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

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DOE OSTI2022

Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles

Due to the high upfront cost of electric vehicles, many public transit agencies can afford only mixed fleets of internal combustion and electric vehicles. Optimizing the operation of such mixed fleets is challenging because it requires accurate trip-level predictions of electricity and fuel use as well as efficient algorithms for assigning vehicles to transit routes. We present a novel framework for the data-driven prediction of trip-level energy use for mixed-vehicle transit fleets and for the optimization of vehicle assignments, which we evaluate using data collected from the bus fleet of CARTA, the public transit agency of Chattanooga, TN. We first introduce a data collection, storage, and processing framework for system-level and high-frequency vehicle-level transit data, including domain-specific data cleansing methods. We train and evaluate machine learning models for energy prediction, demonstrating that deep neural networks attain the highest accuracy. Based on these predictions, we formulate the problem of minimizing energy use through assigning vehicles to fixed-route transit trips. We propose an optimal integer program as well as efficient heuristic and meta-heuristic algorithms, demonstrating the scalability and performance of these algorithms numerically using the transit network of CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Status of MQXFB Quadrupole Magnets for HL-LHC

The MQXFB magnets are superconducting quadrupoles with nominal peak field on the conductor of 11.3 T. With their magnetic length of 7.2 m, they stand as the longest Nb3Sn accelerator magnets designed and manufactured up to now. Together with the companion MQXFA 4.2 m long units, built by the US Accelerator Research Program, they are at the heart of HL-LHC, as they shall replace the inner triplet quadrupoles at either side of the ATLAS and CMS interaction regions of the LHC. This technology has benefited from many years of development, and this specific design was validated with successful short models (MQXFS, 1.2 m long). More recently, several MQXFA magnets were shown to satisfy HL-LHC requirements. In this paper, we report on the cold test results of four MQXFB magnets, focusing on performance, training, behavior after thermal and powering cycles, and field quality. We then provide an update of the overall status, including ongoing verifications of design changes at the level of the coil fabrication.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Batteries (2023 Annual Progress Report)

This document summarizes the progress of VTO battery R&D projects supported during the fiscal year 2023. Its R&D focus was on the development of high-energy batteries for PEVs. The electrochemical energy storage roadmap describes ongoing and planned efforts to develop electrochemical storage technologies for EVs. To advance battery technology, which can in turn improve market penetration of PEVs, the program investigates various battery chemistries to overcome specific technical barriers, e.g., battery cost, performance, life (both the calendar life and the cycle life), its tolerance to abusive conditions, and its recyclability/sustainability.

25 ENERGY STORAGE↗
DOE OSTI2024

Screening Tool for Equitable Adoption and Deployment of Solar (STEADy Solar)

The Screening Tool for Equitable Adoption and DeploYment of Solar (STEADy Solar) is a database and mapping tool designed to promoting clean energy investments for low-income communities across the United States. The tool indicates locations that may be eligible for the Investment Tax Credit bonus adders defined in the 2022 Inflation Reduction Act (IRA) and combines this information with demographics, social vulnerability, solar technical potential, solar economics (modeled net present value), and building counts by use-type. It can be used by states, municipalities, community-based organizations, developers, and researchers to identify sites where solar projects may be economical and where federal incentives may be available to support equitable adoption of solar. Specific values include: Areas eligible for the Energy Communities Tax Credit Bonus Program (including brownfield site counts) Areas eligible for the Low Income Communities Bonus Credit Program (including Tribal Lands, and covered affordable housing project counts) Areas categorized as disadvantaged by Justice40 Commercial and Residential Solar economics characterized by the Net Present Value and Simple Payback Period Total Population, Race, and Ethnicity Median Household Income, Poverty rate, Household Tenure Social Vulnerability Count of buildings, developable rooftop solar capacity (in kWdc) and estimated annual generation potential (in kWh) on four building types: Government General Services, Government Emergency Response, Grade Schools, and Colleges/Universities. The linked report describes the STEADy dataset metadata and presents high level insights from the data. The downloadable and formatted excel dataset makes it easy for users to gain insights for their locations. Supporting .csv and shapefiles provide users with the full data to run their own analyses on equitable solar siting.

