Search results for: additive constraints

Authors: Manikandakumar Shunmugavel, Ashwin Polishetty, Moshe Goldberg, Junior Nomani, Guy Littlefair

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Selective laser melting (SLM), a promising additive manufacturing (AM) technology, has a huge potential in the fabrication of Ti-6Al-4V near-net shape components. However, poor surface finish of the components fabricated from this technology requires secondary machining to achieve the desired accuracy and tolerance. Therefore, a systematic understanding of the machinability of SLM fabricated Ti-6Al-4V components is paramount to improve the productivity and product quality. Considering the significance of machining in SLM fabricated Ti-6Al-4V components, this research aim is to study the influence of build orientation on machinability characteristics by performing low speed orthogonal cutting tests. In addition, the machinability of SLM fabricated Ti-6Al-4V is compared with conventionally produced wrought Ti-6Al-4V to understand the influence of SLM technology on machining. This paper is an attempt to provide evidence to the hypothesis associated that build orientation influences cutting forces, chip formation and surface integrity during orthogonal cutting of SLM Ti-6Al-4V samples. Results obtained from the low speed orthogonal cutting tests highlight the practical importance of microstructure and build orientation on machinability of SLM Ti-6Al-4V.

Keywords: Additive manufacturing, build orientation, machinability, titanium alloys (Ti-6Al-4V).

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Authors: Timothy Hinchman, Carrie Taylor

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This quantitative quasi-experimental research investigated disparities in mean and median performance among millennial soccer players. According to research, the fear of failure causes millennials to struggle with difficult jobs. The application of specified limitations has been found to increase individual productivity. The study utilized the constraint-based model of novelty (C-BMN) framework and the game performance assessment instrument (GPAI) to assess data concerning constraint-type and its impact on the productivity of 18 soccer players. Individual components cooperation and trapping had statistical significance throughout the intervention, while positioning, passing, and dribbling did not. The GPAI was statistically significant between the control and both restriction types. A two-way mixed ANOVA revealed no significant interaction between limitations and temperaments, however only 72% of individuals completed the temperament exam.

Keywords: Constraints, temperament, physical performance, GPAI.

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Authors: Kai Jin, Hyder Abdul-Razzak, Yousri Elkassabgi, Hong Zhou, Aaron Herrera

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Six Sigma is a well known discipline that reduces variation using complex statistical tools and the DMAIC model. By integrating Goldratts-s Theory of Constraints, the Five Focusing Points and System Thinking tools, Six Sigma projects can be selected where it can cause more impact in the company. This research defines an integrated model of six sigma and constraint management that shows a step-by-step guide using the original methodologies from each discipline and is evaluated in a case study from the production line of a Automobile engine monoblock V8, resulting in an increase in the line capacity from 18.7 pieces per hour to 22.4 pieces per hour, a reduction of 60% of Work-In-Process and a variation decrease of 0.73%.

Keywords: Constraint Management, Manufacturing Process Improvement, Six Sigma, System Thinking.

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Authors: Abdulmajeed Dabwan, Saqib Anwar, Ali Al-Samhan

Abstract:

Electron Beam Melting (EBM) is a metal powder bed-based Additive Manufacturing (AM) technology, which uses computer-controlled electron beams to create fully dense three-dimensional near-net-shaped parts from metal powder. It gives the ability to produce any complex parts directly from a computer-aided design (CAD) model without tools and dies, and with a variety of materials. However, the quality of the surface finish in EBM process has limitations to meeting the performance requirements of additively manufactured components. The aim of this study is to investigate the cutting forces induced during milling Ti6Al4V produced by EBM as well as the surface quality of the milled surfaces. The effects of cutting speed and radial depth of cut on the cutting forces, surface roughness, and surface morphology were investigated. The results indicated that the cutting speed was found to be proportional to the resultant cutting force at any cutting conditions while the surface roughness improved significantly with the increase in cutting speed and radial depth of cut.

Keywords: Electron beam melting, additive manufacturing, Ti6Al4V, surface morphology.

