Search results for: reduce order aeroelastic model (ROAM)

Authors: Anjian Chen, Joseph C. Chen

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

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

Procedia PDF Downloads 399

Authors: Karima Bouakaz, Amel Youcefi, Abdessamad Abada

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We determine a compact analytic expression for the complete next-to-leading contribution to the retarded transverse photons self-energy in the context of hard-thermal-loop summed perturbation of massless quantum electrodynamics (QED) at high temperature to calculate the next-to-leading order dispersion relations for slow-moving transverse photons at high temperature scalar quantum electrodynamics (Scalar QED), using the real time formalism (RTF) in physical representation. We derive the analytic expressions of hard thermal loop (HTL) contributions to propagators and vertices to determine the expressions of the effective propagators and vertices in RTF that contribute to the complete next-to leading order contribution of retarded transverse photons self-energy.

Keywords: hard thermal loop, hot scalar QED, NLO computations, soft transverse photons

Procedia PDF Downloads 85

Authors: Hélène Knoerr

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In an increasingly global world, more and more international students attend academic courses and programs in a second or foreign language, and local students register in language learning classes in order to improve their employability. These students need to quickly become proficient in the new language. How can we, as administrators, curriculum developers and teachers, make sure that they have the tools they need in order to develop their language skills in an academic context? This paper will describe the development and implementation of a new course, Learning to learn, as part of the Major in French/English as a Second Language at the University of Ottawa. This academic program was recently completely overhauled in order to reflect the current approaches in language learning (more specifically, the action-oriented approach as embodied in the Common European Framework of Reference for Languages, and the concept of life-long autonomous learning). The course itself is based on research on language learning strategies, with a particular focus on the characteristics of the “good language learner”. We will present the methodological and pedagogical foundations, describe the course objectives and learning outcomes, the language learning strategies, and the classroom activities. The paper will conclude with students’ feedback and suggest avenues for further exploration.

Keywords: curriculum development, language learning, learning strategies, second language

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Authors: Jose Ramon Sanabria Navarro, Yahilina Silveira Perez, Valentin Molina Moreno, Digna Dionisia Perez Bravo

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The general objective of this research is to conceive a model of strategic direction for Latin American high-performance sports centers for the improvement of their results. The sample is 62 managers, 187 trainers, 2930 athletes and 62 expert researchers from centers in Cuba, Venezuela, Ecuador, Colombia and Argentina, for 3241. The measurement instrument includes 12 key variables in the process of management strategies which are consolidated with the factorial analysis and the ANOVA of a factor through the SPSS 24.0. The reliability of the scale obtained an alpha higher than 0.7 in each sample. In this sense, a model is obtained that taxes the deficiencies detected in the diagnosis, based on the needs of the members of these organizations, considering criteria and theories of the strategic direction in the improvement of the organizational results. The validation of the model for high performance sports centers of the countries analyzed aims to develop joint strategies to generate synergies in their operational mode, which leads to enhance the sports organization.

Keywords: sports organization, information management, decision making, control

Procedia PDF Downloads 134

Authors: Mohammad Bagher Anvari, Arman Shojaei

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Incremental launching, a widely adopted bridge erection technique, offers numerous advantages for bridge designers. However, accurately simulating and modeling the dynamic behavior of the bridge during each step of the launching process proves to be tedious and time-consuming. The perpetual variation of internal forces within the deck during construction stages adds complexity, exacerbated further by considerations of other load cases, such as support settlements and temperature effects. As a result, there is an urgent need for a reliable, simple, economical, and fast algorithmic solution to model bridge construction stages effectively. This paper presents a novel Finite Element (FE) model that focuses on studying the static behavior of bridges during the launching process. Additionally, a simple method is introduced to normalize all quantities in the problem. The new FE model overcomes the limitations of previous models, enabling the simulation of all stages of launching, which conventional models fail to achieve due to underlying assumptions. By leveraging the results obtained from the new FE model, this study proposes solutions to improve the accuracy of conventional models, particularly for the initial stages of bridge construction that have been neglected in previous research. The research highlights the critical role played by the first span of the bridge during the initial stages, a factor often overlooked in existing studies. Furthermore, a new and simplified model termed the "semi-infinite beam" model, is developed to address this oversight. By utilizing this model alongside a simple optimization approach, optimal values for launching nose specifications are derived. The practical applications of this study extend to optimizing the nose-deck system of incrementally launched bridges, providing valuable insights for practical usage. In conclusion, this paper introduces a comprehensive Finite Element model for studying the static behavior of bridges during incremental launching. The proposed model addresses limitations found in previous approaches and offers practical solutions to enhance accuracy. The study emphasizes the importance of considering the initial stages and introduces the "semi-infinite beam" model. Through the developed model and optimization approach, optimal specifications for launching nose configurations are determined. This research holds significant practical implications and contributes to the optimization of incrementally launched bridges, benefiting both the construction industry and bridge designers.

