In this paper, we present DEMC, a deep dual-encoder network to remove Monte Carlo noise efficiently while preserving details. Denoising Monte Carlo rendering is different from natural image denoising since inexpensive...In this paper, we present DEMC, a deep dual-encoder network to remove Monte Carlo noise efficiently while preserving details. Denoising Monte Carlo rendering is different from natural image denoising since inexpensive by-products (feature buffers) can be extracted in the rendering stage. Most of them are noise-free and can provide sufficient details for image reconstruction. However, these feature buffers also contain redundant information. Hence, the main challenge of this topic is how to extract useful information and reconstruct clean images. To address this problem, we propose a novel network structure, dual-encoder network with a feature fusion sub-network, to fuse feature buffers firstly, then encode the fused feature buffers and a noisy image simultaneously, and finally reconstruct a clean image by a decoder network. Compared with the state-of-the-art methods, our model is more robust on a wide range of scenes, and is able to generate satisfactory results in a significantly faster way.展开更多
Learning-based techniques have recently been shown to be effective for denoising Monte Carlo rendering methods. However, there remains a quality gap to state-of-the-art handcrafted denoisers. In this paper, we propose...Learning-based techniques have recently been shown to be effective for denoising Monte Carlo rendering methods. However, there remains a quality gap to state-of-the-art handcrafted denoisers. In this paper, we propose a deep residual learning based method that outperforms both state-of-the-art handcrafted denoisers and learning-based denoisers.Unlike the indirect nature of existing learning-based methods(which e.g., estimate the parameters and kernel weights of an explicit feature based filter), we directly map the noisy input pixels to the smoothed output. Using this direct mapping formulation, we demonstrate that even a simple-and-standard ResNet and three common auxiliary features(depth, normal,and albedo) are sufficient to achieve high-quality denoising. This minimal requirement on auxiliary data simplifies both training and integration of our method into most production rendering pipelines. We have evaluated our method on unseen images created by a different renderer. Consistently superior quality denoising is obtained in all cases.展开更多
The goal of this study is to provide a stochastic method to investigate the eff ects of the randomness of soil properties due to their natural spatial variability on the response spectra spatial variation at sites wit...The goal of this study is to provide a stochastic method to investigate the eff ects of the randomness of soil properties due to their natural spatial variability on the response spectra spatial variation at sites with varying conditions. For this purpose, Monte Carlo Simulations are used to include the variability of both incident ground motion and soil parameters in the response spectra by mean of an appropriate coherency loss function and a site-dependent transfer function, respectively. The approach is built on the assumption of vertical propagation of SH type waves in soil strata with uncertain parameters. The response spectra are obtained by numerical integration of the governing equation of a single-degree-of-freedom (SDOF) system under non-stationary site-dependent and spatially varying ground motion accelerations simulated with non-uniform spectral densities and coherency loss functions. Numerical examples showed that randomness of soil properties signifi cantly aff ects the amplitudes of the response spectra, indicating that as the heterogeneity induced by the randomness of the parameters of the medium increases, the spectral ordinates attenuate.展开更多
Integration system is used to denote practices that combine systematic use of the land and technologies,in which forest species are used in conjunction with herbaceous plants and/or animals respecting a spatial or tem...Integration system is used to denote practices that combine systematic use of the land and technologies,in which forest species are used in conjunction with herbaceous plants and/or animals respecting a spatial or temporal arrangement.Knowing that this type of production seeks to balance ecological and economic factors,it is important to understand the financial benefits and risks involved in this production.Financial analysis,therefore,acts as an important analysis tool to foster this type of activity.The paper aimed to conduct analysis of investment risk of a crop-livestock-forestry system deployed in Brazil,comparing two different production scenarios,scenario I with 17 ha and scenario II with 25 ha.The risk analysis was performed using the Monte Carlo method and sensitivity analysis(by varying the factors:the discount rate,productivity and price).A cash flow was elaborated based on annual cost and revenues data of the agricultural crops(corn and soybeans),livestock and eucalyptus,using an interest rate of 6%per year.The results indicated that the optimal age for cutting the eucalyptus was at seven years on both scenarios;scenario I had better return on investment using deterministic and probabilistic methods;scenario I presents higher investments risks;there is a negative relation between discount rate and annualized net present value(ANPV);increased productivity of crops provides greater profitability to the system;there has been an increase in the economic viability of the system,as value has been added to the products.Monte Carlo method and the sensitivity analysis showed to be an appropriate tool to analyze the risk of crop-livestock-forestry systems,making it possible to foresee how the project will respond to possible scenarios.展开更多
