This study introduces the novel application of a Multi-Task Gaussian Process (MTGP) model to predict biogas production and critical anaerobic digestion (AD) performance indicators (soluble COD, volatile fatty acids (VFAs)), addressing feedstock variability and dynamic process behavior. We compare the MTGP against the widely used mechanistic AM2 model to evaluate its accuracy and applicability for probabilistic modeling in AD systems. The MTGP framework leverages multi-output correlations and uncertainty quantification, trained on experimental data, achieving superior predictive performance over AM2in this study, with lower RMSE (SCOD: 0.32 g/L; VFAs: 0.87 mmol/L; biogas: 0.15 L/day) and higher R² values (SCOD:0.91, VFAs:0.94, biogas :0.88) under the conditions tested. While AM2 provides biochemical insights, its reliance on unvalidated assumptions may limits robustness. The flexibility of MTGP and precision suggest its potential for real-world applications such as Bayesian Optimization... [more]

This article studies four dimple shapes: spherical, smoothed-spherical, normal distribution, and error distribution and how they enhance heat transfer on a plate within a plate heat exchanger using computational fluid dynamics. The dimple that showed the greatest efficiency of heat transfer was the normal distribution dimple, giving a temperature increase of 7.5 times of the smoothed-spherical and 15% more than the error distribution dimple shape. This was primarily due to the large increase in the turbulent kinetic energy caused by the eddies created upon the flow over the normal distribution shape. With the normal distribution shape being found to be the most effective in enhancing heat transfer, a layout of multiple normal distribution dimples based on the stage of flow development was also studied. It was found that a fully developed flow resulted in 9.5% more efficiency than half developed flow and 31% more efficient than placing dimples directly next to each other.

Optimizing twin-screw extruder (TSE) performance is critical in the plastics industry but is often resource-intensive. This study introduces a novel surrogate modeling approach using a Recurrent Deep Embedding Network (RDEN) that integrates deep autoencoders with recurrent neural networks to capture sequential dependencies and physical relationships in TSE processes. Leveraging Progressive Latin Hypercube Sampling (PLHS), the RDEN achieves robust predictions of key process variable, like mean residence time. Results demonstrate the model’s accuracy, generalization capabilities, and potential for automated screw design optimization.

Mixing is a critical operation in numerous industrial processes, traditionally performed in agitated tanks to ensure homogenization. Despite its importance, the design of tanks and impellers is often neglected during agitation system selection, resulting in excessive energy consumption and inefficient mixing. To mitigate these challenges, Computational Fluid Dynamics (CFD) serves as a powerful tool for analyzing tank hydrodynamics and quantifying mixing times. CFD employs mathematical models to simulate mass, heat, and momentum transport phenomena within fluid systems. Among the latest advancements in modeling stirred tank hydrodynamics is Smoothed Particle Hydrodynamics (SPH), a mesh-free Lagrangian approach that tracks individual particles characterized by properties such as mass, position, velocity, and pressure. SPH provides significant advantages over traditional mesh-based methods by accurately capturing fluid behavior through particle interactions. In this study, the performance... [more]

The mathematical modeling of enzymatic reactors for esterification of fatty acids with sugars in the production of biosurfactants has been a useful tool for studying and optimizing the process. In particular, artificial neural networks and fuzzy systems emerge as promising methods for developing models for those processes. In this work, regarding artificial neural networks application, coupling of networks to reactor mass balances was considered in hybrid models to infer reactant concentrations over time. Computationally, an algorithm was constructed incorporating material balances, neural reaction rates, and step-by-step numerical integration (employing the classical Runge-Kutta method). Besides, based on an available set of experimental data, fuzzy logic was applied for modeling and optimization of the conversion of esterification as a function of operational process parameters (such as time, temperature and molar ratio of substrates). All computational development was carried out us... [more]

Nanotechnology, an innovative field focused on nanosized materials, is combined with plant biotechnology through the green chemical strategy of synthesizing plant-induced nanoparticles (NPs). Synthesizing these NPs through novel, cost-effective, and eco-friendly methods plays a significant role in degrading and eliminating organic pollutants. The presence of dangerous biological agents and chemicals in water that surpass the standard threshold and could potentially impact human health and the environment is called water pollution. In the current study, we synthesized copper–silver bimetallic nanoparticles (BMNPs) using a novel, robust, and inexpensive method with leaf broth of Azadirachta indica as both the reducing and capping agent. Scanning electron microscopy and transmission electron microscopy investigations were used to examine the morphology of the synthesized BMNPs, and results indicate that synthesized NPs are in spherical core–shell morphology with a size of 20 nm. Research... [more]

