Search NASA⌕ Search

SEARCH · Search NASA

Results for “experimental database”

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.

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

At least 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Impact of CH 4 addition on the electron properties and electric field dynamics in a Ar nanosecond-pulsed dielectric barrier discharge

Non-equilibrium plasmas derive their low temperature reactivity from producing and driving energetic electrons and active species under large electric fields. Therefore, the impact of reactants on the plasma properties including electron number density, electric field, and electron temperature is critical for applications such as plasma CH 4 reforming. Due to experimental complexity, electron properties and the electric field are rarely measured together in the same discharge. Here, we combine time-resolved Thomson scattering and electric field induced second harmonic generation (EFISH) to probe electron temperature, electron density, and electric field strength in a 60 Torr CH 4 /Ar nanosecond-pulsed dielectric barrier discharge (ns-DBD) while varying the CH 4 mole fraction from 0 to 8%. These measurements are compared to a 1-D numerical model to benchmark its predictions and identify areas of uncertainty. Nonlinear coupling between CH 4 addition, electron temperature, electron density, and the electric field was directly observed. Contrary to previous measurements in He, the electron temperature increased with CH 4 mole fraction. This rise in electron temperature is identified as electron heating by residual electric fields that increased with larger CH 4 mole fraction. Moreover, the electron number density has been found to decrease rapidly with the increase of methane mole fraction. Comparison of these measurements with the model yielded better agreement at higher CH 4 mole fractions and with the usage of ab initio calculated Ar electron-impact cross-sections from the B-spline R-matrix (BSR) database. Furthermore, the calculated plasma properties are shown to be sensitive to the residual surface charge implanted on the quartz dielectric surfaces. Without considering surface charge in the simulations, the calculated electric field profiles agreed well with the measurements, but the electron properties were underpredicted by more than a factor of three. Therefore, measurements of either the electric field or electron properties measurements alone are insufficient to fully validate modelling predictions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Diffusion coefficients of transition metals in fcc cobalt

Using first-principles density functional theory (DFT), we calculate the diffusivities of 32 different solute elements—all transition metals, together with Al and Si—in fcc cobalt within the formalism of the five-frequency model. For self-diffusion in fcc cobalt, we compare the accuracy of various approximations to the exchange-correlation energy functional of DFT in estimating the activation energy, and find that only the Perdew-Burke-Ernzerhof (PBE) approximation agrees well with experimental reports and all other functionals largely overestimate it. Our calculations also show that an accurate estimation of the self-diffusion coefficient requires explicit calculation of the effective jump frequency and vacancy formation entropy via phonons. Using accurate self-diffusion data and scaling all solute-related attempt frequencies with respect to the attempt frequency for self-diffusion using a simple relation involving the atomic mass and melting temperature of the solute yields solute diffusivities in excellent agreement with experiments, where such data is available. Additionally, we find that large solutes spontaneously relax toward the nearest neighbor vacancy to relieve the misfit strain, and the extent of this relaxation correlates negatively with the migration energy. Thus, in general, larger solutes have lower migration energies and diffuse faster than smaller solutes in fcc cobalt. However, extremely large solutes, e.g., group III elements Sc, Y, Lu, tend to be trapped in an energy valley located halfway toward the vacancy, and monovacancy mediated diffusion may no longer be valid in such cases. Finally, for all the solutes considered, we systematically tabulate the diffusion-related quantities calculated—diffusion prefactors, migration and activation energies—constructing an extensive and accurate first-principles database for solute diffusion in fcc cobalt.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Comparative Genomics and Functional Analysis of Carbohydrate Utilization Networks in Unicyanobacterial Consortia Derived from Hypersaline Lake Microbial Mats

