approach was able to identify the pre-mixed and diffusive combustion phases, for different engine loads. Results were compared with a simple inversion procedure, showing a good agreement. The combustion ignition delay was also calculated, showing its variation with the engine load. Keywords Rate of heat release • Inverse problems • Bayesian technique List of symbols A Area A/F Air/fuel ratio B Piston bore CA Crankshaft angle f Linear or non-linear function of the state variables g Linear or non-linear function representing the observation model h Heat transfer coefficient LHV Lower heating value m Mass n Engine speed in Hz n Vector of noise associated with the observation model P Pressure Q Heat t Time T Temperature v Average gas velocity within the cylinder v Vector of noise associated with the evolution model V Volume w Weights of particles W Covariance matrix x Mass fraction of burned fuel y Vector of state variables z Vector of observation variables Abstract The rate of heat released during the combustion in Diesel engines is important for many reasons, including performance evaluation, pollutant formation, and control. Combustion in Diesel engines can be generally divided into three phases: pre-mixed, diffusive or mixed-controlled, and late combustion. The objective of this paper is to estimate the rate of heat released by the fuel in a marine Diesel engine, in order to identify the pre-mixed and diffusive phases, using the Sampling Importance Resampling (SIR) Bayesian Particle Filter. Experimental pressure data obtained from a piezoelectric sensor, installed in a research marine diesel engine (MAN Innovator 4c), was used to feed the observation model in such Bayesian approach. The evolution model for the pressure was formulated in terms of a set of ordinary differential equations, coming from the First Law of Thermodynamics, together with a random walk model for the unknown state variable. The proposed

A distinct characteristic of reservoir fluids in different Brazilian pre-salt fields is the high Gas-Oil- Ratio (GOR) and high content of CO2 in the associated gas. In particular, the presence of CO2 in significant amounts is known to have a strong influence on the thermophysical properties and phase equilibria of the oil mixtures. Due to the strategy of re-injection of CO2-rich streams for EOR purposes, these aspects can be even more pronounced in the production fluids in future scenarios. In the present work, a parametric study is performed to investigate the influence of both CO2 molar content and GOR, in a controlled manner, on the simulations of a pre-salt field configuration for various operating conditions. PVT look-up tables were used with a commercial multiphase flow simulator. First, the thermodynamic modelling of a 20% molar CO2 pre-salt oil was performed, along with well characterized CO2-live oil mixtures taken from the literature, in order to generate PVT look-up tables. They were used to successfully reproduce field data and assess the validity of multiphase flow simulation results from a commercial software. For the CO2-rich live oil mixtures from the literature, a parametric study was performed in which the CO2 molar content ranged from 20% to 50% with 300-600 Sm3/Sm3 of GOR. Simulation results of temperature, total pressure drop, gas volume fraction and gas- liquid density ratio are presented and compared.

Material properties such as thermal conductivity, magnetic permeability, electric permittivity, modulus of elasticity, Poisson's ratio, thermal expansion coefficient, etc. can vary spatially throughout a given solid object as it is the case in functionally graded materials. Finding this spatial variation is an inverse problem that requires boundary values of the field quantity such as temperature, magnetic field potential or electric field potential and its derivatives normal to the boundaries. In this paper, we solve the direct problem of predicting the spatial distribution of the field variable based on its measured boundary values and on the assumed spatial distribution of the diffusion coefficient using radial basis functions, the finite volume method and the finite element method, whose accuracies are verified against analytical solutions. Minimization of the sum of normalized least-squares differences between the calculated and measured values of the field quantity at the boundaries then leads to the correct parameters in the analytic model for the spatial distribution of the spatially varying material property.

There are several challenges associated to the pre-salt development at the Santos basin, such as long distances from the coast, low temperature reservoirs, high pressures, high water depth, among others. Additional aspects contributing to the complex production scenario are related to fluid characteristics and flow assurance. In particular, the high CO 2 content in the dissolved gas is an important characteristic that should be also analyzed, because CO 2 is not only a heavy component, when compared to lighter components present in the gas phase, but has also a high Joule-Thomson coefficient. This affects pressure drop and specially the mixture cooling behavior during decompression. The cooling effect is expected to be strong at high production rates. Thus, the objective of the present work is to evaluate these effects under present and future production scenarios, taking into account increasing CO 2 contents due to re-injection strategies.Two different field configurations were investigated and a variety of operating conditions was used, along with real and model fluids ranging from 5% to 50% CO 2 content (molar basis). PVT data for the model fluids with high CO 2 content were generated by a simulated swelling test with CO 2 of an existing mixture with lower CO 2 content. A parametric study was carried out aiming at investigating primarily the total pressure and temperature drop in the pipeline when the total CO 2 content of the mixture is increased. Furthermore, variation of the fluid properties along the well, flowline and riser was evaluated. Results are also discussed in view of the impact of increasing CO 2 contents and the challenges experienced during simulation of such flows.