Search results for: artificial boundary condition

Authors: Maryam Hasanali, Syed Mohammad Mojtabaei, Iman Hajirasouliha, G. Charles Clifton, James B. P. Lim

Abstract:

Cold-formed steel (CFS) elements are increasingly being used as main load-bearing components in the modern construction industry, including low- to mid-rise buildings. In typical multi-storey buildings, CFS structural members act as beam-column elements since they are exposed to combined axial compression and bending actions, both in moment-resisting frames and stud wall systems. Current design specifications, including the American Iron and Steel Institute (AISI S100) and the Australian/New Zealand Standard (AS/NZS 4600), neglect the beneficial effects of warping-restrained boundary conditions in the design of beam-column elements. Furthermore, while a non-linear relationship governs the interaction of axial compression and bending, the combined effect of these actions is taken into account through a simplified linear expression combining pure axial and flexural strengths. This paper aims to evaluate the reliability of the well-known Direct Strength Method (DSM) as well as design proposals found in the literature to provide a better understanding of the efficiency of the code-prescribed linear interaction equation in the strength predictions of CFS beam columns and the effects of warping-restrained boundary conditions on their behavior. To this end, the experimentally validated finite element (FE) models of CFS elements under compression and bending were developed in ABAQUS software, which accounts for both non-linear material properties and geometric imperfections. The validated models were then used for a comprehensive parametric study containing 270 FE models, covering a wide range of key design parameters, such as length (i.e., 0.5, 1.5, and 3 m), thickness (i.e., 1, 2, and 4 mm) and cross-sectional dimensions under ten different load eccentricity levels. The results of this parametric study demonstrated that using the DSM led to the most conservative strength predictions for beam-column members by up to 55%, depending on the element’s length and thickness. This can be sourced by the errors associated with (i) the absence of warping-restrained boundary condition effects, (ii) equations for the calculations of buckling loads, and (iii) the linear interaction equation. While the influence of warping restraint is generally less than 6%, the code suggested interaction equation led to an average error of 4% to 22%, based on the element lengths. This paper highlights the need to provide more reliable design solutions for CFS beam-column elements for practical design purposes.

Keywords: beam-columns, cold-formed steel, finite element model, interaction equation, warping-restrained boundary conditions

Procedia PDF Downloads 99

Authors: M. A. Talha, M. Osman Gani, M. Ferdows

Abstract:

This paper focuses on the study of two dimensional magnetohydrodynamic (MHD) steady incompressible viscous Williamson nanofluid with exponential internal heat generation containing gyrotactic microorganism over a stretching sheet. The governing equations and auxiliary conditions are reduced to a set of non-linear coupled differential equations with the appropriate boundary conditions using similarity transformation. The transformed equations are solved numerically through spectral relaxation method. The influences of various parameters such as Williamson parameter γ, power constant λ, Prandtl number P_r, magnetic field parameter M, Peclet number P_e, Lewis number Le, Bioconvection Lewis number Lb, Brownian motion parameter Nb, thermophoresis parameter Nt, and bioconvection constant σ are studied to obtain the momentum, heat, mass and microorganism distributions. Moment, heat, mass and gyrotactic microorganism profiles are explored through graphs and tables. We computed the heat transfer rate, mass flux rate and the density number of the motile microorganism near the surface. Our numerical results are in better agreement in comparison with existing calculations. The Residual error of our obtained solutions is determined in order to see the convergence rate against iteration. Faster convergence is achieved when internal heat generation is absent. The effect of magnetic parameter M decreases the momentum boundary layer thickness but increases the thermal boundary layer thickness. It is apparent that bioconvection Lewis number and bioconvection parameter has a pronounced effect on microorganism boundary. Increasing brownian motion parameter and Lewis number decreases the thermal boundary layer. Furthermore, magnetic field parameter and thermophoresis parameter has an induced effect on concentration profiles.

