Abstract:Reliable live load value is the prerequisite for reliability design of civil engineering buildings， and the collection of live load samples is the key data foundation for load modeling. Aiming at the problems of difficulty in entering households， weighing， low efficiency， and small samples that exist in the traditional research methods of sample collection and weighing in households， and based on the research thinking of big data， a new research method of residential persistent live load based on panoramic VR（virtual reality） house viewing system is proposed. Through the VR system of open network platform， multi-source heterogeneous data such as pictures and videos， combined with Internet resources， comprehensive network crawler， and other means， live load investigation is realized by non-weighing method， and practical research is conducted by taking residential buildings as examples. The characteristic value of residential live load was obtained by statistical analysis and load combination of 4 676 rooms in 9 cities （with a total area of nearly 75 000 square meters）. The results show that the standard deviation of sustained live loads significantly increases at any given time， the time of live load variations is different among different cities， which， overall， presents a decreasing trend. The combination of VR system and internet big data can achieve efficient and convenient residential live load surveys， forming a new research method for live loads.

Abstract:Reliable live load value is the prerequisite for reliability design of civil engineering buildings. Traditionally, building live loads are investigated by means of indoor objects sampling and weighing. This method has many problems such as low efficiency, high labor cost, long duration, limited samples, poor timelines in reflecting indoor items change and difficulty in weighing large items. Inspired by the big data concept, this paper proposes a new research method for investigating indoor sustained live loads. Through the multi-source heterogeneous data such as photos, videos, identification codes, and voices, combined with internet resources, the weight of objects in the building is obtained by means of object detection, image retrieval, voice or text recognition. After the detailed introduction of the implementation method, further case studies show that the use of big data technology can achieve efficient and convenient building live load survey, and build a new load research paradigm

Abstract:Deformation characteristics of main cable in suspension bridges was studied under the effect of displacement of tower, elastic elongation and unbalanced load. The relationship among the change of cable sag, the elongation of the cable and the displacement of tower top was studied. The smaller the sag ratio was, the larger the sag changed. The most unfavorable loading mode was researched by means of energy method and equilibrium condition of force. Results show if there was no elongation, the maximum deflection caused by unbalanced distributed load was relevant to the ratio of live load to dead load and the sag of cable. Analytic formulas were given and verified by a finite element model. The results agreed well with the theoretical value.