Search Results (209)

To improve fracturing support efficiency of terrestrial shale oil reservoirs with uneven proppant placement, this study used complex mesh flat-plate simulations and ANSYS FLUENT (2020) simulations to test four sand addition processes. Proppants were 70/140 mesh quartz sand with a density of 2650 kg/m³ and 40/70 mesh ceramic particles with a density of 2000 kg/m³, and the carrier was hydroxypropyl guar gum fracturing fluid with a viscosity of 4.46–13.4 mPa·s at 25 °C. Alternating sand addition performed best: sand-laying efficiency reached 52 percent, 10 percentage points higher than continuous sand addition and 12 percentage points higher than mixed sand addition; sand embankment void area was 1400 cm², 18.3 percent lower than continuous sand addition; proppant entry into secondary cracks increased 23.8 percent compared with reverse sand addition; at branch crack Position 2, 1.3 m from the inlet and at a 90-degree angle, its equilibrium height was 210 mm and paving rate 0.131. This study fills gaps of no systematic multi-process comparison and insufficient quantification of crack geometry–sand parameter coupling in existing research; its novelty lies in the unified visualization comparison of four processes, revealing geometry–parameter coupling and integrating experiment simulation; the optimal scheme also improves fracture support efficiency 21.5 percent compared with conventional continuous sand addition. Full article

Surface ozone pollution poses a significant threat to human health and ecosystems. However, its highly variable spatiotemporal distribution, especially at hourly scales across China, complicates effective risk management. This variability presents substantial challenges for accurate estimation and forecasting, underscoring the importance of evaluating current hourly surface ozone estimation methods. Therefore, this study collaboratively evaluated the performance of chemical transport model simulations and satellite-based estimates of hourly surface ozone concentrations over mainland China in 2019. Using data from 3185 ground monitoring stations operated by the Ministry of Ecology and Environment, as well as six independent observation sites in Hong Kong, Xianghe, Nam Co, Akedala, Longfengshan, and Waliguan, this study found that both datasets exhibited systematic biases and lacked spatiotemporal consistency. The Community Atmosphere Model with Chemistry simulation results exhibited an average relative bias of 23.17%, generally overestimated ozone concentrations in high-altitude regions, but outperformed the satellite-based estimates at the independent sites, while consistently underestimating ozone concentrations in densely populated urban areas. In contrast, the satellite-based estimates performed better in regions with dense monitoring sites, with mean biases typically within 10% of observations, but their accuracy was limited in remote areas due to sparse ground-based calibration. It is particularly noteworthy that both datasets showed deficiencies in capturing extremely high-value events, nighttime ozone variations, and dynamic transport processes, underscoring challenges in the representation of photochemical processes in the model and in the design of satellite estimation algorithms. The results highlight the importance of optimizing model parameterization schemes, improving satellite estimation algorithms, and integrating multi-source data to enhance the accuracy and stability of hourly ozone estimates. This study provides multi-scale quantitative insights into the relative strengths and limitations of different ozone estimation methods, laying a solid scientific foundation for future data integration, regional air quality management, and policy development. Full article

In the context of rapid advancements in big data and artificial intelligence, similarity measurement methods between samples have been widely applied in data mining, pattern recognition, medical diagnosis, financial risk control, and other fields. The Mahalanobis distance, due to its effectiveness in capturing correlations within high-dimensional data, has become a crucial tool in many practical scenarios. However, sample data often contains sensitive privacy information, making it essential to achieve secure and privacy-preserving computation of Mahalanobis distance. This paper proposes a secure Mahalanobis distance calculation scheme tailored for sample vectors that effectively resists malicious cheating behaviors. The designed multi-party computation algorithms ensure privacy protection while maintaining computational efficiency and minimizing communication overhead. The experimental results compare three algorithms in terms of execution time and communication delay across varying sample sizes and vector dimensions. The results demonstrate that our proposed scheme achieves a favorable balance between security and performance. This research provides a practical and robust solution for similarity measurement under privacy constraints and lays a theoretical and practical foundation for secure data collaboration in multi-party computing environments, offering significant application potential. Full article