Keywords: convection flow, similarity, numerical analysis, spectral method, Williamson nanofluid, internal heat generation

Procedia PDF Downloads 175

Authors: Takashi Yamaguchi, Ichio Asanuma, Jong G. Park, Kenneth J. Mackin, John Mittleman

Abstract:

In this paper, vessel detection using the artificial neural network is proposed in order to automatically construct the vessel detection model from the satellite imagery of day/night band (DNB) in visible infrared in the products of Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (Suomi-NPP).The goal of our research is the establishment of vessel detection method using the satellite imagery of DNB in order to monitor the change of vessel activity over the wide region. The temporal vessel monitoring is very important to detect the events and understand the circumstances within the maritime environment. For the vessel locating and detection techniques, Automatic Identification System (AIS) and remote sensing using Synthetic aperture radar (SAR) imagery have been researched. However, each data has some lack of information due to uncertain operation or limitation of continuous observation. Therefore, the fusion of effective data and methods is important to monitor the maritime environment for the future. DNB is one of the effective data to detect the small vessels such as fishery ships that is difficult to observe in AIS. DNB is the satellite sensor data of VIIRS on Suomi-NPP. In contrast to SAR images, DNB images are moderate resolution and gave influence to the cloud but can observe the same regions in each day. DNB sensor can observe the lights produced from various artifact such as vehicles and buildings in the night and can detect the small vessels from the fishing light on the open water. However, the modeling of vessel detection using DNB is very difficult since complex atmosphere and lunar condition should be considered due to the strong influence of lunar reflection from cloud on DNB. Therefore, artificial neural network was applied to learn the vessel detection model. For the feature of vessel detection, Brightness Temperature at the 3.7 μm (BT3.7) was additionally used because BT3.7 can be used for the parameter of atmospheric conditions.

Keywords: artificial neural network, day/night band, remote sensing, Suomi National Polar-orbiting Partnership, vessel detection, Visible Infrared Imaging Radiometer Suite

Procedia PDF Downloads 234

Authors: Ricardo Merlo, María González, Zully Rivero, Laura González

Abstract:

This exploratory work was to know the perception of the use of artificial intelligence (AI) that university students have during their passage through the classroom. The significance of using AI in education, the degree of interest, knowledge acquisition, and how it would influence an interactive resource for acquiring skills were explored. Within this framework, a test with 30 items was designed and administered to 800 volunteer first-year university students of natural and exact sciences. Based on a randomized pilot test, it was validated with Cronbach's Alpha coefficient. Subsequently, the descriptive statistics of the sample used allowed us to observe the preponderance of the dimensions that constitute the attitude construct. Then, the factorial analysis by dimensions contributed to discern about the students' habits according to the knowledge acquired and the emotions put into play in the topics developed in the classroom.

Keywords: attitude, artificial intelligence, didactics, teaching

Procedia PDF Downloads 22

Authors: Ishtiaq A. Chaudhry, Z. R. Tahir, F. A. Siddiqui, Z. Anwar, F. Valenzuelacalva

Abstract:

A series of experiments involving the particle image velocimetry technique are carried out to analyse the quantitative effectiveness of the synthesized vortical structures towards actual flow separation control. The streamwise vortices are synthesized from the synthetic jet actuator and introduced into the attached and separating boundary layer developed on the flat plate surface. Two types of actuators with different geometrical set up are used to analyse the evolution of vortical structures in the near wall region and their impact towards achieving separation delay on the actual aircraft wing. Firstly a single circular jet is synthesized at varying actuator operating parameters and issued into the boundary layer to evaluate the dynamics of the interaction between the vortical structures and the near wall low momentum fluid in the separated region. Secondly, an array of jets has been issued into the artificially separated region to assess the effectiveness of various vortical structures towards achieving the reattachment of the separated flow in the streamwise direction.

