Biochemical engineering deals with the processing of biological or chemical materials using enzymes or living cells as biological catalysts [...]

Computational fluid dynamics (CFD) have been extensively used to simulate the hydrodynamics of multiphase flows (MPFs) in rotating machinery. In the presence of a granular dense phase, the Kinetic Theory of Granular Flow (KTGF) is usually coupled to Eulerian multi-fluid models to obtain tractable computational fluid models. In the present work, the hydrodynamic behavior of a three dimensional, industrial scale, and rotating drum granulator with gas−solid flows is assessed using the Eulerian−Eulerian approach coupled with the k-ε standard turbulence model. A Eulerian−Eulerian Two-Fluid Model (TFM) is used with the KTGF model for the granular phase. The sensitivities to different operating parameters, including the rotational speed (8, 16, and 24 rpm), inclination degree (3.57∘, 5.57∘, and 7.57∘), and degree of filling (20%, 30%, and 40%) are studied. Moreover, the impact of the drag model on the simulation accuracy is investigated. The flow behavior, regime transitions, and particle dis... [more]

This paper studies the characteristics of four dual-load systems, coaxial different sides, coaxial same side, different axis same side, and coplanar coaxial, based on the principle of near-field resonance wireless power transmission. Firstly, a dual-load cooperative coupling equivalent circuit model is established, the mathematical expression of system energy efficiency is derived, and the influence of the cross-coupling of the receiving coils in the system on the performance of the system is compared and analyzed in four coupling situations. Secondly, the magnetic field distribution characteristics and the influence of transmission distance and load impedance on the transmission characteristics are studied by electromagnetic field simulation software. Finally, the experimental results show that the maximum efficiency of the dual-load wireless power transmission system is only 0.43 in the case of coaxial and coplanar coupling, which is not suitable for power transmission. In the case o... [more]

Due to the large size and large span of heavy-duty machine tools, the structural deformation errors caused by gravity account for a large proportion of the static errors, and the influence of gravity deformation must thus be considered in the machine tool precision design. This paper proposes a precision design method for heavy-duty vertical machining centers based on gravity deformation error modelling. By abstracting the machine tool into a multibody system topology, the static error model of the machine tool is established based on the multibody system theory and a homogeneous coordinate transformation. Assuming that the static error of each motion axis is composed of two parts, i.e., the manufacturing-induced geometric error and the gravity deformation error, the machine tool stiffness model of the relationship between gravity and deformation error is developed using the spatial beam elements. In the modelling process, the stiffness coefficients and volume coefficients of the compo... [more]

Large eddy simulations were performed for the conjugate heat transfer in a ribbed channel with a geometry, that mimics the internal cooling passage of a gas turbine, using 566, 100, 10, and 1 as the solid and fluid thermal conductivity ratios (K*) and 30,000, 7000 (turbulent flow), and 1000 (laminar flow) as the Reynolds numbers. A fully coupled simulation was conducted using the immersed boundary method (IBM) and a dynamic sub-grid-scale (SGS) model. In pure convection, a decrease in the Reynolds number from 30,000 to 7000 increased the heat transfer on the channel wall by 5% but decreased that on the rib by 20%. When K* > 10, the Reynolds number effect is stronger in the rib than in the wall. In the laminar flow, the effect of conduction appears at a low K*, and the heat transfer promotion is poor in the typical ribbed channel geometry. In the turbulent flow, if K* ≥ 100, then a heat transfer promotion is expected in the ribbed channel even at a low Reynolds number. For K* < 10, t... [more]

