The quest for controlled fusion energy has been ongoing for over a half century. The demonstration of ignition and energy gain from thermonuclear fuels in the laboratory has been a major goal of ...fusion research for decades. Thermonuclear ignition is widely considered a milestone in the development of fusion energy, as well as a major scientic achievement with important applications in national security and basic sciences. The US is arguably the world leader in the inertial connement approach to fusion and has invested in large facilities to pursue it, with the objective of establishing the science related to the safety and reliability of the stockpile of nuclear weapons. Although signicant progress has been made in recent years, major challenges still remain in the quest for thermonuclear ignition via laser fusion. Here, we review the current state of the art in inertial connement fusion research and describe the underlying physical principles.
•User-defined parameters in Data-Driven Stochastic Subspace Identification are studied.•Increasing the rows of the future output matrix can improve the identification.•Damping ratios are better ...identified with a proper selection of the parameters.
The paper focuses on the time domain output-only technique called Data-Driven Stochastic Subspace Identification (DD-SSI); in order to identify modal models (frequencies, damping ratios and mode shapes), the role of its user-defined parameters is studied, and rules to determine their minimum values are proposed. Such investigation is carried out using, first, the time histories of structural responses to stationary excitations, with a large number of samples, satisfying the hypothesis on the input imposed by DD-SSI. Then, the case of non-stationary seismic excitations with a reduced number of samples is considered. In this paper, partitions of the data matrix different from the one proposed in the SSI literature are investigated, together with the influence of different choices of the weighting matrices.
The study is carried out considering two different applications: (1) data obtained from vibration tests on a scaled structure and (2) in-situ tests on a reinforced concrete building. Referring to the former, the identification of a steel frame structure tested on a shaking table is performed using its responses in terms of absolute accelerations to a stationary (white noise) base excitation and to non-stationary seismic excitations of low intensity. Black-box and modal models are identified in both cases and the results are compared with those from an input-output subspace technique. With regards to the latter, the identification of a complex hospital building is conducted using data obtained from ambient vibration tests.
In recent years, a new research direction in structural condition assessment has been focusing on developing automated or semi-automated procedures to identify a structure’s modal parameters from its ...response measurements. This is because long-term structural monitoring systems rely on the implementation of system identification methodologies that often involve the intervention of an expert user with an acquired experience in the field.
This paper aims to offer a semi-automated methodology for extracting the modal parameters independently of the chosen parametric system identification technique with minimum user involvement in the parameter selection process. Here, the framework is applied to two different parametric system identification algorithms: Data-Driven Stochastic Subspace Identification (DD-SSI) and Output Only Observer Kalman Filter (O/O OKID). The procedure can be represented as a multi-stage strategy where unsupervised tools and three clustering options are offered to the user to reach a reliable estimate of the modal parameters. The proposed procedure is validated with an application in the operational modal analysis of an existing hospital structure located in Italy. The results demonstrated excellent accuracy and robust performance of the methodology, even in the presence of closely spaced modes. The proposed procedure helps to improve the data analysis process in continuous monitoring, where usually, the algorithm’s parameters need to be constantly updated by the user.
•Semi-automated operational modal analysis with low user interaction•Methodology independent from the parametric system identification algorithm adopted•Three clustering techniques available to the user: two k-means approaches and DBSCAN•Application on the analysis of vibration data recorded on a RC hospital structure•Validation using two system identification algorithms: DD-SSI and O/O OKID
The self-similar nonlinear evolution of the multimode ablative Rayleigh-Taylor instability (ARTI) is studied numerically in both two and three dimensions. It is shown that the nonlinear multimode ...bubble-front penetration follows the α_{b}A_{T}(∫sqrtgdt)^{2} scaling law with α_{b} dependent on the initial conditions and ablation velocity. The value of α_{b} is determined by the bubble competition theory, indicating that mass ablation reduces α_{b} with respect to the classical value for the same initial perturbation amplitude. It is also shown that ablation-driven vorticity accelerates the bubble velocity and prevents the transition from the bubble competition to the bubble merger regime at large initial amplitudes leading to higher α_{b} than in the classical case. Because of the dependence of α_{b} on initial perturbation and vorticity generation, ablative stabilization of the nonlinear ARTI is not as effective as previously anticipated for large initial perturbations.
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