Search results for: hydrostatic and hydrodynamic optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3515

Search results for: hydrostatic and hydrodynamic optimization

1355 Optimizing Design Parameters for Efficient Saturated Steam Production in Fire Tube Boilers: A Cost-Effective Approach

Authors: Yoftahe Nigussie Worku

Abstract:

This research focuses on advancing fire tube boiler technology by systematically optimizing design parameters to achieve efficient saturated steam production. The main objective is to design a high-performance boiler with a production capacity of 2000kg/h at a 12-bar design pressure while minimizing costs. The methodology employs iterative analysis, utilizing relevant formulas, and considers material selection and production methods. The study successfully results in a boiler operating at 85.25% efficiency, with a fuel consumption rate of 140.37kg/hr and a heat output of 1610kW. Theoretical importance lies in balancing efficiency, safety considerations, and cost minimization. The research addresses key questions on parameter optimization, material choices, and safety-efficiency balance, contributing valuable insights to fire tube boiler design.

Keywords: safety consideration, efficiency, production methods, material selection

Procedia PDF Downloads 48
1354 A Review of Fused Deposition Modeling Process: Parameter Optimization, Materials and Design

Authors: Elisaveta Doncheva, Jelena Djokikj, Ognen Tuteski, Bojana Hadjieva

Abstract:

In the past decade, additive manufacturing technology or 3D printing has been promoted as an efficient method for fabricating hybrid composite materials and structures with superior mechanical properties and complex shape and geometry. Fused deposition modeling (FDM) process is commonly used additive manufacturing technique for production of polymer products. Therefore, many studies and experiments are focused on investigating the possibilities for improving the obtained results on product properties as a key factor for expanding the spectrum of their application. This article provides an extensive review on recent research advances in FDM and reports on studies that cover the effects of process parameters, material, and design of the product properties. The paper conclusions provide a clear up-to date information for optimum efficiency and enhancement of the mechanical properties of 3D printed samples and recommends further research work and investigations.

Keywords: additive manufacturing, critical parameters, filament, print orientation, 3D printing

Procedia PDF Downloads 174
1353 Intrusion Detection Using Dual Artificial Techniques

Authors: Rana I. Abdulghani, Amera I. Melhum

Abstract:

With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

Procedia PDF Downloads 369
1352 Agent-Based Simulation for Supply Chain Transport Corridors

Authors: Kamalendu Pal

Abstract:

Supply chains are the spinal cord of trade and commerce. Their logistics use different transport corridors on regular basis for operational purpose. The international supply chain transport corridors include different infrastructure elements (e.g. weighbridge, package handling equipment, border clearance authorities, and so on) in supply chains. This paper presents the use of multi-agent systems (MAS) to model and simulate some aspects of transportation corridors, and in particular the area of weighbridge resource optimization for operational profit generation purpose. An underlying multi-agent model provides a means of modeling the relationships among stakeholders in order to enable coordination in a transport corridor environment. Simulations of the costs of container unloading, reloading, and waiting time for queuing up tracks have been carried out using data sets. Results of the simulation provide the potential guidance in making decisions about optimal service resource allocation in a trade corridor.

Keywords: multi-agent systems, simulation, supply chain, transport corridor, weighbridge

Procedia PDF Downloads 340
1351 Developing a Tissue-Engineered Aortic Heart Valve Based on an Electrospun Scaffold

Authors: Sara R. Knigge, Sugat R. Tuladhar, Alexander Becker, Tobias Schilling, Birgit Glasmacher

Abstract:

