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Recently, this steel section has found increasing popularity in residential, industrial and commercial buildings with their high load-carrying capacity due to the nature of high strength to weight ratio properties. However, the rise on the price of steel section should be more emphasized; therefore, the optimization in steel section design is needed to overcome the issue of material cost. As such, tapered steel sections save on material use, while the introduction of web openings allows the placement of mechanical and electrical services, plumbing and also aesthetic design considerations.

The purpose of this study is to investigate the lateral torsional buckling behavior of a tapered steel section with an ellipse-shaped opening by analyzing its structural parameters. To achieve this, the finite element analysis (FEA) of the section is modeled using LUSAS software, which allows for a detailed analysis of the section's behavior under varying loads and conditions. It involves the variation in web opening size, opening layout, opening rotation angle and the tapering ratio. Eigenvalue buckling analysis is adopted to know the parametric effects of each 108 model. The size of opening varies from 0.2 to 0.5 d of the total depth where the opening located. There are three type of layouts applied in this study, which are the layouts A, B and C. There are three types of rotation angles for the ellipse-shaped opening, including the non-rotated vertical opening and two additional types formed by rotating the opening 45 degrees clockwise and counterclockwise around the center-point of the ellipse. A fixed-free boundary condition was applied, resulting in a simulation of a cantilever beam. The models are fixed at one end with a larger depth, and free at the other end with a smaller depth. Loading condition is an application of 10 kN/m uniform distributed load in the direction of gravity along the mid-span of the top flange.

It is observed that the model 82 with Layout A, tapering ratio 0.3, opening size 0.5 d and opening rotated in 45 degree anti-clockwise direction results in the highest structural efficiency among the 108 models. Therefore, the buckling moment of model 82 is 1,013.08 kNm with structural efficiency of 481.26, which shows an increase of 3.17% compared to the controlled model.

The FEA results shows a significant increase in ductility and stiffness of the tapered steel section with elipse shape opening and consequently changes in the behaviour of yield point.

The stress concentration factor (SCF) is commonly utilized to assess the fatigue life of a tubular T-joint in offshore structures. Parametric equations derived from experimental testing and finite element analysis (FEA) are utilized to estimate the SCF efficiently. The mathematical equations provide the SCF at the crown and saddle of tubular T-joints for various load scenarios. Offshore structures are subjected to a wide range of stresses from all directions, and the hotspot stress might occur anywhere along the brace. It is critical to incorporate stress distribution since using the single-point SCF equation can lead to inaccurate hotspot stress and fatigue life estimates. As far as we know, there are no equations available to determine the SCF around the axis of the brace.

A mathematical model based on the training weights and biases of artificial neural networks (ANNs) is presented to predict SCF. 625 FEA simulations were conducted to obtain SCF data to train the ANN.

Using real data, this ANN was used to create mathematical formulas for determining the SCF. The equations can calculate the SCF with a percentage error of less than 6%.

Engineers in practice can use the equations to compute the hotspot stress precisely and rapidly, thereby minimizing risks linked to fatigue failure of offshore structures and assuring their longevity and reliability. Our research contributes to enhancing the safety and reliability of offshore structures by facilitating more precise assessments of stress distribution.

Precisely determining the SCF for the fatigue life of offshore structures reduces the potential hazards associated with fatigue failure, thereby guaranteeing their longevity and reliability. The present study offers a systematic approach for using FEA and ANN to calculate the stress distribution along the weld toe and the SCF in T-joints since ANNs are better at approximating complex phenomena than standard data fitting techniques. Once a database of parametric equations is available, it can be used to rapidly approximate the SCF, unlike experimentation, which is costly and FEA, which is time consuming.

In recent years, natural dyes have attracted significant attention globally because of growing public awareness of the environment and health hazards associated with synthetic dyes. Natural dyes can provide special aesthetic qualities as well as the ethical significance of a product which is environmentally friendly. By keeping this burning issue in mind, this study aims to explore the dyeing properties of various unexplored environmentally friendly natural dyes.

In this study, the aqueous extract of coconut leaves is used for dyeing purpose. The silk and jute fabrics were dyed with the extract alone as well as in combination with metal salts as mordants by employing pre-, meta- and postmordanting techniques. The dyeing properties of the colored samples were evaluated by measuring their color strength; CIEL*a*b* values; and color fastness to washing, light and rubbing.

