State Of Collapse Research Articles

Upset or Collapse Detection System for ASD Children Using Smart Watch with Machine Learning Algorithm

ASD is characterised by severe and violent behavioural issues that are referred to as "meltdowns (upset) or tantrums (collapse)" and can include aggression, hyperactivity, intolerance, unpredictability and self-injury. This research work intends to develop and implement a non-invasive real-time Upset or Collapse Detection System (UCDS) for people with ASD. With a certain model of smart watch, the non-invasive biological indications such as Pulse Rate (PR), Skin Temperature (ST), and Galvanic Skin Reaction (GSR) can be artificially captured. In order to create the UCDS, deep learning algorithms like CNN, LSTM, and the hybrid of CNN-LSTM are given the physiological signals that are captured to a server. The deep learning algorithm could recognise aberrant upset or collapse states from real-time physiological signs after being trained. Deep learning algorithms including CNN, LSTM, and CNN-LSTM are used to train and test the proposed UCDS system, and it is discovered that hybrid CNN-LSTM beat them all with an average training and testing accuracy of 96% and a low mean absolute error (MAE) of 0.10 for training and 0.04 for testing. Furthermore, the suggested UCDS system is supported by 93% of the ASD caretakers.

SEISMIC FRAGILITY EVALUATION OF SOIL-PILE-STRUCTURE INTERACTION EFFECTS SUBJECTED TO MAINSHOCK-AFTERSHOCK RECORDS

In most current seismic design on bridges, only mainshock actions are considered without incorporating the effect of mainshock-aftershock (MA) sequences and interaction soil-pile.However, a large mainshock usually triggers numerous aftershocks in a short period. This paperstudy the effect of mainshock-aftershock sequences on the behavior of interaction Soil-pile-structure system (ISPS). abeam on nonlinearWinkler foundation (BNWF) model is usingand subjected to non-linear static analysis and incremental dynamic analysis (IDA) leading finally to the fragility curves which are developed. These analyses aim to capture the collapse state of structures under aftershock events preceded by various mainshock levels. Results obtained from capacity curve, incremental dynamic and fragility curves of ISSP system.The analytical results show that in the MA sequences,for dense soil the vulnerable of mainshock-aftershock (MS-AS) loading are more damage due to mainshock loading for all diameter of the pile and the mass. For soft soil are more vulnerable to damage due to mainshock-aftershock (MS-AS) loading. But in the stiff clay the effect of mainshock-aftershock (MS-AS) loading for all the diameter of pile and for masse are neglected.
 Keywords:bridge,interaction soil-pile-structure, Winkler foundation, dynamic analysis, fragility curves,mainshock-aftershock.

Assessing the seismic behavior of structures controlled with a novel elastoplastic-tuned mass damper inerter considering the effects of soil-structure interactions

In this paper, an elastoplastic-tuned mass damper inerter (PTMDI) is introduced, and its practical advantages under soil-structure interaction are investigated.For this purpose, a nine-story building frame equipped with PTMDI is modeled nonlinearly in the OpenSees software using the concentrated plasticity model. The Bald Eagle Search Optimization Algorithm calculates the PTMDI parameters for a structure with a fixed base or located on three soil types (i.e., soft, medium, and stiff soils).The objective function is the minimization of the Park-Ang damage index of the controlled structure. The results show that PTMDI has dramatically reduced the Park-Ang damage index in the controlled structure using the inertia-strengthening effect and the nonlinear behavior of the PTMDI system. The results show that the PTMDI has reduced the structural damage index of the controlled structures by more than 50% compared to the uncontrolled ones since the controlled system reduces the deformation of the members and drift story. Also, more energy is dissipated because the spring of the control system goes into the nonlinearity. It has also depicted that the PTMDI increases the performance level of the structure from the collapse state to the life safety state. Due to the inertia-enhancing effect of the PTMDI, the mass ratio of the proposed control system does not significantly affect the behavior of the structure. Therefore, the dynamic responses of the structure can be controlled with a small mass.

