Search results for: damage prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4522

Search results for: damage prediction

2542 Development of Hit Marks on Clothes Using Amino Acid Reagents

Authors: Hyo-Su Lim, Ye-Eun Song, Eun-Bi Lee, Sang-Yoon Lee, Young-Il Seo, Jin-Pyo Kim, Nam-Kyu Park

Abstract:

If we analogize any physical external force given to victims in many crimes including violence, it would be possible not only to presume mutual action between victims and suspects, but to make a deduction of more various facts in cases. Therefore, the aim of this study is to identify criminal tools through secretion on clothes by using amino acid reagents such as Ninhydrin, DFO(1,8-dizafluoren-9-one), 1,2 – IND (1,2-indanedione) which are reacting to skin secretion. For more effective collecting condition, porcine skin which is physiologically similar to human was used. Although there were little differences of shape identification according to sensitivity, amino acid reagents were able to identify the fist, foot, and baseball bat. Furthermore, we conducted the experiments for developmental variations through change over time setting up 5-weeks period including first damage as variation factor, and developing materials in each action through certain reagents. Specimen level of development depending on change over time was identified. As a result, each of initial level of development was seen no changes.

Keywords: hit marks, amino acid reagents, porcine skin, criminal tool

Procedia PDF Downloads 262
2541 Far-Field Noise Prediction of Tandem Cylinders Using Incompressible Large Eddy Simulation

Authors: Jesus Ruano, Francesc Xavier Trias, Asensi Oliva

Abstract:

A three-dimensional incompressible Large Eddy Simulation (LES) is performed to compute the hydrodynamic field around a pair of tandem cylinders. Symmetry-preserving schemes will be used during this simulation in conjunction with Finite Volume Method (FVM) to obtain the hydrodynamic field around the selected geometry. A set of results consisting of pressure and velocity and the combination of them will be stored at different surfaces near the cylinders as the initial input for the second part of the study. A post-processing of the obtained results based on Ffowcs-Williams and Hawkings (FWH) equation with a Fourier Transform of the acoustic sources will be used to compute noise at several probes located far away from the region where the hydrodynamics are computed. Directivities as well as spectral profile of the obtained acoustic field will be analyzed.

Keywords: far-field noise, Ffowcs-Williams and Hawkings, finite volume method, large eddy simulation, long-span bodies

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2540 Prediction of Solidification Behavior of Al Alloy in a Cube Mold Cavity

Authors: N. P. Yadav, Deepti Verma

Abstract:

This paper focuses on the mathematical modeling for solidification of Al alloy in a cube mould cavity to study the solidification behavior of casting process. The parametric investigation of solidification process inside the cavity was performed by using computational solidification/melting model coupled with Volume of fluid (VOF) model. The implicit filling algorithm is used in this study to understand the overall process from the filling stage to solidification in a model metal casting process. The model is validated with past studied at same conditions. The solidification process are analyzed by including the effect of pouring velocity and temperature of liquid metal, effect of wall temperature as well natural convection from the wall and geometry of the cavity. These studies show the possibility of various defects during solidification process.

Keywords: buoyancy driven flow, natural convection driven flow, residual flow, secondary flow, volume of fluid

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2539 Performance Analysis of N-Tier Grid Protocol for Resource Constrained Wireless Sensor Networks

Authors: Jai Prakash Prasad, Suresh Chandra Mohan

Abstract:

Modern wireless sensor networks (WSN) consist of small size, low cost devices which are networked through tight wireless communications. WSN fundamentally offers cooperation, coordination among sensor networks. Potential applications of wireless sensor networks are in healthcare, natural disaster prediction, data security, environmental monitoring, home appliances, entertainment etc. The design, development and deployment of WSN based on application requirements. The WSN design performance is optimized to improve network lifetime. The sensor node resources constrain such as energy and bandwidth imposes the limitation on efficient resource utilization and sensor node management. The proposed N-Tier GRID routing protocol focuses on the design of energy efficient large scale wireless sensor network for improved performance than the existing protocol.

