A review of investigations on the effect of drag-reducing agents in curved pipe flows is presented in this work. Proposed mechanisms of drag reduction, as well as factors that influence their effectiveness also received attention. In addition, this review outlined proposed friction factor and fluid flux models for flow of drag-reducing agents in curved pipes. It was shown in this report that significant drag reduction in curved pipes can be achieved using drag-reducing agents. Drag reduction by additives in curved pipes are generally lower than the corresponding drag reduction in straight pipes. It decreases with increase in curvature ratio and is more pronounced in the transition and turbulent flow regimes. Drag reduction depends strongly on the concentration of polymers and surfactants as well as the bubble fraction of micro-bubbles. It is also reported that drag reduction in curved pipes depends on other factors such as temperature and presence of dissolved salts. Maximum drag reduction asymptote differed between straight and curved pipes and between polymer and surfactant. Due to the limited studies in the area of drag reduction for gas-liquid flow in curved pipes no definite conclusion could be drawn on the effect of drag-reducing agents on such flows. A number of questions remain such as the mechanism of drag reduction in curved pipes and how drag-reducing agents interact with secondary flows. Hence, some research gaps have been identified with recommendations for areas of future researches.

The demand for electricity is increasing all over the world. In Bangladesh, there are many rural areas where the grid connection has not reached yet. In this paper, a performance evaluation was done with a solar-wind hybrid renewable energy system with diesel backup for a school located in a remote area, Baje Fulchari village in Gaibandha district, Bangladesh. For the proposed site, the load demand was considered 10.468 kWh/day for a normal working day (taken from a field survey) having peak demand of 3.3 kW. HOMER software was used for the simulation. The solar radiation and wind speed data were collected from NASA Surface meteorology and Solar Energy database. The NPC for the most economical system configuration is found USD 6,191 with a COE of 0.125 $/ kWh. Compared to the conventional power plants the proposed system can reduce the COE and GHG emission of about 29.85% and 69% respectively. The system evaluated in this work might be implemented in a school or any other location of similar load profile anywhere in the world having the same geographical and meteorological conditions.

A new beam switch antenna based on a composite right/left-handed (CRLH) Butler matrix is presented and experimentally validated. The CRLH transmission line (TL) is proposed to increase the number of beams. The proposed CRLH TL has more than 100◦ phase differences using variable bias voltages. Different combinations of phase shifts are achieved by applying different bias voltages between 0 and 8V. The CRLH TL is added to the conventional Butler matrix to increase the progressive phase difference between adjacent ports, and consequently, the beam pattern. A 5◦ beam resolution within a spatial range of 100◦ is achieved. The measurement results are in good agreement with the simulations.

This research reports on an image processing technique used to merge Magnetic Resonance Imaging (MRI) or Magnetic Resonance Angiography (MRA) with their intensity-curvature functional (ICF). Given a two-dimensional MR image, six 2D model polynomial functions were fitted to the image, and six ICF images were calculated. The MR image and its ICF were direct Fourier transformed. The phase of MR image was estimated pixel-by-pixel as arctangent of ratio between imaginary and real components of k-space and is called phase ratio. The phase of ICF is the phase of inverse Fourier transformation and is called base phase. The two values of phase were summed up and used to reconstruct ICF images through inverse Fourier transformation. The reconstructed image is the combination of MR and ICF. Data obtained with T2-MRI and MRA indicates that the technique improves vessel detection in T2-MRI and contrast enhances T2-MRI and MRA.

