Academic literature on the topic 'Planetary Modeling'
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Journal articles on the topic "Planetary Modeling"
Tarasik, Vladimir Petrovich. "MODELING OF PLANETARY GEAR." Вестник Белорусско-Российского университета, no. 4 (2016): 78–89. http://dx.doi.org/10.53078/20778481_2016_4_78.
Full textHu, H., and B. Wu. "PLANETARY3D: A PHOTOGRAMMETRIC TOOL FOR 3D TOPOGRAPHIC MAPPING OF PLANETARY BODIES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W5 (May 29, 2019): 519–26. http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-519-2019.
Full textHarrington, J. P., K. J. Borkowski, and Z. I. Tsvetanov. "Modeling hydrogen-deficient Planetary Nebulae." Symposium - International Astronomical Union 180 (1997): 235. http://dx.doi.org/10.1017/s0074180900130554.
Full textSchulz, Michael, and Michael C. McNab. "Source-surface modeling of planetary magnetospheres." Journal of Geophysical Research: Space Physics 101, A3 (March 1, 1996): 5095–118. http://dx.doi.org/10.1029/95ja02987.
Full textWicht, J., and A. Tilgner. "Theory and Modeling of Planetary Dynamos." Space Science Reviews 152, no. 1-4 (March 18, 2010): 501–42. http://dx.doi.org/10.1007/s11214-010-9638-y.
Full textOliveira, P., J. Soares, H. A. Karam, M. M. R. Pereira, and E. P. Marques Filho. "NUMERICAL MODELING OF THE PLANETARY BOUNDARY LAYER." Revista de Engenharia Térmica 3, no. 1 (June 30, 2004): 74. http://dx.doi.org/10.5380/reterm.v3i1.3490.
Full textPelkowski, J., L. Chevallier, B. Rutily, and O. Titaud. "Exact results in modeling planetary atmospheres—III." Journal of Quantitative Spectroscopy and Radiative Transfer 109, no. 1 (January 2008): 43–51. http://dx.doi.org/10.1016/j.jqsrt.2007.07.014.
Full textNesvorný, David, Fernando Roig, and William F. Bottke. "Modeling the Historical Flux of Planetary Impactors." Astronomical Journal 153, no. 3 (February 9, 2017): 103. http://dx.doi.org/10.3847/1538-3881/153/3/103.
Full textVan Hoof, Peter A. M., and Griet C. Van De Steene. "Modeling and distance determination of planetary nebulae." Astrophysics and Space Science 238, no. 1 (April 1996): 83–86. http://dx.doi.org/10.1007/bf00645498.
Full textEfthymiopoulos, Christos, and Rocío I. Páez. "Modeling resonant trojan motions in planetary systems." Proceedings of the International Astronomical Union 9, S310 (July 2014): 70–73. http://dx.doi.org/10.1017/s1743921314007868.
Full textDissertations / Theses on the topic "Planetary Modeling"
Chan, Tsz-pan Henry, and 陳子斌. "Morpho-kinematic modeling of planetary nebulae." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42182293.
Full textChan, Tsz-pan Henry. "Morpho-kinematic modeling of planetary nebulae." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B42182293.
Full textSondkar, Prashant B. "Dynamic Modeling of Double-Helical Planetary Gear Sets." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338481548.
Full textEisen, Howard J. (Howard Jay). "Scale and computer modeling of wheeled vehicles for planetary exploration." Thesis, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/43001.
Full textWagner, Richard A. "Sand modeling of crustal extension." Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/59038.
Full textMicrofiche copy available in Archives and Science.
Vita.
Bibliography: leaf 53.
by Richard A. Wagner, Jr.
M.S.
Hoffman, Nick(Nicholas D. ). "Modeling methylmercury in Maine's tribal meres." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122866.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 59-76).
Methylmercury (MeHg) concentrations in the fish of twenty Maine lakes were projected for the year 2035 under three different policy scenarios. A mechanistic model of Hg fate and transport was calibrated for Maine's environment using four parameters: volumetric outflow rate, settling velocity, burial velocity, and Hg(II) biotic solids partitioning coefficient. The model was evaluated through comparison with measured results from the year 1993. The model results showed that the strictest global Hg regulations will lead to the greatest decreases in MeHg concentration. No piscivore will be safe for frequent consumption, even under the strictest regulations in the cleanest lakes. The Wabanaki traditional-subsistence diet will continue to entail unsafe MeHg exposures.
by Nick Hoffman.
S.B.
S.B. Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences
Alsaadan, Sami Ibrahim. "Modeling velocity dispersion In Gypsy site, Oklahoma." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62484.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (p. 73-76).
