Sterilization Effect of Cooking Process for Guilin Rice Noodles Based on Heat Conduction Model

Guilin rice noodles, a unique cuisine from Guilin, Guangxi, is renowned both domestically and internationally as one of the top ten “Guilin Classics”. Utilizing a heat conduction model, this study explores the effectiveness of the cooking process in sterilizing Guilin rice noodles before consumption. The model assumes that a large pot is filled with boiling water which is maintained at a constant high temperature heat resource through continuous gentle heating. And the room temperature is set as the initial temperature for the preheating process and the final temperature for the cooling process. The objective is to assess whether the cooking process achieves satisfactory sterilization results. The temperature distribution function of rice noodle with time is analytically obtained using the separation of variables method in the three-dimensional cylindrical coordinate system. Meanwhile, the thermal diffusion coefficient of Guilin rice noodles is obtained in terms of Riedel’ theory. By analyzing the elimination characteristics of Pseudomonas cocovenenans subsp. farinofermentans, this study obtains the optimal time required for effective sterilization at the core of Guilin rice noodles. The results show that the potential Pseudomonas cocovenenans subsp. farinofermentans will be completely eliminated through continuously preheating more than 31 seconds during the cooking process before consumption. This study provides a valuable reference of food safety standards in the cooking process of Guilin rice noodles, particularly in ensuring the complete inactivation of potentially harmful strains such as Pseudomonas cocovenenans subsp. farinofermentans.

Fractal Prediction Model of Thermal Contact Conductance of Rough Surfaces

The thermal contact conductance problem is an important issue in studying the heat transfer of engineering surfaces, which has been widely studied since last few decades, and for predicting which many theoretical models have been established. However, the models which have been existed are lack of objectivity due to that they are mostly studied based on the statistical methodology characterization for rough surfaces and simple partition for the deformation formats of contact asperity. In this paper, a fractal prediction model is developed for the thermal contact conductance between two rough surfaces based on the rough surface being described by three-dimensional Weierstrass and Mandelbrot fractal function and assuming that there are three kinds of asperity deformation modes： elastic, elastoplastic and fully plastic. Influences of contact load and contact area as well as fractal parameters and material properties on the thermal contact conductance are investigated by using the presented model. The investigation results show that the thermal contact conductance increases with the increasing of the contact load and contact area. The larger the fractal dimension, or the smaller the fractal roughness, the larger the thermal contact conductance is. The thermal contact conductance increases with decreasing the ratio of Young＇s elastic modulus to the microhardness. The results obtained indicate that the proposed model can effectively predict the thermal contact conductance at the interface, which provide certain reference to the further study on the issue of heat transfer between contact surfaces.

Thermal conductivity model of filled polymer composites

Theoretical and empirical models for predicting the thermal conductivity of polymer composites were summarized since the 1920s.The effects of particle shape,filler amount,dispersion state of fillers,and interfacial thermal barrier on the thermal conductivity of filled polymer composites were investigated,and the agreement of experimental data with theoretical models in literatures was discussed.Silica with high thermal conductivity was chosen to mix with polyvinyl-acetate （EVA） copolymer to prepare SiO2/EVA co-films.Experimental data of the co-films＇ thermal conductivity were compared with some classical theoretical and empirical models.The results show that Agari＇s model,the mixed model,and the percolation model can predict well the thermal conductivity of SiO2/EVA co-films.

A prediction model for the effective thermal conductivity of nanofluids considering agglomeration and the radial distribution function of nanoparticles

Conventional heat transfer fluids usually have low thermal conductivity, limiting their efficiency in many applications. Many experiments have shown that adding nanosize solid particles to conventional fluids can greatly enhance their thermal conductivity. To explain this anomalous phenomenon, many theoretical investigations have been conducted in recent years. Some of this research has indicated that the particle agglomeration effect that commonly occurs in nanofluids should play an important role in such enhancement of the thermal conductivity, while some have shown that the enhancement of the effective thermal conductivity might be accounted for by the structure of nanofluids, which can be described using the radial distribution function of particles. However, theoretical predictions from these studies are not in very good agreement with experimental results. This paper proposes a prediction model for the effective thermal conductivity of nanofluids, considering both the agglomeration effect and the radial distribution function of nanoparticles. The resulting theoretical predictions for several sets of nanofluids are highly consistent with experimental data.

