Location Of Sampling Points Research Articles

An active learning multi-fidelity metamodeling method based on the bootstrap estimator

Multi-fidelity (MF) metamodel has attracted significant attention recently in simulation-based design and optimization. It can achieve a desirable modeling accuracy with relatively lower simulation cost by making use of the data from both low-fidelity (LF) and high-fidelity (HF) simulations. To facilitate the usage of MF metamodel, there are still challenging issues on (1) how to determine the location of sample points, and (2) how to allocate the limited computational budget to HF and LF simulations. In this study, a bootstrap-based sequential multi-fidelity (BB-SMF) metamodeling method is proposed for data regression of computationally expensive black-box problems. First, constrained optimization problems with the goal of reducing the global predicted error of the MF metamodel are constructed to obtain the candidates for HF and LF simulations, respectively. Specifically, the predicted error of the MF metamodel is evaluated by a developed MF bootstrap estimator. Second, a criterion based on the uncertainty of pseudo-updated MF metamodel is developed to determine whether one HF sample or several LF sample points with the equivalent computational budget are selected to update the MF metamodel. To demonstrate the performance of the proposed method, two analytical functions and a maximum stress prediction problem of the micro-aerial vehicle (MAV) fuselage are adopted. Different test conditions are also discussed, such as different correlation level, initial sample sizes, and cost ratios. Results show that the proposed BB-SMF metamodel is more accurate and robust than the compared methods.

Статистика Getis-Ord Gi* при обработке многолетних данных содержания углеводородов в бассейне реки Большой Балык

Balyk river basin for the period 2006–2017 using ArcGIS Pro statistical analysis tools are presented in this article. The information basis of the research is the local environment monitoring data of license areas of Ugra, Khanty-Mansiysk Autonomous Okrug, RF. The research was implemented in two stages. At the first stage, pollution hot spots were revealed basing on the calculation of local Getis-Ord Gi* index for each year. The calculation was made taking into account the mutual location of sampling points and value of the neighborhood. At the second stage hot spots genesis for 12 years was analyzed via modelling space-and-time cube. Clustering time series of hydrocarbons average annual concentration according to the Getis-Ord Gi* indicator made it possible to determine the places of one-off pollution, most likely associated with oil spills, and to track pollutants transportation along the current. The location of the increasing river ecosystem pollution was also determined. The obtained results enable bringing out basic zones of permanent high hydrocarbon concentrations and places of periodic discharges into the river basin.

A trustworthiness indicator to select sample points for the individual predictive soil mapping method (iPSM)

Observations of soil at georeferenced sample points are the indispensable input to digital soil mapping (DSM) models that relate soil properties and types to the soil-forming environment. Many existing DSM methods require soil samples to be collected following a pre-defined sampling pattern. This requirement is often not met due to various operational reasons. The individual sample-based predictive soil mapping (iPSM) method has been developed to avoid this requirement. However, the prediction accuracy of iPSM depends heavily on the reliability of the known sample points used in prediction. Unreliable sample points are those with unreliable soil-environment relationship: the target soil property value and environmental covariate data are not correctly paired at the sample point location. Such unreliable sample points will lead to poorly constructed models and low prediction accuracy. This paper presents a new method to estimate the reliability of soil-environment relationship at each sample location and to evaluate the trustworthiness of prediction at each unvisited location. Under the assumption that sample points with similar environmental conditions have similar soil property values, the method first identifies the sample points that are environmentally similar to the sample point to be evaluated, then uses their agreement on the targeted soil property to evaluate the reliability of soil-environment relationship at the sample point. The effectiveness of the method was assessed in a case study located in Anhui Province in China to map soil organic matter content (SOM, %) in the topsoil. When the reliability threshold increased from 0.5 to 0.8, more unreliable sample points are excluded from prediction: 41% of total sample points were excluded when the threshold was set to 0.5, and 88% were excluded when the threshold was set to 0.8. As a result, less unknown area could be predicted – only nine validation points were predictable with the 0.8 reliability threshold. However, the prediction accuracy was improved: the root mean squared error, RMSE, decreased from 1.37% to 0.63%, and R2 increased from 0.21 to 0.98. Prediction trustworthiness at each unvisited location was also produced along with prediction accuracy, which was negatively related to the absolute prediction residuals. This study shows that the reliability of individual sample points is an important determinant of the prediction accuracy of the iPSM method. When applying iPSM method, an optimal trade-off between prediction accuracy and completeness of the predicted map needs to be found by adjusting the reliability threshold on the sample points used in prediction.