Keywords: incremental launching, bridge construction, finite element model, optimization

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Authors: Abdelrahman Elsehsah, Hany Madkour, Khalid Farah

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This article presents a 3-D modified non-linear elastic model in the strain space. The Helmholtz free energy function is introduced with the existence of a dissipation potential surface in the space of thermodynamic conjugate forces. The constitutive equation and the damage evolution were derived as well. The modified damage has been examined to model the nonlinear behavior of reinforced concrete (RC) slabs with an opening. A parametric study with RC was carried out to investigate the impact of different factors on the behavior of RC slabs. These factors are the opening area, the opening shape, the place of opening, and the thickness of the slabs. And the numerical results have been compared with the experimental data from literature. Finally, the model showed its ability to be applied to the structural analysis of RC slabs.

Keywords: damage mechanics, 3-D numerical analysis, RC, slab with opening

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Authors: S. Lertsakulpasuk, S. Athichanagorn

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As depletion-drive gas reservoirs are abandoned when there is insufficient production rate due to pressure depletion, waterflooding has been proposed to increase the reservoir pressure in order to prolong gas production. Due to high cost, water injection may not be economically feasible. Water dumpflood into gas reservoirs is a new promising approach to increase gas recovery by maintaining reservoir pressure with much cheaper costs than conventional waterflooding. Thus, a simulation study of water dumpflood into multiple nearly abandoned or already abandoned thin-bedded gas reservoirs commonly found in the Gulf of Thailand was conducted to demonstrate the advantage of the proposed method and to determine the most suitable operational parameters for reservoirs having different system parameters. A reservoir simulation model consisting of several thin-layered depletion-drive gas reservoirs and an overlying aquifer was constructed in order to investigate the performance of the proposed method. Two producers were initially used to produce gas from the reservoirs. One of them was later converted to a dumpflood well after gas production rate started to decline due to continuous reduction in reservoir pressure. The dumpflood well was used to flow water from the aquifer to increase pressure of the gas reservoir in order to drive gas towards producer. Two main operational parameters which are wellhead pressure of producer and the time to start water dumpflood were investigated to optimize gas recovery for various systems having different gas reservoir dip angles, well spacings, aquifer sizes, and aquifer depths. This simulation study found that water dumpflood can increase gas recovery up to 12% of OGIP depending on operational conditions and system parameters. For the systems having a large aquifer and large distance between wells, it is best to start water dumpflood when the gas rate is still high since the long distance between the gas producer and dumpflood well helps delay water breakthrough at producer. As long as there is no early water breakthrough, the earlier the energy is supplied to the gas reservoirs, the better the gas recovery. On the other hand, for the systems having a small or moderate aquifer size and short distance between the two wells, performing water dumpflood when the rate is close to the economic rate is better because water is more likely to cause an early breakthrough when the distance is short. Water dumpflood into multiple nearly-depleted or depleted gas reservoirs is a novel study. The idea of using water dumpflood to increase gas recovery has been mentioned in the literature but has never been investigated. This detailed study will help a practicing engineer to understand the benefits of such method and can implement it with minimum cost and risk.

Keywords: dumpflood, increase gas recovery, low-pressure gas reservoir, multiple gas reservoirs

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Authors: Guo Yan

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Clothing recycling bin is a traditional way to collect textile waste in many areas. In the clothing recycling business, the transportation cost normally takes over 50% of total costs. This case gives a good way to reduce transportation cost by reverse logistics system. In this reverse logistics system, there are offline strategic alliance partners, such as transport firms, convenience stores, laundries, and post office which are integrated onto the mobile APP. Offline strategic alliance partners provide the service of textile waste collection, and transportation by their vacant vehicles return journey from convenience stores, laundries and post offices to sorting centers. The results of the case study provide the strategic alliance with a valuable and light - asset business model by using the logistics of offline memberships. The company in this case just focuses on textile waste sorting, reuse, recycling etc. The research method of this paper is a case study of a clothing recycling company in Chengdu by field research and interview; the analysis is based on the theory of the reverse logistics system.

