With the development of machine vision technology, deep learning and image recognition technology has become a research focus for agricultural product non-destructive inspection. During the ripening process, banana appearance and nutrients clearly change, causing damage and unjustified economic loss. A high-efficiency banana ripeness recognition model was proposed based on a convolutional neural network and transfer learning. Banana photos at different ripening stages were collected as a dataset, and data augmentation was applied. Then, weights and parameters of four models trained on the original ImageNet dataset were loaded and fine-tuned to fit our banana dataset. To investigate the learning rate’s effect on model performance, fixed and updating learning rate strategies are analyzed. In addition, four CNN models, ResNet 34, ResNet 101, VGG 16, and VGG 19, are trained based on transfer learning. Results show that a slower learning rate causes the model to converge slowly, and the tra... [more]

This paper introduces a novel and cost-effective method for detecting adulterated diesel, specifically targeting contamination with kerosene, by leveraging machine learning and the refractive index values of mixed diesel samples. It proposes a laser-based sensor, employing COMSOL simulations for synthetic data generation to facilitate machine learning training. This innovative approach not only streamlines the detection process by eliminating the need for expensive equipment and specialized personnel but also enables on-site testing without extensive sample preparation. The sensor’s design, utilizing light refraction and reflection principles, allows for the accurate measurement of diesel adulteration levels. Validation results showcase the machine learning models’ high precision in predicting adulteration percentages, as evidenced by an R-squared value of 0.999 and a mean absolute error of 0.074. This research signifies a leap in sensor technology, offering a practical solution for ra... [more]

In order to remove high-concentration emulsified oil from wastewater, a chitosan-based magnetic flocculant, denoted as FS@CTS-P(AM-DMC), was employed in this present study. The effects of factors including the magnetic flocculant dose, pH values, and coexisting ions were investigated. A comparative dosing mode with the assistance of polyacrylamide (PAM) was also included. The evolution of floc size was studied using microscopic observation to investigate the properties of flocs under different pH values and dosing modes. Particle image velocimetry (PIV) and extended Deryaguin−Landau−Verwey−Overbeek models were utilized to illustrate the distribution and velocity magnitude of the particle flow fields and to delve into the mechanism of magnetic flocculation. The results showed that FS@CTS-P(AM-DMC) achieved values of 96.4 and 74.5% for both turbidity and COD removal for 3000 mg/L of simulated emulsified oil. In the presence of PAM, the turbidity and COD removal reached 95.7 and 71.6%. In... [more]

Water quality deterioration and eutrophication have become a global concern, while reservoir pollution caused by multiple factors has led to frequent algal blooms, posing a serious threat to rural drinking water security and urban water supply. The purpose of this paper is to analyze the current water quality of Waihu Reservoir and use the single index method, the weighted comprehensive scoring method, and the nutrient level index method (TLI) to evaluate eutrophication. On this basis, the pollution sources of the reservoir are comprehensively analyzed and discussed, and effective control strategies are proposed. The evaluation results indicate that the reservoir is of moderate eutrophication type. Therefore, reducing the input of nutrients such as nitrogen and phosphorus in water is the main goal of alleviating exogenous pollution. The combination of engineering intervention and ecological restoration strategies to remove nutrients from the aquatic environment is an effective strategy... [more]

Surimi-based products typically demand cold storage and a cold chain distribution system, which not only affects their physical properties and flavor but also escalates production costs. In this study, we introduced a novel high-temperature and high-pressure retort processing method to enable room temperature storage and distribution of a surimi-based product, a fish paste cake. Our optimization efforts focused on refining the processing conditions for the fish paste cake. This included incorporating transglutaminase, sugar additives, natural herbal or seaweed extracts, and optimizing retort processing conditions to enhance textural properties, minimize browning and off flavor, and extend the shelf-life of the product. Our results demonstrated that the addition of 0.3% ACTIVA TG-K, 1.0% trehalose, and 0.5% sea tangle extract during the production process significantly enhanced the gel strength, minimized browning, and improved the overall flavor of the fish paste cake prototype. Import... [more]

