Mechatronics is the integration of different sciences and techniques of mechanical engineering, automatic control, electronics, and informatics. The rapid evolution of the market competitors requires the reduction of development time of a product while increasing the quality and performance. It is, therefore, necessary to increase the efficiency of the design process. To meet this need, simulation and, especially, virtual prototyping have become a key technology. It is difficult to find simulation tools are able to analyze multidependent systems of different areas. However, an environment that allows a simulation integrating multidisciplinary mechatronic systems is necessary. This paper describes a method of design and simulation of mechatronic systems. First, we identify the behavior model and its associated 3D geometric model. The behavior model is seen as a dynamic hybrid system of two coupled hybrid automata (operative part and control part). Then, we present OpenMASK and OpenModelica simulators, the IEEE1516 standard HLA and work related to this distributed architecture for simulation. In a top-down approach, we present our method and experiments to integrate HLA functionalities in these simulators and to distribute the modeling elements of mechatronic systems. Also, we propose extensions to integrate real-time for interactive simulations. Finally, we apply our approach on a representative example of a mechatronic system.

With today’s advanced measurement equipment for monitoring road condition, it is possible to measure road geometry at high precision within a large span of wavelengths. Detailed information about the roads’ longitudinal and lateral profiles, including macro texture, would in theory be sufficient for a realistic reproduction of road induced vibration and noise in a driving simulator. Especially, it would be possible to create a direct connection between the visual information of the road condition and the ride experience, which would increase the level of realism in the simulation. VTI has, during three years, performed an internal project called SHAKE with the aim to develop and implement models in VTI driving simulator III that use measured road data for generating realistic vibrations and audible road noise connected to the visual impression presented on the projection screen. This has indeed resulted in a more realistic driving experience, and a validation study with test persons driving both in the simulator and in the field has been undertaken. The OpenDRIVE standard is used as a framework for describing the road properties (e.g., visual, vibrations, and noise). For this purpose, some augmentations to the OpenDRIVE standard had to be made. This paper describes the technical implementations in the driving simulator, along with results from test drives on the implemented road sections.

Thanks to recent advances in computing power and speed, engineers can now generate a wealth of data on demand to support design decision-making. These advances have enabled new approaches to search multidimensional trade spaces through interactive data visualization and exploration. In this paper, we investigate the effectiveness and efficiency of interactive trade space exploration strategies by conducting human subject experiments with novice and expert users. A single objective, constrained design optimization problem involving the sizing of an engine combustion chamber is used for this study. Effectiveness is measured by comparing the best feasible design obtained by each user, and efficiency is assessed based on the percentage of feasible designs generated by each user. Results indicate that novices who watch a 5-min training video before the experiment obtain results that are not significantly different from those obtained by expert users, and both groups are statistically better than the novices without the training video in terms of effectiveness and efficiency. Frequency and ordering of the visualization and exploration tools are also compared to understand the differences in each group’s search strategy. The implications of the results are discussed along with future work.

Based on the problem of visualizing the potential energy of a two-degree-of-freedom spring-mass system restrained by an elastic string, several advancements to visualizing functions with constraints and inequalities of two variables are introduced. These innovations include logarithmically spacing level curves (either mapped on the surface or projected on the bottom plane) and the possibility of truncating the portions of the function surface that exceed above and below the bounding box—both allowing better detailing of certain regions of the function surface, in particular the minimum and maximum areas. By selectively displaying the surface patches that either intersect or not the top and/or bottom planes of the bounding box in a truncated representation, sets of inequalities of two variables can be represented graphically in a suggestive manner. Also proposed are a new approach to producing the gradient of the function as an arrow field mapped on the bottom of the plot box that uses a finite-difference scheme applied to the 2D image-space nodes of the function surface rather than the original 3D data, and a new way of displaying the color scale in 3D surface plots.

