Search results for: saturated modeling

Authors: Mohammad Moridzadeh, Mohammad Djavid, Barry Doyle

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An assessment of the long-term stability of a cavern in Chagrin shale excavated by the sequential excavation method was performed during and after construction. During the excavation of the cavern, deformations of rock mass were measured at the surface of excavation and within the rock mass by surface and deep measurement instruments. Rock deformations were measured during construction which appeared to result from the as-built excavation sequence that had potentially disturbed the rock and its behavior. Also some additional time dependent rock deformations were observed during and post excavation. Several opinions have been expressed to explain this time dependent deformation including stress changes induced by excavation, strain softening (or creep) in the beddings with and without clay and creep of the shaley rock under compressive stresses. In order to analyze and replicate rock behavior observed during excavation, including current and post excavation elastic, plastic, and time dependent deformation, Finite Element Analysis (FEA) was performed. The analysis was also intended to estimate long term deformation of the rock mass around the excavation. Rock mass behavior including time dependent deformation was measured by means of rock surface convergence points, MPBXs, extended creep testing on the long anchors, and load history data from load cells attached to several long anchors. Direct creep testing of Chagrin Shale was performed on core samples from the wall of the Pump Room. Results of these measurements were used to calibrate the FEA of the excavation. These analyses incorporate time dependent constitutive modeling for the rock to evaluate the potential long term movement in the roof, walls, and invert of the cavern. The modeling was performed due to the concerns regarding the unanticipated behavior of the rock mass as well as the forecast of long term deformation and stability of rock around the excavation.

Keywords: Cavern, Chagrin shale, creep, finite element.

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Authors: Rahim Jafari, Tuba Okutucu-Özyurt

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The hydrodynamics and heat transfer characteristics of a vaporized elongated bubble in a rectangular microchannel have been simulated based on Cahn-Hilliard phase-field method. In the simulations, the initially nucleated bubble starts growing as it comes in contact with superheated water. The growing shape of the bubble compared with the available experimental data in the literature.

Keywords: microchannel, boiling, Cahn-Hilliard method, simulation

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Authors: El Montassir Dahmane, Nadia Eladlani, Aziz Ouahrouch, Mohammed Rhazi, Moha Taourirte

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The present study was aimed to approximate the optimal conditions to chromium recovery from wastewater by nanoparticles and whiskers of chitosan. Chitosan with an average molecular weight of 63 kDa and a 96% deacetylation degree was prepared according to our previous study. Chromium recovery is influenced by different parameters. In our search, we determined the appropriate range of pH to form chitosan–Cr(III), nanoparticles Cr(III), and whiskers– Cr(III) complex. We studied also the influence of chromium concentration and the nature of chitosan-based materials on the complexation process. Our main aim is to approximate the optimal conditions to remove chromium(III) from the tanning bath, recuperated from tannery wastewater of Marrakech in Morocco. A Perkin Elmer optima 2000 Inductively Coupled Plasma- Optical Emission Spectrometer (ICP-OES), was used to determine the quantity of chromium persistent in tannery wastewater after complexation phenomenon. To the best of our knowledge, this is the first report interested in the optimal conditions for chromium recovery from wastewater by nanoparticles and whiskers of chitosan. From our research, we found that in chromium solution, the appropriate range of pH to form complex is between 5.6 and 6.7. Also, the complexation of Cr(III) is depending on the nature of complexing ligand and chromium concentration. The obtained results reveal that nanoparticles present an excellent adsorption capacity regardless of chromium concentration. In addition, after a critical chromium concentration (250 mg/l), our ligand becomes saturated, that requires an increase of ligand mass for increasing chromium concentration in order to have a better adsorption capacity. Hence, in the same conditions, we used chitosan, its nanoparticles, whiskers, and chitosan based films to remove Cr(III) from tannery wastewater. The pH of this effluent was around 6, and its chromium concentration was 300 mg/l. The results expose that the sequence of complexing ligand in the effluent is the same in chromium solution, determined via our previous study. However, the adsorbed quantity is less due to the presence of other metallic ions in tannery wastewater. We conclude that the best complexing ligand-based chitosan is chitosan nanoaprticles whether it’s in chromium solution or in tannery wastewater. Nanoparticles are the best complexing ligand after 24 h of contact nanoparticles can remove 70% of chromium from this tannery wastewater.