Electrical-hydraulic conductivity model for a weatheredfractured aquifer system of Olbanita, Lower Baringo Basin, Kenya Rift

Groundwater yield in the Kenya Rift is highly unsustainable owing to geological variability.In this study,field hydraulic characterization was performed by using geoelectric approaches.The relations between electrical-hydraulic(eh)conductivities were modeled hypothetically and calibrated empirically.Correlations were based on the stochastic models and field-scale hydraulic parameters were contingent on pore-level parameters.By considering variation in pore-size distributions over eh conduction interval,the relations were scaled-up for use at aquifer-level.Material-level electrical conductivities were determined by using Vertical Electrical Survey and hydraulic conductivities by analyzing aquifer tests of eight boreholes in the Olbanita aquifer located in Kenya rift.VES datasets were inverted by using the computer code IP2Win.The main result is that ln T=0.537(ln Fa)+3.695;the positive gradient indicating eh conduction through pore-surface networks and a proxy of weathered and clayey materials.An inverse(1/F-K)correlation is observed.Hydraulic parameters determined using such approaches may possibly contribute significantly towards sustainable yield management and planning of groundwater resources.

Thermal conductivity modeling of water containing metal oxide nanoparticles

The nano particles have demonstrated great potential to improve the heat transfer characteristics of heat transfer fluids.Possible parameters responsible for this increase were studied. The heat transfer profile in the nanolayer region was combined with other parameters such as volume fraction, particle radius thermal conductivity of the fluid, particle and nanolayer, to formulate a thermal conductivity model. Results predicting the thermal conductivity of nanofluids using the model were compared with experimental results as well as studies by other researchers. The comparison of the results obtained for the Cu O/water and Ti O2/water nanofluids studied shows that the correlation proposed is in closest proximity in predicting the experimental results for the thermal conductivity of a nanofluid. Also, a parametric study was performed to understand how a number of factors affect the thermal conductivity of nanofluids using the developed correlation.

Hybrid graded element model for transient heat conduction in functionally graded materials

This paper presents a hybrid graded element model for the transient heat conduction problem in functionally graded materials （FGMs）. First, a Laplace transform approach is used to handle the time variable. Then, a fundamental solution in Laplace space for FGMs is constructed. Next, a hybrid graded element is formulated based on the obtained fundamental solution and a frame field. As a result, the graded properties of FGMs are naturally reflected by using the fundamental solution to interpolate the intra-element field. Further, Stefest＇s algorithm is employed to convert the results in Laplace space back into the time-space domain. Finally, the performance of the proposed method is assessed by several benchmark examples. The results demonstrate well the efficiency and accuracy of the proposed method.

A New Modified Conductivity Model for Prediction of Shear Yield Stress of Electrorheological Fluids Based on Face-center Square Structure

A new modified conductivity model was established to predict the shear yield stress of electrorheological fluids (ERF). By using a cell equivalent method, the present model can deal with the face-center square structure of ERF. Combining the scheme of the classical conductivity model for the single-chain structure, a new formula for the prediction of the shear yield stress of ERF was set up. The influences of the separation distance of the particles, the volume fraction of the particles and the applied electric field on the shear yield stress were investigated.

Forecasting conductivities of LiBOB-EC/DEC electrolytes by the mass triangle model

Conductivities of lithium bis（oxalato）borate （LiBOB）-ethyl carbonate （EC）/diethyl carbonaten （DEC） electrolytes at 25℃ and 50℃ were studied. The electrolyte component with the highest conductivity at each temperature was obtained through changing the concentration of LiBOB and the ratio of EC/DEC. The mass triangle model was applied to calculate the conductivity of Li- BOB-EC/DEC ternary system at 25℃ and 50℃. The results show that the calculated and experimental results have reached a good agreement. Therefore, it is expected that the experimental work can be vastly reduced by introducing the mass triangle model.

Modeling and Dynamic Analysis of Fractional-Order Buck Converter in Continuous Conduction Mode

According to the fact that the actual inductor and actual capacitor are fractional, the mathematical and state-space averaging models of fractional order Buck converters in continuous conduction mode(CCM) are constructed by using fractional calculus theory. Firstly, the parameter conditions that ensure that the converter working in CCM is given and transfer functions are derived. Also, the inductor current and the output voltage are analyzed. Then the difference between the mathematical model and the circuit model are analyzed, and the effect of fractional order is studied by comparing the integer order with fractional order model. Finally, the dynamic behavior of the current-controlled Buck converter is investigated. Simulation experiments are achieved via the use of Matlab/Simulink. The experimental results verify the correctness of theoretical analysis, the order should be taken as a significant parameter. When the order is taken as a bifurcation parameter, the dynamic behavior of the converter will be affected and bifurcation points will be changed as order varies.

