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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Techno-Economic Analysis of Green Hydrogen Energy Storage in A Cryogenic Flux Capacitor

The Cryogenic Flux Capacitor (CFC) is a cold, dense energy storage core that is being studied in the cryo-compressed, about 300 bar and 80K, region of gaseous hydrogen (GH 2 ) storage and liquid hydrogen (LH 2 ) region near the normal boiling point. Hydrogen storage is improved by physically bonding the molecules within the nanoscale pores of the aerogel composite blanket material. The process of bonding or debonding is governed by principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (~1,000 m 2 /g) allows its storage performance to easily exceed capacities of high-pressure GH 2 storage for an equivalent volume. With the integrated aerogel, subscale tests have shown that storage is increased by about 36% over a simple tank filled with GH 2 at the same operating temperature and pressure. For LH 2 conditions, the CFC is shown to operate at improved densities, but testing is ongoing. For the techno-economic analysis (TEA), the source of hydrogen is compared between onsite steam methane reforming (SMR) and onsite solar photovoltaic (PV) panels providing power to electrolyzers to produce green GH 2 . The TEA compares pure hydrogen produced at a small scale for a 25 MW power system and at a large scale in a 500 MW power system. The system allowed for hydrogen imports and exports at a set price with a tank sized for 10 hours of power production. The two power producing technologies are a combined cycle gas turbine (CCGT) and hydrogen fuel cells. The SMR system uses natural gas as an input and includes a carbon capture and storage (CCS) system. The levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH), and levelized cost of storage (LCOS) are developed based on the capital cost and operating cost of the systems. The results are shown for current costs using a 2021 benchmark and DOE projections for cost improvements by 2030. The TEA showed that onsite hydrogen generation from SMR has an LCOH of about 1.4 to 2 USD per kg over the life of the plant and the PV hydrogen production LCOH is about 5.2 to 5.5 USD per kg. The LCOS of conventional GH 2 systems is estimated to be $210/MWh and cost of storage for LH 2 systems is $205/MWh for fuel cell systems and $249/MWh for CCGT systems. CFC improved the LCOS of all these systems to $198/MWh, $191/MWh and $233/MWh respectively. The LCOE also improved with conventional systems between $171/MWh and $228/MWh improved by CFC to between $167/MWh and $212/MWh. Using projections for improvement in costs following DOE’s goals by 2030, green hydrogen improved to as low as $78/MWh LCOS and LCOE for conventional cases. CFC improved over conventional storage with the lowest LCOS being $62/MWh and the lowest LCOE being $73/MWh. These results correspond to an LCOH of $2/kg. Finally, the TEA shows how LCOE is improved for hydrogen conditioning and storage over conventional systems and caverns in the 10 to 50 hour range.

