Search results for: fracture modeling

Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng

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The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.

Keywords: area-based traffic, car-following model, micro-simulation, stochastic modeling

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Authors: Gianmarco Taveri, Ivo Dlouhy

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Geopolymers are well-suited materials to abate CO2 emission coming from the Portland cement production, and then replace them, in the near future, in building and other applications. The cost of production of geopolymers may be seen the only weakness, but the use of wastes as raw materials could provide a valid solution to this problem, as demonstrated by the successful incorporation of fly-ash, a by-product of thermal power plants, and waste glasses. Recycled glass in waste-derived geopolymers was lately employed as a further silica source. In this work we present, for the first time, the introduction of recycled borosilicate glass (BSG). BSG is actually a waste glass, since it derives from dismantled pharmaceutical vials and cannot be reused in the manufacturing of the original articles. Owing to the specific chemical composition (BSG is an ‘alumino-boro-silicate’), it was conceived to provide the key components of zeolitic networks, such as amorphous silica and alumina, as well as boria (B2O3), which may replace Al2O3 and contribute to the polycondensation process. The solid–state MAS NMR spectroscopy was used to assess the extent of boron oxide incorporation in the structure of geopolymers, and to define the degree of networking. FTIR spectroscopy was utilized to define the degree of polymerization and to detect boron bond vibration into the structure. Mechanical performance was tested by means of 3 point bending (flexural strength), chevron notch test (fracture toughness), compression test (compressive strength), micro-indentation test (Vicker’s hardness). Spectroscopy (SEM and Confocal spectroscopy) was performed on the specimens conducted to failure. FTIR showed a characteristic absorption band attributed to the stretching modes of tetrahedral boron ions, whose tetrahedral configuration is compatible to the reaction product of geopolymerization. 27Al NMR and 29Si NMR spectra were instrumental in understanding the extent of the reaction. 11B NMR spectroscopies evidenced a change of the trigonal boron (BO3) inside the BSG in favor of a quasi-total tetrahedral boron configuration (BO4). Thanks to these results, it was inferred that boron is part of the geopolymeric structure, replacing the Si in the network, similarly to the aluminum, and therefore improving the quality of the microstructure, in favor of a more cross-linked network. As expected, the material gained as much as 25% in compressive strength (45 MPa) compared to the literature, whereas no improvements were detected in flexural strength (~ 5 MPa) and superficial hardness (~ 78 HV). The material also exhibited a low fracture toughness (0.35 MPa*m1/2), with a tangible brittleness. SEM micrographies corroborated this behavior, showing a ragged surface, along with several cracks, due to the high presence of porosity and impurities, acting as preferential points for crack initiation. The 3D pattern of the surface fracture, following the confocal spectroscopy, evidenced an irregular crack propagation, whose proclivity was mainly, but not always, to follow the porosity. Hence, the crack initiation and propagation are largely unpredictable.

Keywords: borosilicate glass, characterization, fly-ash, geopolymerization

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Authors: Razieh Arian, Hadi Adibi-Asl

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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine

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Authors: Mehran Dizbadi, Daniyal Safarzadeh, Behrooz Arastoo, Ansgar Brunn

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Rapid and uncontrolled expansion of cities has led to unplanned aerial development. In this way, modeling and predicting the urban growth of a city helps decision-makers. In this study, the aspect of sustainable urban development has been studied for the city of Mashhad. In general, the prediction of urban aerial development is one of the most important topics of modern town management. In this research, using the Cellular Automaton (CA) model developed for geo data of Geographic Information Systems (GIS) and presenting a simple and powerful model, a simulation of complex urban processes has been done.

