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DOE OSTI2026

NGEE Arctic Integrated Modeling (IM3): Improved snow-vegetation interaction

This data product represents the integration of new code capability for arctic tundra snow-vegetation-terrain interactions into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The NGEE Arctic project developed a total of six Integrated Modeling (IM) modules informed by observations and experiments. New ELM capability represented by this data product (IM3) falls into three categories: 1) Downscaling from gridcell to topographic unit level when working through the existing coupler bypass code. 2) Four new parameters (taper, stocking, bendresist, and vegshape) have been added to ELM to allow for flexible definition of snow-vegetation interactions. 3) Vegshape and bendresist parameters are used to calculate the fraction of leaf area and/or stem area buried by snow for a given snow depth. This data record consists of a single document (pdf format) that describes the theoretical basis for the snow-vegetation-terrain interactions added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗
DOE OSTI2024

Carbon Management Projects (CONNECT) Database and Explorer

Overview The Carbon Management Projects (CONNECT) Toolkit is an online exploratory visualization tool developed by the U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM) with support from other federal agencies such as the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation (DOT). It provides a single point of access to authoritative information on federal agency investment in a portfolio of research, development, and demonstration (RD&D) projects that have been publicly announced to advance technologies for point source carbon capture, carbon dioxide removal, transport, storage, and conversion, collectively referred to as carbon management. The RD&D programs covered in this tool are authorized by annual congressional appropriations ("Base Program") and the 2021 Infrastructure Investment and Jobs Act (IIJA). The tool also incorporates public information on other federal initiatives, such as the Regional Clean Hydrogen Hubs, and public information released by other government agencies, such as the Environmental Protection Agency's (EPA) and Primacy States’ Underground Injection Control Class VI permits and EPA’s facility level greenhouse gas (GHG) emissions. Developed in a geographic information system, the tool organizes carbon management projects into five groups based on the primary technology that a project aims to advance, each visually represented as a digital layer ("carbon management project layer"). Only federally funded projects are included, which can be awarded projects that are completed or ongoing, or projects that have been selected but are currently under negotiation. Project information can be viewed in the map or in the attribute table below it when turned on. In the map view, each project is displayed at either its host site (for field work), where available, or its performer site (project lead's location, further explained in the table below). Host sites and performer sites are represented in distinct icons. Several reference layers offer additional public information on infrastructural and natural resource environment for carbon management. These reference layers, combined with multiple geographical basemaps, enable users to visualize the carbon management project layers in context. Carbon management project information will be updated monthly based on feedback and information availability. Carbon management project layers Point Source Carbon Capture (PSC) This layer contains DOE-funded projects focused on capturing carbon dioxide (CO2) from power plants or industrial facilities. Carbon Dioxide Removal (CDR) This layer contains DOE-funded projects focused on capturing CO2 from the atmosphere, including direct air capture (DAC) and DAC hubs, direct ocean capture, enhanced mineralization, and biomass carbon removal and storage. For projects with multiple host sites, each of the sites are displayed individually with the project cost and cost sharing information representing the total for the entire project. Carbon Transport This layer contains DOE- and DOT-funded projects focused on CO2 transport. The Transport Research and Development sublayer contains projects that do not involve physical infrastructure; the Proposed Transport Corridor sublayer contains projects for which either a route for the transport infrastructure has been proposed or a general area for the transport infrastructure has been identified. Carbon Storage This layer contains DOE-funded key projects focused on CO2 storage. For projects with multiple field-work sites, each of the sites are displayed individually on the map with the project cost and cost sharing information representing the overall total for the entire project. Carbon Conversion This layer contains DOE-funded projects focused on converting CO2 into economically valuable products. Reference layers The following layers provide additional information in the geographic proximity of carbon management projects. Users should reference the original sources for more details (weblinks provided below and in pop-up windows on the map). Regional Clean Hydrogen Hub and Facility These layers illustrate the approximate areas of the Regional Clean Hydrogen Hubs announced by DOE's Office of Clean Energy Demonstrations (OCED) and the approximate locations of individual facilities that constitute the hubs (see "Where are the H2Hubs located?" on the webpage linked above). EPA Facility Level GHG Emissions (direct emitter) This layer shows direct CO2 emissions from stationary sources in 2022, using data extracted from EPA's Facility Level Information on GreenHouse gases Tool (FLIGHT). Captured and injected CO2 are not deducted from direct emitters’ total emissions. Contact EPA for additional details. Underground Injection Control Class VI permit/permit application This layer shows the locations of CO2 injection wells that are granted or in the process of applying for an Underground Injection Control Class VI permit by EPA or a Primacy State (currently Louisiana, North Dakota, and Wyoming). The URLs for the permits or permit applications are provided in the pop-up windows associated with the well locations. Contact EPA for additional details. Carbon Storage Resource This layer contains information on prospective CO2 storage resources in saline formations and oil and gas reservoirs provided by the National Carbon Sequestration Database and Geographic Information System (NATCARB) spatial database. Contact NETL for additional details. Existing CO2 pipeline This layer shows active CO2 pipelines based on information digitized from the map issued by the Pipeline and Hazardous Materials Safety Administration (PHMSA). Contact PHMSA for additional details.

