scholarly journals A Comprehensive Planning Framework for Urban Inland Oil Spill Management

2021 ◽  
Author(s):  
Marija Eric
Keyword(s):  
Monte Carlo ◽  
Travel Time ◽  
Oil Spill ◽  
Overland Flow ◽  
Hot Spot ◽  
Series Data ◽  
Comprehensive Planning ◽  
Planning Framework ◽  
Simulation Results ◽  
Storm Sewer

Oil spills occurring on land have accounted for at least one third or over 24,000 of all land spills (approximately 76,000) of various substances reported in Ontario from 1988 to 2013. The objective of this research was to develop a comprehensive planning framework for urban inland oil spill management encompassing all three stages of spill management: (1) prevention, (2) control and (3) response. An inland oil spill database was developed and the source of each spill was analyzed. Preliminary analyses determined that approximately 46 % of spills occur at fixed locations (stationary spills), 21 % of spills involve moving vehicles (transportation-related), 13 % involve moving vehicle accidents (transportation-related accidents) and 20 % were categorized as other kinds of spills. Sub-databases were developed for both stationary and transportation-related spills which include numeric and non-numeric data variables. Hot spot analyses (optimized version) were performed on a subset of transportation-related spills to develop a highway spill model. The highway spill model illustrates that the majority of highway spills (75 %) occur at interchanges and the remaining spills occur either on the highway (8 %) or at unknown locations (17%). A macro program was developed to simulate future spill events based on historical spill events of gasoline spills within the case study area. The variables under study were fitted with distributions and Monte Carlo or Iman Conover methods were used to generate simulation results spreadsheets of spill series data based on the fitted distributions. The final macro program generated 30,000 simulation results spreadsheets and compiled the results in an aggregate spreadsheet. Descriptive statistics of the numeric variables were calculated and used to recommend spill management strategies. A simulation results spreadsheet with predicted spill records was used to develop a Geographic Information Systems (GIS) model to delineate spill pathways and calculate travel-time for overland flow and channel flow within the storm sewer system (geometric network). The model delineates the overland spill path and traces the spill path through the storm sewer network. The travel-time for each type of path is calculated and can be summed to determine the total travel-time for each predicted spill. Keywords: inland oil spill, comprehensive planning framework, spill management, prevention, control, response, stationary, transportation-related, hot spot analysis, macro program, Monte Carlo, Iman Conover, simulation, GIS, travel-time, spill path, geometric network

scholarly journals A Comprehensive Planning Framework for Urban Inland Oil Spill Management

2021 ◽  
Author(s):  
Marija Eric
Keyword(s):  
Monte Carlo ◽  
Travel Time ◽  
Oil Spill ◽  
Overland Flow ◽  
Hot Spot ◽  
Series Data ◽  
Comprehensive Planning ◽  
Planning Framework ◽  
Simulation Results ◽  
Storm Sewer

Oil spills occurring on land have accounted for at least one third or over 24,000 of all land spills (approximately 76,000) of various substances reported in Ontario from 1988 to 2013. The objective of this research was to develop a comprehensive planning framework for urban inland oil spill management encompassing all three stages of spill management: (1) prevention, (2) control and (3) response. An inland oil spill database was developed and the source of each spill was analyzed. Preliminary analyses determined that approximately 46 % of spills occur at fixed locations (stationary spills), 21 % of spills involve moving vehicles (transportation-related), 13 % involve moving vehicle accidents (transportation-related accidents) and 20 % were categorized as other kinds of spills. Sub-databases were developed for both stationary and transportation-related spills which include numeric and non-numeric data variables. Hot spot analyses (optimized version) were performed on a subset of transportation-related spills to develop a highway spill model. The highway spill model illustrates that the majority of highway spills (75 %) occur at interchanges and the remaining spills occur either on the highway (8 %) or at unknown locations (17%). A macro program was developed to simulate future spill events based on historical spill events of gasoline spills within the case study area. The variables under study were fitted with distributions and Monte Carlo or Iman Conover methods were used to generate simulation results spreadsheets of spill series data based on the fitted distributions. The final macro program generated 30,000 simulation results spreadsheets and compiled the results in an aggregate spreadsheet. Descriptive statistics of the numeric variables were calculated and used to recommend spill management strategies. A simulation results spreadsheet with predicted spill records was used to develop a Geographic Information Systems (GIS) model to delineate spill pathways and calculate travel-time for overland flow and channel flow within the storm sewer system (geometric network). The model delineates the overland spill path and traces the spill path through the storm sewer network. The travel-time for each type of path is calculated and can be summed to determine the total travel-time for each predicted spill. Keywords: inland oil spill, comprehensive planning framework, spill management, prevention, control, response, stationary, transportation-related, hot spot analysis, macro program, Monte Carlo, Iman Conover, simulation, GIS, travel-time, spill path, geometric network

Coping with uncertainties in integrated urban water management

1997 ◽  
Vol 36 (8-9) ◽  
pp. 265-269
Author(s):  
Govert D. Geldof
Keyword(s):  
Water Management ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Interdisciplinary Approach ◽  
Urban Water ◽  
Urban Water Management ◽  
Integrated Water Management ◽  
Good Design ◽  
Management Techniques ◽  
Simulation Results

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.