A high-performance Z-scheme heterojunction photocatalytic compound, ZnBiGdO₄/SnS₂ (ZS), was prepared for the first time using a microwave-assisted solvothermal method. ZS significantly improved the separation efficiency of photoinduced carriers and effectively broadened the response range to visible light through the unique mechanism of the Z-type heterojunction. Therefore, ZS exhibited an excellent photocatalytic performance during the degradation process of tinidazole (TNZ). Specifically, the removal rate of TNZ by ZS reached 99.63%, and the removal rate of total organic carbon (TOC) reached 98.37% with ZS as catalyst under visible light irradiation (VLIN). Compared to other photocatalysts, the photocatalytic performance of ZS was significantly better than that of ZnBiGdO₄, SnS₂, or N-doped TiO₂ (N-T). The removal rate of TNZ by ZS was 1.12 times, 1.26 times, or 2.41 times higher than that by ZnBiGdO₄, SnS₂, or N-T, respectively. The mineralization efficiency of TNZ for TOC with ZS as a catalyst was 1.15 times, 1.28 times, or 2.57 times higher than that with ZnBiGdO₄, SnS₂, or N-T as a catalyst, respectively. Free radical scavenging experiments and the electron paramagnetic resonance experiments confirmed that ZS could generate multiple reactive species such as hydroxyl radicals (•OH), superoxide anions (•O₂⁻), and photoinduced holes (h⁺) during the photocatalytic degradation process of TNZ. The photocatalytic degradation performance of ZS on TNZ under VLIN was evaluated, concurrently, the reliability, reproducibility, and stability of ZS were verified by five cycle experiments. This study explored the degradation mechanism and degradation pathway of TNZ with ZS as a catalyst under VLIN. This study not only provides new ideas for the design and preparation of Z-type heterojunction photocatalysts but also lays an important foundation for the development of efficient environmental remediation technologies for TNZ pollution. Full article

Expandable polystyrene (EPS) nozzle covers can be used to replace traditional metal nozzle covers due to their excellent mechanical properties, as well as being lightweight and ablatable. As an important part of the solid rocket motor, the nozzle cover needs to be designed according to the requirements of the overall system. This study lays a theoretical foundation for the engineering design and performance optimization of the EPS nozzle cover. In this paper, the method of combining test research and numerical simulation is used to explore the pressure bearing capacity of EPS nozzle covers with different thicknesses under linear load. Firstly, the quasi-static tensile, compression and shear tests of EPS materials were carried out by universal testing machine, and the key parameters such as stress-strain curve, elastic modulus and yield strength were obtained; Based on the experimental data, the constitutive model of EPS material with respect to density is fitted and modified; The VUMAT subroutine of the material was written in Fortran language, and the mechanical properties of the nozzle cover with different material model distribution schemes and different thicknesses were explored by ABAQUS finite element numerical simulation technology. The results indicate that the EPS nozzle cover design based on the two material model allocation schemes better aligns with practical conditions; when the end thickness of the EPS nozzle cover exceeds 3 mm, the opening pressure formula for the cover based on the pure shear theory of thin-walled circular plates becomes inapplicable; the EPS nozzle cover exhibits excellent pressure-bearing capacity and performance, with its pressure-bearing capacity showing a positive correlation with its end thickness, and an EPS nozzle cover with a 9 mm end thickness can withstand a pressure of 7.58 MPa (under internal pressure conditions); the pressure-bearing capacity of the EPS nozzle cover under internal pressure conditions is higher than under external pressure conditions, and when the end pressure-bearing surface thickness increases to 9 mm, the internal pressure-bearing capacity is 3.13 MPa higher than under external pressure conditions. Full article

