The Claus process is a sulfur recovery unit wherein hydrogen sulfide is converted into the elemental sulfur. This study aims to model the thermal section of the Claus process, which consists of a reaction furnace and a waste heat boiler, as a configuration of two reactors, and subsequently optimize the entire section. Two different reduced kinetic schemes were provided for both units. Using the validated kinetics, mathematical models were developed. The waste heat boiler was modeled as a plug flow reactor with heat transfer, instead of a heat exchanger. The main objective was to maximize the amount of elemental sulfur at the end of the thermal section. Additionally, maximizing the amount of steam generated in the WHB was considered as a secondary objective, and the multi-objective optimization problem was solved. The sulfur production was improved 14.1% and 30% as a result of single- and multi-objective optimization studies. In addition, as an alternative, the Taguchi method was also u... [more]

In nuclear power systems, centrifugal pumps often need to operate under extreme conditions. However, accurately determining the cavitation status of centrifugal pumps under such extreme conditions is challenging. To improve the recognition accuracy of the three statuses of non-cavitation, incipient cavitation, and severe cavitation while improving the anti-interference capability of the monitoring system, this study extracted cavitation features from centrifugal pumps’ motor current and vibration signals under three different operational conditions. It fused the features using feature-level multi-source information fusion (MSIF) based on the backpropagation neural network (BPNN) or support vector machine (SVM) to construct a cavitation status recognition model and analyzed the results to compare with those of recognition without information fusion. The results show that, compared with one signal source, MSIF can significantly improve the recognition accuracy of cavitation statuses. Com... [more]

Pistachio and walnut shells accumulate in large quantities as waste during food processing and represent a promising lignocellulosic biomass for the extraction of valuable components. Subcritical water technology was used as an environmentally friendly technique to study the extraction of active ingredients and other valuable degradation products from walnut and pistachio waste. Subcritical water extraction (SWE) was carried out under different process conditions (temperature (150−300 °C) and short reaction times (15−60 min)) and compared with conventional extraction using different organic solvents (acetone, 50% acetone and ethanol). The extracts obtained from pistachio and walnut shell waste are rich in various bioactive and valuable components. The highest contents of total phenols (127.08 mg GA/g extract at 300 °C for 15 min, from walnut shells), total flavonoids (10.18 mg QU/g extract at 200 °C for 60 min, from pistachio shells), total carbohydrates (602.14 mg TCH/g extract at 200... [more]

This manuscript deals with the synthesis of different types of zeolites from natural kaolinite samples for CO2 adsorption. A zeolite A was prepared from kaolinite by means of an alkaline fusion process, followed by hydrothermal treatment, whereas a highly crystalline zeolite X was synthesized by optimizing the previously mentioned synthetic procedure. In detail, the SiO2/Al2O3 molar ratio in the preliminary mixture was modified with the addition of a secondary silicon source (sodium silicate) in order to obtain the one required for zeolites X. The physicochemical properties of the pristine clay and of the different zeolites were investigated by means of a multi-technique approach, including XRPD; SEM-EDX; 23Na, 27Al and 29Si MAS NMR spectroscopy; and N2 physisorption analysis at 77 K. Since the Si and Al molar ratios and reactivities are key parameters for the synthesis of zeolites, these aspects, primarily related to the use of a naturally occurring aluminosilicate as the raw material... [more]

The prediction of dissolved gas change trends in power transformer oil is very important for the diagnosis of transformer faults and ensuring its safe operation. Considering the time series and nonlinear features of the gas change trend, this paper proposes a novel robust extreme learning machine (ELM) model combining an improved data decomposition method for gas content forecasting. Firstly, the original data with nonlinear and sudden change properties will make the forecasting model unstable, and thus an improved variational modal decomposition (IPVMD) method is developed to decompose the original data to obtain the multiple modal dataset, in which the marine predators algorithm (MPA) optimization method is utilized to optimize the free parameters of the VMD. Second, the ELM as an efficient and easily implemented tool is used as the basic model for dissolved gas forecasting. However, the traditional ELM with mean square error (MSE) criterion is sensitive to the non-Gaussian measureme... [more]

