Reliability Analysis Tool Research Articles

Fault Tree Analysis With Interval Uncertainty: A Case Study of the Aircraft Flap Mechanism

This article proposes an uncertainty analysis method for evaluating the reliability of a system and calculating the relative importance of the system inputs when the probabilities of basic events are characterized by intervals. The reliability requirement or the safety criterion is first considered in the system reliability assessment. A nonprobabilistic reliability index, called R-index, is defined to evaluate the reliability of the system. Two importance measure indices, called location effect and size effect, are introduced for estimating the influence of the probability uncertainties of basic events on the R-index, thus identifying influential and noninfluential basic events and comparing their relative importance. Then, the proposed method is applied to an illustrative fault tree example and the fault tree analysis of unilateral asymmetric movement of an aircraft flap mechanism, thereby explaining the significance of this method. The results show that the proposed method provides a viable tool for system reliability and importance measure analysis when probability intervals are involved.

Uncertainty Quantified Parametrically Homogenized Constitutive Models for Microstructure-Integrated Structural Simulations

This paper investigates the role of material microstructures in structural analysis and establishes the need for microstructure-integrated constitutive models in predicting structural response. A focus is on microstructure and temperature dependency of stresses and plastic strains in a structural panel under realistic loading conditions. Structural analysis is conducted using the recently developed uncertainty-quantified parametrically homogenized constitutive model (UQ-PHCM) for near-alpha Titanium alloys like Ti6242S. PHCMs exhibit explicit microstructural dependency and are developed from homogenization of crystal plasticity finite element simulation results with machine learning. Uncertainties due to model reduction, data sparsity and microstructural variability are accounted for in the model. Structural response with the UQ-PHCMs is compared to those predicted by isotropic elasticity and $${J}_2$$ plasticity models without explicit microstructure information. Parametric studies illustrate how different uncertainties in the UQ-PHCM framework propagate to the structural response variables. The results also show the relative contribution of different microstructural features to the propagated uncertainty in structural response variables. The studies establish the UQ-PHCM as an effective tool for reliable structural analysis with consequences in material design.

Versatile live-cell activity analysis platform for characterization of neuronal dynamics at single-cell and network level

Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Current labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended time scales. We report on a dual-mode high-density microelectrode array, which can simultaneously record in (i) full-frame mode with 19,584 recording sites and (ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we develop reliable analysis tools, which drastically increase the throughput to infer axonal morphology and conduction speed.

Electroencephalographic Source Reconstruction by the Finite-Element Approximation of the Elliptic Cauchy Problem.

This paper develops a novel approach for fast and reliable reconstruction of EEG sources in MRI-based head models. The inverse EEG problem is reduced to the Cauchy problem for an elliptic partial-derivative equation. The problem is transformed into a regularized minimax problem, which is directly approximated in a finite-element space. The resulting numerical method is efficient and easy to program. It eliminates the need to solve forward problems, which can be a tedious task. The method applies to complex anatomical head models, possibly containing holes in surfaces, anisotropic conductivity, and conductivity variations inside each tissue. The method has been verified on a spherical shell model and an MRI-based head. Numerical experiments indicate high accuracy of localization of brain activations (both cortical potential and current) and rapid execution time. This study demonstrates that the proposed approach is feasible for EEG source analysis and can serve as a rapid and reliable tool for EEG source analysis. The significance of this study is that it develops a fast, accurate, and simple numerical method of EEG source analysis, applicable to almost arbitrary complex head models.

Rapid Microbiological Assessment in Raw Milk: Validation of a Rapid Alternative Method for the Assessment of Microbiological Quality in Raw Milk.

