Search results for: uncertainty simulation
3797 Radiosensitization Properties of Gold Nanoparticles in Brachytherapy of Uterus Cancer by High Dose Rate I-125 Seed: A Simulation Study by MCNPX and MCNP6 Codes
Authors: Elham Mansouri, Asghar Mesbahi
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Purpose: In the current study, we aimed to investigate the macroscopic and microscopic dose enhancement effect of metallic nanoparticles in interstitial brachytherapy of uterus cancer by Iodin-125 source using a nano-lattice model in MCNPX (5) and MCNP6.1 codes. Materials and methods: Based on a nano-lattice simulation model containing a radiation source and a tumor tissue with cellular compartments loaded with 7mg/g spherical nanoparticles (bismuth, gold, and gadolinium), the energy deposited by the secondary electrons in microscopic and macroscopic level was estimated. Results: The results show that the values of macroscopic DEF is higher than microscopic DEF values and the macroscopic DEF values decreases as a function of distance from the brachytherapy source surface. Also, the results revealed a remarkable discrepancy between the DEF and secondary electron spectra calculated by MCNPX (5) and MCNP6.1 codes, which could be justified by the difference in energy cut-off and electron transport algorithms of two codes. Conclusion: According to the both MCNPX (5) and MCNP6.1 outputs, it could be concluded that the presence of metallic nanoparticles in the tumor tissue of uteruscancer increases the physical effectiveness of brachytherapy by I-125 source. The results presented herein give a physical view of radiosensitization potential of different metallic nanoparticles and could be considered in design of analytical and experimental radiosensitization studies in tumor regions using various radiotherapy modalities in the presence of heavy nanomaterials.Keywords: MCNPX, MCNP6, nanoparticle, brachytherapy
Procedia PDF Downloads 1033796 Numerical Simulation of Free Surface Water Wave for the Flow Around NACA 0012 Hydrofoil and Wigley Hull Using VOF Method
Authors: Omar Imine, Mohammed Aounallah, Mustapha Belkadi
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Steady three-dimensional and two free surface waves generated by moving bodies are presented, the flow problem to be simulated is rich in complexity and poses many modeling challenges because of the existence of breaking waves around the ship hull, and because of the interaction of the two-phase flow with the turbulent boundary layer. The results of several simulations are reported. The first study was performed for NACA0012 of hydrofoil with different meshes, this section is analyzed at h/c= 1, 0345 for 2D. In the second simulation, a mathematically defined Wigley hull form is used to investigate the application of a commercial CFD code in prediction of the total resistance and its components from tangential and normal forces on the hull wetted surface. The computed resistance and wave profiles are used to estimate the coefficient of the total resistance for Wigley hull advancing in calm water under steady conditions. The commercial CFD software FLUENT version 12 is used for the computations in the present study. The calculated grid is established using the code computer GAMBIT 2.3.26. The shear stress k-ωSST model is used for turbulence modeling and the volume of the fluid technique is employed to simulate the free-surface motion. The second order upwind scheme is used for discretizing the convection terms in the momentum transport equations, the Modified HRICscheme for VOF discretization. The results obtained compare well with the experimental data.Keywords: free surface flows, breaking waves, boundary layer, Wigley hull, volume of fluid
Procedia PDF Downloads 3763795 Multi-Point Dieless Forming Product Defect Reduction Using Reliability-Based Robust Process Optimization
Authors: Misganaw Abebe Baye, Ji-Woo Park, Beom-Soo Kang
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The product quality of multi-point dieless forming (MDF) is identified to be dependent on the process parameters. Moreover, a certain variation of friction and material properties may have a substantially worse influence on the final product quality. This study proposed on how to compensate the MDF product defects by minimizing the sensitivity of noise parameter variations. This can be attained by reliability-based robust optimization (RRO) technique to obtain the optimal process setting of the controllable parameters. Initially two MDF Finite Element (FE) simulations of AA3003-H14 saddle shape showed a substantial amount of dimpling, wrinkling, and shape error. FE analyses are consequently applied on ABAQUS commercial software to obtain the correlation between the control process setting and noise variation with regard to the product defects. The best prediction models are chosen from the family of metamodels to swap the computational expensive FE simulation. Genetic algorithm (GA) is applied to determine the optimal process settings of the control parameters. Monte Carlo Analysis (MCA) is executed to determine how the noise parameter variation affects the final product quality. Finally, the RRO FE simulation and the experimental result show that the amendment of the control parameters in the final forming process leads to a considerably better-quality product.Keywords: dimpling, multi-point dieless forming, reliability-based robust optimization, shape error, variation, wrinkling
Procedia PDF Downloads 2543794 Investigating the Minimum RVE Size to Simulate Poly (Propylene carbonate) Composites Reinforced with Cellulose Nanocrystals as a Bio-Nanocomposite
Authors: Hamed Nazeri, Pierre Mertiny, Yongsheng Ma, Kajsa Duke
