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At least 307 records · Page 17

Initial Integration of Noise Prediction Tools for Acoustic Scattering Effects

This effort provides an initial glimpse at NASA capabilities available in predicting the scattering of fan noise from a non-conventional aircraft configuration. The Aircraft NOise Prediction Program, Fast Scattering Code, and the Rotorcraft Noise Model were coupled to provide increased fidelity models of scattering effects on engine fan noise sources. The integration of these codes led to the identification of several keys issues entailed in applying such multi-fidelity approaches. In particular, for prediction at noise certification points, the inclusion of distributed sources leads to complications with the source semi-sphere approach. Computational resource requirements limit the use of the higher fidelity scattering code to predict radiated sound pressure levels for full scale configurations at relevant frequencies. And, the ability to more accurately represent complex shielding surfaces in current lower fidelity models is necessary for general application to scattering predictions. This initial step in determining the potential benefits/costs of these new methods over the existing capabilities illustrates a number of the issues that must be addressed in the development of next generation aircraft system noise prediction tools.

Nark, Douglas M.↗

HART-II Acoustic Predictions using a Coupled CFD/CSD Method

This paper documents results to date from the Rotorcraft Acoustic Characterization and Mitigation activity under the NASA Subsonic Rotary Wing Project. The primary goal of this activity is to develop a NASA rotorcraft impulsive noise prediction capability which uses first principles fluid dynamics and structural dynamics. During this effort, elastic blade motion and co-processing capabilities have been included in a recent version of the computational fluid dynamics code (CFD). The CFD code is loosely coupled to computational structural dynamics (CSD) code using new interface codes. The CFD/CSD coupled solution is then used to compute impulsive noise on a plane under the rotor using the Ffowcs Williams-Hawkings solver. This code system is then applied to a range of cases from the Higher Harmonic Aeroacoustic Rotor Test II (HART-II) experiment. For all cases presented, the full experimental configuration (i.e., rotor and wind tunnel sting mount) are used in the coupled CFD/CSD solutions. Results show good correlation between measured and predicted loading and loading time derivative at the only measured radial station. A contributing factor for a typically seen loading mean-value offset between measured data and predictions data is examined. Impulsive noise predictions on the measured microphone plane under the rotor compare favorably with measured mid-frequency noise for all cases. Flow visualization of the BL and MN cases shows that vortex structures generated in the prediction method are consist with measurements. Future application of the prediction method is discussed.

Boyd, D. Douglas, Jr.↗

Near Real-Time Optimal Prediction of Adverse Events in Aviation Data

The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we demonstrate how to recast the anomaly prediction problem into a form whose solution is accessible as a level-crossing prediction problem. The level-crossing prediction problem has an elegant, optimal, yet untested solution under certain technical constraints, and only when the appropriate modeling assumptions are made. As such, we will thoroughly investigate the resilience of these modeling assumptions, and show how they affect final performance. Finally, the predictive capability of this method will be assessed by quantitative means, using both validation and test data containing anomalies or adverse events from real aviation data sets that have previously been identified as operationally significant by domain experts. It will be shown that the formulation proposed yields a lower false alarm rate on average than competing methods based on similarly advanced concepts, and a higher correct detection rate than a standard method based upon exceedances that is commonly used for prediction.

Martin, Rodney Alexander↗

Broadband Fan Noise Prediction System for Turbofan Engines: Setup_BFaNS User's Manual and Developer's Guide - Volume 1

