Relevant bibliographies by topics / Plume dispersion model

Contents

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

Academic literature on the topic 'Plume dispersion model'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Plume dispersion model"

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Kylling, Arve, Hamidreza Ardeshiri, Massimo Cassiani, et al. "Can statistics of turbulent tracer dispersion be inferred from camera observations of SO<sub>2</sub> in the ultraviolet? A modelling study." Atmospheric Measurement Techniques 13, no. 6 (2020): 3303–18. http://dx.doi.org/10.5194/amt-13-3303-2020.

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Abstract. Atmospheric turbulence and in particular its effect on tracer dispersion may be measured by cameras sensitive to the absorption of ultraviolet (UV) sunlight by sulfur dioxide (SO2), a gas that can be considered a passive tracer over short transport distances. We present a method to simulate UV camera measurements of SO2 with a 3D Monte Carlo radiative transfer model which takes input from a large eddy simulation (LES) of a SO2 plume released from a point source. From the simulated images the apparent absorbance and various plume density statistics (centre-line position, meandering, a
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Meir, Talmor, Julie Pullen, Alan F. Blumberg, Teddy R. Holt, Paul E. Bieringer, and George Bieberbach. "Simulation of Airborne Transport and Dispersion for Urban Waterside Releases." Journal of Applied Meteorology and Climatology 56, no. 1 (2017): 27–44. http://dx.doi.org/10.1175/jamc-d-16-0025.1.

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AbstractResults are presented from a tracer-release modeling study designed to examine atmospheric transport and dispersion (“T&amp;D”) behavior surrounding the complex coastal–urban region of New York City, New York, where air–sea interaction and urban influences are prominent. The puff-based Hazard Prediction Assessment Capability (HPAC, version 5) model is run for idealized conditions, and it is also linked with the urbanized COAMPS (1 km) meteorological model and the NAM (12 km) meteorological model. Results are compared with “control” plumes utilizing surface meteorological input from 22
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Bisignano, Andrea, Luca Mortarini, Enrico Ferrero, and Stefano Alessandrini. "Model chain for buoyant plume dispersion." International Journal of Environment and Pollution 62, no. 2/3/4 (2017): 200. http://dx.doi.org/10.1504/ijep.2017.089406.

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Ferrero, Enrico, Luca Mortarini, Andrea Bisignano, and Stefano Alessandrini. "Model chain for buoyant plume dispersion." International Journal of Environment and Pollution 62, no. 2/3/4 (2017): 200. http://dx.doi.org/10.1504/ijep.2017.10010374.

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Chosson, F., R. Paoli, and B. Cuenot. "Ship plume dispersion rates in convective boundary layers for chemistry models." Atmospheric Chemistry and Physics 8, no. 16 (2008): 4841–53. http://dx.doi.org/10.5194/acp-8-4841-2008.

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Abstract. Detailed ship plume simulations in various convective boundary layer situations have been performed using a Lagrangian Dispersion Model driven by a Large Eddy Simulation Model. The simulations focus on the early stage (1–2 h) of plume dispersion regime and take into account the effects of plume rise on dispersion. Results are presented in an attempt to provide to atmospheric chemistry modellers a realistic description of characteristic dispersion impact on exhaust ship plume chemistry. Plume dispersion simulations are used to derive analytical dilution rate functions. Even though res
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Chosson, F., R. Paoli, and B. Cuenot. "Ship plume dispersion rates in convective boundary layers for chemistry models." Atmospheric Chemistry and Physics Discussions 8, no. 2 (2008): 6793–824. http://dx.doi.org/10.5194/acpd-8-6793-2008.

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Abstract. Detailed ship plume simulations in various convective boundary layer situations have been performed using a Lagrangian Dispersion Model driven by a Large Eddy Simulation Model. The simulations focus on early stage (1–2 h) of plume dispersion regime and take into account the effects of plume rise on dispersion. Results are presented in an attempt to provide to chemical modellers community a realistic description of the impact of characteristic dispersion on exhaust ship plume chemistry. Plume dispersion simulations are used to derive analytical dilution rate functions. Even though res
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Kukkonen, J., J. Nikmo, M. Sofiev, et al. "Applicability of an integrated plume rise model for the dispersion from wild-land fires." Geoscientific Model Development Discussions 7, no. 1 (2014): 483–527. http://dx.doi.org/10.5194/gmdd-7-483-2014.

