The recovery of sulfuric acid in the presence of Zr(IV) and Hf(IV) was studied via solvent extraction using TEHA (tri-2-ethylhexyl amine) and its mixtures. A solidification phenomenon occurred in the loaded organic phase when a single TEHA was employed in the extraction of 1 to 5 M H2SO4. Octanol, decanol and TBP (tri butyl phosphate) were mixed with TEHA, separately, to prevent the solidification of sulfuric-acid-loaded organic. Due to the relatively high aqueous solubility of octanol and decanol, the mixture of TEHA + TBP was selected as the optimal system for the extraction of H2SO4. Simulated counter-current extraction and stripping experiments were performed on the basis of the McCabe−Thiele diagrams, indicating that sulfuric acid could be reduced by TEHA + TBP from 4.2 to around 0.5 M without Zr(IV) and Hf(IV) extraction and recovered by its complete stripping with water. The proposed sulfuric acid recovery step would contribute to the completion of the closed-circuit of the Zr(I... [more]

The feasibility of an adsorbent material like biochar (BC) depends on its regeneration capacity and its ability to achieve high removal efficiencies on real wastewater (WW) effluents. In this study, the regeneration capacity of the Pinus patula BC previously used in the removal of Indigo Carmine from water was evaluated. The regeneration technique that resulted in the highest desorption efficiency was a thermo-chemical method that consisted of heating the spent BC in a stove at 160 °C for 45 min followed by regeneration with ethanol (C2H6O) at a concentration of 75% for 6 h. Through this regeneration method, it was found that Pinus patula BC could be used in seven consecutive adsorption−desorption cycles. The feasibility of this BC was also assessed by evaluating the adsorbent’s efficiency in real textile WW. Under optimal operational conditions (solution pH = 3, BC dose = 13.5 g/L, and BC particle size = 300−450 µm), the highest removal efficiencies in terms of colour and dissolved or... [more]

In this work, an experimental analysis of the performance of a cross-flow turbine, commonly referred to as a Michell−Banki turbine (MBT), is carried out for small-scale hydropower production in rural areas located in developing countries to support their social and economic development activities. The study investigates how the efficiency of the MBT is influenced by the presence or absence of a nozzle, along with variations in the internal guide vane (GV) and its angle. The runner had 26 blades that were arranged symmetrically in the periphery between two circular plates. The designed MBT had the ability to generate a maximum of 100 W of power at a water flow rate and a head of 0.009 m3/s and 0.6311 m, respectively. The experimental tests were carried out using a hydraulic bench. The turbine efficiency without the inner GV was found to be higher than that of the turbine with the inner GV; i.e., it was found that the utilization of the GV did not enhance the efficiency of the MBT due to... [more]

Spray dust reduction is one of the most economical and effective technologies for controlling coal dust in coal mining faces. We aimed to reproduce a spray dust reduction process in a simulation and investigate the mechanism by which the spray angle and airflow speed influence the dust reduction effect. Based on the DPM (discrete phase model) and the mixture model, we constructed a spray dust reduction evaluation model by considering two-way momentum coupling between the discrete phase and the continuous phase. The results showed that installing nozzles near the dust source (coal mining drum) significantly reduced the dust concentration at the coal mining face from 0.0005 kg/m3 to 0.0001 kg/m3. The increase in airflow speed and spray angle enhanced the horizontal transportation of droplets and dust, providing opportunities for the droplets to condense the dust; however, if the droplets have too large an angle, this will result in an insufficient concentration of droplets in the vicinit... [more]

The discontinuation of pumping and drainage activities upon the cessation of mining operations leads to the gradual accumulation of groundwater. This inflow into mined-out areas affects the properties of the rock, disturbing the previously stable goaf and exacerbating instability. In this study, we advance an existing theoretical framework pertaining to the residual deformation of mines by delineating the mechanisms through which groundwater influences the degradation of the overlying strata in goaf areas. Using analogous material simulation experiments and rigorous theoretical analyses, we clarify the specific mechanisms by which groundwater causes structural damage to these regions. The deformation of overlying rock is divided into three different forms: the compressive deformation of rock, the sliding instability of rock, and the rotational instability of rock. The main contributions of this study are its refinement of the existing theory of the residual deformation of mines, an ana... [more]