The consumption of dairy products and the dairy industry are one of the main global agri-food sectors for its size, economic importance, and level of technology. Microbiological quality of pasteurized milk or other milk products is dependent on microbiological quality of raw milk. A variety of microbiological count methods is available for monitoring the hygienic quality of raw milk. Among them, the pour plate method is the official essay for counting the number of colony-forming units in milk samples according to International Organization for Standardization (ISO) No. 4833-1:2013. The aim of the present study is the validation of the Micro Biological Survey (MBS) method, against the reference plate-count method, for the assessment of the microbiological quality of raw milk. This comparative study, performed in collaboration with the Istituto Zooprofilattico Sperimentale del Lazio e della Toscana M. Aleandri (IZSLT), demonstrates the accuracy of this alternative method for the determination of total viable bacterial count in cow’s raw milk. The results obtained with the MBS method highlight its potential as a valid tool for reliable microbiological analysis in dairy industries.

Morphogo: An Automatic Bone Marrow Cell Classification System on Digital Images Analyzed by Artificial Intelligence

Introduction: The nucleated-cell differential count on the bone marrow aspirate smears is required for the clinical diagnosis of hematological malignancy. Manual bone marrow differential count is time consuming and lacks consistency. In this study, a novel artificial intelligence (AI)-based system was developed to perform cell automatic classification of bone marrow cells and determine its potential clinical applications. Materials and Methods: Bone marrow aspirate smears were collected from the Xinqiao Hospital of Army Medical University. First, an automated analysis system (Morphogo) scanned and generated whole digital images of bone marrow smears. Then, the nucleated marrow cells in the selected areas of the smears at a magnification of ×1,000 were analyzed by the software utilizing an AI-based platform. The cell classification results were further reviewed and confirmed independently by 2 experienced pathologists. The automatic cell classification performance of the system was evaluated using 3 categories: accuracy, sensitivity, and specificity. Correlation coefficients and linear regression equations between automatic cell classification by the AI-based system and concurrent manual differential count were calculated. Results: In 230 cases, the classification accuracy was above 85.7% for hematopoietic lineage cells. Averages of sensitivity and specificity of the system were found to be 69.4 and 97.2%, respectively. The differential cell percentage of the automated count based on 200–500 cell counts was correlated with differential cell percentage provided by the pathologists for granulocytes, erythrocytes, and lymphocytes (r ≥ 0.762, p < 0.001). Discussion/Conclusion: This pilot study confirmed that the Morphogo system is a reliable tool for automatic bone marrow cell differential count analysis and has potential for clinical applications. Current ongoing large-scale multicenter validation studies will provide more information to further confirm the clinical utility of the system.

The Point Interpolation Method for Static Analysis Using Quadratically Consistent Three-Point Integration Scheme

The element free Galerkin method (EFG) is much interest in recent years due to its merits of only node information needed in constructing shape functions and high precision. However, its low computational efficiency becomes a technical issue in the simulation of realistic problems. To develop a more efficient and accurate method, the point interpolation method using quadratically consistent three-point integration scheme (PIM-QC3) is proposed, based on consistency framework for meshfree nodal shape function and its derivatives. And the shape functions along with corrected nodal derivatives at integration points, adopt quadratic basis, meet the differentiation of the approximation consistency (DAC) and the discrete divergence consistency (DDC). In addition, they possess Kronecker delta property and could enforce displacement boundary conditions simply. The T6-Scheme is utilized for node selection in constructing approximation, to avoid the singular moment matrix and make the computation of shape functions simple. Numerical results show the excellence of the proposed method in accuracy and efficiency of all tested methods. Specially, it is more efficient than three-point integration scheme based on element-free Galerkin method. The research in this paper could provide an efficient and reliable tool for analysis of engineering structure.

