Search results for: structural applications

Authors: Bashar Mudhaffar Abdullah, Hasniza Zaman Huri, Nany Hairunisa

Abstract:

This study was carried out to determine the thermal properties and spectroscopy study of Malaysian Jatropha curcas seed oil. The J. curcas seed oil physicochemical properties such as free fatty acid (FFA %), acid value, saponification value, iodine value, unsaponifiable matter, and viscosity (cp) gave values of 1.89±0.10%, 3.76±0.07, 203.36±0.36 mg/g, 4.90±0.25, 1.76±0.03%, and 32, respectively. Gas chromatography (GC) was used to determine the fatty acids (FAs) composition. J. curcas seed oil is consisting of saturated FAs (19.55%) such as palmitic (13.19%), palmitoleic (0.40%), and stearic (6.36%) acids and unsaturated FAs (80.42%) such as oleic (43.32%) and linoleic (36.70%) acids. The thermal properties using differential scanning calorimetry (DSC) showed that crystallized TAG was observed at -6.79°C. The melting curves displayed three major exothermic regions of J. curcas seed oil, monounsaturated (lower-temperature peak) at -31.69°C, di-unsaturated (medium temperature peak) at -20.23°C and tri-unsaturated (higher temperature peak) at -12.72°C. The results of this study showed that the J. curcas seed oil is a plausible source of polyunsaturated fatty acid (PUFA) to be developed in the future for pharmaceutical applications.

Keywords: Jatropha curcas seed oil, thermal properties, crystallization, melting, spectroscopy

Procedia PDF Downloads 478

Authors: Jinan Fiaidhi, Sabah Mohammed

Abstract:

Cross-domain learning in the medical field is a research challenge as many conditions, like in oncology imaging, use different imaging modalities. Moreover, in most of the medical learning applications, the sample training size is relatively small. Although few-shot learning (FSL) through the use of a Siamese neural network was able to be trained on a small sample with remarkable accuracy, FSL fails to be effective for use in multiple domains as their convolution weights are set for task-specific applications. In this paper, we are addressing this problem by enabling FSL to possess the ability to shift across domains by designing a two-layer FSL network that can learn individually from each domain and produce a shared features map with extra modulation to be used at the second layer that can recognize important targets from mix domains. Our initial experimentations based on mixed medical datasets like the Medical-MNIST reveal promising results. We aim to continue this research to perform full-scale analytics for testing our cross-domain FSL learning.

Keywords: Siamese neural network, few-shot learning, meta-learning, metric-based learning, thick data transformation and analytics

Procedia PDF Downloads 56

Authors: Mikhail Zarechnev, Bora I. Kumova

Abstract:

A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

Procedia PDF Downloads 411

Authors: Hong Yu, Ion Matei

Abstract:

Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

Procedia PDF Downloads 195

Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

Abstract:

Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

Procedia PDF Downloads 357

Authors: I. Kurashvili, A. Sichinava, G. Bokuchava, G. Darsavelidze

Abstract:

Si-Ge solid solutions (bulk poly- and monocrystalline samples, thin films) are characterized by high perspectives for application in semiconductor devices, in particular, optoelectronics and microelectronics. In this light complex studying of structural state of the defects and structural-sensitive physical properties of Si-Ge solid solutions depending on the contents of Si and Ge components is very important. Present work deals with the investigations of microstructure, electrophysical characteristics, microhardness, internal friction and shear modulus of Si1-xGex(x≤0,02) bulk monocrystals conducted at a room temperatures. Si-Ge bulk crystals were obtained by Czochralski method in [111] crystallographic direction. Investigated monocrystalline Si-Ge samples are characterized by p-type conductivity and carriers concentration 5.1014-1.1015cm-3, dislocation density 5.103-1.104cm-2, microhardness according to Vickers method 900-1200 Kg/mm2. Investigate samples are characterized with 0,5x0,5x(10-15) mm3 sizes, oriented along [111] direction at torsion oscillations ≈1Hz, multistage changing of internal friction and shear modulus has been revealed in an interval of strain amplitude of 10-5-5.10-3. Critical values of strain amplitude have been determined at which hysteretic changes of inelastic characteristics and microplasticity are observed. The critical strain amplitude and elasticity limit values are also determined. Tendency to decrease of dynamic mechanical characteristics is shown with increasing Ge content in Si-Ge solid solutions. Observed changes are discussed from the point of view of interaction of various dislocations with point defects and their complexes in a real structure of Si-Ge solid solutions.

