Enhancement of thermal conductivity with carbon nanotube for nanofluids

Thermal conductivity enhancements in ethylene glycol and synthetic engine oil in the presence of multi-walled carbon nanotubes (MWNTs) are investigated. CNT nanofluids are prepared using a two-step method. The volume concentration of CNT–ethylene glycol suspensions is below 1.0 vol.% and that of CNT–synthetic engine oil suspensions is below 2.0 vol.%. The thermal conductivities of the CNT suspensions are measured with a modified transient hot wire method. The results show that CNT–ethylene glycol suspensions have noticeably higher thermal conductivities than the ethylene glycol base fluid without CNT. The results for CNT–synthetic engine oil suspensions also exhibit the same trend. For CNT–ethylene glycol suspensions at a volume fraction of 0.01 (1 vol.%), thermal conductivity is enhanced by 12.4%. On the other hand, for CNT–synthetic engine oil suspension, thermal conductivity is enhanced by 30% at a volume fraction of 0.02 (2 vol.%). The rates of increase are, however, different for different base fluids. The CNT–synthetic engine oil suspension has a much higher enhanced thermal conductivity ratio than the CNT–ethylene glycol suspension.     

Investigation of a miniature centrifugal fan

A centrifugal fan was designed with a matching centrifugal volute flow channel in order to investigate a numerical simulation with prototype manufacturing, and to compare with experimental results. The fan configuration was developed according to a fan-design theorem. A model P-60 turbojet engine compressor blade design was adopted for the fan aerodynamic analysis and design. The results were verified using the STAR-CD code. Also, based on the findings, a miniature centrifugal fan was designed and manufactured using a CNC five axes machine. The P–Q performance curves were tested using an AMCA standard 210-85 test chamber apparatus. From the numerical analysis results, the pressure on the suction and pressure surfaces will increase gradually from the inlet to one-half the distance of the hub’s camber line, however, it will increase more rapidly afterwards. In addition, stress-concentration phenomenon occurred at the tip of the suction and pressure surfaces. In other words, the tip was more prone to damage when the fan was operated. Experiments show that the designed fan maximum flow rate Q and static pressure P were 32% and 59%, respectively, which were lower than the commercial fan data at 2000 rpm rotational speed. However, when the rotational speed was increased to 4000 rpm, the maximum flow rate Q and static pressure P were increased to 38% and 82%. This study concluded that a centrifugal fan’s static pressure at high rotational speed is higher than that of an axial-flow fan. Therefore, a centrifugal fan should be chosen if high static pressure cooling or blowing is required. This advanced research investigation is to build up the capabilities of design, analysis, manufacturing, and measurement of a centrifugal fan with an outer diameter smaller than 10 cm.     

Forming consensus in the networks of knowledge

Information granules, such as e.g., fuzzy sets, capture essential knowledge about data and the key dependencies between them. Quite commonly, we may envision that information granules (fuzzy sets) have become a result of fuzzy clustering and therefore could be succinctly represented in the form of some fuzzy partition matrices. Interestingly, the same data set could be represented from various standpoints and this multifaceted view yields a collection of different partition matrices being reflective of the higher-order granular knowledge about the data. The levels of specificity of the clusters the data are organized into could be quite different—the larger the number of clusters, the more detailed insight into the structure of data becomes available. Given the granularity of the resulting constructs (rather than plain data themselves), one could view a collection of partition matrices as a certain type of a network of knowledge. Considering a variety of sources of knowledge encountered across the network, we are interested in forming consensus between them. In a nutshell, this leads to the construction of certain fuzzy partition matrices which “reconcile” the knowledge captured by the individual partition matrices. Given that the granularity of the sources of knowledge under consideration could vary quite substantially, we develop a unified optimization perspective by introducing fuzzy proximity matrices that are induced by the corresponding partition matrices. In the sequel, the optimization is realized on a basis of these proximity matrices. We offer a detailed algorithm and illustrate its performance using a series of numeric experiments.     

Modeling and simulation of drug delivery from a new type of biodegradable polymer micro-device

In this paper, modeling and simulation of a new type of controlled drug delivery micro-device based on biodegradable polymers is reported. The micro-device consists of micro-chambers arrays for drug storage to achieve linear release. The micro-chambers are fabricated with polyanhydrides (CPP-SA) using the UV-LIGA technology and the controlled release process are the combined results of the design of the micro-chambers and the biodegradable characteristics of the polymer. This type of drug delivery system has some unique advantages in controlled long-term drug delivery, such as larger loading volume than the matrices release systems, easier control for the release rate, etc. It is necessary to optimize the structure for the long-term and zero-order drug release. Based on the Monte Carlo erosion model, the drug release model is founded for the drug delivery system and using the new model, the drug release profiles from the delivery systems with different structures are simulated. The simulated results indicate that the effect of the drug delivery is dependent on the micro-structure of the delivery system and the simulated drug profiles of coaxial rings micro-cavity shape equal to zero-order released model approximatively. The simulated results are very important to the application research of the new biodegradable polymer micro-device.     