A yellow shade was achieved when the fabric samples were dyed solely with the extract. However, shade variations were observed when different mordants and mordanting techniques were applied. In all the cases, metallic salts improved the color fastness properties of dyed samples to washing, light and rubbing especially for the silk fabric.

To the best of the authors’ knowledge, this is the first report on a natural dye extracted from the leaves of coconut. Leaf as the source of dye has added an extra advantage, as it is reproducible and can be collected easily without harming the plants. The reported dye could be an attractive choice for sustainable and eco-friendly dyeing.

Despite city authorities in Bangladesh being concerned about urban sustainability, they often face difficulties in addressing predominant urban challenges threatening urban sustainability, due to limited relevant literature. To reduce this gap, this study aims to address the predominant urban challenges and assess their severity levels in four city corporations of Bangladesh, e.g. Rajshahi, Sylhet, Barishal, and Gazipur.

Using a mixed-method approach, this study rigorously analyzed field-level data obtained from 1,200 residents across selected cities using diverse statistical techniques. The quantitative analysis included descriptive analysis, exploratory factor analysis, and chi-square tests, whereas qualitative insights were derived through thematic analysis.

The study uncovered nine predominant urban challenges under two crucial factors “Feeble Urban Management” and “Illicit Activities” that collectively explain 62.20% variance. “Feeble Urban Management” explains 44.17% variance, whereas “Illicit Activities” accounts for 18.13%. Within these challenges, uncontrolled urban sprawl, inadequate disaster management, congested roads, and shabby drainage and waste management pose significant threats to urban sustainability. Illicit activities, manifested by encroachment on water sources, grabbing roadside, destruction of natural properties, and activities undermining social security, compound the urban sustainability issue. Severity analysis reveals Sylhet (54.5%), Rajshahi (46.4%), and Barishal (31.2%) as highly impacted, whereas Gazipur exhibits moderate severity (66.7%).

The findings of this study reveal intrinsic insights into urban challenges in Bangladesh that will provide valuable guidance to city authorities, equipping them to implement integrated and effective initiatives and programs that overcome these predominant urban challenges, with a specific focus on Rajshahi, Sylhet, and Barishal city corporations.

Stress concentration factors (SCFs) are commonly used to assess the fatigue life of tubular T-joints in offshore structures. SCFs are usually estimated from parametric equations derived from experimental data and finite element analysis (FEA). However, these equations provide the SCF at the crown and saddle points of tubular T-joints only, while peak SCF might occur anywhere along the brace. Using the SCF at the crown and saddle can lead to inaccurate hotspot stress and fatigue life estimates. There are no equations available for calculating the SCF along the T-joint's brace axis under in-plane and out-of-plane bending moments.

In this work, parametric equations for estimating SCFs are developed based on the training weights and biases of an artificial neural network (ANN), as ANNs are capable of representing complex correlations. 1,250 finite element simulations for tubular T-joints with varying dimensions subjected to in-plane bending moments and out-of-plane bending moments were conducted to obtain the corresponding SCFs for training the ANN.

The ANN was subsequently used to obtain equations to calculate the SCFs based on dimensionless parameters (α, β, γ and τ). The equations can predict the SCF around the T-joint's brace axis with an error of less than 8% and a root mean square error (RMSE) of less than 0.05.

Accurate SCF estimation for determining the fatigue life of offshore structures reduces the risks associated with fatigue failure while ensuring their durability and dependability. The current study provides a systematic approach for calculating the stress distribution at the weld toe and SCF in T-joints using FEA and ANN, as ANNs are better at approximating complex phenomena than typical data fitting techniques. Having a database of parametric equations enables fast estimation of SCFs, as opposed to costly testing and time-consuming FEA.

Composite materials are effective alternatives for rehabilitating critical members of offshore platforms, bridges, and other structures. The structural response of composite reinforcement greatly depends on the orientation of fibres in the composite material. Joints are the most critical part of tubular structures. Various existing studies have identified optimal reinforcement orientations for a single load component, but none has addressed the combined load case, even though most practical loads are multiplanar.

This study investigates the optimal orientation of composite reinforcement for reducing stress concentration factors (SCF) of tubular KT-joints. The joint reinforcement was modelled and simulated using ANSYS. A parametric study was carried out to determine the effect of the orientations of reinforcement in the interface region on SCF at every 15° offset along the weld toe using linear extrapolation of principal stresses. The impact of orientation for uniplanar and multiplanar loads was investigated, and a general result about optimum orientation was inferred.

