Search results for: optimization cost

Authors: Bahiru Tsegaye, Chandrajit Balomajumder, Partha Roy

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The limited supply and related negative environmental consequence of fossil fuels are driving researcher for finding sustainable sources of energy. Lignocellulose biomass like sorghum straw is considered as among cheap, renewable and abundantly available sources of energy. However, lignocellulose biomass conversion to bioenergy like bioethanol is hindered due to the reluctant nature of lignin in the biomass. Therefore, removal of lignin is a vital step for lignocellulose conversion to renewable energy. The aim of this study is to optimize microwave pretreatment conditions using design expert software to remove lignin and to release maximum possible polysaccharides from sorghum straw for efficient hydrolysis and fermentation process. Sodium hydroxide concentration between 0.5-1.5%, v/v, pretreatment time from 5-25 minutes and pretreatment temperature from 120-2000C were considered to depolymerize sorghum straw. The effect of pretreatment was studied by analyzing the compositional changes before and after pretreatments following renewable energy laboratory procedure. Analysis of variance (ANOVA) was used to test the significance of the model used for optimization. About 32.8%-48.27% of hemicellulose solubilization, 53% -82.62% of cellulose release, and 49.25% to 78.29% lignin solubilization were observed during microwave pretreatment. Pretreatment for 10 minutes with alkali concentration of 1.5% and temperature of 1400C released maximum cellulose and lignin. At this optimal condition, maximum of 82.62% of cellulose release and 78.29% of lignin removal was achieved. Sorghum straw at optimal pretreatment condition was subjected to enzymatic hydrolysis and fermentation. The efficiency of hydrolysis was measured by analyzing reducing sugars by 3, 5 dinitrisylicylic acid method. Reducing sugars of about 619 mg/g of sorghum straw were obtained after enzymatic hydrolysis. This study showed a significant amount of lignin removal and cellulose release at optimal condition. This enhances the yield of reducing sugars as well as ethanol yield. The study demonstrates the potential of microwave pretreatments for enhancing bioethanol yield from sorghum straw.

Keywords: cellulose, hydrolysis, lignocellulose, optimization

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Authors: Ruedee Niyomrath

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The purposes of this research is aim to build the energy saving stove for stew coconut sugar. The research started from explores ceramic raw materials in local area, create the appropriate mixture of ceramic raw materials for construction material of stove, and make it by ceramic process. It includes design and build the energy saving stove, experiment the efficiency of energy saving stove as to thermal efficiency, energy saving, performance of time, and energy cost efficiency, transfer the knowledge for community, stove manufacturers, and technicians. The findings must be useful to the coconut sugar enterprises producing, to reduce the cost of production, preserve natural resources, and environments.

Keywords: ceramic raw material, energy saving stove, stove design, performance of stove, stove for stew coconut sugar

Procedia PDF Downloads 345

Authors: Ava Zarif Sanayei, Mustafa Farjad-Fard, Mohammad-Reza Mohammadian-Behbahani, Leyli Ebrahimi, Sedigheh Sina

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The fabrication and testing of a low-cost air-filled ion chamber for X-ray dosimetry is studied. The chamber is made of a metal cylinder, a central wire, a BC517 Darlington transistor, a 9V DC battery, and a voltmeter in order to have a cost-effective means to measure the dose. The output current of the dosimeter is amplified by the transistor and then fed to the large internal resistance of the voltmeter, producing a readable voltage signal. The dose-response linearity of the ion chamber is evaluated for different exposure scenarios by the X-ray tube. kVp values 70, 90, and 120, and mAs up to 20 are considered. In all experiments, a solid-state dosimeter (Solidose 400, Elimpex Medizintechnik) is used as a reference device for chamber calibration. Each case of exposure is repeated three times, the voltmeter and Solidose readings are recorded, and the mean and standard deviation values are calculated. Then, the calibration curve, derived by plotting voltmeter readings against Solidose readings, provided a linear fit result for all tube kVps of 70, 90, and 120. A 99, 98, and 100% linear relationship, respectively, for kVp values 70, 90, and 120 are demonstrated. The study shows the feasibility of achieving acceptable dose measurements with a simplified setup. Further enhancements to the proposed setup include solutions for limiting the leakage current, optimizing chamber dimensions, utilizing electronic microcontrollers for dedicated data readout, and minimizing the impact of stray electromagnetic fields on the system.

