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The turbine disc plays a crucial role in aerospace engine, significantly influencing both their fatigue life and overall reliability. Due to the substantial uncertainties present, devising a method for the probabilistic analysis of turbine disc fatigue life becomes crucial. This paper introduces a novel framework that combines adaptive Kriging Monte Carlo simulation (AK‐MCS) with a mean stress correction model to evaluate fatigue life distribution effectively. AK‐MCS, stands out as an algorithm that constructs a Kriging model, effectively reducing the need for an extensive finite element analysis. Furthermore, a mean stress correction model is proposed for the Masson‐Coffin equation tailored for fatigue life prediction of GH4133 disc material. This model has been empirically validated to be effective. The presented framework for probabilistic fatigue life analysis not only holds considerable engineering value but also offers innovative approaches for tackling analogous challenges in the field. [ABSTRACT FROM AUTHOR]

The load history exerts a considerable impact on the low cycle fatigue (LCF) life of turbine discs. Thus, oversimplifying the load history leads to substantial errors in fatigue life prediction. This study introduces a probabilistic fatigue life prediction method for turbine discs, accounting for the randomness inherent in LCF load history. The method involves quantifying the randomness of load history through numerical simulation and employing a surrogate model enhanced with learning functions to balance computational efficiency and accuracy. The probabilistic LCF life prediction of full‐scale turbine disc was conducted, demonstrating that the fatigue life scatter predicted by the proposed method more closely aligns with experimental data compared to the original approach. By refining the numerical simulation process, the proposed method better accounts for uncertainties in load history while maintaining computational efficiency, offering significant insights for the fatigue reliability design of turbine discs. [ABSTRACT FROM AUTHOR]

This study utilizes the rank correlation coefficient to examine the multi‐site failure correlation of turbine discs. Drawing from the stress‐strength interference model, reliability models both with and without factoring in the multi‐site failure correlation are constructed. Furthermore, the weakest link theory (WLT) within the context of the Weibull distribution function is invoked to develop a model for predicting the fatigue life of turbine discs, taking into account the quantity of critical sections. The variability in the low cycle fatigue (LCF) of turbine discs is scrutinized, leading to the formulation of a probabilistic fatigue life prediction method for these discs. When comparing theoretical values with experimental ones, it becomes evident that factoring in the multi‐site failure correlation significantly enhances the accuracy of turbine disc life predictions. [ABSTRACT FROM AUTHOR]

Dynamic fault tree (DFT) is a reliable method for modeling complex systems with dynamic characteristics. However, evaluating the reliability of such systems can be complex. The sequential binary decision diagram (SBDD) method simplifies this process by reducing computational complexity. This study investigates factors influencing SBDD size and proposes a new method, the complete priority ordering method, for ordering basic events in SBDDs. Results demonstrate the method's effectiveness in comparison to existing approaches. [ABSTRACT FROM AUTHOR]

This paper proposes an active learning Kriging (ALK) based reliability analysis method for a multi‐output structural system by using a multiple response Gaussian process (MRGP) model. Firstly, various failure modes, including their interactions, are involved in a multi‐output structural system. The MRGP model is used to construct the surrogate model directly because it can efficiently characterize the correlation between different failure modes. The particle swarm optimization (PSO) algorithm is integrated into the MRGP model to optimize the hyperparameter. Secondly, similar to ALK‐based reliability method, three improved functions for these common learning functions (e.g., U‐function, EFF‐function, H‐function) are proposed, which consider the distance requirement between the iteration sample point and training samples. Finally, the cross‐validation methodology is employed as the stopping criterion and several numerical examples are provided to illustrate the effectiveness. [ABSTRACT FROM AUTHOR]

