Damage mitigation of a near-full-scale deployable tensegrity structure through behavior biomimetics

Current infrastructure is designed and built such that it must simultaneously comply with all possible loads. This leads to overdesigned structures that are inefficient in terms energy and cost. A structure that can self-identify damage, adapt, and learn for future events addresses the emerging field of intelligent infrastructure through inspiration from biology. The required material and embodied energy of structural elements is reduced while maintaining structural integrity with a small increase in operational energy for active control. Tensegrity structures are cable-strut systems held in equilibrium due to self-stress. There is potential for damage tolerance when they are kinematically redundant. This paper presents active control algorithms applied for damage mitigation and service loading of the tensegrity structure. Active control using a path-planning RRT*-connect algorithm and soft-constraint algorithm changes the shape of the tensegrity structure to reduce member stresses and to restrict vertical (downward) displacement caused by a damaged element. Though the effect improves the configuration of the structure, it cannot be fully restored to the design configuration. Effectiveness of the RRT*-connect and soft-constraint algorithms for the half structure depends on the relative change of nodal positions and feasibility to bring the structure back within serviceability limits. Since correction of end-node coordinates can be grouped according to the direction vector to mitigate the configuration of the structure and resulting cable-length changes, case-based reasoning (CBR) is useful to reduce time of execution and to avoid unnecessary cable-length changes. Mitigation techniques are successfully demonstrated for serviceability thresholds for a uniformly distributed load.

Element location and classification following a damage event of a near-full-scale deployable tensegrity structure

Ian Smith, Ann Christine Sychterz

Current infrastructure is designed and built such that it must resistall possible loads. This leads to overdesigned structures that are inefficient in terms energy and cost. A structure that can self-identify damage, adapt, and learn for future events results from research intothe emerging field of intelligent infrastructure and structural health monitoring.Two halves of a “hollow-rope” tensegrity structure deploy from supports to join at midspan by controlling the length of active cables on each half of the structure. These active cables are continuous throughthe length of the half-structure, guided by intermediary jointswhere cables slide. Springs along the circumference of the structure facilitate deployment due to increasing the diameter of the structure when folding and subsequent decreasing during deployment. Although previous work has addressed damage locationand mitigationof ruptured cableswhen the cables are the load-critical elements of the structure, this work hasnot studiedthe classification of the type of element that is damaged, element locationand damage mitigation.This paper presents work on element classification, detection,and location of damaged elements in a deployable tensegrity footbridge. The footbridge isstudied through monitoring dynamic behavior. Displacement and strain values are measured before, during, and after cable breakage. Natural frequencies inhealthy and damaged states are compared. Free-vibration dynamic behavior of the tensegrity structure are characterized for two situations,deployment and in-service. Examination of ambient vibrations for the half structure and forced vibrations for the full structure successfully led to detection of ruptured cables. Correlation methods using strain measurements also successfullydetect and locate a ruptured cable. Detection of abuckled strut and aruptured cableis successful by observing differences of natural frequencies between healthy and damaged states. Location of a damaged element is successful using nodal-position measurements through excluding possible damage scenarios and using strain measurements to identify elements of significant changes in eigenvector coefficients using principal component analysis. Therefore, excluding scenarios from a population for damageidentification is effective for highly-coupled structures that are capable of large shape changes. These methods reveal the potential for damage identification of complex sensed structures.Classification and location of a damaged element on a complex near-full-scale structure is successful using nodal position measurements through excluding possible damage cases and using strain measurements to identify elements of significant changes in eigenvector coefficients using principal component analysis. Implementing error-domain model falsification to exclude possible scenarios for location of damaged elements successfully reduced the number of probable casesof damage location. Paterns of influence from damaged cables and struts are useful to classify the type of element that is damaged. Therefore, the methodology involving error-domain model falsification (EDMF) for damage location is useful for closely-coupled structures that are capable of large shape changes.

2019

Biomimetic adaptive control of a deployable tensegrity structure

Ann Christine Sychterz

Biomimetic behavior includes aspects such as learning from previous experience, self-diagnosis, and adaptation. This thesis describes control methodologies that are essential to development towards biomimetic behavior of a complex deployable structure. Simulations of the structure are improved from previous work to include friction effects of cables sliding over joints. Despite improved simulations, testing shows that significant uncertainties in the behavior of the structure remain. Therefore, control is not effective with predetermined actuation movements. Special methodologies for feedback control using simulations and measurements are required. A near-full-scale deployable tensegrity structure is used to test methodologies. Active control methods are proposed for deployment, midspan connection of both halves of the structure, and self-stress. This thesis presents a method using feedback to compare measurements and simulations to modify control commands. Since collision of elements is possible in the folded state and produce undesirable bending stresses, a path-planning algorithm is implemented for the first stage of deployment. Error in nodal positions at midspan is successfully reduced through the use of the path-planning method and deployment time is significantly reduced compared with previous work. Lastly, algorithms for self-stress, involving penalty and rejection constraints on element stress, are useful for correcting nodal positions after deployment. Damage is detected in this thesis using vibration measurements. The method uses dynamic behavior of the structure to determine whether or not the structure is damaged. Using parameters of the structure and a set of candidate locations for the damaged element, candidates are successively excluded until few candidates remain, successfully including the true location of damage. Adaptation and learning are demonstrated by mitigation methods after damage and in-service loading (such as pedestrians). Active control is useful to manipulate the shape of the tensegrity structure to reduce the member stresses and vertical downwards displacement caused by a damaged element. Though the response improves the condition of the structure to respect the serviceability limit for vertical downwards displacement, the tensegrity structure cannot be fully restored to the design configuration. Since correction of end-node coordinates can be grouped by the direction of correction and resulting cable-length changes, case-based reasoning is useful to reduce time of execution and to reduce unnecessary cable-length changes. Single pedestrian and crowd loading configuration is applied analytically and experimentally to the tensegrity structure. Application of mitigation techniques is useful beyond serviceability thresholds for a moving load used to simulate in-service loading. The research question of this thesis: "Is it feasible for a deployable tensegrity structure to improve movement and service performance through behavior biomimetics?". The answer is yes. This work presents methods inspired by those observed in nature for efficient movement that is generalizable for future deployable structures.