Commercially available mechanical or biological heart valve prostheses both tend to fail long-term due to thrombosis, calcific degeneration, infection, or immunogenic rejection. Moreover, these prostheses are non-viable and do not grow with the patients, which is a problem for young patients. As a result, patients often need to undergo redo-operations. Tissue-engineered (TE) heart valves based on degradable electrospun fiber scaffolds represent a promising approach to overcome these limitations. Such scaffolds need sufficient mechanical properties to withstand the hydrodynamic stress of intracardiac hemodynamics. Additionally, the scaffolds should be colonized by autologous or homologous cells to facilitate the in vivo remodeling of the scaffolds to a viable structure. This study investigates how process parameters of electrospinning and degradation affect the mechanical properties of electrospun scaffolds made of FDA-approved, biodegradable polymer polycaprolactone (PCL). Fiber mats were produced from a PCL/tetrafluoroethylene solution by electrospinning. The e-spinning process was varied in terms of scaffold thickness, fiber diameter, fiber orientation, and fiber interconnectivity. The morphology of the fiber mats was characterized with a scanning electron microscope (SEM). The mats were degraded in different solutions (cell culture media, SBF, PBS and 10 M NaOH-Solution). At different time points of degradation (2, 4 and 6 weeks), tensile and cyclic loading tests were performed. Fresh porcine pericardium and heart valves served as a control for the mechanical assessment. The progression of polymer degradation was quantified by SEM and differential scanning calorimetry (DSC). Primary Human aortic endothelial cells (HAECs) and Human induced pluripotent stem cell-derived endothelial cells (iPSC-ECs) were seeded on the fiber mats to investigate the cell colonization potential. The results showed that both the electrospinning parameters and the degradation significantly influenced the mechanical properties. Especially the fiber orientation has a considerable impact and leads to a pronounced anisotropic behavior of the scaffold. Preliminary results showed that the polymer became strongly more brittle over time. However, the embrittlement can initially only be detected in the mechanical test. In the SEM and DSC investigations, neither morphological nor thermodynamic changes are significantly detectable. Live/Dead staining and SEM imaging of the cell-seeded scaffolds showed that HAECs and iPSC-ECs were able to grow on the surface of the polymer. In summary, this study's results indicate a promising approach to the development of a TE aortic heart valve based on an electrospun scaffold.

Keywords: electrospun scaffolds, long-term polymer degradation, mechanical behavior of electrospun PCL, tissue engineered aortic heart valve

Procedia PDF Downloads 125
1350 Android Graphics System: Study of Dual-Software VSync Synchronization Architecture and Optimization

Authors: Prafulla Kumar Choubey, Krishna Kishor Jha, S. B. Vaisakh Punnekkattu Chirayil

Abstract:

In Graphics-display subsystem, frame buffers are shared between producer i.e. content rendering and consumer i.e. display. If a common buffer is operated by both producer and consumer simultaneously, their processing rates mismatch can cause tearing effect in displayed content. Therefore, Android OS employs triple buffered system, taking in to account an additional composition stage. Three stages-rendering, composition and display refresh, operate synchronously on three different buffers, which is achieved by using vsync pulses. This synchronization, however, brings in to the pipeline an additional latency of up to 26ms. The present study details about the existing synchronization mechanism of android graphics-display pipeline and discusses a new adaptive architecture which reduces the wait time to 5ms-16ms in all the use-cases. The proposed method uses two adaptive software vsyncs (PLL) for achieving the same result.

Keywords: Android graphics system, vertical synchronization, atrace, adaptive system

Procedia PDF Downloads 298
1349 Comparison of Heuristic Methods for Solving Traveling Salesman Problem

Authors: Regita P. Permata, Ulfa S. Nuraini

Abstract:

Traveling Salesman Problem (TSP) is the most studied problem in combinatorial optimization. In simple language, TSP can be described as a problem of finding a minimum distance tour to a city, starting and ending in the same city, and exactly visiting another city. In product distribution, companies often get problems in determining the minimum distance that affects the time allocation. In this research, we aim to apply TSP heuristic methods to simulate nodes as city coordinates in product distribution. The heuristics used are sub tour reversal, nearest neighbor, farthest insertion, cheapest insertion, nearest insertion, and arbitrary insertion. We have done simulation nodes using Euclidean distances to compare the number of cities and processing time, thus we get optimum heuristic method. The results show that the optimum heuristic methods are farthest insertion and nearest insertion. These two methods can be recommended to solve product distribution problems in certain companies.

