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

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    [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). Characterising performance of environmental models. Environmental Modelling & Software, 40, 1-20. doi:10.1016/j.envsoft.2012.09.011Biswas, 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)00092-5Blocken, 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.2012.02.001Bombardelli, F. A., Meireles, I., & Matos, J. (2010). Laboratory measurements and multi-block numerical simulations of the mean flow and turbulence in the non-aerated skimming flow region of steep stepped spillways. Environmental Fluid Mechanics, 11(3), 263-288. doi:10.1007/s10652-010-9188-6Bradshaw, P. (1997). Understanding and prediction of turbulent flow—1996. International Journal of Heat and Fluid Flow, 18(1), 45-54. doi:10.1016/s0142-727x(96)00134-8Caishui, H. (2012). Three-dimensional Numerical Analysis of Flow Pattern in Pressure Forebay of Hydropower Station. Procedia Engineering, 28, 128-135. doi:10.1016/j.proeng.2012.01.694Castillo L. G. J. M. Carrillo J. T. García and A. Vigueras-Rodríguez. 2014. “Numerical simulations and laboratory measurements in hydraulic jumps.” In Proc. 11th Int. Conf. of Hydroinformatics. New York: Spanish Ministry of Economy.Castro-Orgaz, O., & Hager, W. H. (2009). Classical hydraulic jump: basic flow features. Journal of Hydraulic Research, 47(6), 744-754. doi:10.3826/jhr.2009.3610Procedure for Estimation and Reporting of Uncertainty Due to Discretization in CFD Applications. (2008). Journal of Fluids Engineering, 130(7), 078001. doi:10.1115/1.2960953Chachereau, 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.2011.01.009Chanson, H. (2006). Bubble entrainment, spray and splashing at hydraulic jumps. Journal of Zhejiang University-SCIENCE A, 7(8), 1396-1405. doi:10.1631/jzus.2006.a1396Chanson, H. (2009). Current knowledge in hydraulic jumps and related phenomena. A survey of experimental results. European Journal of Mechanics - B/Fluids, 28(2), 191-210. doi:10.1016/j.euromechflu.2008.06.004Chanson, H. (2013). Hydraulics of aerated flows:qui pro quo? Journal of Hydraulic Research, 51(3), 223-243. doi:10.1080/00221686.2013.795917Chanson, 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)00016-6Chanson, H., & Gualtieri, C. (2008). Similitude and scale effects of air entrainment in hydraulic jumps. Journal of Hydraulic Research, 46(1), 35-44. doi:10.1080/00221686.2008.9521841Chanson, H., & Montes, J. S. (1995). Characteristics of Undular Hydraulic Jumps: Experimental Apparatus and Flow Patterns. Journal of Hydraulic Engineering, 121(2), 129-144. doi:10.1061/(asce)0733-9429(1995)121:2(129)Cheng, C.-K., Tai, Y.-C., & Jin, Y.-C. (2017). Particle Image Velocity Measurement and Mesh-Free Method Modeling Study of Forced Hydraulic Jumps. Journal of Hydraulic Engineering, 143(9), 04017028. doi:10.1061/(asce)hy.1943-7900.0001325Dong, 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/w11101956Fuentes-Pérez, J. F., Silva, A. T., Tuhtan, J. A., García-Vega, A., Carbonell-Baeza, R., Musall, M., & Kruusmaa, M. (2018). 3D modelling of non-uniform and turbulent flow in vertical slot fishways. Environmental Modelling & Software, 99, 156-169. doi:10.1016/j.envsoft.2017.09.011Gualtieri, 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/s10652-006-9016-1Hager, W. H. (1992). Energy Dissipators and Hydraulic Jump. Water Science and Technology Library. doi:10.1007/978-94-015-8048-9Hager, W. H., & Bremen, R. (1989). Classical hydraulic jump: sequent depths. Journal of Hydraulic Research, 27(5), 565-585. doi:10.1080/00221688909499111Hager, W. H., Bremen, R., & Kawagoshi, N. (1990). Classical hydraulic jump: length of roller. Journal of Hydraulic Research, 28(5), 591-608. doi:10.1080/00221689009499048Heller, V. (2011). Scale effects in physical hydraulic engineering models. Journal of Hydraulic Research, 49(3), 293-306. doi:10.1080/00221686.2011.578914Hirt, C. ., & Nichols, B. . (1981). Volume of fluid (VOF) method for the dynamics of free boundaries. 