Relevant bibliographies by topics / Flush air data sensing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Flush air data sensing'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Flush air data sensing"

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Shyam Mohan, N., M. Jayakumar, T. Sivamurugan, K. C. Finitha, S. B. Vidya, Jayanta Dhoaya, N. Remesh, M. Prasath, Shashi Krishna, and Aisha Sidhique. "Flush Air Data Sensing System." Current Science 114, no. 01 (January 10, 2018): 68. http://dx.doi.org/10.18520/cs/v114/i01/68-73.

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Srivastava, Ankur, Andrew J. Meade, and Kurtis R. Long. "Learning Air-Data Parameters for Flush Air Data Sensing Systems." Journal of Aerospace Computing, Information, and Communication 9, no. 3 (November 2012): 110–24. http://dx.doi.org/10.2514/1.54947.

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Zhan, Ye, Li Ming Chang, Jun Li, and Ming Shu Jiao. "Study on Flush Air Data Sensing Technology." Advanced Materials Research 962-965 (June 2014): 2766–69. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.2766.

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Accurate measurement of atmospheric data is important for the control and navigation of aircraft. With the development of Aerospace Technology, the traditional probe air data sensing system has been could not meet the requirements of advanced flight. For this problem, the flush air data sensing system (FADS) has been proposed. The paper listed and compared some FADS algorithms and summarizes the characteristics and using conditions of several algorithm based on introducing the FADS measuring principle and compositions.
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ZHOU, WeiJiang, GuoHui DOU, XiuXin DOU, WuYue LIU, and GuangQiang CHEN. "Flush air data sensing system design for air breathing air-to-air missile." SCIENTIA SINICA Technologica 46, no. 11 (October 28, 2016): 1193–206. http://dx.doi.org/10.1360/n092016-00258.

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Rohloff, Thomas J., Stephen A. Whitmore, and Ivan Catton. "Fault-Tolerant Neural Network Algorithm for Flush Air Data Sensing." Journal of Aircraft 36, no. 3 (May 1999): 541–49. http://dx.doi.org/10.2514/2.2489.

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KUNISHIGE, Tatsuki, Koichi YONAMOTO, Takahiro FUJIKAWA, Guna Surendra GOSSAMSETTI, and Daisuke MORIYAMA. "Analysis on Singularity in Flush-Type Air Data Sensing Algorithm." Proceedings of Conference of Kyushu Branch 2018.71 (2018): J35. http://dx.doi.org/10.1299/jsmekyushu.2018.71.j35.

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Chen, Guangqiang, Bingyan Chen, Pengfei Li, Peng Bai, and Chunqun Ji. "Study on Algorithms of Flush Air Data Sensing System for HypersonicVehicle." Procedia Engineering 99 (2015): 860–65. http://dx.doi.org/10.1016/j.proeng.2014.12.613.

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Gao, Qinghua, Zhengguang Shen, Jingyu Dong, and Jingchun Yuan. "Faults Self-detection of Self-validating Flush Air Data Sensing System." International Journal of Control and Automation 10, no. 3 (March 31, 2017): 227–40. http://dx.doi.org/10.14257/ijca.2017.10.3.19.

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Samy, Ihab, Ian Postlethwaite, Da-Wei Gu, and John Green. "Neural-Network-Based Flush Air Data Sensing System Demonstrated on a Mini Air Vehicle." Journal of Aircraft 47, no. 1 (January 2010): 18–31. http://dx.doi.org/10.2514/1.44157.

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Ding, Zhijian, Huan Zhou, Feng Wang, Dongsheng Wu, Yingchuan Wu, and Yuanyuan He. "An implementation of the cubature Kalman filter for estimating trajectory parameters and air data of a hypersonic vehicle." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 12 (April 3, 2019): 4554–70. http://dx.doi.org/10.1177/0954410019835977.

