Development of a Modal Selection Method for Full Strain Field Estimation

Full field response of a structure is critical for evaluating the performance of large slender structures. Since only several discrete measurements can be acquired during operation, the data expansion method is important for the estimation of the full field responses of the large complex structure. In previous studies, modal transformation methods were mainly applied in model reduction/expansion and global shape sensing. Compared to other expansion methods, the modal method is straightforward to implement and computational efficient, which makes it the most suitable approach for real-time expansion. However, only the first several modes were included in the modal transformation method in previous studies. Since the errors due to truncated mode components can occur under high frequency band excitations, it is necessary to include all of the modes that contribute significantly to the responses of the structure. Therefore, in this study, a modal selection method based on operational modal analysis (OMA) is proposed for selecting proper modes. The modal characteristics of the system were derived with the strain data at several discrete locations. The contribution of each mode was quantified. By sorting the modes based on their contribution, the most significant modes can be used in the expansion process. Two operational modal analysis methods, stochastic system identification (SSI) and frequency domain decomposition (FDD), were considered and compared. The proposed approach was implemented with a computational model. Considerable improvement has been observed when high bandwidth excitations were added. The proposed modal selection method can successfully rank the participated modes. It can improve the accuracy of the modal transformation approach as shown in the impact loading case. It can be used for data expansion even when high frequency band is excited. Finally, we believe the novel methods presented in this study could be used in the development of more reliable health monitoring systems for turbomachinery.

La selección modal en las cláusulas adverbiales introducidas por como si

The conjunction como si select usually in the subordinated adverbial clauses (modal, conditional and comparative) the tenses of the subjunctive mood cantara / cantase and hubiera / hubiese cantado. However in some papers is mentioned the possibility of the construction of como si with the tenses of indicative mood. This paper contains the analysis of the modal selection after como si and, particularly, the possible substitution of subjunctive by the indicative tenses. The analyses is realized on the ground of the corpus of Real Academia Española (CORPES XXI, CREA, CREA. Versión anotada).

The why, what, where, when and how of goal-directed choice: neuronal and computational principles

The central problems that goal-directed animals must solve are: ‘ What do I need and Why , Where and When can this be obtained, and How do I get it?' or the H4W problem. Here, we elucidate the principles underlying the neuronal solutions to H4W using a combination of neurobiological and neurorobotic approaches. First, we analyse H4W from a system-level perspective by mapping its objectives onto the Distributed Adaptive Control embodied cognitive architecture which sees the generation of adaptive action in the real world as the primary task of the brain rather than optimally solving abstract problems. We next map this functional decomposition to the architecture of the rodent brain to test its consistency. Following this approach, we propose that the mammalian brain solves the H4W problem on the basis of multiple kinds of outcome predictions, integrating central representations of needs and drives (e.g. hypothalamus), valence (e.g. amygdala), world, self and task state spaces (e.g. neocortex, hippocampus and prefrontal cortex, respectively) combined with multi-modal selection (e.g. basal ganglia). In our analysis, goal-directed behaviour results from a well-structured architecture in which goals are bootstrapped on the basis of predefined needs, valence and multiple learning, memory and planning mechanisms rather than being generated by a singular computation.

Research on Modal Parameter Identification of the Cable Stayed Bridges Based on the Singular Value Decomposition of the Power Spectrum

In view of the modal parameter identification when only has the output signals of the system under ambient excitations has difficulty, a new method which can identify the structural modal parameters exactly based on singular value decomposition of the power spectrum is put forward. This method is used in the modal parameter identification of a cable stayed bridge under ambient excitations, and the identification frequency is compared with the finite element computation frequency. The results indicated that this method has overcome the subjectivity in modal selection of frequency domain pick-peaking method, choose eigenfrequency and identify close modal accurately and objectively. With the advantages of practical, processing simply and fast.