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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 OSTI2019

Analysis of the Effect of Vehicle Platooning on the Optimal Control of a Heavy Duty Engine Thermal System

One promising method for reducing fuel consumption and emissions, particularly in heavy duty trucks, is platooning. As the distance between vehicles decreases, the following vehicles will experience less aerodynamic drag on the front of the vehicle. However, reducing the velocity of the air contacting the front of the vehicle could have adverse effects on the temperature of the engine. To compensate for this effect, the energy consumption of the engine cooling system might increase, ultimately limiting the overall improvements obtained with platooning. Understanding the coupling between drag reduction and engine cooling load requirement is key for successfully implementing platooning strategies. Additionally, in a Connected and Automated Vehicle (CAV) environment, where information of the future engine load becomes available, the operation of the cooling system can be optimized in order to achieve the maximum fuel consumption reduction. In this paper, a control-oriented physics-based model for the engine cooling loop of a Volvo engine is developed and validated against road data. Starting from the validated model, an optimal control problem for the coolant system is formulated considering the tradeoff between the tracking of the engine temperature setpoint and the corresponding fuel consumption under different trailing distances. To compare the coolant system performance, Dynamic Programming (DP) is used to determine the global optimal solution for the coolant system actuator. The coupling between optimal cooling system operation and reduction in ram air are evaluated by comparing the results obtained from the DP under different platooning conditions against the unrestricted scenario. In addition, the paper analyzes the changes in the tradeoff between fuel consumption and setpoint tracking for different vehicle distances. This analysis will provide useful insight on the sensitivity of the coolant system controller calibration to the platoon distance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

A Task Based Approach for Co-Scheduling Ensemble Workloads on Heterogeneous Nodes

Scientific workflows consist of multiple, connected applications, with data and results flowing from one to another in a pipeline. Traditionally, such workflows are executed in sequential order, storing intermediate data in storage disks. Co-scheduling application workflows concurrently on the same compute nodes would greatly reduce the cost of moving data to/from storage and allow real-time analysis of intermediate results. Nevertheless, most parallel programming runtimes do not allow seamless integration of various applications in a scientific workflow, in part due to the complexity of managing data and resources. The situation is even more complicated for heterogeneous systems. In this work we extend the Minos Computing Library (MCL) runtime to accelerate pipe-lined and parallel workloads where multiple applications are running in the same system. MCL’s asynchronous task library and runtime dynamically manages resources to allow co-scheduling of multiple processes sharing heterogeneous resources. In addition, we design a custom ex- tension of the Open Compute Language (OpenCL) to enable multiple processes to share device memory. We enable MCL to coordinate these shared buffers to allow for easy, fast data sharing between applications. Using malleable micro-benchmarks and two application workflows that combine scientific simulation and AI-based analysis, we show that our method outperforms traditional approaches.

Index Terms—Parallel systems, Scheduling and Task ↗

DOE OSTI2023

HopPyBar

HopPyBar is a python program to import, analyze, and export split-Hopkinson pressure bar (SHPB, also known as Kolsky bar) data. Traditional analysis offers a black box approach, where input data is converted to analyzed output by performing a series of calculations without user involvement. This program serves as a developmental platform to "white box" the data analysis process. Data streams can be captured (in-situ) to enable advanced or unconventional analyses, statistics, and comparisons. Additionally, the program is geared towards the standardized forms of input and output used at LANL to streamline analysis, but the open nature of the program makes additional input/output schemes straightforward to add. General workflow will import SHPB data in one of a number of formats, identify relevant portions of data signals, and convert to stress-strain-strain rate to show material behavior as a function of dynamic testing.

