Search Results (378)

This study develops a novel transverse steel damper (TSD) to enhance the seismic performance of tall-pier girder bridges, featuring superior lateral strength and energy dissipation capacity. The TSD’s design and arrangement are presented, with its hysteretic behavior simulated in ABAQUS. Key parameters (yield strength: 3000 kN; initial gap: 100 mm; post-yield stiffness ratio: 15%) are optimized through seismic analysis under near-fault ground motions, incorporating pulse characteristic investigations. The optimized TSD effectively reduces bearing displacements and results in smaller pier top displacements and internal forces compared to the bridge with fixed bearings. Due to the higher-order mode effects, there is no direct correlation between top displacements and bottom internal forces. As pier height decreases, the S-shaped shear force and bending moment envelopes gradually become linear, reflecting the reduced influence of these modes. Medium- to long-period pulse-like motions amplify seismic responses due to resonance (pulse period ≈ fundamental period) or susceptibility to large low-frequency spectral values. Higher-order mode effects on bending moments and shear forces intensify under prominent high-frequency components. However, the main velocity pulse typically masks the influence of high-order modes by the overwhelming seismic responses due to large spectral values at medium to long periods. Full article

Dragon fruit or pitaya (Hylocereus sp.) is an exotic tropical plant gaining popularity in the United States as it is a nutrient-rich fruit with mildly sweet flavor and a good source of fiber. Although high tunnels are being used to produce specialized crops, little is known about how pitaya growth, physiology and nutrient uptake change throughout the production period. This study aims to evaluate the impact of high tunnels and varying rates of vermicompost on three varieties of pitaya, White Pitaya (WP), Yellow Pitaya (YP), and Red Pitaya (RP), to assess the soil and plant nutrient dynamics, spectral reflectance changes and plant growth. Plants were assessed at 120 and 365 DAP (Days After Plantation). YP thrived in a high tunnel compared to an open environment in terms of survival before 120 DAP, with no diseased incidence and higher nutrient retention. The nutrient accumulation in the RP, WP, and YP shoot samples 120 DAP were ranked in the following order, K > N > Ca > Mg > P > Fe > Zn > B > Mn, while 365 DAP, they were ranked as K > Ca > N > Mg > P > S > Fe > Zn > B > Mn. The nutrient accumulation in the RP, WP, and YP, soil samples 120 and 365 DAP were ranked in the following order: N > Ca > Mg > P > K > Na > Zn. Soil nutrients showed a higher concentration of Na and K grown inside the high tunnels in all three pitaya species due to the increased concentration of soluble salts. Spectral reflectance analysis showed that RP and WP had higher reflectance in the visible and NIR region compared to YP due to their higher plant biomass and canopy cover. This study emphasizes the importance of environmental conditions, nutrition strategies, and plant physiology in the different pitaya plant species. The results suggest that high tunnels with appropriate vermicompost can enhance pitaya growth and development. Full article

This study investigates the complementary noise control capabilities of two passive jet noise mitigation strategies: a traditional ejector nozzle and a novel application of 3M™ Nextel™ 312 ceramic fabric as a thermal–acoustic liner on the central cone of a micro turbojet nozzle. Three nozzle configurations, baseline, ejector, and Nextel-treated, were evaluated under realistic operating conditions using traditional and advanced acoustic diagnostics applied to data from a five-microphone circular array. The results show that while the ejector provides superior directional suppression and low-frequency redistribution, making it ideal for far-field noise control, it maintains high total energy levels and requires structural modifications. In contrast, the Nextel lining achieves comparable reductions in overall noise, especially in high-frequency ranges, while minimizing structural impact and promoting spatial energy dissipation. Analyses in both the time-frequency and spatial–spectral domains demonstrate that the Nextel configuration not only lowers acoustic energy but also disrupts coherent noise patterns, making it particularly effective for near-field protection in compact propulsion systems. A POD analysis further shows that NEXTEL more evenly distributes energy across mid-order modes, indicating its role in smoothing spatial variations and dampening localized acoustic concentrations. According to these results, ceramic fabric linings offer a lightweight, cost-effective solution for reducing the high noise levels typically associated with drones and UAVs powered by small turbojets. When combined with ejectors, they could enhance acoustic suppression in compact propulsion systems where space and weight are critical. Full article

