1. Investigación

The scientific understanding of the concepts of cold and heat that have accompanied the human species throughout history has not been easy. The concept of heat is more widespread and studied among us, as well as its consequences. However, we wonder what would happen if we lowered the temperature a lot? As the temperature begins to drop, it can be predicted that the atoms tend to slow down, slowing down their speed, and when this happens, existing theories begin to tremble. The laws governing the atomic world, so small and tiny, do not allow objects (atoms, protons, neutrons, etc.) to stop. This is where quantum physics appears, it tells us how particles behave at the atomic level, and they appear in a forceful way when we approach temperature values around absolute zero. If atoms stopped moving, they would have zero energy, however, quantum mechanics makes it impossible to have this kind of energy.

The use of supplementary cementitious materials has been widely accepted due to increasing global carbon emissions resulting from demand and the consequent production of Portland cement. Moreover, researchers are also working on complementing the strength deficiencies of concrete; fiber reinforcement is one of those techniques. This study aims to assess the influence of recycling wheat straw ash (WSA) as cement replacement material and coir/coconut fibers (CF) as reinforcement ingredients together on the mechanical properties, permeability and embodied carbon of concrete. A total of 255 concrete samples were prepared with 1:1.5:3 mix proportions at 0.52 water-cement ratio and these all-concrete specimens were cured for 28 days. It was revealed that the addition of 10 % WSA and 2 % CF in concrete were recorded the compressive, splitting tensile and flexural strengths by 33 MPa, 3.55 MPa and 5.16 MPa which is greater than control mix concrete at 28 days respectively. Moreover, it was also observed that the permeability of concrete incorporating 4 % of coir fiber and 20 % of WSA was reduced by 63.40 % than that of the control mix after 28 days which can prevent the propagation of major and minor cracks. In addition, the embodied carbon of concrete is getting reduced when the replacement level of cement with WSA along with CF increases in concrete. Furthermore, based on the results obtained, the optimum amount of WSA was suggested to be 10 % and that of coir fiber reinforcement was suggested to be 2 % for improved results.

Researchers are investigating eco-friendly binders like coconut shell ash (CSA), metakaolin (MK), and calcined clay (CC) as supplementary cementitious materials (SCM) in high-strength concrete (HSC). Abundantly available as industrial or agricultural waste, these materials, when combined with Portland cement (PC), offer synergistic benefits. This not only improves concrete performance but also addresses waste disposal issues, presenting a sustainable and environmentally friendly solution for long-term use in HSC production. However, this study performed on fresh and mechanical characteristics of HSC blended with CSA, MK, and CCA alone and together as SCM after 28 days of curing. A total of 504 samples of standard concrete were cast and the cubical samples were tested to achieve the targeted compressive strength about 80 MPa after 28 days. The experimental results indicated that the rise in tensile, flexural and compressive strengths of 9.62%, 8.27%, and 10.71% at 9% of CSA, MK, and CC as SCM after 28 days of curing. As SCM content increases, the density, porosity and water absorption of concrete decrease. Moreover, the workability of fresh concrete is getting reduced when the concentration of SCMs increases in HSC. In addition, the concrete’s sustainability assessment revealed that employing 18% MK, CC, and CSA as SCM reduced carbon emissions by approximately 11.78%. It is suggested that using 9% CC, MK and CSA together in HSC yields the best results for practical applications in civil engineering.

A new logistic model tree (LMT) model is developed to predict slope stability status based on an updated database including 627 slope stability cases with input parameters of unit weight, cohesion, angle of internal friction, slope angle, slope height and pore pressure ratio. The performance of the LMT model was assessed using statistical metrics, including accuracy (Acc), Matthews correlation coefficient (Mcc), area under the receiver operating characteristic curve (AUC) and F-score. The analysis of the Acc together with Mcc, AUC and F-score values for the slope stability suggests that the proposed LMT achieved better prediction results (Acc = 85.6%, Mcc = 0.713, AUC = 0.907, F-score for stable state = 0.967 and F-score for failed state = 0.923) as compared to other methods previously employed in the literature. Two case studies with ten slope stability events were used to verify the proposed LMT. It was found that the prediction results are completely consistent with the actual situation at the site. Finally, risk analysis was carried out, and the result also agrees with the actual conditions. Such probability results can be incorporated into risk analysis with the corresponding failure cost assessment later.

People may be exposed to energy sources that they cannot perceive with their senses, but which may be harmful to their organism, and therefore, individuals cannot avoid them. One of these energy sources is the sound, particularly sound out of the hearing range (20–20000 Hz). Although the sounds are imperceptible for frequencies below 200 Hz unless they have high intensities. Sound with frequencies below 200 Hz is called “low frequency sound”. This study focuses on low frequency sound generated by artificial sources, and specially in sound located in urban areas. Specifically in the measurement and detection of low frequency sources from the perspective of individuals who are manifesting the symptoms associated with their exposure. To this end, a household of Madrid with individuals who have symptoms is taken as sample. This home did not have large potential sources of low-frequency sounds near its location, such as streets with high intensity of traffic or the subway in order to better contrast other possible sources that are not so obvious. The results show high levels of sound emission at the lowest frequency range (20–200 Hz). These results also show that filters should not be applied to remove non-audible frequency spectrums, such as A type, because it omits sounds in urban areas that could affect people. Data treatment incorporates analysis methods based on machine learning which allow differentiate between sources without measuring on them. Finally, further developments must incorporate measurements bellow 20 Hz and will increase the numbers of households sampled.