Search results for: interlaminar damage model
17756 State Forest Management Practices by Indigenous Peoples in Dharmasraya District, West Sumatra Province, Indonesia
Authors: Abdul Mutolib, Yonariza Mahdi, Hanung Ismono
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The existence of forests is essential to human lives on earth, but its existence is threatened by forest deforestations and degradations. Forest deforestations and degradations in Indonesia is not only caused by the illegal activity by the company or the like, even today many cases in Indonesia forest damage caused by human activities, one of which cut down forests for agriculture and plantations. In West Sumatra, community forest management are the result supported the enactment of customary land tenure, including ownership of land within the forest. Indigenous forest management have a positive benefit, which gives the community an opportunity to get livelihood and income, but if forest management practices by indigenous peoples is not done wisely, then there is the destruction of forests and cause adverse effects on the environment. Based on intensive field works in Dhamasraya District employing some data collection techniques such as key informant interviews, household surveys, secondary data analysis, and satellite image interpretation. This paper answers the following questions; how the impact of forest management by local communities on forest conditions (foccus in Forest Production and Limited Production Forest) and knowledge of the local community on the benefits of forests. The site is a Nagari Bonjol, Dharmasraya District, because most of the forest in Dharmasraya located and owned by Nagari Bonjol community. The result shows that there is damage to forests in Dharmasraya because of forest management activities by local communities. Damage to the forest area of 33,500 ha in Dharmasraya because forests are converted into oil palm and rubber plantations with monocultures. As a result of the destruction of forests, water resources are also diminishing, and the community has experienced a drought in the dry season due to forest cut down and replaced by oil palm plantations. Knowledge of the local community on the benefits of low forest, the people considered that the forest does not have better benefits and cut down and converted into oil palm or rubber plantations. Local people do not understand the benefits of ecological and environmental services that forests. From the phenomena in Dharmasraya on land ownership, need to educate the local community about the importance of protecting the forest, and need a strategy to integrate forests management to keep the ecological functions that resemble the woods and counts the economic benefits for the welfare of local communities. One alternative that can be taken is to use forest management models agroforestry smallholders in accordance with the characteristics of the local community who still consider the economic, social and environmental.Keywords: community, customary land, farmer plantations, and forests
Procedia PDF Downloads 33717755 UML Model for Double-Loop Control Self-Adaptive Braking System
Authors: Heung Sun Yoon, Jong Tae Kim
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In this paper, we present an activity diagram model for double-loop control self-adaptive braking system. Since activity diagram helps to improve visibility of self-adaption, we can easily find where improvement is needed on double-loop control. Double-loop control is adopted since the design conditions and actual conditions can be different. The system is reconfigured in runtime by using double-loop control. We simulated to verify and validate our model by using MATLAB. We compared single-loop control model with double-loop control model. Simulation results show that double-loop control provides more consistent brake power control than single-loop control.Keywords: activity diagram, automotive, braking system, double-loop, self-adaptive, UML, vehicle
Procedia PDF Downloads 41717754 Vulnerability Assessment of Reinforced Concrete Frames Based on Inelastic Spectral Displacement
Authors: Chao Xu
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Selecting ground motion intensity measures reasonably is one of the very important issues to affect the input ground motions selecting and the reliability of vulnerability analysis results. In this paper, inelastic spectral displacement is used as an alternative intensity measure to characterize the ground motion damage potential. The inelastic spectral displacement is calculated based modal pushover analysis and inelastic spectral displacement based incremental dynamic analysis is developed. Probability seismic demand analysis of a six story and an eleven story RC frame are carried out through cloud analysis and advanced incremental dynamic analysis. The sufficiency and efficiency