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 multifracture competitive growth from a horizontal well is an essential issue in multi-cluster fracturing design. In recent years, extremely limited entry (ELE) fracturing has been implemented to promote uniform multifracture growth. However, the mechanism of multifracture growth and ELE design remain unclear. Based on the planar three-dimensional multifracture propagation model, a multi-cluster horizontal well fracturing model that considers ELE design has been developed. The model considers flow in the wellbore and fluid filtration loss in the fracture. The simulator enables the simulation and analysis of non-uniform in situ stress, filtration loss, and fracture properties. Using this program, we simulated the propagation process of multiple clusters of fractures in ELE fracturing of horizontal wells. The results show the following: The perforation friction in the ELE fracturing can counteract the difference in fluid allocation caused by stress interference, allowing all clusters... [more]

In this study, we propose a hypocenter localization algorithm that uses the time difference of arrival (TDOA) and angle of arrival (AOA) as a hybrid model. The hypocenter measurements are detected by the accelerator sensors of the four separate observatories that are closest to the origin of an earthquake. The measurements are calibrated by the proposed deep learning P-onset picking system with short-time Fourier transform (STFT) signal analysis because the accurate detection of Primary waves (P-waves) is limited by seismic environmental noise. The revised measurements are used to calculate the precise distances between the observatories and hypocenters. The proposed hybrid TDOA/AOA is represented by a linear matrix equation that includes the unknowns of the precise distances, coordinates, and arrival angles to the observatories. We estimate a hypocenter using the constrained least squares method (CLS) under the constraints of the TDOA/AOA. The objective function with the constraints i... [more]

In recent years, we have seen an increasing dependency between different urban critical infrastructures, which raises the demands on their analysis and cybersecurity. Current open-source solutions do not provide simulations of interconnected data networks and power grids, which are essential for analysing of both infrastructures weak parts and reducing the risk of emerging threats. The main purpose of this paper is to describe the design of a simulation platform that provides this type of simulation to customers using the virtual user interface. The paper describes the development of a complex model of interconnected power and data infrastructures. Created virtualization platform that consists of several open-source tools is described in detail. Outputs of this paper can be used for analysis of critical infrastructures at the level of urban networks.

Emerging contaminants (ECs) include a diverse group of compounds not commonly monitored in wastewaters, which have become a global concern due to their potential harmful effects on aquatic ecosystems and human health. In the present work, six ECs (ibuprofen, diclofenac, erythromycin, triclosan, imidacloprid and 17α-ethinylestradiol) were monitored for nine months in influents and effluents taken from four wastewater treatment plants (WWTPs). Except for the case of ibuprofen, which was in all cases in lower concentrations than those usually found in previous works, results found in this work were within the ranges normally reported. Global removal efficiencies were calculated, in each case being very variable, even when the same EC and facility were considered. In addition, the SimpleTreat model was tested by comparing simulated and real ibuprofen, diclofenac and erythromycin data. The best agreement was obtained for ibuprofen which was the EC with the highest removal efficiencies.

In this work, the principle of metamorphic mechanism is optimized for the product design based on variable topological structures. One metamorphic element consisting of kinematic pair and kinematic size is proposed firstly and a configuration synthesis strategy for feed mechanism is performed in term of the translocation, inversion and duplication variation methods. Metamorphic elements are obtained by decomposing the source metamorphic mechanism. A novelty configuration scheme based on constraint variation features is established by the solution of the constraint relationship of metamorphic elements, and three kinds of configurations are synthesized. Comparisons with kinematic performances between source mechanism and developed mechanism configurations are modelled by the kinematic simulation. Results demonstrate that the multiple types of metamorphic mechanisms can be successfully synthesized, and the demands of functional targets are satisfied completely.

