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AmeriFlux FLUXNET-1F US-OPE Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-OPE Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3). This is the FLUXNET version of the carbon flux data for the site US-OPE Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) produced by applying the standard ONEFlux (1F) software. Site Description - The Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) site is located at the Beltsville Agricultural Research Center in Prince George's County, MD, and consists of a 22-ha production field, with an adjacent riparian wetland and first-order stream. Scientists from several U.S. Federal agencies, universities (foreign and domestic), and private industry have conducted multidisciplinary research at this location since 1998.

Alfieri, Joe [USDA-ARS Hydrology and Remote Sensin↗

Perspectives on future research directions in green manufacturing for discrete products

With the increasing concern due to climate change caused by a higher atmospheric concentration of CO 2 and other greenhouse gases, reducing environmental impact is becoming more important for every part of society. Manufacturing is responsible for a significant amount of energy/material consumption and environmental burden and, therefore, has a great opportunity to reduce its impact through green manufacturing. Green manufacturing presents opportunities across the manufacturing enterprise to increase the efficient usage of energy and material resources. These opportunities include designing products to consume fewer materials and energy during manufacturing and use, incorporating more efficient manufacturing processes, streamlining and optimizing manufacturing schedules and plans, and circularizing products. The goal of this paper will be to provide a perspective from the authors on the opportunities that exist within green manufacturing for discrete products through a review of pertinent topics and future directions. The paper will focus on processes, manufacturing equipment, manufacturing systems, recovering value at a product’s end-of-life, and additional thoughts that include metrics and indicators, techno-economic assessment, and a discussion of efficiency and effectiveness. Key findings from this review include a need for social indicators and renewable energy considerations in scheduling and process planning, integrating Industry 4.0 into circular economy along with social and institutional dimensions, consistency in the ability to measure and conceptualize metrics and indicators, a detailed evaluation of the life cycle impacts and cost of Addit Manuf, and more human and environment-oriented considerations for smart manufacturing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Investigation of the background in coherent $J/\psi$ production at the EIC

Understanding fundamental properties of nucleons and nuclei are among the most important scientific goals of the next-generation machine, the Electron-Ion Collider (EIC). With the unprecedented versatility provided by the EIC, it will provide answers to many standing puzzles and open questions in modern nuclear physics. One of the golden measurements at the EIC is coherent vector meson production in electron-nucleus (eA) scattering in order to obtain the spatial gluon density distribution in heavy nuclei. This requires the experiment to overcome an overwhelmingly large background arising from the incoherent diffractive production, where the nucleus mostly breaks up into fragments of particles in the far-forward direction close to the hadron beam rapidity. In this report, we systematically study the rejection of incoherent J/\psi J / ψ production by vetoing products from the nuclear breakup - protons, neutrons, and photons, which is modeled with the BeAGLE event generator and the most up-to-date EIC Far-forward Interaction Region design.

Chang, Wan↗

Micropulse Lidar Cloud Mask (MPLCMASK) Value-Added Product for the Fast-Switching Polarized Micropulse Lidar Technical Report

Lidar backscattered signal is a useful tool for identifying vertical cloud structure in the atmosphere in optically thin clouds. Cloud boundaries derived from lidar signals are a necessary input for popular ARM data products, such as the Active Remote Sensing of Clouds (ARSCL) product. An operational cloud boundary algorithm (Wang and Sassen 2001) has been implemented for use with the ARM Micropulse Lidar (MPL) systems. In addition to retrieving cloud boundaries above 500 m, the value-added product (VAP) named Micropulse Lidar Cloud Mask (MPLCMASK) applies lidar-specific corrections (i.e., range-square, background, deadtime, and overlap) as described in Campbell et al. (2002) to the measured backscattered lidar. Depolarization ratio is computed using the methodology developed by Flynn et al. (2007) for polarization-capable MPL systems. The cloud boundaries output from MPLCMASK will be the primary lidar cloud mask for input to the ARSCL product and will be applied to all MPL systems, including historical data sets.