Due to the complexity of wind power, traditional prediction models are incapable of fully extracting the hidden features of multidimensional strong fluctuation data, which results in poor multi-step prediction performance. To predict continuous power effectively in the future, an improved wind power multi-step prediction model combining variational mode decomposition (VMD) with sequence-to-sequence (Seq2Seq) is proposed. Firstly, the wind power sequence is smoothed using VMD and the decomposition parameters of VMD are optimized by using the squirrel search algorithm (SSA) to effectively optimize the decomposition effect. Then, the subsequence obtained from decomposition, together with the original wind power data, is reconstructed into multivariate time series features. Finally, a Seq2Seq model is constructed, and convolutional neural networks (CNNs) with bidirectional gate recurrent units (BiGRUs) are used to learn the coupling and timing relationships of the input data and encode the... [more]

Mass tourism puts enormous pressure on wastewater treatment plants due to its expansive growth during the summer months. To adapt to the fluctuations, the Ravda wastewater treatment plant (WWTP) uses innovative methods and technologies, allowing for “shrinking” and “expanding” of the facilities according to the season. This has been built in stages over the years, with two separate biological treatment lines adapting to different numbers of tourists and to the quantity of influent wastewater. The aim of this study is to make a comparative assessment of the work of WWTP Ravda in the summer and winter seasons and its effectiveness, as well as to compare them. In addition, it examines the years of the COVID-19 pandemic, when a much higher consumption of water per person was noted. Data were analyzed for the period of 2018−2022 inclusive, comparing influent and effluent BOD5 and COD in the summer and winter. Nitrogen and phosphorus removal efficiencies were also tracked. The study shows th... [more]

The lack of service lifetime of bearings has become a bottleneck that restricts the performance of aero engines. How to solve or improve this problem is the focus of most surface engineering researchers at present. In this study, plasma immersion ion implantation was conducted; in order to enhance the ion implantation efficiency and improve the wear resistance of 8Cr4Mo4V bearing steel, the dose-rate-enhanced method was adopted during ion implantation. The surface roughness, phase constituents, elemental concentration, hardness, contact angle and wear resistance of samples after ion implantation was determined by atomic force microscopy (AFM), grazing incidence X-ray diffraction (GIXRD), elemental dispersive spectroscopy (EDS), X-ray diffraction, nanoindentation tester, universal friction and wear tester, etc. The results showed that the high-dose-rate method had a significant enhancement influence on ion implantation efficiency. At the dose rate of 2.60 × 1017 ions/cm2·h, the roughnes... [more]

Aiming at the problem of the low reuse rate of mine water due to the high content of heavy metals in mine water, in this research, the microcharacterization means of EDX, XRD, BET, SEM, and FT-IR were used to characterize the nonstick coal in a mine in western China. The effects of solid−liquid ratio, solution pH, solution temperature, adsorption time, and initial concentration of the solution on the adsorption of Fe(II) by the nonstick coal were analyzed. The adsorption performance of nonstick coal on adsorbed Fe(II) was analyzed under different influencing factors. The results showed that the adsorption capacity and unit removal rate of the coal samples gradually decreased with the increase in the solid−liquid ratio; the adsorption amount increased with the increase in pH in an “S” shape, and the adsorption effect was better in the range of pH = 5~7; and the adsorption amount increased linearly with the temperature. The quasi-secondary kinetic model and Langmuir model could fit the a... [more]

As industrial practices continue to evolve, complex process industries often exhibit characteristics such as multivariate correlation, dynamism, and nonlinearity, making traditional mechanism modeling inadequate in terms of addressing the intricacies of complex industrial problems. In recent years, with advancements in control theory and industrial practices, there has been a substantial increase in the volume of industrial data. Data-driven dynamic operation optimization techniques have emerged as effective solutions for handling complex industrial processes. By responding to dynamic environmental changes and utilizing advanced optimization algorithms, it is possible to achieve dynamic operational optimization in industrial processes, thereby reducing costs and emissions, improving efficiency, and increasing productivity. This correlates nicely with the goals set forth by conventional process operation optimization theories. Nowadays, this dynamic, data-driven strategy has shown signi... [more]