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The background of the present study is the use of environment-friendly biopolymer and biocomposite materials. Among the recently introduced biopolymers, poly (propylene carbonate) (PPC) has been gaining attention. This study focuses on the size of representative volume elements (RVE) in order to simulate PPC composites reinforced by cellulose nanocrystals (CNCs) as a bio-nanocomposite. Before manufacturing nanocomposites, numerical modeling should be implemented to explore and predict mechanical properties, which may be accomplished by creating and studying a suitable RVE. In other studies, modeling of composites with rod shaped fillers has been reported assuming that fillers are unidirectionally aligned. But, modeling of non-aligned filler dispersions is considerably more difficult. This study investigates the minimum RVE size to enable subsequent FEA modeling. The matrix and nano-fillers were modeled using the finite element software ABAQUS, assuming randomly dispersed fillers with a filler mass fraction of 1.5%. To simulate filler dispersion, a Monte Carlo technique was employed. The numerical simulation was implemented to find composite elastic moduli. After commencing the simulation with a single filler particle, the number of particles was increased to assess the minimum number of filler particles that satisfies the requirements for an RVE, providing the composite elastic modulus in a reliable fashion.Keywords: biocomposite, Monte Carlo method, nanocomposite, representative volume element
Procedia PDF Downloads 4433793 Memristor-A Promising Candidate for Neural Circuits in Neuromorphic Computing Systems
Authors: Juhi Faridi, Mohd. Ajmal Kafeel
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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS. Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems
Procedia PDF Downloads 1743792 Control and Automation of Fluid at Micro/Nano Scale for Bio-Analysis Applications
Authors: Reza Hadjiaghaie Vafaie, Sevda Givtaj
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Automation and control of biological samples and solutions at the microscale is a major advantage for biochemistry analysis and biological diagnostics. Despite the known potential of miniaturization in biochemistry and biomedical applications, comparatively little is known about fluid automation and control at the microscale. Here, we study the electric field effect inside a fluidic channel and proper electrode structures with different patterns proposed to form forward, reversal, and rotational flows inside the channel. The simulation results confirmed that the ac electro-thermal flow is efficient for the control and automation of high-conductive solutions. In this research, the fluid pumping and mixing effects were numerically studied by solving physic-coupled electric, temperature, hydrodynamic, and concentration fields inside a microchannel. From an experimental point of view, the electrode structures are deposited on a silicon substrate and bonded to a PDMS microchannel to form a microfluidic chip. The motions of fluorescent particles in pumping and mixing modes were captured by using a CCD camera. By measuring the frequency response of the fluid and exciting the electrodes with the proper voltage, the fluid motions (including pumping and mixing effects) are observed inside the channel through the CCD camera. Based on the results, there is good agreement between the experimental and simulation studies.Keywords: microfluidic, nano/micro actuator, AC electrothermal, Reynolds number, micropump, micromixer, microfabrication, mass transfer, biomedical applications
Procedia PDF Downloads 793791 Estimations of Spectral Dependence of Tropospheric Aerosol Single Scattering Albedo in Sukhothai, Thailand
Authors: Siriluk Ruangrungrote
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Analyses of available data from MFR-7 measurement were performed and discussed on the study of tropospheric aerosol and its consequence in Thailand. Since, ASSA (w) is one of the most important parameters for a determination of aerosol effect on radioactive forcing. Here the estimation of w was directly determined in terms of the ratio of aerosol scattering optical depth to aerosol extinction optical depth (ωscat/ωext) without any utilization of aerosol computer code models. This is of benefit for providing the elimination of uncertainty causing by the modeling assumptions and the estimation of actual aerosol input data. Diurnal w of 5 cloudless-days in winter and early summer at 5 distinct wavelengths of 415, 500, 615, 673 and 870 nm with the consideration of Rayleigh scattering and atmospheric column NO2 and Ozone contents were investigated, respectively. Besides, the tendency of spectral dependence of ω representing two seasons was observed. The characteristic of spectral results reveals that during wintertime the atmosphere of the inland rural vicinity for the period of measurement possibly dominated with a lesser amount of soil dust aerosols loading than one in early summer. Hence, the major aerosol loading particularly in summer was subject to a mixture of both soil dust and biomass burning aerosols.Keywords: aerosol scattering optical depth, aerosol extinction optical depth, biomass burning aerosol, soil dust aerosol
Procedia PDF Downloads 4053790 Linkages between Postponement Strategies and Flexibility in Organizations
Authors: Polycarpe Feussi
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Globalization, technological and customer increasing changes, amongst other drivers, result in higher levels of uncertainty and unpredictability for organizations. In order for organizations to cope with the uncertain and fast-changing economic and business environment, these organizations need to innovate in order to achieve flexibility. In simple terms, the organizations must develop strategies leading to the ability of these organizations to provide horizontal information connections across the supply chain to create and deliver products that meet customer needs by synchronization of customer demands with product creation. The generated information will create efficiency and effectiveness throughout the whole supply chain regarding production, storage, and distribution, as well as eliminating redundant activities and reduction in response time. In an integrated supply chain, spanning activities include coordination with distributors and suppliers. This paper explains how through postponement strategies, flexibility can be achieved in an organization. In order to achieve the above, a thorough literature review was conducted via the search of online websites that contains material from scientific journal data-bases, articles, and textbooks on the subject of postponement and flexibility. The findings of the research are found in the last part of the paper. The first part introduces the concept of postponement and its importance in supply chain management. The second part of the paper provides the methodology used in the process of writing the paper.Keywords: postponement strategies, supply chain management, flexibility, logistics
