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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Atmospheric Capture On Mars (and Processing)

The ultimate destination of NASA's human exploration program is Mars. In Situ Resource Utilization (ISRU) is a key technology required to enable such missions, as first proposed by Prof. Robert Ash in 1976. This presentation will review progress in the systems required to produce rocket propellant, oxygen, and other consumables on Mars using the carbon dioxide atmosphere and other potential resources. For many years, NASA, commercial companies, and academia have been developing, and demonstrating techniques to capture and purify Martian atmospheric gases for their utilization for the production of hydrocarbons, oxygen, and water in ISRU systems. Other gases will be required to be separated from Martian atmospheric gases to provide pure CO2 for processing elements. Significant progress has been demonstrated in CO2 collection via adsorption by molecular sieves, freezing, and direct compression. Early stage work in adsorption in Ionic Liquids followed by electrolysis to oxygen is also underway. In addition, other Martian gases, such as nitrogen and argon, occur in concentrations high enough to be useful as buffer gas and could be captured as well. Gas separation requirements include, but are not limited to the selective separation of: (1) methane and water from unreacted carbon oxides (CO2-CO) and hydrogen typical of a Sabatier-type process, (2) carbon oxides and water from unreacted hydrogen from a Reverse Water-Gas Shift process, and (3) carbon oxides from oxygen from a trash/waste processing reaction.

propellant production↗
NASA NTRS2018

Greedy Sampling and Incremental Surrogate Model-Based Tailoring of Aeroservoelastic Model Database for Flexible Aircraft

This paper presents a data analysis and modeling framework to tailor and develop linear parameter-varying (LPV) aeroservoelastic (ASE) model database for flexible aircrafts in broad 2D flight parameter space. The Kriging surrogate model is constructed using ASE models at a fraction of grid points within the original model database, and then the ASE model at any flight condition can be obtained simply through surrogate model interpolation. The greedy sampling algorithm is developed to select the next sample point that carries the worst relative error between the surrogate model prediction and the benchmark model in the frequency domain among all input-output channels. The process is iterated to incrementally improve surrogate model accuracy till a pre-determined tolerance or iteration budget is met. The methodology is applied to the ASE model database of a flexible aircraft currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that the proposed method can reduce the number of models in the original database by 67%. Even so the ASE models obtained through Kriging interpolation match the model in the original database constructed directly from the physics-based tool with the worst relative error far below 1%. The interpolated ASE model exhibits continuously-varying gains along a set of prescribed flight conditions. More importantly, the selected grid points are distributed non-uniformly in the parameter space, a) capturing the distinctly different dynamic behavior and its dependence on flight parameters, and b) reiterating the need and utility for adaptive space sampling techniques for ASE model database compaction. The present framework is directly extendible to high-dimensional flight parameter space, and can be used to guide the ASE model development, model order reduction, robust control synthesis and novel vehicle design of flexible aircraft.

numerical analysi↗
NASA NTRS2002

The StarLight interferometer architecture and operational concepts

The StarLight flight project was designed to demonstrate the key technologies of spacebome long-baseline stellar interferometry and precision formation flying for potential use on the Terrestrial Planet Finder (TPF) and other future astrophysics missions. Interferometer performance validation could be achieved over a 6-12 month period by obtaining several hundred fringe visibility amplitude measurements for stars in the band 600-1000 nm for a variety of stellar visibilities (0.2-1.0), magnitudes (Mv = 2-5), and baselines (B = 30-125 meters). Interferometry could be performed both in a 1 meter fixed-baseline combiner-only mode and in a two-spacecraft formation mode. In formation mode, the combiner spacecraft would remain at the focus of a virtual parabola, while the collector spacecraft assumed various positions along the parabola such that the two arms of the interferometer remained equal over a variety of separations and bearing angles. Challenges to be encountered in flight include high-bandwidth inter-spacecraft stellar and metrology pointing control, alignment and shear correction, delay and delay-rate estimation, visibility calibration, and robust fringe tracking in the presence of local and inter-spacecraft dynamics. This paper is based on the StarLight project design-capture of March 2002 and will describe the StarLight Interferometer System architecture and selected operational concepts (both of which have relevance to the on-going TPF Technology Program).

