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LA100 Equity Strategies

LA100 Equity Strategies is a collaborative effort between LADWP, NREL, UCLA, and Kearns & West that employs an interdisciplinary approach utilizing distinct - but connected - research efforts informed and guided by the project Steering Committee, which met monthly through the duration of the project. Chapters 1 through 4 address recognition and procedural justice through recognition, process, and community strategies, while Chapters 5 through 12 address distributional justice through program and infrastructure strategies. Chapters 13 through 17 provide policy and program strategies. Each chapter provides data, methods, tools, insights, and strategies to help LADWP make data-driven, community-informed decisions for equitable investments and program development.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

Equity-Centered Engagement Through Climate Resilience Policy in Massachusetts

Communities who experience disproportionate climate change impacts tend to be excluded from resilience planning (Vale, 2014). Those efforts typically follow top-down processes within established governance practices that are inaccessible to marginalized folks and reinforce inequalities (Malloy & Ashcraft, 2020; Adger, 2003). Such participatory planning processes may offer the public little opportunity to influence the process itself or the outcomes (Smith & McDonough, 2001). They might ignore important public values or alternative ways of knowing which can be critical assets in resilience (Few et al., 2007). Designing communities for climate action and resilience means creating opportunities for everyone to meaningfully shape those decisions and experience related benefits. Having the opportunity to shape one’s community is necessary for human flourishing (Allen, 2016). Resilience planning that shifts power into communities and focuses on social vulnerability can affect how people survive and thrive in a climate changed world. The Massachusetts Municipal Vulnerability Preparedness (MVP) 2.0 program is an attempt to change the status quo in resilience planning by bringing new voices into decision-making power, recognizing their labor, addressing root causes of vulnerability, and investing in social infrastructure. It aspires to build capacity for equity-focused community engagement within teams of municipal staff and community liaisons, and ultimately build social capital and community cohesion. My mixed methods research investigates implementation of this state grant program in several western Massachusetts towns. I am using document review, participant observation, and interviews to understand the MVP 2.0 process as written, how different towns navigate it, and how individuals make sense of their experiences in it. I seek to understand how those experiences explain relationships between engagement approaches, mediating factors, and process outcomes. I am interested in the conditions that allow for community empowerment and how a model like MVP 2.0 can shift conditions that hold systems in place. In a practical sense, our findings will help municipalities reflect on their work during MVP 2.0 and plan for future community engagement. They may be informative for designing future iterations of the MVP program and for other municipalities, offices of community engagement, and practitioners. The findings will also contribute to the participation, resilience, and climate justice literatures, by adding perspectives on equity-centered resilience and community engagement approaches in smaller towns and rural settings. References: Adger, W. N. (2003). Social capital, collective action, and adaptation to climate change. Economic Geography, 79, 387-404. Allen, D. (2016). Toward a connected society. Our compelling interests: The value of diversity for democracy and a prosperous society, 71-105. Few, R., Brown, K., & Tompkins, E. L. (2007). Public participation and climate change adaptation: avoiding the illusion of inclusion. Climate Policy, 7(1), 46–59. Malloy, J. T., & Ashcraft, C. M. (2020). A framework for implementing socially just climate adaptation. Climatic Change, 160(1), 1–14. Smith, P. D., & McDonough, M. H. (2001). Beyond public participation: Fairness in natural resource decision making. Society & natural resources, 14(3), 239-249. Vale, L. J. (2014). The politics of resilient cities: whose resilience and whose city? Building Research & Information, 42(2), 191–201.

