Reliability Assessment Model Research Articles

Venske tromboembolijske komplikacije kod pacijenata sa limfomom

Lymphomas represent a heterogeneous group of malignant hematological diseases with high risk for development of venous thromboembolic complications (VTE). Consequently, VTE significantly impacts morbidity and mortality in these patients. Another concern is the financial burden of the healthcare system caused by diagnostic and therapeutic procedures of cancer-associated thrombosis (CAT). The complex biology of lymphoma, in conjunction with patient and treatment related risk factors for the development of VTE, results in a procoagulant hemostatic dysregulation. Considering the incidence of VTE in patients with lymphoma, there is an emerging demand for both reliable risks assessment model (RAM) for prediction of VTE, as well as for effective VTE prophylaxis and treatment. The clinical course of patients with malignant diseases is accompanied by a wide range of potential treatment complications, making the task of prevention and treatment of VTE even more challenging. In recent years, great progress has been achieved in understanding the pathophysiological mechanisms of thrombotic complications, while the significant number of randomized controlled trials (RCT) have provided standards of prophylaxis and treatment of VTE complications in patients with malignancy. In comparison to previous recommendations and guidelines for CAT, the use of direct oral anticoagulants (DOAC) has been gradually approaching low molecular weight heparins (LMWH) in terms of efficacy and safety profile in these indications. This systematic review is focused on the latest pathophysiological advances, risk factors assessment, prophylactic and therapeutic recommendations and guidelines concerning VTE in patients with lymphoma.

Reliability Assessment Model for Water Distribution Networks

AbstractThe aging water distribution networks in the US are approaching the end of their useful life, and more than 240,000 pipeline breaks are estimated to occur every year, which corresponds to a...

МАРКОВСЬКІ МОДЕЛІ ОЦІНЮВАННЯ ФУНКЦІОНАЛЬНОЇ БЕЗПЕКИ ПРОГРАМНО-ТЕХНІЧНИХ КОМПЛЕКСІВ НА САМОДІАГНОСТОВНИХ ПРОГРАМОВНИХ ПЛАТФОРМАХ З УРАХУВАННЯМ ПОМИЛОК ЗАСОБІВ КОНТРОЛЮ

Ensuring the safe operation of nuclear power plants remains one of the most important tasks. An important role in ensuring the safety of nuclear power plants is played by instrumentation and control systems (ICS). Extremely high demands are made on such systems, first of all, on their reliability and functional safety. The object of research and analysis in this work is the Nuclear Island I&C Instrumentation System and Reactor Protection System, which are developed based on programmable RadICS Platform with self-diagnostic. The failure trees of such platforms and ICS based on them were developed. In the next stage, several Markov models of redundant ICS are developed. The article aims to develop and analyze the results of research on Markov models for reliability and safety assessment of ICS based on self-checking programmable platforms. The models take into account errors of checking and diagnostic tools, namely errors associated with identifying failures and failures of the corresponding components of the hardware and software/FPGA and channels of redundant structures. Models have been developed for various options of redundant structures and taking into account the diversity principle for ISC structure and failure rate caused by design defects. Multiple-fragment Markov Models of ICS were also investigated. The scientific novelty lies in the fact that the proposed models take into account an expanded set of parameters of self-diagnosing programmable platforms, ICS, the processes of their use and maintenance. Recommendations on the selection of parameters and structural ICS are formulated.

Reliability Assessment Model of Water Distribution Networks against Fire Following Earthquake (FFE)

Fire following earthquake (FFE) is a common secondary disaster that can inflict great damage to humans. A large number of seismic resilience evaluation methods have been proposed, but few of them consider the influence of FFE. In this study, a multi-scenario simulation based model was developed to evaluate the post-disaster performance of water distribution networks (WDNs) in supplying both firefighting flow and original demand under the effect of seismic damage and FFEs. Hypothetical earthquakes were generated and the spatial–temporal distribution of FFEs was simulated by the Poisson distribution model and the Weibull distribution model. The post-disaster performance was evaluated by two types of seismic reliability metrics. The developed model was applied to a WDN currently operating in China with eight pre-determined earthquake scenarios. The results showed that the firefighting flow was concentrated in the first few hours after the earthquake. Thus, the serviceability of both original demand and firefighting flow was influenced significantly within the first few hours, while little impact was observed after the concentrated firefighting flow was delivered. The proposed model quantified the WDN’s performance under specific seismic damage and potential FFEs, and can be used for the planning, design, and maintenance of WDNs.

