NDT methods for underwater concrete structures can generally be divided, according to the physical principle utilized and with respect to their testing capabilities DivineMadhoorandSolomon2014, into two main categories: 1) (physical principle) and 2) (defect detection). Two broad categories of LD are pertinent to this report [4].

2.1.1. Acoustic-Based Methods

Acoustic NDT methods evaluate the interior of concrete using stress waves (mechanical vibrations). These techniques are very sensitive to the presence of internal anomalies such as voids, delamination’s and cracks [5]. Typical techniques based on acoustic include the following:

Impact-Echo(IE):

Applies a short-term mechanical impact to generate stress waves within a structure [6].Analyzes reflected waves from internal defects to identify anomalies.Commonly used for measuring thickness, detecting voids, and mapping delamination.

UltrasonicTesting(UT):

Employs high-frequency sound waves that pass-through concrete.Can be utilized in various scanning modes, including pulse-echo, through-transmission, and phased array.Ideal for assessing concrete quality, searching for voids, and determining material homogeneity [7].

AcousticEmission(AE):

Monitors real-time elastic waves emitted by active defects such as crack growth or corrosion.AE sensors capture the released energy, which is analyzed to locate the source of damage.Particularly effective for tracking the structural health over time [8].

Advantages:

Internal defects are easily detectable.Provides an objective means of collecting both quantitative and qualitative data.Can be adapted for underwater applications by selecting appropriate sensors.

Limitations:

Sound signal propagation can be attenuated in water.Interpretation of results may be complicated by noise and the heterogeneity of concrete.

2.1.2. Hybrid NDT Techniques

Hybrid Non-Destructive Testing (NDT) methods are created by combining two or more individual modalities to enhance diagnostic reliability, sensitivity, and coverage. The integration of complementary physical principles enables a more comprehensive structural characterization [9].

CommonHybridApproaches:

AcousticEmission(AE)+Review+ElectrochemicalSensor:

This approach is used for corrosion monitoring. AE detects cracks caused by corrosion, while electrochemical sensors measure chloride ingress and half-cell potential [10].

UltrasonicTesting(UT)+InfraredThermography(IR):

Currently applied in monitoring systems for thick-walled welds, this combination utilizes non-contact detection and temperature measurement. UT identifies internal flaws, while IR detects variations in surface temperature indicative of subsurface defects or moisture ingress [11].

Drones+Multi-SensorVehicles(MSVs):

Utilizing remotely operated vehicles (ROVs) or drones equipped with ground-penetrating radar (GPR), sonar, visual, and imaging sensors, this approach facilitates extensive underwater inspections [12].

Advantages:

Mitigates the limitations of individual methods.Enhances confidence in defect characterization.Reduces false positives and increases coverage area.

Limitations:

Challenges in data fusion and interpretation.Higher costs due to the complexity and number of sensors required.Necessitates advanced software and skilled operators.

Applying Non-Destructive Testing (NDT) methods to underwater concrete structures presents unique technical and operational challenges that differ significantly from those in dry or above-water conditions. These challenges impact the reliability, accuracy, and feasibility of inspection procedures [13].

2.2.1. Signal Attenuation due to Water and Marine Growth

UnderwaterInterface:Acoustic signals, especially high-frequency waves, experience rapid attenuation in water and concrete during transmission.This attenuation is influenced by factors such as depth, temperature variations, salinity differences, and the presence of suspended particles.As a result, the distance for effective defect inspection is limited, and the signal strength diminishes, making it challenging to detect small defects [14].MarineGrowth:Biofouling organisms, including barnacles, algae, and mollusks, create inhomogeneities on the concrete surface, impacting signal propagation [15].The presence of marine life forms an insulating barrier between the sensor and the concrete surface, disrupting effective coupling.This can lead to deflection or absorption of acoustic signals, resulting in distorted readings and inaccurate measurements [16].

2.2.2. Challenges in Sensor Placement and Data Collection

LimitedAccessibilityandStability:Underwater structures are often located in hard-to-reach or hazardous areas, such as submerged pier supports and offshore platforms.The manual deployment of sensors by divers is time-consuming, labor-intensive, and poses safety risks.Maintaining sensor contact with the structure’s surface is challenging due to water currents and poor visibility [17].SurfacePreparation:Effective non-destructive testing (NDT) relies on clean, flat surfaces for optimal signal transmission.Cleaning surfaces underwater is difficult, often requiring mechanical tools or abrasive blasting, depending on the situation.EquipmentMovementRestrictions:The movement of equipment is limited, complicating the installation of heavy and delicate devices in aquatic environments.Constraints related to tethering, power availability, and diver time further impede data collection efforts [18].

