Perturbative benchmark models for a dark shower search program
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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BETO 2021 Peer Review - Algal Biofuels Techno-Economic Analysis 1.3.5.200
The objective of NREL's Algal Biofuel Techno-Economic Analysis (TEA) project is to provide process modeling and analysis to support Algae Program activities, utilizing TEA models to relate key process parameters with overall economics for cultivation, processing, and conversion of algal biomass to fuels and coproducts. By quantifying economic implications of key process metrics, TEA models highlight the technical requirements to achieve future program cost goals as well as enabling a means to track progress towards these goals. This project provides high impact and relevance though generation of critical cost data tied to funded research, with our analyses subsequently exercised by BETO to guide program plans, FOA priorities, and other directives. This includes costs for both algal biomass production and downstream conversion, most notably to support BETO's fuel cost targets below $2.5/GGE by 2030. To mitigate a key risk/challenge in constraining our work to academic analyses rooted only in future projections, our work also seeks to provide near-term value to today's algae industry through frequent industry engagement, while maintaining close ties with other BETO collaborators. This project has made numerous accomplishments since the 2019 peer review, including a continued focus on opportunities for value-added products, with related analyses for new pathway opportunities to achieve BETO cost goals and notable State-of-Technology (SOT) improvements over prior cost benchmarks.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
ARM-Led Improvements Aerosols in Climate and Climate Models
The DOE ARM program has played a foundational role in efforts to quantify aerosol effects on climate, beginning with the early back-of-the-envelope estimates of direct radiative forcing by anthropogenic sulfate and biomass burning aerosol (Penner et al., 1994). In this chapter we review the role that ARM has played in subsequent detailed estimates based on physically-based representations of aerosols in climate models. The focus is on quantifying the direct and indirect effects of anthropogenic aerosol on the planetary energy balance. Only recently have other DOE programs applied the aerosol modeling capability to simulate the climate response to the radiative forcing.
aerosol↗
The importance of delayed neutron precursors in gamma dose calculations for activated primary heat exchanger components in the Molten Salt Breeder Reactor
The Molten Salt Reactor (MSR) Multiphysics Applications technical area in the Nuclear Energy Advanced Modeling and Simulation program has supported the development of 3D Monte Carlo models of the Molten Salt Breeder Reactor (MSBR) over the last couple of years. This MSBR model was previously run with the Shift Monte Carlo code to perform radiation shielding calculations in the reactor cell area. The MSBR is a 2250 MWth (1000 MWe) liquid-fueled molten salt reactor design developed at Oak Ridge National Laboratory in the 1970s. Determining the source terms from activated primary heat exchanger (HX) components is important because delayed and prompt neutron fluxes incident on these components affect the dose rate in the primary HX maintenance areas. This information can be used in the development of remote handling procedures required during shutdown for maintenance. A methodology has been developed and is proposed in this paper to quantify the activated source term from the primary HX components as a result of the movement of the delayed neutron precursors in flowing primary fuel salt through the primary HXs in the MSBR. The goal of this research is to evaluate the gamma dose rates in the maintenance hatches above the primary HX using the activated HX source terms. The study showed that the gamma dose rates are approximately two orders of magnitudes higher when accounting for the neutron activation from the movement of delayed neutron precursors through the HXs than when flowing fuel is not considered. Thus, the movement of delayed neutron precursors must be taken into account for accurately predicting the neutron activation of primary loop components.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Prospective estimation of organ dose in CT under tube current modulation
Purpose: Computed tomography (CT) has been widely used worldwide as a tool for medical diagnosis and imaging. However, despite its significant clinical benefits, CT radiation dose at the population level has become a subject of public attention and concern. In this light, optimizing radiation dose has become a core responsibility for the CT community. As a fundamental step to manage and optimize dose, it may be beneficial to have accurate and prospective knowledge about the radiation dose for an individual patient. In this study, the authors developed a framework to prospectively estimate organ dose for chest and abdominopelvic CT exams under tube current modulation (TCM). Methods: The organ dose is mainly dependent on two key factors: patient anatomy and irradiation field. A prediction process was developed to accurately model both factors. To model the anatomical diversity and complexity in the patient population, the authors used a previously developed library of computational