Carbon Conversion↗
DOE OSTI2014

Discrete Element Modeling Results of Proppant Rearrangement in the Cooke Conductivity Cell

The study of propped fracture conductivity began in earnest with the development of the Cooke cell which later became part of the initial API standard. Subsequent developments included a patented multicell design to conduct 4 tests in a press at the same time. Other modifications have been used by various investigators. Recent studies by the Stim-Lab proppant consortium have indicated that the flow field across a Cooke proppant conductivity testing cell may not be uniform as initially believed which resulted is significantly different conductivity results. Post test analysis of low temperature metal alloy injections at the termination of proppant testing prior to the release of the applied stress suggest that higher flow is to be expected along the sides and top of the proppant pack than compared to the middle of the pack. To evaluate these experimental findings, a physics-based two-dimensional (2-D) discrete element model (DEM) was developed and applied to simulate proppant rearrangement during stress loading in the Cooke conductivity cell and the resulting porosity field. Analysis of these simulations are critical to understanding the impact of modification to the testing cell as well as understanding key proppant conductivity issues such as how these effects are manifested in proppant concentration testing results. The 2-D DEM model was constructed to represent a realistic cross section of the Cooke cell with a distribution of four material properties, three that represented the Cooke cell (steel, sandstone,square rings), and one representing the proppant. In principle, Cooke cell materials can be approximated as assemblies of independent discrete elements (particles) of various sizes and material properties that interact via cohesive interactions, repulsive forces, and frictional forces. The macroscopic behavior can then be modeled as the collective behavior of many interacting discrete elements. This DEM model is particularly suitable for modeling proppant mechanical interactions subjected to an applied stress, where the experimental cell is represented as a cohesive body composed of a large number of discrete elements, and proppants can be modeled as the individual discrete particles with various sizes (following the proppant size distribution-density function used in the test) that exhibit no cohesive strength between the particles. Initial 2-D DEM modeling results suggest that proppant rearrangement and non-uniform stress distribution across the proppant pack results in significant non-uniform porosity distribution across the Cooke cell. Larger porosities develop along the edge of the proppant pack beneath the square ring seal and would result in a disproportionate higher flow field along these edges as compared to the middle of the proppant pack. These results suggest that reported conductivity values determined by the Cooke cell may be biased to overestimate the actual conductivity of the proppant at high stresses and that modifications to the standard Cooke cell will affect the magnitude of this bias.

03 NATURAL GAS↗
DOE OSTI2013

Integrating Solar PV in Utility System Operations

This study develops a systematic framework for estimating the increase in operating costs due to uncertainty and variability in renewable resources, uses the framework to quantify the integration costs associated with sub-hourly solar power variability and uncertainty, and shows how changes in system operations may affect these costs. Toward this end, we present a statistical method for estimating the required balancing reserves to maintain system reliability along with a model for commitment and dispatch of the portfolio of thermal and renewable resources at different stages of system operations. We estimate the costs of sub-hourly solar variability, short-term forecast errors, and day-ahead (DA) forecast errors as the difference in production costs between a case with “realistic” PV (i.e., subhourly solar variability and uncertainty are fully included in the modeling) and a case with “well behaved” PV (i.e., PV is assumed to have no sub-hourly variability and can be perfectly forecasted). In addition, we highlight current practices that allow utilities to compensate for the issues encountered at the sub-hourly time frame with increased levels of PV penetration. In this analysis we use the analytical framework to simulate utility operations with increasing deployment of PV in a case study of Arizona Public Service Company (APS), a utility in the southwestern United States. In our analysis, we focus on three processes that are important in understanding the management of PV variability and uncertainty in power system operations. First, we represent the decisions made the day before the operating day through a DA commitment model that relies on imperfect DA forecasts of load and wind as well as PV generation. Second, we represent the decisions made by schedulers in the operating day through hour-ahead (HA) scheduling. Peaking units can be committed or decommitted in the HA schedules and online units can be redispatched using forecasts that are improved relative to DA forecasts, but still imperfect. Finally, we represent decisions within the operating hour by schedulers and transmission system operators as real-time (RT) balancing. We simulate the DA and HA scheduling processes with a detailed unit-commitment (UC) and economic dispatch (ED) optimization model. This model creates a least-cost dispatch and commitment plan for the conventional generating units using forecasts and reserve requirements as inputs. We consider only the generation units and load of the utility in this analysis; we do not consider opportunities to trade power with neighboring utilities. We also do not consider provision of reserves from renewables or from demand-side options. We estimate dynamic reserve requirements in order to meet reliability requirements in the RT operations, considering the uncertainty and variability in load, solar PV, and wind resources. Balancing reserve requirements are based on the 2.5th and 97.5th percentile of 1-min deviations from the HA schedule in a previous year. We then simulate RT deployment of balancing reserves using a separate minute-by-minute simulation of deviations from the HA schedules in the operating year. In the simulations we assume that balancing reserves can be fully deployed in 10 min. The minute-by-minute deviations account for HA forecasting errors and the actual variability of the load, wind, and solar generation. Using these minute-by-minute deviations and deployment of balancing reserves, we evaluate the impact of PV on system reliability through the calculation of the standard reliability metric called Control Performance Standard 2 (CPS2). Broadly speaking, the CPS2 score measures the percentage of 10-min periods in which a balancing area is able to balance supply and demand within a specific threshold. Compliance with the North American Electric Reliability Corporation (NERC) reliability standards requires that the CPS2 score must exceed 90% (i.e., the balancing area must maintain adequate balance for 90% of the 10-min periods). The combination of representing DA forecast errors in the DA commitments, using 1-min PV data to simulate RT balancing, and estimates of reliability performance through the CPS2 metric, all factors that are important to operating systems with increasing amounts of PV, makes this study unique in its scope.

