Search results for: Kendall's coefficient of concordance

Authors: Syed Hadi Hasan, Devendra Kumar Singh, Viyaj Kumar

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Cr (VI) is a known toxic heavy metal and has been considered as a priority pollutant in water. The effluent of various industries including electroplating, anodizing baths, leather tanning, steel industries and chromium based catalyst are the major source of Cr (VI) contamination in the aquatic environment. Cr (VI) show high mobility in the environment and can easily penetrate cell membrane of the living tissues to exert noxious effects. The Cr (VI) contamination in drinking water causes various hazardous health effects to the human health such as cancer, skin and stomach irritation or ulceration, dermatitis, damage to liver, kidney circulation and nerve tissue damage. Herein, an attempt has been done to develop an efficient adsorbent for the removal of Cr (VI) from water. For this purpose nanosorbent composed of polyvinyl alcohol functionalized graphene oxide (GO/PVA) was prepared. Thus, obtained GO/PVA was characterized through FTIR, XRD, SEM, and Raman Spectroscopy. As prepared nanosorbent of GO/PVA was utilized for the removal Cr (VI) in batch mode experiment. The process variables such as contact time, initial Cr (VI) concentration, pH, and temperature were optimized. The maximum 99.8 % removal of Cr (VI) was achieved at initial Cr (VI) concentration 60 mg/L, pH 2, temperature 35 °C and equilibrium was achieved within 50 min. The two widely used isotherm models viz. Langmuir and Freundlich were analyzed using linear correlation coefficient (R2) and it was found that Langmuir model gives best fit with high value of R2 for the data of present adsorption system which indicate the monolayer adsorption of Cr (VI) on the GO/PVA. Kinetic studies were also conducted using pseudo-first order and pseudo-second order models and it was observed that chemosorptive pseudo-second order model described the kinetics of current adsorption system in better way with high value of correlation coefficient. Thermodynamic studies were also conducted and results showed that the adsorption was spontaneous and endothermic in nature.

Keywords: adsorption, GO/PVA, isotherm, kinetics, nanosorbent, thermodynamics

Procedia PDF Downloads 389

Authors: Purevdolgor Luvsantseren, Ajnai Luvsan-Ish, Oyuntsetseg Sandag, Javzmaa Tsend, Akhit Tileubai, Baasandorj Chilhaasuren, Jargalbat Puntsagdash, Galbadrakh Chuluunbaatar

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One of the indicators of the quality of university services is student satisfaction. Aim: We aimed to study the level of satisfaction of students in the first year of premedical courses in the course of Medical Physics using the cluster method. Materials and Methods: In the framework of this goal, a questionnaire was collected from a total of 324 students who studied the medical physics course of the 1st course of the premedical course at the Mongolian National University of Medical Sciences. When determining the level of satisfaction, the answers were obtained on five levels of satisfaction: "excellent", "good", "medium", "bad" and "very bad". A total of 39 questionnaires were collected from students: 8 for course evaluation, 19 for teacher evaluation, and 12 for student evaluation. From the research, a database with 39 fields and 324 records was created. Results: In this database, cluster analysis was performed in MATLAB and R programs using the k-means method of data mining. Calculated the Hopkins statistic in the created database, the values are 0.88, 0.87, and 0.97. This shows that cluster analysis methods can be used. The course evaluation sub-fund is divided into three clusters. Among them, cluster I has 150 objects with a "good" rating of 46.2%, cluster II has 119 objects with a "medium" rating of 36.7%, and Cluster III has 54 objects with a "good" rating of 16.6%. The teacher evaluation sub-base into three clusters, there are 179 objects with a "good" rating of 55.2% in cluster II, 108 objects with an "average" rating of 33.3% in cluster III, and 36 objects with an "excellent" rating in cluster I of 11.1%. The sub-base of student evaluations is divided into two clusters: cluster II has 215 objects with an "excellent" rating of 66.3%, and cluster I has 108 objects with an "excellent" rating of 33.3%. Evaluating the resulting clusters with the Silhouette coefficient, 0.32 for the course evaluation cluster, 0.31 for the teacher evaluation cluster, and 0.30 for student evaluation show statistical significance. Conclusion: Finally, to conclude, cluster analysis in the model of the medical physics lesson “good” - 46.2%, “middle” - 36.7%, “bad” - 16.6%; 55.2% - “good”, 33.3% - “middle”, 11.1% - “bad” in the teacher evaluation model; 66.3% - “good” and 33.3% of “bad” in the student evaluation model.

Keywords: questionnaire, data mining, k-means method, silhouette coefficient

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Authors: Ryo Shikimoto, Hidehito Niimura, Hisashi Kida, Kota Suzuki, Yukiko Miyasaka, Masaru Mimura

