Total organic carbon (TOC) content is a key indicator for determining the hydrocarbon content of shale. The current model for calculating the TOC content of shale is relatively simplistic, the modeling process is cumbersome, and the parameters involved are influenced by subjective factors, which have certain shortcomings. To address this problem, a time-domain convolutional neural network (TCN) model for predicting total organic carbon content based on logging sequence information was established by starting from logging sequence information, conducting logging parameter sensitivity analysis experiments, prioritizing logging-sensitive parameters as model feature vectors, and constructing a TCN network. Meanwhile, to overcome the problem of an insufficient sample size, a five-fold cross-validation method was used to train the TCN model and obtain the weight matrix with the minimum error, and then a shale reservoir TOC content prediction model based on the TCN model was established. The... [more]

The Marangoni effect involves a mass transfer along an interface between two phases owing to the gradient of the interfacial tension. The flow caused by this phenomenon is called Marangoni convection, a complex phenomenon that involves mass transfer processes, such as surfactant adsorption/desorption processes, solvent dissolution phenomena, and viscous dissipation processes. Therefore, the strength of the convection depends on the various thermodynamic and physical properties of the fluids. In this study, we experimentally investigated the relationship between the Marangoni convection generated inside a hanging oil droplet and the interfacial tension of the oil droplet in an aqueous phase by the particle image velocimetry method. This convection velocity depended on the initial value of the interfacial tension in the oil−water interfacial tension oscillation phenomenon accompanied by the expansion and contraction of the hanging drop. Additionally, the droplet oscillation frequency dec... [more]

Process system engineering (PSE) is a multidisciplinary research field that aims to address engineering problems related to the design, operation, control, and management of process systems [...]

This article explores the impact of operating parameters on the classification efficiency of a rotor classifier. Based on the experimental data of calcined petroleum coke classification, a single-factor experimental analysis is conducted to find the relationship between operating parameters and classification performance. The cut size becomes progressively smaller as the rotor speed and feeding speed increase, and progressively larger as the inlet air volume increases. Newton’s classification efficiency and classification accuracy decreased with the increase in feeding speed. The range analysis of the orthogonal experiment shows that the rotor speed and inlet air volume have significant effects on the classification performance, but the effect of feed speed is relatively weak. In addition, the optimal combination of operating parameters is obtained by optimizing the operating parameters. Newton’s classification efficiency under this combination is estimated, and the estimated value is... [more]

In this paper, a waste heat recovery compound system for series hybrid electric vehicles is established. The existing components of vehicle air conditioning are used in the organic Rankine cycle (ORC) to realize miniaturization. The waste heat recovery compound system is constructed using GT-SUITE, and the objective of the analysis is to increase the power output and engine thermal efficiency increase ratio (ETEIR). The effects of the expander speed, pump speed, working fluid mass flow rate, and working fluid type on the waste heat recovery compound system are analyzed. The simulation results show that the optimal schemes for the ORC system and compound system corresponding to the expander speed and pump speed are 1000 pm, 2500 rpm, 1200 rpm, and 2500 rpm, respectively. Compared with the ORC system, the maximum power output of the compound system with the same working fluid in three states (1500 rpm, 2500 rpm, and 3500 rpm) of the engine is increased by 21.67%, 24.05%, and 28.23%, resp... [more]

Large-scale volumetric fracturing is generally used during shale gas development. The return rate of fracturing fluid is low, and a large amount of slickwater is retained in the reservoir. The adsorption and desorption of partially hydrolyzed polyacrylamide (HPAM), an additive commonly used in slickwater, on the surface of shale was studied using Longmaxi shale from the Sichuan Basin. The experimental results showed that the mass ratio of the HPAM solution to shale reached saturation adsorption at 20:1 when the concentration of HPAM solution was 1000 mg/L and 25:1 when the concentration of HPAM solution was 500 mg/L. The mass ratio of the HPAM solution to shale was fixed at 25:1, and the adsorption equilibrium was reached at a HPAM concentration of 1000 mg/L when the aqueous solution temperature was 30 °C and 800 mg/L when the aqueous solution temperature was 60 °C. The Langmuir adsorption model yielded a better fit than the Freundlich adsorption model. The adsorption equilibrium time... [more]

