Search results for: energy models

Authors: Charmaine Lamiel, Van Hoa Nguyen, Marjorie Baynosa, Jae-Jin Shim

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The depletion of non-renewable sources had led to the continuous development of various energy storage systems in order to cope with the world’s demand in energy. Supercapacitors have attracted considerable attention because they can store more energy than conventional capacitors and have higher power density than batteries. The combination of carbon-based material and metal chalcogenides are now being considered in response to the search for active electrode materials exhibiting high electrochemical performance. In this study, a hierarchical mesoporous carbon sphere@nickel cobalt sulfide (CS@Ni-Co-S) core-shell was synthesized using a simple hydrothermal method. The CS@Ni-Co-S core-shell microstructures exhibited a high capacitance of 724.4 F g−1 at 2 A g−1 in a 6 M KOH electrolyte. Good specific retention of 86.1% and high Coulombic efficiency of 97.9% was obtained after 2000 charge-discharge cycles. The electrode exhibited a high energy density of 58.0 Wh kg−1 (1440 W kg−1) and high power density of 7200 W kg−1 (34.2 Wh kg−1). The reaction involved green synthesis without further sulfurization or post-heat treatment. Through this study, a cost-effective and facile synthesis of CS@Ni-Co-S as an active electrode showed favorable electrochemical performance.

Keywords: carbon sphere, electrochemical, hydrothermal, nickel cobalt sulfide, supercapacitor

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Authors: Arian Hosseini, Mahmudul Hasan

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To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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Authors: Nessreen Y. Ibrahim

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Designing the future according to realistic analytical study for the futuristic market needs can be a milestone strategy to make a huge improvement in developing countries economics. In developing countries, access to high technology and latest science approaches is very limited. The financial problems in low and medium income countries have negative effects on the kind and quality of imported new technologies and application for their markets. Thus, there is a strong need for shifting paradigm thinking in the design process to improve and evolve their development strategy. This paper discusses future possibilities in developing countries, and how they can design their own future according to specific future models FDM (Future Design Models), which established to solve certain economical problems, as well as political and cultural conflicts. FDM is strategic thinking framework provides an improvement in both content and process. The content includes; beliefs, values, mission, purpose, conceptual frameworks, research, and practice, while the process includes; design methodology, design systems, and design managements tools. In this paper the main objective was building an innovative economic model to design a chosen possible futuristic scenario; by understanding the market future needs, analyze real world setting, solve the model questions by future driven design, and finally interpret the results, to discuss to what extent the results can be transferred to the real world. The paper discusses Egypt as a potential case study. Since, Egypt has highly complex economical problems, extra-dynamic political factors, and very rich cultural aspects; we considered Egypt is a very challenging example for applying FDM. The paper results recommended using FDM numerical modeling as a starting point to design the future.

Keywords: developing countries, economic models, future design, possible futures

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Authors: Retno Ambarwati Sigit Lestari

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Microalga is one of the organisms that can be considered ideal and potential for raw material of bioenergy production, because the content of lipids in microalga is relatively high. Microalga is an aquatic organism that produces complex organic compounds from inorganic molecules using carbon dioxide as a carbon source, and sunlight for energy supply. Microalga-CO₂ fixation has potential advantages over other carbon captures and storage approaches, such as wide distribution, high photosynthetic rate, good environmental adaptability, and ease of operation. The rates of growth and CO₂ capture of microalga are influenced by CO₂ concentration and light intensity. This study quantitatively investigates the effects of CO₂ concentration on the rates of growth and CO₂ capture of a type of microalga, cultivated in bioreactors. The works include laboratory experiments as well as mathematical modelling. The mathematical models were solved numerically and the accuracy of the model was tested by the experimental data. It turned out that the mathematical model proposed can well quantitatively describe the growth and CO₂ capture of microalga, in which the effects of CO₂ concentration can be observed.

