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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages

This report is being submitted for the task “Final Report” of DOE NEUP Project 15-8121 “Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages.” Typical nuclear power plant (NPP) outages always involve thousands of maintenance and refueling activities and a large number of workers in limited workspaces, while having tight schedules and zero-tolerance for accidents. During an outage, thousands of workers will be working in various workspaces across the NPP. High outage costs and expensive delays (approximately 1.5 million dollars of loss per day of delay) in NPP maintenance demand tight outage schedules. In packed workspaces, an automatic system that monitors human behaviors in real-time and provides insights about current and pending schedule deviations from the plan is critical for ensuring: 1) effective collaboration among workers and worker teams from different trades; 2) less waste of time and resources due to the lack of situational awareness; and 3) proactive outage project control. The overall goal of this project is to test the hypothesis that real-time imagery-based object tracking and spatial analysis, as well as human behavior modeling of outage participants, will significantly improve the efficiency of outage control while lowering the rates of accidents and incidents. Three objectives of this project are: 1) Establish real-time object tracking and spatiotemporal analysis methods that automatically assess the productivity of field activities and detect anomalous spatiotemporal relationships among activities that cause inefficiencies and risks; 2) Establish realtime human tracking and human factor modeling methods for automatically diagnosing unexpected actions of and interactions between outage participants, those which cause inefficient collaborations between Advanced Outage Control Center (AOCC), satellite outage centers, NPP workers, and maintenance service providers; and 3) Test the proposed automated object tracking, human behavior modeling, and spatiotemporal analysis methods in outage control case studies in order to characterize the effectiveness of automated imagery-data-driven methods in proactively improving the efficiency and safety of workflows in outage coordination and risk management. Recent studies of detailed human behavior monitoring on construction sites have examined the potential of applying advanced computer vision algorithms in detecting and tracking anomalous workers (i.e., workers who do not wear hard hats or safety vests) for ensuring job site safety. Some studies of human factor studies revealed the importance of modeling detailed interactions between individuals within and across teams in better understanding the impact of human in proactive project control. Other studies in the construction domain have developed computational simulation frameworks that formalize detailed spatiotemporal interactions between tasks in order to simulate the impacts of individual tasks on the performance of workflows. While integrated analyses that combine human factor assessment, as well as image processing and simulation, are in demand for effective decision-making, limited studies have examined the potential of such integrated analyses in NPP outage control. This research project has examined an automatic outage monitoring and control system that integrates human factor analysis, computer vision techniques, and simulation methods in order to enable engineers to better understand the interactions between humans, resources, and workflows during outage processes. The project aims at providing NPP maintenance agencies insights into more efficient use of limited resources in extending the life of a nuclear plant, as well as reducing waste while ensuring sufficient generation of electricity. This study is significant for the safety of nuclear plants, sustainable electricity generation for livable communities, and cost savings for maintaining electricity infrastructures in the United States.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

LEISURE: Load-Balanced Network-Wide Traffic Measurement and Monitor Placement

We report that network-wide traffic measurement is of interest to network operators to uncover global network behavior for the management tasks of traffic accounting, debugging or troubleshooting, security, and traffic engineering. Increasingly, sophisticated network measurement tasks such as anomaly detection and security forensic analysis are requiring in-depth fine-grained flow-level measurements. However, performing in-depth per-flow measurements (e.g., detailed payload analysis) is often an expensive process. Given the fast-changing Internet traffic landscape and large traffic volume, a single monitor is not capable of accomplishing the measurement tasks for all applications of interest due to its resource constraint. Moreover, uncovering global network behavior requires network-wide traffic measurements at multiple monitors across the network since traffic measured at any single monitor only provides a partial view and may not be sufficient or accurate. These factors call for coordinated measurements among multiple distributed monitors. In this paper, we present a centralized optimization framework, LEISURE (Load- EqualIzed meaSUREment), for load-balancing network measurement workloads across distributed monitors. Specifically, we consider various load-balancing problems under different objectives and study their extensions to support both fixed and flexible monitor deployment scenarios. We formulate the latter flexible monitor deployment case as an MILP (Mixed Integer Linear Programming) problem and propose several heuristic algorithms to approximate the optimal solution and reduce the computation complexity. We evaluate LEISURE via detailed simulations on Abilene and GEANT network traces to show that LEISURE can achieve much better load-balanced performance (e.g., 4.75 × smaller peak workload and 70 × smaller variance in workloads) across all coordinated monitors in comparison to a naive solution (uniform assignment) to accomplish network-wide traffic measurement tasks under the fixed monitor deployment scenario. Lastly, we also show that under the flexible monitor deployment setting, our heuristic solutions can achieve almost the same load-balancing performance as the optimal solution while reducing the computation times by a factor up to 22.5 × in Abilene and 800 × in GEANT.