Keywords: Microhardness, internal friction, shear modulus, Monocrystalline

Procedia PDF Downloads 352

Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Rozaimah Baharim, M. Hanif M. Nasir

Abstract:

This paper will discuss how EDA tools are integrated and automated in an Integrated Circuit Design Environment. Some of the problems face in our current environment is that users need to configure manually on the library paths, start-up files and project directories. Certain manual processes that happen between the users and applications can be automated but they must be transparent to the users. For example, the users can run the applications directly after login without knowing the library paths and start-up files locations. The solution to these problems is to automate the processes using standard configuration files which will benefit the users and EDA support. This paper will discuss how the implementation is done to automate the process using scripting languages such as Perl, Tcl, Scheme and Shell Script. These scripting tools are great assets for design engineers to build a robust and powerful design flow and this technique is widely used to integrate all the tools together.

Keywords: EDA tools, Integrated Circuits, scripting, integration, automation

Procedia PDF Downloads 324

Authors: Georgeta Voicu, Cristina Daniela Ghitulica, Andreia Cucuruz, Cristina Busuioc

Abstract:

In the field of tissue engineering, the compositional and microstructural features of the employed materials play an important role, with implications on the mechanical and biological behaviour of the medical devices. In this context, the development of apatite - natural biopolymer composites represents a choice of many scientific groups. Thus, hydroxyapatite powders were synthesized by a wet method, namely co-precipitation, starting from high purity reagents (CaO, MgO, and H3PO4). Moreover, the substitution of calcium with magnesium have been approached, in the 5 - 10 wt.% range. Afterward, the phosphate powders were integrated in two types of composites with chitosan, different from morphological point of view. First, 3D porous scaffolds were obtained by a freeze-drying procedure. Second, uniform, compact films were achieved by film casting. The influence of chitosan molecular weight (low, medium and high), as well as apatite powder to polymer ratio (1:1 and 1:2) on the morphological properties, were analysed in detail. In conclusion, the reported biocomposites, prepared by a straightforward route are suitable for bone substitution or repairing applications.

Keywords: bone reconstruction, chitosan, composite scaffolds, hydroxyapatite

Procedia PDF Downloads 322

Authors: Jiří Kubásek, Peter Minárik, Klára Hosová, Stanislav Šašek, Jozef Veselý, Jitka Stráská, Drahomír Dvorský, Dalibor Vojtěch, Miloš Janeček

Abstract:

Mg-2Y-2Gd-1Ca and Mg-4Y-4Gd-2Ca alloys were processed by extrusion or equal channel angular pressing (ECAP) to analyse the effect of the microstructure on ignition temperature, mechanical properties and corrosion resistance. The alloys are characterized by good mechanical properties and exceptionally high ignition temperature, which is a critical safety measure. The effect of extrusion and ECAP on the microstructure, mechanical properties and ignition temperature was studied. The obtained results indicated a substantial effect of the processing conditions on the average grain size, the recrystallized fraction and texture formation. Both alloys featured a high strength, depending on the composition and processing condition, and a high ignition temperature of ≈1100 °C (Mg-4Y-4Gd-2Ca) and ≈950 °C (Mg-2Y-2Gd-1Ca), which was attributed to the synergic effect of Y, Gd and Ca oxides, with the dominant effect of Y₂O₃. The achieved combination of enhanced mechanical properties and the ignition temperature makes these alloys a prominent candidate for aircraft applications.

