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[Abstract] Timber-concrete composite systems are a high-performance alternative for building floors, of great interest in the current context of environmental concerns. Looking for a more eco-friendly solution, the paper presents a new flooring system with a wood-concrete connection that does not require adhesives or special metal elements. Four-point bending tests were performed on TCC flooring samples with a span of 6.0, 7.2 and 8.4 m. Its cross section was a prefabricated piece in the shape of an inverted T made up of a lower glulam flange, glued together with a central plywood rib with aligned holes in its upper part that go through the entire thickness of the plywood. The set was completed with a top layer of poured-in-place concrete. The connection between both materials is achieved by penetrating the concrete into the rib holes. Additionally, corrugated steel bars were placed through said holes to achieve ductile behaviour. In all cases, a slenderness ratio of L/24 was used. The experimental results showed that the lowest value of ultimate load obtained was 4.3 times higher than the total service load estimated for a building for public use (9 kN/m2). The maximum deflection of the total load was between L/573 and L/709 for the loads corresponding to a building for public use (9 kN/m2) and between L/1069 and L/1340 for the case of residential type building (5 kN/m2). An analysis of the effects of vibrations in the service limit state in relation to user comfort has been included. The results indicate that the system satisfies the requirements for the intended uses. Consequently, the proposed solution shows its effectiveness both in terms of strength and stiffness for the construction of light floors, being easy to build and having high performance. Ministerio de Ciencia e Innovación; PID2019-107859RB-I00

The construction industry encounters significant challenges in effectively managing solid waste produced during the extraction and production of building materials. In different countries, slurry waste generated from granite and marble processing industries, such as glass industry waste, constitutes a considerable portion of the total solid waste. Its undesirable disposal is causing unprecedented environmental damage. Using these non-biodegradable wastes to produce building materials would reduce the environmental burden and contribute to sustainable construction. This study, in detail, investigates the feasibility of utilizing Granite Powder (GP), Ground Granite Powder (GGP), and Ground Glass Waste (GGW) as partial replacements of components in blended mortar mixes. The mix modifications consist of partial replacement of cement with GGW, GP, and GGP in the range of 5–15% and fine aggregate replacement with Marble powder (MP) in 10–30% by mass. The mechanical, physical, and microstructure properties of blended and control mortar mixes were studied on the 3rd, 7th, 28th, and 91st curing days. The results demonstrate that the partial substitution of 10% GGW and 5% GP with cement and 10% MP with fine aggregates in blended mortars enhance the compressive strength at the later curing age (28 and 91 days) compared to that of a control mortar, which is associated to the development of higher pozzolanic reactivity. The XRD results showed the formation of the lowest content of calcium hydroxide (CH) and the highest content of calcium silicate gel in the blended mortars compared to the control mortar. The results enrich the data available in the literature not always univocal, as in the case of using marble and glass waste, providing also interesting information about the influence of granite powder on the hydration process in a mortar mix actually missing.

Funding Information: This work was supported by the National Key R&D Program of China (No. 2019YFA0705502 , 2019YFA0705501 ), the Young and Middle-aged Excellent Team Project for Scientific and Technological Innovation of Jilin Province , China, the National Natural Science Foundation of China ( 42202345 ), and the National Natural Science Foundation of China (Grant No. 41972324 , 52074212 ). Publisher Copyright: © 2022 Elsevier Ltd In this study, a temperature optimization strategy for the Huadian oil shale autothermal pyrolysis in-situ conversion process (ATS) was first proposed by systematically investigating the reaction characteristics of various semi-cokes. As the pyrolysis temperature rised, the semi-coke's calorific value was found to undergo three different stages of increasing, decreasing, and flattening, peaking at around 330 °C. Additionally, the semi-cokes formed at different temperatures exhibited similar combustion characteristics, including combustion activation energy, combustion characteristic parameters, and product release characteristics. Due to the serious pore blockage caused by the substantial generation and the ignition coking of the bitumen, the reaction characteristics of semi-cokes were dramatically decreased at about 330 °C. Finally, the relationship between in-situ heat generation and demand at various stages of ATS process was discussed, and a reasonable strategy for the screening of temperature parameters was proposed. According to this strategy, the optimal control temperature for the preheating stage was determined at 350–370 °C and at Tact (defined in 4.3.2) for the retorting zone in the reaction stage. The results of this study provide a new perspective on the theoretical foundation of the ATS process and have crucial guiding implications for practical engineering applications.

The need to reduce environmental impact inevitably leads to research on new, more sustainable construction materials. In recent times, the use of the main slags from the steel industry has been vigorously investigated; however, the use of other industrial by-products should also be considered. This study aims to analyze the viability of the use of value-added silicomanganese slag (siderurgical aggregates from ferroalloy industries) in two ways. On the one hand, the potential of ground silicomanganese siderurgical aggregates as a binder or supplementary cementitious material (SCM) due to their high content of silica and alumina. On the other hand, the use of silicomanganese siderurgical aggregates for the manufacture of concrete. The hydraulicity of the ground material has been determined by designing mortars with 20 % replacement of cement and comparing the mechanical performance with Portland cement and fly ash at different ages. Its application as a granulometric skeleton of concrete has been analyzed by comparing the physical-mechanical performance and docility in the fresh state with a conventional limestone aggregate concrete. The results obtained guarantee the pozzolanicity of the material, obtaining resistances similar to Portland cement mortar at 90 days. Furthermore, the material as an aggregate meets the geometric, mechanical and leaching requirements imposed by current regulations, although its use with almost total replacement leads to mechanical losses of 25-30 %. For this reason, its use is only recommended in small replacement proportions or in concrete for non-structural use. This research was financed by COBASA Grupo Logístico S.L. The research was possible thanks to the collaboration of the company FERROATLANTICA, the department LADICIM (University of Cantabria) and the company ROCACERO.

