Search results for: model of postural system behavior
29612 Emissivity Analysis of Hot-Dip Galvanized Steel in Fire
Authors: Christian Gaigl, Martin Mensinger
Abstract:
Once a fire resistance rating is necessary, it has to be proofed that the load bearing behavior of a steel construction under the exposure of fire still fits the static demands. High costs of passive fire protection, which satisfies the requirements, frequently result in a concrete solution. To optimize these expenses, one method is to determine the critical temperature according to the Eurocode DIN EN 1993-1-2. For this purpose, positive effects of hot-dip galvanized surface layers on the temperature development of steel members in the accidental situation of fire exposure has been investigated. The test results show a significant better heating behavior of hot-dip galvanized steel components compared to normal steel specimen. This leads in many cases to a R30 (30 minutes of ISO-fire) fire protection requirement of unprotected steel members and therefore to an economic added value.Keywords: fire resistance, hot-dip galvanizing, steel constructions, R30 requirement, emissivity
Procedia PDF Downloads 26229611 Surface Morphology and Wetting Behavior of the Aspidiotus spp. Scale Covers
Authors: Meril Kate Mariano, Billy Joel Almarinez Divina Amalin, Jose Isagani Janairo
Abstract:
The scale insects Aspidiotus destructor and Aspidiotus rigidus exhibit notable scale covers made of wax which provides protection against water loss and is capable to resist wetting, thus making them a desirable model for biomimetic designs. Their waxy covers enable them to infest mainly leaves of coconut trees despite the harsh wind and rain. This study aims to describe and compare the micro morphological characters on the surfaces of their scale covers consequently, how these micro structures affect their wetting properties. Scanning electron microscope was used for the surface characterization while an optical contact angle meter was employed in the wetting measurement. The scale cover of A. destructor is composed of multiple overlapping layers of wax that is arranged regularly while that of A. rigidus is composed of a uniform layer of wax with much more prominent wax ribbons irregularly arranged compared to the former. The protrusions found on the two organisms are formed by the wax ribbons that differ in arrangement with their height being A. destructor (3.57+1.29) < A. rigidus (4.23+1.22) and their density A. destructor (15+2.94) < A. rigidus (18.33+2.64). These morphological measurements could affect the contact angle (CA θ) measurement of A. destructor (102.66+9.78°) < A. rigidus (102.77 + 11.01°) wherein the assessment that the interaction of the liquid to the microstructures of the substrate is a large factor in the wetting properties of the insect scales is realized. The calculated surface free energy of A. destructor (38.47 mJ/m²) > A. rigidus (31.02 mJ/m²) shows inverse proportionality with the CA measurement. The dispersive interaction between the surface and liquid is more prevalent compared to the polar interaction for both Aspidiotus species, which was observed using the Fowkes method. The results of this study have possible applications to be a potential biomimetic design for various industries such as textiles and coatings.Keywords: Aspidiotus spp., biomimetics, contact angle, surface characterization, wetting behavior
Procedia PDF Downloads 12129610 A Fully Coupled Thermo-Hydraulic Mechanical Elastoplastic Damage Constitutive Model for Porous Fractured Medium during CO₂ Injection
Authors: Nikolaos Reppas, Yilin Gui
Abstract:
A dual-porosity finite element-code will be presented for the stability analysis of the wellbore during CO₂ injection. An elastoplastic damage response will be considered to the model. The Finite Element Method (FEM) will be validated using experimental results from literature or from experiments that are planned to be undertaken at Newcastle University. The main target of the research paper is to present a constitutive model that can help industries to safely store CO₂ in geological rock formations and forecast any changes on the surrounding rock of the wellbore. The fully coupled elastoplastic damage Thermo-Hydraulic-Mechanical (THM) model will determine the pressure and temperature of the injected CO₂ as well as the size of the radius of the wellbore that can make the Carbon Capture and Storage (CCS) procedure more efficient.Keywords: carbon capture and storage, Wellbore stability, elastoplastic damage response for rock, constitutive THM model, fully coupled thermo-hydraulic-mechanical model
Procedia PDF Downloads 17429609 Model Updating Based on Modal Parameters Using Hybrid Pattern Search Technique
Authors: N. Guo, C. Xu, Z. C. Yang
Abstract:
In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search
Procedia PDF Downloads 16129608 Optimal Operation of a Photovoltaic Induction Motor Drive Water Pumping System
Authors: Nelson K. Lujara
Abstract:
The performance characteristics of a photovoltaic induction motor drive water pumping system with and without maximum power tracker is analyzed and presented. The analysis is done through determination and assessment of critical loss components in the system using computer aided design (CAD) tools for optimal operation of the system. The results can be used to formulate a well-calibrated computer aided design package of photovoltaic water pumping systems based on the induction motor drive. The results allow the design engineer to pre-determine the flow rate and efficiency of the system to suit particular application.Keywords: photovoltaic, water pumping, losses, induction motor
Procedia PDF Downloads 30229607 Optimizing Fire Suppression Time in Buildings by Forming a Fire Feedback Loop
Authors: Zhdanova A. O., Volkov R. S., Kuznetsov G. V., Strizhak P. A.
