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Showing 14 results for Interpolation
A NEW METHOD FOR TOOL-PATH GENERATION AND ADAPTIVE Interpolation OF A THREE-AXIS CNC MILLING MACHINE
Volume 2, Issue 1 (4-2002)
Abstract
In this paper we present a new method for tool-path generation and adaptive interpolation for a three-axis CNC milling machine. This method satisfied the force and / or the error conditions by using a variable-direction variable-feedrate strategy based on Maximum Feedrate Map. The proposed adaptive interpolator modifies the cutting path and the moving direction according to the actual instantaneous position error in real time. It also adaptively slows down the speed of the cutting tool if the position error exceeds a permissible threshold so as to decrease the error. As the cutting points on the spline at each cycle are not calculated beforehand, memory requirement for the interpolator drastically reduces. The significance of the proposed method on the reduction of the cutting error in the presence of disturbance is demonstrated via computer simulations.
Volume 7, Issue 4 (9-2019)
Abstract
Aims: Monitoring and zoning of water resources are one of the important principles in environmental planning and management. Therefore, considering the issues raised and the importance of Anzali wetland monitoring, the assessment of effective factors in zoning (GIS) along with TSI p, TSI n, and NSFWQI indices and the study of land use effects justifies the necessity of this study.
Materials & Methods: In this study, physicochemical parameters of water (phosphate, total nitrogen and total dissolved solids, dissolved oxygen, acidity, electrical conductivity, and BOD5 properties) and water quality indicators (TSI p, TSI n, and NSFWQI) were modeled using GIS interpolation functions. To determine the effect of land use, the partial and Pearson correlations coefficient were used.
Findings: According to zonation maps of annual mean values of qualitative parameters, the lowest dissolved oxygen content was in the eastern part of the wetland, the highest electrical conductivity, as well as BOD5 observed in the center of the north, in the east and north of the wetland, respectively. A survey of the total phosphate zonation map revealed the increasing trend from west to east of the wetland. The partial correlation analysis showed that the electrical conductivity, acidity and total dissolved solids were directly affected by inputs and effluent from the land use (p<0.05; p<0.01).
Conclusion: Based on the coefficient of determination, about 70% of the pollution derived from the use of wetlands surrounding and entering wastewater from agricultural fields, industrial and urban.
Materials & Methods: In this study, physicochemical parameters of water (phosphate, total nitrogen and total dissolved solids, dissolved oxygen, acidity, electrical conductivity, and BOD5 properties) and water quality indicators (TSI p, TSI n, and NSFWQI) were modeled using GIS interpolation functions. To determine the effect of land use, the partial and Pearson correlations coefficient were used.
Findings: According to zonation maps of annual mean values of qualitative parameters, the lowest dissolved oxygen content was in the eastern part of the wetland, the highest electrical conductivity, as well as BOD5 observed in the center of the north, in the east and north of the wetland, respectively. A survey of the total phosphate zonation map revealed the increasing trend from west to east of the wetland. The partial correlation analysis showed that the electrical conductivity, acidity and total dissolved solids were directly affected by inputs and effluent from the land use (p<0.05; p<0.01).
Conclusion: Based on the coefficient of determination, about 70% of the pollution derived from the use of wetlands surrounding and entering wastewater from agricultural fields, industrial and urban.
Volume 11, Issue 1 (2-2023)
Abstract
Aims: The availability of precipitation data plays an important role in many meteorological, hydrological and applications.
Materials & Methods: In this study, to improve precipitation maps and increase the accuracy of precipitation maps, linear regression, multivariate, and Kriging subsets were used. The data from 14 meteorological stations and IMERG images in the period of 20 years (2001 to 2020), digital elevation model, Latitude and Longitude maps were used. At first, based on regression in Minitab software, the relationship between air and ground parameters was taken. Finally, with the interpolation methods and based on the error coefficients, the best equations for predicting precipitation were determined and the spatial distribution of precipitation was obtained.
