Search results for: predict

Authors: Bin Shi, Mouhab Meshreki, Grégoire Bazin, Helmi Attia

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Large monolithic components are widely used in the aerospace industry in order to reduce airplane weight. Milling is an important operation in manufacturing of the monolithic parts. More than 90% of the material could be removed in the milling operation to obtain the final shape. This results in low rigidity and post-machining distortion. The post-machining distortion is the deviation of the final shape from the original design after releasing the clamps. It is a major challenge in machining of the monolithic parts, which costs billions of economic losses every year. Three sources are directly related to the part distortion, including initial residual stresses (RS) generated from previous manufacturing processes, machining-induced RS and thermal load generated during machining. A finite element model was developed to simulate a milling process and predicate the post-machining distortion. In this study, a rolled-aluminum plate AA7175 with a thickness of 60 mm was used for the raw block. The initial residual stress distribution in the block was measured using a layer-removal method. A stress-mapping technique was developed to implement the initial stress distribution into the part. It is demonstrated that this technique significantly accelerates the simulation time. Machining-induced residual stresses on the machined surface were measured using MTS3000 hole-drilling strain-gauge system. The measured RS was applied on the machined surface of a plate to predict the distortion. The predicted distortion was compared with experimental results. It is found that the effect of the machining-induced residual stress on the distortion of a thick plate is very limited. The distortion can be ignored if the wall thickness is larger than a certain value. The RS generated from the thermal load during machining is another important factor causing part distortion. Very limited number of research on this topic was reported in literature. A coupled thermo-mechanical FE model was developed to evaluate the thermal effect on the plastic deformation of a plate. A moving heat source with a feed rate was used to simulate the dynamic cutting heat in a milling process. When the heat source passed the part surface, a small layer was removed to simulate the cutting operation. The results show that for different feed rates and plate thicknesses, the plastic deformation/distortion occurs only if the temperature exceeds a critical level. It was found that the initial residual stress has a major contribution to the part distortion. The machining-induced stress has limited influence on the distortion for thin-wall structure when the wall thickness is larger than a certain value. The thermal load can also generate part distortion when the cutting temperature is above a critical level. The developed numerical model was employed to predict the distortion of a frame part with complex structures. The predictions were compared with the experimental measurements, showing both are in good agreement. Through optimization of the position of the part inside the raw plate using the developed numerical models, the part distortion can be significantly reduced by 50%.

Keywords: modelling, monolithic parts, optimization, post-machining distortion, residual stresses

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Authors: Yee-Ting Lee, Jyun-Rong Zhuang, Wen-Hsin Hsieh, An-Shik Yang

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Additive manufacturing (AM) is increasingly crucial in biomedical and aerospace industries. As a recently developed AM technique, selective laser melting (SLM) has become a commercial method for various manufacturing processes. However, the molten pool configuration during SLM of metal powders is a decisive issue for the product quality. It is very important to investigate the heat transfer characteristics during the laser heating process. In this work, the finite element method (FEM) software ANSYS^® (work bench module 16.0) was used to predict the unsteady temperature distribution for resolving molten pool dimensions with consideration of temperature-dependent thermal physical properties of TiAl6V4 at different laser powers and scanning speeds. The simulated results of the temperature distributions illustrated that the ratio of laser power to scanning speed can greatly influence the size of molten pool of titanium alloy powder for SLM development.

Keywords: additive manufacturing, finite element method, molten pool dimensions, selective laser melting

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Authors: H. H. Goh, Q. S. Chua, S. W. Lee, B. C. Kok, K. C. Goh, K. T. K. Teo

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At present, the evaluation of voltage stability assessment experiences sizeable anxiety in the safe operation of power systems. This is due to the complications of a strain power system. With the snowballing of power demand by the consumers and also the restricted amount of power sources, therefore, the system has to perform at its maximum proficiency. Consequently, the noteworthy to discover the maximum ability boundary prior to voltage collapse should be undertaken. A preliminary warning can be perceived to evade the interruption of power system’s capacity. The effectiveness of line voltage stability indices (LVSI) is differentiated in this paper. The main purpose of the indices is used to predict the proximity of voltage instability of the electric power system. On the other hand, the indices are also able to decide the weakest load buses which are close to voltage collapse in the power system. The line stability indices are assessed using the IEEE 14 bus test system to validate its practicability. Results demonstrated that the implemented indices are practically relevant in predicting the manifestation of voltage collapse in the system. Therefore, essential actions can be taken to dodge the incident from arising.

