WFIP3 - SHIP site - NREL Scanning Lidar (StreamLine XR+ #235) / Processed Data
This dataset contains processed data from NREL's Halo XR+ scanning lidar at WFIP3's SHIP site.
17 WIND ENERGY↗
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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.
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WREF Halo Streamline scanning lidar / Derived data / RHI
This dataset contains streamwise velocity retrieved from the Range Height Indicator (RHI) scans done by the UC Davis scanning Lidar. The quality control of the radial wind speed is performed following the algorithm of Beck & Kuhn (2017). Instantaneous realizations characterized by wind misalignment greater than 60 degrees (based on the closest VAD scan in time) are discarded.
17 WIND ENERGY↗
WREF Halo Streamline scanning lidar / Derived data / High-frequency wind profiles
This dataset contains wind profiles retrieved from 6-beam Velocity Azimuth Display (VAD) scans done by the UC Davis scanning Lidar. The wind components (expressed as zonal, meridional and vertical) are retrieved through the algorithm of Paschke et al. (2015). The quality control of the radial wind speed is performed following the algorithm of Goring & Nikora (2002).
17 WIND ENERGY↗
tRNA Fusion to Streamline RNA Structure Determination: Case Studies in Probing Aminoacyl-tRNA Sensin
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Grigg, Jason C.↗
A Multi-Streamline Approach for Upcycling PET into a Biodiesel and Asphalt Modifier
The non-degradable nature of petroleum-based plastics and the dependence on petroleum-based products in daily life and production are dilemmas of human development today. We hereby developed a plastic waste upcycling process to address these challenges. A multi-stream fraction strategy was developed to process poly (ethylene terephthalate) (PET) plastics into soluble and insoluble fractions. The soluble fraction was used as a sole carbon source for microbial fermentation to produce biodiesel precursor lipids with an appreciable bioconversion yield. The insoluble fraction containing fractionated polymers was used as the asphalt binder modifiers. The downsized PET additive improved the high-temperature performance of the asphalt binder by 1 performance grade (PG) without decreasing the low-temperature PG. Subsequent SEM imaging unveiled alterations in the micromorphology induced by PET incorporation. Further FTIR and 1 H NMR analysis highlighted the aromatic groups of PET polymers as a crucial factor influencing performance enhancement. The results demonstrated the multi-stream fraction as a promising approach for repurposing plastic waste to produce biodiesel and modify asphalt. Finally, this approach holds the potential to tackle challenges in fuel supply and enhance infrastructure resilience to global warming.
09 BIOMASS FUELS↗
Grid Code Essentials and Streamlining Process for Interconnections
This presentation was part of a webinar entitled "A Practitioner's Guide to Implementing Solar Rooftop Programs and Navigating Net-Metering Policies," hosted by USAID Clean Power Asia and included speakers the Hawaii Natural Energy Institute as well as NREL. This presentation outlines grid codes in general, and IEEE Std 1547-2018 specifically, and discusses their adoption into interconnection requirements. Key capabilities, now enabled by IEEE Std 1547-2018, such as voltage regulation and frequency ride-through are described.
DER↗
Streamlining Energy Sprawl: Assessment of Geothermal Impacts on Public Lands
Renewable energy power generation, including geothermal, solar photovoltaics (PV), and wind, can have significant land use impacts depending on the technology and the size of the facility. At the same time, innovations across these renewable technologies are working to improve plant efficiency per acre of disturbance. Through a survey of satellite imagery and other sources, this analysis reevaluates the impact of geothermal power generation and examines the variations in land use for different geothermal technologies (binary, flash, and dry steam). Geothermal operations on Bureau of Land Management (BLM) sites serve as the focus for this analysis - i.e., only active sites with federal mineral ownership for which the BLM receives royalties from power production. The results show significant variation in direct land disturbance across the operations sites and across these three geothermal technologies. Although there is variation across plants within the same geothermal technology category, dry steam plants (The Geysers) were shown to have the lowest impact, in acres per megawatt capacity and acres per gigawatt-hour generation, followed by flash steam and binary plants. Overall, direct land impacts relative to capacity and generation have declined 16-27% for facilities constructed since 2000 as compared to those constructed prior, even though most new facilities are binary plants (which traditionally had higher land disturbance). Additionally, capacity factors based on actual net production data were found to average only 50% across all operations sites, suggesting that previous estimates based on nameplate capacity only may lead to an undercounting of generation-based land disturbance metrics. Should the geothermal industry capture additional market share, improving land disturbance metrics through accurate net production and capacity data and further minimizing impacts will be increasingly important as competition over land use intensifies.
