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.
This paper presents a complete design procedure, with an optimized feeding method, of two-dimensional slotted waveguide antenna arrays (2D SWAs). For a desired sidelobe level ratio, the proposed system provides a pencil shape pattern with a narrow halfpower beamwidth, large sidelobe level ratio (SLR), and very low sidelobe levels (SLL), which makes it suitable for high power microwave applications. The radiating slotted waveguide antennas use longitudinal slots, designed for a specified slidelobe level ratio and resonance frequency. The resulting two-dimensional slotted waveguide antenna array is formed by stacking a number of similarly designed radiating SWAs, and fed with an additional SWA. The proposed feeding method uses longitudinal coupling slots rather than the conventional inclined coupling slots, which can provide better values of SLR and easily obtain very low SLLs, in comparison with the conventional systems. The feeder dimensions and slots positions are deduced from the dimensions and total number of the radiating SWAs. For a desired SLR, the slots excitation in the radiating and feeder SWAs are calculated based on a specified distribution. Then, using simplified closed-form equations and for a desired resonance frequency, the slots lengths, widths, and their distribution along the length of the radiating SWAs and feeder SWA can be found. Two examples are illustrated with different number of slots and radiating elements, and one is fabricated and tested. Chebyshev distribution is used to estimate the excitations of the SWA slots in the examples. The obtained measured and simulated results are in accordance with the design objectives.
Random sampling is a ubiquitous tool in simulations and modeling in a variety of applications. There are efficient algorithms for these for several known distributions, but in general, one must resort to computing or approximating the inverse to the distribution to generate random samples, given a random number generator for a uniform distribution. In certain physical and biomedical applications with which we have been particularly concerned, it has proven to be more efficient to provide random times for a walk of a fixed length, rather than the conventional random step lengths in a given time step for the walker. For these, the hitting-time distributions which have to be sampled have been computed, and proved to be complicated expressions with no efficient method to compute the inverse. In this paper, we explore a well known probability (the F-ratio distribution) - whose inverses are efficiently computable - as an alternative to generating look-up tables and interpolations to obtain the required time samples. We find that this distribution approximates the hitting-time distribution well, and report on error measures for both the approximation to the desired, and the error in the generated time samples. Future Monte Carlo simulations in a number of fields of application may benefit from methods such as we report here.
In a paper manufacturing system, it can be substantially important to detect machine failure before it occurs and take necessary maintenance actions to prevent a detrimental breakdown of the system. Multiple sensor data collected from a machine provides useful information on the system's health condition. However, it is hard to predict the system condition ahead of time due to the lack of clear ominous signs for future failures, a rare occurrence of failure events, and a wide range of sensor signals which might be correlated with each other. In this paper, we present two versions of feature extraction techniques based on the nearest neighbor combined with machine learning algorithms to detect a failure of the paper manufacturing machinery earlier than its occurrence from the multi-stream system monitoring data. First, for each sensor stream, the time series data is transformed into the binary form by extracting the class label of the nearest neighbor. We feed these transformed features into the decision tree classifier for the failure classification. Second, expanding the idea, the relative distance to the local nearest neighbor has been measured, results in the real-valued feature, and the support vector machine is used as a classifier. Our proposed algorithms are applied to the dataset provided by IISE 2019 data competition, and the results show the better performance than the given baseline.
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.
The nascent wave of disruptive competition in the current business environment brought about by the fourth industrial revolution (Fashion 4.0 or Apparel 4.0) is enormous. Therefore, it is paramount important to apparel industry to be flexible enough to respond quickly to the unstable customers’ demand through continuous improvement of their process efficiency and productivity. This study aims at achieving an optimal trouser assembly line balancing using simulation-based optimization via design of experiment. The empirical study is conducted at Southern Range Nyanza Limited (NYTIL) garment facility and a complex trouser assembly line with 72 operations is considered. The discrete event simulation of the trouser assembly line is developed using Arena simulation software. The local optimal solution is obtained from simulation experimentation and is adopted for the optimization process. The OptQuest tool is utilized to solve a single objective function (throughput) optimization problem. The results show that average throughput increases from the existing design (490 pieces per day) to local optimal design (638) and global optimal design (762). Consequently, the line efficiency increases from 61.2% to 79.7% to 95.2% respectively. The high increase in line efficiency and average throughput confirms the suitability assembly line balancing using simulation-based optimization via design of experiment.
