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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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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Near-Field Corrosion Interactions between Glass and Corrosion Resistant Alloys

This study explores the corrosion interactions between model nuclear waste glass materials and corrosion resistant alloys, under conditions that simulate the near field of a nuclear waste repository. The interactions between the corrosion of stainless steel (SS) 316, alloy G30, or alloy 625, and international simple glass or soda-lime silica glass are systematically studied. The dissimilar materials were exposed in close proximity to each other in different electrolytes at 90 oC. After exposure, the glass surface exposed near metals showed different regimes of corrosion, with distinct surface morphologies and chemistries that were likely affected by the local environment created by the localized corrosion of metals. Surface and solution analyses showed that the corrosion rate of glass was enhanced by the presence of metals. Infrared spectroscopy data suggested the local build-up of stresses in the contact area of glass, which may lead to the mechanical instability of the glass alteration layer. On the other hand, the effect of glass on metal corrosion is strongly dependent on the leaching solution. In electrolytes containing abundant aggressive anions such as Cl-, glass seems to suppress the localized corrosion of SS by the precipitation of a Si-rich surface film that protects the SS substrate from solutions. However, in less aggressive electrolytes, the corrosion rate of SS was increased by the presence of glass corrosion products. Overall, our study showed that the hidden and localized damage on glass in contact with metals may enhance the release of incorporated radionuclides compared to typical uniform glass corrosion. Therefore, more attention should be paid to the corrosion interactions between metals and glass under repository conditions.

Guo, Xiaolei↗
DOE OSTI2024

Machine learning surrogates for surface complexation model of uranium sorption to oxides

Abstract The safety assessments of the geological storage of spent nuclear fuel require understanding the underground radionuclide mobility in case of a leakage from multi-barrier canisters. Uranium, the most common radionuclide in non-reprocessed spent nuclear fuels, is immobile in reduced form (U(IV) and highly mobile in an oxidized state (U(VI)). The latter form is considered one of the most dangerous environmental threats in the safety assessments of spent nuclear fuel repositories. The sorption of uranium to mineral surfaces surrounding the repository limits their mobility. We quantify uranium sorption using surface complexation models (SCMs). Unfortunately, numerical SCM solvers often encounter convergence problems due to the complex nature of convoluted equations and correlations between model parameters. This study explored two machine learning surrogates for the 2-pK Triple Layer Model of uranium retention by oxide surfaces if released as U(IV) in the oxidizing conditions: random forest regressor and deep neural networks. Our surrogate models, particularly DNN, accurately reproduce SCM model predictions at a fraction of the computational cost without any convergence issues. The safety assessment of spent fuel repositories, specifically the migration of leaked radioactive waste, will benefit from having ultrafast AI/ML surrogates for the computationally expensive sorption models that can be easily incorporated into larger-scale contaminant migration models. One such model is presented here.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Uranium carbonate complexes demonstrate drastic decrease in stability at elevated temperatures

Quantitative understanding of uranium transport by high temperature fluids is crucial for confident assessment of its migration in a number of natural and artificially induced contexts, such as hydrothermal uranium ore deposits and nuclear waste stored in geological repositories. An additional recent and atypical context would be the seawater inundated fuel of the Fukushima Daiichi Nuclear Power Plant. Given its wide applicability, understanding uranium transport will be useful regardless of whether nuclear power finds increased or decreased adoption in the future. The amount of uranium that can be carried by geofluids is enhanced by the formation of complexes with inorganic ligands. Carbonate has long been touted as a critical transporting ligand for uranium in both ore deposit and waste repository contexts. However, this paradigm has only been supported by experiments conducted at ambient conditions. We have experimentally evaluated the ability of carbonate-bearing fluids to dissolve (and therefore transport) uranium at high temperature, and discovered that in fact, at temperatures above 100 °C, carbonate becomes almost completely irrelevant as a transporting ligand. This demands a re-evaluation of a number of hydrothermal uranium transport models, as carbonate can no longer be considered key to the formation of uranium ore deposits or as an enabler of uranium transport from nuclear waste repositories at elevated temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Modernising ATLAS Software Build Infrastructure

