Search results for: runoff estimation
1957 Identification of Suitable Rainwater Harvesting Sites Using Geospatial Techniques with AHP in Chacha Watershed, Jemma Sub-Basin Upper Blue Nile, Ethiopia
Authors: Abrha Ybeyn Gebremedhn, Yitea Seneshaw Getahun, Alebachew Shumye Moges, Fikrey Tesfay
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Rainfed agriculture in Ethiopia has failed to produce enough food, to achieve the increasing demand for food. Pinpointing the appropriate site for rainwater harvesting (RWH) have a substantial contribution to increasing the available water and enhancing agricultural productivity. The current study related to the identification of the potential RWH sites was conducted at the Chacha watershed central highlands of Ethiopia which is endowed with rugged topography. The Geographic Information System with Analytical Hierarchy Process was used to generate the different maps for identifying appropriate sites for RWH. In this study, 11 factors that determine the RWH locations including slope, soil texture, runoff depth, land cover type, annual average rainfall, drainage density, lineament intensity, hydrologic soil group, antecedent moisture content, and distance to the roads were considered. The overall analyzed result shows that 10.50%, 71.10%, 17.90%, and 0.50% of the areas were found under highly, moderately, marginally suitable, and unsuitable areas for RWH, respectively. The RWH site selection was found highly dependent on a slope, soil texture, and runoff depth; moderately dependent on drainage density, annual average rainfall, and land use land cover; but less dependent on the other factors. The highly suitable areas for rainwater harvesting expansion are lands having a flat topography with a soil textural class of high-water holding capacity that can produce high runoff depth. The application of this study could be a baseline for planners and decision-makers and support any strategy adoption for appropriate RWH site selection.Keywords: runoff depth, antecedent moisture condition, AHP, weighted overlay, water resource
Procedia PDF Downloads 181956 Drying and Transport Processes in Distributed Hydrological Modelling Based on Finite Volume Schemes (Iber Model)
Authors: Carlos Caro, Ernest Bladé, Pedro Acosta, Camilo Lesmes
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The drying-wet process is one of the topics to be more careful in distributed hydrological modeling using finite volume schemes as a means of solving the equations of Saint Venant. In a hydrologic and hydraulic computer model, surface flow phenomena depend mainly on the different flow accumulation and subsequent runoff generation. These accumulations are generated by routing, cell by cell, from the heights of water, which begin to appear due to the rain at each instant of time. Determine when it is considered a dry cell and when considered wet to include in the full calculation is an issue that directly affects the quantification of direct runoff or generation of flow at the end of a zone of contribution by accumulations flow generated from cells or finite volume.Keywords: hydrology, transport processes, hydrological modelling, finite volume schemes
Procedia PDF Downloads 3591955 Combined Localization, Beamforming, and Interference Threshold Estimation in Underlay Cognitive System
Authors: Omar Nasr, Yasser Naguib, Mohamed Hafez
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This paper aims at providing an innovative solution for blind interference threshold estimation in an underlay cognitive network to be used in adaptive beamforming by secondary user Transmitter and Receiver. For the task of threshold estimation, blind detection of modulation and SNR are used. For the sake of beamforming several localization algorithms are compared to settle on best one for cognitive environment. Beamforming algorithms as LCMV (Linear Constraint Minimum Variance) and MVDR (Minimum Variance Distortion less) are also proposed and compared. The idea of just nulling the primary user after knowledge of its location is discussed against the idea of working under interference threshold.Keywords: cognitive radio, underlay, beamforming, MUSIC, MVDR, LCMV, threshold estimation
Procedia PDF Downloads 5541954 Simulation and Experimental Study on Tensile Force Measurement of PS Tendons Using an Embedded EM Sensor
Authors: ByoungJoon Yu, Junkyeong Kim, Seunghee Park
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The tensile force estimation PS tendons is in great demand on monitoring the structural health condition of PSC girder bridges. Measuring the tensile force of the PS tendons inside the PSC girder using conventional methods is hard due to its location. In this paper, an embedded EM sensor based tensile force estimation of PS tendon was carried out by measuring the permeability of the PS tendons in PSC girder. The permeability is changed due to the induced tensile force by the magneto-elastic effect and the effect then lead to the gradient change of the B-H curve. An experiment was performed to obtain the signals from the EM sensor using three down-scaled PSC girder models. The permeability of PS tendons was proportionally decreased according to the increase of the tensile forces. To verify the experiment results, a simulation of tensile force estimation will be conducted in further study. Consequently, it is expected that both the experiment results and the simulation results increase the accuracy of the tensile force estimation, and then it could be one of the solutions for evaluating the performance of PSC girder.Keywords: tensile force estimation, embedded EM sensor, PSC girder, EM sensor simulation, cross section loss
