يعرض 1 - 20 نتائج من 184 نتيجة بحث عن '"Gustavo, Gatica"', وقت الاستعلام: 0.58s تنقيح النتائج
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    وصف الملف: 13 páginas; application/pdf

    Relation: Water; 1. Ramezani, L.; Karney, B.; Malekpour, A. The Challenge of Air Valves: A Selective Critical Literature Review. J. Water Resour. Plan. Manag. 2016, 141, 04015017. [CrossRef]; 2. Fuertes-Miquel, V.S.; Coronado-Hernández, Ó.E.; Mora-Melia, D.; Iglesias-Rey, P.L. Hydraulic Modeling during Filling and Emptying Processes in Pressurized Pipelines: A Literature Review. Urban Water J. 2019, 16, 299–311. [CrossRef]; 3. AWWA (American Water Works Association). Manual of Water Supply Practices M51—Air Valves: Air Release, Air/Vacuum and Combination; AWWA: Denver, CO, USA, 2016.; 4. Coronado-Hernández, O.E.; Fuertes-Miquel, V.S.; Besharat, M.; Ramos, H.M. Subatmospheric Pressure in a Water Draining Pipeline with an Air Pocket. Urban Water J. 2018, 15, 346–352. [CrossRef]; 5. Coronado-Hernández, O.E.; Fuertes-Miquel, V.S.; Iglesias-Rey, P.L.; Martínez-Solano, F.J. Rigid Water Column Model for Simulating the Emptying Process in a Pipeline Using Pressurized Air. J. Hydraul. Eng. 2018, 144, 06018004. [CrossRef]; 6. Coronado-Hernández, Ó.E.; Fuertes-Miquel, V.S.; Quiñones-Bolaños, E.E.; Gatica, G.; Coronado-Hernández, J.R. Simplified Mathematical Model for Computing Draining Operations in Pipelines of Undulating Profiles with Vacuum Air Valves. Water 2020, 12, 2544. [CrossRef]; 7. Laanearu, J.; Annus, I.; Koppel, T.; Bergant, A.; Vuˇckoviˇc, S.; Hou, Q.; van’t Westende, J.M.C. Emptying of Large-Scale Pipeline by Pressurized Air. J. Hydraul. Eng. 2012, 138, 1090–1100. [CrossRef]; 8. Tijsseling, A.; Hou, Q.; Bozku¸s, Z.; Laanearu, J. Improved One-Dimensional Models for Rapid Emptying and Filling of Pipelines. J. Press. Vessel Technol. 2016, 138, 031301. [CrossRef]; 9. Besharat, M.; Coronado-Hernández, O.E.; Fuertes-Miquel, V.S.; Viseu, M.T.; Ramos, H.M. Backflow Air and Pressure Analysis in Emptying Pipeline Containing Entrapped Air Pocket. Urban Water J. 2018, 15, 769–779. [CrossRef]; 11. Besharat, M.; Coronado-Hernández, O.E.; Fuertes-Miquel, V.S.; Viseu, M.T.; Ramos, H.M. Computational fluid dynamics for sub-atmospheric pressure analysis in pipe drainage. J. Hydraul. Res. 2020, 58, 553–565. [CrossRef]; 12. Liou, C.P.; Hunt, W.A. Filling of pipelines with undulating elevation profiles. J. Hydraul. Eng. 1996, 122, 534–539. [CrossRef]; 13. Izquierdo, J.; Fuertes, V.; Cabrera, E.; Iglesias, P.; Garcia-Serra, J. Pipeline start-up with entrapped air. J. Hydraul. Res. 1999, 37, 579–590. [CrossRef]; 14. Martins, N.M.; Delgado, J.N.; Ramos, H.M.; Covas, D.I. Maximum transient pressures in a rapidly filling pipeline with entrapped air using a CFD model. J. Hydraul. Res. 2017, 55, 506–519. [CrossRef]; 15. Zhou, L.; Liu, D. Experimental Investigation of Entrapped Air Pocket in a Partially Full Water Pipe. J. Hydraul. Res. 2013, 51, 469–474. [CrossRef]; 16. Zhou, L.; Liu, D.; Karney, B. Investigation of hydraulic transients of two entrapped air pockets in a water pipeline. J. Hydraul. Eng. 2013, 139, 949–959. [CrossRef]; 17. Fuertes-Miquel, V.S.; López-Jiménez, P.A.; Martínez-Solano, F.J.; López-Patiño, G. Numerical modelling of pipelines with air pockets and air valves. Can. J. Civ. Eng. 2016, 