Search results for: hybrid simulation

Authors: Shanawaz Patil, Mohamed Haneef, K. S. Narayanaswamy

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In the recent years, aluminum metal matrix composites were most widely used, which are finding wide applications in various field such as automobile, aerospace defense etc., due to their outstanding mechanical properties like low density, light weight, exceptional high levels of strength, stiffness, wear resistance, high temperature resistance, low coefficient of thermal expansion and good formability. In the present work, an effort is made to study the effect of heat treatment on mechanical properties of aluminum 7075 alloy reinforced with constant weight percentage of naturally occurring mineral beryl and varying weight percentage of graphene. The hybrid composites are developed with 0.5 wt. %, 1wt.%, 1.5 wt.% and 2 wt.% of graphene and 6 wt.% of beryl  by stir casting liquid metallurgy route. The cast specimens of unreinforced aluminum alloy and hybrid composite samples were prepared for heat treatment process and subjected to solutionizing treatment (T6) at a temperature of 490±5 ^oC for 8 hours in a muffle furnace followed by quenching in boiling water. The microstructure analysis of as cast and heat treated hybrid composite specimens are examined by scanning electron microscope (SEM). The tensile test and hardness test of unreinforced aluminum alloy and hybrid composites are examined. The wear behavior is examined by pin-on disc apparatus. The results of as cast specimens and heat treated specimens were compared. The heat treated Al7075-Beryl-Graphene hybrid composite had better properties and significantly improved the ultimate tensile strength, hardness and reduced wear loss when compared to aluminum alloy and  as cast hybrid composites.

Keywords: beryl, graphene, heat treatment, mechanical properties

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Authors: Shilpa Murthy, Hazlina Binti Abu Bakar, Juliet Mathew, Chandrashekhar Thummala Hlly Sreerama Reddy, Pathiyil Ravi Shankar

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Simulation is defined as a technique that replaces or expands real experiences with guided experiences that interactively imitate real-world processes or systems. Simulation enables learners to train in a safe and non-threatening environment. For decades, simulation has been considered an integral part of clinical teaching and learning strategy in medical education. The several types of simulation used in medical education and the clinical environment can be applied to several models, including full-body mannequins, task trainers, standardized simulated patients, virtual or computer-generated simulation, or Hybrid simulation that can be used to facilitate learning. Simulation allows healthcare practitioners to acquire skills and experience while taking care of patient safety. The recent COVID pandemic has also led to an increase in simulation use, as there were limitations on medical student placements in hospitals and clinics. The learning is tailored according to the educational needs of students to make the learning experience more valuable. Simulation in the pre-clinical years has challenges with resource constraints, effective curricular integration, student engagement and motivation, and evidence of educational impact, to mention a few. As instructors, we may have more reliance on the use of simulation for pre-clinical students while the students’ confidence levels and perceived competence are to be evaluated. Our research question was whether the implementation of simulation-based learning positively influences preclinical medical students' confidence levels and perceived competence. This study was done to align the teaching activities with the student’s learning experience to introduce more low-fidelity simulation-based teaching sessions for pre-clinical years and to obtain students’ input into the curriculum development as part of inclusivity. The study was carried out at International Medical University, involving pre-clinical year (Medical) students who were started with low-fidelity simulation-based medical education from their first semester and were gradually introduced to medium fidelity, too. The Student Satisfaction and Self-Confidence in Learning Scale questionnaire from the National League of Nursing was employed to collect the responses. The internal consistency reliability for the survey items was tested with Cronbach’s alpha using an Excel file. IBM SPSS for Windows version 28.0 was used to analyze the data. Spearman’s rank correlation was used to analyze the correlation between students’ satisfaction and self-confidence in learning. The significance level was set at p value less than 0.05. The results from this study have prompted the researchers to undertake a larger-scale evaluation, which is currently underway. The current results show that 70% of students agreed that the teaching methods used in the simulation were helpful and effective. The sessions are dependent on the learning materials that are provided and how the facilitators engage the students and make the session more enjoyable. The feedback provided inputs on the following areas to focus on while designing simulations for pre-clinical students. There are quality learning materials, an interactive environment, motivating content, skills and knowledge of the facilitator, and effective feedback.