2.2.3. Environmental Noise and Signal Clarity

BackgroundNoise:Underwater environments are rich in sound, filled with waves, marine organism calls, ship traffic, pumps, and turbines.These diverse frequencies can interfere with NDT signal frequencies, obscuring data clarity [19].Signal-to-NoiseRatio(SNR)Challenges:The SNR, defined as the ratio of signal power to noise power, is crucial for detecting weak or subtle signals, particularly in Acoustic Emission and Ultrasonic techniques.Low SNR can mask early signs of damage, delaying necessary interventions [20].InterferencefromElectronicDevices:Underwater facilities may introduce electromagnetic or acoustic interference, complicating interactions with sensitive sensors.

Impact-Echo(IE)MethodOverview

The Impact-Echo (IE) method is a widely used acoustic nondestructive testing (NDT) technique for evaluating the condition of concrete structures. It is particularly effective for non-destructive inspections aimed at identifying internal defects, and it can be applied in both wet and underwater environments [21].

3.1.1. Principle

The IE technique operates by generating a brief impact on the concrete surface using a small hammer, steel ball, or solenoid plunger.This impact produces low-frequency stress waves—both compression and shear—that propagate through the material.When these waves encounter changes in the material, such as voids, delamination’s, or boundaries, they are reflected back to the surface.A receiver (transducer or sensor) captures the lateral vibrations at the surface, which are then analyzed by performing a Fast Fourier Transform (FFT) to convert the time-domain signal into the frequency domain [22].The frequency spectrum reveals peaks that correspond to resonant frequencies, which are used to ascertain the depth and location of internal discontinuities based on known wave speeds [23].

3.1.2. Applications

The Impact-Echo method is versatile and applicable to various types of concrete elements. Key applications include:

InternalVoids: Detection of issues such as honeycombing and inadequate compaction within concrete.DelaminationMapping: Identification of cracking between layers (e.g., concrete overlays) or between reinforcing layers and concrete covers [24].DepthMeasurement: Measuring the depth of walls and structural members in situations where only one side is accessible [25].PrecastInspection: Evaluating precast units for structural integrity prior to installation.

The IE method can also be adapted for underwater conditions using submersible sensors and remote impact devices, enabling the evaluation of submerged piers, slabs, and offshore platforms [26].

3.1.3. Limitations

While the IE method offers several advantages, it also presents limitations, particularly in underwater scenarios:

DependenceonSurfaceCondition:Rough or uneven surfaces can scatter waves, complicating the interpretation of signals.Marine growth or water layers may hinder sensor coupling, negatively impacting signal quality [27].InterpretationChallenges:Differentiating multiple reflections in non-homogeneous concrete can be difficult.Overlapping peaks and low signal-to-noise ratios can complicate the measurement of flaw depth and size [28].SinglePointLimitation:Conventional IE measurements are taken at specific sensor locations, which may result in missed local defects unless a dense grid of measurements is employed [29].

3.1.4. Recent Improvements

Recent advancements in the Impact-Echo method have been driven by innovative technologies:

MachineLearningandAdaptiveSignalAnalysis:These technologies facilitate pattern recognition, clustering algorithms, and neural networks for automated defect classification, reducing human interpretation errors.They enhance the repeatability and precision of defect detection and measurement [30].MultitransducerDevices:Multi-channel/beam IE systems can simultaneously measure over larger areas.This capability leads to faster data acquisition and improved spatial resolution [31].3DSIBIEImaging(StackImagingofSpectralAmplitudesBasedonImpact-Echo):This imaging technique provides a 3D visualization of internal concrete voids derived from multiple IE measurements.It offers a more comprehensive analysis and better focus on flaws compared to conventional single-frequency methods [32].

