Search results for: engineering demand parameter

Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

Procedia PDF Downloads 125

Authors: Andreas Aceranti, Guido Bighiani, Francesca Crotto, Marco Colorato, Stefania Zaghi, Marino Zanetti, Simonetta Vernocchi

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The management of eye parameters such as convergence, accommodation, and miosis is very complex; in fact, both the neurovegetative system and the complex Oculocephalgiria system come into play. We have found the effectiveness of the "highvelocity low amplitude" technique directed on C7-T1 (where the cilio-spinal nucleus of the budge is located) in improving the convergence parameter through the measurement of the point of maximum convergence. With this research, we set out to investigate whether the improvement obtained through the High Velocity Low Amplitude maneuver lasts over time, carrying out a pre-manipulation measurement, one immediately after manipulation and one month after manipulation. We took a population of 30 subjects with both refractive and non-refractive problems. Of the 30 patients tested, 27 gave a positive result after the High Velocity Low Amplitude maneuver, giving an improvement in the point of maximum convergence. After a month, we retested all 27 subjects: some further improved the result, others kept, and three subjects slightly lost the gain obtained. None of the re-tested patients returned to the point of maximum convergence starting pre-manipulation. This result opens the door to a multidisciplinary approach between ophthalmologists and osteopaths with the aim of addressing oculomotricity and convergence deficits that increasingly afflict our society due to the massive use of devices and for the conduct of life in closed and restricted environments.

Keywords: point of maximum convergence, HVLA, improvement in PPC, convergence

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Suneeta Kumari, Abanti Sahoo

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Industrial effluents treatment is a major problem in the world. All wastewater treatment methods have some problems in the environment. Due to this reason, today many natural biopolymers are being used in the waste water treatment because those are safe for our environment. In this study, synthesis and characterization of polyethersulfone/chitosan membranes (Thin film composite membrane) are carried out. Fish scales are used as raw materials. Different characterization techniques such as Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), scanning electron microscope (SEM) and Thermal gravimetric analysis (TGA) are analysed for the synthesized membrane. The performance of membranes such as flux, rejection, and pore size are also checked. The synthesized membrane is used for the treatment of steel industry waste water where Biochemical oxygen demand (BOD), Chemical Oxygen Demand (COD), pH, colour, Total dissolved solids (TDS), Total suspended solids (TSS), Electrical conductivity (EC) and Turbidity aspects are analysed.

Keywords: fish scale, membrane synthesis, treatment of industrial effluents, chitosan

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Authors: Farida Kaouah, Chahida Oussalah, Wassila Hachi, Salim Boumaza, Mohamed Trari

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A catalyst of ZnO nanoparticles was used in the photocatalytic process of treatment for potential use towards bisphenol A (BPA) degradation in an aqueous solution. To achieve this study, the effect of parameters such as the catalyst dose, initial concentration of BPA and pH on the photocatalytic degradation of BPA was studied. The results reveal that the maximum degradation (more than 93%) of BPA occurred with ZnO catalyst in 120 min of stirring at natural pH (7.1) under solar light irradiation. It was found that chemical oxygen demand (COD) reduction takes place at a faster rate under solar light as compared to that of UV light. The kinetic studies were achieved and revealed that the photocatalytic degradation process obeyed a Langmuir–Hinshelwood model and followed a pseudo-first order rate expression. This work envisages the great potential that sunlight mediated photocatalysis has in the removal of bisphenol A from wastewater.