Abstract:
Fires in different types of facilities are a serious problem worldwide.It is still an unaccomplished science and technology objective to establish the minimum number and type of sensors in automatic systems of compartment fire suppression which would turn the fire-extinguishing agent spraying on and off in real time depending on the state of the fire, minimize the amount of agent applied, delay time in fire suppression and system response, as well as the time of combustion suppression. Based on the results of experimental studies, the conclusion was made that it is reasonable to use a gas analysis system and heat sensors (in the event of their prior activation) to determine the effectiveness of fire suppression (fire-extinguishing composition interacts with the fire). Thus, the concentration of CO in the interaction of the firefighting liquid with the fire increases to 0.7–1.2%, which indicates a slowdown in the flame combustion, and heat sensors stop responding at a gas medium temperature below 80 ºC, which shows a gradual decrease in the heat release from the fire. The evidence from this study suggests that the information received from the video recording equipment (video camera) should be used in real time as an additional parameter confirming fire suppression. Research was supported by Russian Science Foundation (project No 21-19-00009, https://rscf.ru/en/project/21-19-00009/).Keywords: compartment fires, fire suppression, continuous control of fire behavior, feedback systems
Procedia PDF Downloads 12929606 Improvement of the Q-System Using the Rock Engineering System: A Case Study of Water Conveyor Tunnel of Azad Dam
Authors: Sahand Golmohammadi, Sana Hosseini Shirazi
Abstract:
Because the status and mechanical parameters of discontinuities in the rock mass are included in the calculations, various methods of rock engineering classification are often used as a starting point for the design of different types of structures. The Q-system is one of the most frequently used methods for stability analysis and determination of support systems of underground structures in rock, including tunnel. In this method, six main parameters of the rock mass, namely, the rock quality designation (RQD), joint set number (Jn), joint roughness number (Jr), joint alteration number (Ja), joint water parameter (Jw) and stress reduction factor (SRF) are required. In this regard, in order to achieve a reasonable and optimal design, identifying the effective parameters for the stability of the mentioned structures is one of the most important goals and the most necessary actions in rock engineering. Therefore, it is necessary to study the relationships between the parameters of a system and how they interact with each other and, ultimately, the whole system. In this research, it has attempted to determine the most effective parameters (key parameters) from the six parameters of rock mass in the Q-system using the rock engineering system (RES) method to improve the relationships between the parameters in the calculation of the Q value. The RES system is, in fact, a method by which one can determine the degree of cause and effect of a system's parameters by making an interaction matrix. In this research, the geomechanical data collected from the water conveyor tunnel of Azad Dam were used to make the interaction matrix of the Q-system. For this purpose, instead of using the conventional methods that are always accompanied by defects such as uncertainty, the Q-system interaction matrix is coded using a technique that is actually a statistical analysis of the data and determining the correlation coefficient between them. So, the effect of each parameter on the system is evaluated with greater certainty. The results of this study show that the formed interaction matrix provides a reasonable estimate of the effective parameters in the Q-system. Among the six parameters of the Q-system, the SRF and Jr parameters have the maximum and minimum impact on the system, respectively, and also the RQD and Jw parameters have the maximum and minimum impact on the system, respectively. Therefore, by developing this method, we can obtain a more accurate relation to the rock mass classification by weighting the required parameters in the Q-system.Keywords: Q-system, rock engineering system, statistical analysis, rock mass, tunnel
Procedia PDF Downloads 7329605 Multi-Objective Optimization of a Solar-Powered Triple-Effect Absorption Chiller for Air-Conditioning Applications
Authors: Ali Shirazi, Robert A. Taylor, Stephen D. White, Graham L. Morrison
Abstract:
In this paper, a detailed simulation model of a solar-powered triple-effect LiBr–H2O absorption chiller is developed to supply both cooling and heating demand of a large-scale building, aiming to reduce the fossil fuel consumption and greenhouse gas emissions in building sector. TRNSYS 17 is used to simulate the performance of the system over a typical year. A combined energetic-economic-environmental analysis is conducted to determine the system annual primary energy consumption and the total cost, which are considered as two conflicting objectives. A multi-objective optimization of the system is performed using a genetic algorithm to minimize these objectives simultaneously. The optimization results show that the final optimal design of the proposed plant has a solar fraction of 72% and leads to an annual primary energy saving of 0.69 GWh and annual CO2 emissions reduction of ~166 tonnes, as compared to a conventional HVAC system. The economics of this design, however, is not appealing without public funding, which is often the case for many renewable energy systems. The results show that a good funding policy is required in order for these technologies to achieve satisfactory payback periods within the lifetime of the plant.Keywords: economic, environmental, multi-objective optimization, solar air-conditioning, triple-effect absorption chiller
