Search results for: model estimation

Authors: Changgil Lee, Seunghee Park

Abstract:

Although vehicle driving test for the development of BWIM system is necessary, but it needs much cost and time in addition application of various driving condition. Thus, we need the numerical-simulation method resolving the cost and time problems of vehicle driving test and the way of measuring response of bridge according to the various driving condition. Using the precision analysis model reflecting the dynamic characteristic is contributed to increase accuracy in numerical simulation. In this paper, we conduct a numerical simulation to apply precision analysis model, which reflects the dynamic characteristic of bridge using Bridge Weigh-in-Motion technique and suggest overload vehicle enforcement technology using precision analysis model.

Keywords: bridge weigh-in-motion(BWIM) system, precision analysis model, dynamic characteristic of bridge, numerical simulation

Procedia PDF Downloads 292

Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

Abstract:

This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

Procedia PDF Downloads 369

Authors: Giriraj Achari, Malay Bhattacharyya

Abstract:

In this paper, the effectiveness of Copula Markov Switching Multifractal (MSM) models at forecasting Value-at-Risk of a two-stock portfolio is studied. The innovations are allowed to be drawn from distributions that can capture skewness and leptokurtosis, which are well documented empirical characteristics observed in financial returns. The candidate distributions considered for this purpose are Johnson-SU, Pearson Type-IV and α-Stable distributions. The two univariate marginal distributions are combined using the Student-t copula. The estimation of all parameters is performed by Maximum Likelihood Estimation. Finally, the models are compared in terms of accurate Value-at-Risk (VaR) forecasts using tests of unconditional coverage and independence. It is found that Copula-MSM-models with leptokurtic innovation distributions perform slightly better than Copula-MSM model with Normal innovations. Copula-MSM models, in general, produce better VaR forecasts as compared to traditional methods like Historical Simulation method, Variance-Covariance approach and Copula-Generalized Autoregressive Conditional Heteroscedasticity (Copula-GARCH) models.

Keywords: Copula, Markov Switching, multifractal, value-at-risk

Procedia PDF Downloads 164

Authors: Anton Stadler, Thorsten Ike

Abstract:

In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

Procedia PDF Downloads 355

Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

Abstract:

In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation (RADTRAD), symbolic nuclear analysis package (SNAP), dose, PWR

Procedia PDF Downloads 463

Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan

Abstract:

Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.

Keywords: production estimation, paddy, remote sensing, geography information system, land suitability

Procedia PDF Downloads 341

Authors: Muhammad Tayyab Afzal, Muhammad Arslan, Mirza Muhammad Waqar

Abstract:

One of the key components of the water cycle is evapotranspiration (ET), which represents water consumption by vegetated and non-vegetated surfaces. Conventional techniques for measurements of ET are point based and representative of the local scale only. Satellite remote sensing data with large area coverage and high temporal frequency provide representative measurements of several relevant biophysical parameters required for estimation of ET at regional scales. The objective is of this research is to exploit satellite data in order to estimate evapotranspiration. This study uses Surface Energy Balance System (SEBS) model to calculate daily actual evapotranspiration (ETa) in Larkana District, Sindh Pakistan using Landsat TM data for clouds-free days. As there is no flux tower in the study area for direct measurement of latent heat flux or evapotranspiration and sensible heat flux, therefore, the model estimated values of ET were compared with reference evapotranspiration (ETo) computed by FAO-56 Penman Monteith Method using meteorological data. For a country like Pakistan, agriculture by irrigation in the river basins is the largest user of fresh water. For the better assessment and management of irrigation water requirement, the estimation of consumptive use of water for agriculture is very important because it is the main consumer of water. ET is yet an essential issue of water imbalance due to major loss of irrigation water and precipitation on cropland. As large amount of irrigated water is lost through ET, therefore its accurate estimation can be helpful for efficient management of irrigation water. Results of this study can be used to analyse surface conditions, i.e. temperature, energy budgets and relevant characteristics. Through this information we can monitor vegetation health and suitable agricultural conditions and can take controlling steps to increase agriculture production.

