No abstract

Criteria for evaluating acoustic induced vibration damage (AIV) has been based on available data, often referred to as the Carucci-Mueller approach1. The Carucci-Mueller approach has been developed with several variances, but all approaches apply the internal sound power formula used with that original published data. However, the equation is an approximation to sound power which is used in very few other applications. This paper will show a correlation between the Carucci-Mueller data and the related design curve to one generated using the IEC 60534-8-3 Control Valve Aerodynamic prediction noise standard2. Additional corrections for fabrication quality will be reviewed. Using internal sound power and the coupling to pipe wall vibration, the resulting external sound pressure can be directly related to strain and thus fatigue failure criteria which are material based. Utilizing the IEC noise standard as well as standards which give corrections for fabrication quality can move the AIV evaluation techniques to methods that are documented in international standards.

The calculation of acoustic induced vibration (AIV) for piping downstream of a valve is a critical step in predicting the damage from extreme levels of noise generated by pressure relief valves in flare systems. Three noise prediction schemes are considered for this purpose: International Electrotechnical Commission (IEC) 60534-8-3, the Carucci-Mueller (C-M) formulation for sound power, and an industry valve noise prediction methodology published in the 1980’s. The application of these prediction methods is reviewed utilizing data from a full-scale test system consisting of an NPS6x8 pressure relief valve flowing into a NPS12 tailpipe that is connected through a tee to an NPS20 header. The results show good correlation between the IEC-based predictions and measured internal sound pressure and pipe wall vibration in the AIV frequency region. The industry method provides useful predictions without requiring the level of detailed information needed for the IEC method, whilst the C-M sound power model has limitations when applied to discrete predictions of vibration and strain levels. Observations are also made regarding the relative importance of the FIV contribution to the overall dynamic stresses and associated fatigue life.

The air flow in a centrifugal blower was studied using a variety of flow and sound measurement techniques. The flow measurement techniques employed included Particle Image Velocimetry (PIV), pitot tubes, and a five hole spherical probe. PIV was used to measure instantaneous and ensemble-averaged velocity fields over large area of the outlet duct as a function of fan position, allowing for the visualization of the flow as it leave the fan blades and progressed downstream. The results from the flow measurements were reviewed along side the results of the sound measurements with the goal of identifying sources of noise and inefficiencies in flow performance. The radiated sound power was divided into broadband and tone noise and measures of the flow. The changes in the tone and broadband sound were compared to changes in flow quantities such as the turbulent kinetic energy and Reynolds stress. Results for each method will be presented to demonstrate the strengths of each flow measurement technique as well as their limitations. Finally, the role that each played in identifying noise sources is described.

Tests were performed on a mockup of a typical relief/blowdown system. The system consisted of an NPS6x8 pressure relief valve, an NPS12 tailpipe, and an NPS20 header. Small bore connections were installed in the tailpipe and header. Simple structures representing a valve mass and stiffness were attached to the small bore connections. Various industry standard tee connections between the tailpipe and header and the small-bore connections to the tailpipe and the header were studied. The goal of the testing program was to provide data to quantify the tee connection style, mitigation methods, and provide data for improvements and validation of Acoustic Induced Vibration (AIV) and Flow Induced Vibration (FIV) prediction and assessment methods. This paper describes the challenges with measuring the very high strain and vibration levels and the data processing used to extract meaningful data. The learnings about the shifting of internal acoustic modes, separating the contributions of AIV and FIV, and separating the contributions of pipe bending modes, higher order pipe modes, higher order acoustic modes, and acoustic/structural coincidence are also described. This work is connected to other presentations which focus on using the data to predict AIV and FIV in realistic blowdown systems.