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Authors: K. Rattawan, W. Intagun, W. Kanoksilapatham

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Objective of this research is to study effect of coffee grounds on physical and heating value properties of sugarcane bagasse pellets. The coffee grounds were tested as an additive for pelletizing process of bagasse pellets. Pelletizing was performed using a Flat–die pellet mill machine. Moisture content of raw materials was controlled at 10-13%. Die temperature range during the process was 75-80 ^oC. Physical characteristics (bulk density and durability) of the bagasse pellet and pellets with 1-5% coffee ground were determined following the standard assigned by the Pellet Fuel Institute (PFI). The results revealed increasing values of 648±3.4, 659 ± 3.1, 679 ± 3.3 and 685 ± 3.1 kg/m³ (for pellet bulk density); and 98.7 ± 0.11, 99.2 ± 0.26, 99.3 ± 0.19 and 99.4 ± 0.07% (for pellet durability), respectively. In addition, the heating values of the coffee ground supplemented pellets (15.9 ± 1.16, 17.0 ± 1.23 and 18.8 ± 1.34 MJ/kg) were improved comparing to the non-supplemented control (14.9 ± 1.14 MJ/kg), respectively. The results indicated that both the bulk density and durability values of the bagasse pellets were increased with the increasing proportion of the coffee ground additive.

Keywords: Bagasse, coffee grounds, pelletizing, heating value, sugar cane bagasse.

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Authors: A. Azadeh, Z. Raoofi

Abstract:

Natural gas, as one of the most important sources of energy for many of the industrial and domestic users all over the world, has a complex, huge supply chain which is in need of heavy investments in all the phases of exploration, extraction, production, transportation, storage and distribution. The main purpose of supply chain is to meet customers’ need efficiently and with minimum cost. In this study, with the aim of minimizing economic costs, different levels of natural gas supply chain in the form of a multi-echelon, multi-period fuzzy linear programming have been modeled. In this model, different constraints including constraints on demand satisfaction, capacity, input/output balance and presence/absence of a path have been defined. The obtained results suggest efficiency of the recommended model in optimal allocation and reduction of supply chain costs.

Keywords: Cost Approach, Fuzzy Theory, Linear Programming, Natural Gas Supply Chain.

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Authors: Zarabizan Zakaria, Syuhaida Ismail, Aminah Md Yusof

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Project management process starts from the planning stage up to the stage of completion (handover of buildings, preparation of the final accounts and the closing balance). Seeing as this process is not easy to be implemented efficiently and effectively, the issue of unsuccessful delivery as per contract in construction has become a major problem for construction projects. These issues have been blamed mainly on inefficient traditional construction practices that continue to dominate the current industry. This is due to several factors, such as environments of construction technology, sophisticated design and customer demand, that are constantly changing and influencing, either directly or indirectly, to the practice of management. Among the identified influences are physical environment, social environment, information environment, political and moral atmosphere. Therefore, this paper is emerged to determine the fundamental variables in the final account closing success in construction project. This aim can be achieved via its objectives of identifying the key constraints to the closing of final accounts in construction projects in Malaysia, investigating solutions to the identified constraints and analysing the relative levels of impact of the identified constraints. It is expected that this paper provides effective measures to avoid or at least reduce the problems in final account closing to the optimum level. It is also anticipated that the finding or outcome reported in this paper could address the unsuccessful contributors in final account closing and define tools for their mitigation for the better development of construction project.

Keywords: Fundamental variables, closing of final account, construction project, Malaysia.

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Authors: Shilpesh R. Rajpurohit, Harshit K. Dave

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Additive manufacturing gains the popularity in recent times, due to its capability to create prototype as well functional as end use product directly from CAD data without any specific requirement of tooling. Fused deposition modeling (FDM) is one of the widely used additive manufacturing techniques that are used to create functional end use part of polymer that is comparable with the injection-molded parts. FDM printed part has an application in various fields such as automobile, aerospace, medical, electronic, etc. However, application of FDM part is greatly affected by poor mechanical properties. Proper selection of the process parameter could enhance the mechanical performance of the printed part. In the present study, experimental investigation has been carried out to study the behavior of the mechanical performance of the printed part with respect to process variables. Three process variables viz. raster angle, raster width and layer height have been varied to understand its effect on tensile strength. Further, effect of process variables on fractured surface has been also investigated.