This study evaluates, for the first time, the effects of UV/PMS and UV/H2O2/PMS processes on the degradation of sunscreen agents in synthetic and natural water matrices and compares their effectiveness with the more conventional UV/H2O2. Investigations were conducted using a mixture of organic UV filters containing 4-methylbenzylidene camphor (4-MBC) and 2-ethylhexyl-4-methoxycinnamate. Among the investigated UV-driven AOPs, UV/PMS/H2O2 was the most effective in synthetic water, while in natural water, the highest degradation rate was observed during the degradation of EHMC by UV/PMS. The degradation of UV filters in the UV/PMS system was promoted by sulfate radical (68% of the degradation), with hydroxyl radical contributing approximately 32%, while both radical species contributed approximately equally to the degradation in the UV/H2O2/PMS system. The Vibrio fischeri assay showed an increase in inhibition (up to 70%) at specific stages of UV/H2O2 treatment when applied to natural wat... [more]

Mine fires have always been one of the disasters that restrict coal mining in China and endanger the life safety of underground workers. The research and development of new fire prevention materials are undoubtedly important to ensure the safe and efficient production of modern mines. At present, the main inhibiting materials used are grout material, inert gas, retarding agent, foam, gel, and so on. In order to explore the current situation of coal spontaneous combustion (CSC) fire prevention, the existing fire prevention materials were reviewed and prospected from three aspects: physical, chemical, and physicochemical inhibition. The results show that, at present, most of the methods of physicochemical inhibition are used to inhibit CSC. Antioxidants have become popular chemical inhibitors in recent years. In terms of physical inhibition, emerging biomass-based green materials, including foams, gels, and gel foams, are used to inhibit CSC. In addition, CSC fire-fighting materials also... [more]

TLC (thin-layer chromatography) and HPTLC (high-performance thin-layer chromatography) in normal (NP) and reversed (RP) phase systems were combined with densitometry to analyze caffeine, propyphenazone, and paracetamol. This work aims to check whether comparable limit of detection (LOD) values can be obtained on TLC and HPTLC plates. Analyses were performed on five (NP) or four (RP) different stationary phases (chromatographic plates), testing, in both cases, three mobile phases. It is shown that by using both TLC and HPTLC plates, it is possible to develop chromatographic conditions that enable the detection of compounds analyzed in amounts ranging from a dozen to several dozen µg/spot. In the RP system, lower LOD values for all tested compounds were obtained using TLC than HPTLC. However, performing analyses in the NP, similar (of the same order) LOD values were obtained for caffeine, propyphenazone, and paracetamol when using both TLC and HPTLC plates. For example, during the NP-HPT... [more]

Nature is an amazing source of natural bioactive compounds derived from numerous species of plants, marine bacteria, and fungi [...]

The classifier is an essential tool for the development of contemporary engineering technology. The application of classifiers is to categorize mixed-sized particles into multi-stage uniform particle sizes. In current studies, the particles in the classifier obtain their initial velocity when feeding. The classification effect is impacted by the inability to precisely control the initial state of the particles. To solve this problem, a pusher feed classifier was designed in this study, and a numerical simulation was performed to investigate its flow field characteristics and classification performance using the RNG-DPM method. A pusher is utilized to achieve particle feeding without initial velocity and to precisely control the initial state of the particles in the classification flow field. A newly developed two-way air inlet structure is designed to provide a superimposed flow field and enable the five-stage classification. Our results show that this pusher feed classifier has the be... [more]

The erosive wear encountered in some industrial processes results in economic loss and even disastrous consequences. Hitherto, the mechanism of the erosive wear is not clear, especially when the erosive wear is caused by large particles (>3.0 mm) carried by a flowing liquid. Current approaches of predicting erosive wear need improvement, and the optimization of relevant equipment and systems lacks a sound guidance. It is of significance to further explore such a subject based on the relevant literature. The present review commences with a theoretical analysis of the dynamics of large particles and the fundamental mechanism of erosion. Then the characteristics of the erosion of various equipment are explicated. Effects of influential factors such as particle size and properties of the target material are analyzed. Subsequently, commonly used erosion models, measurement techniques, and numerical methods are described and discussed. Based on established knowledge and the studies reported,... [more]

Cucumbers are a popular vegetable consumed worldwide and are known for their nutritional value, containing carbohydrates, antioxidants, vitamin C, etc. The abundance of a high moisture content is correlated to cucumber perishability, which encourages investigation into ways to maintain its quality and increase shelf-life. This study was carried out to determine the effect of a moringa oil−beeswax coating on the quality of fresh cucumber at different storage temperatures for 27 days of storage. Freshly harvested cucumbers were divided into two groups: the first group was coated with the moringa oil−beeswax edible coating, while the other one was not coated (control). Each group was divided into three other subgroups, for storage at 4, 10, and 22 °C. Different quality parameters, including weight loss, color change, firmness, total soluble solid (TSS), vitamin C, and pH, were evaluated. The findings showed that the weight loss of cucumber was highly increased in non-coated samples stored... [more]

This work presents the reconstruction of the pressure head map of a water distribution system (WDS). This approach relies on historical data collected from a reduced number of sensors placed at some nodes of the WDS. Thus, a Gaussian regression process is then applied to estimate the pressure head at those nodes without a sensor, which allows the reconstruction of the pressure map for the whole network. Then, for leak diagnosis purposes, a dataset of pressure head maps of the WDN is created considering leaky scenarios, and a correlation method is applied to estimate the leak location. Then, for clarity, the Hanoi network is used to evaluate the performance of this leak diagnosis strategy in a simulation environment, assuming the availability of only three sensors. The results showed the potential for pressure head map reconstruction and leak localization.

