Search results for: numerical optimization

Authors: Yuanrui Xu, Zailin Yang, Yunqiu Song, Guanxixi Jiang

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It is an important subject of seismology on the influence of local topography on ground motion during earthquake. In mountainous areas with complex terrain, the construction of the tunnel is often the most effective transportation scheme. In these projects, the local terrain can be simplified into hills with different shapes, and the underground tunnel structure can be regarded as a subsurface cavity. The presence of the subsurface cavity affects the strength of the rock mass and changes the deformation and failure characteristics. Moreover, the scattering of the elastic waves by underground structures usually interacts with local terrains, which leads to a significant influence on the surface displacement of the terrains. Therefore, it is of great practical significance to study the surface displacement of local terrains with underground tunnels in earthquake engineering and seismology. In this work, the region is divided into three regions by the method of region matching. By using the fractional Bessel function and Hankel function, the complex function method, and the wave function expansion method, the wavefield expression of SH waves is introduced. With the help of a constitutive relation between the displacement and the stress components, the hoop stress and radial stress is obtained subsequently. Then, utilizing the continuous condition at different region boundaries, the undetermined coefficients in wave fields are solved by the Fourier series expansion and truncation of the finite term. Finally, the validity of the method is verified, and the surface displacement amplitude is calculated. The surface displacement amplitude curve is discussed in the numerical results. The results show that different parameters, such as radius and buried depth of the tunnel, wave number, and incident angle of the SH wave, have a significant influence on the amplitude of surface displacement. For the underground tunnel, the increase of buried depth will make the response of surface displacement amplitude increases at first and then decreases. However, the increase of radius leads the response of surface displacement amplitude to appear an opposite phenomenon. The increase of SH wave number can enlarge the amplitude of surface displacement, and the change of incident angle can obviously affect the amplitude fluctuation.

Keywords: method of region matching, scattering of SH wave, subsurface cavity, trapezoidal hill

Procedia PDF Downloads 121

Authors: Ajith Kumar S., Sankaran Namboothiri, Sankrish J., SarathKumar S., S. Anil Lal

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A numerical analysis of flow over a heated circular cylinder is done in this paper. The governing equations, Navier-Stokes, and energy equation within the Boussinesq approximation along with continuity equation are solved using hybrid FEM-FVM technique. The density gradient created due to the heating of the cylinder will induce buoyancy force, opposite to the direction of action of acceleration due to gravity, g. In the present work, the flow direction and the direction of buoyancy force are taken as same (vertical flow configuration), so that the buoyancy force accelerates the mean flow past the cylinder. The relative dominance of the buoyancy force over the inertia force is characterized by the Richardson number (Ri), which is one of the parameter that governs the flow dynamics and heat transfer in this analysis. It is well known that above a certain value of Reynolds number, Re (ratio of inertia force over the viscous forces), the unsteady Von Karman vortices can be seen shedding behind the cylinder. The shedding wake patterns could be seriously altered by heating/cooling the cylinder. The non-dimensional shedding frequency called the Strouhal number is found to be increasing as Ri increases. The aerodynamic force coefficients CL and CD are observed to change its value. In the present vertical configuration of flow over the cylinder, as Ri increases, shedding frequency gets increased and suddenly drops down to zero at a critical value of Richardson number. The unsteady vortices turn to steady standing recirculation bubbles behind the cylinder after this critical Richardson number. This phenomenon is well known in literature as "Breakdown of the Karman Vortex Street". It is interesting to see the flow structures on further increase in the Richardson number. On further heating of the cylinder surface, the size of the recirculation bubble decreases without loosing its symmetry about the horizontal axis passing through the center of the cylinder. The separation angle is found to be decreasing with Ri. Finally, we observed a second critical Richardson number, after which the the flow will be attached to the cylinder surface without any wake behind it. The flow structures will be symmetrical not only about the horizontal axis, but also with the vertical axis passing through the center of the cylinder. At this stage, there will be a "single plume" emanating from the rear stagnation point of the cylinder. We also observed the transition of the plume is a strong function of the Richardson number.

Keywords: drag reduction, flow over circular cylinder, flow control, mixed convection flow, vortex shedding, vortex breakdown

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Authors: Anwar ul Haq

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Muhammad Iqbal was arguably the most significant South Asian Islamic philosopher of the last two centuries. While he is the most revered philosopher of the region, particularly in Pakistan, he is probably the least studied philosopher outside the region. The paper offers a philosophical reconstruction of Iqbal’s view of human agency; it has three sections. Section 1 focuses on Iqbal’s starting point of reflection in practical philosophy (inspired by Kant): our consciousness of ourselves as free agents. The paper brings out Iqbal’s continuity with Kant but also his divergence, in particular his non-Kantian view that we possess a non-sensory intuition of ourselves as free personal causes. It also offer an argument on Iqbal’s behalf for this claim, which is meant as a defense against a Kantian objection to the possibility of intuition of freedom and a skeptic’s challenge to the possibility of freedom in general. Remaining part of the paper offers a reconstruction of Iqbal’s two preconditions of the possibility of free agency. Section 2 discusses the first precondition, namely, the unity of consciousness involved in thought (this is a precondition of agency whether or not it is free). The unity has two aspects, a quantitative (or numerical) aspect and a qualitative (or rational) one. Section 2 offers a defense of these two aspects of the unity of consciousness presupposed by agency by focusing, with Iqbal, on the case of inference.Section 3 discusses a second precondition of the possibility of free agency, that thought and will must be identical in a free agent. Iqbal offers this condition in relief against Bergson’s view. Bergson (on Iqbal’s reading of him) argues that freedom of the will is possible only if the will’s ends are entirely its own and are wholly undetermined by anything from without, not even by thought. Iqbal observes that Bergson’s position ends in an insurmountable dualism of will and thought. Bergson’s view, Iqbal argues in particular, rests on an untenable conception of what an end consists in. An end, correctly understood, is framed by a thinking faculty, the intellect, and not by an extra-rational faculty. The present section outlines Iqbal’s argument for this claim, which rests on the premise that ends possess a certain unity which is intrinsic to particular ends and holds together different ends, and this unity is none other than the quantitative and qualitative unity of a thinking consciousness but in its practical application. Having secured the rational origin of ends, Iqbal argues that a free will must be identical with thought, or else it will be determined from without and won’t be free on that account. Freedom of the self is not a freedom from thought but a freedom in thought: it involves the ability to live a thoughtful life.

