Modal Interface Automata

De Alfaro and Henzinger's Interface Automata (IA) and Nyman et al.'s recent combination IOMTS of IA and Larsen's Modal Transition Systems (MTS) are established frameworks for specifying interfaces of system components. However, neither IA nor IOMTS consider conjunction that is needed in practice when a component shall satisfy multiple interfaces, while Larsen's MTS-conjunction is not closed and Bene\v{s} et al.'s conjunction on disjunctive MTS does not treat internal transitions. In addition, IOMTS-parallel composition exhibits a compositionality defect. This article defines conjunction (and also disjunction) on IA and disjunctive MTS and proves the operators to be 'correct', i.e., the greatest lower bounds (least upper bounds) wrt. IA- and resp. MTS-refinement. As its main contribution, a novel interface theory called Modal Interface Automata (MIA) is introduced: MIA is a rich subset of IOMTS featuring explicit output-must-transitions while input-transitions are always allowed implicitly, is equipped with compositional parallel, conjunction and disjunction operators, and allows a simpler embedding of IA than Nyman's. Thus, it fixes the shortcomings of related work, without restricting designers to deterministic interfaces as Raclet et al.'s modal interface theory does.Comment: 28 page

A Few Considerations on Structural and Logical Composition in Specification Theories

Over the last 20 years a large number of automata-based specification theories have been proposed for modeling of discrete,real-time and probabilistic systems. We have observed a lot of shared algebraic structure between these formalisms. In this short abstract, we collect results of our work in progress on describing and systematizing the algebraic assumptions in specification theories.Comment: In Proceedings FIT 2010, arXiv:1101.426

Towards an I/O Conformance Testing Theory for Software Product Lines based on Modal Interface Automata

We present an adaptation of input/output conformance (ioco) testing principles to families of similar implementation variants as appearing in product line engineering. Our proposed product line testing theory relies on Modal Interface Automata (MIA) as behavioral specification formalism. MIA enrich I/O-labeled transition systems with may/must modalities to distinguish mandatory from optional behavior, thus providing a semantic notion of intrinsic behavioral variability. In particular, MIA constitute a restricted, yet fully expressive subclass of I/O-labeled modal transition systems, guaranteeing desirable refinement and compositionality properties. The resulting modal-ioco relation defined on MIA is preserved under MIA refinement, which serves as variant derivation mechanism in our product line testing theory. As a result, modal-ioco is proven correct in the sense that it coincides with traditional ioco to hold for every derivable implementation variant. Based on this result, a family-based product line conformance testing framework can be established.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301

Design oriented simulation of contact-friction instabilities in application to realistic brake assemblies

This paper presents advances in non-linear simulations for systems with contact-friction, with an application to brake squeal. A method is proposed to orient component structural modifications from brake assembly simulations in the frequency and time domains. A reduction method implementing explicitly component-wise degrees of freedom at the system level allows quick parametric analyses giving modification clues. The effect of the modification is then validated in the time domain where non-linearities can be fully considered. A reduction method adapted for models showing local non-linearities is purposely presented along with an optimization of a modified non linear Newmark scheme to make such computation possible for industrial models. The paper then illustrates the importance of structural effects in brake squeal, and suggests solutions

Role-Based Interface Automata

No abstract available

Energy-Based Optimal Ranking of the Interior Modes for Reduced-Order Models under Periodic Excitation

This paper introduces a novel method for ranking and selecting the interior modes to be retained in the Craig-Bampton model reduction, in the case of linear vibrating systems under periodic excitation. The aim of the method is to provide an effective ranking of such modes and hence an optimal sequence according to which the interior modes should be progressively included to achieve a desired accuracy of the reduced-order model at the frequencies of interest, while keeping model dimensions to a minimum. An energy-based ranking (EBR) method is proposed, which exploits analytical coefficients to evaluate the contribution of each interior mode to the forced response of the full-order system. The application of the method to two representative systems is discussed: an ultrasonic horn and a vibratory feeder. The results show that the EBR method provides a very effective ranking of the most important interior modes and that it outperforms other state-of-the-art benchmark techniques

A Modeling approach for analysis and improvement of spindle-holder-tool assembly dynamics

The most important information required for chatter stability analysis is the dynamics of the involved structures, i.e. the frequency response functions (FRFs) which are usually determined experimentally. In this study, the tool point FRF of a spindle-holder-tool assembly is analytically determined by using the receptance coupling and structural modification techniques. Timoshenko’s beam model is used for increased accuracy. The spindle is also modeled analytically with elastic supports representing the bearings. The mathematical model is used to determine the effects of different parameters on the tool point FRF and to identify contact dynamics from experimental measurements. The applications of the model are demonstrated and the predictions are verified experimentally

Understanding friction induced damping in bolted assemblies through explicit transient simulation

The design of joints is seeing increased interest as one of the ways of controlling damping levels in lighter and more flexible aeronautic structures. Damping induced by joint dissipation has been studied for more than a decade, mostly experimentally due to the difficulty of simulating large structures with non-linearities. Experimentally fitted meta-models were thus used for damping estimation at design stage without a possible optimization. The aim of this paper is to demonstrate that damping estimation using local friction models is feasible and that it can be usable for design. The simulation methodology is based on an explicit Newmark time scheme with model reduction and numerical damping that can be compensated for the modes of interest. Practical simulation times counted in minutes are achieved for detailed models. The illustration on a lap-joint shows how simulations can be used to predict the amplitude dependence of modal damping, answer long standing questions such as “does the modeshape change?” or analyze the evolution of pressure fields during a cycle

Design Optimization Utilizing Dynamic Substructuring and Artificial Intelligence Techniques

In mechanical and structural systems, resonance may cause large strains and stresses which can lead to the failure of the system. Since it is often not possible to change the frequency content of the external load excitation, the phenomenon can only be avoided by updating the design of the structure. In this paper, a design optimization strategy based on the integration of the Component Mode Synthesis (CMS) method with numerical optimization techniques is presented. For reasons of numerical efficiency, a Finite Element (FE) model is represented by a surrogate model which is a function of the design parameters. The surrogate model is obtained in four steps: First, the reduced FE models of the components are derived using the CMS method. Then the components are aassembled to obtain the entire structural response. Afterwards the dynamic behavior is determined for a number of design parameter settings. Finally, the surrogate model representing the dynamic behavior is obtained. In this research, the surrogate model is determined using the Backpropagation Neural Networks which is then optimized using the Genetic Algorithms and Sequential Quadratic Programming method. The application of the introduced techniques is demonstrated on a simple test problem