With the development of pipeline networks, many safety accidents were caused by pipeline stress concentration; it is of great significance to accurately monitor the pipeline stress state for maintaining pipeline safety. In this paper, based on alternating current stress measurement (ACSM) methods, a 3D simulation model of a pipeline electromagnetic field was established by ANSYS software. The distribution law of the pipeline magnetic field and eddy current field were analyzed, and the influence of size and structure parameters of the coil inside the probe were studied. The internal stress detection system of the pipeline was designed, and the static tensile stress measurement experiment was carried out. Simulation and test results showed that the excitation coil with a larger diameter-to-height ratio had a higher measurement sensitivity. The sensitivity of the probe decreased monotonically with the increase of the difference between inner diameter and outer diameter of the detection co... [more]

This article presents a methodology for predicting the absolute methane emission rate for longwall caving extraction based on the determination of destressing zones generated by longwall mining operations, by means of numerical modelling. This methodology was applied for the conditions of the K-2 longwall panel in the KWK Pniówek mine. The finite difference method code FLAC2D was employed as an element of the methodology to determine the destressing zones. All results including the numerical modelling results, empirical results and the measured (in situ) results were gathered in the comparative analysis. As the final results, the accuracy and reliability of the proposed methodology were evaluated.

This paper proposes a methodology for numerical modeling of terraforming Mars’ atmosphere using high-energy asteroid impact and greenhouse gas production processes. The developed simulation model uses a spatial data science approach to analyze the Global Climate Model of Mars and cellular automata to model the changes in Mars’ atmospheric parameters. The developed model allows estimating the energy required to raise the planet’s temperature by sixty degrees using different variations of the terraforming process. Using a data science approach for spatial big data analysis has enabled successful numerical simulations of global and local atmospheric changes on Mars and an analysis of the energy potential required for this process.

The radius of the coil, the number of turns of the windings, and the parasitic resistances of energy-storing elements affect the performances of wireless power transfer systems. We aimed to study the effects of coil parameters on a wireless power transfer system with the capacitor−capacitor−coupling coil (CCL)-based circuit using numerical simulations. The power transfer system topologies, including series−CCL (S−CCL), CCL−S, and CCL−CCL, were studied vis-à-vis coil parameters. The helical coil and the system topologies were modeled using MATLAB, and the performances of the topologies were examined in comparison to the series−series (S−S) topology. The variables used in the simulations included the radius and number of turns, the parasitic resistance that was merged in the impedance, and the reactance of energy-storing elements. Subsequently, the performances of the topologies were estimated by numerical simulations under several circumstances. The simulation results showed that the pa... [more]

With the further exploitation of offshore resources, there are more and more offshore oil and gas fields which cannot meet the production capacity requirements. So, it becomes extremely urgent to pay attention to the decommissioning of the exploitation equipment in abandoned offshore fields. A new decommissioning solution is offered by the double-ship integrated offshore platform decommissioning equipment comes. However, as the equipment will inevitably bear the combined actions of various dynamic and static loads during operation, the strength and stability of the overall unit and the connections between different modules will be greatly challenged by the complex ocean. Firstly, the dynamic characteristics of the integrated decommissioning system are analyzed in this paper. Mathematical modeling of the lifting arm system is established based on the unit characteristics matrix, and a dynamic equation of the flexible lifting arm unit and system is developed based on Lagrange’s equation... [more]

This study introduces a Vorticity Index (VI) and an Imminent Vortex Separation Condition (IVSC), which are considered valuable indicators to quantify the vorticity impact on vertical axis wind turbines (VAWTs) operation. The VI and IVSC are specifically applied to a H-Darrieus vertical axis wind turbine (VAWT). Findings show that these two parameters display a direct relationship with the aerodynamic forces that govern the performance of this type of VAWT. This analysis is accomplished via 2D-CFD simulations of a H-Darrieus with a symmetrical NACA 0018, powered by high winds (8 and 20 m/s), by using a Shear Stress Transport SST k-ω model. The 2D model used is validated for Class II winds (8 m/s), for tip speed ratios (λ) ranging from 0.4 to 0.9. Power coefficients (Cp) predictions are close to those obtained with both 3D simulations and with experimental data, reported in the technical literature. It is found with the numerical simulations developed, that despite the significant increa... [more]

AF1410 is a low carbon high alloy ultra-high strength steel. It not only has high strength and high toughness, but also has a high stress corrosion resistance. However, due to the characteristics of hard quality and poor thermal conductivity, AF1410 is a difficult material to process. In the process of milling, the geometric factors of process parameters, the flexible deformation of milling cutter and the flutter of the process system all affect the surface roughness, which makes it difficult to predict the surface roughness of milling parts. In order to solve this problem, a prediction model for surface topography of ultrahigh strength steel AF1410 was studied. To solve this problem, this paper studies the formation of milling surface topography, considers the dynamic displacement of the milling system, proposes a modeling method of surface topography based on the dynamic characteristics of the milling system and forms a prediction model. On this basis, the surface topography of ultra... [more]