of inelastic spectral displacement are investigated by means of regression and residual analysis, and compared with elastic spectral displacement. Vulnerability curves are developed based on inelastic spectral displacement. The study shows that inelastic spectral displacement reflects the impact of different frequency components with periods larger than fundamental period on inelastic structural response. The damage potential of ground motion on structures with fundamental period prolonging caused by structural soften can be caught by inelastic spectral displacement. To be compared with elastic spectral displacement, inelastic spectral displacement is a more sufficient and efficient intensity measure, which reduces the uncertainty of vulnerability analysis and the impact of input ground motion selection on vulnerability analysis result.Keywords: vulnerability, probability seismic demand analysis, ground motion intensity measure, sufficiency, efficiency, inelastic time history analysis
Procedia PDF Downloads 35417753 Digital Reconstruction of Museum's Statue Using 3D Scanner for Cultural Preservation in Indonesia
Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi
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The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.Keywords: 3D reconstruction, light pattern structure, texture mapping, museum
Procedia PDF Downloads 46817752 Structural Equation Modeling Approach: Modeling the Impact of Social Marketing Programs on Combating Female Genital Mutilation in the Sudanese Society
Authors: Nada Abdelsadig Moahamed Saied
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Female Genital Mutilation (FGM) and other similar traditional cultural practices pose a significant problem for Sudanese society. Such actions are severe and seriously detrimental to people's health since they are based on false social perceptions. To address these problems, numerous institutions and organizations were compelled to act rapidly. Female circumcision, or FGM, is one of the riskiest practices. It is referred to as the excision of the genitalia. Any surgeries involving the total or partial removal of the external female genitalia for non-medical reasons fall under this category. The results of FGM can vary depending on the kind and degree of the operation. These can be categorized as short-term, mid-term, or long-term issues. Infections, including the Human, blood, discomfort, and difficulty urinating are the immediate effects. FGM is defined by the World Health Organization (WHO) as practices that purposefully damage or modify female genital organs for non-medical purposes. It often takes place between the ages of one and fifteen. The girl's right to decide on important choices affecting her sexual and reproductive health is violated because the act is usually performed without her consent and frequently against her will. UNICEF, the United Nations International Children's Emergency Fund, aggressively combats the issue of FGM in Sudan. Numerous programs were started by NGOs to stop the practice. To our knowledge, no scientific study has been conducted to evaluate the effects of such social marketing techniques on simulating and comprehending society’s feelings surrounding FGM. This study proposes the development of a structural equation model aiming to determine the impact of awareness programs on people’s intentions to adopt the behavior of abandoning FGM based on theoretical models of behavior change. The model incorporates all the relevant factors that contribute to FGM and possible strategic actions to tackle this problem. The theoretical backdrop for FGM is presented in the next section, which also explains the practice's history, justifications, and potential treatments. The methodology section that follows describes the structural equation model. The proposed model, which compiles all the pertinent elements into a single image, is presented in the fourth part. Finally, conclusions are reached, and suggestions for further research are made.Keywords: social marketing, policy-making, behavioral change, female genital mutilation, culture
Procedia PDF Downloads 7717751 Allium Cepa Extract Provides Neuroprotection Against Ischemia Reperfusion Induced Cognitive Dysfunction and Brain Damage in Mice
Authors: Jaspal Rana, Alkem Laboratories, Baddi, Himachal Pradesh, India Chitkara University, Punjab, India
