Search Results (60)

Reservoir group flood control scheduling decision-making faces multiple uncertainties, such as dynamic fluctuations of evaluation indicators and conflicts in weight assignment. This study proposes a risk analysis model for the decision-making process: capturing the temporal uncertainties of flood control indicators (such as reservoir maximum water level and downstream control section flow) through the Long Short-Term Memory (LSTM) network, constructing a feasible weight space including four scenarios (unique fixed value, uniform distribution, etc.), resolving conflicts among the weight results from four methods (Analytic Hierarchy Process (AHP), Entropy Weight, Criteria Importance Through Intercriteria Correlation (CRITIC), Principal Component Analysis (PCA)) using game theory, defining decision-making risk as the probability that the actual safety level fails to reach the evaluation threshold, and quantifying risks based on the First-Order Second-Moment (FOSM) method. Case verification in the cascade reservoirs of the Qiantang River Basin of China shows that the model provides a risk assessment framework integrating multi-source uncertainties for flood control scheduling decisions through probabilistic description of indicator uncertainties (e.g., Zmax1 with μ = 65.3 and σ = 8.5) and definition of weight feasible regions (99% weight distribution covered by the 3σ criterion), filling the methodological gap in risk quantification during the decision-making process in existing research. Full article

The predictive performance of the remaining useful life (RUL) estimation model for bearings is of utmost importance, and the setting method of the bearing degradation threshold is crucial for detecting its early degradation point, as it significantly affects the performance of the RUL prediction model. To solve these problems, a bearing RUL prediction method based on early degradation detection and optimized BiLSTM is proposed: an optimized VMD combined with the Pearson correlation coefficient is used to denoise the bearing signal. Afterward, multi-domain features are extracted and evaluated using different metrics. The optimal degradation feature is then selected. Furthermore, KPCA is used to integrate the features and establish the health indicators (HIs) for early degradation detection of bearings using a sliding window method combined with the 3σ (3-sigma) criterion and the quartile method. The RUL prediction model is developed by combining the BiLSTM network with the attention mechanism and by employing the SSA to adaptively update the network parameters. The proposed RUL prediction model is tested on various datasets to evaluate its generalization ability and applicability. The obtained results demonstrate that the proposed denoising method has high performance. The dynamic 3σ-threshold setting method accurately detects the early degradation points of bearings. The proposed RUL prediction model has high performance and fitting capacity, as well as very high generalization ability and applicability, enabling the early prediction of bearing RUL. Full article

Granite is the main rock type in hot dry rock reservoirs, and hydraulic fracturing is always required during the process of geothermal production. It is necessary to understand the strength parameters and failure criterion of granite after high-temperature and water-cooling treatment. In this paper, laboratory uniaxial and triaxial compression experiments are carried out on granite samples after high-temperature and water-cooling treatment. Combined with some experimental data collected from pre-existing studies, the variation behaviors of cohesion (c), the internal friction angle ($\phi$) and tensile strength $\left({\sigma }_{\mathrm{t}}\right)$ are systematically studied considering the heating and cooling treatment. It is found that c and $\phi$ generally show two different types of variation behaviors with the increasing heating temperature. Tensile strength decreases in a similar way for the different granite samples with the increasing treatment temperature. Empirical equations are provided to describe these strength parameters. Finally, a modified Mohr–Coulomb failure criterion with a “tension cut-off” is established for the granite samples, considering the effects of high-temperature and water-cooling treatment. This study should be helpful for understanding the mechanical behavior of hot dry rock during hydraulic fracturing in geothermal production, and the proposed failure criterion can be applied for the numerical modeling of reservoirs. Full article

