Search results for: Weibull distribution model

Authors: D. Ramajo, S. Corzo, M. Nigro

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A Multi-dimensional computational fluid dynamics (CFD) two-phase model was developed with the aim to simulate the in-core coolant circuit of a pressurized heavy water reactor (PHWR) of a commercial nuclear power plant (NPP). Due to the fact that this PHWR is a Reactor Pressure Vessel type (RPV), three-dimensional (3D) detailed modelling of the large reservoirs of the RPV (the upper and lower plenums and the downcomer) were coupled with an in-house finite volume one-dimensional (1D) code in order to model the 451 coolant channels housing the nuclear fuel. Regarding the 1D code, suitable empirical correlations for taking into account the in-channel distributed (friction losses) and concentrated (spacer grids, inlet and outlet throttles) pressure losses were used. A local power distribution at each one of the coolant channels was also taken into account. The heat transfer between the coolant and the surrounding moderator was accurately calculated using a two-dimensional theoretical model. The implementation of subcooled boiling and condensation models in the 1D code along with the use of functions for representing the thermal and dynamic properties of the coolant and moderator (heavy water) allow to have estimations of the in-core steam generation under nominal flow conditions for a generic fission power distribution. The in-core mass flow distribution results for steady state nominal conditions are in agreement with the expected from design, thus getting a first assessment of the coupled 1/3D model. Results for nominal condition were compared with those obtained with a previous 1/3D single-phase model getting more realistic temperature patterns, also allowing visualize low values of void fraction inside the upper plenum. It must be mentioned that the current results were obtained by imposing prescribed fission power functions from literature. Therefore, results are showed with the aim of point out the potentiality of the developed model.

Keywords: PHWR, CFD, thermo-hydraulic, two-phase flow

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Authors: Bachir Chemani, Rachid Halfaoui

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The aim of work is to define the distribution density of winding yarn on cylindrical and conical bobbins. It is known that parallel winding gives greater density and more regular distribution, but the unwinding of yarn is much more difficult for following process. The conical spool has an enormous advantage during unwinding and may contain a large amount of yarns, but the density distribution is not regular because of difference in diameters. The variation of specific density over the reel height is explained generally by the sudden change of winding speed due to direction movement variation of yarn. We determined the conditions of uniform winding and developed a calculate model to the change of the specific density of winding wire over entire spool height.

Keywords: textile, cylindrical bobbins, conical bobbins, parallel winding, cross winding

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Authors: Hongbin Yang, Mingxue Liao, Changwen Zheng, Mengyao Kong, Chaohui Liu

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Microfacet-based reflection models are widely used to model light reflections for rough surfaces. Microfacet models have become the standard surface material building block for describing specular components with varying roughness; and yet, while they possess many desirable properties as well as produce convincing results, their design ignores important sources of scattering, which can cause a significant loss of energy. Specifically, they only simulate the single scattering on the microfacets and ignore the subsequent interactions. As the roughness increases, the interaction will become more and more important. So a multiple-scattering microfacet model based on specular V-cavity is presented for this important open problem. However, it spends much unnecessary rendering time because of setting the same number of scatterings for different roughness surfaces. In this paper, we design a geometric attenuation term G to compute the BRDF (Bidirectional reflection distribution function) of multiple scattering of rough surfaces. Moreover, we consider determining the number of scattering by deterministic heuristics for different roughness surfaces. As a result, our model produces a similar appearance of the objects with the state of the art model with significantly improved rendering efficiency. Finally, we derive a multiple scattering BRDF based on the original microfacet framework.

