References of "Estupinan Donoso, Alvaro Antonio 50001760"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailThe XDEM Multi-physics and Multi-scale Simulation Technology: Review on DEM-CFD Coupling, Methodology and Engineering Applications
Peters, Bernhard UL; Baniasadi, Maryam UL; Baniasadi, Mehdi UL et al

in Particuology (in press)

The XDEM multi-physics and multi-scale simulation platform roots in the Ex- tended Discrete Element Method (XDEM) and is being developed at the In- stitute of Computational Engineering at the University ... [more ▼]

The XDEM multi-physics and multi-scale simulation platform roots in the Ex- tended Discrete Element Method (XDEM) and is being developed at the In- stitute of Computational Engineering at the University of Luxembourg. The platform is an advanced multi- physics simulation technology that combines flexibility and versatility to establish the next generation of multi-physics and multi-scale simulation tools. For this purpose the simulation framework relies on coupling various predictive tools based on both an Eulerian and Lagrangian approach. Eulerian approaches represent the wide field of continuum models while the Lagrange approach is perfectly suited to characterise discrete phases. Thus, continuum models include classical simulation tools such as Computa- tional Fluid Dynamics (CFD) or Finite Element Analysis (FEA) while an ex- tended configuration of the classical Discrete Element Method (DEM) addresses the discrete e.g. particulate phase. Apart from predicting the trajectories of individual particles, XDEM extends the application to estimating the thermo- dynamic state of each particle by advanced and optimised algorithms. The thermodynamic state may include temperature and species distributions due to chemical reaction and external heat sources. Hence, coupling these extended features with either CFD or FEA opens up a wide range of applications as diverse as pharmaceutical industry e.g. drug production, agriculture food and processing industry, mining, construction and agricultural machinery, metals manufacturing, energy production and systems biology. [less ▲]

Detailed reference viewed: 123 (11 UL)
Full Text
Peer Reviewed
See detailComputational Study of the Industrial Synthesis of Tungsten Powders
Estupinan Donoso, Alvaro Antonio UL

in Powder Technology (2019)

Discrete Element Method (DEM) is a highly employed Lagrangian technique to represent particulate systems. When DEM techniques are extended by adding thermochemical conversion of solid particles as well as ... [more ▼]

Discrete Element Method (DEM) is a highly employed Lagrangian technique to represent particulate systems. When DEM techniques are extended by adding thermochemical conversion of solid particles as well as their interaction with the surrounding fluid, numerous challenging applications can be numerically studied. Nevertheless, industrial applications with large number of particles, such as powder synthesis or blast furnaces, are often time or size limited due to the high computational efforts that these simulations demand. This contribution introduces the Agglomerated Particle Method (APM) as a numerical technique aiming to reduce the computational costs of coupled Discrete Element Method and Computational Fluid Dynamics (DEM-CFD) approaches for the thermochemical conversion of powder beds. From experimental and numerical investigation on thermochemical conversion of packed beds has been observed that the temperature or composition of particles in a small spatial domain do not vary significantly. Consequently, one single numerical solution may be representative for all the particles on such a domain. Thus, a collection of neighbor particles are represented by one single agglomerated particle solved by eXtended Discrete Element Method (XDEM) techniques. The proposed model is firstly assessed with classic benchmark problems for heating and drying of packed beds. Later, the model approach is employed for predicting the industrial synthesis of metallic tungsten powder. The comparison of APM predictions with resolved XDEM predictions and experimental data shows the proposed model as a viable technique to solve large scale powder applications, such as tungsten powder production, at feasible time. [less ▲]

Detailed reference viewed: 39 (1 UL)
Full Text
Peer Reviewed
See detailA Discrete-Continuous Method for Predicting Thermochemical Phenomena in a Cement Kiln and Supporting Indirect Monitoring
Copertaro, Edoardo UL; Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL

in Engineering Journal (2018), 22(6), 165-183

Thermochemical phenomena involved in cement kilns are still not well understood because of their complexity, besides technical difficulties in achieving direct measurements of critical process variables ... [more ▼]