To gain a competitive edge within the international and compet让ive setting of coal markets, coal producers must find new ways of reducing costs. Increasing bench drilling efficiency and performance in open-cast coal ...To gain a competitive edge within the international and compet让ive setting of coal markets, coal producers must find new ways of reducing costs. Increasing bench drilling efficiency and performance in open-cast coal mines has the potential to generate savings. Specifically, monitoring, analyzing, and optimizing the drilling operation can reduce drilling costs. For example, determining the optimal drill bit replacement time will help to achieve the desirable penetration rate. This paper presents a life data analysis of drill bits to fit a statistical distribution using failure records. These results are then used to formulate a cost minimization problem to estimate the drill bit replacement time using the evolutionary algorithm. The effect of cost on the uncertainty associated with replacement time is assessed through Monte-Carlo simulation. The relationship between the total expected replacement cost and replacement time is also presented. A case study shows that the proposed approach can be used to assist with designing a drill bit replacement schedule and minimize costs in open-cast coal mines.展开更多
Using exact quantum Monte Carlo method,we examine the recent novel electronic states seen in magicangle graphene superlattices.From the Hubbard model on a double-layer honeycomb lattice with a rotation angleθ=1:08...Using exact quantum Monte Carlo method,we examine the recent novel electronic states seen in magicangle graphene superlattices.From the Hubbard model on a double-layer honeycomb lattice with a rotation angleθ=1:08°,we reveal that an antiferromagnetically ordered Mott insulator emerges beyond a critical U_c at half filling,and with a small doping,the pairing with d+id symmetry dominates over other pairings at low temperature.The effective d+id pairing interaction strongly increases as the on-site Coulomb interaction increases,indicating that the superconductivity is driven by electron-electron correlation.Our non-biased numerical results demonstrate that the twisted bilayer graphene shares the similar superconducting mechanism of high temperature superconductors,which is a new and ideal platform for further investigating the strongly correlated phenomena.展开更多
The magnetic properties of inverse ferrite (Fe^3+)[Fe^3+Co^2+]O4^2-,(Fe^3+)[Fe^3+Cu^2+]O4^2,( Fe^3+)[Fe^3+Fe^2+]O4^2,and (Fe^3+)[Fe^3+Ni^2+]O4^2- spinels have been studied using Monte Carlo simulation.We have also cal...The magnetic properties of inverse ferrite (Fe^3+)[Fe^3+Co^2+]O4^2-,(Fe^3+)[Fe^3+Cu^2+]O4^2,( Fe^3+)[Fe^3+Fe^2+]O4^2,and (Fe^3+)[Fe^3+Ni^2+]O4^2- spinels have been studied using Monte Carlo simulation.We have also calculated the critical and Curie Weiss temperatures from the thermal magnetizations and inverse of magnetic susceptibilities for each system.Magnetic hysteresis cycles have been found for the four systems.Finally,we found the critical exponents associated with magnetization,magnetic susceptibility,and external magnetic field.Our results of critical and Curie Weiss temperatures are similar to those obtained by experiment results.The critical exponents are similar to those of known 3D-Ising model.展开更多
In order to solve the problem of the reliability of slope engineering due to complex uncertainties, the Monte Carlo simulation method is adopted. Based on the characteristics of sparse grid, an interpolation algorithm...In order to solve the problem of the reliability of slope engineering due to complex uncertainties, the Monte Carlo simulation method is adopted. Based on the characteristics of sparse grid, an interpolation algorithm, which can be applied to high dimensional problems, is introduced. A surrogate model of high dimensional implicit function is established, which makes Monte Carlo method more adaptable. Finally, a reliability analysis method is proposed to evaluate the reliability of the slope engineering, and is applied in the Sau Mau Ping slope project in Hong Kong. The reliability analysis method has great theoretical and practical significance for engineering quality evaluation and natural disaster assessment.展开更多
The potential-driving model is used to describe the driving potential distribution and to calculate the preneutron emission mass distributions for different incident energies in the 237 Np(n, f)reaction. The potential...The potential-driving model is used to describe the driving potential distribution and to calculate the preneutron emission mass distributions for different incident energies in the 237 Np(n, f)reaction. The potential-driving model is implemented in Geant4 and used to calculate the fission-fragment yield distributions, kinetic energy distributions, fission neutron spectrum and the total nubar for the 237 Np(n, f)reaction. Compared with the built-in G4 ParaFissionModel, the calculated results from the potential-driving model are in better agreement with the experimental data and evaluated data. Given the good agreement with the experimental data, the potential-driving model in Geant4 can describe well the neutron-induced fission of actinide nuclei, which is very important for the study of neutron transmutation physics and the design of a transmutation system.展开更多
Multi-layer connected self-organizing feature maps(SOFMs) and the associated learning procedure were proposed to achieve efficient recognition and clustering of messily grown nanowire morphologies. The network is made...Multi-layer connected self-organizing feature maps(SOFMs) and the associated learning procedure were proposed to achieve efficient recognition and clustering of messily grown nanowire morphologies. The network is made up by several paratactic 2-D SOFMs with inter-layer connections. By means of Monte Carlo simulations, virtual morphologies were generated to be the training samples. With the unsupervised inner-layer and inter-layer learning, the neural network can cluster different morphologies of messily grown nanowires and build connections between the morphological microstructure and geometrical features of nanowires within. Then, the as-proposed networks were applied on recognitions and quantitative estimations of the experimental morphologies. Results show that the as-trained SOFMs are able to cluster the morphologies and recognize the average length and quantity of the messily grown nanowires within. The inter-layer connections between winning neurons on each competitive layer have significant influence on the relations between the microstructure of the morphology and physical parameters of the nanowires within.展开更多
