It is important for data modeling to comply with a data observation window of physical variables behind the data. In this paper, a multivariate data alignment method is proposed to follow different time scales and different role effects. First, the length of the sliding windows is determined by the frequency characteristics of the time-series reconstruction. Then, the time series is aligned to the length of the window by a sequence-to-sequence neural network. This neural network is trained by replacing the loss function with dynamic time warping (DTW) in order to prevent the losses of the time series. Finally, the attention mechanism is introduced to adjust the effect of different variables, which ensures that the data model of the matrix is in accord with the intrinsic relation of the actual system. The effectiveness of the approach is demonstrated and validated by the Tennessee Eastman (TE) model.

This study reports a novel hybrid model for the prediction of six critical process variables of importance in an industrial-scale FCC (fluid catalytic cracking) riser reactor: vacuum gas oil (VGO) conversion, outlet riser temperature, light cycle oil (LCO), gasoline, light gases, and coke yields. The proposed model is developed via the integration of a computational particle-fluid dynamics (CPFD) methodology with artificial intelligence (AI). The adopted methodology solves the first principle model (FPM) equations numerically using the CPFD Barracuda Virtual Reactor 22.0® software. Based on 216 of these CPFD simulations, the performance of an industrial-scale FCC riser reactor unit was assessed using VGO catalytic cracking kinetics developed at CREC-UWO. The dataset obtained with CPFD is employed for the training and testing of a machine learning (ML) algorithm. This algorithm is based on a multiple output feedforward neural network (FNN) selected to allow one to establish correlations... [more]

Effectively managing the quality of iron ore is critical to iron and steel metallurgy. Although quality inspection is crucial, the perspective of sintered surface identification remains largely unexplored. To bridge this gap, we propose a deep learning scheme for mining the necessary information in sintered images processing to replace manual labor and realize intelligent inspection, consisting of segmentation and classification. Specifically, we first employ a DeepLabv3+ semantic segmentation algorithm to extract the effective material surface features. Unlike the original model, which includes a high number of computational parameters, we use SqueezeNet as the backbone to improve model efficiency. Based on the initial annotation of the processed images, the sintered surface dataset is constructed. Then, considering the scarcity of labeled data, a semi-supervised deep learning scheme for sintered surface classification is developed, which is based on pseudo-labels. Experiments show th... [more]

Aiming at addressing the problem of dust generated when grab is unloaded, the flow field characteristics of fugitive dust in an open space were studied and reflected its unstable and complex nonlinear dynamic process. Using coal, sand, and flour as research objects, an experimental model and measurement system for grab unloading were built, and the dust diffusion range, diffusion speed and direction, settling time, dust concentration, and induced wind velocity at different measurement points were compared. The computational fluid dynamics−discrete element method (CFD-DEM) coupling method was adopted, the discrete phase model (DPM) of dust was established, the interaction of the particle, dust, and airflow fields during the unloading process of the grab was further studied, and the distribution and diffusion laws of the induced airflow and dust were obtained. The acquisition of flow field characteristics is of great significance for controlling and guiding the orderly deposition of dust... [more]

Recently, theoretical modeling based on rock physics has emerged as a pivotal approach to studying the resistivity of complex fractured−cavernous microstructures. In this work, to study the effects of fractured−cavernous structures on carbonate reservoir resistivity, electrical conductivity models were developed based on the effective medium theory and Ohm’s Law, and theoretical simulations were performed to examine how the porosity and resistivity of the rock matrix, the formation water resistivity, and the parameters of the fractured−cavernous microstructure affect the resistivity of rocks saturated with petroleum or water. Furthermore, the modeling results revealed the specific relationships between these factors in petroleum-saturated and water-saturated rocks. For vuggy reservoirs, a significant negative correlation between throat diameter and resistivity was revealed when variations in the rock matrix and formation water resistivity were negligible. Furthermore, the pore shape—es... [more]

The worldwide demand for customized centrifugal pumps in numerous industries is intensifying steadily, posing significant challenges to the traditional design model characterized by extended design cycles, numerous errors, and elevated development costs. To address these issues, this paper introduces an intelligent collaborative design methodology for industrial centrifugal pumps grounded in digital twin (DT) technology. The methodology aims to handle the diversified types and intricate design requirements of industrial pumps and is specifically tailored to predict pump performance through a detailed multi-physics model. This model encapsulates various physical processes, including fluid dynamics, thermodynamics, and structural mechanics, and incorporates the designer’s professional knowledge and experience to support enhanced decision-making. Furthermore, the application of intelligent parametric models has facilitated the interconnected design of pump components. This advancement has... [more]

