In today’s urban hotspot regions, service traffic exhibits dynamic variations in both time and location. Traditional fixed macro base stations (FMBSs) are unable to meet these dynamic demands due to their fixed coverage and capacity. Therefore, this paper introduces a novel algorithm for the joint optimization of the placement of terrestrial vehicle-mounted mobile micro base stations (mBSs), the correlation of service clusters (SCs) with mBSs, and resource assignments. The objective is to maximize the matching degree between network capacity and service demands while adhering to constraints related to the power, coverage, and bandwidth of mBSs, as well as the data rate required for the services. Additionally, we investigate the mobility of the mBSs towards the SCs in the spatiotemporal changing service demand network and obtain optimal trajectories for the mBSs. We begin by formulating the problem of maximizing the matching degree by analyzing the capacity provided by the base stations... [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 present communication is focused predominantly on important R&D solutions relevant to renewable energy technologies covering the following: (i) Innovative heat transfer fluid and thermal storage technology based on a molten salt mixture developed by ENEA for large-scale heat storage. The system uses a parabolic trough collector, compared with diathermic oil, which allows higher operating temperature, resulting in significant benefits to the plant’s operation, safety and the environment. (ii) The world’s first solar disk powered by air micro turbine developed by ENEA. (iii) An innovative steam-explosion prototype plant installed at ENEA for the pre-treatment of lignocellulosic biomass and the fractionation of bio components to generate ethanol from lignocellulosic material using hemicellulose and lignin. (iv) The production of hydrogen-enriched biogas using steam as the gasification agent, which helps in obtaining nearly nitrogen-free product gas and with a high calorific value of a... [more]

In intelligent process monitoring and fault detection of the modern process industry, conventional methods mostly consider singular characteristics of systems. To tackle the problem of suboptimal incipient fault detection in nonlinear dynamic systems with non-Gaussian distributed data, this paper proposes a methodology named Gap-Mixed Kernel-Dynamic Canonical Correlation Analysis. Initially, the Gap metric is employed for data preprocessing, followed by fault detection utilizing the Mixed Kernel-Dynamic Canonical Correlation Analysis. Ultimately, fault identification is conducted through a contribution method based on the T2 statistic. Furthermore, a comparative analysis was conducted using Canonical Variate Analysis, Dynamic Canonical Correlation Analysis, and Mixed Kernel-Dynamic Canonical Correlation Analysis on the Tennessee Eastman process. Experimental results indicate varying degrees of improvements in the detection rate, false alarm rate, missed detection rate, and detection ti... [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]

Material treatment in pulsation reactors (PRs) offers the potential to synthesize powdery products with desirable properties, such as nano-sized particles and high specific surface areas, on an industrial scale. These exceptional material characteristics arise from specific process parameters within PRs, characterized by the periodically varying conditions and the resulting enhanced heat and mass transfer between the medium and the particulate material. Understanding flame behavior and the re-ignition mechanism is crucial to controlling the efficiency and stability of the pulse combustion process. In order to accomplish this objective, an investigation was conducted into flame behavior within the combustion chamber of a Helmholtz-type pulsation reactor. The study was focused on primarily analyzing the flame propagation process and examining flame velocity throughout the operational cycle of the reactor. Two optical methods—natural flame luminosity (NFL) and particle image velocimetry (... [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]

The purity of crude glycerol, a by-product of biodiesel production, may be as low as 50%. Thus, it has relatively low economic value without previously applying adequate physical purification or chemical conversion processes. A solid-state sulfated acid photocatalyst, TiO2/SO42− was prepared in this study to catalyze the chemical conversion of bioglycerol with acetic acid to produce an antifreeze of glycerine acetate to improve the low-temperature fluidity of liquid fuel. The experimental results show that similar X-ray intensity structures appeared between the catalysts of TiO2/SO42− and SO42−. An infrared spectra analysis using a Fourier transform infrared (FTIR) spectrometer confirmed the successful sintering of SO42− and ligating with TiO2 for preparing TiO2/SO42−. The effects of the photocatalyst were further excited by the irradiation of ultraviolet light. The highest weight percentage of glycerine acetate was obtained under a reaction time and reaction temperature of 10 h and 12... [more]