Procedia PDF Downloads 23829604 Computational Fluid Dynamics (CFD) Modeling of Local with a Hot Temperature in Sahara
Authors: Selma Bouasria, Mahi Abdelkader, Abbès Azzi, Herouz Keltoum
Abstract:
This paper reports concept was used into the computational fluid dynamics (CFD) code cfx through user-defined functions to assess ventilation efficiency inside (forced-ventilation local). CFX is a simulation tool which uses powerful computer and applied mathematics, to model fluid flow situations for the prediction of heat, mass and momentum transfer and optimal design in various heat transfer and fluid flow processes to evaluate thermal comfort in a room ventilated (highly-glazed). The quality of the solutions obtained from CFD simulations is an effective tool for predicting the behavior and performance indoor thermo-aéraulique comfort.Keywords: ventilation, thermal comfort, CFD, indoor environment, solar air heater
Procedia PDF Downloads 63429603 Statistical Analysis to Compare between Smart City and Traditional Housing
Authors: Taha Anjamrooz, Sareh Rajabi, Ayman Alzaatreh
Abstract:
Smart cities are playing important roles in real life. Integration and automation between different features of modern cities and information technologies improve smart city efficiency, energy management, human and equipment resource management, life quality and better utilization of resources for the customers. One of difficulties in this path, is use, interface and link between software, hardware, and other IT technologies to develop and optimize processes in various business fields such as construction, supply chain management and transportation in parallel to cost-effective and resource reduction impacts. Also, Smart cities are certainly intended to demonstrate a vital role in offering a sustainable and efficient model for smart houses while mitigating environmental and ecological matters. Energy management is one of the most important matters within smart houses in the smart cities and communities, because of the sensitivity of energy systems, reduction in energy wastage and maximization in utilizing the required energy. Specially, the consumption of energy in the smart houses is important and considerable in the economic balance and energy management in smart city as it causes significant increment in energy-saving and energy-wastage reduction. This research paper develops features and concept of smart city in term of overall efficiency through various effective variables. The selected variables and observations are analyzed through data analysis processes to demonstrate the efficiency of smart city and compare the effectiveness of each variable. There are ten chosen variables in this study to improve overall efficiency of smart city through increasing effectiveness of smart houses using an automated solar photovoltaic system, RFID System, smart meter and other major elements by interfacing between software and hardware devices as well as IT technologies. Secondly to enhance aspect of energy management by energy-saving within smart house through efficient variables. The main objective of smart city and smart houses is to reproduce energy and increase its efficiency through selected variables with a comfortable and harmless atmosphere for the customers within a smart city in combination of control over the energy consumption in smart house using developed IT technologies. Initially the comparison between traditional housing and smart city samples is conducted to indicate more efficient system. Moreover, the main variables involved in measuring overall efficiency of system are analyzed through various processes to identify and prioritize the variables in accordance to their influence over the model. The result analysis of this model can be used as comparison and benchmarking with traditional life style to demonstrate the privileges of smart cities. Furthermore, due to expensive and expected shortage of natural resources in near future, insufficient and developed research study in the region, and available potential due to climate and governmental vision, the result and analysis of this study can be used as key indicator to select most effective variables or devices during construction phase and designKeywords: smart city, traditional housing, RFID, photovoltaic system, energy efficiency, energy saving
Procedia PDF Downloads 11329602 Downscaling Seasonal Sea Surface Temperature Forecasts over the Mediterranean Sea Using Deep Learning
Authors: Redouane Larbi Boufeniza, Jing-Jia Luo
Abstract:
This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning
Procedia PDF Downloads 7629601 Impact of Pandemics on Cities and Societies
Authors: Deepak Jugran
Abstract:
Purpose: The purpose of this study is to identify how past Pandemics shaped social evolution and cities. Methodology: A historical and comparative analysis of major historical pandemics in human history their origin, transmission route, biological response and the aftereffects. A Comprehensive pre & post pandemic scenario and focuses selectively on major issues and pandemics that have deepest & lasting impact on society with available secondary data. Results: Past pandemics shaped the behavior of human societies and their cities and made them more resilient biologically, intellectually & socially endorsing the theory of “Survival of the fittest” by Sir Charles Darwin. Pandemics & Infectious diseases are here to stay and as a human society, we need to strengthen our collective response & preparedness besides evolving mechanisms for strict controls on inter-continental movements of people, & especially animals who become carriers for these viruses. Conclusion: Pandemics always resulted in great mortality, but they also improved the overall individual human immunology & collective social response; at the same time, they also improved the public health system of cities, health delivery systems, water, sewage distribution system, institutionalized various welfare reforms and overall collective social response by the societies. It made human beings more resilient biologically, intellectually, and socially hence endorsing the theory of “AGIL” by Prof Talcott Parsons. Pandemics & infectious diseases are here to stay and as humans, we need to strengthen our city response & preparedness besides evolving mechanisms for strict controls on inter-continental movements of people, especially animals who always acted as carriers for these novel viruses. Pandemics over the years acted like natural storms, mitigated the prevailing social imbalances and laid the foundation for scientific discoveries. We understand that post-Covid-19, institutionalized city, state and national mechanisms will get strengthened and the recommendations issued by the various expert groups which were ignored earlier will now be implemented for reliable anticipation, better preparedness & help to minimize the impact of Pandemics. Our analysis does not intend to present chronological findings of pandemics but rather focuses selectively on major pandemics in history, their causes and how they wiped out an entire city’s population and influenced the societies, their behavior and facilitated social evolution.Keywords: pandemics, Covid-19, social evolution, cities
Procedia PDF Downloads 11229600 New Dynamic Constitutive Model for OFHC Copper Film
Authors: Jin Sung Kim, Hoon Huh
Abstract:
The material properties of OFHC copper film was investigated with the High-Speed Material Micro Testing Machine (HSMMTM) at the high strain rates. The rate-dependent stress-strain curves from the experiment and the Johnson-Cook curve fitting showed large discrepancies as the plastic strain increases since the constitutive model implies no rate-dependent strain hardening effect. A new constitutive model was proposed in consideration of rate-dependent strain hardening effect. The strain rate hardening term in the new constitutive model consists of the strain rate sensitivity coefficients of the yield strength and strain hardening.Keywords: rate dependent material properties, dynamic constitutive model, OFHC copper film, strain rate
Procedia PDF Downloads 48629599 Multi-Particle Finite Element Modelling Simulation Based on Cohesive Zone Method of Cold Compaction Behavior of Laminar Al and NaCl Composite Powders
Authors: Yanbing Feng, Deqing Mei, Yancheng Wang, Zichen Chen
Abstract:
With the advantage of low volume density, high specific surface area, light weight and good permeability, porous aluminum material has the potential to be used in automotive, railway, chemistry and construction industries, etc. A layered powder sintering and dissolution method were developed to fabricate the porous surface Al structure with high efficiency. However, the densification mechanism during the cold compaction of laminar composite powders is still unclear. In this study, multi particle finite element modelling (MPFEM) based on the cohesive zone method (CZM) is used to simulate the cold compaction behavior of laminar Al and NaCl composite powders. To obtain its densification mechanism, the macro and micro properties of final compacts are characterized and analyzed. The robustness and accuracy of the numerical model is firstly verified by experimental results and data fitting. The results indicate that the CZM-based multi particle FEM is an effective way to simulate the compaction of the laminar powders and the fracture process of the NaCl powders. In the compaction of the laminar powders, the void is mainly filled by the particle rearrangement, plastic deformation of Al powders and brittle fracture of NaCl powders. Large stress is mainly concentrated within the NaCl powers and the contact force network is formed. The Al powder near the NaCl powder or the mold has larger stress distribution on its contact surface. Therefore, the densification process of cold compaction of laminar Al and NaCl composite powders is successfully analyzed by the CZM-based multi particle FEM.Keywords: cold compaction, cohesive zone, multi-particle FEM, numerical modeling, powder forming
