Search results for: traffic modeling

Authors: Tizi Hayet, Berrama Tarek, Bounif Nadia

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Phenol and its derivatives are organic compounds utilized in the chemical industry. They are introduced into the environment by accidental spills and the illegal release of industrial and municipal wastewater. Phenols are organic intermediaries that are considered potential pollutants. Adsorption is one of the purification and separation techniques used in this area. Algeria annually produces 131000 tons of fig; therefore, a large amount of fig leaves is generated, and the conversion of this waste into adsorbent allows the valorization of agricultural residue. The main purpose of this present work is to describe an application of a statistical method for modeling and to optimize the conditions of the phenol adsorption from agricultural by-products, locally available (fig leaves). The best experimental performance of phenol elimination on the adsorbent was obtained with: Adsorbent concentration (X₂) = 200 mg L⁻¹; Initial concentration (X₃) = 150 mg L⁻¹; Speed agitation (X₁) = 300 rpm.

Keywords: low-cost adsorbents, adsorption, fig leaves, phenol, factorial design

Procedia PDF Downloads 117

Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

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Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

Procedia PDF Downloads 113

Authors: A. Degale Desta, Cheng Jian

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Background: Vehicle detection accuracy is critical to intelligent transportation systems and autonomous driving. The state-of-the-art object identification technology YOLOv8 has shown significant gains in efficiency and detection accuracy. This study uses the BDD100K dataset, which is renowned for its extensive and varied annotations, to assess how well YOLOv8 performs in vehicle detection. Objectives: The primary objective of this research is to assess YOLOv8's performance in intelligent transportation system vehicle identification and its ability to accurately identify cars in urban environments for safety prioritization. Methods: The primary objective of this research is to assess YOLOv8's performance in intelligent transportation system vehicle identification and its ability to accurately identify cars in urban environments for safety prioritization. Results: The results show that YOLOv8 achieves high mAP, recall, precision, and F1-score values, indicating state-of-the-art performance. This suggests that YOLOv8 can identify cars in complex urban environments with a high degree of accuracy and reliable results in a variety of traffic scenarios. Conclusion: The results indicate that YOLOv8 is a useful tool for enhancing vehicle detection accuracy in intelligent transportation systems, hence advancing urban public safety and security. The model's demonstrated performance shows how well it may be incorporated into autonomous driving applications to improve situational awareness and responsiveness.

Keywords: vehicle detection, YOLOv8, BDD100K, object detection, deep learning

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Authors: Peggy Näser

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Factory planning is a systematic, objective-oriented process for planning a factory, structured into a sequence of phases, each of which is dependent on the preceding phase and makes use of particular methods and tools, and extending from the setting of objectives to the start of production. The digital factory, on the other hand, is the generic term for a comprehensive network of digital models, methods, and tools – including simulation and 3D visualisation – integrated by a continuous data management system. Its aim is the holistic planning, evaluation and ongoing improvement of all the main structures, processes and resources of the real factory in conjunction with the product. Digital factory planning has already become established in factory planning. The application of Building Information Modeling has not yet been established in factory planning but has been used predominantly in the planning of public buildings. Furthermore, this concept is limited to the planning of the buildings and does not include the planning of equipment of the factory (machines, technical equipment) and their interfaces to the building. BIM is a cooperative method of working, in which the information and data relevant to its lifecycle are consistently recorded, managed and exchanged in a transparent communication between the involved parties on the basis of digital models of a building. Both approaches, the planning approach of Building Information Modeling and the methodical approach of the Digital Factory, are based on the use of a comprehensive data model. Therefore it is necessary to examine how the approach of Building Information Modeling can be extended in the context of factory planning in such a way that an integration of the equipment planning, as well as the building planning, can take place in a common digital model. For this, a number of different perspectives have to be investigated: the equipment perspective including the tools used to implement a comprehensive digital planning process, the communication perspective between the planners of different fields, the legal perspective, that the legal certainty in each country and the quality perspective, on which the quality criteria are defined and the planning will be evaluated. The individual perspectives are examined and illustrated in the article. An approach model for the integration of factory planning into the BIM approach, in particular for the integrated planning of equipment and buildings and the continuous digital planning is developed. For this purpose, the individual factory planning phases are detailed in the sense of the integration of the BIM approach. A comprehensive software concept is shown on the tool. In addition, the prerequisites required for this integrated planning are presented. With the help of the newly developed approach, a better coordination between equipment and buildings is to be achieved, the continuity of the digital factory planning is improved, the data quality is improved and expensive implementation errors are avoided in the implementation.