HoTDAM! An easy-to-use automated assay expands the inducible thermotolerance phenotype in Drosophila melanogaster: Heat hardening reduces motility

To quantify heat tolerance in insects, two manual observation measures are typically implemented: the time to physiological collapse at a static noxious temperature (time to knockdown; TKD) or the temperature at which collapse occurs as temperature increases (critical thermal maximum; CTmax). Both assay modalities focus on physiological collapse, neglecting the prior behavioral processes. In this study, the locomotion response of Drosophila melanogaster to relatively high temperature (39 and 40.5 °C) was quantified using the TriKinetics Drosophila Activity Monitor (DAM2 system). The absence of locomotion was defined as the state of physiological collapse resulting from extended exposure to high temperature. An easy-to-use executable application that allows the user to automatically extract individual TKD from the activity data was developed. For validation, manual TKD assays were performed in parallel to automated assays across multiple factors, including sex, hardening, recovery time after hardening, and assay temperature, which gave similar results. In terms of behavioral aspects, heat hardening consistently led to reduced activity during a subsequent heat stress, irrespective of assay temperature, sex, or recovery time after hardening. Our automated heat tolerance assay utilizing the DAM2 system is one way to expand the scope of the heat tolerance phenotype to include a behavioral component in conjunction with the traditional TKD measure.

FAST-AlertNet: Early warning fire-induced collapse of large-span steel truss structures

Large-span steel trusses are often adopted as roof structures of public and industrial buildings. Besides significant property loss, the unexpected and sudden collapse of large-span steel trusses caused by fires also threatens the lives of firefighters and trapped people in fires. To prevent casualties to the greatest extent, real-time evaluation of the structural collapse state of the building at fire rescue scenes is critical. This paper presents a novel framework for early warning the collapse of large-span steel truss structures in fire based on proposing the FAST-AlertNet. The FAST-AlertNet can easily obtain real-time displacements based on easily-measured rotations and temperatures of the steel trusses during fire synchronously. Rotations and temperatures, which reflect uncertain structural parameters of steel trusses and fire scenarios, serve as inputs, while displacements are the outputs. A dynamic weighted loss function is employed in the FAST-AlertNet, yielding better performance reflecting the early-warning points than traditional loss functions. To address the high computational cost of obtaining real spatiotemporal patterns of temperature development inside the building in real fire scenes, transfer learning is utilized to transfer the interlinkage among displacements, temperatures, and rotations established by simplified parametric temperature curves, resulting in improved prediction accuracy in reality. A case study demonstrates the availability of the proposed framework, with the predicted remaining pre-collapse time of a typical steel truss satisfactorily matching the real value. Notably, the proposed framework provides a new methodology for early warning building collapse without requiring the difficultly-measured displacements in fire, which advances its feasibility for practical application.

The Sensitivity of Global Structural Parameters for Unreinforced Masonry Buildings Subjected to Simulated Ground Motions

This research performs a parametric study based on Equivalent Single Degree of Freedom (ESDOF) models for simplified seismic analysis of unreinforced masonry (URM) structures. This is a necessary action due to the fact that it is not affordable to model and analyze populations of masonry buildings by using detailed continuum-based models during regional seismic damage and loss estimation studies. Hence, this study focuses on the sensitivity of major structural parameters of a selected idealized hysteretic model for URM buildings. The numerical models are subjected to region-specific simulated ground motion time histories generated using validated seismological parameters. The variations in dynamic analysis results are evaluated using statistical tools for major structural and seismological parameters. The results reveal that the strength factor is the most influential structural parameter, whereas magnitude and distance have a significant impact on the response of idealized URM models as seismological parameters. Furthermore, the specific seismic performance exhibiting limited ductility capacity and the narrow margin of safety between the initial state of inelastic behavior and the ultimate (collapse) state for URM buildings is verified by the statistical approaches employed in this study.