Keywords: bidirectional reflection distribution function, BRDF, geometric attenuation term, multiple scattering, V-cavity model

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Authors: Ishapathik Das, Sumen Sen, N. Rao Chaganty, Pooja Sengupta

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Dependent multivariate count data occur in several research studies. These data can be modeled by a multivariate Poisson or Negative binomial distribution constructed using copulas. However, when some of the counts are inflated, that is, the number of observations in some cells are much larger than other cells, then the copula based multivariate Poisson (or Negative binomial) distribution may not fit well and it is not an appropriate statistical model for the data. There is a need to modify or adjust the multivariate distribution to account for the inflated frequencies. In this article, we consider the situation where the frequencies of two cells are higher compared to the other cells, and develop a doubly inflated multivariate Poisson distribution function using multivariate Gaussian copula. We also discuss procedures for regression on covariates for the doubly inflated multivariate count data. For illustrating the proposed methodologies, we present a real data containing bivariate count observations with inflations in two cells. Several models and linear predictors with log link functions are considered, and we discuss maximum likelihood estimation to estimate unknown parameters of the models.

Keywords: copula, Gaussian copula, multivariate distributions, inflated distributios

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Authors: Akash Verma, Sujit Kumar Samanta

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This study examines a discrete-time Geo/G/1 queueing-inventory system attached with (s, Q) inventory policy. Assume that the customers follow the Bernoulli process on arrival. Each customer demands a single item with arbitrarily distributed service time. The inventory is replenished by an outside supplier, and the lead time for the replenishment is determined by a geometric distribution. There is a single server and infinite waiting space in this facility. Demands must wait in the specified waiting area during a stock-out period. The customers are served on a first-come-first-served basis. With the help of the embedded Markov chain technique, we determine the joint probability distributions of the number of customers in the system and the number of items in stock at the post-departure epoch using the Matrix Analytic approach. We relate the system length distribution at post-departure and outside observer's epochs to determine the joint probability distribution at the outside observer's epoch. We use probability distributions at random epochs to determine the waiting time distribution. We obtain the performance measures to construct the cost function. The optimum values of the order quantity and reordering point are found numerically for the variety of model parameters.

Keywords: discrete-time queueing inventory model, matrix analytic method, waiting-time analysis, cost optimization

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Authors: Ayman Baklizi

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This paper discusses the problem of testing hypotheses about the lifetime distributions of a matched pair based on censored data. A distribution free test based on a runs statistic is proposed. Its null distribution and power function are found in a simple convenient form. Some properties of the test statistic and its power function are studied.

Keywords: censored data, distribution free, matched pair, runs statistics

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Authors: A. Sgobba, C. Meskell

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The feasibility of on-site electricity production from solar and wind and the resulting load management for a specific manufacturing plant in Ireland are assessed. The industry sector accounts directly and indirectly for a high percentage of electricity consumption and global greenhouse gas emissions; therefore, it will play a key role in emission reduction and control. Manufacturing plants, in particular, are often located in non-residential areas since they require open spaces for production machinery, parking facilities for the employees, appropriate routes for supply and delivery, special connections to the national grid and other environmental impacts. Since they have larger spaces compared to commercial sites in urban areas, they represent an appropriate case study for evaluating the technical and economic viability of energy system integration with low power density technologies, such as solar and wind, for on-site electricity generation. The available open space surrounding the analysed manufacturing plant can be efficiently used to produce a discrete quantity of energy, instantaneously and locally consumed. Therefore, transmission and distribution losses can be reduced. The usage of storage is not required due to the high and almost constant electricity consumption profile. The energy load of the plant is identified through the analysis of gas and electricity consumption, both internally monitored and reported on the bills. These data are not often recorded and available to third parties since manufacturing companies usually keep track only of the overall energy expenditures. The solar potential is modelled for a period of 21 years based on global horizontal irradiation data; the hourly direct and diffuse radiation and the energy produced by the system at the optimum pitch angle are calculated. The model is validated using PVWatts and SAM tools. Wind speed data are available for the same period within one-hour step at a height of 10m. Since the hub of a typical wind turbine reaches a higher altitude, complementary data for a different location at 50m have been compared, and a model for the estimate of wind speed at the required height in the right location is defined. Weibull Statistical Distribution is used to evaluate the wind energy potential of the site. The results show that solar and wind energy are, as expected, generally decoupled. Based on the real case study, the percentage of load covered every hour by on-site generation (Level of Autonomy LA) and the resulting electricity bought from the grid (Expected Energy Not Supplied EENS) are calculated. The economic viability of the project is assessed through Net Present Value, and the influence the main technical and economic parameters have on NPV is presented. Since the results show that the analysed renewable sources can not provide enough electricity, the integration with a cogeneration technology is studied. Finally, the benefit to energy system integration of wind, solar and a cogeneration technology is evaluated and discussed.