The formation of solid deposits in the process of supercritical water gasification (SCWG) is one of the main problems hindering the commercial application of the process. Seven experiments were conducted with the grass Reed Canary Grass with different preheating temperatures, but all ended early due to the formation of solid deposits (maximum operation of 3.8 h). The position of solid deposits in the lab plant changed with the variation in the temperature profile. Since the formation of solid deposits consisting of salts, coke, and corrosion products is a severe issue that needs to be resolved in order to enable long-time operation, inner temperature measurements were conducted to determine the temperature range that corresponds with the zone of solid formation. The temperature range was found to be 400 to 440 °C. Wherever this temperature was first reached solid deposits occurred in the system that led to blockage of the flow. Additional to the influence of the temperature, the influe... [more]

During the operation of non-clogging pumps, the flexible long fiber is prone to clogging and winding during the flow process, which can result in damage to the non-clogging pump, so a numerical simulation method of a solid−liquid two-phase flow in a non-clogging pump with a flexible long fiber is proposed in this paper. The unsteady numerical simulation of the two-phase flow of a single flexible fiber with different densities, lengths and diameters in a double-blade non-clogging pump was carried out to study the influence of fiber parameters on fiber transport capability. The results show that at a density of 920 kg/m3, 300 kg/m3 and 732 kg/m3, the transport capability of flexible fibers decreases successively, and the transport time T0 is 0.32 s, 0.36 s and 0.48 s, respectively. The transport capability of flexible fibers with a length of 150 mm, 200 mm and 250 mm decreases successively, and the transport time T0 is 0.34 s, 0.48 s and 0.96 s, respectively. The transport time T0 is 0.4... [more]

Plasma technology is increasing its applications in the textile industry for conferring surface functionalities through greener processes. In this study, plasma treatments are studied to improve the wettability of mycelium-based material, an emerging material with a lot of potential in the near future. The plasma effect was characterized by assessing the added functionality (wettability) and inspecting surface modifications with different techniques, such as scanning electron microscopy (SEM) and X-Ray photoelectron spectroscopy (XPS). Low pressure plasma (LPP) treatments were successfully applied into the mycelium-based material and optimal power of discharge and treatment time were set for this material (750 W, 17.5 min). With the optimized LPP treatments, the water absorption capacity of mycelium-based material was improved by 2000% and some surface morphological modifications were observed by SEM analysis. On the other hand, XPS analysis demonstrated how the plasma treatment change... [more]

The accurate prediction of gas well production is one of the key factors affecting the economical and efficient development of tight gas wells. The traditional oil and gas well production prediction method assumes strict conditions and has a low prediction accuracy in actual field applications. At present, intelligent algorithms based on big data have been applied in oil and gas well production prediction, but there are still some limitations. Only learning from data leads to the poor generalization ability and anti-interference ability of prediction models. To solve this problem, a production prediction method of tight gas wells based on the decline curve and data-driven neural network is established in this paper. Based on the actual production data of fractured horizontal wells in three tight gas reservoirs in the Ordos Basin, the prediction effect of the Arps decline curve model, the SPED decline curve model, the MFF decline curve model, and the combination of the decline curve and... [more]

The goal of steel defect detection is to enhance the recognition accuracy and accelerate the detection speed with fewer parameters. However, challenges arise in steel sample detection due to issues such as feature ambiguity, low contrast, and similarity among inter-class features. Moreover, limited computing capability makes it difficult for small and medium-sized enterprises to deploy and utilize networks effectively. Therefore, we propose a novel lightweight steel detection network (SCFNet), which is based on spatial channel reconstruction and deep feature fusion. The network adopts a lightweight and efficient feature extraction module (LEM) for multi-scale feature extraction, enhancing the capability to extract blurry features. Simultaneously, we adopt spatial and channel reconstruction convolution (ScConv) to reconstruct the spatial and channel features of the feature maps, enhancing the spatial localization and semantic representation of defects. Additionally, we adopt the Weighte... [more]

