Microstructure and Thermal Physical Parameters of Ni60-Cr_3C_2 Composite Coating by Laser Cladding

To satisfy performance and long life requirements for hot forging die,Ni60-Cr3C2 composite coatings were prepared on the high-speed steel W6Mo5Cr4V2 using laser cladding technology.Laser clad coatings with different ratios of Ni60：Cr3C2 were investigated by scanning electron microscopy（SEM）,X-ray diffraction（XRD）,energy-dispersive X-ray analysis（EDX） and micro-hardness tester,respectively.Specific heat capacity and thermal conductivity were measured by Laser Thermal Constant Meter.Thermal expansion coefficient and elastic modulus were measured by Dynamic Mechanical Thermal Analyzer and Electro-Hydraulic Servocontrolled Testing System,respectively.The results indicated that Ni60＋50wt% Cr3C2 composite coating had dense and homogeneous structure,as well as a metallurgical bonding with the substrate.With the increase of Cr3C2 content,volume of chromium-containing compounds in the composite coating increased,microhardness increased and microstructure refined.The thermal physical parameters results showed that Ni60＋50wt% Cr3C2 composite coating was overall worse than W6Mo5Cr4V2,but had a higher hot yield strength to alleviate hot fatigue and surface hot wear of hot forging die during hot forging and thus improve the service life of hot forging die.

Simulations of the Dependence of Gas Physical Parameters on Deposition Variables during HFCVD Diamond Films

During the growth of the hot filament chemical vapor deposition （HFCVD） diamond films, numerical simulations in a 2-D mathematical model were employed to investigate the influence of various deposition parameters on the gas physical parameters, including the temperature, velocity and volume density of gas. It was found that, even in the case of optimized deposition parameters, the space distributions of gas parameters were heterogeneous due primarily to the thermal blockage come from the hot filaments and cryogenic pump effect arisen from the cold reactor wall. The distribution of volume density agreed well with the thermal round-flow phenomenon, one of the key obstacles to obtaining high growth rate in HFCVD process. In virtue of isothermal boundary with high temperature or adiabatic boundary condition of reactor wall, however, the thermal roundflow was profoundly reduced and as a consequence, the uniformity of gas physical parameters was considerably improved, as identified by the experimental films growth.

Influence of physical parameters on the collapse of a spherical bubble

This paper examines the influence of physical parameters on the collapse dynamics of a spherical bubble filled with diatomic gas(κ=7/5).The problem is formulated by the Rayleigh–Plesset dynamical equation,whose numerical solutions are carried out by Maple.Our studies show that each physical parameter affects the bubble collapse dynamics in different degree,which reveals that bubble collapse dynamics must considers all the parameters including liquid viscosity,surface tension,etc,else the outcome cannot be trusted.

Correlation Analysis of Processing Technology,Physical Parameters and Chemical Components during Plain Stir-baking of Trichosanthis Radix

[Objectives]To explore the correlation of processing technology,physical parameters and chemical components during plain stir-baking of Trichosanthis Radix.[Methods]Based on mixture uniform experiment design,the Trichosanthis Radix was prepared by plain stir-bake method.Delphi method was used to evaluate and select the highest-scoring processed product for measuring physical parameters.UV spectrophotometry was used to determine the contents of starch and polysaccharide.The correlation and linear regression model of processing technology,physical parameters and chemical components were established with the aid of SPSS 26.0[Results]After processing by plain stir-bake method,the relative density and chromaticity showed a decreasing trend in the processed products of Trichosanthis Radix,the oxidation value,hydroscopic rate and swelling decreased firstly and then increased,and pH increased firstly and then decreased.The content of total starch decreased,the content of polysaccharide increased,and there was a negative correlation between them.There was a significant positive correlation between temperature and oxidation value,swelling and hydroscopic rate,hydroscopic rate and polysaccharide,and there was a significant negative correlation between relative density and hydroscopic rate or polysaccharide,total starch and hydroscopic rate or swelling.The linear relation model between processing technology and physical parameters and chemical components was r2>0.9.[Conclusions]After processing by plain stir-bake method,the physical parameters of Trichosanthis Radix changed,and there may be mutual conversion between total starch and polysaccharides.To a certain extent,physical parameters can be used to evaluate the quality of processed products of Trichosanthis Radix.This study is expected to provide a reference for research on quality evaluation of processed products of traditional Chinese medicine.

