Special Section on Reliability Modeling and Assessment of Complex Engineering Systems with Mixed Uncertainty

The seven papers included in this special section focus on reliability, resilience, and prognostics modeling of complex engineering systems. This topic has become very challenging due to factors such as complex physical interdependence and functional interactions among mechanical, electrical, software, and control subsystems, as well as the interactions with external environments. The difficulties of modeling the reliability and resilience as well as system performance prognostics of complex engineering system have been observed from many perspectives, e.g., 1) the schedule delays and cost overruns of major government and industry commercial programs, and 2) the challenges when planning and managing recovery activities of critical infrastructure damaged due to extreme events. When multiple sources of information and disparate data are available, how to monitor, model, and predict the system resilience and reliability over time of complex engineering systems becomes essential and critical for safe, reliable, resilient, and economic operations of most cyber-physical systems.

Complex decision making is an important aspect in planning large man-made systems. These systems tend to be of high complexity, which requires an automated, intelligent approach to realize all dimensions of the problem. Decision Support Systems (DSS) are one approach to automate this process by providing modeling and analytical capabilities that assist users in making decisions. In this paper, we present the architecture of a web-based DSS platform for multidimensional modeling (including functional, spatial, and temporal dimensions) of complex engineering systems. We describe the breakdown of the modeling process of such systems in a multidimensional hierarchical manner. We present a case study for power planning in Saudi Arabia.

Reliability modelling and assessment of organic Rankine cycle-based Carnot battery systems with dynamic regulation modes

An important aspect of modern engineering systems is their great diversity. Often they include interactions among different physical domains, contain control subsystems, and are large-scale and complex. The bond graph is a powerful and versatile tool that can help the engineer to design modern engineering systems. Three issues are explored from a bond graph perspective: modeling of engineering systems, simulation of their behavior, and teaching about engineering systems. It is the author’s observation that bond graph methodology is one of the most useful engineering system techniques available and belongs in the problem-solving tool kit of every mechanical engineer. This paper develops a rationale for this viewpoint both for readers familiar with bond graph methods and for readers to whom they are new.

An approach to modeling and thermodynamic analysis of modern power engineering systemsThe new efficient method of modeling and thermodynamic analysis of power engineering systems has been presented. With its help a comparison of different structures and investigation of the influence of a particular constituent process onto the whole system efficiency is possible. The shaft work or the exergy is the main thermodynamic quantity taken into account in analyses, and the appropriate dimensionless modeling parameter has been introduced.

Computer modeling of engineering systems with a large number of interconnected multi degree of freedom (DOF) subsystems requires flexible modeling tools. Flexible modeling tools with arbitrary input-output structure formulate equations to fit the input-output structure of specific engineering systems at the cost of globally reformulating equations with every model change. Each equation formulation requires experimental performance verification. This can be particularly cumbersome in the design, development, and refinement of large models. In previous work Byam and Radcliffe designed modular modeling, a flexible modeling method that eliminates equation reformulation and enhances model experimental performance verification in large models. A fixed input-output structure for all multi DOF modular modeling elements eliminates equation reformulation. The cost is a connector constraint to assemble elements, thereby adding complexity to the global model. Solving linear modular models is a systematic realization of compatible standardized modular elements and connectors. In this work, a modular solution to linear models of engineering systems is defined. Structural and automotive examples are given.

This paper explores the impact of including component repair on the reliability modeling of all-digital protection systems. It is shown that repairable and nonrepairable assumptions make a remarkable difference in the computed reliability indices of the mean time to failure (MTTF) and the mean time to first failure (MTTFF). Theoretical analysis of basic system structures consisting of two components is first examined. Then, a typical all-digital protection system architecture is modeled and numerically analyzed. Some interesting results are found by comparing reliability indices of MTTF and MTTFF and explanations of these results are provided.

THE objective of this special section is to present imperative needs for important advances in developing quality/reliability engineering approaches to dependable information systems. As people increasingly rely on information systems to support critical operations in defense, banking, telecommunication, transportation, electric power, etc., the security & dependability of information systems are necessary. However, information systems have encountered many quality/reliability problems caused by both internal factors (e.g., system vulnerabilities) and external factors (e.g., intrusions by malicious hackers). Special characteristics of information systems have presented both considerable challenges and unique opportunities for researchers in the quality/reliability engineering. This special section will help researchers gain a better understanding of quality/reliability problems with information systems, and thus draw the attention and interest of researchers in this new frontier. Focus: • Design of software programs (including mobile code) and information infrastructures (including network architectures) to overcome security vulnerabilities of information systems. • Detection of intrusions into information systems, in a scalable & robust manner to provide early and reliable warnings. • Tolerance of intrusions and their negative impacts on information systems, to maintain the timely & correct functioning of information systems. Of special interest are research papers that extend conventional quality/reliability engineering theories & techniques, e.g.: • Statistical process control • Risk analysis and assessment • Probabilistic reasoning • Quality/reliability modeling of systems and activities • Engineering design for quality/reliability, or that apply innovative quality/reliability engineering approaches for these topics. Papers not falling in these topics but relating to quality/reliability engineering of information systems are also welcome.

