Field Equipment Research Articles

Mathematical Models and Algorithms for Failed Equipment Planning Replacement

For the operability of deep well pump units under the conditions of oil and gas field equipment rental, it is necessary to plan the required resources. Failed equipment must be replaced with new one. If it is possible to repair the items, they are sent to repair service points. A review of literary sources on the subject of the study and the problem statement are provided. A large number of equipment application points and real operating conditions introduce great uncertainty into planning the failed equipment replacement. The value of the failure rate is a random variable. A mathematical model to manage the process of failed equipment replacing has been developed. Fuzzy logic methods have been used to take into account the uncertainty. Characteristics of fuzzy failure flow have been determined,based on the available information on failures. To perform computational operations, algorithms for working with fuzzy variables have been developed based on, in general case, asymmetric, and parabolic membership functions. The operations of addition, subtraction, multiplication, division, and exponentiation of fuzzy numbers are determined using interval arithmetic andα-cut method. The amount of equipment stock is determined by a fuzzy number. The use of a hybrid genetic algorithm provided an optimal solution to the optimization problem equipment replacement management. The calculation results are given. When solving the fuzzy optimization problem in comparative operations, the rank of the fuzzy number was calculated. The concept of centroid defuzzification of the fuzzy number is used to determine the rank value. The diagram of the fuzzy number membership function and the diagram of the optimization problem objective function: total costs were constructed. Compared with the optimization problem clear formulation, the total costs in the fuzzy formulation turned out to be higher, also the value of the safety stock was determined .

EVALUASI CYCLE TIME TERHADAP KONDISI MEDAN PADA PROYEK PEMBANGUNAN AKSES JALAN SAMOTA LANJUTAN KABUPATEN SUMBAWA

The Samota Road access development project continued in Sumbawa Regency is one part of the Samota area development project which acts as access to mobilization and supports the acceleration of development, economy, social and culture. In large-scale road works, heavy equipment is needed to facilitate work in a relatively shorter time. Errors in the operating time of heavy equipment and differences in the work field will affect cycle time and have an impact on productivity. This study aims to determine the amount of heavy equipment cycle time, heavy equipment productivity, and the effect of cycle time on heavy equipment productivity. The methods used in this research are time study and correlation methods. The time study method is a measurement of work by collecting data based on the time needed to complete a job so that productivity can be calculated, while the correlation method is an analysis to determine the level of relationship between the independent variable (X) and the dependent variable (Y).Based on data analysis, the value of cycle time, productivity and the effect of cycle time on heavy equipment productivity were obtained. In segment 1, the cycle time of the motor grader is 303,247 seconds with a productivity of 916,037 m2/hour and the cycle time of the vibratory roller is 612,345 seconds with a productivity of 1061,400 m3/hour. For the effect of cycle time on the productivity of the motor grader, the correlation test result is 0,986 and the vibratory roller is 0,999. In segment 4, the motor grader cycle time is 316,107 seconds with a productivity of 831,112 m2/ hour and the vibratory roller cycle time is 655,370 seconds with a productivity of 988,200 m3/hour. For the effect of cycle time on motor grader productivity, the correlation test results were obtained at 0,975 and vibratory roller at 0,999. In both segments, there is a very strong influence and relationship between variable X (cycle time) and variable Y (productivity).

Tide-river interaction in the Pechora Delta as revealed by new measurements and numerical modeling

The Pechora is the greatest river of the European Russian Arctic, flowing into the Barents Sea. Its estuarine area includes a vast delta, represented by extensive lowlands that are dissected by the complicated network of arms and branches. Despite the Pechora Delta is considered to be microtidal, tides with a range of 0.5–1 m during the low water period have a significant impact on the nature of currents in the main branches and the distribution of runoff among them during the tidal cycle. Tidal sea level fluctuations as well as storm surges determine the reversing pattern of currents over a significant extent of the delta branches. The modern field equipment combined with 2D hydrodynamic modeling has allowed to understand the contemporary flow features and evaluate their possible alterations under climate changes. The climate impact under considered scenarios is more pronounced during the low flow period, and this can lead to the propagation of tidal currents and an increase in water levels in the city of Naryan-Mar (100 km upstream from the mouth). From a flood risk perspective, sea level rise can be offset by a reduction in flood runoff.