It was found that the maximum decrease of SCF is achieved by orienting the fibres of composite reinforcement along the maximum SCF. Notably, the optimal direction for any load configuration was consistently orthogonal to the weld toe of the chord-brace interface. As such, unidirectional composites wrapped around the brace axis, covering both sides of the brace-chord interface, are most effective for SCF reduction.

The findings of this study are crucial for adequate reinforcement of tubular joints using composites, offering a broader and universally applicable optimum orientation that transcends specific joint and load configuration.

The mega railway infrastructure projects are faced with complex environments and multi-level management challenges. Thus, the mega railway infrastructure project management system not only needs to focus on its composition, but also needs to consider changes and impacts of internal and external environment.

This study attempts to introduce the concept of dissipative structure from the perspective of complexity theory and constructs a positive entropy and negentropy flow index system for mega railway infrastructure project management system in order to analyze the factors of management system more deeply. The Brusselator model is used to construct the structure of the mega railway infrastructure project management system, and the entropy method is used to calculate the positive entropy and negentropy values to verify whether the management system is a dissipative structure.

A plateau railway project in China was used as an example for an empirical study, not only its own characteristics are analyzed, but also the role of constraints and facilitation of the internal and external environment. Based on the research results, several effective suggestions are put forward to improve the stability and work efficiency of mega railway infrastructure project management system.

This study demonstrates that mega railway infrastructure project management system has the characteristics of dissipative structure. It can provide theoretical support for the development of mega railway infrastructure project management system from disorderly state to orderly state.

Examining the role of women on board (WoB) toward corporate sustainable growth (CSG) through leverage policy (LP). This research also investigates the interaction effect of WoB and LP on improving CSG.

This study uses a moderated mediation model to examine the impact of WoB on CSG, mediated by LP. Data from 48 KEHATI IDX ESG Sector Leaders Index companies observed from 2015 to 2021 were analyzed using the structural equation model partial least square (SEM-PLS) Warp.PLS 8.0. The research applies instrumental variables (IV) to test and control endogeneity due to nonrandom sample selection.

We found evidence that LP acts as a full mediator between the presence of WoB and CSG. The presence of WoB plays a moderate role by slightly weakening the influence of LP on CSG. Furthermore, we obtained evidence showing that the relationship between WoB and CSG is J-curve-shaped, a nonlinear relationship related to critical mass. Where the WoB ratio is at least 8.35% or higher, it will increase CSG in companies that have implemented the concept of environment social governance (ESG) in Indonesia.

This model uses a moderated mediation model and J-curve analysis; there is an interaction between WoB and LP on different paths of the mediator to CSG. This model examines the role of WoB as a moderator of the effect of LP on CSG. A nonlinear J-curve test was conducted to determine the minimum level of WoB that can influence the increase of CSG.

For over 25 years, the United States Green Building Council (USGBC) has significantly influenced the US sustainable construction through its leadership in energy and environmental design (LEED) certification program. This study aims to delve into how Baton Rouge, Louisiana, fares in green building adoption relative to other US capital cities and regions.

The study leverages statistical and geospatial analyses of data sourced from the USGBC, among other databases. It scrutinizes Baton Rouge’s LEED criteria performance using the mean percent weighted criteria to pinpoint the LEED criteria most readily achieved. Moreover, unique metrics, such as the certified green building per capita (CGBC), were formulated to facilitate a comparative analysis of green building adoption across various regions.

Baton Rouge’s CGBC stands at 0.31% (C+), markedly trailing behind the frontrunner, Santa Fe, New Mexico, leading at 3.89% (A+) and in LEED building per capita too. Despite the notable concentration of certified green buildings (CGBs) within Baton Rouge, the city’s green building development appears to be in its infancy. Innovation and design was identified as the most attainable LEED benchmark in Baton Rouge. Additionally, socioeconomic factors, including education and income per capita, were associated with a mild to moderate positive correlation (0.25 = r = 0.36) with the adoption of green building practices across the capitals, while sociocultural infrastructure exhibited a strong positive correlation (r = 0.99).

This study is beneficial to policymakers, urban planners and developers for sustainable urban development and a reference point for subsequent postoccupancy evaluations of CGBs in Baton Rouge and beyond.

This study pioneers the comprehensive analysis of green building adoption rates and probable influencing factors in capital cities in the contiguous US using distinct metrics.