Search results for: geometry optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4139

Search results for: geometry optimization

2549 Foliation and the First Law of Thermodynamics for the Kerr Newman Black Hole

Authors: Syed M. Jawwad Riaz

Abstract:

There has been a lot of interest in exploring the thermodynamic properties at the horizon of a black hole geometry. Earlier, it has been shown, for different spacetimes, that the Einstein field equations at the horizon can be expressed as a first law of black hole thermodynamics. In this paper, considering r = constant slices, for the Kerr-Newman black hole, shown that the Einstein field equations for the induced 3-metric of the hypersurface is expressed in thermodynamic quantities under the virtual displacements of the hypersurfaces. As expected, it is found that the field equations of the induced metric corresponding to the horizon can only be written as a first law of black hole thermodynamics. It is to be mentioned here that the procedure adopted is much easier, to obtain such results, as here one has to essentially deal with (n - 1)-dimensional induced metric for an n-dimensional spacetime.

Keywords: black hole space-times, Einstein's field equation, foliation, hyper-surfaces

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2548 Synthesis of Metal Curcumin Complexes with Iron(III) and Manganese(II): The Effects on Alzheimer's Disease

Authors: Emel Yildiz, Nurcan Biçer, Fazilet Aksu, Arash Alizadeh Yegani

Abstract:

Plants provide the wealth of bioactive compounds, which exert a substantial strategy for the treatment of neurological disorders such as Alzheimer's disease. Recently, a lot of studies have explored the medicinal properties of curcumin, including antitumoral, antimicrobial, anti-inflammatory, antioxidant, antiviral, and anti-Alzheimer's disease effects. Metal complexes of curcumin (1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione) were synthesized with Mn(II) and Fe(III). The structures of synthesized metal complexes have been characterized by using spectroscopic and analytic methods such as elemental analysis, magnetic susceptibility, FT-IR, AAS, TG and argentometric titration. It was determined that the complexes have octahedral geometry. The effects of the metal complexes on the disorder of memory, which is an important symptom of Alzheimer's Disease were studied on lab rats with Plus-Maze Tests at Behavioral Pharmacology Laboratory.

Keywords: curcumin, Mn(II), Fe(III), Alzheimer disease, beta amyloid 25-35

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2547 Design and Analysis of an Electro Thermally Symmetrical Actuated Microgripper

Authors: Sh. Foroughi, V. Karamzadeh, M. Packirisamy

Abstract:

This paper presents design and analysis of an electrothermally symmetrical actuated microgripper applicable for performing micro assembly or biological cell manipulation. Integration of micro-optics with microdevice leads to achieve extremely precise control over the operation of the device. Geometry, material, actuation, control, accuracy in measurement and temperature distribution are important factors which have to be taken into account for designing the efficient microgripper device. In this work, analyses of four different geometries are performed by means of COMSOL Multiphysics 5.2 with implementing Finite Element Methods. Then, temperature distribution along the fingertip, displacement of gripper site as well as optical efficiency vs. displacement and electrical potential are illustrated. Results show in addition to the industrial application of this device, the usage of that as a cell manipulator is possible.

Keywords: electro thermal actuator, MEMS, microgripper, MOEMS

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2546 The Optimization of TICSI in the Convergence Mechanism of Urban Water Management

Authors: M. Macchiaroli, L. Dolores, V. Pellecchia

Abstract:

With the recent Resolution n. 580/2019/R/idr, the Italian Regulatory Authority for Energy, Networks, and Environment (ARERA) for the Urban Water Management has introduced, for water managements characterized by persistent critical issues regarding the planning and organization of the service and the implementation of the necessary interventions for the improvement of infrastructures and management quality, a new mechanism for determining tariffs: the regulatory scheme of Convergence. The aim of this regulatory scheme is the overcoming of the Water Service Divided in order to improve the stability of the local institutional structures, technical quality, contractual quality, as well as in order to guarantee transparency elements for Users of the Service. Convergence scheme presupposes the identification of the cost items to be considered in the tariff in parametric terms, distinguishing three possible cases according to the type of historical data available to the Manager. The study, in particular, focuses on operations that have neither data on tariff revenues nor data on operating costs. In this case, the Manager's Constraint on Revenues (VRG) is estimated on the basis of a reference benchmark and becomes the starting point for defining the structure of the tariff classes, in compliance with the TICSI provisions (Integrated Text for tariff classes, ARERA's Resolution n. 665/2017/R/idr). The proposed model implements the recent studies on optimization models for the definition of tariff classes in compliance with the constraints dictated by TICSI in the application of the Convergence mechanism, proposing itself as a support tool for the Managers and the local water regulatory Authority in the decision-making process.

