Effect of copper nanoparticles on thermal behavior of two-phase argon-copper nanofluid flow in rough nanochannels with focusing on the interface properties and heat transfer using molecular dynamics simulation

A comparison between the efficacy of surface boundary structure and presence of nanoparticles on the condensation two-phase flow inside rough nanochannels has been accomplished by applying molecular dynamics procedure to evaluate the thermal conductivity and flow characteristics. Simulation is performed in a computational region with two copper walls containing rectangular rough elements under different saturated temperatures. The main properties of liquid-vapor interface including density and the number of liquid atoms, are obtained. It is observed that the density profile is more affected by nanoparticles than the roughness. Also, compared to the condensation of nanofluid in a smooth nanochannel, the rough wall causes a greater drop in the temperature at the early time steps and by development of liquid films, effects of the wall roughness reduce. At the first of the condensation process, adding nanoparticle causes that transferring argon particles to the liquid phase increases with a steeper slope. Furthermore, heat current autocorrelation function (HCACF) for nanofluid condensation flow over considered correlation time is analyzed and following that the thermal conductivity for different saturated conditions is calculated. It has been represented that at lower temperatures the roughness makes more significant influence on the heat transfer of two-phase flow, while at higher temperatures the importance of nanoparticles prevails.     

New polyamides based on 2,5‐bis[(4‐carboxyanilino) carbonyl] pyridine and aromatic diamines: Synthesis and characterization

Seven new polyamides 6a–g were synthesized through the direct polycondensation reaction of 2,5‐bis[(4‐carboxyanilino) carbonyl] pyridine 4 with seven derivatives of aromatic diamines 5a–g in a medium consisting of N‐methyl‐2‐pyrrolidone, triphenyl phosphite, calcium chloride, and pyridine. The polycondensation reaction produced a series of novel polyamides containing pyridyl moiety in the main chain in high yield with inherent viscosities between 0.32 – 0.72 dL/g. The resulted polymers were fully characterized by means of FTIR spectroscopy, elemental analyses, inherent viscosity, and solubility tests. Thermal properties of these polymers were investigated by using thermal gravimetric analysis and differential thermal gravimetric. All the polymers were soluble at room temperature in polar solvents, such as N,N‐dimethyl acetamide, N,N‐dimethyl formamide, dimethyl sulfoxide, and N‐methyl‐2‐pyrrolidone. 2,5‐Bis[(4‐carboxyanilino) carbonyl] pyridine 4 as a new monomer containing pyridyl moiety was synthesized by using a two‐step reaction. At first 2,5‐pyridine dicarboxylic acid 1 was converted to 2,5‐pyridine dicarbonyl dichloride 2 . Then diacid 4 was prepared by condensation reaction of diacid chloride 2 with p‐aminobenzoic acid 3. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

New photosensitive poly(amid‐imide)s containing chalcone moiety and hydantoin derivatives in the main chain: Synthesis and characterization

Six new poly(amid‐imide)s containing chalchone and hydantoin moieties in the main chain were synthesized through the polycondensation reaction of 1,3‐bis[4,4′‐bis(trimellityimido)phenyl]‐2‐propenone 6 with six hydantoin derivatives 7a‐f in a medium consisting of triphenyl phosphite, calcium chloride, pyridine, and N‐methyl‐2‐pyrrolidone. The polycondensation reaction produced a series of novel poly(amid‐imide)s 8a‐f in high yields with inherent viscosities between 0.26 and 0.42 dL/g. The resulting polymers were characterized by elemental analysis, viscosity measurements, solubility test, thermo gravimetric analysis (TGA and DTG), FTIR, and UV‐Vis spectroscopy. 1,3‐bis[4,4′‐bis(trimellityimido)phenyl]‐2‐propenone 6 was prepared from a three‐step reaction by using 4‐nitro benzaldehyde 1 and 4‐nitro acetophenone 2 as precursors. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Long-term external pitting and corrosion of buried cast iron water pipes

Improved understanding of the development with time of pitting and corrosion of the external surfaces of buried cast iron water pipes is crucial for the management of water supply distribution networks. The present study reports observations of surface topography of cast iron pipes exposed between 34 and 129 years in clay soils. Pit depths, surface areas and widths associated with deeper pits are reported, including as functions of exposure period. Pitting appears to progress in a step-wise manner as also earlier reported for the corrosion of steels. While there is a relation between pit depth and lateral size of pits through the amalgamation of pits to form plateaus into which new pits tend to form, the predominant progression of material loss through corrosion and pitting is into the metal rather than laterally. The practical implications of these observations are discussed.     