In the last year ATLAS has radically updated its software development infrastructure hugely reducing the complexity of building releases and greatly improving build speed, flexibility and code testing. The first step in this transition was the adoption of CMake as the software build system over the older CMT. This required the development of an automated translation from the old system to the new, followed by extensive testing and improvements. This resulted in a far more standard build process that was married to the method of building ATLAS software as a series of 12 separate projects from Subversion. We then proceeded with a migration of the code base from Subversion to Git. As the Subversion repository had been structured to manage each package more or less independently there was no simple mapping that could be used to manage the migration into Git. Instead a specialist set of scripts that captured the software changes across official software releases was developed. With some clean up of the repository and the policy of only migrating packages in production releases, we managed to reduce the repository size from 62 GiB to 220 MiB. After moving to Git we took the opportunity to introduce continuous integration so that now each code change from developers is built and tested before being approved. With both CMake and Git in place we also dramatically simplified the build management of ATLAS software. Many heavyweight homegrown tools were dropped and the build procedure was reduced to a single bootstrap of some external packages, followed by a full build of the rest of the stack. This has reduced the time for a build by a factor of 2. It is now easy to build ATLAS software, freeing developers to test compile intrusive changes or new platform ports with ease. We have also developed a system to build lightweight ATLAS releases, for simulation, analysis or physics derivations which can be built from the same branch.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Generating and manipulating quantized vortices on-demand in a Bose-Einstein condensate: A numerical study

Here, we numerically investigate an experimentally viable method for generating and manipulating on-demand several vortices in a highly oblate atomic Bose-Einstein condensate (BEC) in order to initialize complex vortex distributions for studies of vortex dynamics. The method utilizes moving laser beams to generate, capture, and transport vortices inside and outside the BEC. This methodology is examined in detail and shows a wide parameter range of applicability for the prototypical two-vortex case, as well as case examples of producing and manipulating several vortices for which there is no net circulation, corresponding to equal numbers of positive and negative circulation vortices, and cases for which there is one net quantum of circulation. We also find that the presence of dissipation can help stabilize the pinning of the vortices on their respective laser beam pinning sites. Finally, we illustrate how to utilize laser beams as repositories that hold large numbers of vortices and how to deposit individual vortices in a sequential fashion in the repositories in order to construct superfluid flows about the repository beams with several quanta of circulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Skluma: An extensible metadata extraction pipeline for disorganized data

To mitigate the effects of high-velocity data expansion and to automate the organization of filesystems and data repositories, we have developed Skluma-a system that automatically processes a target filesystem or repository, extracts content-and context-based metadata, and organizes extracted metadata for subsequent use. Skluma is able to extract diverse metadata, including aggregate values derived from embedded structured data; named entities and latent topics buried within free-text documents; and content encoded in images. Skluma implements an overarching probabilistic pipeline to extract increasingly specific metadata from files. It applies machine learning methods to determine file types, dynamically prioritizes and then executes a suite of metadata extractors, and explores contextual metadata based on relationships among files. The derived metadata, represented in JSON, describes probabilistic knowledge of each file that may be subsequently used for discovery or organization. Skluma's architecture enables it to be deployed both locally and used as an on-demand, cloud-hosted service to create and execute dynamic extraction workflows on massive numbers of files. It is modular and extensible-allowing users to contribute their own specialized metadata extractors. Thus far we have tested Skluma on local filesystems, remote FTP-accessible servers, and publicly-accessible Globus endpoints. We have demonstrated its efficacy by applying it to a scientific environmental data repository of more than 500,000 files. We show that we can extract metadata from those files with modest cloud costs in a few hours.

data swamp↗
DOE OSTI2024

Scenario development for safety assessment in deep geologic disposal of high-level radioactive waste and spent nuclear fuel: A review

