Design Process Of Complex Systems Research Articles

Monitoring Environmental Performance During the Design Process of a Complex System

A large part of impacts that will be generated by a system / product during its life cycle are allocated during the earliest stages of the design process. In this paper we propose to trace the evolution of environmental impacts throughout a complex system design process through an industrial case. We follow the stages of a boat design process for maintenance of offshore wind farms. The different architectures sketched throughout the design process are evaluated in order to measure the impact of design decisions on the environmental performance of the system. The problematic of taking into account environmental constraints upstream of the design process abound methods but they often prove inadequate for complex systems whose subsystems interact in complex ways leading to conflicts in the decision of the right parameters. To meet the stakeholders’ needs, that appear (during the design project) in the iterative design process, the initial design is modified to fit the specifications. This iterative path between designers and users leads to uncertainties over the environmental impact of the system. It is then necessary to use smart design support tools allowing a negotiation in definition phase of system specifications. Thus the preliminary design is modified to incorporate changes and contributions occurred during the negotiation phase functional.

On Risk-Based Design of Complex Engineering Systems: An Analytical Extreme Event Framework

In this work, a novel analytical framework is proposed for the risk-based design of complex engineering systems. The risk based-design process is the reverse process of risk propagation that entails the optimum allocation of the desired risk of failure of the system to all of its components. This paper studies the challenges in the design process of complex systems, the mathematical modeling of their topological architecture, and their unique behaviors. These characteristics make it impossible for the designer to use the common reliability and risk methodologies in the design process. The fundamental development of this work is an analytical upper bound for the distribution of risk of failure in the subsystem or element level. This upper bound satisfies the subadditivity condition of a coherent measure of risk. Additionally, its simplicity and low computational cost provide an appropriate framework as a fundamental building block for the risk-based design of complex systems. The proposed methodology is applied to three examples with insignificant desired probability of failure and its accuracy is compared with the Monte Carlo simulation, demonstrating its effectiveness and value.

Multi-level design of an isolation transformer using collaborative optimization

Purpose – The purpose of this paper is to present an application of a multidisciplinary multi-level design optimization methodology for the optimal design of a complex device from the field of electrical engineering throughout discipline-based decomposition. The considered benchmark is a single-phase low voltage safety isolation transformer. Design/methodology/approach – The multidisciplinary optimization of a safety isolation transformer is addressed within this paper. The bi-level collaborative optimization (CO) strategy is employed to coordinate the optimization of the different disciplinary analytical models of the transformer (no-load and full-load electromagnetic models and thermal model). The results represent the joint decision of the three distinct disciplinary optimizers involved in the design process, under the coordination of the CO's master optimizer. In order to validate the proposed approach, the results are compared to those obtained using a classical single-level optimization method – sequential quadratic programming – carried out using a multidisciplinary feasible formulation for handling the evaluation of the coupling model of the transformer. Findings – Results show a good convergence of the CO process with the analytical modeling of the transformer, with a reduced number of coordination iterations. However, a relatively important number of disciplinary models evaluations were required by the local optimizers. Originality/value – The CO multi-level methodology represents a new approach in the field of electrical engineering. The advantage of this approach consists in that it integrates decisions from different teams of specialists within the optimal design process of complex systems and all exchanges are managed within a unique coordination process.

Advances and computational tools towards predictable design in biological engineering.

The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated.

Applying Constraint Programming to Incorporate Engineering Methodologies into the Design Process of Complex Systems

When designing a complex system, adhering to a design methodology is essential to ensure design quality and to shorten the design phase. Until recently, enforcing this could be done only partially or manually. This paper demonstrates how constraint programming technology can enable automation of the design methodology support when the design artifacts reside in a central repository. At any phase of the design, the proposed constraint programming application can indicate whether the design process data complies with the methodology and point out any violations that may exist. Moreover, the application can provide recommendations regarding the design process. The application was successfully used to check the methodology conformance of an industrial example and produced the desired outputs within reasonable times.

CFD optimization for GDI spray model tuning and enhancement of engine performance

► Two examples of CFD based optimization in the design of a GDI SI engine are given. ► The Simplex algorithm is used to automatically validate a GDI spray model. ► Portability of the model to three different GDI multi-hole injectors is proven. ► Optimization of the mixture formation to minimize a GDI engine consumption is also realized. ► Optimal double injection reduces fuel consumption more than single injections. Coupling a 3D Computational Fluid Dynamics (CFD) tool with a rigorous method of decision making is becoming indispensable in the design process of complex systems, as internal combustion engines. CFD based optimization (CFD-O) is here carried out on a single cylinder, four-valve, four-stroke gasoline direct injection (GDI) engine, to enhance mixture formation under stratified charge operation, hence to choose between the single or double injection strategy maximizing the engine power output. A 3D engine model is coupled with the Simplex algorithm to find the optimal synchronization of both injection and spark timing within the working cycle. CFD-O is also addressed to perform the validation of the gasoline spray model, that otherwise reveals tedious and time-consuming. The Simplex algorithm is used to tune the constants entering a model developed by authors, as applied to three different high pressure GDI injectors, preliminary experimentally characterized. Fully automatic procedures are assessed to be exploited in the phase of engine design, whose contribution may be of great importance to reduce development costs and time-to-market of new technologies.

A SysML-Based Methodology for Manufacturing Machinery Modeling and Design

This paper describes a modeling methodology to support the design process of complex systems. The main challenge in modern industrial applications is the sheer volume of data involved in the design process. While using high-level abstraction is necessary to manage this data and analyze the system “as a whole,” designers need also to retain all the low-level information of the system, in order to be able to perform optimizations and modifications at later times. The solution proposed here is to use a hierarchy of models, each one describing the system at different levels of abstraction, and arrange them in such a way that it is possible to easily “map” each level onto the others. The topmost layer of the system description is expressed in System Modeling Language, a general-purpose modeling language based on Unified Modeling Language.

