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The article investigates the possibility of detecting defects in the form of transverse cracks in rail foot under continuous in-service inspection of rails. The MFL method is chosen as an alternative to ultrasonic testing. Computer modeling was carried out, based on the results of which a working model of the system for magnetizing and recording of monitoring signals was developed and constructed. Experimental studies on detection of crack models in rail foot were carried out in laboratory conditions. The studies confirmed the results of computer modeling and proved the possibility of detecting such crack models. The minimum sizes of detectable crack models in the zone of rail fastening and between them have been estimated. [ABSTRACT FROM AUTHOR]

The life-limiting fitness for service of high-temperature components is of interest in design, fabrication and later assessments of remaining creep life. Of the associated indicators, strain reflects creep in design and in service, while the discontinuities like creep cavities are targeted in the in-service inspections. Microstructure and hardness can provide supporting information on the material condition. Here, we assess such indicators for the creep-associated damage, particularly at the early stages. Improvements appear possible, e.g. in microscopy to support metallographic inspections and in utilising the widening inspection experience on newer materials. The present work successfully integrated the Wilshire/LCSP creep strain and rupture models with FE analysis for predicting creep strain evolution. Since the model applies for the whole creep curve, it can be used for early stages of creep down to the limit of negligible creep and to the lower limit of the window where creep cavitation damage can be observed. [ABSTRACT FROM AUTHOR]

Thermal fatigue cracks occurring in pipes in nuclear power plants pose a high degree of risk. Thermal fatigue cracks are generated when the thermal fatigue load caused by local temperature gradients is repeatedly applied. The flaws are mainly found in welds, owing to the effects of stress concentration caused by the material properties and geometric shapes of welds. Thermal fatigue pipes are classified as targets of risk-informed in-service inspection, for which ultrasonic testing, a volumetric non-destructive testing method, is applied. With the advancement of ultrasonic testing techniques, various studies have been conducted recently to apply the phased array ultrasonic testing (PAUT) method to the inspection of thermal fatigue cracks occurring on pipes. A quantitative reliability analysis of the PAUT method must be performed to apply the PAUT method to on-site thermal fatigue crack inspection. In this study, to evaluate the quantitative reliability of the PAUT method for thermal fatigue cracks, we fabricated crack specimens with the thermal fatigue mechanism applied to the pipe welds. We performed a round-robin test to collect PAUT data and determine the validity of the detection performance (probability of detection; POD) and the error in the sizing accuracy (root-mean-square error; RMSE) evaluation. The analysis results of the POD and sizing performance of the length and depth of thermal fatigue cracks were comparatively evaluated with the acceptance criteria of the American Society of Mechanical Engineers Code to confirm the effectiveness of applying the PAUT method. [ABSTRACT FROM AUTHOR]

The automated inspection and mapping of engineering structures are mainly based on photogrammetry and laser scanning. Mobile robotic platforms like unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs), but also handheld platforms, allow efficient automated mapping. Engineering structures like bridges shadow global navigation satellite system (GNSS), which complicates precise localization. Simultaneous localization and mapping (SLAM) algorithms offer a sufficient solution, since they do not require GNSS. However, testing and comparing SLAM algorithms in GNSS-denied areas is difficult due to missing ground truth data. This work presents an approach to measuring the performance of SLAM in indoor and outdoor GNSS-denied areas using a terrestrial scanner Leica RTC360 and a tachymeter to acquire point cloud and trajectory information. The proposed method is independent of time synchronization between robot and tachymeter and also works on sparse SLAM point clouds. For the evaluation of the proposed method, three LiDAR-based SLAM algorithms called KISS-ICP, SC-LIO-SAM, and MA-LIO are tested using a UGV equipped with two light detection and ranging (LiDAR) sensors and an inertial measurement unit (IMU). KISS-ICP is based solely on a single LiDAR scanner and SC-LIO-SAM also uses an IMU. MA-LIO, which allows multiple (different) LiDAR sensors, is tested on a horizontal and vertical one and an IMU. Time synchronization between the tachymeter and SLAM data during post-processing allows calculating the root mean square (RMS) absolute trajectory error, mean relative trajectory error, and the mean point cloud to reference point cloud distance. It shows that the proposed method is an efficient approach to measure the performance of SLAM in GNSS-denied areas. Additionally, the method shows the superior performance of MA-LIO in four of six test tracks with 5 to 7 cm RMS trajectory error, followed by SC-LIO-SAM and KISS-ICP in last place. SC-LIO-SAM reaches the lowest point cloud to reference point cloud distance in four of six test tracks, with 4 to 12 cm. [ABSTRACT FROM AUTHOR]

Looseness of high-strength wind turbine bolts is one of the main types of mechanical failure that threaten the quality and safety of wind turbines, and how to non-destructively detect bolt loosening is essential to accurate assessment of operational reliability of wind turbine structures. Therefore, to address the issue of looseness detection of high-strength wind turbine bolts, this paper proposes a non-destructive detection method based on digital image correlation (DIC). Firstly, the mathematical relationships between the inplane displacement component of the bolt's nut surface, the bolt's preload force loss and the bolt loosening angle are both deduced theoretically. Then, experimental measurements are respectively conducted with DIC with different small bolt loosening angles. The results show that the bolt loosening angle detection method based on DIC has a detection accuracy of over 95%, and the bolt's preload force loss evaluated by the deduced relationship has a good agreement with the empirical value. Therefore, the proposed DIC-based bolt loosening angle detection method can meet the requirements of engineering inspection, and can achieve quantitative assessment of preload forces loss of wind turbine bolt. [ABSTRACT FROM AUTHOR]