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

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Authors: Ammar Maziz, Mostapha Tarfaoui, Said Rechak

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The high mechanical performance of composite pipes can be adversely affected by their low resistance to impact loads. Loads in dynamic origin are dangerous and cause consequences on the operation of pipes because the damage is often not detected and can affect the structural integrity of composite pipes. In this work, an advanced 3-D finite element (FE) model, based on the use of intralaminar damage models was developed and used to predict damage under low-velocity impact. The performance of the numerical model is validated with the confrontation with the results of experimental tests. The results show that at low impact energy, the damage happens mainly by matrix cracking and delamination. The model capabilities to simulate the low-velocity impact events on the full-scale composite structures were proved.

Keywords: composite materials, low velocity impact, FEA, dynamic behavior, progressive damage modeling

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Authors: Komal Rathore, Aydin Sunol, Gita Iranipour, Luke Mulford

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Advanced wastewater treatment plants have complex biological kinetics, time variant influent flow rates and long processing times. Due to these factors, the modeling and operational control of advanced wastewater treatment plants become complicated. However, development of a robust model for advanced wastewater treatment plants has become necessary in order to increase the efficiency of the plants, reduce energy costs and meet the discharge limits set by the government. A dynamic model was designed using the Envirosim (Canada) platform software called BioWin for several wastewater treatment plants in Hillsborough County, Florida. Proper control strategies for various parameters such as mixed liquor suspended solids, recycle activated sludge and waste activated sludge were developed for models to match the plant performance. The models were tuned using both the influent and effluent data from the plant and their laboratories. The plant SCADA was used to predict the influent wastewater rates and concentration profiles as a function of time. The kinetic parameters were tuned based on sensitivity analysis and trial and error methods. The dynamic models were validated by using experimental data for influent and effluent parameters. The dissolved oxygen measurements were taken to validate the model by coupling them with Computational Fluid Dynamics (CFD) models. The Biowin models were able to exactly mimic the plant performance and predict effluent behavior for extended periods. The models are useful for plant engineers and operators as they can take decisions beforehand by predicting the plant performance with the use of BioWin models. One of the important findings from the model was the effects of recycle and wastage ratios on the mixed liquor suspended solids. The model was also useful in determining the significant kinetic parameters for biological wastewater treatment systems.

Keywords: BioWin, kinetic modeling, flowsheet simulation, dynamic modeling

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Authors: Boris Kolev, Matt Kokan, Mohammad Deriszadeh, Farshid Bateni

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Due to the increasing demand for real estate and the need for efficient land utilization in Greater Vancouver, developers have been increasingly considering the construction of high-rise structures with multiple below-grade parking. The temporary excavations required to allow for the construction of underground levels have recently reached up to 40 meters in depth. One of the challenges with deep excavations is the prediction of wall displacements and ground settlements due to their effect on the integrity of City utilities, infrastructure, and adjacent buildings. A large database of survey monitoring data has been collected for deep excavations in various soil conditions and shoring systems. The majority of the data collected is for tie-back anchors and shotcrete lagging systems. The data were categorized, analyzed and the results were evaluated to find a relationship between the most dominant parameters controlling the displacement, such as depth of excavation, soil properties, and the tie-back anchor loading and arrangement. For a select number of deep excavations, finite element modeling was considered for analyses. The lateral displacements from the simulation results were compared to the recorded survey monitoring data. The study concludes with a discussion and comparison of the available empirical and numerical modeling methodologies for evaluating lateral displacements in deep excavations.

Keywords: deep excavations, lateral displacements, numerical modeling, shoring walls, tieback anchors

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Authors: Bouthayna Hayou, Mohamed Mouloud Haddak

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In road accidents in French overseas territories have been understudied, with relevant data often collected late and incompletely. Although these territories account for only 3% to 4% of road traffic injuries in France, their unique characteristics merit closer attention. Despite lower mobility and, consequently, lower exposure to road risks, the actual road risk in Overseas France is as high or even higher than in Metropolitan France. Significant disparities exist not only between Metropolitan France and Overseas territories but also among the overseas territories themselves. The varying population densities in these regions do not fully explain these differences, as each territory has its own distinct vulnerabilities and road safety challenges. This analysis, based on BAAC data files from 2005 to 2018 for both Metropolitan France and the overseas departments and regions, examines key variables such as gender, age, type of road user, type of obstacle hit, type of trip, road category, traffic conditions, weather, and location of accidents. Logistic regression models were built for each region to investigate the risk factors associated with fatal road accidents, focusing on the probability of being killed versus injured. Due to insufficient data, Mayotte and the Overseas Communities (French Polynesia and New Caledonia) were not included in the models. The findings reveal that road safety is worse in the overseas territories compared to Metropolitan France, particularly for vulnerable road users such as pedestrians and motorized two-wheelers. These territories present an accident profile that sits between that of Metropolitan France and middle-income countries. A pressing need exists to standardize accident data collection between Metropolitan and Overseas France to allow for more detailed comparative analyses. Further epidemiological studies could help identify the specific road safety issues unique to each territory, particularly with regard to socio-economic factors such as social cohesion, which may influence road safety outcomes. Moreover, the lack of data on new modes of travel, such as electric scooters, and the absence of socio-economic details of accident victims complicate the evaluation of emerging risk factors. Additional research, including sociological and psychosocial studies, is essential for understanding road users' behavior and perceptions of road risk, which could also provide valuable insights into accident trends in peri-urban areas in France.