Keywords: critical line, line outage, line voltage stability indices (LVSI), maximum loadability, voltage collapse, voltage instability, voltage stability analysis

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Authors: Maha Almumaiz, Harry Evdorides

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Change in land value typically occurs when a new interurban road construction causes an increase in accessibility; this change in the adjacent lands values differs according to land characteristics such as geographic location, land use type, land area and sale time (appraisal time). A multiple regression model is obtained to predict the percent change in land value (CLV) based on four independent variables namely land distance from the constructed road, area of land, nature of land use and time from the works completion of the road. The random values of percent change in land value were generated using Microsoft Excel with a range of up to 35%. The trend of change in land value with the four independent variables was determined from the literature references. The statistical analysis and model building process has been made by using the IBM SPSS V23 software. The Regression model suggests, for lands that are located within 3 miles as the straight distance from the road, the percent CLV is between (0-35%) which is depending on many factors including distance from the constructed road, land use, land area and time from works completion of the new road.

Keywords: interurban road, land use types, new road construction, percent CLV, regression model

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Authors: Sudipta Ghorai, Ossama Salem

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Pavement maintenance, repair, and rehabilitation (MRR) processes may have considerable environmental impacts due to traffic disruptions associated with work zones. The simulation models in use to predict the emission of work zones were mostly static emission factor models (SEFD). SEFD calculates emissions based on average operation conditions e.g. average speed and type of vehicles. Although these models produce accurate results for large-scale planning studies, they are not suitable for analyzing driving conditions at the micro level such as acceleration, deceleration, idling, cruising, and queuing in a work zone. The purpose of this study is to prepare a comprehensive work zone environmental assessment (WEA) framework to calculate the emissions caused due to disrupted traffic; by integrating traffic microsimulation tools with emission models. This will help highway officials to assess the benefits of accelerated construction and opt for the most suitable TMP not only economically but also from an environmental point of view.

Keywords: accelerated construction, pavement MRR, traffic microsimulation, congestion, emissions

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Authors: Gizem Akcan, Erdinc Ozturk

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The purpose of the study was to determine some psychosocial variables that predict dissociation in university students. These psychosocial variables were perceived childhood trauma, alexithymia, and gender. 150 (75 males, 75 females) university students (bachelor, master and postgraduate) were enrolled in this study. They were chosen from universities in Istanbul at the education year of 2016-2017. Dissociative Experiences Scale (DES), Childhood Trauma Questionnaire (CTQ) and Toronto Alexithymia Scale were used to assess related variables. Demographic Information Form was given to students in order to have their demographic information. Frequency Distribution, Linear Regression Analysis, and t-test analysis were used for statistical analysis. Childhood trauma and alexithymia were found to have predictive value on dissociation among university students. However, physical abuse, physical neglect and emotional neglect sub dimensions of childhood trauma and externally-oriented thinking sub dimension of alexithymia did not have predictive value on dissociation. Moreover, there was no significant difference between males and females in terms of dissociation scores of participants.

Keywords: childhood trauma, dissociation, alexithymia, gender

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Authors: Renuka Mahadevan, Maneka Jayasinghe, Dianne Dredge

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Over the last two years, tourism has been subject to unprecedented changes, and experts predict further change, especially with respect to travel and tourism choices. As concerns regarding the environment and climate change grow, many tourism industry stakeholders are particularly keen on taking steps to mitigate the adverse impacts of the travel industry to the broader society and environment. This approach and process is commonly referred to as 'Sustainable Tourism'. An emerging concept that extends beyond 'sustainable tourism' is 'Regenerative Tourism', which aims to impact the local systems, society and environment positively. In particular, it aims to provide transformational experiences to tourists and thereby inspire the travellers while the local cultural heritage and traditions are preserved from generation to generation. This study analyses how tourism stakeholders are shifting their attitude towards travel and tourism, particularly regarding its impact on people, places, businesses and the environment. The analysis will be based on a global survey of 1200 businesses, tourism organisations, employees, and travel consumers. The preliminary analysis of responses reveals a high interest towards transformational experiences during travel.