The impact of low-molecular carboxylic acids on carbon dioxide corrosion of steel in underground gas production equipment in the Dnipro-Donetsk basin fields

The impact of low-molecular carboxylic acids on carbon dioxide corrosion of steel in underground gas production equipment in the Dnipro-Donetsk basin fields

Robust Dynamic State Estimation for Power System Based on Generalized Correntropy Loss Function and Unscented Kalman Filter

Dynamic state estimation (DSE) of the power system is one of the most important means to ensure a safe and stable operation of the power system. However, the electromagnetic field environment, communication noise and equipment failure often lead to the appearance of non‐Gaussian noise and bad data, which ultimately cause performance degradation of traditional DSE algorithms based on the mean‐square error criterion. In this paper, a DSE method based on the generalized correntropy loss (GCL) function is proposed, which is well adapted to estimate the dynamic characteristics of the power system. The new robust DSE method can effectively deal with problems such as non‐Gaussian noise and bad data, thus improving the state estimation accuracy. Simulation results carried out on the IEEE 39‐bus system with synchronous generators demonstrate the robustness of the proposed DSE method. © 2024 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

구글 크롬 뮤직랩을 활용한 초등학교 예비 교원의 AI · 디지털 매체 역량 강화 방안 연구

The purpose of this study is to provide basic data to prospective elementary school teachers to strengthen their teaching and digital media utilization capabilities in the field of music creation using AI · digital media, and to help them research on improving the curriculum of pre-service elementary school teachers. Based on this, the 2022 revised music curriculum, and current music textbooks were analyzed and 4 sessions for pre-service elementary school teachers using Google Chrome Music Lab were developed. The significance of this study is that it presented a curriculum plan for pre-service elementary school teachers that focused on Google Chrome Music Lab among various AI · digital media for music education. It is also significant that the 2022 revised music curriculum, current textbooks, and achievement-based music creation were analyzed to consider the connection between digital media and the educational field. To make suggestions through this study, first, it is necessary to discover various cases of music teaching methods using AI · digital media. Second, music creation training using digital media should be actively conducted not only for pre-service teachers but also for teachers. Finally, it is necessary to create an educational environment with digital literacy in accordance with the changing times by sufficiently establishing AI · digital-related equipment in the educational field. It is hoped that this study will help improve elementary school music creation classes and pre-service teacher curriculum using AI · digital media.

Enhancing cotton whitefly (Bemisia tabaci) detection and counting with a cost-effective deep learning approach on the Raspberry Pi.

The cotton whitefly (Bemisia tabaci) is a major global pest, causing significant crop damage through viral infestation and feeding. Traditional B. tabaci recognition relies on human eyes, which requires a large amount of work and high labor costs. The pests overlapping generations, high reproductive capacity, small size, and migratory behavior present challenges for the real-time monitoring and early warning systems. This study aims to develop an efficient, high-throughput automated system for detection of the cotton whiteflies. In this work, a novel tool for cotton whitefly fast identification and quantification was developed based on deep learning-based model. This approach enhances the effectiveness of B. tabaci control by facilitating earlier detection of its establishment in cotton, thereby allowing for a quicker implementation of management strategies. We compiled a dataset of 1200 annotated images of whiteflies on cotton leaves, augmented using techniques like flipping and rotation. We modified the YOLO v8s model by replacing the C2f module with the Swin-Transformer and introducing a P2 structure in the Head, achieving a precision of 0.87, mAP50 of 0.92, and F1 score of 0.88 through ablation studies. Additionally, we employed SAHI for image preprocessing and integrated the whitefly detection algorithm on a Raspberry Pi, and developed a GUI-based visual interface. Our preliminary analysis revealed a higher density of whiteflies on cotton leaves in the afternoon and the middle-top, middle, and middle-down plant sections. Utilizing the enhanced YOLO v8s deep learning model, we have achieved precise detection and counting of whiteflies, enabling its application on hardware devices like the Raspberry Pi. This approach is highly suitable for research requiring accurate quantification of cotton whiteflies, including phenotypic analyses. Future work will focus on deploying such equipment in large fields to manage whitefly infestations.