54 ENVIRONMENTAL SCIENCES↗

Impacts of the Addition of Sodium Reactor Experiment (SRE) and DR-3 Fuel from H-Canyon to Tank 40 on Acid Stoichiometry and Hydrogen Production

H-Canyon plans to discard Sodium Reactor Experiment (SRE) material that is currently stored in Tanks 16.3 and 16.4. Savannah River Remediation (SRR) determined that a portion of the SRE material can be added to Sludge Batch 9 (SB9) in Tank 40 and the remainder will be added to Sludge Batch 10 (SB10) that is currently being prepared in Tank 51. A processing flowsheet for both the nitric-formic acid flowsheet and the nitric-glycolic acid flowsheet were previously developed for SB9 sludge-only and coupled operation with the Actinide Removal Process – Modular Caustic Side Solvent Extraction Unit (ARP-MCU) and the Salt Waste Processing Facility (SWPF). Due to the compositional change in Tank 40 after the addition of SRE material, it is necessary to determine the influence on the acid stoichiometry operating window and hydrogen production for SB9 processing. An assessment was completed to address the influence of an addition of SRE and DR-3 Fuel from H-Canyon on the chemistry of Tank 40, the defined acid stoichiometry window (with and without SWPF streams) for the nitric-formic and nitric-glycolic acid flowsheets, and the resulting influence of the hydrogen production. Hydrogen production during the SRAT/SME cycles consists of thermolytic, radiolytic, and catalytic hydrogen. For the nitric-formic acid flowsheet, catalytic hydrogen dominates the hydrogen production during DWPF operation mode for the SRAT and SME vessels. This report was written to summarize that assessment. No SRNL testing is needed prior to adding up to 7,100 additional gallons of SRE and DR-3 Fuel from H-Canyon to Tank 40. Also, the addition of SRE will not exceed the Shielded Cells reported values for catalytic hydrogen for either the nitric-formic acid flowsheet (Technical Safety Requirement (TSR) limit of 0.15 lb/h) or the nitric-glycolic acid flowsheet (TSR limit 0.024 lb/h). The addition of the ARP stream from SWPF and the use of the nitric-glycolic acid flowsheet are both expected to decrease hydrogen generation, leading to a larger safety margin in the CPC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Resource Assessment for Hydrogen Production

This analysis was conducted in support of the U.S. Department of Energy's H2@Scale initiative, and this report examines the resources required to meet demand for an additional 10 million metric tonnes (MMT) of hydrogen in 2040. The technical potential of hydrogen production from fossil, nuclear, and renewable energy resources is presented. Updated maps describe the geographical distribution of hydrogen production potential from renewable energy resources. The results conclude that the technical resource availability of domestic energy resources is sufficient to meet an additional 10 MMT of hydrogen demand in 2040, without placing significant pressure on existing resources. While this level of hydrogen demand could result in a significant increase in renewable energy consumption, in particular, the technical potential of each resource is estimated to be sufficient to meet the demand. Future research, to enable the large-scale integration of hydrogen in the U.S. energy and other sectors, will include analyzing the geographic distribution of resources in relation to hydrogen demand for a variety of applications. Additional techno-economic analysis is also needed to understand the economic potential of hydrogen in other industries, beyond transportation; such analysis is currently being undertaken by a multi-lab project initiated by DOE in 2016. Finally, information from techno-economic analyses should be used to continually update and inform R&D targets for energy production, hydrogen production, and hydrogen utilization technologies.

08 HYDROGEN↗

Dissolution of Additively Manufactured Mo Disks and Structures for Accelerator Based Production of Mo-99

The press-and-sinter approach for production of Mo targets has been successfully tested and demonstrated. The main advantage of this process is that it uses readily available technology and tools that have been tuned for production of various metal and metal oxide targets. However, certain target design specifications, such as dimensional accuracy of the diameter and thickness of the disks, are required for proper fit into a target holder and therefore place strict tolerances on sintered Mo disks intended for accelerator production. Furthermore, having a target composed of multiple disks poses certain challenges for post-irradiation processing, where there is a potential for spillage of individual disks during the manipulation for dissolution inside a processing hot cell. Additive manufacturing (AM), also referred to as 3D printing, provides capabilities to design and build a single-piece Mo target that provides the opportunity for better geometry for optimized production of Mo-99, improved cooling capability, and safer post-irradiation handling. A drawback of AM Mo structures is roughness of finished surfaces, which could reduce the effectiveness of gas cooling systems. Process development for AM Mo structures using selective laser melting is described in work by Gibson and Lowden. For post-irradiation processing, it is important to look at the dissolution behavior of AM Mo structures in comparison to readily dissolved press-and-sinter Mo targets. The dissolution behavior of press-and-sinter targets has been well documented in our previous reports. In this report, we discuss results of dissolution experiments conducted with AM Mo disks and structures (provided by Oak Ridge National Laboratory [ORNL]) in 50% hydrogen peroxide (H 2 O 2 ).