Findings: According to the results, six out of 13 models were selected because of low RMSE and high R2, R, and NS. In regression models where only one climatic or edaphic parameter was used, forecast accuracy was reduced. But in the models that were used in the regression elevation, Longitude, Latitude and IMERG parameters in combination with interpolation methods, the extracted data matched the real data with a slight difference. In this study, instead of the average of the input parameters, the maps of each parameter were used, increasing the accuracy of the forecast model to R2=0.8.
Conclusion: results showed that combining satellite precipitation products with interpolation methods led to a more accurate estimate of precipitation in the points without recording data will be precipitated and the multivariate regression method will be more accurate than the linear gradient.
Volume 14, Issue 6 (11-2012)
Abstract
Sustainable management of limited land and water resources is urgently needed to meet the increasing demand for food and to protect the environment. Land suitability analysis is a prerequisite in assessing and proposing sustainable land use alternatives for an area. Soil data are usually available at different levels of detail and stored in various forms, usually soil maps and/or soil observations. Soil data interpretation methods control the reliability of land suitability evaluation results. This has a serious effect on the reliability of the suitability maps, the subsequent land use decisions, and environmental modeling. This study examines the reliability of land suitability mapping using different methods of soil data interpretation – the average of land characteristics for field observations within soil map units (point-in-polygon) and spatial interpolation using field observations only (proximity to points). The degree of agreement between the two methods depends on the type of land utilization – rainfed barley (86%), open range (85%), improved range (75%), drip irrigated vegetables (69%), and drip irrigated trees (59%). This results from the difference in the limiting land characteristic that determines the suitability of each land utilization type and the pattern of spatial variation of each land characteristic in the field. Suitability maps for adaptable (indigenous) crops (such as barley and range crops), which require minimum farming inputs, are generally more accurate because they tolerate a wider range of variability. The interpolation method was more efficient in detecting the spatial distribution and extreme values of limiting land characteristics, resulting in more accurate suitability maps. Therefore, when detailed soil maps are not available, field observations could be used to derive suitability maps using an exact interpolation method.
Volume 16, Issue 7 (9-2016)
Abstract
Uncertainty inherently exists in quantity of a system’s parameters (e.g., loading or elastic modulus of a structure), and thus its effects have always been considered as an important issue for engineers. Meanwhile, numerical methods play significant role in stochastic computational mechanics, particularly for the problems without analytical solutions. In this article, spectral finite element method is utilized for stochastic spectral finite element analysis of 2D continua considering material uncertainties. Here, Lobatto family of higher order spectral elements is extended, and then influence of mesh configuration and order of interpolation functions are evaluated. Furthermore, Fredholm integral equation due to Karhunen Loève expansion is numerically solved through spectral finite element method such that different meshes and interpolation functions’ orders are also chosen for comparison and assessment of numerical solutions solved for this equation. This method needs fewer elements compared to the classic finite element method, and it is specifically useful in dynamic analysis as supplies desirable accuracy with having diagonal mass matrix. Also, these spectral elements accelerate the computation process along with Karhunen Loève and polynomial chaos expansions involving numerical solution of Fredholm integral equation. This research examines elastostatic and elastodynamic benchmark problems to demonstrate the effects of the undertaken parameters on accuracy of the stochastic analysis. Moreover, results demonstrate the effects of higher-order spectral elements on speed, accuracy and efficiency of static and dynamic analysis of continua.
Volume 16, Issue 11 (1-2017)
Abstract
A variety of numerical methods were developed for the wave propagation analysis in the field of structural health monitoring. In this framework, meshless methods are suitable procedure for the analysis of problems such as damage initiation and its propagation or the fracture of materials. In this study, Hermit-type radial point interpolation method (HRPIM) is investigated for the numerical modeling of flexural wave propagation and damage quantification in Euler-Bernoulli beams using MATLAB. This method employs radial basis function (RBF) and its derivatives for interpolation which leads to Hermitian formulation. The evaluation of performance and capability of HRPIM is based on the comparison between the captured HRPIM ang benchmark signals using the root mean square error (RMSE) and reflection ratio from damage. The algorithm of damage quantification is the analytical solution which relates the reflection ratio to the damage extent. In this study, Gausian-type RBF is utilized and the number of field nodes, the size of support domain, shape parameters of RBF, the number of polynomials in the interpolation formula, the arrangement of background cells and the number of Gaussian points in damage length are the effective parameters on results. Based on the evaluation, the acceptable values and range of theses parameters are presented for correct modeling.