Keywords: regenerative tourism, transformational, experience, local systems

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Authors: S. Ebisintei, M. A. Olutoye, A. S. Kovo, U. G. Akpan

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The effect of soil degradation due to ion leachate migration using dumpsite located at Idu industrial area of Abuja was investigated. It was done to assess the health and environmental pollution consequences caused by heavy metals’ concentration in the soil on inhabitants around the settlement. Soil samples collected from four cardinal points and at the center during the dry and wet season were pretreated, digested and heavy metal concentrations present were analyzed using Atomic Absorption Spectrophotometer. The concentrations of Pb, Cu, Mn, Ni, and Cr, were determined and also for control sample obtained 300 m away from the dumpsite. Water samples were collected from three wells to test for physiochemical properties of pH, COD, BOD, DO, hardness, conductivity, and alkalinity. The result showed a significant difference in concentration of toxic heavy metals in the dumpsite as compared to the control sample. A mathematical model was developed to predict the heavy metal concentrations beyond the sampling point. The results indicate that metal concentrations in both dry and wet season were above the WHO, and SON set standards. The trend, if unrestrained, portends danger to human life, reduces agricultural productivity and sustainability.

Keywords: soil degradation, ion leachate, productivity, environment, sustainability

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Authors: Elnaz Bandeh

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This study aimed to predict marital burnout based on irrational beliefs and sexual dysfunction of couples. The research method was descriptive-correlational, and the statistical population included all couples who consulted to counseling clinics in the fall of 2016. The sample consisted of 200 people who were selected by convenience sampling and answered the Ahwaz Irrational Beliefs Questionnaire, Pines Couple Burnout, and Hudson Marital Satisfaction Questionnaire. The data were analyzed using regression coefficient. The results of regression analysis showed that there was a linear relationship between irrational beliefs and couple burnout and dimensions of helplessness toward change, expectation of approval from others, and emotional irresponsibility were positive and significant predictors of couple burnout. However, after avoiding the problem of power, it was not a significant predictor of marital dissatisfaction. There was also a linear relationship between sexual dysfunction and couple burnout, and sexual dysfunction was a positive and significant predictor of couple burnout. Based on the findings, it can be concluded that irrational beliefs and sexual dysfunction play a role in couple dysfunction.

Keywords: couple burnout, irrational beliefs, sexual dysfunction, marital relationship

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Authors: Yoshinori Kitsutaka, Fumiya Ikedo

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In this study, the mechanical model of various anchors embedded in gypsum board subjected cyclic shear loading were investigated. Shear tests for anchors embedded in 200 mm square size gypsum board were conducted to measure the load - load displacement curves. The strength of the gypsum board was changed for three conditions and 12 kinds of anchors were selected which were ordinary used for gypsum board anchoring. The loading conditions were a monotonous loading and a cyclic loading controlled by a servo-controlled hydraulic loading system to achieve accurate measurement. The fracture energy for each of the anchors was estimated by the analysis of consumed energy calculated by the load - load displacement curve. The effect of the strength of gypsum board and the types of anchors on the shear properties of gypsum board anchors was cleared. A numerical model to predict the load-unload curve of shear deformation of gypsum board anchors caused by such as the earthquake load was proposed and the validity on the model was proved.

Keywords: gypsum board, anchor, shear test, cyclic loading, load-unload curve

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Authors: Linda A. O’Higgins, Astrid Wingler, Jorge Oliveira

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The growth of Chlorella vulgaris was characterized as a function of irradiance in a laboratory turbidostat (1 L) and compared to batch growth in sunlit modules (5–25 L) of the commercial Phytobag photobioreactor. The effects of variable sunlight and culture density were deconvoluted by a mathematical model. The analysis showed that algal growth was light-limited due to shading by external construction elements and due to light attenuation within the algal bags. The model was also used to predict maximum biomass productivity. The manipulative experiments and the model predictions were confronted with data from a production season of a 10m2 pilot-scale photobioreactor, Phytobag (10,000 L). The analysis confirmed light limitation in all three photobioreactors. An additional limitation of biomass productivity was caused by the nitrogen starvation that was used to induce lipid accumulation. Reduction of shading and separation of biomass and lipid production are proposed for future optimization.

