Generalized Light Portals

2020 ◽  
Vol 3 (2) ◽  
pp. 1-19
Author(s):  
Shinji Ogaki
Keyword(s):  
Monte Carlo ◽  
Sampling Method ◽  
Sampling Strategy ◽  
Sampling Techniques ◽  
Two Dimensional ◽  
Multiple Importance Sampling ◽  
Path Tracing ◽  
Environment Map ◽  
Efficient Sampling ◽  
Polygon Meshes

Light portals are useful for accelerating the convergence of Monte Carlo path tracing when rendering interiors. However, they are generally limited to flat polygonal shapes. In this paper, we introduce a new concept that allows existing polygon meshes with arbitrary shaders in a scene to be used as generalized light portals. We also present an efficient sampling method that takes into account the pixel values of the environment map and ray guiding two-dimensional textures that are typically opacity or transparency maps. This novel sampling strategy can be combined with other sampling techniques by using multiple importance sampling.

scholarly journals Identification of Efficient Sampling Techniques for Probabilistic Voltage Stability Analysis of Renewable-Rich Power Systems

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2328
Author(s):  
Mohammed Alzubaidi ◽  
Kazi N. Hasan ◽  
Lasantha Meegahapola ◽  
Mir Toufikur Rahman
Keyword(s):  
Monte Carlo ◽  
Stability Analysis ◽  
Power Systems ◽  
Large Scale ◽  
Voltage Stability ◽  
Sampling Technique ◽  
Coefficient Of Determination ◽  
Sampling Techniques ◽  
Quasi Monte Carlo ◽  
Efficient Sampling

This paper presents a comparative analysis of six sampling techniques to identify an efficient and accurate sampling technique to be applied to probabilistic voltage stability assessment in large-scale power systems. In this study, six different sampling techniques are investigated and compared to each other in terms of their accuracy and efficiency, including Monte Carlo (MC), three versions of Quasi-Monte Carlo (QMC), i.e., Sobol, Halton, and Latin Hypercube, Markov Chain MC (MCMC), and importance sampling (IS) technique, to evaluate their suitability for application with probabilistic voltage stability analysis in large-scale uncertain power systems. The coefficient of determination (R2) and root mean square error (RMSE) are calculated to measure the accuracy and the efficiency of the sampling techniques compared to each other. All the six sampling techniques provide more than 99% accuracy by producing a large number of wind speed random samples (8760 samples). In terms of efficiency, on the other hand, the three versions of QMC are the most efficient sampling techniques, providing more than 96% accuracy with only a small number of generated samples (150 samples) compared to other techniques.

scholarly journals Monte Carlo based statistical timing analysis using an efficient sampling method

2016 ◽  
Vol 13 (24) ◽  
pp. 20160735-20160735
Author(s):  
Zhixi Yang ◽  
Jun Yang ◽  
Kefei Xing ◽  
Guang Yang
Keyword(s):  
Monte Carlo ◽  
Sampling Method ◽  
Timing Analysis ◽  
Statistical Timing Analysis ◽  
Efficient Sampling ◽  
Statistical Timing

Comparison of Two Methods for Sensitivity Analysis of Compressor Blades

2016 ◽  
Author(s):  
Robin Schmidt ◽  
Matthias Voigt ◽  
Konrad Vogeler ◽  
Marcus Meyer
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Polynomial Regression ◽  
Optical Measurement ◽  
Measurement Techniques ◽  
Sampling Strategy ◽  
Compressor Blades ◽  
Initial Flow ◽  
Efficient Sampling ◽  
The Impact

This paper will compare two approaches of sensitivity analysis, namely (i) the adjoint method which is used to obtain an initial estimate of the geometric sensitivity of the gas-washed surfaces to aerodynamic quantities of interest and (ii) a Monte Carlo-type simulation with an efficient sampling strategy. For both approaches the geometry is parameterized using a modified NACA parameterization. First the sensitivity of those parameters is calculated using the linear (first order) adjoint model. Since the effort of the adjoint CFD solution is comparable to that of the initial flow CFD solution and the sensitivity calculation is simply a postprocessing step, this approach yields fast results. However, it relies on a linear model which may not be adequate to describe the relationship between relevant aerodynamic quantities and actual geometric shape variations for the derived amplitudes of shape variations. In order to better capture nonlinear and interaction effects, secondly a Monte Carlo-type simulation with an efficient sampling strategy is used to carry out the sensitivity analysis. The sensitivities are expressed by means of the Coefficient of Importance, which is calculated based on modified polynomial regression and therefore able to describe relationships of higher order. The methods are applied to a typical high pressure compressor stage. The impact of a variable rotor geometry is calculated by 3D CFD simulations using a steady RANS model. The geometric variability of the rotor is based on the analysis of a set of 400 blades which have been measured using high-precision 3D optical measurement techniques.

scholarly journals Calculation of MIS Weights for Bidirectional Path Tracing with Photon Maps

2020 ◽  
Author(s):  
Sergey Ershov ◽  
Alexey Voloboy ◽  
Dmitriy Zhdanov ◽  
Andrey Zhdanov
Keyword(s):  
Integral Equation ◽  
Monte Carlo ◽  
Integral Operator ◽  
Closed Form ◽  
Ray Tracing ◽  
Importance Sampling ◽  
Multiple Importance Sampling ◽  
Path Tracing ◽  
Light Rays ◽  
Sphere Radius

A widely used method for noise reduction in Monte-Carlo ray tracing is combing different means of sampling, known as multiple importance sampling (MIS). For bi-directional Monte-Carlo ray tracing with photon maps (BDPM), the join paths are obtained by merging camera and light sub-paths, and since several light paths are checked again the same camera path, and vice versa, the join paths obtained are not statistically independent. Thus the noise in this method obeys laws different from those in simple classic Monte-Carlo with independent samples so the weights that minimize that noise must also be calculated differently. This paper drives that weights for the simplest case when we mix contribution from only two vertices of camera ray. It shows that the weights obey an integral equation which is qualitatively different from the well-known MIS formulae for uncorrelated samples. Besides that, even if forget the integral operator, the weights depend on the integration sphere radius and the number of light rays used. The integral equation is solved analytically in a closed form and it is demonstrated how to perform the necessary calculations in BDPM.