14 SOLAR ENERGY↗
DOE OSTI2014

Supplemental Reactor Physics Calculations and Analysis of ELF Mk 1A Fuel

These calculations supplement previous the reactor physics work evaluating the Enhanced Low Enriched Uranium (LEU) Fuel (ELF) Mk 1A element. This includes various additional comparisons between the current Highly Enriched Uranium (HEU) and LEU along with further characterization of the performance of the ELF fuel. The excess reactivity to be held down at BOC for ELF Mk 1A fuel is estimated to be approximately $2.75 greater than with HEU for a typical cycle. This is a combined effect of the absence of burnable poison in the ELF fuel and the reduced neck shim worth in LEU fuel compared to HEU. Burnable poison rods were conceptualized for use in the small B positions containing Gd2O3 absorber. These were shown to provide $2.37 of negative reactivity at BOC and to burn out in less than half of a cycle. The worth of OSCCs is approximately the same between HEU and ELF Mk 1A (LEU) fuels in the representative loading evaluated. This was evaluated by rotating all banks simultaneously. The safety rod worth is relatively unchanged between HEU and ELF Mk 1A (LEU) fuels in the representative loading evaluated. However, this should be reevaluated with different loadings. Neutron flux, both total and fast (>1 MeV), is either the same or reduced upon changing from HEU to ELF Mk 1A (LEU) fuels in the representative loading evaluated. This is consistent with the well-established trend of lower neutron fluxes for a given power in LEU than HEU.The IPT loop void reactivity is approximately the same or less positive with ELF Mk 1A (LEU) fuel than HEU in the representative loading evaluated.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2015

NSR&D Program Fiscal Year (FY) 2015 Call for Proposals Mitigation of Seismic Risk at Nuclear Facilities using Seismic Isolation

Seismic isolation (SI) has the potential to drastically reduce seismic response of structures, systems, or components (SSCs) and therefore the risk associated with large seismic events (large seismic event could be defined as the design basis earthquake (DBE) and/or the beyond design basis earthquake (BDBE) depending on the site location). This would correspond to a potential increase in nuclear safety by minimizing the structural response and thus minimizing the risk of material release during large seismic events that have uncertainty associated with their magnitude and frequency. The national consensus standard America Society of Civil Engineers (ASCE) Standard 4, Seismic Analysis of Safety Related Nuclear Structures recently incorporated language and commentary for seismically isolating a large light water reactor or similar large nuclear structure. Some potential benefits of SI are: 1) substantially decoupling the SSC from the earthquake hazard thus decreasing risk of material release during large earthquakes, 2) cost savings for the facility and/or equipment, and 3) applicability to both nuclear (current and next generation) and high hazard non-nuclear facilities. Issue: To date no one has evaluated how the benefit of seismic risk reduction reduces cost to construct a nuclear facility. Objective: Use seismic probabilistic risk assessment (SPRA) to evaluate the reduction in seismic risk and estimate potential cost savings of seismic isolation of a generic nuclear facility. This project would leverage ongoing Idaho National Laboratory (INL) activities that are developing advanced (SPRA) methods using Nonlinear Soil-Structure Interaction (NLSSI) analysis. Technical Approach: The proposed study is intended to obtain an estimate on the reduction in seismic risk and construction cost that might be achieved by seismically isolating a nuclear facility. The nuclear facility is a representative pressurized water reactor building nuclear power plant (NPP) structure. Figure 1: Project activities The study will consider a representative NPP reinforced concrete reactor building and representative plant safety system. This study will leverage existing research and development (R&D) activities at INL. Figure 1 shows the proposed study steps with the steps in blue representing activities already funded at INL and the steps in purple the activities that would be funded under this proposal. The following results will be documented: 1) Comparison of seismic risk for the non-seismically isolated (non-SI) and seismically isolated (SI) NPP, and 2) an estimate of construction cost savings when implementing SI at the site of the generic NPP.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Completion of Population of and Quality Assurance on the Nuclear Fuel Cycle Options Catalog.

An Evaluation and Screening team supporting the Fuel Cycle Technologies Program Office of the United States Department of Energy, Office of Nuclear Energy is conducting an evaluation and screening of a comprehensive set of fuel cycle options. These options have been assigned to one of 40 evaluation groups, each of which has a representative fuel cycle option [Todosow 2013]. A Fuel Cycle Data Package System Datasheet has been prepared for each representative fuel cycle option to ensure that the technical information used in the evaluation is high-quality and traceable [Kim, et al., 2013]. The information contained in the Fuel Cycle Data Packages has been entered into the Nuclear Fuel Cycle Options Catalog at Sandia National Laboratories so that it is accessible by the evaluation and screening team and other interested parties. In addition, an independent team at Savannah River National Laboratory has verified that the information has been entered into the catalog correctly. This report documents that the 40 representative fuel cycle options have been entered into the Catalog, and that the data entered into the catalog for the 40 representative options has been entered correctly.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Method development for thermal analyses testing on Reillex HPQ resin using the advanced reactive system screening tool (ARSST)

