The integration of information technologies with the industry has marked the beginning of the Fourth Industrial Revolution and has promoted the development of industrial engineering [...]

The Carboniferous−Permian, coal-bearing, sedimentary succession on the eastern edge of the Ordos Basin in the Shilounan Block contains large accumulations of hydrocarbon resources. During the exploration of coalbed methane and tight sandstone gas in the study area, multiple drilling wells in the tight sandstone reservoirs have yielded favorable gas logging results. The Benxi, Taiyuan, Shanxi, Shihezi, and Shiqianfeng formations contain multiple sets of sandstone reservoirs, and the reservoir quality and the controlling factors of its tight sandstones were affected by sedimentation, diagenetic alteration, and pore structure. This study comprehensively examines the sedimentary environment, distribution of sand bodies, and physical characteristics of tight sandstone reservoirs through drilling, coring, logging, and experimental testing. The results indicate that the Carboniferous−Permian tight sandstones are mainly composed of lithic sandstone and lithic quartz sandstone. The reservoir qu... [more]

Computational intelligence (CI) techniques have developed very fast over the past two decades, with many new methods emerging [...]

Powder bed fusion (PBF), a subset of additive manufacturing methods, is well known for its promise in the production of fully functional artefacts with high densities. The quality of the powder bed, commonly referred to as powder spreading, is a crucial determinant of the final quality of the produced artefact in the PBF process. Therefore, it is critical that we examine the factors that impact the powder spreading, notably the powder bed quality. This study utilised a newly developed testing apparatus, designed specifically for examining the quality of powder beds. The objective was to analyse the influence of various factors, including the recoater shape, recoater gap size, and the different powder flow properties, on the powder bed relative packing fraction. Additionally, the study aimed to assess the variation in the particle size and shape across the build plate. The results indicated that all of the variables examined had an impact on the relative packing fraction, as well as the... [more]

In this work, Eucalyptus grandis sawdust was subjected to steam explosion as the first step in cellulosic ethanol production within a biorefinery approach. The effect of the moisture content in the eucalypt sawdust (8 and 50%) and pretreatment process variables, such as temperature and residence time, were evaluated along with the influence of the water washing of steam-exploded solids on enzymatic hydrolysis and C6 fermentation yields. All other process streams were characterized to evaluate the recovery yield of valuable co-products. A recovery of nearly 100% glucans in the solid fraction and 60% xylans in the liquid fraction, mainly as partially acetylated oligomers, was obtained. The best enzymatic hydrolysis efficiencies (66−67%) were achieved after pretreatment at 205 °C for 10 min. The washing of pretreated sawdust with water improved the hydrolysis efficiencies and ethanol production yields by 10% compared to the unwashed pretreated solids under the same experimental condition.... [more]

Previous studies on the co-combustion of sludge and coal have not effectively utilized the characteristics of the combustion process to predict thermal behavior. Therefore, focusing on these combustion process characteristics is essential to understanding and predicting thermal behavior during the co-combustion of sludge and coal. In this paper, we use thermogravimetric analysis to study the co-combustion of coal and sludge at different temperatures (300−460 °C, 460−530 °C, and 530−600 °C). Our findings reveal that the ignition improves, but the combustion worsens with more sludge. Then, we further employ curve extraction based on temperature and image segmentation to extract the DTG (weight loss rate) curves. We successfully predicted the DTG curves for different blends using nonlinear regression and curve extraction, achieving an excellent R2 of 99.7%. Moreover, the curve extraction method predicts DTG better than artificial neural networks for two samples in terms of R2 (99.7% vs. 9... [more]

The inadequate ability to dissipate heat of the gas head cover of the diaphragm compressor will result in its excessive temperature, which will put the operation of the hydrogen filling station at risk for safety issues and raise operating costs. This paper analyzed the structure and the heat transfer characteristics of the gas head cover, along with the relevant heat transfer boundaries, based on which a finite element simulation model of the temperature distribution was established. A test rig for the temperature test of a 22 MPa diaphragm compressor was built to validate this simulation model. The results indicated that the simulated temperatures agree well with the measured values, and the deviation is within 9.1%. Further, this paper proposed two head cover structures for enhancing the heat transfer according to the temperature field distribution characteristics, and the simulation and experimental verification were carried out, respectively. The findings demonstrate that the meth... [more]