stellar↗
NASA NTRSDate not supplied

Probabilistic Blast Damage Modeling Uncertainties and Sensitivities

Blast overpressure is the predominant source of ground damage posed by potentially hazardous asteroid strikes. Estimates of the extent, severity, and likelihoods of potential blast damage regions will be one of the key metrics needed to mount civil defense or disaster response plans in the face of an impending impact. However, there are many inherent sources of uncertainty in evaluating the damage, both in characterizing the properties of the incoming object and in the approaches used to model the entry/impact and resulting damage, which make it difficult to produce a single ‘accurate’ or ‘best guess’ prediction of ground damage. The current 2021 PDC hypothetical impact scenario poses a particular challenge due to its short warning time. The need for rapid disaster response to prepare for an immanent impact, combined with lack of observational opportunities to refine basic knowledge about the object’s basic size and properties, make understanding the range and relative likelihood of consequences particularly critical. The potential damage caused by these blasts can be evaluated using a range of modeling and simulation approaches and levels of fidelity. Fast-running engineering-level models can be used to run large numbers of probabilistically sampled cases covering wide variations of uncertain properties or parameters. High-fidelity simulations, on the other hand, can capture more detailed/accurate blast physics, but can only be performed for a small selection of specific cases, requiring many assumptions to be made about the initial object and its unpredictable entry/breakup characteristics. In order to provide a more complete picture of the potential threat for effective disaster response, both types of analysis need to be employed together. In this approach, high-fidelity simulations are used to refine and anchor engineering models, and the probabilistic engineering models are used to evaluate broad parameters spaces and guide selection of the most pertinent simulation cases for a given scenario. This presentation expands upon the probabilistic asteroid impact risk assessments being performed as part of the 2021 PDC hypothetical impact exercise, focusing on key aspects of blast damage modeling uncertainties and sensitivities. We review the current modeling and simulation approaches employed in the current assessment, compare the relative levels of uncertainty stemming from each main element of the problem (i.e., knowledge of the asteroid properties, modeling of the atmospheric entry/breakup and airburst, and estimates of the ground damage from the resulting blasts waves), and highlight any notable trends and sensitivities for the current scenario case.

SMD↗
NASA NTRS2021

Remote Concurrent Engineering: A-Team Studies in the Virtual World

NASA Jet Propulsion Laboratory’s (JPL’s)Architecture Team (A-Team) has nearly a decade of experiencein maturing early formulation mission and technology conceptsby combining innovative collaborative engineering methodswith cutting-edge subject matter expertise and advancedanalysis tools in an in-person environment. When COVID-19forced JPL’s workforce to work remotely in March 2020, ATeamhad to quickly pivot from an in-person collaborativeenvironment to a remote working environment.Through introspection, careful planning, and considerablepractice, A-Team was able to develop new operating proceduresto effectively continue early formulation studies in a virtualenvironment. A-Team has held over 57 remote studies in the 10months since the start of mandatory telework at JPL in March2020. In the remote setting, A-Team conducts studies in half-daysessions with clients and subject matter experts (SMEs) viavideoconferencing, shared computer screens, and digitalcollaborative tools.The key lesson is that increased staffing and planning is neededto prepare and successfully run remote A-Team studies. RemoteA-Team studies require careful selection of the appropriatetools for security, accessibility, and usability within theNASA/JPL environment. Knowledge capture methods andtemplates need to be thought out and agreed upon in advance asthere is less room for improvising in a remote format. Variouscommunication channels have to be monitored to allow for teamcoordination while maintaining fruitful participant engagementduring a session. In addition, technical backup for all roleswithin the A-Team have to be identified to allow the study tocontinue even if a team member’s connectivity is temporarilyinterrupted. Finally, careful thought has to be put into methodsand processes to create a collaborative environment in a virtualspace such that a group of experts who are only connected viathe internet can experience the creative spark and flow of a greatcollaborative and innovative study.

