SEARCH · Engineering Papers

Results for “storing”

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.

SourceResearch connectionFrom yearThrough year

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

At least 703 records · Page 39

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Thinking Like a Whole Building: A Whole Foods Market New Construction Case Study

Whole Foods Market participates in the U.S. Department of Energy's Commercial Building Partnerships (CBP) to identify and develop cost-effective, readily deployed, replicable energy efficiency measures (EEMs) for commercial buildings. Whole Foods Market is working with the National Renewable Energy Laboratory (NREL) on a retrofit and a new construction CBP project. Whole Foods Market's CBP newconstruction project is a standalone store in Raleigh, North Carolina. Whole Foods Market examined the energy systems and the interactions between those systems in the design for the new Raleigh store. Based on this collaboration and preliminary energy modeling, Whole Foods Market and NREL identified a number of cost-effective EEMs that can be readily deployed in other Whole Foods Market storesand in other U.S. supermarkets. If the actual savings in the Raleigh store - which NREL will monitor and verify - match the modeling results, each year this store will save nearly $100,000 in operating costs (Raleigh's rates are about $0.06/kWh for electricity and $0.83/therm for natural gas). The store will also use 41% less energy than a Standard 90.1-compliant store and avoid about 3.7million pounds of carbon dioxide emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

The Water, Energy, and Carbon Dioxide Sequestration Simulation Model (WECSsim™): A User’s Manual

The Water, Energy, and Carbon Sequestration Simulation Model (WECSsim) is a national dynamic simulation model that calculates and assesses capturing, transporting, and storing CO 2 in deep saline formations from all coal and natural gas-fired power plants in the U.S. An overarching capability of WECSsim is to also account for simultaneous CO 2 injection and water extraction within the same geological saline formation. Extracting, treating, and using these saline waters to cool the power plant is one way to develop more value from using saline formations as CO 2 storage locations. WECSsim allows for both one-to-one comparisons of a single power plant to a single saline formation along with the ability to develop a national CO 2 storage supply curve and related national assessments for these formations. This report summarizes the scope, structure, and methodology of WECSsim along with a few key results. Developing WECSsim from a small scoping study to the full national-scale modeling effort took approximately 5 years. This report represents the culmination of that effort. The key findings from the WECSsim model indicate the U.S. has several decades' worth of storage for CO 2 in saline formations when managed appropriately. Competition for subsurface storage capacity, intrastate flows of CO 2 and water, and a supportive regulatory environment all play a key role as to the performance and cost profile across the range from a single power plant to all coal and natural gas-based plants' ability to store CO 2 . The overall system's cost to capture, transport, and store CO 2 for the national assessment range from $\$$74 to $\$$208 / tonne stored ($\$$96 to 272 / tonne avoided) for the first 25 to 50% of the 1126 power plants to between $\$$1,585 to well beyond $\$$2,000 / tonne stored ($\$$2,040 to well beyond $\$$2,000 / tonne avoided) for the remaining 75 to 100% of the plants. The latter range, while extremely large, includes all natural gas power plants in the U.S., many of which have an extremely low capacity factor and therefore relatively high system's cost to capture and store CO 2 .

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2019

Structural Stability Study of Crystalline Silicotitanate Dispersed in Caustic Solutions for Extended Periods

The purpose of this study was to determine if pretreated engineered crystalline silicotitanate (CST) utilized in the Tank Cesium Closure Removal (TCCR) process would aggregate when contacted with sodium hydroxide (NaOH) or simulated tank waste solutions over an extended period. The aggregation of CST could be problematic for the TCCR process as it may lead to increased pressure drops across the columns, due to column plugging. Multiple prior studies have been completed on the agglomeration of CST stored in caustic simulants for prolonged periods showing evidence of clumping especially at elevated temperatures. For this study, pretreated CST was combined with various concentrations of sodium hydroxide and SRS simulant, in both glass and plastic storage containers, and monitored for an extended period. The samples were monitored for signs of agglomeration for a period of 8 months. After 7 months weak agglomeration was observed in the sample stored in SRS simulant, while no signs of clumping were observed in the samples stored in 2, 3, or 4 M NaOH. This is consistent with previous work where agglomeration of CST was not observed in simple salt solutions, only in simulants containing Al. In addition, the clumping observed for the sample stored in SRS simulant was not replicated in the duplicate sample stored in a plastic (as opposed to glass) vial, indicating leaching of Si from the glass may have contributed. It was also noted during the study that the solution above the CST stored in 4 M NaOH became opaque. The most likely cause of the opaque solution is the presence of micro-CST particles that may have been generated through sample handling, although this has not been confirmed by analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1992

