Entire Work Area Research Articles

Deep-learning-based natural fracture identification method through seismic multi-attribute data: a case study from the Bozi-Dabei area of the Kuqa Basin, China

Fractures play a crucial role in tight sandstone gas reservoirs with low permeability and low effective porosity. If open, they not only significantly increase the permeability of the reservoir but also serve as channels connecting the storage space. Among numerous fracture identification methods, seismic data provide unique advantages for fracture identification owing to the provision of three-dimensional information between wells. How to accurately identify the development of fractures in geological bodies between wells using seismic data is a major challenge. In this study, a tight sandstone gas reservoir in the Kuqa Basin (China) was used as an example for identifying reservoir fractures using deep-learning-based method. First, a feasibility analysis is necessary. Intersection analysis between the fracture density and seismic attributes (the characteristics of frequency, amplitude, phase, and other aspects of seismic signals) indicates that there is a correlation between the two when the fracture density exceeds a certain degree. The development of fractures is closely related to the lithology and structure, indirectly affecting differences in seismic attributes. This indicates that the use of seismic attributes for fracture identification is feasible and reasonable. Subsequently, the effective fracture density data obtained from imaging logging were used as label data, and the optimized seismic attribute near the well data were used as feature data to construct a fracture identification sample dataset. Based on a feed-forward neural network algorithm combined with natural fracture density and effectiveness control factor constraints, a trained identification model was obtained. The identification model was applied to seismic multi-attribute data for the entire work area. Finally, the accuracy of the results from the training, testing, and validation datasets were used to determine the effectiveness of the method. The relationship between the fracture identification results and the location of the fractures in the target reservoir was used to determine the reasonableness of the results. The results indicate that there is a certain relationship between multiple seismic attributes and fracture development, which can be established using deep learning models. Furthermore, the deep-learning-based seismic data fracture identification method can effectively identify fractures in the three-dimensional space of reservoirs.

Compaction quality assessment of highway using roller-integrated positive maximum kinetic energy increment detection technique

During conventional highway construction, quality control and acceptance (QC/QA) are based on limited spot tests of material density at random locations which may not comprehensively represent the entire compacted area and are vulnerable to potential biases. Based on roller-integrated positive maximum kinetic energy increment detection technique with real-time kinematic global positioning systems, this research adopted kinetic energy compaction value (KECV) as a real-time monitoring index for the highway compaction quality, and subsequently proposed an KECV-based assessment method to estimate the compaction quality of subgrade and pavement materials. Additionally, a global interpolation method (Green spline) was adopted to obtain estimates for both KECVs and compaction quality at any location on the work area, enabling the analysis of the passing rate of compaction quality for the entire work area. A case study on the Hengyong highway project in China indicates a highly linear correlation between the KECV and the compaction parameters, the compactness of LLL silt, and the relative density of cement-stabilized macadam; therefore, it can serve as a reliable index for monitoring compaction quality. Assessment of compaction quality on the entire work area can be fast and continuously achieved using the proposed method, which can effectively overcome the above limitation of conventional testing, timely feedback compaction information to avoid quality defects, and availably improve the construction quality of highways.

Vision-based robotic grasping using faster R-CNN–GRCNN dual-layer detection mechanism

Visual grasping technology plays a crucial role in various robotic applications, such as industrial automation, warehousing, and logistics. However, current visual grasping methods face limitations when applied in industrial scenarios. Focusing solely on the workspace where the grasping target is located restricts the camera’s ability to provide additional environmental information. On the other hand, monitoring the entire working area introduces irrelevant data and hinders accurate grasping pose estimation. In this paper, we propose a novel approach that combines a global camera and a depth camera to enable efficient target grasping. Specifically, we introduce a dual-layer detection mechanism based on Faster R-CNN–GRCNN. By enhancing the Faster R-CNN with attention mechanisms, we focus the global camera on the workpiece placement area and detect the target object within that region. When the robot receives the command to grasp the workpiece, the improved Faster R-CNN recognizes the workpiece and guides the robot towards the target location. Subsequently, the depth camera on the robot determines the grasping pose using Generative Residual Convolutional Neural Network and performs the grasping action. We validate the feasibility and effectiveness of our proposed framework through experiments involving collaborative assembly tasks using two robotic arms.

