Search Results (176)

As the global energy system accelerates its transition toward a low-carbon economy, renewable energy sources (RESs), such as wind and photovoltaic power, are rapidly replacing traditional fossil fuels. These RESs are becoming a critical element of deeply decarbonized power systems (DDPSs). However, the inherent non-stationarity, multi-scale volatility, and uncontrollability of RES output significantly increase the risk of source–load imbalance, posing serious challenges to the reliability and economic efficiency of power systems. Scenario generation technology has emerged as a critical tool to quantify uncertainty and support dispatch optimization. Nevertheless, conventional scenario generation methods often fail to produce highly credible wind and solar output scenarios. To address this gap, this paper proposes a novel renewable energy scenario generation method based on a multi-resolution diffusion model. To accurately capture fluctuation characteristics across multiple time scales, we introduce a diffusion model in conjunction with a multi-scale time series decomposition approach, forming a multi-stage diffusion modeling framework capable of representing both long-term trends and short-term fluctuations in RES output. A cascaded conditional diffusion modeling framework is designed, leveraging historical trend information as a conditioning input to enhance the physical consistency of generated scenarios. Furthermore, a forecast-guided fusion strategy is proposed to jointly model long-term and short-term dynamics, thereby improving the generalization capability of long-term scenario generation. Simulation results demonstrate that MDDPM achieves a Wasserstein Distance (WD) of 0.0156 in the wind power scenario, outperforming DDPM (WD = 0.0185) and MC (WD = 0.0305). Additionally, MDDPM improves the Global Coverage Rate (GCR) by 15% compared to MC and other baselines. Full article

Galactic cosmic rays (GCRs), composed of protons and atomic nuclei, are accelerated in sources such as supernova remnants and pulsar wind nebulae, reaching energies up to the PeV range. As they propagate through the interstellar medium, their interactions with dense regions like molecular clouds produce secondary particles, including gamma-rays and neutrinos. In this study, we use the Geant4 Monte Carlo toolkit to simulate secondary particle production from GCR interactions within the Perseus molecular cloud, a nearby star-forming region. Our model incorporates realistic cloud composition, a wide range of incidence angles, and both hadronic and electromagnetic processes across a broad energy spectrum. The results highlight molecular clouds as significant sites of multi-messenger emissions and contribute to understanding the propagation of GCRs and the origin of diffuse gamma-ray and neutrino backgrounds in the Galaxy. Full article

Poly-ether-ether-ketone (PEEK) is widely used in dynamic sealing applications due to its excellent properties. However, its tribological performance as a sealing material still has limitations, as its relatively high friction coefficient may lead to increased wear of sealing components, affecting sealing effectiveness and service life. To optimize its lubrication performance, this study employs surface modification techniques to synthesize a thin polyimide (PI) film on the surface of PEEK. When paired with bearing steel, this modification reduces the friction coefficient and enhances the anti-wear performance of sealing components. The tribological properties of a friction pair composed of GCr15 steel and PI-modified PEEK were systematically investigated using a nematic liquid crystal as the lubricant. The friction system was analyzed through various tests. The experimental results show that, under identical conditions, the friction coefficient of the PI-modified PEEK system decreased by 83.3% compared to pure PEEK. Under loads of 5 N and 25 N and rotational speeds ranging from 50 rpm to 400 rpm, the system exhibited induced alignment superlubricity. At 50 rpm, superlubricity was maintained when the load was below 105 N, while at 200 rpm, this occurred when the load was below 125 N. Excessively high rotational speeds (above 300 rpm) might affect system stability. The friction coefficient initially decreased and then increased with increasing load. The friction system demonstrated induced alignment superlubricity under the tested conditions, suggesting the potential application of PI-modified PEEK in friction components. Full article

GCr15 bearing steel is widely used in the textile, aerospace, and other industries due to its excellent mechanical properties. However, traditional electroless Ni-B coatings can no longer meet the growing demand for a long service life under high-speed and heavy load conditions. This study focused on depositing Ni-B-Mo alloy coatings on GCr15 steel. An orthogonal experimental design was adopted to investigate the effects of the NiCl₂ and Na₂MoO₄ concentrations and deposition time on the deposition rate and surface hardness of the coatings. The results show that the Na₂MoO₄ concentration has the most significant impact on the deposition rate. An optimal concentration of 5.6 g/L improved both the deposition rate and hardness (up to 881 HV), while excessive Na₂MoO₄ (>15.6 g/L) reduced the coating adhesion and wear resistance. A deposition time of 1–2 h ensured a high deposition rate, but after 3 h, bath component depletion lowered the rate and caused coating defects. The NiCl₂ concentration (20–30 g/L) had a relatively minor influence on the deposition rate but stabilized the Ni²⁺ ion supply, enhancing the coating compactness. The optimized parameters were 5.6 g/L Na₂MoO₄, 25 g/L NiCl₂, and 2 h of deposition. The coating exhibited high hardness, strong adhesion, and excellent wear resistance. After heat treatment at 400 °C for 1 h, the coating transitioned from being amorphous to nanocrystalline, forming Ni₂B, Ni₃B, and Mo₂C phases, increasing the hardness from 737.49 HV to 916.19 HV and reducing the friction coefficient to 0.38. Full article

