Computational Mass Transfer Method for Chemical Process Simulation

The recent works on the development of computational mass transfer （CMT） method and its applications in chemical process simulation are reviewed. Some development strategies and challenges in future research are also discussed.

Prediction of Distillation Column Performance by Computational Mass Transfer Method

A computational mass transfer model is proposed for predicting the concentration profile and Murphree efficiency of sieve tray distillation column. The proposed model is based on using modified c＇2 -εc＇ two equations formulation for closing the differential turbulent mass transfer equation with improvement by considering the vapor injected from the sieve hole to be three dimensional. The predicted concentration distributions by using proposed model were checked by experimental work conducted on a sieve tray simulator of 1.2 meters in diameter for desorbing the dissolved oxygen in the feed water by blowing air. The model predictions were confirmed by the experimental measurement. The validation of the proposed model was further tested by comparing the simulated result with the performance of an industrial scale sieve tray distillation column reported by Kunesh et al. for the stripping of toluene from its water solution. The predicted outlet concentration of each tray and the Murphree tray efficiencies under different operating conditions were in agreement with the published data. The simulated turbulent mass transfer diffusivity on each tray was within the range of the experimental result in the same sieve column reported by Cai et al. In addition, the prediction of the influence of sieve tray structure on the tray efficiency by using the proposed model was demonstrated.

Online Computation Offloading and Trajectory Scheduling for UAV-Enabled Wireless Powered Mobile Edge Computing

The unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) architecture is expected to be a powerful technique to facilitate 5 G and beyond ubiquitous wireless connectivity and diverse vertical applications and services, anytime and anywhere. Wireless power transfer(WPT) is another promising technology to prolong the operation time of low-power wireless devices in the era of Internet of Things(IoT). However, the integration of WPT and UAV-enabled MEC systems is far from being well studied, especially in dynamic environments. In order to tackle this issue, this paper aims to investigate the stochastic computation offloading and trajectory scheduling for the UAV-enabled wireless powered MEC system. A UAV offers both RF wireless power transmission and computation services for IoT devices. Considering the stochastic task arrivals and random channel conditions, a long-term average energyefficiency(EE) minimization problem is formulated.Due to non-convexity and the time domain coupling of the variables in the formulated problem, a lowcomplexity online computation offloading and trajectory scheduling algorithm(OCOTSA) is proposed by exploiting Lyapunov optimization. Simulation results verify that there exists a balance between EE and the service delay, and demonstrate that the system EE performance obtained by the proposed scheme outperforms other benchmark schemes.

Computation Rate Maximization in Multi-User Cooperation-Assisted Wireless-Powered Mobile Edge Computing with OFDMA

In the era of Internet of Things(Io T),mobile edge computing(MEC)and wireless power transfer(WPT)provide a prominent solution for computation-intensive applications to enhance computation capability and achieve sustainable energy supply.A wireless-powered mobile edge computing(WPMEC)system consisting of a hybrid access point(HAP)combined with MEC servers and many users is considered in this paper.In particular,a novel multiuser cooperation scheme based on orthogonal frequency division multiple access(OFDMA)is provided to improve the computation performance,where users can split the computation tasks into various parts for local computing,offloading to corresponding helper,and HAP for remote execution respectively with the aid of helper.Specifically,we aim at maximizing the weighted sum computation rate(WSCR)by optimizing time assignment,computation-task allocation,and transmission power at the same time while keeping energy neutrality in mind.We transform the original non-convex optimization problem to a convex optimization problem and then obtain a semi-closed form expression of the optimal solution by considering the convex optimization techniques.Simulation results demonstrate that the proposed multi-user cooperationassisted WPMEC scheme greatly improves the WSCR of all users than the existing schemes.In addition,OFDMA protocol increases the fairness and decreases delay among the users when compared to TDMA protocol.