Patient-centered communication (PCC) quality is critical to increasing the quality of patient-centered care. Based on the nationally representative data of the Health Information National Trends Survey (HINTS) 2019−2020 (N = 4593), this study combined four machine learning methods, namely, Generalized Linear Models (GLM), Random Forests (Random Forests), Deep Neural Networks (Deep Learning), and Gradient Boosting Machines (GBM), to identify important PCC predictors through variable importance metrics. Fifteen variables were identified as important predictors, involving multiple dimensions, such as individual sociodemographic characteristics, health-related factors, and individual living habits. Among them, four novel potential associated variables are included, an individual’s level of verbal expression, exercise habits, etc., which significantly impacted respondents’ perceived PCC quality. This study revealed the value of combining feature selection with machine learning approaches to... [more]

The Shunbei oil formation is a deep, high-temperature carbonate reservoir. Acid fracturing is an effective technology to stimulate this formation. For acid fracturing, the temperature field is fundamental information for the acid system selection, acid−rock reaction, live acid penetration distance prediction, acid fracturing design, etc. Therefore, in this paper, we conduct a numerical study on the temperature field in acid fracturing to account for the acid−rock reaction in the Shunbei formation. Firstly, a new mathematical model of the fracture temperature field during acid fracturing is established based on the laws of mass and energy conservation and acid−rock reaction kinetics. The fracture model is based on a PKN model, which accounts for a few factors, such as the acid−rock reaction heat, acid−rock reaction rate dependence on the temperature, and the fracture width change with acid erosion. Then, the numerical mode is developed. Next, an extensive numerical study and a parameter... [more]

In this study, an integrated electrospray pyrolysis process was designed to continuously produce a representative nano-catalyst TiO2. A numerical model was also developed to simulate the flow behaviors and droplet transport inside the reactor. The electric field model and particle tracking model were coupled to describe the electrospray pyrolysis process. The effects of key parameters, including electrode configurations, applied voltage, droplet charge density, and flow type of carrying gas on the electric field distribution, particle distribution, and particle collection efficiency, were investigated to help the design and optimization of the integrated electrospray pyrolysis reactor. The results show that the electric potential and electric field strength decrease rapidly with increasing distance away from the nozzle. In addition, the results show that the droplet charge is an important parameter affecting the collection efficiency. The investigation of the key parameters shows that... [more]

Mold temperature is the key parameter in determining the morphology of molded parts. Uneven temperature distribution could induce significant effects on part performances. In such cases, uneven temperature is induced to analyze the morphology developed in the molded specimens. The technology used for controlling mold temperature during the process is crucial to maintain the short processing time. This paper proposed a strategy for controlling mold temperature during the process, avoiding a significant increase in processing time. A thin electrical heater is designed and adapted below the cavity surface, allowing for the increase of the cavity surface temperature soon after the mold closure, and the fast decrease of the mold temperature soon after the filling. The effect of several heating powers and heating durations on the molecular orientation was analyzed and exploited considering the temperature and flow field realized during the process.

Numerical investigations were conducted on the mixing efficiency of resonant acoustic mixing (RAM) technology using a high-viscosity mixture under vertically forced vibrations. The density distribution was analyzed for a mixture of high-melting explosive (HMX) and trinitrotoluene (TNT). The effects of mixing time, amplitude, frequency, fill level, and mixing vessel geometry were evaluated to determine their influence on the blend homogeneity and the efficiency of the mixing process. The results showed that amplitude and frequency both have significant influences on the mixing efficiency of the RAM process. With higher values of amplitude and frequency, the mixing efficiency was very good, and uniform mixing was achieved in a much shorter time. At the same time, it was seen that geometric changes did not affect the mixing process; in contrast, varying the fill level did have a significant effect. This approach could potentially be used for pharmaceutical blending, cosmetics, and explosi... [more]

Sorption is often carried out in stirred batch reactors without any consideration of how much mixing is sufficient to avoid the effect of diffusion without compromising yield and cost due to overmixing. Therefore, the focus of this work was to study how the maximum sorption capacity, removal efficiency, kinetics and power consumption (P) of the studied process are affected by different mixing speeds, i.e., impeller speed/minimum impeller speed for complete suspension (N/NJS) ratio values and zeolite suspension mass concentrations. Experiments were conducted in a baffled reactor with the propeller at a standard off-bottom clearance. In addition to the experimental studies, numerical modelling approaches were carried out to investigate the sorption process using a transient multiphase computational fluid dynamics model and fitting selected kinetic models. The results show that an increase in zeolite mass leads to a slight increase in the NJS and consequently PJS. The impeller speed affec... [more]

This paper constructs a nonlinearly parametrized hypersonic cruise vehicle model on the basis of the existing on-orbit flight data using a curve-fitting technique. The hypersonic cruise vehicle system is separated into two interconnected subsystem: an attitude subsystem with rotational dynamics and a velocity subsystem with engine dynamics. The continuous adaptive controllers are designed for two subsystems using a novel function bounding technique and appropriate coordinate transformations, respectively, which ensure the global boundedness of all signals and achieve the non-zero equilibrium point regulation of nonlinearly parametrized hypersonic vehicle systems. One of the implications of this result is that growing nonlinearities in the uncertain model of the hypersonic vehicle system may be allowed for global stabilization. A simulation result verifies the effectiveness of the proposed adaptive control scheme.

