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At least 739 records · Page 41

The Composition of Comet C 2012 K1 (PanSTARRS) and the Distribution of Primary Volatile Abundances Among Comets

On 2014 May 22 and 24 we characterized the volatile composition of the dynamically new Oort cloud comet C2012 K1 (PanSTARRS) using the long-slit, high resolution ( lambda/delta lambda is approximately or equal to 25,000) near-infrared echelle spectrograph (NIRSPEC) at the 10 m Keck II telescope on Maunakea, Hawaii. We detected fluorescent emission from six primary volatiles (H2O, HCN, CH4, C2H6, CH3OH, and CO). Upper limits were derived for C2H2, NH3, and H2CO. We report rotational temperatures, production rates, and mixing ratios (relative to water). Compared with median abundance ratios for primary volatiles in other sampled Oort cloud comets, trace gas abundance ratios in C2012 K1 (PanSTARRS) for CO and HCN are consistent, but CH3OH and C2H6 are enriched while H2CO, CH4, and possibly C2H2 are depleted. When placed in context with comets observed in the near- infrared to date, the data suggest a continuous distribution of abundances of some organic volatiles (HCN, C2H6, CH3OH, CH4) among the comet population. The level of enrichment or depletion in a given comet does not necessarily correlate across all molecules sampled, suggesting that chemical diversity among comets may be more complex than the simple organics-enriched, organics-normal, and organics-depleted framework.

Roth, Nathan X.↗

Communication Optimizations for a Wireless Distributed Prognostic Framework

Distributed architecture for prognostics is an essential step in prognostic research in order to enable feasible real-time system health management. Communication overhead is an important design problem for such systems. In this paper we focus on communication issues faced in the distributed implementation of an important class of algorithms for prognostics - particle filters. In spite of being computation and memory intensive, particle filters lend well to distributed implementation except for one significant step - resampling. We propose new resampling scheme called parameterized resampling that attempts to reduce communication between collaborating nodes in a distributed wireless sensor network. Analysis and comparison with relevant resampling schemes is also presented. A battery health management system is used as a target application. A new resampling scheme for distributed implementation of particle filters has been discussed in this paper. Analysis and comparison of this new scheme with existing resampling schemes in the context for minimizing communication overhead have also been discussed. Our proposed new resampling scheme performs significantly better compared to other schemes by attempting to reduce both the communication message length as well as number total communication messages exchanged while not compromising prediction accuracy and precision. Future work will explore the effects of the new resampling scheme in the overall computational performance of the whole system as well as full implementation of the new schemes on the Sun SPOT devices. Exploring different network architectures for efficient communication is an importance future research direction as well.

Saha, Sankalita↗

Statistical Analysis of CFD Solutions from the 6th AIAA CFD Drag Prediction Workshop

A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from North America, Europe, Asia, and South America using both common and custom grid sequences as well as multiple turbulence models for the June 2016 6th AIAA CFD Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was the Common Research Model subsonic transport wing-body previously used for both the 4th and 5th Drag Prediction Workshops. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with previous workshops.

Statistical analysis↗

Gateway Element and Payload Materials Outgassing Analyses: HALO, HERMES, and ERSA

Gateway was intended to be humanity’s first space station around the Moon, but its development has been paused as the National Aeronautics and Space Administration (NASA) shifts focus to achieving the United States’ National Space Policy goals. Instead of an orbiting lunar outpost, NASA will now pursue the development of a lunar surface base to support a sustained human presence on the Moon. Before the program’s pause, Gateway’s Induced Environments team worked to ensure payloads and elements (i.e., modules) complied with induced environment requirements. Methods developed and insights gained from this work will have applicability to NASA’s Moon Base and the potential repurposing of Gateway elements and payloads, as well as to induced environments modeling for future space stations. The Gateway program’s induced environment included molecular contamination, electric thruster plume sputter and redeposition, and lunar dust transfer from the Human Landing System (HLS). Primary sources of external molecular contamination included materials outgassing, chemical thruster plume contamination, and vacuum venting. The focus of this paper will be on element- and payload-level materials outgassing analyses performed for Gateway Configuration 1, extending the previously-developed framework for Gateway system-level external molecular contamination modeling. Gateway Configuration 1 consisted of the Power and Propulsion Element (PPE) and the Habitation and Logistics Outpost (HALO). It also included payloads like the European Radiation Sensor Array (ERSA) attached to PPE and the Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) attached to HALO. The element- and payload-level analyses to be introduced in this paper for HALO, HERMES, and ERSA enabled high-fidelity descriptions of Gateway’s external molecular contamination environment. Approaches to geometric modeling, meshing, outgassing rate assignment, molecular transport modeling, and analysis methodology will be presented. Element and payload contaminant deposition onto sensitive Gateway receiver surfaces will be summarized and results compared to induced environment requirements. While these results incorporate refinements made over the course of the program, they were not intended to be final. Therefore, modeling assumptions and inputs, potential improvements, and lessons-learned will be documented to inform future work on Moon Base, repurposed elements and payloads, and other space stations.

