Numerical Models and Methods of Atmospheric Parameters Originating in the Formation of the Earth’s Climatic Cycle

Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in2/s for humidity, 2.993 in2/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .

SOLVING THE VELOCITY PARAMETER OF THE 2-D WAVE INVERSE PROBLEMS WITH THE INTEGRATION-CHARACTERISTIC METHOD

For the 2-D wave inverse problems introduced from geophysical exploration, in this paper, the author presents integration-characteristic method to solve the velocity parameter, and then applies it to common shotpoint model data, in noise-free case. The accuracy is quite good.

Parameter Extraction for 2-π Equivalent Circuit Model of RF CMOS Spiral Inductors

A novel parameter extraction method with rational functions is presented for the 2-πequivalent circuit model of RF CMOS spiral inductors. The final S-parameters simulated by the circuit model closely match experimental data. The extraction strategy is straightforward and can be easily implemented as a CAD tool to model spiral inductors. The resulting circuit models will be very useful for RF circuit designers.

Parameter Optimization of Interval Type-2 Fuzzy Neural Networks Based on PSO and BBBC Methods

Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs.

Fault plane parameters of Tancheng M81/2 earthquake on the basis of present-day seismological data

The great Tancheng earthquake of M81/2 occurred in 1668 was the largest seismic event ever recorded in history in eastern China. This study determines the fault geometry of this earthquake by inverting seismological data of present-day moderate-small earthquakes in the focal area. We relocated those earthquakes with the double-difference method and found focal mechanism solutions using gird test method. The inversion results are as follows： the strike is 21.6°, the dip angle is 89.5°, the slip angle is 170°, the fault length is about 160 km, the lower-boundary depth is about 32 km and the buried depth of upper boundary is about 4 km. This shows that the seismic fault is a NNE-trending upright right-lateral strike-slip fault and has cut through the crust. Moreover, the surface seismic fault, intensity distribution of the earthquake, earthquake-depth distribution and seismic-wave velocity profile in the focal area all verified our study result.

Synthetically quantitative evaluation function of characteristic parameters on CO_2 arc welding process

The statistical probability and their variation regularity of the measurable characteristic parameters in the CO 2 arc welding droplet short circuiting transfer process have been studied. The statistical analysis shows that the sensitivity of each characteristic parameter with regard to the variation of the short circuiting transfer process is different. The sensitivity of 4 kinds among these characteristic parameters is more intense than that of the short circuiting transfer frequency. In order to take account of the synthetic influence of these characteristic parameters, by means of the characteristic parameters synthetic value, a quantitative evaluation function is built up to describe and evaluate the short circuiting transfer process of CO 2 arc welding in real time. The testing shows that the evaluation function can give a suitable synthetic valuation for the short circuiting transfer process with a variety of welding variables.

Unknown parameter’s variance-covariance propagation and calculation in generalized nonlinear least squares problem

The unknown parameter’s variance-covariance propagation and calculation in the generalized nonlinear least squares remain to be studied now, which didn’t appear in the internal and external referencing documents. The unknown parameter’s vari- ance-covariance propagation formula, considering the two-power terms, was concluded used to evaluate the accuracy of unknown parameter estimators in the generalized nonlinear least squares problem. It is a new variance-covariance formula and opens up a new way to evaluate the accuracy when processing data which have the multi-source, multi-dimensional, multi-type, multi-time-state, different accuracy and nonlinearity.

Optimizing near-carbon-free nuclear energy systems:advances in reactor operation digital twin through hybrid machine learning algorithms for parameter identification and state estimation

Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.

