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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.

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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Limited options for low-global-warming-potential refrigerants

Hydrofluorocarbons, currently used as refrigerants in air-conditioning systems, are potent greenhouse gases, and their contribution to climate change is projected to increase. Future use of the hydrofluorocarbons will be phased down and, thus replacement fluids must be found. Here we show that only a few pure fluids possess the combination of chemical, environmental, thermodynamic, and safety properties necessary for a refrigerant and that these fluids are at least slightly flammable.We search for replacements by applying screening criteria to a comprehensive chemical database. For the fluids passing the thermodynamic and environmental screens (critical temperature and global warming potential), we simulate performance in small air-conditioning systems, including optimization of the heat exchangers. We show that the efficiency-versus-capacity trade-off that exists in an ideal analysis disappears when a more realistic system is considered. Furthermore, the maximum efficiency occurs at a relatively high volumetric refrigeration capacity, but there are few fluids in this range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Automated and Distributed Monte Carlo Generation for GlueX

MCwrapper is a set of systems that manages the entire Monte Carlo production workflow for GlueX and provides standards for how that Monte Carlo is produced. MCwrapper was designed to be able to utilize a variety of batch systems in a way that is relatively transparent to the user, thus enabling users to quickly and easily produce valid simulated data at home institutions worldwide. Additionally, MCwrapper supports an autonomous system that takes user’s project submissions via a custom web application. The system then atomizes the project into individual jobs, matches these jobs to resources, and monitors the jobs status. The entire system is managed by a database which tracks almost all facets of the systems from user submissions to the individual jobs themselves. Users can interact with their submitted projects online via a dashboard or, in the case of testing failure, can modify their project requests from a link contained in an automated email. Beginning in 2018 the GlueX Collaboration began to utilize the Open Science Grid (OSG) to handle a bulk of simulation tasks; these tasks are currently being performed on the OSG automatically via MCwrapper. This talk will outline the entire system of MCwrapper, its use cases, and the unique challenges facing the system.

Britton, Thomas↗
DOE OSTI2014

WE-G-9A-01: Radiation Oncology Outcomes Informatics

The construction of databases and support software to enable routine and systematic aggregation, analysis and reporting of patient outcomes data is emerging as an important area. “How have results for our patients been affected by the improvements we have made in our practice and in the technologies we use?” To answer this type of fundamental question about the overall pattern of efficacy observed, it is necessary to systematically gather and analyze data on all patients treated within a clinic. Clinical trials answer, in great depth and detail, questions about outcomes for the subsets of patients enrolled in a given trial. However, routine aggregation and analysis of key treatment parameter data and outcomes information for all patients is necessary to recognize emergent patterns that would be of interest from a public health or practice perspective and could better inform design of clinical trials or the evolution of best practice principals. To address these questions, Radiation Oncology outcomes databases need to be constructed to enable combination essential data from a broad group of data types including: diagnosis and staging, dose volume histogram metrics, patient reported outcomes, toxicity metrics, performance status, treatment plan parameters, demographics, DICOM data and demographics. Developing viable solutions to automate aggregation and analysis of this data requires multidisciplinary efforts to define nomenclatures, modify clinical processes and develop software and database tools requires detailed understanding of both clinical and technical issues. This session will cover the developing area of Radiation Oncology Outcomes Informatics. Learning Objectives: Audience will be able to speak to the technical requirements (software, database, web services) which must be considered in designing an outcomes database. Audience will be able to understand the content and the role of patient reported outcomes as compared to traditional toxicity measures. Audience will be understand approaches, clinical process changes, consensus building efforts and standardizations which must be addressed to succeed in a multi-disciplinary effort to aggregate data for all patients. Audience will be able to discuss technical and process issues related to pooling data among institutions in the context of collaborative studies among the presenting institutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