Keywords: energy efficient, network lifetime, sensor networks, wireless communication

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2538 Development of a Decision-Making Method by Using Machine Learning Algorithms in the Early Stage of School Building Design

Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

Abstract:

Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

Procedia PDF Downloads 86
2537 Settlement Prediction for Tehran Subway Line-3 via FLAC3D and ANFIS

Authors: S. A. Naeini, A. Khalili

Abstract:

Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

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2536 Prediction of the Thermodynamic Properties of Hydrocarbons Using Gaussian Process Regression

Authors: N. Alhazmi

Abstract:

Knowing the thermodynamics properties of hydrocarbons is vital when it comes to analyzing the related chemical reaction outcomes and understanding the reaction process, especially in terms of petrochemical industrial applications, combustions, and catalytic reactions. However, measuring the thermodynamics properties experimentally is time-consuming and costly. In this paper, Gaussian process regression (GPR) has been used to directly predict the main thermodynamic properties - standard enthalpy of formation, standard entropy, and heat capacity -for more than 360 cyclic and non-cyclic alkanes, alkenes, and alkynes. A simple workflow has been proposed that can be applied to directly predict the main properties of any hydrocarbon by knowing its descriptors and chemical structure and can be generalized to predict the main properties of any material. The model was evaluated by calculating the statistical error R², which was more than 0.9794 for all the predicted properties.

Keywords: thermodynamic, Gaussian process regression, hydrocarbons, regression, supervised learning, entropy, enthalpy, heat capacity

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2535 Experimental and Numerical Investigation of Fluid Flow inside Concentric Heat Exchanger Using Different Inlet Geometry Configurations

Authors: Mohamed M. Abo Elazm, Ali I. Shehata, Mohamed M. Khairat Dawood

Abstract:

A computational fluid dynamics (CFD) program FLUENT has been used to predict the fluid flow and heat transfer distribution within concentric heat exchangers. The effect of inlet inclination angle has been investigated with Reynolds number range (3000 – 4000) and Pr=0.71. The heat exchanger is fabricated from copper concentric inner tube with a length of 750 mm. The effects of hot to cold inlet flow rate ratio (MH/MC), Reynolds's number and of inlet inclination angle of 30°, 45°, 60° and 90° are considered. The results showed that the numerical prediction shows a good agreement with experimental measurement. The results present an efficient design of concentric tube heat exchanger to enhance the heat transfer by increasing the swirling effect.

Keywords: heat transfer, swirling effect, CFD, inclination angle, concentric tube heat exchange

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2534 Analysis and Prediction of Netflix Viewing History Using Netflixlatte as an Enriched Real Data Pool

Authors: Amir Mabhout, Toktam Ghafarian, Amirhossein Farzin, Zahra Makki, Sajjad Alizadeh, Amirhossein Ghavi

Abstract:

The high number of Netflix subscribers makes it attractive for data scientists to extract valuable knowledge from the viewers' behavioural analyses. This paper presents a set of statistical insights into viewers' viewing history. After that, a deep learning model is used to predict the future watching behaviour of the users based on previous watching history within the Netflixlatte data pool. Netflixlatte in an aggregated and anonymized data pool of 320 Netflix viewers with a length 250 000 data points recorded between 2008-2022. We observe insightful correlations between the distribution of viewing time and the COVID-19 pandemic outbreak. The presented deep learning model predicts future movie and TV series viewing habits with an average loss of 0.175.

Keywords: data analysis, deep learning, LSTM neural network, netflix

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2533 Study of Cavitation Erosion of Pump-Storage Hydro Power Plant Prototype

Authors: Tine Cencič, Marko Hočevar, Brane Širok

Abstract:

An experimental investigation has been made to detect cavitation in pump–storage hydro power plant prototype suffering from cavitation in pump mode. Vibrations and acoustic emission on the housing of turbine bearing and pressure fluctuations in the draft tube were measured and the corresponding signals have been recorded and analyzed. The analysis was based on the analysis of high-frequency content of measured variables. The pump-storage hydro power plant prototype has been operated at various input loads and Thoma numbers. Several estimators of cavitation were evaluated according to coefficient of determination between Thoma number and cavitation estimators. The best results were achieved with a compound discharge coefficient cavitation estimator. Cavitation estimators were evaluated in several intervals of frequencies. Also, a prediction of cavitation erosion was made in order to choose the appropriate maintenance and repair periods.