Pipelines are the most economical and sensible way to transport oil and gas. Long-distance oil and gas pipelines consist of many steel pipes or pipe fittings joined by welded girth welds, so girth welds are an essential part of pipelines. Owing to the limitations of welding conditions and the complexity of controlling weld quality in the field, some defects are inevitably present in girth welds and adjacent weld areas. These defects can lead to pipeline safety problems; therefore, it is necessary to perform failure risk assessment of pipeline girth welds. In this study, an artificial neural network model was proposed to predict the failure risk of pipeline girth welds with defects. Firstly, many pipeline girth weld failure cases, pipeline excavation, and inspection data were collected and analyzed to determine the main factors influencing girth weld failure. Secondly, a spatial orthogonal optimization method was used to select training samples for the artificial neural network model to... [more]

Capsaicin (Cp) is a secondary metabolite produced by the Capsicum plant family. This molecule exhibits various biological properties such as antioxidant capacities, anti-obesogenic effects, and antidiabetic properties, among others. However, conventional extraction methods for Cp present several disadvantages including toxicity, extraction time, and low purity. Therefore, the utilization of supercritical fluid extraction techniques represents a viable option for obtaining highly pure and low-toxicity oleoresins (capsaicin-rich extracts). This approach involves the use of CO2 in the supercritical state and finds applicability in the pharmaceutical, food, and cosmetic industries. The Capsicum chinense variety from the Yucatán Peninsula is a crop with significant economic impact in the region, due to having the highest concentrations of Cp in Mexico. This significant characteristic is attributed to its adaptation to the unique conditions (climate, soil, solar radiation, humidity) of the s... [more]

As an important natural resource, coal plays a critical role in social and economic development [...]

To solve the problem of the field application of downhole hydraulic fracturing technology due to the difficulty in sealing holes, this study analyzes the influence of special cement, expansion agents, stabilizers, and fiber material on basic properties, such as the setting time, fluidity, and compressive strength of high-pressure sealing materials through systematic tests based on a summary of conventional sealing materials. It was determined that with 20−30% special cement and 4% expansion agent added, and a fiber material length of 8 mm and volume of 1%, the high-pressure sealing material had high fluidity and a large expansion rate, demonstrating early strength. The bond performance of the high-pressure sealing material was tested through the variable-angle shear test. The relationship between the fractal dimension of the coal-rock mass around the borehole and the bond performance of the high-pressure sealing material was also explored.

In this work, deep reinforcement learning methodology takes advantage of transfer learning methodology to achieve a reasonable trade-off between environmental impact and operating costs in the activated sludge process of Wastewater treatment plants (WWTPs). WWTPs include complex nonlinear biological processes, high uncertainty, and climatic disturbances, among others. The dynamics of complex real processes are difficult to accurately approximate by mathematical models due to the complexity of the process itself. Consequently, model-based control can fail in practical application due to the mismatch between the mathematical model and the real process. Control based on the model-free reinforcement deep learning (RL) methodology emerges as an advantageous method to arrive at suboptimal solutions without the need for mathematical models of the real process. However, convergence of the RL method to a reasonable control for complex processes is data-intensive and time-consuming. For this rea... [more]

Skin lesion detection is crucial in diagnosing and managing dermatological conditions. In this study, we developed and demonstrated the potential applicability of a novel mixed-scale dense convolution, self-attention mechanism, hierarchical feature fusion, and attention-based contextual information technique (MSHA) model for skin lesion detection using digital skin images of chickenpox and shingles lesions. The model adopts a combination of unique architectural designs, such as a mixed-scale dense convolution layer, self-attention mechanism, hierarchical feature fusion, and attention-based contextual information, enabling the MSHA model to capture and extract relevant features more effectively for chickenpox and shingles lesion classification. We also implemented an effective training strategy to enhance a better capacity to learn and represent the relevant features in the skin lesion images. We evaluated the performance of the novel model in comparison to state-of-the-art models, incl... [more]

There are various organic compounds that can be utilized in the organic Rankine cycle as working fluids. The selection of a suitable working fluid is complicated due to the large number of options and factors affecting the choice, such as thermodynamic properties, environmental impact, cost, etc. This study evaluates seven different pure organic compounds and twenty-one of their binary zeotropic mixtures as potential working fluids for the organic Rankine cycle powered by a heat source at 200 °C. The pure organic fluids show higher exergy efficiency, higher specific net power output, and lower heat exchange area requirements compared to the binary mixtures. Among the pure fluids, RE347mcc performs the best in terms of exergy efficiency, followed by neopentane, isopentane, and pentane. Cyclopentane exhibits the highest power production capacity per unit mass flow rate of the working fluid. Two mixtures, pentane/Novec 649 and cyclopentane/Novec 649, showed significantly higher exergy eff... [more]

