A machine is described as an assembly that has a drive system installed or is planned to have a drive system installed and that is constituted of linked elements or components, at least one of which moves, that are connected for a particular application (ISO12100). Different types of risks are present in machines, and exposure to them can cause harm or even death. When risk has been adequately reduced, machinery safety considers a machine’s ability to complete its intended duty throughout its life cycle. A literature review was carried out using “safety of machinery” as a keyword, which produced an analysis of 29 papers published from 2008 to 2024. The papers were examined through bibliometric analysis of the year of publication, country, citation statistics, and study of the keywords. These studies were classified into accident analysis papers, papers focused on the normative, papers that addressed risk assessment tools, and papers that conducted quantitative research. In addition, a... [more]

Micro−nanobubbles (MNBs) can generate ·OH in situ, which provides a new idea for the safe and efficient removal of pollutants in water supply systems. However, due to the difficulty in obtaining stable MNBs, the generation efficiency of ·OH is low, and the removal efficiency of pollutants cannot be guaranteed. This paper reviews the application research of MNB technology in water security from three aspects: the generation process of MNBs in water, the generation rule of ·OH during MNB collapse, and the control mechanisms of MNBs on pollutants and biofilms. We found that MNB generation methods are divided into chemical and mechanical (about 10 kinds) categories, and the instability of the bubble size restricts the application of MNB technology. The generation of ·OH by MNBs is affected by the pH, gas source, bubble size, temperature, and external stimulation. And the pH and external stimulus have more influence on ·OH generation in situ than the other factors. Adjusting the pH to alkal... [more]

This paper studies the use of varying threshold in the statistical process control (SPC) of batch processes. The motivation is driven by how when multiple phases are implicated in each repetition, the distributions of the features behind vary with phases or even the time; thus, it is inconsistent to uniformly bound them by an invariant threshold. In this paper, we paved a new path for learning and monitoring batch processes based on an efficient framework integrating a model termed conditional dynamic variational auto-encoder (CDVAE). Phase indicators are first used to split the data and are then separated, serving as an extra input for the model in order to alleviate the learning complexity. Dissimilar to the routine using features across all timescales, only features relevant to local timestamps are aggregated for threshold calculation, producing a varying threshold that is more specific for the process variations occurring among the timeline. Leveraged upon this idea, a fault detect... [more]

Sustainable energy presently represents the energy of the future, which should be based on the application respecting the importance of energy priorities, increasing regional self-sufficiency, regional control of energy, and regulation of resource use. In the area of energy supply, the use of RES has been increasingly popular, mainly due to the instability in the energy market and the political situation worldwide. Paper’s ambition is to evaluate the efficiency of the selected RES use in the specific conditions of Slovakia, with the aim to achieve the EU targets. This is important due to the increasing use of RES in Slovakia. The objective of this paper is achieved through an analysis of the energy profit of the RES system, comparing the costs of the proposed solutions. The evaluation is carried out by calculating the energy and economic efficiency of three possible buildings used in the research. Using the data obtained, the results show the most suitable alternative for each building... [more]

The 1515 mining face in Yongming Coal Mine was upward mined across half of the goaf along the panel direction. In this paper, the methods of field measurement, theoretical analysis, and numerical simulation were used to study the overlying rock fracture structure, support load characteristics, and the mechanism of mine pressure behavior across half of the goaf. The results indicate that the support load of the 1515 upward mining face across half of the goaf along the panel direction exhibits distinct zoning characteristics. The maximum support load is 1.37 times the minimum support load. The development height of the roof separation in the up-mining area is 1.74 times that in the entity coal area, at 9.1 m and 5.22 m respectively. The height of separation and hanging roof length increase and decrease, respectively, along the initial rock fracture area, tensile fracture area, structural fracture area, and compacted fracture area. Based on the definition of the variation coefficient “m”... [more]

