Search Results (109)

The shear strength of rock discontinuities is critical for the stability of deep underground projects. However, its accurate determination is hindered by the discreteness of natural joints and the limitations of conventional direct shear tests, which operate under simplified two-dimensional stress conditions, unlike the true triaxial (σ₁ > σ₂ > σ₃) in situ state. This study introduces and validates a multistage true triaxial direct shear testing method as a practical solution. Through controlled pre-peak unloading, complete failure envelopes were successfully obtained from single specimens of jointed granite and intact marble with minimal strength degradation. The results demonstrate that lateral stress significantly enhances the peak shear strength, characterized by a marked increase in cohesion coupled with a slight decrease in the internal friction angle. For intact marble, increasing the lateral stress from 0 to 20 MPa raised the cohesion by approximately 67% (from 34.9 to 58.4 MPa), while the friction angle decreased from 49.3° to 42.8°. For jointed granite, cohesion showed a more variable but consistently strengthening trend with confinement, accompanied by a minor adjustment in the friction angle. Acoustic emission monitoring confirms that pre-peak unloading confines damage accumulation to microcrack reactivation. From a fracture mechanics perspective, the strength enhancement is attributed to the suppression of tensile crack propagation and the promotion of shear localization under three-dimensional confinement. Collectively, this work establishes a novel experimental framework and elucidates the mechanism by which lateral stress governs the shear behavior of hard rock, offering direct implications for the design and stability assessment of deep excavations and related geo-engineering projects. Full article

The performance upgrading of stratospheric airships hinges on breakthroughs in the mechanical properties of envelope materials. As a multi-layer composite, the envelope’s load-bearing layer exhibits orthotropic and nonlinear mechanical behaviors owing to its unique structure and manufacturing process. To overcome the limitations of traditional testing methods and classical strength criteria in characterizing envelope materials, this paper presents a systematic investigation of typical airship envelope materials. The classical cruciform biaxial specimen was modified with a double-layer heat-sealed loading arm design to ensure preferential failure of the core region. Combined with digital image correlation (DIC) equipment, tensile tests were conducted under seven warp–weft stress ratios to acquire full-range stress–strain data. A three-dimensional stress–strain response surface was fitted based on the experimental results, and biaxial tensile constitutive models with varying precisions were established. Furthermore, a five-parameter implicit quadratic strength criterion was adopted to characterize the failure envelope of the envelope material. The model was calibrated using five biaxial failure points and independently validated against uniaxial tensile strengths, achieving a prediction error of less than 4%. The criterion’s generalization capability was enhanced through systematic parameterization based on the present test data. This work provides experimental evidence and reliable support for the engineering design and strength prediction of envelope materials. Full article

Accurate prediction of the shear strength of rock discontinuities requires accounting for surface roughness, which is a factor neglected in the classical Mohr–Coulomb criterion. This study proposes a fractal-enhanced Mohr–Coulomb model that incorporates the surface fractal dimension Ds as a geometric state variable governing both the cohesion and internal friction angle. The fractal dimension is treated as an objective, scale-invariant descriptor, computable via established methods, such as box-counting and power spectral density analysis, which are known to yield consistent results when applied to joint topography. The model predicts a nonlinear increase in shear strength with Ds, producing a dynamically adjustable failure envelope that can exceed the classical Mohr–Coulomb estimates by 25–40% for rough joints, which is consistent with trends observed in experimental shear tests. By linking strength parameters directly to measurable surface geometry, the framework provides a physically interpretable bridge between micro-scale roughness and macro-scale mechanical response. Although the current formulation assumes monotonic, dry, and quasi-static conditions, the explicit dependence on Ds offers a foundation for future extensions that incorporate anisotropy, damage evolution, and hydro-mechanical coupling. Full article