Keywords: SEBS, remote sensing, evapotranspiration, ETa

Procedia PDF Downloads 333

Authors: P. Deepak Kumar, P. R. Maiti

Abstract:

In recent years, sediment scour near bridge piers and abutment is a serious problem which causes nationwide concern because it has resulted in more bridge failures than other causes. Scour is the formation of scour hole around the structure mounted on and embedded in erodible channel bed due to the erosion of soil by flowing water. The formation of scour hole around the structures depends upon shape and size of the pier, depth of flow as well as angle of attack of flow and sediment characteristics. The flow characteristics around these structures change due to man-made obstruction in the natural flow path which changes the kinetic energy of the flow around these structures. Excessive scour affects the stability of the foundation of the structure by the removal of the bed material. The accurate estimation of scour depth around bridge pier is very difficult. The foundation of bridge piers have to be taken deeper and to provide sufficient anchorage length required for stability of the foundation. In this study, computational model simulations using a 3D Computational Fluid Dynamics (CFD) model were conducted to examine the mechanism of scour around a cylindrical pier. Subsequently, the flow characteristics around these structures are presented for different flow conditions. Mechanism of scouring phenomenon, the formation of vortex and its consequent effect is discussed for a straight channel. Effort was made towards estimation of scour depth around bridge piers under different flow conditions.

Keywords: bridge pier, computational fluid dynamics, multigrid, pier shape, scour

Procedia PDF Downloads 296

Authors: Juan M. Rodriguez-Diaz

Abstract:

The precision of parameter estimators in the Gaussian linear model is traditionally accounted by the variance-covariance matrix of the asymptotic distribution. However, this measure can underestimate the true variance, specially for small samples. Traditionally, optimal design theory pays attention to this variance through its relationship with the model's information matrix. For this reason it seems convenient, at least in some cases, adapt the optimality criteria in order to get the best designs for the actual variance structure, otherwise the loss in efficiency of the designs obtained with the traditional approach may be very important.

Keywords: correlated observations, information matrix, optimality criteria, variance-covariance matrix

Procedia PDF Downloads 443

Authors: Suresh Palla

Abstract:

This research paper presents the results of the study on the estimation of fly ash, slag and cement contents in blended and composite cements by novel selective dissolution method. Types of cement samples investigated include OPC with fly ash as performance improver, OPC with slag as performance improver, PPC, PSC and Composite cement confirming to respective Indian Standards. Slag and OPC contents in PSC were estimated by selectively dissolving OPC in stage 1 and selectively dissolving slag in stage 2. In the case of composite cement sample, the percentage of cement, slag and fly ash were estimated systematically by selective dissolution of cement, slag and fly ash in three stages. In the first stage, cement dissolved and separated by leaving the residue of slag and fly ash, designated as R1. The second stage involves gravimetric estimation of fractions of OPC, residue and selective dissolution of fly ash and slag contents. Fly ash content, R2 was estimated through gravimetric analysis. Thereafter, the difference between the R1 and R2 is considered as slag content. The obtained results of cement, fly ash and slag using selective dissolution method showed 10% of standard deviation with the corresponding percentage of respective constituents. The results suggest that this novel selective dissolution method can be successfully used for estimation of OPC and SCMs contents in different types of cements.

Keywords: selective dissolution method , fly ash, ggbfs slag, edta

Procedia PDF Downloads 156

Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

Abstract:

An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

Procedia PDF Downloads 309

Authors: S. B. Provost, Susan Sheng

Abstract:

An alternative bivariate density estimation methodology is introduced in this presentation. The proposed approach involves estimating the density function associated with the marginal distribution of each of the two variables by means of the saddlepoint approximation technique and applying a bivariate polynomial adjustment to the product of these density estimates. Since the saddlepoint approximation is utilized in the context of density estimation, such estimates are determined from empirical cumulant-generating functions. In the univariate case, the saddlepoint density estimate is itself adjusted by a polynomial. Given a set of observations, the coefficients of the polynomial adjustments are obtained from the sample moments. Several illustrative applications of the proposed methodology shall be presented. Since this approach relies essentially on a determinate number of sample moments, it is particularly well suited for modeling massive data sets.

