Results for “Lab data'” — Page 42

DOE OSTI2021

LABS: Los Alamos Benchmark Suite - Current status and planning [Slides]

The LABS repository now has over 500 verified and revised input files with about 600 input files left to get up to speed with what we currently use. After that there are many, many more to go. We're in the process of building code infrastructure, moving to template output files, automating input file generation, outputting file data mining for calculation results, and benchmarking selection on sensitivity and other benchmark characteristics. We intend to open source LABS. We'll most likely release the input files sooner rather than later. The associated tool will probably be open sourced later.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2000

High-Speed Automated Tester for Vacuum Chamber Feedthrough Connectors and Cables

The Goddard Space Flight Center's thermal vacuum laboratory has developed a high-speed automated system for testing the integrity of 37-pin MIL-C-5015 cylindrical electrical feedthrough connectors used on penetration plates of thermal vacuum chambers. The system consists of a desktop PC driving a data acquisition front end. The latter measures the resistance through each pin of the connector and the resistance from each pin to all other pins and the connector shell. In addition to identifying unacceptable feedthroughs, the system is also used for testing cables. In the special case of Type T thermocouples (used almost exclusively at the lab), the difference in resistance between the copper and constantan wires provides positive proof of accidentally reversed connector wiring. Data acquisition time to completely test a cable or feedthrough connector is less than thirty seconds. The system provides a hardcopy printout of the resistance readings. Connectors or cables with fewer wires are tested using simple adapter cables. Initial tests indicate that the performance of a given feedthrough connector can be predicted on the basis of measured resistance readings, reducing ongoing cost of connector replacement. The opportunity to positively certify the integrity of cables, cable connectors and feedthroughs before the start of a thermal vacuum test minimizes the likelihood of a circuit problem that would require returning the chamber to ambient conditions for repair. This system has two principal advantages for the Goddard thermal vacuum laboratory. Its only significant cost was the labor to fabricate the test cable and shorting cable -- about 40 man-hours total. The system was built around a computer and data acquisition unit that were already on hand. The second advantage is that it very quickly tests both of the parameters that are essential.

Swope, Robert H.↗

DOE OSTI2020

Pilot Study for Determining HVAC Fault Prevalence from Fault Monitoring Data

HVAC faults in U.S. commercial buildings are estimated to waste 0.7 quads of energy annually and many companies have deployed software at scale for fault detection and diagnosis (FDD). Yet the lack of comprehensive published data on fault prevalence makes it difficult for researchers, software developers, and building operators to target the most important types of faults and accelerate the widespread deployment of this technology. A multi-lab effort is underway to quantify the prevalence of commercial building HVAC faults. This paper describes initial analysis conducted on over 2-years of FDD data from 12 campus buildings to inform the methodology and data collection strategy of the full study. The analysis found a large variability in fault prevalence across different buildings, pieces of equipment, and fault types, many duplicate fault alarms, and challenges in validating faults with secondary data sources such as manually entered work order data. This paper also discusses the requirements for a successful full study, which necessitates the acquisition of a large, diverse dataset, from buildings that vary in end-use, climate region, and installed FDD software platform, as well as robust validation data easily linked to the FDD data. It is especially important to perform this analysis on data from multiple FDD providers and building owners to ensure that the results are agnostic to the software methodology used and building-specific settings. Future work will present the results of the full study, which will contain data from several different partner organizations, spanning a large proportion of U.S. climate zones.

Newman, Sarah F.↗

DOE OSTI2021

Hardware-Based Emulator with Deep Learning Model for Building Energy Control and Prediction Based on Occupancy Sensors’ Data