Anaerobic co-digestion (AnCoD) presents several advantages over conventional mono-digestion. Various factors can impact the efficiency of the co-digestion process, including the mixing ratio of the feedstocks. This study primarily investigates the effects of different mixing ratios on methane production during the co-digestion of source-separated municipal organic waste (SSO) with thickened waste activated sludge (TWAS). While the C/N or COD/N ratio has generally been used for optimizing the mixing ratios of co-digested feedstocks, a new approach is introduced in this study to evaluate the effects of the lipid, protein, and carbohydrate (L:P:C) ratios on the efficiency of AnCoD with respect to methane production, kinetics, and synergism at mixing ratios of TWAS:SSO of 10:90, 30:70, 50:50, 70:30, and 10:90. AnCoD improved methane production and kinetics relative to TWAS at all mixing ratios, the highest of which was at the 10:90 ratio, corresponding to a methane yield, maximum methane p... [more]

Adequate power load data are the basis for establishing an efficient and accurate forecasting model, which plays a crucial role in ensuring the reliable operation and effective management of a power system. However, the large-scale integration of renewable energy into the power grid has led to instabilities in power systems, and the load characteristics tend to be complex and diversified. Aiming at this problem, this paper proposes a short-term power load transfer forecasting method. To fully exploit the complex features present in the data, an online feature-extraction-based deep learning model is developed. This approach aims to extract the frequency-division features of the original power load on different time scales while reducing the feature redundancy. To solve the prediction challenges caused by insufficient historical power load data, the source domain model parameters are transferred to the target domain model utilizing Kendall’s correlation coefficient and the Bayesian optim... [more]

The reservoir in the Anyue gas field, located in the Sichuan basin of China, belongs to the second member of the Dengying formation and has distinctive geological features. It is characterized by strong heterogeneity, low porosity, low permeability, and locally developed natural fractures. The reservoir space consists primarily of corrosion holes, natural fractures, and similar voids. Moreover, the lower reservoir exhibits high water saturation and a homogeneous bottom-water interface. Since it is a carbonate-based hydrocarbon reservoir with low porosity and permeability, deep acid fracturing has proven to be an efficient method for enhancing individual well production. However, the reconstruction of the second member of the Dengying formation reservoir poses significant challenges. The reservoir contains high-angle natural fractures, small vertical stress differences, and is located in close proximity to the gas−water interface. As a result, it becomes difficult to control the height... [more]

In view of the high salinity characteristics of reinjection oilfield wastewater in the Gasi Block of Qinghai Oilfield, with the polymer produced by Shandong Baomo as the research target, we systematically investigated the variations in the impact of six ions, Na+, K+, Ca2+, Mg2+, Fe2+, and Fe3+, in the produced water from polymer flooding on the viscosity and stability of the polymer solution. Additionally, we provided the primary research methods for complexation in reinjected wastewater. Experimental results indicate that the main factors leading to a decrease in polymer viscosity are high-valence cations, with the descending order of their influence being Fe2+ > Fe3+ > Mg2+ > Ca2+ > Na+ > K+. High-valent cations also effect the viscosity stability of polymer solutions, and their order from greatest to least impact is: Fe2+ > Ca2+(Mg2+) > Fe3+ > Na+(K+). This article is focused on investigating the influencing factors and extent of the impact of oilfield wastewater on the viscosity o... [more]

Protective coatings are typically applied to enhance their resistance to corrosion. There is considerable research on the corrosion resistance of coated casings. However, few research studies have focused on the erosion resistance on coated casings. In this work, the erosion resistance of resin- and metallic-coated casings in liquid−solid two-phase fluids were investigated using a self-made erosion facility. The results show that the resin coating tends to peel off the material base in the form of brittle spalling or coating bulge in the high-speed sand-carrying liquid. Both resin and metallic coatings were broken through within 20 min in a liquid−solid two-phase flow environment. Compared to resin coatings, metallic coatings exhibit weaker erosion resistance in similar liquid−solid flow. Through the analysis of experimental results and fitted curves, empirical constants for materials and sand content influencing factors were determined using non-dimensional processing. The erosion pre... [more]