Keywords: bisphenol A, photocatalytic degradation, sunlight, zinc oxide, Langmuir–Hinshelwood model, chemical oxygen demand

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

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Authors: Maria Bercea, Bernhard A. Wolf

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The thermodynamic behavior for solutions of poly (methyl methacrylate-ran-t-butyl methacrylate) of variable composition as compared with the corresponding homopolymers was investigated by light scattering measurements carried out for dilute solutions and vapor pressure measurements of concentrated solutions. The complex dependencies of the Flory Huggins interaction parameter on concentration and copolymer composition in solvents of different polarity (toluene and chloroform) can be understood by taking into account the ability of the polymers to rearrange in a response to changes in their molecular surrounding. A recent unified thermodynamic approach was used for modeling the experimental data, being able to describe the behavior of the different solutions by means of two adjustable parameters, one representing the effective number of solvent segments and another one accounting for the interactions between the components. Thus, it was investigated how the solvent quality changes with the composition of the copolymers through the Gibbs energy of mixing as a function of polymer concentration. The largest reduction of the Gibbs energy at a given composition of the system was observed for the best solvent. The present investigation proves that the new unified thermodynamic approach is a general concept applicable to homo- and copolymers, independent of the chain conformation or shape, molecular and chemical architecture of the components and of other dissimilarities, such as electrical charges.

Keywords: random copolymers, Flory Huggins interaction parameter, Gibbs energy of mixing, chemical architecture

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Authors: N. Balamurugan, N. V. Mahalakshmi

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Compression ignition (CI) engines are known for their high thermal efficiency in comparison with spark-ignited (SI) engines. This makes CI engines a potential candidate for the future prime source of power for transportation sector to reduce greenhouse gas emissions and to shrink carbon footprint. However, CI engines produce high levels of NOx and soot emissions. Conventional methods to reduce NOx and soot emissions often result in the infamous NOx-soot trade-off. The injection parameters are one of the most important factors in the working of CI engines. The engine performance, power output, economy etc., is greatly dependent on the effectiveness of the injection parameters. The injection parameter has their direct impact on combustion process and pollutant formation. The injection parameter’s values are required to be optimised according to the application of the engine. Control of fuel injection mode is one method for reduction of NOx and soot emissions that is achievable. This study aims to assess, compare and analyse the influence of the effect of injection characteristics that is SOI timing studied on combustion and emissions in in-cylinder combustion processes with that of conventional DI Diesel Engine system using the commercial Computational Fluid Dynamic (CFD) package STAR- CD ES-ICE.

Keywords: variation of injection timing, compression ignition engine, spark-ignited, Computational Fluid Dynamic

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Authors: E. Marei, A. Hammad, S. Ismail, A. El-Gindy

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This study aims to investigate the ability of different formula of mixed bacteria as a biological treatments of wastewater after primary treatment as a bio-treatment and bio-removal and bio-adsorbent of different heavy metals in natural circumstances. The wastewater was collected from Sarpium forest site-Ismailia Governorate, Egypt. These treatments were mixture of free cells and mixture of immobilized cells of different bacteria. These different formulas of mixed bacteria were prepared under Lab. condition. The obtained data indicated that, as a result of wastewater bio-treatment, the removal rate was found to be 76.92 and 76.70% for biological oxygen demand, 79.78 and 71.07% for chemical oxygen demand, 32.45 and 36.84 % for ammonia nitrogen as well as 91.67 and 50.0% for phosphate after 24 and 28 hrs with mixed free cells and mixed immobilized cells, respectively. Moreover, the bio-removals of different heavy metals were found to reach 90.0 and 50. 0% for Cu ion, 98.0 and 98.5% for Fe ion, 97.0 and 99.3% for Mn ion, 90.0 and 90.0% Pb, 80.0% and 75.0% for Zn ion after 24 and 28 hrs with mixed free cells and mixed immobilized cells, respectively. The results indicated that 13.86 and 17.43% of removal efficiency and reduction of total dissolved solids were achieved after 24 and 28 hrs with mixed free cells and mixed immobilized cells, respectively.

