Row Spacing Research Articles

Carbon and Nitrogen Accumulation in Roots of Signal Grass–Forage Peanut Intercropped Pastures at Varying Planting Spacings

This study highlights the potential of grass–legume intercropping systems in enhancing soil carbon sequestration and cycling nutrientes, providing ecological support for sustainable agriculture. This study evaluated the chemical composition and root biomass of signal grass (Urochloa decumbens cv. Basilisk) pasture grown in monoculture or intercropped with forage peanut (Arachis pintoi cv. Belmonte) under different row spacings (40, 50, 60, 70, and 80 cm), 4–5 years after establishment. The experiment was conducted in a randomized block design with four replicates under intermittent sheep grazing. Results (p < 0.05) indicated that root biomass was higher in the intercropped pastures (6752 to 11,167 kg OM ha−1) than in the monoculture (3696 kg OM ha−1). Carbon (C) and N stored in root biomass were also influenced by the row spacings, with narrower spacings, particularly 40 cm (1282 kg C ha−1) and 50 cm (1424 kg C ha−1), showing higher C storage than in the monoculture (509 kg C ha−1). Similarly, the 40 cm (122 kg N ha−1) and 50 cm (138 kg N ha−1) spacings showed higher N accumulation in root biomass than the monoculture (38.9 kg N ha−1). These spacing also reduced C/N and lignin/ADIN ratios, which enhanced nitrogen cycling efficiency. Based on these results, 40 and 50 cm spacings are recommended for intercropped pastures, as they optimize C and N accumulation and nutrient cycling, and support sustainable pasture management.

Comparison of Different Twin Row and Narrow Row Sowing Methods in Corn A Clay-Textured Soil

Narrow and twin row sowing methods are agronomic applications that aim to increase plant growth and yield by expanding the plant's growing area but, they are highly affected by environmental conditions. The aim of this study is to determine the applicability of different narrow row and twin row sowing methods in clay textured soil in main crop cultivation of corn, which an important grain. The study was carried out Diyarbakır province in the Southeastern Anatolia Region of Türkiye in 2016 and 2017. In the study carried out with two different corn varieties, line abreast narrow row, diagonal narrow row, line abreast twin row, diagonal twin row, single row 1 (70 cm row spacing, 20 cm intra-row spacing) and single row 2 (70 cm row spacing, 12.5 cm intra-row spacing) applications were tried. ADA 351 and Sakarya corn varieties were used in the study. As a result it was determined that line abreast narrow row, diagonal narrow row, line abreast twin row and diagonal twin row applications are not suitable for corn cultivation. The highest grain yield was obtained from single row and 12.5 cm intra-row spacing application.

Image Watermark Embedding Method Based on Security Service Secure

To solve the problem of privacy leakage and response latency in outsourced image watermark embedding in cloud computing, an efficient and privacy-preserving watermark embedding method for outsourced digital images was proposed by introducing edge computing technology. We had proposed a perturbing encryption method with homomorphism to ensure the information security and the correctness of discrete wavelet transformation in the encrypted domain. In addition, the framework was designed to guarantee the safety of singular value decomposition that edge server could not recover the original image matrix. The experimental results show that the proposed method is superior to similar secure watermarking schemes in terms of encryption/decryption time and ciphertext expansion. The proposed method enables the watermarking operation to be performed in an unsafe outsourced environment while achieving a watermarking effect similar to the plaintext equivalent

Left-right difference in acetabular articular cartilage surface area and the quantification of acetabular fractures.

