Processes, Volume 10, Issue 8 (August 2022) – 239 articles

In today’s linear economy, waste streams, environmental pollution, and social–economic differences are increasing with population growth. The need to develop towards a circular economy is obvious, especially since waste streams are composed of valuable compounds. Waste is a heterogeneous and complex matrix, the selective isolation of, for example, polyphenolic compounds, is challenging due to its energy efficiency and at least partially its selectivity. Extraction is handled as an emerging technology in biorefinery approaches. Conventional solid liquid extraction with organic solvents is hazardous and environmentally unfriendly. New extraction methods and green solvents open a wider scope of applications. This research focuses on the question of whether these methods and solvents are suitable to replace their organic counterparts and on the definition of parameters to optimize the processes. This review deals with the process development of agro-food industrial waste streams for biorefineries. It gives a short overview of the classification of waste streams and focuses on the extraction methods and important process parameters for the isolation of secondary metabolites. Full article

Lithium-ion batteries are state of the art and, still, their performance is constantly improving. To increase the energy density and electric conductivity, electrodes are usually calendered. Hereby, a higher degree of compaction, while reducing structural damage, can be reached by heating the calendering rolls. For industrially relevant line speeds, it is however questionable whether the contact time between electrode and roll is sufficient to reach the full positive effect of the increased temperature. This study shows a numerical approach based on the discrete element method to simulate the heating behavior of electrodes before and during calendering using a typical NMC-622-cathode as a model structure. To improve the results of existing, more simplified discrete element method simulations, which neglect the heat transfer through the carbon black–binder matrix, an extension with heat transfer through the carbon black–binder matrix has been implemented. Considering process parameters, such as calender roll temperature and line speed, as well as electrode parameters, such as thickness and porosity, this model can provide an individual calculation of the heating behavior to evaluate the need for a preheating device. Specifically, this study provides an in depth analysis of the influence of the mass loading on the heating time. It becomes clear that preheating can be of great relevance especially for high mass loadings, as well as high line speeds, as the required heating time increases by 116% when the basis weight is increased by 50%. Full article

The failure of thickeners at high temperature results in gelled acid acidification fracturing. To solve the problem, 8 kinds of polymers were synthesized by free radical polymerization of aqueous solution using AM, AMPS, NaAMPS, MAPTAC, DTAB and NVP as raw materials. The polymer was characterized by infrared spectroscopy and viscosity-average molecular weight, and the temperature resistance, rheology, salt resistance and shear resistance of the polymer solution were compared, and the mechanism was analyzed. The results show that the viscosity of GTY−2 is 181.52 mPa·s, and the viscosity loss rate is 56.89% at 180 °C and 100 s⁻¹, and its temperature resistance is the best. Meanwhile, the viscosity retention rate of GTY−2 is 84.58% after 160 min shear, showing the strongest shear resistance. The viscosity loss rate of GTY−1 in 20% hydrochloric acid solution is 80.88%, and its acid resistance is stronger than that of GTY−2. Moreover, due to the amphiphilicity of DTAB, the molecular hydration film becomes thicker, and the salt resistance of GTY−2 is lower than that of GTY−1. The experimental results show that GTY−1 and GTY−2 have good temperature resistance, salt resistance, acid resistance and shear resistance, and can be used as thickeners for acid fracturing with thickened acid to improve the effect of acid fracturing under high temperature conditions. Full article

