Search results for: optimization of composites

Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

Abstract:

Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

Procedia PDF Downloads 135

Authors: Stephanie Guerra-Arias, Stephani Nevarez, Calvin Stewart, Rachel Grodsky, Denis Eichorst

Abstract:

The objective of this study is to describe the framework for optimizing the heat treatment of alkali silicate glasses, to enhance the performance of hermetic seals in extreme environments. When connectors are exposed to elevated temperatures, residual stresses develop due to the mismatch of thermal expansions between the glass, metal pin, and metal shell. Excessive thermal expansion mismatch compromises the reliability of hermetic seals. In this study, a series of heat treatment schedules will be performed on two commercial sealing glasses (one conventional sealing glass and one crystallizable sealing glass) using a design of experiments (DOE) approach. The coefficient of thermal expansion (CTE) will be measured pre- and post-heat treatment using thermomechanical analysis (TMA). Afterwards, the flexural strength of the specimen will be measured using a four-point bend fixture mounted in a static universal testing machine. The measured material properties will be statistically analyzed using MiniTab software to determine which factors of the heat treatment process have a strong correlation to the coefficient of thermal expansion and/or flexural strength. Finally, a heat-treatment will be designed and tested to ensure the optimal performance of the hermetic seals in connectors.

Keywords: glass-ceramics, design of experiment, hermetic connectors, material characterization

Procedia PDF Downloads 137

Authors: Anicet Dansou

Abstract:

Textile reinforced concrete (TRC)is increasingly used nowadays in various fields, in particular civil engineering, where it is mainly used for the reinforcement of damaged reinforced concrete structures. TRC is a composite material composed of multi- or uni-axial textile reinforcements coupled with a fine-grained cementitious matrix. The TRC composite is an alternative solution to the traditional Fiber Reinforcement Polymer (FRP) composite. It has good mechanical performance and better temperature stability but also, it makes it possible to meet the criteria of sustainable development better.TRCs are highly anisotropic composite materials with nonlinear hardening behavior; their macroscopic behavior depends on multi-scale mechanisms. The characterization of these materials through numerical simulation has been the subject of many studies. Since TRCs are multiscale material by definition, numerical multi-scale approaches have emerged as one of the most suitable methods for the simulation of TRCs. They aim to incorporate information pertaining to microscale constitute behavior, mesoscale behavior, and macro-scale structure response within a unified model that enables rapid simulation of structures. The computational costs are hence significantly reduced compared to standard simulation at a fine scale. The fine scale information can be implicitly introduced in the macro scale model: approaches of this type are called non-classical. A representative volume element is defined, and the fine scale information are homogenized over it. Analytical and computational homogenization and nested mesh methods belong to these approaches. On the other hand, in classical approaches, the fine scale information are explicitly introduced in the macro scale model. Such approaches pertain to adaptive mesh refinement strategies, sub-modelling, domain decomposition, and multigrid methods This research presents the main principles of numerical multiscale approaches. Advantages and limitations are identified according to several criteria: the assumptions made (fidelity), the number of input parameters required, the calculation costs (efficiency), etc. A bibliographic study of recent results and advances and of the scientific obstacles to be overcome in order to achieve an effective simulation of textile reinforced concrete in civil engineering is presented. A comparative study is further carried out between several methods for the simulation of TRCs used for the structural reinforcement of reinforced concrete structures.

Keywords: composites structures, multiscale methods, numerical modeling, textile reinforced concrete

Procedia PDF Downloads 99

Authors: Antonin Ponsich, Eric Alfredo Rincon Garcia, Roman Anselmo Mora Gutierrez, Miguel Angel Gutierrez Andrade, Sergio Gerardo De Los Cobos Silva, Pedro Lara Velzquez

Abstract:

The electoral zone design problem consists in redrawing the boundaries of legislative districts for electoral purposes in such a way that federal or state requirements are fulfilled. In Mexico, this process has been historically carried out by the National Electoral Institute (INE), by optimizing an integer nonlinear programming model, in which population equality and compactness of the designed districts are considered as two conflicting objective functions, while contiguity is included as a hard constraint. The solution technique used by the INE is a Simulated Annealing (SA) based algorithm, which handles the multi-objective nature of the problem through an aggregation function. The present work represents the first intent to apply a classical Multi-Objective Evolutionary Algorithm (MOEA), the second version of the Non-dominated Sorting Genetic Algorithm (NSGA-II), to this hard combinatorial problem. First results show that, when compared with the SA algorithm, the NSGA-II obtains promising results. The MOEA manages to produce well-distributed solutions over a wide-spread front, even though some convergence troubles for some instances constitute an issue, which should be corrected in future adaptations of MOEAs to the redistricting problem.