In industrial manufacturing, bearings are crucial for machinery stability and safety. Undetected wear or cracks can lead to severe operational and financial setbacks. Thus, accurately identifying bearing defects is essential for maintaining production safety and equipment reliability. This research introduces an improved bearing defect detection model, YOLOv8-LMG, which is based on the YOLOv8n framework and incorporates four innovative technologies: the VanillaNet backbone network, the Lion optimizer, the CFP-EVC module, and the Shape-IoU loss function. These enhancements significantly increase detection efficiency and accuracy. YOLOv8-LMG achieves a mAP@0.5 of 86.5% and a mAP@0.5−0.95 of 57.0% on the test dataset, surpassing the original YOLOv8n model while maintaining low computational complexity. Experimental results reveal that the YOLOv8-LMG model boosts accuracy and efficiency in bearing defect detection, showcasing its significant potential and practical value in advancing indus... [more]

Although the immunomodulatory effects of natural products have not yet been completely elucidated, attempts to use natural products in the treatment of immune-mediated inflammatory diseases such as autoimmune diseases, chronic inflammatory diseases, mutant viral infections, and even immunosenescence-related cancers are ongoing [...]

The selection of growth substrate geometries for the mechanical dry transfer of carbon nanotubes to device substrates depends on the precision of the assembly equipment. Since these geometries play a decisive role in the overall efficiency of the process, an investigation of the most important geometry parameters is carried out. The substrate geometry affects the number of carbon nanotubes suspended during the growth process and the speed of mechanical assembly at the same time. Since those two criteria are interlinked and affect productivity, a meta-model for the growth and selection of the nanotubes is simulated and a time study of the resulting assembly motions is subsequently performed. The geometry parameters are then evaluated based on the total number of suspended carbon nanotubes and the throughput rate, measured in transfers per hour. The accuracy specifications are then taken into account. Depending on the overall accuracy that can be achieved, different offset angles and ove... [more]

Textiles are often used to protect people from cold environments. While most garments are designed for temperatures not far below 0 °C, very cold regions on the earth near the poles or on mountains necessitate special clothing. The same is true for homeless people who have few possibilities to warm up or workers in cooling chambers and other cold environments. Passive insulating clothing, however, can only retain body heat. Active heating, on the other hand, necessitates energy, e.g., by batteries, which are usually relatively heavy and have to be recharged regularly. This review gives an overview of energy-self-sufficient textile solutions for cold environments, including energy harvesting by textile-based or textile-integrated solar cells; piezoelectric sensors in shoes and other possibilities; energy storage in supercapacitors or batteries; and heating by electric energy or phase-change materials.

This paper addresses the challenging scheduling of crude oil operations (SCOO) problem, characterized by the intricate sequencing of activities involving discrete events and continuous variables. Given the NP-Hard nature of scheduling problems due to their combinatorial complexity, this study employs a data-driven optimization approach. Initially, historical operational data relevant to the SCOO are scrutinized; however, due to data limitations, small-scale instances are solved using a mathematical programming model to generate data. Subsequently, operational solution data are processed using the Apriori algorithm, a renowned data mining technique. The insights gained are translated into heuristic rules, laying the groundwork for a novel data-driven heuristic algorithm tailored for the SCOO problem. This algorithm is then applied to a 45-day scheduling scenario, demonstrating the efficacy of the proposed approach.