Keywords: multivariate logistic regression, overseas France, road safety, road traffic accident, territorial inequalities

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Authors: Sophie Lemoussu, Jean-Charles Chaudemar, Robertus A. Vingerhoeds

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Many innovative projects exist in the field of aeronautics, each addressing specific areas so to reduce weight, increase autonomy, reduction of CO2, etc. In many cases, such innovative developments are being carried out by very small enterprises (VSE’s) or small and medium sized-enterprises (SME’s). A good example concerns airships that are being studied as a real alternative to passenger and cargo transportation. Today, no international regulations propose a precise and sufficiently detailed framework for the development and certification of airships. The absence of such a regulatory framework requires a very close contact with regulatory instances. However, VSE’s/SME’s do not always have sufficient resources and internal knowledge to handle this complexity and to discuss these issues. This poses an additional challenge for those VSE’s/SME’s, in particular those that have system integration responsibilities and that must provide all the necessary evidence to demonstrate their ability to design, produce, and operate airships with the expected level of safety and reliability. The main objective of this research is to provide a methodological framework enabling VSE’s/SME’s with limited resources to organize the development of airships while taking into account the constraints of safety, cost, time and performance. This paper proposes to provide a contribution to this problematic by proposing a Model-Based Systems Engineering approach. Through a comprehensive process modeling approach applied to the development processes, the regulatory constraints, existing best practices, etc., a good image can be obtained as to the process landscape that may influence the development of airships. To this effect, not only the necessary regulatory information is taken on board, also other international standards and norms on systems engineering and project management are being modeled and taken into account. In a next step, the model can be used for analysis of the specific situation for given developments, derive critical paths for the development, identify eventual conflicting aspects between the norms, standards, and regulatory expectations, or also identify those areas where not enough information is available. Once critical paths are known, optimization approaches can be used and decision support techniques can be applied so to better support VSE’s/SME’s in their innovative developments. This paper reports on the adopted modeling approach, the retained modeling languages, and how they all fit together.

Keywords: aeronautics, certification, process modeling, project management, regulation, SME, systems engineering, VSE

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Authors: Emmanuel Iyamuremye

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Extreme rainfall events have caused significant damage to agriculture, ecology, and infrastructure, disruption of human activities, injury, and loss of life. They also have significant social, economic, and environmental consequences because they considerably damage urban as well as rural areas. Early detection of extreme maximum rainfall helps to implement strategies and measures, before they occur, hence mitigating the consequences. Extreme value theory has been used widely in modeling extreme rainfall and in various disciplines, such as financial markets, the insurance industry, failure cases. Climatic extremes have been analyzed by using either generalized extreme value (GEV) or generalized Pareto (GP) distributions, which provides evidence of the importance of modeling extreme rainfall from different regions of the world. In this paper, we focused on Peak Over Thresholds approach, where the Poisson-generalized Pareto distribution is considered as the proper distribution for the study of the exceedances. This research also considers the use of the generalized Pareto (GP) distribution with a Poisson model for arrivals to describe peaks over a threshold. The research used statistical techniques to fit models that used to predict extreme rainfall in Kigali. The results indicate that the proposed Poisson-GP distribution provides a better fit to maximum monthly rainfall data. Further, the Poisson-GP models are able to estimate various return levels. The research also found a slow increase in return levels for maximum monthly rainfall for higher return periods, and further, the intervals are increasingly wider as the return period is increasing.

Keywords: exceedances, extreme value theory, generalized Pareto distribution, Poisson generalized Pareto distribution

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Authors: Vedat Senol, Gursoy Turan, Anders Helmersson, Vortechz Andersson

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In developing a mathematical model of a real structure, the simulation results of the model may not match the real structural response. This is a general problem that arises during dynamic motion of the structure, which may be modeled by means of parameter variations in the stiffness, damping, and mass matrices. These changes in parameters need to be estimated, and the mathematical model is updated to obtain higher control performances and robustness. In this study, a linear fractional transformation (LFT) is utilized for uncertainty modeling. Further, a general approach to the design of an H∞ control of a magneto-rheological damper (MRD) for vibration reduction in a building with mass, damping, and stiffness uncertainties is presented.