Discrepancies in interval velocities estimated from vertical well measurements made with different source central frequencies at Gypsy site could be primarily explained in terms of intrinsic attenuation. Four intervals were chosen for this study based on varying rock properties. The first interval is predominantly shale, second interval is mostly sandstone, and the third interval is made up of shale and sandstone. The fourth interval is the second and third intervals combined. The data used are acquired from three seismic sources; Full Wave Sonic (FWS), Bender log, and Vertical Seismic Profile (VSP) with estimated central frequencies 10kHz, 1kHz, and 100Hz, respectively. The modeling was done using the Discrete Wavenumber (DWN) method and the Logarithmic Dispersion Relation (LDR) to calculate a constant Quality Factor (Q) that best explains the observed velocity dispersion for each of the intervals of interest. The elastic scattering component of the dispersion is negligible. Intrinsic quality factors of 54,35,28, and 30 best explain the field data for first, second, third, and fourth intervals, respectively. The identification and subsequent modeling of velocity dispersion and its components provide key information for integrated reservoir characterization and better enable the prediction of the seismic response at different frequencies.
by Sami Ibrahim Alsaadan.
S.M.
Minsley, Burke J. "Modeling and inversion of self-potential data." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40863.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 235-251).
This dissertation presents data processing techniques relevant to the acquisition, modeling, and inversion of self-potential data. The primary goal is to facilitate the interpretation of self-potentials in terms of the underlying mechanisms that generate the measured signal. The central component of this work describes a methodology for inverting self-potential data to recover the three-dimensional distribution of causative sources in the earth. This approach is general in that it is not specific to a particular forcing mechanism, and is therefore applicable to a wide variety of problems. Self-potential source inversion is formulated as a linear problem by seeking the distribution of source amplitudes within a discretized model that satisfies the measured data. One complicating factor is that the potentials are a function of the earth resistivity structure and the unknown sources. The influence of imperfect resistivity information in the inverse problem is derived, and illustrated through several synthetic examples. Source inversion is an ill-posed and non-unique problem, which is addressed by incorporating model regularization into the inverse problem. A non-traditional regularization method, termed "minimum support," is utilized to recover a spatially compact source model rather than one that satisfies more commonly used smoothness constraints. Spatial compactness is often an appropriate form of prior information for the inverse source problem. Minimum support regularization makes the inverse problem non-linear, and therefore requires an iterative solution technique similar to iteratively re-weighted least squares (IRLS) methods.
(cont.) Synthetic and field data examples are studied to illustrate the efficacy of this method and the influence of noise, with applications to hydrogeologic and electrochemical self-potential source mechanisms. Finally, a novel technique for pre-processing self-potential data collected with arbitrarily complicated survey geometries is presented. This approach overcomes the inability of traditional processing methods to produce a unique map of the potential field when multiple lines of data form interconnected loops. The data are processed simultaneously to minimize mis-ties on a survey-wide basis using either an 12 or 11 measure of misfit, and simplifies to traditional methods in the absence of survey complexity. The 11 measure requires IRLS solution methods, but is more reliable in the presence of data outliers.
by Burke J. Minsley.
Ph.D.
Quinn, Katherine J. (Katherine Jane) 1971. "Atmospheric delay modeling for satellite laser altimetry." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8061.
Full textIncludes bibliographical references.
NASA's Ice, Cloud, and Land Elevation Satellite (ICESat) is a laser altimetry mission with the primary purpose of measuring the mass balance of the ice sheets of Greenland and Antarctica. It will provide 5 years of topography measurements of the ice, as well as land and ocean topography. In order to accurate topography measurements the laser altimeter ranges must be corrected for certain biases. Atmospheric delay is one such bias. As the laser pulse travels through the atmosphere it will be refracted, introducing a delay into the travel time. This delay must be estimated to correct the ranges and the delay estimations need to be validated. Of particular concern are errors in the delay estimates that have the same characteristics as the expected mass balance variations. The main focus of this dissertation is to formulate algorithms for calculating the ICE-Sat atmospheric delay and estimate the expected delay values and errors. Our atmospheric delay algorithm uses numerical weather model data to estimate delay values. We have validated these algorithms using Automatic Weather Stations (AWS) in the polar regions and GPS data over the globe. The GPS data validation was also augmented by in-situ meteorology measurements at some the stations. The GPS validation process additionally allowed us to investigate the estimation of precipitable water vapor using GPS data. The validation studies have shown that our atmospheric delay algorithm errors are well within the ICESat error budget of 20 mm. The overall global delay errors are estimated to be approximately 5.4 mm and the polar delay errors are 12.2 mm. There are no discernible biases in the error and the seasonal variations in error magnitudes are well characterized.
by Katherine J. Quinn.