Keywords: iqbal, freedom, will, self

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Authors: Moustafa Osman Mohammed

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Construction industry, as one of the main contributor in depletion of natural resources, influences climate change. This paper discusses incremental and evolutionary development of the proposed models for optimization of a life-cycle analysis to explicit strategy for evaluation systems. The main categories are virtually irresistible for introducing uncertainties, uptake composite structure model (CSM) as environmental management systems (EMSs) in a practice science of evaluation small and medium-sized enterprises (SMEs). The model simplified complex systems to reflect nature systems’ input, output and outcomes mode influence “framework measures” and give a maximum likelihood estimation of how elements are simulated over the composite structure. The traditional knowledge of modeling is based on physical dynamic and static patterns regarding parameters influence environment. It unified methods to demonstrate how construction systems ecology interrelated from management prospective in procedure reflects the effect of the effects of engineering systems to ecology as ultimately unified technologies in extensive range beyond constructions impact so as, - energy systems. Sustainability broadens socioeconomic parameters to practice science that meets recovery performance, engineering reflects the generic control of protective systems. When the environmental model employed properly, management decision process in governments or corporations could address policy for accomplishment strategic plans precisely. The management and engineering limitation focuses on autocatalytic control as a close cellular system to naturally balance anthropogenic insertions or aggregation structure systems to pound equilibrium as steady stable conditions. Thereby, construction systems ecology incorporates engineering and management scheme, as a midpoint stage between biotic and abiotic components to predict constructions impact. The later outcomes’ theory of environmental obligation suggests either a procedures of method or technique that is achieved in sustainability impact of construction system ecology (SICSE), as a relative mitigation measure of deviation control, ultimately.

Keywords: sustainability, environmental impact assessment, environemtal management, construction ecology

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Authors: Jessica Gu, Yu Chen

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Knowledge Management (KM) is undoubtable crucial to organizational value creation, learning, and adaptation. Although the rapidly growing KM domain has been fueled with full-fledged methodologies and technologies, studies on KM evolution that bridge the organizational performance and adaptation to the organizational environment are still rarely attempted. In particular, creation (or generation) and diffusion (or share/exchange) of knowledge are of the organizational primary concerns on the problem-solving perspective, however, the optimized distribution of knowledge creation and diffusion endeavors are still unknown to knowledge workers. This research proposed an agent-based model of knowledge creation and diffusion in an organization, aiming at elucidating how the intertwining knowledge flows at microscopic level lead to optimized organizational performance at macroscopic level through evolution, and exploring what exogenous interventions by the policy maker and endogenous adjustments of the knowledge workers can better cope with different environmental conditions. With the developed model, a series of simulation experiments are conducted. Both long-term steady-state and time-dependent developmental results on organizational performance, network and structure, social interaction and learning among individuals, knowledge audit and stocktaking, and the likelihood of choosing knowledge creation and diffusion by the knowledge workers are obtained. One of the interesting findings reveals a non-monotonic phenomenon on organizational performance under turbulent environment while a monotonic phenomenon on organizational performance under a stable environment. Hence, whether the environmental condition is turbulence or stable, the most suitable exogenous KM policy and endogenous knowledge creation and diffusion choice adjustments can be identified for achieving the optimized organizational performance. Additional influential variables are further discussed and future work directions are finally elaborated. The proposed agent-based model generates evidence on how knowledge worker strategically allocates efforts on knowledge creation and diffusion, how the bottom-up interactions among individuals lead to emerged structure and optimized performance, and how environmental conditions bring in challenges to the organization system. Meanwhile, it serves as a roadmap and offers great macro and long-term insights to policy makers without interrupting the real organizational operation, sacrificing huge overhead cost, or introducing undesired panic to employees.

Keywords: knowledge creation, knowledge diffusion, agent-based modeling, organizational performance, decision making evolution

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Authors: Sung-Hee Nam, Kwang-Gill Lee, You-Young Jo, HaeYong Kweon

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Entomopathogenic fungi is a Cordyceps species that is isolated from dead silkworm and cicada. Fungi on cicadas were described in old Chinese medicinal books and From ancient times, vegetable wasps and plant worms were widely known to have active substance and have been studied for pharmacological use. Among many fungi belonging to the genus Cordyceps, Cordyceps sinensis have been demonstrated to yield natural products possessing various biological activities and many bioactive components. Generally, It is commonly used to replenish the kidney and soothe the lung, and for the treatment of fatigue. Due to their commercial and economic importance, the demand for Cordyceps has been rapidly increased. However, a supply of Cordyceps specimen could not meet the increasing demand because of their sole dependence on field collection and habitat destruction. Because it is difficult to obtain many insect hosts in nature and the edibility of host insect needs to be verified in a pharmacological aspect. Recently, this setback was overcome that P. tenuipes was able to be cultivated in a large scale using silkworm as host. Pharmacological effects of P. tenuipes cultured on silkworm such as strengthening immune function, anti-fatigue, anti-tumor activity and controlling liver etc have been proved. They are widely commercialized. In this study, we attempted to establish a method for stable growth inhibition of P. tenuipes on silkworm hosts and an optimal condition for synnemata formation. To determine optimum culturing conditions, temperature and light conditions were varied. The length and number of synnemata was highest at 25℃ temperature and 100~300 lux illumination. On an average, the synnemata of wild P. tenuipes measures 70 ㎜ in length and 20 in number; those of the cultured strain were relatively shorter and more in number. The number of synnemata may have increased as a result of inoculating the host with highly concentrated conidia, while the length may have decreased due to limited nutrition per individual. It is not able that changes in light illumination cause morphological variations in the synnemata. However, regulation of only light and temperature could not produce stromata like perithecia, asci, and ascospores. Yamanaka reported that although a complete fruiting body can be produced under optimal culture conditions, it should be regarded as synnemata because it does not develop into an ascoma bearing ascospores.

