Results for “process” — Page 52

DOE OSTI2019

Using failed supernovae to constrain the Galactic r-process element production

ABSTRACT Rapid neutron capture process (r-process) elements have been detected in a large fraction of metal-poor halo stars, with abundances relative to iron (Fe) that vary by over two orders of magnitude. This scatter is reduced to less than a factor of 3 in younger Galactic disc stars. The large scatter of r-process elements in the early Galaxy suggests that the r-process is made by rare events, like compact binary mergers and rare sub-classes of supernovae. Although being rare, neutron star mergers alone have difficulties to explain the observed enhancement of r-process elements in the lowest metallicity stars compared to Fe. The supernovae producing the two neutron stars already provide a substantial Fe abundance where the r-process ejecta from the merger would be injected. In this work we investigate another complementary scenario, where the r-process occurs in neutron star-black hole mergers in addition to neutron star mergers. Neutron star-black hole mergers would eject similar amounts of r-process matter as neutron star mergers, but only the neutron star progenitor would have produced Fe. Furthermore, a reduced efficiency of Fe production from single stars significantly alters the age–metallicity relation, which shifts the onset of r-process production to lower metallicities. We use the high-resolution [(20 pc)3/cell] inhomogeneous chemical evolution tool ‘ICE’ to study the outcomes of these effects. In our simulations, an adequate combination of neutron star mergers and neutron star-black hole mergers qualitatively reproduces the observed r-process abundances in the Galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Towards a Comparative Assessment of Data-Driven Process Models in Health Information Technology

Process mining for conformance analysis focuses on comparing a reference process model against a data-driven process model that is generated via log files from information technology systems. While this approach is helpful when there is an existing process model in an organization, it leaves the question of what to do in the absence of a complete reference process model unanswered. In this paper, we present a comparative assessment approach that combines process mining, process mapping for dimensionality reduction, and statistical analysis. Our goal is to find similarities and dissimilarities in data-driven process models among U.S. Veterans Health Administration (VHA) facilities to assess process conformance among different healthcare facilities, which can help assess the standardization of care. We illustrate our approach by applying it to two clinical radiology order process models generated by two similar facilities. Our results demonstrate statistical similarities in the standardization of care among those two facilities.

Klasky, Hilda↗

DOE OSTI2015

MO-B-BRB-00: Optimizing the Treatment Planning Process

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi-automatic plan evaluation, (e) quality checklist for error prevention, (f) iterative process, (g) balance of speed and quality Learning Objectives: Gain familiarity with the workflow of modern treatment planning process. Understand the scope and challenges of managing modern treatment planning processes. Gain familiarity with Lean Six Sigma approaches and their implementation in the treatment planning workflow.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-B-BRB-01: Optimize Treatment Planning Process in Clinical Environment

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi-automatic plan evaluation, (e) quality checklist for error prevention, (f) iterative process, (g) balance of speed and quality Learning Objectives: Gain familiarity with the workflow of modern treatment planning process. Understand the scope and challenges of managing modern treatment planning processes. Gain familiarity with Lean Six Sigma approaches and their implementation in the treatment planning workflow.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-B-BRB-03: Systems Engineering Tools for Treatment Planning Process Optimization in Radiation Medicine

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi-automatic plan evaluation, (e) quality checklist for error prevention, (f) iterative process, (g) balance of speed and quality Learning Objectives: Gain familiarity with the workflow of modern treatment planning process. Understand the scope and challenges of managing modern treatment planning processes. Gain familiarity with Lean Six Sigma approaches and their implementation in the treatment planning workflow.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Numerical simulation of diverse thermal in situ upgrading processes for the hydrocarbon production from kerogen in oil shale reservoirs