Accurate mathematical patterning of friction has always been a significant research project in the domains of machinery and control, and has played a crucial role in the analysis, control and compensation of mechanical systems containing friction. For high-property electrohydraulic servo control systems, friction compensation is an urgent problem to be solved. The LuGre friction pattern can represent most frictional behaviors, but the LuGre friction pattern is piecewise-continuous, making it non-differentiable. Therefore, the question of how to combine the LuGre friction pattern, enhancing its tracking capacity and robust performance problem, to friction perturbation in hydraulic backstep devices is an important focus for research. In this study, the conventional LuGre friction pattern was enhanced using the continuous differentiability of a friction of rest pattern that laid the foundation of a smooth tangent function. Laying the foundation of an electrohydraulic servo pump-controlled... [more]

The pursuit of low-energy-consumption CO2 capture technology has promoted the renewal and iteration of absorbents for chemical absorption. In order to evaluate the regeneration energy consumption of absorbents and obtain the distribution of energy consumption, a coupling method combining rigorous energy balance and simple estimation is proposed in this study. The data regarding energy balance and material balance from process simulation are transformed into the model parameters required in the simple estimation model. Regenerative energy consumption and distribution are determined by the empirical estimation formula. Two CO2 capture processes of an MEA aqueous solution and MEA−n-propanol aqueous solution (phase-change absorbent) were used to verify the feasibility and applicability of the coupling method. The effects of n-propanol concentration, CO2 loading in the lean solution, and temperature on energy consumption were discussed. The results show that the energy consumption of 30 wt%... [more]

To obtain the macroscale Young’s modulus of glutenite under gravel inclusions, a numerical simulation of macroscale Young’s modulus prediction based on the mesoscale characteristics of glutenite was carried out. Firstly, the micron indentation test was used to obtain the meso-mechanical parameters of gravel and matrix in glutenite to ensure the reasonableness of the numerical simulation parameter settings; secondly, a two-dimensional glutenite physical model generation method based on the secondary development of Python was put forward; and then, the macroscale Young’s modulus variation rule of glutenite under different gravel sizes, particle size ratios, and content characteristics were analyzed using the finite element method (FEM). The results show that Young’s modulus of gravel is larger than Young’s modulus of the matrix, and Young’s modulus of different gravel and matrix has some differences. The gravel content is the main controlling factor affecting the macroscale Young’s modul... [more]

Sodium sulfate (SS) is a neutral activator. SS-activated alkali-activated slag cement (AASC) has lower shrinkage. However, it sets slowly, and the mechanical property develops slowly. Slaked lime (SL) is an alkaline substance widely used in industry that can be used as an activator in AASC. In this paper, SL was used alone, and SL and SS were mixed together to prepare AASC. The effects of SL content on the setting time, shrinkage properties and mechanical strength of AASC were investigated. Furthermore, the mechanism was explored with the analysis of microscopic tests. The results showed that SS could not be used as an activator alone, while SL could be used as an activator alone, and SS could be combined with SL to prepare AASC. The setting time of the SL system or the SS-SL mix system decreased with the increase in SL. The mechanical properties of the SL system were poor. The SS-SL system showed the highest mechanical properties when SL was 3%. With the increase in SL, the autogenous... [more]

Packed bed reactors play a crucial role in various industrial applications. This paper utilizes the Discrete Element Method (DEM), an efficient numerical technique for simulating the behavior of packed beds of particles as discrete phases. The focus is on generating densely packed particle beds. To ensure the model accuracy, specific DEM parameters were studied, including sub-step and rolling resistance. The analysis of the packed bed model extended to a detailed exploration of void fraction distribution along radial and vertical directions, considering the impact of wall interactions. Three different samples, spanning particle sizes from 0.3 mm to 6 mm, were used. Results indicated that the number of sub-steps significantly influences void fraction precision, a key criterion for comparing simulations with experimental results. Additionally, the study found that both loosely and densely packed beds of particles could be accurately represented by incorporating appropriate values for rol... [more]

