Development of sensing concrete: principles, properties and its applications

YesSensing concrete has the capability to sense its condition and environmental changes, including stress (or force), strain (or deformation), crack, damage, temperature and humidity through incorporating functional fillers. Sensing concrete has recently attracted major research interests, aiming to produce smart infrastructures with elegantly integrated health monitoring abilities. In addition to having highly improved mechanical properties, sensing concrete has multifunctional properties, such as improved ductility, durability, resistance to impact, and most importantly self-health monitoring due to its electrical conductivity capability, allowing damage detection without the need of an external grid of sensors. This tutorial will provide an overview of sensing concrete, with attentions to its principles, properties, and applications. It concludes with an outline of some future opportunities and challenges in the application of sensing concrete in construction industry.National Science Foundation of China (51978127 and 51908103), the China Postdoctoral Science Fundation (2019M651116) and the Fundamental Research Funds for the Central Universities in China (DUT18GJ203).National Science Foundation of China (NSFC) (Nos. 51978127 and 51908103), the China Postdoctoral Science Foundation (No. 2019M651116), and the Fundamental Research Funds for the Central Universities in China (No. DUT18GJ203)

Influence of Shear Reinforcement on Reinforced Concrete Continuous Deep Beams

yesTest results of 24 reinforced concrete continuous deep beams are reported. The main variables studied were concrete strength, shear span-to-overall depth ratio (a/h) and the amount and configuration of shear reinforcement. The results of this study show that the load transfer capacity of shear reinforcement was much more prominent in continuous deep beams than in simply supported deep beams. For beams having an a/ h of 0.5, horizontal shear reinforcement was always more effective than vertical shear reinforcement. The ratio of the load capacity measured and that predicted by the strutand-tie model recommended by ACI 318-05 dropped against the increase of a/h. This decrease rate was more remarkable in continuous deep beams than that in simple deep beams. The strut-and-tie model recommended by ACI 318-05 overestimated the strength of continuous deep beams having a/ h more than 1.0

Influence of Type and Replacement Level of Recycled Aggregates on Concrete Properties.

yesTest results of nine recycled aggregate concretes and a control concrete using only natural aggregates are reported. The recycled aggregates used were classified into three different types according to their measured specific gravity and water absorption, namely, RG I for recycled coarse aggregate having a specific gravity of 2.53 and water absorption of 1.9%; RG III for recycled coarse aggregate having a specific gravity of 2.4 and water absorption of 6.2%; and RS II for recycled fine aggregate having a specific gravity of 2.36 and water absorption of 5.4%. The replacement levels of both recycled coarse and fine aggregates were 30, 50, and 100% in separate mixtures. Slump loss and the amount of bleeding with time were recorded for fresh concrete. Compressive and tensile strengths, moduli of rupture and elasticity, and unrestrained shrinkage strain were also measured for hardened concrete. The properties of fresh and hardened concrete tested, together with a comprehensive database reported in the literature, were evaluated with respect to the relative water absorption of aggregates combining the quality and volume of recycled aggregates used. In addition, the properties of hardened concrete with different replacement levels and quality of recycled aggregates were compared with the design equations of ACI 318-05 and empirical equations proposed by Oluokun for natural aggregate concrete, whenever possible. Test results clearly showed that the properties of fresh and hardened concrete containing recycled aggregates were dependent on the relative water absorption of aggregates. In addition, the moduli of rupture and elasticity of recycled aggregate concrete were lower than the design equations specified in ACI 318-05, when the relative water absorption of aggregates is above 2.5% and 3.0%, respectively

An Empirical Investigation on Perception of Organizational Politics, Job Stress & Job Satisfaction Among Academicians in Pakistan Using Second-Order Construct

Level of job satisfactions among academicians has remained enriched area of research for the academic’s institutions. Therefore, the rationale behind conducting research was to investigate the influence of Perception of Organizational Politics (POP) and Job Stress (JSt) on Job satisfaction (JS) academicians. Research framework has been formed based on Social Exchange Theory (SET) to create logical relationships among variable which explained that employees behave accordingly as per response they received from management’s behavior. For the execution of analysis data was collected from 300 teachers of public sector universities of Punjab, Pakistan through psychometric defined instruments. Software SmartPLS was used for assessment of measurement and structural model. Results from the analysis demonstrates that POP has significant and negative effect on JS and significant positive effect on JSt while significant negative effect was observed between JSt and JS. The results revealed useful information for the stakeholders and policy makers to focus and develop and organizational structure to eliminate the influence of POP in academic institutions