Alternative study of reducing Carbon Dioxide (CO2) from the transportation sector in Medan city

Increase of amount greenhouse gas (GHG) emissions from human activities in the form of an increase the number of vehicles indirectly impacting climate change. The purpose of this study is to calculate GHG emissions, namely carbon dioxide (CO2) generated from the transportation sector and determine the scenario of reducing CO2 emissions from the sector transportation in Medan City. The method of calculating GHG emissions in this study uses TIER II from IPCC. The study was conducted in 12 locations of sampling points with a traffic counting time of 12 hours per each point with variations in the time of workdays and weekdays. The results showed that CO2 emissions generated at the twelve sampling locations amounted to 484.41 - 561.16 tons CO2 / year. The scenario of reducing CO2 emissions in this study is the application of Bus Rapid Transit (BRT), parking management systems and fuel substitution. Comparison of the average of the three scenarios in reducing CO2 namely; the application of BRT ± 24.28% with the number of BRT units needed per road segment ranging from 11 - 57 units; fuel substitution of ± 9.16% and parking management system ± 12.08%.

Impact of River Water and Bottom Sediment Pollution on Accumulation of Metal(loid)s and Arsenic Species in the Coastal Plants Stuckenia pectinata L., Galium aparine L., and Urtica dioica L.: A Chemometric and Environmental Study

The role of water and bottom sediment pollution of a river subjected to a strong industrial anthropo-pressure in coastal plants was investigated. The work presented the influence of polluted environment on accumulation of metal(loid)s (including arsenic and its species) in Stuckenia pectinata L., Galium aparine L., and Urtica dioica L. The study provided important information on the contents of organic and inorganic arsenic species in selected plants and their response to heavy metal and arsenic contamination. The As(III), As(V), AB (arsenobetaine), MMA (monomethylarsonic acid), and DMA (dimethylarsinic acid) ions were successfully separated on the Hamilton PRP-X100 column with high-performance liquid chromatography-inductively coupled plasma-mass spectrometry (HPLC-ICP-MS) techniques. The Pollution Load Index and geo-accumulation Index (Igeo) values clearly indicate significant pollution of the examined ecosystem with heavy metals. The chemometric analysis with the concepts of (Dis)similarity Analysis, Cluster Analysis, and Principal Component Analysis helped to visualize the variability of the As species concentrations and to analyse correlations between sampling point locations and analyte contents.

Assessment of groundwater quality and its suitability for the inhabitants of Andrott Island, Lakshadweep

Groundwater serves as the main sources of drinking water for the Islanders. Now a days, the groundwater is contaminated due to sea water intusion and continuous anthropogenic activities. A proper understanding of the groundwater quality is important to meet the increasing demand and also for the future planning and development of the water resources. Andrott island is the largest Island in Lakshadweep having an area of 4.90 km2 with a population density of 2312 person/km2 (2011 Census). It lies in the east–west direction, between 10° 48′ and 10° 50′ N latitude and 73° 39′ and 73° 42′ E longitude. It is 293 km (158 nautical miles) away from Kochi (mainland). This paper aims to appraise the spatial distribution of groundwater quality of Andrott Island using geospatial approach. Detailed physico-chemical studies had been carried out to identify potential fresh groundwater resources and quantifying vulnerable parts of Andrott Island. BIS standard has been adopted to assess the quality of ground water at each sampling locations. 50 Samples were collected from water quality lab Andrott Island and GPS has been used to collect the sampling point locations. The statistical analysis has been performed using standard methods, by calculating correlation coefficients between different pairs of parameters. Spatial interpolation technique inverse distance weighted (IDW) has been used to estimate the spatial distribution of the groundwater parameters. The final integrated WQI map shows three priority classes such as good, poor and very poor groundwater quality zones of the study area and provides a guideline for the suitability of groundwater for domestic purposes. The result of the study estimated that 82% of pre Monsoon and 64% of post Monsoon samples fall under poor water category and the rest is categorized under good and very poor as per the WQI classification. The present study is helpful in proper planning and management of available water resources for drinking purposes.

