Found 79 results
Open Access
Communication
06 February 2026Buckling and Post-Buckling Behavior of the Delaminated Composite Plates
Multilayer composite materials, having high specific strength and rigidity, are sensitive to interlayer defects. The problem of interlayer laminations in a composite plate subjected to a plane compressive load is studied using a new analytical structure previously developed by the authors. Elastic characteristics of a multilayer package of thin lamination, including the elastic characteristics of separate layers, depending on modulus of elasticity, shear modulus, Poisson’s ratio, and angle of orientation of fibers of the unidirectional layer, are determined. Ratios are obtained for the unidirectional composite material that reflect the contribution of each component (fiber, matrix) in proportion to its volume fraction, according to the so-called “mixture rule”. This work examines the behavior after the loss of stability of an elliptical defect in a composite plate. Only the local bulging of the delamination type defect was considered. The difference between this work and others lies in the fact that the application of the developed method, based on the energy approach, makes it possible to obtain explicit analytical expressions for quantities characterizing the critical load and describing the supercritical behavior of the detached part. The energy method is generalized to the case of analyzing the stability of defects in a non-linear formulation. The value of the critical load was obtained, and the analysis of the supercritical deformation of the defect was made.
Open Access
Article
03 February 2026Rebuilding Community Cohesion in Migrant-Sending Villages: A Theory-of-Change Model for Social Work and Public Policy in Depopulating Rural Romania
Rural out-migration has become one of the most significant drivers of social and institutional fragility in contemporary Europe, particularly in peripheral and migrant-sending regions. Beyond demographic decline, sustained mobility generates care drain, school disengagement, elderly isolation, and erosion of interpersonal and institutional trust, ultimately leading to community fragmentation. While existing research has extensively documented these effects, far less attention has been given to how they can be systematically reversed through coordinated public policy and social intervention. This paper proposes a governance-ready Theory of Change that integrates social capital theory, social disorganization, rural migration studies, and cohesion-oriented social policy into a unified framework for restoring community cohesion in migrant-sending rural areas. The model specifies how multi-sectoral policy inputs, spanning social work, education, local government, civil society, and EU cohesion instruments, activate bonding, bridging, and linking forms of social capital, generating measurable improvements in school engagement, community participation, intergenerational solidarity, return-migrant reintegration, and institutional trust. Through two complementary visual models, a linear recovery pathway and a self-reinforcing cohesion cycle, the paper demonstrates how social recovery becomes cumulative and resilient once critical relational and institutional thresholds are reached. The proposed framework advances rural development scholarship by shifting the focus from managing migration impacts to governing social regeneration, offering a transferable policy architecture for strengthening cohesion, resilience, and sustainable development in mobility-affected rural regions.
Open Access
Article
02 February 2026Topology Optimization for Drone Structure: Comprehensive Workflow Including Conceptual Modeling, Components Preparation and Additive Manufacturing
Payload drones are often limited more by frame weight than by motor power. This work aims to design, optimize, and validate a flat octocopter frame with eight independently driven rotors arranged symmetrically on separate arms. The drone frame design in SOLIDWORKS uses Finite Element Analysis (FEA) and topology optimization to remove material from low-stress regions while keeping the main load paths intact. The final design cuts the frame mass by 37.3% compared to the baseline model and reduces the 3D printing time by about five hours using a Creality K1C printer with Polylactic Acid (PLA) filament. These changes increase the available thrust-to-weight margin for payload without exceeding the allowable stress or deformation limits of the material. The electronic components also identified compatible flight controllers, ESCs, motors, and radio systems to show that the proposed frame can be integrated into a complete multirotor platform. Overall, this work demonstrates a practical approach to designing lighter octocopter frames that are easier to 3D print and can be used more effectively for delivery and inspection missions.
