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The built environment significantly impacts the health of individuals and populations in various ways. The health and durability of the built environment are intertwined with availability ofnaturally occurring and man-made resources and their supply chains. Therefore, resource con servation is a key to ensure sustainability of built environments. Many industrial wastes can be turned into valuable resources for reuse in construction of the built environment. For instance, biowaste (woody/ leafy biomass and animal waste) have been used to make construction adhesives (Fini et al., 2011), some urban wastes have been used in road construction (Poulikakos et al., 2017; Schmidt et al., 2021), end of life plastics and polymers have made their way to roadway construction, bio-oils and algae harvested from wastewater treatment plants has been used to make antiaging for outdoor building elements to mitigate UV aging (Kabir et al., 2021); sulfur has been used as an extender in asphalt and recycled mineral powders such as silica and alumina have been used to increase strength and durability against acidic compounds (Fini et al., 2019). These are just a few examples of recycling venues with beneficial uses in the built environment.
The construction and operation of the built environment and the traffic that it attracts or facilitates significantly contribute to the emis sion of greenhouse gasses (GHG) and cause air pollution. The direct and indirect impacts of GHG and air pollutants on the environment and so cieties have been weil established. The built environment can be used as a powerful platform not only for recycling and resource conservation but also to remove near-ground gaseous contaminants. This can be done via tailored design and engineering of adsorptive construction materials via recycling of waste materials. For instance, advanced sorbent systems can be made for removing C02, H2S, and formaldehyde from air. This re quires tailored sorbent design, topology optimization, and catalytic conversion of collected gaseous compounds to name a few.
This special issue covers innovative materials, methods, and man agement practices which aim to simultaneously address durability ofthe built environment, air quality, resource conservation, and supply chain resilience. Such innovative materials, methods, and management prac tices will transform the built environment into not only an active contributor to no waste, no pollution for healthy environment, but also a medium that converts the waste and pollution into beneficial products for use in the built environment, thereby promoting resource conser vation. Followings are examples of topics that the special issue is interested in:
• Venuses to advance resource conservation specifically via novel ap proaches in the built environment.
• Innovative construction materials for passive or active adsorption of harmful gaseous emissions to conserve air, energy, and water.
• Advanced materials, methods, and management practices to pro mote well-being of the built environment.
• Smart buildings to promote resource conservation.
• Research convergence in the built environment for zero waste, zero pollution economy.
In this work, engineered recycled mineral admixtures were obtained from four different industrial residues: basic oxygen furnace slag, iron ore tailings, quartz mining tailings and quartzite mining tailings.
The grinding performance was evaluated in two different programs and the characterization included chemical and mineralogical composition, particle morphology, and physical properties. Performance evaluations were carried out in blended pastes and mortars, including flow properties, hydration kinetics, soundness, pozzolanic activity, and compressive strength. Coarser-than-cement admixtures allowed better flow performance, greater dimensional stability and more economical production, while finer-thancementn admixtures improved mechanical performance by both filler effect and cementing activity.
Proof load testing may be performed to confirm the reliability of the bridge for an existing classification or to prove the reliability for a higher classification. In this paper, a probabilistic decision analysis approach is applied to the scenario for the evaluation of target proof load in the situation where information on the bridge resistance model is lacking. In this case, the resistance model is established by proof loading and taking very basic prior knowledge into account. The decision scenario is modelled in the context of the proof load test planner who shall choose the required load level for assessment of a bridge. The choice of the load level depends on the risks due to the testing and the expected benefit gain from the test. Information acquired about the loading response from monitoring during the proof load testing is modelled by taking basis in the model uncertainty formulation. The optimal proof load level for classification of a single lane, simply supported bridge of 8m span subjected to live load from very heavy (gross weight > 80 tons) transport vehicles was calculated. The optimal proof load level was identified as leading to a positive expected benefit gain to the decision maker while also satisfying target reliability criteria for remaining service life. The analysis was performed for the evaluation of bridge performance with respect to five classifications of very heavy transport vehicles with different vehicle weights and configurations.
This study shows remarkably different features between the oxidation of secondary and primary C₃-C₅ alcohols. The oxidation of primary alcohols is controlled by the oxidative removal of blocking adsorbates, such as CO, formed after the dissociative adsorption of alcohol molecules. Conversely, secondary alcohols do not undergo dissociative adsorption and therefore their oxidation is purely controlled by the energetics of the elementary reaction steps. In this respect, a different role of ruthenium is revealed for the electrooxidation of primary and secondary alcohols on bimetallic platinum-ruthenium catalysts. Ruthenium enhances the oxidation of primary alcohols via the established bifunctional mechanism, in which the adsorption of (hydr)oxide species that are necessary to remove the blocking adsorbates is favored. In contrast, the oxidation of secondary alcohols is enhanced by the Ru-assisted stabilization of an O-bound intermediate that is involved in the potential-limiting step. This alternative pathway enables the oxidation of secondary alcohols close to the equilibrium potential.