Keywords: decision-making process, economic evaluation of projects, optimizing tools, urban water management, water tariff

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2545 An Integrated Framework for Wind-Wave Study in Lakes

Authors: Moien Mojabi, Aurelien Hospital, Daniel Potts, Chris Young, Albert Leung

Abstract:

The wave analysis is an integral part of the hydrotechnical assessment carried out during the permitting and design phases for coastal structures, such as marinas. This analysis aims in quantifying: i) the Suitability of the coastal structure design against Small Craft Harbour wave tranquility safety criterion; ii) Potential environmental impacts of the structure (e.g., effect on wave, flow, and sediment transport); iii) Mooring and dock design and iv) Requirements set by regulatory agency’s (e.g., WSA section 11 application). While a complex three-dimensional hydrodynamic modelling approach can be applied on large-scale projects, the need for an efficient and reliable wave analysis method suitable for smaller scale marina projects was identified. As a result, Tetra Tech has developed and applied an integrated analysis framework (hereafter TT approach), which takes the advantage of the state-of-the-art numerical models while preserving the level of simplicity that fits smaller scale projects. The present paper aims to describe the TT approach and highlight the key advantages of using this integrated framework in lake marina projects. The core of this methodology is made by integrating wind, water level, bathymetry, and structure geometry data. To respond to the needs of specific projects, several add-on modules have been added to the core of the TT approach. The main advantages of this method over the simplified analytical approaches are i) Accounting for the proper physics of the lake through the modelling of the entire lake (capturing real lake geometry) instead of a simplified fetch approach; ii) Providing a more realistic representation of the waves by modelling random waves instead of monochromatic waves; iii) Modelling wave-structure interaction (e.g. wave transmission/reflection application for floating structures and piles amongst others); iv) Accounting for wave interaction with the lakebed (e.g. bottom friction, refraction, and breaking); v) Providing the inputs for flow and sediment transport assessment at the project site; vi) Taking in consideration historical and geographical variations of the wind field; and vii) Independence of the scale of the reservoir under study. Overall, in comparison with simplified analytical approaches, this integrated framework provides a more realistic and reliable estimation of wave parameters (and its spatial distribution) in lake marinas, leading to a realistic hydrotechnical assessment accessible to any project size, from the development of a new marina to marina expansion and pile replacement. Tetra Tech has successfully utilized this approach since many years in the Okanagan area.

Keywords: wave modelling, wind-wave, extreme value analysis, marina

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2544 Monte Carlo Simulation of Magnetic Properties in Bit Patterned Media

Authors: O. D. Arbeláez-Echeverri, E. Restrepo-Parra, J. C. Riano-Rojas

Abstract:

A two dimensional geometric model of Bit Patterned Media is proposed, the model is based on the crystal structure of the materials commonly used to produce the nano islands in bit patterned materials and the possible defects that may arise from the interaction between the nano islands and the matrix material. The dynamic magnetic properties of the material are then computed using time aware integration methods for the multi spin Hamiltonian. The Hamiltonian takes into account both the spatial and topological disorder of the sample as well as the high perpendicular anisotropy that is pursued when building bit patterned media. The main finding of the research was the possibility of replicating the results of previous experiments on similar materials and the ability of computing the switching field distribution given the geometry of the material and the parameters required by the model.

Keywords: nanostructures, Monte Carlo, pattern media, magnetic properties

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2543 Green Supply Chain Network Optimization with Internet of Things

Authors: Sema Kayapinar, Ismail Karaoglan, Turan Paksoy, Hadi Gokcen

Abstract:

Green Supply Chain Management is gaining growing interest among researchers and supply chain management. The concept of Green Supply Chain Management is to integrate environmental thinking into the Supply Chain Management. It is the systematic concept emphasis on environmental problems such as reduction of greenhouse gas emissions, energy efficiency, recycling end of life products, generation of solid and hazardous waste. This study is to present a green supply chain network model integrated Internet of Things applications. Internet of Things provides to get precise and accurate information of end-of-life product with sensors and systems devices. The forward direction consists of suppliers, plants, distributions centres and sales and collect centres while, the reverse flow includes the sales and collects centres, disassembled centre, recycling and disposal centre. The sales and collection centre sells the new products are transhipped from factory via distribution centre and also receive the end-of life product according their value level. We describe green logistics activities by presenting specific examples including “recycling of the returned products and “reduction of CO2 gas emissions”. The different transportation choices are illustrated between echelons according to their CO2 gas emissions. This problem is formulated as a mixed integer linear programming model to solve the green supply chain problems which are emerged from the environmental awareness and responsibilities. This model is solved by using Gams package program. Numerical examples are suggested to illustrate the efficiency of the proposed model.

Keywords: green supply chain optimization, internet of things, greenhouse gas emission, recycling

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2542 Estimation of Pressure Loss Coefficients in Combining Flows Using Artificial Neural Networks

Authors: Shahzad Yousaf, Imran Shafi

Abstract:

This paper presents a new method for calculation of pressure loss coefficients by use of the artificial neural network (ANN) in tee junctions. Geometry and flow parameters are feed into ANN as the inputs for purpose of training the network. Efficacy of the network is demonstrated by comparison of the experimental and ANN based calculated data of pressure loss coefficients for combining flows in a tee junction. Reynolds numbers ranging from 200 to 14000 and discharge ratios varying from minimum to maximum flow for calculation of pressure loss coefficients have been used. Pressure loss coefficients calculated using ANN are compared to the models from literature used in junction flows. The results achieved after the application of ANN agrees reasonably to the experimental values.

