Improvement in the prediction of gasoline pool fire behaviour: CFD modelling and validation

The development and implementation of mathematical models through Computational Fluid Dynamics (CFD) techniques has been acknowledged as a promising tool for the prediction of hydrocarbon pool fires behaviours. In this sense, different approaches, with different assumptions and simplifications, and accounting for different phenomena, have been developed in the literature. However, the deviations in the predictions of the experimentally determined parameters, such as temperatures profiles, flame heights and radiative heat flux, by the implemented models are still high. Therefore, the implementation of these models to predict combustion phenomena and flame behaviours for various scenarios is limited. In this work, the software C3D is used to model gasoline pool fires of different diameters, and under different wind conditions, in order to improve the quality of the predictions of the flame behaviour. The modelled cases correspond to the experimental studies reported in literature. The results from the implemented model show an improved predictive quality when compared with other modelling works reported on literature for the same experimental cases. The deviations in the time averaged temperature, flame height, surface emissive power and radiative heat flux, has been calculated to be 5.0%, 0.05%, 6.32% and 3.82%, respectively.     

IMPROVED ENERGY AND MATERIAL EFFICIENCY USING NEW TOOLS FOR GLOBAL OPTIMISATION OF RESIDUE MATERIAL FLOWS

Residue materials generated in the metallurgical industry have gained an increasing importance, both from the points of view of energy and material supply. A joint process integration model for the integrated steel plant system is developed and used in this paper. It takes into account both residue materials and energy recirculation for the system. The potential for increased recirculation and the effect on the system from an environmental point of view is presented, and implementations and practical experiences are discussed. The model developed can serve as a benchmark for different steelmaking operations and constitute a basis for the continuous work involved in material, energy, environment or economic analyses for the steel production system.     

Modelling radionuclide distribution and transport in the environment

Mathematical models of radionuclide distribution and transport in the environment have been developed to assess the impact on people of routine and accidental releases of radioactivity from a variety of nuclear activities, including: weapons development, production, and testing; power production; and waste disposal. The models are used to estimate human exposures and doses in situations where measurements have not been made or would be impossible or impractical to make. Model results are used to assess whether nuclear facilities are operated in compliance with regulatory requirements, to determine the need for remediation of contaminated sites, to estimate the effects on human health of past releases, and to predict the potential effects of accidental releases or new facilities. This paper describes the various applications and types of models currently used to represent the distribution and transport of radionuclides in the terrestrial and aquatic environments, as well as integrated global models for selected radionuclides and special issues in the fields of solid radioactive waste disposal and dose reconstruction. Particular emphasis is placed on the issue of improving confidence in the model results, including the importance of uncertainty analysis and of model verification and validation.     

Predicting streamflow response to fire-induced landcover change: implications of parameter uncertainty in the MIKE SHE model

Fire is a primary agent of landcover transformation in California semi-arid shrubland watersheds, however few studies have examined the impacts of fire and post-fire succession on streamflow dynamics in these basins. While it may seem intuitive that larger fires will have a greater impact on streamflow response than smaller fires in these watersheds, the nature of these relationships has not been determined. The effects of fire size on seasonal and annual streamflow responses were investigated for a medium-sized basin in central California using a modified version of the MIKE SHE model which had been previously calibrated and tested for this watershed using the Generalized Likelihood Uncertainty Estimation methodology. Model simulations were made for two contrasting periods, wet and dry, in order to assess whether fire size effects varied with weather regime. Results indicated that seasonal and annual streamflow response increased nearly linearly with fire size in a given year under both regimes. Annual flow response was generally higher in wetter years for both weather regimes, however a clear trend was confounded by the effect of stand age. These results expand our understanding of the effects of fire size on hydrologic response in chaparral watersheds, but it is important to note that the majority of model predictions were largely indistinguishable from the predictive uncertainty associated with the calibrated model - a key finding that highlights the importance of analyzing hydrologic predictions for altered landcover conditions in the context of model uncertainty. Future work is needed to examine how alternative decisions (e.g., different likelihood measures) may influence GLUE-based MIKE SHE streamflow predictions following different size fires, and how the effect of fire size on streamflow varies with other factors such as fire location.     

From large-scale to micromachining: A review of force prediction models

In this paper, a review of work performed in the area of force modelling in metal cutting processes is presented. Past and present trends are described and criticised to compare their relevance with current requirements. Several approaches are reviewed, such as empirical, mechanistic and analytical models. The models’ ability to predict forces, from rough machining to finish machining, is analysed.     