42 ENGINEERING↗
DOE OSTI2017

Roofline Analysis in the Intel® Advisor to Deliver Optimized Performance for applications on Intel® Xeon Phi™ Processor

In this session we show, in two case studies, how the roofline feature of Intel Advisor has been utilized to optimize the performance of kernels of the XGC1 and PICSAR codes in preparation for Intel Knights Landing architecture. The impact of the implemented optimizations and the benefits of using the automatic roofline feature of Intel Advisor to study performance of large applications will be presented. This demonstrates an effective optimization strategy that has enabled these science applications to achieve up to 4.6 times speed-up and prepare for future exascale architectures. # Goal/Relevance of Session The roofline model [1,2] is a powerful tool for analyzing the performance of applications with respect to the theoretical peak achievable on a given computer architecture. It allows one to graphically represent the performance of an application in terms of operational intensity, i.e. the ratio of flops performed and bytes moved from memory in order to guide optimization efforts. Given the scale and complexity of modern science applications, it can often be a tedious task for the user to perform the analysis on the level of functions or loops to identify where performance gains can be made. With new Intel tools, it is now possible to automate this task, as well as base the estimates of peak performance on measurements rather than vendor specifications. The goal of this session is to demonstrate how the roofline feature of Intel Advisor can be used to balance memory vs. computation related optimization efforts and effectively identify performance bottlenecks. A series of typical optimization techniques: cache blocking, structure refactoring, data alignment, and vectorization illustrated by the kernel cases will be addressed. # Description of the codes ## XGC1 The XGC1 code [3] is a magnetic fusion Particle-In-Cell code that uses an unstructured mesh for its Poisson solver that allows it to accurately resolve the edge plasma of a magnetic fusion device. After recent optimizations to its collision kernel [4], most of the computing time is spent in the electron push (pushe) kernel, where these optimization efforts have been focused. The kernel code scaled well with MPI+OpenMP but had almost no automatic compiler vectorization, in part due to indirect memory addresses and in part due to low trip counts of low-level loops that would be candidates for vectorization. Particle blocking and sorting have been implemented to increase trip counts of low-level loops and improve memory locality, and OpenMP directives have been added to vectorize compute-intensive loops that were identified by Advisor. The optimizations have improved the performance of the pushe kernel 2x on Haswell processors and 1.7x on KNL. The KNL node-for-node performance has been brought to within 30% of a NERSC Cori phase I Haswell node and we expect to bridge this gap by reducing the memory footprint of compute intensive routines to improve cache reuse. ## PICSAR is a Fortran/Python high-performance Particle-In-Cell library targeting at MIC architectures first designed to be coupled with the PIC code WARP for the simulation of laser-matter interaction and particle accelerators. PICSAR also contains a FORTRAN stand-alone kernel for performance studies and benchmarks. A MPI domain decomposition is used between NUMA domains and a tile decomposition (cache-blocking) handled by OpenMP has been added for shared-memory parallelism and better cache management. The so-called current deposition and field gathering steps that compose the PIC time loop constitute major hotspots that have been rewritten to enable more efficient vectorization. Particle communications between tiles and MPI domain has been merged and parallelized. All considered, these improvements provide speedups of 3.1 for order 1 and 4.6 for order 3 interpolation shape factors on KNL configured in SNC4 quadrant flat mode. Performance is similar between a node of cori phase 1 and KNL at order 1 and better on KNL by a factor 1.6 at order 3 with the considered test case (homogeneous thermal plasma).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

New Insights into the Structure of Nanoporous Carbons from NMR, Raman, and Pair Distribution Function Analysis

