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This purpose of this paper is to quantify the effect of local instability arising from high shear loading on response of steel girders subjected to fire conditions.

A three-dimensional nonlinear finite element model able to evaluate behavior of fire-exposed steel girders is developed. This model, is capable of predicting fire response of steel girders taking into consideration flexural, shear and deflection limit states.

Results obtained from numerical studies show that shear capacity can degrade at a higher pace than flexural capacity under certain loading scenarios, and hence, failure can result from shear effects prior to attaining failure in flexural mode.

The developed model is unique and provides valuable insight (and information) to the fire response of typical hot-rolled steel girder subjected to high shear loading.

This research paper aims to investigate reinforced concrete (RC) walls' behaviour under fire and identify the thermal and mechanical factors that affect their performance.

A three-dimensional (3D) finite element (FE) model is developed to predict the response of RC walls under fire and is validated through experimental tests on RC wall specimens subjected to fire conditions. The numerical model incorporates temperature-dependent properties of the constituent materials. Moreover, the validated model was used in a parametric study to inspect the effect of the fire scenario, reinforcement concrete cover, reinforcement ratio and configuration, and wall thickness on the thermal and structural behaviour of the walls subjected to fire.

The developed 3D FE model successfully predicted the response of experimentally tested RC walls under fire conditions. Results showed that the fire resistance of the walls was highly compromised under hydrocarbon fire. In addition, the minimum wall thickness specified by EC2 may not be sufficient to achieve the desired fire resistance under considered fire scenarios.

There is limited research on the performance of RC walls exposed to fire scenarios. The study contributed to the current state-of-the-art research on the behaviour of RC walls of different concrete types exposed to fire loading, and it also identified the factors affecting the fire resistance of RC walls. This guides the consideration and optimisation of design parameters to improve RC walls performance in the event of a fire.

The extreme nature of fire makes structural fire engineering unique in that the load actions dictating design are intense and neither geographically nor seasonally bound. Simply, fire can break out anywhere, at any time and for any number of reasons. Despite the apparent need, the fire design of structures still relies on expensive fire tests, complex finite element simulations and outdated procedures with little room for innovation. This paper aims to discuss the aforementioned issues.

This primer highlights the latest state of the art in this area with regard to performance-based design in fire structural engineering. In addition, this short review also presents a series of examples of successful implementation of performance-based fire design of structures from around the world.

A comparison between global efforts clearly shows the advances put forth by European and Oceanian efforts as opposed to the rest of the world. In addition, it can be clearly seen that most performance-based fire designs are related to steel and composite structures.

In one study, this paper presents a concise and global view to performance-based fire design of structures from success stories from around the world.

This study examines the effect of temperature-dependent material models for normal-strength (NSC) and high-strength concrete (HSC) on the thermal analysis of reinforced concrete (RC) walls.

The study performs an one-at-a-time (OAT) sensitivity analysis to assess the impact of variables defining the constitutive and parametric fire models on the wall's thermal response. Moreover, it extends the sensitivity analysis to a variance-based analysis to assess the effect of constitutive model type, fire model type and constitutive model uncertainty on the RC wall's thermal response variance. The study determines the wall’s thermal behaviour reliability considering the different constitutive models and their uncertainty.

It is found that the impact of the variability in concrete’s conductivity is determined by its temperature-dependent model, which differs for NSC and HSC. Therefore, more testing and improving material modelling are needed. Furthermore, the heating rate of the fire scenario is the dominant factor in deciding fire-resistance performance because it is a causal factor for spalling in HSC walls. And finally the reliability of wall's performance decreased sharply for HSC walls due to the expected spalling of the concrete and loss of cross-section integrity.

Limited studies in the current open literature quantified the impact of constitutive models on the behaviour of RC walls. No studies have examined the effect of material models' uncertainty on wall’s response reliability under fire. Furthermore, the study's results contribute to the ongoing attempts to shape performance-based structural fire engineering.

This paper aims to present results from numerical studies on the response of fire exposed composite girders subjected to dominant flexural and shear loading. A finite element-based numerical model was developed to trace the thermal and structural response of composite girders subjected to simultaneous structural loading and fire exposure. This model accounts for various critical parameters including material and geometrical nonlinearities, property degradation at elevated temperatures, shear effects, composite interaction between concrete slab and steel girder, as well as temperature-induced local buckling. To generate test data for validation of the model, three composite girders, each comprising of hot-rolled (standard) steel girder underneath a concrete slab, were tested under simultaneous fire and gravity loading.

The validated model was then applied to investigate the effect of initial geometric imperfections, load level, thickness of slab and stiffness of shear stud on fire response of composite girders.

Results from experimental and numerical analysis indicate that the composite girder subjected to flexural loading experience failure through flexural yielding mode, while the girders under shear loading fail through in shear web buckling mode. Further, results from parametric studies clearly infer that shear limit state can govern the response of fire exposed composite girders under certain loading configuration and fire scenario.

This paper presents results from numerical studies on the response of fire exposed composite girders subjected to dominant flexural and shear loading.

This study seeks to understand the connection of methodology by finding relevant papers and their full review using the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA).

Concrete-filled steel tubular (CFST) columns have gained popularity in construction in recent decades as they offer the benefit of constituent materials and cost-effectiveness. Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Gene Expression Programming (GEP) and Decision Trees (DTs) are some of the approaches that have been widely used in recent decades in structural engineering to construct predictive models, resulting in effective and accurate decision making. Despite the fact that there are numerous research studies on the various parameters that influence the axial compression capacity (ACC) of CFST columns, there is no systematic review of these Machine Learning methods.