Volume 17, Issue 2 (3-2017)
Abstract
In this article, the ghost fluid-lattice Boltzmann method, used to simulate the curved boundaries is combined with an extrapolation based refilling method to cope with the moving curved boundaries, where in each iteration some of the solid nodes step into the fluid domain. The refilling method is used to approximate the unknown density and internal energy distribution functions of such solid nodes. To examine the accuracy of the presented method, several case studies are considered. From those case studies, natural convection problem between to concentric and eccentric cylinders as well as heat transfer from a cylinder in a cross flow are considered to validate the ghost-fluid lattice Boltzmann method used to simulate the hydrodynamic and thermal conditions at the curved boundaries. To test the accuracy of the employed refilling method, sedimentation of a single isothermal cold particle in a vertical channel investigated. The results show that the presented ghost fluid-lattice Boltzmann method with refilling is capable of simulating the moving thermal curved boundaries with excellent accuracy.
Mohammad Khajeh, Omolbanin Bazrafshan, Hassan Vagharfard, Yahya Esmaeelpoor,
Volume 18, Issue 4 (1-2015)
Volume 18, Issue 4 (1-2015)
Abstract
Today because of the lack of rainfall over a several year period, excess pumping of water and use of excess groundwater in addition to poor management, it is of utmost importance to pay attention to the quantity and quality of groundwater. In this research we have emphasized one of the most important agricultural areas, Parishan Plain located in Fars Province, Iran. For this purpose, data was collected from 1382-1390 and the contour map and additional characteristics were calculated by interpolation and the use of IDW and GIS. We additionally used SPI to estimate the intensity and duration of climatic dryness. To determine the gradual drawdown the hydrograph from a piezometer (observation) well in Parishan Plain was used. Based on the collected data, the drawdown was approximately 6.25 m from 1382-1390. The hydrograph showed that from 1382-1383 the water table increased by 2.03 m; from 1383-1389 the water table fell by 7.93 m; and from 1389-1390 the water table rose by 0.26 m. Water quality decreased, particularly from 1386-90 due to the dry years and water table drawdown. The results have shown that the recent decade is four times more dry compared to the previous two decades. q q q q q
Volume 19, Issue 4 (7-2017)
Abstract
In Iran, applying geostatistics to regional analysis is said to be in its early stages. The fundamental principle of this technique emphasizes the interpolation of hydrological variables in physiographical, instead of geographical, spaces. This paper deals with the adaptation, application, and comparison of two regional analysis methods based on geostatistics. In this study, data from 38 gauging stations located in the north of Iran were used to investigate the performance of geostatistical methods in two physiographical spaces. Two multivariate analysis methods, namely, Canonical Correlation Analysis (CCA) and Principal Components Analysis (PCA), were used to identify physiographical spaces. Gaussian and exponential models were selected as the best theoretical variogram models in CCA and PCA spaces, respectively. Ordinary and simple kriging geostatistical estimators were also used for regional estimations in both physiographical spaces. Using the interpolation methods in CCA and PCA spaces, regional flood estimations were made for different return periods (10, 20, 50, and 100 years). Finally, performance of both models was studied using five statistical indices. The results showed that both methods had similar and satisfactory performance; however, regional estimations in CCA had higher accuracy and less uncertainty than those in PCA-space. Furthermore, the results indicated that the ordinary kriging method had better performance than the simple kriging method in both spaces and the best interpolation efficiency was observed in the CCA space.
