Reliability Analysis Tool Research Articles

Automated seismic waveform location using Multichannel Coherency Migration (MCM)—II. Application to induced and volcano-tectonic seismicity

Locating microseismic events is essential for many areas of seismology including volcano and earthquake monitoring and reservoir engineering. Due to the large number of microseismic events in these settings, an automated seismic location method is required to perform real time seismic monitoring. The measurement environment requires a precise and noise-resistant event location method for seismic monitoring. In this paper, we apply Multichannel Coherency Migration (MCM) to automatically locate microseismic events of induced and volcano-tectonic seismicity using sparse and irregular monitoring arrays. Compared to other migration-based methods, in spite of the often sparse and irregular distribution of the monitoring arrays, the MCM can show better location performance and obtain more consistent location results with the catalogue obtained by manual picking. Our MCM method successfully locates many triggered volcano-tectonic events with local magnitude smaller that 0, which demonstrates its applicability on locating very small earthquakes. Our synthetic event location example at a carbon capture and storage site shows that continuous and coherent drilling noise in industrial settings will pose great challenges for source imaging. However, automatic quality control techniques including filtering in the frequency domain and weighting are used to automatically select high quality data, and can thus effectively reduce the effects of continuous drilling noise and improve source imaging quality. The location performance of the MCM method for synthetic and real microseismic datasets demonstrates that the MCM method can perform as a reliable and automatic seismic waveform analysis tool to locate microseismic events.

On the dynamic modeling of Brayton cycle power conversion systems with the CATHARE-3 code

As the share of intermittent energy sources is increasing, the dynamic modeling of thermal power plants including their power conversion system gets researchers' attention. Recent applications require transient simulations of high-pressure nitrogen closed Brayton cycle for which the ideal gas assumption is no longer verified. In this work, the REFPROP real gas equation of state and pressure drop correlations suitable for high Reynolds numbers have been implemented in the CATHARE-3 code. Moreover, new real gas turbomachinery and sonic flow models have been developed and integrated in the code. Relative errors obtained for the nominal state of a high-pressure nitrogen closed Brayton cycle are in the range −3%/+0.8%. A detailed analysis of real gas effects is carried out on the heat exchangers heat flux and the piping pressure losses. The new sonic flow computed during a loss of coolant accident is in the best possible agreement with literature experimental results. With regard to the turbomachinery, the new real gas model creates a pressure dependence that brings compressors closer to the choke region when the pressure drops in the cycle. This work is expected to provide an efficient and reliable simulation tool for transient analysis of real gas closed Brayton cycles.

Motion Analysis System (MAS) for production and ergonomics assessment in the manufacturing processes

Nowadays the Smart Factories operating within the Industry 4.0 revolution, require more and more reliable, fast and automatic tools for production analysis and improvement. Manufacturing companies, in which the human labour has a crucial role, need instruments able to manage complex production systems in terms of resource utilization, product mix, component allocation and material handling optimization.In this context, this work presents an original hardware/software architecture, Motion Analysis System (MAS), aimed at the human body digitalization and analysis during the execution of manufacturing/assembly tasks within the common industrial workstation. MAS is based on the integration of the Motion Capture (MOCAP) technology with an ad hoc software developed for productive and ergonomic analysis of the operator during his work. MAS hardware integrates a network of depth cameras initially developed for gaming (Microsoft Kinect v2™, conceived for markerless MOCAP) and now used for industrial analysis, while an original software infrastructure is programmed to automatically and quantitatively provide productive information (human task analysis in terms of time execution and used space within the workplace, movements of hands and locations visited by the operator) and ergonomic information (full body analysis implementing all the internationally adopted indexes OWAS, REBA, NIOSH and EAWS). This double perspective makes MAS a unique and valuable tool for industrial managers oriented to the workplace analysis and design (in terms of productivity) without neglecting the operator health. This proposed contribution ends with a real industrial application analysing a water pump assembly station: the system setup is discussed and the key results obtained adopting MAS are presented and analysed.