Keywords: magnesium alloys, enhanced ignition temperature, mechanical properties, ECAP

Procedia PDF Downloads 109

Authors: Elmira Ghanbari, Jan Van Esch, Stephen J. Picken, Sahil Aggarwal

Abstract:

Low-molecular-weight organogelators form gels by self-assembly into the crystalline network which immobilizes the organic solvent. For single bisamide organogelator systems, the effect of the molecular structure on the molecular interaction and their self-assembly behavior has been explored. The spatial arrangement of bisamide molecules in the gel-state is driven by a combination of hydrogen bonding and Van der Waals interactions. The hydrogen-bonding pattern between the amide groups of bisamide molecules is regulated by the number of methylene spacers; the even number of methylene spacers between two amide groups, in even-spaced bisamides, leads to the antiparallel position of amide groups within a molecule. An even-spaced bisamide molecule with antiparallel amide groups can make two pairs of hydrogen bonding with the molecules on the same plane. The odd-spaced bisamide with a parallel directionality of amide groups can form four independent hydrogen bonds with four other bisamide molecules on different planes. The arrangement of bisamide molecules in the crystalline state and the interaction of these molecules depends on the molecular structure, particularly the parity of the spacer length between the amide groups in the bisamide molecule. In this study, the directionality of amide groups has been exploited as a structural characteristic to affect the arrangement of molecules in the crystalline state and produce different binary bisamide gelators with different degrees of crystallinities. Single odd- and even-spaced single bisamides were synthesized and blended to produce binary bisamide organogelators to be characterized in order to understand the effect of the different directionality of amide groups on the molecular interaction in the crystalline state. The pattern of molecular interactions between these blended molecules, mixing or phase separation, has been monitored via differential scanning calorimetry (DSC) and crystallography techniques; X-ray powder diffraction (XRD) and Small-angle X-ray scattering (SAXS). The formation of lamellar structures for odd- and even-spaced bisamide gelators was confirmed by using SAXS and XRD techniques. DSC results have shown that binary bisamide organogelators with different parity of methylene spacers (odd-even binary blends) have a higher tendency for phase separation compared to the binary bisamides with the same parity (odd-odd or even-even binary blends). Phase separation in binary odd-even bisamides was confirmed by the presence of individual (100) reflections of odd and even lamellar structures. The structural characteristic of bisamide organogelators, the parity of spacer length in binary systems, is a promising tool to control the arrangement of molecules and their crystalline structure.

Keywords: binary bisamide organogelators, crystalline structure, phase separation, self-assembly behavior

Procedia PDF Downloads 185

Authors: Ekin Ozer, Maria Q. Feng, Rupa Purasinghe

Abstract:

Structural deterioration of bridge systems possesses an ongoing threat to the transportation networks. Besides, landmark bridges’ integrity and safety are more than sole functionality, since they provide a strong presence for the society and nations. Therefore, an innovative and sustainable method to inspect landmark bridges is essential to ensure their resiliency in the long run. In this paper, a recently introduced concept, smartphone-based modal frequency estimation is addressed, and this paper targets to authenticate the fidelity of smartphone-based vibration measurements gathered from three landmark suspension bridges. Firstly, smartphones located at the bridge mid-span are adopted as portable and standalone vibration measurement devices. Then, their embedded accelerometers are utilized to gather vibration response under operational loads, and eventually frequency domain characteristics are deduced. The preliminary analysis results are compared with the reference publications and high-quality monitoring data to validate the usability of smartphones on long-span landmark suspension bridges. If the technical challenges such as high period of vibration, low amplitude excitation, embedded smartphone sensor features, sampling, and citizen engagement are tackled, smartphones can provide a novel and cost-free crowdsourcing tool for maintenance of these landmark structures. This study presents the early phase findings from three signature structures located in the United States.

Keywords: smart and mobile sensing, structural health monitoring, suspension bridges, vibration analysis

Procedia PDF Downloads 292

Authors: Karim Sobh, Khaled El-Ayat, Fady Morcos, Amr El-Kadi

Abstract:

Distributed applications deployed on LEO satellites and ground stations require substantial communication between different members in a constellation to overcome the earth coverage barriers imposed by GEOs. Applications running on LEO constellations suffer the earth line-of-sight blockage effect. They need adequate lab testing before launching to space. We propose a scalable cloud-based net-work simulation framework to simulate problems created by the earth line-of-sight blockage. The framework utilized cloud IaaS virtual machines to simulate LEO satellites and ground stations distributed software. A factorial ANOVA statistical analysis is conducted to measure simulator overhead on overall communication performance. The results showed a very low simulator communication overhead. Consequently, the simulation framework is proposed as a candidate for testing LEO constellations with distributed software in the lab before space launch.

