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At least 811 records · Page 45

Wood-to-Fuel for California's Transportation Sector using Autothermal Pyrolysis (Progress Report for FRD-17-002)

Accomplishments this period: Subcontract with Frontline BioEnergy, LLC has been executed and is in place (Task 1). List of TAC members is awaiting input from the CEC including any additional members of their own choosing before we finalize confirmation with the listed individuals. This is also holding off on the documented TAC Member commitment, and the DRAFT TAC Meeting Schedule, as we need to know who is approved to be on the TAC before we get commitments and start setting meetings. We are awaiting input from the CEC as to a requested date for the CPR#1. It was originally set for the beginning of July (July 7th), but as the CEC needs to conduct this, we need their input on the revised date. The additional wood feed stock was sent to ISU for analysis of autothermal pyrolysis products on July 15. The Kern refinery continues to express interest in using the bio-oil produced from the demonstration in one or more of their plants. We believe this analysis information will be a critical component of what we share at our first Workshop later this summer

09 BIOMASS FUELS↗

System Model Calculations for the Active Trenches of the Low-Level Burial Grounds, Hanford Site, Washington

Two lined trenches (Trench 31 and 34) located within the 200 West Low-Level Burial Ground (LLBG) area of the U.S. Department of Energy’s (DOE) Hanford Site are designated for permanent disposal of low-level radioactive waste (LLW) and mixed low-level radioactive waste (MLLW). In accordance with DOE O 435.1, Radioactive Waste Management, radioactive waste shall be managed and disposed in a manner that is protective of worker, public health and safety, and the environment. DOE O 435.1 requires a site-specific radiological performance assessment (PA) that includes calculations of potential releases and subsequent doses to members of the public for a period of 1,000 years after closure of a low-level waste (LLW) disposal facility. The purpose of this environmental calculation file (ECF) is to document the various dose calculations performed to support DOE’s LLBG PA. The dose assessments are performed to evaluate the potential exposure of an all-pathway representative person to radionuclide contaminants of potential concern (COPCs) that may be released from the LLBG Trenches 31 and 34 to the point of calculation (POC) located at the outer edge of a 100 m buffer zone surrounding the trench boundary. This ECF uses inputs from other ECFs and their associated model package reports (MPRs) supporting the LLBG PA. The five major objectives of this ECF are to present the results of the following: (1) Deterministic dose assessments for both groundwater and atmospheric exposure scenarios; (2) Radon-222 (Rn-222) flux emanating at the surface from the disposed wastes; (3) Uncertainty analyses of the groundwater pathway annual dose due to uncertainty in input parameters; (4) Sensitivity analyses of the input parameters that could potentially impact the fate and transport of the contaminants and doses; (5) Doses arising from inadvertent intruder exposure scenarios.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Summary of GNU Octave Lady Godiva Simulator

A pseudo real-time interactive reactor simulator for the Lady Godiva reactor has been developed using the GNU Octave software package. The simulator tracks the time-dependent power and fuel temperature behavior of the Lady Godiva reactor during sub-prompt critical transients. Users interact with the simulator by controlling reactivity input. This input occurs through users repositioning a control rod as desired during simulator operation. Various reactor parameters are displayed graphically in near “real time,” facilitating user assessment and feedback input. The reactor model consists of a lumped-fuel core, a single control rod, and a simple heat transfer mechanism that allows heat to be rejected from the core. The goal of the simulator is to demonstrate in real-time the system response to reactivity perturbations, the effect of reactivity feedback, and the effect of temperature-dependent equilibrium conditions. The dynamic behavior of the reactor is primarily driven by the relative characteristic time-constants between the delayed neutrons and the overall heat transfer parameter. The simulator will allow users to gain experience performing standard reactor operations, such as establishing steady-state at different fuel temperatures and making power level changes

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NEAMS Workbench MOOSE Integration Update

