Seismic performance of tuned mass damper on Shazand Railway Bridge induced by train

Shazand Railway Bridge is located in Markazi province, Iran in north to south-west railway. The bridge consists of ten spans. In 1984, during Iran-Iraq war, that’s main span, which has a length of 72 m, was attacked and severely damaged. Eight month later, damaged span replaced with a steel deck. The deck is straight in plan, but the railway is curved and this causes eccentricity. Excessive vibration was observed during the train passage. Although the bridge was retrofitted in two stages, the problem has not been solved yet, and the trains’ speed should be reduced to around 10 km/h in order to avoid excessive vibration. The present study addressed the effectiveness of tuned mass damper (TMD) in reducing train-induced vibrations of Shazand Railway Bridge. A three dimensional finite-element model of the bridge is developed and dynamic time history analyses under train passage in both as-built and passively controlled with TMD are conducted. Sensitivity analyses are performed to demonstrate the effects of the damper parameters on structural response. The results show that considerable reduction in acceleration response of the bridge can be achieved by employing proper TMD

Cementitious composites reinforced with polypropylene, nylon and polyacrylonitile fibres

This paper compares the adhesion strength between three polymeric fibres (polypropylene (PP), nylon66 (N66) and polyacrylonitrile (PAN)) embedded in a cement paste. The specimens were prepared at a water to cement ratio (w/c) of 0.5, and tested after 7, 14 and 28 curing days. It was found that although the adhesion between the polymeric fibres to the cement matrix is an important factor, the energy absorption capacity or energy dissipation ability of the fibres plays a more important role in the improvement of the cementitious composites fracture toughness. Scanning electron micrographs was used to characterize the fibres surface before and after the Pullout tests

Evaluation of adhesion in polymeric fibre reinforced cementitious composites

In this study adhesion of some polymeric fibres to a cement matrix was evaluated both by a theoretical and by an experimental approach. In common methods adhesion of the fibres to the cementitious materials is determined by pull-out test. This test evaluates the energy failure during the fibre drawing out. This paper analyzes the adhesion theory for fibre reinforced cementitious composites to separate the share of the chemical and mechanical adhesion expressing new parameters, which are effective in the adhesion behaviour. Explanations about how the different fibres, matrix properties, test factors and environmental conditions can affect the adhesion results are given. It was found that for fibre/cement composites the fracture energy due to the interfacial interactions is for several orders of magnitude smaller that the polymeric fibre losses function. By employing adhesion theory, fibre/cement interac- tions are better described by a simple relationship of their surface free energy. Determination of the loss function (energy dissipation) leads us to predict the fibre behaviour in the cement matrix and the selection of the appropriate reinforcement

Simultaneous lidar and airglow temperature measurements in the mesopause region

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94970/1/grl5512.pd

Investigating the influence of surrounding soil properties on leakage discharge from cracks in polyethylene pipes

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: Data will be made available on request.Numerous factors affect the amount of leakage from pipes, e.g. inside pressure, type of pipe failure, soil around the pipe, etc. Few researches have been done on the effect of environment around the pipe on the leakage discharge. In the present study, the leakage from pipes in presence of different soils is experimentally investigated. Leakage from a cracked polyethylene pipe was simulated in the presence of various soils with different properties in a laboratory setup. Leakage- pressure relationships were obtained according to fixed and variable area discharge theory. By quantifying the soil characteristics, the relationship between leakage- pressure coefficients (m and Cd) and soil parameters was obtained. It was concluded that the soil environment affects the amount of leakage discharge. Results show that the particle diameter at 50% passing (D50), dry unit weight ( ) and hydraulic permeability coefficient (k) are more appropriate to represent the characteristics of soils. It was also concluded that there are no strong correlation between leakage and some soil parameters. The obtained relationships between different soil parameters and leakage discharge coefficients are also presented

Evaluating energy harvesting from water distribution networks using combined stakeholder and social network analysis

