Modelling of chemical reactions in metallurgical processes

Since the last three decades, the study of reduction of iron-ore has gained much attention as it is considered a core process for the steel industry. Fluidized bed and moving bed reactors are utilized to reduce the iron-ore efficiently. As reducing agents coal, coke or natural gases are used, which are released as CO2 gas, or sometimes in small amounts as H2O to the environment. The conditions in these reactors are harsh and provide limited accessibility, therefore computational tools are used to investigate them. One such tool is the CFD-DEM method, where the reacting gas species and the governing equations for the gas flow are calculated in the Eulerian (CFD) side, whereas the particle reactions and equation of motion are calculated in the Lagrangian (DEM) side. In the current work, the CFD-DEM method is extended to cover the most dominant types of models for heterogeneous reactions between submerged solids and fluids. One of these models is the Shrinking Particle Model (SPM), which is used to verify the commu- nication framework between the CFD and DEM sides by running preliminary test cases. Another model is the Unreacted Shrinking Core Model (USCM), which is considered as a good model for a reality like iron-ore reduction modelling

The Effect of Propeller Pitch on Ship Propulsion

The appropriate choice of a marine engine identified by using self-propulsion model tests is compulsory, in particular with respect to the improvement of vessel performances. Numerical simulations or experimental methods provide insight into the problem of flow, where fixed pitch propellers or controllable pitch propellers are preferred. While calculation methods are time consuming and computationally demanding for both propeller types, hydrodynamic performance assessment has more workload in controllable pitch propellers. This paper aims to describe and demonstrate the practicability and effectiveness of the self-propulsion estimation (SPE) method in understanding the effect of propeller pitch on ship propulsion. Technically, the hydrostatic and geometric characteristics of the vessel and open-water propeller performances are the focal aspects that affect the self-propulsion parameters estimated by the SPE method. The input coefficients for SPE have been identified using a code that generates propeller open-water performance curves. The propellers utilized to study pitch variations have been based on the Wageningen B-series propeller database. The method was first validated on the full size Seiun Maru ship whose sea trial tests are available in literature. After extensive calculations for full size KCS and DTC at service speeds, the study focused on the effect of the Froude number on propulsion parameters. These calculations have demonstrated that greater propeller pitch does not improve propulsion efficiency, and that maximum propeller efficiency changes with a ship\u27s forward speed

Microstructural defect properties of InGaN/GaN blue light emitting diode structures

Cataloged from PDF version of article.In this paper, we study structural and morphological properties of metal-organic chemical vapour deposition-grown InGaN/GaN light emitting diode (LED) structures with different indium (In) content by means of high-resolution X-ray diffraction, atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FTIR), photoluminescence (PL) and current-voltage characteristic (I-V). We have found out that the tilt and twist angles, lateral and vertical coherence lengths of mosaic blocks, grain size, screw and edge dislocation densities of GaN and InGaN layers, and surface roughness monotonically vary with In content. Mosaic defects obtained due to temperature using reciprocal lattice space map has revealed optimized growth temperature for active InGaN layer of MQW LED. It has been observed in this growth temperature that according to AFM result, LED structure has high crystal dimension, and is rough whereas according to PL and FTIR results, bandgap energy shifted to blue, and energy peak half-width decreased at high values. According to I-V measurements, it was observed that LED reacted against light at optimized temperature. In conclusion, we have seen that InGaN MQW structure's structural, optical and electrical results supported one another

Thesis Pre-Processing ECG & Respiratory Signals for Detection of Stress

The main purpose of this thesis is the removal of different kinds of artifacts from incoming signals and the identification of relevant information which can be utilized for further analysis. This thesis proposes two designs which are used for the pre-processing of the electrocardiogram (ECG) signal and the respiratory signal. The ECG signal system design consists of an artifact removal system, a three-step quality check at the initial stage and after pre-processing the raw signal. The respiratory signal system consists of a two-step quality check, a artifact removal part and a part which calculates the respiratory rate from the respiratory signal