Surface roughness plays a crucial role in determining surface quality, influencing factors such as vibration, noise, assembly precision, lubrication, and wear resistance in bearings. This research examines how surface roughness (Sa) affects the friction and wear characteristics of GCr15 steel under conditions with adequate oil lubrication while varying the applied load. The findings indicate that with an increase in Sa, the friction coefficient of GCr15 steel also increases. As the load rises from 15 N to 35 N, the friction coefficient remains relatively constant. However, higher loads lead to more severe wear of the microprotrusions on the surface of GCr15 steel. The wear area first decreases and then increases as Sa increases. The minimum wear area occurs when Sa is 0.5 μm. Additionally, a back propagation neural network (BPNN) model has been developed to predict the wear performance of GCr15 steel. Validation experiments show that the average prediction error for the BPNN model is 10.64%. Full article

This paper conducts wear tests of rotating shafts and bearings, and collects the wear amount, surface morphology, and friction force signals to study its tribological behaviors using the fractal and chaotic analysis. The rotation shaft surface fractal dimension were calculated to characterize the self-similarity and smoothness, the signals’ phase trajectories were constructed, and its correlation dimension and phase-point saturation were calculated to reveal the dynamic evolution of the system. The results show that the surface fractal dimension increases from low to high. The phase trajectory fluctuates and then maintains in a finite space, and the correlation dimension increases and stabilizes near the larger value while the phase-point saturation has the opposite evolution. The changes in surface fractal dimension, phase trajectories, correlation dimension, and phase-point saturation are similar to the wear rate, exhibiting a transition from instability to stability, which is more objective and sensitive than traditional representation methods. According to the fractal and chaotic characterization results of the worn surface and friction force signal, the material of CrNiMoN has better friction and wear properties than GCr15. The results reveal the tribological behaviors and wear mechanisms of the rotating shaft and provide guidance for material selection and designing, along with a basis for characterizing the wear status of the rotating shaft of wave glider wing. Full article

The influence of static pressure during focused ultrasonic rolling extrusion on the corrosion resistance of GCr15 bearing steel was investigated. Quenched GCr15 bearing steel served as the subject of this study, wherein ultrasonic rolling extrusion was performed using a CNC lathe. Static pressure levels of 200 N, 400 N, and 500 N were applied during the experiments. Following the preparation of samples, which included grinding and cleaning, electrochemical assessments were conducted utilizing an electrochemical workstation. These assessments encompassed measurements of open-circuit potential, Tafel polarization, and electrochemical impedance spectroscopy, employing a three-electrode configuration. Additionally, the microstructural characteristics of the samples were examined using scanning electron microscopy, optical microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The findings indicate that an increase in static pressure results in a forward shift of the open-circuit potential and a reduction in corrosion susceptibility. Tafel analysis revealed an increase in linear polarization resistance, a decrease in corrosion current, and a positive shift in corrosion potential. The impedance spectroscopy results demonstrated that both the modulus of low-frequency impedance and charge transfer resistance increased with elevated static pressure. Microstructural analysis indicated that higher static pressure contributes to a smoother and more compact surface, with a reduction in defects. The primary corrosion products identified were iron oxides and hydroxides. In conclusion, the corrosion resistance of GCr15 bearing steel subjected to ultrasonic rolling extrusion is enhanced as static pressure increases. Full article

Botryosphaeria dieback, a significant grapevine trunk disease (GTD) caused by various pathogens, represents a serious threat to viticulture. Biocontrol emerges as a promising sustainable alternative to chemical control, aligning toward environmentally friendly viticultural practices. This study evaluated the in vitro, in vivo, and in situ biocontrol potential of Chilean native bacteria isolated from wild flora and endophytic communities of grapevine against Neofusicoccum parvum. In vitro biocontrol assays screened 15 bacterial strains at 10, 22, and 30 °C, identifying four Pseudomonas strains with >30% mycelial growth inhibition. In diffusible agar and double plate assays, plant growth-promoting bacteria AMCR2b and GcR15a, which were isolated from native flora, achieved significant inhibition of N. parvum growth, with reductions of up to ~50% (diffusible agar) and up to ~46% (double plate). In vivo experiments on grapevine cuttings revealed that strains AMCR2b and GcR15a inhibited mycelial growth (17–90%); younger grapevines (1–5 years) were more susceptible to N. parvum. In situ trials using Vitis vinifera L. cv. Cabernet Sauvignon and Sauvignon Blanc demonstrated higher fungal susceptibility in Sauvignon Blanc. These results highlight the potential of Pseudomonas sp. AMCR2b and GcR15a to be effective biocontrol agents against GTDs at a wide range of temperatures, contributing to sustainable viticulture. Full article