Multiway Dynamic Trust Chain Model on Virtual Machine for Cloud Computing

This paper sums up four security factors after analyzing co-residency threats caused by the special multitenant environment in the cloud.To secure the factors,a multiway dynamic trust chain transfer model was proposed on the basis of a measurement interactive virtual machine and current behavior to protect the integrity of the system.A trust chain construction module is designed in a virtual machine monitor.Through dynamic monitoring,it achieves the purpose of transferring integrity between virtual machine.A cloud system with a trust authentication function is implemented on the basis of the model,and its practicability is shown.

Second-order two-scale computations for conductive radiative heat transfer problem in periodic porous materials

In this paper, a kind of second-order two-scale （SOTS） computation is developed for conductive-radiative heat trans- fer problem in periodic porous materials. First of all, by the asymptotic expansion of the temperature field, the cell problem, homogenization problem, and second-order correctors are obtained successively. Then, the corresponding finite element al- gorithms are proposed. Finally, some numerical results are presented and compared with theoretical results. The numerical results of the proposed algorithm conform with those of the FE algorithm well, demonstrating the accuracy of the present method and its potential applications in thermal engineering of porous materials.

A code-independent technique for computational verification of fluid mechanics and heat transfer problems

The goal of this paper is to present a versatile framework for solution verification of PDE＇s. We first generalize the Richardson Extrapolation technique to an optimized extrapolation solution procedure that constructs the best consistent solution from a set of two or three coarse grid solution in the discrete norm of choice. This technique generalizes the Least Square Extrapolation method introduced by one of the author and W. Shyy. We second establish the conditioning number of the problem in a reduced space that approximates the main feature of the numerical solution thanks to a sensitivity analysis. Overall our method produces an a posteriori error estimation in this reduced space of approximation. The key feature of our method is that our construction does not require an internal knowledge of the software neither the source code that produces the solution to be verified. It can be applied in principle as a postprocessing procedure to off the shelf commercial code. We demonstrate the robustness of our method with two steady problems that are separately an incompressible back step flow test case and a heat transfer problem for a battery. Our error estimate might be ultimately verified with a near by manufactured solution. While our pro- cedure is systematic and requires numerous computation of residuals, one can take advantage of distributed computing to get quickly the error estimate.

Energy-Delay Tradeoff for Online Offloading Based on Deep Reinforcement Learning in Wireless Powered Mobile-Edge Computing Networks

Benefited from wireless power transfer(WPT)and mobile-edge computing(MEC),wireless powered MEC systems have attracted widespread attention.Specifically,we design an online offloading scheme based on deep reinforcement learning that maximizes the computation rate and minimizes the energy consumption of all wireless devices(WDs).Extensive results validate that the proposed scheme can achieve better tradeoff between energy consumption and computation delay.

MATHEMATICAL MODEL AND COMPUTER SIMULATION OF MOISTURE TRANSFER PROCESS DURING SINTERING

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A NEW COMPUTATION METHOD FOR THE UNSTEADY HEAT TRANSFER COEFFICIENT IN A DEEP MINE

In mine geothermal prediction, the unsteady heat transfer coefficient is an important parameter for heat transfer computation between country rock and mine airflow. In this paper, the rock temperature distributions in the geothermal fields have been derived in mathematics, the unsteady heat transfer coefficients that can expound the relation between its nature and influencing factors have been derived also based on this analytic formula. It is shown both by numerical simulations and through in situ measurernents that the new computation method for determining the unsteady heat transfer cofeeicient is accurate, rapid and simple.

Air-Side Heat Transfer Performance Prediction for Microchannel Heat Exchangers Using Data-Driven Models with Dimensionless Numbers