Keywords: wastewater bio-treatment , bio-sorption heavy metals, biological desalination, immobilized bacteria, free cell bacteria

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Authors: Lizhou Chen, Abdelhamid Belgaid, Assem Elsayed, Xiaoming Yang

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Compression index is essential in foundation settlement calculation. The traditional method for determining compression index is consolidation test which is expensive and time consuming. Many researchers have used regression methods to develop empirical equations for predicting compression index from soil properties. Based on a large number of compression index data collected from consolidation tests, the accuracy of some popularly empirical equations were assessed. It was found that primary compression index is significantly overestimated in some equations while it is underestimated in others. The sensitivity analyses of soil parameters including water content, liquid limit and void ratio were performed. The results indicate that the compression index obtained from void ratio is most accurate. The ANOVA (analysis of variance) demonstrates that the equations with multiple soil parameters cannot provide better predictions than the equations with single soil parameter. In other words, it is not necessary to develop the relationships between compression index and multiple soil parameters. Meanwhile, it was noted that secondary compression index is approximately 0.7-5.0% of primary compression index with an average of 2.0%. In the end, the proposed prediction equations using power regression technique were provided that can provide more accurate predictions than those from existing equations.

Keywords: compression index, clay, settlement, consolidation, secondary compression index, soil parameter

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Authors: Muhammad Zikril Hakim Md. Azizi, Norhafizan Ahmad, Raja Ariffin Raja Ghazilla

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Postural stability, attention level of the archer and particularly the vibrations of the bow itself plays a prominent role in determining the athletes performance. Many techniques and systems had been developing to monitor the parameters of the archers during training. In Malaysia, archery coaches tend to use non-scientific ways that they are familiar with, to evaluate archer performance. An approach that provides more affordable yet accurate systems to the masses and relatively easy system deployment procedure need to be proposed. Hence, this project will address to fulfil the needs. Three area of the archer parameter were included for data monitoring sensors. Attention level can be measured using EEG sensor, centre of mass linked to the postural stability can be measured by foot pressure sensor, and the bow vibrations in three axis will be relayed by the vibrations sensors placed directly on the bow using wireless sensors. Arduino based microcontroller used to relay all the data back to the interfacing systems. Interface systems will be using Python language and C++ framework for user interface and hardware interfacing systems. All sensor data can be observed in real time using the in-house applications, and each sessions can be saved to common files so that coach and the team can have a further discussion and comparisons.

Keywords: archery, graphical user interface, microcontroller, wireless sensor, monitoring system

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Authors: Muhammad N. Khan, Syed O. Gillani, Mohsin Jamil, Tarbia Iftikhar

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With the increasing demand of bandwidth and data rate, there is a dire need to implement antenna systems in mobile phones which are able to fulfill user requirements. A monopole antenna system with multi-antennas configurations is proposed considering the feasibility and user demand. The multi-antenna structure is referred to as multi-input multi-output (MIMO) antenna system. The multi-antenna system comprises of 4 antennas operating below 6 GHz frequency bands for 4G/LTE and 4 antenna for 5G applications at 28 GHz and the dimension of board is 120 × 70 × 0.8mm3. The suggested designs is feasible with a structure of low-profile planar-antenna and is adaptable to smart cell phones and handheld devices. To the best of our knowledge, this is the first design compared to the literature by having integrated antenna system for two standards, i.e., 4G and 5G. All MIMO antenna systems are simulated on commercially available software, which is high frequency structures simulator (HFSS).

Keywords: high frequency structures simulator (HFSS), mutli-input multi-output (MIMO), monopole antenna, slot antenna

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Authors: Somaye Zare

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The critical beam radius is a significant factor that predicts the behavior of the laser beam in the plasma, so if the laser beam radius is adequately greater in comparison to it, the beam will experience stable focusing on the plasma; otherwise, the beam will diverge after entering into the plasma. In this work, considering the paraxial approximation and moment theories, the localization of a relativistic laser beam in thermal quantum plasma is investigated. Using the dielectric function obtained in the quantum hydrodynamic model, the mathematical equation for the laser beam width parameter is attained and solved numerically by the fourth-order Runge-Kutta method. The results demonstrate that the stouter focusing effect is occurred in the moment theory compared to the paraxial approximation. Besides, similar to the two theories, with increasing Fermi temperature, plasma density, and laser intensity, the oscillation rate of the beam width parameter growths and focusing length reduces which means improving the focusing effect. Furthermore, it is understood that behaviors of the critical laser radius are different in the two theories, in the paraxial approximation, the critical radius after a minimum value is enhanced with increasing laser intensity, but in the moment theory, with increasing laser intensity, the critical radius decreases until it becomes independent of the laser intensity.

