Influence of the dispersion number on the estimation of coliform removal in ponds

2003 ◽  
Vol 48 (2) ◽  
pp. 181-188 ◽  
Author(s):  
M. von Sperling
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Input Data ◽  
Flow Model ◽  
The Other ◽  
Empirical Equations ◽  
Input Variables ◽  
High Level ◽  
Dispersion Number

The paper uses the technique of Monte Carlo simulation in order to investigate the sensitivity to the Dispersion Number (d) of the effluent coliform concentration from facultative and maturation ponds. The Dispersion Number is one of the coefficients used in the dispersed-flow model for ponds. Initially, four empirical equations available in the literature for the estimation of d were compared, using the results from 1,000 runs of the Monte Carlo simulation. A second different set of Monte Carlo simulations (1,000 runs) was undertaken, allowing a sensitivity analysis of d, in conjunction with other coefficients and input data used in the design of facultative and maturation ponds (e.g., population, wastewater flow, coliform removal coefficient and others). The results of the simulations suggest that, when considering the high level of uncertainty in all input variables used in the design of the ponds for coliform removal, the Dispersion Number d does not present a greater influence in the model prediction, compared with the other input variables. Based on these considerations, it is likely that, for design purposes, simple models for the prediction of d can be used, without significantly affecting the estimation of the effluent coliform concentration, considering the existing uncertainty in all other input variables.

THE HARDNESS SPECTRUM OF QUARK- AND GLUON-JETS PRODUCED BY DIFFERENT FLAVOR QUARKS

2008 ◽  
Vol 23 (26) ◽  
pp. 4337-4343 ◽  
Author(s):  
FENG-GE TIAN ◽  
GANG CHEN ◽  
HUI-LING WEI
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Transverse Momentum ◽  
The Other ◽  
Other Hand ◽  
Gluon Jets ◽  
Quark Jets

The hardness properties of quark- and gluon-jets produced by different flavor quarks are compared in 3-jet events of e+e- collision generated with Monte Carlo Simulation Jetset 7.4 generator at [Formula: see text]. The 3-jet events are obtained using the Durham algorithm and the quark- and gluon-jets are identified by angular-method. The average values of transverse momentum 〈pt〉, multiplicity 〈N〉 and rapidity 〈y〉 versus hardness for quark- and gluon-jets of different flavors are compared. It turns out that the distributions of 〈pt〉, 〈N〉 and 〈y〉 versus hardness of quark-jets are different to their flavors, while those of the gluon-jets are insensitive to the flavors. On the other hand, the 〈pt〉 and 〈N〉 of quark- and gluon-jets are strong positive correlated with hardness, but the 〈y〉 of those are negatively correlated with hardness.

scholarly journals Practical Risk Assessment of Ground Vibrations Resulting from Blasting, Using Gene Expression Programming and Monte Carlo Simulation Techniques

2020 ◽  
Vol 10 (2) ◽  
pp. 472 ◽  
Author(s):  
Amir Mahdiyar ◽  
Danial Jahed Armaghani ◽  
Mohammadreza Koopialipoor ◽  
Ahmadreza Hedayat ◽  
Arham Abdullah ◽  
...  
Keyword(s):  
Gene Expression ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Gene Expression Programming ◽  
Sensitivity Analyses ◽  
Accurate Estimation ◽  
Blasting Operation ◽  
Simulation Techniques ◽  
Input Variables ◽  
The Impact

Peak particle velocity (PPV) is a critical parameter for the evaluation of the impact of blasting operations on nearby structures and buildings. Accurate estimation of the amount of PPV resulting from a blasting operation and its comparison with the allowable ranges is an integral part of blasting design. In this study, four quarry sites in Malaysia were considered, and the PPV was simulated using gene expression programming (GEP) and Monte Carlo simulation techniques. Data from 149 blasting operations were gathered, and as a result of this study, a PPV predictive model was developed using GEP to be used in the simulation. In order to ensure that all of the combinations of input variables were considered, 10,000 iterations were performed, considering the correlations among the input variables. The simulation results demonstrate that the minimum and maximum PPV amounts were 1.13 mm/s and 34.58 mm/s, respectively. Two types of sensitivity analyses were performed to determine the sensitivity of the PPV results based on the effective variables. In addition, this study proposes a method specific to the four case studies, and presents an approach which could be readily applied to similar applications with different conditions.

