Modelling the temperature, maturity and moisture content in a drying concrete block

In this paper we continue work from a previous Study Group in developing a model for the maturation of concrete. The model requires equations describing the temperature, moisture content and maturity (or amount of cement that has reacted with the water). Non-dimensionalisation is used to simplify the model and provide simple analytical solutions which are valid for early time maturation. A numerical scheme is also developed and simulations carried out for maturation over one day and then two months. For the longer simulation we also investigate the effect of building the block in a single pour or two stages

Piped water cooling of concrete dams

Piped water is used to remove hydration heat from concrete dams during construction. By examining simple models we obtain an estimate for the temperature rise along the pipe network and within the concrete. To leading order, for practically useful networks, the temperature distribution is quasi-steady, so that exact analytic solutions are obtained. The temperature in the water increases linearly with distance along the pipe and varies logarithmically with radial distance from the pipe in the concrete. Using these results we obtained estimates for the optimal spacing of pipes and pipe length. Some preliminary work on optimal network design has been done. This is work in progress

Pebble bed: reflector treatment and pressure\ud velocity coupling

In this report, we describe some models and numerical methods used to simulate the flow and temperature in a pebble bed modular nuclear reactor. The reactor core is filled with around 450000 spheres containing low enriched uranium and helium is forced through these hot pebbles to cool the system down. The group first investigated the flow model in the pebbles. Numerical aspects were then considered to tackle difficulties encountered with the flow simulation and the temperature inside the pebbles. Numerical schemes are presented that can significantly improve the accuracy of the computed results

Constructive Relationships Between Algebraic Thickness and Normality

We study the relationship between two measures of Boolean functions; \emph{algebraic thickness} and \emph{normality}. For a function $f$, the algebraic thickness is a variant of the \emph{sparsity}, the number of nonzero coefficients in the unique GF(2) polynomial representing $f$, and the normality is the largest dimension of an affine subspace on which $f$ is constant. We show that for $0 < \epsilon<2$, any function with algebraic thickness $n^{3-\epsilon}$ is constant on some affine subspace of dimension $\Omega\left(n^{\frac{\epsilon}{2}}\right)$. Furthermore, we give an algorithm for finding such a subspace. We show that this is at most a factor of $\Theta(\sqrt{n})$ from the best guaranteed, and when restricted to the technique used, is at most a factor of $\Theta(\sqrt{\log n})$ from the best guaranteed. We also show that a concrete function, majority, has algebraic thickness $\Omega\left(2^{n^{1/6}}\right)$.Comment: Final version published in FCT'201

An automatic multi-stepping approach to aircraft ice prediction

Flying an aircraft in icing conditions may seriously degrade its aerodynamical performance and threaten the flight safety. Over the years, new technologies and improved procedures have limited the potential risks caused by aircraft icing. Experimental studies being very expensive, numerous computer codes have been developed to simulate ice shapes and tackle the problem. Typically in these codes, a flow solution and key icing parameters are evaluated around a clean un-iced geometry and their values remain constant during the entire simulation. This approach may be acceptable for short exposure times or when the ice shape only slightly deforms the initial geometry. However, in other cases, the values of the icing parameters may vary and the simulation will loose its accuracy: for large shapes, the presence of the ice influences the surrounding airflow significantly, altering the value of icing parameters and ultimately the ice accretion. Calculating more accurate ice shapes therefore requires to periodically recompute the flow field around the body during the simulation and determine updated values for icing parameters. This procedure, known as multi-stepping, is investigated in this thesis and adapted to the new threedimensional icing code ICECREMO2. Several multi-step algorithms are presented and tested on cylinders and airfoils. When possible, the ice shapes simulated are compared with experimental results. The first multi-step calculations were generally performed manually. The user had to perform a rather tedious work and inappropriate instructions could lead to severe inaccuracies in the simulations. To avoid these difficulties, a fully automated procedure will be developed including all stages of a multi-step computation. This significantly reduces user interaction and the overall computing time. The present research work forms part of the ICECREMO2 project. ICECREMO2 is a three-dimensional ice accretion and water flow code developed collaboratively by Airbus UK, BAe Systems, Dunlop Aerospace, Rolls-Royce, GKN Westland Helicopters, QinetiQ and Cranfield University under the auspices of the UK Department of Trade and Industry. iEThOS - Electronic Theses Online ServiceGBUnited Kingdo

Numerical benchmark campaign of cost action tu1404 – microstructural modelling

This paper presents the results of the numerical benchmark campaign on modelling of hydration and microstructure development of cementitious materials. This numerical benchmark was performed in the scope of COST Action TU1404 “Towards the next generation of standards for service life of cement-based materials and structures”. Seven modelling groups took part in the campaign applying different models for prediction of mechanical properties (elastic moduli or compressive strength) in cement pastes and mortars. The simulations were based on published experimental data. The experimental data (both input and results used for validation) were open to the participants. The purpose of the benchmark campaign was to identify the needs of different models in terms of input experimental data, verify predictive potential of the models and finally to provide reference cases for new models in the future. The results of the benchmark show that a relatively high scatter in the predictions can arise between different models, in particular at early ages (e.g. elastic Young’s modulus predicted at 1 d in the range 6-20 GPa), while it reduces at later age, providing relatively good agreement with experimental data. Even though the input data was based on a single experimental dataset, the large differences between the results of the different models were found to be caused by distinct assumed properties for the individual phases at the microstructural level, mainly because of the scatter in the nanoindentation-derived properties of the C-S-H phase.</jats:p