36 MATERIALS SCIENCE↗

A Multi-Instrument Cloud Condensation Nuclei Spectrum Product (Final Technical Report)

A wealth of observational data exists on the characteristics of atmospheric particulate matter, over multiple years, at the DOE ARM Southern Great Plains (SGP) Central Facility site. This site is located in a region of the country that frequently experiences weather extremes, and that is removed from many local sources of pollution but is affected by transported smoke, dust, and urban emissions. The relationships between particulate matter, cloud formation and evolution, and precipitation are therefore of strong interest, and are being explored via modeling on a variety of scales. These models require as input detailed information on the characteristics of particles capable of serving as the nuclei for cloud formation. Sufficient data exist to be able to put together a picture of the nature of the total aerosol and the cloud condensation nuclei (CCN) subset, and their variability, through merged data products. This study was aimed at exploiting the multiple measurement types at SGP to develop the first such multi-year estimates. Further, the resulting data were analyzed to understand temporal patterns ranging from hourly to seasonal, thereby gaining insights into the particle sources affecting the atmosphere in this region. DOE-funded datasets that were analyzed in this study include total particle number concentrations, submicron aerosol scattering coefficients, dry aerosol size distributions, and more recently, time-resolved submicron aerosol chemical composition. Data are also available for the number concentrations of particles that are activated in a cloud condensation nucleus instrument at a series of setpoint supersaturations, providing direct observations of the number concentrations of “CCN”. This variable is the quantity that is generally desired for inclusion in numerical models that seek to represent and predict the impacts of varying aerosol characteristics on the formation and microphysical properties of clouds. One limitation of the use of direct CCN observations is that they are not available for supersaturations larger than about 1%, which is insufficient for deep convection and may be insufficient even for shallow convection, depending on the nature of the available CCN and the dynamics of the cloud. We developed a data-based approach to representing the full aerosol size spectrum with size-dependent hygroscopicity, and used this to extrapolate CCN spectra beyond the limited measurements. Five years of SGP aerosol data (2009 -2013) were analyzed. As a side product of our work, we identified and communicated several previously-unflagged data quality issues. The resulting merged aerosol distributions, along with fits for seasonal averages, were published and submitted to the ARM archive as a special value-added product (VAP; submitted as a PI product). CCN spectra were computed for the same data period and will similarly be published and submitted to the archive for use by the community. We also note that our methodologies and findings have been discussed at several Joint ARM User Facility/Atmospheric System Research (ASR) Principal Investigators Meetings and that recent ARM/ASR aerosol data reporting strategies have included similar ideas for data merging, indicating that this work has had a lasting impact on ARM aerosol data acquisition and reporting. The proposed work advances the science of the interactions of aerosols, clouds and precipitation, with direct application to improve representation of such interactions for clouds in regional and global climate models. The archived data will continue to serve research studies in the future.

54 ENVIRONMENTAL SCIENCES↗

Methanotrophic-Mediated Methylmercury Transformation: Characterization of Products, Mechanism, and Environmental Significance (Final Technical Report)

Previous work in the laboratories of the PIs found that methanotrophs, through the production of a novel metal chelator called methanobactin (MB), can bind inorganic mercury (Hg[II]). By doing so, methanotrophs substantially reduce Hg[II] toxicity. We have also recently shown that MB can bind a much more toxic form of mercury, the neurotoxin methylmercury (MeHg). MeHg bioaccumulates and biomagnifies in biota such as fish, and is of significant concern. Further, certain methanotrophs expressing MB are able to demethylate significant amounts of MeHg despite lacking merB, the organomercurial lyase. Further, unlike the canonical organomercurial lyase, methanotrophs take up and degrade MeHg at environmentally relevant pH and Hg concentrations (i.e., picomolar to nanomolar), suggesting that methanotrophs likely play a critical role in controlling net MeHg production and toxicity in situ. However, although MB is necessary for methanotrophic-mediated MeHg degradation, it is not sufficient as purified MB binds, but does not degrade MeHg. That is, MB appears to serve as binding device leading to demethylation of MeHg by an as yet unknown mechanism. The major goals of this project were to extend this initial work and characterize the mechanism of methanotrophic-mediated MeHg demethylation and how methanobactin production may affect net methylmercury production in situ.