Keywords: paecilomyces tenuipes, entomopathogenic fungi, silkworm larva, bombyx mori

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Authors: Jatin Gupta, Bishakh Bhattacharya

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With the aging process, many people start suffering from the problem of weak limbs resulting in mobility disorders and loss of sensory and motor function of limbs. Wearable robotic devices are viable solutions to help people suffering from these issues by augmenting their strength. These robotic devices, popularly known as exoskeletons aides user by providing external power and controlling the dynamics so as to achieve desired motion. Present work studies a simplified dynamic model of the human gait. A four link open chain kinematic model is developed to describe the dynamics of Single Support Phase (SSP) of the human gait cycle. The dynamic model is developed integrating mathematical models of the motion of inverted and triple pendulums. Stance leg is modeled as inverted pendulum having single degree of freedom and swing leg as triple pendulum having three degrees of freedom viz. thigh, knee, and ankle joints. The kinematic model is formulated using forward kinematics approach. Lagrangian approach is used to formulate governing dynamic equation of the model. For a system of nonlinear differential equations, numerical method is employed to obtain system response. Reference trajectory is generated using human body simulator, LifeMOD. For optimal mechanical design and controller design of exoskeleton system, it is imperative to study parameter sensitivity of the system. Six different parameters viz. thigh, shank, and foot masses and lengths are varied from 85% to 115% of the original value for the present work. It is observed that hip joint of swing leg is the most sensitive and ankle joint of swing leg is the least sensitive one. Changing link lengths causes more deviation in system response than link masses. Also, shank length and thigh mass are most sensitive parameters. Finally, the present study gives an insight on different factors that should be considered while designing a lower extremity exoskeleton.

Keywords: lower limb exoskeleton, multibody dynamics, energy based formulation, optimal design

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Authors: Surinder Pal, Ajay Gupta, Johny Khajuria

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Casting simulation helps visualize mold filling and casting solidification; predict related defects like cold shut, shrinkage porosity and hard spots; and optimize the casting design to achieve the desired quality with high yield. Flow and solidification of molten metals are, however, a very complex phenomenon that is difficult to simulate correctly by conventional computational techniques, especially when the part geometry is intricate and the required inputs (like thermo-physical properties and heat transfer coefficients) are not available. Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mockup of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome. The all casting simulation software has own requirements, like magma cast has only best for crack simulation. The latest generation software Auto CAST developed at IIT Bombay provides a host of functions to support method engineers, including part thickness visualization, core design, multi-cavity mold design with common gating and feeding, application of various feed aids (feeder sleeves, chills, padding, etc.), simulation of mold filling and casting solidification, automatic optimization of feeders and gating driven by the desired quality level, and what-if cost analysis. IIT Bombay has developed a set of applications for the foundry industry to improve casting yield and quality. Casting simulation is a fast and efficient solution for process for advanced tool which is the result of more than 20 years of collaboration with major industrial partners and academic institutions around the world. In this paper the process of casting simulation is studied.

Keywords: casting simulation software’s, simulation technique’s, casting simulation, processes

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Authors: Hamzeh Alipour, Masoumeh Bagheri, Abbasali Raz, Javad Dadgar Pakdel, Kourosh Azizi, Aboozar Soltani, Mohammad Djaefar Moemenbellah-Fard

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Background: Maggot debridement therapy is an appropriate, effective, and controlled method using sterilized larvae of Luciliasericata (L.sericata) to treat wounds. Netrin-A is an enzyme in the Laminins family which secreted from salivary gland of L.sericata with a central role in neural regeneration and angiogenesis. This study aimed to production of new recombinant Netrin-A protein of Luciliasericata larvae by baculovirus expression vector system (BEVS) in SF9. Material and methods: In the first step, gene structure was subjected to the in silico studies, which were include determination of Antibacterial activity, Prion formation risk, homology modeling, Molecular docking analysis, and Optimization of recombinant protein. In the second step, the Netrin-A gene was cloned and amplified in pTG19 vector. After digestion with BamH1 and EcoR1 restriction enzymes, it was cloned in pFastBac HTA vector. It was then transformed into DH10Bac competent cells, and the recombinant Bacmid was subsequently transfected into insect Sf9 cells. The expressed recombinant Netrin-A was thus purified in the Ni-NTA agarose. This protein evaluation was done using SDS-PAGE and western blot, respectively. Finally, its concentration was calculated with the Bradford assay method. Results: The Bacmid vector structure with Netrin-A was successfully constructed and then expressed as Netrin-A protein in the Sf9 cell lane. The molecular weight of this protein was 52 kDa with 404 amino acids. In the in silico studies, fortunately, we predicted that recombinant LSNetrin-A have Antibacterial activity and without any prion formation risk.This molecule hasa high binding affinity to the Neogenin and a lower affinity to the DCC-specific receptors. Signal peptide located between amino acids 24 and 25. The concentration of Netrin-A recombinant protein was calculated to be 48.8 μg/ml. it was confirmed that the characterized gene in our previous study codes L. sericata Netrin-A enzyme. Conclusions: Successful generation of the recombinant Netrin-A, a secreted protein in L.sericata salivary glands, and because Luciliasericata larvae are used in larval therapy. Therefore, the findings of the present study could be useful to researchers in future studies on wound healing.

Keywords: blowfly, BEVS, gene, immature insect, recombinant protein, Sf9

Procedia PDF Downloads 76

Authors: Qingqing Feng, S. Thomas Ng, Frank J. Xu, Jiduo Xing

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Faced with unprecedented challenges including aging assets, lack of maintenance budget, overtaxed and inefficient usage, and outcry for better service quality from the society, today’s infrastructure systems has become the main focus of many metropolises to pursue sustainable urban development and improve resilience. Digital twin, being one of the most innovative enabling technologies nowadays, may open up new ways for tackling various infrastructure asset management (IAM) problems. Digital twin application for IAM, as its name indicated, represents an evolving digital model of intended infrastructure that possesses functions including real-time monitoring; what-if events simulation; and scheduling, maintenance, and management optimization based on technologies like IoT, big data and AI. Up to now, there are already vast quantities of global initiatives of digital twin applications like 'Virtual Singapore' and 'Digital Built Britain'. With digital twin technology permeating the IAM field progressively, it is necessary to consider the maturity of the application and how those institutional or industrial digital twin application processes will evolve in future. In order to deal with the gap of lacking such kind of benchmark, a draft maturity model is developed for digital twin application in the IAM field. Firstly, an overview of current smart cities maturity models is given, based on which the draft Maturity Model of Digital Twin Application for Infrastructure Asset Management (MM-DTIAM) is developed for multi-stakeholders to evaluate and derive informed decision. The process of development follows a systematic approach with four major procedures, namely scoping, designing, populating and testing. Through in-depth literature review, interview and focus group meeting, the key domain areas are populated, defined and iteratively tuned. Finally, the case study of several digital twin projects is conducted for self-verification. The findings of the research reveal that: (i) the developed maturity model outlines five maturing levels leading to an optimised digital twin application from the aspects of strategic intent, data, technology, governance, and stakeholders’ engagement; (ii) based on the case study, levels 1 to 3 are already partially implemented in some initiatives while level 4 is on the way; and (iii) more practices are still needed to refine the draft to be mutually exclusive and collectively exhaustive in key domain areas.