Thermochemical phenomena involved in cement kilns are still not well understood because of their complexity, besides technical difficulties in achieving direct measurements of critical process variables. This article addresses the problem of their comprehensive numerical prediction. The presented numerical model exploits Computational Fluid Dynamics and Finite Difference Method approaches for solving the gas domain and the rotating wall, respectively. The description of the thermochemical conversion and movement of the powder particles is addressed with a Lagrangian approach. Coupling between gas, particles and the rotating wall includes momentum, heat and mass transfer. Three-dimensional numerical predictions for a full-size cement kiln are presented and they show agreement with experimental data and benchmark literature. The quality and detail of the results are believed to provide a new insight into the functioning of a cement kiln. Attention is paid to the computational burden of the model and a methodology is presented for reducing the time-to-solution and paving the way for its exploitation in quasireal-time, indirect monitoring. [less ▲]

Detailed reference viewed: 25 (2 UL)
Full Text
See detailHumidity Measurement Analysis for Flow Simulations
Estupinan Donoso, Alvaro Antonio UL

Presentation (2018, August 30)

Detailed reference viewed: 14 (2 UL)
Full Text
Peer Reviewed
See detailExploring a Multiphysics Resolution Approach for Additive Manufacturing
Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL

in JOM (2018)

Metal additive manufacturing (AM) is a fast-evolving technology aiming to efficiently produce complex parts while saving resources. Worldwide, active research is being performed to solve the existing ... [more ▼]

Metal additive manufacturing (AM) is a fast-evolving technology aiming to efficiently produce complex parts while saving resources. Worldwide, active research is being performed to solve the existing challenges of this growing technique. Constant computational advances have enabled multiscale and multiphysics numerical tools that complement the traditional physical experimentation. In this contribution, an advanced discrete--continuous concept is proposed to address the physical phenomena involved during laser powder bed fusion. The concept treats powder as discrete by the extended discrete element method, which predicts the thermodynamic state and phase change for each particle. The fluid surrounding is solved with multiphase computational fluid dynamics techniques to determine momentum, heat, gas and liquid transfer. Thus, results track the positions and thermochemical history of individual particles in conjunction with the prevailing fluid phases' temperature and composition. It is believed that this methodology can be employed to complement experimental research by analysis of the comprehensive results, which can be extracted from it to enable AM processes optimization for parts qualification. [less ▲]

Detailed reference viewed: 59 (11 UL)
Full Text
Peer Reviewed
See detailA comparison between discrete analysis and a multiphase approach for predicting heat conduction in packed beds
Copertaro, Edoardo UL; Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL

in Proceedings of the 10th International Conference on Computer Modeling and Simulation (2018)

the Discrete Element Method (DEM) is a Lagrangian approach initially developed for predicting particles flow. The eXtended Discrete Element Method (XDEM) framework, developed at the LuXDEM Research Centre ... [more ▼]

the Discrete Element Method (DEM) is a Lagrangian approach initially developed for predicting particles flow. The eXtended Discrete Element Method (XDEM) framework, developed at the LuXDEM Research Centre of the University of Luxembourg, extends DEM by including the thermochemical state of particles, as well as their interaction with a Computational Fluid Dynamics (CFD) domain. The level of detail of its predictions makes the XDEM suite a powerful tool for predicting complex industrial processes like steel making, powder metallurgy and additive manufacturing. Like in any other DEM software, the critical aspect of the simulations is the computation requirement that grows rapidly as the number of particles increases. Indeed, such burden currently represents the main bottleneck to its full exploitation in large-scale scenarios. Digital Twin, a research project founded by the European Regional Development Fund (ERDF), aims at drastically accelerate XDEM through different approaches and make it an effective tool for numerical predictions in industry as well as virtual prototyping. The Multiphase Particle- In-Cell (MP-PIC) method has been introduced for reducing the computation burden of DEM. It has been initially developed for predicting particles flow and uses a two-way transfer of information between the Lagrangian entities and a computation grid. The method avoids explicit contact detection and can potentially achieve a drastic reduction of the time-to-solution respect to DEM. The present contribution introduces a multiphase approach for predicting the conductive heat transfer within a static packed bed of particles. Results from a test case are qualitatively and quantitatively compared against reference XDEM predictions. The method can be effectively exploited in combination with MP- PIC for predicting the thermochemical state of particles. [less ▲]

Detailed reference viewed: 19 (0 UL)
Full Text
Peer Reviewed
See detailXDEM for Tuning Lumped Models of Thermochemical Processes Involving Materials in the Powder State
Copertaro, Edoardo UL; Chiariotti, Paolo; Estupinan Donoso, Alvaro Antonio UL et al

in Engineering Journal (2016), 20(5), 187-201

Processes involving materials in gaseous and powder states cannot be modelled without coupling interactions between the two states. XDEM (Extended Discrete Element Method) is a valid tool for tackling ... [more ▼]