Very high viscosity significantly impacts the mobility of heavy crude oil representing difficulties in production and a decrease in the well’s efficiency. Downhole electric heating delivers a uniform injection of heat to the fluid and reservoir, resulting in a substantial decrease in dynamic viscosity due to its exponential relationship with temperature and a drop in frictional losses between the production zone and the pump intake. Therefore, this study predicts temperature and viscosity profiles in heavy oil-production wells implementing a downhole induction heater employing a simplified CFD model. For the development of the research, the geometry model was generated in CAD software based on the geometry provided by the BCPGroup and simulated in specialized CFD software. The model confirmed a 46.1% effective decrease of mean 12° API heavy-oil dynamic viscosity compared with simulation results without heating. The developed model was validated with experimental data provided by the BC... [more]

This study presents a novel hybrid framework combining feature selection, oversampling, and machine learning (ML) to improve the prediction performance of vehicle insurance. The framework addresses the class imbalance problem in binary classification tasks by employing principal component analysis for feature selection, the synthetic minority oversampling technique for oversampling, and the random forest ML classifier for prediction. The results demonstrate that the proposed hybrid framework outperforms the conventional approach and achieves better accuracy. The purpose of this study is to provide insurance managers and practitioners with novel insights into how to improve prediction accuracy and decrease financial risks for the insurance industry.

The purpose of the software development presented in the article is to obtain detailed information about the surface of the walls in wells necessary for more efficient and safe drilling and casing of the wellbore. The developed software of the automated system “LogPWin” allows obtaining a clear idea of the mine itself, as well as reducing the time spent on processing and analyzing the model obtained during the logging process. A software product developed as a result of the work provides visualization of data coming from an acoustic profiler, giving a visual and informative idea of the object of study. The program gives detailed information about the surface of the mine’s walls through 3D modeling. It possesses the possibility of rotating and scaling the object; there is also a color palette that can be changed depending on the incoming data. The program can be applied in the oil and gas industry and mining, as well as when drilling wells for other purposes. The program interface is qu... [more]

By researching the influence of micro-groove texture on the surface tribological properties of the stator and rotor pair of oil production hydraulic motors, this paper aims to reduce the frictional resistance moment of the spiral pair of hydraulic motors, and further solve the problem of the difficult restart of the pump of a certain type of hydraulic-driven screw pump. According to the spiral pair of screw motors, a metal-rubber flat plate reciprocating friction model is established, and rectangular micro-grooves with different texture angles and depths are machined on the surface of the metal specimen. A combination of finite element simulation and tribological tests is used to carry out a study on the influence of different texture parameters on the friction performance of the hydraulic motor spiral pair. The results showed that at a certain texture angle, the friction coefficient of each specimen basically increases with the texture depth. When the texture depth is constant, the fr... [more]

Artificial intelligence-based hardware devices are deployed in manufacturing units and industries for emission gas monitoring and control. The data obtained from the intelligent hardware are analyzed at different stages for standard emissions and carbon control. This research article proposes a control-centric data classification technique (CDCT) for analyzing as well as controlling pollution-causing emissions from manufacturing units. The gas and emission monitoring AI hardware observe the intensity, emission rate, and composition in different manufacturing intervals. The observed data are used for classifying its adverse impact on the environment, and as a result industry-adhered control regulations are recommended. The classifications are performed using deep neural network analysis over the observed data. The deep learning network classifies the data according to the environmental effect and harmful intensity factor. The learning process is segregated into classifications and analy... [more]

Distillation columns represent the most widely used separation equipment in the petrochemical industry. It is usually difficult to apply the traditional mechanism modeling method to online optimization and control because of its complex structure, and common simplified models produce obvious errors. Therefore, we analyze the mass transfer process of gas-liquid fluid on each column tray based on the theory of gas-liquid equilibrium and establish a nonlinear dynamic model of the distillation process. The proposed model can accurately characterize the nonlinear characteristics of the distillation process, and the model structure is largely simplified compared with the traditional mechanism model. Therefore, the model provides a new approach for model-based methods in distillation columns, especially for cases that require efficient online models. Two case studies of benzene-toluene distillation systems show that the nonlinear model has high concentration observation accuracy. Finally, a g... [more]