When deep-buried tunnels are excavated using the drill-and-blast method, the surrounding rock is subjected to combined cyclic blasting loads and excavation-induced stress unloading. Understanding the distribution characteristics of rock damage zones under these conditions is crucial for the design and safety of building-integrated underground structures. This study investigates the relationship between surrounding rock damage and in situ stress conditions through numerical simulation methods. A constitutive model suitable for simulating rock mass damage was developed and implemented in the LS-DYNA (version R12) code via a user-defined material model, with parameters determined using the Hoek–Brown failure criterion. A finite element model was established to analyze surrounding rock damage under cyclic blasting loads, and the model was validated using field data. Simulations were then carried out to explore the evolution of the damage zone under various stress conditions. The results show that with increasing hydrostatic pressure, the extent of the damage zone first decreases and then increases, with blasting-induced damage dominating under lower pressure and unloading-induced shear failure prevailing at higher pressure. When the hydrostatic pressure is less than 20 MPa, the surrounding rock stabilizes at a distance greater than 12.6 m from the tunnel face, whereas at hydrostatic pressures of 30 MPa and 40 MPa, this distance increases to 29.4 m. When the lateral pressure coefficient is low, tensile failure occurs mainly at the vault and floor, while shear failure dominates at the arch waist. As the lateral pressure coefficient increases, the failure mode at the vault shifts from tensile to shear. Additionally, when the horizontal stress perpendicular to the tunnel axis (σ_H) is less than the vertical stress (σ_v), variations in the axial horizontal stress (σ_h) have a significant effect on shear failure. Conversely, when σ_H exceeds σ_v, changes in σ_h have little impact on the extent of rock damage. Full article

This work presents a novel, compact (six pieces), low-cost (<$500 USD), and easy-to-manufacture metallography mounting device. The device is designed to produce high-quality polymer encapsulated samples that rival those obtained from commercial equipment ($5000–$10,000 USD). Utilizing the House of Quality (HoQ) framework within Quality Function Deployment (QFD), the device prioritizes critical customer requirements, including safety (validated via finite element method, FEM), affordability, and compatibility with standard hydraulic presses. FEM analysis under 29 MPa pressure revealed a maximum Von Mises stress of 80 MPa, well below the AISI 304 stainless steel yield strength of 170 MPa, yielding a static safety factor of 2.1. Fatigue analysis under cyclic loading (mean stress ${\sigma }_m$ = 40 MPa, amplitude stress ${\sigma }_a$ = 40 MPa) using the Modified Goodman Criterion demonstrated a fatigue safety factor of 3.75, ensuring infinite cycle durability. The device was validated at 140 °C (413.15 K) with a 5-min dwell time, encapsulating samples in a cylindrical configuration (31.75 mm diameter) using a 200 W heating band. Benchmarking confirmed performance parity with commercial systems in edge retention and surface uniformity, while reducing manufacturing complexity (vs. conventional 100-piece systems). This solution democratizes access to metallography, particularly in resource-constrained settings, fostering education and industrial innovation. Full article

Rapid and precise detection of hydrogen sulfide (H₂S) at trace levels is critical for industrial safety and environmental air quality monitoring, yet existing methods often struggle with cost, speed, or sensitivity. A cost-effective cavity ring-down spectroscopy (CRDS) analyzer is presented, incorporating a novel digital locking circuit for sequential laser-cavity mode matching. This system demonstrates rapid and precise hydrogen sulfide (H₂S) detection capability at parts-per-billion (ppb) concentration levels. Compared to traditional wavelength meters, our system delivers a 140-fold improvement in frequency interval precision (0.07 MHz, 0.027% relative uncertainty). Allan variance analysis under vacuum conditions demonstrates a sensitivity limit of 3 × 10⁻¹² cm⁻¹ at a 60-s averaging time. Validated through calibrated gas dilution tests, the analyzer detects a 4 ppb H₂S absorption signal with a signal-to-noise ratio (SNR) > 6, establishing a 2 ppb detection limit (3σ criterion). This innovative approach meets stringent industrial and environmental requirements, offering a significant advancement in trace gas-sensing technology. Full article

The mechanical properties and envelope curve predictions of polyurethane-improved calcareous sand are significantly influenced by the magnitude and direction of principal stress. This study conducted a series of directional shearing tests with varying polyurethane contents (c = 2.5%, 5%, and 7.5%), stress Lode angles (${\theta }_{\sigma }$ = −19.1°, 0°, 19.1°, and 30°), and major principal stress angles (α = 0°, 30°, 45°, 60°, and 90°) to investigate the strength and non-coaxial characteristics of calcareous sand improved by polyurethane foam adhesive (PFA). Key findings revealed that failure strength varied significantly with the major principal stress axis direction, initially decreasing to a minimum at α = 45° before increasing, with a 30% decrease and 25% increase observed at c = 5%. Non-coaxial characteristics between strain increment and stress directions became more pronounced, with angles varying up to 15°. Increasing polyurethane content from 2.5% to 7.5% enhanced sample strength by 20% at ${\theta }_{\sigma }$ = −19.1° and α = 60°. A generalized linear strength theory in the π-plane accurately described strength envelope variations, while a modified Lade criterion, incorporating polymer content, effectively predicted multiaxial strength characteristics with less than 10% deviation from experimental results. These contributions provide quantitative insights into failure strength and non-coaxial behavior, introduce a robust strength prediction framework, and enhance multiaxial strength prediction accuracy, advancing the understanding of polyurethane-improved calcareous sand for engineering applications. Full article

