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TAKING NON-DESTRUCTIVE EVALUATION TO THE NEXT GENERATION

25 April 2024




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Non-destructive Evaluation (NDE) is widely used in the nuclear power industry
for routine maintenance, asset management and in-service assessments. The NDE
industry is constantly evolving its tools and techniques with the integration of
new and emerging automation technology.

--------------------------------------------------------------------------------





Above: The nuclear industry has moved beyond manual ultrasonic testing for
volumetric examinations

In the early days of nuclear power plant inspection, there were only the basic
methods of radiography (RT) and manual ultrasonic testing (UT) for volumetric
examinations. Inspectors used cumbersome single-wave UT tools that had limited
capabilities to detect flaws in nuclear reactor components and piping. Today,
the once analogue practice of nuclear plant inspections has undergone a digital
transformation. Technological advances in predictive maintenance, such as AI,
sensors and other automated tools, have led to improved inspection quality to
enhance nuclear safety.

Non-destructive Evaluation (NDE), or Non-destructive Testing (NDT), refers to
the inspection of materials without affecting their useability and the overall
integrity of the asset in which they are installed. NDE is applied in many
industries. In the case of nuclear power generation, it is used to evaluate
components in both the initial manufacturing phase and throughout the reactor’s
lifecycle.

NDE helps maintain the very strict quality control standards in place to ensure
safe operation of nuclear power plants. Engaging certified NDE inspectors in
routine evaluations helps reduce the risk of manufacturing defects and
in-service flaws going undetected, which in a worst-case scenario, may lead to
operational failure.


CHANGING NDE IN THE NUCLEAR INDUSTRY

With the integration of new technology, NDE is shaping the future of nuclear
safety. The American Society of Mechanical Engineers (ASME) and the Nuclear
Regulatory Commission (NRC) heavily regulate nuclear power plants in the United
States. For both Boiling Water Reactors (BWR) and Pressurized Water Reactors
(PWR), several safety-related systems are required to undergo regular
inspections, in addition to routine assessments of primary reactor components
and containment vessels. The rules dictate when and how often inspectors must
test each asset using NDE and which inspection methods should be applied.

Frequently used NDE techniques in the nuclear power industry include ultrasonic
testing and Phased Array Ultrasonic Testing (PAUT), Liquid Penetrant Testing
(PT), Eddy current Testing, (ET), Magnetic Particle testing (MP) and Visual
Testing (VT). Of these, PAUT represents an advanced method of UT inspection, and
uses a set of probes made up of multiple segments that can be individually
computer-activated by the examiner. Each of the probes allows separate,
staggered pulses, enabling NDE professionals to create a guided sound beam to
sweep across the component collecting data and visualising the component’s
inspected area.

In contrast, PT is an NDE method that requires minimal training. It is used
widely for inspecting nuclear power plant piping and components. PT inspections
check components for material flaws visible at the surface by flowing a very
thin liquid known as a penetrant into any potential discontinuities and then
drawing the liquid out with a chalk-like developer to reveal if an actual flaw
exists. Because most of the components in nuclear reactors contain
non-ferromagnetic materials PT can easily and quickly reveal surface breaking
flaws.


NDE IN THE DIGITAL AGE

As the concept of a fourth industrial revolution takes hold in the energy
industry, NDE technology leaders are going beyond traditional tools and
procedures by integrating automation and artificial intelligence (AI) into
inspection techniques. The goal of these efforts is to leverage new
technological advancements to improve inspection efficiency and detection
probabilities.

Adopting new, advanced technologies and tools has become necessary for NDE
inspectors as they support plant engineers in meeting the needs of the nuclear
energy industry. As technology such as automation and AI evolves and grows in
adjacent sectors, that technology can be adapted to bring enhancements to NDE
methodologies as well. NDE experts in the power generation industry are working
to tap into this potential.

In the nuclear energy field, integrating advanced technology and adequately
training inspectors in advanced inspection procedures can improve the
reliability and efficiency of inspections. Evolving toward a monitoring approach
rather than traditional inspection may offer real benefits to utilities as well,
since inspection personnel can spend less time in high-temperature,
high-pressure, and potentially dangerous conditions. For emerging reactor
designs such as Small Modular Reactors (SMRs) and non-light water reactors,
monitoring of components at high temperatures could be paramount.

When any flaw is detected, the examiner must look at various aspects, such as
thermal shock and fatigue. Conventional ultrasonic sensory technology is built
to survive a maximum temperature of about 200°C (392°F). As nuclear plants
install advanced reactor vessels with much higher temperatures, sensors also
will need to advance to survive. Extensive thermal testing trials are currently
underway with sensor prototypes to demonstrate leading-edge sensor prototypes,
and to find adhesive alternatives to clamps that can secure permanent sensory
technology in place to monitor hot reactor components.

In the modern age of digitalization, emerging technologies in machine learning
and AI are improving workplace efficiency and making automated industry
capabilities possible. From the introduction of UT and PT to the emergence of
PAUT, digitalisation of NDE has been steering advances in automation.
Organisations such as EPRI – the Electric Power Research Institute – are leading
the way in exploring and testing emerging technology. EPRI’s team of researchers
is currently examining how advancing automation technology such as AI, drones
and sensors can benefit the nuclear and NDE industries. Additionally, other
leading-edge technology being evaluated supports the implementation of permanent
sensors in the nuclear industry that can monitor and alert personnel if
maintenance is needed on structures or components.


