Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “infrastructure analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

Provenance infrastructure for multimodal x-ray experiments and reproducible analysis

Exploring relationships between material structures and desired properties for material discovery and synthesis requires mining machine-readable databases and linking experimental data with sufficiently rich annotations. There are vast gaps both in these data sources and in the connections between them. We present a provenance-based data management and analysis framework that enables capturing, persisting, and reanalyzing experimental data from the BNL National Synchrotron Light Source II (NSLS-II). Our system leverages NSLS-II Bluesky for experimental data acquisition, captures analysis parameters, and enriches the search space with results from the scientific literature. We describe in detail the challenges and benefits of data-driven approaches when comparing computational and experimental data, such as the multiple possible scenarios of interest in often ill-posed inverse problems and missing data. Our infrastructure utilizes the NSLS-II event model and includes discovery mechanisms across multiple beamlines. A text and data mining module using natural language processing classification techniques extracts relevant information from the literature that is added to data sources. We describe a provenance acquisition and analysis rerun workflow based on a directed acyclic graph that keeps track of process and data provenance and allows to replay analysis.

97 MATHEMATICS AND COMPUTING↗

Regional Supply of Hydrogen

Analysis focuses on support of geographic and temporal distribution of hydrogen demand for light duty vehicle markets in the US. Demand analysis leverages existing hydrogen infrastructure and produces competitive supply chain selection for incremental production, delivery and retail installations from 2020 through 2040. This analysis assesses a novel hydrogen delivery pathway of the Hydrogen Grid, which delivers dispensing pressure hydrogen via intra-city pipelines to retail stations. Modelling leverages NREL's SERA model.

30 DIRECT ENERGY CONVERSION↗

Enhancing Lifeline Infrastructure Resilience

Establish operational critical infrastructure research environment with focus on control systems security Continue enhancement of critical infrastructure cyber-physical interdependency analysis and knowledge management capabilities

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Evolutionary Space Station infrastructure

This paper discusses the approach to Space Station evolution planning and the preliminary analysis of options for the evolution of the infrastructure. The approach emphasizes the analysis of evolution paths, driven by specific user requirements, and evolution modes, i.e., the infrastructure required to support the evolution paths. The objective is to determine the near-term actions that must be taken to protect the future options. These include the identification of evolution 'hooks and scars' on the baseline Space Station and the establishment of an evolution advanced development program. The near term emphasis of the evolution planning is on methods of increasing the efficiency and productivity of the Space Station and on requirements to support new initiatives currently being studied by NASA.

Diaz, Alphonso V.↗

Automated Integration of Continental-Scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interactions

The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new machine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are already building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance.

Durden, David J.↗

A Higher Fidelity Cost Analysis of Wind and Uranium from Seawater Acquisition symbiotic Infrastructure

The vastness of the worlds oceans makes the low concentration of naturally existing uranium, 3.3 ppb, appealing as a recoverable natural resource. Although ample uranium is available currently through conventional means, uranium from seawater is a widely studied topic due to the long term security it can assure the nuclear fuel cycle. It is important to mention that seawater uranium is not meant to act as a direct competitor to terrestrial uranium, but instead create a cost ceiling that provides economic stability and potential savings. Additionally, seawater uranium could circumvent some of the environmental impacts associated with recovery of any land based resource. The system currently studied by a nation-wide consortium of national lab and university partners involves the passive recovery of uranium using polymer based adsorbents. High Density Polyethylene fibers undergo a radiation induced graft co-polymerization process involving amidoxime, to attract uranium, and a polar co-monomer to increase hydrophilicity. After further chemical conditioning adsorbent fibers are braided into 60 meter strands for marine deployment. Braids are moored to the ocean floor for the duration of their soaking campaign. After sufficient seawater exposure they are winched up so the adsorbed uranium may be eluted off the braids. This deployment and elution process is repeated multiple times before the adsorbent's ultimate disposal, where its lifetime is dictated by the degradation it suffers with each re-cycle. Previous economic analyses have identified the adsorbent production and mooring as the most expensive components of the recovery process. Therefore, a later publication by Picard et al. proposed an alternative deployment method in an effort to reduce seawater uranium production cost. The Wind and Uranium from Seawater Acquisition symbiotic Infrastructure (WUSABI) couples uranium recovery with off shore wind to reduce mooring capital cost. The uranium harvesting structure attached to the underwater base of the wind turbine supports elution tanks and an adsorbent pulley system. This allows for a nearly autonomous mooring and elution procedure as adsorbent is in constant motion, reaching the elution tanks at the end of its soaking campaign. Although the original publication did include a short economic section, further analysis was carried out to provide a higher fidelity production cost estimate for uranium recovered by this system. Sufficient detail was provided regarding the capital and operating costs of the novel uranium harvesting units. The adsorbent production and uranium elution and purification steps however were estimated by simpler methods, for example applying a previously reported cost for producing a unit mass of adsorbent. This methodology, although satisfactory for the zeroth-order approximation desired in the original publication, overlooks many of the complexities and feedbacks embedded in the full cost model, which are necessary to provide a more accurate estimate. Perhaps more importantly, given the constant updates regarding adsorbent synthesis and performance this value quickly become outdated. Syncing an improved estimate for the WUSABI harvesting units with the existing economic analysis for adsorbent production and elution, which evolves in tandem with the technology, provides a more robust production cost estimate that will remain current over time. In addition to the updates and higher level of detail provided in this independent analysis, consistency in methodology allows for accurate comparison of uranium production costs across recovery methods. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

