Site response analysis of liquefiable soil employing continuous wavelet transform

Propagation of the earthquake motion towards the ground surface alters both the acceleration and frequency content of the motion. Acceleration time record and Fourier amplitude spectrum of the motion reveal changes in the acceleration and frequency content. However, Fourier amplitude spectrum fails to give frequency-time variation. Wavelet transform overcomes this difficulty. In the present study, site response analysis of a liquefiable soil domain has been investigated employing wavelet transform. Three earthquake motions with distinct predominant frequencies are considered. It is revealed that the moment soil undergoes initial liquefaction, it causes a spike in the acceleration time history. Frequency of the spikes is found to be greater than the predominant frequency of the acceleration-time history recorded at the ground surface from the analysis. Interestingly, the spikes belong to the sharp tips of the shear stress-shear strain curve. Immediately after the spike, acceleration deamplification is observed. Post-liquefaction deamplification (filtering) of the frequency components is also observed.

Application of the Logistic Model to the COVID-19 Pandemic in South Africa and the United States: Correlations and Predictions

We apply the simple logistic model to the four waves of COVID-19 taking place in South Africa over the period 2020~January~1 through 2022 January 11. We show that this model provides an excellent fit to the time history of three of the four waves. We then derive a theoretical correlation between the growth rate of each wave and its duration, and demonstrate that it is well obeyed by the South Africa data. We then turn to the data for the United States. As shown by Roberts (2020a, 2020b), the basic logistic model provides only a marginal fit to the early data. Here we break the data into six "waves," and treat each one separately. For four of the six the logistic model is useful, and we present full results. We then ask if these data provide a way to predict the length of the ongoing Omicron wave in the US (commonly called "wave 4," but the sixth wave as we have broken the data up). Comparison of these data to those from South Arica, and internal comparison of the US data, suggests that this last wave will die out by about 2022-January-20.

Development of Combined Load Spectra for Offshore Structures Subjected to Wind, Wave, and Ice Loading

Fixed offshore wind turbines continue to be developed for high latitude areas where not only wind and wave loads need to be considered but also moving sea ice. Current rules and regulations for the design of fixed offshore structures in ice-covered waters do not adequately consider the effects of ice loading and its stochastic nature on the fatigue life of the structure. Ice crushing on such structures results in ice-induced vibrations, which can be represented by loading the structure using a variable-amplitude loading (VAL) sequence. Typical offshore load spectra are developed for wave and wind loading. Thus, a combined VAL spectrum is developed for wind, wave, and ice action. To this goal, numerical models are used to simulate the dynamic ice-, wind-, and wave-structure interaction. The stress time-history at an exemplarily selected critical point in an offshore wind energy monopile support structure is extracted from the model and translated into a VAL sequence, which can then be used as a loading sequence for the fatigue assessment or fatigue testing of welded joints of offshore wind turbine support structures. This study presents the approach to determine combined load spectra and standardized time series for wind, wave, and ice action.

A systematic review on papers that study on Single Nucleotide Polymorphism that affects coronavirus 2019 severity

Background COVID-19, caused by SARS-CoV-2 has become the most threatening issue to all populations around the world. It is, directly and indirectly, affecting all of us and thus, is an emerging topic dealt in global health. To avoid the infection, various studies have been done and are still ongoing. COVID-19 cases are reported all over the globe, and among the millions of cases, genetic similarity may be seen. The genetical common features seen within confirmed cases may help outline the tendency of infection and degree severity of the disease. Here, we reviewed multiple papers on SNPs related to SARS-CoV-2 infection and analyzed their results. Methods The PubMed databases were searched for papers discussing SNPs associated with SARS-CoV-2 infection and severity. Clinical studies with human patients and statistically showing the relevance of the SNP with virus infection were included. Quality Assessment of all papers was done with Newcastle Ottawa Scale. Results In the analysis, 21 full-text literature out of 2956 screened titles and abstracts, including 63,496 cases, were included. All were human-based clinical studies, some based on certain regions gathered patient data and some based on big databases obtained online. ACE2, TMPRSS2, and IFITM3 are the genes mentioned most frequently that are related to SARS-CoV-2 infection. 20 out of 21 studies mentioned one or more of those genes. The relevant genes according to SNPs were also analyzed. rs12252-C, rs143936283, rs2285666, rs41303171, and rs35803318 are the SNPs that were mentioned at least twice in two different studies. Conclusions We found that ACE2, TMPRSS2, and IFITM3 are the major genes that are involved in SARS-CoV-2 infection. The mentioned SNPs were all related to one or more of the above-mentioned genes. There were discussions on certain SNPs that increased the infection and severity to certain groups more than the others. However, as there is limited follow-up and data due to a shortage of time history of the disease, studies may be limited.

Effects of Barrier Stiffness on Debris Flow Dynamic Impact—II: Numerical Simulation

The destructive and impactful forces of debris flow commonly causes local damage to engineering structures. The effect of a deformable barrier on the impact dynamics is important in engineering design. In this study, a flow–structure coupled with Smoothed Particle Hydrodynamics model was presented to investigate the effects of barrier stiffness on the debris impact. A comparison of the results of physical tests and simulation results revealed that the proposed smoothed particle hydrodynamics model effectively reproduces the flow kinematics and time history of the impact force. Even slight deflections of the deformable barrier lead to obvious attenuation of the peak impact pressure. Additionally, deformable barriers with lower stiffness tend to deform more downstream upon loading, shifting the deposited sand toward the active failure mode and generating less static earth pressure. When the debris flow has a higher frontal velocity, the impact force on the barrier is dominated by the dynamic component and there is an appreciable effect of the stiffness of the deformable barrier on load attenuation.

