A framework for the selection of the right nuclear power plant

Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe

Design, implementation, and testing of advanced virtual coordinate-measuring machines

Copyright @ 2011 IEEE. This article has been made available through the Brunel Open Access Publishing Fund.Advanced virtual coordinate-measuring machines (CMMs) (AVCMMs) have recently been developed at Brunel University, which provide vivid graphical representation and powerful simulation of CMM operations, together with Monte-Carlo-based uncertainty evaluation. In an integrated virtual environment, the user can plan an inspection strategy for a given task, carry out virtual measurements, and evaluate the uncertainty associated with the measurement results, all without the need of using a physical machine. The obtained estimate of uncertainty can serve as a rapid feedback for the user to optimize the inspection plan in the AVCMM before actual measurements or as an evaluation of the measurement results performed. This paper details the methodology, design, and implementation of the AVCMM system, including CMM modeling, probe contact and collision detection, error modeling and simulation, and uncertainty evaluation. This paper further reports experimental results for the testing of the AVCMM

Practical considerations regarding results from static and dynamic load testing of bridges

Bridge tests are a helpful tool for bridge assessment and evaluation. Both in the case of a static and dynamic load testing, each element of the test: the load selection and application, the creation of a numerical model to follow the progress of the test or to check the validity of the test results, the measurement process itself and the comparative analysis of experimental results and calculations could be a source of errors in the bridge final evaluation if these errors and uncertainties are not properly considered. The article presents some of the most important factors that may bring errors in the interpretation of the test results and their comparison to targeted values or values derived from a numerical model. This, at the end, may result in the adoption of decisions that are not accurate and appropriate. The selected sources of feasible errors are presented with the division into static and dynamic loading tests. The presented examples of bridge load testing show how the use of improper test methods could lead to significant errors in bridge assessment and evaluation and, consequently, to wrong decisions.Peer ReviewedPostprint (published version

Experimental and numerical investigations of the optical and thermal aspects of a PCM-glazed unit

This paper reports on the thermal and optical characterisation of PCM (phase change material) RT27 using the T-history method and spectrophotometry principles, respectively, and the experimental and numerical performance evaluation of a PCM-glazed unit. Various relationships describing the variations in the extinction, scattering and absorption coefficients within the phase change region were developed, and were validated in a numerical CFD model. The results show that: (i) during rapid phase changes, the transmittance spectra from the PCM are unstable, while under stable conditions visible transmittance values of 90% and 40% are obtained for the liquid and phases, respectively; (ii) the radiation scattering effects are dominant in the solid phase of the PCM, while radiation absorption dominates in the liquid phase; (iii) the optical/radiation performance of PCM can be successfully modelled using the liquid fraction term as the main variable; (iv) the addition of PCM improves the thermal mass of the unit during phase change, but risks of overheating may be a significant factor after the PCM has melted; (v) although the day-lighting aspects of PCM-glazed units are favourable, the change in appearance as the PCM changes phase may be a limiting factor in PCM-glazed units

Procedure to Approximately Estimate the Uncertainty of Material Ratio Parameters due to Inhomogeneity of Surface Roughness

Roughness parameters that characterize contacting surfaces with regard to friction and wear are commonly stated without uncertainties, or with an uncertainty only taking into account a very limited amount of aspects such as repeatability of reproducibility (homogeneity) of the specimen. This makes it difficult to discriminate between different values of single roughness parameters. Therefore uncertainty assessment methods are required that take all relevant aspects into account. In the literature this is scarcely performed and examples specific for parameters used in friction and wear are not yet given. We propose a procedure to derive the uncertainty from a single profile employing a statistical method that is based on the statistical moments of the amplitude distribution and the autocorrelation length of the profile. To show the possibilities and the limitations of this method we compare the uncertainty derived from a single profile with that derived from a high statistics experiment.Comment: submitted to Meas. Sci. Technol., 12 figure