54 ENVIRONMENTAL SCIENCES↗

Systems Level Study of a Novel Fast-Growing Cyanobacterial Strain for Next Generation Biofuel Production

The overall objective of this project is to use an integrated systems biology approach to develop a fast growing cyanobacterial strain as a platform organism for photobiological production of advanced biofuels and other useful chemicals. Cyanobacteria are oxygenic photosynthetic microbes that use light and CO 2 as feedstocks, and hence offer enormous promises for sustainable bioenergy production. One of the key issues in cyanobacterial biofuel production is the growth rates of these microbes. Compared to other oxygenic photosynthetic organisms such as plants and eukaryotic algae, many cyanobacterial strains have superior growth properties. However, they grow significantly slower than heterotrophic microbes such as E. coli and yeast that are commonly used in biofuel research. We have recently identified Synechococcus elongatus UTEX 2973, a unicellular cyanobacterium that has the ability of rapid photoautotrophic growth comparable to that of the yeast Saccharomyces cerevisiae. In this project, we will pursue a systems approach to develop Synechococcus 2973 as a versatile and useful model cyanobacterial host to be used by the bioenergy research community during the coming era. The knowledge base generated during this project will also be helpful for sustainable biofuel production by other cyanobacterial as well as eukaryotic photosynthetic hosts that use sunlight and CO 2 as renewable feedstocks.

09 BIOMASS FUELS↗

Machine learning to identify geologic factors associated with production in geothermal fields: A casestudy using 3D geologic data, Brady geothermal field, Nevada

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in the Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid flow pathways are relatively rare in the subsurface but are critical components of hydrothermal systems like Brady and many other types of fluid flow systems in fractured rock. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of fourteen 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate the macro-scale faults and a local step-over in the fault system preferentially occur along with production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate 1) the specific geologic controls on the Brady hydrothermal system and 2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.

15 GEOTHERMAL ENERGY↗

A Novel Platform for Algal Biomass Production Using Cellulosic Mixotrophy (CeMix) (Final Technical Report)

This novel project, branded CeMIX for cellulosic mixotrophy, targets solutions for several technological barriers limiting the deployment of algae cultivation in sunny, arid regions (specifically the southwest United States). Opening up the region for algae cultivation could increase DOE’s resource assessments and biofuel potential for the U.S. Mixotrophic metabolism in support of liquid fuel production is completely dependent on the availability of waste organic carbon in order to avoid diversion of food resources for fuel production. The use of cellulosic sugar hydrolysate (CSH) produced via the NREL process provided a standardized carbon source for study of the underlying biochemistry and metabolic adjustments to mixotrophy. Mixotrophic metabolism uses both photosynthetic CO 2 fixation and sugar oxidation to improve biomass productivity and harvest yield. The project was high-risk, high-reward in the sense that adding organic carbon to algal cultivation is an invitation for rapid-growth, heterotrophic contaminants to overtake the culture and consume mineral nutrients needed for algal growth. To help evade this outcome the project focused on acidophilic red algae that require low pH conditions with 40-48°C optimal temperature profiles that define them as low-range thermophiles. This is the only project in the BETO portfolio to utilize extreme conditions of low pH and high operating temperatures to control pathogens and competitors in mass culture. The project yielded five major outcomes. 1) Harvest densities of 5-10 g ash-free dry weight are easily achieved, providing a 10-fold reduction in water required and dewatering demand. 2) Catabolic repression of photosynthesis in G. sulphuraria is conditionally repressed by low oxygen. 3) Mixotrophic growth on cellulosic hydrolysate consumes all C6 and C5 sugars concomitant with increases in floridean starch with little change in lipid content. Protein content can be manipulated between 35 and 54 wt% by varying the C:N molar ratio from 10:1 to 20:1, respectively. 4) Mixotrophic cultures with up to 50 mM total sugar are remarkably stable at pH 2.5 and daily average reactor temperatures of 40°C. 5) Capital costs for glass tubular photobioreactors are prohibitive for liquid fuel production using a hydrothermal liquefaction processing pathway. The economic outlook for covered raceway ponds is better with a project minimum fuel selling price at $3.32 dm 3 GE -1 .

