Many industrial and manufacturing processes exhibit complex and coupled fluid flow phenomena [...]

In this study, a specimen geometry for testing finger joints was developed using finite element simulation and proofed by experimental testing. Six different wood species and three adhesives were used for finger-jointing specimens. With the test specimen geometry, the bonding strength of the finger joints was determined without the usual self-locking of the joint. Under load, the test specimen geometry introduces maximum stress at the beginning of the bond line (adhesive zone). However, the test specimen geometry does not generate a symmetric stress state. The main difficulty here is the flank angle of the finger joint geometry. The wood species and adhesives significantly influenced the performance of the finger joints.

We modified the Zwart−Gerber−Belamri (ZGB) cavitation and RNG turbulence models based on their rotational motion characteristics, as well as simulating the phenomenon of small fluctuations in rotational speed due to the action of hydraulic excitation force, to increase the precision of numerical simulations of the cavitation characteristics of centrifugal pumps. According to the theory behind the enhanced model, the pressure gradient in the impeller runner changes uniformly, and the cavitation bubble initially manifests itself at the front edge of the blade’s suction. With the reduction in the effective margin, changes in the impeller flow channel’s pressure gradient increased, the blade’s suction-side cavitation area expanded, and the flow field’s internal disturbance enhanced, resulting in hydraulic loss to the centrifugal pump, considerably reduced operating performance, and the blade pressure side by the cavitation-affected area becoming smaller. The blade’s suction-surface pressur... [more]

This article presents an ultramodern modelling algorithm for predicting the remnant cellulose life cycle for oil-submerged power transformers based on the adaptive neuro-fuzzy interference system (ANFIS). The polymer characteristics, degree of polymerization (DP), and 2-furaldehyde (2FAL) of 100 power transformers were measured and collated, which were apportioned into 70 training databanks and 30 as testing datasets. The remnant cellulose life cycle of the transformer was predicted using the proposed ANFIS model characterized by polymer characteristics, DP and 2FAL as inputs. The proposed approach returns 98.23% training and 99.86% testing reliability. The proposed model was applied to 10 transformer case studies in predicting their remnant cellulose life cycle. To corroborate the proposed ANFIS, a comparative study was carried out by employing existing approaches in predicting the remnant life cycle of the case studies, and significant error margins were observed. At large, the resul... [more]

This article presents the preliminary results on the drying process in a fountain dryer designed and adapted to drying waist sawdust and/or chips of various morphology and moisture content. In terms of drying technology, it is important to reduce the demand for heat and electricity. The phenomena occurring during the drying of sawdust in a fountain dryer were analyzed. Modifications of a typical fountain dryer were proposed in order to dry the chips, to obtain appropriate moisture and quality suitable for the process of their further granulation for the production of pellets. The test stand and the most important properties of the fountain dryer were described and discussed. Such characteristic aims of the device, i.e., efficiency, combustion, air and exhaust gas flow measurements, among others, were presented. The characteristics of the sawdust drying curves as a function of temperature were also determined. Computer simulations of heat exchange, air, and exhaust gas flow velocities w... [more]

The slide valve-type direct-acting relief valve with external orifice (SVTDARVWEO) is widely used in hydraulic systems, and its response characteristics are influenced by key factors. It is of great significance to carry out research on the influencing factors of the response characteristics of the SVTDARVWEO. The working principle of the SVTDARVWEO is analyzed in the present study. The simulation model of the SVTDARVWEO is established using AMESim. The influence of the orifice diameter, viscosity coefficient, valve element mass, spring stiffness, oil seal length, and valve element diameter on the response characteristics of the SVTDARVWEO is studied. The results show that: (1) The smaller the orifice diameter is, the smaller the oscillation frequency, amplitude and maximum overshoot of pressure, flowrate, displacement and velocity are. (2) When the viscosity coefficient is 50 N/(m/s), 55 N/(m/s) and 60 N/(m/s), the pressure, flowrate, displacement and velocity oscillate periodically,... [more]

Accurate prediction of the compressive strength of concrete is of great significance to construction quality and progress. In order to understand the current research status in the concrete compressive strength prediction field, a bibliometric analysis of the relevant literature published in this field in the last decade was conducted first. The 3135 journal articles published from 2012 to 2021 in the Web of Science core database were used as the database, and the knowledge map was drawn with the help of the visualisation software CiteSpace 6.1R2 to analyse the field at the macro level in terms of spatial and temporal distribution, hotspot distribution and evolutionary trends, respectively. Afterwards, we go into the detail and divide concrete compressive strength prediction methods into two categories: traditional and machine-learning methods, and introduce the typical methods of each. In addition, a boosting-based ensemble machine-learning algorithm, namely the gradient boosting regr... [more]

This work presents an overview of (passive) solar chimney research, from the natural convection fundamentals to the recent progress for achieving thermohydraulic best-performance. Solar chimneys are attractive because they contribute to increasing the efficiency in air conditioning processes for dwellings and buildings, and therefore also aid to reduction in greenhouse gas emissions. A wide number of works dealing with solar chimneys (and Trombe walls or similar) shape designs, as well as with the inclusion of obstacles for disturbing the airflow, is commented in detail. Several numerical simulation procedures used in the literature are specially discussed, and different recommendations are pointed out to be considered for the appropriate numerical simulation of the operating modes of a solar chimney. Investigations aiming for the best performance conditions (for both thermal, and dynamic or ventilation modes) deserve special attention.