A photovoltaic (PV)-powered electric motor is used for hose-drawn traveler driving instead of a water turbine to achieve high transmission efficiency. PV power generation (PVPG) is affected by different meteorological conditions, resulting in different power generation of PV panels for a hose-drawn traveler. In the above situation, the hose-drawn traveler may experience deficit power generation. The reasonable determination of the PV panel capacity is crucial. Predicting the PVPG is a prerequisite for the reasonable determination of the PV panel capacity. Therefore, it is essential to develop a method for accurately predicting PVPG. Extreme gradient boosting (XGBoost) is currently an outstanding machine learning model for prediction performance, but its hyperparameters are difficult to set. Thus, the XGBoost model based on particle swarm optimization (PSO-XGBoost) is applied for PV power prediction in this study. The PSO algorithm is introduced to optimize hyperparameters in XGBoost mo... [more]

This paper addresses the pressing need for advanced simulation tools in electric phasor modeling and Smart Grid-Power to X systems. The motivation for this study stems from the critical importance of enhancing the balance between performance and the detailed dynamic representation of the system behavior in the simulations. The identified problem lies in the absence of a comprehensive framework that seamlessly integrates electric phasor DQ0 components into a multi-purpose object-oriented environment. The primary objective of this research is to develop and introduce two simulation libraries, centered around the core component, Electric_DQ0. These libraries aim to establish a robust phasor-based framework, incorporating essential electric components such as sources, loads, branches, power converters, and electric machines. The main goal is to enable dynamic frequency and voltage simulations, particularly focusing on transients in alternators and facilitating Voltage and Frequency Rate of... [more]

Remanufacturing processes are one of the key pillars of the so-called closed-cycle economy. Unfortunately, the design and organization of such processes pose a significant problem, due to, among other things, the high variability of the process as a consequence of both the degree of wear and tear and the quality of the remanufactured components. This article presents a method for optimizing the flow of the brake caliper remanufacturing process in the MTO (make-to-order) model. For the optimization process, the system dynamics (SD) method, which belongs to a group of simulation methods, was used. The developed model allows, in particular, the prediction of the number of components at the input to the regeneration process and the method of defining the size of the transport batch and evaluating its impact on the length of the production cycle of the batch of regenerated products. The issues of staffing management at individual positions and the organization of transport operations with v... [more]

The real-time and accurate recognition of fruits and vegetables is crucial for the intelligent control of fruit and vegetable robots. In this research, apple picking is selected. This study proposed a lightweight, coupon-product, neural-net terminal YOLO algorithm for apple image recognition. Compared with the YOLO series algorithm, the tiny algorithm shows a strong relationship with the calculation speed. In traditional red fruit detection, the recognition time is generally several seconds, which is unacceptable in the real-time system. In this research, a total of 2000 apple images from different environments are used as a dataset for training and testing. The YOLOv4-tiny model is detailed, instructed, and used for the identification. The indicators, such as F1Score (0.92) and mAP (95.5% average), are analyzed by calculating the loss rate, accuracy rate (96.21%), and recall rate (95.47%). Finally, the algorithm shows good accuracy and high speed (no more than 5 ms) in online real-tim... [more]

Solid−liquid separation is a fundamental operation in process engineering and thus an important part of many process chains in the preparation of slurries in the chemical industry and other parts of the industrial environment. For the separation of micron-sized particles which, due to their size, do not settle or settle very slowly in the earth’s gravity field, centrifuges are often used. The preferred choice are often decanter centrifuges because they work continuously and stabilize the process against product fluctuations due to their adjustment possibilities. The design of the apparatus is complex: The main components of the apparatus are the cylindrical-conical bowl, which rotates at a high speed, and a screw located inside the bowl, which rotates in the same direction at a low differential speed to transport the separated solids out of the apparatus. Geometrical properties of the apparatus, as well as the adjustable operating parameters, such as rotational speed or differential sp... [more]

Pressure-driven water injection technology shows significant potential in addressing the key challenges of low-permeability oil reservoirs, improving water flooding development efficiency. Grounded in FDEM theory, this study establishes fluid matrix constitutive equations and employs FDEM to resolve rock stress−strain fields. A numerical simulation method for pressure-driven water injection in low-permeability reservoirs is developed to study the impact of different well pattern densities. The results indicate that the 90° horizontal well pattern using the five-spot method yields optimal outcomes, with approximately 32.32% higher cumulative liquid production than vertical well patterns. The 45° horizontal well pattern with the reversed nine-spot method also performs well, with about 30% higher cumulative liquid production than single-row vertical wells. Pressure-driven water injection improves matrix oil−water permeability and expands water flooding coverage. Based on the pressure grad... [more]