X-ray computer tomography scans were carried out on 11 female and 9 male dry bony pelvises. A 512 x 512 image matrix was used with a slice thickness and separation of 2 mm. Images were transferred onto a computer and the articular cartilage marked on each relevant image. The points were connected to form a triangle mesh and the total articular cartilage area calculated by summing the area of each triangle. There was a highly significant difference (p < 0.001) between the male and female acetabular areas, 25.4 ± 2.7 cm2 and 19.5 ± 2.0 cm2, respectively. The mean left-right difference was 0.2 ± 0.9 cm2 for males and-0.2 ± 0.47 cm2 for females. When the sign of the differences are removed, the mean and standard deviations of the differences is 0.5 ± 0.46 cm2 (2.3% ± 1.8%) for males and females, 0.66 ± 0.61 cm2 for males and 0.4 ± 0.27 cm2 for females. Each articular surface was outlined twice in order to assess the repeatability of the technique. The left-right variation in articular surface area was found to be similar to the variation in repeatability, suggesting that if any left-right difference does exist it is too small to be reliably detected by this technique. This enables the area of articular cartilage of the fragments of a fractured acetabulum to be compared directly with surface area of the contralateral intact acetabulum. Acetabular fractures can therefore be quantified by measurement of the articular surface area of the fracture components. Comparison with the clinical results will enable surface area to be developed as a prognostic factor in the management of acetabular fractures.

Wheat-soybean relay cropping allows corn cultivation as the third crop of the year in Southern Brazil

Relay cropping allows soybean to overlap with wheat for a period, reducing the production risks associated with wheat and enabling earlier sowing and harvesting of soybean. This study aimed to evaluate the technical and economic feasibility of a wheat-soybean relay cropping system and the cultivation of corn as a third crop within the same agricultural year. The experiment was conducted using a randomized block design with a 4 x 3 factorial arrangement, featuring three repetitions during the 2019/2020 and 2020/2021 growing seasons. Four wheat inter-row spacings, with configurations of 17 and 22 cm in single and double rows, resulted in soybean row spacings of 51 and 66 cm. Soybean was sown at the wheat's milk and dough grain stages, and a control was sown after wheat harvest with 45 cm inter-row spacing. The best wheat-soybean relay cropping arrangement was 17D, where wheat produced 2,812 and 2,267 kg ha-1, or 69.41 and 64.82% of the total produced by the control treatment in the first and second evaluated years, respectively. In the first year, soybean in the 51-cm arrangement sown during the second sowing season (09/23/19) produced 6,029.42 kg ha-1, which was 32.5% higher than the first season on 09/13/19 and 11.8% lower than the control on 10/03/19. In the second year, the same treatment sown on September 29 yielded 4,235.00 kg ha-1, which was 12.58% more than the first sowing period on September 14 and 7.4% lower than the control sown on October 23, 2020. Although its yield was 1,239 kg ha-1 less than the control (17S), relay cropping allowed corn sowing to be advanced by 15 days, which resulted in a grain yield increase of 1,956 kg ha-1 compared to corn sown after soybean harvest in the conventional system. The trade-off between wheat yield losses and corn yield gains indicates that wheat-soybean relay cropping has a positive balance and can be used as a management strategy to reduce crop risks and achieve higher grain yields per area. Additionally, wheat-soybean relay cropping provides grain yield gains per area and contributes to the productivity of the system, reducing risks for the three crops and yielding higher economic returns in both studied years.

Calculation of Blasting Damage Zone Radius of Different Charge Structures in Burnt Rock

The radius of the failure area after a blasting fracture process of burnt rock is affected by joint fissures, does not conform to the existing theoretical calculation formula and the distribution law of the failure area also changes. The fracture area is large, and the fracture extension and expansion area are small. Therefore, in order to describe the damage of blasting to a fractured rock mass more objectively and accurately, on the basis of summarizing the previous research results, a damage variable was introduced to characterize the initial crushing degree of the fractured rock mass, and the corresponding rock failure criterion was used to derive the calculation formula of a blasting crushing circle and fracture circle radius of burnt rock with different charge structures. The results show that the blasting failure zone of fractured rock mass with different charge structures was not only related to the radius of the blast hole and the explosive and rock properties, but also had a strong relationship with the initial damage degree of the rock mass. Taking an open-pit coal mine in Xinjiang as an example, the radius of the fracture zone with different charge structures was obtained by using the obtained calculation formula, and it was applied to the determination of row spacing and hole spacing.