phantoms with broad distributions of sizes, ages, and genders. A selected clinical patient, represented by a computational phantom in the study, was optimally matched with another computational phantom in the library to obtain a representation of the patient’s anatomy. To model the irradiation field, a previously validated Monte Carlo program was used to model CT scanner systems. The tube current profiles were modeled using a ray-tracing program as previously reported that theoretically emulated the variability of modulation profiles from major CT machine manufacturers Li et al., [Phys. Med. Biol. 59, 4525–4548 (2014)]. The prediction of organ dose was achieved using the following process: (1) CTDI{sub vol}-normalized-organ dose coefficients (h{sub organ}) for fixed tube current were first estimated as the prediction basis for the computational phantoms; (2) each computation phantom, regarded as a clinical patient, was optimally matched with one computational phantom in the library; (3) to account for the effect of the TCM scheme, a weighted organ-specific CTDI{sub vol} [denoted as (CTDI{sub vol}){sub organ,weighted}] was computed for each organ based on the TCM profile and the anatomy of the “matched” phantom; (4) the organ dose was predicted by multiplying the weighted organ-specific CTDI{sub vol} with the organ dose coefficients (h{sub organ}). To quantify the prediction accuracy, each predicted organ dose was compared with the corresponding organ dose simulated from the Monte Carlo program with the TCM profile explicitly modeled. Results: The predicted organ dose showed good agreements with the simulated organ dose across all organs and modulation profiles. The average percentage error in organ dose estimation was generally within 20% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions. For an average CTDI{sub vol} of a CT exam of 10 mGy, the average error at full modulation strength (α = 1) across all organs was 0.91 mGy for chest exams, and 0.82 mGy for abdominopelvic exams. Conclusions: This study developed a quantitative model to predict organ dose for clinical chest and abdominopelvic scans. Such information may aid in the design of optimized CT protocols in relation to a targeted level of image quality.
60 APPLIED LIFE SCIENCES↗
Assessment of the MAMMOTH and PRONGHORN Pebble Bed Reactor Modeling Capabilities for the HTR-PM Design
This assessment explores the current analysis methodologies of various external and MOOSE-based tools available at the Idaho National Laboratory to model pebble bed reactor multiphysics phenomena. The study involves three MOOSE-based, coupled codes: 1) MAMMOTH for reactor physics, 2) Rattlesnake for neutron transport and 3) Pronghorn for thermal fluids and strongly coupled conjugate heat transfer. These advanced tools are being developed under DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program (NEAMS). They currently contain a collection of advanced modeling capabilities that allow high-fidelity simulations of advanced reactor concepts including gas and fluoride-salt cooled pebble bed reactors. Software development of these tools follows NQA-1 standards ensuring software quality that many of the currently deployed legacy codes lack. In this work, the MAMMOTH Pronghorn tools are compared to the legacy codes PEBBED-THERMIX-KONVEK. The external codes in use are LAMMPS for pebble mechanics and Serpent for cross section preparation. The coupling under MOOSE enables significant flexibility for modern engineering tools since MOOSE applications can be seamlessly coupled with various levels of resolution. This report focuses on low-resolution (r-z) and midresolution (3-D) homogenized geometries. The high-resolution Pebble Tracking Transport solution is not pursued herein and is postponed to future work. The results from this assessment show that the new MOOSE-based tools compare well with the results from legacy tools (r-z) and produce reasonable accuracy limited by the methods in the legacy tools. In the 3-D studies, the PJFNK-SPH methodology available in MAMMOTH allows the reproduction of Monte Carlo results with a transport-corrected diffusion solution. This has implications for the coupled solutions since without the SPH correction the temperature coefficient of reactivity is under-predicted and leads to lower temperature feedback and a significantly higher eigenvalue showing a difference of 2000 pcm.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Modeling Enhancements, Cross-Section Generation Updates, and Benchmarking with Shift
This technical report documents the modeling enhancements, cross-section generation updates, and bench marking with the Shift Monte Carlo code performed under the US Department of Energy Nuclear Energy Advanced Modeling and Simulation Program in FY 2024. The work performed included several modeling enhancements, such as integration of cross-section generation in Titan and the ability to produce microscopic multigroup cross sections with Shift. Benchmarking of the cross sections produced by Shift and the two-step workflow with Griffin was performed for three problems: the Advanced Breeder Test Reactor, a generic pebble bed reactor, and a TRISO heat pipe microreactor. Comparisons of results from these benchmark problems were done with Serpent, OpenMC, and Griffin. These enhancements provide a robust foundation for applying Shift for both reference and two-step neutronics analysis for advanced reactor simulation.