To address the challenge of effectively extracting early-stage failure features in rolling bearings, this paper proposes a two-stage harmonic optimization-gram method based on spectral amplitude modulation (SAM-TSHOgram). The method first employs amplitude spectra with varying weighting exponents to preprocess the signal, performing nonlinear adjustments to the vibration signal’s spectrum to enhance weak periodic impact characteristics. Subsequently, a two-stage evaluation strategy based on spectral coherence (SCoh) was designed to adaptively identify the optimal frequency band (OFB). The first stage employs the Periodic Harmonic Correlation Strength (PHCS) metric, based on autocorrelation, to coarsely screen candidate bands with strong periodic structures. The second stage utilizes the Sparse Harmonic Significance (SHS) metric, based on spectral negative entropy, to refine the candidate set, selecting bands with the most prominent harmonic features. Finally, SCoh is integrated over the selected OFB to generate an Improved Envelope Spectrum (IES). The proposed method was validated using both simulated and experimental vibration signals from bearings and gearboxes. The results demonstrate that SAM-TSHOgram significantly outperforms conventional approaches such as EES, Fast Kurtogram, and IESFOgram in terms of signal-to-noise ratio (SNR) enhancement, harmonic clarity, and diagnostic robustness. These findings confirm its potential for reliable early fault detection in rolling bearings. Full article

To address the energy and environmental challenges, this study targets the need for ultra-low energy buildings in China’s hot summer-cold winter region (HSCW) by developing high-performance alkali-activated foam concrete (AAFC) insulation material. Initially, a target performance indicator system was established. Subsequently, a mix proportion design method based on the volume method was proposed, and preliminary mix proportions were designed and tested to achieve the target performance. Accordingly, eight factors, including alkali equivalent and SiO₂ aerogel content, were selected for further optimization. A systematic optimization of performance was then conducted using an L₃₂(4⁸) orthogonal experimental design. Range analysis and analysis of variance indicated that foam content significantly affected all target properties. The water-to-binder ratio notably influenced mechanical performance and dry density. Alkali equivalent and activator modulus directly regulated the reaction process. Notably, the incorporation of 2.5 wt% SiO₂ aerogel reduced the thermal conductivity to 0.1107 W/(m·K), highlighting its significant role in improving thermal insulation and effectively resolving the common trade-off between insulation and mechanical properties in FC. Furthermore, the waterproofing agent played a critical role in reducing water absorption and enhancing frost resistance. Finally, the optimal mix proportion was determined through matrix analysis, with all material properties meeting the expected targets. Test results confirmed that the optimized FC achieved a dry density of 576.34 kg/m³, compressive and flexural strengths of 5.83 MPa and 1.41 MPa, respectively, a drying shrinkage rate of only 0.614 mm/m, a mass water absorption of 3.87%, and strength and mass loss rates below 10.5% and 1.8% after freeze–thaw cycles. Therefore, this material presents a novel solution for the envelope structures of low-energy buildings. Full article

Aircraft with a twin vertical tail and leading-edge extension configuration may experience vertical tail buffeting during high-angle-of-attack maneuvering flight. This issue can lead to structural fatigue damage in the vertical tail, shortening its service life and increasing maintenance costs, ultimately compromising flight safety. Therefore, accurate prediction of buffeting loads and responses is essential during design. In the preliminary stage, wind tunnel testing is the primary means to obtain dynamic data such as fluctuating pressure and acceleration response, which can be transformed to full-scale conditions through similitude principles. However, the elastic scaling model used in buffeting tests is usually established for a specific flight condition. When the flow velocity or objective flight condition changes, the similitude relationship becomes invalid, limiting the applicability of test results and preventing full-envelope strength verification. To overcome this limitation, this study proposes a multi-objective point response prediction method for vertical tail buffeting. The method enables the prediction of full-scale responses at multiple objective flight conditions using wind tunnel data that do not strictly satisfy similitude criteria. A complete aircraft vertical tail buffet (rigid/elastic) hybrid model was developed for testing, and an Adjusted Model incorporating elastic scaling transformation was established. The proposed method was validated through experiments, demonstrating improved test data utilization and prediction accuracy across multiple-objective flight conditions. Full article