Influence of inclined web reinforcement on reinforced concrete deep beams with web openings.

yesThis paper reports the testing of fifteen reinforced concrete deep beams with openings. All beams tested had the same overall geometrical dimensions. The main variables considered were the opening size and amount of inclined reinforcement. An effective inclined reinforcement factor combining the influence of the amount of inclined reinforcement and opening size on the structural behaviour of the beams tested is proposed. It was observed that the diagonal crack width and shear strength of beams tested were significantly dependent on the effective inclined reinforcement factor that ranged from 0 to 0.318 for the test specimens. As this factor increased, the diagonal crack width and its development rate decreased, and the shear strength of beams tested improved. Beams having effective inclined reinforcement factor more than 0.15 had higher shear strength than that of the corresponding solid beams. A numerical procedure based on the upper bound analysis of the plasticity theory was proposed to estimate the shear strength and load transfer capacity of reinforcement in deep beams with openings. Predictions obtained from the proposed formulas have a consistent agreement with test results

A systematic review of physiological signals based driver drowsiness detection systems.

Driving a vehicle is a complex, multidimensional, and potentially risky activity demanding full mobilization and utilization of physiological and cognitive abilities. Drowsiness, often caused by stress, fatigue, and illness declines cognitive capabilities that affect drivers' capability and cause many accidents. Drowsiness-related road accidents are associated with trauma, physical injuries, and fatalities, and often accompany economic loss. Drowsy-related crashes are most common in young people and night shift workers. Real-time and accurate driver drowsiness detection is necessary to bring down the drowsy driving accident rate. Many researchers endeavored for systems to detect drowsiness using different features related to vehicles, and drivers' behavior, as well as, physiological measures. Keeping in view the rising trend in the use of physiological measures, this study presents a comprehensive and systematic review of the recent techniques to detect driver drowsiness using physiological signals. Different sensors augmented with machine learning are utilized which subsequently yield better results. These techniques are analyzed with respect to several aspects such as data collection sensor, environment consideration like controlled or dynamic, experimental set up like real traffic or driving simulators, etc. Similarly, by investigating the type of sensors involved in experiments, this study discusses the advantages and disadvantages of existing studies and points out the research gaps. Perceptions and conceptions are made to provide future research directions for drowsiness detection techniques based on physiological signals. [Abstract copyright: © The Author(s), under exclusive licence to Springer Nature B.V. 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Sensing the heat: Climate change vulnerability and foreign direct investment inflows

We investigate whether climate change vulnerability determines foreign direct investment (FDI) inflows. We reason that multinational firms foresee a higher climate change vulnerability of host-country a locational disadvantage while making FDI allocation decisions. Utilizing annual data from 152 countries spanning the period 1996–2019 and employing the panel pooled ordinary least square regressions, we evidence that FDI inflows are lower in countries more vulnerable to climate change. We also observe that FDI inflows are only sensitive to climate-related risks in high- and middle-income countries, but not in low-income countries where the market size is a primary driver of FDI inflows. Moreover, we also find that host countries may weaken the adverse effects of climate change vulnerability on FDI inflows by strengthening the economic, institutional, and social environment

Flow and Compressive Strength of Alkali-Activated Mortars.

yesTest results of thirty six ground granulated blast-furnace slag (GGBS)-based mortars and eighteen fly ash (FA)-based mortars activated by sodium silicate and/or sodium hydroxide powders are presented. The main variables investigated were the mixing ratio of sodium oxide (Na2O) of the activators to source materials, water-to-binder ratio, and fine aggregate-to-binder ratio. Test results showed that GGBS based alkali-activated (AA) mortars exhibited much higher compressive strength but slightly less flow than FA based AA mortars for the same mixing condition. Feed-forward neural networks and simplified equations developed from nonlinear multiple regression analysis were proposed to evaluate the initial flow and 28-day compressive strength of AA mortars. The training and testing of neural networks, and calibration of the simplified equations were achieved using a comprehensive database of 82 test results of mortars activated by sodium silicate and sodium hydroxide powders. Compressive strength development of GGBS-based alkali-activated mortars was also estimated using the formula specified in ACI 209 calibrated against the collected database. Predictions obtained from the trained neural network or developed simplified equations were in good agreement with test results, though early strength of GGBS-based alkali-activated mortars was slightly overestimated by the proposed simplified equations