3.2.1. Types

Ultrasonic testing methods used for underwater concrete inspection can be broadly categorized into Pulse-Echo, Through-Transmission, and Phased Array Ultrasonic Testing (PAUT). The Pulse-Echo technique utilizes a single transducer that emits ultrasonic waves into the concrete and then receives the reflected echoes from internal flaws or interfaces. This method is particularly suitable for underwater environments where only single-sided access is available, such as in submerged piers or dam faces. In contrast, the Through-Transmission method requires a transmitter and a receiver to be placed on opposite sides of the structure. A decrease in received signal energy typically indicates the presence of internal defects. However, due to the need for dual-sided access, this method is less practical for underwater applications. Finally, Phased Array Ultrasonic Testing (PAUT) employs an array of transducers that can emit synchronized ultrasonic pulses, allowing for beam steering, focusing, and real-time imaging. This technique provides high-resolution inspections and is highly suitable for underwater use, especially when integrated with Remotely Operated Vehicles (ROVs) or Autonomous Underwater Vehicles (AUVs) for automated and extended coverage of submerged structures [33].

Pulse-Echo is favored in underwater inspections where only one side of the structure is accessible.

PAUT offers real-time defect imaging and is increasingly adopted for offshore concrete and steel-concrete composites.

3.2.2. Applications

Ultrasonic testing serves a range of diagnostic purposes in underwater concrete structures. It is widely used for flaw detection, enabling the identification of internal anomalies such as cracks, voids, honeycombing, and delamination. The method is also effective for thickness measurement, particularly when access is available from only one side of the structure, as in the case of submerged walls or piles. In addition, ultrasonic testing allows for material characterization, such as estimating the elastic modulus, density, and homogeneity of the concrete. Lastly, it plays a key role in bond integrity testing, helping to evaluate the effectiveness of overlays, grout injections, or the interface between steel reinforcements and concrete [34] (Table 1).

Table 1. Applications of ultrasonic testing in underwater concrete structures.

3.2.3. Limitations

Ultrasonic testing faces several limitations when applied to underwater concrete structures. One major constraint is the need for an effective coupling medium; although water itself can act as a medium, marine growth, biofouling, or surface irregularity can hinder proper transducer coupling and reduce signal reliability [35]. Additionally, signal attenuation occurs due to the presence of coarse aggregates and water-filled pores, which diminish wave intensity and reduce the depth of penetration. The presence of heterogeneous materials, such as embedded steel reinforcements or large aggregates, further complicates signal interpretation by causing wave scattering and diffraction. Finally, access and alignment challenges arise because precise positioning of sensors underwater is difficult, especially without the assistance of robotic systems or positioning arms, which limits inspection coverage and repeatability [36].

3.2.4. Recent Improvements

Recent advancements have significantly enhanced the effectiveness of ultrasonic testing in underwater environments. The adoption of Phased Array Ultrasonic Testing (PAUT) allows for fast, steerable scanning and provides 2D or 3D imaging, which improves the detection and characterization of subsurface defects. In parallel, advanced signal processing techniques—such as Fast Fourier Transform (FFT), wavelet analysis, and AI-based classification algorithms—have improved the accuracy of flaw detection by enhancing signal clarity and enabling automated interpretation [37]. The development of smart underwater probes, including self-leveling sensors or those mounted on Remotely Operated Vehicles (ROVs), ensures better stability and precision during inspections in turbulent or inaccessible zones [38]. Finally, the hybrid integration of ultrasonic methods with other techniques like Impact-Echo or Acoustic Emission boosts diagnostic reliability by providing complementary insights from multiple NDT approaches [39] (Table 2).

Table 2. Recent improvements in ultrasonic testing for underwater concrete structures.

KeyEquations

1)DepthEstimationinPulse-EchoMode

Used to determine defect or back-wall location:

where:

d = depth or thickness (m)C = ultrasonic wave velocity in concrete (typically 3500 - 4500 m/s)t = round-trip time-of-flight of the signal (s)

2)MaterialCharacterizationviaWaveSpeed

Determines compressional wave velocity:

where:

C = wave speed (m/s)L = known distance between sensors (m)t = travel time of wave (s)

3)DynamicModulusEstimation

If density ρ is known:

where:

E d = dynamic modulus of elasticity (Pa) ρ = concrete density (kg/m³) C = wave velocity (m/s)

AcousticEmission(AE) is a passive, non-destructive method used to observe transient elastic waves generated by the rapid release of energy from localized sources, such as crack formation, corrosion activity, or micro-damage within a structure. AE is increasingly advantageous for monitoring underwater concrete structures, enabling real-time assessment of degradation processes without interrupting service [40].