Reillex™ HPQ resin was developed by Los Alamos Laboratory and Reilly Industries Inc. in an effort to increase safety and process efficiency during the recovery and purification of plutonium. Ionac™ A-641, another strong base macroporous anion exchange resin used in the nuclear industry, was known to undergo a runaway reaction in hot nitric acid solutions. Because of this, an extensive amount of thermal analyses testing on the Reillex™ HPQ resin in SRNL was performed in 1999-2001 prior to use. A report on the thermal stability qualification of the Reillex™ HPQ resin in 8M (35%) and 12M (53%) HNO 3 was reported in 2000. In 2001, the reactivity of Reillex™ HPQ resin in 14.4M (64%) HNO 3 was evaluated. In January of 2001, thermal stability scoping tests were performed on irradiated Reillex™ HPQ resin in 14.4M (64%) HNO 3 (as a worst case scenario) and the results sent to Fauske and Associates to calculate a rupture disk size for the HB-Line resin column. A technical report by Fauske and Associates was issued in February 2001 recommending a 2.0” vent line with a rupture disk set pressure of 60 psig. This calculation was based on ARSST thermal analyses scoping tests at SRNL in which 4 grams of dried resin and 6.0 grams of 64% nitric acid in a 10 gram test cell, produced a maximum pressure rate (dP/dt) of 720 psi/min (12 psi/sec) and a maximum temperature of 250 °C. In 2015, a new batch of Reillex™ HPQ resin was manufactured by Vertellus Industries. A test sample of the resin was sent to SRNL to perform acceptance and qualification thermal stability testing using the ARSST. During these tests, method development was performed to ensure that a representative resin to acid ratios were used while running the tests in the ARSST. Fauske and Associates recommended to either use a full test cell representative of the HB-Line column or a 10 gram sample in the test cell that was representative of the ratios of resin to nitric acid in the actual HB-Line column. An observation was made during method development testing that the 4 grams of resin to 6 grams of 64% acid ratio used in 2001 to determine the rupture disk size did not entirely wet the resin and was not representative of the actual HB-Line column. The results of this study raised questions as to whether the ratio of 4 grams of resin to 6 grams of 64% nitric acid recommended by Fauske and Associates in 2001 was the correct ratio.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Determining the Release of Radionuclides from Tank 18F Waste Residual Solids: FY2016 Report

Pore water leaching studies were conducted on actual Savannah River Site (SRS) Tank 18F residual waste solids to support Liquid Waste tank closure efforts. A test methodology was developed during previous simulant testing to produce slurries of tank residual solids and grout-representative solids in grout pore water solutions (based on SRS groundwater compositions) with pH and E h values expected during the aging of the closed waste tank. The target conditions are provided below where the initial pore water has a reducing potential and a relatively high pH (Reducing Region II). The pore water is expected to become increasingly oxidizing with time (Oxidizing Region II) and during the latter stages of aging (Oxidizing Region III) the pH is expected to decrease. For the reducing case, tests were conducted with both unwashed and washed Tank 18F residual solids. For the oxidizing cases (Oxidizing Regions II and III), all samples were washed with simulated grout pore water solutions prior to testing, since it is expected that these conditions will occur after considerable pore water solution has passed through the system. For the reducing case, separate tests were conducted with representative ground grout solids and with calcium carbonate reagent, which is the grout phase believed to be controlling the pH. Ferrous sulfide (FeS) solids were also added to the reducing samples to lower the slurry E h value. Calcium carbonate solids were used as the grout-representative solid phase for each of the oxidizing cases. Air purge-gas with and without CO 2 removed was transferred through the oxidizing test samples and nitrogen purge-gas was transferred through the reducing test samples during leach testing. The target pH values were achieved to within 0.5 pH units for all samples. Leaching studies were conducted over an E h range of approximately 0.7 V. However, the highest and lowest E h values achieved of ~+0.5 V and ~-0.2 V were significantly less positive and less negative, respectively, than the target values. Achievement of more positive and more negative E h values is believed to require the addition of non-representative oxidants and reductants, respectively.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

U.S. Commercial Spent Nuclear Fuel Assembly Characteristics - 1968-2013

Activities related to management of spent nuclear fuel (SNF) are increasing in the US and many other countries. Over 240,000 SNF assemblies have been discharged from US commercial reactors since the late 1960s. The enrichment and burnup of SNF have changed significantly over the past 40 years, and fuel assembly designs have also evolved. Understanding the general characteristics of SNF helps regulators and other stakeholders form overall strategies towards the final disposal of US SNF. This report documents a survey of all US commercial SNF assemblies in the GC-859 database and provides reference SNF source terms (e.g., nuclide inventories, decay heat, and neutron/photon emission) at various cooling times up to 200 years after fuel discharge. This study reviews the distribution and evolution of fuel parameters of all SNF assemblies discharged over the past 40 years. Assemblies were categorized into three groups based on discharge year, and the median burnups and enrichments of each group were used to establish representative cases. An extended burnup case was created for boiling water reactor (BWR) fuels, and another was created for the pressurized water reactor (PWR) fuels. Two additional cases were developed to represent the eight mixed oxide (MOX) fuel assemblies in the database. Burnup calculations were performed for each representative case. Realistic parameters for fuel design and operations were used to model the SNF and to provide reference fuel characteristics representative of the current inventory. Burnup calculations were performed using the ORIGEN code, which is part of the SCALE nuclear modeling and simulation code system. Results include total activity, decay heat, photon emission, neutron flux, gamma heat, and plutonium content, as well as concentrations for 115 significant nuclides. These quantities are important in the design, regulation, and operations of SNF storage, transportation, and disposal systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

DYNA3D/ParaDyn Regression Test Suite Inventory

The following table constitutes an initial assessment of feature coverage across the regression test suite used for DYNA3D and ParaDyn. It documents the regression test suite at the time of preliminary release 16.1 in September 2016. The columns of the table represent groupings of functionalities, e.g., material models. Each problem in the test suite is represented by a row in the table. All features exercised by the problem are denoted by a check mark (√) in the corresponding column. The definition of “feature” has not been subdivided to its smallest unit of user input, e.g., algorithmic parameters specific to a particular type of contact surface. This represents a judgment to provide code developers and users a reasonable impression of feature coverage without expanding the width of the table by several multiples. All regression testing is run in parallel, typically with eight processors, except problems involving features only available in serial mode. Many are strictly regression tests acting as a check that the codes continue to produce adequately repeatable results as development unfolds; compilers change and platforms are replaced. A subset of the tests represents true verification problems that have been checked against analytical or other benchmark solutions. Users are welcomed to submit documented problems for inclusion in the test suite, especially if they are heavily exercising, and dependent upon, features that are currently underrepresented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Analyzing The Impacts of the Biogas-to-Electricity Purchase Incentives on Electric Vehicle Deployment with the MA3T Vehicle Choice Model

