Search results for: consequence modeling

Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

Procedia PDF Downloads 65

Authors: Meng H. Lean, Wei-Ping L. Chu

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The effects of ferroelectric nanofiller size, shape, loading, and polarization, on bipolar charge injection, transport, and recombination through amorphous and semicrystalline polymers are studied. A 3D particle-in-cell model extends the classical electrical double layer representation to treat ferroelectric nanoparticles. Metal-polymer charge injection assumes Schottky emission and Fowler-Nordheim tunneling, migration through field-dependent Poole-Frenkel mobility, and recombination with Monte Carlo selection based on collision probability. A boundary integral equation method is used for solution of the Poisson equation coupled with a second-order predictor-corrector scheme for robust time integration of the equations of motion. The stability criterion of the explicit algorithm conforms to the Courant-Friedrichs-Levy limit. Trajectories for charge that make it through the film are curvilinear paths that meander through the interspaces. Results indicate that charge transport behavior depends on nanoparticle polarization with anti-parallel orientation showing the highest leakage conduction and lowest level of charge trapping in the interaction zone. Simulation prediction of a size range of 80 to 100 nm to minimize attachment and maximize conduction is validated by theory. Attached charge fractions go from 2.2% to 97% as nanofiller size is decreased from 150 nm to 60 nm. Computed conductivity of 0.4 x 1014 S/cm is in agreement with published data for plastics. Charge attachment is increased with spheroids due to the increase in surface area, and especially so for oblate spheroids showing the influence of larger cross-sections. Charge attachment to nanofillers and nanocrystallites increase with vol.% loading or degree of crystallinity, and saturate at about 40 vol.%.

Keywords: nanocomposites, nanofillers, electrical double layer, bipolar charge transport

Procedia PDF Downloads 354

Authors: Mudassir Ghafoor, Irsalan Arif, Shuaib Salamat

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This paper presents modeling and analysis of different intake bump (compression surface) configurations and comparison with an existing supersonic aircraft having bump intake configuration. Many successful aircraft models have shown that Diverter less Supersonic Inlet (DSI) as compared to conventional intake can reduce weight, complexity and also maintenance cost. The research is divided into two parts. In the first part, four different intake bumps are modeled for comparative analysis keeping in view the consistency of outer perimeter dimensions of fighter aircraft and various characteristics such as flow behavior, boundary layer diversion and pressure recovery are analyzed. In the second part, modeled bumps are integrated with intake duct for performance analysis and comparison with existing supersonic aircraft data is carried out. The bumps are named as uniform large (Config 1), uniform small (Config 2), uniform sharp (Config 3), non-uniform (Config 4) based on their geometric features. Analysis is carried out at different Mach Numbers to analyze flow behavior in subsonic and supersonic regime. Flow behavior, boundary layer diversion and Pressure recovery are examined for each bump characteristics, and comparative study is carried out. The analysis reveals that at subsonic speed, Config 1 and Config 2 give similar pressure recoveries as diverterless supersonic intake, but difference in pressure recoveries becomes significant at supersonic speed. It was concluded from research that Config 1 gives better results as compared to Config 3. Also, higher amplitude (Config 1) is preferred over lower (Config 2 and 4). It was observed that maximum height of bump is preferred to be placed near cowl lip of intake duct.

Keywords: bump intake, boundary layer, computational fluid dynamics, diverter-less supersonic inlet

Procedia PDF Downloads 243

Authors: Paula Paulino, Alzira Matias, Ana Margarida Veiga Simão

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Self-regulated learning (SRL) directs students in analyzing proposed tasks, setting goals and designing plans to achieve those goals. The literature has suggested a metacognitive strategy for goal attainment known as Mental Contrasting with Implementation Intentions (MCII). This strategy involves Mental Contrasting (MC), in which a significant goal and an obstacle are identified, and Implementation Intentions (II), in which an "if... then…" plan is conceived and operationalized to overcome that obstacle. The present study proposes to assess the MCII process and whether it promotes students’ commitment towards learning goals during school tasks in sciences subjects. In this investigation, we intended to study the MCII strategy in a systemic context of the classroom. Fifty-six students from middle school and secondary education attending a public school in Lisbon (Portugal) participated in the study. The MCII strategy was explicitly taught in a procedure that included metacognitive modeling, guided practice and autonomous practice of strategy. A mental contrast between a goal they wanted to achieve and a possible obstacle to achieving that desire was instructed, and then the formulation of plans in order to overcome the obstacle identified previously. The preliminary results suggest that the MCII metacognitive strategy, applied to the school context, leads to more sophisticated reflections, the promotion of learning goals and the elaboration of more complex and specific self-regulated plans. Further, students achieve better results on school tests and worksheets after strategy practice. This study presents important implications since the MCII has been related to improved outcomes and increased attendance. Additionally, MCII seems to be an innovative process that captures students’ efforts to learn and enhances self-efficacy beliefs during learning tasks.

Keywords: implementation intentions, learning goals, mental contrasting, metacognitive strategy, self-regulated learning