Keywords: closed-loop recycles system, clothing recycling, end-of-life clothing, sharing economy, strategic alliance, reverse logistics.

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Authors: Cheng-Kuang Hsu, Chih-Hsiang Chang, Chi-Chih Wang

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Black soybeans contain high amount of antioxidants including polyphenols, anthocyanins and flavones. The protective function of black soybean against CCl4 (a strong oxidant) induced acute and chronic liver damage was investigated in vivo using SD rats or ICR mouse. The evaluation of CCl4 induced oxidative stress in the liver tissues included the measurements of the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), the concentration of thiobarbituric acid reactive substances (TBARS), the activities of antioxidant enzymes (superoxide dismutase SOD, catalase, and glutathione peroxidase GPx), as well as the level of histological lesion in the liver tissues. For chronic experiment, a decoction at the concentration of 100 or 1000 mg/kg of body weight, produced by baking black soybean at 130°C for 5 min and followed by immerging in 100°C hot water for 20 min, showed the inhibitory effect against CCl4 induced liver damage in SD rats. Hot-water extract (80 °C for 30 min) from un-preheated black soybean at the concentration of 200 mg/kg of body weight could not reduce ALT and AST levels in CCl4 treated SD rats, but the hot-water extract from preheated black soybean did enhance antioxidant enzymes activities, decline ALT and AST levels. Specially, the hot-water extract from the seed cost of black soybean had the highest liver protective function since it can reduce vacuolization and necrosis in the liver tissues. For acute experiment, the hot-water extracts from black soybean and the seed coat, as well as pure cyanidin-3-glucoside (C3G) could reduce ALT and AST levels of CCl4 induced ICR mouse. The decoction and hot-water extract from the seed coat of black soybean had higher total polyphenols, anthocyanins and flavones contents than those extracts from whole black soybean. Such results agreed with high liver protective function in the decoction and hot-water from the seed coat of black soybean. Black soybean showed protective function only after preheating process (baking at 130°C for 5 to 10 min) because preheating treatment damaged the cell wall and made the extraction of the antioxidants more effectively.

Keywords: black soybean, liver protective function, antioxidant, antioxidative stress

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Authors: S. M. Anowarul Haque, Md. Asiful Islam

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Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: load forecasting, artificial neural network, particle swarm optimization

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Authors: Sh. Wafa, M. Alanoud, S. Liyakathunisa

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Online booking for a trip or hotel has become an indispensable traveling tool today, people tend to be more interested in selecting air flight travel as their first choice when going for a long trip. People's shopping behavior has greatly changed by the advent of social network. Traditional ticket booking methods are considered as outdated with the advancement in tools and technology. Web based booking framework is an 'absolute necessity to have' for any visit or movement business that is investing heaps of energy noting telephone calls, sending messages or considering employing more staff. In this paper, we propose a process model for online trip reservation for our designed web application. Our proposed system will be highly beneficial and helps in reduction in time and cost for customers.

Keywords: trip, hotel, reservation, process model, time, cost, web app

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Authors: Mohanad Al-Behadili, Xiang Song, Djamila Ouelhadj, Alex Fraess-Ehrfeld