Tight sandstone oil reservoirs in the Upper Triassic Yanchang Formation of the Ordos Basin are the most promising exploration and development fields owing to their huge production potential. Even though they have received considerable attention in recent years, common productivity prediction methods were not well applied during pre-development owing to their strong internal heterogeneity. In this study, the factors influencing oil production of the Chang 9 Member in the Jiyuan area were investigated and summarized based on drill cores, such as sediment characteristic analysis, lithofacies analysis, other analytical tests, and conventional logging curves. The findings show that fine-sandstone reservoirs with smooth sand body architectures are the main types of tight sandstone commercial oil reservoirs. Furthermore, having high porosity and oil content are prerequisites for commercial oil reservoirs, and the cumulative thickness of effective reservoirs serves as a crucial resource base f... [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]

During perforation in ultra-deep wells, the blast shock wave can induce dynamic responses of the perforating tubing, leading to potential downhole accidents such as vibration, deformation, and even fracture of the perforating tubing. To comprehend the dynamic response characteristics of the perforating tubing under blast impact load, we conducted a joint finite element simulation using SolidWorks, Hypermesh, and LS-DYNA. The simulation included deformation analysis, motion analysis, and strength analysis of the perforating tubing. By analyzing these factors, we obtained the change in velocity, acceleration, and equivalent stress of the perforating tubing over time under the blast load. The finite element analysis indicates the following: (a) the bottom of the perforating tubing is susceptible to significant tension compression cycle; (b) the velocity amplitude variation is smallest at the top of the perforating tubing, while the frequency and peak values of velocity changes are maximal... [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]

Metal processing may benefit from innovative lean-and-green datacentric engineering techniques. Broad process improvement opportunities in the efficient usage of materials and energy are anticipated (United Nations Sustainable Development Goals #9, 12). A CO2 laser cutting method is investigated in this study in terms of product characteristics (surface roughness (SR)) and process characteristics (energy (EC) and gas consumption (GC) as well as cutting time (CT)). The examined laser cutter controlling factors were as follows: (1) the laser power (LP), (2) the cutting speed (CS), (3) the gas pressure (GP) and, (4) the laser focus length (F). The selected 10mm-thick carbon steel (EN10025 St37-2) workpiece was arranged to have various geometric configurations so as to simulate a variety of real industrial milling demands. Non-linear saturated screening/optimization trials were planned using the Taguchi-type L9(34) orthogonal array. The resulting multivariate dataset was treated using a co... [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]

A greater H/C ratio and energy demand are factors that boost natural gas conversion into electricity. The Brazilian offshore pre-salt basin has large reserves of CO2-rich associated gas. Selling this gas requires high-depth long-distance subsea pipelines, making gas-to-pipe costly; in particular, gas-to-wire instead of gas-to-pipe is more practical since it is easier to transmit electricity via long subsea distances. This research proposes and investigates an innovative low-emission gas-to-wire alternative consisting of installing supercritical direct-methane-to-methanol upstream to gas-to-wire, which is embedded in an exhaust-gas recycle loop that reduces the subsequent carbon capture costs. The process exports methanol and electricity from remote offshore oil-and-gas fields with available CO2-rich natural gas, while capturing CO2. Techno-economic, thermodynamic and lost work analyses assess the alternative. Supercritical direct-methane-to-methanol is conducted in supercritical water... [more]

In this study, the thermal transition of seaweed Saccharina latissima (raw and blanched) during drying and quality stabilization was considered in view of understanding physico-chemical changes, color changes, sorption changes and thermal property changes with respect to drying kinetics. The variations in the effective moisture diffusivity coefficient with shrinkage changes and temperature lie between 1.0 and 5.0 × 10−10 m2 s−1 (raw) and 0.5 and 3.6 × 10−10 m2 s−1 (blanched), respectively. Noticeable physical and chemical changes were observed during longer drying times, especially in the case of blanched seaweeds. At the temperature of 38.0 °C, a more yellow-colored product was obtained from raw form input materials. The blanched seaweeds accumulated moisture in a linear manner with an increase in the relative humidity of the drying air in the range of 20.0~80.0%, which resulted in high level of hysteresis between the sorption and desorption behavior. Shrinkage changes during the dryi... [more]

Centrifugal granulation technology using a spinning cup opens a potential way to recycle steel slag that is currently difficult to reuse. The objective of this research was to study the flow characteristics of a molten slag−metal mixture that was produced during smelting reduction in molten steel slag, passing over a spinning cup, so as to explore the feasibility of using centrifugal granulation technology to treat the steel slag. This was achieved by developing and implementing a computational fluid dynamics (CFD) model that incorporated free-surface multiphase flow to predict the thickness of the liquid slag film at the edge of the spinning cup (slag film thickness for short), which was an important parameter for estimating the size of the slag particles resulting from centrifugal granulation of the molten slag−metal mixture. The influences of various relevant parameters, including spinning cup diameter, slag feeding rate, cup spinning speed, etc., on the slag film thickness were ana... [more]

