Generalized graphic-analytical model for evaluation of the fatality / structural collapse production mechanism on a building affected by an explosion

The paper highlights the generalized grapho-analytical model of analysis and evaluation of the mechanism of occurrence of the event scenario for the production of fatality/structural collapse in the case of a building affected by explosion. This mathematical model is based on research results in the field of civil explosives for the technological/occupational risks estimation and assessment, as well as threats to the security of protected areas that may be vulnerable through acts of malice. The process of quantitative risk assessment associated with explosion phenomena as a result of the detonation of an explosive charge, allows estimating result indicators based on the use of algorithms and models specific to associated hazards, in order to model the effects and consequences of event scenarios.

Harmonious K-I-O Co-modification of g-C3N4 for Improved Charge Separation and Photocatalysis

Co-modification of graphitic carbon nitride (g-C3N4) photocatalysts can maximally optimize its intrinsic photoelectric structures, but usually involve complex multistep reactions, thus is challenging because the structural collapse and active sites...

Estimating collapse risk and reliability of concrete moment frame structure using response surface method and hybrid of artificial neural network with particle swarm optimization algorithm

Structural collapse performance assessment has been at the center of many researchers’ interest due to complications of this phenomenon and uncertainties involved in modeling the simulation of the structural collapse response. This research aims to predict the structural collapse responses including mean collapse capacity, collapse standard deviation, and collapse drift by considering modeling uncertainties and then estimating collapse fragility curves, collapse risk, and reliability using Response Surface Method (RSM) and Artificial Neural Network (ANN). Modeling uncertainties for evaluating collapse responses are the parameters of the modified Ibarra-Krawinkler moment-rotation curve. Moreover, to analyze the structural uncertainty, the correlation between the model parameters in one component and between two structural components was considered. The Latin Hypercube Sampling (LHS) method and Cholesky decomposition were used to produce independent and dependent random variables, respectively. To predict the collapse responses of the structure, taking into account the uncertainties, as the number of uncertainties increases, the number of simulations for the uncertainties also increases, leading to a significant increase in the computational effort to estimate the structural responses, in the presence of a limited number of samples for uncertainties, a hybrid of ANN with PSO algorithm was used to reduce the computational effort in order to estimate the collapse fragility curves, collapse risk, and structural reliability. The results show that structural collapse responses can be predicted with appropriate accuracy by producing a limited number of samples for uncertainties and using an ANN-PSO algorithm.

The volcanic geology of Morella Crater, Ganges Cavus and Elaver Vallis, Mars

Mars contains a large number of yet unexplained collapse features, sometimes spatially linked to large outflow channels. These pits and cavi are often taken as evidence for collapse due to the release of large volumes of pressurized groundwater. One such feature, Ganges Cavus, is an extremely deep (~ 6 km) collapse structure nested on the southern rim of Morella Crater, a 78-km-diameter impact structure breached on its east side by the Elaver Vallis outflow channel. Previous workers have concluded that Ganges Cavus, and other similar collapse features in the Valles Mariners area formed due to catastrophic release of pressurized groundwater that ponded and ultimately flowed over the surface. However, in the case of Ganges Cavus and Morella Crater, I show that the groundwater hypothesis cannot adequately explain the geology. The geology of Morella Crater, Ganges Cavus and the surrounding plains including Elaver Vallis is dominantly volcanic. Morella Crater contained a large picritic to komatiitic lava lake (> 3400 km3), which may have spilled through the eastern wall of the basin. Ganges Cavus is a voluminous (> 2100 km3) collapsed caldera. Morella Crater, Ganges Cavus and Elaver Vallis illustrate a volcanic link between structural collapse, formation and potential spillover of a large lake, and erosion and transport, but in this case, the geology is volcanic from source to sink. The geologic puzzle of Morella Crater and Ganges Cavus has important implications for the origins of other collapse structures on Mars and challenges the idea of pressurized groundwater release on Mars.

Stepwise collapse of a giant pore metal–organic framework

Defect engineering is used to augment the porosity of MIL-100. Incorporation of defects leads to structural collapse and ultimately causes amorphisation. Pair distribution function analysis reveals a stepwise collapse of the hierarchical structure.

Well-controlled Three-dimensional Tree-like Core-shell Structural Electrode for Flexible All-solid-state Supercapacitors with Favorable Mechanical and Electrochemical Durability.

Although coupling high pseudocapacitive species with flexible carbon substrates to fabricate hybrid electrodes holds promise for high-performance flexible supercapacitors, the structural collapse and performance degradation under repeated mechanical deformation remain...