Cost Analysis of Wind and Uranium from Seawater Acquisition symbiotic Infrastructure using Shell Enclosures

At current consumption rates, global conventional reserves of uranium, estimated to be 7.6 million tonnes, could be depleted in a little over a century. As these reserves decrease, extraction of uranium is expected to shift to lower quality sites, resulting in higher extraction costs and greater environmental impact. Fortunately, the ocean contains approximately 4.5 billion tonnes of uranium, as uranyl ions at low concentrations of about 3 ppb. Uranium from seawater is a widely studied topic due to the long term security it can assure the nuclear fuel cycle. Additionally, harvesting uranium from seawater could reduce some of the environmental impacts associated with the recovery of land-based uranium. Seawater uranium is meant to create a cost ceiling that provides economic stability and potential savings, not to act as a direct competitor to terrestrial uranium. A recent review of uranium recovery technologies by found uranium adsorption by chelating polymers to be the most promising in terms of adsorbent capacity, environmental footprint, and cost. In this technology, chelating polymers are deployed in seawater and remain submerged until the amount of captured uranium approaches the adsorption capacity. Then, an elution bath is used to strip metal ions, such as uranium, off the adsorbent polymer. A polymer may be immersed in a number of elution baths before it is regenerated by an alkali wash to free its functional groups, allowing for the reuse of the polymer. The output from the elution process undergoes purification and precipitation typical for mined uranium to produce yellowcake. Offshore systems for the extraction of uranium from seawater have been developed since the early 2000's. The system currently studied by a nationwide consortium of national laboratory and university partners utilizes continuous adsorbent polyethylene fibers that are braided around a porous polypropylene float which can be made into long lengths. However, because this deployment scheme requires the adsorbent be brought to a mother-ship for the elution process and redeployed afterward, it has significant practical and economic deployment challenges. Detailed economic analysis have identified the adsorbent production and mooring as the most expensive components of the recovery process. Based on these results, proposed an alternative deployment method that is attached to an offshore wind turbine and continuously takes the adsorbent, that is fabricated into a belt, from the ocean through an elution process and before submerging it back into the sea. However, it has been found that adsorbents with high tensile strength and durability often have very low uranium adsorption properties. Hence, the Wind and Uranium from Seawater Acquisition symbiotic Infrastructure (WUSABI) previously studied, which requires the adsorbent into a belt held in tension, could face difficulties in an ocean environment. Instead, the design, further referred to in this paper as WUSABI-Koosh, utilized a two-part system to decouple the mechanical and chemical needs of an adsorbent for seawater harvesting of uranium. In these designs, the uranium adsorbent material with high adsorbent capacity is enclosed in a hard permeable outer shell with sufficient mechanical strength and durability for use in an offshore environment and chemical resilience against elution treatments. The integration of the design of a uranium harvesting system into an offshore wind turbine tower is pursued because the development of offshore wind or uranium harvesting by themselves bears a high capital cost for the structures, but if the mooring function can be shared, the overall cost for each will be lower. Furthermore, initial design analysis and prototyping of these symbiotic systems has proven they are technically feasible. This paper presents preliminary cost analysis for comparison to uranium recovery via alternative deployment schemes.

