Search Results (7)

Over the last decades, cement has been observed to be the most adaptive material for global development in the construction industry. The use of ordinary concrete primarily requires the addition of cement. According to the record, there has been an increase in the direct carbon footprint during cement production. The International Energy Agency, IEA, is working toward net zero emissions by 2050. To achieve this target, there should be a decline in the clinker-to-cement ratio. Also, the deployment of innovative technologies is required in the production of cement. The use of alternative binding materials can be an easy solution. There are several options for a substitute to cement as a binding agent, which are available commercially. Non-crystalline alkali-aluminosilicate geopolymers have gained the attention of researchers over time. Geopolymer concrete uses byproduct waste to reduce direct carbon dioxide emissions during production. Despite being this advantageous, its utilization is still limited as it shows the quasi-brittle behavior. Using different fibers has been started to overcome this weakness. This article emphasizes and reviews various mechanical properties of fiber-reinforced geopolymer concrete, focusing on its development and implementation in a wide range of applications. This study concludes that the use of fiber-reinforced geopolymer concrete should be commercialized after the establishment of proper standards for manufacturing. Full article

Computer simulations are challenging in terms of modeling the appropriate behavior of brick masonry structures. These numerical simulations are becoming increasingly difficult due to several design code requirements considered for the technical assessment of brick masonry structures for rehabilitation. In Romania, many brick masonry structures have withstood powerful earthquakes during their lifetime and require rehabilitation works. This paper aims to further assess various simulation challenges regarding the boundary conditions of spandrels and masonry structural behavior. This paper presents a comparative numerical study of two different spandrel-piers scenarios: one considers the link between them as unaffected, and the other attempts to simulate the occurrence of damage by replacing the spandrel’s presence in the initial structure. The proposed model follows the “strong pier–weak spandrel model” and is aimed at practicing engineers. Models are computed with ordinary design software such as Robot Structural Analysis with 2D shells finite elements for masonry walls and, in a more complex manner, software such as Ansys with 3D solid finite elements. Time history analyses are carried out for three distinct accelerograms recorded in Romania. A comparison of the results acquired from these two models is presented and discussed. The purpose of this research is to highlight the importance of proper modeling of unreinforced brick masonry structures to optimize operational and maintenance practices. Full article

This paper aims to investigate the differences in standing balance control ability between freestyle skiing aerials athletes and ordinary graduate students by means of wavelet transform (WT) and the overall stability index (OSI) and to discover the characteristics of the postural control ability of dissimilar subjects and appropriate methods to assess the postural control ability of the human body. Research Methods: In all, 16 subjects were tested, including 8 from the Chinese national team who had won the world championships of freestyle skiing aerials, with 10+ years of training (age: 23 ± 23.1 years, Height: 176 ± 2.1 cm, and weight: 69 ± 3.5 kg), and 8 ordinary graduate students of Shenyang Institute of Physical Education (age: 22.6 ± 4.6 years, Height: 179 ± 3.3 cm, and weight: 73 ± 4.1 kg). When performing the tasks, the research subjects were required to stand on the steady support surface (with eyes closed and legs closed) for 30 s in each testing. The displacement data of the anteroposterior (AP) direction and the mediolateral (ML) direction of their centre of pressure (COP) were recorded. Then, WT and OSI were calculated. Two dissimilar methods were compared to analyse the characteristics of balance ability. Results: (1) The athletes’ WT values in the AP direction and the ML direction were concentrated in the interval of 22~30 s and 0–8 s, respectively, while the ordinary graduate students’ WT values in the AP direction and the ML direction were concentrated in the interval of 10~25 s and 0–7 s, respectively; (2) the WT values of the regular graduate students in the AP direction and the ML direction were higher than those of the athletes (p < 0.01); and (3) the OSI value in the AP direction of the athletes was higher than of the ordinary graduate students, while the OSI value in the ML direction of the athletes was lower than that of regular graduate students. Conclusion: Compared to the OSI, WT can analyse the characteristics of balance control ability more effectively. The COP displacement frequencies of the athletes and ordinary graduate students were concentrated in the low-frequency bands. The athletes had superior adjustment ability in an imbalanced state and could adjust to the best position without effort. In addition, the athletes had a stronger adaptive ability. In comparison, the ordinary graduate students had comparatively poor adaptive ability and weak adjustment ability in the imbalanced state, so it was difficult for them to attain the best angle after adjustment. Full article

We study the distribution theory of some statistics related to records from a sequence of geometrically distributed random variables. The main novelty in this study is the introduction of q-calculus techniques. We obtain representations for the probability functions of some variables of interest, such as, for instance, record times, number of records, inter-record times, record indicators, etc., in terms of multiple q-integrals. It is remarkable to note that the expressions thus obtained are q-analogues of the corresponding well-known results in the absolutely continuous case. We also explore a duality between the results in the case of weak and ordinary records. Full article