Keywords: laser localization, quantum plasma, paraxial approximation, moment theory, quantum hydrodynamic model

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Authors: Peter J. Robinson, W. J. Wouter Botzen

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Individuals often over-weight low probabilities and under-weight moderate to high probabilities, however very low probabilities are either significantly over-weighted or neglected. Little is known about factors affecting probability weighting in Prospect Theory related to emotions specific to risk (anticipatory and anticipated emotions), the threshold of concern, as well as personality traits like locus of control. This study provides these insights by examining factors that influence probability weighting in the context of flood insurance demand in an economic experiment. In particular, we focus on determinants of flood probability neglect to provide recommendations for improved risk management. In addition, results obtained using real incentives and no performance-based payments are compared in the experiment with high experimental outcomes. Based on data collected from 1’041 Dutch homeowners, we find that: flood probability neglect is related to anticipated regret, worry and the threshold of concern. Moreover, locus of control and regret affect probabilistic pessimism. Nevertheless, we do not observe strong evidence that incentives influence flood probability neglect nor probability weighting. The results show that low, moderate and high flood probabilities are under-weighted, which is related to framing in the flooding context and the degree of realism respondents attach to high probability property damages. We suggest several policies to overcome psychological factors related to under-weighting flood probabilities to improve flood preparations. These include policies that promote better risk communication to enhance insurance decisions for individuals with a high threshold of concern, and education and information provision to change the behaviour of internal locus of control types as well as people who see insurance as an investment. Multi-year flood insurance may also prevent short-sighted behaviour of people who have a tendency to regret paying for insurance. Moreover, bundling low-probability/high-impact risks with more immediate risks may achieve an overall covered risk which is less likely to be judged as falling below thresholds of concern. These measures could aid the development of a flood insurance market in the Netherlands for which we find to be demand.

Keywords: flood insurance demand, prospect theory, risk perceptions, risk preferences

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Authors: Bashiru Abdullahi, Isah Bala Yabo, Ibrahim Yakubu Seini

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In this paper, the steady/transient MHD heat transfer within radiative porous channel due to convective boundary conditions is considered. The solution of the steady-state and that of the transient version were conveyed by Perturbation and Finite difference methods respectively. The heat transfer mechanism of the present work ascertains the influence of Biot number〖(B〗_i1), magnetizing parameter (M), radiation parameter(R), temperature difference, suction/injection(S) Grashof number (Gr) and time (t) on velocity (u), temperature(θ), skin friction(τ), and Nusselt number (Nu). The results established were discussed with the help of a line graph. It was found that the velocity, temperature, and skin friction decay with increasing suction/injection and magnetizing parameters while the Nusselt number upsurges with suction/injection at y = 0 and falls at y =1. The steady-state solution was in perfect agreement with the transient version for a significant value of time t. It is interesting to report that the Biot number has a cogent influence consequently, as its values upsurge the result of the present work slant the extended literature.

Keywords: heat transfer, thermal radiation, porous channel, MHD, transient, convective boundary condition

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Authors: Francis Okodede, Edafe Lucky Okotie

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Conventional energy sources based on oil, coal, and natural gas has posed a trait to environment and to human health. Green energy stands as an alternative because it has proved to be eco-friendly. The prospective of renewable energy sources are quite vast as they can, in principle, meet many times the world’s energy demand. Renewable energy sources, such as wind and solar, can provide sustainable energy services based on the use of routinely available indigenous resources. New renewable energy sources (solar energy, wind energy, and modern bio-energy) are currently contributing immensely to global energy demand. A number of studies have shown the potential and contribution of renewable energy to global energy supplies, indicating that in the second half of the 21st century, it is going to be a major source and driver in the telecommunication sector. Green energy contribution might reach as much as 50 percent of global energy demands if the right policies are in place. This work suggests viable non-conventional means of energy supply to power a cellular base station.