Importance sampling for system reliability analysis of soil slopes based on shear strength reduction

ABSTRACT Probabilistic methods are increasingly used to quantify the effect of uncertainties on slope stability assessment. The shear strength reduction method can be used for slope stability analysis without prior assumption on the shape of the failure surfaces, and hence is an attractive method for slope stability analysis. Since it is computationally more demanding than limit equilibrium methods, reliability analysis based on the shear strength reduction method is often considered as computationally challenging. In this paper, an importance sampling method is suggested to conduct system reliability analysis of soil slopes based on the shear strength reduction method. In the suggested method, the design points are first identified using a response surface method. Then, a sampling function is constructed centred at the design points. An efficient method is used to identify the failure samples based on the shear strength reduction method. Results from two illustrative examples show that the suggested importance sampling method is an effective and robust tool for system reliability analysis of soil slopes.

Experimental and Analytical Study of Partially Replaced Waste Materials in Rigid Pavement

In India, the 64.5% of goods transport by road network. The rural road connection improves the Social and economic development of rural area. Generally the village road gets low traffic intensity i.e, 450CVPD. It’s necessary to provide cost effective solution for road construction. The construction waste is one of the major wastes generated. In this present study aim is using GGBS and RCA for low cost concreting purpose. In the place of coarse aggregate the Recycled aggregate will be used in the percentage of 0,20,25,30,35% by the weight of coarse aggregate. In the place of cement the GGBS will be replaced in the percentage of 30%.the recycled aggregate concrete properties is found and compared with non recycled aggregate concrete. Thus properties obtained from various experimental investigations. Based on the various experimental results the pavement thickness is optimized by using IRC58. Present study includes the static response analysis of concrete pavement resting on liquid foundation. The 3 dimensional modeling of pavement purpose ANSYS software used and the analysis result compared with westergaard’s analysis. The study shows the finite element tool is reliable tool for concrete analysis

Person-Based Micro-Simulation Demand Model for National Long-Distance Travel in the U.S.A.

As the nation and various states engage in funding transportation infrastructure improvements to meet future long-distance passenger travel demand, it is imperative to develop effective and practical modeling methods for analysis of long-distance passenger travel. Evaluating national-level infrastructure improvements requires a reliable analysis tool to model the demand for long-distance travel. The national travel demand model presented in this paper implements a person-level tour-based micro-simulation approach for modeling individuals’ long-distance or national activities in the U.S.A. This paper reviews the model framework, explains the model calibration, and presents applications of the model for policy evaluation and demand prediction. The model was estimated using the latest long-distance travel survey in the U.S.A., which is the 1995 American Travel Survey. As the estimation data is old, and no new long-distance travel survey with appropriate sample size is available to re-estimate the model, model calibration is the solution used to update the model and make it capable of capturing up-to-date travel patterns. Calibrating such a large-scale model can be challenging, because each calibration iteration is very costly. This paper describes the calibration effort conducted on the national long-distance micro-simulation model to showcase how a large-scale travel demand model can be calibrated efficiently. A fuel price scenario is analyzed to show how the national travel demand will change under a national fuel price increase scenario in the future year 2040. Another scenario analysis corresponding to construction of high-speed rail (HSR) is conducted to observe the effects of adding a HSR system to the northeast corridor on travel demand from a national perspective.

Z-number integrated weighted VIKOR technique for hazard prioritization and its application in virtual prototype based EOT crane operations

Hazard identification and its ranking is one of the foundation steps of safety management. Nowadays, failure mode and effect analysis (FMEA), a reliability analysis tool, is widely used to identify, assess, and rank hazards/failure events related to products, processes, and services because of its simplistic nature. Traditional FMEA focuses on computing the risk priority number (RPN) to rank the identified hazards based on three risk factors, occurrence (O), severity (S), and detectability (D) of a failure mode (FM). However, the traditional RPN method has been criticized because of its limitations in the assessment of hazards/failure events, weighting of the risk factors, and prioritization of the FMs. Furthermore, experts usually provide rating on the risk factors based on their expertise, which introduces impreciseness, uncertainty, and vagueness in the subsequent assessments. In this study, Z-number is used to capture the uncertainty and unreliability associated with experts’ evaluation. Also, the concept of objectivity is deployed along with subjectivity in the weight calculation of the risk factors in the information assessment process. Classic VIKOR (ViseKriterijum-ska Optimizacija I Kompromisno Resenje) method is also extended in Z-environment to rank the identified hazards by incorporating the concepts of maximum group utility and minimum regret. For the illustration purpose, we have applied our proposed method in virtual prototyping based EOT crane operations. Sensitivity analysis and comparative evaluation with the existing methods are also presented to validate our proposed method.