Processes involving materials in gaseous and powder states cannot be modelled without coupling interactions between the two states. XDEM (Extended Discrete Element Method) is a valid tool for tackling this issue, since it allows a coupled CFD- DEM simulation to be run. Such strength, however, mainly finds in long computational times its main drawback. This aspect is indeed critical in several applications, since a long computational time is in contrast with the increasing demand for predictive tools that can provide fast and accurate results in order to be used in new monitoring and control strategies. This paper focuses on the use of the XDEM framework as a tool for fine tuning a lumped representation of the non-isothermal decarbonation of a CaCO3 sample in powder state. The tuning of the lumped model is performed exploiting the multi-objective optimization capability of genetic algorithms. Results demonstrate that such approach makes it possible to estimate fast and accurate models to be used, for instance, in the fields of virtual sensing and predictive control. [less ▲]

Detailed reference viewed: 60 (6 UL)
Full Text
Peer Reviewed
See detailA discrete-continuous approach to describe CaCO3 decarbonation in non-steady thermal conditions
Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL; Copertaro, Edoardo et al

in Powder Technology (2015), 275

In cement production, direct measurements of thermal and chemical variables are often unfeasible as a consequence of aggressive environments, moving parts and physical inaccessibility, and therefore ... [more ▼]

In cement production, direct measurements of thermal and chemical variables are often unfeasible as a consequence of aggressive environments, moving parts and physical inaccessibility, and therefore prediction models are essential tools in these types of industrial applications. This article addresses the problem of the numerical prediction of the CaCO3 calcination process, which is the first and the most energy expensive process in clinker production. This study was conducted using the Extended Discrete Element Method (XDEM), a framework which allows a Eulerian approach for the gas phase to be combined with a Lagrange one for the powder phase. A detailed validation of the numerical model was performed by comparison to non-isothermal TG curves for mass loss during the CaCO3 decarbonation process. The complex three-dimensional predictions for solid and gas phases are believed to represent a first step towards a new insight into the cement production process. Thus, the high accuracy and detailed description of the problem addressed, serve as a basis to assess the uncertainty of more simplified models such as those used in soft sensors. [less ▲]

Detailed reference viewed: 128 (16 UL)
Full Text
Peer Reviewed
See detailXDEM Used for Predicting Tungsten-Oxide Reduction
Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL

Scientific Conference (2015, April 27)

Detailed reference viewed: 124 (12 UL)
Full Text
Peer Reviewed
See detailA discrete/continuous numerical approach to multi-physics
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

in IFAC-PapersOnLine (2015), 28(1), 645-650

A variety of technical applications are not only the physics of a single domain, but include several physical phenomena, and therefore are referred to as multi-physics. As long as the phenomena being ... [more ▼]

A variety of technical applications are not only the physics of a single domain, but include several physical phenomena, and therefore are referred to as multi-physics. As long as the phenomena being taken into account is either continuous or discrete i.e. Euler or Lagrangian a homogeneous solution concept can be employed. However, numerous challenges in engineering include continuous and discrete phase simultaneously, and therefore cannot be solved only by continuous or discrete approaches. Problems include both a continuous and a discrete phase are important in applications of the pharmaceutical Industry e.g. drug production, agriculture and food processing industry, mining, construction and Agricultural machinery, metal production, power generation and systems biology. The Extended Discrete Element Method (XDEM) is a novel technique, which provides a significant advance for the coupled discrete and continuous numerical simulation concepts. It expands the dynamics of particles as described by the classical discrete element method (DEM) by a thermodynamic state or stress/strain coupled as fluid flow or structures for each particle in a continuum phase. XDEM additionally estimates properties such as the interior temperature and/or species distribution. These predictive capabilities are extended to fluid flow through an interaction by heat, mass and momentum transfer important for process engineering. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. [less ▲]

Detailed reference viewed: 51 (3 UL)
Full Text
Peer Reviewed
See detailPredicting Tungsten Oxide Reduction with the Extended Discrete Element Method
Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL

in Advances in Powder Metallurgy & Particulate Materials (2015), (Proceedings of the 2015 International Conference on Powder Metallurgy Particulate Materials), 0235--0248

During technical reduction of tungsten trioxide powder in hydrogen atmospheres, the local temperature and the ratio of water vapor to hydrogen partial pressures govern the conversion rate. Water vapor ... [more ▼]

