M. Rajabalinejad

Dynamic bounds coupled with Monte Carlo simulations

For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper describes a method to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely present monotonicity. For models exhibiting monotonic (decreasing or increasing) behavior, dynamic bounds (DB) are defined, which in a coupled Monte Carlo simulation are updated dynamically, resulting in a failure probability estimate, as well as a strict (non-probabilistic) upper and lower bounds. Accurate results are obtained at a much lower cost than an equivalent ordinary Monte Carlo simulation. In a two-dimensional and a four-dimensional numerical example, the cost reduction factors are 130 and 9, respectively, where the relative error is smaller than 5%. At higher accuracy levels, this factor increases, though this effect is expected to be smaller with increasing dimension. To show the application of DB method to real world problems, it is applied to a complex finite element model of a flood wall in New Orleans.

Application of the dynamic bounds method in the safety assessment of flood defences, a case study: 17th Street flood wall, New Orleans

In this paper we provide a computational framework for evaluation of reliability and safety assessment of infrastructures. It is based on the combined application of the dynamic bounds (DB) method and a probabilistic finite element model (FEM). The DB improves the computational efficiency of the FEM when calculating time-dependent failure analyses of coastal and offshore structures, and can speed up the simulation process by several orders of magnitude. Our approach is demonstrated here for an example problem, and shown to be the most efficient method in applications with a limited number of influential variables, which is true for geotechnical and coastal flood defence systems. It is applied to the 17th Street flood wall, a failing component of the flood defence system in New Orleans during Hurricane Katrina. The variation in soil parameters is a critical input in the reliability estimation of this structure, and the calculated probability of failure depends on these assumed values.

Modelling dependencies and couplings in the design space of meshing gear sets

This work presents a design methodology based on the combination of a set of compatibility equations for determining nominal tooth and cutter geometry and a set of tooth contact analysis equations for determining modified tooth surfaces and motion transmission laws. Both have been shown separately to lead to various optimisations, and some parametric subspaces of the designed gears are shown to be so weakly coupled that optimisations found individually may be superimposed, as shown in the case of the gear pair stiffness function, dynamical load factor, bending fatigue strength and pitting/ scoring resistance optimisation. This is in contrast to traditional strengthening methods, such as profile shifting, which invariably produce much stronger couplings and thereby trade-offs.

Operation, safety and human: Critical factors for the success of railway transportation

This paper focuses on three categories of performance indicators for railway transportation: the excellence of operation, system safety and human factors. These are among the most critical indicators for delivering high quality services. This paper discusses the main issues, challenges and future directions of public transportation on these themes.

A theory of complexity escalation and collapse for system of systems

In this paper we urge the creation of new managerial tools and techniques that are relevant to the complexity of todays system of systems (SOS). Normal modes of command and control systems cannot be effective under conditions where new constraints are added on a recurrent basis to the system of systems in response to emergent problems within the systems due to increased coupling introduced in component elements of the SOS. We present a first-step understanding of why unanticipated failures find more potential and more pathways to their occurrence when interventions in SOS operations, standards or processes are conducted without enough insight and without a care for basic laws of complexity. We then demonstrate a condition where the incremental changes actually lead to failure of the SOS to meet its performance parameters. We hope that this work set the foundation for exploring the effects of coupling across hierarchical levels of SOS.

A model based safety architecture framework for Dutch high speed train lines

This paper presents a model-based safety architecture framework (MBSAF) for capturing and sharing architectural knowledge of safety cases of safety-critical systems of systems (SoS). Whilst architecture frameworks in the systems engineering domain consider safety often as dependent attribute, this study focusses specifically on sharing architectural knowledge of safety cases between stakeholders and managing safety in systems development. For this purpose, we adapt the A3 architecture overview (A3AO) tool. The application is shown though the case study of Dutch high speed train lines and shows how to derive requirements from various stakeholders by carrying out iterative validations of the A3AOs. The implemented technique consists of systems modeling language-based (SysML) diagrams. Outcomes of the assessment lead to guidelines for two A3AOs. This results in increasing and effective interaction between stakeholders, more overview for managing safety complexity, more insight into finding required safety information, and therefore; an increasing efficiency in safety engineering.

A Bayesian framework for uncertainty formulation of engineering design proces

Uncertainties in the design process are investigated in this paper. A formal Bayesian method is presented for designers to quantify uncertainties in design process. The uncertainties are implemented in a decision support system that plays a key role in design of complex projects where a large and multidisciplinary team of engineers are involved. The proposed method produces the probability distribution function of the model score or uncertainty. Two example applications for design and empirical demonstrate application of the method.

Naive Fault Trees for Safety Evaluations in Early Project Phase

Naive Fault Trees (NFT) aim to extend the application of Fault Trees (FT) and make them appealing for system designers in the early project life cycle. NFT use input intervals and values to estimate the frequency of a top event. This extension facilitates the assignment of failure probability to basic events when exact data is difficult to find, unavailable or even not existent. The formulation of the problem and results are presented in this paper through an application to a real-world example. ed from different candidates contain ample information, which might not appear evident at first sight. The complexity of the situation requires an intelligent extraction of the information from the data. An analysis tool IndEvawas developed to handle this complexity and provide an accurate, detailed and reliable evaluation of inspection systems and personnel. Besides the plain evaluation regarding the fulfilment of the qualification requirements, critical test flaws as well as test block sections, which are likely to cause false positive indications can be identified. Statistic results display the dependency of the system performance on various parameters and parameter combinations to provide a clear picture of the performance. Country-specific evaluation standards can be applied and compared, especially with regard to the continuous improvement of the qualification methodology.

Dynamical Simulation and Calculation of the Load Factor of Spur Gears with Indexing Errors and Profile Modifications for Optimal Gear Design

The exact geometry of tooth meshing is incorporated into a dynamical non-linear model of the considered gear system, in consideration of the effect of pitch errors, tooth separation, DOF-coupling, and profile modifications. Various possible combinations of error distributions and profile corrections are applied to the gear model, which is simulated dynamically to calculate the load factor.

A Gaussian decision-support tool for engineering design process

Decision-making in design is of great importance, resulting in success or failure of a system (Liu et al., 2010; Roozenburg and Eekels, 1995; Spitas, 2011a). This paper describes a robust decision-support tool for engineering design process, which can be used throughout the design process in either the concept or knowledge space described in Hatchuel and Weil (2009). The tool is graphical and designed to communicate efficiently with different fields of expertise. It takes into account the Gaussian form of expert lack of certainty and generates the concept or model uncertainty which is necessary for a robust design. Recently, this tool was successfully used by an interdisciplinary design team consisting of different experience level and diverse design knowledge as described in this paper.