Hot Lake is a meromictic, hypersaline lake located in Washington state, USA. It harbors a phototrophic microbial mat community stable in dramatic seasonal environmental changes. The complexity of natural community hinders to analyze metabolic interactions between its members. To manage this obstacle, unicyanobacterial consortia (UCC) were sampled from the community and sequenced. UCC is a microbial community in which one cyanobacterium serves as the sole primary producer of carbon sources to several heterotrophic bacteria. Recently available metagenomes for two UCC revealed a shared set of 19 microbial operational taxonomic units (OTU), whose individual genomes were reconstructed by co‐assembly and abundance profile binning. We used this genomic data and a comparative genomics approach to infer carbohydrate utilization pathways and their transcription regulation. We scanned all UCC proteomes against the KEGG Orthology, Pfam, GO and SEED databases to reveal genes potentially involved in sugar utilization. Then we analyzed the genomic and functional contexts of gene loci encoding the obtained proteins and reconstructed the respective metabolic pathways and transcriptional regulons. As result, we observed catabolic pathways for 32 various carbohydrates and their derivatives. Distribution of the inferred catabolic pathways has highly mosaic structure across the UCC genomes. The largest number of pathways was observed in two representatives of the Halomonas genus (14–15 pathways) and one Rhodobacteriaceae sp. (15 pathways). In other UCC genomes, we found up to 10 carbohydrate utilization pathways per genome. However in 7 genomes we didn't observe any pathway. The most widely distributed pathways in UCC were the alpha‐glucosides and the DeLey‐Doudoroff galactose utilization pathways. Both were found in 7 genomes. Majority of pathways are distributed among 1–3 genomes. The reconstructed catabolic pathways were partially validated by phenotypic analyses of UCC community members that were isolated in a pure culture. In the Rhodobacteriaceae sp., we found a novel catabolic pathway that was proposed to be involved in mannoheptulose utilization. To our knowledge, the proposed mannoheptulose catabolic pathway is the first case of a pathway for heptose utilization and will require further experimental validation. The identified pathways are potentially regulated by local transcription factors (TFs) that are often co‐localized with the respective sugar catabolic gene loci. For 63 out of the 80 identified TFs we identified their cognate DNA binding motifs and reconstructed regulons using the bioinformatics approach. Support or Funding Information This research was supported by the Genomic Science Program (GSP), Office of Biological and Environmental Research (OBER), and U.S. Department of Energy (DOE) and is a contribution of the Pacific Northwest National Laboratory (PNNL) Foundational Scientific Focus Area.

Leyn, Semen A.↗
DOE OSTI2025

Towards Automatically Matching Security Advisories to CPEs: String Similarity-based Vendor Matching

When a vulnerability is reported by the National Vulnerability Database (NVD), affected products are listed in the structured Common Platform Enumeration (CPE) format. Unfortunately, if the vulnerability is in a software library (e.g., Log4j), it will not include CPEs for each product containing that library. In these cases, security operators need to manually read the vendor's or third-party security advisories to see if their product is affected. However, these advisories do not report affected products in a structured format, which prevents automated processing, This paper makes the first effort towards automatically constructing structured CPEs for the vulnerable products in a non-NVD security advisory from the unstructured data in the advisory. Since this is a very challenging problem, this paper specifically focuses on the initial but key step of matching the un-structured vendor names in security advisories to the structured vendor representations in the standard CPE format. We explore the feasibility of using string similarity to solve the problem. The basic idea is to compare a vendor name from the non-NVD advisory with each vendor in the official CPE dictionary. The CPE vendor with the highest similarity score to the advisory's vendor will be considered as the match. We first conduct an experimental, comparative study of multiple mainstream string similarity metrics for this matching problem. To improve the performance, we then design a new string similarity metric that is adapted from an existing metric by weighing different tokens in the advisory's vendor name differently.

McClanahan, Kylie↗
DOE OSTI2017

A Scientific Data Provenance Harvester for Distributed Applications

Data provenance provides a way for scientists to observe how experimental data originates, conveys process history, and explains influential factors such as experimental rationale and associated environmental factors from system metrics measured at runtime. The US Department of Energy Office of Science Integrated end-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows (IPPD) project has developed a provenance harvester that is capable of collecting observations from file based evidence typically produced by distributed applications. To achieve this, file based evidence is extracted and transformed into an intermediate data format inspired in part by W3C CSV on the Web recommendations, called the Harvester Provenance Application Interface (HAPI) syntax. This syntax provides a general means to pre-stage provenance into messages that are both human readable and capable of being written to a provenance store, Provenance Environment (ProvEn). HAPI is being applied to harvest provenance from climate ensemble runs for Accelerated Climate Modeling for Energy (ACME) project funded under the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) Earth System Modeling (ESM) program. ACME informally provides provenance in a native form through configuration files, directory structures, and log files that contain success/failure indicators, code traces, and performance measurements. Because of its generic format, HAPI is also being applied to harvest tabular job management provenance from Belle II DIRAC scheduler relational database tables as well as other scientific applications that log provenance related information.