Radiation and radioactive substances result in the production of radioactive wastes which require safe management and disposal to avoid risks to human health and the environment. To ensure permanent safe disposal, the performance of a deep geological repository for radioactive waste is assessed against internationally agreed risk-based standards. Assessing postclosure safety of the future system's evolution includes screening of features, events, and processes (FEPs) relevant to the situation, their subsequent development into scenarios, and finally the development and execution of safety assessment (SA) models. Global FEP catalogs describe important natural and man-made repository system features and identify events and processes that may affect these features into the future. By combining FEPs, many of which are uncertain, different possible future system evolution scenarios are derived. Repository licensing should consider both the reference or “base” evolution as well as alternative futures that may lead to radiation release, pollution, or exposures. Scenarios are used to derive and consider both base and alternative evolutions, often through production of scenario-specific SA models and the recombination of their results into an assessment of the risk of harm. Furthermore, while the FEP-based scenario development process outlined here has evolved somewhat since its development in the 1980s, the fundamental ideas remain unchanged. A spectrum of common approaches is given here (e.g., bottom–up vs. top–down scenario development, probabilistic vs. bounding handling of uncertainty), related to how individual numerical models for possible futures are converted into a determination as to whether the system is safe (i.e., how aleatoric uncertainty and scenarios are integrated through bounding or Monte Carlo approaches).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Design, testing and emplacement of sand-bentonite for the construction of a gas-permeable seal test (gast)

The main aim of a gas-permeable seal is to increase the gas transport capacity of the backfilled underground structures without compromising the radionuclide retention capacity of the engineered barrier system or the host rock. Such a seal, proposed by NAGRA as part of the 'Engineered Gas Transport System' in a L/ILW repository, considers specially designed backfill and sealing materials such as sand/bentonite (S/B) mixtures with a bentonite content of 20- 30%. NAGRA's RD and D plan foresees demonstrating the construction and performance of repository seals and improving the understanding and the database for reliably predicting water and gas transport through these systems. The fluid flow and gas transport properties of these backfills have been determined at the laboratory scale and through modelling the maximum gas pressures in the near field of a repository system and the gas flow rates have been evaluated. Within this context, the Gas-permeable Seal Test (GAST) was constructed at Grimsel Test Site (GTS) to validate the effective functioning of gas-permeable seals at realistic scale. The intrinsic permeability of such seals should be in the order of 10-18 m2. Because the construction of S/B seals is not common practice for construction companies, a stepwise approach was followed to evaluate different construction and quality assurance methods. As a first step, an investigation campaign with simple tests in the laboratory and in the field followed by 1:1 scale pre-tests at GTS was performed. Through this gradual increase of the degree of complexity, practical experience was gained and confidence in the methods and procedures to be used was built, which allowed reliably producing and working with S/B mixtures at a realistic scale. During the whole pre-testing phase, a quality assurance (QA) programme for S/B mixtures was developed and different methods were assessed. They helped to evaluate and choose appropriate emplacement techniques and methodologies to achieve the target S/B dry density of 1.70 g/cm{sup 3}, which results in the desired intrinsic permeability throughout the experiment. The final QA methodology was targeted at engineering measures to decide if the work can proceed, and at producing high resolution material properties database for future water and gas transport modelling activities. The different applied QA techniques included standard core cutter tests, the application of neutron-gamma (Troxler) probes and two mass balance methods (2D and 3D). The methods, looking at different representative scales, have provided only slightly different results and showed that the average density of the emplaced S/B plug was between 1.65 and 1.73 g/cm{sup 3}. Spatial variability of dry densities was observed at decimeter scale. Overall, the pre-testing and QA programme performed for the GAST project demonstrated how the given design criteria and requirements can be met by appropriately planning and designing the material emplacement. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Norm - contaminated iodine production facilities decommissioning in Turkmenistan: experience and results

