A machine learning‐based operational control framework for reducing energy consumption of an amine‐based gas sweetening process

This study proposes a data‐driven operational control framework using machine learning‐based predictive modeling with the aim of decreasing the energy consumption of a natural gas sweetening process. This multi‐stage framework is composed of the following steps: (a) a clustering algorithm based on Density‐Based Spatial Clustering of Applications with Noise methodology is implemented to characterize the sampling space of all possible states of the operation and to determine the operational modes of the gas sweetening unit, (b) the lowest steam consumption of each operational mode is selected as a reference for operational control of the gas sweetening process, and (c) a number of high‐accuracy regression models are developed using the Gradient Boosting Machines algorithm for predicting the controlled parameters and output variables. This framework presents an operational control strategy that provides actionable insights about the energy performance of the current operations of the unit and also suggests the potential of energy saving for gas treating plant operators. The ultimate goal is to leverage this data‐driven strategy in order to identify the achievable energy conservation opportunity in such plants. The dataset for this research study consists of 29 817 records that were sampled over the course of 3 years from a gas train in the South Pars Gas Complex. Furthermore, our offline analysis demonstrates that there is a potential of 8% energy saving, equivalent to 5 760 000 Nm³ of natural gas consumption reduction, which can be achieved by mapping the steam consumption states of the unit to the best energy performances predicted by the proposed framework.     

CFD study of non-premixed swirling burners: Effect of turbulence models

This research investigates a numerical simulation of swirling turbulent non-premixed combustion. The effects on the combustion characteristics are examined with three turbulence models: namely as the Reynolds stress model, spectral turbulence analysis and Re-Normalization Group. In addition, the P-1 and discrete ordinate (DO) models are used to simulate the radiative heat transfer in this model. The governing equations associated with the required boundary conditions are solved using the numerical model. The accuracy of this model is validated with the published experimental data and the comparison elucidates that there is a reasonable agreement between the obtained values from this model and the corresponding experimental quantities. Among different models proposed in this research, the Reynolds stress model with the Probability Density Function (PDF) approach is more accurate (nearly up to 50%) than other turbulent models for a swirling flow field. Regarding the effect of radiative heat transfer model, it is observed that the discrete ordinate model is more precise than the P-1 model in anticipating the experimental behavior. This model is able to simulate the subcritical nature of the isothermal flow as well as the size and shape of the internal recirculation induced by the swirl due to combustion.     

Vicious cycle during chemical degradation of sulfonated aromatic proton exchange membranes in the fuel cell application

Weak phase separation and vulnerable linking groups between aromatic units are common setbacks of sulfonated aromatic proton exchange membranes (PEMs) from durability point of view. In this study, sulfonated poly(ether ether ketone) (SPEEK) membranes were exposed to Fenton's solution for a specific time, ranging from 10 to 60 minutes. Chemical structure and morphology evolution, decay in mechanical and thermal stability, and H₂ permeability of SPEEK membranes were evaluated during the chemical degradation. Less-entangled polymeric chains with lower average molecular weight of degraded SPEEK samples diminished mechanical rigidity. In addition, reduction of aromatic rings in each repeat unit led to higher thermal decomposition rate. Furthermore, randomly distributed micro-defects in the SPEEK morphology and an increase in water sorption can reduce the fatigue strength of membranes in the wet-dry cycles. Eventually, hydrogen cross-over rate was gradually increased, and henceforth, accelerated destructive radical formation and degradation can be predicted.     

Crude oil price forecasting: a biogeography-based optimization approach

The importance of crude oil in the world economy has made it imperative for efficient models to be designed for predicting future prices. This paper proposes an alternative approach based on a time series and biogeography-based optimization (BMMR–BBO) for the estimation of the West Texas Intermediate (WTI) crude oil price. To evaluate the forecasting ability of the presented model, we compared its performance with those of time series functions. The results of the experiment showed that BMMR-BBO performed better than the other methods and is a fairly good option for crude oil price prediction. The proposed model can be useful in the formulation of policies related to international crude oil price estimations, development plans, and industrial production.     

An experimental study of forced convective heat transfer for fully developed Al 2 O 3 –water nanofluid in an annulus tube

Nanofluids have been known as practical materials to ameliorate heat transfer within diverse industrial systems. The current work presents an empirical study on forced convection effects of Al₂O₃–water nanofluid within an annulus tube. A laminar flow regime has been considered to perform the experiment in high Reynolds number range using several concentrations of nanofluid. Also, the boundary conditions include a constant uniform heat flux applied on the outer shell and an adiabatic condition to the inner tube. Nanofluid particle is visualized with transmission electron microscopy to figure out the nanofluid particles. Additionally, the pressure drop is obtained by measuring the inlet and outlet pressure with respect to the ambient condition. The experimental results showed that adding nanoparticles to the base fluid will increase the heat transfer coefficient (HTC) and average Nusselt number. In addition, by increasing viscosity effects at maximum Reynolds number of 1140 and increasing nanofluid concentration from 1% to 4% (maximum performance at 4%), HTC increases by 18%.     