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Trajectory parameters (including the position, velocity, and attitude angles of a vehicle) and air data (consisting of the flow angles, the Mach number, and the freestream static pressure) are vital data for the analysis and evaluation process in the hypersonic flight tests. This paper describes a data fusion estimation algorithm for a flush air data sensing system/inertial navigation system/global positioning system integrated system, which is used to estimate the trajectory parameters and air data for an unpowered hypersonic vehicle. In the approach, the raw outputs of flush air data sensing system (i.e. the surface pressure measurements) are integrated with global positioning system results (the vehicle’s position and velocity) and inertial navigation system measurements (including the acceleration and the angular velocity measurements) by using a nonlinear Kalman filter algorithm. Firstly, the system state vector is defined with the trajectory parameters, the biases of the inertial sensors and the winds. Then, the system dynamic models are built based on the motion equations of an unpowered hypersonic vehicle, the inertial sensor error models and the wind model. Besides, the system measurement vector is designed with the global positioning system results and the flush air data sensing system raw outputs. Based on these works, the system state is directly estimated by using the cubature Kalman filter algorithm. After that, the air data is calculated based on the estimated values and a high-fidelity model of atmosphere. Simulation cases are implemented to assess the performance of the proposed algorithm. The results show that the proposed method could estimate the trajectory parameters and air data for hypersonic vehicle with a high precision.
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Dissertations / Theses on the topic "Flush air data sensing"

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Black, Richard Allyn. "A flush mounted microelectromechanical system (MEMS) pressure and flow sensor based air data system /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/10012.

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Shollenberger, Tara Krystyna. "Statistical Entry, Descent, and Landing Flight Reconstruction with Flush Air Data System Observations using Inertial Navigation and Monte Carlo Techniques." Thesis, North Carolina State University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3584009.

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Research suggests what leaders should do or the qualities or characteristics they should have to be ethical leaders (Brown & Treviño, 2006). The ethical decision-making process that leaders should follow to avoid scandals and unethical behavior are overlooked. Few studies focused on ethical decision-making within higher education. Yet, educational leaders have an ethical responsibility that may be even more complex than those of other leaders due in part to increasingly diverse student populations enrolled in higher education that is having an impact on the growth of educational institutions on a global basis (Shapiro & Stekfovich, 2011). Further, ethical scandals are no longer contained by national borders. The rapid growth of technology coupled with changes in political and societal landscapes has advanced ethical scandals to global prominence. A more collective need to understand ethical values and ethical decision-making practices on a global level has emerged. To be globally effective, leaders must be aware of the similarities and differences across and within cultures that could influence business practices (Resick, Hanges, Dickson, & Mitchelson, 2006). However, cross-cultural research has not yet addressed the topic of ethical decision-making. In this study, the ethical decision-making process of higher education was not only examined in the United Stated but also in Poland. This exploratory study used the Delphi research technique to identify an ethical decision-making definition that higher administration leaders in both the United States and Poland use to make ethical decisions and identify the environmental factors that influence their decisions. Findings showed that the United States and Polish expert panels were different and showed very little in common in the identification of a definition and environmental factors. Lastly, both sets of experts identified a new process for ethical decision-making, each constructing a different ethical decision-making process model. This research on ethical decision-making provided evidence that the Polish and United States cultures are not as similar as identified in previous studies in terms of how they identify ethical decision-making and the factors they identify with influencing ethical decision-making. Using this information will create a better understanding of the practices and approaches to ethics that leaders use because of the huge influence they have and exert on people within their own organization and society around them.

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Lugo, Rafael Andres. "Statistical Entry, Descent, and Landing Flight Reconstruction with Flush Air Data System Observations using Inertial Navigation and Monte Carlo Techniques." Thesis, North Carolina State University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3584008.

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A method is introduced to consider flush air data system (FADS) pressures using a technique based on inertial navigation to reconstruct the trajectory of an atmospheric entry vehicle. The approach augments the recently-developed Inertial Navigation Statistical Trajectory and Atmosphere Reconstruction (INSTAR), which is an extension of inertial navigation that provides statistical uncertainties by utilizing Monte Carlo dispersion techniques and is an alternative to traditional statistical approaches to entry, descent, and landing trajectory and atmosphere reconstruction.