Procedia PDF Downloads 4431953 Introduction of Robust Multivariate Process Capability Indices
Authors: Behrooz Khalilloo, Hamid Shahriari, Emad Roghanian
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Process capability indices (PCIs) are important concepts of statistical quality control and measure the capability of processes and how much processes are meeting certain specifications. An important issue in statistical quality control is parameter estimation. Under the assumption of multivariate normality, the distribution parameters, mean vector and variance-covariance matrix must be estimated, when they are unknown. Classic estimation methods like method of moment estimation (MME) or maximum likelihood estimation (MLE) makes good estimation of the population parameters when data are not contaminated. But when outliers exist in the data, MME and MLE make weak estimators of the population parameters. So we need some estimators which have good estimation in the presence of outliers. In this work robust M-estimators for estimating these parameters are used and based on robust parameter estimators, robust process capability indices are introduced. The performances of these robust estimators in the presence of outliers and their effects on process capability indices are evaluated by real and simulated multivariate data. The results indicate that the proposed robust capability indices perform much better than the existing process capability indices.Keywords: multivariate process capability indices, robust M-estimator, outlier, multivariate quality control, statistical quality control
Procedia PDF Downloads 2501952 Channel Estimation Using Deep Learning for Reconfigurable Intelligent Surfaces-Assisted Millimeter Wave Systems
Authors: Ting Gao, Mingyue He
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Reconfigurable intelligent surfaces (RISs) are expected to be an important part of next-generation wireless communication networks due to their potential to reduce the hardware cost and energy consumption of millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) technology. However, owing to the lack of signal processing abilities of the RIS, the perfect channel state information (CSI) in RIS-assisted communication systems is difficult to acquire. In this paper, the uplink channel estimation for mmWave systems with a hybrid active/passive RIS architecture is studied. Specifically, a deep learning-based estimation scheme is proposed to estimate the channel between the RIS and the user. In particular, the sparse structure of the mmWave channel is exploited to formulate the channel estimation as a sparse reconstruction problem. To this end, the proposed approach is derived to obtain the distribution of non-zero entries in a sparse channel. After that, the channel is reconstructed by utilizing the least-squares (LS) algorithm and compressed sensing (CS) theory. The simulation results demonstrate that the proposed channel estimation scheme is superior to existing solutions even in low signal-to-noise ratio (SNR) environments.Keywords: channel estimation, reconfigurable intelligent surface, wireless communication, deep learning
Procedia PDF Downloads 1111951 A New Criterion Using Pose and Shape of Objects for Collision Risk Estimation
Authors: DoHyeung Kim, DaeHee Seo, ByungDoo Kim, ByungGil Lee
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As many recent researches being implemented in aviation and maritime aspects, strong doubts have been raised concerning the reliability of the estimation of collision risk. It is shown that using position and velocity of objects can lead to imprecise results. In this paper, therefore, a new approach to the estimation of collision risks using pose and shape of objects is proposed. Simulation results are presented validating the accuracy of the new criterion to adapt to collision risk algorithm based on fuzzy logic.Keywords: collision risk, pose, shape, fuzzy logic
Procedia PDF Downloads 4901950 Temporal Estimation of Hydrodynamic Parameter Variability in Constructed Wetlands
Authors: Mohammad Moezzibadi, Isabelle Charpentier, Adrien Wanko, Robert Mosé
