The report presents results of using the digital filters in numerical algorithms for the problem of restoration of the dynamically distorted signal from the observed one knowing the transfer function ...of the measuring transducer based on the spline method. Two approaches were used to reconstruct the dynamically distorted incoming signal in the presence of interference of different nature. In the first one, the moving average filter or the Savitsky–Goley filter were used. The second approach presents a new numerical algorithm, according to which the reconstructed signal is a result of averaging of approximate optimal dynamic measurements obtained by combining the spline method and the sampling theorem. The report presents the results of computational experiments of each approach on a data set obtained during bench tests of the pressure sensor. To demonstrate the effectiveness of the proposed methods the numerical results are compared with the data of the control sensor.
This paper aims at introducing a methodology to compute stable coupled state-space models for dynamic substructuring applications by introducing two novel approaches targeted to accomplish this task: ...(a) a procedure to impose Newtons’s second law without relying on the use of undamped RCMs (residual compensation modes) and (b) a novel approach to impose stability on unstable coupled state-space models. The enforcement of stability is performed by dividing the unstable model into two different models, one composed by the stable poles (stable model) and the other composed by the unstable ones (unstable model). Then, the poles of the unstable state-space model are forced to be stable, leading to the computation of a stabilized state-space model. If this model is composed by real poles, it should be divided into two different ones, one composed by the pairs of complex conjugate poles and the other composed by the real poles. Afterwards, to make sure that the Frequency Response Functions (FRFs) of the stabilized model well match the FRFs of the unstable model, the Least-Squares Frequency Domain (LSFD) method is exploited to update the modal parameters of the stabilized model composed by the pairs of complex conjugate poles. The validity of the proposed methodologies is presented and discussed by exploiting experimental data. Indeed, by exploiting the FRFs of a real system, accurate state-space models respecting Newton’s second law are computed. Then, decoupling and coupling operations are performed with the identified state-space models, no matter the models resultant from the decoupling/coupling operations are unstable. Stability is then imposed on the computed unstable coupled model by following the approach proposed in this paper. The methodology proved to work well on these data. Moreover, the paper also shows that the coupled state-space models obtained using this methodology are suitable to be exploited in time-domain analyses and simulations.
•Accurate SSMs verifying Newton’s second law can be computed by using damped RCMs.•Reliable stable coupled SSMs can be computed from unstable coupled SSMs.•Iterative algorithms are not mandatory to compute stable coupled SSMs.•All steps to compute accurate stable coupled SSMs are described and deeply analyzed.•Experimental validation of the discussed approaches is provided.
3D-printing technology is opening up new possibilities for the co-printing of sensory elements. While quasi-static research has shown promise, the dynamic performance has yet to be researched. This ...study researched smart 3D structures with embedded and printed sensory elements. The embedded strain sensor was based on the conductive PLA (Polylactic Acid) material. The research was focused on dynamic measurements of the strain and considered the theoretical background of the piezoresistivity of conductive PLA materials, the temperature effects, the nonlinearities, the dynamic range, the electromagnetic sensitivity and the frequency range. A quasi-static calibration used in the dynamic measurements was proposed. It was shown that the temperature effects were negligible, the sensory element was linear as long as the structure had a linear response, the dynamic range started at ∼ 30 μ ϵ and broadband performance was in the range of few kHz (depending on the size of the printed sensor). The promising results support future applications of smart 3D-printed systems with embedded sensory elements being used for dynamic measurements in areas where currently piezo-crystal-based sensors are used.
•An approach of system identification for combining both static and dynamic measurements.•A measurement selection strategy to detect abnormal measurements.•Applied to a highway flyover bridge in ...Singapore.•Used the surrogates based on Gaussian processes to reduce computation time.
In situ measurements have the potential to provide valuable information about the safety and the condition of bridges through implementation of system-identification methodology. A significant amount of research has focused on system identification using either dynamic or static measurements separately. Realizing the complementary relationship between static and dynamic measurements, traditional model updating methods adopt error functions to account for the residual between modeling and measured values for various types of measurements. Behavioral models may be inaccurate due to incomplete representation of modeling and measurement uncertainties. Furthermore, the normalization of error functions may bring additional uncertainty to the identification process. In this paper, an approach based on the model falsification method is proposed to combine both static and dynamic measurements with explicit consideration of both modeling and measurement uncertainties. A measurement selection strategy is also used to help detect abnormal measurements. The approach has been evaluated using a highway flyover bridge in Singapore. Dynamic measurement data include natural frequencies and mode shapes whereas static measurement data include inclinations, deflections and strains. By combining both static and dynamic measurements, this approach leads to falsification of additional model instances and obtains a more precise prediction of parameter values than approaches which interpret static measurements only.
•The in-situ dynamic measurements of the track structure in an operating subway line were conducted;•The multi-objective functions according to the simulated and measured results were proposed;•The ...sensitivity analysis based on the Latin Hypercube Sampling (LHS) was designed and implemented;•The model updating process based on the multi-island genetic algorithm (MIGA) was devised and performed;•Results indicate that the proposed method is effective and feasible.