Wet fluidized bed granulation and coating processes have been widely used in the pharmaceutical and food industries. The complex gas−solid flow coupled with heat and mass transfer in such processes made it hard to form complete control over the apparatuses. To serve better design, scaling-up, and optimization of granulators and coaters, the underlying micro-scale mechanisms must be clarified. Computational fluid dynamics coupled with the discrete element method (CFD-DEM) provides a useful tool to study in-depth the gas-solid hydrodynamics of the granulation and coating processes. This review firstly introduced the fundamental theory of CFD-DEM from governing equations, force calculation, and coupling schemes. Then the application of CFD-DEM in simulating wet fluidized bed granulation and coating was presented. Specifically, the research focus and the role of CFD-DEM in resolving issues were discussed. Finally, the outlook on the development of CFD-DEM in the context of granulation and... [more]

MoS2 nanomaterials and ionic liquids (ILs) have attracted tremendous interest as the prime electrodes and electrolytes of supercapacitors. However, the corresponding charge storage mechanisms have not yet been clearly understood. Herein, we study the molecular-level energy storage mechanisms of the MoS2 electrode in imidazolium ionic liquid ([BMI+][PF6−]) using molecular dynamics (MD) simulation. The electric double-layer (EDL) structures of MoS2 electrodes in [BMI+][PF6−] electrolytes are comprehensively studied in terms of number density, MD snapshots, separation coefficient, and ion-electrode interaction energy. Based on this, the electric potential and electric field distributions are calculated by integrating Poisson equations. Importantly, a bell-shaped differential capacitance profile is proposed, different from the U-shaped curve from the conventional Gouy−Chapman theory. Especially, it can be well reproduced by the differential charge density curve in the Helmholtz layer. This... [more]

In this study, chromate adsorption onto red peanut skin (RPS) was investigated in a fixed-bed column; FTIR, PZC, SEM, DLS, and BET were used to evaluate its adsorption properties. The experiments were conducted to determine the effect of physical parameters, including the inlet initial Cr(VI) concentration (100−500 mg L−1), bed height (10−20 cm), and feed flow rate (13.59−23.45 mL min−1). They were carried out to predict breakthrough curves. The adsorption capacity coefficients were determined using the most widely used Bohart−Adams model. It was tested to fit experimental data, for a better understand the dynamic behavior, and for further optimize column performance. It was found that the Cr(VI) uptake decreases when increasing the flow rate and that high chromate concentration and bed height consequently increase the column’s life span. A high column adsorption capacity can be achieved with a higher Cr(VI) concentration due to the higher driving force. The results indicated that the... [more]

The contamination of the environment by pesticides is becoming a burning issue in many countries in the World. Development, design, and synthesis of new eco-friendly pesticides and modification of existing ones in order to improve their efficacy with the lowest impact on the environment are two main future possibilities in crop protection and the provision of sufficient food for the growing world population. The present study is focused on the comparative analysis of a series of eight symmetrical triazine derivatives, as potential herbicide candidates with acyclic (alkyl) and cyclic (cycloalkyl) substituents, in terms of their antifungal activity towards Aspergillus flavus as an opportunistic fungal pathogenic microorganism responsible for frequent contaminations of crops with aflatoxin, and in terms of their potential application as herbicides in maize, common wheat, barley, and rice crops. The applied methods include the chemometric pattern recognition method (hierarchical cluster an... [more]

Hidden moving target defense (HMTD) is a proactive defense strategy that is kept hidden from attackers by changing the reactance of transmission lines to thwart false data injection (FDI) attacks. However, alert attackers with strong capabilities pose additional risks to the HMTD and thus, it is much-needed to evaluate the hiddenness of the HMTD. This paper first summarizes two existing alert attacker models, i.e., bad-data-detection-based alert attackers and data-driven alert attackers. Furthermore, this paper proposes a novel model-based alert attacker model that uses the MTD operation models to estimate the dispatched line reactance. The proposed attacker model can use the estimated line reactance to construct stealthy FDI attacks against HMTD methods that lack randomness. We propose a novel random-enabled HMTD (RHMTD) operation method, which utilizes random weights to introduce randomness and uses the derived hiddenness operation conditions as constraints. RHMTD is theoretically pr... [more]