Keywords: nanoparticles, whiskers, chitosan, chromium

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Authors: M. Alkhalidi, S. Neelamani, Z. Al-Zaqah

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This paper investigates the interaction of single and twin offshore rubble mound breakwaters with regular and random water waves through physical modeling to assess their reflection, transmission and energy dissipation characteristics. Various combinations of wave heights and wave periods were utilized in a series of experiments, along with three different water depths. The single and twin permeable breakwater models were both constructed with one layer of rubbles. Both models had the same total volume; however, the single breakwater was of trapezoidal type while the twin breakwaters were of triangular type. Physical modeling experiments were carried out in the wave flume of the coastal engineering laboratory of Kuwait Institute for Scientific Research (KISR). Measurements of the six wave probes which were fixed in the two-dimensional wave flume were collected and used to determine the generated incident wave heights, as well as the reflected and transmitted wave heights resulting from the wave-breakwater interaction. The possible factors affecting the wave attenuation efficiency of the breakwater models are the relative water depth (d/L), wave steepness (H/L), relative wave height ((h-d)/Hi), relative height of the breakwater (h/d), and relative clear spacing between the twin breakwaters (S/h). The results indicated that the single and double breakwaters show different responds to the change in their relative height as well as the relative wave height which demonstrates that the effect of the relative water depth on wave reflection, transmission, and energy dissipation is highly influenced by the change in the relative breakwater height, the relative wave height and the relative breakwater spacing. In general, within the range of the relative water depth tested in this study, and under both regular and random waves, it is found that the single breakwater allows for lower wave transmission and shows higher energy dissipation effect than both of the tested twin breakwaters, and hence has the best overall performance.

Keywords: random waves, regular waves, relative water depth, relative wave height, single breakwater, twin breakwater, wave steepness

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Authors: C. Patrascioiu, V. Matei, N. Nicolae

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The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.

Keywords: hydrofining, kinetic, modeling, optimization

Procedia PDF Downloads 438

Authors: Thomas Wetere

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Background: The coronavirus disease 2019 (COVID-19) pandemic (COVID-19) virus infection is a severe infectious disease with the highly transmissible variant, which become the global public health treat now. It has taken the life of more than 4 million people so far. What makes the disease the worst of all is no specific effective treatment available, its dynamics is not much researched and understood. Methodology: To end the global COVID-19 pandemic, implementation of multiple population-wide strategies, including vaccination, environmental factors, Government action, testing, and contact tracing, is required. In this article, a new mathematical model incorporating both temperature and government action to study the dynamics of the COVID-19 pandemic has been developed and comprehensively analysed. The model considers eight stages of infection: susceptible (S), infected Asymptomatic and Undetected(IAU ), infected Asymptomatic and detected(IAD), infected symptomatic and Undetected(ISU ), infected Symptomatic and detected(ISD), Hospitalized or threatened(H), Recovered(R) and Died(D). Results: The existence as well as non-negativity of the solution to the model is also verified, and the basic reproduction number is calculated. Besides, stability conditions are also checked, and finally, simulation results are compared with real data. The results demonstrates that effective government action will need to be combined with vaccination to end the ongoing COVID-19 pandemic. Conclusion: Vaccination and Government action are highly the crucial measures to control the COVID-19 pandemic. Besides, as the cost of vaccination might be high, we recommend an optimal control to reduce the cost and number of infected individuals. Moreover, in order to prevent COVID-19 pandemic, through the analysis of the model, the government must strictly manage the policy on COVID-19 and carry it out. This, in turn, helps for health campaigning and raising health literacy which plays a role to control the quick spread of the disease. We finally strongly believe that our study will play its own role in the current effort of controlling the pandemic.

Keywords: modeling, COVID-19, MCMC, stability

Procedia PDF Downloads 114

Authors: J. X. Dong, C. J. An, Z. Chen, E. H. Owens, M. C. Boufadel, E. Taylor, K. Lee

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Shorelines are vulnerable to significant environmental impacts from oil spills. Stranded oil can cause potential short- to long-term detrimental effects along beaches that include injuries to the ecosystem, socio-economic and cultural resources. In this study, a three-dimensional (3D) numerical modeling approach is developed to evaluate the fate and transport of spilled oil for hypothetical oiled shoreline cases under various combinations of beach geomorphology and environmental conditions. The developed model estimates the spatial and temporal distribution of spilled oil for the various test conditions, using the finite volume method and considering the physical transport (dispersion and advection), sinks, and sorption processes. The model includes a user-friendly interface for data input on variables such as beach properties, environmental conditions, and physical-chemical properties of spilled oil. An experimental mesoscale tank design was used to test the developed model for dissolved petroleum hydrocarbon within shorelines. The simulated results for effects of different sediment substrates, oil types, and shoreline features for the transport of spilled oil are comparable to those obtained with a commercially available model. Results show that the properties of substrates and the oil removal by shoreline effects have significant impacts on oil transport in the beach area. Sensitivity analysis, through the application of the one-step-at-a-time method (OAT), for the 3D model identified hydraulic conductivity as the most sensitive parameter. The 3D numerical model allows users to examine the behavior of oil on and within beaches, assess potential environmental impacts, and provide technical support for decisions related to shoreline clean-up operations.