Effects of Different Spatial Distributions of Vegetation on the Hydraulic Characteristics of Overland Flow

ABSTRACTVegetation plays a crucial role in mitigating and controlling soil erosion caused by overland flow. However, variations in the hydraulic characteristics of overland flow induced by the spatial distribution of vegetation with different row and column spacings are often overlooked in existing literature, potentially leading to significant deviations in predicting these characteristics. In this study, 180 lab‐scale runoff tests were conducted to clarify the hydraulic characteristics of overland flow considering six α (the ratio of the lateral distance of vegetation to stem diameter) levels, six β (the ratio of the slope distance of vegetation to stem diameter) levels, and three slope angles (θ) under five flow discharges (Q) conditions. The results show that the observed flow regime of overland flow belongs to the transition flow regions, shifting from slow to rapid as α and/or β increase. The friction coefficient and the proportion of frictional resistance in the total flow resistance increase with increasing α and β. The local resistance dominates the total flow resistance of bare glass slopes. The local resistance coefficient ξ decreases with increasing α and β, however, it initially increases and then decreases with increasing θ. The impact of β on the local resistance is greater for gentle slopes, whereas the impact of α is more significant for steep slopes. ξ exhibits a negative correlation with Re and the ξ‐Re curves gradually level off as α or β increases, while they become steeper with increasing θ. A prediction model for the total flow resistance was established taking into account the combined effects of Re, α, β and θ, which provides better prediction performance than two other relevant models. The results obtained from this study provide valuable insights into the hydraulic characteristics of overland flow and offer clear guidance for vegetation management in controlling soil erosion on slopes with heterogeneous vegetation coverage.

Single plant segmentation and growth parameters measurement of maize seedling stage based on point cloud intensity

Maize growth parameters are key pieces of information describing the growth, development and yield of plants, and they are of great significance for high quality and high yield maize breeding. Plants counting, row spacing, and plant spacing are closely related to maize sowing quality and yield. Plant height is closely related to maize photosynthetic rate and biomass. The main problem with measuring phenotypic parameters during the maize seedling stage is that maize plants are small, making it difficult to segment maize plant point clouds from ground point clouds, and there is a lack of automatic methods for measuring growth parameters. A point cloud intensity segmentation and improved Euclidean clustering method for single plant segmentation was proposed based on terrestrial laser scanning (TLS) technical, and an automatic measuring method of growth parameters of maize seedling stage was realized. First, TLS was used to scan maize plants at two planting densities at V1 (first leaf is fully expanded) and V2 (second leaf is fully expanded) stages. Second, the segmentation based on point cloud intensity method and the improved Euclidean clustering single plant segmentation method were used to achieve the segmentation of a single maize plant. Finally, the automatic measurement of maize plants counting, row spacing, plant spacing, and plant height were realized. When plants counting of maize, the percentage error was lower than 1.70%. In the measurement of row spacing, plant spacing and plant height of maize plants, the mean absolute percentage error (MAPE) were lower than 1.50%, 5.50% and 3.10%, respectively. These results demonstrate that the point cloud intensity segmentation and growth parameters measurement method is feasible for maize V1 and V2 stages and different planting densities. The automatic measurement values of the number of maize plants, row spacing, plant spacing and plant height has high measurement accuracy and small error. This study provides a rapid, automatic and accurate measurement method for researchers to measure maize growth parameters.