Natural gas hydrate reservoirs, with shallow burial, poor cementation, and low strength, are prone to submarine landslides triggered by hydrate decomposition during extraction. Prior studies have inadequately considered factors such as the dynamic decomposition of hydrates during depressurization, and its impacts on the reservoir’s geomechanical properties. In this paper, a coupled thermal−hydraulic−mechanical−chemical mathematical model of hydrate decomposition is proposed, and the dynamic geomechanical response and the effect of hydrate decomposition on seafloor settlement and slope destabilization during the process of depressurization mining are analyzed by combining the strength discount method with the example of a hydrate-bearing seafloor slope in the Shenhu area. Furthermore, the study employs an orthogonal experimental design along with range and variance analysis to gauge the impact of critical factors (degree of hydrate decomposition, seawater depth, hydrate reservoir burial... [more]

Steel slag micronized powder, granulated blast furnace slag, and cement were used as cementitious materials to prepare a foamed lightweight soil for roadbed filling to reduce the settlement and additional stress of the foundation and to solve the environmental problems caused by the storage of large amounts of steel slag. However, the instability of steel slag and the multi-angular nature of its surface limit the resource utilization of steel slag. Currently, concrete technology is unable to achieve a large amount of steel slag. Therefore, it is necessary to deeply explore the influence of steel slag content and the specific surface area of steel slag on the working performance, compressive strength, durability, and micro-mechanism of foam light soil. Through the modification of steel slag and the improvement of the production process, the preparation of foam light soil with a large amount of steel slag can be realized. In this study, the foamed lightweight soil with 1.0 Mpa was prepar... [more]

Traditional data-driven soft sensor methods can be regarded as an optimization process to minimize the predicted error. When applying the mean squared error as the objective function, the model tends to be trained to minimize the global errors of overall data samples. However, there are deviations in data from practical operation, in which the model performance in the estimation of the local variations in the target parameter worsens. This work presents a solution to this challenge by considering higher-order moments of prediction residuals, which enables the evaluation of deviations of the residual distribution from the normal distribution. By embedding constraints on the distribution of residuals into the objective function, the model tends to converge to the state where both stationary and deviation data can be accurately predicted. Data from the Tennessee Eastman process and an industrial cracking furnace are considered to validate the performance of the proposed modeling method.

This paper presents the preparation and characterization of bentonite coated with hydroxide double lamellar Mg/Al-bentonite and Zn/Al-bentonite as a potential adsorbent material. The coating process involved co-precipitation of mixed metal nitrate solution (Mg-Al) or (Zn-Al), followed by immersion of bentonite (B-Na+) dispersion. The structures and morphologies of the coated bentonites were characterized using XRD, FTIR, BET, and SEM analysis. The results of the BET analysis indicate that Mg/Al-bentonite and Zn/Al-bentonite have larger surface areas and pore volumes compared to bentonite alone. Specifically, the surface area of Mg/Al-bentonite is 209.25 m2/g with a pore volume of 0.423 cm3/g, while Zn/Al-bentonite has a surface area of 175.95 m2/g and a pore volume of 0.313 cm3/g. In contrast, the surface area and pore volume of bentonite alone are 110.43 m2/g and 0.132 cm3/g, respectively. The Mg/Al-bentonite reaches 85% uptake within 3 h (equivalent to 724.20 mg/g at 25 °C and pH 7),... [more]

A novel self-assembly approach was employed to produce micro-spherical composite energetic material (EM) comprising 2,4,6,8,10,12-Hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane/nitrocellulose (CL-20/NC) via the spray-drying method, with precise control over parameters such as droplet diameter, ambient temperature, and nozzle injection rate. In this method, NC was utilized as a coating for CL-20 to imbue it with distinct spatial characteristics, thereby mitigating its high sensitivity. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses were conducted to investigate the morphology of the CL-20/NC micro-spheres. Additionally, differential scanning calorimetry (DSC) was employed to study the thermal decomposition kinetics of both CL-20 and CL-20/NC. XRD findings revealed that the crystal structure of CL-20/NC micro-spheres prepared using acetone as the solvent remained unchanged, albeit with noticeable attenuation in diffraction peaks. DSC analysis indicated an increase... [more]