Keywords: Microalga, CO2 concentration, photobioreactor, mathematical model

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Authors: Sabrina N. Rabelo, Tiago de F. Paulino, Willian M. Duarte, Samer Sawalha, Luiz Machado

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Energy use is one of the main indicators for the economic and social development of a country, reflecting directly in the quality of life of the population. The expansion of energy use together with the depletion of fossil resources and the poor efficiency of energy systems have led many countries in recent years to invest in renewable energy sources. In this context, solar-assisted heat pump has become very important in energy industry, since it can transfer heat energy from the sun to water or another absorbing source. The direct-expansion solar assisted heat pump (DX-SAHP) water heater system operates by receiving solar energy incident in a solar collector, which serves as an evaporator in a refrigeration cycle, and the energy reject by the condenser is used for water heating. In this paper, a DX-SAHP using carbon dioxide as refrigerant (R744) was assembled, and the influence of the variation of the water mass flow rate in the system was analyzed. The parameters such as high pressure, water outlet temperature, gas cooler outlet temperature, evaporator temperature, and the coefficient of performance were studied. The mainly components used to assemble the heat pump were a reciprocating compressor, a gas cooler which is a countercurrent concentric tube heat exchanger, a needle-valve, and an evaporator that is a copper bare flat plate solar collector designed to capture direct and diffuse radiation. Routines were developed in the LabVIEW and CoolProp through MATLAB software’s, respectively, to collect data and calculate the thermodynamics properties. The range of coefficient of performance measured was from 3.2 to 5.34. It was noticed that, with the higher water mass flow rate, the water outlet temperature decreased, and consequently, the coefficient of performance of the system increases since the heat transfer in the gas cooler is higher. In addition, the high pressure of the system and the CO₂ gas cooler outlet temperature decreased. The heat pump using carbon dioxide as a refrigerant, especially operating with solar radiation has been proven to be a renewable source in an efficient system for heating residential water compared to electrical heaters reaching temperatures between 40 °C and 80 °C.

Keywords: water mass flow rate, R-744, heat pump, solar evaporator, water heater

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Authors: Yeliz Ekinci, Melis Koyuncu

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Successful planning of solid waste management systems requires successful prediction of the amount of solid waste generated in an area. Waste management planning can protect the environment and human health, hence it is tremendously important for countries. The lack of information in waste generation can cause many environmental and health problems. Turkey is a country that plans to join European Union, hence, solid waste management is one of the most significant criteria that should be handled in order to be a part of this community. Solid waste management system requires a good forecast of solid waste generation. Thus, this study aims to forecast solid waste generation in Turkey. Artificial Neural Network and Linear Regression models will be used for this aim. Many models will be run and the best one will be selected based on some predetermined performance measures.

Keywords: forecast, solid waste generation, solid waste management, Turkey

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Authors: Shahroz Khan, Erkan Gunpinar, Kemal Mart

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Recently parametric design techniques became a vital concept in the field of Computer Aided Design (CAD), which helps to provide sophisticated platform to the designer in order to automate the design process in efficient time. In these techniques, design process starts by parameterizing the important features of design models (typically the key dimensions), with the implementation of design constraints. The design constraints help to retain the overall shape of the model while modifying its parameters. However, the process of initializing an appropriate number of design parameters and constraints is the crucial part of parametric design techniques, especially for complex surface models such as yacht hull. This paper introduces a method to create complex surface models in favor of parametric design techniques, a method to define the right number of parameters and respective design constraints, and a system to implement design parameters in contract to design constraints schema. For this, in our proposed approach the design process starts by dividing the yacht hull into three sections. Each section consists of different shape lines, which form the overall shape of yacht hull. The shape lines are created using Cubic Bezier Curves, which allow larger design flexibility. Design parameters and constraints are defined on the shape lines in 3D design space to facilitate the designers for better and individual handling of parameters. Afterwards, shape modifiers are developed, which allow the modification of each parameter while satisfying the respective set of criteria and design constraints. Such as, geometric continuities should be maintained between the shape lines of the three sections, fairness of the hull surfaces should be preserved after modification and while design modification, effect of a single parameter should be negligible on other parameters. The constraints are defined individually on shape lines of each section and mutually between the shape lines of two connecting sections. In order to validate and visualize design results of our shape modifiers, a real time graphic interface is created.