Morrow, Benjamin↗

DOE OSTI2017

Hydrated Ordinary Portland Cement as a Carbonic Cement: The Mechanisms, Dynamics, and Implications of Self-Sealing and CO 2 Resistance in Wellbore Cements

This report analyzes the dynamics and mechanisms of the interactions of carbonated brine with hydrated Portland cement. The analysis is based on a recent set of comprehensive reactive-transport simulations, and it relies heavily on the synthesis of the body of work on wellbore integrity that we have conducted for the Carbon Storage Program over the past decade.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Development of a Pre-Combustion CO 2 Capture Process Using High-Temperature PBI Hollow-Fiber Membranes

The overall objective of this project was to evaluate the advantages of transformational polybenzimidazole (PBI) polymer hollow-fiber membrane (HFM)-based, carbon dioxide (CO 2 ) capture and purification technology at bench-scale using an actual coal-derived syngas stream from a coal gasification facility. The project was carried out over two budget periods. The technical objectives in Budget Period 1 (BP1) included preparing HFs and modules and upgrading the available skid for field testing. The technical objectives for BP2 were to field-test the skid unit with actual coal-derived syngas from an oxygen-blown gasifier to obtain performance data, update the Techno-Economic Analysis (TEA) that would assist with future process scale-up, and provide information on the design of a small pilot-scale test unit. The goal was to advance the PBI-HFM CO 2 capture and gas separation system for pre-combustion applications beyond second-generation economic performance predictions and make progress toward meeting overall fossil energy performance goals of CO 2 capture with 95% CO 2 purity at a cost of electricity (COE) 30% less than baseline capture approaches. The research program was designed with progressive technical tasks leading to both dynamic and steady-state testing of the PBI-HFM skid with actual coal-derived syngas. The work plan was to: (1) fabricate sufficient Generation-2 (GEN-2) fibers for module fabrication; (2) upgrade the fiber skid to accommodate large fiber modules for bench-scale field testing; (3) conduct dynamic and steady-state testing with coal-derived syngas from an oxygen-blown gasifier and obtain system performance data; (4) perform a TEA and environmental, health, and safety (EH&S) assessment; (5) update the State-Point Data Table, Technology Gap Analysis (TGA), and Technology Maturation Plan (TMP); (6) uninstall and return the test skid to the Recipient’s facilities; and (7) submit a Final Report that describes the results and analysis of the project research effort.

03 NATURAL GAS↗

DOE OSTI2021

CFD/FEA Co-Simulation Framework for Analysis of the Thermal Barrier Coating Design and Its Impact on the HD Diesel Engine Performance

Thermal barrier coatings (TBCs) have been investigated both experimentally and through simulation for mixing controlled combustion (MCC) concepts as a method for reducing heat transfer losses and increasing cycle efficiency, but it is still a very active research area. Early studies were inconclusive, with different groups discovering obstacles to realizing the theoretical potential. Nuanced papers have shown that coating material properties, thickness, microstructure, and surface morphology/roughness all can impact the efficacy of the thermal barrier coating and must be accounted for. Adding to the complexities, a strong spatial and temporal heat flux inhomogeneity exists for mixing controlled combustion (diesel) imposed onto the surfaces from the impinging flame jets. In support of the United States Department of Energy SuperTruck II program goal to achieve 55% brake thermal efficiency on a heavy-duty diesel engines, this study sought to develop a deeper insight into the inhomogeneous heat flux from mixing controlled combustion on thermal barrier coatings and to infer concrete guidance for designing coatings. To that end, a co-simulation approach was developed that couples high-fidelity computational fluid dynamics (CFD) modeling of in-cylinder processes and combustion, and finite element analysis (FEA) modeling of the thermal barrier-coated and metal engine components to resolve spatial and temporal thermal boundary conditions. The models interface at the surface of the combustion chamber; FEA modeling predicts the spatially resolved surface temperature profile, while CFD develops insights into the effect of the thermal barrier coating on the combustion process and the boundary conditions on the gas side. The paper demonstrates the capability of the framework to estimate cycle impacts of the temperature swing at the surface, as well as identify critical locations on the piston/thermal barrier coating that exhibit the highest charge temperature and highest heat fluxes. In addition, the FEA results include predictions of thermal stresses, thus enabling insight into factors affecting coating durability. An example of the capability of the framework is provided to illustrate its use for investigating novel coatings and provide deeper insights to guide future coating design.

