The technology of radial-well-assisted hydraulic fracturing is applied in the stimulation of low-permeability hydrocarbon reservoirs where commercial production cannot be achieved by the conventional fracturing method. Here, a study on the reservoir stimulation effect and the fracture propagation pattern of radial-well-assisted deflagration fracturing was carried out. Based on smooth particle hydrodynamics (SPH), rock mechanics theory, and finite element theory, a numerical model of radial-well-assisted deflagration fracturing was established by integrating the JWL state equation. Research on the effects of the deflagration position, radial well azimuth and horizontal principal stress difference on the fracture propagation was carried out. The results show that the deflagration position, radial well azimuth and horizontal principal stress difference have significant effects on the fracture area in deflagration fracturing. The closer distance from the deflagration position is, the large... [more]

When drilling or exploiting fractured formations, gas fluid displacement and invasion often occur, and gas invasion is very subtle and difficult to find. The gas in the fracture enters the wellbore and arrives near the wellhead with the drilling fluid. Improper treatment may lead to serious accidents such as lost circulation and blowout. In this study, using computational fluid dynamics (CFD) simulation software for modeling and grid generation, based on the volume of fluid (VOF) method, the gas invasion behavior under different conditions was simulated to explore the flow process and characteristics of gas invasion, and the effects of different drilling fluid properties and fracture morphology on gas invasion were analyzed. The experimental results show that the drilling fluid enters the fracture to compress the gas, making the pressure in the fracture greater than that in the wellbore, thus leading to the occurrence of gas invasion. The viscosity and density of the drilling fluid hav... [more]

In this paper, a novel composite fault diagnosis method combining adaptive feature mode decomposition (FMD) and minimum noise amplitude deconvolution (MNAD) is proposed. Firstly, chaos mapping and leader mutation selection strategy were introduced to improve the Northern Goshawk algorithm (NGO), and a chaotic leadership Northern Goshawk optimization (CLNGO) algorithm was proposed. The advantages of the CLNGO algorithm in convergence accuracy and speed were verified by 12 benchmark functions. Then, a new index called sparse pulse and cyclicstationarity (SPC) is proposed to evaluate signal sparsity. Finally, SPC is used as the fitness function of CLNGO to optimize FMD and MNAD. The optimal decomposition mode n and filter length of FMD, and filter length L and noise ratio ρ of MNAD are selected. The CLNGO-FMD is used to decompose signal into different modes. The signal is reconstructed based on the kurtosis criterion and the CLNGO-MNAD method is used to reduce the noise of the reconstruct... [more]

Biotrickling filtration is a well-established technology for the treatment of air polluted with odorous and volatile organic compounds (VOCs). Besides dozens of successful industrial applications of this technology, there are still gaps in a full understanding and description of the mechanisms of biotrickling filtration. This review focuses on recent research results on biotrickling filtration of air polluted with single and multiple VOCs, as well as process modeling. The modeling offers optimization of a process design and performance, as well as allows deeper understanding of process mechanisms. An overview of the developments of models describing biotrickling filtration and conventional biofiltration, as primarily developed and in many aspects through similar processes, is presented in this paper.

The modeling and simulation of combustion processes is still a challenging field [...]

Temperature is one of the most important parameters in the combustion processes. Accurate surface temperature can help to gain insight into the combustion characteristics of various solid or liquid fuels, as well as to evaluate the operating status of combustion power facilities such as internal combustion engines and gas turbines. This paper mainly summarizes and compares the main surface thermometry techniques, from the aspects of their principles, current state of development, and specific applications. These techniques are divided into two categories: contact-based thermometry and non-intrusive thermometry. In contact-based thermometry, conventional thermocouples as well as thin-film thermocouples are introduced. These methods have been developed for a long time and are simple and economical. However, such methods have disadvantages such as interference to flow and temperature field and poor dynamic performance. Furthermore, this paper reviews the latest non-intrusive thermometry m... [more]

In manufacturing processes using computerized numerical control (CNC) machines, machine tools are operated repeatedly for a long period for machining hard and difficult-to-machine materials, such as stainless steel. These operating conditions frequently result in tool breakage. The failure of machine tools significantly degrades the product quality and efficiency of the target process. To solve these problems, various studies have been conducted for detecting faults in machine tools. However, the most related studies used only the univariate signal obtained from CNC machines. The fault-detection methods using univariate signals have a limitation in that multivariate models cannot be applied. This can restrict in performance improvement of the fault detection. To address this problem, we employed empirical mode decomposition to construct a multivariate dataset from the univariate signal. Subsequently, auto-associative kernel regression was used to detect faults in the machine tool. To v... [more]