Experimental and numerical analyses of unreinforced masonry wall components and building

In this study, three masonry shear wall prototypes with different opening configurations and a single room (URM) building constituted by the assemblage of the aforementioned walls are studied. Numerical results are compared with the experimental results carried out to validate the advanced numerical modelling. Two different Finite Element models are adopted for the numerical simulations; the first assumes that masonry behaves as a simple homogenous isotropic material exhibiting separate damage in tension and compression, the second relies on discretization of the individual walls and the whole building by means of elastic 8 noded elements and homogenized interfaces. Even though the first method provides acceptable predictions of the lateral load carrying capacity, damage criteria obtained are often not too close to those experimentally observed. Conversely, the second model exhibits the sufficient level of complexity that allows not only to accurately predict the global behavior, but also provides crack patterns very close to those experimentally obtained, so being considered a reliable tool for analysis of URM buildings and further to devise strengthening schemes to reduce their seismic vulnerability.

Developing a Valid and Reliable Gender Analysis Tool Applied in Disaster Management: A Community-Based Survey.

Women and men are assigned roles and responsibilities based on their gender in all contexts. Measuring gender-based differences through gender analysis can help understand who will be at greater risk in disasters. Thus, the present study is aimed to develop a valid and reliable gender analysis tool to collect accurate and necessary gender-disaggregated information in disaster-affected regions. A mix method approach using qualitative and quantitative studies was applied for conducting this study. A total of 20 people affected by the earthquakes and floods and 10 key informants were interviewed in the qualitative stage. The validity and reliability of the tool were measured using the experts as well as women and men living in the destroyed villages of Razavi Khorasan province during the quantitative stage. The Graneheim approach and SPSS software were used to analyze the data collected in both stages. At the first stage, 7 categories were extracted from the data, namely, livelihood status, social status, health, household/family management, reconstruction, welfare and educational facilities, and disaster prevention. The results of content validity ratio (0.69) and content validity index (0.88) confirmed that the tool is valid. The amount of Cronbach's alpha (0.75) and test-retest (0.83) examination indicated that the tool was also reliable. The results of content validity and reliability measurements approved that the gender analysis tool can be applied for postdisaster gender analysis surveys. It is highly suggested to use the information provided by the gender analysis tool for future disaster management plans, programs, and policies in health systems.

Genetic diversity and species differentiation of medicinal plant Persian Poppy (Papaver bracteatum L.) using AFLP and ISSR markers

Persian Poppy ( Papaver bracteatum L.) is a unique alpine medicinal plant. The plant is a rare source of opiate thebaine in nature. Thebaine is a valuable therapeutic precursor alkaloid. Seven ISSR primers and ten AFLP primer combinations were used to examine the genetic variations of 67 P.bracteatum genotypes freshly collected from nine wild populations over Iran. A total 52% ISSR and 48% AFLP genetic polymorphism among the populations were detected. The genetic diversity within the populations was 38% and 41% by ISSR and AFLP markers. The mean coefficient of gene differentiation (Gst) were 0.54 (ISSR) and 0.52 (AFLP). Geneflow was 0.413 (ISSR) and 0.470 (AFLP). AMOVA confirmed the higher variation within the populations. AFLP and ISSR similarly separated the P. bracteatum accessions into three main and one minor group, which was correlated with the samples geographical distributions. Both markers firmly differentiated the out-species accessions, and identified the unknown accession as P. oreintale . The AFLP with higher mean marker resolution power (Rp = 9.74) were more efficient in revealing genetic variations of the Papaver species. The moderate genetic variation within the populations, and very low variation and geneflow among populations could be largely due to anthropogenic factors. It is critical to protect the species by implementing in/ex situ conservation programs. The results of this study could be used for molecular studies, breeding and conservation programs. • This study investigated the genetic variation of wild P. bracteatum genotypes from Iran. • AFLP and ISSR molecular markers proved to be efficient and reliable tools for genetic variation analysis of the species. • The meaningful genetic variation among P. bracteatum populations was higher than that within the populations. • There was limited gene flow among the populations, and the existence of highly preserved genetic resources.