Formation of Extended Tubular Plasma in Argon at Low Pressure and in a Weak Longitudinal Magnetic Field

The results of experimental studies on the formation and subsequent evolution of extended (l = 300 mm) and thin-walled (Δr ≈ 10 mm) tubular (2r ≈ 110 mm) plasma in a weak longitudinal magnetic field (B = 175 G) without the use of a thermionic cathode are presented. The cylindrical chamber in which the tubular plasma was formed was pumped with high purity argon (99.998%) at an average velocity of about 1 m/s at a pressure of P = 10–3–10–2 Torr. Two methods of creating seed electrons initiating the development of ionization avalanches were used. The difference inherent to these methods has been established in the dynamics of breakdown, completing in the formation of a tubular discharge. In the first of them, a pulsed discharge preceding the high voltage supply of the main discharge created gas preionization in a small area around the sectioned cathodes. In the second method, seed electrons were created in the entire working area of the discharge chamber by an RF discharge with a frequency of 85 kHz and duration of about 1 s. High-speed shooting with a 4-frame ICCD camera allowed us to establish the dynamics of tubular discharge formation at all its stages. Measurements of the longitudinal and radial discharge current were carried out. The results we obtained showed the possibility of spatial isolation of an extended tubular plasma from the close located metal wall of the discharge chamber by using a weak longitudinal magnetic field.

Research on thermal error compensation strategy of CNC machine tools based on full working area modeling

Abstract Traditional manufacturing equipment is developing in the direction of precision, intelligence and integration, and the precision requirements of CNC machine tools are getting higher and higher. Compensating and controlling the thermal error of the machine tool is an important part of improving machining accuracy. This paper uses a cuckoo search algorithm to optimize the BP neural network to get the CSBP neural network model and inputs the temperature value of the CNC machine tool into the CSBP model to get the thermal error prediction results. Combined with the thermal error values of each measurement point on the CNC machine table, the B-spline function is used to fit the thermal error prediction model for the entire working area. Finally, the thermal error compensation system of the CNC machine tool has been established. Simulation and empirical studies show that the fitting and prediction accuracy of the model in this paper are better, and the maximum error value of the prediction is reduced by 20.27% compared to the LSTM model. After the application of the thermal compensation system in this paper, the thermal error of the CNC machine tool is greatly reduced, and most of the offset caused by the thermal deformation of the machine tool is eliminated through compensation. In this paper, the design of a thermal error compensation system based on full work area modeling can effectively reduce the thermal error of CNC machine tools, which can be applied to the actual machining process of machine tools to improve the machining accuracy of CNC machine tools.

Features of ion exchange between the electrodes in metal-ion batteries during discharge

The importance and relevance of the storage of electrical energy is confirmed by events in the world and trends in the development and use of various electrical energy systems, household appliances, computer equipment, communication devices, etc. In addition to the growth of the metal-ion battery markets, there are trends towards a search for metals that in the future will be inexpensive and will have characteristics required for storage systems. This paper considers ion exchange between the electrodes of metal-ion batteries whose charge carriers are metal ions, which diffuse in the process of discharge from the negative electrode to the positive one. A mathematical model was developed and tested. The model is based on a system of diffusion transport equations with the Nernst–Planck–Poisson potential equation replaced by an equivalent conductivity potential equation. Quasi-equilibrium regimes are considered. The entire working area consists of a pore electrode space and a neutral separator. The mathematical model employed consists of potential distribution equations and an electrolyte concentration distribution equation supplemented by the dependence of the electrode surface current on the overvoltage and equations that determine the electrode pore structure depending on the masses transferred inside the electrode. The electric potential and diffuse component mass transfer equations are written within the framework of the modern theory of effective electrical conductivity in batteries with account for current exchange between the solid electrodes and the liquid electrolyte. The research results showed the following. A change in the resistance of the separator (a change in porosity) has little effect, if any, on the electrode current densities, but it causes some change in the potentials themselves. A change in the resistance of the electrolyte affects both the electrode potentials and the internal current distribution between the electrodes and the electrolyte.