Keywords: design parameter, design constraints, shape modifies, yacht hull

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Authors: Pratiksha Dubey, Praveen Singh, Shantanu Sen Gupta, Anand K. Bachhawat

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5-oxoproline (pyroglutamic acid) is a cyclic lactam of glutamic acid. In the cell, it can be produced by several different pathways and is metabolized into glutamate with the help of the 5-oxoprolinase enzyme (OPLAH or OXP1). The inhibition of 5-oxoprolinase enzyme in mammals was found to result in heart failure and is thought to be a consequence of oxidative stress [1]. To analyze the consequences of 5-oxoproline accumulation more clearly, we are generating models for 5-oxoproline accumulation in yeast. The 5-oxoproline accumulation model in yeast is being developed by two different strategies. The first one is by overexpression of the mouse  -glutamylcyclotransferase enzyme. It degrades -glu-met dipeptide into 5-oxoproline and methionine taken by the cell from the medium. The second strategy is by providing high concentration of 5-oxoproline externally to the yeast cells. The intracellular 5-oxoproline levels in both models are being evaluated. In addition, the metabolic and cellular consequences are being investigated.

Keywords: 5-oxoproline, pyroglutamic acid, yeast, genetics

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Authors: S. F. Wong, S. S. Dol

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Automotive designers have been trying to use dimples to reduce drag in vehicles. In this work, a car model has been applied with dimple surface with a parameter called dimple ratio DR, the ratio between the depths of the half dimple over the print diameter of the dimple, has been introduced and numerically simulated via k-ε turbulence model to study the aerodynamics performance with the increasing depth of the dimples The Ahmed body car model with 25 degree slant angle is simulated with the DR of 0.05, 0.2, 0.3 0.4 and 0.5 at Reynolds number of 176387 based on the frontal area of the car model. The geometry of dimple changes the kinematics and dynamics of flow. Complex interaction between the turbulent fluctuating flow and the mean flow escalates the turbulence quantities. The maximum level of turbulent kinetic energy occurs at DR = 0.4. It can be concluded that the dimples have generated extra turbulence energy at the surface and as a result, the application of dimples manages to reduce the drag coefficient of the car model compared to the model with smooth surface.

Keywords: aerodynamics, boundary layer, dimple, drag, kinetic energy, turbulence

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Authors: Hosein Falahaty, Hitoshi Gotoh, Abbas Khayyer

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Performance of a Hamiltonian based particle method in simulation of nonlinear structural dynamics is subjected to investigation in terms of stability and accuracy. The governing equation of motion is derived based on Hamilton's principle of least action, while the deformation gradient is obtained according to Weighted Least Square method. The hyper-elasticity models of Saint Venant-Kirchhoff and a compressible version similar to Mooney- Rivlin are engaged for the calculation of second Piola-Kirchhoff stress tensor, respectively. Stability along with accuracy of numerical model is verified by reproducing critical stress fields in static and dynamic responses. As the results, although performance of Hamiltonian based model is evaluated as being acceptable in dealing with intense extensional stress fields, however kinds of instabilities reveal in the case of violent collision which can be most likely attributed to zero energy singular modes.

Keywords: Hamilton's principle of least action, particle-based method, hyper-elasticity, analysis of stability

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Authors: I. Hua Chu, Hsiang-Chi Yu, Hsuan Su

