Level Of Reliability Research Articles

Development of a streamlined framework for probabilistic and comparative life cycle assessment of road pavements

This study presents a novel framework to address the challenges of extensive data requirements and uncertainties in road pavement life cycle assessment (LCA). We introduce a streamlined framework that employs a structured data underspecification approach. In this study, we categorized the required data into four specificity levels (M1 to M4) to manage data uncertainty in a systematic way. Using 10 case studies with various data specificity levels, our method proves effective in adapting to different degrees of data scarcity. The proposed framework supports a confident decision-making process, in which the comparison indicator shows discerned results at least 90 % of Monte Carlo runs by reducing the data collection burden by 85.7 %. For example, in the Boston pavement scenarios, one can achieve a 90 % reliability level by selectively specifying the maintenance and repair (M&R) activities to an M3-level specificity, while maintaining all other data at a lower level of detail, i.e., M2.

The Role of Patient-Reported Outcomes to Measure Treatment Satisfaction in Drug Development.

Treatment satisfaction is a person's rating of his or her treatment experience, including processes and outcomes. It is directly related to treatment adherence, which may be predictive of treatment effectiveness in clinical and real-world research. Consequently, patient-reported outcome (PRO) instruments have been developed to incorporate patient experience throughout various stages of drug development and routine care. PRO instruments enable clinicians and researchers to evaluate and compare treatment satisfaction data in different clinical settings. It is important to select fit-for-purpose PRO instruments that have demonstrated adequate levels of reliability, validity, and sensitivity to change to support their use. Some of these instruments are unidimensional while some are multidimensional; some are generic and can be applied across different therapeutic areas, while others have been developed for use in a specific treatment modality or condition. This article describes the role of treatment satisfaction in drug development as well as regulatory and Health Technology Assessment (HTA) decision making and calls for more widespread use of carefully selected treatment satisfaction PRO instruments in early- and late-phase drug development.

Improving the reliability of nanosatellite swarms by adopting blockchain technology

AbstractSatellite swarm networks have occupied a prominent position in many modern applications due to their low cost, simplicity of design, and flexibility. Reliability is an influential factor in the design of satellite networks with different structures. Usually, small satellites are based on COST components, which may reduce continues operability due to the lack of using backup system on board the sagecraft. Any failure in one subsystem means a complete loss of the function and data stored in this subsystem; hence the need for a reliable and applicable solution for this matter is a crucial topic. Using the redundancy strategy in satellite swarm networks increases reliability and availability. Blockchain is characterized by using a distributed ledger which enables the database to be replicated across nodes in the network and results in increasing transparency, security, and trust. This paper suggests adoption of blockchain technology in distributed multi-satellite mission swarm networks to provide a high level of reliability and availability of the entire system; the blockchain is usually used to secure system transactions in multilayer approach by storage of the key parameters in more than one node; here we suggest the adoption of this approach not only to secure satellite network transaction, but also to increase system reliability so that failure of one node can be recovered by other nodes. We compared this approach with similar traditional networks that do not use blockchain. The results show a higher reliability efficiency of 95.3% for applying blockchain technology compared to 64.3% without the use of blockchain, as well as a higher availability of 99% compared to 91%.

Dual‐Interface Competitive Fracture Model for Curvature‐Based Transfer Printing Method

AbstractTransfer printing is a key technology in the fabrication of flexible electronics. Transfer printing method based on curvature provides a simple and effective way to transfer films onto weakly adhesive or even adhesiveless surfaces, overcoming the shortage of traditional transfer printing methods that it is difficult to print functional materials from strong interface to weak interface and can only be applicable to surfaces with certain interfacial strength. So far, the theoretical principle of the curvature‐based transfer printing method has not yet been developed. In this article, a dual‐interface competitive fracture model is established to analyze the mechanism of printing and picking up processes and quantitatively provide the critical transfer printing radius in terms of material and geometric properties of the transfer printing system. This model is verified to be both correct and widely applicable by rich experimental results, providing a new and reliable theory for the fabrication of inorganic flexible electronics.

