This work attempts to address the quest of removing carbon dioxide from flue gas streams to help preserve the environment. It is based on a model that is able to describe the solid-liquid-vapour and solid-vapour phase equilibria for the ternary system of N2-O2-CO2 at pressures from 5 to 130 bar and over a wide range of temperature (140 to 220 K). Furthermore, a corresponding state-of-the art solid-vapor (SV) CO2 capture/separation unit is developed and introduced in this work. The SV unit was modeled using the Aspen Custom Modeler software by implementing the thermodynamic model developed before. It was then simulated using the Aspen Plus simulator; its performance was studied and analyzed. Moreover, the performance of the unit was optimized and compared to the most conventional corresponding technology used by the industry (i.e., amine-scrubbing). Results proved that for the same output clean gas composition, which contains only 0.3% CO2, the developed state-of-the-art SV unit consume... [more]

Global demand for Low-Alcohol Beer (LAB) and Alcohol-Free Beer (AFB) has surged due to flavor attributes, health benefits, and lifestyle changes, prompting efforts for process intensification. This paper aims to offer a detailed modelling basis for LAB manufacturing study and optimisation. A first-principles dynamic model for conventional beer manufacturing has been re-parameterized and used for dynamic simulation of Cold Contact Fermentation (CCF), an effective LAB and AFB production method, with concentrations tracked along plausible temperature manipulation profiles. Parameter estimation is pursued using industrial production data, with a detailed local sensitivity analysis portraying the effect of key parameter variation on sugar consumption, ethanol production, and key flavor component (ethyl acetate and diacetyl) evolution during (and final values after) CCF. Ethyl acetate (esters in general) affecting fruity flavors emerge as most sensitive to CCF conditions.

The present work discusses the development and application of a machine-learning-based model to predict the enthalpy of combustion of various oxygenated fuels of interest. A detailed dataset containing 207 pure compounds and 38 surrogate fuels has been prepared, representing various chemical classes, namely paraffins, olefins, naphthenes, aromatics, alcohols, ethers, ketones, and aldehydes. The dataset was subsequently used for constructing an artificial neural network (ANN) model with 14 input layers, 26 hidden layers, and 1 output layer for predicting the enthalpy of combustion for various oxygenated fuels. The ANN model was trained using the collected dataset, validated, and finally tested to verify its accuracy in predicting the enthalpy of combustion. The results for various oxygenated fuels are discussed, especially in terms of the influence of different functional groups in shaping the enthalpy of combustion values. In predicting the enthalpy of combustion, 96.3% accuracy was ac... [more]

This paper investigates the pyrolysis of PODEn (n = 3, 4, 5) using ReaxFF molecular dynamics simulation. A large-scale model, which contains 2000 PODEn molecules, is simulated at 3000 K. The higher frequencies of the initial PODEn decomposition reaction at α or β C-O bond show that the α or β C-O bond in PODEn is not easy to break, which is approximately half the number of the other type of C-O bond dissociation. Furthermore, the bond dissociation energies (BDEs) are calculated using the ReaxFF method. The BDE of α or β C-O bond is higher than that of the other C-O bond, ~3−11 kcal/mol, indicating that BDE is one of the factors causing the different proportions of bonds broken. The evolution of pyrolysis products is also investigated. The results reveal that long-chain pyrolysis products from the initial PODEn decomposition are prone to further reaction, while a large amount of CH3O and CH3 remains in the system. This helps explain the difficulty in α and β C-O bond dissociation reacti... [more]

The increase in mining depth causes the temperature of the coal seam to rise. Studying the effect of temperature on the mechanical property of coal is very necessary. In this paper, based on the results of conventional triaxial compression experiments of coal samples, the discrete element program PFC2D was used to conduct a conventional triaxial compression simulation of coal samples to obtain microscopic parameters. On this basis, the conventional triaxial simulation study of coal samples at different temperatures was carried out to explore the influence of temperature on the physical and mechanical properties of coal. In this process, acoustic emission and energy monitoring were carried out. The damage and failure process of coal is divided into three stages: the undamaged stage, the stable damage stage, and the rapid damage stage. The relationship between acoustic emission characteristic law, energy transformation law, and crack evolution in the damage and failure process of coal wa... [more]

