This paper aims to propose a new algorithm for designing thermal vapor compressors (TVCs) using given operation parameters. First, an axisymmetric model was used to simulate a TVC, and the results were compared with those from published experimental results. A simulation set was designed to analyze the TVC dimensions, and then statistically-significant parameters (p-value < 0.05) were chosen for the subsequent studies. Thereafter, three parametric lengths were defined and a model presenting entrainment ratio (ER) was developed using a set of simulation results. The obtained characteristic equation allows us to scale (up or down) the TVC to different capacities, calculate the real-time sizes or predict the performance. It was found that the critical “TVC/primary nozzle” throat diameter ratio is constant in every scale-up study, depending on operation conditions. By establishing a characteristic graph, the approach was expanded for a broader algorithm. The comparative results revealed... [more]

The effect of the cam profile on the nonlinear dynamics phenomenon of the follower is studied at three involutes’ profiles for the cam. The value of the Lyapunov exponent parameter is calculated at different internal distances of the follower guide from inside and at different cam speeds. The effect of the Lyapunov exponent value on the contact stress is studied based on the clearance between the follower and its guides. The contact between the cam and the square grooving key and between the cam and the follower has been taken into consideration at different locations. The finite element method is used to calculate the contact stress numerically using the SolidWorks program. The nonlinear response of the follower is calculated analytically using the Newton−Euler equations of rigid body dynamics of translation and rotation motions while the follower position is tracked experimentally using a high-speed 3-D camera device. The contact stress is checked and verified using photo-elastic app... [more]

Mammals and birds have quicker heart rates compared to other species. Mammalian cardiomyocytes have T-tubule membranes that facilitate rapid changes in Ca2+ concentrations. In contrast, bird cardiomyocytes do not possess T-tubule membranes, which raises the question of how birds achieve fast heartbeats. In this study, we compared the changes in Ca2+ concentration in cardiomyocytes isolated from adult quails and rats to elucidate the mechanism resulting in rapid heart rates in birds. Cardiomyocytes isolated from quails were significantly narrower than those isolated from rats. When Ca2+ concentration changes in the entire cardiomyocytes were measured using Fura-2 acetoxymethyl ester (AM), the time to peak was statistically longer in quails than in rats. In contrast, the decay time was markedly shorter in quails than in rats. As a result, the total time of Ca2+ concentration change was shorter in quails than in rats. A spatiotemporal analysis of Ca2+ concentration changes in quail cardio... [more]

In order to predict and assess the danger from crown forest fires, it is necessary to study the thermal degradation of different forest fuels in a high-temperature environment. In this paper, the main characteristics of pyrolysis accompanied by moisture evaporation in a foliage sample of angiosperms (birch) were investigated within conditions typical for a crown forest fire. The heat and mass transfer in the forest fuel element is described by the system of non-stationary non-linear heat conduction equations with corresponding initial and boundary conditions. The considered problem is solved within the framework of the three-dimensional statement by the finite difference method. The locally one-dimensional method was used to solve three-dimensional equations for heat conduction. The simple iteration method was applied to solve nonlinear effects caused by the forest fuel pyrolysis and moisture evaporation. The fourth kind of boundary conditions are applicable at the interface between th... [more]

Social networks have become an integral part of our daily lives. With their rapid growth, our communication using these networks has only increased as well. Twitter is one of the most popular networks in the Middle East. Similar to other social media platforms, Twitter is vulnerable to spam accounts spreading malicious content. Arab countries are among the most targeted, possibly due to the lack of effective technologies that support the Arabic language. In addition, as a complex language, Arabic has extensive grammar rules and many dialects that present challenges when extracting text data. Innovative methods to combat spam on Twitter have been the subject of many current studies. This paper addressed the issue of detecting spam accounts in Arabic on Twitter by collecting an Arabic dataset that would be suitable for spam detection. The dataset contained data from premium features by using Twitter premium API. Data labeling was conducted by flagging suspended accounts. A combined frame... [more]