Keywords: demand, energy system integration, load, manufacturing, national grid, renewable energy sources

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Authors: Mohamed K. Metwally, Sherif H. El-Gohary, Kyung Min Byun, Seung Moo Han, Soo Yeol Lee, Min Hyoung Cho, Gon Khang, Jinsung Cho, Tae-Seong Kim

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Photoacoustic imaging (PAI) is a non-invasive and non-ionizing imaging modality that combines the absorption contrast of light with ultrasound resolution. Laser is used to deposit optical energy into a target (i.e., optical fluence). Consequently, the target temperature rises, and then thermal expansion occurs that leads to generating a PA signal. In general, most image reconstruction algorithms for PAI assume uniform fluence within an imaging object. However, it is known that optical fluence distribution within the object is non-uniform. This could affect the reconstruction of PA images. In this study, we have investigated the influence of optical fluence distribution on PA back-propagation imaging using finite element method. The uniform fluence was simulated as a triangular waveform within the object of interest. The non-uniform fluence distribution was estimated by solving light propagation within a tissue model via Monte Carlo method. The results show that the PA signal in the case of non-uniform fluence is wider than the uniform case by 23%. The frequency spectrum of the PA signal due to the non-uniform fluence has missed some high frequency components in comparison to the uniform case. Consequently, the reconstructed image with the non-uniform fluence exhibits a strong smoothing effect.

Keywords: finite element method, fluence distribution, Monte Carlo method, photoacoustic imaging

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Authors: Petr Gurný

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One of the most important tasks in the risk management is the correct determination of probability of default (PD) of particular financial subjects. In this paper a possibility of determination of financial institution’s PD according to the credit-scoring models is discussed. The paper is divided into the two parts. The first part is devoted to the estimation of the three different models (based on the linear discriminant analysis, logit regression and probit regression) from the sample of almost three hundred US commercial banks. Afterwards these models are compared and verified on the control sample with the view to choose the best one. The second part of the paper is aimed at the application of the chosen model on the portfolio of three key Czech banks to estimate their present financial stability. However, it is not less important to be able to estimate the evolution of PD in the future. For this reason, the second task in this paper is to estimate the probability distribution of the future PD for the Czech banks. So, there are sampled randomly the values of particular indicators and estimated the PDs’ distribution, while it’s assumed that the indicators are distributed according to the multidimensional subordinated Lévy model (Variance Gamma model and Normal Inverse Gaussian model, particularly). Although the obtained results show that all banks are relatively healthy, there is still high chance that “a financial crisis” will occur, at least in terms of probability. This is indicated by estimation of the various quantiles in the estimated distributions. Finally, it should be noted that the applicability of the estimated model (with respect to the used data) is limited to the recessionary phase of the financial market.

Keywords: credit-scoring models, multidimensional subordinated Lévy model, probability of default