Joshua Schmitt↗
NASA NTRSDate not supplied

Volumetric Assessment of UPRITE Exercises From Marker-Based Motion Capture

BACKGROUND Lack of volumetric data on full-body movement of exercises presents a challenge to ensuring the fit of crew member’s full range of motion on the International Space Station (ISS). The Upright Proprioception Retention via In-flight Training and Evaluation (UPRITE) is a sensorimotor countermeasure device designed for maintaining crew members’ proprioception in a microgravity environment. A footplate—attached to a static base—rotates in two degrees of freedom (pitch and roll) up to a 20 deg angle. An initial volumetric assessment assuming an upright standing posture produced a cone-like shape with a narrow bottom and wide top. Such general volumetric assessments risk creating an overly conservative volume estimate, taking up more space than is necessary on the already limited interior space of the ISS, and neglecting necessary volume due to oversimplifying assumptions. Rather, higher-fidelity volumetric assessments offer more comprehensive insights in an environment where every area counts. The main objective of this work is to provide the spatial parameters of exercises on the UPRITE such that it is placed on the ISS according to its volumetric demands or that usage is adjusted to fit the available space. METHODS In 2023, a data collection was performed originally to inform loads and dynamics of system use and was recently leveraged for volumetric assessment. Three human subjects representing different body types (~63-76 inches in stature) performed a variety of board manipulations using UPRITE with body weight offload. The test collected the 3D positional data of a modified full-body Plug-in Gait marker set [1] via a 16-camera OptiTrack MoCap system. After processing – filling marker gaps and trimming data – in OptiTrack Motive, the recorded marker location data, which included device markers, was exported to a readable trajectory file. To accurately represent the full volume defining landmarks, additional markers were digitally added to an unscaled Modified Full Body Model [2]. The model was then scaled according to its subject parameters upon which an inverse kinematics analysis was performed. A custom plugin yielded model marker location data files. Volumetric analyses were performed on the recorded trajectory and model trajectory files using a custom Python-built tool that extracted the marker location data and plotted it in a 3D space. Concerned with only the maximum volume of the motion, a 3D convex hull analysis was applied to the plot, extracting the vertices or external points of the eventual 3D CAD output, dubbed aptly as a “volume shell”. This overall approach was based on guidance in a NASA-STD-3001 Technical Brief [3]. RESULTS AND DISCUSSION Batch volumetric assessment on the exercises for each subject was performed, producing high-fidelity volume shells in minimal time. Preliminary results highlighted the value in higher-fidelity volumes based on collected data when possible. For example, revolving a single posture in the cone assessment would not have sufficiently captured a single leg stance; rather, it would need to involve swinging the leg both forward and back. Additional observations and the maximal dimensions of the volumes, including those based on scaled data for ISS anthropometric requirements, will be presented at the Human Research Program Investigator’s Workshop. CONCLUSIONS While this work’s primary objective was for the UPRITE-to-ISS integration, the tool built to conduct this analysis has wide applications for future exercise systems as an informational tool for optimal device placement. The tool and its findings also have implications for exercise device design and spacecraft interior considerations on Gateway, the Lunar Pressurized Rover, and beyond. REFERENCES [1] Bell, C. A., et al. (2023) Recent Improvements and Verification of a Full Body Model in OpenSim. NASA Human Research Program Investigator’s Workshop. https://ntrs.nasa.gov/citations/20230001080 [2] Lostroscio, K., et al (2023) The Digital Astronaut Simulation. AHFE International Conference on Human Factors in Design, Engineering, and Computing for All. [3] Exercise Overview. (2023) NASA-STD-3001 Technical Brief. https://www.nasa.gov/wp-content/uploads/2023/12/ochmo-tb-031-exercise-overview.pdf?emrc=9d454c?emrc=9d454c

L D Quinto↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗
NASA NTRSDate not supplied

STARscan: Spatial Targeting and Alignment Rig for Scanning

The Spatial Targeting and Alignment Rig for Scanning (STARScan) is a 3D photogrammetry system developed at NASA Ames Research Center to address bottlenecks in pre/post-test scanning of arcjet test articles. It reduces scan time from 15 minutes with handheld laser scanners to under 2 minutes, while maintaining high accuracy (±0.2-0.5 mm). STARScan integrates an array of cameras, a 3D-printed rack, turntable, and LED light panels, all controlled via a user-friendly graphical user interface (GUI). The system offers tools for scan visualization, mesh analysis, and data export, automating tasks such as alignment of pre/post-test scans, material recession measurements, surface roughness assessment, and curvature analysis. By integrating scanning, imaging, and post-processing into one application, STARScan significantly improves efficiency in scanning and analyzing arcjet test samples.