While COVID-19 vaccines are generally available, not all people receive vaccines. To reach herd immunity, most of a population must be vaccinated. It is, thus, important to identify factors influencing people’s vaccination preferences, as knowledge of these preferences allows for governments and health programs to increase their vaccine coverage more effectively. Fortunately, vaccination data were collected by U.S. Census Bureau in partnership with the CDC via the Household Pulse Survey (HPS) for Americans. This study presents the first analysis of the 24 vaccination datasets collected by the HPS from January 2021 to May 2022 for 250 million respondents of different ages, genders, sexual orientations, races, education statuses, marital statuses, household sizes, household income levels, and resources used for spending needs, and with different reasons for not receiving or planning to receive a vaccine. Statistical analysis techniques, including an analysis of variance (ANOVA), Tukey multiple comparisons test, and hierarchical clustering (HC), were implemented to analyze the HPS vaccination data in the R language. It was found that sexual orientation, gender, age, and education had statistically significant influences on the vaccination rates. In particular, the gay/lesbian group showed a higher vaccination rate than the straight group; the transgender group had a lower vaccination rate than either the female or the male groups; older respondents showed greater preference for vaccination; respondents with higher education levels also preferred vaccination. As for the other factors that were not significant enough to influence vaccinations in the ANOVA, notable trends were found. Asian Americans had higher vaccination rates than other races; respondents from larger household sizes had a lower chance of getting vaccinated; the unmarried group showed the lowed vaccination rate in the marital category; the respondents depending on borrowed money from the Supplemental Nutrition Assistance Program (SNAP) showed a lower vaccination rate than people with regular incomes. Concerns regarding the side-effects and the safety of the vaccines were the two major reasons for vaccination hesitance at the beginning of the pandemic, while having no trust in the vaccines and no trust in the government became more common in the later stage of the pandemic. The findings in this study can be used by governments or organizations to improve their vaccination campaigns or methods of combating future pandemics. Full article

To improve the battery state of charge (SOC) of the electric vehicle (EV), this paper proposes a master–slave electro-hydraulic hybrid electric vehicle (MSEH-HEV). The MSEH-HEV uses a planetary row as the core transmission component to realize the interconversion between mechanical energy, hydraulic energy and electrical energy. Meanwhile, this paper introduces the six working modes in vehicle operation, matches the parameters of key components to the requirements of the vehicle’s performance and designs a rule-based control strategy to dominate the energy distribution and the operating mode switching. The research uses AMESim and Simulink to perform a co-simulation of the MSEH-HEV, and the superiority of MSEH-HEV is testified by comparing it with an AMESim licensed EV. The simulation results show that in the Economic Commission for Europe (ECE) and the Extra Urban Driving Cycle (EUDC), the MSEH-HEV has a 15% reduction in battery consumption, and the motor peak torque is greatly reduced. Moreover, a fuzzy control strategy is designed to optimize the rule-based control strategy. Ultimately, the optimized strategy further reduces the motor torque while maintaining the battery SOC. In this paper, the applicable research consists of the necessary references for the design matching of future electro-hydraulic hybrid electricity systems. Full article

Research aimed at finding alternative fuels to replace petroleum diesel (petrodiesel) used in controlled combustion engines (CCEs) has identified biodiesel as one of the main candidates, due to its sustainability and potential for use in energy matrices. In this study, the gas emissions from a diesel CCE were investigated, with a focus on total hydrocarbons (THC) and carbon monoxide (CO). Biodiesel (B100) samples derived from the transesterification of frying oil, produced applying conventional chemical catalysis (CC) or non-thermal plasma (NTP) technology, were tested as alternative fuels. Three engine rotation speeds were investigated (900, 1500, and 2500 rpm) and biodiesel samples obtained from the residual frying oil were compared with conventional road diesel (S-500) without biodiesel added, acquired from a gas station. Blends were also prepared with S-500 and B100 obtained applying NTP for 15 or 30 min, in mixes containing 2, 12, 20, and 50% of biodiesel. These blends showed reductions in THC and CO emissions of 62% and 80%, respectively, compared with the emissions for 100% S-500. Thus, biodiesel produced from frying oil offers low emissions of CO and THC, highlighting the potential for reductions using biodiesel produced applying the NTP technology. Full article

