Felician Campean

A comparison of two methods of analysing staircase fatigue test data

When the fatigue strength of components or material is tested by the staircase or up-and-down method, the data can be analysed in either the fatigue strength domain, which is the most popular approach, or the life domain, based on life regression models. In this paper we exploit a simple relationship between families of models in the two domains to obtain an estimate of the distribution of fatigue strength directly from a fitted life regression model. We use simulation to compare the two approaches, concluding that for estimating important features of the fatigue strength distribution the method of maximum likelihood is more effective if it is applied in the life domain. In particular, it is more robust to the choice of xh, the step height of the staircase, provided xh is in the range σX–2σX, where σX is the standard deviation of the log-strengths. Most of our results are insensitive to the value of the initial stress amplitude. Copyright

PermGA algorithm for a sequential optimal space filling DoE framework

This paper presents the development and implementation of a customised Permutation Genetic Algorithm (PermGA) for a sequential Design of Experiment (DoE) framework based on space filling Optimal Latin Hypercube (OLH) designs. The work is motivated by multivariate engineering problems such as engine mapping experiments, which require efficient DoE strategies to minimise expensive testing. The DoE strategy is based on a flexible Model Building - Model Validation (MB-MV) sequence based on space filling OLH DoEs, which preserves the space filling and projection properties of the DoEs through the iterations. A PermGA algorithm was developed to generate MB OLHs, subsequently adapted for generation of infill MV test points as OLH DoEs, preserving good space filling and projection properties for the merged MB + MV test plan. The algorithm was further modified to address issues with non-orthogonal design spaces. A case study addressing the steady state engine mapping of a Gasoline Direct Injection was used to illustrate and validate the practical application of MB-MV sequence based on the developed PermGA algorithm.

A Structured Approach for Function Based Decomposition of Complex Multi-disciplinary Systems

The aim of this paper is to introduce the Systems State Flow Diagram as a structured approach to high level solution-independent function based decomposition of a complex multi-disciplinary system. The approach is discussed in the context of existing function modelling frameworks and in relation to current practice in industry. A generic case study is used to introduce the approach and to highlight the salient features, followed by an illustration on its application to the analysis of an electric vehicle powertrain. Experience with the practical application of the approach with engineering teams is discussed.

Ergonomic Data Measuring System for Driver-Pedals Interaction

This paper presents the design and development of an ergonomic data measurement system for driver–pedals interaction. The work focuses in particular on the actuation of the acceleration and brake pedals, and aims to support the development of a deeper understanding of the factors influencing the driving comfort associated with the right leg. The ergonomic data measurement system integrates five subsystems: an electrogoniometry system and a pressure-pads system to monitor driver’s positioning and movements, an electromiography system to observe the muscular activity of the lower leg, the vehicle on-board diagnostic system, a GPS system and an audio-visual system for providing environment and driving situation information. A validation exercise involving a series of test drive events confirmed the system capability to record meaningful objective comfort data which can differentiate between driving postures and styles.

Reliability-inspired species conservation for multimodal functions

Species Mutation technique, inspired from reliability design, is combined with a species conserving genetic algorithm (SCGA) to solve multimodal optimization problems. In reliability design, in order to improve system reliability and safety requirements, a redundancy component is added to a most efficient subsystem, in which the ratio of the increase of reliability to the increase of resources is maximal. This idea is introduced into the SCGA and a proper species is selected for mutation in order to maximally improve the SCGA efficiency. After each generation, the SCGA will determine species from populations and find the solutions from species. Species mutation mutates a selected species. Some numerical tests show that this simple technique can greatly decrease objective evaluations for the SCGA in searching solutions of the test problems.

Simultaneous Uniform DoEs for Model Building and Validation in the Multidisciplinary Optimization Framework

In this paper two optimum Latin Hypercube (OLH) DOEs are constructed simultaneously, these are used in metamodeling as a model building set and a model validation set. In each case the goal is to optimize the uniformity of both sets with respect to the space-filling properties of the designs. A key concept is that the merged DOE, which comprises the union of the build and validation sets, also has good space-filling properties. A permutation Genetic Algorithm (PermGA) with a variety of genetic operator strategies has been implemented. The evaluation of fitness is based upon the Audze-Eglais potential energy function. The relative efficiency of various strategies for implementing the concept and the associated computational aspects are discussed with respect to the quality of designs obtained.