Effects of Seasonal Variations in Physical Parameters on Quality of Gravity Flow Water in Kyanamira Sub-County, Kabale District, Uganda

The effect of seasonal variations in physical parameters on quality of gravity flow water was investigated in Kyanamira Sub-County, Kabale District, Uganda. The seasonal variations in the physical parameters (pH, temperature, electrical conductivity (EC), turbidity, colour, total dissolved solids (TDS), and total suspended solids (TSS)) were determined during wet and dry seasons. Composite samples from gravity flow water sources were collected monthly from March to August, 2014 and then analyzed. Temperature was measured using thermometer;pH, EC and TDS were determined using a multimeter, turbidity, colour and total suspended solids were determined by spectrophotometric method. TDS, pH and temperature were the most contributing parameters to water quality variations in both seasons. The mean pH values varied between 3.78 - 4.84 from March to August, 2014 at all study sites. These pH values were consistently below the WHO permissible range of 6.5 - 8.5. Similarly, total suspended solids varied between 0.66 - 2.17 mg·L-1 and were well above the recommended WHO limit of zero mg·L-1 at all study sites. Turbidity mean values varied between 0.83 - 3.7 NTU and were outside the recommended limits of 3 NTU at Kigata (3.7 NTU) only. Temperatures (20.3°C - 21.15°C) for all the study sites were within the recommended limit of 20°C - 30°C in water for domestic purposes. The mean values of physical parameters for the wet season were: temperature (21.12°C), colour (12.5 PtCoU), turbidity (3.4 NTU), TDS (76.76 mg·L-1), TSS (2.13 mg·L-1), pH (4.19) and EC (152.7 μS·cm-1) were different from those of the dry season (temperature (20.99°C), colour (0.93 PtCoU), turbidity (0.53 NTU), TDS (77.33 mg·L-1), TSS (0.67 mg·L-1), pH (4.86) and EC (158.65 μS·cm-1). Basing on these findings above, it was evident to justify discouraging the use of gravity flow water at these study sites for domestic purposes without proper treatment.

MEASUREMENT AND APPLICATION OF PHYSICAL PARAMETERSIN UNSTEADY HEAT CONDUCTION

As far as the accuracy of calculating unsteady temperature field is concerned, it is very important to find the accurate physical parameters such as specific heat, thermal conductivity, latent heat of phase transformation and surface heat flux. The model for calculating H and Q is established in this paper. The measurement methods and data processing for physical parameters such as volume specific heat C, thermal conductivity k, volume latent heat of phase transformation c1 and surface heat flux are introduced The physical parameters of 1Cr18Ni9Ti and 45 steels and the surface heat flux for 1 Cr18Ni9Ti probe cooled in water,10% NaCl water and oil with different temperatures are measured, respectively. These data show that the probability of absolute error less than 2* C between the calculated and measured values in temperature field calculation reaches above 80% if using the above physical parameters, which provides a reliable technology basis for precise calculation of temperature field.

Calculation of thermal physical parameters of dissociated air by the dissociation degree method

The high temperature gas occurs behind shock or near the wall surface of vehicle in the hypersonic flight. As the temperature exceeds 2 000 K, 4 000 K, respectively, O2 and N2 molecules are successively dissociated. Because of variable components at dif- ferent temperatures and pressures, the dissociated air is no longer a perfect gas, In this paper, a new method is developed to calculate accurate thermal physical parameters with the dissociation degree providing the thermochemical equilibrium procedure. Based on the dissociation degree, it is concluded that few numbers of equations and the solutions are easily obtained. In addition, a set of formulas relating the parameter to the dissociation degree are set up four-species, O2 molecule The thermodynamic properties of dissociated air containing and N2 molecule, O atom and N atom, are studied with the new method, and the results are consistent with those with the traditional equilibrium constant method. It is shown that this method is reliable for solving thermal physical parameters easily and directly.

Nonlinear simultaneous inversion of pore structure and physical parameters based on elastic impedance

Carbonate reservoirs have complex pore structures,which not only significantly affect the elastic properties and seismic responses of the reservoirs but also affect the accuracy of the prediction of the physical parameters.The existing rockphysics inversion methods are mainly designed for clastic rocks,and the inversion objects are generally porosity and water saturation.The data used are primarily based on the elastic parameters,and the inversion methods are mainly linear approximations.To date,there has been a lack of a simultaneous pore structure and physical parameter inversion method for carbonate reservoirs.To solve these problems,a new Bayesian nonlinear simultaneous inversion method based on elastic impedance is proposed.This method integrates the differential effective medium model of multiple-porosity rocks,Gassmann equation,Amplitude Versus Offset(AVO)theory,Bayesian theory,and a nonlinear inversion algorithm to achieve the simultaneous quantitative prediction of the pore structure and physical parameters of complex porous reservoirs.The forward modeling indicates that the contribution of the pore structure,i.e.,the pore aspect ratio,to the AVO response and elastic impedance is second only to that of porosity and is far greater than that of water saturation.The application to real data shows that the new inversion method for determining the pore structure and physical parameters directly from pre-stack data can accurately predict a reservoir's porosity and water saturation and can evaluate the pore structure of the effective reservoir.