Gateway↗

A Unified Computational Model for Solar and Stellar Flares

We present a unified computational framework that can be used to describe impulsive flares on the Sun and on dMe stars. The models assume that the flare impulsive phase is caused by a beam of charged particles that is accelerated in the corona and propagates downward depositing energy and momentum along the way. This rapidly heats the lower stellar atmosphere causing it to explosively expand and dramatically brighten. Our models consist of flux tubes that extend from the sub-photosphere into the corona. We simulate how flare-accelerated charged particles propagate down one-dimensional flux tubes and heat the stellar atmosphere using the Fokker-Planck kinetic theory. Detailed radiative transfer is included so that model predictions can be directly compared with observations. The flux of flare-accelerated particles drives return currents which additionally heat the stellar atmosphere. These effects are also included in our models. We examine the impact of the flare-accelerated particle beams on model solar and dMe stellar atmospheres and perform parameter studies varying the injected particle energy spectra. We find the atmospheric response is strongly dependent on the accelerated particle cutoff energy and spectral index.

radiative transfer↗

Spacecraft materials: Comparison between flight results obtained on LDEF and MIR

Two flight experiments dedicated to the study of the performance of materials in space have been carried out. Material samples have been exposed passively to low-Earth orbit (LEO) environment, then retrieved for laboratory study. The first experiment was conducted in the framework of the FRECOPA project and was flown on the trailing edge of the Long Duration Exposure Facility (LDEF) (exposure to vacuum and ultraviolet (UV) radiation for 5.5 years). The experiment COMES was installed outside of the MIR space station during an extravehicular activity; it was exposed to vacuum, O-atoms, and UV radiation for 1.1 year; and it was brought back to Earth by cosmonauts. The difference in exposure conditions and the use of transparent filters protecting some samples of COMES enable to differentiate the effects of UV radiation and oxygen atoms. The degradations of several thermal control coatings (paints, metalized polymeric films with and without ITO), structural materials, and optical components have been observed, measured, and compared after these two flight experiments. This paper summarizes various 'lessons learned' that can be used to identify aspects of space aging, to orient future research in this field, and to assist in spacecraft design.

Guillaumon, Jean-Claude↗

Joint Bayesian Component Separation and CMB Power Spectrum Estimation

We describe and implement an exact, flexible, and computationally efficient algorithm for joint component separation and CMB power spectrum estimation, building on a Gibbs sampling framework. Two essential new features are (1) conditional sampling of foreground spectral parameters and (2) joint sampling of all amplitude-type degrees of freedom (e.g., CMB, foreground pixel amplitudes, and global template amplitudes) given spectral parameters. Given a parametric model of the foreground signals, we estimate efficiently and accurately the exact joint foreground- CMB posterior distribution and, therefore, all marginal distributions such as the CMB power spectrum or foreground spectral index posteriors. The main limitation of the current implementation is the requirement of identical beam responses at all frequencies, which restricts the analysis to the lowest resolution of a given experiment. We outline a future generalization to multiresolution observations. To verify the method, we analyze simple models and compare the results to analytical predictions. We then analyze a realistic simulation with properties similar to the 3 yr WMAP data, downgraded to a common resolution of 3 deg FWHM. The results from the actual 3 yr WMAP temperature analysis are presented in a companion Letter.