Computations of the unsteady flow about a generic wing/pylon/finned-store configuration

An overset grid approach is used to carry out a set of computations of the unsteady flow about a generic wing, pylon, and finned-store configuration. The geometry, discretization procedure, and governing equations are presented. Thin-layer Navier-Stokes solutions are presented for four store separation cases: store in carriage position, store at two different separation positions, and a time-accurate simulation of the forced store separation from the wing pylon carriage. Computational results are compared with wind tunnel data for the three 'static store' cases. Dynamic loads and trajectory data are presented for the forced separation case.

Meakin, Robert L.↗

NASA NTRS1993

Optoelectronic associative memory

An associative optical memory including an input spatial light modulator (SLM) in the form of an edge enhanced liquid crystal light valve (LCLV) and a pair of memory SLM's in the form of liquid crystal televisions (LCTV's) forms a matrix array of an input image which is cross correlated with a matrix array of stored images. The correlation product is detected and nonlinearly amplified to illuminate a replica of the stored image array to select the stored image correlating with the input image. The LCLV is edge enhanced by reducing the bias frequency and voltage and rotating its orientation. The edge enhancement and nonlinearity of the photodetection improves the orthogonality of the stored image. The illumination of the replicate stored image provides a clean stored image, uncontaminated by the image comparison process.

Chao, Tien-Hsin↗

NASA NTRS1997

Effect of Storage on Performance of Super Nickel-Cadmium Cells

A study was undertaken to examine the capacity maintenance features of SUPER nickel-cadmium cells when stored for extended periods to determine whether the features change when the same kinds of positive plates as that used in nickel-hydrogen cells are used, The cells maintained their capacity when stored at 0 C in the discharged state and at 0 C in the charged state by continuously trickle charging. There was a capacity loss when stored in the open-circuit condition at 28 C. A cycling test at 17% depth of discharge for 2400 cycles using cells stored at various conditions showed that cells maintained good end of discharge voltage regardless of their storage history. However, the EOD voltages of stored cells were lower by 10 mV compared to those of fresh cells. The capacity at the end of the cycling test decreased for the stored cells by 2-7 Ah. The storage related capacity loss is lower for SUPER Ni-Cd cells compared to that of Ni-H2 cells containing a hydrogen precharge. The results suggest the pivotal role of hydrogen pressure in the capacity loss phenomenon.

Vaidyanathan, Hari↗

NASA NTRS2019

Forming Aggregations using Virtual Sharding: Lessons Learned from Simple Scalable Storage (S3)

Data aggregation is the ability to combine separate datasets to form a single new logical dataset provides users with a powerful abstraction. The advantage of an aggregate dataset is that the users are freed from having to understand, and incorporate into their workflow, knowledge about the (ad hoc) organization of the constituent datasets. However, aggregating large numbers of files can be computationally complex with data server systems performing many repetitive operations. As part of the authors work on subsetting data stored on Amazon Web Service (AWS) Simple Storage Service (S3), we developed technology to read portions of otherwise monolithic data files. This enables the formation of virtual shards for user in subsetting data stored in HDF5 (hierarchical data format, version 5) files. This same tool can be used to form aggregations that combine data stored in many HDF5 files when those files are stored on S3. The nature of the virtual sharding and the algorithm that exploits it for subsetting is such that it can also be used for aggregation with the need for many of the repetitive operations required by the per file aggregation techniques. We will present timing information that demonstrates the flexibility of this approach. However, the lessons learned is that while this is a useful result in and of itself, these very same techniques can be applied in other contexts where data are stored in services and on media other than S3. For example, this same technique can be applied to data stored on spinning disk. Pushing the envelope for S3 forced a reexamination of our data access techniques which lead to unexpected positive benefits.

