Numerical investigation for the suitable choice of bubble diameter correlation for EMMS/bubbling drag model

Mesoscale bubbles exist inherently in bubbling fluidized beds and hence should be considered in the constitutive modeling of the drag force. The energy minimization multiscale bubbling (EMMS/bubbling) drag model takes the effects of mesoscale structures (i.e., bubbles) into the modeling of drag coefficient and thus improves the coarse-grid simulation of bubbling and turbulent fluidized beds. However, its dependence on the bubble diameter correlation has not been thoroughly investigated. The hydrodynamic disparity between homogeneous and heterogeneous fluidization is accounted for by the heterogeneity index,H_d, which can be affected by choice of bubble diameter correlation. How this choice of bubble diameter correlation influences the model prediction calls for further fundamental research. This article incorporated seven different bubble diameter correlations into EMMS/bubbling drag model and studied their effects onH_d. The performance of these correlations has been compared with the correlation used previously by EMMS/bubbling drag model. We found that some of the correlations predicted lower H_d by order of a magnitude than the correlation used by the original EMMS/bubbling drag. Based on such analysis, we proposed a modification in the EMMS drag model for bubbling and turbulent fluidized beds. A computational fluid dynamics (CFD) simulation using two-fluid model with the modified EMMS/bubbling drag model was performed for two bubbling and one turbulent fluidized beds. Voidage distribution, time averaged solid concentration and axial solid concentration profiles were studied and compared with the previous version of the EMMS/bubbling drag model and experimental data. We found that the right choice of bubble diameter correlations can significantly improve the results for CFD simulations.     

A novel minimum weight formulation of topology optimization implemented with reanalysis approach

In this paper, we develop an efficient diagonal quadratic optimization formulation for minimum weight design problem subject to multiple constraints. A high-efficiency computational approach of topology optimization is implemented within the framework of approximate reanalysis. The key point of the formulation is the introduction of the reciprocal-type variables. The topology optimization seeking for minimum weight can be transformed as a sequence of quadratic program with separable and strictly positive definite Hessian matrix, thus can be solved by a sequential quadratic programming approach. A modified sensitivity filtering scheme is suggested to remove undesirable checkerboard patterns and mesh dependence. Several typical examples are provided to validate the presented approach. It is observed that the optimized structure can achieve lighter weight than those from the established method by the demonstrative numerical test. Considerable computational savings can be achieved without loss of accuracy of the final design for 3D structure. Moreover, the effects of multiple constraints and upper bound of the allowable compliance upon the optimized designs are investigated by numerical examples.     

On Structural,Optical, and Electrical Properties of Chromium Oxide Cr2O3 Thin Film for Applications

Protection of Metals and Physical Chemistry of Surfaces - Chromium oxide thin films were grown on Al2O3 substrates by ablating a pure Cr2O3 target using a KrF excimer laser. The energy density on...     

Topology optimization of transient problem with maximum dynamic response constraint using SOAR scheme

Frontiers of Mechanical Engineering - This paper proposes a novel method for the continuum topology optimization of transient vibration problem with maximum dynamic response constraint. An...     

Ultrahigh molecular weight polyethylene with improved crosslink density,oxidation stability,and microbial inhibition by chemical crosslinking and tea polyphenols for total joint replacements

Highly crosslinked ultrahigh molecular weight polyethylene (UHMWPE) stabilized by vitamin E (VE) is widely applied in artificial joints as the bearings. Despite the approval, there is a discord that VE lowers the crosslinking efficiency, limiting its use at high concentration. In this work, we aim to obtain highly crosslinked and oxidation resistant UHMWPE through the conjunction of tea polyphenol and chemical crosslinking. We hypothesized that highly incorporated tea polyphenol with multiple reactive sites can ameliorate crosslinking efficiency of chemical crosslinked UHMWPE in comparison to VE. Epigallocatechin gallate (EGCG) as representative tea polyphenol was incorporated into UHMWPE at high concentration (2–8 wt%), followed by chemical crosslinking with 2 wt% organic peroxide. Unlike VE/UHMWPE blends as the control, chemical crosslinking achieved an increasing trend in crosslink density of EGCG/UHMWPE blends with increasing antioxidant concentration. High concentration of EGCG also enhanced the oxidation stability of UHMWPE. Intriguingly, EGCG endowed UHMWPE with an excellent antimicrobial property, which was inefficient in VE/UHMWPE. Cell viability was hardly affected by the high loaded antioxidant and peroxide. The chemically crosslinked UHMWPE blended with EGCG is proved to be a reasonable, cost effective and realistic alternative for use in artificial joints.     

