PAUT for effectiveness measurement chloride stress corrosion cracking

PAUT for effectiveness measurement chloride stress corrosion cracking

#Phased array ultrasonic #Stress corrosion cracking #Shear wave #Full Longitudinal wave #Austenitic stainless steel #PAUT #SCC #Cracking 

Author: Vittawas Bunjang / Puripong Klamdith , Plant Inspection, GCME

Background :

   Chloride Stress Corrosion Cracking (Cl-SCC) is a significant threat to austenitic stainless steel components, and traditional inspection methods like Liquid Penetrant Testing (PT) have limitations in detecting and sizing these cracks. Phased Array Ultrasonic Testing (PAUT) offers a promising solution, but optimizing its parameters is crucial for accurate results, as improper setup or parameter selection can lead to missed detections and potential catastrophic failures. Through experimental methods involving various PAUT configurations and specimens with Cl-SCC, optimal conditions for detection and sizing were identified. This research enhances the detection and precision of Cl-SCC inspection, improves asset integrity, and reduces the risk of unexpected failures, ultimately contributing to safer and more reliable industrial operations.

Technical detail :

SCC Background

   Chloride Stress Corrosion Cracking (Cl-SCC) represents a significant damage mechanism in austenitic stainless steel (SS) piping and equipment. There are several factors that influence the occurrence of stress corrosion cracking in metals, including elevated temperatures and the presence of environmental chloride ions, which can accelerate SCC formation. These factors fall into three broad categories: metallurgical factors, environmental factors, and mechanical factors.

   While Liquid penetrant testing (PT) remains a suitable method for detecting surface-breaking chloride stress corrosion cracks (Cl-SCC), it has limitations that often necessitate equipment shutdown. PT fundamentally requires thorough cleaning and drying of the test surface for accurate results.  In complex systems, this cleaning process can necessitate extended downtime. Additionally, PT can only detect surface-breaking defects, potentially missing subsurface cracks and unable to determine the size of subsurface cracks.

 

   The shallow, highly branched morphology of stress corrosion cracks (SCC) poses a significant challenge for traditional non-destructive testing (NDT) methods. These fine, branching cracks can be difficult to resolve or size accurately, particularly when they remain subsurface

 

   In such cases, Phased Array Ultrasonic Testing (PAUT) offers advantages for measuring crack depth and suitability for on-stream inspections.

 

   PAUT is an advanced method of ultrasonic testing (UT) that uses a set of ultrasonic testing probes made up of numerous small elements. Each of these is pulsed individually with computer-calculated timing to create the phased aspect of the process, while the array refers to the multiple elements that make up a PAUT system.

Elements are pulsed in groups with precalculated time delays for each element.

     However, even with PAUT, careful selection of probe type, wave type, frequency, and a thorough understanding of stress corrosion cracking signal patterns are crucial for achieving the best possible sizing of SCC indications. To optimize these parameters, it's often necessary to develop experiments specifically designed to determine the best combination for accurately sizing SCC indications within a given material and testing environment.

 

Experimental methods

1.                   Specimen Selection: Select Chloride Stress Corrosion Cracking (Cl-SCC) specimens exposed to 11 distinct conditions. Establish baseline crack size measurements for these SCC specimens using a macroscopic testing method.

2.                   PAUT Test Preparation:  Configure 6 different PAUT probe types with 11 variable setups (executed at room temperature).

Conditions	Method	Probe type	Freq (MHz)	Elements	dB	Wave type / Mode type
1	PAUT	A10	5	16	12	Shear wave
2	PAUT	A10	5	32	12	Shear wave
3	PAUT	A10	10	16	6	Shear wave
4	PAUT	A10	10	32	10	Shear wave
5	PAUT	A15	7.5	16	6	Longitudinal wave
6	PAUT	A31	5	16	12	Shear wave
7	PAUT	A31	5	32	12	Shear wave
8	PAUT	A31	10	16	12	Shear wave
9	PAUT	A31	10	32	12	Shear wave
10	PAUT	A32	5	16	12	Shear wave
11	PAUT	A32	5	32	12	Shear wave

3.                   Data Acquisition and Interpretation: Record PAUT signals. Interpret resultant data and classify SCCs.

4.                   Accuracy Analysis:  Employ the following PAUT score criteria for accuracy evaluation:

No.	Indicator	Criteria
1	Response TCG level. (Amplitude)	Score 1 : < 25%  Score 2 : 25% - 50%  Score 3 : 50% - 75%  Score 4 : > 75%
2	Signal to noise ratio	Score 1 : < 3:1  Score 2 : 3:1 to 6:1  Score 3 : > 6:1
3	Signal to perfection	Score 1 : < 25%  Score 2 : 25% - 50%  Score 3 : 50% - 75%  Score 4 : > 75%

Results and conclusion

  Analysis of the experimental results indicates that three conditions achieved excellence performance, exhibiting no missed defects and the highest overall scores. These conditions are:

 

  Item 1 : 5L32A10 (Condition 1), Item 3 : 10L32A10 (Condition 3), Item 5 : 7.5CCEV35-16-A15 (Condition 5)

 

  Natural Near Zone Impact: The depth of the natural near zone (NNZ) influences PAUT signal quality and crack sizing accuracy.

 

  A shallow NNZ can improve signal strength but risks oversizing defects, while a deep NNZ can weaken the signal and lead to missed defects.

   Average Deviation and Crack Height: The average deviation in SCC detection varies with crack height, as shown in the table below.

Key benefits:

 

Enhanced Detection and Sizing Accuracy: Optimized PAUT configurations established in this experiment will directly improve the accuracy of Cl-SCC detection and sizing. This translates to a reduced risk of missed defects and better-informed maintenance decisions.

 

Improved Asset Integrity:  The enhanced detection capabilities resulting from this work contribute to improved asset integrity and the reliability of austenitic stainless steel components. This helps mitigate the risks of unexpected failures and associated safety and environmental concerns.

 

Foundation for Further Research: This study provides a valuable dataset and methodology that can be adapted for investigating the detection of other types of defects using PAUT. The established principles of parameter optimization can also be applied and refined in future studies examining the impact of high-temperature conditions on defect detection."