The method is demonstrated using flight data from the Mars Science Laboratory (MSL) entry vehicle, which contained an inertial measurement unit and a flush air data system called the Mars Entry Atmospheric Data System (MEADS). An MSL trajectory and atmosphere solution that was updated using landing site location in INSTAR is first presented. This solution and corresponding uncertainties, which were obtained from Monte Carlo dispersions, are then used in a minimum variance algorithm to obtain aerodynamic estimates and uncertainties from the MEADS observations. MEADS-derived axial force coefficient and freestream density estimates and uncertainties are also derived from the minimum variance solutions independent of the axial force coefficients derived from computation fluid dynamics (CFD), which have relatively high a priori uncertainty. Results from probabilistic analyses of the solutions are also presented.

This dissertation also introduces a method to consider correlated CFD uncertainties in INSTAR. From a priori CFD uncertainties, CFD force and pressure coefficients are dispersed in a Monte Carlo sense and carried over into the reconstructions. An analysis of the subsequent effects on the trajectory, atmosphere, and aerodynamic estimates and statistics is presented.

Trajectory, atmospheric, and aerodynamic estimates compare favorably to extended Kalman filter solutions obtained by the MSL reconstruction team at NASA Langley Research Center. The uncertainties obtained through the methods from this work are generally smaller in magnitude because of assumptions made regarding sources of error in the MEADS pressure transducer uncertainties. Using data-derived uncertainties in the pressure measurement noise covariance results in aerodynamic parameter estimate uncertainties that are in better agreement with the uncertainties derived from the Monte Carlo dispersions. CFD database errors dominate the uncertainties of parameters derived from aerodatabase axial force coefficients.

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Nergis, Damirag Melodi. "Web Based Cloud Interaction and Visualization of Air Pollution Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254401.

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According to World Health Organization, around 7 million people die every year due to diseases caused by air pollution. With the improvements in Internet of Things in the recent years, environmental sensing systems has started to gain importance. By using technologies like Cloud Computing, RFID, Wireless Sensor Networks, and open Application Programming Interfaces, it has become easier to collect data for visualization on different platforms. However, collected data need to be represented in an efficient way for better understanding and analysis, which requires design of data visualization tools. The GreenIoT initiative aims to provide open data with its infrastructure for sustainable city development in Uppsala. An environmental web application is presented within this thesis project, which visualizes the gathered environmental data to help municipality organizations to implement new policies for sustainable urban planning, and citizens to gain more knowledge to take sustainable decisions in their daily life. The application has been developed making use of the 4Dialog API, which is developed to provide data from a dedicated cloud storage for visualization purposes. According to the evaluation presented in this thesis, further development is needed to improve the performance to provide faster and more reliable service as well as the accessibility to promote openness and social inclusion.
Enligt World Health Organization dör 7 miljoner människor varje år på grund av sjukdomar orsakade av luftföroreningar. Med förbättringar inom Internet of Things under senare år, har betydelsen av system för miljösensorer. Genom att använda tekniker som molntjänster, RFID, trådlösa sensornätverk och öppna programmeringsgränssnitt, har det blivit enklare att samla in data för visualisering på olika plattformar. Men insamlad data behöver bli representerad på ett effektivt sätt för bättre förståelse och analys, vilket kräver utformande av verktyg för visualisering av data. Initiativet GreenIoT strävar mot att erbjuda öppen data med sin infrastruktur för hållbar stadsutveckling i Uppsala. I detta arbete presenteras en webb-tillämpning, som visualiserar den insamlade miljödatan för att hjälpa kommunen att implementera nya policies för hållbar stadsutveckling, och stimulera medborgare till att skaffa mer kunskap för att göra miljövänliga val i sin vardag. Tillämpningen har utvecklats med hjälp av 4Dialog API, som tillhandahåller data från lagring i molnet för visualiseringssyfte. Enligt den utvärdering som presenteras i denna rapport konstateras att vidare utveckling behövs för att förbättra dels prestanda för att erbjuda en snabbare och mer tillförlitlig service, och dels åtkomstmöjligheter för att främja öppenhet och social inkludering.
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Alcantara, Lehi Sttenio. "Deploying and Analyzing Air Quality Sensors in Mongolian Gers." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/8908.