Sharp bending as one of the mechanical properties of double-stranded DNA(dsDNA) on the nanoscale is essential for biological functions and processes. Force sensors with optical readout have been designed to measure th...Sharp bending as one of the mechanical properties of double-stranded DNA(dsDNA) on the nanoscale is essential for biological functions and processes. Force sensors with optical readout have been designed to measure the forces inside short, strained loops composed of both dsDNA and single-stranded DNA(ssDNA). Recent FRET singlemolecule experiments were carried out based on the same force sensor design, but provided totally contrary results. In the current work, Monte Carlo simulations were performed under three conditions to clarify the discrepancy between the two experiments. The criterion that the work done by the force exerted on dsDNA by ssDNA should be larger than the nearest-neighbor(NN) stacking interaction energy is used to identify the generation of the fork at the junction of dsDNA and ssDNA. When the contour length of dsDNA in the sensor is larger than its critical length, the fork begins to generate at the junction of dsDNA and ssDNA, even with a kink in dsDNA. The forces inferred from simulations under three conditions are consistent with the ones inferred from experiments, including extra large force and can be grouped into two different states, namely, fork states and kink states. The phase diagrams constructed in the phase space of the NN stacking interaction energy and excited energy indicate that the transition between the fork state and kink state is difficult to identify in the phase space with an ultra small or large number of forks, but it can be detected in the phase space with a medium number of forks and kinks.展开更多
An absorption-desorption model with long-ranged interaction is simulated by the dynamic Monte Carlo method.The dynamic process has an inert phase and an active phase that is controlled by the absorption rate.In the ac...An absorption-desorption model with long-ranged interaction is simulated by the dynamic Monte Carlo method.The dynamic process has an inert phase and an active phase that is controlled by the absorption rate.In the active phase,the number of vacancies increases with time exponentially,while in the inert phase the vacant sites will be occupied by adsorbates rapidly.At the critical absorption rate,both the number of vacancies and the time-depending active probability exhibit power-law behavior.We determine the critical absorption rate and the scaling exponents of the power-laws.The effect of the interaction range of desorption on the critical exponents is investigated.In the short-ranged interaction limit, the critical exponents of Schlogl’s first model are recovered.The model may describe the sta bility of the inner Helmholtz layer,an essential component of the electrochemical double-layer capacitor at a nanowire.展开更多
Dear editor,Polar codes can achieve the symmetric capacity of binary-input memoryless channels with infinite code length under successive cancellation(SC)decoding(1)Cyclic redundancy check(CRC)aids in successive cance...Dear editor,Polar codes can achieve the symmetric capacity of binary-input memoryless channels with infinite code length under successive cancellation(SC)decoding(1)Cyclic redundancy check(CRC)aids in successive cancellation list(CA-SCL)[2,3]and a decoder is proposed to improve the finite length performance of polar codes.To achieve the spectrum efficiency required by next generation wireless networks,it is essential to combine polar codes with higher order modulation.展开更多
Geochronology is essential for understanding Earth’s history. The availability of precise and accurate isotopic data is increasing;hence it is crucial to develop transparent and accessible data reduction techniques a...Geochronology is essential for understanding Earth’s history. The availability of precise and accurate isotopic data is increasing;hence it is crucial to develop transparent and accessible data reduction techniques and tools to transform raw mass spectrometry data into robust chronological data. Here we present a Monte Carlo sampling approach to fully propagate uncertainties from linear regressions for isochron dating. Our new approach makes no prior assumption about the causes of variability in the derived chronological results and propagates uncertainties from both experimental measurements(analytical uncertainties) and underlying assumptions(model uncertainties) into the final age determination.Using synthetic examples, we find that although the estimates of the slope and y-intercept(hence age and initial isotopic ratios) are comparable between the Monte Carlo method and the benchmark‘‘Isoplot' algorithm, uncertainties from the later could be underestimated by up to 60%, which are likely due to an incomplete propagation of model uncertainties. An additional advantage of the new method is its ability to integrate with geological information to yield refined chronological constraints. The new method presented here is specifically designed to fully propagate errors in geochronological applications involves linear regressions such as Rb-Sr, Sm-Nd, Re-Os, Pt-Os, Lu-Hf, U-Pb(with discordant points),Pb-Pb and Ar-Ar.展开更多
This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the infl...This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the influences of the multiscale spatial variability of soil properties on the probability of failure(P_f) of the slopes. In the proposed approach, the relationship between the factor of safety and the soil strength parameters characterized with spatial variability is approximated by the MARS, with the aid of Karhunen-Loeve expansion. MCS is subsequently performed on the established MARS model to evaluate Pf.Finally, a nominally homogeneous cohesive-frictional slope and a heterogeneous cohesive slope, which are both characterized with different spatial variabilities, are utilized to illustrate the proposed approach.Results showed that the proposed approach can estimate the P_f of the slopes efficiently in spatially variable soils with sufficient accuracy. Moreover, the approach is relatively robust to the influence of different statistics of soil properties, thereby making it an effective and practical tool for addressing slope reliability problems concerning time-consuming deterministic stability models with low levels of P_f.Furthermore, disregarding the multiscale spatial variability of soil properties can overestimate or underestimate the P_f. Although the difference is small in general, the multiscale spatial variability of the soil properties must still be considered in the reliability analysis of heterogeneous slopes, especially for those highly related to cost effective and accurate designs.展开更多