The advent of the Fourth Industrial Revolution has revolutionized the manufacturing sector by integrating artificial intelligence into vision inspection systems to improve the efficiency and quality of products. Supervised-learning-based vision inspection systems have emerged as a powerful tool for automated quality control in various industries. During visual inspection or final inspection, a human operator physically inspects a product to determine its condition and categorize it based on their know-how. However, the know-how-based visual inspection process is limited in time and space and is affected by many factors. High accuracy in vision inspection is highly dependent on the quality and precision of the labeling process. Therefore, supervised learning methods of 1-STAGE DETECTION, such as You Only Look Once (YOLO), are utilized in automated inspection to improve accuracy. In this paper, we proposed a labeling method that achieves the highest inspection accuracy among labeling met... [more]

Soybean mosaic disease, caused by the soybean mosaic virus (SMV), is responsible for major losses in yield and seed quality worldwide. Although resistant cultivars are used for its prevention and control, an alternative strategy could consist of applying environmentally friendly antimicrobial agents, such as extracts and essential oils (EOs) of aromatic plants. This study assessed an extract of Achyrocline satureioides and EOs of Minthostachys verticillata, Origanum vulgare, and Thymus vulgaris in terms of their phytotoxicity in soybean. Since all the concentrations tested were found to be safe, the activity of each product against SMV was then assayed in vivo, i.e., in experimentally infected soybean plants. The parameters measured were plant height, wet weight, and virus titer. All the treated plants had a greater height and weight than those in the viral control group. The EOs of M. verticillata (0.80 mg/mL) and T. vulgaris (0.71 mg/mL) inhibited the production of viral antigens, as... [more]

Recently, Japan and the European Union have been experiencing declining petroleum demand owing to global initiatives aimed at reducing environmental impact by curtailing CO2 emissions. Consequently, alternative products and operational conditions should be developed to utilize the fluid catalytic cracking (FCC) unit. Using simulation software (Aspen Hysys), this study modeled a typical FCC unit and compared the simulation results with operational data to ensure reproducibility. Two new process models were developed to investigate two scenarios: (i) the slurry discharged from the FCC unit is utilized as a feedstock for the FCC process and (ii) the slurry and fraction obtained from the downstream absorber of the FCC unit are introduced into a delayed coker unit to facilitate carbon fixation. Within an optimum riser outlet temperature (ROT) of 520−530 °C, the yields of gasoline and liquefied petroleum gas increased up to 4%. For profit performance, although ROT of 535−545 °C yielded peak... [more]

Fiber-reinforced additive manufacturing components have been used in various industrial applications in recent years, including in the production of aerospace, automobile, and biomedical components. Compared to conventional methods, additive manufacturing (AM) methods can be used to obtainin lighter parts with superior mechanical properties with lower setup costs and the ability to design more complex parts. Additionally, the fabrication of onyx composites using the conventional method can result in delamination, which is a significant issue during composite machining. To address these shortcomings, the fabrication of onyx composites via additive manufacturing with the Mark forged 3D-composite printer was considered. Machinability tests were conducted using abrasive water jet machining (AWJM) with various drilling diameters, traverse speeds, and abrasive mass flow rates. These parameters were optimized using Taguchi analysis and then validated using the Genetic algorithm (GA) and the M... [more]

Peptide modification has emerged as an important topic in the academic community and pharmaceutical industry. However, they are primarily focused on the diversification of amines, thiols, and alcohols. Direct and chemoselective modification of acid residues in peptides is relatively underdeveloped. In this context, we report a novel and efficient method for the direct functionalization of acid residues in peptides. By using ynamides as reaction partners, the adducts are rapidly obtained in moderate to excellent yields at room temperature in water. This approach shows excellent chemoselectivity and a broad scope including dipeptides bearing unprotected Trp or Tyr residue and free Ser or Gln residue.