This study explores the effectiveness of machine learning models in predicting the air-side performance of microchannel heat exchangers.The data were generated by experimentally validated Computational Fluid Dynam-ics(CFD)simulations of air-to-water microchannel heat exchangers.A distinctive aspect of this research is the comparative analysis of four diverse machine learning algorithms:Artificial Neural Networks(ANN),Support Vector Machines(SVM),Random Forest(RF),and Gaussian Process Regression(GPR).These models are adeptly applied to predict air-side heat transfer performance with high precision,with ANN and GPR exhibiting notably superior accuracy.Additionally,this research further delves into the influence of both geometric and operational parameters—including louvered angle,fin height,fin spacing,air inlet temperature,velocity,and tube temperature—on model performance.Moreover,it innovatively incorporates dimensionless numbers such as aspect ratio,fin height-to-spacing ratio,Reynolds number,Nusselt number,normalized air inlet temperature,temperature difference,and louvered angle into the input variables.This strategic inclusion significantly refines the predictive capabilities of the models by establishing a robust analytical framework supported by the CFD-generated database.The results show the enhanced prediction accuracy achieved by integrating dimensionless numbers,highlighting the effectiveness of data-driven approaches in precisely forecasting heat exchanger performance.This advancement is pivotal for the geometric optimization of heat exchangers,illustrating the considerable potential of integrating sophisticated modeling techniques with traditional engineering metrics.

Study of heat transfer by using DEM–CFD method in a randomly packed pebble-bed reactor

The pebble-bed reactor is one of the most promising designs for the nuclear energy industry. In this paper,a discrete element method-computational fluid dynamics(DEM-CFD) approach that includes thermal conduction, radiation, and natural convection mechanisms was proposed to simulate the thermal-fluid phenomena after the failure of forced circulation cooling system in a pebble-bed core. The whole large-scale packed bed was created using the DEM technique, and the calculated radial porosity of the bed was validated with empirical correlations reported by researchers. To reduce computational costs, a segment of the bed was extracted, which served as a good representative of the large-scale packed bed for CFD calculation. The temperature distributions simulated with two different fluids in this DEM-CFD approach were in good agreement with SANA experimental data. The influence of the natural convection mechanism on heat transfer must be taken into account for coolants with strong convective capacity. The proposed DEM-CFD methodology offers a computationally efficient and widely applied method for understanding the heat transfer process in a pebble-bed core. The method can also be easily extended to assess the passive safety features of newly designed fluoride-salt-cooled pebble-bed reactors.

A Lightweight CNN Based on Transfer Learning for COVID-19 Diagnosis

The key to preventing the COVID-19 is to diagnose patients quickly and accurately.Studies have shown that using Convolutional Neural Networks(CNN)to analyze chest Computed Tomography(CT)images is helpful for timely COVID-19 diagnosis.However,personal privacy issues,public chest CT data sets are relatively few,which has limited CNN’s application to COVID-19 diagnosis.Also,many CNNs have complex structures and massive parameters.Even if equipped with the dedicated Graphics Processing Unit(GPU)for acceleration,it still takes a long time,which is not conductive to widespread application.To solve above problems,this paper proposes a lightweight CNN classification model based on transfer learning.Use the lightweight CNN MobileNetV2 as the backbone of the model to solve the shortage of hardware resources and computing power.In order to alleviate the problem of model overfitting caused by insufficient data set,transfer learning is used to train the model.The study first exploits the weight parameters trained on the ImageNet database to initialize the MobileNetV2 network,and then retrain the model based on the CT image data set provided by Kaggle.Experimental results on a computer equipped only with the Central Processing Unit(CPU)show that it consumes only 1.06 s on average to diagnose a chest CT image.Compared to other lightweight models,the proposed model has a higher classification accuracy and reliability while having a lightweight architecture and few parameters,which can be easily applied to computers without GPU acceleration.Code:github.com/ZhouJie-520/paper-codes.

Experimental and CFD Heat Transfer Studies of Al2Oa-Water Nanofluid in a Coiled Agitated Vessel Equipped with Propeller

This paper presents the heat transfer characteristics of A1203-water nanofluid in a coiled agitated vessel with propeller agitator. The experimental study was conducted using 0.10%, 0.20% and 0.30% volume concentra tion of A1203-water nanofluids. The results showed considerable enhancement of convective heat transfer using the nanofluids. The empirical correlations developed for Nusselt number in terms of Reynolds number, Prandtl number, viscosity ratio and volume concentration fit with the experimental data within ±10%. The heat transfer characteris tics were also simulated using computational fluid dynamics using FLUENT software with the standard ke model and multiple reference frame were adopted. The computational fluid dynamics （CFD） predicted Nusselt number agrees well with the experimental value and the discrepancy is found to be less than ＋8%.