numerical↗

Simulations of Aerosol Microphysics in the NASA GEOS-5 Model

Aerosol-cloud-chemistry interactions have potentially large but uncertain impacts on Earth's climate. One path to addressing these uncertainties is to construct models that incorporate various components of the Earth system and to test these models against data. To that end, we have previously incorporated the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) module online in the NASA Goddard Earth Observing System model (GEOS-5). GEOS-5 provides a platform for Earth system modeling, incorporating atmospheric and ocean general circulation models, a land surface model, a data assimilation system, and treatments of atmospheric chemistry and hydrologic cycle. Including GOCART online in this framework has provided a path for interactive aerosol-climate studies; however, GOCART only tracks the mass of aerosols as external mixtures and does not include the detailed treatments of aerosol size distribution and composition (internal mixtures) needed for aerosol-cloud-chemistry-climate studies. To address that need we have incorporated the Community Aerosol and Radiation Model for Atmospheres (CARMA) online in GEOS-5. CARMA is a sectional aerosol-cloud microphysical model, capable of treating both aerosol size and composition explicitly be resolving the aerosol distribution into a variable number of size and composition groupings. Here we present first simulations of dust, sea salt, and smoke aerosols in GEOS-5 as treated by CARMA. These simulations are compared to available aerosol satellite, ground, and aircraft data and as well compared to the simulated distributions in our current GOCART based system.

Colarco, Peter↗

Performance Analysis of Optimized STARC-ABL Designs Across the Entire Mission Profile

Boundary layer ingestion (BLI) offers the potential for significant fuel burn reduction by exploiting strong aeropropulsive interactions. NASA’s STARC–ABL concept uses an electri- cally powered BLI tail cone thruster on what is otherwise a traditional airframe. Despite the traditional airframe of this configuration, aeropropulsive integration is critical to the perfor- mance of the BLI propulsor. Furthermore, due to being electrically powered, the fan pressure ratio and efficiency of the BLI tail cone thruster vary widely across the flight envelope, and this variation in fan performance must be accounted for with the aeropropulsive integration of the BLI system. Thus, accurate performance prediction for this novel propulsion configu- ration requires the use of a coupled aeropropulsive model across the flight envelope. In this work, we analyze the off-design performance of 18 optimized designs using an aeropropulsive model that is built with the OpenMDAO framework to couple 3-D RANS CFD simulations to 1-D thermodynamic cycle analyses. The designs are created via high-fidelity aeropropulsive design optimizations that span a range of fan pressure ratio and thrust values at the cruise conditions for the STARC-ABL concept, which was chosen as the aerodynamic design point for the propulsor. Performance analyses we present herein are then performed at a range of off-design flight conditions that span the flight envelope, including low-speed and low-altitude flight conditions. This study provides the first set of high-fidelity data for the STARC–ABL configuration at off-design conditions, and the results quantify the power savings through BLI compared to a traditional propulsion system across the entire mission profile.

optimization↗

Micromechanics Modeling of Textiles for Re-Entry Parachute Applications

Recent flight test projects and NASA missions have highlighted the challenges associated with accurately and efficiently modeling the behavior of parachute deployment systems needed for parachute design. Moreover, parachute deployment has been identified as one of the higher risk components for such missions. The analysis of textile fabrics used for atmospheric entry is inherently complex due to the multiple scales present in the fabric structure, including individual fiber filaments at the microscale, yarn bundles of fibers at the mesoscale, and the overall woven fabric at the macroscale. Computational tools for simulating fabric behavior must be able to account for the different mechanisms present at each scale without sacrificing computational efficiency. This work examines the generalized multiscale method of cells micromechanics theory, which has previously been used for the analysis of reinforced composite structures, to unreinforced textile fabrics. Modifications to the existing composite multiscale framework, implemented in NASA’s Multiscale Analysis Tool (NASMAT), include the specific mechanics unique to unreinforced textile fabrics, and overcoming the assumptions of a fixed fiber angle. It looks to assess the feasibility of using the NASMAT tool for efficient prediction of the response of unreinforced fabrics to loading such that it can ultimately be applied to fluid structure interaction tools for the prediction of parachute deployment systems. In this work, fabric behavior is simulated in NASMAT through homogenization of a triply periodic repeating unit cell, where the geometry of the subcells can change as a function of loading to represent the relative rotation and uncrimping that can occur in fabric tows. Predictions from the amended NASMAT code are compared to experimental data for uniaxial and off-axis tension to verify the ability of the code to incorporate lower-scale mechanics in prediction of unreinforced fabrics under loading.