Keywords: uncertainty modeling, structural control, MR Damper, H∞, robust control

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Authors: Serge B. Provost, Yishan Zhang

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A moment-based adjustment to the saddlepoint approximation is introduced in the context of density estimation. First applied to univariate distributions, this methodology is extended to the bivariate case. It then entails estimating the density function associated with each marginal distribution by means of the saddlepoint approximation and applying a bivariate adjustment to the product of the resulting density estimates. The connection to the distribution of empirical copulas will be pointed out. As well, a novel approach is proposed for estimating the support of distribution. As these results solely rely on sample moments and empirical cumulant-generating functions, they are particularly well suited for modeling massive data sets. Several illustrative applications will be presented.

Keywords: empirical cumulant-generating function, endpoints identification, saddlepoint approximation, sample moments, density estimation

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Authors: Y. Galerkin, K. Soldatova, A. Drozdov

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The 6th version of Universal modeling method for centrifugal compressor stage calculation is described. Identification of the new mathematical model was made. As a result of identification the uniform set of empirical coefficients is received. The efficiency definition error is 0,86 % at a design point. The efficiency definition error at five flow rate points (except a point of the maximum flow rate) is 1,22 %. Several variants of the stage with 3D impellers designed by 6th version program and quasi three-dimensional calculation programs were compared by their gas dynamic performances CFD (NUMECA FINE TURBO). Performance comparison demonstrated general principles of design validity and leads to some design recommendations.

Keywords: compressor design, loss model, performance prediction, test data, model stages, flow rate coefficient, work coefficient

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Chen-Chen Lo, Yin-Tzu Lin, Kang Lo

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Background: Driving fatigue related to inadequate or disordered sleep accounts for a major percentage of traffic accidents. Obstructive sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. However, the effects of OSAS severity on driving drowsiness remain unclear. Objective: The aim of this study is to investigate the relationship between OSAS severity and driving fatigue. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. OSAS severity was quantified as the polysomnography, and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). The severity of OSAS was diagnosed by the apnea and hypopnea index (AHI) with the American Academy of Sleep Medicine (AASM) guideline. The logistic regression model was used to examine the associations after adjusted age, gender, neck circumstance, waist circumstance, and body mass index (BMI). Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for OSAS as well as completed the driver condition questionnaire. 752 subjects were diagnosed with OSA, and 484 subjects had fatigue driving behavior in the past week. Patients diagnosed with OSAS had a 9.42-fold higher odds ratio (p < 0.01, 95% CI = 5.41 – 16.42) of driving drowsiness for cohorts with a normal degree. Conclusion: We observe the considerable correlation between OSAS and driving fatigue. For the purpose of promoting traffic safety, OSAS should be monitored and treated.

Keywords: obstructive sleep apnea syndrome, driving fatigue, polysomnography, apnea and hypopnea index

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Authors: H. S. Sathish, H. S. Jagadeesh, Skanda Kumar

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Journey time and delay study is used to evaluate the quality of service, the travel time and study can also be used to evaluate the quality of traffic movement along the route and to determine the location types and extent of traffic delays. Components of delay are boarding and alighting, issue of tickets, other causes and distance between each stops. This study investigates the total journey time required to travel along the stretch and the influence the delays. The route starts from Kempegowda Bus Station to Yelahanka Satellite Station of Bangalore City. The length of the stretch is 16.5 km. Modal split analysis has been done for this stretch. This stretch has elevated highway connecting to Bangalore International Airport and the extension of metro transit stretch. From the regression analysis of total journey time it is affected by delay due to boarding and alighting moderately, Delay due to issue of tickets affects the journey time to a higher extent. Some of the delay factors affecting significantly the journey time are evident from F-test at 10 percent level of confidence. Along this stretch work trips are more prevalent as indicated by O-D study. Modal shift analysis indicates about 70 percent of commuters are ready to shift from current system to Metro Rail System. Metro Rail System carries maximum number of trips compared to private mode. Hence Metro is a highly viable choice of mode for Bangalore Metropolitan City.

Keywords: delay, journey time, modal choice, regression analysis

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Authors: Shervin Khazaeli, Shahab Haj-zamani

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Recently, advanced geotechnical engineering problems related to soil movement, particle loss, and modeling of local failure (i.e. discontinua) as well as modeling the in-contact structures (i.e. continua) are of the great interest among researchers. The aim of this research is to meet the requirements with respect to the modeling of the above-mentioned two different domains simultaneously. To this end, a coupled numerical method is introduced based on Discrete Element Method (DEM) and eXtended-Finite Element Method (X-FEM). In the coupled procedure, DEM is employed to capture the interactions and relative movements of soil particles as discontinua, while X-FEM is utilized to model in-contact structures as continua, which may consist of different types of discontinuities. For verification purposes, the new coupled approach is utilized to examine benchmark problems including different contacts between/within continua and discontinua. Results are validated by comparison with those of existing analytical and numerical solutions. This study proves that extended-finite-discrete element method can be used to robustly analyze not only contact problems, but also other types of discontinuities in continua such as (i) crack formations and propagations, (ii) voids and bimaterial interfaces, and (iii) combination of previous cases. In essence, the proposed method can be used vastly in advanced soil-structure interaction problems to investigate the micro and macro behaviour of the surrounding soil and the response of the embedded structure that contains discontinuities.