Keywords: dosimetry, ion chamber, radiation detection, X-ray

Procedia PDF Downloads 51

Authors: Fairouz Fakhfakh, Hatem Hadj Kacem, Ahmed Hadj Kacem

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Cloud computing offers a new model of service provisioning for workflow applications, thanks to its elasticity and its paying model. However, it presents various challenges that need to be addressed in order to be efficiently utilized. The resources provisioning problem for workflow applications has been widely studied. Nevertheless, the existing works did not consider the change in workflow instances while they are being executed. This functionality has become a major requirement to deal with unusual situations and evolution. This paper presents a first step towards the resources provisioning for a dynamic workflow. In fact, we propose a provisioning algorithm which minimizes the overall workflow execution cost, while meeting a deadline constraint. Then, we extend it to support the dynamic adding of tasks. Experimental results show that our proposed heuristic demonstrates a significant reduction in resources cost by using a consolidation process.

Keywords: cloud computing, resources provisioning, dynamic workflow, workflow applications

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Authors: Fabian Velasquez, John Espitia, Henry Hernadez, Sebastian Escobar, Jader Rodriguez

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Non-centrifuged cane sugar (NCS) is a concentrated product obtained through the evaporation of water contain from sugarcane juice inopen heat exchangers (OE). The heat supplied to the evaporation stages is obtained from the cane bagasse through the thermochemical process of combustion, where the thermal energy released is transferred to OE by the flue gas. Therefore, the optimization of energy usage becomes essential for the proper design of the production process. For optimize the energy use, it is necessary modeling and simulation of heat transfer between the combustion gases and the juice and to understand the major mechanisms involved in the heat transfer. The main objective of this work was simulated heat transfer phenomena between the flue gas and open heat exchangers using Computational Fluid Dynamics model (CFD). The simulation results were compared to field measured data. Numerical results about temperature profile along the flue gas pipeline at the measurement points are in good accordance with field measurements. Thus, this study could be of special interest in design NCS production process and the optimization of the use of energy.

Keywords: mathematical modeling, design variables, computational fluid dynamics, overall thermal efficiency

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Authors: M. Pappa, C. Efstathiou, G. Livanos, P. Xidas, D. Vakondios, E. Maravelakis, M. Zervakis, A. Antoniadis

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The choice of cutting tools in manufacturing processes is an essential parameter on which the required manufacturing time, the consumed energy and the cost effort all depend. If the number of tool changing times could be minimized or even eliminated by using a single convex tool providing multiple profiles, then a significant benefit of time and energy saving, as well as tool cost, would be achieved. A typical machine contains a variety of tools in order to deal with different curvatures and material removal rates. In order to minimize the required cutting tool changes, Actively Deformable micro-Cutters (ADmC) will be developed. The design of the Actively Deformable micro-Cutters will be based on the same cutting technique and mounting method as that in typical cutters.

Keywords: deformable cutters, cutting tool, milling, turning, manufacturing

Procedia PDF Downloads 441

Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

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Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Yu Song, Yuefei Jin

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Urban public transportation can be integrated when there is an efficient connection between urban rail lines, however, there are currently no effective or quick solutions being investigated for this connection. This paper analyzes the space-time distribution and travel demand of passenger connection travel based on taxi track data and data from the road network, excavates potential bus connection stations based on potential connection demand data, and introduces the link growth probability model in the complex network to solve the basic connection bus lines in order to ascertain the direction of the bus lines that are the most connected given the demand characteristics. Then, a tree view exhaustive approach based on constraints is suggested based on graph theory, which can hasten the convergence of findings while doing chain calculations. This study uses WEI QU NAN Station, the Xi'an Metro Line 2 terminal station in Shaanxi Province, as an illustration, to evaluate the model's and the solution method's efficacy. According to the findings, 153 prospective stations have been dug up in total, the feeder bus network for the entire line has been laid out, and the best route adjustment strategy has been found.