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The purpose of this research is to develop best practices for deploying air quality sensors in a remote location such as Mongolia. I discussed the architecture and design constraints when collecting remote air quality sensors data, the challenges that emerge while implementing a sensor-based network in a remote location such as Mongolia. The tradeoffs of using different architectures are described. I observed the usage of electrical heaters in modified gers in remote locations and conclude how effective they are in reducing PM2.5 levels by analyzing air quality data and go through the process of cleaning up the data and removing humidity from low-cost sensors used to deploy in a remote location such as Mongolia so that the PM2.5 reading is more accurate. In order to help many humanitarian efforts dealing with better air quality in developing countries, an air quality sensor was designed to keep low cost as much as possible. The cost is about $200 to build, which is cheaper than other low-cost sensors, yet provides more functionality (e.g., CO2 sensing) and used cellular connectivity to upload data in real-time. This sensor has implications beyond Mongolia. The sensor can be used anywhere WiFi connectivity is not available, such as parks, bus stops, and along roadways, breaking the constraints that other low-cost sensors have. Removing the need for WiFi is a necessary step in allowing ubiquitous air quality sensing. The contributions in this thesis are: First, I presented the challenges one should consider while deploying air quality sensors in developing countries. Second, since Mongolia offers a unique environment and constraints, I shared experiences in deploying sensors in a remote location like Mongolia. This experience goes beyond air quality sensors and can inform anyone who is deploying sensors in remote areas. Third the analysis of the PM2.5 on the gers gives us better insights as to whether modifying gers with insulation and using electrical heaters as opposed to burning coal to heat up the gers makes a difference in regard to better air quality in the gers.
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Kaynak, Burcak. "Assimilation of trace gas retrievals obtained from satellite (SCIAMACHY), aircraft and ground observations into a regional scale air quality model (CMAQ-DDM/3D)." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/37134.

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A major opportunity for using satellite observations of tropospheric chemical concentrations is to improve our scientific understanding of atmospheric processes by integrated analysis of satellite, aircraft, and ground-based observations with global and regional scale models. One endpoint of such efforts is to reduce modeling biases and uncertainties. The idea of coupling these observations with a regional scale air quality model was the starting point of this research. The overall objective of this research was to improve the NOₓ emission inventories by integrating observations from different platforms and regional air quality modeling. Specific objectives were: 1) Comparison of satellite NO₂ retrievals with simulated NO₂ by the regional air quality model. Comparison of simulated tropospheric gas concentrations simulated by the regional air quality model, with aircraft and ground-based observations; 3) Assessment of the uncertainties in comparing satellite NO₂ retrievals with NOₓ emissions estimates and model simulations; 4) Identification of biases in emission inventories by data assimilation of satellite NO₂ retrievals, and ground-based NO, NO₂ and O₃ observations with an iterative inverse method using the regional air quality model coupled with sensitivity calculations; 5) Improvement of our understanding of NOₓ emissions, and the interaction between regional and global air pollution by an integrated analysis of satellite NO₂ retrievals with the regional air quality model. Along with these objectives, a lightning NOₓ emission inventory was prepared for two months of summer 2004 to account for a significant upper level NOₓ source. Spatially-resolved weekly NO₂ variations from satellite retrievals were compared with estimated NOₓ emissions for different region types. Data assimilation of satellite NO₂ retrievals, and ground-based NO, NO₂ and O₃ observations were performed to evaluate the NOₓ emission inventory. This research contributes to a better understanding of the use of satellite NO₂ retrievals in air quality modeling, and improvements in the NOₓ emission inventories by correcting some of the inconsistencies that were found in the inventories. Therefore, it may provide groups that develop emissions estimates guidance on areas for improvement. In addition, this research indicates the weaknesses and the strengths of the satellite NO₂ retrievals and offers suggestions to improve the quality of the retrievals for further use in the tropospheric air pollution research.
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Fraczek, Michael Darius [Verfasser], and Volker [Akademischer Betreuer] Wulfmeyer. "Aircraft air data system based on the measurement of Raman and elastic backscatter via active optical remote-sensing / Michael Darius Fraczek. Betreuer: Volker Wulfmeyer." Hohenheim : Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim, 2014. http://d-nb.info/1048384799/34.

