Analysis on Construction Technology and Reinforcement Technology of Building Foundation

In the field of construction engineering, foundation engineering plays a critical role. In actual construction, we must first effectively regulate the foundation construction to ensure the safety and stability of the entire building in order to improve the overall quality of the project. It's also important to look into the technologies that go into building foundations. The construction technology and reinforcing technology of building foundations are examined in this study as a reference.

Evaluation of the Static Design Procedure in the Canadian Foundation Engineering Manual for Piles in Cohesionless Soil

Piles provide a convenient solution for heavy structures, where the foundation soil bearing capacity, or the tolerable settlement may be exceeded due to the applied loads. In cohesionless soils, the two frequently used pile installation methods are driving and drilling (or boring). This paper reviews the results of a large database of pile load tests of driven and drilled piles in cohesionless soils at various locations worldwide. The load test results are compared with the static analysis design method for single piles recommended in the Canadian Foundation Engineering Manual (CFEM) and other codes and standards such as the American Association of State Highway and Transportation Officials, Federal Highway Administration, American Petroleum Institute, Eurocode, and the Naval Facilities Engineering Command. An improved pile design procedure is proposed linking the pile design coefficients and to the friction angle of the soil, rather than employing the generalized soil type grouping scheme previously used in the CFEM. This improvement included in the new version of the CFEM 2021 produces a more unified value of the pile capacity calculated by different designers, reducing the obtained design capacity discrepancies.

Foundation engineering for offshore gravity structures

Gravity based structures are in play from early times. Numerous structures are being installed around the globe. These structures had shown a rigid face towards the harsh conditions/situation in the offshore environment. The key factors for sustainability are geotechnical design and the sub soil survey. These structures are used for collection, transport and also for temporary storage of crude gas and oil. These structures serve as a bridge between the much need fuel and the modern world. The installation of GBS involves major wings of modern engineering i.e. Mechanical, Structural, architecture and Geotechnical engineering because these structures are a great challenge as considering the harsh and hard off shore conditions. These structures are having a much importance apart from its features i.e. from the point of economy, as the oil prices are touching the heights, it influences construction of GBS. Now a days most of the multinational companies are focusing towards the construction of offshore GBS, as well as paying much attention on research work off these structures because to make huge profit. In this paper an effort has been made to understand the different aspects which are related to GBS i.e. pre-construction operations, soil investigation, construction, installment and some of the safety aspects as considering it one of the most focused topics now and in future.

Application of the WNN-Based SCG Optimization Algorithm for Predicting Soft Soil Foundation Engineering Settlement

Settlement prediction in soft soil foundation engineering is a newer technique. Predicting soft soil settling has long been one of the most challenging techniques due to difficulties in soft soil engineering. To overcome these challenges, the wavelet neural network (WNN) is mostly used. So, after assessing its estimate performance, two elements, early parameter selection and system training techniques, are chosen to optimize the traditional WNN difficulties of readily convergence to the local infinitesimal point, low speed, and poor approximation performance. The number of hidden layer nodes is determined using a self-adaptive adjustment technique. The wavelet neural network (WNN) is coupled with the scaled conjugate gradient (SCG) to increase the feasibility and accuracy of the soft fundamental engineering settlement prediction model, and a better wavelet network for the soft ground engineering settlement prediction is suggested in this paper. Furthermore, we have proposed the technique of locating the early parameters based on autocorrelation. The settlement of three types of traditional soft foundation engineering, including metro tunnels, highways, and high-rise building foundations, has been predicted using our proposed model. The findings revealed that the model is superior to the backpropagation neural network and the standard WNN for solving problems of approximation performance. As a result, the model is acceptable for soft foundation engineering settlement prediction and has substantial project referential value.