Micromechanics↗

A LaGrangian Perspective of the Surface Energy Budget Contributions to Sea Ice Evolution in the ‘New Arctic’

Recent Arctic warming outpaces global warming and is characterized by dramatic changes in sea ice (record sea ice loss, thinner and more seasonal ice cover), warming SSTs, and a lengthening melt season. These changes impact the surface energy budget and the sensitivity of sea ice to radiative forcing, namely an increased sensitivity of thinner ice to local radiative forcings and a weaker buffering of surface-atmosphere exchanges of heat and moisture. However, these processes are a large source of uncertainty in global climate models with prior studies finding that poor representations of downwelling longwave radiation and sea ice albedo lead to model spread in sea ice conditions. A limitation of prior work is examining sea ice-atmosphere interactions through an Eulerian framework. This study utilizes a sea ice parcel dataset in a LaGrangian framework, allowing for tracking of surface energy budget-sea ice interactions over the lifespan of individual sea ice parcels; this framework also allows for the quantification of the sea ice response to episodic weather events along with seasonal drivers, including the drivers of rapid growth and melt events. First, lag-lead relationships between relevant surface energy budget terms and sea ice thickness changes are explored to understand the atmospheric conditions preceding rapid growth and melt. The impact of episodic events- moisture intrusion, warm air outbreaks, cyclones- on sea ice growth are also investigated by stratifying first-year parcels by sea ice thickness at the end of the growth season and analyzing the effect of atmospheric variability (number and intensity of episodic events) on parcel thickness change. Lastly, parcel growth and melt and the associated radiative anomalies are compared to snowfall events/snow thickness to determine how snowfall modifies the interaction between the local surface energy budget and sea ice mass balance.

Patrick Taylor↗

SMEX-Lite Modular Solar Array Architecture

For the most part, Goddard solar arrays have been custom designs that are unique to each mission. The solar panel design has been frozen prior to issuing an RFP for their procurement. There has typically been 6-9 months between RFP release and contract award, followed by an additional 24 months for performance of the contract. For Small Explorer (SMEX) missions, with three years between mission definition and launch, this has been a significant problem. The SMEX solar panels have been sufficiently small that the contract performance period has been reduced to 12-15 months. The bulk of this time is used up in the final design definition and fabrication of flight solar cell assemblies. Even so, it has been virtually impossible to have the spacecraft design at a level of maturity sufficient to freeze the solar panel geometry and release the RFP in time to avoid schedule problems with integrating the solar panels to the spacecraft. With that in mind, the SMEX-Lite project team developed a modular architecture for the assembly of solar arrays to greatly reduce the cost and schedule associated with the development of a mission- specific solar array. In the modular architecture, solar cells are fabricated onto small substrate panels. This modular panel (approximately 8.5" x 17" in this case) becomes the building block for constructing solar arrays for multiple missions with varying power requirements and geometrical arrangements. The mechanical framework that holds these modules together as a solar array is the only mission-unique design, changing in size and shape as required for each mission. There are several advantages to this approach. First, the typical solar array development cycle requires a mission unique design, procurement, and qualification including a custom qualification panel. With the modular architecture, a single qualification of the SMEX-Lite modules and the associated mechanical framework in a typical configuration provided a qualification by similarity to multiple missions. It then becomes possible to procure solar array modules in advance of mission definition and respond quickly and inexpensively to a selected mission's unique requirements. The solar array modular architecture allows the procurement of solar array modules before the array geometry has been frozen. This reduces the effect of procurement lead-time on the mission integration and test flow by as much as 50%. Second, by spreading the non-recurring costs over multiple missions, the cost per unit area is also reduced. In the case of the SMEX-Lite procurement, this reduction was by about one third of the cost per unit area compared to previous SMEX mission-unique procurements. Third, the modular architecture greatly facilitates the infusion of new solar cell technologies into flight programs as these technologies become available. New solar cell technologies need only be fabricated onto a standard-sized module to be incorporated into the next available mission. The modular solar array can be flown in a mixed configuration with some new and some standard cell technologies. Since each module has its own wiring terminals, the array can be arranged as desired electrically with little impact to cost and schedule. The solar array modular architecture does impose some additional constraints on systems and subsystem engineers. First, they must work with discrete solar array modules rather than size the array to fit exactly within an available envelope. The array area is constrained to an integer multiple of the module area. Second, the modular design is optimized for space radiation and thermal environments not greatly different from a typical SMEX LEO environment. For example, a mission with a highly elliptical orbit (e.g., Polar, SMEX/FAST) would require thicker coverglasses to protect the solar cells from the more intense radiation environment.