Keywords: contact problems, discrete element method, extended-finite element method, soil-structure interaction

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Authors: Kyoungjin Kim

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Nanoscale thermites such as the composite mixture of nano-sized aluminum and molybdenum trioxide powders possess several technical advantages such as much higher reaction rate and shorter ignition delay, when compared to the conventional energetic formulations made of micron-sized metal and oxidizer particles. In this study, the self-propagation of combustion wave in compacted pellets of nanoscale thermite composites is modeled and computationally investigated by utilizing the activation energy reduction of aluminum particles due to nanoscale particle sizes. The present computational model predicts the speed of combustion wave propagation which is good agreement with the corresponding experiments of thermite reaction. Also, several characteristics of thermite reaction in nanoscale composites are discussed including the ignition delay and combustion wave structures.

Keywords: nanoparticles, thermite reaction, combustion wave, numerical modeling

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Authors: Meryem Kanzari, Rabah Boukhanouf, Hatem G. Ibrahim

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Indirect Evaporative Cooling process has the advantage of supplying cool air at constant moisture content. However, such system can only supply air at temperatures above wet bulb temperature. This paper presents a mathematical model for a sub-wet bulb temperature indirect evaporative cooling arrangement that can overcome this limitation and supply cool air at temperatures approaching dew point and without increasing its moisture content. In addition, the use of porous ceramics as wet media materials offers the advantage of integration into building elements. Results of the computer show that the proposed design is capable of cooling air to temperatures lower than the ambient wet bulb temperature and achieving wet bulb effectiveness of about 1.17.

Keywords: indirect evaporative cooling, porous ceramic, sub-wet bulb temperature, mathematical modeling

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Authors: Slawomir Lasota, Tomasz Kajdanowicz

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This research examines the application of predictive modelling and optimization algorithms to improve production efficiency in smart factories. Utilizing gradient boosting and neural networks, the study builds robust KPI estimators to predict production outcomes based on real-time data. Optimization methods, including Bayesian optimization and gradient-based algorithms, identify optimal process configurations that maximize availability, efficiency, and quality KPIs. The paper highlights the modular architecture of a recommender system that integrates predictive models, data visualization, and adaptive automation. Comparative analysis across multiple production processes reveals significant improvements in operational performance, laying the foundation for scalable, self-regulating manufacturing systems.

Keywords: predictive modeling, optimization, smart factory, efficiency

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Authors: Pei-Chen Wu

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Both preexisting cross-sectional and longitudinal studies of personality-depression relationship have suffered from one main limitation: they ignored the stability of the construct of interest (e.g., personality and depression) can be expected to influence the estimate of the association between personality and depression. To address this limitation, the Trait-State-Occasion (TSO) modeling was adopted to analyze the sources of variance of the focused constructs. A TSO modeling was operated by partitioning a state variance into time-invariant (trait) and time-variant (occasion) components. Within a TSO framework, it is possible to predict change on the part of construct that really changes (i.e., time-variant variance), when controlling the trait variances. 750 high school students were followed for 4 waves over six-month intervals. The baseline data (T1) were collected from the senior high schools (aged 14 to 15 years). Participants were given Beck Depression Inventory and Big Five Inventory at each assessment. TSO modeling revealed that 70~78% of the variance in personality (five constructs) was stable over follow-up period; however, 57~61% of the variance in depression was stable. For personality construct, there were 7.6% to 8.4% of the total variance from the autoregressive occasion factors; for depression construct there were 15.2% to 18.1% of the total variance from the autoregressive occasion factors. Additionally, results showed that when controlling initial symptom severity, the time-invariant components of all five dimensions of personality were predictive of change in depression (Extraversion: B= .32, Openness: B = -.21, Agreeableness: B = -.27, Conscientious: B = -.36, Neuroticism: B = .39). Because five dimensions of personality shared some variance, the models in which all five dimensions of personality were simultaneous to predict change in depression were investigated. The time-invariant components of five dimensions were still significant predictors for change in depression (Extraversion: B = .30, Openness: B = -.24, Agreeableness: B = -.28, Conscientious: B = -.35, Neuroticism: B = .42). In sum, the majority of the variability of personality was stable over 2 years. Individuals with the greater tendency of Extraversion and Neuroticism have higher degrees of depression; individuals with the greater tendency of Openness, Agreeableness and Conscientious have lower degrees of depression.