An Adaptive First-Order Reliability Analysis Method for Nonlinear Problems

The HL-RF algorithm of the first-order reliability method (FORM) is a widely useful tool in structural reliability analysis. However, the iteration results of HL-RF algorithm may not converge due to periodic cycles for some highly nonlinear reliability problems. In this paper, an adaptive first-order reliability method (AFORM) is proposed to improve solution efficiency for some highly nonlinear reliability problems by introducing an adaptive factor. In AFORM, based on the two-parameter approximate first-order reliability method, the new iteration point and the previous iteration point are used to obtain the corresponding angle, and the result of convergence is judged by angle condition. According to the convergence degree of the results, two iteration parameters of the approximate reliability method are adjusted continuously by adaptive factor. Moreover, iteration step size is adjusted by changing the parameters to improve the efficiency and robustness of FORM. Finally, four numerical examples and one mechanical reliability analysis example are used to verify the proposed method. Compared with the different algorithms, the results show that AFORM has better efficiency and robustness for some highly nonlinear reliability problems.

Longitudinal Changes of Cerebellar Thickness in Autism Spectrum Disorder

Many studies have reported abnormal cerebellar volume in patients with autism spectrum disorder (ASD) and that this abnormal volume can change with age. In the present study, we used CERES, an automated and reliable quantitative analysis tool, and adopted a longitudinal design to examine developmental changes in the cerebellar lobular thickness in ASD and quantified the relationship between cerebellar thickness development and clinical symptoms. Nineteen individuals with ASD (16 males; age, 12.53 ± 2.34 years at baseline, interval: 2.33 years) and 14 typically developing controls (TD; 12 males; age, 13.50 ± 1.77 years at baseline, interval: 2.31 years) underwent T1-weighted magnetic resonance imaging at two time points. To explore the relationship between cerebellar lobular thickness and the symptoms of ASD, the correlation of Autism Diagnostic Observation Schedule (ADOS) score with lobular thickness data was calculated. The cerebellar lobule thickness decreased in the right Crus II and the Crus II asymmetry was reduced in individuals with ASD. The reduction in lobular thickness and the asymmetry in Crus II were associated with the severity of stereotyped behavior symptoms. Structural differences and behavioral correlations were concentrated in the right cerebellar Crus II. These results emphasize the importance of the potential functional effect of structural differences in cerebellar subregions on ASD and suggest that the changes of thickness in the right cerebellar Crus II are related to the core profile of ASD.

Reliability-based optimal control of semi-rigid steel frames under simulated earthquakes using liquid column vibration absorbers

Liquid column vibration absorbers (LCVAs) have been proved to be highly efficient in vibration suppression of buildings under earthquake and wind loads. This article proposes an efficient computational framework for reliability-based optimal design and placement of LCVAs in semi-rigidly connected buildings subjected to stochastic ground motions. The reduced function evaluations method is used as an efficient tool for structural reliability analysis, while a novel algorithm is proposed for efficient structural optimization. Excessive interstorey drifts of a building and absolute accelerations of its floors are considered as failure events in calculating the probability of failure of the building. The uncertainty regarding the characteristics of future earthquakes is accounted for by applying a probabilistic approach. The effects of pulse components of stochastic pulse-wise ground motions, fixity factor of semi-rigid beam-to-column connections and values of different parameters of LCVAs on the performance and safety of semi-rigidly connected steel-framed buildings are investigated.