Background: The widespread use of large-space structures has led to a subsequent increase in the demand for the inspection and monitoring of engineering structures. Digital construction of engineering structures poses a challenge to conventional measurement methods. The development of noncontact measurement methods based on computer vision and photogrammetry technologies has made these measurements possible. Objective: In this study, cable tension and progressive collapse processes of suspen-dome structure were investigated using unmanned aerial vehicle (UAV)-assisted close-range photogrammetry and multi-camera stereo-digital image correlation (stereo-DIC). Methods: Based on the principles of close-range photogrammetry, three-dimensional (3D) points reconstructed by a digital single-lens reflex (DSLR) camera and camera mounted on UAV are registered, and the global coordinate system is established. In the cable tension process, a stereo-DIC system enhanced by parallel computing was used to monitor the displacement of the local structure in real time, and the tension process was accurately controlled using real-time monitoring data. The UAV was then used to measure the whole-field static displacement of the upper control points after tension. Finally, the progressive collapse displacement monitoring of the structure is realized by a multi-camera stereo-DIC system comprising 12 high-speed cameras, and the coordinate system of the 12 subsystems is unified to the established global coordinate system. Results: The results indicate that the displacement sensitivity of a multi-camera stereo-DIC system is higher than 0.05 mm. The measurement results show that the structure meets the design index after tension. The static displacement of the nodes before and after tension can be measured accurately based on the UAV and close-range photogrammetry, which directly reflects the overall deformation trend of the structure after tension. The collapse test results indicate that the structure collapsed quickly after slow deformation for approximately 2.5 s. Conclusions: The UAV-assisted close-range photogrammetry and multi-camera stereo-DIC system accurately captured the 3D displacement data of both cable tension and progressive collapse processes. The accurate measurement of these data has a great value for engineering applications, model tests, and numerical analysis. [ABSTRACT FROM AUTHOR]

Ultrasound is widely used in medical and engineering inspections due to its non-destructive and easy-to-use characteristics. However, the complex internal structure of plant stems presents challenges for ultrasound testing. The density and thickness differences in various types of stems can cause different attenuation of ultrasonic signal propagation and the formation of different echo locations. To detect structural changes in plant stems, it is crucial to acquire complete ultrasonic echo RF signals. However, there is currently no dedicated ultrasonic RF detection equipment for plant stems, and some ultrasonic acquisition equipment has limited memory capacity that cannot store a complete echo signal. To address this problem, this paper proposes a double-layer multiple-timing trigger method, which can store multiple trigger sampling memories to meet the sampling needs of different plant stems with different ultrasonic echo locations. The method was tested in experiments and found to be effective in acquiring complete ultrasonic RF echo signals for plant stems. This approach has practical significance for the ultrasonic detection of plant stems. [ABSTRACT FROM AUTHOR]

International fabrication codes and standards provide minimum distance criteria for proximity welds, although rigorous justification is lacking. These distances are either based on practical experience or mutual agreement and are often left to the engineering judgment of contractors, inspection engineers, etc., especially in cases of repair welds fabricated in proximity to existing welds. Previous studies have shown high tensile residual stresses and altered mechanical and microstructural properties between proximity welds. This article focuses on numerical and experimental quantification of residual stresses in the proximity region by X-ray diffraction (XRD) and finite element method (FEM) thermo-mechanical models. Specimens were machine welded, then repair welded at distances of 5–15 mm. A fair agreement in results was achieved between FEM and XRD. The most detrimental effect was observed at the weld root toe for the repair weld at 5 mm proximity, likely due to the high constraint and multiaxial stress state. These findings enable practitioners to propose technical justification and corrective actions while specifying minimum distance criteria for proximity welds. [ABSTRACT FROM AUTHOR]

Most WWER-440 reactors are operated over the planned operational lifetime of 30 years. Now, the owners/operators are preparing for the second phase of extending the operation. The paper presents an overview of the most important aspects of ageing of the main components of the WWER-440-type reactors based on the operational and ageing management experiences and primary research efforts supporting the operation. The paper aims to demonstrate that the expectations for the operability of these reactors for up to 60–70 years are realistic. The scope of the review is limited to the ageing of the reactor pressure vessel, vessel internals, and steam generator, which are the lifetime-limiting components besides the containment structure. Some of the corrective actions, improvements of in-service inspections, maintenance, and ageing management are also considered in the paper. It is shown that the selection of materials and unavoidable material degradation processes do not limit the operation of the WWER-440 reactors for up to 60–70 years under the established operational environment and ageing management practice. [ABSTRACT FROM AUTHOR]

The safety operation of dams after extreme load is an important frontier research topic in the field of dam engineering. The dam health monitoring provides a reliable data basis for a safety evaluation after extreme loads. This study proposes a novel data-driven fusion model for a dam safety evaluation after extreme load based on monitoring data derived by sensors. First, the relationship between dam environmental quantity and effect quantity is deeply excavated based on bidirectional long short-term memory (BiLSTM) network, which is a deeply improved LSTM model. Aiming at the parameter optimization problem of BiLSTM model, sparrow search algorithm (SSA), which is an advanced optimization algorithm, is integrated. Second, conducting the constructed SSA-BiLSTM model to estimate the change law of dam effect quantity after the extreme load. Finally, the Mann–Whitney U-test theory is introduced to establish the evaluation criterion of the dam safety state. Project case shows that the multiple quantitative prediction accuracy evaluation indicators of the proposed method are significantly superior to the comparison method, with mean absolute percentage error (MAPE) and mean absolute error (MAE) values decreasing by 30.5% and 27.8%, respectively, on average. The proposed model can accurately diagnose the dam safety state after the extreme load compared with on-site inspection results of the engineering department, which provides a new method for dam safety evaluation. [ABSTRACT FROM AUTHOR]

Model inspections are important to ensure high‐quality software and to satisfy legal obligations in model‐based engineering processes. As model‐based specifications are typically documented on type‐level, errors concerning the interactions between multiple system instances can go unnoticed. For collaborative cyber‐physical systems (CPS), a plethora of possible instance‐level configurations need to be taken into account. Therefore, we propose the definition of instance‐level review diagrams that show representative interactions of instance‐level configurations that help detect defects in the system specification. To evaluate the approach, we conducted a controlled experiment whose results indicate that instance‐level review diagrams have—compared with type‐level diagrams—important positive effects on reviewing processes for behavioral specifications of CPS. Specifically, the experiment provides empirical evidence that instance‐level review diagrams are significantly more expressive and effective than type‐level diagrams. [ABSTRACT FROM AUTHOR]

