Thermal Protection System (TPS) with thick tiles, low thermal conductivity, and a short re-entry stage stands as a critical element within reusable aircraft, whose reliability is related to the function and changes with their physical properties, external conditions, and degradation. Meanwhile, due to the limitation of testing resources, epistemic uncertainties stemming from the small samples are present in TPS reliability modeling. However, current TPS reliability modeling methods face challenges in characterizing the relationships among reliability and physical properties, external conditions, degradation, and epistemic uncertainties. Therefore, under the framework of belief reliability theory, a TPS reliability model is constructed, which takes into account the physical principle, external conditions, performance degradation, and epistemic uncertainties. A reliability simulation algorithm is proposed to calculate TPS reliability. Through a case study and comparison analysis, the proposed method is validated as more effective than the existing method. Additionally, reliability sensitivity analysis is conducted to identify the sensitive factors of reliability under the condition of small samples, through which suggestions are provided for TPS functional design and improvement.

This article reviews the development history of reliability testing, and points out the historical limitations of the existing reliability research paradigm, which is centered on the probability distribution of failure time. This paradigm is only applicable in situations with failure observation data and proves ineffective for the development of innovative products. Specifically, reliability indicators exhibit characteristics of small samples, dynamic behavior, and subjectivity, while quality characteristics are large-sample, static, and objective. Consequently, traditional reliability statistical testing has erroneously adopted the probability sampling acceptance methods for quality management. Moreover, accelerated life testing and accelerated degradation testing, due to their reliance on empirical acceleration models based on failure physics in micro dimensions, are not suitable for true system-level products with function requirements. This paper analyzes the necessity of reliability science experiments aimed at validating causal laws from the perspective of reliability science principles. Reliability experiments are then defined as controlled experiments intended for verification of opportunity causation laws between system margins and performance and performance requirements. The connotations of reliability experiments, including the clarity of laws, black-box epistemology, and opportunity causation, are explored, and fundamental principles for reliability experimental methods—system integration, classification judgement, and optimization equilibrium—are proposed. Furthermore, a model-centered spatiotemporal reliability verification and testing system is established based on the principles of reliability experiments, demonstrating that this system is the only one that is derived based on the connotation of reliability characteristic and meets engineering demands. Finally, the scope of application of reliability scientific experiments is discussed, and developmental ideas for the spatiotemporal reliability verification and testing system are proposed.

The Complementary Metal-Oxide Semiconductor (CMOS) image sensor is a critical component with the function of providing accurate positioning in many space application systems. Under long-time operation in space environments, there are radiation related degradation and various uncertainties affecting the positioning accuracy of CMOS image sensors, which further leads to a reliability reduction of CMOS image sensors. Obviously, the reliability of CMOS image sensors is related to their specified function, degradation, and uncertainties; however, current research has not fully described this relationship. In this paper, a comprehensive approach to reliability modelling of CMOS image sensors is proposed based on the reliability science principles. Firstly, the performance margin modelling of centroid positioning accuracy is conducted. Then, the degradation model of CMOS image sensors is derived considering the dark current increase induced by the total ionizing dose effects. Finally, various uncertainties are analyzed and quantified, and the measurement equation of reliability is proposed. A case study of a CMOS image sensor is conducted to apply the proposed method, and the sensitivity analysis can provide suggestions for design and use of CMOS image sensors to ensure reliability. A simulation study is conducted to present the advantages of the proposed comprehensive approach.