518,988 research outputs found

    On the impact of DPF downsizing and cellular geometry on filtration efficiency in pre- and post-turbine placement

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    [EN] the current work a computational study to evaluate the effect of the DPF downsizing on filtration efficiency is performed. The DPF is conventionally placed downstream of the turbine. However, its placement upstream of the turbine is growing in interest because of the benefits in specific fuel consumption, passive regeneration and aptitude to downsizing. Hence both pre- and post-turbine placement are considered in presence of clean and soot loaded substrates. An in-house 1D wall-flow DPF model for unsteady compressible flow is used. Volume reduction is approached considering diameter and length variation. In parallel, the cell density is also varied modifying the meso-geometry, i.e. cell size and porous wall thickness, imposing constant thermal integrity factor. The sensitivity to this last parameter is also analysed resulting its influence of second order in comparison to volume and cellular geometry effects. The lower Peclet number in the pre-turbine placement leads to higher filtration efficiency than post-turbine location comparing at the same DPF volume. Diameter based volume reduction provides slightly better results in filtration efficiency than length based reduction because of the way the filtration velocity field is varied. This general behaviour involves additional advantages to the potential for volume reduction of pre-turbine DPFs. Thus, different strategies with boundaries defined by volume reduction at constant filtration area or at constant specific filtration area can be approached looking for the best balance between fuel economy reduction and filtration efficiency increase provided by pre-turbine DPF placement.This work has been partially funded by FEDER and Government of Spain through Project No. TRA2016-79185-R. Additionally, the Ph.D. student E. Angiolini has been funded by a grant from Conselleria de Educacio, Cultura i Esport of the Generalitat Valenciana with reference GRISOLIA/2013/036. These supports are gratefully acknowledged by the authors.Serrano, J.; Bermúdez, V.; Piqueras, P.; Angiolini, E. (2017). On the impact of DPF downsizing and cellular geometry on filtration efficiency in pre- and post-turbine placement. Journal of Aerosol Science. 113:20-35. https://doi.org/10.1016/j.jaerosci.2017.07.014S203511

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

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    [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. Journal of Computational Physics, 39(1), 201-225. doi:10.1016/0021-9991(81)90145-5Bombardelli, 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/s10652-010-9188-6Pope, S. B. (2001). Turbulent Flows. Measurement Science and Technology, 12(11), 2020-2021. doi:10.1088/0957-0233/12/11/705Harlow, F. H. (1967). Turbulence Transport Equations. Physics of Fluids, 10(11), 2323. doi:10.1063/1.1762039Launder, B. E., & Sharma, B. I. (1974). Application of the energy-dissipation model of turbulence to the calculation of flow near a spinning disc. Letters in Heat and Mass Transfer, 1(2), 131-137. doi:10.1016/0094-4548(74)90150-7Yakhot, 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:10.1063/1.858424Li, 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

    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. 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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. 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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. 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    Multiscale computational homogenization: review and proposal of a new enhanced-first-order method

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    This is a copy of the author 's final draft version of an article published in the Archives of computational methods in engineering. The final publication is available at Springer via http://dx.doi.org/10.1007/s11831-016-9205-0The continuous increase of computational capacity has encouraged the extensive use of multiscale techniques to simulate the material behaviour on several fields of knowledge. In solid mechanics, the multiscale approaches which consider the macro-scale deformation gradient to obtain the homogenized material behaviour from the micro-scale are called first-order computational homogenization. Following this idea, the second-order FE2 methods incorporate high-order gradients to improve the simulation accuracy. However, to capture the full advantages of these high-order framework the classical boundary value problem (BVP) at the macro-scale must be upgraded to high-order level, which complicates their numerical solution. With the purpose of obtaining the best of both methods i.e. first-order and second-order, in this work an enhanced-first-order computational homogenization is presented. The proposed approach preserves a classical BVP at the macro-scale level but taking into account the high-order gradient of the macro-scale in the micro-scale solution. The developed numerical examples show how the proposed method obtains the expected stress distribution at the micro-scale for states of structural bending loads. Nevertheless, the macro-scale results achieved are the same than the ones obtained with a first-order framework because both approaches share the same macro-scale BVP.Peer ReviewedPostprint (author's final draft