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Authors: Malay K. Pramanik

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In recent years, climate change has become a major threat and has been widely documented in the geographic distribution of many plant species. However, the impacts of climate change on the distribution of ecologically vulnerable medicinal species remain largely unknown. The identification of a suitable habitat for a species under climate change scenario is a significant step towards the mitigation of biodiversity decline. The study, therefore, aims to predict the impact of current, and future climatic scenarios on the distribution of the threatened Garcinia indica across the northern Western Ghats using Maximum Entropy (MaxEnt) modelling. The future projections were made for the year 2050 and 2070 with all Representative Concentration Pathways (RCPs) scenario (2.6, 4.5, 6.0, and 8.5) using 56 species occurrence data, and 19 bioclimatic predictors from the BCC-CSM1.1 model of the Intergovernmental Panel for Climate Change’s (IPCC) 5th assessment. The bioclimatic variables were minimised to a smaller number of variables after a multicollinearity test, and their contributions were assessed using jackknife test. The AUC value of 0.956 ± 0.023 indicates that the model performs with excellent accuracy. The study identified that temperature seasonality (39.5 ± 3.1%), isothermality (19.2 ± 1.6%), and annual precipitation (12.7 ± 1.7%) would be the major influencing variables in the current and future distribution. The model predicted 10.5% (19318.7 sq. km) of the study area as moderately to very highly suitable, while 82.60% (151904 sq. km) of the study area was identified as ‘unsuitable’ or ‘very low suitable’. Our predictions of climate change impact on habitat suitability suggest that there will be a drastic reduction in the suitability by 5.29% and 5.69% under RCP 8.5 for 2050 and 2070, respectively. Finally, the results signify that the model might be an effective tool for biodiversity protection, ecosystem management, and species re-habitation planning under future climate change scenarios.

Keywords: Garcinia Indica, maximum entropy modelling, climate change, MaxEnt, Western Ghats, medicinal plants

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Authors: M. R. Ebrahimi, B. Mahdaviani

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Conventional electric distribution systems are radial in nature, supplied at one end through a main source. These networks generally have a simple protection system usually implemented using fuses, re-closers, and over-current relays. Recently, great attention has been paid to applying Distributed energy resources (DERs) throughout electric distribution systems. Presence of such generation in a network leads to losing coordination of protection devices. Therefore, it is desired to develop an algorithm which is capable of protecting distribution systems that include DER. On the other hand smart grid brings opportunities to the power system. Fast advancement in communication and measurement techniques accelerates the development of multi agent system (MAS). So in this paper, a new approach for the protection of distribution networks in the presence of DERs is presented base on MAS. The proposed scheme has been implemented on a sample 27-bus distribution network.

Keywords: distributed energy resource, distribution network, protection, smart grid, multi agent system

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Authors: Barbara Kilosanidze, George Kakauridze, Levan Nadareishvili, Yuri Mshvenieradze

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A new method for determining the distribution of birefringence and linear dichroism in optical polymer materials is presented. The method is based on the use of polarization-holographic diffraction grating that forms an orthogonal circular basis in the process of diffraction of probing laser beam on the grating. The intensities ratio of the orders of diffraction on this grating enables the value of birefringence and linear dichroism in the sample to be determined. The distribution of birefringence in the sample is determined by scanning with a circularly polarized beam with a wavelength far from the absorption band of the material. If the scanning is carried out by probing beam with the wavelength near to a maximum of the absorption band of the chromophore then the distribution of linear dichroism can be determined. An appropriate theoretical model of this method is presented. A laboratory setup was created for the proposed method. An optical scheme of the laboratory setup is presented. The results of measurement in polymer films with two-dimensional gradient distribution of birefringence and linear dichroism are discussed.

Keywords: birefringence, linear dichroism, graded oriented polymers, optical polymers, optical anisotropy, polarization-holographic grating

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Authors: Paul Han, Jun-Geol Baek

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In the flat panel display industry, the scheduler and dispatching system to meet production target quantities and the deadline of production are the major production management system which controls each facility production order and distribution of WIP (Work in Process). In dispatching system, delivery time is a key factor for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors and a forecasting model of delivery time. Of survival analysis techniques to select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the Accelerated Failure Time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the Mean Square Error (MSE) criteria, the AFT model decreased by 33.8% compared to the existing prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing a delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

Keywords: delivery time, survival analysis, Cox PH model, accelerated failure time model

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Authors: A. B. Arani, R. Shojaee

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Electrical power distribution system is one of the vital infrastructures of an oil refinery, which requires wide area of study and planning before construction. In this paper, power distribution reliability of Tehran Refinery’s KHDS/GHDS unit has been taken into consideration to investigate the importance of these kinds of studies and evaluate the designed system. In this regard, the authors chose and evaluated different configurations of electrical power distribution along with the existing configuration with the aim of finding the most suited configuration which satisfies the conditions of minimum cost of electrical system construction, minimum cost imposed by loss of load, and maximum power system reliability.