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Abstract. We have presented an overview of a mathematical model, BUOYANT, that was originally designed for the evaluation of the dispersion of buoyant plumes originated from major warehouse fires. The model addresses the variations of the cross-plume integrated properties of a buoyant plume in the presence of a vertically varying atmosphere. The model also includes a treatment for a rising buoyant plume interacting with an inversion layer. We have compared the model predictions with the data of two prescribed wild-land fire experiments. For the SCAR-C experiment in Quinault (US) in 1994, the p
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Kukkonen, J., J. Nikmo, M. Sofiev, et al. "Applicability of an integrated plume rise model for the dispersion from wild-land fires." Geoscientific Model Development 7, no. 6 (2014): 2663–81. http://dx.doi.org/10.5194/gmd-7-2663-2014.

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Abstract. We have presented an overview of a mathematical model, BUOYANT, that was originally designed for the evaluation of the dispersion of buoyant plumes originated from major warehouse fires. The model addresses the variations of the cross-plume integrated properties of a buoyant plume in the presence of a vertically varying atmosphere. The model also includes a treatment for a rising buoyant plume interacting with an inversion layer. We have compared the model predictions with the data of two prescribed wild-land fire experiments. For the SCAR-C experiment in Quinault (US) in 1994, the p
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Fay, James A., and Stephen G. Zemba. "Integral model of dense gas plume dispersion." Atmospheric Environment (1967) 20, no. 7 (1986): 1347–54. http://dx.doi.org/10.1016/0004-6981(86)90005-3.

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Lott, Robert A. "Model performance—Plume dispersion over elevated terrain." Atmospheric Environment (1967) 20, no. 8 (1986): 1547–54. http://dx.doi.org/10.1016/0004-6981(86)90243-x.

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Dissertations / Theses on the topic "Plume dispersion model"

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Cheung, Soe Hoo. "Development of models for the atmospheric dispersion of odours from different source types." Thesis, Queen's University Belfast, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268226.

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Haroutunian, V. "A time-dependent finite element model for atmospheric dispersion of gases heavier than air." Thesis, University of Manchester, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380523.

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Zakeri, Shahvari Saba. "Assessment and improvement of the 2019 ASHRAE Handbook model for exhaust-to-intake dilution calculations for rooftop exhaust systems (ASHRAE 1823-RP)." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1575921032418665.

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Nironi, Chiara. "Concentration fluctuations of a passive scalar in a turbulent boundary layer." Phd thesis, Ecole Centrale de Lyon, 2013. http://tel.archives-ouvertes.fr/tel-00964852.

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This experimental study analyses the dynamics of concentration fluctuations in a passive plume emitted by a point source within the turbulent boundary layer. We aim to extend the popular study of Fackrell and Robins (1982) about concentration fluctuations and fluxes from point sources by including third and fourth moments of concentration. We also further inquire into the influence of source conditions, such as the source size, source elevation and emission velocity, on higher order concentration moments. The data set is completed by a detailed description of the velocity statistics within the
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Sallet, Marieli, and Marieli Sallet. "Desenvolvimento de um modelo lagrangeano para dispersão de poluentes em condições de vento fraco." Universidade Federal de Pelotas, 2007. http://repositorio.ufpel.edu.br/handle/ri/2183.

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Made available in DSpace on 2014-08-20T14:25:46Z (GMT). No. of bitstreams: 1 dissertacao_marieli_sallet.pdf: 231023 bytes, checksum: f445526b62fbfcde40fb1bc5ca90923a (MD5) Previous issue date: 2007-02-23<br>Currently, the search for analytical solutions for the dispersion problems is one of the main research subjects in the pollutant dispersion modeling. These solutions become important due to the intention to obtain dispersion models that generate reliable results in a small computational time, which are of great interest for regulatory air quality applications. Lagrangian particle mo
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Dinoko, Tshepo Samuel. "Modeling of the dispersion of radionuclides around a nuclear power station." Thesis, University of the Western Cape, 2009. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_3451_1360933219.

