Search results for: multi-objective particle swarm optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4754

Search results for: multi-objective particle swarm optimization

3704 Hybrid Gravity Gradient Inversion-Ant Colony Optimization Algorithm for Motion Planning of Mobile Robots

Authors: Meng Wu

Abstract:

Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.

Keywords: motion planning, gravity gradient inversion algorithm, ant colony optimization

Procedia PDF Downloads 139
3703 Optimizing the Public Policy Information System under the Environment of E-Government

Authors: Qian Zaijian

Abstract:

E-government is one of the hot issues in the current academic research of public policy and management. As the organic integration of information and communication technology (ICT) and public administration, e-government is one of the most important areas in contemporary information society. Policy information system is a basic subsystem of public policy system, its operation affects the overall effect of the policy process or even exerts a direct impact on the operation of a public policy and its success or failure. The basic principle of its operation is information collection, processing, analysis and release for a specific purpose. The function of E-government for public policy information system lies in the promotion of public access to the policy information resources, information transmission through e-participation, e-consultation in the process of policy analysis and processing of information and electronic services in policy information stored, to promote the optimization of policy information systems. However, due to many factors, the function of e-government to promote policy information system optimization has its practical limits. In the building of E-government in our country, we should take such path as adhering to the principle of freedom of information, eliminating the information divide (gap), expanding e-consultation, breaking down information silos and other major path, so as to promote the optimization of public policy information systems.

Keywords: China, e-consultation, e-democracy, e-government, e-participation, ICTs, public policy information systems

Procedia PDF Downloads 867
3702 X-Ray Diffraction and Crosslink Density Analysis of Starch/Natural Rubber Polymer Composites Prepared by Latex Compounding Method

Authors: Raymond Dominic Uzoh

Abstract:

Starch fillers were extracted from three plant sources namely amora tuber (a wild variety of Irish potato), sweet potato and yam starch and their particle size, pH, amylose, and amylopectin percentage decomposition determined accordingly by high performance liquid chromatography (HPLC). The starch was introduced into natural rubber in liquid phase (through gelatinization) by the latex compounding method and compounded according to standard method. The prepared starch/natural rubber composites was characterized by Instron Universal testing machine (UTM) for tensile mechanical properties. The composites was further characterized by x-ray diffraction and crosslink density analysis. The particle size determination showed that amora starch granules have the highest particle size (156 × 47 μm) followed by yam starch (155× 40 μm) and then the sweet potato starch (153 × 46 μm). The pH test also revealed that amora starch has a near neutral pH of 6.9, yam 6.8, and sweet potato 5.2 respectively. Amylose and amylopectin determination showed that yam starch has a higher percentage of amylose (29.68), followed by potato (22.34) and then amora starch with the lowest value (14.86) respectively. The tensile mechanical properties testing revealed that yam starch produced the best tensile mechanical properties followed by amora starch and then sweet potato starch. The structure, crystallinity/amorphous nature of the product composite was confirmed by x-ray diffraction, while the nature of crosslinking was confirmed by swelling test in toluene solvent using the Flory-Rehner approach. This research study has rendered a workable strategy for enhancing interfacial interaction between a hydrophilic filler (starch) and hydrophobic polymeric matrix (natural rubber) yielding moderately good tensile mechanical properties for further exploitation development and application in the rubber processing industry.

Keywords: natural rubber, fillers, starch, amylose, amylopectin, crosslink density

Procedia PDF Downloads 171
3701 A Deep Learning Approach for Optimum Shape Design

Authors: Cahit Perkgöz

Abstract:

Artificial intelligence has brought new approaches to solving problems in almost every research field in recent years. One of these topics is shape design and optimization, which has the possibility of applications in many fields, such as nanotechnology and electronics. A properly constructed cost function can eliminate the need for labeled data required in deep learning and create desired shapes. In this work, the network parameters are optimized differentially, which differs from traditional approaches. The methods are tested for physics-related structures and successful results are obtained. This work is supported by Eskişehir Technical University scientific research project (Project No: 20ADP090)

Keywords: deep learning, shape design, optimization, artificial intelligence

Procedia PDF Downloads 154
3700 Simulation-Based Optimization Approach for an Electro-Plating Production Process Based on Theory of Constraints and Data Envelopment Analysis

Authors: Mayada Attia Ibrahim

Abstract:

Evaluating and developing the electroplating production process is a key challenge in this type of process. The process is influenced by several factors such as process parameters, process costs, and production environments. Analyzing and optimizing all these factors together requires extensive analytical techniques that are not available in real-case industrial entities. This paper presents a practice-based framework for the evaluation and optimization of some of the crucial factors that affect the costs and production times associated with this type of process, energy costs, material costs, and product flow times. The proposed approach uses Design of Experiments, Discrete-Event Simulation, and Theory of Constraints were respectively used to identify the most significant factors affecting the production process and simulate a real production line to recognize the effect of these factors and assign possible bottlenecks. Several scenarios are generated as corrective strategies for improving the production line. Following that, data envelopment analysis CCR input-oriented DEA model is used to evaluate and optimize the suggested scenarios.