The thermal characteristics of the spindle system for CNC machine tools are influenced by multiple factors which are nonlinear and time-varying. In this paper, a nonlinear time-varying thermal characteristics solving model for the spindle system was established based on the numerical solution method. Through theoretical deduction and data fitting, mathematical models of nonlinear time-varying factors including the friction torque generated by lubricants, convective heat transfer coefficient, and coolant and ambient temperature are constructed. The temperature and displacement of the spindle system at each time step are solved by considering the comprehensive effect of multiple nonlinear time-varying factors. And the actual temperature and axial deformation data of the spindle system are obtained through thermal characteristics detection experiments. By comparing solution results affected by multiple nonlinear time-varying factors and by non time-varying factors with experimental data,... [more]

With the adjustment of energy structure, the utilization of hydrogen energy has been widely attended. China’s carbon neutrality targets make it urgent to change traditional coal-fired power generation. The paper investigates the combustion of pulverized coal blended with hydrogen to reduce carbon emissions. In terms of calorific value, the pulverized coal combustion with hydrogen at 1%, 5%, and 10% blending ratios is investigated. The results show that there is a significant reduction in CO2 concentration after hydrogen blending. The CO2 concentration (mole fraction) decreased from 15.6% to 13.6% for the 10% hydrogen blending condition compared to the non-hydrogen blending condition. The rapid combustion of hydrogen produces large amounts of heat in a short period, which helps the ignition of pulverized coal. However, as the proportion of hydrogen blending increases, the production of large amounts of H2O gives an overall lower temperature. On the other hand, the temperature distributi... [more]

This article is devoted to the further development of a viable technology for low-temperature cryopreservation of reproductive cells of sturgeon fish using acoustic−mechanical fields and intelligent control of the freezing process. Before vitrification begins, the piezoactuator acts on a mixture of cryoprotectant and reproductive cells. This promotes intensive mixing of the cryoprotector and its diffusion through the cell membrane. When vitrification is carried out directly, a phase transition phenomenon is observed, accompanied by crystal formation. This article presents a new mathematical model describing this process as developed by the authors. The corresponding boundary conditions are formulated. Numerical experiments were carried out using the finite element method. It has been established that during vitrification without the use of a cryoprotectant, a sharp temperature jump is observed at the front of the crystalline formation boundary. The use of a cryoprotectant leads to a sl... [more]

The occurrence of slope instability disasters seriously endangers the safety of people’s lives and property in China. Therefore, it is essential to study the slope instability process and the interaction between soil and retaining walls. In this paper, the smoothed-particle hydrodynamics (SPH) method, based on the elastoplastic constitutive model of rock and soil, was used to simulate the entire process of slope instability and the interaction between soil and retaining walls. The model, based on the classical elastic−plastic theory, includes linear elastic deformation and plastic deformation following the non-associated flow rule under the Drucker−Prager (DP) yield criterion. By considering the plastic characteristics of geotechnical materials, this method can accurately simulate the slope movement process. The model was established, calculated, and compared with a slope example, thus verifying its feasibility. Furthermore, the motion response of the retaining wall under different con... [more]

Pyrolysis is a promising disposal method for municipal solid waste (MSW) due to the high-value utilization of the organic components of MSW. Traditional indirect heating has low heat transfer efficiency and requires an increase in the heat exchange area. In this study, a refined numerical simulation model for the pyrolysis of four typical MSW components with high-temperature flue gas was established to study the influence of flue gas on the heat transfer and reaction characteristics of MSW. The temperature distribution and particle size change in different components were obtained, and the effects of flue gas temperature and velocity on the pyrolysis process were analyzed. It was found that the temperature difference of the four components along the bed height direction was about 1.36−1.81 K/mm, and the energy efficiency was about 55−61%. When the four components were uniformly mixed, the temperature increase rates of each component were similar during the pyrolysis process. As the flu... [more]

The multi-layered and complex nature of cellular regulation enhances the need for advanced computational methodologies that can serve as scaffolds for organizing experimental data to facilitate the inference of meaningful relationships [...]

Electrical capacitance volume tomography (ECVT) is an experimental technique capable of reconstructing 3D solid volume fraction distribution inside a sensing region. This technique has been used in fluidized beds as it allows for accessing data that are very difficult to obtain using other experimental devices. Recently, artificial neural networks have been proposed as a new type of reconstruction algorithm for ECVT devices. One of the main drawbacks of neural networks is that they need a database containing previously reconstructed images to learn from. Previous works have used databases with very simple or limited configurations that might not be well adapted to the complex dynamics of fluidized bed configurations. In this work, we study two different approaches: a supervised learning approach that uses simulated data as a training database and a reinforcement learning approach that relies only on experimental data. Our results show that both techniques can perform as well as the cla... [more]