Aftershock collapse capacity assessment of special steel moment frame structures

This study assessment of the collapse capacity of special steel moment frames (SSMFs) with considering earthquake shock sequences for structures height from 4 to 20 stories. The collapse capacity is expressed in terms of the Sa(T1) value at which the system reaches the collapse state. Collapse identification relies on the capability of the model to accurately simulate damage of members and the resulting behavior deterioration. The softening in the lateral response expressed in terms of maximum interstory drift (MID) when it is expressed against the Sa(T1) values is thus used to identify collapse occurrence. The mainshock-aftershock (MS-AS) effect and the uncertainties associated with it are simulated by utilizing a set of 32 natural record pairs. The level of damage induced by MS is represented by two parameters including MID and peak residual story drift (PRSD). Using these parameters, the MS is applied so as to various pre-selected damage levels are imposed. For each MS damage level, an incremental dynamic analysis (IDA) is performed using the AS record that follows MS and a free vibration phase. The AS intensity causing the collapse state is finally identified and respected for evaluating the effect of MS damage level. The correlation between the median collapse Sa’s, called aftershock median collapse capacity, and the MS damage indicated by MID and PRSD parameters is quantified. The study results indicate that larger mainshock damages are required to reduce the collapse capacity of high-rise SSMFs compared to low- to mid-rise structures. Furthermore, the structural collapse capacity may reduce significantly when the building is subjected to a high intensity MS. A comparison between the trendlines presented by the regression equations developed in terms of the MID and PRSD variables was indicated that the MID parameter was more predictable trend.The PRSD parameter was, however, said to be useful in the sense that its value could be measured just after an MS excitation.

High-resolution APEX/LAsMA 12CO and 13CO (3–2) observation of the G333 giant molecular cloud complex

Context. Hub-filament systems are suggested to be the birth cradles of high-mass stars and clusters. Aims. We investigate the gas kinematics of hub-filament structures in the G333 giant molecular cloud complex using 13CO (3–2) observed with the APEX/LAsMA heterodyne camera. Methods. We applied the FILFINDER algorithm to the integrated intensity maps of the 13CO J = 3–2 line to identify filaments in the G333 complex, and we extracted the velocity and intensity along the filament skeleton from moment maps. Clear velocity and density fluctuations are seen along the filaments, allowing us to fit velocity gradients around the intensity peaks. Results. The velocity gradients we fit to the LAsMA and ALMA data agree with each other over the scales covered by ALMA observations in the ATOMS survey (<5 pc). Changes in velocity gradient with scale indicate a funnel structure of the velocity field in position-position-velocity (PPV) space. This is indicative of a smooth, continuously increasing velocity gradient from large to small scales, and thus is consistent with gravitational acceleration. The typical velocity gradient corresponding to a 1 pc scale is ~1.6 km s−1 pc−1. Assuming freefall, we estimate a kinematic mass within 1 pc of ~1190 M⊙, which is consistent with typical masses of clumps in the ATLASGAL survey of massive clumps in the inner Galaxy. We find direct evidence for gravitational acceleration from a comparison of the observed accelerations to those predicted by freefall onto dense hubs with masses from millimeter continuum observations. On large scales, we find that the inflow may be driven by the larger-scale structure, consistent with the hierarchical structure in the molecular cloud and gas inflow from large to small scales. The hub-filament structures at different scales may be organized into a hierarchical system extending up to the largest scales probed through the coupling of gravitational centers at different scales. Conclusions. We argue that the funnel structure in PPV space can be an effective probe for the gravitational collapse motions in molecular clouds. The large-scale gas inflow is driven by gravity, implying that the molecular clouds in the G333 complex may be in a state of global gravitational collapse.

Forest productivity recovery or collapse? Model-data integration insights on drought-induced tipping points.