This study aimed to isolate, purify, and identify some bacteria from different sources known to be contaminated with pesticides and evaluate their ability to degrade two important pesticides, chlorantraniliprole (CAP), and flubendiamide (FBD). In our study, six isolates showed maximum growth in the presence of CAP and FBD in the growth media as a sole carbon source. The isolates were purified and then identified by biochemical and morphological tests, MALD-TOF-MS, and 16S rRNA techniques, as Bacillus subtilis subsp. subtilis AZFS3, Bacillus pumilus AZFS5, Bacillus mojavensis AZFS15, Bacillus paramycoides AZFS18, Pseudomonas aeruginosa KZFS4, and Alcaligenes aquatilis KZFS11. The degradation ability of studied bacterial strains against pesticides was estimated under different conditions (temperatures, pH, salt, and incubation time). The results reveal that the optimal conditions for all bacterial strains’ growth were 30−35 °C, pH 7.0, 0.0−0.5% NaCl, and an incubation period of 11 days a... [more]

Utilization of bioenergy with carbon capture can realize carbon-negative syngas production. The quadruple fluidized bed gasifier (QFBG) integrates a chemical looping oxygen generation process and a dual fluidized bed gasifier with limestone as bed material. It is one promising device that can convert biomass to H2-rich syngas whilst capturing CO2 with little energy penalty. However, experimental or numerical simulation of QFBG is rarely reported on due to its complex structure, hindering the further commercialization and deployment of QFBG. In this work, a new computational fluid dynamics (CFD) solver is proposed to predict the complex physicochemical processes in QFBG based on the multi-phase particle in cell (MPPIC) methodology with the assistance of the open source software, OpenFOAM. The solver is first validated against experimental data in terms of hydrodynamics and reaction kinetics. Then, the solver is used to investigate the QFBG property. It is found that the QFBG can operate... [more]

The outlet liquid material concentration is a key production indicator to evaluate the evaporation quality and an important basis to adjust the evaporation operation parameters. However, the online concentration analyzer has strict installation conditions and high prices, and it is difficult to obtain the liquid material concentration in time. Usually, the field works perform imprecise operations according to the time delay information. In addition, the process data contain errors, which affects the accuracy and timeliness of process optimization and control. Therefore, a hybrid prediction model of concentration based on data reconciliation is presented in this paper. First, to obtain the high-quality process data, the data reconciliation method is applied for preprocessing. Moreover, the process mechanistic model is constructed by utilizing the process knowledge and the balance principle. Taking into account the volatility and nonlinearity characteristics, a data-driven model based on... [more]

The last-mile logistics is regarded as one of the least efficient, most expensive, and polluting part of the entire supply chain and has a significant impact and consequences on sustainable delivery operations. The leading business model in e-commerce called Attended Home Delivery is the most expensive and demanding when a short delivery window is mutually agreed upon with the customer, decreasing possible optimizing flexibility. On the other hand, last-mile logistics is changing as decisions should be made in real time. This paper is focused on the proposed solution of sustainability opportunities in Attended Home Delivery, where we use a new approach to achieve more sustainable deliveries with machine learning forecasts based on real-time data, different dynamic route planning algorithms, tracking logistics events, fleet capacities and other relevant data. The developed model proposes to influence customers to choose a more sustainable delivery time window with important sustainabili... [more]

Bisphenol A, bisphenol S, and fluconazole are environmental contaminants widely found in surface waters because of their extensive usage and low biodegradability. Therefore, other methods are often considered for the removal of these compounds. The present study aims at their photodegradation with the use of UV light and three different catalysts, ZnO, TiO2, and Ag-TiO2. The results obtained show that photocatalytic removal of these compounds is also problematic and the use of catalysts, such as ZnO and TiO2, at increasing concentrations mostly leads to lower degradation of the tested compounds. The modification of TiO2 with silver increases the degradation of both bisphenols up to 100%, which was achieved in 60 min by bisphenol A and in as little as 10 min by bisphenol S. Nevertheless, the degradation of fluconazole remained at the same level, not exceeding 70% in 60 min, i.e., still much lower than expected. In addition, the degradation products of bisphenols show the hydroxylation a... [more]

Due to the fitted structure of fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems, and evolutionary neural systems, we can study computational intelligence [...]