This study investigates the effectiveness of using conditional generative adversarial networks (CGAN) to synthesize Optical Coherence Tomography (OCT) images for medical diagnosis. Specifically, the CGAN model is trained to generate images representing various eye conditions, including normal retina, vitreous warts (DRUSEN), choroidal neovascularization (CNV), and diabetic macular edema (DME), creating a dataset of 102,400 synthetic images per condition. The quality of these images is evaluated using two methods. First, 18 transfer-learning neural networks (including AlexNet, VGGNet16, GoogleNet) assess image quality through model-scoring metrics, resulting in an accuracy rate of 97.4% to 99.9% and an F1 Score of 95.3% to 100% across conditions. Second, interpretative analysis techniques (GRAD-CAM, occlusion sensitivity, LIME) compare the decision score distribution of real and synthetic images, further validating the CGAN network’s performance. The results indicate that CGAN-generated... [more]

Wood pellets are a versatile ingredient to produce bioenergy and bioproducts. Wood pellet manufacturing in Canada started as a way of using the excess sawdust from sawmilling operations. With the recent dwindling availability of sawdust and the growth in demand for wood pellets, the industry uses more non-sawdust woody biomass as feedstock. In this study, woody biomass materials received from nine wood pellet plants in British Columbia (BC) and Alberta were analyzed for their properties, especially those used for fractionating feedstock to make pellets. Half of the feedstock received at the plants was non-sawdust. Moisture contents varied from 10 to 60% wet basis, with the hog having an average of 50%. Ash contents ranged from 0.3 to 4% dry basis and were highest in the hog fraction. Bulk density varied from 50 to 450 kg/m3, with shavings having the lowest bulk density. Particle density ranged from 359 kg/m3 for infeed mix to 513 kg/m3 for sawdust. In total, 25% of particles received w... [more]

A geographical information system (GIS) is an advanced tool for collecting, managing, and analyzing spatially-referenced data. The contribution of GIS use to process performance indicators can be improved by combining it with multi-criteria decision analysis (MCDA). Combining a GIS and MCDA is, in the scientific literature, rarely discussed for planning an internal transportation system in a manufacturing plant’s outdoor area. The purpose of this article is to clarify what mangers can expect from using a combined approach when deciding on a transport fleet and the operational routing of vehicles. Beside the simulation of MCDA, the computer software ArcGIS Pro 3.0.2 with the Network Analyst extension was used for modelling the transportation system in the form of a case study. The article demonstrates the feasibility and effectiveness of GIS and MCDA use and reveals the extent of the challenge of how decision makers could make the most of ArcGIS functionality. The final solution for an... [more]

The production potential of highly deviated wells cannot be fully realized by conventional acid fracturing, as it can only generate a single fracture. To fully enhance the productivity of highly deviated wells, it is necessary to initiate multiple fractures along a prolonged well section to ensure the optimal number of fractures, thereby maximizing the economic returns post-stimulation. Thus, the number of fractures is a crucial parameter in the acid fracturing design of highly deviated wells. Considering factors such as the random distribution of natural fractures within the reservoir and interference between fractures during production, and, based on the oil−water two-phase flow equation, a three-dimensional reservoir−fracture production coupling model and its seepage difference model are established to simulate the production performance of highly deviated wells under varying conditions, including the number of fractures, fracture spacing, and conductivity parameters. A numerical mo... [more]

In this paper, the dynamic deposition behavior of Na-enriching Zhundong coal ash on tube bundles with varying longitudinal and transverse pitches was numerically studied. By using a modified critical viscosity model, an improved CFD deposition model has been established and key parameters, including deposit mass and morphology, particle trajectories and impaction and sticking probabilities, as well as the heat flux distribution, have been analyzed. The results show that the ash deposited on tubes in the first row is, respectively, 1.74 and 3.80 times higher than that on the second and third rows, proving that ash deposition in the downstream is lessened. As the longitudinal pitch increased from 1.50 D to 2.50 D, deposit mass in the downstream increased two times, suggesting that an increase in longitudinal pitch would aggravate ash deposition. The effect of transverse pitch, however, with the least deposit propensity at St/D = 1.75, is non-linear due to the joint effect of adjacent tub... [more]