The recovery of degraded marine coasts and the improvement of natural habitats are current issues of vital importance for the development of life, both marine and terrestrial. In this sense, the immersion of artificial reefs (ARs) in the marine environment is a way to stimulate the recovery of these damaged ecosystems. But it is necessary to have a multidisciplinary approach that analyses the materials, designs and construction process of artificial reefs in order to understand their true impact on the environment. For this reason, this paper presents the manufacture of artificial reefs by 3D printing, proposing designs with a combination of prismatic and random shapes, with different external overhangs as well as inner holes. For the definition of the artificial reef designs, criteria provided by marine biologists and the results obtained from a numerical simulation with ANSYS were taken into account, with which the stability of the artificial reefs on the seabed was analysed. Three dosages of cement mortars and three dosages of geopolymer mortars were studied as impression materials. The studies included determination of the rheological properties of the mortars, to define the printability, determination of the cost of the materials used, and determination of the mechanical strength and biological receptivity in prismatic specimens that were immersed in the sea for 3 months. To evaluate the environmental impact of the materials used in the production of the mortars, a Life Cycle Assessment (LCA) was carried out. In order to choose the mortars that encompassed the best properties studied, Multi-Criteria Decision Making (MCDM) was applied and the two best mortars were used for the manufacture of the artificial reefs. Finally, the advantages and disadvantages of the 3D printing process used were analysed. The results of the studies carried out in this research show that cement mortars have better characteristics for artificial reef applications using 3D printing, and that the technique applied for the manufacture of the artificial reefs allowed the digital models to be faithfully reproduced. This work has been co-financed by the European Regional Development Fund through the Interreg Atlantic Area Programme, under the project “Artificial Reef 3D Printing for Atlantic Area - 3DPARE” (EAPA_174/2016). Besides, the authors want to thank the following companies for their contribution: Solvay, for supplying the fly ash and sodium hydroxide; BASF, for providing the additives used in the research; Abonomar S.L., for providing the seashells sand; FCC ámbito, for providing the crushed recycled glass and Grupo Cementos Portland Valderribas (Mataporquera plant) for providing the cement.

Renewable energy sources are of great importance in protecting the environment by reducing greenhouse gas emissions and global warming. Recently, more efficient conversion technologies and different types of resources have been introduced to generate energy in a sustainable way. Biomass-to-energy systems need to be designed efficiently due to high volumes of raw material flows and transportation costs. This study proposes a novel integrated approach for the solution of biomass supply chain network design using artificial intelligence, geographic information systems, multi criteria decision making and mathematical modelling. First, the five-year forecasts of biomass raw materials including animal waste, agricultural residues, and municipal solid waste were made using support vector regression. Alternative biogas facility locations were determined spatially based on various criteria using geographic data and a decision-making technique. Then, considering annual net present value streams, the bioenergy system has been configured using a mixed integer linear programming model. The proposed methodology was applied on a real case in the city of Denizli, Turkey. The results showed that nine conversion facilities could be opened with 2000 kWh capacity each, and approximately 83.2% of net income could came from electricity sales, with the remainder from fertilizer sales. Furthermore, a sensitivity analysis was carried out to see the variations in model parameters such as biomass purchase cost, transportation cost, fertilizer sales prices and discount rate. It was found that the most dominant factor affecting net present value was fertilizer sales price, which was followed by discount rate. © 2023 Elsevier Ltd

Today, the increase in fuel consumption with the increasing number of vehicles has increased the efforts to make the engines more efficient. Diesel engines are subject to severe restrictions due to the emission problem. Although there is an emission problem, it is widely used especially in freight transportation. Many studies on diesel engines emission problems are made by academicians and manufacturers. In this sense, many studies have been carried out by adding nanomaterials to diesel fuel to reduce emissions in diesel engines. In this study, borax decahydrate as a fuel additive was studied in a diesel single-cylinder engine. Borax decahydrate was dissolved in 500 ml of methanol, 5 gr, 15 gr and 25 gr, and methanol was added to 10% diesel. To be 90% Diesel +10% Methanol (D90M10) 90% Diesel 10% Methanol + 1 gr Borax decahydrate (D90M10B1) 90% Diesel 10% Methanol + 3 gr Borax decahydrate (D90M10B2) 90% Diesel 10% Methanol + 5 gr Borax decahydrate (D90M10B3) four different fuel mixtures were tested. The experimental test measured in-cylinder pressure, heat release rate, fuel consumption, power, torque, exhaust gas temperature, smoke opacity, and exhaust emissions. Due to the rich oxygen content of borax decahydrate, it has been observed to reduce emissions, excluding NOx emissions. There was an increase in exhaust temperature, nitrogen oxides (NOx), and carbon dioxide (CO2) emissions and a serious decrease in HC, CO, brake-specific fuel consumption, and smoke opacity values. Studies should be expanded and enriched with different mixing ratios and usage patterns of boron-doped fuels in the future. © 2022 Elsevier Ltd