Keywords: boundary layer, flow separation, streamwise vortices, synthetic jet actuator

Procedia PDF Downloads 461

Authors: Hua Li, Hongwu Deng

Abstract:

The turbine blade's leading edge is usually cooled by jet impingement cooling technology due to the heaviest heat load. For a rotating turbine blade, however, the channel orientation (β, the angle between the jet direction and the rotating plane) could play an important role in influencing the flow field and heat transfer. Therefore, in this work, the effects of channel orientation (from 90° to 180°) on heat transfer in a jet impingement cooling channel are experimentally investigated. Furthermore, the investigations are conducted under an isothermal boundary condition. Both the jet-to-target surface distance and jet-to-jet spacing are three times the jet hole diameter. The jet Reynolds number is 5,000, and the maximum jet rotation number reaches 0.24. The results show that the rotation-induced variations of heat transfer are different in each channel orientation. In the cases of 90°≤β≤135°, a vortex generated in the low-radius region of the supply channel changes the mass-flowrate distribution in each jet hole. Therefore, the heat transfer in the low-radius region decreases with the rotation number, whereas the heat transfer in the high-radius region increases, indicating that a larger temperature gradient in the radial direction could appear in the turbine blade's leading edge. When 135°<β≤180°; however, the heat transfer of the entire stagnant zone decreases with the rotation number. The rotation-induced jet deflection is the primary factor that weakens the heat transfer, and jets cannot reach the target surface at high rotation numbers. For the downstream regions, however, the heat transfer is enhanced by 50%-80% in every channel orientation because the dead zone is broken by the rotation-induced secondary flow in the impingement channel.

Keywords: heat transfer, jet impingement cooling, channel orientation, high rotation number, isothermal boundary

Procedia PDF Downloads 99

Authors: Seyed Sobhan Alvani, Mohammad Gohari

Abstract:

By developing cities and increasing the population, traffic congestion has become a vital problem. Due to this crisis, urban designers try to present solutions to decrease this difficulty. On the other hand, predicting the model with perfect accuracy is essential for solution-providing. The current study presents a model based on artificial intelligence which can predict traffic index based on city population, growth rate, and area. The accuracy of the model was evaluated, which is acceptable and it is around 90%. Thus, urban designers and planners can employ it for predicting traffic index in the future to provide strategies.

Keywords: traffic index, population growth rate, cities wideness, artificial neural network

Procedia PDF Downloads 31

Authors: Fausto Morais

Abstract:

Artificial intelligence has been widely used in law. Programs are able to classify suits, to identify decision-making patterns, to predict outcomes, and to formalize legal arguments as well. In Brazil, the artificial intelligence victor has been classifying cases to supreme court’s standards. When those programs act doing those tasks, they simulate some kind of legal decision and legal arguments, raising doubts about how artificial intelligence can be integrated into legal reasoning. Taking this into account, the following three issues are identified; the problem of hypernormatization, the argument of legal anthropocentrism, and the artificial legal principles. Hypernormatization can be seen in the Brazilian legal context in the Supreme Court’s usage of the Victor program. This program generated efficiency and consistency. On the other hand, there is a feasible risk of over standardizing factual and normative legal features. Then legal clerks and programmers should work together to develop an adequate way to model legal language into computational code. If this is possible, intelligent programs may enact legal decisions in easy cases automatically cases, and, in this picture, the legal anthropocentrism argument takes place. Such an argument argues that just humans beings should enact legal decisions. This is so because human beings have a conscience, free will, and self unity. In spite of that, it is possible to argue against the anthropocentrism argument and to show how intelligent programs may work overcoming human beings' problems like misleading cognition, emotions, and lack of memory. In this way, intelligent machines could be able to pass legal decisions automatically by classification, as Victor in Brazil does, because they are binding by legal patterns and should not deviate from them. Notwithstanding, artificial intelligent programs can be helpful beyond easy cases. In hard cases, they are able to identify legal standards and legal arguments by using machine learning. For that, a dataset of legal decisions regarding a particular matter must be available, which is a reality in Brazilian Judiciary. Doing such procedure, artificial intelligent programs can support a human decision in hard cases, providing legal standards and arguments based on empirical evidence. Those legal features claim an argumentative weight in legal reasoning and should serve as references for judges when they must decide to maintain or overcome a legal standard.