Heating, ventilation, and air conditioning (HVAC) is the largest source of residential energy consumption. Occupancy sensors’ data can be used for HVAC control since it indicates the number of people in the building. HVAC and sensors form a typical cyber-physical system (CPS). In this paper, we aim to build a hardware-based emulation platform to study the occupancy data’s features, which can be further extracted by using machine learning models. In particular, we propose two hardware-based emulators to investigate the use of wired/wireless communication interfaces for occupancy sensor-based building CPS control, and the use of deep learning to predict the building energy consumption with the sensor data. We hypothesize is that the building energy consumption may be predicted by using the occupancy data collected by the sensors, and question what type of prediction model should be used to accurately predict the energy load. Another hypothesis is that an in-lab hardware/software platform could be built to emulate the occupancy sensing process. The machine learning algorithms can then be used to analyze the energy load based on the sensing data. To test the emulator, the occupancy data from the sensors is used to predict energy consumption. The synchronization scheme between sensors and the HVAC server will be discussed. We have built two hardware/software emulation platforms to investigate the sensor/HVAC integration strategies, and used an enhanced deep learning model—which has sequence-to-sequence long short-term memory (Seq2Seq LSTM)—with an attention model to predict the building energy consumption with the preservation of the intrinsic patterns. Because the long-range temporal dependencies are captured, the Seq2Seq models may provide a higher accuracy by using LSTM architectures with encoder and decoder. Meanwhile, LSTMs can capture the temporal and spatial patterns of time series data. The attention model can highlight the most relevant input information in the energy prediction by allocating the attention weights. The communication overhead between the sensors and the HVAC control server can also be alleviated via the attention mechanism, which can automatically ignore the irrelevant information and amplify the relevant information during CNN training. Our experiments and performance analysis show that, compared with the traditional LSTM neural network, the performance of the proposed method has a 30% higher prediction accuracy.

Ye, Zhijing↗

NASA NTRSDate not supplied

Genomics Study of Effect of Redox-Active Metalloporphyrin on Murine Retina During Spaceflight

Astronauts returning from spaceflight have experienced eye problems, which may decrease retinal performance and lead to long-term effects on visual acuity. This study leverages the collected data from spaceflown murine retinas that were treated with redox-active metalloporphyrin (BuOE) to mitigate spaceflight-induced changes. 10-week-old adult C57BL/6 male mice (n=5 in each of BuOE treated and saline control groups) were flown on Space-X 24 to the ISS national lab, kept in low earth orbit for 35 days and returned to Earth alive. Our analysis of RNA-sequencing data generated from subsequent murine retina tissues uncovered genes, pathways, and epigenetic modifications consistent with therapeutic potential of BuOE. For spaceflown murine samples, the treatment group show differentially expressed genes relative to saline controls that reached significance (adjusted p-value < 0.05) and included genes Gpx3 and Crhbp, which are related to protection against cell oxidative damage and cellular response to organonitrogen compounds. Ranked fold-changes from the same contrast were used for gene set enrichment analysis, which showed biological processes reaching significance (adjusted p-value < 0.05) including glutathione metabolic processes and cellular response to xenobiotic stimulus. The findings from this investigation have the potential to provide valuable insights into the molecular mechanisms underlying conditions like spaceflight associated neuro-ocular syndrome and assess the effectiveness of BuOE as a countermeasure for astronauts experiencing neuro-ophthalmic abnormalities, which can lead to long-term effects on visual acuity.

Machine Learning↗

NASA NTRSDate not supplied

Genomics Study of Effect of Redox-Active Metalloporphyrin on Murine Retina During Spaceflight

Astronauts returning from spaceflight have experienced eye problems, which may decrease retinal performance and lead to long-term effects on visual acuity. This study leverages the collected data from spaceflown murine retinas that were treated with redox-active metalloporphyrin (BuOE) to mitigate spaceflight-induced changes. 10-week-old adult C57BL/6 male mice (n=5 in each of BuOE treated and saline control groups) were flown on Space-X 24 to the ISS national lab, kept in low earth orbit for 35 days and returned to Earth alive. Our analysis of RNA-sequencing data generated from subsequent murine retina tissues uncovered genes, pathways, and epigenetic modifications consistent with therapeutic potential of BuOE. For spaceflown murine samples, the treatment group show differentially expressed genes relative to saline controls that reached significance (adjusted p-value < 0.05) and included genes Gpx3 and Crhbp, which are related to protection against cell oxidative damage and cellular response to organonitrogen compounds. Ranked fold-changes from the same contrast were used for gene set enrichment analysis, which showed biological processes reaching significance (adjusted p-value < 0.05) including glutathione metabolic processes and cellular response to xenobiotic stimulus. The findings from this investigation have the potential to provide valuable insights into the molecular mechanisms underlying conditions like spaceflight associated neuro-ocular syndrome and assess the effectiveness of BuOE as a countermeasure for astronauts experiencing neuro-ophthalmic abnormalities, which can lead to long-term effects on visual acuity.