The implications of a variety of structural characteristics on machine learning performance parameters are addressed and reviewed. The comparison analysis of current design codes and machine learning tools to predict the performance of CFST columns is summarized. The discussion results indicate that machine learning tools better understand complex datasets and intricate testing designs.

This study examines machine learning techniques for forecasting the axial bearing capacity of concrete-filled steel tubular (CFST) columns. This paper also highlights the drawbacks of utilizing existing techniques to build CFST columns, and the benefits of Machine Learning approaches over them. This article attempts to introduce beginners and experienced professionals to various research trajectories.

The 2030 United Nations Agenda has framed Sustainable Development Goal 9 around eight targets outlined in Resolution A/RES/71/313 (U.N. General Assembly, 2017). The purpose of this chapter is that the lectors, without much previous knowledge on SDG9, understand the fundamental concepts involved in each of the eight targets. Multiple discussion points emerge when reflecting on the nature of these concepts and others emerge when reflecting on them in the industry settings. The first section of this chapter covers issues concerning resilient infrastructure. Resilient infrastructure is related to targets 9.1, 9.4, and 9.a. This concept needs to cope with extreme natural events potentially associated with global warming and climate change. The second section focusses on the importance of technological innovation in the context of targets 9.5 and 9.b. In a business domain, innovation allows to strengthen industrial competitiveness and increases corporate sustainability. The third concept covered in this chapter is the Information and Communication Technology that is a key to understand target 9.c. Last but not the least, two essential ideas are discussed: Inclusive and sustainable industrialisation and financial services, which are fundamental elements in target 9.2 and target 9.3. In a certain way, it is possible to conclude that both concepts integrate all previous conceptions.

The ultimate capacity and ductility behavior of a reinforced concrete (RC) beam generally depends on its constituent material properties. This study aims to use ANSYS to accentuate the nonlinear parametric finite element (FE) simulations of RC sections under monotonic loading.

The concrete matrix and steel reinforcement are the primary constituent materials of RC beams. The material properties such as tensile reinforcement area, tensile bars yield strength, concrete compressive strength and strain rate in tensile reinforcement at nominal strength have significantly influenced the ultimate response of RC beams. Therefore, these intensive parameters are considered in this study to ascertain their effect on the RC beam's ultimate behavior. The nonlinear response up to the ultimate load capacity and the crack evolutions of RC beams are predicted efficiently.

The parametric study reveals that increasing the tensile steel reinforcements (from Ast = 213–857 mm2) significantly improves the ultimate load capacity by 229% and yield deflections by 20%. However, it declines the ultimate deflection by 47% and ductility by 56% substantially. Varying the strain limit (?tn = 0.010–0.0015) of tensile reinforcement has proficiently increased the ultimate load-resisting capacity by 20%, whereas the ductility declined by 62%. When the concrete strength increases (from fck = 25–65 MPa), the cracking load increases profoundly by 51%, whereas the ultimate capacity has found an insignificant effect.

The load-deflection response plots extracted from the proposed numerical model exhibit satisfactory accuracy (less than 9% deviation) against the experimental curves available in the literature, which emphasizes the proficiency of the proposed FE model.

In this study, engineering stress-strain relationships considering an effect of strain rate on steel materials at elevated temperatures were formulated and a simplified analytical model using a two-dimensional beam element to analytically examine the effect of strain rate on the load-bearing capacity and collapse temperature was proposed.

The stress-strain relationships taking into account temperature, strain, and strain rate were established based on the past coupon test results with strain rate as the test parameter. Furthermore, an elasto-plastic analysis using a two-dimensional beam element, which considered the effect on strain rate, was conducted for both transient- and steady-state conditions.

The analytical results agreed relatively well with the test results, which used small steel beam specimens with a rectangular cross-section under various heating rates (transient-state condition) and deformation rates (steady-state condition). It was found that the bending strength and collapse temperature obtained from the parametric analyses agreed relatively well with those evaluated using the effective strength obtained from the coupon tests with strain equal to 0.01 or 0.02 under the fast strain rates.

The effect of stress degradation, including the stress-strain relationships at elevated temperature, was mitigated by considering the effect of strain rate on the analytical model. This is an important point to consider when considering the effect of strain rate on steel structural analysis at elevated temperatures to maintain analytical stability unaccompanied by the stress degradation.

There seems to be no controversy about Nigeria being an agricultural country with food sufficiency up till the late 1970s. However, in recent times the country is finding it very difficult to provide sufficient food for the teeming population which has resulted in the majority of the country’s citizens slipping into poverty. The ability of the country to provide sufficiently for the citizens was a result of a lack of reliable and effective developmental and transformational strategies in the agricultural sector of the country which is a major employer of labour in the rural community. To this end, this chapter mainly focuses on factors inhibiting the development of agricultural companies in Nigeria and how to overcome the developmental barriers in the agricultural sector in Nigeria. The findings from the review show that the bane of the agricultural sector in Nigeria is due to the lack of an agricultural regulatory framework and policy transmission mechanism and over-dependence on oil revenue amongst other things (Adams, 2016). It is therefore imperative for the country to embark on the development of a reliable agricultural framework and model that will aid food sufficiency in the country.