Open Access
Article
30 January 2026Forecasting Forest Product Yields in China Based on a Random Forest Model: Interaction Between Climate Change and Socio-Economic Factors
This study presents a comprehensive projection of China’s forest product yield dynamics (encompassing commodity timber and logs) through 2100, employing an innovative integration of machine learning and economic modeling. We developed a hybrid analytical framework combining random forest algorithms with Cobb-Douglas production functions to assess multi-dimensional drivers, including climatic variables, socio-economic indicators, and demographic trends. Our multi-model validation demonstrated strong predictive performance (R2 are 0.86 and 0.92), particularly in quantifying climate-production interactions, with sensitivity analysis identifying surface downward shortwave radiation (RSDS), population density (POP), and mean annual temperature (MAT) as dominant predictors explaining 68% of yield variance. Future yields exhibited significant spatial and temporal variations under different SSP scenarios, especially under SSP126, where yields were more stable, and under SSP245 and SSP370, where yields showed a moderate increasing trend. The SSP585 shows higher fluctuations and a decreasing trend in yields due to climate change. Geospatial modeling uncovered critical regional disparities, suggesting potential production migration from traditional southern bases to north-eastern/northwestern frontiers under climate stress. The southern subtropical belt emerged as particularly vulnerable to thermal extremes and precipitation variability, while northern regions demonstrated greater climate resilience but require substantial silvicultural adaptation. These results provide a scientific basis for developing more precise forest management policies and sustainable development strategies to help meet the challenges posed by future demand for forest products and climate change.
Open Access
Article
16 January 2026Operation Management Optimization of Hydropower Stations Based on Big Data Technology: A Case Study of X Hydropower Station Group
In the operation management of hydropower stations, uneven scheduling often leads to issues such as resource wastage and unequal energy distribution; big data technology offers a new approach for optimizing the scheduling of hydropower stations in the information era. Taking the X Hydropower Station Group as a case study, this paper explores data acquisition, cleaning, clustering analysis, and the formulation of seasonal scheduling strategies to enhance the efficient utilization of hydropower resources and ensure the stable operation of the power grid. K-means clustering analysis is applied to explore typical output curves of cascaded hydropower stations, revealing the relationships between water levels, inflow rates, and load rates. Furthermore, a grey prediction model is developed to forecast future load rates, providing robust data support for short-term operational scheduling plans. The research not only improves monitoring and decision-support capabilities but also enhances the adaptability and response speed to seasonal changes, ensuring the stability and reliability of the power supply.
Open Access
Article
14 January 2026Large-Scale Language Model Assisted Construction of Multi-Source Heterogeneous Knowledge Graphs for Marine Renewable Energy
Marine renewable energy systems, particularly offshore wind and photovoltaic (PV) installations, generate large volumes of heterogeneous maintenance texts. However, the resulting knowledge remains fragmented due to dispersed sources, diverse formats, and domain-specific terminology. To address these challenges, this study proposes a large-scale language model assisted methodology for constructing a multi-source heterogeneous knowledge graph for intelligent operation and maintenance (O&M). The method integrates unified document preprocessing, domain-oriented prompt engineering, large-scale language model–based entity and relation extraction, and multi-level entity normalization. It systematically transforms unstructured documents (e.g., standards, procedures, manuals, inspection records, and environmental reports) into structured triples, enabling the construction of a dynamically evolving O&M knowledge graph. A rigorous ablation study on real-world offshore wind and PV datasets demonstrates that the proposed workflow exhibits exceptional robustness against OCR noise (e.g., scanned artifacts, stamps, and signatures) and substantially improves extraction volume, accuracy, and coverage compared with traditional methods. In particular, combining high-quality preprocessing and optimized prompts yields the most reliable and semantically coherent results. The study provides a practical technical pathway for automated knowledge management in marine renewable energy and offers a foundation for future applications in intelligent diagnostics, predictive maintenance, and digital-twin systems.
Open Access
Article
08 January 2026A Large-Scale Language Model Based System for Automated Generation of Offshore Wind Power Feasibility Study Reports
Driven by global energy transition goals, the large-scale development of offshore wind power imposes rigid requirements for professionalism, standardization, and timeliness on feasibility study reports (FSR). Traditional manual compilation and existing automated methods fail to meet these requirements due to interdisciplinary complexity, poor process controllability, and insufficient domain adaptation. To address these challenges, this paper proposes a configurable and interpretable offshore wind FSR generation system built on a three-tier framework that encompasses “data support, process orchestration, and quality assurance”. The system integrates a YAML-based workflow architecture, multi-level prompt engineering, and a comprehensive evaluation system. Notably, the introduced “Cyclic Aggregation Mode” enables the iterative generation and logical summarization of multi-subproject data, effectively distinguishing this system from traditional linear text generation models. Experimental results demonstrate that the proposed “Retrieval-Augmented Generation (RAG) + Large-scale Language Model (LLM) + Workflow” system outperforms baseline models with key metrics including semantic consistency (0.6592), information coverage (0.3908), structural compliance (0.5123), and an overall score (0.5965). Ablation studies validate the independent contributions of the RAG and Workflow components, thereby establishing the “RAG + LLM + Workflow” paradigm for intelligent professional document generation. This work addresses core challenges related to controllability, accuracy, and interpretability in high-stakes decision-making scenarios while providing a reusable technical pathway for the automated feasibility demonstration of offshore wind power projects.