Spatial Analysis of Coastline Change by Remote Sensing in the North Coast of Karawang Regency

<p><em>The existence of the coast in the northern part of Karawang Regency is very worrying. Seawater<strong> </strong>that was far up to tens of meters from the side of the road, is now on the lip of the road, even some parts of the road are cut off due to abrasion of seawater. Some villages were affected by abrasion erosion. One of the effects of damage due to abrasion and sedimentation is the occurrence of shoreline changes. This change in coastline will affect people's lives and spatial planning for the development of the area. For this reason, this study aims to determine the extent and rate of shoreline changes that occurred on the coast of Karawang Regency in the periods of 1989, 1995, 2001, 2005, 2009, 2016, and 2018. The shoreline data was obtained from the extraction of Landsat 3 MSS, Landsat 5 TM, Landsat 7 ETM +, and Landsat 8 </em><em>OLI</em>-<em>TIRS after the NDWI process was previously carried out. While the rate of change is calculated at 6 sample point locations scattered along the northern coast of Karawang Regency. The results showed that the largest area damaged by abrasion occurred in Sedari Village covering an area of 166.802 hectares, and the area formed by the largest sedimentation occurred in Muara Cilamaya Village at 276,318 hectares. Meanwhile, the fastest rate of shoreline change due to abrasion occurred in Sukajaya Village at 10 meters </em>/<em>year, while the slowest in Sedari Village at 3.77 meters / year. The fastest sedimentation process in Muara Cimalaya Village is 4.5 meters / year, while the late one in Tanjung Pakis Village is 3.09 meters / year.</em><em></em></p><p><strong><em>Keywords: </em></strong><em>Abra</em><em>sion, Accretion, Coastline Changes, Karawang</em><em></em></p>

Reducing Statistical Uncertainty in Elastic Settlement Analysis of Shallow Foundations Relying on Targeted Field Investigation: A Random Field Approach

The present paper deals with the practical problem of reducing statistical uncertainty in elastic settlement analysis of shallow foundations by relying on targeted field investigation with the aim of an optimal design. In a targeted field investigation, the optimal number and location of sampling points are known a priori. As samples are taken from the material field (i.e., the ground), which simultaneously is a stress field (stresses caused by the footing), the coexistence of these two fields allows for some points in the ground to better characterize the serviceability state of structure. These points are identified herein through an extensive parametric analysis of the factors controlling the magnitude of settlement; the number of different cases considered was 3318. This is done in an advanced probabilistic framework using the Random Finite Element Method (RFEM) properly considering sampling of soil property values. In this respect, the open source RSETL2D program, which combines elastic finite element analysis with the theory of random fields, has been modified as to include the function of sampling of soil property values from the generated random fields and return the failure probability of footing against excessive settlement. Two sampling strategies are examined: (a) sampling from a single point and (b) sampling a domain (the latter refers to e.g., continuous cone penetration test data). As is shown in this work, by adopting the proper sampling strategy (defined by the number and location of sampling points), the statistical error can be significantly reduced. The error is quantified by the difference in the probability of failure comparing different sampling scenarios. Finally, from the present analysis, it is inferred that the benefit from a targeted field investigation is much greater as compared to the benefit from the use of characteristic values in a limit state design framework.

