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Evaluation of Story Maps to Enhance Public Engagement and Communication at Legacy Management Sites - 17334

The US Department of Energy's Office of Legacy Management's (LM) mission is to fulfill the department's post-closure responsibilities and to ensure protection of human health and the environment. Accomplishing that mission currently requires managing 91 legacy sites across the country by performing efficient long-term surveillance and maintenance activities, preserving and making accessible historic site records, and identifying opportunities for beneficial reuse. Integral to the success of these activities is connecting and effectively communicating with the public, governments, and other interested parties. Relationships with such entities are so important that the Office of Legacy Management has elevated such engagement to one of its strategic goals for the next 10 years. Several public engagement efforts are currently supported, including stakeholder meetings, interpretive visitor centers, hard-copy documents, and Internet-based information sources. The tools available to communicate with the public via the Internet are continually improving, and LM proactively evaluates these tools to enhance public engagement. The use of ESRI Story Maps to effectively and more succinctly communicate LM's long-term surveillance and maintenance practices is one tool currently being evaluated. Story Maps can utilize multiple types of content to engage users through site narratives, illustrations of change over time, photos, videos, and embedded links to external sources of information. The ability to illustrate site complexities via graphics and geo-spatial data is particularly useful for staff as well as communicating to stakeholders. Staff with a variety of expertise and functions in the organization can be empowered to respond to stakeholder questions using this tool. In addition, Story Maps can be easily initiated and managed in real time by LM site managers, an efficiency that would be invaluable to them as immediate site communication needs arise. A series of test Story Maps for several sites were developed to explore the capabilities of the tool. The test Story Maps included pages that described site description and overview, historical conditions and use, cleanup conditions, current monitoring data if applicable, and institutional controls. Links to existing communications tools were also incorporated in Story Maps, such as existing web sites that currently store environmental reports and the Geo-spatial Environmental Mapping System (GEMS), where stakeholders can download monitoring data. As with any tool, many things must be taken into consideration, such as: 1) Can the current IT infrastructure support the tool? 2) What data quality protocols need to be established? 2) What resources will be needed to maintain this tool? 3) What type of information should be shared? 4) Who will be responsible for information updates? This paper explores potential approaches for developing and deploying this tool for the public. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

RAVEN Theory Manual

RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

RAVEN Theory Manual

RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.

97 MATHEMATICS AND COMPUTING↗

Status of PyGriffin Development for Integration into the NEAMS Workbench

The integration of Griffin into Workbench, by way of the PyGriffin code package, was initiated by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in FY-2022. PyGriffin was developed as a Python wrapper to Griffin to streamline the complex workflow involving mesh, cross section, and Griffin input generation, code execution, and results postprocessing, by improving user experience with high fidelity neutronics analysis through the Workbench GUI interface. PyGriffin can be used as a standalone application or through the PyARC code suite. FY-2023 saw the continued development of PyGriffin to expand its capabilities including advanced post-processing of simulation results and initial development of the Monte Carlo (MC) cross section generation workflow with the Shift MC code. PyGriffin was also approved for open-source software status in FY-2023, initiating plans to move the code repository into an open location. In addition to PyGriffin development, there were many improvements and developments made in PyARC leading to several software releases (latest version is v2.3.0), but the focus of this report is PyGriffin.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Laser ablation spectrometry for studies of uranium plasmas, reactor monitoring, and spent fuel safety

Nuclear security is one of the defining challenges of our time. Nuclear threats range from deliberate dispersal of radioactive material to contaminate the vital infrastructure to diversion and smuggling of special nuclear material for clandestine nuclear programs and nuclear terrorism, respectively. There is an associated need to develop and sustain the nuclear forensics capabilities, which requires the understanding of complex processes that occur in plasmas of nuclear materials. The area of nuclear safety has seen a resurgence of public interest, and there is a concomitant need to safely store used nuclear fuel and detect structural material failure in nuclear power systems, especially in innovative reactor designs envisioned for future adoption. Laser-produced plasmas are complicated extreme environments that can generate intense and rich, highly specific signatures of nuclear and radiological materials, which can then be explored in a wide range of applications. They include interdiction and rapid detection of nuclear materials, including their isotopic composition, detection over long distances, laboratory simulation of weapons effects, monitoring the condition of structural materials in dry cask storage containers, and novel instrumentation for nuclear power systems. We present a compilation of recent representative examples of the application of laser spectroscopy, and laser-induced breakdown spectroscopy in particular, to nuclear safety and security problems. A case is made that spectroscopic techniques based on laser-produced plasmas offer complementary, and sometimes unique, capabilities that motivate the continued exploration of their efficient production and understanding of the signatures they produce