Machine Learning↗

DOE OSTI2025

Optimal Control of an Oscillating Surge Wave Energy Converter

During this project, we experimentally investigated the hydrodynamics and performance of a laboratory-scale oscillating surge wave energy converter (OSWEC).We looked at how flap buoyancy and driveline losses (primarily in the form of stiction) affected the dynamics and performance of the device. In addition, we assessed the influence of flap profile (rounded vs. square edges) on OSWEC hydrodynamics. Through this, we were able to develop a deeper understanding of OSWEC performance and provide guidance on strategies to counteract artifacts that may be present in laboratory models, but are absent in field-scale devices. To do this, we tested a laboratory-scale OSWEC in the Sea Wave Environmental Lab (SWEL) wave tank at the National Renewable Energy Laboratory (NREL). We ran several types of experiments to investigate the hydrodynamics and performance of the device. Overall, we achieved the overall goal of experimentally investigating the hydrodynamics and performance of this device. We discovered important and unexpected trends in performance, and collected time-resolved data to help us further investigate the underlying hydrodynamics responsible for these trends. In addition, we are currently using the time-resolved data from these experiments to build data-driven models of the dynamics, which can in turn be used to inform data-driven model predictive control of this device and address this objective in the future.

16 TIDAL AND WAVE POWER↗

DOE OSTI2022

Data from: “Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats”

This dataset contains supplementary information for a manuscript describing the ESS-DIVE (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) data repository's community data and metadata reporting formats. The purpose of creating the ESS-DIVE reporting formats was to provide guidelines for formatting some of the diverse data types that can be found in the ESS-DIVE repository. The 6 teams of community partners who developed the reporting formats included scientists and engineers from across the Department of Energy National Lab network. Additionally, during the development process, 247 individuals representing 128 institutions provided input on the formats. The primary files in this dataset are 10 data and metadata crosswalk for ESS-DIVE’s reporting formats (all files ending in _crosswalk.csv). The crosswalks compare elements used in each of the reporting formats to other related standards and data resources (e.g., repositories, datasets, data systems). This dataset also contains additional files recommended by ESS-DIVE’s file-level metadata reporting format. Each data file has an associated dictionary (files ending in _dd.csv) which provide a brief description of each standard or data resource consulted in the data reporting format development process. The flmd.csv file describes each file contained within the dataset.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Cross Section Evaluation for Exclusive Channels of K+Λ and K+Σ0 Electroproduction off Protons Using CLAS Detector Data

In this work, a method for evaluating the cross sections of electroproduction of K+Λ0 and K+Σ0 off protons in the region of invariant masses of final hadrons MK + MY <W < 2.65 GeV (MK and MY being the masses of the kaon and hyperon, respectively) and squares of four-momentum transfers of virtual photons, i.e., photon virtualities 0 < Q2 < 5 GeV2, is developed based on experimental data of these exclusive channels’ cross sections measured by the CLAS detector in Hall B at Jefferson Lab. A set of algorithms has been implemented to evaluate the differential cross sections of these channels, along with their statistical and systematic uncertainties. A program was developed for the evaluation of differential cross sections and structure functions using C++ and Python libraries. An interactive website was created for working with the program, enabling the analysis of one-dimensional and two-dimensional dependences of structure functions and differential cross sections. The evaluation of differential cross sections for the K+Λ and K+Σ0 electroproduction channels is necessary for extracting the structure function σLT from the data on the polarization asymmetry of electroproduction reactions of these final states with longitudinally polarized electrons. The obtained results are also important for the development of realistic Monte Carlo event generators in planning future experiments and for evaluating the efficiency of detecting final particles when extracting reaction cross sections from experimental data.