Modeling of thermal conductivity and density of alumina/silica in water hybrid nanocolloid by the application of Artificial Neural Networks

In this research work, the thermal conductivity and density of alumina/silica(Al_2O_3/SiO_2) in water hybrid nanofluids at different temperatures and volume concentrations have been modeled using the artificial neural networks(ANN). The nanocolloid involved in the study was synthesized by the two-step method and characterized by XRD, TEM, SEM–EDX and zeta potential analysis. The properties of the synthesized nanofluid were measured at various volume concentrations(0.05%, 0.1% and 0.2%) and temperatures(20 to 60 °C). Established on the observational data and ANN, the optimum neural structure was suggested for predicting the thermal conductivity and density of the hybrid nanofluid as a function of temperature and solid volume concentrations. The results indicate that a neural network with 2 hidden layers and 10 neurons have the lowest error and a highest fitting coefficient o thermal conductivity, whereas in the case of density, the structure with 1 hidden layer consisting of 4 neurons proved to be the optimal structure.

A composite sphere assemblage model for porous oolitic rocks:Application to thermal conductivity

The present work is devoted to the determination of linear effective thermal conductivity of porous rocks characterized by an assemblage of grains(oolites) coated by a matrix. Two distinct classes of pores, i.e.micropores or intra oolitic pores(oolite porosity) and mesopores or inter oolitic pores(inter oolite porosity), are taken into account. The overall porosity is supposed to be connected and decomposed into oolite porosity and matrix porosity. Within the framework of Hashin composite sphere assemblage(CSA)models, a two-step homogenization method is developed. At the first homogenization step, pores are assembled into two layers by using self-consistent scheme(SCS). At the second step, the two porous layers constituting the oolites and the matrix are assembled by using generalized self-consistent scheme(GSCS) and referred to as three-phase model. Numerical results are presented for data representative of a porous oolitic limestone. It is shown that the influence of porosity on the overall thermal conductivity of such materials may be significant.

Finite Element Modeling Of Low Heat Conducting Building Bricks

Heat conduction through conventional and interlocking building bricks with cavities was studied in this work. Heat transfer analysis was carried out using MATLAB? partial differential equation toolbox. Regular and staggered hole arrangements were studied. Results showed that four staggered holed interlocking bricks were effective in thermal resistance into the bricks and increasing the holes beyond four did not give any thermal resistance advantage. For the conventional bricks staggered holes did not give any thermal resistance advantage but the four-holed bricks were also adjudged to be effective in thermal resistance into the brick surface. Increasing the number of holes beyond four in conventional bricks did give some thermal resistivity advantage but very minimal. Structural strengths of holed bricks were not considered in this study.

INTERACTION MODELS FOR EFFECTIVE THERMAL AND ELECTRIC CONDUCTIVITIES OF CARBON NANOTUBE COMPOSITES

The present article provides supplementary information of previous works of analytic models for predicting conductivity enhancements of carbon nanotube composites. The models, though fairly simple, are able to take account of the effects of conductivity anisotropy, nonstraightness, and aspect ratio of the CNT additives on the conductivity enhancement of the composite and to give predictions agreeing well with existing experimental data. The omitted detailed derivation of this model is demonstrated in the present article with a more systematical analysis, which may help with further development in this direction. Furthermore, the effects of various orientation distributions of CNTs are reported here for the first time. The information may be useful in design or fabrication technology of CNT composites for better or specified conductivities.

MEASUREMENT METHOD AND PHYSICAL MODEL OF VSC CONDUCTIVITY AND ITS APPLICATIONS IN CONDUCTING POLYMERS

Method of VSC (Voltage Shorted Compaction)can be used to determine the intrinsic temperature dependence ofconductivity ofpolycrystalline compaction. The experimental conditions and technical key for preparation of VSC device and its physical model as well as its applications in conducting polymers are discussed in detail.

Three-dimensional magnetotelluric modeling in the spherical and Cartesian coordinate systems:A comparative study

With the increase in the coverage area of magnetotelluric data,three-dimensional magnetotelluric modeling in spherical coordinates and its differences with respect to traditional Cartesian modeling have gradually attracted attention.To fully understand the influence of the Earth’s curvature and map projection deformations on Cartesian modeling,qualitative and quantitative analyses based on realistic three-dimensional models need to be examined.Combined with five representative map projections,a type of model conversion method that transforms the original spherical electrical conductivity model to Cartesian coordinates is described in this study.The apparent resistivity differences between the spherical western United States electrical conductivity model and the corresponding five Cartesian models are then compared.The results show that the cylindrical equal distance map projection has the smallest error.A meridian convergence correction resulting from the deformation of the map projection is introduced to rotate the Cartesian impedance tensor from grid north to geographic north,which reduces differences from the spherical results.On the basis of the magnetotelluric field data,the applicability of the Cartesian coordinate system to western and contiguous United States models is quantitatively evaluated.Precise interpretations of the contiguous United States model were found to require spherical coordinates.