Keywords: microalgae, batch cultivation, Chlorella vulgaris, Mathematical model, photobioreactor, scale-up

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Authors: Galina Mihaleva, C. Koh

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Fashion, like many other design fields, undergoes numerous evolutions throughout the ages. This paper aims to recognize and evaluate the significance of advance technology in fashion design and examine how it changes the role of modern fashion designers by modifying the creation process. It also touches on how modern culture is involved in such developments and how it affects fashion design in terms of conceptualizing and fabrication. The methodology used is through surveying the various examples of technological applications to fashion design and drawing parallels between what was achievable then and what is achievable now. By comparing case studies, existing fashion design examples and crafting method experimentations; we then spot patterns in which to predict the direction of future developments in the field. A breakdown on the elements of technology in fashion design helps us understand the driving force behind such a trend. The results from explorations in the paper have shown that there is an observed pattern of a distinct increase in interest and progress in the field of fashion technology, which leads to the birth of hybrid crafting methods. In conclusion, it is shown that as fashion technology continues to evolve, their role in clothing crafting becomes more prominent and grows far beyond the humble sewing machine.

Keywords: fashion design, functional aesthetics, smart textiles, 3D printing

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Authors: Aviva Lvan, Lipaz Shamoa-Nir

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Recently, has increased the research interest in modern fatherhood especially, the increasing involvement of fathers in the family. However, there is a little research evidence on fathers to children with special needs. Therefore, the purpose of this study was to examine the effects of stress and coping style on involvement in school among fathers to children with special needs in inclusive education. We compared the fathers to children with special needs (N=72) with fathers to non-special needs children (N = 75), and found that higher stress levels, greater educational involvement and greater use of social support coping style, were found among fathers of children with special needs. In addition, mission coping style and emotional coping style predict involvement in the school and emotional coping style predicts high levels of stress. The above findings contribute to the investigation of changes in the perception of the role of fathers and their involvement in their children's lives especially, among fathers to children with special needs. From the applied aspect, the findings may increase the understanding of the role of fathers and their unique contribution to the social, emotional, and academic development of their children.

Keywords: coping style, educational involvement, special needs, stress

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Authors: Jingde Li, Hong Hao

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Recent oil and gas accidents have reminded us the severe consequences of gas explosion on structure damage and financial loss. In order to protect the structures and personnel, engineers and researchers have been working on numerous different explosion mitigation methods. Amongst, venting is the most economical approach to mitigate gas explosion overpressure. In this paper, venting is used as the overpressure alleviation method. A theoretical method and a numerical technique are presented to predict the internal and external pressure from vented gas explosion in a large enclosure. Under idealized conditions, a number of experiments are used to calibrate the accuracy of the theoretically calculated data. A good agreement between the theoretical results and experimental data is seen. However, for realistic scenarios, the theoretical method over-estimates internal pressures and is incapable of predicting external pressures. Therefore, a CFD simulation procedure is proposed in this study to estimate both the internal and external overpressure from a large-scale vented explosion. Satisfactory agreement between CFD simulation results and experimental data is achieved.

Keywords: vented gas explosion, internal pressure, external pressure, CFD simulation, FLACS, ANSYS Fluent

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Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

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This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

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Authors: Ida Bagus Mandhara Brasika, I Dewa Gde Sathya Deva

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Wolbachia is recently developed as the natural enemy of Dengue virus (DENV). It inhibits the replication of DENV in Aedes aegypti. Both DENV and its vector, Aedes aegypty, are sensitive to climate factor especially temperature. The changing of climate has a direct impact on temperature which means changing the vector transmission. Temperature has been known to effect Wolbachia density as it has an ideal temperature to grow. Some scenarios, which are known as Representative Concentration Pathways (RCPs), have been developed by Intergovernmental Panel on Climate Change (IPCC) to predict the future climate based on greenhouse gases concentration. These scenarios are applied to mitigate the future change of Aedes aegypti migration and how Wolbachia could control the virus. The prediction will determine the schemes to release Wolbachia-injected Aedes aegypti to reduce DENV transmission.

