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The objective was to investigate the utility of cottonseed oil (CSO) as a raw material for the synthesis of CSO water-based alkyd resin. The synthesis involved the polymerization of CSO, trimethylolpropane, phthalic anhydride (PA) and trimellitic anhydride (TMA). The prepared resin coating material was subsequently applied to the surface of steel structure material.

This study aimed to synthesize water-based alkyd resins using CSO. Therefore, the alkyd resin was introduced with TMA containing carboxyl groups and neutralized with triethylamine (TEA) to form a water-soluble salt. Then, the esterification kinetics of CSO water-based alkyd resin were investigated, and finally, the basic properties of CSO water-based alkyd resin coating were evaluated.

It was demonstrated that CSO water-based alkyd resin exhibited excellent water solubility and that the esterification kinetic of the synthesis reaction could be described by a second-order reaction. The coating properties of the material were investigated and found to have good basic properties, with 40% resin addition having the best corrosion resistance. Consequently, it could be effectively applied to the surface of steel structural materials.

This study not only met the requirement of environmentally friendly development but also expanded the application of CSO through the synthesis of CSO water-based alkyd resin via alcoholysis. Compared to fatty acid process, the alcoholysis reduced the need for fatty acid pre-extraction, simplifying the alkyd resin synthesis process. Thus, economic costs are effectively reduced.

The purpose of this paper is to propose a new combined finite-discrete element method (FDEM) to analyze the mechanical properties, failure behavior and slope stability of soil rock mixtures (SRM), in which the rocks within the SRM model have shape randomness, size randomness and spatial distribution randomness.

Based on the modeling method of heterogeneous rocks, the SRM numerical model can be built and by adjusting the boundary between soil and rock, an SRM numerical model with any rock content can be obtained. The reliability and robustness of the new modeling method can be verified by uniaxial compression simulation. In addition, this paper investigates the effects of rock topology, rock content, slope height and slope inclination on the stability of SRM slopes.

Investigations of the influences of rock content, slope height and slope inclination of SRM slopes showed that the slope height had little effect on the failure mode. The influences of rock content and slope inclination on the slope failure mode were significant. With increasing rock content and slope dip angle, SRM slopes gradually transitioned from a single shear failure mode to a multi-shear fracture failure mode, and shear fractures showed irregular and bifurcated characteristics in which the cut-off values of rock content and slope inclination were 20% and 80°, respectively.

This paper proposed a new modeling method for SRMs based on FDEM, with rocks having random shapes, sizes and spatial distributions.

The application of reinforcing old bridges by adding external prestressed steel bundles is becoming more and more widespread. However, the long-term safety performance test of the strengthening method is rarely carried out. In this paper, the bearing capacity of a 420 m prestressed concrete (PC) continuous girder bridge after five years of strengthening is analyzed.

The bridge model of the bridge structure and strengthening scheme is established by the finite element software of the bridge. The theoretical load-bearing capacity of the bridge under the latest standard load grade is obtained by finite element analysis. The actual bearing capacity of the bridge is obtained by field test. Through the comparative analysis of theory and practice, the health state of the bridge after five years of reinforced operation is judged. The damage to the overall stiffness and external prestressing of the bridge is also analyzed.

The results of deflection and strain show that the stiffness and strength of the secondary side span and the middle span decrease slightly, and the maximum reduction of bearing capacity is 4.5%. The static stiffness of the whole bridge decreases as a result of cracks, and the maximum decrease is 21%. In the past five years, the relaxation loss of the external prestressing of the bridge is 3.31–3.97%, which is the main reason for the decrease in bearing capacity.

Through the joint analysis of the bridge stiffness and the loss of external prestressing, the strengthening condition of the bridge after five years of operation is effectively analyzed. The strengthening effect of the external prestressed steel beam strengthening method is analyzed, which can provide a reference for similar bridge strengthening.

This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.