Structurally Constrained Initial Impedance Modeling for Poststack Seismic Inversion

The establishment of initial subsurface model is a crucial step for seismic inversion. An accurate and reasonable initial model can mitigate the ill-posedness of seismic inversion and improve the quality of inversion result. A common method for building initial model is the well-log data interpolation. However, the traditional well-log interpolation method ignores the structural information of the subsurface, resulting in the constructed initial model lacking geological meaning. We propose a novel structurally constrained modeling method (SCMM) to obtain a geologically reasonable initial impedance model for poststack seismic inversion. Well-log interpolation can be represented as an inverse problem. SCMM constrains the inversion process by using a regularization operator that forces the well-log data to be extended to the entire seismic working area along the subsurface local structural direction. First, we calculate the seismic dip from the poststack seismic profile. Then, we design the structural operator based on the estimated seismic dip information to constrain the interpolation process. Under the framework of inversion, the interpolation objective function can be established by combining the structural operator with the well-log data misfit term, and it can be solved efficiently by the conjugate gradient algorithm. Synthetic and field data tests show that the initial model built by SCMM is more consistent with the geological rules than that built by traditional method, and the poststack impedance inversion using SCMM is better than that using traditional modeling method in terms of convergence property and accuracy of inversion result.

Modelling and mapping forest structure from aerial LiDAR data

A methodology for estimating forest structure and fuel variables from airborne LiDAR data is presented, based on the following steps: (1) data pre-treatment to obtain the digital terrain model and the canopy height model; (2) extraction of features or attributes from the LiDAR data for each sampling plot; (3) generation of prediction models for structure variables at plot level; and (4) its extension for the generation of maps of forest variables in larger areas. The methodology was applied to a study area of 4,100 ha in the municipality of Cuenca, where a LiDAR flight was carried out with a nominal density of 4 points/m2. For the generation of the prediction models, stepwise multiple regression was used, taking as reference measurements made in 110 field plots, obtaining values of R2 greater than 0.9 for total biomass, volume and fraction of canopy cover, and above 0.86 for basal area, stem biomass and root biomass. The generated models were applied to the entire work area for the creation of maps of forest structure variables, and the entire procedure was integrated into a specific software application.

Research of expendable turbojet tubular combustion chamber

This paper presents research related to the tubular combustion chamber of an expendable turbojet. Although annular combustors are dominant at present, tubular combustors are still attractive because they are simpler to produce and require lower amounts of air flow for testing. The objective of this research was to assess the combustor’s primary zone configuration, and four configurations were tested to obtain experimental answers for use in future work. The configuration of the combustion chamber is a simple and classic design in line with its expendable purpose. The test methodology was to perform initial testing of the primary and secondary zones under atmospheric conditions using the four configurations, and then to subsequently complete the combustor using the best configuration. The complete combustor was then tested under both atmospheric conditions and working conditions. The results showed that the stability margin was wide enough to cover the combustor’s entire working area. The measured efficiency and pressure drop were in very good agreement with the corresponding designed values. The design and testing methodology proposed here could be used for similar scientific and engineering research applications.

Modelling of soil moisture change during the operation of the “Frigate” sprinkler

The irrigation process is one of the most important elements of technologies for growing crops on irrigated soils. The tasks of ensuring optimal soil water regime, eliminating gravita-tional water losses outside the zone of active moisture exchange and promoting the fullest use of plants of bioclimatic potential of the region require modeling of soil moisture dynamics in the process of wetting, as well as structures and technologies related to irrigation facilities. Soil moistening in the south of Ukraine is carried out mainly by sprinkling with the use of a Frigate sprinkler, which is largely close to the natural processes of moisture in soil structures, especially with the use of the latest Xi-Wob sprinklers, which provide uniform irrigation and uniform droplet size. The aim of the article is to develop a model of soil moisture change, which will determine the moisture content in both the root and near-surface layers of the soil and prognoses the movement parameters of the "Frigate" sprinkler elements. The designs of sprinklers currently available allow to provide uniform intensity of spraying of drops on all working area of "Frigate" sprinkler, therefore it is possible to choose a separate point for modeling. The data obtained for one point can be extended to the entire work area. The Darcy equation is used to mathematically describe the movement of water in the soil. The finite difference method was used to solve the Darcy equation based on the initial and boundary conditions. Assuming that within each soil element the humidity changes linearly, and replacing the partial derivatives of moisture in depth and time with the analogues, the discretized model of soil moisture dynamics in the final differences was obtained, which allows you to predict moisture at any time due to hydro-soil characteristics in previous time and boundary conditions. Discretization of the Darcy equation made it possible to obtain a model of the dynamics of the humidity of the root layer in the space of states. It turned out to be nonlinear due to the hydrophysical characteristics of the soil and was linearized by transformation into the Taylor series. The developed mathematical model of soil moisture change in the space of states allows to determine the moisture content in both the root and near-surface soil layer depending on its hydrological characteristics, type of cultivated plants, volume of water entering the fields from irrigation systems or in the form of random precipitation used to predict the movement parameters of the "Frigate" sprinkler elements.