Quantitative analysis of honey adulteration by spectrum analysis combined with several high-level data fusion strategies

Illegal addition of syrup to honey products would refdeduce the natural nutritional value of honey. It is essential to develop convenient and accurate analytical methods to rapidly monitor products quality. This study investigated the potential usability of combining mid infrared(MIR) and Raman for the quantification of HFGS (high fructose syrup) in bass honey blends. Where in the partial least squares (PLS) model was established to predict the concentration of the adulterant. Three data fusion strategies (low, mid and high-level) were applied to take advantage of the synergistic effect of chemical information from MIR and Raman, and adopted three high-level data fusion strategies to improve the prediction accuracy of the quantitative model. After data fusion, the RMSEP of high-level (1–3) were better than MIR (1.93) and Raman (2.30). Besides, calibration coefficient of determination (R2) and the RMSECV of high-level data fusion (1–3)also outperformed Raman (0.80, 3.38) and MIR (0.95,1.63).Results showed that: (1) The chemical information obtained from MIR and Raman have complementary advantages. (2) The three high-level fusion strategies can be used as a reliable tool for quantitative analysis.

The use of 18S ribosomal DNA, ITS and rbcL molecular markers to study the genus Dunaliella (Dunaliellaceae) in Iranian samples: A phylogenetic approach

Abstract The microalga Dunaliella has been the focus of attention over recent decades owing to its high biotechnological potential for the production of β-carotene, biofuels and even as a good expression system for the production of recombinant proteins. Different species of this genus have unique features, biological characteristics and biotechnological potential. Therefore, it is necessary to have a clear and reliable taxonomic method to identify different species of Dunaliella. Although several taxonomic systems are available for Dunaliella based on morphological, physiological and molecular features, none of these methods are reliable enough and some controversies exist over different classification systems. In the current study, molecular techniques and bioinformatics tools have been used to re-assess the phylogenetic position of Dunaliella species based on 18S ribosomal DNA (18S rDNA), ITS and rbcL regions. The overall findings based on these markers provide a new and more reliable tool for phylogenetic analysis of Dunaliella species/strains.

A Sensitive HPTLC Method for the Estimation of Glibenclamide, Rosiglitazone Maleate and Metformin Hydrochloride from a Multicomponent Dosage Form.

A sensitive, rapid and cost-effective method based on HPTLC with UV detection was developed for the quantitation of Glibenclamide (GLIBEN), Rosiglitazone maleate (ROSI) and Metformin hydrochloride (MET) from a combined dosage form. Pre-coated RP-18 F254s aluminum sheets were used as the stationary phase. Methanol-tetrahydrofuran-water-glacial acetic acid (16: 3.6: 4: 0.4, v/v) used as the mobile phase, along with chamber saturation of 10min offered an optimum migration (Rf=0.54, 0.62 and 0.80 for GLIBEN, ROSI and MET, respectively). TLC Scanner 3 was used for densitometric evaluation of the chromatograms. DigiStore 2 Documentation System with winCATS software version 1.4.10 was used for the quantitation and photodocumentation. The LOD for GLIBEN, ROSI and MET was found to be 80 ng, 80 ng and 48ng, respectively. Moreover, the LOQ was 200 ng, 200 ng and 120ng for GLIBEN, ROSI and MET, respectively. The method was linear for GLIBEN (r=0.9991), ROSI (r=0.9993) and MET (r=0.9988) within the tested range (200-1000, 200-1000 and 120-600ng/band, respectively). The method was found to be precise and accurate for all the three drugs. The method was applied for the analysis of Triglucored tablets, and it proved to be a reliable quality control tool for the routine analysis of GLIBEN, ROSI and MET in a combined dosage form.