Keywords: feeder bus, route optimization, link growth probability, the graph theory

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Authors: Wi Sung Yoo, Seung Woo Lee, Youn Kyoung Hur, Sung Hwan Kim

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Large-scale construction projects are continuously increasing, and the need for tools to monitor and evaluate the project success is emphasized. At the construction industry level, there are limitations in deriving performance evaluation factors that reflect the diversity of construction sites and systems that can objectively evaluate and manage performance. Additionally, there are difficulties in integrating structured and unstructured data generated at construction sites and deriving improvements. In this study, we propose the Key Performance Indicators (KPIs) to enable performance evaluation that reflects the increased diversity of construction sites and the unstructured data generated, and present a model for measuring performance by the derived indicators. The comprehensive performance of a unit construction site is assessed based on 6 areas (Time, Cost, Quality, Safety, Environment, Productivity) and 26 indicators. We collect performance indicator information from 30 construction sites that meet legal standards and have been successfully performed. And We apply data augmentation and optimization techniques into establishing measurement standards for each indicator. In other words, the KPI for construction site performance evaluation presented in this study provides standards for evaluating performance in six areas using institutional requirement data and document data. This can be expanded to establish a performance evaluation system considering the scale and type of construction project. Also, they are expected to be used as a comprehensive indicator of the construction industry and used as basic data for tracking competitiveness at the national level and establishing policies.

Keywords: key performance indicator, performance measurement, structured and unstructured data, data augmentation

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Authors: Yu-Ching Cheng, Yi-Kai Juan, Daniel Castro

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Energy consumption of buildings has been an increasing concern for researchers and practitioners in the last decade. Sustainable building renovation can reduce energy consumption and carbon dioxide emissions; meanwhile, it also can extend existing buildings useful life and facilitate environmental sustainability while providing social and economic benefits to the society. School buildings are different from other designed spaces as they are more crowded and host the largest portion of daily activities and occupants. Strategies that focus on reducing energy use but also improve the students’ learning environment becomes a significant subject in sustainable school buildings development. A decision model is developed in this study to solve complicated and large-scale combinational, discrete and determinate problems such as school renovation projects. The task of this model is to automatically search for the most cost-effective (lower cost and higher quality) renovation strategies. In this study, the search process of optimal school building renovation solutions is by nature a large-scale zero-one programming determinate problem. A* is suitable for solving deterministic problems due to its stable and effective search process, and genetic algorithms (GA) provides opportunities to acquire global optimal solutions in a short time via its indeterminate search process based on probability. These two algorithms are combined in this study to consider trade-offs between renovation cost and improved quality, this decision model is able to evaluate current school environmental conditions and suggest an optimal scheme of sustainable school buildings renovation strategies. Through adoption of this decision model, school managers can overcome existing limitations and transform school buildings into spaces more beneficial to students and friendly to the environment.

Keywords: decision model, school buildings, sustainable renovation, genetic algorithm, A* search algorithm

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Authors: Loris Franchi, Daniele Calvi, Sabrina Corpino

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This paper presents a design methodology in which stakeholders are assisted with the exploration of a so-called negotiation space, aiming to the maximization of both group social welfare and single stakeholder’s perceived utility. The outcome results in less design iterations needed for design convergence while obtaining a higher solution effectiveness. During the early stage of a space project, not only the knowledge about the system but also the decision outcomes often are unknown. The scenario is exacerbated by the fact that decisions taken in this stage imply delayed costs associated with them. Hence, it is necessary to have a clear definition of the problem under analysis, especially in the initial definition. This can be obtained thanks to a robust generation and exploration of design alternatives. This process must consider that design usually involves various individuals, who take decisions affecting one another. An effective coordination among these decision-makers is critical. Finding mutual agreement solution will reduce the iterations involved in the design process. To handle this scenario, the paper proposes a design methodology which, aims to speed-up the process of pushing the mission’s concept maturity level. This push up is obtained thanks to a guided negotiation space exploration, which involves autonomously exploration and optimization of trade opportunities among stakeholders via Artificial Intelligence algorithms. The negotiation space is generated via a multidisciplinary collaborative optimization method, infused by game theory and multi-attribute utility theory. In particular, game theory is able to model the negotiation process to reach the equilibria among stakeholder needs. Because of the huge dimension of the negotiation space, a collaborative optimization framework with evolutionary algorithm has been integrated in order to guide the game process to efficiently and rapidly searching for the Pareto equilibria among stakeholders. At last, the concept of utility constituted the mechanism to bridge the language barrier between experts of different backgrounds and differing needs, using the elicited and modeled needs to evaluate a multitude of alternatives. To highlight the benefits of the proposed methodology, the paper presents the design of a CubeSat mission for the observation of lunar radiation environment. The derived solution results able to balance all stakeholders needs and guaranteeing the effectiveness of the selection mission concept thanks to its robustness in valuable changeability. The benefits provided by the proposed design methodology are highlighted, and further development proposed.