The structural characterization of nanoporous carbons is a challenging task as they generally lack long-range order and can exhibit diverse local structures. Such characterization represents an important step toward understanding and improving the properties and functionality of porous carbons, yet few experimental techniques have been developed for this purpose. In this paper, we demonstrate the application of nuclear magnetic resonance (NMR) spectroscopy and pair distribution function (PDF) analysis as new tools to probe the local structures of porous carbons, alongside more conventional Raman spectroscopy. Together, the PDFs and the Raman spectra allow the local chemical bonding to be probed, with the bonding becoming more ordered for carbide-derived carbons (CDCs) synthesized at higher temperatures. The ring currents induced in the NMR experiment (and thus the observed NMR chemical shifts for adsorbed species) are strongly dependent on the size of the aromatic carbon domains. We exploit this property and use computer simulations to show that the carbon domain size increases with the temperature used in the carbon synthesis. The techniques developed here are applicable to a wide range of porous carbons and offer new insights into the structures of CDCs (conventional and vacuum-annealed) and coconut shell-derived activated carbons.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Towards Resilient Near Real-Time Analysis Workflows in Fusion Energy Science

Nuclear fusion holds the promise of an endless source of energy. Several research experiments across the world and joint modeling and simulation efforts between the nuclear physics and high performance computing communities are actively preparing the operation of the International Thermonuclear Experimental Reactor (ITER). Both experimental reactors and their simulated counterparts generate data that must be analyzed quickly and in a resilient way to support decision making for the configuration of subsequent runs or prevent a catastrophic failure. However, the cost if the traditional techniques used to improve the resilience of analysis workflows, i.e., replicating datasets and computational tasks, becomes prohibitive with explosion of the volume of data produced by modern instruments and simulations. Therefore, we advocate in this paper for an alternate approach based on data reduction and data streaming. The rationale is that by allowing for a reasonable, controlled, and guaranteed loss of accuracy it becomes possible to transfer smaller amounts of data, shorten the execution time of analysis workflows, and lower the cost of replication to increase resilience. We develop our research and development roadmap towards resilient near real-time analysis workflows in fusion energy science and present early results showing that data streaming and data reduction is a promising way to speed up the execution and improve the resilience of analysis workflows.

Suter, Fred↗
DOE OSTI2025

The Analysis Description Language Ecosystem: Latest developments and physics applications

We present latest developments in Analysis Description Language (ADL), a declarative domain-specific language describing the physics algorithm of a HEP data analysis decoupled from software frameworks. Analyses written in ADL can be integrated into any framework for various tasks. ADL is a multipurpose construct with uses ranging from analysis design to preservation, reinterpretation, queries, visualisation, combination, etc. The most advanced infrastructure to execute ADL on events is the CutLang runtime interpreter. Recent technical developments include an automated interface with different data types, generation of the abstract syntax tree, a visualization tool that that auto-converts analysis flows to graphs, incorporation of trained machine learning models and a Jupyter-based plotting tool. We also report physics implications including a large scale LHC analysis implementation and validation effort for beyond the standard model reinterpretation purposes and studies with ATLAS and CMS open data.

Sekmen, Sezen [Kyungpook National Univ., Daegu (Ko↗
DOE OSTI2015

Area of Interest 1. Interregional Electricity Reliability Issue and Assessment Analysis

In 2010, the U.S. Department of Energy (DOE) tasked Lawrence Berkeley National Laboratory (LBNL) and the Pacific Northwest National Laboratory (PNNL), in separate contracts, to provide coordinated technical support to the electricity industry for two national electricity reliability initiatives. The first initiative focused on improving the frequency response of each of the three North American interconnections. The second initiative focused on improving industry understanding of the causes and consequences of fault-induced delayed voltage recovery, which has been observed in all three interconnections. Both initiatives were conducted in close coordination with the North American Electric Reliability Corporation (NERC) and the Western Electric Coordination Council (WECC) and involved the participation of leading utilities from across the United States. This is the final report on LBNL’s activities. It consists of summaries of each activity, including references to published documents that were prepared through the course of the project. (Activities under taken by PNNL are reported on in a separate report.)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Understanding Dynamical Systems in High-Dimensional Parameter Spaces (Final Report)