Keywords: cavitation erosion, turbine, cavitation measurement, fluid dynamics

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2532 Cyclostationary Gaussian Linearization for Analyzing Nonlinear System Response Under Sinusoidal Signal and White Noise Excitation

Authors: R. J. Chang

Abstract:

A cyclostationary Gaussian linearization method is formulated for investigating the time average response of nonlinear system under sinusoidal signal and white noise excitation. The quantitative measure of cyclostationary mean, variance, spectrum of mean amplitude, and mean power spectral density of noise is analyzed. The qualitative response behavior of stochastic jump and bifurcation are investigated. The validity of the present approach in predicting the quantitative and qualitative statistical responses is supported by utilizing Monte Carlo simulations. The present analysis without imposing restrictive analytical conditions can be directly derived by solving non-linear algebraic equations. The analytical solution gives reliable quantitative and qualitative prediction of mean and noise response for the Duffing system subjected to both sinusoidal signal and white noise excitation.

Keywords: cyclostationary, duffing system, Gaussian linearization, sinusoidal, white noise

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2531 Artificial Steady-State-Based Nonlinear MPC for Wheeled Mobile Robot

Authors: M. H. Korayem, Sh. Ameri, N. Yousefi Lademakhi

Abstract:

To ensure the stability of closed-loop nonlinear model predictive control (NMPC) within a finite horizon, there is a need for appropriate design terminal ingredients, which can be a time-consuming and challenging effort. Otherwise, in order to ensure the stability of the control system, it is necessary to consider an infinite predictive horizon. Increasing the prediction horizon increases computational demand and slows down the implementation of the method. In this study, a new technique has been proposed to ensure system stability without terminal ingredients. This technique has been employed in the design of the NMPC algorithm, leading to a reduction in the computational complexity of designing terminal ingredients and computational burden. The studied system is a wheeled mobile robot (WMR) subjected to non-holonomic constraints. Simulation has been investigated for two problems: trajectory tracking and adjustment mode.

Keywords: wheeled mobile robot, nonlinear model predictive control, stability, without terminal ingredients

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2530 Pressure-Detecting Method for Estimating Levitation Gap Height of Swirl Gripper

Authors: Kaige Shi, Chao Jiang, Xin Li

Abstract:

The swirl gripper is an electrically activated noncontact handling device that uses swirling airflow to generate a lifting force. This force can be used to pick up a workpiece placed underneath the swirl gripper without any contact. It is applicable, for example, in the semiconductor wafer production line, where contact must be avoided during the handling and moving of a workpiece to minimize damage. When a workpiece levitates underneath a swirl gripper, the gap height between them is crucial for safe handling. Therefore, in this paper, we propose a method to estimate the levitation gap height by detecting pressure at two points. The method is based on theoretical model of the swirl gripper, and has been experimentally verified. Furthermore, the force between the gripper and the workpiece can also be estimated using the detected pressure. As a result, the nonlinear relationship between the force and gap height can be linearized by adjusting the rotating speed of the fan in the swirl gripper according to the estimated force and gap height. The linearized relationship is expected to enhance handling stability of the workpiece.

Keywords: swirl gripper, noncontact handling, levitation, gap height estimation

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2529 Analysis and Prediction of the Behavior of the Landslide at Ain El Hammam, Algeria Based on the Second Order Work Criterion

Authors: Zerarka Hizia, Akchiche Mustapha, Prunier Florent

Abstract:

The landslide of Ain El Hammam (AEH) is characterized by a complex geology and a high hydrogeology hazard. AEH's perpetual reactivation compels us to look closely at its triggers and to better understand the mechanisms of its evolution in mass and in depth. This study builds a numerical model to simulate the influencing factors such as precipitation, non-saturation, and pore pressure fluctuations, using Plaxis software. For a finer analysis of instabilities, we use Hill's criterion, based on the sign of the second order work, which is the most appropriate material stability criterion for non-associated elastoplastic materials. The results of this type of calculation allow us, in theory, to predict the shape and position of the slip surface(s) which are liable to ground movements of the slope, before reaching the rupture given by the plastic limit of Mohr Coulomb. To validate the numerical model, an analysis of inclinometer measures is performed to confirm the direction of movement and kinematic of the sliding mechanism of AEH’s slope.