Forecasting the life cycle of reinforced concrete structures in severe climatic conditions

The article considers the problem of design forecasting of the life cycle of reinforced concrete structures operated in severe climatic conditions using the methodology of limit states. The authors propose to use the reliability index β, conditionally regulated by the norms for design limit states, as a criterion index of the functional suitability of structures. The kinetics of the reliability index β during cyclic freezing and thawing is evaluated by means of multifactor periodic experimental control of strength and deformability indices in frozen and thawed states. Testing was conducted using prismatic (100×100×400 mm) and cubic (100 mm) specimens of the B25 mature concrete (180 days), F270 frost resistance grade. In this case, the parametric failure of an element was identified by the moment when the criterion parameter reached the threshold value. The threshold is extablished (with the required level of reliability) by normative functional models of the limit state, transformed to a form describing the dependence of the concrete resistance parameter on the value of the estimated force and section parameters. Test intervals were determined considering the specificity of concrete frost degradation as a multistage process of structural adaptability, as well as microcrack formation and accumulation. Statistical aspects of resistance parameters were identified from experimental data using the maximum likelihood method and Pearson’s criterion (χ2) in assessing their consistency with the theoretical distribution. Additional transient design situations that consider the thermal-moisture state of the structures are considered. The presented experimental data confirmed the feasibility of the proposed approach.

Experimental and numerical investigations on shear behavior of RC beams strengthened with U-wrapped PET FRP

This paper reports the investigations of experimental and numerical programs on the shear performance of U-shaped Polyethylene Terephthalate (PET) FRP-retrofitted RC beams. Twelve RC beams were fabricated and tested under monotonic three-point loading with the test parameters being FRP strip width and shear span-to-effective depth ratio. A comprehensive analysis and investigation were conducted in terms of the failure modes, shear load–deflection responses, shear capacities, the strain evolution of FRP and stirrups, and the interaction of shear contributions among FRP, stirrups and concrete. Larger debonding strains were observed for PET FRP. Five design guidelines and two models available in the literature were assessed against the measured PET FRP shear contribution. A modified model of the shear contribution for PET FRP was developed and verified by the test results. Finally, a finite element model was established to further understand the shear performance of retrofitted beams, in which the bond-slip relationship between concrete and FRP was considered. The FE model was validated by comparing the test and FE results. The proposed FE model could accurately capture the propagation of shear critical cracks and FRP debonding failure for the specimens with medium and large shear spans.

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on hidden Markov model

To address the shortcomings of traditional reliability theory in characterizing the stability of deep underground structures, the advanced first order second moment of reliability was improved to obtain fuzzy random reliability, which is more consistent with the working conditions. The traditional sensitivity analysis model was optimized using fuzzy random optimization, and an analytical calculation model of the mean and standard deviation of the fuzzy random reliability sensitivity was established. A big data hidden Markov model and expectation-maximization algorithm were used to improve the digital characteristics of fuzzy random variables. The fuzzy random sensitivity optimization model was used to confirm the effect of concrete compressive strength, thick-diameter ratio, reinforcement ratio, uncertainty coefficient of calculation model, and soil depth on the overall structural reliability of a reinforced concrete double-layer wellbore in deep alluvial soil. Through numerical calculations, these characteristics were observed to be the main influencing factors. Furthermore, while the soil depth was negatively correlated, the other influencing factors were all positively correlated with the overall reliability. This study provides an effective reference for the safe construction of deep underground structures in the future.

Periodic and random incremental backup policies in reliability theory

Periodic and random incremental backup policies in reliability theory

Development and validation of a nomogram to predict overall survival in patients with glioma: a population-based study.