Computational fluid dynamic simulation of gas-liquid flow in rotating packed bed:A review

The rotating packed bed(RPB)has been widely used in gas-liquid flow systems as a process intensification device,exhibiting excellent mass transfer enhancement characteristics.However,the complex internal structure and the high-speed rotation of the rotor in RPB bring significant challenges to study the intensification mechanism by experiment methods.In the past two decades,Computational fluid dynamics(CFD)has been gradually applied to simulate the hydrodynamics and mass transfer characteristics in RPB and instruct the reactor design.This article covers the development of the CFD simulation of gasliquid flow in RPB.Firstly,the improvement of the simulation method in the aspect of mathematical models,geometric models,and solving methods is introduced.Secondly,new progress of CFD simulation about hydrodynamic and mass transfer characteristics in RPB is reviewed,including pressure drop,velocity distribution,flow pattern,and concentration distribution,etc.Some new phenomena such as the end effect area with the maximum turbulent have been revealed by this works.In addition,the exploration of developing new reactor structures by CFD simulation is introduced and it is proved that such new structures are competitive to different applications.The defects of current research and future development directions are also discussed at last.

Heat transfer performance for DCLL blanket with no-wetting insulator walls

Magnetohydrodynamic (MHD) effect and heat transfer are two key issues for design of dual coolant lead lithium (DCLL) blanket. Flow channel insert (FCI) has been applied to decouple the liquid metal from the walls to efficiently decline MHD pressure drops and reduce heat losses from the liquid metal for increasing bulk exit temperatures of the blanket. However, there are still big pressure drops and a higher velocity jet located at the gap flow. Moreover, the FCI made from silicon carbide (SiC) constitutes a complex blanket structures which potentially causes special flow phenomena. In the present work, the characteristics of fluid flow and heat transfer in the DCLL blanket channel are investigated for the first wall (FW) sprayed a layer of no-wetting nano coating (NWNC) on its inner surface. The results show that the pressure drop with NWNC wall is oneorder magnitude lower than that with FCI in the general DCLL blanket. The Nusselt number on the NWNC wall is about half of that on the general wall. On this basis, a heat transfer criterion equation of DCLL channel is achieved for the NWNC wall without FCI. The results are compared with that criterion equation of general wall conditions, which indicates the criterion equation can well predict the convection heat transfer of DCLL channel.

Conjugate Heat Transfer Analysis of an Ultrasonic Molten Metal Treatment System

In piezoceramic ultrasonic devices,the piezoceramic stacks may fail permanently or function improperly if their working temperatures overstep the Curie temperature of the piezoceramic material.While the end of the horn usually serves near the melting point of the molten metal and is enclosed in an airtight chamber,so that it is difficult to experimentally measure the temperature of the transducer and its variation with time,which bring heavy difficulty to the design of the ultrasonic molten metal treatment system.To find a way out,conjugate heat transfer analysis of an ultrasonic molten metal treatment system is performed with coupled fluid and heat transfer finite element method.In modeling of the system,the RNG model and the SIMPLE algorithm are adopted for turbulence and nonlinear coupling between the momentum equation and the energy equation.Forced air cooling as well as natural air cooling is analyzed to compare the difference of temperature evolution.Numerical results show that,after about 350 s of working time,temperatures in the surface of the ceramic stacks in forced air cooling drop about 7 K compared with that in natural cooling.At 240 s,The molten metal surface emits heat radiation with a maximum rate of about 19 036 W/m2,while the heat insulation disc absorbs heat radiation at a maximum rate of about 7922 W/m2,which indicates the effectiveness of heat insulation of the asbestos pad.Transient heat transfer film coefficient and its distribution,which are difficult to be measured experimentally are also obtained through numerical simulation.At 240 s,the heat transfer film coefficient in the surface of the transducer ranges from–17.86 to 20.17 W/（m2？K）.Compared with the trial and error method based on the test,the proposed research provides a more effective way in the design and analysis of the temperature control of the molten metal treatment system.