Keywords: dissolved petroleum hydrocarbons, environmental multimedia model, finite volume method, sensitivity analysis, total petroleum hydrocarbons

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Authors: Mohammadreza Sedighi, Mohammad Said Saidi, Hesamoddin Salarian

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A numerical study has been performed to investigate the effect of using different turbulent models on natural convection flow field and temperature distributions in partially heated square cavity compare to benchmark. The temperature of the right vertical wall is lower than that of heater while other walls are insulated. The commercial CFD codes are used to model. Standard k-w model provided good agreement with the experimental data.

Keywords: Buoyancy, Cavity, CFD, Heat Transfer, Natural Convection, Turbulence

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Authors: Redhouane Ghernaout, Amira Fredj, Boualem Remini

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Suspended sediment transport is a serious problem worldwide, but it is much more worrying in certain regions of the world, as is the case in the Maghreb and more particularly in Algeria. It continues to take disturbing proportions in Northern Algeria due to the variability of rains in time and in space and constant deterioration of vegetation. Its prediction is essential in order to identify its intensity and define the necessary actions for its reduction. The purpose of this study is to analyze the concentration data of suspended sediment measured at Wadi El-Abtal Hydrometric Station. It also aims to find and highlight regressive power relationships, which can explain the suspended solid flow by the measured liquid flow. The study strives to find models of artificial neural networks linking the flow, month and precipitation parameters with solid flow. The obtained results show that the power function of the solid transport rating curve and the models of artificial neural networks are appropriate methods for analysing and estimating suspended sediment transport in Wadi Mina at Wadi El-Abtal Hydrometric Station. They made it possible to identify in a fairly conclusive manner the model of neural networks with four input parameters: the liquid flow Q, the month and the daily precipitation measured at the representative stations (Frenda 013002 and Ain El-Hadid 013004 ) of the watershed. The model thus obtained makes it possible to estimate the daily solid flows (interpolate and extrapolate) even beyond the period of observation of solid flows (1985/86 to 1999/00), given the availability of the average daily liquid flows and daily precipitation since 1953/1954.

Keywords: suspended sediment, concentration, regression, liquid flow, solid flow, artificial neural network, modeling, mina, algeria

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Authors: Guillaume Richard, Sarra Zaied

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Marine waste quantities increase more and more, 5 million tons of plastic waste enter the ocean every year. Their spatiotemporal distribution is never homogeneous and depends mainly on the hydrodynamic characteristics of the environment, as well as the size and location of the waste. As part of optimizing collect of marine plastic wastes, it is important to measure and monitor their evolution over time. In this context, diverse studies have been dedicated to describing waste behavior in order to identify its accumulation in ocean areas. None of the existing tools which track objects at sea had the objective of tracking down a slick of waste. Moreover, the applications related to marine waste are in the minority compared to rescue applications or oil slicks tracking applications. These approaches are able to accurately simulate an object's behavior over time but not during the collection mission of a waste sheet. This paper presents numerical modeling of a boat’s wake impact on the floating marine waste behavior during a collection mission. The aim is to predict the trajectory of a marine waste slick to optimize its collection using meteorological data of ocean currents, wind, and possibly waves. We have made the choice to use Ocean Parcels which is a Python library suitable for trajectoring particles in the ocean. The modeling results showed the important role of advection and diffusion processes in the spatiotemporal distribution of floating plastic litter. The performance of the proposed method was evaluated on real data collected from the Copernicus Marine Environment Monitoring Service (CMEMS). The results of the evaluation in Cape of Good Hope (South Africa) prove that the proposed approach can effectively predict the position and velocity of marine litter during collection, which allowed for optimizing time and more than $90\%$ of the amount of collected waste.

Keywords: marine litter, advection-diffusion equation, sea current, numerical model

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Authors: Emna Hlel, Salma Jamousi, Abdelmajid Ben Hamadou

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Every model for knowledge representation to model real-world applications must be able to cope with the effects of uncertain phenomena. One of main defects of classical ontology is its inability to represent and reason with uncertainty. To remedy this defect, we try to propose a method to construct probabilistic ontology for integrating uncertain information in an ontology modeling a set of basic publications DBLP (Digital Bibliography & Library Project) using a probabilistic model.