Keywords: landslide, second order work, precipitation, inclinometers

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2528 Finite Element Analysis of the Ordinary Reinforced Concrete Bridge Piers

Authors: Nabin Raj Chaulagain

Abstract:

Most of the concrete bridges in Nepal constructed during 90's and before are made up of low strength ordinary concrete which might be one of the reasons for damage in higher magnitude earthquake. Those bridges were designed by the outdated bridge codes which might not account the large seismic loads. This research investigates the seismic vulnerability of the existing single column ordinary concrete bridge pier by finite element modeling, using the software Seismostruct. The existing bridge pier capacity has been assessed using nonlinear pushover analysis and performance is compared after retrofitting those pier models with CFRP. Furthermore, the seismic evaluation was made by conducting cyclic loading test at different drift percentage. The performance analysis of bridge pier by nonlinear pushover analysis is further validated by energy dissipation phenomenon measured from the hysteric loop for each model of ordinary concrete piers.

Keywords: finite element modeling, ordinary concrete bridge pier, performance analysis, retrofitting

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2527 Challenges of Integrating Islamic Education with Contemporary Secular System in Igaland, Kogi State Of Nigeria

Authors: Yunusa Odiba

Abstract:

Islam, from its root is a divine religion and it does not exercise anything except within the scope of its divinity-its culture, tradition morality, and the like. The damage done to the legacies, traditions, culture, morality, viability, continued existence and relevance of the Islamic religious way of life by the prevalent western secular education system in the Muslim world has become a thing of interest to many scholars especially, the Muslim scholars, hence, advocating the integration of Islamic education with the western circular educational system. The aim is to produce a new generation of dedicated Muslims whose education has prepared them for the challenges of contemporary materialistic circulation alongside real Islamic knowledge. This paper, however, examines the process of integrating Islamic schools with the contemporary western based schools that would under-take the unification which should function as basic organ of Muslim ideological revivalism, cultural retention, identity formation, socio-economic development, and scientific and ecological inventiveness.

Keywords: challenges, integrating, Islamic education, secular system, Igalaland

Procedia PDF Downloads 689
2526 Effective Removal of Tetrodotoxin with Fiber Mat Containing Activated Charcoal

Authors: Min Sik Kim, Hwa Sung Shin

Abstract:

From 2013, small eel farms, which are located in Han River Estuary, South Korea suffer damage because of unknown massive perish. In the middle of discussion that the cause of perish could be environmental changes or waste water, a large amount of unknown nemertean was discovered during that time. Some nemerteans are known releasing neurotoxin substance. In this study, we isolated intestinal bacteria using selective media and conducted 16s rDNA microbial identification by gene alignment. As a result, there was a type of bacteria producing TTX, blocks sodium-channel inducing organism’s death. TTX production from the bacteria was confirmed by ELISA and liquid chromatography coupled with mass spectrometer. Additionally, the activated-charcoal which has an ability to absorb small molecules like toxin was applied to fibrous mesh to prevent ingestion of aquatic organisms and increase applicable area. The viability of zebrafish in the water with TTX and charcoal fiber mat were not decreased meaning it could be used for solving the perishing problem in fish farm.