The objective is to investigate the prognostic factors associated with gliomas and to develop and assess a predictive nomogram model connected to survival that may serve as an additional resource for the clinical management of glioma patients. From 2010 to 2015, participants included in the study were chosen from the Surveillance Epidemiology and End Results (SEER) database. Gliomas were definitively diagnosed in each of them. They were divided into the training group and the validation cohort at random (7/3 ratio) using a random number table. To identify the independent predictive markers for overall survival (OS), Cox regression analysis was utilized. Subsequently, the training cohort's survival-related nomogram predictive model for OS was created by incorporating the fundamental patient attributes. Following that, the training cohort's model underwent internal validation. The nomogram model's authenticity and reliability were assessed through the computation of receiver operating characteristic (ROC) curves and concordance index (C-index). To evaluate the degree of agreement between the observed and predicted values in the training and validation cohorts, calibration plots were created. Age, primary site, histological type, surgery, chemotherapy, marital status, and grade were the independent predictive factors for OS in the training cohort, according to Cox regression analysis. Moreover, the nomogram model for predicting 1-year, 3-year, and 5-year OS was built using these variables. The C-indexes of OS for glioma patients in the training cohort and internal validation cohort were found to be 0.779 (95% CI=0.769-0.789) and 0.776 (95% CI=0.760-0.792), respectively, according to the results. The ROC curves also demonstrated good discrimination. Additionally, calibration plots demonstrated a fair amount of agreement. In summary, the nomogram prediction model of OS demonstrated a moderate level of reliability in its predictive performance, offering valuable reference data to enable doctors to quickly and easily determine the survival likelihood of patients with gliomas.

INCREASING THE RELIABILITY OF THE SYSTEM OF AUTOMATIC VOLTAGE REGULATION OF LOW-VOLTAGE CIRCUITS OF ELECTRICAL DIRECT CURRENT MOVEMENT COMPONENTS

Purpose. The purpose of this work is the analysis of possible directions for improving the performance indicators of electric rolling stock of direct current railways. The work is devoted to the improvement of systems of automatic voltage regulation of low-voltage circuits where the power source is a direct current generator. The number of electric locomotives and electric trains of railways and their units, which have exhausted their service life, but will be in service for a long time, preserves the relevance of research into possible directions of modernization and the specifics of system operation. Methodology. The work uses the analysis and generalization of previously performed research. The methodological basis of the research is the mathematical apparatus of the theory of automatic control and the theory of reliability. The object of research is the process of functioning of low-voltage control circuits of electric rolling stock of direct current railways with direct current generators as an energy source. The subject of the study is a voltage regulator for own needs based on a modern element base. Findings. A variant of the system of automatic voltage regulation of low-voltage circuits with generator power sources for electric rolling stock of direct current is offered. The basis of the system is the voltage regulation node, which in the existing structure is made on the basis of a carbon vibration regulator on a strip. As an alternative, a system based on operational amplifiers and the use of proportional or proportional-integral laws of the regulator in the structure is proposed. Modeling of dynamic processes indicates the structural stability of the system and qualitative transition processes. A comparison of the no-failure indicators of the nodes indicates a possible increase in terms between services and cost savings. The comparison is made for systems that are in operation for a long time and those that are offered. Originality. It is proposed to implement the node of the system of automatic voltage regulation on a modern elemental basis, which allows to improve the reliability of the system and implement a small, economical, modernization of rolling stock of railways with an exhausted service life. Practical value. The obtained results can be used by enterprises that carry out major repairs of electric trains and direct current electric locomotives with extended service life. The implementation of the proposed units makes it possible to replace existing contact-based relay systems with fast contact wear, frequent maintenance and debugging. As a result, new units can be transferred to service during current repairs due to the introduction of non-contact systems and increase the probability of trouble-free operation and use the personnel who are always present in locomotive depots. This reduces the cost of maintenance due to the introduction of a modern element base and exclusion from the technological process of maintenance of existing units.