During technical reduction of tungsten trioxide powder in hydrogen atmospheres, the local temperature and the ratio of water vapor to hydrogen partial pressures govern the conversion rate. Water vapor removal rate not only affects the conversion progress, but also drives the final metallic tungsten powder size distribution. The amount of water vapor inside the bed depends on the hydrogen flow, the height of powder beds and the size characteristics of the initial oxide. The chemically aggressive environment and high temperatures make it difficult to do the measurements inside the reactors for studying or control the process. On the other hand, multi-physics computational techniques help to understand the evolution of the complex phenomena involved in the process. This contribution presents the eXtended Discrete Element Method as a novel approach to investigate the complex thermochemical conversion of tungsten oxides into tungsten metal. The recently emerged technique is based on a coupled discrete and continuous numerical simulation framework. In the study, an advanced and consolidated two-phase Computational Fluid Dynamics (CFD) tool for porous media represents gaseous phase penetration and transport. The discrete feedstock description includes one-dimensional and transient distributions of temperature and species for each powder particle. This allows gaining a new and valuable insight into the process, which may lead into finer tungsten powder production, and consequently more resistant tungsten carbide products. Transient and spatial results for powder composition, gas species as well as a mass loss comparison with experimental data for non-isothermal hydrogen reduction of tungsten trioxide are demonstrated and discussed. [less ▲]

Detailed reference viewed: 18 (1 UL)
Full Text
See detailIntroduction to the eXtended Discrete Element Method
Estupinan Donoso, Alvaro Antonio UL

Learning material (2014)

Detailed reference viewed: 96 (3 UL)
Full Text
Peer Reviewed
See detaileXtended Discrete Element Method used for predicting tungsten-oxide reduction in a dry-hydrogen atmosphere
Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL

in LLanes, Luis (Ed.) eXtended Discrete Element Method used for predicting tungsten-oxide reduction in a dry-hydrogen atmosphere (2014, March 10)

Detailed reference viewed: 200 (23 UL)
Full Text
Peer Reviewed
See detailXDEM employed to predict reduction of tungsten oxide in a dry hydrogen atmosphere
Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL

in International Journal of Refractory Metals & Hard Materials (2014)

Abstract The Extended Discrete Element Method (XDEM) is a novel concept to model tungsten oxides reduction. The concept extends the classical discrete element method (DEM) with additional properties such ... [more ▼]

Abstract The Extended Discrete Element Method (XDEM) is a novel concept to model tungsten oxides reduction. The concept extends the classical discrete element method (DEM) with additional properties such as the thermodynamic state. Moreover, the concept treats a solid phase represented by particles, and a fluid phase as two distinguished phases that are coupled through heat, mass and momentum transfer. hydrogen atmosphere is modelled by a direct oxygen removal from the solid oxides mechanism for which temperature and reaction progress is described by the Discrete Particle Method (DPM). An outstanding feature of the herein proposed numerical concept is that powder particles are treated as individual entities which are described by its thermodynamic state, e.g. temperature and species distribution within the particle. Therefore, it allows a detailed and accurate characterisation of isothermal literature experimentation with a high degree of accuracy. Therefore, the current approach provides a new and deep insight into the process, because particle temperatures, concentration of species and interaction of particles with the environment are inaccessible in a furnace during experiments. [less ▲]

Detailed reference viewed: 113 (8 UL)
Full Text
Peer Reviewed
See detailThe extended discrete element method (XDEM) applied to drying of a packed bed
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

in Industrial Combustion (2014), 14

A vast number of engineering applications involve physics not solely of a single domain but of several physical phenomena, and therefore are referred to as multi-physical. As long as the phenomena ... [more ▼]

A vast number of engineering applications involve physics not solely of a single domain but of several physical phenomena, and therefore are referred to as multi-physical. As long as the phenomena considered are to be treated by either a continuous (i.e. Eulerian) or discrete (i.e. Lagrangian) approach, numerical solution methods may be employed to solve the problem. However, numerous challenges in engineering exist and evolve; those include modelling a continuous and discrete phase simultaneously, which cannot be solved accurately by continuous or discrete approaches only. Problems that involve both a continuous and a discrete phase are important in applications as diverse as the pharmaceutical industry, the food processing industry, mining, construction, agricultural machinery, metals manufacturing, energy production and systems biology. A novel technique referred to as Extended Discrete Element Method (XDEM) has been developed that offers a significant advancement for coupled discrete and continuous numerical simulation concepts. XDEM extends the dynamics of granular materials or particles as described through the classical discrete element method (DEM) to include additional properties such as the thermodynamic state or stress/strain for each particle coupled to a continuous phase such as a fluid flow or a solid structure. Contrary to a continuum mechanics concept, XDEM aims at resolving the particulate phase through the various processes attached to particles. While DEM predicts the spatial-temporal position and orientation for each particle, XDEM additionally estimates properties such as the internal temperature and/or species distribution during drying, pyrolysis or combustion of solid fuel material such as biomass in a packed bed. These predictive capabilities are further extended by an interaction with fluid flow by heat, mass and momentum transfer and the impact of particles on structures. © International Flame Research Foundation, 2014. [less ▲]