Keywords: multi-objective optimization, NSGA-II, redistricting, zone design problem

Procedia PDF Downloads 356

Authors: Szymon Kowieski, Zygmunt Mikno

Abstract:

The study involved the optimization of process parameters during resistance spot welding of Al-coated martensitic boron steel 22MnB5, applied in hot stamping, performed using a programme with a multiple current impulse mode and a programme with variable pressure force. The aim of this research work was to determine the possibilities of a growth in welded joint strength and to identify the expansion of a welding lobe. The process parameters were adjusted on the basis of welding process simulation and confronted with experimental data. 22MnB5 steel is known for its tendency to obtain high hardness values in weld nuggets, often leading to interfacial failures (observed in the study-related tests). In addition, during resistance spot welding, many production-related factors can affect process stability, e.g. welding lobe narrowing, and lead to the deterioration of quality. Resistance spot welding performed using the above-named welding programme featuring 3 levels of force made it possible to achieve 82% of welding lobe extension. Joints made using the multiple current impulse program, where the total welding time was below 1.4s, revealed a change in a peeling mode (to full plug) and an increase in weld tensile shear strength of 10%.

Keywords: 22MnB5, hot stamping, interfacial fracture, resistance spot welding, simulation, single lap joint, welding lobe

Procedia PDF Downloads 373

Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

Abstract:

Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security

Procedia PDF Downloads 320

Authors: Michael Dreyfuss, Yahel Giat

Abstract:

Limited battery range and long recharging times are the greatest obstacles to the successful adoption of electric cars. One of the suggestions to overcome these problems is that carmakers retain ownership of batteries and provide battery swapping service so that customers exchange their depleted batteries for recharged batteries. Motivated by this example, we consider the problem of optimal spares allocation in an exchangeable-item, multi-location repair system. We generalize the standard service measures of fill rate and average waiting time to reflect the fact that customers penalize the service provider only if they have to wait more than a ‘tolerable’ time window. These measures are denoted as the window fill rate and the truncated waiting time, respectively. We find that the truncated waiting time is convex and therefore a greedy algorithm solves the spares allocation problem efficiently. We show that the window fill rate is generally S-shaped and describe an efficient algorithm to find a near-optimal solution and detail a priori and a posteriori upper bounds to the distance from optimum. The theory is complemented with a large scale numerical example demonstrating the spare battery allocation in battery swapping stations.

Keywords: convex-concave optimization, exchangeable item, M/G/infinity, multiple location, repair system, spares allocation, window fill rate

Procedia PDF Downloads 483

Authors: Indunil Jayatilake, Warna Karunasena, Weena Lokuge

Abstract:

An Australian manufacturer has fabricated an innovative GFRP sandwich panel made from E-glass fiber skin and a modified phenolic core for structural applications. Debonding, which refers to separation of skin from the core material in composite sandwiches, is one of the most common types of damage in composites. The presence of debonding is of great concern because it not only severely affects the stiffness but also modifies the dynamic behaviour of the structure. Generally, it is seen that the majority of research carried out has been concerned about the delamination of laminated structures whereas skin-core debonding has received relatively minor attention. Furthermore, it is observed that research done on composite slabs having multiple skin-core debonding is very limited. To address this gap, a comprehensive research investigating dynamic behaviour of composite panels with single and multiple debonding is presented. The study uses finite-element modelling and analyses for investigating the influence of debonding on free vibration behaviour of single and multilayer composite sandwich panels. A broad parametric investigation has been carried out by varying debonding locations, debonding sizes and support conditions of the panels in view of both single and multiple debonding. Numerical models were developed with Strand7 finite element package by innovatively selecting the suitable elements to diligently represent their actual behavior. Three-dimensional finite element models were employed to simulate the physically real situation as close as possible, with the use of an experimentally and numerically validated finite element model. Comparative results and conclusions based on the analyses are presented. For similar extents and locations of debonding, the effect of debonding on natural frequencies appears greatly dependent on the end conditions of the panel, giving greater decrease in natural frequency when the panels are more restrained. Some modes are more sensitive to debonding and this sensitivity seems to be related to their vibration mode shapes. The fundamental mode seems generally the least sensitive mode to debonding with respect to the variation in free vibration characteristics. The results indicate the effectiveness of the developed three-dimensional finite element models in assessing debonding damage in composite sandwich panels