Correlation between the physical parameters and the electrochemical performance of a silicon anode in lithium-ion batteries

Lithium-ion battery anode used as silicon particles were obtained from different major suppliers,and they were characterized by different spectroscopic techniques and evaluated by electrochemical experiments.Correlations between the key physical parameters and electrochemical properties of the silicon particles were investigated.Silicon particle size,surface oxygen content,-OH content and physical appearance are found to strongly influence the electrochemical properties of the Si anode.The particle size of 100 nm has great promise for the practical application of Si nanoparticles in the lithium-ion battery industry.An inverse correlation between the oxygen content and the reversible capacity or first coulombic efficiency was obtained.The-OH content by surface treatment contributes to enhanced cycling stability by the improved affinity between the Si particle and the water-soluble binder.Spherical Si particles perform better compared to irregular particles,and agglomeration dramatically decreases the cycling stability of the Si anode.Among the investigated Si particles,the sample that exhibited a reversible capacity of more than 2500 mAh g^(-1),a first coulombic efficiency of 89.26%and an excellent cycling stability,has great potential for use in the battery industry.

Seabed Physical Parameter Research Based on Active-Source OBS Data in the Chukchi Sea Shelf of the Arctic

The acquisition of seabed physical parameters is one of the focuses of marine acoustic researches.However,the activesource ocean bottom seismometer(OBS)detection method in the marine geophysical research is rarely used to acquire seabed physical parameters,and less work is performed in the Arctic.In this study,two active-source OBS data collected from the 9th and 11th Chinese National Arctic Research Expedition(CHINARE)are selected to obtain the physical parameters of seabed sediments.Two kinds of energy spark are used as the active sources,while the cost function inversion method is used based on the arrival time difference between the reflected and direct waves.The thickness and sound velocity of the sediment layers are obtained by inversion,and the empirical formula is used to calculate the physical parameters of the seabed sediment,which are compared with the measured results.The cost function inversion method based on the time difference of arrival of the reflected and direct waves is tested to be effective and feasible in the inversion of seabed parameters from active-source OBS data.The method is further applied to obtain the physical parameters of Chukchi seabed sediments,which provides the idea and reference for the application of marine geophysical activesource OBS detection technology in the inversion of polar seabed physical parameters.

Intelligent direct analysis of physical and mechanical parameters of tunnel surrounding rock based on adaptive immunity algorithm and BP neural network

Because of complexity and non-predictability of the tunnel surrounding rock, the problem with the determination of the physical and mechanical parameters of the surrounding rock has become a main obstacle to theoretical research and numerical analysis in tunnel engineering. During design, it is a frequent practice, therefore, to give recommended values by analog based on experience. It is a key point in current research to make use of the displacement back analytic method to comparatively accurately determine the parameters of the surrounding rock whereas artificial intelligence possesses an exceptionally strong capability of identifying, expressing and coping with such complex non-linear relationships. The parameters can be verified by searching the optimal network structure, using back analysis on measured data to search optimal parameters and performing direct computation of the obtained results. In the current paper, the direct analysis is performed with the biological emulation system and the software of Fast Lagrangian Analysis of Continua (FLAC3D. The high non-linearity, network reasoning and coupling ability of the neural network are employed. The output vector required of the training of the neural network is obtained with the numerical analysis software. And the overall space search is conducted by employing the Adaptive Immunity Algorithm. As a result, we are able to avoid the shortcoming that multiple parameters and optimized parameters are easy to fall into a local extremum. At the same time, the computing speed and efficiency are increased as well. Further, in the paper satisfactory conclusions are arrived at through the intelligent direct-back analysis on the monitored and measured data at the Erdaoya tunneling project. The results show that the physical and mechanical parameters obtained by the intelligent direct-back analysis proposed in the current paper have effectively improved the recommended values in the original prospecting data. This is of practical significance to the appraisal of stability and informationization design of the surrounding rock.