Pratt & Whitney has developed a Broadband Fan Noise Prediction System (BFaNS) for turbofan engines. This system computes the noise generated by turbulence impinging on the leading edges of the fan and fan exit guide vane, and noise generated by boundary-layer turbulence passing over the fan trailing edge. BFaNS has been validated on three fan rigs that were tested during the NASA Advanced Subsonic Technology Program (AST). The predicted noise spectra agreed well with measured data. The predicted effects of fan speed, vane count, and vane sweep also agreed well with measurements. The noise prediction system consists of two computer programs: Setup_BFaNS and BFaNS. Setup_BFaNS converts user-specified geometry and flow-field information into a BFaNS input file. From this input file, BFaNS computes the inlet and aft broadband sound power spectra generated by the fan and FEGV. The output file from BFaNS contains the inlet, aft and total sound power spectra from each noise source. This report is the first volume of a three-volume set documenting the Broadband Fan Noise Prediction System: Volume 1: Setup_BFaNS User s Manual and Developer s Guide; Volume 2: BFaNS User's Manual and Developer s Guide; and Volume 3: Validation and Test Cases. The present volume begins with an overview of the Broadband Fan Noise Prediction System, followed by step-by-step instructions for installing and running Setup_BFaNS. It concludes with technical documentation of the Setup_BFaNS computer program.

Morin, Bruce L.↗

Broadband Fan Noise Prediction System for Turbofan Engines: BFaNS User's Manual and Developer's Guide - Volume 2

Pratt & Whitney has developed a Broadband Fan Noise Prediction System (BFaNS) for turbofan engines. This system computes the noise generated by turbulence impinging on the leading edges of the fan and fan exit guide vane, and noise generated by boundary-layer turbulence passing over the fan trailing edge. BFaNS has been validated on three fan rigs that were tested during the NASA Advanced Subsonic Technology Program (AST). The predicted noise spectra agreed well with measured data. The predicted effects of fan speed, vane count, and vane sweep also agreed well with measurements. The noise prediction system consists of two computer programs: Setup_BFaNS and BFaNS. Setup_BFaNS converts user-specified geometry and flow-field information into a BFaNS input file. From this input file, BFaNS computes the inlet and aft broadband sound power spectra generated by the fan and FEGV. The output file from BFaNS contains the inlet, aft and total sound power spectra from each noise source. This report is the second volume of a three-volume set documenting the Broadband Fan Noise Prediction System: Volume 1: Setup_BFaNS User s Manual and Developer s Guide; Volume 2: BFaNS User s Manual and Developer s Guide; and Volume 3: Validation and Test Cases. The present volume begins with an overview of the Broadband Fan Noise Prediction System, followed by step-by-step instructions for installing and running BFaNS. It concludes with technical documentation of the BFaNS computer program.

Morin, Bruce L.↗

Broadband Fan Noise Prediction System for Turbofan Engines: Validation and Test Cases - Volume 3

Pratt & Whitney has developed a Broadband Fan Noise Prediction System (BFaNS) for turbofan engines. This system computes the noise generated by turbulence impinging on the leading edges of the fan and fan exit guide vane, and noise generated by boundary-layer turbulence passing over the fan trailing edge. BFaNS has been validated on three fan rigs that were tested during the NASA Advanced Subsonic Technology Program (AST). The predicted noise spectra agreed well with measured data. The predicted effects of fan speed, vane count, and vane sweep also agreed well with measurements. The noise prediction system consists of two computer programs: Setup_BFaNS and BFaNS. Setup_BFaNS converts user-specified geometry and flow-field information into a BFaNS input file. From this input file, BFaNS computes the inlet and aft broadband sound power spectra generated by the fan and FEGV. The output file from BFaNS contains the inlet, aft and total sound power spectra from each noise source. This report is the third volume of a three-volume set documenting the Broadband Fan Noise Prediction System: Volume 1: Setup_BFaNS User s Manual and Developer s Guide; Volume 2: BFaNS User s Manual and Developer s Guide; and Volume 3: Validation and Test Cases. The present volume begins with an overview of the Broadband Fan Noise Prediction System, followed by validation studies that were done on three fan rigs. It concludes with recommended improvements and additional studies for BFaNS.