Keywords: urban modeling, sustainable development, fuzzy cellular automaton, geo-information system

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Authors: Patricia Shirley Almeida Prado, Selma Paixão Argollo, Maria De Fátima Teixeira Guimarães, Leticia Matos Sobrinho

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Skeletal differential diagnosis is essential in forensic anthropology in order to differentiate skeletal trauma from normal osseous variation and pathological processes. Thus, part of forensic anthropological field is differentiate skeletal criminal injuries from the normal skeletal variation (bone fusion or nonunion, transitional vertebrae and other non-metric traits), non-traumatic skeletal pathology (myositis ossificans, arthritis, bone metastasis, osteomyelitis) from traumatic skeletal pathology (myositis ossificans traumatic) avoiding misdiagnosis. This case shows the importance of effective pathological diagnosis in order to accelerate the identification process of skeletonized human remains. THE CASE: An unidentified skeletal remains at the medico legal institute Nina Rodrigues-Salvador, of a male young adult (29 to 40 years estimated) showing a massive heterotopic ossification on its right tibia at upper epiphysis and adjacent articular femur surface; an extensive ossification on the right clavicle (at the sternal extremity) also presenting an heterotopic ossification at right scapulae (upper third of scapulae lateral margin and infraglenoid tubercule) and at the head of right humerus at the shoulder joint area. Curiously, this case also shows an unusual porosity in certain vertebrae´s body and in some tarsal and carpal bones. Likewise, his left fifth metacarpal bones (right and left) showed a healed fracture which led both bones distorted. Based on identification, of pathological conditions in human skeletal remains literature and protocols these alterations can be misdiagnosed and this skeleton may present more than one pathological process. The anthropological forensic lab at Medico-legal Institute Nina Rodrigues in Salvador (Brazil) adopts international protocols to ancestry, sex, age and stature estimations, also implemented well-established conventions to identify pathological disease and skeletal alterations. The most compatible diagnosis for this case is hematogenous osteomyelitis due to following findings: 1: the healed fracture pattern at the clavicle showing a cloaca which is a pathognomonic for osteomyelitis; 2: the metacarpals healed fracture does not present cloaca although they developed a periosteal formation. 3: the superior articular surface of the right tibia shows an extensive inflammatory healing process that extends to adjacent femur articular surface showing some cloaca at tibia bone disease. 4: the uncommon porosities may result from hematogenous infectious process. The fractures probably have occurred in a different moments based on the healing process; the tibia injury is more extensive and has not been reorganized, while metacarpals and clavicle fracture is properly healed. We suggest that the clavicle and tibia´s fractures were infected by an existing infectious disease (syphilis, tuberculosis, brucellosis) or an existing syndrome (Gorham’s disease), which led to the development of osteomyelitis. This hypothesis is supported by the fact that different bones are affected in diverse levels. Like the metacarpals that do not show the cloaca, but then a periosteal new bone formation; then the unusual porosities do not show a classical osteoarthritic processes findings as the marginal osteophyte, pitting and new bone formation, they just show an erosive process without bone formation or osteophyte. To confirm and prove our hypothesis we are working on different clinical approaches like DNA, histopathology and other image exams to find the correct diagnostic.

Keywords: bone disease, forensic anthropology, hematogenous osteomyelitis, human identification, human remains

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Authors: Sayed M. Soleimani, Nader H. Ghareeb, Nourhan H. Shaker, Muhammad B. Siddiqui

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Honeycomb sandwich panels have been widely used as protective structural elements against blast loading. The main advantages of these panels include their light weight due to the presence of voids, as well as their energy absorption capability. Terrorist activities have imposed new challenges to structural engineers to design protective measures for vital structures. Since blast loading is not usually considered in the load combinations during the design process of a structure, researchers around the world have been motivated to study the behavior of potential elements capable of resisting sudden loads imposed by the detonation of explosive materials. One of the best candidates for this objective is the honeycomb sandwich panel. Studying the effects of explosive materials on the panels requires costly and time-consuming experiments. Moreover, these type of experiments need permission from defense organizations which can become a hurdle. As a result, modeling and simulation using an appropriate tool can be considered as a good alternative. In this research work, the finite element package ABAQUS® is used to study the behavior of hexagonal and squared honeycomb steel sandwich panels under the explosive effects of different amounts of trinitrotoluene (TNT). The results of finite element modeling of a specific honeycomb configuration are initially validated by comparing them with the experimental results from literature. Afterwards, several configurations including different geometrical properties of the honeycomb wall are investigated and the results are compared with the original model. Finally, the effectiveness of the core shape and wall thickness are discussed, and conclusions are made.

