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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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At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Design of the cryogenic systems for the Near and Far LAr-TPC detectors of the Short-Baseline Neutrino program (SBN) at Fermilab

The Short-Baseline Neutrino (SBN) physics program at Fermilab and Neutrino Platform (NP) at CERN are part of the international Neutrino Program leading to the development of Long-Baseline Neutrino Facility/Deep Underground Neutrino Experiment (LBNF/DUNE) science project. The SBN program consisting of three Liquid Argon Time Projection Chamber (LAr-TPC) detectors positioned along the Booster Neutrino Beam (BNB) at Fermilab includes an existing detector known as MicroBooNE (170-ton LAr-TPC) plus two new experiments known as SBN’s Near Detector (SBND, ~260 tons) and SBN’s Far Detector (SBN-FD, ~760 tons). All three detectors have distinctly different design of their cryostats thus defining specific requirements for the cryogenic systems. Fermilab has already built two new facilities to house SBND and SBN-FD detectors. The cryogenic systems for these detectors are in various stages of design and construction with CERN and Fermilab being responsible for delivery of specific sub-systems. This contribution presents specific design requirements and typical implementation solutions for each sub-system of the SBND and SBN-FD cryogenic systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Data Driven Analysis for Modernization Program Management

NNSA is responsible for managing national nuclear security missions: ensuring a safe, secure, and reliable nuclear deterrent; supplying nuclear fuel to the Navy; and supporting the nation’s nuclear nonproliferation efforts. However, over half of NNSA’s facilities are more than 40 years old, and roughly one-third date back to the Manhattan Project. To execute its critical nuclear security missions, NNSA is making large investments to modernize its nuclear production capabilities. This ramp up represents NNSA’s largest modernization effort since the Cold War. Given the scale of these efforts, NNSA’s Office of Secondary Stage Production Modernization has implemented data driven techniques to prioritize investments and inform strategic decision making. NNSA, with support from its site managing contractors, has developed and implemented an integrated schedule and risk management system to address the issues and limitations with the traditional approach. The multi-year integrated schedules are key to identifying program linkages and managing large portfolios comprised of many different projects and efforts. In conjunction with the integrated schedule, a new program risk management system has also been developed and implemented, which manages program risks and opportunities, along with specific mitigation strategies to reduce or eliminate the risks per timelines that are tracked in the integrated schedule. This paper is supplemented with a follow-on presentation on effective management of program material and throughput modeling.

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

Revenue prediction for integrated renewable energy and energy storage system using machine learning techniques

Revenue estimation for integrated renewable energy and energy storage systems is important to support plant owners or operators’ decisions in battery sizing selection that leads to maximized financial performances. A common approach to optimizing revenues of a hybrid hydro and energy storage system is using mixed-integer linear programming (MILP). Although MILP models can provide accurate production cost estimations, they are typically very computationally expensive. To provide a fast yet accurate first-step information to hydropower plant owners or operators who consider integrating energy storage systems, we propose an innovative approach to predicting optimal revenues of an integrated energy generation and storage system. In this study, we examined the performance of two prediction techniques: Generalized Additive Models (GAMs) and machine learning (ML) models developed based on artificial neural networks (ANN). Predictive equations and models are generated based on optimized solutions from a market participation optimization model, the Conventional Hydropower Energy and Environmental Resource System (CHEERS) model. The two predicting techniques reduce the computational time to evaluate annual revenue for one set of battery configurations from 3 h to 1 to 4 min per run while also being implementable with significantly less data. The model validation prediction errors of developed GAMs and ML models are generally below 5%; for model testing predictions, the ML models consistently outperform the regression equations in terms of root mean square errors. This new approach allows plant owners, operators, or potential investors to quickly access multiple battery configurations under different energy generation and market scenarios. This new revenue prediction method will therefore help reduce the barriers, and thereby promoting the deployment of battery hybridization with existing renewable energy sources.