Stephan, Eric G.↗
NASA NTRSDate not supplied

Space Flown Rodent Liver RNA Sequencing Data for Machine Learning in Space Biology Research

High-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. Data analysis has been accelerated in recent years by the adoption of artificial intelligence (AI) and machine learning (ML) techniques by biomedical researchers. In space biology research, RNAseq datasets from space-flown experimental samples are critical for characterizing the gene expression aberrations associated with exposure to spaceflight stressors. However, space biological experiments tend to be very low sample size, so identifying proper AI/ML algorithms for sequencing data analysis is an ongoing challenge since these algorithms typically require large sample size. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML”, focused on creating datasets meant for three main applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. These scientific benchmarks consist of an AI-ready dataset and a reference implementation on a specific scientific question. In this work, we focused on generating standardized datasets to allow the scientific community to benchmark AI/ML algorithms in the domain of space biology. We present here a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data as a collaboration between the NASA AI4LS (Artificial Intelligence for Life Sciences) working group. and NASA’s SMD. This dataset consists of space-flown and ground control mouse liver found in the NASA GeneLab omics database. However, to amplify the small sample number (n=112 samples) for ML purposes, we employ Gaussian noise and a generative adversarial network to extend this dataset to 6,000 synthetic samples, matching the original gene expression characteristics.

James Casaletto↗
DOE OSTI2014

AGR-2 Final Data Qualification Report for U.S. Capsules - ATR Cycles 147A Through 154B

This report provides the data qualification status of AGR-2 fuel irradiation experimental data in four U.S. capsules from all 15 Advanced Test Reactor (ATR) Cycles 147A, 148A, 148B, 149A, 149B, 150A, 150B, 151A, 151B, 152A, 152B, 153A, 153B, 154A, and 154B, as recorded in the Nuclear Data Management and Analysis System (NDMAS). Thus, this report covers data qualification status for the entire AGR-2 irradiation and will replace four previously issued AGR-2 data qualification reports (e.g., INL/EXT-11-22798, INL/EXT-12-26184, INL/EXT-13-29701, and INL/EXT-13-30750). During AGR-2 irradiation, two cycles, 152A and 153A, occurred when the ATR core was briefly at low power, so AGR-2 irradiation data are not used for physics and thermal calculations. Also, two cycles, 150A and 153B, are Power Axial Locator Mechanism (PALM) cycles when the ATR power is higher than during normal cycles. During the first PALM cycle, 150A, the experiment was temporarily moved from the B-12 location to the ATR water canal and during the second PALM cycle, 153B, the experiment was temporarily moved from the B-12 location to the I-24 location to avoid being overheated. During the “Outage” cycle, 153A, seven flow meters were installed downstream from seven Fission Product Monitoring System (FPMS) monitors to measure flows from the monitors and these data are included in the NDMAS database.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2019

The Effect of Incoming Boundary Layer Characteristics on the Performance of a Distributed Propulsion System

An experimental study is conducted in an effort to advance the understanding of flow physics associated with a boundary layer ingesting, distributed propulsion system. The influence of incoming boundary layer thickness and flow distortions are studied on the flow downstream and the overall performance of the system. The propulsion model, fabricated using additive manufacturing and integrated with electrical fans, is mounted on a flat plate and tested at subsonic speeds. Detailed characterization of the incoming boundary layer and subsequent assessment of the downstream flow field is performed using hotwire anemometry. Modification of the incoming boundary layer is achieved by placing tripping devices, such as rods and vortex generating ramps, near the leading edge of the flat plate. The overall performance of the system for different incoming flow conditions is analyzed by comparing magnitudes of exhaust velocities as well as estimated propulsive power to the corresponding baseline values. For a constant input power to the fans, smaller upstream flow distortions and moderately thickened boundary layers result in marginal changes in the flow field downstream. On the other hand, notable reductions in downstream flow velocities and propulsive power are observed in the case of a significantly thicker and/or distorted incoming boundary layer. It is hoped that this study will serve as a database for this technologically relevant flow field that has not been explored adequately before.