Based on the Box−Behnken design (BBD) methodology, an experimental study of the preparation of graphene using ultrasonication was conducted. The yield of graphene served as the response variable, with ultrasonication process time, ultrasonic power, the graphite initial weight, and their interactive effects acting as the independent variables influencing the yield. A multivariate nonlinear regression model was established to describe the ultrasonic production of graphene. Verification of the experiments suggests that the developed multivariate nonlinear regression model is highly significant and provides a good fit, enabling an effective prediction of the graphene yield. The yield of graphene was found to increase with higher ultrasonic power but decrease with longer ultrasonication times and the initial weight of the graphite. The optimal process parameters according to the regression model were determined to be 30 min of ultrasonication time, an ultrasonic power of 1500 W, and a graph... [more]

Chemical sequestration is one important manner of CCUS. The injection of CO2 into an oil reservoir can not only sequestrate CO2 but also raise the oil recovery factor. The performance of chemical sequestration of CO2 depends on the interaction between CO2 solution and reservoir rock. In this paper, we have conducted three different scales of experiments, e.g., microscopic scale, core scale, and time scale, to fully investigate the interaction and resultant variation to mineral content, microscopic structure, porosity, and permeability under reservoir conditions (i.e., reservoir temperature of 90 °C) in Jimusar shale oil formation. The microscopic-scale experiment applied SEM and hyperspectral scanning to obtain microscopic pore throat structure and element distribution before and after soaking the rock in CO2 solution. The core-scale experiment employed XRD to evaluate mineral content variation caused by CO2 solution. Core flooding experiments were conducted to evaluate porosity and pe... [more]

As an alternative to the traditional advanced oxidation process of adding potassium persulfate (PS) and its activator to the solution separately, in this study, M(AC-PS), an integrated activator and catalyst, was synthesized by vacuum ball milling of PS and activated carbon (AC) to improve the PS’s utilization efficiency. The joint mechanical milling caused a change in the preferentially exposed crystal surface of the PS and the generation of more π-π* structures on the AC, leading to successful and stable connection of the PS onto the surface of the AC. Within 40 min, the M(AC-PS) achieved a degradation rate of 97.3% for tetracycline (TC, 20 mg/L), while the mixed system where AC and PS were separately ball milled achieved only a 53.1% removal of TC. Reactive oxygen species and electrochemical tests showed that M(AC-PS) mainly oxidized TC through non-free radical mechanisms. In M(AC-PS), AC provided oxygen-containing functional groups (e.g., C=O) to activate the PS and electron holes... [more]

Comprehending the water absorption process inherent to coal, including the associated spatial distribution patterns of water, proves indispensable in the design and evaluation of coal pillar dams in underground water reservoirs. To better understand this process, a series of NMR (nuclear magnetic resonance) tests were carried out on cylindrically shaped coal samples immersed in water for varying durations, with the upper and lower surfaces of the samples sealed. A method involving image digital processing and finite element simulation was used to quantitatively characterise the water absorption process, as well as the spatial distribution of water in the samples. The results showed that NMR imaging colour brightness differences were positively correlated with water content and that the wetted ring gradually increased in width as the water immersion time increased. The expectation and sum of squared deviations of the pixel greyscale values of the NMR images, which were used to character... [more]

This article is devoted to the study of decision-making problems of hydrotreating process control in the production of high-quality gasoline under conditions of scarcity and fuzziness of the initial information, ultimately developing an approach to solve them. A systematic method is proposed that makes it possible to develop a package of mathematical models of a complex of interconnected units of chemical-technological systems based on available information of various types. Using the proposed system method, a package of models of the main interconnected units in which the hydrotreating process took place was developed. A decision-making problem was formulated to control the hydrotreating process in a fuzzy environment based on the developed system of models. By modifying the Pareto principle of optimality for fuzzy conditions, a heuristic method for solving the given decision-making problem was developed to control the hydrotreating process in a fuzzy environment. The novelty of the p... [more]

Exposure to environmental pollution due to the contamination of soil, surface and groundwater, and air poses potential health risks to biotic and abiotic ecosystems [...]