More frequent and severe droughts are driving increased forest mortality around the globe. We urgently need to describe and predict how drought affects forest carbon cycling and identify thresholds of environmental stress that trigger ecosystem collapse. Quantifying the effects of drought at an ecosystem level is complex because dynamic climate-plant relationships can cause rapid and/or prolonged shifts in carbon balance. We employ the CARbon DAta MOdel fraMework (CARDAMOM) to investigate legacy effects of drought on forest carbon pools and fluxes. Our Bayesian model-data fusion approach uses tower observed meteorological forcing and carbon fluxes to determine the response and sensitivity of aboveground and belowground ecological processes associated with the 2012-2015 California drought. Our study area is a mid-montane mixed conifer forest in the Southern Sierras. CARDAMOM constrained with gross primary productivity (GPP) estimates covering 2011-2017 show a ~75% reduction in GPP, compared to negligible GPP change when constrained with 2011 only. Precipitation across 2012-2015 was 45% (474 mm) lower than the historical average and drove a cascading depletion in soil moisture and carbon pools (foliar, labile, roots, and litter). Adding 157 mm during an especially stressful year (2014, annual rainfall = 293 mm) led to a smaller depletion of water and carbon pools, steering the ecosystem away from a state of GPP tipping-point collapse to recovery. We present novel process-driven insights that demonstrate the sensitivity of GPP collapse to ecosystem foliar carbon and soil moisture states-showing that the full extent of GPP response takes several years to arise. Thus, long-term changes in soil moisture and carbon pools can provide a mechanistic link between drought and forest mortality. Our study provides an example for how key precipitation threshold ranges can influence forest productivity, making them useful for monitoring and predicting forest mortality events.

Effect of Coulomb impurities on the electronic structure of magic angle twisted bilayer graphene

In graphene, charged defects break the electron-hole symmetry and can even give rise to exotic collapse states when the defect charge exceeds a critical value which is proportional to the Fermi velocity. In this work, we investigate the electronic properties of twisted bilayer graphene (tBLG) with charged defects using tight-binding calculations. Like monolayer graphene, tBLG exhibits linear bands near the Fermi level but with a dramatically reduced Fermi velocity near the magic angle (approximately 1.1°). This suggests that the critical value of the defect charge in magic-angle tBLG should also be very small. We find that charged defects give rise to significant changes in the low-energy electronic structure of tBLG. Depending on the defect position in the moiré unit cell, it is possible to open a band gap or to induce an additional flattening of the low-energy valence and conduction bands. Our calculations suggest that the collapse states of the two monolayers hybridize in the twisted bilayer. However, their in-plane localization remains largely unaffected by the presence of the additional twisted layer because of the different length scales of the moiré lattice and the monolayer collapse state wavefunctions. These predictions can be tested in scanning tunneling spectroscopy experiments.

Биоремедиация техногенно деградированных земель после завершения специальной военной операции на территории новых субъектов Российской Федерации

One of the consequences of a special military operation to demilitarize and denazify the territories of Ukraine adjacent to the borders of the Russian Federation is the severe environmental consequences associated with the destruction of the natural landscape, close to the state of collapse – the irreversible loss of its biological productivity. It is necessary to develop and approve a federal target program to bring the territories where a special military operation was carried out into an ecologically safe state suitable for human life, as well as for representatives of the flora and fauna. The implementation of this federal target program will require an integrated approach to ensure the restoration of disturbed lands and their return to use for their intended purpose. It is quite natural that the restoration of degraded lands will have to be carried out with the obligatory consideration of the potential of plant-microbial complexes (natural or artificially created) in the course of soil bioremediation. The totality of theoretical and experimental data gives grounds to believe that the relevant designs are ready and possible to be introduced into the practice of bioremediation of degraded lands.

