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At least 163 records · Page 9

Design and permitting considerations of a floating hydrogen production and dispensing Barge for the Port of San Francisco

This paper reports on the design of a Floating Hydrogen Production and Dispensing Barge destined for the Port of San Francisco (SF). The H 2 Barge is designed to produce renewable H 2 at the rate of ∼530 kg/day, storing 512 kg of hydrogen at 517-bar, allowing fast refueling of hydrogen fuel cell vessels and land-side hydrogen delivery trailers for distribution into the nascent SF hydrogen ecosystem. The broader considerations that impacted H 2 Barge design are also described. An account is given of a new review process formulated by the United States Coast Guard (USCG) to review this first-of-its-kind maritime implementation of hydrogen technology. Furthermore, the immediate goals of the H 2 Barge Project are to 1) demonstrate the feasibility, viability and methods of hydrogen production, storage and fueling in a maritime context, 2) help shape (where needed) and navigate the required local, state and federal regulatory gauntlet and 3) catalyze a “green hydrogen ecosystem” (both marine and landside) with locally produced renewable hydrogen at the San Francisco waterfront.

08 HYDROGEN↗

Exploration Medical System Trade Study Tools Overview

ExMC is creating an ecosystem of tools to enable well-informed medical system trade studies. The suite of tools address important system implementation aspects of the space medical capabilities trade space and are being built using knowledge from the medical community regarding the unique aspects of space flight. Two integrating models, a systems engineering model and a medical risk analysis model, tie the tools together to produce an integrated assessment of the medical system and its ability to achieve medical system target requirements. This presentation will provide an overview of the various tools that are a part of the tool ecosystem. Initially, the presentation's focus will address the tools that supply the foundational information to the ecosystem. Specifically, the talk will describe how information that describes how medicine will be practiced is captured and categorized for efficient utilization in the tool suite. For example, the talk will include capturing what conditions will be planned for in-mission treatment, planned medical activities (e.g., periodic physical exam), required medical capabilities (e.g., provide imaging), and options to implement the capabilities (e.g., an ultrasound device). Database storage and configuration management will also be discussed. The presentation will include an overview of how these information tools will be tied to parameters in a Systems Modeling Language (SysML) model, allowing traceability to system behavioral, structural, and requirements content. The discussion will also describe an HRP-led enhanced risk assessment model developed to provide quantitative insight into each capability's contribution to mission success. Key outputs from these various tools, to be shared with the space medical and exploration mission development communities, will be assessments of medical system implementation option satisfaction of requirements and per-capability contributions toward achieving requirements.

Mindock, J.↗

All Systems Go: Regional Collaborations for Scaling AEC Innovation: Preprint

The high and rising cost of preserving and delivering housing in the U.S. requires changes to existing practices of finance, design, and construction. Innovative methods such as industrialized construction could offer the means to address housing undersupply while reducing delivery costs, operational costs and material waste in the building industry, but they face challenges to success and to scale. Simultaneously, construction and cleantech innovators themselves face skepticism from the traditional entrepreneurial ecosystem such as incubators and accelerators while attempting to navigate systems level challenges. To respond to this need, various public and private sector stakeholders have launched initiatives to support innovative companies. These include nonprofits such as Terner Labs and Ivory Innovations offering curated programming to architecture, engineering, and construction (AEC) startups; housing developers in Minnesota and California "bundling" multiple projects together to reach economies of scale with a consistent project team; public and private sector entities developing "catalogues" of pre-approved home designs in the U.S. and Canada. This exploratory paper documents several of these emerging ecosystem-development efforts to support innovative housing approaches, characterizing them by leading stakeholder and intervention strategy based on publicly available information. The paper finds that these initiatives share similar high level goals but vary in implementation, reflecting different stakeholder priorities, regional market and policy dynamics, and housing typologies. The early stage of these efforts offer limited data for comparing actual outcomes, but the paper highlights common qualitative themes and identifies opportunities for further research and potential coordination among these efforts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dependable classical-quantum computing systems engineering

Increasing evidence suggests quantum computing (QC) complements traditional High-Performance Computing (HPC) by leveraging its unique capabilities, leading to the emergence of a new, hybrid paradigm, QHPC. However, this integration introduces new challenges, with dependability–defined by reproducibility, resiliency, and security and privacy–emerging as a central concern for building trustworthy systems that provide an advantage to the users. This paper proposes a framework for dependable QHPC system design, organized around these three pillars. We identify integration challenges, anticipate roadblocks, and highlight productive synergies across QC, HPC, cloud platforms, and network security. Drawing from both classical computing principles and quantum-specific insights, we present a roadmap for co-design that supports robust hybrid architectures. Our approach offers concrete metrics for assessing dependability, provides design guidance for engineers working at the QC-HPC interface, and surfaces new engineering questions around complexity, scale, and fault tolerance. Ultimately, designing for dependability is key to realizing practical, scalable QHPC systems and accelerating the broader quantum ecosystem capable of translating quantum promises into actual application delivery.

