Operations research applications in the plywood industry

There are several areas in the plywood industry where Operations Research techniques have greatly assisted in better decision-making. These have resulted in improved profits, reduction of wood losses and better utilization of resources. Realizing these, some of the plywood manufacturing firms in the developed countries have established separate Operations Research departments or divisions. In the face of limited raw-material resources, raising costs and a competitive environment, the benefits attributable to the use of these techniques are becoming more and more significant.     

The microscopy cell (MicCell), a versatile modular flowthrough system for cell biology, biomaterial research, and nanotechnology

We describe a novel microfluidic perfusion system for high-resolution microscopes. Its modular design allows pre-coating of the coverslip surface with reagents, biomolecules, or cells. A poly(dimethylsiloxane) (PDMS) layer is cast in a special molding station, using masters made by photolithography and dry etching of silicon or by photoresist patterning on glass or silicon. This channel system can be reused while the coverslip is exchanged between experiments. As normal fluidic connectors are used, the link to external, computer-programmable syringe pumps is standardized and various fluidic channel networks can be used in the same setup. The system can house hydrogel microvalves and microelectrodes close to the imaging area to control the influx of reaction partners. We present a range of applications, including single-molecule analysis by fluorescence correlation spectroscopy (FCS), manipulation of single molecules for nanostructuring by hydrodynamic flow fields or the action of motor proteins, generation of concentration gradients, trapping and stretching of live cells using optical fibers precisely mounted in the PDMS layer, and the integration of microelectrodes for actuation and sensing.     

Modeling the tensile properties in β-processed α/β Ti alloys

The development of a set of computational tools that permit microstructurally based predictions for the tensile properties of commercially important titanium alloys, such as Ti-6Al-4V, is a valuable step toward the accelerated maturation of materials. This paper will discuss the development of neural network models based on a Bayesian framework to predict the yield and ultimate tensile strengths of Ti-6Al-4V at room temperature. The development of such rules-based model requires the population of extensive databases, which in the present case are microstructurally based. The steps involved in database development include producing controlled variations of the microstructure using novel approaches to heat treatments, the use of standardized stereology protocols to characterize and quantify microstructural features rapidly, and mechanical testing of the heat-treated specimens. These databases have been used to train and test neural network models for prediction of tensile properties. In addition, these models have been used to identify the influence of individual microstructural features on the tensile properties, consequently guiding the efforts toward development of more robust mechanistically based models. Based on the neural network model, it is possible to investigate the influence of individual microstructural features on the tensile properties, and in certain cases these dependencies can point toward unrecognized phenomena. For example, the apparently unexpected trend of increase in tensile strength with increasing prior β-grain size has led to the determination of the pronounced role of the basketweave microstructure in strengthening these alloys, especially in case of larger prior β grains. This article is based on a presentation made in the symposium “Computational Aspects of Mechanical Properties of Materials,” which occurred at the 2005 TMS Annual Meeting, February 13–17, 2005, in San Francisco, CA, under the auspices of the MPMD-Computational Materials Science & Engineering (Jt. ASM-MSCTS) Committee.     

Modeling of anaerobic treatment of wastewater in ponds.

A mathematical model to simulate the performance of anaerobic ponds was developed incorporating both settling of particulate components and the biological anaerobic digestion process. The biological activity includes solubilization of particulate organic matter; methanogenesis and the sulphate reduction process. The model considers that an anaerobic pond comprises a series of equal size columns. Each column has three compartments viz. liquid layer, active sediment layer and inert sediment layer. The existence of organic matter and sulphate removal mechanisms both in the bulk as well as sediment layer of the ponds and the exchange of the soluble components between the layers has been included in the model. The model was transferred to a computer program using VisSim Basic software. The model was verified by comparing simulated results with full-scale as well as with laboratory-scale anaerobic pond performance data. A good agreement between the simulated and the observed pond performance was achieved.     

A comparison of biofilms from macrophytes and rocks for taste and odour producers in the St. Lawrence river.

Given their widespread and prolific annual development in the St. Lawrence River (SLR), macrophytes (i.e. submerged aquatic plants) represent large surface areas for biofilm growth and potentially important sites for associated production of taste and odour (T&O) compounds. We therefore evaluated the importance of submerged macrophytes and their associated biofilms for production of T&O compounds, 2-methylisoborneol (MIB) and geosmin (GM), compared with biofilms from adjacent rocks. We also tested the hypothesis that production of these compounds would differ between macrophyte species, based on the premise that they are not inert substrates but directly influence the communities that colonise their surfaces. Samples collected from transects across the SLR between Kingston and Cornwall, ON were dominated by the flat-bladed Vallisneria spp., and the leafed Myriophyllum spicatum, Elodea canadensis, Chara spp., Potamgeton spp., and Ceratophyllum spp. Overall, MIB and GM levels in biofilms ranged widely between samples. Expressed per g dry weight of biofilm, median levels from macrophyte were 50 (range 1-5000) ng MIB g(-1) and 10 (<1 to 580) ng GM g(-1) compared with 50 (range 5-970) ng MIB g(-1) and 160 (1-1600) ng GM g(-1) from rocks. Based on non-parametric statistical analysis, levels of GM were higher on a g dry weight basis in biofilms from rocks than macrophytes (P = 0.02), but MIB levels were similar (P = 0.94). However, when normalised for differences in substrate surface area (i.e. ng cm(-2)), levels of both MIB and GM were higher in biofilms from rocks than from macrophytes (P < 0.01). There were no discernable differences in MIB and GM concentrations from biofilms of different macrophytes based on either g dry weight sample or surface area (P > 0.05). Overlying water (OLW) concentrations ranged between 2-45 ng L(-1) for MIB and 5-30 ng L(-1) for GM and were not correlated with levels in adjacent biofilms. However, OLW concentrations peaked in shallow, low energy embayments consistent with enhanced production and release of MIB and GM in nearshore areas. The results support our previous work showing the importance of biofilms on various surfaces (rocks, macrophytes and zebra mussels) for MIB and GM production in the SLR, but suggest that inert surfaces like rocks are more productive sites per unit surface area than macrophytes.     

Electromagnetic compatibility of electric rolling stock for rail transportation

A circuit design is proposed and the possibilities for incorporation of an input double-notch low-frequency ripple filter are considered. Recommendations regarding the use of mathematical models for the calculation of transient processes in a DC electric-traction network are given. An analysis of the simulation of processes in a low-frequency filter shows that the emission of interference by the electric rolling stock should be estimated using the wavelet analysis since this approach best suits the studies of nonstationary signals.     

Multistage Zeolite Drying for Energy-Efficient Drying

This work discusses the potential of three multistage zeolite drying systems (counter-, co-, and cross-current) with a varying number of stages. The evaluation showed that for 2-4 stages with heat recovery the efficiency of the systems ranges between 80 and 90%. Additionally, by introducing a compressor, the latent heat in the exhaust air from the regenerator is recovered and used to heat the inlet air for an additional drying stage. As a result, for the counter-current drying system and compressor pressure 1.5-2 bar, a maximum energy efficiency of 120% is achieved, which results in halving the energy consumption compared to conventional drying systems.