97 MATHEMATICS AND COMPUTING↗
Python Measurement-Informed Modelling Method (PythonMIMM) v1.02
This Python program implements the calculations for electrical energy efficiency and electrical losses in the paper "Energy and power quality measurement for electrical distribution in AC and DC microgrid buildings" (https://www.sciencedirect.com/science/article/abs/pii/S0306261921015658). The inputs are metered voltage, current, or power data of meters located throughout the DC system. In the absence of metered data, the user must input some other information about the building such as the types of power converters or wire lengths. The program will build a loss model of the DC system based on metered data and electrical information. It will also generate an equivalent AC system and determine the losses and efficiency.
Gerber, Daniel [Lawrence Berkeley National Laborat↗
Small Reactors in Microgrids: Technology Modeling and Selection (Net-Zero Microgrid Program Project Report)
This report demonstrates the capabilities of the net-zero microgrid (NZM) Xendee platform for modeling an SR module with electricity, heat extraction and thermal storage in microgrids configurations. The model effectively captures the most important technical and economic considerations for SR technology specific analysis: cost and operational characteristics of SR technology and financial costs and incentives. The model can analyze multiple scenarios to establish metrics for cost-competitive and zero-carbon microgrids connected to the grid or completely isolated. The model is fully integrated within the Xendee platform for modeling and analysis of clean energy microgrids with storage and generation from renewable energy sources. The model captures the capabilities, constraints, and nuances of SR by incorporating parameters related to plant economics, design efficiency and performance, plant operation and component and fuel lifespan. The cost and operational parameters modeled in the SR module are specific to the technology selected for integration in the microgrid. Cost parameters recognize advanced nuclear technology for modular production and installation based on economies of scale from factory manufacture and related commissioning, and cost reduction through technology maturation—first-of-a-kind (FOAK) and nth-of-a-Kind (NOAK). The cost parameters include installation, operations and maintenance (O&M), fuel refueling cycle, and reactor life. Installation cost reflects economies of scale due to unit sizing at scale and colocation. O&M economies of scale for both fixed- and variable-cost fuel life-cycle costs are incurred at every refueling interval, with separate front- and back-end fuel costs, as well as waste-handling and disposition costs. This report investigates key characteristics of different SR technologies suitable for microgrid applications, including design principles, sizing, coolant properties, temperature ratings, fuel structures, and life-cycle considerations. This also includes fuel technologies applicable to these SR systems, alongside strategies for nuclear-waste and spent-fuel management and approaches to address safety, security, and proliferation challenges. Four primary groups of SR technologies are examined: water-cooled, liquid-metal-cooled, high-temperature gas-cooled, and molten-salt-cooled systems. In this report, an initial guideline for technology selection is established, aligning the characteristics of the technologies with the requirements of microgrids. The selection of technology in a microgrid is influenced by various factors, including financial capacity, location and accessibility, demand type and characteristics, reliability and resilience requirements, area constraints, and the lifespan of the microgrid. The types of electrical and non-electrical applications within the microgrid also play a significant role in technology selection. The characteristics of SRs, such as their smaller size, modularity, transportability, long refueling interval, improved safety features, ability to operate in autonomous or semi-autonomous mode, and provision of high-grade heat, are particularly appealing for microgrids. Furthermore, a list of considerations for implementing SRs in microgrids is outlined. The SR model is created to be continuously improved with the acquisition of actual data on investment and operational costs, experience with supply chains, production at scale, and field deployments. In the near term, performance data on applications in microgrids will become available from lessons learned from laboratory tests, such as those planned for the Microreactor Applications Research Validation and Evaluation Project (MARVEL), led by Idaho National Laboratory (INL). The SR model incorporates scenario data and known SR design specifications, enabling technoeconomic analysis for SR deployment in microgrids. It specifically considers the distinctive attributes of SRs as generators in technoeconomic studies. SRs can be modeled and analyzed with generation from renewable-energy sources, energy storage, and flexible loads over a range of functionality and applications. This offers a comprehensive tool for feasibility studies, scenario development, and sensitivity analysis for “what-if” consideration of any range of assumptions about SRs in microgrids and other aggregations of distributed-energy resources, including virtual power plants.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NEAMS Burnup Extension Accomplishments and Remaining Modeling Gaps