The inspection of structures operating at high temperatures is a major challenge in a variety of industries, including the energy and petrochemical industries. Operators are typically performing nondestructive evaluations using ultrasound to monitor component thicknesses during scheduled shutdowns, thereby ensuring safe operation of their plants. However, despite being costly, this calendar-based approach may lead to undetected corrosion, which can potentially result in catastrophic failures. There is therefore a need for ultrasonic transducers designed to withstand permanent exposure to high temperatures, so as to continuously monitor the remnant thicknesses of structures in real time. This paper discusses the design of a heat-resistant ultrasonic transducer based on a piezoelectric element. The piezoelectric material, the electrodes, the backing layer, the wires and the casing are presented in detail from the acoustic and thermal expansion point of view. Four transducers optimized for 3 MHz were manufactured and tested to destruction in different conditions: (1) 72-h temperature steps from room temperature to 750 ∘ C, (2) thermal cycles from room temperature to 500 ∘ C and (3) 60 days of continuous operation at >550 ∘ C. The paper discusses the results, as well as the effect of temperature over time on the properties of the transducer. [ABSTRACT FROM AUTHOR]

This paper presents an automated Non-Destructive Testing (NDT) system for the in-service inspection of orbital welds on tubular components operating at temperatures as high as 200 °C. The combination of two different NDT methods and respective inspection systems is here proposed to cover the detection of all potential defective weld conditions. The proposed NDT system combines ultrasounds and Eddy current techniques with dedicated approaches for dealing with high temperature conditions. Phased array ultrasound was employed, searching for volumetric defects within the weld bead volume while Eddy currents were used to look for surface and sub-surface cracks. The results from the phased array ultrasound results showed the effectiveness of the cooling mechanisms and that temperature effects on sound attenuation can be easily compensated for up to 200 °C. The Eddy current results showed almost no influence when temperatures were raised up to 300 °C. [ABSTRACT FROM AUTHOR]

Response measurement of various functionality states of machines is an inevitable part of smooth production. An effectively efficient measurement and control system of the machinery helps the inspection engineers to detect failures. In the recent age, the concept of industry 5.0, which focuses on the interaction between humans and machines, has increased the importance of sensors in the industry. Various sensing devices may aid and support the machining process, making it more efficient. These sensing devices support machine tools and enhance productivity by reducing failures. The application of an online monitoring system that includes vibration measurement and tool wear measurement, and the electrical energy consumption is getting fame in industry and academia. This paper mainly presents a holistic review of various sensors and their application in the manufacturing processes. Advancements in the sensor for quality measurement, cutting force measurement, and tool wear measurement are discussed. Furthermore, the adoption of the Internet of Things (IoT) in machining processes and conversion of conventional manufacturing processes into modern digitalized systems are discussed. Recent trends of research to improve the sensor technology have been improved. This study provides fundamental guidelines for using and adopting the various types of sensors in machining processes. [ABSTRACT FROM AUTHOR]

The heat generated in reactor core is extracted using the sodium water heat exchanger system in fast breeder reactor. In the heat exchanger system there are 8 steam generators. Steam generator uses sodium and water to generate steam. Sodium–water reaction is exothermic in nature, so SG tubes need inspection to check healthiness of the tube. Due to space constraints, in-service inspection of SG needs remote-controlled robotic arm to locate SG tubes. The tube sheet is planar, so revolute joint two-link robotic arm is adapted. The movement of two-axis robotic arm needs control on position as well as velocity. The dynamic equation of two-axis robotic arm is coupled in nature which makes the control of end effector very difficult. The un-modeled phenomena, as that of friction and errors in mass distribution, will drastically affect the tracking of the end effector in the desired path. The Coriolis Effect is also accounted in the model. To precisely control the robotic arm end effector, the computed torque control technique is proposed and used in this paper. [ABSTRACT FROM AUTHOR]

The use of Unmanned Aerial Vehicles (UAVs) for surveying is at the forefront of their use in the Architectural Engineering and Construction (AEC) industry. UAVs make accessing hard-to-reach construction regions simpler and more cost-effective because of their small size, ease of mobility, and the wealth of information given by their integrated sensors. Accordingly, their use is thriving in different AEC sectors such as the management and inspection of engineering facilities such as concrete bridges. Overpass bridge engineering inspections are still applied using high accuracy surveying instruments in situ to ensure meeting the quality standards of construction. One important application is to measure the bridge pier caps centerline fitting using total stations, which is costly in terms of time and labor. Therefore, in this article, a new approach based on consumer-grade UAV imaging is proposed for replacing the traditional surveying techniques which are expected to improve automation and reduce time and cost. The proposed method utilized a sequence of processes on the UAV point clouds of the bridge concrete pier caps to finally extract the pier pads center and check their alignment. In two experiments, point clouds are created using DJI Phantom 3 images taken over bridge pier projects under construction, and concrete pad centers are then estimated and compared to the reference total station measurements. The results of both tests reveal the ability of the proposed method to attain the required accuracy for the pads' alignment, as the root mean square error (RMSE) is one centimeter and two centimeters for the first and second tests, respectively. In addition, the new approach can reduce implementation time and the project budget. [ABSTRACT FROM AUTHOR]

Failure due to cracks is a major structural safety issue for engineering constructions. Human examination is the most common method for detecting crack failure, although it is subjective and time-consuming. Inspection of civil engineering structures must include crack detection and categorization as a key component of the process. Images can automatically be classified using convolutional neural networks (CNNs), a subtype of deep learning (DL). For image categorization, a variety of pre-trained CNN architectures are available. This study assesses seven pre-trained neural networks, including GoogLeNet, MobileNet-V2, Inception-V3, ResNet18, ResNet50, ResNet101, and ShuffleNet, for crack detection and categorization. Images are classified as diagonal crack (DC), horizontal crack (HC), uncracked (UC), and vertical crack (VC). Each architecture is trained with 32,000 images equally divided among each class. A total of 100 images from each category are used to test the trained models, and the results are compared. Inception-V3 outperforms all the other models with accuracies of 96%, 94%, 92%, and 96% for DC, HC, UC, and VC classifications, respectively. ResNet101 has the longest training time at 171 min, while ResNet18 has the lowest at 32 min. This research allows the best CNN architecture for automatic detection and orientation of cracks to be selected, based on the accuracy and time taken for the training of the model. [ABSTRACT FROM AUTHOR]