Bioscorodite crystallization is a promising process for the proper immobilization of arsenic from acidic metallurgical wastewater, and Acidianus brierleyi is an effective archaeon to oxidize Fe(II) and As(III) simultaneously. This paper deals with the development of an experimentally validated mathematical model to gain insight into the simultaneous processes of Fe(II) and As(III) oxidation via microbial cells and the exopolysaccharide (EPS) matrix, As(V) precipitation, and bioscorodite crystallization, which are affected by several factors. After the mathematical structure was proposed, a model fitting was performed, finding global determination coefficients between 0.96 and 0.99 (with p-values < 0.001) for all the variables. The global sensitivity analysis via Monte Carlo simulations allowed us to identify the critical parameters whose sensitivity depends on culture conditions. The model was then implemented to evaluate the effect of cell concentration, Fe(II) and As(III) concentr... [more]

This work presents the numerical modeling of a droplet’s sessile and dynamic behavior on a grooved surface. A droplet is placed on horizontal and vertical sliding conditions to observe its behavior under wettable and non-wettable conditions. The numerical analysis uses the multicomponent multiphase Shan-Chen Lattice Boltzmann Model (SC-LBM). The Cassie−Baxter and Wenzel states are reproduced for the sessile condition, and the enhancement of the contact angle is appreciated under the action of the grooved-ridged horizontal surface. The sliding droplet is analyzed through the Bond number by varying the ratio between the body force and the surface tension number. For Cassie−Baxter and Wenzel wettability conditions, a critical Bond number was discovered above which the sliding droplet will continue to deform indefinitely. The numerical model proved its suitability to predict the gradual deformation of a droplet over a grooved vertical surface subject to a tangential body force until the dr... [more]

Since the lack of a specific design method, guidance and user participation in the product innovation design of digital twins, a product innovation design process of a user requirement-driven digital twin combined with flow function analysis is proposed based on the constructed innovation design model of the PPE-PVE-VVE-VPE digital twin. First, to obtain the orientation of the product innovation design, the user requirement knowledge graph is generated on the basis of product functional decomposition to intuitively express the mapping relationship between user requirements and product functional components. Then, composition analysis of the prototype physical entity (PPE) is conducted in the physical domain; flow function analysis identifies the prototype virtual entity (PVE) defects in the virtual domain; the vision virtual entity (VVE) is solved via flow evolution path as well as evaluated and selected from the users’ perspective to display simulation and rehearsal analysis. Finally,... [more]

Myocardial infarction is a type of heart disease marked by rapid progression and high mortality. In this paper, a novel intelligent recognition algorithm of multiple myocardial infarctions using a bidirectional long short-term memory (BiLSTM) neural network classification was proposed. This algorithm was based on morphological feature extraction, which can greatly improve the diagnostic efficiency of doctors for different kinds of myocardial infarction diseases. The algorithm includes noise reduction and beat segmentation of electrocardiogram (ECG) signals from the Physikalisch-Technische Bundesanstalt (PTB) database. According to the medical diagnosis guide, the distance feature of the whole waveform and the amplitude feature of the branch lead waveform are extracted. According to the extracted features, the long short-term memory network (LSTM) and the BiLSTM neural networks are built to classify and recognize heartbeats. The experimental results show that the accuracy of the morphol... [more]

Dendrite is among the most frequently observed structures during the solidification process. Different dendrite morphologies caused by environmental conditions can affect the physical properties of materials. The formation of snowflakes can generate various morphologies under different conditions, and is used in this work as an example. Simulation technologies provide insight into the correlation between a resulting morphology and its impact parameter, including the phase-field method (PF) and cellular automaton (CA). The PF method is derived from thermodynamic functions and kinetic equations, while the CA model is established by interaction rules between subsystems. It is difficult to solve the PF method due to the coupled differential equations, wherein the actual physical parameters are included. The CA model is conceptually simple and computationally efficient; however, the physical meaning of the parameters is absent. In this work, an example of snowflake formation is considered b... [more]