42 ENGINEERING↗

DOE OSTI2018

An Ensemble Optimization Framework for Coupled Design of Hydropower Contracts and Real-Time Reservoir Operating Rules

Often, revenues from hydropower generation depend on the operator's ability to provide firm power in the presence of uncertain inflows. The primary options available for optimizing revenue are negotiation of a firm power contract before operations begin and adjustment of the reservoir release during operations. Contract and release strategy optimization are closely coupled and most appropriately analyzed with stochastic real-time control methods. Here we use an ensemble-based approach to stochastic optimization that provides a convenient way to construct nonparametric revenue probability distributions to explore the implications of uncertainty. The firm power contract is a simplified bilateral fixed price agreement that partially insulates operator and buyer from price fluctuations. The release control laws and firm energy target are jointly optimized to maximize the operator's expected revenue. Revenue probability distributions and related spill performance statistics indicate that predictive operating strategies such as stochastic dynamic programming and model predictive control can give significantly better performance than standard deterministic operating rules. The performance obtained from batch optimization with perfect inflow information establishes a convenient upper bound on potential revenue and provides a baseline for assessing the significance of differences between real-time operating strategies. Sensitivity analysis indicates that the benefits of predictive operational strategies are greatest for reservoirs with medium nondimensional residence times and less important for reservoirs with large residence times. Overall, probabilistic analysis of the coupled hydropower contract-operations problem provides a realistic way to assess revenue and risk for reservoirs that must provide firm power when inflows are uncertain.

13 HYDRO ENERGY↗

DOE OSTI2019

Linking the Codependence of Grain Boundary Structure and Density to Defect Evolution Mechanisms during Radiation Damage

There is little understanding of the direct link between grain boundary character and density, and defect denuded zones. For example, the role of reduced grain size to the nanocrystalline regime and subsequent increase in grain boundary density is not fully understood in the context of dislocation or void behavior near grain boundaries. In addition, little is understood experimentally on how defect absorption changes the structure of the grain boundary during irradiation and may play a role in the migration of defects and solutes. This work aims to define a framework for understanding the origin of radiation damage mechanisms in model BCC and FCC nanocrystalline materials, on which a foundation of radiation tolerant material development can be built. The key questions that will be addressed by this work are: 1. What is the influence of GB density and GB character (GBC) on radiation damage accumulation near grain boundaries in model nanocrystalline FCC and BCC alloys; how are these two effects connected? 2. In the context of radiation induced segregation (RIS), what effect does species dependent interstitial diffusion have on the GB chemistry in light of these two dependencies? 3. How does grain boundary sink efficiency evolve with radiation over time? In situ and analytical transmission electron microscopy techniques are used to study both pure and alloy nanocrystalline materials under irradiation. TEM samples prepared from thin films will be irradiated in-situ, allowing for dynamic observation of the behavior of the alloy under ion irradiation. The key findings from this program were (1) the control of thin film texture via sputtering; (2) the development of characterization tools for defects and grain boundary quantification; (3) the development of new techniques for defect characterization toward high throughput analysis; (4) a mapped out parameter space for defect evolution as a function of grain size and grain boundary character; and finally (5) an indication of sink efficiency and its stability during irradiation.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Integration of a grey-box refrigerated case model in EnergyPlus via Python plugin

Commercial buildings, in particular grocery stores (due mainly to their large refrigeration load), provide opportunities for energy cost reductions. Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity. This load flexibility could come from modifying the control of heating, ventilation, and air conditioning (HVAC) systems, refrigeration systems, or both. Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature, estimating load flexibility of refrigeration systems is nascent and has been a challenge, in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases. The existing refrigerated case model within EnergyPlus, a whole building energy simulation program, assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case. In addition, it does not encompass modeling of temperatures of the product inside the refrigerated case. This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential. In this paper, we present a grey-box model for modeling refrigerated cases in grocery stores, which include medium temperature and low temperature. Four cases are modeled; two are low-temperature closed cases and two are medium-temperature cases with one closed and one open. Data from an experimental facility are used to train and test the models. Results demonstrate the efficacy of the grey-box models in predicting the temperatures. This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment (case credits). These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost, develop and test unique algorithms that could affect refrigeration interactions with HVAC, and refine store design for any commercial building with refrigeration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