Keywords: low-fidelity simulation, pre-clinical simulation, students satisfaction, self-confidence

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Mohammed Habchi, Sidi Mohammed Mesli, Rafik Benallal, Mohammed Kotbi

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On the basis of four partial correlation functions and some geometric constraints obtained from neutron scattering experiments, a Reverse Monte Carlo (RMC) simulation has been performed in the study of the aqueous electrolyte LiCl6H2O at the glassy state. The obtained 3-dimensional model allows computing pair radial and orientational distribution functions in order to explore the structural features of the system. Unrealistic features appeared in some coordination peaks. To remedy to this, we use the Hybrid Reverse Monte Carlo (HRMC), incorporating an additional energy constraint in addition to the usual constraints derived from experiments. The energy of the system is calculated using an Environment Dependence Interaction Potential (EDIP). Ions effects is studied by comparing correlations between water molecules in the solution and in pure water at room temperature Our results show a good agreement between experimental and computed partial distribution functions (PDFs) as well as a significant improvement in orientational distribution curves.

Keywords: LiCl6H2O, glassy state, RMC, HRMC

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Authors: Tahira Zaman

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The paper intends to discover the utility of hybrid teaching methods to aid undergraduate students to improve their English academic writing skills. A total of 45 undergraduate students were selected randomly from three classes from varying language abilities, with the research design of monitoring and rubrics evaluation as a means of measure. Language skills of the students were upgraded with the help of experiential learning methods using reflective writing technique, guided method in which students were merely directed to correct form of writing techniques along with self-guided method for the students to produce a library research-based article measured through a standardized rubrics provided. The progress of the students was monitored and checked through rubrics and self-evaluation and concluded that a change was observed in the students’ writing abilities.

Keywords: self evaluation, hybrid, self evaluation, reflective writing

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Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

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Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

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Authors: Benga Ebouele, Thomas Tengen

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Due to long lead time, work in process (WIP) inventory can manifest within the supply chain of most manufacturing system. It implies that there are lesser finished good on hand and more in the process because the work remains in the factory too long and cannot be sold to either customers The supply chain of most manufacturing system is then considered as inefficient as it take so much time to produce the finished good. Time consumed in each operation of the supply chain has an associated energy costs. Such phenomena can be harmful for a hybrid inventory system because a lot of space to store these semi-finished goods may be needed and one is not sure about the final energy cost of producing, holding and delivering the good to customers. The principle that reduces waste of energy within the supply chain of most manufacturing firms should therefore be available to all inventory managers in pursuit of profitability. Decision making by inventory managers in this condition is a modeling process, whereby a dynamical approach is used to depict, examine, specify and even operationalize the relationship between energy consumption and hybrid inventory level. The relationship between energy consumption and inventory level is established, which indicates a poor level of control and hence a potential for energy savings.

Keywords: dynamic modelling, energy used, hybrid inventory, supply chain

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Authors: Kayode A. Olaniyi, Adeola A. Ogunleye, Tola M. Osifeko

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Electric Vehicles (EV) appear to be gaining increasing patronage as a feasible alternative to Internal Combustion Engine Vehicles (ICEVs) for having low emission and high operation efficiency. The EV energy storage systems are required to handle high energy and power density capacity constrained by limited space, operating temperature, weight and cost. The choice of strategies for energy storage evaluation, monitoring and control remains a challenging task. This paper presents review of various energy storage technologies and recent researches in battery evaluation techniques used in EV applications. It also underscores strategies for the hybrid energy storage management and control schemes for the improvement of EV stability and reliability. The study reveals that despite the advances recorded in battery technologies there is still no cell which possess both the optimum power and energy densities among other requirements, for EV application. However combination of two or more energy storages as hybrid and allowing the advantageous attributes from each device to be utilized is a promising solution. The review also reveals that State-of-Charge (SoC) is the most crucial method for battery estimation. The conventional method of SoC measurement is however questioned in the literature and adaptive algorithms that include all model of disturbances are being proposed. The review further suggests that heuristic-based approach is commonly adopted in the development of strategies for hybrid energy storage system management. The alternative approach which is optimization-based is found to be more accurate but is memory and computational intensive and as such not recommended in most real-time applications.