This report summarizes the data, including the cost parameters of the former iodine production facilities decommissioning project in Turkmenistan. Before the closure, these facilities were producing the iodine from the underground mineral water by the methods of charcoal adsorption. Balkanabat iodine and Khazar chemical plants' sites remediation, transportation and disposal campaigns main results could be seen. The rehabilitated area covers 47.5 thousand square meters. The remediation equipment main characteristics, technical solutions and rehabilitation operations performed are indicated also. The report shows the types of the waste shipping containers, the quantity and nature of the logistics operations. The project waste turnover is about 2 million ton-kilometers. The problems encountered during the remediation of the Khazar chemical plant site are discussed: undetected waste quantities that were discovered during the operational activities required the additional volume of the disposal facility. The additional repository wall superstructure was designed and erected to accommodate this additional waste. There are data on the volume and characteristics of the NORM waste disposed: 60.4 thousand cu.m. of NORM with total activity 1 439 x 10{sup 9} Bq (38.89 Ci) were disposed at all. This report summarizes the project implementation results, from 2009 to 15.02.2012 (the date of the repository closure and its placement under the controlled supervision), including monitoring results within a year after the repository closure. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

A consistent approach for the development of a comprehensive data base of time-dependent parameters for concrete engineered barriers

This paper presents a consistent approach for the development of a comprehensive data base of time-dependent hydraulic and transport parameters for concrete engineered barriers of the future Dessel near surface repository for low level waste. The parameter derivation is based on integration of selected data obtained through an extensive literature review, data from experimental studies on cementitious materials specific for the Dessel repository and numerical modelling using physically-based models of water and mass transport. Best estimate parameter values for assessment calculations are derived, together with source and expert range and their probability density function wherever the data was sufficient. We further discuss a numerical method for up-scaling laboratory derived parameter values to the repository scale; the resulting large-scale effective parameters are commensurate with numerical grids used in models for radionuclide migration. To accommodate different levels of conservatism in the various assessment calculations defined by ONDRAF/NIRAS, several sets of parameter values have been derived based on assumptions that introduce different degrees of conservatism. For pertinent parameters, the time evolution of such properties due to the long-term concrete degradation is also addressed. The implementation of the consistent approach is demonstrated by considering the pore water diffusion coefficient as an example. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

The Role of Data Filtering in Open Source Software Ranking and Selection

Faced with more than 100M open source projects, a more manageable small subset is needed for most empirical investigations. More than half of the research papers in leading venues investigated filtering projects by some measure of popularity with explicit or implicit arguments that unpopular projects are not of interest, may not even represent "real" software projects, or that less popular projects are not worthy of study. However, such filtering may have enormous effects on the results of the studies if and precisely because the sought-out response or prediction is in any way related to the filtering criteria.This paper exemplifies the impact of this common practice on research outcomes, specifically how filtering of software projects on GitHub based on inherent characteristics affects the assessment of their popularity. Using a dataset of over 100,000 repositories, we used multiple regression to model the number of stars -a commonly used proxy for popularity- based on factors such as the number of commits, the duration of the project, the number of authors and the number of core developers. Our control model included the entire dataset, while a second filtered model considered only projects with ten or more authors. The results indicated that while certain characteristics of the repository consistently predict popularity, the filtering process significantly alters the relationships between these characteristics and the response. We found that the number of commits exhibited a positive correlation with popularity in the control sample but showed a negative correlation in the filtered sample. These findings highlight the potential biases introduced by data filtering and emphasize the need for careful sample selection in empirical research of mining software repositories. We recommend that empirical work should either analyze complete datasets such as World of Code, or employ stratified random sampling from a complete dataset to ensure that filtering is not biasing the results.

Malviya Thakur, Addi↗
DOE OSTI2024

ComStock™ 2024 Release 1 [SWR-19-33 and SWR-20-32]

ComStock™ is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics. This repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository. Execution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock™ and ComStock™ , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers. The dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website. ComStock is a direct result of the NREL residential stock modeling tool ResStock™ (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen™. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio® and EnergyPlus® visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software. is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.