Callaham, Shannon↗

Cytochrome Nanowire XRD

Microbial metabolism plays an important role in the global cycling of carbon, nutrients, and metals. Recent discovery of microorganisms sharing energy using direct electrical connections might represent a prominent strategy by which anaerobic microorganisms interact with the diversity of environments. The purpose of the proposed research is to apply these newly developed principles of electron exchange in microbial communities to the study of biogeochemical cycling in climate and subsurface systems. Previous studies revealed that soil bacteria Geobacter sulfurreducens produce conductive pili nanofilaments that facilitate long-range electron transport to extracellular electron acceptors and other cells. This discovery has already transformed our understanding of the function of microbial communities in diverse environments, making basic contributions to microbial ecology and helping to improve practical applications such as increasing current output of microbial fuel cells and enhancing the conversion of organic waste to methane. Microbial electron exchange via pili may also contribute to methane production in terrestrial environments that are major sources of atmospheric methane. However, the mechanism of electron transport through pili is not well understood. Initial studies have suggested that pili exhibit metallic-like conductivity similar to conducting polymer polyaniline. However, these studies were limited to electrical measurements. X-ray diffraction studies have suggested that aromatic amino acids tyrosine and phenylalanine are closely packed in pili. But these studies used homology modeling to predict the pilus assembly and information about the number of monomers in each pilus assembly unit and their organization are still lacking. The central hypothesis of this proposal is aromatics in pili enable intermolecular electron delocalization due to pi-stacking that can give rise to metallic-like conductivity. By analyzing pili structure using infrared scattering-scanning near field optical microscope (IR s-SNOM) and combining with solution NMR, Focused Ion Beam (FIB and computational capabilities, this work will provide comprehensive understanding of the conduction mechanism from a structure-function perspective. The specific aims are: 1) With infrared scattering scanning near field optical microscope (IR s-SNOM), image the organization and density of pilin monomers and pH-induced conformational changes in a pilus filament. 2) With solution NMR, resolve pH-induced structural changes in the pilin monomer. 3) Using Focused Ion Beam (FIB), draw electrodes on single pili to measure their conductivity. 4) With computational modeling using the NWChem, simulate the effect of environment on the electronic properties of pili as a function of pH. The proposed work will gain the nanoscale insight into the structure of the pili, as the basis for understanding interspecies electrical communications. The improved understanding will be harnessed to accelerate bioenergy production and bioremediation using pili as well as for predictive modeling of carbon cycling in diverse environments to reach the central goals of DOE-BER to develop sustainable energy sources, regulate the contaminants in the subsurface and understand the effects of greenhouse gas emissions on biosphere. The proposed studies will provide design principles for engineering of electrical interactions among these communities by manipulating the amino acid composition of pili. Moreover, these studies will identify the forces that maintain the function of these communities in the face of environmental perturbation. Therefore, these studies will help to address the need "to incorporate process understanding of biogeochemical cycling into a scalable hierarchy of predictive capabilities" specified in EMSL's Science Themes.

59 BASIC BIOLOGICAL SCIENCES↗

Assessment of the ParFlow–CLM CONUS 1.0 integrated hydrologic model: evaluation of hyper-resolution water balance components across the contiguous United States

Abstract. Recent advancements in computational efficiency and Earth system modeling have awarded hydrologists with increasingly high-resolution models of terrestrial hydrology, which are paramount to understanding and predicting complex fluxes of moisture and energy. Continental-scale hydrologic simulations are, in particular, of interest to the hydrologic community for numerous societal, scientific, and operational benefits. The coupled hydrology–land surface model ParFlow–CLM configured over the continental United States (PFCONUS) has been employed in previous literature to study scale-dependent connections between water table depth, topography, recharge, and evapotranspiration, as well as to explore impacts of anthropogenic aquifer depletion to the water and energy balance. These studies have allowed for an unprecedented process-based understanding of the continental water cycle at high resolution. Here, we provide the most comprehensive evaluation of PFCONUS version 1.0 (PFCONUSv1) performance to date by comparing numerous modeled water balance components with thousands of in situ observations and several remote sensing products and using a range of statistical performance metrics for evaluation. PFCONUSv1 comparisons with these datasets are a promising indicator of model fidelity and ability to reproduce the continental-scale water balance at high resolution. Areas for improvement are identified, such as a positive streamflow bias at gauges in the eastern Great Plains, a shallow water table bias over many areas of the model domain, and low bias in seasonal total water storage amplitude, especially for the Ohio, Missouri, and Arkansas River basins. We discuss several potential sources for model bias and suggest that minimizing error in topographic processing and meteorological forcing would considerably improve model performance. Results here provide a benchmark and guidance for further PFCONUS model development, and they highlight the importance of concurrently evaluating all hydrologic components and fluxes to provide a multivariate, holistic validation of the complete modeled water balance.