Concentration distribution is essential for the emergency disposal of cryogenic fuel leakage. In the dispersion process of cryogenic gas, its concentration is greatly influenced by the atmospheric water vapor. The authors have presented an adiabatic mixing model to derive the concentration of the cryogenic gas, in which the value of water vapor density is obtained by referring to the NIST database continuously. However, it is difficult to achieve fast system response times for real-time monitoring systems when calling NIST. Thus, a simple algebraic model of water vapor density with high calculation efficiency is necessary. Based on the detection of temperature and the solution of water vapor partial pressure, a calculation model was developed. For a given initial ambient temperature and relative humidity, the dew point could be solved by Qian’s correlation. By temperature comparisons of the mixture cloud, dew point, and triple point, the water vapor partial pressure can be calculated b... [more]

From large-scale aerospace systems to household appliances and other systems in daily life, the application of parallel systems is involved. A parallel system is a typical structural dependence multi-component system, in addition to a series system and hybrid system. This paper takes a parallel system as the research object and minimizes the expected cost rate or maximizes the availability by determining the optimal two-dimensional age replacement interval. The structural dependence of the components is described by the copula function, and the system life model is established. Based on the system life model, the two-dimensional age replacement expected cost rate model and availability model are proposed. In case analysis, the simulated annealing algorithm (SAA), genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are used to find the optimal warranty scheme for the engine fuel fine filter. SAA can converge faster and find a warranty scheme that makes the warranty co... [more]

In recent times, important contributions and the incorporation of renewable sources, such as photovoltaic, fuel cells, etc., are the main reasons for the popularity of DC microgrids. Integrating renewable sources into the microgrid requires high-voltage, high-efficiency DC-to-DC converters. Without modification, traditional converters are not suitable for achieving the required voltage in microgrid applications, due to the requirement for a large duty cycle, inductor resistance, voltage rating of switches, reverse recovery of the diode, high current rating inductors, etc. Various converters based on the circuitry of voltage multipliers, switched inductors/capacitors, coupled inductors, transformers, etc., have been proposed in the literature and have their drawbacks. In this paper, to realize significant voltage gain with two duty cycle controls, a new multi-leg (ML) converter is recommended as a solution for use in DC microgrids. The converter is designed by incorporating multiple leg... [more]

Municipal solid waste treatment and disposal have become one of the major concerns in waste management due to the excessive production of waste and higher levels of pollution. To address these challenges and protect the environment in sustainable ways, the hydrothermal pretreatment (HTP) technique coupled with anaerobic digestion (AD) becomes a preferred alternative technology that can be used for municipal solid waste stabilization and the production of renewable energy. However, the impact of HTP parameters such as temperature, retention time, pH, and solid content on the fermentation of TWAS is yet to be well studied and analyzed. Hence this study was conducted to review the effect of hydrothermal pretreatment of thickened waste-activated sludge (TWAS) on fermentation and anaerobic digestion processes. Many studies reported that fermentation of TWAS at pretreatment temperature ranges from 160 °C to 180 °C resulted in a 50% increase in volatile fatty acid (VFA) yields compared to no... [more]

In order to utilize the benefits of blackthorn flower polyphenols and provide their stabilization during processing and storage, and to facilitate their application in functional food products, this study aimed to evaluate the encapsulation parameters during the spray-drying process of blackthorn flower extract. The effect of the type of wall material (maltodextrin (MD) and its mixtures with gum arabic (GA) and inulin (IN)), its ratio to extract dry matter (0.5, 1, and 2) and drying temperature (120, 150, and 180 °C) on the concentration of different polyphenolic groups was studied. While the lowest applied amount of wall material at the lowest drying temperature enabled efficient encapsulation of all polyphenolic groups, the type of wall material applied caused significant differences in retention. The highest concentrations of both phenolic acids and flavonoids were achieved with the addition of 25% of GA in MD. Unlike the addition of GA, mixtures of MD with IN did not show a positiv... [more]

In the Yuanba area, many lost circulation accidents occur due to the complex geological structure, broken strata, and developed fractures, which seriously affect construction safety and drilling costs. Therefore, the Yuanba district is the focus of this paper. Firstly, a three-dimensional geomechanical model is established through multi-source information fusion to identify the main geological risk factors of lost circulation, according to the data on drilling and well logging in the operation area. Then a risk warning model and evaluation methods for loss circulation, based on geological engineering data fusion, are established, through which the characteristic parameters of various loss of circulation risks can be calculated in real time, parameters along the well trajectory can be extracted and compared, and thus, the risk of lost circulation is warned and analyzed in real time. The early warning of lost circulation risk can be achieved during drilling operations, which can improve... [more]

With the rapid development of artificial intelligence, the application of this new technology to music generation has attracted more attention and achieved gratifying results. This study proposes a method for combining the transformer deep-learning model with generative adversarial networks (GANs) to explore a more competitive music generation algorithm. The idea of text generation in natural language processing (NLP) was used for reference, and a unique loss function was designed for the model. The training process solves the problem of a nondifferentiable gradient in generating music. Compared with the problem that LSTM cannot deal with long sequence music, the model based on transformer and GANs can extract the relationship in the notes of long sequence music samples and learn the rules of music composition well. At the same time, the optimized transformer and GANs model has obvious advantages in the complexity of the system and the accuracy of generating notes.

