Browse Topic: Exterior noise

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Analysis Techniques for Racecar Data Acquisition [mms update 07.03.25]R-367To be published on 03/22/2099
Data acquisition has become an invaluable tool for establishing racecar - and car/driver - performance. Now that the ability exists to analyze each and every performance parameter for car and driver, accurate use of this data can provide a key advantage on the racetrack. This book provides a thorough overview of the varied methods for analyzing racecar data acquisition system outputs, with a focus on vehicle dynamics.
Segers, Jorge
Noise Reduction of Construction Equipment Vehicle Through Structure-borne and air-borne Noise Reduction Strategy2026-26-0318To be published on 01/16/2026
One can witness the constant development and redevelopment of cities throughout the world. Construction equipment vehicles (CEVs) are commonly used on the construction site. However, the noise pollution from construction sites due to the use of CEV has become a major problem for many cities. The construction equipment employed is one of the main causes of these elevated noise levels. The construction workers face a potential risk to their auditory health and well-being due to the noise levels they are exposed to. Different countries have imposed exterior and operator’s ear noise limits for construction equipment vehicles, enabling them to control noise pollution. In this study, three vehicles were selected and checked for NVH performance and found that the operator ear noise level of the identified vehicle is 6 dB(A) higher than the benchmark vehicle level in dynamic conditions, when tested as per ISO 6396. Similarly, there was another vehicle having exterior noise 2 dB(A) higher than
Shinde, Gaurav, Jawale, Pradeep, Jain, Sachinkumar, Harishchandra Walke, Nagesh
Measurement of Exterior Noise Produced by Aircraft Auxiliary Power Units (APUs) and Associated Aircraft Systems During Ground OperationARP1307C (Current)11/26/2025
Test procedures are described for measuring noise at specific receiver locations (passenger and cargo doors, and servicing positions) and for conducting general noise surveys around aircraft. Procedures are also described for measuring noise level and directivity at noise source locations to facilitate the understanding and interpretation of the data. Requirements are identified with respect to instrumentation; acoustic and atmospheric environment; data acquisition, reduction and presentation, and such other information as is needed for reporting the results. This document makes no provision for predicting APU or component noise from basic engine characteristics or design parameters, nor for measuring noise of more than one aircraft operating at the same time. No attempt is made to suggest acceptable levels of noise or suitable subjective criteria for judging acceptability. ICAO Annex 16 Volume I Attachment C provides guidance on recommended maximum noise levels.
A-21 Aircraft Noise Measurement Aviation Emission Modeling
Basic Science and Art of Aircraft Wreckage ReconstructionR-48004/23/2025
Basic Science and Art of Aircraft Wreckage Reconstruction is a unique title which addresses important aspects of investigating crashes, who does this kind of work, and how a healthy attitude and open mind are required to properly perform investigations. It also discusses what to expect from the on-scene part of the investigation, and the fundamental approaches to common types of wreckage reconstruction. Written by Don Knutson, a veteran of this industry, Basic Science and Art of Aircraft Wreckage Reconstruction is intended for the practitioner, student, or those who are simply curious about how aircraft wreckage is reconstructed. Full references are provided in the various chapters for additional reading and research. Many examples of aircraft crash scenarios and circumstances are presented in a "generic" form but relate to actual investigations, which should prove as a useful investigative resource whether you are an apprentice or an experience professional with a government aviation
Knutson, Donald F.