This research study investigates the modelling and simulation of biomass anaerobic dark fermentation in bio-hydrogen production in a continuous plug flow reactor. A CFD multiphase full transient model in long-term horizons was adopted to model dark fermentation biohydrogen production in continuous mode. Both the continuous discharge of biomass, which prevents the accumulation of solid parts, and the recirculation of the liquid phase ensure constant access to the nutrient solution. The effect of the hydraulic retention time (HRT), pH and the feed rate on the bio-hydrogen yield and production rates were examined in the simulation stage. Metabolite proportions (VFA: acetic, propionic, butyric) constitute important parameters influencing the bio-hydrogen production efficiency. The model of substrate inhibition on bio-hydrogen production from glucose by attached cells of the microorganism T. neapolitana applied to the modelling of the kinetics of bio-hydrogen production was used. The modell... [more]

Al-Sn-Al wafer bonding is a new semiconductor manufacturing technology that plays an important role in device manufacturing. Optimization of the bonding process and testing of the bonding strength remain key issues. However, using only physical experiments to study the above problems presents difficulties such as repeating many experiments, high costs, and low efficiency. Deep learning algorithms can quickly simulate complex physical correlations by training large amounts of data, which is a good solution to the difficulties in studying wafer bonding. Therefore, this paper proposes the use of deep learning models (2-layer CNN and 50-layer ResNet) to achieve autonomous recognition of bonding strengths corresponding to different bonding conditions, and the results from a comparative test set show that the ResNet model has an accuracy of 99.17%, outperforming the CNN model with an accuracy of 91.67%. Then, the identified images are analyzed using the Canny edge detector, which showed that... [more]

In industrial piping systems, turbomachinery, heat exchangers etc., pipe bends are essential components. Computational fluid dynamics (CFD), which is frequently used to analyse the flow behaviour in such systems, provides extremely precise estimates but is computationally expensive. As a result, a computationally efficient method is developed in this paper by leveraging machine learning for such computationally expensive CFD problems. Random forest regression (RFR) is used as the machine learning algorithm in this work. Four different fluid flow characteristics (i.e., axial velocity, x-velocity, y-velocity and z-velocity) are studied in this work. The accuracy of the RFR models is assessed by using a number of statistical metrics such as mean-absolute error (MAE), mean-squared-error (MSE), root-mean-squared-error (RMSE), maximum error (Max.Error) and median error (Med.Error) etc. It is observed that the RFR models can produce considerable cost reductions in computing by surrogating the... [more]

Pharmacokinetics (PK) is a branch of pharmacology present and of vital importance for the research and development (R&D) of new drugs, post-market monitoring, and continued optimizations in clinical contexts. Ultimately, pharmacokinetics can contribute to improving patients’ clinical outcomes, helping enhance the efficacy of treatments, and reducing possible adverse side effects while also contributing to precision medicine. This article discusses the methods used to predict and study human pharmacokinetics and their evolution to the current physiologically based pharmacokinetic (PBPK) modeling and simulation methods. The importance of therapeutic drug monitoring (TDM) and PBPK as valuable tools for Model-Informed Precision Dosing (MIPD) are highlighted, with particular emphasis on antibiotic therapy since dosage adjustment of antibiotics can be vital to ensure successful clinical outcomes and to prevent the spread of resistant bacterial strains.

Modelling the profile of a liquid droplet has been a mainstream technique for researchers to study the physical properties of a liquid. This study proposes a facile modelling approach using an elliptic model to generate the profile of sessile droplets, with MATLAB as the simulation environment. The concept of the elliptic method is simple and easy to use. Only three specific points on the droplet are needed to generate the complete theoretical droplet profile along with its critical parameters such as volume, surface area, height, and contact radius. In addition, we introduced fitting coefficients to accurately determine the contact angle and surface tension of a droplet. Droplet volumes ranging from 1 to 300 µL were chosen for this investigation, with contact angles ranging from 90° to 180°. Our proposed method was also applied to images of actual water droplets with good results. This study demonstrates that the elliptic method is in excellent agreement with the Young−Laplace equatio... [more]