© 2017, © The Author(s) 2017. We investigate the productivity and product selectivity of diverse thermal in situ upgrading processes in oil shale reservoirs. In situ upgrading processes applying the ideas of Shell In situ Conversion Process, ExxonMobil Electrofrac, and Texas A&M Steamfrac are simulated by using sector models with the assumption of symmetric patterns. In-house fully functional simulator is used, which has been developed for the kerogen pyrolysis and hydrocarbon production. In the simulation cases, sensitivity analyses to the factors having major influence on the productivity and product selectivity are conducted. The effects of the temperature of vertical heaters, the spacing of hydraulic fractures, and the position of horizontal production wells are analyzed in the applied In situ Conversion Process, Electrofrac, and Steamfrac, respectively. In the applied In situ Conversion Process cases, hydrocarbon production increases with the increasing heater temperature. In the applied Electrofrac cases, hydrocarbon production increases with the increasing spacing of hydraulic fractures, even though longer time period for the process is needed. In the applied Steamfrac cases, the case of production well located at the same depth to the injection well shows the least hydrocarbon production. Among the processes, the applied In situ Conversion Process cases show the highest weight percentage of total hydrocarbon components in the produced fluid, and the applied Electrofrac cases follow it. The applied Steamfrac cases show far lower weight percentage of hydrocarbon production than the other methods. In terms of the mass ratio of produced hydrocarbon to decomposed kerogen, the applied Steamfrac cases show the largest value among the processes by aqueous phase sweeping liquid organic phase, but they also show the huge water oil mass ratio by the continuous injection of hot water. All the applied In situ Conversion Process cases and the Electrofrac case with the short spacing of hydraulic fractures show good heating efficiency by decomposing whole kerogen in the system.

Lee, Kyung Jae↗

DOE OSTI2019

Non-Aqueous Processing

Next generation nuclear reactors may require alternative processing flowsheets, and one area of particular interest is around non-aqueous process flowsheets. These flowsheets utilize high temperatures and molten salt systems to solubilize the spent fuel and the fission products. Separations are then achieved primarily through electrochemical processes. These processes can either be off-line, such as pyro processing, where the spent fuel charge is processed after removal from the reactor, or potentially in-line in a molten salt reactor configuration. There are a large number of process options that can be explored using these non-aqueous processing options. A brief summary of both chloride and fluoride salt processing approaches is provided as background for how these process flowsheets could be developed

Simpson, Michael↗

DOE OSTI2021

Application of Sequential Design of Experiments (SDoE) to Large Pilot-Scale Solvent-Based CO2 Capture Process at Technology Centre Mongstad (TCM)

The United States Department of Energy’s Carbon Capture Simulation for Industry Impact (CCSI2) program has developed a framework for sequential design of experiments (SDoE) that aims to maximize knowledge gained from budget- and schedule-limited pilot scale testing. SDoE was applied to the planning and execution of campaigns for testing CO2 capture systems at pilot-scale in order to optimally allocate resources available for the testing. In this methodology, a stochastic process model is developed by quantifying the parametric uncertainty in submodels of interest; for a solvent-based CO2 capture system, these may include physical properties and equipment performance submodels (e.g., mass transfer, interfacial area). This uncertainty is propagated through the full process model, over variable operating conditions, for estimating the resulting uncertainty in key model outputs (e.g., percentage of CO2 capture, solvent regeneration energy requirement). In developing a data collection plan, the predicted output uncertainty is incorporated into an algorithm that seeks simultaneously to select process operating conditions for which the predicted uncertainty is relatively high and to ensure that the entire space of operation is well represented. This test plan is then used to guide operation of the pilot plant at varying steady-state conditions, with resulting process data incorporated into the existing model using Bayesian inference to refine parameter distributions. The updated stochastic model, with reduced parametric uncertainty from data collected, is then used to guide additional data collection, thus the sequential nature of the experimental design. The SDoE process was implemented at the pilot test unit (12 MWe in scale) at Norway’s Technology Centre Mongstad (TCM) in a summer 2018 test campaign with aqueous monoethanolamine (MEA). During the test campaign, the varied operating conditions included the flowrates of circulated solvent, flue gas, and reboiler steam and the CO2 concentration in the flue gas. The process data were used to update probability distributions of mass transfer and interfacial area parameters of a stochastic process model developed by the CCSI2 team. Two iterations of the SDoE process were executed, resulting in the uncertainty in model predicted CO2 capture percentage decreasing by an average of 58.0 ± 4.7% over the full input space of interest. This work demonstrates the potential of the SDoE process for model refinement through reduction in process model parametric uncertainty, and ultimately risk in scale-up, in CO2 capture technology performance.

carbon capture↗

DOE OSTI2014

FY13 Glycolic-Nitric Acid Flowsheet Demonstrations of the DWPF Chemical Process Cell with Simulants