Keywords: battery state estimation, hybrid electric vehicle, hybrid energy storage, state of charge, state of health

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Authors: Anirudh Sharma

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Introduction: The Covid-19 pandemic necessitated a change in the manner outpatient fracture clinics are conducted due to the need to reduce footfall in hospital. While studies regarding virtual fracture clinics have shown these to be useful and effective, they focus exclusively on remote consultations. However, our service was bespoke to the patient – either a face-to-face or telephone consultation depending on patient need – a ‘hybrid virtual clinic (HVC).’ We report patient satisfaction and outcomes with this novel service. Methods: Patients booked onto our fracture clinics during the first 2 weeks of national lockdown were retrospectively contacted to assess the mode of consultations (virtual, face-to-face, or hybrid), patient experience, and outcome. Patient experience was assessed using the net promoter (NPS), customer effort (CES) and customer satisfaction scores (CSS), and their likelihood of using the HVC in the absence of a pandemic. Patient outcomes were assessed using the components of the EQ5D score. Results: Of 269 possible patients, 140 patients responded to the questionnaire. Of these, 66.4% had ‘hybrid’ consultations, 27.1% had only virtual consultations, and 6.4% had only face-to-face consultations. The mean overall NPS, CES, and CSS (on a scale of 1-10) were 7.27, 7.25, and 7.37, respectively. The mean likelihood of patients using the HVC in the absence of a pandemic was 6.5/10. Patients who had ‘hybrid’ consultations showed better effort scores and greater overall satisfaction than those with virtual consultations only and also reported superior EQ5D outcomes (mean 79.27 vs. 72.7). Patients who did not require surgery reported increased satisfaction (mean 7.51 vs. 7.08) and were more likely to use the HVC in the absence of a pandemic. Conclusion: Our study indicates that a bespoke HVC has good overall patient satisfaction and outcomes and is a better format of fracture clinic service than virtual consultations alone. It may be the preferred mode for fracture clinics in similar situations in the future. Further analysis needs to be conducted in order to explore the impact on resources and clinician experience of HVC in order to appreciate this new paradigm shift.

Keywords: hybrid virtual clinic, coronavirus, COVID-19, fracture clinic, remote consultation

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Authors: Kizito Ugochukwu Nwajeri

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This paper explores the application of hybrid block methods for solving boundary value problems (BVPs), which are prevalent in various fields such as science, engineering, and applied mathematics. Traditionally, numerical approaches such as finite difference and shooting methods, often encounter challenges related to stability and convergence, particularly in the context of complex and nonlinear BVPs. To address these challenges, we propose a hybrid block method that integrates features from both single-step and multi-step techniques. This method allows for the simultaneous computation of multiple solution points while maintaining high accuracy. Specifically, we employ a combination of polynomial interpolation and collocation strategies to derive a system of equations that captures the behavior of the solution across the entire domain. By directly incorporating boundary conditions into the formulation, we enhance the stability and convergence properties of the numerical solution. Furthermore, we introduce an adaptive step-size mechanism to optimize performance based on the local behavior of the solution. This adjustment allows the method to respond effectively to variations in solution behavior, improving both accuracy and computational efficiency. Numerical tests on a variety of boundary value problems demonstrate the effectiveness of the hybrid block methods. These tests showcase significant improvements in accuracy and computational efficiency compared to conventional methods, indicating that our approach is robust and versatile. The results suggest that this hybrid block method is suitable for a wide range of applications in real-world problems, offering a promising alternative to existing numerical techniques.

Keywords: hybrid block methods, boundary value problem, polynomial interpolation, adaptive step-size control, collocation methods

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Authors: Abdelhadi Adel, Kadri Ouahab

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This paper proposes a hybrid algorithm for the integration of systematic preventive maintenance policies in hybrid flow shop scheduling to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time, methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi-agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. To solve such a complex problem, we proposed an approach which we have used advanced operators such as uniform crossover set and single point mutation. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Keywords: multi-agent systems, emergence, genetic algorithm, makespan, systematic maintenance, scheduling, hybrid flow shop scheduling

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Authors: A. Derrouazin, N. Mekkakia-M, R. Taleb, M. Helaimi, A. Benbouali

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Nowadays the use of different sources of renewable energy for the production of electricity is the concern of everyone, as, even impersonal domestic use of the electricity in isolated sites or in town. As the conventional sources of energy are shrinking, a need has arisen to look for alternative sources of energy with more emphasis on its optimal use. This paper presents design of a sustainable Hybrid Power System (PV-Wind-Storage) assisted by grid as supplementary sources applied to case study residential house, to meet its entire energy demand. A Fuzzy control system model has been developed to optimize and control flow of power from these sources. This energy requirement is mainly fulfilled from PV and Wind energy stored in batteries module for critical load of a residential house and supplemented by grid for base and peak load. The system has been developed for maximum daily households load energy of 3kWh and can be scaled to any higher value as per requirement of individual /community house ranging from 3kWh/day to 10kWh/day, as per the requirement. The simulation work, using intelligent energy management, has resulted in an optimal yield leading to average reduction in cost of electricity by 50% per day.