13 HYDRO ENERGY↗
DOE OSTI2022

Electrochemically-Induced Phase Transformations in Battery Storage Compounds (Final Technical Report)

Compounds of interest for ion storage in advanced batteries frequently exhibit phase transformations as the working ion concentration varies. Under large electrochemical driving forces inherent to practical use, systems are often driven far from equilibrium. This program combines experiments and theory to understand the phase transition behavior of ion insertion compounds when electrochemically driven far from equilibrium. As model systems, we focus on alkaline metal phosphates AMPO4 (A = alkali; M = first row transition metal) of olivine structure, which are both technologically interesting and ideally suited for fundamental study due to the ability to systematically tune transformation strain, and along with it, the phase transformation pathway. Behavior in compositions having large transformation strains (~15 vol%) requiring plasticity for strain accommodation is emphasized. Experimental techniques include operando characterization of structure while simultaneously varying electrokinetic parameters, and high resolution microscopy of nanoscale and interfacial phenomena. Phase-field modeling is used to model the thermodynamics and kinetics of competing transformation pathways, extended to include the effects of plasticity, and integrated with porous electrode kinetic theory to treat multi-particle effects. Success in this project will lead to an ability to design ion storage compounds with predictable transformation pathways, electrochemical kinetics, capacity utilization, and durability. New technologically important compounds may also be discovered.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Systems-Level Modeling for CRISPR-Based Metabolic Engineering

The CRISPR-Cas system has enabled the development of sophisticated, multigene metabolic engineering programs through the use of guide RNA-directed activation or repression of target genes. To optimize biosynthetic pathways in microbial systems, we need improved models to inform design and implementation of transcriptional programs. Recent progress has resulted in new modeling approaches for identifying gene targets and predicting the efficacy of guide RNA targeting. Genome-scale and flux balance models have successfully been applied to identify targets for improving biosynthetic production yields using combinatorial CRISPR-interference (CRISPRi) programs. Here, the advent of new approaches for tunable and dynamic CRISPR activation (CRISPRa) promises to further advance these engineering capabilities. Once appropriate targets are identified, guide RNA prediction models can lead to increased efficacy in gene targeting. Developing improved models and incorporating approaches from machine learning may be able to overcome current limitations and greatly expand the capabilities of CRISPR-Cas9 tools for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Hydrogen Component Leak Rate Quantification for System Risk and Reliability Assessment through QRA and PHM Frameworks: Preprint

The National Renewable Energy Laboratory's (NREL) Hydrogen Safety Research and Development (HSR&D) program in collaboration with the University of Maryland's Systems Risk and Reliability Analysis Laboratory (SyRRA) are working to improve reliability and reduce risk in hydrogen systems. This approach strives to use quantitative data on component leaks and failures, together with Prognosis and Health Management (PHM), and Quantitative Risk Assessment (QRA) to identify at-risk components, reduce component failures and downtime, and predict when components require maintenance. Hydrogen component failures increase facility maintenance cost, facility downtime, and reduce public acceptance of hydrogen technologies, ultimately increasing facility size and cost because of potentially overly conservative requirements. Leaks are a predominant failure mode for hydrogen components. However, uncertainties in the amount of hydrogen emitted from leaking components and the frequency of those failure events limit the understanding of the risks that they present under real-world operational conditions. NREL has deployed a test fixture, the Leak Rate Quantification Apparatus (LRQA), to quantify the mass flow rate of leaking gases from medium and high-pressure components that have failed while in service. Quantitative hydrogen leak rate data from this system could ultimately be used to better inform risk assessment and Regulation Codes and Standards (RCS). Parallel activity explores the use of PHM and QRA techniques to assess and reduce risk, thereby improving safety and reliability of hydrogen systems. The results of QRAs could further provide a systematic and science-based foundation for the design and implementation of RCS, as in the latest versions of the NFPA 2 code for gaseous hydrogen stations. Alternatively, data-driven techniques of PHM could provide new damage diagnosis and health-state prognosis tools. This research will help end users, station owners and operators, and regulatory bodies move towards risk-informed preventative maintenance versus emergency corrective maintenance, reducing cost and improving reliability. Predictive modelling of failures could improve safety and affect RCS requirements such as setback distances at liquid refuelling sites. The combination of leak rate quantification research, PHM, and QRA can lead to better informed models enabling data-based decision to be made for hydrogen system safety improvements.

codes and standards↗
DOE OSTI2015

Development of numerical simulation system for thermal-hydraulic analysis in fuel assembly of sodium-cooled fast reactor

A numerical simulation system, which consists of a deformation analysis program and three kinds of thermal-hydraulics analysis programs, is being developed in Japan Atomic Energy Agency in order to offer methodologies to clarify thermal-hydraulic phenomena in fuel assemblies of sodium-cooled fast reactors under various operating conditions. This paper gives the outline of the system and its applications to fuel assembly analyses as a validation study.