Keywords: digital twin, infrastructure asset management, maturity model, smart city

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Authors: Ahmed Slami, Med El Amine Brixi Nigassa, Nassima Labdelli, Sofiane Soulimane, Arnaud Pothier

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Many people suffer from diabetes, a disease marked by abnormal levels of sugar in the blood; 285 million people have diabetes, 6.6% of the world adult population (in 2010), according to the International Diabetes Federation. Insulin medicament is invented to be injected into the body. Generally, the injection requires the patient to do it manually. However, in many cases he will be unable to inject the drug, saw that among the side effects of hyperglycemia is the weakness of the whole body. The researchers designed a medical device that injects insulin too autonomously by using micro-pumps. Many micro-pumps of concepts have been investigated during the last two decades for injecting molecules in blood or in the body. However, all these micro-pumps are intended for slow infusion of drug (injection of few microliters by minute). Now, the challenge is to develop micro-pumps for fast injections (1 microliter in 10 seconds) with accuracy of the order of microliter. Recently, studies have shown that only piezoelectric actuators can achieve this performance, knowing that few systems at the microscopic level were presented. These reasons lead us to design new smart microsystems injection drugs. Therefore, many technological advances are still to achieve the improvement of materials to their uses, while going through their characterization and modeling action mechanisms themselves. Moreover, it remains to study the integration of the piezoelectric micro-pump in the microfluidic platform features to explore and evaluate the performance of these new micro devices. In this work, we propose a new micro-pump model based on piezoelectric actuation with a new design. Here, we use a finite element model with Comsol software. Our device is composed of two pumping chambers, two diaphragms and two actuators (piezoelectric disks). The latter parts will apply a mechanical force on the membrane in a periodic manner. The membrane deformation allows the fluid pumping, the suction and discharge of the liquid. In this study, we present the modeling results as function as device geometry properties, films thickness, and materials properties. Here, we demonstrate that we can achieve fast injection. The results of these simulations will provide quantitative performance of our micro-pumps. Concern the spatial actuation, fluid rate and allows optimization of the fabrication process in terms of materials and integration steps.

Keywords: COMSOL software, piezoelectric, micro-pump, microfluidic

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Authors: Parul Goel, Jyeshtharaj B. Joshi, Arun K. Nayak

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Nucleate boiling is characterized by the nucleation, growth and departure of the tiny individual vapor bubbles that originate in the cavities or imperfections present in the heating surface. It finds a wide range of applications, e.g. in heat exchangers or steam generators, core cooling in power reactors or rockets, cooling of electronic circuits, owing to its highly efficient transfer of large amount of heat flux over small temperature differences. Hence, it is important to be able to predict the rate of heat transfer and the safety limit heat flux (critical heat flux, heat flux higher than this can lead to damage of the heating surface) applicable for any given system. A large number of experimental and analytical works exist in the literature, and are based on the idea that the knowledge of the bubble dynamics on the microscopic scale can lead to the understanding of the full picture of the boiling heat transfer. However, the existing data in the literature are scattered over various sets of conditions and often in disagreement with each other. The correlations obtained from such data are also limited to the range of conditions they were established for and no single correlation is applicable over a wide range of parameters. More recently, a number of researchers have been trying to remove empiricism in the heat transfer models to arrive at more phenomenological models using extensive numerical simulations; these models require state-of-the-art experimental data for a wide range of conditions, first for input and later, for their validation. With this idea in mind, experiments with sub-cooled and saturated demineralized water have been carried out under atmospheric pressure to study the bubble dynamics- growth rate, departure size and frequencies for nucleate pool boiling. A number of heating elements have been used to study the dependence of vapor bubble dynamics on the heater surface finish and heater geometry along with the experimental conditions like the degree of sub-cooling, super heat and the heat flux. An attempt has been made to compare the data obtained with the existing data and the correlations in the literature to generate an exhaustive database for the pool boiling conditions.

Keywords: experiment, boiling, bubbles, bubble dynamics, pool boiling

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Authors: Bharti Verma, Chandrajit Balomajumder

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Water pollution is escalated owing to industrialization and random ejection of one or more toxic heavy metal ions from the semiconductor industry, electroplating, metallurgical, mining, chemical manufacturing, tannery industries, etc., In semiconductor industry various kinds of chemicals in wafers preparation are used . Fluoride, toxic solvent, heavy metals, dyes and salts, suspended solids and chelating agents may be found in wastewater effluent of semiconductor manufacturing industry. Also in the chrome plating, in the electroplating industry, the effluent contains heavy amounts of Chromium. Since Cr(VI) is highly toxic, its exposure poses an acute risk of health. Also, its chronic exposure can even lead to mutagenesis and carcinogenesis. On the contrary, Cr (III) which is naturally occurring, is much less toxic than Cr(VI). Discharge limit of hexavalent chromium and trivalent chromium are 0.05 mg/L and 5 mg/L, respectively. There are numerous methods such as adsorption, chemical precipitation, membrane filtration, ion exchange, and electrochemical methods for the heavy metal removal. The present study focuses on the removal of Chromium ions by using flat sheet UF5kDa membrane. The Ultra filtration membrane process is operated above micro filtration membrane process. Thus separation achieved may be influenced due to the effect of Sieving and Donnan effect. Ultrafiltration is a promising method for the rejection of heavy metals like chromium, fluoride, cadmium, nickel, arsenic, etc. from effluent water. Benefits behind ultrafiltration process are that the operation is quite simple, the removal efficiency is high as compared to some other methods of removal and it is reliable. Polyamide membranes have been selected for the present study on rejection of Cr(VI) from feed solution. The objective of the current work is to examine the rejection of Cr(VI) from aqueous feed solutions by flat sheet UF5kDa membranes with different parameters such as pressure, feed concentration and pH of the feed. The experiments revealed that with increasing pressure, the removal efficiency of Cr(VI) is increased. Also, the effect of pH of feed solution, the initial dosage of chromium in the feed solution has been studied. The membrane has been characterized by FTIR, SEM and AFM before and after the run. The mass transfer coefficients have been estimated. Membrane transport parameters have been calculated and have been found to be in a good correlation with the applied model.