Keywords: photovoltaic (PV), wind turbine, battery, microcontroller, fuzzy control (FC), Matlab

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Authors: Hanefi Cinar, Musa Cibuk, Ismail Erturk, Fikri Aggun, Munip Geylani

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Mobile Wireless Sensor Networks (MWSNs) carry heterogeneous data traffic with different urgency and quality of service (QoS) requirements. There are a lot of studies made on energy efficiency, bandwidth, and communication methods in literature. But delay, high throughput, utility parameters are not well considered. Increasing demand for real-time data transfer makes these parameters more important. In this paper we design new MAC protocol which is delay constrained and targets for improving delay, utility, and throughput performance of the network and finding solutions on collision and interference problems. Protocol improving QoS requirements by using TDMA, FDM, and OFDMA hybrid communication methods with multi-channel communication.

Keywords: MWSN, delay, hybrid MAC, TDMA, FDM, OFDMA

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Authors: Jim J. Catina, Jackee M. Gwynn, Jin S. Kang

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Additive manufacturing (AM) for hybrid rocket engines is becoming increasingly attractive due to its ability to create complex grain configurations with improved regression rates when compared to cast grains. However, the presence of microvoids in parts produced through the additive manufacturing method of Fused Deposition Modeling (FDM) results in a lower fuel density and is believed to cause a decrease in regression rate compared to ideal performance. In this experiment, FDM was used to create hybrid rocket fuel grains with a star configuration composed of acrylonitrile butadiene styrene (ABS). Testing was completed to determine the effect of heat treatment as a post-processing method to improve the combustion performance of hybrid rocket fuel grains manufactured by FDM. For control, three ABS star configuration grains were printed using FDM and hot fired using gaseous oxygen (GOX) as the oxidizer. Parameters such as thrust and mass flow rate were measured. Three identical grains were then heat treated to varying degrees and hot fired under the same conditions as the control grains. This paper will quantitatively describe the amount of improvement in engine performance as a result of heat treatment of the AM hybrid fuel grain. Engine performance is measured in this paper by specific impulse, which is determined from the thrust measurements collected in testing.

Keywords: acrylonitrile butadiene styrene, additive manufacturing, fused deposition modeling, heat treatment

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

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Authors: Kun Huang

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This paper investigates whether the combination of local and stochastic volatility models can be calibrated exactly to any arbitrage-free implied volatility surface of European option. The risk neutral Brownian Bridge density is applied for calibration of the leverage function of our Hybrid model. Furthermore, the tails of marginal risk neutral density are generated by Generalized Extreme Value distribution in order to capture the properties of asset returns. The local volatility is generated from the arbitrage-free implied volatility surface using stochastic volatility inspired parameterization.

Keywords: arbitrage free implied volatility, calibration, extreme value distribution, hybrid model, local volatility, risk-neutral density, stochastic volatility

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Authors: Çağrı Bekir Baysal, Göktuğ Burak Çalık