A review of the application of matrix solid-phase dispersion (MSPD) in the extraction of biologically active compounds and impurities from plants and food samples with a particular emphasis on conventional and new types of sorbents has been provided. An overview of MSPD applications for the isolation of organic residues from biological samples, determined using chromatographic and spectroscopic techniques, has been presented. In this study, procedural solutions that may extend MSDP applicability for the extraction such as vortex-assisted, ultrasound-assisted, microwave-assisted, and extraction with a magnetic sorbent have been discussed. Special attention has been paid to MSPD sorbents including modified silica, diatomite, magnesium silicate, alumina, carbon materials (carbon nanotubes, graphene oxide, graphene, or graphite), molecularly imprinted polymers, and cyclodextrin. An important aspect of the MSPD procedure is the use of high-purity and environmentally friendly solvents for ex... [more]

In this study, Principal Component Analysis (PCA) was applied to discern the underlying trends for 31 distinct MFI (Mobil No. 5)-zeolite membranes of 11 textural, chemical, and operational factors related to manufacturing processes. Initially, a comprehensive PCA approach was employed for the entire dataset, revealing a moderate influence of the first two principal components (PCs), which collectively accounted for around 38% of the variance. Membrane samples exhibited close proximity, which prevented the formation of any clusters. To address this limitation, a subset acquisition strategy was followed, based on the findings of the PCA for the entire dataset. This resulted in an enhanced overall contribution and the revelation of diverse patterns among the membranes and the considered manufacturing factors (total variance between 55% and 77%). The segmentation of the data unveiled a robust correlation between silica (SiO2) concentration and pervaporation conditions. Additionally, a nota... [more]

In this study, nanostructured cerium-doped TiO2 (Ce-TiO2) films with the addition of different amounts of cerium (0.00, 0.08, 0.40, 0.80, 2.40, and 4.10 wt.%) were deposited on a borosilicate glass substrate by the flow coating sol-gel process. After flow coating, the deposited films were dried at a temperature of 100 °C for 1 h, followed by calcination at a temperature of 450 °C for 2 h. For the characterization of sol-gel TiO2 films, the following analytic techniques were used: X-ray diffraction (XRD), differential thermal analysis (DTA), thermal gravimetry (TG), differential scanning calorimetry (DSC), diffuse reflectance spectroscopy (DRS), and energy dispersive X-ray spectroscopy (EDS). Sol-gel-derived Ce-TiO2 films were used for photocatalytic degradation of ciprofloxacin (CIP). The influence of the amount of Ce in TiO2 films, the duration of the photocatalytic decomposition, and the irradiation type (UV-A and simulated solar light) on the CIP degradation were monitored. Kinetics... [more]

While technical optimization focuses on maximizing the annual energy yield of utility-scale PV parks, the ultimate goal for power plant owners is to maximize investment profit. This paper aims to bridge the gap between technical and economic approaches by using simulation data from a real-case utility-scale PV park. It analyzes how changes in configuration parameters such as the DC−AC ratio and string length and PV technologies like solar tracking systems and bifacial modules impact the economic metrics of the project, i.e., net present value (NPV) and internal rate of return (IRR). PVSyst software was utilized as a simulation tool, while in-house developed software implementing appropriate technical and economic models served as a comparison platform and was used to validate the outputs generated through PVSyst. Results indicate that the commonly used horizontal single-axis tracking configuration may economically underperform compared with fixed-tilt setups. The optimal DC−AC ratio fe... [more]

Bohai X oilfield has reached the extra-high water cut stage of more than 95%, dominated by the bottom water reservoir. The oilfield mainly adopts horizontal-well exploitation, with the characteristics of high difficulty and low success rate for well water plugging. To solve the above problem, the segmented production technology of horizontal wells was developed to guide oilfield applications and tap their potential. In the segmented design stage, the horizontal section is objectively segmented by drilling condition analysis, optimally based on drilling through interlayers or permeability discrepancy formation, simultaneously combined with the numerical simulation method. When implementing measures, annulus chemical packer materials are squeezed between segments to effectively inhibit the fluid flow between the open hole and the sand-packing screen pipe. Moreover, the packers are used to seal between segments to effectively restrain the flow between the screen and the central tube, achi... [more]