Ph.D.
DesAutels, Christopher Gerald 1975. "Upper-ocean influences on hurricane intensification modeling." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/53046.
Full textIncludes bibliographical references (leaves 32-33).
Hurricane intensification modeling has been a difficult problem for the atmospheric science community. Complex models have been built to simulate the process, but with only a certain amount of success. A model developed by Dr. Kerry Emanuel is much simpler compared to previous studies. The Emanuel model approaches hurricane intensification as an ocean-controlled process where the upper-ocean heat content limits intensification. It is shown that this ocean-based model can produce very accurate results when the true structure of the ocean can be determined. The Ocean Topography Experiment (TOPEX) provides an opportunity for the model to be tested through the use of satellite altimetry. Measurements of the mixed layer depth and upper-ocean heat content are incorporated into the model for Hurricanes Bret, Gert, Opal, Mitch and Dolly. This technique is shown to be quite reliable for many storms, especially in the Gulf of Mexico. Limitations are examined where this method breaks down and improvements are suggested for its development into a forecasting tool.
by Christopher Gerald DesAutels.
S.M.
Books on the topic "Planetary Modeling"
Haider, S. A., Haider S. A, and Shyam Lal. Modeling of planetary atmospheres. Edited by Physical Research Laboratory (Ahmadābād, India). Delhi: Macmillan Publishers India, 2010.
Find full textParker, Robert G. Modeling, modal properties, and mesh stiffness variation instabilities of planetary gears. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2001.
Find full textBorysow, Aleksandra. Modeling of collision induced absorption spectra of CO₂-CO₂ pairs for planetary atmosphere of Venus. [Washington, DC: National Aeronautics and Space Administration, 1995.
Find full textBorysow, Aleksandra. Modeling of collision induced absorption spectra of CO₂-CO₂ pairs for planetary atmosphere of Venus. [Washington, DC: National Aeronautics and Space Administration, 1995.
Find full textKargel, J. S. (Jeffrey Stuart), 1958- and SpringerLink (Online service), eds. Cold Aqueous Planetary Geochemistry with FREZCHEM: From Modeling to the Search for Life at the Limits. Berlin, Heidelberg: Springer-Verlag, 2008.
Find full textLin, Yuh-Lang. Numerical modeling studies of wake vortex transport and evolution within the planetary boundary layer: FY94 July semi-annual report. Raleigh, NC: Dept. of Marine, Earth and Atmospheric Sciences, North Carolina State University, 1994.
Find full textHaskin, Larry A. Analytical, experimental, and modelling studies of lunar and terrestrial rocks: Final report--summary of research, NASA grant no. NAGW-3343, Washington University fund #1041-59981. [Washington, DC: National Aeronautics and Space Administration, 1997.
Find full textManfrida, Roberto, and Daniele Contini, eds. Proceedings of Physmod 2003 International Workshop on Physical Modelling of Flow and Dispersion Phenomena. Florence: Firenze University Press, 2003. http://dx.doi.org/10.36253/88-8453-095-4.
Full textBurlina, E. I︠A︡. Gorod, strana, planeta: Modeli gumanizma v khudozhestvennoiĭ kulʹture. Samara: Samarskiĭ Dom pechati, 1995.
Find full textHollingsworth, Jeffery L. Modeling of forced planetary waves in the Mars atmosphere. 1992.
Find full textBook chapters on the topic "Planetary Modeling"
Harrington, J. P., K. J. Borkowski, and Z. I. Tsvetanov. "Modeling Hydrogen-Deficient Planetary Nebulae." In Planetary Nebulae, 235. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5244-0_91.
Full textWicht, J., and A. Tilgner. "Theory and Modeling of Planetary Dynamos." In Planetary Magnetism, 501–42. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-5901-0_15.
Full textBoslough, Mark. "Modeling." In Handbook of Cosmic Hazards and Planetary Defense, 1–24. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02847-7_56-1.
Full textRead, Peter L., Edgar P. Pérez, Irene M. Moroz, and Roland M. B. Young. "General Circulation of Planetary Atmospheres." In Modeling Atmospheric and Oceanic Flows, 7–44. Hoboken, NJ: John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781118856024.ch1.
Full textVisconti, Guido. "Progress in Climate Modeling." In Climate, Planetary and Evolutionary Sciences, 155–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74713-8_5.
Full textYamamoto, T. M., F. H. Sellmaier, A. W. A. Pauldrach, and T. Hoffmann. "The influence of new NLTE model atmospheres with wind effects in nebular modeling." In Planetary Nebulae, 135. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5244-0_53.