CSP-7124 testTATSIANA07/17/2024
QA Test
Airlines Electronic Engineering Committee
CSP-7124 QA TestTATSIANAA07/15/2024
QA Testing
Aviation Maintenance Committee
PrePrint Testing - Tatsiana 0153PMSAE-PP-0944707/12/2024
QA Test
Mutagaana, Festo
QA Test for CSP-70370530202405/15/2024
QA Test
Airlines Electronic Engineering Committee
Automation Title for Group Code D23PC-Auto-1715022264466 (Current)05/06/2024
Automation Abstract for Group Code D23
Automation Title for Group Code D22PC-Auto-1715022197983 (Current)05/06/2024
Automation Abstract for Group Code D22
Infrastructure Enablers for Automation: Vol. 2EPRCOMPV10202305/03/2024
ABSTRACT
Coyner, Kelley, Bittner, Jason, Lambermont, Serge, De Boer, Niels
Legal Issues and Policy: Vol. 2EPRCOMPV13202305/03/2024
ABSTRACT
McQueen, Bob, Williams, Ian
Transportation Ecosystem and Autonomy: Vol. 1EPRCOMPV19202305/03/2024
One-way car-sharing services (CSSs) are believed to be a promising transportation mode for urban mobility. Because of the disparity of city functional areas and population, travel demand and vehicle supply in a CSS system may inevitably tend to be imbalanced as well. Therefore, an essential requirement of one-way CSSs is the capability of providing fleet management solutions to improve the quality of service and system performance. In other words, a CSS depends heavily on technologies that offer strategic decisions for topics like fleet sizing, location and capacity of depots and charging stations, matching of travelers with vehicles, relocation of vehicles and dispatchers for fleet rebalancing, and the balancing and charging schedules of electric vehicles. This chapter addresses trending CSS technologies and outlines some insights into the existing unsettled issues and potential solutions. The discussions and outlook are presented as a collection of key points encountered in system
Guo, Ge, Hou, Yuqin, Kang, Ming, Lv, Chen, Hemphill, Jeff
Vehicle Experience and Human Interaction: Vol. 1EPRCOMPV17202305/03/2024
Connected and autonomous vehicles (CAVs) and their productization are a major focus of the automotive and mobility industries as a whole. However, despite significant investments in this technology, CAVs are still at risk of collisions, particularly in unforeseen circumstances or “edge cases.” It is also critical to ensure that redundant environmental data are available to provide additional information for the autonomous driving software stack in case of emergencies. Additionally, vehicle-to-everything (V2X) technologies can be included in discussions on safer autonomous driving design. Recently, there has been a slight increase in interest in the use of responder-to-vehicle (R2V) technology for emergency vehicles, such as ambulances, fire trucks, and police cars. R2V technology allows for the exchange of information between different types of responder vehicles, including CAVs. It can be used in collision avoidance or emergency situations involving CAV responder vehicles. The
Abdul Hamid, Umar Zakir, Roth, Christian, Nickerson, Jeffrey, Lyytinen, Kalle, King, John Leslie
Sensors: Vol. 1EPRCOMPV11202305/03/2024
ABSTRACT
Beiker, Sven, Porcel Magnusson, Cristina, Waraniak, John
Commercial Vehicles: Vol. 1EPRCOMPV14202305/03/2024
ABSTRACT
Lehmann, Johannes, Moorehead, Stewart, Muelaner, Jody E.
Legal Issues and Policy: Vol. 2EPRCOMPV132023-TEST-REC05/03/2024
ABSTRACT
McQueen, Bob, Williams, Ian
Infrastructure Enablers for Automation: Vol. 2EPRCOMPV102023-TEST-REC05/03/2024
ABSTRACT
Coyner, Kelley, Bittner, Jason, Lambermont, Serge, De Boer, Niels
Automation Title for Group Code D21: Updated in Authoring: 5/03/24PC-Auto-1714611830430 (Current)05/02/2024
Automation Abstract for Group Code D21. Updated in Authoring: 5/03/24
Automation Title for Group Code D22PC-Auto-1713447343633 (Current)04/18/2024
Automation Abstract for Group Code D22
Airlines Electronic Engineering Committee
Automation Title for Group Code D21PC-CUR-1232 (Current)04/18/2024
Automation Abstract for Group Code D21
Airlines Electronic Engineering Committee
Automation Title for Group Code D23PC-Auto-1713447365379 (Current)04/18/2024
Automation Abstract for Group Code D23
Flight Simulator Engineering and Maintenance Committee
Automation Title for Group Code D21PC-Auto-1713447321320 (Current)04/18/2024
Automation Abstract for Group Code D21
Airlines Electronic Engineering Committee
Additive Manufacturing in the Mobility Industry: Vol. 1EPRCOMPV01202304/15/2024
Additive Manufacturing in the Mobility Industry: Vol. 1EPRCOMPV012023-TEST-REC04/15/2024
An eleventh one for CUR-1174PC11-CUR-1174 (Current)04/02/2024
Italic
Flight Simulator Engineering and Maintenance Committee
A sixth one for CUR-1174PC6-CUR-1174 (Current)03/26/2024
N/A
testing tasksSAE-PP-0922503/21/2024
3rd task
Mutagaana, Festo
QA Test 032124SAE-PP-0921903/21/2024
Test
Mutagaana, Festo
QA TestingSAE-PP-0920103/13/2024
Test
Mutagaana, Festo
Liquid Runway Deicing/Anti-icing ProductAMS1435E (Current)03/12/2024
This specification covers runway deicing and anti-icing products in the form of a liquid. Unless otherwise stated, all specifications referenced herein are latest (current) revision.