O'Neill, Mary M. F. (ORCID:0000000221455165)↗

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas

Many decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NO x ), and sulfur dioxide (SO 2 ), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution. To address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities. Version 1.0 of LOCAETA displays the estimated primary PM 2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH 3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics. LOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

ArQTiC: A Full-stack Software Package for Simulating Materials on Quantum Computers

ArQTiC is an open-source, full-stack software package built for the simulations of materials on quantum computers. It currently can simulate materials that can be modeled by any Hamiltonian derived from a generic, one-dimensional, time-dependent Heisenberg Hamiltonian. ArQTiC includes modules for generating quantum programs for real- and imaginary-time evolution, quantum circuit optimization, connection to various quantum backends via the cloud, and post-processing of quantum results. By enabling users to seamlessly design, execute, and analyze materials simulations on quantum computers, ArQTiC opens this field to a broader community of scientists from a wider range of scientific domains.

97 MATHEMATICS AND COMPUTING↗

Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operationson Spatial Accelerators

To meet the extreme compute demands for deep learning across commercial and scientific applications, dataflow accelerators are becoming increasingly popular. While these“domain-specific” accelerators are not fully programmable like CPUs and GPUs, they retain varying levels of flexibility with respect to data orchestration, i.e., dataflow and tiling optimizations to enhance efficiency. There are several challenges when designing new algorithms and mapping approaches to execute the algorithms for a target problem on new hardware. Previous works have addressed these challenges individually. To address this challenge as a whole, in this work, we present an HW-SW co-design ecosystem for spatial accelerators called Union within the popular MLIR compiler infrastructure. Our framework allows exploring different algorithms and their mappings on several accelerator cost models. Union also includes a plug-and-play library of accelerator cost models and mappers which can easily be extended. The algorithms and accelerator cost models are connected via a novel mapping abstraction that captures the map space of spatial accelerators which can be systematically pruned based on constraints from the hardware, workload, and mapper. We demonstrate the value of Union for the community with several case studies which examine offloading different tensor operations (CONV/GEMM/Tensor Contraction) on diverse accelerator architectures using different mapping schemes.

Jeong, Geonhwa↗

Carbon acquisition ecological strategies to connect soil microbial biodiversity and carbon cycling

Soil carbon feedbacks to global change are uncertain, and the biological processes that govern soil organic matter decomposition are not resolved in current ecosystem models. Though it is recognized that microbial biodiversity influences decomposition rates, incorporating this relationship into ecosystem models is challenging because microbial communities are prohibitively diverse. It is likely necessary to distill microbial biodiversity by focusing on functional groups or ecological strategies. The ecological strategies that currently dominate the microbial ecology literature derive from macroecological theory, have clear weaknesses, and have had limited success when applied to predict soil carbon dynamics. Here, we present a new framework for soil microorganisms: Carbon Acquisition Ecological Strategies (CAES), and we outline a path toward incorporating microbial biodiversity into ecosystem models using this framework to enhance predictions of soil carbon feedbacks to global change. Because a microorganism's diet is central to its ecological niche and likely to covary with other ecologically significant traits, we posit that carbon acquisition may serve as a tractable foundation for developing ecological strategies. Further, we describe four candidate ecological strategies for soil microorganisms: 1° decomposers that assimilate complex plant polymers, 2° decomposers that assimilate microbial necromass, passive consumers that assimilate dissolved organic carbon, and predatory microbes that assimilate live microbial biomass. These strategies are directly linked to soil carbon pools currently represented in ecosystem models and may provide a foundation for greater integration of microbial community dynamics into ecosystem models.