Procedia PDF Downloads 241

Authors: Florina Magdalena Anichitoae, Anca Dobrean, Ionut Stelian Florean

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Due to the fact that cyberbullying victimization is an increasing problem nowadays, affecting more and more children and adolescents around the world, we wanted to take a step forward analyzing this phenomenon. So, we took a look at some variables which haven't been studied together before, trying to develop another way to view cyberbullying victimization. We wanted to test the effects of the mother, father, and peer attachment on adolescent involvement in cyberbullying as victims through unconditional self acceptance. Furthermore, we analyzed each subscale of the IPPA-R, the instrument we have used for parents and peer attachment measurement, in regards to cyberbullying victimization through unconditional self acceptance. We have also analyzed if gender and age could be taken into consideration as moderators in this model. The analysis has been performed on 653 adolescents aged 11-17 years old from Romania. We used structural equation modeling, working in R program. For the fidelity analysis of the IPPA-R subscales, USAQ, and Cyberbullying Test, we have calculated the internal consistency index, which varies between .68-.91. We have created 2 models: the first model including peer alienation, peer trust, peer communication, self acceptance and cyberbullying victimization, having CFI=0.97, RMSEA=0.02, 90%CI [0.02, 0.03] and SRMR=0.07, and the second model including parental alienation, parental trust, parental communication, self acceptance and cyberbullying victimization and had CFI=0.97, RMSEA=0.02, 90%CI [0.02, 0.03] and SRMR=0.07. Our results were interesting: on one hand, cyberbullying victimization is predicted by peer alienation and peer communication through unconditional self acceptance. Peer trust directly, significantly, and negatively predicted the implication in cyberbullying. In this regard, considering gender and age as moderators, we found that the relationship between unconditional self acceptance and cyberbullying victimization is stronger in girls, but age does not moderate the relationship between unconditional self acceptance and cyberbullying victimization. On the other hand, regarding the degree of cyberbullying victimization as being predicted through unconditional self acceptance by parental alienation, parental communication, and parental trust, this hypothesis was not supported. Still, we could identify a direct path to positively predict victimization through parental alienation and negatively through parental trust. There are also some limitations to this study, which we've discussed in the end.

Keywords: adolescent, attachment, cyberbullying victimization, parents, peers, unconditional self-acceptance

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Authors: Arwin Malabanan, Carl Chester Ragudo, Jerome Tadiosa, John Dee Mangoba, Eric Augustus Tingatinga, Romeo Eliezer Longalong

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Concrete hollow blocks (CHB) are the most commonly used masonry block for walls in residential houses, school buildings and public buildings in the Philippines. During the recent 2013 Bohol earthquake (Mw 7.2), it has been proven that CHB walls are very vulnerable to severe external action like strong ground motion. In this paper, a numerical model of CHB structures is proposed, and seismic behavior of CHB houses is presented. In modeling, the Rigid Body Spring-Discrete Element method (RBS-DEM)) is used wherein masonry blocks are discretized into rigid elements and connected by nonlinear springs at preselected contact points. The shear and normal stiffness of springs are derived from the material properties of CHB unit incorporating the grout and mortar fillings through the volumetric transformation of the dimension using material ratio. Numerical models of reinforced and unreinforced walls are first subjected to linearly-increasing in plane loading to observe the different failure mechanisms. These wall models are then assembled to form typical model masonry houses and then subjected to the El Centro and Pacoima earthquake records. Numerical simulations show that the elastic, failure and collapse behavior of the model houses agree well with shaking table tests results. The effectiveness of the method in replicating failure patterns will serve as a basis for the improvement of the design and provides a good basis of strengthening the structure.

Keywords: concrete hollow blocks, discrete element method, earthquake, rigid body spring model

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Authors: Addisu H. Addis, Hugh T. Blair, Paul R. Kenyon, Stephen T. Morris, Nicola M. Schreurs, Dorian J. Garrick

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Agent-based modeling (ABM) enables an in silico representation of complex systems and cap-tures agent behavior resulting from interaction with other agents and their environment. This study developed an ABM to represent a pasture-based beef cattle finishing systems in New Zea-land (NZ) using attributes of the rearer, finisher, and processor, as well as specific attributes of dairy-origin beef cattle. The model was parameterized using values representing 1% of NZ dairy-origin cattle, and 10% of rearers and finishers in NZ. The cattle agent consisted of 32% Holstein-Friesian, 50% Holstein-Friesian–Jersey crossbred, and 8% Jersey, with the remainder being other breeds. Rearers and finishers repetitively and simultaneously interacted to determine the type and number of cattle populating the finishing system. Rearers brought in four-day-old spring-born calves and reared them until 60 calves (representing a full truck load) on average had a live weight of 100 kg before selling them on to finishers. Finishers mainly attained weaners from rearers, or directly from dairy farmers when weaner demand was higher than the supply from rearers. Fast-growing cattle were sent for slaughter before the second winter, and the re-mainder were sent before their third winter. The model finished a higher number of bulls than heifers and steers, although it was 4% lower than the industry reported value. Holstein-Friesian and Holstein-Friesian–Jersey-crossbred cattle dominated the dairy-origin beef finishing system. Jersey cattle account for less than 5% of total processed beef cattle. Further studies to include re-tailer and consumer perspectives and other decision alternatives for finishing farms would im-prove the applicability of the model for decision-making processes.

Keywords: agent-based modelling, dairy cattle, beef finishing, rearers, finishers

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Authors: Farshid Marbouti, Jale Ulas, Julia Thompson

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The main sources of stress among college students are: changes in sleeping and eating habits, undertaking new responsibilities, and financial difficulties as the most common sources of stress, exams, meeting new people, career decisions, fear of failure, and pressure from parents, transition to university especially if it requires leaving home, working with people that they do not know, trouble with parents, and relationship with the opposite sex. The students use a variety of stress coping strategies, including talking to family and friends, leisure activities and exercising. The Yerkes–Dodson law indicates while a moderate amount of stress may be beneficial for performance, too high stress will result in weak performance. In other words, if students are too stressed, they are likely to have low academic performance. In a preliminary study conducted in 2017 with engineering students enrolled in three high failure rate classes, the majority of the students stated that they have high levels of stress mainly for academic, financial, or family-related reasons. As the second stage of the study, the main purpose of this research is to investigate the students’ level of stress, sources of stress, their relationship with student demographic background, students’ coping strategies, and academic performance. A device is being developed to gather data from students breathing patterns and measure their stress levels. In addition, all participants are asked to fill out a survey. The survey under development has the following categories: exam stressor, study-related stressors, financial pressures, transition to university, family-related stress, student response to stress, and stress management. After the data collection, Structural Equation Modeling (SEM) analysis will be conducted in order to identify the relationship among students’ level of stress, coping strategies, and academic performance.