Modified Double Row Spacing and Fertilizer Rate for Improved Productivity of Glutinous Corn

Various high yielding glutinous corn varieties have been developed and NSIC registered, however, the national and regional yield averages are still very low. A study therefore, was conducted to increase the yield of glutinous corn in Ilocos Norte though modification of planting distance and fertilizer rate. Experimental setups were established for two consecutive dry seasons from 2019-2021 which were laid-out in Split-Plot following the randomized complete block design with three replications using MMSU Glut 1 variety as test plants. Soil pH level of the soil before and after harvest from a depth 0-20 cm and 21-40 cm was increased from 7.26 to 7.52 and 7.33 to 7.60, respectively. MDR plots have higher OM at the 0-20 cm depth by 11.67% to 15.55% as N levels applied increase from 120 to 200 kg N ha-1. At 90 DAE, glutinous corn fertilized with 200-100-100 kg NP2O5K2O ha-1 was significantly taller by 4.2% and 10.77%; higher ear height by 9.6% and 21.40%, longer ear length, and wider ear diameter than those applied with 120-60-60 kg NP2O5K2O ha-1 and unfertilized corn plants, respectively. Heavier ear weight and larger seed size were attained from treatment combination of PD 75 cm x 20 cm and FR of 200-100-100 kg NP2O5K2O kg ha-1 and PD – MDR and FR of 200-100-100 kg NP2O5K2O ha-1. Combination of PD (MDR) and FR 200-100-100 kg NP2O5K2O ha-1 obtained the highest shelling percentage of 93.23%. PD and FR significantly affected the agronomic fertilizer use efficiency (AFUE) of glutinous corn. Application of FR 200-100-100 kg NP2O5K2O ha-1 provided glutinous corn an increased in yield of 17.5% (PD 75 cm x 20 cm), 55% (PD 60 cm x 20 cm) and 105% (PD 80:30 cm x 20 cm) over FR 180-80-80 kg NP2O5K2O ha-1, FR 120-60-60 kg NP2O5K2O ha-1, and the unfertilized, respectively. Treatment combination of PD MDR and FR 200-100-100 kg NP2O5K2O ha-1 gave glutinous corn higher yield by 28.10% using the combination of PD 60 cm x 20 cm and FR 200-100-100 kg NP2O5K2O ha-1 and 29.53% using ...

Support Patterns of Roadways Under Fractured Surrounding Rocks Based on the Quality Level of Rock Mass

The roadway project of broken rock mass in the Shilu Iron Deposit was taken as the research object to discuss the stability control of the surrounding rocks using support patterns with broken rock mass. The grade evaluation of rock mass quality was conducted based on the geomechanical classification of rock mass. The roadway support effect in broken rock mass was calculated. Then, the section convergence characteristics of roadway surrounding rocks were analyzed under the current support scheme using displacement monitoring technology. The conclusions were described as follows: (1) The surrounding rock integrity of the No. 6 and No. 7 transportation roadways in the middle section of the Baoxiu mining area (Level 120) is poor. Based on geological survey data and rock mass classification, the rock mass quality in this region has been rated as Class IV. The joint support pattern of the anchor net and shotcrete was used according to the support guidelines. (2) The parameters for the support structure within Shilu Iron Deposit were designed, according to the requirements, as follows: the use of Portland cement; a shotcrete thickness of 55 mm; resin bolts with a minimum outer diameter of φ 20 mm and a length of 2200 mm; and row and column spacings of 1100 mm each. Meanwhile, a rectangular metal mesh of 80 × 80 mm was used as the anchor mesh. (3) The cross-section displacement reached 20 mm within a week using the support pattern according to displacement monitoring results of the on-site roadway section. Moreover, the convergence deformation rate significantly changed. However, the rate rapidly decreased after the first week, and the cross-section showed no further deformation after one month. The support pattern could control the displacement of surrounding rocks, which was verified by the monitoring results.