RELIABILITY ANALYSIS OF SWITCH’S CONTROL SCHEMES

Purpose. The purpose of this article is to conduct an analysis of the reliability of the control schemes of the electric arrow drive with the aim of optimizing and modernizing them to increase the reliability indicators. To show an approach to optimizing the control circuits of an electric turnout that is advantageous from an operational point of view, the implementation of fewer control circuits will minimize the number of failures. To demonstrate a principled circuit solution for optimizing the control circuit of an electric turner with the use of separate redundancy with always-on redundancy and integer multiplicity. Methods. During the research, methods of comparative analysis, synthesis, probability theory, and reliability theory were used. Findings. The paper analyzes the types of re-reservation as a way to increase the reliability of the arrow control scheme. A comparative study of the reliability of various options for reserving the turnout control scheme was carried out in comparison with the classic situation on the railways of Ukraine - the absence of a reserve. It has been proven that the use of separate redundancy with always-on reserve and integer multiplicity provides the maximum increase in reliability, but the significant amount of necessary equipment significantly reduces the economic attractiveness of this method. On the other hand, the use of separate redundancy with substitution and fractional multiplicity (sliding redundancy) gives a positive result only if one redundancy unit serves no more than 15 turnout electric drives, otherwise the overall reliability of the subsystem may decrease. The optimization of the arrow control subsystem at the station is proposed, which requires the use of only six arrow control schemes, one of which is a sliding reserve. The influence of different types of redundancy on the reliability indicators of the arrow control scheme is considered. The most effective option for optimizing the arrow control subsystem has been determined. Scientific novelty. The scientific novelty of the work consists in the well-founded sufficiency of using only six arrow control schemes in combination with the use of sliding redundancy of the arrow control scheme for the control of arrows when disbanding warehouses on the sorting slide. The proposed method makes it possible to increase the reliability of the arrow control subsystem while maintaining the operational parameters of the station. Practical significance. The practical significance of the results lies in the fact that when using the proposed optimization, the resource use of hill automation devices is improved, the maintenance process is simplified, and the total cost of equipment and maintenance costs are reduced.

Large dump critical zone of interest identification and slope failure prediction using realistic 3D numerical modelling

Dump failure is one of the most catastrophic hazards in the opencast mining industry and involves sudden and violent failures. Therefore, susceptible region identification is essential for slope failure mitigation in the large dump. This study proposed a sustainable approach for large dump critical zone of interest (CZI) identification, stability monitoring and slope failure prediction. UAV close-range photogrammetry survey and structure-from-motion (SfM) approach were used for the dump realistic 3D model reconstruction. 3D numerical modelling was employed for dump stability analysis. In this investigation, the dump critical zone, slope factor of safety (FOS), displacement and slope failure prediction were analysed using the 3D numerical modelling. The results indicate that maximum displacement was found in the critical zone I. However, the dump was stable under static conditions. Dump critical slope failure time is predicted using the inverse velocity method. The results of this investigation are reliable and establish the scope of UAV photogrammetry for realistic 3D modelling. In addition, the slope stability state and failure model were consistent with field observations. The proposed approach can be used for the mine, hill, and roadcut slopes. UAV technology and 3D modelling approaches have substantially reduced data collection time and expense.

Methods to Increase Reliability in Quality Improvement Projects.

Although many quality improvement initiatives in health care see early and laudable success, 1 of the greatest challenges is sustaining the gains and avoiding the natural tendency of systems to revert to their original state, function, and outcomes. Reliability science describes a mathematical and systematic framework for understanding the level of reliability of interventions, and therefore the anticipated success and failure rate of both the steps of a process and the cumulative process overall. Successful utilization of this framework, along with the mindful organizing principles of high-reliability organizations, will facilitate ongoing and long-lasting improvement in outcomes. In this article, we describe practical methods to increase the reliability of interventions toward achieving and sustaining improvement goals.

Shear behavior of externally prestressed precast concrete segmental beams with both positive and negative moment regions

To investigate the shear behavior of externally prestressed precast concrete segmental beams with both positive and negative moment regions (EPCS P&N beams), eight specimens were subjected to failure under various shear span to depth ratios, moment ratios, and joint types. Throughout the testing process, critical crack initiation and development, joint slippage and opening, failure processes and modes, as well as strains in concrete, stirrups, and external prestressing tendons were meticulously recorded. At the point of failure, the concrete in the shear-compression zone near the top surface of the joint section (closest to the loading point in the positive moment region) or near the bottom surface of the joint section (closest to the interior support in the negative moment region) experienced crushing. Subsequently, the external tendons lost support and underwent elastic retraction, causing the two segments on either side of the critical web-shear crack to slide against each other. The elastic strain energy was released significantly as a consequence of the external tendons retracting, leading to the rupture of stirrups intersecting the failure cracks, followed by flange buckling. Based on the test results, a strut-and-tie model was developed to analyze the shear resistance mechanism, and a detailed flowchart for computing the shear resistance of EPCS P&N beams was established. The predictions from the proposed analytical method were compared with the test results, showing good agreement and confirming the rationality of the proposed shear resistance mechanism.