HPC↗

Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a Systems Model

One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must trade between time and cost for analysis quality and quantity. The quality often correlates with greater run time in multidisciplinary models and the quantity is associated with the number of alternatives that can be analyzed. The trade-off is due to the resource intensive process of creating a cohesive multidisciplinary systems model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than hand-written translation scripts between multi-disciplinary models and their analyses. The key is to work from a core systems model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query/View/Transformation (QVT), from the OMG community. SysML was designed to model multidisciplinary systems. The QVT standard was designed to transform SysML models into other models, including those leveraged by engineering analyses. The Europa Habitability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, symbolic analysis (supported by Wolfram Mathematica) is coordinated by data objects transformed from the systems model, enabling extremely flexible and powerful design exploration and analytical investigations of expected system performance.

Operational QVT↗

Grid Communications Supply Chain & Emerging Regulation Challenges Session 1

The TADA Grid Communications Workshops are designed to strengthen cybersecurity and digital assurance across the energy sector by focusing on secure deployment and management of grid communications technologies. These workshops bring together state energy offices, utilities, and technology suppliers to explore the intersection of communications infrastructure, supply chain risks, and emerging regulatory requirements. Participants will apply Cyber-Informed Engineering (CIE) principles to reduce risks in communications systems, engage with INL’s procurement guidance, and explore future tools. Through scenario-based exercises and peer exchange, attendees will develop risk-based security strategies and actionable compliance roadmaps tailored to their grid communications projects. The workshops also help participants navigate evolving regulatory frameworks such as FEOC rules in the OBBB, NERC CIP-013, and NDAA 2024, while identifying compliance gaps in mixed-technology environments. A key outcome is the formation of a practitioner network with ongoing access to INL expertise and resources, fostering long-term resilience in the digital energy ecosystem.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Evaluating SAR Radiometric Terrain Correction Solutions: Optimal products for applied users

Operational applications of Synthetic Aperture Radar (SAR) are under development around the world, driven by the regularly-acquired, free-and-open source C-band SAR observations provided by ESA’s Sentinel-1 sensor constellation since 2014. Groups like SERVIR, a joint NASA and USAID initiative, are at the forefront of remote sensing applications for societal benefit. A takeaway from SERVIR’s experience is the need for appropriately geocoded and fully calibrated SAR data that is ready to use for a range of ecosystems-related applications. Radiometric Terrain Corrected (RTC) data are key entry-level products for multiple applications that range from ecosystems to hazards. This work fills a gap in current research by evaluating several RTCs produced by open-source software solutions (SNAP-7 and ISCE-2), the gold standard commercial software (GAMMA), a Google Earth Engine (GEE) based workflow, and the uncorrected GRD products currently available in GEE. RTCs were analyzed for geolocation quality, absolute radiometric calibration, and fidelity of the radiometric terrain flattening over ten sites representing varied terrains. In addition, a time series analysis was conducted over two locations. Overall, no significant differences for radiometric calibration were found across RTC products. However, all RTCs performed better than uncorrected GRD products. The main differences between products were found in geolocation quality. These results not only demonstrate the need for the uptake and distribution of RTC products for ecosystems applications, but demonstrate the ability to do so with open source methods, adding value to developing affordable operational applications.

Helen Blue Parache↗

Climate change challenges, plant science solutions

Abstract Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Artificial Intelligence and Digital Engineering as Enablers for System Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.

42 - ENGINEERING↗

Artificial Intelligence and Digital Engineering as Enablers for Systems Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world?s energy demands and build energy security.

42 - ENGINEERING↗

NASA GRC ICME Schema for Materials Data Management: An Executive Summary

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

Materials↗

Three-Dimensional Grid Visualization for Planning Activities: A Dubai Case Study

National Laboratory of the Rockies (NLR), in collaboration with the Dubai Electricity and Water Authority (DEWA) and Infra-X, has undertaken the Energy Visualization Analysis Project. The aim of this project is to enhance analytical and 3D visualization capabilities for distribution network planning and renewable energy integration. As modern grid continues to evolve with large-scale solar PV deployment and emerging distributed energy resources (DERs), the ability to effectively analyze, visualize, and communicate complex grid behaviors has become increasingly critical. The project focuses on developing empirical use cases based on real distribution feeder data and engineering workflows, ensuring the outcomes are directly aligned with operational environment. Through time-series power flow simulations and nodal hosting capacity analysis, the study quantifies the impacts of high PV penetration on voltage and thermal limits within representative 11 kV feeders. These analyses identify specific nodes and conditions where DER integration challenges arise. Furthermore, a Battery Energy Storage System (BESS) optimization algorithm was applied to determine the optimal size and placement of storage systems that can mitigate network constraints and enhance hosting capacity. The comparative results between base-case and BESS-augmented scenarios clearly demonstrate improvements in network stability and load management efficiency. In parallel, the NLR team developed an immersive 3D visualization framework, enabling interactive exploration of grid simulations using commodity head-mounted display (HMD) systems. This framework transforms conventional 2D simulation data into spatially intuitive visual environments - allowing engineers to analyze feeder conditions, PV hosting potential, and BESS effects in real time. This report represents the first foundational phase in establishing a visualization-driven analytical ecosystem. It provides a methodological foundation for data integration, visualization architecture, and simulation-based decision support, paving the way for large-scale adoption of immersive visualization across DEWA's Smart Grid Initiative, R&D activities, and future network resilience studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Drivers of stability and transience in composition-functioning links during serial propagation of litter-decomposing microbial communities