Keywords: heavy metal removal, membrane process, waste water treatment, ultrafiltration

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Authors: Ana-Carolina Feltrin, Daniel Hedman, Farid Akhtar

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High entropy ceramic (HEC) materials are characterized by their compositional disorder due to different metallic element atoms occupying the cation position and non-metal elements occupying the anion position. Several studies have focused on the processing and characterization of high entropy carbides and high entropy borides, as these HECs present interesting mechanical and chemical properties. A few studies have been published on HECs containing two non-metallic elements in the composition. Dual-phase high entropy (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)BxCy ceramics with different amounts of x and y, (0.25 HfC + 0.25 ZrC + 0.25 VC + 0.25 TiB₂), (0.25 HfC + 0.25 ZrC + 0.25 VB2 + 0.25 TiB₂) and (0.25 HfC + 0.25 ZrB2 + 0.25 VB2 + 0.25 TiB₂) were sintered from boride and carbide precursor powders using SPS at 2000°C with holding time of 10 min, uniaxial pressure of 50 MPa and under Ar atmosphere. The sintered specimens formed two HEC phases: a Zr-Hf rich FCC phase and a Ti-V HCP phase, and both phases contained all the metallic elements from 5-50 at%. Phase quantification analysis of XRD data revealed that the molar amount of hexagonal phase increased with increased mole fraction of borides in the starting powders, whereas cubic FCC phase increased with increased carbide in the starting powders. SPS consolidated (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)BC0.5 and (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)B1.5C0.25 had respectively 94.74% and 88.56% relative density. (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)B0.5C0.75 presented the highest relative density of 95.99%, with Vickers hardness of 26.58±1.2 GPa for the borides phase and 18.29±0.8 GPa for the carbides phase, which exceeded the reported hardness values reported in the literature for high entropy ceramics. The SPS sintered specimens containing lower boron and higher carbon presented superior properties even though the metallic composition in each phase was similar to other compositions investigated. Dual-phase high entropy (Ti₀.₂₅V₀.₂₅Zr₀.₂₅H₀.₂₅)BxCy ceramics were successfully fabricated in a boride-carbide solid solution and the amount of boron and carbon was shown to influence the phase fraction, hardness of phases, and density of the consolidated HECs. The microstructure and phase formation was highly dependent on the amount of non-metallic elements in the composition and not only the molar ratio between metals when producing high entropy ceramics with more than one anion in the sublattice. These findings show the importance of further studies about the optimization of the ratio between C and B for further improvements in the properties of dual-phase high entropy ceramics.

Keywords: high-entropy ceramics, borides, carbides, dual-phase

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Authors: V. Keim, J. Spachtholz, J. Hammer

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The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation

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Authors: Kuhorfah Emmanuel Mawuli

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Generally, for firms to enhance their operational efficiency of logistics, it is imperative to assess the logistics function. The cost of logistics conventionally represents a key consideration in the pricing decisions of firms, which suggests that cost efficiency in logistics can go a long way to improve margins. Warehousing, which is a key part of logistics operations, has the prospect of influencing operational efficiency in logistics management as well as customer value, but this potential has often not been recognized. It has been found that there is a paucity of research that evaluates the efficiency of warehouses. Indeed, limited research has been conducted to examine potential barriers to effective warehousing management. Due to this paucity of research, there is limited knowledge on how to address the obstacles associated with warehousing management. In order for warehousing management to become profitable, there is the need to integrate, balance, and manage the economic inputs and outputs of the entire warehouse operations, something that many firms tend to ignore. Management of warehousing is not solely related to storage functions. Instead, effective warehousing management requires such practices as maximum possible mechanization and automation of operations, optimal use of space and capacity of storage facilities, organization through "continuous flow" of goods, a planned system of storage operations, and safety of goods. For example, there is an important need for space utilization of the warehouse surface as it is a good way to evaluate the storing operation and pick items per hour. In the setting of Mantrac Ghana, not much knowledge regarding the management of the warehouses exists. The researcher has personally observed many gaps in the management of the warehouse facilities in the case organization Mantrac Ghana. It is important, therefore, to assess the warehouse facility management of the case company with the objective of identifying weaknesses for improvement. The study employs an in-depth qualitative research approach using interviews as a mode of data collection. Respondents in the study mainly comprised warehouse facility managers in the studied company. A total of 10 participants were selected for the study using a purposive sampling strategy. Results emanating from the study demonstrate limited warehousing effectiveness in the case company. Findings further reveal that the major barriers to effective warehousing facility management comprise poor layout, poor picking optimization, labour costs, and inaccurate orders; policy implications of the study findings are finally outlined.

Keywords: assessing, warehousing, facility, management

Procedia PDF Downloads 46

Authors: Ibtisam A. Abbas Al-Darkazly

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In this study, the mechanical properties of alginate hydrogel material for self-standing 3D scaffold architecture with proper shape fidelity are investigated. In-lab built 3D bio-printer extrusion-based technology is utilized to fabricate 3D alginate scaffold constructs. The pressure, needle speed and stage speed are varied using a computer-controlled system. The experimental result indicates that the concentration of alginate solution, calcium chloride (CaCl₂) cross-linking concentration and cross-linking ratios lead to the formation of alginate hydrogel with various gelation states. Besides, the gelling conditions, such as cross-linking reaction time and temperature also have a significant effect on the mechanical properties of alginate hydrogel. Various experimental tests such as the material gelation, the material spreading and the printability test for filament collapse as well as the swelling test were conducted to evaluate the fabricated 3D scaffold constructs. The result indicates that the fabricated 3D scaffold from composition of 3.5% wt alginate solution, that is prepared in DI water and 1% wt CaCl₂ solution with cross-linking ratios of 7:3 show good printability and sustain good shape fidelity for more than 20 days, compared to alginate hydrogel that is prepared in a phosphate buffered saline (PBS). The fabricated self-standing 3D scaffold constructs measured 30 mm × 30 mm and consisted of 4 layers (n = 4) show good pore geometry and clear grid structure after printing. In addition, the percentage change of swelling degree exhibits high swelling capability with respect to time. The swelling test shows that the geometry of 3D alginate-scaffold construct and of the macro-pore are rarely changed, which indicates the capability of holding the shape fidelity during the incubation period. This study demonstrated that the mechanical and physical properties of alginate hydrogel could be tuned for a 3D bio-printing extrusion-based system to fabricate self-standing 3D scaffold soft structures. This 3D bioengineered scaffold provides a natural microenvironment present in the extracellular matrix of the tissue, which could be seeded with the biological cells to generate the desired 3D live tissue model for in vitro and in vivo tissue engineering applications.