Propulsion↗
DOE OSTI2015

Active site and laminarin binding in glycoside hydrolase family 55

The Carbohydrate Active Enzyme (CAZy) database indicates that glycoside hydrolase family 55 (GH55) contains both endo- and exo-β-1,3-glucanases. The founding structure in the GH55 is PcLam55A from the white rot fungus Phanerochaete chrysosporium . Here, we present high resolution crystal structures of bacterial SacteLam55A from the highly cellulolytic Streptomyces sp. SirexAA-E with bound substrates and product. These structures, along with mutagenesis and kinetic studies, implicate Glu-502 as the catalytic acid (as proposed earlier for Glu-663 in PcLam55A) and a proton relay network of four residues in activating water as the nucleophile. Further, a set of conserved aromatic residues that define the active site apparently enforce an exo-glucanase reactivity as demonstrated by exhaustive hydrolysis reactions with purified laminarioligosaccharides. Two additional aromatic residues that line the substrate-binding channel show substrate-dependent conformational flexibility that may promote processive reactivity of the bound oligosaccharide in the bacterial enzymes. Gene synthesis carried out on ~30% of the GH55 family gave 34 active enzymes (19% functional coverage of the nonredundant members of GH55). These active enzymes reacted with only laminarin from a panel of 10 different soluble and insoluble polysaccharides and displayed a broad range of specific activities and optima for pH and temperature. Furthermore, application of this experimental method provides a new, systematic way to annotate glycoside hydrolase phylogenetic space for functional properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Exascale Co-design for Modeling Materials in Extreme Environments

Computational materials science has provided great insight into the response of materials under extreme conditions that are difficult to probe experimentally. For example, shock-induced plasticity and phase transformation processes in single-crystal and nanocrystalline metals have been widely studied via large-scale molecular dynamics simulations, and many of these predictions are beginning to be tested at advanced 4th generation light sources such as the Advanced Photon Source (APS) and Linac Coherent Light Source (LCLS). I will describe our simulation predictions and their recent verification at LCLS, outstanding challenges in modeling the response of materials to extreme mechanical and radiation environments, and our efforts to tackle these as part of the multi-institutional, multi-disciplinary Exascale Co-design Center for Materials in Extreme Environments (ExMatEx). ExMatEx has initiated an early and deep collaboration between domain (computational materials) scientists, applied mathematicians, computer scientists, and hardware architects, in order to establish the relationships between algorithms, software stacks, and architectures needed to enable exascale-ready materials science application codes within the next decade. We anticipate that we will be able to exploit hierarchical, heterogeneous architectures to achieve more realistic large-scale simulations with adaptive physics refinement, and are using tractable application scale-bridging proxy application testbeds to assess new approaches and requirements. Such current scale-bridging strategies accumulate (or recompute) a distributed response database from fine-scale calculations, in a top-down rather than bottom-up multiscale approach.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Southwest Regional Partnership on Carbon Sequestration: Phase III (Final Scientific/Technical Report)