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. Atmospheric Environment, 38(19), 3039-3048. doi:10.1016/j.atmosenv.2004.02.047Kim, S.-E., & Boysan, F. (1999). Application of CFD to environmental flows. Journal of Wind Engineering and Industrial Aerodynamics, 81(1-3), 145-158. doi:10.1016/s0167-6105(99)00013-6Kirkgöz, 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)Langhi, M., & Hosoda, T. (2018). Three-dimensional unsteady RANS model for hydraulic jumps. ISH Journal of Hydraulic Engineering, 1-8. doi:10.1080/09715010.2018.1555775Liu, M., Rajaratnam, N., & Zhu, D. Z. (2004). Turbulence Structure of Hydraulic Jumps of Low Froude Numbers. Journal of Hydraulic Engineering, 130(6), 511-520. doi:10.1061/(asce)0733-9429(2004)130:6(511)Liu, T., Song, L., Fu, W., Wang, G., Lin, Q., Zhao, D., & Yi, B. (2018). 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. Journal of Hydraulic Research, 37(4), 541-558. doi:10.1080/00221686.1999.9628267Padulano, 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.1943-4774.0001150Resch, F. J., & Leutheusser, H. J. (1972). Le ressaut hydraulique : mesures de turbulence dans la région diphasique. La Houille Blanche, 58(4), 279-293. doi:10.1051/lhb/1972021Sarfaraz M. and J. Attari. 2011. “Numerical simulation of uniform flow region over a steeply sloping stepped spillway.” In Proc. 6th National Congress on Civil Engineering. Semnan Iran: Iran Water and Power Development Company.Spalart, P. . (2000). Strategies for turbulence modelling and simulations. International Journal of Heat and Fluid Flow, 21(3), 252-263. doi:10.1016/s0142-727x(00)00007-2Speziale, C. G., & Thangam, S. (1992). Analysis of an RNG based turbulence model for separated flows. International Journal of Engineering Science, 30(10), 1379-IN4. doi:10.1016/0020-7225(92)90148-aSpoljaric A. 1984. “Dynamic characteristics of the load on the bottom plate under hydraulic jump.” In Proc. Int. Conf. Hydrosoft’84: Hydraulic Engineering Software. New York: Elsevier.Teuber, 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.2019.103266Toso, 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)Valero D. and D. B. Bung. 2015. “Hybrid investigations of air transport processes in moderately sloped stepped spillway flows.” In Vol. 28 of E-proc. 36th IAHR World Congress 1–10. The Hague Netherlands: IHE Delft.Valero, D., & Bung, D. B. (2016). Sensitivity of turbulent Schmidt number and turbulence model to simulations of jets in crossflow. Environmental Modelling & Software, 82, 218-228. doi:10.1016/j.envsoft.2016.04.030Valero, 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/w11010028von Kármán T. 1930. “Mechanische Ähnlichkeit und Turbulenz.” In Proc. 3rd Int. Congress on Applied Mechanics. New York: Springer.Wang H. 2014. “Turbulence and air entrainment in hydraulic jumps.” Ph.D. thesis Dept. of Civil Engineering Univ. of Queensland.Wang, H., & Chanson, H. (2013). Air entrainment and turbulent fluctuations in hydraulic jumps. Urban Water Journal, 12(6), 502-518. doi:10.1080/1573062x.2013.847464Wang, H., & Chanson, H. (2015). Experimental Study of Turbulent Fluctuations in Hydraulic Jumps. Journal of Hydraulic Engineering, 141(7), 04015010. doi:10.1061/(asce)hy.1943-7900.0001010Weller, H. G., Tabor, G., Jasak, H., & Fureby, C. (1998). A tensorial approach to computational continuum mechanics using object-oriented techniques. Computers in Physics, 12(6), 620. doi:10.1063/1.168744Witt, A., Gulliver, J., & Shen, L. (2015). Simulating air entrainment and vortex dynamics in a hydraulic jump. International Journal of Multiphase Flow, 72, 165-180. doi:10.1016/j.ijmultiphaseflow.2015.02.012Wu, J., Zhou, Y., & Ma, F. (2018). Air entrainment of hydraulic jump aeration basin. Journal of Hydrodynamics, 30(5), 962-965. doi:10.1007/s42241-018-0088-4Xiang, 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.2014.08.016Yakhot, V., Orszag, S. A., Thangam, S., Gatski, T. B., & Speziale, C. G. (1992). Development of turbulence models for shear flows by a double expansion technique. Physics of Fluids A: Fluid Dynamics, 4(7), 1510-1520. doi:10.1063/1.858424Zhang, 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-