Keywords: concurrent engineering, artificial intelligence, negotiation in engineering design, multidisciplinary optimization

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Authors: Chun-Lang Chang, Chun-Kai Liu

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In this study, the patients that have undergone total knee replacement surgery from the 2010 National Health Insurance database were adopted as the study participants. The important factors were screened and selected through literature collection and interviews with physicians. Through the Cross Entropy Method (CE), Genetic Algorithm Logistic Regression (GALR), and Particle Swarm Optimization (PSO), the weights of the factors were obtained. In addition, the weights of the respective algorithms, coupled with the Excel VBA were adopted to construct the Case Based Reasoning (CBR) system. The results through statistical tests show that the GALR and PSO produced no significant differences, and the accuracy of both models were above 97%. Moreover, the area under the curve of ROC for these two models also exceeded 0.87. This study shall serve as a reference for medical staff as an assistance for clinical assessment of infections in order to effectively enhance medical service quality and efficiency, avoid unnecessary medical waste, and substantially contribute to resource allocations in medical institutions.

Keywords: Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization, Total Knee Replacement Surgery

Procedia PDF Downloads 310

Authors: Aldona Kluczek

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In recent years, manufacturing processes have interacted with sustainability issues realized in the cost-effective ways that minimalize energy, decrease negative impacts on the environment and are safe for society. However, the attention has been on separate sustainability assessment methods considering energy and material flow, energy consumption, and emission release or process control. In this paper, the energy-led sustainability assessment approach combining the methods: energy Life Cycle Assessment to assess environmental impact, Life Cycle Cost to analyze costs, and Social Life Cycle Assessment through ‘energy LCA-based value stream map’, is used to assess the energy sustainability of the hardwood lumber manufacturing process in terms of technologies. The approach integrating environmental, economic and social issues can be visualized in the considered energy-efficient technologies on the map of an energy LCA-related (input and output) inventory data. It will enable the identification of efficient technology of a given process to be reached, through the effective analysis of energy flow. It is also indicated that interventions in the considered technology should focus on environmental, economic improvements to achieve energy sustainability. The results have indicated that the most intense energy losses are caused by a cogeneration technology. The environmental impact analysis shows that a substantial reduction by 34% can be achieved with the improvement of it. From the LCC point of view, the result seems to be cost-effective, when done at that plant where the improvement is used. By demonstrating the social dimension, every component of the energy of plant labor use in the life-cycle process of the lumber production has positive energy benefits. The energy required to install the energy-efficient technology amounts to 30.32 kJ compared to others components of the energy of plant labor and it has the highest value in terms of energy-related social indicators. The paper depicts an example of hardwood lumber production in order to prove the applicability of a sustainability assessment method.

Keywords: energy efficiency, energy life cycle assessment, life cycle cost, social life cycle analysis, manufacturing process, sustainability assessment

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Authors: Markandeya Kunchi

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Usability testing (UT) is one of the vital steps in the User-centred design (UCD) process when designing a product. In an e-commerce ecosystem, UT becomes primary as new products, features, and services are launched very frequently. And, there are losses attached to the company if an unusable and inefficient product is put out to market and is rejected by customers. This paper tries to answer why UT is important in the product life-cycle of an E-commerce ecosystem. Secondary user research was conducted to find out work patterns, development methods, type of stakeholders, and technology constraints, etc. of a typical E-commerce company. Qualitative user interviews were conducted with product managers and designers to find out the structure, project planning, product management method and role of the design team in a mid-level company. The paper tries to address the usual apprehensions of the company to inculcate UT within the team. As well, it stresses upon factors like monetary resources, lack of usability expert, narrow timelines, and lack of understanding of higher management as some primary reasons. Outsourcing UT to vendors is also very prevalent with mid-level e-commerce companies, but it has its own severe repercussions like very little team involvement, huge cost, misinterpretation of the findings, elongated timelines, and lack of empathy towards the customer, etc. The shortfalls of the unavailability of a UT process in place within the team and conducting UT through vendors are bad user experiences for customers while interacting with the product, badly designed products which are neither useful and nor utilitarian. As a result, companies see dipping conversions rates in apps and websites, huge bounce rates and increased uninstall rates. Thus, there was a need for a more lean UT system in place which could solve all these issues for the company. This paper highlights on optimizing the UT process with a collaborative method. The degree of optimization and structure of collaborative method is the highlight of this paper. Collaborative method of UT is one in which the centralised design team of the company takes for conducting and analysing the UT. The UT is usually a formative kind where designers take findings into account and uses in the ideation process. The success of collaborative method of UT is due to its ability to sync with the product management method employed by the company or team. The collaborative methods focus on engaging various teams (design, marketing, product, administration, IT, etc.) each with its own defined roles and responsibility in conducting a smooth UT with users In-house. The paper finally highlights the positive results of collaborative UT method after conducting more than 100 In-lab interviews with users across the different lines of businesses. Some of which are the improvement of interaction between stakeholders and the design team, empathy towards users, improved design iteration, better sanity check of design solutions, optimization of time and money, effective and efficient design solution. The future scope of collaborative UT is to make this method leaner, by reducing the number of days to complete the entire project starting from planning between teams to publishing the UT report.