Keywords: electroplating process, simulation, design of experiment, performance optimization, theory of constraints, data envelopment analysis

Procedia PDF Downloads 100
3699 Optimization of Soybean Oil by Modified Supercritical Carbon Dioxide

Authors: N. R. Putra, A. H. Abdul Aziz, A. S. Zaini, Z. Idham, F. Idrus, M. Z. Bin Zullyadini, M. A. Che Yunus

Abstract:

The content of omega-3 in soybean oil is important in the development of infants and is an alternative for the omega-3 in fish oils. The investigation of extraction of soybean oil is needed to obtain the bioactive compound in the extract. Supercritical carbon dioxide extraction is modern and green technology to extract herbs and plants to obtain high quality extract due to high diffusivity and solubility of the solvent. The aim of this study was to obtain the optimum condition of soybean oil extraction by modified supercritical carbon dioxide. The soybean oil was extracted by using modified supercritical carbon dioxide (SC-CO2) under the temperatures of 40, 60, 80 °C, pressures of 150, 250, 350 Bar, and constant flow-rate of 10 g/min as the parameters of extraction processes. An experimental design was performed in order to optimize three important parameters of SC-CO2 extraction which are pressure (X1), temperature (X2) to achieve optimum yields of soybean oil. Box Behnken Design was applied for experimental design. From the optimization process, the optimum condition of extraction of soybean oil was obtained at pressure 338 Bar and temperature 80 °C with oil yield of 2.713 g. Effect of pressure is significant on the extraction of soybean oil by modified supercritical carbon dioxide. Increasing of pressure will increase the oil yield of soybean oil.

Keywords: soybean oil, SC-CO₂ extraction, yield, optimization

Procedia PDF Downloads 256
3698 Microvesicles in Peripheral and Uterine Blood in Women with Atypical Hyperplasia and Endometrioid Endometrial Cancer

Authors: Barbara Zapala, Marek Dziechciowski, Olaf Chmura, Monika Piwowar, Katarzyna Gawlik, Dorota Pawlicka-Gosiewska, Krzysztof Skotniczny, Bogdan Solnica, Kazimierz Pitynski

Abstract:

BACKGROUND: Endometrial cancer is one of the most common gynecologic malignancy in developed countries.We hypothesized that amount of circulating micro-particles in blood may be connected with the development of endometrial hyperplasia and endometrial cancer. The aim of this study was to measure the micro-particles amount in uterine venous blood and in peripheral venous blood in women with atypical endometrial hyperplasia and endometrioid endometrial cancer. MATERIALS AND METHODS: By using flow cytometry (BD Canto II cytometer) we measured micro-particles amount in citrate plasma samples from peripheral and uterine venous blood of women with atypical hyperplasia of endometrium or endometrial cancer. We determined the amount of total (TF+), endothelial (CD144+) and monocytic (CD14+) micro- particles. RESULTS: Here we show statistically significant higher micro-particle levels in women with atypical hyperplasia of endometrium or endometrial cancer in comparison to healthy women. Performing measurements of the amounts of total, endothelial and monocytic microparticles allow for reliable differentiation between healthy, atypical hyperplasia and endometrial cancer groups. In blood samples from uterine veins the circulating micro-particle levels were significantly different from peripheral blood samples. The micro-particle levels in uterine blood samples were 7-fold higher than in those from peripheral blood of women with both atypical hyperplasia of endometrium and endometrial cancer when compared to the control group of healthy women. CONCLUSION: These results strongly suggested that the level of circulating micro-particles may be a sign of endometrial cancer development, however the detailed study is needed focusing on molecular processes passed through this small circulating molecules.

Keywords: endometrial cancer, endometrial hyperplasia, microvesicles, uterine blood

Procedia PDF Downloads 137
3697 Characterization of Particle Charge from Aerosol Generation Process: Impact on Infrared Signatures and Material Reactivity

Authors: Erin M. Durke, Monica L. McEntee, Meilu He, Suresh Dhaniyala

Abstract:

Aerosols are one of the most important and significant surfaces in the atmosphere. They can influence weather, absorption, and reflection of light, and reactivity of atmospheric constituents. A notable feature of aerosol particles is the presence of a surface charge, a characteristic imparted via the aerosolization process. The existence of charge can complicate the interrogation of aerosol particles, so many researchers remove or neutralize aerosol particles before characterization. However, the charge is present in real-world samples, and likely has an effect on the physical and chemical properties of an aerosolized material. In our studies, we aerosolized different materials in an attempt to characterize the charge imparted via the aerosolization process and determine what impact it has on the aerosolized materials’ properties. The metal oxides, TiO₂ and SiO₂, were aerosolized expulsively and then characterized, using several different techniques, in an effort to determine the surface charge imparted upon the particles via the aerosolization process. Particle charge distribution measurements were conducted via the employment of a custom scanning mobility particle sizer. The results of the charge distribution measurements indicated that expulsive generation of 0.2 µm SiO₂ particles produced aerosols with upwards of 30+ charges on the surface of the particle. Determination of the degree of surface charging led to the use of non-traditional techniques to explore the impact of additional surface charge on the overall reactivity of the metal oxides, specifically TiO₂. TiO₂ was aerosolized, again expulsively, onto a gold-coated tungsten mesh, which was then evaluated with transmission infrared spectroscopy in an ultra-high vacuum environment. The TiO₂ aerosols were exposed to O₂, H₂, and CO, respectively. Exposure to O₂ resulted in a decrease in the overall baseline of the aerosol spectrum, suggesting O₂ removed some of the surface charge imparted during aerosolization. Upon exposure to H₂, there was no observable rise in the baseline of the IR spectrum, as is typically seen for TiO₂, due to the population of electrons into the shallow trapped states and subsequent promotion of the electrons into the conduction band. This result suggests that the additional charge imparted via aerosolization fills the trapped states, therefore no rise is seen upon exposure to H₂. Dosing the TiO₂ aerosols with CO showed no adsorption of CO on the surface, even at lower temperatures (~100 K), indicating the additional charge on the aerosol surface prevents the CO molecules from adsorbing to the TiO₂ surface. The results observed during exposure suggest that the additional charge imparted via aerosolization impacts the interaction with each probe gas.

Keywords: aerosols, charge, reactivity, infrared

Procedia PDF Downloads 124
3696 Zero Energy Buildings in Hot-Humid Tropical Climates: Boundaries of the Energy Optimization Grey Zone

Authors: Nakul V. Naphade, Sandra G. L. Persiani, Yew Wah Wong, Pramod S. Kamath, Avinash H. Anantharam, Hui Ling Aw, Yann Grynberg

Abstract:

Achieving zero-energy targets in existing buildings is known to be a difficult task requiring important cuts in the building energy consumption, which in many cases clash with the functional necessities of the building wherever the on-site energy generation is unable to match the overall energy consumption. Between the building’s consumption optimization limit and the energy, target stretches a case-specific optimization grey zone, which requires tailored intervention and enhanced user’s commitment. In the view of the future adoption of more stringent energy-efficiency targets in the context of hot-humid tropical climates, this study aims to define the energy optimization grey zone by assessing the energy-efficiency limit in the state-of-the-art typical mid- and high-rise full AC office buildings, through the integration of currently available technologies. Energy models of two code-compliant generic office-building typologies were developed as a baseline, a 20-storey ‘high-rise’ and a 7-storey ‘mid-rise’. Design iterations carried out on the energy models with advanced market ready technologies in lighting, envelope, plug load management and ACMV systems and controls, lead to a representative energy model of the current maximum technical potential. The simulations showed that ZEB targets could be achieved in fully AC buildings under an average of seven floors only by compromising on energy-intense facilities (as full AC, unlimited power-supply, standard user behaviour, etc.). This paper argues that drastic changes must be made in tropical buildings to span the energy optimization grey zone and achieve zero energy. Fully air-conditioned areas must be rethought, while smart technologies must be integrated with an aggressive involvement and motivation of the users to synchronize with the new system’s energy savings goal.

Keywords: energy simulation, office building, tropical climate, zero energy buildings

Procedia PDF Downloads 185
3695 Second Order Cone Optimization Approach to Two-stage Network DEA

Authors: K. Asanimoghadam, M. Salahi, A. Jamalian

Abstract:

Data envelopment analysis is an approach to measure the efficiency of decision making units with multiple inputs and outputs. The structure of many decision making units also has decision-making subunits that are not considered in most data envelopment analysis models. Also, the inputs and outputs of the decision-making units usually are considered desirable, while in some real-world problems, the nature of some inputs or outputs are undesirable. In this thesis, we study the evaluation of the efficiency of two stage decision-making units, where some outputs are undesirable using two non-radial models, the SBM and the ASBM models. We formulate the nonlinear ASBM model as a second order cone optimization problem. Finally, we compare two models for both external and internal evaluation approaches for two real world example in the presence of undesirable outputs. The results show that, in both external and internal evaluations, the overall efficiency of ASBM model is greater than or equal to the overall efficiency value of the SBM model, and in internal evaluation, the ASBM model is more flexible than the SBM model.