07 ISOTOPE AND RADIATION SOURCES↗

Comparing multi-source urban flood indicators: satellite, simulation, and citizen-reported data

Urban flooding arises from complex mechanisms, making it challenging to capture accurately with a single detection method. This study evaluates three complementary approaches to detect flooding across three Chicago neighborhoods: (i) Sentinel-1 synthetic aperture radar (SAR), offering weather-independent, high-resolution (10 m) imagery of surface inundation; (ii) the storm water management model (SWMM), simulating combined sewer overflow and drainage performance; and (iii) citizen-generated 311 service requests, capturing observed flooding impacts. By analyzing six storms ranging from severe to mild, we examine how each source uniquely contributes to identifying urban flood events. SAR imagery effectively identifies standing water but can miss brief flooding due to satellite revisit constraints. SWMM provides detailed insights into system-wide drainage behavior yet may underestimate localized street-level flooding. Meanwhile, 311 calls reflect real-world flooding impacts but are vulnerable to underreporting. Statistical overlap analysis highlights chronic flood hotspots repeatedly identified across multiple detection methods, indicating persistent infrastructure and topographic vulnerabilities. Temporal analysis further reveals that while SWMM flooding aligns closely with rainfall peaks, 311 calls typically precede or persist beyond these peaks. Our findings emphasize the value of using satellite observations, hydrological modeling, and resident-reported data in a complementary manner to better interpret patterns in flood timing, severity, and spatial distribution—providing insights that can inform targeted infrastructure improvements and contribute to urban flood resilience planning.

311↗

Shungnak Energy Configuration Options.

Power systems in rural Alaska villages face a unique combination of challenges that can increase the cost of energy and lowers energy supply reliability. In the case of the remote village of Shungnak, diesel and heating fuel is either shipped in by barge or flown in by aircraft. This report presents a technical analysis of several energy infrastructure upgrade and modification options to reduce the amount of fuel consumed by the community of Shungnak. Reducing fuel usage saves money and makes the village more resilient to disruptions in fuel supply. The analysis considers demand side options, such as energy efficiency, alongside the installation of wind and solar power generation options. Some novel approaches are also considered including battery energy storage and the use of electrical home heating stoves powered by renewable generation that would otherwise be spilled and wasted. This report concludes with specific recommendations for Shungnak based on economic factors, and fuel price sensitivity. General conclusions are also included to support future work analyzing similar energy challenges in remote arctic regions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

High-Performance Computational Modeling of Strong Ground Motion for Seismic Response Analysis with Implications for High-Hazard and/or Nuclear Facilities and Critical Infrastructure at the NNSSNLV-015-19, Year 2

Presentation to be given at the FY 2020 SDRD Annual Meeting, to be held Sept. 23-24, on WebEx. There is one video also attached. This presentation is a reduced slide deck of the recently STIPped version, DOE/NV/03624--0875, presented 9-15-20 at the work in progress seminar. High-Performance Computational Modeling of Strong Ground Motion for Seismic Response Analysis with Implications for High-Hazard and/or Nuclear Facilities and Critical Infrastructure at the NNSSNLV-015-19, Year 2

58 GEOSCIENCES↗

Airport Ground Support Equipment Infrastructure & Logistics Electrification Assessment Tool: 2025 Data Development, Modeling and Analysis for DFW

The aviation industry is increasingly turning to modernize freight facilities by integrating electric Ground Support Equipment (eGSE) to enhance operational efficiency of freight facility moving vehicles and equipment. Airports worldwide are adopting eGSE to streamline cargo movement, reduce fuel and maintenance costs, and improve logistics coordination.1 North America, with its advanced aviation infrastructure, leads this transition, leveraging Internet of things (IoT)-enabled automation and zero emission technologies to boost reliability and reduce human errors.2 Electrification of freight facility moving vehicles and equipment boosts turnaround times, improves equipment reliability, and optimizes logistics coordination, giving operators a competitive advantage. With rising fuel price volatility and the pressure to meet stringent performance benchmarks, airports are focusing on cost-effective, scalable solutions for long-term financial and operational gains. To further accelerate electrification, airports are integrating Zero Emission Vehicles (ZEVs) into rental car fleets and deploying electric baggage carts, requiring strategic investments in charging infrastructure. 3 The shift, however, presents challenges, such as limited technical expertise, high capital costs, and complex procurement processes. By forging strategic partnerships, leveraging advanced technologies, and optimizing infrastructure investments, airports can create a resilient, future-ready ecosystem that enhances the movement of people and goods through electrification-driven efficiency. Supported by the U.S. Department of Energy (DOE) Vehicle Technologies Office (VTO), this electrification effort provides a scalable, cost-effective solution to improve airport freight operations. Through targeted investments and innovation, airports enhance efficiency, reduce costs, and meet performance benchmarks while advancing toward a resilient, electrified future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Compatibility Assessment of Fuel System Thermoplastics with Bio-Blendstock Fuel Candidates Using Hansen Solubility Analysis

