Critical heat flux prediction by using radial basis function and multilayer perceptron neural networks: A comparison study

Critical heat flux (CHF) is an important parameter for the design of nuclear reactors. Although many experimental and theoretical researches have been performed, there is not a single correlation to predict CHF because it is influenced by many parameters. These parameters are based on fixed inlet, local and fixed outlet conditions. Artificial neural networks (ANNs) have been applied to a wide variety of different areas such as prediction, approximation, modeling and classification. In this study, two types of neural networks, radial basis function (RBF) and multilayer perceptron (MLP), are trained with the experimental CHF data and their performances are compared. RBF predicts CHF with root mean square (RMS) errors of 0.24%, 7.9%, 0.16% and MLP predicts CHF with RMS errors of 1.29%, 8.31% and 2.71%, in fixed inlet conditions, local conditions and fixed outlet conditions, respectively. The results show that neural networks with RBF structure have superior performance in CHF data prediction over MLP neural networks. The parametric trends of CHF obtained by the trained ANNs are also evaluated and results reported.     

Numerical Investigation of Engineering Systems: Analysis of Accuracy Reduction Due to Model Oversimplification

When faced with the mathematical modeling of any engineering system, whether for design, performance assessment, optimization, or control, the engineer has to determine the level of accuracy versus the simplicity of the mathematical formulation. Although it is universally accepted that the more complex the formulation, the more accurate the results will be, these usually come at the expense of larger CPU times, a substantial amount of computer resources, and are generally limited by the capacity of computers and computing power, which most times precludes their use in favor of simpler models. Many times, however, engineers do not realize the potential risk that oversimplification of a problem generates in terms of accuracy of the results; that is, the model solution does not resemble the system behavior. Through a demonstrative example, the present study addresses the issue of oversimplification of the resulting mathematical model and the corresponding accuracy of its solution. After constructing three sets of models of the physical system, each with a different level of detail, the solutions are then compared to experimental data. The results show that the accuracy of the numerical approximation depends directly on the level of complexity of the mathematical model used, and that oversimplification may result in up to a ninefold degradation of the results. In addition, minor changes in the inlet boundary condition and geometry result in significant changes in the flow pattern, up to a fivefold difference between different models in the recirculation bubble relative error. This information is fundamental for engineering professionals to consider during the modeling process in applications.     

Seismic Performance Evaluation of SSMF with Simple Beam–Column Connections Under the Base Level

Simple beam–column connections are simpler and cheaper in construction than rigid beam–column connections, moreover, beams under the base level are only carrying gravity loads because of high rigidity of basement walls; therefore, seismic performance of special steel moment frame with basement wall is investigated in two cases in this paper. First, as the normal case of design, rigid beam–column connections are used under the base level, then all of the beam–column connections under the base level are changed to simple connections. The seismic performance of these two types is evaluated by FEMA P695 method. For predicting the collapse capacity of each archetype, adjusted collapse margin ratios are evaluated based on several nonlinear analyses and compared to acceptance criteria. Finally, seismic performance of these two kinds of structures is compared with each other. Despite the structural system’s change in height, seismic performance factors of special steel moment frames are considered for designing whole of the structures. Finally all two types of structures pass the acceptability checks and all the initial assumption are proved.     

Surface and structure characteristics of commercial K-Feldspar powders: Effects of temperature and leaching media

This study presents morphological and structural variations of K-Feldspar mineral after acid treatment. Both organic and inorganic acids such as C₂H₂O₄, HCl, HNO₃ and H₂SO₄ were employed for this purpose. Another aim of this study was to find an optimum experimental condition for iron (Fe) removal with a minimum damage on the structure of K-Feldspar in which high whiteness index is obtained. The effect of different parameters such as concentration, pH and temperature on the final structure of this mineral was investigated. To find out the chemical composition of powder, XRF was utilized. FTIR, XRD and SEM were employed to study the structure of mineral. Spectrophotometry was chosen to analyze whiteness index of powder after acid treatment. It was found that O—Al—O bond at 647 cm^-1 for H₂SO₄ and HNO₃ treated sample disappeared. However, HCl and C₂H₂O₄ were ineffective at this band. In addition, the results revealed an increase in K-Feldspar content, a decrease in Fe content, an increase in whiteness index and no significant structural change for C₂H₂O₄ leached sample. Whiteness index of 91% was obtained for C₂H₂O₄ leached sample with the pH of 2.5 to 3 at temperature of 50℃ and during 1 h.     

Audio watermarking based on synergy between Lucas regular sequence and Fast Fourier Transform

Multimedia Tools and Applications - The growth of digital technology over the recent years has led to increased sending and saving of electronic media. Taking advantage of digital works without...     