A Multi-State Model for Reliability Assessment of Integrated Gas and Power Systems Utilizing Universal Generating Function Techniques

Large-scale adoption of gas-fired power plants (GPPs) significantly accelerates the integration of power systems and natural gas systems (NGSs). Because the operation of NGS has a significant impact on the reliability of power system, it is important to simultaneously evaluate the reliabilities of power system and NGS. Moreover, due to the stochastic failures and various operating characteristics of components, the integrated gas and power systems (IGPS) considering multiple states can be viewed as a multi-state system. Therefore, a multi-state model is proposed for reliability evaluation of IGPS based on universal generating function (UGF) techniques. First, a framework is proposed to evaluate the reliability of NGS: multi-state models for different components in the NGS are developed as the corresponding UGFs. These UGFs are aggregated utilizing the gas flow calculation operator to obtain the multi-state model of NGS. Moreover, a gas-to-power calculation operator is developed to convert the multi-state model of gas injection at each node to the power output models of GPPs in power system. In this manner, the impacts of NGS could be incorporated into the reliability evaluation of power system. Furthermore, nodal reliability indices for both the NGS and the power system are proposed to evaluate the reliability performances of IGPS. The proposed methods are validated using the integrated gas and power test system.

System Reliability Assessment Based on Energy Dissipation: Modeling and Application in Electro-Hydrostatic Actuation System

This paper addresses a new reliability model, based on energy dissipation, considering performance degradation behaviors. Different from the two-state reliability model and traditional reliability model based on failure rate statistics, this paper focuses on the component energy loss due to its fault evolution, such as fatigue, aging and wear, and presents a reliability model based on the component’s energy dissipation, as well as establishing a power dissipation constrained reliability model for degradation-based reliability assessment. As a demonstration, the proposed method is applied to model and evaluate the failure behavior of the electro-hydrostatic actuation system. The results indicate that the proposed method is effective in describing its life-cycle degradation in the energy field, and provides a reliability assessment based on energy dissipation.

Data-based models for fatigue reliability assessment and life prediction of orthotropic steel deck details considering pavement temperature and traffic loads

Considering the effects of long-term moving vehicle loads and ambient temperature on the fatigue life of details in orthotropic steel decks in cable-stayed bridges, a novel fatigue damage regression analysis model was developed and then used with reliability profiles to predict fatigue life. The regression model can characterize the normal correlation pattern between the daily averaged pavement temperatures, the annual average hourly aggregated traffic volume (AAHTV) or annual average hourly traffic weight (AAHTW) and a stress-based performance indicator. Prediction models based on the monitoring outcomes from the structural health monitoring systems installed on a Yangtze River cable-stayed bridge were first developed and used to describe and predict the time-series of the long-term moving vehicle loads and asphalt concrete (AC) pavement temperatures. An exponential regression model was then developed to quantify the relationship between daily averaged pavement temperatures, moving vehicle loads and the stress-based indicator, which is derived using S–N principles from strain measurements. Further, a limit equation based on the exponential regression model mentioned above for the fatigue life prediction, which considers both the traffic conditions and pavement temperature, has been developed. Finally, this methodology was employed to predict the fatigue life of details in orthotropic steel decks.

An assessment model for identifying maintenance priorities strategy for bridges

Abstract The main purpose of this paper is to develop a model which is capable of assessing the overall condition of bridges as well as the condition of each element for the purpose of prioritizing maintenance strategies. The model will also be capable of ranking the bridges in a network according to their urgency of need for repair based on specific parameters. This paper explains how to achieve reliable assessment of a bridge starting with visual inspection and proceeding with the collection of information and carrying out in-depth investigations to achieve a reliable indication of the bridge's repair needs and its priority in the road network. The model is designed especially for bridges in Egypt as a typical example of a developing country. The methodology of the research was started by surveying the various inspection techniques of bridges. Then all probable defects, their causes and the appropriate repair techniques are identified and classified. After that, the experience and knowledge of bridge maintenance experts in Egypt were added to create evaluation criteria for reliable assessment model to prioritize maintenance strategy of bridges. This is incorporated via conducting questionnaires and interviewing those experts. The final outcome is a Bridge Overall Priority Indicator (BOPI) that ranks the bridges in a network according to their condition and maintenance urgency. The model is designed to be applied to the bridges in Egypt as it is based on the body of knowledge and expertise gained by maintenance and repair experts but it can easily be adjusted to suit any other country. Also the model is designed to cover specific bridge elements which are of major significance in bridge performance as described in this work while overlooking some, less important, elements. It has been observed that there is no effective bridge maintenance plan in most of the developing countries and that in most cases maintenance is carried out after an event has occurred and resulted in severe damage and caused a public outcry. Also developing countries have limited budgets for maintaining their assets. Therefore, it is very important to have an assessment criterion as a development tool to optimize the use of scarce maintenance budgets and get the most out of aging bridge networks.

