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In this paper, we propose modeling for a single repairable system with a hierarchical structure under the assumption that the failures follow a nonhomogeneous Poisson process (which corresponds to minimal repair action) with a power-law intensity function. The properties of the new model are discussed in detail. The parameter estimators are obtained using the maximum likelihood method. A corrective approach is used to remove bias with order O(n −1), and the respective exact confidence intervals are proposed. A simulation study is conducted to show that our estimators are bias-free. The proposed modeling is illustrated via a toy example on a butterfly valve system, an example of an early-stage real project related to the traction system of an in-pipe robot, and also a real example on a blowout preventer system.

In order to reduce the harmful effect on the environment, using the oxygenated fuels such as biofuel blends as fuel has been on the spotlights for the internal combustion engines. For this rationale; the diesel engine operated with blends of sunflower biodiesel and diesel fuel (blending of 0%, 10%, 20%, and 100% biodiesel fuel with conventional diesel fuel). In this study, an experimental and numerical model for Heat release rate (HRR) and the characteristic performance of diesel engine such as cylinder pressure and emission characteristics (NOx, CO, and HC) in internal combustion engines is presented. To ensure the integrity of modeling, the results were compared with the experimental results. This comparison indicated a good agreement between the two. A Gaussian and Fourier series of second order was used to define a function relating the pressure and emission characteristics. Presented numerical model, implemented in proprietary software AVL FIRE, is able to capture chemical phenomena and to predict pollutant emission concentration trends. © 2017 American Institute of Chemical Engineers Environ Prog, 37: 1540–1550, 2018

Sub-grid closures for filtered two-fluid models (fTFM) useful in large scale simulations of riser flows can be derived from highly resolved simulations (HRS) with microscopic two-fluid modeling (mTFM). Accurate sub-grid closures require accurate mTFM formulations as well as accurate correlation of relevant filtered parameters to suitable independent variables. This article deals with both of those issues. The accuracy of mTFM is touched by assessing the impact of gas sub-grid turbulence over HRS filtered predictions. A gas turbulence alike effect is artificially inserted by means of a stochastic forcing procedure implemented in the physical space over the momentum conservation equation of the gas phase. The correlation issue is touched by introducing a three-filtered variable correlation analysis (three-marker analysis) performed under a variety of different macro-scale conditions typical or risers. While the more elaborated correlation procedure clearly improved accuracy, accounting for gas subgrid turbulence had no significant impact over predictions.