Keywords: base station, energy storage, green energy, rotor efficiency, solar energy, wind energy

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Authors: Anjian Chen, Joseph C. Chen

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This paper studies a case where the targeted surface roughness of fused deposition modeling (FDM) additive manufacturing process is improved. The process is designing to reduce or eliminate the defects and improve the process capability index Cp and Cpk for an FDM additive manufacturing process. The baseline Cp is 0.274 and Cpk is 0.654. This research utilizes the Taguchi methodology, to eliminate defects and improve the process. The Taguchi method is used to optimize the additive manufacturing process and printing parameters that affect the targeted surface roughness of FDM additive manufacturing. The Taguchi L9 orthogonal array is used to organize the parameters' (four controllable parameters and one non-controllable parameter) effectiveness on the FDM additive manufacturing process. The four controllable parameters are nozzle temperature [°C], layer thickness [mm], nozzle speed [mm/s], and extruder speed [%]. The non-controllable parameter is the environmental temperature [°C]. After the optimization of the parameters, a confirmation print was printed to prove that the results can reduce the amount of defects and improve the process capability index Cp from 0.274 to 1.605 and the Cpk from 0.654 to 1.233 for the FDM additive manufacturing process. The final results confirmed that the Taguchi methodology is sufficient to improve the surface roughness of FDM additive manufacturing process.

Keywords: additive manufacturing, fused deposition modeling, surface roughness, six-sigma, Taguchi method, 3D printing

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Authors: Olga Biedova, Victoria Steblovskaya, Kai Wallbaum

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In the current capital market environment, investors constantly face the challenge of finding a successful and stable investment mechanism. Highly volatile equity markets and extremely low bond returns bring about the demand for sophisticated yet reliable risk management strategies. Investors are looking for risk management solutions to efficiently protect their investments. This study compares a classic Constant Proportion Portfolio Insurance (CPPI) strategy to a Volatility Target portfolio insurance (VTPI). VTPI is an extension of the well-known Option Based Portfolio Insurance (OBPI) to the case where an embedded option is linked not to a pure risky asset such as e.g., S&P 500, but to a Volatility Target (VolTarget) portfolio. VolTarget strategy is a recently emerged rule-based dynamic asset allocation mechanism where the portfolio’s volatility is kept under control. As a result, a typical VTPI strategy allows higher participation rates in the market due to reduced embedded option prices. In addition, controlled volatility levels eliminate the volatility spread in option pricing, one of the frequently cited reasons for OBPI strategy fall behind CPPI. The strategies are compared within the framework of the stochastic dominance theory based on numerical simulations, rather than on the restrictive assumption of the Black-Scholes type dynamics of the underlying asset. An extended comparative quantitative analysis of performances of the above investment strategies in various market scenarios and within a range of input parameter values is presented.

Keywords: CPPI, portfolio insurance, stochastic dominance, volatility target

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Authors: Arpan Dwivedi, Yogesh Pahariya

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In this paper, optimal design of hybrid standalone power supply system (SAPS) is done for off grid applications in remote areas where transmission of power is difficult. The hybrid SAPS system uses two primary energy sources, wind and solar, and in addition to these diesel generator is also connected to meet the load demand in case of failure of wind and solar system. This paper presents mathematical modeling of 1.4 MW hybrid SAPS system for rural electrification. This paper firstly focuses on mathematical modeling of PV module connected in a string, secondly focuses on modeling of permanent magnet wind turbine generator (PMWTG). The hybrid controller is also designed for selection of power from the source available as per the load demand. The power output of hybrid SAPS system is analyzed for meeting load demands at urban as well as for rural areas.