Keywords: power distribution system, oil refinery, reliability, investment cost, interruption cost

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Authors: Gabriel I. Loaiza Ossa, Carlos A. Cadavid Moreno, Juan C. Arango Parra

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It is known that the Riemannian manifold determined by the family of inverse Gaussian distributions endowed with the Fisher metric has negative constant curvature κ= -1/2, as does the family of usual Gaussian distributions. In the present paper, firstly, we arrive at this result by following a different path, much simpler than the previous ones. We first put the family in exponential form, thus endowing the family with a new set of parameters, or coordinates, θ₁, θ₂; then we determine the matrix of the Fisher metric in terms of these parameters; and finally we compute this matrix in the original parameters. Secondly, we define the inverse q-Gaussian distribution family (q < 3) as the family obtained by replacing the usual exponential function with the Tsallis q-exponential function in the expression for the inverse Gaussian distribution and observe that it supports two possible geometries, the Fisher and the q-Fisher geometry. And finally, we apply our strategy to obtain results about the Fisher and q-Fisher geometry of the inverse q-Gaussian distribution family, similar to the ones obtained in the case of the inverse Gaussian distribution family.

Keywords: base of changes, information geometry, inverse Gaussian distribution, inverse q-Gaussian distribution, statistical manifolds

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Authors: Alexander K. Guo

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PM2.5 poses a large threat to people’s health and the environment and is an issue of large concern in Beijing, brought to the attention of the government by the media. In addition, both the United States Embassy in Beijing and the government of China have increased monitoring of PM2.5 in recent years, and have made real-time data available to the public. This report utilizes hourly historical data (2008-2016) from the U.S. Embassy in Beijing for the first time. The first objective was to attempt to fit probability distributions to the data to better predict a number of days exceeding the standard, and the second was to uncover any yearly, seasonal, monthly, daily, and hourly patterns and trends that may arise to better understand of air control policy. In these data, 66,650 hours and 2687 days provided valid data. Lognormal, gamma, and Weibull distributions were fit to the data through an estimation of parameters. The Chi-squared test was employed to compare the actual data with the fitted distributions. The data were used to uncover trends, patterns, and improvements in PM2.5 concentration over the period of time with valid data in addition to specific periods of time that received large amounts of media attention, analyzed to gain a better understanding of causes of air pollution. The data show a clear indication that Beijing’s air quality is unhealthy, with an average of 94.07µg/m3 across all 66,650 hours with valid data. It was found that no distribution fit the entire dataset of all 2687 days well, but each of the three above distribution types was optimal in at least one of the yearly data sets, with the lognormal distribution found to fit recent years better. An improvement in air quality beginning in 2014 was discovered, with the first five months of 2016 reporting an average PM2.5 concentration that is 23.8% lower than the average of the same period in all years, perhaps the result of various new pollution-control policies. It was also found that the winter and fall months contained more days in both good and extremely polluted categories, leading to a higher average but a comparable median in these months. Additionally, the evening hours, especially in the winter, reported much higher PM2.5 concentrations than the afternoon hours, possibly due to the prohibition of trucks in the city in the daytime and the increased use of coal for heating in the colder months when residents are home in the evening. Lastly, through analysis of special intervals that attracted media attention for either unnaturally good or bad air quality, the government’s temporary pollution control measures, such as more intensive road-space rationing and factory closures, are shown to be effective. In summary, air quality in Beijing is improving steadily and do follow standard probability distributions to an extent, but still needs improvement. Analysis will be updated when new data become available.