Ablation↗
NASA NTRS2025

State-of-the-Art Small Spacecraft Technology

The objective of this report is to assess and provide an overview of the state of the art in small spacecraft technologies for use by mission designers, project managers, technologists, and students, connecting current small spacecraft missions to available technologies. This report focuses on the spacecraft system in its entirety, provides current best practices for integration and key considerations for the reader where possible, and presents devices from publicly available sources for each specific spacecraft subsystem. This report is a survey of small spacecraft technologies sourced from open literature; it is not an original source. In addition, this report only considers literature in the public domain. Information presented in this report is limited to SmallSat technology that is publicly available as of September 30, 2024. It does not include information on instrumentation, science payloads, or advances or developments that have not been publicly disclosed. Commonly used sources for data include manufacturer data sheets, press releases, conference papers, journal papers, public filings with government agencies, news articles, presentations, the compendium of databases accessed via NASA’s Small Spacecraft Systems Virtual Institute (S3VI) Information Search, and engagement with companies. Data not appropriate for public dissemination, such as proprietary, export controlled, or otherwise restricted data, are not considered. We encourage the SmallSat community to publish mission outcomes and technology development milestones in publicly available conference papers, press releases, or company websites so they can be reflected in future editions of this report. This report is funded by NASA’s Space Technology Mission Directorate (STMD). It was first commissioned by the Small Spacecraft Technology (SST) program within NASA’s STMD in mid2012 in response to the rapid growth in interest in using small spacecraft for low-Earth orbit, lowcost missions. The report was subsequently updated in 2015, 2018, 2020, 2021, 2022, and 2023 to capture SmallSat technology growth and maturation. In addition to reporting currently available state-of-the-art technologies that have achieved Technology Readiness Level (TRL) 5 or above, a prognosis is provided describing technologies as "on the horizon" if they are being considered for future application.

Sasha V Weston↗
NASA NTRS2026

Turbofan Engine Power Extraction Demonstration Final Report

As GE Aerospace advances toward a revolutionary step change in propulsion efficiency, the integration and demonstration of new engine architectures and technology systems are essential. The NASA Turbofan Engine Power Extraction Demonstration (PEx), conducted through the Hybrid Thermally Efficient Core (HyTEC) project, aims to develop and demonstrate megawatt-class hybrid electric capability on a modern commercial turbofan engine. The hybrid electric system is critical to meeting the needs of the U.S. aviation industry for next-generational propulsion systems with greater efficiency, durability, and range. This supports energy independence and helps ensure the security and resilience of one of America's largest export industries. The PEx project specifically targets three key objectives: mechanically integrating hybrid electric capability into a commercial turbofan engine, integrating electric machine control with turbofan control for advanced power management, and de-risking performance modeling of future hybrid electric architectures. To mature these technologies to Technology Readiness Level (TRL) 6, a series of electric power system component tests and a baseline engine performance test campaign were conducted. These efforts culminated in an integrated hybrid electric turbofan test campaign demonstrating power extraction, power insertion, and power transfer between spools. Tests of the electric power system were completed at GE Aerospace’s Electrical Power Integrated Systems Center in Dayton, Ohio and engine tests were completed at Peebles Test Operation in Peebles, Ohio. Hybrid electric trade studies extended the demonstrated capability to altitude using the validated cycle model from the PEx test campaigns, allowing for comments on expanded mission benefits not demonstrated in the ground campaign. The knowledge gained from PEx also supports GE Aerospace’s Compact Core Demonstrator as part of HyTEC Phase 2 and ultimately informs the implementation of hybrid electric systems in the next generation of GE Aerospace commercial engine products. This report provides a summary of the program background, test campaigns, trade studies, and insights into the technical maturation required to support future commercial products.

Hybrid Electric↗
DOE OSTI2014

Relative importance of multiple factors on terrestrial loading of DOC to Arctic river networks

Terrestrial carbon dynamics influence the contribution of dissolved organic carbon (DOC) to river networks in addition to controlling carbon fluxes between the land surface and the atmosphere. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that the pan-arctic watershed has contributed, on average, 32 Tg C/yr of DOC to the Arctic Ocean over the 20th century with most coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of increases in air temperatures and precipitation. These increases have been partially compensated by decreases in terrestrial DOC loading caused by wildfires. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both compensated and enhanced concurrent effects on hydrology to influence terrestrial DOC loading. Future increases in riverine DOC concentrations and export may occur from warming-induced increases in terrestrial DOC production associated with enhanced microbial metabolism and the exposure of additional organic matter from permafrost degradation along with decreases in water yield associated with warming-induced increases in evapotranspiration. Improvements in simulating terrestrial DOC loading to pan-arctic rivers in the future will require better information on the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic effluents on carbon budgets of rivers in western Russia.