The economic viability of light-water reactors (LWRs) in the United States is declining in heavily subsidized markets, and as a result, the nuclear industry is looking for opportunities to enhance the economic competitiveness of nuclear power. This is not a foreign concept to the nuclear industry: in the mid-2000s, the nuclear industry set out to achieve zero fuel failures by 2010. The goal in this effort was to drive down the cost of reactor shut down by replacing a pin or bundle in response to fuel rod failure. 2010 brought about the initiative to deliver the nuclear promise to reduce operating cost by 30% to improve nuclear energy’s economic competitiveness before 2020. The emergence of accident-tolerant fuel also offers the nuclear industry an opportunity to build on these past successes and deliver affordable, clean energy. Accident-tolerant fuel has been shown to provide superior performance compared to traditional Zircaloy/UO2 fuel concepts, offering the unique ability to remove operational limitations that inhibit the economic viability of nuclear power. This has led the industry to begin building a technical case to extend the peak rod average burnup beyond 62 GWd/tU to extend pressurized water reactor cycle lengths to 24 months and to develop more efficient boiling water reactor core designs. The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program mission is to develop advanced modeling and simulation tools and capabilities to accelerate the deployment of advanced nuclear energy technologies. The primary safety concern inhibiting the nuclear industry from extending burnup is related to high-burnup fuel fragmentation, relocation, and dispersal. Therefore, the NEAMS program developed a targeted 5-year plan to support the industry’s efforts to extend burnup. This milestone report summarizes the 5-year plan that was enacted in FY20, followed by a discussion of the ongoing activates required to fulfill the 5-year plan, as well as the approach to address the current modeling gaps. Additionally, an LWR stakeholder meeting was held to communicate work performed in the NEAMS program over the past three years, to assess the LWR community’s perspective on the impact of the program, and to identify remaining significant gaps in the NEAMS suite of capabilities. This engagement will be documented by the Electric Power Research Institute and used by NEAMS to redirect current LWR scope as needed and to develop the next phase for LWR research and development.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Fluid-Structure Interaction of Deforming Porous Media
Sandia National Laboratories (SNL) and the Procter and Gamble Company (P&G) collaborated to develop a computational tool that predicts the in-use performance of consumer good products based on specific loading, geometries, materials, and boundary conditions. This computational tool is particularly useful in exploring the consumer-product interface and product performance. The benefit to P&G was many-fold, as the numerous project-tasks that were funded under this agreement led to advanced analysis software that allowed P&G to improve the performance and manufacturing of many of their products across several business units. The benefit to SNL was many-fold as well, including improved reduced-order models for thin-region dynamics (used for customers through DSA, NW, and EC PMUs), improved computational mechanics capability for capillary hydrodynamics, porous flow, structural mechanics, and more. Example applications of these improved capabilities at SNL include, but are not limited to, encapsulation, welding, soldering, and brazing models for NW, interface sliding models for DoD SPP programs, and porous-elastic subsidence modeling for energy and climate applications. Moreover, many current code developers on the ASC program’s SIERRA applications gained valuable skills working on this CRADA.
97 MATHEMATICS AND COMPUTING↗
Meso-Scale Fuel Performance Modeling using the MARMOT Code
The in-pile behavior of light-water-reactor (LWR) fuels is governed by the physics from various time and spatial scales. Accordingly, multi-scale modeling and simulation are needed to accurately predict the fuel performance at the engineering scale. To improve the traditional fuel performance modeling, the Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program targets at developing multi-scale, multiphysics modeling tools for in-pile fuel behavior prediction under various operating or accident scenarios. In traditional fuel performance modeling, the history of fuel is represented by a single parameter, fuel burn-up. Burn-up measures the energy that has been extracted from fuels. However, it is not an adequate measure of fuel history as it ignores the flux effect, which is critical for the irradiation-induced microstructural evolution in fuels. Moreover, the traditional fuel performance models are usually fitted to experimental data. Their capabilities of being extrapolated to new operating conditions and being extended to new types of fuels are strongly limited by the empirical or semi-empirical nature. To improve the burn-up based models, a microstructure based fuel approach, the MOOSE-BISON-MARMOT (MBM) tool-kit, is being developed under the fuel product line (FPL) of the NEAMS program for predictive fuel performance modeling. In the MBM approach, the evolution of fuel microstructure and changes in fuel properties are described by the MARMOT