Search results for: steel frame ground structure optimization

Authors: H. M. Ferreira, H. Cockings, D. F. Gordon

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Climate change is driving a transition in the energy sector, with low-carbon energy sources such as hydrogen (H2) emerging as an alternative to fossil fuels. However, the successful implementation of a hydrogen economy requires an expansion of hydrogen production, transportation and storage capacity. The costs associated with this transition are high but can be partly mitigated by adapting the current oil and natural gas networks, such as pipeline, an important component of the hydrogen infrastructure, to transport pure or blended hydrogen. Steel pipelines are designed to withstand fatigue, one of the most common causes of pipeline failure. However, it is well established that some materials, such as steel, can fail prematurely in service when exposed to hydrogen-rich environments. Therefore, it is imperative to evaluate how defects (e.g. inclusions, dents, and pre-existing cracks) will interact with hydrogen under cyclic loading and, ultimately, to what extent hydrogen induced failure will limit the service conditions of steel pipelines. This presentation will explore how the exposure of API 5L X65 to a hydrogen-rich environment and cyclic loads will influence its susceptibility to hydrogen induced failure. That evaluation will be performed by a combination of several techniques such as hydrogen permeation testing (ISO 17081:2014), fatigue crack growth (FCG) testing (ISO 12108:2018 and AFGROW modelling), combined with microstructural and fractographic analysis. The development of a FCG test setup coupled with an electrochemical cell will be discussed, along with the advantages and challenges of measuring crack growth rates in electrolytic hydrogen environments. A detailed assessment of several electrolytic charging conditions will also be presented, using hydrogen permeation testing as a method to correlate the different charging settings to equivalent hydrogen concentrations and effective diffusivity coefficients, not only on the base material but also on the heat affected zone and weld of the pipelines. The experimental work is being complemented with AFGROW, a useful FCG modelling software that has helped inform testing parameters and which will also be developed to ultimately help industry experts perform structural integrity analysis and remnant life characterisation of pipeline steels under representative conditions. The results from this research will allow to conclude if there is an acceleration of the crack growth rate of API 5L X65 under the influence of a hydrogen-rich environment, an important aspect that needs to be rectified instandards and codes of practice on pipeline integrity evaluation and maintenance.

Keywords: AFGROW, electrolytic hydrogen charging, fatigue crack growth, hydrogen, pipeline, steel

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Authors: Ishiyaku Abdulkadir, Satish Kumar J

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Land Productivity is a measure of the greenness of above-ground biomass in health and potential gain and is not related to agricultural productivity. Monitoring land productivity dynamics is essential to identify, especially when and where the trend is characterized degraded for mitigation measures. This research aims to monitor the land productivity trend of Gombe State between 2001 and 2015. QGIS was used to compute NDVI from AVHRR/MODIS datasets in a cloud-based method. The result appears that land area with improving productivity account for 773sq.km with 4.31%, stable productivity traced to 4,195.6 sq.km with 23.40%, stable but stressed productivity represent 18.7sq.km account for 0.10%, early sign of decline productivity occupied 5203.1sq.km with 29%, declining productivity account for 7019.7sq.km, represent 39.2%, water bodies occupied 718.7sq.km traced to 4% of the state’s area.

Keywords: above-ground biomass, dynamics, land productivity, man-environment relationship

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Authors: Khaled Ben Oualid Medani, Samir Sayah

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The Optimal Reactive Power Dispatch (ORPD) problem has been solved and analysed usually in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, power system analysis, real power loss minimization, contingency condition, metaheuristic technique, whale optimization algorithm

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Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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Authors: Asselah Amel, Affif Chaouche M'yassa, Toudji Amira, Tazerouti Amel

