Three-dimensional elastodynamic solution for an arbitrary thick FGM rectangular plate resting on a two parameter viscoelastic foundation

A three-dimensional semi-analytic analysis based on the linear elasticity theory is offered to study the transient vibration characteristics of an arbitrarily thick, simply supported, functionally graded (FGM) rectangular plate, resting on a linear Winkler–Pasternak viscoelastic foundation, and subjected to general distributed driving forces of arbitrary temporal and spatial variations. The problem solution is obtained by adopting a laminate model in conjunction with the powerful state space solution technique involving a global transfer matrix and Durbin’s numerical Laplace inversion algorithm. Numerical calculations are carried out for the transient displacement and stress responses of aluminum-zirconia FGM square plates of selected thickness parameters and compositional gradients, resting on “soft” or “stiff” elastic foundations, under the action of moving transverse forces as well as uniformly distributed blast loads. Also, the response curves for the FGM plates are compared with those of equivalent bilaminate plates containing comparable total volume fractions of constituent materials. It is observed that the material gradient variation is substantially more influential on the dynamic stress concentrations induced across the plate thickness than on the displacement response of the inhomogeneous plates. In particular, the displacement response of the equivalent bilaminate plates can provide an accurate estimate for prediction of the dynamic response of the corresponding FGM plates, especially for thick plates resting on a stiff foundation. Limiting cases are considered and good agreements with the data available in the literature as well as with the computations made by using a commercial finite element package are obtained.     

Effect of carbon nanotube network morphology on thin film transistor performance

The properties of electronic devices based on carbon nanotube networks (CNTNs) depend on the carbon nanotube (CNT) deposition method used, which can yield a range of network morphologies. Here, we synthesize single-walled CNTs using an aerosol (floating catalyst) chemical vapor deposition process and deposit CNTs at room temperature onto substrates as random networks with various morphologies. We use four CNT deposition techniques: electrostatic or thermal precipitation, and filtration through a filter followed by press transfer or dissolving the filter. We study the mobility using pulsed measurements to avoid hysteresis, the on/off ratio, and the electrical noise properties of the CNTNs, and correlate them to the network morphology through careful imaging. Among the four deposition methods thermal precipitation is found to be a novel approach to prepare high-performance, partially aligned CNTNs that are dry-deposited directly after their synthesis. Our results provide new insight into the role of the network morphologies and offer paths towards tunable transport properties in CNT thin film transistors.      

Interface-induced negative differential resistance and memristive behavior in Gr/MoSe2 heterostructure

Journal of Materials Science: Materials in Electronics - Heterostructures of materials can possess the prominent characteristics of their individual layers or gain newly emerged interface effects...     

Monitoring Bernoulli processes considering measurement errors and learning effect

This paper presents the effect of measurement errors and learning on monitoring processes with individual Bernoulli observations. A cumulative sum control chart is considered to evaluate the possible impacts of measurement errors and learning. We propose a time‐dependent learning effect model along with measurement errors and incorporate them into the Bernoulli CUSUM control chart statistic. The performance of the Bernoulli CUSUM control chart is then merely assessed by comparing the average number of observations to signal (ANOS) under two proposed conditions with the condition of no possible errors. Thus, the ANOS values are obtained under different proportions of non‐conforming items, once considering errors due to measurement by inspectors, and once considering both errors and learning effect together. The experimental results show that the efficiency of the control chart to detect assignable causes deteriorates in the presence of measurement errors and enhances when learning affects operators' performance. The proposed approach has a potential to be used in monitoring high‐quality Bernoulli processes as well as disease diagnosis, and other health care applications with Bernoulli observations.     

Flow shop scheduling problems with assembly operations: a review and new trends

The past few years have witnessed a resurgence of interest in assembly flow shop scheduling as evidenced by increasing number of published articles in this field. A basic assembly flow shop consists of two types of stages: fabrication or machining stage and assembly stage. Machining and assembly stages are composed of either one or a set of machines that are working in parallel. Final products have hierarchical assembly structure with several components and assembly operation(s). The components need to be processed in the machining stage(s) and then assembled based on hierarchical assembly structure. The goal is to find the sequence of jobs that optimises certain objectives. Assembly flow shop scheduling problem has several interesting derivatives and applications in various manufacturing and service industries. This paper provides a consolidated survey of assembly flow shop models with their solution methodology. Finally, the paper concludes by presenting some problems receiving less attention and proposes several salient research opportunities.     

Covalent Protein Immobilization on 3D-Printed Microfiber Meshes for Guided Cartilage Regeneration

Current biomaterial-based strategies explored to treat articular cartilage defects have failed to provide adequate physico-chemical cues in order to guide functional tissue regeneration. Here, it is hypothesized that atmospheric-pressure plasma (APPJ) treatment and melt electrowriting (MEW) will produce microfiber support structures with covalently-immobilized transforming growth factor beta-1 (TGFβ1) that can stimulate the generation of functional cartilage tissue. The effect of APPJ operational speeds to activate MEW polycaprolactone meshes for immobilization of TGFβ1 is first investigated and chondrogenic differentiation and neo-cartilage production are assessed in vitro. All APPJ speeds test enhanced hydrophilicity of the meshes, with the slow treatment speed having significantly less C C/C H and more COOH than the untreated meshes. APPJ treatment increases TGFβ1 loading efficiency. Additionally, in vitro experiments highlight that APPJ-based TGFβ1 attachment to the scaffolds is more advantageous than direct supplementation within the medium. After 28 days of culture, the group with immobilized TGFβ1 has significantly increased compressive modulus (more than threefold) and higher glycosaminoglycan production (more than fivefold) than when TGFβ1 is supplied through the medium. These results demonstrate that APPJ activation allows reagent-free, covalent immobilization of TGFβ1 on microfiber meshes and, importantly, that the biofunctionalized meshes can stimulate neo-cartilage matrix formation. This opens new perspectives for guided tissue regeneration.     

