performing a probabilistic study rather than a determinist one is a relatively easy way to quantify the uncertainty in an engineering design. due to the complexity and poor accuracy of the statistical moment methods, the monte carlo simulation (mcs) method is wildly used in an engineering design. in this work, an mcs-based reliability analysis was carried out for the stability of the chain pill...

one of the most important parameters used for determining the performance of tunnel boring machines (tbms) is their penetration rate. the parameters affecting the penetration rate can be divided in two categories. the first category is the controllable parameters such as the tbm technical characteristics, and type and geometry of the tunnel, and the second one is the uncontrollable parameters s...

background: the purpose of this study was to investigate the application of the monte carlo technique to calculate and analysis of dosimetric parameters for electron beams used in radiotherapy. this technique is based on statistical method and has a powerful role in different radiotherapy aspects. materials and methods: the simulated medical linear accelerator was the varian clinac 2100c. the e...

Citation: Thomazo C, Buoncristiani J-F, Vennin E, Pellenard P, Cocquerez T, Mugnier JL and Gérard E (2017) Geochemical Processes Leading to the Precipitation of Subglacial Carbonate Crusts at Bossons Glacier, Mont Blanc Massif (French Alps). Front. Earth Sci. 5:70. doi: 10.3389/feart.2017.00070 Geochemical Processes Leading to the Precipitation of Subglacial Carbonate Crusts at Bossons Glacier,...

Monte Carlo simulation is named after the city of Monte Carlo in Monaco, which is famous for gambling such as roulette, dice, and slot machines. Since the simulation process involves generating chance variables and exhibits random behaviors, it has been called Monte Carlo simulation. Monte Carlo simulation is a powerful statistical analysis tool and widely used in both non-engineering fields an...

The uniform random number can be manipulated to simulate the characteristics of any probability density function. For power system reliability analysis the exponential and the Weibull distributions are well suited. Simulated exponential and Weibull random variables can be obtained from uniform (0,1) RNs by making use of the fact that the cumulative density function (CDF) is uniform between zero...

Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies. We will review methods we have developed to perform QMC for the electrons coupled to another MC simulation for the ions. In this method, one estimates the Born-Oppenheimer energy E(Z) where Z repr...

Contemporary scientific studies often rely on the understanding of complex quantum systems via computer simulation. This paper initiates the statistical study of quantum simulation and proposes a Monte Carlo method for estimating analytically intractable quantities. We derive the bias and variance for the proposed Monte Carlo quantum simulation estimator and establish the asymptotic theory for ...