The multi‐output structural system with implicit function widely exists in actual engineering, which refers that the multiple output responses of structural system can be obtained by one experiment or finite element simulation. Considering the correlation of multiple output responses and the small failure probability involved in multi‐output structural system, this article proposes a novel active learning Kriging (ALK) based reliability method for multi‐output structural system by combining multiple response Gaussian process (MRGP) and importance sampling (IS). First, due to the Kriging model can only construct the surrogate model under the single‐output variable, the MRGP model is introduced to substitute the Kriging model and thus the correlation in multiple output responses can be efficiently described by a correlation matrix in MRGP model. Second, for the case that the distance information of new iterated sample point is not considered by the commonly used learning functions (U‐function, EFF‐function and H‐function) in ALK, three improved learning functions are correspondingly proposed. Finally, aiming at the problem that the small failure probability leads to the increasing of candidate sample pool and further results in low computational efficiency, the IS method is combined with the MRGP model to efficiently accomplish the reliability analysis for multi‐output structural system. Several examples are also provided to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Degradation data and failure‐time data are two types of data commonly used in reliability analysis. Both types of data are collected from different sources for reliability analysis of complex products. For highly reliable products, however, it is often difficult to collect sufficient useful data for reliability analysis with high accuracy, which poses the challenge for small sample size problems, that is, single‐type data with few samples. In this paper, three novel Bayesian information fusion models are first proposed to characterize the inherent relationship between the failure‐time data and the degradation data, and further to integrate the heterogeneous data to obtain accurate reliability analysis results under small sample size. Then, a model selection method is developed to choose appropriate model from the Wiener process, gamma process, and IG process models. Finally, the reliability analysis is completed based on the parameter estimation of the Bayesian information fusion model with the aid of the MCMC method. An industrial example is presented to demonstrate the effectiveness of the proposed Bayesian information fusion method. [ABSTRACT FROM AUTHOR]

During the use of rolling bearings in wind turbines, aero engines, and other equipment, they often operate under variable operating and loading conditions. The practice has shown that the sequence of these loads and their interaction has a significant impact on the fatigue life of rolling bearings. In order to better understand this issue, a modified nonlinear fatigue damage accumulation model, which considers the influences of both load sequence and load interaction, is proposed in this paper and verified using the fatigue testing data for six materials. Then, the verified model was applied to evaluate the fatigue damage accumulation and fatigue life of a rolling bearing. The results have shown that, compared with the existing models, the proposed model can more accurately predict the damage accumulation and fatigue life of the rolling bearing under variable loading conditions. [ABSTRACT FROM AUTHOR]

Aero‐engine hot section components experience combined high and low cycle fatigue (CCF) loading under actual working conditions. This paper proposes a modified fatigue damage accumulation model to precisely predict lifetimes of aero‐engine materials according to the newly presented interaction factor, which is able to quantitatively map damage interactions introduced by high cycle fatigue (HCF) and low cycle fatigue (LCF) loads. With the model, the lifetimes of four typical engine materials are predicted and compared to their factual data from experiments. The validation of the model is illustrated by a comprehensive comparison of the results concluded by the proposed model and that of other classical methodologies, which indicates that the new model holds the best performance in lifetime predictions. Moreover, an actual engineering case, which is the lifetime prediction of third stage turbine blades of an aero‐engine, is completed to validate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Traditional reliability analysis is based on probability theory with precise distributions. However, determining the distribution of all variables precisely is impossible due to insufficient information. Therefore, random and interval variables may be encountered, and probabilistic reliability methods are hard to use. The existing interval variables make reliability analysis more difficult. In this article, an efficient and robust hybrid reliability analysis method is proposed for structures with both random and interval variables. Firstly, a single‐loop procedure is proposed by performing probabilistic analysis and interval analysis simultaneously in each most probable point search process. Then an improved conjugate sensitivity factor method based on hybrid conjugate gradient direction and adaptive finite step length is developed for probabilistic analysis. Meanwhile, the hybrid conjugate gradient direction together with active set is introduced into the projected gradient method for interval analysis. Finally, a comparison analysis with six numerical examples is provided to validate the performance of the proposed method. The results demonstrate that the proposed method is better than the existing methods in terms of efficiency and robustness for hybrid reliability analysis with random and interval variables. [ABSTRACT FROM AUTHOR]

Discrete‐time Bayesian network (DTBN) is a popular tool for the reliability analysis of dynamic systems, which, however, is insufficient in analyzing the reliability of multilevel system (MLS) with warm spare (WSP) gates. Additionally, conventional DTBNs are not able to consider the situation that dormant components and primary components may fail during the same time interval. To this end, this paper analyzes the dynamic reliability characteristics of dormant systems with WSP gates by utilizing DTBNs. Moreover, an algorithm of modeling the conditional probability table (CPT) for WSP gates together with a new schedule of constructing dynamic Bayesian networks is put forward. The validation of the proposed techniques is implemented by Monte Carlo simulation (MCS) and reliability analysis of an actual communication station system. [ABSTRACT FROM AUTHOR]