Procedia PDF Downloads 1933789 A Three-Dimensional (3D) Numerical Study of Roofs Shape Impact on Air Quality in Urban Street Canyons with Tree Planting
Authors: Bouabdellah Abed, Mohamed Bouzit, Lakhdar Bouarbi
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The objective of this study is to investigate numerically the effect of roof shaped on wind flow and pollutant dispersion in a street canyon with one row of trees of pore volume, Pvol = 96%. A three-dimensional computational fluid dynamics (CFD) model for evaluating air flow and pollutant dispersion within an urban street canyon using Reynolds-averaged Navier–Stokes (RANS) equations and the k-Epsilon EARSM turbulence model as close of the equation system. The numerical model is performed with ANSYS-CFX code. Vehicle emissions were simulated as double line sources along the street. The numerical model was validated against the wind tunnel experiment. Having established this, the wind flow and pollutant dispersion in urban street canyons of six roof shapes are simulated. The numerical simulation agrees reasonably with the wind tunnel data. The results obtained in this work, indicate that the flow in 3D domain is more complicated, this complexity is increased with presence of tree and variability of the roof shapes. The results also indicated that the largest pollutant concentration level for two walls (leeward and windward wall) is observed with the upwind wedge-shaped roof. But the smallest pollutant concentration level is observed with the dome roof-shaped. The results also indicated that the corners eddies provide additional ventilation and lead to lower traffic pollutant concentrations at the street canyon ends.Keywords: street canyon, pollutant dispersion, trees, building configuration, numerical simulation, k-Epsilon EARSM
Procedia PDF Downloads 3663788 Seawater Intrusion in the Coastal Aquifer of Wadi Nador (Algeria)
Authors: Abdelkader Hachemi & Boualem Remini
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Seawater intrusion is a significant challenge faced by coastal aquifers in the Mediterranean basin. This study aims to determine the position of the sharp interface between seawater and freshwater in the aquifer of Wadi Nador, located in the Wilaya of Tipaza, Algeria. A numerical areal sharp interface model using the finite element method is developed to investigate the spatial and temporal behavior of seawater intrusion. The aquifer is assumed to be homogeneous and isotropic. The simulation results are compared with geophysical prospection data obtained through electrical methods in 2011 to validate the model. The simulation results demonstrate a good agreement with the geophysical prospection data, confirming the accuracy of the sharp interface model. The position of the sharp interface in the aquifer is found to be approximately 1617 meters from the sea. Two scenarios are proposed to predict the interface position for the year 2024: one without pumping and the other with pumping. The results indicate a noticeable retreat of the sharp interface position in the first scenario, while a slight decline is observed in the second scenario. The findings of this study provide valuable insights into the dynamics of seawater intrusion in the Wadi Nador aquifer. The predicted changes in the sharp interface position highlight the potential impact of pumping activities on the aquifer's vulnerability to seawater intrusion. This study emphasizes the importance of implementing measures to manage and mitigate seawater intrusion in coastal aquifers. The sharp interface model developed in this research can serve as a valuable tool for assessing and monitoring the vulnerability of aquifers to seawater intrusion.Keywords: seawater, intrusion, sharp interface, Algeria
Procedia PDF Downloads 753787 Temporal and Spatial Distribution Prediction of Patinopecten yessoensis Larvae in Northern China Yellow Sea
Authors: RuiJin Zhang, HengJiang Cai, JinSong Gui
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It takes Patinopecten yessoensis larvae more than 20 days from spawning to settlement. Due to the natural environmental factors such as current, Patinopecten yessoensis larvae are transported to a distance more than hundreds of kilometers, leading to a high instability of their spatial and temporal distribution and great difficulties in the natural spat collection. Therefore predicting the distribution is of great significance to improve the operating efficiency of the collecting. Hydrodynamic model of Northern China Yellow Sea was established and the motions equations of physical oceanography and verified by the tidal harmonic constants and the measured data velocities of Dalian Bay. According to the passivity drift characteristics of the larvae, combined with the hydrodynamic model and the particle tracking model, the spatial and temporal distribution prediction model was established and the spatial and temporal distribution of the larvae under the influence of flow and wind were simulated. It can be concluded from the model results: ocean currents have greatest impacts on the passive drift path and diffusion of Patinopecten yessoensis larvae; the impact of wind is also important, which changed the direction and speed of the drift. Patinopecten yessoensis larvae were generated in the sea along Zhangzi Island and Guanglu-Dachangshan Island, but after two months, with the impact of wind and currents, the larvae appeared in the west of Dalian and the southern of Lvshun, and even in Bohai Bay. The model results are consistent with the relevant literature on qualitative analysis, and this conclusion explains where the larvae come from in the perspective of numerical simulation.Keywords: numerical simulation, Patinopecten yessoensis larvae, predicting model, spatial and temporal distribution