Tunnels had been undergone accidental and intentional blast in the past. An analysis of a rock tunnel when subjected to internal blast loading has been presented in this paper. A three-dimensional finite element model of a huge rock mass comprising the tunnel has been developed in Abaqus/CAE. Diameter of the tunnel has been kept constant to a two-lane transportation tunnel. However, liner thickness of the concrete, overburden pressure on the tunnel has been varied to observe the response in different possible conditions. To incorporate the elastoplastic response of rock mass, Mohr-Coulomb constitutive material model has been considered. For modelling of trinitrotoluene (TNT), Jones-Wilkins-Lee material model has been adopted. Concrete Damage Plasticity material model has been adopted for tunnel lining. For the blast loading, Coupled-Eulerian-Lagrangian (CEL) model has been considered. Results highlight the importance of tunnel lining thickness and overburden depth while designing the tunnel in rocks. Under any amount of explosive, deep tunnels have been found to be safer than shallow tunnel.

Optical cables are enormous transmission media which carries high-speed data across transatlantic, intercontinental, international boundaries and cities. The optical cable is essential in data communication. The cable has become an indispensable component in optical communications infrastructure; hence, conscious efforts are always adopted to prevent or minimize faults in the optical network infrastructure. Typically, tracing fault in the underground optical network has been difficult even though optical time-domain reflectometer (OTDR) has been used to measure the distance of faults in the underground fiber cable. The methodologies deployed in the reviewed literature indicate a vast gap between the fault distance measured by the OTDR and the actual distance of fault. This paper observed the difficulties involved in tracing the actual spot of fault in the underground optical networks. The difficulty of tracing these underground faults mostly result in an undue delay and loss of revenue. This research presents a machine learning (ML) approach to predict the actual location of a fiber cable fault in an underground optical transmission link. Linear regression in the python sci-kit learn library was used to predict the actual location of a fault in an underground optical network. The MSE and MAE evaluation matrix used provided good accuracy results of 0.061291 and 0.080143, respectively. The result obtained in this paper indicates that faults in underground optical networks can be found quickly to avoid the delays in the fault tracing process, which leads to an excessive revenue loss.

The hot deformation characteristics of Nickel-based corrosion resistant alloy was studied in the temperature range of 1050~1200oC and the strain rate range of 0.001~0.1s-1 by employing hot compression tests. The results show that the peak stress increases with decreasing temperature and increasing strain rate, and the activation energy is about 409kJ/mol. Basing on the Avrami equation through using the critical strain (εc) and the strain for 50% DRX (ε0.5), a kinetic model for dynamic recrystallization (DRX) was established, where the model parameters could be obtained using the modified Zener-Hollomon parameter (Z*). Applying the model, the predicted value of the steady state strain (εss) and the strain for maximum softening rate (εm) agree well with the experimental results. Accordingly, the relationship between ε m and ε 0.5 is established, which is mainly dependent on the Avrami exponent (n). When n <3.25, εm becomes less than ε0.5 and the difference in between decreases with increasing the strain rate or decreasing the deformation temperature. Finally, through observing DRX microstructure under different deformation conditions, a power law relation between DRX grain size (Ddrx) and Z*, with an exponent of -0.36, was found.

Autonomous dishwasher loading is a benchmark problem in robotics that highlights the challenges of robotic perception, planning and manipulation in an unstructured environment. Current approaches resort to a specialized solution, however, these technologies are not viable in a domestic setting. Learning-based solutions seem promising for a general purpose solutions, however, they require large amounts of catered data, to be applied in real-world scenarios. This paper presents a novel solution based on pre-trained object detection networks. By developing a perception, planning and manipulation framework around an off-the-shelf object detection network, we are able to develop robust pick-and-place solutions that are easy to develop and general purpose requiring only a RGB feedback and a pinch gripper. Analysis of a real-world canteen tray data is first performed and used for developing our in-lab experimental setup. Our results obtained from real-world scenarios indicate that such approaches are highly desirable for plug-and-play domestic applications with limited calibration. All the associated data and code of this work is shared in a public repository.