Supply chain disruptions and challenges have and will always exist, but preparing in advance and improving resilience for the upcoming consequences should be the utmost important goal. This paper explores trends that affect innovation in the technological sphere of supply chain systems. More precisely, the research is focused on Digital Twin technology applicability through other logistics IT trends and aims to research the pressing issue of ensuring the visibility and resilience of future supply chain systems. The paper’s objective is to produce a conceptual model enabling the investment assessment of the necessary IT resources. Initially, a theoretical confirmation of logistics IT trends’ relevance to supply chain systems was established. After, propositions of Digital Twin technology applications to other logistics IT trends were made, which were divided into corresponding constant multitudes of supply chain systems. Lastly, the conceptual model for the investment assessment of the... [more]

This study used computational fluid dynamics for low greenhouse effect refrigerant (R-513A) simulation analysis in the two-stage 150 USRT class oil-free centrifugal refrigerant compressor using integrated part load value (IPLV) and internal flow field. The compressor rotor speed and mass flow rate for the IPLV working conditions with various loads were planned using Stage 1 and Stage 2 simulations, respectively. The performance and flow field numerical simulation analyses for the two-stage centrifugal compressor is discussed. This study used Ansys-CFX software for numerical simulation analysis and the conservation form of a 3D steady-state Navier−Stokes equation set with the finite volume discretization method for computation. The computing mode produced better computing efficiency and flexible mesh setting using the k-omega (k-ω) model, which has better computational performance in the near wall boundary layer and low Reynolds number flow field (used as the turbulence model) for simul... [more]

In recent years, global climate change, environmental pollution, and energy shortage have become increasingly serious [...]

γ-valerolactone can be a game-changer in the chemical industry because it could substitute fossil feedstocks in different fields. Its production is from the hydrogenation of levulinic acid or alkyl levulinates and can present some risk of thermal runaway. To the best of our knowledge, no studies evaluate the thermal stability of this production in a continuous reactor. We simulated the thermal behavior of the hydrogenation of butyl levulinate over Ru/C in a continuous stirred-tank reactor and performed a sensitivity analysis. The kinetic and thermodynamic constants from Wang et al.’s articles were used. We found that the risk of thermal stability is low for this chemical system.

In 2019, a new lethal and mutant virus (COVID-19) spread around the world, causing the deaths of millions of people. COVID-19 demonstrates that scientists are involved in significant research efforts to face bacteria with less effort than that dedicated to viruses. Since then, engineers and bio-materials scientists have been trying to develop antiviral research and find a suitable effective medication. Strategies and opportunities for interference diagnostics, treatment strategies, and predicting future factors became mandatory. From a statistical point of view, estimating and modelling these factors play an important role in preventing future viral epidemics. In this article, modelling the recovery rate of COVID-19 is investigated through a new distribution which is called the unit exponential Pareto distribution. The new continuous distribution with three parameters displays a prominent level of flexibility to model decreasing, symmetric, and asymmetric data with a monotone failure r... [more]

Bearings and other revolute pairs in gear drives will form clearances due to wear after working for a long time, which will aggravate the vibration and noise of the gear. Therefore, taking the gear drives with revolute pair clearance as the research object, the calculation formulas of the backlash and contact ratio is derived, and the time-varying mesh stiffness model considering the clearance is presented in this work. Then, a nonlinear dynamic model for the gear drives with revolute pair clearance is proposed by combining the backlash, contact ratio and the time-varying mesh stiffness. The effects of the clearance on the meshing stiffness, load sharing factor and nonlinear behavior are investigated. Results indicate that the revolute pair clearance weakens the meshing stiffness and increases working hours in single teeth contact area, thereby increasing the risk of premature failure of the gear drive. In addition, the revolute pair clearance has negligible effect on the nonlinear beh... [more]