09 BIOMASS FUELS↗

Fission Product Transport in TRISO Particles and Pebbles

This document demonstrates completion of the goals described in the technical narrative of the FOA project titled: ”Modeling and Simulation Development Pathways to Accelerating KP-FHR Licensing” regarding fission product transport in the Kairos-proposed fuel pebble by INL and Kairos Power. Showcased in this report are code developments and simulations in BISON that extend the state of the art in computation and understanding of fission product transport in a TRISO fuel particle and pebble. These enhancements lay the foundation for making predictions of fission product transport that can be used as input in the fuel licensing process. This was achieved by installing existing fuel material models originally used in PARFUME, developing a new failure probability method that is efficient and multi-dimensional, employing material homogenization, and expanding verification and validation simulations to demonstrate the efficacy of the work. All this work is leveraged to spotlight the main deliverable; a three-dimensional model and corresponding demonstration simulation of a pebble, which will serve as the starting point for models used to predict fission product release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Exploring Whether Subsurface Fluid Production Can Minimize Triggered Seismicity in Geothermal Fields

Fluid injection and production related to energy recovery and other industrial operations alter the pressure and stress state of subsurface reservoirs which can lead to induced seismicity. Here, the primary goal is to investigate the hypothesis that the modulation of stress state in subsurface reservoirs through fluid injection/production operations can reduce the likelihood of inducing seismicity. Validation of this mitigation strategy will provide an active operational method to control induced seismicity in subsurface reservoir exploitations such as geothermal energy recovery and carbon storage. In this project, we analyze the relationship between extensive fluid production and the paucity of aftershock activity at the Coso Geothermal plant (CGP) following the 2019 Ridgecrest earthquake sequence, where high rates of aftershock triggering were expected. We developed a high-fidelity multiphase coupled thermo-hydro-mechanical (THM) model to simulate fluid injection/production activities at the CGP between 1986 and 2020. THM results of surface subsidence due to high rates of fluid production agree well with field observations from global positioning system (GPS) and interferometric synthetic aperture radar (InSAR). Subsequently, the variations of pore pressure, temperature and stress state were used to drive numerical earthquake simulations of the aftershock response to the 2019 Ridgecrest earthquakes. The earthquake simulations show that seismic quiescence may occur following the Ridgecrest event, depending on the initial stress state at the time of the mainshock and at the initiation of geothermal energy production. Seismic quiescence occurs in 20% of the cases we explored, where rates are decreased by 50% of the background rate in the two years following the mainshock. In circumstances where aftershock rates increase near the CGP following Ridgecrest, the average rate change is a factor of two larger than background rates from simulations with no operations. These findings indicate that unlike many other operations that bring faults closer to failure, operations at the CGP are acting to stabilize faults such that triggering in the current stress state is minimal.

58 GEOSCIENCES↗

Developing Advanced Genetic and Synthetic Biology Tools for Improved Algae Productivity

Under the UCSD-led Productivity Enhanced Algae and ToolKits (PEAK) project we sought to develop tools to enable the production of valuable co-products, as well as strategies to decrease the cost of cultivation, with an intended outcome of enabling the economic production of algae-based biofuel. We have developed new genetic tools and high throughput selection methods for eukaryotic green algae and used them to express a high value recombinant protein; a growth factor known as Osteopontin (OPN). Recombinant OPN protein expression levels were improved through a newly developed rapid breeding and mutagenesis strain improvement method to generate a robust strain capable of growing in outdoors raceway conditions in brackish water that tolerated high pH and large temperature swings. We further applied the new genetic tools to express recombinant protein in a recently bioprospected strain with even more robust growth characteristics. In response to the COVID-19 pandemic we used our improved workflow to rapidly express, purify, and characterize a recombinant SARS-CoV-2 spike protein Receptor Binding Domain (RBD) and demonstrate that it functionally interacts with its cognate human host receptor ACE2. The newly identified extremophile strain Chlamydomonas sp (402), both mating type (mt+) and mating type (mt-), have been deposited in the Chlamydomonas Resource Center (https://www.chlamycollection.org/), making them available world-wide with no restrictions. In addition, all of genetic tools are also deposited at this site and are also available world-wide with no restrictions.