As designers push engine efficiency closer to thermodynamic limits, the analysis of flow instabilities developed in a high-pressure turbine (HPT) is crucial to minimizing aerodynamic losses and optimizing secondary air systems. Purge flow, while essential for protecting turbine components from thermal stress, significantly impacts the overall efficiency of the engine and is strictly connected to cavity modes and rim-seal instabilities. This paper presents an experimental investigation of these instabilities in an HPT stage, tested under engine-representative flow conditions in the short-duration turbine rig of the von Karman Institute. As operating conditions significantly influence instability behavior, this study provides valuable insight for future turbine design. Fast-response pressure measurements reveal asynchronous flow instabilities linked to ingress–egress mechanisms, with intensities modulated by the purge rate (PR). The maximum strength is reached at PR = 1.0%, with comparable intensities persisting for higher rates. For lower PRs, the instability diminishes as the cavity becomes unsealed. An analysis based on the cross-power spectral density is applied to quantify the characteristics of the rotating instabilities. The speed of the asynchronous structures exhibits minimal sensitivity to the PR, approximately 65% of the rotor speed. In contrast, the structures’ length scale shows considerable variation, ranging from 11–12 lobes at PR = 1.0% to 14 lobes for PR = 1.74%. The frequency domain analysis reveals a complex modulation of these instabilities and suggests a potential correlation with low-engine-order fluctuations. Full article

Partial discharge (PD) in insulators will not only lead to the gradual degradation of insulation performance but even cause power system failure in serious cases. Because there is strong noise interference in the field, it is difficult to accurately locate the position of the PD source. Therefore, this paper proposes a three-dimensional spatial localization method of the PD source with a four-element ultra-high-frequency (UHF) array based on improved wavelet packet dynamic threshold denoising and the $G_{xx}-\beta$ generalized cross-correlation algorithm. Firstly, considering the field noise interference, the PD signal is decomposed into sub-signals with different frequency bands by the wavelet packet, and the corresponding wavelet packet coefficients are extracted. By using the improved threshold function to process the wavelet packet coefficients, the PD signal with low distortion rate and high signal-to-noise ratio (SNR) is reconstructed. Secondly, in order to solve the problem that the amplitude of the first wave of the PD signal is small and the SNR is low, an improved weighting function, $G_{xx}-\beta$, is proposed, which is based on the self-power spectral density of the signal and is adjusted by introducing an exponential factor to improve the accuracy of the first wave arrival time and time difference calculation. Finally, the influence of different sensor array shapes and PD source positions on the localization results is analyzed, and a reasonable arrangement scheme is found. In order to verify the performance of the proposed method, simulation and experimental analysis are carried out. The results show that the improved wavelet packet denoising algorithm can effectively realize the separation of PD signal and noise and improve the SNR of the localization signal with low distortion rate. The improved $G_{xx}-\beta$ weighting function significantly improves the estimation accuracy of the time difference between UHF sensors. With the sensor array designed in this paper, the relative localization error is 3.46%, and the absolute error is within 6 cm, which meets the requirements of engineering applications. Full article

Experimental measurements of midwave infrared thermal images of methane diffusion flames at different concomitant flow velocities were obtained as snapshot data to analyze the flame scintillation effect. The spectral proper orthogonal decomposition (SPOD) method was used to extract the frequency-spectral features of the flame to characterize the effect of the co-flow on the flame scintillation characteristics. The results show that, under the effect of the Kelvin-Helmholtz instability, a rolled-up vortex structure is formed within the shear layer, which triggers periodic flickering during flame combustion. The frequency-spectral characteristics of the flickering phenomenon corresponding to unstable combustion show an octave distribution. An increase in the co-flow velocity leads to an increase in the peak flicker frequency. The peak frequency was 11.6 Hz in the case without associated flow and 16.6 Hz in the case with associated flow. The SPOD analysis results indicated that the high-frequency first-order modes dominated by the flickering phenomenon exhibited an axisymmetric distribution, whereas the second-order modes exhibited an antisymmetric distribution. In contrast, the low-frequency first-order modes exhibit an antisymmetric distribution, whereas the second-order modes exhibit an axisymmetric distribution. Full article