In the last few decades, computational models, especially of the complex dynamical systems of greatest interest, i.e., climate, high energy density science, combustion, etc. have become increasingly accurate and sophisticated. Consequently, they are now routinely used to predict outcomes of experiments or to inform design decisions. However, many such simulations depend on a (large) number of parameters in order to, for example, approximate physical phenom whose exact solution is unknown or describe material properties in situations with little or no experimental data. Choosing these parameters and understanding how the outcomes of such a simulation changes with respect to the inputs are rapidly becoming some of the primary challenges in many application areas. Simulations have long been too complex for humans to fully comprehend and thus are often treated as black-box systems. The inputs to the systems are typically a collection of parameters with expert-selected ranges, and the outputs are various quantities of interest (QoIs) describing the performance of the system. Therefore, the fundamental challenge can be described as one of understanding a high-dimensional (many input parameters), multi-variate (many QoIs) function. Unfortunately, existing analysis tools are only of limited use for this task as most techniques can neither deal with many input dimensions nor offer opportunities to jointly study several QoIs. Furthermore, data analysis has long relied on an exploratory process in which scientist first visualize the available data, for example, using scatter plots or 3D renderings, form new hypotheses on some phenomena of interest, and subsequently test these hypotheses using dedicated analysis or statistics approaches. However, for high-dimensional functions this exploration is difficult if not impossible using existing tools as there are too many QoIs to simultaneously observe, and visualizations of high-dimensional spaces are abstract and difficult to understand if they exist at all. The goal of this project is to build new analysis techniques and tool that offer high level insights for exploring high-dimensional scientific data. And to extend existing approach beyond single scalar functions and instead consider multiple QoIs simultaneously.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Baseload Nitrate Salt Central Receiver Power Plant Design (Final Report)

The objectives of the work were to demonstrate that a 100 MWe central receiver plant, using nitrate salt as the receiver coolant, thermal storage medium, and heat transport fluid in the steam generator, can 1) operate, at full load, for 6,400 hours each year using only solar energy, and 2) satisfy the DOE levelized energy cost goal of $0.09/kWhe (real 2009 $). To achieve these objectives the work incorporated a large range of tasks relating to many different aspects of a molten salt tower plant. The first Phase of the project focused on developing a baseline design for a Molten Salt Tower and validating areas for improvement. Tasks included a market study, receiver design, heat exchanger design, preliminary heliostat design, solar field optimization, baseline system design including PFDs and P&IDs and detailed cost estimate. The baseline plant met the initial goal of less than $0.14/kWhe, and reinforced the need to reduce costs in several key areas to reach the overall $0.09/kWhe goal. The major improvements identified from Phase I were: 1) higher temperature salt to improve cycle efficiency and reduce storage requirements, 2) an improved receiver coating to increase the efficiency of the receiver, 3) a large receiver design to maximize storage and meet the baseload hours objective, and 4) lower cost heliostat field. The second Phase of the project looked at advancing the baseline tower with the identified improvements and included key prototypes. To validate increasing the standard solar salt temperature to 600 °C a dynamic test was conducted at Sandia. The results ultimately proved the hypothesis incorrect and showed high oxide production and corrosion rates. The results lead to further testing of systems to mitigate the oxide production to be able to increase the salt temperature for a commercial plant. Foster Wheeler worked on the receiver design in both Phase I and Phase II looking at both design and lowering costs utilizing commercial fossil boiler manufacturing. The cost and design goals for the project were met with this task, but the most interesting results had to do with defining the failure modes and looking at a “shakedown analysis” of the combined creep-fatigue failure. A separate task also looked at improving the absorber coatings on the receiver tubes that would improve the efficiency of the receiver. Significant progress was made on developing a novel paint with a high absorptivity that was on par with the current Pyromark, but shows additional potential to be optimized further. Although the coating did not meet the emissivity goals, preliminary testing the new paint shows potential to be much more durable, and potential to improve the receiver efficiency through a higher average absorptivity over the lifetime. Additional coatings were also designed and modeled results meet the project goals, but were not tested. Testing for low cycle fatigue of the full length receiver tubes was designed and constructed, but is still currently undergoing testing. A novel small heliostat was developed through an extensive brainstorming and down select. The concept was then detailed further with inputs from component testing and eventually a full prototype was built and tested. This task met or exceeded the accuracy and structure goals and also beat the cost goal. This provides a significant solar field costs savings for Abengoa that will be developed further to be used in future commercial plants. Ultimately the $0.09/kWhe (real 2009 $) and 6,400 hours goals of the project were met.

