A Modified Monte Carlo Model of Speckle Tracking of Shear Wave Induced by Acoustic Radiation Force for Acousto-Optic Elasticity Imaging

A modified Monte Carlo model of speckle tracking of shear wave propagation in scattering media is proposed. The established Monte Carlo model mainly concerns the variations of optical electric field and speckle. The two- dimensional intensity distribution and the time evolution of speckles in different probe locations are obtained. The fluctuation of speckle intensity tracks the acoustic-radiation-force shear wave propagation, and especially the reduction of speckle intensity implies attenuation of shear wave. Then, the shear wave velocity is estimated quantitatively on the basis of the time-to-peak algorithm and linear regression processing. The results reveal that a smaller sampling interval yields higher estimation precision and the shear wave velocity is estimated more efficiently by using speckle intensity difference than by using speckle contrast difference according to the estimation error. Hence, the shear wave velocity is estimated to be 2.25 m/s with relatively high accuracy for the estimation error reaches the minimum （0.071）.

Improved Monte Carlo model for multiple scattering calculations

The coupling between the Monte Carlo （MC） method and geometrical optics to improve accuracy is investigated. The results obtained show improved agreement with previous experimental data, demonstrating that the MC method, when coupled with simple geometrical optics, can simulate multiple scattering with enhanced fidelity.

Fraunhofer diffraction of irregular apertures by Heisenberg uncertainty Monte Carlo model

Geometrical optics and the Monte Carlo method are very flexible in dealing with the interaction of light with non-spherical particles, but usually diffraction is not considered. To cover this gap, the Heisenberg Uncertainty Monte Carlo （HUMC） model is applied to calculate separately the diffraction of a ray or a photon. In this paper, we report an improvement of the HUMC model by specifying the phase of the photon subject to the Fraunhofer diffraction condition. After validating the model by comparing its results with analytical results for apertures of simple shapes, the HUMC model is then applied in simulations of Fraunhofer diffraction by apertures of complex shapes, such as those composed of one or two elliptical openings. We have shown that the diffracted intensity distributions of simple apertures obtained by the HUMC model are in good agreement with the results calculated from analytical expressions. The simulations of diffraction by apertures composed of two square or elliptical openings prove that the HUMC model is a powerful and flexible too] for predicting the Fraunhofer diffraction by a complex optical system.

Validation of the Ability of Full Configuration Interaction Quantum Monte Carlo for Studying the 2D Hubbard Model

To validate the ability of full configuration interaction quantum Monte Carlo （FCIQMC） for studying the 2D Hubbard model near half-filling regime, the ground state energies of a 4×44×4 square lattice system with various interaction strengths are calculated. It is found that the calculated results are in good agreement with those obtained by exact diagonalization （i.e., the exact values for a given basis set） when the population of psi particles （psips） is higher than the critical population required to correctly sample the ground state wave function. In addition, the variations of the average computational time per 20 Monte Carlo cycles with the coupling strength and the number of processors are also analyzed. The calculated results show that the computational efficiency of an FCIQMC calculation is mainly affected by the total population of psips and the communication between processors. These results can provide useful references for understanding the FCIQMC algorithm, studying the ground state properties of the 2D Hubbard model for the larger system size by the FCIQMC method and using a computational budget as effectively as possible.

Monte Carlo Simulations of Topological Properties in Two-Phase Polycrystalline Materials for Several Diffusion Mechanism

Numerical simulations by means of the Monte Carlo Potts model have been provided to simulate grain structures in two-phase polycrystalline materials. The topological features in the simulated microstructure analyzed for different diffusion mechanisms over a broad range of volume fractions for both phases. The topological properties include the average number of sides, grain topology distribution and the topological size relation function. It is found that the average number of sides depends proportionally on the volume fraction. It increases as the volumes fraction increases and vice versa. Moreover, it is shown that the grain topology distribution in the self-similar growth regime can be described by time unchanged function of the relative grain size. Additionally, topological size function in the simulated microstructure can be evaluated by a quadratic function.