Interlayer contradiction (high-pressure oil that prevents low-pressure oil from being extracted) has always been the main factor affecting the oil-recovery efficiency of the many oil-bearing series in shale oil wells in Eastern Shandong, China. If steps to deal with interlayer contradiction are not taken, Shengli Oilfield’s oil-recovery efficiency will be significantly reduced after a certain period of exploitation. Furthermore, as the drilling depth increases, the formation-fluid supply capacity of Shengli Oilfield becomes worse and further increases the difficulty of oil recovery as well as production costs. In order to improve the oil-recovery efficiency of shale oil wells in Eastern Shandong and realize cost reductions and efficiency increases, we designed a new jet pump in this study. The pump can be used for oil recovery according to the principle of Venturi jet propulsion, as the required power fluid is not a high-pressure fluid injected from the ground, but rather high-pressure... [more]

The use of residual gases from steel production processes as fuel for steel treatment furnaces has attracted great interest as a method for reducing fossil fuel consumption and the steel footprint. However, these gases often have a low calorific value, and a direct substitution can lead to low temperatures or combustion instability issues. CFD simulations of the combustion of these gases can help steel producers forecast the results of the substitution before real testing and implementation. In this study, a CFD model of an industrial experimental furnace in the steel sector is developed and validated. The results are calculated using the combustion, radiation, and heat transfer models included in the software Ansys Fluent. The validation of the simulated results is performed with data acquired from experimental tests under the same simulated conditions at three air-to-fuel equivalence ratios, which vary from an excess of 0% to an excess of 5% oxygen at the outlet. The model is adjuste... [more]

Object recognition and tracking is a challenge for underwater vehicles. Traditional algorithm requires a clear feature definition, which suffers from uncertainty as the variation of occlusion, illumination, season and viewpoints. A deep learning approach requires a large amount of training data, which suffers from the computation. The proposed method is to avoid the above drawbacks. The Siamese Region Proposal Network tracking algorithm using two weights sharing is applied to track the target in motion. The key point to overcome is the one-shot detection task when the object is unidentified. Various complex and uncertain environment scenarios are applied to evaluate the proposed system via the deep learning model’s predictions metrics (accuracy, precision, recall, P-R curve, F1 score). The tracking rate based on Siamese Region Proposal Network Algorithm is up to 180 FPS.

With the aim of determining the influence of the fluid−structure coupling dynamic effect of the oil and gas transmission medium and pipeline on the seismic response, an oil pipeline supported by a cable-stayed spanning structure was taken as the study object. Kinetic equations taking into account the action of oil and gas medium were studied, and a finite element model structure considering the additional-mass method and the fluid−structure coupling effect were established separately. In addition, the mechanism of the oil−gas−pipeline coupling action on the seismic response of pipeline structure was analyzed, and the results were obtained. The results show that the pipeline has a minimal seismic response at the abutment location, the seismic response gradually increases along the abutment to the main tower, and the seismic response reach is maximized at about one-fifth of the bridge platform. The seismic response of the oil and gas pipeline model structure using the additional-mass met... [more]

Reactive and biased human decision-making during well construction operations can result in problems ranging from minor inefficiencies to events that can have far-reaching negative consequences for safety, environmental compliance and cost. A system that can automatically generate an optimal action sequence from any given state to meet an operation’s objectives is therefore highly desirable. Moreover, an intelligent agent capable of self-learning can offset the computation and memory costs associated with evaluating the action space, which is often vast. This paper details the development of such action planning systems by utilizing reinforcement learning techniques. The concept of self-play used by game AI engines (such as AlphaGo and AlphaZero in Google’s DeepMind group) is adapted here for well construction tasks, wherein a drilling agent learns and improves from scenario simulations performed using digital twins. The first step in building such a system necessitates formulating the... [more]

This study develops robust numerical algorithms for the simulation of three-phase (solid-liquid-gas) boiling and bubble formation problems in rectangular channels. The numerical algorithms are based on the Finite Volume Methods (FVM) and implement both the volume-of-fluid (VOF) methods for liquid-gas interface tracking as well as the volume-fraction methods to account for the concentration of embedded solid nano-particles in the liquid phase. Water is used as the base-liquid and the solid phase is modelled via metallic nano-particles (both aluminium oxide and titanium oxide nano-particles are considered) that are homogeneously mixed within the liquid phase. The gas phase is considered as a vapour arising from the bolling processes of the liquid-phase. The finite volume methodology is implemented on the OpenFOAM software platform, specifically by careful modification and manipulation of existing OpenFOAM solvers. The governing fluid dynamical equations, for the three-phase boiling probl... [more]

