Characterization of Structural Properties in High Reynolds Hydraulic Jump Based on CFD and Physical Modeling Approaches

[EN] A classical hydraulic jump with Froude number (Fr1=6) and Reynolds number (Re1=210,000) was characterized using the computational fluid dynamics (CFD) codes OpenFOAM and FLOW-3D, whose performance was assessed. The results were compared with experimental data from a physical model designed for this purpose. The most relevant hydraulic jump characteristics were investigated, including hydraulic jump efficiency, roller length, free surface profile, distributions of velocity and pressure, and fluctuating variables. The model outcome was also compared with previous results from the literature. Both CFD codes were found to represent with high accuracy the hydraulic jump surface profile, roller length, efficiency, and sequent depths ratio, consistently with previous research. Some significant differences were found between both CFD codes regarding velocity distributions and pressure fluctuations, although in general the results agree well with experimental and bibliographical observations. This finding makes models with these characteristics suitable for engineering applications involving the design and optimization of energy dissipation devices.The research presented herein was possible thanks to the Generalitat Valenciana predoctoral grants [Ref. (2015/7521)], in collaboration with the European Social Funds and to the research project La aireacion del flujo y su implementacion en prototipo para la mejora de la disipacion de energia de la lamina vertiente por resalto hidraulico en distintos tipos de presas (BIA2017-85412-C2-1-R), funded by the Spanish Ministry of Economy.Macián Pérez, JF.; Bayón, A.; García-Bartual, R.; López Jiménez, PA.; Vallés-Morán, FJ. (2020). Characterization of Structural Properties in High Reynolds Hydraulic Jump Based on CFD and Physical Modeling Approaches. Journal of Hydraulic Engineering. 146(12):1-13. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001820S11314612Abdul Khader, M. H., & Elango, K. (1974). TURBULENT PRESSURE FIELD BENEATH A HYDRAULIC JUMP. Journal of Hydraulic Research, 12(4), 469-489. doi:10.1080/00221687409499725Bakhmeteff B. A. and A. E. Matzke. 1936. “The hydraulic jump in terms of dynamic similarity.” In Vol. 101 of Proc. American Society of Civil Engineers 630–647. Reston VA: ASCE.Bayon A. 2017. “Numerical analysis of air-water flows in hydraulic structures using computational fluid dynamics (CFD).” Ph.D. thesis Research Institute of Water and Environmental Engineering Universitat Politècnica de València.Bayon-Barrachina, A., & Lopez-Jimenez, P. A. (2015). Numerical analysis of hydraulic jumps using OpenFOAM. Journal of Hydroinformatics, 17(4), 662-678. doi:10.2166/hydro.2015.041Bayon A. J. F. Macián-Pérez F. J. Vallés-Morán and P. A. López-Jiménez. 2019. “Effect of RANS turbulence model in hydraulic jump CFD simulations.” In E-proc. 38th IAHR World Congress. Panama City Panama: Spanish Ministry of Economy.Bayon, A., Toro, J. P., Bombardelli, F. A., Matos, J., & López-Jiménez, P. A. (2018). Influence of VOF technique, turbulence model and discretization scheme on the numerical simulation of the non-aerated, skimming flow in stepped spillways. Journal of Hydro-environment Research, 19, 137-149. doi:10.1016/j.jher.2017.10.002Bayon, A., Valero, D., García-Bartual, R., Vallés-Morán, F. ​José, & López-Jiménez, P. A. (2016). Performance assessment of OpenFOAM and FLOW-3D in the numerical modeling of a low Reynolds number hydraulic jump. Environmental Modelling & Software, 80, 322-335. doi:10.1016/j.envsoft.2016.02.018Bennett, N. D., Croke, B. F. W., Guariso, G., Guillaume, J. H. A., Hamilton, S. H., Jakeman, A. J., … Andreassian, V. (2013). 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Journal of Computational Physics, 39(1), 201-225. doi:10.1016/0021-9991(81)90145-5Ho, D. K. H., & Riddette, K. M. (2010). Application of computational fluid dynamics to evaluate hydraulic performance of spillways in australia. Australian Journal of Civil Engineering, 6(1), 81-104. doi:10.1080/14488353.2010.11463946Jesudhas, V., Balachandar, R., Roussinova, V., & Barron, R. (2018). Turbulence Characteristics of Classical Hydraulic Jump Using DES. Journal of Hydraulic Engineering, 144(6), 04018022. doi:10.1061/(asce)hy.1943-7900.0001427Jesudhas, V., Roussinova, V., Balachandar, R., & Barron, R. (2017). Submerged Hydraulic Jump Study Using DES. Journal of Hydraulic Engineering, 143(3), 04016091. doi:10.1061/(asce)hy.1943-7900.0001231KIM, J. (2004). A numerical study of the effects of ambient wind direction on flow and dispersion in urban street canyons using the RNG k?? turbulence model. 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Experimental Study on Single-Hole Injection of Kerosene into Pressurized Quiescent Environments. Journal of Energy Engineering, 144(3), 04018014. doi:10.1061/(asce)ey.1943-7897.0000536Ma, J., Oberai, A. A., Lahey, R. T., & Drew, D. A. (2011). Modeling air entrainment and transport in a hydraulic jump using two-fluid RANS and DES turbulence models. Heat and Mass Transfer, 47(8), 911-919. doi:10.1007/s00231-011-0867-8McCorquodale, J. A., & Khalifa, A. (1983). Internal Flow in Hydraulic Jumps. Journal of Hydraulic Engineering, 109(5), 684-701. doi:10.1061/(asce)0733-9429(1983)109:5(684)McDonald P. W. 1971. “The computation of transonic flow through two-dimensional gas turbine cascades.” In Proc. ASME 1971 Int. Gas Turbine Conf. and Products Show. Houston: International Gas Turbine Institute.Mossa, M. (1999). On the oscillating characteristics of hydraulic jumps. 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Evaluation of different heat transfer conditions on an automotive turbocharger