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The calibration of hydrodynamic parameters for subsurface constructed wetlands (CWs) is a sensitive process since highly non-linear equations are involved in unsaturated flow modeling. CW systems are engineered systems designed to favour natural treatment processes involving wetland vegetation, soil, and their microbial flora. Their significant efficiency at reducing the ecological impact of urban runoff has been recently proved in the field. Numerical flow modeling in a vertical variably saturated CW is here carried out by implementing the Richards model by means of a mixed hybrid finite element method (MHFEM), particularly well adapted to the simulation of heterogeneous media, and the van Genuchten-Mualem parametrization. For validation purposes, MHFEM results were compared to those of HYDRUS (a software based on a finite element discretization). As van Genuchten-Mualem soil hydrodynamic parameters depend on water content, their estimation is subject to considerable experimental and numerical studies. In particular, the sensitivity analysis performed with respect to the van Genuchten-Mualem parameters reveals a predominant influence of the shape parameters α, n and the saturated conductivity of the filter on the piezometric heads, during saturation and desaturation. Modeling issues arise when the soil reaches oven-dry conditions. A particular attention should also be brought to boundary condition modeling (surface ponding or evaporation) to be able to tackle different sequences of rainfall-runoff events. For proper parameter identification, large field datasets would be needed. As these are usually not available, notably due to the randomness of the storm events, we thus propose a simple, robust and low-cost numerical method for the inverse modeling of the soil hydrodynamic properties. Among the methods, the variational data assimilation technique introduced by Le Dimet and Talagrand is applied. To that end, a variational data assimilation technique is implemented by applying automatic differentiation (AD) to augment computer codes with derivative computations. Note that very little effort is needed to obtain the differentiated code using the on-line Tapenade AD engine. Field data are collected for a three-layered CW located in Strasbourg (Alsace, France) at the water edge of the urban water stream Ostwaldergraben, during several months. Identification experiments are conducted by comparing measured and computed piezometric head by means of the least square objective function. The temporal variability of hydrodynamic parameter is then assessed and analyzed.Keywords: automatic differentiation, constructed wetland, inverse method, mixed hybrid FEM, sensitivity analysis
Procedia PDF Downloads 1281949 Geodesign Application for Bio-Swale Design: A Data-Driven Design Approach for a Case Site in Ottawa Street North in Hamilton, Ontario, Canada
Authors: Adele Pierre, Nadia Amoroso
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Changing climate patterns are resulting in increased in storm severity, challenging traditional methods of managing stormwater runoff. This research compares a system of bioswales to existing curb and gutter infrastructure in a post-industrial streetscape of Hamilton, Ontario. Using the geodesign process, including rule-based set parameters and an integrated approach combining geospatial information with stakeholder input, a section of Ottawa St. North was modelled to show how green infrastructure can ease the burden on aging, combined sewer systems. Qualitative data was gathered from residents of the neighbourhood through field notes, and quantitative geospatial data through GIS and site analysis. Parametric modelling was used to generate multiple design scenarios, each visualizing resulting impacts on stormwater runoff along with their calculations. The selected design scenarios offered both an aesthetically pleasing urban bioswale street-scape system while minimizing and controlling stormwater runoff. Interactive maps, videos and the 3D model were presented for stakeholder comment via ESRI’s (Environmental System Research Institute) web-scene. The results of the study demonstrate powerful tools that can assist landscape architects in designing, collaborating and communicating stormwater strategies.Keywords: bioswale, geodesign, data-driven and rule-based design, geodesign, GIS, stormwater management
Procedia PDF Downloads 1511948 Classic Training of a Neural Observer for Estimation Purposes
Authors: R. Loukil, M. Chtourou, T. Damak
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This paper investigates the training of multilayer neural network using the classic approach. Then, for estimation purposes, we suggest the use of a specific neural observer that we study its training algorithm which is the back-propagation one in the case of the disponibility of the state and in the case of an unmeasurable state. A MATLAB simulation example will be studied to highlight the usefulness of this kind of observer.Keywords: training, estimation purposes, neural observer, back-propagation, unmeasurable state
Procedia PDF Downloads 5391947 Off-Line Parameter Estimation for the Induction Motor Drive System
Authors: Han-Woong Ahn, In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee
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It is important to accurately identify machine parameters for direct vector control. To obtain the parameter values, traditional methods can be used such as no-load and rotor locked tests. However, there are many differences between values obtained from the traditional tests and actual values. In addition, there are drawbacks that additional equipment and cost are required for the experiment. Therefore, it is hard to temporary operation to estimate induction motor parameters. Therefore, this paper deals with the estimation algorithm of induction motor parameters without a motor operation and the measurement from additional equipment such as sensors and dynamometer. The validity and usefulness of the estimation algorithm considering inverter nonlinearity is verified by comparing the conventional method with the proposed method.Keywords: induction motor, parameter, off-line estimation, inverter nonlinearity