A Review of CiteSpace Visualisation and Analysis of High-Temperature Corrosion Inhibitors for Oil and Gas Fields

With the increasing global energy demand, the exploitation depth of oil and gas fields is gradually increasing. At the same time, importing many high-acid crude oil makes it increasingly heavy and inferior, and its acid value is constantly improving. This change has led to the increasingly severe corrosion problem of oil and gas field equipment, which has become an essential factor affecting the national economy and society's sustainable development. As an economical and practical anticorrosion measure, corrosion inhibitors play a crucial role in the anticorrosion of oil and gas field equipment. Through the research method of biorientation, retrieve the Web of Science database in 2008-2024 about oil and gas field high-temperature corrosion inhibitor research literature information, using CiteSpace measurement analysis software visual analysis in the literature keywords, publications, high citation frequency, cooperation and word clustering information change trend, analyze the research situation of oil and gas field in recent years, summarizes the research hotspot of oil field high-temperature corrosion inhibitor, prominent authors and institutions, reference relationship and development trend. The number of documents on high-temperature corrosion inhibitors in oil and gas fields is smaller, and the authors, institutions, and countries are not closely related. There is less research cooperation on high-temperature corrosion inhibitors in oil and gas fields, and more independent studies exist. China University of Petroleum has the first number of publications, and China is the country with the first number of publications. The study of mass spectrometry for corrosion inhibitors in oil and gas fields is prominent, while the literature on high-temperature corrosion inhibitors is rare.

Phenotypic and Genomic Characterization of a Sulfate-Reducing Bacterium Pseudodesulfovibrio methanolicus sp. nov. Isolated from a Petroleum Reservoir in Russia.

The search for the microorganisms responsible for sulfide formation and corrosion of steel equipment in the oil fields of Tatarstan (Russia) resulted in the isolation of a new halotolerant strictly anaerobic sulfate-reducing bacterium, strain 5S69T. The cells were motile curved Gram-negative rods. Optimal growth was observed in the presence of 2.0-4.0% (w/v) NaCl, at pH 6.5, and at 23-28 °C under sulfate-reducing conditions. The isolate was capable of chemoorganotrophic growth with sulfate and other sulfoxides as electron acceptors, resulting in sulfide formation; and of pyruvate fermentation resulting in formation of H2 and acetate. The strain utilized lactate, pyruvate, ethanol, methanol, fumarate, and fructose, as well as H2/CO2/acetate for sulfate reduction. The genome size of the type strain 5S69T was 4.16 Mb with a G + C content of 63.0 mol%. On the basis of unique physiological properties and results of the 16S rRNA gene-based phylogenetic analysis, phylogenomic analysis of the 120 conserved single copy proteins and genomic indexes (ANI, AAI, and dDDH), assigning the type strain 5S69T ((VKM B-3653T = KCTC 25499T) to a new species within the genus Pseudodesulfovibrio, is suggested, with the proposed name Pseudodesulfovibrio methanolicus sp. nov. Genome analysis of the new isolate showed several genes involved in sulfate reduction and its sulfide-producing potential in oil fields with high saline formation water.

Application of energy storage performance regulation of ferroelectric thin films in sports competitions

With the continuous improvement of sports competition level and technological progress, accurate recording and analysis of athletes’ physical condition and training data have become increasingly important. In sports competitions, finding a new type of material that can store the training abilities of athletes has become a challenge. As an emerging energy storage material, ferroelectric thin films have unique advantages in energy storage performance and flexibility. This article explored the application of energy storage performance regulation of ferroelectric thin films in sports competitions, and analyzed that the biological monitoring indicators and health management of athlete training needed to comprehensively consider multiple aspects, including physical and physiological indicators. The measured data of multiple athletes were collected and the relationships among the multiple indicators were analyzed through t-tests. The article explored the capture and conversion of motion kinetic energy, and analyzed the general architecture of motion capture systems as an example. In terms of the energy storage performance of ferroelectric thin films, data before and after the enhancement of sports equipment in the sports field was collected for research based on the energy storage performance of ferroelectric thin films. In the evaluation and exploration of the application effect of ferroelectric thin films in the sports field, combined with multiple tests and satisfaction feedback, it was found that the satisfaction rate of male athletes reached 94% −98% at week 7, while the satisfaction rate of female athletes reached 94% −96% at week 7. With the progress of technology and continuous innovation, it is believed that ferroelectric thin film energy storage technology can play a greater role in the field of sports in the future.