AI AND SENSORS: THE KEY TO NDE AUTOMATION

Artificial intelligence is a powerful new tool that can help expedite and
improve the data and image collection process of NDE by taking on monotonous,
tedious and repetitive tasks now handled by examiners. It will not replace the
work of an NDE inspector but will allow them to efficiently analyse the most
pertinent data collected by new technologies.

Another potentially important use for AI is to analyse new types of flaws that
may arise from new reactor designs and manufacturing techniques. Everything the
industry knows about fabrication flaws is based on what examiners have seen for
decades and which is then used to form a general expectation of what each kind
of fabrication looks like. With new SMR and non-light water reactor designs as
well as new manufacturing techniques, it can be more difficult for engineers to
know what to expect.

Implementing new manufacturing techniques can lead to new types of flaws
unfamiliar even to experienced inspectors. For example, fabrication techniques
like electron beam welds are not expected to produce the kinds of flaws typical
of conventional welding methods. Any new kinds of flaws will have to be
addressed by the industry as they are encountered using enhanced inspection
methods and comprehensive training courses.

Integrating AI into the NDE inspection process will increase reliability and
efficiency by helping inspection professionals make well-informed, data-driven
decisions. Recently, EPRI conducted NDE field trials on partial penetration
J-groove welds and dissimilar metal welds (DMWs) at various nuclear stations.
The AI programme collected a vast amount of data and raised flags for further
review by examiners. AI automated much of the confirmation process and shaved
off substantial time throughout this process. In one instance, AI cut the data
analysis process down from four days to just four hours without loss of
assessment integrity. This advancement can enhance nuclear safety by allowing
examiners to focus more time assessing areas of welds that require a more
detailed evaluation. It can also ease staffing issues for NDE personnel with the
added advantage of the AI program’s ability to significantly shorten inspection
time.

For example, as a part of its training for a Reactor Vessel Upper Head (RVUH)
application, an AI model was fed a large volume of UT data from a two-unit PWR
that had been slated for decommissioning. Experts instructed the model to
evaluate the data and alert the examiner if further review and consideration
were needed. Although most of the data volume yielded no flagged indications of
interest, the AI tool was able to identify benign conditions such as
fabrication-related responses that require review from a qualified examiner to
confirm their status. As the AI application performed the monotonous task of
searching through all the UT data looking for indications of interest, the UT
examiners could spend more time evaluating each pre-identified indication by
comparing the response in the new UT data against the long history of archived
data files from the previous examinations. If any changes to the UT indication
were noted to have occurred over time, any changes to the UT responses were
further scrutinised as potentially originating from service-induced degradation.
Such a detailed historical comparison requires significant time, and the use of
AI provided time savings in other areas that then afforded examiners the ability
to expend this additional time where it mattered the most. In the future,
experts plan to develop an AI program for manual and automated PAUT inspections
that will be more heavily involved and complex with the ability to evaluate the
data in real time.

As experts address areas of improvement for Reactor Vessel Upper Head AI tools,
new program field trials for AI applications for other nuclear components have
already begun to launch. Experts are now exploring a comparable program
development and testing process for dissimilar metal welds that may enable them
to build an AI application to examine core shroud welds in BWRs and core barrel
welds in PWRs.

Through these field trials, the industry is seeking a way to close the
technology gap. Online monitoring will perhaps then be able to replace NDE data
collection where it is unsafe for human inspectors to evaluate the reactor
components. With permanent sensors, examiners can continuously monitor for
defects in the component and track flaws that might trigger a need for repairs.

In addition to AI, uncrewed inspection systems, such as drones and permanent
sensors, are emerging automation tools. By integrating all these advanced
technologies into NDE inspection, examiners can use remote inspection for a
potentially fully automated analysis. Automation is the key to efficiency and
reliability. It can also improve the quality of data and lower the cost of
inspections.


FUTURE EVOLUTION OF NDE

As countries focus their attention on advancing nuclear power generation
capabilities, it will become increasingly important for engineers to invest in
effective and cost-efficient advanced monitoring and sensor technology. The
integration of automation into NDE techniques will continue to develop across
the nuclear energy industry. Although experts are still working out the kinks of
using advanced technologies, it is paramount that inspection methodologies
evolve as surrounding technologies evolve to ensure reliable and cost-effective
asset integrity evaluation and monitoring. The success of today’s NDE digital
transformation will also rely on comprehensive training for examiners to become
proficient in the latest and newest tools and technology.

Given nuclear plant inspections continue to evolve from the cumbersome original
tools to increasingly advanced, powerful, and efficient new toolsets, the
transformation of NDE will continue to ensure the safe and sustainable future of
nuclear energy.

--------------------------------------------------------------------------------

Authors: Danny Keck, Independent NDE Consultant and Current Chair of the Board
of ASNT; Randy Linden, Senior Level III for Sonic Systems International; Bret
Flesner, Principal Technical Leader at EPRI; Luke Breon, Senior Technical Leader
at EPRI



Magnetic Particle testing is another technique commonly deployed in nuclear NDE
Safety-related reactor systems are required to undergo regular inspections, in
addition to routine assessments of primary reactor components and containment
vessels

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