Results for “databases” — Page 69

NASA NTRSDate not supplied

SpaceX Dragon 1 Post Flight MMOD Inspection Campaign

Introduction The SpaceX Dragon 1 spacecraft performed 20 resupply missions to the International Space Station (ISS) between 2012 and 2020. After each mission, a team from the NASA John-son Space Center Hypervelocity Impact Technology Group inspected each Dragon 1 capsule for hypervelocity impact damage features. Data from these inspections are collected into a database that includes impact feature dimensions as well as the location on the vehicle. Additional details on the type and size of particle that produced the damage site are provided when sampling data and definitive spectroscopic analysis results are available. Observation data can be compared with impact estimates from risk assessment codes as a check on the micrometeoroid and orbital debris (MMOD) environment predictions. Scope A general description of the areas of the vehicle that were inspected are provided as well as mission details such as exposure duration and launch dates. The paper documents the general inspection procedure for collection of data and the post inspection data analysis process. It also provides details of the observation data collected as well as the results of analysis of intact samples collected for spectroscopic analysis to discern the source of the impacting particle. A comparison between observed impacts and the expected number of damage features calculated by Bumper 3 with the latest MMOD environments are also presented. Findings Statistics on the >300 impact features documented in the database will provide insight into the depth to diameter ratios and other relationships. The quality of the comparison between the observations and code predictions are dependent on several factors. The paper provides de-tails of each of these variables. (1) Damage equations (2) Impact condition assumptions a. Projectile density b. Impact speed c. Impact angle (3) Analysis results a. pre-flight vs. on-orbit damage b. MMOD vs. non-MMOD Conclusions and Recommendations The ISS visiting vehicle impact database is an ongoing project. SpaceX provides crew rotations as well as resupply and cargo return with the Dragon 2 spacecraft. Sierra Space is manifested for resupply and cargo return services starting in 2023. Boeing is expected to provide crew rotations as well. All of these spacecraft will provide additional opportunities for post flight MMOD inspections of space exposed hardware. Acknowledgements Over the course of the inspection campaign various personnel at the SpaceX Texas Test Site in McGregor and at the SpaceX headquarters in Hawthorne CA provided valuable support to this activity.

James L Hyde↗

NASA NTRS2022

Flow Visualization, Heat Transfer, and Critical Heat Flux of Flow Boiling in Earth Gravity with Saturated Liquid-Vapor Mixture Inlet Conditions – In Preparation for Experiments Onboard the International Space Station

This study investigates flow boiling of n-Perfluorohexane with saturated two-phase mixture inlet in a rectangular channel of dimensions 114.6-mm heated length, 2.5-mm width, and 5 mm-height. The experiments were performed as part of the Mission Sequence Testing of the Flow Boiling and Condensation Experiment’s (FBCE) Flow Boiling Module (FBM) in the vertical upflow configuration in Earth gravity using the same experimental system that was launched to the International Space Station (ISS) in August 2021. The operating parameters varied are heating configuration (single- and double-sided), mass velocity (380 – 2400 kg/m2s), inlet quality (0.011 – 0.519), and inlet pressure (120 – 179 kPa). High-speed video photographs are presented to explain the two-phase flow patterns within the channel’s heated length. Flow patterns are constituted by low-density and high-density fronts moving along the channel, with the high-density fronts gradually reducing in length due to evaporation. Heat transfer results in terms of flow boiling curves, streamwise wall temperature profiles, streamwise heat transfer coefficient profiles, and average heat transfer coefficients are presented and trends discussed. CHF data from the present experiments are combined with prior databases to compile a consolidated FBCE-CHF database for saturated inlet to expand the ranges of operating conditions and include other flow orientations in Earth gravity. Experimental CHF trends are also discussed. The interfacial lift-off model shows a good CHF predictive accuracy evidenced by a mean absolute error of 11.97% for this consolidated database after constraining it to mass velocities greater than or equal to 500 kg/m2s. Finally, this study confirmed reliability of the upcoming ISS experiments for saturated inlet conditions and the collected Earth-gravity data will be compared to ISS microgravity data.