G-12RDP Runway Deicing Product Committee
Liquid Runway Deicing/Anti-icing ProductAMS1435E-TEST-REC (Current)03/12/2024
This specification covers runway deicing and anti-icing products in the form of a liquid. Unless otherwise stated, all specifications referenced herein are latest (current) revision.
G-12RDP Runway Deicing Product Committee
Regression 03_05SAE-PP-0919103/05/2024
QA Test
Mutagaana, Festo
Machine-Learning-Accelerated Simulations for the Design of Airbag Constrained by Obstacles at Rest2023-22-000103/04/2024
Abstract Predicting airbag deployment geometries is an important task for airbag and vehicle designers to meet safety standards based on biomechanical injury risk functions. This prediction is also an extraordinarily complex problem given the number of disciplines and their interactions. State-of-the-art airbag deployment geometry simulations (including time history) entail large, computationally expensive numerical methods such as finite element analysis (FEA) and computational fluid dynamics (CFD), among others. This complexity results in exceptionally large simulation times, making thorough exploration of the design space prohibitive. This paper proposes new parametric simulation models which drastically accelerate airbag deployment geometry predictions while maintaining the accuracy of the airbag deployment geometry at reasonable levels; these models, called herein machine learning (ML)-accelerated models, blend physical system modes with data-driven techniques to accomplish fast
Valenzuela del Rio, Jose E., Lancashire, Richard, Chatrath, Karan, Ritmeijer, Peter, Arvanitis, Elena, Mirabella, Lucia
Machine-Learning-Accelerated Simulations for the Design of Airbag Constrained by Obstacles at Rest2023-22-0001-TEST-REC03/04/2024
Abstract Predicting airbag deployment geometries is an important task for airbag and vehicle designers to meet safety standards based on biomechanical injury risk functions. This prediction is also an extraordinarily complex problem given the number of disciplines and their interactions. State-of-the-art airbag deployment geometry simulations (including time history) entail large, computationally expensive numerical methods such as finite element analysis (FEA) and computational fluid dynamics (CFD), among others. This complexity results in exceptionally large simulation times, making thorough exploration of the design space prohibitive. This paper proposes new parametric simulation models which drastically accelerate airbag deployment geometry predictions while maintaining the accuracy of the airbag deployment geometry at reasonable levels; these models, called herein machine learning (ML)-accelerated models, blend physical system modes with data-driven techniques to accomplish fast
Valenzuela del Rio, Jose E., Lancashire, Richard, Chatrath, Karan, Ritmeijer, Peter, Arvanitis, Elena, Mirabella, Lucia
TEST - 791P2-2: Mark I Aviation Ku-Band and Ka-Band Satellite Communication System, Part 2, Electrical Interfaces and Functional Equipment DescriptionARINC791P2-2-CSP (Historical)02/23/2024
This document (ARINC Characteristic 791, Part 2) provides the non-networking interface definition of the Mark I (ARINC 791) and Mark II (ARINC 792) Ku-Band and Ka-Band Satellite Communication (satcom) system intended for passenger entertainment on commercial transport aircraft. ARINC Characteristic 791 Part 1 of this document provides an overview of Ku-band and Ka-band satcom systems. System provisions, including Line Replaceable Unit (LRU) form factors, attachments, cooling, and inter-system wiring, are defined. Signals between the Modem/Modem Manager (Modman) and the Antenna Subsystem are described to permit interchangeability between any Modman and any Antenna Subsystem. ARINC Characteristic 791 Part 2 of this document provides the non-networking interface definition of the satcom system. Any signal crossing into or out of the communication system is documented to ease aircraft integration. Signals within the satcom system, and in particular, between the Modman and the Antenna
Airlines Electronic Engineering Committee
TEST - Designing for Long Life with ElastomersAIR1412E-CSP (Historical)02/23/2024
This document lists those guidelines recognized as being essential for consideration by the designer who is preparing to select an elastomer as part of an aerospace design.
Airlines Electronic Engineering Committee
TEST - 800P1 Cabin Connectors and Cables, Part 1, Description and OverviewARINC800P1-CSP (Historical)02/23/2024
This document is the first of a multi-part specification that will provide a catalog of cabin connector and cables that may be used in ARINC Standard cabin systems, including In-Flight Entertainment. Part 1 describes connector and cable requirements and evaluation criteria for the interface components used in the integration of cabin systems. Future releases will define connectors, contacts, and termination methods in Part 2. Cables will be specified in Part 3.