Keywords: Euclidean, heuristics, simulation, TSP

Procedia PDF Downloads 113
1348 A Parallel Approach for 3D-Variational Data Assimilation on GPUs in Ocean Circulation Models

Authors: Rossella Arcucci, Luisa D'Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

Abstract:

This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: data assimilation, GPU architectures, ocean models, parallel algorithm

Procedia PDF Downloads 396
1347 Advanced Mechatronic Design of Robot Manipulator Using Hardware-In-The-Loop Simulation

Authors: Reza Karami, Ali Akbar Ebrahimi

Abstract:

This paper discusses concurrent engineering of robot manipulators, based on the Holistic Concurrent Design (HCD) methodology and by using a hardware-in-the-loop simulation platform. The methodology allows for considering numerous design variables with different natures concurrently. It redefines the ultimate goal of design based on the notion of satisfaction, resulting in the simplification of the multi-objective constrained optimization process. It also formalizes the effect of designer’s subjective attitude in the process. To enhance modeling efficiency for both computation and accuracy, a hardware-in-the-loop simulation platform is used, which involves physical joint modules and the control unit in addition to the software modules. This platform is implemented in the HCD design architecture to reliably evaluate the design attributes and performance super criterion during the design process. The resulting overall architecture is applied to redesigning kinematic, dynamic and control parameters of an industrial robot manipulator.

Keywords: concurrent engineering, hardware-in-the-loop simulation, robot manipulator, multidisciplinary systems, mechatronics

Procedia PDF Downloads 435
1346 A Hybrid System of Hidden Markov Models and Recurrent Neural Networks for Learning Deterministic Finite State Automata

Authors: Pavan K. Rallabandi, Kailash C. Patidar

Abstract:

In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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1345 Line Heating Forming: Methodology and Application Using Kriging and Fifth Order Spline Formulations

Authors: Henri Champliaud, Zhengkun Feng, Ngan Van Lê, Javad Gholipour

Abstract:

In this article, a method is presented to effectively estimate the deformed shape of a thick plate due to line heating. The method uses a fifth order spline interpolation, with up to C3 continuity at specific points to compute the shape of the deformed geometry. First and second order derivatives over a surface are the resulting parameters of a given heating line on a plate. These parameters are determined through experiments and/or finite element simulations. Very accurate kriging models are fitted to real or virtual surfaces to build-up a database of maps. Maps of first and second order derivatives are then applied on numerical plate models to evaluate their evolving shapes through a sequence of heating lines. Adding an optimization process to this approach would allow determining the trajectories of heating lines needed to shape complex geometries, such as Francis turbine blades.

Keywords: deformation, kriging, fifth order spline interpolation, first, second and third order derivatives, C3 continuity, line heating, plate forming, thermal forming

Procedia PDF Downloads 441
1344 Diesel Engine Performance Optimization to Reduce Fuel Consumption and Emissions Issues

Authors: hadi kargar, bahador shabani

Abstract:

In this article, 16 cylinder motor combustion CFD modeling with a diameter of 165 mm and 195 mm along the way to help the FIRE software to optimize its function to work. A three-dimensional model of the processes that formed inside the cylinder made that involves mixing the fuel and air, ignition and spraying. In this three-dimensional model, all chemical species, density of air fuel spraying and spray with full profile intended to detailed results from mixing the fuel and air, igniting the ignition advance, spray, and mixed media in different times and get fit by moving the piston. Optimal selection of the model for the shape of the piston and spraying fuel specifications (including the management of spraying, the number of azhneh hole, start time of spraying and spraying angle) to achieve the best fuel consumption and minimal pollution. The spray hole 6 and 7 in three different configurations with five spraying and gives the best geometry and various performances in the simulation. 6 hole spray angle, finally spraying 72.5 degrees and two forms of spraying a better performance in comparison with other items of their own.

Keywords: spray, FIRE, CFD, optimize, diesel engine

Procedia PDF Downloads 402
1343 Optimal Hedging of a Portfolio of European Options in an Extended Binomial Model under Proportional Transaction Costs

Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

Abstract:

Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

Procedia PDF Downloads 240
1342 Development of an Erodable Matrix Drug Delivery Platform for Controled Delivery of Non Steroidal Anti Inflamatory Drugs Using Melt Granulation Process

Authors: A. Hilsana, Vinay U. Rao, M. Sudhakar

Abstract:

Even though a number of non-steroidal anti-inflammatory drugs (NSAIDS) are available with different chemistries, they share a common solubility characteristic that is they are relatively more soluble in alkaline environment and practically insoluble in acidic environment. This work deals with developing a wax matrix drug delivery platform for controlled delivery of three model NSAIDS, Diclofenac sodium (DNa), Mefenamic acid (MA) and Naproxen (NPX) using the melt granulation technique. The aim of developing the platform was to have a general understanding on how an erodible matrix system modulates drug delivery rate and extent and how it can be optimized to give a delivery system which shall release the drug as per a common target product profile (TPP). Commonly used waxes like Cetostearyl alcohol and stearic acid were used singly an in combination to achieve a TPP of not 15 to 35% in 1 hour and not less than 80% Q in 24 hours. Full factorial design of experiments was followed for optimization of the formulation.