Formation of γ-LiAlO2 nano-network in an Al-based metal matrix composite

We report the synthesis of a nanostructured γ-LiAlO₂ network in an Al-based metal matrix composite (MMC) by arc-melting a powder compact of Al–15 wt.%Li₂O. During synthesis, chemical reactions between Al and Li₂O occurred, and a two-phase Al-γ-LiAlO₂ MMC was produced. The γ-LiAlO₂ was in the form of nano-network extended evenly in the Al matrix. The apparent density and Vickers' hardness number of the MMC were determined to be 2.31 gcm^− 3 and 143, respectively, and having a relative density of 0.87. The MMC was made nano-porous by etching away Al with a 2 M NaOH solution. The sizes of pores were about 150 nm and the width of the branches in the γ-LiAlO₂ network was about 90 nm. Atomic force microscopy revealed that the branches were composed of fine grains of 50 nm in diameter. Microstructure of the network was not altered even after prolonged etching, and this suggested that γ-LiAlO₂ was chemically inert to NaOH corrosion. Specific surface area of the γ-LiAlO₂ nano-network was measured to be 79 m²/g, and its porosity was determined to be 43.7%.     

The Reverse Monte Carlo localization algorithm

Global localization is a very fundamental and challenging problem in Robotic Soccer. Here, the main aim is to find the best method which is very robust and fast and requires less computational resources and memory compared to similar approaches and is precise enough for robot soccer games and technical challenges. In this work, the Reverse Monte Carlo localization (R-MCL) method is introduced. The algorithm is designed for fast, precise and robust global localization of autonomous robots in the robotic soccer domain, to overcome the uncertainties in the sensors, environment and the motion model. R-MCL is a hybrid method based on Markov localization (ML) and Monte Carlo localization (MCL), where the ML based module finds the region where the robot should be and the MCL based part predicts the geometrical location with high precision by selecting samples in this region. It is called Reverse since the MCL routine is applied in a reverse manner in this algorithm. In this work, this method is tested on a challenging data set that is used by many other researchers and compared in terms of error rate against different levels of noise, and sparsity. Additionally, the time required to recover from kidnapping and the processing time of the methods are tested and compared. According to the test results R-MCL is a considerable method against high sparsity and noise. It is preferable when its recovery from kidnapping and processing times are considered. It gives robust and fast but relatively coarse position estimations against imprecise and inadequate perceptions, and coarse action data, including regular misplacements, and false perceptions.     

A three-dimensional non-epitaxial atomistic growth model for thin-film deposition: effect of surface mobility

The effect of the atomic mobility on a film surface has been studied by using a three-dimensional atomistic thin-film deposition model which simulates three-dimensional thin-film images, surface profiles and cross-sectional area pictures. In addition, quantitative results of surface RMS roughness, average film thickness, atomic coordination number and its distribution, and solid fraction of the deposited thin films, were obtained from the simulations. When the film surface mobility increased from 0.3 to 3.0, RMS roughness decreased from 6.5 to 1.1, solid fraction increased from 0.27 to 0.56 and average film thickness decreased from 40 to 28, due to the reduction of the voids within the film. The full-width half magnitude of the atomic coordination distribution became narrower indicating the increased degree of crystallization. With increase in surface mobility crossing the boundary to 1.5, the film evolved from a porous or loose columnar structure with voids, to a densely packed fibrous grain structure which can be categorized by the zone structure models.     

Small volume PCR in PDMS biochips with integrated fluid control and vapour barrier

In this paper we demonstrate a new method for microfabricating PDMS devices that controls vapour diffusion, thereby reducing water loss at elevated temperatures and greatly increasing the reliability of the PCR. In the past, the vapour and liquid diffusion properties of the PDMS material in microfluidic devices have impaired performance. We show that this water loss is primarily due to vapour diffusion from the PDMS biochip and by implanting a polyethylene vapour barrier layer in the PDMS, the overall fluid loss was almost eliminated (reduced by a factor of 3). We have also developed a procedure to ensure irreversible bonding between the PDMS and the implant. With this improved microfabrication method we demonstrate the feasibility and advantages of performing small volume PCR genetic amplification (i.e. with less than 2 μl of PCR sample) within a PDMS–glass hybrid biochip. Diaphragm pumps and pinch-off valves were integrated in the system and these enabled fluid retention during the amplification stage and will facilitate higher levels of on-chip automation.     

The influence of ply sequence and thermoelastic stress field on asymmetric delamination crack growth behavior of embedded elliptical delaminations in laminated FRP composites

The influence of ply lay up and the interaction of residual thermal stresses and mechanical loading on the interlaminar asymmetric embedded delamination crack growth behavior have been investigated. Two sets of full three-dimensional thermo-elastic finite element analyses have been performed for the interlaminar elliptical delaminations, which may be due to manufacturing defects or other reasons and are located symmetrically with respect to the midplane in a quasi-isotropic FRP composite laminate lay up. Depending upon the through-the-thickness location of the embedded elliptical delaminations, four different laminate configurations have been considered. Strain energy release rate (SERR) procedures have been employed to assess the delamination crack growth characteristics at the interfaces. It is found that the individual fracture modes exhibit asymmetric and non self-similar crack growth behavior along the delamination front depending upon the location of the interfacial delaminations; ply sequence and orientation and thermo-elastic anisotropy of the laminae.