Flow boiling↗

NASA NTRSDate not supplied

Introduction of the NASA Microgravity Research Library

As opportunities for conducting experiments in space are rare, more studies have been published using ground-based analogs that simulate microgravity conditions. For example, when conducting a literature search in PubMed for peer-reviewed articles and studies that used simulated microgravity conditions, results will yield over 5,000 publications dating back to 1961. The issue with this search technique and medium is that these articles are vast in quantity and spread out across multiple web-based databases, repositories, and libraries; some of which, are wholly inaccessible. For example, in PubMed for a single year, we found 1,000+ microgravity research articles among more than 12,000 general, space research articles; these, were within an overarching 350,000+ total, general medical research articles for just 2020. The KSC Microgravity Simulation Support Facility (MSSF), with support from the KSC Information Technology (IT) Applications Development Team and the NASA Space Biology Program, took the initiative to develop a database that would serve as the central repository for existing microgravity research. This repository site is open to the public and houses not only peer-reviewed publications relating to microgravity research, but also dissertations, technical publications such as white papers, NASA technical publications, and patent publications. In this presentation, we will discuss some of our literature research findings as well as present a working prototype version of the Library. It is our goal that the future infrastructure of this database advance to become a fully-functional, NASA Space Life-Sciences Research Library.

Anna Maria Ruby↗

NASA NTRSDate not supplied

Assessing the use of UAS-related terms in ASRS using Seed Topic Modeling

Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants and other involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts. The de-identified reports are then disseminated to the aviation community in a number of ways including entry into an online database. Augmenting the discovery of topics of user interest in this online database would therefore be beneficial to the community it serves. Aim: We propose and execute an experiment to assess the use of seed term topic modeling using the database narratives to identify UAS reports. The use of seed term topic modeling would enable users to identify groups of related narratives associated to a topic of their interest. Method: We use a newly curated field in ASRS reports which identify UAS from non-UAS reports in combination of different set of UAS related terms to assess if seed topic modeling can be used in ASRS.

LDA↗

NASA NTRSDate not supplied

Mining the Gravity Mutants of Arabidopsis

Gravity mutants are a valuable resource for understanding gravity perception, signaling, and response in plants. A review of 190 publications resulted in a list of 97 loci with mutations that caused a gravitropic phenotype. While all these mutants show some form of gravity phenotype, several are also generally defective in growth. After removing these nonspecific mutants, 76 loci were deemed to have true gravity mutants. The gene list was then used to create a sortable database containing key factors of gravity signaling as well as data on methodologies and the development of mutant lines. Indexing this database has allowed us to pull out trends that were not visible in individual publications. For example, mutants that are unable to rearrange starch statoliths make up a larger proportion of the described inflorescence stems mutants than any other organ. Comparing these statolith mutants across organs shows that root and inflorescence stems consistently display different phenotypes for the same class of defect. The more severe gravity defects are most commonly described in root tissue while other tissues are more likely to show only a delayed or reduced response to gravity. The experience of members of the GeneLab plant Analytics Working Group (AWG) in data visualization and gene mapping have sparked new ideas for utilizing this database. Knowledge of shared traits, mutant development, and growth can provide a new resource for the production of seed lines specialized for their response to gravity.

gravitropism↗

NASA NTRSDate not supplied

Using A Guided Interview to Create an Individual Exposure Profile for The Lifetime Surveillance of Astronaut Health (LSAH)