Zusack, Steven↗
NASA NTRSDate not supplied

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗
NASA NTRSDate not supplied

Utilizing Gaps and Key Performance Parameters to Inform NASA Environmental Control and Life Support and Human Health and Performance Capability Technology Decisions

Human spaceflight is a complex endeavor requiring a multitude of capabilities for transportation, crew health, scientific goals, and safe return to Earth. The difference between spaceflight proven capabilities and those needed for a particular mission is defined as a capability gap. Capability gaps are not technology specific. Each capability gap is approachable with a wide array of technologies that have unique benefits and challenges. Determining what a capability’s relevant and distinguishing key performance parameters (KPPs) are for a mission is critical. Mass, power, and volume are always constrained and important, but defining these in a way normalized by performance is challenging. Additionally, KPP definition for reliability, dormancy, and integration needs are very important and still evolving. This paper provides the approach of the Environmental Control and Life Support – Crew Health and Performance (ECLSS-CHP) System Capability Leadership Team (SCLT) to defining gaps and KPPs in support of the NASA’s Capabilities Integration Team data call objectives. The nine ECLSS-CHP capability areas are decomposed to capabilities, gaps, and KPPs. Rather than defining very detailed gaps, ECLSS-CHP defines high-level gaps to be technology agnostic. Within a gap, detailed KPPs are defined to both compare technologies and measure progress within a technology over time. Ideally, KPPs are clearly defined, widely communicated both internally and externally, and provide a common nomenclature to describe the state of the art and the degree of improvement required for exploration missions. KPPs help define when the gap is closed and the core mission objectives can be accomplished. Further technology improvements to enhance the capability, as measured by improved KPPs, must then be weighed against investments in open capability gaps that prevent NASA from achieving its exploration missions. It is uncommon that a technology maturation to improve all the relevant KPPs simultaneously but using KPPs is a critical technology investment decision making component. In addition to traditional technology selections, KPPs are informing how investments in ground testing prior to and in parallel with ISS technology demonstrations are required to improve reliability KPPs. The collection of all major technology activities within a capability area are captured on technology roadmaps to communicate how diverse program activities are coordinated to close gaps and infuse into exploration mission needs. A selection of ECLSS-CHP gaps and KPPs and their formulation, current state, and how they inform capability roadmap planning are discussed. The paper will contain a summary of the approximately 60 gaps. Gaps are classified as to their type (architecture, knowledge, technology, developmental, or engineering) depending on the magnitude of the gap. The paper will provide brief overviews of a few major technology challenges and the technologies being considered, but will reference detailed papers for a more thorough treatment of the challenges and state of the art. Data analysis of the gaps is in work and results are not currently available for this abstract. It is anticipated the paper will include examples of select KPPs with descriptions as to why these are the relevant measures. Additionally some KPPs will be graphically presented over time to show progress to date and when performance targets need to be achieved to support exploration missions. Graphical summaries of how gaps closures with near term mission elements support follow-on mission elements will be provided.

Life Support↗
NASA NTRSDate not supplied

Utilizing Gaps and Key Performance Parameters to Inform NASA Environmental Control and Life Support and Human Health and Performance Capability Technology Decisions