To improve the quality of design, reduce the cost of production, and shorten the cycle of product development, an effective system to manage and reuse existing design resources is established. A novel two-step algorithm based on integrated product information model is put forward to analyze the reusability of design resources. First, the global shape ignoring the interior details is compared with check if they belong to the same category. Then, the detailed feature shape is compared with catch, the exact reusable design resources. Finally, a case study proves that the proposed method has higher accuracy.

It is well recognized that 3D finite element analysis is inappropriate for analyzing thin structures such as plates and shells. Instead, a variety of highly efficient and specialized 2D methods have been developed for analyzing such structures. However, 2D methods pose serious automation challenges in today’s 3D design environment. Specifically, analysts must manually extract cross-sectional properties from a 3D computer aided design (CAD) model and import them into a 2D environment for analysis. In this paper, we propose two efficient yet easily automatable dual representation methods for analyzing thin plates. The first method exploits standard off-the-shelf 3D finite element packages and achieves high computational efficiency through an algebraic reduction process. In the reduction process, a 3D plate bending stiffness matrix is constructed from a 3D mesh and then projected onto a lower-dimensional space by appealing to standard 2D plate theories. In the second method, the analysis is carried out by integrating 2D shape functions over the boundary of the 3D plate. Both methods do not entail extraction of the cross-sectional properties of the plate. However, the user must identify the plate or thickness direction. The proposed methodologies are substantiated through numerical experiments.

A knowledge-based computer-aided design tool for microelectromechanical systems (MEMS) design synthesis called case-based synthesis of MEMS (CaSyn-MEMS) has been developed. MEMS-based technologies have the potential to revolutionize many consumer products and to create new market opportunities in areas such as biotechnology, aerospace, and data communications. However, the commercialization of MEMS still faces many challenges due to a lack of efficient computer-aided design tools that can assist designers during the early conceptual phases of the design process. CaSyn-MEMS combines a case-based reasoning (CBR) algorithm and a MEMS case library with parametric optimization and a multi-objective genetic algorithm (MOGA) to synthesize new MEMS design topologies that meet or improve upon a designer’s specifications. CBR is an artificial intelligence methodology that uses past design solutions and adapts them to solve current problems. Having the ability to draw upon past design knowledge is advantageous to MEMS designers, allowing reuse and modification of previously successful designs to accelerate the design process. To enable knowledge reuse, a hierarchical MEMS case library has been created. A reasoning algorithm retrieves cases with solved problems similar to the current design problem. Focusing on resonators as a case study, case retrieval demonstrated an 82% success rate. Using the retrieved cases, approximate design solutions were proposed by first adapting cases with parametric optimization, resulting in a 25% reduction in design area on average while bringing designs within 2% of the frequency goal. In situations where parametric optimization was not sufficient, a more radical design adaptation was performed through the use of MOGA. CBR provided MOGA with good starting points for optimization, allowing efficient convergence to higher quantities of Pareto optimal design concepts while reducing design area by up to 43% and meeting frequency goals within 5%.

In this paper, two approaches for computing the topological information content of function models in mechanical engineering design are developed and compared. Previously, a metric for computing information content of functions and flows within function models was proposed. Here, this metric is evolved to include the information contained in the connections between flows and functions in a function model. The first approach is based on uniform unconditional probability of a flow connecting any two functions within the model. The second approach is based on additional knowledge that the functions and flows in a model have limited compatibility, thereby, reducing the choices for origin and destination functions for each flow. This additional knowledge is represented using a new graphical representation supported by syntactic grammar rules. Both approaches are then applied to an example function model. Comparison between the approaches shows that the inclusion of this additional knowledge increases the expressiveness by reducing the uncertainty associated with function models.

A lot of methods have been proposed for the kinematic chain isomorphism problem. However, the tool is still needed in building intelligent systems for product design and manufacturing. In this paper, we design a novel multivalued neural network that enables a simplified formulation of the graph isomorphism problem. In order to improve the performance of the model, an additional constraint on the degree of paired vertices is imposed. The resulting discrete neural algorithm converges rapidly under any set of initial conditions and does not need parameter tuning. Simulation results show that the proposed multivalued neural network performs better than other recently presented approaches.