This analysis represents the biogas-to-electricity pathway under the Renewable Fuel Standard (RFS) as a point of purchase incentive and tests the impact of this incentive on EV deployment using a vehicle consumer choice model. The credit value generated under this policy was calculated in a number of scenarios based on electricity use of each power train choice on a yearly basis over the 15 year vehicle lifetime, accounting for the average electric vehicle miles travelled and vehicle efficiency, competition for biogas-derived electricity among electric vehicles (EVs), the RIN equivalence value and the time value of money. The credit value calculation in each of these scenarios is offered upfront as a point of purchase incentive for EVs using the Market Acceptance of Advanced Automotive Technologies (MA3T) vehicle choice model, which tracks sales, fleet size and energy use over time. The majority of the scenarios use a proposed RIN equivalence value, which increases the credit value as a way to explore the analysis space. Additional model runs show the relative impact of the equivalence value on EV deployment. The MA3T model output shows that a consumer incentive accelerates the deployment of EVs for all scenarios relative to the baseline (no policy) case. In the scenario modeled to represent the current biogas-to-electricity generation capacity (15 TWh/year) with a 5.24kWh/RIN equivalence value, the policy leads to an additional 1.4 million plug-in hybrid electric vehicles (PHEVs) and 3.5 million battery electric vehicles (BEVs) in 2025 beyond the no-policy case of 1.3 million PHEVs and 2.1 million BEVs when the full value of the credit is passed on to the consumer. In 2030, this increases to 2.4 million PHEVs and 7.3 million BEVs beyond the baseline. This larger impact on BEVs relative to PHEVs is due in part to the larger credit that BEVs receive in the model based on the greater percentage of electric vehicle miles traveled by BEVs relative to PHEVs. In this scenario 2025 also represents the last year in which biogas-derived electricity is able to fully supply the transportation electricity demand in the model. After 2025, the credit value declines on a per vehicle basis. At the same time a larger fraction of the credit may shift towards biogas producers in order to incent additional biogas production. The expanded 41 TWh/year biogas availability scenarios represent an increase beyond today s generation capacity and allow greater eRIN generation. With a 5.24kWh/RIN equivalence value, when all of the credit is directed towards reducing vehicle purchase prices, the 41 TWh/year biogas scenario results in 4.1 million additional PHEVs and 12.2 million additional BEVs on the road in 2030 beyond the baseline of 2.5 million PHEVs and 6.1 million BEVs. Under this expanded biogas capacity, biogas-derived electricity generation is able to fully supply electricity for a fleet of over 21 million EVs (15.6 million BEVs and 5.8 million PHEVs) on a yearly basis. In addition to assessing the full value credit scenarios described above, multiple scenarios were analyzed to determine the impact if only a fraction of the credit value was passed on to the consumer. In all of these cases, the EV deployment was scaled back as the fraction of the credit that was passed on to the consumer was reduced. These scenarios can be used to estimate the impact if the credit value is reduced in other ways as well, as demonstrated by the scenarios where the current (22.6 kWh/RIN) equivalence value was used. The EV deployment that results from an equivalence value of 22.6 kWh/RIN equivalence value is roughly equivalent to the EV deployment observed in the 25% case using the 5.24 kWh/RIN equivalence value. A higher equivalence value means that a smaller number of credits, and therefore value, is created for each kWh, and therefore the impact on EV deployment is reduced. This analysis shows several of the drivers that will impact eRIN generation and credit value, and tests the impact of an eRIN point of purchase incentive on EV deployment. This additional incentive can accelerate the deployment of EVs when it is used to reduce vehicle purchase prices. However, the ultimate impact of this policy, as modeled here, will be determined by future RIN prices, the extent to which eRIN credit value can be passed on to the consumer as a point of purchase incentive and the equivalence value.

09 BIOMASS FUELS↗
DOE OSTI2017

Using the D-Wave 2X Quantum Computer to Explore the Formation of Global Terrorist Networks