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Purpose: To examine the associations between self-determined motivation and physical activity in patients with coronary heart disease (CHD) in a longitudinal study. Methods: Patients with CHD were recruited for this study. Their motivations for exercise were measured by the Behavioral Regulation in Exercise Questionnaire-2 (BREQ-2). Physical activity was assessed using the 7-day physical activity recall questionnaire. Duration and energy expenditure of moderate to vigorous physical activity (MVPA) were used in data analysis. All outcome measures were assessed at baseline and 12 months follow up. Data were analyzed using Pearson correlation analysis and regression analysis. Results: The results of the 45 participants (mean age 60.24 yr; 90.2% male) revealed that there were significant negative correlations between amotivation at baseline and duration (r=-.295, p=.049) and energy expenditure (r=-.300, p=.045) of MVPA at 12 months. In contrast, there were significant positive correlations between calculated relative autonomy index (RAI) at baseline and duration (r=.377, p=.011) and energy expenditure (r=.382, p=.010) of MVPA at 12 months. There was no significant correlation between other subscales of the BREQ-2 and duration or energy expenditure of MVPA. Regression analyses revealed that RAI was a significant predictor of duration (p=.011) and energy expenditure (p=.010) of MVPA at 12 months follow-up. Conclusions: These results suggest that the relative degree of self-determined motivation could predict long-term MVPA behaviors in CHD patients. Physical activity interventions are recommended to target enhancing one’s identified and intrinsic motivation to increase the likelihood of physical activity participation in this population.

Keywords: self-determined motivation, physical activity, coronary heart disease, relative autonomy index (RAI)

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Authors: Farhana Arzu, Roslan Hashim

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Renewable energy is the only alternative sources of energy to meet the current energy demand, healthy environment and future growth which is considered essential for essential sustainable development. Marine renewable energy is one of the major means to meet this demand. Turbines (both horizontal and vertical) play a vital role for extraction of tidal energy. The influence of swept area on the performance improvement of tidal turbine is a vital factor to study for the reduction of relatively high power generation cost in marine industry. This study concentrates on performance investigation of variable length blade tidal turbine concept that has already been proved as an efficient way to improve energy extraction in the wind industry. The concept of variable blade length utilizes the idea of increasing swept area through the turbine blade extension when the tidal stream velocity falls below the rated condition to maximize energy capture while blade retracts above rated condition. A three bladed horizontal axis variable length blade horizontal axis tidal turbine was modelled by modifying a standard fixed length blade turbine. Classical blade element momentum theory based numerical investigation has been carried out using QBlade software to predict performance. The results obtained from QBlade were compared with the available published results and found very good agreement. Three major performance parameters (i.e., thrust, moment, and power coefficients) and power output for different blade extensions were studied and compared with a standard fixed bladed baseline turbine at certain operational conditions. Substantial improvement in performance coefficient is observed with the increase in swept area of the turbine rotor. Power generation is found to increase in great extent when operating at below rated tidal stream velocity reducing the associated cost per unit electric power generation.

Keywords: variable length blade, performance, tidal turbine, power generation

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Authors: Vinayambika S. Bhat, S. Shanmuga Priya, I. Thirunavukkarasu, Shreeranga Bhat

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An attempt has been made to design a decoupling controller for systems with more inputs more outputs with dead time in it. The de-coupler is designed for the chemical process industry 3×3 plant transfer function with dead time. The Quantitative Feedback Theory (QFT) based controller has also been designed here for the 2×2 distillation column transfer function. The developed control techniques were simulated using the MATLAB/Simulink. Also, the stability of the process was analyzed, together with the presence of various perturbations in it. Time domain specifications like setting time along with overshoot and oscillations were analyzed to prove the efficiency of the de-coupler method. The load disturbance rejection was tested along with its performance. The QFT control technique was synthesized based on the stability and performance specifications in the presence of uncertainty in time constant of the plant transfer function through sequential loop shaping technique. Further, the energy efficiency of the distillation column was improved by proper tuning of the controller. A distillation column consumes 3% of the total energy consumption of the world. A suitable control technique is very important from an economic point of view. The real time implementation of the process is under process in our laboratory.