In order to analyze comprehensively the safety and stability of the water diversion channel in service in large-scale irrigation area, and to provide a reliable disease control scheme, aiming at the diseases commonly in the diversion canal in large-scale irrigation area and taking the diversion canal of Yinqin irrigation area in Jiaozuo City as an example, the in-situ quality inspection and numerical simulation were made in the diversion canal, and then comprehensive evaluation was made on the safety and software of the diversion canal, while a targetable strengthening disease control scheme was put forward. The research results show that the method combining in-situ inspection and analysis with numerical simulation of the static and dynamic statuses can evaluate the overall safety and stability of the diversion canal structure more scientifically. [ABSTRACT FROM AUTHOR]

For 9–12% Cr creep-resistant steels, a new kind of replica, contemporaneously morphological and extractive, is nowadays in use. This method is non-destructive and 'in situ' applicable via a customised portable equipment and allows the study of the steel microstructure evolution during in-service inspections. The technique produces a neat imprint of the steel microstructure, like a morphological replica, but contemporaneously extracts particles down to 15–20 nm diameters. The use of a good electrical conductor extraneous to the steel composition as a replication basis allows the investigation of the martensitic (sub-) microstructure together with the particle distribution, nanometric dimensional and chemical analyses using a tungsten electrode scanning electron microscope at magnifications up to 500000×. For component residual life assessment, besides a measuring technique and a damage witnessing criterion, a reference is needed against which spent lifetime through which or actual damage can be estimated.. [ABSTRACT FROM AUTHOR]

Regular inspection of pavement cracks is an important task to ensure the safety of the transportation system. At present, many pavement crack detection methods still rely on the manual way. These methods are usually time-consuming and subjective. Moreover, although the automatic crack detection method has made great progress recently, there are still difficulties such as poor anti-interference ability and low detection efficiency. Therefore, this paper proposes a pavement crack detection algorithm, which can solve the above problems well. This algorithm combines single stage salient-instance segmentation (S4Net) and concatenated feature pyramid network (CFPN), which greatly improves the ability to acquire feature information. Experiments show that on the noise-free dataset, the average precision, average recall, and F1-score are 0.9331, 0.9358, and 0.9344, respectively. On the complex noise dataset, the average precision, average recall, and F1-score are 0.8244, 0.8653, and 0.8443, respectively. Compared with other methods, our method has the advantages of strong anti-noise ability, high detection accuracy and fast detection speed. In addition, we propose a method for calculating the physical size of cracks. Through error analysis, the relative errors of calculating the length and width of the cracks are 0.056 and 0.084 respectively, which can meet the needs of engineering inspection. [ABSTRACT FROM AUTHOR]

As protection for nuclear power plants is quite necessary, the nuclear fuel is sealed in zirconium alloy thin wall cladding. During service, fuel rods might be damaged caused by wall-thickness thinning, cladding corrosion and cracking, etc. This will cause the coolant to enter into the fuel rod, which may lead to the failure of the fuel assembly. However, current diagnostic methods have limitations due to the special structure of the fuel assembly and the underwater and radioactive environment. In this paper, a novel inspection method is proposed to recognize the failure of a fuel rod. The fuel rod failure can be detected based on the presence or absence of coolant inside the fuel rod by using an ultrasonic plate wave. The inspection model and process algorithm are proposed for in-service inspection. The relationship between signal and scanning position is established and analyzed. Both ultrasound field simulation and experiment have been carried out for validation. The corresponding results illustrate that the failed nuclear fuel rod of the whole fuel assembly (including the internal rods) can be effectively detected without the influence of the near-field region by using the proposed method. [ABSTRACT FROM AUTHOR]

The article presents non-destructive testing (NDT)-related products including Cygnus New Underwater Tester, Teledyne FLIR's Lepton 3.1R radiometric thermal camera module, and Phoenix Inspection Systems Ltd.'s Gyro rotary axis scanner.

Photographs of bridges can reveal considerable technical information such as the part of the structure that is damaged and the type of damage. Maintenance and inspection engineers can benefit greatly from a technology that can automatically extract and express such information in readable sentences. This is possibly the first study on developing a deep learning model that can generate sentences describing the damage condition of a bridge from images through an image captioning method. Our study shows that by introducing an attention mechanism into the deep learning model, highly accurate descriptive sentences can be generated. In addition, often multiple forms of damage can be observed in the images of bridges; hence, our algorithm is adapted to output multiple sentences to provide a comprehensive interpretation of complex images. In our dataset, the scores of Bilingual Evaluation Understudy (BLEU)‐1 to BLEU‐4 were 0.782, 0.749, 0.711, and 0.693, respectively, and the percentage of correctly output explanatory sentences is 69.3%. All of these results are better than the model without the attention mechanism. The developed method makes it possible to provide user‐friendly, text‐based explanations of bridge damage in images, making it easier for engineers with relatively little experience and even administrative staff without extensive technical expertise to understand images of bridge damage. Future research in this field is expected to lead to the unification of field expertise with artificial intelligence (AI), which will be the foundation of the evolutionary development of bridge inspection AI. [ABSTRACT FROM AUTHOR]

Risk-based inspection (RBI) analysis and recommendations provide an optimal strategy for inspection planning in the oil, gas, and petrochemical industries. The RBI analysis and recommendations are performed based on qualitative, semiquantitative, and quantitative approaches. The suggested approach complements the qualitative RBI analysis approaches, as the existing techniques result in suboptimal inspection intervals. Although quantitative RBI methods have been well-developed for above-ground (and topside) piping and equipment, there is a significant need for developing quantitative or semiquantitative approaches for underground (or subsea) hazardous liquid pipelines. This manuscript presents a new approach to assess risk for liquid pipelines. The proposed method encompasses both time-dependent and time-independent damage types. In a proposed approach, for risk analysis of time-independent damages, an improved Kent Muhlbauer method is suggested. The improved Kent Muhlbauer method uses logical weight factors and modification factors which help to obtain repeatable results. In addition, the general failure frequency method as proposed in API-RP 581 is suggested for time-dependent damage types. The combination of these two methods constitutes the core of the proposed risk assessment algorithm of this study. The proposed method was implemented in a pipeline integrity assessment project. The overall study findings revealed that the results are satisfactory and reasonable and have a practical significance for inspection planning engineers. [ABSTRACT FROM AUTHOR]