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Oxidative stress has been identified as an underlying cause of ischemia-reperfusion (IR) related cognitive dysfunction and brain damage. Therefore, antioxidant based therapies to treat IR injury are being investigated. Allium cepa L. (onion) is used as culinary medicine and is documented to have marked antioxidant effects. Hence, the present study was designed to evaluate the effect of A. cepa outer scale extract (ACE) against IR induced cognition and biochemical deficit in mice. ACE was prepared by maceration with 70% methanol and fractionated into ethylacetate and aqueous fractions. Bilateral common carotid artery occlusion for 10 min followed by 24 h reperfusion was used to induce cerebral IR injury. Following IR injury, ACE (100 and 200 mg/kg) was administered orally to animals for 7 days once daily. Behavioral outcomes (memory and sensorimotor functions) were evaluated using Morris water maze and neurological severity score. Cerebral infarct size, brain thiobarbituric acid reactive species, reduced glutathione, and superoxide dismutase activity was also determined. Treatment with ACE significantly ameliorated IR mediated deterioration of memory and sensorimotor functions and rise in brain oxidative stress in animals. The results of the present investigation revealed that ACE improved functional outcomes after cerebral IR injury, which may be attributed to its antioxidant properties.Keywords: stroke, neuroprotection, ischemia reperfusion, herbal drugs
Procedia PDF Downloads 10617750 Evaluation of Turbulence Modelling of Gas-Liquid Two-Phase Flow in a Venturi
Authors: Mengke Zhan, Cheng-Gang Xie, Jian-Jun Shu
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A venturi flowmeter is a common device used in multiphase flow rate measurement in the upstream oil and gas industry. Having a robust computational model for multiphase flow in a venturi is desirable for understanding the gas-liquid and fluid-pipe interactions and predicting pressure and phase distributions under various flow conditions. A steady Eulerian-Eulerian framework is used to simulate upward gas-liquid flow in a vertical venturi. The simulation results are compared with experimental measurements of venturi differential pressure and chord-averaged gas holdup in the venturi throat section. The choice of turbulence model is nontrivial in the multiphase flow modelling in a venturi. The performance cross-comparison of the k-ϵ model, Reynolds stress model (RSM) and shear-stress transport (SST) k-ω turbulence model is made in the study. In terms of accuracy and computational cost, the SST k-ω turbulence model is observed to be the most efficient.Keywords: computational fluid dynamics (CFD), gas-liquid flow, turbulence modelling, venturi
Procedia PDF Downloads 17317749 Evaluation of High Damping Rubber Considering Initial History through Dynamic Loading Test and Program Analysis
Authors: Kyeong Hoon Park, Taiji Mazuda
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High damping rubber (HDR) bearings are dissipating devices mainly used in seismic isolation systems and have a great damping performance. Although many studies have been conducted on the dynamic model of HDR bearings, few models can reflect phenomena such as dependency of experienced shear strain on initial history. In order to develop a model that can represent the dependency of experienced shear strain of HDR by Mullins effect, dynamic loading test was conducted using HDR specimen. The reaction of HDR was measured by applying a horizontal vibration using a hybrid actuator under a constant vertical load. Dynamic program analysis was also performed after dynamic loading test. The dynamic model applied in program analysis is a bilinear type double-target model. This model is modified from typical bilinear model. This model can express the nonlinear characteristics related to the initial history of HDR bearings. Based on the dynamic loading test and program analysis results, equivalent stiffness and equivalent damping ratio were calculated to evaluate the mechanical properties of HDR and the feasibility of the bilinear type double-target model was examined.Keywords: base-isolation, bilinear model, high damping rubber, loading test
Procedia PDF Downloads 12317748 Analysis of Reliability of Mining Shovel Using Weibull Model
Authors: Anurag Savarnya
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The reliability of the various parts of electric mining shovel has been assessed through the application of Weibull Model. The study was initiated to find reliability of components of electric mining shovel. The paper aims to optimize the reliability of components and increase the life cycle of component. A multilevel decomposition of the electric mining shovel was done and maintenance records were used to evaluate the failure data and appropriate system characterization was done to model the system in terms of reasonable number of components. The approach used develops a mathematical model to assess the reliability of the electric mining shovel components. The model can be used to predict reliability of components of the hydraulic mining shovel and system performance. Reliability is an inherent attribute to a system. When the life-cycle costs of a system are being analyzed, reliability plays an important role as a major driver of these costs and has considerable influence on system performance. It is an iterative process that begins with specification of reliability goals consistent with cost and performance objectives. The data were collected from an Indian open cast coal mine and the reliability of various components of the electric mining shovel has been assessed by following a Weibull Model.Keywords: reliability, Weibull model, electric mining shovel