Social networks with signed edges (+/-) play an important role in an area of social network theory called structural balance. In these networks, edges represent relationships that are labeled as either friendly (+) or hostile (-). A signed social network is balanced only if all cycles of three or more nodes in the graph have an odd number of hostile edges. A fundamental property of a balanced network is that it can be cleanly divided into 2 factions, where all relationships within each faction are friendly, and all relationships between members of different factions are hostile. The more unbalanced a network is, the more edges will fail to adhere to this rule, making factions more ambiguous. Social theory suggests unbalanced networks should be unstable, a finding that has been supported by research on gangs, which shows that unbalanced relationships are associated with greater violence, possibly due to this increased ambiguity about factional allegiances (Nakamura et al). One way to estimate the imbalance in a network, if only edge relationships are known, is to assign nodes to factions that minimize the number of violations of the edge rule described above. This problem is known to be computationally NP-hard. However, Facchetti et al. have pointed out that it is equivalent to an Ising model with a Hamiltonian that effectively counts the number of edge rule violations. Therefore, finding the assignment of factions that minimizes energy of the equivalent Ising system yields an estimate of the imbalance in the network. Based on the Ising model equivalence of the signed-social network balance problem, we have used the D-Wave 2X quantum annealing computer to explore some aspects of signed social networks. Because connectivity in the D-Wave computer is limited to its particular native topology, arbitrary networks cannot be represented directly. Rather, they must be “embedded” using a technique in which multiple qubits are chained together with special weights to simulate a collection of nodes with the required connectivity. This limits the size of a fully connected network in the D-Wave to about 50 simulated nodes, using all of the approximately 1150 qubits in the machine. In order to keep within this limitation, while exploring a problem of potential social relevance, we constructed time series of historical network snapshots from Stanford’s Mapping Militants Project, where nodes represent militant organizations, and edges represent either alliances or rivalries between organizations. We constructed two series from different theaters – Iraq and Syria – spanning timelines from about 2000 to 2016, each with networks whose maximum size was in the 20-30 node range. Computationally, our experience suggests D-Wave technology is promising, providing fast, nearly constant scaling of computational effort in the main part of the calculation that relies on the quantum annealing cycle. However, the cost of embedding an arbitrary network of interest in the D-Wave native topology scales poorly. If the embedding cost can be amortized relative to the annealing cycle, it may be possible to gain a substantial advantage over classical computing methods, provided a large enough network can be accommodated by partitioning into subnetworks or some similar strategy. In terms of our application to networks of militant organizations, we found a rise in network imbalance in the Syrian theater that appears to correspond roughly with the entrance of the Islamic State into a milieu already populated with other groups, a phenomenon we plan to explore in more detail. In these very preliminary results, we also noticed that during at least one period where both the size and imbalance of the network increased substantially, the imbalance per edge seemed to remain fairly steady. This may suggest some adaptive behavior among the participating factions, which may also warrant further exploration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Performance of a Steel/Oxide Composite Waste Form for Combined Waste Steams from Advanced Electrochemical Processes

The results of electrochemical corrosion tests and modeling activities performed collaboratively by researchers at the University of Illinois at Chicago and Argonne National Laboratory as part of workpackage NU-13-IL-UIC-0203-02 are summarized herein. The overall objective of the project was to develop and demonstrate testing and modeling approaches that could be used to evaluate the use of composite alloy/ceramic materials as high-level durable waste forms. Several prototypical composite waste form materials were made from stainless steels representing fuel cladding, reagent metals representing metallic fuel waste streams, and reagent oxides representing oxide fuel waste streams to study the microstructures and corrosion behaviors of the oxide and alloy phases. Microelectrodes fabricated from small specimens of the composite materials were used in a series of electrochemical tests to assess the corrosion behaviors of the constituent phases and phase boundaries in an aggressive acid brine solution at various imposed surface potentials. The microstructures were characterized in detail before and after the electrochemical tests to relate the electrochemical responses to changes in both the electrode surface and the solution composition. The results of microscopic, electrochemical, and solution analyses were used to develop equivalent circuit and physical models representing the measured corrosion behaviors of the different materials pertinent to long-term corrosion behavior. This report provides details regarding (1) the production of the composite materials, (2) the protocol for the electrochemical measurements and interpretations of the responses of multi-phase alloy and oxide composites, (3) relating corrosion behaviors to microstructures of multi-phase alloys based on 316L stainless steel and HT9 (410 stainless steel was used as a substitute) with added Mo, Ni, and/or Mn, and (4) modeling the corrosion behaviors and rates of several alloy/oxide composite materials made with added lanthanide and uranium oxides. These analyses show the corrosion behaviors of the alloy/ceramic composite materials are very similar to the corrosion behaviors of multi-phase alloy waste forms, and that the presence of oxide inclusions does not impact the corrosion behaviors of the alloy phases. Mixing with metallic waste streams is beneficial to lanthanide and uranium oxides in that they react with Zr in the fuel waste to form highly durable zirconates. The measured corrosion behaviors suggest properly formulated composite materials would be suitable waste forms for combined metallic and oxide waste streams generated during electrometallurgical reprocessing of spent nuclear fuel. Electrochemical methods are suitable for evaluating the durability and modeling long-term behavior of composite waste forms: the degradation model developed for metallic waste forms can be applied to the alloy phases formed in the composite and an affinity-based mineral dissolution model can be applied to the ceramic phases.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Minimize Solvent Oxidation with NO X Pre-Scrubbing

A novel method to remove nitrogen dioxide (NO 2 ) from the flue gas of coal-fired power plants with CO 2 capture was further developed for commercial implementation. The technology leverages the equipment and chemistry in an existing (sulfur dioxide) SO 2 polishing scrubber upstream of the main CO 2 capture unit to remove the NO 2 , preventing degradation of the CO 2 capture solvent and formation of nitrosamines (environmental hazards). The research in this report focuses on further evaluation of the chemical additives and operating conditions associated with the NO 2 removal process to define conditions for commercial scale testing and deployment. Experimental work systematically evaluated a series of potential additives to minimize the oxidation of sulfite in a representative SO 2 pre-scrubber solution (sulfite, in turn, absorbs NO 2 ). The additive combinations and concentrations were varied alongside important process conditions such as temperature, oxygen concentration, and metals present in solution to mimic the conditions expected in a commercial system. Important results of the parametric experimental work include identifying a new, potent sulfite oxidation inhibitor, revealing the importance of combining inhibitors with metal chelating agents, validation of a low-cost additive process, and development of a new semi-empirical model to represent mechanisms associated with sulfite oxidation. In addition, the experimental work reveled the impact of operating at higher temperatures (representative of a field test unit), which will guide the selection and concertation of additives as well. Engineering analysis found that waste solutions from the pre-scrubber with NO 2 additives may potentially be integrated with existing processes on site (e.g., flue gas desulfurization unit). In addition, techno-economic analysis identified potential net savings as large as $1.30/tonne CO 2 captured and quantified the potential benefit of low cost additive options actively being pursued by the development team. Finally, the experimental results and engineering analysis supported the development of a detailed field testing plan and protocol to evaluate the technology at near-commercial scale. The field test preparation included development of procedures to introduce chemical additives to an existing SO 2 polishing unit and identification of representative flue gas conditions based on a review of existing plants. These activities will have direct bearing on operation and design of commercial units.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2017