Keywords: artificial intelligence, artificial legal principles, hypernormatization, legal anthropocentrism argument, legal reasoning

Procedia PDF Downloads 141

Authors: Yi-Guang Li, Suresh Sampath

Abstract:

Gas turbine performance degrades over time, and the degradation is greatly affected by environmental, ambient, and operating conditions. The engines may degrade slowly under favorable conditions and result in a waste of engine life if a scheduled maintenance scheme is followed. They may also degrade fast and fail before a scheduled overhaul if the conditions are unfavorable, resulting in serious secondary damage, loss of engine availability, and increased maintenance costs. To overcome these problems, gas turbine owners are gradually moving from scheduled maintenance to condition-based maintenance, where condition monitoring is one of the key supporting technologies. This paper presents an integrated adaptive GPA diagnostics and performance monitoring system developed at Cranfield University for gas turbine gas path condition monitoring. It has the capability to predict the performance degradation of major gas path components of gas turbine engines, such as compressors, combustors, and turbines, using gas path measurement data. It is also able to predict engine key performance parameters for condition monitoring, such as turbine entry temperature that cannot be directly measured. The developed technology has been implemented into digital twin computer Software, Pythia, to support the condition monitoring of gas turbine engines. The capabilities of the integrated GPA condition monitoring system are demonstrated in three test cases using a model gas turbine engine similar to the GE aero-derivative LM2500 engine widely used in power generation and marine propulsion. It shows that when the compressor of the model engine degrades, the Adaptive GPA is able to predict the degradation and the changing engine performance accurately using gas path measurements. Such a presented technology and software are generic, can be applied to different types of gas turbine engines, and provide crucial engine health and performance parameters to support condition monitoring and condition-based maintenance.

Keywords: gas turbine, adaptive GPA, performance, diagnostics, condition monitoring

Procedia PDF Downloads 84

Authors: Yuchen Yang, Zhenming Wang, Jun Zhu, Ning Zhao

Abstract:

An easy-to-implement and robust finite volume multi-resolution Weighted Essentially Non-Oscillatory (WENO) scheme is proposed on adaptive cartesian grids in this paper. Such a multi-resolution WENO scheme is combined with the ghost cell immersed boundary method (IBM) and wall-function technique to solve Navier-Stokes equations. Unlike the k-exact finite volume WENO schemes which involve large amounts of extra storage, repeatedly solving the matrix generated in a least-square method or the process of calculating optimal linear weights on adaptive cartesian grids, the present methodology only adds very small overhead and can be easily implemented in existing edge-based computational fluid dynamics (CFD) codes with minor modifications. Also, the linear weights of this adaptive finite volume multi-resolution WENO scheme can be any positive numbers on condition that their sum is one. It is a way of bypassing the calculation of the optimal linear weights and such a multi-resolution WENO scheme avoids dealing with the negative linear weights on adaptive cartesian grids. Some benchmark viscous problems are numerical solved to show the efficiency and good performance of this adaptive multi-resolution WENO scheme. Compared with a second-order edge-based method, the presented method can be implemented into an adaptive cartesian grid with slight modification for big Reynolds number problems.

Keywords: adaptive mesh refinement method, finite volume multi-resolution WENO scheme, immersed boundary method, wall-function technique.

Procedia PDF Downloads 144

Authors: Dolapo Adeyemo

Abstract:

Technology can be designed specifically for geriatrics and persons with disabilities or ICT accessibility solutions. Both solutions stand to benefit from advances in Artificial intelligence, which are computer systems that perform tasks that require human intelligence. Tasks such as decision making, visual perception, speech recognition, and even language translation are useful in both situation and will provide significant benefits to people with temporarily or permanent disabilities. This research’s goal is to review innovations focused on the use of artificial intelligence that bridges the accessibility gap in technology from a user-centered perspective. A mixed method approach that utilized a comprehensive review of academic literature on the subject combined with semi structure interviews of users, developers, and technology product owners. The internet of things and artificial intelligence technology is creating new opportunities in the assistive technology space and proving accessibility to existing technology. Device now more adaptable to the needs of the user by learning the behavior of users as they interact with the internet. Accessibility to devices have witnessed significant enhancements that continue to benefit people with disabilities. Examples of other advances identified are prosthetic limbs like robotic arms supported by artificial intelligence, route planning software for the visually impaired, and decision support tools for people with disabilities and even clinicians that provide care.