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench is a graphical user interface (GUI) that provides a common analysis environment for the accelerated use of the NEAMS toolkit. To improve design and analysis of current and future nuclear energy systems, the NEAMS Workbench provides an integrated development environment for model creation, review, execution, output review, and visualization for integrated tools. In addition to a GUI, the NEAMS Workbench provides the Workbench Analysis Sequence Processor, an open-source tool set that facilitates input-content assistance for supported domain-specific input languages and user-friendly syntaxes. These supported syntaxes enable accelerated development and deployment of enhanced user inputs and workflows. The Multiphysics Object-Oriented Simulation Environment (MOOSE) has been supported in the NEAMS Workbench since 2016 and receives continuous updates. Efforts to improve MOOSE-based tool integration in the NEAMS Workbench are ongoing. This document details the current and planned enhancements of the NEAMS Workbench and the MOOSE framework to improve integration and usability of MOOSE-based applications within the NEAMS Workbench.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Development of an Interactive Valuation Model for Distributed Energy Resource Value

The Oklahoma Secretary of Commerce & Tourism (OSCT) seeks to address perceived challenges and barriers to the deployment of distributed energy generation resources (DERs), including solar and other technologies, in the state of Oklahoma. The Scope of Work (SOW) outlines follow-on tasks related to the previous CRADA # CRD-18-762. The first task will finalize the Interactive Valuation Model Requirements Document, the final draft of which was provided in June 2018. The second task includes the building, validation, and finalization of the interactive valuation model for expressing distributed energy resource value based on user inputs to be completed by June 30, 2019. Training for how to prepare the data inputs and use the model will also be provided. To address perceived challenges and barriers to the deployment of distributed energy generation resources (DERs), including solar and other technologies, in the state of Oklahoma, the work under this CRADA will: 1) finalize the draft Interactive Valuation Model Requirements Document delivered in June 2018; 2) finish building and validating the interactive valuation model for expressing DER value based on user inputs, and 3) provide training for use of this model.

14 SOLAR ENERGY↗

Software Quality Assurance for EBR-II Fuels Irradiation and Physics Database (FIPD)

The Fuels Irradiation and Physics Database (FIPD) is an ongoing DOE project on archival of the EBR-II metal-alloy fuel irradiation experiments. As part of its use in support of license applications, the Quality Assurance Program Plan (QAPP) was drafted and endorsed by NRC in an effort to demonstrate its compliance with regulatory expectations. Software Quality Assurance (SQA) for the physics portion of FIPD is intended to qualify the calculated quantities such as fuel and cladding temperatures, neutron fluence and axially varying burnup estimates for irradiated fuel elements. This report covers the initial evaluation of SQA status of three neutron physics and thermo-fluid codes (REBUS, RCT and SE2RCT) that form the basis of calculated quantities for as-irradiated characteristics of the tested metallic fuel elements. The report also introduces an SQA plan to address the identified deficiencies. The REBUS, RCT, and SE2RCT codes are all part of the Argonne Reactor Code (ARC) code system. There is considerable knowledge and experience on REBUS and RCT but relatively less on SE2RCT. During FY2021, efforts focused on an assessment of how the data in the EBR-II Physics and Analysis DataBase (PADB) is generated with SE2RCT and used in FIPD. Additional tasks included considerations of uncertainties for power estimates in REBUS and RCT calculations and their impact on the combined RCT methodology. The RCT software usage in FIPD was assessed this year and the input/output details studied. A “requirements” document was created that identifies the key features of the RCT software being used in FIPD that need to have SQA documentation. A brief discussion on the history of RCT and its input is included in this report along with the basic SQA roadmap laid out in the requirements document. The SE2RCT software usage in FIPD is still being studied noting that there is no current manual. As part of the work done this year, two bugs were identified in the SE2RCT software which have a minor impact on the accuracy of the results it produces. No requirements document has been created, but one identified feature of SE2RCT being used that needs verification was its fuel pin temperature calculation. The work completed this year confirms that the approximations which will be included in the software verification report for SE2RCT are accurate. In addition to software quality assurance work for RCT and SE2RCT, an automated verification framework is proposed to simplify the software quality assurance process. The purpose of this framework is to streamline code verification and documentation while minimizing repetitive tasks for code developers and reviewers. The reduction of repeated input (between reference solution, software, and documentation input) throughout the SQA process reduces potential for human errors during the preparation of the supporting software quality records. The automation of the verification and documentation process proposed for this project leverages the existing verification structure already in place for the SAS4A/SASSYS-1 code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Feedstock Carbon Intensity Calculator (FD-CIC) Users’ Manual and Technical Documentation