Keywords: Aedes aegypti, climate change, dengue virus, Intergovernmental Panel on Climate Change, representative concentration pathways, Wolbachia

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Authors: Theena Thayalan, K. N. Ramesh Babu

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Machining induced residual stress (RS) is one of the most important surface integrity parameters that characterize the near surface layer of a mechanical component, which plays a crucial role in controlling the performance, especially its fatigue life. Since experimental determination of RS is expensive and time consuming, it would be of great benefit if they could be predicted. In such case, it would be possible to select the cutting parameters required to produce a favorable RS profile. In the present study, an effort has been made to develop a 'two dimensional finite element model (FEM)' to simulate orthogonal cutting process and to predict surface and sub-surface RS using the commercial FEA software DEFORM-2D. The developed finite element model has been validated through experimental investigation of RS. In the experimentation, the orthogonal cutting tests were carried out on AISI 4340 by varying the cutting speed (VC) and uncut chip thickness (f) at three levels and the surface & sub-surface RS has been measured using XRD and Electro polishing techniques. The comparison showed that the RS obtained using developed numerical model is in reasonable agreement with that of experimental data.

Keywords: FEM, machining, residual stress, XRF

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Authors: Wanghongshu Zhou

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This study aims to explore the relationship between the L2MSS and WTC among Chinese non-English major students in order to provide pedagogical implications for English as a Foreign Language (EFL) classrooms in Chinese universities. By employing a mixed methods approach, we involved 103 Chinese non-English major students from a typical university in China, conducted questionnaire survey to measure their levels of L2WTC and L2MSS level, and then analyzed the correlation between the two above mentioned variables. Semi-structured interviews were conducted with eight participants to provide a deeper understanding and explanation of the questionnaire data. Findings show that 1) Chinese non-English major students’ ideal L2 self and L2 learning experience could positively predict their L2 WTC in EFL class; 2) Chinese non-English major students’ ought-to L2 self might have no significant impact on their L2 WTC in EFL class; and 3) self-confidence might be another main factor that will influence Chinese non-English major students’ L2 WTC in EFL class. These findings might shed light on the second language acquisition field and provide pedagogical recommendations for pre-service as well as in-service EFL teachers.

Keywords: L2 willingness to communicate, L2 motivation, self-confidence, Chinese non-English major students

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Authors: Eusebio Odiari, Mark Birkin, Susan Grant-Muller, Nicolas Malleson

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Big data typically refers to consumer datasets revealing some detailed heterogeneity in human behavior, which if harnessed appropriately, could potentially revolutionize our understanding of the collective phenomena of the physical world. Inadvertent missing values skew these datasets and compromise the validity of the thesis. Here we discuss a conceptually consistent strategy for identifying other relevant datasets to combine with available big data, to plug the gaps and to create a rich requisite comprehensive dataset for subsequent analysis. Specifically, emphasis is on how these methodologies can for the first time enable the construction of more detailed pictures of passenger demand and drivers of mobility on the railways. These methodologies can predict the influence of changes within the network (like a change in time-table or impact of a new station), explain local phenomena outside the network (like rail-heading) and the other impacts of urban morphology. Our analysis also reveals that our new imputation data model provides for more equitable revenue sharing amongst network operators who manage different parts of the integrated UK railways.

Keywords: big-data, micro-simulation, mobility, ticketing-data, commuters, transport, synthetic, population

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Authors: Khaleel Sami Hamdan, Dong-Eok Kim, Sang-Ki Moon

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An appropriate model to predict the size of the droplets resulting from the break-up with the structures will help in a better understanding and modeling of the two-phase flow calculations in the simulation of a reactor core loss-of-coolant accident (LOCA). A droplet behavior impacting on a hot surface above the Leidenfrost temperature was investigated. Droplets of known size and velocity were impacted to an inclined plate of hot temperature, and the behavior of the droplets was observed by a high-speed camera. It was found that for droplets of Weber number higher than a certain value, the higher the Weber number of the droplet the smaller the secondary droplets. The COBRA-TF model over-predicted the measured secondary droplet sizes obtained by the present experiment. A simple model for the secondary droplet size was proposed using the mass conservation equation. The maximum spreading diameter of the droplets was also compared to previous correlations and a fairly good agreement was found. A better prediction of the heat transfer in the case of LOCA can be obtained with the presented model.