Curved plate forming is essential in shipbuilding but traditionally relies on manual methods with low efficiency. Achieving automation in curved plate forming requires robust methods to generate processing solutions. This paper introduces a novel method for deriving the processing routes and strain distributions necessary to form complex curve plate using integrated heating and mechanical rolling forming equipment. The key aspects of this method include analyzing the target surface and solving for the required processing strains based on finite element analysis, discretizing the strain paths and refining them into engineering-feasible processing routes, deriving processing schemes from the calculated strains, and predicting and validating the processing schemes using the inherent strain method. The method is validated by applying it to typical surface of ship hull plates. Key outcomes demonstrate the method’s effectiveness and applicability: (1) The proposed method effectively establishes a quantitative relationship between the target surface geometry, processing routes, and the required processing strains. (2) By analyzing various target surface cases, the method demonstrates wide applicability. Standardized procedures can be applied to different surface shapes to derive the necessary processing routes and strains, thereby laying a solid foundation for the automation of curved hull plate forming. (3) Experimental forming tests on typical curved surfaces confirm that the processing schemes based on the proposed strain generation method can reliably achieve the desired geometries, showcasing the method’s capability to guide practical forming processes. The comparison between the formed and target shapes shows that the processing deviation of the schemes generated by this method remains within 5 mm, demonstrating high accuracy. Full article

Over the last three decades, composite structures have become increasingly more common in everyday life, such as in wind turbines as part of the solution to produce clean energy, and their use in the aerospace industry due to their advantages over conventional materials. Most of these advantages are dependent upon the reliability and quality of the manufacturing process to ensure that there are no defects/faults or imperfections during manufacturing. Thus, it is critical to monitor the enclosed environment of moulds during fabrication in real time. This need has caused many researchers—past and present—to create or apply many sensing technologies to achieve real-time monitoring of the manufacturing processes of composite structures to ensure that the structures can meet their requirements. A consequence of these research activities is the myriad of sensing schemes, (for example, optical, electrical, piezo, and nanomaterial schemes and the use of digital twins) available to consider, and the investigations all of them have both strengths and weaknesses for a given application, with no apparent option having a distinct advantage. This review reveals that the best possible sensing solution depends upon a large set of parameters, the geometry of the composite structure, the required specification, and budget limits, to name a few. Furthermore, challenges remain for researchers trying to find solutions, such as a sensing scheme that can directly detect wrinkles/waviness during the laying-up procedure, real-time detection of the resin flow front throughout the mould, and the monitoring of the resin curing spatially, all at a spatial resolution of ~1 cm with the required sensitivity along with the need to obtain the true interpretation of the real-time data. This review offers signposts through the variety of sensing options, with their advantages and failings, to readers from the composite and sensing community to aid in making an informed decision on the possible sensing approaches to help them meet their composite structure’s desired function and tolerances, and the challenges that remain. Full article

In brain mapping, structural templates derived from population-specific MRI scans are essential for normalizing individual brains into a common space. This normalization facilitates accurate group comparisons and statistical analyses. Although templates have been developed for various populations, none currently exist for the Saudi population. To our knowledge, this work introduces the first structural brain template constructed and evaluated from a homogeneous subset of T1-weighted MRI scans of 11 healthy Saudi female subjects aged 25 to 30. Our approach combines the symmetric model construction (SMC) method with a covariance-based weighting scheme to mitigate bias caused by over-represented anatomical features. To enhance the quality of the template, we employ a patch-based mean-shift intensity estimation method that improves image sharpness, contrast, and robustness to outliers. Additionally, we implement computational optimizations, including parallelization and vectorized operations, to increase processing efficiency. The resulting template exhibits high image quality, characterized by enhanced sharpness, improved tissue contrast, reduced sensitivity to outliers, and minimized anatomical bias. This Saudi-specific brain template addresses a critical gap in neuroimaging resources and lays a reliable foundation for future studies on brain structure and function in this population. Full article

