Search results for: tuned mass damper model

Authors: Saeed Khandan Siar, Stefan Tenbohlen, Christian Breuer, Raphael Lebreton

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The goal of this article is to investigate the detailed temperature distribution and the fluid flow of an oil cooled winding of a power transformer by means of computational fluid dynamics (CFD). The experimental setup consists of three passes of a zig-zag cooled disc type winding, in which losses are modeled by heating cartridges in each winding segment. A precise temperature sensor measures the temperature of each turn. The laboratory setup allows the exact control of the boundary conditions, e.g. the oil flow rate and the inlet temperature. Furthermore, a simulation model is solved using the open source computational fluid dynamics solver OpenFOAM and validated with the experimental results. The model utilizes the laminar and turbulent flow for the different mass flow rate of the oil. The good agreement of the simulation results with experimental measurements validates the model.

Keywords: CFD, conjugated heat transfer, power transformers, temperature distribution

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Authors: N. S. Achour, M. Hamdaoui, S. Ben Nasrallah

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Wicking and evaporation of water in porous knitted fabrics is investigated by combining experimental and analytical approaches: The standard wicking model from Lucas and Washburn is enhanced to account for evaporation and gravity effects. The goal is to model the effect of gravity and evaporation on wicking using simple analytical expressions and investigate the influence of fabrics geometrical parameters, such as porosity and thickness on evaporation impact on maximum reachable height values. The results show that fabric properties have a significant influence on evaporation effect. In this paper, an experimental study of determining water kinetics from different knitted fabrics were gravimetrically investigated permitting the measure of the mass and the height of liquid rising in fabrics in various atmospheric conditions. From these measurements, characteristic pore parameters (capillary radius and permeability) can be determined.

Keywords: evaporation, experimental study, geometrical parameters, model, porous knitted fabrics, wicking

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Authors: Qian You, Ibrahim Hassan, Lyes Kadem

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An experiment is conducted to fundamentally investigate flow oscillation characteristics in different sizes of single microtubes in vertical upward flow direction. Three microtubes have 0.889 mm, 0.533 mm, and 0.305 mm hydraulic diameters with 100 mm identical heated length. The mass flux of the working fluid FC-72 varies from 700 kg/m2•s to 1400 kg/m2•s, and the heat flux is uniformly applied on the tube surface up to 9.4 W/cm2. The subcooled inlet temperature is maintained around 24°C during the experiment. The effect of hydraulic diameter and mass flux are studied. The results showed that they have interactions on the flow oscillations occurrence and behaviors. The onset of flow instability (OFI), which is a threshold of unstable flow, usually appears in large microtube with diversified and sustained flow oscillations, while the transient point, which is the point when the flow turns from one stable state to another suddenly, is more observed in small microtube without characterized flow oscillations due to the bubble confinement. The OFI/transient point occurs early as hydraulic diameter reduces at a given mass flux. The increased mass flux can delay the OFI/transient point occurrence in large hydraulic diameter, but no significant effect in small size. Although the only transient point is observed in the smallest tube, it appears at small heat flux and is not sensitive to mass flux; hence, the smallest microtube is not recommended since increasing heat flux may cause local dryout.

Keywords: flow boiling instability, hydraulic diameter effect, a single microtube, vertical upward flow

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Authors: Kodo Sektani, Apostolos Tsouvalas, Andrei Metrikine

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The reassessment of existing movable bridges in The Netherlands has created the need for acceptance/rejection criteria to assess whether the machineries are meet certain design demands. However, the existing design code defines a different limit state design, meant for new machineries which is based on a simple linear spring-mass model. Observations show that existing bridges do not confirm the model predictions. In fact, movable bridges are nonlinear systems consisting of mechanical components, such as, gears, electric motors and brakes. Next to that, each movable bridge is characterized by a unique set of parameters. However, in the existing code various variables that describe the physical characteristics of the bridge are neglected or replaced by partial factors. For instance, the damping ratio ζ, which is different for drawbridges compared to bascule bridges, is taken as a constant for all bridge types. In this paper, a model is developed that overcomes some of the limitations of existing modelling approaches to capture the dynamics of the powertrain of a class of bridge machineries First, a semidefinite dynamic model is proposed, which accounts for stiffness, damping, and some additional variables of the physical system, which are neglected by the code, such as nonlinear braking torques. The model gives an upper bound of the peak forces/torques occurring in the powertrain during emergency braking. Second, a discrete nonlinear dynamic model is discussed, with realistic motor torque characteristics during normal operation. This model succeeds to accurately predict the full time history of the occurred stress state of the opening and closing cycle for fatigue purposes.