14 SOLAR ENERGY↗
DOE OSTI2012

Development and validation of a radial inflow turbine model for simulation of the SNL S-CO 2 split-flow loop

A one-dimensional model for a radial inflow turbine has been developed for super-critical carbon dioxide (S-CO 2 ) Brayton cycle applications. The model accounts for the main phenomena present in the volute, nozzle, and impeller of a single-stage turbine. These phenomena include internal losses due to friction, blade loading, and angle of incidence and parasitic losses due to windage and blade-housing leakage. The model has been added as a component to the G-PASS plant systems code. The model was developed to support the analysis of S-CO 2 cycles in conjunction with small-scale loop experiments. Such loops operate at less than a MWt thermal input. Their size permits components to be reconfigured in new arrangements relatively easily and economically. However, the small thermal input combined with the properties of carbon dioxide lead to turbomachines with impeller diameters of only one to two inches. At these sizes the dominant phenomena differ from those in larger more typical machines. There is almost no treatment in the literature of turbomachines at these sizes. The present work therefore is aimed at developing turbomachine models that support the task of S-CO 2 cycle analysis using small-scale tests. Model predictions were compared against data from an experiment performed for Sandia National Laboratories in the split-flow Brayton cycle loop currently located at Barber-Nichols Inc. The split-flow loop incorporates two turbo-alternator-compressor (TAC) units each incorporating a radial inflow turbine and a radial flow compressor on a common shaft. The predicted thermodynamic conditions at the outlet of the turbine on the main compressor shaft were compared with measured values at different shaft speeds. Two modifications to the original model were needed to better match the experiment data. First, a representation of the heat loss from the volute downstream of the sensed inlet temperature was added. Second, an empirical multiplicative factor was applied to the Euler head and another to the head loss to bring the predicted outlet pressure into better agreement with the experiment. These changes also brought the overall efficiency of the turbine into agreement with values cited by Barber Nichols for small turbines. More generally, the quality of measurement set data can in the future be improved by additional steps taken in the design and operation of the experimental apparatus. First, a thermocouple mounted at the nozzle inlet would provide a better indication of temperature at this key point. Second, heat losses from the turbine should be measured directly. Allowing the impeller to free wheel at inlet conditions and measuring the temperature drop between inlet and outlet would provide a more accurate measure of heat loss. Finally, the enthalpy change during operation is more accurately obtained by measuring the torque on the stator using strain gauges rather than by measuring pressure and temperature at inlet and outlet to infer thermodynamic states.