The urban heat island (UHI) effect increases the ambient temperatures in cities and alters the energy budget of building materials. Urban surfaces such as pavements and roofs absorb solar heat and re-emit it back into the atmosphere, contributing towards the UHI effect. Over the past few decades, researchers have identified albedo and thermal inertia as two of the most significant thermal properties that influence pavement surface temperatures under a given solar load. However, published data for comparisons of albedo and thermal inertia are currently inadequate. This work focuses on asphalt and concrete as two important materials used in the construction of pavements. Computational fluid dynamics (CFD) analyses are performed on asphalt and concrete pavements with the same dimensions and under the same ambient conditions. Under given conditions, the pavement top surface temperature is evaluated with varying albedo and thermal inertia values. The results show that the asphalt surface te... [more]

Tolerance analysis is crucial in every manufacturing process, such as electrical machine design, because tight tolerances lead to high manufacturing costs. A FEM-based solution of the tolerance analysis of an electrical machine can easily lead to a computationally expensive problem. Many papers have proposed the design of experiments, surrogate-model-based methodologies, to reduce the computational demand of this problem. However, these papers did not focus on the information loss and the limitations of the applied methodologies. Regardless, the absolute value of the calculated tolerance and the numerical error of the applied numerical methods can be in the same order of magnitude. In this paper, the tolerance and the sensitivity of BLDC machines’ cogging torque are analysed using different methodologies. The results show that the manufacturing tolerances can have a significant effect on the calculated parameters, and that the mean value of the calculated cogging torque increases. The... [more]

Casein kinase 2 (CK2) is considered an important target for anti-cancer drugs. Given the structural diversity and broad spectrum of pharmaceutical activities of natural products, numerous studies have been performed to prove them as valuable sources of drugs. However, there has been little study relevant to identifying structural factors responsible for their inhibitory activity against CK2 with machine learning methods. In this study, classification studies were conducted on 115 natural products as CK2 inhibitors. Seven machine learning methods along with six molecular fingerprints were employed to develop qualitative classification models. The performances of all models were evaluated by cross-validation and test set. By taking predictive accuracy(CA), the area under receiver operating characteristic (AUC), and (MCC)as three performance indicators, the optimal models with high reliability and predictive ability were obtained, including the Extended Fingerprint-Logistic Regression mod... [more]

Dowex® HCR-S ion-exchange resin was used to adsorb ectoine in a batch system under varying operation conditions in terms of contact time, temperature, pH value, initial concentration of ectoine, and type of salt. Six adsorption isotherm models (Langmuir, Freundlich, Temkin, Dubinin−Radushkevich, Sips, and Redlich−Peterson) and three kinetic models (pseudo-first-order, pseudo-second-order, and intraparticle diffusion) were used to investigate the ectoine adsorption mechanism of ion-exchange resin. According to the experimental results, the mechanism of ectoine adsorption using an ion exchanger includes the ion-exchange reaction and physisorption. Both the Langmuir and Freundlich models were found to have a high fitting. For the kinetic analysis, the pseudo-second-order and intraparticle diffusion models were suitable to describe the ectoine adsorption. Dowex® HCR-S resin has an average saturated adsorption capacity of 0.57 g/g and 93.6% of ectoine adsorption at 25~65 °C, with an initial... [more]

A jet pump is used to transport a variety of working media and is especially suitable for dredged soil transporting. In this study, a three-dimensional numerical study of a jet pump that is used for slurry delivery was carried out. The characteristics of the internal flow field of the mixing chamber with different working parameters were comprehensively analyzed. The results indicate that the pressure of the axial line decreases with increasing flow ratio (ratio of suction flux and inlet flux) while the pressure of the injected slurry shows a downward trend. With the increase in the flow ratio, the pressure ratio (difference between inlet pressure and suction pressure divided by the difference between exit pressure and suction pressure) falls off while the efficiency presents a parabolic distribution. The pressure ratio can be promoted by properly increasing the length of the mixing chamber so that the available efficiency is broadened. When the mixing chamber length is L = 2.5Dn~4.0Dn... [more]