(020.3260) Isotope shifts, (140.3440) Laser-induce↗

Invited Article: miniTimeCube

We present the development of the miniTimeCube (mTC), a novel compact neutrino detector. The mTC is a multipurpose detector, aiming to detect not only neutrinos but also fast/thermal neutrons. Potential applications include the counterproliferation of nuclear materials and the investigation of antineutrino short-baseline effects. The mTC is a plastic 0.2% 10 B - doped scintillator (13 cm) 3 cube surrounded by 24 Micro-Channel Plate (MCP) photon detectors, each with an 8×8 anode totaling 1536 individual channels/pixels viewing the scintillator. It uses custom-made electronics modules which mount on top of the MCPs, making our detector compact and able to both distinguish different types of events and reject noise in real time. The detector is currently deployed and being tested at the National Institute of Standards and Technology (NIST) Center for Neutron Research (NCNR) nuclear reactor (20 MW th ) in Gaithersburg, MD. A shield for further tests is being constructed, and calibration and upgrades are ongoing. The mTC's improved spatiotemporal resolution will allow for determination of incident particle directions beyond previous capabilities.

47 OTHER INSTRUMENTATION↗

Derivation of Multiple Covarying Material and Process Parameters Using Physics-Based Modeling of X-ray Data

There is considerable interest in developing multimodal characterization frameworks capable of probing critical properties of complex materials by relying on distinct, complementary methods or tools. Any such framework should maximize the amount of information that is extracted from any given experiment and should be sufficiently powerful and efficient to enable on-the-fly analysis of multiple measurements in a self-consistent manner. Such a framework is demonstrated in this work in the context of self-assembling polymeric materials, where theory and simulations provide the language to seamlessly mesh experimental data from two different scattering measurements. Specifically, the samples considered here consist of diblock copolymers (BCP) that are self-assembled on chemically nanopatterned surfaces. The copolymers microphase separate into ordered lamellae with characteristic dimensions on the scale of tens of nanometers that are perfectly aligned by the substrate over macroscopic areas. These aligned lamellar samples provide ideal standards with which to develop the formalism introduced in this work and, more generally, the concept of high-information-content, multimodal experimentation. In conclusion, the outcomes of the proposed analysis are then compared to images generated by 3D scanning electron microscopy tomography, serving to validate the merit of the framework and ideas proposed here.

36 MATERIALS SCIENCE↗

Physical formulation and numerical algorithm for simulating N immiscible incompressible fluids involving general order parameters

We present a family of physical formulations, and a numerical algorithm, based on a class of general order parameters for simulating the motion of a mixture of N (N⩾2) immiscible incompressible fluids with given densities, dynamic viscosities, and pairwise surface tensions. The N-phase formulations stem from a phase field model we developed in a recent work based on the conservations of mass/momentum, and the second law of thermodynamics. The introduction of general order parameters leads to an extremely strongly-coupled system of (N−1) phase field equations. On the other hand, the general form enables one to compute the N-phase mixing energy density coefficients in an explicit fashion in terms of the pairwise surface tensions. We show that the increased complexity in the form of the phase field equations associated with general order parameters in actuality does not cause essential computational difficulties. Our numerical algorithm reformulates the (N−1) strongly-coupled phase field equations for general order parameters into 2(N−1) Helmholtz-type equations that are completely de-coupled from one another. This leads to a computational complexity comparable to that for the simplified phase field equations associated with certain special choice of the order parameters. We demonstrate the capabilities of the method developed herein using several test problems involving multiple fluid phases and large contrasts in densities and viscosities among the multitude of fluids. In particular, by comparing simulation results with the Langmuir–de Gennes theory of floating liquid lenses we show that the method using general order parameters produces physically accurate results for multiple fluid phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Updating and Refining BISON TRISO Assessment