This study provides a basis for designing and optimizing the key components of hanging-cup transplanters. The discrete element method, a high-speed photography test, and indoor soil bin tests were used to explore soil disturbance behavior during the hole drilling process. A comparative analysis of the discrete element method and the high-speed photography test indicated that soil particles are mainly affected by the coupled effects of the shear force and the squeezing force of the planter. The soil disturbance range in the horizontal and longitudinal sections gradually increases with the movement of the planter. The change in the soil particle velocity of the horizontal and longitudinal sections in different zones shows a trend of first increasing, then decreasing, and finally stabilizing. The velocity of soil particles in the longitudinal section varies significantly in the direction of burial. The soil in the horizontal section mainly moves to both sides when the duckbill is opened.... [more]

Deep Learning (DL) has gained enormous popularity recently; however, it is an opaque technique that is regarded as a black box. To ensure the validity of the model’s prediction, it is necessary to explain its authenticity. A well-known locally interpretable model-agnostic explanation method (LIME) uses surrogate techniques to simulate reasonable precision and provide explanations for a given ML model. However, LIME explanations are limited to tabular, textual, and image data. They cannot be provided for signal data features that are temporally interdependent. Moreover, LIME suffers from critical problems such as instability and local fidelity that prevent its implementation in real-world environments. In this work, we propose Bootstrap-LIME (B-LIME), an improvement of LIME, to generate meaningful explanations for ECG signal data. B-LIME implies a combination of heartbeat segmentation and bootstrapping techniques to improve the model’s explainability considering the temporal dependencie... [more]

In order to obtain the damage characteristics of a roadway wall caused by a gas explosion, the damage evaluation theory of a roadway wall under the dynamic and static loads of a gas explosion is analyzed in this paper. Meanwhile, an evaluation method (overpressure−impulse criterion) is selected to evaluate the damage of the roadway wall under the impact load of the gas explosion. A mathematical model and a physical analysis model of the roadway wall damage are established by LS-DYNA software. The dynamic response of the roadway wall caused by the dynamic and static loads of the gas explosion is numerically simulated. The overpressure and impulse of gas explosion propagation are measured, while the damage data of the roadway wall under different overpressure and impulse loads are obtained. The P-I curves of the roadway wall under different dynamic and static loads of gas explosion are drawn. The fitting formula of P-I curves of the roadway wall is obtained. The influence of different ge... [more]

This paper proposes a timetable coordination method for transfer problems in a bus transit system. With a given bus network, a stochastic mixed-integer linear programming (MILP) model has been formulated to obtain coordinated bus timetables with the objective of minimizing a weighted sum of the average value of total waiting time and its average absolute deviation value, allowing for random bus travel time. The vital decision variable is the terminal departure offset time of each target bus trip within a certain off-peak period. The robust MILP model can also be used to solve the first-bus transfer problem with the introduction of several new linear constraints. A solution method based on the Monte Carlo simulation has been developed to solve the MILP model. Numerical experiments have been conducted for different scenarios. The results indicate that bus timetables coordinated by the developed model are capable of substantially reducing waiting time for transfer and non-transfer passeng... [more]

This work established a finite element analysis (FEA) model of an inserted tooth-type slip assembly under bear setting load and axial load, calculated the differences between the inserted teeth of the sidetracking packer slip-formed furrow shapes on the casing face, and analyzed the setting reliability of the inserted tooth slip sidetracking packer. The orthogonal optimization analysis of the structural parameters of the sidetracking packer was carried out on the basis of the furrow effect. Finally, the setting experiment was conducted with the inserted tooth slip sidetracking packer developed to verify correctness of the FEA model and the simulation results. The results show that in the FEA and calculation of the setting process of the inserted tooth-type slip, it is not only necessary to consider the furrow friction coefficient, but also the effect of the ridge on the furrow friction coefficient. The corresponding furrow friction coefficient varies according to the different furrow e... [more]

This paper proposed a semi-theoretical model to quantitatively predict leakage rate of tubing and casing premium connections. The geometric parameters of the sealing surface profile approximated by a sinusoidal micro-convex surface were first obtained based on the random normal distribution sampling method. With the actual area prediction formula for elastic−plastic contact of an axisymmetric sinusoidal micro-convex body based on the equivalent simulation principle, the circumferential leakage width and radial average leakage height of the micro-leakage channel between sealing surfaces were then acquired with the surface roughness and geometric mean contact pressure. At last, the actual micro-leakage rate of the premium connection was derived by considering the non-uniform contact pressure distribution between sealing surfaces. An example was investigated to validate the model and reveal the sealing and leakage characteristics, and anti-leakage measures were proposed. The results show... [more]