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In off-shore wind farms, turbine blade inspection accessibility under various sea states is very challenging and greatly affects the downtime of wind turbines. Maintenance of any offshore system is not an easy task due to the restricted logistics and accessibility. The multirotor unmanned helicopter is of increasing interest in inspection applications due to its manoeuvrability and payload capacity. These advantages increase when many of them are deployed simultaneously in a swarm. Hence this paper proposes a drone swarm framework for inspecting offshore wind turbine blades and nacelles so as to reduce downtime. One of the big challenges of this task is that when operating a drone swarm, an individual drone may not have enough power to fly and communicate during missions and it has no capability of refueling due to its small size. Once the drone power is drained, there are no signals transmitted and the links become intermittent. Vessels equipped with 5G masts and small power units are utilised as platforms for drones to recharge/swap batteries. The research work aims at designing a smart energy management system, which provides automated vessel and drone routing and recharging plans. To achieve this goal, a novel mathematical optimisation model is developed with the main objective of minimising the number of drones and vessels, which carry the charging stations, and the downtime of the wind turbines. There are a number of constraints to be considered, such as each wind turbine must be inspected once and only once by one drone; each drone can inspect at most one wind turbine after recharging, then fly back to the charging station; collision should be avoided during the drone flying; all wind turbines in the wind farm should be inspected within the given time window. We have developed a real-time Ant Colony Optimisation (ACO) algorithm to generate real-time and near-optimal solutions to the drone swarm routing problem. The schedule will generate efficient and real-time solutions to indicate the inspection tasks, time windows, and the optimal routes of the drones to access the turbines. Experiments are conducted to evaluate the quality of the solutions generated by ACO.

Keywords: drone swarm, routing, scheduling, optimisation model, ant colony optimisation

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Authors: Samuel Matylewicz, K. W. Goossen

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The deployment of white or cool (high albedo) roofing is a common energy savings recommendation for a variety of buildings all over the world. Here, the effect of a white roof on the energy savings of an ice rink facility in the northeastern US is determined by measuring the effect of solar irradiance on the consumption of the rink's ice refrigeration system. The consumption of the refrigeration system was logged over a year, along with multiple weather vectors, and a statistical model was applied. The experimental model indicates that the expected savings of replacing the existing grey roof with a white roof on the consumption of the refrigeration system is only 4.7 %. This overall result of the statistical model is confirmed with isolated instances of otherwise similar weather days, but cloudy vs. sunny, where there was no measurable difference in refrigeration consumption up to the noise in the local data, which was a few percent. This compares with a simple theoretical calculation that indicates 30% savings. The difference is attributed to a lack of convective cooling of the roof in the theoretical model. The best experimental model shows a relative effect of the weather vectors dry bulb temperature, solar irradiance, wind speed, and relative humidity on refrigeration consumption of 1, 0.026, 0.163, and -0.056, respectively. This result can have an impact on decisions to apply white roofing to refrigerated buildings in general.

Keywords: cool roofs, solar cooling load, refrigerated buildings, energy-efficient building envelopes

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Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

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The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

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Authors: Dana Alghool, Tarek ElMekkawy, Mohamed Haouari, Adel Elomari

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District cooling systems have captured the attentions of many researchers recently due to the enormous benefits offered by such system in comparison with traditional cooling technologies. It is considered a major component of urban cities due to the significant reduction of energy consumption. This paper aims to find the optimal design and operation of district cooling systems by developing a mixed integer linear programming model to minimize the annual total system cost and satisfy the end-user cooling demand. The proposed model is experimented with different cooling demand scenarios. The results of the very high cooling demand scenario are only presented in this paper. A sensitivity analysis on different parameters of the model was performed.

Keywords: Annual Cooling Demand, Compression Chiller, Mathematical Modeling, District Cooling Systems, Optimization

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Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load.

Keywords: cross-organization process mining, process behaviour, path of execution, polynomial regression model

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Authors: Tumisang Seodigeng, Hilary Rutto

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In this study we investigate the use of a laboratory batch digester to derive kinetic parameters for anaerobic digestion of garden grass and cattle dung. Laboratory experimental data from a 5 liter batch digester operating at mesophilic temperature of 32 C is used to derive parameters for Michaelis-Menten kinetic model. These fitted kinetics are further used to predict the scale-up parameters of a batch digester using DynoChem modeling and scale-up software. The scale-up model results are compared with performance data from 20 liter, 50 liter, and 200 liter batch digesters. Michaelis-Menten kinetic model shows to be a very good and easy to use model for kinetic parameter fitting on DynoChem and can accurately predict scale-up performance of 20 liter and 50 liter batch reactor based on parameters fitted on a 5 liter batch reactor.