This paper reviews and analyzes three types of vertical-axis wind rotors: the classic Savonius, spiral Savonius, and Darrieus designs. Using numerical modeling methods, including computational fluid dynamics (CFD), their aerodynamic characteristics, power output, and efficiency under different operating conditions are examined. Key parameters such as lift, drag, torque, and power coefficient are compared to identify the strengths and weaknesses of each rotor. Results highlight that the Darrieus rotor demonstrates the highest efficiency at higher wind speeds due to lift-based operation, while the spiral Savonius offers improved stability, smoother torque characteristics, and adaptability in turbulent or low-wind environments. The classic Savonius, though less efficient, remains simple, cost-effective, and suitable for small-scale urban applications where reliability is prioritized over high performance. In addition, the study outlines the importance of blade geometry, tip speed ratio, and advanced materials in enhancing rotor durability and efficiency. The integration of modern optimization approaches, such as CFD-based design improvements and machine learning techniques, is emphasized as a promising pathway for developing more reliable and sustainable vertical-axis wind turbines. Although the primary analysis relies on numerical simulations, the observed performance trends are consistent with findings reported in experimental studies, indicating that the results are practically meaningful for design screening, technology selection, and siting decisions. Unlike prior studies that analyze Savonius and Darrieus rotors in isolation or under heterogeneous setups, this work (i) establishes a harmonized, fully specified CFD configuration (common domain, BCs, turbulence/near-wall treatment, time-stepping) enabling like-for-like comparison; (ii) couples the transient aerodynamic loads p(θ,t) into a dynamic FEA + fatigue pipeline (rainflow + Miner with mean-stress correction), going beyond static loading proxies; (iii) quantifies a prototype-stage materials choice rationale (aluminum) with a validated migration path to orthotropic composites; and (iv) reports reproducible wake/torque metrics that are cross-checked against mature models (DMST/actuator-cylinder), providing design-ready envelopes for small/medium VAWTs. Overall, the work provides recommendations for selecting rotor types under different wind conditions and operational scenarios to maximize energy conversion performance and long-term reliability. Full article

High energy consumption in Chinese rural residential buildings, caused by rudimentary construction methods and the poor thermal performance of building envelopes, poses a significant challenge to national sustainability and “dual carbon” goals. To address this, this study proposes a comprehensive modeling and analysis framework integrating an improved Bio-inspired Black-winged Kite Optimization Algorithm (IBKA) with Support Vector Regression (SVR). Firstly, to address the limitations of the original B-inspired BKA, such as premature convergence and low efficiency, the proposed IBKA incorporates diversification strategies, global information exchange, stochastic behavior selection, and an NGO-based random operator to enhance exploration and convergence. The improved algorithm is benchmarked against BKA and six other optimization methods. An orthogonal experimental design was employed to generate a dataset by systematically sampling combinations of influencing factors. Subsequently, the IBKA-SVR model was developed for energy consumption prediction and analysis. The model’s predictive accuracy and stability were validated by benchmarking it against six competing models, including GA-SVR, PSO-SVR, and the baseline SVR and so forth. Finally, to elucidate the model’s internal decision-making mechanism, the SHAP (SHapley Additive exPlanations) interpretability framework was employed to quantify the independent and interactive effects of each influencing factor on energy consumption. The results indicate that: (1) The IBKA demonstrates superior convergence accuracy and global search performance compared with BKA and other algorithms. (2) The proposed IBKA-SVR model exhibits exceptional predictive accuracy. Relative to the baseline SVR, the model reduces key error metrics by 37–40% and improves the R² to 0.9792. Furthermore, in a comparative analysis against models tuned by other metaheuristic algorithms such as GA and PSO, the IBKA-SVR consistently maintained optimal performance. (3) The SHAP analysis reveals a clear hierarchy in the impact of the design features. The Insulation Thickness in Outer Wall and Insulation Thickness in Roof Covering are the dominant factors, followed by the Window-wall Ratios of various orientations and the Sun space Depth. Key features predominantly exhibit a negative impact, and a significant non-linear relationship exists between the dominant factors (e.g., insulation layers) and the predicted values. (4) Interaction analysis reveals a distinct hierarchy of interaction strengths among the building design variables. Strong synergistic effects are observed among the Sun space Depth, Insulation Thickness in Roof Covering, and the Window-wall Ratios in the East, West, and North. In contrast, the interaction effects between the Window-wall Ratio in the South and other variables are generally weak, indicating that its influence is approximately independent and linear. Therefore, the proposed bio-inspired framework, integrating the improved IBKA with SVR, effectively predicts and analyzes residential building energy consumption, thereby providing a robust decision-support tool for the data-driven optimization of building design and retrofitting strategies to advance energy efficiency and sustainability in rural housing. Full article