The global navigation satellite system (GNSS) struggles to deliver the precision and reliability required for positioning, navigation, and timing (PNT) services in environments with severe interference. Fifth-generation (5G) cellular networks, with their low latency, high bandwidth, and large capacity, offer a robust communication infrastructure, enabling 5G base stations (BSs) to extend coverage into regions where traditional GNSSs face significant challenges. However, frequent multi-sensor faults, including missing alarm thresholds, uncontrolled error accumulation, and delayed warnings, hinder the adaptability of navigation systems to the dynamic multi-source information of complex scenarios. This study introduces an advanced, tightly coupled GNSS/5G/IMU integration framework designed for distributed PNT systems, providing all-source fault detection with weighted, robust adaptive filtering. A weighted, robust adaptive filter (MCC-WRAF), grounded in the maximum correntropy criterion, was developed to suppress fault propagation, relax Gaussian noise constraints, and improve the efficiency of observational weight distribution in multi-source fusion scenarios. Moreover, we derived the intrinsic relationships of filtering innovations within wireless measurement models and proposed a time-sequential, observation-driven full-source FDE and sensor recovery validation strategy. This approach employs a sliding window which expands innovation vectors temporally based on source encoding, enabling real-time validation of isolated faulty sensors and adaptive adjustment of observational data in integrated navigation solutions. Additionally, a covariance-optimal, inflation-based integrity protection mechanism was introduced, offering rigorous evaluations of distributed PNT service availability. The experimental validation was carried out in a typical outdoor scenario, and the results highlight the proposed method’s ability to mitigate undetected fault impacts, improve detection sensitivity, and significantly reduce alarm response times across step, ramp, and multi-fault mixed scenarios. Additionally, the dynamic positioning accuracy of the fusion navigation system improved to 0.83 m ($1\sigma$). Compared with standard Kalman filtering (EKF) and advanced multi-rate Kalman filtering (MRAKF), the proposed algorithm achieved 28.3% and 53.1% improvements in its $1\sigma$ error, respectively, significantly enhancing the accuracy and reliability of the multi-source fusion navigation system. Full article

Four quaternary Zintl phase thermoelectric (TE) materials belonging to the Ba_1-xEu_xZn₂Sb₂ (x = 0.02(1), 0.04(1), 0.08(1), 0.15(1)) system were successfully synthesized using the molten Pb-flux or the conventional high-temperature reaction methods. Their crystal structures were characterized by both powder and single-crystal X-ray diffraction analyses, and all four isotypic title compounds adopted the orthorhombic BaCu₂S₂-type (Pnma, Z = 4, Pearson code oP20) structure. The radius ratio criterion, based on the cationic and anionic elements (i.e., r₊/r₋), was successfully verified in the title system, as in our previous reports, where r₊/r₋ > 1 for the BaCu₂S₂-type structure. A series of density functional theory calculations were performed using a hypothetical model with the idealized compositions of Ba_0.75Eu_0.25Zn₂Sb₂, and the results were compared with the ternary parental compound BaZn₂Sb₂ to understand the influence of Eu substituents in the Ba_1-xEu_xZn₂Sb₂ system. A similar overall shape of the density of states (DOS) curves and the near-constant DOS values at E_F before and after the cationic substitution suggest only marginal changes in the carrier concentration. Therefore, carrier mobility has a dominant role in rationalizing the observed variations in the electrical transport properties of the title system. Temperature-dependent TE property measurements proved that an increase in the Seebeck coefficient S and a decrease in electrical conductivity σ were observed as the Eu substituents gradually increased in the Ba_1-xEu_xZn₂Sb₂ system, although the overall S and σ values were lower than those in the parental compound BaZn₂Sb₂. The thermal conductivities of these title compounds were successfully lowered by phonon scattering, but due to the overall smaller electrical transport properties, the observed maximum ZT was 0.49 at 773 K for Ba_0.98(1)Eu_0.02Zn₂Sb₂. Full article

