Comparison of two community noise models applied to a NASA urban air mobility concept vehicle

2021 ◽  
Vol 263 (6) ◽  
pp. 787-798
Author(s):  
Juliet Page ◽  
Stephen A. Rizzi ◽  
Rui Cheng
Keyword(s):  
Noise Exposure ◽  
Simulation Method ◽  
Design Tool ◽  
Noise Model ◽  
Urban Air ◽  
Noise Power ◽  
Modeling Tools ◽  
Community Noise ◽  
Propagation Modeling ◽  
Concept Vehicle

Predictions of community noise exposure from the NASA urban air mobility (UAM) concept vehicles have been conducted for representative operations using the FAA Aviation Environmental Design Tool (AEDT) in order to demonstrate modeling tool interoperability and assess applicability, capabilities and limitations of integrated noise modeling tools. To both quantify limitations and highlight other capabilities, a comparative analysis is performed using a time simulation method, in particular, using the Volpe Advanced Acoustic Model (AAM). Starting with the same source noise model, the 3D directivity of a UAM concept vehicle is predicted in terms of aeroacoustic pressure time histories at a sphere of observers near the vehicle. In addition to distilling those data to a set of noise-power-distance data for input to AEDT, the data are processed preserving directivity, into narrowband, one-twelfth and one-third octave bands for input to AAM. Results from AEDT and AAM modeling are provided for a variety of metrics to demonstrate the effect that source noise and propagation modeling fidelity have on predicted results at receptors over a study area.

Validation of the aviation environmental design tool's noise model using high fidelity weather

2021 ◽  
Vol 263 (2) ◽  
pp. 4810-4822
Author(s):  
Ana Gabrielian ◽  
Tejas Puranik ◽  
Mayank Bendarkar ◽  
Michelle Kirby ◽  
Dimitri Marvis
Keyword(s):  
Real World ◽  
Noise Exposure ◽  
Environmental Design ◽  
Design Tool ◽  
Noise Model ◽  
Weather Data ◽  
High Fidelity ◽  
Real World Data ◽  
Community Noise ◽  
Fuel Burn

To enable sustainable aviation growth, mitigation of environmental effects must be developed in parallel. To further this effort, these effects are modeled using capabilities such as the Aviation Environmental Design Tool (AEDT), a program that is able to model aircraft performance, fuel burn, emissions, and noise. Past and current projects are performed with the intent of improving the accuracy of the models within AEDT to capture various real-world effects. This paper targets the sensitivity of the noise prediction and propagation by varying multiple assumptions within AEDT. To validate the noise capabilities, multiple streams of real-world data will be used to accurately model actual flights to and from SFO airport. This data includes High-Fidelity weather data,detailed flight performance characteristics from airline flight data records and noise monitoring data obtained from stations around the airport. The results from this study are expected to offer recommendations and help users prioritize and more accurately quantify community noise exposure using AEDT.

scholarly journals Guidelines for the LTO Noise Assessment of Future Civil Supersonic Aircraft in Conceptual Design

Aerospace ◽  
2022 ◽  
Vol 9 (1) ◽  
pp. 27
Author(s):  
Grazia Piccirillo ◽  
Nicole Viola ◽  
Roberta Fusaro ◽  
Luigi Federico
Keyword(s):  
Conceptual Design ◽  
Aircraft Design ◽  
Low Noise ◽  
Aircraft Noise ◽  
Noise Model ◽  
Noise Power ◽  
Community Noise ◽  
Prediction Program ◽  
Supersonic Aircraft ◽  
Noise Assessment

One of the most critical regulatory issues related to supersonic flight arises from limitations imposed by community noise acceptability. The most efficient way to ensure that future supersonic aircraft will meet low-noise requirements is the verification of noise emissions from the early stages of the design process. Therefore, this paper suggests guidelines for the Landing and Take-Off (LTO) noise assessment of future civil supersonic aircraft in conceptual design. The supersonic aircraft noise model is based on the semi-empirical equations employed in the early versions of the Aircraft NOise Prediction Program (ANOPP) developed by NASA, whereas sound attenuation due to atmospheric absorption has been considered in accordance with SAE ARP 866 B. The simulation of the trajectory leads to the prediction of the aircraft noise level on ground in terms of several acoustic metrics (LAmax, SEL, PNLTM and EPNL). Therefore, a dedicated validation has been performed, selecting the only available supersonic aircraft of the Aircraft Noise and Performance database (ANP), that is, the Concorde, through the matching with Noise Power Distance (NPD) curves for LAmax and SEL, obtaining a maximum prediction error of ±2.19%. At least, an application to departure and approach procedures is reported to verify the first noise estimations with current noise requirements defined by ICAO at the three certification measurement points (sideline, flyover, approach) and to draw preliminary considerations for future low-noise supersonic aircraft design.

