It is believed that structures and actuation systems should be tightly integrated together in the future to create fast moving, efficient, lightweight dynamic machines. Such actuated structures could be used for morphing aircraft wings, lightweight actuated space structures, or in robotics. This requires actuators to be distributed through the structure. A tensegrity structure is a very promising candidate for this future integration due to its potentially excellent stiffness and strength-to-weight ratio, and the inherent advantage of being a multi-element structure into which actuators can be embedded. Development of these machines will utilise expertise in several fields, involving kinematics, dynamics, actuation and multi-axis motion control. The research presented in this thesis concerns the study of multi-axis actuated tensegrity structures. A form-finding method has been developed to find stable geometries and determine stiffness properties of the type of tensegrity structure proposed. It has been shown that a tensegrity structure, with practical nodes of finite size, can be designed with actuated members to give shape-changing properties while potentially allowing a good stiffness to mass ratio. An antagonistic multi-axis control scheme has been developed for the tensegrity structure. The describing function technique has been used to analyse the dead band controller in the control scheme, giving a stability criterion. An experimental actuated tensegrity system has been designed and built incorporating pneumatic muscles controlled by switching valves. Mathematical models for the experimental actuated tensegrity system have been developed in detail, including the pneumatic actuation system and the structure geometry. The dynamic behaviour of the tensegrity system has been investigated via several simulation studies, using the developed models and the proposed control scheme. Experimental validation has been successfully conducted. The multi-axis control scheme can accurately control the tensegrity structure to achieve shape changes while maintaining a desired level of internal pre-load. The mathematical models can be used as a basis for further development.

abstract: This investigation focuses on the development of uncertainty modeling methods applicable to both the structural and thermal models of heated structures as part of an effort to enable the design under uncertainty of hypersonic vehicles. The maximum entropy-based nonparametric stochastic modeling approach is used within the context of coupled structural-thermal Reduced Order Models (ROMs). Not only does this strategy allow for a computationally efficient generation of samples of the structural and thermal responses but the maximum entropy approach allows to introduce both aleatoric and some epistemic uncertainty into the system. While the nonparametric approach has a long history of applications to structural models, the present investigation was the first one to consider it for the heat conduction problem. In this process, it was recognized that the nonparametric approach had to be modified to maintain the localization of the temperature near the heat source, which was successfully achieved. The introduction of uncertainty in coupled structural-thermal ROMs of heated structures was addressed next. It was first recognized that the structural stiffness coefficients (linear, quadratic, and cubic) and the parameters quantifying the effects of the temperature distribution on the structural response can be regrouped into a matrix that is symmetric and positive definite. The nonparametric approach was then applied to this matrix allowing the assessment of the effects of uncertainty on the resulting temperature distributions and structural response. The third part of this document focuses on introducing uncertainty using the Maximum Entropy Method at the level of finite element by randomizing elemental matrices, for instance, elemental stiffness, mass and conductance matrices. This approach brings some epistemic uncertainty not present in the parametric approach (e.g., by randomizing the elasticity tensor) while retaining more local character than the operation in ROM level. The last part of this document focuses on the development of “reduced ROMs” (RROMs) which are reduced order models with small bases constructed in a data-driven process from a “full” ROM with a much larger basis. The development of the RROM methodology is motivated by the desire to optimally reduce the computational cost especially in multi-physics situations where a lack of prior understanding/knowledge of the solution typically leads to the selection of ROM bases that are excessively broad to ensure the necessary accuracy in representing the response. It is additionally emphasized that the ROM reduction process can be carried out adaptively, i.e., differently over different ranges of loading conditions. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2019

