Monte Carlo Simulation of Optical Temperature Sensors in RTP Systems

1995 ◽  
Vol 387 ◽  
Author(s):  
J. Vernon Cole ◽  
Karson L. Knutson ◽  
Anthony T. Fiory ◽  
Klavs F. Jensen

AbstractWe present simulation and experimental results for determining the distribution of radiation throughout an RTP system and evaluating the design of optical temperature sensors. The simulations are performed with a general purpose, three dimensional Monte Carlo method. The simulation models internal reflection, absorption, and transmission within participating media explicitly, and includes wavelength, temperature, and material dependent properties. Simulation results are compared to measurements of the lamp intensity profile within the lamphouse and at possible sensor locations. Simulations are used to examine the effect of several optical probe designs. The predicted responses of potential sensor designs resulting from these studies are presented.

1994 ◽  
Vol 342 ◽  
Author(s):  
J. Vernon Cole ◽  
Karson L. Knutson ◽  
Klavs F. Jensen

ABSTRACTWe present a general purpose Monte Carlo method for the simulation of radiation heat transfer in rapid thermal processing (RTP) chambers. Three-dimensional mesh generation software is used to discretize the surfaces within the system, allowing the simulation of realistic chamber and reflector designs. An adaptive subdivision of the chamber geometry reduces the number of raysurface intersections which must be computed. The method models internal reflection, absorption, and transmission within participating media, and includes wavelength, temperature, and material dependent optical properties. Radiation heat transfer simulations are used to examine a reflector assembly, and to test the assumptions of optical wafer temperature measurement techniques.


1997 ◽  
Vol 36 (8-9) ◽  
pp. 265-269
Author(s):  
Govert D. Geldof

In the practice of integrated water management we meet complexity, subjectivity and uncertainties. Uncertainties come into play when new urban water management techniques are applied. The art of a good design is not to reduce uncertainties as much as possible, but to find the middle course between cowardice and recklessness. This golden mean represents bravery. An interdisciplinary approach is needed to reach consensus. Calculating uncertainties by using Monte Carlo simulation results may be helpful.


2021 ◽  
pp. 107962
Author(s):  
Julio Almansa ◽  
Francesc Salvat-Pujol ◽  
Gloria Díaz-Londoño ◽  
Artur Carnicer ◽  
Antonio M. Lallena ◽  
...  

2021 ◽  
Vol 48 (4) ◽  
pp. 53-61
Author(s):  
Andrea Marin ◽  
Carey Williamson

Craps is a simple dice game that is popular in casinos around the world. While the rules for Craps, and its mathematical analysis, are reasonably straightforward, this paper instead focuses on the best ways to cheat at Craps, by using loaded (biased) dice. We use both analytical modeling and simulation modeling to study this intriguing dice game. Our modeling results show that biasing a die away from the value 1 or towards the value 5 lead to the best (and least detectable) cheating strategies, and that modest bias on two loaded dice can increase the winning probability above 50%. Our Monte Carlo simulation results provide validation for our analytical model, and also facilitate the quantitative evaluation of other scenarios, such as heterogeneous or correlated dice.


2021 ◽  
Vol 49 (2) ◽  
pp. 262-293
Author(s):  
Vincent Dekker ◽  
Karsten Schweikert

In this article, we compare three data-driven procedures to determine the bunching window in a Monte Carlo simulation of taxable income. Following the standard approach in the empirical bunching literature, we fit a flexible polynomial model to a simulated income distribution, excluding data in a range around a prespecified kink. First, we propose to implement methods for the estimation of structural breaks to determine a bunching regime around the kink. A second procedure is based on Cook’s distances aiming to identify outlier observations. Finally, we apply the iterative counterfactual procedure proposed by Bosch, Dekker, and Strohmaier which evaluates polynomial counterfactual models for all possible bunching windows. While our simulation results show that all three procedures are fairly accurate, the iterative counterfactual procedure is the preferred method to detect the bunching window when no prior information about the true size of the bunching window is available.


Author(s):  
Gregory Gutin ◽  
Tomohiro Hirano ◽  
Sung-Ha Hwang ◽  
Philip R. Neary ◽  
Alexis Akira Toda

AbstractHow does social distancing affect the reach of an epidemic in social networks? We present Monte Carlo simulation results of a susceptible–infected–removed with social distancing model. The key feature of the model is that individuals are limited in the number of acquaintances that they can interact with, thereby constraining disease transmission to an infectious subnetwork of the original social network. While increased social distancing typically reduces the spread of an infectious disease, the magnitude varies greatly depending on the topology of the network, indicating the need for policies that are network dependent. Our results also reveal the importance of coordinating policies at the ‘global’ level. In particular, the public health benefits from social distancing to a group (e.g. a country) may be completely undone if that group maintains connections with outside groups that are not following suit.


Author(s):  
Subir K Das ◽  
Nalina Vadakkayil

For quicker formation of ice, before inserting inside a refrigerator, heating up of a body of water can be beneficial. We report first observation of a counterpart of this intriguing...


Instruments ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 17
Author(s):  
Eldred Lee ◽  
Kaitlin M. Anagnost ◽  
Zhehui Wang ◽  
Michael R. James ◽  
Eric R. Fossum ◽  
...  

High-energy (>20 keV) X-ray photon detection at high quantum yield, high spatial resolution, and short response time has long been an important area of study in physics. Scintillation is a prevalent method but limited in various ways. Directly detecting high-energy X-ray photons has been a challenge to this day, mainly due to low photon-to-photoelectron conversion efficiencies. Commercially available state-of-the-art Si direct detection products such as the Si charge-coupled device (CCD) are inefficient for >10 keV photons. Here, we present Monte Carlo simulation results and analyses to introduce a highly effective yet simple high-energy X-ray detection concept with significantly enhanced photon-to-electron conversion efficiencies composed of two layers: a top high-Z photon energy attenuation layer (PAL) and a bottom Si detector. We use the principle of photon energy down conversion, where high-energy X-ray photon energies are attenuated down to ≤10 keV via inelastic scattering suitable for efficient photoelectric absorption by Si. Our Monte Carlo simulation results demonstrate that a 10–30× increase in quantum yield can be achieved using PbTe PAL on Si, potentially advancing high-resolution, high-efficiency X-ray detection using PAL-enhanced Si CMOS image sensors.


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