Kicklighter, David W.↗
DOE OSTI2014

Tool coupling for the design and operation of building energy and control systems based on the Functional Mock-up Interface standard

This paper describes software tools developed at the Lawrence Berkeley National Laboratory (LBNL) that can be coupled through the Functional Mock-up Interface standard in support of the design and operation of building energy and control systems. These tools have been developed to address the gaps and limitations encountered in legacy simulation tools. These tools were originally designed for the analysis of individual domains of buildings, and have been difficult to integrate with other tools for runtime data exchange. The coupling has been realized by use of the Functional Mock-up Interface for co-simulation, which standardizes an application programming interface for simulator interoperability that has been adopted in a variety of industrial domains. As a variety of coupling scenarios are possible, this paper provides users with guidance on what coupling may be best suited for their application. Furthermore, the paper illustrates how tools can be integrated into a building management system to support the operation of buildings. These tools may be a design model that is used for real-time performance monitoring, a fault detection and diagnostics algorithm, or a control sequence, each of which may be exported as a Functional Mock-up Unit and made available in a building management system as an input/output block. We anticipate that this capability can contribute to bridging the observed performance gap between design and operational energy use of buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Comprehensive ecosystem model-experiment synthesis using multiple datasets at two temperate forest free-air CO2 enrichment experiments: model performance and compensating biases

Free Air CO2 Enrichment (FACE) experiments provide a remarkable wealth of data to test the sensitivities of terrestrial ecosystem models (TEMs). In this study, a broad set of 11 TEMs were compared to 22 years of data from two contrasting FACE experiments in temperate forests of the south eastern US the evergreen Duke Forest and the deciduous Oak Ridge forest. We evaluated the models' ability to reproduce observed net primary productivity (NPP), transpiration and Leaf Area index (LAI) in ambient CO2 treatments. Encouragingly, many models simulated annual NPP and transpiration within observed uncertainty. Daily transpiration model errors were often related to errors in leaf area phenology and peak LAI. Our analysis demonstrates that the simulation of LAI often drives the simulation of transpiration and hence there is a need to adopt the most appropriate of hypothesis driven methods to simulate and predict LAI. Of the three competing hypotheses determining peak LAI (1) optimisation to maximise carbon export, (2) increasing SLA with canopy depth and (3) the pipe model the pipe model produced LAI closest to the observations. Modelled phenology was either prescribed or based on broader empirical calibrations to climate. In some cases, simulation accuracy was achieved through compensating biases in component variables. For example, NPP accuracy was sometimes achieved with counter-balancing biases in nitrogen use efficiency and nitrogen uptake. Combined analysis of parallel measurements aides the identification of offsetting biases; without which over-confidence in model abilities to predict ecosystem function may emerge, potentially leading to erroneous predictions of change under future climates.

Walker, Anthony P↗
DOE OSTI2014

Secret Objective Standoff: International Safeguards Educational Exercise

The International Safeguards Regime, being so multi-faceted, can be overwhelming to those first introduced to its many components. The organizers and lecturers of workshops and courses on nonproliferation often provide a series of independent lectures and must somehow demonstrate the cohesive and effective nature of the system. An exercise titled The Secret Objective Standoff was developed to complement lectures with hands-on learning to assist participants in bringing all the many components (IAEA agreements, export controls, treaty obligations, international diplomacy, etc.) of the International Safeguards Regime together. This exercise divides participants into teams that are assigned the role of either a country or the IAEA and asks that they fully immerse themselves in their roles. The teams are then randomly assigned three unique and secret objectives that are intended to represent realistic and current geopolitical scenarios. Through construction, trading, or hoarding of four resources (experts, technology, money, and uranium), the teams have a finite number of turns to accomplish their objectives. Each turn has three phases random dispersal of resources, a timed discussion where teams can coordinate and strategize with others, and an action phase. During the action phase, teams inform the moderator individually and secretly what they will be doing that turn. The exercise has been tested twice with Oak Ridge National Laboratory personnel, and has been conducted with outside participants twice, in each case the experience was well received by both participants and instructors. This exercise provides instructors the ability to modify the exercise before or during game play to best fit their educational goals. By offering a range of experiences, from an in-depth look at specific components to a generalized overview, this exercise is an effective tool in helping participants achieve a full understanding the International Safeguards Regime.