Procedia PDF Downloads 5011946 Deep Learning-Based Channel Estimation for RIS-Assisted Unmanned Aerial Vehicle-Enabled Wireless Communication System
Authors: Getaneh Berie Tarekegn
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Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles
Procedia PDF Downloads 191945 Signal Estimation and Closed Loop System Performance in Atrial Fibrillation Monitoring with Communication Channels
Authors: Mohammad Obeidat, Ayman Mansour
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In this paper a unique issue rising from feedback control of Atrial Fibrillation monitoring system with embedded communication channels has been investigated. One of the important factors to measure the performance of the feedback control closed loop system is disturbance and noise attenuation factor. It is important that the feedback system can attenuate such disturbances on the atrial fibrillation heart rate signals. Communication channels depend on network traffic conditions and deliver different throughput, implying that the sampling intervals may change. Since signal estimation is updated on the arrival of new data, its dynamics actually change with the sampling interval. Consequently, interaction among sampling, signal estimation, and the controller will introduce new issues in remotely controlled Atrial Fibrillation system. This paper treats a remotely controlled atrial fibrillation system with one communication channel which connects between the heart rate and rhythm measurements to the remote controller. Typical and optimal signal estimation schemes is represented by a signal averaging filter with its time constant derived from the step size of the signal estimation algorithm.Keywords: atrial fibrillation, communication channels, closed loop, estimation
Procedia PDF Downloads 3521944 Mathematics Model Approaching: Parameter Estimation of Transmission Dynamics of HIV and AIDS in Indonesia
Authors: Endrik Mifta Shaiful, Firman Riyudha
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Acquired Immunodeficiency Syndrome (AIDS) is one of the world's deadliest diseases caused by the Human Immunodeficiency Virus (HIV) that infects white blood cells and cause a decline in the immune system. AIDS quickly became a world epidemic disease that affects almost all countries. Therefore, mathematical modeling approach to the spread of HIV and AIDS is needed to anticipate the spread of HIV and AIDS which are widespread. The purpose of this study is to determine the parameter estimation on mathematical models of HIV transmission and AIDS using cumulative data of people with HIV and AIDS each year in Indonesia. In this model, there are parameters of r ∈ [0,1) which is the effectiveness of the treatment in patients with HIV. If the value of r is close to 1, the number of people with HIV and AIDS will decline toward zero. The estimation results indicate when the value of r is close to unity, there will be a significant decline in HIV patients, whereas in AIDS patients constantly decreases towards zero.Keywords: HIV, AIDS, parameter estimation, mathematical models
Procedia PDF Downloads 2181943 Blind Super-Resolution Reconstruction Based on PSF Estimation
Authors: Osama A. Omer, Amal Hamed
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Successful blind image Super-Resolution algorithms require the exact estimation of the Point Spread Function (PSF). In the absence of any prior information about the imagery system and the true image; this estimation is normally done by trial and error experimentation until an acceptable restored image quality is obtained. Multi-frame blind Super-Resolution algorithms often have disadvantages of slow convergence and sensitiveness to complex noises. This paper presents a Super-Resolution image reconstruction algorithm based on estimation of the PSF that yields the optimum restored image quality. The estimation of PSF is performed by the knife-edge method and it is implemented by measuring spreading of the edges in the reproduced HR image itself during the reconstruction process. The proposed image reconstruction approach is using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. A series of experiment results show that the proposed method can outperform other previous work robustly and efficiently.Keywords: blind, PSF, super-resolution, knife-edge, blurring, bilateral, L1 norm
Procedia PDF Downloads 3361942 Parameter Estimation via Metamodeling
Authors: Sergio Haram Sarmiento, Arcady Ponosov