No-core Monte Carlo shell model calculations with unitary correlation operator method and similarity renormalization group

The unitary correlation operator method （UCOM） and the similarity renormalization group theory （SRG） are compared and discussed in the framework of the no-core Monte Carlo shell model （MCSM） calculations for ^3H and ^4He. The treatment of spurious center-of-mass motion by Lawson＇s prescription is performed in the MCSM calculations. These results with both transformed interactions show good suppression of spurious center-of-mass motion with proper Lawson＇s prescription parameter βc.m. values. The UCOM potentials obtain faster convergence of total energy for the ground state than that of SRG potentials in the MCSM calculations, which differs from the cases in the no-core shell model calculations （NCSM）. These differences are discussed and analyzed in terms of the truncation scheme in the MCSM and NCSM, as well as the properties of the potentials of SRG and UCOM.

Hot electron effects on the operation of potential well barrier diodes

A study has just been carried out on hot electron effects in GaAs/Al0.3Ga0.7As potential well barrier(PWB)diodes using both Monte Carlo(MC)and drift-diffusion(DD)models of charge transport.We show the operation and behaviour of the diode in terms of electric field,mean electron velocity and potential,mean energy of electrons andΓ-valley population.The MC model predicts lower currents flowing through the diode due to back scattering at anode(collector)and carrier heating at higher bias.At a bias of 1.0 V,the current density obtained from experimental result,MC and DD simulation models are 1.35,1.12 and1.77μA/μm^2 respectively.The reduction in current over conventional model,is compensated to a certain extent because less charge settles in the potential well and so the barrier is slightly reduced.The DD model results in higher currents under the same bias and conditions.However,at very low bias specifically,up to 0.3 V without any carrier heating effects,the DD and MC models look pretty similar as experimental results.The significant differences observed in the I-V characteristics of the DD and MC models at higher biases confirm the importance of energy transport when considering these devices.

Combining Monte Carlo and Ensemble Probabilities in Tropical Cyclone Forecasts near Landfall

The Monte Carlo probability(MCP)model,which has been used for official tropical cyclone(TC)warnings to the public by the United States’National Hurricane Center(NHC),can estimate the probability of wind speed in the vicinity of a TC during the forecast period.It has been successful in the operational environment for many years.However,due to its strong dependence on a given forecast track(e.g.,forecast from the NCEP Global Forecast System),the MCP model may generate a poor probability map for TCs near landfall.In this study,we proposed and tested a modified MCP method for TC forecasts near landfall.We first adjusted the MCP model by adding limits to the direction angle and motion distance to deal with the substantial change in TC moving direction and the low wind speeds during landfall.Then,we combined ensemble probability maps generated from ECMWF,United Kingdom Met Office(UKMO),and NCEP ensemble forecasts,obtained from The International Grand Global Ensemble(TIGGE),into the MCP model to configure a modified MCP model.Wind speed probability maps for the 0-120-h forecast from both the original and modified MCP models are compared.It is found that the modified MCP model can provide a better wind speed probability map during landfall,especially at wind speeds of 20-64 kt near TC landfall.The results from this study prove the benefits of combining the MCP model with ensemble forecasting in potential applications for improved TC forecasts.

Numerical simulation of heat-affected zone microstructure in GMAW

The grain size in the heat-affected zone （ HAZ） of workpieces is an important factor for evaluating the welding quality. The Monte Carlo technique of grain growth in the heat-affected zone of alloy is widely used. A finite element model （FEM） was employed to simulate the temperature field of gas metal arc welding （GMAW） ; the data of thermal cycles were used in the Monte Carlo model to calculate the grain sizes in different welding heat inputs. The equation for the relationship between Monte Carlo Step and real time has been estimated using regression analysis. Then mathematics model of the grain growth could be worked out by both the kinetic model and the Monte Carlo model. The dynamic process of grain growth was simulated by the result of the Monte Carlo model. The experimental result was used to prove the validity of this method in simulating of microstructure.