Keywords: 3D printing, fused deposition modeling, layer height, raster angle, raster width, tensile strength.

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Authors: S. Kahvecioglu, A. Karamancioglu, A. Yazici

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In this paper, a nonlinear model predictive swing-up and stabilizing sliding controller is proposed for an inverted pendulum-cart system. In the swing up phase, the nonlinear model predictive control is formulated as a nonlinear programming problem with energy based objective function. By solving this problem at each sampling instant, a sequence of control inputs that optimize the nonlinear objective function subject to various constraints over a finite horizon are obtained. Then, this control drives the pendulum to a predefined neighborhood of the upper equilibrium point, at where sliding mode based model predictive control is used to stabilize the systems with the specified constraints. It is shown by the simulations that, due to the way of formulating the problem, short horizon lengths are sufficient for attaining the swing up goal.

Keywords: Inverted pendulum, model predictive control, swingup, stabilization.

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Authors: Seham Ghalwash, Ayman Ismail

Abstract:

Resources are crucial to the development and sustainability of social ventures. Thus, resources and resources scarcity are central concepts to study and understand the phenomenon of social entrepreneurship specially in developing countries where resources are very limited. Social entrepreneurs in developing countries face bigger challenges because financial resources are scarce. The empirical findings in this paper suggest that social enterprises in poor resources environments survive and grow because of the existence of social and human capitals in which they serve as prerequisites for the physical resources required for sustainability. This research paper explores how governments and policymakers might take nativities to support and foster social entrepreneurial activities in a resource-constraints environment reflecting on the experiences of Egypt-based social enterprises.

Keywords: Social ventures, financial constraints, intangible resources, scarce resources, legitimacy, developing countries, Egypt.

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Authors: Steven W. Su , Hung Nguyen, Rob Jarman, Joe Zhu, David Lowe, Peter McLean, Shoudong Huang, Nghia T. Nguyen, Russell Nicholson, Kaili Weng

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This paper proposed a nonlinear model predictive control (MPC) method for the control of gantry crane. One of the main motivations to apply MPC to control gantry crane is based on its ability to handle control constraints for multivariable systems. A pre-compensator is constructed to compensate the input nonlinearity (nonsymmetric dead zone with saturation) by using its inverse function. By well tuning the weighting function matrices, the control system can properly compromise the control between crane position and swing angle. The proposed control algorithm was implemented for the control of gantry crane system in System Control Lab of University of Technology, Sydney (UTS), and achieved desired experimental results.

Keywords: Model Predictive Control, Control constraints, Input nonlinearity compensation, Overhead gantry crane.

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Authors: Svetlana Saksonova

Abstract:

Every commercial bank optimises its asset portfolio depending on the profitability of assets and chosen or imposed constraints. This paper proposes and applies a stylized model for optimising banks' asset and liability structure, reflecting profitability of different asset categories and their risks as well as costs associated with different liability categories and reserve requirements. The level of detail for asset and liability categories is chosen to create a suitably parsimonious model and to include the most important categories in the model. It is shown that the most appropriate optimisation criterion for the model is the maximisation of the ratio of net interest income to assets. The maximisation of this ratio is subject to several constraints. Some are accounting identities or dictated by legislative requirements; others vary depending on the market objectives for a particular bank. The model predicts variable amount of assets allocated to loan provision.