This paper presents a combination of theoretical and experimental investigations for determining the main heat fluxes within a turbocharger. These investigations consider several engine speeds and loads as well as different methods of conduction, convection, and radiation heat transfer on the turbocharger. A one-dimensional heat transfer model of the turbocharger has been developed in combination with simulation of a turbocharged engine that includes the heat transfer of the turbocharger. Both the heat transfer model and the simulation were validated against experimental measurements. Various methods were compared for calculating heat transfer from the external surfaces of the turbocharger, and one new method was suggested. The effects of different heat transfer conditions were studied on the heat fluxes of the turbocharger using experimental techniques. The different heat transfer conditions on the turbocharger created dissimilar temperature gradients across the turbocharger. The results show that changing the convection heat transfer condition around the turbocharger affects the heat fluxes more noticeably than changing the radiation and conduction heat transfer conditions. Moreover, the internal heat transfers from the turbine to the bearing housing and from the bearing housing to the compressor are significant, but there is an order of magnitude difference between these heat transfer rates.The Swedish Energy Agency and KTH Royal Institute of Technology sponsored this work within the Competence Centre for Gas Exchange (CCGEx).Aghaali, H.; Angström, H.; Serrano Cruz, JR. (2015). Evaluation of different heat transfer conditions on an automotive turbocharger. International Journal of Engine Research. 16(2):137-151. doi:10.1177/1468087414524755S137151162Romagnoli, A., & Martinez-Botas, R. (2012). Heat transfer analysis in a turbocharger turbine: An experimental and computational evaluation. Applied Thermal Engineering, 38, 58-77. doi:10.1016/j.applthermaleng.2011.12.022Romagnoli, A., & Martinez-Botas, R. (2009). Heat Transfer on a Turbocharger Under Constant Load Points. Volume 5: Microturbines and Small Turbomachinery; Oil and Gas Applications. doi:10.1115/gt2009-59618Baines, N., Wygant, K. D., & Dris, A. (2010). The Analysis of Heat Transfer in Automotive Turbochargers. Journal of Engineering for Gas Turbines and Power, 132(4). doi:10.1115/1.3204586Serrano, J. R., Olmeda, P., Páez, A., & Vidal, F. (2010). An experimental procedure to determine heat transfer properties of turbochargers. Measurement Science and Technology, 21(3), 035109. doi:10.1088/0957-0233/21/3/035109Bohn, D., Heuer, T., & Kusterer, K. (2005). Conjugate Flow and Heat Transfer Investigation of a Turbo Charger. Journal of Engineering for Gas Turbines and Power, 127(3), 663-669. doi:10.1115/1.1839919Galindo, J., Luján, J. M., Serrano, J. R., Dolz, V., & Guilain, S. (2006). Description of a heat transfer model suitable to calculate transient processes of turbocharged diesel engines with one-dimensional gas-dynamic codes. Applied Thermal Engineering, 26(1), 66-76. doi:10.1016/j.applthermaleng.2005.04.010Sirakov, B., & Casey, M. (2012). Evaluation of Heat Transfer Effects on Turbocharger Performance. Journal of Turbomachinery, 135(2). doi:10.1115/1.4006608Serrano, J., Olmeda, P., Arnau, F., Reyes-Belmonte, M., & Lefebvre, A. (2013). Importance of Heat Transfer Phenomena in Small Turbochargers for Passenger Car Applications. SAE International Journal of Engines, 6(2), 716-728. doi:10.4271/2013-01-0576Larsson, P.-I., Westin, F., Andersen, J., Vetter, J., & Zumeta, A. (2009). Efficient turbo charger testing. MTZ worldwide, 70(7-8), 16-21. doi:10.1007/bf03226965Aghaali, H., & Ångström, H.-E. (2012). Turbocharged SI-Engine Simulation With Cold and Hot-Measured Turbocharger Performance Maps. Volume 5: Manufacturing Materials and Metallurgy; Marine; Microturbines and Small Turbomachinery; Supercritical CO2 Power Cycles. doi:10.1115/gt2012-68758Leufven, O., & Eriksson, L. (2012). Investigation of compressor correction quantities for automotive applications. International Journal of Engine Research, 13(6), 588-606. doi:10.1177/146808741243901

Analysis of the Flow in a Typified USBR II Stilling Basin through a Numerical and Physical Modeling Approach