BACKGROUND To support NASA’s Lifetime Surveillance of Astronaut Health (LSAH) project, Individual Exposure Profiles (IEPs) were developed to record an astronaut’s pre-, in-, and post-NASA exposures. NASA astronauts were invited to participate in a one-time guided interview to review known hazard exposures and medical history documented in NASA records and to add new information not otherwise reported. The purpose of the IEP project was to determine if any significant information was gained from these interviews and identify potential trends in long-term health. METHODOLOGY The pre-filled exposure profile data was extracted from several sources including medical records, biographies, and LSAH records. The information that was pre-filled before the interview included occupational exposures prior to selection to the Astronaut Corps, during active astronaut career (e.g., EVA and ground-based training, on-orbit exposures), and after active career. The IEPs also contained relevant medical history (e.g., audiometry, illnesses, injuries) and significant non-occupational exposures. 189 interviews were conducted from 2012-2014. A Microsoft Access database was created to store the information collected in the IEPs before and after the interviews. The database houses the information from the IEPs to track the updates made to the original data. By analyzing which astronauts supplied additional information and which kinds of data were consistently added, potential gaps and trends in missing data may be identified. In designing the database, an efficient structure was implemented for ease of inputting data and to create variables that would generate quantifiable data. Creating standardized variables within the structure helped ease the process of inputting, organizing data, and analyzing data. Additional updates/data were denoted and were categorized by type of update. The categories identified were “Confirmed”, “Confirmed & Supplemented”, “Supplemented”, “Denied”, “Denied & Supplemented”, and “Other”. STATISTICAL ANALYSIS AND RESULTS To assess frequency of exposure updates, descriptive statistics will be generated and stratified by relevant factors such as astronaut selection decade, age at selection, and program/era. Hypothesis testing will be performed to understand the associations between updates to exposure information and population characteristics.

Astronaut health↗

NASA NTRSDate not supplied

Flow Boiling & Condensation Experiment (FBCE): Flow Boiling in Earth Gravity and Onboard the International Space Station

Two phase thermal management systems that capitalize on both latent and sensible heats of the working fluid can yield orders of magnitude enhancements in flow boiling and condensation heat transfer coefficients and reduce size and weight of future space systems. Because the understanding of microgravity influences on two-phase flow and heat transfer is quite limited, there is presently an urgent need for a new experimental microgravity facility to enable investigators to perform long-duration flow boiling and condensation experiments in pursuit of reliable databases. This presentation will discuss results from the Flow Boiling and Condensation Experiment (FBCE), a collaborative effort between Purdue University and NASA Glenn Research Center. Experiments have been performed using the final system with the Flow Boiling Module (FBM) in vertical orientation in Earth gravity (Mission Sequence Tests, MST) and in microgravity onboard the International Space Station (ISS). High-speed-video flow visualization, heat transfer, and critical heat flux (CHF) results from the MST are presented for both subcooled liquid and saturated liquid-vapor inlet conditions. CHF predictions made using the Interfacial Lift-off Model are compared with a consolidated database made by compiling FBM datasets obtained in prior years for different orientations in Earth gravity and on parabolic flights. New explicit correlations for CHF and subcooled flow boiling heat transfer coefficient are developed and shown to be excellent in their predictive accuracies against consolidated experimental databases. Computations are performed for flows in microgravity and horizontal flows in Earth gravity, the results of which show a good predictive accuracy for both void fraction and wall temperature. Finally, similar preliminary results from the recent ISS experiments are presented.

Issam Mudawar↗

NASA NTRSDate not supplied

Introduction of the NASA Microgravity Research Library

As opportunities for conducting experiments in space are rare, more studies have been published using ground-based analogs that simulate microgravity conditions. For example, when conducting a literature search in PubMed for peer-reviewed articles and studies that used simulated microgravity conditions, results will yield over 5,000 publications dating back to 1961. The issue with this search technique and medium is that these articles are vast in quantity and spread out across multiple web-based databases, repositories, and libraries; some of which, are wholly inaccessible. For example, in PubMed for a single year, we found 1,000+ microgravity research articles among more than 12,000 general, space research articles; these, were within an overarching 350,000+ total, general medical research articles for just 2020. The KSC Microgravity Simulation Support Facility (MSSF), with support from the KSC Information Technology (IT) Applications Development Team and the NASA Space Biology Program, took the initiative to develop a database that would serve as the central repository for existing microgravity research. This repository site is open to the public and houses not only peer-reviewed publications relating to microgravity research, but also dissertations, technical publications such as white papers, NASA technical publications, and patent publications. In this presentation, we will discuss some of our literature research findings as well as present a working prototype version of the Library. It is our goal that the future infrastructure of this database advance to become a fully-functional, NASA Space Life-Sciences Research Library.

