SEARCH · Engineering Papers

Results for “process analysis”

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

SourceResearch connectionFrom yearThrough year

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

At least 1,243 records · Page 69

All sources NASA NTRS DOE OSTI

NASA NTRS2008

The Mars Phoenix Thermal Evolved-Gas Analysis: The Role of an Organic Free Blank in the Search for Organics

The Thermal Evolved-Gas Analyzer (TEGA) instrument onboard the 2007 Phoenix Lander will perform differential scanning calorimetry (DSC) and evolved-gas analysis of soil samples collected from the surface. Data from the instrument will be compared with Mars analog mineral standards, collected under TEGA Mars-like conditions to identify the volatile-bearing mineral phases [1] (e.g., Fe-oxyhydroxides, phyllosilicates, carbonates, and sulfates) found in the Martian soil. Concurrently, the instrument will be looking for indications of organics that might also be present in the soil. Organic molecules are necessary building blocks for life, although their presence in the ice or soil does not indicate life itself. The spacecraft will certainly bring organic contaminants to Mars even though numerous steps were taken to minimize contamination during the spacecraft assembly and testing. It will be essential to distinguish possible Mars organics from terrestrial contamination when TEGA instrument begins analyzing icy soils. To address the above, an Organic Free Blank (OFB) was designed, built, tested, and mounted on the Phoenix spacecraft providing a baseline for distinguishing Mars organics from terrestrial organic contamination. Our objective in this report is to describe some of the considerations used in selecting the OFB material and then report on the processing and analysis of the final candidate material

Lauer, H. V., Jr.↗

DOE OSTI2024

In Search of Optimum Fresh-Cut Raw Material: Using Computer Vision Systems as a Sensory Screening Tool for Browning-Resistant Romaine Lettuce Accessions

The popularity of ready-to-eat (RTE) salads has prompted novel technology to prolong the shelf life of their ingredients. Fresh-cut romaine lettuce is widely used in RTE salads; however, its tendency to quickly discolor continues to be a challenge for the industry. Selecting the ideal lettuce accessions for use in RTE salads is essential to ensure maximum shelf life, and it is critical to have a practical way to assess and compare the quality of multiple lettuce accessions that are being considered for use in fresh-cut applications. Thus, in this work we aimed to determine whether a computer vision system (CVS) composed of image acquisition, processing, and analysis could be effective to detect visual quality differences among 16 accessions of fresh-cut romaine lettuce during postharvest storage. The CVS involved a post-capturing color correction, effective image segmentation, and calculation of a browning index, which was tested as a predictor of quality and shelf life of fresh-cut romaine lettuce. The results demonstrated that machine vision software can be implemented to replace or supplement the scoring of a trained panel and instrumental quality measurements. Overall visual quality, a key sensory parameter that determines food preferences and consumer behavior, was highly correlated with the browning index, with a Pearson correlation coefficient of −0.85. Other important sensory decision parameters were also strongly or moderately correlated with the browning index, with Pearson correlation coefficients of −0.84 for freshness, 0.79 for off odor, and 0.57 for browning. The ranking of the accessions according to quality acceptability from the sensory evaluation produced a similar pattern to those obtained with the CVS. This study revealed that multiple lettuce accessions can be effectively benchmarked for their performance as fresh-cut sources via a CVS-based method. Future opportunities and challenges in using machine vision image processing to predict consumer preferences for RTE salad greens is also discussed.