Keywords: ICT, IOT, accessibility solutions, universal design

Procedia PDF Downloads 85

Authors: Mohammad Motiee

Abstract:

From Kierkegaard to Sartre, the concept of 'being' was debated over various angles in the philosophy of being. Then, the futility, nothingness and absurdity of human condition in the world were all justified and led to a kind of solution by different approaches like Christianity, loss of faith, authentic existence and responsibility. In an extreme concern, the human condition in the world was pondered in different ways and the philosophy of thought tried to render an awareness of such condition for human beings. The present study aims at illustration of some approaches presented by prominent existentialists to justify the controversies in the concept of existence in human life.

Keywords: existence, existentialism, alienation, being

Procedia PDF Downloads 551

Authors: László Schmidt

Abstract:

In the context of artificial intelligence, we need to pay primary and particular attention to ethical principles not only in the design process but also during the application process. According to the European Commission's Ethical Guidelines, AI must have three main characteristics: it must be legal, ethical and stabil. We must never lose sight of the ethical principles because we risk that this new technology will not help democratic decision-making under the rule of law, but will, on the contrary, destroy it. The rapid spread and use of artificial intelligence poses an enormous challenge to both lawmaking and law enforcement. On legislation because AI permeates many areas of our daily lives that the legislator must regulate. We can see how challenging it is to regulate e.g., selfdriving cars/taxis/vans etc. Not to mention, more recently, cryptocurrencies and Chat GPT, the use of which also requires legislative intervention, from copyright to scientific use and even law of succession. Artificial intelligence also poses an extraordinary challenge to law enforcement. In criminal cases, police and prosecutors can make great use of AI in investigations, e.g. in forensics, DNA samples, reconstruction, identification, etc. But it can also be of great help in the detection of crimes committed in cyberspace. In criminal or civil court proceedings, AI can also play a major role in the evaluation of evidence and proof. For example, a photo or video or audio recording could be immediately revealed as genuine or fake. Likewise, the authenticity or falsification of a document could be determined much more quickly and cheaply than with current procedure (expert witnesses). Neither the current Hungarian Civil Procedure Act nor the Criminal Procedure Act allows the use of artificial intelligence in the evidentiary process. However, this should be changed. To use this technology in court proceedings would be very useful. The procedures would be faster, simpler, and therefore cheaper. Artificial intelligence could also replace much of the work of expert witnesses. Its introduction into judicial procedures would certainly be justified, but with due respect for human rights, the right to a fair trial and other democratic and rule of law guarantees.

Keywords: artificial intelligence, judiciary, Hungarian, court practice

Procedia PDF Downloads 71

Authors: Neeta Kumari, Gopal Pathak

Abstract:

Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

Procedia PDF Downloads 541

Authors: Masoumeh Mofarrah, Amir NahanMoghadam

Abstract:

Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise, and improve EOR methods and their application. Recently, Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic, and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization infeasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

Procedia PDF Downloads 485

Authors: Asadollah Bahrami

Abstract:

In the present study, spectral radiative entropy generation is analyzed in a furnace filled with a mixture of H₂O, CO₂ and soot at radiative equilibrium. For the angular and spatial discretization of the radiative transfer equation and radiative entropy generation equations, the discrete ordinates method and the finite volume method are used, respectively. Spectral radiative properties are obtained using the correlated-k (CK) non-gray model with updated parameters based on the HITEMP2010 high-resolution database. In order to evaluate the effects of the location of the heat source, boundary condition and wall emissivity on radiative entropy generation, five cases are considered with different conditions. The spectral and total radiative entropy generation in the system are calculated for all cases and the effects of mentioned parameters on radiative entropy generation are attentively analyzed and finally, the optimum condition is especially presented. The most important results can be stated as follows: Results demonstrate that the wall emissivity has a considerable effect on the radiative entropy generation. Also, irreversible radiative transfer at the wall with lower temperatures is the main source of radiative entropy generation in the furnaces. In addition, the effect of the location of the heat source on total radiative entropy generation is less than other factors. Eventually, it can be said that characterizing the effective parameters of radiative entropy generation provides an approach to minimizing the radiative entropy generation and enhancing the furnace's performance practicality.