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Based on appropriate multivariate statistical methodology, we suggest a generic framework for efficient parameter estimation for ordinary differential equations and the corresponding nonlinear models. In this framework classical linear regression strategies is refined into a nonlinear regression by a locally linear modelling technique (known as metamodelling). The approach identifies those latent variables of the given model that accumulate most information about it among all approximations of the same dimension. The method is applied to several benchmark problems, in particular, to the so-called ”power-law systems”, being non-linear differential equations typically used in Biochemical System Theory.Keywords: principal component analysis, generalized law of mass action, parameter estimation, metamodels
Procedia PDF Downloads 4791941 Density-based Denoising of Point Cloud
Authors: Faisal Zaman, Ya Ping Wong, Boon Yian Ng
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Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this, we present a novel approach using modified kernel density estimation (KDE) technique with bilateral filtering to remove noisy points and outliers. First we present a method for estimating optimal bandwidth of multivariate KDE using particle swarm optimization technique which ensures the robust performance of density estimation. Then we use mean-shift algorithm to find the local maxima of the density estimation which gives the centroid of the clusters. Then we compute the distance of a certain point from the centroid. Points belong to outliers then removed by automatic thresholding scheme which yields an accurate and economical point surface. The experimental results show that our approach comparably robust and efficient.Keywords: point preprocessing, outlier removal, surface reconstruction, kernel density estimation
Procedia PDF Downloads 3051940 Overhead Reduction by Channel Estimation Using Linear Interpolation for Single Carrier Frequency Domain Equalization Transmission
Authors: Min-Su Song, Haeng-Bok Kil, Eui-Rim Jeong
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This paper proposes a new method to reduce the overhead by pilots for single carrier frequency domain equalization (SC-FDE) transmission. In the conventional SC-FDE transmission structure, the overhead by transmitting pilot is heavy because the pilot are transmitted at every SC-FDE block. The proposed SC-FDE structure has fewer pilots and many SC-FCE blocks are transmitted between pilots. The channel estimation and equalization is performed at the pilot period and the channels between pilots are estimated through linear interpolation. This reduces the pilot overhead by reducing the pilot transmission compared with the conventional structure, and enables reliable channel estimation and equalization.Keywords: channel estimation, linear interpolation, pilot overhead, SC-FDE
Procedia PDF Downloads 2501939 Approximation of the Time Series by Fractal Brownian Motion
Authors: Valeria Bondarenko
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In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates.Keywords: fractional Brownian motion, Gausssian processes, approximation, time series, estimation of properties of the model
Procedia PDF Downloads 3431938 Extended Constraint Mask Based One-Bit Transform for Low-Complexity Fast Motion Estimation
Authors: Oğuzhan Urhan
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In this paper, an improved motion estimation (ME) approach based on weighted constrained one-bit transform is proposed for block-based ME employed in video encoders. Binary ME approaches utilize low bit-depth representation of the original image frames with a Boolean exclusive-OR based hardware efficient matching criterion to decrease computational burden of the ME stage. Weighted constrained one-bit transform (WC‑1BT) based approach improves the performance of conventional C-1BT based ME employing 2-bit depth constraint mask instead of a 1-bit depth mask. In this work, the range of constraint mask is further extended to increase ME performance of WC-1BT approach. Experiments reveal that the proposed method provides better ME accuracy compared existing similar ME methods in the literature.Keywords: fast motion estimation; low-complexity motion estimation, video coding
Procedia PDF Downloads 2921937 Deep Learning-Based Channel Estimation for Reconfigurable Intelligent Surface-Assisted Unmanned Aerial Vehicle-Enabled Wireless Communication System
Authors: Getaneh Berie Tarekegn
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Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles
Procedia PDF Downloads 531936 Hydrological Modelling of Geological Behaviours in Environmental Planning for Urban Areas
Authors: Sheetal Sharma