Realizing the dynamic redundancy of sensors is of great significance to ensure the energy saving and normal operation of the heating, ventilation, and air-conditioning (HVAC) system. Building a virtual sensor model is an effective method of redundancy and fault tolerance for hardware sensors. In this paper, a virtual sensor modeling method combining the maximum information coefficient (MIC) and the spatial−temporal attention long short-term memory (STA-LSTM) is proposed, which is named MIC-STALSTM, to achieve the dynamic and nonlinear modeling of the supply and return water temperature at both ends of the chiller. First, MIC can extract the influencing factors highly related to the target variables. Then, the extracted impact factors via MIC are used as the input variables of the STA-LSTM algorithm in order to construct an accurate virtual sensor model. The STA-LSTM algorithm not only makes full use of the LSTM algorithm’s advantages in handling historical data series information, but... [more]

This paper proposes a quasi-resonant step-up DC-DC converter to provide the DC-link voltage for piezoelectric transmitters (PZETs). The resonance not only provides a soft-switching condition for the converter switches, but also helps to decrease the converter element sizes for marine applications. Operation modes of the proposed converter are discussed. The current and voltage of the converter components are derived analytically, and hence the converter gain is obtained. The performance of the proposed high-step-up, high-power density converter is examined through a comprehensive simulation study. The simulation results demonstrate the soft-switching operation and short transient time required for the converter to reach the reference output voltage. The converter output voltage remains unchanged when an inverter with a passive filter is placed at its output while supplying the PZET. The proposed DC-DC converter is prototyped to validate the converter gain and soft-switching operation e... [more]

This paper uses two competing machine learning models, namely the Support Vector Regression (SVR) and the eXtreme Gradient Boosting (XGBoost) against the Autoregressive Integrated Moving Average ARIMAX (p,d,q) model to identify their predictive performance of the crude oil volatility index before and during COVID-19. In terms of accuracy, forecasting results reveal that the SVR model dominates the XGBoost and ARIMAX models in predicting the crude oil volatility index before COVID-19. However, the XGBoost model provides more accurate predictions of the crude oil volatility index than the SVR and ARIMAX models during the pandemic. The inverse cumulative distribution of residuals suggests that both ML models produce good results in terms of convergence. Findings also indicate that there is a fast convergence to the optimal solution when using the XGBoost model. When analyzing the feature importance, the Shapley Additive Explanation Method reveals that the SVR performs significantly better... [more]

Data-driven electrical energy efficiency management is the emerging trend in electrical energy forecasting and management. This fusion of data science, artificial intelligence, and electrical energy management has turned out to be the most precise and robust energy management solution. The Smart Energy Informatics Lab (SEIL) of the Indian Institute of Technology (IIT) conducted an experimental study in 2019 to collect massive data on university campus energy consumption. The comprehensive comparative study preparatory to the recommendation of the best candidate out of 24 machine learning algorithms on the SEIL dataset is presented in this work. In this research work, an exhaustive parametric and empirical comparative study is conducted on the SEIL dataset for the recommendation of the optimal machine learning algorithm. The simulation results established the findings that Bagged Trees, Fine Trees, and Medium Trees are, respectively, the best-, second-best-, and third-best-performing al... [more]

The article presents a study of the flow through a tunable check valve used as a hydraulic lock in a system with an actuator. Special attention is given to energy losses of the liquid stream in the poppet gap. In the first stage of the research, CFD methods were used to determine the speed and pressure distributions for the fixed values of the input flow rate and the poppet position. The values of the jet angle and pressures determined based on the CFD results were used to build a simulation model of the entire hydraulic system in Matlab/Simulink environment. The influence of the spring parameters pressing the poppet against the valve seat on the pressure drop and thus on the amount of energy lost was investigated. In particular, the spring stiffness and initial tension were studied. The obtained results were used to develop guidelines for constructing a valve prototype. Finally, the results of simulation tests were verified based on the actual valve characteristic obtained on a test b... [more]

With the advantage of integrating distributed energy, storage and DC load with high efficiency, the DC distribution network recently attracted wide attention in the field of nearly zero energy buildings. Considering the large number of buildings and the enormous energy-saving potential, the distribution form and the revenue distribution are key factors affecting energy efficiency and operational economy. Aiming at the characteristics of AC and DC distribution topologies in nearly zero energy buildings, an energy efficiency evaluation method is proposed based on time-sequential power flow simulation, where the piecewise linear efficiency function of converters and dynamic line power loss model are established. Based on a DC distribution demonstration project, an AC power distribution system with the same boundary conditions is designed. The results show that the efficiency of DC distribution topology is about 6% higher than the AC system, while the efficiency advantage in office, hotel,... [more]