This paper presents the modeling and simulation of an industrial-scale chemical looping combustion (CLC) power plant, including all process units (reactors, flue gas treatment units, heat integration, steam cycle, and CO2 compression train). A model of a 525 MWth CLC power plant was built using a rigorous representation of the solid fuel and oxygen carrier. Petcoke was considered the main fuel of interest in this study, and it is compared with other solid fuels. The flue gas compositions obtained with the model show that cleanup units are mandatory to comply with CO2 quality requirements. High levels of flue gas treatment, including 97.1% deNOx and 99.4% deSOx, are needed to achieve typical specifications for captured CO2. This is mainly due to the high level of contaminants in the fuel, but also to the absence of nitrogen in the CLC flue gas, thus resulting in higher concentrations for all substances. The high level of flue gas treatment is thus one of the important challenges for sol... [more]

Industrial automation systems, such as chemical processes, manufacturing processes, power networks, transportation systems, sustainable energy systems, wireless sensor networks, robotic systems, and biomedical systems, are becoming more complex [...]

Methanol is considered a sustainable alternative energy source due to its ease of storage and high-octane rating. However, the conventional methanol production process is accompanied by resource consumption and significant greenhouse gas emissions. The electrochemical reaction of electrochemically reacted hydrogen (H2) with captured carbon dioxide (CO2) offers an alternative route to methanol production. This paper presents a new green poly-generation system consisting of a parabolic trough solar collector (PTC) unit, an organic Rankine cycle (ORC) unit, a CO2 capture unit, an alkaline electrolysis unit, a green methanol synthesis and distillation unit, and a double-effect lithium bromide absorption refrigeration (ARC) unit. The system mainly produced 147.4 kmol/h of methanol at 99.9% purity, 283,500 kmol/h of domestic hot water, and a cooling load of 1341 kW. A total 361.34 MW of thermal energy was supplied to the ORC by the PTC. The alkaline electrolysis unit generated 464.2 kmol/h o... [more]

A compact static mixer for gas−liquid dispersion in pipelines is studied in this paper with a Reynolds averaged two fluid model approach. A procedure based on the lumped parameter solution of a population balance model is applied to obtain the bubble Sauter mean diameter needed to model the interphase forces. The gas distribution in the pipe is analyzed in two different operative conditions and the efficiency of the static mixer is assessed in terms of the gas homogeneity in the pipe section, with low coefficients of variations being obtained. A computational model to obtain the volumetric mass transfer coefficient, kLa, developed for partially segregated systems is applied finding kLa values comparable to those typically obtained with other static mixers. The proposed computational model allows us to locally analyze the oxygen transfer rate by observing the limitations due to gas accumulation behind the body of the static mixer, which leads to the local depletion of the driving force.... [more]

This article describes the performance of hemp shives, a co-product of the hemp industry, when used as an adsorbent to recover copper present in aqueous solutions by a batch method. Two materials provided by an industrial partner, namely water-washed hemp shives (SHI-W) and Na2CO3-activated shives (SHI-C), were studied. Two important variables in the water treatment industry, i.e., pH and ionic strength of the solution, were studied to evaluate their impact on the purification performance of the materials. The results obtained clearly indicated that the performance in terms of Cu removal obtained from the SHI-C material was significantly higher than that obtained with SHI-W, mainly due to the structural and chemical modifications after carbonate treatment. For each dose of this adsorbent, a percentage of recovery between 90 and 100% was achieved, independently of the pH value in the range 3−5. In the case of SHI-W, the highest values were between 60 and 75% and were both dependent on t... [more]

Long-term development of fluvial reservoirs causes regular changes in the microscopic pore-throat structure, physical properties and phase permeability curves of the reservoirs, and the evolution history of different oil layer varies. These effects can be explored using a four-dimensional (4D) model of the maturing field. The logging curves of 89 sand bodies of the Nanpu No. 2 structure in the Bohai Bay Basin were restored to the non-water flooded state based on the changing status of water flooding layers at different stages and levels, and an original geological model was established by combining data for the old wells. The time-varying relationship was incorporated in the dynamic model with surface flux as the variable, and the numerical simulation analysis was conducted based on the reservoir time-varying characteristics. The results showed that ① the logging data of the water-flooded layer significantly affected the simulation results of the geological model and can only be used f... [more]