Multi-dimensional Simulation of Phase Change by a 0D-2D Model Coupling via Stefan Condition

Considering phase changes associated with a high-temperature molten material cooled down from the outside,this work presents an improvement of the modelling and the numerical simulation of such processes for an application pertaining to the safety of light water nuclear reactors.Postulating a core meltdown accident,the behaviour of the core melt(aka corium)into a steel vessel is of tremendous importance when evaluating the vessel integrity.Evaluating correctly the heat fluxes requires the numerical simulation of the interaction between the liquid material and its solid counterpart which forms during the solidification process,but also may melt back.To simulate this configuration,encoun-tered in various industrial applications,one considers a bi-phase model constituted by a liquid phase in contact and interaction with its solid phase.The liquid phase may solidify in presence of low energetic source,while the solid phase may melt due to an intense heat flux from the high-temperature liquid.In the frame of the in-house legacy code,several simplifying assumptions(0D multi-layer discretization,instantaneous heat transfer via a quadratic temperature profile in solids)are made for the modelling of such phase changes.In the present work,these shortcomings are illustrated and further overcome by solving a 2D heat conduction model in the solid by a mixed Raviart-Thomas finite element method coupled to the liquid phase due to heat and mass exchanges through Stefan condition.The liquid phase is modeled with a 0D multi-layer approach.The 0D-liquid and 2D-solid mod-els are coupled by a Stefan like phase change interface model.Several sanity checks are performed to assess the validity of the approach on 1D and 2D academical configurations for which exact or reference solutions are available.Then more advanced situations(genu-ine multi-dimensional phase changes and an"industrial-like scenario")are simulated to verify the appropriate behavior of the obtained coupled simulation scheme.

The Relationship of Sodium and Potassium Conductances with Dynamic States of a Mathematical Model of Electrosensory Pyramidal Neurons

Electrosensory pyramidal neurons in weakly electric fish can generate burst firing. Based on the Hodgkin-Huxley scheme, a previous study has developed a mathematical model that reproduces this burst firing. This model is called the ghostbursting model and is described by a system of non-linear ordinary differential equations. Although the dynamic state of this model is a quiescent state during low levels of electrical stimulation, an increase in the level of electrical stimulation transforms the dynamic state first into a repetitive spiking state and finally into a burst firing state. The present study performed computer simulation analysis of the ghostbursting model to evaluate the sensitivity of the three dynamic states of the model (i.e., the quiescent, repetitive spiking, and burst firing states) to variations in sodium and potassium conductance values of the model. The present numerical simulation analysis revealed the sensitivity of the electrical stimulation threshold required for eliciting the burst firing state to variations in the values of four ionic conductances (i.e., somatic sodium, dendritic sodium, somatic potassium, and dendritic potassium conductances) in the ghostbursting model.

Modeling of the Electrical Conductivity of Graphite Dispersions in Electrolytes

The electrical conductivity of graphite dispersions in potassium chloride (KCl) solutions in the alternating (1000 Hz) and constant electric field has been measured. In the alternating electric field (0.0005 - 0.01 М KCI) the electrical conductivity increases depending on the mass fraction of the dispersed phase. In the constant electrical conductivity (0.001 - 0.01 M KCl) the electrical conductivity changes slightly depending on the mass fraction of the dispersed phase (up to 15 % of the mass.). The electrical conductivity increases in case the dispersed phase contains 15% - 20% (mass.). In more concentrated solutions (0.1 M KCl) in the alternating and constant electric field the dependence of the electrical conductivity of the suspension decreased, and then it increased when the dispersed phase exceeded 15% - 20% (mass.). A model of the electrical conductivity of graphite dispersions in electrolytes is offered. The main contribution to the increase in the electrical conductivity in dilute electrolytes in the alternating electric field is made by the polarization of particles due to their surface conductivity. It is suggested that the aggregation of graphite particles occurs at dispersed phase concentrations of more than 15% - 20% (mass).

小麦叶片和冠层尺度气体交换模型关键参数的季节变化特征

本文从叶片和冠层尺度入手,采用手持式光合仪和涡动相关法,分析确定C3作物春小麦和冬小麦气体交换模型关键参数随季节变化的特征。结果表明:春小麦叶片尺度最大羧化速率和最大电子传递速率在生育末期快速减小,其他阶段差异不显著,但二者之比随发育期变化相对稳定,均值为2.2;春小麦生长季叶片气孔导度模型斜率在9~11间变动,均值为9.7。冬小麦冠层尺度最大羧化速率和最大电子传递速率随发育期呈抛物线变化,但二者之比相对稳定,均值为1.43;冬小麦冠层导度模型斜率在不同年份不同季节变化无明显规律,整个生育期围绕均值12波动。本研究论证了表征作物光合能力的参数随生育期变化以及气孔导度模型斜率相对稳定的特征。可为陆气相互作用过程分析以及生态系统碳—水循环模拟提供参数化依据。