The Southwest Regional Partnership on Carbon Sequestration (SWP) is one of 7 regional partnerships formed in 2003 under the U.S. Department of Energy’s (DOE) Regional Carbon Sequestration Partnerships (RCSPs) initiative. The overall purpose of the initiative was to help determine and implement the technology, infrastructure, and regulations most appropriate to promote carbon storage in different regions of the country. Covering Arizona, Colorado, New Mexico, Oklahoma, Utah, and parts of Texas, Wyoming, and Kansas, the SWP evaluated regional carbon storage and utilization potential and focused on technologies and sites that could complement the region’s strong position in energy production. The project progressed through three phases: • Phase I (2003–2005): Characterized regional geologic formations and CO 2 sources, assessed sequestration potential, and identified pilot test sites. • Phase II (2005–2013): Conducted small-scale field tests to validate sequestration methods, including geologic and terrestrial projects. • Phase III (2008–2022): Demonstrated large-scale CO 2 injection at a commercial oil field to test monitoring, verification, and long-term storage strategies. This report covers Phase III. The final project site, the Farnsworth Unit (FWU) in Texas, provided real-world testing of reservoir characterization, monitoring, and risk evaluation tools and processes that could be used in any commercial scale carbon capture, utilization, and storage (CCUS) project. Extensive data collection and analysis helped refine best practices for reservoir characterization, injection monitoring, and storage verification. The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Key lessons learned include the importance of robust data management, strategic site selection, regulatory navigation, and effective industry collaboration. The project’s findings will inform ongoing and future carbon storage initiatives. Task 1 (Regional Characterization) • The SWP continued to participate in national outreach efforts and NATCARB. • The SWP evaluated multiple potential sites before selecting the FWU as the primary field test location. Task 2 (Public Outreach and Education) • The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Task 3 (Permitting and Regulatory Compliance) • The SWP ensured compliance with federal and state regulations, including National Environmental Policy Act (NEPA) requirements. • The SWP obtained all necessary permits for drilling, injection, and monitoring activities. Task 4 (Site Characterization and Planning) • The SWP developed work plans for four key activities: characterization, simulation, monitoring and verification, and risk evaluation. • The SWP collected and synthesized legacy data from multiple sources to build initial static geological models and dynamic reservoir models demonstrating project feasibility. • The SWP conducted an initial risk evaluation and developed mitigation plans. Task 5 (Field Operations and Data Collection) • The SWP drilled, logged, and cored three characterization wells to gather critical subsurface data. • The SWP conducted multiple geophysical surveys, including 3D seismic, crosswell seismic, and vertical seismic profiling, to improve reservoir characterization. Task 6 (Monitoring and Verification) • The SWP performed extensive geological characterization using data from characterization wells and seismic surveys. • The SWP established a surface monitoring network to track CO 2 flux in soil gas, groundwater chemistry, and near-surface atmospheric CO 2 levels. • The SWP built and refined reservoir models to study the effects of relative permeability on simulation behavior and improve calibration with experimental data. Task 7 (Risk Assessment and Model Refinement) • The SWP conducted multiple studies to evaluate reservoir integrity, predict CO 2 plume behavior and improve predictive modeling capabilities. • The SWP refined geological models and used them to enhance the accuracy of simulation models. • The SWP continued quantitative risk assessment of top-ranked risks and strengthened the link between qualitative and quantitative risk methodologies.

02 PETROLEUM↗
DOE OSTI2016

Can I solve my structure by SAD phasing? Planning an experiment, scaling data and evaluating the useful anomalous correlation and anomalous signal

A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. Here, we describe algorithms and tools for evaluating and optimizing the useful anomalous correlation and the anomalous signal in a SAD experiment. A simple theoretical framework [Terwilliger et al. (2016), Acta Cryst. D 72 , 346–358] is used to develop methods for planning a SAD experiment, scaling SAD data sets and estimating the useful anomalous correlation and anomalous signal in a SAD data set. The phenix.plan_sad_experiment tool uses a database of solved and unsolved SAD data sets and the expected characteristics of a SAD data set to estimate the probability that the anomalous substructure will be found in the SAD experiment and the expected map quality that would be obtained if the substructure were found. The phenix.scale_and_merge tool scales unmerged SAD data from one or more crystals using local scaling and optimizes the anomalous signal by identifying the systematic differences among data sets, and the phenix.anomalous_signal tool estimates the useful anomalous correlation and anomalous signal after collecting SAD data and estimates the probability that the data set can be solved and the likely figure of merit of phasing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Puromycin-resistant lentiviral control shRNA vector, pLKO.1 induces unexpected cellular differentiation of P19 embryonic stem cells

RNA silencing is used as a common method for investigating loss-of-function effects of genes of interest. In mammalian cells, RNA interference (RNAi) or RNA silencing can be achieved by transient siRNA (small or short interfering RNA) transfection or by stable shRNA (short hairpin RNA) systems. Various vectors are used for efficient delivery of shRNA. Lentiviral vectors offer an efficient delivery system for stable and long-term expression of the shRNA in mammalian cells. The widely used lentiviral pLKO.1 plasmid vector is very popular in RNAi studies. A large RNAi database, a TRC (the RNAi Consortium) library, was established based on the pLKO.1-TRC plasmid vector. This plasmid (also called pLKO.1-puro) has a puromycin-resistant gene for selection in mammalian cells along with designs for generating lentiviral particles as well for RNA silencing. While using the pLKO.1-puro TRC control shRNA plasmid for transfection in murine P19 embryonic stem (ES) cells, it was unexpectedly discovered that this plasmid vector induced robust endodermal differentiation. Since P19 ES cells are pluripotent and respond to external stimuli that have the potential to alter the phenotype and thus its stemness, other cell types used in RNA silencing studies do not display the obvious effect and therefore, may affect experiments in subtle ways that would go undetected. This study for the first time provides evidence that raises concern and warrants extreme caution while using the pLKO.1-puro control shRNA vector because of its unexpected non-specific effects on cellular integrity. - Highlights: • In P19 ES cells the pLKO.1-puro lentiviral control shRNA vector induced endodermal differentiation. • P19 ES cells harboring the pCDNA3 plasmid vector retained their stem-ness as opposed to those harboring the pLKO.1-puro vector. • P19 ES cells can serve as a sensor to determine vector safety. • Extreme caution is warranted while using the widely used pLKO.1-puro lentiviral vector for experimental and therapeutic designs.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2016