[EN] Adaptation of stilling basins to higher discharges than those considered for their design implies deep knowledge of the flow developed in these structures. To this end, the hydraulic jump occurring in a typified United States Bureau of Reclamation Type II (USBR II) stilling basin was analyzed using a numerical and experimental modeling approach. A reduced-scale physical model to conduct an experimental campaign was built and a numerical computational fluid dynamics (CFD) model was prepared to carry out the corresponding simulations. Both models were able to successfully reproduce the case study in terms of hydraulic jump shape, velocity profiles, and pressure distributions. The analysis revealed not only similarities to the flow in classical hydraulic jumps but also the influence of the energy dissipation devices existing in the stilling basin, all in good agreement with bibliographical information, despite some slight differences. Furthermore, the void fraction distribution was analyzed, showing satisfactory performance of the physical model, although the numerical approach presented some limitations to adequately represent the flow aeration mechanisms, which are discussed herein. Overall, the presented modeling approach can be considered as a useful tool to address the analysis of free surface flows occurring in stilling basins.This research was funded by 'Generalitat Valenciana predoctoral grants (Grant number [2015/7521])', in collaboration with the European Social Funds and by the research project: 'La aireacion del flujo y su implementacion en prototipo para la mejora de la disipacion de energia de la lamina vertiente por resalto hidraulico en distintos tipos de presas' (BIA2017-85412-C2-1-R), funded by the Spanish Ministry of Economy.Macián Pérez, JF.; García-Bartual, R.; Huber, B.; Bayón, A.; Vallés-Morán, FJ. (2020). Analysis of the Flow in a Typified USBR II Stilling Basin through a Numerical and Physical Modeling Approach. Water. 12(1):1-20. https://doi.org/10.3390/w12010227S120121Bayon, A., Valero, D., García-Bartual, R., Vallés-Morán, F. ​José, & López-Jiménez, P. A. (2016). Performance assessment of OpenFOAM and FLOW-3D in the numerical modeling of a low Reynolds number hydraulic jump. Environmental Modelling & Software, 80, 322-335. doi:10.1016/j.envsoft.2016.02.018Chanson, H. (2008). Turbulent air–water flows in hydraulic structures: dynamic similarity and scale effects. Environmental Fluid Mechanics, 9(2), 125-142. doi:10.1007/s10652-008-9078-3Heller, V. (2011). Scale effects in physical hydraulic engineering models. Journal of Hydraulic Research, 49(3), 293-306. doi:10.1080/00221686.2011.578914Chanson, H. (2013). Hydraulics of aerated flows:qui pro quo? Journal of Hydraulic Research, 51(3), 223-243. doi:10.1080/00221686.2013.795917Blocken, B., & Gualtieri, C. (2012). Ten iterative steps for model development and evaluation applied to Computational Fluid Dynamics for Environmental Fluid Mechanics. Environmental Modelling & Software, 33, 1-22. doi:10.1016/j.envsoft.2012.02.001Wang, H., & Chanson, H. (2015). Experimental Study of Turbulent Fluctuations in Hydraulic Jumps. Journal of Hydraulic Engineering, 141(7), 04015010. doi:10.1061/(asce)hy.1943-7900.0001010Valero, D., Viti, N., & Gualtieri, C. (2018). Numerical Simulation of Hydraulic Jumps. Part 1: Experimental Data for Modelling Performance Assessment. Water, 11(1), 36. doi:10.3390/w11010036Viti, N., Valero, D., & Gualtieri, C. (2018). Numerical Simulation of Hydraulic Jumps. Part 2: Recent Results and Future Outlook. Water, 11(1), 28. doi:10.3390/w11010028Bayon-Barrachina, A., & Lopez-Jimenez, P. A. (2015). Numerical analysis of hydraulic jumps using OpenFOAM. Journal of Hydroinformatics, 17(4), 662-678. doi:10.2166/hydro.2015.041Teuber, K., Broecker, T., Bayón, A., Nützmann, G., & Hinkelmann, R. (2019). CFD-modelling of free surface flows in closed conduits. Progress in Computational Fluid Dynamics, An International Journal, 19(6), 368. doi:10.1504/pcfd.2019.103266Chachereau, Y., & Chanson, H. (2011). Free-surface fluctuations and turbulence in hydraulic jumps. Experimental Thermal and Fluid Science, 35(6), 896-909. doi:10.1016/j.expthermflusci.2011.01.009Zhang, G., Wang, H., & Chanson, H. (2012). Turbulence and aeration in hydraulic jumps: free-surface fluctuation and integral turbulent scale measurements. Environmental Fluid Mechanics, 13(2), 189-204. doi:10.1007/s10652-012-9254-3Mossa, M. (1999). On the oscillating characteristics of hydraulic jumps. Journal of Hydraulic Research, 37(4), 541-558. doi:10.1080/00221686.1999.9628267Chanson, H., & Brattberg, T. (2000). Experimental study of the air–water shear flow in a hydraulic jump. International Journal of Multiphase Flow, 26(4), 583-607. doi:10.1016/s0301-9322(99)00016-6Murzyn, F., Mouaze, D., & Chaplin, J. R. (2005). Optical fibre probe measurements of bubbly flow in hydraulic jumps. International Journal of Multiphase Flow, 31(1), 141-154. doi:10.1016/j.ijmultiphaseflow.2004.09.004Gualtieri, C., & Chanson, H. (2007). Experimental analysis of Froude number effect on air entrainment in the hydraulic jump. Environmental Fluid Mechanics, 7(3), 217-238. doi:10.1007/s10652-006-9016-1Chanson, H., & Gualtieri, C. (2008). Similitude and scale effects of air entrainment in hydraulic jumps. Journal of Hydraulic Research, 46(1), 35-44. doi:10.1080/00221686.2008.9521841Ho, D. K. H., & Riddette, K. M. (2010). Application of computational fluid dynamics to evaluate hydraulic performance of spillways in australia. Australian Journal of Civil Engineering, 6(1), 81-104. doi:10.1080/14488353.2010.11463946Dong, Wang, Vetsch, Boes, & Tan. (2019). Numerical Simulation of Air–Water Two-Phase Flow on Stepped Spillways Behind X-Shaped Flaring Gate Piers under Very High Unit Discharge. Water, 11(10), 1956. doi:10.3390/w11101956Toso, J. W., & Bowers, C. E. (1988). Extreme Pressures in Hydraulic‐Jump Stilling Basins. Journal of Hydraulic Engineering, 114(8), 829-843. doi:10.1061/(asce)0733-9429(1988)114:8(829)Houichi, L., Ibrahim, G., & Achour, B. (2006). Experiments for the Discharge Capacity of the Siphon Spillway Having the Creager-Ofitserov Profile. International Journal of Fluid Mechanics Research, 33(5), 395-406. doi:10.1615/interjfluidmechres.v33.i5.10Padulano, R., Fecarotta, O., Del Giudice, G., & Carravetta, A. (2017). Hydraulic Design of a USBR Type II Stilling Basin. Journal of Irrigation and Drainage Engineering, 143(5), 04017001. doi:10.1061/(asce)ir.1943-4774.0001150Hirt, C. ., & Nichols, B. . (1981). Volume of fluid (VOF) method for the dynamics of free boundaries. 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Physics of Fluids A: Fluid Dynamics, 4(7), 1510-1520. doi:10.1063/1.858424Li, S., & Zhang, J. (2018). Numerical Investigation on the Hydraulic Properties of the Skimming Flow over Pooled Stepped Spillway. Water, 10(10), 1478. doi:10.3390/w10101478Zhang, W., Wang, J., Zhou, C., Dong, Z., & Zhou, Z. (2018). Numerical Simulation of Hydraulic Characteristics in A Vortex Drop Shaft. Water, 10(10), 1393. doi:10.3390/w10101393Xiang, M., Cheung, S. C. P., Tu, J. Y., & Zhang, W. H. (2014). A multi-fluid modelling approach for the air entrainment and internal bubbly flow region in hydraulic jumps. Ocean Engineering, 91, 51-63. doi:10.1016/j.oceaneng.2014.08.016Procedure for Estimation and Reporting of Uncertainty Due to Discretization in CFD Applications. (2008). Journal of Fluids Engineering, 130(7), 078001. doi:10.1115/1.2960953Cartellier, A., & Achard, J. L. (1991). Local phase detection probes in fluid/fluid two‐phase flows. 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H., Bremen, R., & Kawagoshi, N. (1990). Classical hydraulic jump: length of roller. Journal of Hydraulic Research, 28(5), 591-608. doi:10.1080/00221689009499048Bennett, N. D., Croke, B. F. W., Guariso, G., Guillaume, J. H. A., Hamilton, S. H., Jakeman, A. J., … Andreassian, V. (2013). Characterising performance of environmental models. Environmental Modelling & Software, 40, 1-20. doi:10.1016/j.envsoft.2012.09.011McCorquodale, J. A., & Khalifa, A. (1983). Internal Flow in Hydraulic Jumps. Journal of Hydraulic Engineering, 109(5), 684-701. doi:10.1061/(asce)0733-9429(1983)109:5(684)Kirkgöz, M. S., & Ardiçlioğlu, M. (1997). Velocity Profiles of Developing and Developed Open Channel Flow. Journal of Hydraulic Engineering, 123(12), 1099-1105. doi:10.1061/(asce)0733-9429(1997)123:12(1099

Computational fluid dynamics assessment of subcooled flow boiling in internal-combustion engine-like conditions at low flow velocities with a volume-of-fluid model and a two-fluid model