3.3.1. Principle

AE can detect stress waves produced by internal activities, such as micro-cracking or corrosion-induced rupture, within the material. These waves propagate through the concrete and are captured by sensors, which may be either surface-mounted or embedded within the material [41].

The underlying principle is based on wave propagation theory, which states that local events (such as crack tips) emit elastic waves.In concrete, AE signals typically fall within the frequency range of 100 kHz to 1 MHz.Triangulation of the event source is achieved by analyzing the Time-of-Arrival (TOA) of signals detected by multiple sensors.

KeyEquation:SourceLocation(Triangulation)

In 2D localization:

where:

( x , y ) : source coordinates ( x i , y i ) : sensor location v : wave velocity in concrete t i : arrival time at sensor iii t o : event occurrence time.

3.3.2. Applications

Acoustic Emission (AE) monitoring plays a vital role in the real-time evaluation of underwater concrete structures. One of its primary uses is in crack propagation monitoring, where it detects the release of energy during active crack formation, especially under conditions of mechanical loading or thermal variation. This provides valuable insight into the structure’s response to environmental or operational stresses. Additionally, AE is effective in corrosion detection, as it can sense micro-events associated with rust-induced expansion or deterioration of steel-concrete bonds [42]. Another key application is in identifying leakage or cavitation, where sudden pressure changes or fluid turbulence in submerged pipelines or structures produce high-energy acoustic signals. Finally, AE is widely used in structural health monitoring, enabling long-term, continuous surveillance of concrete condition throughout its service life, which is essential for early fault detection and preventive maintenance planning [43] (Table 3).

Table 3. Applications of acoustic emission monitoring in underwater concrete structures.

3.3.3. Limitations

While Acoustic Emission (AE) monitoring offers real-time diagnostic capabilities, its application in underwater environments faces several limitations. One of the most significant issues is environmental noise interference, where marine traffic, wave activity, and biological sources such as fish or marine mammals can generate background noise that mimics or obscures true AE signals [44]. Another challenge is source localization, which requires accurate acoustic velocity models of the structure and often a dense array of sensors to triangulate the emission source—a requirement that is difficult to achieve underwater. Additionally, signal attenuation is a critical limitation; high-frequency AE waves are more rapidly absorbed in water compared to lower-frequency signals used in methods like ultrasonic testing, which reduces the detection range and sensitivity. Finally, complex data interpretation is a persistent issue due to waveform dispersion, overlapping events, and the need to distinguish between different types of signals, often requiring advanced filtering or machine learning techniques to improve reliability [45].

3.3.4. Recent Improvements

Recent technological advancements have significantly enhanced the performance and applicability of Acoustic Emission (AE) monitoring in underwater concrete structures. One major improvement is the development of fiber-optic AE sensors, such as Fiber Bragg Grating (FBG) sensors, which are highly resistant to corrosion, unaffected by electromagnetic interference, and capable of functioning reliably in high-pressure submerged environments [46]. In addition, machine learning algorithms—including neural networks and Support Vector Machines (SVMs)—have been applied to classify AE signals more accurately, reducing false alarms by distinguishing between structural emissions and background noise. Another advancement is the use of wavelet-based de-noising techniques, which help extract meaningful AE data from noisy underwater environments by isolating relevant signal components. Lastly, AE data is increasingly being integrated with structural models, such as finite element simulations, to correlate acoustic activity with predicted stress or damage zones, enabling predictive assessments and enhancing decision-making in maintenance planning [47].

KeySignalParametersinAEAnalysis

Concept

“Hybrid Non-Destructive Testing (NDT) involves combining two or more NDT techniques, either independently or in tandem, to leverage the complementary strengths of each method while minimizing their individual limitations. In underwater concrete structures, hybrid systems offer significantly more reliable and clearer signals with higher resolution compared to localized measurements [48].

Some commonly used hybrid approaches include:

IE + UT for detecting voids and delamination’sAcoustic Emission (AE) + Electrochemical Impedance Spectroscopy (EIS) for monitoring corrosion due to CO₂AE + Infrared Thermography (IRT) for assessing crack progression and moisture levelsUltrasonic Testing (UT) + Ground Penetrating Radar (GPR) for internal structural imaging”

Benefits

IllustrativeExample

MathematicalRepresentation:DataFusion

Hybrid systems often rely on datafusion techniques to combine outputs. A basic data fusion model:

where:

D hybrid : fused diagnostic decision D i : diagnostic data from method iii f fusion function (e.g., weighted average, machine learning model)

HybridApproachesinNon-DestructiveTesting(NDT)

Hybrid approaches are increasingly prevalent in both field and laboratory applications, addressing the limitations of individual NDT techniques. Below, we present two illustrative examples that highlight the utility and convenience of these methods for underwater assessments [49].