An imaging energetic electron spectrometer built by the Peking University team(BD-IES) onboard a Chinese navigation satellite in an inclined GEO orbit has been launched successfully in September 2015, which measures t...An imaging energetic electron spectrometer built by the Peking University team(BD-IES) onboard a Chinese navigation satellite in an inclined GEO orbit has been launched successfully in September 2015, which measures the spectra of the energetic electrons with the energy range of 50–600 keV in nine directions. In this study, Monte Carlo simulations of the BD-IES sensor head were performed using Geant4 and the corresponding characteristic responses to the isotropic energetic particles were derived. The effective geometric factors were estimated using the typical electron and proton spectra in the GEO orbit and the corresponding simulated sensor head responses. It was found that the average effective geometric factors of nine directions are close to the nominal geometric factors calculated with the traditional method, but the effective geometric factor decreases as the center energy of the energy channel decreases. The BD-IES sensor head also responses to the energetic protons, but the average contamination rate of all 72 channels is about 2%, which means that the proton contamination is acceptable. The spectra of the energetic electrons measured by BD-IES are derived using the effective geometric factors of the sensor head and are comparable with the spectra measured by the magnetic electron ion spectrometer(MagEIS) instrument onboard Van Allen Probes.展开更多
Multiple analytical methods and Monte Carlo simulations were performed to evaluate neutron penetration in straight and curved labyrinths. Factors studied included variations in beam losses of off-axis point source,on-...Multiple analytical methods and Monte Carlo simulations were performed to evaluate neutron penetration in straight and curved labyrinths. Factors studied included variations in beam losses of off-axis point source,on-axis point source,and line source. For the straight labyrinth, it was found that the analytical expressions neglect the dose rate platform appearing at the bend of the labyrinth, and the agreement between analytical methods and Monte Carlo estimation was related to the type of neutron source term. For the curved labyrinth, the neutron attenuation length obtained under different conditions was nearly identical and appeared to be in quite good accord with the empirical formula calculation. Moreover, the neutron energy spectra along the centerline distance of the labyrinth were also analyzed. In the first leg, differences in beam loss led to variance in the distribution of spectra,while in the second and subsequent legs, the spectra were similar, where the main contributors were thermal neutrons. This work is valuable for practical design of the labyrinths in the accelerator facilities.展开更多
We study the magnetic properties of the double perovskite ruthenate compound Sr2YRuO6 using Monte Carlo simulations(MCS).We elaborate the ground state phase diagrams for all possible and stable configurations.The magn...We study the magnetic properties of the double perovskite ruthenate compound Sr2YRuO6 using Monte Carlo simulations(MCS).We elaborate the ground state phase diagrams for all possible and stable configurations.The magnetizations and the susceptibilities as a function of temperature for the studied system are also reported.The effects of the exchange coupling interactions and the crystal field are examined and discussed.On the other hand, since the compound Sr2YRuO6 exhibits an antiferromagnetic behavior, we find its Néel temperature, TN≈ 31 K, which is in good agreement with the experimental results in the literature.To complete this study, the hysteresis loops and the coercive field as a function of the external magnetic field are also obtained for fixed values of the physical parameters.展开更多
Stochastic gradient Markov chain Monte Carlo(SG-MCMC)has been developed as a flexible family of scalable Bayesian sampling algorithms.However,there has been little theoretical analysis of the impact of minibatch size ...Stochastic gradient Markov chain Monte Carlo(SG-MCMC)has been developed as a flexible family of scalable Bayesian sampling algorithms.However,there has been little theoretical analysis of the impact of minibatch size to the algorithm’s convergence rate.In this paper,we prove that at the beginning of an SG-MCMC algorithm,i.e.,under limited computational budget/time,a larger minibatch size leads to a faster decrease of the mean squared error bound.The reason for this is due to the prominent noise in small minibatches when calculating stochastic gradients,motivating the necessity of variance reduction in SG-MCMC for practical use.By borrowing ideas from stochastic optimization,we propose a simple and practical variance-reduction technique for SG-MCMC,that is efficient in both computation and storage.More importantly,we develop the theory to prove that our algorithm induces a faster convergence rate than standard SG-MCMC.A number of large-scale experiments,ranging from Bayesian learning of logistic regression to deep neural networks,validate the theory and demonstrate the superiority of the proposed variance-reduction SG-MCMC framework.展开更多
The variational and diffusion Monte Carlo approaches are used to study the ground-state properties of a hydrogen molecular ion in a spheroidal box.In this work,we successfully treat the zero-point motion of protons in...The variational and diffusion Monte Carlo approaches are used to study the ground-state properties of a hydrogen molecular ion in a spheroidal box.In this work,we successfully treat the zero-point motion of protons in the same formalism with as of electrons and avoid the Born–Oppenheimer approximation in density function theory.The study shows that the total energy increases with the decrease in volume,and that the distance between protons decreases as the pressure increases.Considering the motion of protons,the kinetic energy of the electron is higher than that of the fixed model under the same conditions and increases by 5%.The kinetic energy of the proton is found to be small under high pressure,which is only a fraction of the kinetic energy of the electron.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant Nos. 91748104,U1811463, 61632006,61425002,and 61751203the National Key Research and Development Program of China under Grant No. 2018YFC0910506+1 种基金the Open Project Program of the State Key Laboratory of CAD&CG of Zhejiang University of China under Grant No. A1901the Open Research Fund of Beijing Key Laboratory of Big Data Technology for Food Safety Project under Grant No. BTBD-2018KF.