The primary supporting structure of an automobile and its other vital systems is the chassis. The chassis structure is required to bear high shock, stresses, and vibration, and therefore it should possess adequate strength. The objective of current research is to analyze a heavy motor vehicle chassis using numerical and experimental methods. The CAD design and FE analysis is conducted using the ANSYS software. The design of the chassis is then optimized using Taguchi design of Experiments (DOE); the optimization techniques used are the central composite design (CCD) scheme and optimal space filling (OSF) design. Thereafter, sensitivity plots and response surface plots are generated. These plots allow us to determine the critical range of optimized chassis geometry values. The optimization results obtained from the CCD design scheme show that cross member 1 has a higher effect on the equivalent stresses as compared to cross members 2 and 3. The chassis mass reduction obtained from the C... [more]

Non-traditional machining (NTM) has gained significant attention in the last decade due to its ability to machine conventionally hard-to-machine materials. However, NTMs suffer from several disadvantages such as higher initial cost, lower material removal rate, more power consumption, etc. NTMs involve several process parameters, the appropriate tweaking of which is necessary to obtain economical and suitable results. However, the costly and time-consuming nature of the NTMs makes it a tedious and expensive task to manually investigate the appropriate process parameters. The NTM process parameters and responses are often not linearly related and thus, conventional statistical tools might not be enough to derive functional knowledge. Thus, in this paper, three popular machine learning (ML) methods (viz. linear regression, random forest regression and AdaBoost regression) are employed to develop predictive models for NTM processes. By considering two high-fidelity datasets from the liter... [more]

The paper presents an experimental study regarding the treatment of a real textile wastewater using the spinning disc (SD) technology, either individually or associated with an advanced Fenton oxidation step. The SD efficiency was investigated by studying the color, suspended solids, or turbidity removals, at distinctive feeding flowrates (10−30 L/h) and disc rotating speeds (100−1500 rpm). The data revealed increasing removal trends and allowed to establish the highest removal values. Based on obtained experimental results, the wastewater treatment efficiency by SD technology was reasonably good and thus, the WW indicators can be improved within relatively short periods of time. Additionally, based on supervised learning algorithms, the study includes treatment modeling for turbidity and color removal, followed by turbidity removal optimization relying on the best learned models. Satisfactory results obtained with the modeling and optimization procedures provide useful predictions for... [more]

Microwave drying of suspensions of lignocellulosic fibers has the potential to produce porous foam materials that can replace materials such as expanded polystyrene, but the design and control of this drying method are not well understood. The main objective of this study was to develop a microwave drying model capable of predicting moisture loss regardless of the shape and microwave power input. A microwave heating model was developed by coupling electromagnetic and heat transfer physics using a commercial finite element code. The modeling results predicted heating time behavior consistent with experimental results as influenced by electromagnetic fields, waveguide size and microwave power absorption. The microwave heating modeling accurately predicted average temperature increase for 100 cm3 water domain at 360 and 840 W microwave power inputs. By dividing the energy absorption by the heat of vaporization, the amount of water evaporation in a specific time increment was predicte... [more]

Based on the theory of computational fluid dynamics (CFD), with the help of the Fluent software and the powerful parallel computing capability of the super cloud computer, the single-phase flow transient simulation calculation of the windage power loss of the engagement spiral bevel gear pair (SBGP) was performed. The two-equation SST k-ω turbulence model based on the assumption of eddy viscosity was adopted, which was improved from the standard k-ε model combined with the Wilcox k-ω model. The SST k-ω turbulence model inherited the respective advantages of the Wilcox k-ω model in the near-wall region and the k-ε model in the free shear layer and could more accurately describe the resistance and separation effect of the gear tooth surface on the airflow. The simulation analyzed the airflow characteristics around SBGP and the mechanism of the windshield to reduce the windage loss of the gear. It also studied the influence of the windshield clearance and opening size on the windage power... [more]