Keywords: SAPS, DG, PMWTG, rural area, off-grid, PV module

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Authors: Gurinder Singh Brar, Sarbjeet Singh, Harry Garg

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Wire Electric Discharge Machining (WEDM) is thermal machining process capable of machining very hard electrically conductive material irrespective of their hardness. WEDM is being widely used to machine micro-scale parts with the high dimensional accuracy and surface finish. The objective of this paper is to optimize the process parameters of wire EDM to fabricate the microchannels and to calculate the surface finish and material removal rate of microchannels fabricated using wire EDM. The material used is aluminum 6061 alloy. The experiments were performed using CNC wire cut electric discharge machine. The effect of various parameters of WEDM like pulse on time (TON) with the levels (100, 150, 200), pulse off time (TOFF) with the levels (25, 35, 45) and current (IP) with the levels (105, 110, 115) were investigated to study the effect on output parameter i.e. Surface Roughness and Material Removal Rate (MRR). Each experiment was conducted under different conditions of a pulse on time, pulse off time and peak current. For material removal rate, TON and Ip were the most significant process parameter. MRR increases with the increase in TON and Ip and decreases with the increase in TOFF. For surface roughness, TON and Ip have the maximum effect and TOFF was found out to be less effective.

Keywords: microchannels, Wire Electric Discharge Machining (WEDM), Metal Removal Rate (MRR), surface finish

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Authors: Jianning Tang, Trevor Hocksun Kwan, Xiaofeng Wu

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With the increasing demand for space use in multiple sectors (navigation, telecommunication, imagery, etc.), the deployment and maintenance demand of satellites are growing. Considering the high launching cost and the restrictions on weight and size of the payload when using launch vehicle, the technique of on-orbit manufacturing has obtained more attention because of its significant potential to support future space missions. 3D printing is the most promising manufacturing technology that could be applied in space. However, due to the lack of autonomous quality assessment, the operation of conventional 3D printers still relies on human presence to supervise the printing process. This paper is proposed to develop an automatic 3D reconstruction system aiming at detecting failures on the 3D printed objects through application of point cloud technology. Based on the data obtained from the point cloud, the 3D printer could locate the failure and repair the failure. The system will increase automation and provide 3D printing with more feasibilities for space use without human interference.

Keywords: 3D printing, quality assessment, point cloud, on-orbit manufacturing

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Authors: Shativel S., Chandana B. R., Kavya B. C., Obli B. Vikram, Suganthi J., Nagendra Rao G.

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Satellite communication plays a pivotal role in modern global communication networks, serving as a vital link between terrestrial infrastructure and remote regions. The demand for reliable satellite reception systems, especially in UHF (Ultra High Frequency) and VHF (Very High Frequency) bands, has grown significantly over the years. This research paper presents the design and optimization of a high-gain, dual-band crossed Yagi-Uda antenna in CST Studio Suite, specifically tailored for satellite reception. The proposed antenna system incorporates a circularly polarized (Right-Hand Circular Polarization - RHCP) design to reduce Faraday loss. Our aim was to use fewer elements and achieve gain, so the antenna is constructed using 6x2 elements arranged in cross dipole and supported with a boom. We have achieved 10.67dBi at 146MHz and 9.28dBi at 437.5MHz.The process includes parameter optimization and fine-tuning of the Yagi-Uda array’s elements, such as the length and spacing of directors and reflectors, to achieve high gain and desirable radiation patterns. Furthermore, the optimization process considers the requirements for UHF and VHF frequency bands, ensuring broad frequency coverage for satellite reception. The results of this research are anticipated to significantly contribute to the advancement of satellite reception systems, enhancing their capabilities to reliably connect remote and underserved areas to the global communication network. Through innovative antenna design and simulation techniques, this study seeks to provide a foundation for the development of next-generation satellite communication infrastructure.

Keywords: Yagi-Uda antenna, RHCP, gain, UHF antenna, VHF antenna, CST, radiation pattern.