Shale reservoirs typically exhibit high density, necessitating the use of horizontal wells and hydraulic fracturing techniques for efficient extraction. Proppants are commonly employed in hydraulic fracturing to prevent crack closure. However, limited research has been conducted on the impact of shale mineral composition and proppant filling patterns on shale stress sensitivity. In this study, shale cylindrical core samples from two different lithologies in Jimusaer, Xinjiang in China were selected. The mineral composition and microscopic structures were tested, and a self-designed stress sensitivity testing system was employed to conduct stress sensitivity tests on natural cores and fractured cores with different proppant filling patterns. The experimental results indicate that the stress sensitivity of natural shale porous cores is weaker, with a stress sensitivity coefficient below 0.03, significantly lower than that of fractured cores. The shale mineral composition has a significan... [more]

This article describes the results of a comprehensive comparative study of the production of fatty acid ethyl esters (FAEEs) for use as biodiesel in perfect mixing reactors (PMRs) and plug flow reactors (PFRs). The products obtained on a laboratory scale at all stages of the separation and purification of the FAEE phase were analyzed using the FTIR, XRF and GC-MS methods. We compared distillation methods for the separation of stoichiometrically excessive ethanol from the reaction mixture. Neutralization methods with H2SO4 solution and carbonation with CO2 were applied for FAEE phase purification from the catalyst. Emulsions formed during the water flushing stage were analyzed via the optical microscopy method. The optimal conditions of stirring speed and temperature were selected to maintain a high level of FAEE−water phase contact area with minimum phase separation time. The efficiency of the carbonation method for catalyst neutralization in the FAEE phase has been proven, allowing us... [more]

In the era of rapid technological advancement and evolving industrial landscapes, embracing the concept of the factory of the future (FoF) is crucial for companies seeking to optimize efficiency, enhance productivity, and stay sustainable. This case study explores the concept of the FoF and its role in driving the energy transition and digital transformation within the automotive sector. By embracing advancements in technology and innovation, these factories aim to establish a smart, sustainable, inclusive, and resilient growth framework. The shift towards hybrid and electric vehicles necessitates significant adjustments in vehicle components and production processes. To achieve this, the adoption of lighter materials becomes imperative, and new technologies such as additive manufacturing (AM) and artificial intelligence (AI) are being adopted, facilitating enhanced efficiency and innovation within the factory environment. An important aspect of this paradigm involves the development a... [more]

Nitrogen fixation, the conversion of atmospheric nitrogen into biologically useful compounds, is crucial for sustaining biological processes and industrial productivity. Recent advances have explored plasma-assisted processes as an innovative approach to facilitate nitrogen fixation. This review offers a comprehensive summary of the development, current state of the art, and potential future applications of plasma-based nitrogen fixation. The analysis encompasses fundamental principles, mechanisms, advantages, challenges, and prospects associated with plasma-induced nitrogen fixation.

There has been a tendency in oil and gas industry towards the adoption of multilateral wells (MLWs) with completions that incorporate multiple types of flow control devices (FCDs). In this completion technique, passive inflow control devices (ICDs) or autonomous inflow control devices (AICDs) are positioned within the laterals, while interval control valves (ICVs) are installed at lateral junctions to regulate the overall flow from each lateral. While the outcomes observed in real field applications appear promising, the efficacy of this specific downhole completion combination has yet to undergo comparative testing against alternative completion methods that employ a singular flow control device type. Additionally, the design and current evaluations of such completions are predominantly based on analytical tools that overlook dynamic reservoir behavior, long-term production impacts, and the correlation effects among different devices. In this study, we explore the potential of integra... [more]