A transfer learning enhanced physics-informed neural network for parameter identification in soft materials

Soft materials,with the sensitivity to various external stimuli,exhibit high flexibility and stretchability.Accurate prediction of their mechanical behaviors requires advanced hyperelastic constitutive models incorporating multiple parameters.However,identifying multiple parameters under complex deformations remains a challenge,especially with limited observed data.In this study,we develop a physics-informed neural network(PINN)framework to identify material parameters and predict mechanical fields,focusing on compressible Neo-Hookean materials and hydrogels.To improve accuracy,we utilize scaling techniques to normalize network outputs and material parameters.This framework effectively solves forward and inverse problems,extrapolating continuous mechanical fields from sparse boundary data and identifying unknown mechanical properties.We explore different approaches for imposing boundary conditions(BCs)to assess their impacts on accuracy.To enhance efficiency and generalization,we propose a transfer learning enhanced PINN(TL-PINN),allowing pre-trained networks to quickly adapt to new scenarios.The TL-PINN significantly reduces computational costs while maintaining accuracy.This work holds promise in addressing practical challenges in soft material science,and provides insights into soft material mechanics with state-of-the-art experimental methods.

Effect of Process Parameters on Morphology and Grain Refinement Efficiency of TiAl_3 and TiB_2 in Alumimum Casting

This paper presents the effects of different process parameters in producing Al-STi-1B grain refiner,i.e.various sequences and reaction time,on grain refinement efficiency of aluminum castings.It was found that different process parameters resulted in different morphology and size distribution of TiAl-3 and TiB-2 in grain refiner. The experiment was carried out by adding KBF-4 and K-2TiF-6 to molten aluminum.The melting temperature was controlled at 800℃in an electric resistance furnace.Three different sequences of KBF-4 and K-2TiF-6 additions were applied,i.e.,adding KBF-4 before K-2TiF-6,adding K-2TiF-4 before KBF-4 and mixing both KBF-4 and K-2TiF-6 before adding to molten aluminum.Three different holding time at 1 min,30 min and 60 min were applied.The results showed that no significant difference of morphology and size distribution was found by varying three different sequences.Whereas,the different holding time provided major differences in both morphology and size distribution,which are technically expectable from diffusion and agglomeration between particles resulting in larger particle size and wider range of size distribution of TiAI3 and TiB2.If the reaction time was longer than 30 rain,morphology of both TiAl-3 and TiB-2 became too large.If the reaction time was too short,less reaction between TiAl-3 and TiB2 to form would be obtained.For grain refinement efficiency, it was found that mixing KBF-4 and K-2TiF-6 before adding to molten aluminum with a holding time of 30 min resulted in best grain refinement efficiency.

Enriched Constant Elements in the Boundary Element Method for Solving 2D Acoustic Problems at Higher Frequencies

The boundary element method(BEM)is a popular method for solving acoustic wave propagation problems,especially those in exterior domains,owing to its ease in handling radiation conditions at infinity.However,BEM models must meet the requirement of 6–10 elements per wavelength,using the conventional constant,linear,or quadratic elements.Therefore,a large storage size of memory and long solution time are often needed in solving higher-frequency problems.In this work,we propose two new types of enriched elements based on conventional constant boundary elements to improve the computational efficiency of the 2D acoustic BEM.The first one uses a plane wave expansion,which can be used to model scattering problems.The second one uses a special plane wave expansion,which can be used tomodel radiation problems.Five examples are investigated to showthe advantages of the enriched elements.Compared with the conventional constant elements,the new enriched elements can deliver results with the same accuracy and in less computational time.This improvement in the computational efficiency is more evident at higher frequencies(with the nondimensional wave numbers exceeding 100).The paper concludes with the potential of our proposed enriched elements and plans for their further improvement.

Effects of Additive AlCl_3 on Crystal Phase, Particle Size and Microstructural Parameters of Nanocrystalline TiO_2 Prepared by HF-PCVD

Nanocrystalline TiO2 was prepared by high frequency plasma chemical vapor deposition (HF-PCVD). The effects of additive AlCl3 on crystal phase, particle size and microstructurai parameters of TiO2 nanocrystallites were investigated by X-ray diffraction(XRD) and transmission electron microscopy (TEM). The nanocrystallites obtained experimentally are mixture of anatase and rutile, the uniform diameters of particles are about 30 nm. The phase transformation from anatase to rutile was accelerated by AlCl3, and rutile content is increased from 26.7 wt pct to 53.6 wt pct with increasing of addition of AlCl3 from 0.0 wt pct to 5.0 wt pct. The particle size is reduced and the size distribution becomes very narrow. The crystal lattice constants have the trend to decrease, and celi volumes appear as shrinkable.