42 ENGINEERING↗
DOE OSTI2016

Design and Evaluation of joint resistance in SSC Rutherford type cable splices for Torus magnet for the Jefferson Lab 12 GeV Upgrade

The Hall B 3.6-T superconducting torus magnet is being designed and built as part of the Jefferson Lab 12-GeV upgrade. The magnet consists of six trapezoidal coils connected in series, with an operating current of 3770 A. The magnet and the joints (or splices) connecting the coils are all conduction cooled by supercritical 4.6-K helium. This paper studies the design and manufacturing process of the splices made between two SSC Rutherford-type cables and discusses the tests performed to evaluate the performance of the splices under varying incident magnetic fields.

Ghoshal, Probir K.↗
DOE OSTI2018

Dynamic Studies of Photo- and Electron-Induced Reactions on Nanostructured Surfaces

Our current research program examines the photon- and electron-initiated reaction mechanisms, half-collision dynamics, and other nonequilibrium-excited dynamics effects, occurring with excitation of adsorbates on well-characterized metal-oxide of metalchalcogenide surfaces, both in single-crystal and in nanocrystalline forms. The program has made extensive use of STM methods, collaborations with the Nanoprobing SPLEEM system at Brookhaven National Lab, and XPS methods. As our current program terminates, it brings to an end a sustained and major effort to understand reactions and electronic structure on materials of interest for photochemistry on precision surfaces. The last two close-out years of our program allowed us to complete our STM surface studies, interact with scientists at BNL on programs useful for two dimensional (2D) materials, and initiate a new effort in ultrafast two-photon photoemission spectroscopy. Our work has then shown how nanoscale stressed surface regions on sold crystal surfaces (typically TiO 2 ) lead to enhanced reactivity of adsorbate molecules – a result of much importance for nanocatalysis. In addition we have developed several new surface and near-surface probing methods – these, also, are of general use to the community. Finally due to the pervasive interest in DOE labs in these materials, we have exploited our earlier synchrotron-based understanding of the electronic structure in (2D) materials to begin a study of surface chemical reactions in these same materials and their corresponding molecular dynamics. These efforts are described briefly below and in the references or DOE publications presented in the publications section of this report. We are pleased to have been able to contribute so many publications in the last two years of this many year DOE program. We also wish to thank DOE for the sustained funding that has made this program such a success.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Optimizing design and dispatch of a renewable energy system with combined heat and power

We embellish a mixed-integer program that prescribes a set of renewable energy, conventional generation, and storage technologies to procure, along with a corresponding dispatch strategy. Specifically, we add combined heat and power to this set. The model minimizes fixed and operational costs less incentives for the use of various technologies, subject to a series of component interoperability and system-wide constraints. The resulting mixed-integer linear program contains hundreds of thousands of variables and constraints. We demonstrate how to efficiently formulate and solve the corresponding instances such that we produce near-optimal solutions in minutes. A previous rendition of the model required hours of solution time for the same instances.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Nuclear-Renewable Energy Systems Secondary Product Market Analysis Study