EPFL2018

Functional polymer brushes via surface-initiated controlled radical polymerizations

Stefano Tugulu

The term polymer brush refers to a well defined arrangement of polymer chains, which are tethered with one end to an interface and usually the surface of a solid substrate. Due to steric repulsion the polymer chains furthermore adopt a defined, stretched chain conformation, which significantly differs from the random walk conformation of free polymer chains in solution or in conventionally solution casted polymer coatings. From a structural point of view polymer brushes can therefore be regarded as the most defined type of polymer coating that can currently be realized. Especially the combination of surface-initiated polymerizations (SIP) with modern, controlled polymerization methods thereby allows tailoring the structure of the polymer brushes almost on the molecular level. Specifically precise control over the thickness, composition, chain architecture, grafting density and via the use of lithographic techniques also over the topography of the brushes can be achieved. This high degree of control over the structural and implicated (physico-)chemical properties of the brush allows at the same time tailoring and fine tuning the interfacial properties of the brush. This thesis describes the systematic exploitation of well-defined polymer brushes as functional coatings with fine-tuned physicochemical properties to direct and control the interaction with and the response of specific biological, bioanalytical and even reactive chemical environments. In detail the use of surface-initiated atom transfer radical polymerization (SI-ATRP) for the fabrication of functional polymer brushes will be presented. These brushes were used as highly defined coatings in various applications ranging from biomedical and bioanalytical applications to biomimetic materials fabrication (Figure 1). Figure 1 Numerous synthetic approaches for the preparation of polymer brushes have been described in the literature. Chapter 2 will therefore present a summary of the most important types of surface-initiated polymerizations, focusing especially on controlled SIP methods and SI-ATRP. Chapter 3 describes a chemoselective and specific immobilization strategy to decorate intrinsically bioinert polymer brushes with proteins of interest in a defined orientation and density. Specifically the resulting substrates represent attractive candidates for the realization of protein microarrays. In view of this application protein-small molecule and protein-protein interactions as well as posttranslational modifications were analyzed within a feasibility study. Due to their well-defined structure polymer brushes represent also attractive candidates for the realization of molecularly defined cell adhesion substrates for tissue engineering or as highly defined biophysical model system to analyze cell adhesion and mechanics. Chapter 4 describes the decoration of intrinsically bioinert polymer brushes with small peptide ligands with defined density to induce integrin specific cell adhesion on the brushes. Peptide functionalized polymer brushes could be readily endothelialized and adhering cell layers have shown to preserve their homeostatic ability to respond to an applied mechanical stimulus in a physiological manner. In Chapter 5 the limitations of high density polymer brushes in biomedical applications were assessed by analyzing their stability under in vitro cell culture conditions. Intrinsically bioinert high density polymer brushes were found to degraft from glass or silicon substrates upon swelling in good solvents, which lead to deterioration of the bioinert properties of the substrate. The degrafting of the brushes might be connected to swelling induced mechanical activation of chemical bonds, which link the brushes to the substrate. Chapter 6 describes the transfer of the developed SIP approach onto flexible PDMS substrates by exploiting the formation of interpenetrating networks of ATRP-initiator siloxane and PDMS. The modification of the PDMS substrates with hydrophilic brushes effectively reduces the unspecific protein adsorption on the substrates. This approach might therefore represent an attractive and facile route for the surface modification of miniaturized PDMS devices for biomedical or bioanalytical applications. In Chapter 7 the systematic development of a reliable and robust protocol for the aqueous SI-ATRP of sodium methacrylate is presented, which gives access to poly(methacrylic acid) (PMAA) brushes with defined molecular weight and grafting density. The resulting brushes were assessed for their ability to direct the mineralization of calcium carbonate. Chapter 8 describes the use of photolithographically patterned poly(methacrylic acid) brushes as biomimetic, acidic macromolecular matrix to fabricate microstructured calcite thin films that are an exact 3D replica of the PMAA brush. The presented strategy relies on three key elements: (i) the use of photolithographic techniques to prepare microstructured PMAA brushes; (ii) the ability of PMAA brushes to stabilize amorphous calcium carbonate (ACC) and (iii) the possibility to convert the metastable ACC phase into a polycrystalline calcite film via a thermal treatment.

EPFL2007