In this study, high-temperature resistances of oven- and microwave-cured pumice-, perlite-, fly ash- and burnt clay-based geopolymer were investigated and, the results were compared with that of the cement mortars. The effect of high-temperature on the matrix microstructure was investigated by SEM and changes in the crystal structure were monitored by XRD analyses. High-temperature experiments were carried out with 3 h exposure to 450, 600, 750 and 900 °C. The results indicated that both oven- and microwave-cured geopolymer mortars are more resistant to high-temperatures at all temperatures than their portland cement counterpart. However, it was also determined that pumice- and perlite-based mortars could not maintain their volumetric stability at elevated temperatures. © 2022 Elsevier Ltd, Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK: 119M950, The authors acknowledge the contribution of Ege University Central Research, Test and Analysis Laboratory for SEM analysis and Izmir Katip Celebi University Central Research Laboratory for XRD analysis., This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) [Grant No 119M950].

Many tank structures may not be stable during the construction phase, and this may lead to their becoming vulnerable to buckling under environmental loading conditions such as wind. Installing intermediate ring stiffeners of the proper size at the mid-height of the cylindrical shell may be the most effective way to stabilize these structures, especially under the effects of wind action. In the study, analytical and numerical studies were conducted to identify the required strength and stiffness for the intermediate ring stiffener. First, a new cylindrical shell-to- intermediate ring stiffness ratio was derived by considering curved beam and shell membrane theories. For strength criteria, the tributary height and the effect of shell- ring interaction on the internal forces and moments were examined by making use of Linear Analysis (LA) and Geometrically Nonlinear Analysis (GNA). The stress resultants developed in the intermediate ring stiffener were identified so that they could be used as strength criteria. For stiffness criteria, by considering the changes in the buckling resistance based on the developed stiffness ratio, an expression to compute the minumum intermediate ring stiffness was determined. In addition, Geometrically Nonlinear Analysis including Imperfections (GNIA) was also performed to examine the effect of the geometric imperfections on buckling strength of the steel tank with an intermediate ring stiffener, taking different imperfection amplitudes into account. The developed design equations in simple algebraic form can be utilized for the structural stability of cylindrical steel tanks during erection.

The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations. Ministry of Education Humanities and Social Sciences Youth Fund Project

Using soft computing methods could be of great interest in predicting the compressive strength of Ultra-High-Performance Fibre Reinforced Concrete (UHPFRC). Therefore, this study developed four soft computing techniques. The models are the Linear- relationship (LR), pure quadratic, M5P-tree (M5P), and artificial neural network (ANN). The models were trained and developed using 306 datasets comprising 11 input parameters, including the curing temperature (T), the water-to-cement ratio (w/c), silica fume (SF), cement content (C), fiber content (Fb), water (W), sand content (S), superplasticizer (SP), fiber aspect ratio (AR) and curing time (t). Experimental results were used and compared to the model performances to validate the developed models. The models were developed based on 192 training datasets, and the model's accuracy was checked using 41 testing datasets; the model's outcomes were validated using 32 experimental datasets. The results show a high prediction accuracy of the compressive strength of UHPFRC using ANN models. Based on the optimum developed ANN model, a closed-form equation is presented, proving to be a reliable and useful tool for researchers and, above all, for practicing engineers in compressive strength prediction.

Wake interactions between wind turbines have a great impact on the overall performance of a wind farm. In this work, a novel deep learning method, called Bilateral Convolutional Neural Network (BiCNN), is proposed and then employed to accurately model dynamic wind farm wakes based on flow field data generated by high-fidelity simulations. Different from the existing machine-learning-based dynamic wake models where dimensionality reduction is essential, the proposed BiCNN is designed to directly process the different types of inputs through a background path and a foreground path, thus avoiding the errors due to dimensionality reduction. Substantial results show that the developed machine learning based wake model can achieve accurate wake predictions in real time, i.e. it captures the spatial variations of the dynamic wakes similarly as high-fidelity wake models and runs as fast as low-fidelity static wake models. The overall prediction error of the developed model is 3.7% with respect to the freestream wind speed. Furthermore, the results for a test farm consisting of 25 turbines show that the developed model can predict the dynamic wind farm wakes within several seconds using

Reinforced concrete bond strength deterioration is one of the most serious problems in the construction industry. It is one of the most common factors impacting structural deterioration and the major cause of premature decadence of reinforced concrete structures. Therefore, developing an accurate model with the lowest variance and high reliability for the bond strength of corroded reinforced concrete is very important. The current work evaluates the efficiency of convolution-based ensemble learning algorithms. To address these issues, convolution-based ensemble learning models are developed using a database collected from the previous experimental studies of relative bond strength for corroded reinforced concrete. Seven parameters are considered as inputs, including bar diameter, the ratio of concrete cover to bar diameter, the ratio of the bar diameter to embedment length, transverse reinforcement ratio, yielding strength, concrete compressive strength and the corrosion level. Results indicate that the convolution-based integrated stacking model produces excellent predictions with the coefficient of determination, a-20 index, and mean square error values of 0.84, 0.75, and 0.022. Since machine learning based models are commonly black-box models, the Shapley Additive Explanations (SHAP) method is used to explicitly relate the predicted output to the inputs. Based on SHAP, the corrosion level, concrete compressive strength, transverse reinforcement ratio, and the concrete cover to bar diameter ratio are ranked among the most influential parameters on the bond strength of the corroded reinforced concrete.