A transparent and easy-to-use tool for feedstock-specific, farm-level CI calculation of feedstocks is helpful. With the ARPA-E support, we have developed a tool–the Feedstock Carbon Intensity Calculator (FD-CIC). The first version of FD-CIC was released with the GREET® model in 2020 (Wang et al., 2020) so that corn feedstock producers could use this publicly available tool (https://greet.es.anl.gov/tool_fd_cic) to quantify corn grain CIs with farm-level input data and management practices. In the 2021 version, we expand the tool’s capabilities by including additional feedstocks such as soybeans, sorghum, and rice. Similar to corn, it calculates the farm-level CI for these feedstocks by allowing user-defined farm-level farming inputs and incorporating the GHG emission intensities of these inputs from GREET (in particular, GREET1, the fuel cycle model of GREET).

09 BIOMASS FUELS↗

Assessment of the Griffin Reactor Multiphysics Application Using the Empire Micro Reactor Design Concept

In late 2019, INL and ANL agreed to jointly develop the reactor physics code named Griffin based on the integration of the two code suites, MAMMOTH/Rattlesnake (INL) and MC2 - 3/PROTEUS (ANL). Griffin is being developed based on the MOOSE framework and MOOSE quality assurance procedures. This decision was made to be able to allow DOE-NE to efficiently invest funding to this area and to provide effective and timely support for existing and potential users; the latter includes industry and government organizations who are developing various types of advanced reactors in the near and long term. Since MAMMOTH/Rattlesnake has been developed based on the MOOSE framework, the INL/ANL Griffin development team agreed to build Griffin beginning with a merger of MAMMOTH and Rattlesnake into a single code and moving forward by implementing capabilities from the PROTEUS suite into Griffin. Moving forward, both ANL and INL efforts are equally invested in the Griffin project, with management support, to provide an advanced reactor multiphysics tool to assist in reactor design, optimization, and safety analysis. Much work remains in moving Griffin forward to migrate PROTEUS capabilities and to optimize performance to meet user needs. The main objective of this work is to assess the current status of Griffin capabilities in terms of performance and accuracy, to determine priorities for PROTEUS migration, and to identify capabilities and features to improve for supporting the code integration effort. For this assessment, the Empire micro reactor problem that was developed in the ARPA-E MEITNER program was selected as an advance reactor concept of interest to the technical community. The Empire reactor problem was expanded from its original incomplete specification to be a small heat-pipe-cooled micro reactor core with ~113 cm radius and 70 cm in height, composed of 18 fuel assemblies, 12 control drums, and beryllium radial and axial reflectors. In the current model, using 5 cm axial reflectors specified in the original Empire assembly model, more than 10% of neutrons leak axially and through the empty center safety hole, as well as through heat pipe channels in fuel assembly elements that extend through the top reflector region. Several calculation models of the core were defined for systematic assessment, including 2-D and 3-D fuel assemblies and whole cores with cylindrical boundaries. Cross sections were generated using Serpent 2, and meshes were produced using the Argonne mesh tool or the INL neutronics meshing tools combined with CUBIT. Cross sections and meshes were converted to the ISOXML and Exodus formats, respectively, so that Griffin and PROTEUS could use consistent data for solving the reactor problems. With the prepared cross sections and meshes, PROTEUS was run first to ensure that all input data were correctly generated and input options in terms of angle, mesh, and energy group were accurately determined. Comparisons against Serpent 2 solutions were made in terms of eigenvalue and pin power. The same calculations and comparisons were then conducted using Griffin. For the fuel assembly and whole core problems, the PROTEUS eigenvalues agreed well with reference Serpent 2 solutions within 100 and 30 pcm, respectively, and pin power differences relative to Serpent 2 were overall less than 2.2% and RMS 0.8% for the whole core models. This indicated that all input data were properly prepared. Using the same data, Griffin was run selecting the SAAF-CFEM SN solver with Legendre-Gaussian quadrature and NDA and DSA for acceleration. It was found that the SAAF-CFEM solver of Griffin required finer meshes to achieve eigenvalue and pin power solutions in good agreement with Serpent 2, consequently requiring more memory requirement and longer computation time. On the other hand, the SPH-Diffusion 2-D core calculations performed using Griffin were able to recover the exact eigenvalue from the reference Serpent 2 solutions, resulting in a pin-power distribution with an RMS of 0.6% and maximum absolute difference of less than 1.4%. The runtimes for SPH-Diffusion for the 2-D core were less than 3 minutes on 40 cores. During this evolution of this evaluation, many updates were made in Griffin by the Griffin development team of INL (focusing on software updates) and ANL (reviewing and supporting software updates) to complete this assessment. Observations from the code assessment are presented in the conclusion section of this report, followed by a discussion of recommendations for future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗

LIM1TR: Lithium-Ion Modeling with 1-D Thermal Runaway (V.1.0)

LIM1TR (Lithium-Ion Modeling with 1-D Thermal Runaway) is an open-source code that uses the finite volume method to simulate heat transfer and chemical kinetics on a quasi 1-D domain. The target application of this software is to simulate thermal runaway in systems of lithium-ion batteries. The source code for LIM1TR can be found at https://github.com/ajkur/lim1tr. This user guide details the steps required to create and run simulations with LIM1TR starting with setting up the Python environment, generating an input file, and running a simulation. Additional details are provided on the output of LIM1TR as well as extending the code with custom reaction models. This user guide concludes with simple example analyses of common battery thermal runaway scenarios. The corresponding input files and processing scripts can be found in the “Examples” folder in the on-line repository, with select input files included in the appendix of this document.

25 ENERGY STORAGE↗

Fission Product Evaluation (Quarterly Report)

The LLNL team has developed a theoretical framework to compute the fission fragment charge and mass distributions of odd-mass nuclei, which can be formed in neutron-induced reactions on even-even nuclei. For example, n+ 238 U leads to the compound nucleus 239 U which has 147 neutrons. Odd-mass and odd-odd nuclei are spin-polarized: the spin of the nucleus is not equal to 0 as in even-even nuclei (a consequence of pairing correlations) but is in fact set by a single particle. In practice, that single particle can occupy different quantum-mechanical configurations, each with different spin. This affects the deformation properties of the nucleus and, as a result, the distribution of fission fragments. These distributions require two inputs for the calculation: a potential energy surface (= the total energy of the nucleus as a function of the deformation of the nuclear shape, often parametrized with 2 degrees of freedom) and the collective inertia tensor associated with each point of the PES. In an odd-mass or odd-odd nucleus, each quantity depends on the configuration of the single particle. We computed of the order of 20 to 30 different such configurations to extract the PES for spins K=1/2, 3/2, 5/2, 7/2, and 9/2 of 239 U. We then computed the primary yields for each such PES, as shown in Fig. 1 below. These yields were weighed with the spin distribution associated with the reaction 238 U+n and the resulting distribution used as input to FREYA to compute the independent yields shown in Fig. 2. These yields are then used as inputs to the FIER code to extract the cumulative yields and compare with LLNL-LANL measurements at TUNL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improving the Economic Viability of Biological Utilization of Coal Power Plant CO 2 by Improved Algae Productivity and Integration with Wastewater Treatment

