Modeling the oxidative coupling of methane using artificial neural network and optimizing of its operational conditions using genetic algorithm

The effect of some operating conditions such as temperature, gas hourly space velocity (GHSV), CH₄/O₂ ratio and diluents gas (mol% N₂) on ethylene production by oxidative coupling of methane (OCM) in a fixed bed reactor at atmospheric pressure was studied over Mn/Na₂WO₄/SiO₂ catalyst. Based on the properties of neural networks, an artificial neural network was used for model developing from experimental data. To prevent network complexity and effective data input to the network, principal component analysis method was used and the number of output parameters was reduced from 4 to 2. A feed-forward back-propagation network was used for simulating the relations between process operating conditions and those aspects of catalytic performance including conversion of methane, C₂ products selectivity, C2 yielding and C₂H₄/C₂H₆ ratio. Levenberg-Marquardt method is presented to train the network. For the first output, an optimum network with 4-9-1 topology and for the second output, an optimum network with 4-6-1 topology was prepared. After simulating the process as well as using ANNs, the operating conditions were optimized and a genetic algorithm based on maximum yield of C₂ was used. The average error in comparing the experimental and simulated values for methane conversion, C₂ products selectivity, yield of C₂ and C₂H₄/C₂H₆ ratio, was estimated as 2.73%, 10.66%, 5.48% and 10.28%, respectively.     

Deterioration Assessment and Rehabilitation Design of Existing Steel Bridge

Diagnostic truck-load tests and microstructural analysis were applied for structural deterioration assessment of a steel truss bridge and its rehabilitation design. The feasibility and potential benefits of using advanced field experimental techniques within a structural-identification framework have been demonstrated. Experimental information, coupled with visual inspection, engineering experience, and intuition, increased the level of confidence in the results of the condition-assessment process, permitting a more rational and cost-effective rehabilitation design. Based on the condition assessment, a two-step rehabilitation is recommended for the bridge: Restoration for a safe service life of 5–7 years, and a subsequent effort for preservation beyond.     

Efficient algorithms for online tracking of set points in robust model predictive control

This paper presents some computationally efficient algorithms for online tracking of set points in robust model predictive control context subject to state and input constraints. The nonlinear systems are represented by a linear model along with an additive nonlinear term which is locally Lipschitz. As an unstructured uncertainty, this term is replaced in the robust stability constraint by its Lipschitz coefficient. A scheduled control technique is employed to transfer the system to desired set points, given online, by designing local robust model predictive controllers. This scheme includes estimating the regions of feasibility and stability of the related equilibriums and online switching among the local controllers. The proposed optimisation problems for calculating the regions of feasibility and stability are defined as linear matrix inequalities that can be solved in polynomial time. The effectiveness of the proposed algorithms is illustrated by an example.     

Dam break flood wave under different reservoir’s capacities and lengths

Dam failure has been the subject of many hydraulic engineering studies due to its complicated physics with many uncertainties involved and the potential to cause many losses of lives and economical losses. A primary source of uncertainties in many dam failure analyses refers to prediction of the reservoir’s outflow hydrograph, which is studied in the present investigation. This paper presents an experimental study on instantaneous dam failure flood under different reservoir’s capacities and lengths in which the side slopes change within a range of 30°–90°. Thus, several outflow hydrographs are calculated and compared. The results reveal the role of the side slopes on dam break flood wave, such that lower side slope creates more catastrophic outflow. The reservoir capacity and length are also recognized to be important factors, such that they do affect peak discharge and time to peak of the outflow hydrograph. Finally, the paper presents two simple relations for peak discharge and maximum water level estimation at any downstream location.     

Measurement and modeling of average void fraction, bubble size and interfacial area

The local void fraction, bubble size and interfacial area concentration for co-current air-water bubbly flow through a horizontal pipe of 50.3 mm internal diameter were investigated experimentally using the double-sensor resistivity probe method. The local and area-averaged void fractions and interfacial area concentrations were analyzed as a function of liquid and gas flow rates. These parameters were found to increase systematically with decreasing liquid flow and increasing gas flow. However, variations with the liquid flow were not as significant as with the gas flow. A consistent variation of the gas phase drift velocity and distribution parameter with the liquid flow rate was observed. It was demonstrated that presentation of the average void fraction in terms of flowing volumetric concentration was more appropriate for horizontal bubbly flow. Several bubble break-up mechanisms were discussed. It was concluded that average pressure fluctuations generated by the turbulent liquid fluctuations acting across a bubble diameter are the only mechanism which causes distortion of a bubble. Based on this force and the competing surface tension force, a theoretical model was developed for mean bubble size and interfacial area concentration. The theoretically predicted mean bubble size and interfacial area concentration were found to agree reasonably well with those measured by the double-sensor resistivity method.     

INFLUENCE OF VIBRATION ON SORET-DRIVEN CONVECTION IN POROUS MEDIA

Two-dimensional thermosolutal natural convection with Soret effect under the simultaneous action of vibrational and gravitational accelerations is investigated. We consider a porous cavity saturated by a binary mixture and adopt the time-averaging formulation. For an infinite horizontal layer, a stability analysis is performed from which the threshold of stability is determined. Numerical simulations, using a pseudo-spectral Chebyshev collocation method, are performed to describe the convective motion. The problem is investigated for different aspect ratios with various directions of vibration. It is concluded that, for both the stationary and the Hopf bifurcation, the vertical vibration has a stabilizing effect while the horizontal vibration has a destabilizing effect on the onset of convection.     

Constructing biocatalytic nanochannel membranes for unidirectional isomer conversion and separation

Isomer conversion and separation are crucial in the chemical, pharmaceutical, and food industries. However, this process remains challenging due to the reversed conversion of isomers and their similar boiling points and kinetic diameters. Herein, an enzyme-catalyzed nanochannel membrane with a hierarchical structure is fabricated for selective and directional isomeric conversion and separation. The enzyme is embedded in a confined polymer network that shows high stability and retains 95% of its initial activity after 50 reaction cycles. Studying the transport mechanisms between isomers through the membrane shows that the hierarchical layers of the membrane impose unequal energy barriers to the forward and backward transport of products, promoting unidirectional diffusion of products and interrupting the equilibrium of the isomerization reaction to increase the conversion rate by 43%. Overall, this work opens a new avenue for the design of biocatalytic nanochannel membranes and the directional production and in situ separation of isomers.     

Chaotic imperialist competitive algorithm for optimum design of truss structures

The imperialist competitive algorithm is a new socio-politically motivated optimization algorithm which recently is applied for structural problems. This paper utilizes the idea of using chaotic systems instead of random processes in the imperialist competitive algorithm. The resulting method is called chaotic imperialist competitive algorithm (CICA) in which chaotic maps are utilized to improve the movement step of the algorithm. Some well-studied truss structures are chosen to evaluate the efficiency of the new algorithm.