The Sliding Hinge Joint: Final Steps towards an Optimum Low Damage Seismic-Resistant Steel System

2018 ◽  
Vol 763 ◽  
pp. 751-760 ◽  
Author(s):  
Shahab Ramhormozian ◽  
George Charles Clifton ◽  
Gregory A. MacRae ◽  
Hsen Han Khoo
Keyword(s):  
Large Scale ◽  
Limit State ◽  
Model Development ◽  
Research Work ◽  
Research Programme ◽  
Service Condition ◽  
Moment Frame ◽  
Steel Moment Frame ◽  
Hinge Joint ◽  
Moment Resisting

The Sliding Hinge Joint with Asymmetric Friction Connectors (SHJ), to give its full name, is a semi-rigid moment resisting joint used between the beams and columns of a moment-resisting steel frame and also at the column base between the column and the ground. It’s performance is intended to be as follows: 1) On completion of construction, rigid under serviceability limit state conditions, 2) During a severe earthquake, allowing controlled rotation between the column and the beam or foundation on designated friction sliding planes within the connection, then 3) Returning to its rigid in-service condition at the end of the severe shaking with the building returning to its pre-earthquake position (self-centering). During its development and proof of concept through large scale testing, the initial results showed that the SHJ as originally designed and detailed performs 1) and 2) very well, but the bolts in the friction sliding planes loose much of their original installed bolt tension during significant sliding, lowering the level at which rotation within the joint will occur post severe earthquake. A concerted research programme of component testing, analytical model development and numerical modelling in recent years has developed solutions to the bolt tension loss issue as well as enhanced the joint’s performance to deliver dependable self-centering capability for the building. This work marks the final steps towards developing an optimum low damage seismic-resisting steel moment frame system. This paper presents key findings from the research work and general recommendations for the optimum performing sliding hinge joint.

Bottlenecks in the Implementation of On-Site Wastewater Treatment Plants on a Large Scale in The Netherlands

1990 ◽  
Vol 22 (3-4) ◽  
pp. 291-298
Author(s):  
Frits A. Fastenau ◽  
Jaap H. J. M. van der Graaf ◽  
Gerard Martijnse
Keyword(s):  
Wastewater Treatment ◽  
The Netherlands ◽  
Large Scale ◽  
Wastewater Treatment Plants ◽  
Housing Stock ◽  
Research Work ◽  
Field Research ◽  
Domestic Wastewater ◽  
Research Programme ◽  
Definition Of

More than 95 % of the total housing stock in the Netherlands is connected to central sewerage systems and in most cases the wastewater is treated biologically. As connection to central sewerage systems has reached its economic limits, interest in on-site treatment of the domestic wastewater of the remaining premises is increasing. A large scale research programme into on-site wastewater treatment up to population equivalents of 200 persons has therefore been initiated by the Dutch Ministry of Housing, Physical Planning and Environment. Intensive field-research work did establish that the technological features of most on-site biological treatment systems were satisfactory. A large scale implementation of these systems is however obstructed in different extents by problems of an organisational, financial and/or juridical nature and management difficulties. At present research is carried out to identify these bottlenecks and to analyse possible solutions. Some preliminary results are given which involve the following ‘bottlenecks':-legislation: absence of co-ordination and absence of a definition of ‘surface water';-absence of subsidies;-ownership: divisions in task-setting of Municipalities and Waterboards; divisions involved with cost-sharing;-inspection; operational control and maintenance; organisation of management;-discharge permits;-pollution levy;-sludge disposal. Final decisions and practical elaboration of policies towards on-site treatment will have to be formulated in a broad discussion with all the authorities and interest groups involved.

Performance of self-centering steel moment frame considering stress relaxation in prestressed cables

2020 ◽  
Vol 23 (9) ◽  
pp. 1813-1822
Author(s):  
Seyyed Morteza Asadolahi ◽  
Nader Fanaie
Keyword(s):  
Stress Relaxation ◽  
Stress Reduction ◽  
Original Position ◽  
Dissipated Energy ◽  
Moment Frame ◽  
Steel Moment Frame ◽  
Moment Resisting Frames ◽  
Moment Resisting Frame ◽  
Moment Resisting ◽  
Over Time

Buildings can be designed to limit the earthquake-induced damage to members that can easily be repaired. Self-centering moment-resisting frames can be used as effective structural systems for this purpose. Self-centering moment-resisting frames with prestressed cables are able to return the structure to its original position after the earthquake. The internal forces in self-centering moment-resisting frames are transferred between the beam and the column by post-tensioned cables. As a main member of self-centering connections, prestressed cables play a significant role in such systems. Cable tension decreases over time due to the effect of stress relaxation on the performance of the system. Stress relaxation is a time-dependent phenomenon causing stress reduction over time in the members prestressed at a constant strain. Therefore, the effect of stress relaxation on the performance of self-centering moment-resisting frames can be significant. In this article, after simulating and validating a moment-resisting frame with self-centering connections, stiffness and moment–rotation hysteresis diagrams were analyzed after 0, 1, 5, 10, and 20 years of cable prestressing. According to the results, two equations were presented to estimate the reduction in the connection stiffness and dissipated energy by the system based on prestressing level and the time after prestressing. The proposed equations could be used to model semi-rigid connections.