The non-oxygenated oil product of the pyrolysis of polypropylene cannot be used directly as an engine fuel due to its high content of alkenes. However, high pressure of hydrogen gas is commonly employed in the hydrotreatment of alkenes to produce alkanes. A semi-batch hydrogenation reaction using a hydrogen gas self-inducing impeller to internally recirculate the hydrogen gas has been implemented in the present work to provide small hydrogen gas bubbles so that the gas dispersion in the liquid phase is intensified. This technique is expected to improve the contact of hydrogen, oil, and the Ni/Al₂O₃ catalyst, which in turn alleviates high pressures of hydrogen gas. The hydrogenation reaction was performed at 185 °C with an impeller speed of 400 rpm. The pressure was varied from 2 to 8 bar. At the pressure of 2 bar, the main reactions are the hydrogenation of alkenes and cyclization of alkenes leading to cycloalkane formation, while at the pressures of 4, 6, and 8 bar, the main reactions are dimerization or oligomerization and hydrogenation of alkenes. The hydrogenation reaction shifts the carbon chain length in the oil towards the carbon chain length attributed to diesel fuel with more branching as the hydrogen pressure is increased. The gas inducement technique employed in the present work has succeeded in saturating almost all alkenes at moderate pressures (below 9 bar), lower than the pressures used by previous researchers, i.e., above 9 bar. Full article

Powder deaggregation in Dry Powder Inhalers (DPI) with carrier-based formulations is a key process for the effectiveness of drug administration. Carrier-wall collisions are one of the recognised mechanisms responsible for active pharmaceutical ingredient (API) aerosolisation, and DPI geometries are designed to maximise their efficacy. The detachment of fine and cohesive API particles is investigated at a fundamental level by simulating with DEM the normal collision of a carrier sphere with an API particle attached. The impact velocity at which detachment occurs (escape velocity) is determined as a function of key parameters, such as cohesiveness, coefficient of restitution, static and rolling friction. An analytical model for the escape velocity is then derived, examining the role of the initial position of the particle, cohesion model and particle size. Finally, the results are framed in the context of DPI inhalers, comparing the results obtained with impact velocities typically recorded in commercial devices. Full article

Bubble size and its distribution are the important parameters which have a direct impact on mass transfer in bubble column reactors. For this, a new robust image processing technique was presented for investigating hydrodynamic aspects and bubble behavior in real chemical or biochemical processes. The experiments were performed in a small-scale bubble column. The study was conducted for the wide range of clear liquid heights and superficial gas velocities. However, a major challenge in image analysis techniques is identification of overlapping or cluster bubbles. This problem can be overcome with the help of the proposed algorithm. In this respect, large numbers of videos were recorded using a high-speed camera. Based on detailed experiments, the gas–liquid dispersion area was divided into different zones. A foam region width was found as inversely proportional to the clear liquid height. An entry region width was found as directly proportional to the clear liquid height. Hydrodynamic parameters, including gas holdup, bubble size distribution, and Sauter mean bubble diameter were evaluated and compared for different operating conditions. The gas holdup was calculated from both height measurement and pixel intensity methods, and it was found to be indirectly proportional to clear liquid height. Bubble sizes affect the bubble column performance; therefore, bubbles are tracked to calculate the bubble size distribution. Experimental results proved that the proposed scheme is robust. Full article

Lignite’s large abundance, physicochemical properties and low cost are attractive for industrial wastewater remediation. However, directly applying lignite for wastewater treatment suffers low efficiency. Here, we synthesize highly efficient zero-valent iron (ZVI)-decorated lignite carbon through the in-situ carbonization of a lignite and FeCl₂ mixture for heavy metal removal. The effect of carbonization temperature on the morphology, structure and crystallite phases of ZVI-decorated lignite carbons (ZVI-LXs) was investigated. At an optimized temperature (i.e., 1000 °C), ZVI particles were found evenly distributed on the lignite matrix with the particles between 20 to 190 nm. Moreover, ZVI particles were protected by a graphene shell that was formed in situ during the carbonization. The synthesized ZVI-L1000 exhibited higher Cu²⁺, Pb²⁺ and Cd²⁺ stripping capacities than pristine lignite in a wide pH range of 2.2–6.3 due to the surface-deposited ZVI particles. The maximum Langmuir adsorption capacities of ZVI-L1000 for Cd²⁺, Pb²⁺ and Cu²⁺ were 38.3, 55.2 and 42.5 mg/g at 25 °C, respectively, which were 7.8, 4.5 and 10.6 times greater than that of pristine lignite, respectively. ZVI-L1000 also exhibited a fast metal removal speed (~15 min), which is ideal for industrial wastewater treatment. The pseudo-second-order model fits well with all three adsorptions, indicating that chemical forces control their rate-limiting adsorption steps. The reduction mechanisms of ZVI-L1000 for heavy metals include reduction, precipitation and complexation. Full article