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Runoff,decreasing water levels and recharge in urban areas have been a complex issue now a days pointing defective urban design and increasing demography as cause. Very less has been discussed or analysed for water sensitive Urban Master Plans or local area plans. Land use planning deals with land transformation from natural areas into developed ones, which lead to changes in natural environment. Elaborated knowledge of relationship between the existing patterns of land use-land cover and recharge with respect to prevailing soil below is less as compared to speed of development. The parameters of incompatibility between urban functions and the functions of the natural environment are becoming various. Changes in land patterns due to built up, pavements, roads and similar land cover affects surface water flow seriously. It also changes permeability and absorption characteristics of the soil. Urban planners need to know natural processes along with modern means and best technologies available,as there is a huge gap between basic knowledge of natural processes and its requirement for balanced development planning leading to minimum impact on water recharge. The present paper analyzes the variations in land use land cover and their impacts on surface flows and sub-surface recharge in study area. The methodology adopted was to analyse the changes in land use and land cover using GIS and Civil 3d auto cad. The variations were used in computer modeling using Storm-water Management Model to find out the runoff for various soil groups and resulting recharge observing water levels in POW data for last 40 years of the study area. Results were anlayzed again to find best correlations for sustainable recharge in urban areas.Keywords: geology, runoff, urban planning, land use-land cover
Procedia PDF Downloads 2851935 Effect of Soil Corrosion in Failures of Buried Gas Pipelines
Authors: Saima Ali, Pathamanathan Rajeev, Imteaz A. Monzur
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In this paper, a brief review of the corrosion mechanism in buried pipe and modes of failure is provided together with the available corrosion models. Moreover, the sensitivity analysis is performed to understand the influence of corrosion model parameters on the remaining life estimation. Further, the probabilistic analysis is performed to propagate the uncertainty in the corrosion model on the estimation of the renaming life of the pipe. Finally, the comparison among the corrosion models on the basis of the remaining life estimation will be provided to improve the renewal plan.Keywords: corrosion, pit depth, sensitivity analysis, exposure period
Procedia PDF Downloads 4941934 Software Engineering Inspired Cost Estimation for Process Modelling
Authors: Felix Baumann, Aleksandar Milutinovic, Dieter Roller
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Up to this point business process management projects in general and business process modelling projects in particular could not rely on a practical and scientifically validated method to estimate cost and effort. Especially the model development phase is not covered by a cost estimation method or model. Further phases of business process modelling starting with implementation are covered by initial solutions which are discussed in the literature. This article proposes a method of filling this gap by deriving a cost estimation method from available methods in similar domains namely software development or software engineering. Software development is regarded as closely similar to process modelling as we show. After the proposition of this method different ideas for further analysis and validation of the method are proposed. We derive this method from COCOMO II and Function Point which are established methods of effort estimation in the domain of software development. For this we lay out similarities of the software development rocess and the process of process modelling which is a phase of the Business Process Management life-cycle.Keywords: COCOMO II, busines process modeling, cost estimation method, BPM COCOMO
Procedia PDF Downloads 4021933 Reliability Estimation of Bridge Structures with Updated Finite Element Models
Authors: Ekin Ozer
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Assessment of structural reliability is essential for efficient use of civil infrastructure which is subjected hazardous events. Dynamic analysis of finite element models is a commonly used tool to simulate structural behavior and estimate its performance accordingly. However, theoretical models purely based on preliminary assumptions and design drawings may deviate from the actual behavior of the structure. This study proposes up-to-date reliability estimation procedures which engages actual bridge vibration data modifying finite element models for finite element model updating and performing reliability estimation, accordingly. The proposed method utilizes vibration response measurements of bridge structures to identify modal parameters, then uses these parameters to calibrate finite element models which are originally based on design drawings. The proposed method does not only show that reliability estimation based on updated models differs from the original models, but also infer that non-updated models may overestimate the structural capacity.Keywords: earthquake engineering, engineering vibrations, reliability estimation, structural health monitoring
Procedia PDF Downloads 1781932 Estimation of Break Points of Housing Price Growth Rate for Top MSAs in Texas Area
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Applying the structural break estimation method proposed by Perron and Bai (1998) to the housing price growth rate of top 5 MSAs in the Texas area, this paper estimated the structural break date for the growth rate of housing prices index. As shown in the estimation results, the break dates for each region are quite different, which indicates the heterogeneity of the housing market in response to macroeconomic conditions.Keywords: structural break, housing prices index, ADF test, linear model