Keywords: Biogas, kinetics, DynoChem Scale-up, Michaelis-Menten

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Authors: Ludivine Saint-Mard, Masato Nakajima, Gloria Senfaute

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In areas with low to moderate seismicity, the probabilistic seismic hazard analysis frequently uses a Poisson approach, which assumes independence in time and space of events to determine the annual probability of earthquake occurrence. Nevertheless, in countries with high seismic rate, such as Japan, it is frequently use non-poissonian model which assumes that next earthquake occurrence depends on the date of previous one. The objective of this paper is to apply a non-poissonian models in a region of low to moderate seismicity to get a feedback on the following questions: can we overcome the lack of data to determine some key parameters?, and can we deal with uncertainties to apply largely this methodology on an industrial context?. The Brownian-Passage-Time model was applied to a fault located in France and conclude that even if the lack of data can be overcome with some calculations, the amount of uncertainties and number of scenarios leads to a numerous branches in PSHA, making this method difficult to apply on a large scale of low to moderate seismicity areas and in an industrial context.

Keywords: probabilistic seismic hazard, non-poissonian model, earthquake occurrence, low seismicity

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Authors: Frederic Schenker, Jonathan J. Hendriks, Gianluca Nicchiotti

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In a product industrialization perspective, the end-product shall always be at the peak of technological advancement and developed in the shortest time possible. Thus, the constant growth of complexity and a shorter time-to-market calls for important changes on both the technical and business level. Undeniably, the common understanding of the system is beclouded by its complexity which leads to the communication gap between the engineers and the sale department. This communication link is therefore important to maintain and increase the information exchange between departments to ensure a punctual and flawless delivery to the end customer. This evolution brings engineers to reason with more hindsight and plan ahead. In this sense, they use new viewpoints to represent the data and to express the model deliverables in an understandable way that the different stakeholder may identify their needs and ideas. This article focuses on the usage of Model-Based System Engineering (MBSE) in a perspective of system industrialization and reconnect the engineering with the sales team. The modeling method used and presented in this paper concentrates on displaying as closely as possible the needs of the customer. Firstly, by providing a technical solution to the sales team to help them elaborate commercial offers without omitting technicalities. Secondly, the model simulates between a vast number of possibilities across a wide range of components. It becomes a dynamic tool for powerful analysis and optimizations. Thus, the model is no longer a technical tool for the engineers, but a way to maintain and solidify the communication between departments using different views of the model. The MBSE contribution to cost optimization during New Product Introduction (NPI) activities is made explicit through the illustration of a case study describing the support provided by system models to architectural choices during the industrialization of a novel optical sensor.

Keywords: analytical model, architecture comparison, MBSE, product industrialization, SysML, system thinking

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Authors: Bunakiye R. Japheth, Ogude U. Cyril

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Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: control process, metrics of engineering, structured abstraction, semantic model

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Authors: Marcelo Costa Cardoso, Luciano Pessanha Moreira

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In this work, the plastic behaviour of cold-rolled zinc coated dual-phase steel sheets DP600 and DP800 grades is firstly investigated with the help of uniaxial, hydraulic bulge and Forming Limit Curve (FLC) tests. The uniaxial tensile tests were performed in three angular orientations with respect to the rolling direction to evaluate the strain-hardening and plastic anisotropy. True stress-strain curves at large strains were determined from hydraulic bulge testing and fitted to a work-hardening equation. The limit strains are defined at both localized necking and fracture conditions according to Nakajima’s hemispherical punch procedure. Also, an elasto-plastic localization model is proposed in order to predict strain and stress based forming limit curves. The investigated dual-phase sheets showed a good formability in the biaxial stretching and drawing FLC regions. For both DP600 and DP800 sheets, the corresponding numerical predictions overestimated and underestimated the experimental limit strains in the biaxial stretching and drawing FLC regions, respectively. This can be attributed to the restricted failure necking condition adopted in the numerical model, which is not suitable to describe the tensile and shear fracture mechanisms in advanced high strength steels under equibiaxial and biaxial stretching conditions.

Keywords: advanced high strength steels, forming limit curve, numerical modelling, sheet metal forming

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Authors: Xinli Chen, Xue Su

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In the urban rail transit CBTC system, interlocking is considered one of the most basic sys-tems, which has the characteristics of logical complexity and high-security requirements. The development and verification of traditional interlocking subsystems are entirely manual pro-cesses and rely too much on the designer, which often hides many uncertain factors. In order to solve this problem, this article is based on the multi-template nib tracking algorithm for model construction and verification, achieving the main safety attributes and using SCADE for formal verification. Experimental results show that this method helps to improve the quality and efficiency of interlocking software.

