continued external assistance. This paper discusses the INPLT model and highlights some of the initial outcomes from the successfully delivered INPLTs and the overall impact in terms of numbers of plants/participants trained, impacted energy footprints, and potential replication of identified opportunities.

In-Plant Training (INPLT) Model↗

DOE OSTI2019

Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences

Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret these data to advance human health. The recent rise of machine learning as a powerful technique to integrate multimodality, multifidelity data, and reveal correlations between intertwined phenomena presents a special opportunityin this regard. However, classical machine learning techniques often ignore the fundamental laws of physics and result in ill-posed problems or non-physical solutions. Multiscale modeling is a successful strategy to integrate multiscale, multiphysics data and uncover mechanisms that explain the emergence of function. However, multiscale modeling alone often fails to efficiently combine large data sets from different sources and different levels of resolution. Here we demonstrate that machine learning and multiscale modeling can naturally complement each other to create robust predictive models that integrate the underlying physics to manage ill-posed problems and explore massive design spaces. We critically review the current literature, highlight applications and opportunities, address open questions, and discuss potential challenges and limitations in four overarching topical areas: ordinary differential equations, partial differential equations, data-driven approaches, and theory-driven approaches. Towards these goals, we leverage expertise in applied mathematics, computer science, computational biology, biophysics, biomechanics, engineering mechanics, experimentation, and medicine. Our multidisciplinary perspective suggests that integrating machine learning and multiscale modeling can provide new insights into disease mechanisms, help identify new targets and treatment strategies, and inform decision making for the benefit of human health.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

On the Symmetry of Blast Waves

This paper presents a brief historical review of G. I. Taylor’s solution of the point blast wave problem which was applied to the Trinity test of the first atomic bomb. Lie group symmetry techniques (also referred to throughout this paper as geometric techniques) are used to derive Taylor’s famous two-fifths law that relates the position of a blast wave to the time after the explosion and the total energy released. The theory of exterior differential systems is combined with the method of characteristics to demonstrate that the solution of the blast wave problem is directly related to the basic relationships that exist between the symmetry (or geometry) and the physics of wave propagation through the equations of motion. The point blast wave model is cast in terms of two exterior differential systems, and both systems are shown to be integrable with local solutions for the velocity, pressure, and density along curves in space and time behind the blast wave. This work is dedicated to the memory of Professor Roy Axford, who introduced many of his students to the topic of symmetry analysis of differential equations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2011

Gasoline surrogate modeling of gasoline ignition in a rapid compression machine and comparison to experiments

The use of gasoline in homogeneous charge compression ignition engines (HCCI) and in duel fuel diesel - gasoline engines, has increased the need to understand its compression ignition processes under engine-like conditions. These processes need to be studied under well-controlled conditions in order to quantify low temperature heat release and to provide fundamental validation data for chemical kinetic models. With this in mind, an experimental campaign has been undertaken in a rapid compression machine (RCM) to measure the ignition of gasoline mixtures over a wide range of compression temperatures and for different compression pressures. By measuring the pressure history during ignition, information on the first stage ignition (when observed) and second stage ignition are captured along with information on the phasing of the heat release. Heat release processes during ignition are important because gasoline is known to exhibit low temperature heat release, intermediate temperature heat release and high temperature heat release. In an HCCI engine, the occurrence of low-temperature and intermediate-temperature heat release can be exploited to obtain higher load operation and has become a topic of much interest for engine researchers. Consequently, it is important to understand these processes under well-controlled conditions. A four-component gasoline surrogate model (including n-heptane, iso-octane, toluene, and 2-pentene) has been developed to simulate real gasolines. An appropriate surrogate mixture of the four components has been developed to simulate the specific gasoline used in the RCM experiments. This chemical kinetic surrogate model was then used to simulate the RCM experimental results for real gasoline. The experimental and modeling results covered ultra-lean to stoichiometric mixtures, compressed temperatures of 640-950 K, and compression pressures of 20 and 40 bar. The agreement between the experiments and model is encouraging in terms of first-stage (when observed) and second-stage ignition delay times and of heat release rate. The experimental and computational results are used to gain insight into low and intermediate temperature processes during gasoline ignition.

02 PETROLEUM↗

DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Report

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of subcritical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Program Review

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Summarizing experimental sensitivities of collider experiments to dark matter models and comparison to other experiments

Comparisons of the coverage of current and proposed dark matter searches can help us to understand the context in which a discovery of particle dark matter would be made. In some scenarios, a discovery could be reinforced by information from multiple, complementary types of experiments; in others, only one experiment would see a signal, giving only a partial, more ambiguous picture; in still others, no experiment would be sensitive and new approaches would be needed. In this whitepaper, we present an update to a similar study performed for the European Strategy Briefing Book performed within the dark matter at the Energy Frontier (EF10) Snowmass Topical Group We take as a starting point a set of projections for future collider facilities and a method of graphical comparisons routinely performed for LHC DM searches using simplified models recommended by the LHC Dark Matter Working Group and also used for the BSM and dark matter chapters of the European Strategy Briefing Book. These comparisons can also serve as launching point for cross-frontier discussions about dark matter complementarity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