Keywords: asset structure, commercial bank, model, optimisation

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Authors: Marwa H. Mahmoud, Ferial M. Abu-Salem

Abstract:

Soy protein is a common ingredient added to processed meats to enhance its functional characteristics. In our study, soybean products (fermented soy Natto and protein hydrolysate) containing hydrolyzed peptides and amino acids, with or without ascorbic acid were added to burger in order to improve its quality characteristics. Results showed that soy additives significantly increased moisture and protein content and reduced (P < 0.05) fat values. Ash content did not affect with Natto additive. Color tools, lightness and yellowness were higher (P<0.05) for the samples with added soybean products (with or without ascorbic acid), while redness decreased. Both of protein hydrolysate and ascorbic acid increased the softiness while, Natto additive increased the hardness of samples. Natto & protein hydrolysate additives increased the total volatile basic nitrogen while, samples with ascorbic acid decreased TVBN values at significant levels. Also, soy additives were improved both of cooking quality and sensory evaluation of the burger in order to prove that soy products actually affect the quality characteristics of meat products.

Keywords: Burger, protein hydrolysate, fermented soy Natto, quality characterization.

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Authors: I. A. Farhat

Abstract:

The The dynamic economic dispatch (DED) problem is one of the complex constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Keywords: Artificial Immune System (AIS), Dynamic Economic Dispatch (DED).

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Authors: C. Bay, A. Mahr, H. Groneberg, F. Döpper

Abstract:

Additive Manufacturing processes are becoming increasingly established in the industry for the economic production of complex prototypes and functional components. Laser beam melting (LBM), the most frequently used Additive Manufacturing technology for metal parts, has been gaining in industrial importance for several years. The LBM process chain – from material storage to machine set-up and component post-processing – requires many manual operations. These steps often depend on the manufactured component and are therefore not standardized. These operations are often not performed in a standardized manner, but depend on the experience of the machine operator, e.g., levelling of the build plate and adjusting the first powder layer in the LBM machine. This lack of standardization limits the reproducibility of the component quality. When processing metal powders with inhalable and alveolar particle fractions, the machine operator is at high risk due to the high reactivity and the toxic (e.g., carcinogenic) effect of the various metal powders. Faulty execution of the operation or unintentional omission of safety-relevant steps can impair the health of the machine operator. In this paper, all the steps of the LBM process chain are first analysed in terms of their influence on the two aforementioned challenges: reproducibility and work safety. Standardization to avoid errors increases the reproducibility of component quality as well as the adherence to and correct execution of safety-relevant operations. The corresponding lean method 5S will therefore be applied, in order to develop approaches in the form of recommended actions that standardize the work processes. These approaches will then be evaluated in terms of ease of implementation and their potential for improving reproducibility and work safety. The analysis and evaluation showed that sorting tools and spare parts as well as standardizing the workflow are likely to increase reproducibility. Organizing the operational steps and production environment decreases the hazards of material handling and consequently improves work safety.

Keywords: Additive manufacturing, lean production, reproducibility, work safety.

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Authors: P. Chultheera, T. Rirksomboon, S. Kulprathipanja, C. Liu, W. Chinsirikul, N. Kerddonfag

Abstract:

Gas separation by selective transport through polymeric membranes is one of the rapid growing branches of membrane technology. However, the tradeoff between the permeability and selectivity is one of the critical challenges encountered by pure polymer membranes, which in turn limits their large-scale application. To enhance gas separation performances, mixed matrix membranes (MMMs) have been developed. In this study, MMMs were prepared by a solution-coating method and tested for CO₂/CH₄ separation through permeability and selectivity using a membrane testing unit at room temperature and a pressure of 100 psig. The fabricated MMMs were composed of silicone rubber dispersed with the activated carbon individually absorbed with polyethylene glycol (PEG) as a liquid additive. PEG emulsified silicone rubber MMMs showed superior gas separation on cellulose acetate membrane with both high permeability and selectivity compared with silicone rubber membrane and alone support membrane. However, the MMMs performed limited stability resulting from the undesirable PEG leakage. To stabilize the MMMs, PEG was then incorporated into activated carbon by adsorption. It was found that the incorporation of solid and liquid was effective to improve the separation performance of MMMs.