Keywords: Dynamics of movable bridges, Bridge machinery, Powertrains, Torque measurements

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Authors: K. AlJimaz, A. Abdullah, A. Abdulsalam, K. Ebdah, A. Abdalrasheed

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Understanding flow distribution and head losses is essential to design and calculate Thermo fluid parameters in order to reduce the pressure to a certain required pressure. This paper discusses the ways acquired in design and simulation to create and design an impedance box that reduces pressure. It's controlled by specific scientific principles such as Bernoulli’s principle and conservation of mass. In this paper, the design is made using SOLIDWORKS, and the simulation is done using ANSYS software to solve differential equations and study the parameters in the 3D model, also to understand how the design of this box reduced the pressure. The design was made so that fluid enters at a certain pressure of 3000 Pa in a single inlet; then, it exits from six outlets at a pressure of 300 Pa with respect to the conservation of mass principle. The effect of the distribution of flow and the head losses has been noticed that it has an impact on reducing the pressure since other factors, such as friction, were neglected and also the temperature, which was constant. The design showed that the increase in length and diameter of the pipe helped to reduce the pressure, and the head losses contributed significantly to reduce the pressure to 10% of the original pressure (from 3000 Pa to 300 Pa) at the outlets.

Keywords: box, pressure, thermodynamics, 3D

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Authors: Gian Bhushan, Vinkel Arora, M. L. Aggarwal

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The objective of the present study is to determine better eye end design of a mono leaf spring used in light motor vehicle. A conventional 65Si7 spring steel leaf spring model with standard eye, casted and riveted eye end are considered. The CAD model of the leaf springs is prepared in CATIA and analyzed using ANSYS. The standard eye, casted, and riveted eye leaf springs are subjected to similar loading conditions. The CAE analysis of the leaf spring is performed for various parameters like deflection and Von-Mises stress. Mass reduction of 62.9% is achieved in case of riveted eye mono leaf spring as compared to standard eye mono leaf spring for the same loading conditions.

Keywords: CAE, leaf spring, standard, casted, riveted eye

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Authors: William Middleton, Nodumo Zulu, Sue Harrison

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Open raceway ponds are currently the most used system for the commercial cultivation of algal biomass, as it is a cost-effective means of production. However, raceway ponds suffer from lower algal productivity when compared to closed photobioreactors. This is due to poor gas exchange between the fluid and the atmosphere. Carbon dioxide (CO₂) mass transfer is a large concern in the production of algae in raceway pond systems. The utilization of atmospheric CO₂ does not support maximal growth; however, CO₂ supplementation in the form of flue gas or concentrated CO₂ is not cost-effective. The introduction of slopes into the raceway system presents a possible improvement to the mass transfer from the air, as seen in previous work conducted at CeBER. Slopes improve turbulence (decreasing the concentration gradient of dissolved CO₂) and can cause air entrainment (allowing for greater surface area and contact time between the air and water). This project tests the findings of previous studies conducted in an indoor lab-scale raceway on a larger scale under outdoor conditions. The addition of slopes resulted in slightly increased CO₂ mass transfer as well as algal growth rate and productivity. However, there were reductions in energy consumption and average fluid velocity in the system. These results indicate a potential to improve the economic feasibility of algal biomass production, but further economic assessment would need to be carried out.

Keywords: algae, raceway ponds, mass transfer, algal culture, biotechnology, reactor design

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Authors: Ali Reza Mirzagoltabar Roshan, H. Ahmadi Taleshian, A. Eliasi

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This paper examines the effects of viscous and viscoelastic dampers as an efficient technique for seismic pounding mitigation. To aim that, 15 steel frame models with different numbers of stories and bays and also with different types of ductility were analyzed under 10 different earthquake records for assigned values of link damping and stiffness and the most suitable values of damper parameters (damping and stiffness) are presented. Moreover, it is demonstrated that viscous dampers can perform as efficiently as viscoelastic alternative with a more economical aspect for pounding mitigation purposes.