Under proper loading conditions, micro-to-nanoscale heterogeneities (i.e., the bond system) that are commonly found within the materials of a system can coalesce until causing macroscopic alterations of the system properties. The bond system is responsible for atypical and invariant-scale non-linear elastic processes in granular media, from laboratory-tested materials (mm) to the Earth’s crust (km). The unusual observed behavior involves slow recovery, or relaxation, of the elastic properties after dynamic loading. Several models have been designed to explain non-linear elasticity, although their physics is still partially unknown. Here, we show that recovery processes are also observed at intermediary scales (m) in civil engineering structures, and that they might be related to structural health due to the healing of cracks. For Japanese buildings subjected to earthquakes, we observe rapid co-seismic reductions of their resonance frequency, followed by fascinating recoveries over different time-scales: over short times (i.e. seconds) for a single earthquake; over intermediate times (i.e. months) for a sequence of aftershocks; and over long times (i.e. years) for a series of earthquakes. By comparing two buildings with different damage levels after the 2011 Tohoku earthquake, we show how relaxation models can characterize the level of cracking caused by damaging events. Our results bridge the gap between the laboratory and seismological observation scales, verifying in this way the universality of recovery processes, and demonstrating their value for the detection and characterization of damage.
A Novel beam switch antenna based on a CRLH Butler matrix is presented in this manuscript. The CRLH transmission line is proposed to increase the number of beams switch. The proposed CRLH TL has more than 100- degree phase deference with different bias voltages. By different bias voltages between 0 to 8 Volt, different combinations of phase shifts are achieved. The CRLH transmission line is added to the conventional butler matrix to increase the number of phase incremental combination and consequently the beam pattern. A 5-degree beam resolution is achieved. The measurement results follow well with the simulation result.
Temperature, time and particle size effects on Irvingia gabonensis kernel oil (IGKO) yield, as well as the kinetics and thermodynamics parameters were investigated. Highest oil yield of 68.80 % (by weight) was obtained at 55 °C, 150 min., and 0.5 mm. Evaluated physicochemical properties of IGKO indicated that viscosity, acidity, dielectric strength, flash and pour points were 19.37 mm2s-1, 5.18 mg KOHg-1, 25.83 KV, 285 °C, and 17 °C, respectively, suggesting its feasibility as transformer fluid upon further treatment. Of the pseudo second order (PSO) and hyperbolic kinetic models studied, the former gave better fit to the experimental data. ∆H, ∆S and ∆G values of IGKO extraction at 0.5 mm and 328 K were, 251.81 KJ/mol, 1.08 KJ/mol and -105.49 KJ/mol, respectively, indicating the endothermic, irreversible and spontaneous nature of the process. Kinetic model equations that describe the process were successfully developed for both models based on the process parameters.
A study is considered to a steady, two-dimensional boundary layer flow of an incompressible MHD fluid for the Blasius and Sakiadis flows about a flat plate in the presence of thermo-diffusion (Dufour) and thermal-diffusion (Soret) effects for variable parameters. The governing partial differential equations are transformed into a system of nonlinear ordinary differential equations using similarity variables. The transformed systems are solved numerically by Runge-Kutta Gills method with shooting techniques. The variations of the flow velocity, temperature and concentration as well as the characteristics of heat and mass transfer are presented graphically with tabulated results. The numerical computations show that thermal boundary layer thickness is found to be increased with increasing values of Eckert number (Ec), Prandtl number (Pr) and local Grashof number (Gr_x) for both Blasius and Sakiadis flow. The Blasius flow elevates the thickness of the thermal boundary layer compared with the Sakiadis flow. The local magnetic field has shown that flow is retarded in the boundary layer but enhances temperature and concentration distributions.