Keywords: distillation, energy, MIMO process, time delay, robust stability

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Authors: M. Vezir Kahraman, Emre Basturk

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Energy storage technology offers new ways to meet the demand to obtain efficient and reliable energy storage materials. Thermal energy storage systems provide the potential to acquire energy savings, which in return decrease the environmental impact related to energy usage. For this purpose, phase change materials (PCMs) that work as 'latent heat storage units' which can store or release large amounts of energy are preferred. Phase change materials (PCMs) are being utilized to absorb, collect and discharge thermal energy during the cycle of melting and freezing, converting from one phase to another. Phase Change Materials (PCMs) can generally be arranged into three classes: organic materials, salt hydrates and eutectics. Many kinds of organic and inorganic PCMs and their blends have been examined as latent heat storage materials. PCMs have found different application areas such as solar energy storage and transfer, HVAC (Heating, Ventilating and Air Conditioning) systems, thermal comfort in vehicles, passive cooling, temperature controlled distributions, industrial waste heat recovery, under floor heating systems and modified fabrics in textiles. Ultraviolet (UV)-curing technology has many advantages, which made it applicable in many different fields. Low energy consumption, high speed, room-temperature operation, low processing costs, high chemical stability, and being environmental friendly are some of its main benefits. UV-curing technique has many applications. One of the many advantages of UV-cured PCMs is that they prevent the interior PCMs from leaking. Shape-stabilized PCM is prepared by blending the PCM with a supporting material, usually polymers. In our study, this problem is minimized by coating the fatty alcohols with a photo-cross-linked thiol-ene based polymeric system. Leakage is minimized because photo-cross-linked polymer acts a matrix. The aim of this study is to introduce a novel thiol-ene based shape-stabilized PCM. Photo-crosslinked thiol-ene based polymers containing fatty alcohols were prepared and characterized for the purpose of phase change materials (PCMs). Different types of fatty alcohols were used in order to investigate their properties as shape-stable PCMs. The structure of the PCMs was confirmed by ATR-FTIR techniques. The phase transition behaviors, thermal stability of the prepared photo-crosslinked PCMs were investigated by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). This work was supported by Marmara University, Commission of Scientific Research Project.

Keywords: differential scanning calorimetry (DSC), Polymeric phase change material, thermal energy storage, UV-curing

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Authors: Gagandeep Singh, Navdeep Singh

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Due to limited battery of sensor nodes, so energy efficiency found to be main constraint in WSN. Therefore the main focus of the present work is to find the ways to minimize the energy consumption problem and will results; enhancement in the network stability period and life time. Many researchers have proposed different kind of the protocols to enhance the network lifetime further. This paper has evaluated the issues which have been neglected in the field of the WSNs. WSNs are composed of multiple unattended ultra-small, limited-power sensor nodes. Sensor nodes are deployed randomly in the area of interest. Sensor nodes have limited processing, wireless communication and power resource capabilities Sensor nodes send sensed data to sink or Base Station (BS). I-LEACH gives adaptive clustering mechanism which very efficiently deals with energy conservations. This paper ends up with the shortcomings of various adaptive clustering based WSNs protocols.

Keywords: WSN, I-Leach, MATLAB, sensor

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

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Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

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Authors: Peng Liu, Chyng Wen Tee, Xiaofei Xu

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This paper integrates machine learning forecasting techniques into the multi-period portfolio optimization framework, enabling dynamic asset allocation based on multiple future periods. We explore both theoretical foundations and practical applications, employing diverse machine learning models for return forecasting. This comprehensive guide demonstrates the superiority of multi-period optimization over single-period approaches, particularly in risk mitigation through strategic rebalancing and enhanced market trend forecasting. Our goal is to promote wider adoption of multi-period optimization, providing insights that can significantly enhance the decision-making capabilities of practitioners and researchers alike.

Keywords: multi-period portfolio optimization, look-ahead constrained optimization, machine learning, sequential decision making

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Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

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Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

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In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: deep learning, convolutional neural network, LSTM, housing prediction

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Authors: Rishikesh Dingari, Sai Kiran Dornala

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In this paper, a simple method of achieving maximum power by mechanical energy transmission device (METD) with integration to induction generator is proposed. METD functioning is explained and dynamic response of system to step input is plotted. Induction generator is being operated at self-excited mode with excitation capacitor at stator. Voltage and current are observed when linked to METD.