Procedia PDF Downloads 51517747 Discussion on the Impact and Improvement Strategy of Bike Sharing on Urban Space
Authors: Bingying Liu, Dandong Ge, Xinlan Zhang, Haoyang Liang
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Over the past two years, a new generation of No-Pile Bike sharing, represented by the Ofo, Mobike and HelloBike, has sprung up in various cities in China, and spread rapidly in countries such as Britain, Japan, the United States and Singapore. As a new green public transportation mode, bike sharing can bring a series of benefits to urban space. At first, this paper analyzes the specific impact of bike sharing on urban space in China. Based on the market research and data analyzing, it is found that bike sharing can improve the quality of urban space in three aspects: expanding the radius of public transportation service, filling service blind spots, alleviating urban traffic congestion, and enhancing the vitality of urban space. On the other hand, due to the immature market and the imperfect system, bike sharing has gradually revealed some difficulties, such as parking chaos, malicious damage, safety problems, imbalance between supply and demand, and so on. Then the paper investigates the characteristics of shared bikes, business model, operating mechanism on Chinese market currently. Finally, in order to make bike sharing serve urban construction better, this paper puts forward some specific countermeasures from four aspects. In terms of market operations, it is necessary to establish a public-private partnership model and set up a unified bike-sharing integrated management platform. From technical methods level, the paper proposes to develop an intelligent parking system for regulating parking. From policy formulation level, establishing a bike-sharing assessment mechanism would strengthen supervision. As to urban planning, sharing data and redesigning slow roadway is beneficial for transportation and spatial planning.Keywords: bike sharing, impact analysis, improvement strategy, urban space
Procedia PDF Downloads 17117746 Application and Assessment of Artificial Neural Networks for Biodiesel Iodine Value Prediction
Authors: Raquel M. De sousa, Sofiane Labidi, Allan Kardec D. Barros, Alex O. Barradas Filho, Aldalea L. B. Marques
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Several parameters are established in order to measure biodiesel quality. One of them is the iodine value, which is an important parameter that measures the total unsaturation within a mixture of fatty acids. Limitation of unsaturated fatty acids is necessary since warming of a higher quantity of these ones ends in either formation of deposits inside the motor or damage of lubricant. Determination of iodine value by official procedure tends to be very laborious, with high costs and toxicity of the reagents, this study uses an artificial neural network (ANN) in order to predict the iodine value property as an alternative to these problems. The methodology of development of networks used 13 esters of fatty acids in the input with convergence algorithms of backpropagation type were optimized in order to get an architecture of prediction of iodine value. This study allowed us to demonstrate the neural networks’ ability to learn the correlation between biodiesel quality properties, in this case iodine value, and the molecular structures that make it up. The model developed in the study reached a correlation coefficient (R) of 0.99 for both network validation and network simulation, with Levenberg-Maquardt algorithm.Keywords: artificial neural networks, biodiesel, iodine value, prediction
Procedia PDF Downloads 60717745 Calycosin Ameliorates Osteoarthritis by Regulating the Imbalance Between Chondrocyte Synthesis and Catabolism
Authors: Hong Su, Qiuju Yan, Wei Du, En Hu, Zhaoyu Yang, Wei Zhang, Yusheng Li, Tao Tang, Wang yang, Shushan Zhao