Keywords: artificial neural networks, combining flow, pressure loss coefficients, solar collector tee junctions

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2541 Optimization of the Culture Medium, Incubation Period, pH and Temperatures for Maximal Dye Bioremoval Using A. Fumigates

Authors: Wafaa M. Abd El-Rahim, Magda A. El-Meleigy, Eman Refaat

Abstract:

This study dealing with optimization the conditions affecting the formation of extracellular lignin- degrading enzymes to achieve maximal decolorization activity of Direct Violet dye by one fungal strain. In this study Aspergillus fumigates fungal strain used for production extracellular ligninolytic enzymes for removing Direct Violet dye under different conditions: culture medium, incubation period, pH and temperatures. The results indicted that the removal efficiency of A. fumigatus was enhanced by addition glucose and peptone to the culture medium. The addition of peptone and glucose was found to increase the decolorization activity of the fungal isolate from 51.38% to 93.74% after 4 days of incubation. The highest production of extracellular lignin degrading enzymes also recorded in Direct Violet dye medium supplemented with peptone and glucose. It was also found the decolorization activity of A. fumigatus was decreased gradually by increasing the incubation period up to 4 days. Also it was found that the fungal strain can grow and produce extracellular ligninolytic enzymes which accompanied by efficient removal of Direct Violet dye in a wide pH range of 4-8. The results also found that the maximal biosynthesis of ligninolytic enzymes which accompanied with maximal removal of Direct Violet dye was obtained at a temperature of 28C. This indicates that the different conditions of culture medium, incubation period, pH and temperatures are effective on dye decolorization on the fungal biomass and played a role in Direct Violet dye removal along with enzymatic activity of A. fumigatus.

Keywords: A. fumigates, extracellular lignin- degrading enzymes, textile dye, dye removing

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2540 The Strength and Metallography of a Bimetallic Friction Stir Bonded Joint between AA6061 and High Hardness Steel

Authors: Richard E. Miller

Abstract:

12.7-mm thick plates of 6061-T6511 aluminum alloy and high hardness steel (528 HV) were successfully joined by a friction stir bonding process using a tungsten-rhenium stir tool. Process parameter variation experiments, which included tool design geometry, plunge and traverse rates, tool offset, spindle tilt, and rotation speed, were conducted to develop a parameter set which yielded a defect free joint. Laboratory tensile tests exhibited yield stresses which exceed the strengths of comparable AA6061-to-AA6061 fusion and friction stir weld joints. Scanning electron microscopy and energy dispersive X-ray spectroscopy analysis also show atomic diffusion at the material interface region.

Keywords: dissimilar materials, friction stir, welding, materials science

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2539 Experimental and Numerical Studies of Droplet Formation

Authors: Khaled Al-Badani, James Ren, Lisa Li, David Allanson

Abstract:

Droplet formation is an important process in many engineering systems and manufacturing procedures, which includes welding, biotechnologies, 3D printing, biochemical, biomedical fields and many more. The volume and the characteristics of droplet formation are generally depended on various material properties, microfluidics and fluid mechanics considerations. Hence, a detailed investigation of this process, with the aid of numerical computational tools, are essential for future design optimization and process controls of many engineering systems. This will also improve the understanding of changes in the properties and the structures of materials, during the formation of the droplet, which is important for new material developments to achieve different functions, pending the requirements of the application. For example, the shape of the formed droplet is critical for the function of some final products, such as the welding nugget during Capacitor Discharge Welding process, or PLA 3D printing, etc. Although, most academic journals on droplet formation, focused on issued with material transfer rate, surface tension and residual stresses, the general emphasis on the characteristics of droplet shape has been overlooked. The proposed work for this project will examine theoretical methodologies, experimental techniques, and numerical modelling, using ANSYS FLUENT, to critically analyse and highlight optimization methods regarding the formation of pendant droplet. The project will also compare results from published data with experimental and numerical work, concerning the effects of key material parameters on the droplet shape. These effects include changes in heating/cooling rates, solidification/melting progression and separation/break-up times. From these tests, a set of objectives is prepared, with an intention of improving quality, stability and productivity in modelling metal welding and 3D printing.

Keywords: computer modelling, droplet formation, material distortion, materials forming, welding

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2538 Enhanced Production of Endo-β-1,4-Xylanase from a Newly Isolated Thermophile Geobacillus stearothermophilus KIBGE-IB29 for Prospective Industrial Applications

Authors: Zainab Bibi, Afsheen Aman, Shah Ali Ul Qader

Abstract:

Endo-β-1,4-xylanases [EC 3.2.1.8] are one of the major groups of enzymes that are involved in degradation process of xylan and have several applications in food, textile and paper processing industries. Due to broad utility of endo-β-1,4-xylanase, researchers are focusing to increase the productivity of this hydrolase from various microbial species. Harsh industrial condition, faster reaction rate and efficient hydrolysis of xylan with low risk of contamination are critical requirements of industry that can be fulfilled by synthesizing the enzyme with efficient properties. In the current study, a newly isolated thermophile Geobacillus stearothermophilus KIBGE-IB29 was used in order to attain the maximum production of endo-1,4-β-xylanase. Bacterial culture was isolated from soil, collected around the blast furnace site of a steel processing mill, Karachi. Optimization of various nutritional and physical factors resulted the maximum synthesis of endo-1,4-β-xylanase from a thermophile. High production yield was achieved at 60°C and pH-6.0 after 24 hours of incubation period. Various nitrogen sources viz. peptone, yeast extract and meat extract improved the enzyme synthesis with 0.5%, 0.2% and 0.1% optimum concentrations. Dipotassium hydrogen phosphate (0.25%), potassium dihydrogen phosphate (0.05%), ammonium sulfate (0.05%) and calcium chloride (0.01%) were noticed as valuable salts to improve the production of enzyme. The thermophilic nature of isolate, with its broad pH stability profile and reduced fermentation time indicates its importance for effective xylan saccharification and for large scale production of endo-1,4-β-xylanase.