An efficient and accurate method for optimizing capsule-type plate heat exchangers is proposed in this paper. This method combines computational fluid dynamics simulation, a backpropagation algorithm and multi-objective optimization to obtain better heat transfer performance of heat exchanger structures. For plate heat exchangers, the heat transfer coefficient j and friction coefficient f are a pair of contradictory objectives. The optimization of capsule-type plate heat exchangers is a multi-objective optimization problem. In this paper, a backpropagation neural network was used to construct an approximate model. The plate shape was optimized by a multi-objective genetic algorithm. The optimized capsule-type plate heat exchanger has lower flow resistance and higher heat exchange efficiency. After optimization, the heat transfer coefficient is increased by 8.3% and the friction coefficient is decreased by 14.3%, and the heat transfer effect is obviously improved. Further, analysis of f... [more]

The parameters of coalbed methane reservoirs have large differences, and the precise values cannot represent the resource and production characteristics of the whole block. In order to address these problems, an index system for evaluating the production potential of coalbed methane blocks was constructed, the weights of evaluation parameters were determined, and a model for the preferential selection of coalbed methane blocks based on the subjective−objective combination of weights method was established. The main coal seams (No. 2-1 and No. 4-2) of the Pingdingshan-Shoushan I Mine Block were taken as the research objects to rank the development potential of CBM blocks in a preferential way. The results show that the six resource and production parameters of No. 2-1 coal are gas content, top and bottom rock properties, coal seam thickness, coal seam depth, coal body structure, and tectonic conditions, in descending order of importance, and the parameters of No. 4-2 coal are gas conten... [more]

To address the issue of low accuracy in detecting defects of battery cell casings with low space ratio and small object characteristics, the low space ratio feature and small object feature are studied, and an object detection algorithm based on dual-coordinate attention and small object loss feedback is proposed. Firstly, the EfficientNet-B1 backbone network is employed for feature extraction. Secondly, a dual-coordinate attention module is introduced to preserve more positional information through dual branches and embed the positional information into channel attention for precise localization of the low space ratio features. Finally, a small object loss feedback module is incorporated after the bidirectional feature pyramid network (BiFPN) for feature fusion, balancing the contribution of small object loss to the overall loss. Experimental comparisons on a battery cell casing dataset demonstrate that the proposed algorithm outperforms the EfficientDet-D1 object detection algorithm,... [more]

Driven by growing concerns about food supply and the environment, research on alternative protein sources has become increasingly important. In this context, de-oiled seed cakes, particularly soybean cakes, have emerged as a promising option. However, the conventional methods, such as organic solvent extraction, from which these cakes are obtained present several limitations. This study aims to evaluate the efficiency of supercritical fluid extraction (SFE) as an alternative method for de-oiling soybean seeds and obtaining related protein isolates. By using SFE for de-oiling, it was possible to achieve 19% more protein isolates from soybean cakes than the conventional de-oiling method using hexane. Moreover, protein isolates from the SFE de-oiled cake reported significantly improved (p < 0.05) emulsifying abilities and water absorption capacity. Gel electrophoresis and differential scanning calorimetry indicated the presence of a higher concentration of proteins in their native stat... [more]

Heat-transfer enhancement and entropy generation were investigated for a double-helical-type-channel heat sink with different rib structures set on the upper wall. Based on available experimental data, a series of simulations with various turbulence models were conducted to find the best numerical model. Five different rib structures were considered, which were diamond (FC-DR), rectangular (FC-RR), drop-shaped (FC-DSR), elliptic (FC-ER) and frustum (FC-FR). The research was carried out under turbulent flow circumstances with a Reynolds number range of 10,000−60,000 and a constant heat-flow density. The numerical results show that the thermal performance of the flow channel set with a rib structure is better than that of the smooth channel. FC-ER offers the lowest average temperature and the highest temperature uniformity, with a Nusselt number improvement percentage ranging from 15.80% to 30.77%. Overall, FC-ER shows the most excellent performance evaluation criteria and lowest augment... [more]