The distribution law of the ground stress field is of great significance in guiding the design of coal mine roadway alignment, determining the parameters of roadway support, and preventing and controlling the impact of ground pressure in coal mines. A geostress inversion method combining Rhino surface modeling and FLAC3D 6.0 numerical simulation software is proposed. Based on the geological data of the coal mine and the results of on-site measurements, a three-dimensional geological model of Yingcheng Coal Mine is established for the geostress inversion, and the distribution law of the geostress field in Yingcheng Coal Mine is obtained. Research shows the following: (1) The horizontal maximum principal stress values of the Yingcheng Mine are between 33.9 and 35.3 MPa, the horizontal minimum principal stress values are between 23.6 and 25.4 MPa, and the direction of the horizontal maximum principal stress is roughly in the southwest to west direction; (2) the three-way principal stress... [more]

A three-dimensional Navier−Stokes and continuity equation model is employed to numerically predict the resonant modes of sessile droplets on horizontally vibrating substrates. A dynamic contact angle model is implemented to simulate the contact angle variations during vibrations. The four resonant modes (n = 1, 2, 3 and 4) of a droplet under horizontal vibrations are investigated. Simulations are compared to experimental results for validation. Excellent agreement is observed between predicted results and experiments. The model is used to simulate the internal flow patterns within the droplet under resonant modes. It is found that the flow in all four resonant modes can be divided into the Stokes region, the gas−liquid interface region, and the transition region located in between. Numerical simulations show that the average velocity within the droplet increases with the increase in frequency, while the fluctuations in average velocity after reaching the steady state show different tre... [more]

The subcellular localization of long non-coding RNA (lncRNA) provides important insights and opportunities for an in-depth understanding of cell biology, revealing disease mechanisms, drug development, and innovation in the biomedical field. Although several computational methods have been proposed to identify the subcellular localization of lncRNA, it is difficult to accurately predict the subcellular localization of lncRNA effectively with these methods. In this study, a new deep-learning predictor called PreSubLncR has been proposed for accurately predicting the subcellular localization of lncRNA. This predictor firstly used the word embedding model word2vec to encode the RNA sequences, and then combined multi-scale one-dimensional convolutional neural networks with attention and bidirectional long short-term memory networks to capture the different characteristics of various RNA sequences. This study used multiple RNA subcellular localization datasets for experimental validation, a... [more]

In this work, a simple, cost-effective successive ionic layer adsorption and reaction (SILAR) deposition technique has been used to deposit a high-quality tin selenide (SnSe) thin film onto a glass substrate. Structural, morphologic, and thermoelectric properties have been characterized for the prepared thin film. X-ray diffraction (XRD) results of the SnSe thin film reveal an orthorhombic structure phase. The morphological properties of the prepared thin films have been studied using field emission scanning electron microscopy (FESEM). The stoichiometric composition of the deposited thin film and the elemental binding energies of the Sn and Se elements have been investigated with energy-dispersive spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS). The Fourier transformation infrared (FTIR) spectrum of the SnSe thin film displays vibrational modes of chalcogenides bonds. These results suggest that the developed thin film is crystalline, uniform, and without impurities and i... [more]