Agriculture↗

NASA NTRS2011

Integration Process for the Habitat Demonstration Unit

The Habitat Demonstration Unit (HDU) is an experimental exploration habitat technology and architecture test platform designed for analog demonstration activities. The HDU previously served as a test bed for testing technologies and sub-systems in a terrestrial surface environment. in 2010 in the Pressurized Excursion Module (PEM) configuration. Due to the amount of work involved to make the HDU project successful, the HDU project has required a team to integrate a variety of contributions from NASA centers and outside collaborators The size of the team and number of systems involved With the HDU makes Integration a complicated process. However, because the HDU shell manufacturing is complete, the team has a head start on FY--11 integration activities and can focus on integrating upgrades to existing systems as well as integrating new additions. To complete the development of the FY-11 HDU from conception to rollout for operations in July 2011, a cohesive integration strategy has been developed to integrate the various systems of HDU and the payloads. The highlighted HDU work for FY-11 will focus on performing upgrades to the PEM configuration, adding the X-Hab as a second level, adding a new porch providing the astronauts a larger work area outside the HDU for EVA preparations, and adding a Hygiene module. Together these upgrades result in a prototype configuration of the Deep Space Habitat (DSH), an element under evaluation by NASA's Human Exploration Framework Team (HEFT) Scheduled activates include early fit-checks and the utilization of a Habitat avionics test bed prior to installation into HDU. A coordinated effort to utilize modeling and simulation systems has aided in design and integration concept development. Modeling tools have been effective in hardware systems layout, cable routing, sub-system interface length estimation and human factors analysis. Decision processes on integration and use of all new subsystems will be defined early in the project to maximize the efficiency of both integration and field operations. In addition a series of tailored design reviews are utilized to quickly define the systems and their integration into the DSH configuration. These processes are necessary to ensure activities, such as partially reversing integration of the X-Hab second story of the HDU and deploying and stowing the new work porch for transportation to the JSC Rock Yard and to the Arizona Black Point Lava Flow Site are performed with minimal or no complications. In addition, incremental test operations leading up to an Integrated systems test allows for an orderly systems test program. For FY-11 activities, the HDU DSH will act as a laboratory utilizing a new X-Hab inflatable second floor with crew habitation features. In addition to the day to day operations involving maintenance of the HDU and exploring the surrounding terrain, testing and optimizing the use of the new X-Hab, work porch, Hygiene Module, and other sub-system enhancements will be the focus of the FY-11 test objectives. The HDU team requires a successful integration strategy using a variety of tools and approaches to prepare the DSH for these test objectives. In a challenging environment where the prototyping influences the system design, as well as Vice versa, results of the HDU DSH field tests will influence future designs of habitat systems.

Gill, Tracy↗

NASA NTRS2003

Unlocking the Mystery of Columbia's Tragic Accident Through Materials Characterization

The wing and underbelly reconstruction of Space Shuttle Columbia took place at the Shuttle Landing Facility Hangar after the accident which destroyed STS-107. Fragments were placed on a grid according to their original location on the orbiter. Some Reinforced Carbon-Carbon (RCC) panels of the left wing leading edge and other parts from both leading edges were recovered and incorporated into the reconstruction. The recovered parts were tracked on a database according to a number and also tracked on a map of the orbiter. This viewgraph presentation describes the process of failure analysis undertaken by the Materials and Processes (M&P) Problem Resolution Team. The team started with factual observations about the accident, and identified highest level questions for it to answer in order to understand where on the orbiter failure occured, what component(s) failed, and what was the sequence of events. The finding of Columbia's MADS/OEX data recorder shifted the focus of the team's analysis to the left wing leading edge damage. The team placed particular attention on slag deposits on some of the RCC panels. The presentation lists analysis techniques, and lower level questions for the team to answer.

Shah, Sandeep↗

NASA NTRS1987

The Land Analysis System (LAS) - A general purpose system for multispectral image processing

The present, general-purpose Land Analysis System (LAS) for image processing furnishes a comprehensive set of functions for the manipulation of MSS data; the initial version has more than 240 functions and utilities ranging from pixel manipulation to complex classification. A LAS user's guide describes each such function in terms of purpose, input parameters, illustrative examples, algorithms, error messages, and user codes. The LAS source code is so distributed as to simplify system maintenance; the Transportable Application Executive is employed as the user interface, thereby accommodating both expert and novice users by means of menus and tutored prompting.

Wharton, Stephen W.↗

NASA NTRSDate not supplied

Development Strategies for Uncertainty Quantification to Enable Aircraft Certification by Analysis

Aircraft Certification by Analysis (CbA) is a broad term that describes the process by which engineering analysis tools are used to supplement flight testing to demonstrate compliance with regulatory requirements. For each requirement that is to be met through this process, the analysis tools must be sufficiently accurate to ensure that an equivalent level of safety is obtained as if the aircraft to be certified had been flight tested for the requirement. In recent decades, the ability of analysis tools to accurately predict aircraft performance has improved dramatically, leading to increasing interest and limited early adoption of Certification by Analysis across the aerospace industry. However, rigorously demonstrating the credibility of analysis tools remains a challenge for many types of certification requirements, yet is necessary for widespread adoption of CbA approaches in the future. The field of uncertainty quantification is well-suited to address this problem, but will require substantial advances in order to achieve the ambitious industry goals for Certification by Analysis. The objective of this position paper is to highlight gaps in the current technical and programmatic state of uncertainty quantification. Four main categories – Mindset & Awareness, Tools & Capabilities, Data and Benchmarks for V&V, and Applied Research & Established Processes – will be introduced. Each of these categories contains several shortcomings and impediments which, if overcome, will enable more widespread possibilities for Certification by Analysis in the 2040-2050 timeframe.