Throughput-Oriented NoC Topology Generation and Analysis for High Performance SoCs

This paper presents a new approach to the design and analysis of NoC topologies which is based on the transaction-oriented communication methods of on-chip components. We propose two algorithms that attempt to meet the communication requirement of an on-chip application using a minimum number of network resources for the task, by generating application-specific topologies. In addition, to aid the design process of complex systems, the design method incorporates a form of predictive analysis which can estimate the degree of contention in a given system without performing detailed simulation. This predictive analysis method is used to determine the minimum frequency of operation for generated topologies, and is incorporated into the topology generation process. The proposed design method was tested using real-word applications, including an MPEG4 decoder and a multi-window display application. The generated topologies were found to offer similar or better performance when compared with regular topologies. However, the topologies generated by our method were more economical, using, on average, half the network resources of regular topologies.

SOFTWARE FRAMEWORK FOR THE APPROACH: COMPUTER AIDED SAFETY INTEGRATION IN DESIGN PROCESS (CASID)

Nowadays, safety is often integrated at too late a stage in the design process of complex systems, such as machines or production lines. In most cases, this integration is made on an individual basis without any systematic method. Moreover, there are very few computer-aided software packages that allow the integration of safety aspects into the design process. In this paper, we present propositions of a model working situation using (UML).1 This model is implemented by prototype software called Computer Aided Safety Integration in Design process (CASID). The CASID approach is founded on a database in which all previous data generated by the designer using CASID is stored; furthermore, the software allows communication between designers in order to solve safety problems.

Local Pareto approximation for multi-objective optimization

The design process of complex systems often resorts to solving an optimization problem, which involves different disciplines and where all design criteria have to be optimized simultaneously. Mathematically, this problem can be reduced to a vector optimization problem. The solution of this problem is not unique and is represented by a Pareto surface in the objective function space. Once a Pareto solution is obtained, it may be very useful for the decision-maker to be able to perform a quick local approximation in the vicinity of this Pareto solution for sensitivity analysis. In this article, new linear and quadratic local approximations of the Pareto surface are derived and compared to existing formulas. The case of non-differentiable Pareto points (solutions) in the objective space is also analysed. The concept of a local quick Pareto analyser based on local sensitivity analysis is proposed. This Pareto analysis provides a quantitative insight into the relation between variations of the different objective functions under constraints. A few examples are considered to illustrate the concept and its advantages.

Designing infrastructures using a complex systems perspective

Networked infrastructures are complex socio-technical systems. Their complexity shows in the physical networks, in the actor networks, and the combination thereof. This paper addresses the question, 'how should the design of these systems be undertaken?' Both for physical networks and for actor networks, design processes exist that can be applied separately. For integrated networks, however, an integrated approach is proposed. Three case studies are discussed concerning the design of a district heating system, a gas network and a seaport development, respectively. It is concluded that the integrated socio-technical complex system design process proposed has merit for networked infrastructures.

Decoupled approach to multidisciplinary design optimization under uncertainty

We propose solution methods for multidisciplinary design optimization (MDO) under uncertainty. This is a class of stochastic optimization problems that engineers are often faced with in a realistic design process of complex systems. Our approach integrates solution methods for reliability-based design optimization (RBDO) with solution methods for deterministic MDO problems. The integration is enabled by the use of a deterministic equivalent formulation and the first order Taylor’s approximation in these RBDO methods. We discuss three specific combinations: the RBDO methods with the multidisciplinary feasibility method, the all-at-once method, and the individual disciplinary feasibility method. Numerical examples are provided to demonstrate the procedure.

A web-based simulation game as a learning tool for the design process of complex systems

While relational simulation games have been widely used for learning activities in areas such as business, management and communication, their development in the engineering field is still very limited. In this paper a web-based simulation game was designed in order to fill this existing gap in the development of relational simulation games related to engineering aspects and in particular to the design process of complex systems. An evaluation of a first web trial competition, carried out by questionnaires, shows a satisfactory achievement of the proposed learning tool objectives.

Neural network based tools for uncertainty management with applications to control system design

Almost all kinds of men’s activities associated with design, manufacturing and maintenance of complex systems consist of two main classes of problems: a generation of decision alternative set allowed for situation studied and decision making, i.e. choice of some decision alternative from the set of allowed ones. A role of various kind of uncertainties related to complex system design process is discussed founding on intelligent flight control system design example. A mixed information technology is used to solve this problem basing on mathematical modeling, multi-purpose system methodology and artificial neural networks. This is very promising approach for a solving not only FCS gain scheduling problem, but another kinds of FCS synthesis problems. The approach promises also to ensure effective technical decision generation and making tool for problem solving with various kind of uncertainties involved.

Designing the automatic transformation of visual languages

The design process of complex systems requires a precise checking of the functional and dependability attributes of the target design. The growing complexity of systems necessitates the use of formal methods, as the exhaustiveness of checks performed by the traditional simulation and testing is insufficient. For this reason, the mathematical models of various formal verification tools are automatically derived from UML-diagrams of the model by mathematical transformations guaranteeing a complete consistency between the target design and the models of verification and validation tools. In the current paper, a general framework for an automated model transformation system is presented. The method starts from a uniform visual description and a formal proof concept of the particular transformations by integrating the powerful computational paradigm of graph transformation, planner algorithms of artificial intelligence, and various concepts of computer engineering.