4.2.1. Acoustic Emission (AE) and Voltammetry Monitoring

Philosophy:

Acoustic Emission (AE) techniques are capable of detecting mechanical energy resulting from both active cracking and corrosion. When combined with electrochemical methods—such as half-cell potential measurements and electrochemical impedance spectroscopy (EIS)—these techniques provide valuable insights into corrosion kinetics and the electrochemical behavior of reinforcing materials [50].

Applications:

Inspection of underwater bridge piles and subaqueous tunnel liningsMonitoring the initiation and progression of corrosion in reinforced concrete over the service life [51].

Benefits:

Localization and timing of damage mechanisms (e.g., crack initiation) through AEComprehensive corrosion assessments, including corrosion rates and states (passive/active) via electrochemical methodsIntegrated early warning and tracking capabilities [52]

ExampleWorkflow:

1) AE transducers are employed to continuously monitor microcrack emissions.

2) These emissions are spectrally correlated with anodic corrosion activity using electrochemical probes.

3) The resulting data on the location and severity of damage, as determined by AE and EIS, informs maintenance priorities.

Continued

4.2.2. Drones Equipped with GPR and Infrared Sensors

Drone vehicles are equipped with Ground Penetrating Radar (GPR) for subsurface scanning and Infrared Thermography (IRT) for surface temperature mapping. This technology effectively identifies moisture ingress, delaminations, and thermal anomalies in concrete structures, particularly those near or extending to bodies of water.

Applications:

Bridge decks, dam faces, and harbor structures above the waterlineAccess-restricted or hazardous areas

Benefits:

GPR detects subsurface flaws, including voids and corrosion zones in steelIRT captures temperature gradients indicative of moisture entrapment or delaminationUAVs enable rapid, wide-area, and repeatable scanning [53]

CaseExample:

During the inspection of a sea-facing retaining wall, drones equipped with 1 GHz GPR antennas and FLIR IRT cameras were deployed. The GPR identified areas of steel corrosion, while the IRT revealed heat concentrations corresponding to water ingress. This combined analysis produced a detailed 3D damage map [54].

Hybrid Non-Destructive Testing (NDT) techniques offer higher accuracy and improved diagnostic capabilities. However, their application, particularly in underwater concrete structures, is limited due to various technical, practical, and economic challenges. Understanding these limitations is essential for optimizing their use and guiding future advancements [55].

4.3.1. Technical Complexity

DataSynchronization: Acquiring and synchronizing data from multiple NDT techniques, such as Acoustic Emission (AE) and Electrical Impedance Spectroscopy (EIS), requires precise timing, calibration, and sophisticated synchronization algorithms.SensorIntegration: Hybrid systems necessitate that sensors be compatible not only physically (in terms of environmental and mechanical factors like waterproofing and pressure resistance) but also functionally, ensuring they can operate effectively under similar conditions [56].Interference: Signal integrity can be compromised due to overlapping frequency bands or electromagnetic interference among devices, leading to distorted or corrupted data [57].

4.3.2. Fusion and Interpretation of Data

ComplexAlgorithms: Effective integration of data across different modalities (mechanical, thermal, electrical) often relies on machine learning (ML), artificial intelligence (AI), or statistical modeling, which can introduce significant computational demands [58].RequiredExpertise: Interpreting the combined outputs necessitates expertise across various domains, including signal processing, electrochemistry, and structural engineering.UncertaintyQuantification: The results from integrated methods must quantify confidence intervals and uncertainties, a process that can be more complex than that associated with single-method approaches.

Equation(BasicDataFusionModel):

where:

D h y b r i d : combined diagnostic decision;

D i : diagnostic data from method iii;

w i : weighting factor based on reliability or signal quality.

4.3.3. Operational Constraints

IncreasedEquipmentSizeandWeight: The integration of multiple tools (such as Ground Penetrating Radar (GPR) and Infrared Thermography (IRT) with drones or Autonomous Underwater Vehicles (AUVs)) typically leads to an increase in payload, which can compromise mobility and maneuverability, particularly in robotics designed for underwater environments [59].