59 BASIC BIOLOGICAL SCIENCES↗

DOE BSSD Performance Management Metrics Report Q1

Microbes play key roles in our biosphere, from driving global nutrient cycling to impacting plant, animal and human health and disease. Complex data from microbial genomes, proteins, and metabolites provide a window into these tiny engines that drive life on our planet. Yet these data are dispersed among researchers’ laboratories and various repositories, making it difficult to access. This calls for new ways of managing data, improving data interoperability, advancing community standards, and creating an infrastructure where data are shared efficiently. We have built the National Microbiome Data Collaborative (NMDC) to advance how scientists create, use, and reuse data to redefine the way we understand and harness the power of microbes. The vision of the National Microbiome Data Collaborative (NMDC) is to drive a microbiome data sharing network connecting data, people, and ideas to advance microbiome innovation and discovery. The NMDC was launched in 2019 and brought together DOE National Laboratories to collaborate across resources, capabilities, and expertise. The NMDC team was strategically assembled to include software developers, microbial researchers, metadata experts, and multi-omics specialists. The diversity of the NMDC team reflects the inherently interdisciplinary nature of microbiome science, and we leverage the strengths of the DOE National Laboratory system. Towards BER’s goal of advancing an iterative systems biology approach to the understanding of microbial genomes, the NMDC serves as a foundation for infrastructure, data standards, and community building. Together with the flagship DOE User Facilities, the Joint Genome Institute (JGI) and the Environmental Molecular Sciences Laboratory (EMSL), we are developing core capabilities in metadata standards for environmental descriptors and sample handling and processing; standardized bioinformatic workflows; an interface for data search and access; and robust community engagement activities. The NMDC production platform supports long-term data infrastructure and community building for BER’s bioenergy and environmental research goals. Our approach leverages lessons learned and an ambitious framework for collaborative, interdisciplinary data infrastructure to support microbiome research. The NMDC supports data, information, and knowledge access through three defined software tools – the Submission Portal, NMDC EDGE, and the Data Portal – driven by community needs. Herein, we describe the value proposition for the microbiome research community, our overarching strategy, and challenges and opportunities for developing the NMDC as both an infrastructure and community engagement program.

59 BASIC BIOLOGICAL SCIENCES↗

Sizing Small-Scale Renewable Energy Systems for the Navajo Nation and Rural Communities

The Navajo Nation consists of about 55,000 residential homes spread across 27,000 square miles of trust land in the Southwest region of the United States. The Navajo Tribal Utility Authority (NTUA) reports that approximately 15,000 homes on the reservation do not have electricity due to the high costs of connecting rural homes located miles from utility distribution lines. In order to get these rural homeowners access electricity, NTUA and other Native owned companies are examining small-scale renewable energy systems to provide power for necessary usage such as lighting and refrigeration. The goal of this study is to evaluate the current renewable deployment efforts and provide additional considerations for photovoltaic (PV) systems that will optimize performance and improve efficiency to reduce costs. There are three case studies presented in different locations on the Navajo Nation with varying solar resource and energy load requirements. For each location, an assessment is completed that includes environmental parameters of the site- specific landscape and a system performance analysis of an off-grid residential PV system. The technical process, repeated for each location, demonstrates how the variance and uniqueness of each household can impact the system requirements after optimizations are applied. Therefore, the household variabilities and difference in locations must be considered. The differing results of each case study suggests additional analysis is needed for designing small-scale PV systems that takes a home-land-family specific approach to allow for better efficiency and more flexibility for future solar innovations to be considered for overall cost reductions.

14 SOLAR ENERGY↗

Quantifying magnetic field driven lattice distortions in kagome metals at the femto-scale using scanning tunneling microscopy

A wide array of unusual phenomena has recently been uncovered in kagome solids. The charge density wave (CDW) state in the kagome superconductor AV 3 Sb 5 , in particular, intrigued the community; the CDW phase appears to break the time-reversal symmetry despite the absence of spin magnetism, which has been tied to exotic orbital loop currents possibly intertwined with magnetic field tunable crystal distortions. To test this connection, precise determination of the lattice response to an applied magnetic field is crucial but can be challenging at the atomic scale. We establish a scanning tunneling microscopy (STM) based method to study the evolution of the AV 3 Sb 5 atomic structure as a function of magnetic field. The method substantially reduces the errors of typical STM measurements, which are at the order of 1% when measuring an in-plane lattice constant change. Here, we find that the out-of-plane lattice constant of AV 3 Sb 5 remains unchanged (within 10 —6 ) by the application of both in-plane and out-of-plane magnetic fields. We also reveal that the in-plane lattice response to magnetic field is at most at the order of 0.05%. Our experiments provide further constraints on time-reversal symmetry breaking in kagome metals and establish a tool for higher-resolution extraction of the field-lattice coupling at the nanoscale applicable to other quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Universal Monte Carlo Event Generator