ABSTRACT Biotic factors that influence the temporal stability of microbial community functioning are an emerging research focus for the control of natural and engineered systems. The discovery of common features within community ensembles that differ in functional stability over time is a starting point to explore biotic factors. We serially propagated a suite of soil microbial communities through five generations of 28-day microcosm incubations to examine microbial community compositional and functional stability during plant litter decomposition. Using dissolved organic carbon (DOC) abundance as a target function, we hypothesized that microbial diversity, compositional stability, and associated changes in interactions would explain the relative stability of the ecosystem function between generations. Communities with initially high DOC abundance tended to converge towards a “low DOC” phenotype within two generations, but across all microcosms, functional stability between generations was highly variable. By splitting communities into two cohorts based on their relative DOC functional stability, we found that compositional shifts, diversity, and interaction network complexity were associated with the stability of DOC abundance between generations. Further, our results showed that legacy effects were important in determining compositional and functional outcomes, and we identified taxa associated with high DOC abundance. In the context of litter decomposition, achieving functionally stable communities is required to utilize soil microbiomes to increase DOC abundance and long-term terrestrial DOC sequestration as one solution to reduce atmospheric carbon dioxide concentrations. Identifying factors that stabilize function for a community of interest may improve the success of microbiome engineering applications. IMPORTANCE Microbial community functioning can be highly dynamic over time. Identifying and understanding biotic factors that control functional stability is of significant interest for natural and engineered communities alike. Using plant litter–decomposing communities as a model system, this study examined the stability of ecosystem function over time following repeated community transfers. By identifying microbial community features that are associated with stable ecosystem functions, microbial communities can be manipulated in ways that promote the consistency and reliability of the desired function, improving outcomes and increasing the utility of microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

Potential use of engineered nanoparticles in ocean fertilization for large-scale atmospheric carbon dioxide removal

Artificial ocean fertilization (AOF) aims to safely stimulate phytoplankton growth in the ocean and enhance carbon sequestration. AOF carbon sequestration efficiency appears lower than natural ocean fertilization processes due mainly to the low bioavailability of added nutrients, along with low export rates of AOF-produced biomass to the deep ocean. Here we explore the potential application of engineered nanoparticles (ENPs) to overcome these issues. Data from 123 studies show that some ENPs may enhance phytoplankton growth at concentrations below those likely to be toxic in marine ecosystems. ENPs may also increase bloom lifetime, boost phytoplankton aggregation and carbon export, and address secondary limiting factors in AOF. Life-cycle assessment and cost analyses suggest that net CO 2 capture is possible for iron, SiO 2 and Al 2 O 3 ENPs with costs of 2–5 times that of conventional AOF, whereas boosting AOF efficiency by ENPs should substantially enhance net CO 2 capture and reduce these costs. Therefore, ENP-based AOF can be an important component of the mitigation strategy to limit global warming.

54 ENVIRONMENTAL SCIENCES↗

Leveraging High Resolution Remotely Sensed Evapotranspiration Data to Assess Water Availability and Vulnerability in the Memphis Aquifer Area in West Tennessee

The Memphis aquifer is an indispensable source of water for municipal, agricultural, and industrial use across west Tennessee. The aquifer's water is thousands of years old and in pristine condition due to the natural geological filtering by the aquifer’s confining clay layers. To sustain the aquifer’s water supply, recharge must happen at a rate efficient enough to keep up with pumping from the aquifer. In partnership with Protect Our Aquifer and the University of Memphis Center for Applied Earth Science and Engineering Research, this project examined multiple factors to discover thriving areas of recharge in west Tennessee. The team used Integrated Multi-satellite Retrievals for GPM (IMERG) precipitation data, ECOsystem Spaceborne Thermal Radiometer on Space Station (ECOSTRESS) evapotranspiration data, Landsat 8 and National Land Cover Database (NLCD) to track landcover change, and the North American Land Data Assimilation System (NLDAS) Noah land surface model to estimate monthly runoff. These factors were averaged seasonally from 2019 to 2022 to understand seasonal relationships within the study area. Precipitation and evapotranspiration data were used to create water balance maps and with the evaporative stress index (ESI), landcover, and runoff maps, the team pinpointed locations that are most conducive to recharge. The team determined that areas where the water balance is low, ESI is high, and where there is sufficient pervious landcover are locations where recharge happens most effectively. Identification of effective recharge locations may be used by the partners to prioritize areas in need of protection before they become impacted by industrialization and urbanization.

Lauren Webster↗

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study include: CA-OAS, CA-OBS, US-NR1, US-TON, US-VAR, US-SRM, US-WHS, US-WKG. Snotel sites Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP) are included as well 16 east river locations with different vegetation types denoted by evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed Fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO). Trained models and metrics for parameters for the Fluxnet sites were added in an update on November 2, 2020; 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. NDVI datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

54 ENVIRONMENTAL SCIENCES↗