Flow State Logic (FSL) for Analysis of Failure Propagation in Early Design

Author(s):  
David Jensen ◽  
Irem Y. Tumer ◽  
Tolga Kurtoglu

For safety critical complex systems, reliability and risk analysis are important design steps. Implementing these analyses early in the design stage can reduce costs associated with redesign and provide important information on design viability. In the past several years, various research methods have been presented in the design community to move reliability analysis into the early conceptual design stages. These methods all use a functional representation as the basis for reliability analysis. This paper asserts that, in non-nominal system states, the functional representation limits the scope of failure analysis. Specifically, when failures are modeled to propagate along energy, material, and signal (EMS) flows, a nominal-state functional model is insufficient for modeling all types of failures. To capture possible failure propagation paths, a function-based reliability method must consider all potential flows, and not be limited to the function structure of the nominal state. In this light, this paper introduces the Flow State Logic (FSL) method as a means for reasoning on the state of EMS flows that allows the assessment of failure propagation over potential flows that were not considered in a functional representation of a “nominally functioning” design. A liquid fueled rocket engine serves as a case study to illustrate the benefits of the methodology.

Author(s):  
Zhen Hu ◽  
Xiaoping Du

Fatigue damage analysis is critical for systems under stochastic loadings. To estimate the fatigue reliability at the design level, a hybrid reliability analysis method is proposed in this work. The First Order Reliability Method (FORM), the inverse FORM, and the peak distribution analysis are integrated for the fatigue reliability analysis at the early design stage. Equations for the mean value, the zero upcrossing rate, and the extreme stress distributions are derived for problems where stationary stochastic processes are involved. Then the fatigue damage is analyzed with the peak counting method. The developed methodology is demonstrated by a simple mathematical example and is then applied to the fatigue reliability analysis of a shaft under stochastic loadings. The results indicate the effectiveness of the proposed method in predicting fatigue damage and reliability.


Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1820
Author(s):  
Mohamed El Amine Ben Seghier ◽  
Behrooz Keshtegar ◽  
Hussam Mahmoud

Reinforced concrete (RC) beams are basic elements used in the construction of various structures and infrastructural systems. When exposed to harsh environmental conditions, the integrity of RC beams could be compromised as a result of various deterioration mechanisms. One of the most common deterioration mechanisms is the formation of different types of corrosion in the steel reinforcements of the beams, which could impact the overall reliability of the beam. Existing classical reliability analysis methods have shown unstable results when used for the assessment of highly nonlinear problems, such as corroded RC beams. To that end, the main purpose of this paper is to explore the use of a structural reliability method for the multi-state assessment of corroded RC beams. To do so, an improved reliability method, namely the three-term conjugate map (TCM) based on the first order reliability method (FORM), is used. The application of the TCM method to identify the multi-state failure of RC beams is validated against various well-known structural reliability-based FORM formulations. The limit state function (LSF) for corroded RC beams is formulated in accordance with two corrosion types, namely uniform and pitting corrosion, and with consideration of brittle fracture due to the pit-to-crack transition probability. The time-dependent reliability analyses conducted in this study are also used to assess the influence of various parameters on the resulting failure probability of the corroded beams. The results show that the nominal bar diameter, corrosion initiation rate, and the external loads have an important influence on the safety of these structures. In addition, the proposed method is shown to outperform other reliability-based FORM formulations in predicting the level of reliability in RC beams.


Author(s):  
Daniel Krus ◽  
Katie Grantham Lough

When designing a product, the earlier the potential risks can be identified, the more costs can be saved, as it is easier to modify a design in its early stages. Several methods exist to analyze the risk in a system, but all require a mature design. However, by applying the concept of “common interfaces” to a functional model and utilizing a historical knowledge base, it is possible to analyze chains of failures during the conceptual phase of product design. This paper presents a method based on these “common interfaces” to be used in conjunction with other methods such as Risk in Early Design in order to allow a more complete risk analysis during the conceptual design phase. Finally, application of this method is demonstrated in a design setting by applying it to a thermal control subsystem.