Войната в Украйна в ракурса на предизборната кампания за 49-ото обикновено народно събрание

The crisis in political speech in our country (2022 – 2023) was strongly influenced by the military conflict in Ukraine that officially began on February 26, 2022. The war, which has shaken politics at the international level, has exposed the thick red lines between political entities in Bulgaria, deepening the parliamentary crisis that has reached a state of collapse in the past year and a half. And the media – intentionally or not, became a witness and accomplice to what was happening. The relevance of the chosen topic is dictated by the need to analyze the political speech regarding the military conflict in Ukraine during the election campaign for the fifth consecutive early parliamentary elections in Bulgaria (April 2, 2023). In the analysis, the author refers to the messages from the political formations and the position they take on the war, as well as their media coverage. The positions of media experts are presented. Sociological surveys were also examined, which show the attitude of the voters on the question. The goals of the development are to make an attempt to analyze the behavior of the main political subjects in our country regarding the war in Ukraine, the position they take, as well as the messages they send to the voters; to examine the results of each party’s strategy and how far it was able to influence the election result; to offer a prediction about the future development of the parties (possible and impossible partners) in the perspective of their political speech related to the military conflict. The pre-election campaign for the 49th Ordinary National Assembly was marked by the theme of the war in Ukraine and made it necessary for political subjects to clearly define their position on the conflict both to the voters and to their competitors, but also to future potential partners in the attempt to form a cabinet. In the current uncertain domestic political and international situation, the Bulgarian voter demonstrates the need for clearly stated and categorical positions in which to recognize his convictions.

TRACES OF AHI-ORDER VALUES IN NASREDDIN HODJA ANECDOTES

13-15. centuries; It was a period when political, social, and economic turmoil and social conflicts were seen intensely in Anatolia. During this period, when the power struggles continued violently, the people of Anatolia retreated into their shells in despair and began to gather around the Turkmen dervishes. At this time when literary and cultural life was impoverished under the influence of foreign cultures, it was seen that Sufi movements and oral literature tradition had increased. The people, who could not know Arabic and Persian sources or could not access a limited number of Turkish works, tried to meet the need to read and listen to the folk literature goods that continued in their language and oral tradition, and the Seljuk society, which experienced a state of social collapse with what they learned from this, embraced the anecdotes of Nasreddin Hodja, which represented an important sage type of the period as a moral hub. In his anecdotes, there are solutions to every aspect of society that is flawed/disrupted. Articles about Nasreddin Hodja’s anocdotes were selected among many text publications by considering certain criteria. Here, rather than one of both the anecdotes belong to Nasreddin Hodja or not, more emphasis is placed on whether thet are told in the tradition of Nasreddin Hodja. This article is aimed to address the basic values of the Ethic organization from selected anecdotes of the teacher. Keywords: Ahi-Order, Nasreddin Hodja, Nasreddin Hodja Anecdote, 13-15th Centuries, Oral Culture, Principles of Ahi-Order.

Prediction of Reservoir Bank Collapse Based on the Limit Equilibrium Theory

The prediction of reservoir bank collapse width is a unique problem encountered in the construction of hydropower projects. Existing empirical graphic methods are based on the final state of bank collapse and can be used to predict only bank collapse width, and they thus do not adequately reflect the characteristics of the bank collapse process. To solve this problem, a prediction model for bank collapse width based on the limit equilibrium theory was established, and the key parameters and bank collapse process of the model were analyzed. The results reveal the necessity of selecting a reasonable underwater accumulation rate when predicting the bank collapse width using the limit equilibrium theory. At a constant ratio of water depth to bank slope height, the underwater accumulation rate increases with increasing bank slope height, with a linear relationship between them. In contrast, the bank slope angle has little impact on bank collapse width. Specifically, it mainly affects the width of the first bank collapse but has little effect on the width of subsequent bank collapses. With an increase in the bank slope angle, the bank collapse width fluctuates and rises. The prediction model of bank collapse width based on the limit equilibrium theory can better explain the time-dependent behavior of bank collapse. The research results are of high significance for the prediction of loess bank collapse.

