A risk approach to the management of boiler tube thinning

A large set of industrial thickness inspection data covering four boiler units of a power station over a period of five years was made available to the authors. The measurements were made in regions of the boiler where corrosion/erosion was the major cause of failure of the boiler tubes. There were over 40,000 separately measured data points in the data and all were collected with some care and expense.In the development of maintenance strategies for equipment, this type of data is typical of the data that must be collected and assessed. This data thus represents an opportunity to evaluate the ability to generate a useful risk approach to the management of the tubing.An important example of a risk-based approach is the American Petroleum Institute (API) Risk Based Inspection (“RBI”), API 581. A variety of problems were encountered applying this to boiler tubes. The problems include irrelevant API 581 corrosion rate tables, lack of information on how to analyse inspection data, difficulty of dealing with multiple inspection categories and lack of suitable direction for programming inspection intervals.     

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.     

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.     

Pattern Effect Removal Technique for Semiconductor-Optical-Amplifier-Based Wavelength Conversion

A technique to overcome pattern dependence in semiconductor-optical-amplifier-based wavelength converters is presented. The technique is based on a careful selection of red- and blue-shifted spectral components having complementary pattern effects in the output spectrum of a wavelength-converted signal. Significant signal quality improvements are reported at a bit rate of 40 Gb/s.     

High-rate sulphidogenic fluidised-bed treatment of metal-containing wastewater at high temperature.

The applicability of fluidised-bed reactor (FBR) based sulphate reducing bioprocess was investigated for the treatment of iron containing (40-90 mg/L) acidic wastewater at 65 degrees C. The FBR was inoculated with sulphate-reducing bacteria (SRB) originally enriched from a hot mining environment. Ethanol or acetate was supplemented as carbon and electron source for the SRB. A rapid startup with 99.9, 46 and 29% ethanol, sulphate and acetate removals, in respective order, was observed even after 6 days. Iron was almost completely removed with a rate of 90 mg/L.d. The feed pH was decreased gradually from its initial value of 6 to around 3.7 during 100 days of operation. The wastewater pH of 4.3-4.4 was neutralised by the alkalinity produced in acetate oxidation and the average effluent pH was 7.8 +/- 0.8. Although ethanol removal was complete, acetate accumulated. Later the FBR was fed with acetate only. Although acetate was present in the reactor for 295 days, its oxidation rates did not improve, which may be due to low growth rate and poor attachment ability of acetate oxidising SRB. Hence, the oxidation of acetate is the rate limiting step in the sulphidogenic ethanol oxidation by the thermophilic SRB.