The snake-laying method is widely employed as an effective strategy for global buckling mitigation in submarine pipelines. The uneven distribution of soil resistance along pipeline routes significantly amplifies the complexity of global buckling responses in snake-laid pipelines and challenges their control mechanisms. This study establishes a finite element computational model to investigate the effects of soil resistance distribution gradients and patterns along pipeline routes, alongside their coupling with critical snake-laying parameters (spacing, offset, curvature). The research revealed that an uneven distribution of soil resistance can induce the global buckling submersion phenomenon in snake-laid pipelines. Among the critical snake-laying parameters, curvature enhancement proves to be the most effective mitigation strategy against the global buckling submersion phenomenon. Additionally, an improvement in the conventional uniform-laying scheme is proposed for uneven soil resistance distribution: the originally planned snake-laid section can be replaced by a straight pipeline section in the high-resistance zone. This study provides enhanced technical solutions for global buckling prevention in pipelines traversing uneven seabeds. Full article

Recent research in agricultural remote sensing mainly focuses on how soil background affects canopy reflectance and the inversion of LAI, while often overlooking the influence of the weed layer. The coexistence of crop and weed layers forms two-layered vegetation canopies in tall crops such as sugarcane and maize. Although radiative transfer models can simulate the weed layer’s influence on canopy reflectance and LAI inversion, few experimental investigations use in situ measurement data to verify these effects. Here, we propose a practical background modification scheme in which black material with near-zero reflectance covers the weed layer and alters the background spectrum of crop canopies. We conduct an experimental investigation in a sugarcane field with different background properties (i.e., bare soil and a weed layer). Tower-based and UAV-based hyperspectral measurements examine the spectral differences in sugarcane canopies with and without the black covering. We then use LAI measurements to evaluate the weed layer’s impact on LAI inversion from UAV-based hyperspectral data through a hybrid inversion method. We find that the weed layer significantly affects the canopy reflectance spectrum, changing it by 13.58% and 42.53% in the near-infrared region for tower-based and UAV-based measurements, respectively. Furthermore, the weed layer substantially interferes with LAI inversion of sugarcane canopies, causing significant overestimation. Estimated LAIs of sugarcane canopies with a soil background generally align well with measured values (root mean square error (RMSE) = 0.69 m²/m²), whereas those with a weed background are considerably overestimated (RMSE = 2.07 m²/m²). We suggest that this practical background modification scheme quantifies the weed layer’s influence on crop canopy reflectance from a measurement perspective and that the weed layer should be considered during the inversion of crop LAI. Full article

Recent catastrophic bridge fire incidents have highlighted the critical need for effective post-fire assessment of bridges, thereby challenging the dominant practice of complete replacement following these destructive events. This study investigates the post-fire performance of bare, isolated, and Carbon Fiber Reinforced Polymer (CFRP)-repaired Reinforced Concrete (RC) bridge columns under single-unit truck impact followed by air blast. This extreme loading scenario was deliberately selected given the increased vulnerability of bridge columns to this loading scenario in the recent few years. Three-dimensional Finite Element (FE) models of the structural system and surrounding environment were developed and validated in LS-DYNA. The effectiveness of two in-situ retrofitting schemes in mitigating damage and enhancing structural integrity of three column diameters under the selected multi-hazards was assessed. Results demonstrated that wrapping the bottom half of the column height prevents shear failure and significantly reduces the damage under the coupled impact and blast. In contrast, employing a combination of CFRP bars and externally bonded sheets showed limited enhancement on post-fire impact and blast performance. This study provides critical insights into the feasibility and efficacy of retrofitting bridge columns that have experienced fire, thus laying the groundwork for the reconsideration of current design and rehabilitation protocols. Full article