Human spaceflight is a complex endeavor requiring multiple capabilities for transportation, crew health, scientific goals, and safe return to Earth. The difference between spaceflight proven capabilities and those needed for future exploration architectures is defined as a capability gap. Capability gaps are not technology specific. Each capability gap is approachable with a wide array of technologies that have unique benefits and challenges. Determining what a capability’s relevant and distinguishing key performance parameters (KPPs) are for a mission is critical. Mass, power, and volume are always constrained and important, but defining these in a way normalized by performance is challenging. Additionally, KPP definition for reliability, dormancy, and integration needs are very important and still evolving. This paper provides the approach of the Environmental Control and Life Support – Crew Health and Performance (ECLSS-CHP) System Capability Leadership Team (SCLT) has used to define gaps and KPPs in support of the NASA’s Capabilities Integration Team data call objectives. The nine ECLSS-CHP capability areas are decomposed to capabilities with ~76 gaps and supported with KPPs. Rather than defining very detailed gaps, ECLSS-CHP defines high-level gaps to be technology agnostic. Within a gap, detailed KPPs are defined to both compare technologies and measure progress within a technology over time. Ideally, KPPs are clearly defined, widely communicated both internally and externally, and provide a common nomenclature to describe the state of the art and the degree of improvement required for exploration missions. KPPs help define when the gap is closed, and the core mission objectives can be accomplished. Further technology improvements to enhance the capability, as measured by improved KPPs, must then be weighed against investments in open capability gaps that prevent NASA from achieving its exploration missions. It is uncommon that a technology maturation to improve all the relevant KPPs simultaneously but using KPPs is a critical technology investment decision making component. In addition to traditional technology selections, KPPs are informing how investments in ground testing prior to and in parallel with ISS technology demonstrations are required to improve reliability KPPs. The collection of all major technology activities within a capability area are captured on technology roadmaps to communicate how diverse program activities are coordinated to close gaps and infuse into exploration mission needs. A selection of ECLSS-CHP gaps and KPPs and their formulation, current state, and how they inform capability roadmap planning are discussed.

Life Support↗
NASA NTRS1971

Neutron capture on Sm-149 in lunar samples.

High precision isotopic composition measurements of Sm have been carried out for two terrestrial and seven lunar samples from three Apollo sites. The lunar samples, selected to show a wide variation in cosmic ray exposure ages, have a wide range of enrichments in Sm-150/Sm-154 (up to 0.8%) and depletions in Sm-149/Sm-154 which are due to neutron capture. The ratio of the number of neutrons captured per atom by Sm-149 to Gd-157 is 0.9 and reflects a hardened lunar neutron spectrum. This ratio is in reasonable but not exact agreement with that obtained from the theoretical lunar neutron energy spectrum of Lingenfelter, Canfield and Hampel. The average composition for terrestrial samarium is given.

Russ, G. P., III↗
NASA NTRS2016

Storage of Physical Sample Metadata in the Astrobiology Habitable Environments Database (AHED)

The National Aeronautics and Space Administration has begun an effort to store, curate, and publish information about physical samples collected and analyzed in conjunction with NASA-funded astrobiology research. Astrobiology is a multidisciplinary area of scientific research being conducted by collaborating teams of biologists, chemists, geologists, atmospheric scientists, oceanographers, astrophysicists, astronomers, and other specialists. Astrobiology studies the origin, evolution, and distribution of life in the Universe. NASA uses the results of astrobiology research to focus its future missions on targets of opportunity for the discovery of life off Earth. Astrobiology researchers conduct both field-based and laboratory-based research, during which physical samples are collected, processed, and catalogued. The cataloguing practices employed by different teams of astrobiologists vary widely, and there are no specific standards available to guide the collection and recording of astrobiology sample data. The disparity in data collection approaches and the lack of a centralized sample repository makes it difficult for astrobiology teams to share data and benefit from resultant synergies.To facilitate data sharing within the astrobiology community, NASA is developing a prototype database the Astrobiology Habitable Environments Database (AHED) and an associated set of data collection templates. The database will store information about samples, along with associated measurements and analyses, including information about biological cultures enriched or isolated from samples, and the results of analyses performed on the samples (e.g., via spectrography, microscopy, etc.). In addition, the system will store contextual information about field sites where samples were collected, the instruments or equipment used for analysis, and people and institutions involved in their collection. AHED is being implemented on top of Open Data Repository's Data Publisher [1], an open source software platform for the publication of scientific datasets. The data collection templates under development represent an initial attempt to propose a set of metadata for capture and storage within AHED. The design of these templates is being conducted by a consolidated group of astrobiologists from active research teams at NASA Ames Research Center, assisted by data science and software engineering specialists. These initial templates must be vetted with the broader astrobiology community through a defined process to ensure that they meet community needs. Each template captures a different type of data collection record. For each template, we are developing a list of fields to be captured, including a set of required entry fields, a set of recommended but optional fields, and a set of discretionary fields. A datatype selected from a variety of text and numeric types is specified for each field. Included is a 'choice' type that restricts user input to an enumerated list of values. Many of the fields and field values capture information of particular interest to the astrobiology community, and are intended to facilitate search and retrieval of relevant data across multiple datasets.