The Impact of Palm Oil Mill Wastewater on the Soil Properties of Paddy Fields

A paddy field is a wetland area which always muddy and constantly flooded by irrigation. This land possesses impermeable layers, hence the irrigation water quality ought to be maintained, to prevent changes in its properties, as well as the paddy field features. Furthermore, wetland pollution by the palm oil mill wastewater PT BSS was experienced in June 2018, characterized by a lowered quality of water in the fields of Manggopoh Village, Agam District, West Sumatra. The purpose of this study, therefore, is to determine the effect of PT BSS palm oil mill wastewater on the quality of paddy fields, using a survey method to obtain samples through random sampling techniques. This research was conducted downstream, based on the direction of flow along the irrigation channel as well as on the uncontaminated fields upstream. Furthermore, a ring and ground drill was used in the collection process, and analysis for physical and chemical properties was conducted in the Soil laboratory of the faculty of Agriculture, Andalas University. Subsequently, the evaluation involved averaging the soil data, followed by a comparison with the criterion level of damage, and ANOVA was used to estimate the difference between sample point locations, at a significance level of 0.05%. The results obtained indicate the absence of any changes in soil properties, in contrast with the water characteristics that can cause damage because the paddy soil is in a saturated state. Thus, wastewater is unable to permeate the soil matrix. Hence, it does not change the properties, since the values obtained passed the threshold criteria for soil.

An assessment of how distance and diesel oxidation catalyst will impact thermal decomposition behaviors of particles

Decomposition mass loss and pyrolysis products analyses of particles sampled at various locations along the tailpipe of a Euro-IV diesel engine were performed using a thermogravimetry in conjunction with Fourier transformation infrared spectrometry-mass spectrum. Diesel particles were collected at the same location with and without diesel oxidation catalyst (DOC) mounted on the test engine separately. The three poles in thermal gravity-differential thermal gravity images suggested that the decomposition process of diesel particles could be divided into three stages which correspond to the decompositions of lower boiling substances, higher boiling substances and soot respectively. It is noticed that no matter whether DOC was mounted or not, the further the particles were sampled away from the engine block, the lower the peak temperatures and the heavier the mass losses within the first two stages, which indicated that the soluble organic fraction in the particle samples increased and therefore lowering the activation energy of thermal decomposition. Hydroxyl, ammonia, CxHy fragments, benzene, toluene, and phenol were found to be the primary products of particle decomposition, which didn't change with the location of particle sample point. The employment of DOC increased the activation energy for particle oxidation and resulted in a higher peak temperature and lower mass loss within the first-stage. Moreover, the CO stretching bands of aldehyde and ketone at 1771 cm−1 was only detected without a DOC, while the NO2 peak at 1634 cm−1 was solely noticed with the presence of DOC. Compared to the first-stage pyrolysis products, more polycyclic aromatic hydrocarbons and less CxHy fragments were seen in the second-stage.

Mineralogical Characteristics and Physico-Chemical Properties of a Newly Reclaimed Tidal Flat of Haenam Bay in the Southwestern Coast of Korea

The aim of this investigation was to identify the soil physical and chemical properties and the mineralogies of recently reclaimed tidal flat land (RTFL) consisted of five different soil series within the investigation site located in Youngsan-river Bay of Southwestern coast in Korea, that has to be only used as upland according to the policy of designated absolute agricultural land. The results show that the soil textures of the soil horizons are sandy loam and silt loam for all five soil series, with typical soil colors of yellow to pale yellow for Ap horizons containing higher clay content greater (> 18%) and greenish gray containing higher sand content (> 60%). The pHs of surface horizons for Bokchun (BC), Junbook (JB) and Poseung (PS) soil series are not only acidic (< 4.5) but also soil color is dark brown with reddish brown mottles. The X-ray diffraction (XRD) analyses represent the major minerals are illite, kaolinite and quartz for BC, JB and PS soil series while quartz and illite are major minerals for Taehan (TH) and Gwangpo (GP) soil series. Silicon and aluminum dominant in the Ap and Bg horizons are significantly higher in the soil series of BC, JB and PS than those in TH and GP. Also, we found that the kaolinite particles of varying sizes are arranged in face-to-face patterns along with the presence of spherical particles of quartz, especially in BC, JB and PS. Index map and Locations of soil profile investigation pits and soil sampling points for five soil series within the experimental site at the RTFS within the Haenam Bay. Numerous dendritic streams on the wide tidal flat and main tidal channel (maximum depth of 25 m) comprise the coastal embayment.