This paper focuses on the use of AI in various MEMS (Micro-Electro-Mechanical System) biosensor types. Al increases the potential of Micro-Electro-Mechanical System biosensors and opens up new opportunities for automation, consumer electronics, industrial manufacturing, defense, medical equipment, etc. Micro-Electro-Mechanical System microcantilever biosensors are currently making their way into our daily lives and playing a significant role in the advancement of social technology. Micro-Electro-Mechanical System biosensors with microcantilever structures have a number of benefits over conventional biosensors, including small size, high sensitivity, mass production, simple arraying, integration, etc. These advantages have made them one of the development avenues for high-sensitivity sensors. The next generation of sensors will exhibit an intelligent development trajectory and aid people in interacting with other objects in a variety of scenario applications as a result of the active development of artificial intelligence (AI) and neural networks. As a result, this paper examines the fundamentals of the neural algorithm and goes into great detail on the fundamentals and uses of the principal component analysis approach. A neural algorithm application in Micro-Electro-Mechanical System microcantilever biosensors is anticipated through the associated application of the principal com-ponent analysis approach. Our investigation has more scientific study value, because there are currently no favorable reports on the market regarding the use of AI with Micro-Electro-Mechanical System microcantilever sensors. Focusing on AI and neural networks, this paper introduces Micro-Electro-Mechanical System biosensors using artificial intelligence, which greatly promotes the development of next-generation intelligent sensing systems, and the potential applications and prospects of neural networks in the field of microcantilever biosensors. Full article

This work focused on the optimization of the ultrasound (US) extraction of polyphenols from sweet cherry pulp by monitoring cyanidin-3O-rutinoside, quercetin-3O-rutinoside, and trans-3-O-coumaroylquinic acid, representing the main anthocyanin, flavonol, and hydroxycinnamate, respectively, identified in the extracts through chromatographic analyses (HPLC-DAD), as output variables. The optimization was performed following a two-level central composite design and the influence of the selected independent variables (i.e., extraction time and solid to solvent ratio) was checked through the response surface methodology. The maximum recovery of the phenolic compounds was obtained at 3 min and 0.25 g/mL in water/ethanol (1:1, v/v) at a set temperature (25 °C), sonication power (100 W), and sonication frequency (37 kHz). Subsequent validation experiments proved the effectiveness and reliability of the gathered mathematical models in defining the best ultrasound-assisted extraction conditions. Full article

In this brief, we consider the mean-field type ${\mathcal{H}}_{-}$ index problem for stochastic Markovian jump systems. A sufficient condition is derived for stochastic Markovian jump systems with $(x,u)$-dependent noise based on generalized differential Riccati equations. Especially for stochastic Markovian jump systems with only x-dependent noise, a sufficient and necessary condition is developed to characterize ${\mathcal{H}}_{-}$ index larger than some $\xi >0$. Finally, a numerical example is addressed to verify the effectiveness of our obtained results. Full article

Aiming at the problem of low positioning accuracy caused by modal aliasing and noise interference in DC cable fault location analysis of a VSC-HVDC system, a double-ended fault location method for flexible DC cables based on improved local mean decomposition is proposed. Firstly, the local mean decomposition (LMD) is used to decompose the six-mode voltage signal to obtain the product function (PF) component; then, to overcome the problem that the instantaneous frequency function of the LMD is limited by the extreme value, the Hilbert transform is performed on the PF1 to obtain the instantaneous frequency curve, and the arrival time of the voltage traveling wave head is determined from the mutation information. Finally, the fault distance is obtained by using the principle of double-ended traveling wave fault location. Different fault conditions are simulated, analyzed, and compared with wavelet transform and Hilbert–Huang transform. The results show that the proposed method has a positioning error within 1%, and it is less affected by interference noise and transition resistance. Full article