Golda, A. V.↗

DOE OSTI2023

U.S. Offshore Wind Energy Noise Reduction Associated with Installation of Fixed-Bottom Foundations: Workshop Report

As offshore wind energy development grows in the United States, solutions are needed to reduce the underwater noise and substrate vibration generated during fixed-bottom turbine installation to help protect marine life. Monopiles are currently the main turbine foundation type installed globally and impact pile driving, the primary installation method, can be a major source of noise and vibration generation during wind farm construction. Opportunities exist to reduce the amount of noise and vibration produced during future offshore wind farm development. The use of alternative foundation types and installation methods, as well as innovative noise abatement technologies, would help reduce the potential detrimental effects on sensitive marine species. To explore these opportunities, the Department of Energy’s Wind Energy Technologies Office, in collaboration with the Bureau of Ocean Energy Management and the National Oceanic and Atmospheric Administration, funded the National Renewable Energy Laboratory and the Pacific Northwest National Laboratory to organize, host, and facilitate a virtual workshop in December 2022. The goal of the workshop was to gather input from the offshore wind energy community on noise reduction strategies for the installation of fixed-bottom offshore wind turbines in U.S. waters across multiple regions, including the U.S. Atlantic Coast, Gulf of Mexico, and Great Lakes to inform recommendations on future research. The joint lab team convened industry representatives, subject matter experts, and regulators to discuss potential pathways to reduce noise and vibration associated with fixed-bottom turbine installation, including the practicality of using alternative foundations and installation methods, the effectiveness of noise abatement technologies, as well as research and monitoring needs. In preparation for the workshop, the team invited experts to be part of a steering committee and worked with its members to help focus activities to meet the workshop goals. Additional pre-workshop activities included developing the invitee list and workshop agenda, reviewing existing Construction and Operations Plans (COP) for proposed offshore wind projects, distributing a brief questionnaire to industry representatives, and drafting the workshop discussion questions and Mural boards. In total, 128 workshop participants provided over 600 comments in response to the 17 group discussion questions used over two workshop sessions. Overarching recommendations highlighted across themes included future investments to provide data sharing, consistency, transparency, and opportunities for sharing best available science, knowledge, and expertise. The joint lab team synthesized the comments and identified four key research and development themes that could help advance the successful implementation of noise and vibration reduction strategies (see report). This report provides an overview of the workshop goals and scope, reviews the pre-workshop activities, presents brief summaries of participant feedback, and concludes with detailed research themes and recommendations for future investments. Appendix A includes the group discussion questions, Appendix B includes the results of the COP review, and Appendix C includes the results of the industry questionnaire. Overall, there was a high level of interest and engagement in the workshop. The sessions provided an opportunity for significant exchange of information between workshop participants from across sectors. Participants identified a variety of opportunities for next steps towards the noise reduction of offshore wind turbine installation in U.S. waters, including recommendations for future investments to provide certainty in the use of new technologies associated with alternative foundation types, noise abatement systems, and efficacy monitoring.

17 WIND ENERGY↗

DOE OSTI2022

Leaf C and N content by leaf age, Feb2017, PA-SLZ: Panama

This dataset contains carbon, hydrogen and nitrogen content measurements of sunlit canopy leaves of Apeiba membranacea (APEIME), Guatteria dumetorum (GUATDU), Miconia borealis (MICOBO), Terminalia amazonia (TERMAM), Virola multiflora (VIROSP) and Vochysia ferruginea (VOCHFE) species. Data was collected from the NGEE-Tropics Bosque Protector San Lorenzo (PA-SLZ) site in Panama in February of 2017 as part of the 2017 Brookhaven National Lab–Smithsonian Tropical Research Institute leaf traits by age campaign. A PDF with full sapling protocol is included in this dataset, along with metadata files in Excel file format. Data is in both CSV (Panama2017_CHN.csv) and Excel file formats. See related datasets for further sample details, leaf spectra, sap flow, leaf water potential, leaf mass per area (LMA), and gas exchange measurements.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1998