A reliability assessment model for an outdoor 88 kV XLPE cable termination

A metropolitan power utility has been experiencing systematic and premature failures of a particular type of XLPE cable terminations operating at 88kV (rms). The utility therefore desired to understand the modes of failure in order to evaluate the risk with the terminations still in service. Failed terminations were forensically analysed. The dominant modes of degradation were identified as electro-thermal, galvanic corrosion and thermomechanic fatigue. Based on the weakest link principle, a reliability model was developed using the life factor models corresponding to the identified modes of degradation. Galvanic corrosion and thermomechanic fatigue life factors were found to have the predominant influence on the overall reliability of the termination as they reduced the cable termination life by more than 10 years. The model can be used to track the probability of the remaining life of the terminations as well as evaluating the effectiveness of alternative designs and/or in-situ repairs.

A novel experimental data-driven exponential convex model for reliability assessment with uncertain-but-bounded parameters

The convex model is commonly applied to quantify the uncertain-but-bounded parameters. However, the typical interval and ellipsoid models may lead to inaccurate approximation for existing experimental data, which may incur either too risk or conservative for safety assessment. To this end, this study aims to create a novel data-driven exponential convex model to achieve accurate approximation for experiment data, in which the dimension reduction minimum volume method plays the key role. Furthermore, a novel relaxed exponential nominal value method (RENVM) is developed to evaluate the corresponding non-probabilistic reliability index robustly and efficiently, and the sensitivities are also derived based on the straight forward perturbation method to guarantee its efficiency. Through numerical and experimental studies, the accuracy and validity of the proposed data-driven exponential convex model are validated compared to the interval and ellipsoid models, and the robustness and efficiency of the proposed RENVM are also demonstrated for solving both linear and nonlinear problems.

Reliability modeling for Integrated Community Energy System considering dynamic process of thermal loads

The Integrated Community Energy System (ICES) has developed rapidly, but the reliability assessment models of ICES are somehow out of date. A new reliability assessment model for ICES is proposed incorporating electricity, gas and heat, considering dynamic process of thermal loads. First, the static model of ICES consisting of three subsystems is constructed based on the energy hub model. Then the inertial features of loads are incorporated in the reliability of ICES. Thereafter, a quasi-sequential simulation based on a decomposed optimisation method is proposed to assess the reliability of ICES. Case studies are conducted on an ICES with four energy hubs to validate the performance of the presented model. Results show that the proposed reliability assessment model is more practical and the identified weak points of each subsystem have changed after utilising the new model.

Reliability Assessment of Double-Sided Linear Switched Reluctance Generator System Based on Hierarchical Markov Model

This paper presents a hierarchical Markov model to assess the reliability of a double-sided linear switched reluctance generator (DLSRG) system. The proposed reliability model can be applied to find the balance point of reliability assessment accuracy and model complexity. First, the dominant fault modes of the DLSRG system are highlighted to quantitatively obtain the operation states, survival or failure, with a novel failure criterion. Second, a hierarchical Markov model is adopted to build a systematic reliability model of the DLSRG system, wherein a state transition diagram can be built in the detailed description to constitute the graphical Markov reliability model. And then the solving process to get state probability matrix P ( t ) is intensively investigated. Notably, a reliability block diagram model is also built to compare with the hierarchical Markov model, whose results verify that the Markov model can capture the effect of fault-tolerance capability on system reliability. Moreover, it is expected that the one-level Markov model is the most suitable model for the DLSRG system for its ability of decreasing the model complexity and improving the assessment accuracy. Analytic investigation in conjunction with simulation and experimental measurements demonstrates the feasibility and validity of the proposed model.

