System Reliability Evaluation Research Articles

Cost-effectiveness and reliability evaluation of hydrogen storage-based hybrid energy systems for unreliable grid

Cost-effectiveness and reliability evaluation of hydrogen storage-based hybrid energy systems for unreliable grid

Experimental Study on Horizontal Resistance Parameter of Gravelly Soil Considering Slope Gradient Factor

Horizontal resistance can be significantly different for gravelly soil slope sites with different gradients. The impact of slope gradient on the horizontal resistance of soil based on a three-dimensional physical simulation test has been investigated, and the displacement of the pile top and soil pressure for four piles under various gradients (slope gradient 0–45°) was analyzed. The research reveals that ① The soil resistance exhibits a linear increase stage, non-linear steep increase stage, and gradually stabilizing stage with the increase in load. ② The ultimate soil resistance is significantly affected by depth and displacement, and hyperbolic variation characteristics related to the displacement stage. It has a slope weakening effect, and the steeper the slope gradient, the lower the ultimate soil resistance of the pile sides, which effect is negligible when the depth exceeds 0.6–0.7 times that of the pile buried depth. ③ Based on the characteristics of horizontal ultimate resistance-displacement-depth variation in soil, a gradient factor, which is only related to the slope gradient, was used to describe the impact of gradient on the soil resistance modulus (kini) and ultimate resistance (pu). kini is reduced close to the ground surface and gradually increases with depth until it becomes equal to the value of level ground. The ratio between pu in slope ground and level ground was determined for slope angles. The above horizontal resistance parameters were expressed as a function based on the test data to calculate the lateral ultimate bearing capacity of gravelly soil considering the slope gradient factor. The research results developed the theory of foundation design for building structures, promoting the reliability evaluation of pile soil systems towards a more scientific and rigorous direction.

Unified framework for stochastic dynamic responses and system reliability analysis of long-span cable-stayed bridges under near-fault ground motions

Long-span cable-stayed bridges are complex systems with numerous components, and prone to failures of multiple components under near-fault ground motions with long-period velocity pulses. The evaluation of dynamic system reliability of cable-stayed bridges is an important challenging issue. In this work, a unified framework for simultaneously determining both the stochastic dynamic responses and system reliabilities of long-span cable-stayed bridges under near-fault stochastic ground motions is proposed based on direct probability integral method (DPIM) with adaptive strategy. Firstly, the 3-dimensional finite element model of typical cable-stayed bridge and the stochastic synthesis model of near-fault ground motions are established. Based on probability density integral equation, new formulas in input probability space of time-variant moments of response are derived. Then, DPIM with adaptive strategy is suggested to calculate the mean value and standard deviation of response via new formulas. Dynamic system reliability of cable-stayed bridge under near-fault stochastic ground motions is evaluated by establishing failure criteria of extreme value mappings of multiple performance functions. Finally, numerical results indicate that the long-period velocity pulse of near-fault motions imposes an important effect, resulting in large mean responses and failure of cables. Failure probability of cables is significantly increased with the occurrence of velocity pulses, which causes the decrease of system reliability of cable-stayed bridge. Thus, the randomness and velocity pulse effect of near-fault ground motions should be seriously considered for reliability-based design and safety assessment of cable-stayed bridges.

A Fully Analytical Approach for the Real-Time Dynamic Reliability Evaluation of Composite Power Systems with Renewable Energy Sources

Renewable energy sources (RES) have strong uncertainties, which significantly increase the risks of power imbalance and load shedding in composite power systems. It is thus necessary to evaluate the operational reliability for guiding economic dispatch and reducing the risks. Current methods cannot meet the requirement for the operational timeliness of reliability evaluations due to the high computational complexity of the optimal power flow (OPF) calculations of massive contingencies. This paper proposes a fully analytical approach to construct fast-to-run analytical functions of reliability indices and avoid reassessments when the load and RES change. The approach consists of uniform design (UD)-based contingency screening and a modified stochastic response surface method (mSRSM). The contingency screening method is used to select critical contingencies while considering the uncertainties. The mSRSM is used to construct the analytical functions of the load shedding to the load and RES generation for the selected contingencies. An analytical function of a smooth virtual variable that maps to the load shedding is established in such a way that, when the load and RES vary, the reliability can be assessed within a very short time rather than using laborious OPF calculations. Case studies illustrate the excellent performance of the proposed method for real-time reliability evaluation.