We present a numerical method for simulating 2D flow through a channel with deformable walls. The fluid is assumed to be incompressible and viscous. We consider the highly viscous regime, where fluid dynamics are described by the Stokes equations, and the less viscous regime described by the Navier-Stokes equations. The model is formulated as an immersed boundary problem, with the channel defined by compliant walls that are immersed in a larger computational fluid domain. The channel traverses through the computational domain, and the walls do not form a closed region. When the walls deviate from their equilibrium position, they exert singular forces on the underlying fluid. We compute the numerical solution to the model equations using the immersed interface method, which preserves sharp jumps in the solution and its derivatives. The immersed interface method typically requires a closed immersed interface, a condition that is not met by the present configuration. Thus, a contribution of the present work is the extension of the immersed interface method to immersed boundary problems with open interfaces. Numerical results indicate that this new method converges with second-order accuracy in both space and time, and can sharply capture discontinuities in the fluid solution.

The paper presents a novel technique to detect the solvents in water like sugar, salt, and its combination using a wideband CPW fed microstrip antenna with periodic EBG ground structure. The antenna is designed and fabricated to operates at the bandwidth of 3 GHz with a stable gain of 9 dBi maintaining VSWR<2. The uniquely designed antenna works as a sensor in its near field to sense the solvents in water in terms of resonant frequency and reflection method in wider bandwidth. The technique also detects the changes in the temperature of the soft drinks as a function of reflection characteristics. This technique will be useful for finding the percentage of solvents in soft drinks before consumption. The sensing technique is without physical contact with the solution and chemical process. Therefore it is a healthy way to find the ingredients in solutions like soft drinks. The technique will be useful to the food regulation boards to limit the contents of beverages and cold drinks.

The synthetic rubber industry is of great importance and it is present in the daily life of world society. BR (butadiene rubber or polybutadiene) is one of the most used polymers in this field, mainly in tire production. Therefore, the control of operational conditions and final properties of the polymer formed are important points to be studied as they are a challenge for the industry. Thus, the present work focus in simulate the batch polymerization of polybutadiene using the Aspen Plus software, where 1,3-butadiene, titanium tetrachloride, triethylaluminium and hexane were used as monomer, catalyst, co-catalyst and solvent, respectively. Four cases were simulated changing the number of catalyst sites in order to predict and compare the final properties of polybutadiene resins including the average molecular weights, the molecular weight distribution and the evolution of operation conditions that are used at plant to monitor the course of the reaction like the reaction temperature and pressure.

A CALculation of PHase Diagrams (CALPHAD) approach was used to study the formation temperatures of nitride and carbonitride precipitates in nominated linepipe steels. The calculated results were in good agreement with relevant experimental data reported in the literatures, where the optimum titanium to nitrogen ratio and austenite grain growth was studied in similar steel compositions. The niobium concentration up to 0.12 wt% showed no influence on the formation temperature of nitrides in a common linepipe steel composition, while significantly increased the precipitation temperature of niobium carbides up to 0.03 wt%. Nitride precipitates contained a high concentration of titanium while niobium contributed mostly to the formation of carbide/carbonitrides. Although the dissolution and growth of precipitates are controlled kinetically, the thermodynamic calculation approach can be used to efficiently predict the equilibrium amount and composition of the stable phases in chemically complex systems. This results in a more accurate design of experiments, to minimise the number of tests required to obtain optimum chemical compositions and heat treatment procedures.

A document by Md Sarwar. Click on the document to view its contents.

Many scientific researches have shown an obvious fact that the quality control charts with variable sampling schemes are more effective than the classical ones in improving statistical measures. The average number of false alarms (ANF), the average number of samples (ANS), the average number of inspected items (ANI), and the adjusted average time to signal (AATS) are the most important statistical measures that have always been attending in the evaluation of control charts. In this paper, a comprehensive analytical review on the U control chart by the statistical measures have been explained. For this purpose, different levels of the possible factors are determined and presented the results of calculating the statistical measures with the obtained parameters on the sampling schemes of the U control chart. It is shown that the variable U control charts are able to improve the effectiveness statistical, especially for detecting shifts and number of false alarms.