Savannah River Remediation is evaluating changes to its current Defense Waste Processing Facility flowsheet to replace formic acid with glycolic acid in order to improve processing cycle times and decrease by approximately 100x the production of hydrogen, a potentially flammable gas. Higher throughput is needed in the Chemical Processing Cell since the installation of the bubblers into the melter has increased melt rate. Due to the significant maintenance required for the safety significant gas chromatographs and the potential for production of flammable quantities of hydrogen, eliminating the use of formic acid is highly desirable. Previous testing at the Savannah River National Laboratory has shown that replacing formic acid with glycolic acid allows the reduction and removal of mercury without significant catalytic hydrogen generation. Five back-to-back Sludge Receipt and Adjustment Tank (SRAT) cycles and four back-to-back Slurry Mix Evaporator (SME) cycles were successful in demonstrating the viability of the nitric/glycolic acid flowsheet. The testing was completed in FY13 to determine the impact of process heels (approximately 25% of the material is left behind after transfers). In addition, back-to-back experiments might identify longer-term processing problems. The testing was designed to be prototypic by including sludge simulant, Actinide Removal Product simulant, nitric acid, glycolic acid, and Strip Effluent simulant containing Next Generation Solvent in the SRAT processing and SRAT product simulant, decontamination frit slurry, and process frit slurry in the SME processing. A heel was produced in the first cycle and each subsequent cycle utilized the remaining heel from the previous cycle. Lower SRAT purges were utilized due to the low hydrogen generation. Design basis addition rates and boilup rates were used so the processing time was shorter than current processing rates.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2014

Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

DOE-GTRC-05596 11/24/2104 Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate PI: Dr. Yi Deng (PI) School of Earth and Atmospheric Sciences Georgia Institute of Technology 404-385-1821, yi.deng@eas.gatech.edu El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The projection of future changes in the ENSO and AM variability, however, remains highly uncertain with the state-of-the-science climate models. This project conducted a process-resolving, quantitative evaluations of the ENSO and AM variability in the modern reanalysis observations and in climate model simulations. The goal is to identify and understand the sources of uncertainty and biases in models’ representation of ENSO and AM variability. Using a feedback analysis method originally formulated by one of the collaborative PIs, we partitioned the 3D atmospheric temperature anomalies and surface temperature anomalies associated with ENSO and AM variability into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. In the past 4 years, the research conducted at Georgia Tech under the support of this project has led to 15 peer-reviewed publications and 9 conference/workshop presentations. Two graduate students and one postdoctoral fellow also received research training through participating the project activities. This final technical report summarizes key scientific discoveries we made and provides also a list of all publications and conference presentations resulted from research activities at Georgia Tech. The main findings include: 1) the distinctly different roles played by atmospheric dynamical processes in establishing surface temperature response to ENSO at tropics and extratropics (i.e., atmospheric dynamics disperses energy out of tropics during ENSO warm events and modulate surface temperature at mid-, high-latitudes through controlling downward longwave radiation); 2) the representations of ENSO-related temperature response in climate models fail to converge at the process-level particularly over extratropics (i.e., models produce the right temperature responses to ENSO but with wrong reasons); 3) water vapor feedback contributes substantially to the temperature anomalies found over U.S. during different phases of the Northern Annular Mode (NAM), which adds new insight to the traditional picture that cold/warm advective processes are the main drivers of local temperature responses to the NAM; 4) the overall land surface temperature biases in the latest NCAR model (CESM1) are caused by biases in surface albedo while the surface temperature biases over ocean are related to multiple factors including biases in model albedo, cloud and oceanic dynamics, and the temperature biases over different ocean basins are also induced by different process biases. These results provide a detailed guidance for process-level model turning and improvement, and thus contribute directly to the overall goal of reducing model uncertainty in projecting future changes in the Earth’s climate system, especially in the ENSO and AM variability.

58 GEOSCIENCES↗

DOE OSTI2017

Recovery of Rare Earth Elements from Coal and Coal Byproducts via a Closed Loop Leaching Process: Final Report