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<p>Nuclear reactors release small amounts of radioactivity during their normal operations. The most common method of calculating the dose to the public that results from such releases uses Gaussian Plume models. We are investigating these methods using CAP88-PC, a computer code developed for the Environmental Protection Agency (EPA) in the USA that calculates the concentration of radionuclides released from a stack using Pasquill stability classification. A buoyant or momentum driven part is also included. The uptake of the released radionuclide by plants, animals and humans, directly and indi
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Nekouee, Navid. "Dynamics and numerical modeling of river plumes in lakes." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/41104.

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Models of the fate and transport of river plumes and the bacteria they carry into lakes are developed. They are needed to enable informed decisions about beach closures to avoid economic losses, and to help design water intakes and operate combined sewer overflow schemes to obviate exposure of the public to potential pathogens. This study advances our understanding of river plumes dynamics in coastal waters by means of field studies and numerical techniques. Extensive field measurements were carried out in the swimming seasons of 2006 and 2007 on the Grand River plume as it enters Lake Michig
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Zacharias, Daniel Constantino. "Desenvolvimento do STFM (Spill, Transport and Fate Model): Modelo computacional lagrangeano de transporte e degradação de manchas de óleo." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/14/14133/tde-08052018-192547/.

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Os derramamentos de petróleo são consequência inevitável e indesejável da produção e transporte do petróleo e seus derivados. A maioria desses derramamentos são relativamente pequenos, mas alguns deles são grandes o suficiente para causar significativo impacto ambiental. Nessas situações, os modelos computacionais são ferramentas importantes para estimar a trajetória, dimensionamento e comportamento do óleo derramado no ambiente marinho, sendo determinantes na elaboração de planos de ação e trabalho das equipes de resposta. O transporte e destino de óleo offshore derramado são regidos majorita
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KEONG, KOK TEO. "COMPARISON OF TWO AERIAL DISPERSION MODELS FOR THE PREDICTION OF CHEMICAL RELEASE ASSOCIATED WITH MARITIME ACCIDENTS NEAR COASTAL AREAS." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1014648666.

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DOURADO, H. O. "Estudo da dispersão de gases odorantes ao redor de obstáculos através do modelo de pluma flutuante." Universidade Federal do Espírito Santo, 2007. http://repositorio.ufes.br/handle/10/3880.

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Made available in DSpace on 2016-08-29T15:09:35Z (GMT). No. of bitstreams: 1 tese_2639_Harerton Oliveira Dourado - Dissertação.pdf: 1884341 bytes, checksum: 5a0fb0840af372b7ababb381fe5dea25 (MD5) Previous issue date: 2007-08-28<br>A emissão atmosférica de compostos odorantes pode causar impactos ambientais, causando incômodo e trazendo prejuízos à saúde. Uma das ferramentas empregadas nos estudos desses impactos são os modelos matemáticos, baseados na solução das equações de transporte do poluente. Um aspecto importante é a capacidade dos modelos em incluir o efeito da presença de obstáculos
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Books on the topic "Plume dispersion model"

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Henderson-Sellers, Brian. Modeling of Plume Rise and Dispersion — The University of Salford Model: U.S.P.R. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-82976-5.

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Truppi, Lawrence E. EPA complex terrain model development: Description of a computer data base from the Full Scale Plume Study, Tracy Power Plant, Nevada. U.S. Environmental Protection Agency, Atmospheric Sciences Research Laboratory, 1987.

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Air & Waste Management Association., ed. Practical guide to atmospheric dispersion modeling. Trinity Consultants, Inc., 2007.

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Turner, D. Bruce. Workbook of atmospheric dispersion estimates: An introduction to dispersion modeling. 2nd ed. Lewis Publishers, 1994.