This dissertation focuses on the design, modeling, characterization and experimental verification of a class of nonlinear energy sink, based on a cantilever beam vibrating laterally between two specially shaped surfaces that limit the vibration amplitude, thus providing a variable beam length throughout its deflection, therefore producing a smooth nonlinear restoring force. First, a methodology to evaluate and visualize the energy interactions between the nonlinear energy sink and its host structure is developed. Then, an semi-analytical dynamic model for simulating the device under actual working conditions is proposed, and finally, an experimental verification step is conducted where the numerical results are compared and correlated to the experimental results.<br>

This thesis addresses the problem of identifying the modal properties of a system based only on measurements of the system responses. This situation is frequently encountered in structural dynamics and is particularly relevant for systems where the in-service excitation is not artificially reproducible. The inherent non-linearities in these systems mean that the modal properties estimated using traditional input/output techniques will be different to those exhibited in operation. A common example from the literature is an aircraft in flight where the modal properties are heavily influenced by the operating point, i.e. the combination of load, speed, altitude etc., at which the aircraft is travelling. The process of identifying the modal properties of systems in-service is called Operational Modal Analysis (OMA). Not knowing the input complicates the analysis. Most of the techniques in the literature overcome the lack of knowledge about the unmeasured excitations by assuming they are both spatially and frequentially white, i.e. of equal magnitude and with a flat autospectrum. This thesis presents a new technique for OMA which relaxes these constraints, requiring only that the system is excited by a so called cyclostationary input with a unique cyclic frequency, and that the log spectrum of the second order component of this input is frequentially smooth, as will be explained. Such systems include vehicles with internal combustion engines as the vibration from such an engine exhibits cyclostationary statistics. In this thesis, the technique is applied to a laboratory test rig and a passenger train both using an artificial input, and to a race car using the engine as the excitation. By combining cyclostationary signal processing and the concept of the cepstrum, the technique identifies the resonances and anti-resonances in the transfer functions between each response and the cyclostationary source. These resonances and antiresonances can be used to regenerate Frequency Response Functions (FRFs) and it is shown how the unknown scaling of the system can be recovered by employing finite element model updating in conjunction with this regeneration. In addition, the contribution made to model updating by the anti-resonances is also investigated. Finally, the potential of OMA to inform a model updating process is demonstrated using an experimental case study on a diesel railcar.

This thesis discusses developing new tools to probe DNA damage resulting from photoinduced chemical processes and probing the initial excited-state structural dynamics of nucleic acids and sunscreen agents. The results of this thesis show that UV resonance Raman spectroscopy (UVRRS) is an information-rich probe of chemical compositions in in situ analysis of sunscreen formulations. The results indicate that 244-nm excited UV resonance Raman spectra can provide a limit of detection of 0.23% w/w of sunscreen active ingredients (AIs), far below typical active ingredient (AI) concentrations in sunscreen formulations. UVRRS was used to probe the photostability of sunscreens, by determining the initial excited-state structural dynamics of Benzophenone-3 (BZ3), a common sunscreen active ingredient. Only minor excited-state structural distortions were obtained, based on the low displacement values, suggesting an inherently stable molecule. The largest structural change occurs along the carbonyl stretch, suggesting a strong interaction with the methanol solvent and a dissipative decay path for the molecule. Similarly, to gain an insight into how the structure of nucleic acids determine their photochemistry, UVRRS was used to probe the initial excited-state structural dynamics of 9-methyladenine (9-MeA). As for BZ3, the initial excited-state structural dynamics obtained for 9-MeA, are low, and much lower than for pyrimidine bases, providing a strong evidence for the photochemical stability of this purine base analog, compared to pyrimidines. Since DNA does not exist in isolation in cells, the role of a UV-absorbing amino acid, tryptophan, in UV-induced DNA photodamage was explored using molecular beacons (MBs) to detect the damage. The results indicate that tryptophan protective effects on DNA far outweighs their photodamage potential. However, MBs are expensive and they have some technical limitations, despite their exquisite sensitivity. Therefore, a new DNA damage detection method was developed based on smart probes (SPs). These probes are shown to be sensitive and sequence specific for detecting DNA photodamage.