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Armored vehicles may have different traction layouts as a result of terrain capabilities and mobility needs. Two main categories of layouts can be separated as wheeled and tracked. Tracked vehicles have superior off-road capabilities but what they gain on terrain performance they lose on mobility front. Wheeled vehicles on the other hand do not have as good terrain capabilities as tracked vehicles but they have superior mobility capabilities such as top speed, range and agility with respect to tracked vehicles. Conventional armored vehicles employ a diesel ICE as main power source. In these vehicles ICE is mechanically connected to the powertrain. This determines the ICE rpm as a result of speed and torque requested by the driver. ICE efficiency changes drastically with torque and speed required and conventional vehicles suffer in terms of fuel consumption because of this. Hybrid electric vehicles employ at least one electric motor in order to improve fuel efficiency. There are different types of hybrid vehicles but main types are Series Hybrid, Parallel Hybrid and Series-Parallel Hybrid. These vehicles introduce an electric motor for traction and also can have a generator electric motor for range extending purposes. Having an electric motor as the traction power source brings the flexibility of either using the ICE as an alternative traction source while it is in efficient range or completely separating the ICE from traction and using it solely considering efficiency. Hybrid configurations have additional advantages for armored vehicles in addition to fuel efficiency. Heat signature, silent operation and prolonged stationary missions can be possible with the help of the high-power battery pack that will be present in the vehicle for hybrid drivetrain. Because of the reasons explained, hybrid armored vehicles are becoming a target area for military and also for vehicle suppliers. In order to have a better idea and starting point when starting a hybrid armored vehicle design, hybrid drivetrain configuration has to be selected after performing a trade-off study. This study has to include vehicle mobility simulations, integration level, vehicle level and performance level criteria. In this study different hybrid traction configurations possible for an 8x8 vehicle is compared using above mentioned criteria set. In order to compare hybrid traction configurations ease of application, cost, weight advantage, reliability, maintainability, redundancy and performance criteria have been used. Performance criteria points have been defined with the help of vehicle simulations and tests. Results of these simulations and tests also help determining required tractive power for an armored vehicle including conditions like trench and obstacle crossing, gradient climb. With the method explained in this study, each configuration is assigned a point for each criterion. This way, correct configuration can be selected objectively for every application. Also, key aspects of armored vehicles, mine protection and ballistic protection will be considered for hybrid configurations. Results are expected to vary for different types of vehicles but it is observed that having longitudinal differential locking capability improves mobility and having high motor count increases complexity in general.

Keywords: armored vehicles, electric drivetrain, electric mobility, hybrid vehicles

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Authors: Kai Jin, Hua Li, Qing Song

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Homeland security and border safety is an issue for any country. This paper takes the border security of US as an example to discuss the usage and efficiency of simulation tools in the homeland security application. In this study, available resources and different illegal infiltration parameters are defined, including their individual behavior and objective, in order to develop a model that describes border patrol system. A simulation model is created in Arena. This simulation model is used to study the dynamic activities in the border security. Possible factors that may affect the effectiveness of the border patrol system are proposed. Individual and factorial analysis of these factors is conducted and some suggestions are made.

Keywords: resource optimization, simulation, modeling, border security

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Authors: Pawel Twardowski, Tadeusz Chwalczuk, Szymon Wojciechowski

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Inconel 718 is a material characterized by the unique mechanical properties, high temperature strength, high thermal conductivity and the corrosion resistance. However, these features affect the low machinability of this material, which is usually manifested by the intense tool wear and low surface finish. Therefore, this paper is focused on the evaluation of surface roughness during hybrid machining of Inconel 718. The primary aim of the study was to determine the relations between the vibrations generated during hybrid turning and the formed surface roughness. Moreover, the comparison of tested machining techniques in terms of vibrations, tool wear and surface roughness has been made. The conducted tests included the face turning of Inconel 718 with laser assistance in the range of variable cutting speeds. The surface roughness was inspected with the application of stylus profile meter and accelerations of vibrations were measured with the use of three-component piezoelectric accelerometer. The carried out research shows that application of laser assisted machining can contribute to the reduction of surface roughness and cutting vibrations, in comparison to conventional turning. Moreover, the obtained results enable the selection of effective cutting speed allowing the improvement of surface finish and cutting dynamics.

Keywords: hybrid machining, nickel alloys, surface roughness, turning, vibrations

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Authors: Habib Ur Rahman Habib

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Renewable energy resources are being realized as suitable options in hybrid energy planning for on-grid and micro grid. In this paper, operation, planning and optimal design of on-grid distributed energy resources based hybrid system are investigated. The aim is to minimize the cost of the overall energy system keeping in view the environmental emission and minimum penetration of conventional energy resources. Seven grid connected different case studies including diesel only, diesel-renewable based, and renewable based only are designed to perform economic analysis, operational planning and emission. Sensitivity analysis is implemented to investigate the impact of different parameters on the performance of energy resources.