Keywords: density estimation, empirical cumulant-generating function, moments, saddlepoint approximation

Procedia PDF Downloads 280

Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

Abstract:

Over the last several years, concern has developed over how to minimize the spread of HIV/AIDS epidemic in many countries. AIDS epidemic has tremendously stimulated the development of mathematical models of infectious diseases. The transmission dynamics of HIV infection that eventually developed AIDS has taken a pivotal role of much on building mathematical models. From the initial HIV and AIDS models introduced in the 80s, various improvements have been taken into account as how to model HIV/AIDS frameworks. In this paper, we present the impact of migration on the spread of HIV/AIDS. Epidemic model is considered by a system of nonlinear differential equations to supplement the statistical method approach. The model is calibrated using HIV incidence data from Malaysia between 1986 and 2011. Bayesian inference based on Markov Chain Monte Carlo is used to validate the model by fitting it to the data and to estimate the unknown parameters for the model. The results suggest that the migrants stay for a long time contributes to the spread of HIV. The model also indicates that susceptible individual becomes infected and moved to HIV compartment at a rate that is more significant than the removal rate from HIV compartment to AIDS compartment. The disease-free steady state is unstable since the basic reproduction number is 1.627309. This is a big concern and not a good indicator from the public heath point of view since the aim is to stabilize the epidemic at the disease equilibrium.

Keywords: epidemic model, HIV, MCMC, parameter estimation

Procedia PDF Downloads 600

Authors: Seongsoo Lee

Abstract:

Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization

Procedia PDF Downloads 363

Authors: C. Romero, R. Ortega, P. Sánchez-Camacho, P. Aguilar, V. Segur, J. Ruiz, G. Gutiérrez

Abstract:

Introduction: Breast cancer is a leading cause of death in CLM. (2.8% of all deaths in women and 13,8% of deaths from tumors in womens). It is the most tumor incidence in CLM region with 26.1% from all tumours, except nonmelanoma skin (Cancer Incidence in Five Continents, Volume X, IARC). Cancer registries are a good information source to estimate cancer incidence, however the data are usually available with a lag which makes difficult their use for health managers. By contrast, mortality and survival statistics have less delay. In order to serve for resource planning and responding to this problem, a method is presented to estimate the incidence of mortality and survival data. Objectives: To estimate the incidence of breast cancer by age group in CLM in the period 1991-2013. Comparing the data obtained from the model with current incidence data. Sources: Annual number of women by single ages (National Statistics Institute). Annual number of deaths by all causes and breast cancer. (Mortality Registry CLM). The Breast cancer relative survival probability. (EUROCARE, Spanish registries data). Methods: A Weibull Parametric survival model from EUROCARE data is obtained. From the model of survival, the population and population data, Mortality and Incidence Analysis MODel (MIAMOD) regression model is obtained to estimate the incidence of cancer by age (1991-2013). Results: The resulting model is: Ix,t = Logit [const + age1*x + age2*x2 + coh1*(t – x) + coh2*(t-x)2] Where: Ix,t is the incidence at age x in the period (year) t; the value of the parameter estimates is: const (constant term in the model) = -7.03; age1 = 3.31; age2 = -1.10; coh1 = 0.61 and coh2 = -0.12. It is estimated that in 1991 were diagnosed in CLM 662 cases of breast cancer (81.51 per 100,000 women). An estimated 1,152 cases (112.41 per 100,000 women) were diagnosed in 2013, representing an increase of 40.7% in gross incidence rate (1.9% per year). The annual average increases in incidence by age were: 2.07% in women aged 25-44 years, 1.01% (45-54 years), 1.11% (55-64 years) and 1.24% (65-74 years). Cancer registries in Spain that send data to IARC declared 2003-2007 the average annual incidence rate of 98.6 cases per 100,000 women. Our model can obtain an incidence of 100.7 cases per 100,000 women. Conclusions: A sharp and steady increase in the incidence of breast cancer in the period 1991-2013 is observed. The increase was seen in all age groups considered, although it seems more pronounced in young women (25-44 years). With this method you can get a good estimation of the incidence.