硅含量对TIG焊Al-Si/SiCp复合层包覆A380铝合金显微组织的影响

采用钨极惰性气体（TIG）在铸态A380铝合金表面制备复合涂层。将Al,Si和SiC粉末混合物与硅酸钠溶液混合后涂覆在基材上,采用TIG焊进行表面熔化,在基体表面制备Al-SiC涂层。采用XRD、SEM和EDS研究显微组织的变化,采用显微硬度和滑动磨损试验研究包覆层的性能。结果表明,SiC粒子均匀分布在树枝状的铝基体中。加入过量的硅造成包覆层共晶和粗大硅粒子的形成,从而导致包覆层具有较高的硬度和耐磨性。     

Mechanical and biological performance of rainbow trout collagen-boron nitride nanocomposite scaffolds for soft tissue engineering

We aim to investigate the potential of collagen extracted from rainbow trout for tissue engineering applications. In this regard, nanocomposite scaffolds based on the extracted collagen reinforced with various concentrations of boron nitride (BN) nanoparticles (0, 3, 6, 9, and 12 wt%) were developed. In addition, the role of various concentrations of BN nanoparticles and two-step cross-linking process on the physical and chemical properties of nanocomposite scaffolds were investigated. Our results demonstrated the isolation of Type I collagen with excellent thermal stability but with some structural and chemical differences compared to other sources. The synergic role of BN nanoparticles and two-step cross-linking process resulted in a noticeable improvement in the mechanical properties of collagen-BN scaffolds. Noticeably, incorporation of 6 wt% BN along with a two-step cross-linking process significantly increased the compressive strength (9.5 times) and elastic modulus (four times) of the collagen scaffold. Besides, nanocomposite scaffolds significantly improved proliferation and spreading of MG-63 cell line, confirming their biocompatibility. The results suggested that the incorporation of BN nanoparticles along with a two-step cross-linking process not only could promote the mechanical and thermal performances of collagen scaffolds, but also enhanced high cell viability, and proliferation supporting their potential in tissue engineering applications.     

Dynamic Fractional Frequency Reuse (DFFR) with AMC and Random Access in WiMAX System

In this paper; dynamical resource allocation scheme is proposed to improve throughput and fairness in the modern broadband wireless systems such as IEEE 802.16 Worldwide Interoperability for Microwave Access. To assign the subcarriers to users, dynamic fractional frequency reuse is used. In dynamic fractional frequency reuse, each cell is partitioned into two regions, one called super region and another called regular region. Regular region is divided into 3 parts which correspond to the three sectors. In this method, a utility function is firstly used for the subcarrier allocation to the geographical regions and then opportunistic scheduling is applied for the assignment subcarriers to users in each cell. In order to increase the throughput of the system, adaptive modulation and coding techniques are used. Using dynamic fractional frequency reuse reduces fairness among users of a cell. Therefore a random access sub-band is applied to improve the fairness of the system.     

Prediction of boundary shear stress in circular and trapezoidal channels with entropy concept

Relying on the power law to develop new relationships, the present study developed the Shannon entropy concept to predict shear stress distribution. The presented method was evaluated and compared with valid laboratory results and the shear stress distribution surveyed through this concept in circular, circular with flat bed and trapezoidal channels. By increasing the flow depth in circular channels, the model presented herein gives an improved prediction of shear stress distribution, while in circular channels with flat bed it is better in predicting shear stress both at lower flow depth and subcritical flow conditions. In comparison, in trapezoidal channels the model is much better in predicting the shear stress distribution at lower flow depths. Accordingly, with a mean error percentage of 1.99% in circular channels, 3.69% in circular channels with flat bed and 4.1% in trapezoidal channels, this novel model shows good ability in predicting shear stress distribution.     

Shear stress distribution prediction in symmetric compound channels using data mining and machine learning models

Shear stress distribution prediction in open channels is of utmost importance in hydraulic structural engineering as it directly affects the design of stable channels. In this study, at first, a series of experimental tests were conducted to assess the shear stress distribution in prismatic compound channels. The shear stress values around the whole wetted perimeter were measured in the compound channel with different floodplain widths also in different flow depths in subcritical and supercritical conditions. A set of, data mining and machine learning algorithms including Random Forest (RF), M5P, Random Committee, KStar and Additive Regression implemented on attained data to predict the shear stress distribution in the compound channel. Results indicated among these five models; RF method indicated the most precise results with the highest R² value of 0.9. Finally, the most powerful data mining method which studied in this research compared with two well-known analytical models of Shiono and Knight method (SKM) and Shannon method to acquire the proposed model functioning in predicting the shear stress distribution. The results showed that the RF model has the best prediction performance compared to SKM and Shannon models.     

Real-time removal of impulse noise from MR images for radiosurgery applications

In the recent years, image processing techniques are used as a tool to improve detection and diagnostic capabilities in the medical applications. Among these techniques, medical image enhancement algorithms play an essential role in the removal of the noise, which can be produced by medical instruments and during image transfer. Impulse noise is a major type of noise, which is produced by medical imaging systems, such as MRI, computed tomography (CT), and angiography instruments. An embeddable hardware module, which can denoise medical images before and during surgical operations, could be very helpful. In this paper, an accurate algorithm is proposed for real-time removal of impulse noise in medical images. Our algorithm categorizes all image blocks into three types of edge, smooth, and disordered areas. A different reconstruction method is applied to each category of blocks for noise removal. The proposed method is tested on MR images. Simulation results show acceptable denoising accuracy for various levels of noise. Also, an field programmable gate array (FPGA) implementation of our denoising algorithm shows acceptable hardware resource utilization. Hence, the algorithm is suitable for embedding in medical hardware instruments such as radiosurgery devices.