Uncertainty Quantification↗

NASA NTRS2022

Ideas on the NASA Senior Review and Mission Extension Process

Extended mission budgets fund a significant part of our community, particularly young scientists who in a relatively short time are exposed to a broad range of experiences and opportunities available in space science and other STEM fields. In particular, mission-funded science offers a relatively stable funding stream that enables meaningful mentoring efforts and interactions, including apprenticeships ranging from project management, to mission operations, to data processing and analysis, to hardware and software development, to STEM-related education and outreach. It moreover provides professional contacts that fuel diversity in mission leadership and in the science and technical workforce at-large. Last but not least, it sustains the scientific productivity of NASA’s missions, which constitute major national investments meriting their full exploitation. Budgets cuts, however, are exercising pressure on the science and operations of the extended mission fleet despite being only a small portion of the overall Division budget. The history of Heliophysics has demonstrated that maintaining the operation of missions beyond their prime phase invariably leads to a much deeper knowledge of the original mission science goals, together with new applications often not foreseen during their original design. Their operation as part of the Heliophysics System Observatory (HSO)---a coordinated, 1eliophysics, multipoint observing system of the heliosphere, is a prime example. Some of the first activities undertaken by the Parker Solar Probe and Solar Orbiter missions required recreating the larger context of their new observations by using the diversity of HSO mission capabilities. The marginal cost of maintaining this valuable, working science resource, in the form of both continuing high quality data access and expertise, is small compared to the cost of the original missions or of new missions to achieve similar objectives, making the operation of extended missions, the best “science per dollar” investment in Heliophysics. We argue that reducing both extended mission operations and science budgets will have a ripple effect across the community, including reducing employment and training opportunities for young scientists, to lowering the quality/impact of the Heliophysics Systems Observatory. Instead, we suggest that the proposal process for mission extension should be re-examined. We offer several ideas for reducing costs of extended missions toward maintaining science output and streamlining the management process.

A. Vourlidas↗

NASA NTRS1991

Application of software technology to automatic test data analysis

The verification process for a major software subsystem was partially automated as part of a feasibility demonstration. The methods employed are generally useful and applicable to other types of subsystems. The effort resulted in substantial savings in test engineer analysis time and offers a method for inclusion of automatic verification as a part of regression testing.

Stagner, J. R.↗

NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗

DOE OSTI2025

Adsorptive denitrogenation of model aviation fuel using mesoporous silica in a packed bed adsorption system

This study aims to understand the effects of system process parameters such as flow rate, adsorbent particle size, and use of recycled adsorbent on denitrogenation performance of a model fuel using mesoporous silica gel. The goal is to reduce the nitrogen content of the model fuel from 1500 parts per million to single-digit ppm to meet ASTM specifications for drop-in fuels. This work was done with the intent of applying adsorptive denitrogenation to sustainable aviation fuel (SAF) product fractions produced via hydrothermal liquefaction (HTL). The adsorption performance of the silica is evaluated via packed column breakthrough data, with data generated from collecting from the column outlet and quantifying nitrogen content via gas chromatography. Select experiments use a significantly larger (2.5x column diameter and length) column to demonstrate linear scalability of the process. Thermogravimetric analysis data is collected to evaluate the effects of thermal calcination as a sorbent regeneration method. Effects of a more complex feed are also investigated using a known reference fuel with additional added nitrogen containing compounds. The results presented in this work successfully demonstrate up to 99.8 % removal of NCCs from a model fuel fraction at an original NCC concentration of approximately 1500 ppm to single-digit parts per million after treatment. We also examine calcination of sorbent materials to remove the adsorbed species to enable sorbent reuse and minimize waste generation and show that the calcined material can be reused up to 5 cycles with reduced adsorption capacity. Overall, this work indicates that adsorptive denitrogenation using silica gel is a viable solution to enable the integration of HTL-derived aviation fuels into existing fuel infrastructure.