Compaction Density Evaluation Model of Sand-Gravel Dam Based on Elman Neural Network With Modified Particle Swarm Optimization

The compaction density of sand-gravel materials has a strong gradation correlation, mainly affected by some material source parameters such as P5 content (material proportion with particle size greater than 5 mm), maximum particle size and curvature coefficient. When evaluating the compaction density of sand-gravel materials, the existing compaction density evaluation models have poor robustness and adaptability because they do not take into full consideration the impact of material source parameters. To overcome the shortcomings of existing compaction density models, this study comprehensively considers the impact of material source parameters and compaction parameters on compaction density. Firstly, asymmetric data were fused and a multi-source heterogeneous dataset was established for compaction density analysis. Then, the Elman neural network optimized by the adaptive simulated annealing particle swarm optimization algorithm was proposed to establish the compaction density evaluation model. Finally, a case study of the Dashimen water conservancy project in China is employed to demonstrate the effectiveness and feasibility of the proposed method. The results show that this model performs high-precision evaluation of the compaction density at any position of the entire working area which can timely correct the weak area of compaction density on the spot, and reduce the number of test pit tests.

Small-size streak tube with high edge spatial resolution

A small-size streak tube with high spatial resolution over the entire working area is designed, manufactured and tested. The streak tube adopts curved photocathode and curved screen to improve the spatial resolution, especially at the edge area by decreasing the aberration. An accelerating slit electrode, instead of a mesh which limits the luminance gain of the tube, is employed next to the photocathode to improve the electrical resistance, reliability and the temporal resolution by increasing the electron acceleration field. The results in the numerical simulations show that the spatial resolution is 29 lp/mm @ MTF = 10 % over the whole effective photocathode area. The tested results show that the small-size streak tube can offer static spatial resolution as high as 20 lp/mm over the whole effective area. And, the maximum point of the static spatial resolution 25 lp/mm, is deviated away from the center of the photocathode. The experiment results indicate that the spatial resolution is higher than 23.4 lp/mm @ MTF = 10 %. The luminance gain can reach to 39.4 and the dimension of the streak tube is only Φ40 mm × 140 mm. Comparing with 5200 streak tube_XIOPM, we demonstrated that this small-size streak tube in our design not only possesses the compact size, but also obtain a much larger effective working area and much higher luminance gain.

ОРТАДАН ТЕПКІШ СОРҒЫЛАРДЫ ЖЕТІЛДІРУ ҮШІН ГАЗ СЕПАРАТОРЛАРЫН ҚОЛДАНУ

In this article, the problem of monitoring the energy consumption of electric centrifugal pumps and the method of application in the fields with the use of gas separators on the basis of reducing the harmful gas impact on electric centrifugal pumps is developed. Methods of optimization of power consumption by borehole pumps are considered. Conducting comparative bench tests of new stages of a centrifugal pump designed for pumping gas-liquid mixtures (GLM), and determining the degree of influence of free gas on the operating parameters in the entire possible working area of the stage when pumping model GLM. It is concluded that the technology of electric centrifugal pumps is used.