The compatibility of key fuel system infrastructure plastics with 39 bio-blendstock fuel candidates was examined using Hansen solubility analysis. Fuel types included multiple alcohols, esters, ethers, ketones, alkenes and one alkane. These compounds were evaluated as neat molecules and as blends with the gasoline surrogate, dodecane, and a mix of dodecane and 10% ethanol (E10D). The plastics included polyphenylene sulfide (PPS), polyethylene terephthalate (PET), polytetrafluoroethylene (PTFE), polyvinylidene fluoride (PVDF), polyoxymethylene (POM), polybutylene terephthalate (PBT), polypropylene (PP), high density polyethylene (HDPE), along with several nylon grades. These materials have been rigorously studied with other fuel types, and their volume change results were found to correspond well with their predicted solubility levels.The compatibility was assessed using Hansen solubility parameters and in many instances peak solubility occurred for blends rather than the neat fuel components. The results showed that good compatibilities can be expected for PPS, PVDF, PET, nylons, acetal, PEI, PVC, HDPE and PBT. PTFE showed potential incompatibilities at low blend concentrations, especially when E10D was used as the base fuel blend. Although, the nylons show good overall compatibility, the results do indicate that mid-range and high alcohol contents may not be suitable for Nylon 6 and Nylon 11 in applications requiring low volume swell. Poor potential compatibility was limited to two plastic types; PETG exposed to mid and high blend levels of the ethers and PP exposed to sabinene and the aromatics. In general, the data showed good compatibility for the majority of the candidate fuels and plastics.

09 BIOMASS FUELS↗

New EVSE Analytical Tools/Models: Electric Vehicle Infrastructure Projection Tool (EVI-Pro)

This presentation addresses the fundamental question of how much charging infrastructure is needed in the United States to support PEVs. It complements ongoing EVSE initiatives by providing a comprehensive analysis of national PEV charging infrastructure requirements. The result is a quantitative estimate for a U.S. network of non-residential (public and workplace) EVSE that would be needed to support broader PEV adoption. The analysis provides guidance to public and private stakeholders who are seeking to provide nationwide charging coverage, improve the EVSE business case by maximizing station utilization, and promote effective use of private/public infrastructure investments.

30 DIRECT ENERGY CONVERSION↗

Integration of Experimental Hydroprocessing and FCC Data with Process (Aspen Plus) and Refinery Optimization (Aspen PIMS) Models

NREL's Economic, Sustainability, and Market Analysis (ESMA) team develops process models in Aspen Plus to support techno-economic analysis (TEA) and life-cycle assessment (LCA) of conversion pathways from renewable and circular resources to fuels and chemicals. These tools are being applied to assess probable operational constraints or bottlenecks associated with refinery co-processing and repurposing opportunities. The team also utilizes optimizable refinery models to quantify opportunities for biofuel and bioproduct pathways through integration with existing refining infrastructure. The goals of analysis are to model the transition of refineries to renewable and circular feedstocks and quantify the costs production and CO2 abatement through utilization of existing refineries. At the core of the ESMA team's work is the process data derived from conversion experiments on hydroprocessing and fluid catalytic cracking performed at NREL. The objective of this presentation is to highlight new analysis approaches and capabilities in pathway analysis and refinery optimization modeling with specific emphasis on integration of experimental data.

