Two-state energy model and experimental study of coal adsorb methane

There are two states of methane existing in coal, free methane and adsorptive methane. The two states of methane exchanged with each other which need the energy exchange with outside. It is released heat when methane adsorption on coal, instead of absorbed heat. According to the gas molecules Boltzmann energy distribution, is obtained the equilibrium equations of the two states of methane in coal, as well as the heat of adsorption equation when exchanged into each other. At the same time, high temperature experiments of methane adsorption on coal have been certificated to the theoretical model. At last the experimental results presented that： the two-state energy model could be accurately described the distribution of the two states of methane in the coal; the adsorption heat is related to the initial equilibrium state of methane adsorption; the adsorption heats are different with different coal ranks.

Effective Two-State Model and NOON States for Double-Well Bose-Einstein Condensates in Strong-Interaction Regime

The model of double-well Bose-Einstein condensates in the strong-interaction regime is shown to reduce adiabatically to an effective two-state model describing the Rabi oscillations between the two atomic Fock states ｜N, 0〉 and [0, N〉, and the NOON states of arbitrary ultracold atoms can therefore be generated periodically from the initial state of either one of the Foek states.

Large Signal Modulation Characteristics in the Transition Regime for Two-State Lasing Quantum Dot Lasers

Large-signal modulation capability, as an important performance indicator, is directly related to the high-speed optical communication technology involved. We experimentally and theoretically investigate the large-signal modulation characteristics of the simultaneous ground-state （GS） and the excited-state （ES） lasing in InAs/OaAs quantum dot laser diodes. The large-signal modulation capability of total light intensity in the transition regime from OS lasing to two-state lasing is unchanged as the bias-current increases. However, GS and ES large-signal eye diagrams show obvious variations during the transition. Relaxation oscillations and large-signal eye diagrams for OS, ES, and total light intensities are numerically simulated and analyzed in detail by using a rate-equation model. The -ndings show that a complementary relationship between the light intensities for OS and ES lasing exists in both the transition regime and the two-state lasing regime, leading to a much smaller overshooting power and a shorter settling time for the total light intensity. Therefore, the eye diagrams of GS or ES lasing are diffuse whereas those of total light intensity are constant as the bias-current increases in the transition regime.

A Deep Two-State Gated Recurrent Unit for Particulate Matter (PM_(2.5)) Concentration Forecasting

Air pollution is a significant problem in modern societies since it has a serious impact on human health and the environment.Particulate Matter(PM_(2.5))is a type of air pollution that contains of interrupted elements with a diameter less than or equal to 2.5 m.For risk assessment and epidemiological investigations,a better knowledge of the spatiotemporal variation of PM_(2.5) concentration in a constant space-time area is essential.Conventional spatiotemporal interpolation approaches commonly relying on robust presumption by limiting interpolation algorithms to those with explicit and basic mathematical expression,ignoring a plethora of hidden but crucial manipulating aspects.Many advanced deep learning approaches have been proposed to forecast Particulate Matter(PM_(2.5)).Recurrent neural network(RNN)is one of the popular deep learning architectures which is widely employed in PM_(2.5) concentration forecasting.In this research,we proposed a Two-State Gated Recurrent Unit(TS-GRU)for monitoring and estimating the PM_(2.5) concentration forecasting system.The proposed algorithm is capable of considering both spatial and temporal hidden affecting elements spontaneously.We tested our model using data from daily PM_(2.5) dimensions taken in the contactual southeast area of the United States in 2009.In the studies,three evaluation matrices were utilized to compare the overall performance of each algorithm:Mean Absolute Error(MAE),Root Mean Square Error(RMSE),and Mean Absolute Percentage Error(MAPE).The experimental results revealed that our proposed TS-GRU model outperformed compared to the other deep learning approaches in terms of forecasting performance.

Measurement Problem and Two-State Vector Formalism

In this paper, I show that an interpretation of quantum mechanics using two-state vector formalism proposed by Aharonov, Bergmann, and Lebowitz, can solve one of the measurement problems formulated by Maudlin. According to this interpretation, we can simultaneously insist that the wave function of a system is complete, that the wave function is determined by the Schr?dinger equation, and that the measurement of a physical quantity always has determinate outcomes, although Maudlin in his formulation of the measurement problem states that these three claims are mutually inconsistent. Further, I show that my interpretation does not contradict the uncertainty relation and the no-go theorem.

Einstein Dilemma and Two-State Vector Formalism

In the famous EPR paper published in 1935, Einstein, Podolsky, and Rosen suggested a thought experiment, which later became known as the “EPR experiment”. Using the EPR experiment, they posited that quantum mechanics was incomplete. Einstein, however, was dissatisfied with the EPR paper and published a second work on the EPR experiment, in which he discussed the dilemma of choosing whether quantum mechanics was incomplete or nonlocal. Currently, most physicists choose the nonlocality of quantum mechanics over Einstein’s choice of the incompleteness of quantum mechanics. However, with an appropriate alternate hypothesis, both of these choices can be rejected. Herein, I demonstrate an approach to overcome the Einstein Dilemma by proposing a new interpretation invoked by a new formalism of quantum mechanics known as two-state vector formalism.