Reliability Assessment Model for Industrial Control System Based on Belief Rule Base

This paper establishes a novel reliability assessment method for industrial control system (ICS). Firstly, the qualitative and quantitative information were integrated by evidential reasoning(ER) rule. Then, an ICS reliability assessment model was constructed based on belief rule base (BRB). In this way, both expert experience and historical data were fully utilized in the assessment. The model consists of two parts, a fault assessment model and a security assessment model. In addition, the initial parameters were optimized by covariance matrix adaptation evolution strategy (CMA-ES) algorithm, making the proposed model in line with the actual situation. Finally, the proposed model was compared with two other popular prediction methods through case study. The results show that the proposed method is reliable, efficient and accurate, laying a solid basis for reliability assessment of complex ICSs.

Quality management in healthcare organizations: Empirical evidence from the baldrige data

The purpose of this paper is to investigate the determinants of customer satisfaction and quality results in the healthcare industry using the Baldrige data. We use publicly available data on quality assessment of healthcare organizations that applied for the Baldrige award to examine two research questions: 1) whether the Baldrige model is a reliable and valid model for assessment of quality practices in healthcare organizations, and 2) to determine the relationship between quality practices and their impact on quality results in the healthcare organizations. Using structural equation modeling, the findings suggest that the Baldrige model is a valid and reliable quality assessment model for healthcare organizations. Consistent with previous studies, the findings suggest that the main driver of the system is leadership, which has a significant effect on all quality practices in the healthcare industry. Controlling for the applicants’ year, the findings indicate that 1) Information analysis and knowledge management has a significant impact on Quality results, 2) Workforce development and human resource management has a significant impact on both Customer focus and satisfaction and Quality results, and 3) Strategic planning for quality has a significant impact on Customer focus and satisfaction. The study provides insights and suggestions for healthcare organizations on how to improve their quality systems using the Baldrige model.

A stochastic defect growth model for reliability assessment of corroded underground pipelines

A stochastic corrosion growth model is established for underground pipeline structures. The model has been developed with the concept in mind that the evolution of localized corrosion damage is time-dependent following an activation stage (nucleation) – growth stage (propagation) – steady state stage (passivation) mechanism. The temporal correlation of the defect evolution is able to be well represented by a geometric Brownian bridge process. The variation of activation time is taken into consideration. Two applications are illustrated: 1) predicting the evolution of the probability density function (PDF) of the corrosion depth, and 2) assessing the reliability of a pipeline structure.

Treating Epistemic Uncertainty Using Bootstrapping Selection of Input Distribution Model for Confidence-Based Reliability Assessment

Accurately predicting the reliability of a physical system under aleatory uncertainty requires a very large number of physical output testing. Alternatively, a simulation-based method can be used, but it would involve epistemic uncertainties due to imperfections in input distribution models, simulation models, and surrogate models, as well as a limited number of output testing due to cost. Thus, the estimated output distributions and their corresponding reliabilities would become uncertain. One way to treat epistemic uncertainty is to use a hierarchical Bayesian approach; however, this could result in an overly conservative reliability by integrating possible candidates of input distribution. In this paper, a new confidence-based reliability assessment method that reduces unnecessary conservativeness is developed. The epistemic uncertainty induced by a limited number of input data is treated by approximating an input distribution model using a bootstrap method. Two engineering examples and one mathematical example are used to demonstrate that the proposed method (1) provides less conservative reliability than the hierarchical Bayesian analysis, yet (2) predicts the reliability of a physical system that satisfies the user-specified target confidence level, and (3) shows convergence behavior of reliability estimation as numbers of input and output test data increase.

ПІДВИЩЕННЯ НАДІЙНІСНИХ ПОКАЗНИКІВ ПРОГРАМНО-ОРІЄНТОВАНОЇ МЕРЕЖІ

In this work the reliable indicators of the software-oriented network were analyzed, the comparison of centralized and decentralized management types was made, that program-managed networks need to optimize and increase reliability to the current standards of 3gpp. The model of calculation of the reliability of centralized and decentralized networks is proposed, with the help of which it is possible to identify weak or less susceptible sites in the mobile communication system. The method of estimation and enhancement of reliable characteristics of the information management system of the mobile communication network is developed, based on the hierarchical model of hardware and software reliability assessment. The dependence of equipment on applications or applications is taken into account. The system allows to optimize the process of deployment of the network, modernization and increase the reliability of servicing subscribers of mobile networks. This significantly improves the planning and modeling of the network infrastructure, which in turn increases the efficiency of use and reduces the cost of equipment and labor costs of man-hours. It is also proposed to use this mathematical model for software management model but less reliable sleep structure, so its optimization is a necessary factor in the use of these types of networks.