Modelling of chemical reactions in metallurgical processes

Since the last three decades, the study of reduction of iron-ore has gained much attention as it is considered a core process for the steel industry. Fluidized bed and moving bed reactors are utilized to reduce the iron-ore efficiently. As reducing agents coal, coke or natural gases are used, which are released as CO2 gas, or sometimes in small amounts as H2O to the environment. The conditions in these reactors are harsh and provide limited accessibility, therefore computational tools are used to investigate them. One such tool is the CFD-DEM method, where the reacting gas species and the governing equations for the gas flow are calculated in the Eulerian (CFD) side, whereas the particle reactions and equation of motion are calculated in the Lagrangian (DEM) side. In the current work, the CFD-DEM method is extended to cover the most dominant types of models for heterogeneous reactions between submerged solids and fluids. One of these models is the Shrinking Particle Model (SPM), which is used to verify the commu- nication framework between the CFD and DEM sides by running preliminary test cases. Another model is the Unreacted Shrinking Core Model (USCM), which is considered as a good model for a reality like iron-ore reduction modelling

A Lagrangian‐Eulerian hybrid model for the simulation of direct reduction of iron ore in fluidized beds

Fluidized bed and moving bed reactors are one of the most important technologies in several branches of process industry. Especially, it is known since decades that iron can be reduced rapidly and efficiently from iron carrier materials using such. The primary energy sources and reducing agents are natural gas, coal, coke, pulverized coal, which are finally released as CO2 and in a lesser extent as H2O to the environment. Iron reduction consumes about 70% of the energy during steelmaking therefore offering potential in energy and CO2 savings. Due to the limited accessibility for measurements, simulation methods have become one of the most important tools for optimizing the iron making processes. While the two-fluid model (Schneiderbauer et al., 2012) would be a good candidate to attack the simulation of large-scale multi-phase processes it lacks from a proper representation of the particle size distribution and the related physical phenomena. This, in turn, gives rise to particle-based approaches, such as the coupling between CFD and DEM methods, which can easily handle particle segregation, particle growth and particle mixing. Furthermore, chemical reactions can be evaluated per particle and it is not required to transfer these reactions to a continuum representation. However, CFD-DEM approaches require an appropriate coarse-graining to considerably reduce their computational demands. We, therefore, present a generalization of the Lagrangian-Eulerian hybrid model for the numerical assessment of reacting poly-disperse gas-solid flows (Schneiderbauer et al., 2016b) to fluidized beds used for iron ore reduction. The main idea of such a modeling strategy is to use a combination of a Lagrangian discrete phase model (DPM) and a coarse-grained two-fluid model (TFM) to take advantage of the benefits of those two different formulations. On the one hand, the DPM model unveils additional information such as the local particle size distribution, which is not covered by TFM. On the other hand, the TFM solution deflects the DPM trajectories due to the inter-particle stresses. This hybrid approach further enables the efficient evaluation of the gas-solid phase reduction of iron ore at a particle level using DPM. The predictive capability and numerical efficiency of this reactive hybrid modeling approach is demonstrated in the case of a lab-scale fluidized bed. The results show that the model is able to correctly predict fractional reduction of the iron ore. The results further give a closer insight about the temperatures and reaction gas consumption due to the reduction process.The authors want to acknowledge the support of Dr. Christoph Klaus-Nietrost, who provided the c-code for the reduction model developed during his PhD work "Development of Conversion Models for Iron-Carriers and Additives within a Melter-Gasifier or Blast Furnace" (Institute for Energy Systems and Thermodynamics, TU Vienna, 2016). This work was funded by the Christian-Doppler Research Association, the Austrian FederalMinistry of Economy, Family and Youth, and the Austrian National Foundation for Research, Technology and Development. The author also wants to acknowledge the financial support from the K1MET center for metallurgical research in Austria (www.k1-met.com).publishedVersio