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Introduction: In Japan, the most aged country in the world, it is important to explore predictive factors of cognitive function among the elderly. Coping behavior relieves chronic stress and improves lifestyle, and consequently may reduce the risk of cognitive impairment. One of the most widely investigated frameworks evaluated in previous studies is approach-oriented and avoidance-oriented coping strategies. The purpose of this study is to investigate the relationship between cognitive function and coping strategies among elderly residents in urban areas of Japan. Method: This is a part of the cross-sectional Arakawa geriatric cohort study for 1,099 residents (aged 65 to 86 years; mean [SD] = 72.9 [5.2]). Participants were assessed for cognitive function using the Mini-Mental State Examination (MMSE) and diagnosed by psychiatrists in face-to-face interviews. They were then investigated for their each coping behaviors and coping strategies (approach- and avoidance-oriented coping) using stress and coping inventory. A multiple regression analysis was used to investigate the relationship between MMSE score and each coping strategy. Results: Of the 1,099 patients, the mean MMSE score of the study participants was 27.2 (SD = 2.7), and the numbers of the diagnosis of normal, mild cognitive impairment (MCI), and dementia were 815 (74.2%), 248 (22.6%), and 14 (1.3%), respectively. Approach-oriented coping score was significantly associated with MMSE score (B [partial regression coefficient] = 0.12, 95% confidence interval = 0.05 to 0.19) after adjusting for confounding factors including age, sex, and education. Avoidance-oriented coping did not show a significant association with MMSE score (B [partial regression coefficient] = -0.02, 95% confidence interval = -0.09 to 0.06). Conclusion: Approach-oriented coping was clearly associated with neurocognitive function in the Japanese population. A future longitudinal trial is warranted to investigate the protective effects of coping behavior on cognitive function.

Keywords: approach-oriented coping, cognitive impairment, coping behavior, dementia

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Authors: Lexi Li, Vanessa H. K. Pang

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This study aims to demonstrate how native and learner corpora can be used to enhance modal verb treatment in EFL textbooks in mainland China. It contributes to a corpus-informed and learner-centered design of grammar presentation in EFL textbooks that enhances the authenticity and appropriateness of textbook language for target learners. The linguistic focus is will, would, can, could, may, might, shall, should, must. The native corpus is the spoken component of BNC2014 (hereafter BNCS2014). The spoken part is chosen because pedagogical purpose of the textbooks is communication-oriented. Using the standard query option of CQPweb, 5% of each of the nine modals was sampled from BNCS2014. The learner corpus is the POS-tagged Ten-thousand English Compositions of Chinese Learners (TECCL). All the essays under the 'secondary school' section were selected. A series of five secondary coursebooks comprise the textbook corpus. All the data in both the learner and the textbook corpora are retrieved through the concordance functions of WordSmith Tools (version, 5.0). Data analysis was divided into two parts. The first part compared the patterns of modal verbs in the textbook corpus and BNC2014 with respect to distributional features, semantic functions, and co-occurring constructions to examine whether the textbooks reflect the authentic use of English. Secondly, the learner corpus was analyzed in terms of the use (distributional features, semantic functions, and co-occurring constructions) and the misuse (syntactic errors, e.g., she can sings*.) of the nine modal verbs to uncover potential difficulties that confront learners. The analysis of distribution indicates several discrepancies between the textbook corpus and BNCS2014. The first four most frequent modal verbs in BNCS2014 are can, would, will, could, while can, will, should, could are the top four in the textbooks. Most strikingly, there is an unusually high proportion of can (41.1%) in the textbooks. The results on different meanings shows that will, would and must are the most problematic. For example, for will, the textbooks contain 20% more occurrences of 'volition' and 20% less of 'prediction' than those in BNCS2014. Regarding co-occurring structures, the textbooks over-represented the structure 'modal +do' across the nine modal verbs. Another major finding is that the structure of 'modal +have done' that frequently co-occur with could, would, should, and must is underused in textbooks. Besides, these four modal verbs are the most difficult for learners, as the error analysis shows. This study demonstrates how the synergy of native and learner corpora can be harnessed to improve EFL textbook presentation of modal verbs in a way that textbooks can provide not only authentic language used in natural discourse but also appropriate design tailed for the needs of target learners.

Keywords: English as Foreign Language, EFL textbooks, learner corpus, modal verbs, native corpus

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Authors: Daniel Dahis, Haim Azhari

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Noninvasive image-guided intracranial treatments using high intensity focused ultrasound (HIFU) are on the course of translation into clinical applications. They include, among others, tumor ablation, hyperthermia, and blood-brain-barrier (BBB) penetration. Since many of these procedures are associated with local temperature elevation, thermal monitoring is essential. MRI constitutes an imaging method with high spatial resolution and thermal mapping capacity. It is the currently leading modality for temperature guidance, commonly under the name MRgHIFU (magnetic-resonance guided HIFU). Nevertheless, MRI is a very expensive non-portable modality which jeopardizes its accessibility. Ultrasonic thermal monitoring, on the other hand, could provide a modular, cost-effective alternative with higher temporal resolution and accessibility. In order to assess the feasibility of ultrasonic brain thermal monitoring, this study investigated the usage of brain tissue attenuation coefficient (AC) temporal changes as potential estimators of thermal changes. Newton's law of cooling describes a temporal exponential decay behavior for the temperature of a heated object immersed in a relatively cold surrounding. Similarly, in the case of cerebral HIFU treatments, the temperature in the region of interest, i.e., focal zone, is suggested to follow the same law. Thus, it was hypothesized that the AC of the irradiated tissue may follow a temporal exponential behavior during cool down regime. Three ex-vivo bovine brain tissue specimens were inserted into plastic containers along with four thermocouple probes in each sample. The containers were placed inside a specially built ultrasonic tomograph and scanned at room temperature. The corresponding pixel-averaged AC was acquired for each specimen and used as a reference. Subsequently, the containers were placed in a beaker containing hot water and gradually heated to about 45ᵒC. They were then repeatedly rescanned during cool down using ultrasonic through-transmission raster trajectory until reaching about 30ᵒC. From the obtained images, the normalized AC and its temporal derivative as a function of temperature and time were registered. The results have demonstrated high correlation (R² > 0.92) between both the brain AC and its temporal derivative to temperature. This indicates the validity of the hypothesis and the possibility of obtaining brain tissue temperature estimation from the temporal AC thermal changes. It is important to note that each brain yielded different AC values and slopes. This implies that a calibration step is required for each specimen. Thus, for a practical acoustic monitoring of the brain, two steps are suggested. The first step consists of simply measuring the AC at normal body temperature. The second step entails measuring the AC after small temperature elevation. In face of the urging need for a more accessible thermal monitoring technique for brain treatments, the proposed methodology enables a cost-effective high temporal resolution acoustical temperature estimation during HIFU treatments.

