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At least 73 records · Page 4

Editorial for Special Issue: Grid-Interactive Efficient Buildings—Part 2

This issue of the ASME Journal of Engineering for Sustainable Buildings and Cities (JESBC) is fully dedicated to peer-reviewed papers specific to technologies and applications of Grid-interactive Efficient Buildings (GEBs). As defined by a series of publications by the U.S. Department of Energy (DOE) and outlined in Part 1 of the editorial of JESBC August 2020 issue, GEBs are efficient, connected, smart, and flexible buildings. This GEB special issue covers some technologies and applications for grid-connected buildings and communities. Some of technologies included in the special issue are dynamic insulation systems for building envelopes, building integrated fuel cells, and rooftop PV systems. Furthermore, the issue outlines the designs and cost-benefits of net-zero energy (NZE) buildings and carbon neutral communities in the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

EDX ClaiMM

EDX ClaiMM is a centralized data & analytical platform designed to revolutionize U.S. critical minerals and materials (CMM) activities. By providing a robust digital infrastructure, ClaiMM will accelerate the combination, leveraging, and rapid utilization of vital data, advanced tools, and cutting-edge research advancements in CMM. This adaptive digital research hub connects the CMM community to essential knowledge products and offers access to interoperable datasets, databases, models, software, and tools from the National Energy Technology’s (NETL’s) Energy Data eXchange (EDX) and other authoritative sources, serving both public and private sectors. EDX ClaiMM delivers AI-informed solutions to address fundamental knowledge gaps and fosters the innovation of new techniques for enhanced characterization and recovery of CMMs within the U.S. By leveraging cloud-hosted, scalable digital infrastructure, ClaiMM meets public–private applied energy needs. It equips the CMM community with priority digital resources that harness on-site and cloud compute capabilities, enabling big data storage, advanced processing, analytics, and visualization.

Critical Materials; Critical Minerals; Rare Earth ↗

National Community Solar Partnership Credit Ready Solar Initiative

This fact sheet discusses the Credit Ready Solar Initiative, which will leverage working groups, technical assistance, training, and strategic partnerships to build a pipeline of credit-ready community solar projects and broad access to a community solar marketplace that connects owners, developers, lenders, and philanthropy to support more equitable deployment of community solar.

solar, solar energy, community solar, national com↗

Research Connections: Career and Research Journeys from the SMP Community. Association for Women in Mathematics Series

This book aims to provide perspectives on important questions that undergraduate and graduate students in mathematics ask themselves. Each chapter gives readers a taste of a different mathematician’s work, presented with enough background material that an advanced undergraduate or early graduate student can understand the key ideas of the research. Each mathematical contribution is prefaced by a short biography of the mathematician who wrote the chapter, to give the reader a connection to the author and provide examples of paths from undergraduate education, through graduate school and beyond.

mathematics, research, biographies↗

Comparison of Microbial Profiling and Tracer Testing for the Characterization of Injector-Producer Interwell Connectivities

Insufficient understanding of the microbial communities and associated microbial processes in geological reservoirs hinders the utilization of this rich data source for improved resource management. In this study, along with four interwell tracer tests at a 1478-m deep fractured crystalline-rock aquifer, we analyzed the microbial communities in the injected and produced water by high-throughput sequencing. The microbial community similarities across boreholes during an interwell flow scenario frequently encountered in reservoir development was explored. Despite the significant tracer recoveries (~30%) in all tracer tests and the cumulatively >100,000 L of exogenous water (carrying exogenous microbes) injected into the 10-m-scale reservoir, the overall structure of produced-fluid microbiome did not increasingly resemble that of the injectate. However, producers with better connectivity with the injector (based on tracer test results) did have more amplicon sequence variants (ASVs) that overlapped with those in the injectate. We identified possible drivers behind our observations and verified the practicality of repeated microbial sampling in the context of reservoir characterization and long-term monitoring. We highlight that injector-producer microbial profiling could provide insights on the relative connectivities across different producers with a given injector, and that the associated logistical needs may be comparable or even less than that of classic tracer tests.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial Community Composition in Deep‐Subsurface Reservoir Fluids Reveals Natural Interwell Connectivity