Rice straw is waste material from agriculture as a renewable biomass resource, but the black liquor produced by straw pulping causes serious pollution problems. The twin-screw pulping machine was designed by Solidworks software and the straw breakage model was created by the Discrete Element Method (DEM). The model of straw particles breakage process in the Twin-screw pulping machine was built by the Tavares model. The simulation results showed that the highest number of broken straw particles was achieved when the twin-screw spiral casing combination was negative-positive-negative-positive and the tooth groove angle arrangement of the negative spiral casing was 45°−30°−15°. The multi-factor simulation showed that the order of influence of each factor on the pulp yield was screw speed > straw moisture content > tooth groove angle. The Box-Behnken experiment showed that when screw speed was 550 r/min, tooth groove angle was 30°, straw moisture content was 65% and pulping yield achieved... [more]

Pavement structure bearing capacity is an important evaluation parameter in pavement design, construction, maintenance management, and reconstruction, and is generally expressed by the pavement deflection value. Some of the current road bearing capacity detection equipment have high detection accuracy, but the detection speed is slow, they cannot achieve real-time continuous detection; and some detection speeds are fast, but the measurement accuracy is easily affected by the pavement roughness and vehicle vibration. Moreover, the detection result is the pavement displacement, which cannot directly reflect the comprehensive modulus of the pavement structure. In this paper, firstly, a two-stage jump mechanical model of “machine-pavement” system is established in order to develop a device that can simulate the real driving load and continuously test the bearing capacity of pavement structure, and the main factors affecting the acceleration response of vibrating drums were determined throu... [more]

Accurate estimation of the state of charge (SOC) is an indispensable part of a vehicle management system. The accurate estimation of SOC can ensure the safe and reliable operation of the vehicle management system. With the development of intelligent transportation systems (ITS), vehicles can not only obtain the dynamic changes inside the battery through sensors, but also obtain the traffic information around the vehicle through vehicle−road collaboration. In addition, the development of onboard graphic processing units (GPUs) and Internet of Vehicles (IOV) technology make the computing power of vehicles no longer limited by hardware, which makes neural networks applied to the intelligent control of vehicles. Aiming at the problem that the traditional network cannot effectively obtain the complex spatial information of sample attributes, we developed an attention-based CONV-LSTM module for SOC prediction based on a convolutional neural network (CNN) and a long short-term memory (LSTM) n... [more]

For many applications (e.g., surveillance and disaster response), situational awareness is essential. In these applications, human body posture recognition in real time plays a crucial role for corresponding response. Traditional posture recognition suffers from accuracy, due to the low robustness against uncertainty. Those uncertainties include variation from the environment (e.g., viewpoint, illumination and occlusion) and the postures (e.g., ambiguous posture and the overlap of multiple people). This paper proposed a drone surveillance system to distinguish human behaviors among violent, normal and help needed based on deep learning approach under the influence of those uncertainties. First, the real-time pose estimation is performed by the OpenPose network, and then the DeepSort algorithm is applied for tracking multi-person. The deep neural network model (YOLO) is trained to recognize each person’s postures based on a single frame of joints obtained from OpenPose. Finally, the fuz... [more]

The development of the construction industry generates construction waste which could contribute to environmental issues. Construction waste reduction management plays an important role in directly reducing emissions and solving the environmental pollution caused by construction waste. The limited rationality hypothesis and an evolutionary game model are used to construct a simulation model for the effects of environmental policies’ influences on the behavior of government and construction enterprises in construction waste reduction activities. Simulation results show that: (1) The government and enterprises evolve in the same direction under the sewage fees system or the subsidy system. The relationship between the initial ratio of the two sides and the position of the saddle point determines the evolution direction of the system. (2) The government could adjust the sewage fees rate, the penalty ratio, and the upper limit of construction waste emission to obtain a superior effect unde... [more]