Agrivoltaics have emerged as a promising solution to mitigate climate change effects as well as competition for land use between food and energy production. While previous studies have demonstrated the potential of agrivoltaic systems to enhance land productivity, limited research has focused on their impact on specific crops, particularly in organic processing tomatoes. In the present study, a two-year experiment was conducted in northwest Italy to assess the suitability of the agrivoltaic system on processing tomato yield and quality in the organic farming system. In the first growing season, the transplanting of tomato was carried out under the following light conditions: internal control (A1)—inside the tracker rows obtained by removing PV panels; extended agrivoltaic panels—shaded condition with an increased ground coverage ratio (GCR) of 41% (A2); and external control (FL)—full-light conditions outside the tracker rows. The second year of experimentation involved the transplanting of tomato under the following light conditions: internal control (B1); dynamic shading conditions that consist of solar panels in a vertical position until full fruit set (B2); standard agrivoltaic trackers (GCR = 13%, shaded conditions) (B3); and external control (FL). In 2023, the results showed that A2 achieved a total yield of only 24.5% lower than FL, with a marketable yield reduction of just 6.5%, indicating its potential to maintain productivity under shaded conditions. In 2024, B2 management increased marketable yield by 80.6% compared to FL, although it also led to a 46.2% increase in fruit affected by blossom end rot. Moreover, B2 improved nitrogen agronomic efficiency and fruit water productivity by 6.4% while also reducing the incidence of rotten fruit. Our findings highlight that moderate coverage (A2 and B2) can sustain high marketable yields and improve nitrogen use efficiency in different growing seasons. Full article

The main focus of this work is the successful deposition of hard and wear-resistant TiAlCN coating on the surface of GCr15 bearing steel by means of magnetron sputtering technology. The phase composition of the chromium nitride transition layer was monitored by precisely controlling the nitrogen (N₂) flow rate to strengthen the bonding between the TiAlCN coating and the GCr15 bearing steel surface. It was found that coating performance reached the optimal state at a N₂ flow rate of 40 sccm, yielding a hardness of 23.3 GPa, a friction coefficient of only 0.27, and a wear rate of 0.19 × 10⁻⁸ mm³/N·m. Full article

Background: Colorectal cancer liver metastasis (CRLM) is a significant contributor to cancer-related illness and death. Neoadjuvant chemotherapy (NAC) is an essential treatment approach; however, optimal patient selection remains a challenge. This study aimed to develop a machine learning-based predictive model using hematological biomarkers to assess the efficacy of NAC in patients with CRLM. Methods: We retrospectively analyzed the clinical data of 214 CRLM patients treated with the XELOX regimen. Blood characteristics before and after NAC, as well as the ratios of these biomarkers, were integrated into the machine learning models. Logistic regression, decision trees (DTs), random forest (RF), support vector machine (SVM), and AdaBoost were used for predictive modeling. The performance of the models was evaluated using the AUROC, F1-score, and external validation. Results: The DT (AUROC: 0.915, F1-score: 0.621) and RF (AUROC: 0.999, F1-score: 0.857) models demonstrated the best predictive performance in the training cohort. The model incorporating the ratio of post-treatment to pre-treatment gamma-glutamyl transferase (rGGT) and carcinoembryonic antigen (rCEA) formed the GCR index, which achieved an AUROC of 0.853 in the external validation. The GCR index showed strong clinical relevance, predicting better chemotherapy responses in patients with lower rCEA and higher rGGT levels. Conclusions: The GCR index serves as a predictive biomarker for the efficacy of NAC in CRLM, providing a valuable clinical reference for the prognostic assessment of these patients. Full article