In order to properly create a program surrounding the development of any technological concept it is necessary to fully understand the market in which it is being developed. In the case of Integrated Nuclear-Renewable Hybrid Energy Systems (HES), there are two economic markets in which it must be able to participate in: the electricity market and the secondary product market associated with the specific system. The purpose of the present report is to characterize the secondary product market in the U.S. and to provide recommendations for further developing the HES program. While HESs have been discussed in depth in many other reports, it is helpful to discuss them briefly in the present work [REF]. The concept of the HES can be deduced to a system, featuring a combination of a nuclear power plant, a renewable energy source, and an industrial manufacturing plant . The system is designed in a fashion that allows it either to produce electricity or to manufacture a secondary product as needed. The primary benefit of this concept lies in its ability to maximize economic performance of the integrated system and to manufacture products in a carbon-free manner. A secondary benefit is the enhanced supply-side flexibility gained by allowing the HES to economically provide grid services. A key tenant to nuclear power plant economics in today’s electricity market is their ability to operate at a very high capacity factor. Unfortunately, in regions with a high penetration of renewable energy, the carbon free energy produced by nuclear power may not be needed at all times. This forces the nuclear power plant to find a user for its excess capacity. This may include paying the electric grid to find a user, releasing energy to the environment by ‘dumping steam’, or reducing power. If the plant is unable to economically or safely do any of these actions, the plant is at risk of being shutdown. In order to allow for nuclear power plants to continue to contribute carbon free electricity to the grid in a future with high renewable energy penetration, HESs allow for excess capacity to be diverted to a chemical process. If the chemical products sold on the market replace those sold previously – which would be the case if a currently operating manufacturing plant was modified to be a HES component – then the products would now be produced with reduced emission of carbon and other greenhouse gases. There are several key economic barriers that must be surmounted for HESs to be developed. The two primary barriers are the increased capital cost associated with coupling and controlling the HES components and the decreased utilization of the manufacturing plant capital due to intermittent energy delivery . Because of this, manufacturing plants that are less complex and have smaller non-variable operations and capital costs may be more attractive for integration. A secondary economic barrier for the HES is the market availability for its products. The system must operate a region where there is either an intermittent demand for its electricity, an intermittent demand for its secondary product, or both. In a region with an intermittent demand, product prices should shift accordingly, making it less attractive to produce one of the products. The HES then can shift production in order to maximize profit. Without an intermittent demand for at least one of its products, there would be little need for it to expend the extra capital required for integration as an HES.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Assessment of allowance mechanism China's carbon trading pilots

The allowance mechanism is one of the core and sensitive aspects in design of a carbon trading scheme and affects the compliance cost for each company covered under the scheme. By examining China's allowance mechanism from two aspects including allowance allocation and allowance distribution, this paper compares China's carbon trading pilots with the EU Emissions Trading System and California Cap-and-Trade Program, and through the comparison identify issues that affect the efficiency of the pilots. The paper also recommends course of actions to strengthen China's existing pilots and build valuable experiences for the establishment of the national cap-and-trade system in China.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida

Abstract The present work evaluates historical precipitation and its indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) in suites of dynamically and statistically downscaled regional climate models (RCMs) against NOAA’s Global Historical Climatology Network Daily (GHCN-Daily) dataset over Florida. The models examined here are: (1) nested RCMs involved in the North American CORDEX (NA-CORDEX) program, (2) variable resolution Community Earth System Models (VR-CESM), (3) Coupled Model Intercomparison Project phase 5 (CMIP5) models statistically downscaled using localized constructed analogs (LOCA) technique. To quantify observational uncertainty, three in situ-based (PRISM, Livneh, CPC) and three reanalysis (ERA5, MERRA2, NARR) datasets are also evaluated against the station data. The reanalyses and dynamically downscaled RCMs generally underestimate the magnitude of the monthly precipitation and the frequency of the extreme rainfall in summer. The models forced with CanESM2 miss the phase of the seasonality of extreme precipitation. All models and reanalyses severely underestimate both the mean and interannual variability of mean wet-day precipitation (SDII), consecutive dry days (CDD), and overestimate consecutive wet days (CWD). Metric analysis suggests large uncertainty across NA-CORDEX models. Both the LOCA and VR-CESM models perform better than the majority of models. Overall, RegCM4 and WRF models perform poorer than the median model performance. The performance uncertainty across models is comparable to that in the reanalyses. Specifically, NARR performs poorer than the median model performance in simulating the mean indices and MERRA2 performs worse than the majority of models in capturing the interannual variability of the indices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Automated Radiology Report Summarization Using an Open-Source Natural Language Processing Pipeline