Разработка элементов виртуальной исследовательской среды для анализа, оценки и прогнозирования последствий глобальных климатических изменений

Представлены описание и первые результаты разработки виртуальной вычислительно-информационной среды для анализа, оценки и прогноза последствий глобальных климатических изменений окружающей среды и климата в выбранном регионе. Созданная среда основана на информационных ресурсах трехслойной архитектуры. Intermediate results of the project aimed at improving methods of the detailed analysis, assessment and prediction of global climate change impact on the regional environment and climate are presented. New reliable interactive tools for in-depth statistical analysis and studying climate change impact obtained in this project will provide specialists, professionals, decision-makers and stakeholders with detailed climatic information. The project addresses the development of a topical virtual research environment (VRE) for the comprehensive study of ongoing and possible future climate change. It analyses the relevant subsequent effects. Such VRE will provide full topical informational required for studying regional economic, political and social consequences of the global climate change. The ultimate goal of this work is a design of hardware and software prototype supporting the topical virtual research environment for climate and environmental monitoring and analysis of the impact of climate change on socioeconomic processes on both local and regional scales. This VRE will integrate both already known and new archives of climate data sets with software realizations of traditional and advanced methods for statistical analysis of big spatial data sets. VRE prototype will provide scientists, decision-makers and stakeholders the access to processing resources and services for interactive analysis of geographically distributed spatial data through a web browser. It will present the results of the analysis using geoinformation technologies and ensure the systematization of spatial data and associated climate information. Also, the work describes an ontological approach to this systematization, which makes it possible to compare the semantics of meteorological and climatic parameters used in different collections and applied problems.

Design Aspects for Large-scale Pit and Aquifer Thermal Energy Storage for District Heating and Cooling

Large-scale seasonal thermal energy storage (TES) can help maximize renewable energy integration into district heating and cooling (DHC) systems. However, expertise and concrete projects in the field is limited and there is currently a lack of reliable and adequate analysis tools and cost data to assess the technical-economic potential of aquifer thermal energy storage (ATES) or pit thermal energy storage (PTES). This paper provides a review summary for current ATES and PTES systems, including design concepts, application criteria, specific cost comparisons of various storage systems, as well as a summary of applicable modelling and design tools currently available.

Patient-Centered Insights: Using Health Care Complaints to Reveal Hot Spots and Blind Spots in Quality and Safety.

Policy Points: Health care complaints contain valuable data on quality and safety; however, there is no reliable method of analysis to unlock their potential.We demonstrate a method to analyze health care complaints that provides reliable insights on hot spots (where harm and near misses occur) and blind spots (before admissions, after discharge, systemic and low‐level problems, and errors of omission).Systematic analysis of health care complaints can improve quality and safety by providing patient‐centered insights that localize issues and shed light on difficult‐to‐monitor problems. ContextThe use of health care complaints to improve quality and safety has been limited by a lack of reliable analysis tools and uncertainty about the insights that can be obtained. The Healthcare Complaints Analysis Tool, which we developed, was used to analyze a benchmark national data set, conceptualize a systematic analysis, and identify the added value of complaint data.MethodsWe analyzed 1,110 health care complaints from across England. “Hot spots” were identified by mapping reported harm and near misses onto stages of care and underlying problems. “Blind spots” concerning difficult‐to‐monitor aspects of care were analyzed by examining access and discharge problems, systemic problems, and errors of omission.FindingsThe tool showed moderate to excellent reliability. There were 1.87 problems per complaint (32% clinical, 32% relationships, and 34% management). Twenty‐three percent of problems entailed major or catastrophic harm, with significant regional variation (17%‐31%). Hot spots of serious harm were safety problems during examination, quality problems on the ward, and institutional problems during admission and discharge. Near misses occurred at all stages of care, with patients and family members often being involved in error detection and recovery. Complaints shed light on 3 blind spots: (1) problems arising when entering and exiting the health care system; (2) systemic failures pertaining to multiple distributed and often low‐level problems; and (3) errors of omission, especially failure to acknowledge and listen to patients raising concerns.ConclusionsThe analysis of health care complaints reveals valuable and uniquely patient‐centered insights on quality and safety. Hot spots of harm and near misses provide an alternative data source on adverse events and critical incidents. Analysis of entry‐exit, systemic, and omission problems provides insight on blind spots that may otherwise be difficult to monitor. Benchmark data and analysis scripts are downloadable as supplementary files.