Keywords: attenuation coefficient, brain, HIFU, image-guidance, temperature

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: B. O. Diyaolu

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The globalization of football especially among youth over the decade is uprising. Nigeria youth displaying football jerseys at every opportunity is an acceptance of football globalization. The Love for English Premier League (EPL) football jersey is very strong among Nigeria fans. Football club jerseys of the EPL are a common sports product among fans in Nigeria. This study investigates the contribution of football club jerseys towards EPL fans’ loyalty in Nigeria. Descriptive survey research design was used for the study. The population consists of EPL fans in Nigeria. Simple random sampling technique (fish bowl without replacement) was used to select two states from the six geo-political zones. Purposive sampling technique was used to pick eight viewing centres while accidental sampling technique was used to pick five vendor stands from each State. An average of 250 respondents was selected from each state. A total of 3,200 respondents participated in the research. Two research instruments were used. A self-developed structured questionnaire on Football Jersey Scale (FJS): The instrument consists of 10 items. Fans Loyalty Scale (FLS): The instrument was modified from the psychological commitment to team (PCT) scale, and consists of 20 items. The Cronbach’s Alpha reliability coefficient of 0.72 and 0.75 was obtained, respectively. The hypothesis was tested at 0.05 significant levels. Data were analysed using frequency, percentages count, pie chart and multiple regressions. The result showed that the b-value of football club jersey is 0.148 also the standard regression coefficient (Beta) is 0.089. The t = 4.759 is statistically significant at p = 0.000. This signified a relative contribution of football club jersey on EPL fans loyalty in Nigeria. Club jersey, which is the most outstanding identifier of every club, was found to significantly predict loyalty. The jersey on the body of the fan has become the site for a declaration of loyalty which becomes available for social interaction and negotiation. The Nigerian local league clubs in an attempt to keep Nigerian fans loyal must borrow a leaf from their European counterparts.

Keywords: club Jerseys, English Premier League, football fans, Nigeria youth

Procedia PDF Downloads 256

Authors: Liu Bijin

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Floating breakwaters have several advantages, including being environmentally friendly, easy to construct, and cost-effective regardless of water depth. They have a broad range of applications in coastal engineering. However, they face significant challenges due to the unstable effect of wave dissipation, structural vulnerability, and high mooring system requirements. This paper investigates the wave dissipation performance of a floating breakwater structure. The structure consists of double cylinders, double vertical plates, and horizontal connecting plates. The investigation is carried out using physical model tests and numerical simulation methods based on STAR-CCM+. This paper discusses the impact of wave elements, relative vertical plate heights, and relative horizontal connecting plate widths on the wave dissipation performance of the double-cylinder, double-plate floating breakwater (DCDPFB). The study also analyses the changes in local vorticity and velocity fields around the DCDPFB to determine the optimal structural dimensions. The study found that the relative width of the horizontal connecting plate, the relative height of the vertical plate, and the size of the semi-cylinder are the key factors affecting the wave dissipation performance of the DCDPFB. The transmittance coefficient is minimally affected by the wave height and the depth of water entry. The local vortex and velocity field formed around the DCDPFB are important factors for dissipating wave energy. The test section of the DCDPFB, constructed according to the relative optimal structural dimensions, showed good wave dissipation performance during offshore prototype tests. The test section of DCDPFB, constructed with optimal structural dimensions, exhibits excellent wave dissipation performance in offshore prototype tests.

Keywords: floating breakwater, wave dissipation performance, transmittance coefficient, model test

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Authors: Peng Zhang, Lihui Zheng, Xiangchun Wang, Xiaopan Kou

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Quantitative research on the main control factors of lost circulation has few considerations and single data source. Using Unmanned Intervention Algorithm to find the main control factors of lost circulation adopts all measurable parameters. The degree of lost circulation is characterized by the loss rate as the objective function. Geological, engineering and fluid data are used as layers, and 27 factors such as wellhead coordinates and WOB are used as dimensions. Data classification is implemented to determine function independent variables. The mathematical equation of loss rate and 27 influencing factors is established by multiple regression method, and the undetermined coefficient method is used to solve the undetermined coefficient of the equation. Only three factors in t-test are greater than the test value 40, and the F-test value is 96.557%, indicating that the correlation of the model is good. The funnel viscosity, final shear force and drilling time were selected as the main control factors by elimination method, contribution rate method and functional method. The calculated values of the two wells used for verification differ from the actual values by -3.036m3/h and -2.374m3/h, with errors of 7.21% and 6.35%. The influence of engineering factors on the loss rate is greater than that of funnel viscosity and final shear force, and the influence of the three factors is less than that of geological factors. Quantitatively calculate the best combination of funnel viscosity, final shear force and drilling time. The minimum loss rate of lost circulation wells in Shunbei area is 10m3/h. It can be seen that man-made main control factors can only slow down the leakage, but cannot fundamentally eliminate it. This is more in line with the characteristics of karst caves and fractures in Shunbei fault solution oil and gas reservoir.