Procedia PDF Downloads 15229598 Effect of Water Absorption on the Fatigue Behavior of Glass/Polyester Composite
Authors: Djamel Djeghader, Bachir Redjel
Abstract:
The composite materials of glass fibers can be used as a repair material for damage elements under repeated stresses, and in various environments. A cyclic bending characterization of a glass/polyester composite material was carried out with consideration of the period of immersion in water. These tests describe the behavior of materials and identify the mechanical fatigue characteristics using the Wohler Curve for different immersion time: 0, 90, 180 and 270 days in water. These curves are characterized by a dispersion in the lifetimes were modeled by straight whose intercepts are very similar and comparable to the static strength. This material deteriorates fatigue at a constant rate, which increases with increasing immersion time in water at a constant speed. The endurance limit seems to be independent of the immersion time in the water.Keywords: fatigue, composite, glass, polyester, immersion, wohler
Procedia PDF Downloads 31429597 Automatic Number Plate Recognition System Based on Deep Learning
Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi
Abstract:
In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.Keywords: ANPR, CS, CNN, deep learning, NPL
Procedia PDF Downloads 30629596 Investigating the Steam Generation Potential of Lithium Bromide Based CuO Nanofluid under Simulated Solar Flux
Authors: Tamseela Habib, Muhammad Amjad, Muhammad Edokali, Masome Moeni, Olivia Pickup, Ali Hassanpour
Abstract:
Nanofluid-assisted steam generation is rapidly attracting attention amongst the scientific community since it can be applied in a wide range of industrial processes. Because of its high absorption rate of solar energy, nanoparticle-based solar steam generation could be a major contributor to many applications, including water desalination, sterilization and power generation. Lithium bromide-based iron oxide nanofluids have been previously studied in steam generation, which showed promising results. However, the efficiency of the system could be improved if a more heat-conductive nanofluid system could be utilised. In the current paper, we report on an experimental investigation of the photothermal conversion properties of functionalised Copper oxide (CuO) nanoparticles used in Lithium Bromide salt solutions. CuO binary nanofluid was prepared by chemical functionalization with polyethyleneimine (PEI). Long-term stability evaluation of prepared binary nanofluid was done by a high-speed centrifuge analyser which showed a 0.06 Instability index suggesting low agglomeration and sedimentation tendencies. This stability is also supported by the measurements from dynamic light scattering (DLS), transmission electron microscope (TEM), and ultraviolet-visible (UV-Vis) spectrophotometer. The fluid rheology is also characterised, which suggests the system exhibits a Newtonian fluid behavior. The photothermal conversion efficiency of different concentrations of CuO was experimentally investigated under a solar simulator. Experimental results reveal that the binary nanofluid in this study can remarkably increase the solar energy trapping efficiency and evaporation rate as compared to conventional fluids due to localized solar energy harvesting by the surface of the nanofluid. It was found that 0.1wt% CuO NP is the optimum nanofluid concentration for enhanced sensible and latent heat efficiencies.Keywords: nanofluids, vapor absorption refrigeration system, steam generation, high salinity
Procedia PDF Downloads 8429595 Designing Ecologically and Economically Optimal Electric Vehicle Charging Stations
Authors: Y. Ghiassi-Farrokhfal
Abstract:
The number of electric vehicles (EVs) is increasing worldwide. Replacing gas fueled cars with EVs reduces carbon emission. However, the extensive energy consumption of EVs stresses the energy systems, requiring non-green sources of energy (such as gas turbines) to compensate for the new energy demand caused by EVs in the energy systems. To make EVs even a greener solution for the future energy systems, new EV charging stations are equipped with solar PV panels and batteries. This will help serve the energy demand of EVs through the green energy of solar panels. To ensure energy availability, solar panels are combined with batteries. The energy surplus at any point is stored in batteries and is used when there is not enough solar energy to serve the demand. While EV charging stations equipped with solar panels and batteries are green and ecologically optimal, they might not be financially viable solutions, due to battery prices. To make the system viable, we should size the battery economically and operate the system optimally. This is, in general, a challenging problem because of the stochastic nature of the EV arrivals at the charging station, the available solar energy, and the battery operating system. In this work, we provide a mathematical model for this problem and we compute the return on investment (ROI) of such a system, which is designed to be ecologically and financially optimal. We also quantify the minimum required investment in terms of battery and solar panels along with the operating strategy to ensure that a charging station has enough energy to serve its EV demand at any time.Keywords: solar energy, battery storage, electric vehicle, charging stations