    Homogenization of plain weave composites with imperfect microstructure: Part II--Analysis of real-world materials

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    A two-layer statistically equivalent periodic unit cell is offered to predict a macroscopic response of plain weave multilayer carbon-carbon textile composites. Falling-short in describing the most typical geometrical imperfections of these material systems the original formulation presented in (Zeman and \v{S}ejnoha, International Journal of Solids and Structures, 41 (2004), pp. 6549--6571) is substantially modified, now allowing for nesting and mutual shift of individual layers of textile fabric in all three directions. Yet, the most valuable asset of the present formulation is seen in the possibility of reflecting the influence of negligible meso-scale porosity through a system of oblate spheroidal voids introduced in between the two layers of the unit cell. Numerical predictions of both the effective thermal conductivities and elastic stiffnesses and their comparison with available laboratory data and the results derived using the Mori-Tanaka averaging scheme support credibility of the present approach, about as much as the reliability of local mechanical properties found from nanoindentation tests performed directly on the analyzed composite samples.Comment: 28 pages, 14 figure

    Cavitation Induction by Projectile Impacting on a Water Jet

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    The present paper focuses on the simulation of the high-velocity impact of a projectile impacting on a water-jet, causing the onset, development and collapse of cavitation. The simulation of the fluid motion is carried out using an explicit, compressible, density-based solver developed by the authors using the OpenFOAM library. It employs a barotropic two-phase flow model that simulates the phase-change due to cavitation and considers the co-existence of non-condensable and immiscible air. The projectile is considered to be rigid while its motion through the computational domain is modelled through a direct-forcing Immersed Boundary Method. Model validation is performed against the experiments of Field et al. [Field, J., Camus, J. J., Tinguely, M., Obreschkow, D., Farhat, M., 2012. Cavitation in impacted drops and jets and the effect on erosion damage thresholds. Wear 290–291, 154–160. doi:10.1016/j.wear.2012.03.006. URL http://www.sciencedirect.com/science/article/pii/S0043164812000968 ], who visualised cavity formation and shock propagation in liquid impacts at high velocities. Simulations unveil the shock structures and capture the high-speed jetting forming at the impact location, in addition to the subsequent cavitation induction and vapour formation due to refraction waves. Moreover, model predictions provide quantitative information and a better insight on the flow physics that has not been identified from the reported experimental data, such as shock-wave propagation, vapour formation quantity and induced pressures. Furthermore, evidence of the Richtmyer-Meshkov instability developing on the liquid-air interface are predicted when sufficient dense grid resolution is utilised

    Theoretical and numerical comparison of hyperelastic and hypoelastic formulations for Eulerian non-linear elastoplasticity

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    The aim of this paper is to compare a hyperelastic with a hypoelastic model describing the Eulerian dynamics of solids in the context of non-linear elastoplastic deformations. Specifically, we consider the well-known hypoelastic Wilkins model, which is compared against a hyperelastic model based on the work of Godunov and Romenski. First, we discuss some general conceptual differences between the two approaches. Second, a detailed study of both models is proposed, where differences are made evident at the aid of deriving a hypoelastic-type model corresponding to the hyperelastic model and a particular equation of state used in this paper. Third, using the same high order ADER Finite Volume and Discontinuous Galerkin methods on fixed and moving unstructured meshes for both models, a wide range of numerical benchmark test problems has been solved. The numerical solutions obtained for the two different models are directly compared with each other. For small elastic deformations, the two models produce very similar solutions that are close to each other. However, if large elastic or elastoplastic deformations occur, the solutions present larger differences.Comment: 14 figure
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