Keywords: college student stress, coping strategies, academic performance, measuring stress

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Authors: Xianping Du, Runlu Miao, Guanjun Zhang, Libo Cao, Feng Zhu

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Current vehicle safety standards and human body injury criteria were established based on the biomechanical response of Euro-American human body, without considering the difference in the body anthropometry and injury characteristics among different races, particularly the East Asian people with smaller body size. Absence of such race specific design considerations will negatively influence the protective performance of safety products for these populations, and weaken the accuracy of injury thresholds derived. To resolve these issues, in this study, we aim to develop a race specific finite element model to simulate the impact response of the lower extremity of a 50th percentile East Asian (Chinese) male. The model was built based on medical images for the leg of an average size Chinese male and slightly adjusted based on the statistical data. The model includes detailed anatomic features and is able to simulate the muscle active force. Thirteen biomechanical tests available in the literature were used to validate its biofidelity. Using the validated model, a pedestrian-car impact accident taking place in China was re-constructed computationally. The results show that the newly developed lower leg model has a good performance in predicting dynamic response and tibia fracture pattern. An additional comparison on the fracture tolerance of the East Asian and Euro-American lower limb suggests that the current injury criterion underestimates the degree of injury of East Asian human body.

Keywords: lower limb, East Asian body characteristics, traffic accident reconstruction, finite element analysis, injury tolerance

Procedia PDF Downloads 288

Authors: S. Wakim, M. Nemer, B. Zeghondy, B. Ghannam, C. Bouallou

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Designing the optimal heat exchanger is still an essential objective to be achieved. Parametrical optimization involves the evaluation of the heat exchanger dimensions to find those that best satisfy certain objectives. This method contributes to an enhanced design rather than an optimized one. On the contrary, topology optimization finds the optimal structure that satisfies the design objectives. The huge development in metal additive manufacturing allowed topology optimization to find its way into engineering applications especially in the aerospace field to optimize metal structures. Using topology optimization in 3d heat and mass transfer problems requires huge computational time, therefore coupling it with CFD simulations can reduce this it. However, existed CFD models cannot be coupled with topology optimization. The CFD model must allow creating a uniform mesh despite the initial geometry complexity and also to swap the cells from fluid to solid and vice versa. In this paper, a porous media approach compatible with topology optimization criteria is developed. It consists of modeling the fluid region of the heat exchanger as porous media having high porosity and similarly the solid region is modeled as porous media having low porosity. The switching from fluid to solid cells required by topology optimization is simply done by changing each cell porosity using a user defined function. This model is tested on a plate and fin heat exchanger and validated by comparing its results to experimental data and simulations results. Furthermore, this model is used to perform a material reallocation based on local criteria to optimize a plate and fin heat exchanger under a constant heat duty constraint. The optimized fin uses 20% fewer materials than the first while the pressure drop is reduced by about 13%.

Keywords: computational methods, finite element method, heat exchanger, porous media, topology optimization

Procedia PDF Downloads 154

Authors: Ashneel Ajay Singh, Kazumi Sakuramoto, Naoki Suzuki, Kalla Alok, Nath Paras

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Bluefin (Thunnus orientalis) tuna is one of the most economically valuable tuna species in the world. In recent years the stock has been observed to decline. It is suspected that the stock-recruitment relationship and population structure is influenced by environmental and climatic variables. This study was aimed at investigating the influence of environmental and climatic conditions on the trajectory of the different life stages of the North Pacific bluefin tuna. Exploratory analysis was performed for the North Pacific sea surface temperature (SST) and Pacific Decadal Oscillation (PDO) on the time series of the bluefin tuna cohorts (age-0, 1, 2,…,9, 10+). General Additive Modeling (GAM) was used to reconstruct the recruitment (R) trajectory. The spatial movement of the SST was also monitored from 1953 to 2012 in the distribution area of the bluefin tuna. Exploratory analysis showed significance influence of the North Pacific Sea Surface temperature (SST) and Pacific Decadal Oscillation (PDO) on the time series of the age-0 group. Other age group (1, 2,…,9, 10+) time series did not exhibit any significant correlations. PDO showed most significant relationship in the months of October to December. Although the stock-recruitment relationship is of biological significance, the recruits (age-0) showed poor correlation with the Spawning Stock Biomass (SSB). Indeed the most significant model incorporated the SSB, SST and PDO. The results show that the stock-recruitment relationship of the North Pacific bluefin tuna is multi-dimensional and cannot be adequately explained by the SSB alone. SST and PDO forcing of the population structure is of significant importance and needs to be accounted for when making harvesting plans for bluefin tuna in the North Pacific.

Keywords: pacific bluefin tuna, Thunnus orientalis, cohorts, recruitment, spawning stock biomass, sea surface temperature, pacific decadal oscillation, general additive model

Procedia PDF Downloads 236

Authors: Aymen Laadhari

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During the last decade, an increasing number of contributions have been made in the fields of scientific computing and numerical methodologies applied to the study of the hemodynamics in the heart. In contrast, the numerical aspects concerning the interaction of pulsatile blood flow with highly deformable thin leaflets have been much less explored. This coupled problem remains extremely challenging and numerical difficulties include e.g. the resolution of full Fluid-Structure Interaction problem with large deformations of extremely thin leaflets, substantial mesh deformations, high transvalvular pressure discontinuities, contact between leaflets. Although the Lagrangian description of the structural motion and strain measures is naturally used, many numerical complexities can arise when studying large deformations of thin structures. Eulerian approaches represent a promising alternative to readily model large deformations and handle contact issues. We present a fully Eulerian finite element methodology tailored for the simulation of pulsatile blood flow in the aorta and sinus of Valsalva interacting with highly deformable thin leaflets. Our method enables to use a fluid solver on a fixed mesh, whilst being able to easily model the mechanical properties of the valve. We introduce a semi-implicit time integration scheme based on a consistent NewtonRaphson linearization. A variant of the classical Newton method is introduced and guarantees a third-order convergence. High-fidelity computational geometries are built and simulations are performed under physiological conditions. We address in detail the main features of the proposed method, and we report several experiments with the aim of illustrating its accuracy and efficiency.