43, 1052–1061. [CrossRef]; 18. Chapra, S.; Canale, R. Numerical Methods for Engineers, 7th ed.; Mcgraw-Hill Education, Cop: New York, NY, USA, 2015.; 19. Stoer, J.; Bulirsch, R. Introduction to Numerical Analysis; Springer: New York, NY, USA; London, UK, 2011.; 20. Zill, D. Differential Equations with Boundary-Value Problems; Cengage Learning: Melbourne, Australia, 2016.; 21. Suribabu, C.R. Location and Sizing of Scour Valves in Water Distribution Network. J. Hydraul. Eng. 2009, 15, 118–130. [CrossRef]; 22. Suribabu, C.R. Optimal locations and sizing of scour valves in water distribution networks. J. Pipeline Syst. Eng. 2020, 11, 04019056. [CrossRef]; 23. Fuertes-Miquel, V.S.; Coronado-Hernández, Ó.E.; Mora-Melia, D.; Iglesias-Rey, P.L. Transient phenomena during the emptying process of a single pipe with water–air interaction. J. Hydraul. Res. 2018, 57, 3. [CrossRef]; 13; 21; 14; Coronado-Hernández, O.E.; Bonilla-Correa, D.M.; Lovo, A.; Fuertes-Miquel, V.S.; Gatica, G.; Linfati, R.; Coronado-Hernández, J.R. An Implicit Formulation for Calculating Final Conditions in Drainage Maneuvers in Pressurized Water Installations. Water 2022, 14, 3364. https://doi.org/10.3390/ w14213364; https://hdl.handle.net/11323/10915; Corporación Universidad de la Costa; REDICUC – Repositorio CUC; https://repositorio.cuc.edu.co/

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    وصف الملف: 20 páginas; application/pdf

    Relation: Water; 1. González-Álvarez, Á.; Viloria-Marimón, O.M.; Coronado-Hernández, Ó.E.; Vélez-Pereira, A.M.; Tesfagiorgis, K.; CoronadoHernández, J.R. Isohyetal maps of daily maximum rainfall for different return periods for the Colombian Caribbean Region. Water 2019, 11, 358. [CrossRef]; 2. Vahabzadeh, G.; Saleh, I.; Safari, A.; Khosravi, K.; Vahabzadeh, G.; Saleh, I.; Safari, A.; Khosravi, K. Determination of the best method of estimating the time of concentration in pasture watersheds (case study: Banadak Sadat and Siazakh Watersheds, Iran). J. Biodivers. Environ. Sci. 2013, 3, 150–159.; 3. Vélez, J.J.; Gutierrez, B.A. Estimación del tiempo de concentración y tiempo de rezago en la cuenca experimental urbana de la quebrada San Luis, Manizales. Dyna 2011, 78, 58–71.; 4. Avila, L.; Ávila, H. Hazard Analysis in Urban Streets Due to Flash Floods: Case Study of Barranquilla, Colombia. In World Environmental and Water Resources Congress; American Society of Civil Engineers: Reston, VA, USA, 2016; pp. 144–154. Available online: ascelibrary.org (accessed on 9 September 2021).; 5. Salimi, E.T.; Nohegar, A.; Malekian, A.; Hoseini, M.; Holisaz, A. Estimating time of concentration in large watersheds. Paddy Water Environ. 2017, 15, 123–132. [CrossRef]; 6. McCuen, R.H.; Wong, S.L.; Rawls, W.J. Estimating urban time of concentration. J. Hydraul. Eng. 1984, 110, 887–904. [CrossRef]; 7. Amatya, D.; Cupak, A.; Walega, A. Influence of tIme of concentratIon on variation of runoff from a small urbanized watershed. Geomat. Landmanagement Landsc. 