Detailed reference viewed: 52 (3 UL)
Full Text
Peer Reviewed
See detaileXtended Discrete Element Method used for convective heat transfer predictions
Estupinan Donoso, Alvaro Antonio UL; Hoffmann, Florian UL; Peters, Bernhard UL

in International Review of Mechanical Engineering (2013), 7(2), 329-336

Packed bed reactors dominate a broad range of engineering applications. In a packed bed reactor, heat is transferred from the solid particles to the gas flow stream through the void space between ... [more ▼]

Packed bed reactors dominate a broad range of engineering applications. In a packed bed reactor, heat is transferred from the solid particles to the gas flow stream through the void space between particles. Using a XDEM approach, continuous and discrete phases have been coupled in order to predict convective heat transfer between solid and fluid within packed beds. For the solid matrix a discrete intra-particle model, namely DPM, was used to solve for each particle of the bed, and a CFD tool was employed to resolve the fluid flow. [less ▲]

Detailed reference viewed: 251 (36 UL)
Full Text
Peer Reviewed
See detailDie Extended Discrete Element Method (XDEM) für multiphysikalische Anwendungen
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

Scientific Conference (2013)

A vast number of engineering applications include a continuous and discrete phase simultaneously, and therefore, cannot be solved accurately by continuous or discrete approaches only. Problems that ... [more ▼]

A vast number of engineering applications include a continuous and discrete phase simultaneously, and therefore, cannot be solved accurately by continuous or discrete approaches only. Problems that involve both a continuous and a discrete phase are important in applications as diverse as pharmaceutical industry e.g. drug production, agriculture food and processing industry, mining, construction and agricultural machinery, metals manufacturing, energy production and systems biology. <br />A novel technique referred to as Extended Discrete Element Method (XDEM) is developed, that offers a significant advancement for coupled discrete and continuous numerical simulation concepts. XDEM treats the solid phase representing the particles and the fluidised phase usually a fluid phase or a structure as two distinguished phases that are coupled through heat, mass and momentum transfer. An outstanding feature of the numerical concept is that each particle is treated as an individual entity that is described by its thermodynamic state e.g. temperature and reaction progress and its position and orientation in time and space. The thermodynamic state includes one-dimensional and transient distributions of temperature and species within the particle and therefore, allows a detailed and accurate characterisation of the reaction progress in a fluidised bed. Thus, the proposed methodology provides a high degree of resolution ranging from scales within a particle to the continuum phase as global dimensions. <br />These superior features as compared to traditional and pure continuum mechanics approaches are applied to predict drying of wood particles in a packed bed and impact of particles on a membrane. Pre- heated air streamed through the packed bed, and thus, heated the particles with simultaneous evaporation of moisture. Water vapour is transferred into the gas phase at the surface of the particles and transported to the exit of the reactor. A rather inhomogeneous drying process in the upper part of the reactor with higher temperatures around the circumference of the inner reactor wall was observed. The latter is due to increased porosity in conjunction with higher mass flow rates than in the centre of the reactor, and thus, augmented heat transfer. A comparison of the weight loss over time agreed well with measurements. <br />Under the impact of falling particles the surface of a membrane deforms that conversely affects the motion of particles on the surface. Due to an increasing vertical deformation particles roll or slide down toward the bottom of the recess, where they are collected in a heap. Furthermore, during initial impacts deformation waves are predicted that propagate through the structure, and may, already indicate resonant effects already before a prototype is built. Hence, the Extended Discrete Element Method offers a high degree of resolution avoiding further empirical correlations and extends the knowledge into the underlying physics. Although most of the work load concerning CFD and FEM is arranged in the ANSYS workbench, a complete integration is intended that allows for a smooth workflow of the entire simulation environment. [less ▲]

Detailed reference viewed: 297 (26 UL)