Security anomaly detection in software‐defined networking based on a prediction technique

Nowadays, software‐defined networking (SDN) is regarded as the best solution for the centralized handling and monitoring of large networks. However, it should be noted that SDN architecture suffers from the same security issues, which are the case with common networks. As a case in point, one of the shortcomings of SDNs is related to its high vulnerability to distributed denial of service (DDoS) attacks and other similar ones. Indeed, anomaly detection systems have been considered to deal with these attacks. The challenges are related to designing these systems including gathering data, extracting effective features, and selecting the best model for anomaly detection. In this paper, a novel combined approach is proposed; this method uses NetFlow protocol for gathering information and generating dataset, information gain ratio (IGR), in order to select the effective and relevant features and ensemble learning scheme (Stacking) for developing a structure with desirable performance and efficiency for detecting anomaly in SDN environment. The results obtained from the experiments revealed that the proposed method performs better than other methods in terms of enhancing accuracy (AC) and detection rate (DR) and reducing classification error (CE) and false alarm rate (FAR). The AC, DR, CE, and FAR of the proposed model were measured as 99.92%, 99.83%, 0.08%, and 0.03%, respectively. Furthermore, the proposed method prevents the occurrence of excessive overload on the controller and OpenFlow.     

Smart films based on bacterial cellulose nanofibers modified by conductive polypyrrole and zinc oxide nanoparticles

In this study, we synthesized novel films based on bacterial cellulose (BC), BC modified by polypyrrole (PPy), and a PPy–zinc oxide nanocomposite (BC–PPy–ZnO). The soft polymerization method at room temperature was used to obtain the BC–PPy and BC–PPy–ZnO films. The Combined D‐Optimal design was used to study the effects of the pyrrole monomer concentration, ZnO concentration, and polymerization time on the morphological, physical, color, and electrical conductivity properties of the films. Fourier transform infrared results reflected that some new interactions occurred between BC and PPy and PPy–ZnO. The X‐ray diffraction analysis showed that the crystalline behavior of the BC fiber was hindered because of the complete coating with the amorphous PPy particles. Scanning electron microscopy results show that the ZnO, PPy, and PPy–ZnO nanoparticles were placed between the BC fibers. PPy decreased the water vapor permittivity and total soluble matter percentage. Electrical conductivity studies of the synthesized BC–PPy–ZnO film showed that the film's electrical resistance was changed in different oxidation–reduction or volatile compounds media, so the results suggest that the BC–PPy–ZnO films could be used in antioxidative food active packaging and smart packaging. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46617.     

Visible Light-Induced Degradation of Methylene Blue in the Presence of Photocatalytic ZnS and CdS Nanoparticles

ZnS and CdS nanoparticles were prepared by a simple microwave irradiation method under mild conditions. The obtained nanoparticles were characterized by XRD, TEM and EDX. The results indicated that high purity of nanosized ZnS and CdS was successfully obtained with cubic and hexagonal crystalline structures, respectively. The band gap energies of ZnS and CdS nanoparticles were estimated using UV-visible absorption spectra to be about 4.22 and 2.64 eV, respectively. Photocatalytic degradation of methylene blue was carried out using physical mixtures of ZnS and CdS nanoparticles under a 500-W halogen lamp of visible light irradiation. The residual concentration of methylene blue solution was monitored using UV-visible absorption spectrometry. From the study of the variation in composition of ZnS:CdS, a composition of 1:4 (by weight) was found to be very efficient for degradation of methylene blue. In this case the degradation efficiency of the photocatalyst nanoparticles after 6 h irradiation time was about 73% with a reaction rate of 3.61 × 10⁻³ min⁻¹. Higher degradation efficiency and reaction rate were achieved by increasing the amount of photocatalyst and initial pH of the solution.     

A DXDR large deflection analysis of uniformly loaded square, circular and elliptical orthotropic plates using non-uniform rectangular finite-differences

A finite-difference analysis of the large deflection response of uniformly loaded square, circular and elliptical clamped and simply-supported orthotropic plates is presented. Several types of non-uniform (graded) mesh are investigated and a mesh suited to the curved boundary of the orthotropic circular and elliptical plate is identified. The DXDR method-a variant of the DR (dynamic relaxation) method-is used to solve the finite-difference forms of the governing orthotropic plate equations. The DXDR method and irregular rectilinear mesh are combined along with the Cartesian coordinates to treat all types of boundaries and to analyze the large deformation of non-isotropic circular/elliptical plates. The results obtained from plate analyses demonstrate the potential of the non-uniform meshes employed and it is shown that they are in good agreement with other results for square, circular and elliptical isotropic and orthotropic clamped and simply-supported plates in both fixed and movable cases subjected to transverse pressure loading.     

Multi-objective modelling of day ahead scheduling of MMG-based distribution networks accompanied by DEA considering economics,emissions and power quality

ABSTRACT

This paper presents the state of the art relating to multi-objective modelling for day ahead scheduling of multi micro grid-based distribution networks, using optimal power flow (OPF) accompanied by data envelopment analysis (DEA). In this paper eco-reliability cost function, power quality enhancement and emission reduction are treated as the objective functions and the uncertainties of renewable distributed generations (DGs), load demand and market price are incorporated into the problem. This method is able to find the optimum operation of DGs in grid-connected or isolated MGs, power transaction between each MG and upstream networks/other MGs and hourly reconfiguration instants. For this purpose, firstly OPF is applied to the problem, then the obtained optimal solutions are prioritised by DEA and ranking is done, based on the efficiencies of the optimal solutions. Finally, the provided results validate the practicability of the proposed method and accuracy of the outcomes.