Solute transport in crystalline rocks at Äspö — II: Blind predictions, inverse modelling and lessons learnt from test STT1

Based on the results from detailed structural and petrological characterisation and on up-scaled laboratory values for sorption and diffusion, blind predictions were made for the STT1 dipole tracer test performed in the Swedish Äspö Hard Rock Laboratory. The tracers used were nonsorbing, such as uranine and tritiated water, weakly sorbing ²²Na⁺, ⁸⁵Sr²⁺, ⁴⁷Ca²⁺and more strongly sorbing ⁸⁶Rb⁺, ¹³³Ba²⁺, ¹³⁷Cs⁺.Our model consists of two parts: (1) a flow part based on a 2D-streamtube formalism accounting for the natural background flow field and with an underlying homogeneous and isotropic transmissivity field and (2) a transport part in terms of the dual porosity medium approach which is linked to the flow part by the flow porosity.The calibration of the model was done using the data from one single uranine breakthrough (PDT3). The study clearly showed that matrix diffusion into a highly porous material, fault gouge, had to be included in our model evidenced by the characteristic shape of the breakthrough curve and in line with geological observations.After the disclosure of the measurements, it turned out that, in spite of the simplicity of our model, the prediction for the nonsorbing and weakly sorbing tracers was fairly good. The blind prediction for the more strongly sorbing tracers was in general less accurate. The reason for the good predictions is deemed to be the result of the choice of a model structure strongly based on geological observation. The breakthrough curves were inversely modelled to determine in situ values for the transport parameters and to draw consequences on the model structure applied. For good fits, only one additional fracture family in contact with cataclasite had to be taken into account, but no new transport mechanisms had to be invoked. The in situ values for the effective diffusion coefficient for fault gouge are a factor of 2–15 larger than the laboratory data. For cataclasite, both data sets have values comparable to laboratory data. The extracted K_d values for the weakly sorbing tracers are larger than Swedish laboratory data by a factor of 25–60, but agree within a factor of 3–5 for the more strongly sorbing nuclides. The reason for the inconsistency concerning K_ds is the use of fresh granite in the laboratory studies, whereas tracers in the field experiments interact only with fracture fault gouge and to a lesser extent with cataclasite both being mineralogically very different (e.g. clay-bearing) from the intact wall rock.     

Density-dependent kinetics models for a simple description of complex phenomena in macroscopic mass-balance modeling of bioreactors

From experiments originally proposed by Ardity et al. [Arditi, R., Perrin, N., Saïah, H., 1991. Functional responses and heterogeneities: an experimental test with cladocerans. Oikos 60, 69–75] in the field of fundamental ecology, this paper derives conditions under which mass balance ratio-dependent kinetics models are more appropriate (in a sense to be specified in the sequel) than substrate-dependent kinetics models to macroscopically describe bioprocesses with attached biomass. From literature results, it is also suggested that the use of Contois growth functions should be preferred to substrate-dependent kinetics when macroscopically modeling an immobilized-biomass bioreactor. The “robustness” of this result, rather based on a qualitative reasoning, is investigated in simulation and a number of fundamental properties of ratio-dependent models are highlighted. Furthermore, it is shown that ratio-dependent models are well suited to describe macroscopically bioreactors where the diffusion phenomenon is obviously one of the most important limiting factor.     

Modelling multiple dispersion of radionuclides through the environment

The migration of a contaminant through the environment is the result of the transport by a variety of biotic and abiotic carriers which move according to different dispersion mechanisms. Consequently, the patterns of the distribution of a pollutant in the environment cannot be ever explained on the basis of a single migration process or assuming that the concentrations of contaminant in the different kinds of carriers quickly reach the equilibrium condition. The present work discusses two examples (wash-off from catchments and transport through soils of radionuclides) that clearly demonstrate the inadequacy of “single dispersion” models to predict these patterns. On the contrary, models based on multiple dispersion can successfully simulate the particular features of the above mentioned processes. It was demonstrated that the time behaviour of radionuclide migration rates from catchment of different rivers vary within small ranges as a consequence of multiple dispersion. This result can be useful for the development of generic predictive models.     

Autocorrelation offsets zero-inflation in models of tropical saplings density

Modelling the local density of tropical saplings can provide insights into the ecological processes that drive species regeneration and thereby help predict population recovery after disturbance. Yet, few studies have addressed the challenging issues in autocorrelation and zero-inflation of local density. This paper presents Hierarchical Bayesian Modelling (HBM) of sapling density that includes these two features. Special attention is devoted to variable selection, model estimation and comparison.