NGNP Data Management and Analysis System Analysis and Web Delivery Capabilities

Projects for the Very High Temperature Reactor (VHTR) Technology Development Office provide data in support of Nuclear Regulatory Commission licensing of the very high temperature reactor. Fuel and materials to be used in the reactor are tested and characterized to quantify performance in high-temperature and high-fluence environments. The NGNP Data Management and Analysis System (NDMAS) at the Idaho National Laboratory has been established to ensure that VHTR data are (1) qualified for use, (2) stored in a readily accessible electronic form, and (3) analyzed to extract useful results. This document focuses on the third NDMAS objective. It describes capabilities for displaying the data in meaningful ways and for data analysis to identify useful relationships among the measured quantities. The capabilities are described from the perspective of NDMAS users, starting with those who just view experimental data and analytical results on the INL NDMAS web portal. Web display and delivery capabilities are described in detail. Also the current web pages that show Advanced Gas Reactor, Advanced Graphite Capsule, and High Temperature Materials test results are itemized. Capabilities available to NDMAS developers are more extensive, and are described using a second series of examples. Much of the data analysis efforts focus on understanding how thermocouple measurements relate to simulated temperatures and other experimental parameters. Statistical control charts and correlation monitoring provide an ongoing assessment of instrument accuracy. Data analysis capabilities are virtually unlimited for those who use the NDMAS web data download capabilities and the analysis software of their choice. Overall, the NDMAS provides convenient data analysis and web delivery capabilities for studying a very large and rapidly increasing database of well-documented, pedigreed data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Fuel Aging in Storage and Transportation (FAST): Accelerated Characterization and Performance Assessment of the Used Nuclear Fuel Storage System

This Integrated Research Project (IRP) was established to characterize key limiting phenomena related to the performance of used nuclear fuel (UNF) storage systems. This was an applied engineering project with a specific application in view (i.e., UNF dry storage). The completed tasks made use of a mixture of basic science and engineering methods. The overall objective was to create, or enable the creation of, predictive tools in the form of observation methods, phenomenological models, and databases that will enable the design, installation, and licensing of dry UNF storage systems that will be capable of containing UNF for extended period of time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

HyMARC Seedling: Optimized Hydrogen Adsorbents via Machine Learning and Crystal Engineering

This final report is presented in two parts: In Part 1, the H 2 capacities of a diverse set of 918,734 metal-organic frameworks (MOFs) sourced from 19 databases is predicted via machine learning (ML). Using only 7 structural features as input, ML identifies 8,282 MOFs with the potential to exceed the capacities of state-of-the-art materials. The identified MOFs are predominantly hypothetical compounds having low densities (<0.31 g/cm3) in combination with high surface areas (>5,300 m2/g), void fractions ($0.90), and pore volumes (>3.3 cm3/g). The relative importance of the input features are characterized, and dependencies on the ML algorithm and training set size are quantified. The most important features for predicting H 2 uptake are pore volume (for gravimetric capacity) and void fraction (for volumetric capacity). The ML models are available on the web, allowing for rapid and accurate predictions of the hydrogen capacities of MOFs from limited structural data; the simplest models require only a single crystallographic feature. In part 2, ways to improve the poor powder packing density of MOFs is discussed. More specifically, a strategy that improves packing efficiency and volumetric hydrogen gas storage density dramatically through engineered morphologies and controlled-crystal size distributions is presented that holds promise for maximizing storage capacity for a given MOF. The packing density improvement, demonstrated for the benchmark sorbent MOF-5, leads to a significant enhancement of volumetric hydrogen storage performance relative to commercial MOF-5. System model projections demonstrate that engineering of crystal morphology/size or use of a bimodal distribution of cubic crystal sizes in tandem with system optimization can surpass the 25 g/L volumetric capacity of a typical 700 bar compressed storage system and exceed the DOE targets 2020 volumetric capacity (30 g/L). Finally, a critical link between improved powder packing density and reduced damage upon compaction is revealed leading to sorbents with both high surface area and high density.