Procedia PDF Downloads 3043786 Vibration Analysis and Optimization Design of Ultrasonic Horn
Authors: Kuen Ming Shu, Ren Kai Ho
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Ultrasonic horn has the functions of amplifying amplitude and reducing resonant impedance in ultrasonic system. Its primary function is to amplify deformation or velocity during vibration and focus ultrasonic energy on the small area. It is a crucial component in design of ultrasonic vibration system. There are five common design methods for ultrasonic horns: analytical method, equivalent circuit method, equal mechanical impedance, transfer matrix method, finite element method. In addition, the general optimization design process is to change the geometric parameters to improve a single performance. Therefore, in the general optimization design process, we couldn't find the relation of parameter and objective. However, a good optimization design must be able to establish the relationship between input parameters and output parameters so that the designer can choose between parameters according to different performance objectives and obtain the results of the optimization design. In this study, an ultrasonic horn provided by Maxwide Ultrasonic co., Ltd. was used as the contrast of optimized ultrasonic horn. The ANSYS finite element analysis (FEA) software was used to simulate the distribution of the horn amplitudes and the natural frequency value. The results showed that the frequency for the simulation values and actual measurement values were similar, verifying the accuracy of the simulation values. The ANSYS DesignXplorer was used to perform Response Surface optimization, which could shows the relation of parameter and objective. Therefore, this method can be used to substitute the traditional experience method or the trial-and-error method for design to reduce material costs and design cycles.Keywords: horn, natural frequency, response surface optimization, ultrasonic vibration
Procedia PDF Downloads 1173785 Internet of Things Networks: Denial of Service Detection in Constrained Application Protocol Using Machine Learning Algorithm
Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio
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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.Keywords: algorithm, CoAP, DoS, IoT, machine learning
Procedia PDF Downloads 803784 A Two-Stage Bayesian Variable Selection Method with the Extension of Lasso for Geo-Referenced Data
Authors: Georgiana Onicescu, Yuqian Shen
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Due to the complex nature of geo-referenced data, multicollinearity of the risk factors in public health spatial studies is a commonly encountered issue, which leads to low parameter estimation accuracy because it inflates the variance in the regression analysis. To address this issue, we proposed a two-stage variable selection method by extending the least absolute shrinkage and selection operator (Lasso) to the Bayesian spatial setting, investigating the impact of risk factors to health outcomes. Specifically, in stage I, we performed the variable selection using Bayesian Lasso and several other variable selection approaches. Then, in stage II, we performed the model selection with only the selected variables from stage I and compared again the methods. To evaluate the performance of the two-stage variable selection methods, we conducted a simulation study with different distributions for the risk factors, using geo-referenced count data as the outcome and Michigan as the research region. We considered the cases when all candidate risk factors are independently normally distributed, or follow a multivariate normal distribution with different correlation levels. Two other Bayesian variable selection methods, Binary indicator, and the combination of Binary indicator and Lasso were considered and compared as alternative methods. The simulation results indicated that the proposed two-stage Bayesian Lasso variable selection method has the best performance for both independent and dependent cases considered. When compared with the one-stage approach, and the other two alternative methods, the two-stage Bayesian Lasso approach provides the highest estimation accuracy in all scenarios considered.Keywords: Lasso, Bayesian analysis, spatial analysis, variable selection
Procedia PDF Downloads 1443783 Hybrid Structure Learning Approach for Assessing the Phosphate Laundries Impact
Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed
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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis
Procedia PDF Downloads 1283782 Performance Evaluation of Diverging Diamond Interchange Compared to Single Point Diamond Interchange in Riyadh City
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
Procedia PDF Downloads 2583781 Determinants of International Volatility Passthroughs of Agricultural Commodities: A Panel Analysis of Developing Countries
Authors: Tetsuji Tanaka, Jin Guo
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The extant literature has not succeeded in uncovering the common determinants of price volatility transmissions of agricultural commodities from international to local markets, and further, has rarely investigated the role of self-sufficiency measures in the context of national food security. We analyzed various factors to determine the degree of price volatility transmissions of wheat, rice, and maize between world and domestic markets using GARCH models with dynamic conditional correlation (DCC) specifications and panel-feasible generalized least square models. We found that the grain autarky system has the potential to diminish volatility pass-throughs for three grain commodities. Furthermore, it was discovered that the substitutive commodity consumption behavior between maize and wheat buffers the volatility transmissions of both, but rice does not function as a transmission-relieving element, either for the volatilities of wheat or maize. The effectiveness of grain consumption substitution to insulate the pass-throughs from global markets is greater than that of cereal self-sufficiency. These implications are extremely beneficial for developing governments to protect their domestic food markets from uncertainty in foreign countries and as such, improves food security.Keywords: food security, GARCH, grain self-sufficiency, volatility transmission