Volume 19, Issue 4 (11-2019)
Abstract
In conventional analyzes of soil slopes failure, resistance parameters are assumed to be stable even in large strains without change. However, during the rupture, soil resistance exhibits maximum and residual amounts, and its strength increases prematurely by increasing the plastic strain. In addition to changing soil resistance parameters in the progressive mechanism, the non-uniform nature of the soil also causes spatial variations of these parameters. Therefore, geotechnical systems should be considered in terms of the uncertainty of soil parameters values uncertainly using the concepts of statistics and probabilities. The simulation of a progressive failure is definite or non-deterministic only by applying numerical techniques such as finite element method that are able to simulate the development of deviant plastic strain. Although the finite element method is widely used in the analysis of sustainability issues, however, this approach is based on problems that are essentially related to gridding. In this research, a radial point interpolation method in combination with a random field was used to model the spatial variations of soil resistance properties and slope instability analysis. In order to consider the progressive failure of soil, elastoplastic method has been developed with the Coulomb Moore's behavioral model for applying strain softness. For probabilistic analysis, the random field is also used to determine the cohesion parameters and the friction angle as well as the plastic strain threshold based on their mean values and standard deviation. In order to investigate the application of the point interpolation method with randomized radial functions, a geotechnical earthwork with definite and non-deterministic geometry has been analyzed and its reliability coefficient has been investigated. Based on the analysis of the progressive failure modeling, it is concluded that the actual failure of the soil and the occurrence of continuous displacements occur simultaneously with the formation of a progressive mechanism of soil degradation and the arrival of the slipping path to the ground. In the following, probabilistic distribution functions of the coefficient of reliability were determined by probabilistic analysis and the production of random fields, and then the statistical parameters are calculated.
Volume 19, Issue 5 (9-2017)
Abstract
To identify the Cereal Cyst Nematodes (CCN) and their distribution and population density in wheat fields in Chaharmahal and Bakhtiari Province based on interpolation by geographic information system, a total of 212 composite soil and root samples were randomly collected from different wheat fields of nine districts of the province during 2013-2014. The soil samples were explored for number of cysts, second-stage Juveniles (J2) and eggs. The species were identified based on morphological, morphometric and molecular characteristics. Analysis was performed by Arc GIS software using interpolation technique for determination of raster map. The results showed that 42% of soil samples were infested with Heterodera filipjevi containing an average of 994 eggs and J2 per 200 g of soil. The maximum infestation was observed in Dehsahra region in Lordegan district with an average of 4720 eggs and J2 per 200 g soil. Wheat fields of Kohrang, Kiyar and Farsan districts showed low population density while moderate infestation was observed in Ardal, Ben, Saman and Borujen districts. Instead high population density of H. filipjevi was found in Shahrekord and Lordegan. Based on interpolation of population density and interpolation maps, the eastern part of Shahrekord and southern and western parts of Lordegan districts were predicted as regions with high infestation to H. filipjevi and considered as hotspots for this disease.
Volume 21, Issue 1 (3-2021)
Abstract
Precipitation affects quantity and quality of water resources and agricultural production. Therefore, the estimation and analysis of its spatial-temporal variations is of great importance. In many regions of Iran, limited spatial-temporal information is available due to sparse distribution of monitoring stations and short observational records. On the other hand, dependency of rain-fed and irrigated production systems on precipitation increases the importance of the analysis of spatiotemporal variations of this weather variable. One way to address this limitation is to use regional/global gridded datasets. In this study, monthly precipitation data were obtained from the CRU dataset (developed principally by the UK's Natural Environment Research Council (NERC) and the US Department of Energy) and used to investigate temporal trends in annual, seasonal and monthly precipitations in 675 grid cells (0.5°×0.5°) across Iran over two periods, 1957-1986 and 1987-2016. The results of the previous studies showed that the CRU gridded dataset offers quality data in Iran, especially for trend analysis. Also, the accuracy of the CRU dataset was validated in 14 selected stations regarding monthly precipitations and temporal trends over two different periods, pre-1987 and post-1987. The significance of temporal trends was assessed using a modified version