Biomimetic ligands are synthetic compounds that mimic the structure and binding properties of natural biological ligands. The first uses of textile dyes as pseudo-affinity ligands paved the way for the rational design and de novo synthesis of low-cost, non-toxic and highly stable triazine-scaffolded affinity ligands. A novel method to assess and enhance protein stability, employing triazine-based biomimetic ligands and using cutinase from Fusarium solani pisi as a protein model, has been previously reported. This innovative approach combined the concepts of molecular modeling and solid-phase combinatorial chemistry to design, synthesize and screen biomimetic compounds able to bind cutinase through complementary affinity-like interactions while maintaining its biological functionality. The screening of a 36-member biased combinatorial library enabled the identification of promising lead ligands. The immobilization/adsorption of cutinase onto a particular lead (ligand 3′/11) led to a not... [more]

To reduce pollution and improve the efficiency of coal resource utilization, this study proposed an integrated process for smelting reduction ironmaking and coal gasification. A multi-zone constrained mathematical model, based on heat and mass balance calculations, was developed to predict the energy and material flows required to produce 1 ton of hot metal. Two scenarios were examined: one using pure O2 as the gasification agent (referred to as the non-hydrogen-rich process) and the other using a combination of pure O2 and pure steam (referred to as the hydrogen-rich process). In the non-hydrogen rich process, as the PCR (Post Combustion Ratio) varies from 0% to 8%, the total coal consumption, O2 consumption, and volume of exported gas decrease by 57%, 57% and 53%, respectively. In the hydrogen-rich process, as the H2 content increases from 30% to 50%, the exported gas volume increases by 38%. The upper limit of H2 content in the SRV (Smelting Reduction Vessel) off-gas is mainly deter... [more]

In recent years, the Broad Learning System (BLS) has been acknowledged for its potential to revolutionize traditional artificial intelligence methods due to its short training time, strong interpretability, and simple structure. In the evolution of BLS, Prof. C. L. Philip Chen’s team introduced the Fuzzy Broad Learning System (FBLS) by replacing the feature nodes of BLS with fuzzy subsystems, thereby further reducing the training time. However, the traditional FBLS, with its straightforward structure, falls short in achieving higher fault diagnosis accuracy when handling raw vibration signals. This paper presents a bearing fault diagnosis approach employing multi-domain feature selection and the fuzzy broad learning system (MS-FBLS), aiming to enhance the diagnostic accuracy of FBLS through multi-domain feature selection. Primarily, a set of 49 features spanning time domain, frequency domain, time-frequency domain, and entropy values is extracted from the original vibrational signals.... [more]

Regarding the difficulty of extracting fault information in the faulty status of UAV (unmanned aerial vehicle) engines and the high time cost and large data requirement of the existing deep learning fault diagnosis algorithms with many training parameters, in this paper, a small-sample transfer learning fault diagnosis algorithm is proposed. First, vibration signals under the engine fault status are converted into a two-dimensional time-frequency map by multiple simultaneous squeezing S-transform (MSSST), which reduces the randomness of manually extracted features. Second, to address the problems of slow network model training and large data sample requirement, a transfer diagnosis strategy using the fine-tuned time-frequency map samples as the pre-training model of the ResNet-18 convolutional neural network is proposed. In addition, in order to improve the training effect of the network model, an agent model is introduced to optimize the hyperparameter network autonomously. Finally, e... [more]

Pool boiling heat transfer is recognized as an exceptionally effective method, widely applied across various industries. The adoption of non-azeotropic binary mixtures aligns with the environmental objectives of modern industrial development and enhances the coefficient of performance (COP) in numerous systems. Therefore, investigating the boiling heat transfer characteristics of these mixtures is crucial to improving their industrial usability. In this study, mixtures of ethylene glycol and deionized water (EG/DW) in varying concentrations were chosen as the working fluids. A comprehensive experimental setup was developed, followed by a series of experiments to assess their pool boiling performance. Simultaneously, the thermophysical parameters of these mixtures underwent detailed examination and analysis. The research revealed that the concentration of EG in the mixture markedly affects its thermal properties and temperature glide, both of which are crucial in influencing the heat tr... [more]