ИНСУЛЬТ МЕНЕН ООРУГАН БЕЙТАПТАРДАГЫ ТЕРЕҢ ТАМЫР ТРОМБОЗУНУН ТОБОКЕЛДИК ФАКТОРЛОРУ ЖАНА БОЖОМОЛДООЛОРУ (ИЛИМИЙ АДАБИЯТТАРДЫ КАРАП ЧЫГУУ)

Currently there is no reliable evaluation system for predicting deep vein thrombosis (DVT) in the hospital after ischemic and even more – hemorrhagic stroke. Objective: to review current literature data on the verification of risk factors for the development of DVT in stroke patients and aggressive and early screening strategies in the early post-stroke period. Three fundamental factors underlie the development of DVT: damage to the venous wall, the tendency of blood to hypercoagulation and slow blood flow. Most of the factors that are more or less associated with the development of thromboembolic events revolve around these 3 elements. Typical factors were older age, female gender, changes in the levels of clinical and laboratory variables such as D-dimer or scores on the Berg equilibrium scale. An effective model of risk stratification for DVT at the hospital level after a stroke would be useful for identifying high-risk patients and for implementing individual preventive strategies, therefore further population studies are needed, including in Kyrgyzstan.

Knowledge embedding synchronous surrogate modeling for multi-objective operational reliability evaluation of complex mechanical systems

To effectively assess the multi-objective operational reliability of complex mechanical system, the concept of Knowledge Embedding Surrogate Modeling (KeSM) is proposed by integrating Knowledge-based Decomposition-Coordination (K-DC) strategy, Knowledge-based Parameter Decomposition (K-PD) strategy, and the surrogate model. In this concept, the K-DC strategy is used to decompose a complex problem into several smaller sub problems, coordinating outcomes from the bottom-up; the K-PD is applied to decompose complex parameters into two parts: associated trends and local fluctuations; the surrogate model is adopted to establish the mapping relationship between input and output. Under this concept, the Knowledge Embedding Synchronous Surrogate Modeling (S-KeSM) multi-objective operational reliability evaluation method is developed by combining linkage important sampling technique and synchronous modeling thought with KeSM concept. In addition, an engineering case (civil aircraft braking system temperature with multi-failures) is employed to validate the proposed method. Through comparison and validation with multiple methods, the results show that the proposed method has significant advantages in analysis accuracy and efficiency. This study can provide theoretical references for the multi-objective operational reliability evaluation of complex mechanical systems.

A comparative study of numerical methods for reliability assessment based on semi-Markov processes

The semi-Markov process, renowned for its versatile applications, has garnered significant attention in recent years. However, deriving closed-form expressions for computing reliability metrics proves challenging when sojourn times deviate from exponential distributions. This paper investigates three numerical techniques for computing the transition function matrix of the semi-Markov process, including the algebraic method, the truncated method, and the iterative method. It delves into their truncation and discretization errors, as well as their computational complexities. Additionally, the Laplace-based method and the semi-Markov-chain-based method are discussed to contrast their effectiveness with the three devised numerical approaches. Building on the linkage between the Markov renewal equation and system reliability metrics, five computational methods are applied to the evaluation of system reliability and availability. A case study on sequential cyber-attacks is presented to illustrate the applicability of these methods, considering sojourn times that follow exponential, gamma, lognormal, and Weibull distributions respectively. The results reveal that the three proposed numerical methods not only achieve high precision and rapid speed but also address scenarios beyond the capability of the Laplace-based method.

A novel evolutionary strategy optimization algorithm for reliability redundancy allocation problem with heterogeneous components

The reliability-redundancy allocation problem (RRAP) is an optimization problem that maximizes system reliability under some constraints. In most studies on the RRAP, either active redundant components or cold standby components are used in a subsystem. This paper presents a new model for the RRAP of a system with a mixed redundancy strategy, in which all components can be heterogeneous. This formulation leads to a more precise solution for the problem; however, RRAP is an np-hard problem, and the new mixed heterogeneous model will be more complicated to solve. After formulating the issue, a novel design of an evolutionary strategy optimization algorithm is proposed to solve that. The problem consists of discrete and continuous variables, and different mutation strategies are designed for each. The new formulation of the problem and the new method for solving it lead to better results than those reported in other recent papers. We implement the new suggested heterogeneous model with the PSO and SPSO algorithms to better compare the proposed algorithm. Results show improvement in both system reliability and fitness evaluation count.