The use of subcooled flow boiling is a convenient option for the thermal management of downsized engines, but proper control of the phenomenon requires the accurate prediction of heat transfer at the coolant side, for which the use of computational fluid dynamics is a suitable alternative. While in most of the applications found to engine cooling a single-fluid equivalent method is used, in this paper the performance of a twofluid method is evaluated in engine-like conditions with special interest in the low velocity range. The results indicate that the description of the process at low velocities provided by the two-fluid method is better than that of a single-fluid model, while model calibration is simpler and more robust and the computational cost is substantially reduced.The equipment used in this work was partially supported by FEDER project funds 'Dotacion de infraestructuras cientifico tecnicas para el Centro Integral de Mejora Energetica y Medioambiental de Sistemas de Transporte' (grant number FEDER-ICTS-2012-06), framed in the operational program of the unique scientific and technical infrastructure of the Ministry of Science and Innovation of Spain. This work was partially supported by Senacyt Panama (Omar Cornejo, grant 797-7-2)Torregrosa, AJ.; Olmeda González, PC.; Gil Megías, A.; Cornejo, O. (2015). Computational fluid dynamics assessment of subcooled flow boiling in internal-combustion engine-like conditions at low flow velocities with a volume-of-fluid model and a two-fluid model. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 229(13):1830-1839. https://doi.org/10.1177/0954407015571674S1830183922913Pang, H. H., & Brace, C. J. (2004). Review of engine cooling technologies for modern engines. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 218(11), 1209-1215. doi:10.1243/0954407042580110Burke, R. D., Brace, C. J., Hawley, J. G., & Pegg, I. (2010). Review of the systems analysis of interactions between the thermal, lubricant, and combustion processes of diesel engines. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 224(5), 681-704. doi:10.1243/09544070jauto1301Steiner, H., Brenn, G., Ramstorfer, F., & Breitschadel, B. (2011). Increased Cooling Power with Nucleate Boiling Flow in Automotive Engine Applications. New Trends and Developments in Automotive System Engineering. doi:10.5772/13489Li, Z., Huang, R.-H., & Wang, Z.-W. (2011). Subcooled boiling heat transfer modelling for internal combustion engine applications. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 226(3), 301-311. doi:10.1177/0954407011417349Hawley, J. G., Wilson, M., Campbell, N. A. F., Hammond, G. P., & Leathard, M. J. (2004). Predicting boiling heat transfer using computational fluid dynamics. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 218(5), 509-520. doi:10.1243/095440704774061165Li, G., Fu, S., Liu, Y., Liu, Y., Bai, S., & Cheng, L. (2009). A homogeneous flow model for boiling heat transfer calculation based on single phase flow. Energy Conversion and Management, 50(7), 1862-1868. doi:10.1016/j.enconman.2008.12.029Chen, J. C. (1966). Correlation for Boiling Heat Transfer to Saturated Fluids in Convective Flow. Industrial & Engineering Chemistry Process Design and Development, 5(3), 322-329. doi:10.1021/i260019a023Torregrosa, A. J., Broatch, A., Olmeda, P., & Cornejo, O. (2014). Experiments on subcooled flow boiling in I.C. engine-like conditions at low flow velocities. Experimental Thermal and Fluid Science, 52, 347-354. doi:10.1016/j.expthermflusci.2013.10.004Robinson, K., Hawley, J. G., & Campbell, N. A. F. (2003). Experimental and modelling aspects of flow boiling heat transfer for application to internal combustion engines. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 217(10), 877-889. doi:10.1243/095440703769683289Lee, H. S., & O’Neill, A. T. (2009). Forced convection and nucleate boiling on a small flat heater in a rectangular duct: Experiments with two working fluids, a 50–50 ethylene glycol—water mixture, and water. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 223(2), 203-219. doi:10.1243/09544070jauto1008Biswas, R., & Strawn, R. C. (1998). Tetrahedral and hexahedral mesh adaptation for CFD problems. Applied Numerical Mathematics, 26(1-2), 135-151. doi:10.1016/s0168-9274(97)00092-5Hernandez-Perez, V., Abdulkadir, M., & Azzopardi, B. J. (2011). Grid Generation Issues in the CFD Modelling of Two-Phase Flow in a Pipe. The Journal of Computational Multiphase Flows, 3(1), 13-26. doi:10.1260/1757-482x.3.1.13Pioro, I. L., Rohsenow, W., & Doerffer, S. S. (2004). Nucleate pool-boiling heat transfer. II: assessment of prediction methods. International Journal of Heat and Mass Transfer, 47(23), 5045-5057. doi:10.1016/j.ijheatmasstransfer.2004.06.020Saiz Jabardo, J. M. (2010). An Overview of Surface Roughness Effects on Nucleate Boiling Heat Transfer~!2009-10-31~!2010-01-01~!2010-04-16~! The Open Transport Phenomena Journal, 2(1), 24-34. doi:10.2174/1877729501002010024Podowski, M. Z. (2012). TOWARD MECHANISTIC MODELING OF BOILING HEAT TRANSFER. Nuclear Engineering and Technology, 44(8), 889-896. doi:10.5516/net.02.2012.720Lo, S., & Osman, J. (2012). CFD Modeling of Boiling Flow in PSBT 5×5 Bundle. Science and Technology of Nuclear Installations, 2012, 1-8. doi:10.1155/2012/795935Del Valle, V. H., & Kenning, D. B. R. (1985). Subcooled flow boiling at high heat flux. International Journal of Heat and Mass Transfer, 28(10), 1907-1920. doi:10.1016/0017-9310(85)90213-3Cole, R. (1960). A photographic study of pool boiling in the region of the critical heat flux. AIChE Journal, 6(4), 533-538. doi:10.1002/aic.69006040

A Study of the Transient Response of Duct Junctions: Measurements and Gas-Dynamic Modeling with a Staggered Mesh Finite Volume Approach