Keywords: breast cancer, incidence, cancer registries, castilla-la mancha

Procedia PDF Downloads 311

Authors: Tsui-Tsai Lin

Abstract:

Cooperative orthogonal frequency division multiplexing (OFDM) transmission, which possesses the advantages of better connectivity, expanded coverage, and resistance to frequency selective fading, has been a more powerful solution for the physical layer in wireless communications. However, such a hybrid scheme suffers from the carrier frequency offset (CFO) effects inherited from the OFDM-based systems, which lead to a significant degradation in performance. In addition, insertion of a cyclic prefix (CP) at each symbol block head for combating inter-symbol interference will lead to a reduction in spectral efficiency. The design on the CFO estimation for the cooperative OFDM system without CP is a suspended problem. This motivates us to develop a low complexity CFO estimator for the cooperative OFDM decode-and-forward (DF) communication system without CP over the multipath fading channel. Especially, using a block-type pilot, the CFO estimation is first derived in accordance with the least square criterion. A reliable performance can be obtained through an exhaustive two-dimensional (2D) search with a penalty of heavy computational complexity. As a remedy, an alternative solution realized with an iteration approach is proposed for the CFO estimation. In contrast to the 2D-search estimator, the iterative method enjoys the advantage of the substantially reduced implementation complexity without sacrificing the estimate performance. Computer simulations have been presented to demonstrate the efficacy of the proposed CFO estimation.

Keywords: cooperative transmission, orthogonal frequency division multiplexing (OFDM), carrier frequency offset, iteration

Procedia PDF Downloads 265

Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

Abstract:

In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

Procedia PDF Downloads 151

Authors: Babatunde Dosumu, Obuks Ejohwomu, Akilu Yunusa-Kaltungo

Abstract:

Cost estimation in construction is often difficult, particularly when dealing with risks and uncertainties, which are inevitable and peculiar to developing countries like Nigeria. Direct consequences of these are major deviations in cost, duration, and quality. The fundamental aim of this study is to develop a framework for assessing the impacts of risk on cost estimation, which in turn causes variabilities between contract sum and final account. This is very important, as initial estimates given to clients should reflect the certain magnitude of consistency and accuracy, which the client builds other planning-related activities upon, and also enhance the capabilities of construction industry professionals by enabling better prediction of the final account from the contract sum. In achieving this, a systematic literature review was conducted with cost variability and construction projects as search string within three databases: Scopus, Web of science, and Ebsco (Business source premium), which are further analyzed and gap(s) in knowledge or research discovered. From the extensive review, it was found that factors causing deviation between final accounts and contract sum ranged between 1 and 45. Besides, it was discovered that a cost estimation framework similar to Building Cost Information Services (BCIS) is unavailable in Nigeria, which is a major reason why initial estimates are very often inconsistent, leading to project delay, abandonment, or determination at the expense of the huge sum of money invested. It was concluded that the development of a cost estimation framework that is adjudged an important tool in risk shedding rather than risk-sharing in project risk management would be a panacea to cost estimation problems, leading to cost variability in the Nigerian construction industry by the time this ongoing Ph.D. research is completed. It was recommended that practitioners in the construction industry should always take into account risk in order to facilitate the rapid development of the construction industry in Nigeria, which should give stakeholders a more in-depth understanding of the estimation effectiveness and efficiency to be adopted by stakeholders in both the private and public sectors.

Keywords: cost variability, construction projects, future studies, Nigeria

Procedia PDF Downloads 209

Authors: Kyoung-Jin Joo, In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee

Abstract:

Recently, the permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) that can be substituted for the induction motor has been studying because of the needs of the development of the premium high efficiency motor for the minimum energy performance standard (MEPS). PMa-SynRM is required to the speed and position information for motor speed and torque controls. However, to apply the sensors has many problems that are sensor mounting space shortage and additional cost, etc. Therefore, in this paper, speed-sensorless control based on model reference adaptive system (MRAS) is introduced to eliminate the sensor. The sensorless method is constructed in a reference model as standard and an adaptive model as the state observer. The proposed algorithm is verified by the simulation.