Keywords: Mixed matrix membrane, membrane, CO2/CH4 separation, activated carbon.

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Authors: I. A. Farhat

Abstract:

The dynamic economic dispatch (DED) problem is one of the complex constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand.  Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Keywords: Artificial Immune System (AIS), Dynamic Economic Dispatch (DED).

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Authors: S. Aziz, B. Alexander, C. Gengnagel, S. Weinzierl

Abstract:

This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the Building Information Modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.

Keywords: Acoustical design, additive manufacturing, computational design, multimodal optimization.

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Authors: Mohamad Mahdavi

Abstract:

Most of the real queuing systems include special properties and constraints, which can not be analyzed directly by using the results of solved classical queuing models. Lack of Markov chains features, unexponential patterns and service constraints, are the mentioned conditions. This paper represents an applied general algorithm for analysis and optimizing the queuing systems. The algorithm stages are described through a real case study. It is consisted of an almost completed non-Markov system with limited number of customers and capacities as well as lots of common exception of real queuing networks. Simulation is used for optimizing this system. So introduced stages over the following article include primary modeling, determining queuing system kinds, index defining, statistical analysis and goodness of fit test, validation of model and optimizing methods of system with simulation.

Keywords: Estimation, queuing system, simulation model, probability distribution, non-Markov chain.

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Authors: Mehmet Bozca

Abstract:

Singular value decomposition based optimisation of geometric design parameters of a 5-speed gearbox is studied. During the optimisation, a four-degree-of freedom torsional vibration model of the pinion gear-wheel gear system is obtained and the minimum singular value of the transfer matrix is considered as the objective functions. The computational cost of the associated singular value problems is quite low for the objective function, because it is only necessary to compute the largest and smallest singular values (μmax and μmin) that can be achieved by using selective eigenvalue solvers; the other singular values are not needed. The design parameters are optimised under several constraints that include bending stress, contact stress and constant distance between gear centres. Thus, by optimising the geometric parameters of the gearbox such as, the module, number of teeth and face width it is possible to obtain a light-weight-gearbox structure. It is concluded that the all optimised geometric design parameters also satisfy all constraints.

Keywords: Singular value, optimisation, gearbox, torsional vibration.

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Authors: S. Kavitha, Nirmala P. Ratchagar

Abstract:

This paper presents the novel deterministic dynamic programming approach for solving optimization problem with quadratic objective function with linear equality and inequality constraints. The proposed method employs backward recursion in which computations proceeds from last stage to first stage in a multi-stage decision problem. A generalized recursive equation which gives the exact solution of an optimization problem is derived in this paper. The method is purely analytical and avoids the usage of initial solution. The feasibility of the proposed method is demonstrated with a practical example. The numerical results show that the proposed method provides global optimum solution with negligible computation time.

Keywords: Backward recursion, Dynamic programming, Multi-stage decision problem, Quadratic objective function.

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Authors: Erik Delarue, David Bekaert, Ronnie Belmans, William D'haeseleer

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This paper presents the development of an electricity simulation model taking into account electrical network constraints, applied on the Belgian power system. The base of the model is optimizing an extensive Unit Commitment (UC) problem through the use of Mixed Integer Linear Programming (MILP). Electrical constraints are incorporated through the implementation of a DC load flow. The model encloses the Belgian power system in a 220 – 380 kV high voltage network (i.e., 93 power plants and 106 nodes). The model features the use of pumping storage facilities as well as the inclusion of spinning reserves in a single optimization process. Solution times of the model stay below reasonable values.

Keywords: Electricity generation modeling, Unit Commitment(UC), Mixed Integer Linear Programming (MILP), DC load flow.