The physical and mechanical properties of the materials in the swirling fluidized-bed seed pelleting unit affect the mixing degree of the materials in the pelleting and coating process, which is of great significance to research on pelleting and coating. The problem of discrete particle model parameters affecting CFD-DEM simulation results is addressed. In this paper, red clover seeds (referred to as seeds) and pelletized coating powder (referred to as powder) were used as the research objects, and the JKR. model was selected to calibrate the contact parameters between seeds and powder based on particle amplification theory. With the powder rest angle as the response value, a simulation calibration test was conducted; the parameters with significant effects on the response value were screened based on the Plackett−Burman test, and the steepest climb test determined the range of factor levels of essential parameters. The Box−Behnken test was used to establish the curvilinear response su... [more]

The benzene alkylation reactor using the dry gas is the most significant equipment in the ethylbenzene manufacturing process. In this paper, a two-dimensional homogeneous model is developed for steady state simulation of the industrial multi-stage catalytic reactor for ethylbenzene. The model validation on a practical benzene alkylation reactor shows the model is accurate and can calculate the hot spot temperatures. The composition of dry gas from upstream process varies with the operating conditions, which can cause unexpected hot spots in the reactor and catalyst deactivation. Considering the uncertainty in dry gas composition, a robust multi-objective optimization framework is proposed: first, the back-off in constraints is introduced to the multi-objective optimization problem to hedge against the worst case; then the optimal operating point can be selected using the multi-criteria decision-making. The reactor optimization objectives are maximizing selectivity of ethylene and conve... [more]

Mechanics-seepage synchronous tests on gas-bearing coal under three different stress paths were designed and implemented to evaluate how load path affected the mechanical strength and permeability of deep mining-disturbed coal. The cracks-count evolution of coal specimens during instability was observed through DEM numerical simulation. The results showed significant stress-strain and strength variations under different paths. At the time of failure, the specimen deformation and peak strength were Test 1 > Test 2 > Test 3, while the permeability was Test 3 > Test 2 > Test 1, with specimen permeability in Test 3 rising prominently. From numerical simulation, the cracks count was Test 2 > Test 3 > Test 1, with tensile cracks taking the largest proportion in Test 2 and shear cracks taking the largest proportion in Test 3. Our findings shed some light on the research and disaster prevention regarding coal and gas outburst.

Extractive distillation has great significance for the separation of ethylbenzene from C8 aromatic hydrocarbons. Herein, a distillation process for the separation of ethylbenzene was designed using methyl phenylacetate as an extractant. A genetic algorithm (GA) was used to evaluate the economic and environmental factors of the process, and Aspen Dynamic was used to assess the dynamic performance. The sequential optimization method was used to obtain the initial process parameters. Then, the total annual cost and CO2 emissions were minimized by NSGA-III to increase the economic and environmental benefits. To enhance the search performance of GA, the mutation probability and crossover probability were studied and adjusted. The optimal total annual cost and CO2 emissions were 11.7% and 23.7% lower than those of the initial process. Based on a steady process, two control strategies, which were the flow rate of the recycling solvent controlled by entrainer makeup flow rate (CS1) and the bot... [more]

The transport and prediction of hexavalent chromium (Cr(VI)) contamination in “slag−soil−groundwater” is one with many uncertainties. Based on the column experiments, a migration model for Cr(VI) in the slag−soil−groundwater system was investigated. The hydraulic conductivity (Kt), distribution coefficient (Kd), retardation factor (Rd), and other hydraulic parameters were estimated in a laboratory. Combining these hydraulic parameters with available geological and hydrogeological data for the study area, the groundwater flow and Cr(VI) migration model were developed for assessing groundwater contamination. Subsequently, a Cr(VI) migration model was developed to simulate the transport of Cr(VI) in the slag−soil−groundwater system and predict the effect of three different control programs for groundwater contamination. The results showed that the differences in the measured and predicted groundwater head values were all less than 3 m. The maximum and minimum differences in Cr(VI) between... [more]