Application of permutation genetic algorithm for sequential model building---model validation design of experiments

The work presented in this paper is motivated by a complex multivariate engineering problem associated with engine mapping experiments, which require efficient design of experiments (DoE) strategies to minimise expensive testing. The paper describes the development and evaluation of a Permutation Genetic Algorithm (PermGA) to enable an exploration-based sequential DoE strategy for complex real-life engineering problems. A known PermGA was implemented to generate uniform OLH DoEs, and substantially extended to support generation of model building–model validation (MB–MV) sequences, by generating optimal infill sets of test points as OLH DoEs that preserve good space-filling and projection properties for the merged MB + MV test plan. The algorithm was further extended to address issues with non-orthogonal design spaces, which is a common problem in engineering applications. The effectiveness of the PermGA algorithm for the MB–MV OLH DoE sequence was evaluated through a theoretical benchmark problem based on the Six-Hump-Camel-Back function, as well as the Gasoline Direct Injection engine steady-state engine mapping problem that motivated this research. The case studies show that the algorithm is effective in delivering quasi-orthogonal space-filling DoEs with good properties even after several MB–MV iterations, while the improvement in model adequacy and accuracy can be monitored by the engineering analyst. The practical importance of this work, demonstrated through the engine case study, is that significant reduction in the effort and cost of testing can be achieved.

A framework for complex product architecture analysis using an integrated approach

Contemporary design decomposition and synthesis analytical tasks at the conceptual design stage rely on functional and structural modelling approaches. There is a wide diversity of elements used by various modelling approaches for information and representation of product architecture, which incurs difficulties for multidisciplinary engineers working across different phases of design in capturing, visualising, sharing and tracing consistent yet common knowledge and elements across the function and structure domains. This prompts for fixation of detail and common modelling knowledge across both functional and structural analytical approaches which are also critical from automatised software perspective. A limitation of the existing approaches is that they tend to focus more on ‘what’ and less on ‘how’ (and vice versa). This article proposes an integrated conceptual product architecting approach that combines and expands the functional and structural modelling approaches, enabling capturing and tracing knowledge coherently through a common binding domain. This is underpinned by the view that most interaction requirements among the physical components during structural modelling can be derived from functional modelling. The proposed integrated approach is underpinned by the critical analysis and synthesis of the existing approaches in the literature dealing with functional and structural architecture analyses, integrated within a multiple domain matrix to fuse the knowledge of both solution-independent (functional) and solution-dependent (structural) analyses. The proposed framework is illustrated with a case study of solar robot toy, followed by discussion and suggestions for future work.

Function-Based Conceptual Design Expert (CDE) Systems: Development Trend and Gaps Identification

This paper presents an overview of existing function-based conceptual design expert (CDE) systems with a view to identifying their scope in the contexts of functional modeling knowledge representation and conceptual design process. A number of heterogeneous function-based CDE systems are identified and listed. A key comprehensive benchmarking framework is developed in this paper that helps in identifying the trend, gaps and scope of current function-based CDE systems. Accordingly, the gaps in the aforementioned contexts are discussed which are to date have not been summarized and highlighted for a well-balanced system development for a product conceptual design.

SYNTHESIS OF FUNCTIONAL MODELS FROM USE CASES USING THE SYSTEM STATE FLOW DIAGRAM: A NESTED SYSTEMS APPROACH

The research presented in this paper addresses the challenge of developing functional models for complex systems that have multiple modes of operation or use cases. An industrial case study of an electric vehicle is used to illustrate the proposed methodology, which is based on a systematic modelling of functions through nested systems using the system state flow diagram (SSFD) method. The paper discusses the use of SSFD parameter based state definition to identify physical and logical conditions for joining function models, and the use of heuristics to construct complex function models.