2,5-Furandicarboxylic acid (FDCA) is an important monomer for manufacturing biobased plastics. Biocatalysis has been recognized as a sustainable tool in organic synthesis. To date, the efficiencies of most biocatalytic processes toward FDCA remain low. So, it is highly desired to develop efficient processes. In this work, a biocatalytic route toward FDCA was developed by integrating a cell-free extract of galactose oxidase variant M3−5 with a whole-cell biocatalyst harboring NAD+-dependent vanillin dehydrogenases and NADH oxidase, starting from 5-hydroxymethylfurfural. FDCA was produced in a concurrent mode with >90% yields within 36 h at 20 mM substrate concentration. In addition, biocatalytic synthesis of FDCA was performed on a preparative scale, with 78% isolated yield. The present work may lay the foundation for sustainable production of FDCA.

Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are a category of persistent, non-degradable pollutants that are widespread in the environment and in humans. They have attracted considerable attention due to their high bioaccumulation, multiple toxicities, long-term stability, and, in particular, their effects on human health. Therefore, there is an urgent need for highly efficient technologies and systematic mechanisms for the degradation of PFOS and PFOA. Therefore, we summarize four mainstream technologies for the degradation of PFOS and PFOA in water and their research progress in this review, namely adsorption, advanced oxidation processes, microbial treatment, and membrane separation. Among them, adsorption technology is the earliest and relatively mature, the advanced oxidation process has relatively high treatment efficiency, there are deep and broad development prospects for microbial treatment in the future, and membrane separation technology can recycle ra... [more]

Proper working conditions must be one of the employers’ main concerns in any type of company but particularly in work locations where the employees are chronically exposed to hazardous compounds, like factories and production lines. Regarding this challenge, the present research addresses the mapping of a car factory painting line to possibly toxic volatile organic compounds emitted by all the coatings and chemicals used during the work shifts for the future evaluation of employees’ exposure. For the first time, a Gas Chromatography−Ion Mobility Spectrometry device was employed for the in situ detection of volatile organic compounds in an automotive factory. A total of 26 analytes were detected at nine different locations, of which 15 VOCs were accurately identified. Pure chemical-grade substances were used for the development of the VOC database. Although quantitative analysis was not the goal of this study, a calibration model was presented to one analyte for exemplificative purposes... [more]

The volatility and uncertainty introduced by increasingly integrated renewable energy pose challenges to the reliable and stable operation of the power system. To mitigate the operation risks, a two-stage optimal preventive control model that incorporates transient stability constraints and considers uncertainties from multiple resources is proposed. First, the uncertainties of different re-sources are modeled, with which the non-sequential Monte Carlo sampling method is used to correspondingly generate the scenarios. Thereafter, a two-stage control model that balances operational safety and economy and realizes preventive control and emergency control is built. The operation schedule from the preventive control stage aims to minimize the transient stability probability and operation costs. If any faults destabilize the system, the emergency control stage will be activated immediately to help the system recover stability with minimal control costs. To expedite the solving of the two-st... [more]

The paper presents a novel charging load prediction model for electric vehicles that takes into account traffic conditions and ambient temperature, which are often overlooked in conventional EV load prediction models. Additionally, the paper investigates the impact of disordered charging on distribution networks. Firstly, the paper creates a traffic road network topology and speed-flow model to accurately simulate the driving status of EVs on real road networks. Next, we calculate the electric vehicle power consumption per unit kilometer by considering the effects of temperature and vehicle speed on electricity consumption. Then, we combine the vehicle’s main parameters to create a single electric vehicle charging model, use the Monte Carlo method to simulate electric vehicle travel behavior and charging, and obtain the spatial and temporal distribution of total charging load. Finally, the actual traffic road network and typical distribution network in northern China are used to analyz... [more]

The ocean economy plays a critical role in global economic growth, yet it confronts substantial environmental risks. This study employs topic modeling of South Korean news articles to analyze the evolving trends of environmental risks and sustainability in ocean economy. A dataset comprising 50,213 articles from 2008 to 2022 is examined, revealing prevalent environmental concerns that have persisted over the years. The findings demonstrate an increasing emphasis on sustainability and marine environmental issues, as evidenced by prominent keywords related to construction, safety, plastic pollution, and ecosystem conservation. Through Latent Dirichlet Allocation (LDA) in topic modeling, 10 distinct themes are identified, encompassing sustainable fisheries management, accident and disaster response, polar environment, carbon neutrality, microplastic pollution, habitat ecosystems, cruise tourism development, nuclear power plant pollution, and infectious diseases. The outcomes highlight the... [more]