Procedia PDF Downloads 22329594 Experimental Study and Numerical Modelling of Failure of Rocks Typical for Kuzbass Coal Basin
Authors: Mikhail O. Eremin
Abstract:
Present work is devoted to experimental study and numerical modelling of failure of rocks typical for Kuzbass coal basin (Russia). The main goal was to define strength and deformation characteristics of rocks on the base of uniaxial compression and three-point bending loadings and then to build a mathematical model of failure process for both types of loading. Depending on particular physical-mechanical characteristics typical rocks of Kuzbass coal basin (sandstones, siltstones, mudstones, etc. of different series – Kolchuginsk, Tarbagansk, Balohonsk) manifest brittle and quasi-brittle character of failure. The strength characteristics for both tension and compression are found. Other characteristics are also found from the experiment or taken from literature reviews. On the base of obtained characteristics and structure (obtained from microscopy) the mathematical and structural models are built and numerical modelling of failure under different types of loading is carried out. Effective characteristics obtained from modelling and character of failure correspond to experiment and thus, the mathematical model was verified. An Instron 1185 machine was used to carry out the experiments. Mathematical model includes fundamental conservation laws of solid mechanics – mass, impulse, energy. Each rock has a sufficiently anisotropic structure, however, each crystallite might be considered as isotropic and then a whole rock model has a quasi-isotropic structure. This idea gives an opportunity to use the Hooke’s law inside of each crystallite and thus explicitly accounting for the anisotropy of rocks and the stress-strain state at loading. Inelastic behavior is described in frameworks of two different models: von Mises yield criterion and modified Drucker-Prager yield criterion. The damage accumulation theory is also implemented in order to describe a failure process. Obtained effective characteristics of rocks are used then for modelling of rock mass evolution when mining is carried out both by an open-pit or underground opening.Keywords: damage accumulation, Drucker-Prager yield criterion, failure, mathematical modelling, three-point bending, uniaxial compression
Procedia PDF Downloads 17529593 Analysis and Modeling of Photovoltaic System with Different Research Methods of Maximum Power Point Tracking
Authors: Mehdi Ameur, Ahmed Essakdi, Tamou Nasser
Abstract:
The purpose of this paper is the analysis and modeling of the photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturb and observe (P&O), incremental conductance (INC) and fuzzy logic controller(FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.Keywords: photovoltaic array, maximum power point tracking, MPPT, perturb and observe, P&O, incremental conductance, INC, hill climbing, HC, fuzzy logic controller, FLC
Procedia PDF Downloads 42929592 Development and Application of the Proctoring System with Face Recognition for User Registration on the Educational Information Portal
Authors: Meruyert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova, Madina Ermaganbetova
Abstract:
This research paper explores the process of creating a proctoring system by evaluating the implementation of practical face recognition algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As an outcome, a proctoring system will be created, enabling the conduction of tests and ensuring academic integrity checks within the system. Due to the correct operation of the system, test works are carried out. The result of the creation of the proctoring system will be the basis for the automation of the informational, educational portal developed by machine learning.Keywords: artificial intelligence, education portal, face recognition, machine learning, proctoring
Procedia PDF Downloads 12629591 Photoplethysmography-Based Device Designing for Cardiovascular System Diagnostics
Authors: S. Botman, D. Borchevkin, V. Petrov, E. Bogdanov, M. Patrushev, N. Shusharina
Abstract:
In this paper, we report the development of the device for diagnostics of cardiovascular system state and associated automated workstation for large-scale medical measurement data collection and analysis. It was shown that optimal design for the monitoring device is wristband as it represents engineering trade-off between accuracy and usability. The monitoring device is based on the infrared reflective photoplethysmographic sensor, which allows collecting multiple physiological parameters, such as heart rate and pulsing wave characteristics. Developed device use BLE interface for medical and supplementary data transmission to the coupled mobile phone, which process it and send it to the doctor's automated workstation. Results of this experimental model approbation confirmed the applicability of the proposed approach.Keywords: cardiovascular diseases, health monitoring systems, photoplethysmography, pulse wave, remote diagnostics
Procedia PDF Downloads 49229590 Retrospective Reconstruction of Time Series Data for Integrated Waste Management
Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy
Abstract:
The development, operation and maintenance of Integrated Waste Management Systems (IWMS) affects essentially the sustainable concern of every region. The features of such systems have great influence on all of the components of sustainability. In order to reach the optimal way of processes, a comprehensive mapping of the variables affecting the future efficiency of the system is needed such as analysis of the interconnections among the components and modelling of their interactions. The planning of a IWMS is based fundamentally on technical and economical opportunities and the legal framework. Modelling the sustainability and operation effectiveness of a certain IWMS is not in the scope of the present research. The complexity of the systems and the large number of the variables require the utilization of a complex approach to model the outcomes and future risks. This complex method should be able to evaluate the logical framework of the factors composing the system and the interconnections between them. The authors of this paper studied the usability of the Fuzzy Cognitive Map (FCM) approach modelling the future operation of IWMS’s. The approach requires two input data set. One is the connection matrix containing all the factors affecting the system in focus with all the interconnections. The other input data set is the time series, a retrospective reconstruction of the weights and roles of the factors. This paper introduces a novel method to develop time series by content analysis.Keywords: content analysis, factors, integrated waste management system, time series
Procedia PDF Downloads 32629589 Flood Early Warning and Management System
Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare
Abstract:
The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.Keywords: flood, modeling, HPC, FOSS
Procedia PDF Downloads 8929588 Streamlining Cybersecurity Risk Assessment for Industrial Control and Automation Systems: Leveraging the National Institute of Standard and Technology’s Risk Management Framework (RMF) Using Model-Based System Engineering (MBSE)
Authors: Gampel Alexander, Mazzuchi Thomas, Sarkani Shahram
Abstract:
The cybersecurity landscape is constantly evolving, and organizations must adapt to the changing threat environment to protect their assets. The implementation of the NIST Risk Management Framework (RMF) has become critical in ensuring the security and safety of industrial control and automation systems. However, cybersecurity professionals are facing challenges in implementing RMF, leading to systems operating without authorization and being non-compliant with regulations. The current approach to RMF implementation based on business practices is limited and insufficient, leaving organizations vulnerable to cyberattacks resulting in the loss of personal consumer data and critical infrastructure details. To address these challenges, this research proposes a Model-Based Systems Engineering (MBSE) approach to implementing cybersecurity controls and assessing risk through the RMF process. The study emphasizes the need to shift to a modeling approach, which can streamline the RMF process and eliminate bloated structures that make it difficult to receive an Authorization-To-Operate (ATO). The study focuses on the practical application of MBSE in industrial control and automation systems to improve the security and safety of operations. It is concluded that MBSE can be used to solve the implementation challenges of the NIST RMF process and improve the security of industrial control and automation systems. The research suggests that MBSE provides a more effective and efficient method for implementing cybersecurity controls and assessing risk through the RMF process. The future work for this research involves exploring the broader applicability of MBSE in different industries and domains. The study suggests that the MBSE approach can be applied to other domains beyond industrial control and automation systems.Keywords: authorization-to-operate (ATO), industrial control systems (ICS), model-based system’s engineering (MBSE), risk management framework (RMF)
Procedia PDF Downloads 9529587 Elemental Graph Data Model: A Semantic and Topological Representation of Building Elements
Authors: Yasmeen A. S. Essawy, Khaled Nassar
Abstract:
With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory
Procedia PDF Downloads 38229586 A Comparative Study of Approaches in User-Centred Health Information Retrieval
Authors: Harsh Thakkar, Ganesh Iyer
Abstract:
In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF eHealth 2014 Task 3 for this purpose. We classify and focus on comparing the two most prevalent retrieval models in biomedical information retrieval namely: Language Model (LM) and Vector Space Model (VSM). We also report on the effectiveness of using external medical resources and ontologies like MeSH, Metamap, UMLS, etc. We observed that the LM based retrieval systems outperform VSM based systems on various fronts. From the results we conclude that the state-of-art system scores for MAP was 0.4146, P@10 was 0.7560 and NDCG@10 was 0.7445, respectively. All of these score were reported by systems built on language modeling approaches.Keywords: clinical document retrieval, concept-based information retrieval, query expansion, language models, vector space models
Procedia PDF Downloads 32029585 Multi-Stream Graph Attention Network for Recommendation with Knowledge Graph