Keywords: adjacent buildings, separation distance, seismic pounding mitigation, viscoelastic link

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Authors: Chul Ho Han, Kyoung Hoon Kim

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This paper carries out a performance analysis based on the first and second laws of thermodynamics for heat recovery vapor generator (HRVG) of ammonia-water mixture when the heat source is low-temperature energy in the form of sensible heat. In the analysis, effects of the ammonia mass concentration and mass flow ratio of the binary mixture are investigated on the system performance including the effectiveness of heat transfer, entropy generation, and exergy efficiency. The results show that the ammonia concentration and the mass flow ratio of the mixture have significant effects on the system performance of HRVG.

Keywords: entropy, exergy, ammonia-water mixture, heat exchanger

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Authors: Said Alshukri, Mazhar Hussain Malik

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Green hydrogen is hydrogen produced using renewable energy sources. In the last few years, Oman aimed to reduce its dependency on fossil fuels. Recently, the hydrogen economy has become a global trend, and many countries have started to investigate the feasibility of implementing this sector. Oman created an alliance to establish the policy and rules for this sector. With motivation coming from both global and local interest in green hydrogen, this paper investigates the potential of producing hydrogen from wind and solar energies in three different locations in Oman, namely Duqm, Salalah, and Sohar. By using machine learning-based software “WEKA” and local metrological data, the project was designed to figure out which location has the highest wind and solar energy potential. First, various supervised models were tested to obtain their prediction accuracy, and it was found that the Random Forest (RF) model has the best prediction performance. The RF model was applied to 2021 metrological data for each location, and the results indicated that Duqm has the highest wind and solar energy potential. The system of one wind turbine in Duqm can produce 8335 MWh/year, which could be utilized in the water electrolysis process to produce 88847 kg of hydrogen mass, while a solar system consisting of 2820 solar cells is estimated to produce 1666.223 MWh/ year which is capable of producing 177591 kg of hydrogen mass.

Keywords: green hydrogen, machine learning, wind and solar energies, WEKA, supervised models, random forest

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Authors: Kanouni Fares

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This paper describes application of X-doped AlN (X=Sc, Cr and Y) to wideband surface acoustic wave (SAW) resonators in 200–300 MHz range. First, it is shown theoretically that Cr doped AlN thin film has the highest piezoelectric strain constant, accompanied by a lowest mechanical softening compared to Sc doped AlScN and Y doped AlN thin films for transition metals concentrations ranging from 0 to 25%. Next, the impact of transition metals (Sc, Cr and Y) concentration have been carried out for the first time, in terms of surface wave velocity, electrode reflectivity, transduction coefficient and distributed finger capacitance. Finely, the insertion loss of two-port SAW resonator based on AlXN (X=Sc, Cr and Y) deposited on sapphire substrate is obtained using P-matrix model, and it is shown that AlCrN-SAW resonator exhibit lower insertion loss compared to those based on AlScN and AlYN for metal concentrations of 25%.This finding may position Cr doped AlN as a prime piezoelectric material for low loss SAW resonators whose performance can be tuned via Cr composition.

Keywords: P-Matrix, SAW-delay line, interdigital transducer, nitride aluminum, metals transition

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Authors: Kamran Siddique, Hiroyuki Asada, Yoshifumi Ogami

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The use of Micro Gas Turbine (MGT) as the engine in Unmanned Aerobic Vehicles (UAVs) and power source in Robotics is widespread these days. Research has been conducted in the past decade or so to improve the performance of different components of MGT. This type of engine has interrelated components which have non-linear characteristics. Therefore, the overall engine performance depends on the individual engine element’s performance. Computational Fluid Dynamics (CFD) is one of the simulation method tools used to analyze or even optimize MGT system performance. In this study, the compressor of the MGT is designed, and performance optimization is being done using CFD. Performance of the micro compressor is improved in order to increase the overall performance of MGT. A high value of pressure ratio is to be achieved by studying the effect of change of different operating parameters like mass flow rate and revolutions per minute (RPM) and aerodynamical and geometrical parameters on the pressure ratio of the compressor. Two types of compressor designs are considered in this study; 3D centrifugal and ‘planar’ designs. For a 10 mm impeller, the planar model is the simplest compressor model with the ease in manufacturability. On the other hand, 3D centrifugal model, although more efficient, is very difficult to manufacture using current microfabrication resources. Therefore, the planar model is the best-suited model for a micro compressor. So. a planar micro compressor has been designed that has a good pressure ratio, and it is easy to manufacture using current microfabrication technologies. Future work is to fabricate the compressor to get experimental results and validate the theoretical model.