Keywords: assessment, depression, personality, trait-state-occasion model

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Authors: Dariush Jafari, Seyed Ali Jafari

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The recommended limit for cadmium concentration in potable water is less than 0.005 mg/L. A continuous biosorption process using indigenous red seaweed, Gracilaria corticata, was performed to remove cadmium from the potable water. The process was conducted under fixed conditions and the breakthrough curves were achieved for three consecutive sorption-desorption cycles. A modeling based on Artificial Neural Network (ANN) was employed to fit the experimental breakthrough data. In addition, a simplified semi empirical model, Thomas, was employed for this purpose. It was found that ANN well described the experimental data (R2>0.99) while the Thomas prediction were a bit less successful with R2>0.97. The adjusted design parameters using the nonlinear form of Thomas model was in a good agreement with the experimentally obtained ones. The results approve the capability of ANN to predict the cadmium concentration in potable water.

Keywords: ANN, biosorption, cadmium, packed-bed, potable water

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Authors: Maged A. Mogalli, Abdullah I. Al-Mansour, Seongkwan Mark Lee

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In the last decades, population growth has gradually exceeded transportation infrastructure growth, and today’s transportation professionals are facing challenge on how to meet the mobility needs of a rising population especially in the absence of adequate public transport, as is the case in Saudi Arabia. The traffic movement congestion can be decreased by carrying out some appropriate alternative designs of interchanges such as diverging diamond interchange (DDI) and single diamond interchange (SPDI). In this paper, evaluation of newly implemented DDIs at the interchange of Makkah road with Prince Turki road and the interchange of King Khaled road with Prince Saud Ibn Mohammed Ibn Mugrin road in Riyadh city was carried out. The comparison between the DDI and SPDI is conducted by evaluating different measures of effectiveness (MOE) such as stop delay, average queue length, and number of stops. In this connection, each interchange type was evaluated for traffic flow at peak hours using micro-simulation program namely 'Synchro/SimTarffic' to measure its effectiveness such as stop delay, average queue length, and number of stops. The results of this study show that DDI provides a better result when compared with SPDI in terms of stope delay, average queue length, and number of stops. The stop delay for the SPDI is greater than DDI by three times. Also, the average queue length is approximately twice that of the SPDI when compared to the DDI. Furthermore, the number of stops for the SPDI is about twice as the DDI.

Keywords: single point diamond interchange, diverging diamond interchange, measures of effectiveness, simulation

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Authors: Vahid Ebrahimipour

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Word representation and context meaning of text-based documents play an essential role in knowledge modeling. Business procedures written in natural language are meant to store technical and engineering information, management decision and operation experience during the production system life cycle. Context meaning representation is highly dependent upon word sense, lexical relativity, and sematic features of the argument. This paper proposes a method for lexical semantic analysis and context meaning representation of maintenance activity in a mass production system. Our approach constructs a straightforward lexical semantic approach to analyze facilitates semantic and syntactic features of context structure of maintenance report to facilitate translation, interpretation, and conversion of human-readable interpretation into computer-readable representation and understandable with less heterogeneity and ambiguity. The methodology will enable users to obtain a representation format that maximizes shareability and accessibility for multi-purpose usage. It provides a contextualized structure to obtain a generic context model that can be utilized during the system life cycle. At first, it employs a co-occurrence-based clustering framework to recognize a group of highly frequent contextual features that correspond to a maintenance report text. Then the keywords are identified for syntactic and semantic extraction analysis. The analysis exercises causality-driven logic of keywords’ senses to divulge the structural and meaning dependency relationships between the words in a context. The output is a word contextualized representation of maintenance activity accommodating computer-based representation and inference using OWL/RDF.

Keywords: lexical semantic analysis, metadata modeling, contextual meaning extraction, ontology modeling, knowledge representation

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Authors: Lavanya Ratnabala, Robinroy Peter, E. Y. A. Charles

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This research paper addresses the challenges of exploration and navigation in unknown environments from an evolutionary swarm robotics perspective. Path formation plays a crucial role in enabling cooperative swarm robots to accomplish these tasks. The paper presents a method called the sub-goal-based path formation, which establishes a path between two different locations by exploiting visually connected sub-goals. Simulation experiments conducted in the Argos simulator demonstrate the successful formation of paths in the majority of trials. Furthermore, the paper tackles the problem of inter-collision (traffic) among a large number of robots engaged in path formation, which negatively impacts the performance of the sub-goal-based method. To mitigate this issue, a task allocation strategy is proposed, leveraging local communication protocols and light signal-based communication. The strategy evaluates the distance between points and determines the required number of robots for the path formation task, reducing unwanted exploration and traffic congestion. The performance of the sub-goal-based path formation and task allocation strategy is evaluated by comparing path length, time, and resource reduction against the A* algorithm. The simulation experiments demonstrate promising results, showcasing the scalability, robustness, and fault tolerance characteristics of the proposed approach.

