Juan Manuel Rodríguez Prieto

Dr. Juan Manuel Rodríguez Prieto


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 June 2020 in Computational Mechanics
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Journal Article
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JCJ. M. Carbonell
J. M. Carbonell
JPJuan Manuel Rodríguez Prieto
Juan Manuel Rodríguez Prieto
EOE. Oñate
E. Oñate

9 January 2021 in Minerals
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SLSimon Larsson
Simon Larsson
JPJuan Manuel Rodríguez Prieto
Juan Manuel Rodríguez Prieto
HHHannu Heiskari
Hannu Heiskari
Pär JonsénPär Jonsén
Pär Jonsén
Modeling of wet stirred media mill processes is challenging since it requires the simultaneous modeling of the complex multiphysics in the interactions between grinding media, the moving internal agitator elements, and the grinding fluid. In the present study, a multiphysics model of an HIG5 pilot vertical stirred media mill with a nominal power of 7.5 kW is developed. The model is based on a particle-based coupled solver approach, where the grinding fluid is modeled with the particle finite element method (PFEM), the grinding media are modeled with the discrete element method (DEM), and the mill structure is modeled with the finite element method (FEM). The interactions between the different constituents are treated by loose (or weak) two-way couplings between the PFEM, DEM, and FEM models. Both water and a mineral slurry are used as grinding fluids, and they are modeled as Newtonian and non-Newtonian fluids, respectively. In the present work, a novel approach for transferring forces between grinding fluid and grinding media based on the Reynolds number is implemented. This force transfer is realized by specifying the drag coefficient as a function of the Reynolds number. The stirred media mill model is used to predict the mill power consumption, dynamics of both grinding fluid and grinding media, interparticle contacts of the grinding media, and the wear development on the mill structure. The numerical results obtained within the present study show good agreement with experimental measurements.

24 April 2020 in Materials
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Journal Article
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JPJuan Manuel Rodríguez Prieto
Juan Manuel Rodríguez Prieto
SLSimon Larsson
Simon Larsson
JCJ. M. Carbonell
J. M. Carbonell
Pär JonsénPär Jonsén
Pär Jonsén
Machining of metals is an essential operation in the manufacturing industry. Chip formation in metal cutting is associated with large plastic strains, large deformations, high strain rates and high temperatures, mainly located in the primary and in the secondary shear zones. During the last decades, there has been significant progress in numerical methods and constitutive modeling for machining operations. In this work, the Particle Finite Element Method (PFEM) together with a dislocation density (DD) constitutive model are introduced to simulate the machining of Ti-6Al-4V. The work includes a study of two constitutive models for the titanium material, the physically based plasticity DD model and the phenomenology based Johnson–Cook model. Both constitutive models were implemented into an in-house PFEM software and setup to simulate deformation behaviour of titanium Ti6Al4V during an orthogonal cutting process. Validation show that numerical and experimental results are in agreement for different cutting speeds and feeds. The dislocation density model, although it needs more thorough calibration, shows an excellent match with the results. This paper shows that the combination of PFEM together with a dislocation density constitutive model is an excellent candidate for future numerical simulations of mechanical cutting.

1 July 2022 in Computational Particle Mechanics
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JPJuan Manuel Rodríguez Prieto
Juan Manuel Rodríguez Prieto
SLSimon Larsson
Simon Larsson
JCJ. M. Carbonell
J. M. Carbonell
Pär JonsénPär Jonsén
Pär Jonsén
This work presents the development of an explicit/implicit particle finite element method (PFEM) for the 2D modeling of metal cutting processes. The purpose is to study the efficiency of implicit and explicit time integration schemes in terms of precision, accuracy and computing time. The formulation for implicit and explicit time marching schemes is developed, and a detailed study on the explicit solution steps is presented. The PFEM remeshing procedures for insertion and removal of particles have been improved to model the multiple scales of time and/or space of the solution. The detection and treatment of the rigid tool contact are presented for both, implicit and explicit schemes. The performance of explicit/implicit integration is studied with a set of different two-dimensional orthogonal cutting tests of AISI 4340 steel at cutting speeds ranging from 1 m/s up to 30 m/s. It was shown that if the correct selection of the time integration scheme is made, the computing time can decrease up to 40 times. It allows us to affirm that the computing time of the PFEM simulations can be excessive due to the used time marching scheme independently of the meshing process. As a practical result, a set of recommendations to select the time integration schemes for a given cutting speed are given. This is intended to minimize one of the negative constraints pointed out by the industry when using metal cutting simulators.

4 February 2024 in Computational Particle Mechanics
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OSOlle Sandin
Olle Sandin
JPJuan Manuel Rodríguez Prieto
Juan Manuel Rodríguez Prieto
PLPatrick Larour
Patrick Larour
SPSergi Parareda
Sergi Parareda
DFDavid Frómeta
David Frómeta
Daniel CasellasDaniel Casellas
Daniel Casellas
Shear cutting introduces residual strains, notches and cracks, which negatively affects edge-formability. This is especially relevant for forming of high-strength sheets, where edge-cracking is a serious industrial problem. Numerical modelling of the shear cutting process can aid the understanding of the sheared edge damage and help preventing edge-cracking. However, modelling of the shear cutting process requires robust and accurate numerical tools that handle plasticity, large deformation and ductile failure. The use of conventional finite element methods (FEM) may give rise to distorted elements or loss of accuracy during re-meshing schemes, while mesh-free methods have tendencies of tensile instability or excessive computational cost. In this article, the authors propose the particle finite element method (PFEM) for modelling the shear cutting process of high-strength steel sheets, acquiring high accuracy results and overcoming the stated challenges associated with FEM. The article describe the implementation of a mixed axisymmetric formulation, with the novelty of adding a ductile damage- and failure model to account for material fracture in the shear-cutting process. The PFEM shear-cutting model was validated against experiments using varying process parameters to ensure the predictive capacity of the model. Likewise, a thorough sensitivity analysis of the numerical implementation was conducted. The results show that the PFEM model is able to predict the process forces and cut edge shapes over a wide range of cutting clearances, while efficiently handling the numerical challenges involved with large material deformation. It is thus concluded that the PFEM implementation is an accurate predictive tool for sheared edge damage assessment.

29 March 2023 in Journal of Computing and Information Science in Engineering
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DZDaobo Zhang
Daobo Zhang
JPJuan Manuel Rodríguez Prieto
Juan Manuel Rodríguez Prieto
XYXialong Ye
Xialong Ye
RMRalf Müller
Ralf Müller
In this work, the particle finite element method (PFEM) is extended to simulate additive manufacturing processes in a variety of different complicated geometries. A three-dimensional α-shape approach is used to carry out the material addition procedure. It overcomes the limitation of merely employing the traditional element birth and death technique and reduces the degrees-of-freedom compared to this technique. Furthermore, numerical examples are used to evaluate and demonstrate the applicability of the PFEM method for additive manufacturing within the framework of a weakly coupled thermoelasticity formulation. During additive manufacturing operations, deflections, stresses, and temperature are computed using a user-defined implementation in FEniCS.