Keywords: Abaqus, blast loading, finite element modeling, steel honeycomb sandwich panel

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Authors: Hueiwang Anna Jeng, Norou Diawara, Nancy Welch, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari

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Modeling effort is needed to predict the COVID-19 trends for developing management strategies and adaptation measures. The objective of this study was to assess whether SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalization cases, and death cases using copula-based time series modeling. SARS-CoV-2 RNA load in raw wastewater in Chesapeake VA was measured using the RT-qPCR method. Gaussian copula time series marginal regression model, incorporating an autoregressive moving average model and the copula function, served as a forecasting model. COVID-19 cases were correlated with wastewater viral load, hospitalization cases, and death cases. The forecasted trend of COVID-19 cases closely paralleled one of the reported cases, with over 90% of the forecasted COVID-19 cases falling within the 99% confidence interval of the reported cases. Wastewater SARS-CoV-2 viral load could serve as a predictor for COVID-19 cases and hospitalization cases.

Keywords: COVID-19, modeling, time series, copula function

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Authors: Y. Ruchi, A. Prerna, S. Deepshikha

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Amyotrophic lateral sclerosis (ALS), also known as “Lou Gehrig’s disease”. It is a neurodegenerative disease associated with degeneration of motor neurons in the cerebral cortex, brain stem, and spinal cord characterized by distal muscle weakness, atrophy, normal sensation, pyramidal signs and progressive muscular paralysis reflecting. ALS2 is a juvenile autosomal recessive disorder, slowly progressive, that maps to chromosome 2q33 and is associated with mutations in the alsin gene, a putative GTPase regulator. In this paper we have done homology modeling of alsin2 protein using multiple templates (3KCI_A, 4LIM_A, 402W_A, 4D9S_A, and 4DNV_A) designed using the Prime program in Schrödinger software. Further modeled structure is used to identify effective binding sites on the basis of structural and physical properties using sitemap program in Schrödinger software, structural and function analysis is done by using Prosite and ExPASy server that gives insight into conserved domains and motifs that can be used for protein classification. This paper summarizes the structural, functional and binding site property of alsin2 protein. These binding sites can be potential drug target sites and can be used for docking studies.

Keywords: ALS, binding site, homology modeling, neuronal degeneration

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Authors: Vassilios Moussas, Dimos N. Pantazis, Panagioths Stratakis

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The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed.

Keywords: coastal transport, modeling, optimization

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Authors: M. Ziółkowska, J. T. Duda, J. Milewska-Duda

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This paper describes an approach to the adsorption phenomena modeling aimed at specifying the adsorption mechanisms on localized or nonlocalized adsorbent sites, when applied to the nanocarbons. The concept comes from the fundamental thermodynamic description of adsorption equilibrium and is based on numerical calculations of the hydrogen adsorbed particles volume on the surface of selected nanocarbons: single-walled nanotube and nanocone. This approach enables to obtain information on adsorption mechanism and then as a consequence to take appropriate mathematical adsorption model, thus allowing for a more reliable identification of the material porous structure. Theoretical basis of the approach is discussed and newly derived results of the numerical calculations are presented for the selected nanocarbons.

Keywords: adsorption, mathematical modeling, nanocarbons, numerical analysis

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Authors: Arun Prabhakar

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Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model.

Keywords: directed acyclic graph, ontology, patterns, threat identification, threat modeling

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Authors: F. Clara Fang, Hernan Castaneda

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The Connecticut Department of Transportation (ConnDOT) has constructed four roundabouts in the State of Connecticut within the past ten years. VISSIM traffic simulation software was utilized to analyze these roundabouts during their design phase. The queue length and level of service observed in the field appear to be better than predicted by the VISSIM model. The objectives of this project are to: identify VISSIM input variables most critical to accurate modeling; recommend VISSIM calibration factors; and, provide other recommendations for roundabout traffic operations modeling. Traffic data were collected at these roundabouts using Miovision Technologies. Cameras were set up to capture vehicle circulating activity and entry behavior for two weekdays. A large sample size of filed data was analyzed to achieve accurate and statistically significant results. The data extracted from the videos include: vehicle circulating speed; critical gap estimated by Maximum Likelihood Method; peak hour volume; follow-up headway; travel time; and, vehicle queue length. A VISSIM simulation of existing roundabouts was built to compare both queue length and travel time predicted from simulation with measured in the field. The research investigated a variety of simulation parameters as calibration factors for describing driver behaviors at roundabouts. Among them, critical gap is the most effective calibration variable in roundabout simulation. It has a significant impact to queue length, particularly when the volume is higher. The results will improve the design of future roundabouts in Connecticut and provide decision makers with insights on the relationship between various choices and future performance.