MFANS 2024 - Formally Proving Characteristics of Cyber-Physical Systems

Cyber-physical systems (CPS) are engineered systems that rely on the smooth integration of computational algorithms and physical elements. This integration presents new challenges for verifying that systems will behave as expected. The goal of this presentation is to present current challenges and potential solutions for the formal verification of cyber-physical systems. For cyber systems, formal methods refer to systematically rigorous mathematical techniques employed in the specification, development, analysis, and verification of both software and hardware systems. Recent advancements in computer science have yielded sophisticated tools specifically designed to address challenges associated with formal methods in complex systems. These tools leverage various foundational concepts such as logic, formal languages, program semantics, type systems, type theory, and automata theory. A notable achievement in the application of formal methods is the seL4 microkernel, claimed to be the first general-purpose operating-system kernel to be verified. Its proof implies the absence of bugs and guarantees that the kernel meets specifications. For physical systems, dynamic and control theory has a history of using rigorous analytic techniques to prove functional correctness. Lyapunov, optimal, classical, modern, and robust control theories all provide rigorous mathematical methods both to analyze system performance and to design controller that can be guaranteed to meet certain objectives. Recent computational techniques like level set theory and reachability analysis provide assertions that a system's state will avoid unsafe regions. Even though success has been independently achieved for cyber systems and physical systems, the integration of such systems creates new challenges. In particular, there is an obvious discrepancy between finite-state machines and infinite-state systems, resulting in different approaches for modeling and analyzing these system. While it is possible to simulate hybrid systems, this provides only a demonstration of a performance and not proof. For hybrid systems, current formal methods and system analysis approaches typically require a workarounds to work on hybrid systems like CPS. This paper will outline the state of the art and limits of current practice for formally verifying CPS and will identify possible research directions that require attention.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