Keywords: LEO, cloud computing, constellation, satellite, network simulation, netfilter

Procedia PDF Downloads 386

Authors: Hamed Ouattara, Pierre Duthon, Frédéric Bernardin, Omar Ait Aider, Pascal Salmane

Abstract:

In this article, we present three neural network architectures for real-time classification of weather conditions (sunny, rainy, snowy, foggy) from images. Inspired by recent advances in style transfer, two of these architectures -Truncated ResNet50 and Truncated ResNet50 with Gram Matrix and Attention- surpass the state of the art and demonstrate re-markable generalization capability on several public databases, including Kaggle (2000 images), Kaggle 850 images, MWI (1996 images) [1], and Image2Weather [2]. Although developed for weather detection, these architectures are also suitable for other appearance-based classification tasks, such as animal species recognition, texture classification, disease detection in medical images, and industrial defect identification. We illustrate these applications in the section “Applications of Our Models to Other Tasks” with the “SIIM-ISIC Melanoma Classification Challenge 2020” [3].

Keywords: weather simulation, weather measurement, weather classification, weather detection, style transfer, Pix2Pix, CycleGAN, CUT, neural style transfer

Procedia PDF Downloads 3

Authors: Dario Milani, Guido Morgenthal

Abstract:

Fluid dynamic computation of wind caused forces on bluff bodies e.g light flexible civil structures or high incidence of ground approaching airplane wings, is one of the major criteria governing their design. For such structures a significant dynamic response may result, requiring the usage of small scale devices as guide-vanes in bridge design to control these effects. The focus of this paper is on the numerical simulation of the bluff body problem involving multiscale phenomena induced by small scale devices. One of the solution methods for the CFD simulation that is relatively successful in this class of applications is the Vortex Particle Method (VPM). The method is based on a grid free Lagrangian formulation of the Navier-Stokes equations, where the velocity field is modeled by particles representing local vorticity. These vortices are being convected due to the free stream velocity as well as diffused. This representation yields the main advantages of low numerical diffusion, compact discretization as the vorticity is strongly localized, implicitly accounting for the free-space boundary conditions typical for this class of FSI problems, and a natural representation of the vortex creation process inherent in bluff body flows. When the particle resolution reaches the Kolmogorov dissipation length, the method becomes a Direct Numerical Simulation (DNS). However, it is crucial to note that any solution method aims at balancing the computational cost against the accuracy achievable. In the classical VPM method, if the fluid domain is discretized by Np particles, the computational cost is O(Np2). For the coupled FSI problem of interest, for example large structures such as long-span bridges, the aerodynamic behavior may be influenced or even dominated by small structural details such as barriers, handrails or fairings. For such geometrically complex and dimensionally large structures, resolving the complete domain with the conventional VPM particle discretization might become prohibitively expensive to compute even for moderate numbers of particles. It is possible to reduce this cost either by reducing the number of particles or by controlling its local distribution. It is also possible to increase the accuracy of the solution without increasing substantially the global computational cost by computing a correction of the particle-particle interaction in some regions of interest. In this paper different strategies are presented in order to extend the conventional VPM method to reduce the computational cost whilst resolving the required details of the flow. The methods include temporal sub stepping to increase the accuracy of the particles convection in certain regions as well as dynamically re-discretizing the particle map to locally control the global and the local amount of particles. Finally, these methods will be applied on a test case and the improvements in the efficiency as well as the accuracy of the proposed extension to the method are presented. The important benefits in terms of accuracy and computational cost of the combination of these methods will be thus presented as long as their relevant applications.