Pre-Post Monsoon Assessment of Ground Water of Ghot Village in Gadchiroli District

there basic need of human being that is food, shelter and Cloth. So as In food water is very important after air, around 72% of earth surface is covered with water but among them only few percentage of source are available for drinking and other domestic purposed. Sub-Surface water is one of the most priceless naturally occurring things which balance human health and development of ecology. In this research find out safe drinking water source in Ghot village of Gadchiroli district. Also find determine chipset filtration process required other drinking water sources so that people from Ghot village are easily use this water for drinking and domestic purposed. With the help of sample analysis from different location of Ghot village are tested in laboratory and check with BIS and WHO standards. Water quality guidelines provide a threshold value for each parameter for drinking water. It is necessary that the quality of drinking water should be checked at regular time intervals, because due to the use of contaminated drinking water, the human population suffers from various water borne diseases. There are some parameters of drinking water quality parameters like World Health Organization (WHO) and Indian Standard IS 12500: 2012. The objectives of this study are to analyses the underground water quality of Ghot Village of Gadchiroli region by water quality index. In this research 11 sample point location were selected on five parameter which are essential for check for quality. Physico-chemical parameters such as PH, Turbidity, Total Hardness, Fluoride and Total Dissolved Solids collected different place like boar well, pond, River etc. In this study find out the range of water quality index so that treatment on water can be perform properly on respective drinking water source

AFM Modes for in-Situ Hyperspectral Mapping of Nanomechanics, Conductivity, and Local Electrochemical Activity

The local differences in structural, mechanical, electrical, and/or electrochemical properties all together account for the reactivity heterogeneity of materials on the nanoscale. This requires approaches capable of simultaneously capturing correlated multidimensional information at this level. Additionally, in situ, in vivo, non-invasive methodologies are also highly desired. Atomic force microscopy (AFM) is a well-adopted method with its capability of measuring surface topography, mechanics, electricity, chemistry, optical properties, and electrochemistry in different environments. Traditional AFM modes operate in either ‘imaging’ or ‘spectroscopic’ modes, in situ or ex situ. The traditional imaging modes performed at discrete operation conditions captured only snap-shot-wise information in an inefficient way. In conventional spectroscopic mode, however, only a single or few sample point locations are selected. Our DataCube modes combine the ‘imaging’ and ‘spectroscopic’ modes into a single approach providing a spectrum of a property or multiple properties in every pixel of the image. This new approach probing in situ, in operando, continuous, complete, and structured information about the system performance when critical properties are varying by control. We have recently also developed batch-fabricated, high-quality and robust nanoelectrode probes. These probes have the exposed Pt-coated tip apex of ~200 nm height and the end tip radius of ~25 nm. Modes enabled by these probes include include PeakForce scanning electrochemical microscopy (SECM) for the simultaneous acquisition of local EC, conductivity and nanomechanical information. This has also been extended to DataCube SECM, which provides highly-dimensional, big-data results allowing us to perform in-depth data mining for improved electrochemical kinetic quantification, 3-D nano-EC and nanomechanical characterization. In addition, many applications require performing nanoelectrical studies in electrolyte solutions, e.g. battery, bioelectricity, and bioelectromechanics. However, these are technically challenging. The general implementation requires avoiding electrical shorting, liquid spilling and chemical corrosion. Minimal parasitic electrochemistry and stray capacitance are also needed. With the use of these nanoelectrode AFM tips, we have developed a suite of solutions to conduct multi-dimensional nanoelectrical measurements in liquid, where the DataCube method has been also integrated with these implementations. This work introduces our recent developments with a variety of applications examples in different research areas. All these cases demonstrate the versatile capabilities of these solutions for today’s highly-multidisciplinary research. Figure 1. Left: SEM images of the probe. Middle: PeakForce SECM images of a mesh pattern with 1 µm wide platinum strands separated by 2 µm x 2 µm square silicon nitride islands. Right: DataCube conductive AFM mode in aqueous solution. Reference: [1] Cui et al., Nanotechnology, 2019, 30, 235701 Nellist et al., Nanotechnology, 2017, 28, 095711. [2] Jiang et al., ChemSusChem 2017, 10, 4657 Figure 1