Abstract The identification of natural fractures and the wells they connect is crucial for the development of geological reservoirs because it may have an important impact on reservoir model construction and hydraulic fracture propagation. In this study we investigated the use of a novel data source, the microbial community composition in the reservoir formation fluids, for identification of interwell connectivity caused by natural fractures. We verified this concept at a newly developed mesoscale enhanced geothermal system (EGS) field testbed located 4,850 ft (1,478 m) beneath ground surface at the Sanford Underground Research Facility in Lead, SD. Fluids produced at or near the EGS testbed were sampled and subjected to high‐throughput 16S rRNA gene amplicon sequencing to analyze the microbial community profile therein. Despite the typically substantial heterogeneity across the community profiles of samples spatially distributed (10 m to 1.9 km apart) throughout the site, samples from two wells at the EGS testbed showed highly similar microbial community composition, suggesting the two wells intersected the same natural fracture. This evidence of natural connectivity between the two wells at the EGS testbed was later corroborated by core log analysis and sewer camera surveys into the boreholes. Besides the field case described in this study, microbial community composition as a reservoir diagnostic tool would be applicable in a much broader context such as unconventional hydrocarbon exploitation, groundwater reservoir characterization, and environmental remediation, adding valuable “hard” data capable of pinpointing the origins of fluids unambiguously.

Zhang, Yuran↗

Landscape connectivity for the invisibles

Because of land use changes, a worldwide decrease in biodiversity is underway, mostly driven by habitat degradation and fragmentation. Increasing landscape connectivity (i.e. the degree to which the landscape facilitates movement between habitat patches) has been proposed as a key landscape-level strategy to counterbalance the negative effects of habitat fragmentation. A robust theoretical and methodological framework has been developed for the concept of connectivity, and an increasing body of empirical evidence supports the relevance of connectivity for biodiversity. However, the framework was built ignoring species that represent the dominant proportion of biodiversity on earth: microorganisms. The extent to which the existing conceptual and methodological frameworks on connectivity can be applied to microorganisms remain unknown. We reviewed existing evidence and analyzed methods to test the influence of connectivity on microorganisms. We included all types of microorganisms, from symbiotic to pathogenic and free-living microorganisms, across all ecosystems. We describe the effect of connectivity on microorganism populations and communities, and identify the limitations and large gaps in current knowledge. Microorganisms can differ from macroorganisms in their response to connectivity due to short (distance less than a meter) dispersal distance of some groups, longer time lag of microorganisms response (possibly accompanied by evolutionary processes) and host association. The latter relies on tight interactions and feedback effects that drive microbial-landscape relationships and lead to possible coadaptation processes. Incorporating the connectivity concept in microbial community assembly rules to preserve the diversity of microbial communities and the ecosystem services they provide could be a crucial step forward in the face of pressing global changes.

60 APPLIED LIFE SCIENCES↗

The Evolution of the Peridynamics Co-Authorship Network

We report peridynamics is a relatively new field in continuum mechanics that has developed over the past 20 years. This paper studies the evolution of collaborations in the field of peridynamics since its inception using social network analysis. For this purpose, we construct a network for each year from 2000 to 2019 describing co-authorship between scientists in peridynamics. In these networks, each node represents a scientist and each link connects two co-authoring scientists with a link weight representing the frequency and strength of their collaboration; each network as a whole can be thought of as a graph representation of the peridynamics community for the given year. By constructing a network for each year, we are able to analyze the evolution of the network in time and discuss the implications of this evolution for the peridynamics community. Our study demonstrates that the peridynamics community has been growing exponentially in size in recent years. Centrality metrics are also used to identify the most collaborative scientists in the community. Moreover, we compute link recommendations based on both elevating a scientist’s position in the network with respect to certain centrality metrics or closing structural holes in the network identified with persistent homology. We further extend the analysis to higher-order networks whose nodes represent groups of scientists in the community and whose links connect collaborating groups. In some sense, our work studies the past, present, and future of the peridynamics community.

