Computational Evolutionary Embryogeny

Evolutionary and developmental processes are used to evolve the configurations of 3-D structures in silico to achieve desired performances. Natural systems utilize the combination of both evolution and development processes to produce remarkable performance and diversity. However, this approach has not yet been applied extensively to the design of continuous 3-D load-supporting structures. Beginning with a single artificial cell containing information analogous to a DNA sequence, a structure is grown according to the rules encoded in the sequence. Each artificial cell in the structure contains the same sequence of growth and development rules, and each artificial cell is an element in a finite element mesh representing the structure of the mature individual. Rule sequences are evolved over many generations through selection and survival of individuals in a population. Modularity and symmetry are visible in nearly every natural and engineered structure. An understanding of the evolution and expression of symmetry and modularity is emerging from recent biological research. Initial evidence of these attributes is present in the phenotypes that are developed from the artificial evolution, although neither characteristic is imposed nor selected-for directly. The computational evolutionary development approach presented here shows promise for synthesizing novel configurations of high-performance systems. The approach may advance the system design to a new paradigm, where current design strategies have difficulty producing useful solutions

Engineering by fundamental elements of evolution

The method presented in this note mimics two fundamental mechanisms from nature, growth, and development, for the synthesis of new three-dimensional structures. The structures were synthesized to support a load generated by a wind. Every structure grows from a single artificial cell following a set of genes, encoded in an artificial genome shared by all cells. Genes are a set of commands that control the growth process. Genes are regulated by interaction with the environment. The environment is both external and internal to the structure. The performance each structure is measured by its ability to hold the load and other additional engineering criteria. A population of structures is evolved using a genetic algorithm, which alters the genome of two mating individuals. We will present evolved phenotypes with high degrees of modularity and symmetry which evolved according to engineering criteria. Neither one of these two characteristics has been directly imposed as the fitness evaluation, but rather spontaneously emerge as a consequence of natural selection. We will argue that the types of rules we are using in this model are not biased toward any of these characteristics, but rather basic rules for growth and development

A novel evolutionary method for synthesis of 3D continuous structures

The design of complex structures which benefit the usage of inhomogeneous properties is a very difficult task. In this paper we present a novel approach in which we synthesize the design of structures by mimicking two fundamental processes from biology - Evolution and Development. We will show that by using these two processes in a computational model, we are able to evolve high performance structures. These structures contain a high degree of complexity from a topological aspect and from a materials distribution aspect. This degree of complexity is difficult or even impossible to achieve by ordinary design methods

Modularity and symmetry in computational embryogeny

Modularity and symmetry are two properties observed in almost every engineering and biological structure. The origin of these properties in nature is still unknown. Yet, as engineers we tend to generate designs which share these properties. In this paper we will report on the origin of these properties in three dimensional evolved structures (phenotypes). The phenotypes were evolved in an evolutionarydevelopmental model of biological structures. The phenotypes were grown under a high volatility stochastic environment. The phenotypes have evolved to function within the environment using the very basic requirements. Even though neither modularity nor symmetry have been directly imposed as part of the requirements, the phenotypes were able to generate these properties after only a few hundred generations. These results may suggest that modularity and symmetry are both very fundamental properties that develop during the early stages of evolution. This result may give insight to the origin of both modularity and symmetry in biological organisms

ESDA2008-59036 A NOVEL EVOLUTIONARY METHOD FOR SYNTHESIS OF 3D CONTINUOUS STRUCTURES

ABSTRACT The design of complex structures which benefit the usage of inhomogeneous properties is a very difficult task. In this paper we present a novel approach in which we synthesize the design of structures by mimicking two fundamental processes from biology -Evolution and Development. We will show that by using these two processes in a computational model, we are able to evolve high performance structures. These structures contain a high degree of complexity from a topological aspect and from a materials distribution aspect. This degree of complexity is difficult or even impossible to achieve by ordinary design methods

Computational Evolutionary Embryogeny

Evolution and development (Evo-Devo), are the two main processes which produce all of the different kinds of phenotypes we see in nature. Evolutionary process is responsible for eliminating the genetic information of weak phenotypes through natural selection, and also for exploring novel genotypes through genetic operations; crossover, mutation. The development process is the process of using the set of rules (codons) written in a genome, to turn a single set (zygote) into a mature phenotype. In this thesis, evolutionary and developmental processes are used to evolve the configurations of three-dimensional structures in silico to achieve desired performances. Although natural systems utilize the combination of both evolution and development processes to produce remarkable performance and diversity, this approach has not yet been applied extensively to the design of continuous three-dimensional load-supporting structures. Beginning with a single artificial cell containing information analogous to a DNA sequence, a structure is grown according to the rules encoded in the sequence. Each artificial cell in the structure contains the same sequence of growth and development rules, and each artificial cell is an element in a finite element mesh representing the structure of the mature individual. Rule sequences are evolved over many generations through selection and survival of individuals in a population. Modularity and symmetry are visible in nearly every natural and engineered structure. Understanding of the evolution and expression of symmetry and modularity is emerging from recent biological research. Initial evidence of these attributes is present in the phenotypes that are developed from the artificial evolution, although neither characteristic is imposed nor selected for directly. The computational evolutionary development approach presented here shows promise for synthesizing novel configurations of high-performance systems. The approach may advance system design to a new paradigm, where current design strategies have difficulty producing useful solutions. In addition to a new design approach perse, this model gives us the ability to explore the development process, from the standpoint of complex systems analysis. The phenotypes in our system have been grown under a highly stochastic environment, which serves as a triggered mechanism for gene expression. Still, evolution was able to find solutions which are robust to these stochastic elements, both at the phenotype level (the phenotype ability to function under the environment) and the growth process itself. In addition we have also explored the effects of symmetric and nonsymmetric environment over the topology of the phenotypes; we have found strong evidence that indicates a high correlation between the two. Finally we have also established a tool which enables us to understand the relationship between the environment and the degree of modularity of the phenotype.</p

Growth Control and Disease Mechanisms in Computational Embryogeny

This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum 3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads

A novel energy-based approach for merging finite elements

A novel approach for merging two intersecting finite elements is presented and demonstrated. The solution mimics concepts from biology and uses principles rooted in continuum mechanics. The problem of attaching (or merging) two coincident finite elements is common when using the plastering technique as part of the advancing front method. This problem is particularly challenging for 3-D meshes of non-convex shapes. Some automatic meshing methods require portions of the partially formed mesh to coincide and merge. This problem is generally solved with heuristic rules, which lack generality, and may have difficulties with unforeseen situations. The problem of merging two overlapping polyhedra may also appear in other applications such as computer graphics and CAD software. A new approach to address the problem of merging is presented here. This solution does not utilize heuristic rules, but rather uses an approach based on minimization of strain energy. A fully automatic merging routine has been created that can address, in an optimum way, any situation of two nearby or overlapping elements that are to be merged. This approach, with minor adjustments, is suitable for most types of 3-D elements