code. The transient fuel properties obtained from MARMOT are then fed into the BISON code for engineering scale fuel performance modeling. Both BISON and MARMOT are developed within the MOOSE framework, which was developed at Idaho National Laboratory. In this summary, the development and the capabilities of the MARMOT code will be introduced. In the past few years, several materials models have been developed including: (1) a grain growth model that describes the grain size evolution as a function of time, temperature and fuel porosity, considering the effects of impurity and porosity dragging and anisotropic grain boundary energy, (2) a fission gas release model that describes the fission gas diffusion in grain interior, fission gas bubble formation in grain interior and at grain boundaries, and fission gas release to the fuel-cladding gap, (3) a fracture model that describes the fracture initiation and propagation in grain interior and along grain boundaries, and (4) a thermal conductivity model that describes the change in thermal conductivity due to grain growth, gas bubble formation, fracture and radiation damage. Several other models are also being developed in MARMOT for hydride formation in Zr-based cladding, radiation damage and grain size subdivision. In most cases, these materials models are coupled with each other. For instance, to accurate predict the transient thermal conductivity, information on grain size, fission gas density, porosity and fracture is required. Further development is on going to improve all these models. These models are developed primarily for UO{sub 2} fuels used in LWRs. They can be extended to other fuels with possibly new development. All models in MARMOT will be rigorously verified and validated before being applied for fuel performance modeling. A version of MARMOT was recently released in September 2015 with an assessment report. (authors)
36 MATERIALS SCIENCE↗
Pressurizer dynamic model and emulated programmable logic controllers for nuclear power plants cybersecurity investigations
This work demonstrates the functionality of the pressurizer using a fast-running three regions, non-equilibrium model and control programs of emulated PLCs. The state variables from an integrated model of primary loop in a representative PWR plant are communicated to the pressurizer’s emulated PLCs using a synchronized data transfer function. In turn, the PLCs communicate back instructions to the pressurizer model to adjust the pressure and water level to remain within preprogramed setpoints. Pressurizer model simultaneously solves the coupled mass and energy conservation equations in the saturated vapor and saturated and subcooled liquid regions using fixed step solver. Results demonstrate the response of the pressurizer model linked to an emulated pressure and water level PLCs in a simulated transient involving surge-in and surge-out events. The 50 ms response delay time for the emulated PLC insignificantly affects operation and predictions of the pressurizer model.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
The SONATA data format for efficient description of large-scale network models
Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility.
59 BASIC BIOLOGICAL SCIENCES↗
Integrating Concentrating Solar Power Technologies into the Hybrid Optimization and Performance Platform (HOPP)
As the world increases renewable energy deployment, there is an increasing interest in hybridizing various generation and storage technologies to maximize net benefit to the developer and/or off-taker. A particularly interesting combination of renewable technologies is concentrating solar power (CSP) with thermal energy storage (TES), photovoltaics (PV), and electrochemical battery energy storage (BESS). Due to the system complexity of CSP technology, it is difficult to evaluate the technological and financial performance of a CSP-PV hybrid system without detailed modeling of annual operations. To address this challenge, we have developed a modeling framework for evaluating the performance and financial viability of CSP systems hybridized with PV and battery technologies. This modeling effort incorporates CSP tower and trough systems into an existing modeling tool recently developed by NREL referred to as the Hybrid Optimization and Performance Platform (HOPP). This report outlines the modeling methodology as well as preliminary results from example case studies conducted using the model. The methodology describes: (i) the integration of CSP tower and troughs into HOPP using python interfaces to access System Advisor Model (SAM) underlining technology models, (ii) the mathematical formulation of the mixed integer linear program dispatch optimization model which optimizes operations of storage asset to either maximize system revenue or minimize operating cost while load following, (iii) the design analysis methods implemented within HOPP, and (iv) simulation clustering for the purposes of reducing computational expense. We exercise the model using a case study of a future scenario where we assume (i) CSP and PV technologies achieve the 2030 cost targets provided by the Solar Energy Technologies Office (SETO), (ii) battery costs reduce to the 2030 mid cost projection presented by NREL. Lastly, (iii) electricity prices for southern California in 2030 are provided by NREL's Cambium database, and (iv) a capacity payment of $150/kW-yr based on the system capacity factor during the to 100 net-load hours.