09 BIOMASS FUELS↗

Developing Multi-Gene CRISPRa/I Programs to Accelerate DBTL Cycles in ABF Hosts Engineered for Chemical Production (CRADA 468)

Bacterial metabolism is comprised of large and complex gene networks that can produce valuable chemical products. Sophisticated organism engineering efforts are required to optimize production of high-value compounds from these networks. In principle, synthetic multi-gene transcriptional programs could be constructed to reengineer these networks for efficient industrial chemical production. In practice, however, our incomplete ability to understand and model the underlying networks, combined with our limited ability to predictably control the expression of multiple genes makes achieving this goal difficult. To overcome these challenges, we will combine new CRISPR-Cas multi-gene expression programs with computational modeling, machine learning, and multi-omics data to enhance the efficacy of design-build-test-learn (DBTL) cycles. For industrially promising microorganisms in early stages of development, creating technologies for rapidly engineering complex multi-gene programs could be transformative for accelerating data- and model-driven strain design. New CRISPR-Cas tools allow programmable gene activation (CRISPRa) or repression (CRISPRi) at multiple genes simultaneously, using the catalytically inactive Cas9 protein (dCas9) with guide RNAs that recognize DNA targets through predictable Watson-Crick base pairing. To enable accelerated DBTL cycles, we will combine these technologies with advanced Agile BioFoundry (ABF) capabilities for multi-omics data collection and machine learning. We will demonstrate the immediate applicability of these tools by rapidly improving the production of an industrial aromatic in multiple ABF organisms. We recently identified and optimized new transcriptional activators that can be linked to programmable CRISPR-Cas DNA binding domains to activate gene expression in E. coli. We can now use these CRISPRa tools as generalizable trans-acting regulators for combinatorial multi-gene expression tuning that can be easily transferred to new pathways and networks without additional genome engineering. We anticipate these tools will also transfer to new hosts. We have recently found that CRISPRa systems developed in E. coli can be readily ported to Pseudomonas putida, suggesting that multi-gene CRISPRa/i programs for diverse ABF organisms may be within reach.

59 BASIC BIOLOGICAL SCIENCES↗

A Method for Evaluating and Tracking Production-Sample Test (PST) Delay Risk

This report describes a method for evaluating risk from delayed Production Sample Testing (PST), and strategies for reducing test backlogs. Risk contributions to overall risk from delayed PST include a Steady State Risk (SSR) contribution that is inherent in the qualified design and manufacturing processes, and a Non-Homogenous Production Risk (NHPR) contribution from production variation. Both definitions and evaluation techniques for these risk contributions are provided along with correlation to the standard Quality Assurance Process, QA001.2, risk ranking matrix. Methods for tracking test backlogs, and reducing backlogs are also discussed. The delayed PST evaluation method described here includes the merger of both slightly quantitative methods for tracking defect levels and the propensity for production variation with general risk management tracking tools like the likelihood vs. consequence risk ranking matrix. This merger is important because it allows more effective evaluation and communication with regards to delayed PST.

42 ENGINEERING↗

Techno-Economic Analysis of Product Diversification Options for Sustainability of the Monticello and Prairie Island Nuclear Power Plants

The objective of this work was to perform techno-economic analysis (TEA) of hybrid options that could be integrated with light water reactor (LWR) nuclear power plants (NPPs) in order to improve the viability and sustainability of existing LWRs through product diversification by utilizing nuclear energy not only to produce grid electricity but to also produce carbon free products such as hydrogen, ammonia or synthetic fuels. Much of the analysis herein could be generally applied to any LWR (high temperature steam electrolysis- HTSE design), but hydrogen demand and the optimization of the HTSE was completed with specific collaboration and data from Xcel Energy’s Prairie Island and Monticello nuclear generating stations and the surrounding market and logistics potential in the greater Minneapolis region. Xcel Energy has set aggressive goals with regards to decarbonization, including an 80% reduction in CO 2 emissions from 2005 levels, by 2030 and 100% carbon free by 2050. Other TEAs regarding hydrogen production with nuclear energy have been completed in collaboration with other utility companies previously. Besides being the first TEA in this regard specific to Xcel Energy and the surrounding markets and logistics, this TEA adds to the previously completed TEAs by providing the most up to date and state of the art analysis and optimization of the hydrogen production plant integrated with nuclear power (NPP-HTSE).

08 HYDROGEN↗