Agricultural productivity plays a vital role in a country’s economy, which can be increased by providing the proper water needed for crops. Proper water provision ensures suitable moisture and appropriate conditions essential for crops, water resource preservation, minimized water wastage, and energy consumption. However, adequate water provision is challenging due to intermittent and uncertain environmental and weather conditions. On this note, a model with uncertain and stochastic conditions (rain, wet, dry, humidity, and moisture) capturing abilities is needed. Thus, a smart-sensors-based solar-powered system is developed for monitoring and controlling the tube well that ensures proper water provision to crops. The developed system properly checks weather and environmental conditions (rain, temperature, irradiance, humidity, etc.), soil conditions (wet or dry), and crop conditions to monitor and regulate water flow accordingly to minimize water and energy consumption wastage. The developed system is an integrated system of four modules: Arduino with a built-in Atmel AT mega microcontroller, sensors, solar power, and a global system for mobile communication (GSM). The GSM module exchanges acknowledgement messages with the operator and controller about the various statuses, such as weather and environmental conditions, soil conditions (wet or dry), crop conditions, and the toggle status of the motor (OFF, ON/main power supply, or solar power). In order for the controller module to determine the motor state, the sensors module computes many parameters, including rain, wet, dry, humidity, and moisture. In addition, the sensor module also prevents the motor from dry running. The developed smart irrigation system is superior to existing irrigation systems in aspects of water wastage and energy consumption minimization. Full article

Identifying combustion regimes is important for understanding combustion phenomena and the structure of flames. This study proposes a combustion regime identification (CRI) method based on rotated principal component analysis (PCA), clustering analysis and the back-propagation neural network (BPNN) method. The methodology is tested with large-eddy simulation (LES) data of two turbulent non-premixed flames. The rotated PCA computes the principal components of instantaneous multivariate data obtained in LES, including temperature, and mass fractions of chemical species. The frame front results detected using the clustering analysis do not rely on any threshold, indicating the quantitative characteristic given by the unsupervised machine learning provides a perspective towards objective and reliable CRI. The training and the subsequent application of the BPNN rely on the clustering results. Five combustion regimes, including environmental air region, co-flow region, combustion zone, preheat zone and fuel stream are well detected by the BPNN, with an accuracy of more than 98% using 5 scalars as input data. Results showed the computational cost of the trained supervised machine learning was low, and the accuracy was quite satisfactory. For instance, even using the combined data of CH4-T, the method could achieve an accuracy of more than 95% for the entire flame. The methodology is a practical method to identify combustion regime, and can provide support for further analysis of the flame characteristics, e.g., flame lift-off height, flame thickness, etc. Full article

Both anthropogenic and natural sources of pollution are regionally significant. Therefore, in order to monitor and protect the quality of Langat River from deterioration, we use Artificial Intelligence (AI) to model the river water quality. This study has applied several machine learning models (two support vector machines (SVMs), six regression models, and artificial neural network (ANN)) to predict total suspended solids (TSS), total solids (TS), and dissolved solids (DS)) in Langat River, Malaysia. All of the models have been assessed using root mean square error (RMSE), mean square error (MSE) as well as the determination of coefficient (R²). Based on the model performance metrics, the ANN model outperformed all models, while the GPR and SVM models exhibited the characteristic of over-fitting. The remaining machine learning models exhibited fair to poor performances. Although there are a few researches conducted to predict TDS using ANN, however, there are less to no research conducted to predict TS and TSS in Langat River. Therefore, this is the first study to evaluate the water quality (TSS, TS, and DS) of Langat River using the aforementioned models (especially SVM and the six regression models). Full article

Currently, the concern for achieving and fulfilling the Sustainable Development Goals (SDGs) is a constant in advanced societies. The scientific community and various organisations are working on obtaining an information system that will make it possible to offer the necessary value to this type of sustainability information. The article aims to incorporate criteria on the technology used in the reporting system, specifically in collecting the different types of data and generating other interfaces. The methods described here are carried out on a specific case study, a Smart City, showing the different types of data that exist and the possible interfaces that allow objective monitoring of the achievement of the SDGs. It is, therefore, a descriptive study of a process whose results are the establishment of criteria concerning the different data sources as well as the generation of a set of interfaces that motivate the monitoring that can be carried out in a specific city to observe its compliance and deviations from critical values, for example, environmental. The main conclusions of this research establish the importance of incorporating and sizing the technology needed to develop the criteria for monitoring the SDGs. There is a need for convergence between the correct, objective and universal provision of this type of sustainability information and the technology used for the collection and presentation of the data. Full article