Keywords: swarm, path formation, task allocation, Argos, exploration, navigation, sub-goal

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Authors: Jirod Chaisan, Somchai Maneewan, Chantana Punlek, Ninnart Rachapradit, Surapong Chirarattananon, Pattana Rakkwamsuk

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In this paper, simulation modeling of heat transfer, air flow and distribution emitted from CO2 was performed in a regenerated air. The study room was divided in 3 types: common room, small lecture room and large lecture room under evaluated condition in two case: released and unreleased CO2 including of used hybrid air ventilation system for regenerated air under Thailand climate conditions. The carbon dioxide was located on the center of the room and released rate approximately 900-1200 ppm corresponded with indoor air quality standard (IAQs). The indoor air in the thermal comfort zone was calculated and simulated with the numerical method that using real data from the handbook guideline. The results of the study showed that in the case of hybrid air ventilation system explained thermal and CO2 distribution due to the system was adapted significantly in the comfort zone. The results showed that when CO2 released on the center of the other room, the CO2 high concentration in comfort zone so used hybrid air ventilation that decreased CO2 with regeneration air including of reduced temperature indoor. However, the study is simulation modeling and guideline only so the future should be the experiment of hybrid air ventilation system for evaluated comparison of the systems.

Keywords: air ventilation, indoor air quality, thermal comfort, thermoelectric, photovoltaic, dehumidify

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Authors: A. Naamane, M. Hasnaoui

Abstract:

Numerical modeling of fluid flows, whether compressible or incompressible, laminar or turbulent presents a considerable contribution in the scientific and industrial fields. However, the development of an approximate model of a supersonic flow requires the introduction of specific and more precise techniques and methods. For this purpose, the object of this paper is modeling a supersonic flow of inviscid fluid around a dihedral airfoil. Based on the thin airfoils theory and the non-dimensional stationary Steichen equation of a two-dimensional supersonic flow in isentropic evolution, we obtained a solution for the downstream velocity potential of the oblique shock at the second order of relative thickness that characterizes a perturbation parameter. This result has been dealt with by the asymptotic analysis and characteristics method. In order to validate our model, the results are discussed in comparison with theoretical and experimental results. Indeed, firstly, the comparison of the results of our model has shown that they are quantitatively acceptable compared to the existing theoretical results. Finally, an experimental study was conducted using the AF300 supersonic wind tunnel. In this experiment, we have considered the incident upstream Mach number over a symmetrical dihedral airfoil wing. The comparison of the different Mach number downstream results of our model with those of the existing theoretical data (relative margin between 0.07% and 4%) and with experimental results (concordance for a deflection angle between 1° and 11°) support the validation of our model with accuracy.

Keywords: asymptotic modelling, dihedral airfoil, supersonic flow, supersonic wind tunnel

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Authors: Michael Gerges, Ograbe Ahiakwo, Martin Jaeger, Ahmad Asaad

Abstract:

Recent advances of Building Information Modeling (BIM) especially in the Middle East have increased remarkably. Dubai has been taking a lead on this by making it mandatory for BIM to be adopted for all projects that involve complex architecture designs. This is because BIM is a dynamic process that assists all stakeholders in monitoring the project status throughout different project phases with great transparency. It focuses on utilizing information technology to improve collaboration among project participants during the entire life cycle of the project from the initial design, to the supply chain, resource allocation, construction and all productivity requirements. In view of this trend, the paper examines the extent of applying BIM in the State of Kuwait, by exploring practitioners’ perspectives on BIM, especially their perspectives on main barriers and main advantages. To this end structured interviews were carried out based on questionnaires and with a range of different construction professionals. The results revealed that practitioners perceive improved communication and mitigated project risks by encouraged collaboration between project participants. However, it was also observed that the full implementation of BIM in the State of Kuwait requires concerted efforts to make clients demanding BIM, counteract resistance to change among construction professionals and offer more training for design team members. This paper forms part of an on-going research effort on BIM and its application in the State of Kuwait and it is on this basis that further research on the topic is proposed.