Keywords: biomaterial, calcium chloride, 3D bio-printing, extrusion, scaffold, sodium alginate, tissue engineering

Procedia PDF Downloads 97

Authors: Ramon Omar Rosales-Espinoza

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Pile-to-pile mechanical connections are used if the depth of the soil layers with sufficient bearing strength exceeds the original (“leading”) pile length, with the additional pile segment being termed “extension” pile. Mechanical connectors permit a safe transmission of forces from leading to extension pile while meeting strength and serviceability requirements. Common types of connectors consist of an assembly of sleeve-type external couplers, bolts, pins, and other mechanical interlock devices that ensure the transmission of compressive, tensile, torsional and bending stresses between leading and extension pile segments. While welded connections allow for a relatively simple structural design, mechanical connections are advantageous over welded connections because they lead to shorter installation times and significant cost reductions since specialized workmanship and inspection activities are not required. However, common practices followed to design mechanical connectors neglect important aspects of the assembly response, such as stress concentration around pin/bolt holes, torsional stresses from the installation process, and interaction between the forces at the installation (torsion), service (compression/tension-bending), and removal stages (torsion). This translates into potentially unsatisfactory designs in terms of the ultimate and service limit states, exhibiting either reduced strength or excessive deformations. In this study, the experimental response under compressive forces of a type of mechanical connector is presented, in terms of strength, deformation and failure modes. The tests revealed that the type of connector used can safely transmit forces from pile to pile. Using the results from the compressive tests, an analysis model was developed using the finite element (FE) method to study the interaction of forces under installation and service stages of a typical mechanical connector. The response of the analysis model is used to identify potential areas for design optimization, including size, gap between leading and extension piles, number of pin/bolts, hole sizes, and material properties. The results show the design of mechanical connectors should take into account the interaction of forces present at every stage of their life cycle, and that the torsional stresses occurring during installation are critical for the safety of the assembly.

Keywords: piles, FEA, steel, mechanical connector

Procedia PDF Downloads 250

Authors: Baba Mbaye

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In collaborative filtering recommendation systems, a user receives suggested items based on the opinions and evaluations of a community of users. This type of recommendation system uses only the information (notes in numerical values) contained in a usage matrix as input data. This matrix can be constructed based on users' behaviors or by offering users to declare their opinions on the items they know. The cold start problem leads to very poor performance for new users. It is a phenomenon that occurs at the beginning of use, in the situation where the system lacks data to make recommendations. There are three types of cold start problems: cold start for a new item, a new system, and a new user. We are interested in this article at the cold start for a new user. When the system welcomes a new user, the profile exists but does not have enough data, and its communities with other users profiles are still unknown. This leads to recommendations not adapted to the profile of the new user. In this paper, we propose an approach that improves cold start by using the notions of similarity and semantic proximity between users profiles during cold start. We will use the cold-metadata available (metadata extracted from the new user's data) useful in positioning the new user within a community. The aim is to look for similarities and semantic proximities with the old and current user profiles of the system. Proximity is represented by close concepts considered to belong to the same group, while similarity groups together elements that appear similar. Similarity and proximity are two close but not similar concepts. This similarity leads us to the construction of similarity which is based on: a) the concepts (properties, terms, instances) independent of ontology structure and, b) the simultaneous representation of the two concepts (relations, presence of terms in a document, simultaneous presence of the authorities). We propose an ontology, OIVCSRS (Ontology of Improvement Visitor Cold Start in Recommender Systems), in order to structure the terms and concepts representing the meaning of an information field, whether by the metadata of a namespace, or the elements of a knowledge domain. This approach allows us to automatically attach the new user to a user community, partially compensate for the data that was not initially provided and ultimately to associate a better first profile with the cold start. Thus, the aim of this paper is to propose an approach to improving cold start using semantic technologies.

Keywords: visitor cold start, recommender systems, collaborative filtering, semantic filtering

Procedia PDF Downloads 204

Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

Procedia PDF Downloads 69

Authors: Calister Wingang Makebe, Wilson Ambindei Agwanande, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1 as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated, and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

Procedia PDF Downloads 56

Authors: Aliaa Mahmoud Issa

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Green tea may provide an alternative treatment for many skin system disorders. Intrinsic or chronological aging represents the structural, functional, and metabolic changes in the skin, which depend on the passage of time per se. The aim of the present study is to compare the effect of green tea extract administration, in drinking water or topically, on the chronological changes of the old Swiss albino mice skin. A total number of forty Swiss albino female mice (Mus musculus) were used; thirty were old females, 50-52 weeks old and the remaining ten young females were about 10 weeks old. The skin of the back of all the studied mice was dehaired with a topical depilatory cream. Treatment with green tea extract was applied in two different ways: in the drinking water (0.5mg/ml/day) or topically, applied to the skin of the dorsal side (6mg/ml water). They were divided into four main groups each of 10 animals: Group I: young untreated, Group II: old untreated groups, Group III: tea-drinking (TD) group, and Group IV: topical tea (TT) group. The animals were euthanized after 3 and 6 weeks from the beginning of green tea extract treatment. The skin was subject to morphometric (epidermal, dermal, and stratum corneum thicknesses; collagen and elastin content) studies. The skin ultrastructure of the groups treated for 6 weeks with the green tea extract was also examined. The old mouse skin was compared to the young one to investigate the chronological changes of the tissue. The results revealed that the skin of mice treated with green tea extract, either topically or to less extent in drinking water, showed a reduction in the aging features manifested by a numerical but statistically insignificant improvement in the morphometric measurements. A remarkable amelioration in the ultrastructure of the old skin was also observed. Generally, green tea extract in the drinking water revealed inconsistent results. The topical application of green tea extract to the skin revealed that the epidermal, dermal and stratum corneum thicknesses and the elastin content, that were statistically significant, approach those of the young group. The ultrastructural study revealed the same observations. The disjunction of the lower epidermal keratinocytes was reduced. It could be concluded that the topical application of green tea extract to the skin of old mice showed improvement in reversing markers of skin system aging more than using the extract in the drinking water.