Keywords: driver critical gap, roundabout analysis, simulation, VISSIM modeling

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Authors: Hadi Ardiny, Amir Mohammad Beigzadeh

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Through the utilization of a combination of various sensors and data fusion methods, the detection of potential nuclear threats can be significantly enhanced by extracting more information from different data. In this research, an experimental and modeling approach was employed to track a radioactive source by combining a surveillance camera and a radiation detector (NaI). To run this experiment, three mobile robots were utilized, with one of them equipped with a radioactive source. An algorithm was developed in identifying the contaminated robot through correlation between camera images and camera data. The computer vision method extracts the movements of all robots in the XY plane coordinate system, and the detector system records the gamma-ray count. The position of the robots and the corresponding count of the moving source were modeled using the MCNPX simulation code while considering the experimental geometry. The results demonstrated a high level of accuracy in finding and locating the target in both the simulation model and experimental measurement. The modeling techniques prove to be valuable in designing different scenarios and intelligent systems before initiating any experiments.

Keywords: nuclear threats, radiation detector, MCNPX simulation, modeling techniques, intelligent systems

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Authors: Motalleb Byzedi, Seyedeh Chaman Naderi Korvandan

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Regarding annual statistics of groundwater level resources about current piezometers at Qorveh plains, both ARMA & PARMA modeling methods were applied in this study by the using of SAMS software. Upon performing required tests, a model was used with minimum amount of Akaike information criteria and suitable model was selected for piezometers. Then it was possible to make necessary estimations by using these models for future fluctuations in each piezometer. According to the results, ARMA model had more facilities for modeling of aquifer. Also it was cleared that eastern parts of aquifer had more failures than other parts. Therefore it is necessary to prohibit critical parts along with more supervision on taking rates of wells.

Keywords: qorveh plain, groundwater level, ARMA, PARMA

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Authors: Serena Gomez, Raeesa Tanseen, Netra Shaligram, Nithin Francis, Sandesh B. J.

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The human gut consists of a community of microbes which has a lot of effects on human health disease. Metabolic modeling can help to predict relative populations of stable microbes and their effect on health disease. In order to study and visualize microbes in the human gut, we developed a tool that offers the following modules: Build a tool that can be used to perform Flux Balance Analysis for microbes in the human gut using the Artificial Bee Colony optimization algorithm. Run simulations for an individual microbe in different conditions, such as aerobic and anaerobic and visualize the results of these simulations.

Keywords: microbes, metabolic modeling, flux balance analysis, artificial bee colony

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Authors: Ghasem Sharifi, Hamed Shahmohamadi Ousaloo, Milad Azimi, Mehran Mirshams

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The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation.

Keywords: experimental modeling, friction parameters, model identification, reaction wheel

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Authors: Donald G. Danmeier, Gian Marco Pizzo, Matthew Brennan

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Although wetlands have been proposed as a green alternative to manage coastal flood hazards because of their capacity to adapt to sea level rise and provision of multiple ecological and social co-benefits, they are often overlooked due to challenges in quantifying the uncertainty and naturally, variability of these systems. This objective of this study was to quantify wave attenuation provided by a natural marsh surrounding a large oil refinery along the US Gulf Coast that has experienced steady erosion along the shoreward edge. The vegetation module of the SWAN was activated and coupled with a hydrodynamic model (DELFT3D) to capture two-way interactions between the changing water level and wavefield over the course of a storm event. Since the marsh response to relative sea level rise is difficult to predict, a range of future marsh morphologies is explored. Numerical results were examined to determine the amount of wave attenuation as a function of marsh extent and the relative contributions from white-capping, depth-limited wave breaking, bottom friction, and flexing of vegetation. In addition to the coupled DELFT3D-SWAN modeling of a storm event, an uncoupled SWAN-VEG model was applied to a simplified bathymetry to explore a larger experimental design space. The wave modeling revealed that the rate of wave attenuation reduces for higher surge but was still significant over a wide range of water levels and outboard wave heights. The results also provide insights to the minimum marsh extent required to fully realize the potential wave attenuation so the changing coastal hazards can be managed.