Keywords: eulerian, level set, newton, valve

Procedia PDF Downloads 278

Authors: Helen Pluut, Remus Ilies, Nikos Dimotakis, Maral Darouei

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This study aims to examine recovery from work as an important daily activity with implications for workplace behavior. Building on affective events theory and the stressor-detachment model as frameworks, this paper proposes and tests a comprehensive within-individual model that uncovers the role of recovery processes at home in linking workplace demands (e.g., workload) and stressors (e.g., workplace incivility) to next-day organizational citizenship behaviors (OCBs). Our sample consisted of 126 full-time employees in a large Midwestern University. For a period of 16 working days, these employees were asked to fill out 3 electronic surveys while at work. The first survey (sent out in the morning) measured self-reported sleep quality, recovery experiences the previous day at home, and momentary effect. The second survey (sent out close to the end of the workday) measured job demands and stressors as well as OCBs, while the third survey in the evening assessed job strain. Data were analyzed using Hierarchical Linear Modeling (HLM). Results indicated that job demands and stressors at work made it difficult to unwind properly at home and have a good night’s sleep, which had repercussions for next day’s morning effect, which, in turn, influenced OCBs. It can be concluded that processes of recovery are vital to an individual’s daily effective functioning and behavior at work, but recovery may become impaired after a hard day’s work. Thus, our study sheds light on the potentially persistent nature of strain experienced as a result of work and points to the importance of recovery processes to enable individuals to avoid such cross-day spillover. Our paper will discuss this implication for theory and practice as well as potential directions for future research.

Keywords: affect, job demands, organizational citizenship behavior, recovery, strain

Procedia PDF Downloads 139

Authors: Aihong Zhao, Priya Sastry, Mark L Field, Mohamad Bashir, Arvind Singh, David Richens

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Objectives: Intramural haematoma (IMH) is one of the pathologies, along with acute aortic dissection, that present as Acute Aortic Syndrome (AAS). Evidence suggests that unlike aortic dissection, some intramural haematomas may regress with medical management. However, intramural haematomas have been traditionally managed like acute aortic dissections. Given that some of these pathologies may regress with conservative management, it would be useful to be able to identify which of these may not need high risk emergency intervention. A computational aortic model was used in this study to try and identify intramural haematomas with risk of progression to aortic dissection. Methods: We created a computational model of the aorta with luminal blood flow. Reports in the literature have identified 11 mm as the radial clot thickness that is associated with heightened risk of progression of intramural haematoma. Accordingly, haematomas of varying sizes were implanted in the modeled aortic wall to test this hypothesis. The model was exposed to physiological blood flows and the stresses and strains in each layer of the aortic wall were recorded. Results: Size and shape of clot were seen to affect the magnitude of aortic stresses. The greatest stresses and strains were recorded in the intima of the model. When the haematoma exceeded 10 mm in all dimensions, the stress on the intima reached breaking point. Conclusion: Intramural clot size appears to be a contributory factor affecting aortic wall stress. Our computer simulation corroborates clinical evidence in the literature proposing that IMH diameter greater than 11 mm may be predictive of progression. This preliminary report suggests finite element modelling of the aortic wall may be a useful process by which to examine putative variables important in predicting progression or regression of intramural haematoma.

Keywords: intramural haematoma, acute aortic syndrome, finite element analysis,

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Authors: R. Hellmuth

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The method of factory planning has changed a lot, especially when it is about planning the factory building itself. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity and Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Furthermore, digital building models are increasingly being used in factories to support facility management and manufacturing processes. The main research question of this paper is, therefore: What kind of digital factory model is suitable for the different areas of application during the operation of a factory? First, different types of digital factory models are investigated, and their properties and usabilities for use cases are analysed. Within the scope of investigation are point cloud models, building information models, photogrammetry models, and these enriched with sensor data are examined. It is investigated which digital models allow a simple integration of sensor data and where the differences are. Subsequently, possible application areas of digital factory models are determined by means of a survey and the respective digital factory models are assigned to the application areas. Finally, an application case from maintenance is selected and implemented with the help of the appropriate digital factory model. It is shown how a completely digitalized maintenance process can be supported by a digital factory model by providing information. Among other purposes, the digital factory model is used for indoor navigation, information provision, and display of sensor data. In summary, the paper shows a structuring of digital factory models that concentrates on the geometric representation of a factory building and its technical facilities. A practical application case is shown and implemented. Thus, the systematic selection of digital factory models with the corresponding application cases is evaluated.

Keywords: building information modeling, digital factory model, factory planning, maintenance

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Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

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In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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Authors: H. Shokouhmand, M. Tajerian

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A numerical investigation of laminar forced convection flows through a square cross section micro heat pipe by applying electrohydrodynamic (EHD) field has been studied. In the present study, pentane is selected as working fluid. Temperature and velocity profiles and heat transfer enhancement in the micro heat pipe by using EHD field at the two-dimensional and single phase fluid flow in steady state regime have been numerically calculated. At this model, only Coulomb force is considered. The study has been carried out for the Reynolds number 10 to 100 and EHD force field up to 8 KV. Coupled, non-linear equations governed on the model (continuity, momentum, and energy equations) have been solved simultaneously by CFD numerical methods. Steady state behavior of affecting parameters, e.g. friction factor, average temperature, Nusselt number and heat transfer enhancement criteria, have been evaluated. It has been observed that by increasing Reynolds number, the effect of EHD force became more significant and for smaller Reynolds numbers the rate of heat transfer enhancement criteria is increased. By obtaining and plotting the mentioned parameters, it has been shown that the EHD field enhances the heat transfer process. The numerical results show that by increasing EHD force field the absolute value of Nusselt number and friction factor increases and average temperature of fluid flow decreases. But the increasing rate of Nusselt number is greater than increasing value of friction factor, which makes applying EHD force field for heat transfer enhancement in micro heat pipes acceptable and applicable. The numerical results of model are in good agreement with the experimental results available in the literature.