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This study covers two aspects ; the biodegradability and the performances in corrosion inhibition of a series of synthetized surfactants namely Φ- sodium methyl ester sulfonates (Φ-MES: C₁₂-MES, C₁₄-MES and C₁₆-MES. The biodegradability of these organic compounds was studied using the respirometric method, ‘the standard ISO 9408’. Degradation was followed by analysis of dissolved oxygen using the dissolved oxygen meter over 28 days and the results were compared with that of sodium dodecyl sulphate (SDS). The inoculum used consists of activated sludge taken from the aeration basin of the biological wastewater treatment plant in the city of Boumerdes-Algeria. In addition, the anticorrosive performances of Φ-MES surfactants on a carbon steel "X70" were evaluated in an injection water from a well of Hassi R'mel region- Algeria, known as Baremian water, and are compared to sodium dodecyl sulphate. Two technics, the weight loss and the linear polarization resistance corrosion rate (LPR) are used allowing to investigate the relationships between the concentrations of these synthetized surfactants and their surface properties, surface coverage and inhibition efficiency. Various adsorption isotherm models were used to characterize the nature of adsorption and explain their mechanism. The results show that the MES anionic surfactants was readily biodegradable, degrading faster than SDS, about 88% for C₁₂-MES compared to 66% for the SDS. The length of their carbon chain affects their biodegradability; the longer the chain, the lower the biodegradability. The inhibition efficiency of these surfactants is around 78.4% for C₁₂-MES, 76.60% for C₁₄-MES and 98.19% for C₁₆-MES and increases with their concentration and reaches a maximum value around their critical micelle concentrations ( CMCs). Scanning electron microscopy coupled to energy dispersive X-ray spectroscopy allowed to the visualization of a good adhesion of the protective film formed by the surfactants to the surface of the steel. The studied surfactants show the Langmuirian behavior from which the thermodynamic parameters as adsorption constant (Kads), standard free energy of adsorption (〖∆G〗_ads^0 ) are determined. Interaction of the surfactants with steel surface have involved physisorptions.

Keywords: corrosion, surfactants, adsorption, adsorption isotherems

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Authors: Siamak Epackachi, Andrew S. Whittaker, Amit H. Varma

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There are a large number of methods to connect SC walls to RC foundations. An experimental study of the cyclic nonlinear behavior of SC walls in the NEES laboratory at the University at Buffalo used a connection detail involving the post-tensioning of a steel baseplate to the SC wall to a RC foundation. This type of connection introduces flexibility that influenced substantially the global response of the SC walls. The assumption of a rigid base, which would be commonly made by practitioners, would lead to a substantial overestimation of initial stiffness. This paper presents an analytical approach to characterize the rotational flexibility and to predict the initial stiffness of flexure-critical SC wall piers with baseplate connection. The good agreement between the analytical and test results confirmed the utility of the proposed method for calculating the initial stiffness of an SC wall with baseplate connection.

Keywords: steel-plate composite shear wall, flexure-critical wall, cyclic loading, analytical model

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Authors: Viranshu Kumar, Hitesh Arora, Pradeep Joshi

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SS 304 is Austenitic stainless steel with Chromium and Nickel as basic constituents. It has excellent corrosion resistance properties and very good weldability. Austenitic stainless steels have superior mechanical properties at high temperatures and are used extensively in a range of applications. SS 304L has wide applications in various industries viz. Nuclear, Pharmaceutical, marine, chemical etc. due to its excellent applications and ease of joining this material has become very popular for fabrication as well as weld surfacing. Austenitic stainless steels have a tendency to form chromium depleted zones at the grain boundaries during welding and heat treatment, where chromium combines with available carbon in the vicinity of the grain boundaries, to produce an area depleted in chromium, and thus becomes susceptible to intergranular corrosion. This phenomenon is known as sensitization.

Keywords: sensitization, SS 304, GTAW, mechanical properties, carbideprecipitationHAZ, microstructure, micro hardness, tensile strength

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Authors: K. Kusakana

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A hybrid energy system is a combination of renewable energy sources with back up, as well as a storage system used to respond to given load energy requirements. Given that the electrical output of each renewable source is fluctuating with changes in weather conditions, and since the load demand also varies with time; one of the main attributes of hybrid systems is to be able to respond to the load demand at any time by optimally controlling each energy source, storage and back-up system. The induced optimization problem is to compute the optimal operation control of the system with the aim of minimizing operation costs while efficiently and reliably responding to the load energy requirement. Current optimization research and development on hybrid systems are mainly focusing on the sizing aspect. Thus, the aim of this paper is to report on the state-of-the-art of optimal operation control of hybrid renewable energy systems. This paper also discusses different challenges encountered, as well as future developments that can help in improving the optimal operation control of hybrid renewable energy systems.