With the Jefferson Lab 12 GeV physics program underway and plans for the future Electron-Ion Collider (EIC), the nuclear physics community is entering a new era of exploration of QCD phenomena involving extensive data taking and event-level processing. This brings with it the potential for unprecedented access to multidimensional particle momentum distributions (PMDs) that can be connected to various theoretical frameworks by unfolding the emergent quantum mechanical properties of QCD using the PMDs. In practice, the PMDs are rendered as discretized histograms (typically one- or two-dimensional projections), and detector effects must be taken into account to unfold the pure detector effect-free PMDs that can be connected with theory. One of the challenges in this new era is obtaining faithful reconstructions of the multidimensional PMDs that preserve all of the inherent particle correlations. In this LDRD project we developed a novel approach using machine learning (ML) that solves this challenge, by avoiding entirely the need to use histograms as the main numerical technique to obtain the detector effect-free PMDs. The new approach is, moreover, scalable to higher dimensional PMDs. The central idea involves training neural networks (NNs) to generate synthetic event-level data (momenta 4-vectors of final state particles) to preserve all correlations among the particles. This is achieved by converting the trial synthetic vertex-level events to detector-level events using detector simulators. The NNs are then tuned using a specialized distance metric between the synthetic detector events and the real detector events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Control of Low-Inertia Power Systems

Electric power systems are undergoing an unprecedented transition from fossil fuel–based power plants to low-inertia systems that rely predominantly on power electronics and renewable energy resources. This article reviews the resulting control challenges and modeling fallacies, at both the device and system level, and focuses on novel aspects or classical concepts that need to be revised in light of the transition to low-inertia systems. To this end, we survey the literature on modeling of low-inertia systems, review research on the control of grid-connected power converters, and discuss the frequency dynamics of low-inertia systems. Moreover, we discuss system-level services from a control perspective. Overall, we conclude that the system-theoretic mindset is essential to bridge different research communities and understand the complex interactions of power electronics, electric machines, and their controls in large-scale low-inertia power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Changing Microbiomes: A Symposium Hosted by the Microbiome Center at the Pennsylvania State University

The first “Changing Microbiomes” conference was successfully held at the Pennsylvania State University from May 31st – June 3rd, 2022. The overall goal of the symposium was to provide space for researchers to connect, exchange knowledge, and partner to advance our understanding of the mechanisms and applications of ecological and evolutionary changes in microbiomes across systems. The symposium spanned terrestrial and aquatic contexts and host-associated and free-living microbial communities. As such, the symposium will enable cross-disciplinary knowledge and idea exchange to promote future interdisciplinary collaborations. In addition, the program allowed formal and informal interactions between and among students, postdocs, PIs, and industry scientists.

54 ENVIRONMENTAL SCIENCES↗

State changes: insights from the U.S. Long Term Ecological Research Network

Understanding the complex and unpredictable ways ecosystems are changing and predicting the state of ecosystems and the services they will provide in the future requires coordinated, long-term research. This paper is a product of a U.S. National Science Foundation funded Long Term Ecological Research (LTER)network synthesis effort that addressed anticipated changes in future populations and communities. Each LTER site described what their site would look like in50 or 100 yr based on long-term patterns and responses to global change drivers in each ecosystem. Common themes emerged and predictions were grouped into state change, connectivity, resilience, time lags, and cascading effects. Here, we report on the “state change” theme, which includes examples from the Georgia Coastal (coastal marsh), Konza Prairie (mesic grassland), Luquillo(tropical forest), Sevilleta (arid grassland), and Virginia Coastal (coastal grassland) sites. Ecological thresholds(the point at which small changes in an environmental driver can produce an abrupt and persistent state change in an ecosystem quality, property, or phenomenon) were most commonly predicted. For example, in coastal ecosystems, sea-level rise and climate change could convert salt marsh to mangroves and coastal barrier dunes to shrub thicket. Reduced fire frequency has converted grassland to shrubland in mesic prairie, whereas overgrazing combined with drought drive shrub encroachment in arid grasslands. Lastly, tropical cloud forests are susceptible to climate-induced changes in cloud base altitude leading to shifts in species distributions. Overall, these examples reveal that state change is a likely outcome of global environmental change across adverse range of ecosystems and highlight the need for long-term studies to sort out the causes and consequences of state change. The diversity of sites within the LTER network facilitates the emergence of overarching concepts about state changes as an important driver of ecosystem structure, function, services, and futures.