Keywords: computational fluid dynamics, microfabrication, MEMS, unmanned aerobic vehicles

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Authors: Vasile Simulescu, Jakub Mondek, Miloslav Pekař

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Hyaluronic acid (HA) is an anionic glycosaminoglycan distributed throughout connective, epithelial and neural tissues. The importance of hyaluronic acid increased in the last decades. It has many applications in medicine and cosmetics. Hyaluronic acid has been used in attempts to treat osteoarthritis of the knee via injecting it into the joint. Bovine serum albumin (also known as BSA) is a protein derived from cows, which has many biochemical applications. The aim of our research work was to compare the thermal degradation of hyaluronic acid and BSA in powder and in solution, by determining changes in molar mass and conformation, by using SEC-MALLS (size exclusion chromatography -multi angle laser light scattering). The aim of our research work was to observe the degradation in powder and in solution of different molar mass hyaluronic acid samples, at different temperatures for certain periods. The degradation of the analyzed samples was mainly observed by modifications in molar mass.

Keywords: thermal degradation, hyaluronic acid, BSA, SEC-MALLS

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Authors: Mustafa Metin Donma, Orkide Donma

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Vitamin deficiencies are common in obese individuals. Particularly, the status of vitamin B12 and its association with vitamin B9 (folate) and vitamin D is under investigation in recent time. Vitamin B12 is closely related to many vital processes in the body. In clinical studies, its involvement in fat metabolism draws attention from the obesity point of view. Obesity, in its advanced stages and in combination with metabolic syndrome (MetS) findings, may be a life-threatening health problem. Pediatric obesity is particularly important because it may be a predictor of severe chronic diseases during the adulthood period of the child. Due to its role in fat metabolism, vitamin B12 deficiency may disrupt metabolic pathways of the lipid and energy metabolisms in the body. The association of low B12 levels with obesity degree may be an interesting topic to be investigated. Obesity indices may be helpful at this point. Weight- and fat-based indices are available. Of them, body mass index (BMI) is in the first group. Fat mass index (FMI), fat-free mass index (FFMI) and diagnostic obesity notation model assessment-II (D2I) index lie in the latter group. The aim of this study is to clarify possible associations between vitamin B12 status and obesity indices in the pediatric population. The study comprises a total of one hundred and twenty-two children. Thirty-two children were included in the normal body mass index (N-BMI) group. Forty-six and forty-four children constitute groups with morbid obese children without MetS and with MetS, respectively. Informed consent forms and the approval of the institutional ethics committee were obtained. Tables prepared for obesity classification by World Health Organization were used. Metabolic syndrome criteria were defined. Anthropometric and blood pressure measurements were taken. Body mass index, FMI, FFMI, D2I were calculated. Routine laboratory tests were performed. Vitamin B9, B12, D concentrations were determined. Statistical evaluation of the study data was performed. Vitamin B9 and vitamin D levels were reduced in MetS group compared to children with N-BMI (p>0.05). Significantly lower values were observed in vitamin B12 concentrations of MetS group (p<0.01). Upon evaluation of blood pressure as well as triglyceride levels, there exist significant increases in morbid obese children. Significantly decreased concentrations of high density lipoprotein cholesterol were observed. All of the obesity indices and insulin resistance index exhibit increasing tendency with the severity of obesity. Inverse correlations were calculated between vitamin D and insulin resistance index as well as vitamin B12 and D2I in morbid obese groups. In conclusion, a fat-based index, D2I, was the most prominent body index, which shows a strong correlation with vitamin B12 concentrations in the late stage of obesity in children. A negative correlation between these two parameters was a confirmative finding related to the association between vitamin B12 and obesity degree.