Horsey, Henry↗
DOE OSTI2025

EV-ELM (Electric Vehicle Policies with the Energy Language Model) [SWR-25-156]

Electric Vehicle Policies with the Energy Language Model (EV-ELM) leverages previous work using Large Language Models (LLMs) to find, download, and parse policy information related to energy infrastructure. In this application, we use LLMs to find policy documents related to the permitting and installation of electric vehicle charging infrastructure. This software contains the code to find, download, and parse these documents, while a related data record in the Open Energy Data Initiative (OEDI) will include the resulting output dataset that can be used for downstream analysis. The EV-ELM repository contains code for the EV-ELM project, which focuses on retrieving and processing EV permitting processes using large language models. The project is composed of two pipelines: (1) a web scraping pipeline for discovering and downloading EV permitting documents, and (2) a document parsing and extraction pipeline that processes the downloaded files to produce structured data. The web scraping pipeline is designed to extract relevant information from various websites, while the document parsing pipeline processes and analyzes the extracted documents to derive meaningful insights. Both pipelines depend on the NLR elm repository, which provides essential tools and functionalities for handling and processing the data. The web scraping pipeline is a modified version of the ordinance_gpt example within the elm repository. It has been adapted to fit the specific requirements of the EV-ELM project, ensuring that it effectively captures and processes the necessary information related to EV permitting.

Olson, Reid [National Laboratory of the Rockies (N↗
DOE OSTI2026

Polarized Deep-Inelastic Scattering with Spin Correlations in Herwig 7

This repository is the research software and reproducibility companion for the HerwigPol polarized deep-inelastic scattering implementation developed for Herwig 7. It brings together the modified Herwig and ThePEG source snapshots, the curated POLDIS fixed-order reference code, the custom Rivet analyses, the DIS validation workflow, and the paper source in a single formal repository layout. The repository is intended to preserve the source-level ingredients needed to rebuild and re-run the validated DIS studies. It therefore tracks code, input cards, workflow drivers, and technical notes, while intentionally excluding generated artifacts such as build products, campaign outputs, merged YODA files, plots, and rendered paper outputs.

Papaefstathioou, Andreas [Kennesaw State Universit↗
DOE OSTI2021

GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information about SmartTensors can be found at the SmartTensors Github Repository and the SmartTensors page at LANL.gov. Links to these pages are included in this submission. GeoThermalCloud.jl is a repository containing all the data and codes required to demonstrate applications of machine learning methods for geothermal exploration. GeoThermalCloud.jl includes: - site data - simulation scripts - jupyter notebooks - intermediate results - code outputs - summary figures - readme markdown files GeoThermalCloud.jl showcases the machine learning analyses performed for the following geothermal sites: - Brady: geothermal exploration of the Brady geothermal site, Nevada - SWNM: geothermal exploration of the Southwest New Mexico (SWNM) region - GreatBasin: geothermal exploration of the Great Basin region, Nevada Reports, research papers, and presentations summarizing these machine learning analyses are also available and will be posted soon.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