The importance of biocatalysis for ecologically sustainable syntheses in the chemical industry and for applications in everyday life is increasing. To design efficient applications, it is important to know the related enzyme kinetics; however, the measurement is laborious and error-prone. Flow reactors are suitable for rapid reaction parameter screening; here, a novel workflow is proposed including digital image processing (DIP) for the quantification of product concentrations, and the use of structured data acquisition with EnzymeML spreadsheets combined with ontology-based semantic information, leading to rapid and smooth data integration into a simulation tool for kinetics evaluation. One of the major findings is that a flexibly adaptive ontology is essential for FAIR (findability, accessibility, interoperability, reusability) data handling. Further, Python interfaces enable consistent data transfer.

Fugitive methane emissions from the mining industry, particularly so-called ventilation air methane (VAM) emissions, are considered among the largest sources of greenhouse gas (GHG) emissions. VAM emissions not only contribute to the global warming but also pose a significant hazard to mining safety due to the risk of accidental fires and explosions. This research presents a novel approach that investigates the capture of CH4 in a controlled environment using 1-butyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide [BMIM][TF2N] ionic liquid (IL), which is an environmentally friendly solvent. The experimental and modelling results confirm that CH4 absorption in [BMIM][TF2N], in a packed column, can be a promising technique for capturing CH4 from point sources, particularly the outlet streams of ventilation shafts in underground coal mines, which typically accounts for <1% v/v of the flow. This study assessed the effectiveness of CH4 removal in a packed bed column by testing va... [more]

Additive manufacturing (AM) has revolutionized production across industries, yet challenges persist in achieving optimal part quality. This paper studies the enhancement of post-processing techniques to elevate the overall quality of AM-produced components. This study focuses on optimizing various post-processing methodologies to address prevalent issues such as surface roughness, dimensional accuracy, and material properties. Through an extensive review, this article identifies and evaluates a spectrum of post-processing methods, encompassing thermal, chemical, and mechanical treatments. Special attention is given to their effects on different types of additive manufacturing technologies, including selective laser sintering (SLS), fused deposition modeling (FDM), and stereolithography (SLA) and their dedicated raw materials. The findings highlight the significance of tailored post-processing approaches in mitigating inherent defects, optimizing surface finish, and enhancing mechanical... [more]

As a clean alternative fuel oil for marine engines, methanol has received increasing attention, but its low cetane number requires diesel ignition, which increases the difficulty of retrofitting existing engine fuel injection systems. Polymethoxy dimethyl ether (PODEn) is an ether fuel mixture whose chemical structural formula can be expressed as CH3O(CH2O)nCH3 (n≥2). PODE3 is the predominant component in the blend, and its properties are representative of the blend. PODE is a low-carbon fuel with a high cetane number and is easy to compression ignite, and, as such, can be used to ignite methanol in a marine diesel engine. This article explores the combustion mechanism of mixed methanol−PODE fuel using the characteristics of PODE that can be easily mixed with methanol for combustion. Taking methanol and PODE3 as representative fuels, the detailed combustion mechanism of PODE3 and the detailed combustion mechanism of methanol are simplified using a DRGEPSA (direct relationship graph wit... [more]