Keywords: body mass index, children, D2I index, fat mass index, obesity

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Authors: A. Soria-Salinas, M.-P. Zorzano, J. Martín-Torres, J. Sánchez-García-Casarrubios, J.-L. Pérez-Díaz, A. Vakkada-Ramachandran

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The current state-of-the-art methods of mass gauging of Electric Propulsion (EP) propellants in microgravity conditions rely on external measurements that are taken at the surface of the tank. The tanks are operated under a constant thermal duty cycle to store the propellant within a pre-defined temperature and pressure range. We demonstrate using computational fluid dynamics (CFD) simulations that the heat-transfer within the pressurized propellant generates temperature and density anisotropies. This challenges the standard mass gauging methods that rely on the use of time changing skin-temperatures and pressures. We observe that the domes of the tanks are prone to be overheated, and that a long time after the heaters of the thermal cycle are switched off, the system reaches a quasi-equilibrium state with a more uniform density. We propose a new gauging method, which we call the Improved PVT method, based on universal physics and thermodynamics principles, existing TRL-9 technology and telemetry data. This method only uses as inputs the temperature and pressure readings of sensors externally attached to the tank. These sensors can operate during the nominal thermal duty cycle. The improved PVT method shows little sensitivity to the pressure sensor drifts which are critical towards the end-of-life of the missions, as well as little sensitivity to systematic temperature errors. The retrieval method has been validated experimentally with CO₂ in gas and fluid state in a chamber that operates up to 82 bar within a nominal thermal cycle of 38 °C to 42 °C. The mass gauging error is shown to be lower than 1% the mass at the beginning of life, assuming an initial tank load at 100 bar. In particular, for a pressure of about 70 bar, just below the critical pressure of CO₂, the error of the mass gauging in gas phase goes down to 0.1% and for 77 bar, just above the critical point, the error of the mass gauging of the liquid phase is 0.6% of initial tank load. This gauging method improves by a factor of 8 the accuracy of the standard PVT retrievals using look-up tables with tabulated data from the National Institute of Standards and Technology.

Keywords: electric propulsion, mass gauging, propellant, PVT, xenon

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Authors: Bita Mohajernia, R. J. Urbanic

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Mold making techniques have focused on meeting the customers’ functional and process requirements; however, today, molds are increasing in size and sophistication, and are difficult to manufacture, transport, and set up due to their size and mass. Presently, mold weight saving techniques focus on pockets to reduce the mass of the mold, but the overall size is still large, which introduces costs related to the stock material purchase, processing time for process planning, machining and validation, and excess waste materials. Reducing the overall size of the mold is desirable for many reasons, but the functional requirements, tool life, and durability cannot be compromised in the process. It is proposed to use Finite Element Analysis simulation tools to model the forces, and pressures to determine where the material can be removed. The potential results of this project will reduce manufacturing costs. In this study, a light weight structure is defined by an optimal distribution of material to carry external loads. The optimization objective of this research is to determine methods to provide the optimum layout for the mold structure. The topology optimization method is utilized to improve structural stiffness while decreasing the weight using the OptiStruct software. The optimized CAD model is compared with the primary geometry of the mold from the NX software. Results of optimization show an 8% weight reduction while the actual performance of the optimized structure, validated by physical testing, is similar to the original structure.

Keywords: finite element analysis, plastic injection molding, topology optimization, weight reduction

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Authors: Sapan Tiwari, Namrata Ghosh

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In urban mass transit, crew scheduling always plays a significant role. It deals with the formulation of work timetables for its staff so that an organization can meet the demand for its products or services. The efficient schedules of a specified timetable have an enormous impact on staff demand. It implies that an urban mass transit company's financial outcomes are strongly associated with planning operations in the region. The research aims to demonstrate the state of the crew scheduling studies and its practical implementation in mass transit businesses in metropolitan areas. First, there is a short overview of past studies in the field. Subsequently, the restrictions and problems with crew scheduling and some models, which have been developed to solve the related issues with their mathematical formulation, are defined. The comments are completed by a description of the solution opportunities provided by computer-aided scheduling program systems for operational use and exposures from urban mass transit organizations. Furthermore, Bus scheduling is performed using the Hungarian technique of problem-solving tasks and mathematical modeling. Afterward, the crew scheduling problem, which consists of developing duties using predefined tasks with set start and end times and places, is resolved. Each duty has to comply with a set line of work. The objective is to minimize a mixture of fixed expenses (number of duties) and varying costs. After the optimization of cost, the outcome of the research is that the same frequency can be provided with fewer buses and less workforce.