文摘In this paper, we present DEMC, a deep dual-encoder network to remove Monte Carlo noise efficiently while preserving details. Denoising Monte Carlo rendering is different from natural image denoising since inexpensive by-products (feature buffers) can be extracted in the rendering stage. Most of them are noise-free and can provide sufficient details for image reconstruction. However, these feature buffers also contain redundant information. Hence, the main challenge of this topic is how to extract useful information and reconstruct clean images. To address this problem, we propose a novel network structure, dual-encoder network with a feature fusion sub-network, to fuse feature buffers firstly, then encode the fused feature buffers and a noisy image simultaneously, and finally reconstruct a clean image by a decoder network. Compared with the state-of-the-art methods, our model is more robust on a wide range of scenes, and is able to generate satisfactory results in a significantly faster way.
基金supported by the Research Grants Council of the Hong Kong Special Administrative Region,under RGC General Research Fund(Project No.CUHK14217516).
文摘Learning-based techniques have recently been shown to be effective for denoising Monte Carlo rendering methods. However, there remains a quality gap to state-of-the-art handcrafted denoisers. In this paper, we propose a deep residual learning based method that outperforms both state-of-the-art handcrafted denoisers and learning-based denoisers.Unlike the indirect nature of existing learning-based methods(which e.g., estimate the parameters and kernel weights of an explicit feature based filter), we directly map the noisy input pixels to the smoothed output. Using this direct mapping formulation, we demonstrate that even a simple-and-standard ResNet and three common auxiliary features(depth, normal,and albedo) are sufficient to achieve high-quality denoising. This minimal requirement on auxiliary data simplifies both training and integration of our method into most production rendering pipelines. We have evaluated our method on unseen images created by a different renderer. Consistently superior quality denoising is obtained in all cases.
文摘The goal of this study is to provide a stochastic method to investigate the eff ects of the randomness of soil properties due to their natural spatial variability on the response spectra spatial variation at sites with varying conditions. For this purpose, Monte Carlo Simulations are used to include the variability of both incident ground motion and soil parameters in the response spectra by mean of an appropriate coherency loss function and a site-dependent transfer function, respectively. The approach is built on the assumption of vertical propagation of SH type waves in soil strata with uncertain parameters. The response spectra are obtained by numerical integration of the governing equation of a single-degree-of-freedom (SDOF) system under non-stationary site-dependent and spatially varying ground motion accelerations simulated with non-uniform spectral densities and coherency loss functions. Numerical examples showed that randomness of soil properties signifi cantly aff ects the amplitudes of the response spectra, indicating that as the heterogeneity induced by the randomness of the parameters of the medium increases, the spectral ordinates attenuate.
文摘Integration system is used to denote practices that combine systematic use of the land and technologies,in which forest species are used in conjunction with herbaceous plants and/or animals respecting a spatial or temporal arrangement.Knowing that this type of production seeks to balance ecological and economic factors,it is important to understand the financial benefits and risks involved in this production.Financial analysis,therefore,acts as an important analysis tool to foster this type of activity.The paper aimed to conduct analysis of investment risk of a crop-livestock-forestry system deployed in Brazil,comparing two different production scenarios,scenario I with 17 ha and scenario II with 25 ha.The risk analysis was performed using the Monte Carlo method and sensitivity analysis(by varying the factors:the discount rate,productivity and price).A cash flow was elaborated based on annual cost and revenues data of the agricultural crops(corn and soybeans),livestock and eucalyptus,using an interest rate of 6%per year.The results indicated that the optimal age for cutting the eucalyptus was at seven years on both scenarios;scenario I had better return on investment using deterministic and probabilistic methods;scenario I presents higher investments risks;there is a negative relation between discount rate and annualized net present value(ANPV);increased productivity of crops provides greater profitability to the system;there has been an increase in the economic viability of the system,as value has been added to the products.Monte Carlo method and the sensitivity analysis showed to be an appropriate tool to analyze the risk of crop-livestock-forestry systems,making it possible to foresee how the project will respond to possible scenarios.
基金The authors gratefully thank the Natural Sciences and Engineering Research Council of Canada (NSERC)(ID: 236482) for supporting this research.
文摘To gain a competitive edge within the international and compet让ive setting of coal markets, coal producers must find new ways of reducing costs. Increasing bench drilling efficiency and performance in open-cast coal mines has the potential to generate savings. Specifically, monitoring, analyzing, and optimizing the drilling operation can reduce drilling costs. For example, determining the optimal drill bit replacement time will help to achieve the desirable penetration rate. This paper presents a life data analysis of drill bits to fit a statistical distribution using failure records. These results are then used to formulate a cost minimization problem to estimate the drill bit replacement time using the evolutionary algorithm. The effect of cost on the uncertainty associated with replacement time is assessed through Monte-Carlo simulation. The relationship between the total expected replacement cost and replacement time is also presented. A case study shows that the proposed approach can be used to assist with designing a drill bit replacement schedule and minimize costs in open-cast coal mines.