Machine learning-based collapse prediction for post-earthquake damaged RC columns under subsequent earthquakes

The rapid assessment for numerous post-earthquake damaged reinforced concrete (RC) structures is critical for making informed post-earthquake decisions. However, this often requires significant resources in terms of manpower and calculation costs. This study proposes a machine learning (ML)-based method for predicting the collapse state of post-earthquake damaged RC columns under subsequent earthquakes, which are a critical earthquake-resistant component in RC structures. First, the damage strain field theory is introduced to establish the numerical analysis models for 10000 post-earthquake damaged RC columns. A dataset is constructed using time history analysis results obtained from these numerical analysis models under the action of 1000 ground motion records. The Random Forest (RF) algorithm is then utilized to train an ML model that can predict the collapse state of post-earthquake damaged RC columns under subsequent earthquakes. To evaluate the accuracy of the ML prediction model, a testing dataset consisting of 47 full-size RC columns from the Pacific Earthquake Engineering Research Center (PEER) database is constructed. Results demonstrate that the prediction model has good accuracy, with an Area Under Curve (AUC) value and an F1 measure of 0.87 and 0.76, respectively. The SHapley Additive exPlanation (SHAP) algorithm is then utilized to interpret the ML prediction model, and the influences of design parameters, ground motion intensity parameters, and damage index on the prediction results are discussed. Finally, an interactive and user-friendly graphical user interface (GUI) tool is developed to provide a rapid collapse prediction of post-earthquake damaged RC columns. This study represents a pioneering step towards the application of ML in post-earthquake assessment for damaged RC columns.

Multiple-level earthquake-resistant design strategy for precast concrete frames with semi-rigid connections: A case study

The design of precast concrete (PC) structures with semi-rigid connections is primarily based on the design of cast-in-suit structures by adjusting the relevant parameters of PC connections. However, it is necessary to further verify whether the seismic collapse resistance capacity of these PC structures meets the requirements, and to examine how to achieve the optimal seismic resistance design of PC structures. To explore a more concise and effective design scheme for PC structures, the influence of different PC connection parameters and the number of structural stories on the collapse resistance capacity of PC structures is discussed based on a case study. In this work, we set three series of 8-story PC structures and one series of 18-story PC structures, based on different PC connection parameters. Firstly, a simplified algorithm of the inter-story drift (ISD) ratio, based on a modified Muto’s method, is performed to preliminarily screen PC structures subjected to frequent-level earthquakes, and the lower limit value of the semi-rigid connection coefficient of each series of structures can be determined. Next, based on the modal pushover analysis and the capacity spectrum, the ISD ratio of the structures subjected to rare-level earthquakes is analyzed to further screen out the structures that do not meet the specification limits. The distribution ratio of the hysteretic energy in each story of the PC structures is discussed using time history analysis. Then, in the collapse stage, based on a global damage model and incremental dynamic analysis, the collapse state points of the structure can be obtained so that the collapse probability curve of each PC structure is determined, and the collapse safety margin of PC structures can be analyzed. PC structures can be further screened based on the collapse margin ratio (CMR), and the influences of PC connection parameters on the CMR and failure path of PC structures are assessed. Finally, the optimization of structures with semi-rigid PC connections based on multilevel seismic action is realized.

Vertically neutral collapse of a pulsating bubble at the corner of a free surface and a rigid wall