Canopy chlorophyll content (CCC) is a key indicator for assessing the carbon sequestration capacity and material cycling efficiency of ecosystems, and its accurate retrieval holds significant importance for analyzing ecosystem functioning. Although numerous destructive and remote sensing methods have been developed to estimate CCC, the accurate estimation of CCC remains a significant challenge in mountainous regions with complex terrain and heterogeneous vegetation types. Through the synergistic analysis of ground hyperspectral and Sentinel-2 data, this study employed Pearson correlation analysis and spectral resampling techniques to identify Sentinel-2 blue band B1 (443 nm) and red band B4 (665 nm) as chlorophyll-sensitive bands through spectral matching with the hyperspectral reflectance of typical grassland vegetation. Based on this, we developed a new four-band vegetation index (VI), the Dual Red-edge and Coastal Aerosol Vegetation Index (DRECAVI), for estimating the CCC of heterogeneous grasslands in the middle section of the Tianshan Mountains. DRECAVI incorporates red-edge anti-saturation modules (bands B4 and B7) and aerosol correction modules (bands B1 and B8). In order to test the performance of the new index, we compared it with eight commonly used indices and a hybrid model, the Sentinel-2 Biophysical Processor (S2BP). The results indicated the following: (1) DRECAVI demonstrated the highest accuracy in CCC retrieval for mountainous vegetation (R² = 0.74, RMSE = 16.79, MAE = 12.50) compared to other VIs and hybrid methods, effectively mitigating saturation effects in high biomass areas and capturing a weak bimodal distribution pattern of CCC in the montane meadow. (2) The blue band B1 enhances atmospheric correction robustness by suppressing aerosol scattering, and the red-edge band B7 overcomes the sensitivity limitations of conventional red-edge indices (such as NDVI705, CIred-edge, and NDRE), demonstrating the potential application of the synergy mechanism between the blue band and the red-edge band. (3) Although the S2BP achieved high accuracy (R² = 0.73, RMSE = 19.83, MAE = 14.71) without saturation effects and detected a bimodal distribution of CCC in the montane meadow of the study area, its algorithmic complexity hindered large-scale operational applications. In contrast, DRECAVI maintained similar precision while reducing algorithmic complexity, making it more suitable for regional-scale grassland dynamic monitoring. This study confirms that the synergistic use of multi-source data effectively overcomes the limitations of the spectral–spatial resolution of a single data source, providing a novel methodology for the precision monitoring of mountain ecosystems. Full article

A majority of hyperspectral super-resolution methods aim to enhance the spatial resolution of hyperspectral imaging data (HSI) by integrating high-resolution multispectral imaging data (MSI), leveraging rich spectral information for various geospatial applications. Key challenges include spectral distortions from high-frequency spatial data, high computational complexity, and limited training data, particularly for new-generation sensors with unique noise patterns. In this contribution, we propose a novel parallel patch-wise sparse residual learning (P²SR) algorithm for resolution enhancement based on fusion of HSI and MSI. The proposed method uses multi-decomposition techniques (i.e., Independent component analysis, Non-negative matrix factorization, and 3D wavelet transforms) to extract spatial and spectral features to form a sparse dictionary. The spectral and spatial characteristics of the scene encoded in the dictionary enable reconstruction through a first-order optimization algorithm to ensure an efficient sparse representation. The final spatially enhanced HSI is reconstructed by combining the learned features from low-resolution HSI and applying an MSI-regulated guided filter to enhance spatial fidelity while minimizing artifacts. P²SR is deployable on a high-performance computing (HPC) system with parallel processing, ensuring scalability and computational efficiency for large HSI datasets. Extensive evaluations on three diverse study sites demonstrate that P²SR consistently outperforms traditional and state-of-the-art (SOA) methods in both quantitative metrics and qualitative spatial assessments. Specifically, P²SR achieved the best average PSNR (25.2100) and SAM (12.4542) scores, indicating superior spatio-spectral reconstruction contributing to sharper spatial features, reduced mixed pixels, and enhanced geological features. P²SR also achieved the best average ERGAS (8.9295) and Q2n (0.5156), which suggests better overall fidelity across all bands and perceptual accuracy with the least spectral distortions. Importantly, we show that P²SR preserves critical spectral signatures, such as Fe²⁺ absorption, and improves the detection of fine-scale environmental and geological structures. P²SR’s ability to maintain spectral fidelity while enhancing spatial detail makes it a powerful tool for high-precision remote sensing applications, including mineral mapping, land-use analysis, and environmental monitoring. Full article

To address the graphitization of diamond induced by high temperatures during laser cladding of diamond-reinforced composites, this study proposes a laser cladding method utilizing Inconel 718 (IN718) nickel-based alloy as a transition layer which has a lower melting point than the substrate of 45# steel. And then, in order to analyze the detailed characteristics of the samples, scanning electron microscopy (SEM), EDS, Raman spectral analyzer, super-depth-of-field microscope, and friction tests were used. Experimental study and the test results demonstrate that the IN718 transition layer enhances coating performance through dual mechanisms: firstly, its relatively low melting point (1392 °C) reduces the molten pool’s peak temperature, effectively suppressing thermal-induced graphitization of the diamond; on the other hand, simultaneously it acts as a diffusion barrier to inhibit Fe migration from the substrate and weaken Fe–C interfacial catalytic reactions. Microstructural analysis reveals improved diamond encapsulation and reduced interfacial sintering defects in coatings with the transition layer. Tribological tests confirm that samples with the transition layer L exhibit lower friction coefficients and significantly enhanced wear resistance compared to those without. This study elucidates the synergistic mechanism of the transition layer in thermal management optimization and interfacial reaction suppression, providing an innovative solution to overcome the high-temperature damage bottleneck in laser-clad diamond tools. Full article