Keywords: NSAIDs, controlled delivery, target product profile, melt granulation

Procedia PDF Downloads 322
1341 Bi-Objective Optimization for Sustainable Supply Chain Network Design in Omnichannel

Authors: Veerpaul Maan, Gaurav Mishra

Abstract:

The evolution of omnichannel has revolutionized the supply chain of the organizations by enhancing customer shopping experience. For these organizations need to develop well-integrated multiple distribution channels to leverage the benefits of omnichannel. To adopt an omnichannel system in the supply chain has resulted in structuring and reconfiguring the practices of the traditional supply chain distribution network. In this paper a multiple distribution supply chain network (MDSCN) have been proposed which integrates online giants with a local retailers distribution network in uncertain environment followed by sustainability. To incorporate sustainability, an additional objective function is added to reduce the carbon content through minimizing the travel distance of the product. Through this proposed model, customers are free to access product and services as per their choice of channels which increases their convenience, reach and satisfaction. Further, a numerical illustration is being shown along with interpretation of results to validate the proposed model.

Keywords: sustainable supply chain network, omnichannel, multiple distribution supply chain network, integrate multiple distribution channels

Procedia PDF Downloads 209
1340 Modeling and Simulation Analysis and Design of Components of the Microgrid Prototype System

Authors: Draou Azeddine, Mazin Alahmadi, Abdulrahmane Alkassem, Alamri Abdullah

Abstract:

The demand for electric power in Saudi Arabia is steadily increasing with economic growth. More power plants should be installed to increase generation capacity and meet demand. Electricity in Saudi Arabia is mainly dependent on fossil fuels, which are a major problem as they deplete natural resources and increase CO₂ emissions. In this research work, performance and techno-economic analyzes are conducted to evaluate a microgrid system based on hybrid PV/wind diesel power sources as a stand-alone system for rural electrification in Saudi Arabia. The total power flow, maximum power point tracking (MPPT) efficiency, effectiveness of the proposed control strategy, and total harmonic distortion (THD) are analyzed in MATLAB/Simulink environment. Various simulation studies have been carried out under different irradiation conditions. The sizing, optimization, and economic feasibility analysis were performed using Homer energy software.

Keywords: WIND, solar, microgrid, energy

Procedia PDF Downloads 91
1339 Model-Based Process Development for the Comparison of a Radial Riveting and Roller Burnishing Process in Mechanical Joining Technology

Authors: Tobias Beyer, Christoph Friedrich

Abstract:

Modern simulation methodology using finite element models is nowadays a recognized tool for product design/optimization. Likewise, manufacturing process design is increasingly becoming the focus of simulation methodology in order to enable sustainable results based on reduced real-life tests here as well. In this article, two process simulations -radial riveting and roller burnishing- used for mechanical joining of components are explained. In the first step, the required boundary conditions are developed and implemented in the respective simulation models. This is followed by process space validation. With the help of the validated models, the interdependencies of the input parameters are investigated and evaluated by means of sensitivity analyses. Limit case investigations are carried out and evaluated with the aid of the process simulations. Likewise, a comparison of the two joining methods to each other becomes possible.

Keywords: FEM, model-based process development, process simulation, radial riveting, roller burnishing, sensitivity analysis

Procedia PDF Downloads 93
1338 Smart Production Planning: The Case of Aluminium Foundry

Authors: Samira Alvandi

Abstract:

In the context of the circular economy, production planning aims to eliminate waste and emissions and maximize resource efficiency. Historically production planning is challenged through arrays of uncertainty and complexity arising from the interdependence and variability of products, processes, and systems. Manufacturers worldwide are facing new challenges in tackling various environmental issues such as climate change, resource depletion, and land degradation. In managing the inherited complexity and uncertainty and yet maintaining profitability, the manufacturing sector is in need of a holistic framework that supports energy efficiency and carbon emission reduction schemes. The proposed framework addresses the current challenges and integrates simulation modeling with optimization for finding optimal machine-job allocation to maximize throughput and total energy consumption while minimizing lead time. The aluminium refinery facility in western Sydney, Australia, is used as an exemplar to validate the proposed framework.