Several advanced reactor concepts consider tristructural isotropic (TRISO) fuel in their designs. To support the advanced reactor industry, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program within the U.S. Department of Energy (DOE) is developing modeling and simulation capabilities within the BISON fuel performance code. Assessment of these capabilities against available experi- mental data, such as the Advanced Gas Reactor (AGR) program, is essential in instilling confidence in the code predictions. Associated uncertainties in model inadequacy, experimental measurements, and manufacturing are also of importance. This report discusses the updating and standardization of the existing assessment suite in BISON for TRISO fuel performance analysis. The cases considered the AGR-1, AGR-2, and AGR-3/4 experimental programs. The report also includes a preliminary investigation into the sources of model inadequacy associated with silver (Ag) release fractions using the AGR-2 Compact 2-1-2 as a case study. The results indicate that uncertainties in the operating temperatures supplied to the model and the form of those temperature conditions (spatially averaged versus spatially resolved) both affect Ag release predictions. This suggests that previously observed model inadequacy can be attributed to both physical models and the operating conditions supplied to them. These findings will be leveraged to guide development of assessment cases for additional experiments and refinement of physical models for behaviors that potentially influence Ag release, such as palladium penetration.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Application of Neutron Imaging to InvestigateFlow Through Fractures for EGS

This paper will describe ongoing efforts at Oak Ridge National Laboratory to develop a unique experimental capability for investigating flow through porous and fractured geological media using neutron imaging techniques. This capability is expected to support numerous areas of investigation associated with flow processes relevant to EGS including, but not limited to: experimental visualization and measurement of velocity profiles and other flow characteristics to better inform reduced-order modeling of flow through fractures; laboratory scale validation of flow models and simulators; and a 'real-time' tool for studying geochemical rock/fluid interactions by noninvasively measuring material effects such as precipitation and dissolution in EGS representative conditions. Neutron scattering and attenuation based techniques have many distinctive advantages over other radiographic imaging methods for studying certain types of physical processes because cold and thermal neutrons are more highly attenuated by materials with large Hydrogen compositions while they more easily penetrate higher Z materials, such as those used in structural applications. Experiments exploiting this behavior may therefore be devised to study flow behaviors in samples even when thick pressure vessel walls and large sample masses are present. The objective of this project is to develop an experimental setup and methodology for taking EGS representative core samples with engineered fractures and fracture features, subjecting them to a triaxial stress state at EGS representative temperatures (up to 300 degrees C), and pumping high pressure fluid through the sample while imaging and measuring fluid flow characteristics using high flux neutron beams. This effort will take advantage of signature Oak Ridge National Laboratory facilities, including the Spallation Neutron Source and High Flux Isotope Reactor, as well as its core expertise in Neutron Science. Towards this end, a geothermal pressure test cell and flow system has been developed that can accommodate 1.5 diameter, 6 long core samples and apply a radial confining pressure up to 10,000 psi with fluid flow pressures up to 5,000 psi. This cell has been specially designed to optimize the transmission of neutrons and permit improved imaging of the interior of the sample of interest. Proof of principle measurements of the system have been performed and will be discussed in this paper. Techniques for injecting fluid contrast agents to permit visualization and quantification of flow profiles are also being developed and will be described along with future development plans.