Keywords: geobacillus, optimization, production, xylanase

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2537 Improving Patient-Care Services at an Oncology Center with a Flexible Adaptive Scheduling Procedure

Authors: P. Hooshangitabrizi, I. Contreras, N. Bhuiyan

Abstract:

This work presents an online scheduling problem which accommodates multiple requests of patients for chemotherapy treatments in a cancer center of a major metropolitan hospital in Canada. To solve the problem, an adaptive flexible approach is proposed which systematically combines two optimization models. The first model is intended to dynamically schedule arriving requests in the form of waiting lists whereas the second model is used to reschedule the already booked patients with the goal of finding better resource allocations when new information becomes available. Both models are created as mixed integer programming formulations. Various controllable and flexible parameters such as deviating the prescribed target dates by a pre-determined threshold, changing the start time of already booked appointments and the maximum number of appointments to move in the schedule are included in the proposed approach to have sufficient degrees of flexibility in handling arrival requests and unexpected changes. Several computational experiments are conducted to evaluate the performance of the proposed approach using historical data provided by the oncology clinic. Our approach achieves outstandingly better results as compared to those of the scheduling system being used in practice. Moreover, several analyses are conducted to evaluate the effect of considering different levels of flexibility on the obtained results and to assess the performance of the proposed approach in dealing with last-minute changes. We strongly believe that the proposed flexible adaptive approach is very well-suited for implementation at the clinic to provide better patient-care services and to utilize available resource more efficiently.

Keywords: chemotherapy scheduling, multi-appointment modeling, optimization of resources, satisfaction of patients, mixed integer programming

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2536 Investigation on Flexural Behavior of Non-Crimp 3D Orthogonal Weave Carbon Composite Reinforcement

Authors: Sh. Minapoor, S. Ajeli

Abstract:

Non-crimp three-dimensional (3D) orthogonal carbon fabrics are one of the useful textiles reinforcements in composites. In this paper, flexural and bending properties of a carbon non-crimp 3D orthogonal woven reinforcement are experimentally investigated. The present study is focused on the understanding and measurement of the main bending parameters including flexural stress, strain, and modulus. For this purpose, the three-point bending test method is used and the load-displacement curves are analyzed. The influence of some weave's parameters such as yarn type, geometry of structure, and fiber volume fraction on bending behavior of non-crimp 3D orthogonal carbon fabric is investigated. The obtained results also represent a dataset for the simulation of flexural behavior of non-crimp 3D orthogonal weave carbon composite reinforcement.

Keywords: non-crimp 3D orthogonal weave, carbon composite reinforcement, flexural behavior, three-point bending

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2535 Regret-Regression for Multi-Armed Bandit Problem

Authors: Deyadeen Ali Alshibani

Abstract:

In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

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2534 Relationship between Interfacial Instabilities and Mechanical Strength of Multilayer Symmetric Polymer Melts

Authors: Mohammad Ranjbaran Madiseh

Abstract:

In this research, an experimental apparatus has been developed for observing interfacial stability and deformation of multilayer pressure-driven channel flows. The interface instability of the co-extrusion flow of polyethylene and polypropylene is studied experimentally in a slit geometry. By investigating the growing interfacial wave (IW) and tensile stress of extrudate samples, a relationship between interfacial instability (II) and mechanical properties of polypropylene (PP) and high-density polyethylene (HDPE) has been established. It is shown that the mechanism of interfacial strength is related to interfacial instabilities as well as interfacial strength. It is shown that there is an ability to forecast the quality of final products in the co-extrusion process. In this study, it is found that the instability is controlled by its dominant wave number, which is associated with maximum tensile stress at the interface.

Keywords: interfacial instability, interfacial strength, wave number, interfacial wave

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2533 Optimizing Data Integration and Management Strategies for Upstream Oil and Gas Operations

Authors: Deepak Singh, Rail Kuliev

Abstract:

The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

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2532 Designing and Simulation of the Rotor and Hub of the Unmanned Helicopter

Authors: Zbigniew Czyz, Ksenia Siadkowska, Krzysztof Skiba, Karol Scislowski

Abstract:

Today’s progress in the rotorcraft is mostly associated with an optimization of aircraft performance achieved by active and passive modifications of main rotor assemblies and a tail propeller. The key task is to improve their performance, improve the hover quality factor for rotors but not change in specific fuel consumption. One of the tasks to improve the helicopter is an active optimization of the main rotor providing for flight stages, i.e., an ascend, flight, a descend. An active interference with the airflow around the rotor blade section can significantly change characteristics of the aerodynamic airfoil. The efficiency of actuator systems modifying aerodynamic coefficients in the current solutions is relatively high and significantly affects the increase in strength. The solution to actively change aerodynamic characteristics assumes a periodic change of geometric features of blades depending on flight stages. Changing geometric parameters of blade warping enables an optimization of main rotor performance depending on helicopter flight stages. Structurally, an adaptation of shape memory alloys does not significantly affect rotor blade fatigue strength, which contributes to reduce costs associated with an adaptation of the system to the existing blades, and gains from a better performance can easily amortize such a modification and improve profitability of such a structure. In order to obtain quantitative and qualitative data to solve this research problem, a number of numerical analyses have been necessary. The main problem is a selection of design parameters of the main rotor and a preliminary optimization of its performance to improve the hover quality factor for rotors. This design concept assumes a three-bladed main rotor with a chord of 0.07 m and radius R = 1 m. The value of rotor speed is a calculated parameter of an optimization function. To specify the initial distribution of geometric warping, a special software has been created that uses a numerical method of a blade element which respects dynamic design features such as fluctuations of a blade in its joints. A number of performance analyses as a function of rotor speed, forward speed, and altitude have been performed. The calculations were carried out for the full model assembly. This approach makes it possible to observe the behavior of components and their mutual interaction resulting from the forces. The key element of each rotor is the shaft, hub and pins holding the joints and blade yokes. These components are exposed to the highest loads. As a result of the analysis, the safety factor was determined at the level of k > 1.5, which gives grounds to obtain certification for the strength of the structure. The construction of the joint rotor has numerous moving elements in its structure. Despite the high safety factor, the places with the highest stresses, where the signs of wear and tear may appear, have been indicated. The numerical analysis carried out showed that the most loaded element is the pin connecting the modular bearing of the blade yoke with the element of the horizontal oscillation joint. The stresses in this element result in a safety factor of k=1.7. The other analysed rotor components have a safety factor of more than 2 and in the case of the shaft, this factor is more than 3. However, it must be remembered that the structure is as strong as the weakest cell is. Designed rotor for unmanned aerial vehicles adapted to work with blades with intelligent materials in its structure meets the requirements for certification testing. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: main rotor, rotorcraft aerodynamics, shape memory alloy, materials, unmanned helicopter

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2531 A Multilayer Perceptron Neural Network Model Optimized by Genetic Algorithm for Significant Wave Height Prediction

Authors: Luis C. Parra

Abstract:

The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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2530 An A-Star Approach for the Quickest Path Problem with Time Windows

Authors: Christofas Stergianos, Jason Atkin, Herve Morvan

Abstract:

As air traffic increases, more airports are interested in utilizing optimization methods. Many processes happen in parallel at an airport, and complex models are needed in order to have a reliable solution that can be implemented for ground movement operations. The ground movement for aircraft in an airport, allocating a path to each aircraft to follow in order to reach their destination (e.g. runway or gate), is one process that could be optimized. The Quickest Path Problem with Time Windows (QPPTW) algorithm has been developed to provide a conflict-free routing of vehicles and has been applied to routing aircraft around an airport. It was subsequently modified to increase the accuracy for airport applications. These modifications take into consideration specific characteristics of the problem, such as: the pushback process, which considers the extra time that is needed for pushing back an aircraft and turning its engines on; stand holding where any waiting should be allocated to the stand; and runway sequencing, where the sequence of the aircraft that take off is optimized and has to be respected. QPPTW involves searching for the quickest path by expanding the search in all directions, similarly to Dijkstra’s algorithm. Finding a way to direct the expansion can potentially assist the search and achieve a better performance. We have further modified the QPPTW algorithm to use a heuristic approach in order to guide the search. This new algorithm is based on the A-star search method but estimates the remaining time (instead of distance) in order to assess how far the target is. It is important to consider the remaining time that it is needed to reach the target, so that delays that are caused by other aircraft can be part of the optimization method. All of the other characteristics are still considered and time windows are still used in order to route multiple aircraft rather than a single aircraft. In this way the quickest path is found for each aircraft while taking into account the movements of the previously routed aircraft. After running experiments using a week of real aircraft data from Zurich Airport, the new algorithm (A-star QPPTW) was found to route aircraft much more quickly, being especially fast in routing the departing aircraft where pushback delays are significant. On average A-star QPPTW could route a full day (755 to 837 aircraft movements) 56% faster than the original algorithm. In total the routing of a full week of aircraft took only 12 seconds with the new algorithm, 15 seconds faster than the original algorithm. For real time application, the algorithm needs to be very fast, and this speed increase will allow us to add additional features and complexity, allowing further integration with other processes in airports and leading to more optimized and environmentally friendly airports.

Keywords: a-star search, airport operations, ground movement optimization, routing and scheduling

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2529 Perovskite-Type La1−xCaxAlO3 (x=0, 0.2, 0.4, 0.6) as Active Anode Materials for Methanol Oxidation in Alkaline Solutions

Authors: M. Diafi, M. Omari, B. Gasmi

Abstract:

Perovskite-type La1−xCaxAlO3 were synthesized at 1000◦C by a co- precipitation method. The synthesized oxide powders were characterized by X-ray diffraction (XRD) and the oxide powders were produced in the form of films on pretreated Ni-supports by an oxide-slurry painting technique their electrocatalytic activities towards methanol oxidation in alkaline solutions at 25°C using cyclic voltammetry, chronoamperometry, and anodic Tafel polarization techniques. The oxide catalysts followed the rhombohedral hexagonal crystal geometry. The rate of electro-oxidation of methanol was found to increase with increasing substitution of La by Ca in the oxide matrix. The reaction indicated a Tafel slope of ~2.303RT/F, The electrochemical apparent activation energy (〖∆H〗_el^(°#)) was observed to decrease on increasing Ca content. The results point out the optimum electrode activity and stability of the Ca is x=0.6 of composition.