Keywords: micro heat pipe, electrohydrodynamic force, Nusselt number, average temperature, friction factor

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Authors: N. Umasuthan, S. D. N. K. Bathige, W. S. Thulasitha, I. Whang, J. Lee

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The MyD88 is an evolutionarily conserved host-expressed adaptor protein that is essential for proper TLR/ IL1R immune-response signaling. A previously identified complete cDNA (1626 bp) of OfMyD88 comprised an ORF of 867 bp encoding a protein of 288 amino acids (32.9 kDa). The gDNA (3761 bp) of OfMyD88 revealed a quinquepartite genome organization composed of 5 exons (with the sizes of 310, 132, 178, 92 and 155 bp) separated by 4 introns. All the introns displayed splice signals consistent with the consensus GT/AG rule. A bipartite domain structure with two domains namely death domain (24-103) coded by 1st exon, and TIR domain (151-288) coded by last 3 exons were identified through in silico analysis. Moreover, homology modeling of these two domains revealed a similar quaternary folding nature between human and rock bream homologs. A comprehensive comparison of vertebrate MyD88 genes showed that they possess a 5-exonic structure. In this structure, the last three exons were strongly conserved, and this suggests that a rigid structure has been maintained during vertebrate evolution. A cluster of TATA box-like sequences were found 0.25 kb upstream of cDNA starting position. In addition, putative 5'-flanking region of OfMyD88 was predicted to have TFBS implicated with TLR signaling, including copies of NFB1, APRF/ STAT3, Sp1, IRF1 and 2 and Stat1/2. Using qPCR technique, a ubiquitous mRNA expression was detected in liver and blood. Furthermore, a significantly up-regulated transcriptional expression of OfMyD88 was detected in head kidney (12-24 h; >2-fold), spleen (6 h; 1.5-fold), liver (3 h; 1.9-fold) and intestine (24 h; ~2-fold) post-Fla challenge. These data suggest a crucial role for MyD88 in antibacterial immunity of teleosts.

Keywords: MyD88, innate immunity, flagellin, genomic analysis

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Authors: Islam Abou El-Magd, Elham Ali, Moahmed Zakzouk, Nesreen Khairy, Naglaa Zanaty

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Maine environment and coastal zone are wealthy with natural resources that contribute to the local economy of Egypt. The Gulf of Suez and Red Sea area accommodates diverse human activities that contribute to the local economy, including oil exploration and production, touristic activities, export and import harbors, etc, however, it is always under the threat of pollution due to human interaction and activities. This research aimed at integrating in-situ measurements and remotely sensed data with hydrodynamic model to map and simulate the oil pollution. High-resolution satellite sensors including Sentinel 2 and Plantlab were functioned to trace the oil pollution. Spectral band ratio of band 4 (infrared) over band 3 (red) underpinned the mapping of the point source pollution from the oil industrial estates. This ratio is supporting the absorption windows detected in the hyperspectral profiles. ASD in-situ hyperspectral device was used to measure experimentally the oil pollution in the marine environment. The experiment used to measure water behavior in three cases a) clear water without oil, b) water covered with raw oil, and c) water after a while from throwing the raw oil. The spectral curve is clearly identified absorption windows for oil pollution, particularly at 600-700nm. MIKE 21 model was applied to simulate the dispersion of the oil contamination and create scenarios for crises management. The model requires precise data preparation of the bathymetry, tides, waves, atmospheric parameters, which partially obtained from online modeled data and other from historical in-situ stations. The simulation enabled to project the movement of the oil spill and could create a warning system for mitigation. Details of the research results will be described in the paper.

Keywords: oil pollution, remote sensing, modelling, Red Sea, Egypt

Procedia PDF Downloads 347

Authors: Mateus Silva Mendonça, Wender Pereira de Oliveira, Gabriel Heleno de Paula Araújo, Hiago Tenório Teixeira Santana Rocha, Augusto César Teixeira Malaquias, José Guilherme Coelho Baeta

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The stricter legislation and the greater demand of the population regard to gas emissions and their effects on the environment as well as on human health make the automotive industry reinforce research focused on reducing levels of contamination. This reduction can be achieved through the implementation of improvements in internal combustion engines in such a way that they promote the reduction of both specific fuel consumption and air pollutant emissions. These improvements can be obtained through numerical simulation, which is a technique that works together with experimental tests. The aim of this paper is to build, with support of the GT-Suite software, a one-dimensional model of a single-cylinder research engine to analyze the impact of the variation of swirl and tumble coefficients on the performance and on the air pollutant emissions of an engine. Initially, the discharge coefficient is calculated through the software Converge CFD 3D, given that it is an input parameter in GT-Power. Mesh sensitivity tests are made in 3D geometry built for this purpose, using the mass flow rate in the valve as a reference. In the one-dimensional simulation is adopted the non-predictive combustion model called Three Pressure Analysis (TPA) is, and then data such as mass trapped in cylinder, heat release rate, and accumulated released energy are calculated, aiming that the validation can be performed by comparing these data with those obtained experimentally. Finally, the swirl and tumble coefficients are introduced in their corresponding objects so that their influences can be observed when compared to the results obtained previously.