    On the use of stabilization techniques in the Cartesian grid finite element method framework for iterative solvers

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    "This is the peer reviewed version of the following article: Navarro-Jiménez, José Manuel, Enrique Nadal, Manuel Tur, José Martínez-Casas, and Juan José Ródenas. 2020. "On the Use of Stabilization Techniques in the Cartesian Grid Finite Element Method Framework for Iterative Solvers." International Journal for Numerical Methods in Engineering 121 (13). Wiley: 3004-20. doi:10.1002/nme.6344, which has been published in final form at https://doi.org/10.1002/nme.6344. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."[EN] Fictitious domain methods, like the Cartesian grid finite element method (cgFEM), are based on the use of unfitted meshes that must be intersected. This may yield to ill-conditioned systems of equations since the stiffness associated with a node could be small, thus poorly contributing to the energy of the problem. This issue complicates the use of iterative solvers for large problems. In this work, we present a new stabilization technique that, in the case of cgFEM, preserves the Cartesian structure of the mesh. The formulation consists in penalizing the free movement of those nodes by a smooth extension of the solution from the interior of the domain, through a postprocess of the solution via a displacement recovery technique. The numerical results show an improvement of the condition number and a decrease in the number of iterations of the iterative solver while preserving the problem accuracy.The authors wish to thank the Spanish "Ministerio de Economía y Competitividad," the "Generalitat Valenciana," and the "Universitat Politècnica de València" for their financial support received through the projects DPI2017-89816-R, Prometeo 2016/007 and the FPI2015 program, respectively.Navarro-Jiménez, J.; Nadal, E.; Tur Valiente, M.; Martínez Casas, J.; Ródenas, JJ. (2020). On the use of stabilization techniques in the Cartesian grid finite element method framework for iterative solvers. International Journal for Numerical Methods in Engineering. 121(13):3004-3020. https://doi.org/10.1002/nme.6344S3004302012113Burman, E., & Hansbo, P. (2010). Fictitious domain finite element methods using cut elements: I. A stabilized Lagrange multiplier method. Computer Methods in Applied Mechanics and Engineering, 199(41-44), 2680-2686. doi:10.1016/j.cma.2010.05.011Ruiz-Gironés, E., & Sarrate, J. (2010). Generation of structured hexahedral meshes in volumes with holes. Finite Elements in Analysis and Design, 46(10), 792-804. doi:10.1016/j.finel.2010.04.005Geuzaine, C., & Remacle, J.-F. (2009). Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities. International Journal for Numerical Methods in Engineering, 79(11), 1309-1331. doi:10.1002/nme.2579Parvizian, J., Düster, A., & Rank, E. (2007). Finite cell method. Computational Mechanics, 41(1), 121-133. doi:10.1007/s00466-007-0173-yDüster, A., Parvizian, J., Yang, Z., & Rank, E. (2008). The finite cell method for three-dimensional problems of solid mechanics. Computer Methods in Applied Mechanics and Engineering, 197(45-48), 3768-3782. doi:10.1016/j.cma.2008.02.036Nadal, E., Ródenas, J. J., Albelda, J., Tur, M., Tarancón, J. E., & Fuenmayor, F. J. (2013). Efficient Finite Element Methodology Based on Cartesian Grids: Application to Structural Shape Optimization. Abstract and Applied Analysis, 2013, 1-19. doi:10.1155/2013/953786Nadal, E., Ródenas, J. J., Sánchez-Orgaz, E. M., López-Real, S., & Martí-Pellicer, J. (2014). Sobre la utilización de códigos de elementos finitos basados en mallados cartesianos en optimización estructural. Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, 30(3), 155-165. doi:10.1016/j.rimni.2013.04.009Giovannelli, L., Ródenas, J. J., Navarro-Jiménez, J. M., & Tur, M. (2017). Direct medical image-based Finite Element modelling for patient-specific simulation of future implants. Finite Elements in Analysis and Design, 136, 37-57. doi:10.1016/j.finel.2017.07.010Schillinger, D., & Ruess, M. (2014). The Finite Cell Method: A Review in the Context of Higher-Order Structural Analysis of CAD and Image-Based Geometric Models. Archives of Computational Methods in Engineering, 22(3), 391-455. doi:10.1007/s11831-014-9115-yBurman, E., Claus, S., Hansbo, P., Larson, M. G., & Massing, A. (2014). CutFEM: Discretizing geometry and partial differential equations. International Journal for Numerical Methods in Engineering, 104(7), 472-501. doi:10.1002/nme.4823Tur, M., Albelda, J., Marco, O., & Ródenas, J. J. (2015). Stabilized method of imposing Dirichlet boundary conditions using a recovered stress field. Computer Methods in Applied Mechanics and Engineering, 296, 352-375. doi:10.1016/j.cma.2015.08.001Tur, M., Albelda, J., Nadal, E., & Ródenas, J. J. (2014). Imposing Dirichlet boundary conditions in hierarchical Cartesian meshes by means of stabilized Lagrange multipliers. International Journal for Numerical Methods in Engineering, 98(6), 399-417. doi:10.1002/nme.4629De Prenter, F., Verhoosel, C. V., van Zwieten, G. J., & van Brummelen, E. H. (2017). Condition number analysis and preconditioning of the finite cell method. Computer Methods in Applied Mechanics and Engineering, 316, 297-327. doi:10.1016/j.cma.2016.07.006Berger-Vergiat, L., Waisman, H., Hiriyur, B., Tuminaro, R., & Keyes, D. (2011). Inexact Schwarz-algebraic multigrid preconditioners for crack problems modeled by extended finite element methods. International Journal for Numerical Methods in Engineering, 90(3), 311-328. doi:10.1002/nme.3318Menk, A., & Bordas, S. P. A. (2010). A robust preconditioning technique for the extended finite element method. International Journal for Numerical Methods in Engineering, 85(13), 1609-1632. doi:10.1002/nme.3032Dauge, M., Düster, A., & Rank, E. (2015). Theoretical and Numerical Investigation of the Finite Cell Method. Journal of Scientific Computing, 65(3), 1039-1064. doi:10.1007/s10915-015-9997-3Elfverson, D., Larson, M. G., & Larsson, K. (2018). CutIGA with basis function removal. Advanced Modeling and Simulation in Engineering Sciences, 5(1). doi:10.1186/s40323-018-0099-2Verhoosel, C. V., van Zwieten, G. J., van Rietbergen, B., & de Borst, R. (2015). Image-based goal-oriented adaptive isogeometric analysis with application to the micro-mechanical modeling of trabecular bone. Computer Methods in Applied Mechanics and Engineering, 284, 138-164. doi:10.1016/j.cma.2014.07.009Burman, E. (2010). Ghost penalty. Comptes Rendus Mathematique, 348(21-22), 1217-1220. doi:10.1016/j.crma.2010.10.006BadiaS VerdugoF MartínAF. The aggregated unfitted finite element method for elliptic problems;2017.Jomo, J. N., de Prenter, F., Elhaddad, M., D’Angella, D., Verhoosel, C. V., Kollmannsberger, S., … Rank, E. (2019). Robust and parallel scalable iterative solutions for large-scale finite cell analyses. Finite Elements in Analysis and Design, 163, 14-30. doi:10.1016/j.finel.2019.01.009Béchet, É., Moës, N., & Wohlmuth, B. (2008). A stable Lagrange multiplier space for stiff interface conditions within the extended finite element