Keywords: collaborative method, e-commerce, product management method, usability testing

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Authors: Amina Umulisa

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Background: Despite efforts to enhance profitability and project planning, Rwanda has experienced a decline in project success rates, notably in housing projects managed by the Rwanda Social Security Board (RSSB). This study aims to assess the impact of investment strategies and project planning practices on the performance of pension funds projects in Rwanda, focusing on housing projects by RSSB. Methods: Using descriptive and correlational research designs, this study surveyed 109 randomly selected respondents from a pool of 148 workers. Data analysis was conducted using descriptive and inferential statistics in STATA version 18. Results: Findings revealed that 54% of respondents acknowledged the importance of personnel generation. Additionally, 61% agreed with the effectiveness of training programs, and 79% supported the cost of human resource utilization. In terms of project management practices, 65.7% could determine when a project needed adjustments, 65.7% agreed with the approved budget, and 73% supported forecasted expenses. Furthermore, 68% agreed with order placement, 76.0% with using the right materials, and 64.4% with defining project scope. The study found significant associations between order placement and project quality outcomes (r=0.711, P-value <0.001), as well as with time management (Pearson was 0.701 and sing was 0.00) and cost management (r=0.885, P-value <0.001). Moreover, project time targets were found to significantly affect quality management (Pearson was 0.798, sing was 0.000), time management, and cost management (r=0.740, P-value <0.001). Conclusion: The findings highlight the positive association between the project implementation stage and quality management, indicating effective project planning practices among senior staff. However, there is a need to enhance project team collaboration and coordination to improve the performance of constructed houses.

Keywords: project success rates, investment strategies, training programs, cost management

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Authors: E. Manikandan, C. Chilambarasan, M. Sulthan Ariff Rahman, S. Kanagaraj, Abhimanyu Pugazhandhi, V. R. Sanal Kumar

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The designer of any flying car has the major concern on the creation of upward force with low takeoff velocity, with minimum drag, coupled with better stability and control warranting its overall high performance both in road and air. In this paper, 3D numerical simulations of external flow of a Ferrari F430 fitted with different NACA series rectangular wings have been carried out for finding the best aerodynamic design option in road and air. The principle that allows a car to rise off the ground by creating lift using deployable wings with desirable lifting characteristics is the main theme of our paper. Additionally, the car body is streamlined in accordance with the speed range. Further, the rounded and tapered shape of the top of the car is designed to slice through the air and minimize the wind resistance. The 3D SST k-ω turbulence model has been used for capturing the intrinsic flow physics during the take off phase. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier-Stokes equations is employed. Through the detailed parametric analytical studies, we have conjectured that Ferrari F430 can be converted into a lucrative flying car with best fit NACA wing through a proper aerodynamic design optimization.

Keywords: aerodynamics of flying car, air taxi, Ferrari F430, roadable airplane

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Authors: Nabil Hameed Al-Farsi

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This study’s main goal is to develop a model and a maintenance strategy for a cement factory called Arabian Cement Company, Rabigh Plant. The proposed work here depends on Reliability centric maintenance approach to develop a strategy and maintenance schedule that ensures increasing the reliability of the production system components, thus ensuring continuous productivity. The cost-effective maintenance of the plant’s dependability performance is the key goal of durability-based maintenance is. The cement plant consists of 7 important steps, so, developing a maintenance plan based on Reliability centric maintenance (RCM) method is made up of 10 steps accordingly starting from selecting units and data until performing and updating the model. The processing unit chosen for the analysis of this case is the calcinatory unit regarding model’s validation and the Travancore Titanium Products Ltd (TTP) using the claimed data history acquired from the maintenance department maintenance from the mentioned company. After applying the proposed model, the results of the maintenance simulation justified the plant's existing scheduled maintenance policy being reconsidered. Results represent the need for preventive maintenance for all Class A criticality equipment instead of the planned maintenance and the breakdown one for all other equipment depends on its criticality and an FMEA report. Consequently, the additional cost of preventive maintenance would be offset by the cost savings from breakdown maintenance for the remaining equipment.