With the rapid development of subway transportation, it has brought great convenience to us, but the induced vibration has seriously influenced our daily life. The simulation models are the major approach to investigate this problem. However, due to the discreteness and randomness of the physical parameters of various materials and inappropriate simplifications of the finite element (FE) model, the simulated results cannot reflect the actual dynamic responses accurately. To solve this issue, we carried out systematic investigations as follows: (1) conducting in-situ dynamic measurements of the track structure in an operating subway line; (2) establishing a simulation model of the vehicle-track coupled system; (3) proposing the multi-objective functions according to the simulated and measured results; (4) designing and implementing the sensitivity analysis based on the Latin Hypercube Sampling (LHS); (5) devising and performing the model updating process based on the multi-island genetic algorithm (MIGA). The results reveal that the updated model can simulate the dynamic responses accurately, and the simulation results have an excellent agreement with the in-situ measurements. Overall, the developed method in this work can obviously improve the accuracy of the dynamic simulation of the track structure and provide a way for the model updating and vibration analysis of the vehicle-track coupled system.
We present a new algorithm for processing the results of dynamic measurements in which it is necessary to find the input signal based on the known output or observed signal and the known transfer ...function of the measuring device. Previously, the authors developed a theory of optimal dynamic measurements in which methods of optimal control theory were successfully used to reconstruct dynamically distorted signals. On model examples, the first numerical algorithms of the theory of optimal dynamic measurements have shown the efficiency of the result in terms of the achieved error with a considerable computation time. The proposed numerical algorithm for solving the problem under study permits one to reduce the computation time more than fivefold. The necessary theoretical information, the general scheme of the algorithm, experimental data, and the results of processing experimental data according to the proposed algorithm are presented.
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•The largest multi-city database with dynamic pulmonary function monitoring in adult asthmatic patients.•We found robust associations of decreased pulmonary function with PM2.5 and ...PM2.5-10.•PM2.5-10 may be more hazardous than PM2.5 in reducing pulmonary function.•The associations of PM2.5 and PM2.5-10 occurred at lag day 1 and vanished a week later.
The short-term associations of fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) with pulmonary function were inconsistent and rarely evaluated by dynamic measurements. Our study aimed to investigate the associations of PM2.5 and PM2.5–10 with real-time pulmonary function. We conducted a longitudinal study based on dynamic pulmonary function measurements among adult asthmatic patients in 25 cities of 19 provincial regions of China from 2017 to 2020. Linear mixed-effects models combined with polynomial distributed lag models were used for statistical analysis. A total of 298,396 records among 4,992 asthmatic patients were evaluated. We found generally inverse associations of PM2.5 and PM2.5–10 with 16 pulmonary function indicators that were independent of gaseous pollutants. The associations occurred at lag 1 d, became the strongest at lag 4 d, and vanished a week later. PM2.5-10 had stronger associations than PM2.5, especially in southern China. Nationally, an interquartile increase in PM2.5-10 (28.0 μg/m3) was significantly associated with decreases in forced expiratory volume in 1 s (FEV1, 41.6 mL), the ratio of FEV1 in forced vital capacity (1.1%), peak expiratory flow (136.9 mL/s), and forced expiratory flow at 25–75% of forced vital capacity (54.3 mL/s). We observed stronger associations in patients of male, BMI ≥ 25 kg/m2, age ≥ 45 years old, and during warm seasons. In conclusion, this study provided robust evidence for impaired pulmonary function by short-term exposure to PM2.5 and PM2.5-10 in asthmatic patients using the largest dataset of dynamic monitoring. The associations can last for one week and PM2.5-10 may be more hazardous.
Although the ice phase greatly influences the properties of ice cream, other structural components also affect its rheological behavior, particularly after melting. In this study, mix viscosity ...(serum phase viscosity), extent of fat destabilization (FD), and overrun were manipulated to produce different microstructures. The effects of these structural components were evaluated on the rheological properties of the ice creams and melted ice creams. In oscillatory thermorheometry, mix viscosity and then overrun, influenced G’ and tanδ below −10 °C. When ice phase decreased (between −10 and −2.7 °C), mix viscosity had reduced effects, but continued to strongly affect G’ and tanδ, followed by FD, and with lower effects from overrun. When the ice phase was completely melted at 0 °C, FD had most influence on G’ and tanδ, followed by overrun, and with lower effects from mix viscosity. In creep/recovery test, six‐element model described well creep behavior of melted ice cream at 0 °C. Viscous behavior at lower shear rate (η0 0 °C) was most influenced by mix viscosity, followed by FD, and lower overrun effects. In stress growth measurement, transient behavior, represented by σY 0 °C, of melted matrix at 0 °C was most influenced by FD, followed by mix viscosity, with lower overrun effects. In flow ramp measurement, Hysteresis Area was most affected by mix viscosity, followed by overrun, and with lower FD effects. Moreover, correlation between Hyst 0 °C and tanδ Peak suggested that structure formation affected the magnitude of tanδ Peak. These results document the importance of microstructure on properties of melted ice cream.
Practical Application
The understanding of how structural components, such as mix viscosity, fat destabilization, and overrun, affect the ice cream matrix can help manufacturers to control its rheological behavior. The influence of these structural components on the G’, tanδ, η0 0 °C, σY 0 °C, and Hyst 0 °C can be also used to understand the structural rearrangements that occur in meltdown tests and sensory analyses for future studies. Therefore, elucidation of these mechanisms on the rheological properties can directly assist in quality control and new product development in the ice cream industry.
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