Anna Maria Ruby↗

NASA NTRSDate not supplied

Aerodynamic Loading on Crew Access Arm

An aerodynamic database for the crew access arm during deployment is generated. While initial attempts used data derived from wind tunnel testing, limitations lead to the use of computational fluid dynamics to improve analysis. This computational data compared favorably to the experimental data increasing confidence in both. Further analysis lead to simplification showing the ability to build the database with a single relative wind variable which takes into account both arm deployment angle and wind direction. Eventually geometric simplifications and conservative results lead to the use of simulations of the CAA alone to build the database.Finally these static conditions are then compared to a dynamic simulation where the CAA rotates into position to test the quasi-steady state assumptions used to generate the database. The dynamic case showed an increase in the moment of interest but within acceptable bounds for now.

SLS↗

NASA NTRSDate not supplied

Ground Wind Loads on the Space Launch System’s Mobile Launcher Crew Access Arm

An aerodynamic database for the crew access arm during deployment is generated. While initial attempts used data derived from wind tunnel testing, limitations lead to the use of computational fluid dynamics to improve analysis. This computational data compared favorably to the experimental data increasing confidence in both. Further analysis lead to simplification showing the ability to build the database with a single relative wind variable which takes into account both arm deployment angle and wind direction. Eventually geometric simplifications and conservative results lead to the use of simulations of the CAA alone to build the database.Finally these static conditions are then compared to a dynamic simulation where the CAA rotates into position to test the quasi-steady state assumptions used to generate the database. The dynamic case showed an increase in the moment of interest but within acceptable bounds for now.

SLS↗

NASA NTRSDate not supplied

AVT-297 Development of a Framework for Validation of Computational Tools

Design of aerospace vehicles relies on system models. These models rely on validation data to ensure accurate representation of the system. This paper provides an introduction to the problem and an overview of a NATO STO Activity, AVT-297, which developed a framework to determine validation experiments required to support system level models. The goals of the research group were to develop a process to identify a validation database for intended uses of a vehicle system, demonstrate the process on vehicles and document the process. Applying this process to multiple intended uses and collecting this set of validation databases identifies a set of validation experiments that could be applied to the design of multiple vehicles, further reducing the cost and time to develop air and naval vehicles. Four subgroup teams focused on different aspects of the validation database process: two focused on different aspects of a missile, and two focused on different aspects of a fixed-wing mobility transport class vehicle. This resulted in three different processes to decompose the multi-disciplinary problem to identify critical validation data. All four of the teams demonstrated their process on a sample problem demonstrating the benefit of the process.

Validation↗

NASA NTRSDate not supplied

IMPACT, a Tool Suite for Crew Health and Performance System Trade Analyses and Decision Support - Status of Development