基金the National Natural Science Foundation of China(11374034 and 11334012)Beijing Natural Science Foundation(1192011)+1 种基金support of HSCC of Beijing Normal Universitythe Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund.
文摘Using exact quantum Monte Carlo method,we examine the recent novel electronic states seen in magicangle graphene superlattices.From the Hubbard model on a double-layer honeycomb lattice with a rotation angleθ=1:08°,we reveal that an antiferromagnetically ordered Mott insulator emerges beyond a critical U_c at half filling,and with a small doping,the pairing with d+id symmetry dominates over other pairings at low temperature.The effective d+id pairing interaction strongly increases as the on-site Coulomb interaction increases,indicating that the superconductivity is driven by electron-electron correlation.Our non-biased numerical results demonstrate that the twisted bilayer graphene shares the similar superconducting mechanism of high temperature superconductors,which is a new and ideal platform for further investigating the strongly correlated phenomena.
文摘The magnetic properties of inverse ferrite (Fe^3+)[Fe^3+Co^2+]O4^2-,(Fe^3+)[Fe^3+Cu^2+]O4^2,( Fe^3+)[Fe^3+Fe^2+]O4^2,and (Fe^3+)[Fe^3+Ni^2+]O4^2- spinels have been studied using Monte Carlo simulation.We have also calculated the critical and Curie Weiss temperatures from the thermal magnetizations and inverse of magnetic susceptibilities for each system.Magnetic hysteresis cycles have been found for the four systems.Finally,we found the critical exponents associated with magnetization,magnetic susceptibility,and external magnetic field.Our results of critical and Curie Weiss temperatures are similar to those obtained by experiment results.The critical exponents are similar to those of known 3D-Ising model.
基金projects of China Ocean Research Mineral Resources R & D Association (COMRA) Special Foundation (DY135-R2-1-01, DY135-46)the Province/Jilin University Co-Construction Project-Funds for New Materials (SXGJSF2017-3).
文摘In order to solve the problem of the reliability of slope engineering due to complex uncertainties, the Monte Carlo simulation method is adopted. Based on the characteristics of sparse grid, an interpolation algorithm, which can be applied to high dimensional problems, is introduced. A surrogate model of high dimensional implicit function is established, which makes Monte Carlo method more adaptable. Finally, a reliability analysis method is proposed to evaluate the reliability of the slope engineering, and is applied in the Sau Mau Ping slope project in Hong Kong. The reliability analysis method has great theoretical and practical significance for engineering quality evaluation and natural disaster assessment.
基金the National Natural Science Foundation of China (11705071, 11875155, 11675069, 21327801)NSAF (U1830102)+2 种基金NSFC-Nuclear Technology Innovation Joint Fund (U1867213)the DSTI Foundation of Gansu (2018ZX-07)the Fundamental Research Funds for the Central Universities (lzujbky-2017-13.lzujbky-2018-bt09, lzujbky-2019-bt09).
文摘The potential-driving model is used to describe the driving potential distribution and to calculate the preneutron emission mass distributions for different incident energies in the 237 Np(n, f)reaction. The potential-driving model is implemented in Geant4 and used to calculate the fission-fragment yield distributions, kinetic energy distributions, fission neutron spectrum and the total nubar for the 237 Np(n, f)reaction. Compared with the built-in G4 ParaFissionModel, the calculated results from the potential-driving model are in better agreement with the experimental data and evaluated data. Given the good agreement with the experimental data, the potential-driving model in Geant4 can describe well the neutron-induced fission of actinide nuclei, which is very important for the study of neutron transmutation physics and the design of a transmutation system.
基金supported by the National Natural Science Foundation of China under Grant Nos. 51727804 and 51672223supported by the “111” project under grant No.B08040.
文摘Multi-layer connected self-organizing feature maps(SOFMs) and the associated learning procedure were proposed to achieve efficient recognition and clustering of messily grown nanowire morphologies. The network is made up by several paratactic 2-D SOFMs with inter-layer connections. By means of Monte Carlo simulations, virtual morphologies were generated to be the training samples. With the unsupervised inner-layer and inter-layer learning, the neural network can cluster different morphologies of messily grown nanowires and build connections between the morphological microstructure and geometrical features of nanowires within. Then, the as-proposed networks were applied on recognitions and quantitative estimations of the experimental morphologies. Results show that the as-trained SOFMs are able to cluster the morphologies and recognize the average length and quantity of the messily grown nanowires within. The inter-layer connections between winning neurons on each competitive layer have significant influence on the relations between the microstructure of the morphology and physical parameters of the nanowires within.
基金the National Natural Science Foundation of China under Grant Nos.11204045,11464004,and 11864006the State Scholarship Fund(20173015)Guizhou Scientific and Technological Program(20185781).