Dual Electrolytic Eluent Generation for Oligosaccharides Analysis Using High-Performance Anion-Exchange Chromatography.

The research on oligosaccharides is growing and gaining in importance at a rapid pace. The efforts to understand their bioactivity and to develop new products based on oligosaccharides in biotherapeutics and food industry require effective and reliable tools for analysis of oligosaccharides. Here we present a dual electrolytic eluent generation platform for the analysis of oligosaccharides by high-performance anion-exchange liquid chromatography (HPAE) in both analytical and capillary column formats. The system consists of one eluent generator producing methanesulfonic acid (MSA) connected in series with a second eluent generator producing potassium hydroxide (KOH). Through manipulating the concentration output of both eluent generators, chromatographic performance comparable to that obtained using the conventional sodium acetate/sodium hydroxide (NaOAc/NaOH) eluents is achieved using the electrolytically generated potassium methanesulfonate/potassium hydroxide (KMSA/KOH) eluent. This platform utilizes deionized water as the only carrier stream through a single isocratic pump, overcomes the various drawbacks associated with manually prepared NaOAc/NaOH eluents, and offers an easy to use, simplified operation solution for oligosaccharides profiling with increased precision and accuracy.

An effective approach for kinematic reliability analysis of steering mechanisms

The paper presents an effective surrogate model for system reliability analysis of mechanisms based on an extreme-value kinematic error model and the Kriging approximation. In this regard, two types of kinematic reliability problems are considered, i.e., the system reliability that requires the kinematic error remains within an accuracy threshold along an entire output trajectory, whereas the time-dependent reliability accounts for gradually propagated system failure domain due to the varied pseudo-time parameter from its beginning to the current realization. Both kinematic reliability problems need to evaluate the extreme-valued error function presented in the mixture of absolute and maximum operators. By contrast, the simple position-based error function allows developing accurate surrogate models with a rather small number of training samples. Therefore, an approximation model was proposed to deal with kinematic reliability problems of steering mechanisms. Compared to available reliability methods in the literature, results have demonstrated high accuracy of the proposed method for various kinematic reliability problems. Note that the proposed method for time-dependent reliability analysis requires only one round of design of experiment, rather than repeatedly running the kinematic model like the first-order reliability method. It therefore provides an effective simulation tool for kinematic reliability analysis of mechanisms.

Stereoscopic 3DTV Video Quality Metric: the Compressed Average Image Intensity

This paper presents a newly designed stereoscopic video quality metric. Overall insights towards the creation of mechanisms utilized within the genuine metric are presented herein. Delivery of the core information and motivation behind the features implemented, as well as functionality of the Compressed Average Image Intensity (CAII) quality metric are of utmost importance. The mechanisms created might be characterized as an objective, reliable and versatile quality evaluation tool for advanced analysis of the content delivery chain within stereoscopic video services.