Keywords: 1D simulation, single-cylinder research engine, swirl coefficient, three pressure analysis, tumble coefficient

Procedia PDF Downloads 105

Authors: Pejman Salimi, Sebastiano Tieuli, Somayeh Taghavi, Michela Signoretto, Remo Proietti Zaccaria

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Increasing the growth of industrial waste due to the large quantities of production leads to numerous environmental and economic challenges, such as climate change, soil and water contamination, human disease, etc. Energy recovery of waste can be applied to produce heat or electricity. This strategy allows for the reduction of energy produced using coal or other fuels and directly reduces greenhouse gas emissions. Among different factories, leather manufacturing plays a very important role in the whole world from the socio-economic point of view. The leather industry plays a very important role in our society from a socio-economic point of view. Even though the leather industry uses a by-product from the meat industry as raw material, it is considered as an activity demanding integrated prevention and control of pollution. Along the entire process from raw skins/hides to finished leather, a huge amount of solid and water waste is generated. Solid wastes include fleshings, raw trimmings, shavings, buffing dust, etc. One of the most abundant solid wastes generated throughout leather tanning is shaving waste. Leather shaving is a mechanical process that aims at reducing the tanned skin to a specific thickness before tanning and finishing. This product consists mainly of collagen and tanning agent. At present, most of the world's leather processing is chrome-tanned based. Consequently, large amounts of chromium-containing shaving wastes need to be treated. The major concern about the management of this kind of solid waste is ascribed to chrome content, which makes the conventional disposal methods, such as landfilling and incineration, not practicable. Therefore, many efforts have been developed in recent decades to promote eco-friendly/alternative leather production and more effective waste management. Herein, shaving waste resulting from metal-free tanning technology is proposed as low-cost precursors for the preparation of carbon material as anodes for lithium-ion batteries (LIBs). In line with the philosophy of a reduced environmental impact, for preparing fully sustainable and environmentally friendly LIBs anodes, deionized water and carboxymethyl cellulose (CMC) have been used as alternatives to toxic/teratogen N-methyl-2- pyrrolidone (NMP) and to biologically hazardous Polyvinylidene fluoride (PVdF), respectively. Furthermore, going towards the reduced cost, we employed water solvent and fluoride-free bio-derived CMC binder (as an alternative to NMP and PVdF, respectively) together with LiFePO₄ (LFP) when a full cell was considered. These actions make closer to the 2030 goal of having green LIBs at 100 $ kW h⁻¹. Besides, the preparation of the water-based electrodes does not need a controlled environment and due to the higher vapour pressure of water in comparison with NMP, the water-based electrode drying is much faster. This aspect determines an important consequence, namely a reduced energy consumption for the electrode preparation. The electrode derived from leather waste demonstrated a discharge capacity of 735 mAh g⁻¹ after 1000 charge and discharge cycles at 0.5 A g⁻¹. This promising performance is ascribed to the synergistic effect of defects, interlayer spacing, heteroatoms-doped (N, O, and S), high specific surface area, and hierarchical micro/mesopore structure of the biochar. Interestingly, these features of activated biochars derived from the leather industry open the way for possible applications in other EESDs as well.

Keywords: biowaste, lithium-ion batteries, physical activation, waste management, leather industry

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Authors: Velly Anatasia

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In the last few decades extensive research has been conducted into information technology (IT) adoption, testing a series of factors considered to be essential for improved diffusion. Some studies analyze IT characteristics such as usefulness, ease of use and/or security, others focus on the emotions and experiences of users and a third group attempts to determine the importance of socioeconomic user characteristics such as gender, educational level and income. The situation is similar regarding e-commerce, where the majority of studies have taken for granted the importance of including these variables when studying e-commerce adoption, as these were believed to explain or forecast who buys or who will buy on the internet. Nowadays, the internet has become a marketplace suitable for all ages and incomes and both genders and thus the prejudices linked to the advisability of selling certain products should be revised. The objective of this study is to test whether the socioeconomic characteristics of experienced e-shoppers such as gender rally moderate the effect of their perceptions of online shopping behavior. Current development of the online environment and the experience acquired by individuals from previous e-purchases can attenuate or even nullify the effect of these characteristics. The individuals analyzed are experienced e-shoppers i.e. individuals who often make purchases on the internet. The Technology Acceptance Model (TAM) was broadened to include previous use of the internet and perceived self-efficacy. The perceptions and behavior of e-shoppers are based on their own experiences. The information obtained will be tested using questionnaires which were distributed and self-administered to respondent accustomed using internet. The causal model is estimated using structural equation modeling techniques (SEM), followed by tests of the moderating effect of socioeconomic variables on perceptions and online shopping behavior. The expected findings of this study indicated that gender moderate neither the influence of previous use of the internet nor the perceptions of e-commerce. In short, they do not condition the behavior of the experienced e-shopper.

Keywords: Internet shopping, age groups, gender, income, electronic commerce

Procedia PDF Downloads 336

Authors: Inga Badasyan

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Every year we do monitoring of water pollution of catchment basin of Debed River. Next, the Ministry of Nature Protection does modeling programme. Finely, we are managing the impact of water pollution in Debed river. Ecosystem technologies efficiency performance were estimated based on the physical, chemical, and macrobiological analyses of water on regular base between 2012 to 2015. Algae community composition was determined to assess the ecological status of Debed river, while vegetation was determined to assess biodiversity. Last time, experts werespeaking about global warming, which is having bad impact on the surface water, freshwater, etc. As, we know that global warming is caused by the current high levels of carbon dioxide in the water. Geochemical modelling is increasingly playing an important role in various areas of hydro sciences and earth sciences. Geochemical modelling of highly concentrated aqueous solutions represents an important topic in the study of many environments such as evaporation ponds, groundwater and soils in arid and semi-arid zones, costal aquifers, etc. The sampling time is important for benthic macroinvertebrates, for that reason we have chosen in the spring (abundant flow of the river, the beginning of the vegetation season) and autumn (the flow of river is scarce). The macroinvertebrates are good indicator for a chromic pollution and aquatic ecosystems. Results of our earlier investigations in the Debed river reservoirs clearly show that management problem of ecosystem reservoirs is topical. Research results can be applied to studies of monitoring water quality in the rivers and allow for rate changes and to predict possible future changes in the nature of the lake.