Hydraulic fracturing is extensively utilized for the prevention and control of gas outbursts and rockbursts in the deep sections of coal mines. The determination of fracturing construction parameters based on the coal seam conditions and stress environments merits further investigation. This paper constructs a damage analysis model for coal under hydraulic loads, factoring in the influence of the intermediate principal stress, grounded in the octahedron strength theory analysis approach. It deduces the theoretical analytical equation for the damage distribution of a coal medium subjected to small-flow-rate hydraulic fracturing in underground coal mines. Laboratory experiments yielded the mechanical parameters of coal in the study area and facilitated the fitting of the intermediate principal stress coefficient. Leveraging these datasets, the study probes into the interaction between hydraulic loads and damage radius under assorted influence ranges, porosity, far-field crustal stresses,... [more]

Compliant physical interactions, interactive learning, and robust position control are crucial to improving the effectiveness and safety of rehabilitation robots. This paper proposes a human−robot cooperation control strategy (HRCCS) for lower limb rehabilitation robots. The high-level trajectory planner of the HRCCS consists of a trajectory generator, a trajectory learner, a desired trajectory predictor, and a soft saturation function. The trajectory planner can predict and generate a smooth desired trajectory through physical human−robot interaction (pHRI) in a restricted joint space and can learn the desired trajectory using the locally weighted regression method. Moreover, a triple-step controller was designed to be the low-level position controller of the HRCCS to ensure that each joint tracks the desired trajectory. A nonlinear disturbance observer is used to observe and compensate for total disturbances. The radial basis function neural networks (RBFNN) approximation law and rob... [more]

A series of experiments has been conducted to investigate the tribological properties of a TiN film sliding against GCr15 steel balls in ambient air, low vacuum and high vacuum environments. Various friction loads and sliding velocities were also applied. The TiN film displays a steady-state friction stage after the running-in stage in all the above environments, while the durations of running-in stages are different. The steady-state friction coefficients of the TiN film were around 0.56 in ambient air and 0.3 in the high vacuum environment (1 × 10−5 mbar). In the low vacuum (1 × 10−2 mbar) environment, a low friction coefficient (around 0.19) was attained for all the friction tests on TiN film, irrespective of the applied load and sliding velocity. In the meantime, it was noticed that the applied loads and the sliding velocities would change the duration of the running-in stage before reaching the low friction coefficient. It is revealed by the analysis of wear tracks that the metal... [more]

We aimed to investigate the corrosion patterns and the main controlling factors of N80 steel and P110 steel tubing under different sections. Conducting weight loss corrosion experiments for 168 h using high-temperature and high-pressure autoclaves to simulate the corrosion behavior of two types of casing materials, N80 steel and P110 steel, in different well sections under specific conditions of CO2 content, chloride ion concentration, temperature, pressure, and sulfate-reducing bacteria population in highly mineralized formation water. X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS) were used to analyze the corrosion products, surface morphology, and elemental composition of the two steel pipes. Additionally, 3D microscopy was employed to observe the morphology and measure the dimensions of localized corrosion pits. Under different well sections, the corrosion products formed on N80 steel and P110 steel mainly consist of FeCO... [more]

Within the domain of industrial control systems, safeguarding data integrity stands as a pivotal endeavor, especially in light of the burgeoning menace posed by malicious tampering and potential data loss. Traditional data storage paradigms, tethered to physical hard disks, are fraught with inherent susceptibilities, underscoring the pressing need for the deployment of resilient preservation frameworks. This study delves into the transformative potential offered by distributed ledger technology (DLT), with a specific focus on IOTA, within the expansive landscape of the Internet of Things (IoT). Through a meticulous examination of the intricacies inherent to data transmission protocols, we present a novel paradigm aimed at fortifying data security. Our approach advocates for the strategic placement of IOTA nodes on lower-level devices, thereby streamlining the transmission pathway and curtailing vulnerabilities. This concerted effort ensures the seamless preservation of data confidentia... [more]