Design and Implementation of Yunnan Province Soil Environmental Quality Database Based on ArcSDE for Oracle

The environmental quality monitoring work in Yunnan Province began in the 1970s. After 40 years of development, the Yunnan Province Environmental Monitoring System was initially established. However, the soil environmental monitoring data of the province lacks a unified warehousing standard, and a spatial database of soil environmental quality has not been established to integrate and standardize the data. Based on the research and reference to the relevant standards of soil database construction method and management at home and abroad, GeoDatabase is used as the spatial data model, and the conceptual model, logical organization model and storage model of Yunnan Province soil environmental quality database are designed by using Oracle and ArcSDE technologies. In order to accurately reflect the spatial location of the soil sampling points and the characteristic properties of the samples, and to ensure the uniqueness and rationality of the primary key in the data table, this paper designs the coding of the soil environmental quality database. The construction of soil environmental quality database in Yunnan Province realized the seamless integration of spatial data and attribute data, and provided comprehensive and accurate basic data and scientific decision support for soil pollution prevention and soil ecological restoration in Yunnan Province.

Analysis of Sample Correlations for Monte Carlo Rendering

AbstractModern physically based rendering techniques critically depend on approximating integrals of high dimensional functions representing radiant light energy. Monte Carlo based integrators are the choice for complex scenes and effects. These integrators work by sampling the integrand at sample point locations. The distribution of these sample points determines convergence rates and noise in the final renderings. The characteristics of such distributions can be uniquely represented in terms of correlations of sampling point locations. Hence, it is essential to study these correlations to understand and adapt sample distributions for low error in integral approximation. In this work, we aim at providing a comprehensive and accessible overview of the techniques developed over the last decades to analyze such correlations, relate them to error in integrators, and understand when and how to use existing sampling algorithms for effective rendering workflows.

Tree radial growth-climate relationship in Changbai Mountain, Northeast China.

Changbai Mountain is one of the hotspots for tree ring research in Northeast China, with a large number of related research results having been published. To clarify the advance of tree ring research in Changbai Mountain and understand the responses of tree radial growth to climate factors, we reviewed the related literature and analyzed the differences among them based on tree species identity, elevation, and detrended methods. The radial growth of trees in Changbai Mountain was generally affected by temperature and precipitation, with greater influence of temperature. The relationship between tree radial growth and climate variables varied across both species and altitudes. Most studies reported that the radial growth of conifers were mainly affected by temperature in early growing season (April-May) and growing season precipitation (June-August). The radial growth of broadleaved trees were mainly affected by the temperature in previous and current growing season, the precipitation in dormancy season (November-March), and the precipitation in the current growing season. The previous September precipitation had significant effects on the radial growth of conifers and broadleaved trees. However, many studies had reported different or even opposite results. Most of the differences in the results of the studies appeared at low and medium altitudes, indicating that the altitudinal location of sampling points had impacts on the results. In addition, the detrended method was also the main cause for the variation of results across different studies. Comparatively, the linear or negative exponential detrended method might increase the effective significance of precipitation, especially the effect of precipitation on tree growth during dormancy period, and also strengthen the effective significance of the temperature at the end of the growing season. This study showed the habitat and the detrended method used in chronology were the main reasons for the difference of results among the studies. Therefore, for tree ring research in Changbai Mountain, the number of sampling sites should be increased and the detrended method should be carefully selected.