Theoretical and experimental modal analysis, i.e., the computation of vibration modes from a mathematical model and from experimental data, respectively, is quite sophisticated and advanced in linear structural dynamics. However, nonlinearity is a frequent occurrence in real-world engineering structures, and the existing linear methodologies fail dramatically in the presence of nonlinear dynamical phenomena. Therefore, the present thesis focuses on the development of a practical nonlinear analog of modal analysis for properly accounting for nonlinearity in mechanical systems. The concept of nonlinear normal mode (NNM) provides solid mathematical and theoretical foundations for a rigorous, yet understandable by the practicing engineer, analysis of nonlinear dynamical behaviors. In this context, a useful framework for nonlinear modal analysis of vibrating structures, which includes the computation of NNMs from finite element models and their identification from experimental data, is proposed in this dissertation. In view of the still limited use of NNMs in structural dynamics, special attention is devoted to progress toward a practical tool that has the potential to deal with large-scale, real-world structures. Targeting an effective and exact computation of NNMs, even in strongly nonlinear regimes of motion, one original contribution of this work is to resort to numerical methods. An algorithm combining a shooting procedure and the so-called pseudo-arclength continuation method is developed. On the other hand, a nonlinear extension of phase resonance testing (also known as force appropriation) is introduced for the experimental identification of NNMs, which is another innovative aspect of the doctoral thesis. In particular, the phase lag quadrature criterion, which is used for linear experimental modal analysis, is generalized in the presence of nonlinear dynamical behavior. Academic examples are first considered to illustrate, in a simple manner, that the proposed methods form an effective and adequate framework for nonlinear modal analysis. Furthermore, more realistic structures, including a full-scale aircraft, are studied to demonstrate the potential applicability of the approach to large-scale, real-life applications.

This thesis presents a study of the wind load forces and their influence on the response of structures. The study is based on the capacity of the Proper Orthogonal Decomposition method (POD) to identify and extract organized patterns that are hidden or embedded inside a complex field. Technically this complex field is defined as a multi-variate random process, which in wind engineering is represented by unsteady pressure signals recorded on multiple points of the surface of a structure. The POD method thus transforms the multi-variate random pressure field into a sequence of load shapes that are uncorrelated with each other. The effect of each uncorrelated load shape on the structural response is relatively easy to evaluate and the individual contributions can be added linearly afterwards. Additionally, since each uncorrelated load shape is associated with a percentage of the total energy involved in the loading process, it is possible to neglect those load shapes with low energy content. Furthermore, the load shapes obtained with the POD often reveal physical flow structures, like vortex shedding, oscillations of shear layers, etc. This later property can be used in conjunction with classical results in fluid mechanics to theorize about the physical nature of different flow mechanics and their interactions. The POD method is well suited to be used in conjunction with the classical modal analysis, not only to calculate the structural response for a given pressure field but to observe the details of the wind-structure interaction. A detailed and complete application is presented here but the methodology is very general since it can be applied to any recorded pressure field and for any type of structure.

This thesis presents a study of the wind load forces and their influence on the response of structures. The study is based on the capacity of the Proper Orthogonal Decomposition method (POD) to identify and extract organized patterns that are hidden or embedded inside a complex field. Technically this complex field is defined as a multi-variate random process, which in wind engineering is represented by unsteady pressure signals recorded on multiple points of the surface of a structure. The POD method thus transforms the multi-variate random pressure field into a sequence of load shapes that are uncorrelated with each other. The effect of each uncorrelated load shape on the structural response is relatively easy to evaluate and the individual contributions can be added linearly afterwards. Additionally, since each uncorrelated load shape is associated with a percentage of the total energy involved in the loading process, it is possible to neglect those load shapes with low energy content. Furthermore, the load shapes obtained with the POD often reveal physical flow structures, like vortex shedding, oscillations of shear layers, etc. This later property can be used in conjunction with classical results in fluid mechanics to theorize about the physical nature of different flow mechanics and their interactions. The POD method is well suited to be used in conjunction with the classical modal analysis, not only to calculate the structural response for a given pressure field but to observe the details of the wind-structure interaction. A detailed and complete application is presented here but the methodology is very general since it can be applied to any recorded pressure field and for any type of structure.