Keywords: PMa-SynRM, sensorless control, robust estimation, MRAS method

Procedia PDF Downloads 404

Authors: Marlon Gallo, Eduardo Miguel, Laura Oca, Eneko Gonzalez, Unai Iraola

Abstract:

The heat generation of an energy storage system is an essential topic when designing a battery pack and its cooling system. Heat generation estimation is used together with thermal models to predict battery temperature in operation and adapt the design of the battery pack and the cooling system to these thermal needs guaranteeing its safety and correct operation. In the present work, a comparison between the use of a heat flux sensor (HFS) for indirect measurement of heat losses in a cell and the widely used and simplified version of Bernardi’s equation for estimation is presented. First, a Li-ion cell is thermally characterized with an HFS to measure the thermal parameters that are used in a first-order lumped thermal model. These parameters are the equivalent thermal capacity and the thermal equivalent resistance of a single Li-ion cell. Static (when no current is flowing through the cell) and dynamic (making current flow through the cell) tests are conducted in which HFS is used to measure heat between the cell and the ambient, so thermal capacity and resistances respectively can be calculated. An experimental platform records current, voltage, ambient temperature, surface temperature, and HFS output voltage. Second, an equivalent circuit model is built in a Matlab-Simulink environment. This allows the comparison between the generated heat predicted by Bernardi’s equation and the HFS measurements. Data post-processing is required to extrapolate the heat generation from the HFS measurements, as the sensor records the heat released to the ambient and not the one generated within the cell. Finally, the cell temperature evolution is estimated with the lumped thermal model (using both HFS and Bernardi’s equation total heat generation) and compared towards experimental temperature data (measured with a T-type thermocouple). At the end of this work, a critical review of the results obtained and the possible mismatch reasons are reported. The results show that indirectly measuring the heat generation with HFS gives a more precise estimation than Bernardi’s simplified equation. On the one hand, when using Bernardi’s simplified equation, estimated heat generation differs from cell temperature measurements during charges at high current rates. Additionally, for low capacity cells where a small change in capacity has a great influence on the terminal voltage, the estimated heat generation shows high dependency on the State of Charge (SoC) estimation, and therefore open circuit voltage calculation (as it is SoC dependent). On the other hand, with indirect measuring the heat generation with HFS, the resulting error is a maximum of 0.28ºC in the temperature prediction, in contrast with 1.38ºC with Bernardi’s simplified equation. This illustrates the limitations of Bernardi’s simplified equation for applications where precise heat monitoring is required. For higher current rates, Bernardi’s equation estimates more heat generation and consequently, a higher predicted temperature. Bernardi´s equation accounts for no losses after cutting the charging or discharging current. However, HFS measurement shows that after cutting the current the cell continues generating heat for some time, increasing the error of Bernardi´s equation.

Keywords: lithium-ion battery, heat flux sensor, heat generation, thermal characterization

Procedia PDF Downloads 389

Authors: A. Shebani, C. Pislaru

Abstract:

Wear of materials is an everyday experience and has been observed and studied for long time. The prediction of wear is a fundamental problem in the industrial field, mainly correlated to the planning of maintenance interventions and economy. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin which is made of steel with a tip, is positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument; where the Talysurf profilometer was used to measure the pin/disc wear scar depth, and the alicona was used to measure the volume loss for pin and disc. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling and the simulation results are implemented by using the Matlab program. This paper focuses on how the alicona can be considered as a powerful tool for wear measurements and how the neural network is an effective algorithm for wear estimation.

Keywords: wear modelling, Archard Model, ASTM Model, Neural Networks Model, Pin-on-disc Test, Talysurf, digital microscope, Alicona

Procedia PDF Downloads 456

Authors: Rajamani Doraiswami, Lahouari Cheded

Abstract:

Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

Procedia PDF Downloads 499

Authors: Saba Arif, Anam Nadeem, Roman Kalvin, Tanzeel Rashid, Burhan Ali, Juntakan Taweekun

Abstract:

Currently, the energy crisis is taking serious attention. Globally, industries and building are major share takers of energy. 72% of total global energy is consumed by residential houses, markets, and commercial building. Additionally, in appliances air conditioners are major consumer of electricity; about 60% energy is used for cooling purpose in houses due to HVAC units. Energy demand will aid in determining what changes will be needed whether it is the estimation of the required energy for households or instituting conservation measures. Bottom-up model is one of the most famous methods for forecasting. In current research bottom-up model of air conditioners' energy consumption in all income classes in comparison with seasonal variation and hourly consumption is calculated. By comparison of energy consumption of all income classes by usage of air conditioners, total consumption of actual demand and current availability can be seen.