A novel approach for selecting sampling points locations to river water quality monitoring in data-scarce regions

In order to rationalize a surface water quality monitoring network (WQMN), it is critical to appropriately design surface water quality sampling locations. This is due to high installation, operational, and maintenance costs for each sampling representative of the whole water system conditions. The main objective of this study was to propose an integrated method to determine the most appropriate sampling points in the Khoy watershed northwest of Iran, where financial resources and water quality data are limited. Multi criteria evaluation method including analytic network process (ANP) and Fuzzy logic were incorporated in River Mixing Length (RML) procedure in order to identify exact locations of sampling points. Based on RML procedure, 15 candidate sampling points were identified to suitably select sampling points based on budget deficiency. Relative weights for 12 criteria and 10 sub-criteria related to non-point sources and surficial rocks as well as criteria of topography were then calculated by the ANP method. According to the obtained results, a new total potential pollution score (TPPS) was presented to prioritize 15 candidate sampling points. Then, the values of TPPS were classified and fuzzified to distinguish real differences between scores. Based on current monitoring stations and budget deficiency, the hierarchy value, and Fuzzy rank, six points are proposed as the most appropriate locations for surface water quality monitoring. Furthermore, four points are identified as the second most appropriate for enhancing a robust WQMN in the study area in order for an expansion plan in the future. The results of this study should be valuable for water quality monitoring agencies looking for an efficient approach for selecting exact sampling locations.

An adaptive sampling methodology for measuring blades with CMM based on dominant feature points

Sampling strategy is one of the most critical components of the contact probing process with coordinate measuring machines (CMMs). The number and location of sampling points have direct impacts on the efficiency and reliability of the measurements. Blades of aviation engines have complex geometry and extremely high precision requirements, but the sampling strategy of blades is still a difficult problem which limits the use of CMMs in blade inspection. To balance the measuring efficiency and accuracy of CMM, an adaptive sampling algorithm based on dominant feature points is proposed. In this algorithm, the points are adaptively sampled through a modified B-spline least-square fitting process with dominant feature points and new dominant points if necessary, and the new dominant points are computed by a new method, namely weighted curvature mass moment method. The sections of the blade to be measured are determined with this adaptive sampling algorithm to be the leading and trailing edge curves, and the points on each section to be measured are determined using dominant feature points of the blade profile. The definition and extraction methods for dominant feature points of the blade profile are also researched. By comparing the reconstruction errors of sampling points for several different blades, this adaptive sampling algorithm is proved to be more efficient and accurate than the equal parameter sampling method, equal arc length sampling method, and chord deviation sampling method.

Load identification for viscoplastic materials with some unknown material parameters

To inversely identify the loads applied on structure, sufficient information about the material properties is usually required. In this paper, an innovative and robust inverse approach is proposed for the load identification of a viscoplastic material with some unknown viscoplastic constants, where both of the unknown constants and the applied load are simultaneously identified using two nested inverse algorithms. In this work, the well-known damped Gauss–Newton method is used for the load identification and the Marquardt–Levenberg method for identifying the unknown material parameters. Suitable regularization techniques are also used to obtain more smooth solutions. The Perzyna model is used for description of the viscoplastic behavior. A meshfree method is used for the direct and sensitivity analysis of the viscoplastic problem. In order to show the effectiveness of the proposed method, two different examples are presented. Also, influences of the effective parameters, such as the number and location of sampling points, on the results are investigated too.

Adaptation of segmented elbow on the flow meter by using CFD tools

This paper presents the possibility of non-invasive adaptation of the existing pipeline infrastructure in front of the condenser to the measurement of cooling water flow rate. In the analyzed variant, for the measurement of water flow rate in the cooling system, local pressure difference in the segmented elbow was applied. CFD (ANSYS CFX) was used as a tool for diagnosing flow structure, including the location of sampling points of pressure in the elbow. Many variants of flow were modelled (“What if?” analysis type) in this paper. These variants were used to determine the correlation between the differential pressure in the elbow and the flow rate. In addition, the article identifies the advantages and disadvantages of the solutions of this type against a background of standard elements and measuring distances and discusses the basic procedures for preparing and conducting CFD numerical experiment.