Fluid bed granulation is faced with a high level of complexity due to the simultaneous occurrence of agglomeration, breakage, and drying. These complexities should be thoroughly investigated through particle−particle, particle−droplet, and particle−fluid interactions to understand the process better. The present contribution focuses on the importance of drying and the associated challenges when modeling a granulation process. To do so, initially, we will present a summary of the numerical approaches, from micro-scale to macro-scale, used for the simulation of drying and agglomeration in fluid bed granulators. Depending on the modeled scale, each approach features several advantages and challenges. We classified the imposed challenges based on their contributions to the drying rate. Then, we critically scrutinized how these challenges have been addressed in the literature. Our review identifies some of the main challenges related to (i) the interaction of droplets with particles; (ii) t... [more]

The transmission in automobiles is the core component to ensure operational stability. Heat accumulation in the meshing process will reduce the transmission efficiency and affect the service life. Here, the essential physical process to improve transmission heat dissipation is the dynamic evolution process and the thermal transfer characteristics of lubricating oil fields during gear meshing. This paper presents a modeling and solving method for gear meshing lubrication and thermal transfer features based on the volume of the fluid model and piecewise linear interface construction (VOF-PLIC). The dynamic mesh technique combines spring smoothing and reconstruction to optimize the numerical solution process. The dynamic evolution law of gear meshing lubrication and thermal transfer is obtained by analyzing the lubrication evolution process under different speed/steering conditions. The results show that the proposed modeling and solving method could well reveal the lubrication and therma... [more]

In the process of metal cutting, a large amount of chips that are difficult to reuse will be produced, resulting in resource waste. As a novel metal forming process, cryogenic-temperature extrusion machining (CT-EM) can directly process chips into usable fins with a surface micro-groove structure, which has the advantage of high efficiency, energy saving and flexibility. In this study, the effects of four parameters (compression ratio λ, rake angle of the tool α, friction coefficient μ and the constraining tool corner radius R) on the effective stress, temperature and formability of micro-groove fins produced by CT-EM and room-temperature extrusion machining (RT-EM) are investigated. The results show that the maximum effective stress and formability of CT-EM are larger than that of RT-EM, which indicates that CT-EM has greater advantages in the preparation of micro-groove fins. At a λ of 0.7, the formability of CT-EM is the best. Reducing the λ and α, or increasing the μ, can improve t... [more]

Conventionally, fused deposition modeling (FDM) 3D printing allows for multiple color printing, but it is limited to only various monochromatic colors. Consequently, the effect of progressive color transition cannot be reflected. To produce the progressive 3-D color printing effect, the only solution is to implement stereolithography technology, which is particularly expensive. Therefore, the aim of this paper is to develop a color mixing mechanism to be incorporated into an FDM 3D printer, which is relatively inexpensive. The underlying idea is to pre-mix the color so that the FDM 3D printer can produce a progressive color printing effect. Three conceptual color mixing mechanisms are designed, i.e., a triangular stirring shaft, a rectangular spoiler stirring shaft, and a spiral blade stirring shaft. The mixing process is modeled based on the non-Newtonian fluid theory, in which the Carreau model is used to simulate the motion of pseudoplastic fluids in FDM 3D printing under forced mix... [more]

Liquid−liquid extraction has proven to be an aid in biologics manufacturing for cell and component separation. Because distribution coefficients and separation factors can be appropriately adjusted via phase screening, especially in aqueous two-phase systems, one stage is frequently feasible. For biologics separation, aqueous two-phase systems have proven to be feasible and efficient. The simple mixer−settler equipment type is still not standard in biologics manufacturing operations. Therefore, a scalable digital twin would be of aid for operator training, process design under the regulatory demanded quality by design approach for risk analysis, design and control space definition, and predictive maintenance. Autonomous operation is achieved with the aid of process analytical technology to update the digital twin to real time events and to allow process control near any optimal operation point. Autonomous operation is first demonstrated with an experimental feasibility study based on a... [more]

Automated crack detection technologies based on deep learning have been extensively used as one of the indicators of performance degradation of concrete structures. However, there are numerous drawbacks of existing methods in crack segmentation due to the fine and microscopic properties of cracks. Aiming to address this issue, a crack segmentation method is proposed. First, a pyramidal residual network based on encoder−decoder using Omni-Dimensional Dynamic Convolution is suggested to explore the network suitable for the task of crack segmentation. Additionally, the proposed method uses the mean intersection over union as the network evaluation index to lessen the impact of background features on the network performance in the evaluation and adopts a multi-loss calculation of positive and negative sample imbalance to weigh the negative impact of sample imbalance. As a final step in performance evaluation, a dataset for concrete cracks is developed. By using our dataset, the proposed me... [more]