High-precision maps of soil organic carbon (SOC) are beneficial for managing soil fertility and understanding the global carbon cycle. Digital soil mapping plays an important role in efficiently obtaining the spatial distribution of SOC, which contributes to precision agriculture. However, traditional soil-forming factors (i.e., terrain or climatic factors) have weak variability in low-relief areas, such as plains, and cannot reflect the spatial variation of soil attributes. Meanwhile, vegetation cover hinders the acquisition of the direct information of farmland soil. Thus, useful environmental variables should be utilized for SOC prediction and the digital mapping of such areas. SOC has an important effect on crop growth status, and remote sensing data can record the apparent spectral characteristics of crops. The normalized difference vegetation index (NDVI) is an important index reflecting crop growth and biomass. This study used NDVI time series data rather than traditional soil-forming factors to map SOC. Honghu City, located in the middle of the Jianghan Plain, was selected as the study region, and the NDVI time series data extracted from Landsat 8 were used as the auxiliary variables. SOC maps were estimated through stepwise linear regression (SLR), partial least squares regression (PLSR), support vector machine (SVM), and artificial neural network (ANN). Ordinary kriging (OK) was used as the reference model, while root mean square error of prediction (RMSE_P) and coefficient of determination of prediction (R²_P) were used to evaluate the model performance. Results showed that SOC had a significant positive correlation in July and August (0.17, 0.29) and a significant negative correlation in January, April, and December (−0.23, −0.27, and −0.23) with NDVI time series data. The best model for SOC prediction was generated by ANN, with the lowest RMSE_P of 3.718 and highest R²_P of 0.391, followed by SVM (RMSE_P = 3.753, R²_P = 0.361) and PLSR (RMSE_P = 4.087, R²_P = 0.283). The SLR model was the worst model, with the lowest R²_P of 0.281 and highest RMSE_P of 3.930. ANN and SVM were better than OK (RMSE_P = 3.727, R²_P = 0.372), whereas PLSR and SLR were worse than OK. Moreover, the prediction results using single-data NDVI or short time series NDVI showed low accuracy. The effect of the terrain factor on SOC prediction represented unsatisfactory results. All these results indicated that the NDVI time series data can be used for SOC mapping in plain areas and that the ANN model can maximally extract additional associated information between NDVI time series data and SOC. This study presented an effective method to overcome the selection of auxiliary variables for digital soil mapping in plain areas when the soil was covered with vegetation. This finding indicated that the time series characteristics of NDVI were conducive for predicting SOC in plains. Full article

The association between elevation (agro-climatic zones, ACZs) and the mean annual total rainfall (MATRF) is not straightforward in different parts of the world. This study sought to estimate the amount of MATRF across four elevation zones of Jema watershed, which is situated in the northwestern highlands of Ethiopia, by employing an appropriate interpolation method. The elevation of the watershed ranges from 1895 to 3518 m a.s.l. For the sake of this study, 34 sample MATRF data were extracted from satellite and nearby gauge stations that were recorded from 1983 to 2010. These data sources were reconstructed by International Research Institute for Climate and Society at Columbia University, USA, at a scale of 10 km by 10 km. An elevation data set generated from a digital elevation model with 30-m resolution (DEM 30 m) was considered as a covariable to estimate the MATRF. To identify the optimal interpolation model, mean errors were computed using cross-validation statistics. The root-mean-square error (RMSE) analysis showed that ordinary cokriging (OCK) was the most accurate model with a predictive power of 87.3%. The root-mean-square standardized (RMSSE) analysis showed that the best precision value (0.72) occurred in OCK. Stable and Gaussian trend lines together with local polynomial types of trend removal, and an elliptical neighborhood search function could perform best to maximize the accuracy and the precision of estimating MATRF. Elevation, as a covariable, enhanced the degree of accuracy and precision of estimation. The value of the trend line function (least square) between the MATRF and elevation was very weak (R² = 0.07), whereas the value of trend line function (least square) between the MATRF and the longitude coordinates (east–west direction) was medium (R² = 0.34). The estimated MATRF for the entire watershed under study ranged from 1228 to 1640 mm. To conclude, elevation could contribute to the estimation of the MATRF. The value of the MATRF showed a declining pattern from the lower to higher elevation areas of the watershed. Full article

The Dubas bug Ommatissus lybicus is a serious pest of date palms. The infestation level of the Dubas bug varies from location to location, as well as from one season to the next. Climate factors are considered to be the main drivers for fluctuations in infestation levels. Few studies have examined the effects of solar radiation on O. lybicus infestation. This study was undertaken to examine the effect of solar radiation on O. lybicus infestation levels in Oman. Infestation data were collected during the spring infestation seasons of 2009 and 2016 from 49 and 69 locations, respectively, from seven governorates of North Oman. The monthly clear-sky potential solar radiation was calculated from a digital elevation model (DEM) with 20-m resolution in the ArcGIS environment, and the average daily solar radiation was calculated for each month. Ordinary least square regression (OLS) and geographic weight regression (GWR) models were run to find the relationship between infestation levels and solar radiation. The infestation level ranged from 0.02 insect/leaflet to 32.98 insects/leaflet, with an average of 7.50 insects/leaflet in 2009 and 0.17 insect/leaflet to 17.52 insects/leaflet, with an average of 4.38 insects/leaflet in 2016. The highest solar radiation was recorded in June, with an average of 27.7 MJ/m²/day, and the minimum was in December, with an average of 14.1 MJ/m²/day. The higher infestation rate showed a weak correlation with solar radiation. Full article