The main goal of this study is to determine the aerodynamic performance and to characterize unsteady flows in a high-speed high-reaction pre-whirl axial flow fan. The pressure waves’ main diametrical modes where two blades interact with two vanes and their sequences are predicted. There are mainly two mechanisms of IGV-rotor interactions identified; the first is attributed to the potential effect whereas the second is due to the wake-blade interaction and the advection of wake mixing into the blades’ passages. Both effects are dependent on the circumferential positions of blades and the axial inter-distance between IGV and rotor. The time mode analyses of pressure fluctuations recorded from different monitor points are determined and the frequencies of prevailing modes and those related to the vortical flow structure through the components are also identified. The understanding of vanes and blade rows interactions at various axial inter-distances is an important step in determining the beneficial and detrimental effects on the design of high performance axial fan stage.
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.
High duty engineering component life is usually demonstrated through extensive testing and statistical analysis applied to empirical curve-fit equations. Because of this, the extent of the testing required is huge and costly: it must consider the load cycle range and test to high numbers of cycles. Furthermore, this testing must be repeated for every material, method of manufacture, and subsequent post-processing. Additive Manufacturing (AM) for high duty components has brought to the fore the question of the effect of porosity and surface roughness on fatigue life. Because there is relatively little service life experience, it is possible that the testing approach could also fail to represent conservatively the true life of a critical component. The authors propose the development of a fatigue model based on well-established engineering physics principles, by creating computational specimens with modelled surface roughness and porosity, and subjected to cyclic loading using Finite Element Analysis. They show that the combination of roughness features and sub-surface pores leads to an equivalent plastic strain distribution pattern that suggests an emergent physical process. Such a phenomenological understanding of the fatigue failure process should lead to improved life prediction techniques, more cost effective test procedures, and the development of better AM methods.
Reduction in the torsional vibration of heavy rotors like turbo-generator rotor is important for the safe and efficient functioning of the power plant. In this paper theoretical study is performed to control the torsional vibration in the turbo-generator rotor using piezoelectric material as sensor and actuator. Polyvinylidene fluoride (PVDF) layer is used as sensor and actuator. Proportional and velocity feedback is used as control law. The variation in the electromagnetic torque of synchronous generator during various electrical faults is evaluated using dq0 model. Finite element method is used to model the rotor elements. The coupled equations are solved in MATLAB using Newmark-beta integration method. The coupling elements of turbine and generator are most susceptible to the shear failure so torsional vibration of coupled rotor on coupling elements are compare for controlled and uncontrolled scenario. Simulation results show that for actively controlled rotor significant reduction in the amplitude of torsional vibrations is observed.
Aerospace components and its coatings are required to possess excellent surface properties namely: fatigue, wear and corrosion resistance over a wide temperature range. Stainless steels, titanium, nickel superalloy and more recently high entropy alloys have been used to improve the exterior properties of these components. In this study, AlCoCrFeNiCu and AlTiCrFeCoNi High Entropy Alloys were successfully fabricated using laser additive manufacturing to produce coatings on a mild steel base plate. The influence of the laser parameters (laser power and scan speed) on the microstructure, hardness and coat geometry (height, width and depth) were also investigated. The results revealed that coatings homogeneously adhered to substrate. The optimum processing parameters for both alloys with defect free structures at a preheat temperature of 400 °C, were at 1200-1600 W at 8-12 mm/s with the layers composed of both FCC and BCC phases. The laser parameters affected the geometry, quality and hardness. The results showed that optimizing the laser parameters achieved by preheating temperature invariably improved the performance of the alloys with potential coatings and aerospace structural applications.
Simulated microgravity (s-µg) devices provide unique conditions for elucidating the effects of gravitational unloading on biological processes. However, s-µg devices are being increasingly applied for mechanobiology studies without proper characterization of the mechanical environment generated by these systems, which confounds results and limits their interpretation. Furthermore, the cell culture methodology central to s-µg approaches introduces new conditions that can fundamentally affect results, but these are currently not addressed. It is essential to understand the complete culture environment and how constituent conditions can individually and synergistically affect cellular responses in order to interpret results correctly, otherwise outcomes may be misattributed to the effects of microgravity alone. For the benefit of the growing space biology community, this article critically reviews a typical s-µg cell culture environment in terms of three key conditions: fluid-mediated mechanical stimuli, oxygen tension and biochemical (cell signalling). Their implications for biological analysis are categorically discussed. A new set of controls is proposed to properly evaluate the respective effects of s-µg culture conditions, along with a reporting matrix and potential strategies for addressing the current limitations of simulated microgravity devices as a platform for mechanobiology.
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.