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Authors: Abbas Alli Taghipoor Bafghi, Hosein Bakhoda, Fateme Khodaei Chegeni

Abstract:

An experimental investigation is carried out to establish the performance characteristics of a compression ignition engine while using cerium oxide nanoparticles as additive in neat diesel and diesel-biodiesel blends. In the first phase of the experiments, stability of neat diesel and diesel-biodiesel fuel blends with the addition of cerium oxide nanoparticles is analyzed. After series of experiments, it is found that the blends subjected to high speed blending followed by ultrasonic bath stabilization improves the stability. In the second phase, performance characteristics are studied using the stable fuel blends in a single cylinder four stroke engine coupled with an electrical dynamometer and a data acquisition system. The cerium oxide acts as an oxygen donating catalyst and provides oxygen for combustion. The activation energy of cerium oxide acts to burn off carbon deposits within the engine cylinder at the wall temperature and prevents the deposition of non-polar compounds on the cylinder wall results reduction in HC emissions. The tests revealed that cerium oxide nanoparticles can be used as additive in diesel and diesel-biodiesel blends to improve complete combustion of the fuel significantly.

Keywords: Diesel engine, cerium oxide, diesel-biodiesel blends, nanoparticles.

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Authors: Muhammed Ertuğrul Çeloğlu, Mehmet Yılmaz

Abstract:

In this study, apricot seed shell, walnut shell, and sawdust were chosen as biomass sources. The materials were sorted by using a sieve No. 50 and the sieved materials were subjected to pyrolysis process at 400 °C, resulting in three different biochar products. The resulting biochar products were added to the bitumen at three different rates (5%, 10% and 15%), producing modified bitumen. Penetration, softening point, rotation viscometer and dynamic shear rheometer (DSR) tests were conducted on modified binders. Thus the modified bitumen, which was obtained by using additives at 3 different rates obtained from biochar produced at 400 °C temperatures of 3 different biomass sources were compared and the effects of pyrolysis temperature and additive rates were evaluated. As a result of the conducted tests, it was determined that the rheology of the pure bitumen improved significantly as a result of the modification of the bitumen with the biochar. Additionally, with biochar additive, it was determined that the rutting parameter values obtained from softening point, viscometer and DSR tests were increased while the values in terms of penetration and phase angle decreased. It was also observed that the most effective biomass is sawdust while the least effective was ground apricot seed shell.

Keywords: Rheology, biomass, pyrolysis, biochar.

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Authors: Yu-Cheng Chou, Po Ting Lin

Abstract:

The network of delivering commodities has been an important design problem in our daily lives and many transportation applications. The delivery performance is evaluated based on the system reliability of delivering commodities from a source node to a sink node in the network. The system reliability is thus maximized to find the optimal routing. However, the design problem is not simple because (1) each path segment has randomly distributed attributes; (2) there are multiple commodities that consume various path capacities; (3) the optimal routing must successfully complete the delivery process within the allowable time constraints. In this paper, we want to focus on the design optimization of the Multi-State Flow Network (MSFN) for multiple commodities. We propose an efficient approach to evaluate the system reliability in the MSFN with respect to randomly distributed path attributes and find the optimal routing subject to the allowable time constraints. The delivery rates, also known as delivery currents, of the path segments are evaluated and the minimal-current arcs are eliminated to reduce the complexity of the MSFN. Accordingly, the correct optimal routing is found and the worst-case reliability is evaluated. It has been shown that the reliability of the optimal routing is at least higher than worst-case measure. Two benchmark examples are utilized to demonstrate the proposed method. The comparisons between the original and the reduced networks show that the proposed method is very efficient.

Keywords: Multiple Commodities, Multi-State Flow Network (MSFN), Time Constraints, Worst-Case Reliability (WCR)

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Authors: Niyati Parameswaran, Bharathi Muthu, Madiajagan Muthaiyan

Abstract:

This paper presents Qmulus- a Cloud Based GPS Model. Qmulus is designed to compute the best possible route which would lead the driver to the specified destination in the shortest time while taking into account real-time constraints. Intelligence incorporated to Qmulus-s design makes it capable of generating and assigning priorities to a list of optimal routes through customizable dynamic updates. The goal of this design is to minimize travel and cost overheads, maintain reliability and consistency, and implement scalability and flexibility. The model proposed focuses on reducing the bridge between a Client Application and a Cloud service so as to render seamless operations. Qmulus-s system model is closely integrated and its concept has the potential to be extended into several other integrated applications making it capable of adapting to different media and resources.