Objectives: Through this grant, Battelle proposes to address Area of Interest (AOI) 1 to develop a bench-scale technology to economically separate, extract, and concentrate mixed REEs from coal ash. U.S. coal and coal byproducts provide the opportunity for a domestic source of REEs. The DOE’s National Energy Technology Laboratory (NETL) has characterized various coal and coal byproducts samples and has found varying concentrations of REE ranging up to 1,000 parts per million by weight. The primary project objective is to validate the economic viability of recovering REEs from the coal byproduct coal ash using Battelle’s patented closed-loop Acid Digestion Process (ADP). This will be accomplished by selecting coal sources with the potential to provide REE concentrations above 300 parts per million by weight, collecting characterization data for coal ash samples generated via three different methods, and performing a Techno-Economic Analysis (TEA) for the proposed process. The regional availability of REE-laden coal ash, the regional market for rare earth concentrates, and the system capital and operating costs for rare earth recovery using the ADP technology will be accounted for in the TEA. Limited laboratory testing will be conducted to generate the parameters needed for the design of a bench scale system for REE recovery. The ultimate project outcome will be the design for an optimized, closed loop process to economically recovery REEs such that the process may be demonstrated at the bench scale in a Phase 2 project. Project Description: The project will encompass evaluation of the ADP technology for the economic recovery of REEs from coal and coal ash. The ADP was originally designed and demonstrated for the U.S. Army to facilitate demilitarization of cast-cured munitions via acid digestion in a closed-loop process. Proof of concept testing has been conducted on a sample of Ohio-based Middle Kittanning coal and has demonstrated the feasibility of recovering REEs using the ADP technology. In AOI 1, Ohio coal sources with the potential to provide a consistent source of rare earth element concentrations above 300 parts per million will be identified. Coal sample inventories from West Virginia and Pennsylvania will also be assessed for purposes of comparison. Three methods of preparing the coal ash will be evaluated for their potential to enhance the technical feasibility and economics of REE recovery. Three sources of coal ash are targeted for evaluation of the economics of REE recovery in this project: (1) coal ash from power generation stations, to include fly ash and/or bottom ash, (2) ash generated in a lower temperature ashing process, and (3) ash residual from Battelle’s coal liquefaction process. Making use of residual ash from coal liquefaction processes directly leverages work currently being conducted by Battelle for DOE NETL in response to DE-FOA-0000981 entitled “Greenhouse Gas Emissions Reductions Research and Development Leading to Cost-Competitive Coal-to-Liquids Based Jet Fuel Production.” Using the sample characterization results and regional information regarding REE concentration, availability and cost, a TEA will be developed. The previously generated laboratory testing results for leaching and REE recovery via the ADP will be used to perform the TEA, along with common engineering assumptions for scale up of equipment and labor costs. Finally, upon validation of the economic feasibility of the process by the TEA, limited laboratory testing will be performed to support the design of a bench scale system. In a future project phase, it is envisioned that the bench scale system will be constructed and operated to prove the process on a continuous basis.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2017

Commercially Scalable Process to Fabricate Porous Silicon

Navitas Advanced Solutions Group proposes a novel, commercially scalable approach to supply microporous silicon (μpSi) to lithium ion battery manufacturers. If successful, this project will result in a significant reduction in the cost and environmental impact of high capacity anodes that are needed to meet the EV Everywhere battery goals. Silicon nanocomposite materials have been identified as a viable anode technology for EV batteries. Presently, high capacity silicon-based anodes rely either on materials that are expensive (e. g., silane or nano-silicon powder) or on processes that are limited by low yield methods (e.g., chemical vapor deposition). Microporous silicon potentially avoids these limitations and is attracting increasing attention as a lower cost alternative for the manufacture of high capacity silicon-based anodes. Microporous silicon suitable for EV batteries is not currently available as a commodity material. Microporous silicon can be produced at lab scale through a metal catalyzed hydrofluoric acid etching process. However, this process is expensive and hazardous. Our proposed production route will facilitate the availability of μpSi to lithium ion battery producers and developers at a scale and cost able to support EV battery production. Under the Vehicle Technologies FOA AOI 4 seeks Advances in Existing and Next-Generation Battery Material Manufacturing to reduce the cost of EV batteries. The EV Everywhere initiative establishes a goal of $100/kWh system level cost for an EV battery. This cost target can be met with moderate risk through pairing silicon-based high capacity anodes with lithium metal-rich nickel manganese cobalt oxide 'LMR-NMC' cathodes. For this set of assumptions, the silicon anode active material cost would need to be <$25/kg. The Navitas µpSi powder manufacturing process will reach this target through a combination of low-cost commodity raw materials and reactants with scalable and low environmental impact processes. Processing will involve mechanical milling and thermal reduction operations that are in wide application at industrial scale. The goal of this program is to reach most or all of the MRL 6 criteria in a pilot scale demonstration for the manufacturing of porous silicon powder, while minimizing raw material added cost and limiting hazardous and environmental impact and using scalable industrial processing (i.e. mechanical milling, thermal reduction). The Navitas μpSi fabrication process represents a novel approach to reduce the cost of silicon anode material manufacturing. This process has been shown to be more efficient (higher yield) and economical on scaling up than conventional metal-assisted etching. The process significantly reduces the cost on $/mAh basis versus existing anode materials. The μpSi powders can be modified to form nanocomposite structures through blending with graphite or coating with carbon or a metal oxide to decrease initial capacity loss (ICL) and improve cell cycle life, a key barrier to adoption of silicon anodes into EV batteries. The impact of this technology will be driven by the projected rate of EV adoption and market share. By reducing battery cost, the proposed technology will stimulate EV adoption rate. Assuming this technology enables capturing an additional 6% of the present PHEV + EV market the reduction in petroleum consumption would be 90,000 gallons of gasoline per day, or 1.6M barrels per year. The carbon emissions from a gallon of gasoline = 2.4 kg/gallon. Thus, if the proposed technology was incorporated into just 0.1% of all new vehicles produced and if all the electricity to power those electric-drive vehicles was produced from clean, renewable sources such as wind and solar, it would result in 15K metric tons/yr reduction of CO2 emissions.