Keywords: network DEA, conic optimization, undesirable output, SBM

Procedia PDF Downloads 194
3694 Multi-Objective Optimization of the Thermal-Hydraulic Behavior for a Sodium Fast Reactor with a Gas Power Conversion System and a Loss of off-Site Power Simulation

Authors: Avent Grange, Frederic Bertrand, Jean-Baptiste Droin, Amandine Marrel, Jean-Henry Ferrasse, Olivier Boutin

Abstract:

CEA and its industrial partners are designing a gas Power Conversion System (PCS) based on a Brayton cycle for the ASTRID Sodium-cooled Fast Reactor. Investigations of control and regulation requirements to operate this PCS during operating, incidental and accidental transients are necessary to adapt core heat removal. To this aim, we developed a methodology to optimize the thermal-hydraulic behavior of the reactor during normal operations, incidents and accidents. This methodology consists of a multi-objective optimization for a specific sequence, whose aim is to increase component lifetime by reducing simultaneously several thermal stresses and to bring the reactor into a stable state. Furthermore, the multi-objective optimization complies with safety and operating constraints. Operating, incidental and accidental sequences use specific regulations to control the thermal-hydraulic reactor behavior, each of them is defined by a setpoint, a controller and an actuator. In the multi-objective problem, the parameters used to solve the optimization are the setpoints and the settings of the controllers associated with the regulations included in the sequence. In this way, the methodology allows designers to define an optimized and specific control strategy of the plant for the studied sequence and hence to adapt PCS piloting at its best. The multi-objective optimization is performed by evolutionary algorithms coupled to surrogate models built on variables computed by the thermal-hydraulic system code, CATHARE2. The methodology is applied to a loss of off-site power sequence. Three variables are controlled: the sodium outlet temperature of the sodium-gas heat exchanger, turbomachine rotational speed and water flow through the heat sink. These regulations are chosen in order to minimize thermal stresses on the gas-gas heat exchanger, on the sodium-gas heat exchanger and on the vessel. The main results of this work are optimal setpoints for the three regulations. Moreover, Proportional-Integral-Derivative (PID) control setting is considered and efficient actuators used in controls are chosen through sensitivity analysis results. Finally, the optimized regulation system and the reactor control procedure, provided by the optimization process, are verified through a direct CATHARE2 calculation.

Keywords: gas power conversion system, loss of off-site power, multi-objective optimization, regulation, sodium fast reactor, surrogate model

Procedia PDF Downloads 309
3693 Superoxide Dismutase Activity of Male Rats after Administration of Extract and Nanoparticle of Ginger Torch Flower

Authors: Tresna Lestari, Tita Nofianti, Ade Yeni Aprilia, Lilis Tuslinah, Ruswanto Ruswanto

Abstract:

Nanoparticle formulation is often used to improve drug absorptivity, thus increasing the sharpness of the action. Ginger torch flower extract was formulated into nanoparticle form using poloxamer 1, 3 and 5%. The nanoparticle was then characterized by its particle size, polydispersity index, zeta potential, entrapment efficiency and morphological form by SEM. The result shows that nanoparticle formulations have particle size 134.7-193.1 nm, polydispersity index less than 0.5 for all formulations, zeta potential -41.0 - (-24.3) mV and entrapment efficiency 89.93-97.99 against flavonoid content with a soft surface and spherical form of particles. Methanolic extract of ginger torch flower could enhance superoxide dismutase activity by 1,3183 U/mL in male rats. Nanoparticle formulation of ginger torch extract is expected to increase the capability of the drug to enhance superoxide dismutase activity.

Keywords: superoxide dismutase, ginger torch flower, nanoparticle, poloxamer

Procedia PDF Downloads 159
3692 Optimization of Black-Litterman Model for Portfolio Assets Allocation

Authors: A. Hidalgo, A. Desportes, E. Bonin, A. Kadaoui, T. Bouaricha

Abstract:

Present paper is concerned with portfolio management with Black-Litterman (B-L) model. Considered stocks are exclusively limited to large companies stocks on US market. Results obtained by application of the model are presented. From analysis of collected Dow Jones stock data, remarkable explicit analytical expression of optimal B-L parameter τ, which scales dispersion of normal distribution of assets mean return, is proposed in terms of standard deviation of covariance matrix. Implementation has been developed in Matlab environment to split optimization in Markovitz sense from specific elements related to B-L representation.

Keywords: Black-Litterman, Markowitz, market data, portfolio manager opinion

Procedia PDF Downloads 260
3691 Optimization of the Flexural Strength of Biocomposites Samples Reinforced with Resin for Engineering Applications

Authors: Stephen Akong Takim

Abstract:

This study focused on the optimization of the flexural strength of bio-composite samples of palm kernel, whelks, clams, periwinkles shells and bamboo fiber reinforced with resin for engineering applications. The aim of the study was to formulate different samples of bio-composite reinforced with resin for engineering applications and to evaluate the flexural strength of the fabricated composite. The hand lay-up technique was used for the composites produced by incorporating different percentage compositions of the shells/fiber (10%, 15%, 20%, 25% and 30%) into varied proportions of epoxy resin and catalyst. The cured samples, after 24 hours, were subjected to tensile, impact, flexural and water absorption tests. The experiments were conducted using the Taguchi optimization method L25 (5x5) with five design parameters and five level combinations in Minitab 18 statistical software. The results showed that the average value of flexural was 114.87MPa when compared to the unreinforced 72.33MPa bio-composite. The study recommended that agricultural waste, like palm kernel shells, whelk shells, clams, periwinkle shells and bamboo fiber, should be converted into important engineering applications.