Keywords: debonding, free vibration behaviour, GFRP sandwich panels, three dimensional finite element modelling

Procedia PDF Downloads 303

Authors: Mahdiye Khorasani, Arjun Vijay, Ali Mashayekh, Christian Trapp

Abstract:

The performance of Proton Exchange Membrane Fuel Cell (PEMFC) is highly dependent on the pressure and mass flow of media (Hydrogen and air) throughout the cells and the stack. Higher pressure, on the one hand, results in higher output power of the stack but, on the other hand, increases the electrical power demand of the compressor. In this work, a simulation model of a PEMFC system for vehicle and airplane applications is developed. With this new model, the effect of different pressures and air mass flow rates are investigated to discover the optimum operating point in a PEMFC system, and innovative operation strategies are implemented to optimize reactants flow while minimizing electrical power demand of the compressor for optimum performance. Additionally, a fuel cell system test bench is set up, which contains not only all the auxiliary components for conditioning the gases, reactants, and flows but also a dynamic titling table for testing different orientations of the stack to simulate the flight conditions during take-off and landing and off-road-vehicle scenarios. The results of simulation will be tested and validated on the test bench for future works.

Keywords: air mass flow effect, optimization of operation, pressure effect, PEMFC system, PEMFC system simulation

Procedia PDF Downloads 165

Authors: P. K. Singhal, R. Naresh, V. Sharma

Abstract:

This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

Procedia PDF Downloads 365

Authors: Emanuele Bonamente, Andrea Aquino, Franco Cotana

Abstract:

The exploitation of the low-temperature geothermal resource via ground-source heat pumps is often limited by the high investment cost mainly due to borehole drilling. From the monitoring of a prototypal system currently used by a commercial building, it was found that a simple upgrade of the conventional layout, obtained including a thermal storage between the ground-source heat exchangers and the heat pump, can optimize the ground energy exploitation requiring for shorter/fewer boreholes. For typical applications, a reduction of up to 66% with respect to the conventional layout can be easily achieved. Results from the monitoring campaign of the prototype are presented in this paper, and upgrades of the thermal storage using phase change materials (PCMs) are proposed using computational fluid dynamics simulations. The PCM thermal storage guarantees an improvement of the system coefficient of performance both for summer cooling and winter heating (up to 25%). A drastic reduction of the storage volume (approx. 1/10 of the original size) is also achieved, making it possible to easily place it within the technical room, avoiding extra costs for underground displacement. A preliminary optimization of the PCM geometry is finally proposed.

Keywords: computational fluid dynamics (CFD), geothermal energy, ground-source heat pumps, phase change materials (PCM)

Procedia PDF Downloads 254

Authors: Meshal Alsaiari

Abstract:

Fused Deposition Modeling is one of the additive manufacturing technologies the industry is shifting to nowadays due to its simplicity and low affordable cost. The fabrication processing parameters predominantly influence FDM part strength and mechanical properties. This presentation will demonstrate the influences of the two manufacturing parameters on the tensile testing evaluation indexes, infill density, and Printing Orientation, which were analyzed to create a piping spacer suitable for oil and gas applications. The tensile specimens are made of two polymers, Acrylonitrile Styrene Acrylate (ASA) and High high-impact polystyrene (HIPS), to characterize the mechanical properties performance for creating the final product. The mechanical testing was carried out per the ASTM D638 testing standard, following Type IV requirements. Taguchi's experiment design using an L-9 orthogonal array was used to evaluate the performance output and identify the optimal manufacturing factors. The experimental results demonstrate that the tensile test is more pronounced with 100% infill for ASA and HIPS samples. However, the printing orientations varied in reactions; ASA is maximum at 0 degrees while HIPS shows almost similar percentages between 45 and 90 degrees. Taguchi-Gray integrated methodology was adopted to minimize the response and recognize optimal fabrication factors combinations.