Dual-dimensional contrastive learning for incomplete multi-view clustering

Incomplete multi-view clustering (IMVC) is a critical task in real-world applications, where missing data in some views can severely limit the ability to leverage complementary information across views. This issue leads to incomplete sample representations, hindering model performance. Current contrastive learning methods for IMVC exacerbate the problem by directly constructing data pairs from incomplete samples, ignoring essential information and resulting in class collisions, where samples from different classes are incorrectly grouped together due to a lack of label guidance. These challenges are particularly detrimental in fields like recommendation systems and bioinformatics, where accurate clustering of high-dimensional and incomplete data is essential for decision-making. To address these issues, we propose Dual-dimensional Contrastive Learning (DCL), an online IMVC model that fills missing values through multi-view consistency transfer, enabling simultaneous clustering and representation learning via instance-level and cluster-level contrastive learning in both row and column spaces. DCL mitigates class collision issues by generating high-confidence pseudo-labels and using an optimal transport matrix, significantly improving clustering accuracy. Extensive experiments demonstrate that DCL achieves state-of-the-art results across five datasets. The code is available at https://github.com/2251821381/DCL.

Experimental study on tsunami-driven debris damming loads on columns of an elevated coastal structure

This study presents experimental findings on debris damming loads on columns of an elevated coastal structure under tsunami-like wave conditions. A total of 183 cases (140 with and 43 without debris) were tested at a 1:20 scale to understand the impact of various factors on debris-driven damming loads, including wave characteristics, structure configurations, and debris shapes. The debris impact and damming processes were observed and quantified from optical measurements, and corresponding loads were measured on the entire structure using a force balance plate and on an individual column in the front row using a multi-axial load cell. The experimental results indicated the horizontal debris damming load on the entire column structure increased by up to 3.2 times compared to conditions without debris, while the load on the individual column increased by up to 11.0 times. The total damming loads for the whole structure increased, but the load for the individual column decreased at a reduced opening ratio. The smaller debris sizes relative to column spacing showed significantly lower chances of debris damming across different column configurations. Overall, the load on the whole structure showed stronger correlations between debris damming loads and hydro-kinematic variables such as flow depth, velocity, momentum flux, and Froude number compared to the loads on the individual column. Among these variables, momentum flux emerged as the most consistently influential across all categories.

Research on prediction of PPV in open pit mine used on intelligent hybrid model of extreme gradient boosting

Peak particle velocity (PPV) serves as a critical metric in assessing the appropriateness of blasting design parameters. However, existing methods for accurately measuring PPV remain insufficient. To develop a robust PPV prediction model, this study integrates the Extreme Gradient Boosting (XGBoost) algorithm with four distinct optimization techniques: Runge Kutta Optimizer (RUN), Equilibrium Optimizer (EO), Gradient-Based Optimizer (GBO), and Reptile Search Algorithm (RSA). Real-time blasting data from open-pit mines are employed to predict PPV, utilizing parameters including Charge Quantity per Hole (CQH/kg), Total Charge Quantity (TCQ/kg), Distance from Bursting Point to Measuring Point (DBM/m), Drilling Depth (DP/m), Borehole Diameter (BD/mm), Spacing (S/m), Row Spacing (RS/m), Minimum Burden (MB/m), and Depth Displacement (DD/m). The predictive outcomes of the XGBoost model, optimized by various algorithms, are benchmarked against the Sadovsky empirical formula, the conventional XGBoost model, and several traditional machine learning models (Ridge, LASSO, SVM, SVR) using performance metrics including R2, RMSE, VAF, MAE, and MBE. Additionally, the Shapley Additive Explanations (SHAP) method is employed to assess the impact of various factors on PPV prediction outcomes. The findings reveal that the GBO-optimized XGBoost model surpasses the RUN, EO, and RSA-optimized XGBoost models, along with other machine learning models and traditional empirical formulas, in predicting PPV. This study further corroborates that the XGBoost model, when enhanced with various optimization algorithms, effectively manages the non-linear characteristics of multiple factors, resulting in a reliable, straightforward, and efficient PPV prediction model. Moreover, the SHAP sensitivity analysis identifies DBM, TCQ, and CQH as the primary factors influencing PPV, enabling engineers to mitigate the impact on nearby structures, equipment, and personnel through the careful adjustment of explosive quantities.