Keywords: classical ontology, probabilistic ontology, uncertainty, Bayesian network

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Authors: Carolina Payares-Asprino

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Dual-phase duplex stainless steel comprised of ferrite and austenite has shown high strength and corrosion resistance in many aggressive environments. Joining duplex alloys is challenging due to several embrittling precipitates and metallurgical changes during the welding process. The welding parameters strongly influence the quality of a weld joint. Therefore, it is necessary to quantify the weld bead’s integral properties as a function of welding parameters, especially when part of the weld bead is removed through a machining process due to aesthetic reasons or to couple the elements in the in-service structure. The present study uses the existing stress-strain model to predict the stress-strain curves for duplex stainless-steel welds under different welding conditions. Having mathematical expressions that predict the shape of the stress-strain curve is advantageous since it reduces the experimental work in obtaining the tensile test. In analysis and design, such stress-strain modeling simplifies the time of operations by being integrated into calculation tools, such as the finite element program codes. The elastic zone and the plastic zone of the curve can be defined by specific parameters, generating expressions that simulate the curve with great precision. There are empirical equations that describe the stress-strain curves. However, they only refer to the stress-strain curve for the stainless steel, but not when the material is under the welding process. It is a significant contribution to the applications of duplex stainless steel welds. For this study, a 3x3 matrix with a low, medium, and high level for each of the welding parameters were applied, giving a total of 27 weld bead plates. Two tensile specimens were manufactured from each welded plate, resulting in 54 tensile specimens for testing. When evaluating the four models used to predict the stress-strain curve in the welded specimens, only one model (Rasmussen) presented a good correlation in predicting the strain stress curve.

Keywords: duplex stainless steels, modeling, stress-stress curve, tensile test, welding

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Authors: Mohand Kessal, Rachid Boucetta, Mourad Tikobaini, Mohammed Zamoum

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Leakage problem of two-component fluids flow is modeled for a transient one-dimensional homogeneous bubbly flow and developed by taking into account the effect of a leak located at the middle point of the pipeline. The corresponding three conservation equations are numerically resolved by an improved characteristic method. The obtained results are explained and commented in terms of physical impact on the flow parameters.

Keywords: fluid transients, pipelines leaks, method of characteristics, leakage problem

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Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

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Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

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Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

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Authors: Marc Sango, Olimpia Hoinaru, Christophe Gransart, Laurence Duchien

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Ontologies offer a means for representing and sharing information in many domains, particularly in complex domains. For example, it can be used for representing and sharing information of System Requirement Specification (SRS) of complex systems like the SRS of ERTMS/ETCS written in natural language. Since this system is a real-time and critical system, generic ontologies, such as OWL and generic ERTMS ontologies provide minimal support for modeling temporal information omnipresent in these SRS documents. To support the modeling of temporal information, one of the challenges is to enable representation of dynamic features evolving in time within a generic ontology with a minimal redesign of it. The separation of temporal information from other information can help to predict system runtime operation and to properly design and implement them. In addition, it is helpful to provide a reasoning and querying techniques to reason and query temporal information represented in the ontology in order to detect potential temporal inconsistencies. Indeed, a user operation, such as adding a new constraint on existing planning constraints can cause temporal inconsistencies, which can lead to system failures. To address this challenge, we propose a lightweight 3-layer temporal Quality of Service (QoS) ontology for representing, reasoning and querying over temporal and non-temporal information in a complex domain ontology. Representing QoS entities in separated layers can clarify the distinction between the non QoS entities and the QoS entities in an ontology. The upper generic layer of the proposed ontology provides an intuitive knowledge of domain components, specially ERTMS/ETCS components. The separation of the intermediate QoS layer from the lower QoS layer allows us to focus on specific QoS Characteristics, such as temporal or integrity characteristics. In this paper, we focus on temporal information that can be used to predict system runtime operation. To evaluate our approach, an example of the proposed domain ontology for handover operation, as well as a reasoning rule over temporal relations in this domain-specific ontology, are given.