Gallagher, James↗

DOE OSTI2015

Dynamic graph system for a semantic database

A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Dynamic graph system for a semantic database

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

SEPTUM MAGNET DESIGN FOR THE APS-U

The Advanced Photon Source is in the process of upgrading its storage ring from a double-bend to a multi-bend lattice as part of the APS Upgrade Project (APS-U). A swap-out injection scheme is planned for the APS-U to keep a constant beam current and to enable a small dynamic aperture. A septum magnet with a minimum thickness of 2 mm and an injection field of 1.06 T has been designed, delivering the required total deflecting angle is 89 mrad with a ring energy of 6 GeV. The stored beam chamber has an 8 mm x 6 mm super-ellipsoidal aperture. The magnet is straight; however, it is tilted in yaw, roll, and pitch from the stored beam chamber to meet the on axis swap out injection requirements for the APS-U lattice. In order to minimize the leakage field inside the stored beam chamber, four different techniques were utilized in the design. As a result, the horizontal deflecting angle of the stored beam was held to only 5 µrad, and the integrated skew quadrupole inside the stored beam chamber was held to 0.09 T. The detailed techniques that were applied to the design, field multipoles, and resulting trajectories of the injected and stored beams are reported.

Abliz, M.↗

DOE OSTI2020

Augmented Monitoring and Condition Assessment Program for SNF Wet Storage Life Extension - 20489

Approximately 27 MTHM of spent nuclear fuel (SNF) owned and managed by the U.S. Department of Energy, Office of Environmental Management is stored in the L Basin at the Savannah River Site (SRS). This 'DOE SNF' is comprised of approximately 12,000 aluminum-clad, aluminum-based fuel assemblies (∼7 MTHM), and approximately 2000 non-aluminum fuel assemblies (∼20 MTHM). A program is in progress to perform Non-Destructive Examination (NDE) of the fuel and their storage containers to characterize the materials' condition, and to evaluate the effects of service to enable continued safe wet storage of the SNF. The Augmented Monitoring and Condition Assessment Program (AMCAP), a two-part program to develop and implement remote underwater Non-Destructive Examination of the aluminum SNF, and of the containers of the non-aluminum SNF, respectively, is aimed at the characterization and evaluation of corrosion degradation of aluminum fuel and container materials. The predominant design of the aluminum SNF (ASNF) stored in L Basin is the Materials Test Reactor (MTR) equivalent design, a plate fuel design. These SNF are stored in 5'' diameter tubes or 5'' x 5'' squares (called bundles) that are nominally 12' or up to 14' long. The SNF is de-bundled and inspected using a custom-designed MTR Fuel Inspection Table. The inspection table provides for indexed fuel positioning for a video camera examination with controlled lighting. A total of 10 of the SNF originating from foreign research and test reactors were selected for examination based on burnup, enrichment, and prior damage caused by service/storage history. A special inspection campaign of these 10 assemblies is in progress. The observed corrosion damage included minor to moderate attack from general corrosion, pitting, crevice, end grain and galvanic corrosion. Example results from the completed inspections are shown and discussed. The focus is a comparison of the as-received condition versus the as-found current storage condition that will serve to validate Water Chemistry and Corrosion Monitoring Programs. The non-aluminum SNF (NASNF) stored in L Basin are of diverse design that includes various geometries with claddings of stainless steel, Zircaloy, and Hastelloy. The fuel core materials include uranium alloys, oxides/mixed oxides, and carbides. These SNF materials, originating from early experimental and test reactors, are in various physical forms including single fuel elements and cut pieces. The fuel is stored in L Basin in various configurations including in direct bundled storage in aluminum tubes and in isolation cans that are in the bundles or in a larger over-size storage container (OSC). Concern with inside-out corrosion and the potential loss of configuration control and ability to handle the storage containers prompted the development of remote NDE methods that include visual and UT technologies to assess the condition of the containers. Candidate stored materials were selected for a special inspection campaign; the development of the NDE methods for the inspection for galvanic, crevice and sediment-induced corrosion (inside-out) are discussed. A summary of the SNF storage in L Basin at the SRS, and an overview of the AMCAP to enable continued safe storage of DOE SNF are described. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Design of a thermosyphon-based thermal valve for controlled high-temperature heat extraction