Okowita, Samantha L↗
DOE OSTI2014

A Visual Analytics Approach to Structured Data Analysis to Enhance Nonproliferation and Arms Control Verification Activities

Analysis activities for Nonproliferation and Arms Control verification require the use of many types of data. Tabular structured data, such as Excel spreadsheets and relational databases, have traditionally been used for data mining activities, where specific queries are issued against data to look for matching results. The application of visual analytics tools to structured data enables further exploration of datasets to promote discovery of previously unknown results. This paper discusses the application of a specific visual analytics tool to datasets related to the field of Arms Control and Nonproliferation to promote the use of visual analytics more broadly in this domain. Visual analytics focuses on analytical reasoning facilitated by interactive visual interfaces (Wong and Thomas 2004). It promotes exploratory analysis of data, and complements data mining technologies where known patterns can be mined for. Also with a human in the loop, they can bring in domain knowledge and subject matter expertise. Visual analytics has not widely been applied to this domain. In this paper, we will focus on one type of data: structured data, and show the results of applying a specific visual analytics tool to answer questions in the Arms Control and Nonproliferation domain. We chose to use the T.Rex tool, a visual analytics tool developed at PNNL, which uses a variety of visual exploration patterns to discover relationships in structured datasets, including a facet view, graph view, matrix view, and timeline view. The facet view enables discovery of relationships between categorical information, such as countries and locations. The graph tool visualizes node-link relationship patterns, such as the flow of materials being shipped between parties. The matrix visualization shows highly correlated categories of information. The timeline view shows temporal patterns in data. In this paper, we will use T.Rex with two different datasets to demonstrate how interactive exploration of the data can aid an analyst with arms control and nonproliferation verification activities. Using a dataset from PIERS (PIERS 2014), we will show how container shipment imports and exports can aid an analyst in understanding the shipping patterns between two countries. We will also use T.Rex to examine a collection of research publications from the IAEA International Nuclear Information System (IAEA 2014) to discover collaborations of concern. We hope this paper will encourage the use of visual analytics structured data analytics in the field of nonproliferation and arms control verification. Our paper outlines some of the challenges that exist before broad adoption of these kinds of tools can occur and offers next steps to overcome these challenges.

arms control↗
DOE OSTI2014

Stopping Illicit Procurement: Lessons from Global Finance

Government regulators and the financial sector cooperate to combat money laundering and terrorist financing. This information-sharing relationship is built upon a strong legislative foundation and effective operational procedures. As with money-laundering and terrorist financing, halting the illicit procurement of dual-use commodities requires close coordination between government and industry. However, many of the legal and operational features present in financial threat cooperation do not exist in the export control realm. This article analyzes the applicability of financial industry cooperative measures to nonproliferation.

Finance↗
DOE OSTI2015

GOTTCHA, Version 1

One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions. In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure. During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical "shape" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably. During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.

Freitas, Tracey↗
DOE OSTI2015

GOTTCHA Database, Version 1

One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions.In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure.During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical "shape" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably.During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.The DATABASE provided is the result of the algorithm described.

Freitas, Tracey↗
DOE OSTI2014

Accessorizing Building Science – A Web Platform to Support Multiple Market Transformation Programs

As demand for improved energy efficiency in homes increases, builders need information on the latest findings in building science, rapidly ramping-up energy codes, and technical requirements for labeling programs. The Building America Solution Center is a Department of Energy (DOE) website containing hundreds of expert guides designed to help residential builders install efficiency measures in new and existing homes. Builders can package measures with other media for customized content. Website content provides technical support to market transformation programs such as ENERGY STAR and has been cloned and adapted to provide content for the Better Buildings Residential Program. The Solution Center uses the Drupal open source content management platform to combine a variety of media in an interactive manner to make information easily accessible. Developers designed a unique taxonomy to organize and manage content. That taxonomy was translated into web-based modules that allow users to rapidly traverse structured content with related topics, and media. We will present information on the current design of the Solution Center and the underlying technology used to manage the content. The paper will explore development of features, such as “Field Kits” that allow users to bundle and save content for quick access, along with the ability to export PDF versions of content. Finally, we will discuss development of an Android based mobile application, and a visualization tool for interacting with Building Science Publications that allows the user to dynamically search the entire Building America Library.