Wobble-plate axial piston pumps, characterized by the lack of a slipper mechanism, experience reduced leakage in comparison to their swash-plate counterparts, which contributes to their higher volumetric efficiency. Presently, the primary focus of the research conducted by scholars both domestically and internationally is concentrated on wobble-plate axial piston pumps. The performance studies within this field are predominantly focused on investigating flow pulsation. They also investigate pressure pulsation. Additionally, they investigate cavitation phenomena. Research on inclined-axis axial piston pumps has been limited. This study focused on analyzing the operational form of the piston within an inclined-axis axial piston pump. A correction factor k was introduced based on the motion characteristics of the piston. The application of this factor significantly improved the accuracy of the simulations when compared to the experimental results. Specifically, at a load pressure of 10 MP... [more]

For mitigating global warming, polymer electrolyte membrane fuel cells have become promising, clean, and sustainable alternatives to existing energy sources. To increase the energy density and efficiency of polymer electrolyte membrane fuel cells (PEMFC), a comprehensive numerical modeling approach that can adequately predict the multiphysics and performance relative to the actual test such as an acceptable depiction of the electrochemistry, mass/species transfer, thermal management, and water generation/transportation is required. However, existing models suffer from reliability issues due to their dependency on several assumptions made for the sake of modeling simplification, as well as poor choices and approximations in material characterization and electrochemical parameters. In this regard, data-driven machine learning models could provide the missing and more appropriate parameters in conventional computational fluid dynamics models. The purpose of the present overview is to expl... [more]

The optimization of cell disruption is a critical step in microalgal biorefineries. We used the same batch of Tetraselmis suecica culture to compare two mechanical cell disruption techniques, focusing on the extraction yield of water-soluble molecules. The conditions for high-pressure homogenization (HPH) studied were two passes at a moderate pressure of 300 bars. For ultrasound (US) treatment, we used an amplitude of 20% (equivalent to 100 W) for 25 min. These conditions were chosen on the basis of a preliminary screen of extraction conditions. HPH extracted proteins and pigments more efficiently than US, whereas US was superior for uronic acid extraction. Interestingly, the two methods had similar extraction yields for carbohydrates under the studied conditions. We also analyzed the kinetics of molecule release by considering the centrifugation time lag for HPH and applying a first-order kinetic model for US. HPH outperformed US in terms of the immediate extraction and release of mol... [more]

Employing catalytic decomposition to break down reducing agents in intermediate-level radioactive waste during nuclear fuel reprocessing offers significant advantages. This study focuses on investigating the deactivation behavior of 5% Ru/C catalysts by two different synthesis processes used for reducing agent destruction. Deactivation experiments were conducted by subjecting the 5% Ru/C catalysts to 100 and 150 reaction cycles. Changes in the concentration of free radicals on the carbon-based carrier were measured to analyze the loading position and loss of Ru ions. Additionally, sorption−desorption curves and pore size distributions of the four catalysts were obtained. Analysis results reveal that Ru ions on the catalyst adsorb onto active free radical sites on the carbon-based carrier. Under ultrasonic conditions, some Ru ions partially desorb from the free radical sites on the carbon-based carrier, and desorbed Ru ions may adsorb onto weak free radical sites, while undesorbed Ru io... [more]

Carbonate reservoirs account for 60% of global reserves for oil, making them one of the most important types of sedimentary rock reservoirs for petroleum production. This study aimed to identify key production features that significantly impact oil production rates, enhancing reservoir management and optimizing production strategies. A comprehensive dataset is built from reserves and production history data of 377 onshore carbonate oilfields globally, encompassing features such as production, recovery rate, and recovery degree of the whole lifecycle of an oilfield. XGBoost classifier is trained by K-fold cross-validation and its hyperparameters are optimized by Optuna optimization framework. The results show that XGBoost has the best performance evaluated with metrics including accuracy, precision, recall, and F1 score comparing with decision tree, random forest, and support vector machine. Key production features are identified by analyzing the classification feature importance of XGB... [more]

Wearing safety helmets is an important way to ensure the safety of workers’ lives. To address the challenges associated with low accuracy, large parameter values, and slow detection speed of existing safety helmet detection algorithms, we propose a receptive field-enhanced lightweight safety helmet detection algorithm called YOLOv5s-CR. First, we use a lightweight backbone, a high-resolution feature fusion network, and a small object detection layer to improve the detection accuracy of small objects while substantially decreasing the model parameters. Next, we embed a coordinate attention mechanism into the feature extraction network to improve the localization accuracy of the detected object. Finally, we propose a new receptive field enhancement module (RFEM) to substitute the SPPF module in the original network, enabling the model to acquire features under multiple receptive fields, thereby enhancing the detection precision of multi-scale objects. Using the Safety Helmet Detection da... [more]