In offshore drilling and geological exploration, the stability of jack-up rigs is predominantly determined by the bearing capacities of spudcan foundations during seabed penetration. The penetration depth of spudcans is relatively shallow in hard clay. The formation of a cavity on the top surface of a spudcan often complicates accurate estimation of its capacity. This study employs the finite element method, in conjunction with the Swipe and Probe loading techniques, to examine the failure surfaces of soils of varying strengths. Numerical simulations that consider different gradients of undrained shear strength and cavity depths demonstrate that cavity depth significantly influences the failure envelope. The findings indicate that higher soil strength increases the bearing capacity and reduces the area of soil displacement at failure. Moreover, an enhanced theoretical equation for predicting the vertical-horizontal-moment (V-H-M) failure envelope in hard clay strata is proposed. The equation’s accuracy has been verified against numerical simulation results, revealing an error margin of 3–10% under high vertical loads. This model serves as a practical and valuable tool for assessing the stability of jack-up rigs in hard clay, providing critical insights for engineering design safety and risk assessment. Full article

The integration of renewable energy technologies into the building sector is critical for achieving climate and energy targets, particularly within the framework of the European Union’s decarbonization policies. Building-integrated photovoltaics (BIPV) offer a promising solution by enabling the dual function of building envelope components and on-site electricity generation. However, the widespread adoption of BIPV faces significant barriers, including high initial investment costs, design and integration complexity, fragmented standardisation and a shortage of skilled labour. This study systematically identifies, evaluates and prioritises the key factors influencing the implementation of BIPV technologies using a hybrid SWOT (strengths, weaknesses, opportunities, threats) and Analytic Hierarchy Process (AHP) methodology. A comprehensive literature review and a modified Delphi method involving expert input were employed to select and rank the most relevant factors in each SWOT category. The results indicate that external factors—particularly regulatory requirements for energy efficiency, renewable energy adoption and financial incentives—are the most significant drivers for BIPV deployment. Conversely, competition from building-attached photovoltaics (BAPV), high investment costs and the complexity of integration represent the main barriers and threats, compounded by internal weaknesses such as a lack of qualified workforce and fragmented standardisation. The findings underscore the importance of targeted regulatory and financial support, standardisation and workforce development to accelerate BIPV adoption. This research provides a structured decision-making framework for policymakers and stakeholders, supporting strategic planning for the integration of BIPV in the construction sector and contributing to the transition towards sustainable urban energy systems. Full article

Obtaining the echo of individual fish is an important prerequisite for fisheries acoustic applications, such as in situ measurement of fish target strength and assessment of fish abundance using the counting method. It is also the foundation for evaluating the growth status of farmed fish and managing aquaculture risks. The density of farmed fish populations is typically higher, and such high-density aquaculture further increases the difficulty of obtaining individual fish echoes in practical applications. Building upon previous research and considering the behavioral characteristics of fish in aquaculture settings, this study conducted performance simulations, live fish experiments in simulated aquaculture cages, and comparative evaluations of three individual fish broadband echo detection methods based on a broadband signal system: the amplitude pulse width method (APM) based on echo envelopes, the peak detection and time delay estimation method (PDM), and the peak time delay combined with instantaneous frequency method (PDIM). This study assumed a dorsolateral fish orientation, which limits its research scope and applicability. The results showed that the PDIM achieved a detection accuracy of 78.34% and a false recognition rate of 1.32%. The APM based on echo envelopes was insensitive to individual fish echoes and had lower recognition accuracy. The PDM exhibited better individual fish echo capture capabilities, while the PDIM demonstrated superior overlapping echo rejection capabilities. Full article