Keywords: engineering, reliability, strategy, maintenance, failure modes, effects and criticality analysis (FMEA)

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Authors: Shinn-Dar Wu

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This study aims to synthesize lithium iron phosphate cathode material using a recycling technology involving non-protective gas calcination. The advantages include lower cost and easier production than traditional methods that require a large amount of protective gas. The novel technology may have extensive industrial applications. Given that the traditional gas calcination has a large number of protection free Fe3+ production, this study developed a precursor iron phosphate (Fe2+) material recycling technology and conducted related tests and analyses. It focused on flow field design of calcination and new technology as well as analyzed the best conditions for powder calcination combination. The electrical properties were determined by button batteries and exhibited a capacity of 118 mAh/g (The use of new materials synthesis, capacitance is about 122 mAh/g). The cost reduced to 50% of the original.

Keywords: lithium battery, lithium iron phosphate, calcined technology, recycling technology

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Authors: Krutika K. Sawant, Anil Solanki

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The present study deals with the preparation and optimization of ethyl cellulose-containing disopyramide phosphate loaded microspheres using solvent evaporation technique. A central composite design consisting of a two-level full factorial design superimposed on a star design was employed for optimizing the preparation microspheres. The drug:polymer ratio (X1) and speed of the stirrer (X2) were chosen as the independent variables. The cumulative release of the drug at a different time (2, 6, 10, 14, and 18 hr) was selected as the dependent variable. An optimum polynomial equation was generated for the prediction of the response variable at time 10 hr. Based on the results of multiple linear regression analysis and F statistics, it was concluded that sustained action can be obtained when X1 and X2 are kept at high levels. The X1X2 interaction was found to be statistically significant. The drug release pattern fitted the Higuchi model well. The data of a selected batch were subjected to an optimization study using Box-Behnken design, and an optimal formulation was fabricated. Good agreement was observed between the predicted and the observed dissolution profiles of the optimal formulation.

Keywords: disopyramide phosphate, ethyl cellulose, microspheres, controlled release, Box-Behnken design, factorial design

Procedia PDF Downloads 441

Authors: Armin Amindari

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Hermetic compressors are used widely for refrigeration, heat pump, and air conditioning applications. With the improvement of energy conservation and environmental protection requirements, inverter compressors that operates at different speeds have become increasingly attractive in the industry. Although speed change capability is more efficient, passing through resonant frequencies may lead to excessive vibrations. In this work, an integrated vibration control approach based on flexible multi-body dynamics theory is used for optimizing the vibration amplitudes of the compressor at different operating speeds. To examine the compressor vibrations, all the forces and moments exerted on the cylinder block were clarified and minimized using balancers attached to the upper and lower ends of the motor rotor and crankshaft. The vibration response of the system was simulated using Motionview™ software. In addition, mass-spring optimization was adopted to shift the resonant frequencies out of the operating speeds. The modal shapes of the system were studied using Optistruct™ solver. Using this approach, the vibrations were reduced up to 56% through dynamic simulations. The results were in high agreement with various experimental test data. In addition, the vibration resonance problem observed at low speeds was solved by shifting the resonant frequencies through optimization studies.

Keywords: vibration, MBD, compressor, hermetic

Procedia PDF Downloads 86

Authors: Sanat K. Dash, Rama S. Verma, Sarit K. Das

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A logarithmic microfluidic shear device was designed and fabricated for cellular mechanotransduction studies. The device contains four cell culture chambers in which flow was modulated to achieve a logarithmic increment. Resistance values were optimized to make the device compact. The network of resistances was developed according to a unique combination of series and parallel resistances as found via optimization. Simulation results done in Ansys 16.1 matched the analytical calculations and showed the shear stress distribution at different inlet flow rates. Fabrication of the device was carried out using conventional photolithography and PDMS soft lithography. Flow profile was validated taking DI water as working fluid and measuring the volume collected at all four outlets. Volumes collected at the outlets were in accordance with the simulation results at inlet flow rates ranging from 1 ml/min to 0.1 ml/min. The device can exert fluid shear stresses ranging four orders of magnitude on the culture chamber walls which will cover shear stress values from interstitial flow to blood flow. This will allow studying cell behavior in the long physiological range of shear stress in a single run reducing number of experiments.