Automated ISS Flight Utilities

During my internship at NASA Johnson Space Center, I worked in the Space Radiation Analysis Group (SRAG), where I was tasked with a number of projects focused on the automation of tasks and activities related to the operation of the International Space Station (ISS). As I worked on a number of projects, I have written short sections below to give a description for each, followed by more general remarks on the internship experience. My first project is titled "General Exposure Representation EVADOSE", also known as "GEnEVADOSE". This project involved the design and development of a C++/ ROOT framework focused on radiation exposure for extravehicular activity (EVA) planning for the ISS. The utility helps mission managers plan EVAs by displaying information on the cumulative radiation doses that crew will receive during an EVA as a function of the egress time and duration of the activity. SRAG uses a utility called EVADOSE, employing a model of the space radiation environment in low Earth orbit to predict these doses, as while outside the ISS the astronauts will have less shielding from charged particles such as electrons and protons. However, EVADOSE output is cumbersome to work with, and prior to GEnEVADOSE, querying data and producing graphs of ISS trajectories and cumulative doses versus egress time required manual work in Microsoft Excel. GEnEVADOSE automates all this work, reading in EVADOSE output file(s) along with a plaintext file input by the user providing input parameters. GEnEVADOSE will output a text file containing all the necessary dosimetry for each proposed EVA egress time, for each specified EVADOSE file. It also plots cumulative dose versus egress time and the ISS trajectory, and displays all of this information in an auto-generated presentation made in LaTeX. New features have also been added, such as best-case scenarios (egress times corresponding to the least dose), interpolated curves for trajectories, and the ability to query any time in the EVADES output. As mentioned above, GEnEVADOSE makes extensive use of ROOT version 6, the data analysis framework developed at the European Organization for Nuclear Research (CERN), and the code is written to the C++11 standard (as are the other projects). My second project is the Automated Mission Reference Exposure Utility (AMREU).Unlike GEnEVADOSE, AMREU is a combination of three frameworks written in both Python and C++, also making use of ROOT (and PyROOT). Run as a combination of daily and weekly cron jobs, these macros query the SRAG database system to determine the active ISS missions, and query minute-by-minute radiation dose information from ISS-TEPC (Tissue Equivalent Proportional Counter), one of the radiation detectors onboard the ISS. Using this information, AMREU creates a corrected data set of daily radiation doses, addressing situations where TEPC may be offline or locked up by correcting doses for days with less than 95% live time (the total amount time the instrument acquires data) by averaging the past 7 days. As not all errors may be automatically detectable, AMREU also allows for manual corrections, checking an updated plaintext file each time it runs. With the corrected data, AMREU generates cumulative dose plots for each mission, and uses a Python script to generate a flight note file (.docx format) containing these plots, as well as information sections to be filled in and modified by the space weather environment officers with information specific to the week. AMREU is set up to run without requiring any user input, and it automatically archives old flight notes and information files for missions that are no longer active. My other projects involve cleaning up a large data set from the Charged Particle Directional Spectrometer (CPDS), joining together many different data sets in order to clean up information in SRAG SQL databases, and developing other automated utilities for displaying information on active solar regions, that may be used by the space weather environment officers to monitor solar activity. I consulted my mentor Dr. Ryan Rios and Dr. Kerry Lee for project requirements and added features, and ROOT developer Edmond Offermann for advice on using the ROOT library. I also received advice and feedback from Dr. Janet Barzilla of SRAG, who tested my code. Besides these inputs, I worked independently, writing all of the code by myself. The code for all these projects is documented throughout, and I have attempted to write it in a modular format. Assuming that ROOT is updated accordingly, these codes are also Y2038-compliant (and Y10K-compliant). This allows the code to be easily referenced, modified and possibly repurposed for non-ISS missions in the future, should the necessary inputs exist. These projects have taught me a lot about coding and software design - I have become a much more skilled C++ programmer and ROOT user, and I also learned to code in Python and PyROOT (and its advantages and disadvantages compared to C++/ ROOT). Furthermore, I have learned about space radiation and radiation modeling, topics that greatly interest me as I pursue a degree in physics. Working alongside experimental physicists like Dr. Rios, I have developed a greater understanding and appreciation for experimental science, something I have always leaned towards but to which I lacked significant exposure. My work in SRAG has also given me the invaluable opportunity to witness the work environment for physicists at NASA, and what a career in academia may look like at a government laboratory such as NASA Johnson Space Center. As I continue my studies and look forward to graduate school and a future career, this experience at NASA has given me a meaningful and enjoyable opportunity to put my skills to use and see what my future career path might hold.