Sulfate radicals are increasingly recognized for their potent oxidative capabilities, making them highly effective in degrading persistent organic pollutants (POPs) in aqueous environments. These radicals excel in breaking down complex organic molecules that are resistant to traditional treatment methods, addressing the challenges posed by POPs known for their persistence, bioaccumulation, and potential health impacts. The complexity of predicting interactions between sulfate radicals and diverse organic contaminants is a notable challenge in advancing water treatment technologies. This study bridges this gap by employing a range of machine learning (ML) models, including random forest (DF), decision tree (DT), support vector machine (SVM), XGBoost (XGB), gradient boosting (GB), and Bayesian ridge regression (BR) models. Predicting performances were evaluated using R2, RMSE, and MAE, with the residual plots presented. Performances varied in their ability to manage complex relationships... [more]

In a gear transmission system in a closed space, the heat transfer between gears and fluids presents highly nonlinear characteristics due to the complex physical processes involved in heat exchange and fluid motion, and constructing and solving the thermodynamic model of the gearbox becomes a task that involves considerable difficulty. This paper takes a conical−cylindrical two-stage gearbox as the research object, proposes a fluid−solid coupled dynamics model based on the lattice Boltzmann (LBM) combined with the large eddy simulation (LES) method, and the adopted lattice model is the D3Q27 velocity model, which is used to numerically simulate the distribution of the flow field inside the gearbox and undertake in-depth research on the fluid motion law of the complex gear transmission system in the enclosed space. The model is solved to reveal the laws determining the gear speed and the effects of the lubricant’s dynamic viscosity and thermal conductivity coefficient on the gear heat d... [more]

This paper researches the heat transfer equation and thermal balance equation of a shell-and-tube evaporator; constructs an accurate mathematical model for the evaporator; and derives equations including detailed and accurate calculation methods for all heat transfer coefficients, such as the refrigerant side heat transfer coefficient, water side heat transfer coefficient, refrigerant kinematic viscosity, density, and specific enthalpy. Adopting this approach involves fitting the relationships between the density, thermal conductivity, kinematic viscosity, and enthalpy of R134a refrigerants in saturated vapor and liquid states. The relationships between superheated gas enthalpy, density, and temperature were also assessed, and heat transfer coefficients were obtained through calculation methods and microelement heat transfer relationships in both the single-phase and two-phase zones, matching empirical formulas concerning the relationship between superheated enthalpy and temperature. N... [more]

To address the deformation and instability characteristics of a formation after an offshore shallow gas well blowout, a theoretical model of formation deformation caused by shallow gas blowouts was constructed, based on porous elastic medium theory and incorporating the sand-out erosion criterion. The spatiotemporal dynamics of formation subsidence were then investigated, and deformation patterns during a blowout were analyzed under various factors. The results indicate that, following a blowout, a shallow gas formation near a borehole experiences significant subsidence and uplift at the upper and lower ends, with the maximum subsidence values at 12 h, 24 h, 36 h, and 48 h post blowout being 0.072 m, 0.132 m, 0.164 m, and 0.193 m, respectively. The overlying rock layer forms a distinctive “funnel” shape, exhibiting maximum subsidence at the borehole, while more distant strata show uniform subsidence. The effective stress within the shallow gas stratum and surrounding rock layers increa... [more]

The regression model has higher requirements for the quality and balance of data to ensure the accuracy of predictions. However, there is a common problem of imbalanced distribution in real datasets, which directly affects the prediction accuracy of regression models. In order to solve the problem of data imbalance regression, considering the continuity of the target value and the correlation of the data and using the idea of optimization and confrontation, we propose an IRGAN (imbalanced regression generative adversarial network) algorithm. Considering the context information of the target data and the disappearance of the deep network gradient, we constructed a generation module and designed a composite loss function. In the early stages of training, the gap between the generated samples and the real samples is large, which easily causes the problem of non-convergence. A correction module is designed to train the internal relationship between the state and action as well as the subse... [more]

This study conducts a theoretical exploration of the free radical polymerization of polydimethylsiloxane homopolymers with a methyl methacrylate end group (PDMS-MA). To achieve this, a methodology is developed to model and simulate experimental data previously reported by one of the authors. The model incorporates a typical chain reaction mechanism, encompassing initiation, propagation, chain transfer, and termination stages. The resulting ordinary differential equations from this mechanistic approach are numerically integrated over time. Employing a semi-heuristic procedure, the study derives estimated values for the diffusive steps of termination (ktd) and propagation (kpd). Methodological accuracy is assessed through a comparison of the mathematical model results and experimental data. This evaluation includes the estimation of conversion and the average molecular weight (both number (Mn) and weight (Mw)) at three distinct monomer concentrations, considering a 4.78% mol initiator-to... [more]