The flammable hydrogen-blended methane–air and natural gas–air mixtures raise specific safety and environmental issues in the industry and transportation; therefore, their explosion characteristics such as the explosion limits, explosion pressures, and rates of pressure rise have significant importance from a safety point of view. At the same time, the laminar burning velocities are the most useful parameters for practical applications and in basic studies for the validation of reaction mechanisms and modeling turbulent combustion. In the present study, an experimental and numerical study of the effect of hydrogen addition on the laminar burning velocity (LBV) of methane–air and natural gas–air mixtures was conducted, using mixtures with equivalence ratios within 0.90 and 1.30 and various hydrogen fractions rH within 0.0 and 0.5. The experiments were performed in a 14 L spherical vessel with central ignition at ambient initial conditions. The LBVs were calculated from p(t) data, determined in accordance with EN 15967, by using only the early stage of flame propagation. The results show that hydrogen addition determines an increase in LBV for all examined binary flammable mixtures. The LBV variation versus the fraction of added hydrogen, rH, follows a linear trend only at moderate hydrogen fractions. The further increase in rH results in a stronger variation in LBV, as shown by both experimental and computed LBVs. Hydrogen addition significantly changes the thermal diffusivity of flammable CH4–air or NG–air mixtures, the rate of heat release, and the concentration of active radical species in the flame front and contribute, thus, to LBV variation.
Performance of calcium phosphate cements in the augmentation of sheep vertebrae - An ex vivo study
(2021)
Oil-based calcium phosphate cement (Paste-CPC) shows not only prolonged shelf life and injection times, but also improved cohesion and reproducibility during application, while retaining the advantages of fast setting, mechanical strength, and biocompatibility. In addition, poly(L-lactideco-glycolide) (PLGA) fiber reinforcement may decrease the risk for local extrusion. Bone defects (diameter 5 mm; depth 15 mm) generated ex vivo in lumbar (L) spines of female Merino sheep (2–4 years) were augmented using: (i) water-based CPC with 10% PLGA fiber reinforcement (L3); (ii) Paste-CPC (L4); or (iii) clinically established polymethylmethacrylate (PMMA) bone cement (L5). Untouched (L1) and empty vertebrae (L2) served as controls. Cement performance was analyzed using micro-computed tomography, histology, and biomechanical testing. Extrusion was comparable for Paste-CPC(-PLGA) and PMMA, but significantly lower for CPC + PLGA. Compressive strength and Young’s modulus were similar for Paste-CPC and PMMA, but significantly higher compared to those for empty defects and/or CPC + PLGA. Expectedly, all experimental groups showed significantly or numerically lower compressive strength and Young’s modulus than those of untouched controls. Ready-to-use Paste-CPC demonstrates a performance similar to that of PMMA, but improved biomechanics compared to those of water-based CPC + PLGA, expanding the therapeutic arsenal for bone defects. O, significantly lower extrusion of CPC + PLGA fibers into adjacent lumbar spongiosa may help to reduce the risk of local extrusion in spinal surgery.
Tribological properties of ultrahigh-molecular weight polyethylene (UHMWPE) and cross-linked polyethylene (XLPE) were studied in two different wear modes. Firstly, reciprocating sliding wear studies under non-conformal contact investigated the effects of counterface surface roughness (polished, lapped and ground) of Ti6Al4V on the friction and wear of the polyethylenes. Secondly, two-body abrasive wear studies in conformal contact against different abrasive grit size papers were also carried out to ascertain the wear sensitivity of the polyethylenes under these adverse conditions. Wear mechanisms were studied using optical and scanning electron micrographs. The results of the reciprocating sliding wear studies showed that surface roughness of the counterface influenced friction and wear characteristics although no correlation was found between the coefficient of friction and specific wear rate. XLPE demonstrated wear sensitivity, particularly under severe abrasive wear condition. The results indicated that the performance of the polyethylenes greatly depends upon the tribological system under which it is operating.
Compared with most common construction materials, fiber reinforced cementitious materials are well known to exhibit better physical, working and mechanical properties. In this study, three fibers were selected: polypropylene fiber (PPF) and polyvinyl alcohol fiber (PVAF), which represented synthetic fibers, and sisal fiber (SF), which represented natural fibers. Effects of these fibers on the flowability, rheological properties, and adsorption behavior of the cement paste with polycarboxylate superplasticizer (PCE) were investigated. Furthermore, the above experimental results were verified by measuring the contact angle of the fiber with water and PCE solution and the apparent morphology of the fiber. Results revealed that the addition of fibers significantly reduces the fluidity of the cement paste, while the yield stress and plastic viscosity of the cement paste increase with the addition of fibers. From the contact angle and scanning electron microscope, the surface of SF was relatively rough, and the contact angle of SF with water or PCE solution was the smallest. It can be concluded that the plant fiber has a significant influence on the fluidity and rheology of cement paste.
Understanding on how a machine learning model interprets data is a crucial step to verify its reliability and avoid overfitting. While the focus of the scientific community is nowadays orientated towards deep learning approaches, which are considered as black box approaches, this work presents a toolbox that is based on complementary methods of feature extraction and selection, where the classification decisions of the model are transparent and can be physically interpreted. On the example of guided wave benchmark data from the open guided waves platform, where delamination defects were simulated at multiple positions on a carbon fiber reinforced plastic plate under varying temperature conditions, the authors could identify suitable frequencies for further investigations and experiments. Furthermore, the authors presented a realistic validation scenario which ensures that the machine learning model learns global damage characteristics rather than position specific characteristics.