Keywords: electrocatalysis, oxygen evolution, perovskite-type La1−x Cax AlO3, methanol oxidation

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2528 Computational Quantum Mechanics Study of Oxygen as Substitutional Atom in Diamond

Authors: K. M. Etmimi, A. A. Sghayer, A. M. Gsiea, A. M. Abutruma

Abstract:

Relatively few chemical species can be incorporated into diamond during CVD growth, and until recently the uptake of oxygen was thought to be low perhaps as a consequence of a short surface residence time. Within the literature, there is speculation regarding spectroscopic evidence for O in diamond, but no direct evidence. For example, the N3 and OK1 EPR centres have been tentatively assigned models made up from complexes of substitutional N and substitutional oxygen. In this study, we report density-functional calculations regarding the stability, electronic structures, geometry and hyperfine interaction of substitutional oxygen in diamond and show that the C2v, S=1 configuration very slightly lower in energy than the other configurations (C3v, Td, and C2v with S=0). The electronic structure of O in diamond generally gives rise to two defect-related energy states in the band gap one a non-degenerate a1 state lying near the middle of the energy gap and the other a threefold-degenerate t2 state located close to the conduction band edges. The anti-bonding a1 and t2 states will be occupied by one to three electrons for O+, O and O− respectively.

Keywords: DFT, oxygen, diamond, hyperfine

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2527 Quantifying Multivariate Spatiotemporal Dynamics of Malaria Risk Using Graph-Based Optimization in Southern Ethiopia

Authors: Yonas Shuke Kitawa

Abstract:

Background: Although malaria incidence has substantially fallen sharply over the past few years, the rate of decline varies by district, time, and malaria type. Despite this turn-down, malaria remains a major public health threat in various districts of Ethiopia. Consequently, the present study is aimed at developing a predictive model that helps to identify the spatio-temporal variation in malaria risk by multiple plasmodium species. Methods: We propose a multivariate spatio-temporal Bayesian model to obtain a more coherent picture of the temporally varying spatial variation in disease risk. The spatial autocorrelation in such a data set is typically modeled by a set of random effects that assign a conditional autoregressive prior distribution. However, the autocorrelation considered in such cases depends on a binary neighborhood matrix specified through the border-sharing rule. Over here, we propose a graph-based optimization algorithm for estimating the neighborhood matrix that merely represents the spatial correlation by exploring the areal units as the vertices of a graph and the neighbor relations as the series of edges. Furthermore, we used aggregated malaria count in southern Ethiopia from August 2013 to May 2019. Results: We recognized that precipitation, temperature, and humidity are positively associated with the malaria threat in the area. On the other hand, enhanced vegetation index, nighttime light (NTL), and distance from coastal areas are negatively associated. Moreover, nonlinear relationships were observed between malaria incidence and precipitation, temperature, and NTL. Additionally, lagged effects of temperature and humidity have a significant effect on malaria risk by either species. More elevated risk of P. falciparum was observed following the rainy season, and unstable transmission of P. vivax was observed in the area. Finally, P. vivax risks are less sensitive to environmental factors than those of P. falciparum. Conclusion: The improved inference was gained by employing the proposed approach in comparison to the commonly used border-sharing rule. Additionally, different covariates are identified, including delayed effects, and elevated risks of either of the cases were observed in districts found in the central and western regions. As malaria transmission operates in a spatially continuous manner, a spatially continuous model should be employed when it is computationally feasible.

Keywords: disease mapping, MSTCAR, graph-based optimization algorithm, P. falciparum, P. vivax, waiting matrix

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2526 Deep Reinforcement Learning-Based Computation Offloading for 5G Vehicle-Aware Multi-Access Edge Computing Network

Authors: Ziying Wu, Danfeng Yan

Abstract:

Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

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2525 CO2 Emission and Cost Optimization of Reinforced Concrete Frame Designed by Performance Based Design Approach

Authors: Jin Woo Hwang, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

Abstract:

As greenhouse effect has been recognized as serious environmental problem of the world, interests in carbon dioxide (CO2) emission which comprises major part of greenhouse gas (GHG) emissions have been increased recently. Since construction industry takes a relatively large portion of total CO2 emissions of the world, extensive studies about reducing CO2 emissions in construction and operation of building have been carried out after the 2000s. Also, performance based design (PBD) methodology based on nonlinear analysis has been robustly developed after Northridge Earthquake in 1994 to assure and assess seismic performance of building more exactly because structural engineers recognized that prescriptive code based design approach cannot address inelastic earthquake responses directly and assure performance of building exactly. Although CO2 emissions and PBD approach are recent rising issues on construction industry and structural engineering, there were few or no researches considering these two issues simultaneously. Thus, the objective of this study is to minimize the CO2 emissions and cost of building designed by PBD approach in structural design stage considering structural materials. 4 story and 4 span reinforced concrete building optimally designed to minimize CO2 emissions and cost of building and to satisfy specific seismic performance (collapse prevention in maximum considered earthquake) of building satisfying prescriptive code regulations using non-dominated sorting genetic algorithm-II (NSGA-II). Optimized design result showed that minimized CO2 emissions and cost of building were acquired satisfying specific seismic performance. Therefore, the methodology proposed in this paper can be used to reduce both CO2 emissions and cost of building designed by PBD approach.