Keywords: nemertean, TTX, fiber mat, activated charcoal, zebrafish

Procedia PDF Downloads 204
2525 Natural Hazards and Their Costs in Albanian Part of Ohrid Graben

Authors: Mentor Sulollari

Abstract:

Albania, according to (UNU-EHS) United Nations University, Institute for Environment and Human Security studies for 2015, is listed as the number one country in Europe for the possibility to be caught by natural catastrophes. This is conditioned by unstudied human activity, which has seriously damaged the environment. Albanian part of Ohrid graben that lies in Southeast of Albania, is endangered by landslides and floods, as a result of uncontrolled urban development and low level of investment in infrastructure, rugged terrain in its western part and capricious climate caused by global warming. To be dealt with natural disasters, which cause casualties and material damage, it is important to study them in order to anticipate and reduce damages in future. As part of this study is the construction of natural hazards map, which show us where they are distributed, and which are the vulnerable areas. This article will also be dealing with socio-economic and environmental costs of those events and what are the measures to be taken to reduce them.

Keywords: flooding, landslides, natural catastrophes mapping, Pogradec, lake Ohrid, Albanian part of Ohrid graben

Procedia PDF Downloads 291
2524 Survey on Malware Detection

Authors: Doaa Wael, Naswa Abdelbaky

Abstract:

Malware is malicious software that is built to cause destructive actions and damage information systems and networks. Malware infections increase rapidly, and types of malware have become more sophisticated, which makes the malware detection process more difficult. On the other side, the Internet of Things IoT technology is vulnerable to malware attacks. These IoT devices are always connected to the internet and lack security. This makes them easy for hackers to access. These malware attacks are becoming the go-to attack for hackers. Thus, in order to deal with this challenge, new malware detection techniques are needed. Currently, building a blockchain solution that allows IoT devices to download any file from the internet and to verify/approve whether it is malicious or not is the need of the hour. In recent years, blockchain technology has stood as a solution to everything due to its features like decentralization, persistence, and anonymity. Moreover, using blockchain technology overcomes some difficulties in malware detection and improves the malware detection ratio over-than the techniques that do not utilize blockchain technology. In this paper, we study malware detection models which are based on blockchain technology. Furthermore, we elaborate on the effect of blockchain technology in malware detection, especially in the android environment.

Keywords: malware analysis, blockchain, malware attacks, malware detection approaches

Procedia PDF Downloads 79
2523 Determining Earthquake Performances of Existing Reinforced Concrete Buildings by Using ANN

Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

Abstract:

In this study, an artificial intelligence-based (ANN based) analytical method has been developed for analyzing earthquake performances of the reinforced concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code- 2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: artificial intelligence, earthquake, performance, reinforced concrete

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2522 Long-Term Psychosocial Issues Among COVID-19 Survivors in Kathmandu Valley

Authors: Nabin Prasad Joshi, Samiksha Neupane

Abstract:

Since its emergence in December 2019, Corona Virus disease has impacted several countries, affecting many people. The first cases were recorded in Wuhan, China, between December 2019 and January 2020. Italy is one of the affected countries in Europe. The relations between India and Nepal have reverted to the pre-pandemic period as both countries have open borders. The study focused on the overall psychosocial impact among covid-19 survivors in their life what are the changes they are facing after covid also how are their relations with friends and relatives after they have covid in different municipalities of Kathmandu valley, where people from different regions are living in rent and have their own houses. Support from friends and family during a pandemic can prevent it if it is strong enough. Nonetheless, there were risk factors for psychosocial damage, including a lack of or insufficient family and social support, psychiatric assistance, and inadequate insurance or compensation. Poorer mental health outcomes were inversely correlated with social rejection or isolation.

Keywords: stress, anxiety, depression, Kathmandu

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2521 Facile Synthesis of Potassium Vanadium Fluorophosphate: Semiconducting Properties and Its Photocatalytic Performance for Dye Degradation under Visible Light

Authors: S. Tartaya, R. Bagtache, A. M. Djaballah, M. Trari

Abstract:

Due to the increase in the trade of colored products and their applications in various fields such as cosmetic, food, textile, pharmaceutical industries, etc. Dyes constitute a large part of the contaminants in wastewater and cause serious damage in the environment and the aquatic system. Photocatalytic systems are highly efficient processes for treating wastewater in the presence of semiconductor photocatalysts. In this field, we report our contribution by synthesizing a potassium vanadium fluorophosphate compound KVPO4F (which is abbreviated KVPOF) by a simplified hydrothermal method at 180°C for 5 days. The as synthesized product has been characterized physically and photoelectrochemically. The indirect optical transition of 1.88 eV, determined from the diffuse reflectance, was assigned to the charge transfer. Moreover, the curve (C-2–E) of the KVPOF displayed n-type character of the semiconductor. Even more, interestingly, the photocatalytic performance was evaluated through the photo-degradation of cationic dye Methyl Violet (MV). An abatement of 61% was obtained after 6 h of irradiation under visible light.