Keywords: FDM, ASTM D638, tensile testing, acrylonitrile styrene acrylate

Procedia PDF Downloads 77

Authors: T. Sattarpour, D. Nazarpour

Abstract:

This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.

Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)

Procedia PDF Downloads 290

Authors: Qais M. Yousef, Yasmeen A. Alshaer

Abstract:

Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

Procedia PDF Downloads 166

Authors: Hanlin Liu, Hua Li, Yintan AI

Abstract:

Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

Procedia PDF Downloads 31

Authors: Irati Barandiaran, Xabier Velasco-Iza, Galder Kortaberria

Abstract:

Hybrid inorganic/organic nanostructured materials based on block copolymers are of considerable interest in the field of Nanotechnology, taking into account that these nanocomposites combine the properties of polymer matrix and the unique properties of the added nanoparticles. The use of block copolymers as templates offers the opportunity to control the size and the distribution of inorganic nanoparticles. This research is focused on the surface modification of inorganic nanoparticles to reach a good interface between nanoparticles and polymer matrices which hinders the nanoparticle aggregation. The aim of this work is to obtain a good and selective dispersion of Fe3O4 magnetic nanoparticles into different types of block copolymers such us, poly(styrene-b-methyl methacrylate) (PS-b-PMMA), poly(styrene-b-ε-caprolactone) (PS-b-PCL) poly(isoprene-b-methyl methacrylate) (PI-b-PMMA) or poly(styrene-b-butadiene-b-methyl methacrylate) (SBM) by using different grafting strategies. Fe3O4 magnetic nanoparticles have been surface-modified with polymer or block copolymer brushes following different grafting methods (grafting to, grafting from and grafting through) to achieve a selective location of nanoparticles into desired domains of the block copolymers. Morphology of fabricated hybrid nanocomposites was studied by means of atomic force microscopy (AFM) and with the aim to reach well-ordered nanostructured composites different annealing methods were used. Additionally, nanoparticle amount has been also varied in order to investigate the effect of the nanoparticle content in the morphology of the block copolymer. Nowadays different characterization methods were using in order to investigate magnetic properties of nanometer-scale electronic devices. Particularly, two different techniques have been used with the aim of characterizing synthesized nanocomposites. First, magnetic force microscopy (MFM) was used to investigate qualitatively the magnetic properties taking into account that this technique allows distinguishing magnetic domains on the sample surface. On the other hand, magnetic characterization by vibrating sample magnetometer and superconducting quantum interference device. This technique demonstrated that magnetic properties of nanoparticles have been transferred to the nanocomposites, exhibiting superparamagnetic behavior similar to that of the maghemite nanoparticles at room temperature. Obtained advanced nanostructured materials could found possible applications in the field of dye-sensitized solar cells and electronic nanodevices.

Keywords: atomic force microscopy, block copolymers, grafting techniques, iron oxide nanoparticles

Procedia PDF Downloads 250

Authors: Sarra Kitanou

Abstract:

Membrane bioreactor (MBR) systems are one of the most widely used wastewater treatment processes for various municipal and industrial waste streams. It is based on complex interactions between biological processes, filtration process and rheological properties of the liquid to be treated. Its complexity makes understanding system operation and optimization more difficult, and traditional methods based on experimental analysis are costly and time consuming. The present study was based on an external membrane bioreactor pilot scale with ceramic membranes compared to conventional activated sludge process (ASP) plant. Both systems received their influent from a domestic wastewater. The membrane bioreactor (MBR) produced an effluent with much better quality than ASP in terms of total suspended solids (TSS), organic matter such as biological oxygen demand (BOD) and chemical oxygen demand (COD), total Phosphorus and total Nitrogen. Other effluent quality parameters also indicate substantial differences between ASP and MBR. This study leads to conclude that in the case domestic wastewater, MBR treatment has excellent effluent quality. Hence, the replacement of the ASP by the MBRs may be justified on the basis of their improved removal of solids, nutrients, and micropollutants. Furthermore, in terms of reuse the great quality of the treated water allows it to be reused for irrigation.