Fatigue life prediction for high-speed railway bridges by reconstructing monitoring-based dynamic stress

Abstract Bridge responses that are excited by high-speed trains have the characteristics of high amplitude, high cycle, and large dynamic effects, which greatly affect the fatigue bearing capacity of affected bridges. To achieve reliable analysis of the fatigue performance of high-speed railway bridges, this study developed a bridge fatigue life prediction method based on the reconstruction of the train-induced dynamic stress time history. First, the equations for solving the static stress time history under influence line virtual loading are derived, and then the dynamic stress time history reconstruction method based on two types of dynamic correction factors is proposed. The statistical characteristics of the train loads and dynamic correction factors are fit according to monitoring data, and bridge fatigue life prediction is realized by use of the reliability theory. Finally, the applicability and effectiveness of the proposed method are verified by using a train-bridge interaction model and monitoring data from a long-span high-speed railway bridge. The results show that the proposed method can greatly improve the accuracy of fatigue performance analysis and can effectively predict the fatigue life of high-speed railway bridges under complex loads. These results can provide an important reference for fatigue evaluation of high-speed railway bridges.

Machine learning-driven real-time identification of large-space building fires and forecast of temperature development

In firefighting, real-time knowledge of fire dynamics is crucial yet often unavailable. The building geometry and measured gas temperatures are integrated to ascertain fire states and predict temperature evolution, utilizing a machine learning framework that combines long short-term memory networks and transfer learning. The model is pre-trained on datasets with 1000 samples from parametric fire models and 200 from field simulations, enabling real-time predictions with on-site data. Numerical simulations in portal frame buildings demonstrate over 95 % accuracy in identifying fire states and 90 % in predicting gas temperatures. A method using correlation coefficients and standard deviations effectively detects damaged thermocouples with over 96% accuracy, given a damage ratio below 30 %. Validation in two real fire scenarios showed more than 92 % accuracy in locating fires and over 89 % in forecasting gas temperatures 20 min ahead, which costs 2.14 s and 1.83 s, respectively. The machine learning framework also exhibits robustness to changes in ventilation conditions by making temperature predictions using reliability theory. The proposed framework provides clear information about the state and development of the fire to firefighters and is useful for promoting smart firefighting

Advancement of data-driven SHM: a research paradigm on AE-based switch rail condition monitoring

The past ten years have witnessed the tremendous progress of structural health monitoring applications in civil infrastructures. This is particularly embodied in railway engineering. The increasing train speed brings greater challenges to safety and ride comfort, and the primary theme of maintenance has been gradually altered from offline inspection to online monitoring. Rail operators must get an in-time warning of potential structural defects before critical failure takes place. It is more favourable that the rail operators can take hold of the real-time status of the key components and infrastructures in railway systems. This paper summarizes a long-term research series by the authors’ research team on online monitoring of rail tracks at turnout areas utilizing acoustic emission-based sensing technique, and more importantly, successively advancing signal processing methods and data-driven analysing frameworks, covering Bayesian inference, convolutional neural networks, transfer learning and task similarity analysis. The proposed algorithms tackle noise interference brought by wheel-rail impacts, great uncertainties in an open environment, and insufficiency of monitoring data, and realize comprehensive monitoring of rail tracks in turnout areas from basic crack detection to regressive condition assessment step-by-step.