Keywords: drilling and completion, drilling fluid, lost circulation, loss rate, main controlling factors, unmanned intervention algorithm

Procedia PDF Downloads 112

Authors: Pinna Beatrice., Laini Alex, Negro Giovanni, Burgazzi Gemma, Viaroli Pierluigi, Vezza Paolo

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Habitat models rarely consider macroinvertebrates as ecological targets in rivers. Available approaches mainly focus on single macroinvertebrate species, not addressing the ecological needs and functionality of the entire community. This research aimed to provide an approach to model the habitat of the macroinvertebrate community. The approach is based on the recently developed Flow-T index, together with a Random Forest (RF) regression, which is employed to apply the Flow-T index at the meso-habitat scale. Using different datasets gathered from both field data collection and 2D hydrodynamic simulations, the model has been calibrated in the Trebbia river (2019 campaign), and then validated in the Trebbia, Taro, and Enza rivers (2020 campaign). The three rivers are characterized by a braiding morphology, gravel riverbeds, and summer low flows. The RF model selected 12 mesohabitat descriptors as important for the macroinvertebrate community. These descriptors belong to different frequency classes of water depth, flow velocity, substrate grain size, and connectivity to the main river channel. The cross-validation R² coefficient (R²𝒸ᵥ) of the training dataset is 0.71 for the Trebbia River (2019), whereas the R² coefficient for the validation datasets (Trebbia, Taro, and Enza Rivers 2020) is 0.63. The agreement between the simulated results and the experimental data shows sufficient accuracy and reliability. The outcomes of the study reveal that the model can identify the ecological response of the macroinvertebrate community to possible flow regime alterations and to possible river morphological modifications. Lastly, the proposed approach allows extending the MesoHABSIM methodology, widely used for the fish habitat assessment, to a different ecological target community. Further applications of the approach can be related to flow design in both perennial and non-perennial rivers, including river reaches in which fish fauna is absent.

Keywords: ecological flows, macroinvertebrate community, mesohabitat, river habitat modeling

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Authors: Ghaem Zamani, Farveh Aghaye Nezhad, Amin Barari

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The installation process of caissons has usually been a challenging step in the design phase, especially in the case of suction-assisted installation. The engineering practice for estimating the caisson penetration resistance is primarily controlled by the resistance governed by inner and outer skirt friction and the tip resistance. Different methods have been proposed in the literature to evaluate the above components, while the CPT-based methodology has attained notable popularity among others. In this method, two empirical coefficients are suggested, k𝒻 and kp, which relate the frictional resistance and tip resistance to the cone penetration resistance (q𝒸), respectively. A series of jacking installation and uninstallation experiments for different soil densities were carried out in the offshore geotechnical laboratory of Aalborg University, Denmark. The main goal of these tests was to find appropriate values for empirical coefficients of the CPT-based method for the buckets with large embedment ratio (i.e., d/D=1, where d is the skirt length and D is the diameter) and increased tip area penetrated into dense sand deposits. The friction resistance effects were isolated during the pullout experiments; hence, the k𝒻 was back-measured from the tests in the absence of tip resistance. The actuator force during jacking installation equals the sum of frictional resistance and tip resistance. Therefore, the tip resistance of the bucket is calculated by subtracting the back-measured frictional resistance from penetration resistance; hence the relevant coefficient kp would be achieved. The cone penetration test was operated at different points before and after each installation attempt to measure the cone penetration resistance (q𝒸), and the average value of q𝒸 is used for calculations. The experimental results of the jacking installation tests indicated that a larger friction area considerably increased the penetration resistance; however, this effect was completely diminished when foundation suction-assisted penetration was used. Finally, the values measured for the empirical coefficient of the CPT-based method are compared with the highest expected and most probable values suggested by DNV(1992) for uniform thickness buckets.

Keywords: suction caisson, offshore geotechnics, cone penetration test, wind turbine foundation

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Authors: Nia Mair Fry, Matthew Profit, Chenfeng Li

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This work focuses on the development and implementation of a fully implicit-implicit, coupled mechanical deformation and porous flow, finite element software tool. The fully implicit software accurately predicts classical fundamental analytical solutions such as the Terzaghi consolidation problem. Furthermore, it can capture other analytical solutions less well known in the literature, such as Gibson’s sedimentation rate problem and Coussy’s problems investigating wellbore stability for poroelastic rocks. The mechanical volume strains are transferred to the porous flow governing equation in an implicit framework. This will overcome some of the many current industrial issues, which use explicit solvers for the mechanical governing equations and only implicit solvers on the porous flow side. This can potentially lead to instability and non-convergence issues in the coupled system, plus giving results with an accountable degree of error. The specification of a fully monolithic implicit-implicit coupled porous media code sees the solution of both seepage-mechanical equations in one matrix system, under a unified time-stepping scheme, which makes the problem definition much easier. When using an explicit solver, additional input such as the damping coefficient and mass scaling factor is required, which are circumvented with a fully implicit solution. Further, improved accuracy is achieved as the solution is not dependent on predictor-corrector methods for the pore fluid pressure solution, but at the potential cost of reduced stability. In testing of this fully monolithic porous media code, there is the comparison of the fully implicit coupled scheme against an existing staggered explicit-implicit coupled scheme solution across a range of geotechnical problems. These cases include 1) Biot coefficient calculation, 2) consolidation theory with Terzaghi analytical solution, 3) sedimentation theory with Gibson analytical solution, and 4) Coussy well-bore poroelastic analytical solutions.