Keywords: ecohydrological monitoring, flood risk management, global warming, aquatic macroinvertebrates

Procedia PDF Downloads 288

Authors: Nima Safaei, Arezoo Masoud, Babak Safaei

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In recent years, there has been a growing emphasis on the role of urban planning in walking capability and the effects of individual and socioeconomic factors on the physical activity levels of city dwellers. Although considerable number of studies are conducted about walkability and for identifying the effective factors in walking mode choice in developed countries, to our best knowledge, literature lacks in the study of factors affecting choice of walking mode in developing countries. Due to the high importance of health aspects of human societies and in order to make insights and incentives for reducing traffic during rush hours, many researchers and policy makers in the field of transportation planning have devoted much attention to walkability studies; they have tried to improve the effective factors in the choice of walking mode in city neighborhoods. In this study, effective factors in walkability that have proven to have significant impact on the choice of walking mode, are studied at the same time in work trips. The data for the study is collected from the employees in their workplaces by well-instructed people using questionnaires; the statistical population of the study consists of 117 employed people who commute daily from work to home in Rasht city of Iran during the beginning of spring 2015. Results of the study which are found through the linear regression modeling, show that people who do not have freedom of choice for choosing their living locations and need to be present at their workplaces in certain hours have lower levels of walking. Additionally, unlike some of the previous studies which were conducted in developed countries, coincidental effects of Body Mass Index (BMI) and the income level of employees, do not have a significant effect on the walking level in work travels.

Keywords: BMI, linear regression, transportation, walking, work trips

Procedia PDF Downloads 196

Authors: Marilyn S. Painagan, Willie Jones B. Saliling

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This paper reports an optimized cropping calendar and land suitability for maize in North Cotabato derived from modeling crop productivity over time and space. Using Quantum GIS, eight representative soil types and 0.3o x 0.3o climate grids shapefiles were intersected to form thirty two pedoclimatic zones within the boundaries of the province. Surveys were done to ascertain crop performance and phenological properties on field. Based on these surveys, crop parameters were calibrated specific for a variety of maize. Soil properties and climatic data (daily precipitation, maximum and minimum temperatures) from pedoclimatic zones were loaded to the FAO Aquacrop Water Productivity Model along with the crop properties from field surveys to simulate yield from 1980 to 2010. The average yield per month was computed to come up with the month of planting having the highest and lowest probable yield in a year assuming that all lands were planted with maize. The yield attributes were visualized in the Quantum GIS environment. The study revealed that optimal cropping patterns varied across North Cotabato. Highest probable yield (8000 kg/ha) can be obtained when maize is planted on May and September (sandy clay-loam soils) in the northern part of the province while the lowest probable yield (1000 kg/ha) can be obtained when maize is planted on January, February and March (clay loam soils) at the northern part of the province. Yields are simulated on the basis of varieties currently planted by farmers of North Cotabato. The resulting maps suggest where and when maize is most suitable to achieve high yields. There is a need to ground truth and validate the cropping calendar on field.

Keywords: aquacrop, quantum GIS, maize, cropping calendar, water productivity

Procedia PDF Downloads 255

Authors: Yutong Xu, Wanting Zhang, Jia Wang, Zihan Guo, Weiguang Ma

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Background: The resilience education of intern nursing students has significant implications for the development and improvement of the nursing workforce. The clinical internship period is a critical time for enhancing resilience. Aims: To evaluate the resilience level of Chinese nursing interns and identify the factors affecting resilience early in their careers. Methods: The cross-sectional study design was adopted. From March 2022 to May 2023, 512 nursing interns in tertiary care hospitals were surveyed online with the Connor-Davidson Resilience Scale, the Clinical Learning Environment scale for Nurse, and the Career Adapt-Abilities Scale. Structural equation modeling was used to clarify the relationships among these factors. Indirect effects were tested using bootstrapped Confidence Intervals. Results: The nursing interns showed a moderately high level of resilience[M(SD)=70.15(19.90)]. Gender, scholastic attainment, had a scholarship, career adaptability and clinical learning environment were influencing factors of nursing interns’ resilience. Career adaptability and clinical learning environment positively and directly affected their resilience level (β = 0.58, 0.12, respectively, p＜0.01). career adaptability also positively affected career adaptability (β = 0.26, p < 0.01), and played a fully mediating role in the relationship between clinical learning environment and resilience. Conclusion: Career adaptability can enhance the influence of clinical learning environment on resilience. The promotion of career adaptability and the clinical teaching environment should be the potential strategies for nursing interns to improve their resilience, especially for those female nursing interns with low academic performance. Implications for Nursing Educators Nursing educators should pay attention to the cultivation of nursing students' resilience; for example, by helping them integrate to the clinical learning environment and improving their career adaptability. Reporting Method: The STROBE criteria were used to report the results of the observations critically. Patient or Public Contribution No patient or public contribution.

Keywords: resilience, clinical learning environment, career adaptability, nursing interns

Procedia PDF Downloads 89

Authors: Nicolas Bigot, M'hamed Boutaous, Nahiene Hamila, Shihe Xin

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Composite materials with polymer matrices are widely used in most industrial areas, particularly in aeronautical and automotive ones. Thanks to the development of a high-performance thermoplastic semicrystalline polymer matrix, those materials exhibit more and more efficient properties. The polymer matrix in composite materials can manifest a specific crystalline structure characteristic of crystallization in a fibrous medium. In order to guarantee a good mechanical behavior of structures and to optimize their performances, it is necessary to define realistic mechanical constitutive laws of such materials considering their physical structure. The interaction between fibers and matrix is a key factor in the mechanical behavior of composite materials. Transcrystallization phenomena which develops in the matrix around the fibers constitute the interphase which greatly affects and governs the nature of the fiber-matrix interaction. Hence, it becomes fundamental to quantify its impact on the thermo-mechanical behavior of composites material in relationship with processing conditions. In this work, we propose a numerical model coupling the thermal and crystallization kinetics in long fiber-based composite materials, considering both the spherulitic and transcrystalline types of the induced structures. After validation of the model with comparison to results from the literature and noticing a good correlation, a parametric study has been led on the effects of the thermal kinetics, the fibers volume fractions, the deformation, and the pressure on the crystallization rate in the material, under processing conditions. The ratio of the transcrystallinity is highlighted and analyzed with regard to the thermal kinetics and gradients in the material. Experimental results on the process are foreseen and pave the way to establish a mechanical constitutive law describing, with the introduction of the role on the crystallization rates and types on the thermo-mechanical behavior of composites materials.