Keywords: computer interlocking subsystem, penpoint tracking, communication-based train control system, multi-template tip tracking

Procedia PDF Downloads 162

Authors: Ahmed Al-Mansour, Qiang Zeng

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Recycling waste plastics in the form of concrete components, i.e. fine aggregates, has been an attractive topic among the society of civil engineers. Not only does the recycling of plastics reduce the overall cost of concrete production, but it also takes part in solving environmental issues. Nevertheless, the incorporation of recycled plastics into concrete results in an increasing reduction in the mechanical properties of concrete as the percentage of replacement of natural aggregates increases. In order to overcome this reduction, Ethylene-vinyl acetate (EVA) was used as an additive in concrete with recycled plastic aggregates. The aim of this additive is to: 1) increase the interfacial interaction at the interfacial transition zone (ITZ) between plastic pellets and cement matrix, and 2) mitigate the loss in mechanical properties. Three different groups of samples (i.e. cubes and prisms) were tested according to the plastics substituting fine aggregates. 5, 10, and 15% of fine aggregates were substituted for recycled plastic pellets, and 2 – 4% of the cement was substituted for EVA that produces a flexible agent when mixed properly with water. Compressive and tensile strength tests were conducted for the mechanical properties, while SEM and X-CT scan were implemented for further investigation of calcium-silicate-hydrate (C–S–H) formation and ITZ analysis. The optimal amount of plastic particles with EVA is suggested to get the most compact and dense matrix structure according to the results of this study.

Keywords: the durability of concrete, ethylene-vinyl acetate (EVA), interfacial transition zone (ITZ), recycled plastics

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Authors: A. H. Choudhury

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In this paper, a highly accurate numerical method for the solution of one-dimensional fourth-order wave equation is derived. This hyperbolic problem is solved by using semidiscrete approximations. The space direction is discretized by wavelet-Galerkin method, and the time variable is discretized by using Newmark schemes.

Keywords: hyperbolic problem, semidiscrete approximations, stability, Wavelet-Galerkin Method

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Authors: Ahteshamul Haq, Srikant Gupta, Murshid Kamal, Irfan Ali

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This case study designs and builds a multi-objective production planning model for a hardware firm with certain & uncertain data. During the time of interaction with the manager of the firm, they indicate some of the parameters may be vague. This vagueness in the formulated model is handled by the concept of fuzzy set theory. Triangular & Trapezoidal fuzzy numbers are used to represent the uncertainty in the collected data. The fuzzy nature is de-fuzzified into the crisp form using well-known defuzzification method via graded mean integration representation method. The proposed model attempts to maximize the production of the firm, profit related to the manufactured items & minimize the carrying inventory costs in both certain & uncertain environment. The recommended optimal plan is determined via fuzzy programming approach, and the formulated models are solved by using optimizing software LINGO 16.0 for getting the optimal production plan. The proposed model yields an efficient compromise solution with the overall satisfaction of decision maker.

Keywords: production planning problem, multi-objective optimization, fuzzy programming, fuzzy sets

Procedia PDF Downloads 216

Authors: Hend Mesbah, Yehia Youssef, Ibrahim Hassan, Shaaban Nosier, Ahmed El-Shazly, Ahmed Helal

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The problem of drinking water shortage is becoming more crucial nowadays as a result of the increased demand due to the population growth and the rise in the standard living. In recent years, desalination using electrodialysis powered by solar energy (PV-ED) is being widely used to help provide treated water and reduce the scarcity in water supply. In the present study, a water desalination laboratory scale ED cell with a fixed bed circulation system was designed, developed, and tested. The effect of three parameters (namely, cell voltage , flowrate, and salt concentration) on the removal percentage of salt ions was studied. The cell voltage was adjusted at 3 , 4 and 6 V. A flow rate of 5, 10, and 20 ml/s and an initial salt concentration of 2000, 5000, and 7000 ppm were investigated. The maximum salt percentage removal obtained was 52.5% at the lowest initial concentration (2000 ppm) and at the highest cell voltage (6 V). There was no significant effect of the flow rate on the removal percentage. A model of PV module has also been developed to calculate the dimensions of a solar cell based on the amount of energy consumed and it was calculated from the Overall ED cell voltage.