Keywords: data management, renewable energy, distributed energy, smart grid, micro-grid, modeling, energy planning, design optimization

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Authors: Radhia Toujani, Jalel Akaichi

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Social Networks generally present a hierarchy of communities. To determine these communities and the relationship between them, detection algorithms should be applied. Most of the existing algorithms, proposed for hierarchical communities identification, are based on either agglomerative clustering or divisive clustering. In this paper, we present a hybrid hierarchical clustering approach for community detection based on both bottom-up and bottom-down clustering. Obviously, our approach provides more relevant community structure than hierarchical method which considers only divisive or agglomerative clustering to identify communities. Moreover, we performed some comparative experiments to enhance the quality of the clustering results and to show the effectiveness of our algorithm.

Keywords: agglomerative hierarchical clustering, community structure, divisive hierarchical clustering, hybrid hierarchical clustering, opinion mining, social network, social network analysis

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Authors: K. Paradkar, S. N. Mudliar, A. Sharma, A. B. Pandit, R. A. Pandey

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The study explores the hybrid combination of Hydrodynamic Cavitation (HC) and Subcritical Wet Air Oxidation-based pretreatment of complex industrial effluent to enhance the biodegradability selectively (without major COD destruction) to facilitate subsequent enhanced downstream processing via anaerobic or aerobic biological treatment. Advanced oxidation based techniques can be less efficient as standalone options and a hybrid approach by combining Hydrodynamic Cavitation (HC), and Wet Air Oxidation (WAO) can lead to a synergistic effect since both the options are based on common free radical mechanism. The HC can be used for initial turbulence and generation of hotspots which can begin the free radical attack and this agitating mixture then can be subjected to less intense WAO since initial heat (to raise the activation energy) can be taken care by HC alone. Lab-scale venturi-based hydrodynamic cavitation and wet air oxidation reactor with biomethanated distillery wastewater (BMDWW) as a model effluent was examined for establishing the proof-of-concept. The results indicated that for a desirable biodegradability index (BOD: COD - BI) enhancement (up to 0.4), the Cavitation (standalone) pretreatment condition was: 5 bar and 88 min reaction time with a COD reduction of 36 % and BI enhancement of up to 0.27 (initial BI - 0.17). The optimum WAO condition (standalone) was: 150oC, 6 bar and 30 minutes with 31% COD reduction and 0.33 BI. The hybrid pretreatment (combined Cavitation + WAO) worked out to be 23.18 min HC (at 5 bar) followed by 30 min WAO at 150oC, 6 bar, at which around 50% COD was retained yielding a BI of 0.55. FTIR & NMR analysis of pretreated effluent indicated dissociation and/or reorientation of complex organic compounds in untreated effluent to simpler organic compounds post-pretreatment.

Keywords: hybrid, hydrodynamic cavitation, wet air oxidation, biodegradability index

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Authors: Norshazmira Mat Azmi, Sayidal El Fatimah Masnan, Shatirah Akib

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More than 70% of the Earth is covered by oceans, which are considered to possess boundless renewable energy, such as tidal energy, tidal current energy, wave energy, thermal energy, and chemical energy. The hybrid system help in improving the economic and environmental sustainability of renewable energy systems to fulfill the energy demand. The concept of hybridizing renewable energy is to meet the desired system requirements, with the lowest value of the energy cost. This paper propose a hybrid power generation system suitable for remote area application and highlight the impact of surface waves on turbine design and performance, and the importance of understanding the site-specific wave conditions.

Keywords: marine current energy, tidal turbines, wave turbine, renewable energy, surface waves, hydraulic flume experiments, instantaneous wave phase

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, multi-objective optimization

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Authors: Ziraguen O. Williams, Shield B. Lin, Fouad N. Matari, Leslie J. Quiocho

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In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, feedback delay, and signal noise were added to a simulation model of an active-controlled vibration isolation system to regulate the movement of the exercise platform. Previous simulation work was conducted primarily via MATLAB/Simulink. Two additional simulation tools used in this study were Trick and MBDyn, NASA co-developed software simulation environments. Simulation results obtained from these three tools were very similar. All simulation results support the hypothesis that an active-controlled vibration isolation system outperforms a passive-controlled system even with the addition of feedback delay and signal noise to the active-controlled system. In this paper, squat exercise was used in creating excited force to the simulation model. The exciter force from a squat exercise was calculated from the motion capture of an exerciser. The simulation results demonstrate much greater transmitted force reduction in the active-controlled system than the passive-controlled system.