Keller, Rich↗
NASA NTRS2012

Postures and Motions Library Development for Verification of Ground Crew Human Systems Integration Requirements

Spacecraft and launch vehicle ground processing activities require a variety of unique human activities. These activities are being documented in a Primitive motion capture library. The Library will be used by the human factors engineering in the future to infuse real to life human activities into the CAD models to verify ground systems human factors requirements. As the Primitive models are being developed for the library the project has selected several current human factors issues to be addressed for the SLS and Orion launch systems. This paper explains how the Motion Capture of unique ground systems activities are being used to verify the human factors analysis requirements for ground system used to process the STS and Orion vehicles, and how the primitive models will be applied to future spacecraft and launch vehicle processing.

Jackson, Mariea Dunn↗
NASA NTRS1991

SIMS analysis of extended impact features on LDEF experiment

Discussed here are the first Secondary Ion Mass Spectroscopy (SIMS) analysis of projectile material deposited in extended impact features on Ge wafers from the trailing edge. Although most capture cells lost their plastic film covers, they contain extended impact features that apparently were produced by high velocity impacts when the plastic foils were still intact. Detailed optical scanning of all bare capture cells from the trailing edge revealed more than 100 impacts. Fifty-eight were selected by scanning electron microscope (SEM) inspection as prime candidates for SIMS analysis. Preliminary SIMS measurements were made on 15 impacts. More than half showed substantial enhancements of Mg, Al, Si, Ca, and Fe in the impact region, indicating micrometeorites as the projectiles.

Amari, S.↗
NASA NTRS2010

Omniview motionless camera orientation system

An apparatus and method is provided for converting digital images for use in an imaging system. The apparatus includes a data memory which stores digital data representing an image having a circular or spherical field of view such as an image captured by a fish-eye lens, a control input for receiving a signal for selecting a portion of the image, and a converter responsive to the control input for converting digital data corresponding to the selected portion into digital data representing a planar image for subsequent display. Various methods include the steps of storing digital data representing an image having a circular or spherical field of view, selecting a portion of the image, and converting the stored digital data corresponding to the selected portion into digital data representing a planar image for subsequent display. In various embodiments, the data converter and data conversion step may use an orthogonal set of transformation algorithms.

Martin, H. Lee↗
NASA NTRS2023

A Summary of the Development and Validation of the Scale for Habitat Usability (SHU)

Usability is an important concept to consider when designing space habitats/vehicles. In addition to objective outcomes (success rate, net habitable volume etc.), collecting users’ subjective judgments via comments and questionnaires can provide valuable data for evaluating conceptual designs, identifying potential layout issues, improving concept of operations, substantiating design changes, or selecting between competing mockups. Historically at NASA, there has been no “gold standard” questionnaire for capturing users’ subjective viewpoint regarding habitat design. To address this gap a Human Research Program (HRP) study was conducted to create a new measurement tool: the Scale for Habitat Usability (SHU).