Keywords: building information modeling, BIM, construction industry, Kuwait

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Authors: Marco Sewald

Abstract:

Comparing present to past the numbers of Americans expatriating U. S. citizenship have risen. Even though these numbers are small compared to the immigrants, U. S. citizens expatriations have historically been much lower, making the uptick worrisome. In addition, the published lists and numbers from the U.S. government seems incomplete, with many not counted. Different branches of the U. S. government report different numbers and no one seems to know exactly how big the real number is, even though the IRS and the FBI both track and/or publish numbers of Americans who renounce. Since there is no single explanation, anecdotal evidence suggests this uptick is caused by global tax law and increased compliance burdens imposed by the U.S. lawmakers on U.S. citizens abroad. Within a research project the question arose about the reasons why a constant growing number of U.S. citizens are expatriating – the answers are believed helping to explain the underlying governmental policy rational, leading to such activities. While it is impossible to locate former U.S. citizens to conduct a survey on the reasons and the U.S. government is not commenting on the reasons given within the process of expatriation, the chosen methodology is Structural Equation Modeling (SEM), in the first step by re-using current surveys conducted by different researchers within the population of U. S. citizens residing abroad during the last years. Surveys questioning the personal situation in the context of tax, compliance, citizenship and likelihood to repatriate to the U. S. In general SEM allows: (1) Representing, estimating and validating a theoretical model with linear (unidirectional or not) relationships. (2) Modeling causal relationships between multiple predictors (exogenous) and multiple dependent variables (endogenous). (3) Including unobservable latent variables. (4) Modeling measurement error: the degree to which observable variables describe latent variables. Moreover SEM seems very appealing since the results can be represented either by matrix equations or graphically. Results: the observed variables (items) of the construct are caused by various latent variables. The given surveys delivered a high correlation and it is therefore impossible to identify the distinct effect of each indicator on the latent variable – which was one desired result. Since every SEM comprises two parts: (1) measurement model (outer model) and (2) structural model (inner model), it seems necessary to extend the given data by conducting additional research and surveys to validate the outer model to gain the desired results.

Keywords: expatriation of U. S. citizens, SEM, structural equation modeling, validating

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Authors: Nalluri Lakshmi Ramu, C. Venkat Nihit, Narayana Kumar, Dillep

Abstract:

Masonry bridges are the iconic heritage transportation infrastructure throughout the world. Continuous increase in traffic loads and speed have kept engineers in dilemma about their structural performance and capacity. Henceforth, research community has an urgent need to propose an effective methodology and validate on real-time bridges. The presented research aims to assess the structural health of an Eighty-year-old masonry railway bridge in India using wireless accelerometer sensors. The bridge consists of 44 spans with length of 24.2 m each and individual pier is 13 m tall laid on well foundation. To calculate the dynamic characteristic properties of the bridge, ambient vibrations were recorded from the moving traffic at various speeds and the same are compared with the developed three-dimensional numerical model using finite element-based software. The conclusions about the weaker or deteriorated piers are drawn from the comparison of frequencies obtained from the experimental tests conducted on alternative spans. Masonry is a heterogeneous anisotropic material made up of incoherent materials (such as bricks, stones, and blocks). It is most likely the earliest largely used construction material. Masonry bridges, which were typically constructed of brick and stone, are still a key feature of the world's highway and railway networks. There are 1,47,523 railway bridges across India and about 15% of these bridges are built by masonry, which are around 80 to 100 year old. The cultural significance of masonry bridges cannot be overstated. These bridges are considered to be complicated due to the presence of arches, spandrel walls, piers, foundations, and soils. Due to traffic loads and vibrations, wind, rain, frost attack, high/low temperature cycles, moisture, earthquakes, river overflows, floods, scour, and soil under their foundations may cause material deterioration, opening of joints and ring separation in arch barrels, cracks in piers, loss of brick-stones and mortar joints, distortion of the arch profile. Few NDT tests like Flat jack Tests are being employed to access the homogeneity, durability of masonry structure, however there are many drawbacks because of the test. A modern approach of structural health assessment of masonry structures by vibration analysis, frequencies and stiffness properties is being explored in this paper.

Keywords: masonry bridges, condition assessment, wireless sensors, numerical analysis modal frequencies

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Authors: A. A. Hussen, I. N. Jleta

Abstract:

Micro-electromechanical system (MEMS) accelerometers and gyroscopes are suitable for the inertial navigation system (INS) of many applications due to the low price, small dimensions and light weight. The main disadvantage in a comparison with classic sensors is a worse long term stability. The estimation accuracy is mostly affected by the time-dependent growth of inertial sensor errors, especially the stochastic errors. In order to eliminate negative effect of these random errors, they must be accurately modeled. Where the key is the successful implementation that depends on how well the noise statistics of the inertial sensors is selected. In this paper, the Allan variance technique will be used in modeling the stochastic errors of the inertial sensors. By performing a simple operation on the entire length of data, a characteristic curve is obtained whose inspection provides a systematic characterization of various random errors contained in the inertial-sensor output data.

Keywords: Allan variance, accelerometer, gyroscope, stochastic errors

Procedia PDF Downloads 444