In the realm of sensing technologies, the appeal of sensors lies in their exceptional detection ability, high selectivity, sensitivity, cost-effectiveness, and minimal sample usage. Notably, molecularly imprinted polymer (MIP)-based sensors have emerged as focal points of interest spanning from clinical to environmental applications. These sensors offer a promising avenue for rapid, selective, reusable, and real-time screening of diverse molecules. The preparation technologies employed in crafting various polymer formats, ranging from microparticles to nanomaterials, wield a profound influence. These techniques significantly impact the assembly of simplified sensing systems, showcasing remarkable compatibility with other technologies. Moreover, they are poised to play a pivotal role in the realization of next-generation platforms, streamlining the fabrication of sensing systems tailored for diverse objectives. This review serves as a comprehensive exploration, offering concise insights... [more]

In rural areas with higher agricultural energy consumption, ensuring low-carbon transformation and rapid penetration is crucial; therefore, the importance of rural energy system in energy transformation is even more prominent. In order to better understand the research progress of rural integrated energy system, the existing structure of rural energy system and design method are briefly introduced, and the bibliometric method is applied to analyze publications from 2013 to 2023. Based on the Scopus database, 915 publications have been retrieved. These publications are analyzed from the perspective of citation, author, address, and published journal. It is concluded that existing researches mostly use conventional energy technologies to achieve power supply in rural areas, lacking analysis of the potential application of emerging energy technologies and research on multi-energy demand. Furthermore, the review reveals the economy of grid-connected rural energy system is mainly related to... [more]

Thermo-rechargeable batteries, or tertiary batteries, are prospective energy-harvesting devices that are charged by changes in the battery temperature. Previous studies on tertiary batteries have utilized an electrolyte solution, yet the volume of this electrolyte solution could be a disadvantage in terms of the heat capacity given to the tertiary batteries. To overcome this drawback, the performance of an electrolyte-free tertiary battery consisting of physically joined Na1.60Co[Fe(CN)6]0.902.9H2O (NCF90) and Na0.72Ni[Fe(CN)6]0.685.1H2O (NNF68) thin films was investigated for the first time. During thermal cycling between 5 °C and 15 °C, the thermal voltage (VTB) was observed to be 8.4 mV. This result is comparable to the VTB of conventional tertiary batteries that use electrolyte solutions made of NCF90 and NNF68 thin films.

During growth, plants produce bioactive compounds—secondary metabolites. Their concentration can be stimulated by the presence of a stressful factor—an elicitor. Since chlorine dioxide is commonly used in water plants to disinfect drinking water, its application as a plant elicitor seems to be very attractive. The aim of this work was to investigate the influence of a new elicitor, ClO2, on the quality of seeds and bioactive compounds of sprouts. Elicitation of radish and broccoli seeds using ClO2 solutions did not significantly reduce their germination percentage (GP remained over 90%). Radish sprouts sprouted from seeds elicited in chlorine dioxide solutions with concentrations up to 800 ppm did not differ statistically significantly in terms of polyphenol content. Sprouts which were grown in the presence of ClO2 contained significantly fewer polyphenolic compounds. Elicitation of broccoli seeds in 800−1000 ppm ClO2 solutions causes an increase in total phenolic content and concentra... [more]

Design processes are always in motion, since more and more data-driven methods are used for various design and validation tasks. However, small and medium enterprises especially struggle with enhancing their processes with data-driven methods due to a lack of practical and easy-to-use analysis and redesign methods which can handle design process characteristics. In this paper, we present PADDME, which stands for process analysis for digital development in mechanical engineering, as a novel method that, in contrast to currently available analysis methods, considers those design process characteristics with respect to the integration of data-driven methods. Furthermore, a novel technology-readiness framework for digital engineering is introduced. Using the PADDME method, an industrial case study on introducing data-driven methods into the design and evaluation process chain is presented. The usability and novelty of the method are shown by the case study. Thus, PADDME allows a detailed c... [more]