Museum cultural relics are valuable heritages of the development and change of the Chinese Nation over thousands of years, so the research on the protection of cultural relics is of great ...significance. In this paper, for the research on double shockproof of museums and cultural relics showcases in the museum, finite element models of the base fixed structure, base isolated structure and viscous fluid damper structure of the museum are established, modal analysis and time-history analysis are carried out to compare the seismic effect of the three kinds of structures. At the same time, the fixed cultural relics showcase, isolated cultural relics showcase and viscous fluid damper cultural relics showcase are established, and the seismic response analysis is carried out by inputting seismic waves and floor waves of the museums to study the acceleration and displacement response of the showcase countertop. The results show that, compared with the base fixed structure and base isolated structure of the museum, the viscous fluid damper structure of the museum can better reduce the inter-story shear force, inter-story drift and the floor acceleration response of the structure, and more effectively consume the seismic energy input to the structure, with the most obvious effect of shock absorption and seismic isolation; relative to the base fixed structure and base isolated structure, under the action of floor waves of the viscous fluid damper structure of the museum, the isolated cultural relics showcase and viscous fluid damper cultural relics showcase for shock absorption and seismic isolation are very obvious, so the isolated cultural relics showcase and viscous fluid damper cultural relics showcase are placed in the viscous fluid damper structure of the museum, all can achieve the purpose of the double shockproof of the cultural relics.
In the infrastructure of the future, based on intelligent computerized systems and control and monitoring devices, the smart home is part of the Internet of Things (IoT). However, in addition to the ...need to address energy consumption, the widespread adoption of smart homes may also exacerbate the growing problem of increasing amounts of non-recyclable e-waste from IoT devices. Compared to synthetic plastics, biopolymers offer many unique advantages such as robust structure, light weight, mechanical flexibility, biocompatibility, biodegradability and renewability. Biopolymers, which are abundant in natural products such as cellulose, silk fibroin, polylactic acid, chitosan, collagen, keratin, alginate, starch and gelatin, have great promise for the production of environmentally friendly Internet of Things devices. They are ideal candidates for the use of low-temperature sol–gel coating and ink-printing processes to facilitate the development of low-cost, large-area flexible electronic devices. This work presents developments known from the literature, as well as the results of original research on the use of biopolymer materials to create flexible, wearable and textile electronic devices, such as sensors, energy storage devices and nanogenerators, soft hydrogel actuators and wireless communication devices that are promising for the Internet of Things but have not yet been implemented in smart homes.
Graphical Abstract
This work aimed to investigate and compare the performance of different machine learning models in predicting the compressive strength of concrete using a data set of 1234 compressive strength ...values. The predictive variables were selected based on their relevance using the SelectKBest method, resulting in an analysis of eight and six predictive variables. The evaluation was conducted through linear correlation studies via simple linear regression and non-linear correlation studies using support vector regression (SVR), random forest (RF), gradient boosting (GB), and artificial neural networks (ANN). The results showed a coefficient of determination (R
2
) = 0.897 and a root mean square error (RMSE) = 6.535 MPa for SVR, R
2
= 0.885 and RMSE = 5.437 MPa for GB, R
2
= 0.868 and RMSE = 5.859 MPa for GB and R
2
= 0.894 and RMSE = 5.192 MPa for ANN, all for test set and eight predictor variables. The comparison between the machine learning methods revealed significant differences. For instance, ANN stood out with a higher R
2
value, demonstrating its remarkable ability to explain the variability in the data. ANN also showed the lowest RMSE value, indicating notable accuracy in the predictions. Although ANN has demonstrated higher performance, GB shows a closer performance, which no differences from a practical application. The choice between these approaches depends on considerations regarding the balance between explainability and accuracy. While GB provides a more in-depth understanding of the relationship between variables, ANN stands out for the accuracy of its predictions.
The recent IPCC 2023 report reiterates that humans are responsible for global warming over the past 200 years, causing a rise in temperature of 1.1 °C above pre-industrial levels, urging the ...implementation of mitigation options, especially in the building energy sector. One strong mitigation strategy is designing and building net zero energy buildings (NZEB), although their implementation faces challenges such as opposition to change, especially in tropical countries with traditional and conservative design and construction practices. This paper uses data from a pilot NZEB Laboratory building at UCA, El Salvador, and details its results by comparing different construction system scenarios. The present work presents the results of the Life-cycle assessment (LCA) in three popular construction systems in El Salvador, comparing them with the baseline of its current operation, through 3 iterative calculation tools: structural, thermal and carbon footprint estimation, managing to visualize important findings on how vernacular systems could meet the NZEB performance with added insulation in the structural walls. In addition, a triple-axis sustainability analysis (environmental, economic and social) is conducted using the weighted criteria matrix, which provides nuanced results, such as the proportional share of embodied carbon between the proposals, there is not much difference between the results of the proposed systems, but compared to the baseline, the proposals represent a significant increase of more than 50%. Our results show that in this context, the scalability of NZEB buildings is feasible for different construction systems, paving the way for a progressive and incremental.
