In this paper, a comprehensive overview was conducted on machine vision in potato cultivation, harvesting, and storage. Common weeds and diseases encountered during potato cultivation were summarized, and the advantages and disadvantages of various detection methods were compared. Additionally, methods for soil clod separation and tuber damage detection during harvesting were reviewed, along with a comparative analysis of their strengths and weaknesses. Furthermore, the defect grading and sprouting detection methods during storage were discussed. While machine vision technology shows good detection ability in potato cultivation, harvesting, and storage, further research is still needed to enhance the accuracy and adaptability of these methods, ultimately promoting the development of the potato industry.

Shield tunnel is a type of linear underground structure assembled by lining segments, characterized with long joint, weak stiffness, and strict deformation control requirement. The situation of the long-term deformation and defect of the shield tunnel in soft ground in coastal area of China is severe, mainly attributed to the tunneling-induced ground consolidation, frozen cross passage, groundwater pumping, cyclic train load, and nearby construction. Shield tunnel is buried in ground, and the above factors could result in underlying ground settlement, overlying ground loading/unloading, and at-side ground unloading. As a result, the tunnel could suffer from different types of structural deformation and defect. Based upon the aforementioned different reasons, this study investigates the characteristics of the tunnel deformation and defect corresponding to the different types of ground stress change and deformation. It is found that tunneling-induced ground consolidation, frozen cross passage, groundwater pumping, and cyclic train load mainly contribute to the longitudinal differential settlement but negligible transverse convergence, associated with water leakages at circumferential joints. In comparison, surface surcharge and at-side unloading not only cause significant longitudinal differential deformation but also increase transverse lining internal forces, resulting in water leakages at circumferential joints, longitudinal lining concrete cracks and water leakages. Finally, nearby construction could strongly disturb the ground and cause the generation of excess pore-water pressure, making the shield tunnel deformation develops continuously after the nearby construction is completed.

Cement-soil mortar is a composite material that provides an efficient and cost-effective solution for a wide range of construction applications. This study analyzes the mechanical properties of cement-soil mortar through experimental investigation and explores the application and parameter calibration of the Concrete Damage Plasticity (CDP) model in the finite element simulation of cement-soil mortar. Additionally, an innovative Initial Defect Generation (IDG) method is proposed to enhance the accuracy in simulation of failure mode. The research findings provide a simulation framework that balances simplicity and accuracy for cement-soil mortar. Uniaxial compressive tests are first conducted on cement-soil mortar specimens with water contents ranging from 40 % to 70 %, and cement-to-soil proportions from 30 % to 300 %. Based on the experimental results, the regression relationships correlating unconfined compressive strength (UCS) with elastic modulus, peak strain and stress-strain curves are established. Then, the simplified equations for calculating CDP model parameters from the UCS of cement-soil mortar are further proposed following damage mechanics. A parameter table summarizing the calculation methods for all relevant CDP parameters is provided to streamline the model calibration process. Simulations incorporating the simplified calibration method and IDG method successfully replicated the stress-strain responses and failure modes observed in uniaxial compressive strength tests of cement-soil specimens with varied strength. The results demonstrate the reliability and broad applicability of this simulation framework in predicting the mechanical performance of cement-soil mortar.

Non -invasive potato defects detection has been demanded for sorting and grading purpose. Researches on the classification of the defects has been available, however, investigation on the severity level calculation is limited. For the detection of the common scab, it has been found that imaging in the infrared region provide an interesting characteristic that could distinguish defected area to normal area. Thus, investigations on this wavelength range is interesting to add more knowledge and for applications. In this research, the multispectral image has been obtained and investigated especially at three wavelengths (950, 1 150, 1 600 nm). Image pre-processing and pseudo-color conversion techniques were explored to enhance the contrast between defects, normal background skin area and soil deposits. Results show that external defects, such as common scab and some mechanical damage types, appear brighter in the near infrared region, especially at 1600 nm against the normal skin background. It has been found that pseudo-color images conversion provides more information regarding type if surface characteristics compared to grayscale single imaging. Image segmentation using pseudo-color images after multiplication operation preprocessing could be used for common scab and mechanical damage detection excluding soil deposits with a Dice Sorensen coefficient of 0.64. In addition, image segmentation using single image at 1 600 nm shown relatively better results with Dice Sorensen coefficient of 0.72 with note that thick soil deposits will also be segmented. Defect severity level evaluation had an R2 correlation of 0.84 against standard measurements of severity. (c) 2022 China Agricultural University. Production and hosting by Elsevier B.V. on behalf of KeAi. This is an open access article under the CC BY -NC -ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).