Lyons, John↗

Assimilation of Multi-Frequency, Multi-Polarization Passive Microwave Brightness Temperature Observations in North America over Snow-Covered Regions Using Support Vector Machines

Accurately estimating the mass of water within a snowpack (a.k.a. snow water equivalent, or SWE) across regional or continental scales is a challenge. In order to overcome some of the limitations in traditional SWE retrieval algorithms or radiative transfer-based snow emission models, this study explores the use of a support vector machine (SVM) to merge an advanced land surface model within a radiance emission (i.e., brightness temperature) assimilation framework. The goal of direct radiance assimilation is preferable as it avoids inconsistencies in the use of ancillary data between the assimilation system and the independently-generated geophysical retrieval. The impact of assimilating multiple observations simultaneously at different frequency and polarization combinations is then evaluated via comparisons to state-of-the-art SWE and snow depth products as well as available ground-based measurements across North America for the years 2002 through 2011. It is found that assimilation-derived estimates (relative to estimates without assimilation) tend to better agree with state-of-the-art snow products. In addition, an overall improvement in goodness-of-fit statistics for snow estimates is achieved via assimilation when compared against ground-based snow measurements. In addition, these improvements in snow are shown to translate into improvements in streamflow predictions. Specifically, 11 out of the 13 major snow-dominated basins investigated have improved cumulative runoff estimates versus ground-based discharge measurements compared to the no-assimilation scenario. It is proven that a SVM can serve as an efficient and effective observation operator for a snow mass analysis within a radiance assimilation system.

Xue, Yuan↗

Data-driven landslide nowcasting at the global scale

Landslides affect nearly every country in the world each year. To better understand this global hazard, the Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed previously. LHASA version 1 combines satellite precipitation estimates with a global landslide susceptibility map to produce a gridded map of potentially hazardous areas from 60° North-South every 3 h. LHASA version 1 categorizes the world’s land surface into three ratings: high, moderate, and low hazard with a single decision tree that first determines if the last seven days of rainfall were intense, then evaluates landslide susceptibility. LHASA version 2 has been developed with a data-driven approach. The global susceptibility map was replaced with a collection of explanatory variables, and two new dynamically varying quantities were added: snow and soil moisture. Along with antecedent rainfall, these variables modulated the response to current daily rainfall. In addition, the Global Landslide Catalog (GLC) was supplemented with several inventories of rainfall-triggered landslide events. These factors were incorporated into the machine-learning framework XGBoost, which was trained to predict the presence or absence of landslides over the period 2015–2018, with the years 2019–2020 reserved for model evaluation. As a result of these improvements, the new global landslide nowcast was twice as likely to predict the occurrence of historical landslides as LHASA version 1, given the same global false positive rate. Furthermore, the shift to probabilistic outputs allows users to directly manage the trade-off between false negatives and false positives, which should make the nowcast useful for a greater variety of geographic settings and applications. In a retrospective analysis, the trained model ran over a global domain for 5 years, and results for LHASA version 1 and version 2 were compared. Due to the importance of rainfall and faults in LHASA version 2, nowcasts would be issued more frequently in some tropical countries, such as Colombia and Papua New Guinea; at the same time, the new version placed less emphasis on arid regions and areas far from the Pacific Rim. LHASA version 2 provides a nearly real-time view of global landslide hazard for a variety of stakeholders.

XGBoos↗

The Virtual Observatory Service TheoSSA: Establishing a Database of Synthetic Stellar Flux Standards II. NLTE Spectral Analysis of the OB-Type Subdwarf Feige 110

Context. In the framework of the Virtual Observatory (VO), the German Astrophysical VO (GAVO) developed the registered service TheoSSA (Theoretical Stellar Spectra Access). It provides easy access to stellar spectral energy distributions (SEDs) and is intended to ingest SEDs calculated by any model-atmosphere code, generally for all effective temperatures, surface gravities, and elemental compositions. We will establish a database of SEDs of flux standards that are easily accessible via TheoSSA's web interface. Aims. The OB-type subdwarf Feige 110 is a standard star for flux calibration. State-of-the-art non-local thermodynamic equilibrium stellar-atmosphere models that consider opacities of species up to trans-iron elements will be used to provide a reliable synthetic spectrum to compare with observations. Methods. In case of Feige 110, we demonstrate that the model reproduces not only its overall continuum shape from the far-ultraviolet (FUV) to the optical wavelength range but also the numerous metal lines exhibited in its FUV spectrum. Results. We present a state-of-the-art spectral analysis of Feige 110. We determined Teff =47 250 +/- 2000 K, log g=6.00 +/- 0.20, and the abundances of He, N, P, S, Ti, V, Cr, Mn, Fe, Co, Ni, Zn, and Ge. Ti, V, Mn, Co, Zn, and Ge were identified for the first time in this star. Upper abundance limits were derived for C, O, Si, Ca, and Sc. Conclusions. The TheoSSA database of theoretical SEDs of stellar flux standards guarantees that the flux calibration of astronomical data and cross-calibration between different instruments can be based on models and SEDs calculated with state-of-the-art model atmosphere codes.