TRAILS Output Files

Overview This data repository contains ZIP files that store compressed versions of the output of running the WaterPaths utility planning and management tool in the DU Re-Evaluation mode (to download the tool, please see this GitHub repository). The tool was used to simulate the six-utility North Carolina Research Triangle problem. Details on the contents of each ZIP file can be seen below. Data details Temporal range: Weekly data for 2,344 weeks from 2015 to 2060 (45 years). Spatial range: Six water utilities in the North Carolina Research Triangle region (0: Chapel Hil/OWASA, 1: Durham, 2: Cary, 3: Raleigh, 4: Pittsboro, and 5: Chatham) File types: CSV and OUT Different solutions available The solution numbers correspond to the different pathway strategies (henceforth referred to as "solutions") discussed in paper's main and supporting text (abstract and link to the paper here). They are as follows: Sol92: The Durham-focused pathway strategy Sol132: The Raleigh-focused pathway strategy Sol140: The regionally-robust pathway strategy Objectives files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Objectives_RDMXX_solsXX_to_XX.csv files. Each CSV file will consist of a row representing all the objective values for that specific solution, while every six columns represents the reliability, restriction frequency, infrastructure net present value ($ mil), peak financial cost, worst-case cost, and unit cost ($ per MG; in that order) for each of the six utilities. There will be 1,000 such files, denoting the performance of the six utilities across the 1,000 deeply uncertain states of the world (DU SOWs). Pathway files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Pathways_sXX_RDMXX.out file. Each OUT corresponds to the set of infrastructure being triggered in a specific DU SOW, and each file will have the name file will consist of four tab-delimited columns that are described as follows: Realization: The realization in which an infrastructure options being triggered utility: The utility currently triggering infrastructure week: The week in which a specific infrastructure option is being triggered infra.: The infrastructure option being triggered If the OUT file contains only the header line, no infrastructure was triggered for that specific DU SOW. Policies files These files can be obtained by unzipping Policies.zip. Each of the 1,000 CSV files within the unzipped folder will contain weekly water use restriction policies for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: 0rest_m: restriction multiplier for utility 0 (values between 0 and 1) 1rest_m: restriction multiplier for utility 1 (values between 0 and 1) 2rest_m: restriction multiplier for utility 2 (values between 0 and 1) 3rest_m: restriction multiplier for utility 3 (values between 0 and 1) 4rest_m: restriction multiplier for utility 4 (values between 0 and 1) 5rest_m: restriction multiplier for utility 5 (values between 0 and 1) 0transf: transfer volume for utility 0 (in MGD) 1transf: transfer volume for utility 1 (in MGD) 2transf: transfer volume for utility 2 (in MGD) 3transf: transfer volume for utility 3 (in MGD) 4transf: transfer volume for utility 4 (in MGD) 5transf: transfer volume for utility 5 (in MGD) Water Sources files These files can be obtained by unzipping WaterSources_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each water source for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xvolume: available water volume from source X (in MGD) Xs_area: surface area of source X (in ACF) Xdemand: demand drawn from a water source from source X (in MGD) Xup_spill: upstream spillage from source X (in MGD) Xww_inflow: wastewater inflow from source X (in MGD) Xcatch_inflow: upstream catchment inflow to source X (in MGD) Xevap: evaporation multiplier for source X (values between 0 and 1) Xds_spill: downstream spillage from source X (in MGD) X_Y_alloc_cap: the allocated capacity from source X to utility Y (values between 0 and 1) X_Y_alloc_dem: the allocated demand from source X to utility Y (values between 0 and 1) Xtrmt_alloc_Y: the allocated treatment capacity from source X to utility Y (values between 0 and 1) Utilities files These files can be obtained by unzipping Utilities_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each utility for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xst_vol: total available storage volume of utility X (in MG) Xcapacity: total storage capacity of utility X (in MG) Xnet_inf: : net inflow for all storage infrastructure for utility X (in MGD) Xst_rof: short term ROF for utility X (values between 0 and 1) Xst_stor_rof: short-term storage ROF for utility X (values between 0 and 1) Xst_trmt_rof: short-term treatment ROF for utility X (values between 0 and 1) Xlt_rof: long-term ROF for utility X (values between 0 and 1) Xlt_stor_rof: long-term storage ROF for utility X (values between 0 and 1) Xlt_trmt_rof: long-term treatment ROF for utility X (values between 0 and 1) Xrest_demand: restricted demand for utility X (in MGD) Xunrest_demand: unrestricted demand for utility X (in MGD) Xunfulf_demand: unfulfilled demand for utility X (in MGD) Xwastewater: wastewater return for utility X (in MGD) Xtreat_capacity: total treatment capacity for utility X (in MG) Xcont_fund: reserve (contingency) fund balance for utility X Xins_pout: insurance payout for utility X (% annual volumetric revenue) Xins_price: insurance price for utility X (% annual volumetric revenue) Xinfra_npv: infrastructure net present value for utility ($mil) Xst_vol: total available storage volume of utility X (in MG) Xdebt_serv: debt service for utility X (usually once per year if the infrastructure is triggered; % annual volumetric revenue) Xstor_vol: total stored volume (in MGD) Xobs_ann_dem: observed annual demand for utility X (in MGD) Xproj_dem: projected annual demand for utility X (in MGD) Xpv_debt_serv: present value of debt service payments for utility X (% annual volumetric revenue) Xgross_rev: gross revenue for utility X ($mil) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

Artificial Intelligence↗

DOE OSTI2021

Transportation Energy Analytics Dashboard (TEAD)