Spectral Parameters of Nd^(3+) Ion in Nd^(3+):NaGd(MoO_4)_2 Crystal

The spectral parameters of Nd^3＋ ions in Nd^3＋-doped NaGd（MoO4）2 crystal have been investigated based on Judd-Ofelt theory and obtained as follows： The intensity parameters Ωeff are Ω2 = 24.77×10^20, Ω4 = 7.31×10^-20 and Ω6 = 6.91×10^-20 cm^2. The radiative lifetime is 100 μs, and the quantum efficiency is 93.9%. The fluorescence branch ratios were calculated to be β1 = 0.441, β2 = 0.469,β3 = 0.086 and β4=0.004.

Effects of Solid-State Reaction Synthesis Processing Parameters on Thermoelectric Properties of Mg_2Si

The Mg_(2)Si-matrix thermoelectric material was synthesized by low temperature solid-state reaction.This paper studies the effects of holding time and reaction temperature on the particle size and the properties of the material,and also studies effects of doping elemental Sb,Te and their doping seqence on the properties of the material.The result shows that excessively high temperature and elongated holding time of solid-state reaction are harmful,there is a range of particle size to ensure optimum properties and the doping sequence of Sb or Te without influencing the properties.

Numerical estimation of choice of the regularization parameter for NMR T2 inversion

Nuclear Magnetic inversion is the basis of NMR Resonance （NMR） T2 logging interpretation. The regularization parameter selection of the penalty term directly influences the NMR T2 inversion result. We implemented both norm smoothing and curvature smoothing methods for NMR T2 inversion, and compared the inversion results with respect to the optimal regular- ization parameters （（Xopt） which were selected by the dis- crepancy principle （DP）, generalized cross-validation （GCV）, S-curve, L-curve, and the slope of L-curve methods, respectively. The numerical results indicate that the DP method can lead to an oscillating or oversmoothed solution which is caused by an inaccurately estimated noise level. The （Xopt selected by the L-curve method is occa- sionally small or large which causes an undersmoothed or oversmoothed T2 distribution. The inversion results from GCV, S-curve and the slope of L-curve methods show satisfying inversion results. The slope of the L-curve method with less computation is more suitable for NMR T2 inversion. The inverted T2 distribution from norm smoothing is better than that from curvature smoothing when the noise level is high.

Effects of preparation parameters on growth and properties of β-Ga_(2)O_(3) film

The Ga_(2)O_(3) films are deposited on the Si and quartz substrates by magnetron sputtering, and annealing. The effects of preparation parameters(such as argon–oxygen flow ratio, sputtering power, sputtering time and annealing temperature)on the growth and properties(e.g., surface morphology, crystal structure, optical and electrical properties of the films) are studied by x-ray diffractometer(XRD), scanning electron microscope(SEM), and ultraviolet-visible spectrophotometer(UV-Vis). The results show that the thickness, crystallization quality and surface roughness of the β-Ga_(2)O_(3) film are influenced by those parameters. All β-Ga_(2)O_(3) films show good optical properties. Moreover, the value of bandgap increases with the enlarge of the percentage of oxygen increasing, and decreases with the increase of sputtering power and annealing temperature, indicating that the bandgap is related to the quality of the film and affected by the number of oxygen vacancy defects. The I–V curves show that the Ohmic behavior between metal and β-Ga_(2)O_(3) films is obtained at 900℃. Those results will be helpful for the further research of β-Ga_(2)O_(3) photoelectric semiconductor.