Procedia PDF Downloads 1553780 A Techno-Economic Simulation Model to Reveal the Relevance of Construction Process Impact Factors for External Thermal Insulation Composite System (ETICS)
Authors: Virgo Sulakatko
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The reduction of energy consumption of the built environment has been one of the topics tackled by European Commission during the last decade. Increased energy efficiency requirements have increased the renovation rate of apartment buildings covered with External Thermal Insulation Composite System (ETICS). Due to fast and optimized application process, a large extent of quality assurance is depending on the specific activities of artisans and are often not controlled. The on-site degradation factors (DF) have the technical influence to the façade and cause future costs to the owner. Besides the thermal conductivity, the building envelope needs to ensure the mechanical resistance and stability, fire-, noise-, corrosion and weather protection, and long-term durability. As the shortcomings of the construction phase become problematic after some years, the common value of the renovation is reduced. Previous work on the subject has identified and rated the relevance of DF to the technical requirements and developed a method to reveal the economic value of repair works. The future costs can be traded off to increased the quality assurance during the construction process. The proposed framework is describing the joint simulation of the technical importance and economic value of the on-site DFs of ETICS. The model is providing new knowledge to improve the resource allocation during the construction process by enabling to identify and diminish the most relevant degradation factors and increase economic value to the owner.Keywords: ETICS, construction technology, construction management, life cycle costing
Procedia PDF Downloads 4193779 Fuzzy Total Factor Productivity by Credibility Theory
Authors: Shivi Agarwal, Trilok Mathur
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This paper proposes the method to measure the total factor productivity (TFP) change by credibility theory for fuzzy input and output variables. Total factor productivity change has been widely studied with crisp input and output variables, however, in some cases, input and output data of decision-making units (DMUs) can be measured with uncertainty. These data can be represented as linguistic variable characterized by fuzzy numbers. Malmquist productivity index (MPI) is widely used to estimate the TFP change by calculating the total factor productivity of a DMU for different time periods using data envelopment analysis (DEA). The fuzzy DEA (FDEA) model is solved using the credibility theory. The results of FDEA is used to measure the TFP change for fuzzy input and output variables. Finally, numerical examples are presented to illustrate the proposed method to measure the TFP change input and output variables. The suggested methodology can be utilized for performance evaluation of DMUs and help to assess the level of integration. The methodology can also apply to rank the DMUs and can find out the DMUs that are lagging behind and make recommendations as to how they can improve their performance to bring them at par with other DMUs.Keywords: chance-constrained programming, credibility theory, data envelopment analysis, fuzzy data, Malmquist productivity index
Procedia PDF Downloads 3653778 Investigating The Effect Of Convection On The Rating Of Buried Cables Using The Finite Element Method
Authors: Sandy J. M. Balla, Jerry J. Walker, Isaac K. Kyere
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The heat transfer coefficient at the soil–air interface is important in calculating underground cable ampacity when convection occurs. Calculating the heat transfer coefficient accurately is complex because of the temperature variations at the earth's surface. This paper presents the effect of convection heat flow across the ground surface on the rating of three single-core, 132kV, XLPE cables buried underground. The Finite element method (FEM) is a numerical analysis technique used to determine the cable rating of buried cables under installation conditions that are difficult to support when using the analytical method. This study demonstrates the use of FEM to investigate the effect of convection on the rating ofburied cables in flat formation using QuickField finite element simulation software. As a result, developing a model to simulate this type of situation necessitates important considerations such as the following boundary conditions: burial depth, soil thermal resistivity, and soil temperature, which play an important role in the simulation's accuracy and reliability. The results show that when the ground surface is taken as a convection interface, the conductor temperature rises and may exceed the maximum permissible temperature when rated current flows. This is because the ground surface acts as a convection interface between the soil and the air (fluid). This result correlates and is compared with the rating obtained using the IEC60287 analytical method, which is based on the condition that the ground surface is an isotherm.Keywords: finite element method, convection, buried cables, steady-state rating
Procedia PDF Downloads 1313777 Evolutionary Swarm Robotics: Dynamic Subgoal-Based Path Formation and Task Allocation for Exploration and Navigation in Unknown Environments