54 ENVIRONMENTAL SCIENCES↗

Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding

Abstract Climate change is intensifying the global water cycle, with increased frequency of drought and flood. Water is an important driver of soil carbon dynamics, and it is crucial to understand how moisture disturbances will affect carbon availability and fluxes in soils. Here we investigate the role of water in substrate-microbe connectivity and soil carbon cycling under extreme moisture conditions. We collected soils from Alaska, Florida, and Washington USA, and incubated them under Drought and Flood conditions. Drought had a stronger effect on soil respiration, pore-water carbon, and microbial community composition than flooding. Soil response was not consistent across sites, and was influenced by site-level pedological and environmental factors. Soil texture and porosity can influence microbial access to substrates through the pore network, driving the chemical response. Further, the microbial communities are adapted to the historic stress conditions at their sites and therefore show site-specific responses to drought and flood.

58 GEOSCIENCES↗

Data for "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding"

This dataset contains data used for the paper "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding". The Related References field will be updated with a full citation when available.Climate change is intensifying the global water cycle, with increased frequency of drought and flood. Water is an important driver of soil carbon dynamics, and it is crucial to understand how moisture disturbances will affect carbon availability and fluxes in soils. Here we investigate the role of water in substrate-microbe connectivity and soil carbon cycling under extreme moisture conditions. We collected soils from Alaska, Florida, and Washington USA, and incubated them under Drought and Flood conditions. Drought had a stronger effect on soil respiration, pore-water carbon, and microbial community composition than flooding. Soil response was not consistent across sites, and was influenced by site-level pedological and environmental factors. Soil texture and porosity can influence microbial access to substrates through the pore network, driving the chemical response. Further, the microbial communities are adapted to the historic stress conditions at their sites and therefore show site-specific responses to drought and flood.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/TES_3Soils_2021 (DOI: 10.5281/zenodo.4792655).

54 ENVIRONMENTAL SCIENCES↗

The EGS Collab Project: Learnings from Experiment 1

The primary objective of the EGS Collab Project sponsored by DOE is to increase the understanding needed to efficiently implement enhanced geothermal systems (EGS). One goal of the EGS Collab project is to create a collaborative research environment in which to study stimulation of crystalline rock at the 10 meter scale. Key to this effort is the collection of high quality data to allow comparison to numerical coupled process models in an effort to build confidence in the codes and modeling techniques used. In response to this, the EGS Collab team has created an underground test bed at the Sanford Underground Research Facility (SURF) in Lead SD at a depth of approximately 1.5 km to examine hydraulic fracturing (Experiment 1). We are currently designing a second test bed aimed at investigating shear stimulation (Experiment 2). At the Experiment 1 location, we have characterized our host rock using laboratory testing and numerous field-based geophysical and geological techniques, and created a well-instrumented test bed to allow us to carefully monitor stimulation events and flow tests. In addition to the installed geophysical sensors, we have used tracer tests, differences in the ambient microbial communities at flow collection locations, and cold water injection to inform us about dynamic flow pathways. In Experiment 1, we have hydraulically stimulated the host rock in a number times at several locations in one well, creating new fractures that connect to existing fractures between the injection and production boreholes. We have performed long-term ambient and chilled water injection tests as an analog to EGS, and have monitored system changes resulting from these water injections through geophysical monitoring, flow and pressure measurements, tracer tests, and microbiology. Here, we summarize the tests performed, issues identified including poroelastic and thermoelastic effects, Joule-Thomson effects, restarting effects, indications of flow channeling, and the primary learnings from Experiment 1.

Enhanced Geothermal Systems, EGS Collab, stimulati↗