By employing a specific particle interaction theory and a high-precision equation of states for the liquid and vapor phases of H2, respectively, a new H2 solubility model in pure water and aqueous NaCl solutions is proposed in this study. The model established by fitting the experimental data of H2 solubility can be used to estimate H2 solubility in pure water at temperatures and pressures of 273.15−423.15 K and 0−1100 bar, respectively, and in salt solutions (NaCl concentration = 0−5 mol/kg) at temperatures and pressures of 273.15−373.15 K and 0−230 bar, respectively. By adopting the theory of liquid electrolyte solutions, the model can also be used to predict H2 solubility in seawater without fitting the experimental data of a seawater system. Within or close to experimental data uncertainty, the mean absolute percentage error between the model-predicted and experimentally obtained H2 solubilities was less than 1.14%.

Condition monitoring of high voltage apparatus is of much importance for the maintenance of electric power systems. Whether it is detecting faults or partial discharges that take place in high voltage equipment, or detecting contamination and degradation of outdoor insulators, deep learning which is a branch of machine learning has been extensively investigated. Instead of using hand-crafted manual features as an input for the traditional machine learning algorithms, deep learning algorithms use raw data as the input where the feature extraction stage is integrated in the learning stage, resulting in a more automated process. This is the main advantage of using deep learning instead of traditional machine learning techniques. This paper presents a review of the recent literature on the application of deep learning techniques in monitoring high voltage apparatus such as GIS, transformers, cables, rotating machines, and outdoor insulators.

Amongst energy-related CO2 emissions, electricity is the largest single contributor, and with the proliferation of electric vehicles and other developments, energy use is expected to increase. Load forecasting is essential for combating these issues as it balances demand and production and contributes to energy management. Current state-of-the-art solutions such as recurrent neural networks (RNNs) and sequence-to-sequence algorithms (Seq2Seq) are highly accurate, but most studies examine them on a single data stream. On the other hand, in natural language processing (NLP), transformer architecture has become the dominant technique, outperforming RNN and Seq2Seq algorithms while also allowing parallelization. Consequently, this paper proposes a transformer-based architecture for load forecasting by modifying the NLP transformer workflow, adding N-space transformation, and designing a novel technique for handling contextual features. Moreover, in contrast to most load forecasting studies... [more]

Two-phase expansion is the process where a fluid undergoes a pressure drop through or in the liquid−vapor dome. This operation was historically avoided. However, currently it is studied for a multitude of processes. Due to the volume increase in volumetric expanders, a pressure drop occurs in the fluid resulting in flashing phenomena occurring. These phenomena have been studied before in other processes such as two-phase flows or static flash. However, this has not been extensively studied in volumetric expanders and is mostly neglected. Even if data has shown this is not always neglectable depending on the expander type. The thermal non-equilibrium occurring can be modeled on different principles of flashing flows, such as the mixture model, boiling delay model, and homogeneous relaxation model. The main application area in current literature for volumetric two-phase expansion machines, is in low-temperature two-phase heat-to-power cycles. These cycles have shown benefit over classic... [more]

The Mackenzie Delta (MD) is a permafrost-bearing region along the coasts of the Canadian Arctic which exhibits high sub-permafrost gas hydrate (GH) reserves. The GH occurring at the Mallik site in the MD is dominated by thermogenic methane (CH4), which migrated from deep conventional hydrocarbon reservoirs, very likely through the present fault systems. Therefore, it is assumed that fluid flow transports dissolved CH4 upward and out of the deeper overpressurized reservoirs via the existing polygonal fault system and then forms the GH accumulations in the Kugmallit−Mackenzie Bay Sequences. We investigate the feasibility of this mechanism with a thermo−hydraulic−chemical numerical model, representing a cross section of the Mallik site. We present the first simulations that consider permafrost formation and thawing, as well as the formation of GH accumulations sourced from the upward migrating CH4-rich formation fluid. The simulation results show that temperature distribution, as well as... [more]

The efficient utilization of energy in rich fuel detonation processes and the effective control method of soot are important topics in combustion research. In this paper, we numerically study the detonation wave behavior of acetylene−air systems in rich fuel condition by using a reduced reaction mechanism. The non-stiff terms of the governing equations are solved explicitly using the gas kinetic scheme, and the stiff terms are solved implicitly. Our results show that the acetylene pyrolysis is the dominant reaction process. The oxidation reaction is exploited to initiate the reaction induction process, providing the required energy to overcome the potential energy barrier. The secondary detonation structure is due to the stable interaction of the transverse waves and the combined action of the vinyl reaction system, thus effectively improve the energy release rate and providing a powerful solution for the fuel-rich high-energy release of advanced heat engines. The area of the unreacted... [more]

The heat pump system has been widely used in residential and commercial applications due to its attractive advantages of high energy efficiency, reliability, and environmental impact. The massive exergy loss during the isenthalpic process in the expansion valve is a major drawback of the heat pump system. Therefore, the Tesla turbine exergy analysis in terms of transiting exergy efficiency is investigated and integrated with the transcritical heat pump system. The aim is to investigate the factors that reduce exergy losses and increase the coefficient of performance and exergy efficiency. The contribution of this paper is twofold. First, a three-dimensional numerical analysis of the supercritical CO2 flow simulation in the Tesla turbine in three different geometries is carried out. Second, the effect of the Tesla turbine on the coefficient of performance and exergy efficiency of the heat pump system is investigated. The effect of the rotor speed and disk spacing on the Tesla turbine po... [more]

Pre-chamber turbulent jet ignition represents one of the most promising techniques to improve spark ignition engines efficiency and reduce pollutant emissions. This technique consists of igniting the air-fuel mixture in the main combustion chamber by means of several hot turbulent flame jets exiting a pre-chamber. In the present study, the combustion process of a 4-stroke, gasoline SI, PFI engine equipped with a passive pre-chamber has been investigated through three-dimensional CFD (Computational Fluid Dynamics) analysis. A detailed chemistry solver with a reduced reaction mechanism was employed to investigate ignition and flame propagation phenomena. Firstly, the combustion model was validated against experimental data for the baseline engine configuration (i.e., without pre-chamber). Eventually, the validated numerical model allowed for predictive simulations of the pre-chamber-equipped engine. By varying the shape of the pre-chamber body and the size of pre-chamber orifices, differ... [more]

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]