References of "Estupinan Donoso, Alvaro Antonio 50001760"
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See detailHEAT AND MASS TRANSFER BETWEEN XDEM & OPENFOAM USING PRECICE COUPLING LIBRARY
Adhav, Prasad UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

Scientific Conference (2022, June 09)

This work demonstrates the rapid development of a simulation environment to achieve Heat and Mass Transfer (HMT) between Discrete Element Methods (DEM) and Computa- tional Fluid Dynamics (CFD). The HMT ... [more ▼]

This work demonstrates the rapid development of a simulation environment to achieve Heat and Mass Transfer (HMT) between Discrete Element Methods (DEM) and Computa- tional Fluid Dynamics (CFD). The HMT coupling can be employed to simulate processes such as drying, pyrolysis, combustion, melting, solid-fluid reactions etc and have indus- trial applications such as biomass furnaces, boilers, heat exchangers, and flow through packed beds. This shows that diverse CFD features and solvers need to be coupled with DEM in order to achieve various applications mentioned above. The proposed DEM-CFD Eulerian-Lagrangian coupling for heat and mass transfer is achieved by employing the preCICE coupling library[1] on volumetric meshes. In our prototype, we use the eXtended Discrete Element Method (XDEM)[2] for handling DEM calculations and OpenFOAM for the CFD. The XDEM solver receives various CFD data fields such as fluid properties, and flow conditions exchanged through preCICE, which are used to set boundary conditions for particles. Various heat transfer and mass transfer laws have been implemented in XDEM to steer HMT source term computations. The heat and mass source terms computed by XDEM are transferred to CFD solver and added as source. These source terms represent particles in CFD. The generic coupling interface of preCICE, XDEM and its adapter allows to tackle a di- verse range of applications. We demonstrate the heat, mass & momentum coupling capa- bilities through various test cases and then compared with our legacy XDEM-OpenFOAM coupling and experimental results. [less ▲]

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See detailXDEM study of burden distribution in iron ore pellet firing
Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL; Amani, H et al

in Ironmaking and Steelmaking (2022), 49(6), 615-625

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See detailMathematical modeling of thermal behavior of single iron ore pellet during heat hardening oxidation
Amani, Hafez; Alamdari, E.K; Ale Ebrahim, H. et al

in Journal of Thermal Analysis and Calorimetry (2021)

In this study, a one-dimensional generic model capable of being integrated with reactor scale models is proposed for a single pellet through solving the transient diferential conservation equations ... [more ▼]

In this study, a one-dimensional generic model capable of being integrated with reactor scale models is proposed for a single pellet through solving the transient diferential conservation equations. Predicted results comparison with the experimental data showed close agreement. In addition, the model was used to investigate the relevance of physical characteristics of pellet, reacting gas composition, difusion factors, and prevailing regime. It was found that the pure magnetite pellet could achieve a temperature rise of about 245 K at oxygen concentration of 40 vol.%, whereas the maximum temperature diference inside the pellet was approximately 24 K. Moreover, increasing pellet size, the maximum attainable temperature reached a peak and then leveled out. Furthermore, by decreasing the pore diameter, the pellet size with peak temperature shifted to the smaller pellet sizes. Analyzing the numerical results also showed that for the small pellet sizes, shortening the difusion path leads to the spreading of the reaction interface. The modeling methodology herein can be applied to any particulate processes and is not limited to the aforementioned case. [less ▲]

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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 ▲]

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See detailIdentification of optimal process parameters in selective laser sintering
Kabore, Brice Wendlassida UL; Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL et al

Scientific Conference (2019)

Selective Laser Sintering (SLS) is an efficient method for manufacturing complex geometries with high strength and durability. The SLS process subjects a powder bed to thermal cycles allowing theparticles ... [more ▼]

Selective Laser Sintering (SLS) is an efficient method for manufacturing complex geometries with high strength and durability. The SLS process subjects a powder bed to thermal cycles allowing theparticles to coalesce into a solid part without being completely melted. The thermal cycles along withthe thermo-mechanical properties of the powder dictate the properties of the manufactured part.Choosing optimal parameters that lead to functional parts with the desired stiffness, density andstrength requires extensive testing. Microscales models such that Molecular dynamics and DiscreteParticles offer great flexibilities and capacity to reproduce the SLS process from the physical point ofview [1].This study presents a multi-physical model based on the Extended Discrete Element Method forsimulating the thermodynamics and thermo-mechanics that take place in the SLS process as well asthe microstructure evolution of the part. A thermo-viscoelastic constitutive model for discreteparticles is coupled with heat transfer, sintering and fracture to predict.A genetic algorithm is employed to identify optimal process parameters, namely laser power,scanning speed, preheating temperature and layer thickness in an automated iterative process. Theseparameters are identified so that the density and strength of the cooled part meet the target values. [less ▲]

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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 (2019), 44

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 ▲]

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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 ▲]

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See detailHumidity Measurement Analysis for Flow Simulations
Estupinan Donoso, Alvaro Antonio UL

Presentation (2018, August 30)

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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 ▲]

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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 ▲]

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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 ▲]

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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 ▲]

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See detailXDEM Used for Predicting Tungsten-Oxide Reduction
Estupinan Donoso, Alvaro Antonio UL; Peters, Bernhard UL

Scientific Conference (2015, April 27)

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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 ▲]

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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 ▲]

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See detailIntroduction to the eXtended Discrete Element Method
Estupinan Donoso, Alvaro Antonio UL

Learning material (2014)

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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: 235 (28 UL)