Keywords: green infrastructure, wave attenuation, wave modeling, wetland

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Authors: Cristian Patrascioiu, Loredana Negoita

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This paper is focused on modeling and simulation of the tubular heaters. The paper is structured in four parts: the structure of the tubular convection section, the heat transfer model, the adaptation of the mathematical model and the solving model. The main hypothesis of the heat transfer modeling is that the heat exchanger of the convective tubular heater is a lumped system. In the same time, the model uses the heat balance relations, Newton’s law and criteria relations. The numerical program achieved allows for the estimation of the burn gases outlet temperature and the heated flow outlet temperature.

Keywords: heat exchanger, mathematical modelling, nonlinear equation system, Newton-Raphson algorithm

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Authors: Miral Selim, May Haggag, Ibrahim Abotaleb

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The aging of transportation infrastructure presents significant challenges, particularly concerning the monitoring and maintenance of bridges. This study investigates the application of Random Forest algorithms for predictive modeling of bridge conditions, utilizing data from the US National Bridge Inventory (NBI). The research is significant as it aims to improve bridge management through data-driven insights that can enhance maintenance strategies and contribute to overall safety. Random Forest is chosen for its robustness, ability to handle complex, non-linear relationships among variables, and its effectiveness in feature importance evaluation. The study begins with comprehensive data collection and cleaning, followed by the identification of key variables influencing bridge condition ratings, including age, construction materials, environmental factors, and maintenance history. Random Forest is utilized to examine the relationships between these variables and the predicted bridge conditions. The dataset is divided into training and testing subsets to evaluate the model's performance. The findings demonstrate that the Random Forest model effectively enhances the understanding of factors affecting bridge conditions. By identifying bridges at greater risk of deterioration, the model facilitates proactive maintenance strategies, which can help avoid costly repairs and minimize service disruptions. Additionally, this research underscores the value of data-driven decision-making, enabling better resource allocation to prioritize maintenance efforts where they are most necessary. In summary, this study highlights the efficiency and applicability of Random Forest in predictive modeling for bridge management. Ultimately, these findings pave the way for more resilient and proactive management of bridge systems, ensuring their longevity and reliability for future use.

Keywords: data analysis, random forest, predictive modeling, bridge management

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Authors: Saeed Zeinali, Nasser Talebbeydokhti, Mehdi Saeidian, Shahrad Vosough

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In this article, bathymetry changes have been studied as a case study for Larak Island, located in The South of Iran. The advanced 2D model of Mike21 has been used for this purpose. A simple procedure has been utilized in this model. First, the hydrodynamic (HD) module of Mike21 has been used to obtain the required output for sediment transport model (ST module). The ST module modeled the area for tidal currents only. Bed level changes are resulted by series of modeling for both HD and ST module in 3 months time step. The final bathymetry in each time step is used as the primary bathymetry for next time step. This consecutive procedure been continued until bathymetry for the year 2020 is obtained.

Keywords: bed level changes, Larak Island, hydrodynamic, sediment transport

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Authors: Jamel Boukhatem, Mouldi Djelassi

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Contrary to the existing literature generally focusing on the role played by Sukuk in enhancing investors' and shareholders' wealth, this paper sheds some light on the Sukuk wealth effect across all economic agents: households, government, and investors by implementing a two-period life-cycle model with overlapping generations to show whether Sukuk is net wealth. The main findings are threefold: i) the effect of a change in Sukuk issuances on the consumers’ utility level will be different from one generation to another, ii) an increase in taxes due to the increase in Sukuk and rents is covered by transfers made by the members of generation 1 in the form of inheritance, and iii) the existence of a positive relationship between the asset prices representative of Sukuk and the real activity.