Keywords: bio-composite, resin, palm kernel shells, welk shells, periwinkle shells, bamboo fiber, Taguchi techniques and engineering application

Procedia PDF Downloads 77
3690 Thermodynamic Properties of Calcium-Containing DPPA and DPPC Liposomes

Authors: Tamaz Mdzinarashvili, Mariam Khvedelidze, Eka Shekiladze, Salome Chinchaladze, Mariam Mdzinarashvili

Abstract:

The work is about the preparation of calcium-containing 1,2-Dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and 1,2-Dipalmitoyl-sn-glycero-3-phosphatidic acid (DPPA) and their calorimetric study. In order to prepare these complex liposomes, for the first stage it is necessary for ligands and lipids to directly interact, followed by the addition of pH-buffered water or solvent at temperatures slightly above the liposome phase transition temperature. The resulting mixture is briefly but vigorously shaken and then transformed into liposomes of the desired size using an extruder. Particle sizing and calorimetry were used to evaluate liposome formation. We determined the possible structure of calcium-containing liposomes made by our new technology and determined their thermostability. The paper provides calculations showing how many phospholipid molecules are required to make a 200 nm diameter liposome. Calculations showed that 33x10³ lipid molecules are needed to prepare one DPPA and DPPC liposome. Based on the calorimetric experiments, we determined that the structure of uncomplexed DPPA liposomes is unilaminar (one double layer), while DPPC liposome is a nanoparticle with a multilaminar (multilayer) structure. This was determined by the cooperativity of the heat absorption peak. Calorimetric studies of calcium liposomes made by our technology showed that calcium ions are placed in the multilaminar structure of the DPPC liposome. Calcium ions also formed a complex in the DPPA liposome structure, moreover, calcium made the DPPA liposome multilaminar, since the cooperative narrow heat absorption peak was transformed into a three-peak heat absorption peak. Since both types of liposomes in complex with calcium ions present a multilaminar structure, where the number of lipid heads in one particle is large, the number of calcium ions in one particle will also be increased. That makes it possible to use these nanoparticles as transporters of a large amount of calcium ions in a living organism.

Keywords: calcium, liposomes, thermodynamic parameters, calorimetry

Procedia PDF Downloads 49
3689 An Evaluation of the Feasibility of Several Industrial Wastes and Natural Materials as Precursors for the Production of Alkali Activated Materials

Authors: O. Alelweet, S. Pavia

Abstract:

In order to face current compelling environmental problems affecting the planet, the construction industry needs to adapt. It is widely acknowledged that there is a need for durable, high-performance, low-greenhouse gas emission binders that can be used as an alternative to Portland cement (PC) to lower the environmental impact of construction. Alkali activated materials (AAMs) are considered a more sustainable alternative to PC materials. The binders of AAMs result from the reaction of an alkali metal source and a silicate powder or precursor which can be a calcium silicate or an aluminosilicate-rich material. This paper evaluates the particle size, specific surface area, chemical and mineral composition and amorphousness of silicate materials (most industrial waste locally produced in Ireland and Saudi Arabia) to develop alkali-activated binders that can replace PC resources in specific applications. These include recycled ceramic brick, bauxite, illitic clay, fly ash and metallurgical slag. According to the results, the wastes are reactive and comply with building standards requirements. The study also evidenced that the reactivity of the Saudi bauxite (with significant kaolinite) can be enhanced on thermal activation; and high calcium in the slag will promote reaction; which should be possible with low alkalinity activators. The wastes evidenced variable water demands that will be taken into account for mixing with the activators. Finally, further research is proposed to further determine the reactive fraction of the clay-based precursors.

Keywords: alkali activated materials, alkali-activated binders, sustainable building materials, recycled ceramic brick, bauxite, red mud, clay, fly ash, metallurgical slags, particle size, chemical and mineral composition and amorphousness, water demand, particle density

Procedia PDF Downloads 126
3688 Capacity Optimization in Cooperative Cognitive Radio Networks

Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

Abstract:

Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: cooperative networks, normalized capacity, sensing time

Procedia PDF Downloads 636
3687 Improving Fused Deposition Modeling Efficiency: A Parameter Optimization Approach

Authors: Wadea Ameen

Abstract:

Rapid prototyping (RP) technology, such as fused deposition modeling (FDM), is gaining popularity because it can produce functioning components with intricate geometric patterns in a reasonable amount of time. A multitude of process variables influences the quality of manufactured parts. In this study, four important process parameters such as layer thickness, model interior fill style, support fill style and orientation are considered. Their influence on three responses, such as build time, model material, and support material, is studied. Experiments are conducted based on factorial design, and the results are presented.