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Osteoarthritis (OA) is a severe chronic inflammatory disease. As the main active component of Astragalus mongholicus Bunge, a classic traditional ethnic herb, calycosin exhibits anti-inflammatory action and its mechanism of exact targets for OA have yet to be determined. In this study, we established an anterior cruciate ligament transection (ACLT) mouse model. Mice were randomized to sham, OA, and calycosin groups. Cartilage synthesis markers type II collagen (Col-2) and SRY-Box Transcription Factor 9 (Sox-9) increased significantly after calycosin gavage. While cartilage matrix degradation index cyclooxygenase-2 (COX-2), phosphor-epidermal growth factor receptor (p-EGFR), and matrix metalloproteinase-9 (MMP9) expression were decreased. With the help of network pharmacology and molecular docking, these results were confirmed in chondrocyte ATDC5 cells. Our results indicated that the calycosin treatment significantly improved cartilage damage, this was probably attributed to reversing the imbalance between chondrocyte synthesis and catabolism.Keywords: calycosin, osteoarthritis, network pharmacology, molecular docking, inflammatory, cyclooxygenase 2
Procedia PDF Downloads 10617744 R Software for Parameter Estimation of Spatio-Temporal Model
Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan
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In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.Keywords: GSTAR Model, MAPE, OLS method, oil production, R software
Procedia PDF Downloads 24317743 Forecasting Models for Steel Demand Uncertainty Using Bayesian Methods
Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow
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A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.Keywords: forecasting model, steel demand uncertainty, hierarchical Bayesian framework, exponential smoothing method
Procedia PDF Downloads 35017742 Developing Fuzzy Logic Model for Reliability Estimation: Case Study
Authors: Soroor K. H. Al-Khafaji, Manal Mohammad Abed
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The research aim of this paper is to evaluate the reliability of a complex engineering system and to design a fuzzy model for the reliability estimation. The designed model has been applied on Vegetable Oil Purification System (neutralization system) to help the specialist user based on the concept of FMEA (Failure Mode and Effect Analysis) to estimate the reliability of the repairable system at the vegetable oil industry. The fuzzy model has been used to predict the system reliability for a future time period, depending on a historical database for the two past years. The model can help to specify the system malfunctions and to predict its reliability during a future period in more accurate and reasonable results compared with the results obtained by the traditional method of reliability estimation.Keywords: fuzzy logic, reliability, repairable systems, FMEA
Procedia PDF Downloads 61617741 Application of a Model-Free Artificial Neural Networks Approach for Structural Health Monitoring of the Old Lidingö Bridge
Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi
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Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring
Procedia PDF Downloads 21017740 Developing a Systems Dynamics Model for Security Management
Authors: Kuan-Chou Chen
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This paper will demonstrate a simulation model of an information security system by using the systems dynamic approach. The relationships in the system model are designed to be simple and functional and do not necessarily represent any particular information security environments. The purpose of the paper aims to develop a generic system dynamic information security system model with implications on information security research. The interrelated and interdependent relationships of five primary sectors in the system dynamic model will be presented in this paper. The integrated information security systems model will include (1) information security characteristics, (2) users, (3) technology, (4) business functions, and (5) policy and management. Environments, attacks, government and social culture will be defined as the external sector. The interactions within each of these sectors will be depicted by system loop map as well. The proposed system dynamic model will not only provide a conceptual framework for information security analysts and designers but also allow information security managers to remove the incongruity between the management of risk incidents and the management of knowledge and further support information security managers and decision makers the foundation for managerial actions and policy decisions.Keywords: system thinking, information security systems, security management, simulation
Procedia PDF Downloads 43117739 Location Quotients Model in Turkey’s Provinces and Nuts II Regions
Authors: Semih Sözer