Keywords: renewable energies, hybrid systems, optimization, operation control

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Authors: Elena Vinogradova, Aleksei Pleshakov, Aleksei Yakovlev

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During the flight of a supersonic aircraft under various conditions (altitude, Mach, etc.), it becomes necessary to coordinate the operating modes of the air intake and engine. On the supersonic aircraft, it’s been done by changing various control factors (the angle of rotation of the wedge panels and etc.). This paper investigates the possibility of using modern optimization methods to determine the optimal position of the supersonic air intake wedge panels in order to maximize the total pressure recovery coefficient. Modern software allows us to conduct auto-optimization, which determines the optimal position of the control elements of the investigated product to achieve its maximum efficiency. In this work, the flow in the supersonic aircraft inlet has investigated and optimized the operation of the flaps of the supersonic inlet in an aircraft in a 2-D setting. This work has done using ANSYS CFX software. The supersonic aircraft inlet is a flat adjustable external compression inlet. The braking surface is made in the form of a three-stage wedge. The IOSO NM software package was chosen for optimization. Change in the position of the panels of the input device is carried out by changing the angle between the first and second steps of the three-stage wedge. The position of the rest of the panels is changed automatically. Within the framework of the presented work, the position of the moving air intake panel was optimized under fixed flight conditions of the aircraft under a certain engine operating mode. As a result of the numerical modeling, the distribution of total pressure losses was obtained for various cases of the engine operation, depending on the incoming flow velocity and the flight altitude of the aircraft. The results make it possible to obtain the maximum total pressure recovery coefficient under given conditions. Also, the initial geometry was set with a certain angle between the first and second wedge panels. Having performed all the calculations, as well as the subsequent optimization of the aircraft input device, it can be concluded that the initial angle was set sufficiently close to the optimal angle.

Keywords: optimal angle, optimization, supersonic air intake, total pressure recovery coefficient

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Authors: M. Suresh Kumar, K. Ramani

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This paper proposed the harmonic elimination of Cascaded H-Bridge Multi-Level Inverter by using Selective Harmonic Elimination-Pulse Width Modulation method programmed with Particle Swarm Optimization algorithm. PSO method determine proficiently the required switching angles to eliminate low order harmonics up to the 11th order from the inverter output voltage waveform while keeping the magnitude of the fundamental harmonics at the desired value. Results demonstrate that the proposed method does efficiently eliminate a great number of specific harmonics and the output voltage is resulted in minimum Total Harmonic Distortion. The results shown that the PSO algorithm attain successfully to the global solution faster than other algorithms.

Keywords: multi-level inverter, Selective Harmonic Elimination Pulse Width Modulation (SHEPWM), Particle Swarm Optimization (PSO), Total Harmonic Distortion (THD)

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Authors: Ipek Kivanc, Demet Ozgur-Unluakin

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Over the past years, technological innovations and advancements have played an important role in the industrial world. Due to technological improvements, the degree of complexity of the systems has increased. Hence, all systems are getting more uncertain that emerges from increased complexity, resulting in more cost. It is challenging to cope with this situation. So, implementing efficient planning of maintenance activities in such systems are getting more essential. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for stochastic sequential decision problems under uncertainty. Although maintenance optimization in a dynamic environment can be modeled as such a sequential decision problem, POMDPs are not widely used for tackling maintenance problems. However, they can be well-suited frameworks for obtaining optimal maintenance policies. In the classical representation of the POMDP framework, the system is denoted by a single node which has multiple states. The main drawback of this classical approach is that the state space grows exponentially with the number of state variables. On the other side, factored representation of POMDPs enables to simplify the complexity of the states by taking advantage of the factored structure already available in the nature of the problem. The main idea of factored POMDPs is that they can be compactly modeled through dynamic Bayesian networks (DBNs), which are graphical representations for stochastic processes, by exploiting the structure of this representation. This study aims to demonstrate how maintenance planning of dynamic systems can be modeled with factored POMDPs. An empirical maintenance planning problem of a dynamic system consisting of four partially observable components deteriorating in time is designed. To solve the empirical model, we resort to Symbolic Perseus solver which is one of the state-of-the-art factored POMDP solvers enabling approximate solutions. We generate some more predefined policies based on corrective or proactive maintenance strategies. We execute the policies on the empirical problem for many replications and compare their performances under various scenarios. The results show that the computed policies from the POMDP model are superior to the others. Acknowledgment: This work is supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) under grant no: 117M587.