Effect of atmospheric pressure on physical parameters of steels and solidification conditions during PESR process:a review

The pressurized electroslag remelting(PESR)process has a remarkable impact on manufacturing high nitrogen steels,which can alter the physical parameters of steels and solidification conditions at different atmospheric pressures.The principle and applications of the PESR process are reviewed.The effect of atmospheric pressure,including Gibbs free energy,nitrogen solubility,melting point,viscosity,diffusion coefficient,partition coefficient,and nucleation rate,is explicitly expressed by empirical knowledge and quantified by thermodynamic relationships.The variation of interfacial heat transfer coefficient is discussed at different atmospheric pressures.Furthermore,the effect of atmospheric pressure on physical parameters of steels and solidification conditions during the PESR process is still in their embryonic research stage and it is important to do further study in this research field.Finally,a general concluding remark and suggestions for future development are proposed.

Comprehensive insights into recent innovations:Magnesium-inclusive high-entropy alloys

This review focuses on thermodynamic and physical parameters,synthesis methods,and reported phases of Magnesium(Mg)containing high-entropy alloys(HEAs).Statistical data of publications concerning Mg-containing HEAs were collected and analyzed.Data on the chemical elements included in Mg-containing HEAs,their theoretical end experimental densities,thermodynamic parameters,physical parameters,fabricated techniques and reported phases were also collected and discussed.On the basis of this information,a new classification for HEAs was proposed.It is also shown that the existing thermodynamic parameters cannot accurately predict the formation of a single phase solid solution for Mg-containing HEAs.The physical parameters of Mg-containing HEAs are within a wide range,and most of the synthesized Mg-containing HEAs have a complex multiphase structure.

Total ionizing dose effect modeling method for CMOS digital-integrated circuit

Simulating the total ionizing dose(TID)of an electrical system using transistor-level models can be difficult and expensive,particularly for digital-integrated circuits(ICs).In this study,a method for modeling TID effects in complementary metaloxide semiconductor(CMOS)digital ICs based on the input/output buffer information specification(IBIS)was proposed.The digital IC was first divided into three parts based on its internal structure:the input buffer,output buffer,and functional area.Each of these three parts was separately modeled.Using the IBIS model,the transistor V-I characteristic curves of the buffers were processed,and the physical parameters were extracted and modeled using VHDL-AMS.In the functional area,logic functions were modeled in VHDL according to the data sheet.A golden digital IC model was developed by combining the input buffer,output buffer,and functional area models.Furthermore,the golden ratio was reconstructed based on TID experimental data,enabling the assessment of TID effects on the threshold voltage,carrier mobility,and time series of the digital IC.TID experiments were conducted using a CMOS non-inverting multiplexer,NC7SZ157,and the results were compared with the simulation results,which showed that the relative errors were less than 2%at each dose point.This confirms the practicality and accuracy of the proposed modeling method.The TID effect model for digital ICs developed using this modeling technique includes both the logical function of the IC and changes in electrical properties and functional degradation impacted by TID,which has potential applications in the design of radiation-hardening tolerance in digital ICs.

Physical Characteristics and the Effect of Boiling and Fermentation on the Nutritional Value of <i>Telfairia occidentalis</i>Seeds

This work evaluates some physical parameters (the weight, length, diameter of fruits and seeds, number of seeds per fruit) and the effect of boiling and fermentation on the nutritional value of Telfairia occidentalis (fluted pumpkin) seeds. Firstly, a survey was done in the city of Yaounde on the different treatments applied to the seeds before cooking. From the results of the survey, the seeds were divided into three groups: raw, boiled and fermented. The moisture, lipid, protein, fibre, carbohydrate and ash contents were analysed using AOAC methods and minerals by atomic absorption spectrophotometry. The results showed that T. occidentalis fruit averagely weighed 6.35 kg and contained about 90 seeds. The decorticated seeds had an ovoid shape, 3.70 cm long and weighed 8.91 g. Boiling led to an increase in lipid (16.29% - 31.44%) and carbohydrate (19.20% - 21.8%) but a decrease in protein (54.06% - 34.17%) contents. Fermentation increased the crude fibre (0.70% - 1.1%) but decreased the ash content (4.07% - 3.14% DM). Boiled seeds had higher calcium, magnesium, potassium and sodium, while fermented seeds had higher zinc levels. Boiling proved better in preserving most of the seed nutrients. These seeds could be used to prevent some mineral deficiencies and their high proteins suggest their potential for the formulation of infant foods.