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Fraczek, Michael [Verfasser], and Volker [Akademischer Betreuer] Wulfmeyer. "Aircraft air data system based on the measurement of Raman and elastic backscatter via active optical remote-sensing / Michael Darius Fraczek. Betreuer: Volker Wulfmeyer." Hohenheim : Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:100-opus-9650.

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Aval, Josselin. "Automatic mapping of urban tree species based on multi-source remotely sensed data." Thesis, Toulouse, ISAE, 2018. http://www.theses.fr/2018ESAE0021/document.

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Avec l'expansion des zones urbaines, la pollution de l'air et l'effet d'îlot de chaleur augmentent, entraînant des problèmes de santé pour les habitants et des changements climatiques mondiaux. Dans ce contexte, les arbres urbains sont une ressource précieuse pour améliorer la qualité de l'air et promouvoir les îlot de fraîcheur. D'autre part, les canopées sont soumises à des conditions spécifiques dans l'environnement urbain, causant la propagation de maladies et la diminution de l'espérance de vie parmi les arbres. Cette thèse explore le potentiel de la télédétection pour la cartographie automatique des arbres urbains, de la détection des couronnes d'arbres à l'estimation des espèces, une tâche préliminaire essentielle pour la conception des futures villes vertes, et pour une surveillance efficace de la végétation. Fondé sur des données hyperspectrales aéroportées, panchromatiques et un modèle numérique de surface, le premier objectif de cette thèse consiste à tirer parti de plusieurs sources de données pour améliorer les cartes d'arbres urbains existants, en testant différentes stratégies de fusion (fusion de caractéristiques et fusion de décision). La nature des résultats nous a conduit à optimiser la complémentarité des sources. En particulier, le deuxième objectif est d'étudier en profondeur la richesse des données hyperspectrales, en développant une approche d'ensemble classifier fondée sur des indices de végétation, où les "classifier" sont spécifiques aux espèces. Enfin, la première partie a mis en évidence l'intérêt de distinguer les arbres de rue des autres structures d'arbres urbains. Dans un cadre de Marked Point Process, le troisième objectif est de détecter les arbres en alignement urbain. Par le premier objectif, cette thèse démontre que les données hyperspectrales sont le principal moteur de la précision de la prédiction des espèces. La stratégie de fusion au niveau de décision est la plus appropriée pour améliorer la performance en comparaison des données hyperspectrales seules, mais de légères améliorations sont obtenues (quelques %) en raison de la faible complémentarité des caractéristiques texturales et structurelles en plus des caractéristiques spectrales. L'approche d'ensemble classifier développée dans la deuxième partie permet de classer les espèces d'arbres à partir de références au sol, avec des améliorations significatives par rapport à une approche standard de classification au niveau des caractéristiques. Chaque classifieur d'espèces extrait reflète les attributs spectraux discriminants de l'espèce et peut être relié à l'expertise des botanistes. Enfin, les arbres de rue peuvent être cartographiés grâce au terme d'interaction des MPP proposé qui modélise leurs caractéristiques contextuelles (alignement et hauteurs similaires). De nombreuses améliorations doivent être explorées comme la délimitation plus précise de la couronne de l'arbre, et plusieurs perspectives sont envisageables après cette thèse, parmi lesquelles le suivi de l'état de santé des arbres urbains
With the expansion of urban areas, air pollution and heat island effect are increasing, leading to state of health issues for the inhabitants and global climate changes. In this context, urban trees are a valuable resource for both improving air quality and promoting freshness islands. On the other hand, canopies are subject to specific conditions in the urban environment, causing the spread of diseases and life expectancy decreases among the trees. This thesis explores the potential of remote sensing for the automatic urban tree mapping, from the detection of the individual tree crowns to their species estimation, an essential preliminary task for designing the future green cities, and for an effective vegetation monitoring. Based on airborne hyperspectral, panchromatic and Digital Surface Model data, the first objective of this thesis consists in taking advantage of several data sources for improving the existing urban tree maps, by testing different fusion strategies (feature and decision level fusion). The nature of the results led us to optimize the complementarity of the sources. In particular, the second objective is to investigate deeply the richness of the hyperspectral data, by developing an ensemble classifiers approach based on vegetation indices, where the classifiers are species specific. Finally, the first part highlighted to interest of discriminating the street trees from the other structures of urban trees. In a Marked Point Process framework, the third objective is to detect trees in urban alignment. Through the first objective, this thesis demonstrates that the hyperspectral data are the main driver of the species prediction accuracy. The decision level fusion strategy is the most appropriate one for improving the performance in comparison the hyperspectral data alone, but slight improvements are obtained (a few percent) due to the low complementarity of textural and structural features in addition to the spectral ones. The ensemble classifiers approach developed in the second part allows the tree species to be classified from ground-based references, with significant improvements in comparison to a standard feature level classification approach. Each extracted species classifier reflects the discriminative spectral attributes of the species and can be related to the expertise of botanists. Finally, the street trees can be mapped thanks to the proposed MPP interaction term which models their contextual features (alignment and similar heights). Many improvements have to be explored such as the more accurate tree crown delineation, and several perspectives are conceivable after this thesis, among which the state of health monitoring of the urban trees
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POZZETTI, LUCILA M. V. "Criação de um banco de dados dinâmico e análise de medições LIDAR em formato WEB do Laboratório de Aplicações Ambientais a Laser do Instituto de Pesquisas Energéticas e Nucleares." reponame:Repositório Institucional do IPEN, 2006. http://repositorio.ipen.br:8080/xmlui/handle/123456789/11405.