To investigate the effects of different aging times, three An−tea samples were selected for comparison with a non-aged sample as the control (CK, one-year-old) and labeled as high-aged (HAS, 12 years old), medium-aged (MAS, 7 years old), and low-aged samples (LAS, 2 years old). Changes in the volatile components of the different An−tea samples were investigated using headspace−solid-phase microextraction (HS-SPME) combined with gas chromatography−mass spectrometry (GC-MS). The volatile components of An−tea consisted of eight types of compounds. Aldehydes and hydrocarbons were dominant in LAS, while esters, ketones, alcohols, nitrogen-containing compounds, and ethers were the most abundant compound in MAS. Esters were dominant in HAS, while phenols were only present in LAS and CK. As aging time increased, the number of identical compounds gradually decreased, while the relative contents of the alcohols also decreased. Except for CK, the contents of ketones and aldehydes gradually decrea... [more]

This paper proposes a new approach for remaining useful life prediction that combines a bond graph, the Gaussian Mixture Model and similarity techniques to allow the use of both physical knowledge and the data available. The proposed method is based on the identification of relevant variables that carry information on degradation. To this end, the causal properties of the bond graph (BG) are first used to identify the relevant sensors through the fault observability. Then, a second stage of analysis based on statistical metrics is performed to reduce the number of sensors to only the ones carrying useful information for failure prognosis, thus, optimizing the data to be used in the prognosis phase. To generate data in the different system state, a simulator based on the developed BG is used. A Gaussian Mixture Model is then applied on the generated data for fault diagnosis and clustering. The Remaining Useful Life is estimated using a similarity technique. An application on a mechatron... [more]

In loess the aggregate is the basic structural unit, and its stability is an important factor affecting the composition, water stability and strength of loess. However, due to the difficulty of sample preparation, few scholars have done independent research on it. In this manuscript, a numerical model of aggregate is constructed by the discrete element method. Under the continuous action of certain stress, the uninterrupted development process of sample deformation with time was observed, that is, the creep of aggregate structures. The results show that the creep of aggregates is closely related to the relative movement, rotation and rearrangement of internal structural elements, and the most intuitive mesoscopic evolution of the adjustment process of structural elements is the change of contact number, namely the coordination number. The microscopic parameters and evolutionary characteristics of fabric can reveal the microscopic mechanism behind the macroscopic creep phenomenon. With... [more]

Alizarin dye is toxic and has a negative influence on human life and the environment. Consequently, the scientific community faces a difficult issue in developing efficient approaches for removing alizarin from water streams. Six distinct deep eutectic solvents (DESs) containing different hydrogen bond acceptors (HBAs), namely trioctylphosphine, trioctylamine and trihexylamine, and two hydrogen bond donors (HBDs), namely salicylic acid and malonic acid, were used to rapidly remove alizarin from high concentration solutions up to 2000 mg/L at room temperature using the liquid−liquid micro-extraction method (LLE). DES-3 had the highest extraction efficiency for alizarin among the other synthesized DESs. The effect of process variables such pH, contact time, dye initial concentration, volume ratio, temperature and salt on alizarin extraction efficiency from water stream was explored, optimized and reported. Statistical analysis was conducted to ensure the accuracy of values for the optimi... [more]

The hot jet of an aero engine is one of the main radiation sources of infrared detectors in 3−5 microwave bands. Transverse jets were introduced into a hot jet to enhance mixing and reduce the infrared radiation characteristics. This proved to be a high-efficiency and low-resistance infrared suppression technology. The steady-state distribution of temperature data was simulated, which was needed in the thermal radiation calculation. The radiation characteristics were calculated based on the anti-Monte Carlo method in 3−5 microwave bands. The mechanics of enhanced mixing by a rectangular nozzle or transverse jets was investigated with the LES simulation. Compared with an axisymmetric nozzle, a rectangular nozzle induced abundant counter-rotating vortex pairs (CVP), hairpins, shears, and helical vortexes, which resulted in significant mixing enhancement and infrared radiation decrease of the hot jets. Further, circumferential transverse jets of different types were introduced downstream... [more]