Countries have started to aggressively undertake energy structure transformation strategies in order to reach the objective of carbon neutrality. Both clean and efficient coal energy use and clean energy use will be crucial to the process of changing the energy structure since the two cannot be totally replaced within a short period of time. In this study, we quantify emotions as an irrational factor, combine them with an evolutionary game using RDEU theory, and build an evolutionary game model between government regulators and energy consumers. We then analyze how low-carbon emotions of decision-makers affect their choice of strategy and the transformation of the energy structure. The findings support that by affecting the relative importance of each strategic choice, emotions have a profound impact on the evolutionary steady state of the system. Appropriate stress and anxiety can increase decision-makers’ feelings of responsibility, while pleasant emotions frequently support strategic conduct. The main countermeasures are as follows: Allow government regulators and energy consumers to properly release positive information, with government regulators forming subsidies and energy consumers actively cooperating and promoting low-carbon activities. This will properly guide the low-carbon sentiment of game subjects to keep them realistically pessimistic. Full article

The objective of this research work was to investigate the potential of control models based on reinforcement learning in the optimization of solar thermal cooling systems (STCS) operation through a case study. In this, the performance of the installation working with a traditional predictive control approach and with a reinforcement learning (RL)-based control approach was analyzed and compared using a specific realistic simulation tool. In order to achieve the proposed objective, a control system module based on the reinforcement learning approach with the capacity for interacting with the aforementioned realistic simulation tool was developed in Python. For the studied period and the STCS operating with a control system based on RL, the following was observed: a 35% reduction in consumption of auxiliary energy, a 17% reduction in the electrical consumption of the pump that feeds the absorption machine and more precise control in the generation of cooling energy regarding the installation working under a predictive control approach. Through the obtained results, the advantages and potential of control models based on RL for the controlling and regulation of solar thermal cooling systems were verified. Full article

A large number of microfluidic applications are based on effective mixing. In the application of water purification, the contaminated water needs to be effectively mixed with a solution that is loaded with nanoparticles. In this work, the Tesla valve was used as a micromixer device in order to evaluate the effect of this type of geometry on the mixing process of two streams. For this reason, several series of simulations were performed in order to achieve an effective mixing of iron oxide nanoparticles and contaminated water in a duct. In the present work, a stream loaded with Fe₃O₄ nanoparticles and a stream with contaminated water were numerically studied for various inlet velocity ratios and initial concentrations between the two streams. The Navier–Stokes equations were solved for the water flow and the discrete motion of particles was evaluated by the Lagrangian method. Results indicate that the Tesla valve can be used as a micromixer since mixing efficiency reached up to 63% for V_p/V_c = 20 under various inlet nanoparticles rates for the geometry of the valve that was used in this study. Full article

An electro-hydraulic servo pump control system realizes the basic action of a hydraulic cylinder by controlling the servo motor, which effectively improves the problems of a traditional valve control system such as high energy consumption, low power-to-weight ratio, and poor anti-pollution ability. However, the static accuracy and dynamic performance of an electro-hydraulic servo pump control system are limited due to the electro-hydraulic coupling and flow nonlinearity. Based on this, in this paper, we establish a mathematical model of an electro-hydraulic servo pump control system. Starting from the internal control mechanism of the system, the Simulink simulation model is established to analyze the dynamic response of the system current loop, speed loop, position loop, and pressure loop. The system parameters are obtained by combining the system dynamic analysis and component technology samples. The position/force control model of the electro-hydraulic servo pump control system is built for simulation, and the experimental platform is built for experimental verification. The results show that the system position/force control can achieve good dynamic response and steady-state accuracy after the parameters are determined based on the dynamic analysis of control loops. Full article