A study is presented on applications of computational intelligence (CI) techniques for monitoring and prognostics of machinery conditions. The machine condition is assessed through an energy-based feature, termed as “energy index,” extracted from the vibration signals. The progression of the “monitoring index” is predicted using the CI techniques, namely, recursive neural network (RNN), adaptive neurofuzzy inference system (ANFIS), and support vector regression (SVR). The proposed procedures have been evaluated through benchmark data sets for one-step-ahead prediction. The prognostic effectiveness of the techniques has been illustrated through vibration data set of a helicopter drivetrain system gearbox. The prediction performance of SVR was better than RNN and ANFIS. The improved performance of SVR can be attributed to its inherently better generalization capability. The training time of SVR was substantially higher than RNN and ANFIS. The results are helpful in understanding the relationship of machine conditions, the corresponding indicating feature, the level of damage or degradation, and their progression.

Recent advancements in computing power and speed provide opportunities to revolutionize trade space exploration, particularly for the design of complex systems such as automobiles, aircraft, and spacecraft. In this paper, we introduce three visual steering commands to support trade space exploration and demonstrate their use within a powerful data visualization tool that allows designers to explore multidimensional trade spaces using glyph, 1D and 2D histograms, 2D scatter, scatter matrix, and parallel coordinate plots, linked views, brushing, preference shading, and Pareto frontier display. In particular, we define three user-guided samplers that enable designers to explore (1) the entire design space, (2) near a point of interest, or (3) within a region of high preference. We illustrate these three samplers with a vehicle configuration model that evaluates the technical feasibility of new vehicle concepts. Future research is also discussed.

In reverse engineering, 2D profile curve reconstruction based on cross-sectional points is a very crucial step for surface reconstruction such as lofting surface, swept surface, translational surface, and rotational surface. Unlike the traditional constrained fitting method that assumes that the cross-sectional points have been segmented in advance, and that the initial fitted curves are very close to the points, we propose a nonrigid registration method, through which a template curve can be automatically transformed and deformed to best fit the cross-sectional points. Compared with constrained fitting, nonrigid registration does not need any data preprocessing such as sorting, segmentation, and parametrization. The simulated and real examples have demonstrated the effectiveness and superiority of nonrigid registration for 2D blade profile curve reconstruction.

Microfluidic devices exhibit a high-aspect ratio in that their channel-widths are much smaller than their overall lengths. High-aspect geometry leads to an unduly large finite element mesh, making the (otherwise popular) finite element method (FEM) a poor choice for modeling microfluidic devices. An alternate computational strategy is to exploit well-known analytical solutions for fluid flow over the narrow channels of a device, and then either (a) assume the same analytical solutions for the cross-flow regions, or (b) exploit these solutions to set-up artificial boundary conditions over the cross-flow regions. Such simplified models are computationally far superior to brute-force FEM, but do not support the generality or flexibility of FEM. In this paper, we propose a third strategy for exploiting the analytical solutions: (c) directly incorporate them into standard FE-based analysis via algebraic reduction techniques. The advantages of the proposed strategy are (1) designers can use standard computer-aided design/computer-aided engineering (CAD/CAE) environments to model, analyze, and postprocess microfluidic simulation; (2) well-established dual-weighted residuals can be used to estimate modeling errors; and (3), if desired, one can eliminate the dependency on analytical solutions over selected regions, and instead revert to brute-force FEM. The simplicity and generality of the proposed method is inherited from the model reduction process, so are its theoretical properties, while simultaneously its computational efficiency is inherited from the use of analytical solutions.