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Books on the topic "Flush air data sensing"

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Larson, Terry J. Wind-tunnel investigation of a flush airdata system at Mach numbers from 0.7 to 1.4. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1990.

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Strub, Richard. BOREAS level-0 ER-2 navigation data. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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J, Davis Roy, Fife John Michael, and Hugh L. Dryden Flight Research Center., eds. In-flight demonstration of a Real-Time Flush Airdata Sensing (RT-FADS) system. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1995.

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J, Davis Roy, Fife John Michael, and Hugh A. Dryden Flight Research Center., eds. In-flight demonstration of a Real-Time Flush Airdata Sensing (RT-FADS) system. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1995.

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J, Davis Roy, Fife John Michael, and Hugh A. Dryden Flight Research Center., eds. In-flight demonstration of a Real-Time Flush Airdata Sensing (RT-FADS) system. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1995.

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R, Cobleigh Brent, Haering Edward A, and NASA Dryden Flight Research Center., eds. Design and calibration of the X-33 flush airdata sensing (FADS) system. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1998.

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Qualitative evaluation of a flush air data system at transonic speeds and high angles of attack. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1987.

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Wind-tunnel investigation of a flush airdata system at Mach numbers from 0.7 to 1.4. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1990.

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R, Moes Timothy, Siemers Paul M, and Dryden Flight Research Facility, eds. Wind-tunnel investigation of a flush airdata system at Mach numbers from 0.7 to 1.4. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1990.

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Roseanne, Dominguez, Newcomer J, and Goddard Space Flight Center, eds. BOREAS level-0 ER-2 navigation data. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Book chapters on the topic "Flush air data sensing"

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Chen, Guangqiang, Xiuxin Dou, Guohui Dou, Weijiang Zhou, and Yunjun Yang. "Flush Air Data Sensing System Design and Test for Supersonic Vehicle." In Lecture Notes in Electrical Engineering, 74–81. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3305-7_6.

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Gabrys, Jennifer. "Sensing air, creaturing data." In Data Publics, 116–27. London ; New York : Routledge, 2020. | Series: Routledge research in design, technology and society ; volume 2: Routledge, 2020. http://dx.doi.org/10.4324/9780429196515-8.

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Erener, Arzu, Gülcan Sarp, and Özge Yıldırım. "Seasonal Air Pollution Investigation and Relation Analysis of Air Pollution Parameters to Meteorological Data (Kocaeli/Turkey)." In Advances in Remote Sensing and Geo Informatics Applications, 355–58. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01440-7_78.

