Sampling Density Increases Research Articles

Novel preparation method and fire performance study of EPS composites based on calcium sulphate hemihydrate

A novel approach was used to prepare a new expanded polystyrene (EPS) composite based on calcium sulphate hemihydrate that significantly improves its fire performance. Negative pressure was applied to open cavities between the EPS beads and promoted the absorption of flame retardant slurry. Three fire retardant EPS (FR-EPS) composites with different densities were obtained. Although, a large number of inorganic additives were added, causing the increase in thermal conductivity to 0.043–0.045 W/(m∙K) and water absorption to 4.7–5.8%, the properties remained within an acceptable range. The results of limiting oxygen index (LOI), UL-94 vertical burning and Cone Calorimeter tests revealed that the FR-EPS1 increased LOI from 18.1% to 35.8%, achieved UL94 V-0 grade, decreased PHRR from 384.12 to 81.39 kW/m2, and reduced PSPR from 0.159 to 0.014 m2/s. With the continued increase of sample density, the measured LOI was further improved, while heat release and smoke production were better suppressed. TG results, and carbon residue after burning indicate that the endothermic dehydration reaction of calcium sulphate dihydrate and the physical barrier effect of the carbonaceous layer contribute to the extraordinary flame retardancy and smoke suppression of the FR-EPS composites.

Simultaneous perception–action design via invariant finite belief sets

Although perception is an increasingly dominant portion of the overall computational cost for autonomous systems, only a fraction of the information perceived is likely to be relevant to the current task. To alleviate these perception costs, we develop a novel simultaneous perception–action design framework wherein an agent senses only the task-relevant information. This formulation differs from that of a partially observable Markov decision process, since the agent is free to synthesize not only its policy for action selection but also its belief-dependent observation function. The method enables the agent to balance its perception costs with those incurred by operating in its environment. To obtain a computationally tractable solution, we approximate the value function using a novel method of invariant finite belief sets, wherein the agent acts exclusively on a finite subset of the continuous belief space. We solve the approximate problem through value iteration in which a linear program is solved individually for each belief state in the set, in each iteration. Finally, we prove that the value functions, under an assumption on their structure, converge to their continuous state-space values as the sample density increases.

Implicit Surface Reconstruction With a Curl-Free Radial Basis Function Partition of Unity Method

Surface reconstruction from a set of scattered points, or a point cloud, has many applications ranging from computer graphics to remote sensing. We present a new method for this task that produces an implicit surface (zero-level set) approximation for an oriented point cloud using only information about (approximate) normals to the surface. The technique exploits the fundamental result from vector calculus that the normals to an implicit surface are curl-free. By using curl-free radial basis function (RBF) interpolation of the normals, we can extract a potential for the vector field whose zero-level surface approximates the point cloud. We use curl-free RBFs based on polyharmonic splines for this task, since they are free of any shape or support parameters. To make this technique efficient and able to better represent local sharp features, we combine it with a partition of unity method. The result is the curl-free partition of unity (CFPU) method. We show how CFPU can be adapted to enforce exact interpolation of a point cloud and can be regularized to handle noise in both the normals and the point positions. Numerical results are presented that demonstrate how the method converges for a known surface as the sampling density increases, how regularization handles noisy data, and how the method performs on various problems found in the literature.

Analysis of the Thermal Conductivity of a Bio-Based Composite Made of Hemp Shives and a Magnesium Binder

The evolution of bio-based composites in the building industry is strongly linked with the growing demand for sustainable development, which is relevant nowadays. Hemp shives are a large group of organic residues that are obtained in the process of oil extraction as well as straw processing. These residues could be utilized along with a binder as constituents in the manufacture of bio-based building composites. This study is focused on the impact of density and relative humidity on the effective thermal conductivity of hemp shive-based bio-composites with a magnesium binder. For this reason, a series of samples with variable densities was manufactured and subjected to conditioning in a climatic chamber at a constant temperature and different relative humidity settings. As soon as samples were stabilized, the guarded hot plate method was applied to determine their thermal conductivities. Before each measurement, great care was taken during sample preparation to ensure minimum moisture loss during long-lasting measurements. The results showed that an increase in sample density from 200 kg/m3 to 600 kg/m3 corresponded to up to a three-fold higher composite thermal conductivity. In the case of sample conditioning, a change in relative humidity from a very low value to 90% also resulted in almost 60% average higher thermal conductivity.