Computational simulation of steel moment frame to resist progressive collapse in fire

2016 ◽  
Vol 7 (4) ◽  
pp. 286-305 ◽  
Author(s):  
Ha Nguyen ◽  
Ann E. Jeffers ◽  
Venkatesh Kodur
Keyword(s):  
Experimental Data ◽  
Large Scale ◽  
Progressive Collapse ◽  
Computational Simulation ◽  
Three Dimensional ◽  
Fe Model ◽  
Moment Frame ◽  
Steel Moment Frame ◽  
Fixed Temperature ◽  
Content Type

Purpose This paper aims to address a need for improving the structural resilience to multi-hazard threats including fire and progressive collapse caused by the loss of a column. Design/methodology/approach The focus is on a steel moment frame that uses welded-unreinforced flange-bolted web connections between the beams and columns. A three-dimensional finite element (FE) model was created in ABAQUS with temperature-dependent properties for steel based on the Eurocode. The model was validated against experimental data at ambient and elevated temperature. Findings The failure mechanisms in the FE model were consistent with experimental observations. Two scenarios were considered: fixed load with increasing temperature (i.e. simulating column failure prior to fire) and fixed temperature with increasing load (i.e. simulating column failure during fire). Originality/value A macro element (or component-based) model was also introduced and validated against the FE model and the experimental data, offering the possibility of analyzing large-scale structural systems with reasonable accuracy and improved computational efficiency.

scholarly journals Optimum Performance-Based Design Of Unsymmetrical 2D Steel Moment Frame

2021 ◽  
Author(s):  
Arezoo Asaad Samani ◽  
Seyed Rohollah Hoseini Vaez ◽  
Mohammad Ali Fathali
Keyword(s):  
Lateral Loading ◽  
Performance Based Design ◽  
Nonlinear Static Analysis ◽  
Second Step ◽  
Analysis Method ◽  
Moment Frame ◽  
Steel Moment Frame ◽  
Steel Moment Resisting Frames ◽  
Moment Resisting ◽  
Nonlinear Static

Abstract The most commonly used analysis method in performance-based design (PBD) is the nonlinear static analysis (NSA). In unsymmetrical 2D frames, unlike its symmetrical state, NSA should be performed in two lateral loading directions, which complicates the process of achieving a feasible optimal design in addition to increasing the volume of calculations. In this study, a two-step approach is proposed for the design of unsymmetrical 2D steel moment-resisting frames (SMRF). In this approach, in two independent steps, the structure is analyzed with lateral loading pattern based on the first mode shape in positive and negative direction, respectively. The implementation of the second step is conditional on the satisfactory completion of the first step. The objective function takes into account the differences between successful and unsuccessful steps. The constraints considered are based on the acceptance criteria for SMRFs according to FEMA-356 at each performance level. The effectiveness of the proposed approach has been investigated by employing four meta-heuristic optimization algorithms to determine the optimum design for case studies of SMRF structures having three and nine stories.

Green synthesis, characterization of silver sulfide nanoparticles and antibacterial activity evaluation

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Antibacterial Activity ◽  
Large Scale ◽  
Research Work ◽  
Silver Sulfide ◽  
Morphological Properties ◽  
Effective Diameter ◽  
Novel Approach ◽  
Transmission Electron ◽  
Green Route ◽  
Silver Sulfide Nanoparticles

This research work presents a facile and green route for synthesis silver sulfide (Ag2SNPs) nanoparticles from silver nitrate (AgNO3) and sodium sulfide nonahydrate (Na2S.9H2O) in the presence of rosemary leaves aqueous extract at ambient temperature (27 oC). Structural and morphological properties of Ag2SNPs nanoparticles were analyzed by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The surface Plasmon resonance for Ag2SNPs was obtained around 355 nm. Ag2SNPs was spherical in shape with an effective diameter size of 14 nm. Our novel approach represents a promising and effective method to large scale synthesis of eco-friendly antibacterial activity silver sulfide nanoparticles.

