Prediction and mitigation of construction noise in an urban environment

2003 ◽  
Vol 30 (4) ◽  
pp. 659-672 ◽  
Author(s):  
A Gilchrist ◽  
E N Allouche ◽  
D Cowan
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Urban Areas ◽  
Deterministic Model ◽  
Field Measurements ◽  
Mitigation Strategies ◽  
Source Control ◽  
Construction Site ◽  
Noise Mitigation ◽  
Monte Carlo Simulation Technique

A growing number of construction projects are performed in congested urban areas. Often, the surrounding community finds these projects annoying because of noise, vibration, dust, light, and greenhouse gas emissions. This paper focuses on one type of irritant, noise. Common noise generators on construction sites are identified, and the elements of a generic program for mitigating construction-related noise are outlined. Mitigation strategies including source control, path control, and receiver control are discussed. A deterministic model based on the Monte Carlo simulation technique is used. It is capable of predicting the magnitude and frequency of noise levels generated by construction equipment at receptor locations around a construction site during each construction stage. The utilization of the model as a planning tool for optimizing the composition, geometry, and location of noise barriers around a construction site is demonstrated via a case history, namely the construction of an eight-storey parking garage in London, Ont. The model is validated by comparing its predictions to field measurements undertaken during various construction stages. Predictions agree favourably with field measurements.Key words: construction, noise, mitigation, barriers, modeling, Monte Carlo simulation.

On Using Monte Carlo Simulations for Project Risk Management

2016 ◽  
pp. 150-173
Author(s):  
Cristiana Tudor ◽  
Maria Tudor
Keyword(s):  
Monte Carlo Simulation ◽  
Risk Management ◽  
Monte Carlo ◽  
Decision Makers ◽  
Project Schedule ◽  
Project Risk ◽  
Monte Carlo Simulation Technique ◽  
Basic Probability ◽  
The Cost

This chapter covers the essentials of using the Monte Carlo Simulation technique (MSC) for project schedule and cost risk analysis. It offers a description of the steps involved in performing a Monte Carlo simulation and provides the basic probability and statistical concepts that MSC is based on. Further, a simple practical spreadsheet example goes through the steps presented before to show how MCS can be used in practice to assess the cost and duration risk of a project and ultimately to enable decision makers to improve the quality of their judgments.

Influence of the Back-Jump Correlations on the Fermi-Dirac Statistics

1991 ◽  
Vol 02 (01) ◽  
pp. 227-231
Author(s):  
T. BARSZCZAK ◽  
R. KUTNER
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Technique ◽  
Monte Carlo Simulation Technique

The influence of the essential Bardeen-Herring back-jump correlations on the Fermi-Dirac statistics is studied by the Monte Carlo simulation technique and semi-analytically.

Exact cash-account deflator for the G2++ model

2020 ◽  
Vol 07 (01) ◽  
pp. 2050009
Author(s):  
Francesco Strati ◽  
Luca G. Trussoni
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Insurance Industry ◽  
Random Variable ◽  
Time Span ◽  
Discrete Random Variable ◽  
Variable Formula ◽  
Monte Carlo Simulation Technique ◽  
Insurance Contracts ◽  
Embedded Options

In this paper, we shall propose a Monte Carlo simulation technique applied to a G2++ model: even when the number of simulated paths is small, our technique allows to find a precise simulated deflator. In particular, we shall study the transition law of the discrete random variable :[Formula: see text] in the time span [Formula: see text] conditional on the observation at time [Formula: see text], and we apply it in a recursive way to build the different paths of the simulation. We shall apply the proposed technique to the insurance industry, and in particular to the issue of pricing insurance contracts with embedded options and guarantees.

EFFECTS OF SURFACE LOSS IN REELS SPECTRA OF SILVER

1997 ◽  
Vol 04 (05) ◽  
pp. 955-958 ◽  
Author(s):  
K. TÖKÉSI ◽  
L. KÖVÉR ◽  
D. VARGA ◽  
J. TÓTH ◽  
T. MUKOYAMA
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Energy Loss ◽  
Electron Scattering ◽  
Primary Beam ◽  
Monte Carlo Simulation Technique ◽  
Surface Normal ◽  
Beam Incidence ◽  
Polycrystalline Silver ◽  
Electron Energy Loss

The energy distribution of the electrons backscattered in the direction of the surface normal of polycrystalline silver samples was studied using reflected electron energy loss spectroscopy (REELS) at 200 eV and 2 keV primary beam energies. For modeling the electron scattering processes, the Monte Carlo simulation technique was used and the REELS spectra were calculated at various (25°, 50° and 75°, with respect to the surface normal) angles of primary beam incidence. The effects of the surface energy loss process in REELS are evaluated from the comparison of the experimental and simulated spectra.

Monte Carlo simulation of damaged ship survivability

2005 ◽  
Vol 219 (1) ◽  
pp. 25-35 ◽  
Author(s):  
T A Santos ◽  
C Guedes Soares
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Vertical Position ◽  
Sea State ◽  
Direct Estimate ◽  
Monte Carlo Simulation Technique ◽  
The Moment ◽  
Damage Condition ◽  
Equivalent Method ◽  
Damaged Ship

A probabilistic methodology for assessing damaged ship survivability based on Monte Carlo simulation is proposed. The damage condition is generated using statistical distributions of damage location and extent, derived during a recent research project, coupled to an algorithm that identifies the damaged compartments. Survivability of the ship in each damage condition is evaluated using the formulae recently proposed in Report SLF 46, which are partly based on the static equivalent method and partly on a more conventional approach. The Monte Carlo simulation technique is applied taking into consideration random quantities related to the damage and loading conditions at the time of accident. This methodology is applied to a passenger roll-on roll-off ship, allowing for a direct estimate of the damaged ship survivability in terms of the number of simulated ship capsizes. The effects of changes in the vertical position of the centre of gravity and in the sea state distribution at the moment of accident are also evaluated.

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