Keywords: composite materials, crystallization, heat transfer, modeling, transcrystallization

Procedia PDF Downloads 192

Authors: C. K. Ngaw

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Crystal facet engineering, which involves tuning and controlling a crystal surface and morphology, is a commonly employed strategy to optimize the performance of crystalline nanocrystals. The principle behind this strategy is that surface atomic rearrangement and coordination, which inherently determines their catalytic activity, can be easily tuned by morphological control. Because of this, the catalytic properties of a nanocrystal are closely related to the surface of an exposed facet, and it has provided great motivation for researchers to synthesize photocatalysts with high catalytic activity by maximizing reactive facets exposed through morphological control. In this contribution, octahedral NaInS₂ crystals have been successfully developed via solvothermal method. The formation of the octahedral NaInS₂ crystals was investigated using field emission scanning electron microscope (FESEM) and X-Ray diffraction (XRD), and results have shown that the concentration of sulphur precursor plays an important role in the growth process, leading to the formation of other NaInS₂ crystal structures in the form of hexagonal nanosheets and microspheres. Structural modeling analysis suggests that the octahedral NaInS₂ crystals were enclosed with {012} and {001} facets, while the nanosheets and microspheres are bounded with {001} facets only and without any specific facets, respectively. Visible-light photocatalytic H₂ evolution results revealed that the octahedral NaInS₂ crystals (~67 μmol/g/hr) exhibit ~6.1 and ~2.3 times enhancement as compared to the conventional NaInS₂ microspheres (~11 μmol/g/hr) and nanosheets (~29 μmol/g/hr), respectively. The H₂ enhancement of the NaInS₂ octahedral crystal is attributed to the presence of {012} facets on the surface. Detailed analysis of the octahedron model revealed obvious differences in the atomic arrangement between the {001} and {012} facets and this can affect the interaction between the water molecules and the surface facets before reducing into H₂ gas. These results highlight the importance of tailoring crystal morphology with highly reactive facets in improving photocatalytic properties.

Keywords: H₂ evolution, photocatalysis, octahedral, reactive facets

Procedia PDF Downloads 66

Authors: Shulamit Sternin

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Athletes experience injuries that can have both a physical and psychological impact on the individual. In such instances, athletes are able to rely on the established field of sports psychology to facilitate holistic rehabilitation. Musicians, like athletes rely on their bodies to perform in much the same way athletes do and are also susceptible to injury. Due to the similar performative nature of succeeding as an athletes or a musician, these careers share many of the same primary psychological concerns and therefore it is reasonable that athletes and musicians may require similar rehabilitation post-injury. However, musicians face their own unique psychological challenges and understanding the needs of an injured athlete can serve as a foundation for understanding the injured musician but is not enough to fully rehabilitate an injured musician. The current research surrounding musicians and their injuries is primarily focused on physiological aspects of injury and rehabilitation; the psychological aspects have not yet received adequate attention resulting in poor musician rehabilitation post- injury. This review paper uses current models of psychological response to injury in athletes to draw parallels with the psychological response to injury in musicians. Search engines such as Medline and PsycInfo were systematically searched using specific key words, such as psychological response, injury, athlete, and musician. Studies that focused on post-injury psychology of either the musician or the athlete were included. Within the literature there is evidence to support psychological responses, unique to the musician, that are not accounted for by current models of response in athletes. The models of psychological response to injury in athletes are inadequate tools for application to the musician. Future directions for performance arts research that can fill the gaps in our understanding and modeling of musicians’ response to injury are discussed. A better understanding of the psychological impact of injuries on musicians holds significant implications for health care practitioners working with injured musicians. Understanding the unique barriers musicians face post-injury, and how support for this population must be tailored to properly suit musicians’ needs will aid in more holistic rehabilitation and a higher likelihood of musician’s returning to pre-injury performance levels.

Keywords: athlete, injury, musician, psychological response

Procedia PDF Downloads 205

Authors: Shivahari Revathi Venkateswaran

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Segmenting customers plays a significant role in churn prediction. It helps the marketing team with proactive and reactive customer retention. For the reactive retention, the retention team reaches out to customers who already showed intent to disconnect by giving some special offers. When coming to proactive retention, the marketing team uses churn prediction model, which ranks each customer from rank 1 to 100, where 1 being more risk to churn/disconnect (high ranks have high propensity to churn). The churn prediction model is built by using XGBoost model. However, with the churn rank, the marketing team can only reach out to the customers based on their individual ranks. To profile different groups of customers and to frame different marketing strategies for targeted groups of customers are not possible with the churn ranks. For this, the customers must be grouped in different segments based on their profiles, like demographics and other non-controllable attributes. This helps the marketing team to frame different offer groups for the targeted audience and prevent them from disconnecting (proactive retention). For segmentation, machine learning approaches like k-mean clustering will not form unique customer segments that have customers with same attributes. This paper finds an alternate approach to find all the combination of unique segments that can be formed from the user attributes and then finds the segments who have uplift (churn rate higher than the baseline churn rate). For this, search algorithms like fast search and recursive search are used. Further, for each segment, all customers can be targeted using individual churn ranks from the churn prediction model. Finally, a UI (User Interface) is developed for the marketing team to interactively search for the meaningful segments that are formed and target the right set of audience for future marketing campaigns and prevent them from disconnecting.

Keywords: churn prediction modeling, XGBoost model, uplift segments, proactive marketing, search algorithms, retention, k-mean clustering

Procedia PDF Downloads 71