Keywords: microfluidics, mechanotransduction, fluid shear stress, physiological shear

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Authors: Shah Muhammad Butt, Ahmed Masaud Ansari

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Present Financial crisis in Higher Educational Institutes (HEIs) facing lots of problems considerable budget cuts, make difficult to meet the ever growing IT-based research and learning needs, institutions are rapidly planning and promoting cloud-based approaches for their academic and research needs. A cost effective Hybrid Cloud framework for HEI’s will provide educational services for campus or intercampus communication. Hybrid Cloud Framework comprises Private and Public Cloud approaches. This paper will propose the framework based on the Open Source Cloud (OpenNebula for Virtualization, Eucalyptus for Infrastructure, and Aneka for programming development environment) combined with CSP’s services which are delivered to the end-user via the Internet from public clouds.

Keywords: educational services, hybrid campus cloud, open source, electrical and systems sciences

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Authors: Firas Mohamad Al-Sabek

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The Purpose of the paper is to examine the most critical and important factor which will affect the implementation of Total Quality Management (TQM) in the construction industry in the United Arab Emirates. It also examines the most effected Project outcome from implementing TQM. A framework was also proposed depending on the literature studies. The method used in this paper is a quantitative study. A survey with a sample of 60 respondents was created and distributed in a construction company in Abu Dhabi, which includes 15 questions to examine the most critical factor that will affect the implementation of TQM in addition to the most effected project outcome from implementing TQM. The survey showed that management commitment is the most important factor in implementing TQM in a construction company. Also it showed that Project cost is most effected outcome from the implementation of TQM. Management commitment is very important for implementing TQM in any company. If the management loose interest in quality then everyone in the organization will do so. The success of TQM will depend mostly on the top of the pyramid. Also cost is reduced and money is saved when the project team implement TQM. While if no quality measures are present within the team, the project will suffer a commercial failure. Based on literature, more factors can be examined and added to the model. In addition, more construction companies could be surveyed in order to obtain more accurate results. Also this study could be conducted outside the United Arab Emirates for further enchantment.

Keywords: construction project, total quality management, management commitment, cost, theoretical framework

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Authors: James Li, Darko Joksimovic

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Urban development changes the natural hydrologic cycle, resulting in storm water impacts such as flooding, water quality degradation, receiving water erosion, and ecosystem deterioration. An integrated storm water managementapproach utilizing source and conveyance (termed green infrastructure) and end-of-pipe control measures is an effective way to manage urban storm water impacts. This paper focuses onplanning green infrastructure (GI) at the source and along the drainage system on a city level. It consists of (1)geospatial analysis of feasible GI using physical suitability; (2) modelling of cumulative GI's stormwater performance; and (3) cost-effectiveness analysis to prioritize the implementation of GI. A case study of the City of Barrie in Ontario, Canada, was used to demonstrate the GI's planning.

Keywords: cost-effectiveness of storm water controls, green infrastructure, urban storm water, city-level master planning

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Authors: Khachen Kongpakwattana, Charungthai Dejthevaporn, Orapitchaya Krairit, Piyameth Dilokthornsakul, Devi Mohan, Nathorn Chaiyakunapruk

Abstract:

Background: Although an increase in the burden of Alzheimer’s disease (AD) is evident worldwide, knowledge of costs and health-related quality of life (HR-QoL) associated with AD in Low- and Middle-Income Countries (LMICs) is still lacking. We, therefore, aimed to collect real-world cost and HR-QoL data, and investigate their associations with multiple disease-severity indicators among AD patients in Thailand. Methods: We recruited AD patients aged ≥ 60 years accompanied by their caregivers at a university-affiliated tertiary hospital. A one-time structured interview was conducted to collect disease-severity indicators, HR-QoL and caregiving information using standardized tools. The hospital’s database was used to retrieve healthcare resource utilization occurred over 6 months preceding the interview date. Costs were annualized and stratified based on cognitive status. Generalized linear models were employed to evaluate determinants of costs and HR-QoL. Results: Among 148 community-dwelling patients, average annual total societal costs of AD care were 8,014 US$ [95% Confidence Interval (95% CI): 7,295 US$ - 8,844 US$] per patient. Total costs of patients with severe stage (9,860 US$; 95% CI: 8,785 US$ - 11,328 US$) were almost twice as high as those of mild stage (5,524 US$; 95% CI: 4,649 US$ - 6,593 US$). The major cost driver was direct medical costs, particularly those incurred by AD prescriptions. Functional status was the strongest determinant for both total costs and patient’s HR-QoL (p-value < 0.001). Conclusions: Our real-world findings suggest the distinct major cost driver which results from expensive AD treatment, emphasizing the demand for country-specific cost evidence. Increases in cognitive and functional status are significantly associated with decreases in total costs of AD care and improvement on patient’s HR-QoL.