Keywords: coupled, implicit, monolithic, porous media

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Authors: Emejeamara Francis

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The future of potentials wind energy applications within suburban/urban areas are currently faced with various problems. These include insufficient assessment of urban wind resource, and the effectiveness of commercial gust control solutions as well as unavailability of effective and cheaper valuable tools for scoping the potentials of urban wind applications within built-up environments. In order to achieve effective assessment of the potentials of urban wind installations, an estimation of the total energy that would be available to them were effective control systems to be used, and evaluating the potential power to be generated by the wind system is required. This paper presents a methodology of predicting the power generated by a wind system operating within an urban wind resource. This method was developed by using high temporal resolution wind measurements from eight potential sites within the urban and suburban environment as inputs to a vertical axis wind turbine multiple stream tube model. A relationship between the unsteady performance coefficient obtained from the stream tube model results and turbulence intensity was demonstrated. Hence, an analytical methodology for estimating the unsteady power coefficient at a potential turbine site is proposed. This is combined with analytical models that were developed to predict the wind speed and the excess energy (EEC) available in estimating the potential power generated by wind systems at different heights within a built environment. Estimates of turbulence intensities, wind speed, EEC and turbine performance based on the current methodology allow a more complete assessment of available wind resource and potential urban wind projects. This methodology is applied to four major UK cities namely Leeds, Manchester, London and Edinburgh and the potential to map the turbine performance at different heights within a typical urban city is demonstrated.

Keywords: small-scale wind, turbine power, urban wind energy, turbulence intensity, excess energy content

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Authors: Young-Tae Lee, Hee-Chang Lim

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This paper presents the performance characteristics of Darrieus-type vertical axis wind turbine (VAWT) with NACA airfoil blades. The performance of Darrieus-type VAWT can be characterized by torque and power. There are various parameters affecting the performance such as chord length, helical angle, pitch angle and rotor diameter. To estimate the optimum shape of Darrieustype wind turbine in accordance with various design parameters, we examined aerodynamic characteristics and separated flow occurring in the vicinity of blade, interaction between flow and blade, and torque and power characteristics derived from it. For flow analysis, flow variations were investigated based on the unsteady RANS (Reynolds-averaged Navier-Stokes) equation. Sliding mesh algorithm was employed in order to consider rotational effect of blade. To obtain more realistic results we conducted experiment and numerical analysis at the same time for three-dimensional shape. In addition, several parameters (chord length, rotor diameter, pitch angle, and helical angle) were considered to find out optimum shape design and characteristics of interaction with ambient flow. Since the NACA airfoil used in this study showed significant changes in magnitude of lift and drag depending on an angle of attack, the rotor with low drag, long cord length and short diameter shows high power coefficient in low tip speed ratio (TSR) range. On the contrary, in high TSR range, drag becomes high. Hence, the short-chord and long-diameter rotor produces high power coefficient. When a pitch angle at which airfoil directs toward inside equals to -2° and helical angle equals to 0°, Darrieus-type VAWT generates maximum power.

Keywords: darrieus wind turbine, VAWT, NACA airfoil, performance

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Authors: C. Rekha, G. N. Krishnamurthy

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This paper attempts to develop a different approach for key scheduling algorithm which uses both Blowfish and AES algorithms. The main drawback of Blowfish algorithm is, it takes more time to create the S-box entries. To overcome this, we are replacing process of S-box creation in blowfish, by using key dependent S-box creation from AES without affecting the basic operation of blowfish. The method proposed in this paper uses good features of blowfish as well as AES and also this paper demonstrates the performance of blowfish and new algorithm by considering different aspects of security namely Encryption Quality, Key Sensitivity, and Correlation of horizontally adjacent pixels in an encrypted image.

Keywords: AES, blowfish, correlation coefficient, encryption quality, key sensitivity, s-box

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Authors: Eriselda Simoni, Leonard Simoni, Endri Paparisto, Laureta Flaga, Silvana Bara, Edit Xhajanka, Arjan Harxhi

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Background: Some pathologies are encountered more often in HIV/ AIDS, such as those with bacterial, fungal, viral, and neoplastic causes, but what has been more noticeable in recent years is the increased and more aggressive manifestation of periodontal disease and oral caries. Our purpose is to investigate the correlation between the HIV/AIDS stage and CD4 level with oral health, dentition, and periodontal status. Materials and Methods: We conducted a prospective observational study that included 35 patients newly diagnosed with HIV/AIDS and underwent an oral examination at the University Dental Clinic in Tirana, Albania, in the period April - July 2024. This study evaluated the basic demographic, laboratory characteristics, oral hygiene, and the presence of oral lesions. The dentition status was assessed with the values DT (decay teeth), FT (filled teeth), and MT (missing teeth) presented as DMFT. The periodontal status was evaluated through a periodontal probe measuring CPI (community periodontal index) and LOA (loss of attachment) as recommended by the WHO Oral Health Assessment Form 2013. The Pearson Correlation Coefficient (r) was used to evaluate the relationship between levels of CD4+ and DMF, CD4+ and CPI, and CD4+ and LOA. The P value ≤ 0.05 was considered statistically significant. Results: 80% of patients included were males with a mean age of 35.8 years. 8.6% of patients were categorized as HIV stage I, 28.6% as stage II, and 62.8% as HIV stage III/AIDS. The mean level value of CD4+ was 266.2 cells/mm3 and the rapport CD4+/ WBC (White Blood Cells) was 15.7%. Most patients (57.2%) used toothbrushes less than 1 time a day. An important negative correlation was found between CD4+ and dentition and periodontal status. A lower level of CD4+ was correlated with a higher DMFT, CPI, and LOA, respectively coefficient (r) for CD4/DMFT = -0.52, p =0.01, (r) for CD4/CPI= - 0.38, p=0.024 and (r) for CD4/LOA= - 0.37, p=0.029. Conclusions: In our study, it was documented that patients with HIV/AIDS had worse oral health, an important negative correlation between CD4+ and dentition and periodontal status. A lower level of CD4+ was correlated with a worse dentition status (higher DMFT), and poor periodontal health (higher CPI and LOA). The monitoring and treatment of oral pathologies can be important in early HIV/AIDS diagnoses and treatment.