Keywords: factored representation, maintenance, multi-component system, partially observable Markov decision processes

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Authors: Eman Alzahrani, Hala M. Abo-Dief, Ashraf T. Mohamed

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The present work is aimed at examining carbon steel oil pipelines corrosion using three natural extracts (Eruca Sativa, Rosell and Mango peels) that are used as inhibitors of different concentrations ranging from 0.05-0.1wt. %. Two sulphur compounds are used as corrosion mediums. Weight loss method was used for measuring the corrosion rate of the carbon steel specimens immersed in technical white oil at 100ºC at various time intervals in absence and presence of the two sulphur compounds. The corroded specimens are examined using the chemical wear test, scratch test and hardness test. The scratch test is carried out using scratch loads from 0.5 Kg to 2.0 Kg. The scratch width is obtained at various scratch load and test conditions. The Brinell hardness test is carried out and investigated for both corroded and inhibited specimens. The results showed that three natural extracts can be used as environmentally friendly corrosion inhibitors.

Keywords: inhibition, natural extract, oil pipelines corrosion, sulphur compounds

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Authors: Yue-Tzu Yang, Peng-Jen Chen

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The present study deals with the numerical optimization of wavy channel with the help of genetic algorithm (GA). Three design variables related to the wave amplitude (A), the wavelength (λ) and the channel aspect ratio (α) are chosen and their ranges are decided through preliminary calculations of three-dimensional Navier-stokes and energy equations. A parametric study is also performed to show the effects of different design variables on the overall performance of the wavy channel. Objective functions related to the heat transfer and pressure drop, performance factor (PF) is formulated to analyze the performance of the wavy channel. The numerical results show that the wave amplitude and the channel aspect ratio have significant effects on the thermal performance. It can improve the performance of the wavy channels by increasing wave amplitude or decreasing the channel aspect ratio. Increasing wavelengths have no significant effects on the heat transfer performance.

Keywords: wavy channel, genetic algorithm, optimization, numerical simulation

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Authors: Georges Ghazi, Marc-Henry Devillers, Ruxandra M. Botez

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Aircraft flight trajectory optimization has been identified to be a promising solution for reducing both airline costs and the aviation net carbon footprint. Nowadays, this role has been mainly attributed to the flight management system. This system is an onboard multi-purpose computer responsible for providing the crew members with the optimized flight plan from a destination to the next. To accomplish this function, the flight management system uses a variety of look-up tables to compute the optimal speed and altitude for each flight regime instantly. Because the cruise is the longest segment of a typical flight, the proposed algorithm is focused on minimizing fuel consumption for this flight phase. In this paper, a complete methodology to estimate the aircraft performance and subsequently compute the optimal speed in cruise is presented. Results showed that the obtained performance database was accurate enough to predict the flight costs associated with the cruise phase.

Keywords: Cessna Citation X, cruise speed optimization, flight cost, cost index, and golden section search

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Authors: Sebastian Kölbl, Thomas Reitmaier, Mathias Hartmann

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Trial and error approaches to adapt wearable support structures to human physiology are time consuming and elaborate. However, during preliminary design, the focus lies on understanding the interaction between exoskeleton and the human body in terms of forces and moments, namely body mechanics. For the study at hand, a multi-body simulation approach has been enhanced to evaluate actual forces and moments in a human dummy model with and without a digital mock-up of an active exoskeleton. Therefore, different motion data have been gathered and processed to perform a musculosceletal analysis. The motion data are ground reaction forces, electromyography data (EMG) and human motion data recorded with a marker-based motion capture system. Based on the experimental data, the response of the human dummy model has been calibrated. Subsequently, the scalable human dummy model, in conjunction with the motion data, is connected with the exoskeleton structure. The results of the human-machine interaction (HMI) simulation platform are in particular resulting contact forces and human joint forces to compare with admissible values with regard to the human physiology. Furthermore, it provides feedback for the sizing of the exoskeleton structure in terms of resulting interface forces (stress justification) and the effect of its compliance. A stepwise approach for the setup and validation of the modeling strategy is presented and the potential for a more time and cost-effective development of wearable support structures is outlined.