Контроль качества розлива и маркировки пищевых продуктов с использованием интеллектуальных технологий

Статья посвящена повышению эффективности работы пищевого предприятия за счёт разработки и внедрения автоматизированной системы управления технологическим манипулятором на линии розлива и маркировки пищевых напитков с использованием интеллектуальных технологий. Показана необходимость в решении кинематических задач, особенно задач обратной кинематики манипулятора-робота. Проведенный в работе анализ показал, что существующие универсальные алгоритмы расчёта кинематики просты для записи в общем виде, но из-за ряда неустранимых недостатков ресурсоёмки и обладают в некоторых случаях большой вычислительной погрешностью. Если технологические манипуляторы вынуждены работать именно в таких зонах, в которых этот метод приводит к существенным вычислительным ошибкам, то это может привести к замедлению движения манипулятора, что также приводит к снижению производительности, или потребовать вынужденно изменять режим работы с целью удаления рабочего органа от центра рабочей зоны, что займет больше места для каждого манипулятора. Поэтому для расчета кинематики предложено вместо универсального алгоритма использовать набор простых тригонометрических выражений по условиям конкретных движений, что позволяет сохранить требуемую точность во всём объёме рабочей зоны. Для управления манипулятором, поиска оптимальной траектории и взаимодействия с программой-моделью реальности (в среде SolidWorks) использовались программы, созданные в среде LabVIEW с инструментарием NI-SoftMotion в качестве контроллера для управления положением модели. Для автоматизации контроля качества розлива и маркировки пищевых продуктов и модернизации системы управления технологическим манипулятором разработаны алгоритмы решения обратной кинетической задачи для роботов типа PUMA, SCARA и KUKA, а также программное обеспечение, реализующее разработанные алгоритмы. Показаны результаты анализа использования системы оптического распознавания изделий, учитывающего совместное движение манипулятора и изделий. В результате проведенных исследований разработана система виртуального прототипирования мехатронной системы, позволяющая выбрать контроллер управлением движением манипулятора и требуемые двигатели и параметры оптимизации линии розлива и маркировки пищевых продуктов с использованием интеллектуальных технологии. По полученным результатам разработана улучшенная модель робота PUMA 560, к которой добавлены средства для передвижения манипулятора с использованием интеллектуальных технологий, что позволит повысить эффективность работы линии розлива и маркировки пищевых продуктов, улучшить их показатели качества.

Rectification of Bowl-Shape Deformation of Tidal Flat DEM derived from UAV Imaging.

It is necessary to periodically obtain topographic maps of the geographical and environmental characteristics of tidal flats to systemically manage and monitor them. Accurate digital elevation models (DEMs) of the tidal flats are produced while using ground control points (GCPs); however, it is both complicated and difficult to conduct GPS surveys and readings of image coordinates that correspond to these because tidal flat areas are not easy to access. The position and distribution of GCPs affect DEMs, because the entire working area cannot be covered during a survey. In this study, a least-squares height-difference (LHD) DEM matching method with a polynomial model is proposed to increase the number of DEM grids while using a presecured precise DEM to rectify the distortion and bowl effect produced by unmanned aerial vehicle (UAV) images. The most appropriate result was obtained when the translation parameters were quadratic curve polynomials with an increasing number of grids and the rotation parameters were constant. The experimental results indicated that the proposed method reduced the distortion and eliminated the error caused by the bowl effect while only using a reference DEM.

Analisis Spasial Kejadian DBD di Wilayah Kerja Puskesmas Oesapa Tahun 2019

Oesapa Health Center is a health center that has the highest number of dengue cases in Kupang City in 2019 and spread throughout the Puskesmas working area. Regional-based disease management analysis techniques using spatial analysis can be used to facilitate the determination of the DHF problem solving intervention program. Spatial analysis is used to determine the pattern of disease spread and potential areas of dengue transmission based on area. The purpose of this study was to determine the pattern of dengue delivery, the spread of dengue incidence based on population density, the House Index and Container Index and the buffer. This type of research is a descriptive survey with a case study design. The sampling technique used total sampling with 98 people. The results of spatial analysis using Quantum GIS show the distribution pattern of dengue incidence with Clustered pattern with NNI value of 0,60 <1, the entire work area of Oesapa Health Center is included in the category of high population density, House Index and Container Index with the highest incidence of DHF in Oesapa and Lasiana Subdistrict and buffer analysis shows the tendency of dengue disease transmission in most cases to occur within a 100 meter radius, so the Oesapa Community Health Center work area is a high risk area for dengue transmission. Mosquito Nest Eradication Activities can be carried out by the community to prevent the spread of dengue disease.