Manufacturing system evaluation in terms of system reliability via long short-term memory

With the development of system reliability evaluation, more and more studies are published by considering more attributes or adopting different calculation methods. However, existing deep learning (DL) approaches for predicting system reliability of a multi-state manufacturing network (MMN) only considering single attribute, such as time or machine failure. A more comprehensive consideration about an MMN is deliberated in this study. The Long Short-Term Memory is then utilized to construct the prediction model to process time series of an MMN data. Through the experimental results, the proposed prediction model outperforms than the existing method and other DL method in terms of root mean square error and mean absolute error. Moreover, the parameter of an MMN and hyperparameter of the proposed prediction model are discussed to investigate the optimized combination for system reliability prediction.

Quantifying the Reliability Performance of a Guided Wave-Based SHM System Using Piezoelectric Wafer Actuator Sensors

The adoption of structural health monitoring systems can bring important benefits to the aerospace industry. However, the current implementation of SHM technologies in today's aerospace industry remains limited. One of the primary obstacles hindering the adoption of SHM technologies is the challenge associated with assessing the reliability of SHM systems. In aerospace applications, SHM hardware is exposed to harsh environments, including high or low temperatures, vibrations, moisture, and radiation. Consequently, the long-term performance of SHM systems is adversely affected. This study delves into various issues related to the evaluation of SHM system reliability and performance quantification, placing special emphasis on guided wave-based SHM using Piezoelectric Wafer Actuator Sensors. We present experimental and numerical modeling examples designed to illustrate the detrimental effects of aging at the unitary sensor and sensor network levels. Conclusions are drawn regarding the current challenges in quantifying system reliability, emphasizing relevant performance metrics such as the probability of detection, localization, and false call rates.

A path-based simulation approach for multistate flow network reliability estimation without using boundary points

A multistate flow network is useful for the effective and efficient model construction and reliability evaluation of large and complex systems. To evaluate the reliability of a multistate flow network, boundary points for specified demands are generated in the existing path- and cut-based methodologies. Using the boundary points, the system reliability can be calculated using analytical or simulation methodologies. However, evaluating reliability using boundary points is an NP-hard problem. To improve the time efficiency of reliability estimation, a path-based simulation approach without boundary points is proposed in this study, where the minimal path without any cycles is used. The contributions of this study are threefold: First, the proposed path-based simulation complements the cut-based simulation to improve the applicability of reliability estimation for various network topologies. Second, the proposed simulation algorithm presents linear time complexity, whereas conventional boundary-based analytical methodologies or simulations consume exponential/factorial time. Third, the time attribute is included in the proposed simulation approach to analyze the behavior of reliability degradation over time. The experimental results, including those of a case study, indicate that the proposed path-based simulation is more effective and efficient than existing boundary-based approaches, particularly for large and complex systems.

A Proposed Mathematical Model for Networked and Distributed System Reliability Evaluation in Tanzanian Universities

A Proposed Mathematical Model for Networked and Distributed System Reliability Evaluation in Tanzanian Universities

Evaluation of reliability of complex engineering systems using risk acceptance criteria

The reliability evaluation of gas pipeline systems is one of the most important tasks, since the safety of gas supplies determines the reliable operation of the whole system.Purpose: This paper presents the evaluation methodology based on the risk acceptance criteria established in accordance with the current rules and standards.Methodology: A three-component methodology is used to evaluate the reliability level of gas pipeline systems. It is implemented by creating a model of failure consequences, which accounts for environmental conditions and pipeline properties. Acceptable probabilities of the pipeline failure are determined using the risk theory. Based on these data, the model is designed to assess the gas transport reliability in the pipeline system with regard to failure probabilities and hydraulic characteristics.Research findings: The reliability level of the system is determined using the acceptable failure probability. The obtained reliability is compared with that of the real pipeline system. The best procedure is proposed to maintain and improve the system reliability.