On semi-orthogonal matrices with row vectors of equal lengths

When does a rectangular matrix with an orthonormal set of column vectors have row vectors of equal lengths? The column spaces of such matrices are multidimensional generalizations of the projection plane used in isometric perspective. We show that in the absence of unexpected linear relations, any rectangular matrix can be row-scaled so that if we were to orthonormalize the column vectors, the row vectors would attain equal lengths in the process. We use Grassmann coordinates to reduce the question into an instance of the famous matrix scaling problem, and with the help of existing theory introduce simple numerical solutions.

Investigation on the wave focusing effects and energy capture of Oscillating Water Column array

The study of OWC array hydrodynamic performance has been a focus of attention. However, due to the complex flow and strong nonlinearity generated during its interaction with waves, the main challenge and key focus in current research is how to simulate this process both quickly and accurately. A fast-numerical model of the OWC is developed using the open-source software package OpenFOAM. The numerical model replaces the orifice plate with Forchheimer-flow and the vertical walls with an immersed boundary. Compared to the traditional numerical model, the fast-numerical model can speed up the simulation by at least 10 times. The impact of row spacing and column spacing on the array gain is systematically investigated through the simulations of two-OWCs array, four-OWCs lattice array, and five-OWCs interlaced array. The results show that a two-OWCs array can generate a wave focusing area at its rear, and the location of this area changes with row spacings. For the four-OWCs lattice array, the row spacing increasing causes the wave focusing area to move closer to the array. The proximity of the wave focusing area enhances the power output of the second row of OWCs. After increasing the row and column spacing, the reflection of waves from the second row of OWCs to the first row is decreased, resulting in a reduction in the power output of the first row of OWCs. In contrast to the four-OWC lattice array, the five-OWCs interlaced array demonstrates a lower array gain in the first row of OWCs, with the second row displaying a higher array gain.

Growth and yield of little millet (Panicum sumatrense L.) as influence by varieties and row spacings under rainfed condition

Growth and yield of little millet (Panicum sumatrense L.) as influence by varieties and row spacings under rainfed condition

Simulation Approaches for the Study of the Oil Flow Rate Distribution in Lubricating Systems with Rotating Shafts

This study addresses the issue of predicting the distribution of lubricant flow through the outlets of a rotating shaft used in vehicle power transmission. A typical geometry with closely spaced rows of holes, suitable for the lubrication of multi-disk clutches, was considered. Both lumped parameter and computational fluid dynamics approaches were applied and compared. The test rig for model validation was designed with a variable speed shaft featuring an axial oil inlet and three equally spaced pairs of radial outlet holes. The main characteristic of the experimental facility is the possibility to selectively measure the flow rates through each outlet. It was found that the three-dimensional model based on the multiple reference frame approach provides a reliable prediction of how the flow rate is distributed. Generally, the flow rate is lower through the outlet closest to the inlet and is maximum at the farthest exit. The flow distribution is minimally affected by the shaft speed. The influence of geometric parameters on making the flow distribution more uniform was studied. It was found that a better flow balance is obtained with a low ratio between the diameter of the radial holes and that of the axial channel. The results obtained offer best-practice guidelines for accurately simulating comparable systems, in order to optimize reliability of the mechanical transmission and energy efficiency of the flow generation unit.

Effect of planting densities by the practice of twin rows on the agronomic and technological parameters of sugar cane in rainfed cultivation