PowerConsumption: Operating several devices simultaneously demands greater power, necessitating larger power supplies. As a result, our devices may have reduced operational time.

EnvironmentalCompatibility: Each technique has optimal environmental conditions. For example, Infrared Thermography requires thermal gradients, while GPR works best with dry materials. Achieving these conditions can be particularly challenging in underwater or marine settings [60].

4.3.4. Cost and Practicality Factors

IncreasedCapitalCosts: Hybrid systems often require:

Advanced hardware and software developmentSpecialized drones or platformsMore highly educated and trained personnel

MaintenanceandCalibration: The need for maintenance scales with the number of devices; more equipment means more frequent upkeep. Additionally, calibration is necessary for each sensor type that a device accommodates, which poses significant challenges for long-term underwater deployments.

LackofCommercialSolutions: Despite several years of development in hybrid systems, most available options remain prototypes or laboratory-level solutions. Currently, there are no integrated, off-the-shelf solutions specifically designed for underwater concrete applications [61] (Table 4).

Table 4. Summary of challenges in Hybrid NDT systems.

Impact-Echo is ideal for detecting delaminations and thickness changes but struggles with underwater coupling.UltrasonicTesting excels at penetration and resolution but requires sophisticated coupling methods underwater [62].AcousticEmission provides valuable real-time data on active defects but faces challenges with noise and signal localization underwater [63].HybridTechniques offer the most comprehensive approach by combining complementary strengths but come with increased complexity and costs.

6.1.1. Environmental Limits

WaterAttenuation: The quality of signals in acoustic and ultrasonic methods is adversely affected by water attenuation, scattering, and absorption [65].SevereEnvironments: Conditions such as saltwater corrosion, biofouling, and turbulent underwater currents pose challenges to sensor durability and data collection accuracy.TemperatureandPressureEffects: Variations in temperature and pressure can impact sensor calibration and accuracy, especially in deep-water applications [66].

6.1.2. Sensor Distribution and Coupling

Coupling: Reliable methods for coupling underwater ultrasonic or impact-echo transducers are currently lacking, necessitating innovations to create stable interfaces between sensors and structures.RemoteDeployment: Accessing submerged structures typically requires Remotely Operated Vehicles (ROVs) or Autonomous Underwater Vehicles (AUVs) equipped with NDT sensors [67].

6.1.3. Processing and Interpretation of Data

ComplexDataFusion: Effective data fusion involves not only integrating multi-modal data but also utilizing advanced algorithms and AI models to address noise, redundancy, and uncertainties inherent in such data.ExpertiseRequiredforHybridNDT: The interpretation of hybrid NDT data necessitates a diverse skill set, which poses scalability and widespread adoption challenges.

6.1.4. Normalization and Validation

InsufficientStandardProcedures: The absence of standardized procedures for underwater NDT complicates the comparison of test results and the certification of methods.InsufficientFieldValidation: Many innovations are developed and tested in laboratory settings at small scales, lacking adequate field validation [68].

6.2.1. Advanced Sensing Technologies

FiberOpticSensors: These sensors offer high sensitivity, electromagnetic immunity, and enhanced robustness for underwater applications [69].MiniatureandWirelessNodes: These can be easily installed on ROVs/AUVs and at challenging access points [70].Self-PoweredSensors: Energy harvesting from underwater currents or vibrations can power these sensors, significantly extending their operational lifespan.

6.2.2. Artificial Intelligence and Machine Learning

AutomationofFaultDetection: AI models can provide more accurate results and reduce the risk of human interpretation errors.PredictiveMaintenance: Real-time data sharing with NDT and IoT platforms facilitates in-service structural integrity monitoring and predicts defects and failures.DataFusionAlgorithms: Employing robust multi-sensor integration and real-time analytics can enhance the effectiveness of hybrid NDT.

6.2.3. Improvements in Coupling and Deployment Tools

Non-ContactNDTMethods: Techniques such as laser ultrasonics or air-coupled ultrasound can eliminate the need for underwater coupling.IntegratedROV/AUVPlatforms: Custom NDT payloads can be developed for underwater robots to enable autonomous inspections.

6.2.4. Standardization Efforts

Establishing international standards and procedures for underwater NDT techniques, along with constructing benchmark datasets and validation methods, will facilitate method comparison and certification (Table 5).

Table 5. Summary of challenges and future research areas.