CORRELATION OF SOIL PHYSICAL ATTRIBUTES WITH FURROWING SHANK STRENGTH AND DEPTH IN A NO-TILL SEEDER

Furrowing shank horizontal strength and working depth can be correlated with soil compaction in a no-till sowing. This study aimed to evaluate the correlation of furrowing shank strength and working depth with soil physical properties at two working speeds (1.58 and 1.87 m s-1) and four compaction levels induced by an agricultural tractor (0P, 1P, 3P, and 5P+Ballast), with four repetitions in an RBD. Thereby, we aimed to verify a potential increase in sampling density of soil compaction data. Horizontal strength at 1.58 m s-1 had Pearson correlations ranging from 0.74 to 0.73 with soil penetration resistance (SPR), and from 0.57 to 0.72 with some soil properties collected by volumetric ring. Working depth also correlated with several parameters ranging from 0.49 to 0.81. The highest correlations were verified for the speed of 1.58 m s-1, at which shanks maintained greater depth. This increased soil contact with the shank, hence sensitivity to compaction. Our findings show that furrowing shank horizontal strength and working depth can be used to monitor soil compaction.

Macro- and mesoscopic experimental study of the effects of water content on moisture migration in coarse-grained fillings under freeze–thaw cycles and loads

Freeze–thaw cycles and loads are key external factors affecting moisture migration features and frost deformation of coarse-grained fillings. The objective of this study was to clarify the moisture migration features and mesoscopic mechanism of coarse-grained fillings with different initial water contents in seasonal frozen regions under short-term freeze–thaw cycles in the spring thawing period. To this end, a series of experiments realized by mesoscopic observation with X-ray computed tomography (CT) were conducted with fluorescein as a tracer. We then investigated the trends in the temperature field, frost depth and water replenishment, final distribution of the water content, moisture migration images, and changes in the CT value of coarse-grained fillings with different initial water contents under freeze–thaw cycles and static/dynamic loads in a system with an open-water supply. The experimental results demonstrated that under the freeze–thaw cycles and loads, the temperature fields of samples with different water contents change regularly with the change in the external temperature, while the loading pattern has a negligible influence. During the entire process, the external moisture migrated upward, and the initial water content affected the migration process. Typically, the external water replenishment and migration height of the liquid water were inversely proportional to the initial water content, while the final overall water content was higher than the initial value. Under freeze–thaw cycles and dynamic loads, thaw settlement compression deformations were observed during thawing. CT scanning revealed that the pore filling induced by moisture migration leads to grain dislocations after multiple freeze–thaw cycles. Specifically, moisture concentrates in unfrozen areas, the sample density increases, and damage increments are typically negative, which reduces the porosity, thus resulting in thaw settlement compression deformations during thawing.

Evaluating the synergy of three soil spectrometers for improving the prediction and mapping of soil properties in a high anthropic management area: A case of study from Southeast Brazil

Precision agriculture aspires to manage the soil spatial variability within a field. However, agricultural practices can decrease the spatial autocorrelation of soil properties at a short distance, which requires an increase in sampling density to improve the reliability of interpolated surfaces. Data fusion of several soil spectrometers is a promising alternative that can increase knowledge about soil physicochemical variability. Therefore, this research aimed to evaluate whether the synergy of portable X-ray fluorescence, Vis-NIR, and Mid-Infrared spectrometers can successfully increase sampling density and improve the quality of the soil attribute maps, in a high fertilization management study area. We conducted a case study on a sugarcane field in Southeast Brazil. Our spectral data fusion approach did not increase the prediction performance for soil properties, achieving the same accuracy (α ≤ 5%) of the single spectral ranges (Vis-NIR or MIR or pXRF) individually. Thus, Vis-NIR was chosen to evaluate if spectroscopy could improve soil properties prediction and mapping. We used three dataset scenarios to build soil property maps: two were based on soil wet-chemical laboratory analysis using 1 sample per ha, and 1 sample per 0.25 ha and a third used a spectroscopy model with 0.25 samples per ha calibrated using soil wet-chemical laboratory analysis at the rate of 1 sample per ha. In a field with strong anthropic influences, due to liming and soil fertilization, Vis-NIR spectroscopy cannot predict well the amount of phosphorus and pH at a sampling density of 1 sample per 0.25 ha. Increased soil sampling enhances soil mapping accuracy only for chemical properties (e.g., potassium) that are correlated with soil texture. Nevertheless, soil spectra can classify areas of similar soil texture and help farmers with the site-specific management of crops.