• Vision-based 3D scanning techniques, • Determining measurement uncertainty and acceptance level, • Examination of large-surface objects with rough surfaces, • Application of numerical analysis and engineering inspection, • Laboratory tests of External Thermal Insulation Composite Systems (ETICS) Measuring the deformation of large-area objects with non-uniform rough textures using traditional techniques is technically challenging and time-consuming. This article presents a comprehensive solution that enables the precise measurement of the deformation of large-area elements of external thermal insulation composite systems (ETICS). The laboratory tests for environmental resistance were conducted in a climatic chamber. The surface of the wall underwent irregular deformation owing to thermal and humidity cycles. The deformation state at different stages of exposure was recorded using 3D scanning techniques. Scanning results were paired using a simplified cause-effect graph, and the deformation was measured by engineering inspection. Evaluation criteria were developed using measurement uncertainty and a straightforward binary acceptance principle. Finally, compliance tests were performed to confirm the reproducibility and repeatability of the method. [ABSTRACT FROM AUTHOR]

Mud pumping is a major problem for high-speed rail (HSR) slab tracks because it can cause deterioration of track alignment and further compromise operation safety and ride comfort of passengers. Timely inspection for mud pumping is crucial to the operational safety of high-speed rail networks. This paper proposes a novel detection method for mud pumping defects based on the measurement data of track geometry. The time and frequency features of the surface irregularity signal corresponding to the mud pumping sites were first analyzed. The concave anomalies reflecting the features of mud pumping and the peaks at the wavelength of 5 m and its octave on the power spectrum density (PSD) curve were revealed. On this basis, to automatically detect mud pumping defects, a multiscale signal decomposition method was employed and defect-sensitive features were extracted. A mud pumping index (MPI) indicating the severity of mud pumping was then established, and a three-level management scheme for mud pumping maintenance was developed accordingly. The performance of the proposed detection method was verified against visual inspection recorded on an in-service HSR line, which was constructed with the China Railway Track System (CRTS) I slab track. The results show that the proposed detection method can effectively locate and assess the mud pumping defects with acceptable accuracy for HSR track maintenance needs. [ABSTRACT FROM AUTHOR]

Background: In the last years, overviews of systematic reviews, or umbrella reviews, have seen a dramatic increase in their use. An overview aims to provide a summary of the included reviews and will often examine research questions beyond those addressed in the systematic reviews being synthesised. The purpose of this article is to provide some recommendations on how overviews should be conducted and reported. Method: A literature review was performed to identify relevant papers on both methodological and applied overviews. Results: The current literature recommends carrying out overviews by following similar steps to those of systematic reviews: (a) Defining the overview research question; (b) inclusion and exclusion criteria; (c) literature search; (d) data extraction; (e) assessment of risk of bias and reporting quality; (f) overview results; and (g) reporting the overview. Of special interest is how to address dependencies between the systematic reviews. Conclusions: Overviews allow evidence to be efficiently combined from multiple systematic reviews. This offers the possibility of translating and summarizing large amounts of information. As in primary studies and systematic reviews, conducting and reporting of overviews must meet appropriate quality standards. [ABSTRACT FROM AUTHOR]

New BAW bulletin on structure monitoring – sustainable infrastructure management on federal waterways The introduction of the new administrative regulation VV‐WSV 2101 Inspection of Structures adjusts inspection regime of federal waterways be more finely. Structures that have recently been classified in Inspection Category B do in principle have a special hazard potential with regard to the traffic safety to be ensured, but they are not so complex from a structural engineering point of view that they require – in contrast to Inspection Category A – a structural inspection by expert engineers. In this case, structural monitoring will be required in the future. The associated, newly developed BAW bulletin Damage Assessment on Waterway Structures of Inspection Category B (MSV‐B) groups the structures under consideration and provides guidelines for the systematic recording and assessment of damage to them. With the help of extensive standardization, the bulletin meets the requirements for efficient data collection on site as well as for the documentation of the results in the WSVPruf software for maintenance management. After closely concerted development and elaboration in 2021, quality assurance distributed within the administration, and widely distributed training by means of digital e‐learning formats, the bulletin was introduced in March 2022. [ABSTRACT FROM AUTHOR]

After an earthquake, the residual stiffness and strength of structural elements are typically estimated based on a qualitative visual inspection of cracks that is prone to error. In this paper a new approach is proposed to automatically estimate the updated stiffness and strength of damaged unreinforced masonry walls by characterization of crack patterns by a mathematical index. It is shown that structural and textural fractal dimensions of a crack pattern reflect the extent of cracking and the type of cracking or crushing, i.e., whether the cracks pass through joints or whether bricks have been damaged and crushed. Using results of six quasi-static cyclic tests on unreinforced brick masonry walls with different failure modes at various drift ratios, it is shown that the structural and textural fractal dimensions of the crack patterns are an accurate predictor of the stiffness and strength degradation. This procedure seems therefore a promising approach for replacing the traditional assessment methods that are based on visual inspection and engineering judgment by an analytical procedure based on image processing that can eventually be completely automated. [ABSTRACT FROM AUTHOR]

At 03:56 local time on November 26, 2019, an earthquake with a Mw = 6.4 struck western part of Albania. The duration of the tremor lasted less than 50 s and was felt largely also in Albania's capital Tirana, and in places as far away more than 300 km northeast of the epicenter. It caused damage to many public and residential buildings in districts of Durres, Tirana, Lezha, Shkodra, Diver, Berat and surrounding areas. This paper describes rapid visual assessment of the damaged buildings (169 in total) in affected areas by IZIIS teams' inspection of damaged buildings. Severe damages were identified in structural and non-structural elements as a result of inconsistent application of recent knowledge in design, construction and quality control of earthquake resistant structures. Structural errors in design and construction as well as inappropriate quality of built-in materials have been observed. Such results from the rapid damage assessment leads to the necessity of taking specific measures as detailed engineering inspection of vital structures as a basis of definition corresponding technical solutions for repair and strengthening with aim of restoring their operational mode. Last but not least, the biggest effect of earthquake damage was observed in non-structural elements which made the structures not-usable for citizens of the earthquake region. [ABSTRACT FROM AUTHOR]