Failure mode and effects analysis using Dempster-Shafer theory and TOPSIS method: Application to the gas insulated metal enclosed transmission line (GIL)

Failure mode and effects analysis (FMEA) as a useful tool in safety and reliability analysis to identify and eliminate known or potential failures from the process of product design, development and production has been widely used in a variety of industries. However, in traditional FMEA, there are two big flaws that of the acquisition and aggregation of experts’ diversity evaluations and the calculation of the risk priority number of failure modes. In our paper, an improved FMEA approach based on Dempster-Shafer Theory (DST) and Technique for Ordering Preference by Similarity to Ideal Solution (TOPSIS) method is proposed to dispose the flaws for improving the effectiveness of traditional FMEA. In the proposed FMEA approach, a new aggregation method on the basis of DST is introduced for aggregating various kind of evaluations, then the TOPSIS method is utilized to rank the failure modes according to the evaluations in relation to their severity, occurrence and detectability. Based on DST and TOPSIS method, the proposed FMEA approach can well capture and aggregate diversity evaluations of experts and rank the failure modes under a compromise way with the condition of various uncertainties. Finally, the proposed FMEA approach is applied to the hazard analysis of the failure modes identified in a gas insulated metal enclosed transmission line (GIL) and gets a good result which consistent with practical engineering background. By the analysis and comparison with other methods, we find that the proposed approach is more applicable in real application.

Longitudinal 3D Assessment of Facial Asymmetry in Unilateral Cleft Lip and Palate.

Longitudinal evaluation of asymmetry of the surgically managed unilateral cleft lip and palate (UCLP) to assess the impact of facial growth on facial appearance. Prospective study. Glasgow Dental Hospital and School, University of Glasgow, United Kingdom. Fifteen UCLP infants. The 3-D facial images were captured before surgery, 4 months after surgery, and at 4-year follow-up using stereophotogrammetry. A generic mesh which is a mathematical facial mask that consists of thousands of points (vertices) was conformed on the generated 3-D images. Using Procustean analysis, an average facial mesh was obtained for each age-group. A mirror image of each average mesh was mathematically obtained for the analysis of facial dysmorphology. Facial asymmetry was assessed by measuring the distances between the corresponding vertices of the original and the mirror copy of the conformed meshes, and this was displayed in color-coded map. There was a clear improvement in the facial asymmetry following the primary repair of cleft lip. Residual asymmetry was detected around the nasolabial region. The nasolabial region was the most asymmetrical region of the face; the philtrum, columella, and the vermillion border of the upper lip showed the maximum asymmetry which was more than 5 mm. Facial growth accentuated the underlying facial asymmetry in 3 directions; the philtrum of the upper lip was deviated toward the scar tissue on the cleft side. The asymmetry of the nose was significantly worse at 4-year follow-up ( P < .05). The residual asymmetry following the surgical repair of UCLP was more pronounced at 4 years following surgery. The conformed facial mesh provided a reliable and innovative tool for the comprehensive analysis of facial morphology in UCLP. The study highlights the need of refining the primary repair of the cleft and the potential necessity for further corrective surgery.

An efficient fiber beam-column element considering flexure–shear interaction and anchorage bond-slip effect for cyclic analysis of RC structures

In this paper, a fiber beam-column element considering flexure–shear interaction and bond-slip effect is developed for cyclic analysis of reinforced concrete (RC) structures. The element is based on conventional displacement-based Timoshenko beam theory, where the transverse shear deformation is included, and adopts the fiber model to describe the section force–deformation behavior. In the fiber model, shear deformation is assumed to be uniformly distributed along the section and is only resisted by concrete, thus the multi-dimensional concrete damage model is used for concrete fibers and therefore flexure–shear interaction is reflected naturally at the material level. Meanwhile, to account for the significant bond-slip effect at critical regions, the anchorage slip of bars at these regions is analytically derived. Then it is used to modify the uniaxial stress–strain model for steel fibers by assuming that the total strain can be treated as the sum of the bar deformation and anchorage slip, therefore the bond-slip effect is implicitly but simply represented. To validate the proposed element, a series of RC member and structure tests under cyclic loading are simulated. The results indicate that the proposed element can predict cyclic responses of RC structures, and can be used as a reliable tool for analysis of RC structures.