In this study, groundbreaking software has been developed to automate the generation of equations of motion for manipulator robots with varying configurations and degrees of freedom (DoF). The implementation of three algorithms rooted in the Lagrange−Euler (L-E) formulation is achieved through the utilization of .m files in MATLAB R2020a software.This results in the derivation of a symbolic dynamic model for industrial manipulator robots. To comprehend the unique features and advantages of the developed software, dynamic simulations are conducted for two 6- and 9-DoF redundant manipulator robots as well as for a 3-DoF non-redundant manipulator robot equipped with prismatic and rotational joints, which is used to simplify the dynamic equations of the redundant prototypes. Notably, for the 6-DoF manipulator robot, model predictive control (MPC) is employed using insights gained from the dynamic model. This enables optimal control by predicting the future evolution of state variables: spe... [more]

Chromatography modeling for simulation is a tool that can help to predict the separation of molecules inside the column. Knowledge of sorption isotherms in chromatography modeling is a crucial step and methods such as frontal analysis or batch are used to obtain sorption isotherm parameters, but they require a significant quantity of samples. This study aims to predict Langmuir isotherm parameters from Surface Plasmon Resonance (SPR) affinity data (requiring less quantity of sample) to simulate metal chelating peptides (MCPs) separation in Immobilized Metal ion Affinity Chromatography (IMAC), thanks to the analogy between both techniques. The validity of simulation was evaluated by comparing the peptide’s simulated retention time with its experimental retention time obtained by IMAC. Results showed that the peptide affinity constant (KA) can be conserved between SPR and IMAC. However, the maximal capacity (qmax) must be adjusted by a correction factor to overcome the geometry differenc... [more]

Cefazolin is a first-generation cephalosporin used to treat severe infections of the respiratory tract, urinary tract, skin, and soft tissues. This study presents the optimal conditions for the determination of cefazolin by thin-layer chromatography with densitometric detection. A chloroform−methanol−glacial acetic acid mixture (6:4:0.5, v/v/v) was selected as the mobile phase, while TLC silica gel 60F254 plates were used as the stationary phase. Next, the developed procedure was validated in accordance with ICH guidelines. The obtained results showed that the method is selective, precise, and accurate in a linearity range of 0.04−1.00 µg/spot (r > 0.99). Subsequently, qualitative and quantitative analyses of formulations containing cefazolin were performed. It was found that the amount of antibiotic is highly consistent with the content declared by manufacturers. The suitability of the developed method for stability testing under varying environmental conditions was also verified. It... [more]

The problem of power grid capacity expansion focuses on adding or modernizing generation and transmission resources to respond to the rise in demand over a long-term planning period. Traditionally, the problem has been mainly viewed from technical and financial perspectives. However, with the rise in the frequency and severity of natural disasters and their dire impacts on society, it is paramount to consider the problem from a nexus of resilience, sustainability, and equity. This paper presents a novel multi-objective optimization framework to perform power grid capacity planning, while balancing the cost of operation and expansion with the life cycle impacts of various technologies. Further, to ensure equity in grid resilience, a social vulnerability metric is used to weigh the energy not served based on the capabilities (or lack thereof) of communities affected by long-duration power outages. A case study is developed for part of the bulk power system in the state of Colorado. The f... [more]

In this experimental work, a prototype of a hybrid solar−thermal−photovoltaic (HE-PV/T) heat exchanger has been designed, built, and characterized, with rectangular geometry and 12 fins inside, to obtain better heat flow and higher performance in order to achieve a better heat transfer coefficient, reducing and optimizing the working area. The heat exchanger contains 12 photovoltaic cells connected in series, with an angle of inclination of approximately 18° towards the south and a surface area of 0.22 m2, smaller than those available on the market, which individually capture 147.05 W/m2 as a photovoltaic panel and 240 W/m2 as a solar collector. Mathematical models found in the literature from previous work were used for the electrical and thermal evaluations. The temperature of the PV cells was reduced to 13.2 °C and the thermal level of the water was raised to a temperature above 70 °C, with a photovoltaic−thermal coupling power of 307.11 W and a heat transfer coefficient of 5790 W/m... [more]