The investment decisions within the nation’s transportation sector have traditionally been prioritized and measured against safety and travel efficiency goals. Increasingly, federal, state, and local policies are requiring consideration of energy use and emissions in the design of our transportation infrastructure. Yet the processes, analytics, and knowledge to include these new metrics into transportation decisions are lacking. Although targeted studies and before and after analysis are performed from time to time, no comprehensive real-time monitoring systems provide energy and emissions to the same level as congestion and safety. To address this gap, the Center for Advanced Transportation Technology (CATT Lab) and the Maryland Transportation Institute (MTI) at the University of Maryland (UMD), in partnership with the National Renewable Energy Laboratory (NREL), have developed a Transportation Energy Analytics Dashboard, or TEAD, to raise awareness of the energy and emission impacts to the same level of observability as that of safety and mobility concerns. The overall goal of this project was to develop and demonstrate an online tool to monitor transportation energy use and emissions in real-time and to archive this data for retrospective analysis. By combining surface transportation energy and emissions evaluation capability with more traditional safety, mobility and reliability system evaluation, our goal is for TEAD to create a dynamic new paradigm in transportation systems management and performance analyses, for both real-time traffic operations, and longer-term planning for project and program investment decision-making.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

250 kWth Pilot Testing in Support of a 10 MWe Coal-Direct Chemical Looping Demonstration Feasibility Study

The Coal-Direct Chemical Looping (CDCL) process is emerging as a promising technology capable of high efficiency for producing electricity with low cost for carbon capture. In the CDCL process, coal is fully combusted to form carbon dioxide (CO2) and water via reaction with Fe2O3-based oxygen-carrier particles in a moving-bed reducer reactor. During reaction with coal, the Fe2O3 is reduced to form a mixture of Fe and FeO. The reduced particles are then transported to the combustor reactor where they are re-oxidized with air. The oxidation of the Fe and FeO mixture generates heat that can be used to produce steam for power generation. Once the particles are fully regenerated, they are pneumatically recycled to the reducer reactor where another reduction-oxidation (Redox) cycle begins. The Babcock & Wilcox Company (B&W) and The Ohio State University (OSU) have been developing the CDCL technology based on iron-based metal oxide particles circulating in a moving-bed reducer coupled with an entrained-flow combustor. As part of a Phase I effort of a DOE-sponsored project, B&W identified scale-up technology gaps for the coal-direct chemical looping reactor process, most of which fall under the moving-bed reactor design and operation. However, after the Phase I research, B&W concluded that the CDCL technology has the potential of generating electricity while meeting the DOE goals of greater than 90% CO2 capture and less than 35% increase in levelized cost of electricity (LCOE). B&W then moved to a Phase II project to design, build and demonstrate the CDCL technology at a 250 kWth capacity. B&W finished the construction and commissioning of the pilot test facility in 2017. The approach used to design a 250 kWth pilot-scale CDCL facility to investigate the technology gaps is presented. Important lessons from the commissioning activities that would transfer to commercial plant start-up are also shared. The findings from the test program are being incorporated into a Pre-FEED study for a 10 MWe large pilot demonstration. Under a separately-funded heat integration project, B&W and OSU are developing a multiphase computational fluid dynamic model (MFIX) of the combustor to quantify heat transfer to embedded steam generation surface, utilizing pinch analysis (ASPEN Energy Analyzer) to identify potential improvements of the heat integration scheme, and developing an integrated dynamic model (ProTRAX) of the steam turbine coupled with the chemical looping process to identify potential start-up and transient operation issues. Under an advanced control system for optimizing operation, B&W is supporting OSU to install a rules-based optimizer (B&W’s FocalPoint) on their 25 kWt bench-scale facility on the OSU West Campus. Finally, B&W and OSU were recently selected to perform a Phase I Feasibility study to evaluate installation of the 10 MWe pilot at the Dover Power & Light Municipal Power Plant in Dover, Ohio. The feasibility study includes compiling an Environmental Information Volume and generating a cost estimate for the design, construction and commissioning of the plant as well as lining up commitments from potential project participants and funding contributors. Updates on each project will be presented. The status of the technology development will be discussed. We focus on the progress made to date towards closing the technology gaps under each project.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2018

Update on Design of 10 MWe Iron-Based Coal Direct Chemical Looping Demonstration Plant