97 MATHEMATICS AND COMPUTING↗

Genetic Transfer in Action: Uncovering DNA Flow in an Extremophilic Microbial Community

ABSTRACT Horizontal genetic transfer (HGT) is a significant driver of genomic novelty in all domains of life. HGT has been investigated in many studies however, the focus has been on conspicuous protein‐coding DNA transfers that often prove to be adaptive in recipient organisms and are therefore fixed longer‐term in lineages. These results comprise a subclass of HGTs and do not represent exhaustive (coding and non‐coding) DNA transfer and its impact on ecology. Uncovering exhaustive HGT can provide key insights into the connectivity of genomes in communities and how these transfers may occur. In this study, we use the term frequency‐inverse document frequency (TF‐IDF) technique, that has been used successfully to mine DNA transfers within real and simulated high‐quality prokaryote genomes, to search for exhaustive HGTs within an extremophilic microbial community. We establish a pipeline for validating transfers identified using this approach. We find that most DNA transfers are within‐domain and involve non‐coding DNA. A relatively high proportion of the predicted protein‐coding HGTs appear to encode transposase activity, restriction‐modification system components, and biofilm formation functions. Our study demonstrates the utility of the TF‐IDF approach for HGT detection and provides insights into the mechanisms of recent DNA transfer.

Microbiology↗

Demonstrating Computational Equivalence Between Continuous and Discrete Adjoint Methods by Calculating Time-Dependent Adjoint Solutions with Neutron Diffusion Models

The continuous adjoint method and the discrete adjoint method are two alternative approaches used to calculate adjoint solutions for adjoint systems. The continuous adjoint method derives adjoint equations analytically from continuous forward equations and then solves the adjoint equations either analytically or numerically in a discretized form whereas the discrete adjoint method calculates the adjoint solutions directly from the discretized forward equations. With regard to the methodology development and calculation procedure, distinct differences are well recognized between the two methods. For certain reasons, both methods are exclusively preferred and commonly used by different computational communities, but limited studies clarify the connections between the two adjoint methods from either of the communities. Herein, this paper demonstrates the computational equivalence between the continuous and discrete adjoint methods by investigating time-dependent adjoint solutions to the two-group neutron diffusion model in nuclear reactor analysis problems using both methods. Adjoint solutions can be used to estimate system parameters for reactor safety analysis. Appropriate final state conditions for the adjoint systems are specified in both of the methods, and the conditions are clarified with proper physical explanations. With the help of an event-based case study on neutron diffusion models, the accuracy of the time-dependent adjoint fluxes obtained from both methods is verified, and the pros and cons of both adjoint methods are examined. More importantly, the computational equivalence of both methods is demonstrated when they are applied to multigroup neutron diffusion systems. The advantage of calculating time-dependent adjoint fluxes by directly solving time-dependent adjoint systems rather than taking steady-state approximations as in common practice is also demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Investigation of potential aerosol transmission and infectivity of SARS-CoV-2 through central ventilation systems

Here we evaluate the concentrations and probabilities of infection for both building interior and exterior exposure sources using a well-mixed model in a connected multizone building. As a central hub of many community and economic activities, buildings provide social connectivity, but the COVID-19 pandemic has reduced social connectivity due to concerns of viral spread within buildings. Although single zone models of infectious spread are well studied, the impact of aerosolized spread of SARS-CoV-2 via air handling systems in multizone buildings remains unexplored. Here we evaluate the influence of filtration, air exchange rates, and the fraction of outdoor air on the probability of infection using the well-known well-mixed modeling approach for a multizone. We find filtration lowers the concentration and probability of infection in both source and connected rooms provided at least some air is recirculated, but that probability is not zero. Filtration has no influence without recirculation or unless the outdoor air contains virus. We find that increasing the air exchange rate removes virus from the source room faster but also increases the rate of exposure to connected rooms. Therefore, slower air exchange rates reduce infectivity in connected rooms at shorter durations, but higher air exchange rates reduce infectivity at longer durations. We further find that when outdoor air is virus free, increasing the fraction of outdoor air is helpful, but, when outdoor air is infective, pathogen exposure inside can persist for hours after a short-term release.