As the structural response to a time and space dependent non-uniform temperature field is challenging to manage by code-based design, the behaviour of steel beams exposed to a travelling fire was simulated numerically in this paper. The finite element (FE) models for both thermal and mechanical analyses were validated by two benchmark tests and used to study the effect of uniform and non-uniform thermal exposures and different steel grades on the response of steel beams. The developed five-stage mechanism well characterized the response of the beams exposed to the travelling fire. For the beam in the elastic range, the heating-cooling cycles of gas temperatures induced cyclic axial forces, but the cyclic nature of structural responses was cushioned by material plasticity. For the beams stressed into the plastic range, the repetitions of cycles in axial response created residual deformations that induced catenary action in the beams at lower temperatures. The local heating of the critical sections made the beams more prone to a runaway failure than the uniform heating of the whole beam. Compared to the mild steel beams, the axial force response of the HSS beams showed higher axial compression forces and fluctuated more. The critical temperatures based on the deformation or strength criterion were consistent for the beams with the load ratio of 0.3. However, for designing the beam with the load ratio of 0.5, critical temperature of 350 ◦C or the strength criteria based on the proportional limit are recommended as the catenary action was activated at low temperatures. These recommendations can be used as a guide for practical design.

Vegetated roofs reduce temperature and heat flow fluctuations on the building's surface mitigating the urban heat island effects and improving other ecosystem services. The objectives of this work were to quantify thermal reduction and to evaluate the performance of vegetated-microcosm treatments during 15 months with different species composition and growth form combinations. Our results showed considerable attenuation of temperature through the whole system of extensive green roofs (EVRs) in both summer and winter periods. The EVRs decreased the outside temperature from 44.6 °C to 34.7 °C. Temperatures for the EVR showed a lower peak-to-valley-gap and better anti-interference performance during the day and along the year. At the same time, thermal insulation provided by soil and vegetation layers resulted in a negative heat flux (−40 W/m2) reducing the incoming heat flux during the day. Almost all treatments showed ≥90% of plant survival and ≥60% of coverage after the experimental period. Microcosm treatments with the highest diversity showed the best performance in both the short and long terms (particularly those with the native Eustachys distichophylla and the exotic Sedum spp.). Consequently, diverse plant arrangements are recommended when designing EVRs in semi-arid climates because they show a better performance in mitigating urban heat island effects by reducing temperature and heat flow fluctuations and also because they provide ecosystem services in urban environments., Fil: Robbiati,F.O. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Diversidad Biológica y Ecología; Argentina, Fil: Cáceres, N. Universidad Católica de Córdoba (UCC)-CONICET. Instituto de Investigaciones en Recursos Naturales y Sustentabilidad José Sánchez Labrador S. J. (IRNASUS). Laboratorio de Recursos Genéticos y Sustentabilidad Bioclimática; Argentina, Fil: Hick, Emmanuel Christian. Universidad Católica de Córdoba (UCC)-CONICET. Instituto de Investigaciones en Recursos Naturales y Sustentabilidad José Sánchez Labrador S. J. (IRNASUS). Laboratorio de Recursos Genéticos y Sustentabilidad Bioclimática; Argentin, Fil: Suárez, Mario Adolfo. Universidad Católica de Córdoba (UCC)-CONICET. Instituto de Investigaciones en Recursos Naturales y Sustentabilidad José Sánchez Labrador S. J. (IRNASUS). Laboratorio de Recursos Genéticos y Sustentabilidad Bioclimática; Argentina, Fil: Soto, S. Instituto de Floricultura (IF)-INTA; Argentina, Fil: Barea, G. Instituto de Ambiente, Hábitat y Energía (INAHE)-CONICET; Argentina, Fil: Matoff, Evangelina. nstituto Nacional de Tecnología Agropecuaria. Agencia de Extensión Rural; Argentina, Fil: Galetto, L. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Diversidad Biológica y Ecología; Argentina, Fil: Galetto, L. Universidad Nacional de Córdoba. Instituto Multidisciplinario de Biología Vegetal (IMBIV); Argentina, Fil: Imhof, Lelia. Universidad Católica de Córdoba (UCC)-CONICET. Instituto de Investigaciones en Recursos Naturales y Sustentabilidad José Sánchez Labrador S. J. (IRNASUS). Laboratorio de Recursos Genéticos y Sustentabilidad Bioclimática; Argentina

In this study, a model for the estimation of the compressive strength of concretes incorporating metakaolin is developed and parametrically evaluated, using soft computing techniques. Metakaolin is a component extensively employed in recent decades as a means to reduce the requirement for cement in concrete. For the proposed models, six parameters are accounted for as input data. These are the age at testing, the metakaolin percentage in relation to the total binder, the water-to-binder ratio, the percentage of superplasticizer, the binder to sand ratio and the coarse to fine aggregate ratio. For training and verification of the developed models a database of 867 experimental specimens has been compiled, following a broad survey of the relevant published literature. A robust evaluation process has been utilized for the selection of the optimum model, which manages to estimate the concrete compressive strength, accounting for metakaolin usage, with remarkable accuracy. Using the developed model, a number of diagrams is produced that reveal the highly non-linear influence of mix components to the resulting concrete compressive strength.