Keywords: HIV/AIDS, oral health, dentition, periodontal

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Authors: Dylan Santos De Pinho, Nabil Ouerhani

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Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.

Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization

Procedia PDF Downloads 147

Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur

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Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.

Keywords: multiscale, bidimensional, wavelets, backscattering, multilayer, SPM, air pockets

Procedia PDF Downloads 125

Authors: Masoud Ghaemi, MohammadJafar Hedayati, Faezeh Yousefzadeh, Hoseinali Heydarzadeh

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According to the statistics of the International Committee on Large Dams, internal erosion and piping (scour) are major causes of the destruction of earth-fill dams. If such dams are constructed in narrow valleys, the valley walls will increase the arching of the dam body due to the transfer of vertical and horizontal stresses, so the occurrence of hydraulic fracturing in these embankments is more likely. Roudbar Dam in Lorestan is a clay-core pebble earth-fill dam constructed in a relatively narrow valley in western Iran. Three years after the onset of impoundment, there has been a fall in dam behavior. Evaluation of the dam behavior based on the data recorded on the instruments installed inside the dam body and foundation confirms the occurrence of internal erosion in the lower and adjacent parts of the core on the left support (abutment). The phenomenon of hydraulic fracturing is one of the main causes of the onset of internal erosion in this dam. Accordingly, the main objective of this paper is to evaluate the validity of this hypothesis. To evaluate the validity of this hypothesis, the dam behavior during construction and impoundment has been first simulated with a three-dimensional numerical model. Then, using validated empirical equations, the safety factor of the occurrence of hydraulic fracturing phenomenon upstream of the dam score was calculated. Then, using the artificial neural network, the failure time of the given section was predicted based on the maximum stress trend created. The study results show that steep slopes of valley walls, sudden changes in coefficient, and differences in compressibility properties of dam body materials have caused considerable stress transfer from core to adjacent valley walls, especially at its lower levels. This has resulted in the coefficient of confidence of the occurrence of hydraulic fracturing in each of these areas being close to one in each of the empirical equations used.

Keywords: arching, artificial neural network, FLAC3D, hydraulic fracturing, internal erosion, pore water pressure

Procedia PDF Downloads 177

Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

Procedia PDF Downloads 203

Authors: Ogbonnaya Elom, Francis N. Azunku, Ogochukwu Onah

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This study was carried out to determine the correlates of cost effectiveness analysis of rating scale and psycho-productive multiple choice test for assessing students’ performance in rice production. Four research questions were developed and answered, while one hypothesis was formulated and tested. Survey and correlation designs were adopted. The population of the study was 20,783 made up of 20,511 senior secondary (SSII) students and 272 teachers of agricultural science from 221 public secondary schools. Two schools with one intact class of 30 students each was purposely selected as sample based on certain criteria. Four sets of instruments were used for data collection. One of the instruments-the rating scale, was subjected to face and content validation while the other three were subjected to face validation only. Cronbach alpha technique was utilized to determine the internal consistency of the rating scale items which yielded a coefficient of 0.82 while the Kudder-Richardson (K-R 20) formula was involved in determining the stability of the psycho-productive multiple choice test items which yielded a coefficient of 0.80. Method of data collection involved a step-by-step approach in collecting data. Data collected were analyzed using percentage, weighted mean and sign test to answer the research questions while the hypothesis was tested using Spearman rank-order of correlation and t-test statistic. Findings of the study revealed among others, that psycho-productive multiple choice test is more effective than rating scale when the former is applied on the two groups of students. It was recommended among others, that the external examination bodies should integrate the use of psycho- productive multiple choice test into their examination policy and direct secondary schools to comply with it.

Keywords: correlates, cost-effectiveness, psycho-productive multiple-choice scale, rating scale

Procedia PDF Downloads 141

Authors: Kukuri Tavartkiladze, Nana Bolashvili

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The purpose of this paper was separation and study of the part of structure regime, which directly affects the process of desertification. A simple scheme was prepared for the assessment of desertification process; surface air temperature and precipitation for the years of 1936-2009 were analyzed.  The map of distribution of the Desertification Contributing Coefficient in the territory of Georgia was compiled. The simple scheme for identification of the intensity of the desertification contributing process has been developed and the illustrative example of its practical application for the territory of Georgia has been conducted.