Airlines Electronic Engineering Committee
BEARING, PLAIN, SELF-ALIGNING, PTFE LINED, WIDEAS21231B (Current)02/02/2024
ACBG Plain Bearing Committee
Regression 1/18/24SAE-PP-0913801/18/2024
Text
Mutagaana, Festo
633-4 AOC Air-Ground Data and Message Exchange Format, ARINC633-4jms57682425 (Historical)01/16/2024
SAE ITC ARINC IA 2.0 standards (specification) The purpose of ARINC 633 is to specify the format and exchange of Aeronautical Operational Control (AOC) communications. Examples of ARINC 633 AOC Structures/Messages include: Flight Plans, Load Planning (i.e., Weight and Balance and Cargo Planning Load Sheets), NOTAMs, Airport and Route Weather data, Minimum Equipment Lists (MEL) messages, etc. The standardization of AOC messages enables the development of applications shared by numerous airlines on different aircraft types. Benefits include improved dispatchability and reduce operator cost. ARINC 633 is a complete definition of AOC message sets used in commercial aviation with XML schema definitions included. ARINC 633 is a complete definition of AOC message sets used in commercial aviation with XML schema definitions included.
Airlines Electronic Engineering Committee
Regression IISAE-PP-0909801/03/2024
QA Test
Mutagaana, Festo
test download cache issue 01/02/24 at 8:12 amSAE-PP-0909401/02/2024
test download cache issue 01/02/24 at 8:12 am
Mutagaana, Festo
test download manager cache issue 12/27/2023 at 9 amSAE-PP-0908512/27/2023
test download manager cache issue 12/27/2023 at 9 am
Mutagaana, Festo
test download issue 12/27/2023 at 8:13 amSAE-PP-0908412/27/2023
test download issue 12/27/2023 at 8:13 am
Mutagaana, Festo
Implications of Off-road Automation for On-road Automated Driving SystemsEPR202302912/12/2023
Automated vehicles, in the form we see today, started off-road. Ideas, technologies, and engineers came from agriculture, aerospace, and other off-road domains. While there are cases when only on-road experience will provide the necessary learning to advance automated driving systems, there is much relevant activity in off-road domains that receives less attention. Implications of Off-road Automation for On-road Automated Driving Systems argues that one way to accelerate on-road ADS development is to look at similar experiences off-road. There are plenty of people who see this connection, but there is no formalized system for exchanging knowledge. Click here to access the full SAE EDGETM Research Report portfolio.
Key Technology Challenges of Electric Ducted Fan Propulsion Systems for eVTOLEPR202302711/22/2023
Electrical vertical takeoff and landing (eVTOL) vehicles for urban air mobility (UAM) are garnering increased attention from both the automotive and aerospace industries, with use cases ranging from individual transportation, public service, cargo delivery, and more. Distributed electric propulsion systems are their main technical feature; they determine vehicle size and propulsion efficiency and provide distributed thrust to achieve attitude control. Considering the intended role of eVTOL vehicles, ducted-fan systems are ideal choice for the propulsor, as the duct provides a physical barrier between the rotating blades and the human, especially during the take-off and landing phases. Key Technology Challenges of Electric Ducted Fan Propulsion Systems for eVTOL introduces the main bottlenecks and key enablers of ducted-fan propulsion systems for eVTOL applications. Based on the introduction and discussion of these important issues, this report will help eVTOL engineers understand the
Key Technology Challenges of Electric Ducted Fan Propulsion Systems for eVTOLEPR2023027-TEST-REC11/22/2023
Electrical vertical takeoff and landing (eVTOL) vehicles for urban air mobility (UAM) are garnering increased attention from both the automotive and aerospace industries, with use cases ranging from individual transportation, public service, cargo delivery, and more. Distributed electric propulsion systems are their main technical feature; they determine vehicle size and propulsion efficiency and provide distributed thrust to achieve attitude control. Considering the intended role of eVTOL vehicles, ducted-fan systems are ideal choice for the propulsor, as the duct provides a physical barrier between the rotating blades and the human, especially during the take-off and landing phases. Key Technology Challenges of Electric Ducted Fan Propulsion Systems for eVTOL introduces the main bottlenecks and key enablers of ducted-fan propulsion systems for eVTOL applications. Based on the introduction and discussion of these important issues, this report will help eVTOL engineers understand the
Regression II 11/21 4:40PMSAE-PP-0899911/21/2023
QA Testing
Mutagaana, Festo
preprint submission testingSAE-PP-0896111/08/2023
regression preprint submission
Atash, Ganira
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