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One of the most common issues in economic systems is understanding characteristics of economic activities in cities and regions. Although there are critics to economic base models in conceptual and empirical aspects, these models are useful tools to examining the economic structure of a nation, regions or cities. This paper uses one of the methodologies of economic base models namely the location quotients model. Data for this model includes employment numbers of provinces and NUTS II regions in Turkey. Time series of data covers the years of 1990, 2000, 2003, and 2009. Aim of this study is finding which sectors are export-base and which sectors are import-base in provinces and regions. Model results show that big provinces or powerful regions (population, size etc.) mostly have basic sectors in their economic system. However, interesting facts came from different sectors in different provinces and regions in the model results.Keywords: economic base, location quotients model, regional economics, regional development
Procedia PDF Downloads 42617738 Media Richness Perspective on Web 2.0 Usage for Knowledge Creation: The Case of the Cocoa Industry in Ghana
Authors: Albert Gyamfi
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Cocoa plays critical role in the socio-economic development of Ghana. Meanwhile, smallholder farmers most of whom are illiterate dominate the industry. According to the cocoa-based agricultural knowledge and information system (AKIS) model knowledge is created and transferred to the industry between three key actors: cocoa researchers, extension experts, and cocoa farmers. Dwelling on the SECI model, the media richness theory (MRT), and the AKIS model, a conceptual model of web 2.0-based AKIS model (AKIS 2.0) is developed and used to assess the possible effects of social media usage for knowledge creation in the Ghanaian cocoa industry. A mixed method approach with a survey questionnaire was employed, and a second-order multi-group structural equation model (SEM) was used to analyze the data. The study concludes that the use of web 2.0 applications for knowledge creation would lead to sustainable interactions among the key knowledge actors for effective knowledge creation in the cocoa industry in Ghana.Keywords: agriculture, cocoa, knowledge, media, web 2.0
Procedia PDF Downloads 33517737 Artificial Neural Network Based Approach for Estimation of Individual Vehicle Speed under Mixed Traffic Condition
Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh
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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.Keywords: speed model, artificial neural network, arterial, mixed traffic
Procedia PDF Downloads 38917736 Vibro-Acoustic Modulation for Crack Detection in Windmill Blades
Authors: Abdullah Alnutayfat, Alexander Sutin
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One of the most important types of renewable energy resources is wind energy which can be produced by wind turbines. The blades of the wind turbine are exposed to the pressure of the harsh environment, which causes a significant issue for the wind power industry in terms of the maintenance cost and failure of blades. One of the reliable methods for blade inspection is the vibroacoustic structural health monitoring (SHM) method which examines information obtained from the structural vibrations of the blade. However, all vibroacoustic SHM techniques are based on comparing the structural vibration of intact and damaged structures, which places a practical limit on their use. Methods for nonlinear vibroacoustic SHM are more sensitive to damage and cracking and do not need to be compared to data from the intact structure. This paper presents the Vibro-Acoustic Modulation (VAM) method based on the modulation of high-frequency (probe wave) by low-frequency loads (pump wave) produced by the blade rotation. The blade rotation alternates bending stress due to gravity, leading to crack size variations and variations in the blade resonance frequency. This method can be used with the classical SHM vibration method in which the blade is excited by piezoceramic actuator patches bonded to the blade and receives the vibration response from another piezoceramic sensor. The VAM modification of this method analyzes the spectra of the detected signal and their sideband components. We suggest the VAM model as the simple mechanical oscillator, where the parameters of the oscillator (resonance frequency and damping) are varied due to low-frequency blade rotation. This model uses the blade vibration parameters and crack influence on the blade resonance properties from previous research papers to predict the modulation index (MI).Keywords: wind turbine blades, damaged detection, vibro-acoustic structural health monitoring, vibro-acoustic modulation
Procedia PDF Downloads 8517735 Modeling Heat-Related Mortality Based on Greenhouse Emissions in OECD Countries
Authors: Anderson Ngowa Chembe, John Olukuru