The management of technology portfolios is an important element of aerospace system design. New technologies are often applied to new product designs to ensure their competitiveness at the time they are introduced to market. The future performance of yet-to-be designed components is inherently uncertain, necessitating subject matter expert knowledge, statistical methods and financial forecasting. Estimates of the appropriate parameter settings often come from disciplinary experts, who may disagree with each other because of varying experience and background. Due to inherent uncertain nature of expert elicitation in technology valuation process, appropriate uncertainty quantification and propagation is very critical. The uncertainty in defining the impact of an input on performance parameters of a system, make it difficult to use traditional probability theory. Often the available information is not enough to assign the appropriate probability distributions to uncertain inputs. Another problem faced during technology elicitation pertains to technology interactions in a portfolio. When multiple technologies are applied simultaneously on a system, often their cumulative impact is non-linear. Current methods assume that technologies are either incompatible or linearly independent. It is observed that in case of lack of knowledge about the problem, epistemic uncertainty is most suitable representation of the process. It reduces the number of assumptions during the elicitation process, when experts are forced to assign probability distributions to their opinions without sufficient knowledge. Epistemic uncertainty can be quantified by many techniques. In present research it is proposed that interval analysis and Dempster-Shafer theory of evidence are better suited for quantification of epistemic uncertainty in technology valuation process. Proposed technique seeks to offset some of the problems faced by using deterministic or traditional probabilistic approaches for uncertainty propagation. Non-linear behavior in technology interactions is captured through expert elicitation based technology synergy matrices (TSM). Proposed TSMs increase the fidelity of current technology forecasting methods by including higher order technology interactions. A test case for quantification of epistemic uncertainty on a large scale problem of combined cycle power generation system was selected. A detailed multidisciplinary modeling and simulation environment was adopted for this problem. Results have shown that evidence theory based technique provides more insight on the uncertainties arising from incomplete information or lack of knowledge as compared to deterministic or probability theory methods. Margin analysis was also carried out for both the techniques. A detailed description of TSMs and their usage in conjunction with technology impact matrices and technology compatibility matrices is discussed. Various combination methods are also proposed for higher order interactions, which can be applied according to the expert opinion or historical data. The introduction of technology synergy matrix enabled capturing the higher order technology interactions, and improvement in predicted system performance.

Performance-Based (PBE) and Consequence-Based (CBE) are new approaches to seismic design, evaluation and risk assessment, in which design criteria are devised to achieve stated performance objectives, and regional losses to civil infrastructure are mitigated through selective interventions for critical components of a civil infrastructure. These new approaches give engineers more flexibility in achieving performance goals but require substantial additional computational resources to fully achieve performance goals. As a step toward making such approaches feasible, this dissertation develops a number of computationally efficient methods for performing finite element-based structural system dynamic response analysis and reliability assessment. The Enhanced Uncoupled Modal Response History Analysis (EUMRHA) procedure developed herein is an efficient response analysis procedure to make the analysis of dynamic structural response to earthquakes in the nonlinear range less time-consuming. This technique is used to investigate the potential for aftershocks to cause additional damage to steel moment frame buildings, utilizing a technique designed to enhance the efficiency of Monte Carlo simulation in estimating low-probability events. Relatively simple probabilistic tools are proposed for purposes of rapid structural evaluation and condition assessment of damaged buildings. Finally, an analysis-based inspection scheme based on an associated probability model of connection damage is proposed for assessing the safety condition of existing buildings, and a procedure to assess the likely performance of an un-repaired building during a future earthquake is developed.