Comparison of Two Methods for Sensitivity Analysis of Compressor Blades

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Robin Schmidt ◽  
Matthias Voigt ◽  
Konrad Vogeler ◽  
Marcus Meyer
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Polynomial Regression ◽  
Optical Measurement ◽  
Measurement Techniques ◽  
Three Dimensional ◽  
Sampling Strategy ◽  
Initial Flow ◽  
Efficient Sampling ◽  
The Impact

This paper will compare two approaches of sensitivity analysis, namely (i) the adjoint method which is used to obtain an initial estimate of the geometric sensitivity of the gas-washed surfaces to aerodynamic quantities of interest and (ii) a Monte Carlo type simulation with an efficient sampling strategy. For both approaches, the geometry is parameterized using a modified NACA parameterization. First, the sensitivity of those parameters is calculated using the linear (first-order) adjoint model. Since the effort of the adjoint computational fluid dynamics (CFD) solution is comparable to that of the initial flow CFD solution and the sensitivity calculation is simply a postprocessing step, this approach yields fast results. However, it relies on a linear model which may not be adequate to describe the relationship between relevant aerodynamic quantities and actual geometric shape variations for the derived amplitudes of shape variations. Second, in order to better capture nonlinear and interaction effects, a Monte Carlo type simulation with an efficient sampling strategy is used to carry out the sensitivity analysis. The sensitivities are expressed by means of the coefficient of importance (CoI), which is calculated based on modified polynomial regression and therefore able to describe relationships of higher order. The methods are applied to a typical high-pressure compressor (HPC) stage. The impact of a variable rotor geometry is calculated by three-dimensional (3D) CFD simulations using a steady Reynolds-averaged Navier–Stokes model. The geometric variability of the rotor is based on the analysis of a set of 400 blades which have been measured using high-precision 3D optical measurement techniques.

An efficient sampling method for fast and accurate Monte Carlo Simulations

2016 ◽  
Vol 20 (2) ◽  
pp. 160-168 ◽  
Author(s):  
F. L. M. Diermanse ◽  
D. G. Carroll ◽  
J. V. L. Beckers ◽  
R. Ayre
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Sampling Method ◽  
Efficient Sampling

Structures and crystallization of vacuum-deposited amorphous Se and Sb films

1990 ◽  
Vol 48 (4) ◽  
pp. 140-141
Author(s):  
Makoto Shiojiri ◽  
Toshiyuki Isshiki ◽  
Tetsuya Fudaba ◽  
Yoshihiro Hirota
Keyword(s):  
Monte Carlo ◽  
Electron Microscope ◽  
Monte Carlo Method ◽  
Computer Program ◽  
Radial Distribution ◽  
Film Formation ◽  
Amorphous State ◽  
Two Dimensional ◽  
Amorphous Films ◽  
Binding Condition

In hexagonal Se crystal each atom is covalently bound to two others to form an endless spiral chain, and in Sb crystal each atom to three others to form an extended puckered sheet. Such chains and sheets may be regarded as one- and two- dimensional molecules, respectively. In this paper we investigate the structures in amorphous state of these elements and the crystallization.HRTEM and ED images of vacuum-deposited amorphous Se and Sb films were taken with a JEM-200CX electron microscope (Cs=1.2 mm). The structure models of amorphous films were constructed on a computer by Monte Carlo method. Generated atoms were subsequently deposited on a space of 2 nm×2 nm as they fulfiled the binding condition, to form a film 5 nm thick (Fig. 1a-1c). An improvement on a previous computer program has been made as to realize the actual film formation. Radial distribution fuction (RDF) curves, ED intensities and HRTEM images for the constructed structure models were calculated, and compared with the observed ones.

PENGARUH FAKTOR INTERNAL TERHADAP MINAT BERWIRAUSAHA MAHASISWA FAKULTAS EKONOMI DAN BISNIS UNIVERSITAS JAMBI

2019 ◽  
Vol 8 (1) ◽  
pp. 1-12
Author(s):  
Winda Syafitri ◽  
Dahmiri Dahmiri
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Sampling Method ◽  
Descriptive Analysis ◽  
Research Use ◽  
Sampling Techniques ◽  
Student Interest ◽  
Business Faculty ◽  
Internal Factors ◽  
Convenience Sampling

ABSTRAK The purpose of this research is to explain the effect of Internal Factors toward student interest in entrepreneurship on Economics and Business Faculty of Jambi University. Sampling techniques used on is Non-Probability Sampling with Convenience Sampling Method. The number of respondents is 100 consumers. Technique analysis for this research use descriptive analysis to describe the research variables and multiple regression analysis to find the effect between research variables using SPSS 20.0. This research revealed the significant effect of Internal Factors on Student Interest in entrepreneurship on Economics and business Faculty of Jambi University.   Keywords: Internal Factors, Interest in Entrepreneurship

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