Sensor data-based probabilistic monitoring of time-history deflections of railway bridges induced by high-speed trains

Structural condition monitoring of railway bridges has been emphasized for guaranteeing the passenger comfort and safety. Various attempts have been made to monitor structural conditions, but many of them have focused on monitoring dynamic characteristics in frequency domain representation which requires additional data transformation. Occurrence of abnormal structural responses, however, can be intuitively detected by directly monitoring the time-history responses, and it may give information including the time to occur the abnormal responses and the magnitude of the dynamic amplification. Therefore, this study suggests a new Bayesian method for directly monitoring the time-history deflections induced by high-speed trains. To train the monitoring model, the data preprocessing of speed estimation and data synchronization are conducted first for the given training data of the raw time-history deflection; the Bayesian inference is then introduced for the derivation of the probability-based dynamic thresholds for each train type. After constructing the model, the detection of the abnormal deflection data is proceeded. The speed estimation and data synchronization are conducted again for the test data, and the anomaly score and ratio are estimated based on the probabilistic monitoring model. A warning is generated if the anomaly ratio is at an unacceptable level; otherwise, the deflection is considered as a normal condition. A high-speed railway bridge in operation is chosen for the verification of the proposed method, in which a probabilistic monitoring model is constructed from displacement time-histories during train passage. It is shown that the model can specify an anomaly of a train-track-bridge system.

Research on seismic performance of traditional Chinese hall-style timber buildings in the Song and Yuan dynasties (960–1368 AD): a case study of the main hall of Baoguo Temple

The hall-style timber frame built in the Song and Yuan dynasties (960–1368 AD) is one of the most important structural prototypes of the traditional timber architecture in East Asia. The current research, through a typical case of the main hall of Baoguo Temple in Ningbo, China, aims to present an accurate and effective seismic performance evaluation method applicable to hall-style timber structures without time–cost expenditure. To obtain more realistic seismic response of hall-style timber frame, a simplified numerical model of the main hall of Baoguo Temple is established based on in situ measurements and low-cycle reversed loading tests results of mortise–tenon joints, moreover, nonlinear static pushover analysis has been performed to quantify the seismic performance levels under five loading conditions. The generalized force–deformation relationship of the timber plastic hinges is modified regarding to the moment–rotation curves of four special mortise–tenon joints. The seismic behaviour of global hall-style timber frame is evaluated through capacity spectrum method and verified by time history analysis, local failure mechanisms are evaluated by the occurrence sequence of plastic hinges. Finally, a performance-based assessment method adequate for the traditional hall-style timber architectures has been proposed with comparison to the current codes. The results have shown that the structural stiffness of the width-direction is less than that of the depth direction due to the asymmetrical configuration of the timber frame, and the building can maintain a stable state under large lateral displacement before collapsing. The inter-storey drift angles of the building under peak ground accelerations of 0.1 g, 0.2 g, and 0.3 g are less than the suggested ultimate values in the current local codes, however, the main hall represents to be more vulnerable to damage when suffer seismic action along the width-direction. This research can provide a reference for seismic performance evaluation and preventive conservation of ancient hall-style timber architectural heritage.

Seismic Performance of RC Column Using Fiber Hinge Concept with Time Integration Method

Recent seismic events showed the importance of understanding the structural performance of RC column that can be predicted numerically. The accuracy of column performance depends on type of the analysis and representation of seismic effect. Therefore, in this paper a nonlinear time history analysis has been performed to assess the seismic performance of bridge column using fiber hinge concept with time integration method using sap2000 software. A long bridge RC column is utilized and subjected to seismic excitation. The column has been divided into different size and numbers of fiber to assess the accuracy of the analysis and time consuming to analyze each case of fiber hinges. In addition, this paper used three-time integration methods, Newmark, Hilber-Hughes-Taylor, and Chung & Hulbert to predict the most suitable method to be used in column seismic analysis. The time history displacement and base shear in addition to moment rotation of the column are the most important factors to evaluate the column seismic performance. The analysis results demonstrated that the most suitable time integration method is Hilber-Hughes-Taylor for such type of the analysis since it gives more stable base shear result than other two methods. Furthermore, the results indicated that the accuracy of seismic performance increased by number of fibers incremental. Moreover, the number of steel fibers should be equal to the number of bars with same area and location. The unconfined and confined concrete should be divided into small areas to get accurate prediction of column seismic performance.

Research on the Dynamic Response of Gravity Dam under Blasting Vibration

With the continuous development of blasting technology, it has been widely used in various construction projects. While bringing convenience to construction, it also has a series of negative effects on surrounding buildings (structures), especially the negative effects of blasting vibration on buildings (structures), which has been paid close attention by scholars at home and abroad. For blasting vibration on the dynamic response of the gravity dam to produce, this article adopts the method of numerical simulation, the finite element software ANSYS is applied, the numerical calculation model of concrete gravity dam is established and the dynamic time-history analysis is calculated, in the different blasting conditions, the blasting vibration on the dynamic response of gravity dam is obtained, the calculation and analysis results as basis is supplied for the selection of the blasting vibration monitoring part of the gravity dam.