Keywords: air conditioning, bottom up model, income classes, energy demand

Procedia PDF Downloads 248

Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

Abstract:

Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

Procedia PDF Downloads 427

Authors: Naoya Ozaki, Takuya Watanabe, Ryosuke Matsumoto, Noriko Fukasawa

Abstract:

In the metropolitan areas in Japan, in many stations, shopping areas are set up, and escalators and elevators are installed to make the stations be barrier-free. Further, many areas around the stations are being redeveloped. Railway business operators want to know how much effect these circumstances have on attractiveness of the station or number of passengers using the station. So, we performed a questionnaire survey of the station users in the metropolitan areas for finding factors to affect the attractiveness of stations. Then, based on the analysis of the survey, we developed a method to quantitatively evaluate attractiveness of the stations. We also developed an estimation method for number of passengers based on combination of attractiveness of the station quantitatively evaluated and the residential and labor population around the station. Then, we derived precise linear regression models estimating the attractiveness of the station and number of passengers of the station.

Keywords: attractiveness of the station, estimation method, number of passengers of the station, redevelopment around the station, renovation of the station

Procedia PDF Downloads 287

Authors: Paul Kenneth D. Luzon, Maria Antonia N. Tanchuling

Abstract:

The Quezon City Controlled Dumping facility also known as Payatas produces leachate which can contaminate soil and water environment in the area. The goal of this study is to quantify the leachate produced by the QCCDF using the Hydrologic Evaluation of Landfill Performance (HELP) model. Results could be used as input for groundwater contaminant transport studies. The HELP model is based on a simple water budget and is an essential “model requirement” used by the US Environmental Protection Agency (EPA). Annual waste profile of the QCCDF was calculated. Based on topographical maps and estimation of settlement due to overburden pressure and degradation, a total of 10M m^3 of waste is contained in the landfill. The input necessary for the HELP model are weather data, soil properties, and landfill design. Results showed that from 1988 to 2011, an average of 50% of the total precipitation percolates through the bottom layer. Validation of the results is still needed due to the assumptions made in the study. The decrease in porosity of the top soil cover showed the best mitigation for minimizing percolation rate. This study concludes that there is a need for better leachate management system in the QCCDF.

Keywords: help model, landfill, payatas trash slide, quezon city controlled dumping facility

Procedia PDF Downloads 291

Authors: Syed Hammad Ali, Rijan Bhakta Kayastha, Danial Hashmi, Richard Armstrong, Ahuti Shrestha, Iram Bano, Javed Hassan

Abstract:

This paper presents the results of a semi-distributed modified positive degree-day model (MPDDM) for estimating snow and ice melt contributions to discharge from the glacierized Hunza River basin, Pakistan. The model uses daily temperature data, daily precipitation data, and positive degree day factors for snow and ice melt. The model is calibrated for the period 1995-2001 and validated for 2002-2013, and demonstrates close agreements between observed and simulated discharge with Nash–Sutcliffe Efficiencies of 0.90 and 0.88, respectively. Furthermore, the Weather Research and Forecasting model projected temperature, and precipitation data from 2016-2050 are used for representative concentration pathways RCP4.5 and RCP8.5, and bias correction was done using a statistical approach for future discharge estimation. No drastic changes in future discharge are predicted for the emissions scenarios. The aggregate snow-ice melt contribution is 39% of total discharge in the period 1993-2013. Snow-ice melt contribution ranges from 35% to 63% during the high flow period (May to October), which constitutes 89% of annual discharge; in the low flow period (November to April) it ranges from 0.02% to 17%, which constitutes 11 % of the annual discharge. The snow-ice melt contribution to total discharge will increase gradually in the future and reach up to 45% in 2041-2050. From a sensitivity analysis, it is found that the combination of a 2°C temperature rise and 20% increase in precipitation shows a 10% increase in discharge. The study allows us to evaluate the impact of climate change in such basins and is also useful for the future prediction of discharge to define hydropower potential, inform other water resource management in the area, to understand future changes in snow-ice melt contribution to discharge, and offer a possible evaluation of future water quantity and availability.

