Noise from amusement park attractions: Sound level data and abatement strategies

1999 ◽  
Vol 47 (5) ◽  
pp. 166 ◽  
Author(s):  
Christopher W. Menge
Keyword(s):  
Sound Level ◽  
Amusement Park ◽  
Level Data ◽  
Abatement Strategies

scholarly journals Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 170
Author(s):  
Robin Kraft ◽  
Manfred Reichert ◽  
Rüdiger Pryss
Keyword(s):  
Mobile Devices ◽  
Sound Level ◽  
Sensor Data ◽  
Environmental Sound ◽  
Mobile Crowdsensing ◽  
Sound Levels ◽  
Level Data ◽  
Combined Use ◽  
Smartphone Sensors ◽  
Ecological Momentary

The ubiquity of mobile devices fosters the combined use of ecological momentary assessments (EMA) and mobile crowdsensing (MCS) in the field of healthcare. This combination not only allows researchers to collect ecologically valid data, but also to use smartphone sensors to capture the context in which these data are collected. The TrackYourTinnitus (TYT) platform uses EMA to track users’ individual subjective tinnitus perception and MCS to capture an objective environmental sound level while the EMA questionnaire is filled in. However, the sound level data cannot be used directly among the different smartphones used by TYT users, since uncalibrated raw values are stored. This work describes an approach towards making these values comparable. In the described setting, the evaluation of sensor measurements from different smartphone users becomes increasingly prevalent. Therefore, the shown approach can be also considered as a more general solution as it not only shows how it helped to interpret TYT sound level data, but may also stimulate other researchers, especially those who need to interpret sensor data in a similar setting. Altogether, the approach will show that measuring sound levels with mobile devices is possible in healthcare scenarios, but there are many challenges to ensuring that the measured values are interpretable.

scholarly journals Aircraft Noise and Land Use Zoning Compatibility around the Juan Santamaría Airport, Costa Rica

2020 ◽  
Vol 30 (2) ◽  
pp. 14-31
Author(s):  
José Miguel Rivera Acevedo ◽  
Jonathan Agüero Valverde
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Computational Models ◽  
Field Measurements ◽  
Sound Level ◽  
Aircraft Noise ◽  
Noise Levels ◽  
Level Data ◽  
Aircraft Type ◽  
Level Meter

The purpose of this study is to evaluate the noise generated by aeronautical operations around Juan Santamaría Airport and its compatibility with the land use and the proposed zoning around the airport. Aircraft noise can produce discomfort, interference with daily activities, and excessive vibrations; hence, land use planning around airports is of importance. Maps were prepared through computational models representing the noise levels generated by the operations of the airport. The operations were analyzed by aircraft type, schedules, and flight tracks, for 2013 and projections for: 2016, 2026, and 2036. Noise level data were collected with a sound level meter at 28 points surrounding the airport. Comparing the annual maps of 2013 and 2036 it was determined that 41,24 % of the analyzed area will present clearly perceivable increases (5 dB(A) to 10 dB(A)), and 1,36 % of the area will have double loudness increases (10 dB(A) to 14 dB(A)). The 2016 maps show locations where it is recommended to incorporate solutions in the construction regulation that reduce between 25 dB and 30 dB in the residential and scholar areas located within 65 dB(A) and 70 dB(A), such as Coco, Rincón Monge, Rincón Herrera, and Bajo Sorda. This finding is supported by field measurements. The proposed zoning was contrasted against the yearly day-night average sound level of 2036. The biggest issue of excessive aircraft noise is located near the west runway where a range above the 75 dB(A) is expected. Any edification of permanent residence must be banned in here.  

Long Term Ambient Sound Level Survey

2021 ◽  
Vol 263 (2) ◽  
pp. 4755-4766
Author(s):  
Henk de Haan ◽  
Virgini Senden
Keyword(s):  
Sound Level ◽  
Rural Setting ◽  
Weather Data ◽  
The Third ◽  
Ambient Sound ◽  
Level Data ◽  
The City ◽  
Monitoring Stations

A 32 month long nighttime ambient sound level survey was conducted between from April 2017 and December 2019, inclusive. Sound level data was recorded at three locations within approximately 600 m of one another. Weather data was collected at one site. The measurement locations were at the edge of the city, where the suburbs make way for the countryside. Two noise monitoring stations were located near the back yards of detached houses. The third station was located in a more rural setting. This paper will look at trends in the nighttime ambient sound level (e.g. summertime vs wintertime), and try to establish the minimal duration of a measurement program for generating reliable results.