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Authors: U. B. Zubair, A. Kiyani

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Introduction: Depressive illness predispose individuals to a lot of physical and mental health issues. Anxiety and substance use disorders have been studied widely as comorbidity. Biological symptoms also now considered part of the depressive spectrum. Cognitive abilities also decline or get affected and need to be looked into in detail in depressed patients. Objective: To determine the prevalence of cognitive decline among patients with major depressive illness and analyze the associated socio-demographic factors. Methods: 190 patients of major depressive illness were included in our study to determine the presence of cognitive decline among them. Depression was diagnosed by a consultant psychiatrist by using the ICD-10 criteria for major depressive disorder. British Columbia Cognitive Complaints Inventory (BC-CCI) was the psychometric tool used to determine the cognitive decline. Sociodemographic profile was recorded and the relationship of various factors with cognitive decline was also ascertained. Findings: 70% of the patients suffering from depression included in this study showed the presence of some degree of cognitive decline, while 30% did not show any evidence of cognitive decline when screened through BCCCI. Statistical testing revealed that the female gender was the only socio-demographic parameter linked significantly with the presence of cognitive decline. Conclusion: Decline in cognitive abilities was found in a significant number of patients suffering from major depression in our sample population. Screening for this parameter f mental function should be done in depression clinics to pick it early.

Keywords: depression, cognitive decline, prevalence, socio-demographic factors

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: M. Ghanbari, S. Hossainpour, G. Rezazadeh

Abstract:

In this paper, longitudinal vibration of a micro-beam in micro-scale fluid media has been investigated. The proposed mathematical model for this study is made up of a micro-beam and a micro-plate at its free end. An AC voltage is applied to the pair of piezoelectric layers on the upper and lower surfaces of the micro-beam in order to actuate it longitudinally. The whole structure is bounded between two fixed plates on its upper and lower surfaces. The micro-gap between the structure and the fixed plates is filled with fluid. Fluids behave differently in micro-scale than macro, so the fluid field in the gap has been modeled based on micro-polar theory. The coupled governing equations of motion of the micro-beam and the micro-scale fluid field have been derived. Due to having non-homogenous boundary conditions, derived equations have been transformed to an enhanced form with homogenous boundary conditions. Using Galerkin-based reduced order model, the enhanced equations have been discretized over the beam and fluid domains and solve simultaneously in order to obtain force response of the micro-beam. Effects of micro-polar parameters of the fluid as characteristic length scale, coupling parameter and surface parameter on the response of the micro-beam have been studied.

Keywords: micro-polar theory, Galerkin method, MEMS, micro-fluid

Procedia PDF Downloads 176

Authors: Murtadha Kareem, Oliver Faust

Abstract:

Wearable biosensor systems can be designed and developed for health monitoring. There is much interest in both scientific and industrial communities established since 2007. Fundamentally, the cost of healthcare has increased dramatically and the world population is aging. That creates the need to harvest technological improvements with small bio-sensing devices, wireless-communication, microelectronics and smart textiles, that leads to non-stop developments of wearable sensor based systems. There has been a significant demand to monitor patient's health status while the patient leaves the hospital in his/her personal environment. To address this need, there are numerous system prototypes which has been launched in the medical market recently, the aim of that is to provide real time information feedback about patient's health status, either to the patient himself/herself or direct to the supervising medical centre station, while being capable to give a notification for the patient in case of possible imminent health threatening conditions. Furthermore, wearable health monitoring systems comprise new techniques to address the problem of managing and monitoring chronic heart diseases for elderly people. Wearable sensor systems for health monitoring include various types of miniature sensors, either wearable or implantable. To be specific, our proposed system able to measure essential physiological parameter, such as heart rate signal which could be transmitted through Bluetooth to the cloud server in order to store, process, analysis and visualise the data acquisition. The acquired measurements are connected through internet of things to a central node, for instance an android smart phone or tablet used for visualising the collected information on application or transmit it to a medical centre.