14 SOLAR ENERGY↗
MultiSector Dynamics: 2023 Inaugural Workshop Report
Preface The MultiSector Dynamics (MSD) Community of Practice (CoP) hosted an inaugural workshop on October 3-5, 2023 at the University of California, Davis, to bring together members of the MSD community of practice to advance understanding of the co-evolution of human and natural systems, and to build the next generation of tools that bridge sectors, scales, and systems to realize a more resilient and equitable future. The theme of the workshop was "Advancing Complex Adaptive Human-Earth Systems Science in a World of Interconnected Risks". This document outlines the motivation for the workshop, its goals and objectives, the application process, the agenda, overviews of the training sessions offered to the workshop participants and a summary of each breakout session. The MSD workshop report further discusses the feedback from workshop participants and presents some reflections and next steps. The MSD Workshop organizers thank the DOE Office of Science, Earth and Environmental System Modeling, MultiSector Dynamics program area for financial support of its activities through the Integrated Multisector Multiscale Modeling (IM3) project. For more information related to the broader DOE MultiSector Dynamics Program please see https://climatemodeling.science.energy.gov/program-area/multisector-dynamics. D.L.M. and C.M.B. acknowledge support from the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory (ORNL), managed by UT-Battelle, LLC, for the US Department of Energy (DOE). Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither theUnited States Government nor any agency thereof, nor Battelle Memorial Institute, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, complete- ness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial products, process, or service by trade name,trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. Pacific Northwest National Laboratory operated by Battelle for the United States Department of Energy Available from:Office of Scientific and Technical Information http://www.OSTI.gov multisectordynamics.org This work is made available under the terms of the Creative Commons Attribution- NonCommercial 4.0 International (CC BY-NC 4.0) https://creativecommons.org/licenses/by-nc/4 Suggested citation: Monier, E., Reed, P.M., Vernon, C.R., Hadjimichael, A., Brelsford, C.M., Burleyson, C.B., Dyreson, A.R., Fletcher, S.M., Giang, A., Gupta, R.S., Jackson, N.D., Jones, A.D., Lamontagne, J.R., McCollum, D.L., Morris, J.F., Moss, R.H., Peng, W., Saari, R.K., Srikrishnan, V., Szinai, J.K., Yoon, J. (2024) MultiSector Dynamics: 2023 Inaugural Workshop Report. MSD-LIVE Data Repository. doi:10.57931/2371710.
Monier, Erwan↗
Integrated Experimental and Modeling Studies of Mineral Carbonation as a Mechanism for Permanent Carbon Sequestration in Mafic/Ultramafic Rocks
A program of laboratory experiments, modeling and fieldwork was carried out at Yale University, University of Maryland, and University of Hawai‘i, under a DOE Award (DE-FE0004375) to study mineral carbonation as a practical method of geologic carbon sequestration. Mineral carbonation, also called carbon mineralization, is the conversion of (fluid) carbon dioxide into (solid) carbonate minerals in rocks, by way of naturally occurring chemical reactions. Mafic and ultramafic rocks, such as volcanic basalt, are natural candidates for carbonation, because the magnesium and iron silicate minerals in these rocks react with brines of dissolved carbon dioxide to form carbonate minerals. By trapping carbon dioxide (CO 2 ) underground as a constituent of solid rock, carbonation of natural basalt formations would be a secure method of sequestering CO 2 captured at power plants in efforts to mitigate climate change. Geochemical laboratory experiments at Yale, carried out in a batch reactor at 200°C and 150 bar (15 MPa), studied carbonation of the olivine mineral forsterite (Mg 2 SiO 4 ) reacting with CO 2 brines in the form of sodium bicarbonate (NaHCO 3 ) solutions. The main carbonation product in these reactions is the carbonate mineral magnesite (MgCO 3 ). A series of 32 runs varied the reaction time, the reactive surface area of olivine grains and powders, the concentration of the reacting fluid, and the starting ratio of fluid to olivine mass. These experiments were the first to study the rate of olivine carbonation under passive conditions approaching equilibrium. The results show that, in a simple batch reaction, olivine carbonation is fastest during the first 24 hours and then slows significantly and even reverses. A natural measure of the extent of carbonation is a quantity called the carbonation fraction, which compares the amount of carbon removed from solution, during a run, to the maximum amount that could have been removed if the olivine initially present had fully dissolved and the cations released had subsequently precipitated in carbonate minerals. The carbonation fractions observed in batch experiments with olivine grains and powders varied significantly, from less than 0.01 (1%) to more than 0.5 (50%). Over time, the carbonation fractions reached an upper limit after about 24 to 72 hours of reaction, then stayed constant or decreased. The peak Final Scientific/Technical Report DE-FE0004275 | Mineral Carbonation | 4 coincided with the appearance of secondary magnesium-bearing silicate minerals, whose formation competes for magnesium ions in solution and can even promote conditions that