Adsorption techniques↗

NASA NTRS1979

The ground processing simulator - A tool for mission model analysis and planning from a launch site perspective

The Ground Processing Simulator (GPS) is a computer-assisted planning tool designed and developed for Space Shuttle launch site application. Utilizing two programming languages, General Purpose Simulation System and FORTRAN, GPS provides the capability to analyze proposed Shuttle mission models via computer simulation. NASA-developed mission models which specify Shuttle launch rates, mission durations, cargo elements, and designated launch site are tested for feasibility by the simulator. GPS produces facility utilization schedules (including the identification of conflicts), launch data options, cargo element requirement dates, ground support equipment inventory requirements, and other data necessary to assess both the programmatic and launch site resources required to support proposed mission models. The purpose of this computer-assisted analysis is to determine methods which will permit the launching of the maximum number of cargoes per year on schedule, and in the sequence desired, with the minimum expenditure of resources.

Ralph, J. A.↗

NASA NTRS2017

Verification and Validation Process for Progressive Damage and Failure Analysis Methods in the NASA Advanced Composites Consortium

The Advanced Composites Consortium is a US Government/Industry partnership supporting technologies to enable timeline and cost reduction in the development of certified composite aerospace structures. A key component of the consortium's approach is the development and validation of improved progressive damage and failure analysis methods for composite structures. These methods will enable increased use of simulations in design trade studies and detailed design development, and thereby enable more targeted physical test programs to validate designs. To accomplish this goal with confidence, a rigorous verification and validation process was developed. The process was used to evaluate analysis methods and associated implementation requirements to ensure calculation accuracy and to gage predictability for composite failure modes of interest. This paper introduces the verification and validation process developed by the consortium during the Phase I effort of the Advanced Composites Project. Specific structural failure modes of interest are first identified, and a subset of standard composite test articles are proposed to interrogate a progressive damage analysis method's ability to predict each failure mode of interest. Test articles are designed to capture the underlying composite material constitutive response as well as the interaction of failure modes representing typical failure patterns observed in aerospace structures.

Wanthal, Steven↗

NASA NTRS1995

The role of surface chemical analysis in a study to select replacement processes for TCA vapor degreasing

The role of surface-sensitive chemical analysis (ESCA, AES, and SIMS) in a study to select a process to replace 1, 1, 1-trichloroethane (TCA) vapor degreasing as a steel and aluminum bonding surface preparation method is described. The effort was primarily concerned with spray-in-air cleaning processes involving aqueous alkaline and semi-aqueous cleaners and a contamination sensitive epoxy-to-metal bondline. While all five cleaners tested produced bonding strength results equal to or better than those produced by vapor degreasing, the aqueous alkaline cleaners yielded results which were superior to those produced by the semi-aqueous cleaners. The main reason for the enhanced performance appears to be a silicate layer left behind by the aqueous alkaline cleaners. The silicate layer increases the polarity of the surface and enhances epoxy-to-metal bonding. On the other hand, one of the semi-aqueous cleaners left a nonpolar carbonaceous residue which appeared to have a negative effect on epoxy-to-metal bonding. Differences in cleaning efficiency between cleaners/processes were also identified. These differences in surface chemistry, which were sufficient to affect bonding, were not detected by conventional chemical analysis techniques.

Lesley, Michael W.↗

DOE OSTI2024

Microstructural Passivation of Patterned Al 2 O 3 Back Contacts on CdS/CdTe Solar Cells

Abstract Patterned aluminum oxide (Al 2 O 3 ) back contact on cadmium telluride (CdTe) solar cells can effectively mitigate the loss of the majority carriers while retaining the passivation benefits for minority carriers. This study investigates the impact of the point‐contact geometry on cell performance, where the spacing of the microholes is systematically varied at a constant microhole diameter (≈16 µm). Microhole arrays are created on an evaporated Al 2 O 3 layer (≈30 nm) on CdTe using laser‐beam lithography and selective wet etching processes. Comparative analysis indicates a significant decrease in fill factor (FF) and short‐circuit current ( I SC ) when the contact fraction falls below 30%, likely due to the Al 2 O 3 barrier impeding majority carriers. Above this fraction, FF and I SC are comparable to those of baseline CdTe cells without Al 2 O 3 . Open‐circuit voltage ( V OC ) shows a gradual decrease as Al 2 O 3 coverage is reduced but exhibits a slight increase (<15 mV) when the contact fraction exceeds 30%. Cathodoluminescence (CL) characterization reveals that significantly improved radiative recombination occurs within the CdTe grain bulk with Al 2 O 3 , whereas this effect on grain boundaries is minimal. The findings imply complex local carrier dynamics in the patterned back‐contact region, closely tied to the microstructural properties of CdTe‐based solar cells.