14 SOLAR ENERGY↗
DOE OSTI2021

Optimized Quantum Program Execution Ordering to Mitigate Errors in Simulations of Quantum Systems

Simulating the time evolution of a physical system at quantum mechanical levels of detail - known as Hamiltonian Simulation (HS) - is an important and interesting problem across physics and chemistry. For this task, algorithms that run on quantum computers are known to be exponentially faster than classical algorithms; in fact, this application motivated Feynman to propose the construction of quantum computers. Nonetheless, there are challenges in reaching this performance potential. Prior work has focused on compiling circuits (quantum programs) for HS with the goal of maximizing either accuracy or gate cancellation. Our work proposes a compilation strategy that simultaneously advances both goals. At a high level, we use classical optimizations such as graph coloring and travelling salesperson to order the execution of quantum programs. Specifically, we group together mutually commuting terms in the Hamiltonian (a matrix characterizing the quantum mechanical system) to improve the accuracy of the simulation. We then rearrange the terms within each group to maximize gate cancellation in the final quantum circuit. Furthermore, these optimizations work together to improve HS performance and result in an average 40% reduction in circuit depth. This work advances the frontier of HS which in turn can advance physical and chemical modeling in both basic and applied sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Deployment of Gaussian Surrogate Model for Ad-Hoc Adjustments to Elastic Scattering Angular Distributions [Slides]

This presentation is on the deployment of gaussian surrogate model for ad-hoc adjustments to elastic scattering angular distributions. Discussed throughout the presentation is motivation for this lecture. Specifically, the gaussian surrogate models, validation of method with Pb-208, and the application on Be-9 are highlighted. The presentation concludes with a summary.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Iodine Effects on Medical Isotope Producer Delay & Guard Bed Temperature and Performance in Support of NA-23 Program

In support of NA-23’s objective to accelerate the establishment of a reliable commercial United States (U.S.) domestic supply of 99Mo produced without the use of highly enriched uranium (HEU), the Pacific Northwest National Laboratory (PNNL) was tasked with modeling the performance of activated carbon delay and guard beds that may be typical for non-HEU 99Mo production processes. The specific tasks accomplished by PNNL included calculations of long-term effects of iodine on delay bed performance and development of a finite element simulation to better understand delay bed performance under various scenarios specifically with radioxenon and radioiodine decay heating of the delay beds. The main issue of interest in this study is understanding the effect of iodine on the abatement performance of the beds if iodine is not sufficiently removed from gases prior to reaching the delay beds. Finite element simulations of delay bed performance were developed using COMSOL Multiphysics® Software. These simulations are based on partial differential equations that describe xenon and iodine adsorption, heat transfer and decay of radioxenon and radioiodine isotopes. Heat transfer in the activated carbon beds is simulated with a heat source tied to the decay of radioactive xenon and iodine species. These simulations were used to investigate delay bed temperature and hold up time using radioxenon and radioiodine activities and flowrates expected from a non-HEU production process. A bounding case scenario was simulated, where all the iodine was released into the delay beds due to insufficient guarding of the delay beds. In addition, preliminary investigations of the guard beds were conducted.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Modeling the Interaction Between Energy Efficiency and Demand Response on Regional Grid Scales: Preprint

With increasing penetration of intermittent renewable generation at grid and distributed scales, flexible building loads can provide significant system value and support the evolving needs of the grid. The growing value of load flexibility may complicate the traditional separation between energy efficiency (EE) and demand response (DR). EE measures may compete in some cases with a building’s DR capabilities but complement one another in other cases. EE can also increase or decrease the need for DR at the system level and change the availability of DR to meet system needs. In this study we present a bottom-up approach to modeling interactive effects between EE and DR in buildings within two regions of the US electricity grid. From a library of building simulation models for different buildings and climates, we synthesize system-level demand profiles and the impacts of potential future EE portfolios. Coupling the underlying building models with a database of DR-enabling technologies, we then compute the quantity of DR that can be delivered in each scenario. The results show that EE and DR interactions are largely driven by the timing of EE savings that are measure-specific and the coincidence with system peak demand that is region-specific. We also find that perspective of the impacts matters – for instance that some EE measures reduce the system need for DR but also reduce the DR potential. Our results imply that utility EE and DR programs developed without considering interactive effects may lead to increased grid-management challenges over the long term.

buildings↗
DOE OSTI2020

Quantum computing based hybrid solution strategies for large-scale discrete-continuous optimization problems

Quantum computing (QC) has gained popularity due to its unique capabilities that are quite different from that of classical computers in terms of speed and methods of operations. This paper proposes hybrid models and methods that effectively leverage the complementary strengths of deterministic algorithms and QC techniques to overcome combinatorial complexity for solving large-scale mixed-integer programming problems. Four applications, namely the molecular conformation problem, job-shop scheduling problem, manufacturing cell formation problem, and the vehicle routing problem, are specifically addressed. Large-scale instances of these application problems across multiple scales ranging from molecular design to logistics optimization are computationally challenging for deterministic optimization algorithms on classical computers. To address the computational challenges, hybrid QC-based algorithms are proposed and extensive computational experimental results are presented to demonstrate their applicability and efficiency. The proposed QC-based solution strategies enjoy high computational efficiency in terms of solution quality and computation time, by utilizing the unique features of both classical and quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Knowledge Beacons: Web services for data harvesting of distributed biomedical knowledge