The overall goal of this project was to improve the cost-effectiveness of systems using algae to capture and beneficially utilize CO 2 from the flue gas of coal-fired power plants. Algal biomass cultivation is an attractive alternative for carbon capture and utilization because it can uptake more CO 2 per land area than any other photosynthetic crop. Also, the resulting biomass can be used to make valuable large-market commodity products, such as biofuels and animal feed. However, the use of algal carbon capture has been limited by several factors including: (1) high costs for growing algae (>$\$1,300$/ton), (2) large land requirements for algae cultivation, and (3) environmental concerns about the large amount of water and nutrient inputs needed for growing algae. This project has taken direct aim at resolving these key limitations and demonstrated several viable approaches to improve the economic and environmental feasibility of algal carbon capture. In particular, this project demonstrated a significant increase in average annual algal productivity from baseline values of 8 g/m 2 -day to above 20 g/m 2 -day. This supports a much lower projected cost of algae production (<$\$500$/ton) and reduces land requirements by more than 50%. Additionally, this project confirmed the ability to grow multiple algae species with wastewater nutrients, which facilitates the potential for substantial new revenue streams for algae cultivation based on tipping fees for nutrient laden wastewater. This study highlighted that there is more potential value in wastewater nutrient treatment credits than in the primary commodity products made from algae. The use of wastewater inputs also mitigates the concerns associated with the large amount of water needed for growing algae. The algal biomass grown for this project using wastewater and simulated flue gas inputs were characterized for potential use as an animal feed ingredient. The algae had a protein content in the range of 35-40%, which is between some common commodity animal feed products— distiller’s grains (~25-30% protein) and soybean meal (45-50% protein). In-vitro digestion tests using cattle rumen fluids, showed that this algae biomass was best suited for use as “bypass protein”, which is digested in the animal intestine. Based on the protein content and amino acid profile of the algae grown in this study, it was estimated to have market value in the range of $\$190$-$\$280$/ton. There is potential for higher value feed products if the algae content of omega-3 fatty acids or antioxidants is accounted for. This project also did small scale demonstration of forward osmosis algae dewatering and nanofiltration of hydrothermal liquefaction aqueous products, which were shown to improve the cost and energy balance for producing algal products. When all the improvements demonstrated in this study were included in techno-economic analysis, it showed there was a viable pathway to profitable algal CO 2 utilization with a payback period in the range of six to ten years.

01 COAL, LIGNITE, AND PEAT↗

Crossing the Streams – Sampler and the TemplateEngine [Slides]

This presentation discusses Sampler, which is a versatile UQ and parametric study tool that can be applied to any SCALE Sequence. Sampler can perturb any quantity in any SCALE input. Recent work at ORNL has developed new types of covariance data that allow Sampler UQ to be applied to nearly all SCALE applications, including reactor depletion, UNF fuel characterization, source term analysis, and decay heat calculation. In SCALE 6.2 releases, CE data in transport cannot be perturbed. Sampler was originally designed for stochastic sampling with any sequence within SCALE and Parametric capability added in SCALE 6.2.2. Sampler can be used for uncertainty quantification, including sample data in static or depletion calculations and sample inputs for uncertainties in compositions and dimensions. The SCALE TemplateEngine allows for expanding templates to full inputs and the combination provides a powerful UQ tool.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Electrodynamic Shaker Capability Estimation Through Experimental Dynamic Substructuring [Thesis]

Electrodynamic shaker systems are an essential tool in shock and vibration testing of dynamic environments. However, the specific performance capability of these systems is difficult to characterize. The dynamics of the shaker itself, the device under test and the specific test configuration used all couple to create a dynamic response unique to each test. Poorly predicted limitations in shaker capability affect the ability to achieve test specifications, delay testing schedules, and create difficulties for choosing test equipment. To predict shaker capability for a specific test configuration prior to setup, a lumped parameter model of the shaker system and a modal model of a device under test was developed. These models were then analytically coupled using LaGrange multiplier frequency based substructuring to estimate their coupled frequency response functions. The coupled frequency response functions were used to predict electrical inputs required to meet a given test specification. These input requirements were finally compared to a validation test using the specification and setup. Input requirements estimated using the substructuring estimated frequency response functions showed significant error. However, results using an ideal frequency response function showed very little error. These results indicate that with a better method of experimental dynamic substructuring employed it would be possible to accurately predict shaker capability for a given test configuration prior to setup.