Transfer Matrix Approach for Two-State Scattering Problem with Arbitrary Coupling

The present work deals with the calculation of transition probability between two diabatic potentials coupled by any arbitrary coupling. The method presented in this work is applicable to any type of coupling while for numerical calculations we have assumed the arbitrary coupling as Gaussian coupling. This arbitrary coupling is expressed as a collection of Dirac delta functions and by the use of the transfer matrix technique the transition probability from one diabatic potential to another diabatic potential is calculated. We examine our approach by considering the case of two constant potentials coupled by Gaussian coupling as an arbitrary coupling.

Theoretical Investigation for Two-state Reactivity of CO_2 Hydrogenation Catalyzed by Ru in Gas Phase

Gas-phase CO_2 catalyzed activation hydrogenation by Ru atoms was studied with density functional theory. Based on the structure optimization of different potential energy surfaces,there are two crossing points between singlet and triplet potential energy surfaces and there is a crossing point between quintet and triplet potential energy surfaces in the whole catalytic cycle. Spin transition probabilities in the vicinity of the intersections have been calculated by the Landau-Zener model theory. There are three minimum energy crossing points（MECPs） with strong spin-orbital coupling effect and higher spin transition probability,and all spin inversion occurred in s orbital and different d orbitals of ruthenium,indicating this is a typical two-state reactivity（TSR） reaction. Finally,the lowest energy reaction path is ensured.

Simulation of Dynamic Recrystallization in 7075 Aluminum Alloy Using Cellular Automaton

The evolution of microstructure during hot deformation is key to achieving good mechanical properties in aluminum alloys.We have developed a cellular automaton(CA) based model to simulate the microstructural evolution in 7075 aluminum alloy during hot deformation.Isothermal compression tests were conducted to obtain material parameters for 7075 aluminum alloy,leading to the establishment of models for dislocation density,nucleation of recrystallized grains,and grain growth.Integrating these aspects with grain topological deformation,our CA model effectively predicts flow stress,dynamic recrystallization(DRX) volume fraction,and average grain size under diverse deformation conditions.A systematic comparison was made between electron back scattered diffraction(EBSD) maps and CA model simulated under different deformation temperatures(573 to 723 K),strain rates(0.001 to 1 s^(-1)),and strain amounts(30% to 70%).These analyses indicate that large strain,high temperature,and low strain rate facilitate dynamic recrystallization and grain refinement.The results from the CA model show good accuracy and predictive capability,with experimental error within 10%.

Dynamics of Land Use/Land Cover Considering Ecosystem Services for a Dense-Population Watershed Based on a Hybrid Dual-Subject Agent and Cellular Automaton Modeling Approach

Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeholders.This study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China.Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change.The major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change decisions.Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)model.Simultaneously,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion.An agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use conversion.This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services.The results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.

车路协同下基于元胞自动机的精细交通流模型

针对经典元胞自动机交通流模型中元胞尺寸难以准确表达车辆间位置关系的问题,提出通过细化元胞尺寸对基于元胞自动机的双车道模型(symmetrictwo-lanecellularautomaton,STCA)进行改进的方案.首先,分析城市道路双车道环境下的位置、速度、加速度以及车辆间的相互影响,并基于元胞自动机搭建相应数值模型,特别地,针对现有基于元胞自动机的交通流模型与实际车辆行驶现象不符的问题,改进其道路尺寸和元胞表征形式,建立精细化元胞自动机车道模型;其次,结合实际车路环境,对STCA模型中的道路堵塞、换道等行为重新定义,并将车道规则与精细化车道模型相结合,建立新的交通流模型STCA-CH;最后,与STCA、STCA-I、STCA-S、STCA-M模型相对比,通过分析在不同车辆密度下的平均速度、平均流量、换道频率及时空图,验证STCA-CH模型有效性.结果表明,STCA-CH模型的换道频率相较于STCA-M模型提高约21.14%,最大平均流量较STCA-I、STCA-S和STCA-M模型分别提升约25.76%、11.30%和3.75%.