Offermann, Jan Tuzlic↗
DOE OSTI2013

Cementitious Barriers Partnership FY2013 End-Year Report

In FY2013, the Cementitious Barriers Partnership (CBP) demonstrated continued tangible progress toward fulfilling the objective of developing a set of software tools to improve understanding and prediction of the long-term structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. In November 2012, the CBP released “Version 1.0” of the CBP Software Toolbox, a suite of software for simulating reactive transport in cementitious materials and important degradation phenomena. In addition, the CBP completed development of new software for the “Version 2.0” Toolbox to be released in early FY2014 and demonstrated use of the Version 1.0 Toolbox on DOE applications. The current primary software components in both Versions 1.0 and 2.0 are LeachXS/ORCHESTRA, STADIUM, and a GoldSim interface for probabilistic analysis of selected degradation scenarios. The CBP Software Toolbox Version 1.0 supports analysis of external sulfate attack (including damage mechanics), carbonation, and primary constituent leaching. Version 2.0 includes the additional analysis of chloride attack and dual regime flow and contaminant migration in fractured and non-fractured cementitious material. The LeachXS component embodies an extensive material property measurements database along with chemical speciation and reactive mass transport simulation cases with emphasis on leaching of major, trace and radionuclide constituents from cementitious materials used in DOE facilities, such as Saltstone (Savannah River) and Cast Stone (Hanford), tank closure grouts, and barrier concretes. STADIUM focuses on the physical and structural service life of materials and components based on chemical speciation and reactive mass transport of major cement constituents and aggressive species (e.g., chloride, sulfate, etc.). THAMES is a planned future CBP Toolbox component focused on simulation of the microstructure of cementitious materials and calculation of resultant hydraulic and constituent mass transfer parameters needed in modeling. Two CBP software demonstrations were conducted in FY2013, one to support the Saltstone Disposal Facility (SDF) at SRS and the other on a representative Hanford high-level waste tank. The CBP Toolbox demonstration on the SDF provided analysis on the most probable degradation mechanisms to the cementitious vault enclosure caused by sulfate and carbonation ingress. This analysis was documented and resulted in the issuance of a SDF Performance Assessment Special Analysis by Liquid Waste Operations this fiscal year. The two new software tools supporting chloride attack and dual-regime flow will provide additional degradation tools to better evaluate performance of DOE and commercial cementitious barriers. The CBP SRNL experimental program produced two patent applications and field data that will be used in the development and calibration of CBP software tools being developed in FY2014. The CBP software and simulation tools varies from other efforts in that all the tools are based upon specific and relevant experimental research of cementitious materials utilized in DOE applications. The CBP FY2013 program involved continuing research to improve and enhance the simulation tools as well as developing new tools that model other key degradation phenomena not addressed in Version 1.0. Also efforts to continue to verify the various simulation tools through laboratory experiments and analysis of field specimens are ongoing and will continue into FY2014 to quantify and reduce the uncertainty associated with performance assessments. This end-year report summarizes FY2013 software development efforts and the various experimental programs that are providing data for calibration and validation of the CBP developed software.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Continuation Report: Creep-fatigue Behavior and Damage Accumulation of a Candidate Structural Material for Concentrating Solar Thermal Receiver