Reliability framework for CLT floors in out-of-plane bending using Monte Carlo simulation

Sustainably sourced engineered wood products (EWP) such as cross-laminated timber (CLT) floor panels are viable alternatives to conventional concrete and steel, however their inherent natural variability increases perceived risks and limits wide-spread adoption. The reliability index (β) is the metric used by design standards to communicate allowable structural risk. Although not included directly in any structural capacity equations, it governs all the partial resistance factors and load amplification factors that inform those design code calculations. CLT floors have significant partial resistance factors due to the natural variability of the material that effectively penalise the calculated design strength of those products. By exploring their reliability there is the potential to allow these products to be designed more efficiently, leading to increased competitiveness among traditional materials and less waste. A novel statistical capacity prediction model that goes beyond a simple averaged-value strength assumption to include consideration of the variability between individual boards within a panel was validated against experimental data. A CLT database of 237 out-of-plane bending test results was collected for the first time to inform an appropriate model error factor. Monte Carlo simulation (MCS) approaches were adopted to predict the reliability levels of CLT panels by defining the material, geometrical and loading parameters as random variables and assigning each a mean, coefficient of variation and appropriate distribution. The target and calculated reliability levels were compared across both Eurocode 5 and the North American codes ANSI/APA PRG 320 and CSA O86 as the preeminent CLT design codes internationally. This study found that the calculated reliability levels met or exceeded both codes in most scenarios. The impacts of width, load ratio, material strength distribution, and CLT layups on the expected failure probabilities were explored with sensitivity analyses. The MCS framework was also applied to the calibration of an appropriate resistance factor for CLT design to inform the potential creation of an Australian CLT design code. A resistance factor of 0.85 was calibrated which falls between the equivalent European and North American code resistance factors.

Transverse failure prediction of unidirectional carbon fiber reinforced polymer composites subjected to uniaxial and biaxial loading by stress-triaxiality-dependent computational micromechanics

Accurate characterizing the mechanical behavior of the component materials is crucial for failure predicting of unidirectional carbon fiber reinforced polymer (UD CFRP) composites. A stress-triaxiality-dependent micromechanics model is developed for the transverse failure prediction of the composites in this study, in which the stress triaxiality is innovatively adopted to define the plastic hardening behavior of the matrix material. Therefore, diverse hardening behaviors generated by heterostructures, accurate confirmation of biaxial failure, as well as hardening behavior evolution caused by stress status changes during loading process can be considered. The accuracy performance of the micromechanics model is provided by comparing the predicted results (stress–strain curves, RVE profiles and failure points) with existing experimental data and failure envelopes of failure criterion. The comparison results show that the micromechanics model can accurately capture the failure phenomenon and failure evolution mechanism of the composite under uniaxial and biaxial loadings.

Implementation of a Cardiogenic Shock Team in a Tertiary Academic Centre

Observational studies have shown that the management of patients with cardiogenic shock (CS) by dedicated multidisciplinary teams improve clinical outcomes. Nevertheless, these studies reflect a specific organisational setting with most patients being transfers from referring hospitals, hospitalised in cardiac intensive care units (ICU), or treated with mechanical circulatory support (MCS) devices. The purpose of this study was to document the organisation and outcomes of a CS team offering acute care in all-comer population. A CS team was developed in a large academic tertiary institution. The team consisted of emergency care physicians, critical care cardiologists, interventional cardiologists, cardiac surgeons, ICU physicians and heart failure specialists and was supported by predefined operating protocol, dedicated communication platform and regular team meetings. Over 12 months, 70 CS patients (69±13 years old, 67% males) were included. Acute myocardial infarction (AMI-CS) was the most common cause (64%); 31% of the patients presented post-resuscitated cardiac arrest and 56% needed invasive mechanical ventilation (IMV). Coronary angiography was performed in 70% and 53% had percutaneous coronary intervention. MCS was used in 10% and 6% were referred for urgent cardiac surgery. The in-hospital mortality in our centre was 40% with 39% of the patients dying within 24-hours from presentation. 76% of the alive patients were discharged home. Across an all-comer population, AMI was the most common cause of CS. A significant number of patients presented post cardiac arrest, and the majority required IMV. Mortality was high with a significant number dying within hours of presentation.