Different efficiency toward the biomimetic aerobic oxidation of benzyl alcohol in microchannel and bubble column reactors: Hydrodynamic characteristics and gas–liquid mass transfer

The selective aerobic oxidation of benzyl alcohol to benzaldehyde has attracted considerable attention because benzaldehyde is a high value-added product. The rate of this typical gas–liquid reaction is significantly affected by mass transfer. In this study, CoTPP-mediated(CoTPP: cobalt(II) mesotetraphenylporphyrin) selective benzyl alcohol oxidation with oxygen was conducted in a membrane microchannel(MMC) reactor and a bubble column(BC) reactor, respectively. We observed that 83% benzyl alcohol was converted within 6.5 min in the MMC reactor, but only less than 10% benzyl alcohol was converted in the BC reactor. Hydrodynamic characteristics and gas–liquid mass transfer performances were compared for the MMC and BC reactors. The MMC reactor was assumed to be a plug flow reactor,and the dimensionless variance was 0.29. Compared to the BC reactor, the gas–liquid mass transfer was intensified significantly in MMC reactor. It could be ascribed to the high gas holdup(2.9 times higher than that of BC reactor), liquid film mass transfer coefficient(8.2 times higher than that of BC reactor), and mass transfer coefficient per unit interfacial area(3.8 times higher than that of BC reactor). Moreover,the Hatta number for the MMC reactor reached up to 0.61, which was about 15 times higher than that of the BC reactor. The computational fluid dynamics calculations for mass fractions in both liquid and gas phases were consistent with the experimental data.

Numerical investigation of turbulent mass transfer processes in turbulent fluidized bed by computational mass transfer

Turbulent fluidized bed possesses a distinct advantage over bubbling fluidized bed in high solids contact efficiency and thus exerts great potential in applications to many industrial processes.Simulation for fluidization of fluid catalytic cracking(FCC)particles and the catalytic reaction of ozone decomposition in turbulent fluidized bed is conducted using the EulerianeEulerian approach,where the recently developed two-equation turbulent(TET)model is introduced to describe the turbulent mass diffusion.The energy minimization multi-scale(EMMS)drag model and the kinetic theory of granular flow(KTGF)are adopted to describe gaseparticles interaction and particleeparticle interaction respectively.The TET model features the rigorous closure for the turbulent mass transfer equations and thus enables more reliable simulation.With this model,distributions of ozone concentration and gaseparticles two-phase velocity as well as volume fraction are obtained and compared against experimental data.The average absolute relative deviation for the simulated ozone concentration is 9.67%which confirms the validity of the proposed model.Moreover,it is found that the transition velocity from bubbling fluidization to turbulent fluidization for FCC particles is about 0.5 m$se1 which is consistent with experimental observation.

SOLVING 2-D NONLINEAR COUPLED HEAT AND MOISTURE TRANSFER PROBLEMS VIA A SELF-ADAPTIVE PRECISE ALGORITHM IN TIME DOMAIN

A self-adaptive precise algorithm in the time domain was employed to solve 2-D nonlinear coupled heat and moisture transfer problems. By expanding variables at a discretized time interval, the variations of variables can be described more precisely,and a nonlinear coupled initial and boundary value problem was converted into a series of recurrent linear boundary value problems which are solved by FE technique. In the computation, no additional assumption and the nonlinear iteration are required, and a criterion for self-adaptive computation is proposed to maintain sufficient computing accuracy for the change sizes of time steps. In the numerical comparison, the variations of material properties with temperature, moisture content, and both temperature and moisture content are taken into account, respectively. Satisfactory results have been obtained, indicating that the proposed approach is capable of dealing with complex nonlinear problems.