Keywords: adaptation, fluid dynamic, remeshing, substepping, vortex particle method

Procedia PDF Downloads 262

Authors: Neeta Kumari, Gopal Pathak

Abstract:

Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

Procedia PDF Downloads 550

Authors: Roy Y. C. Huang, J. S. Kuang, Hamdolah Behnam

Abstract:

Beam-column connections play an important role in the reinforced concrete moment resisting frame (RCMRF), which is one of the most commonly used structural systems around the world. The premature failure of such connections would severely limit the seismic performance and increase the vulnerability of RCMRF. In the past decades, researchers primarily focused on investigating the structural behaviour and failure mechanisms of conventional beam-column joints, the beam width of which is either smaller than or equal to the column width, while studies in wide beam-column joints were scarce. This paper presents the preliminary experimental results of two full-scale exterior wide beam-column connections, which are mainly designed and detailed according to ACI 318-14 and ACI 352R-02, under reversed cyclic loading. The ratios of the design shear force to the nominal shear strength of these specimens are 1.0 and 1.7, respectively, so as to probe into differences of the joint shear strength between experimental results and predictions by design codes of practice. Flexural failure dominated in the specimen with ratio of 1.0 in which full-width plastic hinges were observed, while both beam hinges and post-peak joint shear failure occurred for the other specimen. No sign of premature joint shear failure was found which is inconsistent with ACI codes’ prediction. Finally, a modification of current codes of practice is provided to accurately predict the joint shear strength in wide beam-column joint.

Keywords: joint shear strength, reversed cyclic loading, seismic vulnerability, wide beam-column joints

Procedia PDF Downloads 323

Authors: Maram Shahad Dana Anfal

Abstract:

This research paper presents the design of a surveillance drone with computer-aided durability and model analyses that provides a cost-effective and efficient solution for various applications. The quadcopter's design is based on a lightweight and strong structure made of materials such as aluminum and titanium, which provide a durable structure for the quadcopter. The structure of this product and the computer-aided durability system are both designed to ensure frequent repairs or replacements, which will save time and money in the long run. Moreover, the study discusses the drone's ability to track, investigate, and deliver objects more quickly than traditional methods, makes it a highly efficient and cost-effective technology. In this paper, a comprehensive analysis of the quadcopter's operation dynamics and limitations is presented. In both simulation and experimental data, the computer-aided durability system and the drone's design demonstrate their effectiveness, highlighting the potential for a variety of applications, such as search and rescue missions, infrastructure monitoring, and agricultural operations. Also, the findings provide insights into possible areas for improvement in the design and operation of the drone. Ultimately, this paper presents a reliable and cost-effective solution for surveillance applications by designing a drone with computer-aided durability and modeling. With its potential to save time and money, increase reliability, and enhance safety, it is a promising technology for the future of surveillance drones. operation dynamic equations have been evaluated successfully for different flight conditions of a quadcopter. Also, CAE modeling techniques have been applied for the modal risk assessment at operating conditions.Stress analysis have been performed under the loadings of the worst-case combined motion flight conditions.

Keywords: drone, material, solidwork, hypermesh

Procedia PDF Downloads 144

Authors: Risikat Oladoyin S. Dauda, Onyebuchi Iwegbu

Abstract:

This study investigates the response of human development outcomes to selected macroeconomic indicators in Nigeria. Human development outcomes is measured by human development index while the selected macroeconomic variables are inflation rate, real interest rate, government capital expenditure, real exchange rate, current account balance, and savings. Structural Vector Autoregression (SVAR) technique is employed in examining the response of human development index to the macroeconomic shocks. The result from the forecast error variance decomposition and Impulse-Response analysis reveals that fiscal policy (government capital expenditure) shock is the greatest determinant of human development outcomes. This result reiterates the role which the government plays in improving the welfare of the citizenry. The fiscal policy tool is pivotal in human development which comes in the form of investment in education, health, housing, and infrastructure. Further conclusion drawn from this study is that human development outcome positively and significantly responds to shocks from real interest rate, a monetary policy transmission variable and is felt greatly in the short run period. The policy implication of this study is that if capital budget implementation falls below expectations, human development will be engendered. Hence, efforts should be made to ensure that full implementation and appraisal of government capital expenditure is taken sacrosanct as any shock from such plan, engenders human development outcome.

