[Objective] Lift-off acoustic environment is most severe during the rocket flight. This broadband random noise can cause high-intensity random responses of the rocket structure. Predicting the lift-off acoustic environment is important to guide the design of rocket noise protection. The Kudryavtsev method is a comprehensive technique that considers five noise sources during lift-off of rocket; however, it weakens the directivity of the free jet and neglects the shielding of the launch pad and service tower. In addition, the multijet equivalent method does not consider the distance between jets. Therefore, three modifications are made based on the Kudryavtsev method to enhance the prediction ability of the lift-off acoustic environment of multinozzle rockets.[Methods] The lift-off acoustic environment was predicted using five types of noise sources, namely the noise of the undisturbed free jet above the launch table, noise of interaction between the jet and launch table, noise of reflection by the launch table, noise of the disturbed free jet between the launch pad entrance and deflector, and noise of diversion channel exit. For free-jet noise sources, the distributed source method II (DSM-TI) was employed to correct directivity and redistribute the noise power. Herein, two normalization curves of noise power distribution in DSM-II were corrected by empirical formulas, increasing the results by about 1. 5 dB. Subsequently, considering the structural shielding in noise propagation paths, Maekawa's noise shielding model was utilized to estimate the noise attenuation of the launch pad and service tower. Based on numerical simulation results, a equivalent method was used for predicting the multijet noise of rockets. The multijet noise of the core stage was calculated by a equivalent single jet, and the single jet noise of boosters was calculated independently. The modified method was employed for predicting the acoustic environment near the service tower of a certain rocket at different times of lift-off.[Results] Comparison results indicated that for the overall sound pressure level (OASPL), the maximum prediction error of the modified method was less than 5. 0 dB within 2 s of lift-off, while the maximum prediction error of the Kudryavtsev method was more than 15. 0 dB. The accuracy was increased by about 10. 0 dB. The modified method can more accurately predict the peak time, and the error of OASPL near peak time was less than 3. 0 dB. In contrast, the peak time predicted by Kudryavtsev method was smaller, and the maximum error of OASPL near peak time was more than 3. 0 dB for the Kudryavtsev method. For the 1/3-octave-band sound pressure level spectrum at the peak time of OASPL, the peak frequency and sound pressure level of the modified method were near the test data. The maximum error of the modified method was less than 6. 0 dB in the full band and less than 3. 0 dB in the 1-5 kHz frequency band. However, the maximum error of Kudryavtsev method was more than 6.0 dB.[Conclusions] Herein, three modifications were done based on the Kudryavtsev method, which effectively enhanced the prediction accuracy. Compared with the original method, the modified method has high accuracy within 2 s of lift-off and near peak time. In addition, the predicted 1/3-octave-band sound pressure level spectrum of the modified method is closer to the test data. Thus, the method presented in this study has higher prediction accuracy and can be better applied in practical engineering. © 2024 Tsinghua University. All rights reserved.