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
Procedia PDF Downloads 423776 Beam Coding with Orthogonal Complementary Golay Codes for Signal to Noise Ratio Improvement in Ultrasound Mammography
Authors: Y. Kumru, K. Enhos, H. Köymen
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In this paper, we report the experimental results on using complementary Golay coded signals at 7.5 MHz to detect breast microcalcifications of 50 µm size. Simulations using complementary Golay coded signals show perfect consistence with the experimental results, confirming the improved signal to noise ratio for complementary Golay coded signals. For improving the success on detecting the microcalcifications, orthogonal complementary Golay sequences having cross-correlation for minimum interference are used as coded signals and compared to tone burst pulse of equal energy in terms of resolution under weak signal conditions. The measurements are conducted using an experimental ultrasound research scanner, Digital Phased Array System (DiPhAS) having 256 channels, a phased array transducer with 7.5 MHz center frequency and the results obtained through experiments are validated by Field-II simulation software. In addition, to investigate the superiority of coded signals in terms of resolution, multipurpose tissue equivalent phantom containing series of monofilament nylon targets, 240 µm in diameter, and cyst-like objects with attenuation of 0.5 dB/[MHz x cm] is used in the experiments. We obtained ultrasound images of monofilament nylon targets for the evaluation of resolution. Simulation and experimental results show that it is possible to differentiate closely positioned small targets with increased success by using coded excitation in very weak signal conditions.Keywords: coded excitation, complementary golay codes, DiPhAS, medical ultrasound
Procedia PDF Downloads 2633775 Impact of Large Scale Solar Power Plant on Airports and Aviation
Authors: Munirah Stapah Salleh, Ahmad Rosly Abbas, Sazalina Zakaria, Nur Iffika Ruslan, Nurfaziera Rahim
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One of the areas that require a massive amount of energy is the airport. Hence, several airports have increased their reliance on renewable energy, specifically solar photovoltaic (PV) systems, to solve the issue. The interest regarding the installations of airport-based solar farms caught much attention. This, at the same time, helps to minimize the reliance on conventional energy sources that are fossil-based. However, many concerns were raised on the solar PV systems, especially on the effect of potential glare occurrence to the pilots during their flies. This paper will be discussing both the positive and negative impact of the large scale solar power plant on airports and aviation. Installing the large scale solar have negative impacts on airport and aviation, such as physical collision hazards, potential interference, or voltage problems with aircraft navigational and surveillance equipment as well as potential glare. On the positive side, it helps to lower environmental footprint, acquiring less energy from the utility provider, which are traditionally highly relying on other energy sources that have larger effects on the environment, and, last but not least, reduce the power supply uncertainty.Keywords: solar photovoltaic systems, large scale solar, airport, glare effects
Procedia PDF Downloads 2133774 Using Business Simulations and Game-Based Learning for Enterprise Resource Planning Implementation Training
Authors: Carin Chuang, Kuan-Chou Chen
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An Enterprise Resource Planning (ERP) system is an integrated information system that supports the seamless integration of all the business processes of a company. Implementing an ERP system can increase efficiencies and decrease the costs while helping improve productivity. Many organizations including large, medium and small-sized companies have already adopted an ERP system for decades. Although ERP system can bring competitive advantages to organizations, the lack of proper training approach in ERP implementation is still a major concern. Organizations understand the importance of ERP training to adequately prepare managers and users. The low return on investment, however, for the ERP training makes the training difficult for knowledgeable workers to transfer what is learned in training to the jobs at workplace. Inadequate and inefficient ERP training limits the value realization and success of an ERP system. That is the need to call for a profound change and innovation for ERP training in both workplace at industry and the Information Systems (IS) education in academia. The innovated ERP training approach can improve the users’ knowledge in business processes and hands-on skills in mastering ERP system. It also can be instructed as educational material for IS students in universities. The purpose of the study is to examine the use of ERP simulation games via the ERPsim system to train the IS students in learning ERP implementation. The ERPsim is the business simulation game developed by ERPsim Lab at HEC Montréal, and the game is a real-life SAP (Systems Applications and Products) ERP system. The training uses the ERPsim system as the tool for the Internet-based simulation games and is designed as online student competitions during the class. The competitions involve student teams with the facilitation of instructor and put the students’ business skills to the test via intensive simulation games on a real-world SAP ERP system. The teams run the full business cycle of a manufacturing company while interacting with suppliers, vendors, and customers through sending and receiving orders, delivering products and completing the entire cash-to-cash cycle. To learn a range of business skills, student needs to adopt individual business role and make business decisions around the products and business processes. Based on the training experiences learned from rounds of business simulations, the findings show that learners have reduced risk in making mistakes that help learners build self-confidence in problem-solving. In addition, the learners’ reflections from their mistakes can speculate the root causes of the problems and further improve the efficiency of the training. ERP instructors teaching with the innovative approach report significant improvements in student evaluation, learner motivation, attendance, engagement as well as increased learner technology competency. The findings of the study can provide ERP instructors with guidelines to create an effective learning environment and can be transferred to a variety of other educational fields in which trainers are migrating towards a more active learning approach.Keywords: business simulations, ERP implementation training, ERPsim, game-based learning, instructional strategy, training innovation