Keywords: aridity, climate change, desertification, precipitation

Procedia PDF Downloads 336

Authors: Najeeb Hassan, Mahmudur Rahman

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Arial Khan River is one of the main south-eastward outlets of the River Padma. This river maintains a meander channel through its course and is erosional in nature. The specific objective of the research is to study and evaluate the hydrological characteristics in the form of assessing changes of cross-sections, discharge, water level and velocity profile in different stations and to create a hydrodynamic model of the Arial Khan River. Necessary data have been collected from Bangladesh Water Development Board (BWDB) and Center for Environment and Geographic Information Services (CEGIS). Satellite images have been observed from Google earth. In this study, hydrodynamic model of Arial Khan River has been developed using well known steady open channel flow code Hydrologic Engineering Centers and River Analysis System (HEC-RAS) using field surveyed geometric data. Cross-section properties at 22 locations of River Arial Khan for the years 2011, 2013 and 2015 were also analysed. 1-D HEC-RAS model has been developed using the cross sectional data of 2015 and appropriate boundary condition is being used to run the model. This Arial Khan River model is calibrated using the pick discharge of 2015. The applicable value of Mannings roughness coefficient (n) is adjusted through the process of calibration. The value of water level which ties with the observed data to an acceptable accuracy is taken as calibrated model. The 1-D HEC-RAS model then validated by using the pick discharges from 2009-2018. Variation in observed water level in the model and collected water level data is being compared to validate the model. It is observed that due to seasonal variation, discharge of the river changes rapidly and Mannings roughness coefficient (n) also changes due to the vegetation growth along the river banks. This river model may act as a tool to measure flood area in future. By considering the past pick flow discharge, it is strongly recommended to improve the carrying capacity of Arial Khan River to protect the surrounding areas from flash flood.

Keywords: BWDB, CEGIS, HEC-RAS

Procedia PDF Downloads 183

Authors: Izadi Banafsheh, Sedaghat Reza

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Maintenance, Repair, and Overhaul (MRO) of machinery are a key recent issue concerning the automotive industry. It has always been a debated question what order or priority should be adopted for the MRO of machinery. This study attempts to examine several criteria including process sensitivity, average time between machine failures, average duration of repair, availability of parts, availability of maintenance personnel and workload through a literature review and experts survey so as to determine the condition of the machine. According to the mentioned criteria, the machinery were ranked in four modes below: A) Need for inspection, B) Need for minor repair, C) Need for part replacement, and D) Need for major repair. The Fuzzy AHP was employed to determine the weighting of criteria. At the end, the obtained weights were ranked through the AHP for each criterion, three groups were specified: shaving machines, assembly and painting in four modes. The statistical population comprises the elite in the Iranian automotive industry at IKCO covering operation managers, CEOs and maintenance professionals who are highly specialized in MRO and perfectly knowledgeable in how the machinery function. The information required for this study were collected from both desk research and field review, which eventually led to construction of a questionnaire handed out to the sample respondents in order to collect information on the subject matter. The results of the AHP for weighting the criteria revealed that the availability of maintenance personnel was the top priority at coefficient of 0.206, while the process sensitivity took the last priority at coefficient of 0.066. Furthermore, the results of TOPSIS for prioritizing the IKCO machinery suggested that at the mode where there is need for inspection, the assembly machines took the top priority while paining machines took the third priority. As for the mode where there is need for minor repairs, the assembly machines took the top priority while the third priority belonged to the shaving machines. As for the mode where there is need for parts replacement, the assembly machines took the top priority while the third belonged to the paining machinery. Finally, as for the mode where there is need for major repair, the assembly machines took the top priority while the third belonged to the paining machinery.

Keywords: maintenance, repair, overhaul, MRO, prioritization of machinery, fuzzy logic, AHP, TOPSIS

Procedia PDF Downloads 286

Authors: E. T. L. Cöuras Ford, V. A. C. Vale, J. U. L. Mendes

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Two of the objective principal in the study of the aerodynamics of vehicles are the safety and the acting. Those objectives can be reached through the development of devices modify the drainage of air about of the vehicle and also through alterations in the way of the external surfaces. The front lowest profile of the vehicle, for instance, has great influence on the coefficient of aerodynamic penetration (Cx) and later on great part of the pressure distribution along the surface of the vehicle. The objective of this work was of analyzing the aerodynamic behavior that it happens on some types the trucks of vehicles, based on experimentation in aerodynamic tunnel, seeking to determine the aerodynamic efficiency of each one of them.

Keywords: aerodynamic, vehicles, wind tunnel, safety, acting

Procedia PDF Downloads 499

Authors: Usoro Anthony E., Udoh Emediong

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Diagonal Vector Autoregressive Models are special classes of the general vector autoregressive models identified under certain conditions, where parameters are restricted to the diagonal elements in the coefficient matrices. Variance, autocovariance, and autocorrelation properties of the upper and lower diagonal VAR models are derived. The new set of VAR models is verified with empirical data and is found to perform favourably with the general VAR models. The advantage of the diagonal models over the existing models is that the new models are parsimonious, given the reduction in the interactive coefficients of the general VAR models.