AIRNOISEUAM: An Urban Air Mobility Noise-Exposure Prediction Tool

2021 ◽  
Vol 263 (6) ◽  
pp. 474-485
Author(s):  
Jinhua Li ◽  
Yun Zheng ◽  
Menachem Rafaelof ◽  
Hok K. Ng ◽  
Stephen A. Rizzi
Keyword(s):  
Noise Exposure ◽  
Modular Design ◽  
Software Tool ◽  
Urban Air ◽  
Fast Time ◽  
Noise Power ◽  
Human In The Loop ◽  
Industry Standard ◽  
Standard Tool ◽  
Aircraft Performance

A new software tool called AIRNOISEUAM is introduced that models the noise exposure of Urban Air Mobility (UAM) operations. Given relevant UAM aircraft performance models, mission profiles, and Noise-Power-Distance data, AIRNOISEUAM predicts the noise exposure footprint for receptors on the ground. The performance of AIRNOISEUAM using a Robinson R66 helicopter model and a six-passenger quadrotor model, and a diverse set of scenarios from NASA’s UAM human-in-the-loop simulations is compared to that of the industry-standard tool with the same inputs. The predicted noise exposure results from both tools are found to be nearly identical. AIRNOISEUAM offers a fast-time, flexible interface and modular design to facilitate the dynamic requirements of the aviation research community.

scholarly journals Selection of Vertiports Using K-Means Algorithm and Noise Analyses for Urban Air Mobility (UAM) in the Seoul Metropolitan Area

2021 ◽  
Vol 11 (12) ◽  
pp. 5729
Author(s):  
Junyoung Jeong ◽  
Minjun So ◽  
Ho-Yon Hwang
Keyword(s):  
Metropolitan Area ◽  
Noise Exposure ◽  
Satellite Image ◽  
Design Tool ◽  
Urban Air ◽  
Real World Data ◽  
Seoul Metropolitan Area ◽  
Shortest Distance ◽  
Selection Of ◽  
Environmental Design Tool

In this study, a combination of well-established algorithms and real-world data was implemented for the forward-looking problem of future vertiport network design in a large metropolitan city. The locations of vertiports were selected to operate urban air mobility (UAM) in the Seoul metropolitan area based on the population of commuters, and a noise priority route was created to minimize the number of people affected by noise using Aviation Environmental Design Tool (AEDT) software. Demand data were analyzed using survey data from the commuting population and were marked on a map using MATLAB. To cluster the data, the K-means algorithm function built in MATLAB was used to select the center of the cluster as the location of the vertiports, and the accuracy and reliability of the clustering were evaluated using silhouette techniques. The locations of the selected vertiports were also identified using satellite image maps to ensure that the location of the selected vertiports were suitable for the actual vertiport location, and if the location was not appropriate, final vertiports were selected through the repositioning process. A helicopter model was then used to analyze the amount of noise reduction achieved by the noise priority route, which is the route between the selected K-UAM vertiports compared to the shortest distance route. As a result, it was shown that the noise priority route that minimized the amount of noise exposure was more efficient than the business priority routes.

Community noise from urban air mobility (UAM) and its control by traffic management

2021 ◽  
Vol 263 (6) ◽  
pp. 187-193
Author(s):  
Michael Bauer
Keyword(s):  
Traffic Management ◽  
Electric Propulsion ◽  
Traffic Noise ◽  
Environmentally Friendly ◽  
Urban Air ◽  
Acoustic Characteristics ◽  
Operational Conditions ◽  
Community Noise ◽  
Open Questions ◽  
Noise Metrics

The awareness about UAM is amplified by steadily growing numbers of air taxi concepts being announced. In general environmentally friendly by electric propulsion, community noise and en-route noise are still prominent open questions. Several studies for larger UAM aircraft, describing the acoustic characteristics of a variety of potential air taxi concepts, have been performed by the author. Due to the abovementioned multitude of different vehicle concepts and their multiple operational conditions, each of them shows individual sound characteristics. Therefore, further investigations of noise created by air taxi fleets appear to be crucial. Understanding of community noise around vertiports and along air taxi routes will strongly depend on those fleets. In this paper, acoustically different air taxi systems are composing different sets of air taxi fleets, used for air traffic noise simulations. The simulations start with baseline scenarios of equally represented taxi systems on fixed flight paths with several flight levels in a certain air lane. The final fleets are consisting of random air taxi composition with randomly populated flight paths. The results, based on common noise metrics and changes in the number of affected residents, could provide a first indication how to reduce community noise by future UAM traffic management.

Improved UFIR Tracking Algorithm for Maneuvering Target

2016 ◽  
Vol 2 (2) ◽  
pp. 344 ◽  
Author(s):  
Shoulin Yin ◽  
Jinfeng Wang ◽  
Tianhua Liu
Keyword(s):  
Target Tracking ◽  
Finite Impulse Response ◽  
Estimation Error ◽  
Statistical Properties ◽  
Noise Model ◽  
Noise Power ◽  
Actual Process ◽  
Maneuvering Target Tracking ◽  
Process Noise ◽  
Maneuvering Target

Maneuvering target tracking is a target motion estimation problem, which can describe the irregular target maneuvering motion. It has been widely used in the field of military and civilian applications. In the maneuvering target tracking, the performance of Kalman filter(KF) and its improved algorithms depend on the accuracy of process noise statistical properties. If there exists deviation between process noise model and the actual process, it will generate the phenomenon of estimation error increasing. Unbiased finite impulse response(UFIR) filter does not need priori knowledge of noise statistical properties in the filtering process. The existing UFIR filters have the problem that generalized noise power gain(GNPG) does not change with measurement of innovation. We propose an improved UFIR filter based on measurement of innovation with ratio dynamic adaptive adjustment at adjacent time. It perfects the maneuvering detect-ability. The simulation results show that the improved UFIR filter has the best filtering effect than KF when process noise is not accurate.

Community noise model for train warning horn

1996 ◽  
Vol 100 (4) ◽  
pp. 2586-2586
Author(s):  
Richard A. Carman
Keyword(s):  
Noise Model ◽  
Community Noise
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