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Usharani, Bhimavarapu, and M. Sreedevi. "Deep Learning Techniques for Air Pollution Prediction Using Remote Sensing Data." In Smart Technologies in Data Science and Communication, 107–23. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1773-7_9.

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Bode, C., Th Eggers, and M. Smart. "Numerical Generation of a Flush Air Data System for the Hypersonic Flight Experiment HIFiRE 7." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 101–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35680-3_13.

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Ambika Naik, Y., M. R. Suma, and P. Madhumathy. "Air Quality Monitoring System Through Mobile Sensing in Metropolitan City." In International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018, 862–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03146-6_98.

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Clerici, G., and S. Sandroni. "A Wind-Field Model for Interpretation of Remote-Sensing Data in a Complex Area." In Air Pollution Modeling and Its Application V, 383–400. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4757-9125-9_25.

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Sivaramakrishnan, K. N., Lipika Deka, and Manik Gupta. "Use of Remote Sensing Data to Identify Air Pollution Signatures in India." In Geo-intelligence for Sustainable Development, 109–25. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4768-0_8.

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Llaguno-Munitxa, Maider, and Elie Bou-Zeid. "Sensing the Environmental Neighborhoods." In Proceedings of the 2020 DigitalFUTURES, 124–33. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4400-6_12.

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AbstractGiven the benefits of fine mapping of large urban areas affordably, mobile environmental sensing technologies are becoming increasingly popular to complement the traditional stationary weather and air quality sensing stations. However the reliability and accuracy of low-cost mobile urban technologies is often questioned. This paper presents the design of a fast-response, autonomous and affordable Mobile Urban Sensing Technology (MUST) for the acquisition of high spatial resolution environmental data. Only when accurate neighborhood scale environmental data is affordable and accessible for architects, urban planners and policy makers, can design strategies to enhance urban health be effectively implemented. The results of an experimental air quality sensing campaign developed within Princeton University Campus is presented.
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Lefebvre, Wouter, Hans Hooyberghs, Felix Deutsch, Frederick Tack, Michel van Roozendael, Marian-Daniel Iordache, Frans Fierens, et al. "Can Aircraft-Based Remote-Sensing NO2 Measurements Combined with High Resolution Model Data Improve NO2 Exposure Estimates over Urban Areas?" In Air Pollution Modeling and its Application XXV, 163–67. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57645-9_26.

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Conference papers on the topic "Flush air data sensing"

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Quindlen, John, and Jack Langelaan. "Flush Air Data Sensing for Soaring-Capable UAVs." In 51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2013. http://dx.doi.org/10.2514/6.2013-1153.

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Shen, Zhengguang, Qinghua Gao, Jingyu Dong, and Jingchun Yuan. "A self-validating flush air data sensing system." In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2015. http://dx.doi.org/10.1109/fskd.2015.7382369.

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Srivastava, Ankur, Andrew Meade, and Kurtis Long. "Learning Airdata Parameters for Flush Air Data Sensing Systems." In AIAA Infotech@Aerospace Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2009. http://dx.doi.org/10.2514/6.2009-1938.

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Artz, Edward J., Nicholas W. Dona, and Thomas R. Yechout. "NASA Orion Flush Air Data Sensing System Feasibility Determination and Development." In 52nd Aerospace Sciences Meeting. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2014. http://dx.doi.org/10.2514/6.2014-1115.

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Karlgaard, Chris D., Prasad Kutty, and Mark Schoenenberger. "Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation." In AIAA Atmospheric Flight Mechanics Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2015. http://dx.doi.org/10.2514/6.2015-0526.

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Srivastava, Ankur, Andrew Meade, and Ali Mokhtarzadeh. "A Hybrid Data-Model Fusion Approach to Calibrate a Flush Air Data Sensing System." In AIAA Infotech@Aerospace 2010. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-3347.

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Lugo, Rafael A., Christopher D. Karlgaard, Richard Powell, and Alicia M. Dwyer-Cianciolo. "Integrated Flush Air Data Sensing System Modeling for Planetary Entry Guidance with Direct Force Control." In AIAA Scitech 2019 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2019. http://dx.doi.org/10.2514/6.2019-0663.