42 ENGINEERING↗
DOE OSTI2013

Development of Technologies and Capabilities for Coal Energy Resources

This is the final report for the Aerojet Rocketdyne (AR) Advanced Gasification Systems Development (AGSD) project that was initiated on October 1, 2004. The project’s primary objective is to demonstrate technologies that improve the availability and efficiency of gasification-based power plants and to reduce plant capital and operational costs. The objective will be accomplished by (1) development and testing of cooled refractory liners, (2) feed system development and demonstration, (3) pilot plant definition and planning, (4) transport gasifier feed analysis, (5) coal-biomass mixture feed analysis, and (6) coal-biomass mixture pilot scale tests. Task 1, development and testing of cooled refractory liners, was conducted at CANMET Energy Technology Centre in Ottawa, Canada. The test objectives were to screen high conductivity CMC materials with alternate manufacturing methods and a variety of surface treatments for cooled metal tubes in a slagging gasifier environment. During the CMC testing, it was found that a constantly cooled CMC will survive in good conditions and that high porosity CMC resulted in high material erosion and corrosion. During cooled tube testing, it was found that hard metal spray coat and bare Haynes 188 performed the best. Task 2, feed system development and demonstration, was conducted at at the Energy and Environmental Research Center (EERC) at the University of North Dakota (UND). For tasks 2.1-2.6, the test objective was to demonstrate 400-tons/day coal feed system operation (to 1,000 psia gasifier pressures) in ultra-dense phase flow without plugging and to achieve multi-element injector flow-split non-uniformities below 2 %RSD. Testing was successfully completed with no feed system plugging of the feed system. The majority of the other Task 2 activities were associated with the Dry Solids Pump design (Task 2.8 and 2.11), development (Task 2.10), fabrication (Task 2.12), amd testing (Task 2.13-2.15). A variety of tests were performed that verified the capability of the Dry Solids Pump to consolidate various pulverized feedstocks to a state capable of sealing and sustaining downstream outlet pressures during mechanical operation of the pump as well as during periods when the pump was turned off. However, the final operating goals were not achieved. Task 3, pilot plant definition and planning, was to define requirements for an advanced commercial gasifier with a cooled liner and to establish a preferred commercial gasifier system configuration to serve as the reference point for an advanced gasifier pilot plant concept definition. A pilot plant concept was successfully defined that is scalable and traceable to the commercial gasifier configuration. The schedule and cost for design, installation, and long-duration test operation of a pilot plant were estimated at 33 months and $\$$25.6M. Taks 4, transport gasifier feed analysis, was to determine the effects of larger sized transport gasifier low rank coals within the AR dry solids pump. It was found for the two low-rank +100 mesh size transport gasifier coals that the cohesion of these larger materials was significantly less than the coals ground to minus 200 mesh. Also, the gas permeability of the MSL transport coal was found to be significantly higher than the permeability of the PRB transport coal. Task 5, coal-biomass mixture feed analysis, was to determine the effects of coal biomass blends within the AR ultra-dense phase feed system and dry solids pump, and to determine the cost of electricity increase of an integrated gasification combined cycle (IGCC) operating on coal/biomass blends with the AR dry solids pump and ultra-dense phase feed system. In summary, it was found that 75/25 wt% coal/corn stover blends produce reasonable economic results for IGCC operation with minimal dry solids pump modifications – especially if the coal is a low rank coal and the corn stover biomass is pelletized. The increase in electricity cost was found to be 1.1 cents/kWh. Task 6, coal-biomass mixture pilot scale tests, was to determine which coal/biomass blends could be tested in the current dry solids pump without major modifications. As reported in detail in the reports by Sprouse (2010) and Sprouse and Darby (2013), the coal/biomass blend having the least impact on pump configuration and operation is the 90/10 wt% Illinois #6 to corn stover ratio blend. The AGSD program was initiated on October 1, 2004. The interim final report was submitted on October 21, 2010 and covered Task 1, Task 2.1-2.9, and Task 3, performed during budget period 1. This final report covers Task 2.10-2.16, 4, 5, and 6, performed during budget period 2. The interim final report is attached as part of the appendix to this report.

Darby, Alan K.↗
DOE OSTI2014

Initial RattleSnake Calculations of the Hot Zero Power BEAVRS

The validation of the Idaho National Laboratory's next generation of reactor physics analysis codes is an essential and ongoing task. The validation process requires a large undertaking and includes detailed, realistic models that can accurately predict the behavior of an operational nuclear reactor. Over the past few years the INL has developed the RattleSnake application and supporting tools on the MOOSE framework to perform these reactor physics calculations. RattleSnake solves the linearized Boltzmann transport equation with a variety of solution meth­ ods. Various traditional reactor physics benchmarks have already been performed, but a more realistic light water reactor comparison was needed to solidify the status of the code and deter­ mine its fidelity. The INL team decided to use the Benchmark for Evaluation and Validation of Reactor Simulations, which was made available in early 2013. This benchmark is a one­ of-a-kind document assembled by the Massachusetts Institute of Technology, which includes two cycles of detailed, measured PWR operational data. The results from this initial study of the hot zero power conditions show the current INL analysis procedure with DRAGON4 cross section preparation and using the low order diffusion solver in RattleSnake for the whole core calculations yield very encouraging results for PWR analysis. The radial assembly power distributions, radial detector measurements and control rod worths were computed with good accuracy. The computation of the isothermal temperature coefficients of reactivity require further study.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Restoration of the Potosi Dynamic Model 2010

