The Design, Predictive Performance Modeling and Field Testing of Underwater Sound Attenuation Systems - A Review of Two Case Studies

2012 ◽  
Author(s):  
Jesse Spence ◽  
Hal Dreyer
Keyword(s):  
Case Studies ◽  
Performance Modeling ◽  
Predictive Performance ◽  
Field Testing ◽  
Sound Attenuation ◽  
Underwater Sound

Predictive performance modeling of Habesha brewery wastewater treatment plant using artificial neural networks

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Neural Networks ◽  
Water Quality ◽  
Wastewater Treatment ◽  
Artificial Neural Networks ◽  
Performance Modeling ◽  
Predictive Performance ◽  
Mathematical Tool ◽  
Effluent Water ◽  
Artificial Neural

Recently, process control in wastewater treatment plants (WWTPs) is, mostly accomplished through examining the quality of the water effluent and adjusting the processes through the operator’s experience. This practice is inefficient, costly and slow in control response. A better control of WTPs can be achieved by developing a robust mathematical tool for performance prediction. Due to their high accuracy and quite promising application in the field of engineering, Artificial Neural Networks (ANNs) are attracting attention in the domain of WWTP predictive performance modeling. This work focuses on applying ANN with a feed-forward, back propagation learning paradigm to predict the effluent water quality of the Habesha brewery WTP. Data of influent and effluent water quality covering approximately an 11-month period (May 2016 to March 2017) were used to develop, calibrate and validate the models. The study proves that ANN can predict the effluent water quality parameters with a correlation coefficient (R) between the observed and predicted output values reaching up to 0.969. Model architecture of 3-21-3 for pH and TN, and 1-76-1 for COD were selected as optimum topologies for predicting the Habesha Brewery WTP performance. The linear correlation between predicted and target outputs for the optimal model architectures described above were 0.9201 and 0.9692, respectively.

Application of the Surface Wave Survey Method on Multi-Scale Engineering Problems: Laboratory and Field Testing Case Studies

2014 ◽  
Vol 43 (2) ◽  
pp. 20140083 ◽  
Author(s):  
Kaoshan Dai ◽  
Xuehang Song ◽  
Xiaofeng Li ◽  
Zhenhua Huang ◽  
Yongdong Pan
Keyword(s):  
Surface Wave ◽  
Case Studies ◽  
Field Testing ◽  
Survey Method ◽  
Multi Scale ◽  
Engineering Problems ◽  
Testing Case

scholarly journals Louvred Noise Barrier for Traffic Noise Reduction

2021 ◽  
Vol 16 (1) ◽  
pp. 140-153
Author(s):  
Tomas Astrauskas ◽  
Pranas Baltrėnas ◽  
Tomas Januševičius ◽  
Raimondas Grubliauskas
Keyword(s):  
Traffic Noise ◽  
Environmental Issues ◽  
Field Testing ◽  
Sound Attenuation ◽  
Shallow Foundation ◽  
Blade Angle ◽  
Airflow Resistance ◽  
Frequency Bands ◽  
Noise Barrier ◽  
Absorbing Material

Environmental issues near roads become more and more important in our society daily life. One of the most critical environmental issues is traffic noise. The present paper study louvred noise barrier designed by authors. The louvred noise barrier provides sound attenuation while allowing airflow and sunlight through it. Since the airflow resistance of the barrier is low, it requires a shallow foundation compared to conventional noise barriers. The sound attenuation performance of the louvred noise barrier was tested experimentally in a sound transmission chamber. Airflow resistance simulated using a computational fluid dynamics model. The simulation and experimental study were done with different louvred noise barrier setup: change of louvre blade angle and sound-absorbing material thickness. The results showed potential for future development for the field testing. Sound attenuation was highest in 2500 Hz and 3150 Hz octave frequency bands. Depending on the louvred barrier setup, sound attenuation was up to 28 dB(A) in mentioned frequency bands. The equivalent sound pressure level reduced up to 17 dB(A). The results showed that an increase in the louvre blade angle increases sound attenuation and increases airflow resistance.

National Strike Force Proposal for Fatigue Guidelines for Emergency Responders

2001 ◽  
Vol 2001 (1) ◽  
pp. 417-421
Author(s):  
Stacey Tyler
Keyword(s):  
Case Studies ◽  
Emergency Response ◽  
Significant Risk ◽  
Field Testing ◽  
Environmental Safety ◽  
Hazardous Material ◽  
Material Response ◽  
Safety Issues ◽  
Emergency Responders

ABSTRACT Fatigue is a significant risk to personnel as we respond to emergencies at all hours of the day and night. Because of this risk, major safety issues are often overlooked and there is the potential for fatigue related accidents that arise from preventable circumstances. Studies on fatigue in the emergency response environment, for all risks and all incidents, particularly hazardous material response, have been limited. The purpose of this paper is to provide three National Strike Force-Pacific Strike Team (NSF-PST) case studies when fatigue was notably a problem, discuss some of the physiological impacts of fatigue in the workplace, share field testing results of a draft NSF work/rest guideline, and make the environmental safety field aware of the problem to prompt formal studies.

scholarly journals A Comparative Study of Neural Networks and Fuzzy Systems in Modeling of a Nonlinear Dynamic System

2011 ◽  
Vol 1 (1) ◽  
pp. 65-73 ◽  
Author(s):  
Metin DEMIRTAS ◽  
Musa ALCI
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fuzzy Systems ◽  
Performance Modeling ◽  
Nonlinear Dynamic System ◽  
Predictive Performance ◽  
Model Parameters ◽  
Data Set ◽  
The Neural Network ◽  
Practical Performance

The aim of this paper is to compare the neural network and fuzzy modeling approaches on a nonlinear system. We have taken Permanent Magnet Brushless Direct Current (PMBDC) motor data and have generated models using both approaches. The predictive performance of both methods was compared on the data set for model configurations.The paper describes the results of these tests and discusses the effects of changing model parameters on predictive and practical performance. Modeling sensitivity was used to compare for two methods. 

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