Conceptual Biorefinery Design and Research Targeted for 2022: Hydrothermal Liquefacation Processing of Wet Waste to Fuels

The Department of Energy Bioenergy Technologies Office (BETO) invests in research and development of new pathways for commercially viable conversion of biomass into drop-in ready transportation fuels, fuel blendstocks and products. The primary emphasis has been on terrestrial and algae feedstocks, but more recently BETO has begun to explore the potential of wet wastes for biofuel production, with focus on wastewater residuals, manure, food waste, and fats, oils and grease. A recent resource analysis estimates that 77 million dry tons per year of these wastes are generated annually, 65% of which are underutilized for any beneficial purpose. Approximately 14 million dry tons of the total resource is wastewater residuals (sludge and biosolids) generated at the nation’s wastewater treatment plants (WWTPs). Conversion of this resource into transportation fuels could significantly contribute to the creation of a new domestic bioenergy and bioproduct industry, while providing an economically and environmentally sustainable alternative for current waste disposal practices. Hydrothermal liquefaction (HTL) is a process that uses hot, pressurized water in the condensed phase to convert biomass to a thermally stable oil product, also known as “biocrude”, which can then be thermo-catalytically upgraded to hydrocarbon fuel blendstocks. HTL is conceptually simple, has a high carbon efficiency, and can be applied to a wide range of wet feedstocks at similar processing conditions. The purpose of this report is to document the conceptual design, economics and supporting data for a sludge-to-fuel pathway via HTL and biocrude upgrading. The configuration includes a HTL plant that is co-located with a WWTP and a larger scale biocrude upgrading plant for production of hydrocarbon fuel blendstocks. Experimental data from bench scale testing of a 1:1 mixture of primary:secondary sludges are used to establish the economic and technical assumptions for the analysis. The design represents a goal case for the pathway, targeting performance that is anticipated to be achievable by 2022 with further research and development. The year 2022 is BETO’s target year for verification of hydrocarbon biofuel pathways. As this analysis represents a goal case, assumed values of several design parameters represent improvements in the technology relative to what has currently been demonstrated in the laboratory. While HTL is fairly well developed and may therefore be ready for commercialization prior to 2022, there are specific advancements addressed in this analysis that are necessary to enhance performance compared to what has been demonstrated to date. In addition, an important aspect to the pathway is the upgrading of biocrude to fuel blendstock, an area that has received much less attention and requires significant research to validate the goal case performance parameters. The estimated plant gate minimum fuel selling price for fuel blendstock from sludge HTL and upgrading is $3.46/gasoline gallon equivalent (gge). This price is within the tolerance (+$0.49/gge) of BETO’s $3/gge programmatic cost target and illustrates that fuel blendstocks generated from HTL of sludge and centralized biocrude upgrading have the potential to be competitive with fossil fuels. This analysis illustrates the feasibility of HTL for point-of-generation conversion of waste feedstock at a scale 1/20th that of the standard lignocellulosic biorefinery scale typically used in BETO design cases. The relevance of this work reaches beyond wastewater treatment sludge to lay the groundwork for application to other distributed wet wastes and blends that together represent a significant resource of underutilized biomass.

09 BIOMASS FUELS↗
DOE OSTI2016

FORTÉ Machine Learning

Of the non-corrupted data collected by the Orbiting Experiment (forté) satellite’s Photo-Diode Detector during the year 2001, I estimate that 7.9% of 914 894 signals are noise. My result differs dramatically from Guillen’s estimate of 96%. To arrive at this estimate, I used Gaussian mixture model (GMM) clustering–unsupervised machine learning–to aggregate the wave forms into groups based on the absolute value of the lowest 25 positive frequency discrete Fourier transform coefficients. Then, I marked several of the groups as noise by inspecting a random sampling of wave forms from each group. Marking groups as either noise or non-noise is a supervised binary classification operation. After removing the signals in noise groups from further consideration, I clustered the remaining signals into families. Again, I used a GMM, but for the familial clustering I used a Non-Negative Matrix Factorization feature vector transform. The result was 9 distinct families of lightning signals, as well as a second stage of noise filtering. To efficiently represent the entirety of the signal space, I broke each family into deciles based on their distance from the family mean. In this case, distance means the log-likelihood based on the GMM. Signals in lower deciles are more similar in shape and amplitude to their family average. I took the top 200 samples from each decile of each group, resulting in 18 000 signals. These signal approximately represent the entirety of the forté observations. To represent outliers, I also kept a zoo of the 1000 signals furthest from any family’s average. All told, the resulting data set represents the forté data with a reduction of about 51:1. To allow synthesis of an arbitrarily large number of test signals, I also captured each family’s average signal and the time-sample covariance matrix over the signals in each family. Using these two pieces of information, I can synthesize new waveforms by using a Gaussian random realization from the family average and covariance matrix. I wrote a program to test the synthesis quality. The program shows me two signals on the screen, one synthesized and one randomly drawn from the data. I attempted to identify the synthesized signal. Although the synthesis is imperfect, in an A/B comparison I only correctly chose the synthesized signal 36% of the time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Experimental Investigation of Forced Convection and Natural Circulation Cooling of a VHTR Core under Normal Operation and Accident Scenarios