Soil salinity mapping using Landsat 8 OLI data and regression modeling in the Great Hungarian Plain

Salt's deposition in the subsoil is known as salinization. It is caused by natural processes such as mineral weathering or human-made activities such as irrigation with saline water. This environmental issue has grown more critical and is frequently occurring in the Hungarian Great Plain, adversely influencing agricultural productivity. This study aims to predict soil salinity in the Great Hungarian Plain, located in the east of Hungary, using Landsat 8 OLI data combined with four state-of-the-art regression models, i.e., Multiple Linear Regression, Partial Least Squares Regression, Ridge Regression, and Feedforward Artificial Neural Network. For this purpose, seventy-six soil samples were collected during a field survey conducted by the Research Institute for Soil Sciences and Agricultural Chemistry between the 15 of September and the 15 of October, 2016. We used the min–max accuracy, the root-mean-square error (RMSE), and the mean squared error (MSE) to evaluate and compare the four models' performance. The results showed that the ridge regression model performed the best in terms of prediction (MSEtraining = 0.006, MSEtest = 0.0007, RMSE = 0.081), with a min–max accuracy equal to 0.75. Hence, the application of regression modeling on spectral indices, principal component analysis, and land surface temperature derived from multispectral data is an efficient method for soil salinity assessment at local scales. The resulting map can provide an overview of salinity levels and evaluate the efficiency of land management strategies in irrigated areas. An increase in sampling density will be recommended to validate this approach on the regional scale.

Discrete curvature and torsion from cross-ratios

Motivated by a Möbius invariant subdivision scheme for polygons, we study a curvature notion for discrete curves where the cross-ratio plays an important role in all our key definitions. Using a particular Möbius invariant point-insertion-rule, comparable to the classical four-point-scheme, we construct circles along discrete curves. Asymptotic analysis shows that these circles defined on a sampled curve converge to the smooth curvature circles as the sampling density increases. We express our discrete torsion for space curves, which is not a Möbius invariant notion, using the cross-ratio and show its asymptotic behavior in analogy to the curvature.

The genesis of solid bitumen and its effect on reservoir physical properties

ABSTRACT Solid bitumen has been found widely in the reservoir of Mahu sag. The geochemical characteristics and genesis of solid bitumen are not well understood. At the same time, the presence of bitumen can block the pore space and affect the physical properties of the reservoir, which seriously restricts the exploration and development of the reservoir in this area. Based on the analysis of bitumen geochemical characteristics and the comparison of reservoir physical properties before and after bitumen dissolution, this paper systematically studied the genesis of the reservoir bitumen and its effect on the reservoir physical properties. The results are as follows. (1) After the oil reservoirs generated in early stage of hydrocarbon expansion of source rocks of the Fengcheng Formation were subjected to biodegradation, they were then subjected to thermal alteration and deformation into bitumen after normal crude oil filling in the later period. (2) Bitumen is black under the microscope, mainly distributed in various cracks such as micro cracks and dissolved pores. (3) After the solid bitumen was dissolved, the average increase of sample density, porosity and permeability is 0.03 g/cm3, 4.12% and 14.48mD, respectively, and the solid bitumen content was positively correlated with the change in porosity, permeability, and density. The relationships are as follows: Y1 = 0.702x+2.3796; Y2 = 6.113x-0.6423; Y3 = 0.0115x-0.0003. The research has important guiding role for the exploration and development of reservoirs in Mahu sag and similar areas.

Influence of the sampling density on the noise level in displacement and strain maps obtained by processing periodic patterns

The aim of this study is to investigate the influence of the sampling density of periodic patterns such as checkerboards or 2D grids on the noise level observed in displacement and strain maps extracted from such images. A spectral method named Localized Spectrum Analysis (LSA) is used to process the images. It is shown that this parameter influences this noise level. This influence is quantified, and a power law is proposed to model it, with a value of the power identified with the measurements. It is also confirmed that checkerboards give a lower noise level than 2D grids, with an improvement which is also quantified, and which increases as the sampling density increases.

Laser Initiation of PETN with Inclusions of Aluminum Nanoparticles under Static Pressure

This paper describes the experimental measurement of thresholds of explosive decomposition of PETN with inclusions of aluminum nanoparticles (an average particle diameter of 100 nm) with a static pressure of 0–0.288 GPa applied to the samples under the action of the first harmonic of a pulsed (14 ns) neodymium laser. Amplitudes of optoacoustic signals as a function of concentration of inclusions in the samples with a fixed density of laser initiation energy are measured. There is a significant decrease in the initiation threshold, which is due to the fact that a gas-dynamic unload is blocked and the sample density increases.