The objective of this study is to create an integrated and sustainability-centered framework to identify optimal locations for wind energy projects in Indonesia. This research employs a novel two-phase multi-criteria decision-making (MCDM) framework that combines the strengths of Data Envelopment Analysis (DEA), Fuzzy Analytic Hierarchy Process (FAHP), and Fuzzy Combined Compromise Solution (F-CoCoSo). Initially, DEA is utilized to pinpoint the most promising sites based on a variety of quantitative factors. Subsequently, these sites are evaluated against qualitative criteria such as technical, economic, environmental, and socio-political considerations using FAHP for criteria weighting and F-CoCoSo for ranking the sites. Comprehensive sensitivity analysis of the criteria weights and a comparative assessment of methodologies substantiate the robustness of the proposed framework. The results converge on consistent rankings across methods, highlighting the effectiveness of the integrated approach. Notably, the results consistently identify Lampung, Aceh, and Riau as the top-ranked provinces, showcasing their strategic suitability for wind plant development. This framework provides a systematic approach for enhancing resource efficiency and strategic planning in Indonesia’s renewable energy sector. Full article

Super-resolution microscopy (SRM) has revolutionized our understanding of subcellular structures, including cell organelles and viruses. For human immunodeficiency virus (HIV), SRM has significantly advanced knowledge of viral structural biology and assembly dynamics. This review analyzes how SRM techniques (particularly PALM, STORM, STED, and SIM) have been applied over the past decade to study HIV structural components and assembly. By categorizing and comparing studies based on SRM methods, HIV components, and labeling strategies, we assess the strengths and limitations of each approach. Our analysis shows that PALM is most commonly used for live-cell imaging of HIV Gag, while STED is primarily used to study the viral envelope (Env). STORM and SIM have been applied to visualize various components, including Env, capsid, and matrix. Antibody labeling is prevalent in PALM and STORM studies, targeting Env and capsid, whereas fluorescent protein labeling is mainly associated with PALM and focused on Gag. A recent emphasis on Gag and Env points to deeper investigation into HIV assembly and viral membrane dynamics. Insights from SRM studies of HIV not only enhance virological understanding but also inform future research in therapeutic strategies and delivery systems, including extracellular vesicles. Full article

Lithium hydride (LiH) is one promising material for nuclear reactor shielding due to its high hydrogen content, but its poor mechanical strength and thermal conductivity pose challenges for fabricating large, crack-free ceramic components via conventional sintering. This study explores microwave sintering as a potential solution to enhance heating uniformity and reduce thermal stress during densification of bulk LiH ceramics. Using implicit function and level set methods, we numerically simulated the microwave field distribution and thermal response in both stationary and rotating samples. The results show that rotational heating improves temperature uniformity by up to 12.9% for specific samples, although uniform temperature control remains difficult through rotation alone. To mitigate stress accumulation from thermal gradients, we propose a cyclic sintering–resting strategy, which leverages LiH’s tensile strength–temperature envelope to guide safe and efficient processing. This strategy successfully reduced total sintering time from several days to 1.63 h without inducing cracks. Our findings offer practical insights into optimizing microwave sintering parameters for large-scale LiH ceramic production and contribute to enabling its application in advanced nuclear shielding systems. Full article

The structural reliability of bottom-fixed offshore wind turbines is generally influenced by the dispersion of and variability in soil properties, which affect their ultimate capacity, serviceability, and both the short- and long-term fatigue. During an earthquake, the soil–pile system is subjected to intense cyclic loads that can lead to stiffness and strength degradation, typically captured through cyclic soil models. Calibration of soil parameter variability is fundamental for reliable structural assessments of wind turbine integrity. In this study, a method to generate randomness of the parameters affecting cyclic soil degradation models is proposed. Fatigue parameters are quantified through random cyclic undrained triaxial tests conducted using the Discrete Element Method. Deterministic simulations are first performed based on experimental results from the Liquefaction Experiments and Analysis Project for validation. Subsequently, variability in the initial particle size distribution functions is introduced to generate random soil samples, and triaxial simulations are repeated to quantify the dispersion of soil fatigue parameters. The proposed procedure is then applied through Monte Carlo simulations on the IEA 15-MW reference wind turbine, which is subjected to both short- and long-duration earthquakes. The results demonstrate the significant impact of soil degradation on the bending moment envelope, as well as the effect of soil uncertainty on tower fatigue, assessed using the damage equivalent load approach. Full article