The aim of this study is to purify industrial textile effluents by treating two types of commonly encountered dyes: blue maxilon (BM), of cationic nature, and black eriochrome (NE), of anionic nature. We intend to employ an innovative approach based on the adsorption of these dyes onto a novel vegetal biomaterial derived from Aleppo pine fibers (FPAs). A kinetic and thermodynamic study was conducted. The effect of some physicochemical parameters on both dye adsorption and FPAs was also evaluated. The modeling of the adsorption results was performed using Langmuir, Freundlich, Temkin, and Dubinin Radushkevich (D-R) isotherms. The results indicate that the equilibrium time strongly depends on the initial concentration of the two dyes, being 60 min with pseudo-second-order adsorption kinetics for both dyes. Adsorption isotherms under the optimal conditions of adsorbent mass, temperature, medium pH, and dye concentration were used to determine the maximum adsorption efficiency, which was c... [more]

The co-gasification of coal and biomass offers numerous benefits, including improved gasification efficiency, reduced pollution emissions, and the utilization of renewable resources. However, there is a lack of comprehensive research on the synergistic effects of, and influence parameters on, coal−biomass co-gasification. This study employs Aspen Plus simulations to investigate the co-gasification behavior of coal and corn straw, focusing on the synergistic effects and the impact of various operating conditions. A synergistic coefficient is defined to quantify the interactions between the feedstocks. Sensitivity analyses explore the effects of gasification temperature (800−1300 °C), coal rank (lignite, bituminous, anthracite), biomass mass fraction (0−50%), oxygen-to-carbon ratio, and steam-to-carbon ratio on the synergistic coefficients of effective syngas content (CO + H2), specific oxygen consumption, specific fuel consumption, and cold gas efficiency. The results reveal an optimal... [more]

Abnormal conditions greatly reduce the efficiency of hydraulic fracturing of unconventional gas reservoirs. Optimizing the fracturing scheme is crucial to minimize the likelihood of abnormal operational conditions, such as pressure channeling, casing deformation, and proppant plugging. This paper proposes a novel machine learning-based method for optimizing abnormal conditions during hydraulic fracturing of unconventional natural gas reservoirs. Firstly, the main controlling factors of abnormal conditions are selected through a hybrid controlling analysis, upon which a surrogate model is established for predicting the occurrence probability of abnormal conditions, rather than whether abnormal conditions happen or not. Subsequently, a machine learning-based optimization algorithm is developed to minimize the occurrence probability of abnormal conditions, acknowledging their inevitability during the fracturing process. The optimal results demonstrate the proposed method outperforms tradi... [more]

Many studies have used fractal theory to characterize pore structure distribution heterogeneity through mercury intake curves. However, there is relatively little research on the fractal model calculation of mercury removal curves. In this study, a high-pressure mercury intrusion test is used to describe the pore and fracture distribution heterogeneity (PFDH). The fractal physical meaning of the mercury removal curve was determined by calculating the change in the curve’s fractal dimension value. The results are as follows. (1) According to mercury removal efficiency and porosity, samples can be divided into types A (mercury removal efficiency above 35%) and B (mercury removal efficiency below 35%). In general, type A sample belongs to micro-pore-developed types, and type B samples belong to the macro-pore-developed type. (2) The Menger model (M) represents the complexity of a specific surface area, while the Sierpinski model (S) represents the roughness of the pore volume. Among all t... [more]

For over four decades, carbon dioxide (CO2) has been instrumental in enhancing oil extraction through advanced recovery techniques. One such method, water alternating gas (WAG) injection, while effective, grapples with limitations like gas channeling and gravity segregation. To tackle the aforementioned issues, this paper proposes an upgrade coupling method named alkaline-surfactant-polymer alternating gas (ASPAG). ASP flooding and CO2 are injected alternately into the reservoir to enhance the recovery of the WAG process. The uniqueness of this method lies in the fact that polymers could help profile modification, CO2 would miscible mix with oil, and alkaline surfactant would reduce oil−water interfacial tension (IFT). To analyze the feasibility of ASPAG, a couples model considering both gas flooding and ASP flooding processes is established by using the CMG-STARS (Version 2021) to study the performance of ASPAG and compare the recovery among ASPAG, WAG, and ASP flooding. Our research... [more]