60 APPLIED LIFE SCIENCES↗

Scalable edge clustering of dynamic graphs via weighted line graphs

Timestamped relational datasets consisting of records (or connections) between pairs of entities are ubiquitous in network science. For applications like peer-to-peer communication, email, various social network interactions, and computer network security, it is useful to organize these records into groups based on how and when they are occurring. Weighted line graphs offer a natural way to model how records are related in such datasets but for large real-world graph topologies, building and utilizing the line graph is prohibitively expensive. Here, we present the framework to cluster the edges of a dynamic graph via the associated line graph that contains two major contributions. The first is a method to work with the line graph implicitly and the second is a distributed scale implementation of an agglomerative hierarchical graph clustering algorithm. We outline a novel hierarchical dynamic graph edge clustering approach that efficiently breaks massive relational datasets into small sets of edges containing events at various timescales. This is in stark contrast to traditional graph clustering algorithms that prioritize highly connected (clique-like) community structures. Our approach relies on constructing a sufficient subgraph of a weighted line graph and applying a hierarchical agglomerative clustering. This approach is related to scalable techniques from spatial clustering, nonlinear-dimension reduction, topological data analysis, and draws particular inspiration from HDBSCAN. As an edge clustering, this method yields an overlapping node clustering. Our algorithm is parallelizable and we demonstrate efficient clustering of a billion-scale, real-world dynamic graph into small edge sets that correlate in topology and time. The entire clustering process for a graph with tens of billions of edges takes just a few minutes of run time on 256 nodes of a distributed compute environment. We argue how the output of the edge clustering is useful for a multitude of data visualization and powerful machine learning tasks, both involving the original massive dynamic graph data and metadata associated with the nodes and edges. Finally, we describe how this approach can be extended to dynamic hypergraphs and dynamic graphs/hypergraphs with unstructured data living on vertices and edges.

Data Analysis↗

Updates to the Alliance of Genome Resources central infrastructure

The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific “landing pages” and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).

59 BASIC BIOLOGICAL SCIENCES↗

Hydrogen Education for a Decarbonized Global Economy (H 2 EDGE) (Final Technical Report)

The energy sector is undergoing rapid growth and transformation, creating urgent demand for a skilled workforce to support emerging technologies and resilient systems. Hydrogen is an emerging solution for “hard to abate” sectors, including heavy industry and transportation that also provides optionality for the electric system and enables long‑duration energy storage. As hydrogen scales from traditional industrial uses to new applications, success depends on knowledgeable engineers, technicians, planners, and operators safely deploying hydrogen technologies across the full value chain: production, delivery, storage, and end use. The H 2 EDGE initiative, funded by the U.S. Department of Energy’s Hydrogen and Fuel Cell Technologies Office from 2020 to 2025, was launched to prepare people for careers hydrogen and related technologies. Through its interactive approach, H 2 EDGE equipped stakeholders with knowledge and tools to build a reliable and sustainable energy future together. H 2 EDGE built a national network of academic and industry partners to deliver modular training, share open-access curricula, and engage diverse talent pipelines. The program leveraged EPRI’s extensive industry membership and expanded on the train-the-trainer model of the GridEd program to connect educators, employers, and community organizations across all regions of the U.S. New methods were introduced to more systematically map hydrogen competencies and assess curricula using traditional and AI-assisted approaches. Outcomes included delivery of professional short courses, developing university curriculum, sponsoring faculty and student projects, and engaging stakeholders through workshops, site tours, and webinars.

08 HYDROGEN↗

Makah Tribe Strategic Energy Plan

The U.S. Department of Energy’s (DOE) Energy Transitions Initiative Partnership Project (ETIPP) connects remote and island communities, regional partners, and the DOE national laboratories to support communities as they seek to build resilience in their energy systems. The Makah Tribe faces several energy challenges, including frequent power outages and the potential for an extended outage due to an earthquake or tsunami. The Tribe joined ETIPP in 2022 to address those challenges, seeking to build energy resilience and sovereignty in the community. The Makah Tribe, Spark Northwest, the Pacific Northwest National Laboratory (PNNL), and the National Renewable Energy Laboratory (NREL) collaborated to develop a strategic energy plan as part of the second cohort of ETIPP communities. The long-term energy vision of the Makah Tribe includes increasing energy efficiency in the community, improving energy management capacity, and developing the renewable energy generation and storage sufficient to independently power the Reservation for one year. Additionally, the ETIPP team worked with Makah leadership, staff, and community members to identify a set of community priorities, values, and goals to guide energy development as the Tribe takes the incremental steps toward their vision for energy sovereignty. Those energy values include ecosystem-based management, energy sovereignty and project ownership, workforce development and capacity, economic opportunity, community wellbeing and priorities, and emergency disaster resilience. To understand what would be needed for a year for energy independence, the PNNL team conducted an assessment to determine the current energy usage of the Tribe and also modeled several scenarios for future energy use. Using the energy usage values, the team estimated how two types of renewable energy technology, specifically locally deployed solar and small-scale wind, could contribute towards the energy independence goal. The energy baseline and resource assessment produced the following key findings:

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

RDPP: Accelerating Diversity in DOE Climate Science and Resilience Research (Final Report)

The scope of the project was set out to accelerate the inclusion of diversity into the Department of Energy (DOE) Earth and Environmental Systems Sciences Division (EESSD) relevant climate science and resilience research to inclusively advance solutions. The Project Objectives were to usher in equitable use-inspired climate-related research with underrepresented Minorities of which this project helped fund 7 HU graduate students work with the DOE (three of which will graduate in Spring 2025). The two key aims underpinning that core goal were AIM1: developing partnerships (18 organized engaged, see partners list) and AIM2: Developing capabilities (3 visits to DOE facilities, 5 DOE partners visits to HU, increased visiting faculty participation in BNL-DOE lab, secured 5 grants together totaling 1.2 million in funds for HU). The project objectives were highly successful as they were designed to ambitiously pull together DOE lab researchers with the long-standing and successful transdisciplinary climate science research programs of the PI and local DC groups. The major outcomes of this RDPP program will be in the new fundamentally inclusive partnerships with DOE and HU tasked to understand the urban-rural impacts due to climate change in the US, Eastern South Atlantic (ESA) Region, related to energy issues driven by heat stress and the water cycle. Overall, this project contributes to the DOE and science community vision for catalyze connections for project-ready underrepresented minorities (URMs) at a prominent HBCU to DOE projects supported by the Biological and Environmental research (BER) Program; particularly, the Earth and Environmental Systems Sciences Division (EESSD).

54 ENVIRONMENTAL SCIENCES↗

Assessment Framework of Marine Hydrokinetic Technologies for Microgrid Applications

Communities in Alaska that are not connected to a regional grid (referred to hereafter as grid-islanded Alaskan communities) rely heavily on stand-alone generators with imported diesel fuel as the primary source of energy. Several of these grid-islanded Alaskan communities have the potential to harness significant wave, tidal, and hydrokinetic power; many also have hydropower or wind potential that could complement these resources. The implementation of marine and hydrokinetic energy focused microgrids in these communities would diversify their energy profiles, with the potential in many communities to keep costs flat while reducing dependance on diesel. This would enhance resilience and reduce environmental impacts. This seedling proposal will systematically identify grid-islanded coastal communities in Alaska with wave, tidal, and hydrokinetic energy potential to add fuel diversity to generation, applying microgrid integration methods and strategies that will meet the community’s needs. This proposal is in partnership with the Alaska Center for Energy and Power (ACEP) and XENDEE Corporation who bring extensive expertise in Alaskan communities and microgrid technoeconomic assessment, respectively. This project will deliver: (1) a database of grid-islanded communities that are candidates for MHK based microgrids, (2) an assessment of possible microgrid integration methods and strategies related to tidal, wave, and hydrokinetic technologies, and (3) a MHK development plan for the XENDEE Microgrid design platform and planning tool that can serve these grid-islanded communities and project developers. In the final stage, the planning tool will allow for the comprehensive comparison between diesel based and MHK based renewable generation.

16 TIDAL AND WAVE POWER↗

Lahaina Energy Partnership: Tasks 1-5

The Lahaina Energy Partnership (LEP) is an initiative funded by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) to support energy planning and rebuilding efforts in Hawaii's historic town of Lahaina on Maui as the community recovers from a devastating fire on August 8, 2023, with technical assistance provided by NREL. To inform the scope of technical assistance, NREL has partnered with Hawaii-based community engagement and sustainability-focused organizations to connect with Lahaina residents, business owners to understand the community's energy priorities and vision for the future. This presentation presents a summary of the community's energy priorities and NREL's scope of work for the project, to be completed in early 2027.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