Keywords: aerobic wastewater treatment, conventional activated sludge process, membrane bioreactor, reuse for irrigation

Procedia PDF Downloads 67

Authors: Payal T. Patel, Ramakant Panchal, Ketankumar G. Patel

Abstract:

Gear in stirred vessel is one of the most critical components in machinery which has power transmission system and it is rotating machinery cost and redesign being the major constraints, there is always a great scope for a mechanical engineer to apply skills to improve the design. Gear will be most effective means of transmitting power in future machinery due to their high degree of compactness. The Galliard moved in the industry from heavy industries such as textile machinery and shipbuilding to industries such as automobile manufacture tools will necessitate the affable application of gear technology. The two-stage planetary reduction gear unit is designed to meet the output specifications. In industries, where the bevel gears are used in turret vessel to transmit the power, that unit is replaced by this planetary gearbox. Use of this type of gearbox is to get better efficiency and also the manufacturing of the bevel gear is more complex than the spur gears. Design a gearbox with the epicyclic gear train. In industries, the power transmission from gearbox to vessel is done through the bevel gears, which transmit the power at a right angle. In this work, the power is to be transmitted vertically from gearbox to vessel, which will increase the efficiency and life of gears. The arrangement of the gears is quite difficult as well as it needs high manufacturing cost and maintenance cost. The design is replaced by the planetary gearbox to reduce the difficulties, and same output is achieved but with a different arrangement of the planetary gearbox.

Keywords: planetary gearbox, epicyclic gear, optimization, dynamic balancing

Procedia PDF Downloads 346

Authors: A. Umar, A. Tamimi

Abstract:

Development of new types of concrete with improved performance is a very important issue for the whole building industry. The development is based on the optimization of the concrete mix design, with an emphasis not only on the workability and mechanical properties but also to the durability and the reliability of the concrete structure in general. Self-compacting concrete (SCC) is a high-performance material designed to flow into formwork under its own weight and without the aid of mechanical vibration. At the same time it is cohesive enough to fill spaces of almost any size and shape without segregation or bleeding. Construction time is shorter and production of SCC is environmentally friendly (no noise, no vibration). Furthermore, SCC produces a good surface finish. Despite these advantages, SCC has not gained much local acceptance though it has been promoted in the Middle East for the last ten to twelve years. The reluctance in utilizing the advantages of SCC, in Bahrain, may be due to lack of research or published data pertaining to locally produced SCC. Therefore, there is a need to conduct studies on SCC using locally available material supplies. From the literature, it has been observed that the use of viscosity modifying admixtures (VMA), micro silica and glass fibers have proved to be very effective in stabilizing the rheological properties and the strength of fresh and hardened properties of self-compacting concrete (SCC). Therefore, in the present study, it is proposed to carry out investigations of SCC with combinations of various dosages of VMAs with and without micro silica and glass fibers and to study their influence on the properties of fresh and hardened concrete.

Keywords: self-compacting concrete, viscosity modifying admixture, micro silica, glass fibers

Procedia PDF Downloads 642

Authors: Naum Simanovsky MD, Michael Zaidman MD, Vladimir Goldman MD.

Abstract:

105 plain AP radiographs of normal adult pelvises (210 hips) were evaluated. Different measurements of normal and dysplastic hip joints in 45 patients were analyzed. Attempt was made to establish reproducible, easy applicable in practice approach for evaluation and follow up of patients with hip dysplasia. The youngest of our patients was 11 years and the oldest was 47 years. Only one of our patients needed conversion to total hip replacement (THR) during ten years of follow-up. It was emphasized that selected set of measurements was built for purpose to serve, especially those who’s scheduled or undergone PAO. This approach was based on concept of acetabulum-femoral head complex and importance of reliable reference points of measurements. Comparative analysis of measured parameters between normal and dysplastic hips was performed. Among 10 selected parameters, we use already well established such as lateral center edge angle and head extrusion index, but to serve specific group of patients with PAO, new parameters were considered such as complex lateralization and complex proximal migration. By our opinion proposed approach is easy applicable in busy clinical practice, satisfactorily delineate hip pathology and give to surgeon who’s going to perform PAO guidelines in condensed form. It is also useful tools for postoperative follow up after PAO.