25 ENERGY STORAGE↗

DOE OSTI2018

Issues Management Process Course # 38401

The purpose of this training it to advise Issues Management Coordinators (IMCs) on the revised Contractor Assurance System (CAS) Issues Management (IM) process. Terminal Objectives: Understand the Laboratory’s IM process; Understand your role in the Laboratory’s IM process. Learning Objectives: Describe the IM process within the context of the CAS; Describe the importance of implementing an institutional IM process at LANL; Describe the process flow for the Laboratory’s IM process; Apply the definition of an issue; Use available resources to determine initial screening risk levels for issues; Describe the required major process steps for each risk level; Describe the personnel responsibilities for IM process implementation; Access available resources to support IM process implementation.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

Electrically-Assisted Tubing Processes for Enhancing Manufacturability of Oxide Dispersion Strengthened Structural Materials for Nuclear Reactor Applications

The overall goal of this project is to enhance the formability of Nanostructured Ferritic Alloys (NFAs) such that high-strength thin-walled claddings can be successfully and economically manufactured for use in future nuclear reactors. Specifically, four objectives were identified: Objective #1 – to achieve a good understanding of the mechanical behavior and resulting microstructure of 14YWT made from the powder form subjected to various Electrically- Assisted (EA) loading conditions. Objective #2 – to conduct EA-flat rolling of 14YWT completed and the prioritization/selection of two alternative designs of EA tube rolling processes. Objective #3 – to design and assemble a new EA tube rolling machine. Objective #4 – to conduct rolling using the new EA rolling machine. The above objectives were achieved and the findings can be further applied to establish other innovative fabrication processes. Specifically, the major accomplishments are summarized as: The use of an EA forming process was investigated to reduce the forming force of ODS ferritic steels. The effect of a continuous electric current on 14YWT during plastic deformation was evaluated. EA uniaxial tension tests show that the electric current is able to reduce the flow stress of 14YWT. 14YWT exhibits a ductility minimum at a current density of 34.5 A/mm2 which is consistent with fractography results. Hardness measurements and TEM results indicate that oxide particles are stable during the EA process. By following the tests, microstructure analysis was performed on the sample in its as-received state and after current treatment. The microstructures are stable when subjected to high current density. The related thermal model was developed to predict the Joule heating temperatures. The temperatures were compared with the experimental results. At last, a temperature-dependent hardening model was used to explore the mechanisms acting during EA deformation. Since the model can accurately predict the yield strength of 14YWT under EA conditions without the incorporation of non-thermal effects, it can be concluded that the reduction in yield strength is due to the Joule heating generated under continuous current loading conditions. An oven-heated pure thermal tension test was conducted to confirm this conclusion. The new EA tube rolling machine has been completely developed. The related work includes: (1) forming process design; (2) analysis of the effect of roll-tube contact geometry on rolling force; (3) analysis of machine performance under mechanical loading; (4) design of machine electrical setting path and insulation; (5) multi-pass process analysis; (6) design of power transmission system (axial/radial/torque feeding mechanisms), roll bearing system, cooling system, workpiece feeding mechanism, and other related mechanical connection support components; (7) design and optimization of roll profiles/dimensions; (8) analysis and simulation of the rolling process; (9) development of engineering drawings and fabrication; (10) assembly and calibration of the EA tube rolling machine; (11) design and integration of the electrical control system; (12) hardware integration for high power supply electrically-assisted rolling process; (13) induction heating system integration; (14) experimental tests for the new rolling process. Through the process from conceptual design to final machine calibration and experimental tests, there are many technical and physical works that have been implemented and improved for the best performance of the innovative prototype.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Characterization of Covetic Materials for Process Control. Final CRADA report