The existence of defects in the enclosure structure is the primary cause of water and sand leakage in foundation pits, as well as being a significant source of danger in pit construction, but current research lacks an in-depth investigation of the generation mechanism and gestation process. In this paper, which comprehensively considers the microscopic particles and macroscopic level, the development mechanism of a water and sand leakage disaster in a foundation pit with a water-rich sand layer was studied using the principle of computational fluid dynamics and discrete element method coupled analysis (CFD-DEM); moreover, based on the anisotropy of the particle force and fluid energy analysis, the deformation of the stratum and ground stress field were analyzed. The results show that the stress field will produce a plugging effect at a certain distance from the defect, and the strata exhibit a dominant displacement tendency in the vertical direction, resulting in the emergence of a gradually concave stress relaxation zone and an elliptical contour in the strata displacement map near the defect. The fluid energy describes the displacement of the sand layer very well, and it is separated into the sand layer's centralized loss region and the major loss area based on the high and low levels of the fluid energy class. The impact of fluid at the defect reaches the maximum kinetic energy, which penetrates the structural weakness and causes the loss of sand particles, and the cross- of the water influx near the defect gradually expands with the loss of particles, indicating that there is a danger of further expansion of the defect under the impact of water flow. These results have technical implications for the management of water and sand leakage disasters in foundation pit engineering.

In this article, we propose a method using T(0,1) guided waves combined with coil coding technique to detect defects in buried liquid-filled pipes implemented by an electromagnetic acoustic transducer (EMAT). Due to its non-dispersive properties and the fact that there is no energy loss in nonviscoelastic fluids, the T(0,1) mode is selected for pipe defects detection. The electromagnetic device that generates the circumferential magnetic field is optimized to excite the pure T(0,1) mode. To realize energy enhancement and defect location identification, the electromagnetic acoustic coil is spatially encoded by 11-bit Barker code and the receiver coil is multiplexed consisting of a spatial coded coil and a unit coil. The defect detection is accomplished through time-of-flight (TOF) time-frequency analysis, and the defect location identification is achieved by digital signal processing methods (cross correlation and convolution). The feasibility of this method is verified by the finite element (FE) model and experimental analysis, indicating the defect locating error in a liquid-filled pipes is less than 1%. Overall, the proposed method achieves a high-precision flaw detection and location identification.

Onshore pipelines are exposed to corrosion degradation, facilitated by the pipeline's management and surrounding aggressive environmental conditions. Every 2 to 6 years, pipeline operators often conduct In -Line (ILI) inspections to screen for pipe damage using magnetic or ultrasonic sensors. Considering soil and fluid aggressive conditions, and the possibility of false alarms or a miss-detections from the inspection device, new defects, i.e., metal loss at either the inner or outer wall, should be expected to occur between consecutive inspections. Considering the possibility of corrosion coloniesand their significance in the pipeline's reliability assessment, different authors have incorporated new corrosion defects in degradation and further reliability assessments using a Homogeneous Poisson Process. This process assumes that corrosion points are evenly distributed, which can be classified as conservative. This study aims to characterize the main spatial distribution of corrosion defects using the Complete Spatial Randomness (CSR) assumption under hypothesis testing. Additionally, it assesses how is the interaction between new and old defects from a repulsion-attraction perspective, and it proposes an alternative to simulate them for further reliability analyses. The suggested approach was applied in a real case study, obtaining that corrosion defects tend to be clustered and little repelled from those already detected.