Soil–conduit interaction: an artificial intelligence application for reinforced concrete and corrugated steel conduits

Neural Computing and Applications - Marston’s load theory is commonly used for understanding the soil–conduit interaction. However, there are no practical methods available which can...     

A study of spin rectification effect enhancement of microwave field by a PIFA

The progress of spin rectification effect, which has the potential in powering the nanoscopic devices wirelessly, has been impeded by its low conversion efficiency. To solve this problem, a 5.8 GHz planar inverted F‐shaped antenna, which is designed to harvest radiated microwave power as well as foster a field enhanced area surrounding a permalloy (Py, Ni₈₀Fe₂₀) monolayer, is presented. The electric and magnetic field are enhanced by ~17.5‐fold and ~ 45‐fold, respectively. With the proposed antenna, a photovoltage of 0.85 μV can be detected in the monolayer 1.5 m away from the transmitting antenna, with input power of 30 dBm. This work provides an effective method to enhance the spin rectification effect signal in the far field region and paves the way for spintronic devices to be potentially utilized in practical wireless applications, such as quantum information, photovoltaics, and nanogenerator.     

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. A distributed architecture based on an intrusion detection system (IDS) ensures that a dynamic, scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is available. In this study, we examined the time-related aspects of network traffic data. We presented an intrusion detection model based on a two-layered bidirectional long short-term memory (Bi-LSTM) with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark dataset. We showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy, precision, recall and F1 score.     

Distinguish Fritillaria cirrhosa and nonFritillaria cirrhosa using laser-induced breakdown spectroscopy

As traditional Chinese medicines, Fritillaria from different origins are very similar and it is difficult to distinguish them. In this study, the laser-induced breakdown spectroscopy combined with learning vector quantization(LIBS-LVQ) was proposed to distinguish the powdered samples of Fritillaria cirrhosa and non-Fritillaria cirrhosa. We also studied the performance of linear discriminant analysis, and support vector machine on the same data set. Among these three classifiers, LVQ had the highest correct classification rate of 99.17%. The experimental results demonstrated that the LIBS-LVQ model could be used to differentiate the powdered samples of Fritillaria cirrhosa and non-Fritillaria cirrhosa.     

Experimental study on repeatedly loaded foundation soil strengthened by wraparound geosynthetic reinforcement technique

In the recent past,the potential benefits of wraparound geosynthetic reinforcement technique for constructing the reinforced soil foundations have been reported.This paper presents the experimental study on the behaviour of model strip footing resting on sandy soil bed reinforced with geosynthetic in wraparound and planar forms under monotonic and repeated loadings.The geosynthetic layers were laid according to the reinforcement ratio to minimise the scale effect.It is found that for the same amount of reinforcement material,the wraparound reinforced model resulted in less settlement in comparison to planar reinforced models.The efficiency of wraparound reinforced model increased with the increase in load amplitude and the rate of total cumulative settlement substantially decreased with the increase in number of load cycles.The wraparound reinforced model has shown about 45% lower average total settlement in comparison to unreinforced model,while the double-layer reinforced model has about 41%lower average total settlement at the cost of approximately twice the material and 1.5 times the occupied land width ratio.Moreover,wraparound models have shown much greater stability in comparison to their counterpart models when subjected to incremental repeated loading.