Risk Management of Construction Schedule by PERT with Monte Carlo Simulation

2014 ◽  
Vol 548-549 ◽  
pp. 1646-1650 ◽  
Author(s):  
Yang Liu ◽  
Yan Li
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Critical Path ◽  
Total Duration ◽  
Control Points ◽  
Schedule Management ◽  
Simulation Results ◽  
Critical Paths ◽  
Construction Schedule

It has been proved that the construction schedule management was an uncertain problem. Traditional CPM method was a good way to define the total duration and critical paths but can not solve uncertainty. The paper use CPM to define the duration and critical path firstly, then defined the parameters with Delphi and make Monte Carlo simulation. Through simulation results, it is found that the probability to finish the work on time was only 35.3%. The following step is to make sensitivity analysis, through the calculation, the work which has large influence was found and treat as key control points. It is proved that Monte Carlo simulation is useful to solve the problem of construction schedule management.

Spiegel Online

2017 ◽  
pp. 1-11
Author(s):  
Karl Schmedders ◽  
Armin Rott
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Web Site ◽  
Business Plan ◽  
Decision Makers ◽  
Bottom Line ◽  
Art Objects ◽  
Input Parameters ◽  
High Level ◽  
The Impact

Spiegel Online (www.spiegel.de) is the leading news Web site in Germany. The site was first designed to accompany Der Spiegel, one of Europe's largest and Germany's most influential weekly magazine, which has a weekly circulation of around one million. The site's content is produced by a team of more than fifty journalists writing in several categories: politics, business, networld, panorama, arts and entertainment, science, university, school, sports, travel, weather, and automobiles. The original content is complemented by articles purchased from news agencies and selected articles from the print edition. Spiegel-Verlag is a major contributor to the Hamburg Media School, which offers professional master's degree programs in Media Management (MBA), film, and journalism. In their second year, MBA students typically engage in consulting projects with major media companies. In a recent assignment, Spiegel Online posed two questions to the MBA team: are there any chances for an economically successful entry into the market for interactive classifieds? And if so, what should the business model look like in detail? A student team analyzed markets for classified ads and found one market segment that appeared to be particularly promising: the market for art objects. During the development of a business plan for a new venture in this market it became apparent that there is much uncertainty about the key input parameters to the business plan. As a result, it is very difficult to assess the viability of the business idea. How can the team properly account for the uncertain input parameters? What is the impact of this uncertainty on the bottom line? Will a Web site for art objects earn or lose money? How can the team communicate this uncertainty to a group of high-level decision makers who want a simple “go or no-go” recommendation?The objective is to make students aware of the applicability of Monte Carlo simulation to the analysis of complex business plans. Students should learn how to explicitly account for uncertain inputs in a business plan, how to assess the impact of uncertainty on the bottom line via Monte Carlo simulation, and how to communicate the results of their analysis to high-level decision makers.

scholarly journals Effective Assessment of Blast-Induced Ground Vibration Using an Optimized Random Forest Model Based on a Harris Hawks Optimization Algorithm

2020 ◽  
Vol 10 (4) ◽  
pp. 1403 ◽  
Author(s):  
Zhi Yu ◽  
Xiuzhi Shi ◽  
Jian Zhou ◽  
Xin Chen ◽  
Xianyang Qiu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Rock Mass ◽  
Random Forest ◽  
Particle Velocity ◽  
Ground Vibration ◽  
Accurate Method ◽  
Peak Particle Velocity ◽  
Simulation Approach ◽  
Input Variables

Most mines choose the drilling and blasting method which has the characteristics of being a cheap and efficient method to fragment rock mass, but blast-induced ground vibration damages the surrounding rock mass and structure and is a drawback. To predict, analyze and control the blast-induced ground vibration, the random forest (RF) model, Harris hawks optimization (HHO) algorithm and Monte Carlo simulation approach were utilized. A database consisting of 137 datasets was collected at different locations around the Tonglvshan open-cast mine, China. Seven variables were selected and collected as the input variables, and peak particle velocity was chosen as the output variable. At first, an RF model and a hybrid model, namely a HHO-RF model, were developed, and the prediction results checked by 3 performance indices to show that the proposed HHO-RF model can provide higher prediction performance. Then blast-induced ground vibration was simulated by using the Monte Carlo simulation approach and the developed HHO-RF model. After analyzing, the mean peak particle velocity value was 0.98 cm/s, and the peak particle velocity value did not exceed 1.95 cm/s with a probability of 90%. The research results of this study provided a simple, accurate method and basis for predicting, evaluating blast-induced ground vibration and optimizing the blast design before blast operation.

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