2015, 2, 7–19.; 8. Ibáñez, S.A.; Moreno, H.R.; Gisbert, J.M.B. Métodos Para la Determinación del Tiempo de Concentración (tc) de una Cuenca Hidrográfica; Universidad Politecnica de Valencia: Valencia, Spain, 2011.; 9. Grimaldi, S.; Petroselli, A.; Tauro, F.; Porfiri, M. Time of concentration: A paradox in modern hydrology. Hydrol. Sci. J. 2012, 57, 217–228. [CrossRef]; 11. De Almeida, I.K.; Almeida, A.K.; Anache, J.A.A.; Steffen, J.L.; Alves, T. Estimation on time of concentration of overland flow in watersheds: A review. Geociências 2014, 33, 661–671.; 12. Gericke, O.J.; Smithers, J.C. Review of methods used to estimate catchment response time for the purpose of peak discharge estimation. Hydrol. Sci. J. 2014, 59, 1935–1971. [CrossRef]; 13. Sharifi, S.; Hosseini, S.M. Methodology for Identifying the Best Equations for Estimating the Time of Concentration of Watersheds in a Particular Region. J. Irrig. Drain. Eng. 2011, 137, 712–719. [CrossRef]; 14. U.S. Department of Agriculture Natural Resources Conservation Service (USDA-NRSC); C.E.D. Urban Hydrology for Small Watersheds, Technical Release 55 (TR-55); U.S. Department of Agriculture Natural Resources Conservation Service (USDA-NRSC), C.E.D.: Washington, DC, USA, 1986.; 15. Kirpich, Z.P. Time of concentration of small agricultural watersheds. Civ. Eng. 1940, 10, 362.; 16. Gericke, O.J.; Smithers, J.C. Are estimates of catchment response time inconsistent as used in current flood hydrology practice in South Africa? J. S. Afr. Inst. Civ. Eng. 2016, 58, 2–15. [CrossRef]; 17. Miller, W. Evolving a shortcut for design of storm sewers. Munic 1951, 89, 42–59.; 18. Highways, C.D.O. California Culvert Practice; Department of Public Works, Division of Highways: Sacramento, CA, USA, 1960.; 19. Ravazzani, G.; Boscarello, L.; Cislaghi, A.; Mancini, M. Review of Time-of-Concentration Equations and a New Proposal in Italy. J. Hydrol. Eng. 2019, 24, 04019039. [CrossRef]; 20. Carter, R.W. Magnitude and Frequency of Floods in Suburban Areas; U.S. Geological Survey: Reston, VA, USA, 1961.; 21. Federal Aviation Agency (FAA). Airport Drainage; Department of Transport Advisory Circular: Washington, DC, USA, 1970.; 22. Welle, P.I.; Woodward, D. Engineering Hydrology—Time of Concentration; Bloomsbury Publishing: London, UK, 1986.; 23. Texas Department of Transportation. Hydraulic Design Manual (Revised); Texas Department of Transportation: Austin, TX, USA, 1994.; 24. Li, M.-H.; Chibber, P. Overland Flow Time of Concentration on Very Flat Terrains. Transp. Res. Rec. J. Transp. Res. Board 2008, 2060, 133–140. [CrossRef]; 25. Li, M.-H.; Chibber, P.; Cahill, A.T. Estimating time of concentration of overland flow on very flat terrains. In 2005 ASAE Annual Meeting; American Society of Agricultural and Biological Engineers: St. Joseph, MI, USA, 2005; p. 1.; 26. Chow, T.; Maidment, D.; Mays, L. Applied Hydrology; McGraw-Hill: New York, NY, USA, 1988.; 27. Williams, G. Flood discharges and the dimensions of spillways in India. Engineering 1922, 134, 321–322.; 28. Fang, X.; Thompson, D.B.; Cleveland, T.G.; Pradhan, P.; Malla, R. Time of concentration estimated using watershed parameters determined by automated and manual methods. J. Irrig. Drain. Eng. 2008, 134, 202–211. [CrossRef]; 29. Kerby, W.S. Time of concentration for overland flow. Civ. Eng. 1959, 29, 60.; 30. González, Á.; Molina, J.; Meza, B.; Viloria, O.; Tesfagiorgis, K.; Mouthón, J. Assessing the Performance of Different Time of Concentration Equations in Urban Ungauged Watersheds: Case Study of Cartagena de Indias, Colombia. Hydrology 2020, 7, 47. [CrossRef]; 31. Coronado-Hernández, Ó.E.; Merlano-Sabalza, E.; Díaz-Vergara, Z.; Coronado-Hernández, J.R. Selection