An economical and cost-effective replacement for conventional building materials is Compressed Stabilized Earth Block (CSEB). However, they are vulnerable to erosion and cracking, particularly in ...humid settings. The use of natural fibers as reinforcement is found effective in overcoming this problem. Areca nut fiber which is a complete waste material in countries like Bangladesh and India is also a sturdy, adaptable, and water-resistant natural fiber that makes it the perfect choice as fiber reinforcement material for CSEBs. In this article, the strength performance analysis of areca nut fiber as a reinforcement material for CSEBs is investigated, where 0%, 0.85%, 2%, 5%, and 8% of areca nut fiber is mixed with soil that is stabilized with 10% cement. CSEB specimens of 4″ × 4″ × 4″ size have been made and tested for compressive strength, tensile strength, bulk density, and water absorption. It is observed that there is an 83.76% increase in compressive strength and an 8.89% increase in splitting tensile strength for 0.85% of areca nut fiber content specimen cured for 90 days. The water absorption was found a minimum of 9.07% for 0.85% areca nut fiber content and the minimum density of the block was observed at 1810 kg/m
3
for the optimum percentage of 0.85% mix. The study indicates that using 0.85% of areca nut fiber content in stabilized CSEB shows a significant improvement in the strength characteristics of compressed stabilized earth blocks.
Graphical Abstract
Rubberized concrete effectively prevents brittle failures and enhances the ductility and energy absorption of concrete. It has been observed that the inclusion of rubber reduces the strength and ...abrasion resistance of concrete; however, the enhancement in energy absorption is significant. A vast number of tires end up as waste, posing a major environmental issue globally. The disposal of waste tires has become an acute environmental challenge, with billions discarded and buried worldwide, representing a significant ecological threat. Consequently, utilizing rubber in the concrete industry can be advantageous for both the environment and the industry. This study presents an extensive review of the effects of various rubber contents on the mechanical properties of concrete. The scope of the review encompasses an analysis of a diverse range of studies conducted over the past decade, focusing on the influence of rubber content on concrete's mechanical performance. The analysis revealed that the optimal amount of rubber to be used in concrete is in the range of 2–5% as a replacement for natural concrete aggregate. Furthermore, replacing aggregate with treated rubber may offer additional benefits, including improved energy absorption and sustainability. However, despite the promising benefits of rubberized concrete, there is a notable gap in the literature regarding the creep behavior of rubberized concrete, a crucial parameter for defining concrete performance, particularly in superstructures. This gap underscores the need for further research to comprehensively understand the long-term behavior of rubberized concrete under sustained loading conditions. Additionally, while coating or treating rubber could mitigate the reduction in mechanical properties associated with rubber inclusion, there remains a need for more investigation into the brittleness index and energy absorption of treated rubber. Addressing these gaps in knowledge will contribute to a more thorough understanding of the potential applications and limitations of rubberized concrete in various engineering contexts.
In this paper, CaCO
3
waste marble dust (WMD) has been utilized in the production of concrete. Raw materials (Cement, Sand, WMD and Crush) were collected from Peshawar, Khyber Pakhtunkhwa, Pakistan. ...Concrete cubes were molded in the laboratory and investigated by XRD. Effect of WMD addition to the concrete was studied. It was reported that 10% addition of WMD as cement replacement showed enhanced performance of the compressive strength as compared to sand replaced WMD blended concrete. Increment in WMD contents beyond 10% resulted in significant decrement of compressive strength. Substituting WMD with cement resulted in a decrement of 29.76%, while with sand, the decrement was 6.09%. Concrete made with cement replaced WMD showed the lowest water absorption rate over 7 days curing as compared to sand replaced (intermediate water absorption) and clean concrete (highest water absorption) samples.