Electrochemical machining (ECM) is a method for removing metal by anodic dissolution. At the interface between the workpiece surface and an electrically conductive fluid (electrolyte), the material is dissolved locally without direct physical contact to the cathodic tool. Due to the force-free nature of the process, ECM is used for machining high-strength or hard materials, such as titanium aluminides, Inconel, Waspaloy, and high nickel, cobalt, and rhenium alloys.1 However, determining suitable process parameters remains challenging due to their interacting effects on working distances during the machining process. Therefore a simulation-based approach to process design substantially reduces resource and time investment to achieve the desired geometry of the finished part. This methodology requires data about the materials electrochemical properties, such as removal velocity and current efficiency, which have to be obtained experimentally. In this study, a methodology for acquiring and processing this data as well as the development of multiphysics simulation models is presented for two use cases: (i) manufacturing a centrifugal impeller with a diameter of 14 mm consisting of the nickel alloy Inconel 713C for use in turbomachinery and (ii) the generation of a defined surface micro structure into the novel Mg-Y-Zn alloy WZ73.

Early detection of increasing values of intraocular pressure (IOP) due to glaucoma can prevent sever ocular diseases and ultimately, prevent loss of vision. Currently, the need for an accurate, mobile measurement of intraocular pressure is unmet within the modern healthcare practices. There is a potential to utilize soundwaves as a mobile measurement method and therefore, the relationship between IOP and the reflection coefficient of sound waves is investigated. Simulations are conducted using COMSOL Multiphysics to provide theoretical confirmation of the worthiness of the experiment. An experimental demonstrated is presented to further investigate the relationship between the internal pressure of an object and its acoustic reflection coefficient. The experiment exploits the use of hydrostatic pressure to determine internal pressure, and the reflection coefficient is measured and analyzed. An initial experiment is conducted to identify the resonant frequency of the object and the optimal frequency for maximizing reflection. The experiment shows comprehensively that there is a relationship between the internal pressure of an object and its acoustic reflection coefficient, providing a confirmation of the theory that would allow mobile measurements of IOP to be conducted with the use of a smart phone.

Applications of transfer function to derivation of a high precision model of tracer flow in a commercial measurement system is presented. A transfer function concept makes easier development of models of complex systems and consequently allows for obtaining a model that matches in the best way a physical system. The method has an additional profit viz. the same numerical algorithm i.e. inverse Laplace transform can be employed to solve the model both on the stage of precise model development (boundary value problem) and to find real model parameters (inverse boundary value problem). As a result of concept application, a very precise model of commercial measurement instrument was developed and, next, it was employed to determination of axial dispersion coefficients for empty tube and packed bed. Presented method is precise in wide range of operating conditions and faster comparing to other methods previously described in literature. The paper shows that mathematical modelling can be exploited to enhance measurements for a commercial measurement instrument i.e unlock the full potential of the commercial measurement system with no equipment design changes. The method is also a fast alternative to computational fluid dynamics for high precision calculations.

Goal: Fast Fourier transform (FFT), has been the main tool for EEG spectral analysis (SPA). As EEG can show nonlinear and non-stationary behavior, FFT may at times be meaningless. A novel method was developed for analyzing nonlinear and non-stationary signals using the Hilbert-Huang transform. Methods: We compared spectral analyses of EEG using FFT with Hilbert marginal spectra (HMS) with a multivariate empirical mode decomposition algorithm. Segments of continuous 60-sec EEGs recorded from 19 leads of 47 healthy volunteers were studied. Results: HMS showed a reduction of the alpha activity (-5.64%), with increments in the beta-1 (+1.67%), and gamma (+1.38%) fast activity bands, an increment in theta (+2.14%), and in delta (+0.45%) bands, and vice versa for the FFT method. For weighted mean frequencies, insignificant mean differences (lower than 1Hz) were observed between both methods for delta, theta, alpha, beta-1 and beta-2 bands, and only for gamma band values. The HMS were 3 Hz higher than the FFT method. Conclusion: HMS may be considered a good alternative for SPA of the EEG when nonlinearity or non-stationarity may be present.