Keywords: aging, green tea extract, morphometry, skin, ultrastructure

Procedia PDF Downloads 122

Authors: Gianmaria Califano, Júlio Augusto Lucena Maciel, Olfa Zarrouk, Miguel Damasio, Jose Silvestre, Ana Margarida Fortes

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Global warming, with rapid and sudden changes in meteorological conditions, is one of the major constraints to ensuring agricultural and crop resilience in the Mediterranean regions. Several strategies are being adopted to reduce the pressure of drought stress on grapevines at regional and local scales: improvements in the irrigation systems, adoption of interline cover crops, and adaptation of pruning techniques. However, still, more can be achieved if also microbial compartments associated with plants are considered in crop management. It is known that the microbial community change according to several factors such as latitude, plant variety, age, rootstock, soil composition and agricultural management system. Considering the increasing pressure of the biotic and abiotic stresses, it is of utmost necessity to also evaluate the effects of drought on the microbiome associated with the grapevine, which is a commercially important crop worldwide. In this study, we characterize the diversity and the structure of the microbial community under three long-term irrigation levels (100% ETc, 50% ETc and rain-fed) in a drought-tolerant grapevine cultivar present worldwide, Syrah. To avoid the limitations of culture-dependent methods, amplicon sequencing with target primers for bacteria and fungi was applied to the same soil samples. The use of the DNeasy PowerSoil (Qiagen) extraction kit required further optimization with the use of lytic enzymes and heating steps to improve DNA yield and quality systematically across biological treatments. Target regions (16S rRNA and ITS genes) of our samples are being sequenced with Illumina technology. With bioinformatic pipelines, it will be possible to obtain a characterization of the bacterial and fungal diversity, structure and composition. Further, the microbial communities will be assessed for their functional activity, which remains an important metric considering the strong inter-kingdom interactions existing between plants and their associated microbiome. The results of this study will lay the basis for biotechnological applications: in combination with the establishment of a bacterial library, it will be possible to explore the possibility of testing synthetic microbial communities to support plant resistance to water scarcity.

Keywords: microbiome, metabarcoding, soil, vinegrape, syrah, global warming, crop sustainability

Procedia PDF Downloads 101

Authors: E. Hovad, J. H. Walther, P. Larsen, J. Thorborg, J. H. Hattel

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In sand casting of metal parts for the automotive industry such as brake disks and engine blocks, the molten metal is poured into a sand mold to get its final shape. The DISAMATIC molding process is a way to construct these sand molds for casting of steel parts and in the present work numerical simulations of this process are presented. During the process green sand is blown into a chamber and subsequently squeezed to finally obtain the sand mould. The sand flow is modelled with the Discrete Element method (DEM) and obtaining the correct material parameters for the simulation is the main goal. Different tests will be used to find or calibrate the DEM parameters needed; Poisson ratio, Young modulus, rolling friction coefficient, sliding friction coefficient and coefficient of restitution (COR). The Young modulus and Poisson ratio are found from compression tests of the bulk material and subsequently used in the DEM model according to the Hertz-Mindlin model. The main focus will be on calibrating the rolling resistance and sliding friction in the DEM model with respect to the behavior of “real” sand piles. More specifically, the surface profile of the “real” sand pile will be compared to the sand pile predicted with the DEM for different values of the rolling and sliding friction coefficients. When the DEM parameters are found for the particle-particle (sand-sand) interaction, the particle-wall interaction parameter values are also found. Here the sliding coefficient will be found from experiments and the rolling resistance is investigated by comparing with observations of how the green sand interacts with the chamber wall during experiments and the DEM simulations will be calibrated accordingly. The coefficient of restitution will be tested with different values in the DEM simulations and compared to video footages of the DISAMATIC process. Energy dissipation will be investigated in these simulations for different particle sizes and coefficient of restitution, where scaling laws will be considered to relate the energy dissipation for these parameters. Finally, the found parameter values are used in the overall discrete element model and compared to the video footage of the DISAMATIC process.

Keywords: discrete element method, physical properties of materials, calibration, granular flow

Procedia PDF Downloads 469

Authors: Nurhafizah Md. Disa, Nurhayati Binti Abdullah, Muhammad Rabie Bin Omar

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This research intends to identify the existing knowledge gap because of the lack of substantial studies to fabricate and characterize bio-graphene created from Oil Palm Shell (OPS) through the means of pre-treatment and slow pyrolysis. By fabricating bio-graphene through OPS, a novel material can be found to procure and used for graphene-based research. The characterization of produced bio-graphene is intended to possess a unique hexagonal graphene pattern and graphene properties in comparison to other previously fabricated graphene. The OPS will be fabricated by pre-treatment of zinc chloride (ZnCl₂) and iron (III) chloride (FeCl3), which then induced the bio-graphene thermally by slow pyrolysis. The pyrolizer's final temperature and resident time will be set at 550 °C, 5/min, and 1 hour respectively. Finally, the charred product will be washed with hydrochloric acid (HCL) to remove metal residue. The obtained bio-graphene will undergo different analyses to investigate the physicochemical properties of the two-dimensional layer of carbon atoms with sp2 hybridization hexagonal lattice structure. The analysis that will be taking place is Raman Spectroscopy (RAMAN), UV-visible spectroscopy (UV-VIS), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), and X-Ray Diffraction (XRD). In retrospect, RAMAN is used to analyze three key peaks found in graphene, namely D, G, and 2D peaks, which will evaluate the quality of the bio-graphene structure and the number of layers generated. To compare and strengthen graphene layer resolves, UV-VIS may be used to establish similar results of graphene layer from last layer analysis and also characterize the types of graphene procured. A clear physical image of graphene can be obtained by analyzation of TEM in order to study structural quality and layers condition and SEM in order to study the surface quality and repeating porosity pattern. Lastly, establishing the crystallinity of the produced bio-graphene, simultaneously as an oxygen contamination factor and thus pristineness of the graphene can be done by XRD. In the conclusion of this paper, this study is able to obtain bio-graphene through OPS as a novel material in pre-treatment by chloride ZnCl₂ and FeCl3 and slow pyrolization to provide a characterization analysis related to bio-graphene that will be beneficial for future graphene-related applications. The characterization should yield similar findings to previous papers as to confirm graphene quality.