文摘Sharp bending as one of the mechanical properties of double-stranded DNA(dsDNA) on the nanoscale is essential for biological functions and processes. Force sensors with optical readout have been designed to measure the forces inside short, strained loops composed of both dsDNA and single-stranded DNA(ssDNA). Recent FRET singlemolecule experiments were carried out based on the same force sensor design, but provided totally contrary results. In the current work, Monte Carlo simulations were performed under three conditions to clarify the discrepancy between the two experiments. The criterion that the work done by the force exerted on dsDNA by ssDNA should be larger than the nearest-neighbor(NN) stacking interaction energy is used to identify the generation of the fork at the junction of dsDNA and ssDNA. When the contour length of dsDNA in the sensor is larger than its critical length, the fork begins to generate at the junction of dsDNA and ssDNA, even with a kink in dsDNA. The forces inferred from simulations under three conditions are consistent with the ones inferred from experiments, including extra large force and can be grouped into two different states, namely, fork states and kink states. The phase diagrams constructed in the phase space of the NN stacking interaction energy and excited energy indicate that the transition between the fork state and kink state is difficult to identify in the phase space with an ultra small or large number of forks, but it can be detected in the phase space with a medium number of forks and kinks.
基金Supported by the National Natural Science Foundation of China under Grant No 11274393the National Basic Research Program of China under Grant No 2013CB933601the National Key Research and Development Program of China under Grant No 2016YFA0202001.
文摘An absorption-desorption model with long-ranged interaction is simulated by the dynamic Monte Carlo method.The dynamic process has an inert phase and an active phase that is controlled by the absorption rate.In the active phase,the number of vacancies increases with time exponentially,while in the inert phase the vacant sites will be occupied by adsorbates rapidly.At the critical absorption rate,both the number of vacancies and the time-depending active probability exhibit power-law behavior.We determine the critical absorption rate and the scaling exponents of the power-laws.The effect of the interaction range of desorption on the critical exponents is investigated.In the short-ranged interaction limit, the critical exponents of Schlogl’s first model are recovered.The model may describe the sta bility of the inner Helmholtz layer,an essential component of the electrochemical double-layer capacitor at a nanowire.
基金supported by National Major Project(Grant No.2017ZX03001002004)National Natural Science Foundation of China(Grant No.61521061)333 Program of Jiangsu(Grant No.BRA2017366).
文摘Dear editor,Polar codes can achieve the symmetric capacity of binary-input memoryless channels with infinite code length under successive cancellation(SC)decoding(1)Cyclic redundancy check(CRC)aids in successive cancellation list(CA-SCL)[2,3]and a decoder is proposed to improve the finite length performance of polar codes.To achieve the spectrum efficiency required by next generation wireless networks,it is essential to combine polar codes with higher order modulation.
基金the State Key Laboratory of Lithospheric Evolution,Institute of Geology and Geophysics,Chinese Academy of Sciences(SKL-K201706)the total endowment fundYale University for support.
文摘Geochronology is essential for understanding Earth’s history. The availability of precise and accurate isotopic data is increasing;hence it is crucial to develop transparent and accessible data reduction techniques and tools to transform raw mass spectrometry data into robust chronological data. Here we present a Monte Carlo sampling approach to fully propagate uncertainties from linear regressions for isochron dating. Our new approach makes no prior assumption about the causes of variability in the derived chronological results and propagates uncertainties from both experimental measurements(analytical uncertainties) and underlying assumptions(model uncertainties) into the final age determination.Using synthetic examples, we find that although the estimates of the slope and y-intercept(hence age and initial isotopic ratios) are comparable between the Monte Carlo method and the benchmark‘‘Isoplot' algorithm, uncertainties from the later could be underestimated by up to 60%, which are likely due to an incomplete propagation of model uncertainties. An additional advantage of the new method is its ability to integrate with geological information to yield refined chronological constraints. The new method presented here is specifically designed to fully propagate errors in geochronological applications involves linear regressions such as Rb-Sr, Sm-Nd, Re-Os, Pt-Os, Lu-Hf, U-Pb(with discordant points),Pb-Pb and Ar-Ar.
基金The Hong Kong Polytechnic University through the project RU3YResearch Grant Council through the project PolyU 5128/13E+1 种基金National Natural Science Foundation of China(Grant No.51778313)Cooperative Innovation Center of Engineering Construction and Safety in Shangdong Blue Economic Zone.
文摘This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the influences of the multiscale spatial variability of soil properties on the probability of failure(P_f) of the slopes. In the proposed approach, the relationship between the factor of safety and the soil strength parameters characterized with spatial variability is approximated by the MARS, with the aid of Karhunen-Loeve expansion. MCS is subsequently performed on the established MARS model to evaluate Pf.Finally, a nominally homogeneous cohesive-frictional slope and a heterogeneous cohesive slope, which are both characterized with different spatial variabilities, are utilized to illustrate the proposed approach.Results showed that the proposed approach can estimate the P_f of the slopes efficiently in spatially variable soils with sufficient accuracy. Moreover, the approach is relatively robust to the influence of different statistics of soil properties, thereby making it an effective and practical tool for addressing slope reliability problems concerning time-consuming deterministic stability models with low levels of P_f.Furthermore, disregarding the multiscale spatial variability of soil properties can overestimate or underestimate the P_f. Although the difference is small in general, the multiscale spatial variability of the soil properties must still be considered in the reliability analysis of heterogeneous slopes, especially for those highly related to cost effective and accurate designs.