Keywords: KVPO4F, photocatalysis, semiconductor, wastewater, environment

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2520 Destructive and Nondestructive Characterization of Advanced High Strength Steels DP1000/1200

Authors: Carla M. Machado, André A. Silva, Armando Bastos, Telmo G. Santos, J. Pamies Teixeira

Abstract:

Advanced high-strength steels (AHSS) are increasingly being used in automotive components. The use of AHSS sheets plays an important role in reducing weight, as well as increasing the resistance to impact in vehicle components. However, the large-scale use of these sheets becomes more difficult due to the limitations during the forming process. Such limitations are due to the elastically driven change of shape of a metal sheet during unloading and following forming, known as the springback effect. As the magnitude of the springback tends to increase with the strength of the material, it is among the most worrisome problems in the use of AHSS steels. The prediction of strain hardening, especially under non-proportional loading conditions, is very limited due to the lack of constitutive models and mainly due to very limited experimental tests. It is very clear from the literature that in experimental terms there is not much work to evaluate deformation behavior under real conditions, which implies a very limited and scarce development of mathematical models for these conditions. The Bauschinger effect is also fundamental to the difference between kinematic and isotropic hardening models used to predict springback in sheet metal forming. It is of major importance to deepen the phenomenological knowledge of the mechanical and microstructural behavior of the materials, in order to be able to reproduce with high fidelity the behavior of extension of the materials by means of computational simulation. For this, a multi phenomenological analysis and characterization are necessary to understand the various aspects involved in plastic deformation, namely the stress-strain relations and also the variations of electrical conductivity and magnetic permeability associated with the metallurgical changes due to plastic deformation. Aiming a complete mechanical-microstructural characterization, uniaxial tensile tests involving successive cycles of loading and unloading were performed, as well as biaxial tests such as the Erichsen test. Also, nondestructive evaluation comprising eddy currents to verify microstructural changes due to plastic deformation and ultrasonic tests to evaluate the local variations of thickness were made. The material parameters for the stable yield function and the monotonic strain hardening were obtained using uniaxial tension tests in different material directions and balanced biaxial tests. Both the decrease of the modulus of elasticity and Bauschinger effect were determined through the load-unload tensile tests. By means of the eddy currents tests, it was possible to verify changes in the magnetic permeability of the material according to the different plastically deformed areas. The ultrasonic tests were an important aid to quantify the local plastic extension. With these data, it is possible to parameterize the different models of kinematic hardening to better approximate the results obtained by simulation with the experimental results, which are fundamental for the springback prediction of the stamped parts.

Keywords: advanced high strength steel, Bauschinger effect, sheet metal forming, springback

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2519 Archaeoseismological Evidence for a Possible Destructive Earthquake in the 7th Century AD at the Ancient Sites of Bulla Regia and Chemtou (NW Tunisia): Seismotectonic and Structural Implications

Authors: Abdelkader Soumaya, Noureddine Ben Ayed, Ali Kadri, Said Maouche, Hayet Khayati Ammar, Ahmed Braham

Abstract:

The historic sites of Bulla Regia and Chemtou are among the most important archaeological monuments in northwestern Tunisia, which flourished as large, wealthy settlements during the Roman and Byzantine periods (2nd to 7th centuries AD). An archaeoseismological study provides the first indications about the impact of a possible ancient strong earthquake in the destruction of these cities. Based on previous archaeological excavation results, including numismatic evidence, pottery, economic meltdown and urban transformation, the abrupt ruin and destruction of the cities of Bulla Regia and Chemtou can be bracketed between 613 and 647 AD. In this study, we carried out the first attempt to use the analysis of earthquake archaeological effects (EAEs) that were observed during our field investigations in these two historic cities. The damage includes different types of EAEs: folds on regular pavements, displaced and deformed vaults, folded walls, tilted walls, collapsed keystones in arches, dipping broken corners, displaced-fallen columns, block extrusions in walls, penetrative fractures in brick-made walls and open fractures on regular pavements. These deformations are spread over 10 different sectors or buildings and include 56 measured EAEs. The structural analysis of the identified EAEs can indicate an ancient destructive earthquake that probably destroyed the Bulla Regia and Chemtou archaeological sites. We then analyzed these measurements using structural geological analysis to obtain the maximum horizontal strain of the ground (e.g., S ₕₘₐₓ) on each building-oriented damage. After the collection and analysis of these strain datasets, we proceed to plot the orientation of Sₕₘₐₓ trajectories on the map of the archaeological site (Bulla Regia). We concluded that the obtained Sₕₘₐₓ trajectories within this site could then be related to the mean direction of ground motion (oscillatory movement of the ground) triggered by a seismic event, as documented for some historical earthquakes across the world. These Sₕₘₐₓ orientations closely match the current active stress field, as highlighted by some instrumental events in northern Tunisia. In terms of the seismic source, we strongly suggest that the reactivation of a neotectonic strike-slip fault trending N50E must be responsible for this probable historic earthquake and the recent instrumental seismicity in this area. This fault segment, affecting the folded quaternary deposits south of Jebel Rebia, passes through the monument of Bulla Regia. Stress inversion of the observed and measured data along this fault shows an N150 - 160 trend of Sₕₘₐₓ under a transpressional tectonic regime, which is quite consistent with the GPS data and the state of the current stress field in this region.

Keywords: NW Tunisia, archaeoseismology, earthquake archaeological effect, bulla regia - Chemtou, seismotectonic, neotectonic fault

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2518 Valuing Cultural Ecosystem Services of Natural Treatment Systems Using Crowdsourced Data

Authors: Andrea Ghermandi

Abstract:

Natural treatment systems such as constructed wetlands and waste stabilization ponds are increasingly used to treat water and wastewater from a variety of sources, including stormwater and polluted surface water. The provision of ancillary benefits in the form of cultural ecosystem services makes these systems unique among water and wastewater treatment technologies and greatly contributes to determine their potential role in promoting sustainable water management practices. A quantitative analysis of these benefits, however, has been lacking in the literature. Here, a critical assessment of the recreational and educational benefits in natural treatment systems is provided, which combines observed public use from a survey of managers and operators with estimated public use as obtained using geotagged photos from social media as a proxy for visitation rates. Geographic Information Systems (GIS) are used to characterize the spatial boundaries of 273 natural treatment systems worldwide. Such boundaries are used as input for the Application Program Interfaces (APIs) of two popular photo-sharing websites (Flickr and Panoramio) in order to derive the number of photo-user-days, i.e., the number of yearly visits by individual photo users in each site. The adequateness and predictive power of four univariate calibration models using the crowdsourced data as a proxy for visitation are evaluated. A high correlation is found between photo-user-days and observed annual visitors (Pearson's r = 0.811; p-value < 0.001; N = 62). Standardized Major Axis (SMA) regression is found to outperform Ordinary Least Squares regression and count data models in terms of predictive power insofar as standard verification statistics – such as the root mean square error of prediction (RMSEP), the mean absolute error of prediction (MAEP), the reduction of error (RE), and the coefficient of efficiency (CE) – are concerned. The SMA regression model is used to estimate the intensity of public use in all 273 natural treatment systems. System type, influent water quality, and area are found to statistically affect public use, consistently with a priori expectations. Publicly available information regarding the home location of the sampled visitors is derived from their social media profiles and used to infer the distance they are willing to travel to visit the natural treatment systems in the database. Such information is analyzed using the travel cost method to derive monetary estimates of the recreational benefits of the investigated natural treatment systems. Overall, the findings confirm the opportunities arising from an integrated design and management of natural treatment systems, which combines the objectives of water quality enhancement and provision of cultural ecosystem services through public use in a multi-functional approach and compatibly with the need to protect public health.