Morin, Bruce L.↗

Prediction of Acoustic Loads Generated by Propulsion Systems

NASA Stennis Space Center is one of the nation's premier facilities for conducting large-scale rocket engine testing. As liquid rocket engines vary in size, so do the acoustic loads that they produce. When these acoustic loads reach very high levels they may cause damages both to humans and to actual structures surrounding the testing area. To prevent these damages, prediction tools are used to estimate the spectral content and levels of the acoustics being generated by the rocket engine plumes and model their propagation through the surrounding atmosphere. Prior to the current work, two different acoustic prediction tools were being implemented at Stennis Space Center, each having their own advantages and disadvantages depending on the application. Therefore, a new prediction tool was created, using NASA SP-8072 handbook as a guide, which would replicate the same prediction methods as the previous codes, but eliminate any of the drawbacks the individual codes had. Aside from replicating the previous modeling capability in a single framework, additional modeling functions were added thereby expanding the current modeling capability. To verify that the new code could reproduce the same predictions as the previous codes, two verification test cases were defined. These verification test cases also served as validation cases as the predicted results were compared to actual test data.

Perez, Linamaria↗

Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

Daigle, Matthew John↗

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for component-loaded curved orthogrid panels typical of launch vehicle skin structures. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was applied to correlate the measured input sound pressures across the energized panel. This application quantifies the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software developed for the RPTF method allows easy replacement of the diffuse acoustic field with other pressure fields such as a turbulent boundary layer (TBL) model suitable for vehicle ascent. Structural responses using a TBL model were demonstrated, and wind tunnel tests have been proposed to anchor the predictions and provide new insight into modeling approaches for this environment. Finally, design load factors were developed from the measured and predicted responses and compared with those derived from traditional techniques such as historical Mass Acceleration Curves and Barrett scaling methods for acreage and component-loaded panels.

Frady, Gregory P.↗

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

A rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for a curved orthogrid panel typical of launch vehicle skin structures. Several test article configurations were produced by adding component equipment of differing weights to the flight-like vehicle panel. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was employed to describe the assumed correlation of phased input sound pressures across the energized panel. This application demonstrates the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software modules developed for the RPTF method can be easily adapted for quick replacement of the diffuse acoustic field with other pressure field models; for example a turbulent boundary layer (TBL) model suitable for vehicle ascent. Wind tunnel tests have been proposed to anchor the predictions and provide new insight into modeling approaches for this type of environment. Finally, component vibration environments for design were developed from the measured and predicted responses and compared with those derived from traditional techniques such as Barrett scaling methods for unloaded and component-loaded panels.

Frady, Gregory P.↗

Assessment of NASA's Aircraft Noise Prediction Capability

A goal of NASA s Fundamental Aeronautics Program is the improvement of aircraft noise prediction. This document provides an assessment, conducted from 2006 to 2009, on the current state of the art for aircraft noise prediction by carefully analyzing the results from prediction tools and from the experimental databases to determine errors and uncertainties and compare results to validate the predictions. The error analysis is included for both the predictions and the experimental data and helps identify where improvements are required. This study is restricted to prediction methods and databases developed or sponsored by NASA, although in many cases they represent the current state of the art for industry. The present document begins with an introduction giving a general background for and a discussion on the process of this assessment followed by eight chapters covering topics at both the system and the component levels. The topic areas, each with multiple contributors, are aircraft system noise, engine system noise, airframe noise, fan noise, liner physics, duct acoustics, jet noise, and propulsion airframe aeroacoustics.

Dahl, Milo D.↗

An Efficient Deterministic Approach to Model-based Prediction Uncertainty Estimation

Prognostics deals with the prediction of the end of life (EOL) of a system. EOL is a random variable, due to the presence of process noise and uncertainty in the future inputs to the system. Prognostics algorithm must account for this inherent uncertainty. In addition, these algorithms never know exactly the state of the system at the desired time of prediction, or the exact model describing the future evolution of the system, accumulating additional uncertainty into the predicted EOL. Prediction algorithms that do not account for these sources of uncertainty are misrepresenting the EOL and can lead to poor decisions based on their results. In this paper, we explore the impact of uncertainty in the prediction problem. We develop a general model-based prediction algorithm that incorporates these sources of uncertainty, and propose a novel approach to efficiently handle uncertainty in the future input trajectories of a system by using the unscented transformation. Using this approach, we are not only able to reduce the computational load but also estimate the bounds of uncertainty in a deterministic manner, which can be useful to consider during decision-making. Using a lithium-ion battery as a case study, we perform several simulation-based experiments to explore these issues, and validate the overall approach using experimental data from a battery testbed.