Keywords: crew scheduling, duty, optimization of cost, urban mass transit

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Authors: J. J. Rickard, A. Belli, P. Goldberg Oppenheimer

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Medical diagnostics, environmental monitoring, homeland security and forensics increasingly demand specific and field-deployable analytical technologies for quick point-of-care diagnostics. Although technological advancements have made optical methods well-suited for miniaturization, a highly-sensitive detection technique for minute sample volumes is required. Raman spectroscopy is a well-known analytical tool, but has very weak signals and hence is unsuitable for trace level analysis. Enhancement via localized optical fields (surface plasmons resonances) on nanoscale metallic materials generates huge signals in surface-enhanced Raman scattering (SERS), enabling single molecule detection. This enhancement can be tuned by manipulation of the surface roughness and architecture at the sub-micron level. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for SERS-based sensing devices. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing. The superior detection properties and the ability to fabricate SERS substrates on the miniaturized scale, will facilitate the development of advanced and novel opto-fluidic devices, such as portable detection systems, and will offer numerous applications in biomedical diagnostics, forensics, ecological warfare and homeland security.

Keywords: hierarchical electrohydrodynamic patterning, medical diagnostics, point-of care devices, SERS

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Authors: Bo Yang, Hali̇l Ceylan, Ali Ulvi̇ Uzer

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This experimental study was performed to investigate the effect of biofuel co-products (BCPs) with sulfur-free lignin addition on the unconsolidated on strength and durability behavior in pavement soil stabilization subjected to freezing–thawing cycles. For strength behavior, a series of unconfined compression tests were conducted. Mass losses were also calculated after freezing–thawing cycles as criteria for durability behavior. To investigate the effect of the biofuel co-products on the durability behavior of the four type’s soils, mass losses were calculated after 12 freezing–thawing cycles. The co-products tested are promising additives for improving durability under freeze-thaw conditions, and each type has specific advantages.

Keywords: durability, mass lose, freezing–thawing test, bio-energy co-product, soil stabilization

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Authors: Abdulrahman Sumayli, Saad M. AlShahrani

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For the hydrogenation process, knowing the solubility of hydrogen (H2) in hydrocarbons is critical to improve the efficiency of the process. We investigated the H2 solubility computation in four heavy crude oil feedstocks using machine learning techniques. Temperature, pressure, and feedstock type were considered as the inputs to the models, while the hydrogen solubility was the sole response. Specifically, we employed three different models: Support Vector Regression (SVR), Gaussian process regression (GPR), and Bayesian ridge regression (BRR). To achieve the best performance, the hyper-parameters of these models are optimized using the whale optimization algorithm (WOA). We evaluated the models using a dataset of solubility measurements in various feedstocks, and we compared their performance based on several metrics. Our results show that the WOA-SVR model tuned with WOA achieves the best performance overall, with an RMSE of 1.38 × 10− 2 and an R-squared of 0.991. These findings suggest that machine learning techniques can provide accurate predictions of hydrogen solubility in different feedstocks, which could be useful in the development of hydrogen-related technologies. Besides, the solubility of hydrogen in the four heavy oil fractions is estimated in different ranges of temperatures and pressures of 150 ◦C–350 ◦C and 1.2 MPa–10.8 MPa, respectively

Keywords: temperature, pressure variations, machine learning, oil treatment

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Authors: Mikhail O. Eremin

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Present work is devoted to experimental study and numerical modelling of failure of rocks typical for Kuzbass coal basin (Russia). The main goal was to define strength and deformation characteristics of rocks on the base of uniaxial compression and three-point bending loadings and then to build a mathematical model of failure process for both types of loading. Depending on particular physical-mechanical characteristics typical rocks of Kuzbass coal basin (sandstones, siltstones, mudstones, etc. of different series – Kolchuginsk, Tarbagansk, Balohonsk) manifest brittle and quasi-brittle character of failure. The strength characteristics for both tension and compression are found. Other characteristics are also found from the experiment or taken from literature reviews. On the base of obtained characteristics and structure (obtained from microscopy) the mathematical and structural models are built and numerical modelling of failure under different types of loading is carried out. Effective characteristics obtained from modelling and character of failure correspond to experiment and thus, the mathematical model was verified. An Instron 1185 machine was used to carry out the experiments. Mathematical model includes fundamental conservation laws of solid mechanics – mass, impulse, energy. Each rock has a sufficiently anisotropic structure, however, each crystallite might be considered as isotropic and then a whole rock model has a quasi-isotropic structure. This idea gives an opportunity to use the Hooke’s law inside of each crystallite and thus explicitly accounting for the anisotropy of rocks and the stress-strain state at loading. Inelastic behavior is described in frameworks of two different models: von Mises yield criterion and modified Drucker-Prager yield criterion. The damage accumulation theory is also implemented in order to describe a failure process. Obtained effective characteristics of rocks are used then for modelling of rock mass evolution when mining is carried out both by an open-pit or underground opening.