Hydraulic fracture networks, especially fracture geometry, height growth, and proppant transport within the networks, present a critical influence on productivity evaluation and optimization of fracturing parameters. However, information about hydraulic fracture networks in post-fractured formations is seldom available. In this study, the characteristics (density and orientation) of hydraulic fractures were obtained from field observations of cores taken from conglomerate hydraulic fracturing test site (CHFTS). A large number of fractures were observed in the cores, and systematic fracture description was carried out. The fracture analysis data obtained includes fracture density, fracture depth, fracture orientation, morphology, fracture surface features, apertures, fill, fracture mechanical origin (type), etc. Our results show that 228 hydraulic fractures were intersected in a span of 293.71 m of slant core and composed of irregularly spaced single fractures and fracture swarms. One of the potential sources of the observed fracture swarms is near-wellbore tortuosity. Moreover, for regions far away from the wellbore, reservoir heterogeneity can promote complex hydraulic fracture trajectories. The hydraulic fractures were mainly cross-gravel and high-angle fractures and align with maximum horizontal stress (S_Hmax) ± 15°. The fracture density, orientations, and types obtained from the core fracture description provided valuable information regarding fracture growth behavior. For the near-wellbore area with a transverse distance of less than 25 m from the hydraulically-fractured wellbore, tensile fractures were dominant. While for the area far away from the wellbore, shear fractures were dominant. Our results provide improved understanding of the spatial hydraulic fracture dimensions, proppant distribution, and mechanism of hydraulic fracture formation. The dataset acquired can also be used to calibrate numerical models and characterize hydraulic fracture geometry and proppant distribution. Full article

Wind resistance is one of the most important safety targets for high-rise buildings, especially slab-shaped ones with relatively large length–width ratios. In this study, the characteristics of wind pressure on a reduced-scale model of a slab-shaped high-rise building were analyzed experimentally. The experiment was conducted using the DTC Initium electronic scanning pressure measurement system in the wind tunnel at the Xiamen University of Technology, China. The spatial distribution and time-frequency characteristics of the wind pressure signals were analyzed with various wind flow directions under uniform and boundary-layer inflow conditions. The results show that both of the inflow conditions and the wind directions have significant influences on the magnitude and distribution characteristics of the wind pressure on the building surfaces. The wavelet transform-based analysis shows that the wind pressure on the building surfaces presents obvious intermittent characteristics, with the instantaneous energies pulsating intensively in the time-frequency domain, illustrating the unsteady nature of the wind pressure loads on the building. The influence and risk of the unsteady pulsating pressure loads should be considered when evaluating the wind-resistant performances of this type of building. Full article

The thermal management of electronic devices has become a major problem in recent years. Therefore, there is a growing need for research on many new materials and innovative fluids due to the developing technology and increasing cooling need in electronic systems. In this paper, heat transfer from a plate fin and pin fin type heat sinks that were placed in a water block that are used in electronic systems was investigated. A base fluid (pure water) and 0.1% mass concentration Al₂O₃-H₂O nanofluid were used as cooling fluids. The experiments were carried out for volumetric flow rates varying between 100 and 800 mL/min and heat flux values of 454.54 W/m² and 1818.18 W/m². The results demonstrated that the Al₂O₃-H₂O nanofluid on the empty surface provided a maximum improvement of 10.5% in heat transfer compared to the base fluid. In the use of plate finned heat sink, the maximum amount of improvement in heat transfer compared to the empty surface was obtained approximately 64.25% for the base fluid and 82.8% for the nanofluid. A similar comparison was made for the pin-fin heat sink, a maximum thermal improvement of 56.4% in the base fluid and 70.27% in the use of nanofluid was determined. Full article

Health monitoring and fault diagnosis of liquid rocket engine (LRE) are the most important concerning issue for the safety of rocket’s flying, especially for the man-carried aerospace engineering. Based on the sensor measurement signals of a certain type of hydrogen-oxygen rocket engine, this paper proposed a real-time fault detection approach using a genetic algorithm-based least squares support vector regression (GA-LSSVR) algorithm for the real-time fault detection of the rocket engine. In order to obtain effective training samples, the data is normalized in this paper. Then, the GA-LSSVR algorithm is derived through comprehensive considerations of the advantages of the Support Vector Regression (SVR) algorithm and Least Square Support Vector Regression (LSSVR). What is more, this paper provided the genetic algorithm to search for the optimal LSSVR parameters. In the end, the computational results of the suggested approach using the rocket practical experimental data are given out. Through the analysis of the results, the effectiveness and the detection accuracy of this presented real-time fault detection method using LSSVR GA-optimized is verified. The experiment results show that this method can effectively diagnose this hydrogen-oxygen rocket engine in real-time, and the method has engineering application value. Full article