In modern autonomous systems, measurement repeatability and precision are crucial for robust decision-making algorithms. Stereovision, which is widely used in safety applications, provides information about an object’s shape, orientation, and 3D localisation. The camera’s lens distortion is a common source of systematic measurement errors, which can be estimated and then eliminated or at least reduced using a suitable correction/calibration method. In this study, a set of cameras equipped with Basler lenses (C125-0618-5M F1.8 f6mm) and Sony IMX477R matrices are calibrated using a state-of-the-art Zhang–Duda–Frese method. The resulting distortion coefficients are used to correct the images. The calibrations are evaluated with the aid of two novel methods for lens distortion measurement. The first one is based on linear regression with images of a vertical and horizontal line pattern. Based on the evaluation tests, outlying cameras are eliminated from the test set by applying the 2$\sigma$ criterion. For the remaining cameras, the MSE was reduced up to 75.4 times, to 1.8 px−6.9 px. The second method is designed to evaluate the impact of lens distortion on stereovision applied to bird tracking around wind farms. A bird’s flight trajectory is synthetically generated to estimate changes in disparity and distance before and after calibration. The method shows that at the margins of the image, lens distortion might introduce errors into the object’s distance measurement of +17%−+20% for cameras with the same distortion and from −41% up to $+\infty$ for camera pairs with different lens distortions. These results highlight the importance of having well-calibrated cameras in systems that require precision, such as stereovision bird tracking in bird–turbine collision risk assessment systems. Full article

So-called strength-ductility trade-off is usually an inevitable scenario in precipitation-strengthened alloys. To address this challenge, high-density coherent nanoprecipitates (CNPs) as a microstructure effectively promote ductility though multiple interactions between CNPs and dislocations (i.e., coherency, order, or Orowan mechanism). Although some strain hardening theories have been reported for individual strengthening, how to increase, artificially and quantitatively, the ductility arising from cooperative strengthening due to the multiple interactions has not been realized. Accordingly, a dislocation-based theoretical framework for strain hardening is constructed in terms of irreversible thermodynamics, where nucleation, gliding, and annihilation arising from dislocations have been integrated, so that the cooperative strengthening can be treated through thermodynamic driving force $∆G$ and the kinetic energy barrier. Further combined with synchrotron high-energy X-ray diffraction, the current model is verified. Following the modeling, the yield stress ${\sigma }_{\mathrm{y}}$ is proved to be correlated with the modified strengthening mechanism, whereas the necking strain ${\epsilon }_{\mathrm{n}}$ is shown to depend on the evolving dislocation density and, essentially, the enhanced activation volume. A criterion of high $∆G$-high generalized stability is proposed to guarantee the volume fraction of CNPs improving ${\sigma }_{\mathrm{y}}$ and the radius of CNPs accelerating ${\epsilon }_{\mathrm{n}}$. This strategy of breaking the strength-ductility trade-off phenomena by controlling the cooperative strengthening can be generalized to designing metallic structured materials. Full article

This paper analyses mechanical property prediction through Machine Learning for continuous fiber-reinforced polymer matrix composites printed using the novel Material Extrusion Additive Manufacturing technique. The composite is formed by a nylon-based matrix and continuous fiber (carbon, Kevlar, or fiberglass). From the literature, the elastic modulus and tensile strength were taken along with printing parameters like fiber content, fiber fill type, matrix lattice, matrix fill density, matrix deposition angle, and fiber deposition angle. Such data were fed to several supervised learning algorithms: Ridge Regression, Bayesian Ridge Regression, Lasso Regression, K-Nearest Neighbor Regression, CatBoost Regression, Decision Tree Regression, Random Forest Regression, and Support Vector Regression. The Machine Learning analysis confirmed that fiber content is the most influential parameter in elasticity (E) and strength ($\sigma$). The results show that the K-Nearest Neighbors and CatBoost provided the closest predictions for E and $\sigma$ compared to the other models, and the tree-based model presented the narrowest error distribution. The computational metrics point to a size versus prediction time tradeoff between these two best predictors, and adopting the prediction time as the most relevant criterion leads to the conclusion that the CatBoost model can be considered, when compared to the others tested, the most appropriate solution to work as a predictor in the task at hand. Full article