The pH treatment unit is widely used in various processes, such as wastewater treatment, pharmaceutical manufacturing, and fermentation. It is essential to get the on-specifications product. Thus, controlling pH is key management for accomplishing the manufacturing objective. However, the highly nonlinear pH characteristics of acid−base titration make pH regulation difficult. Applications of artificial intelligence for process control have progressed and gained popularity recently. The development of reinforcement learning (RL) control with a deep deterministic policy gradient (DDPG) algorithm to handle coupled pH and liquid level control in a continuous stirred tank reactor with a strong acid−base reaction is presented in this study. To validate the RL model, the reward functions are created individually for the level and pH controls. The grid search technique is deployed to optimize the hyperparameters of the RL controller models, including the number of nodes in the hidden layers an... [more]

The modeling of the paint atomization process is a barrier in computational fluid dynamics numerical simulation for the whole process of air spraying, and seriously restricts robot intelligent spray gun trajectory planning and the improvement of coating quality. Consequently, a multi-scale paint atomization model based on the hybrid Euler−Lagrange method was established in this paper, which included a large liquid micelle motion model, a particle motion model, and a turbulence flow model. The Euler method was adopted to capture the gas−liquid interface in the atomization flow field to describe the deformation and motion of large liquid micelles. The identification and transformation mechanisms of large liquid micelles and small particles were constructed by the particle motion model, and the motion of small droplets generated by paint atomization was tracked by the Lagrange method. The turbulence motion of the fluid in the process of paint atomization was described by a two-equation tu... [more]

The anaerobic digestion of swine manure was performed for more than 2 years in a biogas pilot plant with cereal residues as a mono-input, either by a simple intermittent substrate feeding or by feeding with an automated “autopilot” system under the direction of a Fuzzy logic control (FLC) system, working with a closed-loop feedback control. The pilot plant of the University of Applied Sciences in Nordhausen consisted of a 2.5 m3 dosage tank, a 2.5 m3 digestate tank, and a 1 m3 biogas reactor. Only three control parameters were used for FLC: pH, methane %, and the specific gas production rate (GPR) related to the organic loading rate (OLR), that is GPR/OLR m3 biogas/(kgVS d), vs = volatile solids. The specific GPR was referred to the OLR of the last feeding every 8 h in terms of kgVS/(m3 d). In test period I without an FLC system, a safe process with just an OLR of 4 kgVS/(m3 d) was reached, followed by an overloading and reactor disturbance at ≤6.3 kgVS/(m3 d) as indicated by acidifica... [more]

Given the importance of cyclin-dependent kinases (CDKs) in the maintenance of cell development, gene transcription, and other essential biological operations, CDK blockers have been generated to manage a variety of disorders resulting from CDK irregularities. Furthermore, CDK9 has a crucial role in transcription by regulating short-lived anti-apoptotic genes necessary for cancer cell persistence. Addressing CDK9 with blockers has consequently emerged as a promising treatment for cancer. This study scrutinizes the effectiveness of nature-derived compounds (geniposidic acid, quercetin, geniposide, curcumin, and withanolide C) against CDK9 through computational approaches. A molecular docking study was performed after preparing the protein and the ligands. The selected blockers of the CDK9 exerted reliable binding affinities (−8.114 kcal/mol to −13.908 kcal/mol) against the selected protein, resulting in promising candidates compared to the co-crystallized ligand (LCI). The binding affini... [more]

The Kaldor furnace smelting process is currently the mainstream process for treating copper anode slime, but the existence of copper, tellurium and other impurities has adverse effects on the recovery of gold and silver during the Kaldor furnace smelting stage. Therefore, it is necessary to pretreat the copper anode slime to remove these impurities before Kaldor furnace reduction smelting. However, the current pretreatment process of copper anode slime generally has the problem of low removal efficiency of copper and tellurium, and little research on the occurrence state of main metals in copper anode slime. Therefore, this study quantitatively determined the phase composition of Cu, Te, Pb, Bi, As, Sb, Se, Ag and Au, and hydrogen peroxide was introduced to enhance the leaching of impurities. The leaching behavior of each metal in copper anode slime was investigated in detail. The results demonstrate that Cu and Te in the copper anode slime mainly exist in the form of CuO and CuSO4 and... [more]