Keywords: system requirement specification, ERTMS/ETCS, temporal ontologies, domain ontologies

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Authors: Danilo Di Donato

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The continuous new releases of free and open source software (FOSS) and the high costs of proprietary software -whose monopoly is characterized by closed codes and the low level of implementation and customization of software by end-users- impose a reflection on possible tools that can be chosen and adopted for the design and the representation of new steel constructions. The paper aims to show experimentation carried out to verify the actual potential and the effective applicability of FOSS supports to the BIM modeling of steel structures, particularly considering the goal of a possible workflow in order to achieve high level of development (LOD); allow effective interchange methods between different software. To this end, the examined software packages are those with open source or freeware licenses, in order to evaluate their use in architectural praxis. The test has primarily involved the experimentation of Freecad -the only Open Source software that allows a complete and integrated BIM workflow- and then the results have been compared with those of two proprietary software, Sketchup and TeklaBim Sight, which are released with a free version, but not usable for commercial purposes. The experiments carried out on Open Source, and freeware software was then compared with the outcomes that are obtained by two proprietary software, Sketchup Pro and Tekla Structure which has special modules particularly addressed to the design of steel structures. This evaluation has concerned different comparative criteria, that have been defined on the basis of categories related to the reliability, the efficiency, the potentiality, achievable LOD and user-friendliness of the analyzed software packages. In order to verify the actual outcomes of FOSS BIM for the steel structure projects, these results have been compared with a simulation related to a real case study and carried out with a proprietary software BIM modeling. Therefore, the same design theme, the project of a shelter of public space, has been developed using different software. Therefore the purpose of the contribution is to assess what are the developments and potentialities inherent in FOSS BIM, in order to estimate their effective applicability to professional practice, their limits and new fields of research they propose.

Keywords: BIM, steel buildings, FOSS, LOD

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Authors: N. Santatriniaina, J. Deseure, T. Q. Nguyen, H. Fontaine, C. Beitia, L. Rakotomanana

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Nowadays, with the increasing of the wafer's size and the decreasing of critical size of integrated circuit manufacturing in modern high-tech, microelectronics industry needs a maximum attention to challenge the contamination control. The move to 300 mm is accompanied by the use of Front Opening Unified Pods for wafer and his storage. In these pods an airborne cross contamination may occur between wafers and the pods. A predictive approach using modeling and computational methods is very powerful method to understand and qualify the AMCs cross contamination processes. This work investigates the required numerical tools which are employed in order to study the AMCs cross-contamination transfer phenomena between wafers and FOUPs. Numerical optimization and finite element formulation in transient analysis were established. Analytical solution of one dimensional problem was developed and the calibration process of physical constants was performed. The least square distance between the model (analytical 1D solution) and the experimental data are minimized. The behavior of the AMCs intransient analysis was determined. The model framework preserves the classical forms of the diffusion and convection-diffusion equations and yields to consistent form of the Fick's law. The adsorption process and the surface roughness effect were also traduced as a boundary condition using the switch condition Dirichlet to Neumann and the interface condition. The methodology is applied, first using the optimization methods with analytical solution to define physical constants, and second using finite element method including adsorption kinetic and the switch of Dirichlet to Neumann condition.

Keywords: AMCs, FOUP, cross-contamination, adsorption, diffusion, numerical analysis, wafers, Dirichlet to Neumann, finite elements methods, Fick’s law, optimization

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Authors: Laura Álvarez Antón, Joaquín Díaz

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The construction industry is turning towards sustainability. It is a well-known fact that sustainability is based on a balance between environmental, social and economic aspects. In order to achieve sustainability efficiently, these three criteria should be taken into account in the initial project phases, since that is when a project can be influenced most effectively. Thus the aim must be to integrate important tools like BIM and LCA at an early stage in order to make full use of their potential. With the synergies resulting from the integration of BIM and LCA, a wider approach to sustainability becomes possible, covering the three pillars of sustainability.

Keywords: building information modeling (BIM), construction industry, design phase, life cycle assessment (LCA), sustainability

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Authors: Mohsen Adabi, Mahdi Adabi, Reza Saber