Keywords: Beijing, distribution, patterns, pm2.5, trends

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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Authors: O. Arikan, C. Kocatepe, G. Ucar, Y. Hacialiefendioglu

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In this paper, influence of harmonics on medium voltage distribution system of Bogazici Electricity Distribution Inc. (BEDAS) which takes place at Istanbul/Turkey is investigated. A ring network consisting of residential loads is taken into account for this study. Real system parameters and measurement results are used for simulations. Also, probable working conditions of the system are analyzed for %50, %75 and %100 loading of transformers with similar harmonic contents. Results of the study are exhibited the influence of nonlinear loads on %THDV, P.F. and technical losses of the medium voltage distribution system.

Keywords: distribution system, harmonic, technical losses, power factor, total harmonic distortion, residential load, medium voltage

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Authors: Arunas Burinskas, Manuela Tvaronavičienė

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Although the new trade theories, unlike the theories of an industrial organisation, see the structure of the market and competition between enterprises through their heterogeneity according to various parameters, they do not pay any particular attention to the analysis of the market structure and its development. In this article, although we relied mainly on models developed by the scholars of new trade theory, we proposed a different approach. In our simulation model, we model market demand according to normal distribution function, while on the supply side (as it is in the new trade theory models), productivity is modeled with the Pareto distribution function. The results of the simulation show that companies with higher productivity (lower marginal costs) do not pass on all the benefits of such economies to buyers. However, even with higher marginal costs, firms can choose to offer higher value-added goods to stay in the market. In general, the structure of the market is formed quickly enough and depends on the skills available to firms.

Keywords: market, structure, simulation, heterogenous firms

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Authors: Mohamed Noureldin, Jinkoo Kim

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In this study, a genetic algorithm was used to find out the optimum locations of the slit dampers satisfying a target displacement. A seismic retrofit scheme for a building structure was presented using steel plate slit dampers. A cyclic loading test was used to verify the energy dissipation capacity of the slit damper. The seismic retrofit of the model structure using the slit dampers was compared with the retrofit with enlarging shear walls. The capacity spectrum method was used to propose a simple damper distribution scheme proportional to the inter-story drifts. The validity of the simple story-wise damper distribution procedure was verified by comparing the results of the genetic algorithm. It was observed that the proposed simple damper distribution pattern was in a good agreement with the optimum distribution obtained from the genetic algorithm. Acknowledgment: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03032809).

Keywords: slit dampers, seismic retrofit, genetic algorithm, optimum design

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Authors: Jayanta Pokharel, Gokarna Aryal, Netra Kanaal, Chris Tsokos

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Investment in stocks and shares aims to seek potential gains while weighing the risk of future needs, such as retirement, children's education etc. Analysis of the behavior of the stock market returns and making prediction is important for investors to mitigate risk on investment. Historically, the normal variance models have been used to describe the behavior of stock market returns. However, the returns of the financial assets are actually skewed with higher kurtosis, heavier tails, and a higher center than the normal distribution. The Laplace distribution and its family are natural candidates for modeling stock returns. The Variance-Gamma (VG) distribution is the most sought-after distributions for modeling asset returns and has been extensively discussed in financial literatures. In this paper, it explore the other Laplace family, such as Asymmetric Laplace, Skewed Laplace, Kumaraswamy Laplace (KS) together with Variance-Gamma to model the weekly returns of the S&P 500 Index and it's eleven business sector indices. The method of maximum likelihood is employed to estimate the parameters of the distributions and our empirical inquiry shows that the Kumaraswamy Laplace distribution performs much better for stock returns modeling among the choice of distributions used in this study and in practice, KS can be used as a strong alternative to VG distribution.