08 HYDROGEN↗
DOE OSTI2016

The SINFONI Black Hole Survey: The black hole fundamental plane revisited and the paths of (co)evolution of supermassive black holes and bulges

We investigate the correlations between the black hole (BH) mass M{sub BH}, the velocity dispersion σ, the bulge mass M{sub Bu}, the bulge average spherical density ρ{sub h}, and its spherical half-mass radius r{sub h}, constructing a database of 97 galaxies (31 core ellipticals, 17 power-law ellipticals, 30 classical bulges, and 19 pseudobulges) by joining 72 galaxies from the literature to 25 galaxies observed during our recent SINFONI BH survey. For the first time we discuss the full error covariance matrix. We analyze the well-known M{sub BH}–σ and M{sub BH}–M{sub Bu} relations and establish the existence of statistically significant correlations between M{sub Bu} and r{sub h} and anticorrelations between M{sub Bu} and ρ{sub h}. We establish five significant bivariate correlations (M{sub BH}–σ–ρ{sub h}, M{sub BH}–σ–r{sub h}, M{sub BH}–M{sub Bu}–σ, M{sub BH}–M{sub Bu}–ρ{sub h}, M{sub BH}–M{sub Bu}–r{sub h}) that predict M{sub BH} of 77 core and power-law ellipticals and classical bulges with measured and intrinsic scatter as small as ≈0.36 dex and ≈0.33 dex, respectively, or 0.26 dex when the subsample of 45 galaxies defined by Kormendy and Ho is considered. In contrast, pseudobulges have systematically lower M{sub BH} but approach the predictions of all of the above relations at spherical densities ρ{sub h}⩾10{sup 10} M{sub ⊙} kpc{sup −3} or scale lengths r{sub h}⩽1 kpc. These findings fit in a scenario of coevolution of BH and classical-bulge masses, where core ellipticals are the product of dry mergers of power-law bulges and power-law ellipticals and bulges the result of (early) gas-rich mergers and of disk galaxies. In contrast, the (secular) growth of BHs is decoupled from the growth of their pseudobulge hosts, except when (gas) densities are high enough to trigger the feedback mechanism responsible for the existence of the correlations between M{sub BH} and galaxy structural parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

International Space Station Utilization: Tracking Investigations from Objectives to Results

Since the first module was assembled on the International Space Station (ISS), on-orbit investigations have been underway across all scientific disciplines. The facilities dedicated to research on ISS have supported over 1100 investigations from over 900 scientists representing over 60 countries. Relatively few of these investigations are tracked through the traditional NASA grants monitoring process and with ISS National Laboratory use growing, the ISS Program Scientist s Office has been tasked with tracking all ISS investigations from objectives to results. Detailed information regarding each investigation is now collected once, at the first point it is proposed for flight, and is kept in an online database that serves as a single source of information on the core objectives of each investigation. Different fields are used to provide the appropriate level of detail for research planning, astronaut training, and public communications. http://www.nasa.gov/iss-science/. With each successive year, publications of ISS scientific results, which are used to measure success of the research program, have shown steady increases in all scientific research areas on the ISS. Accurately identifying, collecting, and assessing the research results publications is a challenge and a priority for the ISS research program, and we will discuss the approaches that the ISS Program Science Office employs to meet this challenge. We will also address the online resources available to support outreach and communication of ISS research to the public. Keywords: International Space Station, Database, Tracking, Methods