The pyrolysis process is a thermochemical conversion reaction that encompasses an intricate array of simultaneous and competitive reactions occurring in oxygen-depleted conditions. The final products of biomass pyrolysis are bio-oil, biochar, and some gases, with their proportions determined by the pyrolysis reaction conditions and technological pathways. Typically, low-temperature slow pyrolysis (reaction temperature below 500 °C) primarily yields biochar, while high-temperature fast pyrolysis (reaction temperature 700−1100 °C) mainly produces combustible gases. In the case of medium-temperature rapid pyrolysis (reaction temperature around 500−650 °C), conducted at very high heating rates and short vapor residence times (usually less than 1 s), the maximum liquid yield can reach up to 85 wt% (on a wet basis) or achieve 70 wt% (on a dry basis), with bio-oil being the predominant product. By employing the pyrolysis technique, valuable utilization of tobacco stem waste enriched with lign... [more]

Petroleum production forecasting involves the anticipation of fluid production from wells based on historical data. Compared to traditional empirical, statistical, or reservoir simulation-based models, machine learning techniques leverage inherent relationships among historical dynamic data to predict future production. These methods are characterized by readily available parameters, fast computational speeds, high precision, and time−cost advantages, making them widely applicable in oilfield production. In this study, time series forecast models utilizing robust and efficient machine learning techniques are formulated for the prediction of production. We have fused the two-stage data preprocessing methods and the attention mechanism into the temporal convolutional network-gated recurrent unit (TCN-GRU) model. Firstly, the random forest (RF) algorithm is employed to extract key dynamic production features that influence output, serving to reduce data dimensionality and mitigate overfit... [more]

Aiming at the problem of low pollutant concentration in the sewage treatment plant due to external water intrusion into the sewage collection system, which in turn leads to low pollutant reduction efficiency. A sewage system in Zhenjiang City is taken as an example. Analyze the situation of external water intrusion in the sewage pipe network and determine the external water intrusion proportion based on the water quality and quantity method. First, the dry season flow rate of the sewage pipe is obtained according to the monitoring data of the flowmeter. Then, the key research areas are screened out based on the changes in the concentration of water quality characteristic factors. Furthermore, chemical oxygen demand and electrical conductivity are used as water quality characteristic indicators to characterize shallow groundwater and river water. In addition, the proportions of groundwater and river water intrusion in the sewage pipe network are quantitatively analyzed based on the chem... [more]

Renewable natural gas (RNG) is attractive for energy policy goals in the world. Therefore, a regional system is designed to explore RNG combustion for power generation in localities. This study investigates a direct injection (DI) engine fueled with hydrogen (H2) blended into the simulated renewable natural gas, which consists of 50% methane (CH4) and 50% carbon dioxide (CO2) in volume. In order to obtain higher efficiency, comparisons between DI and port fuel injection (PFI) of H2 addition were made. Then, the volume percentage of H2 was changed from 20% to 100% by keeping the volume ratio of CH4 and CO2 at 1:1. Finally, results of power output, brake mean effective pressure (BMEP), brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) were discussed. Results showed that in contrast to PFI, H2 DI injection could increase efficiency by 4%. Additionally, H2 DI could retard the MBT ignition timing at 5 °CA. Compared with CH4/CH4 + CO2 combustion, under stoichiometric... [more]

In engineering, cost minimization, especially in Computer Numerical Control (CNC) machining like pocket milling, is crucial. Existing tool path definition software often lacks optimization, particularly at critical starting and ending points. This study optimizes CNC machine tool paths for energy-efficient multi-pocket milling, utilizing the Symbolic Discrete Control Synthesis (SDCS) method for formal correctness. In our work, the tool path generation is formulated as a traveling salesman problem. We introduce a modeling framework to adapt SDCS to multi-pocket-milling processes, aiming to enhance precision and efficiency for potential cost savings, including energy and time, in engineering applications. This study reports experimental and comparative results, where comparative evaluations were made using metaheuristic algorithms. Our proposed approach improves CNC machining processes for multi-pocket milling. We experimentally evaluate our control algorithms and demonstrate and validat... [more]