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Ellsworth, Joel. "An Analytical Explanation for the X-43A Flush Air Data Sensing System Pressure Mismatch between Flight and Theory." In 28th AIAA Applied Aerodynamics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-4964.

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Krishna, Shashi, Arun Satheesan, S. B. Vidya, K. C. Finitha, N. Remesh, M. Jayakumar, and N. Shyam Mohan. "A method for accurate estimation of altitude in re-entry vehicles using flush air data sensing system (FADS)." In 2014 Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD). IEEE, 2014. http://dx.doi.org/10.1109/aicera.2014.6908179.

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Vidya, S. B., Arun Satheesan, Aisha Sidhick, K. C. Finitha, M. Jayakumar, and A. K. Abdul Samad. "Split range calibration in pressure measurement of re-entry flush air data sensing system (FADS) for overall system accuracy enhancement." In 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT). IEEE, 2014. http://dx.doi.org/10.1109/iccicct.2014.6992949.

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Reports on the topic "Flush air data sensing"

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Coulson, Saskia, Melanie Woods, Drew Hemment, and Michelle Scott. Report and Assessment of Impact and Policy Outcomes Using Community Level Indicators: H2020 Making Sense Report. University of Dundee, 2017. http://dx.doi.org/10.20933/100001192.

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Making Sense is a European Commission H2020 funded project which aims at supporting participatory sensing initiatives that address environmental challenges in areas such as noise and air pollution. The development of Making Sense was informed by previous research on a crowdfunded open source platform for environmental sensing, SmartCitizen.me, developed at the Fab Lab Barcelona. Insights from this research identified several deterrents for a wider uptake of participatory sensing initiatives due to social and technical matters. For example, the participants struggled with the lack of social interactions, a lack of consensus and shared purpose amongst the group, and a limited understanding of the relevance the data had in their daily lives (Balestrini et al., 2014; Balestrini et al., 2015). As such, Making Sense seeks to explore if open source hardware, open source software and and open design can be used to enhance data literacy and maker practices in participatory sensing. Further to this, Making Sense tests methodologies aimed at empowering individuals and communities through developing a greater understanding of their environments and by supporting a culture of grassroot initiatives for action and change. To do this, Making Sense identified a need to underpin sensing with community building activities and develop strategies to inform and enable those participating in data collection with appropriate tools and skills. As Fetterman, Kaftarian and Wanderman (1996) state, citizens are empowered when they understand evaluation and connect it in a way that it has relevance to their lives. Therefore, this report examines the role that these activities have in participatory sensing. Specifically, we discuss the opportunities and challenges in using the concept of Community Level Indicators (CLIs), which are measurable and objective sources of information gathered to complement sensor data. We describe how CLIs are used to develop a more indepth understanding of the environmental problem at hand, and to record, monitor and evaluate the progress of change during initiatives. We propose that CLIs provide one way to move participatory sensing beyond a primarily technological practice and towards a social and environmental practice. This is achieved through an increased focus in the participants’ interests and concerns, and with an emphasis on collective problem solving and action. We position our claims against the following four challenge areas in participatory sensing: 1) generating and communicating information and understanding (c.f. Loreto, 2017), 2) analysing and finding relevance in data (c.f. Becker et al., 2013), 3) building community around participatory sensing (c.f. Fraser et al., 2005), and 4) achieving or monitoring change and impact (c.f. Cheadle et al., 2000). We discuss how the use of CLIs can tend to these challenges. Furthermore, we report and assess six ways in which CLIs can address these challenges and thereby support participatory sensing initiatives: i. Accountability ii. Community assessment iii. Short-term evaluation iv. Long-term evaluation v. Policy change vi. Capability The report then returns to the challenge areas and reflects on the learnings and recommendations that are gleaned from three Making Sense case studies. Afterwhich, there is an exposition of approaches and tools developed by Making Sense for the purposes of advancing participatory sensing in this way. Lastly, the authors speak to some of the policy outcomes that have been realised as a result of this research.
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