Vertically neutral collapse of a pulsating bubble occurs when the boundaries above or below the bubble balance the buoyancy effect over a pulsation. In this study, the vertically neutral collapse of a bubble near a vertical rigid wall below the free surface is investigated. The boundary integral method (BIM) is employed to model the bubble dynamics with an open-domain free surface. Moreover, this method is validated against several buoyant bubble experiments. Bubble dynamics in such conditions are associated with three dimensionless parameters: the bubble-free surface distance $\gamma _{{f}}$ , bubble–wall distance $\gamma _{{w}}$ and buoyancy parameter $\delta$ . We derive the Kelvin impulse of a spherical bubble and the algebraic relationship for vertically neutral collapse, which proves to be accurate for predicting vertically neutral collapse when the bubble is relatively far from the boundaries. Four patterns of the vertically neutral collapse of the bubble for different $\gamma _{{w}}$ and $\gamma _{{f}}$ are identified: (i) formally downward jet; (ii) annular collapse; (iii) horizontal jet; and (iv) weak jet. Despite the downward jet shape, the ‘formally downward jet’ is in the vertically neutral collapse state in terms of the profile of toroidal bubbles and the orientation of local high-pressure zones around the bubble at jet impact. A bulge with a high curvature above the bubble in the ‘annular collapse’ pattern is formed during bubble collapse under two local high-pressure zones at the left and right extremities of the bubble. The ‘horizontal jet’ pattern has the greatest potential to attack the wall, and the power laws of the moment of the jet impact, jet velocity and bubble displacement with respect to the theoretical Kelvin impulse are discussed. In particular, we quantitatively illustrate the role of the free surface on bubble migration towards the wall through the variational power-law exponents of the bubble displacement with respect to $\gamma _{{w}}$ .

Influence of cavitation state and launch angle on water-exit process of vehicle based on moving domain method

This paper, aiming at the water-exit process of the vehicle with cavitation, based on the moving domain method coupled with the SDOF (six degrees of freedom) solver, using VOF (volume of fluid) multiphase model and the Schnerr-Sauer cavitation model, carrying out numerical simulation research on multi-conditions. Comparing vertical launch vehicles with different water-exit Ca (cavitation number) cases, the sudden decrease in cavitation number is closely related to the cavitation state, and there is a maximum influent cavitation state of the cavitation collapse on the process of the water-exit. Comparing different initial launch angle cases, it is found that there is a most unstable launch angle, which makes the angular deflection of the vehicle the most severe during the water-exit process.

Seismic Risk of Weak First-Story RC Structures with Inerter Dampers Subjected to Narrow-Band Seismic Excitations

This study evaluates the seismic risk of weak first-story reinforced concrete (RC) structures retrofitted with inerter dampers at their ground level when subjected to narrow-band seismic excitations. The main advantages brought about by the ground-level inerters are the reductions in seismic demands (e.g., drifts, floor accelerations). This study shows that structures with inerters are reliable systems in terms of peak story drifts for large ground motions. For moderate ground-motion intensities, the opposite could occur, mainly for soft soil sites. The reliabilities of structures with inerter dampers at their ground level are in general higher for buildings under seismic intensities associated to limit state of incipient collapse, especially for low-height buildings. This could be reversed for intensities associated to the limit state of damage limitation. The findings of this study could guide practicing engineers to use inerter-based dampers in retrofitting ductile structures consisting of moment-resisting reinforced concrete (RC) frames subjected to narrow-band earthquake excitations in regions such as Mexico City.

An approach for early-warning collapse of planar steel trapezoid trusses exposed to fire

This paper presents an approach for early warning of the fire-induced collapse of planar steel trapezoid trusses based on real-time measurement of displacements and displacement velocities of key nodes. Firstly, a three-dimensional finite element model is validated by a full-scale fire test of a steel roof truss structure. Secondly, numerical simulations on the collapse process of planar steel trapezoid trusses under fire are conducted. Four collapse modes are summarized based on systematic parametric analyses. By exploring the variation laws of displacements and displacement velocities of key nodes, the early-warning characteristic points are determined, and a three-level early-warning method is proposed for identifying the collapse mode and collapse state. To improve the generality of the proposed method, dimensionless early-warning time ratios are introduced, and their values, with reliability significance, are determined by the Monte Carlo method. Then the accuracy of this proposed method is validated against an existing fire test. Finally, a numerical case study is presented to illustrate the effectiveness of the method for actual planar steel trapezoid trusses in real fire conditions. The accuracy of the proposed approach is validated with a satisfactory agreement between the precise remaining safety time and that early warned.