Polsky, Yarom↗

Crosscutting Recombination Metrology for Expediting VOC Engineering

Work carried out under this grant addressed the need for improved materials and device characterization of solar cell designs. This experimental program aimed to develop joint electrical and optical studies of solar cells based on the group-II-VI semiconductor CdTe and the chalcogenide semiconductor Cu(InGa)Se 2 . Electrical measurements focused on temperature (T) and illumination intensity (I) dependence of the open-circuit voltage (VOC), a quantity that plays an important role in conversion efficiency. The VOC depends on temperature and illumination intensity through the energy gap and positions of the quasiFermi levels (QFLs). Optical measurements exploited the illumination and temperature dependence of absolute photoluminescence (PL) intensity (PL-I), a quantity that also depends on the QFL positions. The QFL splitting is a quantity that also depends on recombination rates within the solar cell, including radiative and non-radiative processes. Other factors affect the electrical and optical properties. These include band offsets at both the front and back interfaces of the device active region where electrical contacts are formed. Understanding, locating, and quantifying the recombination properties of the solar cells was the principal goal of this research. Custom simulations were developed to solve continuity and Poisson equations selfconsistently to obtain free-electron and free-hole concentrations. The measurements of temperature and intensity dependent VOC and PL-I allowed the extraction of a number of physical parameters including the conduction band offset, the shunt constant, and the effective capture coefficient for recombination centers, both within the absorber and at the absorber-buffer interface. In addition, the back-contact barrier height is determined from electrical properties. Each of these is discussed in the report. The illumination intensity dependence of VOC and PL-I do not overlap in experiments primarily because PL is not observed in the low-intensity regime where VOC is studied. Absolute PL-I measurements enabled development of an approach directly comparing it with VOC. This in turn allowed development of a simulation capability that would consistently use both measurements, as functions of T and I, for producing a minimization scheme using a differential evolution algorithm. The approach was applied to both CdTe and Cu(InGa)Se 2 solar cells each prepared under various conditions. Shunt conductivity, QFL splitting, recombination were measured. Also extensively studied are current-voltage and frequency-dependent capacitance voltage. Work completed under this grant included studies of magnesium zinc oxide (MZO) buffered CdTe solar cells including the effects of hydroiodic acid (HI) treatment. From these studies the recombination rates were quantified at the buffer/absorber (front) interface. The effect of back-contact barrier height was investigated. CdTe solar cells were prepared with CdSe and CdS buffer layers. Lower grain-boundary potential fluctuation, higher back-contact barrier height, and greater bulk recombination were observed in early devices with CdSe buffer layer. Investigations were also carried out into CdS/Cu(InGa)Se 2 solar cells. A metal-insulatorsemiconductor capacitance-voltage technique was developed to extract recombinationrelevant properties of the absorber interface. From this work the density of interface states D it , their capture cross-section σ, fixed charge at the interface Q f , and surface recombination velocity were all extracted.

14 SOLAR ENERGY↗

A TCN-Based Hybrid Forecasting Framework for Hours-Ahead Utility-Scale PV Forecasting

This paper presents a Temporal Convolutional Network (TCN) based hybrid PV forecasting framework for enhancing hours-ahead utility-scale PV forecasting. The hybrid framework consists of two forecasting models: a physics-based trend forecasting (TF) model and a data-driven fluctuation forecasting (FF) model. Three TCNs are integrated in the framework for: i) blending the inputs from different Numerical Weather Prediction sources for the TF model to achieve superior performance on forecasting hourly PV profiles, ii) capturing spatial-temporal correlations between detector sites and the target site in the FF model to achieve more accurate forecast of intra- hour PV power drops, and iii) reconciling TF and FF results to obtain coherent hours-ahead PV forecast with both hourly trends and intra-hour fluctuations well preserved. To automatically identify the most contributive neighboring sites for forming a detector network, a scenario-based correlation analysis method is developed, which significantly improves the capability of the FF model on capturing large power fluctuations caused by cloud movements. Here, the framework is developed, tested, and validated using actual PV data collected from 95 PV farms in North Carolina. Simulation results show that the performance of 6 hours ahead PV power forecasting is improved by 20% - 30% compared with state-of-the-art methods.

42 ENGINEERING↗

Idea Paper: The Lifecycle of Software for Scientific Simulations

The software lifecycle is a well researched topic that has produced many models to meet the needs of different types of software projects. However, one class of projects, software development for scientific computing, has received relatively little attention from lifecycle researchers. In particular, software for end-to-end computations for obtaining scientific results has received few lifecycle proposals and no formalization of a development model. An examination of development approaches employed by the teams implementing large multicomponent codes reveals a great deal of similarity in their strategies. This idea paper formalizes these related approaches into a lifecycle model for end-to-end scientific application software, featuring loose coupling between submodels for development of infrastructure and scientific capability. We also invite input from stakeholders to converge on a model that captures the complexity of this development processes and provides needed lifecycle guidance to the scientific software community.