42 ENGINEERING↗

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part I - Analysis with a Small Sample Size

Computer simulations, especially of complex phenomena, can be expensive, requiring high-performance computing resources. Often, to understand a phenomenon, multiple simulations are run, each with a different set of simulation input parameters. These data are then used to create an interpolant, or surrogate, relating the simulation outputs to the corresponding inputs. When the inputs and outputs are scalars, a simple machine learning model can suffice. However, when the simulation outputs are vector valued, available at locations in two or three spatial dimensions, often with a temporal component, creating a surrogate is more challenging. In this report, we use a two-dimensional problem of a jet interacting with high explosives to understand how we can build high-quality surrogates. The characteristics of our data set are unique - the vector-valued outputs from each simulation are available at over two million spatial locations; each simulation is run for a relatively small number of time steps; the size of the computational domain varies with each simulation; and resource constraints limit the number of simulations we can run. We show how we analyze these extremely large data-sets, set the parameters for the algorithms used in the analysis, and use simple ways to improve the accuracy of the spatio-temporal surrogates without substantially increasing the number of simulations required.

97 MATHEMATICS AND COMPUTING↗

Fast Charging Infrastructure for Electrifying Road Trips to and from National Parks in the Western United States

National parks in the Western United States draw over 80 million visitors every year, and most visitors rely on personal cars for their road trips (or long-distance travels). Travel to national parks represents distinct travel demand, as they are typically located in remote areas necessitating long-distance trips. This study investigates the quantity and locations of on-route fast charging infrastructure needed by 2030 to enable seamless travel to/from national parks using electric vehicles in seven target states in the region, employing unprecedented high-resolution spatial and temporal analysis. We find that the required number of fast charging ports for on-route charging infrastructure ranges from 1,200 to 22,000, depending on different assumptions of key input parameters - vehicle electrification rate, charging behavior, average gap between charging stations, port utilization rate, and towing trailers. Our analysis also indicates that electrical load for on-route fast charging infrastructure would peak in the afternoon, in the range of 70-400 MW, varying with the key input parameters. This study illustrates how different input parameters result in different degrees of impact on various aspects of charging infrastructure. We also examine the characteristics of projected charging infrastructure in terms of land use type, relationship with traffic volume, size of stations, and other variables.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Refining Processing Engines from SAPHIRE: Initialization of Fault Tree/Event Tree Solver

SAPHIRE has been extensively employed for over 35 years to model risk-important systems and quantify risk models. As a well-established and thoroughly documented Probabilistic Risk Assessment (PRA) tool, SAPHIRE has continuously tracked computational trends and received regular updates. Despite its ongoing evolution, there remains a need for further enhancements, particularly in dealing with the quantification of exceptionally large models. These improvements could take the form of algorithmic advancements, harnessing the power of parallel computing, and exploring the potential benefits of cloud computing solutions. Considering these aspirations, the notion of a remote solve option was introduced and subsequently evolved into a dedicated project within the SAPHIRE development team. A significant outcome of this initiative is SAPHSOLVE, an engine extracted from the SageRisk API designed specifically for remote solving capabilities. The ongoing project is nearing its culmination, marked by a series of discoveries that have brought undocumented aspects to light. Among these revelations is the intricacy of the input and output format for the SAPHSOLVE engine. This document serves the crucial purpose of meticulously delineating the precise formats for both input and output, as they form an indispensable foundation. The importance of documenting these formats cannot be overstated, as it is a pivotal step in facilitating rigorous testing and comparison. Whether it involves scrutinizing SAPHSOLVE results against those of the internal integrated solver or other external solvers, the ability to construct models or transform existing ones into a compatible SAPHSOLVE format is imperative. Chapter 1 offers a succinct introduction to both SAPHIRE and SAPHSOLVE, followed by Chapter 2 which outlines the roadmap for enhancing SAPHSOLVE. The core of this report is Chapter 3, which intricately elucidates the intricacies of the input and output file formats. To provide a tangible illustration of these formats, a rudimentary example has been compiled and is available in Appendix. SAPHSOLVE represents a novel external solving mechanism developed by the SAPHIRE team, although it has not yet reached the full spectrum of capabilities possessed by SAPHIRE's internal solver. However, the SAPHIRE team has set a comprehensive course for incorporating the functionalities of SAPHSOLVE. A comprehensive outlook on the future of SAPHSOLVE is expounded upon in Chapter 4.