Usability↗
NASA NTRS2013

Postures and Motions Library Development for Verification of Ground Crew Human Factors Requirements

Spacecraft and launch vehicle ground processing activities require a variety of unique human activities. These activities are being documented in a primitive motion capture library. The library will be used by human factors engineering analysts to infuse real to life human activities into the CAD models to verify ground systems human factors requirements. As the primitive models are being developed for the library, the project has selected several current human factors issues to be addressed for the Space Launch System (SLS) and Orion launch systems. This paper explains how the motion capture of unique ground systems activities is being used to verify the human factors engineering requirements for ground systems used to process the SLS and Orion vehicles, and how the primitive models will be applied to future spacecraft and launch vehicle processing.

Stambolian, Damon↗
NASA NTRS1986

Low-speed performance of an axisymmetric, mixed-compression, supersonic inlet with auxiliary inlets

A test program was conducted to determine the aerodynamic performance and acoustic characteristics associated with the low-speed operation of a supersonic, axisymmetric, mixed-compression inlet with auxiliary inlets. Blow-in-auxiliary doors were installed on the NASA Ames P inlet. One door per quadrant was located on the cowl in the subsonic diffuser selection of the inlet. Auxiliary inlets with areas of 20 and 40 percent of the inlet capture area were tested statically and at free-stream Mach numbers of 0.1 and 0.2. The effects of boundary layer bleed inflow were investigated. A JT8D fan simulator driven by compressed air was used to pump inlet flow and to provide a characteristic noise signature. Baseline data were obtained at static free-stream conditions with the sharp P-inlet cowl lip replaced by a blunt lip. Auxiliary inlets increased overall total pressure recovery of the order of 10 percent.

Trefny, C. J.↗
NASA NTRS1993

Measurements of atmospheric carbonyl sulfide during the NASA Chemical Instrumentation Test and Evaluation Project: Implications for the global COS budget

Atmospheric carbonyl sulfide COS concentrations were measured by three analytical systems during the Chemical Instrumentation Test and Evaluation (CITE 3) project. The three systems all used cryogenic sample preconcentration and gas chromatographic (GC) separation but differed in the method of detection. The FPD system used a flame photometric detector, the MS system used a mass selective detector, and the ECD-S system used a fluorinating catalyst followed by an electron capture detector. With the FPD system, we found a mean COS concentration of 510 ppt over the North Atlantic and 442 ppt over the Tropical Atlantic. With the ECD-S system, we found a mean COS concentration of 489 ppt over the North Atlantic and 419 ppt over the Tropical Atlantic. All three systems registered a latitudinal gradient in atmospheric COS of between 1.6 and 2.0 ppt per degree of latitude, with increasing COS concentrations northward which was similar to the gradient measured by Bingemer et al. (1990). It is difficult to reconcile the measured latitudinal concentration gradient with present theories of the global COS budget since the largest sink of COS is thought to be a flux to land plants, most of which are in the northern hemisphere.

Johnson, James E.↗
NASA NTRS2014

Wing Configuration Impact on Design Optimums for a Subsonic Passenger Transport

This study sought to compare four aircraft wing configurations at a conceptual level using a multi-disciplinary optimization (MDO) process. The MDO framework used was created by Georgia Institute of Technology and Virginia Polytechnic Institute and State University. They created a multi-disciplinary design and optimization environment that could capture the unique features of the truss-braced wing (TBW) configuration. The four wing configurations selected for the study were a low wing cantilever installation, a high wing cantilever, a strut-braced wing, and a single jury TBW. The mission that was used for this study was a 160 passenger transport aircraft with a design range of 2,875 nautical miles at the design payload, flown at a cruise Mach number of 0.78. This paper includes discussion and optimization results for multiple design objectives. Five design objectives were chosen to illustrate the impact of selected objective on the optimization result: minimum takeoff gross weight (TOGW), minimum operating empty weight, minimum block fuel weight, maximum start of cruise lift-to-drag ratio, and minimum start of cruise drag coefficient. The results show that the design objective selected will impact the characteristics of the optimized aircraft. Although minimum life cycle cost was not one of the objectives, TOGW is often used as a proxy for life cycle cost. The low wing cantilever had the lowest TOGW followed by the strut-braced wing.

Wells, Douglas P.↗