The collected works

HIS article presents an overview and assessment of the technology leading to the development of intelligent structures. Intelligent structures are those which incorporate actuators and sensors that are highly integrated into the structure and have structural functionality, as well as highly integrated control logic, signal conditioning, and power amplification electronics. Such actuating, sensing, and signal processing elements are incorporated into a structure for the purpose of influencing its states or characteristics, be they mechanical, thermal, optical, chemical, electrical, or magnetic. For example, a mechanically intelligent structure is capable of altering both its mechanical states (its position or velocity) or its mechanical characteristics (its stiffness or damping). An optically intelligent structure could, for example, change color to match its background.17 Definition of Intelligent Structures Intelligent structures are a subset of a much larger field of research, as shown in Fig. I.123 Those structures which have actuators distributed throughout are defined as adaptive or, alternatively, actuated. Classical examples of such mechanically adaptive structures are conventional aircraft wings with articulated leading- and trailing-edge control surfaces and robotic systems with articulated manipulators and end effectors. More advanced examples currently in research include highly articulated adaptive space cranes. Structures which have sensors distributed throughout are a subset referred to as sensory. These structures have sensors which might detect displacements, strains or other mechanical states or properties, electromagnetic states or properties, temperature or heat flow, or the presence or accumulation of damage. Applications of this technology might include damage detection in long life structures, or embedded or conformal RF antennas within a structure. The overlap structures which contain both actuators and sensors (implicitly linked by closed-loop control) are referred to as controlled structures. Any structure whose properties or states can be influenced by the presence of a closed-loop control system is included in this category. A subset of controlled structures are active structures, distinguished from controlled structures by highly distributed actuators which have structural functionality and are part of the load bearing system.

Intelligent structures for aerospace - A technology overview and assessment

Fiber optic sensor technology has experienced tremendous growth since its early beginnings in the 1970's with early laboratory demonstrations of fiber optic gyros and acoustic sensors and the introduction of the first commercial intensity and spectrally based sensors. These early efforts were followed by a tremendous growth of interest in the 1980's when the number of workers in the field increased from perhaps a few hundred to thousands. The result was the introduction in the 1990's of the first mass produced fiber optic sensors that are being used to support navigation and medical applications. The number of fiber optic sensor products can be expected to grow tremendously in the years to come as rapid progress continues to be made in the related optoelectronic and communication fields. This paper provides an overview of some of the technologies being used to support fiber optic sensor development and how they are being applied.

Fiber optic smart structures

Introduction to the Modern Theory of Dynamical Systems: INTRODUCTION: WHAT IS LOW-DIMENSIONAL DYNAMICS?

Driven by enormous clinical need, myocardial tissue engineering has become a prime focus of research within the field of tissue engineering. Myocardial tissue engineering combines isolated functional cardiomyocytes and a biodegradable or nondegradable biomaterial to repair diseased heart muscle. The challenges in heart muscle engineering include cell related issues (such as scale up in a short timeframe, efficiency of cell seeding or cell survival rate, and immune rejection), the design and fabrication of myocardial tissue engineering substrates, and the engineering of tissue constructs in vitro and in vivo. Several approaches have been put forward, and a number of models combining various polymeric biomaterials, cell sources and bioreactors have been developed in the last 10 years for myocardial tissue engineering. This review provides a comprehensive update on the biomaterials, as well as cells and biomimetic systems, used in the engineering of the cardiac muscle. The article is organized as follows. A historic perspective of the evolution of cardiac medicine and emergence of cardiac tissue engineering is presented in the first section. Following a review on the cells used in myocardial tissue engineering (second section), the third section presents a review on biomaterials used in myocardial tissue engineering. This section starts with an overview of the development of tissue engineering substrates and goes on to discuss the selection of biomaterials and design of solid and porous substrates. Then the applications of a variety of biomaterials used in different approaches of myocardial tissue engineering are reviewed in great detail, and related issues and topics that remain challenges for the future progress of the field are identified at the end of each subsection. This is followed by a brief review on the development of bioreactors (fourth section), which is an important achievement in the field of myocardial tissue engineering, and which is also related to the biomaterials developed. At the end of this article, the major achievements and remaining challenges are summarized, and the most promising paradigm for the future of heart muscle tissue engineering is proposed (fifth section).

Biomaterials in cardiac tissue engineering: Ten years of research survey

Paper is a complex structure of composite biological fibers.The behavior of paper is time-dependent with respect to load, moisturecontent, or temperature, whether these control parameters are fixed orvaried in combination. A key question is whether the time-dependentproperties are a consequence of the fiber micro-structure, theinterfiber bond, the fiber distribution in a sheet, or a combination ofthese. Hypotheses for the physical mechanisms responsible forstress-strain relations observed under constant, monotonic, and cyclicloading and, especially, for the role of moisture bonding in thetime-dependent behavior are compared. The moisture accelerated creepphenomenon, due to varying ambient relative humidity, is an importanttime-dependent behavior which creates practical problems such as thewall collapse of stacked cartons in warehouses with non-constanthumidity and control of the paper-making machine. For each type ofloading and ambient control variation, after a discussion of possiblephysical mechanisms inducing the observed response, the mathematicalmodels proposed in the literature are reviewed as tools for the designof both the paper-making process and applications.