This paper presents comprehensive research work on the crack initiation behavior of Semi Flexible Pavements (SFP) with the help of a one-way coupled multiscale modelling approach. The study focuses on elucidating the influence of layer interface conditions on potential cracking patterns under different temperature conditions. By integrating material properties at both local (mixture) and global (pavement) scales using a local de-homogenization approach, the interlocking effect was addressed within the asphalt binder's mesoscale properties. CT-image based mesostructure was employed to reconstruct the Representative Volume Element (RVE). Cohesive Zone Model (CZM) was utilized to simulate cracking initiation within the RVEs, with simulation results validated against practical engineering inspections. Additionally, a potential macroscopic failure index was introduced for SFP. It was found that the typical macroscopic failure indexes utilized for AC pavement may not be suitable for SFP due to the higher degree of heterogeneity. Analysis showed that SFP layer's coarse aggregate and cement grout at the bottom may experience compressive stress, while asphalt binder beneath the tire load may face high tensile stresses. Regardless of the interface conditions, top-down cracking was found to be the dominating failure mode in SFP. Besides, the vulnerable area in bonded interface SFP shifts from under tire load to the adjacent area with the rise in pavement temperature, while bottom-up cracking may appear only in unbonded interface SFP under low temperature conditions. Subsequent analysis demonstrated that top-down cracking is prominent in bonded interface SFP, especially at higher temperatures, compared to unbonded interface SFP. It is expected that critical observations for SFP highlighted above will certainly help in understanding critical failure modes and, hence, designing and constructing durable SFP structures. • A one-way coupled multiscale modelling approach considering interlocking effect was developed. • The interlocking effect was addressed using a local de-homogenization method. • The cracking initiation form of SFP was simulated and validated by pavement inspection. • A potential macro-mechanical failure index was proposed for SFP. [ABSTRACT FROM AUTHOR]

Initial cases of stress corrosion cracking (SCC) in pressurized water reactors (PWRs) occurred mostly but not exclusively in stagnant areas like dead-legs, but recently more extensive IGSCC has occurred in normal free-flowing PWR primary water. Operational experience and laboratory data reveal that the main parameters in IGSCC include cold work and weld residual strain, oxygen, and residual and applied stress. Residual strain, which arises from manufacturing, surface grinding, and welding, should be limited by optimizing manufacturing procedures, minimizing alignment and fit-up stresses and using high-quality weld procedures. Preventing oxygen ingress in the make-up water should be pursued. Stresses created by thermal fluctuations (thermal mixing, low-leakage core operation, and start-ups) deserve more attention. Weld residual stress, fit-up stresses and local stresses from load follow must be maintained below the annealed yield stress. IGSCC should be considered in aging management and in-service inspection. Detection techniques capable of identifying IGSCC should be employed. [ABSTRACT FROM AUTHOR]

One of the most common tasks of groundwater engineers is to estimate aquifer parameters from transient time-drawdown data which are measured during the execution of pumping tests. The classical method consists in the manual superimposition of the observed time-drawdown data over a type-curve, and the appreciation of the goodness-of-fit is left to the visual inspection of the engineer. The present paper proposes a computerized method based on a new hybrid algorithm named CSARao-1. It combines two recent metaheuristic algorithms: the crow search algorithm (CSA) and Rao-1 algorithm for the optimal aquifer parameters estimation, which inherits the advantages of both algorithms. The CSARao-1 hybrid algorithm along with CSA and Rao-1 algorithm was applied in conjunction with both the Theis solution to analyze time-drawdown datasets coming from confined aquifers systems and the Hantush and Jacob solution to analyze datasets coming from leaky aquifers systems. The proposed approach was coded in FORTRAN programming language and evaluated on fourteen time-drawdown datasets coming from different confined and leaky aquifers systems. The results obtained using CSARao-1 hybrid algorithm were compared to those obtained by applying CSA and Rao-1 algorithm separately, and to those recently published. Globally, the proposed CSARao-1 hybrid algorithm was found to exhibit more accuracy, better robustness and higher rate of convergence over the analyzed transient time-drawdown datasets. [ABSTRACT FROM AUTHOR]

Over the last few years, convolutional neural networks (CNNs) have been applied to detect corrosion in images. Unfortunately, the corrosion is detected in bounding boxes, without precisely segmenting the corrosion elements in irregular boundary shapes, and thus it is difficult to assess them quantitatively, such as in terms of corrosion areas and corrosion severity, which are important for engineers to evaluate the performance and condition of an inspection target. In addition, training an effective CNN model requires creating a training data set by labeling the corrosion pixels in each image, which is tedious and labor intensive. This paper presents a semantic segmentation deep learning approach together with an efficient image labelling tool for rapidly preparing large training data sets, and effectively detecting, segmenting, and evaluating corrosions in the images. The image labeling tool was developed by implementing a texture-based unsupervised image segmentation method, integrated with red-green-blue (RGB) feature-based classifier optimization. The tool enables users to construct a pixel-based corrosion classifier with small set of manually labeled images. This small set of labeled images is used for optimizing the pixel-based corrosion classifier to automatically generate corrosion segments for a large number of training images. A CNN model with semantic segmentation feature then is trained for corrosion detection and segmentation. Finally, a corrosion evaluation method is proposed for classifying each pixel of a corrosion segment into user-prescribed categories such as heavy corrosion, medium corrosion, and light corrosion. The integrated approach was tested on images collected by professional inspection engineers. The results indicated that the proposed approach is practically applicable for corrosion assessment for a wide range of industrial facilities and civil infrastructures. [ABSTRACT FROM AUTHOR]