Keywords: CO2 emissions, performance based design, optimization, sustainable design

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2524 Construction and Optimization of Green Infrastructure Network in Mountainous Counties Based on Morphological Spatial Pattern Analysis and Minimum Cumulative Resistance Models: A Case Study of Shapingba District, Chongqing

Authors: Yuning Guan

Abstract:

Under the background of rapid urbanization, mountainous counties need to break through mountain barriers for urban expansion due to undulating topography, resulting in ecological problems such as landscape fragmentation and reduced biodiversity. Green infrastructure networks are constructed to alleviate the contradiction between urban expansion and ecological protection, promoting the healthy and sustainable development of urban ecosystems. This study applies the MSPA model, the MCR model and Linkage Mapper Tools to identify eco-sources and eco-corridors in the Shapingba District of Chongqing and combined with landscape connectivity assessment and circuit theory to delineate the importance levels to extract ecological pinch point areas on the corridors. The results show that: (1) 20 ecological sources are identified, with a total area of 126.47 km², accounting for 31.88% of the study area, and showing a pattern of ‘one core, three corridors, multi-point distribution’. (2) 37 ecological corridors are formed in the area, with a total length of 62.52km, with a ‘more in the west, less in the east’ pattern. (3) 42 ecological pinch points are extracted, accounting for 25.85% of the length of the corridors, which are mainly distributed in the eastern new area. Accordingly, this study proposes optimization strategies for sub-area protection of ecological sources, grade-level construction of ecological corridors, and precise restoration of ecological pinch points.

Keywords: green infrastructure network, morphological spatial pattern, minimal cumulative resistance, mountainous counties, circuit theory, shapingba district

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2523 Influence of Structured Capillary-Porous Coatings on Cryogenic Quenching Efficiency

Authors: Irina P. Starodubtseva, Aleksandr N. Pavlenko

Abstract:

Quenching is a term generally accepted for the process of rapid cooling of a solid that is overheated above the thermodynamic limit of the liquid superheat. The main objective of many previous studies on quenching is to find a way to reduce the total time of the transient process. Computational experiments were performed to simulate quenching by a falling liquid nitrogen film of an extremely overheated vertical copper plate with a structured capillary-porous coating. The coating was produced by directed plasma spraying. Due to the complexities in physical pattern of quenching from chaotic processes to phase transition, the mechanism of heat transfer during quenching is still not sufficiently understood. To our best knowledge, no information exists on when and how the first stable liquid-solid contact occurs and how the local contact area begins to expand. Here we have more models and hypotheses than authentically established facts. The peculiarities of the quench front dynamics and heat transfer in the transient process are studied. The created numerical model determines the quench front velocity and the temperature fields in the heater, varying in space and time. The dynamic pattern of the running quench front obtained numerically satisfactorily correlates with the pattern observed in experiments. Capillary-porous coatings with straight and reverse orientation of crests are investigated. The results show that the cooling rate is influenced by thermal properties of the coating as well as the structure and geometry of the protrusions. The presence of capillary-porous coating significantly affects the dynamics of quenching and reduces the total quenching time more than threefold. This effect is due to the fact that the initialization of a quench front on a plate with a capillary-porous coating occurs at a temperature significantly higher than the thermodynamic limit of the liquid superheat, when a stable solid-liquid contact is thermodynamically impossible. Waves present on the liquid-vapor interface and protrusions on the complex micro-structured surface cause destabilization of the vapor film and the appearance of local liquid-solid micro-contacts even though the average integral surface temperature is much higher than the liquid superheat limit. The reliability of the results is confirmed by direct comparison with experimental data on the quench front velocity, the quench front geometry, and the surface temperature change over time. Knowledge of the quench front velocity and total time of transition process is required for solving practically important problems of nuclear reactors safety.

Keywords: capillary-porous coating, heat transfer, Leidenfrost phenomenon, numerical simulation, quenching

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2522 Investigation of the Cooling and Uniformity Effectiveness in a Sinter Packed Bed

Authors: Uzu-Kuei Hsu, Chang-Hsien Tai, Kai-Wun Jin

Abstract:

When sinters are filled into the cooler from the sintering machine, and the non-uniform distribution of the sinters leads to uneven cooling. This causes the temperature difference of the sinters leaving the cooler to be so large that it results in the conveyors being deformed by the heat. The present work applies CFD method to investigate the thermo flowfield phenomena in a sinter cooler by the Porous Media Model. Using the obtained experimental data to simulate porosity (Ε), permeability (κ), inertial coefficient (F), specific heat (Cp) and effective thermal conductivity (keff) of the sinter packed beds. The physical model is a similar geometry whose Darcy numbers (Da) are similar to the sinter cooler. Using the Cooling Index (CI) and Uniformity Index (UI) to analyze the thermo flowfield in the sinter packed bed obtains the cooling performance of the sinter cooler.