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Greenhouse emissions by human activities are known to irreversibly increase global temperatures through the greenhouse effect. This study seeks to propose a mortality model with sensitivity to heat-change effects as one of the underlying parameters in the model. As such, the study sought to establish the relationship between greenhouse emissions and mortality indices in five OECD countries (USA, UK, Japan, Canada & Germany). Upon the establishment of the relationship using correlation analysis, an additional parameter that accounts for the sensitivity of heat-changes to mortality rates was incorporated in the Lee-Carter model. Based on the proposed model, new parameter estimates were calculated using iterative algorithms for optimization. Finally, the goodness of fit for the original Lee-Carter model and the proposed model were compared using deviance comparison. The proposed model provides a better fit to mortality rates especially in USA, UK and Germany where the mortality indices have a strong positive correlation with the level of greenhouse emissions. The results of this study are of particular importance to actuaries, demographers and climate-risk experts who seek to use better mortality-modeling techniques in the wake of heat effects caused by increased greenhouse emissions.Keywords: climate risk, greenhouse emissions, Lee-Carter model, OECD
Procedia PDF Downloads 34517734 Design Channel Non Persistent CSMA MAC Protocol Model for Complex Wireless Systems Based on SoC
Authors: Ibrahim A. Aref, Tarek El-Mihoub, Khadiga Ben Musa
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This paper presents Carrier Sense Multiple Access (CSMA) communication model based on SoC design methodology. Such model can be used to support the modelling of the complex wireless communication systems, therefore use of such communication model is an important technique in the construction of high performance communication. SystemC has been chosen because it provides a homogeneous design flow for complex designs (i.e. SoC and IP based design). We use a swarm system to validate CSMA designed model and to show how advantages of incorporating communication early in the design process. The wireless communication created through the modeling of CSMA protocol that can be used to achieve communication between all the agents and to coordinate access to the shared medium (channel).Keywords: systemC, modelling, simulation, CSMA
Procedia PDF Downloads 42817733 A Deep Learning Based Integrated Model For Spatial Flood Prediction
Authors: Vinayaka Gude Divya Sampath
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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.Keywords: deep learning, disaster management, flood prediction, urban flooding
Procedia PDF Downloads 14917732 Deflection Behaviour of Retaining Wall with Pile for Pipeline on Slope of Soft Soil
Authors: Mutadi
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Pipes laying on an unstable slope of soft soil are prone to movement. Pipelines that are buried in unstable slope areas will move due to lateral loads from soil movement, which can cause damage to the pipeline. A small-scale laboratory model of the reinforcement system of piles supported by retaining walls was conducted to investigate the effect of lateral load on the reinforcement. In this experiment, the lateral forces of 0.3 kN, 0.35 kN, and 0.4 kN and vertical force of 0.05 kN, 0.1 kN, and 0.15 kN were used. Lateral load from the electric jack is equipped with load cell and vertical load using the cement-steel box. To validate the experimental result, a finite element program named 2-D Plaxis was used. The experimental results showed that with an increase in lateral loading, the displacement of the reinforcement system increased. For a Vertical Load, 0.1 kN and versus a lateral load of 0.3 kN causes a horizontal displacement of 0.35 mm and an increase of 2.94% for loading of 0.35 kN and an increase of 8.82% for loading 0.4 kN. The pattern is the same in the finite element method analysis, where there was a 6.52% increase for 0.35 kN loading and an increase to 23.91 % for 0.4 kN loading. In the same Load, the Reinforcement System is reliable, as shown in Safety Factor on dry conditions were 3.3, 2.824 and 2.474, and on wet conditions were 2.98, 2.522 and 2.235.Keywords: soft soil, deflection, wall, pipeline
Procedia PDF Downloads 16317731 Model of Transhipment and Routing Applied to the Cargo Sector in Small and Medium Enterprises of Bogotá, Colombia
Authors: Oscar Javier Herrera Ochoa, Ivan Dario Romero Fonseca
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This paper presents a design of a model for planning the distribution logistics operation. The significance of this work relies on the applicability of this fact to the analysis of small and medium enterprises (SMEs) of dry freight in Bogotá. Two stages constitute this implementation: the first one is the place where optimal planning is achieved through a hybrid model developed with mixed integer programming, which considers the transhipment operation based on a combined load allocation model as a classic transshipment model; the second one is the specific routing of that operation through the heuristics of Clark and Wright. As a result, an integral model is obtained to carry out the step by step planning of the distribution of dry freight for SMEs in Bogotá. In this manner, optimum assignments are established by utilizing transshipment centers with that purpose of determining the specific routing based on the shortest distance traveled.Keywords: transshipment model, mixed integer programming, saving algorithm, dry freight transportation