The aim of this study is to calculate the risks of automatic checkweigher verification according to the specifications of the international recommendation OIML R51 developed by the International Organization of Legal Metrology (OIML) and to propose an alternative method for performing the verification efficiently. The risks posed by the OIML R51 method to the consumer and producer are calculated using the Monte Carlo method. The OIML R51 method was used to develop an alternative method with improved efficiency and almost equivalent risks. The alternative method involves calculating the sample mean and standard deviation of the error and makes acceptance/rejection decisions after weighing every 10 times. The tolerances of the alternative method are stepwise with the upper and lower limits. After weighing every 10 times, the sample mean and standard deviation were calculated, and if they were both less than the lower tolerance limit, the test was completed and a pass decision was made. Conversely, when the mean or standard deviation exceeded the upper tolerance limit, the test was completed and a failed decision was made. The Monte Carlo method was used to calculate the risks and a reduction in the required number of weighings by the alternative method. The alternative method was applied to an actual instrument to evaluate the efficiency of the method. For the instrument used in this study, the expected value of the required number of weighings is 20 in the weighing range of 400 g or more and one-third of the number stipulated in the international recommendation. This means that significant labor savings are possible. • An alternative method with improved efficiency almost equivalent risks by the OIML R51 method is developed. • An alternative method consisting of stepwise tolerances is proposed. • The calculation result of Monte Carlo method showed the risks of these two methods were found to be almost the same. • The alternative method was applied to an actual instrument to examine the method's efficiency. • The application of the alternative method allows to improve the efficiency of verification/in-service inspection. [ABSTRACT FROM AUTHOR]

Recent advancements in virtual reality (VR) may help unlock the full potential offered by 3-D photorealistic models generated using state-of-the-art photogrammetric methods. Using VR to carry out analyses on photogrammetric models has the potential to assist the user in performing basic offline engineering inspection of digital twins—digitized representations of real-world objects and structures. However, for such benefits to materialize, it is necessary to create suitable interactive systems for working with photogrammetric models in VR. To this end, this article presents PhotoTwinVR—an immersive gesture-controlled system for manipulation and inspection of 3-D photogrammetric models of physical objects in VR. An observational study with three domain experts validates the feasibility of the system design for practical use-cases involving offline inspections of pipelines and other 3-D structures. [ABSTRACT FROM AUTHOR]

Safe transmission of oil pipelines is one of the guarantees of national defense and environmental protection. Magnetic flux leakage (MFL) testing is critical to the safety inspection of in-service pipelines. In the detection process, the incompleteness of MFL data affects defect location and inversion severely. This article proposes an MFL data recovery method based on multifeature condition risk, which can effectively handle the block data gap problem. First, a preprocessing mechanism is proposed to determine defect boundaries and uniformly interpolate the raw data automatically. Second, a multifeature extraction method of MFL defect data is proposed, which takes full advantage of the complete data and reduces the impact of data gaps. Third, a novel data reconstruction method based on feature conditional risk is proposed, where prior information of MFL data is regressed, relying on the regression coefficient calculated by dynamic programming. Finally, comparison experiments on different sizes of data gaps, varying robustness, and average running time are conducted, respectively. The MFL data are derived from actual measurements. The results indicate that the proposed method is more robust, more efficient, and faster. Note to Practitioners—This article is motivated by the problem of data gaps in magnetic flux leakage (MFL) data in actual pipeline safety transmission measurements, which seriously affects defect inversion and assessment. In this article, in terms of the intrinsic characteristics for MFL data, we propose a new and effective approach by extracting the multifeature of defects and using conditional risk to recovery data gaps. Our method takes advantage of the no-missing part of MFL data and prior samples, which are obtained from practical measurements. The experiment results show that our proposed method is more advantageous than the comparison methods, and therefore, our proposed method has strong practical value. Our future work will aim at improving the versatility of the proposed method. [ABSTRACT FROM AUTHOR]

The pressurized heavy-water reactors (PHWR) consist of a low-pressure horizontal reactor vessel, calandria, containing heavy water as moderator. The calandria is pierced by a large number of coolant tubes (also called pressure tubes [PTs], 392 in 540 MWe PHWR), which contains fuel bundles, and through which pressurized heavy-water coolant circulates. During biennial shut down in 2017, in-service inspection of coolant channels in Tarapur atomic power station-4 (TAPS-4) had been carried out and after the review of results of inspection, it was recommended by various groups of experts that channel L-08 should be removed for postirradiation examination at Bhabha Atomic Research Center (BARC). Before the channel removal job, one special shielding flask was designed to shift the removed channel to BARC. The integrity test of special shielding flask was carried out by safely placing cobalt-60 (source strength 851000 MBq) capsule source inside the shielding flask with the help of cranking unit mechanism followed by dose rate mapping on the outer surface of the flask. To establish the hydrogen pickup rates in L-08 PT, sliver samples were collected and separately sent to BARC. Four metallic sliver samples were obtained at four different distances from north E-face. The activity content present in each sliver sample was also estimated. The maximum activity estimated was 2313.24 MBq. Subsequently, L-08 coolant channel was cut from both sides using a chipless tool. Jobs involving heavy water (D2O) collection work were carried out with a ventilated plastic suit. Derived air concentration (DAC) of tritium at the work location was maintained below 1DAC during the entire activity. Particulate DAC was found below the detectable limit. Floor contamination checks and floor decontamination were conducted at regular intervals to avoid buildup of contamination. As a result of such high-quality radiological safety measures, only 25 workers, out of 270 radiation workers, have received a cumulative dose of more than 3 mSv in direct reading dosimeter with a maximum individual dose of 8.45 mSv and maximum individual uptake of 0.39 GBq/m3. Job was completed with a total collective dose of 324.35P-mSv which is 14.5% lower than estimated. This article highlights some of the critical tasks involved in the cutting and the removal of irradiated coolant channel from the core of 540 Mwe TAPS-4 reactor which is a first of kind activity in nature. [ABSTRACT FROM AUTHOR]

Based on the evaluation of bridge structure and similar hydraulic structures and the characteristics of stone arch aqueduct structure, the safety and disease mechanism of a large-scale stone arch aqueduct in service were studied by using the trinity analysis method of field test analysis, static analysis and dynamic analysis. A comprehensive and inclusive analysis was conducted. It is pointed out that the structural analysis and the evaluation plan of the stone arch aqueduct, which combining comprehensive testing with numerical simulation analysis, can fully analyze the aqueduct disease generation mechanism from the whole to the local and from the external to the internal. This method has universal applicability to stone arch aqueducts. [ABSTRACT FROM AUTHOR]

