Summary
Incremental dynamic analysis (IDA) leads to curves expressed in terms of structural response versus intensity, commonly known as the IDA curves. It is known that implementation of IDA usually ...involves significant computational effort and most often significant scaling of the original records to various intensity levels. Employing as the performance variable the critical demand to capacity ratio (DCR) throughout the structure, which is equal to unity at the onset of the limit state, facilitates the identification of the intensity values at the onset of a desired limit state and hence the implementation of the IDA procedure. Employing the structural response to un‐scaled records and the corresponding regression‐based response predictions (a.k.a., the “Cloud Analysis”) helps in identifying the range of intensity values corresponding to demand to capacity ratio values in the vicinity of unity. The Cloud to IDA procedure for structural fragility assessment is proposed on the premise of exploiting the Cloud Analysis results to obtain the IDA curves both with minimum number of analyses and minimum amount of scaling. The transverse frame of a shear‐critical 7‐story older RC building in Van Nuys, CA, which is modeled in Opensees with fiber‐section considering the flexural‐shear‐axial interactions and the bar slip, is employed as a case study. It is demonstrated, by comparing the results to IDA and other state of the art non‐linear dynamic procedures based on no scaling or spectral‐shape‐compatible scaling, that the Cloud to IDA procedure leads to reliable results in terms of structural fragility and risk for the prescribed limit state.
In this paper, two-stage approaches are proposed to study damage detection, localization and quantification in Functionally Graded Material (FGM) plate structures. Metal and Ceramic FGM plates are ...considered using three different composite materials: Al/Al2O3, Al/ZrO2-1, and Al/ZrO2-2. The FGM plates are modelled using IsoGeometric Analysis (IGA), which is more efficient than the classical Finite Element Method (FEM). Using a power-law distribution of the volume fractions of the plate constituents, the material properties of the plates are expected to vary continuously through their thickness. Improved damage indicator based on Frequency Response Function (FRF) is employed to predict the damaged elements in the first stage. A robust and efficient Improved Artificial Neural Network using Arithmetic Optimization Algorithm (IANN-AOA) is implemented for damage quantification problem in the second stage. The main idea is based on eliminating the healthy elements from the numerical model by the improved indicator. Next, collected data from damaged element based on damage index of an improved indicator is used as input and damage level as output. To prove the robustness of IANN-AOA, a Balancing Composite Motion Optimization (BCMO) is considered to improve ANN (IANN-BCMO) and is used for comparison. The results show that the improved indicator can predict the damaged elements with high precision. For damage quantification, IANN-AOA provides more accurate results than IANN-BCMO.
The method of incremental dynamic analysis (IDA) is one of the most accurate nonlinear seismic analyses. IDA is a time-consuming method and has a high computational cost. Also, an IDA curve should be ...obtained from the building analysis subjected to a series of earthquakes that should cover all regions of the structural responses. In this paper, the discrete wavelet transform is used to solve these problems. The results showed that the use of the filtered records reduces the computational cost and time about 87.4% and 73%, respectively, while the maximum error is just about 7.6%.
A ransomware is a unique class of malware which has gotten extremely famous in digital crooks to corkscrew cash. It categorizes the client confines by accessing their machines (PCs, cell phones and ...IoT gadgets) unless the payoff is paid. Consistently, security specialists report numerous types of ransomware assaults, including ransomware families. User's data will be collected at the time of dynamic process. The collected data will be in crypto ransomware type from that we can extract features like IP address, file length, URL. We will do dynamic analyse of the presently data with the antecedent data. Using machine learning algorithm (by combining Random Forest, Gradient Tree Boosting and Support Vector machine algorithm) we can classify the data as benign or ransomware. The achievement rate of classification using machine learning algorithm is 98.45% with false rate 0.01.The proposed achievement rate will be compared among linear regression, navie Bayes and adaboost algorithm. Gandcrab ransomware-Version, algorithm is to be identified.
Summary
It is desirable that nonlinear dynamic analyses for structural fragility assessment are performed using unscaled ground motions. The widespread use of a simple dynamic analysis procedure ...known as Cloud Analysis, which uses unscaled records and linear regression, has been impeded by its alleged inaccuracies. This paper investigates fragility assessment based on Cloud Analysis by adopting, as the performance variable, a scalar demand to capacity ratio that is equal to unity at the onset of limit state. It is shown that the Cloud Analysis, performed based on a careful choice of records, leads to reasonable and efficient fragility estimates. There are 2 main rules to keep in mind for record selection: to make sure that a good portion of the records leads to a demand to capacity ratio greater than unity and that the dispersion in records' seismic intensity is considerable. An inevitable consequence of implementing these rules is that one often needs to deal with the so‐called collapse cases. To formally consider the collapse cases, a 5‐parameter fragility model is proposed that mixes the simple regression in the logarithmic scale with logistic regression. The joint distribution of fragility parameters can be obtained by adopting a Markov Chain Monte Carlo simulation scheme leading directly to the fragility and its confidence intervals. The resulting fragility curves compare reasonably with those obtained from the Incremental Dynamic Analysis and Multiple Stripe Analysis with (variable) conditional spectrum–compatible suites of records at different intensity levels for 3 older reinforced concrete frames with shear‐, shear‐flexure‐, and flexure‐dominant behavior.
•2D and 3D nonlinear pushover and incremental dynamic analyses (IDA) were performed.•Using OpenSees the behavior of a 4-story modular steel building (MSB) was evaluated.•Diaphragm interactions, ...relative displacements and rotations of modules were studied.•The force transfer through connections and column discontinuities are considered.
Modular steel construction is a relatively new construction technique that considerably reduces the time spent on the construction site. However, due to the detailing and assembly requirements of multi-story modular steel buildings (MSBs), these systems are prone to undesirable failure mechanisms during large earthquakes. In this paper a 4-story MSB is designed considering realistic constraints posed during the modular construction. Using a detailed model in OpenSees an assessment of the seismic demand and capacity of this MSB is provided by performing nonlinear static pushover and incremental dynamic analyses (IDA) in two and three dimensions. Diaphragm interactions, relative displacements and rotations between modules, the force transfer through horizontal connections, column discontinuity coupled with possible high inelasticity concentration in vertical connections are some other important aspects that are specifically considered. The results that are summarized with relevant conclusions provide a better insight to the dynamic behavior of multi-story MSBs.