Procedia PDF Downloads 1393773 Conformity and Differentiation in CSR Practices on Capital Market Performance: Empirical Evidence from Stock Liquidity and Price Crash Risk
Authors: Jie Zhang, Chaomin Zhang, Jihua Zhang, Haitong Li
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Using the theory of optimal distinctiveness, this study examines the effects of conformity and differentiation within corporate social responsibility (CSR) practices on capital market performance. Analysing data from Chinese A-share listed firms from 2007 to 2022, this paper demonstrates that when firms conform to the expected scope of CSR, such behaviour enhances investor attention and market acceptance, thereby boosting stock liquidity. Conversely, emphasising differentiation in CSR practices more effectively mitigates stock price crash risk by addressing principal–agent problems and decreasing information asymmetry. This paper also investigates how organisational and environmental factors moderate the relationship between conformity and differentiation in CSR practices and their impact on capital market performance. The results also show that the influence of conformity on stock liquidity is accentuated in smaller firms and environments with stringent legal oversight. By contrast, the benefits of differentiation in reducing stock price crash risk are amplified in firms with robust corporate governance and markets characterised by high uncertainty.Keywords: corporate social responsibility, social responsibility practices, capital market performance, optimal distinctiveness
Procedia PDF Downloads 203772 A Molecular-Level Study of Combining the Waste Polymer and High-Concentration Waste Cooking Oil as an Additive on Reclamation of Aged Asphalt Pavement
Authors: Qiuhao Chang, Liangliang Huang, Xingru Wu
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In the United States, over 90% of the roads are paved with asphalt. The aging of asphalt is the most serious problem that causes the deterioration of asphalt pavement. Waste cooking oils (WCOs) have been found they can restore the properties of aged asphalt and promote the reuse of aged asphalt pavement. In our previous study, it was found the optimal WCO concentration to restore the aged asphalt sample should be in the range of 10~15 wt% of the aged asphalt sample. After the WCO concentration exceeds 15 wt%, as the WCO concentration increases, some important properties of the asphalt sample can be weakened by the addition of WCO, such as cohesion energy density, surface free energy density, bulk modulus, shear modulus, etc. However, maximizing the utilization of WCO can create environmental and economic benefits. Therefore, in this study, a new idea about using the waste polymer is another additive to restore the WCO modified asphalt that contains a high concentration of WCO (15-25 wt%) is proposed, which has never been reported before. In this way, both waste polymer and WCO can be utilized. The molecular dynamics simulation is used to study the effect of waste polymer on properties of WCO modified asphalt and understand the corresponding mechanism at the molecular level. The radial distribution function, self-diffusion, cohesion energy density, surface free energy density, bulk modulus, shear modulus, adhesion energy between asphalt and aggregate are analyzed to validate the feasibility of combining the waste polymer and WCO to restore the aged asphalt. Finally, the optimal concentration of waste polymer and WCO are determined.Keywords: reclaim aged asphalt pavement, waste cooking oil, waste polymer, molecular dynamics simulation
Procedia PDF Downloads 2203771 Selection of Designs in Ordinal Regression Models under Linear Predictor Misspecification
Authors: Ishapathik Das
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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs
Procedia PDF Downloads 3933770 Structured Cross System Planning and Control in Modular Production Systems by Using Agent-Based Control Loops
Authors: Simon Komesker, Achim Wagner, Martin Ruskowski
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In times of volatile markets with fluctuating demand and the uncertainty of global supply chains, flexible production systems are the key to an efficient implementation of a desired production program. In this publication, the authors present a holistic information concept taking into account various influencing factors for operating towards the global optimum. Therefore, a strategy for the implementation of multi-level planning for a flexible, reconfigurable production system with an alternative production concept in the automotive industry is developed. The main contribution of this work is a system structure mixing central and decentral planning and control evaluated in a simulation framework. The information system structure in current production systems in the automotive industry is rigidly hierarchically organized in monolithic systems. The production program is created rule-based with the premise of achieving uniform cycle time. This program then provides the information basis for execution in subsystems at the station and process execution level. In today's era of mixed-(car-)model factories, complex conditions and conflicts arise in achieving logistics, quality, and production goals. There is no provision