of Hydrological Probability Distributions for Extreme Rainfall Events in the Regions of Colombia. Water 2020, 12, 1397. [CrossRef]; 32. Kobiyama, M.; Grison, F.; Lino, J.F.L.; Silva, R.V. Time of concentration in the UFSC campus catchment, Florianópolis-SC (Brazil), calculated with morfometric and hydrological methods. In Proceedings of the Regional Conference on Geomorphology, UFG-IUG, Goiania, Brazil, 6–10 September 2006; Volume 110.; 33. Krisnayanti, D.; Bunganaen, W.; Frans, J.H.; Serán, Y.; Legono, D. Curve Number Estimation for Ungauged Watershed in Semi-Arid Region. Civ. Eng. J. 2021, 7, 1070–1083. [CrossRef]; 34. Michailidi, E.M.; Antoniadi, S.; Koukouvinos, A.; Bacchi, B.; Efstratiadis, A. Timing the time of concentration: Shedding light on a paradox. Hydrol. Sci. J. 2018, 63, 721–740. [CrossRef]; 35. Lopes, A.L. Performance of time of concentration formulas for urban and rural basins. Rev. Bras. Recur. Hídricos 2005, 10, 5–23.; 20; 18; 14; https://hdl.handle.net/11323/10788; Corporación Universidad de la Costa; REDICUC – Repositorio CUC; https://repositorio.cuc.edu.co/

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    مصطلحات موضوعية: Distribution center, Optimization, Waving, Supply chain, Slotting

    وصف الملف: 6 páginas; application/pdf

    Relation: Procedia Computer Science; [1] Sainathuni, B., Parikh, P. J., Zhang, X., & Kong, N. (2014). The warehouse-inventorytransportation problem for supply chains. European Journal of Operational Research, 237(2), 690-700.; [2] Bartholdi, J. J., & Hackman, S. T. (2011). Warehouse & Distribution Science: Release 0.89. Supply Chain and Logistics Institute.; [3] Yingde, L. I., & Smith, J. S. (2012). Dynamic slotting optimization based on skus correlations in a zone-based wave-picking system.; [4] Theys, C., Bräysy, O., Dullaert, W., & Raa, B. (2010). Using a TSP heuristic for routing order pickers in warehouses. European Journal of Operational Research, 200(3), 755-763.; [5] Hwang*, H., Oh, Y. H., & Lee, Y. K. (2004). An evaluation of routing policies for orderpicking operations in low-level picker-to-part system. International Journal of Production Research, 42(18), 3873-3889.; [6] Zhang, G., Nishi, T., Turner, S. D., Oga, K., & Li, X. (2017). An integrated strategy for a production planning and warehouse layout problem: Modeling and solution approaches. Omega, 68, 85-94.; [7] Liang, J., Wu, Z., Zhu, C., & Zhang, Z. H. (2020). An estimation distribution algorithm for wave-picking warehouse management. Journal of Intelligent Manufacturing, 1-14.; [8] Leng, J., Yan, D., Liu, Q., Zhang, H., Zhao, G., Wei, L., . & Chen, X. (2019). Digital twindriven joint optimization of packing and storage assignment in large-scale automated high-rise warehouse product-service system. International Journal of Computer Integrated Manufacturing, 1-18.; [9] Muharni, Y., & Khoirunnisa, M. (2019, May). Warehouse layout designing of slab using dedicated storage and particle swarm optimization. In IOP Conference Series: Materials Science and Engineering (Vol. 532, No. 1, p. 012003). IOP Publishing.; [10] Marvel, H. P., & Peck, J. (2008). Turnover Inventory and product variety. The Journal of Law and Economics, 51(3), 461-478.; 593; 588; 203; https://hdl.handle.net/11323/10795; Corporación Universidad de la Costa; REDICUC – Repositorio CUC; https://repositorio.cuc.edu.co/