Micro-Electric Discharge Machining (μ-EDM) is one of the widely applied micromanufacturing processes. However, it has several limitations, such as a low cutting rate, difficult debris removal, and poor surface integrity, etc. Hybridization of the μ-EDM is proposed as an alternative to overcome the process limitations. Conversely, it complicates the process nature and poses a challenge for modelling and predicting critical process responses. Therefore, in this work, two distinct, nonparametric, previously unreported, workpiece material independent models using a Generalized Regression Neural Network (GRNN) and Gaussian Process Regression (GPR) were developed and compared to assess their performance with limited training data. Various smoothing factors and kernels were tested for GRNN and GPR, respectively. The prediction of models was compared in terms of the mean absolute percentage error, root mean square error, and coefficient of determination. The results showed that GPR outperforms... [more]

Moisture is a crucial quality property for granules in fluidized bed granulation (FBG) and accurate prediction of the granule moisture is significant for decision making. This study proposed a novel stacking ensemble method to predict the granule moisture based on granulation process parameters. The proposed method employed k-nearest neighbor (KNN), random forest (RF), light gradient boosting machine (LightGBM) and deep neural networks (DNNs) as the base learners, and ridge regression (RR) as the meta learner. To improve the diversity of the base learners, perturbations of the input variables and network structures were adopted in the proposed method, implemented by feature construction and combination of multiple DNNs with a different number of hidden layers, respectively. In the feature construction, a SHapley Additive exPlanations (SHAP) approach was innovatively utilized to construct effective synthetic features, which enhanced the prediction performance of the base learners. The c... [more]

The coupling of individual models in terms of end-to-end calculations for unit operations in manufacturing processes is a challenging task. We present a probability distribution-based approach for the combined outcomes of parametric and non-parametric models. With this so-called Bayesian predictive ensemble, the statistical moments such as mean value and standard deviation can be accurately computed without any further approximation. It is shown that the ensemble of different model predictions leads to an uninformed prior distribution, which can be transformed into a predictive posterior distribution using Bayesian inference and numerical Markov Chain Monte Carlo calculations. We demonstrate the advantages of our method using several numerical examples. Our approach is not restricted to certain unit operations, and can also be used for the more robust interpretation and assessment of model predictions in general.

The technology of coal breaking and punching by a high-pressure water jet can increase the permeability of coal seam and prevent gas explosion accidents. As one of the key components of this technology, the structural parameters of the nozzle have an important effect on the performance of the water jet. At present, the relationship between multiple optimization indexes and structural parameters of the nozzle is mostly studied separately. In fact, the influence of the nozzle structural parameters on different optimization indexes is different. When there are multiple optimization indexes, they should be considered collaboratively to achieve the best water jet performance of the nozzle. Therefore, a multi−objective collaborative optimization method is proposed which takes the maximum velocity in X-axis and effective extension distance in Y-axis as the performance evaluation indexes of the water jet. The numerical simulation of the nozzle jet is carried out by computational fluid dynamics... [more]

This paper presents a generic and unsupervised failure prognosis method which can be applied to wide scope of applications. The main contribution of the presented method is automatic relevant data identification based on signal smoothing and trendability analysis and automatic degradation model identification for health indices construction, built using a trained neural network, thus allowing for the automatic adaptation of the degradation trend model to changes in the degradation dynamic. Regarding the failure prognosis, the end of life is first predicted using a fitting model; then, the remaining useful life is predicted using a similarity algorithm. The proposed approach is validated using the turbofan engine data sets provided by NASA. The prediction results have been evaluated using accuracy metrics such as root mean square error and prognostic metrics such α−λ and relative accuracy. The obtained results show the effectiveness of the proposed method, both for the end of life and r... [more]