DAISY Benchmark Performance Data

This repository contains the underlying data from benchmark experiments for Drifting Acoustic Instrumentation SYstems (DAISYs) in waves and currents described in "Performance of a Drifting Acoustic Instrumentation SYstem (DAISY) for Characterizing Radiated Noise from Marine Energy Converters" (https://link.springer.com/article/10.1007/s40722-024-00358-6). DAISYs consist of a surface expression connected to a hydrophone recording package by a tether. Both elements are instrumented to provide metadata (e.g., position, orientation, and depth). Information about how to build DAISYs is available at https://www.pmec.us/research-projects/daisy. The repository's primary content is three compressed archives (.zip format), each containing multiple MATLAB binary data files (.mat format). A table relating individual data files to figures in the paper, as well as the structure of each file, is included in the repository as a Word document (Data Description MHK-DR.docx). Most of the files contain time series information for a single DAISY deployment (file naming convention: [site]_DAISY_[Drift #].mat) consisting of processed hydrophone data and associated metadata. For a limited number of DAISY deployments, the hydrophone package was replaced with an acoustic Doppler velocimeter (file naming convention: [site]_DAISY_[Drift #]_ADV.mat). Data were collected over several years at three locations: (1) Sequim Bay at Pacific Northwest National Laboratory's Marine & Coastal Research Laboratory (MCRL) in Sequim, WA, the energetic tidal channel in Admiralty Inlet, WA (Admiralty Inlet), and the U.S. Navy's Wave Energy Test Site (WETS) in Kaneohe, HI. Brief descriptions of data files at each location follow. - MCRL - (1) Drift #4 and #16 contrast the performance of a DAISY and a reference hydrophone (icListen HF Reson), respectively, in the quiescent interior of Sequim Bay (September 2020). (2) Drift #152 and #153 are velocity measurements for a drifting acoustic Doppler velocimeter in in the tidally-energetic entrance channel inside a flow shield and exposed to the flow, respectively (January 2018). (3) Two non-standard files are also included: DAISY_data.mat corresponds to a subset of a DAISY drift over an Adaptable Monitoring Package (AMP) and AMP_data.mat corresponds to approximately co-temporal data for a stationary hydrophone on the AMP (February 2019). - Admiralty Inlet - (1) Drift #1-12 correspond to tests with flow shielded DAISYs, unshielded DAISYs, a reference hydrophone, and drifting acoustic Doppler velocimeter with 5, 10, and 15 m tether lengths between surface expression and hydrophone recording package (July 2022). (2) Drift #13-20 correspond to tests of flow shielded DAISYs with three different tether materials (rubber cord, nylon line, and faired nylon line) in lengths of 5, 10, and 15 m (July 2022). - WETS - (1) Drift #30-32 correspond to tests with a heave plate incorporated into the tether (standard configuration for wave sites), rubber cord only, and rubber cord, but with a flow shielded hydrophone (November 2022). (2) Drift #49-58 and Drift #65-68 correspond to measurements around mooring infrastructure at the 60 m berth where time-delay-of-arrival localization was demonstrated for different DAISY arrangements and hydrophone depths (November 2022).

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Drifting Acoustic Measurements around C-Power's SeaRay WEC

The repository contains underwater noise measurements and associated metadata collected around C-Power's SeaRay wave energy converter on July 15, 2024 and July 16, 2024 while it was deployed at the U.S. Navy's Wave Energy Test Site (WETS) in Kaneohe, HI. Measurements were obtained using Drifting Acoustic Instrumentation SYstems (DAISYs). DAISYs consist of a surface expression connected to a hydrophone recording package by a tether. Both elements are instrumented to provide metadata (e.g., position, orientation, and depth). Information about how to build DAISYs is available at https://www.pmec.us/research-projects/daisy. The repository's primary content is a compressed archive (.zip format), containing multiple MATLAB binary data files (.mat format). The structure of each file is included in the repository as a Word document (Data Description MHK-DR.docx). Each file contains time series information for a single DAISY deployment (file naming convention: WETS_DAISY_[Drift #].mat) consisting of processed hydrophone data and associated metadata. During these measurements, C-Power's SeaRay was located at approximately 21.48112 N, 157.74451 W.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

FRAMES Metadata Reporting Templates for Ecohydrological Observations, version 1.1

FRAMES is a a set of Excel metadata files and package-level descriptive metadata that are designed to facilitate and improve capture of desired metadata for ecohydrological observations. The metadata are bundled with data files into a data package and submitted to a data repository (e.g. the NGEE Tropics Data Repository) via a web form. FRAMES standardizes reporting of diverse ecohydrological and biogeochemical data for synthesis across a range of spatiotemporal scales and incorporates many best data science practices. This version of FRAMES supports observations for primarily automated measurements collected by permanently located sensors, including sap flow (tree water use), leaf surface temperature, soil water content, dendrometry (stem diameter growth increment), and solar radiation. Version 1.1 extend the controlled vocabulary and incorporates functionality to facilitate programmatic use of data and FRAMES metadata (R code available at NGEE Tropics Data Repository).

54 ENVIRONMENTAL SCIENCES↗