Advanced VTCDREM for dynamic reliability evaluation of railway systems: Integration of fully probabilistic track irregularities and multifaceted random factors

Advanced VTCDREM for dynamic reliability evaluation of railway systems: Integration of fully probabilistic track irregularities and multifaceted random factors

Enhancing quality evaluation in traditional Chinese medicine: Utilizing dual wavelength fusion fingerprint, electrochemical fingerprint, and DSC fingerprint

Developing a reliable and effective quality evaluation system for traditional Chinese medicine (TCM) is both challenging and crucial for its advancement. This study employs fingerprinting techniques to establish precise and comprehensive quality control for TCM, taking Xuezhikang capsules as an example and aiming to facilitate the internationalization of TCM. The “double wavelength absorption coefficient ratio fingerprint” and “Reliability theory” are developed to determine the fingerprint peak purity and fingerprint reliability respectively. Subsequently, the dual-wavelength fusion fingerprint was obtained to avoid the limitations of a single wavelength. In addition, an electrochemical fingerprint (ECFP) was obtained to assess the similarity of electroactive components in the sample, and the Differential Scanning Calorimetry quantized fingerprint (DSC QFP) was introduced for thermal analysis. Fingerprint-efficacy correlations between PL-EC* and dual-wavelength fusion fingerprint (DWFFP) provided valuable insights that there are 76.6 % of the fingerprint compounds exhibited electroactivity. Finally, samples were classified into grades 1∼3 by combining DWFFP, ECFP and DSC QFP through the mean method, meeting the evaluation standard (SL−M > 0.9, PL−M between 80 % and 120 %). This study provides valuable information for ensuring the quality of TCM products, which represents a significant step forward in enhancing the reliability and authenticity of TCM products.

A Study on the Design and Implementation Technologies of EVA at the China Space Station

Extravehicular activity (EVA) is a key point and a difficult point for manned spaceflight tasks, as well as an inevitable trend in the development of the manned spaceflight industry. Equipment maintenance, load installation, and extravehicular routing inspection via EVA on the track are necessary to guarantee the safety and reliability of the long-term in-orbit operation of the China Space Station. In this paper, a comprehensive analysis was conducted on the features of multiple tasks, diverse working modes, and strong systematic coupling during the EVA of the China Space Station (CSS). On this basis, the design, implementation technologies’ development, and in-orbit performance evaluation during EVA were expounded. In the space station system, an extravehicular reliability verification and evaluation system suitable for the requirement for EVA under the conditions of China’s multi-mission, multi-module combination, and repairable spacecraft was constructed. Finally, the in-orbit EVA implementation of the China Space Station since the launch of the core module to the present was summarized, and the subsequent application of the extravehicular technologies in manned lunar landing projects and optical modules was anticipated.

Reliability evaluation of flexible manufacturing systems based on three-layer index system with time-varying weights

With the development of industrial manufacturing, flexible manufacturing system provides an effective way to improve the machining quality and efficiency, as well as reduce the manufacturing cost. Fflexible manufacturing system reliability has been one focus of recent studies. But a systematic, effective and executable reliability evaluation method has not yet proposed in existing researches. This work firstly presented a three-layer index system for flexible manufacturing system reliability evaluation, which is composed of the whole layer indexes, subsystem layer indexes and equipment layer indexes determined by system composition and running features analysis. Time-varying weights of each layer are calculated through the modelling of the reliability and reliability importance based on the classical two-state failure hypothesis. Then, considering multi-state failure modes of elements, a fuzzy evaluation model of flexible manufacturing system reliability is established based on fault grading and statistics, considering grade and number distributions of faults within a certain statistical period. Moreover, through a simulation case of a box-parts finishing flexible manufacturing system, the influence of failure rates and service time on the index weights distribution is firstly revealed, which can provide theoretical basis for the improvement of flexible manufacturing system reliability; then the effectiveness of the proposed method is verified through the comparison of results obtained by the previous model based on two-state failure and the proposed model based on multi-state failure.