[EN] Duct junctions play a major role in the operation and design of most piping systems. The objective of this paper is to establish the potential of a staggered mesh finite volume model as a way to improve the description of the effect of simple duct junctions on an otherwise one-dimensional flow system, such as the intake or exhaust of an internal combustion engine. Specific experiments have been performed in which different junctions have been characterized as a multi-port, and that have provided precise and reliable results on the propagation of pressure pulses across junctions. The results obtained have been compared to simulations performed with a staggered mesh finite volume method with different flux limiters and different meshes and, as a reference, have also been compared with the results of a more conventional pressure loss- based model. The results indicate that the staggered mesh finite volume model provides a closer description of wave dynamics, even if further work is needed to establish the optimal calculation settings.Manuel Hernandez is partially supported through contract FPI-S2-2015-1064 of Programa de Apoyo para la Investigacin y Desarrollo (PAID) of Universitat Politecnica de Valencia.Torregrosa, AJ.; Broatch, A.; García-Cuevas González, LM.; Hernández-Marco, M. (2017). A Study of the Transient Response of Duct Junctions: Measurements and Gas-Dynamic Modeling with a Staggered Mesh Finite Volume Approach. Applied Sciences. 7(5):1-25. https://doi.org/10.3390/app7050480S12575Payri, F., Reyes, E., & Galindo, J. (2000). Analysis and Modeling of the Fluid-Dynamic Effects in Branched Exhaust Junctions of ICE. Journal of Engineering for Gas Turbines and Power, 123(1), 197-203. doi:10.1115/1.1339988Tang, S. K. (2004). Sound transmission characteristics of Tee-junctions and the associated length corrections. The Journal of the Acoustical Society of America, 115(1), 218-227. doi:10.1121/1.1631830Harrison, M. F., De Soto, I., & Rubio Unzueta, P. L. (2004). A linear acoustic model for multi-cylinder IC engine intake manifolds including the effects of the intake throttle. Journal of Sound and Vibration, 278(4-5), 975-1011. doi:10.1016/j.jsv.2003.12.009Karlsson, M., & Åbom, M. (2011). Quasi-steady model of the acoustic scattering properties of a T-junction. Journal of Sound and Vibration, 330(21), 5131-5137. doi:10.1016/j.jsv.2011.05.012Karlsson, M., & Åbom, M. (2010). Aeroacoustics of T-junctions—An experimental investigation. Journal of Sound and Vibration, 329(10), 1793-1808. doi:10.1016/j.jsv.2009.11.024Corberán, J. M. (1992). A New Constant Pressure Model for N-Branch Junctions. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 206(2), 117-123. doi:10.1243/pime_proc_1992_206_167_02Schmandt, B., & Herwig, H. (2015). The head change coefficient for branched flows: Why «losses» due to junctions can be negative. International Journal of Heat and Fluid Flow, 54, 268-275. doi:10.1016/j.ijheatfluidflow.2015.06.004Shaw, C. T., Lee, D. J., Richardson, S. H., & Pierson, S. (2000). Modelling the Effect of Plenum-Runner Interface Geometry on the Flow Through an Inlet System. SAE Technical Paper Series. doi:10.4271/2000-01-0569Pérez-García, J., Sanmiguel-Rojas, E., Hernández-Grau, J., & Viedma, A. (2006). Numerical and experimental investigations on internal compressible flow at T-type junctions. Experimental Thermal and Fluid Science, 31(1), 61-74. doi:10.1016/j.expthermflusci.2006.02.001Naeimi, H., Domiry, G., Gorji, M., Javadirad, G., & Keshavarz, M. (2011). A parametric design of compact exhaust manifold junction in heavy duty diesel engine using CFD. Thermal Science, 15(4), 1023-1033. doi:10.2298/tsci100417041nSakowitz, A., Mihaescu, M., & Fuchs, L. (2014). Turbulent flow mechanisms in mixing T-junctions by Large Eddy Simulations. International Journal of Heat and Fluid Flow, 45, 135-146. doi:10.1016/j.ijheatfluidflow.2013.06.014Bassett, M. D., Winterbone, D. E., & Pearson, R. J. (2001). Calculation of steady flow pressure loss coefficients for pipe junctions. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 215(8), 861-881. doi:10.1177/095440620121500801Hager, W. H. (1984). An Approximate Treatment of Flow in Branches and Bends. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 198(1), 63-69. doi:10.1243/pime_proc_1984_198_088_02Paul, J., Selamet, A., Miazgowicz, K. D., & Tallio, K. V. (2007). Combining Flow Losses at Circular T-Junctions Representative of Intake Plenum and Primary Runner Interface. SAE Technical Paper Series. doi:10.4271/2007-01-0649Pérez-García, J., Sanmiguel-Rojas, E., & Viedma, A. (2010). New coefficient to characterize energy losses in compressible flow at T-junctions. Applied Mathematical Modelling, 34(12), 4289-4305. doi:10.1016/j.apm.2010.05.005Wang, W., Lu, Z., Deng, K., & Qu, S. (2014). An experimental study of compressible combining flow at 45° T-junctions. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 229(9), 1600-1610. doi:10.1177/0954406214546678Peters, B., & Gosman, A. D. (1993). Numerical Simulation of Unsteady Flow in Engine Intake Manifolds. SAE Technical Paper Series. doi:10.4271/930609Bingham, J. F., & Blair, G. P. (1985). An Improved Branched Pipe Model for Multi-Cylinder Automotive Engine Calculations. Proceedings of the Institution of Mechanical Engineers, Part D: Transport Engineering, 199(1), 65-77. doi:10.1243/pime_proc_1985_199_140_01William-Louis, M. J. P., Ould-El-Hadrami, A., & Tournier, C. (1998). On the calculation of the unsteady compressible flow through an N-branch junction. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 212(1), 49-56. doi:10.1243/0954406981521033Bassett, M. D., Pearson, R. J., Fleming, N. P., & Winterbone, D. E. (2003). A Multi-Pipe Junction Model for One-Dimensional Gas-Dynamic Simulations. SAE Technical Paper Series. doi:10.4271/2003-01-0370Pearson, R. J., Bassett, M. D., Batten, P., Winterbone, D. E., & Weaver, N. W. E. (1999). Multi-Dimensional Wave Propagation in Pipe Junctions. SAE Technical Paper Series. doi:10.4271/1999-01-1186Bassett, M. D., Winterbone, D. E., & Pearson, R. J. (2000). Modelling Engines with Pulse Converted Exhaust Manifolds Using One-Dimensional Techniques. SAE Technical Paper Series. doi:10.4271/2000-01-0290Montenegro, G., Onorati, A., Piscaglia, F., & D’Errico, G. (2007). Integrated 1D-MultiD Fluid Dynamic Models for the Simulation of I.C.E. Intake and Exhaust Systems. SAE Technical Paper Series. doi:10.4271/2007-01-0495Onorati, A., Montenegro, G., D’Errico, G., & Piscaglia, F. (2010). Integrated 1D-3D Fluid Dynamic Simulation of a Turbocharged Diesel Engine with Complete Intake and Exhaust Systems. SAE Technical Paper Series. doi:10.4271/2010-01-1194Montenegro, G., Onorati, A., & Della Torre, A. (2013). The prediction of silencer acoustical performances by 1D, 1D–3D and quasi-3D non-linear approaches. Computers & Fluids, 71, 208-223. doi:10.1016/j.compfluid.2012.10.016Morel, T., Silvestri, J., Goerg, K.-A., & Jebasinski, R. (1999). Modeling of Engine Exhaust Acoustics. SAE Technical Paper Series. doi:10.4271/1999-01-1665Sapsford, S. M., Richards, V. C. M., Amlee, D. R., Morel, T., & Chappell, M. T. (1992). Exhaust System Evaluation and Design by Non-Linear Modeling. SAE Technical Paper Series. doi:10.4271/920686Montenegro, G., Della Torre, A., Onorati, A., Fairbrother, R., & Dolinar, A. (2011). Development and Application of 3D Generic Cells to the Acoustic Modelling of Exhaust Systems. SAE Technical Paper Series. doi:10.4271/2011-01-1526Payri, F., Desantes, J. M., & Broatch, A. (2000). Modified impulse method for the measurement of the frequency response of acoustic filters to weakly nonlinear transient excitations. The Journal of the Acoustical Society of America, 107(2), 731-738. doi:10.1121/1.428256Torregrosa, A. J., Broatch, A., Fernández, T., & Denia, F. D. (2006). Description and measurement of the acoustic characteristics of two-tailpipe mufflers. The Journal of the Acoustical Society of America, 119(2), 723. doi:10.1121/1.2159228Torregrosa, A. J., Broatch, A., Arnau, F. J., & Hernández, M. (2016). A non-linear quasi-3D model with Flux-Corrected-Transport for engine gas-exchange modelling. Journal of Computational and Applied Mathematics, 291, 103-111. doi:10.1016/j.cam.2015.03.034Montenegro, G., Della Torre, A., Onorati, A., & Fairbrother, R. (2013). A Nonlinear Quasi-3D Approach for the Modeling of Mufflers with Perforated Elements and Sound-Absorbing Material. Advances in Acoustics and Vibration, 2013, 1-10. doi:10.1155/2013/546120CMT—Motores Térmicos, Universitat Politècnica de Valènciahttp://www.openwam.org/Ikeda, T., & Nakagawa, T. (1979). On the SHASTA FCT Algorithm for the Equation ∂ρ ∂t + ∂ ∂x (υ(ρ)ρ) = 0. Mathematics of Computation, 33(148), 1157. doi:10.2307/2006453Toro, E. F., Spruce, M., & Speares, W. (1994). Restoration of the contact surface in the HLL-Riemann solver. Shock Waves, 4(1), 25-34. doi:10.1007/bf01414629Van Leer, B. (1979). Towards the ultimate conservative difference scheme. V. A second-order sequel to Godunov’s method. Journal of Computational Physics, 32(1), 101-136. doi:10.1016/0021-9991(79)90145-