Keywords: mechanical energy transmitting device(METD), self-excited induction generator, wind turbine, hydraulic actuators

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

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In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: Hussein M. Maghrabie, M. Attalla, Hany. A. Mohamed, M. Salem, E. Specht

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An experimental investigation is carried out on counter-flow Ranque–Hilsch vortex tube (RHVT). The present work is carried out to study the effect of nozzle aspect ratio, tube length and the inlet pressure (P_i) on the coefficient of performance and energy separation of a RHVT. Further, the effect of moist air with different relative humidity (RH) 40, 60, 80 % is also achieved. The air relative humidity is adjusted using air humidification/dehumidification unit. The experimental study accomplished for number of nozzle N=6, with inner diameter D=7.5 mm., and length of the vortex tube (L) 75, 97.5, and 112.5 mm. The results show that the relative humidity has a significant effect on coefficient of performance and energy separation of a RHVT.

Keywords: COP, counter-flow Ranque–Hilsch vortex tube, energy separation, humid air

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Authors: Jerome D. Donovan

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The pandemic has resulted in a dramatic re-consideration of the reliance on international student fees to support university models in Australia. A key resulting initiative for the Australian Federal Government has been shifting the way universities consider their research model, emphasising the importance of commercialising research. This study specifically examines this shift from the perspective of a university spin-off, examining how university support structures and incubation models have assisted in the translation of fundamental research into a high-growth university spin-off. A focused case study approach is adopted in this study, using an auto-ethnographic research method to document the experiences and insights drawn from being a co-founder in a university spin-off in a time where research commercialisation has emerged as a central focus in Australian universities.

Keywords: research commercialisation, spin-offs, university incubation, entrepreneurship

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Authors: L. Vafaei, McDominic Eze

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The performance of thermal energy in homes and buildings is a significant factor in terms of energy efficiency of a building. In a large sense, the performance of thermal energy is dependent on many factors of which the amount of thermal insulation is at one end a considerable factor, as likewise the essence of mass and the wall thickness and also the thermal resistance of wall material. This study is aimed at illustrating the different wall system in Turkish Republic of North Cyprus (TRNC), acknowledge the problem and suggest a solution through comparing the effect of thermal radiation two model rooms- L1 (Ytong wall) and L2 (heat insulated wall using stone wool) set up for experimentation. The model room has four face walls. The study consists of two stage, the first test is to access the effect of solar radiation for south facing wall and the second stage is to test the thermal performance of Ytong and heat insulated wall, the effects of climatic condition during winter. The heat insulated wall contains material hollow brick, stone wool, and gypsum while the Ytong wall contains cement concrete, for the outer surface and the inner surface and Ytong stone. The total heat of the wall was determined, 7T-Type thermocouple was used with a data logger system to record the data, temperature change recorded at an interval of 10 minutes. The result obtained was that Ytong wall save more energy than the heat insulated wall at night while heat insulated wall saves energy during the day when intensity is at maximum.

Keywords: heat insulation, hollow bricks, south facing, Ytong bricks wall

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Authors: Oswaldo Otero, Eduardo A. Orozco, Ana M. Herrera

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In this work, we present results from analytical and numerical studies of the electron acceleration by a TE₀₁₁ cylindrical microwave mode in a static homogeneous magnetic field under electron cyclotron resonance (ECR) condition. The stability of the orbits is analyzed using the particle orbit theory. In order to get a better understanding of the interaction wave-particle, we decompose the azimuthally electric field component as the superposition of right and left-hand circular polarization standing waves. The trajectory, energy and phase-shift of the electron are found through a numerical solution of the relativistic Newton-Lorentz equation in a finite difference method by the Boris method. It is shown that an electron longitudinally injected with an energy of 7 keV in a radial position r=Rc/2, being Rc the cavity radius, is accelerated up to energy of 90 keV by an electric field strength of 14 kV/cm and frequency of 2.45 GHz. This energy can be used to produce X-ray for medical imaging. These results can be used as a starting point for study the acceleration of electrons in a magnetic field changing slowly in time (GYRAC), which has some important applications as the electron cyclotron resonance ion proton accelerator (ECR-IPAC) for cancer therapy and to control plasma bunches with relativistic electrons.