Proppant transport in underground fractures plays a key role in mitigating sand screen-out and enhancing the stimulated production for hydraulic fracturing. The effects of field pumping schedules, however, are not fully studied. We investigate the effect of slickwater-alternate-slurry injection on proppant transport at field-practical scales. A new hybrid approach is proposed to directly connect experimental studies with field operations, which consists of observation experiments, calculations, and deep learning (DL) workflow. The experiments reveal that the alternate injection induces the unexpected proppant ridge. The modified calculations (considering the ridge height) are proposed to extract features for training the DL algorithm. The workflow predicts the downhole pressure (mainly governed by proppant injection) for error analyses. Approximately 20.2% of the error is eliminated by considering the proppant ridge, thus demonstrating its effect on proppant injection. The predictions are significantly improved in early and late periods of fracturing operations when the fracture is initially created and highly filled. The sensitivity analysis suggests that the pump rate may dominate the ridge height compared with other hydraulic parameters. The study of proppant ridge complements the mechanisms of proppant transport, which is essential for controlling fracturing pressure and boosting the proppant injection.

The world is changing, and consequently so are policies on the use of natural resources. One of the most convenient ways to reduce the consumption of natural aggregates in the production of more sustainable construction materials is the use of recovered industrial by-products. In this study, concretes are designed using siderurgical aggregates from electric arc furnaces, taking advantage of their high density to use them as radiation shielding concrete. To verify the suitability of these aggregates, four concrete mixes were designed with different aggregates: limestone, siderurgical magnetite aggregates (the most commonly used in the nuclear field). The comparison of the different mixes was carried out focusing on the physical?mechanical properties in the field of ionizing radiation shielding (gamma radiation and neutron shielding) by means of simulations. In addition, an analysis was performed to establish how the w/c ratio and the amount of CEM affect shielding properties. In terms of linear attenuation coefficient and neutron transmission rate, the concrete with siderurgical aggregates shows intermediate capability in comparison with the limestone aggregate and magnetite concrete. The increase in the amount of cement and the w/c ratio caused a decrease in the linear attenuation coefficient and a reduction in the neutron transmission rate, but the variation in the w/c ratio did not have a significant impact on the neutron transmission rate. This research was co-financed by the European Regional Development Fund (ERDF) and the Ministry of Economy, Industry and Competitiveness (MINECO) within the framework of the project RTC2016-5637-3. The research has been possible thanks to the collaboration of the company INGECID, the department LADICIM (University of Cantabria) the Modern Physics Department of the University of Cantabria and the companies ROCACERO and SIDENOR.

A self-cleaning nanostructured TiO2 coating has demonstrated the capacity to mitigate undesired effects from air pollution. Not only it reduces the deterioration of building materials but may also prevent certain pollution-related human health problems. In this study, mesoporous TiO2/SiO2 photocatalysts were synthesized in order to produce self-cleaning and long-lasting coatings that meet the necessary requirements for outdoor applications. The synthesized products were sprayed on concrete substrates and their self-cleaning and air depolluting capabilities were evaluated. The former one as a function of methylene blue (MB) and soot degradation and the latter, according to nitrogen oxides reduction. The coatings proved to have high photocatalytic activity, and their efficiency was enhanced as TiO2 loadings were increased. Thus, after the first 60 min of their irradiation by UV–vis light, the photocatalysts ST1 and S4T had removed 79% and 95% of the MB, respectively. These coatings presented particulate surfaces that provided more surface area and porosity, which are key factors for a high photocatalytic activity. Moreover, the same samples after 104 h of irradiation exhibited 38% and 49% conversion of total NO, respectively. While E503, a commercially available photocatalyst, produced coating cracked surfaces and a total MB degradation of just 50% after 60 min of irradiation as well as 35% of NO conversion after 104 h of irradiation. The TiO2/SiO2 coatings’ photocatalytic efficacy remained practically invariable after four months of exposure to real-life conditions and three MB degradation cycles. After the outdoor durability tests, the coated surfaces exhibited a practically unchanged structure, which confirms their long-lasting efficiency. © 2022 The Authors, This work has been supported by the Spanish Government MAT2017-84228-R (MINECO/AEI//FEDER, UE) and PID2020- 115843RB-I00/AEI/10.13039/501100011033 . This work has been co-financed by the European Union under the 2014–2020 ERDF Operational Programme and by the Department of Economic Transformation, Industry, Knowledge, and Universities of the Regional Government of Andalusia . Project reference: FEDER-UCA18-106613 .