Low-cost powdered activated coke (PAC) produced by a one-step rapid method with lignite was used as an adsorbent for the advanced treatment of phenol-containing wastewater to evaluate the feasibility of replacing high-cost commercial powdered activated carbon. Characterization using infrared spectral analysis, SEM, and BET showed that the PAC mesopores were well developed. PAC exhibited a high adsorption performance for phenol in static experiments. The adsorption was almost in equilibrium within 20 min, and the removal efficiency reached 85.4% with 1.5 g L⁻¹ PAC and 99.9% with 4 g L⁻¹ PAC. As common components in wastewater, NaCl and Na₂SO₄ did not exhibit significant competitive adsorption with phenol in PAC. The adsorption process occurred in accordance with the Langmuir model and the pseudo-second order kinetic model. Furthermore, the effects of hydrothermal regeneration on PAC adsorbing phenol were studied, and the adsorption capacity of PAC after five regeneration cycles was 86.1% of that of the new PAC, which still had good adsorption performance. PAC offers significant advantages in terms of adsorption capacity, economic feasibility, regeneration, and recycling, providing a practical solution to the problem of phenol-containing wastewater pollution. Full article

Significant new progress has been made in nonlinear integrable systems with Riesz fractional-order derivative, and it is impressive that such nonlocal fractional-order integrable systems exhibit inverse scattering integrability. The focus of this article is on extending this progress to nonlocal fractional-order Schrödinger-type equations with variable coefficients. Specifically, based on the analysis of anomalous dispersion relation (ADR), a novel variable-coefficient Riesz fractional-order generalized NLS (vcRfgNLS) equation is derived. By utilizing the relevant matrix spectral problems (MSPs), the vcRfgNLS equation is solved through the inverse scattering transform (IST), and analytical solutions including n-soliton solution as a special case are obtained. In addition, an explicit form of the vcRfgNLS equation depending on the completeness of squared eigenfunctions (SEFs) is presented. In particular, the 1-soliton solution and 2-soliton solution are taken as examples to simulate their spatial structures and analyze their structural properties by selecting different variable coefficients and fractional orders. It turns out that both the variable coefficients and fractional order can influence the velocity of soliton propagation, but there is no energy dissipation throughout the entire motion process. Such soliton solutions may not only have important value for studying the super-dispersion transport of nonlinear waves in non-uniform media, but also for realizing a new generation of ultra-high-speed optical communication engineering. Full article

With the expansion of high-rise building construction in China, tower cranes have become indispensable key equipment in the construction industry. To ensure the safety and structural reliability of tower cranes under complex working conditions, this paper takes a typical 40 m-high flat-arm tower crane as the research object. For the first time, the orthogonal test method was used to monitor the stress of key components (the root of the tower body and the root of the boom). The stress distribution characteristics of the tower crane structure under different working conditions were systematically analyzed. Then, based on the power spectral density analysis method, the natural frequency of the tower crane structure was identified. The influence of key structural parameters, such as lifting position, rope length, and lifting weight, on the stress of the tower crane was quantitatively studied through orthogonal experiments, revealing the multi-parameter coupling effect. The results show that the stress at the measuring point at the root of the tower body is significantly higher than that at the root of the boom. This indicates that the root of the tower body is the primary stress-bearing part of the tower crane structure, highlighting the need to focus on its fatigue performance and safety assessment. Based on the power spectral density analysis of the root stress of the tower crane, the natural frequencies of the tower crane structure were accurately identified. The first-order frequency was 0.10 Hz, and the second-order frequency was 0.20 Hz, providing data support for the study of the tower crane’s dynamic characteristics. The orthogonal test analysis shows that the influences of lifting position, rope length, and lifting weight on the stress of the tower crane are consistent, with no significant differences. The effects of lifting position and rope length on stress are dominant, while the influence of lifting weight is relatively small. These research findings provide an important basis for the lightweight design and safety assessment of tower cranes. Full article

