Partitioned solution of an unsteady adjoint for strongly coupled fluid-structure interactions and application to parameter identification of a one-dimensional problem

Unsteady fluid-structure interaction (FSI) simulations are generally time-consuming. Gradient-based methods are preferred to minimise the computational cost of parameter identification studies (and more in general optimisation) with a high number of parameters. However, calculating the cost function’s gradient using finite differences becomes prohibitively expensive for a high number of parameters. Therefore, the adjoint equations of the unsteady FSI problem are solved to obtain this gradient at a cost almost independent of the number of parameters. Here, both the forward and the adjoint problems are solved in a partitioned way, which means that the flow equations and the structural equations are solved separately. The application of interest is the identification of the arterial wall’s stiffness by comparing the motion of the arterial wall with a reference, possibly obtained from non-invasive imaging. Due to the strong interaction between the fluid and the structure, quasi-Newton coupling iterations are applied to stabilise the partitioned solution of both the forward and the adjoint problem.     

Statistical analysis of parameter effects on linear velocity of ferrous particles in an AC electric field as a new method for powder transportation

In recent years, AC electric field has been introduced as a new approach for sorting, separation, exact feeding and transportation of particles in manufacturing process. The capability of particle handling demands more studies to recognize parameters influencing linear velocity of particles. In this study, the effects of parameters including frequency, gap between electrodes, electrode width, and signal profile on particle linear velocity in a selected condition were experimentally investigated. Main effects of factors and interactions were considered in this paper and regression equation was derived. A general full factorial method was employed as experimental design.     

Bilevel Parallel Genetic Algorithms for Optimization of Large Steel Structures

This article is concerned with optimization of very large steel structures subjected to the actual constraints of the American Institute of Steel Construction ASD and LRFD specifications on high-performance multiprocessor machines using biologically inspired genetic algorithms. First, parallel fuzzy genetic algorithms (GAs) are presented for optimization of steel structures using a distributed memory Message Passing Interface (MPI) with two different schemes: the processor farming scheme and the migration scheme. Next, two bilevel parallel GAs are presented for large-scale structural optimization through judicious combination of shared memory data parallel processing using the OpenMP Application Programming Interface (API) and distributed memory message passing parallel processing using MPI. Speedup results are presented for parallel algorithms.     

Estimation of sweet cherry antioxidant activity and anthocyanin content during ripening by artificial neural network–assisted image processing technique

This paper presents a new approach for estimating antioxidant activity and anthocyanin content at ripening stages of sweet cherry by combining image processing and artificial neural network (ANN) techniques. The system was consisted of a CCD camera, fluorescent lights, capture card and MATLAB software. Anthocyanin content and antioxidant activity were determined by pH differential and 2, 2‐diphenyl‐1‐picrylhydrazyl methods, respectively. It was found that anthocyanin content was constantly increased during ripening stages, and antioxidant activity decreased during the early stages of development but increased from stage five. Several ANN models were designed and tested. Among these networks, a two hidden layer network with 11‐6‐20‐1 architecture had the highest correlation coefficient (R = 0.965) and the lowest value of mean square error (MSE) (215.4) for modelling anthocyanin content. Similarly, a two hidden layer network with 11‐14‐9‐1 architecture had the highest correlation coefficient (R = 0.914) and the lowest value of MSE (0.070) for modelling antioxidant activity.     

Rheological behavior of starch–poly(vinyl alcohol)–TiO2 nanofluids and their main and interactive effects

In this study, an investigation of the rheological behavior of starch/poly(vinyl alcohol) (PVA)/titanium oxide (TiO₂) nanofluids was performed. It revealed that the rheological behavior of starch suspensions displays a particular change due to the presence of PVA and TiO₂. All examined fluids demonstrated non‐Newtonian behavior and followed the Power law model. The main and interacting effects of starch, PVA, and TiO₂ nanoparticles concentrations were studied using the analysis of variance. The results indicated that the flow behavior index (n), as well as the consistency index (K) of suspensions, is influenced by the PVA and TiO₂ contents. The flow behavior index (n) decreased and consistency index (K) increased by an increase in PVA concentration. A reverse trend is observed by the addition of TiO₂ nanoparticles to starch and PVA blend suspensions. The difference in rheological behaviors was ascribed to the presence of binary and triplet interactions between starch, PVA, and TiO₂ nanoparticles. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 44062.     

Optimization of photooxidative removal of p-nitrophenol in a spinning disc photoreactor using response surface methodology

In this article, response surface methodology (RSM) was used to obtain optimum conditions for removal of p-nitrophenol (PNP) by UV/H₂O₂ process using spinning disk photoreactor (SDP). For this purpose, the effect of five independent variables, the initial concentration of PNP, the initial concentration of H₂O₂, pH, solution volume, and irradiation time on the PNP removal percent, was investigated. Central composite design, one of the response surface techniques used for process optimization. The results showed a good agreement between the RSM predicted and experimental data with “R²” and “Adjusted R²” of 0.9692 and 0.9480, respectively. In addition, “Predicted R²” of 0.8909 is in reasonable agreement with “Adjusted R²” of 0.9488. At optimal conditions, that is, PNP concentration of 20.78?mg L^?1, H₂O₂ concentration of 1355.83?mg L^?1, solution volume of 566.08?mL, irradiation time of 12.30?min, and pH of 4.59 the removal percent predicted by RSM is 100% which has good correspondence with its experimental value (98.67%).     

The influence of interstitial carbon on the γ-surface in austenite

The intrinsic stacking-fault energy (SFE) is a crucial parameter for understanding the plastic deformation behavior of face-centered cubic materials such as austenitic steels. In order to investigate the influence of interstitial carbon on the SFE of iron, we perform ab initio calculations within the framework of density functional theory. By utilizing the linearized augmented planewave method, we compute the SFE for a variety of carbon concentrations, i.e. Fe, Fe₂₄C and Fe₃C, as well as different carbon locations with respect to the stacking-fault plane. Our results demonstrate a strong influence of both parameters on the SFE, in agreement with previous experimental and theoretical reports. Moreover, we compute the generalized SFE (also known as the γ-surface), which provides information about the behavior of the material under shear stress.     

Flow properties and thixotropy of selected hydrocolloids: Experimental and modeling studies

The flow curves and time-dependent rheological behavior of two traditional Iranian hydrocolloids obtained from Salep tubers (wild terrestrial orchids) and Balangu seeds (Lallemantia royleana) have been investigated. All samples exhibited thixotropic behavior at the concentrations used and both in forward and backward measurements were characterized by the power law model. At the constant shear rate, the apparent viscosity decreased rapidly with time of shearing within the first 100 s for Salep and 50 s for Balangu samples, and approached a constant value corresponding to a steady state after approximately 450 and 250 s, respectively. The breakdown rate of all samples accelerated at higher shear rates. Four time-dependent models namely the second order structural kinetic model, Weltman model, first-order stress decay models with zero and non-zero equilibrium stress values were used to describe the thixotropy behavior and different parameters of these models were analyzed. The results showed that the rate of the thixotropic breakdown increased with increasing shear rates for Salep, whereas, the extent of thixotropy increased with shear rate for Salep and decreased for Balangu. In this study, the selected hydrocolloids were adequately modeled by the first-order stress decay model with non-zero equilibrium stress value.