Keywords: Sukuk, households, investors, overlapping generations model, wealth, modeling

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Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li

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Transports of solid particles through the drill pipe, drill string-hole annulus and hydraulically generated fractures are important dynamic processes encountered in oil and gas well drilling and completion operations. Different from particle transport in infinite space, the transports of cuttings, proppants and formation sand are hindered by a finite boundary. Therefore, an accurate description of the particle transport behavior under the bounded wall conditions encountered in drilling and hydraulic fracturing operations is needed to improve drilling safety and efficiency. In this study, the particle settling experiments were carried out to investigate the particle settling behavior in the pipe, annulus and between the parallel plates filled with power-law fluids. Experimental conditions simulated the particle Reynolds number ranges of 0.01-123.87, the dimensionless diameter ranges of 0.20-0.80 and the fluid flow behavior index ranges of 0.48-0.69. Firstly, the wall effect of the annulus is revealed by analyzing the settling process of the particles in the annular geometry with variable inner pipe diameter. Then, the geometric continuity among the pipe, annulus and parallel plates was determined by introducing the ratio of inner diameter to an outer diameter of the annulus. Further, a unified dimensionless diameter was defined to confirm the relationship between the three different geometry in terms of the wall effect. In addition, a dimensionless term independent from the settling velocity was introduced to establish a unified explicit settling velocity model applicable to pipes, annulus and fractures with a mean relative error of 8.71%. An example case study was provided to demonstrate the application of the unified model for predicting particle settling velocity. This paper is the first study of annulus wall effects based on the geometric continuity concept and the unified model presented here will provide theoretical guidance for improved hydraulic design of cuttings transport, proppant placement and sand management operations.

Keywords: wall effect, particle settling velocity, cuttings transport, proppant transport in fracture

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Authors: Mei-Chun Chang

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Due to digital transformation and social media development in recent years, various real-time interactive digital tools have been developed to meet the design demands for virtual reality avatars, which also promote digital content learners' active participation in the creation process. As a result, new social media design tools have the characteristics of intuitive operation with a simplified interface for fast production, from which works can be simply created. This study carried out observations, records, questionnaire surveys, and interviews on the creation and learning of visual avatars made by students of the National Taiwan University of Science and Technology (NTUST) with the VRoid Studio 3D modeling tool so as to explore their learning effectiveness on the design of visual avatars. According to the results of this study, the VRoid Studio 3D character modeling tool has a positive impact on the learners and helps to improve their learning effectiveness. Students with low academic achievements said that they could complete the conceived modeling with their own thinking by using the design tool, which increased their sense of accomplishment. Conclusions are drawn according to the results, and relevant future suggestions are put forward.

Keywords: virtual avatar, character design, social media, vroid studio, creation, digital learning

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Authors: Sigal Portnoy, Yael Kaufman-Cohen, Yafa Levanon

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Introduction: Rehabilitation following wrist fractures often includes exercising flexion-extension movements with a dynamic splint. However, during daily activities, we combine most of our wrist movements with radial and ulnar deviations. Also, the multi-plane wrist motion, named the ‘dart throw motion’ (DTM), was found to be a more stable motion in healthy individuals, in term of the motion of the proximal carpal bones, compared with sagittal wrist motion. The aim of this study was therefore to explore the pathomechanics of the wrist in a common multi-plane movement pattern (DTM) and design a novel splint for rehabilitation following distal radius fractures. Methods: First, a multi-axis electro-goniometer was used to quantify the plane angle of motion of the dominant and non-dominant wrists during various activities, e.g. drinking from a glass of water and answering a phone in 43 healthy individuals. The following protocols were then implemented with a population following distal radius fracture. Two dynamic scans were performed, one of the sagittal wrist motion and DTM, in a 3T magnetic resonance imaging (MRI) device, bilaterally. The scaphoid and lunate carpal bones, as well as the surface of the distal radius, were manually-segmented in SolidWorks and the angles of motion of the scaphoid and lunate bones were calculated. Subsequently, a patient-specific splint was designed using 3D scans of the hand. The brace design comprises of a proximal attachment to the arm and a distal envelope of the palm. An axle with two wheels is attached to the proximal part. Two wires attach the proximal part with the medial-palmar and lateral-ventral aspects of the distal part: when the wrist extends, the first wire is released and the second wire is strained towards the radius. The opposite occurs when the wrist flexes. The splint was attached to the wrist using Velcro and constrained the wrist movement to the desired calculated multi-plane of motion. Results: No significant differences were found between the multi-plane angles of the dominant and non-dominant wrists. The most common daily activities occurred at a plane angle of approximately 20° to 45° from the sagittal plane and the MRI studies show individual angles of the plane of motion. The printed splint fitted the wrist of the subjects and constricted movement to the desired multi-plane of motion. Hooks were inserted on each part to allow the addition of springs or rubber bands for resistance training towards muscle strengthening in the rehabilitation setting. Conclusions: It has been hypothesized that activation of the wrist in a multi-plane movement pattern following distal radius fractures will accelerate the recovery of the patient. Our results show that this motion can be determined from either the dominant or non-dominant wrists. The design of the patient-specific dynamic splint is the first step towards assessing whether splinting to induce combined movement is beneficial to the rehabilitation process, compared to conventional treatment. The evaluation of the clinical benefits of this method, compared to conventional rehabilitation methods following wrist fracture, are a part of a PhD work, currently conducted by an occupational therapist.