Diagnostic radiologists are expected to review and assimilate findings from prior studies when constructing their overall assessment of the current study. Radiology information systems facilitate this process by presenting the radiologist with a subset of prior studies that are more likely to be relevant to the current study, usually by comparing anatomic coverage of both the current and prior studies. It is incumbent on the radiologist to review the full text report and/or images from those prior studies, a process that is time-consuming and confers substantial risk of overlooking a relevant prior study or finding. This risk is compounded when patients have dozens or even hundreds of prior imaging studies. Our goal is to assess the feasibility of natural language processing techniques to automatically extract asserted and negated disease entities from free-text radiology reports as a step towards automated report summarization. We compared automatically extracted disease mentions to a gold-standard set of manual annotations for 50 radiology reports from CT abdomen and pelvis examinations. The automated report summarization pipeline found perfect or overlapping partial matches for 86% of the manually annotated disease mentions (sensitivity 0.86, precision 0.66, accuracy 0.59, F1 score 0.74). The performance of the automated pipeline was good, and the overall accuracy was similar to the interobserver agreement between the two manual annotators.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

A matheuristic for design and dispatch of a utility-connected distributed energy system

Modeling distributed power generation systems often requires complicated mathematical expressions that present challenges for commercial optimization solvers. Here, this paper presents a matheuristic to solve a mixed-integer optimization model that informs decisions regarding the design and dispatch of a utility-connected microgrid. We deploy a genetic algorithm to search the system design space and a linear program to solve the economic dispatch problem. The model is a component of a web tool that requires solutions within a few minutes. Our method yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of our test cases compared to only 10% of our test cases by a traditional optimization solver in the same amount of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Model-based predictive control of multi-stage air-source heat pumps integrated with phase change material-embedded ceilings

This paper presents a model-based predictive control strategy to optimize the operations of phase change material (PCM) ceiling panels coupled with a multi-stage air-source heat pump. A three-stage prototype heat pump unit has been built and tested in the laboratory, with the low and medium stages designed for space heating/cooling and the high compression stage dedicated to charging of the PCM energy storage. To facilitate optimal control of the integrated heat pump system, a mixed-integer linear programming formulation is derived through linearization of the heat pump model and a mixed-integer reformulation of the PCM dynamic governing equations. A predictive control strategy is synthesized based on the resultant control formulation and implemented in a receding horizon scheme that optimizes the PCM charging and the zone temperature schedules simultaneously to leverage both the passive (associated with building construction materials) and active (PCM) storage capacities of a building. The control strategy has been tested along with three benchmarking control scenarios using a co-simulation platform for a prototypical detached house in Atlanta, GA. In this study, test results showed that application of the proposed control strategy to the PCM-integrated heat pump could provide 27.1% electricity cost savings while a fine tuned rule-based control strategy could achieve cost savings of 20.4%, compared to a baseline case without PCM storage, under a time-of-use rate tariff.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Experimental studies of the arc chamber short circuit failure mechanism on the DIII-D neutral beam system

Here we report on efforts to improve performance and longevity of the Neutral Beam Injection (NBI) system by initiating a R&D program aimed at studying the most common failure mechanism for the ion sources. To this end a filament driven plasma chamber has been constructed with plasma parameters similar to the arc chamber of NBI ion sources. A preliminary report of an investigation into the most common failure is presented here: The failure mechanism observed during helium operations on DIII-D is the result of electrical breakdown of the insulation material that separates the filament plates from the anode. The fault is reproduced in a table top experiment analogous to the DIII-D NBI ion source in key parameters and proposals for amelioration of the issue are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Microstructural development from interdiffusion and reaction between U–Mo and AA6061 alloys annealed at 600° and 550 °C

The U.S. Material Management and Minimization Reactor Conversion Program is developing low enrichment fuel systems encased in Al-alloy for use in research and test reactors. Monolithic fuel plates have local regions where the Usingle bondMo fuel plate may come into contact with the Al-alloy 6061 (AA6061) cladding. This results in the development of interdiffusion zones with complex microstructures with multiple phases. In this study, the microstructural development of diffusion couples, U–7 wt%Mo, U–10 wt%Mo, and U–12 wt%Mo vs. AA6061, annealed at 600 °C for 24 h and at 550 °C for 1, 5, and 20 h, were analyzed by scanning electron microscopy with x-ray energy dispersive spectroscopy. The microstructural development and kinetics were compared to diffusion couples U–Mo vs. high purity Al and binary Al–Si alloys. As a result, the diffusion couples developed complex interaction regions where phase development was influenced by the alloying additions of the AA6061.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