The moisture and rate-dependent mechanical properties of paper: a review

The relation between a three-dimensional state of strain and the optical phase retardation in a single mode optical fiber is formalized by drawing together classical three-dimensional crystal optics and classical waveguide theory. Neumann's strain optic relations are described in a form usable in optical fiber sensor design. These relations are then combined with weakly guiding fiber theory to develop an integral which relates the optical phase shift in a structurally embedded interferometric optical fiber strain sensor to the induced three-dimensional strain field. This process leads to a previously undisclosed, additional waveguide dispersion term which contributes on the same order to the total strain induced phase retardation as does the term derived by Butter and Hocker (1978). Still, however, waveguide dispersion effects are found to be negligibly small, even in three- dimensional loading. Butter and Hocker's equation and the complete phase-strain model developed herein can give very similar results...

Complete phase-strain model for structurally embedded interferometric optical fiber sensors

The mechanical behavior of most biological soft tissue is nonlinear viscoelastic rather than elastic. Many of the models previously proposed for soft tissue involve ad hoc systems of springs and dashpots or require measurement of time-dependent constitutive coefficient functions. The model proposed here is a system of evolution differential equations, which are determined by the long-term behavior of the material as represented by an energy function of the type used for elasticity. The necessary empirical data is time independent and therefore easier to obtain. These evolution equations, which represent non-equilibrium, transient responses such as creep, stress relaxation, or variable loading, are derived from a maximum energy dissipation principle, which supplements the second law of thermodynamics. The evolution model can represent both creep and stress relaxation, depending on the choice of control variables, because of the assumption that a unique long-term manifold exists for both processes. It succeeds, with one set of material constants, in reproducing the loading–unloading hysteresis for soft tissue. The models are thermodynamically consistent so that, given data, they may be extended to the temperature-dependent behavior of biological tissue, such as the change in temperature during uniaxial loading. The Holzapfel et al. three-dimensional two-layer elastic model for healthy artery tissue is shown to generate evolution equations by this construction for biaxial loading of a flat specimen. A simplified version of the Shah–Humphrey model for the elastodynamical behavior of a saccular aneurysm is extended to viscoelastic behavior.

Nonlinear viscoelastic, thermodynamically consistent, models for biological soft tissue.

The behavior of a family of dynamical systems representing the elastodynamic response of an internally pressurized, non-linearly elastic spherical membrane lying in an incompressible external fluid is governed primarily by the strain energy function for the membrane, the specific forcing function due to the internal pressure, and the viscosity of the external fluid. It is shown that such systems with an inviscid external fluid and having a constant internal pressure are integrable but not Hamiltonian. Under periodic internal loading, and for a small spherical radius and constitutive relations typical of many biological soft tissues, a periodic orbit in phase space exists near a static equilibrium. A viscous external fluid causes the periodic orbit to be an attractor. The dynamical system is robust under small loading perturbations common in normal biological systems. Rubber models, on the other hand, may admit structural catastrophes. For small initial sphere radii, a jump from one periodic orbit to another is possible for rubber models but not for the classical soft tissue models. It is dangerous, therefore, to model soft biological tissue as a rubber either mathematically or physically in experiments because the predicted instabilities may not exist in tissue.

Dynamics of biological soft tissue and rubber: internally pressurized spherical membranes surrounded by a fluid

We develop the theory of surface-mounted interferometric optical fiber strain sensor design for arbitrarily configured fiber paths and present design techniques to select the path of a curved fiber-optic sensor required to isolate predetermined strain components. Several of these gauges are combined to form a rosette that directly measures the state of strain without the need to solve a set of simultaneous equations. We also use the design procedures to develop an optical fiber sensor that measures a single arbitrary stress component in an isotropic body. The design process is guided by a fundamental relationship among path, strain, and phase change for an arbitrarily configured optical fiber. The design theory is restricted to small strains and flat surfaces. All fiber sensor designs are validated with experiments.

Henry W. Haslach

Papers

The moisture and rate-dependent mechanical properties of paper: a review

Complete phase-strain model for structurally embedded interferometric optical fiber sensors

Nonlinear viscoelastic, thermodynamically consistent, models for biological soft tissue.

Dynamics of biological soft tissue and rubber: internally pressurized spherical membranes surrounded by a fluid

Surface-mounted optical fiber strain sensor design