Keywords: smart production planning, simulation-optimisation, energy aware capacity planning, energy intensive industries

Procedia PDF Downloads 50
1337 Investigation of Comfort Properties of Knitted Fabrics

Authors: Mehmet Karahan, Nevin Karahan

Abstract:

Water and air permeability and thermal resistance of fabrics are the important attributes which strongly influence the thermo-physiological comfort properties of sportswear fabrics in different environmental conditions. In this work, terry and fleece fabrics were developed by varying the fiber content and areal density of fabrics. Further, the thermo-physical properties, including air permeability, water vapor permeability, and thermal resistance, of the developed fabrics were analyzed before and after washing. The multi-response optimization of thermo-physiological comfort properties was done by using principal component analysis (PCA) and Taguchi signal to noise ratio (PCA-S/N ratio) for optimal properties. It was found that the selected parameters resulted in a significant effect on thermo-physiological comfort properties of knitted fabrics. The PCA analysis showed that before wash, 100% cotton fabric with an aerial weight of 220 g.m⁻² gave optimum values of thermo-physiological comfort.

Keywords: thermo-physiological comfort, fleece knitted fabric, air permeability, water vapor transmission, cotton/polyester

Procedia PDF Downloads 96
1336 Software Verification of Systematic Resampling for Optimization of Particle Filters

Authors: Osiris Terry, Kenneth Hopkinson, Laura Humphrey

Abstract:

Systematic resampling is the most popularly used resampling method in particle filters. This paper seeks to further the understanding of systematic resampling by defining a formula made up of variables from the sampling equation and the particle weights. The formula is then verified via SPARK, a software verification language. The verified systematic resampling formula states that the minimum/maximum number of possible samples taken of a particle is equal to the floor/ceiling value of particle weight divided by the sampling interval, respectively. This allows for the creation of a randomness spectrum that each resampling method can fall within. Methods on the lower end, e.g., systematic resampling, have less randomness and, thus, are quicker to reach an estimate. Although lower randomness allows for error by having a larger bias towards the size of the weight, having this bias creates vulnerabilities to the noise in the environment, e.g., jamming. Conclusively, this is the first step in characterizing each resampling method. This will allow target-tracking engineers to pick the best resampling method for their environment instead of choosing the most popularly used one.

Keywords: SPARK, software verification, resampling, systematic resampling, particle filter, tracking

Procedia PDF Downloads 67
1335 Production Optimization through Ejector Installation at ESA Platform Offshore North West Java Field

Authors: Arii Bowo Yudhaprasetya, Ario Guritno, Agus Setiawan, Recky Tehupuring, Cosmas Supriatna

Abstract:

The offshore facilities condition of Pertamina Hulu Energi Offshore North West Java (PHE ONWJ) varies greatly from place to place, depending on the characteristics of the presently installed facilities. In some locations, such as ESA platform, gas trap is mainly caused by the occurrence of flash gas phenomenon which is known as mechanical-physical separation process of multiphase flow. Consequently, the presence of gas trap at main oil line would accumulate on certain areas result in a reduced oil stream throughout the pipeline. Any presence of discrete gaseous along continuous oil flow represents a unique flow condition under certain specific volume fraction and velocity field. From gas lift source, a benefit line is used as a motive flow for ejector which is designed to generate a syphon effect to minimize the gas trap phenomenon. Therefore, the ejector’s exhaust stream will flow to the designated point without interfering other systems.

Keywords: diffuser, ejector, flow, fluent

Procedia PDF Downloads 422
1334 Visco-Acoustic Full Wave Inversion in the Frequency Domain with Mixed Grids

Authors: Sheryl Avendaño, Miguel Ospina, Hebert Montegranario

Abstract:

Full Wave Inversion (FWI) is a variant of seismic tomography for obtaining velocity profiles by an optimization process that combine forward modelling (or solution of wave equation) with the misfit between synthetic and observed data. In this research we are modelling wave propagation in a visco-acoustic medium in the frequency domain. We apply finite differences for the numerical solution of the wave equation with a mix between usual and rotated grids, where density depends on velocity and there exists a damping function associated to a linear dissipative medium. The velocity profiles are obtained from an initial one and the data have been modeled for a frequency range 0-120 Hz. By an iterative procedure we obtain an estimated velocity profile in which are detailed the remarkable features of the velocity profile from which synthetic data were generated showing promising results for our method.