Semi-automatic assessment of unrestrained Java code: a Library, a DSL, and a workbench to assess exams and exercises

© ACM 2015. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in http://dx.doi.org/10.1145/2729094.2742615Automated marking of multiple-choice exams is of great interest in university courses with a large number of students. For this reason, it has been systematically implanted in almost all universities. Automatic assessment of source code is however less extended. There are several reasons for that. One reason is that almost all existing systems are based on output comparison with a gold standard. If the output is the expected, the code is correct. Otherwise, it is reported as wrong, even if there is only one typo in the code. Moreover, why it is wrong remains a mystery. In general, assessment tools treat the code as a black box, and they only assess the externally observable behavior. In this work we introduce a new code assessment method that also verifies properties of the code, thus allowing to mark the code even if it is only partially correct. We also report about the use of this system in a real university context, showing that the system automatically assesses around 50% of the work.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Economíay Competitividad (Secretaría de Estado de Investigación, Desarrollo e Innovación) under grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under grant PROMETEOII2015/013. David Insa was partially supported by the Spanish Ministerio de Educación under FPU grant AP2010-4415.Insa Cabrera, D.; Silva, J. (2015). Semi-automatic assessment of unrestrained Java code: a Library, a DSL, and a workbench to assess exams and exercises. ACM. https://doi.org/10.1145/2729094.2742615SK. A Rahman and M. Jan Nordin. A review on the static analysis approach in the automated programming assessment systems. In National Conference on Programming 07, 2007.K. Ala-Mutka. A survey of automated assessment approaches for programming assignments. In Computer Science Education, volume 15, pages 83--102, 2005.C. Beierle, M. Kula, and M. Widera. Automatic analysis of programming assignments. In Proc. der 1. E-Learning Fachtagung Informatik (DeLFI '03), volume P-37, pages 144--153, 2003.J. Biggs and C. Tang. Teaching for Quality Learning at University : What the Student Does (3rd Edition). In Open University Press, 2007.P. Denny, A. Luxton-Reilly, E. Tempero, and J. Hendrickx. CodeWrite: Supporting student-driven practice of java. In Proceedings of the 42nd ACM technical symposium on Computer science education, pages 09--12, 2011.R. Hendriks. Automatic exam correction. 2012.P. Ihantola, T. Ahoniemi, V. Karavirta, and O. Seppala. Review of recent systems for automatic assessment of programming assignments. In Proceedings of the 10th Koli Calling International Conference on Computing Education Research, pages 86--93, 2010.H. Kitaya and U. Inoue. An online automated scoring system for Java programming assignments. In International Journal of Information and Education Technology, volume 6, pages 275--279, 2014.M.-J. Laakso, T. Salakoski, A. Korhonen, and L. Malmi. Automatic assessment of exercises for algorithms and data structures - a case study with TRAKLA2. In Proceedings of Kolin Kolistelut/Koli Calling - Fourth Finnish/Baltic Sea Conference on Computer Science Education, pages 28--36, 2004.Y. Liang, Q. Liu, J. Xu, and D. Wang. The recent development of automated programming assessment. In Computational Intelligence and Software Engineering, pages 1--5, 2009.K. A. Naudé, J. H. Greyling, and D. Vogts. Marking student programs using graph similarity. In Computers & Education, volume 54, pages 545--561, 2010.A. Pears, S. Seidman, C. Eney, P. Kinnunen, and L. Malmi. Constructing a core literature for computing education research. In SIGCSE Bulletin, volume 37, pages 152--161, 2005.F. Prados, I. Boada, J. Soler, and J. Poch. Automatic generation and correction of technical exercices. In International Conference on Engineering and Computer Education (ICECE 2005), 2005.M. Supic, K. Brkic, T. Hrkac, Z. Mihajlovic, and Z. Kalafatic. Automatic recognition of handwritten corrections for multiple-choice exam answer sheets. In Information and Communication Technology, Electronics and Microelectronics (MIPRO), pages 1136--1141, 2014.S. Tung, T. Lin, and Y. Lin. An exercise management system for teaching programming. In Journal of Software, 2013.T. Wang, X. Su, Y. Wang, and P. Ma. Semantic similarity-based grading of student programs. In Information and Software Technology, volume 49, pages 99--107, 2007

Design and Numerical Analysis of Flow Characteristics in a Scaled Volute and Vaned Nozzle of Radial Turbocharger Turbines

