Optimizing the operation of straight-grate iron-ore pellet induration systems using process models

Mathematical models of straight-grate pellet induration processes have been developed and carefully validated by a number of workers over the past two decades. However, the subsequent exploitation of these models in process optimization is less clear, but obviously requires a sound understanding of how the key factors control the operation. In this article, we show how a thermokinetic model of pellet induration, validated against operating data from one of the Iron Ore Company of Canada (IOCC) lines in Canada, can be exploited in process optimization from the perspective of fuel efficiency, production rate, and product quality. Most existing processes are restricted in the options available for process optimization. Here, we review the role of each of the drying (D), preheating (PH), firing (F), after-firing (AF), and cooling (C) phases of the induration process. We then use the induration process model to evaluate whether the first drying zone is best to use on the up- or down-draft gas-flow stream, and we optimize the on-gas temperature profile in the hood of the PH, F, and AF zones, to reduce the burner fuel by at least 10 pct over the long term. Finally, we consider how efficient and flexible the process could be if some of the structural constraints were removed (i.e., addressed at the design stage). The analysis suggests it should be possible to reduce the burner fuel lead by 35 pct, easily increase production by 5+ pct, and improve pellet quality.

Multilevel mesh partitioning for optimizing domain shape

Multilevel algorithms are a successful class of optimization techniques that address the mesh partitioning problem for mapping meshes onto parallel computers. They usually combine a graph contraction algorithm together with a local optimization method that refines the partition at each graph level. To date, these algorithms have been used almost exclusively to minimize the cut-edge weight in the graph with the aim of minimizing the parallel communication overhead. However, it has been shown that for certain classes of problems, the convergence of the underlying solution algorithm is strongly influenced by the shape or aspect ratio of the subdomains. Therefore, in this paper, the authors modify the multilevel algorithms to optimize a cost function based on the aspect ratio. Several variants of the algorithms are tested and shown to provide excellent results.

Portability, predictability and performance for parallel computing: BSP in practice

We report on practical experience using the Oxford BSP Library to parallelize a large electromagnetic code, the British Aerospace finite-difference time-domain code EMMA T:FD3D. The Oxford BS Library is one of the first realizations of the Bulk Synchronous Parallel computational model to be targeted at numerically intensive scientific (typically Fortran) computing. The BAe EMMA code is one of the first large-scale applications to be parallelized using this library, and it is an important demonstration of the cost effectiveness of the BSP approach. We illustrate how BSP cost-modelling techniques can be used to predict and optimize performance for single-source programs across different parallel platforms. We provide predicted and observed performance figures for an industrial-strength, single-source parallel code for a variety of real parallel architectures: shared memory multiprocessors, workstation clusters and massively parallel platforms.

The development of a CFD based simulator for water mist suppression systems: the development of the fire submodel

The FIRE Detection and Suppression Simulation (FIREDASS) project was concerned with the development of water misting systems as a possible replacement for halon based fire suppression systems currently used in aircraft cargo holds and ship engine rooms. As part of this program of work, a computational model was developed to assist engineers optimize the design of water mist suppression systems. The model is based on Computational Fluid Dynamics (CFD) and comprised of the following components: fire model; mist model; two-phase radiation model; suppression model; detector/activation model. In this paper the FIREDASS software package is described and the theory behind the fire and radiation sub-models is detailed. The fire model uses prescribed release rates for heat and gaseous combustion products to represent the fire load. Typical release rates have been determined through experimentation. The radiation model is a six-flux model coupled to the gas (and mist) phase. As part of the FIREDASS project, a detailed series of fire experiments were conducted in order to validate the fire model. Model predictions are compared with data from these experiments and good agreement is found.

Mathematical modelling: a laser soldering process for an optoelectronics butterfly package

For sensitive optoelectronic components, traditional soldering techniques cannot be used because of their inherent sensitivity to thermal stresses. One such component is the Optoelectronic Butterfly Package which houses a laser diode chip aligned to a fibre-optic cable. Even sub-micron misalignment of the fibre optic and laser diode chip can significantly reduce the performance of the device. The high cost of each unit requires that the number of damaged components, via the laser soldering process, are kept to a minimum. Mathematical modelling is undertaken to better understand the laser soldering process and to optimize operational parameters such as solder paste volume, copper pad dimensions, laser solder times for each joint, laser intensity and absorption coefficient. Validation of the model against experimental data will be completed, and will lead to an optimization of the assembly process, through an iterative modelling cycle. This will ultimately reduce costs, improve the process development time and increase consistency in the laser soldering process.