Robust soil mapping at the farm scale with vis–NIR spectroscopy

SummarySustainable agriculture practices are often hampered by the prohibitive costs associated with the generation of fine‐resolution soil maps. Recently, several papers have been published highlighting how visible and near infrared (vis–NIR) reflectance spectroscopy may offer an alternative to address this problem by increasing the density of soil sampling and by reducing the number of conventional laboratory analyses needed. However, for farm‐scale soil mapping, previous studies rarely focused on sample optimization for the calibration of vis–NIR models or on robust modelling of the spatial variation of soil properties predicted by vis–NIR spectroscopy. In the present study, we used soil vis–NIR spectroscopy models optimized in terms of both number of calibration samples and accuracy for high‐resolution robust farm‐scale soil mapping and addressed some of the most common pitfalls identified in previous research. We collected 910 samples from 458 locations at two depths (A, 0–0.20 m; B, 0.80–1.0 m) in the state of São Paulo, Brazil. All soil samples were analysed by conventional methods and scanned in the vis–NIR spectral range. With the vis–NIR spectra only, we inferred statistically the optimal set size and the best samples with which to calibrate vis–NIR models. The calibrated vis–NIR models were validated and used to predict soil properties for the rest of the samples. The prediction error of the spectroscopic model was propagated through the spatial analysis, in which robust block kriging was used to predict particle‐size fractions and exchangeable calcium content for each depth. The results indicated that statistical selection of the calibration samples based on vis–NIR spectra considerably decreased the need for conventional chemical analysis for a given level of mapping accuracy. The methods tested in this research were developed and implemented using open‐source software. All codes and data are provided for reproducible research purposes.HighlightsVis–NIR spectroscopy enables an increase in sampling density with little additional cost.Guided selection of vis–NIR calibration samples reduced the need for conventional soil analysis.Error of spectroscopic model prediction was propagated by spatial analysis.Maps from the vis–NIR augmented dataset were almost as accurate as those from conventional soil analysis.

ALBATROS: adaptive line-based sampling trajectories for sequential measurements

Measurements in 2D or 3D spaces are ubiquitous among many fields of science and engineering. Often, data samples are gathered via autonomous robots or drones. The path through the measurement space and the location of the samples is traditionally determined upfront using a one-shot design of experiments. However, in certain cases, a sequential approach is preferred. For example, when dealing with a limited sampling budget or when a quick low-resolution overview is desired followed by a steady uniform increase in sampling density, instead of a slow high-resolution one-shot sampling. State-of-the-art sequential design of experiment methods are point-based and are often used to set up experiments both in virtual (simulation) as well as real-world (measurement) environments. In contrast to virtual experimentation, physical measurements require movement of a sensor probe through the measurement space. In these cases, the algorithm not only needs to optimize the sample locations and order but also the path to be traversed by sampling points along measurement lines. In this work, a sequential line-based sampling method is proposed which aims to gradually increase the sampling density across the entire measurement space while minimizing the overall path length. The algorithm is illustrated on a 2D and 3D unit space as well as a complex 3D space and the effectiveness is validated on an engineering measurement use-case. A computer code implementation of the algorithm is provided as an open-source toolbox.

How does sampling density affect mineralization detection in stream sediment geochemical exploration? A case study from NW of Iran

Sampling density is an important parameter in different stages of exploration programs such as stream sediment-based geochemical exploration. Some researchers have suggested the effects of different sampling densities in regional exploration. However, a few researchers have addressed the effect of stream sediment sampling density on anomaly delineation. This research aims at investigating the effect of sampling density in delineating ore-related geochemical signals in stream sediment exploration through sensitivity analysis. A dataset from northwestern Iran with known copper occurrences was employed, and the available data was systematically resampled into different proportions to simulate different sampling densities and analyzed using the true sample catchment basin approach. The results showed a positive correlation between the number of outlining known deposits and sampling density, implying that a higher sampling density increases the chance of outlining new potential zones. Moreover, when sampling density increases, the total size of the delimited anomalous area decreases. The estimated background values ( M j ) for upstream lithologic units varies heavily with sampling density. This is critical as separating anomalous basins depends on M j . M j variation has been more emphasized for lithologies with high estimated background content, displaying heteroscedastic behavior.