基金the National Natural Science Foundation of China (Grant Nos. 41374167, 41421003)the Major Project of Chinese National Programs for Fundamental Research and Development (Grant No. 2012CB825603).
文摘An imaging energetic electron spectrometer built by the Peking University team(BD-IES) onboard a Chinese navigation satellite in an inclined GEO orbit has been launched successfully in September 2015, which measures the spectra of the energetic electrons with the energy range of 50–600 keV in nine directions. In this study, Monte Carlo simulations of the BD-IES sensor head were performed using Geant4 and the corresponding characteristic responses to the isotropic energetic particles were derived. The effective geometric factors were estimated using the typical electron and proton spectra in the GEO orbit and the corresponding simulated sensor head responses. It was found that the average effective geometric factors of nine directions are close to the nominal geometric factors calculated with the traditional method, but the effective geometric factor decreases as the center energy of the energy channel decreases. The BD-IES sensor head also responses to the energetic protons, but the average contamination rate of all 72 channels is about 2%, which means that the proton contamination is acceptable. The spectra of the energetic electrons measured by BD-IES are derived using the effective geometric factors of the sensor head and are comparable with the spectra measured by the magnetic electron ion spectrometer(MagEIS) instrument onboard Van Allen Probes.
基金the National Key R&D Program of China (No.2017YFC0107700).
文摘Multiple analytical methods and Monte Carlo simulations were performed to evaluate neutron penetration in straight and curved labyrinths. Factors studied included variations in beam losses of off-axis point source,on-axis point source,and line source. For the straight labyrinth, it was found that the analytical expressions neglect the dose rate platform appearing at the bend of the labyrinth, and the agreement between analytical methods and Monte Carlo estimation was related to the type of neutron source term. For the curved labyrinth, the neutron attenuation length obtained under different conditions was nearly identical and appeared to be in quite good accord with the empirical formula calculation. Moreover, the neutron energy spectra along the centerline distance of the labyrinth were also analyzed. In the first leg, differences in beam loss led to variance in the distribution of spectra,while in the second and subsequent legs, the spectra were similar, where the main contributors were thermal neutrons. This work is valuable for practical design of the labyrinths in the accelerator facilities.
文摘We study the magnetic properties of the double perovskite ruthenate compound Sr2YRuO6 using Monte Carlo simulations(MCS).We elaborate the ground state phase diagrams for all possible and stable configurations.The magnetizations and the susceptibilities as a function of temperature for the studied system are also reported.The effects of the exchange coupling interactions and the crystal field are examined and discussed.On the other hand, since the compound Sr2YRuO6 exhibits an antiferromagnetic behavior, we find its Néel temperature, TN≈ 31 K, which is in good agreement with the experimental results in the literature.To complete this study, the hysteresis loops and the coercive field as a function of the external magnetic field are also obtained for fixed values of the physical parameters.
文摘Stochastic gradient Markov chain Monte Carlo(SG-MCMC)has been developed as a flexible family of scalable Bayesian sampling algorithms.However,there has been little theoretical analysis of the impact of minibatch size to the algorithm’s convergence rate.In this paper,we prove that at the beginning of an SG-MCMC algorithm,i.e.,under limited computational budget/time,a larger minibatch size leads to a faster decrease of the mean squared error bound.The reason for this is due to the prominent noise in small minibatches when calculating stochastic gradients,motivating the necessity of variance reduction in SG-MCMC for practical use.By borrowing ideas from stochastic optimization,we propose a simple and practical variance-reduction technique for SG-MCMC,that is efficient in both computation and storage.More importantly,we develop the theory to prove that our algorithm induces a faster convergence rate than standard SG-MCMC.A number of large-scale experiments,ranging from Bayesian learning of logistic regression to deep neural networks,validate the theory and demonstrate the superiority of the proposed variance-reduction SG-MCMC framework.
基金the National Key R&D Program of China (Grant No.2018YFA0305900)the National Natural Science Foundation of China (Grant Nos.51632002,51572108,91745203,11634004,11174102,and 1174121)+2 种基金the National Key Research and Development Program of China (Grant No.2016YFB0201204)the Program for Changjiang Scholars and Innovative Research Team in University,China (Grant No.IRT 15R23)the National Fund for Fostering Talents of Basic Science,China (Grant No.J1103202).
文摘The variational and diffusion Monte Carlo approaches are used to study the ground-state properties of a hydrogen molecular ion in a spheroidal box.In this work,we successfully treat the zero-point motion of protons in the same formalism with as of electrons and avoid the Born–Oppenheimer approximation in density function theory.The study shows that the total energy increases with the decrease in volume,and that the distance between protons decreases as the pressure increases.Considering the motion of protons,the kinetic energy of the electron is higher than that of the fixed model under the same conditions and increases by 5%.The kinetic energy of the proton is found to be small under high pressure,which is only a fraction of the kinetic energy of the electron.