Keywords: control, counterweight, isolation, vibration

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Authors: Shu Yin, Zhiyang Ding, Jianzhong Huang, Xiaojun Ruan, Xiaomin Zhu, Xiao Qin

Abstract:

Since large-scale and data-intensive applications have been widely deployed, there is a growing demand for high-performance storage systems to support data-intensive applications. Compared with traditional storage systems, next-generation systems will embrace dedicated processor to reduce computational load of host machines and will have hybrid combinations of different storage devices. The advent of flash- memory-based solid state disk has become a critical role in revolutionizing the storage world. However, instead of simply replacing the traditional magnetic hard disk with the solid state disk, it is believed that finding a complementary approach to corporate both of them is more challenging and attractive. This paper explores an idea of active storage, an emerging new storage configuration, in terms of the architecture and design, the parallel processing capability, the cooperation of other machines in cluster computing environment, and a disk configuration, the hybrid combination of different types of disk drives. Experimental results indicate that the proposed HcDD achieves better I/O performance and longer storage system lifespan.

Keywords: arallel storage system, hybrid storage system, data inten- sive, solid state disks, reliability

Procedia PDF Downloads 434

Authors: A. El-S. Makled, M. K. Al-Tamimi

Abstract:

Ignition phenomena are of great interest area over the past many years, and it has a direct impact on many propulsion and combustion applications. The direct goal of the paper is to realize and evaluate a functioning ignition method, shut-off, throttling and re-start operations for the hybrid rocket motor. A small-scale hybrid rocket motor (SSHRM) is designed, manufactured, demonstrated at various operating conditions and finally equipped for laboratory firing tests with high level of safety. Various solid fuel grains as Polymethyle-methacrylate (PMMA) and Polyethylene (PE) are selected, and it is decided to use the commercial gaseous oxygen (GO2) for its availability and low cost. Examine different types of ignition methods, pyrotechnic charge, fuse wire, heat wire and finally hot oxidizer method by using the heat exchanger, which are proposed as very safe ignition methods. Finally; recognize phenomena of throttling and re-start operations. Ignition by hot GO2 impingement is proved to be a very attractive ignition method for laboratory SSHRM, for its high safety, reliability and acceptable delay time. Finally; the throttling and re-start operations are demonstrated several times and can be carried out more easily with hot air ignition method.

Keywords: hybrid rocket motor, ignition system, re-start phenomena, throttling

Procedia PDF Downloads 294

Authors: F. J. Adeyeye, D. Eni, K. M. Okedoye

Abstract:

In this paper we present a Hybrid of Adomian decomposition method (ADM). This is the substitution of a One-step method of Taylor’s series approximation of orders I and II, into the nonlinear part of Adomian decomposition method resulting in a convergent series scheme. This scheme is applied to solve some Logistic problems represented as Abelian differential equation and the results are compared with the actual solution and Runge-kutta of order IV in order to ascertain the accuracy and efficiency of the scheme. The findings shows that the scheme is efficient enough to solve logistic problems considered in this paper.

Keywords: Adomian decomposition method, nonlinear part, one-step method, Taylor series approximation, hybrid of Adomian polynomial, logistic problem, Malthusian parameter, Verhulst Model

Procedia PDF Downloads 393

Authors: Tsai-Pei Liu, Zhi-Rou Zheng, Tzu-Tzu Wen

Abstract:

Innovative logistics system simulation teaching is to extract the characteristics of the system through simulation methodology. The system has randomness and interaction problems in the execution time. Therefore, the simulation model can usually deal with more complex logistics process problems, giving students different learning modes. Students have more autonomy in learning time and learning progress. System simulation has become a new educational tool, but it still needs to accept many tests to use it in the teaching field. Although many business management departments in Taiwan have started to promote, this kind of simulation system teaching is still not popular, and the prerequisite for popularization is to be supported by students. This research uses an extension of Integration Unified Theory of Acceptance and Use of Technology (UTAUT2) to explore the acceptance of students in universities of science and technology to use system simulation as a learning tool. At the same time, it is hoped that this innovation can explore the effectiveness of the logistics system simulation after the introduction of teaching. The results indicated the significant influence of performance expectancy, social influence and learning value on students’ intention towards confirmed the influence of facilitating conditions and behavioral intention. The extended UTAUT2 framework helps in understanding students’ perceived value in the innovative logistics system teaching context.

Keywords: UTAUT2, logistics system simulation, learning value, Taiwan

Procedia PDF Downloads 101