Keywords: human development outcome, macroeconomic outcomes, structural vector autoregression, SVAR

Procedia PDF Downloads 155

Authors: Muhammed Gündoğan

Abstract:

Permaculture is an important source of science and experience that can ensure the integration of sustainable architecture with nature. Since the past, many applications have been applied in rural areas for generations with the principle of benefiting from the self-renewal potential of nature. This culture, which has been transferred from generation to generation with architectural disciplines, has the potential to significantly improve the sustainability of the rural area and is an important guide with its nature-based solution proposals. Şanlıurfa has arid and semi-arid climate characteristics. Although it has substantial agricultural potential, water is limited, especially in rural areas. In the region, rainwater harvesting practices such as artificial water canals and cisterns have been used for a long time. However, these solutions remained mostly at the urban scale, and their reflections at the building scale were restricted and inadequate solutions. Impermeable surfaces are required for water harvesting, but water harvesting is not possible as rural buildings are mostly surrounded by cultivated land. Therefore, existing structures are important in terms of applicability. In this context, considering the typology of Traditional Şanlıurfa Houses, the aim of the project was to create a proposal for limited potable and utility water, which is a serious problem, especially for rural buildings in Şanlıurfa. In the project proposal, roof systems that can work integrated with the structural shape of Traditional Şanlıurfa Houses, rainwater collection systems in the inner courtyard, and greywater recycling were provided. While the average precipitation amount was 453.7 kg/m3 between 1929 and 2012, this value was measured as 622.7 kg/m3 in 2012. Greywater was used to produce natural fertilizers and compost for small-scale fruit and vegetable gardens, and it was combined with the principles of Permaculture to make it a lifestyle. As a result, it has been estimated that a total of 976.4 m3 kg of water can be saved, with an annual average of 158.8 m3 of rainwater recycling and 817.6 m3 of greywater recycling within the scope of the project.

Keywords: rural, traditional residential building, permaculture, rainwater harvesting, greywater recycling

Procedia PDF Downloads 131

Authors: Pratima Kumari, Sukha Ranjan Samadder

Abstract:

This research aims to contribute to the sustainable production of graphene materials by exploring the extraction of graphite from spent primary and secondary batteries. The increasing demand for graphene materials, a versatile and high-performance material, necessitates environmentally friendly methods for its synthesis. The process involves a well-planned methodology, beginning with the gathering and categorization of batteries, followed by the disassembly and careful removal of graphite from anode structures. The use of environmentally friendly solvents and mechanical techniques ensures an efficient and eco-friendly extraction of graphite. Advanced approaches such as the modified Hummers' method and chemical reduction process are utilized for the synthesis of graphene materials, with a focus on optimizing parameters. Various analytical techniques such as Fourier-transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, thermogravimetric analysis, and Raman spectroscopy were employed to validate the quality and structure of the produced graphene materials. The major findings of this study reveal the successful implementation of the methodology, leading to the production of high-quality graphene materials suitable for advanced material applications. Thorough characterization using various advanced techniques validates the structural integrity and purity of the graphene. The economic viability of the process is demonstrated through a comprehensive economic analysis, highlighting the potential for large-scale production. This research contributes to the field of sustainable production of graphene materials by offering a systematic methodology that efficiently transforms spent batteries into valuable graphene resources. Furthermore, the findings not only showcase the potential for upcycling electronic waste but also address the pressing need for environmentally conscious processes in advanced material synthesis.

Keywords: spent primary batteries, spent secondary batteries, graphite extraction, advanced material synthesis, circular economy approach

Procedia PDF Downloads 54

Authors: A. Bertašienė

Abstract:

Energy harvesting from any structure makes a challenge. Different structure of air/wind flows in industrial, environmental and residential applications emerge the real flow investigation in detail. Many of the application fields are hardly achievable to the detailed description due to the lack of up-to-date statistical data analysis. In situ measurements aim crucial investments thus the simulation methods come to implement structural analysis of the flows. Different configurations of testing environment give an overview how important is the simple structure of field in limited area on efficiency of the system operation and the energy output. Several configurations of modeled working sections in air flow test facility was implemented in CFD ANSYS environment to compare experimentally and numerically air flow development stages and forms that make effects on efficiency of devices and processes. Effective form and amount of these flows under different geometry cases define the manner of instruments/devices that measure fluid flow parameters for effective operation of any system and emission flows to define. Different fluid flow regimes were examined to show the impact of fluctuations on the development of the whole volume of the flow in specific environment. The obtained results rise the discussion on how these simulated flow fields are similar to real application ones. Experimental results have some discrepancies from simulation ones due to the models implemented to fluid flow analysis in initial stage, not developed one and due to the difficulties of models to cover transitional regimes. Recommendations are essential for energy harvesting systems in both, indoor and outdoor cases. Further investigations aim to be shifted to experimental analysis of flow under laboratory conditions using state-of-the-art techniques as flow visualization tool and later on to in situ situations that is complicated, cost and time consuming study.