At the start of this phase, six alloys were determined to be candidate materials for the concentrating solar power (CSP) thermal receiver: Alloys 617, 625, 740H, 230, 282 and Alloy X. From these, Alloys 740H and 282 were determined to be the most suitable, with both alloys exhibiting similar high temperature strength properties. Alloy 740H was selected due to its ease to work with (simpler heat treatments and welding procedures) and a larger database of existing data. Fatigue testing was started in this phase, with four fatigue tests having been completed, with additional fatigue testing planned, as well as tensile, creep and creep-fatigue tests starting in the next phase. Two fatigue tests performed at 850 °C and were completed in significantly fewer cycles than the two tests performed at 750 °C. Metallography was performed on the fatigued specimens to examine crack path and surrounding microstructure. These preliminary results suggest a significant drop in strength at elevated temperatures above 750 °C, however, more test results will be needed prior to setting design limits. Several potential model high temperature design methods were evaluated that could form the basis of our final recommended creep-fatigue design method for Alloy 740H. To do this we expanded on the receiver finite element model to develop a model representative of a potential Gen 3 design using KCl-MgCl2 salt coolant and operating with a salt inlet temperature of 550°C and salt outlet temperature of 720°C. Using the temperature fields from the model thermohydraulic analysis we determined the design life of the reference receiver assuming it was constructed from 740H seamless tubing and assuming high temperature design properties for 740H from literature data and, where required, naïve extrapolation. As experimental data is generated, these tentative design parameters will be updated to match the actual performance of 740H in elevated temperature service. The results of this design study are a rank ordering of potential design methods for two criteria: ease of use and design margin. The end goal of this project is to develop a creep-fatigue design method with adequate, but not over conservative, design margin that is straightforward to execute. Our receiver model is based on the preliminary design provided to DOE by Solar Reserve. Our analysis indicates a peak metal temperature of around 840° C for this design (comparable to Solar Reserve’s analysis, which shows a peak metal temperature of around 830° C). The Solar Reserve tube thickness is too thin to sustain creep-fatigue loading at this temperature. This means that the current trial design is not well-suited for evaluating different design methodologies, as we predict it will have a very short design life. We suggest that we modify our reference design with input from DOE in order to lower the maximum metal temperature to less than 800° C. We can then repeat these analyses and give a more meaningful comparison of different design methods before making a final selection.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Lean Blowout (LBO) Simulations in a Rich-Burn Quick-Quench Lean-Burn (RQL) Gas Turbine Combustor

The transient processes involving lean blowout (LBO) in a RQL combustor such as the single cup combustor in the National Jet Fuels Combustion Program (NJFCP) referee rig are simulated with the reduced mechanisms based on Hybrid Chemistry for two different fuels, Cat-A2 and Cat-C1. Cat-A2 fuel is Jet-A with average or nominal properties based on a survey of the Petroleum Quality Information System database. The Cat-C1, an alternative jet fuel, is a GEVO alcohol-to-jet (ATJ) fuel composed almost entirely of two highly-branched C12 and C16 iso-paraffins. Experiments conducted in the NJFCP referee rig established a stable flame at an equivalence ratio of 0.096 (the near LBO condition) as the starting condition for LBO tests performed with all Category A and C fuels. Simulations of the approach to LBO verify that a stable flame is established at the near-LBO condition for each fuel before reducing fuel flow rate (and thus equivalence ratio) in a step-wise manner. At each new equivalence ratio, the global heat release rate and total fuel evaporation time histories are monitored to verify a new stable flame condition has been established before performing the next reduction in equivalence ratio until the flame is approaching the blowout. Main conclusions are threefold: (1) For Cat-C1 fuel the equivalence ratio for LBO is around 0.087. (2) For Cat-A2 fuel the equivalence ratio for LBO is either 0.082 or 0.078 depended on the time span of equivalence ratio of 0.085. (3) The averaged difference from LES on LBO for Cat-C1 relative to Cat-A2 is 8.75% versus 7.8% from the experimental data.

LES, Lean blow out↗
DOE OSTI2013

Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches

Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure–activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα binding affinity (MTL R{sup 2} = 0.71, STL R{sup 2} = 0.73). For ERβ binding affinity, MTL models were significantly more predictive (R{sup 2} = 0.53, p < 0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. - Highlights: • This is the largest curated dataset inclusive of ERα and β (the latter is unique). • New methodology that for the first time affords acceptable ERβ models. • A combination of QSAR and docking enables prediction of affinity and function. • The results have potential applications to green chemistry. • Models are publicly available for virtual screening via a web portal.

60 APPLIED LIFE SCIENCES↗