Full textEzzedine, Souheil M., and Paul L. Miller. "Water Impact Modeling." In Handbook of Cosmic Hazards and Planetary Defense, 1–19. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02847-7_88-1.
Full textBoslough, Mark. "Airburst Airburst Modeling." In Handbook of Cosmic Hazards and Planetary Defense, 665–92. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-03952-7_56.
Full textGraja, Oussama, Bacem Zghal, Kajetan Dziedziech, Fakher Chaari, Adam Jablonski, Tomasz Barszcz, and Mohamed Haddar. "New Modeling of Planetary Gear Transmission." In Design and Modeling of Mechanical Systems—III, 1227–33. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66697-6_120.
Full textHarrington, J. Patrick. "Modeling the Thermal Emission From Dust in Planetary Nebulae." In Planetary and Proto-Planetary Nebulae: From IRAS to ISO, 239–48. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3891-5_27.
Full textConference papers on the topic "Planetary Modeling"
Balakumar, Ashrith, Neal Bhasin, Oliver Daids, Richard Shanor, Kerry Snyder, and William Whittaker. "Flyover Modeling of Planetary Pits." In AIAA Guidance, Navigation, and Control Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-0101.
Full textShuai, SUN, WANG Lei, LI Zhiping, GU Peng, FENG Yuting, and SUN Yujia. "Modeling and Simulation of Planetary Rover Using Modelica." In 2020 Chinese Automation Congress (CAC). IEEE, 2020. http://dx.doi.org/10.1109/cac51589.2020.9326685.
Full textSteffen, M. "Modeling X-ray Emission from Planetary Nebulae." In PLANETARY NEBULAE AS ASTRONOMICAL TOOLS: International Conference on Planetary Nebulae as Astronomical Tools. AIP, 2005. http://dx.doi.org/10.1063/1.2146260.
Full textCecconi, B. "Jovian Radio Emissions Modeling and their Future Investigation with EJSM (invited; abstract)." In Planetary Radio Emissions VII. Vienna: Austrian Academy of Sciences Press, 2011. http://dx.doi.org/10.1553/pre7s227.
Full textLINDEMANN, RANDEL. "Dynamic modeling and simulation of planetary rovers." In Aerospace Design Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-1269.
Full textGubchenko, V. M. "On Kinetic Approach to Modeling of Sources of Electromagnetic Radiation Located in Planet/Stellar Electroctromagnetic Structures (abstract)." In Planetary Radio Emissions VII. Vienna: Austrian Academy of Sciences Press, 2011. http://dx.doi.org/10.1553/pre7s557.
Full textSimon, Matthew, and Alan Wilhite. "Systems Level Evaluation of Space and Planetary Habitat Interior Layouts." In AIAA Modeling and Simulation Technologies Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-8220.
Full textRokach, Oleg V. "The 2.5-Dimensional Photoionization Code “PAN” for Modeling of Axially Symmetric Nebulae: The Distinctive Features." In PLANETARY NEBULAE AS ASTRONOMICAL TOOLS: International Conference on Planetary Nebulae as Astronomical Tools. AIP, 2005. http://dx.doi.org/10.1063/1.2146232.
Full textESSEX, CHRISTOPHER. "THEORETICAL ALTERNATIVES TO CLIMATE MODELING." In International Seminar on Nuclear War and Planetary Emergencies 38th Session. WORLD SCIENTIFIC, 2008. http://dx.doi.org/10.1142/9789812834645_0024.
Full text"Vision Based Modeling and Localization for Planetary Exploration Rovers." In 55th International Astronautical Congress of the International Astronautical Federation, the International Academy of Astronautics, and the International Institute of Space Law. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2004. http://dx.doi.org/10.2514/6.iac-04-u.2.09.
Full textReports on the topic "Planetary Modeling"
Fox, Matthew W., Xiaoqing Pi, and Jeffrey M. Forbes. Plasmaspheric Modeling Studies, Substorm Response Modeling and Planetary Wave Signatures. Fort Belvoir, VA: Defense Technical Information Center, June 1995. http://dx.doi.org/10.21236/ada299896.
Full textWeil, Jeffrey C. Lagrangian Stochastic Modeling of Dispersion in the Planetary Boundary Layer. Fort Belvoir, VA: Defense Technical Information Center, April 1995. http://dx.doi.org/10.21236/ada295701.
Full textWeil, Jeffrey C. Collaborative Research: Lagrangian Modeling of Dispersion in the Planetary Boundary Layer. Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada413180.
Full text