Systems Characterization of Temperature, Ph and Electrical Conductivity in Aerobic Biodegradation of Wheat Biomass at Differing Mixing Rates

The purpose of this preliminary study is to observe and relate the rate of mixing to pH and electrical conductivity in an aerobic, continuously stirred bioreactor. The objective is to use data collected from successive experiments as a means of a system characterization. Tests were conducted to obtain these data using a continuously stirred 20 L Cytostir glass reaction vessel as a bioreactor operated without built-in temperature or pH control. The tests were conducted on the lab bench at ambient temperatures. The substrate in the bioreactor was ground wheat biomass obtained from the Biomass Production Chamber at NASA Kennedy Space Center. In this study, the data reflect characteristics of the native (uninoculated) systems as well as inoculated systems. In the native systems, it was found that pi levels became stable after approximately 2 to 3 days. The electrical conductivity levels for the native systems tended to decrease over time. In contrast, ion activity was increased after the introduction of bacteria into the system. This could be correlated with the release of nutrients, due to the activity of the bacteria. Also, there were slight increases in pH in the inoculated system, a result which is expected for a system with no active pr controls. The data will be used to test a mathematical model in an automated system.

Calhoun, M.↗

NASA NTRS2010

Photogrammetric Measurements of an EH-60L Brownout Cloud

There is a critical lack of quantitative data regarding the mechanism of brownout cloud formation. Recognizing this, tests were conducted during the Air Force Research Lab 3D-LZ Brownout Test at the US Army Yuma Proving Ground. Photogrammetry was utilized during two rounds of flight tests with an instrumented EH-60L Black Hawk to determine if this technique could quantitatively measure the formation and evolution of a brownout cloud. Specific areas of interest include the location, size, and average convective velocity of the cloud, along with the characteristics of any defined structures within it. Following the first flight test, photogrammetric data were validated through comparison with onboard vehicle data. Lessons learned from this test were applied to the development of an improved photogrammetry system. A second flight test, utilizing the improved system, demonstrated that obtaining quantitative measurements of the brownout cloud are possible. Results from these measurements are presented in the paper. Flow visualization with chalk dust seeding was also tested. It was observed that pickup forces of the brownout cloud appear to be very low. Overall, these tests demonstrate the viability of photogrammetry as a means for quantifying brownout cloud formation and evolution.

Wong, Oliver D.↗

DOE OSTI2024

Data From Experiments on Bubbling Fluidization of Zeolite in a Rectangular Bubbling Fluidized Bed

Fluidization experiments were conducted in a lab-scale rectangular bubbling fluidized bed with the objective of generating a high-quality dataset for model validation and artificial intelligence/machine learning (AI/ML) training. Zeolite was chosen as the bed material, and the fluidizing medium was air as supplied by a compressor. Three different flow rates at the inlet were chosen such that the particles were fluidized but not elutriated from the system. The test matrix involved randomization and replicates to provide uncertainty estimates as well as four different batches of zeolite as the bed material. The quantities of interest obtained from this study were statistics of differential pressures, interface heights, and particle velocities. Considering all the components of the elaborate test plan, the results obtained were consistent and reproducible. Characterization tests were performed to estimate particle properties including size, density, coefficient of friction, coefficient of restitution, and minimum fluidization velocity. In addition, the angle of repose from granular discharge experiments has been reported to account for rolling friction, though its effect on the overall process is expected to be negligible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

NASA’s PACE Ocean Color Instrument Thermal Design Evolution: from Goddard’s Instrument Design Lab through Flight Development