Keywords: assistive devices, ergonomic design, inverse dynamics, inverse kinematics, multibody simulation

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Authors: Hamza Shams, Sajid Saleem, Bilal A. Siddiqui

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This paper investigates the coefficient of friction at nano-levels of commercially available superhydrophobic/oleophobic coatings when applied over 316L SS. 316L Stainless Steel or Marine Stainless Steel has been selected for its widespread uses in structures, marine and biomedical applications. The coatings were investigated in harsh sand-storm and sea water environments. The particle size of the sand during the procedure was carefully selected to simulate sand-storm conditions. Sand speed during the procedure was carefully modulated to simulate actual wind speed during a sand-storm. Sample preparation was carried out using prescribed methodology by the coating manufacturer. The coating’s adhesion and thickness was verified before and after the experiment with the use of Scanning Electron Microscopy (SEM). The value for nano-level coefficient of friction has been determined using Lateral Force Microscopy (LFM). The analysis has been used to formulate a value of friction coefficient which in turn is associative of the amount of wear the coating can bear before the exposure of the base substrate to the harsh environment. The analysis aims to validate the coefficient of friction value as marketed by the coating manufacturers and more importantly test the coating in real-life applications to justify its use. It is expected that the coating would resist exposure to the harsh environment for a considerable amount of time. Further, it would prevent the sample from getting corroded in the process.

Keywords: 316L SS, scanning electron microscopy, lateral force microscopy, marine stainless steel, oleophobic coating, superhydrophobic coating

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Authors: Adamantini Loukodimou, David Weston, Shiladitya Paul

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Offshore structures are subjected to harsh environments. It is documented that carbon steel needs protection from corrosion. The combined effect of UV radiation, seawater splash, and fluctuating temperatures diminish the integrity of these structures. In addition, the possibility of damage caused by floating ice, seaborne debris, and maintenance boats make them even more vulnerable. Their inspection and maintenance when far out in the sea are difficult, risky, and expensive. The most known method of mitigating corrosion of offshore structures is the use of cathodic protection. There are several zones in an offshore wind turbine. In the atmospheric zone, due to the lack of a continuous electrolyte (seawater) layer between the structure and the anode at all times, this method proves inefficient. Thus, the use of protective coatings becomes indispensable. This research focuses on the atmospheric zone. The conversion of commercially available and conventional paint (epoxy) system to an autonomous self-healing paint system via the addition of suitable encapsulated healing agents and catalyst is investigated in this work. These coating systems, which can self-heal when damaged, can provide a cost-effective engineering solution to corrosion and related problems. When the damage of the paint coating occurs, the microcapsules are designed to rupture and release the self-healing liquid (monomer), which then will react in the presence of the catalyst and solidify (polymerization), resulting in healing. The catalyst should be compatible with the system because otherwise, the self-healing process will not occur. The carbon steel substrate will be exposed to a corrosive environment, so the use of a sacrificial layer of Zn is also investigated. More specifically, the first layer of this new coating system will be TSZA (Thermally Sprayed Zn85/Al15) and will be applied on carbon steel samples with dimensions 100 x 150 mm after being blasted with alumina (size F24) as part of the surface preparation. Based on the literature, it corrodes readily, so one additional paint layer enriched with microcapsules will be added. Also, the reaction and the curing time are of high importance in order for this bilayer system of coating to work successfully. For the first experiments, polystyrene microcapsules loaded with 3-octanoyltio-1-propyltriethoxysilane were conducted. Electrochemical experiments such as Electrochemical Impedance Spectroscopy (EIS) confirmed the corrosion inhibiting properties of the silane. The diameter of the microcapsules was about 150-200 microns. Further experiments were conducted with different reagents and methods in order to obtain diameters of about 50 microns, and their self-healing properties were tested in synthetic seawater using electrochemical techniques. The use of combined paint/electrodeposited coatings allows for further novel development of composite coating systems. The potential for the application of these coatings in offshore structures will be discussed.

Keywords: corrosion mitigation, microcapsules, offshore wind turbines, self-healing

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Authors: Julian Sandoval, Philipp Schober

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Lahar sand (lahars) is a material that originates from volcanic debris flows. During and after a volcano eruption, the lahars can move at speeds up to 22 meters per hour or more, so they can easily cover extensive areas and destroy any structure in their path. Mount Pinatubo eruption (1991) brought lahars to its vicinities, and its use has been a matter of research ever since. Lahars are often disposed of for land reclamation projects in the Manila Bay, Philippines. After reclamation, some deep loss deposits may still present and they are prone to liquefaction. To mitigate the risk of liquefaction of such deposits, Vibro compaction has been proposed and used as a ground improvement technique. Cone penetration testing (CPT) campaigns are usually initiated to monitor the effectiveness of the ground improvement works by vibro compaction. The CPT cone resistance is used to analyses the in-situ relative density of the reclaimed sand before and after compaction. Available correlations between the CPT cone resistance and the relative density are only valid for non-crushable sands. Due to the partially crushable nature of lahars, the CPT data requires to be adjusted to allow for a correct interpretation of the CPT data. The objective of this paper is to characterize the chemical and mechanical properties of the lahar sands used for an ongoing project in the Port of Manila, which comprises reclamation activities using lahars from the east of Mount Pinatubo, it investigates their effect in the proposed correction factor. Additionally, numerous CPTs were carried out in a test trial and during the execution of the project. Based on this data, the influence of the grid spacing, compaction steps and the holding time on the compaction results are analyzed. Moreover, the so-called “aging effect” of the lahars is studied by comparing the results of the CPT testing campaign at different times after the vibro compaction activities. A considerable increase in the tip resistance of the CPT was observed over time.