Open Access
Review
30 December 2025Advances in Hydrology of Irrigation Districts in Cold Regions
Given the extreme complexity of systems, the strategic importance of water resources, and the high ecological vulnerability in cold-region irrigation districts (CRIDs), research on the hydrological processes in these areas represents not only an interdisciplinary scientific endeavor, but also a critical practical challenge with direct implications for food security, water security, ecological safety, and sustainable regional development in high-altitude and high-latitude regions. The evolution of this field has progressed from early phenomenon identification to mechanistic analysis and, more recently, to multi-process and multi-scale simulation frameworks. This paper provides a systematic review of hydrological processes in CRIDs. It first examines fundamental components such as precipitation, evaporation, snowmelt, and groundwater recharge, highlighting their distinct behaviors under the combined influence of freeze–thaw cycles and irrigation practices, and further discusses the interactions and coupling mechanisms among these processes. Irrigation not only alters soil moisture distribution and freeze–thaw dynamics but also, together with freeze–thaw processes, shapes the transient hydrological dynamics characteristics of water and energy transfer, thereby influencing system stability and agricultural productivity. Hydrological modeling has advanced from simplified empirical approaches to mechanistic frameworks that integrate multiple processes and scales, yet challenges remain in the representation of nonlinear freeze–thaw, the integration of irrigation management, and cross-scale consistency. Moreover, cold-region irrigation districts exhibit heightened sensitivity to extreme events, such as rapid snowmelt, severe droughts or heavy rainfall. Future research should deepen the integration of freeze–thaw mechanisms with crop models, advance multi-scale coupled simulations, enhance long-term monitoring and scenario analysis, and systematically incorporate water–carbon balance and ecological effects into hydrological assessments. These efforts will support sustainable management and precision regulation of water resources in cold-region irrigation districts.
Open Access
Article
09 December 2025Defiant Doctorates: Reshaping the Social, Cultural and Intellectual Value of the Doctorate in Regional Universities
Universities are ranked and clustered into ‘like-minded’ institutions. Regional universities—as an adjective and noun or a compound noun—are defined via location, rather than academic standards, teaching innovation, research rigour, or the use of innovative technology. Through the ‘regional’ labelling, they are marked and separated as different from, and implicitly less than, urban and metropolitan institutions, which carry the excitement of urbanity, encompassing Virilian speed and prestigious alumni. This differentiation has consequences for grants, funding, academic staff attrition, and leadership. But what happens to PhD students at regional universities? Where is their voice? How are their views recognized, codified, and understood? Written between an experienced supervisor and a PhD student, this paper offers a different pathway through the regional graduate programme, offering a different lens to re-vision regional higher education, beyond cliches of partnerships and collaborations. As a theoretical and conceptual paper, it creates and holds space for PhD students in a revisioning of regional universities.
Open Access
Article
04 December 2025Stakeholder Mental Models for Sustainable Management of the Invasive Pearl Oyster Pinctada radiata in the Eastern Mediterranean
Sustainable management of marine and coastal systems depends not only on ecological dynamics but also on the ways stakeholders perceive and interpret them. This study investigates how fishers, scientists, and government officials understand and frame the management of the Indo-Pacific pearl oyster Pinctada radiata, a non-native yet economically valuable species established around Evia Island, Greece. Using a mixed-methods approach (N = 80), we combined an eleven-item Hydro-ecological Governance Perception Scale (HGPS) with open-ended responses to explore cognitive patterns and governance perspectives. Sampling adequacy was satisfactory (KMO = 0.74; Bartlett’s χ2(55) = 350.41, p < 0.001) and factor analysis revealed two interrelated dimensions explaining 67.8% of total variance (α = 0.84; ω = 0.86; CR = 0.82). Although Kruskal–Wallis tests showed no statistically significant differences among groups (p > 0.05), hierarchical clustering distinguished three partially overlapping cognitive profiles: Ecological Pragmatists, Institutional Collaborators, and Adaptive Stewards (Silhouette = 0.45; CH = 150.23; DBI = 0.75). Thematic and sentiment analyses underscored the importance of collaboration, transparency, and education (mean sentiment = 0.58). The findings demonstrate how cognitive diversity can improve hydro-ecological resilience and the sustainability of coastal governance when it is mobilized through co-management and participatory monitoring.