Keywords: periacetabular osteotomy, plain radiograph’s measurements, adolescents, adult

Procedia PDF Downloads 55

Authors: Ilham Ihoume, Rachid Tadili, Nora Arbaoui

Abstract:

The use of solar energy in agricultural applications has gained significant at‎tention ‎‎in recent years as a sustainable and environmentally friendly alternative to ‎‎conventional energy sources. In particular, solar drying of crops has ‎been identified ‎‎as an effective method to preserve agricultural produce while ‎minimizing energy ‎‎consumption and reducing carbon emissions. In this context, the present study ‎‎aims to evaluate the thermo-economic and ecological ‎performance of a solar-electric hybrid greenhouse dryer designed for grape ‎drying. The proposed system ‎‎integrates solar collectors, an electric heater, ‎and a greenhouse structure to create a ‎‎controlled and energy-efficient environment for grape drying. The thermo-economic assessment involves the ‎analysis of the thermal performance, energy ‎‎consumption, and cost-effectiveness of the solar-electric hybrid greenhouse dryer. ‎‎On the other ‎hand, the ecological assessment focuses on the environmental impact ‎‎of the ‎system in terms of carbon emissions and sustainability. The findings of this ‎‎‎study are expected to contribute to the development of sustainable agricultural ‎‎practices and the promotion of renewable energy technologies in the ‎context of ‎‎food production. Moreover, the results may serve as a basis for the ‎design and ‎‎optimization of similar solar drying systems for other crops and ‎regions.‎

Keywords: solar energy, sustainability, agriculture, energy ‎‎analysis‎

Procedia PDF Downloads 42

Authors: Gabriel Sitler, Yousef Sardahi, Asad Salem

Abstract:

This paper presents an optimal and robust sliding mode controller (SMC) to regulate the position of the knee joint angle for patients suffering from knee injuries. The controller imitates the role of active orthoses that produce the joint torques required to overcome gravity and loading forces and regain natural human movements. To this end, a mathematical model of the shank, the lower part of the leg, is derived first and then used for the control system design and computer simulations. The design of the controller is carried out in optimal and multi-objective settings. Four objectives are considered: minimization of the control effort and tracking error; and maximization of the control signal smoothness and closed-loop system’s speed of response. Optimal solutions in terms of the Pareto set and its image, the Pareto front, are obtained. The results show that there are trade-offs among the design objectives and many optimal solutions from which the decision-maker can choose to implement. Also, computer simulations conducted at different points from the Pareto set and assuming knee squat movement demonstrate competing relationships among the design goals. In addition, the proposed control algorithm shows robustness in tracking a standard gait signal when accounting for uncertainty in the shank’s parameters.

Keywords: optimal control, multi-objective optimization, sliding mode control, wearable knee exoskeletons

Procedia PDF Downloads 72

Authors: Ons Sassi, Wahiba Ramdane Cherif-Khettaf, Ammar Oulamara

Abstract:

In this paper, we consider a new real-life Heterogenous Electric Vehicle Routing Problem with Time Dependant Charging Costs and a Mixed Fleet (HEVRP-TDMF), in which a set of geographically scattered customers have to be served by a mixed fleet of vehicles composed of a heterogenous fleet of Electric Vehicles (EVs), having different battery capacities and operating costs, and Conventional Vehicles (CVs). We include the possibility of charging EVs in the available charging stations during the routes in order to serve all customers. Each charging station offers charging service with a known technology of chargers and time-dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are not necessarily compatible with all available charging technologies and a partial charging is allowed. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and then minimize the total travel and charging costs. In this study, we present a Mixed Integer Programming Model and develop a Charging Routing Heuristic and a Local Search Heuristic based on the Inject-Eject routine with three different insertion strategies. All heuristics are tested on real data instances.