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The recent advancements in nanomaterials have provided a platform to develop efficient transduction matrices for sensors. Modified electrodes allow to electrochemists to enhance the property of electrode surface and provide desired properties such as improved sensing capabilities, higher electron transfer rate and prevention of undesirable reactions competing kinetically with desired electrode process. Nanostructured electrodes including arrays of carbon nanotubes have demonstrated great potential for the development of electrochemical sensors and biosensors. The aim of this work is to evaluate the concentration of multi-walled carbon nanotubes (MWCNTs) on the conductivity of gold electrode. For this work, raw MWCNTs was functionalized and shortened. Raw and shorten MWCNTs were characterized using transfer electron microscopy (TEM). Next, 0.5, 2 and 3.5 mg of Shortened and functionalized MWCNTs were dispersed in 2 mL Dimethyl formamide (DMF) and cysteamine modified gold electrodes were incubated in the different concentrations of MWCNTs for 8 hours. Then, the immobilization of MWCNTs on cysteamine modified gold electrode was characterized by scanning electron microscopy (SEM) and the effect of MWCNT concentrations on electron transfer of modified electrodes was investigated by cyclic voltammetry (CV). The results demonstrated that CV response of ferricyanide redox at modified gold electrodes increased as concentration of MWCNTs enhanced from 0.5 to 2 mg in 2 mL DMF. This increase can be attributed to the number of MWCNTs which enhance on the surface of cysteamine modified gold electrode as the MWCNTs concentration increased whereas CV response of ferricyanide redox at modified gold electrodes did not changed significantly as the MWCNTs concentration increased from 2 to 3.5 mg in 2 mL DMF. The reason may be that amine groups of cysteamine modified gold electrodes are limited to a given number which can interact with the given number of carboxylic groups of MWCNTs and CV response of ferricyanide redox at modified gold do not enhance after amine groups of cysteamine are saturated with carboxylic groups of MWCNTs.

Keywords: carbon nanotube, cysteamine, electrochemical sensor, gold electrode

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Authors: Jean-Jacques Randrianarimanana, Nassim Sebaibi, Mohamed Boutouil

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In order to solve problems associated with stormwater runoff in urban areas and their effects on natural and artificial water bodies, the integration of new technical solutions to the rainwater drainage becomes even more essential. Permeable pavement systems are one of the most widely used techniques. This paper presents a laboratory analysis of stormwater runoff hydraulic and pollutant removal performance of permeable pavement system using pervious pavements based on seashell products. The laboratory prototype is a square column of 25 cm of side and consists of the surface in pervious concrete, a bedding of 3 cm in height, a geotextile and a subbase layer of 50 cm in height. A series of constant simulated rain events using semi-synthetic runoff which varied in intensity and duration were carried out. The initial vertical saturated hydraulic conductivity of the entire pervious pavement system was 0.25 cm/s (148 L/m²/min). The hydraulic functioning was influenced by both the inlet flow rate value and the test duration. The total water losses including evaporation ranged between 9% to 20% for all hydraulic experiments. The temporal and vertical variability of the pollutant removal efficiency (PRE) of the system were studied for total suspended solids (TSS). The results showed that the PRE along the vertical profile was influenced by the size of the suspended solids, and the pervious paver has the highest capacity to trap pollutant than the other porous layers of the permeable pavement system after the geotextile. The TSS removal efficiency was about 80% for the entire system. The first-flush effect of TSS was observed, but it appeared only at the beginning (2 to 6 min) of the experiments. It has been shown that the PPS can capture first-flush. The project in which this study is integrated aims to contribute to both the valorization of shellfish waste and the sustainable management of rainwater.

Keywords: hydraulic, pervious concrete, pollutant removal efficiency, seashell by-products, stormwater runoff

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Authors: H. M. Zakir Hossain

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Cenozoic mudstone samples, obtained from drilled cored and outcrop in northeastern Bengal Basin of Bangladesh were organic geochemically analyzed to identify vertical variations of organic facies, thermal maturity, hydrocarbon potential and depositional environments. Total organic carbon (TOC) content ranges from 0.11 to 1.56 wt% with an average of 0.43 wt%, indicating a good source rock potential. Total sulphur content is variable with values ranging from ~0.001 to 1.75 wt% with an average of 0.065 wt%. Rock-Eval S1 and S2 yields range from 0.03 to 0.14 mg HC/g rock and 0.01 to 0.66 mg HC/g rock, respectively. The hydrogen index values range from 2.71 to 56.09 mg HC/g TOC. These results revealed that the samples are dominated by type III kerogene. Tmax values of 426 to 453 °C and vitrinite reflectance of 0.51 to 0.66% indicate the organic matter is immature to mature. Saturated hydrocarbon ratios such as pristane, phytane, steranes, and hopanes, indicate mostly terrigenous organic matter with small influence of marine organic matter. Organic matter in the succession was accumulated in three different environmental conditions based on the integration of biomarker proxies. First phase (late Eocene to early Miocene): Deposition occurred entirely in seawater-dominated oxic conditions, with high inputs of land plants organic matter including angiosperms. Second phase (middle to late Miocene): Deposition occurred in freshwater-dominated anoxic conditions, with phytoplanktonic organic matter and a small influence of land plants. Third phase (late Miocene to Pleistocene): Deposition occurred in oxygen-poor freshwater conditions, with abundant input of planktonic organic matter and high influx of angiosperms. The lower part (middle Eocene to early Miocene) of the succession with moderate TOC contents and primarily terrestrial organic matter could have generated some condensates and oils in and around the study area.