The numerical model of the granular flow within an aggregate mixture, conducted in the vertical static and/or the conveyor blender, was explored using the discrete element method (DEM) approach. The blending quality of limestone fine aggregate fractions binary mixture for application in self-compacting concrete was studied. The potential of augmenting the conveyor mixer working efficiency by joining its operation to a Komax-type vertical static mixer, to increase the blending conduct was investigated. In addition the impact of the feed height on the flow field in the cone-shaped conveyor mixer was examined using the DEM simulation. Applying the numerical approach enabled a deeper insight into the quality of blending actions, while the relative standard deviation criteria ranked the uniformity of the mixture. The primary objective of this investigation was to examine the behavior of mixture for two types of blenders and to estimate the combined blending action of these two mixers, to ex... [more]

In this paper, a dynamic operational linear regulator (DOLR) based on a GaN high-electron-mobility transistor (HEMT) and wide-bandwidth operational amplifier was developed and implemented. The driving current could be regulated and controlled by the DOLR for 632 nm laser diodes. The constant-current mode for the continuous-wave laser and the pulse-width modulation (PWM) mode for the short-pulsed laser were realizable using this DOLR. This study focused on the rising-edge time change on the laser driving current when the DOLR was operated under the high-frequency PWM mode, because the parasitic components on the GaN HEMT, laser diodes, printed circuit board, and power wires could influence the current’s dynamic behavior. Therefore, the equivalent circuit models of the laser diode and GaN HEMT were applied to establish a DOLR simulation circuit in order to observe the rising-edge time change on the laser driving current. A DOLR prototype was achieved, and so experimental waveform measure... [more]

The paper presents a numerical and experimental investigation of the effect of incindence angle offset in a two-dimensional section of a flat blade cascade in a high-speed wind tunnel. The aim of the current work is tp determine the aerodynamic excitation forces and approximation of the unsteady blade-loading function using a quasi-stationary approach. The numerical simulations were performed with an in-house finite-volume code built on the top of the OpenFOAM framework. The experimental data were acquired for regimes corresponding to the numerical setup. The comparison of the computational and experimental results is shown for the static pressure distributions on three blades and upstream and downstream of the cascade. The plot of the aerodynamic moments acting on all five blades shows that the adjacent blades are significantly influenced by the angular offset of the middle blade.

The global coronavirus pandemic continues to restrict public life worldwide. An effective means of limiting the pandemic is vaccination. Messenger ribonucleic acid (mRNA) vaccines currently available on the market have proven to be a well-tolerated and effective class of vaccine against coronavirus type 2 (CoV2). Accordingly, demand is presently outstripping mRNA vaccine production. One way to increase productivity is to switch from the currently performed batch to continuous in vitro transcription, which has proven to be a crucial material-consuming step. In this article, a physico-chemical model of in vitro mRNA transcription in a tubular reactor is presented and compared to classical batch and continuous in vitro transcription in a stirred tank. The three models are validated based on a distinct and quantitative validation workflow. Statistically significant parameters are identified as part of the parameter determination concept. Monte Carlo simulations showed that the model is pre... [more]

The three-blade combined agitator consists of two propulsion blades of the same type (including planar propeller blades b, δ = 36.87°) and a curved blade (θ = 30°). Using numerical simulation methods, the power characteristics, flow field distribution, turbulence characteristics and dead zone percentage of two kinds of three-blade combined agitators (TBCAs) from laminar flow to turbulent flow in a mixing vessel were studied. Moreover, the torque measurement method was used to perform experimental verification. The results show that the predicted power curve is consistent with the experimental results. The fluid velocity near the propeller blades in the TBC-B type agitator (δ = 36.87°) is significantly high, and the maximum increase of the total velocity can reach 30.3%. The fluid flow velocity near the curved blades is increased, and the radial diffusion ability of the fluid at the bottom of the stirring vessel is enhanced. When mixing low-viscosity fluids, the TBC-B type agitator can... [more]