Formation of Ti5Si3 and V5Si3 by self-propagating high-temperature synthesis and evaluation of combustion wave kinetics

Fabrication of Ti5Si3 and V5Si3 was conducted by self-propagating high-temperature synthesis (SHS) from the elemental powder compacts of their stoichiometries. Combustion wave kinetics was experimentally studied by measuring the combustion front velocity and temperature, and numerically investigated to determine the Arrhenius factor of the rate function (K0) and to evaluate the effective thermal conductivity (keff). Experimental results showed that the 5Ti + 3Si reaction is more exothermic than the 5V + 3Si reaction. With the increase of sample density from 50% to 60% TMD, the flame-front velocity increased from 28 to 50 mm/s for the formation of Ti5Si3 and from 6.9 to 8.5 mm/s for V5Si3. Based upon numerical simulation and experimental validation, K0 = 3 × 109 s−1 and 5 × 107 s−1 were deduced for combustion synthesis of Ti5Si3 and V5Si3, respectively. The ratio of keff/kbulk increasing from 0.02 to 0.05 was employed in the numerical calculations to simulate the effect of sample compaction density on combustion wave kinetics. Moreover, the measured and calculated combustion front temperatures were comparable, which confirmed the reaction exothermicity of the numerical model.

Formation of Ti5Si3 by Combustion Synthesis in a Self-Propagating Mode: Experimental Study and Numerical Simulation

AbstractTitanium silicide (Ti5Si3) was fabricated by self-propagating high-temperature synthesis (SHS) from the elemental powder compact. With the increase of sample density from 50 to 60% TMD, experiments showed that the flame-front velocity increased from 28 to 50 mm/s and combustion temperature from 1,580 to 1,700°C. Based on their dependence, the activation energy of the synthesis reaction, Ea=193 kJ/mol, was deduced. By numerical simulation of combustion wave kinetics, the Arrhenius factor of the rate function, K0=3×109 s−1, was determined for the 5Ti + 3Si reaction system. The effect of sample compaction density on the SHS process was correlated to the variation of the effective thermal conductivity (keff) of the powder compact. The ratio of keff/kbulk=0.02–0.05 was numerically obtained for the 5Ti + 3Si samples with 50–60% TMD and well validated by the experimental data.

The influence of ZrB2-SiC powders mechanical treatment on the structure of sintered ceramic composites

The effect of mechanical treatment by planetary ball milling on the properties of hot pressed ZrB2 - SiC ceramics was studied. It was shown that material densification after mechanical treatment is finished at initial stages of sintering process. Addition of SiC leads to an essential increase of sample density to 99% of theoretically achievable for powder with 2% of SiC, as compared with ZrB2 with the density less than 76%. It was demonstrated that all defects that were accumulated during mechanical treatment are annealed during hot pressing, and there are no changes of CDD values in sintered ceramics.

Effects of Mg addition and sintering temperatures on chemical compositions, microstructures, densities and dielectric properties of strontium titanate

Increasing demands in dielectric capacitors for electronic applications require continuous improvement of dielectric materials in terms of enhanced dielectric constant and minimal dielectric loss. This study aimed at synthesizing strontium titanate powders doped with 10, 20, and 30at% of Mg, and examining relationships among additive concentrations, chemical compositions, sintering temperatures, microstructures, and dielectric properties of strontium titanate. Experimental findings indicated that increasing doping concentrations resulted in increased secondary phase content, MgO, which seemed to have consequently led to grain size reduction. However, MgO concentrations were found to be lower than 10wt%, which possibly have not significantly changed the sample׳s dielectric properties. The results also revealed that a higher sintering temperature has led to an increase in sample density as well as to an enhancement in dielectric constant. It was further observed that strontium titanate samples doped with 30at% Mg and sintered at 1330°C gave the highest dielectric constant value, which was ten times higher than the samples with 10at% Mg sintered at 1250°C, the sample with the lowest dielectric constant. All samples in the study though yielded dielectric losses of less than 3%, which are within the acceptable range for practical applications.

Preparation and quality evaluation of a simulating 90Sr ceramic source

In the present research, a novel approach to prepare 90Sr ceramic source is proposed. The radioactive 90Sr(NO3)2 reacts with its stable decay daughter ZrO2 during sintering to form 90SrZrO3. This method aims to offer a reliable 90Sr source with chemical and thermal stability, meanwhile, the preparation procedure itself is simple and radiologically safe. The effects of Y3+ addition on the microstructure, density and phase stability of simulating ceramic sources are evaluated. With the existence of more Y3+ addition, grain size decreases and becomes more uniform, sample density increases, and the excessive ZrO2 in the source is stabilized in its tetragonal phase. Quality evaluation reveals that the strontium is uniformly distributed on the substrate and most strontium remains stable during immersion test, vibration test and drop test; meanwhile, the Y3+ doped simulating ceramic source layer remains integral during irradiation. Overall, this research proposes a novel and promising approach to prepare 90Sr source.