Recent advances in manufacturing of multifunctional materials that respond to multi-field excitation have motivated the design and prototyping of sensing and actuating devices for various applications aiming to improve functionality and decrease overall cost. Computer aided design is one of the techniques utilized for achieving these goals. However, it requires the development and integration of behavioral evolution models for the respective materials. This paper addresses the initiation of an effort to develop a computational implementation of a theoretical methodology for describing such systems in a way that allows accurate prediction of their behavior within their state space. Continuum mechanics, irreversible thermodynamics, and electrodynamics are utilized to derive the general four dimensional multiphysics field equations of materials used for artificial muscle applications along with the appropriate constitutive theories. The generalized nonlinear Von-Karman equations expressing the behavior of multi-field artificial muscle-based materials are derived as a special case of electric multi-hygrothermoelasticity developed as the closest theory for modeling the behavior electro-hygro-thermo-elasto-active materials. Numerical solution examples of these equations are presented for the case of an ionic polymeric material structure.
NRL's Mechanics of Materials Branch has developed a technology that facilitates sensor selection and placement within a composite structure. The Embedded Sensors for Smart Structures Simulator (ES<SUP>4</SUP>) is a tool that relates the output of a finite number of sensors to strain induced structural and material damage. This tool is based on the use of the dissipative part of the bulk nonlinear material behavior. The methodology used to identify this behavior will be briefly described in the present paper. This paper describes the role of strain measurements and their relation to sensor type and location, the conceptual framework of dissipated energy density as the metric employed for assessing material/structural performance. Emphasis is given on the utilization of dissipated energy density for estimating the error between the health of the structure as 'seen' by the sensors and the actual health of the structure. Useful applications of this difference are sensor placement optimization in the case of the design phase and confidence level measure for the case of an on board simulating capability.
NRL's Mechanics of Materials Branch has developed the Embedded Sensors for Smart Structures Simulator (ES) design tool which relates the output of a finite number of sensors to strain induced structural damage. This tool is based on the use of the dissipative part of the bulk nonlinear material behavior. The methodology used to identify this behavior has evolved at NRL over the past 20 years. This paper describes the role of strain measurements and their relation to sensor type and location, the conceptual framework of dissipated energy density as the metric employed for assessing material/structure performance, the facilities provided by the simulator and their use, as well as implementation details. Through this we hope not only to make designing and verifying embedded sensor layouts on composite material structures a tractable task, but also to promote the use of dissipated energy density as a foundation upon which to build an effective means of measuring material and structural health. 13