method. International Journal for Numerical Methods in Engineering, 78(8), 931-954. doi:10.1002/nme.2515Hautefeuille, M., Annavarapu, C., & Dolbow, J. E. (2011). Robust imposition of Dirichlet boundary conditions on embedded surfaces. International Journal for Numerical Methods in Engineering, 90(1), 40-64. doi:10.1002/nme.3306Hansbo, P., Lovadina, C., Perugia, I., & Sangalli, G. (2005). A Lagrange multiplier method for the finite element solution of elliptic interface problems using non-matching meshes. Numerische Mathematik, 100(1), 91-115. doi:10.1007/s00211-005-0587-4Burman, E., & Hansbo, P. (2012). Fictitious domain finite element methods using cut elements: II. A stabilized Nitsche method. Applied Numerical Mathematics, 62(4), 328-341. doi:10.1016/j.apnum.2011.01.008Gerstenberger, A., & Wall, W. A. (2008). An eXtended Finite Element Method/Lagrange multiplier based approach for fluid–structure interaction. Computer Methods in Applied Mechanics and Engineering, 197(19-20), 1699-1714. doi:10.1016/j.cma.2007.07.002AxelssonO. Iterative solution methods;1994.Stenberg, R. (1995). On some techniques for approximating boundary conditions in the finite element method. Journal of Computational and Applied Mathematics, 63(1-3), 139-148. doi:10.1016/0377-0427(95)00057-7Zienkiewicz, O. C., & Zhu, J. Z. (1987). A simple error estimator and adaptive procedure for practical engineerng analysis. International Journal for Numerical Methods in Engineering, 24(2), 337-357. doi:10.1002/nme.1620240206Zienkiewicz, O. C., & Zhu, J. Z. (1992). The superconvergent patch recovery anda posteriori error estimates. Part 1: The recovery technique. International Journal for Numerical Methods in Engineering, 33(7), 1331-1364. doi:10.1002/nme.1620330702Blacker, T., & Belytschko, T. (1994). Superconvergent patch recovery with equilibrium and conjoint interpolant enhancements. International Journal for Numerical Methods in Engineering, 37(3), 517-536. doi:10.1002/nme.1620370309Díez, P., José Ródenas, J., & Zienkiewicz, O. C. (2007). Equilibrated patch recovery error estimates: simple and accurate upper bounds of the error. International Journal for Numerical Methods in Engineering, 69(10), 2075-2098. doi:10.1002/nme.1837Xiao, Q. Z., & Karihaloo, B. L. (s. f.). Statically Admissible Stress Recovery using the Moving Least Squares Technique. Progress in Computational Structures Technology, 111-138. doi:10.4203/csets.11.5Ródenas, J. J., Tur, M., Fuenmayor, F. J., & Vercher, A. (2007). Improvement of the superconvergent patch recovery technique by the use of constraint equations: the SPR-C technique. International Journal for Numerical Methods in Engineering, 70(6), 705-727. doi:10.1002/nme.1903Zhang, Z. (2001). Advances in Computational Mathematics, 15(1/4), 363-374. doi:10.1023/a:1014221409940González-Estrada, O. A., Nadal, E., Ródenas, J. J., Kerfriden, P., Bordas, S. P. A., & Fuenmayor, F. J. (2013). Mesh adaptivity driven by goal-oriented locally equilibrated superconvergent patch recovery. Computational Mechanics, 53(5), 957-976. doi:10.1007/s00466-013-0942-8Nadal, E., Díez, P., Ródenas, J. J., Tur, M., & Fuenmayor, F. J. (2015). A recovery-explicit error estimator in energy norm for linear elasticity. Computer Methods in Applied Mechanics and Engineering, 287, 172-190. doi:10.1016/j.cma.2015.01.013ZienkiewiczOC TaylorRL. The finite element method fifth edition volume 1: the basis.MA:Butterworth‐Heinemann;2000.Brenner, S. C., & Scott, L. R. (1994). The Mathematical Theory of Finite Element Methods. Texts in Applied Mathematics. doi:10.1007/978-1-4757-4338-