Keywords: Boris method, electron cyclotron resonance, finite difference method, particle orbit theory, X-ray

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Authors: Wang Mimi, Jiang Changjun, Liu Guanjun, Fang Xianwen

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Loop structure often appears in the business process modeling, analyzing the consistency of corresponding workflow net models containing loop structure is a problem, the existing behavior consistency methods cannot analyze effectively the process models with the loop structure. In the paper, by analyzing five kinds of behavior relations of transitions, a three-dimensional figure and two-dimensional behavior relation matrix are proposed. Based on this, analysis method of behavior consistency of business process based on Petri net branching processes is proposed. Finally, an example is given out, which shows the method is effective.

Keywords: workflow net, behavior consistency measures, loop, branching process

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Authors: Tadashi Watanabe, Jinya Katsuyama, Akihiro Mano

Abstract:

The estimation of leak flow rates through narrow cracks in structures is of importance for nuclear reactor safety, since the leak flow could be detected before occurrence of loss-of-coolant accidents. The two-phase critical leak flow rates are calculated using the system analysis code, and two representative non-homogeneous critical flow models, Henry-Fauske model and Ransom-Trapp model, are compared. The pressure decrease and vapor generation in the crack, and the leak flow rates are found to be larger for the Henry-Fauske model. It is shown that the leak flow rates are not affected by the structural temperature, but affected largely by the roughness of crack surface.

Keywords: crack, critical flow, leak, roughness

Procedia PDF Downloads 167

Authors: Chenxi Zhang, Weizhong Qian, Fei Wei

Abstract:

Gas solids multiphase flow is common in many engineering and environmental applications. Turbulence and multiphase flows are two of the most challenging topics in fluid mechanics, and when combined they pose a formidable challenge, even in the dilute dispersed regime. Dimensionless numbers are important in mechanics because their constancy can imply dynamic similarity between systems, despite possible differences in medium or scale. In the fluid mechanics literature, the Strouhal number is usually associated with the dimensionless shedding frequency of a von Karman wake; here we introduce this dimensionless number to investigate bubbling in gas solids fluidization. St=fA/U, which divides stroke frequency (f) and amplitude (A) by forward speed (U). The bubble behavior in a large two-dimensional bubbling fluidized bed (500mm×30mm×6000mm) is investigated. Our result indicates that propulsive efficiency is high and energy dissipation is low over a narrow range of St and usually within the interval 0.2Keywords: bubbles, Strouhal number, two-phase flow, energy dissipation

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Authors: H. Beisch, J. Marx, S. Garlof, R. Shvets, I. I. Grygorchak, A. Kityk, B. Fiedler

Abstract:

Carbon materials, especially three-dimensional carbon foams, show very high potential in the application as electrode material for energy storage systems such as batteries and supercapacitors with unique fast charging and discharging times. Regarding their high specific surface areas (SSA) high specific capacities can be reached. Globugraphite is a newly developed carbon foam with an interconnected globular carbon morphology. Especially, this foam has a statistically distributed hierarchical pore structure resulting from the manufacturing process based on sintered ceramic templates which are synthetized during a final chemical vapor deposition (CVD) process. For morphology characterization scanning electron (SEM) and transmission electron microscopy (TEM) is used. In addition, the SSA is carried out by nitrogen adsorption combined with the Brunauer–Emmett–Teller (BET) theory. Electrochemical measurements in organic and inorganic electrolyte provide high energy densities and power densities resulting from ion absorption by forming an electrochemical double layer. All values are summarized in a Ragone Diagram. Finally, power densities up to 833 W/kg and energy densities up to 48 Wh/kg could be achieved. The corresponding SSA is between 376 m²/g and 859 m²/g. For organic electrolyte a specific capacity of 71 F/g at a density of 20 mg/cm³ was achieved.

Keywords: BET, CVD process, electron microscopy, Ragone diagram

Procedia PDF Downloads 165