GEOTHERMAL ENERGY↗
Survey of Seed Placement and Streamline Selection Techniques
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Bujack, Roxana Barbara↗
AN ISOGEOMETRIC APPROACH TO STREAMLINING HIGH-END STRUCTURAL DYNAMICS SIMULATION FOR AUTOMOTIVE AND OTHER APPLICATIONS
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42 ENGINEERING↗
PVDeg: Development of a Streamlined Tool for PV Degradation Modeling
The photovoltaic (PV) industry constantly aims for lower costs, higher-efficiency cells, and improved module designs. These trends lead to using new materials, designs, and manufacturing processes, resulting in a continually changing technological landscape. These changes can potentially introduce new, unknown degradation mechanisms and failure modes that are difficult to diagnose, analyze, test, and model. This introduces uncertainty into the expected lifetime of PV modules of 25 to 50 years. research efforts aim to achieve this while keeping performance degradation at a minimum for decades. This puts considerable pressure on improving the accuracy of long-term durability and reliability assessments. There is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. Because the core of this type of analysis involves calculations that are complicated but ubiquitous for many degradation processes, an enhanced predictive modeling framework will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this work, we present an online tool that can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. The tool will simplify many of the routine computational operations that are common to many degradation studies. The prediction tool will be built modular and published as open source, enabling users to expand on the existing framework. This repository will contain various degradation models and material parameters suitable for the reliability and durability assessment of materials and components deployed outdoors.
degradation↗
Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)
We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.
02 PETROLEUM↗
Accretion of Gas Giants Constrained by the Tidal Barrier
After protoplanets have acquired sufficient mass to open partial gaps in their natal protostellar disks, residual gas continues to diffuse onto horseshoe streamlines under the effect of viscous dissipation, and to meander in and out of the planets' Hill sphere. Within the Hill sphere, the horseshoe streamlines intercept gas flow in circumplanetary disks. The host star's tidal perturbation induces a barrier across the converging streamlines' interface. Viscous transfer of angular momentum across this tidal barrier determines the rate of mass diffusion from the horseshoe streamlines onto the circumplanetary disks, and eventually the accretion rate onto the protoplanets. Here, we carry out a series of numerical simulations to test the influence of this tidal barrier on superthermal planets. In weakly viscous disks, the protoplanets' accretion rate steeply decreases with their masses above the thermal limit. As their growth timescale exceeds the gas depletion timescale, their masses reach asymptotic values comparable to that of Jupiter. In relatively thick and strongly viscous disks, protoplanets' asymptotic masses exceed several times that of Jupiter. Two-dimensional numerical simulations show that such massive protoplanets strongly excite the eccentricity of nearby horseshoe streamlines, destabilize orderly flow, substantially enhance the diffusion rate across the tidal barrier, and elevate their growth rate until their natal disk is severely depleted. In contrast, eccentric streamlines remain stable in three-dimensional simulations. Based on the upper falloff in the observed mass distribution of known exoplanets, we suggest that their natal disks had relatively low viscosity (α ~ 10 –3 ) and modest thickness (H/R ~ 0.03–0.05).