Graphical Abstract
The automotive industry's globalization and the widespread adoption of cars as primary transportation modes have spurred significant advancements in tire manufacturing. Consequently, a surplus of ...used tires has accumulated in recent years. Concurrently, there has been a shift towards evaluating tire life cycles and developing robust recycling and recovery programs. The potential for repurposing used tires as a valuable resource has become a critical consideration. In response to environmental concerns stemming from tire disposal, researchers have conducted numerous experiments exploring the effects of incorporating crushed rubber tires into concrete mixtures. These endeavors aim to enhance concrete properties while promoting sustainability through recycling. This burgeoning interest in "green concrete" production underscores the importance of investigating waste rubber's applications across various concrete types. This review provides a comprehensive analysis of waste rubber utilization in diverse concrete formulations. Drawing insights from 60 previous studies, the multifaceted impacts of rubber waste on concrete properties were elucidated. This investigation encompasses assessments of compressive strength, tensile strength, flexural strength, density, elastic modulus, and workability parameters through slump, V-funnel, and L-box tests. Through this synthesis, we contribute to a deeper understanding of the potential and limitations of incorporating waste rubber in concrete production, highlighting avenues for future research and practical implementation.
Monitoring civil engineering infrastructure is crucial to ensuring that the structures can continue to function properly. An important aspect of this assessment is detecting structural damage. This ...study proposed a method that combined static loading techniques and modal parameters to establish a third level of damage detection. Specifically, the damage locating vector (DLV) was used as the static technique, and mode shapes, along with Modal Assurance Criteria (MAC), were integrated with the Firefly Algorithm (FA) to define the damage percentage. The objective of this method is to determine the location of the damaged members in space truss structures and accurately estimate the reduction in stiffness of the damaged members. DLV was used to show the location of damaged members, while the Modal Assurance Criteria – Firefly Algorithm (MAC-FA) was used to predict the stiffness loss in structural elements. This combined approach improved the DLV method, which could only identify potentially damaged parts. The fundamental concept behind MAC-FA was the relationship between the predicted mode shape and the mode shape of the structure, represented by the MAC value. This method was used to investigate damage detection in two space truss structures. The results demonstrated that the proposed method could identify damaged elements and quantify the loss of stiffness in space truss structures.
This study is aimed at developing prediction model for structural behavior of Porous Asphalt Pavement (PAP) using ABAQUS software and also developing ANN (Artificial Neural Network) model to predict ...void percentages in Porous Asphalt mix gradations. Data from the past literatures were used to analyze various mixing parameters affecting the properties of Porous Asphalt gradation mixes. The study analyzed PAPs using KENPAVE software. The findings indicated that fewer allowable repetitions to fatigue and rutting failures were observed for thinner Porous Asphalt Concrete (PAC) layer thicknesses. This suggests that thicker PAC layers may offer better resistance to fatigue and rutting failures in pavement systems. The study found that the nature of subgrade material significantly influenced the rutting performance of PAP systems. Specifically, clayey soils exhibited a 77.74% reduction in the design life of the pavement compared to gravelly soil subgrades. This highlights the importance of considering subgrade characteristics in pavement design and construction to optimize pavement performance and longevity. Higher contact pressures resulted in higher tensile stresses at the bottom of PAC layer which in turn reduced the fatigue life of PAP. The findings from ABAQUS analysis indicated that an increase in the void percentage in Porous Asphalt Concrete (PAC) mixes led to a significant increase in horizontal tensile strain at the bottom of the PAC layer, with a 12.3% increase observed. Additionally, there was a noticeable increase in tensile strain for a PAC mix with 28% voids compared to a mix with 16% voids. This suggests that higher void percentages in the PAC mixes can potentially enhance the flexibility and deformation resistance of the pavement structure, which may contribute to improved performance under various loading conditions, hence leading to 92.8% reduction in allowable load repetitions to fatigue failure.
The study further revealed that an increased void percentage in Porous Asphalt Concrete (PAC) mixes resulted in a decrease in vertical stress and deflection in the PAP system. However, no significant effect on the allowable repetitions to rutting failure was observed. This suggests that higher void percentages may lead to better load distribution and reduced vertical stresses within the pavement structure, contributing to improved performance in terms of stress and deflection.
Moreover, Asphalt Pavement mixes were compiled to develop an Artificial Neural Network (ANN) prediction model. The results demonstrated good conformity between predicted and actual data, with a mean square error of 0.109 and a coefficient of correlation of 0.994. This indicates that the ANN model accurately predicts pavement performance based on the compiled asphalt pavement mixes, providing a valuable tool for pavement design and analysis.