Keywords: constructed wetlands, cultural ecosystem services, ecological engineering, waste stabilization ponds

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2517 Automated Prediction of HIV-associated Cervical Cancer Patients Using Data Mining Techniques for Survival Analysis

Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

Abstract:

Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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2516 Integrating Deterministic and Probabilistic Safety Assessment to Decrease Risk & Energy Consumption in a Typical PWR

Authors: Ebrahim Ghanbari, Mohammad Reza Nematollahi

Abstract:

Integrating deterministic and probabilistic safety assessment (IDPSA) is one of the most commonly used issues in the field of safety analysis of power plant accident. It has also been recognized today that the role of human error in creating these accidents is not less than systemic errors, so the human interference and system errors in fault and event sequences are necessary. The integration of these analytical topics will be reflected in the frequency of core damage and also the study of the use of water resources in an accident such as the loss of all electrical power of the plant. In this regard, the SBO accident was simulated for the pressurized water reactor in the deterministic analysis issue, and by analyzing the operator's behavior in controlling the accident, the results of the combination of deterministic and probabilistic assessment were identified. The results showed that the best performance of the plant operator would reduce the risk of an accident by 10%, as well as a decrease of 6.82 liters/second of the water sources of the plant.

Keywords: IDPSA, human error, SBO, risk

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2515 Solar Power Forecasting for the Bidding Zones of the Italian Electricity Market with an Analog Ensemble Approach

Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva

Abstract:

The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.

Keywords: analog ensemble, electricity market, PV forecast, solar energy

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2514 Forced Swim Stress Does Not Induce Structural Chromosomal Aberrations in Rat Bone Marrow

Authors: Mohammad Y. Alfaifi

Abstract:

Anything that poses a challenge or a threat to our well-being is a stress. Understanding the genetic material and cellular response of rats threatened with Repeated swimming stress provides insights that can influence human health. The aim of the present study was to assess the genetical damage and cytological changes caused by exposure of the test organism (Rattus rattus) to forced swimming stress. For this purpose, animals have been submerged in water path 15 minutes daily for 2 weeks. Following that, we performed a micronuclei (MN) test using MNNCE (Micronucleated normocromatic erythrocytes) and MNPCE (Micronucleated polychromatic erythrocytes), NDI (Nuclear division index) and cytological parameters using NDCI (nuclear division cytotoxicity index), necrotic and apoptotic cells in rat's bone marrow samples. Results showed that there was a slightly but not significant increase in the frequency of micronucleated as well as in cytological parameters in bone marrow cells.

Keywords: submergence stress, micronucleus, NDI, NDCI, toxicity, chromosomal aberrations

Procedia PDF Downloads 389
2513 Role of Macro and Technical Indicators in Equity Risk Premium Prediction: A Principal Component Analysis Approach

Authors: Naveed Ul Hassan, Bilal Aziz, Maryam Mushtaq, Imran Ameen Khan

Abstract:

Equity risk premium (ERP) is the stock return in excess of risk free return. Even though it is an essential topic of finance but still there is no common consensus upon its forecasting. For forecasting ERP, apart from the macroeconomic variables attention is devoted to technical indicators as well. For this purpose, set of 14 technical and 14 macro-economic variables is selected and all forecasts are generated based on a standard predictive regression framework, where ERP is regressed on a constant and a lag of a macroeconomic variable or technical indicator. The comparative results showed that technical indicators provide better indications about ERP estimates as compared to macro-economic variables. The relative strength of ERP predictability is also investigated by using National Bureau of Economic Research (NBER) data of business cycle expansion and recessions and found that ERP predictability is more than twice for recessions as compared to expansions.

Keywords: equity risk premium, forecasting, macroeconomic indicators, technical indicators

Procedia PDF Downloads 301