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    جغرافية الموضوع: Colombia, Atlántico

    وصف الملف: 24 páginas; application/pdf

    Relation: Water; 1. Chow, V.T.; Maidment, D.R.; Mays, L.W. Applied Hydrology, 1st ed.; McGraw-Hill: New York, NY, USA, 1988; pp. 350–376.; 2. Ceballos, A.; Schnabel, S. Hydrological behaviour of a small catchment in the dehesa landuse system (Extremadura, SW Spain). J. Hydrol. 1998, 210, 146–160. [CrossRef]; 3. Dusek, J.; Vogel, T. Hillslope-storage and rainfall-amount thresholds as controls of preferential stormflow. J. Hydrol. 2016, 534, 590–605. [CrossRef]; 4. Berne, A.; Delrieu, G.; Creutin, J.D.; Obled, C. Temporal and spatial resolution of rainfall measurements required for urban hydrology. J. Hydrol. 2004, 299, 166–179. [CrossRef]; 5. Manfreda, S.; Fiorentino, M.; Iacobellis, V. DREAM A distributed model for runoff, evapotranspiration, and antecedent soil moisture simulation. Adv. Geosci. 2005, 2, 31–39. [CrossRef]; 6. Lazzari, M.; Piccarreta, M.; Ray, L.R.; Manfreda, S. Modeling Antecedent Soil Moisture to Constrain Rainfall Thresholds for Shallow Landslides Occurrence. In Landslides: Investigation and Monitoring; Ram, L.R., Lazzari, M., Eds.; IntechOpen: London, UK, 2020. Available online: https://www.intechopen.com/chapters/72592 (accessed on 1 February 2022).; 7. Lazzari, M.; Piccarreta, M.; Manfreda, S. The role of antecedent soil moisture conditions on rainfall-triggered shallow landslides. Nat. Hazards Earth Syst. Sci. 2018, 1–11. Available online: https://nhess.copernicus.org/preprints/nhess-2018-371/ (accessed on 20 February 2022). [CrossRef]; 8. Poveda, G.; Jaramillo, A.; Gil, M.M.; Quinceno, N.; Mantilla, R.I. Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia. Water Resour. Res. 2001, 37, 2169–2178. [CrossRef]; 9. Kim, G.-S.; Lee, S.-g.; Lee, J.; Park, E.; Song, C.; Hong, M.; Ko, Y.-J.; Lee, W.-K. Effects of Forest and Agriculture Land Covers on Organic Carbon Flux Mediated through Precipitation. Water 2022, 14, 623. [CrossRef]; 11. Waylen, P.; Poveda, G. El Niño-Southern Oscillation and aspects of western South American hydro-climatology. Hydrol. Process 2002, 16, 1247–1260. [CrossRef]; 12. de Alcântara, L.R.P.; Coutinho, A.P.; dos Santos Neto, S.M.; Carvalho de Gusmão da Cunha Rabelo, A.E.; Antonino, A.C.D. Modeling of the Hydrological Processes in Caatinga and Pasture Areas in the Brazilian Semi-Arid. Water 2021, 13, 1877. [CrossRef]; 13. U.S. Water Resources Council. A Uniform Technique for Determining Flood Flow Frequencies; Bulletin 15; U.S. Water Resources Council: Washington, DC, USA, 1967.; 14. Cunnane, C. Methods and merits of regional flood frequency analysis. J. Hydrol. 1988, 100, 269–290. [CrossRef]; 15. Webster, V.L.; Stedinger, J. Log-Pearson Type III Distribution and Its Application in Flood Frequency Analysis. I: Distribution Characteristics. J. Hydrol. Eng. 2007, 12, 482–491.; 16. Burgess, C.P.; Taylor, M.A.; Stephenson, T.; Mandal, A. Frequency analysis, infilling and trends for extreme precipitation for Jamaica (1895–2100). J. Hydrol. 