Observatory↗

Component Level Regression Testing in a Hierarchical Architecture

The Goddard Earth Observing System (GEOS) is an Earth system model consisting of a large suite of individual model components that can be coupled in a flexible manner to investigate a variety of Earth science issues. Specific GEOS model configurations are composed as a hierarchical collection of components based on the Earth System Modeling Framework (ESMF). Regression testing of GEOS is currently limited to (1) full system tests that are poor at isolating specific defects and (2) a suite of unit tests which have very limited coverage. As part of our approach to improve upon the current testing situation, we have prototyped the capability to perform regression tests on individual GEOS components by leveraging and extending existing checkpoint/restart capabilities. In our implementation, each ESMF component has 3 states: Import (what it needs to run), Export (which it needs to provide to other components), and Internal (the component state proper). By capturing, Import, Export and Internal states for a given component during a ull run of GEOS, a generic driver can then rerun the component offline and compare expected exports with those that have been saved. The hierarchical structure of GEOS introduces an interesting wrinkle when trying to test components that in turn drive interacting child components. To fully isolate a parent component, we use the approach of software mocks, in which the exports of children are also saved during the initial capture run of GEOS. Then when testing the parent component, the children components are replaced by a generic mock component that produces exports from the previously saved data and ensures that that all interdependencies among children components are satisfied.

Thomas Clune↗

Component Level Testing in a Hierarchical Architecture

The Goddard Earth Observing System (GEOS) is an Earth system model consisting of a large suite of individual model components that can be coupled in a flexible manner to investigate a variety of Earth science issues. Specific GEOS model configurations are composed as a hierarchical collection of components based on the Earth System Modeling Framework (ESMF). Regression testing of GEOS is currently limited to (1) full system tests that are poor at isolating specific defects and (2) a suite of unit tests which have very limited coverage. As part of our approach to improve upon the current testing situation, we have prototyped the capability to perform regression tests on individual GEOS components by leveraging and extending existing checkpoint/restart capabilities. In our implementation, each ESMF component has 3 states: Import (what it needs to run), Export (which it needs to provide to other components), and Internal (the component state proper). By capturing, Import, Export and Internal states for a given component during a ull run of GEOS, a generic driver can then rerun the component offline and compare expected exports with those that have been saved. The hierarchical structure of GEOS introduces an interesting wrinkle when trying to test components that in turn drive interacting child components. To fully isolate a parent component, we use the approach of software mocks, in which the exports of children are also saved during the initial capture run of GEOS. Then when testing the parent component, the children components are replaced by a generic mock component that produces exports from the previously saved data and ensures that that all interdependencies among children components are satisfied.

Tom Clune↗

Modified Universal Design Survey: Enhancing Operability of Launch Vehicle Ground Crew Worksites

Operability is a driving requirement for next generation space launch vehicles. Launch site ground operations include numerous operator tasks to prepare the vehicle for launch or to perform preflight maintenance. Ensuring that components requiring operator interaction at the launch site are designed for optimal human use is a high priority for operability. To promote operability, a Design Quality Evaluation Survey based on Universal Design framework was developed to support Human Factors Engineering (HFE) evaluation for NASA s launch vehicles. Universal Design per se is not a priority for launch vehicle processing however; applying principles of Universal Design will increase the probability of an error free and efficient design which promotes operability. The Design Quality Evaluation Survey incorporates and tailors the seven Universal Design Principles and adds new measures for Safety and Efficiency. Adapting an approach proven to measure Universal Design Performance in Product, each principle is associated with multiple performance measures which are rated with the degree to which the statement is true. The Design Quality Evaluation Survey was employed for several launch vehicle ground processing worksite analyses. The tool was found to be most useful for comparative judgments as opposed to an assessment of a single design option. It provided a useful piece of additional data when assessing possible operator interfaces or worksites for operability.

Blume, Jennifer L.↗