Harmful algal blooms (HABs) threaten lake ecosystems and public health. Early HAB detection is possible by monitoring chlorophyll-a (Chl-a) concentration. Ground-based Chl-a data have limited spatial and temporal coverage but can be geo-registered with temporally coincident satellite imagery to calibrate a remote sensing-based predictive model for regional mapping over time. When matching ground and satellite data, positional and temporal discrepancies are unavoidable due particularly to dynamic lake surfaces, thereby biasing the model calibration. This limitation has long been recognized but so far has not been addressed explicitly. To mitigate such effects of data mismatching, we proposed an Akaike Information Criterion (AIC)-like weighted regression algorithm that relies on an error-based heuristic to automatically favor “good” data points and downplay “bad” points. We evaluated the algorithm for estimating Chl-a over inland lakes in Ohio using Harmonized Landsat Sentinel-2. The AIC-like weighted regression estimates showed superior performance with an R² of 0.91 and an error variance (${\sigma }_E^2$) of 0.29 μg/L, outperforming linear regression (R² = 0.34, ${\sigma }_E^2$ = 2.34 μg/L) and random forest (R² = 0.82, ${\sigma }_E^2$ = 0.92 μg/L). We also noticed the poorest performance occurred in the spring due to low reflectance variation in clear water and low Chl-a concentration. Our weighted regression scheme is adaptive and generically applicable. Future studies may adopt our scheme to tackle other remote sensing estimation problems (e.g., terrestrial applications) for alleviating the adverse effects of geolocation errors and temporal discrepancies. Full article

Post-filling coarse aggregate concrete (PFCC) is a new type of concrete that achieves energy-saving and emission-reduction goals through optimizing material proportions. The post-filled coarse aggregates can save the amount of cement material used, improve the strength and elastic modulus, prolong the service life of the material, and reduce expenses. We conducted a biaxial tension–compression test on PFCC cubic specimens, analyzed the strength and stress–strain curve regularity under different post-filling ratios (PFRs) and stress ratios, and proposed a new failure criterion suitable for PFCC. The results demonstrated that the tensile strength and compressive strength of each post-filling ratio concrete specimen under biaxial tension–compression action are lower than its uniaxial tensile and uniaxial compressive strength under the same post-filling ratio. Under the same stress ratio, the variation pattern of the post-filling ratio was the same as that under uniaxial stress, with the maximum value occurring at a PFR of 20%. The strength change rule was affected by both the stress ratio and the post-filling ratio. From the stress–strain curve, it can be seen that the presence of tensile stress significantly reduces the stiffness and ductility of PFCC under biaxial tensile and compressive loading. The strain corresponding to the peak strength of the σ₃/f_c-ε₃ curve was much smaller than the peak strain under uniaxial compression. For example, at a stress ratio of (0.05:1), the strain ε₃ in the compression direction was on average about 50% to 60% of the uniaxial compression strain under the same PFR. The stress–strain curve of PFCC under biaxial tensile and compressive loading was approximately linear throughout the loading process. A failure criterion for PFCC under biaxial tension–compression loading was established, and the calculated values agreed well with the test values. This paper provides references and research data for the study of PFCC under complex stress conditions. Full article

In this paper, based on Gaussian 1σ-criterion and histogram segmentation, a weighted least-squares algorithm is applied and validated on digital holographic speckle pattern interferometric data to perform phase separation on the complex interference fields. The direct structural diagnosis tool is used to investigate defects and their impact on a complex antique wall painting of Giotto. The interferometry data is acquired with a portable off-axis interferometer set-up with a phase-shifted reference beam coupled with the object beam in front of the digital photosensitive medium. A digital holographic speckle pattern interferometry (DHSPI) system is used to register digital recordings of interferogram sequences over time. The surface is monitored for as long as it deforms prior to returning to its initial reference equilibrium state prior to excitation. The attempt to separate the whole vs. local defect complex amplitudes from the interferometric data is presented. The main aim is to achieve isolation and visualization of each defect’s impact amplitude in order to obtain detailed documentation of each defect and its structural impact on the surface for structural diagnosis purposes. Full article