Keywords: porous media, sinter, cooling index (CI), uniformity index (UI), CFD

Procedia PDF Downloads 389
2521 Enhancing Algal Bacterial Photobioreactor Efficiency: Nutrient Removal and Cost Analysis Comparison for Light Source Optimization

Authors: Shahrukh Ahmad, Purnendu Bose

Abstract:

Algal-Bacterial photobioreactors (ABPBRs) have emerged as a promising technology for sustainable biomass production and wastewater treatment. Nutrient removal is seldom done in sewage treatment plants and large volumes of wastewater which still have nutrients are being discharged and that can lead to eutrophication. That is why ABPBR plays a vital role in wastewater treatment. However, improving the efficiency of ABPBR remains a significant challenge. This study aims to enhance ABPBR efficiency by focusing on two key aspects: nutrient removal and cost-effective optimization of the light source. By integrating nutrient removal and cost analysis for light source optimization, this study proposes practical strategies for improving ABPBR efficiency. To reduce organic carbon and convert ammonia to nitrates, domestic wastewater from a 130 MLD sewage treatment plant (STP) was aerated with a hydraulic retention time (HRT) of 2 days. The treated supernatant had an approximate nitrate and phosphate values of 16 ppm as N and 6 ppm as P, respectively. This supernatant was then fed into the ABPBR, and the removal of nutrients (nitrate as N and phosphate as P) was observed using different colored LED bulbs, namely white, blue, red, yellow, and green. The ABPBR operated with a 9-hour light and 3-hour dark cycle, using only one color of bulbs per cycle. The study found that the white LED bulb, with a photosynthetic photon flux density (PPFD) value of 82.61 µmol.m-2 .sec-1 , exhibited the highest removal efficiency. It achieved a removal rate of 91.56% for nitrate and 86.44% for phosphate, surpassing the other colored bulbs. Conversely, the green LED bulbs showed the lowest removal efficiencies, with 58.08% for nitrate and 47.48% for phosphate at an HRT of 5 days. The quantum PAR (Photosynthetic Active Radiation) meter measured the photosynthetic photon flux density for each colored bulb setting inside the photo chamber, confirming that white LED bulbs operated at a wider wavelength band than the others. Furthermore, a cost comparison was conducted for each colored bulb setting. The study revealed that the white LED bulb had the lowest average cost (Indian Rupee)/light intensity (µmol.m-2 .sec-1 ) value at 19.40, while the green LED bulbs had the highest average cost (INR)/light intensity (µmol.m-2 .sec-1 ) value at 115.11. Based on these comparative tests, it was concluded that the white LED bulbs were the most efficient and costeffective light source for an algal photobioreactor. They can be effectively utilized for nutrient removal from secondary treated wastewater which helps in improving the overall wastewater quality before it is discharged back into the environment.

Keywords: algal bacterial photobioreactor, domestic wastewater, nutrient removal, led bulbs

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2520 Approximate Spring Balancing for the Arm of a Humanoid Robot to Reduce Actuator Torque

Authors: Apurva Patil, Ashay Aswale, Akshay Kulkarni, Shubham Bharadiya

Abstract:

The potential benefit of gravity compensation of linkages in mechanisms using springs to reduce actuator requirements is well recognized, but practical applications have been elusive. Although existing methods provide exact spring balance, they require additional masses or auxiliary links, or all the springs used originate from the ground, which makes the resulting device bulky and space-inefficient. This paper uses a method of static balancing of mechanisms with conservative loads such as gravity and spring loads using non-zero-free-length springs with child–parent connections and no auxiliary links. Application of this method to the developed arm of a humanoid robot is presented here. Spring balancing is particularly important in this case because the serial chain of linkages has to work against gravity.This work involves approximate spring balancing of the open-loop chain of linkages using minimization of potential energy variance. It uses the approach of flattening the potential energy distribution over the workspace and fuses it with numerical optimization. The results show the considerable reduction in actuator torque requirement with practical spring design and arrangement. Reduced actuator torque facilitates the use of lower end actuators which are generally smaller in weight and volume thereby lowering the space requirements and the total weight of the arm. This is particularly important for humanoid robots where the parent actuator has to handle the weight of the subsequent actuators as well. Actuators with lower actuation requirements are more energy efficient, thereby reduce the energy consumption of the mechanism. Lower end actuators are lower in cost and facilitate the development of low-cost devices. Although the method provides only an approximate balancing, it is versatile, flexible in choosing appropriate control variables that are relevant to the design problem and easy to implement. The true potential of this technique lies in the fact that it uses a very simple optimization to find the spring constant, free-length of the spring and the optimal attachment points subject to the optimization constraints. Also, it uses physically realizable non-zero-free-length springs directly, thereby reducing the complexity involved in simulating zero-free-length springs from non-zero-free-length springs. This method allows springs to be attached to the preceding parent link, which makes the implementation of spring balancing practical. Because auxiliary linkages can be avoided, the resultant arm of the humanoid robot is compact. The cost benefits and reduced complexity can be significant advantages in the development of this arm of the humanoid robot.

Keywords: actuator torque, child-parent connections, spring balancing, the arm of a humanoid robot

Procedia PDF Downloads 237