[EN] Over the past few decades, the aerodynamic improvements of turbocharger turbines contributed significantly to the overall efficiency augmentation and the advancements in downsizing of internal combustion engines. Due to the compact size of automotive turbochargers, the experimental measurement of the complex internal aerodynamics has been insufficiently studied. Hence, turbine designs mostly rely on the results of numerical simulations and the validation of zero-dimensional parameters as efficiency and reduced mass flow. To push the aerodynamic development even further, a precise validation of three-dimensional flow patterns predicted by applied computational fluid dynamics (CFD) methods is in need. This paper presents the design of an up-scaled volute-stator model, which allows optical experimental measurement techniques. In a preliminary step, numerical results indicate that the enlarged geometry will be representative of the flow patterns and characteristic non-dimensional numbers at defined flow sections of the real size turbine. Limitations due to rotor-stator interactions are highlighted. Measurement sections of interest for available measurement techniques are predefined.The authors disclose receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partly sponsored by the program "Ayuda a Primeros Proyectos de Investigacion (PAID-06-18), Vicerrectorado de Investigacion, Innovacion y Transferencia de la Universitat Politecnica de Valencia (UPV), Spain". The support given to Ms. N.H.G. by Universitat Politecnica de Valencia through the "FPI-Subprograma 2" (No.FPI-2018-S2-1368) grant within the "Programa de Apoyo para la Investigacion y Desarrollo (PAID-01-18)" is gratefully acknowledgedTiseira, A.; Navarro, R.; Inhestern, LB.; Hervás-Gómez, N. (2020). Design and Numerical Analysis of Flow Characteristics in a Scaled Volute and Vaned Nozzle of Radial Turbocharger Turbines. Energies. 13(11):1-19. https://doi.org/10.3390/en13112930S1191311Praveena, V., & Martin, M. L. J. (2018). A review on various after treatment techniques to reduce NOx emissions in a CI engine. Journal of the Energy Institute, 91(5), 704-720. doi:10.1016/j.joei.2017.05.010Sindhu, R., Amba Prasad Rao, G., & Madhu Murthy, K. (2018). Effective reduction of NOx emissions from diesel engine using split injections. Alexandria Engineering Journal, 57(3), 1379-1392. doi:10.1016/j.aej.2017.06.009Gil, A., Tiseira, A. O., García-Cuevas, L. M., Usaquén, T. R., & Mijotte, G. (2018). Fast three-dimensional heat transfer model for computing internal temperatures in the bearing housing of automotive turbochargers. International Journal of Engine Research, 21(8), 1286-1297. doi:10.1177/1468087418804949Suhrmann, J. F., Peitsch, D., Gugau, M., & Heuer, T. (2012). On the Effect of Volute Tongue Design on Radial Turbine Performance. Volume 8: Turbomachinery, Parts A, B, and C. doi:10.1115/gt2012-69525Roumeas, M., & Cros, S. (2012). Aerodynamic Investigation of a Nozzle Clearance Effect on Radial Turbine Performance. Volume 8: Turbomachinery, Parts A, B, and C. doi:10.1115/gt2012-68835Liu, Y., Yang, C., Qi, M., Zhang, H., & Zhao, B. (2014). Shock, Leakage Flow and Wake Interactions in a Radial Turbine With Variable Guide Vanes. Volume 2D: Turbomachinery. doi:10.1115/gt2014-25888Cornolti, L., Onorati, A., Cerri, T., Montenegro, G., & Piscaglia, F. (2013). 1D simulation of a turbocharged Diesel engine with comparison of short and long EGR route solutions. Applied Energy, 111, 1-15. doi:10.1016/j.apenergy.2013.04.016Bohbot, J., Chryssakis, C., & Miche, M. (2006). Simulation of a 4-Cylinder Turbocharged Gasoline Direct Injection Engine Using a Direct Temporal Coupling Between a 1D Simulation Software and a 3D Combustion Code. SAE Technical Paper Series. doi:10.4271/2006-01-3263Inhestern, L. B. (s. f.). Measurement, Simulation, and 1D-Modeling of Turbocharger Radial Turbines at Design and Extreme Off-Design Conditions. doi:10.4995/thesis/10251/119989Tamaki, H., & Unno, M. (2008). Study on Flow Fields in Variable Area Nozzles for Radial Turbines. International Journal of Fluid Machinery and Systems, 1(1), 47-56. doi:10.5293/ijfms.2008.1.1.047Eroglu, H., & Tabakoff, W. (1991). LDV Measurements and Investigation of Flow Field Through Radial Turbine Guide Vanes. Journal of Fluids Engineering, 113(4), 660-667. doi:10.1115/1.2926531Karamanis, N., Martinez-Botas, R. F., & Su, C. C. (2000). Mixed Flow Turbines: Inlet and Exit Flow Under Steady and Pulsating Conditions. Volume 1: Aircraft Engine; Marine; Turbomachinery; Microturbines and Small Turbomachinery. doi:10.1115/2000-gt-0470Galindo, J., Tiseira Izaguirre, A. O., García-Cuevas, L. M., & Hervás Gómez, N. (2020). Experimental approach for the analysis of the flow behaviour in the stator of a real centripetal turbine. International Journal of Engine Research, 22(6), 2010-2020. doi:10.1177/1468087420916281Dufour, G., Carbonneau, X., Cazalbou, J.-B., & Chassaing, P. (2006). Practical Use of Similarity and Scaling Laws for Centrifugal Compressor Design. Volume 6: Turbomachinery, Parts A and B. doi:10.1115/gt2006-91227Tancrez, M., Galindo, J., Guardiola, C., Fajardo, P., & Varnier, O. (2011). Turbine adapted maps for turbocharger engine matching. Experimental Thermal and Fluid Science, 35(1), 146-153. doi:10.1016/j.expthermflusci.2010.07.018Menter, F. R. (1994). Two-equation eddy-viscosity turbulence models for engineering applications. AIAA Journal, 32(8), 1598-1605. doi:10.2514/3.12149Broatch, A., Galindo, J., Navarro, R., & García-Tíscar, J. (2014). Methodology for experimental validation of a CFD model for predicting noise generation in centrifugal compressors. International Journal of Heat and Fluid Flow, 50, 134-144. doi:10.1016/j.ijheatfluidflow.2014.06.006Smirnov, P. E., Hansen, T., & Menter, F. R. (2007). Numerical Simulation of Turbulent Flows in Centrifugal Compressor Stages With Different Radial Gaps. Volume 6: Turbo Expo 2007, Parts A and B. doi:10.1115/gt2007-27376Serrano, J. R., Olmeda, P., Arnau, F. J., Dombrovsky, A., & Smith, L. (2014). Analysis and Methodology to Characterize Heat Transfer Phenomena in Automotive Turbochargers. Journal of Engineering for Gas Turbines and Power, 137(2). doi:10.1115/1.4028261Serrano, J. R., Olmeda, P., Arnau, F. J., Dombrovsky, A., & Smith, L. (2015). Turbocharger heat transfer and mechanical losses influence in predicting engines performance by using one-dimensional simulation codes. Energy, 86, 204-218. doi:10.1016/j.energy.2015.03.130Serrano, J. R., Tiseira, A., García-Cuevas, L. M., Inhestern, L. B., & Tartoussi, H. (2017). Radial turbine performance measurement under extreme off-design conditions. Energy, 125, 72-84. doi:10.1016/j.energy.2017.02.118Serrano, J. R., Gil, A., Navarro, R., & Inhestern, L. B. (2017). Extremely Low Mass Flow at High Blade to Jet Speed Ratio in Variable Geometry Radial Turbines and its Influence on the Flow Pattern: A CFD Analysis. Volume 8: Microturbines, Turbochargers and Small Turbomachines; Steam Turbines. doi:10.1115/gt2017-63368Serrano, J. R., Navarro, R., García-Cuevas, L. M., & Inhestern, L. B. (2019). Contribution to tip leakage loss modeling in radial turbines based on 3D flow analysis and 1D characterization. International Journal of Heat and Fluid Flow, 78, 108423. doi:10.1016/j.ijheatfluidflow.2019.108423Choi, M., Baek, J. H., Chung, H. T., Oh, S. H., & Ko, H. Y. (2008). Effects of the low Reynolds number on the loss characteristics in an axial compressor. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 222(2), 209-218. doi:10.1243/09576509jpe520Klausner, E., & Gampe, U. (2014). Evaluation and Enhancement of a One-Dimensional Performance Analysis Method for Centrifugal Compressors. Volume 2D: Turbomachinery. doi:10.1115/gt2014-25141Tiainen, J., Jaatinen-Värri, A., Grönman, A., Turunen-Saaresti, T., & Backman, J. (2018). Effect of FreeStream Velocity Definition on Boundary Layer Thickness and Losses in Centrifugal Compressors. Journal of Turbomachinery, 140(5). doi:10.1115/1.4038872Vinuesa, R., Hosseini, S. M., Hanifi, A., Henningson, D. S., & Schlatter, P. (2017). Pressure-Gradient Turbulent Boundary Layers Developing Around a Wing Section. Flow, Turbulence and Combustion, 99(3-4), 613-641. doi:10.1007/s10494-017-9840-