A study of the radiological baseline conditions around the planned Sinop (Turkey) nuclear power plant using the mapping method.

This study makes a first attempt at a detailed estimation of the background radioactivity level and its distribution at the Sinop nuclear power plant site. The activity concentration levels of 226Ra, 232Th, 40K and 137Cs radionuclides in soil samples collected from 88 locations around Sinop Province, Turkey, in November 2016, were measured using gamma spectrometry. The distributions of radionuclide levels obtained from the results were evaluated using a geostatistical method, and the estimated radiation levels were determined using the ordinary kriging (OK) method, which is the best linear unbiased estimator (BLUE) for unmeasured points. Estimates of distribution results were evaluated using cross-validation diagrams, and it was shown that the OK method could predict radiological distributions for appropriate criteria. Finally, using the kriging parameters, distributions of radiation levels for the entire work area were mapped at a spatial resolution of 100 × 100m2. These maps show that the natural radionuclides (226Ra, 232Th and 40K) are distributed at higher levels to the southeast of Sinop than in the other regions, and the activity of an artificial radionuclide (137Cs) is high in the interior and northern sections.

A study on the dust control effect of the dust extraction system in TBM construction tunnels based on CFD computer simulation technology

In order to control dust in a tunnel boring machine (TBM) construction tunnels, this paper, in combination with field measurements, applies CFD computer simulation technology to study the dust control effect of TBM construction tunnels under different dust extraction flow rates. Firstly, the dust extraction system is closed, and the result of the simulation show that the dust diffuses to the entire TBM working area within 181 s, indicating the necessity of having a dust extraction system in the tunnel. Secondly, the dust extraction system is open and under the original dust extraction flow rate of Qe = 8 m3/s, the overall dust diffuses to the entire working area Lo = 130 m, and the full-face dust diffusion distance is Lf = 47.54 m. Then the study was carried out with the setting of 2 m3/s ≤ Qe ≤ 14 m3/s. The results show that: when Qe ≤ 8 m3/s, the full-face dust diffuses to 47.54–71.84 m; when Qe > 8 m3/s, the full-face dust can be controlled at 42.81–46.34 m; and when Qe = 8 m3/s, the full-face dust control effect is better, and the average dust concentration in the tunnel is as low as 12.25 mg/m3, indicating that the original dust extraction system has a better design. The field measurement results verify that the CFD computer simulation results are accurate.

Compaction quality assessment of rockfill materials using roller-integrated acoustic wave detection technique

Abstract During conventional earth-rock dam construction, quality control and acceptance (QC/QA) are based on limited spot tests of material density at random locations which may not be representative of the compacted area and may consist of potential bias. Based on roller-integrated acoustic wave detection technique with real-time kinematic global positioning systems, this research adopted sound compaction value (SCV) as a real-time monitoring index for the dam compaction quality, and subsequently proposed an SCV-based assessment method to estimate the compaction quality of rockfill (RF) materials. Additionally, a geostatistical method (Kriging) was adopted to obtain estimates for both SCVs and compaction quality at any location on the work area, thereby calculating the qualified rate of compaction quality for the entire work area. A case study on the Qianping project in China indicates a strong linear correlation between the SCV and the compaction parameters as well as the dry density of RF materials; therefore, it can serve as a reliable index for monitoring compaction quality of RF materials. Assessment of compaction quality on the entire work area can be quickly and continuously achieved using the proposed method, which can effectively overcome the above limitation of conventional testing, timely feedback compaction information to avoid quality defects, and availably improve the construction quality of earth-rock dams.

Porosity- and reliability-based evaluation of concrete-face rock dam compaction quality

Abstract Compaction quality evaluation of concrete-faced rockfill dams (CFRDs) is a complex nonlinear process. Conventional evaluation methods depend on random spot tests, and porosity is considered as the main evaluation index. However, reliability of results is neglected in existing studies. Considering compaction parameters, material properties and their variability characteristics, an evaluation approach of CFRD compaction quality based on porosity and reliability is proposed. Reliability analysis is introduced to measure the variability in highly variable factors and calculate the porosity- and reliability-based index. Porosities of the entire work area are predicted using an elitist genetic algorithm-based artificial neural network, which are consistent with the measured values with an error