In topical Report DOE/FE0002068-1 [2] technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the VW1 and the CCS1 wells, structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for Potosi Formation. Intention was for two million tons per annum (MTPA) of CO2 to be injected for 20 years. In this Task the 2010 Potosi heterogeneous model (referred to as the "Potosi Dynamic Model 2010" in this report) was re-run using a new injection scenario; 3.2 MTPA for 30 years. The extent of the Potosi Dynamic Model 2010, however, appeared too small for the new injection target. It was not sufficiently large enough to accommodate the evolution of the plume. Also, it might have overestimated the injection capacity by enhancing too much the pressure relief due to the relatively close proximity between the injector and the infinite acting boundaries. The new model, Potosi Dynamic Model 2013a, was built by extending the Potosi Dynamic Model 2010 grid to 30 miles x 30 miles (48 km by 48 km), while preserving all property modeling workflows and layering. This model was retained as the base case. Potosi Dynamic Model 2013.a gives an average CO2 injection rate of 1.4 MTPA and cumulative injection of 43 Mt in 30 years, which corresponds to 45% of the injection target. This implies that according to this preliminary model, a minimum of three (3) wells could be required to achieve the injection target. The injectivity evaluation of the Potosi formation will be revisited in topical Report 15 during which more data will be integrated in the modeling exercise. A vertical flow performance evaluation could be considered for the succeeding task to determine the appropriate tubing size, the required injection tubing head pressure (THP) and to investigate whether the corresponding well injection rate falls within the tubing erosional velocity limit. After 30 years, the plume extends 15 miles (24 km) in E-W and 14 miles (22 km) in N-S directions. After injection is completed, the plume continues to migrate laterally, mainly driven by the remaining pressure gradient. After 100 years post-injection, the plume extends 17 miles (27 km) in E-W and 15 miles (24 km) in N-S directions. The increase of reservoir pressure at the end of injection is approximately 370 psia around the injector and gradually decreases away from the well. The reservoir pressure increase is less than 30 psia beyond 14 miles (22 km) away from injector. The initial reservoir pressure is restored after approximately 20 years post-injection. This result, however, is associated with uncertainties on the boundary conditions, and a sensitivity analysis could be considered for the succeeding tasks. It is important to remember that the respective plume extent and areal pressure increase corresponds to an injection of 43 Mt CO2. Should the targeted cumulative injection of 96 Mt be achieved; a much larger plume extent and areal pressure increase could be expected. Re-evaluating the permeability modeling, vugs and heterogeneity distributions, and relative permeability input could be considered for the succeeding Potosi formation evaluations. A simulation using several injectors could also be considered to determine the required number of wells to achieve the injection target while taking into account the pressure interference.

Adushita, Yasmin↗
DOE OSTI2024

Prefeasibility Analysis of Behind-the-Meter Distributed Energy Resources in Highland Park, MI: Highland Park Pathways to Power [Slides]

Through the Communities LEAP (Local Energy Action Program) Pilot, the National Renewable Energy Laboratory (NREL) engaged the Highland Park Stakeholder Coalition to scope four technical assistance work areas to address their energy needs and goals. This slide deck addresses the highlighted tasks under work area "B" related to policy analysis, due diligence, and case studies for removing barriers and providing best practices for local clean energy development. NREL used the REopt platform to evaluate the techno-economic potential of adding solar PV, electric storage, and/or diesel generators at several locations in Highland Park, Michigan: a typical residential and commercial building in Highland Park, the Earnest T. Ford Recreation Center, and the Parker Village Microgrid. The analysis goals focused on the ability of solar PV, electric storage, and/or diesel generators to reduce electricity costs and improve site resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

