This paper presents preliminary results on an intelligent mapping capability that generates high-confidence layouts of
building interiors from limited exterior and interior structural observables. Such a capability could provide critical
support to intelligence gathering and/or life-saving operations in the military, law enforcement, disaster response, and
commercial sectors where rapid understanding of unknown interior layouts is required to save lives, maintain covertness,
or minimize costs. The fundamental approach relies on an intelligent rule-based inferencing process which operates on
limited structural observables. The rules are based on geo-specific design practices and building codes. The mapping
capability has been demonstrated experimentally in a test-case building structure using a set of imaging sensors to scan
the environment. Data was gathered at sparse locations within the building to represent a real-world rapid exploration
scenario. Preliminary results show that this capability can successfully generate high-confidence interior layouts from
limited structural observables. It is envisioned that this intelligent mapping capability could be integrated on unmanned
ground vehicle platforms or in human-borne (soldier, SWAT, urban search-and-rescue personnel) systems.
Health monitoring and damage detection strategies for base-excited structures typically rely on accurate models of the system dynamics. Restoring forces in these structures can exhibit highly non-linear characteristics, thus accurate non-linear system identification is critical. Parametric system identification approaches are commonly used, but require a priori knowledge of restoring force characteristics. Non-parametric approaches do not require this a priori information, but they typically lack direct associations between the model and the system dynamics, providing limited utility for health monitoring and damage detection. In this paper a novel system identification approach, the Intelligent Parameter Varying (IPV) method, is used to identify constitutive non-linearities in structures subject to seismic excitations. IPV overcomes the limitations of traditional parametric and non-parametric approaches, while preserving the unique benefits of each. It uses embedded radial basis function networks to estimate the constitutive characteristics of inelastic and hysteretic restoring forces in a multi-degree-of-freedom structure. Simulation results are compared to those of a traditional parametric approach, the prediction error method. These results demonstrate the effectiveness of IPV in identifying highly nonlinear restoring forces, without a priori information, while preserving a direct association with the structural dynamics.
Recent developments in the new field of auto-adaptive materials offer promising opportunities for developing radically new fastening mechanisms. One of the classes of materials in this category is Shape Memory Alloys (SMAs). SMAs are very attractive for structural application because of their major constitutive behaviors such as pseudoelastic characteristic. Pseudoelastic behavior of NiTi SMAs is a unique hysteretic energy dissipation behavior that combined with a very long fatigue life makes SMAs a viable candidate for developing new fasteners. Pseudoelastic behavior of Shape Memory Alloys, particularly NiTI, can be used for developing passive fastening-mechanisms and tendon-systems. In case of coastal structures, where hurricane destruction inflicted upon residential structures results in million of dollar in financial damages and loss of lives each year, development of more effective fastening-mechanisms and tendon-systems for the connections between the walls and the roofs will aid in damage reduction. A study carried out by the authors has shown that the extent of damping effect of a hybrid tendon-system, made of rigid NiTi sections directly depends on the length-ratio of the rigid NiTi section, tendon diameter and the amount of pre-strain on the tendon. Moreover, because of tendon-system passive design the nature of excitation has a profound effect on its activation and damping capability. In this paper effectiveness of a hybrid NiTi tendon-system for damage mitigation of coastal structures and optimal hybrid tendon length-ratio are studied.
Shape memory alloys (SMAs) are identified with two main characteristics; shape memory effect, and pseudoelasticity; temperature and stress induced phase transformations respectively. By pseudoelasticity, SMAs sustain large amount of strain, without permanent plastic deformation, and recover it upon heating. Constitutive models have been proposed for single/polycrystalline SMAs. The first practical model, was proposed by Tanaka (1985, 1986). That consisted of one equation for stress vs strain, temperature, and martensitic phase fraction (MPF), and a set of kinetic relations, for MPF during phase transformations. Liang and Rogers (1990) proposed a model utilizing a simpler kinetic relation. Brinson (1993) developed a more versatile and realistic model, by incorporating the temperature and stress induced MPF into the kinetic relations. That predicts the material behavior throughout the entire temperature range. This paper presents a comprehensive understanding of temperature and stress induced phase transformation. A thorough interpretation of MPF and critical stresses of phase transformation versus temperature are discussed and capabilities of Brinson's model in reproducing the SMA characteristics under quasi-static thermomechanical loading are demonstrated. Such in-depth elaboration of these relationships has not been reported in the literature; yet is it is essential for capturing the nature of superelasticity. Exploring the capabilities of Brinson's model facilitates applications of autoadaptive materials in structural or mechanical systems.
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