Keywords: vibro compaction, CPT, lahar sands, correction factor, chemical composition

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Authors: Zeev Wiesman, Paula Berman, Nitzan Meiri, Charles Linder

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Supramolecular chemistry refers to the domain of chemistry beyond that of molecules and focuses on the chemical systems made up of a discrete number of assembled molecular sub units or components. Biodiesel components self arrangements is closely related/affect their physical properties in combustion systems and emission. Due to technological difficulties, knowledge regarding the molecular packing of FAMEs (biodiesel) in the liquid phase is limited. Spectral tools such as X-ray and NMR are known to provide evidences related to molecular structure organization. Recently, it was reported by our research group that using 1H Time Domain NMR methodology based on relaxation time and self diffusion coefficients, FAMEs clusters with different motilities can be accurately studied in the liquid phase. Head to head dimarization with quasi-smectic clusters organization, based on molecular motion analysis, was clearly demonstrated. These findings about the assembly/packing of the FAME components are directly associated with fluidity/viscosity of the biodiesel. Furthermore, these findings may provide information of micro/nano-particles that are formed in the delivery and injection system of various combustion systems (affected by thermodynamic conditions). Various relevant parameters to combustion such as: distillation/Liquid Gas phase transition, cetane number/ignition delay, shoot, oxidation/NOX emission maybe predicted. These data may open the window for further optimization of FAME/diesel mixture in terms of combustion and emission.

Keywords: supermolecular chemistry, FAMEs, liquid phase, fluidity, LF-NMR

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Authors: S. Belakry, D. Fasquelle, A. Rolle, E. Capoen, R. N. Vannier, J. C. Carru

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Solid oxide fuel cells (SOFCs) are promising devices for energy conversion due to their high electrical efficiency and eco-friendly behavior. Their performance is not only influenced by the microstructural and electrical properties of the electrodes and electrolyte but also depends on the interactions at the interfaces. Nowadays, commercial SOFCs are electrically efficient at high operating temperatures, typically between 800 and 1000 °C, which restricts their real-life applications. The present work deals with the objectives to reduce the operating temperature and to develop cost-effective intermediate-temperature solid oxide fuel cells (IT-SOFCs). This work focuses on the development of metal-supported solid oxide fuel cells (MS-IT-SOFCs) that would provide cheaper SOFC cells with increased lifetime and reduced operating temperature. In the framework, the local company TIBTECH brings its skills for the manufacturing of porous metal supports. This part of the work focuses on the physical, chemical, and electrical characterizations of porous metallic supports (stainless steel 316 L and FeCrAl alloy) under different exposure conditions of temperature and atmosphere by studying oxidation, mechanical resistance, and electrical conductivity of the materials. Within the target operating temperature (i.e., 500 to 700 ° C), the stainless steel 316 L and FeCrAl alloy slightly oxidize in the air and H2, but don’t deform; whereas under Ar atmosphere, they oxidize more than with previously mentioned atmospheres. Above 700 °C under air and Ar, the two metallic supports undergo high oxidation. From 500 to 700 °C, the resistivity of FeCrAl increases by 55%. But nevertheless, the FeCrAl resistivity increases more slowly than the stainless steel 316L resistivity. This study allows us to verify the compatibility of electrodes and electrolyte materials with metallic support at the operating requirements of the IT-SOFC cell. The characterizations made in this context will also allow us to choose the most suitable fabrication process for all functional layers in order to limit the oxidation of the metallic supports.