Keywords: fused deposition modeling, factorial design, optimization, 3D printing

Procedia PDF Downloads 23
3686 Optimization of Machining Parameters by Using Cryogenic Media

Authors: Shafqat Wahab, Waseem Tahir, Manzoor Ahmad, Sarfraz Khan, M. Azam

Abstract:

Optimization and analysis of tool flank wear width and surface finish of alloy steel rods are studied in the presence of cryogenic media (LN2) by using Tungsten Carbide Insert (CNMG 120404- WF 4215). Robust design concept of Taguchi L9(34) method and ANOVA is applied to determine the contribution of key cutting parameters and their optimum conditions. Through analysis, it revealed that cryogenic impact is more significant in reduction of the tool flank wear width while surface finish is mostly dependent on feed rate.

Keywords: turning, cryogenic fluid, liquid nitrogen, flank wear, surface roughness, taguchi

Procedia PDF Downloads 666
3685 The Reduction of CO2 Emissions Level in Malaysian Transportation Sector: An Optimization Approach

Authors: Siti Indati Mustapa, Hussain Ali Bekhet

Abstract:

Transportation sector represents more than 40% of total energy consumption in Malaysia. This sector is a major user of fossils based fuels, and it is increasingly being highlighted as the sector which contributes least to CO2 emission reduction targets. Considering this fact, this paper attempts to investigate the problem of reducing CO2 emission using linear programming approach. An optimization model which is used to investigate the optimal level of CO2 emission reduction in the road transport sector is presented. In this paper, scenarios have been used to demonstrate the emission reduction model: (1) utilising alternative fuel scenario, (2) improving fuel efficiency scenario, (3) removing fuel subsidy scenario, (4) reducing demand travel, (5) optimal scenario. This study finds that fuel balancing can contribute to the reduction of the amount of CO2 emission by up to 3%. Beyond 3% emission reductions, more stringent measures that include fuel switching, fuel efficiency improvement, demand travel reduction and combination of mitigation measures have to be employed. The model revealed that the CO2 emission reduction in the road transportation can be reduced by 38.3% in the optimal scenario.

Keywords: CO2 emission, fuel consumption, optimization, linear programming, transportation sector, Malaysia

Procedia PDF Downloads 424
3684 Performances Analysis and Optimization of an Adsorption Solar Cooling System

Authors: Nadia Allouache

Abstract:

The use of solar energy in cooling systems is an interesting alternative to the increasing demand of energy in the world and more specifically in southern countries where the needs of refrigeration and air conditioning are tremendous. This technique is even more attractive with regards to environmental issues. This study focuses on performances analysis and optimization of solar reactor of an adsorption cooling machine working with activated carbon-methanol pair. The modeling of the adsorption cooling machine requires the resolution of the equation describing the energy and mass transfer in the tubular adsorber that is the most important component of the machine. The results show the poor heat conduction inside the porous medium and the resistance between the metallic wall and the bed engender the important temperature gradient and a great difference between the metallic wall and the bed temperature; this is considered as the essential causes decreasing the performances of the machine. For fixed conditions of functioning, the total desorbed mass presents a maximum for an optimal value of the height of the adsorber; this implies the existence of an optimal dimensioning of the adsorber.

Keywords: solar cooling system, performances Analysis, optimization, heat and mass transfer, activated carbon-methanol pair, numerical modeling

Procedia PDF Downloads 440
3683 Layout Optimization of a Start-up COVID-19 Testing Kit Manufacturing Facility

Authors: Poojan Vora, Hardik Pancholi, Sanket Tajane, Harsh Shah, Elias Keedy

Abstract:

The global COVID-19 pandemic has affected the industry drastically in many ways. Even though the vaccine is being distributed quickly and despite the decreasing number of positive cases, testing is projected to remain a key aspect of the ‘new normal’. Improving existing plant layout and improving safety within the facility are of great importance in today’s industries because of the need to ensure productivity optimization and reduce safety risks. In practice, it is essential for any manufacturing plant to reduce nonvalue adding steps such as the movement of materials and rearrange similar processes. In the current pandemic situation, optimized layouts will not only increase safety measures but also decrease the fixed cost per unit manufactured. In our case study, we carefully studied the existing layout and the manufacturing steps of a new Texas start-up company that manufactures COVID testing kits. The effects of production rate are incorporated with the computerized relative allocation of facilities technique (CRAFT) algorithm to improve the plant layout and estimate the optimization parameters. Our work reduces the company’s material handling time and increases their daily production. Real data from the company are used in the case study to highlight the importance of colleges in fostering small business needs and improving the collaboration between college researchers and industries by using existing models to advance best practices.