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Coupling an External Plant Code

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) with the aim to develop standalone software to perform the dynamic HRA calculations. Within the HRA, human actions in nuclear power plants (NPPs) are predicated by plant states, and human actions influence the plant. In other words, plant operations are necessarily recursive, and it becomes challenging to model complex human-plant interactions. Consequently, we have linked two software simulations that complement those shortcomings. RELAP5-3D—the Reactor Excursion and Leak Analysis Program (RELAP; Aumiller, Tomlinson, and Bauer 2001) is the foundational thermal-hydraulic software used to model nuclear systems. Using RELAP5-3D, we have simulated the plant operations proceeding according to procedures developed to address emergent situations in NPPs. Plant operations include various actions such as the operator checking plant parameters, as well as actions that are continuously performed over time until a specific parameter reaches certain criteria. That means that HUNTER and RELAP5-3D exchange information with each other and should be carried out simultaneously over time. To simulate plant operations, which represent the actual operator checks of plant parameters and corresponding manual control actions, changes in plant status are identified through simulation and performed according to the criteria and order of the procedure. Thus, the goal of coupling HUNTER with RELAP5-3D is to facilitate synchronous coupling, where human and plant models provide iterative feedback loops that drive the course of actions. The advantage of coupling with RELAP5-3D to serve as the external environment module in HUNTER is the ability to customize the plant model and streamline for particular model applications. In this paper, we will address the key features of the coupling and the coupling structure built to perform the feedback loops.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

Analytical chemistry of nuclear material: case studies from Los Alamos National Laboratory

Presented here are three case studies that demonstrate the breadth of bulk actinide analytical chemistry at Los Alamos National Laboratory (LANL). This laboratory was established during the Manhattan Project and is still considered one of the premier analytical laboratories for special nuclear materials characterization around the globe. First, the analytical chemistry of 238 Pu is presented, showcasing the unique challenges of this high activity isotope. Next, the analysis of 241 AmO 2 is discussed from the perspective of supporting nascent production at LANL. Finally, the analytical chemistry support of the production of plutonium non-destructive assay standards is discussed. Furthermore these examples paint a picture of the analytical capabilities needed to meet the dynamic challenges of LANL’s nuclear programs.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2016

NRV web knowledge base on low-energy nuclear physics

Principles underlying the organization and operation of the NRV web knowledge base on low-energy nuclear physics (http://nrv.jinr.ru) are described. This base includes a vast body of digitized experimental data on the properties of nuclei and on cross sections for nuclear reactions that is combined with a wide set of interconnected computer programs for simulating complex nuclear dynamics, which work directly in the browser of a remote user. Also, the current situation in the realms of application of network information technologies in nuclear physics is surveyed. The potential of the NRV knowledge base is illustrated in detail by applying it to the example of an analysis of the fusion of nuclei that is followed by the decay of the excited compound nucleus formed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

An Investigation of Time Distributions for Task Primitives to Support the HUNTER Dynamic Human Reliability Analysis

As an effort to support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method. GOMS-HRA was developed to provide cognition-based time and human error probability information for dynamic HRA calculation in the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework. HUNTER is a framework to support the dynamic modelling of human error in conjunction with other modelling tools. In this paper, we investigate time distributions using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which suggests an HRA data collection framework to complement full-scope simulator research as well as collect input data for dynamic HRA using simplified simulators such as the Rancor Microworld Simulator. In this study, time required for GOMS-HRA task primitives to satisfy thirteen statistical distributions is investigated. Then, the time distributions from student operators and professional operators are compared and discussed. As a result, this study identified several time distributions on five GOMS-HRA task primitives at a statistically significant level. According to analyses to date, a greater number of significant time distributions was found in abnormal or emergency operating procedures rather than standard operating procedures. In the future, it is expected that the result of this study can provide objective reference on elapsed time data for task primitives as well as help to realistically simulate scenarios within dynamic HRA.

99 GENERAL AND MISCELLANEOUS↗