Mission planners, systems engineers, and clinicians that support crew health and performance face very difficult choices on upcoming exploration missions. Given that there will be a heavily constrained mass and volume allocation for a medical system on these missions, what medical capability should be manifested to minimize both medical risk and mission risk? Given that not all promising research and technology proposals can be funded, how can proposals be prioritized so that those funded research investments produce the maximum benefit in reducing overall medical risk? The Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) project seeks to answer these kinds of questions and others to support upcoming exploration missions. IMPACT enables risk-informed and evidence-based trade space analysis for future space vehicles, missions, and systems. This presentation will discuss the long-term HRP and ExMC vision for the larger ecosystem of tools, which include an updated medical database, consisting of an Evidence Library for medical conditions and a medical item database (MedID) for medical resources, dynamic Probabilistic Risk Assessment (PRA) capabilities, System Modeling Language (SysML) models, and contextual data visualizations of output data. IMPACT is the result of a multi-center collaborative effort. The trade space analyses performed by IMPACT can directly inform mission, vehicle, and habitat development by quantifying medical risk, given a design reference mission, crew attributes and a set of medical capabilities. This presentation will update the audience on the development status of the tool suite as it nears its System Acceptance Review (SAR). It will review IMPACT’s constituent parts, briefly discuss typical outputs and outline the plans for transitioning to operations, currently scheduled for later in FY23. Recent development successes on the IMPACT project include the integration of the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) v2.0 to accommodate segmented missions with multiple carriers and medical systems, full onboarding of the IMPACT Medical Database (IMPACT-MD), clustering medical resources and skills into medical capabilities and mutually-dependent bundles, and the ability to perform trade analyses on different medical sets, different design reference missions (DRM), with different crew complements and extra-vehicular activity (EVA) schedule.

IMPACT↗

NASA NTRSDate not supplied

Evaluating Meteorological Dust Events and Machine-Learning Based Dust Identification in Geostationary Satellite Imagery

NASA scientists in the Short-term Prediction Research and Transition Center (SPoRT) developed a physically-based machine learning approach to identify dust in satellite imagery with a focus on night-time dust detection (Berndt et al. 201; DustTracker-AI). NASA/NOAA Geostationary Environmental Operational Satellite-16 (GOES-16) imagery was used for training and model inputs. The training, testing and validation data set consists of 28 events in the Southwest United States, capturing dust and null events in the region from 2018-2020.With 83 distinct images and millions of pixels a random forest model was trained and validated, correctly labeling 85% of dust pixels.For the first time, the model was run in near-real time production during the spring of 2022 and dust probability visualizations were made available to NOAA National Weather Service (NWS) forecasters to assess its utility for dust forecasting. Results indicated the model helped increase the confidence in the presence of dust and enabled dust tracking for a longer period of time into the night-time hours. Forecaster assessment and running the model in near real-time allowed for the team to determine the types of events missed, captured, and false alarms. To gain additional context on model performance,the SPoRT team sought to gather more detailed information on the training database(e.g., meteorological characteristics and drivers). The goal of this project was to identify the meteorological drivers for the dust events and create a database which synthesized information from observations, forecaster discussions, and analyses pertaining to the dust events to understand the types of events currently used to train the model. A more detailed meteorological synopsis was created for each dust event in the training, testing, and validation datasets. Following the completion of the database and documentation, the classification details revealed that 88% of the dust events were synoptically driven while mesoscale events were less prevalent in model datasets. Meteorological conditions found such as mixing layer depth and wind velocity had mean values of 645mb and 21kt respectively.With conditions of deep mixed layers and moderate to strong surface winds a mesoscale thunderstorm outflow event was considered and subsequently added to the model training data set to test the impact of additional mesoscale training data. The model was retrained and then qualitatively tested on a sample thunderstorm outflow case that the original model was unable to identify. Preliminary results showed potential that the addition of more mesoscale events included in the training data could help to better identify indistinct and localized dust events.

Connor Welch↗

NASA NTRSDate not supplied

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Greg Schuster↗

NASA NTRS2021

The Deep-Time Digital Earth program: data-driven discovery in geosciences

Current barriers hindering data-driven discoveries in deep-time Earth (DE) include: substantial volumes of DE data are not digitized; many DE databases do not adhere to FAIR (findable, accessible, interoperable and reusable) principles; we lack a systematic knowledge graph for DE; existing DE databases are geographically heterogeneous; a significant fraction of DE data is not in open-access formats; tailored tools are needed. These challenges motivate the Deep-Time Digital Earth (DDE) program initiated by the International Union of Geological Sciences and developed in cooperation with national geological surveys, professional associations, academic institutions and scientists around the world. DDE’s mission is to build on previous research to develop a systematic DE knowledge graph, a FAIR data infrastructure that links existing databases and makes dark data visible, and tailored tools for DE data, which are universally accessible. DDE aims to harmonize DE data, share global geoscience knowledge and facilitate data-driven discovery in the understanding of Earth’s evolution.