Characterization of Nanosized Drug Carriers by Analytical Centrifugation

Correct size characterization is a main prerequisite in the field of pharmaceutical nanotechnology. Different methods exist and each method possesses beneficial properties but also some drawbacks. Typical drawbacks are for example a narrow measuring range, which hampers the detection of possible larger particles or the lack to determine size distributions. Therefore, a thorough and reliable size characterization can only be performed by combining different sizing methods. Analytical centrifugation is a relatively novel technology in the field of pharmaceutics and can be used for the characterization of submicron particles. The aim of this study is to investigate if analytical centrifugation is a useful and reliable tool for size analysis of pharmaceutical nanocarriers. Different samples of known composition, that is mono‐, bi‐, tri‐, and tetramodal samples, which are prepared from differently sized particle standards, and different drug nanocarrier systems are characterized by dynamic light scattering and by analytical centrifugation. Analytical centrifugation led to accurate size results and is found to detect all larger sized submicron particles within a small sized main population reliably, when samples with standard particles are analyzed. Size characterization of the different drug nanocarriers is not superior, when compared to classical sizing methods.

Semi-Automated Segmentation of the Tumor Vasculature in Contrast-Enhanced Ultrasound Data

The vascular architecture in tumors contains relevant information for tumor classification and evaluation of therapy responses. To develop a reliable and user-independent analysis tool, a foreground detection algorithm was combined with a maximum-intensity projection to obtain a high signal-to-noise image from contrast-enhanced B-mode data sets, enabling vessel segmentation by thresholding. Parameters describing the density of the vascular network, the number of vessels and the number of branches were extracted. The highly angiogenic A431 tumors had a relative blood volume of 49%, a mean pixel distance to the next vessel of 1.8 ± 0.3 px, 51 ± 29 individual vessels and 478 ± 184 branching points, whereas the more mature and heterogeneous vascularized human epithelial ovarian carcinoma (MLS) and A549 tumors had values of 30%, 3.7 ± 2.7 px, 65 ± 12 and 220 ± 159, and 13%, 7.4 ± 2 px, 31 ± 9 and 59 ± 40, respectively. Thus, our semi-automated analysis method enables the extraction of quantitative vascular features that may help to simplify and standardize tumor characterization.

Structural reliability analysis based on analytical maximum entropy method using polynomial chaos expansion

The maximum entropy (ME) method is a promising tool for structural reliability analysis by estimating the unknown probability density function (PDF) of given model response from its moment constrai...

Simplified framework for system reliability analysis of slopes in spatially variable soils

This paper proposes a simplified framework based on multiple response surface method (MRSM) and Monte Carlo simulation for efficient system reliability analysis of slopes in spatially variable soils. Equivalent spatially constant parameters, which are calculated from an explicit random variable model, are used within this framework to characterise the soil spatial variability such that conventional MRSM can be efficiently performed. In addition, a variance reduction strategy is proposed to enable the framework to be applicable to slope reliability problems that involve more than one type of shear strength. Two slope examples are studied to illustrate the accuracy and efficiency of the proposed framework, based on which the robustness of the proposed framework against various statistics, such as the anisotropic spatial variability, is fully demonstrated by numerous parametric studies. Results show that the proposed framework accurately evaluates the slope reliability considering spatially variable soils in a relatively efficient manner. The proposed framework provides a promising tool for an efficient slope reliability analysis.

Robustness of stochastic expansions for the stability of uncertain nonlinear dynamical systems – Application to brake squeal

Abstract This paper is devoted to the prediction and analysis of brake squeal under random uncertainty. This problem, which is a particular application of a wider issue, namely the stability of random parameter-dependent (RPD) nonlinear dynamical systems, is undertaken by using the non-intrusive generalized polynomial chaos (GPC) and Wiener-Haar expansions. The main objective is to assess the capacities of these meta-models within this framework. A reduced nonlinear non-equally damped, iso-damped and non-damped, disc/pad models are considered in this perspective in order to analyze the robustness of the proposed meta-models with respect to perfect and non-perfect mode coalescence. It turns out that the Wiener-Haar meta-model shows a more robust performance than GPC expansion and consequently offers a more reliable tool for the nonlinear stability analysis and thus for the prediction of brake squeal under parameter uncertainty.