Conventional concentrated solar power (CSP) is a reliable alternative energy source that uses the sun’s heat to drive a heat engine to produce electrical power. An advantage of CSP is its ability to store thermal energy for use during off-sun hours which is typically done by storing sensible heat in molten salts. Alternatively, thermal energy may be stored as latent heat in a phase-change material (PCM), which stores large quantities of thermal energy in an isothermal process. On-sun, the PCM melts, storing energy. Off-sun, the latent heat is extracted to produce dispatchable electrical power. Here, this paper presents the design of a thermosyphon-based device with sodium working fluid that is able to extract heat from a source as demand requires. A prototype has been designed to transfer 37 kW of thermal energy from a 600°C molten PCM tank to an array of 9% efficient thermoelectric generators (TEGs) to produce 3 kW of usable electrical energy for 5 h. This “thermal valve” design incorporates a funnel to collect condensate and a central shut-off valve to control condensate gravity return to the evaporator. Three circumferential tubes allow vapour transport up to the condenser. Pressure and a thermal resistance models were developed to predict the performance of the thermal valve. The pressure model predicts that the thermal valve will function as designed. The thermal resistance model predicts a 5500× difference in total thermal resistance between “on” and “off” states. The evaporator and condenser walls comprise 96% of the “on” thermal resistance, while the small parasitic heat transfer in the “off” state is primarily (77%) due to radiation losses. Lastly, this simple and effective technology can have a strong impact on the feasibility, scalability, and dispatchability of CSP latent storage. In addition, other industrial and commercial applications can benefit from this thermal valve concept.

14 SOLAR ENERGY↗

DOE OSTI2016

Beam studies at the SPEAR3 synchrotron using a digital optical mask

The 3GeV SPEAR3 synchrotron light source operates in top-up injection mode with up to 500 mA circulating in the storage ring (equivalently 392 nC). Each injection pulse contains 40–80 pC producing a contrast ratio between total stored charge and injected charge of about 6500:1. In order to study transient injected beam dynamics during user operations, it is desirable to optically image the injected pulse in the presence of the bright stored beam. In the present work this is done by imaging the visible component of the synchrotron radiation onto a digital micro-mirror-array device (DMD), which is then used as an optical mask to block out light from the bright central core of the stored beam. The physical masking, together with an asynchronously-gated, ICCD imaging camera, makes it possible to observe the weak injected beam component on a turn-by-turn basis. The DMD optical masking system works similar to a classical solar coronagraph but has some distinct practical advantages: i.e. rapid adaption to changes in the shape of the stored beam, a high extinction ratio for unwanted light and minimum scattering from the primary beam into the secondary optics. In this paper we describe the DMD masking method, features of the high dynamic range point spread function for the SPEAR3 optical beam line and measurements of the injected beam in the presence of the stored beam.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Framework for custom event sample augmentations for ATLAS analysis data

For HEP event processing, data is typically stored in column-wise synchronized containers, such as most prominently ROOT’s TTree, which have been used for several decades to store by now over 1 exabyte. These containers can combine row-wise association capabilities needed by most HEP event processing frameworks (e.g. Athena for ATLAS) with column-wise storage, which typically results in better compression and more efficient support for many analysis use-cases. One disadvantage is that these containers, TTree in the HEP use-case, require to contain the same attributes for each entry/row (representing events), which can make extending the list of attributes very costly in storage, even if those are only required for a small subsample of events. Since the initial design, the ATLAS software framework features powerful navigational infrastructure to allow storing custom data extensions for subsamples of events in separate, but synchronized containers. This allows adding event augmentations to ATLAS standard data products (such as DAOD-PHYS or PHYSLITE) avoiding duplication of those core data products, while limiting their size increase. For this functionality, the framework does not rely on any associations made by the I/O technology (i.e. ROOT), however it supports TTree friends and builds the associated index to allow for analysis outside of the ATLAS framework. A prototype based on the Long-Lived Particle search is implemented and preliminary results with this prototype will be presented. At this point, augmented data are stored within the same file as the core data. Storing them in separate files will be investigated in future, as this could provide more flexibility, e.g. certain sites may only want a subset of several augmentations or augmentations can be archived to tape once their analysis is complete.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Total cost of carbon capture and storage implemented at a regional scale: northeastern and midwestern United States