On the importance of FIB-SEM specific segmentation algorithms for porous media

A new algorithmic approach to segmentation of highly porous three dimensional image data gained by focused ion beam tomography is described which extends the key-principle of local threshold backpropagation described in Salzer et al. (2012). The technique of focused ion beam tomography has shown to be capable of imaging the microstructure of functional materials. In order to perform a quantitative analysis on the corresponding microstructure a segmentation task needs to be performed. However, algorithmic segmentation of images obtained with focused ion beam tomography is a challenging problem for highly porous materials if filling the pore phase, e.g. with epoxy resin, is difficult. The gray intensities of individual voxels are not sufficient to determine the phase represented by them and usual thresholding methods are not applicable. We thus propose a new approach to segmentation that pays respect to the specifics of the imaging process of focused ion beam tomography. As an application of our approach, the segmentation of three dimensional images for a cathode material used in polymer electrolyte membrane fuel cells is discussed. We show that our approach preserves significantly more of the original nanostructure than a thresholding approach. - Highlights: • We describe a new approach to the segmentation of FIB-SEM images of porous media. • The first and last occurrences of structures are detected by analysing the z-profiles. • The algorithm is validated by comparing it to a manual segmentation. • The new approach shows significantly less artifacts than a thresholding approach. • A structural analysis also shows improved results for the obtained microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A comprehensive study on the structural evolution of HfO 2 thin films doped with various dopants

The origin of the unexpected ferroelectricity in doped HfO 2 thin films is now considered to be the formation of a non-centrosymmetric Pca 2 1 orthorhombic phase. Due to the polycrystalline nature of the films as well as their extremely small thickness (~10 nm) and mixed orientation and phase composition, structural analysis of doped HfO 2 thin films remains a challenging task. As a further complication, the structural similarities of the orthorhombic and tetragonal phase are difficult to distinguish by typical structural analysis techniques such as X-ray diffraction. To resolve this issue, the changes in the grazing incidence X-ray diffraction (GIXRD) patterns of HfO 2 films doped with Si, Al, and Gd are systematically examined. For all dopants, the shift of o 111/ t 101 diffraction peak is observed with increasing atomic layer deposition (ALD) cycle ratio, and this shift is thought to originate from the orthorhombic to P 4 2 / nmc tetragonal phase transition with decreasing aspect ratio (2 a /(b + c) for orthorhombic and c/a for the tetragonal phase). For quantitative phase analysis, Rietveld refinement is applied to the GIXRD patterns. A progressive phase transition from P 2 1 /c monoclinic to orthorhombic to tetragonal is confirmed for all dopants, and a strong relationship between orthorhombic phase fraction and remanent polarization value is uniquely demonstrated. The concentration range for the ferroelectric properties was the narrowest for the Si-doped HfO 2 films. As a result, the dopant size is believed to strongly affect the concentration range for the ferroelectric phase stabilization, since small dopants can strongly decrease the free energy of the tetragonal phase due to their shorter metal–oxygen bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

ASSERT FY16 Analysis of Feedstock Companion Markets

Meeting Co-Optima biofuel production targets will require large quantities of mobilized biomass feedstock. Mobilization is of key importance as there is an abundance of biomass resources, yet little is available for purchase, let alone at desired quantity and quality levels needed for a continuous operation, e.g., a biorefinery. Therefore Co-Optima research includes outlining a path towards feedstock production at scale by understanding routes to mobilizing large quantities of biomass feedstock. Continuing along the vertically-integrated path that pioneer cellulosic biorefineries have taken will constrain the bioenergy industry to high biomass yield areas, limiting its ability to reach biofuel production at scale. To advance the cellulosic biofuels industry, a separation between feedstock supply and conversion is necessary. Thus, in contrast to the vertically integrated supply chain, two industries are required: a feedstock industry and a conversion industry. The split is beneficial for growers and feedstock processers as they are able to sell into multiple markets. That is, depots that produce value-add feedstock intermediates that are fully fungible in both the biofuels refining and other, so-called companion markets. As the biofuel industry is currently too small to leverage significant investment in up-stream infrastructure build-up, it requires an established (companion) market to secure demand, which de-risks potential investments and makes a build-up of processing and other logistics infrastructure more likely. A common concern to this theory however is that more demand by other markets could present a disadvantage for biofuels production as resource competition may increase prices leading to reduced availability of low-cost feedstock for biorefineries. To analyze the dynamics across multiple markets vying for the same resources, particularly the potential effects on resource price and distribution, the Companion Market Model (CMM) has been developed in this task by experts in feedstock supply chain analysis, market economics, and System Dynamics from the Idaho National Laboratory and MindsEye Computing.

09 BIOMASS FUELS↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