97 MATHEMATICS AND COMPUTING↗

Rapid AI-based Dissection of Ashes using Raman and XRF Spectroscopy (RADAR-X)

Waste-to-energy (WTE) facilities incinerate ~35 million tons of municipal solid waste annually in the United States. The incineration process reduces the mass and the volume of the waste fraction by over 75 and 95%, respectively. The fraction left after incineration remains as ash residues and is referred to as WTE ash, compromising of bottom and fly ash. In the United States, ~10 million tons of WTE ashes are generated annually and predominantly landfilled because of the lack of secondary end-use pathways. This incurs a significant financial burden (landfilling costs) on U.S. WTE facilities and also results in the loss of materials to the landfill. The primary objective of this research is to understand better the elemental and mineralogical composition of WTE ashes from diverse origins and find composition dependent upcycling pathways for diverting these ashes from landfills. This primary objective was addressed through three research tasks –(Task I) An AI-led Multi-Modal Approach for Compositional Analysis, (Task II) Developing a Dissolution-Based Test for Real Time Analysis, and (Task III) Establishing composition-dependent end uses. The chemical composition of WTE ash is dependent on two factors, i.e., the input waste composition and the operational parameters of a WTE facility (combustion conditions). Amongst these two factors, the input waste composition will likely show spatial and temporal variation. As a result, the chemical composition of WTE ash will also fluctuate. To understand the spatial and temporal variation in WTE ash composition, in Task I, we collected 128 ash samples (62 bottom ash and 66 fly ash samples) from 11 WTE facilities located in 11 U.S. states and characterized them via X-ray Fluorescence, powder X-ray Diffraction, and Raman Spectroscopy. The findings from this extensive characterization work indicated that the key elements in WTE fly ashes are Ca, Cl (greater than 10 wt. %), Si, S, K, Zn ( between 1 and 10 wt. %), Mg, Al, P, Ti, Fe, Cu, Br, and Pb (between 0.1 and 1 wt. %). Similarly, the key elements in WTE bottom ash fraction finer than 45μm are Ca (greater than 10 wt. %), Mg, Al, Si, S, Cl, K, Ti, Fe, Zn (between 1 and 10 wt. %), P, V, Cr, Mn, Cu, Br, and Pb (between 0.1 and 1 wt. %). Here, we note that the dominant fraction of WTE bottom ash is the coarse fraction. The coarse WTE bottom ash fraction (rich in silicon) was not characterized in this study because of excessive grinding requirements and their unsuitability as a supplementary cementitious material due to their coarse nature. The elements in WTE bottom ashes are present as calcite, anhydrite, vaterite, hydroxyapatite, quartz, bassanite, gehlenite, akermanite, hydrocalumite, and portlandite. Similarly, the mineralogical species present in WTE fly ashes are calcium chloride hydroxide, halite, calcite, anhydrite, sylvite, hydrocalumite, vaterite, hannebachite, quartz, and bassanite. Temporal variation in ash composition may also result in significant fluctuations in chemical compositions. Therefore, a WTE facility may need to monitor the ash composition (elemental and mineralogical composition) in real time. In Task I, we evaluated the possibility of using a portable X-ray fluorescence (XRF) spectrometer to monitor the elemental composition in real-time. Specifically, we collected XRF data on identical specimens via a portable XRF spectrometer (low-end) and a lab-based benchtop XRF spectrometer (high-end). The collected data was used to train an A.I. algorithm (portable XRF data as an input and benchtop XRF data as an output) to predict accurate elemental composition using portable XRF data. Finally, we developed a 2-minute photobleaching protocol