2014 ◽  
Vol 136 (3) ◽  
Author(s):  
C. Jiang ◽  
G. Y. Lu ◽  
X. Han ◽  
R. G. Bi

Compared with the probability model, the convex model approach only requires the bound information on the uncertainty, and can make it possible to conduct the reliability analysis for many complex engineering problems with limited samples. Presently, by introducing the well-established techniques in probability-based reliability analysis, some methods have been successfully developed for convex model reliability. This paper aims to reveal some different phenomena and furthermore some severe paradoxes when extending the widely used first-order reliability method (FORM) into the convex model problems, and whereby provide some useful suggestions and guidelines for convex-model-based reliability analysis. Two FORM-type approximations, namely, the mean-value method and the design-point method, are formulated to efficiently compute the nonprobabilistic reliability index. A comparison is then conducted between these two methods, and some important phenomena different from the traditional FORMs are summarized. The nonprobabilistic reliability index is also extended to treat the system reliability, and some unexpected paradoxes are found through two numerical examples.


2012 ◽  
Vol 236-237 ◽  
pp. 344-349
Author(s):  
Xiao Feng Yin ◽  
Jing Xing Tan ◽  
Xiu Ting Wu ◽  
Zhi Jun Gong

To improve the timing related performance of the embedded software of automotive control system, a performance modeling language has been developed based on UML (Unified Modeling Language) using meta-modeling technique. The proposed language consists of three kinds of meta-models used to define the high-level modeling paradigms for software structure, target platform and runtime system respectively. The modeling environment configured by the proposed language and software modules of functional model importation, components allocation, task forming and timing analysis can reuse the existing functional models, add timing requirement as well as resource constraints, and fulfill formal timing analysis at an early design stage. As results, the reliability of the automotive embedded control software can be improved and the development cycle and cost can also be reduced.


Author(s):  
Zunling Du ◽  
Yimin Zhang

Axial piston pumps (APPs) are the core energy conversion components in a hydraulic transmission system. Energy conversion efficiency is critically important for the performance and energy-saving of the pumps. In this paper, a time-varying reliability design method for the overall efficiency of APPs was established. The theoretical and practical instantaneous torque and flow rate of the whole APP were derived through comprehensive analysis of a single piston-slipper group. Moreover, as a case study, the developed model for the instantaneous overall efficiency was verified with a PPV103-10 pump from HYDAC. The time-variation of reliability for the pump was revealed by a fourth-order moment technique considering the randomness of working conditions and structure parameters, and the proposed reliability method was validated by Monte Carlo simulation. The effects of the mean values and variance sensitivity of random variables on the overall efficiency reliability were analyzed. Furthermore, the optimized time point and design variables were selected. The optimal structure parameters were obtained to meet the reliability requirement and the sensitivity of design variables was significantly reduced through the reliability-based robust design. The proposed method provides a theoretical basis for designers to improve the overall efficiency of APPs in the design stage.


Author(s):  
David C. Jensen ◽  
Irem Y. Tumer ◽  
Tolga Kurtoglu

Software-driven hardware configurations account for the majority of modern complex systems. The often costly failures of such systems can be attributed to software specific, hardware specific, or software/hardware interaction failures. The understanding of the propagation of failures in a complex system is critical because, while a software component may not fail in terms of loss of function, a software operational state can cause an associated hardware failure. The least expensive phase of the product life cycle to address failures is during the design stage. This results in a need to evaluate how a combined software/hardware system behaves and how failures propagate from a design stage analysis framework. Historical approaches to modeling the reliability of these systems have analyzed the software and hardware components separately. As a result significant work has been done to model and analyze the reliability of either component individually. Research into interfacing failures between hardware and software has been largely on the software side in modeling the behavior of software operating on failed hardware. This paper proposes the use of high-level system modeling approaches to model failure propagation in combined software/hardware system. Specifically, this paper presents the use of the Function-Failure Identification and Propagation (FFIP) framework for system level analysis. This framework is applied to evaluate nonlinear failure propagation within the Reaction Control System Jet Selection of the NASA space shuttle, specifically, for the redundancy management system. The redundancy management software is a subset of the larger data processing software and is involved in jet selection, warning systems, and pilot control. The software component that monitors for leaks does so by evaluating temperature data from the fuel and oxidizer injectors and flags a jet as having a failure by leak if the temperature data is out of bounds for three or more cycles. The end goal is to identify the most likely and highest cost paths for fault propagation in a complex system as an effective way to enhance the reliability of a system. Through the defining of functional failure propagation modes and path evaluation, a complex system designer can evaluate the effectiveness of system monitors and comparing design configurations.


Author(s):  
Wensheng Wang ◽  
Liying Jin ◽  
Xi Sun ◽  
Jing Liu

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