Roy, Etee Kawna↗

DOE OSTI2024

Density estimation via measure transport: Outlook for applications in the biological sciences

Abstract One among several advantages of measure transport methods is that they allow or a unified framework for processing and analysis of data distributed according to a wide class of probability measures. Within this context, we present results from computational studies aimed at assessing the potential of measure transport techniques, specifically, the use of triangular transport maps, as part of a workflow intended to support research in the biological sciences. Scenarios characterized by the availability of limited amount of sample data, which are common in domains such as radiation biology, are of particular interest. We find that when estimating a distribution density function given limited amount of sample data, adaptive transport maps are advantageous. In particular, statistics gathered from computing series of adaptive transport maps, trained on a series of randomly chosen subsets of the set of available data samples, leads to uncovering information hidden in the data. As a result, in the radiation biology application considered here, this approach provides a tool for generating hypotheses about gene relationships and their dynamics under radiation exposure.

gene expression data↗

DOE OSTI2024

Differential cross-section measurements of the production of four charged leptons in association with two jets using the ATLAS detector

Differential cross-sections are measured for the production of four charged leptons in association with two jets. These measurements are sensitive to final states in which the jets are produced via the strong interaction as well as to the purely-electroweak vector boson scattering process. The analysis is performed using proton-proton collision data collected by ATLAS at $\sqrt{s}$ = 13 TeV and with an integrated luminosity of 140 fb –1 . The data are corrected for the effects of detector inefficiency and resolution and are compared to state-of-the-art Monte Carlo event generator predictions. The differential cross-sections are used to search for anomalous weak-boson self-interactions that are induced by dimension-six and dimension-eight operators in Standard Model effective field theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Search for exotic decays of the Higgs boson into long-lived particles in pp collisions at $\sqrt{s}$ = 13 TeV using displaced vertices in the ATLAS inner detector

A novel search for exotic decays of the Higgs boson into pairs of long-lived neutral particles, each decaying into a bottom quark pair, is performed using 139 fb -1 of $\sqrt{s}$ = 13 TeV proton-proton collision data collected with the ATLAS detector at the LHC. Events consistent with the production of a Higgs boson in association with a leptonically decaying Z boson are analysed. Long-lived particle (LLP) decays are reconstructed from inner-detector tracks as displaced vertices with high mass and track multiplicity relative to Standard Model processes. The analysis selection requires the presence of at least two displaced vertices, effectively suppressing Standard Model backgrounds. The residual background contribution is estimated using a data-driven technique. No excess over Standard Model predictions is observed, and upper limits are set on the branching ratio of the Higgs boson to LLPs. Branching ratios above 10% are excluded at 95% confidence level for LLP mean proper lifetimes cτ as small as 4 mm and as large as 100 mm. For LLP masses below 40 GeV, these results represent the most stringent constraint in this lifetime regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Coordinative Entities: Forms of Organizing in Data Intensive Science

Scientific collaboration is a long-standing subject of CSCW scholarship that typically focuses on the development and use of computing systems to facilitate research. The research presented in this article investigates the sociality of science by identifying and describing particular, common forms of organizing that researchers in four different scientific realms employ to conduct work in both local contexts and as part of distributed, global projects. This paper introduces five prototypical forms of organizing we categorize as coordinative entities: the Principal Group, Intermittent Exchange, Sustained Aggregation, Federation, and Facility Organization. Coordinative entities as a categorization help specify, articulate, compare, and trace overlapping and evolving arrangements scientists use to facilitate data intensive research. We use this typology to unpack complexities of data intensive scientific collaboration in four cases, showing how scientists invoke different coordinative entities across three types of research activities: data collection, processing, and analysis. Finally, our contribution scrutinizes the sociality of scientific work to illustrate how these actors engage in relational work within and among diverse, dispersed forms of organizing across project, funding, and disciplinary boundaries.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