Keywords: damage accumulation, Drucker-Prager yield criterion, failure, mathematical modelling, three-point bending, uniaxial compression

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Authors: Sabin Stoica

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In this paper the theoretical challenges in the study of neutrinoless double beta decay are reviewed. Then, new upper limits of the neutrino mass parameters in the case of three isotopes are derived; 48Ca, 76Ge, and 82Se, assuming two possible mechanisms of occurrence of this nuclear process, namely the exchange of i) light left-handed neutrinos and ii) heavy right-handed neutrinos, between two nucleons inside the nucleus. The derivation is based on accurate calculations of the phase space factors and nuclear matrix elements performed with new high-performance computer codes, which are described in more detail in recent publications. These results are useful both for a better understanding of the scale of neutrino absolute mass and for the planning of future double beta decay experiments.

Keywords: double beta decay, neutrino properties, nuclear matrix elements, phase space factors

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Authors: Farzad Jafarpour Taher, Maghsud Solimanpur

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Production planning is one of the complex tasks in multi-product firms that produce a wide range of products. Since resources in mass production companies are limited and different products use common resources, there must be a careful plan so that firms can respond to customer needs efficiently. Azar-battery Company is a firm that provides twenty types of products for its customers. Therefore, careful planning must be performed in this company. In this research, the current conditions of Azar-battery Company were investigated to provide a mathematical programming model to determine the optimum production rate of the products in this company. The production system of this company is multi-stage, multi-product and multi-period. This system is studied in terms of a one-year planning horizon regarding the capacity of machines and warehouse space limitation. The problem has been modeled as a linear programming model with deterministic demand in which shortage is not allowed. The objective function of this model is to minimize costs (including raw materials, assembly stage, energy costs, packaging, and holding). Finally, this model has been solved by Lingo software using the branch and bound approach. Since the computation time was very long, the solver interrupted, and the obtained feasible solution was used for comparison. The proposed model's solution costs have been compared to the company’s real data. This non-optimal solution reduces the total production costs of the company by about %35.

Keywords: multi-period, multi-product production, multi-stage, production planning

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Joshua Garba Dodo

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Corruption has become endemic in Nigeria, affecting almost all facets of the society, thereby thwarting the effort of national development. The thrust of this paper, therefore, is to see how corruption can be brought to its barest minimum if not totally eradicated using social studies and other agents of socialization. In doing that, the paper defines the concepts of corruption, social studies, and socialization. Discourse on the causes of corruption and the effect on national development is made. The paper examines the role of social studies, family, and the mass media in tackling corruption. The paper also asserts that if an aggressive campaign is mounted by the mass media as a way of supporting the present government in her effort to solve the corruption problem in the country, it will help in changing the psyche of the citizenry about corruption. Finally, the paper recommends, among others, that families and communities should sanction their sons and daughters involved in corrupt practices if proven by a competent court of law.

Keywords: corruption, social studies, family, mass media, socialization

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Authors: Mahfoodha Al-Kitani, Dylan Thompson, Keith Stokes