GDC Industries LLC has been performing process research on covetic materials since its formation in February 2015. With assistance from DOE and the Air Force via SBIR projects, GDC focused on the enhancement of aluminum alloys to covetics to replicate a previously reported electrical conductivity of about 67% IACS (International Annealed Copper Standard). GDC has established a joint development agreement with General Cable Corporation, wherein General Cable agreed to perform numerous extrusions of as cast covetics and subsequent tensile and electrical conductivity tests on the resultant wire. Covetics conversion was proven but the significant improvement is yet to be replicated. To control the experiments towards enhanced process control, a series of designed experiments was created by an expert in process control from the automotive industry. Six process variables were identified and a designed experiment matrix requiring 18 independent conversions was created at GDC. The result of those designed experiments has now allowed GDC to focus on two process variables, namely, residence time and DC current in the conversions with the other four variable held constant. While this work is useful in replicating the earlier enhancements, GDC feels it will not be sufficient for the necessary process knowhow for scale up required by industry as GDC still does not have a direct correlation of the process variables to the actual carbon in the finished covetics. Since 2015, GDC has been aware of the capabilities existing at Argonne National Laboratory for performing carbon analysis that exceeds the precision commonly available to Industry. GDC and ANL submitted a proposal in response to the DOE-EERE – Small Business Vouchers Pliot Program announcement and the proposal was selected for funding. GDC will melt-process covetic aluminum samples following their design of experiment criteria and have the as-casted samples extruded by their partner, General Cable. Argonne will measure the conductivity, analyze carbon content, perform X-ray diffraction, and examine the microstructural features of the samples. Careful process variable measurements will be recorded by each party such that correlations can be developed indicating process parameters that yield the best carbon concentration in covetics.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Energy-Storing Cryogenic Carbon Capture™ for Utility and Industrial-scale Processes (Final Report)

This project leverages work completed under funding from previous U.S. Department of Energy (DOE) projects and other sources of funding around the Cryogenic Carbon Capture Process™ (CCC). The purpose of this project is to further develop a perturbation of the CCC process that stores energy called the Cryogenic Carbon Capture™ Energy Storing (CCC-ES) process. The successful completion of the tasks in this project has prepared the CCC-ES process for scaling and developed initial plans and a feasibility analysis for an engineering-scale or small-commercial scale system that can store at least 10 MWh of energy. The specific areas of work in this project are: (1) Develop a conceptual, site-specific integrated process flow diagram: Sustainable Energy Solutions (SES) developed a conceptual, site-specific plan including a process flow diagram for integrating CCC-ES at a specific location. The proposed system was based on a typical engineering-scale CCC system designed to capture 30-50 metric tonnes of CO 2 per day (TPD), with modifications and additional changes and equipment put in place to add the energy storage element to the system. The 30-50 TPD scale corresponds to the required 10 MWh of stored energy. This task includes updating simulation software for transient analysis. SES also coordinated with the Jim Bridger Power Plant in Point of Rocks, Wyoming to get site-specific data. Using these data, SES completed site-specific preliminary process flow diagrams, estimated capital and operating costs for the CCC-ES system, and used the upgraded software package to estimate the primary figures of merit. (2) Complete a technoeconomic analysis (TEA): SES completed a full-scale TEA of the CCC-ES system to meet specific success criteria. This TEA used process information from the host site selected above. (3) Technology and data gap assessment for the CCC-ES process: As part of the technology gap assessment, SES performed an assessment of the best alternative energy storage solutions including figures of merit and operational strengths and weaknesses. SES then compared the proposed system with a discussion of how it addresses the weaknesses of alternative systems, showing for example a cost of stored energy at less than $50/MWh and with a roundtrip efficiency of greater than 95%. This assessment includes technical and other risk analyses and technology gaps with research and development needs to commercialize the process by 2030. Finally, work includes a commercialization roadmap/development pathway outlining the major milestones to move to a commercially operating CCC-ES system. (4) Phase II pre-FEED project plan: SES completed a project plan for the Phase II pre-FEED analysis using the same host site as in the Phase I conceptual study.