Keywords: computerized relative allocation of facilities technique, facilities planning, optimization, start-up business

Procedia PDF Downloads 139
3682 Electron Beam Melting Process Parameter Optimization Using Multi Objective Reinforcement Learning

Authors: Michael A. Sprayberry, Vincent C. Paquit

Abstract:

Process parameter optimization in metal powder bed electron beam melting (MPBEBM) is crucial to ensure the technology's repeatability, control, and industry-continued adoption. Despite continued efforts to address the challenges via the traditional design of experiments and process mapping techniques, there needs to be more successful in an on-the-fly optimization framework that can be adapted to MPBEBM systems. Additionally, data-intensive physics-based modeling and simulation methods are difficult to support by a metal AM alloy or system due to cost restrictions. To mitigate the challenge of resource-intensive experiments and models, this paper introduces a Multi-Objective Reinforcement Learning (MORL) methodology defined as an optimization problem for MPBEBM. An off-policy MORL framework based on policy gradient is proposed to discover optimal sets of beam power (P) – beam velocity (v) combinations to maintain a steady-state melt pool depth and phase transformation. For this, an experimentally validated Eagar-Tsai melt pool model is used to simulate the MPBEBM environment, where the beam acts as the agent across the P – v space to maximize returns for the uncertain powder bed environment producing a melt pool and phase transformation closer to the optimum. The culmination of the training process yields a set of process parameters {power, speed, hatch spacing, layer depth, and preheat} where the state (P,v) with the highest returns corresponds to a refined process parameter mapping. The resultant objects and mapping of returns to the P-v space show convergence with experimental observations. The framework, therefore, provides a model-free multi-objective approach to discovery without the need for trial-and-error experiments.

Keywords: additive manufacturing, metal powder bed fusion, reinforcement learning, process parameter optimization

Procedia PDF Downloads 94
3681 A New Technology for Metformin Hydrochloride Mucoadhesive Microparticles Preparation Utilizing BÜCHI Nano-Spray Dryer B-90

Authors: Tamer M. Shehata

Abstract:

Objective: Currently, mucoadhesive microparticles acquired a high interest in both research and pharmaceutical technology fields. Recently, BÜCHI lunched its latest fourth generation nano spray dryer B-90 used for nanoparticle production. B-90 offers an elegant technology combined particle engineering and drying in one step. In our laboratory, we successfully developed a new formulation for metformin hydrochloride, mucoadhesive microparticles utilizing B-90 technology for treatment of type 2-diabetis. Method: Gelatin or sodium alginate, natural occurring polymers with mucoadhesive properties, solely or in combination was used in our formulation trials. Preformulation studies (atomization head mesh size, flow rate, head temperature, polymer solution viscosity and surface tension) and postformulation characters (particle size, flowability, surface scan and dissolution profile) were evaluated. Finally, hypoglycemic effect of the selected formula was evaluated in streptozotocin-induced diabetic rats. Spray head with 7 µm hole, flow rate of 3.5 mL/min and head temperature 120 ºC were selected. Polymer viscosity was less than 11.5 cP with surface tension less than 70.1 dyne/cm. Result: Discrete, non aggregated particles and free flowing powders with particle size was less than 2000 nm were obtained. Gelatin and sodium alginate combination in ratio 1:3 were successfully sustained the in vitro release profile of the drug. Hypoglycemic evaluation of the previous formula, showed a significant reduction of blood glucose level over 24 h. Conclusion: B-90 technology can open a new era of , mucoadhesive microparticles preparation offering convenient dosage form that can enhance compliance of type 2 diabetic patients.

Keywords: mucoadhesive, microparticles, technology, diabetis

Procedia PDF Downloads 295
3680 Portfolio Selection with Active Risk Monitoring

Authors: Marc S. Paolella, Pawel Polak

Abstract:

The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The latter, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.

Keywords: comfort, financial crises, portfolio optimization, risk monitoring

Procedia PDF Downloads 525
3679 Parameter Optimization and Thermal Simulation in Laser Joining of Coach Peel Panels of Dissimilar Materials

Authors: Masoud Mohammadpour, Blair Carlson, Radovan Kovacevic

Abstract:

The quality of laser welded-brazed (LWB) joints were strongly dependent on the main process parameters, therefore the effect of laser power (3.2–4 kW), welding speed (60–80 mm/s) and wire feed rate (70–90 mm/s) on mechanical strength and surface roughness were investigated in this study. The comprehensive optimization process by means of response surface methodology (RSM) and desirability function was used for multi-criteria optimization. The experiments were planned based on Box– Behnken design implementing linear and quadratic polynomial equations for predicting the desired output properties. Finally, validation experiments were conducted on an optimized process condition which exhibited good agreement between the predicted and experimental results. AlSi3Mn1 was selected as the filler material for joining aluminum alloy 6022 and hot-dip galvanized steel in coach peel configuration. The high scanning speed could control the thickness of IMC as thin as 5 µm. The thermal simulations of joining process were conducted by the Finite Element Method (FEM), and results were validated through experimental data. The Fe/Al interfacial thermal history evidenced that the duration of critical temperature range (700–900 °C) in this high scanning speed process was less than 1 s. This short interaction time leads to the formation of reaction-control IMC layer instead of diffusion-control mechanisms.