With the aim of improving sugar cane productivity under rainfed conditions, a study of the effect of planting densities using paired rows on sugar cane yield parameters was carried out at the CNRA Ferkéssédougou station in northern Côte d'Ivoire. The experimental design used was a Fischer block, comprising three repetitions of six treatments, designated T1 to T6. The results revealed that treatments T1 and T2 improved cane yields, reaching 149±18.04 and 157±44.55 t/ha, respectively. Similarly, an increase in the number of usable stems per hectare of 207,726 ± 13144.44 and 216,468 ± 70412.15 was noted for treatments T1 and T2 respectively. Furthermore, the T6 treatment improved the technological parameters (Brix (22.4 ± 0.86 %); Fibre content (16.8 ± 0.11 %); Pol (19.4 ± 0.81 %) ; Purity of juice (86.7 ± 1.09 %) ; Saccharin content (14.9 ± 0.62 %); Extractable sugar (10.5 ± 0.52 %)). The study also identified three promising planting densities for village cane :1.1m and 1.3m row spacing at 0.4m and 1.3m row spacing at 0.5m. In conclusion, the cultural practice of density in twin rows in sugar cane plantations in rainfed conditions allows an increase in agronomic and technological parameters. This cultivation practice could contribute to an increase in yield or even a substantial increase in sugar production.

Characterization of early fatigue damage in CFRP unidirectional laminates based on Micro‐CT

AbstractFatigue damages of Carbon Fiber Reinforced Polymer (CFRP) laminates are not obvious. Obtaining the evolution of the internal fatigue damage in CFRP laminates before visible cracks occur is of vital importance for ensuring structural reliability. Micro X‐ray computed tomography (Micro‐CT) can provide micron scale nondestructive imaging of internal structure of materials. In this paper, a preliminary study was conducted on the early fatigue damage evolution of 0° UD laminates. Axial tension‐tension fatigue tests of [0]16 CFRP laminates were carried out, and the evolutionary behavior of damages was confirmed by fatigue dissipated energy. Then, the internal damages of fatigued specimens were observed and reconstructed using Micro‐CT, and statistical parameters such as damage sphericity, length and angle were calculated. The spatial distribution characteristics of cracks were further acquired by surface porosity and frequency distribution of damage positions in ROI. Early damages from tensile‐tensile fatigue in 0° UD laminates extend along the fiber direction with original defects in the interlayer resin enrichment areas as the nucleus, and tend to concentrate near the width edge of the specimens. Finally, a “sandwich” structural model was developed to analyze the internal stresses of laminates under the influence of interlayer resin enrichment. The FEA results revealed that the internal stresses σy and σz concentrate near the width edges of the specimen, resulting in cracks tend to evolve more in the regions close to edges.Highlights Imaging matrix cracks of specimens by Micro‐CT at 12.91 μm voxel size. Demonstrating evolution patterns of cracks with its morphology statistics. Revealing crack distributions in ROIs with variations of surface porosity. Analyzing internal stress distribution by “sandwich” model created from reality.

Improved algorithm for fracture-dissolution pore detection in resistivity imaging logging based on dung beetle optimization

Abstract Resistivity imaging logging has become a direct and precise method for visualizing the structural complexities of reservoir fractures and dissolution pores. The current use of Otsu's thresholding for segmentation results in poor segmentation quality and significant noise. Accurate segmentation of sub-images containing fracture and dissolution pore targets is essential for automated structure identification and subsequent parameter calculation. This study leverages the rapid convergence and robust global optimization capabilities of the Dung Beetle Optimizer to develop enhanced image segmentation approaches. Specifically, it introduces a refined K-Means algorithm for multi-category image segmentation and an Otsu algorithm for multi-threshold image segmentation, both optimized by the Dung Beetle Optimizer. Compared to conventional binary segmentation algorithms, this new algorithm effectively isolates noise and extracts multi-category information. Using the segmented sub-images, this paper integrates mathematical morphology techniques to compute parameters such as area, perimeter, tortuosity length, and pore shape factor for identified targets. Additionally, Principal Component Analysis is used to derive recognition factors for fractures and dissolution pores. Applications show that this factor can identify matrix, fracture, and dissolution pore targets in complex background images. By combining parameter information of the target area, the method effectively removes false information in resistivity imaging and segments sub-images of fractures and dissolution pores, calculating fracture area ratio, dissolution pore area ratio, and total area ratio.