dissolve magnesite. The highest carbonation fractions resulted from experiments with low ratios of concentrated solution to olivine, during which amorphous silica spheres or meshes formed, instead of secondary silicate minerals. The highest carbonation fractions appear to result from competing effects. Precipitation of silica layers on olivine reduces the reactive surface area and, thus, the rate of olivine dissolution (which ultimately limits the carbonation rate), but these same silica layers can also inhibit the formation of secondary silicate minerals that consume magnesite formed in earlier stages of carbonation. Simulation of these experiments with simple geochemical models using the software program EQ3/6 reproduces the general trends observed—especially the results for the carbonation fraction in short-run experiments. Although further experimentation and better models are needed, this study nevertheless provides a framework for understanding the optimal conditions for sequestering carbon dioxide by reacting CO 2 -bearing fluids with rocks containing olivine minerals. A series of experiments at the Rock Physics Laboratory at the University of Maryland studied the carbonation process during deformation of thermally cracked olivine-rich rock samples (dunite) saturated with CO 2 brines of varying compositions. A goal of these geomechanical experiments was to see if flow and deformation processes, which accompany natural carbonation reactions in underground settings, work to enhance or inhibit the reactions. The experiments involved hydrostatic compaction, followed by deformation at a constant rate of strain. Sample permeability was monitored during the reactions. Comparison of the samples’ volume changes to their axial strains (shortening) during deformation indicates that samples reacted with CO 2 -saturated brines accommodate more axial compaction, before the onset of dilation (a swelling that precedes rock failure), than samples reacted with distilled water. Analyses of the reacted samples with scanning electron microscope (SEM) images indicate, first, that dissolution of olivine occurring in the initial stages of carbonation can provide pathways to fluid flow that sustain the reaction, and, second, that carbonate minerals precipitated along existing fractures in the rocks may serve as asperities, or roughness on a crack’s surface that restricts its closure. Final Scientific/Technical Report DE-FE0004275 | Mineral Carbonation | 5 In a related study undertaken by one of the principal investigators as a spin-off of the main project, a simple model of (magnesite) crystal growth in the pore space of basalts undergoing carbonation was developed. The model suggests that, under a carefully controlled program of CO 2 injection, carbonate mineral growth can harden the rock formation against earthquakes that might otherwise be induced by the injection of large fluid volumes (Yarushina and Bercovici, 2013). The overall conclusion of the research project is that mineral carbonation of underground mafic and ultramafic rock formations is a viable candidate for long-term sequestration of man-made carbon dioxide. No results obtained during the project indicate that the method is inherently intractable in its implementation; moreover, enormous volumes of basalt near Earth’s surface are candidate locations for large-scale injection programs. The geochemical experiments do indicate, however, that there will be significant engineering challenges in maintaining high rates of carbonation, by delaying the onset of chemical conditions that promote formation of secondary silicate minerals and, therefore, slow down, or even reverse, the carbonation process. It remains an open question as to whether carbonation processes can be sustained for many years in an engineered system operating on a large scale—a scale capable of accommodating millions of tons of CO 2 annually. The development of realistic theoretical models that can systematically describe the combined effects of reactive flow, precipitation and geomechanical deformation is a major barrier to further understanding of the practical viability of mineral carbonation as large-scale method of carbon sequestration.
58 GEOSCIENCES↗
Cost-Optimal Pathways to 75% Fuel Reduction in Remote Alaskan Villages: Preprint
There are thousands of isolated, diesel-powered microgrids that deliver energy to remote communities around the world at very high energy costs. The Remote Communities Renewable Energy program aims to help these communities reduce their fuel consumption and lower their energy costs through the use of high penetration renewable energy. As part of this program, the REopt modeling platform for energy system integration and optimization was used to analyze cost-optimal pathways toward achieving a combined 75% reduction in diesel fuel and fuel oil consumption in a select Alaskan village. In addition to the existing diesel generator and fuel oil heating technologies, the model was able to select from among wind, battery storage, and dispatchable electric heaters to meet the electrical and thermal loads. The model results indicate that while 75% fuel reduction appears to be technically feasible it may not be economically viable at this time. When the fuel reduction target was relaxed, the results indicate that by installing high-penetration renewable energy, the community could lower their energy costs by 21% while still reducing their fuel consumption by 54%.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