2015, 3, 424–443. [CrossRef]; 17. González-Álvarez, Á.; Viloria-Marimón, O.; Coronado-Hernández, Ó.E.; Vélez-Pereira, A.; Tesfagiorgis, K.; Coronado-Hernández, J.R. Isohyetal Maps of Daily Maximum Rainfall for Different Return Periods for the Colombian Caribbean Region. Water 2019, 11, 358. [CrossRef]; 18. Pizarro, R.; Ingram, B.; Gonzalez-Leiva, F.; Valdés-Pineda, R.; Sangüesa, C.; Delgado, N.; García-Chevesich, P.; Valdés, J.B. WEBSEIDF: A Web-Based System for the Estimation of IDF Curves in Central Chile. Hydrology 2018, 5, 40. [CrossRef]; 19. Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Control 1974, 19, 716–723. [CrossRef]; 20. Akaike, H. Information theory and an extension of the maximum likelihood principle. In Selected Papers of Hirotugu Akaike; Springer: Berlin/Heidelberg, Germany, 1998; pp. 199–213.; 21. Salas, J.D.; Obeysekera, J.; Vogel, R.M. Techniques for assessing water infrastructure for nonstationary extreme events: A review. Hydrol. Sci. J. 2018, 63, 325–352. [CrossRef]; 22. Ikechukwu, M.N.; Ebinne, E.; Idorenyin, U.; Raphael, N.I. Accuracy Assessment and Comparative Analysis of IDW, Spline and Kriging in Spatial Interpolation of Landform (Topography): An Experimental Study. Earth Environ. Sci. 2017, 9, 354–371. [CrossRef]; 23. Ngongondo, C.; Li, L.; Gong, L.; Xu, C.-Y.; Alemaw, B.F. Flood frequency under changing climate in the upper kafue river basin, southern africa: A large scale hydrological model application. Stoch. Environ. Res. Risk Assess. 2013, 27, 1883–1898. [CrossRef]; 24. López, J.; Goñi, M.; Martín, I.S.; Erro, J. Regional frequency analysis of annual maximum daily rainfall in Navarra. Quantiles mapping. Ing. Del Agua 2019, 23, 33–51. [CrossRef]; 25. Bhunia, G.S.; Shit, P.K.; Maiti, R. Comparison of GIS-based interpolation methods for spatial distribution of soil organic carbon (SOC). J. Saudi Soc. Agric. Sci. 2018, 17, 114–126. [CrossRef]; 26. Vargas, A.; Santos, A.; Cárdenas, E.; Obregón, N. Distribution and spatial interpolation of rainfall in Bogotá, Colombia. Dyna 2011, 167, 151–159.; 27. Simpson, G.; Wu, Y.H. Accuracy and Effort of Interpolation and Sampling: Can GIS Help Lower Field Costs? Int. J. Geo-Inf. 2014, 3, 1317–1333. [CrossRef]; 28. Mohamed, M.; Attia, K.; Azab, S. ssessment of Coastal Vulnerability to Climate Change Impacts using GIS and Remote Sensing: A Case Study of Al-Alamein New City. J. Clean. Prod. 2021, 290, 125723.; 29. Malam Issa, O.; Valentin, C.; Rajot, J.L.; Cerdan, O.; Desprats, J.F.; Bouchet, T. Runoff generation fostered by physical and biological crusts in semi-arid sandy soils. Geoderma 2011, 167–168, 22–29. [CrossRef]; 30. Dunne, T. Relation of field studies and modeling in the prediction of storm runoff. J. Hydrol. 1983, 65, 25–48. [CrossRef]; 31. Barling, R.D.; Moore, I.D.; Grayson, R.B. A quasi-dynamic wetness index for characterizing the spatial distribution of zones of surface saturation and soil water content. Water Resour. Res. 1994, 30, 1029–1044. [CrossRef]; 24; 14; Salgado-Cassiani, J.J.; Coronado-Hernández, O.E.; Gatica, G.; Linfati, R.; Coronado-Hernández, J.R. Probabilistic Approach to Determine the Spatial Distribution of the Antecedent Moisture Conditions for Different Return Periods in the Atlántico Region, Colombia. Water 2022, 14, 1217. https://doi.org/ 10.3390/w14081217; https://hdl.handle.net/11323/9219; https://doi.org/ 10.3390/w14081217; Corporación Universidad de la Costa; REDICUC - Repositorio CUC; https://repositorio.cuc.edu.co/

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