In our previous work, we investigated the spectra and anisotropy of galactic cosmic rays (GCRs) under the assumption of an axisymmetric distribution of galactic sources. Currently, much observational evidence indicates that the Milky Way is a typical spiral galaxy. In this work, we further utilize an anisotropic propagation model under the framework of spiral distribution sources to study spectra and anisotropy. During the calculation process, we adopt the spatial-dependent propagation (SDP) model, while incorporating the contribution from the nearby Geminga source and the anisotropic diffusion of cosmic rays (CRs) induced by the local regular magnetic field (LRMF). By comparing the results of background sources with spiral and axisymmetric distribution models, it is found that both of them can well reproduce the CR spectra and anisotropy. However, there exist differences in their propagation parameters. The diffusion coefficient with spiral distribution is larger than that with axisymmetric distribution, and its spectral indices are slightly harder. To investigate the effects of a nearby Geminga source and LRMF on anisotropy, two-dimensional (2D) anisotropy sky maps under various contributing factors are compared. Below 100 TeV, the anisotropy is predominantly influenced by both the nearby Geminga source and the LRMF, causing the phase to align with the direction of the LRMF. Above 100 TeV, the background sources become dominant, resulting in the phase pointing towards the Galactic Center (GC). Future high-precision measurements of CR anisotropy and spectra, such as the LHAASO experiment, will be crucial in evaluating the validity of our proposed model. Full article

Joint bearings are widely used in modern industry in order to improve the mechanical properties of the outer surface of its inner ring. A laser quenching experiment was carried out in this paper. First of all, an experimental investigation was conducted on GCr15 ball-bearing material utilizing laser quenching, focusing on the effects of laser irradiation angles ranging from 0° to 10° and laser power levels between 600 W and 1100 W on the degree of hardening and microstructural alterations of the bearing material. Additionally, a reliable finite element analysis model was developed to assess the temperature field throughout the process. The findings indicate that an inclined laser enhances the stability of the hardened layer. Specifically, the hardening effect is minimal when the laser power is below 700 W, and optimal hardening is observed at power levels between 800 W and 900 W. During the laser quenching process when the temperature of the bearing material surpasses Ac1, the cooling rate can exceed 1700 °C/s. In regions where the peak temperature exceeds Ac1, the microstructure will undergo refinement, resulting in a reduction in the size of the martensite and a significant decrease in the number of carbides. In addition, the hardness value of these regions can be increased by 6 to 8 HRC, and the thickness of the quenching layer may exceed 0.3 mm. In the temperature range between Ac1 and Ms, the bearing material undergoes tempering, resulting in lower hardness compared to the base material, along with larger martensite and carbide particles. Furthermore, when using the overlap technique during the laser quenching, there will be a tempering zone both inside and on the surface of the bearing; meanwhile, the heat zones generated by different passes of the laser may have partly interacted, and the hardened zone generated by the previous pass may undergo tempering again. Full article

The microstructure of metallic materials plays a crucial role in determining their performance. In order to accurately predict the dynamic recrystallization (DRX) behavior and microstructural evolution during the hot deformation process of GCr15 bearing steel, a microstructural evolution model for the DRX process of GCr15 steel was established by combining the level set (LS) method with the Yoshie–Laasraoui–Jonas dislocation dynamics model. Firstly, hot compression tests were conducted on GCr15 steel using the Gleeble-1500D thermal simulator, and the hardening coefficient k₁ and dynamic recovery coefficient k₂ of the Yoshie–Laasraoui–Jonas model were derived from the experimental flow stress data. The effects of temperature, strain, and strain rate on DRX behavior and grain size during the hot working process of GCr15 steel were investigated. Through secondary development of the software, the established microstructural evolution model was integrated into the DIGIMU^® software. Metallographic images were imported in situ to reconstruct its initial microstructure, enabling GCr15 steel DRX microstructure finite element simulation of the hot compression process. The predicted mean grain size and flow stress demonstrated a strong correlation and excellent agreement with the experimental results. The results demonstrate that the established DRX model effectively predicts the evolution of the DRX fraction and average grain size during the hot forging process and reliably forecasts DRX behavior. Full article

The numerical simulation of metal heat treatment is of great significance for the development of new materials or processes. The complex coupling relationship in metal heat treatment poses a huge challenge to the overall solution. A finite volume method based on the Crack–Nicolson (C-N) scheme with parallel algorithms is proposed for solving the coupling of metal thermal phase transition. Taking the quenching simulation problem of bearing rings as an example, the calculation accuracy and speed of this method were evaluated by comparing the results of the temperature field and phase transformation field obtained from the literature. In addition, grid independence analysis was conducted to demonstrate the rationality of the established model. The finite volume method using a hexahedral mesh C-N format improves the accuracy of calculations. Optimizing the equation form and using parallel algorithms have improved computational speed. In the trial example, in the 850 °C quenching simulation of GCr15, the outer ring of the bearing is composed of 89.1% martensite and 10.9% residual austenite. The results compare with test verification, which shows that the model performs well in the numerical simulation of metal heat treatment. Full article