Dubey, Anshu↗

APPLICATION OF MATURITY MODELS FOR EVALUATING CYBERSECURITY PROGRAMS AT NUCLEAR AND RADIOLOGICAL FACILITIES

Maturity models can be used to provide government agencies, industry associations, and organizations operating nuclear facilities with the ability to quickly evaluate the maturity of their cybersecurity programs and identify areas to prioritize for improvement. The Cybersecurity Capability Maturity Model (C2M2) was developed by the U.S. Department of Energy to allow organizations in the energy sector to evaluate the programmatic capabilities of their cybersecurity programs in a consistent manner, communicate programmatic maturity information, prioritize cybersecurity investments in targeted areas of concern, and track how the maturity of their cybersecurity program evolves over time. The C2M2 is designed for use by any critical infrastructure organization regardless of ownership, structure, or size. The C2M2 can be easily fine-tuned to access the maturity of nuclear cybersecurity programs and their application at individual facilities. Built on a foundation of existing cybersecurity standards, frameworks, programs, and initiatives, the model features 10 security domains. Performance in each security domain is characterized using a structured set of cybersecurity practices that represent activities an organization can perform to improve cybersecurity in their domain. Each practice can be quickly evaluated as being either fully, largely, partially, or not implemented. Once practices are evaluated for each security domain, the model defines four maturity indicator levels that apply independently to each domain in the model. To earn a maturity level in a given domain, an organization must adequately perform all the practices for that maturity level and its predecessor level(s). A small assessment team can conduct a C2M2 assessment in a single day. A screening version of the C2M2 allows an initial look at the maturity of nuclear cybersecurity programs that could be completed in under an hour.

Cyber security, Nuclear security, maturity model↗

Tech-X contributions to the Center for Tokamak Transients (CTTS) Scientific Discovery through Advanced Computing (SciDAC) project (Final Report)

The Center for Tokamak Transients Simulations (CTTS) consists of computational plasma physicists, computer scientists, and applied mathematicians who are together developing and applying simulation software to improve our understanding of and ability to predict and control transient events in tokamak discharges, particularly those that lead to violent disruptions. We have major simulation activities concerning disruptions that are caused by violating ideal MHD stability criteria, vertical displacement events, resistive wall modes, and tearing modes. We are performing comprehensive modeling of disruption mitigation techniques, particularly by shattered pellet injection (SPI). The Center is built around two mature extended MHD codes: NIMROD and M3D-C1. These codes are being extended in a number of ways as required by the demands of disruption modeling, and are being optimized to work well for larger problem size and modern computer architectures as required to model tokamak plasmas with realistic parameters over the required timescales. The codes will be coupled to the FronTier code for state-of-the-art modeling of SPI. Validation with experimental data on DIII-D, NSTX, and JET is being facilitated by rigorous uncertainty quantification (UQ). The high-level objectives of the center are to: (1) Develop better understanding and improved predictive capability of when crossing a linear stability boundary will likely lead to a disruption, (2) Provide a tool for calculating vessel forces, both axisymmetric and non-axisymmetric, for worst case VDE and other disruptions in tokamaks, (3) Develop increased understanding and improved predictive capability for locked mode disruptions and how best to avoid them, (4) Develop, verify, and validate 3D models for disruption mitigation by shattered pellets that can be used to design and optimize a system for future tokamaks, and (5) Increase the efficiency and scalability of the M3D-C1 and NIMROD codes so that they can model disruptions in ITER scale devices using the most powerful DOE HPC hardware, and (6) Demonstrate code-coupling via FronTier coupling with NIMROD and M3D-C1 and by interfacing these codes within a WDM framework.