79 ASTRONOMY AND ASTROPHYSICS↗
Influence of pilot-fuel mixing on the spatio-temporal progression of two-stage autoignition of diesel-sprays in low-reactivity ambient fuel-air mixture
The spatial and temporal locations of autoignition for direct-injection compression-ignition engines depend on fuel chemistry, temperature, pressure, and mixing trajectories in the fuel jets. Dual-fuel systems can provide insight into both fuel-chemistry and physical effects by varying fuel reactivities and engine operating conditions. In this context, the spatial and temporal progression of two-stage autoignition of a diesel-fuel surrogate, n-heptane, in a lean-premixed charge of synthetic natural-gas (NG) and air is imaged in an optically accessible heavy-duty diesel engine. The lean-premixed charge of NG is prepared by fumigation upstream of the engine intake manifold. Optical diagnostics include high-speed (15kfps) cool-flame chemiluminescence-imaging as an indicator of low-temperature heat-release (LTHR) and OH* chemiluminescence-imaging as an indicator high-temperature heat-release (HTHR). NG prolongs the ignition delay of the pilot fuel and increases the combustion duration. Zero-dimensional chemical-kinetics simulations provide further understanding by replicating a Lagrangian perspective for mixtures evolving along streamlines originating either at the fuel nozzle or in the ambient gas, for which the pilot-fuel concentration is either decreasing or increasing, respectively. The zero-dimensional simulations predict that LTHR initiates most likely on the air streamlines before transitioning to HTHR, either on fuel-streamlines or on air-streamlines in regions of near-constant φ. Due to the relatively short pilot-fuel injection-durations, the transient increase in entrainment near the end of injection (entrainment wave) is important for quickly creating auto-ignitable mixtures. To achieve desired combustion characteristics, e.g., multiple ignition-kernels and favorable combustion phasing and location (e.g., for reducing wall heat-transfer or optimizing charge stratification), adjusting injection parameters could tailor mixing trajectories to offset changes in fuel ignition chemistry.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
EMPOWERED Distributed Energy Resources Permit Accelerator Pilot
This report summarizes the EMPOWERED Distributed Energy Resources (DER) Permit Accelerator Pilot project. Its primary objective was to streamline the design, installation, permitting, and inspections of targeted Distributed Energy Resource (DER) solutions. Streamlining these processes is critical to strengthening and accelerating the adoption of DER solutions nationwide. Moreover, streamlined processes help expedite the clean energy transition and expand energy resilience by improving understanding and capability among key stakeholders like property owners, code officials, and the general workforce. The project team accomplished this by developing and deploying a set of design and permitting guides for simple DER solutions, which they rolled out via a permitting pilot program. The project team developed nine permitting and inspection guides for simple DER solutions, as follows: 1. Single-Family and Duplex: Electric Vehicle Service Equipment (EVSE), and Storage, Solar + Storage (each in two code cycles) 2. Multi-family and Office: EVSE, Storage, Solar + Storage (each in two code cycles) 3. A permitting process guide to support the implementation of the permitting guides. The guides cover key code requirements via plan review and field inspection checklists for code officials and building owners to follow to streamline the permitting and inspections process for DER solutions. Following the development of the initial set of guides, the project team formed two cohorts, each made up of four jurisdictions, to participate in the Permit Accelerator Pilot. Each cohort received training and technical assistance to support them in incorporating the guides into use. The project successfully engaged jurisdictions in two disparate US regions: Chelsea, Somerville, Natick, and Norwood in metro Boston; and Pima County, Town of Gilbert, Flagstaff, and Sedona in Arizona. Feedback gathered from the project was valuable in refining the guides to better address jurisdictional needs. After the pilot period, the project team developed final versions of the guides based on extensive feedback from the cohorts and from external technical peer review. Feedback included needs and barriers related to implementation, as well as detailed technical improvements from external peer review. The final guides were presented in a series of webinars with a national reach, with 192 attendees from 35 states in the live session of the final webinar, and the final guides are posted online and available for use nationwide. Key findings: • The most receptive jurisdictions were those adjacent to other jurisdictions that had already adopted similar initiatives. The least receptive jurisdictions were those in the midst of adopting new code cycles. • The most common barrier to jurisdictional adoption of new guidelines were internal administrative and process delays, more so than technical barriers. • The main technical barrier to adoption proved to be the concern of fire hazard risks posed by energy storage systems. There is some apprehension in the code enforcement community about the safety of the batteries. Education coordinated with fire and safety services will help alleviate concerns and increase confidence in the acceptance of innovative technologies. • Opportunities to further leverage and advance the guides and related resources include outreach, education, and jurisdictional support; updates to the resources to align with code cycle changes and local requirements; and advancements supporting emerging technologies.