Keywords: charging problem, electric vehicle, heuristics, local search, optimization, routing problem

Procedia PDF Downloads 457

Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

Abstract:

Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

Procedia PDF Downloads 113

Authors: Helena Macedo, Larissa Tomaz, Levi Guimarães, Luís Cerqueira-Pinto, José Dinis-Carvalho

Abstract:

In the context of retail logistics, the pursuit of operational efficiency and cost optimization involves a rigorous distinction between value-added and non-value-added activities. In today's competitive market, optimizing efficiency and reducing operational costs are paramount for retail businesses. This research paper focuses on the development of a classification model adapted to the retail sector, specifically examining internal logistics processes. Based on a comprehensive analysis conducted in a retail supermarket located in the north of Portugal, which covered various aspects of internal retail logistics, this study questions the concept of value and the definition of wastes traditionally applied in a manufacturing context and proposes a new way to assess activities in the context of internal logistics. This study combines quantitative data analysis with qualitative evaluations. The proposed classification model offers a systematic approach to categorize operations within the retail logistics chain, providing actionable insights for decision-makers to streamline processes, enhance productivity, and allocate resources more effectively. This model contributes not only to academic discourse but also serves as a practical tool for retail businesses, aiding in the enhancement of their internal logistics dynamics.

Keywords: lean retail, lean logisitcs, retail logistics, value-added and non-value-added

Procedia PDF Downloads 45

Authors: Dominika Pihikova, Stefan Belicky, Tomas Bertok, Roman Sokol, Petra Kubanikova, Jan Tkac

Abstract:

Since aberrant glycosylation is frequently accompanied by both physiological and pathological processes in a human body (cancer, AIDS, inflammatory diseases, etc.), the analysis of tumor-associated glycan patterns have a great potential for the development of novel diagnostic approaches. Moreover, altered glycoforms may assist as a suitable tool for the specificity and sensitivity enhancement in early-stage prostate cancer diagnosis. In this paper we discuss the construction and optimization of ultrasensitive sandwich biosensor platform employing lectin as glycan-binding protein. We focus on the immunoassay development, reduction of non-specific interactions and final glycoprofiling of human serum samples including both prostate cancer (PCa) patients and healthy controls. The fabricated biosensor was measured by label-free electrochemical impedance spectroscopy (EIS) with further lectin microarray verification. Furthermore, we analyzed different biosensor interfaces with atomic force microscopy (AFM) in nanomechanical mapping mode showing a significant differences in the altitude. These preliminary results revealing an elevated content of α-2,3 linked sialic acid in PCa patients comparing with healthy controls. All these experiments are important step towards development of point-of-care devices and discovery of novel glyco-biomarkers applicable in cancer diagnosis.

Keywords: biosensor, glycan, lectin, prostate cancer

Procedia PDF Downloads 358

Authors: Lifar M. S., Tereshchenko A. A., Bulgakov A. N., Guda S. A., Guda A. A., Soldatov A. V.

Abstract:

Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes - adsorption, activation, reaction, and desorption. These processes, in turn, depend on the inlet feed concentrations, temperature, and pressure. At stationary conditions, the active surface sites may be poisoned by reaction byproducts or blocked by thermodynamically adsorbed gaseous reagents. Thus, the yield of reaction products can significantly drop. On the contrary, the dynamic control accounts for the changes in the surface properties and adjusts reaction parameters accordingly. Therefore dynamic control may be more efficient than stationary control. In this work, a reinforcement learning algorithm has been applied to control the simulation of CO oxidation on a catalyst. The policy gradient algorithm is learned to maximize the CO₂ production rate based on the CO and O₂ flows at a given time step. Nonstationary solutions were found for the regime with surface deactivation. The maximal product yield was achieved for periodic variations of the gas flows, ensuring a balance between available adsorption sites and the concentration of activated intermediates. This methodology opens a perspective for the optimization of catalytic reactions under nonstationary conditions.