Studying acoustical capacity and quality of verbal communication in occupied restaurants

2021 ◽  
Vol 263 (5) ◽  
pp. 1645-1651
Author(s):  
Jared Paine ◽  
Lily M. Wang
Keyword(s):  
Verbal Communication ◽  
Sound Level ◽  
Reverberation Time ◽  
Sound Levels ◽  
Level Data ◽  
Infrared Cameras ◽  
University Of Nebraska Lincoln ◽  
The University ◽  
Statistical Metrics

Sound level data and occupancy data has been logged in five restaurants by the research team at the University of Nebraska - Lincoln. Sound levels and Occupancy at 10 second intervals were documented over time periods of two to four hours during active business hours. Noise levels were logged with dosimeters distributed throughout each restaurant, and occupancy was obtained from images recorded by infrared cameras. Previous analyses of this data have focused on average sound levels and statistical metrics, such as L10 and L90 values. This presentation focuses on each restaurant's Acoustical Capacity and Quality of Verbal Communication, as introduced by Rindel (2012). Acoustical Capacity is a metric describing the maximum number of persons for reasonable communication in a space, calculated from the unoccupied reverberation time and the volume of the space. Quality of Verbal Communication is a metric describing the ease with which persons in the space can communicate at a singular point in time, depending on the reverberation time, the volume of the space, and the number of occupants in the space.

Evaluation of noise levels of two micro-wind turbines using a randomised experiment

2014 ◽  
Vol 25 (1) ◽  
pp. 19-25
Author(s):  
Chantelle May Clohessy ◽  
Warren Brettanny ◽  
Gary Sharp ◽  
Frederik Vorster
Keyword(s):  
Wind Turbines ◽  
General Linear Model ◽  
Time Of Day ◽  
Sound Level ◽  
Environmental Concerns ◽  
Noise Levels ◽  
Wind Turbine Noise ◽  
Level Data ◽  
The Relationship ◽  
Noise Impacts

One of the more contentious environmental concerns of wind turbines is the wind turbine noise. This study assesses the noise impacts of two micro-wind turbines on the environment by comparing the noise generated by these turbines to traditionally accepted surrounding sounds. The sound level data was collected using a randomised experiment and fitted using a general linear model (GLM). The GLM was used to determine the relationship between the sound level generated at a given site to the time of day, the wind speed, the wind direction and a fixed predetermined distance from the sound source.

scholarly journals Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare

2019 ◽  
Vol 254 ◽  
pp. 02038 ◽  
Author(s):  
Michał Kekez
Keyword(s):  
Random Forest ◽  
Computational Intelligence ◽  
Sound Pressure ◽  
Prediction Method ◽  
Sound Level ◽  
Pressure Level ◽  
Analytical Models ◽  
Traffic Intensity ◽  
Level Data ◽  
Computational Intelligence Methods

The aim of the paper was to build the models of sound pressure level as a function of traffic intensity in thoroughfare. The models were built by using artificial analytical models or regression trees. The former included Nordic Prediction Method. The latter were represented by Random Forest and Cubist. The analysis of accuracy of all obtained models was conducted. The best models can be used in the process of reconstruction of equivalent sound level data.

scholarly journals Missing values reconstruction in sound level monitoring station by means of intelligent computing

2018 ◽  
Vol 157 ◽  
pp. 02042
Author(s):  
Leszek Radziszewski ◽  
Michał Kekez ◽  
Alžbeta Sapietová
Keyword(s):  
Missing Values ◽  
Regression Tree ◽  
Sound Level ◽  
Training Dataset ◽  
Intelligent Computing ◽  
Sound Levels ◽  
Level Data ◽  
Short Period ◽  
Computational Intelligence Methods ◽  
Level Monitoring

The aim of the paper was to reconstruct the missing data by applying the model which describes variability of sound level in the whole period from 2013 to 2016. To build the model, the computational intelligence methods, like fuzzy systems, or regression trees can be used. The latter approach was applied and we built the model with Cubist regression tree software, using equivalent sound levels recorded in 2013. For the reconstruction of sound level data in short period of time (several days), time series values and day_of_week values together should be used in the training dataset. For the reconstruction of sound level data in long period of time (several months) day_of_week values should be used in the training dataset.

scholarly journals Accuracy of Noise-Power-Distance Definition on Results of Single Aircraft Noise Event Calculation

Aerospace ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 121
Author(s):  
Oleksandr Zaporozhets ◽  
Larisa Levchenko
Keyword(s):  
Traffic Control ◽  
Noise Exposure ◽  
Low Noise ◽  
Sound Level ◽  
General View ◽  
Noise Power ◽  
Contour Maps ◽  
Level Data ◽  
Aircraft Performance ◽  
Definition Of

Aircraft performance and noise database together with operational weights (depending on flight distances) and operational procedures (including low noise procedures) significantly influence results of noise exposure contour maps assessment in conditions of real atmosphere. Current recommendations of the Standard SAE-AIR1845A allow the definition of flight profiles via solutions of balanced motion equations. However, differences are still supervised between the measured sound level data and calculated ones, especially in assessing the single flight noise events. Some of them are well explained by differences between balanced flight parameters (thrust and velocity first of all) and monitored ones by the traffic control system. Statistical data were gathered to make more general view on these differences and some proposal to use them in calculations has been proven. Besides, the real meteorological parameters provide inhomogeneous atmosphere conditions always, which are quite different from the main assumptions of the SAE-AIR1845A, stipulating inaccuracies of sound level calculations.

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