Ruttley, T. M.↗
NASA NTRSDate not supplied

SWIPE: Spectral Water Inversion Processor and Emulator

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will be discussing the progress made developing SWIPE: Spectral Water Inversion Processor and Emulator. SWIPE is a platform for advanced modeling of coastal and inland aquatic habitats. The goal is create a comprehensive and cohesive system to leverage recent advancements in computation and machine learning to develop a synthetic training ground for sensitivity studies and algorithm development. The four principal facets of SWIPE include: 1. Advanced two-layer coated sphere bio-optical modeling and GPU radiative transfer modeling, 2. Big Data involving massive synthetic spectral libraries of optical properties of various global aquatic particles, surface reflectance, and top-of-atmosphere reflectance, all at hyperspectral resolution leveraging high-end computing systems at NASA Ames Research Center, 3. Deep Learning for algorithm development for water quality inversion of concentrations of common biogeophysical variables as well as optics, full uncertainty characterization by water type, and forward emulation, and lastly, 4. Image Processing for application of developed retrieval algorithms for both hyperspectral and multispectral sensors with experimental corrections for global adjacency, noise, sunglint, and benthic reflectance. This presentation will demonstrate the Equivalent Algal Populations (EAP) two-layer coated sphere scattering model which has been used develop spectral libraries of hyperspectral inherent optical properties of roughly 80 species of phytoplankton, covering 15 different classes and nine taxonomic functional types. The EAP model was also used to derive spectral properties of 10 different non-algal particle functional types. Examples of how the SMART-G (Speed-up Monte-carlo Advanced Radiative Transfer using GPU) radiative transfer code is used to model optically complex aquatic signals will be presented and discussed in the context of creating a massive synthetic database which can leverage the full power of next generation machine learning techniques and high end computing for water quality inversion. We will discuss our active investigation in things like appropriate model architectures, dimensionality reduction techniques such as PCA and autoencoders, uncertainty quantification and abstaining, and which variables actually benefit most from hyperspectral information versus multispectral resolution. We are also curious about questions relating to cost/benefit analysis in terms of computation resources, neural network complexity, and data volumes. Answers to these questions will hopefully elaborate on cost efficiency for potential future sensor design considerations.

SWIPE↗
DOE OSTI2012

Algal functional annotation tool

The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps and batch gene identifier conversion.

09 BIOMASS FUELS↗
DOE OSTI2020

Genome‐wide association study of multiple yield traits in a diversity panel of polyploid sugarcane ( Saccharum spp.)

Abstract Sugarcane ( Saccharum spp.) is an important economic crop, contributing up to 80% of sugar and approximately 60% of biofuel globally. To meet the increased demand for sugar and biofuel supplies, it is critical to breed sugarcane cultivars with robust performance in yield traits. Therefore, dissection of causal DNA sequence variants is of great importance, as it provides genetic resources and fundamental information for crop improvement. In this study, we analyzed nine yield traits in a sugarcane diversity panel consisting of 308 accessions primarily selected from the World Collection of Sugarcane and Related Grasses. By genotyping the diversity panel via target enrichment sequencing, we identified a large number of sequence variants. Genome‐wide association studies between the markers and traits were conducted, taking dosages and gene actions into consideration. In total, 217 nonredundant markers and 225 candidate genes were identified to be significantly associated with the yield traits, which can serve as a comprehensive genetic resource database for future gene identification, characterization, and selection for sugarcane improvement. We further investigated runs of homozygosity (ROH) in the sugarcane diversity panel. We characterized 282 ROHs and found that the occurrence of ROHs in the genome were nonrandom and probably under selection. The ROHs were associated with total weight and dry weight, and high ROHs resulted in a decrease in the two traits. This study suggests that genomic inbreeding has led to negative impacts on sugarcane yield.

Yang, Xiping↗
DOE OSTI2012

Residential radon and lung cancer incidence in a Danish cohort

High-level occupational radon exposure is an established risk factor for lung cancer. We assessed the long-term association between residential radon and lung cancer risk using a prospective Danish cohort using 57,053 persons recruited during 1993-1997. We followed each cohort member for cancer occurrence until 27 June 2006, identifying 589 lung cancer cases. We traced residential addresses from 1 January 1971 until 27 June 2006 and calculated radon at each of these addresses using information from central databases regarding geology and house construction. Cox proportional hazards models were used to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI) for lung cancer risk associated with residential radon exposure with and without adjustment for sex, smoking variables, education, socio-economic status, occupation, body mass index, air pollution and consumption of fruit and alcohol. Potential effect modification by sex, traffic-related air pollution and environmental tobacco smoke was assessed. Median estimated radon was 35.8 Bq/m{sup 3}. The adjusted IRR for lung cancer was 1.04 (95% CI: 0.69-1.56) in association with a 100 Bq/m{sup 3} higher radon concentration and 1.67 (95% CI: 0.69-4.04) among non-smokers. We found no evidence of effect modification. We find a positive association between radon and lung cancer risk consistent with previous studies but the role of chance cannot be excluded as these associations were not statistically significant. Our results provide valuable information at the low-level radon dose range.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning

Abstract The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a ‘living data resource.’ Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Thermochemical Modeling of Radionuclide Vapor-Liquid Equilibria in Sodium Pools for SFR Mechanistic Source Term Analysis

Mechanistic source term (MST) analysis of sodium fast reactors (SFR) requires understanding of various radionuclide (RN) transport phenomena influencing potential releases from the fuel to the environment. One such phenomenon includes the retention or release of RNs from the sodium coolant pool, representing the step after possible fuel failures and influencing transport to the cover gas region. Thermodynamic vapor-liquid equilibria (VLE) calculations were performed on systems representing SFR sodium pools containing oxygen impurities and radionuclide (RN) inventories. First, an assessment and recreation of a previously developed thermodynamic database was completed, including updates to thermodynamic parameters. The RN inventories used in VLE calculations represented hypothetical source terms that might be released to the pool during previously analyzed fuel failure scenarios. The calculations were performed for all possible combinations of sodium pool size (i.e., total oxygen) and number of failed fuel pins (i.e., total RNs). In this way, multiple ratios of the RN relative to the oxygen impurity (RN:O) were compared for their impact on RN volatility, which is discussed in terms of the vapor fraction (VF), defined as the fraction of the RN that is calculated to exist in the vapor phase at equilibrium above condensed phases of that element. Similar trends in VLE behavior are seen in the equilibrium calculation results for elements of similar chemistry, and for some element types, it was found that the RN:O ratio can be important due to oxide formation, which typically exist in the condensed phase.

Shahbazi, Shayan↗
DOE OSTI2018

Identification and Removal of Contaminant Sequences From Ribosomal Gene Databases: Lessons From the Census of Deep Life

Earth’s subsurface environment is one of the largest, yet least studied, biomes on Earth, and many questions remain regarding what microorganisms are indigenous to the subsurface. Through the activity of the Census of Deep Life (CoDL) and the Deep Carbon Observatory, an open access 16S ribosomal RNA gene sequence database from diverse subsurface environments has been compiled. However, due to low quantities of biomass in the deep subsurface, the potential for incorporation of contaminants from reagents used during sample collection, processing, and/or sequencing is high. Thus, to understand the ecology of subsurface microorganisms (i.e., the distribution, richness, or survival), it is necessary to minimize, identify, and remove contaminant sequences that will skew the relative abundances of all taxa in the sample. In this meta-analysis, we identify putative contaminants associated with the CoDL dataset, recommend best practices for removing contaminants from samples, and propose a series of best practices for subsurface microbiology sampling. The most abundant putative contaminant genera observed, independent of evenness across samples, were Propionibacterium, Aquabacterium, Ralstonia, and Acinetobacter. While the top five most frequently observed genera were Pseudomonas, Propionibacterium, Acinetobacter, Ralstonia, and Sphingomonas. The majority of the most frequently observed genera (high evenness) were associated with reagent or potential human contamination. Additionally, in DNA extraction blanks, we observed potential archaeal contaminants, including methanogens, which have not been discussed in previous contamination studies. Such contaminants would directly affect the interpretation of subsurface molecular studies, as methanogenesis is an important subsurface biogeochemical process. Utilizing previously identified contaminant genera, we found that ~27% of the total dataset were identified as contaminant sequences that likely originate from DNA extraction and DNA cleanup methods. Thus, controls must be taken at every step of the collection and processing procedure when working with low biomass environments such as, but not limited to, portions of Earth’s deep subsurface. Taken together, we stress that the CoDL dataset is an incredible resource for the broader research community interested in subsurface life, and steps to remove contamination derived sequences must be taken prior to using this dataset.