A study of the internet financial interest rate risk evaluation index system in cloud computing

Cloud computing is a product of computer technologies combined with network technologies and it has been widely applied in China. Experts and scholars in all fields begin to make many studies of cloud computing infrastructure construction and effective resource utilisation. With ITFIN, people can enjoy financial services in dealing with various problems. However, one person can play many identities in the network. This phenomenon posed a severe challenge to ITFIN network security and has largely intensified the risks, including the operational risk, market selection risk and network and information security risk. ITFIN resolves the risks by establishing a reliable, reasonable and effective risk assessment model. We conducted theoretical and empirical analysis, then constructed an assessment model against China's ITFIN risk. The model integrates rough set and particle swarm optimisation support vector machine (PSO-SVM). Finally, the model was used to assess the ITFIN risk in China. The empirical research results indicate that the model can effectively reduce redundant data information with rough set theory. The theory also guarantees a reliable, reasonable and scientific model, enhance the classification effect of the model. The parameters of SVM model obtained by optimising with PSO can effectively avoid local optimum, improve the effect of the classification model. Overall, the model has good generalisation ability and learning ability.

Factors affecting the calculations of Return on Investment (ROI) in Public-Private Partnerships (PPP) projects In Egypt

Public authorities and governments in many countries tended to allocate to the private sector the operations management of existing PPP projects and for financing new projects. There are a lot of benefits from following this approach for all parties. These benefits included risk mitigation, cost savings in governmental expendures, service improvement, employment opportunities, and enhancement in economic indices. This approach was called public-private partnership (PPP). This term was defined as “a cooperative venture between the public and private sectors, built on the expertise of each partner that best meets clearly defined public needs through the appropriate allocation of resources, risks and rewards.” (World Bank, 2016) Public-Private Partnerships (PPP) projects become an important methodology for governments of both developed and developing countries, as a result from crucial role and their worldwide use. The PPP methodology enables public authorities and governments to allocate risks to different parties especially the private sector. According to the World Bank report the private financial participation in Egypt has accounted $219,229.82 Million in the period from 1990 to 2000. This figure has increased to $998,667.36 Million in 2015. (World Bank, 2016) PPP projects are usually more difficult to implement than other traditional procurement models because of their complexity and that their nature and their long duration. Previous research studies on several PPP projects showed that a number of problems exist in the project returns. Additionally these researches show that there is a need for an objective, reliable and practical return assessment model for PPP projects. This required model will help decision makers to assess the profitability of PPP projects at their early stages. To apply PPP projects in Egypt successfully, one of the fundamental requirements is to perform and implement a comprehensive analysis of Return on Investment (ROI). To do that analysis, it should include the factors affecting the ROI relating the projects’ influences such as ; financial, legal, political ,social, etc.

A study of the internet financial interest rate risk evaluation index system in cloud computing

Cloud computing is a product of computer technologies combined with network technologies and it has been widely applied in China. Experts and scholars in all fields begin to make many studies of cloud computing infrastructure construction and effective resource utilisation. With ITFIN, people can enjoy financial services in dealing with various problems. However, one person can play many identities in the network. This phenomenon posed a severe challenge to ITFIN network security and has largely intensified the risks, including the operational risk, market selection risk and network and information security risk. ITFIN resolves the risks by establishing a reliable, reasonable and effective risk assessment model. We conducted theoretical and empirical analysis, then constructed an assessment model against China's ITFIN risk. The model integrates rough set and particle swarm optimisation support vector machine (PSO-SVM). Finally, the model was used to assess the ITFIN risk in China. The empirical research results indicate that the model can effectively reduce redundant data information with rough set theory. The theory also guarantees a reliable, reasonable and scientific model, enhance the classification effect of the model. The parameters of SVM model obtained by optimising with PSO can effectively avoid local optimum, improve the effect of the classification model. Overall, the model has good generalisation ability and learning ability.