97 MATHEMATICS AND COMPUTING↗

Hybrid methods for cybersecurity analysis :

Early 2010 saw a signi cant change in adversarial techniques aimed at network intrusion: a shift from malware delivered via email attachments toward the use of hidden, embedded hyperlinks to initiate sequences of downloads and interactions with web sites and network servers containing malicious software. Enterprise security groups were well poised and experienced in defending the former attacks, but the new types of attacks were larger in number, more challenging to detect, dynamic in nature, and required the development of new technologies and analytic capabilities. The Hybrid LDRD project was aimed at delivering new capabilities in large-scale data modeling and analysis to enterprise security operators and analysts and understanding the challenges of detection and prevention of emerging cybersecurity threats. Leveraging previous LDRD research e orts and capabilities in large-scale relational data analysis, large-scale discrete data analysis and visualization, and streaming data analysis, new modeling and analysis capabilities were quickly brought to bear on the problems in email phishing and spear phishing attacks in the Sandia enterprise security operational groups at the onset of the Hybrid project. As part of this project, a software development and deployment framework was created within the security analyst work ow tool sets to facilitate the delivery and testing of new capabilities as they became available, and machine learning algorithms were developed to address the challenge of dynamic threats. Furthermore, researchers from the Hybrid project were embedded in the security analyst groups for almost a full year, engaged in daily operational activities and routines, creating an atmosphere of trust and collaboration between the researchers and security personnel. The Hybrid project has altered the way that research ideas can be incorporated into the production environments of Sandias enterprise security groups, reducing time to deployment from months and years to hours and days for the application of new modeling and analysis capabilities to emerging threats. The development and deployment framework has been generalized into the Hybrid Framework and incor- porated into several LDRD, WFO, and DOE/CSL projects and proposals. And most importantly, the Hybrid project has provided Sandia security analysts with new, scalable, extensible analytic capabilities that have resulted in alerts not detectable using their previous work ow tool sets.

Dunlavy, Daniel M.↗

Solid Oxide Based Electrolysis and Stack Technology with Ultra-High Electrolysis Current Density (>3A/cm 2 ) and Efficiency

Hydrogen, a valuable commodity gas, is increasingly recognized as an important fuel and energy storage pathway of the future. This project aims to develop an innovative solid oxide based electrolysis cell and stack technology with ultra-high steam electrolysis current (>3A/cm 2 ) for potentially ultra-low-cost, highly efficient hydrogen production from diverse renewable sources. In this project, solid oxide based high power density cells (HiPoD cells) were developed. Those cells demonstrated capability of operating at ultra-high electrolysis current density of 6 A/cm 2 at 1.67V. During a long term steady state electrolysis test, a HiPoD cell was operated for more than 1000 hours at 3 A/cm 2 with a low degradation rate of 1.8% per 1000 hours. A 20-cell electrolysis stack was built using HiPoD cells and an ultra-compact, low-cost stack design platform. This stack was used to explore the boundaries of high current density electrolysis operation and achieved an incredible stack current density of 3 A/cm 2 with an average cell voltage of only 1.493 V. The stack was further operated in steady-state electrolysis at 2 A/cm 2 for more than 1000 hours with an overall degradation of 0.57% per 1000 hours. With an improved understanding of electrolysis operation at ultra-high current density, a new compact stack architecture (CSA) design with scalability up to 55 kW (or 38 kg H 2 per day) was tested. A number of 45-cell CSA stack was built and demonstrated 10 kW and 245 g/hr hydrogen production at 1.8 A/cm 2 electrolysis current density. In addition to cell and stack development, a preliminary system design was developed by integrating the inputs from electrochemistry, cell/stack performance data, and system level implications of configuration and operational parameters. A module design was created based on a circular array of six stacks surrounded in a cool pressure vessel. Further architectural and controls strategies such as stack power control and instrumentation were determined through the development of the module. A comprehensive techno-economic study of an ultra-high current density SOEC system integrated with renewable energy sources has been conducted. To determine the estimated cost of hydrogen for the system, the H2A Current Distributed Hydrogen Production Model version 3.101 was applied. Annual system production cases at both commercial and industrial electricity rates as per the H2A model was analyzed. The option of meeting DOE 2020 Advanced Electrolysis Technologies targets were discussed. Feedstock electricity represents the bulk of projected hydrogen cost with either electricity rate. At an annual production volume of 250 units, H2A hydrogen cost of $2.3/kg can be achieved at electricity cost around 3.5¢/kWh.