to monitor the mineralogical characteristics of WTE ashes via Raman spectroscopy. Overall, the activities in Task I improved our understanding of ash composition and developed techniques to monitor elemental and mineralogical composition in near real-time. Based on the findings of Task I, we find that WTE ashes exhibit wide variability in mineralogy. For ICP-based elemental analysis, all the mineralogical species in WTE ashes must be brought into solution. This is traditionally accomplished with acid digestion using a combination of multiple acids. However, acid digestion with multiple acids is time-consuming and often fails to ensure complete digestion of the ash matrix. To address this limitation, in Task II, we developed an alkali-fusion-based digestion protocol using a combination of lithium tetraborate, lithium metaborate, and their combinations as possible alkali fluxes for digesting WTE ashes entirely and rapidly. The validity of the developed method was evaluated on two standard ash specimens, i.e., SRM 1633c coal fly ash and BCR-176R incineration fly ash specimen. The findings suggest that the developed protocol can ensure complete digestion of elements such as Al, Ba, Ca, Cr, Cu, Mg, Mn, P, Sr, V, Zn, Be, K, and rare earth elements. The recent changes in the energy market towards renewables and increased metal recycling have resulted in reduced supplies of supplementary cementitious materials (coal fly ash and slag). Therefore, in Task III, we evaluated the possibility of employing WTE ashes as SCMs. As the chemical composition of WTE ashes varies temporally (on an hourly basis), there was also a need to develop tests that can evaluate the suitability of material to act as supplementary cementitious material rapidly, i.e., in a few minutes. Therefore, in Task II, we also developed a rapid test to assess the suitability of a material to act as an SCM in 5 minutes. This represents a significant advance over the state-of-the-art R 3 test, which takes ~144 hours. This test was initially validated on amorphous aluminosilicates, such as calcined clays, and could be extended to evaluate other industrial by-products, such as WTE ashes. In Task III, we evaluated the possibility of employing WTE ashes for two applications, i.e., as an SCM and a lime substitute for clay stabilization. The findings from Task I indicated that WTE ashes are enriched in chlorine and, therefore, cannot be used directly as an SCM due to corrosion-related risks and altered hydration kinetics. Accordingly, we developed an ash treatment protocol to reduce the solubility of chlorine-containing species in WTE ashes. The developed treatment protocol also immobilized lead in certain mineral forms. As a result of the treatment, WTE ashes can be used as SCMs without any corrosion or heavy metal leaching concerns. The second application examined in this study was clay stabilization. WTE ashes are calcium-rich and can be an adequate lime replacement for clay stabilization. Our findings reveal that the sum of the concentrations of Ca(OH) 2 and CaClOH controls the clay stabilization capability of WTE ashes. In summary, in this work, we evaluated the elemental and mineralogical characteristics of U.S. WTE ashes from diverse origins and developed tests to evaluate the chemical characteristics of these ashes in real time through a portable XRF and a benchtop Raman spectrometer. Based on the chemical characteristics of these ashes, we developed an ash treatment process to enable the use of WTE ashes as an SCM and also evaluated the possibility of employing these ashes for clay stabilization. Overall, the findings from this work enables the diversion of WTE ashes from landfills for multiple end-uses, i.e., as an SCM or a lime substitute for clay stabilization.

36 MATERIALS SCIENCE↗