Rolling of thin strip and foil: Application of a tribological model for "mixed" lubrication

A mechanical model of cold rolling of foil is coupled with a sophisticated tribological model. The tribological model treats the "mixed" lubrication regime of practical interest, in which there is "real" contact between the roll and strip as well as pressurized oil between the surfaces. The variation of oil film thickness and contact ratio in the bite is found by considering flattening of asperities on the foil and the build-up of hydrodynamic pressure through the bite. The boundary friction coefficient for the contact areas is taken from strip drawing tests under similar tribological conditions. Theoretical results confirm that roll load and forward slip decrease with increasing rolling speed due to the decrease in contact ratio and friction. The predictions of the model are verified using mill trials under industrial conditions. For both thin strip and foil, the load predicted by the model has reasonable agreement with the measurements. For rolling of foil, forward slip is overestimated. This is greatly improved if a variation of friction through the bite is considered.

Analysis of the piston ring/liner oil film development during warm-up for an SI-engine

A one-dimensional ring-pack lubrication model developed at MIT is applied to simulate the oil film behavior during the warm-up period of a Kohler spark ignition engine [1]. This is done by making assumptions for the evolution of the oil temperatures during warm-up and that the oil control ring during downstrokes is fully flooded. The ring-pack lubrication model includes features such as three different lubrication regimes, i.e. pure hydrodynamic lubrication, boundary lubrication and pure asperity contact, non-steady wetting of both inlet and outlet of the piston ring, capability to use all ring face profiles that can be approximated by piece-wise polynomials and, finally, the ability to model the rheology of multi-grade oils. Not surprisingly, the simulations show that by far the most important parameter is the temperature dependence of the oil viscosity. This dependence is subsequently examined further by choosing different oils. The baseline oil is SAE 10W30 and results are compared to those using the SAE 30 and the SAE 10W50 oils.

Comparison of stabilised/solidified mixes of model drill cuttings based on the North Sea and Red Sea Areas

Following the global stringent legislations regulating the wastes generated from the drilling process of oil exploration and production activities, the management of hazardous drill cuttings has become one of the pressing needs confronting the petroleum industry. Most of the prevalent treatment techniques adopted by oil companies are extremely expensive and/or the treated product has to be landfilled without any potential end-use; thereby rendering these solutions unsustainable. The technique of stabilisation/solidification is being investigated in this research to treat drill cuttings prior to landfilling or for potential re-use in construction products. Two case studies were explored namely North Sea and Red Sea. Given the known difficulties with stabilising/solidifying oils and chlorides, this research made use of model drill cutting mixes based on typical drill cutting from the two case studies, which contained 4.2% and 10.95% average concentrations of hydrocarbons; and 2.03% and 2.13% of chlorides, by weight respectively. A number of different binders, including a range of conventional viz. Portland cement (PC) as well as less-conventional viz. zeolite, or waste binders viz. cement kiln dust (CKD), fly ash and compost were tested to assess their ability to treat the North Sea and Red Sea model drill cuttings. The dry binder content by weight was 10%, 20% and 30%. In addition, raw drill cuttings from one of the North Sea offshore rigs were stabilised/solidified using 30% PC. The characteristics of the final stabilised/solidified product were finally compared to those of thermally treated cuttings. The effectiveness of the treatment using the different binder systems was compared in the light of the aforementioned two contaminants only. A set of physical tests (unconfined compressive strength (UCS)), chemical tests (NRA leachability) and micro-structural examinations (using scanning electron microscopy (SEM), and X-ray diffraction (XRD)) were used to evaluate the relative performance of the different binder mixes in treating the drill cuttings. The results showed that the observed UCS covered a wide range of values indicating various feasible end-use scenarios for the treated cuttings within the construction industry. The teachability results showed the reduction of the model drill cuttings to a stable non-reactive hazardous waste, compliant with the UK acceptance criteria for non-hazardous landfills: (a) by most of the 30% and 20% binders for chloride concentrations, and (b) by the 20% and 30% of compost-PC and CKD-PC binders for the Red Sea cuttings. The 20% and 30% compost-PC and CKD-PC binders successfully reduced the leached oil concentration of the North Sea cuttings to inert levels. Copyright 2007, Society of Petroleum Engineers.

Surface excavation with model predictive control

This paper describes the application of variable-horizon model predictive control to trajectory generation in surface excavation. A nonlinear dynamic model of a surface mining machine digging in oil sand is developed as a test platform. This model is then stabilised with an inner-loop controller before being linearised to generate a prediction model. The linear model is used to design a predictive controller for trajectory generation. A variable horizon formulation is augmented with extra terms in the cost function to allow more control over digging, whilst still preserving the guarantee of finite-time completion. Simulations show the generation of realistic trajectories, motivating new applications of variable horizon MPC for autonomy that go beyond the realm of vehicle path planning. ©2010 IEEE.

Simulations of thermal upgrading methods for oil shale reservoirs

This paper analyzes reaction and thermal front development in porous reservoirs with reacting flows, such as those encountered in shale oil extraction. A set of dimensionless parameters and a 3D code are developed in order to investigate the important physical and chemical variables of such reservoirs when heated by in situ methods. This contribution builds on a 1D model developed for the precursor study to this work. Theory necessary for this study is presented, namely shale decomposition chemical mechanisms, governing equations for multiphase flow in porous media and necessary closure models. Plotting the ratio of the thermal wave speed to the fluid speed allows one to infer that the reaction wave front ends where this ratio is at a minimum. The reaction front follows the thermal front closely, thus allowing assumptions to be made about the extent of decomposition solely by looking at thermal wave progression. Furthermore, this sensitivity analysis showed that a certain minimum permeability is required in order to ensure the formation of a traveling thermal wave. It was found that by studying the non-dimensional governing parameters of the system one can ascribe characteristic values for these parameters for given initial and boundary conditions. This allows one to roughly predict the performance of a particular method on a particular reservoir given approximate values for initial and boundary conditions. Channelling and flow blockage due to carbon residue buildup impeded each method's performance. Blockage was found to be a result of imbalanced heating. Copyright 2012, Society of Petroleum Engineers.

Predictive entropy search for efficient global optimization of black-box functions

We propose a novel information-theoretic approach for Bayesian optimization called Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that maximizes the expected information gained with respect to the global maximum. PES codifies this intractable acquisition function in terms of the expected reduction in the differential entropy of the predictive distribution. This reformulation allows PES to obtain approximations that are both more accurate and efficient than other alternatives such as Entropy Search (ES). Furthermore, PES can easily perform a fully Bayesian treatment of the model hyperparameters while ES cannot. We evaluate PES in both synthetic and real-world applications, including optimization problems in machine learning, finance, biotechnology, and robotics. We show that the increased accuracy of PES leads to significant gains in optimization performance.