Keywords: artificial intelligence, catalyst, co oxidation, reinforcement learning, dynamic control

Procedia PDF Downloads 109

Authors: Nima Mahmoudi, Hamzeh Khazaei

Abstract:

Serving machine learning inference workloads on the cloud is still a challenging task at the production level. The optimal configuration of the inference workload to meet SLA requirements while optimizing the infrastructure costs is highly complicated due to the complex interaction between batch configuration, resource configurations, and variable arrival process. Serverless computing has emerged in recent years to automate most infrastructure management tasks. Workload batching has revealed the potential to improve the response time and cost-effectiveness of machine learning serving workloads. However, it has not yet been supported out of the box by serverless computing platforms. Our experiments have shown that for various machine learning workloads, batching can hugely improve the system’s efficiency by reducing the processing overhead per request. In this work, we present MLProxy, an adaptive reverse proxy to support efficient machine learning serving workloads on serverless computing systems. MLProxy supports adaptive batching to ensure SLA compliance while optimizing serverless costs. We performed rigorous experiments on Knative to demonstrate the effectiveness of MLProxy. We showed that MLProxy could reduce the cost of serverless deployment by up to 92% while reducing SLA violations by up to 99% that can be generalized across state-of-the-art model serving frameworks.

Keywords: serverless computing, machine learning, inference serving, Knative, google cloud run, optimization

Procedia PDF Downloads 164

Authors: Karolina Mazur, Stanislaw Kuciel

Abstract:

Polylactides (PLA) and polyhydroxyalkanoates (PHA) are the two groups of biodegradable and biocompatible thermoplastic polymers most commonly utilised in medicine and rehabilitation. The aim of this work is to determine the changes in the strength properties and the microstructures taking place in biodegradable polymer composites during their long-term storage in a highly cooled environment (i.e. a freezer at -24ºC) and to initially assess the durability of such biocomposites when used as single-use elements of rehabilitation or medical equipment. It is difficult to find any information relating to the feasibility of long-term storage of technical products made of PLA or PHA, but nonetheless, when using these materials to make products such as casings of hair dryers, laptops or mobile phones, it is safe to assume that without storing in optimal conditions their degradation time might last even several years. SEM images and the assessment of the strength properties (tensile, bending and impact testing) were carried out and the density and water sorption of two polymers, PLA and PHA (NaturePlast PLE 001 and PHE 001), filled with cellulose fibres (corncob grain – Rehofix MK100, Rettenmaier&Sohne) up to 10 and 20% mass were determined. The biocomposites had been stored at a temperature of -24ºC for 4 years. In order to find out the changes in the strength properties and the microstructure taking place after such a long time of storage, the results of the assessment have been compared with the results of the same research carried out 4 years before. Results shows a significant change in the manner of fractures – from ductile with developed surface for the PHA composite with corncob grain when the tensile testing was performed directly after the injection into a more brittle state after 4 years of storage, which is confirmed by the strength tests, where a decrease of deformation is observed at point of fracture. The research showed that there is a way of storing medical devices made out of PLA or PHA for a reasonably long time, as long as the required temperature of storage is met. The decrease of mechanical properties found during tensile testing and bending for PLA was less than 10% of the tensile strength, while the modulus of elasticity and deformation at fracturing slightly rose, which may implicate the beginning of degradation processes. The strength properties of PHA are even higher after 4 years of storage, although in that case the decrease of deformation at fracturing is significant, reaching even 40%, which suggests its degradation rate is higher than that of PLA. The addition of natural particles in both cases only slightly increases the biodegradation.

Keywords: biocomposites, PLA, PHA, storage

Procedia PDF Downloads 256

Authors: Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Strahinja Z. Kovačević

Abstract:

Benzimidazoles are a group of compounds with significant antibacterial, antifungal and anticancer activity. The studied compounds consist of the main benzimidazole structure with different combinations of substituens. This study is based on the two-dimensional and three-dimensional molecular modeling and calculation of molecular descriptors (physicochemical and lipophilicity descriptors) of structurally diverse benzimidazoles. Molecular modeling was carried out by using ChemBio3D Ultra version 14.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The obtained set of molecular descriptors was used in principal component analysis (PCA) of possible similarities and dissimilarities among the studied derivatives. After the molecular modeling, the quantitative structure-property relationship (QSPR) analysis was applied in order to get the mathematical models which can be used in prediction of pKb values of structurally similar benzimidazoles. The obtained models are based on statistically valid multiple linear regression (MLR) equations. The calculated cross-validation parameters indicate the high prediction ability of the established QSPR models. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina.

Keywords: benzimidazoles, chemometrics, molecular modeling, molecular descriptors, QSPR

Procedia PDF Downloads 277