Multiphysics applications are real world problems with a large number of different shape components that obey different physical laws and manufacturing constraints and interact with each other through geometric and physical interfaces. They demand accurate and efficient solutions and a modern type of computational modeling, which designs the whole physical system with as much detail as possible. The simulation of gas turbine engine is such a multiphysics application and is realized with GasTurbnLab, an agent-based Multiphysics Problem Solving Environment (MPSE). Its performance and evaluation study is presented in this paper. For this, a short description of the software components and hardware infrastructure is given. The performance and the scalability of the parallelism are depicted, and the communication overhead between agents is studied with respect to the number of agents and their location in the “computational grid.” The execution time is recorded, and its analysis verifies the complexity of the solvers in use and the performance of the available hardware. Three different clusters of INTEL Pentium processors were used for experimentation to study how the communication time was affected by processor’s homogeneity/heterogeneity and the different connections between the processors. The study of the numerical experiments shows that the domain decomposition and interface relaxation methodology, along with the usage of agent platforms, does not increase the complexity of the simulation problem, and the communication cost is too low, compared with the computations, to reflect on the total simulation time. Therefore, GasTurbnLab is an efficient example of a complex physical phenomena simulation.

We consider the task of sequential point sampling for three-dimensional structure reconstruction and focus on terrestrial topographic mapping using a laser range scanner. Both the sampling and the reconstruction rely on a stochastic model of the sampled object. We describe several algorithms for sequential point sampling including a new adaptive algorithm that is specifically designed for mechanical devices and produces grid-like sampling patterns. Experimental results verify that relying on the stochastic model indeed leads to efficient sampling associated with accurate surface reconstruction.

When equipped with a handlebar and pedal force display subsystem, motion-generating subsystem, and visual subsystem, the interactive bicycle simulator can bring riders a realistic cycling feeling. In the interactive bicycle simulator, the most important component is the rider-bicycle dynamic model. The Newton-Euler method is adopted to formulate this model. Real-time data gathered by sensors and identified from a terrain database system are used for calculation of the rider-bicycle dynamics. Simple and effective devices are constructed and driven by the outputs of the rider-bicycle dynamic model. These devices are successfully applied to the interactive bicycle simulator.

The objective of this paper is to describe a new method to determine the three-dimensional (3D) digitizing strategy for a computer aided design (CAD) known mechanical part by using a plane laser sensor. The Research Centre for Automatic control in Nancy, France has initiated a project to create an automatic 3D digitizing system. Previous papers focused on the visibility determinations using spherical geometry in a three axis environment. Here, the latest developments are presented. They enable one to improve this approach by taking into account a five axis environment. Using a new approach based on the Minkovsky operations to calculate the visibility of the different face of the B-Rep model of the part, the minimum set of directions required to entirely digitize the part is computed.

Reverse engineering aims at reproducing an existing object by analyzing its dimensions, features, form, and properties. Reversing geometry has traditionally been emphasized in this process. The collected data and information must be transformed into pertinent product knowledge at both the detail and embodiment levels. A thorough analysis of the environment must be conducted in order determine the functional requirements, infer the original needs, and deduce the form and fit features. An integrated approach that blends techniques such as IDEF modeling, scanning, and physical measurements, least-squares methods, and statistics used for process capability analysis in an innovative manner can lead to a more complete model, as no one set of tools can provide a complete, comprehensive engineering representation. An integrated and systematic framework for design recovery of mechanical parts is proposed. Forward engineering techniques should be applied appropriately throughout and integrated with the reverse engineering process to heal the knowledge gaps. Examples are presented that illustrate the application of the proposed integrated approach and highlight its merits.

Computational modeling continues to play an increasingly significant role in the design of more effective vehicle crash safety systems. Researchers now frequently exercise models formulated with sophisticated computer analyses to supplement empirically generated results and conduct extensive what-if exploratory studies for information formerly available solely from costly and time-consuming physical testing. Our research team is developing a modeling and analysis capability that features a scientific visualization toolkit called NYSCEDII CRS visualization module (NCVM). NCVM post-processes conventional crash simulation imagery, enabling modelers to visualize aspects of both the digital model and the sled-test simulation in an immersive visual environment. This paper describes NCVM’s design and development in detail and illustrates its application to a series of sled tests conducted with a recent-production child restraint system and dummy occupant.