for feedback loops of results from the process execution level (resources) and process supporting (quality and logistics) systems and reconsideration in the planning systems. To enable a robust production flow, the complexity of production system control is artificially reduced by the line structure and results, for example in material-intensive processes (buffers and safety stocks - two container principle also for different variants). The limited degrees of freedom of line production have produced the principle of progress figure control, which results in one-time sequencing, sequential order release, and relatively inflexible capacity control. As a result, modularly structured production systems such as modular production according to known approaches with more degrees of freedom are currently difficult to represent in terms of information technology. The remedy is an information concept that supports cross-system and cross-level information processing for centralized and decentralized decision-making. Through an architecture of hierarchically organized but decoupled subsystems, the paradigm of hybrid control is used, and a holonic manufacturing system is offered, which enables flexible information provisioning and processing support. In this way, the influences from quality, logistics, and production processes can be linked holistically with the advantages of mixed centralized and decentralized planning and control. Modular production systems also require modularly networked information systems with semi-autonomous optimization for a robust production flow. Dynamic prioritization of different key figures between subsystems should lead the production system to an overall optimum. The tasks and goals of quality, logistics, process, resource, and product areas in a cyber-physical production system are designed as an interconnected multi-agent-system. The result is an alternative system structure that executes centralized process planning and decentralized processing. An agent-based manufacturing control is used to enable different flexibility and reconfigurability states and manufacturing strategies in order to find optimal partial solutions of subsystems, that lead to a near global optimum for hybrid planning. This allows a robust near to plan execution with integrated quality control and intralogistics.Keywords: holonic manufacturing system, modular production system, planning, and control, system structure
Procedia PDF Downloads 1693769 Technical and Economic Analysis of Smart Micro-Grid Renewable Energy Systems: An Applicable Case Study
Authors: M. A. Fouad, M. A. Badr, Z. S. Abd El-Rehim, Taher Halawa, Mahmoud Bayoumi, M. M. Ibrahim
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Renewable energy-based micro-grids are presently attracting significant consideration. The smart grid system is presently considered a reliable solution for the expected deficiency in the power required from future power systems. The purpose of this study is to determine the optimal components sizes of a micro-grid, investigating technical and economic performance with the environmental impacts. The micro grid load is divided into two small factories with electricity, both on-grid and off-grid modes are considered. The micro-grid includes photovoltaic cells, back-up diesel generator wind turbines, and battery bank. The estimated load pattern is 76 kW peak. The system is modeled and simulated by MATLAB/Simulink tool to identify the technical issues based on renewable power generation units. To evaluate system economy, two criteria are used: the net present cost and the cost of generated electricity. The most feasible system components for the selected application are obtained, based on required parameters, using HOMER simulation package. The results showed that a Wind/Photovoltaic (W/PV) on-grid system is more economical than a Wind/Photovoltaic/Diesel/Battery (W/PV/D/B) off-grid system as the cost of generated electricity (COE) is 0.266 $/kWh and 0.316 $/kWh, respectively. Considering the cost of carbon dioxide emissions, the off-grid will be competitive to the on-grid system as COE is found to be (0.256 $/kWh, 0.266 $/kWh), for on and off grid systems.Keywords: renewable energy sources, micro-grid system, modeling and simulation, on/off grid system, environmental impacts
Procedia PDF Downloads 2703768 Understanding Factor Influence in Mask-Wearing Intention Onboard Airplanes during COVID-19: Attitude as a Mediator
Authors: Jing Yu Pan, Dahai Liu
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Airlines in the US have taken protective measures to battle the COVID-19 pandemic, with a mask mandate being the most important one, especially in the aircraft cabin. As the industry is recovering from the pandemic, mask-wearing will eventually become a personal choice during flight. Nevertheless, COVID-19 will continue to create uncertainty for a long time into the future, making it necessary to understand the attitude and voluntary use of masks by air travelers on airplanes even after masks are no longer mandatory. This study aimed to understand the relationship between demographic characteristics and mask-wearing intention in the US. For age, gender, income, educational, and ethnicity groups, this study examined three factors – subjective norms, risk avoidance, and information seeking and their influence on the mask-wearing intention onboard airplanes during COVID-19 and whether or not attitude toward masks was an important mediator. The results show that all demographic factors except gender could help to explain the group variations in factor impact and the mediating effect in mask-wearing intentions. In particular, Asian travelers had mask-wearing intentions that were not affected by attitude either directly or indirectly. These findings provide useful implications to enhance the health and safety of air travelers, especially in the US, where opposing views toward mask-wearing still widely exist.Keywords: COVID-19, passenger demographics, aircraft cabin, mask-wearing intention, attitude as mediator
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