Effect of Fiber Volume Fraction on Longitudinal Tensile Properties of SiCf/Ti-6Al-4V Composites

The longitudinal tensile properties of SiCf/Ti-6Al-4V composites with different fiber volume fractions were simulated by the Monte Carlo 2-D finite element model. The random distribution of fiber strength was expressed by the two-parameter Weibull function. Meanwhile, contact elements and birth-death elements were used to describe the interfacial sliding process after debonding and fiber breakage（or matrix cracking） respectively, which was realized by subroutine complied in ANSYS-APDL（ANSYS Parametric Design Language）. The experimental results show that the yield stress and ultimate tensile strength of SiCf/Ti-6Al-4V composites increase with increasing fiber volume fraction, while the corresponding strain of them is just on the contrary. In addition, almost the same failure mode is obtained in SiCf/Ti-6Al-4V composites with various fiber volume fractions when the interfacial shear strength is fixed. Finally, the tensile strength predicted by finite element analysis is compared with that predicted by Global load-sharing model, Local load-sharing model and conventional rule of mixtures, thus drawing the conclusion that Local load-sharing model is very perfect for the prediction of the ultimate tensile strength.

Stochastic model updating using distance discrimination analysis

This manuscript presents a stochastic model updating method, taking both uncertainties in models and variability in testing into account. The updated finite element（FE） models obtained through the proposed technique can aid in the analysis and design of structural systems. The authors developed a stochastic model updating method integrating distance discrimination analysis（DDA） and advanced Monte Carlo（MC） technique to（1） enable more efficient MC by using a response surface model,（2） calibrate parameters with an iterative test-analysis correlation based upon DDA, and（3） utilize and compare different distance functions as correlation metrics. Using DDA, the influence of distance functions on model updating results is analyzed. The proposed stochastic method makes it possible to obtain a precise model updating outcome with acceptable calculation cost. The stochastic method is demonstrated on a helicopter case study updated using both Euclidian and Mahalanobis distance metrics. It is observed that the selected distance function influences the iterative calibration process and thus, the calibration outcome, indicating that an integration of different metrics might yield improved results.

Simulation of secondary nucleation of polymer crystallization via a model of microscopic kinetics

We present simulations of the mechanism of secondary nucleation of polymer crystallization,based on a new model accounting for the microscopic kinetics of attaching and detaching.As the key feature of the model,we introduced multibody-interaction parameters that establish correlations between the attaching and detaching rate constants and the resulting thickness and width of the crystalline lamella.Using MATLAB and Monte Carlo method,we followed the evolution of the secondary nuclei as a function of various multibody-interaction parameters.We identified three different growth progressions of the crystal：（i） Widening,（ii） thickening and（iii） simultaneously thickening and widening of lamellar crystals,controlled by the corresponding kinetic parameters.

Uncertainty Analysis of Value for Money Assessment for Public-Private Partnership Projects

In recent years, private sectors are encouraged to take an active part in franchising of urban infrastructure investments and operations, which promotes the rapid development of public-private partnership(PPP)in infrastructure and public service supply. Value for money(VFM) assessment has been officially proposed to provide a reference for selection of projects planning to adopt PPP. Based on the bottlenecks of VFM application in China and the uncertainties for urban infrastructure PPP projects, a discounted cash flow(DCF) model is established for VFM of infrastructure PPP projects. Then, a Monte Carlo simulation model is established on the basis of uncertainty factors for VFM. Through the analysis of Huai'an trams PPP project, coping strategies of uncertainties for VFM are put forward. Findings of the research may propel the establishment of a complete VFM evaluation system for PPP projects. Key instructional functions of VFM during the process of decision-making can be brought into full play and PPP may develop orderly.