08 HYDROGEN↗

California CO 2 Storage Assurance Facility Enterprise (C2SAFE): Final Technical Report

The California CO 2 Storage Assurance Facility Enterprise (C2SAFE) project conducted a preliminary study into the feasibility of a commercial-scale carbon dioxide (CO 2 ) storage complex located in California’s Southern San Joaquin Valley (SSJV). The work represents the first phase of a multi-phased development approach outlined by the United States Department of Energy’s (DOE’s) Carbon Storage Assurance and Facility Enterprise (CarbonSAFE) program meant to develop carbon storage sites capable of permanently storing 50 million metric tonnes of CO 2 , or greater, injected over a typical facility life of 20 to 30 years. This report represents the culmination of work performed under C2SAFE and outlines a phased implementation plan for large-scale, industrial carbon capture and permanent storage in California’s SSJV. The report is meant to be a standalone document and as such provides high-level summaries of all tasks of the project, but is also meant to complement the other three topical reports issued by the project – reports referenced herein. The study considered multiple scenarios including an east-side storage facility, a west-side storage facility, and potential multi-site storage facilities. The east-side storage facility is to be located at Clean Energy Systems, Inc.’s Kimberlina Power Plant, or nearby, and the west-side facility will be located at the California Resources Corporation’s (CRC’s) Elk Hills oil field. The majority of carbon emissions are planned to be captured from existing sources and transported to the selected and verified storage site(s). Capture from the single closest source to the eastern storage facility and the sources within the Elk Hills field would meet the CarbonSAFE storage goal of 50 million tonnes. The study has shown there is sufficient storage capacity to meet this requirement and more; thus, capture from any of the numerous additional large nearby sources would substantially leverage the CarbonSAFE investment. A comparison of preliminary CO 2 capture, transportation, and storage costs to economic value and incentives in the state shows current market conditions make it economically feasible to develop large-scale industrial storage sites in California’s SSJV. The business case for Carbon Capture and Storage (CCS) in California’s SSJV appears economically viable today for large CO 2 point sources involved in the production of transportation fuels, such as oilfield cogeneration units and steam boilers. The overall levelized CCS cost is estimated at roughly 125 per tonne of CO 2 , which includes CO 2 amine-solvent post-combustion capture, transportation, and storage. The levelized CO 2 capture cost is based on today’s technology, with no future cost reduction factored in for technology improvement. The sum of the value of incentives and revenue from California Low Carbon Fuel Standard (LCFS) credits (discounted roughly 20% from their current transaction value), sale of California cap-and-trade emission allowances, and Section 45Q tax credits—either for saline storage or the Enhanced Oil Recovery (EOR) credit plus CO 2 sales revenue—is about 165/tonne-CO 2 . The economic viability of CCS for Natural Gas Combined Cycle (NGCC) power plants in the SSJV is more site-specific. A plant providing power solely to the electric grid, if it added CCS, should be eligible for Section 45Q tax credits and could sell its excess cap-and-trade emission allowances, but it would not generate LCFS credits. Using the cost and incentive values detailed in this report, it would not be economical for such a plant to add CCS today, barring other considerations. An NGCC plant within an oilfield (e.g., CRC Elk Hills and NRG Sunrise) that provides power to the oilfield as well as to the grid should receive “partial credit” in terms of generating LCFS credits if it added CCS (pro-rated for the fraction of power going to the oilfield). Such a plant should also be eligible for Section 45Q tax credits and garner revenue from selling its excess cap-and-trade emission allowances. Using the cost and incentive values described in this report, the economic viability of adding CCS today would depend on the relative fractions of electricity supplied to the oilfield and the grid. As the value of cap-and-trade emission allowances grows over time (either by market forces or the escalating floor price), the relative fraction of power needing to remain in the oilfield to achieve “breakeven” would diminish. At some point, even plants providing all their power to the grid would be candidates for economical CCS application. The C2SAFE team has proposed to expand upon the knowledge gained during this study by conducting a detailed feasibility assessment under a follow-on phase of the program, Phase II – Feasibility. This would include detailed data collection at the two sites, analysis, reporting, stakeholder outreach, and risk mitigation activities to support the development of a commercial carbon storage complex in the SSJV.

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