Hierarchical data replication strategy to improve performance in cloud computing

Cloud computing environment is getting more interesting as a new trend of data management. Data replication has been widely applied to improve data access in distributed systems such as Grid and Cloud. However, due to the finite storage capacity of each site, copies that are useful for future jobs can be wastefully deleted and replaced with less valuable ones. Therefore, it is considerable to have appropriate replication strategy that can dynamically store the replicas while satisfying quality of service (QoS) requirements and storage capacity constraints. In this paper, we present a dynamic replication algorithm, named hierarchical data replication strategy (HDRS). HDRS consists of the replica creation that can adaptively increase replicas based on exponential growth or decay rate, the replica placement according to the access load and labeling technique, and finally the replica replacement based on the value of file in the future. We evaluate different dynamic data replication methods using CloudSim simulation. Experiments demonstrate that HDRS can reduce response time and bandwidth usage compared with other algorithms. It means that the HDRS can determine a popular file and replicates it to the best site. This method avoids useless replications and decreases access latency by balancing the load of sites.     

Optimal Allocation of Water Reuse Using Modified TODIM-GP Approach with Considering the Leopold Matrix Outputs

Allocation of water use is one of the most important challenges of water resources management that needs to evaluate water reuse options, especially in areas with limited water resources, arid climate, increasing water demand due to population growth. In this study, the modified TODIM method (Multi-Criteria Decision-Making in Portuguese with considering the risk preferences of decision makers) that can be used with goal programming (GP) by considering Leopold matrix outputs in order to preform Environmental Impact Assessment (EIA). The present study is aimed at optimally allocate water reuse to multiple stakeholders in Najafabad, Isfahan, Iran. The results showed that the numerical model developed with an integration of optimization and quantitative evaluation can be considered as a useful tool to develop feasible guidelines for adapting the requirements of different stakeholders for optimized allocation of recycled water.

     

Isolation and Identification of Current Biosurfactant-Producing Microbacterium maritypicum ABR5 as a Candidate for Oily Sludge Recovery

Biosurfactants have a wide range of applications in different areas, including petroleum microbiology and environmental biotechnology. In this study, removing and recovering oil from oily sludge using microbactan-producing bacteria have been investigated. The best biosurfactant-producing isolate was obtained from a petroleum reservoir and was identified by 16S rDNA analysis as Microbacterium maritypicum ABR5. Its 16S rDNA sequence was deposited in GenBank, NCBI under the accession number MK100468. Chemical analysis using thin-layer chromatography and Fourier Transform Infrared confirmed that the produced biosurfactant was glycolipoprotein. The strain reduced surface tension from 72 to 34.6 mN m⁻¹. The addition of 5 mg L ZnO nanoparticles to the biosurfactant-producing medium showed no bacterial toxicity effect and raised the emulsification index to 25.7%. Higher concentrations of ZnO nanoparticles, such as 10 and 100 mg L, decreased the bacterial growth rate and biosurfactant production. The mixing of M. maritypicum ABR5 culture medium and oily sludge increased the oil recovery from oily sludge by up to 70% after 5 days of incubation. This is the first report of biosurfactant production by a newly identified strain, M. maritypicum ABR5, isolated from a petroleum reservoir. We proposed that the isolated biosurfactant-producing strain could be considered an economical asset for oil recovery from oily sludge in the petroleum industry and environmental biotechnology.     

Biological removal of phenol from strong wastewaters using a novel MSBR

In this study, the performance of a moving-bed sequencing batch reactor (MSBR) that removes phenol from wastewater is presented. The effects of phenol concentration (50-3325 mg L⁻¹), filling time (0-4 h) and aerating time (4-18 h) on the performance of the MSBR are given in terms of phenol and COD removal efficiencies. Moreover, the effect of the moving media on the overall performance of the reactor is also determined. The reactor can completely remove phenol and COD at inlet concentrations up to 3000 mg phenol L⁻¹ (6780 mg COD L⁻¹), which was the inhibition concentration, and with a 24-h cycle time. The filling time range tested here did not significantly affect phenol or COD removal. The optimum hydraulic retention time (HRT) for the MSBR is 40 h and the critical phenol loading rate is 83.4 g phenol m⁻³ h⁻¹, which gives a phenol removal efficiency of 99%. The reactor can also withstand shock loads from slug feeding. The moving bed contribution to phenol and COD removal efficiencies was up to 28.1 and 34.7%, respectively, at the phenol loading rate of 83.4 g m⁻³ h⁻¹. The findings of this investigation suggest that MSBR can be a robust and promising process for effectively treating wastewaters containing inhibitor or recalcitrant compounds in industrial settings.