This NEUP project #15-8205 entitled “Experimental Investigation of Forced Convection and Natural Circulation Cooling of a VHTR Core under Normal Operation and Accident Scenarios”, has investigated important phenomena in the safety of Very High Temperature Reactors (VHTRs) using the experimental facilities at City College of New York (CCNY) and Kansas State University (KSU), in collaboration with the Idaho State University (ISU) and Idaho National Laboratory (INL). The main objectives of this project were to investigate the forced convection and bypass flow phenomena, natural circulation flow and heat transfer, and graphite oxidation due to air ingress which could occur in a Very High Temperature Reactor (VHTR) with a prismatic core. High pressure/high temperature experiments have been conducted to obtain data that could be used for validation of VHTR design and safety analysis codes. The focus of these experiments was on the generation of benchmark data for design and off-design heat transfer for forced and natural circulation in a VHTR core. This work has built on the previous NEUP project #11-3218 which investigated forced convection and flow laminarization phenomena in a prismatic core of a VHTR and natural circulation of a pure gas under Pressurized Conduction Cooldown (PCC) and Depressurized Conduction Cooldown (DCC) conditions. Under each Task, extensive literature reviews on natural circulation, bypass flow, air ingress and graphite oxidation phenomena were conducted. In Task 1, scaling analyses were conducted by Idaho State University followed by design and construction of experimental facilities needed to conduct both bypass flow and natural circulation experiments at CCNY. Natural circulation experiments were conducted in Task 2 to investigate the air ingress phenomena, and bypass flow phenomena in Task 3, both at CCNY. In Task 4, radiation heat transfer and graphite oxidation tests were performed at Kansas State University. The experimental data were then analyzed to obtain quantitative results on natural circulation of pure gases and gas mixtures under DCC conditions, bypass flow rates, radiation heat transfer and graphite oxidation. In addition, CFD and Direct Numerical Simulations were conducted by INL and CCNY to investigate the flow laminarization phenomenon in strongly heated gas flows. The scaling analyses have shown that the key nondimensional numbers and parameters all have acceptable distortion levels principally because the CCNY facility’s test sections have representative cooling channel dimensions and are using either helium or a scalable gas such as nitrogen at representative state conditions. The natural circulation experiments involving helium and nitrogen gas mixtures at CCNY have elucidated the effect of nitrogen (simulating air) ingress into a lower plenum on the onset of natural circulation, mass flow rates and heat transfer coefficients under different power input levels in the riser section. Also, the transport of nitrogen from the lower plenum to upper plenum due to natural circulation was quantified for the first time. Nusselt number correlations for the heat transfer coefficient under natural circulation as a function of Reynolds and Prandtl numbers was also developed. The experiments at KSU revealed that prior to the onset of natural circulationin a VHTR core. This work has built on the previous NEUP project #11-3218 which investigated forced convection and flow laminarization phenomena in a prismatic core of a VHTR and natural circulation of a pure gas under Pressurized Conduction Cooldown (PCC) and Depressurized Conduction Cooldown (DCC) conditions. Under each Task, extensive literature reviews on natural circulation, bypass flow, air ingress and graphite oxidation phenomena were conducted. In Task 1, scaling analyses were conducted by Idaho State University followed by design and construction of experimental facilities needed to conduct both bypass flow and natural circulation experiments at CCNY. Natural circulation experiments were conducted in Task 2 to investigate the air ingress phenomena, and bypass flow phenomena in Task 3, both at CCNY. In Task 4, radiation heat transfer and graphite oxidation tests were performed at Kansas State University. The experimental data were then analyzed to obtain quantitative results on natural circulation of pure gases and gas mixtures under DCC conditions, bypass flow rates, radiation heat transfer and graphite oxidation. In addition, CFD and Direct Numerical Simulations were conducted by INL and CCNY to investigate the flow laminarization phenomenon in strongly heated gas flows. The scaling analyses have shown that the key nondimensional numbers and parameters all have acceptable distortion levels principally because the CCNY facility’s test sections have representative cooling channel dimensions and are using either helium or a scalable gas such as nitrogen at representative state conditions.The natural circulation experiments involving helium and nitrogen gas mixtures at CCNY have elucidated the effect of nitrogen (simulating air) ingress into a lower plenum on the onset of natural circulation, mass flow rates and heat transfer coefficients under different power input levels in the riser section. Also, the transport of nitrogen from the lower plenum to upper plenum due to natural circulation was quantified for the first time. Nusselt number correlations for the heat transfer coefficient under natural circulation as a function of Reynolds and Prandtl numbers was also developed. The experiments at KSU revealed that prior to the onset of natural circulation(ONC), molecular diffusion plays a significant role in air-ingress, however, at higher temperatures convection currents may be influencing air ingress and in-turn ONC times. Bypass flow experiments faced difficulties in the measurement of gas velocity in the main channel due to the failure of a high temperature Hot Wire Anemometer probe, so an energy balance method was instead employed to estimate the flow distribution between the main and bypass flow channels. In the graphite oxidation experiments conducted at KSU, oxidation was found to increase the thermal diffusivity of nuclear grade graphite. This change is believed to be driven by oxidation decreasing graphite sample density rather than raising the thermal conductivity. Oxidation was also shown to greatly alter graphite emissivity. If large amounts of impurities have built up within the graphite over time and have significantly increased its effective ash content, then air ingress is likely to severely inhibit the radiative heat transfer abilities of the graphite due to the formation of low emissivity, ash layers on its surface. However, if the purity of the graphite at the time of the air ingress is still close to that of its virgin specifications, the oxidation induced roughening of the graphite’s outer surface would have the effect of slightly raising its emissivity. The flow laminarization phenomenon was investigated by INL by examining the results of Direct Numerical Simulations of previous experiments, and by CCNY conducting its own DNS simulations using DOE’s Nek5000 code

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