Reliability analysis methods are used to evaluate the safety of reinforced concrete structures by evaluating the limit state function 𝑔(𝑋𝑖). For implicit limit state function and nonlinear analysis , an advanced reliability analysis methods are needed. Monte Carlo simulation (MCS) can be used in this case however, as the number of input variables increases, the time required for MCS also increases, making it a time consuming method especially for complex problems with implicit performance functions. In such cases, MCS-based FORM (First Order Reliability Method) and Artificial Neural Network-based FORM (ANN FORM) have been proposed as alternatives. However, it is important to note that both MCS-FORM and ANN-FORM can also be time-consuming methods in their own right. MCS-FORM involves running multiple MCS, and the time required increases with problem complexity and desired precision. ANN-FORM, on the other hand, can be faster for repetitive reliability assessments, but the training phase can be computationally expensive, and accuracy depends on training data quality and quantity. To address this computational challenge and enhance the efficiency of reliability analysis, a novel method is proposed in this paper. This method leverages the capabilities of ABAQUS, in combination with MATLAB. The key objective of this proposed approach is to automate and streamline the repetitive tasks involved in reliability analysis, thereby significantly reducing the computational time required for such analyses. The method is based on the development of a custom ABAQUS Python script file, which interfaces with MATLAB. The script serves as a bridge between the finite element analysis capabilities of ABAQUS and the data processing and analysis capabilities of MATLAB. An illustrative example was considered to demonstrate the application of the proposed method. In this example, a deteriorated simply supported concrete beam with an implicit performance function was analysed. The objective was to assess the reliability of the beam under the given conditions. To perform this reliability analysis, the two methods were employed: MCS-FORM and ANN-FORM. Both of these methods were implemented in conjunction with the newly developed approach that integrates ABAQUS and MATLAB. The results of this analysis were quite promising. Both MCS-FORM and ANN-FORM successfully estimated the reliability of the concrete beam, and they exhibited a high level of agreement in their assessments. This presented method demonstrates its suitability for the application of reliability analysis in scenarios such as the one presented. Its efficiency in automating repetitive tasks not only simplifies the analysis process but also facilitates the generation of multiple simulations. By doing so, it significantly minimizes the time and computational resources required for reliability assessments.
In this paper the experimentally obtained conditions for the fusion splicing with photonic crystal fibers (PCF) having large mode areas were reported. The physical mechanism of the splice loss and the microhole collapse property of photonic crystal fiber (PCF) were studied. By controlling the arc-power and the arc-time of a conventional electric arc fusion splicer (FSM-60S), the minimum loss of splicing for fusion two conventional single mode fibers (SMF-28) was (0.00dB), which has similar mode field diameter. For splicing PCF (LMA-10) with a conventional single mode fiber (SMF-28), the loss was increased due to the mode field mismatch.
Realizing the full potential of wireless sensor networks (WSNs) highlights many design issues, particularly the trade-offs concerning multiple conflicting improvements such as maximizing the route overlapping for efficient data aggregation and minimizing the total link cost. While the issues of data aggregation routing protocols and link cost function in a WSNs have been comprehensively considered in the literature, a trade-off improvement between these two has not yet been addressed. In this paper, a comprehensive weight for trade-off between different objectives has been employed, the so-called weighted data aggregation routing strategy (WDARS) which aims to maximize the overlap routes for efficient data aggregation and link cost
... Show MoreBackground: Understanding the challenges facing nurses toward providing care to patients with cerebrovascular accidents is the initial step in developing strategies to address these challenges, thereby ensuring high-quality care. Aim: The study aimed to assess the challenges experienced by nurses in delivering care to patients with CVAs in neurological wards. Results: Of the 80 questionnaire participants in the qualitative part, (MS = 0.66) reported a "moderate" rating as an overall assessment. These challenges are divided into workload (MS = 0.53) at a moderate rate, the psychological burden (MS = 0.85) at a high rate, the supporting materials (MS = 0.85) at a high rate, the sense of responsibility (MS = 0.77) at a high rate, and the role
... Show MoreIn addition to the primary treatment, biological treatment is used to reduce inorganic and organic components in the wastewater. The separation of biomass from treated wastewater is usually important to meet the effluent disposal requirements, so the MBBR system has been one of the most important modern technologies that use plastic tankers to transport biomass with wastewater, which works in pure biofilm, at low concentrations of suspended solids. However, biological treatment has been developed using the active sludge mixing process with MBBR. Turbo4bio was established as a sustainable and cost-effective solution for wastewater treatment plants in the early 1990s and ran on minimal sludge, and is easy to maintain. This
... Show MoreIt is shown that pure and 3% boron doped a-Si0.1Ge0.9:H and a-Si0.1Ge0.9:N thin films
could be prepared by flash evaporation processes. The hydrogenation and nitrogenation
are very successful in situ after depositing the films. The FT-IR analysis gave all the
known absorbing bonds of hydrogen and nitrogen with Si and Ge.
Our data showed a considerable effect of annealing temperature on the structural and
optical properties of the prepared films. The optical energy gap (Eopt.) of a-Si0.1Ge0.9
samples showed to have significant increase with annealing temperature (Ta) also the
refractive index and the real part of dielectric constant increases with Ta, however the
extinction coefficient and imaginary part of dielect
Plasma physics and digital image processing technique (DIPT) were utilized in this research to show the effect of the cold plasma (plasma needle) on blood cells. The second order statistical features were used to study this effect. Different samples were used to reach the aim of this paper; the patients have leukemia and their leukocytes number was abnormal. By studying the results of statistical features (mean, variance, energy and entropy), it is concluded that the blood cells of the sample showed a good response to the cold plasma.
The analysis of the classic principal components are sensitive to the outliers where they are calculated from the characteristic values and characteristic vectors of correlation matrix or variance Non-Robust, which yields an incorrect results in the case of these data contains the outliers values. In order to treat this problem, we resort to use the robust methods where there are many robust methods Will be touched to some of them.
The robust measurement estimators include the measurement of direct robust estimators for characteristic values by using characteristic vectors without relying on robust estimators for the variance and covariance matrices. Also the analysis of the princ
... Show MoreInvestigation of the adsorption of Chromium (VI) on Fe3O4 is carried out using batch scale experiments according to statistical design using a software program minitab17 (Box-Behnken design). Experiments were carried out as per Box-Behnken design with four input parameters such as pH (2-8), initial concentration (50–150mg/L), adsorbent dosage (0.05–0.3 g) and time of adsorption (10–60min). The better conditions were showed at pH: 2; contact time: 60 min; chromium concentration: 50 mg/L and magnetite dosage: 0.3 g for maximum Chromium (VI) removal of (98.95%) with an error of 1.08%. The three models (Freundlich, Langmuir, and Temkin) were fitted to experimental data, Langmuir isotherm has bette
... Show MoreSoil that has been contaminated by heavy metals is a serious environmental problem. A different approach for forecasting a variety of soil physical parameters is reflected spectroscopy is a low-cost, quick, and repeatable analytical method. The objectives of this paper are to predict heavy metal (Ti, Cr, Sr, Fe, Zn, Cu and Pb) soil contamination in central and southern Iraq using spectroscopy data. An XRF was used to quantify the levels of heavy metals in a total of 53 soil samples from Baghdad and ThiQar, and a spectrogram was used to examine how well spectral data might predict the presence of heavy metals metals. The partial least squares regression PLSR models performed well in pr
As the process of estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .
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