用Cellular Automaton模型方法模拟二元合金多晶粒枝晶生长

研究并针对CellularAutomaton凝固组织模拟方法的物理本质、数值计算方法以及在凝固微观组织模拟中的应用进行了探索。并利用CellularAutomaton凝固组织模拟方法,求解了Al4.5Cu等轴晶多个枝晶同时生长过程。模拟结果和试验结果吻合很好。

采用Cellular Automaton法模拟铝合金的微观组织

采用 Cellular Automaton微观模型 ,并与宏观的传热计算相结合 ,对砂型铸造铝合金铸件的凝固组织形成进行了模拟。在模拟过程中 ,采用连续形核的方法处理液态金属的异质形核现象。通过高斯分布函数描述形核质点密度随温度的分布关系 ,在给定过冷度时对分布函数求积分可得该时刻的形核密度。晶粒生长模型则考虑枝晶尖端生长动力学和择优生长方向〈1 0 0〉晶向。模拟计算结果表明 ,在冷却速度不变的情况下 ,随着形核分布参数ΔTN 增加 ,所得到的晶粒尺寸增大。

用Cellular Automaton方法模拟压铸镁合金AM50的微观组织

基于Cellular Automaton(CA)方法的基本原理,建立了压铸镁合金AM50形核和等轴晶粒生长的二维数学物理模型,能够对任意晶向的等轴晶晶粒生长进行模拟。模型耦合了宏观传热与微观组织模拟计算,镁合金AM50阶梯块压铸件的温度场通过热传导反算法计算求得。对阶梯块压铸件不同阶梯表面的微观组织进行了模拟,并与金相试验结果进行了对比,它们在晶粒尺寸上吻合较好。

基于热力学函数的纳米晶粒长大Cellular Automaton仿真研究

基于纳米晶热力学特性表征函数,将纳米晶热力学性质对晶界迁移的影响引入Cellular Automaton算法,对纳米晶粒长大行为进行了定量化和可视化的仿真研究.模拟结果表明,纳米晶粒长大的动力学与传统粗晶材料不同,在恒温条件下,纳米晶粒的长大指数n不是常数(传统粗晶材料的晶粒长大指数n=2为常数),随纳米晶粒长大过程的进行,n值从1.70至6.59发生变化.作为纳米晶粒长大的驱动力,纳米晶界的过剩自由能与纳米晶粒尺寸的变化直接相关.由于纳米晶材料强烈的小尺寸效应,纳米晶组织的热力学性质较大地影响纳米晶界的结构和能量状态,从而影响纳米晶粒长大的动力学特征.因此,只有结合纳米晶热力学特性的仿真研究才能获得对纳米晶粒长大行为本质性的认识.

用Cellular Automaton模型方法模拟二元合金枝晶生长

研究并针对CellularAutomaton凝固组织模拟方法模型的物理本质、数值计算方法以及在凝固微观组织模拟中的应用进行了探索。并利用CellularAutomaton凝固组织模拟方法,求解了Al-4.5%Cu等轴晶枝晶生长。

金属成形过程组织演变的Cellular Automaton模拟技术

结合金属凝固过程和热成形过程的温度场、浓度场、应力应变场等的数值模拟和金属结晶、再结晶过程中的热力学、动力学条件，建立了金属成形过程组织演变的宏－微观耦合模型．利用ＣｅｌｌｕｌａｒＡｕｔｏｍａｔｏｎ方法，依据建立的模型对Ｋ４１７Ｎｉ基合金叶片的凝固组织形成过程和热加工过程的再结晶组织进行了模拟．

采用Cellular automaton法模拟动态再结晶过程的研究

结合金属塑性成形过程的冶金学原理,给出了一种新的模拟动态再结晶过程的元胞自动机(Cellular automaton,CA)模型,用来模拟塑性变形过程中动态再结晶过程。再结晶晶粒的生长速度与再结晶驱动力成正比, 再结晶驱动力取决于晶界能和位错密度。在一个增量步内,根据动态再结晶晶粒生长速度确定与其相邻原胞转变 概率。采用本模型对不同温度、应变速度、应变条件下的动态再结晶过程进行了模拟,模拟结果与试验结果以及 经验公式得到的结果相一致。本模型也可用于再结晶动力学、微观组织和织构变化过程的模拟。

Cellular Automaton法模拟金属凝固显微组织研究进展

介绍了金属凝固过程中显微组织模拟的数学模型和计算模型以及元胞自动机(Cellular automation)法的原理及发展历程。概述了晶粒形核和生长的几个物理模型,并对元胞自动机在凝固过程中微观组织形成过程的计算机模拟的应用作了较详细的介绍。元胞自动机考虑了形核和生长动力学问题,通过宏微观耦合模型可计算固相分数和潜热释放的变化。介绍了两种元胞自动机和有限元方法的耦合方式,并对元胞自动机法的未来发展方向进行了展望。

EVOLUTION COMPL EXITY OF THE ELEMENTARY CELLULAR AUTOMATON OF RUL E 2 2

Cellular automata are the discrete dynamical systems of simple construction but with complex and varied behaviors.In this paper,the elementary cellular automaton of rule 22 is studied by the tools of formal language theory and symbolic dynamics.Its temporal evolution orbits are coarse grained into evolution sequences and the evolution languages are defined.It is proved that for every n ≥2 its width n evolution language is not regular.