Keywords: Bangladesh, geochemistry, hydrocarbon potential, mudstone

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

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

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

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Authors: Ruyuf Y. Alnafisah, Nouf S. Alammari, Amani S. Alqahtani

Abstract:

Background: Beverage choice can have implications for the risk of non-communicable diseases. However, there is a lack of knowledge in assessing the nutritional content of these beverages. This study aims to describe the nutrient content of pre-packaged beverages available in the Saudi market. Design: Data were collected from the Saudi Branded Food Data-base (SBFD). Nutrient content was standardized in terms of units and reference volumes to ensure consistency in analysis. Results: A total of 1490 beverages were analyzed. The highest median levels of the majority of nutrients were found among dairy products; energy (68.4(43-188]kcal/100 ml in a milkshake); protein (8.2(0.5-8.2]g/100 ml in yogurt drinks); total fat (2.1(1.3-3.5]g/100 ml in milk); saturated fat (1.4(0-1.4]g/100 ml in yogurt drinks); cholesterol (30(0-30]mg/100 ml in yogurt drinks); sodium (65(65-65].4mg/100 ml in yogurt drinks); and total sugars (12.9(7.5-27]g/100 ml in milkshake). Carbohydrate level was the highest in nectar (13(11.8-14.2] g/100ml]; fruits drinks (12.9(11.9-13.9] g/100ml), and sparkling juices (12.9(8.8-14] g/100ml). The highest added sugar level was observed among regular soft drinks (12(10.8-14] g/100ml). The average rate of nutrient declaration was 60.95%. Carbo-hydrate had the highest declaration rate among nutrients (99.1%), and yogurt drinks had the highest declaration rate among beverage categories (92.7%). The median content of vitamins A and D in dairy products met the mandatory addition levels. Conclusion: This study provides valuable insights into the nutrient content of pre-packaged beverages in the Saudi market. It serves as a foundation for future research and monitoring. The findings of the study support the idea of taxing sugary beverages and raise concerns about the health effects of high sugar in fruit juices. Despite the inclusion of vitamins D and A in dairy products, the study highlights the need for alternative strategies to address these deficiencies.

Keywords: pre-packaged beverages, nutrients content, nutrients declaration, daily percentage value, mandatory addition of vitamins

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Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

Abstract:

Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

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Authors: Jeferson Brito Fernades, Breno Padovezi Rocha, Roger Augusto Rodrigues, Heraldo Luiz Giacheti

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The geotechnical projects demand the appropriate knowledge of soil characteristics and parameters. The determination of geotechnical soil parameters can be done by means of laboratory or in situ tests. In countries with tropical weather, like Brazil, unsaturated soils are very usual. In these soils, the soil suction has been recognized as an important stress state variable, which commands the geo-mechanical behavior. Triaxial and direct shear tests on saturated soils samples allow determine only the minimal soil shear strength, in other words, no suction contribution. This paper briefly describes the triaxial test with controlled suction as well as discusses the influence of suction on the shear strength parameters of a lateritic tropical sandy soil from a Brazilian research site. In this site, a sample pit was excavated to retrieve disturbed and undisturbed soil blocks. The samples extracted from these blocks were tested in laboratory to represent the soil from 1.5, 3.0 and 5.0 m depth. The stress curves and shear strength envelopes determined by triaxial tests varying suction and confining pressure are presented and discussed. The water retention characteristics on this soil complement this analysis. In situ CPT tests were also carried out at this site in different seasons of the year. In this case, the soil suction profile was determined by means of the soil water retention. This extra information allowed assessing how soil suction also affected the CPT data and the shear strength parameters estimative via correlation. The major conclusions of this paper are: the undisturbed soil samples contracted before shearing and the soil shear strength increased hyperbolically with suction; and it was possible to assess how soil suction also influenced CPT test data based on the water content soil profile as well as the water retention curve. This study contributed with a better understanding of the shear strength parameters and the soil variability of a typical unsaturated tropical soil.