Keywords: stock returns, variance-gamma, kumaraswamy laplace, maximum likelihood

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Authors: Lu Ren, You-Liang Fang, Yan-Gang Zhao

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In recent years, the application of BIM (Building Information Modelling) to construction schedule plan has been the focus of more and more researchers. In order to assess the reasonable level of the BIM-based construction schedule plan, that is whether the schedule can be completed on time, some researchers have introduced reliability theory to evaluate. In the process of evaluation, the uncertain factors affecting the construction schedule plan are regarded as random variables, and probability distributions of the random variables are assumed to be normal distribution, which is determined using two parameters evaluated from the mean and standard deviation of statistical data. However, in practical engineering, most of the uncertain influence factors are not normal random variables. So the evaluation results of the construction schedule plan will be unreasonable under the assumption that probability distributions of random variables submitted to the normal distribution. Therefore, in order to get a more reasonable evaluation result, it is necessary to describe the distribution of random variables more comprehensively. For this purpose, cubic normal distribution is introduced in this paper to describe the distribution of arbitrary random variables, which is determined by the first four moments (mean, standard deviation, skewness and kurtosis). In this paper, building the BIM model firstly according to the design messages of the structure and making the construction schedule plan based on BIM, then the cubic normal distribution is used to describe the distribution of the random variables due to the collecting statistical data of the random factors influencing construction schedule plan. Next the reliability analysis of the construction schedule plan based on BIM can be carried out more reasonably. Finally, the more accurate evaluation results can be given providing reference for the implementation of the actual construction schedule plan. In the last part of this paper, the more efficiency and accuracy of the proposed methodology for the reliability analysis of the construction schedule plan based on BIM are conducted through practical engineering case.

Keywords: BIM, construction schedule plan, cubic normal distribution, reliability analysis

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Authors: I. A. Simsek, S. N. Dogan, A. S. Kipcak, E. Morodor Derun, N. Tugrul

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In this study, the drying characteristics of shrimp are studied by using the traditional drying method of oven. Drying temperatures are selected between 60-80°C. Obtained experimental drying results are applied to eleven mathematical models of Alibas, Aghbashlo et al., Henderson and Pabis, Jena and Das, Lewis, Logaritmic, Midilli and Kucuk, Page, Parabolic, Wang and Singh and Weibull. The best model was selected as parabolic based on the highest coefficient of determination (R²) (0.999990 at 80°C) and the lowest χ² (0.000002 at 80°C), and the lowest root mean square error (RMSE) (0.000976 at 80°C) values are compared to other models. The effective moisture diffusivity (Deff) values were calculated using the Fick’s second law’s cylindrical coordinate approximation and are found between 6.61×10⁻⁸ and 6.66×10⁻⁷ m²/s. The activation energy (Ea) was calculated using modified form of Arrhenius equation and is found as 18.315 kW/kg.

Keywords: activation energy, drying, effective moisture diffusivity, modelling, oven, shrimp

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Authors: Zdeněk Veselý, Milan Honner, Jiří Mach

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The aim of the performed work is to establish the 2D and 3D model of direct unsteady task of sample heat treatment by moving source employing computer model on the basis of finite element method. The complex boundary condition on heat loaded sample surface is the essential feature of the task. Computer model describes heat treatment of the sample during heat source movement over the sample surface. It is started from the 2D task of sample cross section as a basic model. Possibilities of extension from 2D to 3D task are discussed. The effect of the addition of third model dimension on the temperature distribution in the sample is showed. Comparison of various model parameters on the sample temperatures is observed. Influence of heat source motion on the depth of material heat treatment is shown for several velocities of the movement. Presented computer model is prepared for the utilization in laser treatment of machine parts.

Keywords: computer simulation, unsteady model, heat treatment, complex boundary condition, moving heat source

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Authors: Sajida Rasheed, Imran Hashmi, Luiza Campos, Qizhi Zhou, Kim Keu

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A quadratic model (p ˂ 0.0001) was developed by using central composite design of 50 experimental runs (42 non-center + 8 center points) to assess efficiency of background chlorine residuals in combating accidental microbial episode in a prototype distribution network (DN) (rig). A known amount of background chlorine residuals were maintained in DN and a required number of bacteria, Escherichia coli K-12 strain were introduced by an injection port in the pipe loop system. Samples were taken at various time intervals at different pipe lengths. Spread plate count was performed to count bacterial number. The model developed was significant. With microbial concentration and time (p ˂ 0.0001), pipe length (p ˂ 0.022), background chlorine residuals (p ˂ 0.07) and time^2 (p ˂ 0.09) as significant factors. The ramp function of variables shows that at the microbial count of 10^6, at 0.76 L/min, and pipe length of 133 meters, a background residual chlorine 0.16 mg/L was enough for complete inactivation of microbial episode in approximately 18 minutes.