Keywords: spectral radiative entropy generation, non-gray medium, correlated k(CK) model, heat source

Procedia PDF Downloads 95

Authors: Ahmed Emad Ahmed

Abstract:

This paper aims to address the concept of human resources information systems (HRIS) and how to link it to new technologies such as artificial intelligence (AI) to be implemented in two human resources processes. A literature view has been collected to cover the main points related to HRIS, AI, and BC. A study case has been presented by generating a random HRIS to apply some AI operations to it. Then, an algorithm was applied to the database to complete some human resources processes, including training and performance appraisal, using a pre-trained AI model. After that, outputs and results have been presented and discussed briefly. Finally, a conclusion has been introduced to show the ability of new technologies such as AI and ML to be applied to the human resources management processes.

Keywords: human resources new technologies, HR artificial intelligence, HRIS AI models, construction AI HRIS

Procedia PDF Downloads 165

Authors: Elabed Saud

Abstract:

This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

Procedia PDF Downloads 719

Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

Abstract:

This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

Procedia PDF Downloads 193

Authors: B. Moueddene, B. Labbaci, L. Missoum, R. Abdeldjebar

Abstract:

Quality estimation of the experimental simulation of boundary conditions is one of the problems encountered while performing an experimental program. In fact, it is not easy to estimate directly the effective influence of these simulations on the results of experimental investigation. The aim of this is article to evaluate the effect of boundary conditions uncertainties on structure response, using the change of the dynamics characteristics. The experimental models used and the correlation by the Frequency Domain Assurance Criterion (FDAC) allowed an interpretation of the change in the dynamic characteristics. The application of this strategy to stratified composite structures (glass/ polyester) has given satisfactory results.

Keywords: vibration, composite, endommagement, correlation

Procedia PDF Downloads 364

Authors: Annalisa Gaetani, Anna Nora Tassetti, Gianna Fabi

Abstract:

The hydroacoustic technology is an efficient tool to study the sea environment: the most recent advancement in artificial habitat mapping involves acoustic systems to investigate fish abundance, distribution and behavior in specific areas. Along with a detailed high-coverage bathymetric mapping of the seabed, the high-frequency Multibeam Echosounder (MBES) offers the potential of detecting fine-scale distribution of fish aggregation, combining its ability to detect at the same time the seafloor and the water column. Surveying fish schools distribution around artificial structures, MBES allows to evaluate how their presence modifies the biological natural habitat overtime in terms of fish attraction and abundance. In the last years, artificial habitat mapping experiences have been carried out by CNR-ISMAR in the Adriatic sea: fish assemblages aggregating at offshore gas platforms and artificial reefs have been systematically monitored employing different kinds of methodologies. This work focuses on two case studies: a gas extraction platform founded at 80 meters of depth in the central Adriatic sea, 30 miles far from the coast of Ancona, and the concrete and steel artificial reef of Senigallia, deployed by CNR-ISMAR about 1.2 miles offshore at a depth of 11.2 m . Relating the MBES data (metrical dimensions of fish assemblages, shape, depth, density etc.) with the results coming from other methodologies, such as experimental fishing surveys and underwater video camera, it has been possible to investigate the biological assemblage attracted by artificial structures hypothesizing which species populate the investigated area and their spatial dislocation from these artificial structures. Processing MBES bathymetric and water column data, 3D virtual scenes of the artificial habitats have been created, receiving an intuitive-looking depiction of their state and allowing overtime to evaluate their change in terms of dimensional characteristics and depth fish schools’ disposition. These MBES surveys play a leading part in the general multi-year programs carried out by CNR-ISMAR with the aim to assess potential biological changes linked to human activities on.