Recently, the use of fibers has become an attractive option to be implemented as reinforcement in Asphalt Concrete (AC) mixtures. Nonetheless, few studies have been carried out to evaluate the recyclability potential of AC mixtures incorporating fibers. In this study, the reinforcing effect of polyacrylonitrile (PAN) fibers in AC mixtures is investigated. Air voids, Marshall stability, indirect tensile strength (ITS), moisture sensitivity, compactability, rutting, stiffness, and fatigue were the tests taken into consideration. In addition, bituminous mixtures manufactured with higher quantities of artificial reclaimed asphalt pavement containing PAN fibers (PANRAP) were evaluated experimentally. The results indicate that PAN fibers significantly increased the resistance to permanent deformation of the AC mixture. Improvements in ITS, moisture sensitivity and stiffness keeping the same fatigue life were also observed. In addition, a suitable performance was found in mixtures incorporating PANRAP in relation to control mix and remarkable increases in ITS, rutting, and stiffness were noted. The present investigation provides technical evidence of recycling AC mixtures with fibers up to 50% without the presence of rejuvenators. This work has received funding from the CEDR Transnational Road Research Program - call 2017 under the contract N. 867481, ‘‘Fostering the implementation of fiber-reinforced asphalt mixtures by ensuring its safe, optimized and cost-efficient use (FIBRA)”. Scientific support from the consortium partners University of Cantabria (Spain), Empa (Switzerland), Technical University of Braunschweig (Germany), BAM (Netherlands) SINTEF and Veidekke (Norway) is gratefully acknowledged.

Modelling the tensile behaviour of Fabric Reinforced Cementitious Matrix (FRCM) is not a straightforward task due to the inner complexity of the mechanics of this kind of composite materials. In fact, after that the matrix is cracked, the compatibility between the fibre and the surrounding mortar is lost and the system behaves as two separate elements connected by a brittle interface. For this reason, several research studies proposed computational approaches for evaluating the tensile behaviour of FRCM composites, usually referring to brick-based 3D Finite Element Models (FEM) or to complex numerical procedures. This paper shows the formulation of a simplified coupled truss element for modelling the tensile behaviour of FRCM composites. The proposed element includes the interface slip between fibre and matrix and the brittle failure of the fabric and allows to describe the response of the system between the cracks in closed form. The proposed element is also adopted for assessing the tensile constitutive response of FRCMs through a simplified assembly procedure, proving to be reliable and computationally efficient.

This work provides a complete exergy analysis of municipal solid waste incineration process. The work was based on a previous study, and was enriched considering the possibility to increase the O2 %mol in the combustion air, up to oxy-combustion conditions. Two configurations have been considered, with and without flue gas recirculation, and the environmental aspects of oxy-combustion were taken into account, as well as its exergetic cost. The flue gas was used in a boiler for high pressure steam production, expanded in three turbines for power generation. The exergy analysis allowed to identify the process units characterized by major irreversibility and exergy loss as waste. The results showed that the flue gas recirculation led to an exergy efficiency increase of the whole process of about 3% (from 31.1% up to 34% at adiabatic flame temperature equal to 1200 °C). The O2 %mol increase in the combustion air allowed to reduce the flue gas flowrate, leading to environmental benefits. Oxygen-enriched air adoption led to limited exergetic improvements, due to the exergy cost of the air separation unit. The specific energy generation of the plant increased at fixed combustion chamber temperature adopting flue gas recirculation.

This study focuses on the mechanical behaviour of asphalt mastic composed of filler particles bonded with an asphalt bitumens. Asphalt mastics are viscoelastic composite materials widely used in the construction of pavement layers. The mechanical properties and the influence of the fillers on the filler/bitumen (f/b) matrix is one of the main areas of current research. In particular, the elastic determination of fillers for mechanical testing in asphalt mastic is relevant to understand permanent deformation caused by temperature variations caused by seasonal changes and vehicular traffic loads. In this sense, this research proposes a new methodology for rheological characterization of the elastic properties of the filler ?2 and elastic-viscous properties of the asphalt bitumen, ?1 and ?, respectively, complementing the existing designs of asphalt mixture. The proposed methodology allows for identification of the influence of non-conventional fillers in the behavior of the asphalt mastic for the different recovery cycles of the Multiple Stress Creep Recovery (MSCR) and determination of new rheological parameters for the compression of the recovery phenomena and the elastic capacity of the type of filler and weight of the base bitumen. The results obtained show a greater adjustment to the experimental curves in determining the elastic modulus in each cycle for the hydrated lime and fly ash fillers with different filler/bitumen ratios. In particular, the proposed model for bituminous mastics achieves a strong fit with the experimental curves by empirically reducing the quadratic error (R2 = 0.99) and managing to differentiate the elastic capacity ?2 of each filler and its effect with increasing concentration. For example, it establishes that the Hydrated lime filler (HL) acquires an average Young's modulus of 0.005 MPa, being 99.31% more elastic than Fly ash filler (FA) for a load of 3.2 kPa at a 1.25f/b ratio. In addition, the new model can be used to modify bitumen properties to design optimized and stronger asphalt mixtures

The disposal of waste rubber products is a significant issue globally and it poses a serious threat to the environment creating long-term ecological problems. The possible use of rubber aggregates in concrete is a valid alternative to obtain a green construction material. This paper develops probabilistic models for the concrete Strength Reduction Factor (SRF) and Elastic modulus Reduction Factor (ERF) accounting for the amount of rubber aggregates as well as several variables defining the mix design. Three different rubber aggregate types are considered, namely fine and coarse replaced individually and fine and coarse replaced simultaneously. A total of 644 sets of concrete compressive strength and elastic modulus tests are collected from the literature for the model calibration. The paper presents a discussion about the formulation of the models, variance stabilizing transformations, model calibration, and model selection. Once formulated, we calibrate the probabilistic models using data from experimental tests. The unknown model parameters are estimated using a Bayesian approach implemented using A Markov Chain Monte Carlo (MCMC) simulation method. The proposed probabilistic models are used to evaluate the reliability of rubberized concrete structures. As an illustration, the proposed probabilistic models are used to estimate the reliability of an example column made of rubberized concrete under compressive axial force and of an example one-way slab made of rubberized concrete under distributed load.