Procedia PDF Downloads 23317730 A Model for Predicting Organic Compounds Concentration Change in Water Associated with Horizontal Hydraulic Fracturing
Authors: Ma Lanting, S. Eguilior, A. Hurtado, Juan F. Llamas Borrajo
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Horizontal hydraulic fracturing is a technology to increase natural gas flow and improve productivity in the low permeability formation. During this drilling operation tons of flowback and produced water which contains many organic compounds return to the surface with a potential risk of influencing the surrounding environment and human health. A mathematical model is urgently needed to represent organic compounds in water transportation process behavior and the concentration change with time throughout the hydraulic fracturing operation life cycle. A comprehensive model combined Organic Matter Transport Dynamic Model with Two-Compartment First-order Model Constant (TFRC) Model has been established to quantify the organic compounds concentration. This algorithm model is composed of two transportation parts based on time factor. For the fast part, the curve fitting technique is applied using flowback water data from the Marcellus shale gas site fracturing and the coefficients of determination (R2) from all analyzed compounds demonstrate a high experimental feasibility of this numerical model. Furthermore, along a decade of drilling the concentration ratio curves have been estimated by the slow part of this model. The result shows that the larger value of Koc in chemicals, the later maximum concentration in water will reach, as well as all the maximum concentrations percentage would reach up to 90% of initial concentration from shale formation within a long sufficient period.Keywords: model, shale gas, concentration, organic compounds
Procedia PDF Downloads 22717729 Unified Structured Process for Health Analytics
Authors: Supunmali Ahangama, Danny Chiang Choon Poo
Abstract:
Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.Keywords: agile methodology, health analytics, unified process model, UML
Procedia PDF Downloads 50717728 Comparison of Central Light Reflex Width-to-Retinal Vessel Diameter Ratio between Glaucoma and Normal Eyes by Using Edge Detection Technique
Authors: P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong
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Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.Keywords: glaucoma, retinal vessel, central light reflex, image processing, fundus photograph, edge detection
Procedia PDF Downloads 32517727 Pesticidal Potential of Selected Aqueous Plant Extracts for the Control of Webber Caterpillar (Hymenis Recurvalis Fab.) Infestation on Amaranthus in Kashere,Gombe State, Nigeria
Authors: Degri M. M, Samaila A. E., Simon L., Joly G. A.
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The amaranth leaf webber caterpillar (Hymenia recurvalis Fab.) was found to cause serious leaf damage by perforation and reduce amaranth growth and yield. It is a major limiting factor in amaranth production. Field experiments were conducted during 2022 and 2023 with the aim of assessing insecticidal potential of five selected plant leaf extracts, namely Moringa oleifera, Azadiractha indica A. Juss , Balanites aegyptiaca Del., Momordica balsamina and Hyptis suaveolens using Lambda.cyhalothrin 2.5 EC, a synthetic insecticide as a check. The experiment was conducted in a randomized complete block design (RCBD) replicated three times. Results showed that A.indica and H.suaveolous were more effective in reducing H .recurvalis population, leaf perforation, leaf damaged and improved amaranth plant growth and yield. This was closely followed by B. aegyptiaca and M. balsamina while M. oleifera had the lowest effect on the use of pest population and damage. Lambda.cyhalothrin, a synthetic insecticide, was found to be superior to the five plant extracts. The result showed that A. indica and H. suaveolens improved the growth and yield of amaranth during the study period. The study, therefore, recommended the two plant extracts for the control of leaf webber caterpillar (H. recurvalis) to limited resource farmers and as a good alternative to Lambda.cyhalothrin 2.5EC in the study area.Keywords: Amaranth, leaf Webber plant extracts, Lambda cyhalothrin, rainfed
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