Journal of Health and Safety at Work

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Introduction: This study was conducted to assess noise pollution in one of thepetrochemical complex andtakepractical measures to reduce it. Thecompanyis located in site 4 of Mahshahr Special Economic Zone.

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Method and Materials: In the first phase of the research, environmental noise was measured to determine the noise levelsin the different sections of the plant and also identify the main sound sources.Then,using the basic acoustic knowledge, aformulahasbeenproposedasan indexof noise control priority to select one section of the plant as the first priority forcontrolling noise. The main soundsource of the selected section wasknownby referring to noise maps and contours and finally its acoustic properties were analyzed.

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Results: The results showed that safety caution and danger areasof the plant under study were 16.7%, 74.5% and 8.8% respectively and a major part of the danger zone (about 54%) was related to unit Air. Noise level in 24 percent of the caution zone ranged from80 to 85 dBA and alsoitwas above 90 dBA in 33.4% of danger areas.

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Conclusion: Compressionsectionwhich was located in unit Air was knownas first priority based on Noise Control Priority Index.Dryer machineswere the main sound source in this section.

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Introduction: The purpose of this study was prioritizing the noise control methods using Analytic Hierarchy Process (AHP) technique in Hamadan glass industry.

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Material and Method: This is a cross-sectional – descriptive - analytical study. According to a survey of experts by questionnaire and Delphi method four criteria were selected including cost, efficiency, executive capability and not to interfere in the process and eleven alternatives for control options. Prioritizing of the items was conducted based on the study criteria as well as the importance ranking determined in this study.

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Result: The results showed all that consistently Ratios were less than 10 % and compatibility of answers has been confirmed. According to expert’s views, the criteria of executive capability (0.277) and using the barrier between the two main sections (0.111) have achieved the highest priority among the criteria and control methods, respectively.

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Conclusion: In this study a pattern of decision-making structure was introduced based on Analytic Hierarchy Process for determining the method noise control. This method can improve the decision making process and prioritizing noise control methods as an efficient and effective approach.

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Introduction: In the steel industry,air blowers used to supply compressed air are considered as sources of annoying noise. This study aims to acoustics analysis of theairblower workroomand sound source characteristics in order to present noise controlmeasuresinthe steel industry.

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Material and Method: Measurement of noiselevel and its frequency analysis was performed usingsound levelmetermodelof CASELLA-Cell.450. Distribution of noise level in the investigated workroom in form of noise map was provided using Surfer software. In addition, acoustic analysis of workroom and control room was performed in view point of soundabsorption andinsulation. Redesignofdoor and window of controlroom and installation of soundabsorbing materialson theceiling of the workroom were proposed and the efficiency of these interventionswasestimated.

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Result: The totalsound pressurelevelin the blower workroom was 95.4 dB(L) and the dominant frequency was 2000Hz. Sound pressure level inside the room control was 80.1dB(A). The average absorption coefficient and reverberation time in the blower workroom was estimated equal to 0.082 Sab.m2 and 3.9 seconds respectively. These value in control room was 0.04 Sab.m2 and 3/4 seconds respectively. In control room, sound transmission loss between the two parts of the wall dividing was 13.7 dB(A). The average of noise dose in blower operators was 230%. With the installation of sound absorber on ceiling of workroom, average of absorption coefficient can increase to 0.33 Sab.m2 and sound transmission loss of the new designed door and window was estimated equal to 20dB.

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Conclusion: The main cause of noise leakage in the control room was insufficient insulation properties of door and windows. By replacing the door and window and installation of sound absorbing on ceiling of workroom, the noise dose can reduce to 49.6%. New Improved door and window of control room can reduce noise dose to 69.65% solely.

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Introduction: Noise is one of the most harmful industrial agents and there are different methods to control it. Fuzzy analytical hierarchy process is an appropriate technique for selecting the best choice among several control methods. Therefore, the aim of this study was the selection of the most suitable sound control method using fuzzy hierarchical analysis (FAHP) technique in a refinery plant.
Material and Method: The present study was a cross-sectional research in a refinery plant. After identifying the main sources of the noise in the studied palnt, five criteria and ten noise control methods were selected using a questionnaire and Delphi methods. Then, Fuzzy hierarchy analysis was applied for the selection of the best noise control alternative.
Result: The results showed that the performance with a final weight of 0.277 and the non-interference in the process with a final weight of 0.06 were most and least important criteria, respectively. Meanwhile, worker enclosure had highest score (0.207) of the control methods.
Conclusion: In general, the results showed that best criterion for selection of the suitable noise control method is performance. What’s more, based on the results, worker enclosure was selected as best noise control method in the refinery.

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Introduction: Microperforated panels (MPPs), often considered as potential replacements for fiber absorbers, have a significant limitation in their absorption bandwidth, particularly around the natural frequency. This study aims to address this challenge by focusing on the optimization and modeling of sound absorption in a manufactured MPP.
Material and Methods: The study employed Response Surface Methodology (RSM) with a Central Composite Design (CCD) approach using Design Expert software to determine the average normal absorption coefficient within the frequency range of 125 to 2500 Hz. Numerical simulations using the Finite Element Method (FEM) were conducted to validate the RSM findings. An MPP absorber was then designed, manufactured, and evaluated for its normal absorption coefficient using an impedance tube. Additionally, a theoretical Equivalent Circuit Model (ECM) was utilized to predict the normal absorption coefficient for the manufactured MPP.
Results: The optimization process revealed that setting the hole diameter to 0.3 mm, the percentage of perforation to 2.5%, and the air cavity depth behind the panel to 25 mm resulted in maximum absorption within the specified frequency range. Under these optimized conditions, the average absorption coefficient closely aligned with the predictions generated by RSM across numerical, theoretical, and laboratory assessments, demonstrating a 13.8% improvement compared to non-optimized MPPs.
Conclusion: This study demonstrates the effectiveness of using RSM to optimize the parameters affecting MPP performance. The substantial correlation between the FEM numerical model, ECM theory model, and impedance tube results positions these models as both cost-effective and reliable alternatives to conventional laboratory methods. The consistency of these models with the experimental outcomes validates their potential for practical applications.