A Generalized Additive Model (GAM) is proposed to predict the pressure drop in a gas−liquid two-phase flow at horizontal, vertical, and inclined pipes based on 21 different dimensionless numbers. It is fitted from 4605 points, considering a fluid pattern classification as Annular, Bubbly, Intermittent, and Segregated. The GAM non-parametric method reached high prediction capacity and allowed a great degree of interpretability (i.e., it helped to visualize and test statistical inference), considering that each predictor’s marginal effects could be described, unlike in other Machine Learning (ML) methods. The prediction capacity of the GAM model for the pressure gradient obtained an adjusted R2 and a mean relative error of 99.1% and 12.93%, respectively. This capacity is maintained even when ignoring Bubbly flow in the training sample. A regularization technique to filter some variables was used, but most of the predictors must maintain the model’s high predictive ability. For example, d... [more]

Based on the context of Industry 4.0 smart manufacturing and for the prediction of injection molding quality of automobile bumpers, this study proposes a deep learning network that combines artificial neural networks and recognizable performance evaluation methods to better achieve the prediction and control of product quality. A pressure sensor was used to monitor and collect real-time pressure data in the mold cavity of the bumper. The quality indicators reflecting the molding quality were selected, and the correlation between these indicators and the molding quality was evaluated using recognizable performance evaluation methods and Pearson’s correlation coefficient. The standard z-score was used to filter out the abnormal data in the experimental data, and the bumper critical length warpage was converted into different quality levels, and the bumper critical length warpage was defined as either “qualified” and “unqualified” in order to improve the prediction accuracy of the model.... [more]

Biological systems, by nature, are highly complex. These systems exhibit diverse hierarchical spatial and temporal features when driven far from equilibrium. The generated features are susceptible to the initial conditions that largely depend on vast parameter space. Extracting information on their properties and behavior thus becomes far too complex. This work seeks to examine the drying kinetics of the drops containing a globular protein (lysozyme (Lys)), phosphate buffer saline (PBS), and thermotropic liquid crystal (LCs). The drying evolution and the morphological crack patterns of these drops are examined using high-resolution microscopy, textural image analysis, and statistical methods. This study observes that the textural parameters can identify the (i) phase separation of the salts present in the PBS and (ii) the LCs’ birefringence during the drying evolution. This birefringence activities of the LCs slow down when the initial PBS concentration is increased from 0.25 to 1× des... [more]

In order to solve the problems of poor stability of the output speed and poor synchronization of the pump-controlled dual motor in a hydraulic travel system during step input speed and external load disturbance, different control strategies were designed and compared with the state machine using the statechart module control, Z-N frequency response PID control, and GA-based PID parameter self-tuning methods. Our analysis shows that the BP algorithm-based PID parameter self-tuning control method has no overshoot and that the three methods reduced the target speed tracking time by 90.11%, 75.12% and 36.55%, respectively. The average synchronous error for the system output speed was 7.95%. The stability and synchronization requirements of the constant speed of the hydraulic travel system were satisfied. These research results can provide a reference for the design and application of constant speed control for pump-controlled dual-motor hydraulic travel systems in the fields of engineering... [more]

Nonlinearity may cause a model deviation problem, and hence, it is a challenging problem for process monitoring. To handle this issue, local kernel principal component analysis was proposed, and it achieved a satisfactory performance in static process monitoring. For a dynamic process, the expectation value of each variable changes over time, and hence, it cannot be replaced with a constant value. As such, the local data structure in the local kernel principal component analysis is wrong, which causes the model deviation problem. In this paper, we propose a new two-step dynamic local kernel principal component analysis, which extracts the static components in the process data and then analyzes them by local kernel principal component analysis. As such, the two-step dynamic local kernel principal component analysis can handle the nonlinearity and the dynamic features simultaneously.