Abstract:
In recent years, Graph neural network has been widely used in knowledge graph recommendation. The existing recommendation methods based on graph neural network extract information from knowledge graph through entity and relation, which may not be efficient in the way of information extraction. In order to better propose useful entity information for the current recommendation task in the knowledge graph, we propose an end-to-end Neural network Model based on multi-stream graph attentional Mechanism (MSGAT), which can effectively integrate the knowledge graph into the recommendation system by evaluating the importance of entities from both users and items. Specifically, we use the attention mechanism from the user's perspective to distil the domain nodes information of the predicted item in the knowledge graph, to enhance the user's information on items, and generate the feature representation of the predicted item. Due to user history, click items can reflect the user's interest distribution, we propose a multi-stream attention mechanism, based on the user's preference for entities and relationships, and the similarity between items to be predicted and entities, aggregate user history click item's neighborhood entity information in the knowledge graph and generate the user's feature representation. We evaluate our model on three real recommendation datasets: Movielens-1M (ML-1M), LFM-1B 2015 (LFM-1B), and Amazon-Book (AZ-book). Experimental results show that compared with the most advanced models, our proposed model can better capture the entity information in the knowledge graph, which proves the validity and accuracy of the model.Keywords: graph attention network, knowledge graph, recommendation, information propagation
Procedia PDF Downloads 11729584 Assesments of Some Environment Variables on Fisheries at Two Levels: Global and Fao Major Fishing Areas
Authors: Hyelim Park, Juan Martin Zorrilla
Abstract:
Climate change influences very widely and in various ways ocean ecosystem functioning. The consequences of climate change on marine ecosystems are an increase in temperature and irregular behavior of some solute concentrations. These changes would affect fisheries catches in several ways. Our aim is to assess the quantitative contribution change of fishery catches along the time and express them through four environment variables: Sea Surface Temperature (SST4) and the concentrations of Chlorophyll (CHL), Particulate Inorganic Carbon (PIC) and Particulate Organic Carbon (POC) at two spatial scales: Global and the nineteen FAO Major Fishing Areas divisions. Data collection was based on the FAO FishStatJ 2014 database as well as MODIS Aqua satellite observations from 2002 to 2012. Some data had to be corrected and interpolated using some existing methods. As the results, a multivariable regression model for average Global fisheries captures contained temporal mean of SST4, standard deviation of SST4, standard deviation of CHL and standard deviation of PIC. Global vector auto-regressive (VAR) model showed that SST4 was a statistical cause of global fishery capture. To accommodate varying conditions in fishery condition and influence of climate change variables, a model was constructed for each FAO major fishing area. From the management perspective it should be recognized some limitations of the FAO marine areas division that opens to possibility to the discussion of the subdivision of the areas into smaller units. Furthermore, it should be treated that the contribution changes of fishery species and the possible environment factor for specific species at various scale levels.Keywords: fisheries-catch, FAO FishStatJ, MODIS Aqua, sea surface temperature (SST), chlorophyll, particulate inorganic carbon (PIC), particulate organic carbon (POC), VAR, granger causality
Procedia PDF Downloads 48429583 Development of Web Application for Warehouse Management System: A Case Study of Ceramics Factory
Authors: Thanaphat Suwanaklang, Supaporn Suwannarongsri
Abstract:
Presently, there are many industries in Thailand producing various products for both domestic distribution and export to foreign countries. Warehouse is one of the most important areas of business needing to store their products. Such businesses need to have a suitable warehouse management system for reducing the storage time and using the space as much as possible. This paper proposes the development of a web application for a warehouse management system. One of the ceramics factories in Thailand is conducted as a case study. By applying the ABC analysis, fixed location, commodity system, ECRS, and 7-waste theories and principles, the web application for the warehouse management system of the selected ceramics factory is developed to design the optimal storage area for groups of products and design the optimal routes of forklifts. From experimental results, it was found that the warehouse management system developed via the web application can reduce the travel distance of forklifts and the time of searching for storage area by 100% once compared with the conventional method. In addition, the entire storage area can be on-line and real-time monitored.Keywords: warehouse management system, warehouse design method, logistics system, web application
Procedia PDF Downloads 136