We model the costs of carbon capture and storage (CCS) in subsurface geological formations for emissions from 138 northeastern and midwestern electricity-generating power plants. The analysis suggests coal-sourced CO 2 emissions can be stored in this region at a cost of $52–$60 ton -1 , whereas the cost to store emission from natural-gas-fired plants ranges from approximately $80 to $90. Storing emissions offshore increases the lowest total costs of CCS to over $60 per ton of CO 2 for coal. Because there apparently is sufficient onshore storage in the northeastern and midwestern United States, offshore storage is not necessary or economical unless there are additional costs or suitability issues associated with the onshore reservoirs. For example, if formation pressures are prohibitive in a large-scale deployment of onshore CCS, or if there is opposition to onshore storage, offshore storage space could probably store emissions at an additional cost of less than $10 ton -1 . Finally, it is likely that more than 8 Gt of total CO 2 emissions from this region can be stored for less $60 ton -1 , slightly more than the $50 ton -1 Section 45Q tax credits incentivizing CCS.

Life Sciences & Biomedicine - Other Topics↗

DOE OSTI2016

Multifluid geo-energy systems: Using geologic CO 2 storage for geothermal energy production and grid-scale energy storage in sedimentary basins

We present an approach that uses the huge fluid and thermal storage capacity of the subsurface, together with geologic carbon dioxide (CO 2 ) storage, to harvest, store, and dispatch energy from subsurface (geothermal) and surface (solar, nuclear, fossil) thermal resources, as well as excess energy on electric grids. Captured CO 2 is injected into saline aquifers to store pressure, generate artesian flow of brine, and provide a supplemental working fluid for efficient heat extraction and power conversion. Concentric rings of injection and production wells create a hydraulic mound to store pressure, CO 2 , and thermal energy. This energy storage can take excess power from the grid and excess/waste thermal energy, and dispatch that energy when it is demanded and thus enable higher penetration of variable renewable energy technologies (e.g., wind, solar). CO 2 stored in the subsurface functions as a cushion gas to provide enormous pressure-storage capacity and displace large quantities of brine, some of which can be treated for a variety of beneficial uses. Geothermal power and energy-storage applications may generate enough revenues to compensate for CO 2 capture costs. While our approach can use nitrogen (N 2 ), in addition to CO 2 , as a supplemental fluid, and store thermal energy, this study focuses using CO 2 for geothermal energy production and grid-scale energy storage. We conduct a techno-economic assessment to determine the levelized cost of electricity of using this approach to generate geothermal power. We present a reservoir pressure-management strategy that diverts a small portion of the produced brine for beneficial consumptive use to reduce the pumping cost of fluid recirculation, while reducing the risk of seismicity, caprock fracture, and CO 2 leakage.

15 GEOTHERMAL ENERGY↗

DOE OSTI2018

Simulation INsight and Analysis

Sina is a tool set for modern scientific data management that provides flexible, light-weight support of non-bulk data capture for retention in and queries against SQL and noSQL data stores. HPC simulations traditionally maintain their data in files. Extracting data of interest for subsequent analysis then requires the time-consuming process of traversing directories and scraping data from files in a variety of formats. Sina facilitates capturing relevant data during execution or post-processing of simulation runs for retention in and queries from a modern data store. The tools are sufficiently general to allow for the inclusion of new fields as scientists learn more about their data. Libraries, currently in C++ and Python, and a command line interface (CLI) are provided. Sina's flexibility starts with a general schema, in JSON, for the collection of non-bulk simulation data. JSON provides a flexible, human-readable representation of the data that of interest. Sina currently has a C++ library for simulations to write data to and read from a schema-compliant file for subsequent ingestion into one of the supported data stores. However, applications are free to write their data directly into a schema-compliant file. Python packages provide data ingestion, management, query, and export capabilities. A command line interface (CLI) provides simplified access to these features. A common application programming interface (API) is used to maintain and query data in any of the supported data stores, which are currently limited to SQL and Apache Cassandra (a column store). Tutorials, demonstrations, and examples illustrate aspects of the process using scripts and Jupyter notebooks.

Pauli, EstebanT↗