Ultrasonic Rayleigh waves have been employed for in-service NDT inspection in a wide range of industries for years. The excitation of Rayleigh waves can be achieved using a variety of methods, with the so-called wedge technique being the most widely used. Recent years have seen considerable research interest in surface crack detection and sizing using Rayleigh waves excited and detected with the wedge technique. However, in this method, Rayleigh waves experience transmission loss at the wedge interfaces. Moreover, the flexibility to generate Rayleigh waves on different waveguides using the same wedge is limited, as the wedge angle depends on the Rayleigh wave wavelength. This work demonstrates a method that provides an alternative Rayleigh wave excitation method. In this, a conventional ultrasonic phased array transducer is used. As there is an appropriate excitation delay between each piezoelectric element of the array transducer, Rayleigh waves can be generated in a wide range of materials using the same phased array transducer. The delay can be estimated based on the elementary pitch of the transducer and the Rayleigh wave velocity of the waveguide. The proposed Rayleigh wave excitation method is demonstrated through both experiments and FE simulations. Furthermore, a finite element model is used to better understand the features of the generated waves and to validate them through their characteristics as Rayleigh wave. A quantitative comparison between the proposed and existing methods is also presented. The directivity and beam divergence of the generated Rayleigh waves are quantified. The results obtained from experiments are in agreement with finite element simulations and demonstrate the possibility of unidirectional and selective excitation of Rayleigh waves through the proposed method. They also highlight the potential for this new excitation method to be used to develop new Rayleigh wave-based inspection methods. • Wedge-free Rayleigh wave excitation method using a phased array transducer. • Beam steering ability of the phased array is controlled using a linear time delay. • Time delay depends on transducer pitch and Rayleigh wave velocity. • A unidirectional and selective excitation like the wedge technique is achieved. • This method can easily be adapted for a range of materials using the same transducer. [ABSTRACT FROM AUTHOR]

Porosity defects can be found in many engineering structures and their inspection remains a challenge in the field of ultrasonic non-destructive testing. In this paper, ultrasonic array imaging of porosity defects has been studied with the aim of improving the image quality in the "dead zone", which is caused by the masking effects of the uppermost pores. The proposed approach first extracts contributions of the uppermost pores based on a single scattering model by adopting convolutional sparse coding. The extracted dominant contributions are then subtracted from the array data before forming an image, facilitating detection and localization of pores in the shadow zone. The performance of the proposed approach has been studied in simulation and experiments, and the mean localization errors of the pores are small (i.e. , within 0.27 mm or 0.14 λ). In addition, the effects of measurement noise and imaging parameters on robustness of the imaging result have been analyzed, providing guidelines for practical implementation of the proposed approach. • Ultrasonic array imaging of porosity defects has been studied. • Dominant response signal was extracted using convolutional sparse coding. • Image contrast was improved by subtracting the dominant response from the array data. • The effects of measurement noise and imaging parameters have been analyzed. [ABSTRACT FROM AUTHOR]

• Development of a measurement system capable of flexible imaging processes that can provide a 3D distribution of MFD. • Accurate 3D-MFD visualization at grain level via integrated 3-axis TMR data slicing. • An algorithm for extracting grain boundary of certain grain at each polished surface. • An algorithm for matching the accurate 3D-MFD with the microscopic images at each polished surface. • Accurate 3D imaging of the MFD inside of a grain and estimate the distribution of magnetic domains. The increasing demand for improved quality control and maintenance evaluation of ferromagnetic materials has driven the emergence of non-destructive testing (NDT) as a crucial tool. Although electromagnetic-based methods are effective in detecting surface and subsurface defects, the challenge lies in accurately reducing measurement bias. Furthermore, the distribution of magnetic flux densities (MFDs) is influenced by both external excitation fields and the internal microstructure topology of the metal. Unfortunately, the current capability to flexibly image MFD distributions with microscopic resolution for in-service inspection is limited. In this study, we developed a measurement system to image the three-dimensional distribution of MFDs within a single grain. By employing integrated surface polishing techniques and capturing MFD distributions on each layer using a three-axis tunnel magnetoresistive (TMR) sensor, we achieved comprehensive 3D visualization of the MFD within a grain. [ABSTRACT FROM AUTHOR]

• An impact acoustic method is proposed for interfacial debonding detection in CFSTs. • A portable instrument is developed for data recording and real-time analysis. • An energy ratio criterion of two vibration modes is used for debonding evaluation. • Field experiments in Shenzhen SEG Building validate the accuracy of the method. Concrete-filled steel tube (CFST) structures are commonly used in the construction of high-rise buildings and bridges. However, the presence of debonding defects at the steel–concrete interface of CFST structures due to poor construction quality and concrete shrinkage can significantly reduce their load-bearing capacity. In this paper, an impact acoustic method based on the flexural vibration mode is proposed to detect interfacial debonding in CFST structures. A portable instrument comprising a hammer and a data recording and analysis module is developed for real-time inspection. A vibration energy ratio (VER) criterion, which compares the energy distribution between flexural vibration and thickness stretch modes, is proposed to evaluate the degree of debonding. The effectiveness of the proposed method is verified using a CFST column specimen with debonding defects. The laboratory experimental results demonstrate that the proposed method can detect and roughly pinpoint the debonding area. Additionally, the proposed method is applied to evaluate debonding defects in the CFST columns of the Shenzhen SEG Building, which experienced abnormal shaking on May 18–20, 2021. Impact acoustic measurements were conducted along 27 circumferential rings of nine CFST columns, revealing serious debonding damage to the building with a comprehensive debonding rate of 50.4%. It is concluded that that the proposed impact acoustic method can detect and locate debonding defects in CFST structures, and has a broad application prospect for rapid inspection in civil engineering due to its high efficiency. [ABSTRACT FROM AUTHOR]

The article focuses on the 13 International Conference on Industrial Computed Tomography (iCT2024) taking place in Austria, which will cover the latest developments in industrial computed tomography, particularly its applications in non-destructive testing.