This paper presents a coupled computational fluid dynamics−discrete element method (CFD−DEM) simulation to predict cuttings transport by the drilling fluid (mud) in different oil well drilling conditions. The mud rheology is expressed by the Herschel−Bulkley behaviour and modelled in a Eulerian framework (CFD), while the cuttings are modelled using the Lagrangian approach (DEM). In this work, the effects of drill string rotation, inclination angle, cutting size, mud rheology, and annular velocity on cleaning efficiency are investigated. It is found that increasing the well deviation from vertical to horizontal leads to a higher cuttings concentration. However, at low annular velocity, the cuttings concentration for the inclined (45-degree) annulus is found to be higher than the horizontal one due to the sliding motion of cuttings on the lower section of the annulus. Overall, the drill pipe rotation has little effect on decreasing the cuttings concentration, but the effect is more prono... [more]

Pillar stability is of paramount importance in ensuring the safety of underground rock engineering structures. The stability of pillars directly influences the structural integrity of the mine and mitigates the risk of collapses or accidents. Therefore, assessing pillar stability is crucial for safe, productive, reliable, and profitable underground mining engineering processes. This study developed the application of decision intelligence-based predictive modelling of hard rock pillar stability in underground engineering structures using K-Nearest Neighbour coupled with the grey wolf optimization algorithm (KNN-GWO). Initially, a substantial dataset consisting of 236 different pillar cases was collected from seven underground hard rock mining engineering projects. This dataset was gathered by considering five significant input variables, namely pillar width, pillar height, pillar width/height ratio, uniaxial compressive strength, and average pillar stress. Secondly, the original hard r... [more]

Located in the Kuqa foreland basin, Tarim Basin, the Xinkeshen gas field is a rare ultra-deep and ultra-high-pressure fractured tight sandstone gas reservoir. During the development process, the fluid in the well migrates from the bottom hole to the ground. Due to the huge temperature drop and pressure drop in the wellbore, salting-out and scale-out occur in the well to destroy the oil and gas flow channel, resulting in a decrease in gas production in the well and seriously affecting the normal production of the oil field. Aiming at the problem of wellbore scaling and blockage in the Keshen gas field, this paper takes the wellbore of the Keshen block as the research object. After analyzing the composition of produced water and scale in the wellbore, the solution of ‘fixing scale, clarifying mechanism, early prediction, and fine treatment’ is formulated, and the analysis and evaluation technology of the scale formation process and the prediction model of the gas well model are formed. T... [more]

Given the demand for extremely low sulfur content in 5 wt% Si high-silicon austenitic stainless steel (SS-5Si), smelting utilizes a slag composition of CaF2-CaO-Al2O3-MgO-SiO2 with a basicity of 1 to 3, Al2O3 content ranging from 2.04 to 9.61%, and CaF2 content between 20.8 and 31.62%. Experiments designed to investigate the sulfur content in molten steel at temperatures of 1773 K, 1823 K, and 1873 K over durations of 1, 5, 10, 15, and 30 min, under varying slag compositions, corroborated with a theoretically derived model hypothesizing a “rate-controlling” step in mass transfer, revealed that the mass transfer of sulfur within the molten steel was determined to be the rate-controlling step (RCS) in the (CaO) + [S] = (CaS) + [O] reaction kinetics, and the variability of the mass transfer coefficient of sulfur, kS,m, in the molten steel ranged from 1.04 × 10−5 m∙s−1 to 2.24 × 10−5 m∙s−1. Based on the temperature dependency of kS,m, the apparent activation energy for the desulfurization... [more]

The compatibility of constituents making up a petroleum fluid has been recognized as an important factor for trouble-free operations in the petroleum industry. The fouling of equipment and desalting efficiency deteriorations are the results of dealing with incompatible oils. A great number of studies dedicated to oil compatibility have appeared over the years to address this important issue. The full analysis of examined petroleum fluids has not been juxtaposed yet with the compatibility characteristics in published research that could provide an insight into the reasons for the different values of colloidal stability indices. That was the reason for us investigating 48 crude oil samples pertaining to extra light, light, medium, heavy, and extra heavy petroleum crudes, which were examined for their colloidal stability by measuring solvent power and critical solvent power utilizing the n-heptane dilution test performed by using centrifuge. The solubility power of the investigated crude... [more]