Keywords: fluid flow, initial region, tube coefficient, distinct shape

Procedia PDF Downloads 337

Authors: Igor P. Maximkin, Arkady A. Yukhimchuk, Victor V. Baluev, Igor L. Malkov, Rafael K. Musyaev, Damir T. Sitdikov, Alexey V. Buchirin, Vasily V. Tikhonov

Abstract:

Minimization of tritium diffusion leakage when developing devices handling tritium-containing media is key problems whose solution will at least allow essential enhancement of radiation safety and minimization of diffusion losses of expensive tritium. One of the ways to solve this problem is to use Al₂O₃ high-strength non-porous ceramics as a structural material of the bed body. This alumina ceramics offers high strength characteristics, but its main advantages are low hydrogen permeability (as against the used structural material) and high dielectric properties. The latter enables direct induction heating of an hydride-forming metal without essential heating of the pressure and containment vessel. The use of alumina ceramics and induction heating allows: - essential reduction of tritium extraction time; - several orders reduction of tritium diffusion leakage; - more complete extraction of tritium from metal hydrides due to its higher heating up to melting in the event of final disposal of the device. The paper presents computational and experimental results for the tritium bed designed to absorb 6 liters of tritium. Titanium was used as hydrogen isotope sorbent. Results of hydrogen realize kinetic from hydride-forming metal, strength and cyclic service life tests are reported. Recommendations are also provided for the practical use of the given bed type.

Keywords: aluminum oxide ceramic, hydrogen pressure, hydrogen isotope storage, titanium hydride

Procedia PDF Downloads 407

Authors: John-Nelson Ekumah, Xu Han, Qiufang Liang, Benxi Wei, Arif Rashid, Muhammad Safiullah, Abdul Qayum, Selorm Yao-Say Solomon Adade, Nana Adwoa Nkuma Johnson, Abdur Rehman, Xiaofeng Ren

Abstract:

Producing starch gels with superior mechanical attributes remains a challenging pursuit. This research sought to develop a simple method using ethanol exposure to produce robust starch gels. The gels’ mechanical properties, rheology, structural characteristics, and digestion were assessed through textural, rheological, structural, and in vitro digestion analyses. it investigation revealed an improvement in gel’s strength from 62.22 to178.82 g. The thermal transitions were accelerated when ethanol was elevated. The exposure to ethanol resulted in a reduction in syneresis from 11% to 9.5% over a period of 6 hours with noticeable change in size and color. Rheologically, the dominating storage modulus and tan delta (<0.55) emphasized the gel’s improved elasticity. X-ray analysis showed a stable B + V-type pattern after ethanol exposure, with increasing relative crystallinity to 7.9%. Digestibility revealed an ethanol induced resistance, through increased resistant starch from 1.87 to 8.73%. In general, the exposure to ethanol played a crucial role in enhancing the mechanical characteristics of kudzu starch gels, while simultaneously preserving higher levels of resistant starch fractions. These findings have wide-ranging implications in the fields of food and pharmaceuticals, underscoring the extensive academic and industrial importance of this study.