Keywords: stainless steel 316L, FeCrAl alloy, solid oxide fuel cells, porous metallic support

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Authors: Paulinus W. Ihuah, Iyenemi Ibimina Kakulu, Victor A. Akujuru

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The development of the residential property is very expensive in Nigeria, especially as it is observed in Port Harcourt, although it is also investment costly in the other cities of Nigeria. The costly development nature incidentally reasons to the high deficits in residential property availability and affordability for the low-income people. Therefore, the main purpose of this paper is to provide sustainable accommodation design, which should improve residential property expensiveness and shortages for the low-income people. This is achieved through investigation of the tangible requirements and needs of the end-user of the property (low-income people), which thereafter would enhance sustainable and affordable residential property accommodation design for the end-users. Both the quantitative and qualitative instruments of data collection were utilised. The quantitative instrument via questionnaires was designed to examine the real needs and r requirement of the low-income people. However, the qualitative instrument via structured interview was espoused for the gathering of professionals’ opinions on the three predicted sustainable accommodation design alternatives. The analysis employed content analysis parameters, which offered a sustainable accommodation design and designed alternatives minimises costs and environmental impacts whereas exploiting the social satisfaction in residential accommodation developments. The finding underscores that sustainable accommodation design and development is practicable in Nigeria, so that cost of residential accommodation provided through this system is cheap to the low-income people. Further, erection of multi-storey residential accommodation units such as bedsit structure by utilising the concrete frame structure and building the internal and external walls with hollow concrete blocks within areas 60-130 square meters is encouraged. This paper philosophy indicates that by using sustainable accommodation design practices in Nigeria, improvements in the costs and shortages of residential accommodation can be attained for low-income people. However, policies support the government cannot be overemphasised for proper implementation of the suggested scheme.

Keywords: sustainable accommodation, housing design, residential property, low-income people

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Authors: Mohamed M. El Gendy, Ibrahim A. El Arabi, Rafeek W. Abdel-Missih, Omar A. Kandil

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Nonlinear analysis is one of the most important design and safety tools in structural engineering. Based on the finite-element method, a geometrical and material nonlinear analysis of large span reinforced concrete arches is carried out considering soil-structure interaction. The concrete section details and reinforcement distribution are taken into account. The behavior of soil is considered via Winkler's and continuum models. A computer program (NARC II) is specially developed in order to follow the structural behavior of large span reinforced concrete arches up to failure. The results obtained by the proposed model are compared with available literature for verification. This work confirmed that the geometrical and material nonlinearities, as well as soil structure interaction, have considerable influence on the structural response of reinforced concrete arches.

Keywords: nonlinear analysis, reinforced concrete arched structure, soil-structure interaction, geotechnical engineering

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Sonveer Singh, Sanjay Agrawal, D. V. Avasthi, Jayant Shekhar

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The aim of this paper is to improve the efficiency of photovoltaic thermal (PVT) system with the help of Genetic Algorithms with multi-objective function. There are some parameters that affect the efficiency of PVT system like depth and length of the channel, velocity of flowing fluid through the channel, thickness of the tedlar and glass, temperature of inlet fluid i.e. all above parameters are considered for optimization. An attempt has been made to the model and optimizes the parameters of glazed hybrid single channel PVT module when two objective functions have been considered separately. The two objective function for optimization of PVT module is overall electrical and thermal efficiency. All equations for PVT module have been derived. Using genetic algorithms (GAs), above two objective functions of the system has been optimized separately and analysis has been carried out for two cases. Two cases are: Case-I; Improvement in electrical and thermal efficiency when overall electrical efficiency is optimized, Case-II; Improvement in electrical and thermal efficiency when overall thermal efficiency is optimized. All the parameters that are used in genetic algorithms are the parameters that could be changed, and the non-changeable parameters, like solar radiation, ambient temperature cannot be used in the algorithm. It has been observed that electrical efficiency (14.08%) and thermal efficiency (19.48%) are obtained when overall thermal efficiency was an objective function for optimization. It is observed that GA is a very efficient technique to estimate the design parameters of hybrid single channel PVT module.

Keywords: genetic algorithm, energy, exergy, PVT module, optimization

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Authors: Mohamed A. Almoghalis, Osman M. Hegazy, Ibrahim F. Imam, Ali H. Elbastawessy

Abstract:

This paper presents a new hyperspectral image segmentation scheme with respect to both spatial and spectral contexts. The scheme uses the 8-pixels spatial pattern to build a weight structure that holds the number of outlier bands for each pixel among its neighborhood windows in different directions. The number of outlier bands for a pixel is obtained using bands quartile box plots profile among spatial 8-pixels pattern windows. The quartile box plot weight structure represents the spatial-spectral context in the image. Instead of starting segmentation process by single pixels, the proposed methodology starts by pixels groups that proved to share the same spectral features with respect to their spatial context. As a result, the segmentation scheme starts with Jigsaw pieces that build a mosaic image. The following step builds a model for each Jigsaw piece in the mosaic image. Each Jigsaw piece will be merged with another Jigsaw piece using KNN applied to their bands' quartile box plots profiles. The scheme iterates till required number of segments reached. Experiments use two data sets obtained from Earth Observer 1 (EO-1) sensor for Egypt and France. Initial results qualitative analysis showed encouraging results compared with ground truth. Quantitative analysis for the results will be included in the final paper.