"System in package technology" - design for manufacture challenges

Purpose – To present key challenges associated with the evolution of system-in-package technologies and present technical work in reliability modeling and embedded test that contributes to these challenges. Design/methodology/approach – Key challenges have been identified from the electronics and integrated MEMS industrial sectors. Solutions to optimising the reliability of a typical assembly process and reducing the cost of production test have been studied through simulation and modelling studies based on technology data released by NXP and in collaboration with EDA tool vendors Coventor and Flomerics. Findings – Characterised models that deliver special and material dependent reliability data that can be used to optimize robustness of SiP assemblies together with results that indicate relative contributions of various structural variables. An initial analytical model for solder ball reliability and a solution for embedding a low cost test for a capacitive RF-MEMS switch identified as an SiP component presenting a key test challenge. Research limitations/implications – Results will contribute to the further development of NXP wafer level system-in-package technology. Limitations are that feedback on the implementation of recommendations and the physical characterisation of the embedded test solution. Originality/value – Both the methodology and associated studies on the structural reliability of an industrial SiP technology are unique. The analytical model for solder ball life is new as is the embedded test solution for the RF-MEMS switch.

The tilt casting of titanium aluminides

TiAl castings are prone to various defects including bubbles entrained during the turbulent filling of moulds. The present research has exploited the principles of the Durville tilt casting technique to develop a novel process in which the Induction Skull Melting (ISM) of TiAl alloys in a vacuum chamber has been combined with controlled tilt pouring to achieve the tranquil transfer of the metal into a hot ceramic shell mould. Practical casting equipment has been developed to evaluate the feasibility of this process in parallel with the development of novel software to simulate and optimize it. The PHYSICA CFD code was used to simulate the filling, heat transfer and solidification during tilt pouring using a number of free surface modelling techniques, including the novel Counter Diffusion Method (CDM). In view of the limited superheat, particular attention was paid to the mould design to minimize heat loss and gas entrainment caused by interaction between the counter-flowing metal and gas streams. The model has been validated against real-time X-ray movies of the tilt casting of aluminium and against TiAl blade castings. Modelling has contributed to designing a mould to promote progressive filling of the casting and has led to the use of a parabolic tilting cycle to balance the competing requirements for rapid filling to minimize the loss of superheat and slow filling minimize the turbulence-induced defects.

Optimization of an open-ended microwave oven for microelectronics packaging

A physically open, but electrically shielded, microwave open oven can be produced by virtue of the evanescent fields in a waveguide below cutoff. The below cutoff heating chamber is fed by a transverse magnetic resonance established in a dielectric-filled section of the waveguide exploiting continuity of normal electric flux. In order to optimize the fields and the performance of the oven, a thin layer of a dielectric material with higher permittivity is inserted at the interface. Analysis and synthesis of an optimized open oven predicts field enhancement in the heating chamber up to 9.4 dB. Results from experimental testing on two fabricated prototypes are in agreement with the simulated predictions, and demonstrate an up to tenfold improvement in the heating performance. The open-ended oven allows for simultaneous precision alignment, testing, and efficient curing of microelectronic devices, significantly increasing productivity gains.

Model-based pilot and data power adaptation in psam with periodic delayed feedback

We consider the optimum design of pilot-symbol-assisted modulation (PSAM) schemes with feedback. The received signal is periodically fed back to the transmitter through a noiseless delayed link and the time-varying channel is modeled as a Gauss-Markov process. We optimize a lower bound on the channel capacity which incorporates the PSAM parameters and Kalman-based channel estimation and prediction. The parameters available for the capacity optimization are the data power adaptation strategy, pilot spacing and pilot power ratio, subject to an average power constraint. Compared to the optimized open-loop PSAM (i.e., the case where no feedback is provided from the receiver), our results show that even in the presence of feedback delay, the optimized power adaptation provides higher information rates at low signal-to-noise ratios (SNR) in medium-rate fading channels. However, in fast fading channels, even the presence of modest feedback delay dissipates the advantages of power adaptation.