Keywords: kudzu starch gels, mechanical properties, rheological properties, submerged ethanol exposure, In vitro digestion

Procedia PDF Downloads 37

Authors: Vera Wilden, Benno Hoffmeister, Georgios Balaskas, Lukas Rauber, Burkhard Walter

Abstract:

Light-weight timber frame elements represent an efficient structural solution for wooden multistory buildings. The wall elements of such buildings – which act as shear diaphragms- provide lateral stiffness and resistance to wind and seismic loads. The tendency towards multi-story structures leads to challenges regarding the prediction of stiffness, strength and ductility of the buildings. Lightweight timber frame elements are built up of several structural parts (sheeting, fasteners, frame, support and anchorages); each of them contributing to the dynamic response of the structure. This contribution describes the experimental and numerical investigation and development of enhanced lightweight timber frame buildings. These developments comprise high-performance timber frame walls with the variable arrangements of sheathing planes and dissipative anchors at the base of the timber buildings, which reduce damages to the timber structure and can be exchanged after significant earthquakes. In order to prove the performance of the developed elements in the context of a real building a full-scale two-story building core was designed and erected in the laboratory and tested experimentally for its seismic performance. The results of the tests and a comparison of the test results to the predicted behavior are presented. Observation during the test also reveals some aspects of the design and details which need to consider in the application of the timber walls in the context of the complete building.

Keywords: dissipative anchoring, full scale test, push-over-test, wood shear walls

Procedia PDF Downloads 246

Authors: Srinaath Anbu Durai, Wang Zhaoxia

Abstract:

Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data.

Keywords: sentiment analysis, Covid-19, housing price prediction, tweets, social media, Singapore HDB, behavioral economics, neural networks

Procedia PDF Downloads 116

Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

Abstract:

Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

Procedia PDF Downloads 478

Authors: V. K. Banga

Abstract:

Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

Procedia PDF Downloads 297

Authors: O. Mauroner, L. Le, S. Best

Abstract:

Digital technologies offer many opportunities in the design and implementation of brand communication and advertising. Augmented reality (AR) is an innovative technology in marketing communication that focuses on the fact that virtual interaction with a product ad offers additional value to consumers. AR enables consumers to obtain (almost) real product experiences by the way of virtual information even before the purchase of a certain product. Aim of AR applications in relation with advertising is in-depth examination of product characteristics to enhance product knowledge as well as brand knowledge. Interactive design of advertising provides observers with an intense examination of a specific advertising message and therefore leads to better brand knowledge. The elaboration likelihood model and the central route to persuasion strongly support this argumentation. Nevertheless, AR in brand communication is still in an initial stage and therefore scientific findings about the impact of AR on information processing and brand attitude are rare. The aim of this paper is to empirically investigate the potential of AR applications in combination with traditional print advertising. To that effect an experimental design with different levels of interactivity is built to measure the impact of interactivity of an ad on different variables o advertising effectiveness.

Keywords: advertising effectiveness, augmented reality, brand communication, brand recall

Procedia PDF Downloads 302

Authors: Umar Sambo Umar, Ahmad Isah Haruna, Abubakar Sadik Maigari, Muhammad Bello Abubakar

Abstract:

Schist belts in Nigeria occur prominently west of longitude 80 E and sporadic to the east, they are upper Proterozioc low-medium grade deformed metasediments and metavolcanics that were intruded by Pan-African granitoids. The Wonaka schist belt, though reportedly distinctive in composition and metamorphism, is the least understood; the host for primary gold were not defined, structures which may control primary enrichment have not been delineated. The aim of this work is to determine the relationship between litho-structures and the gold around Wonaka schist belt through geological field mapping, petrographic studies and structural data analysis via ArcGis 10.2, Surfer 11.0 and Stereopro 2.0. The results show that the major rock types are mica schist and migmatites, muscovites detected during microstructural analysis suggests low-grade metamorphism in the metapelites. The shear zones identified were trending North Northeast – South Southwest (NNE-SSW), fractures trend mostly Northeast-Southwest (NE-SW) perpendicular to planes of gneissic foliations, these conform to the late Pan-African deformational episode. Pegmatite lodes, net self-cross cutting quartz veins as well as the quartz stringers hosted by both migmatites and schist are delineated as targets for primary gold mineralization, while major confluences of the streams serve as zones for secondary (placer) gold targets since the streams are dendritic and intermittent.

Keywords: gold mineralization, Nigeria, migmatites, Wonaka schist belt

Procedia PDF Downloads 196

Authors: Sandesh Achar

Abstract:

Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

Procedia PDF Downloads 109