Keywords: oil palm shell, bio-graphene, pre-treatment, slow pyrolysis

Procedia PDF Downloads 65

Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

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Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

Procedia PDF Downloads 34

Authors: Asli Tiktas, Huseyin Gunerhan, Arif Hepbasli

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Solar energy, with its abundant and clean features, is one of the prominent renewable energy sources in multigeneration energy systems where various outputs, especially power generation, are produced together. In the literature, concentrated solar energy systems, which are an expensive technology, are mostly used in solar power plants where medium-high capacity production outputs are achieved. In addition, although different methods have been developed and proposed for solar energy-supported integrated power generation systems by different investigators, absorption technology, which is one of the key points of the present study, has been used extensively in cooling systems in these studies. Unlike these common uses mentioned in the literature, this study designs a system in which a flat plate solar collector (FPSC), Rankine cycle, absorption heat transformer (AHT), and cooling systems (ACS) are integrated. The system proposed within the scope of this study aims to produce medium-high-capacity electricity, heating, and cooling outputs using a technique different from the literature, with lower production costs than existing systems. With the proposed integrated system design, the average production costs based on electricity, heating, and cooling load production for similar scale systems are 5-10% of the average production costs of 0.685 USD/kWh, 0.247 USD/kWh, and 0.342 USD/kWh. In the proposed integrated system design, this will be achieved by increasing the outlet temperature of the AHT and FPSC system first, expanding the high-temperature steam coming out of the absorber of the AHT system in the turbine up to the condenser temperature of the ACS system, and next directly integrating it into the evaporator of this system and then completing the AHT cycle. Through this proposed system, heating and cooling will be carried out by completing the AHT and ACS cycles, respectively, while power generation will be provided because of the expansion of the turbine. Using only a single generator in the production of these three outputs together, the costs of additional boilers and the need for a heat source are also saved. In order to demonstrate that the system proposed in this study offers a more optimum solution, the techno-economic parameters obtained based on energy, exergy, economic, and environmental analysis were compared with the parameters of similar scale systems in the literature. The design parameters of the proposed system were determined through a parametric optimization study to exceed the maximum efficiency and effectiveness and reduce the production cost rate values of the compared systems.

Keywords: solar energy, absorption technology, Rankine cycle, multigeneration energy system

Procedia PDF Downloads 38

Authors: Saad Mohamed Elsaid, Nabil Anwar, Mahmoud Rushdi

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One of the reasons for the intensive use of pesticides is to protect agricultural crops and orchards from pests or agricultural worms. The period of time that pesticides stay inside the soil is estimated at about (2) to (12) weeks. Perhaps the most important reason that led to groundwater pollution is the easy leakage of these harmful pesticides from the soil into the aquifers. This research aims to find the best ways to use traded activated charcoal with gold nitrate solution; for removing the deadly pesticides from the aqueous solution by adsorption phenomenon. The most used pesticides in Egypt were selected, such as Malathion, Methomyl Abamectin and, Thiamethoxam. Activated charcoal doped with gold ions was prepared by applying chemical and thermal treatments to activated charcoal using gold nitrate solution. Adsorption of studied pesticide onto activated carbon /Au was mainly by chemical adsorption, forming a complex with the gold metal immobilized on activated carbon surfaces. In addition, the gold atom was considered as a catalyst to cracking the pesticide molecule. Gold activated charcoal is a low cost material due to the use of very low concentrations of gold nitrate solution. its notice the great ability of activated charcoal in removing selected pesticides due to the presence of the positive charge of the gold ion, in addition to other active groups such as functional oxygen and lignin cellulose. The presence of pores of different sizes on the surface of activated charcoal is the driving force for the good adsorption efficiency for the removal of the pesticides under study The surface area of the prepared char as well as the active groups, were determined using infrared spectroscopy and scanning electron microscopy. Some factors affecting the ability of activated charcoal were applied in order to reach the highest adsorption capacity of activated charcoal, such as the weight of the charcoal, the concentration of the pesticide solution, the time of the experiment, and the pH. Experiments showed that the maximum limit revealed by the batch adsorption study for the adsorption of selected insecticides was in contact time (80) minutes at pH (7.70). These promising results were confirmed, and by establishing the practical application of the developed system, the effect of various operating factors with equilibrium, kinetic and thermodynamic studies is evident, using the Langmuir application on the effectiveness of the absorbent material with absorption capacities higher than most other adsorbents.

Keywords: waste water, pesticides pollution, adsorption, activated carbon

Procedia PDF Downloads 55

Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Yutaro Kyuma, Sung-Jun Yoo, Kazuhide Ito

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A commuter bus remains important as a means to network public transportation between railway stations and terminals within cities. In some cases, the boarding time becomes longer, and the boarding rate tends to be higher corresponding to the development of urban cities. The interior environmental quality, e.g. temperature and air quality, in a commuter bus is relatively heterogeneous and complex compared to that of an indoor environment in buildings due to several factors: solar radiative heat – which comes from large-area windows –, inadequate ventilation rate caused by high density of commuters, and metabolic heat generation from travelers themselves. In addition to this, under conditions where many passengers ride in the enclosed space, contact and airborne infectious risk have attracted considerable attention in terms of public health. From this point of view, it is essential to develop the prediction method for assessment of interior environmental quality and infection risk in commuter bus cabins. In this study, we developed a numerical commuter bus model integrated with computer simulated persons to reproduce realistic indoor environment conditions with high occupancy during commuting. Here, computer simulated persons were newly designed considering different types of geometries, e.g., standing position, seating position, and individual differences. Here we conducted coupled computational fluid dynamics (CFD) analysis with radiative heat transfer analysis under steady state condition. Distributions of heterogeneous air flow patterns, temperature, and moisture surrounding the human body under some different ventilation system were analyzed by using CFD technique, and skin surface temperature distributions were analyzed using thermoregulation model that integrated into computer simulated person. Through these analyses, we discussed the interior environmental quality in specific commuter bus cabins. Further, inhaled air quality of each passenger was also analyzed. This study may have possibility to design the ventilation system in bus for improving thermal comfort of occupants.

Keywords: computational fluid dynamics, CFD, computer simulated person, CSP, contaminant, indoor environment, public health, ventilation

Procedia PDF Downloads 237