In low-voltage distribution networks, distributed energy storage systems (DESSs) are widely used to manage load uncertainty and voltage stability. Accurate modeling and estimation of voltage fluctuations are crucial to informed DESS dispatch decisions. However, existing parametric probabilistic approaches have limitations in handling complex uncertainties, since they always rely on predefined distributions and complex inference processes. To address this, we integrate the patch time series Transformer model with the non-parametric Huberized composite quantile regression method to reliably predict voltage fluctuation without distribution assumptions. Comparative simulations on the IEEE 33-bus distribution network show that the proposed model reduces the DESS dispatch cost by 6.23% compared to state-of-the-art parametric models.

Most textile manufacturing companies in the world heavily rely on manual labor, particularly in the fabric inspection section, especially for cotton fabric. Establishing smart manufacturing systems like industrial automation in the textile industry for cotton fabric inspection is important for error-free inspection. The proposed make-to-order (MTO) inventory model focuses on the strategic development of a supply chain network under fuzzy uncertainty. The distinctiveness of this research lies in integrating a methodology that involves human and machine interaction, along with allocating resources to investment in smart manufacturing. This article presents a case study of the Jagatjit Cotton Textiles (JCT) manufacturing company in Punjab, India, as an example to validate the model and check the performance of SMT in the fabric inspection process in cotton TC mills. This paper contributes by developing four distinct textile supply chain models with industrial automation under triangular a... [more]

Coal seam pressure is an important parameter for production performance evaluation and prediction of coalbed methane (CBM). CBM production from undersaturated CBM reservoirs can be divided into two stages according to critical desorption pressure. At present, few prediction models of coal seam pressure performance consider the comprehensive influence of critical desorption pressure, dissolved gas, matrix shrinkage, and stress sensitivity. For the purpose of accurately predicting coal seam pressure during gas production for an undersaturated coalbed methane reservoir, the material balance principle is used to establish the analytical method for predicting coal seam pressure, considering the comprehensive influence of the critical desorption pressure, dissolved gas, matrix shrinkage, and stress sensitivity. Then, the proposed method is verified against a numerical simulation case using a computer modelling group (CMG) and two actual coalbed methane wells. Finally, the sensitivities of in... [more]

The accurate determination of crystal formation during crystallization is crucial for obtaining crystal products with consistent quality and quantity. In this study, we aimed to identify the feasibility of using Raman spectroscopy to monitor the crystal growth stage in the crystallization process using cephalosporin intermediate 7-ACT as an example molecule. By observing the changes in the characteristic peak of the 7-ACT crystal (504 cm−1) and the characteristic peak of the solvent acetonitrile (914 cm−1), a correlation between the crystal growth stage and the change in the Raman intensity of the crystal solution was discovered. The determination of the optimal starting time for the crystal growth stage through a Raman analyzer significantly improves the consistency of crystal product quality. This led to a fivefold reduction in the variation in the weight and water content of the final 7-ACT crystal products compared to those obtained via manual control. In addition, our experiments... [more]

This study explores enhancing the resilience of electric and natural gas networks against extreme events like windstorms and wildfires by integrating parts of the electric power transmissions into the natural gas pipeline network, which is less vulnerable. We propose a novel integrated energy system planning strategy that can enhance the systems’ ability to respond to such events. Our strategy unfolds in two stages. Initially, we devise expansion strategies for the interdependent networks through a detailed tri-level planning model, including transmission, generation, and market dynamics within a deregulated electricity market setting, formulated as a mixed-integer linear programming (MILP) problem. Subsequently, we assess the impact of extreme events through worst-case scenarios, applying previously determined network configurations. Finally, the integrated expansion planning strategies are evaluated using real-world test systems.