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Cooper, P. J. A modelling study of dispersion of elevated plumes at a coastal location during onshore flow. United Kingdom Atomic Energy Authority, Safety and Reliabiblity Directorate, 1987.

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Truppi, Lawrence E. EPA complex terrain model development: Description of a computer data base from Small Hill Impaction Study No. 2, Hogback Ridge, New Mexico. U.S. Environmental Protection Agency, Atmospheric Sciences Research Laboratory, 1986.

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Fundamentals of stack gas dispersion. 3rd ed. Milton R. Beychok, 1994.

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Henderson-Sellers, B. Prise: Plume Rise and Dispersion Model. Computational Mechanics, 1999.

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Modeling of Plume Rise and Dispersion - The University of Salford Model: USPR. Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 1987.

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Henderson-Sellers, Brian. Modeling of Plume Rise and Dispersion the University of Salford Model: U.S.P.R. (Lecture Notes in Engineering). Springer, 1987.

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Book chapters on the topic "Plume dispersion model"

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Macdonald, R. W., R. F. Griffiths, and D. J. Hall. "A Model of Plume Advection Velocity for Dispersion in Urban Arrays." In Air Pollution Modeling and Its Application XIII. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4153-0_89.

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Hanna, Steven R., and Joseph C. Chang. "Revision of the Hybrid Plume Dispersion Model (HPDM) for Application to Urban Areas." In Air Pollution Modeling and Its Application VIII. Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3720-5_87.

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Jenkinson, P., R. Hill, E. Lutman, A. Arnott, and T. G. Parker. "Poster 5 Inter-comparison of CFD, wind tunnel and Gaussian plume models for estimating dispersion from a complex industrial site." In Air Pollution Modeling and Its Application XVIII. Elsevier, 2007. http://dx.doi.org/10.1016/s1474-8177(07)06805-2.

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Conference papers on the topic "Plume dispersion model"

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April L. Hiscox, David R. Miller, and Carmen J. Nappo. "Plume Model Dispersion Parameters Measured with LIDAR." In 2005 Tampa, FL July 17-20, 2005. American Society of Agricultural and Biological Engineers, 2005. http://dx.doi.org/10.13031/2013.18877.

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Nayak, Soumitra K., Prakash Tamboli, and Siddhartha P. Duttagupta. "Plume Profile Estimation in Porous media using Lagrangian Dispersion Model." In 2018 4th International Conference for Convergence in Technology (I2CT). IEEE, 2018. http://dx.doi.org/10.1109/i2ct42659.2018.9058214.

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Yang, Ye, Bo Cao, and Yixue Chen. "Simulation of the Atmospheric Dispersion of Radionuclides Using Gaussian Plume Model." In 2013 21st International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/icone21-16263.

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The Chernobyl accident and Fukushima 1 Nuclear Power Plant accident are the most serious accidents in the history of the nuclear technology and industry. A large amount of radioactive materials from nuclear power plant were released, leading to huge damage and long-term effect on the environment as well as the human health neighbor to the plant. Therefore, simulating the transport and transformation of radionuclides in the atmosphere is significant for decision makers to take steps at all level. Now, many different dispersion models are widely applied and used to simulate the transport and tra
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Ristic, Branko, Ajith Gunatilaka, and Ralph Gailis. "Achievable accuracy in parameter estimation of a Gaussian plume dispersion model." In 2014 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2014. http://dx.doi.org/10.1109/ssp.2014.6884612.

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Zimu Yu, Huiqing Guo, and Claude Laguë. "Development of a Livestock Odor Dispersion Model Based on Fluctuating Plume Theory." In 2008 Providence, Rhode Island, June 29 - July 2, 2008. American Society of Agricultural and Biological Engineers, 2008. http://dx.doi.org/10.13031/2013.25153.