Keywords: Wearable sensor, Heart rate, Internet of things, Chronic heart disease

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Authors: Rubén Bãnos, José Arcos, Oscar Bautista, Federico Méndez

Abstract:

The Oscillatory electroosmotic flow (OEOF) in power law fluids through a microchannel is studied numerically. A time-dependent external electric field (AC) is suddenly imposed at the ends of the microchannel which induces the fluid motion. The continuity and momentum equations in the x and y direction for the flow field were simplified in the limit of the lubrication approximation theory (LAT), and then solved using a numerical scheme. The solution of the electric potential is based on the Debye-H¨uckel approximation which suggest that the surface potential is small,say, smaller than 0.025V and for a symmetric (z : z) electrolyte. Our results suggest that the velocity profiles across the channel-width are controlled by the following dimensionless parameters: the angular Reynolds number, Reω, the electrokinetic parameter, ¯κ, defined as the ratio of the characteristic length scale to the Debye length, the parameter λ which represents the ratio of the Helmholtz-Smoluchowski velocity to the characteristic length scale and the flow behavior index, n. Also, the results reveal that the velocity profiles become more and more non-uniform across the channel-width as the Reω and ¯κ are increased, so oscillatory OEOF can be really useful in micro-fluidic devices such as micro-mixers.

Keywords: low zeta potentials, non-newtonian, oscillatory electroosmotic flow, power-law model

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Authors: Alexandra Monteiro, K. Bousson, Fernando J. O. Moreira, Ricardo Reis

Abstract:

Fixed-wing flying vehicles are usually controlled by means of control surfaces such as elevators, ailerons, and rudders. The failure of these systems may lead to severe or even fatal crashes. These failures resulted in increased popularity for research activities on propulsion control in the last decades. The present work deals with a hybrid control architecture in which the propulsion-controlled vehicle maintains its traditional control surfaces, addressing the issue of robust lateral-directional dynamics control. The challenges stem from the parameter uncertainties in the stability and control derivatives and some unknown terms in the flight dynamics model. Two approaches are implemented and tested: linear quadratic regulation with robustness characteristics and H∞ control. The problem is centered on roll-yaw controller design with full state-feedback, which is able to deal with a standalone propulsion control mode as well as a hybrid mode combining both propulsion control and conventional control surface concepts while maintaining the original flight maneuverability characteristics. The results for both controllers emphasized very good control performances; however, the H∞ controller showed higher stabilization rates and robustness albeit with a slightly higher control magnitude than using the linear quadratic regulator.

Keywords: robust propulsion control, h-infinity control, lateral-directional flight dynamics, parameter uncertainties

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Authors: Manoj K. Sharma, Neha Grover

Abstract:

Dynamical cluster decay model (DCM) is applied to study the decay mechanism of 118Xe* nucleus in reference to recent data on 28Si + 90Zr → 118Xe* reaction, as an extension of our previous work on the dynamics of 112Xe* nucleus. It is relevant to mention here that DCM is based on collective clusterization approach, where emission probability of different decay paths such as evaporation residue (ER), intermediate mass fragments (IMF) and fission etc. is worked out on parallel scale. Calculations have been done over a wide range of center of mass energies with Ec.m. = 65 - 92 MeV. The evaporation residue (ER) cross-sections of 118Xe* compound nucleus are fitted in reference to available data, using spherical and quadrupole (β2) deformed choice of decaying fragments within the optimum orientations approach. It may be noted that our calculated cross-sections find decent agreement with experimental data and hence provide an opportunity to analyze the exclusive role of deformations in view of fragmentation behavior of 118Xe* nucleus. The possible contribution of IMF fragments is worked out and an extensive effort is being made to analyze the role of excitation energy, angular momentum, diffuseness parameter and level density parameter to have better understanding of the decay patterns governed in the dynamics of 28Si + 90Zr → 118Xe* reaction.

Keywords: cross-sections, deformations, fragmentation, angular momentum

Procedia PDF Downloads 312