Keywords: desalination, electrodialysis, solar desalination, photovoltaic electrodialysis

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Authors: Emmanuel Iyamuremye, Jean François Maniriho, Irenee Ndayambaje

Abstract:

Mathematics is the foundational enabling discipline that underpins science, technology, and engineering disciplines. Science, technology, engineering, and mathematics (STEM) subjects are foreseen as the engine for socio-economic transformation. Rwanda has done reforms in education aiming at empowering and preparing students for the real world job by providing career pathways in science, technology, engineering, and mathematics related fields. While that considered so, the performance in mathematics has remained deplorable in both formative and national examinations. Therefore, this paper aims at exploring the extent to which the engage, explore, explain, elaborate and evaluate (5Es) instructional model contributing towards students’ achievement in mathematics. The present study adopted the pre-test, post-test non-equivalent control group quasi-experimental design. The 5Es instructional model was applied to the experimental group while the control group received instruction with the conventional teaching method for eight weeks. One research-made instrument, mathematics achievement test (MAT), was used for data collection. A pre-test was given to students before the intervention to make sure that both groups have equivalent characteristics. At the end of the experimental period, the two groups have undergone a post-test to ascertain the contribution of the 5Es instructional model. Descriptive statistics and analysis of covariance (ANCOVA) were used for the analysis of the study. For determining the improvement in mathematics, Hakes methods of calculating gain were used to analyze the pre-test and post-test scores. Results showed that students exposed to 5Es instructional model achieved significantly better performance in mathematics than students instructed using the conventional teaching method. It was also found that 5Es instructional model made lessons more interesting, easy and created friendship among students. Thus, 5Es instructional model was recommended to be adopted as a close substitute to the conventional teaching method in teaching mathematics in lower secondary schools in Rwanda.

Keywords: 5Es instructional model, achievement, conventional teaching method, mathematics

Procedia PDF Downloads 108

Authors: Eldho Paul, Brijesh Paul

Abstract:

This work proposes an auction mechanism based solution methodology for the optimum scheduling of trucks in a cross-docking centre. The cross-docking centre is an important element of lean supply chain. It reduces the amount of storage and transportation costs in the distribution system compared to an ordinary warehouse. Better scheduling of trucks in a cross-docking center is the best way to reduce storage and transportation costs. Auction mechanism is commonly used for allocation of limited resources in different real-life applications. Here, we try to schedule inbound trucks by integrating auction mechanism with the functioning of a cross-docking centre. A mathematical model is developed for the optimal scheduling of inbound trucks based on the auction methodology. The determination of exact solution for problems involving large number of trucks was found to be computationally difficult, and hence a genetic algorithm based heuristic methodology is proposed in this work. A comparative study of exact and heuristic solutions is done using five classes of data sets. It is observed from the study that the auction-based mechanism is capable of providing good solutions to scheduling problem in cross-docking centres.

Keywords: auction mechanism, cross-docking centre, genetic algorithm, scheduling of trucks

Procedia PDF Downloads 416

Authors: Ana Corberan-Vallet, Karen C. Florez, Ingrid C. Marino, Jose D. Bermudez

Abstract:

In 2016, the Region of the Americas was declared free of measles, a viral disease that can cause severe health problems. However, since 2017, measles has reemerged in Venezuela and has subsequently reached neighboring countries. In 2018, twelve American countries reported confirmed cases of measles. Governmental and health authorities in Colombia, a country that shares the longest land boundary with Venezuela, are aware of the need for a strong response to restrict the expanse of the epidemic. In this work, we apply a Bayesian hierarchical Poisson model with an underlying cluster structure to describe disease incidence in Colombia. Concretely, the proposed methodology provides relative risk estimates at the department level and identifies clusters of disease, which facilitates the implementation of targeted public health interventions. Socio-demographic factors, such as the percentage of migrants, gross domestic product, and entry routes, are included in the model to better describe the incidence of disease. Since the model does not impose any spatial correlation at any level of the model hierarchy, it avoids the spatial confounding problem and provides a suitable framework to estimate the fixed-effect coefficients associated with spatially-structured covariates.

Keywords: Bayesian analysis, cluster identification, disease mapping, risk estimation

Procedia PDF Downloads 156

Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

Abstract:

Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

Procedia PDF Downloads 135