Effects of operating parameters on oxidative coupling of methane over Na-W-Mn/SiO_2 catalyst at elevated pressures

The effects of operating parameters on oxidative coupling of methane （OCM） over Na-W-Mn/SiO2 catalyst have been studied at elevated pressures of 0.2, 0.3 and 0.4 MPa under low gaseous hourly space velocity （GHSV） and low temperature conditions. Experimental results show that when the operating pressure is increased, C2＋ yield slightly decreases, while the maximum ratio of ethylene to ethane remains unchanged. Moreover, it has been found empirically that increase of pressure does not affect the catalyst behavior permanently, the catalyst recovers its original low pressure performance without hysteresis behavior by reducing the pressure. Under the investigated conditions, when oxygen is completely consumed, the increase of GHSV leads to improvement in C2 selectivity, while C3＋ and COx selectivities decrease slightly. The C2＋ selectivity increases by increase of nitrogen diluent in the feed, but the C3＋ hydrocarbons selectivities decrease with increase of nitrogen since it is possible that further dilution at high pressure may reduce the probability of collision between CH3 and C2＋ hydrocarbons. During the stability test at high pressure, the catalyst performance remains unchanged throughout the 20 h running. The fresh and used catalysts were characterized using XRD, SEM and N2 adsorption-desorption methods. It was found that the phase transformation of the support from α-cristobalite to tridymite and quartz does not have obvious effect on catalyst performance at high pressure.

Role of processing parameters on relative density,microstructure and mechanical properties of selective laser melted titanium alloy

The relationships between the selective laser melting(SLM)processing parameters including laser power,scanning speed and hatch space,the relative density,the microstructure,and resulting mechanical properties of Ti-6Al-2Zr-1Mo-1V alloy were investigated in this work.The result shows that laser power acts a dominant role in determining the relative density in comparison with scanning speed and hatch space.The optimal SLM process window for fabricating relative density>99%samples is located in the energy density range of 34.72 J·mm^(-3)to 52.08 J·mm^(-3),where the laser power range is between 125 W and 175 W.An upward trend is found in the micro-hardness as the energy density is increased.The optimum SLM processing parameters of Ti-6Al-2Zr-1Mo-1V alloy are:laser power of 150 W,scanning speed of 1,600 mm·s^(-1),hatch space of 0.08 mm,and layer thickness of 0.03 mm.The highest ultimate tensile strength,yield strength,and ductility under the optimum processing parameter are achieved,which are 1,205 MPa,1,099 MPa,and 8%,respectively.The results of this study can be used to guide SLM production Ti-6Al-2Zr-1Mo-1V alloy parts.

PARAMETER IDENTIFICATION PROBLEM OF THE FRACTAL INTERPOLATION FUNCTIONS

Parameter identification problem is one of essential problem in order to model effectively experimental data by fractal interpolation function.In this paper,we first present an example to explain a relationship between iteration procedure and fractal function.Then we discuss conditions that vertical scaling factors must obey in one typical case.

Investigation of the performance of CF3I/c-C4F8/N2 and CF3I/c-C4F8/CO2 gas mixtures from electron transport parameters

CF3I gas mixtures have attracted considerable attention as potential environmentally-friendly alternatives to SF6 gas,owing to their excellent insulating performance.This paper attempts to study the CF3I ternary gas mixtures with c-C4F8 and buffer gases N2 and CO2 by considering dielectric strength from electron transport parameters based on the Boltzmann method and synergistic effect analysis,compared with SF6 gas mixtures.The results confirm that the critical electric field strength of CF3I/c-C4F8/70%CO2 is greater than that of 30%SF6/70%CO2 when the CF3I content is greater than 17%.Moreover,a higher content of c-C4F8 decreases the sensitivity of gas mixtures to an electric field,and this phenomenon is more obvious in CF3I/c-C4F8/CO2 gas mixtures.The synergistic effects for CF3I/c-C4F8/70%N2 were most obvious when the c-C4F8 content was approximately 20%,and for CF3I/c-C4F8/70%CO2 when the c-C4F8 content was approximately 10%.On the basis of this research,CF3I/c-C4F8/70%N2 shows better insulation performance when the c-C4F8 content is in the15%–20%range.For CF3I/c-C4F8/70%CO2,when the c-C4F8 content is in the 10%–15%range,the gas mixtures have excellent performance.Hence,these gas systems might be used as alternative gas mixtures to SF6 in high-voltage equipment.