Madison, Michael C.↗
DOE OSTI2016

Arrowland v1.0

"Arrowland" is a web-based software application primarily for mapping, integrating and visualizing a variety of metabolism data of living organisms, including but not limited to metabolomics, proteomics, transcriptomics and fluxomics. This software application makes multi-omics data analysis intuitive and interactive. It improves data sharing and communication by enabling users to visualize their omics data using a web browser (on a PC or mobile device). It increases user's productivity by simplifying multi-omics data analysis using well developed maps as a guide. Users using this tool can gain insights into their data sets that would be difficult or even impossible to tease out by looking at raw number, or using their currently existing toolchains to generate static single-use maps. Arrowland helps users save time by visualizing relative changes in different conditions or over time, and helps users to produce more significant insights faster. Preexisting maps decrease the learning curve for beginners in the omics field. Sets of multi-omics data are presented in the browser, as a two-dimensional flowchart resembling a map, with varying levels of detail information, based on the scaling of the map. Users can pan and zoom to explore different maps, compare maps, upload their own research data sets onto desired maps, alter map appearance in ways that facilitate interpretation, visualization and analysis of the given data, and export data, reports and actionable items to help the user initiative.

BIRKEL, GARRETT↗
DOE OSTI2016

Sandbox for Mac Malware v 1.0

This software is an analyzer for automated sandbox analysis of malware on the OS X operating system. It runs inside an OS X virtual machine to collect data about what happens when a given file is opened or run. As of August 2014, there was no sandbox software for Mac OS X malware, as it requires different methods from those used on the Windows OS (which most sandboxes are written for). This software adds OS X analysis capabilities to an existing open-source sandbox, Cuckoo Sandbox (http://cuckoosandbox.org/), which previously only worked for Windows. The analyzer itself can take many different types of files as input: the traditional Mach-O and FAT executables, .app files, zip files, Python scripts, Java archives, and web pages, as well as PDFs and other documents. While the file is running, the analyzer also simulates rudimentary human interaction with clicks and mouse movements in order to bypass the tests some malware use to see if they are being analyzed. The analyzer outputs several different kinds of data: function call traces, network captures, screenshots, and all created and modified files. This work also includes a static analysis Cuckoo module for Mach-O binary files. It extracts file structures, code library imports and exports, and signatures. This data can be used along with the analyzer results to create signatures for malware.

Walkup, Elizabeth↗
DOE OSTI2016

Operational Benefits of Meeting California's Energy Storage Targets

In October 2013, the California Public Utilities Commission (CPUC) finalized procurement targets and other requirements to its jurisdictional utilities for a minimum of 1,325 MW of 'viable and cost-effective' energy storage systems by 2020. The goal of this study is to explore several aspects of grid operations in California and the Western Interconnection resulting from meeting the CPUC storage targets. We perform this analysis using a set of databases and grid simulation tools developed and implemented by the CPUC, the California Independent System Operator (CAISO), and the California Energy Commission (CEC) for the CPUC's Long-term Procurement Plan (LTPP). The 2014 version of this database contains information about generators, storage, transmission, and electrical demand, for California in the year 2024 for both 33 percent and 40 percent renewable energy portfolios. We examine the value of various services provided by energy storage in these scenarios. Sensitivities were performed relating to the services energy storage can provide, the capacity and duration of storage devices, export limitations, and negative price floor variations. Results show that a storage portfolio, as outlined by the CPUC, can reduce curtailment and system-wide production costs for 33 percent and 40 percent renewable scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