Chengshan Wang↗

NASA NTRS2023

Crew Earth Observations: New Tools to Support Your Research

The collection of astronaut photography hosted on the Gateway to Astronaut Photography of Earth (GAPE, eol.jsc.nasa.gov) forms one of the most extensive historical compilations of Earth remote sensing data sets available to researchers and the public. The GAPE database contains astronaut photography spanning all manned NASA spaceflight missions over the past 60 years and continuing to this day with operations on the International Space Station (ISS). The continuous crew presence in low Earth orbit (LEO) on the ISS for the last 22+ years and the advent of digital handheld cameras has resulted in an exponential increase in astronaut photography, growing the GAPE collection to over 4.5M photographs (Figs. 1 and 2). This increase in astronaut photography of Earth has corresponded to a significant increase in interest in the collection by the research community and the public. The Earth Science and Remote Sensing (ESRS) group at Johnson Space Center, which manages Crew Earth Observations (CEO) from the ISS, has been developing multiple new tools to improve the GAPE database so that users can more quickly find the imagery they need. The three major enhancements to GAPE are: a new API to interface with the database, a method for automatically georeferencing ISS photos (Fig. 3), and a new tool for automatically generating timelapse movies.

Kenton R Fisher↗

NASA NTRS2022

Gaussian Process Regression Method for Costing SmallSat Bus Capabilities

NASA is responding to the growing interest in, andcapabilities of, small satellites for science applications with an increasingnumber and frequency of Announcements of Opportunityfor small satellite space missions. Estimating the probabilitythat these mission concepts will fit within the small cost capsof these opportunities is largely driven by the probability thatone of the burgeoning number of small satellite providers will beable to meet the payload’s accommodation requirements withinthe budget for the spacecraft. JPL has collected a databasecontaining technical specifications and cost of commerciallyavailable Smallsat buses across various vendors. The primarypurpose of the database is for use in JPL’s Team X architecturestudies to inform cost estimates of a spacecraft bus which fitsthe customer’s technical requirements for their payload andmission. Customer needs are often unique and don’t alignperfectly with an off-the-shelf commercial spacecraft bus, whichmotivates the need to develop a cost model across the continuoustechnical parameter space.Al’s Bus Cost Distribution Estimator (ABCDE) uses Gaussianprocess regression (GPR) to predict commercial Smallsat spacecraftbus cost based on a subset of a customer’s technicalrequirements (payload mass, payload power, delta V, pointingcontrol, and downlink rate). GPR is implemented in ABCDE asa Bayesian method which fits an implied multivariate regressionon the technical parameters and uses kriging to intentionally“overfit” the residuals. Overfitting the residuals allows costestimates to collapse in uncertainty closer to the data pointswhile maintaining larger uncertainty intervals in regions of parameterspace with fewer data records. The data used to fit thismodel is sensitive and represents cost estimates for off-the-shelfcommercial buses. GPR simultaneously protects the sensitivityof the database and uses the sparse nature of the database toaccount for uncertainty in cost in a useful way. For a givenset of customer technical requirements, the tool provides a costestimate distribution, the percentiles of which can be interpretedas a confidence level of finding a commercial bus under a specifiedcost cap. ABCDE dramatically pushes the boundaries ofspacecraft cost estimation models due to its Bayesian methodology(accounting for the maximum uncertainty in the underlyingregression), the mathematically advanced kriging methodology,and the novelty of its application in Team X architecture tradestudies.

Austin, Alex↗

NASA NTRSDate not supplied

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Elisabeth Andrews↗