The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. As an activity within the feasibility phase of a project called “Translator” (https://ncats.nih.gov/translator) funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (https://biolink.github.io/biolink-model/). Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Technical Report on Waveform Fit Metrics for Global Models

The new WAVEFORMS Initiative in the Ground-based Nuclear Detonation Detection (GNDD) program includes an increased emphasis on the development of Earth models and methods to predict entire seismic and acoustic waveforms more accurately. In general, this increased emphasis is predicated on the need to better characterize seismic events and provide improved model-based discrimination between event types including earthquakes and explosions. More specifically, while current moment tensor inversion methods tend to work well for larger events (M>~4) using tuned 1-D Earth models, the development of state-of-the-art 3-D models and methods is required for the prediction of shorter period waves over large areas for discrimination of smaller events. There is no standard metric for model-based waveform prediction accuracy used in the waveform modeling/inversion community. However, there are several popular waveform misfit definitions; and minimizing the corresponding objective functions is the goal of waveform inversion. Some example misfit definitions employed for adjoint waveform tomography include measures of simple travel time differences (e.g. Tape et al., 2010), cross-correlation travel time differences (e.g. Luo and Schuster, 1991), multi-taper frequency dependent methods (e.g. Lei et al., 2020), time-frequency phase misfit functions (e.g. Fichtner 2010; Rodgers et al., 2022), normalized cross-correlation methods (e.g. Tao et al., 2018), and others. In some cases, these misfit definitions also involve complicated weighting schemes and summations over multiple frequency bands making it difficult to duplicate the misfit measurement with alternative models and datasets. Although each of the misfit definitions mentioned above are useful for developing waveform models, the actual misfit values are not usually meaningful outside of a given project, model, and/or dataset. Therefore, it is difficult to understand and communicate model performance for predicting waveforms and comparing to other models and/or new model iterations with a different dataset. Therefore, there is a need for a generalized method for evaluating overall model performance that is independent from the specific misfit chosen to develop the waveform models that is also intuitive and meaningful. In this report, we describe a new metric we refer to as ‘Percent of Correlated Signal’. The following sections describe and demonstrate the metric with a case study event and a more rigorous test using a random selection of globally distributed events. While the focus here is on global tomography models, the metric is meant to applicable to regional ‘wiggle-for-wiggle’ waveform models/studies as well.

58 GEOSCIENCES↗
DOE OSTI2023

Resilience Development for Electric Energy Delivery Sytems (ResDEEDS): A Tool for Power System Resilience Planning (Rev. 1)

The INL Resilience Framework is built to be customized to a particular system’s characteristics, resilience goals, and hazards that it is likely to face. The challenge with a framework that is built to be customized is that it requires more effort from the user to understand the framework and apply it correctly to a particular system. The goal of the web application described here is to automate the framework application as much as possible. Inputs from users are standardized into a common format, but the modeling platform used is a modular framework built to adapt to any system. Baseline effects from common hazards are programmed with stochastic variables to allow for quick exploration of hazard impacts, but can be customized down to component-level impact if a user desires a high level of detail and specificity.

17 WIND ENERGY↗
DOE OSTI2022

Nonlinear burn control in ITER using adaptive allocation of actuators with uncertain dynamics

Abstract ITER will be the first tokamak to sustain a fusion-producing, or burning, plasma. If the plasma temperature were to inadvertently rise in this burning regime, the positive correlation between temperature and the fusion reaction rate would establish a destabilizing positive feedback loop. Careful regulation of the plasma’s temperature and density, or burn control, is required to prevent these potentially reactor-damaging thermal excursions, neutralize disturbances and improve performance. In this work, a Lyapunov-based burn controller is designed using a full zero-dimensional nonlinear model. An adaptive estimator manages destabilizing uncertainties in the plasma confinement properties and the particle recycling conditions (caused by plasma–wall interactions). The controller regulates the plasma density with requests for deuterium and tritium particle injections. In ITER-like plasmas, the fusion-born alpha particles will primarily heat the plasma electrons, resulting in different electron and ion temperatures in the core. By considering separate response models for the electron and ion energies, the proposed controller can independently regulate the electron and ion temperatures by requesting that different amounts of auxiliary power be delivered to the electrons and ions. These two commands for a specific control effort (electron and ion heating) are sent to an actuator allocation module that optimally maps them to the heating actuators available to ITER: an electron cyclotron heating system (20 MW), an ion cyclotron heating system (20 MW), and two neutral beam injectors (16.5 MW each). Two different actuator allocators are presented in this work. The first actuator allocator finds the optimal mapping by solving a convex quadratic program that includes actuator saturation and rate limits. It is nonadaptive and assumes that the mapping between the commanded control efforts and the allocated actuators (i.e. the effector model) contains no uncertainties. The second actuator allocation module has an adaptive estimator to handle uncertainties in the effector model. This uncertainty includes actuator efficiencies, the fractions of neutral beam heating that are deposited into the plasma electrons and ions, and the tritium concentration of the fueling pellets. Furthermore, the adaptive allocator considers actuator dynamics (actuation lag) that contain uncertainty. This adaptive allocation algorithm is more computationally efficient than the aforementioned nonadaptive allocator because it is computed using dynamic update laws so that finding the solution to a static optimization problem is not required at every time step. A simulation study assesses the performance of the proposed adaptive burn controller augmented with each of the actuator allocation modules.

