A New Heuristic Topology Optimization Method Based on Bone Remodeling Model

The law of bone remodeling asserts that the internal trabecular bone adapts to external loadings, reorienting with the principal stress trajectories to maximize mechanical efficiency creating a naturally optimum structure. In this paper a new heuristic topology optimization method based on ordinary differential equations describing bone remodeling process is presented. The basis for numerical algorithm formulation was the phenomenon of bone adaptation to mechanical stimulation. The resulting optimization system allows fulling mechanical theorem for the stiffest design by use of presented heuristic topology optimization approach. Two widely used numerical examples are shown to confirm the validity and utility of the proposed topology optimization method.

Improved aeroelastic design through structural optimization

The paper presents the idea of coupled multiphysics computations. It shows the concept and presents some preliminary results of static coupling of structural and fluid flow codes as well as biomimetic structural optimization. The model for the biomimetic optimization procedure was the biological phenomenon of trabecular bone functional adaptation. Thus, the presented structural bio-inspired optimization system is based on the principle of constant strain energy density on the surface of the structure. When the aeroelastic reactions are considered, such approach allows fulfilling the mechanical theorem for the stiffest design, comprising the optimizations of size, shape and topology of the internal structure of the wing.

Subtree matching by pushdown automata

Subtree matching is an important problem in Computer Science on which a number of tasks, such as mechanical theorem proving, term-rewriting, symbolic computation and nonprocedural programming languages are based on. A systematic approach to the construction of subtree pattern matchers by deterministic pushdown automata, which read subject trees in prefix and postfix notation, is presented. The method is analogous to the construction of string pattern matchers: for a given pattern, a nondeterministic pushdown automaton is created and is then determinised. In addition, it is shown that the size of the resulting deterministic pushdown automata directly corresponds to the size of the existing string pattern matchers based on finite automata.

On Tree Pattern Matching by Pushdown Automata

Tree pattern matching is an important operation in Computer Science on which a number of tasks such as mechanical theorem proving, term-rewriting, symbolic computation and non-procedural programming languages are based on. Work has begun on a systematic approach to the construction of tree pattern matchers by deterministic pushdown automata which read subject trees in prefix notation. The method is analogous to the construction of string pattern matchers: for given patterns, a non-deterministic pushdown automaton is created and then it is determinised. In this first paper, we present the proposed non-deterministic pushdown automaton which will serve as a basis for the determinisation process, and prove its correctness.