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, set to launch in 2024, seeks to provide data continuity for the ocean color, aerosol and cloud measurements acquired by NASA’s on-orbit Earth Science observatories since the 1990s. It will accomplish this through its Ocean Color Instrument (OCI), an optical spectrometer being developed for hyper-spectral measurements in the ultraviolet-to-near-infrared band between 340 nm and 2260 nm. Although OCI’s instrument architecture will provide greater insight and resolution than its predecessors in this wavelength range, the engineering required to achieve this also poses a greater challenge. In thermal engineering, this translates to a more complex thermal control approach to address high heat dissipations, stringent stabilities, the volume of heat that requires transport, and changing thermal environments due to tilting of the entire instrument ±20° twice per orbit. This current work explores how the PACE OCI instrument design has evolved from its initial conception in NASA Goddard’s Instrument Design Laboratory (IDL) to the current iteration of its flight design. The IDL studies explored three separate instrument configurations and two spatial resolutions per configuration, which were then down selected to a single instrument type and spatial resolution for flight instrument development. OCI subsequently went through major project milestones, including Preliminary Design Review (PDR), Critical Design Review (CDR), Pre-Environmental Review (PER) and Pre-Ship Review (PSR), with significant design updates along the way. This paper aims to provide a comprehensive account of OCI’s thermal control architecture evolution and the engineering drivers that have shaped it, with the goal of identifying trends spanning the full instrument development timeline to inform and advance future instrument thermal designs.

PACE↗

NASA NTRSDate not supplied

NASA’s PACE Ocean Color Instrument Thermal Design Evolution: from Goddard’s Instrument Design Lab through Flight Development

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, set to launch in 2024, seeks to provide data continuity for the ocean color, aerosol and cloud measurements acquired by NASA’s on-orbit Earth Science observatories since the 1990s. It will accomplish this through its Ocean Color Instrument (OCI), an optical spectrometer being developed for hyper-spectral measurements in the ultraviolet-to-near-infrared band between 340 nm and 2260 nm. Although OCI’s instrument architecture will provide greater insight and resolution than its predecessors in this wavelength range, the engineering required to achieve this also poses a greater challenge. In thermal engineering, this translates to a more complex thermal control approach to address high heat dissipations, stringent stabilities, the volume of heat that requires transport, and changing thermal environments due to tilting of the entire instrument ±20° twice per orbit. This current work explores how the PACE OCI instrument design has evolved from its initial conception in NASA Goddard’s Instrument Design Laboratory (IDL) to the current iteration of its flight design. The IDL studies explored three separate instrument configurations and two spatial resolutions per configuration, which were then down selected to a single instrument type and spatial resolution for flight instrument development. OCI subsequently went through major project milestones, including Preliminary Design Review (PDR), Critical Design Review (CDR), Pre-Environmental Review (PER) and Pre-Ship Review (PSR), with significant design updates along the way. This paper aims to provide a comprehensive account of OCI’s thermal control architecture evolution and the engineering drivers that have shaped it, with the goal of identifying trends spanning the full instrument development timeline to inform and advance future instrument thermal designs.

PACE↗

DOE OSTI2025

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2013

Wearable Technology

Wearable technology projects, to be useful, in the future, must be seamlessly integrated with the Flight Deck of the Future (F.F). The lab contains mockups of space vehicle cockpits, habitat living quarters, and workstations equipped with novel user interfaces. The Flight Deck of the Future is one element of the Integrated Power, Avionics, and Software (IPAS) facility, which, to a large extent, manages the F.F network and data systems. To date, integration with the Flight Deck of the Future has been limited by a lack of tools and understanding of the Flight Deck of the Future data handling systems. To remedy this problem it will be necessary to learn how data is managed in the Flight Deck of the Future and to develop tools or interfaces that enable easy integration of WEAR Lab and EV3 products into the Flight Deck of the Future mockups. This capability is critical to future prototype integration, evaluation, and demonstration. This will provide the ability for WEAR Lab products, EV3 human interface prototypes, and technologies from other JSC organizations to be evaluated and tested while in the Flight Deck of the Future. All WEAR Lab products must be integrated with the interface that will connect them to the Flight Deck of the Future. The WEAR Lab products will primarily be programmed in Arduino. Arduino will be used for the development of wearable controls and a tactile communication garment. Arduino will also be used in creating wearable methane detection and warning system.

Watson, Amanda↗