Keywords: central composite design (CCD), distribution network, Escherichia coli, residual chlorine

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Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

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In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Keywords: ER-schema, electronic record, P2P framework, API, query formulation

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Authors: Chao-xun Liu, Shi-hong Lu

Abstract:

In spite of its importance to the aerospace and automobile industries, little or no attention has been devoted to the accurate modeling of the ultrasonic shot peening (USP) process. It is therefore the purpose of this study to conduct finite element analysis of the process using a realistic multiple pin impacts model with the explicit solver of ABAQUS. In this paper, we research the effect of several key parameters on the residual stress distribution within the target, including impact velocity, incident angle, friction coefficient between pins and target and impact number of times were investigated. The results reveal that the impact velocity and impact number of times have obvious effect and impacting vertically could produce the most perfect residual stress distribution. Then we compare the results with the date in USP experiment and verify the exactness of the model. The analysis of the multiple pin impacts date reveal the relationships between peening process parameters and peening quality, which are useful for identifying the parameters which need to be controlled and regulated in order to produce a more beneficial compressive residual stress distribution within the target.

Keywords: ultrasonic shot peening, finite element, multiple pins, residual stress, numerical simulation

Procedia PDF Downloads 448

Authors: Yungtai Lo

Abstract:

Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

Procedia PDF Downloads 349

Authors: C. R. Danielle, S. Erik, T. Patrick, M. Hugh

Abstract:

In the last decade there has been an increase in demand for fine grinding due to the depletion of coarse-grained orebodies and an increase of processing fine disseminated minerals and complex orebodies. These ores have provided new challenges in concentrator design because fine and ultra-fine grinding is required to achieve acceptable recovery rates. Therefore, the correct design of a grinding circuit is important for minimizing unit costs and increasing product quality. The use of ball mills for grinding in fine size ranges is inefficient and, therefore, vertical stirred grinding mills are becoming increasingly popular in the mineral processing industry due to its already known high energy efficiency. This work presents a hypothesis of a methodology to predict the product size distribution of a vertical stirred mill using a Bond ball mill. The Population Balance Model (PBM) was used to empirically analyze the performance of a vertical mill and a Bond ball mill. The breakage parameters obtained for both grinding mills are compared to determine the possibility of predicting the product size distribution of a vertical mill based on the results obtained from the Bond ball mill. The biggest advantage of this methodology is that most of the minerals processing laboratories already have a Bond ball mill to perform the tests suggested in this study. Preliminary results show the possibility of predicting the performance of a laboratory vertical stirred mill using a Bond ball mill.

Keywords: bond ball mill, population balance model, product size distribution, vertical stirred mill

Procedia PDF Downloads 292

Authors: Kateřina Jurdová

Abstract:

Hanging to the trapezoidal sheet by decking hanger is a very widespread solution used in civil engineering to lead the distribution of energy, sanitary, air distribution system etc. under the roof or floor structure. The trapezoidal decking hanger is usually a part of the whole installation system for specific distribution medium. The leading companies offer installation systems for each specific distribution e.g. pipe rings, sprinkler systems, installation channels etc. Every specific part is connected to the base connector which is decking hanger. The own connection has three main components: decking hanger, threaded bar with nuts and web of trapezoidal sheet. The aim of this contribution is determinate the failure mechanism of each component in connection. Load bearing capacity of most components in connection could be calculated by formulas in European codes. This contribution is focused on problematic of bearing resistance of threaded bar in web of trapezoidal sheet. This issue is studied by experimental research and numerical modelling. This contribution presented the initial results of experiment which is compared with numerical model of specimen.

Keywords: decking hanger, concentrated load, connection, load bearing capacity, trapezoidal metal sheet

Procedia PDF Downloads 392