Obtaining data to validate a model of an induction skull melting furnace

A casting route is often the most cost-effective means of producing engineering components. However, certain materials, particularly those based on Ti, TiAl and Zr alloy systems, are very reactive in the molten condition and must be melted in special furnaces. Induction Skull Melting (ISM) is the most widely-used process for melting these alloys prior to casting components such as turbine blades, engine valves, turbocharger rotors and medical prostheses. A major research project is underway with the specific target of developing robust techniques for casting TiAl components. The aims include increasing the superheat in the molten metal to allow thin section components to be cast, improving the quality of the cast components and increasing the energy efficiency of the process. As part of this, the University of Greenwich (UK) is developing a computer model of the ISM process in close collaboration with the University of Birmingham (UK) where extensive melting trials are being undertaken. This paper describes the experimental measurements to obtain data to feed into and to validate the model. These include measurements of the true RMS current applied to the induction coil, the heat transfer from the molten metal to the crucible cooling water, and the shape of the column of semi-levitated molten metal. Data are presented for Al, Ni and TiAl.

A systematic methodology to assess the impact of human factors in ship design

Evaluating ship layout for human factors (HF) issues using simulation software such as maritimeEXODUS can be a long and complex process. The analysis requires the identification of relevant evaluation scenarios; encompassing evacuation and normal operations; the development of appropriate measures which can be used to gauge the performance of crew and vessel and finally; the interpretation of considerable simulation data. Currently, the only agreed guidelines for evaluating HFs performance of ship design relate to evacuation and so conclusions drawn concerning the overall suitability of a ship design by one naval architect can be quite different from those of another. The complexity of the task grows as the size and complexity of the vessel increases and as the number and type of evaluation scenarios considered increases. Equally, it can be extremely difficult for fleet operators to set HFs design objectives for new vessel concepts. The challenge for naval architects is to develop a procedure that allows both accurate and rapid assessment of HFs issues associated with vessel layout and crew operating procedures. In this paper we present a systematic and transparent methodology for assessing the HF performance of ship design which is both discriminating and diagnostic. The methodology is demonstrated using two variants of a hypothetical naval ship.

Data collection in support of the modelling of naval vessels

Evacuation analysis of passenger and commercial shipping can be undertaken using computer-based simulation tools such as maritimeEXODUS. These tools emulate human shipboard behaviour during emergency scenarios; however it is largely based around the behaviour of civilian passengers and fixtures and fittings of merchant vessels. If these tools and procedures are to be applied to naval vessels there is a clear requirement to understand the behaviour of well-trained naval personnel interacting with the fixtures and fittings that are exclusive to warships. Human factor trials using Royal Navy training facilities were recently undertaken to collect data to improve our understanding of the performance of naval personnel in warship environments. The trials were designed and conducted by staff from the Fire Safety Engineering Group (FSEG) of the University of Greenwich on behalf of the Sea Technology Group (STG), Defence Procurement Agency. The trials involved a selection of RN volunteers with sea-going experience in warships, operating and traversing structural components under different angles of heel. This paper describes the trials and some of the collected data.

Numerical optimisation techniques applied to evacuation analysis

A common problem faced by fire safety engineers in the field of evacuation analysis concerns the optimal design of an arbitrarily complex structure in order to minimise evacuation times. How does the engineer determine the best solution? In this study we introduce the concept of numerical optimisation techniques to address this problem. The study makes user of the buildingEXODUS evacuation model coupled with classical optimisation theory including Design of Experiments (DoE) and Response Surface Models (RSM). We demonstrate the technique using a relatively simple problem of determining the optimal location for a single exit in a square room.

Elemental analysis of soil samples for forensic purposes by inductively coupled plasma spectrometry - precision considerations

Major and trace elemental composition provides a powerful basis for forensic comparison of soils, sediments and rocks. However, it is important that the potential 'errors' associated with the procedures are fully understood and quantified, and that standard protocols are applied for sample preparation and analysis. This paper describes such a standard procedure and reports results both for instrumental measurement precision (repeatability) and overall 'method' precision (reproducibility). Results obtained both for certified reference materials and example soils show that the instrumental measurement precision (defined by the coefficient of variation, CV) for most elements is better than 2-3%. When different solutions were prepared from the same sample powder, and from different sub-sample powders prepared from the same parent sample, the CV increased to c. 5-6% for many elements. The largest variation was found in results for certified reference materials generated from 23 instrument runs over an 18 month period (mean CV=c. 11%). Some elements were more variable than others. W was found to be the most variable and the elements V, Cr, Co, Cu, Ni and Pb also showed higher than average variability. SiO2, CaO, Al2O3 and Fe2O3, Rb, Sr, La, Ce, Nd and Sm generally showed lower than average variability, and therefore provided the most reliable basis for inter-sample comparison. It is recommended that, whenever possible, samples relating to the same investigation should be analysed in the same sample run, or at least sequential runs.