of the rank-based nonparametric Mann-Kendall (MK) test. Trend magnitudes (i.e. slope) were estimated with the Theil-Sen approach and the Trend Free Pre-whitening (TFPW) procedure was applied to remove the effect of serial correlation. The results confirm the acceptable accuracy of the CRU dataset for trend analysis purposes, especially over the last three decades, except in the northern strip of the country (RMSE=10.71mm, R2=0.84). Two 30-year periods (1957-1986 and 1987-2016) were compared in terms of spatial patterns and temporal trends. Annual precipitation over the last three decades (1987-2016) has decreased as compare to the previous 30-year period (1957-1986) in most parts of the country. Over the last three decades, around 42% and 50% of the country’s total area experienced significant and insignificant decreasing trends in annual precipitation, respectively. National average annual precipitation has decreased by 15.78 mm/decade over the same period. Three important regions regarding agricultural production experienced the most significant reductions in annual precipitation: (1) Ardebil, East Azerbaijan, Kurdistan, Kermanshah, Ilam, Lorestan, Zanjan, Hamadan, and parts of West Azerbaijan, Markazi and Gilan (in the west and northwest), (2) Sistan and Baluchestan, Kerman, and southern parts of South Khorasan (in the south and south east), and (3) North Khorasan, northern parts of Razavi Khorasan and east of Golestan (in the east and north east). Reduced annual precipitation was mainly attributed to the reduction in seasonal precipitations in winter and spring, which have critical role in agricultural production and domestic water supply. Temporal trends were also analysed at the monthly scale. January, February, March and December revealed the largest number of grid cells with significant decreasing trends over 1987-2016 while November is the only month with significant number of grid cells experiencing significant increasing trends. The results of this study show that the monthly time series of the CRU TS 4.01 dataset, which has an almost complete spatial and temporal coverage in Iran over the last 60 years, are promising alternatives to weather station observations especially in data-scarce regions of Iran. Analysis of variations and the seasonal and monthly scales help understand the recent climate change and target the most crucial features of it when it comes to formulating adaptation strategies.
H. Nazmfar, Ali Eshghi, Sarideh Alavi,
Volume 21, Issue 4 (12-2017)
Volume 21, Issue 4 (12-2017)
Abstract
Housing prices in a city spatial analysis, spatial vision of the city in terms of housing prices creates existence thoroughly. Using such an analysis can be found in the city, where prices are high or low in the analysis. This study were conducted aims to achieve spatial pattern of housing prices in the city. The purpose of applied research and in terms of the nature and method is analytic. The population of the city of Tabriz in 1390, is the residential apartment. Analysis of the spatial pattern analysis is used, cluster analysis in GIS maps and kriging interpolation method. The results of index rating average nearest neighbor with standard 88/22 and P Value 000/0 shows the distribution of cluster housing prices at all levels. According to statistics of General G, P Value and Variance value is zero, indicating a cluster pattern with a high concentration. The results show that the highest concentration of hot spots hot spots (highest price) in the East part of the city with the highest concentration of cold spots (lowest price) in the north, north-western and south-western city of Tabriz. Geocaching and no points given little value estimation using kriging interpolation using adjacent areas indicate that11/34 percent of housing in Tabriz has less than a million.
Majid Goodarzi, Mohammad Ali Feroozi, Omid Saeidi,
Volume 24, Issue 2 (6-2020)
Volume 24, Issue 2 (6-2020)
Abstract
Introduction: Collective mobility focuses on sharing trips, transport modes, and infrastructures. This can reduce the number of vehicles on roads. Thus, it is important to evaluate and measure transport subsystems. One of the most important
Methodology: The present study is applied-theoretical in terms of objectives; also descriptive-analytical and survey in terms of research methods. The research data was collected through documentary, library, survey, and interviewing with people and urban planning experts. The research population consisted of citizens of eight
Results and discussion: In sum, this study identified 36 key barriers to each of Ahvaz public transport land use for analyzing the land use barriers to public transport development in Ahvaz. These barriers
Conclusion: The present study employed barriers covering each of the six physical dimensions. We then need to rank these barriers to identify the most effective barriers to each of the six dimensions of physical barriers (stations, urban terminals, urban arteries, public parking lots, fuel stations, and transport fleets). The significance of this ranking is that the underlying organizations are not capable of removing all of them at a given time, and removing these
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