Daigle, Matthew J.↗

Predicting Loss-of-Control Boundaries Toward a Piloting Aid

This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.

Barlow, Jonathan↗

Towards Bridging the Gaps in Holistic Transition Prediction via Numerical Simulations

The economic and environmental benefits of laminar flow technology via reduced fuel burn of subsonic and supersonic aircraft cannot be realized without minimizing the uncertainty in drag prediction in general and transition prediction in particular. Transition research under NASA's Aeronautical Sciences Project seeks to develop a validated set of variable fidelity prediction tools with known strengths and limitations, so as to enable "sufficiently" accurate transition prediction and practical transition control for future vehicle concepts. This paper provides a summary of selected research activities targeting the current gaps in high-fidelity transition prediction, specifically those related to the receptivity and laminar breakdown phases of crossflow induced transition in a subsonic swept-wing boundary layer. The results of direct numerical simulations are used to obtain an enhanced understanding of the laminar breakdown region as well as to validate reduced order prediction methods.

Choudhari, Meelan M.↗

Auralization Architectures for NASA?s Next Generation Aircraft Noise Prediction Program

Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The assessment of human response to noise from future aircraft can only be afforded through laboratory testing using simulated flyover noise. Recent work by the authors demonstrated the ability to auralize predicted flyover noise for a state-of-the-art reference aircraft and a future hybrid wing body aircraft concept. This auralization used source noise predictions from NASA's Aircraft NOise Prediction Program (ANOPP) as input. The results from this process demonstrated that auralization based upon system noise predictions is consistent with, and complementary to, system noise predictions alone. To further develop and validate the auralization process, improvements to the interfaces between the synthesis capability and the system noise tools are required. This paper describes the key elements required for accurate noise synthesis and introduces auralization architectures for use with the next-generation ANOPP (ANOPP2). The architectures are built around a new auralization library and its associated Application Programming Interface (API) that utilize ANOPP2 APIs to access data required for auralization. The architectures are designed to make the process of auralizing flyover noise a common element of system noise prediction.

Rizzi, Stephen A.↗

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

A code for predicting supersonic jet broadband shock-associated noise was assessed using a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify deficiencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the measured data, a sensitivity analysis of the model parameters with emphasis on the definition of the convection velocity parameter, and a least-squares fit of the predicted to the measured shock-associated noise component spectra, resulted in a new definition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Dahl, Milo D.↗

Operational Dust Prediction

Over the last few years, numerical prediction of dust aerosol concentration has become prominent at several research and operational weather centres due to growing interest from diverse stakeholders, such as solar energy plant managers, health professionals, aviation and military authorities and policymakers. Dust prediction in numerical weather prediction-type models faces a number of challenges owing to the complexity of the system. At the centre of the problem is the vast range of scales required to fully account for all of the physical processes related to dust. Another limiting factor is the paucity of suitable dust observations available for model, evaluation and assimilation. This chapter discusses in detail numerical prediction of dust with examples from systems that are currently providing dust forecasts in near real-time or are part of international efforts to establish daily provision of dust forecasts based on multi-model ensembles. The various models are introduced and described along with an overview on the importance of dust prediction activities and a historical perspective. Assimilation and evaluation aspects in dust prediction are also discussed.

assimilation↗

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

A code for predicting supersonic jet broadband shock-associated noise was assessed us- ing a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify de ciencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the mea- sured data, a sensitivity analysis of the model parameters with emphasis on the de nition of the convection velocity parameter, and a least-squares t of the predicted to the mea- sured shock-associated noise component spectra, resulted in a new de nition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Dahl, Milo D.↗