Non-negative Matrix Factorization (NMF) has gained popularity due to its effectiveness in clustering and feature selection tasks. It is particularly valuable for managing high-dimensional data by reducing dimensionality and providing meaningful semantic representations. However, traditional NMF methods may encounter challenges when dealing with noisy data, outliers, or when the underlying manifold structure of the data is overlooked. This paper introduces an innovative approach called SGRiT, which employs Stiefel manifold optimization to enhance the extraction of latent features. These learned features have been shown to be highly informative for clustering tasks. The method leverages a spectral decomposition criterion to obtain a low-dimensional embedding that captures the intrinsic geometric structure of the data. Additionally, this paper presents a solution for addressing the Stiefel manifold problem and utilizes a Riemannian-based trust region algorithm to optimize the loss function. The outcome of this optimization process is a new representation of the data in a transformed space, which can subsequently serve as input for the NMF algorithm. Furthermore, this paper incorporates a novel subspace graph regularization term that considers high-order geometric information and introduces a sparsity term for the factor matrices. These enhancements significantly improve the discrimination capabilities of the learning process. This paper conducts an impartial analysis of several essential NMF algorithms. To demonstrate that the proposed approach consistently outperforms other benchmark algorithms, four clustering evaluation indices are employed. Full article

The chemical structure of coal is very composite, consisting of a heterogeneous carbonaceous matrix with variable degrees of “turbostratic” order and the inclusion and/or exclusion of mineral matter (ash). The formation of surface oxides on carbon has long been recognized as a key to understanding many chemical and physical properties of carbon materials relevant to their consolidated or emerging applications. The extent and nature of surface oxides can effectively be assessed by high-resolution X-ray photoelectron spectroscopy (XPS), which provides excellent insight into the functional nature of C-O moieties. However, the XPS analysis of ash-bearing carbons may be biased by the interfering effects of inorganics with the most relevant spectral ranges, namely the core levels O_1s and C_1s. The effect of ash components on the spectroscopic characterization of carbon is scrutinized here with reference to a sub-bituminous coal characterized by a fairly large ash content. The coal is subjected to different treatments, including devolatilization, milling, and oxidation. A synthetic carbon (Carboxen) is used as a reference sample for the correct assignment of the carbon–oxygen functionalities in the core-level XPS spectra (C_1s and O_1s) in the absence of mineral matter. On the opposite side, fly ash from an industrial coal boiler is analyzed to investigate the effects of mineral matter. It is shown that the establishment of non-uniform charging of the sample induced by ash provides a key to the interpretation of the XPS spectra of ash-bearing carbon samples. The positive charge on the surface, referred to as the charging effect, brings about a shift of the core-level binding energies towards higher values. Grinding of the samples or partial combustion emphasizes the charging effect. XPS analysis of the fly ash, where carbon is largely consumed and dispersed in the inorganic matter, confirms that charging arises from non-conductive aluminosilicates. These effects may induce remarkable changes in carbon and oxygen peak shapes and need to be accounted for to obtain correct interpretations of the XPS spectra of ash-rich carbonaceous fuels. Full article

Vegetation anomalies are frequently occurring and may greatly affect ecological functions. Many near-real-time (NRT) detection methods have been developed to detect these anomalies in a timely manner whenever a new satellite observation is available. However, the undisturbed vegetation conditions captured by these methods are only applicable to a particular pixel or vegetation type, resulting in a lack of universality. Also, most methods that use single characteristic parameter may ignore the multi-spectral expression of vegetation anomalies. In this study, we developed a universal framework to simultaneously detect various vegetation anomalies in NRT from Landsat observations. Firstly, Landsat surface reflectance data from the Benchmark Land Multisite Analysis and Intercomparison of Products (BELMANIP) sites were selected as a reference vegetation dataset to calculate the normalized difference vegetation index (NDVI) and the normalized burn ratio (NBR), which describe vegetation conditions from the perspectives of greenness and moisture, respectively. After the elimination of cloud-contaminated pixels, the high-quality NDVI and NBR data over the BELMANIP sites were further normalized in order to remove the differences in the growth of the varying vegetation. Based on the normalized NDVI and NBR, kernel density estimation (KDE) was used to create a universal measure of undisturbed vegetation, which described the uniform spectral frequency distribution of different undisturbed vegetation with a series of accumulated probabilities on a monthly basis. Whenever a new Landsat observation is collected, the vegetation anomalies are determined according to the universal measure in NRT. To demonstrate the potential of this framework, three study areas with different anomaly types (deforestation, fire event, and insect outbreak) in distinct ecozones (rainforest, coniferous forest, and deciduous broad-leaf forest) were used. The quantitative analyses showed generally high overall accuracies (>90% with the kappa >0.82). The user accuracy for the fire event and the producer accuracy for the earlier insect infestation were relatively lower. The accuracies may be affected by the complexity of the land surface, the quality of the Landsat image, and the accumulated probability threshold. Full article