No abstract

The operation and maintenance (O&M) of intelligent building information model (IBIM), as an important aspect of modern building informatization, plays a critical role in the construction of smart cities and the renovation of modern buildings. Due to the complex structure and sheer size of IBIM data, the O&M system of IBIM faces a huge workload and a high cost. Based on cloud computing, this paper proposes an O&M strategy for IBIM data, which meets the needs for stable management of massive data, enables three-dimensional (3D) collaborative visualization of building information model (BIM), improves the efficiency of data storage, scheduling, and O&M. Firstly, the basic structure of IBIM data was standardized according to The Industry Foundation Classes (IFC) (ISO 16739-1:2018). Then, the features were sampled from the standardized IBIM cloud data. After that, the storage data were subject to routing, coding, matching feature compression, and adaptive attribute clustering. On this basis, an optimization model was established for the storage structure of IBIM cloud data. Finally, a batch feature extraction method was designed for 3D structure distribution of job-based 3D cloud storage model. The proposed strategy was proved effective through experiments. The research results provide a reference for applying 3D cloud storage model in other fields.

Fire in a tunnel will deteriorate the mechanical properties of the tunnel. For fabricated tunnels formed by splicing prefabricated components through joints, under the high temperature of a fire, the rapid degradation of the bearing capacity of the joints can easily lead to tunnel damage. In this study, a new type of joint (bolt-pin joints (BPJ)) for prefabricated frame tunnels is proposed. To investigate the fire resistance of the new joint and the other three fabricated frame tunnel joints (including mortise joints (MJ), bolt-mortise joints (BMJ), and pin joints (PJ)), a three-dimensional solid model of four types of fabricated frame tunnel joints is established using the finite element calculation software ABAQUS. According to the standard European HC curve, the heat transfer characteristics of the joint model are analyzed, the temperature distribution law of the joint under fire is studied, and the flexural bearing performance and deformation characteristics of the joint before and after the fire are discussed, as well as the influence of the initial axial force on the flexural bearing capacity and the opening of the joint under fire. The analysis result shows that the vertical peak load of the BPJ is higher than that of the other three joints at room temperature. Under the combined action of the pin and bolts and the tongue groove, the vertical peak load of the joints can be effectively increased and the midspan vertical displacement can be reduced. The decrease degree of the vertical peak load of the MJ and BMJ under fire exposure is greater than that of the other two joints, and the opening of the BPJ is 19 mm, which is much smaller than that of the other three joints. When the initial axial force is increased, the openings of the four joints under fire exposure are reduced, the vertical peak loads of the PJ and BPJ are increased, and the vertical peak loads of the MJ and BMJ are not significantly increased. Overall, the BPJ demonstrates better fire resistance.

Green high-performance fiber-reinforced cement (GHPFRC) matrix composite is prepared by mixing matrix composites like slurry, mortar, or concrete with reinforcing materials like metal or inorganic nonmetal fiber, synthetic fiber, or natural organic fiber by a certain method. This composite is more energy-efficient, ductile, low-carbon, economic, and environmentally friendly than ordinary concrete. However, the performance of GHPFRC matrix composite has not been fully studied. The existing research only deals with the seismic performance and fire resistance of the material, failing to systematically discuss the optimal mix ratio. To solve the problem, this paper presents an optimization strategy for multielement GHPFRC matrix composite, and carries out multiple tests on its basic mechanical performance, toughness, impact resistance, shrinkage cracking, dry shrinkage performance, and durability. The test data on various indices verify the superior performance of the prepared multielement GHPFRC matrix composite. Further, the optimal mix ratio of the material was determined as: 60% cement, 30% fly ash, and 10% silica ash, with the water-cement ratio of 0.4, water reducer dosage of 1.5%, and quartz sand dosage of 500g.