Pore pressure prediction is a critical parameter in petroleum engineering and is essential for safe drilling operations and wellbore stability. However, traditional methods for pore pressure prediction, such as empirical correlations, require selecting appropriate input parameters and may not capture the complex relationships between these parameters and the pore pressure. In contrast, artificial neural networks (ANNs) can learn complex relationships between inputs and outputs from data. This paper presents a new empirical correlation for predicting pore pressure using ANNs. The proposed method uses 42 datasets of well log data, including temperature, porosity, and water saturation, to train ANNs for pore pressure prediction. The trained model, with the Bayesian regularization backpropagation function, predicts the pore pressure with an average absolute percentage error (AAPE) and correlation coefficient (R) of 4.22% and 0.875, respectively. The trained ANN is then used to develop a ne... [more]

The online measurement of the aluminum−silicon ratio of red mud in the dissolution stage of the Bayer alumina production process is difficult to achieve. The offline assay method has a high cost and strong time delay. Soft sensors are an effective and economical method to solve such problems. In this paper, a hybrid model (TPRF model) based on a tree-structured Parzen estimator (TPE) optimized random forest (RF) algorithm is proposed to measure the Al−Si ratio of red mud. The probability distribution of the hyperparameters of the random forest model is estimated by combining the TPE optimization algorithm with the random forest algorithm. According to this probability distribution, the hyperparameters of the random forest algorithm are adjusted in the parameter search space to obtain the best combination of hyperparameters. We established a TPRF soft sensing model based on the optimal combination of hyperparameters. The results show that the best performance of the TPRF model is a mean... [more]

We constructed a sodium alginate/soy protein isolate/chitosan gel system and incorporated silver nanoparticles reduced by capsaicin into the system, forming a sodium alginate−soy protein isolate−chitosan−capsaicin−silver nanoparticle composite gel (SA/SPI/CTS/CAP/Ag). In tests, the SA/SPI/CTS/CAP/Ag gel exhibited excellent antimicrobial properties. Using the agar diffusion method, the inhibition zone diameter for Staphylococcus aureus was determined to be 29.5 mm. Soy protein isolate (SPI), containing a large number of hydrophobic amino acid residues, effectively enhanced the moisture retention capability of the gel and improved its stability to a certain extent at an appropriate addition concentration. In a milk preservation experiment, the SA/SPI/CTS/CAP/Ag gel significantly extended the shelf-life of the milk. In dye adsorption experiments, the adsorption curve of the SA/SPI/CTS/CAP/Ag gel well fitted a pseudo-second-order kinetic model. It showed a degree of adsorption capacity for... [more]

Chemical process control relies on a tightly controlled, narrow range of margins for critical variables, ensuring process stability and safeguarding equipment from potential accidents. The availability of historical process data is limited to a specific setpoint of operation. This challenge raises issues for process monitoring in predicting and adjusting to deviations outside of the range of operational parameters. Therefore, this paper proposes simulation-assisted deep transfer learning for predicting and optimizing the final purity and production capacity of the glycerin purification process. The proposed network is trained by the simulation domain to generate a base feature extractor, which is then fine-tuned using few-shot learning techniques on the target learner to extend the working domain of the model beyond historical practice. The result shows that the proposed model improved prediction performance by 24.22% in predicting water content and 79.72% in glycerin prediction over t... [more]

Fracture−cavity carbonate reservoirs account for a considerable proportion of oil and gas resources. Because of the complicated relationships between cavities, fractures and pores in these reservoirs, which are defined as cavity clusters, fracturing technology is employed to enhance their hydrocarbon productivity. However, almost all previous studies have just considered the effect of a single natural cavity or fracture on the propagation of a hydraulic fracture; therefore, the mechanism by which a hydraulic fracture interacts with a cavity cluster needs to be clarified. In this study, cavity clusters with different distributions were accurately prefabricated in synthetically made samples, and large-scale simulation equipment was employed to systematically perform fracturing experiments considering different horizontal differential stress levels. Meanwhile, the hydraulic fracture propagation behaviors were comprehensively analyzed through fracture morphology, fracturing curves, the com... [more]