The increase in industrial activity and societal demand has made the reuse and recovery of industrial waste and by-products a topic of global importance. New technologies focused on the reuse of these materials open up the possibility of promoting a sustainable circular economy in the industrial sector. Ladle furnace slag (LFS) is an industrial waste generated during steel refining, through a process of deoxidation and desulfurization of the material while it is in a liquid state in its second refining stage. This process generates large quantities of LFS without being used on a large scale, and most of it is destined for stockpile fields, producing an environmental and economic impact. The present research is based on the incorporation of Hydrated Ladle Furnace Slag (LFSh) into asphalt mastics to evaluate its viscoelastic behaviour using the Dynamic Shear Rheometer test (DSR-test). The incorporation of this industrial by-product generates an increased stiffness of the asphalt mastic, compared to a conventional mastic made with limestone. This increase in stiffness is greater in large dosages of LFSh filler, causing an inferior performance to limestone mastic at low temperatures in relation to what was demonstrated in the Linear Amplitude Sweep test (LAS) and Binder Yield Energy Test (BYET). The results obtained in the Multiple Stress Creep Recovery test (MSCR) show that the incorporation of LFSh filler is appropriate for warm conditions. Furthermore, the filler/bitumen ratio of 0,75 provides an increase in recoverability (R) of 24.17% over limestone mastic asphalt at a temperature of 70º C and a load of 3.2 kPa, and a significant loss of lower integrity at low temperatures (25º C). This work was supported by the National Research and Development Agency (ANID) of Chile [FONDECYT Regular N°1201029]

Gas-based power plants have attracted more attention in providing electrical energy worldwide because of their lower costs and air pollution. In addition, the use of multi-carrier energy systems has several advantages, such as sustainability benefits and improving performance in supplying the energy demand. This study aims to optimize the total operation cost of multi-carrier energy systems considering the uncertain parameters. The storage technology and consumption side assist the operator in achieving lower costs based on conceptions of demand response programs. Therefore, this study presents a comprehensive mathematical model for the coordinated operation of integrated multi-carrier energy systems while the operational constraints of both gas and power networks are considered. Furthermore, this paper utilizes a new uncertainty modeling method based on Hong's two-point estimate method for addressing the uncertainties of load consumption and wind generation. The proposed model is applied to a gas and power multi-carrier energy system through four case studies. The results affirm the high performance of the presented method and investigate the influence of demand response programs in both sides of energy carriers.

A review on the reference values of the acoustical parameters that have the greatest influence on students' performance at different ages has been completed in this study. Published studies from 2002 to 2020 were summarized, which focus on testing learning attainments and cognitive skills, speech intelligibility, and subjective perceptions under different classroom acoustic conditions. Only 38 papers out of the 56 containing empirical findings on the influence of acoustical parameters on students’ performance were considered, as the remaining 18 lacked ecological validity or did not respond to the selection criteria. Studies were only included if they considered normal hearing subjects and typical lesson settings provided in classrooms without an amplification system. Thus, the studies selected involved subjects between 5 and 40 years old. The values of the acoustical parameters that led to better or worse learning performance were tabulated and the distribution of occurrences was created. The median and interquartile range for the distribution of occurrences were used to describe the central tendency and dispersion and analyzed considering two different age groups. The results obtained were used to develop classroom acoustic guidelines for better learning performance for students under or over 12 years of age, and identified the thresholds that lead to worse performances.

Energy industries and governments consider ocean wave power a promising renewable energy source for reaching the net-zero plan by 2050 and restricting the rise in global temperatures. It expects the potential global ocean wave power production to be around 337 GW annually. Although wave energy forecasting critically enables economic dispatch, optimal power system management, and the integration of wave energy into power grids, the forecasting process is complicated by the stochastic, intermittent, and non-stationary nature of waves. Thus, this paper proposes a novel hybrid forecasting model comprising an adaptive decomposition-based method (Nelder-Mead variational mode decomposition) and a convolutional neural network featuring bi-directional long short-term memory. Furthermore, we propose a fast and effective optimiser to adjust the hybrid model's hyper-parameters and evaluate the decomposition technique's role in increasing the accuracy of wave energy flux predictions considering a forecasting period of 6 h. With regard to assessing the proposed model's effectiveness, we use a real wave dataset from a buoy positioned off Favignana Island in the Mediterranean Sea and compare the proposed model with six well-known forecasting methods and five hybrid deep-learning models. According to our findings, the proposed model significantly outperforms existing approaches over extended time periods and compared with the bi-directional long short-term memory, the developed adaptive decomposition method, and new hyper-parameters tuner improve the prediction accuracy at 45% and 13.6%, respectively.