Keywords: Cloud Services, GPS, Real-Time Constraints, Shortest Path, System Management and Traffic Routing

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Authors: Yao-Hong Tsai

Abstract:

This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: Authentication, iris recognition, Adaboost, local binary pattern.

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Authors: Pichet Sriyanyong

Abstract:

This paper presents the application of an enhanced Particle Swarm Optimization (EPSO) combined with Gaussian Mutation (GM) for solving the Dynamic Economic Dispatch (DED) problem considering the operating constraints of generators. The EPSO consists of the standard PSO and a modified heuristic search approaches. Namely, the ability of the traditional PSO is enhanced by applying the modified heuristic search approach to prevent the solutions from violating the constraints. In addition, Gaussian Mutation is aimed at increasing the diversity of global search, whilst it also prevents being trapped in suboptimal points during search. To illustrate its efficiency and effectiveness, the developed EPSO-GM approach is tested on the 3-unit and 10-unit 24-hour systems considering valve-point effect. From the experimental results, it can be concluded that the proposed EPSO-GM provides, the accurate solution, the efficiency, and the feature of robust computation compared with other algorithms under consideration.

Keywords: Particle Swarm Optimization (PSO), GaussianMutation (GM), Dynamic Economic Dispatch (DED).

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Authors: Ayman A. Aly, Abdallah A. Alshnnaway

Abstract:

The general idea behind the filter is to average a pixel using other pixel values from its neighborhood, but simultaneously to take care of important image structures such as edges. The main concern of the proposed filter is to distinguish between any variations of the captured digital image due to noise and due to image structure. The edges give the image the appearance depth and sharpness. A loss of edges makes the image appear blurred or unfocused. However, noise smoothing and edge enhancement are traditionally conflicting tasks. Since most noise filtering behaves like a low pass filter, the blurring of edges and loss of detail seems a natural consequence. Techniques to remedy this inherent conflict often encompass generation of new noise due to enhancement. In this work a new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of three stages. (1) Define fuzzy sets in the input space to computes a fuzzy derivative for eight different directions (2) construct a set of IFTHEN rules by to perform fuzzy smoothing according to contributions of neighboring pixel values and (3) define fuzzy sets in the output space to get the filtered and edged image. Experimental results are obtained to show the feasibility of the proposed approach with two dimensional objects.

Keywords: Additive noise, edge preserving filtering, fuzzy image filtering, noise reduction, two dimensional mechanical images.

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Authors: J. Hajnys, M. Pagac, J. Petru, P. Stefek, J. Mesicek, J. Kratochvil

Abstract:

The new progressive method of 3D metal printing SLM (Selective Laser Melting) is increasingly expanded into the normal operation. As a result, greater demands are placed on the surface quality of the parts produced in this way. The article deals with research of selected finishing methods (tumbling, face milling, sandblasting, shot peening and brushing) and their impact on the final surface roughness. The 20 x 20 x 7 mm produced specimens using SLM additive technology on the Renishaw AM400 were subjected to testing of these finishing methods by adjusting various parameters. Surface parameters of roughness Sa, Sz were chosen as the evaluation criteria and profile parameters Ra, Rz were used as additional measurements. Optical measurement of surface roughness was performed on Alicona Infinite Focus 5. An experiment conducted to optimize the surface roughness revealed, as expected, that the best roughness parameters were achieved through a face milling operation. Tumbling is particularly suitable for 3D printing components, as tumbling media are able to reach even complex shapes and, after changing to polishing bodies, achieve a high surface gloss. Surface quality after tumbling depends on the process time. Other methods with satisfactory results are shot peening and tumbling, which should be the focus of further research.

Keywords: Additive manufacturing, selective laser melting, surface roughness, stainless steel.

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