16S rRNA↗
NASA NTRS1992

Archiving data from ground-based telescopes

The scientific throughput of a particular observing facility has been demonstrated to be multiplied with the operation of a data archive and its corresponding retrieval system. A requisite to achieve such an exploitation is a well structured observations catalog, i.e. a catalog that includes all information necessary to reduce and analyze the data even many years after its acquisition. At the same time, an information system is required that allow users to browse through the catalog at different levels of detail, adapting the amount of information presented to the actual needs of the user. Archiving data acquired with ground-based telescopes is particularly difficult because of the relative short life-time of instruments and detectors in comparison to the expected life-time of the archive. This feature differentiates ground-based originated archives radically from its spaceborne counterparts. The organization of the observations catalog becomes highly dependent on the capability of the archive to deal with new instrumental configurations. We introduce in this paper, the concept of a catalog database as opposed to the static catalog design currently in use in many archiving facilities, as a method to deal with this problem. We also present a brief review of activities currently in progress in this area.

Albrecht, M. A.↗
NASA NTRS2002

Slat Cove Noise Modeling: A Posteriori Analysis of Unsteady RANS Simulations

A companion paper by Khorrami et al demonstrates the feasibility of simulating the (nominally) self-sustained, large-scale unsteadiness within the leading-edge slat-cove region of multi-element airfoils using unsteady Reynolds-Averaged Navier-Stokes (URANS) equations, provided that the turbulence production term in the underlying two-equation turbulence model is switched off within the cove region. In conjunction with a FfowesWilliams-Hawkings solver, the URANS computations were shown to capture the dominant portion of the acoustic spectrum attributed to slat noise, as well as reproducing the increased intensity of slat cove motions (and, correspondingly, far-field noise as well) at the lower angles of attack. This paper examines that simulation database, augmented by additional simulations, with the objective of transitioning this apparent success to aeroacoustic predictions in an engineering context. As a first step towards this goal, the simulated flow and acoustic fields are compared with experiment and simplified analytical model. Rather intense near-field fluctuations in the simulated flow are found to be associated with unsteady separation along the slat bottom surface, relatively close to the slat cusp. Accuracy of the laminar-cove simulations in this near-wall region is raised to be an open issue. The adjoint Green's function approach is also explored in an attempt to identify the most efficient noise source locations.

Choudhari, Meelan↗
NASA NTRS2010

Wind Tunnel Investigation of Ground Wind Loads for Ares Launch Vehicle

A three year program was conducted at the NASA Langley Research Center (LaRC) Aeroelasticity Branch (AB) and Transonic Dynamics Tunnel (TDT) with the primary objective to acquire scaled steady and dynamic ground-wind loads (GWL) wind-tunnel data for rollout, on-pad stay, and on-pad launch configurations for the Ares I-X Flight Test Vehicle (FTV). The experimental effort was conducted to obtain an understanding of the coupling of aerodynamic and structural characteristics that can result in large sustained wind-induced oscillations (WIO) on such a tall and slender launch vehicle and to generate a unique database for development and evaluation of analytical methods for predicting steady and dynamic GWL, especially those caused by vortex shedding, and resulting in significant WIO. This paper summarizes the wind-tunnel test program that employed two dynamically-aeroelastically scaled GWL models based on the Ares I-X Flight Test Vehicle. The first model tested, the GWL Checkout Model (CM), was a relatively simple model with a secondary objective of restoration and development of processes and methods for design, fabrication, testing, and data analysis of a representative ground wind loads model. In addition, parametric variations in surface roughness, Reynolds number, and protuberances (on/off) were investigated to determine effects on GWL characteristics. The second windtunnel model, the Ares I-X GWL Model, was significantly more complex and representative of the Ares I-X FTV and included the addition of simplified rigid geometrically-scaled models of the Kennedy Space Center (KSC) Mobile Launch Platform (MLP) and Launch Complex 39B primary structures. Steady and dynamic base bending moment as well as model response and steady and unsteady pressure data was acquired during the testing of both models. During wind-tunnel testing of each model, flow conditions (speed and azimuth) where significant WIO occurred, were identified and thoroughly investigated. Scaled data from the Ares I-X GWL model test was used in the determination of worst-case loads for the analysis of Ares I-X FTV design wind conditions. Finally, this paper includes a brief discussion of the limited full-scale GWL data acquired during the rollout and on-pad stay of the Ares I-X FTV that was launched from KSC on October 28, 2009.

Keller, Donald F.↗