Keywords: distal radius fracture, rehabilitation, dynamic magnetic resonance imaging, dart throw motion

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Authors: K. Passbakhsh

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Determination of reinforcement forces is one of the most important and main discussions in designing retaining walls. By determining these forces we refrain from conservative planning. By numerically modeling the reinforced soil retaining walls under dynamic loading reinforcement forces can be calculated. In this study we try to approach the gained forces by pseudo-static method according to FHWA code and gained forces from numerical modeling by finite element method, by selecting seismic horizontal coefficient for different wall height. PLAXIS software was used for numerical analysis. Then the effect of reinforcement stiffness and soil type on reinforcement forces is examined.

Keywords: reinforced soil, PLAXIS, reinforcement forces, retaining walls

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Authors: Rouaz Idriss, Bourahla Nour-Eddine, Kahlouche Farah, Rafa Sid Ali

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The stability of structures made of light-gauge steel depends highly on the contribution of Shear Wall Panel (SWP) systems under horizontal forces due to wind or earthquake loads. Steel plate sheathing is often used with these panels made of cold formed steel (CFS) to improve its shear strength. In order to predict the shear strength resistance, two methods are presented in this paper. In the first method, the steel plate sheathing is modeled with plats strip taking into account only the tension and compression force due to the horizontal load, where both track and stud are modeled according to the geometrical and mechanical characteristics of the specimen used in the experiments. The theoretical background and empirical formulations of this method are presented in this paper. However, the second method is based on a micro modeling of the cold formed steel Shear Wall Panel “CFS-SWP” using Abaqus software. A nonlinear analysis was carried out with an in-plan monotonic load. Finally, the comparison between these two methods shows that the micro modeling with Abaqus gives better prediction of shear resistance of SWP than strips method. However, the latter is easier and less time consuming than the micro modeling method.

Keywords: cold formed steel 'CFS', shear wall panel, strip method, finite elements

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Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

Abstract:

Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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Authors: V. Pourmostaghimi, M. Zadshakoyan

Abstract:

Efficiency and productivity of the finish hard turning can be enhanced impressively by utilizing accurate predictive models for cutting tool wear. However, the ability of genetic programming in presenting an accurate analytical model is a notable characteristic which makes it more applicable than other predictive modeling methods. In this paper, the genetic equation for modeling of tool flank wear is developed with the use of the experimentally measured flank wear values and genetic programming during finish turning of hardened AISI D2. Series of tests were conducted over a range of cutting parameters and the values of tool flank wear were measured. On the basis of obtained results, genetic model presenting connection between cutting parameters and tool flank wear were extracted. The accuracy of the genetically obtained model was assessed by using two statistical measures, which were root mean square error (RMSE) and coefficient of determination (R²). Evaluation results revealed that presented genetic model predicted flank wear over the study area accurately (R² = 0.9902 and RMSE = 0.0102). These results allow concluding that the proposed genetic equation corresponds well with experimental data and can be implemented in real industrial applications.

Keywords: cutting parameters, flank wear, genetic programming, hard turning

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Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

Abstract:

Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: Saeed Sayyad Hagh Shomar

Abstract:

Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using the users’ stated preference in questionnaire models users’ departure time choice affected by congestion pricing schemes in high traffic suburban entrance roads of Tehran. The results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: congestion pricing, departure time, modeling, travel timing, time of the day, transportation planning

Procedia PDF Downloads 298