Keywords: site characterization, triaxial test, CPT, suction, variability

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Authors: Sandra Arango-Caro, Kristine Callis-Duehl

Abstract:

The Education Research and Outreach Lab at the Donald Danforth Plant Science Center established the Plant and Agriculture Augmented and Virtual Reality Learning Laboratory (PAVRLL) to promote science education through professional development, school programs, internships, and outreach events. Professional development is offered to high school and college science and agriculture educators on the use and applications of zSpace and Oculus platforms. Educators learn to use, edit, or create lesson plans in the zSpace platform that are aligned with the Next Generation Science Standards. They also learn to use virtual reality experiences created by the PAVRLL available in Oculus (e.g. The Soybean Saga). Using a cost-free loan rotation system, educators can bring the AVR units to the classroom and offer AVR activities to their students. Each activity has user guides and activity protocols for both teachers and students. The PAVRLL also offers activities for 3D plant modeling. High school students work in teams of art-, science-, and technology-oriented students to design and create 3D models of plant species that are under research at the Danforth Center and present their projects at scientific events. Those 3D models are open access through the zSpace platform and are used by PAVRLL for professional development and the creation of VR activities. Both teachers and students acquire knowledge of plant and agriculture content and real-world problems, gain skills in AVR technology, 3D modeling, and science communication, and become more aware and interested in plant science. Students that participate in the PAVRLL activities complete pre- and post-surveys and reflection questions that evaluate interests in STEM and STEM careers, students’ perceptions of three design features of biology lab courses (collaboration, discovery/relevance, and iteration/productive failure), plant awareness, and engagement and learning in AVR environments. The PAVRLL was established in the fall of 2019, and since then, it has trained 15 educators, three of which will implement the AVR programs in the fall of 2021. Seven students have worked in the 3D plant modeling activity through a virtual internship. Due to the COVID-19 pandemic, the number of teachers trained, and classroom implementations have been very limited. It is expected that in the fall of 2021, students will come back to the schools in person, and by the spring of 2022, the PAVRLL activities will be fully implemented. This will allow the collection of enough data on student assessments that will provide insights on benefits and best practices for the use of AVR technologies in the classrooms. The PAVRLL uses cutting-edge educational technologies to promote science education and assess their benefits and will continue its expansion. Currently, the PAVRLL is applying for grants to create its own virtual labs where students can experience authentic research experiences using real Danforth research data based on programs the Education Lab already used in classrooms.

Keywords: assessment, augmented reality, education, plant science, virtual reality

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Authors: Dchieche Amina, Aboulaich Rajae

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Profit and loss sharing suggests an equitable sharing of risks and profits between the parts involved in a financial transaction. Salam is a contract in which advance payment is made for goods to be delivered at a future date. The purpose of this work is to price a new contract for profit and loss sharing based on Salam contract, using Khiyar Al Ghabn which is an agreement of choice in case of misrepresent facts.

Keywords: Islamic finance, shariah compliance, profit and loss sharing, derivatives, risks, hedging, salam contract

Procedia PDF Downloads 332

Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

Abstract:

Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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Authors: Lorenzo Cocola, Massimo Fedel, Dragiša Savić, Bojana Danilović, Luca Poletto

Abstract:

An instrument for the detection and evaluation of gaseous carbon dioxide in the headspace of closed containers has been developed in the context of Packsensor Italian-Serbian joint project. The device is based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) with a Wavelength Modulation Spectroscopy (WMS) technique in order to accomplish a non-invasive measurement inside closed containers of fermented dairy products (yogurts and fermented cheese in cups and bottles). The purpose of this instrument is the continuous monitoring of carbon dioxide concentration during incubation and storage of products over a time span of the whole shelf life of the product, in the presence of different microorganisms. The instrument’s optical front end has been designed to be integrated in a thermally stabilized incubator. An embedded computer provides processing of spectral artifacts and storage of an arbitrary set of calibration data allowing a properly calibrated measurement on many samples (cups and bottles) of different shapes and sizes commonly found in the retail distribution. A calibration protocol has been developed in order to be able to calibrate the instrument on the field also on containers which are notoriously difficult to seal properly. This calibration protocol is described and evaluated against reference measurements obtained through an industry standard (sampling) carbon dioxide metering technique. Some sets of validation test measurements on different containers are reported. Two test recordings of carbon dioxide concentration evolution are shown as an example of instrument operation. The first demonstrates the ability to monitor a rapid yeast growth in a contaminated sample through the increase of headspace carbon dioxide. Another experiment shows the dissolution transient with a non-saturated liquid medium in presence of a carbon dioxide rich headspace atmosphere.

Keywords: TDLAS, carbon dioxide, cups, headspace, measurement

Procedia PDF Downloads 324