Keywords: seismic inversion, full wave inversion, visco acoustic wave equation, finite diffrence methods

Procedia PDF Downloads 447
1333 Multi-Objective Variable Neighborhood Search Algorithm to Solving Scheduling Problem with Transportation Times

Authors: Majid Khalili

Abstract:

This paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presents a new multi-objective variable neighborhood algorithm (MOVNS). A set of experimental instances are carried out to evaluate the algorithm by advanced multi-objective performance measures. The algorithm is carefully evaluated for its performance against available algorithm by means of multi-objective performance measures and statistical tools. The related results show that a variant of our proposed MOVNS provides sound performance comparing with other algorithms.

Keywords: no-wait hybrid flowshop scheduling; multi-objective variable neighborhood algorithm; makespan; total weighted tardiness

Procedia PDF Downloads 403
1332 An Efficient Process Analysis and Control Method for Tire Mixing Operation

Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

Abstract:

Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

Procedia PDF Downloads 248
1331 Standard and Processing of Photodegradable Polyethylene

Authors: Nurul-Akidah M. Yusak, Rahmah Mohamed, Noor Zuhaira Abd Aziz

Abstract:

The introduction of degradable plastic materials into agricultural sectors has represented a promising alternative to promote green agriculture and environmental friendly of modern farming practices. Major challenges of developing degradable agricultural films are to identify the most feasible types of degradation mechanisms, composition of degradable polymers and related processing techniques. The incorrect choice of degradable mechanisms to be applied during the degradation process will cause premature losses of mechanical performance and strength. In order to achieve controlled process of agricultural film degradation, the compositions of degradable agricultural film also important in order to stimulate degradation reaction at required interval of time and to achieve sustainability of the modern agricultural practices. A set of photodegradable polyethylene based agricultural film was developed and produced, following the selective optimization of processing parameters of the agricultural film manufacturing system. Example of agricultural films application for oil palm seedlings cultivation is presented.

Keywords: photodegradable polyethylene, plasticulture, processing schemes

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1330 Parameters Optimization of the Laminated Composite Plate for Sound Transmission Problem

Authors: Yu T. Tsai, Jin H. Huang

Abstract:

In this paper, the specific sound transmission loss (TL) of the laminated composite plate (LCP) with different material properties in each layer is investigated. The numerical method to obtain the TL of the LCP is proposed by using elastic plate theory. The transfer matrix approach is novelty presented for computational efficiency in solving the numerous layers of dynamic stiffness matrix (D-matrix) of the LCP. Besides the numerical simulations for calculating the TL of the LCP, the material properties inverse method is presented for the design of a laminated composite plate analogous to a metallic plate with a specified TL. As a result, it demonstrates that the proposed computational algorithm exhibits high efficiency with a small number of iterations for achieving the goal. This method can be effectively employed to design and develop tailor-made materials for various applications.

Keywords: sound transmission loss, laminated composite plate, transfer matrix approach, inverse problem, elastic plate theory, material properties

Procedia PDF Downloads 366
1329 Optimization of Multi-Zone Unconventional (Shale) Gas Reservoir Using Hydraulic Fracturing Technique

Authors: F. C. Amadi, G. C. Enyi, G. G. Nasr

Abstract:

Hydraulic fracturing is one of the most important stimulation techniques available to the petroleum engineer to extract hydrocarbons in tight gas sandstones. It allows more oil and gas production in tight reservoirs as compared to conventional means. The main aim of the study is to optimize the hydraulic fracturing as technique and for this purpose three multi-zones layer formation is considered and fractured contemporaneously. The three zones are named as Zone1 (upper zone), Zone2 (middle zone) and Zone3 (lower zone) respectively and they all occur in shale rock. Simulation was performed with Mfrac integrated software which gives a variety of 3D fracture options. This simulation process yielded an average fracture efficiency of 93.8%for the three respective zones and an increase of the average permeability of the rock system. An average fracture length of 909 ft with net height (propped height) of 210 ft (average) was achieved. Optimum fracturing results was also achieved with maximum fracture width of 0.379 inches at an injection rate of 13.01 bpm with 17995 Mscf of gas production.