Renewable energy is a key technology for achieving carbon-free energy transitions, and solar power systems are one of the most reliable resources for achieving this. Solar power systems have a simple structure and are inexpensive. However, depending on the input irradiance, the existing maximum output control algorithm (P&O) has disadvantages due to its slow transient response and steady-state vibration. Therefore, in this paper, we propose a maximum output control algorithm based on a deep learning algorithm that can predict the input irradiance. This can achieve a quick transient response and steady-state stability. The proposed method predicts the irradiance based on the output voltage/current and power of the photovoltaic (PV) system and calculates the duty ratio that can accurately follow the maximum output point according to the irradiance. The deep learning model applied in this study was trained based on the experimental results using a 100 W PV panel, and the performance of th... [more]

Severe blood leakage resulting from the detachment of dialysis tubing is often difficult to detect by nurses in busy clinics. This paper presents a flexible blood leakage detection system featuring a ring-light sensor array with an operating wavelength of 500−700 nm, which is held in place by the gauze covering the dialysis puncture site. A ring-light sensor is connected to a bidirectional hetero-associative memory network, which interprets detected changes in signal strength, the output signal of which is transmitted via WiFi to a server at the nursing station where a machine learning algorithm determines whether blood leakage has occurred. The compact design of this early warning system greatly enhances the comfort and mobility of patients undergoing dialysis. The efficacy of the proposed system was demonstrated in experiments involving artificial blood.

A reflow soldering process (RSP) is generally implemented in advanced manufacturing factories for welding small electronic components together to create a product using heat generated at the welding tip (WT). Improper WT design and operating conditions may lead to defects in some products; therefore, optimizing both is immensely significant in developing the RSP. Accordingly, this article proposes a successful RSP development based on multiphysics in a hard disk drive factory consisting of transient thermal-electric and structural simulations. First, a new shape series WT was designed, and a conventional shape, parallel WT, was considered as a case study. Then, they were assembled and experimented with the RSP actual operating conditions to collect essential data. Next, the heat transfer was determined using a transient thermal-electric simulation (TES). The simulation results showed uneven WT temperatures depending on applied voltages, time, and shapes, which were consistent with the... [more]

In this paper, a stochastic-metaheuristic model is performed for multi-objective allocation of photovoltaic (PV) resources in 33-bus and 69-bus distribution systems to minimize power losses of the distribution system lines, improving the voltage profile and voltage stability of the distribution system buses, considering the uncertainty of PV units’ power and network demand. The decision-making variables, including installation location and the size of PVs, are determined optimally via an improved human learning optimization algorithm (IHLOA). The conventional human learning optimization algorithm (IHLOA) is improved based on Gaussian mutation to enhance the exploration capability and avoid getting trapped in local optimal. The methodology is implemented in two cases as deterministic and stochastic without and with uncertainties, respectively. Monte Carol Simulation (MCS) based on probability distribution function (PDF) is used for uncertainties modeling. The deterministic results prove... [more]

In the range of 800−1200 K, both experiments and kinetic modeling demonstrate a significant difference in the dependence of the ignition delay time of methane and hydrogen on pressure and temperature, with the complex influence of these parameters on the autoignition delay time of methane−hydrogen−air mixtures. In connection with the prospects for the widespread use of methane−hydrogen mixtures in energy production and transport, a detailed analysis of their ignition at temperatures below 1000 K, the most important region from the point of view of their practical application, is carried out. It is shown that such a complex behavior is associated with the transition in this temperature range from low-temperature mechanisms of oxidation of both methane and hydrogen, in which peroxide radicals and molecules play a decisive role, to high-temperature mechanisms of their oxidation, in which simpler radicals dominate. A kinetic interpretation of the processes occurring in this case is propose... [more]