Establishment of a human organoid-based evaluation system for assessing interspecies infection risk of animal-borne coronaviruses

ABSTRACT The COVID-19 pandemic presents a major threat to global public health. Several lines of evidence have shown that the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), along with two other highly pathogenic coronaviruses, SARS-CoV and Middle East Respiratory Syndrome (MERS-CoV) originated from bats. To prevent and control future coronavirus outbreaks, it is necessary to investigate the interspecies infection and pathogenicity risks of animal-related coronaviruses. Currently used infection models, including in vitro cell lines and in vivo animal models, fail to fully mimic the primary infection in human tissues. Here, we employed organoid technology as a promising new model for studying emerging pathogens and their pathogenic mechanisms. We investigated the key host-virus interaction patterns of five human coronaviruses (SARS-CoV-2 original strain, Omicron BA.1, MERS-CoV, HCoV-229E, and HCoV-OC43) in different human respiratory organoids. Five indicators, including cell tropism, invasion preference, replication activity, host response and virus-induced cell death, were developed to establish a comprehensive evaluation system to predict coronavirus interspecies infection and pathogenicity risks. Using this system, we further examined the pathogenicity and interspecies infection risks of three SARS-related coronaviruses (SARSr-CoV), including WIV1 and rRsSHC014S from bats, and MpCoV-GX from pangolins. Moreover, we found that cannabidiol, a non-psychoactive plant extract, exhibits significant inhibitory effects on various coronaviruses in human lung organoid. Cannabidiol significantly enhanced interferon-stimulated gene expression but reduced levels of inflammatory cytokines. In summary, our study established a reliable comprehensive evaluation system to analyse infection and pathogenicity patterns of zoonotic coronaviruses, which could aid in prevention and control of potentially emerging coronavirus diseases.

Reliability Evaluation for Continuous-Wave Functional Near-Infrared Spectroscopy Systems: Comprehensive Testing from Bench Characterization to Human Test.

In recent years, biomedical optics technology has developed rapidly. The current widespread use of biomedical optics was made possible by the invention of optical instruments. The advantages of being non-invasive, portable, effective, low cost, and less susceptible to system noise have led to the rapid development of functional near-infrared spectroscopy (fNIRS) technology for hemodynamics detection, especially in the field of functional brain imaging. At the same time, laboratories and companies have developed various fNIRS-based systems. The safety, stability, and efficacy of fNIRS systems are key performance indicators. However, there is still a lack of comprehensive and systematic evaluation methods for fNIRS instruments. This study uses the fNIRS system developed in our laboratory as the test object. The test method established in this study includes system validation and performance testing to comprehensively assess fNIRS systems' reliability. These methods feature low cost and high practicality. Based on this study, existing or newly developed systems can be comprehensively and easily evaluated in the laboratory or workspace.

Evaluating Rainwater Harvesting Systems for Water Scarcity Mitigation in Small Greek Islands under Climate Change

Rainfall variability, exacerbated by climate change, poses significant challenges to water resource management, particularly in regions prone to intense droughts and floods. The Greek islands, characterized by poor water potential, face interannual water supply issues dating back to their earliest habitation. Rainwater harvesting (RWH) systems emerge as a promising solution to address water scarcity in these regions. This study simulates RWH systems for two small Greek islands, Fourni and Nisyros, representing similar rainfall regimes. Multiple scenarios are explored, and system reliability is assessed in light of simulated daily rainfall time series incorporating climate change projections. Utilizing eight low/medium (RCP 4.5) and eight high (RCP 8.5) emission scenarios over a future 35-year period, the study evaluates system reliability based on model parameters (collection area: 40 to 140 m2, rainwater tank volume: 5 to 30 m3, number of household members: 2, 3), with 30% coverage of total daily water demand (180 L/d). Negligible evapotranspiration effects are assumed due to closed-type tanks. Results indicate that the RWH system demonstrates high efficiency in general. The investigation for the future period revealed that the system’s performance varies, with instances where daily demand targets are not met, even with a 30 m3 tank. This research underscores the potential of RWH systems as a cost-effective “green” solution, particularly in regions with deficient rainfall regimes. It highlights the importance of localized water management strategies, reducing reliance on mainland water transportation, and assisting desalination unit operations. In conclusion, this study contributes to the assessment of RWH systems, demonstrating their viability as a sustainable water management solution in regions facing water scarcity, contingent on local rainfall conditions and system design parameters.