Shale gas gathering and transportation pipeline poses significant risk due to special geographical conditions and different climatic conditions in high consequence areas such as Sichuan and Chongqing. The risks become critical as gas pipelines run through high consequence areas such as hospital, market, and scenic areas. This study presents a risk classification method for the pipelines running through high consequence areas. The proposed method considers different failure scenarios including third-party damage, corrosion, design and construction defects, mis-operation, and natural disasters. The method uses subjective and objective data from different sources. To minimize the subjectivity and data uncertainty, an improved fuzzy analytic hierarchy process was used to process data. The estimated risk is used to classify different risk zones. After the failure of shale gas pipelines in HCAs, in order to reduce the adverse impact of emergencies, personnel should immediately organize an ev... [more]

Based on fuel crossover behavior and bubble nucleation in the microfluidic fuel cell’s channel, this research numerically presents the performance of air-breathing direct formic acid microfluidic fuel cells. In the simulation, a three-dimensional microfluidic fuel cell model was used. The continuity, momentum, species transport, and charge equations were used to develop the model transport behavior, whereas the Brinkman equation represented the porous medium flow in the gas diffusion layer. The I−V and power density curves are generated using the Butler−Volmer equation. The simulation and current experimental data were compared under identical operating conditions to validate the I−V curve of the microfluidic fuel cell model. The model was used to investigate the current density distribution in the microchannel due to bubble obstruction and the reactant concentration on both electrodes. Fuel crossover resulted in a large decrease in open-circuit voltage and a reduction in fuel concentr... [more]

In the train operation department, the most important and dynamic factor is that the department employees are involved in all areas. Realizing the dynamic control of “key person, key event, and key period” to fundamentally curb employee inertia violation is a significant issue that needs to be solved on the railway site. The traditional “probability−severity” two-dimensional risk assessment model is carried out from the perspective of the system, ignoring the spatiotemporal risk characteristics of the individual, and a large amount of hazard factor data generated in the operation process is not applied in the risk assessment process. As a result, safety behavior risk practice lacks pertinence, accuracy, and individuation. This study proposes a safety behavior risk assessment model based on the grid management and hazard factor assignment function to improve the traditional two-dimensional risk matrix. By introducing spatial location variables, the method accurately locates and classifi... [more]

The current investigations are carried out to study the influence of the Darcy−Forchheimer relation on third-grade fluid flow and heat transfer over an angled exponentially stretching sheet embedded in a porous medium. In the current study, the applied magnetic field, Joule heating, thermaldiffusion, viscous dissipation, and diffusion-thermo effects are incorporated. The proposed model in terms of partial differential equations is transformed into ordinary differential equations using suitable similarity transformation. The reduced model is then solved numerically with the help of MATLAB built-in function bvp4c.The numerical solutions for velocity profile, temperature profile, and mass concentration under the effects of pertinent parameters involved in the model are determined and portrayed in graphical form. The graphical effects of the skin friction coefficient, the Nusselt number, and the Sherwood number are also shown. From the displayed results, we conclude that when the Joule hea... [more]

The LH11-1 FPSO is an 80,000 t cylindrical structure that is responsible for the processing, storage, and offloading of process oil from existing and newly developed oilfields. In this paper, a full probabilistic analysis was developed based on very detailed CFD simulation results to evaluate ventilation, gas dispersion, explosion, and fire scenarios. A detailed fire and explosion risk analysis of LH11-1 FPSO was performed based on NORSOK Z-013 and FABIG Technical Note 11. The risk-based calculations were performed applying FLACS, KFX, and DNV GLEXPRESS Fire. Finally, the oil and gas dispersion, fire, and explosion consequence risks were calculated under the credible combination of leak frequency and leak location. By this probabilistic risk analysis, it was found that the west wind could generate optimal ventilation conditions for the topside process area of FPSO compared to other wind directions, while the hull region was poorly ventilated for all wind directions. The explosion risk... [more]