Effects of physical parameter range on dimensionless variable sensitivity in water flooding reservoirs

The similarity criterion for water flooding reservoir flows is concerned with in the present paper. When finding out all the dimensionless variables governing this kind of flow, their physical meanings are subsequently elucidated. Then, a numerical approach of sensitivity analysis is adopted to quantify their corresponding dominance degree among the similarity parameters. In this way, we may finally identify major scaling law in different parameter range and demonstrate the respective effects of viscosity, permeability and injection rate.

Structural physical parameter identification based on evolutionary-simplex algorithm and structural dynamic response

Evolutionary computation based on the idea of biologic evolution is one type of global optimization algorithm that uses self-adaptation,self-organization and random searching to solve optimization problems.The evolutionary-simplex algorithm is introduced in this paper.It contains floating encoding which combines the evolutionary computation and the simplex algorithm to overcome the problems encountered in the genetic algorithm and evolutionary strategy methods. Numerical experiments are performed using seven typical functions to verify the algorithm.An inverse analysis method to identify structural physical parameters based on incomplete dynamic responses obtained from the analysis in the time domain is presented by using the evolutionary-simplex algorithm.The modal evolutionary-simplex algorithm converted from the time domain to the modal domain is proposed to improve the inverse efficiency.Numerical calculations for a 50-DOF system show that when compared with other methods,the evolutionary-simplex algorithm offers advantages of high precision, efficient searching ability,strong ability to resist noise,independence of initial value,and good adaptation to incomplete information conditions.

Physical Parameter Identification Method Based on Modal Analysis for Two-axis On-road Vehicles:Theory and Simulation

Physical parameters are very important for vehicle dynamic modeling and analysis.However,most of physical parameter identification methods are assuming some physical parameters of vehicle are known,and the other unknown parameters can be identified.In order to identify physical parameters of vehicle in the case that all physical parameters are unknown,a methodology based on the State Variable Method（SVM） for physical parameter identification of two-axis on-road vehicle is presented.The modal parameters of the vehicle are identified by the SVM,furthermore,the physical parameters of the vehicle are estimated by least squares method.In numerical simulations,physical parameters of Ford Granada are chosen as parameters of vehicle model,and half-sine bump function is chosen to simulate tire stimulated by impulse excitation.The first numerical simulation shows that the present method can identify all of the physical parameters and the largest absolute value of percentage error of the identified physical parameter is 0.205%;and the effect of the errors of additional mass,structural parameter and measurement noise are discussed in the following simulations,the results shows that when signal contains 30 d B noise,the largest absolute value of percentage error of the identification is 3.78%.These simulations verify that the presented method is effective and accurate for physical parameter identification of two-axis on-road vehicles.The proposed methodology can identify all physical parameters of 7-DOF vehicle model by using free-decay responses of vehicle without need to assume some physical parameters are known.

Influence of Structure Parameters on Performance of the Thermoelectric Module

A numerical model of thermoelectric module （TEM） is created by academic analysis,and the impacts of the resistance ratio and thermoelement size on the output power and thermoelectric efficiency of the TEM are analyzed by the MATLAB numerical calculation.The numerical model is validated by the ANSYS thermal,electrical,and structural coupling simulation.The effects of the variable physical property parameters and contact effect on the output power and thermoelectric efficiency are evaluated,and the concept of aspect ratio optimal domain is proposed,which provides a new design approach for the TEM.

A New Sensitivity Analysis Approach Using Conditional Nonlinear Optimal Perturbations and Its Preliminary Application

Simulations and predictions using numerical models show considerable uncertainties,and parameter uncertainty is one of the most important sources.It is impractical to improve the simulation and prediction abilities by reducing the uncertainties of all parameters.Therefore,identifying the sensitive parameters or parameter combinations is crucial.This study proposes a novel approach:conditional nonlinear optimal perturbations sensitivity analysis(CNOPSA)method.The CNOPSA method fully considers the nonlinear synergistic effects of parameters in the whole parameter space and quantitatively estimates the maximum effects of parameter uncertainties,prone to extreme events.Results of the analytical g-function test indicate that the CNOPSA method can effectively identify the sensitivity of variables.Numerical results of the theoretical five-variable grassland ecosystem model show that the maximum influence of the simulated wilted biomass caused by parameter uncertainty can be estimated and computed by employing the CNOPSA method.The identified sensitive parameters can easily change the simulation or prediction of the wilted biomass,which affects the transformation of the grassland state in the grassland ecosystem.The variance-based approach may underestimate the parameter sensitivity because it only considers the influence of limited parameter samples from a statistical view.This study verifies that the CNOPSA method is effective and feasible for exploring the important and sensitive physical parameters or parameter combinations in numerical models.