Community noise has been an ongoing problem for aircraft, and is projected to be a major concern in the future due to increased air traffic. NASA’s Advanced Air Vehicles Program (AAVP), Integrated Aviation Systems Program (IASP), and Transformative Aeronautics Concepts Program (TACP) include multi-disciplinary efforts to cultivate new technologies and mature existing technologies from conceptual design to the current airspace system. Specifically, TACP’s Transformational Tools and Technologies (TTT) project focuses on developing new computer-based tools, models, and knowledge that provide a first-of-a-kind capability to analyze and predict performance of new aircraft concepts. Both conventional and unconventional aircraft designs continue to be evaluated, where assessments are performed using aircraft noise prediction and measured data, if available. The accuracy of the assessments, particularly for unconventional aircraft where measurement data is typically nonexistent, relies solely on the prediction. Hence, any comprehensive aircraft noise prediction method must contain the capability for application to new designs, and the reliability to predict outside the current experience base.
The Aircraft NOise Prediction Program (ANOPP) was designed to provide the U.S. Government with an independent aircraft system noise prediction capability that can be used as a standalone program or within larger trade studies that include performance, emissions, and fuel burn. Similar to its predecessor, the ANOPP2 framework is designed to facilitate the combination of acoustic approaches of varying fidelity for the analysis of noise from conventional and unconventional aircraft. ANOPP2 integrates noise prediction and propagation methods, including those found in ANOPP, into a unified system that is compatible for use within general aircraft analysis software, such as NASA’s OpenMDAO multidisciplinary environment.
ANOPP2 provides the capability and a framework to integrate acoustic approaches for source noise component prediction, installation effects, and propagation to the far-field. The predictions from ANOPP2 include the fidelity and flexibility required to predict outside any experience base that currently exists. A focal point of ANOPP2 is a combination of acoustic approaches; that is, to offer several options for a specific noise mechanism depending on requested fidelity and execution speed. This allows ANOPP2 to include fast prediction methods for design optimization while including prediction methods that contain the fidelity required for understanding, and provide insight into controlling noise physics.
The objectives of ANOPP2 are to:
- Provide the capability to predict noise from arbitrary aircraft designs, including conventional and unconventional aircraft designs of full-scale and model-scale size, as well as Unmanned Aerial Vehicles (UAVs), Personal Aerial Vehicles (PAVs), and other external acoustic applications.
- Establish a framework where a combination of acoustic prediction methods of varied fidelity can communicate in a unified system. This ranges from fast computations with reduced order models for system-level assessment and design to potentially computationally intensive, high-fidelity, physics-based methods for investigating and understanding noise generation and propagation effects at the component and aircraft system level.
- Include acoustic effects for comparison to flight and model-scale test data such as flight test environment, Doppler effects, convective amplification, and propagation.
- Include physics-based prediction of Propulsion Airframe Aeroacoustics (PAA), airframe interaction effects such as scattering of undercarriage noise by the airframe, and propulsion interactions like those seen in closely spaced twin jets or open-rotors.
- Provide capability to assess noise reduction technologies and approaches. Provide standards, benchmarks, and evaluations of component noise prediction.
ANOPP2 must also satisfy several major constraints. These fall into nine categories; performance, modularity, reliability, interoperability, extensibility, portability, maintainability, usability, and scalability.