The Bayesian network (BN) is an efficient tool for probabilistic modeling and causal inference, and it has gained considerable attentions in the field of reliability assessment. The common cause failure (CCF) is simultaneous failure of multiple elements in a system under a common cause, and it is a common phenomenon in engineering systems with dependent elements. Several models and methods have been proposed for modeling and assessment of complex systems with CCF. In this paper, a new reliability assessment method is proposed for the systems suffering from CCF in a dynamic environment. The CCF among components is characterized by a BN, which allows for bidirectional reasoning. A proportional hazards model is applied to capture the dynamic working environment of components and then the reliability function of the system is obtained. The proposed method is validated through an illustrative example, and some comparative studies are also presented. [ABSTRACT FROM AUTHOR]

Due to its high efficiency and low power consumption, switched‐mode power supply (SMPS) represents the development trend of the stabilized voltage power supply. However, tolerance has become one of the key factors in the design of SMPS because of the process fluctuation of electronic components, unstable input parameters of the circuit system, influence of working conditions and environment, and the effect of aging. In order to improve the reliability of SMPS and reduce the manufacturing cost, this paper proposes a reliability analysis and optimization design method based on the tolerance and sensitivity analysis. Finally, this method is applied to the tolerance design for the positive switching power supply of the SMPS circuits, and the optimal tolerance design scheme is obtained. Furthermore, the reliability and probability density curves are evaluated. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the feasibility of blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) to evaluate visceral adipose tissue (VAT) oxygenation in Zucker diabetic fatty (ZDF) rats and its associations with systemic metaflammation.Methods: Five-week-old ZDF rats and Zucker lean (ZL) rats were fed a high-fat diet (HFD) for 18 weeks. A baseline BOLD-MRI scan of perirenal adipose tissue was performed after 8 weeks of HFD feeding, and then the rats were randomized to receive pioglitazone or a vehicle for the following 10 weeks. At sacrifice, BOLD-MRI scan, Hypoxyprobe-1 injection, and circulating T helper 17 (Th17), regulatory T (Treg) cells, and monocyte subtype flow cytometry analysis were performed.Results: HFD feeding led to a significant increase in VAT BOLD-MRI R2* signals (20.14 ± 0.23 per second vs. 21.53 ± 0.20 per second; P = 0.012), an indicator for decreased oxygenation. R2* signal was significantly correlated with VAT pimonidazole adduct-positive area, insulin resistance, Th17 and Treg cells, CD43 + and CD43+ + monocyte subtypes, and VAT macrophage infiltration. Pioglitazone treatment improved the insulin resistance and was associated with a delayed progression of VAT oxygenation.Conclusions: This work demonstrated the feasibility of BOLD-MRI for detecting the VAT oxygenation status in ZDF rats, and the BOLD-MRI signals were associated with insulin resistance and systemic metaflammation in ZDF rats during the development of obesity. [ABSTRACT FROM AUTHOR]

Micro RNAs have been shown to play a role in B-cell differentiation and activation. Here, we found miR-182 to be highly induced in activated B cells. However, mice lacking miR-182 have normal B-cell and T-cell development. Interestingly, mutant mice exhibited a defective antibody response at early time-points in the immunization regimen when challenged with a T-cell-dependent antigen. Germinal centres were formed but the generation of extrafollicular plasma cells was defective in the spleens of immunized miR-182-deficient mice. Mutant mice were also not able to respond to a T-cell-independent type 2 antigen, which typically elicited an extrafollicular B-cell response. Taken together, the data indicated that miR-182 plays a critical role in driving extrafollicular B-cell antibody responses. [ABSTRACT FROM AUTHOR]

Background Reconstruction of the internal carotid artery (ICA) is an operative challenge for lesions involving the lateral skull base because of excessive blood loss, intraoperative cranial nerve injury, and difficulties in cerebral protection. Methods Between January 2010 and October 2014, 9 patients with vascular lesions at the lateral skull base were treated with a 'pre-reconstruction' technique, which means reconstruction of the ICA in advance of excising the lesions. Results All operations were technically successful with no mortality or strokes. The mean blood loss was 921 ± 210 mL. The mean total clamping time was 18 ± 5 minutes. Among the 5 patients without invasion of specific cranial nerves, no long-term sequelae occurred during the follow-up period ranging from 11 to 54 months. Conclusion With less blood loss, slighter cranial nerve injuries, and shorter clamping time, the 'pre-reconstruction' technique was safe and effective for the treatment of vascular lesions at the lateral skull base. © 2016 Wiley Periodicals, Inc. Head Neck 38: E1562-E1567, 2016 [ABSTRACT FROM AUTHOR]