Keywords: hydraulic fracturing, optimisation, shale, tight reservoir

Procedia PDF Downloads 413
1328 Optimization of Process Parameters for Peroxidase Production by Ensifer Species

Authors: Ayodeji O. Falade, Leonard V. Mabinya, Uchechukwu U. Nwodo, Anthony I. Okoh

Abstract:

Given the high utility of peroxidase in several industrial processes, the search for novel microorganisms with enhanced peroxidase production capacity is of keen interest. This study investigated the process conditions for optimum peroxidase production by Ensifer sp, new ligninolytic proteobacteria with peroxidase production potential. Also, some agricultural residues were valorized for peroxidase production under solid state fermentation. Peroxidase production was optimum at an initial medium pH 7, incubation temperature of 30 °C and agitation speed of 100 rpm using alkali lignin fermentation medium supplemented with guaiacol as the most effective inducer and ammonium sulphate as the best inorganic nitrogen. Optimum peroxidase production by Ensifer sp. was attained at 48 h with specific productivity of 12.76 ± 1.09 U mg⁻¹. Interestingly, probable laccase production was observed with optimum specific productivity of 12.76 ± 0.45 U mg⁻¹ at 72 h. The highest peroxidase yield was observed with sawdust as solid substrate under solid state fermentation. In conclusion, Ensifer sp. possesses the capacity for enhanced peroxidase production that can be exploited for various biotechnological applications.

Keywords: catalase-peroxidase, enzyme production, peroxidase, polymerase chain reaction, proteobacteria

Procedia PDF Downloads 291
1327 Geophysical Methods and Machine Learning Algorithms for Stuck Pipe Prediction and Avoidance

Authors: Ammar Alali, Mahmoud Abughaban

Abstract:

Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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1326 Voyage Analysis of a Marine Gas Turbine Engine Installed to Power and Propel an Ocean-Going Cruise Ship

Authors: Mathias U. Bonet, Pericles Pilidis, Georgios Doulgeris

Abstract:

A gas turbine-powered cruise Liner is scheduled to transport pilgrim passengers from Lagos-Nigeria to the Islamic port city of Jeddah in Saudi Arabia. Since the gas turbine is an air breathing machine, changes in the density and/or mass flow at the compressor inlet due to an encounter with variations in weather conditions induce negative effects on the performance of the power plant during the voyage. In practice, all deviations from the reference atmospheric conditions of 15 oC and 1.103 bar tend to affect the power output and other thermodynamic parameters of the gas turbine cycle. Therefore, this paper seeks to evaluate how a simple cycle marine gas turbine power plant would react under a variety of scenarios that may be encountered during a voyage as the ship sails across the Atlantic Ocean and the Mediterranean Sea before arriving at its designated port of discharge. It is also an assessment that focuses on the effect of varying aerodynamic and hydrodynamic conditions which deteriorate the efficient operation of the propulsion system due to an increase in resistance that results from some projected levels of the ship hull fouling. The investigated passenger ship is designed to run at a service speed of 22 knots and cover a distance of 5787 nautical miles. The performance evaluation consists of three separate voyages that cover a variety of weather conditions in winter, spring and summer seasons. Real-time daily temperatures and the sea states for the selected transit route were obtained and used to simulate the voyage under the aforementioned operating conditions. Changes in engine firing temperature, power output as well as the total fuel consumed per voyage including other performance variables were separately predicted under both calm and adverse weather conditions. The collated data were obtained online from the UK Meteorological Office as well as the UK Hydrographic Office websites, while adopting the Beaufort scale for determining the magnitude of sea waves resulting from rough weather situations. The simulation of the gas turbine performance and voyage analysis was effected through the use of an integrated Cranfield-University-developed computer code known as ‘Turbomatch’ and ‘Poseidon’. It is a project that is aimed at developing a method for predicting the off design behavior of the marine gas turbine when installed and operated as the main prime mover for both propulsion and powering of all other auxiliary services onboard a passenger cruise liner. Furthermore, it is a techno-economic and environmental assessment that seeks to enable the forecast of the marine gas turbine part and full load performance as it relates to the fuel requirement for a complete voyage.

Keywords: cruise ship, gas turbine, hull fouling, performance, propulsion, weather

Procedia PDF Downloads 157