Keywords: break-up, droplet, impact, inclined hot plate, Leidenfrost temperature, LOCA

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Authors: Luther Ollier, Sylvie Thiria, Anastase Charantonis, Carlos E. Mejia, Michel Crépon

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Sea Surface Height Anomaly (SLA) is a signature of the sub-mesoscale dynamics of the upper ocean. Sea Surface Temperature (SST) is driven by these dynamics and can be used to improve the spatial interpolation of SLA fields. In this study, we focused on the temporal evolution of SLA fields. We explored the capacity of deep learning (DL) methods to predict short-term SLA fields using SST fields. We used simulated daily SLA and SST data from the Mercator Global Analysis and Forecasting System, with a resolution of (1/12)◦ in the North Atlantic Ocean (26.5-44.42◦N, -64.25–41.83◦E), covering the period from 1993 to 2019. Using a slightly modified image-to-image convolutional DL architecture, we demonstrated that SST is a relevant variable for controlling the SLA prediction. With a learning process inspired by the teaching-forcing method, we managed to improve the SLA forecast at five days by using the SST fields as additional information. We obtained predictions of a 12 cm (20 cm) error of SLA evolution for scales smaller than mesoscales and at time scales of 5 days (20 days), respectively. Moreover, the information provided by the SST allows us to limit the SLA error to 16 cm at 20 days when learning the trajectory.

Keywords: deep-learning, altimetry, sea surface temperature, forecast

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Authors: Ji-Yuan Lin, Yu-Ming Liou, Yi-Ting Chen, Chen-Syuan Lin

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Soil water index obtained by tank model is now commonly used in soil and sand disaster alarm system in Japan. Comparing with the rainfall trigging index in Taiwan, the tank model is easy to predict the slope water content on large-scale landslide. Therefore, this study aims to estimate the threshold value of large-scale landslide using the soil water index Sixteen typhoons and heavy rainfall events, were selected to establish the, to relationship between landslide event and soil water index. Finally, the proposed threshold values for landslides on country road No.89 are suggested in this study. The study results show that 95% landslide cases occurred in soil water index more than 125mm, and 30% of the more serious slope failure occurred in the soil water index is greater than 250mm. Beside, this study speculates when soil water index more than 250mm and the difference value between second tank and third tank less than -25mm, it leads to large-scale landslide more probably.

Keywords: soil water index, tank model, landslide, threshold values

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Authors: A. Abdel-Moniem, H. Madkour, K. Farah, A. Abdullah

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The reduction in dapped end beams depth nearby the supports tends to produce stress concentration and hence results in shear cracks, if it does not have an adequate reinforcement detailing. This study investigates numerically the efficiency of applying different external strengthening techniques to the dapped end of such beams. A two-dimensional finite element model was built to predict the structural behavior of dapped ends strengthened with different techniques. The techniques included external bonding of the steel angle at the re-entrant corner, un-bounded bolt anchoring, external steel plate jacketing, exterior carbon fiber wrapping and/or stripping and external inclined steel plates. The FE analysis results are then presented in terms of the ultimate load capacities, load-deflection and crack pattern at failure. The results showed that the FE model, at various stages, was found to be comparable to the available test data. Moreover, it enabled the capture of the failure progress, with acceptable accuracy, which is very difficult in a laboratory test.

Keywords: dapped-end beams, finite element, shear failure, strengthening techniques, reinforced concrete, numerical investigation

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Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

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Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

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Authors: Qingli Lei

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This study investigates the impact of family socioeconomic status and parental involvement on the academic performance of elementary school students, specifically focusing on migrant students in China. The findings reveal that gender has a stronger influence on academic performance compared to local status and parental tutoring time. Female students tend to achieve higher scores than males. Parental education level does not significantly predict academic performance, while parent tutoring time does have a significant impact. Furthermore, there is a significant interaction between local status and parental education level, indicating that migrant students with lower-educated parents perform better than their local counterparts, while local children excel when their parents' education levels are higher. These results emphasize the importance of parental involvement, particularly for immigrant students, and highlight the need for interventions that enhance parental engagement in education to improve academic outcomes.