Keywords: Alzheimer's disease, associations, costs, disease-severity indicators, health-related quality of life

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Authors: Mohammad Bagher Anvari, Arman Shojaei

Abstract:

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: A. Ribeiro, N. Pacheco, M. Soares, N. Valério, L. Nascimento, A. Silva, C. Vilarinho, J. Carvalho

Abstract:

Hydrogen will play a key role in changing the current global energy paradigm, associated with the high use of fossil fuels and the release of greenhouse gases. This work intended to identify and quantify the potential of Solid Recovered Fuels (SFR) existing in Portugal and project the cost of hydrogen, produced through its steam gasification in different scenarios, associated with the size or capacity of the plant and the existence of carbon capture and storage (CCS) systems. Therefore, it was performed a techno-economic analysis simulation using an ASPEN base model, the H2A Hydrogen Production Model Version 3.2018. Regarding the production of SRF, it was possible to verify the annual production of more than 200 thousand tons of SRF in Portugal in 2019. The results of the techno-economic analysis simulations showed that in the scenarios containing a high (200,000 tons/year) and medium (40,000 tons/year) amount of SFR, the cost of hydrogen production was competitive concerning the current prices of hydrogen. The results indicate that scenarios 1 and 2, which use 200,000 tons of SRF per year, have lower hydrogen production values, 1.22 USD/kg H2 and 1.63 USD/kg H2, respectively. The cost of producing hydrogen without carbon capture and storage (CCS) systems in an average amount of SFR (40,000 tons/year) was 1.70 USD/kg H2. In turn, scenarios 5 (without CCS) and 6 (with CCS), which use only 683 tons of SFR from urban sources, have the highest costs, 6.54 USD/kg H2 and 908.97 USD/kg H2, respectively. Therefore, it was possible to conclude that there is a huge potential for the use of SRF for the production of hydrogen through steam gasification in Portugal.

Keywords: gasification, hydrogen, solid recovered fuels, techno-economic analysis, waste-to-energy

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Authors: Yen-Luan Chen

Abstract:

Maintenance has a great impact on the capacity of production and on the quality of the products, and therefore, it deserves continuous improvement. Maintenance procedure done before a failure is called preventive maintenance (PM). Sequential PM, which specifies that a system should be maintained at a sequence of intervals with unequal lengths, is one of the commonly used PM policies. This article proposes a generalized sequential PM policy for a system subject to shocks with imperfect maintenance and random working time. The shocks arrive according to a non-homogeneous Poisson process (NHPP) with varied intensity function in each maintenance interval. As a shock occurs, the system suffers two types of failures with number-dependent probabilities: type-I (minor) failure, which is rectified by a minimal repair, and type-II (catastrophic) failure, which is removed by a corrective maintenance (CM). The imperfect maintenance is carried out to improve the system failure characteristic due to the altered shock process. The sequential preventive maintenance-last (PML) policy is defined as that the system is maintained before any CM occurs at a planned time Ti or at the completion of a working time in the i-th maintenance interval, whichever occurs last. At the N-th maintenance, the system is replaced rather than maintained. This article first takes up the sequential PML policy with random working time and imperfect maintenance in reliability engineering. The optimal preventive maintenance schedule that minimizes the mean cost rate of a replacement cycle is derived analytically and determined in terms of its existence and uniqueness. The proposed models provide a general framework for analyzing the maintenance policies in reliability theory.

Keywords: optimization, preventive maintenance, random working time, minimal repair, replacement, reliability

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Authors: Bita Payami-Shabestari, Dariush Eslami

Abstract:

The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

Procedia PDF Downloads 113