Keywords: climate variability, future discharge projection, positive degree day, regional climate model, water resource management

Procedia PDF Downloads 290

Authors: Sung Hyun Yoo, In Hwan Choi, Jun Ho Jung, Choon Ki Ahn, Myo Taeg Lim

Abstract:

Home energy management system (HEMS) has been issued to reduce the power consumption. The HEMS performs electric power control for the indoor electric device. However, HEMS commonly treats the smart devices. In this paper, we suggest the output estimation of home legacy device using the artificial neural fuzzy inference system (ANFIS). This paper discusses the overview and the architecture of the system. In addition, accurate performance of the output estimation using the ANFIS inference system is shown via a numerical example.

Keywords: artificial neural fuzzy inference system (ANFIS), home energy management system (HEMS), smart device, legacy device

Procedia PDF Downloads 543

Authors: Eslam Mohammed Abdelkader, Mohamed Marzouk, Tarek Zayed

Abstract:

Infrastructure systems are crucial to every aspect of life on Earth. Existing Infrastructure is subjected to degradation while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges play a crucial role in urban transportation networks. Moreover, they are subjected to high level of deterioration because of the variable traffic loading, extreme weather conditions, cycles of freeze and thaw, etc. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays especially in the large transportation networks due to the huge variance between the need for maintenance actions, and the available funds to perform such actions. Deterioration models represent a very important aspect for the effective use of BMSs. This paper presents a probabilistic time-based model that is capable of predicting the condition ratings of the concrete bridge decks along its service life. The deterioration process of the concrete bridge decks is modeled using semi-Markov process. One of the main challenges of the Markov Chain Decision Process (MCDP) is the construction of the transition probability matrix. Yet, the proposed model overcomes this issue by modeling the sojourn times based on some probability density functions. The sojourn times of each condition state are fitted to probability density functions based on some goodness of fit tests such as Kolmogorov-Smirnov test, Anderson Darling, and chi-squared test. The parameters of the probability density functions are obtained using maximum likelihood estimation (MLE). The condition ratings obtained from the Ministry of Transportation in Quebec (MTQ) are utilized as a database to construct the deterioration model. Finally, a comparison is conducted between the Markov Chain and semi-Markov chain to select the most feasible prediction model.

Keywords: bridge management system, bridge decks, deterioration model, Semi-Markov chain, sojourn times, maximum likelihood estimation

Procedia PDF Downloads 211

Authors: Mostafa Aminzadeh, Min Deng

Abstract:

Modeling loss data is an important part of actuarial science. Actuaries use models to predict future losses and manage financial risk, which can be beneficial for marketing purposes. In the insurance industry, small claims happen frequently while large claims are rare. Traditional distributions such as Normal, Exponential, and inverse-Gaussian are not suitable for describing insurance data, which often show skewness and fat tails. Several authors have studied classical and Bayesian inference for parameters of composite distributions, such as Exponential-Pareto, Weibull-Pareto, and Inverse Gamma-Pareto. These models separate small to moderate losses from large losses using a threshold parameter. This research introduces a computational approach using a nonlinear regression model for loss data that relies on multiple predictors. Simulation studies were conducted to assess the accuracy of the proposed estimation method. The simulations confirmed that the proposed method provides precise estimates for regression parameters. It's important to note that this approach can be applied to datasets if goodness-of-fit tests confirm that the composite distribution under study fits the data well. To demonstrate the computations, a real data set from the insurance industry is analyzed. A Mathematica code uses the Fisher information algorithm as an iteration method to obtain the maximum likelihood estimation (MLE) of regression parameters.

Keywords: maximum likelihood estimation, fisher scoring method, non-linear regression models, composite distributions

Procedia PDF Downloads 33