14 SOLAR ENERGY↗
The Case for Optimized Edge-Centric Tractography at Scale
The anatomic validity of structural connectomes remains a significant uncertainty in neuroimaging. Edge-centric tractography reconstructs streamlines in bundles between each pair of cortical or subcortical regions. Although edge bundles provides a stronger anatomic embedding than traditional connectomes, calculating them for each region-pair requires exponentially greater computation. We observe that major speedup can be achieved by reducing the number of streamlines used by probabilistic tractography algorithms. To ensure this does not degrade connectome quality, we calculate the identifiability of edge-centric connectomes between test and re-test sessions as a proxy for information content. We find that running PROBTRACKX2 with as few as 1 streamline per voxel per region-pair has no significant impact on identifiability. Variation in identifiability caused by streamline count is overshadowed by variation due to subject demographics. This finding even holds true in an entirely different tractography algorithm using MRTrix. Incidentally, we observe that Jaccard similarity is more effective than Pearson correlation in calculating identifiability for our subject population.
59 BASIC BIOLOGICAL SCIENCES↗
Inter-well connectivity detection in CO 2 WAG projects using statistical recurrent unit models
Routine well-wise injection and production measurements contain significant information on subsurface structure and properties. Data-driven technology that interprets surface data into subsurface structure or properties can assist operators in making informed decisions by providing a better understanding of field assets. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO 2 EOR projects utilizing the water-alternating-gas (WAG) process. SRU is a special type of recurrent neural network (RNN) that allows for better characterization of temporal trends, by learning various statistics of the input at different time scales. In our application, the complete states (injection rate, pressure and cumulative injection) at injectors and pressure states at producers are fed to SRU as the input and the phase rates at producers are treated as the output. Once the SRU is trained and validated, it is then used to assess the connectivity of each injector to any producer using permutation variable importance method, wherein inputs corresponding to an injector are shuffled and the increase in prediction error at a given producer is recorded as the importance (connectivity metric) of the injector to the producer. This method is tested in both synthetic and field-scale cases. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. This significantly improves confidence in our data-driven procedure. The novelty of this work is that it is purely data-driven method and can directly interpret routine surface measurements to intuitive subsurface knowledge. Furthermore, the streamline-based validation procedure provides physics-based backing to the results obtained from data analytics. This study results in a reliable and efficient data analytics framework that is well-suited for large field applications.
42 ENGINEERING↗
Steady detonation propagation in thin channels with strong confinement
We examine asymptotically the dynamics of two-dimensional, steady detonation wave propagation and failure for a strongly confined high explosive (HE), in which the width of the explosive is small relative to the reaction zone length. An energy balance equation is derived, which shows how the longitudinal acceleration of subsonic flow behind the detonation shock is influenced both by chemical reaction and by the effects of HE boundary streamline deflection, specifically via the induced rate of change of mass flux through the detonation wave. The latter serves to either counteract or reinforce the acceleration of longitudinal flow, depending on the sign of the gradient of the boundary streamline deflection at the detonation shock. The analysis is valid for general equations of state and chemical reaction rates in the HE. The asymptotically derived form of the energy equation represents an eigenvalue problem for the determination of the steady detonation propagation speed, solved via a shooting method. We explore specific results for ideal and stiffened equations of state, along with a pressure-dependent reaction rate for which changes in the pressure exponent and reaction order are also studied. We consider the influences of both straight and curved HE boundary streamline shapes. The asymptotic analysis reveals significant physical insights into how detonation propagation and failure are affected by strong confinement.
42 ENGINEERING↗
BioSTEAMDevelopmentGroup/biosteam
BioSTEAM is a fast and flexible package for the design, simulation, and techno-economic analysis of biorefineries under uncertainty. BioSTEAM’s framework is built to streamline and automate early-stage technology evaluations and to enable rigorous sensitivity and uncertainty analyses. Complete biorefinery configurations are available at the Bioindustrial-Park GitHub repository, BioSTEAM’s premier repository for biorefinery models and results. The long-term growth and maintenance of BioSTEAM is supported through both community-led development and the research institutions invested in BioSTEAM. Through the open-source and community-lead platform, BioSTEAM aims to foster communication and transparency within the biorefinery research community for an integrated effort to expedite the evaluation of candidate biofuels and bioproducts. Additionally, an agile life cycle assessment (LCA) platform has been designed to interface with BioSTEAM, BioSTEAM-LCA. This open-source, installable package allows users to perform streamlined LCAs of biorefineries. The focus of BioSTEAM-LCA is to streamline and automate early-stage environmental impact analyses of processes and technologies, and to enable rigorous sensitivity and uncertainty analyses linking process design, performance, economics, and environmental impacts.
Cortes-Peña, Yoel↗