Numerical study of the influence of particle size and packing on pyrolysis products using XDEM

in International Communications in Heat and Mass Transfer (2016), 71

Conversion of biomass as a renewable source of energy is one of the most challenging topics in industry and academy. Numerical models may help designers to understand better the details of the involved ... [more ▼]

Conversion of biomass as a renewable source of energy is one of the most challenging topics in industry and academy. Numerical models may help designers to understand better the details of the involved processes within the reactor, to improve process control and to increase the efficiency of the boilers. In this work, XDEM as an Euler-Lagrange model is used to predict the heat-up, drying and pyrolysis of biomass in a packed bed of spherical biomass particles. The fluid flow through the void space of a packed bed (which is formed by solid particles) is modeled as three-dimensional flow through a porous media using a continuous approach. The solid phase forming the packed bed is represented by individual, discrete particles which are described by a Lagrangian approach. On the particle level, distributions of temperature and species within a single particle are accounted for by a system of one-dimensional and transient conservation equations. The model is compared to four sets of experimental data from independent research groups. Good agreements with all experimental data are achieved, proving reliability of the used numerical methodology. The proposed model is used to investigate the impact of particle size in combination with particle packing on the char production. For this purpose, three setups of packed beds differing in particle size and packing mode are studied under the same process conditions. The predicted results show that arranging the packed bed in layers of small and large particles may increase the final average char yield for the entire bed by 46 %. © 2015 Elsevier B.V. [less ▲]

Performance Evaluation of the XDEM framework on the OpenStack Cloud Computing Middleware

in Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering (2015, February)

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing ... [more ▼]

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing middleware using our XDEM application simulating the pyrolysis of biomass as a benchmark. We propose a systematic study based on a fully automated benchmarking framework to evaluate 3 different configurations: Native (i.e. no virtualization), OpenStack with KVM and XEN hypervisors. Our approach features the following advantages: real user application, the fair comparison using the same hardware, the large scale distributed execution, while fully automated and reproducible. Experiments has been run on two different clusters, using up to 432 cores. Results show a moderate overhead for sequential execution and a significant penalty for distributed execution under the Cloud middleware. The overhead on multiple nodes is between 10% and 30% for OpenStack/KVM and 30% and 60% for OpenStack/XEN. [less ▲]

A discrete/continuous numerical approach to multi-physics

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 ▲]

Application of XDEM as a novel approach to predict drying of a packed bed

in International Journal of Thermal Sciences (2014), 75

A majority of solid fuels especially biomass contains moisture, which may amount up to the mass of the dry particles. Thus it is important to determine the details of drying when considering biomass as a ... [more ▼]

A majority of solid fuels especially biomass contains moisture, which may amount up to the mass of the dry particles. Thus it is important to determine the details of drying when considering biomass as a fuel. Therefore, the objective of this work is to apply the Extended Discrete Element Method (XDEM) as a numerical simulation framework to prediction of drying within a packed bed reactor. The novel numerical concept resolves the particulate phase by the classical Discrete Element Method (DEM), however, extends it by the thermodynamic state e.g. temperature distribution and evaporation of water content of each particle in conjunction with heat and mass transfer to the surrounding gas phase. The latter is described by a continuous approach namely a set of differential conservation equations as employed in Computational Fluid Dynamics (CFD) for porous media. Comparison with measurement was carried out and good agreement was achieved. [less ▲]

An Integral Approach to Multi-physics Application for Packed Bed Reactors

in 24th European Symposium on Computer Aided Process Engineering, ESCAPE 24 (2014)

MHD natural convection and entropy generation in a trapezoidal enclosure using Cu–water nanofluid

in Computers and Fluids (2013)

Application of the Extended Discrete Element Method (XDEM) in Computer-Aided Process Engineering

Scientific Conference (2013)

Enhanced Thermal Process Engineering by the Extended Discrete Element Method (XDEM)

in Universal Journal of Engineering Science (2013), 1

A vast number of engineering applications <br />include a continuous and discrete phase simultaneously, <br />and therefore, cannot be solved accurately by continu- <br />ous or discrete approaches only ... [more ▼]

A vast number of engineering applications <br />include a continuous and discrete phase simultaneously, <br />and therefore, cannot be solved accurately by continu- <br />ous or discrete approaches only. Problems that involve <br />both a continuous and a discrete phase are important <br />in applications as diverse as pharmaceutical industry <br />e.g. drug production, agriculture food and process- <br />ing industry, mining, construction and agricultural <br />machinery, metals manufacturing, energy production <br />and systems biology. A novel technique referred to as <br />Extended Discrete Element Method (XDEM) is devel- <br />oped, that o ers a signi cant advancement for coupled <br />discrete and continuous numerical simulation concepts. <br />The Extended Discrete Element Method extends the <br />dynamics of granular materials or particles as described <br />through the classical discrete element method (DEM) to <br />additional properties such as the thermodynamic state <br />or stress/strain for each particle coupled to a continuum <br />phase such as <br />uid <br />ow or solid structures. Contrary <br />to a continuum mechanics concept, XDEM aims at <br />resolving the particulate phase through the various <br />processes attached to particles. While DEM predicts <br />the spacial-temporal position and orientation for each <br />particle, XDEM additionally estimates properties such <br />as the internal temperature and/or species distribution. <br />These predictive capabilities are further extended by an <br />interaction to <br />uid <br />ow by heat, mass and momentum <br />transfer and impact of particles on structures. [less ▲]

Die Extended Discrete Element Method (XDEM) als integraler Ansatz für reagierende Mehrphasenströmungen

in 26. Deutscher Flammentag Verbrennung und Feuerung (2013)