Physics↗
DOE OSTI2024

Options for Achieving Cost Reduction in Advanced Reactors through Open Architecture

A key contributor to high capital costs and schedule overruns for new nuclear power plants is lack of standardization, driven by site-specific customization and construction of multiple designs by competing vendors rather than commitment to a single standardized program. While advanced reactor vendors typically individually target repeat construction of standardized units, the many competing designs could exacerbate the problem. “Open Architecture”, the open specification of requirements and interfaces for structures, systems and components (SSCs), has been proposed as a means of promoting standardization, by facilitating existing non-nuclear suppliers to enter the industry and/or allowing SSCs to be configured for more than one reactor within the same technology type. Contracting mechanisms that facilitate information sharing and alignment of incentives between stakeholders may complement such an approach. A preliminary scheme is presented for selection of SSCs for which such strategies could be adopted, based on a vendor make/buy decision model and stakeholder interviews. SSCs are categorized according to number of suppliers and their contribution to the reactor’s competitive edge. SSCs with many potential suppliers and a high contribution to competitive edge may be attractive for widening the supply chain via open specification of system requirements and interfaces, e.g., SSCs in the power island. SSCs with few suppliers and low contribution to competitive edge may be potential avenues for common system specification between vendors, e.g., some of the auxiliary SSCs. Potential cost reductions from such strategies will depend upon the size of the build program and the reactor type.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

A tool and a methodology to use macros for abstracting variations in code for different computational demands

Scientific software used on high-performance computing platforms is in a phase of transformation because of the combined increase in the heterogeneity and complexity of models and hardware platforms. Having separate implementations for different platforms can easily lead to combinatorial explosions; therefore, the computational science community has been looking for mechanisms to express code through abstractions that can be specialized for different platforms. Most existing approaches use template meta-programming in C++, and are, therefore language specific. Here, we have developed a tool that uses customized expansion of macros to mimic some of C++ behavior in other languages. It enables unification of any code variants that may be necessary to run efficiently on different target architectures and different computational environments through use of macros with multiple alternative definitions and ability to arbitrate on definition selection for expansion. Combined with two other tools, a custom runtime, and a user specified recipe translator, our custom macroprocessor becomes a part of an overall performance portability solution that does not depend on any specific programming language. We also use macros as code-shorthand that lets code snippets become building blocks that allow variations in control flow to explore performance options. We demonstrate use of macros in Flash-X, a multiphysics multicomponent code with many Fortran legacy components derived from an earlier community code FLASH.

Heterogenous computing↗
DOE OSTI2022

M4SF-22LL010301062-Surface Complexation Database and Hybrid ML Model Development for GDSA

This progress report (Level 4 Milestone Number M4SF-22LL010301062) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite International Collaborations Activity Number Activity SF-22LL01030106. The activity is focused on our long-term commitment to engaging our partners in international nuclear waste repository research. The focus of this milestone is the establishment of international collaborations for surface complexation modeling and the associated impacts of unlocking larger, community-based datasets. More specifically, we are developing a database framework for Spent Fuel and Waste and Science Technology (SFWST) that is aligned with the Helmholtz Zentrum Dresden Rossendorf (HZDR) sorption database development group in support of the database needs of the SFWST program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

An Application of Faster R-CNNs in Object Detection Efforts Applied to the Critical Infrastructure Domain

Object detection and segmentation approaches have been successfully applied to multiple interdisciplinary domains ranging from medical imaging to autonomous vehicles. The following study details efforts to apply segmentation methods to the critical infrastructure domain. Specifically, the identification of critical sub-components of four facilities: airports, hospitals, hydroelectric dams, and water treatment plants. Data for this study was extracted from the U.S. Department of Agriculture’s National Agriculture Imagery Program data set. Each facility class was considered independently of the other facilities, producing four different segmentation models during the testing and training process. Ultimately, the study team concluded there are significant challenges associated with object detection modeling when applied to facility analysis within the critical infrastructure domain. The study team was able to identify possible sources of these challenges that could be potentially addressed in future work.

97 MATHEMATICS AND COMPUTING↗