Hybrid Reliability Analysis Framework for Reliability Analysis of Tunnels

Numerical modelling of tunnels, generally carried out by using some numerical analysis tools [e.g., finite element (FE) method, discrete element method], is often computationally expensive. Hence, it becomes extremely difficult to perform reliability analysis of such models using conventional reliability analysis tools. This necessitates development of efficient techniques for reliability analysis. In this work, a novel framework, referred to as a hybrid reliability analysis framework (HRAF), is developed for reliability analysis of tunnels. The proposed approach utilizes a hybrid polynomial correlated function expansion (H-PCFE), a distribution adaptive sequential experimental design (DA-SED), and an adaptive algorithm for further refining the estimates of DA-SED based H-PCFE. The primary idea of HRAF is to use DA-SED based H-PCFE in zones where the probability of misclassification is less and to use actual simulation for zones with a higher probability of misclassification. As a consequence, results obtained are highly accurate and, at that too, from a reasonably lower number of training points and/or actual simulations. Two tunnel problems have been presented to illustrate the performance of the proposed approach. Results obtained have been benchmarked against results obtained using a full-scale Monte Carlo simulation (MCS) with 105 sample points. Results obtained indicate the excellent performance (both in accuracy and efficiency) of the proposed framework.

Theoretical analysis of mixing in liquid clouds – Part IV: DSD evolution and mixing diagrams

Abstract. Evolution of droplet size distribution (DSD) due to mixing between cloudy and dry volumes is investigated for different values of the cloud fraction and for different initial DSD shapes. The analysis is performed using a diffusion–evaporation model which describes time-dependent processes of turbulent diffusion and droplet evaporation within a mixing volume. Time evolution of the DSD characteristics such as droplet concentration, LWC and mean volume radii is analyzed. The mixing diagrams are plotted for the final mixing stages. It is shown that the difference between the mixing diagrams for homogeneous and inhomogeneous mixing is insignificant and decreases with an increase in the DSD width. The dependencies of the normalized cube of the mean volume radius on the cloud fraction were compared with those on normalized droplet concentration and found to be quite different. If the normalized droplet concentration is used, mixing diagrams do not show any significant dependence on relative humidity in the dry volume. The main conclusion of the study is that traditional mixing diagrams cannot serve as a reliable tool for analysis of mixing type.

Failure Mode and Effects Analysis by Using the House of Reliability-Based Rough VIKOR Approach

Failure mode and effects analysis (FMEA) is a widely used reliability analysis tool for identifying and eliminating known or potential failures in system, design, and process. In traditional FMEA, failure modes are evaluated by FMEA team members with respect to three risk factors: severity (S), occurrence (O), and detectability (D), and ranked via their risk priority number (RPN), which is obtained by multiplying the crisp values of S, O, and D. However, traditional RPN has been considerably criticized due to the following shortcomings: not considering the different weights of risk factors; the identical value of RPN for different combinations of S, O, and D; the diversity and uncertainty of evaluation information given by FMEA team members and without considering the dependence among different failure modes. Although significant efforts have been made in FMEA literatures to overcome these shortcomings, there are still some deficiencies. In this paper, a new risk priority model is presented for FMEA by using the house of reliability (HoR)-based rough VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) approach. In the proposed model, the HoR is introduced to identify the dependence among different failure modes and the link between failure modes and the risk factors of O, D and the subcriteria of S. Rough number is introduced to manipulate the subjectivity and vagueness in decision making and VIKOR approach is used to determine the risk priority order of failure modes in a comprehensive way. Finally, an illustrative case in transmission system of a vertical machining center has demonstrated the effectiveness and practicality of the proposed model.