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Sickle cell disease (SCD) and sickle cell trait (SCT) are the most common hematological diseases in Oman according to the national survey of genetic blood disorders. The aim of this study was to determine markers of physical fitness and anthropometrics indices in children with sickle cell disease and children with sickle cell trait and compare them with normal healthy children of the same age. One hundred and twenty male children participated in the present study divided to three groups: 40 with sickle disease (SCD; age, 13.3(.80), height, 131.9(3.5), mass, 29.2(3.1)); 40 with sickle cell trait (SCT; age, 12.2(.80), height, 141.0(9.9), mass, 38.0(4.4)); and 40 controls with normal hemoglobin (Con; age, 12.8(.80), height, 139.4(8.7), mass, 37.2(4.3)). All children completed a 5-min running exercise test on a treadmill at speed corresponding to 5 km/hr. Heart rate and was recorded during exercise and during 10-min of recovery. Blood lactate was measured before and 5 min after the completion of exercise. Children with SCD exhibited a higher mean value (P < 0.05) for percent body fat and fat mass than the normal healthy subjects and SCT subjects. Resting values of hemoglobin were similar in SCT (11.04(.78)) and control (10.8(94)) groups, and lower in SCD (8.89(.54); P < 0.05). There was a strong correlation between peak heart rate and resting hemoglobin levels for the three groups (r= -.472. n= 120, p < .0005).The SCD group (175.2(10.3)) exhibited higher mean heart rate during exercise than those observed in the SCT (143.7(9.5)) and normal control children (144.5(22.4); P < 0.05). Additionally, SCD children showed higher serum lactate values before and after treadmill exercise compared to the other groups (P < 0.05). Children with sickle cell trait demonstrate similar physical fitness level and similar exercise responses to treadmill stress test to normal children. In contrast, SCD children have lower body mass, higher fat mass and lower physical fitness than children with SCT and healthy controls.

Keywords: sickle cell disease, sickle cell trait, children, exercise

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Authors: Anders Schou Simonsen, Kim Sorensen, Thomas Condra

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Wet scrubbers are used for flue gas desulfurization by injecting water directly into the flue gas stream from a set of sprayers. The water droplets will flow freely inside the scrubber, and flow down along the scrubber walls as a thin wall film while reacting with the gas phase to remove SO₂. This complex multiphase phenomenon can be divided into three main contributions: the continuous gas phase, the liquid droplet phase, and the liquid wall film phase. This study proposes a complete model, where all three main contributions are taken into account and resolved using OpenFOAM for the continuous gas phase, and MATLAB for the liquid droplet and wall film phases. The 3D continuous gas phase is composed of five species: CO₂, H₂O, O₂, SO₂, and N₂, which are resolved along with momentum, energy, and turbulence. Source terms are present for four species, energy and momentum, which are affecting the steady-state solution. The liquid droplet phase experiences breakup, collisions, dynamics, internal chemistry, evaporation and condensation, species mass transfer, energy transfer and wall film interactions. Numerous sub-models have been implemented and coupled to realise the above-mentioned phenomena. The liquid wall film experiences impingement, acceleration, atomization, separation, internal chemistry, evaporation and condensation, species mass transfer, and energy transfer, which have all been resolved using numerous sub-models as well. The continuous gas phase has been coupled with the liquid phases using source terms by an approach, where the two software packages are couples using a link-structure. The complete CFD model has been verified using 16 experimental tests from an existing scrubber installation, where a gradient-based pattern search optimization algorithm has been used to tune numerous model parameters to match the experimental results. The CFD model needed to be fast for evaluation in order to apply this optimization routine, where approximately 1000 simulations were needed. The results show that the complex multiphase phenomena governing wet scrubbers can be resolved in a single model. The optimization routine was able to tune the model to accurately predict the performance of an existing installation. Furthermore, the study shows that a coupling between OpenFOAM and MATLAB is realizable, where the data and source term exchange increases the computational requirements by approximately 5%. This allows for exploiting the benefits of both software programs.

Keywords: desulfurization, discrete phase, scrubber, wall film

Procedia PDF Downloads 232

Authors: Yungtai Lo

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Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

Procedia PDF Downloads 327

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

Procedia PDF Downloads 80

Authors: Manish Kumar Thakur, Chiranjit Sarkar

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Sedimentation of magnetorheological (MR) fluid affects its working. MR fluid is a smart fluid that has unique qualities such as quick responsiveness and easy controllability. It is used in the MR damper, MR brake, and MR clutch. In this work effect of sedimentation on torque transmission in the shear mode operated MR clutch is investigated. A test rig is developed to test the impact of sedimentation on torque transmission in the MR clutch. Torque transmission capability of MR clutch has been measured under two conditions to confirm the result of sedimentation. The first experiment is done just after filling and the other after one week. It has been observed that transmission torque is decreased after sedimentation. Hence sedimentation affects the working of the MR clutch.

Keywords: clutch, magnetorheological fluid, sedimentation, torque

Procedia PDF Downloads 154