Wave energy technologies have the potential to play a significant role in the supply of renewable energy worldwide. One of the most promising designs for wave energy converters (WECs) are fully submerged buoys. In this paper, we explore the optimisation of WEC arrays consisting of three-tether buoys. Such arrays can be optimised for total energy output by adjusting the relative positions of buoys in a wave farm. As there are complex hydrodynamic interactions among WECs, the evaluation of each parameter setting is computationally expensive and thus limits the feasible number of full model evaluations that can be made. Furthermore, these WEC interactions make up a non-convex, multi-modal (with multiple local-optima), continuous and constrained optimisation problem. This problem is challenging to solve using optimisation methods. To tackle the challenge of optimising the positions of WECs in a wave farm, we propose a novel multi-swarm cooperative co-evolution algorithm which consists of three meta-heuristics: the multi verse optimiser (MVO) algorithm, the equilibrium optimisation (EO) method, and the moth flame optimisation (MFO) approach with a backtracking strategy, we introduce a fast, effective new surrogate model to speed up the process of optimisation. To assess the effectiveness of our proposed approach, 11 state-of-the-art bio-inspired algorithms and three recent hybrid heuristic techniques were compared in six real wave situations located on the coasts of Australia, with two wave farm sizes (four and nine WECs). The experimental study presented in this paper shows that our hybrid cooperative framework exhibited the best performance in terms of the quality of obtained solutions, computational efficiency, and convergence speed compared with other 14 state-of-the-art meta-heuristics. Furthermore, we found that the power output of the best-found 9-buoy arrangements were higher than that of perpendicular layouts at at 4.15%, 3.29%, 3.62%, 9.2%, 5.74%, and 2.43% for the Perth, Adelaide, Sydney, Tasmania, Brisbane, and Darwin wave sites, respectively. Our investigations reveal that the best-found arrangement at the Tasmania wave site was able to absorb the highest level of wave power relative to the other locations.

The EU has a comprehensive legislation to facilitate the energy transition towards a low carbon energy system and achieve the EU’s Paris Agreement commitments for reducing greenhouse gas emissions. The European Green Deal is an integral part of the EU strategy for a sustainable and climate neutral economy by 2050. The decarbonisation of the power generation is essential to achieve the goal of decarbonising the energy and transport sectors. This paper presents a study conducted to quantify the carbon emissions associated to the production of electricity produced and used in European countries, based on a comprehensive methodology developed for this purpose. A spreadsheet model has been developed that considers the various sources for electricity generation, the type of plants, conversion efficiencies, upstream emissions and emissions from power plant construction, as well as the electricity trade. The results show the greenhouse gas emissions from the production and use of electricity in all European countries, revealing significant variations between countries. The carbon intensity of electricity shows a clear reduction trend since 1990, for most of the European countries. In the European Union, carbon intensity of electricity used at low voltage degreased from 641 gCO2eq/kWh in 1990 to 334 gCO2eq/kWh in 2019, and this trend is expected to continue in the coming years.

The literature has been increasingly examining the existence of possible compatibility or conflict hypotheses between biofuels and food security in recent years. While current research outputs do not provide a consensus, the new evidence can guide sustainable development policies. In this context, this paper investigates the co-movements between fuel ethanol production and corn prices for the US employing oil production, population, and real exchange rate control variables via the Morlet wavelet analysis from 1990:m1 to 2021:m4. The results of the analysis provide empirical evidence for the dynamics of the relationship between ethanol production and corn prices in the short and long term. However, the striking output of this paper is that increases in corn prices have followed increases in fuel ethanol production in the US markets since 2010. Especially in the long-term (from 2010:m3 to 2019:m12), the increase in ethanol production caused an increase in corn prices. From a sustainable development perspective, this paper points to the existence of a conflict between ethanol production and corn prices in the US over the past decade. © 2022 Elsevier Ltd

Assessment of performance of turbofan engine with different design parameters is crucial for meeting the performance requirements by considering each key components of the engine. To comprehend influences of component efficiencies to mitigate environmental effect from turbofans has been hot topics in aviation field recently. In this study, firstly, impacts of polytropic efficiencies of fan, compressor and turbine as well as pressure ratio of combustor (CPR) on several turbofan performance are dealt with at several flight conditions. Secondly, it is tried to show difference of performance metrics under ideal and real conditions. The discrepancy between performance parameters computed at ideal and real cases gets relatively high. Namely, at take-off condition, the difference between ideal and real specific fuel consumption is computed as 29.12% whereas it is found as 28.37% at cruise condition, which shows that considering the system as ideal makes the computations inappropriate for performance analysis. Moreover, performance parameters of turbofan is more sensitive to compressor efficiency compared with turbine. As the polytropic efficiencies of fan and compressor are close to highest, net thrust of the engine develops from 109.05 kN (baseline) to 124.71 kN at take-off while it increases from 26.36 kN (baseline) to 29.27 kN at cruise condition. With effect of the elevated pressure ratio of combustor and efficiency of turbine, thrust of the engine increases to 118.23 kN at take off and to 27.84 kN at cruise condition. Finally, as Mach number increases, the difference between ideal and real performance values sharply increases. Therefore, when analyzing on turbofan engines, the assumptions should be minimum as possible as, otherwise the findings make the engineers to misguide for system optimization. Besides, these outcomes show that if the components with higher polytropic efficiency can be obtained, overall efficiency of turbofan, thereby environmental sustainability could be elevated to upper level compared with baseline.