Transesterification of Canola Oil to Biodiesel Using CaO/Talc Nanopowder as a Mixed Oxide Catalyst

A series of heterogeneous catalysts including different molar ratios of CaO/talc was synthesized to study the transesterification reaction of canola oil and methanol under different reaction conditions. Characterization and kinetic results revealed that the activity of this catalyst was enhanced due to the increase of CaO/talc molar ratio value leading to an improvement in the biodiesel production. Moreover, the effect of various parameters on the activity of the undertaken catalysts was studied in order to determine the optimum process conditions. Leaching measurements and the durability of the CaO/talc catalyst under several reaction cycles were evaluated and proved it to be a stable catalyst.     

Gas holdup in two phase gas–liquid and three phase gas–liquid–solid production and transportation

The gas holdup is an important parameter that is needed for design and development of surface facilities and transportation pipelines in the field of petroleum engineering. There is no general model for prediction of this parameter in different systems and under different conditions. As a result, development of accurate and general models for prediction of this parameter in various situations is of great importance. This study presents new experimental gas holdup data in the kerosene+CO₂ and kerosene+N₂ systems. The experimental data were measured by using a bubble column setup. Moreover, a computer-based model namely PSO-ANFIS model is also developed for prediction of the gas holdup in different systems. A total of 818 experimental gas holdup data in various systems were utilized including the newly measured experimental data in the present work as well as experimental data from several published works in the literature. Results showed that the developed PSO-ANFIS model is accurate for prediction of experimental data with an R² value of 0.998 and average absolute relative deviation (AARD%) of 3.4%.     

Properties of PET/clay nanocomposite films

Polyethylene terephthalate (PET) nanocomposite films were prepared by cast extrusion followed by uniaxial stretching, using chill rolls. Transmission electron microscopy (TEM) and wide angle X‐ray diffraction (WAXD) showed that the clay layers were aligned in the machine direction (MD) in the PET/clay nanocomposite (PCN) films. Differential scanning calorimetry (DSC) showed that PCN films have higher crystallinity than the neat PET films, possibly due to the nucleating role of the silicate layers. The PCN films became hazier as the clay content increased, but the film transparency remained in the acceptable range. Oxygen permeability of the PCN films decreased by 23% compared to the neat PET film. This is comparable with predictions of models proposed in the literature. Silicate incorporation brought about 20% increase in the tensile modulus, while the puncture and tear propagation resistance were reduced, due to brittleness of the PCN films. The measured modulus (1.7 GPa) was somewhat smaller than the values predicted using the Pseudoinclusion model (2.1 GPa). POLYM. ENG. SCI., 2012. © 2011 Society of Plastics Engineers     

A simplified equation of state for polymer melts from perturbed Yukawa hard-sphere chain

This paper addresses the modeling of the pressure?Cvolume?Ctemperature (PVT) properties of 14 polymer melts using simplified Yukawa hard-sphere-chain equation of sate (EOS) plus first-order perturbation theory. Three pure-component parameters appeared in the EOS have been determined via the volumetric data. These parameters reflect the segment number, non-bonded segment?Csegment interaction energy, and segment size. Likewise, this study considered chains that interact through a range-parameter of Yukawa potential with l.8. The reliability of the proposed model has been assessed by comparing the results with 1,315 experimental data points over a broad range of pressures and temperatures for which, their measured values were available in the literature. Our calculations on the specific volume of studied liquid polymers reproduce very accurately the experimental PVT data. The overall average absolute deviation of the calculated specific volumes from literature data was found to be 0.89?%.     

NUMERICAL SIMULATION OF FLOW OVER TWO SIDE-BY-SIDE CIRCULAR CYLINDERS

In the present paper, the unsteady, viscous, incompressible and 2-D flow around two side-by-side circular cylinders was simulated using a Cartesian-staggered grid finite volume based method. A great-source term technique was employed to identify the solid bodies (cylinders) located in the flow field and boundary conditions were enforced by applying the ghost-cell technique. Finally, the characteristics of the flow around two side-by-side cylinders were comprehensively obtained through several computational simulations. The computational simulations were performed for different transverse gap ratios (1.5≤T/D≤4) in laminar (Re=100,200) and turbulent (Re=104) regimes, where T and D are the distance between the centers of cylinders and the diameter of cylinders, respectively. The Reynolds number is based on the diameter of cylinders,D. The pressure field and vorticity distributions along with the associated streamlines and the time histories of hydrodynamic forces were also calculated and analyzed for different gap ratios. Generally, different flow patterns were observed as the gap ratio and Reynolds number varied. Accordingly, the hydrodynamic forces showed irregular variations for small gaps while they took a regular pattern at higher spacing ratios.