Keywords: hyperspectral image segmentation, image processing, remote sensing, box plot

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Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

Abstract:

This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

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Authors: K. Tahir, C. Belfedal, T. Allaoui, C. Gerard, M. Doumi

Abstract:

In this paper, we presented an optimized RST controller using Particle Swarm Optimization (PSO) meta-heuristic technique of the active and reactive power regulation of a grid connected wind turbine based on a wound field synchronous generator. This regulation is achieved below the synchronous speed, by means of a maximum power point tracking algorithm. The control of our system is tested under typical wind variations and parameters variation, fault grid condition by simulation. Some results are presented and discussed to prove simplicity and efficiency of the WRSG control for WECS. On the other hand, according to simulation results, variable speed driven WRSG is not significantly impacted in fault conditions.

Keywords: wind energy, particle swarm optimization, wound rotor synchronous generator, power control, RST controller, maximum power point tracking

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Authors: Bastien Batardière, Joon Kwon

Abstract:

For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.

Keywords: convex optimization, variance reduction, adaptive algorithms, loopless

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Authors: Bounar Nedjemeddine

Abstract:

Materials with the pyrochlore lattice structure have attracted much recent attention due to their wide applications in ceramic thermal barrier coatings, high-permittivity dielectrics, and potential solid electrolytes in solid-oxide fuel cells. The work described in this paper is devoted to the synthesis and characterization of a pyrochlore structure based on lanthanum (La₂O₃) and tin (SnO₂) oxides of general formula La₂Sn₂O₇, substituted by Sr at the site La. Their structures were determined from X-ray powder diffraction using CELFER analysis. All the compositions present the space group Fd-3m. The substitution of La by Sr in the La₂Sn₂O₇ compound causes a variation of the cell parameters. The difference in charge between La³⁺ and Sr²⁺ and the difference in size cause the cell parameters to decrease from a=10.7165 A° to a=10.6848 A° for the substitution rates (x = 0.05, 0.1, 0.15 ...), which leads to a decrease in the volume of the mesh. For a substitution rate x = 0.25, there is an increase in the cell parameters (a=10.7035A°), which can be explained by a competitiveness of the size effect and the presence of a gap in the structure which go in the opposite direction.

Keywords: solid-oxide fuel cells, structure, pyrochlore, X-ray diffraction

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Authors: Yogish Huchaiah, Chandrashekara Krishnappa

Abstract:

This study considers the optimization and validation of experimental results using Multi-Functional Criteria Technique (MFCT). MFCT is concerned with structuring and solving decision and planning problems involving multiple variables. Production of biodiesel from Composite Oil Methyl Esters (COME) of Jatropha and Pongamia oils, mixed in various proportions and Biodiesel thus obtained from two step transesterification process were tested for various Physico-Chemical properties and it has been ascertained that they were within limits proposed by ASTME. They were blended with Petrodiesel in various proportions. These Methyl Esters were blended with Petrodiesel in various proportions and coded. These blends were used as fuels in a computerized CI DI engine to investigate Performance and Emission characteristics. From the analysis of results, it was found that 180MEM4B20 blend had the maximum Performance and minimum Emissions. To validate the experimental results, MFCT was used. Characteristics such as Fuel Consumption (FC), Brake Power (BP), Brake Specific Fuel Consumption (BSFC), Brake Thermal Efficiency (BTE), Carbon dioxide (CO2), Carbon Monoxide (CO), Hydro Carbon (HC) and Nitrogen oxide (NOx) were considered as dependent variables. It was found from the application of this method that the optimized combination of Injection Pressure (IP), Mix and Blend is 178MEM4.2B24. Overall corresponding variation between optimization and experimental results was found to be 7.45%.

Keywords: COME, IP, MFCT, optimization, PI, PN, PV

Procedia PDF Downloads 211