In process optimization, a process is adjusted so as to optimize a set of parameters while meeting constraints, with the objective to either minimize the total processing time or maximize the throughput. This article focused on the process optimization of a fully automated yogurt and flavor-filling machine developed based on the industrial revolution 4.0 concept. Mathematical models were developed for minimizing the total processing time or maximizing the throughput of an Industry 4.0-based yogurt filling system with two different machine settings called Case-I and Case-II. In Case-I, the yogurt and flavors are filled at two distinct points while Case-II considers the filling of yogurt and flavors at a single point. The models were tested with real data and the results revealed that Case-II is faster than Case-I in processing a set of customer orders. The results were used as inputs for the single-dimension rules to check which one results in more intended outputs. Additionally, different performance measures were considered and the one with most importance to the management was selected. Full article

In order to prepare a novel landfill liner material, we used industrial calcium-containing waste (slag, fly ash, and desulfurized gypsum) to solidify municipal sludge. The mechanical and permeability properties of the solidified sludge material (SSM) were evaluated using straight shear, uniaxial compression, and permeability tests. The hydration products, microscopic morphology, and elemental composition of the SSM after the wet and dry cycles were analyzed using a combination of scanning electron microscopy (SEM + EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). The SSM has high strength and low hydraulic conductivity. The values of cohesion c and internal friction angle φ reached 0.45–3.31 MPa and 6.52–36.28°. The SSM exhibited a compressive strength of 0.93–11.67 MPa and hydraulic conductivity of 4.80 × 10⁻⁹–1.34 × 10⁻⁷ cm/s. Analysis shows that SiO₂, Al₂O₃, and CaO in industrial calcium-containing solid wastes and sludges produce dense bulk and agglomerated C-S-H and C-A-S-H gels under alkali excitation. The optimum ratio of sludge, desulfurized gypsum, fly ash, and slag in the solidified sludge was 1:0.61:0.62:0.54, whereas the optimum exciter was Ca(OH)₂. The SSM may be used as a good barrier material to prevent water seepage in landfills. Full article

Erosion wear is a common failure form of slotted screen in service. In this paper, based on CFD software and sand production data of a gas field in the Tarim Basin, the particle velocity and shear force at the slot of the flow field in the sieve tube were studied to determine the maximum area of erosion; at the same time, the velocity, viscosity, particle size and concentration of sand-carrying fluid were analyzed by orthogonal test, and the regression model of multi-factor maximum erosion rate was established. ① Through the analysis of the four factors on the degree of dependent variables, the order of the primary and secondary factors are: sand-carrying liquid flow rate, particle concentration, fluid viscosity, particle diameter, the effect of fluid viscosity and particle diameter on erosion rate is relatively small; ② According to the analysis of variance and range, the combination scheme of minimum erosion generation is obtained, and the calculation model of the erosion rate of the slotted screen is established. In order to reduce the erosion and abrasion in the actual oil and gas production process, the reasonable flow control and precise sand control method design and precision selection can be adopted; it provides a design basis for sand control and long-term effects of production in high-yield gas field. Full article

This study investigated the effects of the addition of chitosan (0–1.0%) or glucono-δ-lactone (GDL) (0–60 mM) on the gel properties, microstructure, and texture of pea-based tofu-type product. Following the addition of 0.5% chitosan or 20 mM GDL, we observed a significant decrease in the hardness and cohesiveness of the tofu, resulting in a slightly discontinuous network structure with pores smaller than those in samples without chitosan or GDL. SDS-PAGE analysis revealed the induced aggregation of pea legumin (11S) and vicilin (7S) subunits (30, 34, and 50 kDa), legumin α subunit (40 kDa), and legumin β subunit (20 kDa) by chitosan or GDL. It appears that chitosan and GDL could potentially be used as food additives for the development of texture-modified pea-based tofu-type products. Full article