    Cellular Helmet Liner Design through Bio-inspired Structures and Topology Optimization of Compliant Mechanism Lattices

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    The continuous development of sport technologies constantly demands advancements in protective headgear to reduce the risk of head injuries. This article introduces new cellular helmet liner designs through two approaches. The first approach is the study of energy-absorbing biological materials. The second approach is the study of lattices comprised of force-diverting compliant mechanisms. On the one hand, bio-inspired liners are generated through the study of biological, hierarchical materials. An emphasis is given on structures in nature that serve similar concussion-reducing functions as a helmet liner. Inspiration is drawn from organic and skeletal structures. On the other hand, compliant mechanism lattice (CML)-based liners use topology optimization to synthesize rubber cellular unit cells with effective positive and negative Poisson's ratios. Three lattices are designed using different cellular unit cell arrangements, namely, all positive, all negative, and alternating effective Poisson's ratios. The proposed cellular (bio-inspired and CML-based) liners are embedded between two polycarbonate shells, thereby, replacing the traditional expanded polypropylene foam liner used in standard sport helmets. The cellular liners are analyzed through a series of 2D extruded ballistic impact simulations to determine the best performing liner topology and its corresponding rubber hardness. The cellular design with the best performance is compared against an expanded polypropylene foam liner in a 3D simulation to appraise its protection capabilities and verify that the 2D extruded design simulations scale to an effective 3D design

    Equivalent air spring suspension model for quarter-passive model of passenger vehicles

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    This paper investigates the GENSIS air spring suspension system equivalence to a passive suspension system. The SIMULINK simulation together with the OptiY optimization is used to obtain the air spring suspension model equivalent to passive suspension system, where the car body response difference from both systems with the same road profile inputs is used as the objective function for optimization (OptiY program). The parameters of air spring system such as initial pressure, volume of bag, length of surge pipe, diameter of surge pipe, and volume of reservoir are obtained from optimization. The simulation results show that the air spring suspension equivalent system can produce responses very close to the passive suspension system

    Carbon capture from natural gas combined cycle power plants: Solvent performance comparison at an industrial scale

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    Natural gas is an important source of energy. This article addresses the problem of integrating an existing natural gas combined cycle (NGCC) power plant with a carbon capture process using various solvents. The power plant and capture process have mutual interactions in terms of the flue gas flow rate and composition vs. the extracted steam required for solvent regeneration. Therefore, evaluating solvent performance at a single (nominal) operating point is not indicative and solvent performance should be considered subject to the overall process operability and over a wide range of operating conditions. In the present research, a novel optimization framework was developed in which design and operation of the capture process are optimized simultaneously and their interactions with the upstream power plant are fully captured. The developed framework was applied for solvent comparison which demonstrated that GCCmax, a newly developed solvent, features superior performances compared to the monoethanolamine baseline solvent

    A Variational r-Adaption and Shape-Optimization Method for Finite-Deformation Elasticity

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    This paper is concerned with the formulation of a variational r-adaption method for finite-deformation elastostatic problems. The distinguishing characteristic of the method is that the variational principle simultaneously supplies the solution, the optimal mesh and, in problems of shape optimization, the equilibrium shapes of the system. This is accomplished by minimizing the energy functional with respect to the nodal field values as well as with respect to the triangulation of the domain of analysis. Energy minimization with respect to the referential nodal positions has the effect of equilibrating the energetic or configurational forces acting on the nodes. We derive general expressions for the configuration forces for isoparametric elements and nonlinear, possibly anisotropic, materials under general loading. We illustrate the versatility and convergence characteristics of the method by way of selected numerical tests and applications, including the problem of a semi-infinite crack in linear and nonlinear elastic bodies; and the optimization of the shape of elastic inclusions
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