Keywords: VAR models, diagonal VAR models, variance, autocovariance, autocorrelations

Procedia PDF Downloads 116

Authors: Jemal Ebrahim Dessie, Lukács Zsolt

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High-strength aluminum alloys have drawn a lot of attention because of the expanding demand for lightweight vehicle design in the automotive sector. Due to poor formability at room temperature, warm and hot forming have been advised. However, warm and hot forming methods need more steps in the production process and an advanced tooling system. In contrast, since ordinary tools can be used, forming sheets at room temperature in the W temper condition is advantageous. However, springback of supersaturated sheets and their thinning are critical challenges and must be resolved during the use of this technique. In this study, AA6082-T6 aluminum alloy was solution heat treated at different oven temperatures and times using a specially designed and developed furnace in order to optimize the W-temper heat treatment temperature. A U-shaped bending test was carried out at different time periods between W-temper heat treatment and forming operation. Finite element analysis (FEA) of U-bending was conducted using AutoForm aiming to validate the experimental result. The uniaxial tensile and unload test was performed in order to determine the kinematic hardening behavior of the material and has been optimized in the Finite element code using systematic process improvement (SPI). In the simulation, the effect of friction coefficient & blank holder force was considered. Springback parameters were evaluated by the geometry adopted from the NUMISHEET ’93 benchmark problem. It is noted that the change of shape was higher at the more extended time periods between W-temper heat treatment and forming operation. Die radius was the most influential parameter at the flange springback. However, the change of shape shows an overall increasing tendency on the sidewall as the increase of radius of the punch than the radius of the die. The springback angles on the flange and sidewall seem to be highly influenced by the coefficient of friction than blank holding force, and the effect becomes increases as increasing the blank holding force.

Keywords: aluminum alloy, FEA, springback, SPI, U-bending, W-temper

Procedia PDF Downloads 100

Authors: Jonghyuk Yoon, Hyoungwoon Song

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Recently, there are lots of increasing interest in a smart farming that represents application of modern Information and Communication Technologies (ICT) into agriculture since it provides a methodology to optimize production efficiencies by managing growing conditions of crops automatically. In order to obtain high performance and stability for smart greenhouse, it is important to identify the effect of various working parameters such as capacity of ventilation fan, vent opening area and etc. In the present study, a 3-dimensional CFD (Computational Fluid Dynamics) simulation for single-span greenhouse was conducted using the commercial program, Ansys CFX 18.0. The numerical simulation for single-span greenhouse was implemented to figure out the internal thermal and flow characteristics. In order to numerically model solar radiation that spread over a wide range of wavelengths, the multiband model that discretizes the spectrum into finite bands of wavelength based on Wien’s law is applied to the simulation. In addition, absorption coefficient of vinyl varied with the wavelength bands is also applied based on Beer-Lambert Law. To validate the numerical method applied herein, the numerical results of the temperature at specific monitoring points were compared with the experimental data. The average error rates (12.2~14.2%) between them was shown and numerical results of temperature distribution are in good agreement with the experimental data. The results of the present study can be useful information for the design of various greenhouses. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Advanced Production Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA)(315093-03).

Keywords: single-span greenhouse, CFD (computational fluid dynamics), solar radiation, multiband model, absorption coefficient

Procedia PDF Downloads 136

Authors: Nasrin Akter, Bilkis Banu, Farhana Faruque, Fatema Afrin, Sujana Haque Chowdhury, Sarder Mahmud Hossain

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Objectives: To combat the growing prevalence of hypertension in Bangladesh, it is pivotal to have an in-depth understanding of quality of life (QOL) among hypertensive people. The aim of this study was to measure QOL of hypertensive people and its determinants in a selected tertiary hospital in Dhaka city. Design & Methods: This analytical cross-sectional study was conducted among randomly selected 300 hypertensive patients from two cardiac departments of Square Hospitals Limited. Data were collected through the face-to-face interview method. WHOQOL-BREF questionnaire was used to assess the QOL. Mean scores of quality of life were analyzed through descriptive statistics. Cronbach’s alpha coefficient and Pearson’s correlation coefficient were applied to estimate the internal consistency, and the level of agreement among different domains of WHOQOL-BREF, respectively. Chi-square test followed by binary regression analyses were used to measure the association between QOL domains and independent variables. Results: Both overall QOL and domains had a good internal consistency, (r = 0.13–0.77, p< 0.01). The QOL among hypertensive patients was found to be poor in the psychological (71%) and social (74.7%) domains and good in the environmental (63%) and physical (65%) domains. Backward binary regressions revealed that being older (p=0.01), diabetic (p=0.02), having history of COVID-19 (p=0.01), and poor monthly income (USD ≤853.14) (p=0.01) were significantly associated with poor QOL in all domain. Moreover, older age (p=0.01) and poor lifestyle (p=0.02) were significantly associated with poor overall quality of life and poor general health perception. Conclusion: The results revealed low QOL in the psychological and social domain including significant factors associated with the poor QOL in all domains. To enhance the quality of life for hypertensive patients—especially those who are older, diabetic, have lower incomes, experienced COVID-19, and maintain poor lifestyles—effective interventions and health system strengthening are crucial.

Keywords: quality of life, hypertension, WHOQOL-BREF, analytical cross-sectional study

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Authors: Litim Tarek, Taamallah Ouahiba

Abstract:

This work relates to the physico-geometrical aspect of the surface layers of 16NC6 steel having undergone the burnishing treatment by hard steel ball. The results show that the optimal effects of burnishing are closely linked to the shape and the material of the active part of the device as well as to the surface plastic deformation ability of the material to be treated. Thus the roughness is improved by more than 70%, and the consolidation rate is increased by 30%. In addition, modeling of the rational traction curves provides a work hardening coefficient of up to 0.3 in the presence of burnishing.

Keywords: 16NC6 steel, burnishing, hardening, roughness

Procedia PDF Downloads 164