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Paraschiv, Spiru, Gelu Coman, and Lizica Simona Paraschiv. "Simulation of plume dispersion emitted from industrial sources based on Gaussian model." In XIAMEN-CUSTIPEN WORKSHOP ON THE EQUATION OF STATE OF DENSE NEUTRON-RICH MATTER IN THE ERA OF GRAVITATIONAL WAVE ASTRONOMY. AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5116986.

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Miner, Heidi E., and Adam Rasmussen. "Evolution of Ground Level Scalar Concentrations Through a Compact Cylinder Array Embedded in the Atmospheric Surface Layer." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-39626.

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Experiments for this study were designed to understand gas dispersion in the presence of surface mounted obstacles. To this end, model field experiments were conducted in a compact barrel array employing a spatial distribution of concentration sensors. Specific aims were to explore the effects of atmospheric stability and plume source initial conditions on the plume dispersion through the barrel array. The present results indicate a relaxation towards Gaussian behavior along the plume centerline. The rate of this Gaussian-like behavior is dependent upon atmospheric stability conditions. Plume
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Rohmah, Ratnasari Nur, and Nurokhim. "Simulation of I-131 Dispersion around KNS (Kawasan Nuklir Serpong) using Gaussian Plume Model." In 2017 15th International Conference on Quality in Research (QiR): International Symposium on Electrical and Computer Engineering. IEEE, 2017. http://dx.doi.org/10.1109/qir.2017.8168521.

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Chen, Baixin, Yongchen Song, Masahiro Nishio, and Makato Akai. "Numerical Prediction of the Effects of Oceanic Flow Characters on the Evolution of CO2 Eniched Plumes." In ASME 2004 23rd International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2004. http://dx.doi.org/10.1115/omae2004-51103.

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The near-field dynamics of CO2 rich plume draw attention of assessment of the local impacts of CO2 ocean sequestration on natural oceanic environment. In this study, we attempt to predict numerically the role of ocean flow characters, including the current profile and the turbulent intensity, and of the injection parameters, including the injection rate and initial droplet diameters, on the evolution of liquid CO2 (LCO2) droplet and CO2 enriched seawater plumes. The numerical model we used in this study is a two-phase large-eddy simulation model. From numerical experiments we found: 1). The pl
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Tani, Giovanni, Leonardo Orazi, Alessandro Fortunato, and Gabriele Cuccolini. "3-D Transient Simulation Model for Laser Micromilling Processes." In ASME 2007 International Manufacturing Science and Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/msec2007-31072.

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In this paper a laser milling simulator package is shown and discussed. The software system has been developed to simulate the micromanufacturing process using solid state lasers with pulse width in the range of 10–100 ns, but it can simulate every spatial and temporal distribution of the laser beam, so it is well suited to simulate both continuous and pulsed emission and every kind of laser spot distribution and trajectory. The system can simulate the effect of the laser beam on the workpiece, keeping into account the surface conditions, the evolution of the work-piece temperature field, the
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Reports on the topic "Plume dispersion model"

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Brown, D. F., W. E. Dunn, A. J. Policastro, and D. Maloney. FIREPLUME model for plume dispersion from fires: Application to uranium hexafluoride cylinder fires. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/510554.

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Hanna, S. R., and J. C. Chang. HGSYSTEM/UF{sub 6} model enhancements for plume rise and dispersion around buildings, lift-off of buoyant plumes, and robustness of numerical solver. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/491393.

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Brown, M. J., C. Mueller, B. Bush, and P. Stretz. Exposure estimates using urban plume dispersion and traffic microsimulation models. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/564119.

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Farrell, Jay A., John Murlis, Xuezhu Long, Wei Li, and Ring Carde. Filament-Based Atmospheric Dispersion Model to Achieve Short Time-Scale Structure of Odor Plumes. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada399832.

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Prasad, Kuldeep R., Adam L. Pintar, Heming Hu, Israel Lopez Coto, Dennis T. Ngo, and James R. Whetstone. Greenhouse Gas Emissions and Dispersion 3. Reducing Uncertainty in Estimating Source Strength and Location through Plume Inversion Models. National Institute of Standards and Technology, 2015. http://dx.doi.org/10.6028/nist.sp.1175.

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