Based on the characteristics of polycations of chitosan and glucoamylase, which are oppositely charged, they were successfully alternatingly deposited onto the surface of aldehyde-modified Fe3O4 nanoparticles by using a layer-by-layer method to form magnetic carriers to construct multilayer films (designated as Fe3O4@(CS/GA) n). The (CS/GA) n film systems were endowed with the pH-dependent properties of chitosan as well as the of glucoamylase. The changes in weight loss and surface chemistry, morphology, and magnetic sensitivity were monitored and verified by UV/Vis spectroscopy, zeta potential, TEM, and a vibrating sample magnetometer. Subsequently, the influence of the number of bilayers, storage stability, pH, temperature, and reusability of Fe3O4@(CS/GA)5 biocatalysts on were investigated. The results from characterization and determination remarkably indicate that Fe3O4@(CS/GA)5 presents excellent , storage stability, pH stability, and reusability in comparison with free enzyme. Fe3O4@(CS/GA)5 retained >60 % of its initial activity at 65 °C over 6 h; the optimum temperature and pH also increased to the ranges of 45-65 °C and 2.5-3.5, respectively, and only 27 % activity was lost after 10 cycles. This new strategy simplifies the reaction protocol and improves encapsulation efficiency and for new potential applications in biotechnology. [ABSTRACT FROM AUTHOR]

In this study, the polysulfone (PSF) capsules containing graphite nanosheets (GNS) were successfully prepared by a phase inversion precipitation method. Scanning electron microscopy and thermogravimetry were employed in the characterization of the as-prepared PSF/GNS composites capsules. Meanwhile, the adsorption properties of the composites capsules for the phenol in aqueous solution were investigated by batch methods. The results showed that the phenol adsorption uptake would be increased with the enhancement of initial concentration and adsorption time, and the adsorption of phenol should be more favorable at pH value less than 9. The composites capsules would be a kind of promising alternative adsorbent with high adsorption capacity for the phenol from aqueous solutions at a low concentration. The adsorption kinetics of the capsules for phenol accorded with pseudo-second-order model, and the best fits of adsorption isotherms followed the Freundlich equation. POLYM. COMPOS., 2013. © 2013 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]

Macromolecule antimicrobials have been explored in foundational research and practical application due to their potential merit for reducing the residual toxicity, increasing their efficiency, selectivity, and prolonging the lifetime of the antimicrobial material. In this work, the quaternized poly(styrene)- b-poly(DMAEMA) diblock polymers are synthesized by reversible addition-fragmentation chain transfer polymerization (RAFT). The minimum inhibitory concentration (MIC) evaluation and optical density (OD) method demonstrated that the amphiphilic antibacterial biomaterials have exceptional antibacterial properties. The amphiphilic polycation has an admirable antibacterial property, and these quaternized diblocks are potent biocides and nonhemolytic. The relationship between the structure and activity is discussed with respect to molecular weight of the diblocks and bacteria structural dependence. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The article discusses a study which examined the characteristics and preparation of new polymides from condensed 2-amino-5-(4-aminophenyl)-thiazole (AAPT). It describes the process of one-step polyimidation in the polycondensation of AAPT with aromatic dianhydrides, which were found to obtain strong and flexible polymide films. It was found that the polymide films exhibited good thermal and thermo-oxidative stability, and better performance for tensile strength and elongation at breakage.

The asymmetric unit of the title compound, {[MgNa₂(C₁₀H₄O₈)₂(H₂O)₈]·2H₂O}(n), contains one octa-hedrally coordin-ated Mg(II) atom (site symmetry 2/m), one octahedrally coordinated Na(I) atom (site symmetry 2) and one half of the dihydrogen benzene-1,2,4,5-tetra-carboxyl-ate (btec) ligand, the second half of the ligand being generated by a twofold rotation axis. The basic framework of the title compound features infinite (-Na-Na-Mg-)(n) chains along [10-1] with the metal cations bridged by the coordinating water molecules. The chains are isolated from each other by μ₄-bridging btec ligands, which form inter-molecular O-H⋯O hydrogen bonds to uncoordinated water mol-ecules and the coordinated water mol-ecules of a neighbouring chain. In each btec ligand, there are also intramolecular O-H⋯O hydrogen bonds.