Keywords: academic performance, family socioeconomic status, migrant students, parental involvement

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Authors: Erfan Memarian, Seyyed Fazayel Alizadeh

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This study aims to evaluate the impacts of the oil and financial markets of the United States on Iran stock exchange and to develop an ARDL model to predict the short and long-term relationship between these markets. In this regard, all 713 weekly data between 28 July 1999 and 20 March 2013 were analyzed by using Microfit4.0 and Eviews7 econometric softwares. The independent variable of the study is the “Price and Yield Index (TEDPIX)” of Tehran Stock Exchange and the independent variables include S & P 500 Index, the US three-month treasury bill rate and West Texas Intermediate oil spot price index. The results show that the West Texas Intermediate oil spot price and the S&P 500 indices have significant positive relationships with Iran's TEDPIX. Also, there exists a significant negative relationship between Iran's TEDPIX and the US three-month Treasury bill rate.

Keywords: TEDPIX; Tehran Stock Exchange; S&P 500 index; USA three-month Treasury bill rate; West Texas Intermediate oil

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Authors: Muskaan Sethi, Arnab Banerjee, Bappaditya Manna

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The present paper aims to investigate a suitable contact between a wheel rolling over a flexible beam. A Linear Complementary (LCP) based approach has been adopted to simulate the contact dynamics for a rigid wheel traversing over a flexible Euler Bernoulli simply supported beam. The adopted methodology is suitable to incorporate the effect of frictional force acting at the wheel-beam interface. Moreover, the possibility of the generation of a gap between the two bodies has also been considered. The present method is based on a unilateral contact assumption which assumes that no penetration would occur when the two bodies come in contact. This assumption helps to predict the contact between wheels and beams in a more practical sense. The proposed methodology is validated with the previously published results and is found to be in good agreement. Further, this method is applied to simulate the contact between wheels and beams for various railway configurations. Moreover, different parametric studies are conducted to study the contact dynamics between the wheel and beam more thoroughly.

Keywords: contact dynamics, linear complementary problem, railway dynamics, unilateral contact

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Authors: Seon Soon Choi

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It is necessary to predict a fatigue crack propagation life for estimation of structural integrity. Because of an uncertainty and a randomness of a structural behavior, it is also required to analyze stochastic characteristics of the fatigue crack propagation life at a specified fatigue crack size. The essential purpose of this study is to present the good probability distribution fit for the fatigue crack propagation life at a specified fatigue crack size in magnesium alloys under various fatigue load ratio conditions. To investigate a stochastic crack growth behavior, fatigue crack propagation experiments are performed in laboratory air under several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability distribution of the fatigue crack propagation life is performed and the good probability distribution fit for the fatigue crack propagation life is presented. The effect of load ratio on variability of fatigue crack propagation life is also investigated.

Keywords: fatigue crack propagation life, load ratio, magnesium alloys, probability distribution

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Authors: M. Palizvan, M. H. Sadr, M. T. Abadi

Abstract:

The representative volume element (RVE) plays a central role in the mechanics of random heterogeneous materials with a view to predicting their effective properties. In this paper, a computational homogenization methodology, developed to determine effective linear elastic properties of composite materials, is extended to predict the effective nonlinear elastoplastic response of long fiber reinforced composite. Finite element simulations of volumes of different sizes and fiber volume fractures are performed for calculation of the overall response RVE. The dependencies of the overall stress-strain curves on the number of fibers inside the RVE are studied in the 2D cases. Volume averaged stress-strain responses are generated from RVEs and compared with the finite element calculations available in the literature at moderate and high fiber volume fractions. For these materials, the existence of an RVE is demonstrated for the sizes of RVE corresponding to 10–100 times the diameter of the fibers. In addition, the response of small size RVE is found anisotropic, whereas the average of all large ones leads to recover the isotropic material properties.

Keywords: homogenization, periodic boundary condition, elastoplastic properties, RVE

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