Keywords: laser welding-brazing, finite element, response surface methodology (RSM), multi-response optimization, cross-beam laser

Procedia PDF Downloads 352
3678 Optimization Model for Identification of Assembly Alternatives of Large-Scale, Make-to-Order Products

Authors: Henrik Prinzhorn, Peter Nyhuis, Johannes Wagner, Peter Burggräf, Torben Schmitz, Christina Reuter

Abstract:

Assembling large-scale products, such as airplanes, locomotives, or wind turbines, involves frequent process interruptions induced by e.g. delayed material deliveries or missing availability of resources. This leads to a negative impact on the logistical performance of a producer of xxl-products. In industrial practice, in case of interruptions, the identification, evaluation and eventually the selection of an alternative order of assembly activities (‘assembly alternative’) leads to an enormous challenge, especially if an optimized logistical decision should be reached. Therefore, in this paper, an innovative, optimization model for the identification of assembly alternatives that addresses the given problem is presented. It describes make-to-order, large-scale product assembly processes as a resource constrained project scheduling (RCPS) problem which follows given restrictions in practice. For the evaluation of the assembly alternative, a cost-based definition of the logistical objectives (delivery reliability, inventory, make-span and workload) is presented.

Keywords: assembly scheduling, large-scale products, make-to-order, optimization, rescheduling

Procedia PDF Downloads 459
3677 Comparative Analysis of in vitro Release profile for Escitalopram and Escitalopram Loaded Nanoparticles

Authors: Rashi Rajput, Manisha Singh

Abstract:

Escitalopram oxalate (ETP), an FDA approved antidepressant drug from the category of SSRI (selective serotonin reuptake inhibitor) and is used in treatment of general anxiety disorder (GAD), major depressive disorder (MDD).When taken orally, it is metabolized to S-demethylcitalopram (S-DCT) and S-didemethylcitalopram (S-DDCT) in the liver with the help of enzymes CYP2C19, CYP3A4 and CYP2D6. Hence, causing side effects such as dizziness, fast or irregular heartbeat, headache, nausea etc. Therefore, targeted and sustained drug delivery will be a helpful tool for increasing its efficacy and reducing side effects. The present study is designed for formulating mucoadhesive nanoparticle formulation for the same Escitalopram loaded polymeric nanoparticles were prepared by ionic gelation method and characterization of the optimised formulation was done by zeta average particle size (93.63nm), zeta potential (-1.89mV), TEM (range of 60nm to 115nm) analysis also confirms nanometric size range of the drug loaded nanoparticles along with polydispersibility index of 0.117. In this research, we have studied the in vitro drug release profile for ETP nanoparticles, through a semi permeable dialysis membrane. The three important characteristics affecting the drug release behaviour were – particle size, ionic strength and morphology of the optimised nanoparticles. The data showed that on increasing the particle size of the drug loaded nanoparticles, the initial burst was reduced which was comparatively higher in drug. Whereas, the formulation with 1mg/ml chitosan in 1.5mg/ml tripolyphosphate solution showed steady release over the entire period of drug release. Then this data was further validated through mathematical modelling to establish the mechanism of drug release kinetics, which showed a typical linear diffusion profile in optimised ETP loaded nanoparticles.

Keywords: ionic gelation, mucoadhesive nanoparticle, semi-permeable dialysis membrane, zeta potential

Procedia PDF Downloads 295
3676 Hidro-IA: An Artificial Intelligent Tool Applied to Optimize the Operation Planning of Hydrothermal Systems with Historical Streamflow

Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

Abstract:

The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

Procedia PDF Downloads 420
3675 Research on the Application of Flexible and Programmable Systems in Electronic Systems

Authors: Yang Xiaodong

Abstract:

This article explores the application and structural characteristics of flexible and programmable systems in electronic systems, with a focus on analyzing their advantages and architectural differences in dealing with complex environments. By introducing mathematical models and simulation experiments, the performance of dynamic module combination in flexible systems and fixed path selection in programmable systems in resource utilization and performance optimization was demonstrated. This article also discusses the mutual transformation between the two in practical applications and proposes a solution to improve system flexibility and performance through dynamic reconfiguration technology. This study provides theoretical reference for the design and optimization of flexible and programmable systems.

Keywords: flexibility, programmable, electronic systems, system architecture

Procedia PDF Downloads 13