Procedia PDF Downloads 1171931 Biochar - A Multi-Beneficial and Cost-Effective Amendment to Clay Soil for Stormwater Runoff Treatment
Authors: Mohammad Khalid, Mariya Munir, Jacelyn Rice Boyaue
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Highways are considered a major source of pollution to storm-water, and its runoff can introduce various contaminants, including nutrients, Indicator bacteria, heavy metals, chloride, and phosphorus compounds, which can have negative impacts on receiving waters. This study assessed the ability of biochar for contaminants removal and to improve the water holding capacity of soil biochar mixture. For this, ten commercially available biochar has been strategically selected. Lab scale batch testing was done at 3% and 6% by the weight of the soil to find the preliminary estimate of contaminants removal along with hydraulic conductivity and water retention capacity. Furthermore, from the above-conducted studies, six best performing candidate and an application rate of 6% has been selected for the column studies. Soil biochar mixture was filled in 7.62 cm assembled columns up to a fixed height of 76.2 cm based on hydraulic conductivity. A total of eight column experiments have been conducted for nutrient, heavy metal, and indicator bacteria analysis over a period of one year, which includes a drying as well as a deicing period. The saturated hydraulic conductivity was greatly improved, which is attributed to the high porosity of the biochar soil mixture. Initial data from the column testing shows that biochar may have the ability to significantly remove nutrients, indicator bacteria, and heavy metals. The overall study demonstrates that biochar could be efficiently applied with clay soil to improve the soil's hydraulic characteristics as well as remove the pollutants from the stormwater runoff.Keywords: biochar, nutrients, indicator bacteria, storm-water treatment, sustainability
Procedia PDF Downloads 881930 Point Estimation for the Type II Generalized Logistic Distribution Based on Progressively Censored Data
Authors: Rana Rimawi, Ayman Baklizi
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Skewed distributions are important models that are frequently used in applications. Generalized distributions form a class of skewed distributions and gain widespread use in applications because of their flexibility in data analysis. More specifically, the Generalized Logistic Distribution with its different types has received considerable attention recently. In this study, based on progressively type-II censored data, we will consider point estimation in type II Generalized Logistic Distribution (Type II GLD). We will develop several estimators for its unknown parameters, including maximum likelihood estimators (MLE), Bayes estimators and linear estimators (BLUE). The estimators will be compared using simulation based on the criteria of bias and Mean square error (MSE). An illustrative example of a real data set will be given.Keywords: point estimation, type II generalized logistic distribution, progressive censoring, maximum likelihood estimation
Procedia PDF Downloads 1671929 Estimation and Restoration of Ill-Posed Parameters for Underwater Motion Blurred Images
Authors: M. Vimal Raj, S. Sakthivel Murugan
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Underwater images degrade their quality due to atmospheric conditions. One of the major problems in an underwater image is motion blur caused by the imaging device or the movement of the object. In order to rectify that in post-imaging, parameters of the blurred image are to be estimated. So, the point spread function is estimated by the properties, using the spectrum of the image. To improve the estimation accuracy of the parameters, Optimized Polynomial Lagrange Interpolation (OPLI) method is implemented after the angle and length measurement of motion-blurred images. Initially, the data were collected from real-time environments in Chennai and processed. The proposed OPLI method shows better accuracy than the existing classical Cepstral, Hough, and Radon transform estimation methods for underwater images.Keywords: image restoration, motion blur, parameter estimation, radon transform, underwater
Procedia PDF Downloads 1521928 On Parameter Estimation of Simultaneous Linear Functional Relationship Model for Circular Variables
Authors: N. A. Mokhtar, A. G. Hussin, Y. Z. Zubairi
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This paper proposes a new simultaneous simple linear functional relationship model by assuming equal error variances. We derive the maximum likelihood estimate of the parameters in the simultaneous model and the covariance. We show by simulation study the small bias values of the parameters suggest the suitability of the estimation method. As an illustration, the proposed simultaneous model is applied to real data of the wind direction and wave direction measured by two different instruments.Keywords: simultaneous linear functional relationship model, Fisher information matrix, parameter estimation, circular variables
Procedia PDF Downloads 329