Load Testing to Collapse Limit State of Barr Creek Bridge

2000 ◽  
Vol 1696 (1) ◽  
pp. 92-102 ◽  
Author(s):  
Nicholas Haritos ◽  
Anil Hira ◽  
Priyan Mendis ◽  
Rob Heywood ◽  
Armando Giufre
Keyword(s):  
Finite Element ◽  
Failure Modes ◽  
Flexural Rigidity ◽  
Load Capacity ◽  
Limit State ◽  
Dynamic Test ◽  
Service Condition ◽  
Flat Slab ◽  
Testing Program ◽  
Static Testing

VicRoads, the road authority for the state of Victoria, Australia, has been undertaking extensive research into the load capacity and performance of cast-in-place reinforced concrete flat slab bridges. One of the key objectives of this research is the development of analytical tools that can be used to better determine the performance of these bridges under loadings to the elastic limit and subsequently to failure. The 59-year-old Barr Creek Bridge, a flat slab bridge of four short continuous spans over column piers, was made available to VicRoads in aid of this research. The static testing program executed on this bridge was therefore aimed at providing a comprehensive set of measurements of its response to serviceability level loadings and beyond. This test program was preceded by the performance of a dynamic test (a simplified experimental modal analysis using vehicular excitation) to establish basic structural properties of the bridge (effective flexural rigidity, EI) and the influence of the abutment supports from identification of its dynamic modal characteristics. The dynamic test results enabled a reliably tuned finite element model of the bridge in its in-service condition to be produced for use in conjunction with the static testing program. The results of the static testing program compared well with finite element modeling predictions in both the elastic range (serviceability loadings) and the nonlinear range (load levels taken to incipient collapse). Observed collapse failure modes and corresponding collapse load levels were also found to be predicted well using yield line theory.

DeepSSPred: A Deep Learning Based Sulfenylation site predictor via a novel n-segmented optimize federated feature encoder

2020 ◽  
Vol 27 ◽  
Author(s):  
Zaheer Ullah Khan ◽  
Dechang Pi
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
Research Work ◽  
Training Data ◽  
Training Dataset ◽  
Validation Dataset ◽  
Cytokine Signaling ◽  
Minority Class ◽  
Independent Dataset ◽  
Feature Encoding

Background: S-sulfenylation (S-sulphenylation, or sulfenic acid) proteins, are special kinds of post-translation modification, which plays an important role in various physiological and pathological processes such as cytokine signaling, transcriptional regulation, and apoptosis. Despite these aforementioned significances, and by complementing existing wet methods, several computational models have been developed for sulfenylation cysteine sites prediction. However, the performance of these models was not satisfactory due to inefficient feature schemes, severe imbalance issues, and lack of an intelligent learning engine. Objective: In this study, our motivation is to establish a strong and novel computational predictor for discrimination of sulfenylation and non-sulfenylation sites. Methods: In this study, we report an innovative bioinformatics feature encoding tool, named DeepSSPred, in which, resulting encoded features is obtained via n-segmented hybrid feature, and then the resampling technique called synthetic minority oversampling was employed to cope with the severe imbalance issue between SC-sites (minority class) and non-SC sites (majority class). State of the art 2DConvolutional Neural Network was employed over rigorous 10-fold jackknife cross-validation technique for model validation and authentication. Results: Following the proposed framework, with a strong discrete presentation of feature space, machine learning engine, and unbiased presentation of the underline training data yielded into an excellent model that outperforms with all existing established studies. The proposed approach is 6% higher in terms of MCC from the first best. On an independent dataset, the existing first best study failed to provide sufficient details. The model obtained an increase of 7.5% in accuracy, 1.22% in Sn, 12.91% in Sp and 13.12% in MCC on the training data and12.13% of ACC, 27.25% in Sn, 2.25% in Sp, and 30.37% in MCC on an independent dataset in comparison with 2nd best method. These empirical analyses show the superlative performance of the proposed model over both training and Independent dataset in comparison with existing literature studies. Conclusion : In this research, we have developed a novel sequence-based automated predictor for SC-sites, called DeepSSPred. The empirical simulations outcomes with a training dataset and independent validation dataset have revealed the efficacy of the proposed theoretical model. The good performance of DeepSSPred is due to several reasons, such as novel discriminative feature encoding schemes, SMOTE technique, and careful construction of the prediction model through the tuned 2D-CNN classifier. We believe that our research work will provide a potential insight into a further prediction of S-sulfenylation characteristics and functionalities. Thus, we hope that our developed predictor will significantly helpful for large scale discrimination of unknown SC-sites in particular and designing new pharmaceutical drugs in general.

scholarly journals Seismic Performance of a Green Roof Structure

2021 ◽  
Vol 13 (8) ◽  
pp. 4278
Author(s):  
Svetlana Tam ◽  
Jenna Wong
Keyword(s):  
Green Roof ◽  
Time History ◽  
Green Roofs ◽  
Moment Frame ◽  
Steel Moment Frame ◽  
Roof Structure ◽  
Nonlinear Time History Analyses ◽  
Vegetated Roofs ◽  
Nonlinear Time History ◽  
The Impact

Sustainability addresses the need to reduce the structure’s impact on the environment but does not reduce the environment’s impact on the structure. To explore this relationship, this study focuses on quantifying the impact of green roofs or vegetated roofs on seismic responses such as story displacements, interstory drifts, and floor level accelerations. Using an archetype three-story steel moment frame, nonlinear time history analyses are conducted in OpenSees for a shallow and deep green roof using a suite of ground motions from various distances from the fault to identify key trends and sensitivities in response.

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