Keywords: artificial habitat mapping, fish assemblages, hydroacustic technology, multibeam echosounder

Procedia PDF Downloads 256

Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

Abstract:

The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

Procedia PDF Downloads 112

Authors: Alanod Alqasim, Yasmine Iskandarani, Sita Algethami, Jawaher alzughaiby

Abstract:

This study focuses on the usage of AI (Artificial Intelligence) systems and features on the Instagram application and how it influences user experience and satisfaction. The aim is to evaluate the techniques and current capabilities, restrictions, and potential future directions of AI in an Instagram application. Following a concise explanation of the core concepts underlying AI usage on Instagram. To answer this question, 19 randomly selected users were asked to complete a 9-question survey on their experience and satisfaction with the app's features (Filters, user preferences, translation tool) and authenticity. The results revealed that there were three prevalent allegations. These declarations include that Instagram has an extremely attractive user interface; secondly, Instagram creates a strong sense of community; and lastly, Instagram has an important influence on mental health.

Keywords: AI (Artificial Intelligence), instagram, features, satisfaction, experience

Procedia PDF Downloads 81

Authors: Hamed Zolfaghari, Mojtaba Kord

Abstract:

After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

Procedia PDF Downloads 92

Authors: Djoudi Ali

Abstract:

In this article, we shall expose some of the more interesting interactions of philosophy and cybernetics, some philosophical issues arising in cybernetic systems, and some questions in philosophy of our daily life related to the artificial intelligence. Many of these are fruitfully explored in the article..This article will shed light also on the importance of science and technology in our life and what are the main problems of misusing the latest technologies known under artificial intelligence and cybernatics acoording to Bertrand Russell’s point of view; then to analyse his project of reforms inculding science progress risks , the article show also the whole aspect of the impact of technology on peace , nature and on individual daily behavior, we shall discuss all issues and defies imposing by this new era , The article will invest in showing what Russell will suggest to eliminate or to slow down the dangers of these changes and what are the main solutions to protect the indiviual’s rights and responsiblities In this article, We followed a different methodology, like analysis method and sometimes the historical or descriptive method, without forgetting criticizing some conclusions when it is logically needed In the end, we mentioned what is supposed to be solutions suggested by Bertrand Russell that should be taken into considerations during the next decades and how to protect our ennvironement and the human being of any risk of disappearing

Keywords: artificial intelligence, technology, cybernetics, sience

Procedia PDF Downloads 120

Authors: Bauer Peter, Murillo Jenny

Abstract:

This paper investigates the bounds of achievable fuel efficiency improvements in engines due to cycling between two operating points assuming a series hybrid configuration . It is shown that for linear bsfc dependencies (as a function of power), cycling is only beneficial if the average power needs are smaller than the power at the optimal bsfc value. Exact expressions for the fuel efficiency gains relative to the constant output power case are derived. This asymptotic analysis is then extended to the case where transient losses due to a change in the operating point are also considered. The case of the boundary bsfc trajectory where constant power application and cycling yield the same fuel consumption.is investigated. It is shown that the boundary bsfc locations of the second non-optimal operating points is hyperbolic. The analysis of the boundary case allows to evaluate whether for a particular engine, cycling can be beneficial. The introduced concepts are illustrated through a number of real world examples, i.e. large production Diesel engines in series hybrid configurations.

Keywords: cycling, efficiency, bsfc, series hybrid, diesel, operating point

Procedia PDF Downloads 501

Authors: Sungho Kim, Jaechoul Shin, Yujin Baek

Abstract:

In recent years, due to the environmental impacts and time factor, etc., various type of pavement deterioration is increasing rapidly such as crack, pothole, rutting and roughness degradation. The Ministry of Land, Infrastructure and Transport maintains regular pavement condition of the highway and the national highway using the pavement condition survey equipment and structural survey equipment in Korea. Local governments that maintain local roads, farm roads, etc. are difficult to maintain the pavement condition using the pavement condition survey equipment depending on economic conditions, skills shortages and local conditions such as narrow roads. This study presents a quantitative evaluation method of the pavement condition through the visual inspection to overcome these problems of roads managed by local governments. It is difficult to evaluate rutting and roughness with the naked eye. However, the condition of cracks can be evaluated with the naked eye. Linear cracks (m), area cracks (m²) and potholes (number, m²) were investigated with the naked eye every 100 meters for survey the cracks. In this paper, crack ratio was calculated using the results of the condition of cracks and pavement condition was evaluated by calculated crack ratio. The pavement condition survey equipment also investigated the pavement condition in the same section in order to evaluate the reliability of pavement condition evaluation by the calculated crack ratio. The pavement condition was evaluated through the SPI (Seoul Pavement Index) and calculated crack ratio using results of field survey. The results of a comparison between 'the SPI considering only crack ratio' and 'the SPI considering rutting and roughness either' using the equipment survey data showed a margin of error below 5% when the SPI is less than 5. The SPI 5 is considered the base point to determine whether to maintain the pavement condition. It showed that the pavement condition can be evaluated using only the crack ratio. According to the analysis results of the crack ratio between the visual inspection and the equipment survey, it has an average error of 1.86%(minimum 0.03%, maximum 9.58%). Economically, the visual inspection costs only 10% of the equipment survey and will also help the economy by creating new jobs. This paper advises that local governments maintain the pavement condition through the visual investigations. However, more research is needed to improve reliability. Acknowledgment: The author would like to thank the MOLIT (Ministry of Land, Infrastructure, and Transport). This work was carried out through the project funded by the MOLIT. The project name is 'development of 20mm grade for road surface detecting roadway condition and rapid detection automation system for removal of pothole'.