Corrosion-mechanical destruction of bainite structures in oilfield environments

The main direction in solving the problem of increasing the reliability of field equipment, is the creation of new steels with higher resistance to corrosion-mechanical destruction. Currently, to produce oil and gas pipeline systems, low-carbon, low-alloy steels are used, in which lath carbide-free bainite is formed when quenched in water. Such a structure provides a combination of high strength and resistance to brittle fracture. However, issues of increasing corrosion resistance are still open. The purpose of this work is to identify the structural condition of low-carbon, low-alloy, pipe steels, providing a combination of high mechanical properties with increased corrosion resistance in oilfield environments. The studies were carried out on the latest generation 08KhFA, 08KhFMA and 05KhGB steels, most popular when manufacturing oil and gas pipelines. Samples for the study were cut from the pipes and quenched from the austenite region in water, which formed the structure of lath carbide-free bainite. The quenched samples were tempered at temperatures of 200, 300, 400, 500, 600, and 700°C. To identify the relationship between the morphology of bainite structures and their properties, the samples after quenching and tempering at each temperature, were subjected to metallographic analysis, X-ray diffraction analysis, mechanical tests, and corrosion resistance tests. The work shows the sequence of structure transformation, temperature ranges of phase and structural transformations, changes in mechanical properties, and corrosion resistance that occur during tempering of lath carbide-free low-carbon bainite. It is shown that tempering of lath carbide-free bainite (08KhFA, 08KhMFA and 05KhGB steels) does not affect the rate of carbon dioxide corrosion. It has been found that medium tempering forms the structural condition of carbide-free low-carbon lath bainite providing a combination of high mechanical properties and high corrosion resistance in oil field environments. For each of the steels under study, the authors give recommended heat treatment modes.

The Pangolin Universal Notching System: a scale-marking methodology for pangolins

Abstract Despite thousands of individuals entering the illegal wildlife trade each year, assessments of pangolin populations are largely non-existent, even in areas with high exploitation and limited personnel and field equipment. Although pangolins have unique keratin-based scales, there is no universal scale-marking method for individuals despite some pangolin conservation programmes utilizing marking for reference and cataloguing. Each programme currently establishes and manages its own system, resulting in inconsistencies and limiting data sharing. To facilitate pangolin monitoring and research, we developed a standardized method for assigning individual identification numbers, which we call the Pangolin Universal Notching System. This system is neither resource nor training intensive, which could facilitate its adoption and implementation globally. Its application could help to address knowledge gaps in pangolin ageing, reproduction, survivorship, migration and local trafficking patterns, and could be used in combination with other tagging techniques for research on pangolin biology.

Maximizing efficiency and uniformity in SAGD steam circulation through effect of heat convection

The thermal recovery is facing the challenge of improving quality and efficiency. Steam-assisted gravity drainage (SAGD) steam circulation has a profound implications for the formal production. There is a lack of research on the situation when the steam injection pressure of injection well is lower than that of production well during startup stage. In this paper, the effects of diverse injection pressure difference on SAGD steam circulation and production stage are investigated by analytical modeling and numerical simulation, especially when the steam injection pressure of producer well is larger than that of injection well, and reliable results are obtained by temperature falloff test and model comparison validation. Meanwhile, in order to minimize the factors affecting the simulation accuracy, a sensitivity analysis of the temperature prediction model for the startup stage is carried out using Monte Carlo method and the finest possible mesh is used in the numerical simulation. The results show that:①The preheating results are faster and more uniform than the conventional preheating method when steam injection pressure of producer is greater than that of injector, and the subsequent production indexes are also superior to those of the conventional preheating method. ②The injected steam temperature had the greatest effect on the prediction accuracy of the analytical model; The finer the numerical simulation grid division, the lower the midpoint temperature of the horizontal well pair; ③An optimal range of injection pressure differences that achieves the best balance between preheating efficiency and thermal recovery effectiveness is achieved with Pprod-Pinj in the range of 400–500 kPa. ④The preheating method investigated in this paper minimizes the effect by unfavorable factors such as reservoir non-homogeneity, which holds the potential for more uniform, time-saving preheating and without the addition of field equipment.