This is the final version. Available from Elsevier via the DOI in this record. Data availability: Data will be made available on request.The chance of success in implementing a new project in a water distribution network (WDN) significantly depends on the behaviour of the involved stakeholders. In this paper, the feasibility of installing the micro-turbines in WDNs for generating hydro-power energy is studied from the stakeholders’ perspective. Stakeholders’ analysis (SA) and social network analysis (SNA) are performed to methodically recognise the environment and the relationships among stakeholders. 18 stakeholders at the local, regional, and national levels were identified and their representatives were interviewed. In SA, the power, interest, access to information, and satisfaction from the current condition of the system were evaluated for each stakeholder. The Water and Wastewater Company and Ministry of Energy were found as the stakeholders with the highest power and interest. Unexpectedly, the Regional Electricity Company was discovered with medium power and low access to information. In SNA, cooperative and non-cooperative relationships between stakeholders were analysed and an assessment was made for the role of each stakeholder in their social network, through four centrality metrics. The correlation between SA and SNA results suggests that SA factors could be estimated using the SNA metrics.Iran National Science Foundation (INSF

Customised-sampling approach for pipe failure prediction in water distribution networks

This is the final version. Available from Nature Research via the DOI in this record. Data availability. Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions. All case study data is owned by the utility company and is subject to a non-disclosure agreement (NDA), thereby limiting its availability for public dissemination. Requests for non-commercial usage of the scripts will be evaluated on a case-by-case basis, by contacting the corresponding author at [email protected] paper presents a new methodology for addressing imbalanced class data for failure prediction in Water Distribution Networks (WDNs). The proposed methodology relies on existing approaches including under-sampling, over-sampling, and class weighting as primary strategies. These techniques aim to treat the imbalanced datasets by adjusting the representation of minority and majority classes. Under-sampling reduces data in the majority class, over-sampling adds data to the minority class, and class weighting assigns unequal weights based on class counts to balance the influence of each class during machine learning (ML) model training. In this paper, the mentioned approaches were used at levels other than “balance point” to construct pipe failure prediction models for a WDN with highly imbalanced data. F1-score, and AUC–ROC, were selected to evaluate model performance. Results revealed that under-sampling above the balance point yields the highest F1-score, while over-sampling below the balance point achieves optimal results. Employing class weights during training and prediction emphasises the efficacy of lower weights than the balance. Combining under-sampling and over-sampling to the same ratio for both majority and minority classes showed limited improvement. However, a more effective predictive model emerged when over-sampling the minority class and under-sampling the majority class to different ratios, followed by applying class weights to balance data.Datatecnics Corporation LimitedUKRIKnowledge Transfer Partnership (KTP) InnovateU

Toxic heavy metals removal from river water using a porous phospho-calcic hydroxyapatite

The process of adsorption of copper ions on synthesized hydroxyapatites (p-HAp) by the wet route has been studied experimentally to make a comparison between the adsorption capacity of our porous phospho-calcic material and the phosphate hydroxyapatite. The specific surface of p-HAp was studied by BET, as well as the characterization of p-HAp by FTIR and XRD showed that the synthetic hydroxyapatite has an apatite phase of crystalline structure which is very interesting for the adsorption of metals. Heavy, the results of the adsorption study obtained that the mechanism of adsorption of Cu2+ ions was best described by the pseudo-second-order kinetic model and obeyed the linear models of Langmuir isotherms, continued that the adsorption is done in the surface area of p-HAp. Langmuir model parameters reveal that, the adsorption mechanism of Cu2+ is fit with this model. The pseudo-first-order and pseudo-second-order models were also used to determine the adsorption kinetic. The experimental data were well fitted by the pseudo-second-order model. Thermodynamic parameters showed that, the adsorption of Cu2+  ion onto the composite surface is a spontaneous and favored at neutral pH and at a temperature little higher than room temperature

Efficacy of Tree-Based Models for Pipe Failure Prediction and Condition Assessment: A Comprehensive Review

This is the final version. Available on open access from ASCE via the DOI in this recordData Availability Statement: All data, models, and code generated or used during the study appear in the published article.This paper provides a comprehensive review of tree-based models and their application in condition assessment and prediction of water, wastewater, and sewer pipe failures. Tree-based models have gained significant attention in recent years due to their effectiveness in capturing complex relationships between parameters of systems and their ability in handling large data sets. This study explores a range of tree-based models, including decision trees and ensemble trees utilizing bagging, boosting, and stacking strategies. The paper thoroughly examines the strengths and limitations of these models, specifically in the context of assessing the pipes’ condition and predicting their failures. In most cases, tree-based algorithms outperformed other prevalent models. Random forest was found to be the most frequently used approach in this field. Moreover, the models successfully predicted the failures when augmented with a richer failure data set. Finally, it was identified that existing evaluation metrics might not be necessarily suitable for assessing the prediction models in the water and sewer networks.Datatecnics Corporation LimitedUKR