scholarly journals Cheating at Craps

2021 ◽  
Vol 48 (4) ◽  
pp. 53-61
Author(s):  
Andrea Marin ◽  
Carey Williamson
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Modeling And Simulation ◽  
Analytical Model ◽  
Quantitative Evaluation ◽  
Mathematical Analysis ◽  
Simulation Modeling ◽  
Analytical Modeling ◽  
The World ◽  
Simulation Results

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.

scholarly journals A Comparison of Different Data-driven Procedures to Determine the Bunching Window

2021 ◽  
Vol 49 (2) ◽  
pp. 262-293
Author(s):  
Vincent Dekker ◽  
Karsten Schweikert
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Income Distribution ◽  
Prior Information ◽  
Structural Breaks ◽  
Data Driven ◽  
Taxable Income ◽  
Counterfactual Models ◽  
Simulation Results ◽  
Second Procedure

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.

scholarly journals The effect of social distancing on the reach of an epidemic in social networks

2021 ◽  
Author(s):  
Gregory Gutin ◽  
Tomohiro Hirano ◽  
Sung-Ha Hwang ◽  
Philip R. Neary ◽  
Alexis Akira Toda
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Social Networks ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Disease Transmission ◽  
Global Level ◽  
Social Distancing ◽  
The Public ◽  
Simulation Results

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.

Should a hotter paramagnet transform quicker to a ferromagnet? Monte Carlo simulation results for Ising model

2021 ◽  
Author(s):  
Subir K Das ◽  
Nalina Vadakkayil
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Ising Model ◽  
Simulation Results ◽  
Heating Up

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...

scholarly journals Monte Carlo Modeling and Design of Photon Energy Attenuation Layers for >10× Quantum Yield Enhancement in Si-Based Hard X-ray Detectors

Instruments ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 17
Author(s):  
Eldred Lee ◽  
Kaitlin M. Anagnost ◽  
Zhehui Wang ◽  
Michael R. James ◽  
Eric R. Fossum ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Quantum Yield ◽  
Photon Energy ◽  
High Efficiency ◽  
High Energy ◽  
Yield Enhancement ◽  
X Ray ◽  
Simulation Results ◽  
Conversion Efficiencies

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.

Polymer Loop Formation on a Functionalized Hard Surface: Quantitative Insight by Comparison of Experimental and Monte Carlo Simulation Results

Langmuir ◽  
2010 ◽  
Vol 26 (1) ◽  
pp. 202-209 ◽  
Author(s):  
Zhenyu Haung ◽  
Haining Ji ◽  
Jimmy Mays ◽  
Mark Dadmun ◽  
Grant Smith ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Loop Formation ◽  
Hard Surface ◽  
Simulation Results

Some statistical aspects of the estimation of seismic travel times

1968 ◽  
Vol 58 (4) ◽  
pp. 1243-1260 ◽  
Author(s):  
William Tucker ◽  
Eugene Herrin ◽  
Helen W. Freedman
Keyword(s):  
Monte Carlo ◽  
Least Squares ◽  
Travel Time ◽  
Iterative Process ◽  
Iterative Technique ◽  
Absolute Minimum ◽  
Station Corrections ◽  
Monte Carlo Studies ◽  
Confidence Ellipses ◽  
Large Earthquakes

Abstract Some of the statistical aspects of estimating travel-time anomalies and station corrections are considered. In order to estimate these quantities using earthquake data the events themselves must first be located. We investigated the use of the Gauss-Newton iterative technique to obtain a least-squares epicenter location employing Monte Carlo methods. Results of these studies indicate that the Gauss-Newton process converges to an absolute minimum and that confidence ellipses computed by linear techniques are reliable for reasonable networks of well-distributed stations. Also the Monte Carlo studies indicate that a least-squares solution may be inaccurate if appreciable travel-time anomalies or station-error means exist. We then expanded the location procedure to include the estimation of travel-time anomalies and station corrections. In order to obtain these estimates data from some 278 large earthquakes were analyzed by using a modified Seidel iterative process.

scholarly journals Sign-Problem-Free Fermionic Quantum Monte Carlo: Developments and Applications

2019 ◽  
Vol 10 (1) ◽  
pp. 337-356 ◽  
Author(s):  
Zi-Xiang Li ◽  
Hong Yao
Keyword(s):  
Monte Carlo ◽  
Quantum Monte Carlo ◽  
Hot Spot ◽  
High Temperature Superconductors ◽  
System Size ◽  
Many Body ◽  
Broken Symmetries ◽  
Sign Problem ◽  
Universal Quantum ◽  
Many Body Systems

Reliable simulations of correlated quantum systems, including high-temperature superconductors and frustrated magnets, are increasingly desired nowadays to further our understanding of essential features in such systems. Quantum Monte Carlo (QMC) is a unique numerically exact and intrinsically unbiased method to simulate interacting quantum many-body systems. More importantly, when QMC simulations are free from the notorious fermion sign problem, they can reliably simulate interacting quantum models with large system size and low temperature to reveal low-energy physics such as spontaneously broken symmetries and universal quantum critical behaviors. Here, we concisely review recent progress made in developing new sign-problem-free QMC algorithms, including those employing Majorana representation and those utilizing hot-spot physics. We also discuss applications of these novel sign-problem-free QMC algorithms in simulations of various interesting quantum many-body models. Finally, we discuss possible future directions of designing sign-problem-free QMC methods.

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