Design and implementation of tilting‐plate drainage equipment for paddy field

AbstractDrainage equipment is an important part of paddy field drainage and irrigation system, and its performance research and application are conducive to the promotion and implementation of high‐standard farmland construction. Aiming at the different water demand of rice in different growing stages, low water level control precision, large manual operation and extensive management of existing drainage machinery, a tilting‐plate drainage equipment using upper overflow mode was proposed in this paper. Based on the Geneva mechanism principle, a unique linkage mechanism is designed, which can realize water retaining operation and silt discharge operation through a single motor drive, and the relationship between the motor angle and the water retaining height is established. Through mechanical analysis and dynamic simulation of the mechanism, the motion characteristics of the water baffle, silt plate and the change of the motor torque are studied. A remote control system based on a 4G module is designed to control the drainage equipment easily through the user layer. The performance test of the prototype shows that the precision error of the optimized water retaining height control is less than 3.75%. The maximum height of water retaining operation is 180 mm, and the maximum load of silt discharge operation is 10 kg, which can meet the actual operation requirements. The design is beneficial to improve the precision and intelligence level of paddy field drainage management, and the research process can provide some help for the development and application of this kind of equipment.

Research Progress on Autonomous Operation Technology for Agricultural Equipment in Large Fields

Agriculture is a labor-intensive industry. However, with the demographic shift toward an aging population, agriculture is increasingly confronted with a labor shortage. The technology for autonomous operation of agricultural equipment in large fields can improve productivity and reduce labor intensity, which can help alleviate the impact of population aging on agriculture. Nevertheless, significant challenges persist in the practical application of this technology, particularly concerning adaptability, operational precision, and efficiency. This review seeks to systematically explore the advancements in unmanned agricultural operations, with a focus on onboard environmental sensing, full-coverage path planning, and autonomous operational control technologies. Additionally, this review discusses the challenges and future directions of key technologies for the autonomous operation of agricultural equipment in large fields. This review aspires to serve as a foundational reference for the development of autonomous operation technologies for large-scale agricultural equipment.

A visual digital twin framework based on residual-based fourier neural operator online simulation method

ABSTRACT To enjoy a wonderful cooking experience in a smart kitchen, users and designers need a visual interaction platform. This paper proposes a DT framework incorporating data processing, flow field online simulation, equipment monitoring, interaction and visualization. Specifically, the DT online simulation and visualization of the kitchen fume flow field serve as the foundation for appliance design and control. Additionally, users can gain deeper insight into the state and change trends of the kitchen. To address the online simulation of the flow field, a RFNO online simulation method is proposed. In addition, this paper proposes an Echarts-based 2D and UE5-based 3D flow field visualization method to enable dynamic visualization and interaction of the flow field. The proposed DT framework was successfully verified in the case of the smart kitchen, demonstrating its efficiency and effectiveness.

Ant-observer: A new approach for automatic acquisition and autonomous analyses of individual species abundance and interactions

Traditional methods, such as direct observations or manually photographing bait stations, are limited in both data collection efficiency and accuracy. Consequently, they fail to capture the dynamic changes and complex relationships between ant species. We developed a novel system as a potential solution that combines processed consumer-grade camera equipment and software that acquires data needed for in situ experiments. This software features a user-friendly graphics user interface (GUI) for data collection and post-hoc analysis from videos captured by the camera equipment. Researchers can use this system to (1) count species abundance per frame; (2) calculate species speed; (3) detect ant interactions; and (4) count the abundance of different subcastes within species on baits. To demonstrate the complete workflow, we applied this system on ant videos collected in Hong Kong. Practical guides (supplement materials) detailing suggestions for camera equipment and software operations in both field and laboratory studies are provided. We present the results of ten in situ experiments of ants (each lasting 1–1.5 h) conducted in Hong Kong though processed consumer-grade camera equipment, with videos analyzed using the newly developed software. The analysis captured a range of variables related to ant foraging behavior, including resource discovery time, nestmate recruitment rate, and interspecific interactions. Our results confirm that the developed software provides an integrated and efficient approach for data collection, extraction, and analysis in in situ experiments, enhancing the capabilities of insect ecology research.