The method for modeling reliability of systems with dependent failure when the life is measured by the number of loadings is developed.Dependent failure existing among components is considered,and reliability models of systems with dependent failure are derived through introducing the conditional reliability of systems.Taking the analysis of static strength failure and fatigue failure as the backgrounds,the models for calculating the reliability and failure rate of systems under repeated random load without strength degeneration and those with strength degeneration are derived respectively.Then,the relationship between the reliability of systems and the number of loadings,and that between the failure rate of systems and the number of loadings are discussed in different cases.The result shows that even though strength doesn't degenerate,both reliability and the failure rate of systems decrease as the number of loadings increases,and the failure rate curves have the partial characteristics of bathtub curve with early failure period and random failure period.When strength degenerates with the number of loadings,the reliability of systems decreases more obviously as the number of loadings,and the failure rate of systems decreases first and then increases as the number of loadings,showing the whole shape of bathtub curve.The models proposed can be applied to guiding the reliability design,reliability test and the whole lifecycle management of systems.

This paper proposes a complete set of dynamic reliability quantitative assessment method which is applicable to any type of relay protection system. First, taking into account the comprehensiveness and representativeness, choose the reliability assessment indexes for relay protection system. Secondly, establish the dynamic fault tree model of the relay protection system reliability and transform the dynamic fault tree into a failure matrix to achieve a standard expression of the dynamic fault tree. On this basis, the quantitative assessment of the relay protection system reliability is realized using Monte Carlo simulation combining the dynamic fault tree and Markov chain. And finally, the effectiveness of this method is verified through the analysis of a practical example. The proposed method allows maintenance personnel to master the weaknesses of the relay protection system, and then take appropriate preventive maintenance measures. It is of great significance to the operation and maintenance of the system.

Differential equations serve as foundational tools in the modeling and analysis of dynamic mechanical systems. Their application spans various mechanical engineering domains, including vibrations, heat transfer, fluid mechanics, and structural analysis. This paper explores the role of ordinary and partial differential equations in representing physical laws governing mechanical systems. Analytical and numerical approaches to solving these equations are examined, and real-world applications are highlighted. The integration of modern computational techniques is also discussed, offering insights into the future of differential equation modeling in mechanical engineering.

Established reliability modelling and analysis techniques are not readily extended to address whole systems which include software — it is difficult to incorporate software elements of a system within reliability block diagrams and no means of predicting the reliability of software elements has become established. An approach has been developed based on the technique of functional thread analysis — borrowed from software structured analysis and design methods — which allows reliability modelling and analyses of entire software intensive systems to be initiated from early in the system development.

Availability of fast computer resources nowadays has facilitated more in-depth modeling of complex engineering systems which involve strong multiphysics interactions. This multiphysics modeling is an important necessity in nuclear reactor safety studies where efforts are being made worldwide to combine the knowledge from all associated disciplines at one place to accomplish the most realistic simulation of involved phenomenon. On these lines coupled modeling of nuclear reactor neutron kinetics, fuel heat transfer and coolant transport is a regular practice nowadays for transient analysis of reactor core. However optimization between modeling accuracy and computational economy has always been a challenging task to ensure the adequate degree of reliability in such extensive numerical exercises. Complex reactor core modeling involves estimation of evolving 3-D core thermal state, which in turn demands an expensive multichannel based detailed core thermal hydraulics model. A novel approach of power weighted coupling between core neutronics and thermal hydraulics presented in this work aims to reduce the bulk of core thermal calculations in core dynamics modeling to a significant extent without compromising accuracy of computation. Coupled core model has been validated against a series of international benchmarks. Accuracy and computational efficiency of the proposed multiphysics model has been demonstrated by analyzing a reactivity initiated transient.

The scope of this work is to enhance the reliability of three dimensional finite element (FE) models for modal analysis of engine-transmission of vehicles taking into account uncertainties. Uncertainty sources may be due to the system characteristics such as geometry, material behavior, boundary conditions and mesh density or as results of assumptions made during the modeling. To this end, the natural frequencies of the entire unit are computed numerically using a 3D FE model and compared to experimental results obtained from the non-contact experimental modal analysis using Laser Doppler Vibrometer (LDV). Essential experiences and knowledge are collected from primary experimental investigations on single and bolted joints beam-like components. This helps to identify uncertainty sources and limitations in FE modeling. Finally, uncertainties due to the initial torque of bolted connections and boundary conditions associated to the unit are considered. The FE model then is updated to achieve accurate results compared to experimental data. In addition to accomplish a reasonable accurate model for the investigated system, the gained experiences and results in this paper can be employed as general guidance and references for FE modeling of real complex engineering systems.

Industrial companies are the largest electric power consumers in our country (about 60% of all generated power). Mining companies are key to the budget formation of the Republic of Sakha (Yakutia). They are, at the same time, very energy intensive. For instance, diamond, gold, and coal mining companies consume about 75% of all the generated power. Therefore, energy-saving technologies are getting more popular in designing the electric power systems for such enterprises. When designing electric power supply and drive systems for an industrial company, it is necessary to perform a lot of calculations and analyze a large number of diagrams. This process can be significantly simplified through the use of computer modeling software. During the design stage, it is safe to make mistakes in a computer model because the program can always identify the parameter or element that caused the problem. Currently, specific programs designed for the modeling of complex engineering systems can boast modeling accuracies of 90-95%. MatLab is one of such programs that can help develop both mathematical and physical models. Modeling uses real-life specifications of production plants and industrial companies. Modeling can provide information on such physical parameters of the electric power system as the current, voltage, and power levels, short-circuit currents, load schedules, quality of electricity, and deviations of modeled parameter values from the calculated ones, etc. Based on the calculations performed, we can provide recommendations for the power supply services of industrial companies and deploy energy-saving technologies.