Cell Formation Heuristic Procedure Considering Production Data

[EN] Manufacturing cell formation is one of foremost, and critical aspect of any manufacturing cell design problem. A large number of cell formation methods are developed and still counting. Consideration of production data in cell formation makes these methods more complex and tedious. In this paper an attempt has been made to develop a simple, easy to understand and implement cell formation procedure, having the capability to handle production data viz. operation sequence, production volume, and inter-cell movement cost simultaneously. The results obtained from proposed procedures are in tune with some highly complex methods, which validates the performance of proposed procedure. To demonstrate its ability to handle other production parameters with little modifications, a modification for consideration to part processing cost in addition to above mentioned production data is developed and explained. Towards the end the procedure to handle alternate process plans in conjugation with production data by the proposed cell formation procedure is also discussed.Kumar, S.; Sharma, RK. (2014). Cell Formation Heuristic Procedure Considering Production Data. International Journal of Production Management and Engineering. 2(2):75-84. doi:10.4995/ijpme.2014.2078SWORD758422Ahi, A., Aryanezhad, M. B., Ashtiani, B., & Makui, A. (2009). A novel approach to determine cell formation, intracellular machine layout and cell layout in the CMS problem based on TOPSIS method. Computers & Operations Research, 36(5), 1478-1496. doi:10.1016/j.cor.2008.02.012Arkat, J., Hosseinabadi Farahani, M., & Hosseini, L. (2011). Integrating cell formation with cellular layout and operations scheduling. The International Journal of Advanced Manufacturing Technology, 61(5-8), 637-647. doi:10.1007/s00170-011-3733-4Beaulieu, A., Ait-Kadi, D., & Gharbi, A. (1993). Heuristic for Flexible Machine Selection Problems. Journal of Decision Systems, 2(3-4), 241-253. doi:10.1080/12460125.1993.10511583Beaulieu, A., Gharbi, A., & Ait-Kadi. (1997). An algorithm for the cell formation and the machine selection problems in the design of a cellular manufacturing system. International Journal of Production Research, 35(7), 1857-1874. doi:10.1080/002075497194958Boutsinas, B. (2013). Machine-part cell formation using biclustering. European Journal of Operational Research, 230(3), 563-572. doi:10.1016/j.ejor.2013.05.007Chow, W. S., and Hawaleshka, O., (1992), An efficient algorithm for solving the machine chaining problem in cellular manufacturing, Computers ind. Engng., Vol. 22, No. 1, 95-100.CHU, C.-H., & TSAI, M. (1990). A comparison of three array-based clustering techniques for manufacturing cell formation. International Journal of Production Research, 28(8), 1417-1433. doi:10.1080/00207549008942802Nair, G. J., & Narendran, T. T. (1998). CASE: A clustering algorithm for cell formation with sequence data. International Journal of Production Research, 36(1), 157-180. doi:10.1080/002075498193985Jie Lian, Chen Guang Liu, Wen Juan Li, Steve Evans, Yong Yin, (2013), Formation of independent manufacturing cells with the consideration of multiple identical machines, International journal of production research, Kim, C. O.,Baek, J. G., Baek, J. K., (2004), A two-phase heuristic algorithm for cell formation problems considering alternative part routes and machine sequences, International Journal of Production Research, 42:18, 3911-3927,Krushinsky, D., & Goldengorin, B. (2012). An exact model for cell formation in group technology. Computational Management Science, 9(3), 323-338. doi:10.1007/s10287-012-0146-2Kumar, L. (2008). Part-machine group formation with operation sequence, time and production volume. International Journal of Simulation Modelling, 7(4), 198-209. doi:10.2507/ijsimm07(4)4.113Lokesh, K., & Jain, P. K. (2010). Concurrently part-machine groups formation with important production data. International Journal of Simulation Modelling, 9(1), 5-16. doi:10.2507/ijsimm09(1)1.133Miltenburg, J., & Zhang, W. (1991). A comparative evaluation of nine well-known algorithms for solving the cell formation problem in group technology. Journal of Operations Management, 10(1), 44-72. doi:10.1016/0272-6963(91)90035-vMukattash, A. M., Adil, M. B., & Tahboub, K. K. (2002). Heuristic approaches for part assignment in cell formation. Computers & Industrial Engineering, 42(2-4), 329-341. doi:10.1016/s0360-8352(02)00020-7Mahesh, O., & Srinivasan, G. (2002). Incremental cell formation considering alternative machines. International Journal of Production Research, 40(14), 3291-3310. doi:10.1080/00207540210146189Sudhakara Pandian, R., & Mahapatra, S. S. (2009). Manufacturing cell formation with production data using neural networks. Computers & Industrial Engineering, 56(4), 1340-1347. doi:10.1016/j.cie.2008.08.003Papaioannou, G., & Wilson, J. M. (2010). The evolution of cell formation problem methodologies based on recent studies (1997–2008): Review and directions for future research. European Journal of Operational Research, 206(3), 509-521. doi:10.1016/j.ejor.2009.10.020Sarker, B. R., (1996), The resemblance coefficients in group technology: a survey and comparative study of relational metrics, Computers ind. Engng., Vol. 30, No. 1, 103-116.Seifoddini, H., (1998), Comparison between single linkage and average linkage clustering techniques in forming machine cells", Computers & industrial engineering 15(14), 210-216.SHAFER, S. M., & MEREDITH, J. R. (1990). A comparison of selected manufacturing cell formation techniques. International Journal of Production Research, 28(4), 661-673. doi:10.1080/00207549008942747VENUGOPAL, V., & NARENDRAN, T. T. (1994). Machine-cell formation through neural network models. International Journal of Production Research, 32(9), 2105-2116. doi:10.1080/00207549408957061Won, Y., & Lee, K. C. (2001). Group technology cell formation considering operation sequences and production volumes. International Journal of Production Research, 39(13), 2755-2768. doi:10.1080/00207540010005060Yasuda *, K., Hu, L., & Yin, Y. (2005). A grouping genetic algorithm for the multi-objective cell formation problem. International Journal of Production Research, 43(4), 829-853. doi:10.1080/00207540512331311859Yin, Y., & Yasuda, K. (2005). Similarity coefficient methods applied to the cell formation problem: a comparative investigation. Computers & Industrial Engineering, 48(3), 471-489. doi:10.1016/j.cie.2003.01.001Yin, Y., & Yasuda, K. (2006). Similarity coefficient methods applied to the cell formation problem: A taxonomy and review. International Journal of Production Economics, 101(2), 329-352. doi:10.1016/j.ijpe.2005.01.01

Direct simulation of liquid-gas-solid flow with a free surface lattice Boltzmann method

Direct numerical simulation of liquid-gas-solid flows is uncommon due to the considerable computational cost. As the grid spacing is determined by the smallest involved length scale, large grid sizes become necessary -- in particular if the bubble-particle aspect ratio is on the order of 10 or larger. Hence, it arises the question of both feasibility and reasonability. In this paper, we present a fully parallel, scalable method for direct numerical simulation of bubble-particle interaction at a size ratio of 1-2 orders of magnitude that makes simulations feasible on currently available super-computing resources. With the presented approach, simulations of bubbles in suspension columns consisting of more than $100\,000$ fully resolved particles become possible. Furthermore, we demonstrate the significance of particle-resolved simulations by comparison to previous unresolved solutions. The results indicate that fully-resolved direct numerical simulation is indeed necessary to predict the flow structure of bubble-particle interaction problems correctly.Comment: submitted to International Journal of Computational Fluid Dynamic