This paper comprehensively examines symmetric difference operators within logical systems generated by nilpotent t-norms and t-conorms, specifically addressing their behavior and applicability in bounded and Łukasiewicz fuzzy logic systems. We identify two distinct symmetric difference operators and analyze their fundamental properties, revealing their inherent non-associativity. Recognizing the limitations posed by non-associative behavior in practical multi-step logical operations, we introduce a novel aggregated symmetric difference operator constructed through the arithmetic mean of the previously defined operators. The primary theoretical contribution of our research is establishing the associativity of this new aggregated operator, significantly enhancing its effectiveness for consistent multi-stage computations. Moreover, this operator retains critical properties including symmetry, neutrality, antitonicity, and invariance under negation, thus making it particularly valuable for various computational and applied domains such as image processing, pattern recognition, fuzzy neural networks, cryptographic schemes, and medical data analysis. The demonstrated theoretical robustness and practical versatility of our associative operator provide a clear improvement over existing methodologies, laying a solid foundation for future research in fuzzy logic and interdisciplinary applications. Our broader aim is to derive and study symmetric difference operators in both bounded and Łukasiewicz systems, as this represents a new direction of research. Full article

This study proposes an Evolutionary Algorithm (EA) to optimize the workstation layout in multi-product handcrafted furniture workshops with simultaneous manufacturing. The algorithm models the arrangement of workstations within a limited space, enhancing activity coordination and reducing unnecessary worker movement. The optimized solution is obtained through the application of evolutionary operators, including selection, crossover, mutation, and refinement, iterating over successive generations. To evaluate the EA’s performance, a computational simulation is conducted using ProModel^®, comparing its efficiency against conventional methodologies such as Systematic Layout Planning (SLP) and the CRAFT algorithm. In a case study involving the simultaneous elaboration of three different products, each by a different artisan, the EA successfully reduces the total worker travel distance by 51.45% and the system’s total processing time by 13.2%. The results indicate that the proposed approach not only enhances operational efficiency in a smaller environment but also lays the groundwork for integrating advanced strategies. These include cellular manufacturing and hybrid production schemes, ultimately enhancing flexibility and sustainability in this sector. Full article

A Codonopsis pilosula film-laying and outcrop transplantation machine is developed to solve problems, such as unstable quality of transplanted seedlings, high intensity of manual work, and low efficiency of work in the seedling transplantation of Codonopsis pilosula. This paper outlines the structure and working principle of the machine and analyzes the key components of the prototype, designs the seed bed preparer, analyzes its working process and the force required for furrowing into the soil. Additionally, based on EDEM discrete element simulation technology, a soil-component simulation model was established. In addition, the Hertz–Mindlin model was selected as the contact model between the discrete element simulation soil particles and the seed bed preparer to simulate the operation process of the seed bed preparer. The structure and relevant parameters of the seedling planting device and soil covering device are determined, the transmission system scheme is established, and the working mechanism of the core components is analyzed. Field experiment results indicate that at forward speeds of 0.20, 0.25, and 0.3 m/s, the average qualified rate of planting depth is 91.08%, and the average qualified rate of plant spacing is 89.8%. The field performance test indicators met national and industry standards, which require both qualified rates to exceed 80%, and the test results met the design requirements, demonstrating the integrated operation of trenching, seedling planting, film-laying, and topsoil covering. Full article

The construction industry’s transition toward sustainability and the circular economy is vital in reducing its environmental impacts. At the same time, modular construction is gaining wider recognition in the industry. However, studies that apply circular economy principles in modular construction are lacking. This study investigates the challenges and strategies in applying circular economy principles, particularly the 10R principles, in modular construction in Australia. The research utilised qualitative methods such as expert interviews and secondary case studies and analysed data using thematic analysis. The findings reveal that, while rethink and recycle principles are generally implemented, the adoption of the remaining 10R principles is minimal due to limited industry awareness and insufficient initiatives. Case studies highlight challenges such as a lack of technical knowledge, industry engagement, and policy support, as well as the need for strategies such as capacity building, stakeholder collaboration, and government-led initiatives to overcome these barriers. This study contributes to research and practice by identifying key challenges and proposing strategies for the integration of sustainable principles into the Australian modular construction industry, aligning with global sustainability benchmarks and advancing a circular economy. The study emphasises the importance of supportive policies and government schemes to encourage the broader adoption of circular economy practices. Its findings have the potential to shape policy development and influence industry standards, laying a foundation for future studies to deepen our understanding and drive transformative change in the industry. Full article