Optimizing Clubroot Management and the Role of Canola Cultivar Mixtures.

The sustainable cultivation of canola is under threat from clubroot disease (Plasmodiophora brassicae). The pathogen's resting spores can survive in the soil for extended periods, complicating disease management. Therefore, effective clubroot control requires a combination of tactics that provide multiple layers of protection. Management strategies have focused on pathogen avoidance and reducing disease levels in infested fields. The sanitation of machinery and field equipment remains the most effective method for preventing the pathogen's introduction into non-infested fields. For disease reduction, crop rotation, liming, chemical control, and host resistance are commonly employed, with the use of clubroot-resistant cultivars being the most effective to date. However, resistance breakdown has been observed within four years of the introduction of new cultivars, jeopardizing the long-term effectiveness of this approach. A promising yet underexplored strategy is the use of cultivar mixtures. This approach leverages mechanisms such as the dilution effect, the barrier effect, induced resistance, disruptive selection, and the compensatory effect to control the disease. Cultivar mixtures have the potential to reduce the impact of clubroot on canola production while preserving pathogen population structure, thereby minimizing the likelihood of resistance breakdown. Given its potential, further research into cultivar mixtures as a management strategy for clubroot disease is warranted.

Water penetrating radar: A fluvial scour study of antenna performance and data processing

AbstractGround‐penetrating radar (syn. water‐penetrating radar, or WPR hereon) has been used previously in the detection and characterisation of riverine scour. This paper presents field data, equipment calibration and processing output results from a new generation of high dynamic range (HDR) radar systems. These provide a new and more sophisticated model of fluvial scour for the study site. The adaptability for deployment on water, wide bandwidth and good quality in raw and processed data, demonstrates the advantages of the system. Data processing and depth calibration are issues in the interpretation of WPR data, which are both discussed. WPR demonstrates the potential for surveying sedimentation where palaeoscour occurred and thus anticipated. This maybe in conjunction with other techniques or where aquatic vegetation, rocky substrates or methane gas bubble release preclude use of sonar.

Digital twin-driven intelligent operation and maintenance platform for large-scale hydro-steel structures

Large-scale hydro-steel structures (LS-HSS) are pivotal in hydraulic engineering, boasting high lift, expansive apertures, and discharge capacities. Conventional methods of operation and maintenance for LS-HSS require a digital revolution to ensure safety, reliability, and durability. This study introduces a novel approach, harnessing the power of a digital twin (DT) to integrate physical and virtual elements in LS-HSS operation and maintenance seamlessly. A digital twin modeling framework of LS-HSS operation and maintenance is first presented, incorporating five levels of a physical entity, a virtual entity, DT data, services, and connections. Subsequently, a DT-driven intelligent operation and maintenance (DT-IOM) platform is constructed and applied, which features real-time mapping, closed-loop control, dynamic health assessment, and intelligent decision-making. This platform provides a pathway for digitally transforming conventional LS-HSS operation and maintenance and paves the way for a new era of intelligent infrastructure management. The proposed approach has been successfully implemented and validated with multiple engineering projects, including radial gates of reservoir spillways, plain gates of flood discharge orifices, and emergency gates of pumped storage power stations. The impressive results demonstrate a significant anomaly response and processing efficiency improvement of over 60%. Moreover, the platform has substantially reduced field inspection time and equipment failure rate by approximately 50% and 20%, respectively. These tangible benefits further highlight the platform’s functional advantages, including its capability for IoT connection, modeling and integration, virtual-real interaction, 2D/3D visualization, and service expansion. The results demonstrate the unique features in the closed loop of perception, analysis, decision-making, and optimization for DT-IOM, especially for integrating data, models, knowledge, and services in LS-HSS intelligent operation and maintenance.