03 NATURAL GAS↗

DOE OSTI2023

Integrated Process Optimization for Biochemical Conversion

This research is motivated by the challenges faced during biomass processing in bioenergy plants. It has been observed that variations in biomass characteristics, such as moisture, ash, and carbohydrate contents cause variations in feeding of the system which led to underutilization of equipment and the reactor. The objective of this research is to ensure a continuous flow of biomass to the reactor in plants that use the biochemical conversion process to generate liquid fuels. The overall goal is to lower the cost of producing biofuels, which could lead to improving US’s energy independency and growing US’s rural economy. The research team developed analytical models, such as discrete element method (DEM) models and mathematical models. The DEM models are unit-level models that explicitly capture biomass characteristics and quantify the impacts of biomass characteristics on bulk material properties and the performance of specific equipment. The mathematical models are system-level models that capture the impacts of system infeed rate, equipment processing rate, storage location and capacity, and biomass characteristics on system throughput. The functional relations predicting the bulk material properties from DEM models are incorporated to the mathematical models. The models developed were validated and evaluated using data collected at Idaho National Laboratory’s biomass processing facility. Via these models, we identified process control strategies that ensure a continuous flow of biomass to the reactor, while meeting the requirements of biochemical conversion process. Our analysis indicates that sequencing of biomass bales based on moisture level, and carbohydrate contents could have a positive impact on reducing processing time and inventory level and increasing throughput rate. Short bale sequences that repeat frequently, seem to have the greatest impact on improving system’s performance. Based on our experiments, the total annual system operating costs reduced by 20-30%, and the maximum inventory level reduced by 3 to 4 times. The operating costs include the annual equipment amortization cost and processing cost. The implementation of the models developed requires the use of standardized bale format, Radio Frequency Identification technology, sensing and real time monitoring of material attributes, automated material handling equipment, and automated process control. The scope of the model proposed can be extended to include the whole supply chain. The supply chain models help identify how many bales of different biomass feedstock to purchase given biomass availability in the region, biomass price and quality, and the biomass processing capabilities of the biorefinery. Thus, the outcomes of supply chain models can be used to inform the design of long-term contracts among farmers and the biorefinery.

09 BIOMASS FUELS↗

DOE OSTI2023

Integrated Process Testing of MSR Salt Spill Accidents

Part of the licensing process for new nuclear reactors requires vendors to assess the potential consequences of identified accident scenarios using accident progression modeling. The accident scenario that will likely be evaluated by all molten salt reactor (MSR) developers is a spill of radionuclide-bearing fuel salt onto the reactor containment floor (i.e., a salt spill accident). The development of accident progression models requires experimental data to inform which processes to incorporate, to enable the calculation of parameters to model these processes, and to validate the model predictions. The data should quantify the sensitivities of key processes (e.g., molten salt spreading, heat transfer, containment structure corrosion, radionuclide vaporization, and aerosol generation) towards the initial conditions of the spill, the ambient environment, and the features of the containment. In addition, results from integrated process tests that quantify coupled processes are required to validate systems-level models. This report documents results from integrated process tests conducted on simulated molten salt spill accidents. The generated experimental data simultaneously quantify the heat transfer behavior of the spilled salt, compositional changes to the bulk salt, and the release of surrogate fission products from the spilled salt as aerosol particles. All tests that were conducted used FLiNaK doped with surrogate fission products, and the variables that were evaluated included the initial salt temperature and the concentration of surrogate fission products present in the salt. The major accomplishments of this work include identifying surrogate fuel salt compositions that provide insight into the dispersal behavior of radionuclides of potential significance to the source term, employing previously developed methods and measurement techniques to simultaneously measure key processes, generating data on the coupled processes of molten salt heat transfer and surrogate fission product release as aerosol particles, demonstrating new test methods for real-time monitoring of the flow rate of the spill and aerosol size quantification in an argon atmosphere, and developing a mass transfer model for cesium and iodine release from molten FLiNaK to provide insight into aerosol formation by vapor condensation. The same methodology applied herein can be employed to study different salt compositions of interest to MSR developers, different environmental conditions, and other variables that are relevant to postulated accident scenarios. The insights gained from these integrated process tests conducted at a laboratory scale will be incorporated into future integral effects tests conducted at an engineering scale.

20 FOSSIL-FUELED POWER PLANTS↗