BIOMASS FUELS,ENERGY PLANNING, POLICY, AND ECONOMY↗

An Application of Faster R-CNNs in Object Detection Efforts Applied to the Critical Infrastructure Domain

Object detection and segmentation approaches have been successfully applied to multiple interdisciplinary domains ranging from medical imaging to autonomous vehicles. The following study details efforts to apply segmentation methods to the critical infrastructure domain. Specifically, the identification of critical sub-components of four facilities: airports, hospitals, hydroelectric dams, and water treatment plants. Data for this study was extracted from the U.S. Department of Agriculture’s National Agriculture Imagery Program data set. Each facility class was considered independently of the other facilities, producing four different segmentation models during the testing and training process. Ultimately, the study team concluded there are significant challenges associated with object detection modeling when applied to facility analysis within the critical infrastructure domain. The study team was able to identify possible sources of these challenges that could be potentially addressed in future work.

97 MATHEMATICS AND COMPUTING↗

Optimization of Energy Flow through Synthetic Metabolic Modules and Regulatory Networks in a Model Photosynthetic Eukaryotic Microbe

Photosynthetic organisms have recently gained considerable attention for a role in development of renewable energy sources. Genome-enabled systems biology methods, coupled with functional and synthetic genomics, present opportunities to develop sustainable and economical applications such as fuel production within the next 10 to 15 years. However, optimization of light-driven metabolism for biomass or biofuel production will require a detailed systems biology understanding of photosynthetic processes and cellular metabolism. Genome-scale metabolic models (GEMs) are at the core of systems analysis of cellular processes and form a common organizational framework for analyses of data resulting from functional genomics experimental work and computational studies. Therefore, there is a clear demand for high quality photosynthetic model organisms and the appropriate computational tools that enable systems analysis of light-driven metabolism. Through research conducted we expanded the currently available repertoire of photosynthetic GEMs to include the commercially valuable model diatom Phaeoctylum tricornutum. Diatoms have a peculiar and distinct evolutionary footprint and represent a major eukaryotic lineage that is taxonomically and functionally distinct from green and red algae and vascular plants. Therefore, the true potential for light-driven metabolism aimed at biofuel production remains poorly understood at a systems level for a large subset of the global diversity of photosynthetic organisms. The metabolic capabilities of P. tricornutum were comparatively modeled with those from other photosynthetic groups in order to elucidate the occurrence of metabolic traits within and between phototrophs. Additionally, this research resulted in significant extension of the COnstraints Based Reconstruction and Analysis (COBRA) Toolbox to accommodate the crucial need for infrastructure required for ‘omics data integration and analysis in the context of genome-scale models. Therefore, the proposed research achieved two important goals. First, within the broad scope of photosynthetic organisms, we functionally compared and, as a result, identified cellular processes that require optimization in order to enable deployment as biofuel feedstock. Second, the proposed research resulted in development of key computational infrastructure, which can be further extended to other biological systems, that is currently lacking but necessary for multiple ‘omics data integration.

59 BASIC BIOLOGICAL SCIENCES↗

Observing and modeling the effects of production infrastructure in electromagnetic surveys

Electromagnetic (EM) methods are among the original techniques for subsurface characterization in exploration geophysics because of their particular sensitivity to the earth electrical conductivity, a physical property of rocks distinct yet complementary to density, magnetization, and strength. However, this unique ability also makes them sensitive to metallic artifacts — infrastructure such as pipes, cables, and other forms of cultural clutter — the EM footprint of which often far exceeds their diminutive stature when compared to that of bulk rock itself. In the hunt for buried treasure or unexploded ordnance, this is an advantage; in the long-term monitoring of mature oil fields after decades of production, it is quite troublesome indeed. In this study we consider the latter through the lens of an evolving energy industry landscape in which the traditional methods of EM characterization for the exploration geophysicist are applied toward emergent problems in well-casing integrity, carbon capture and storage, and overall situational awareness in the oil field. We introduce case studies from these exemplars, showing how signals from metallic artifacts can dominate those from the target itself and impose significant burdens on the requisite simulation complexity. Furthermore, we show how recent advances in numerical methods mitigate the computational explosivity of infrastructure modeling, providing feasible and real-time analysis tools for the desktop geophysicist. Lastly, we demonstrate through comparison of field data and simulation results that incorporation of infrastructure into the analysis of such geophysical data is, in a growing number of cases, a requisite but now manageable step.

58 GEOSCIENCES↗