Keywords: asphalt pavement maintenance, crack ratio, evaluation of asphalt pavement condition, SPI (Seoul Pavement Index), visual investigation

Procedia PDF Downloads 162

Authors: Ali Mortazavi

Abstract:

The main objective of this research project is to delve into a multitude of geomechanical risks associated with various mining methods employed within the underground mining industry. Controlling geotechnical design parameters and operational factors affecting the selection of suitable mining techniques for a given underground mining condition will be considered from a risk assessment point of view. Important geomechanical challenges will be investigated as appropriate and relevant to the commonly used underground mining methods. Given the complicated nature of rock mass in-situ and complicated boundary conditions and operational complexities associated with various underground mining methods, the selection of a safe and economic mining operation is of paramount significance. Rock failure at varying scales within the underground mining openings is always a threat to mining operations and causes human and capital losses worldwide. Geotechnical design is a major design component of all underground mines and basically dominates the safety of an underground mine. With regard to uncertainties that exist in rock characterization prior to mine development, there are always risks associated with inappropriate design as a function of mining conditions and the selected mining method. Uncertainty often results from the inherent variability of rock masse, which in turn is a function of both geological materials and rock mass in-situ conditions. The focus of this research is on developing a methodology which enables a geomechanical risk assessment of given underground mining conditions. The outcome of this research is a geotechnical risk analysis algorithm, which can be used as an aid in selecting the appropriate mining method as a function of mine design parameters (e.g., rock in-situ properties, design method, governing boundary conditions such as in-situ stress and groundwater, etc.).

Keywords: geomechanical risk assessment, rock mechanics, underground mining, rock engineering

Procedia PDF Downloads 141

Authors: S. M. Anowarul Haque, Md. Asiful Islam

Abstract:

Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: load forecasting, artificial neural network, particle swarm optimization

Procedia PDF Downloads 167

Authors: Supriyadi, Andi Intan Purnamasari, Aminuddin Kasim, Sulbadana, Mohammad Reza

Abstract:

The development of the Industrial Revolution Era 4.0 brought a significant influence in the administration of countries in all parts of the world, including Indonesia, not only in the administration and economic sectors but the ways and methods of forming laws should also be adjusted. Until now, the process of making laws carried out by the Parliament with the Government still uses the classical method. The law-making process still uses manual methods, such as typing harmonization of regulations, so that it is not uncommon for errors to occur, such as writing errors, copying articles and so on, things that require a high level of accuracy and relying on inventory and harmonization carried out manually by humans. However, this method often creates several problems due to errors and inaccuracies on the part of officers who harmonize laws after discussion and approval; this has a very serious impact on the system of law formation in Indonesia. The use of artificial intelligence in the process of forming laws seems to be justified and becomes the answer in order to minimize the disharmony of various laws and regulations. This research is normative research using the Legislative Approach and the Conceptual Approach. This research focuses on the question of how to use Artificial Intelligence for Harmonization in the Lawmaking Process.

Keywords: artificial intelligence, harmonization, laws, intelligence

Procedia PDF Downloads 151