This paper focuses on the nonlinear simulation of soil-wall interaction via a simple and efficient yet accurate solution. First, an overview of the subject and the reasoning behind using the proposed method is discussed. Then, the formulations are presented in a comprehensive and stepwise manner. At the end, a large-scale test found in the literature is studied and the precision of the method suggested in this research is verified via comparison between the force-displacement relationship between the simulation and the test program.
This study focuses on using an optimization technique to control the crack propagation in reinforced concrete T-beams by employing multi-objective optimization and numerical simulations to enhance the shear strength. Four key factors (concrete density, Young's modulus of elasticity of concrete, steel density, and Young's modulus of elasticity of steel) were considered within a predefined range to predict the ductility and the elastic shear strain for the structural member. Box-Behnken design sampling method was utilized to prepare 27 numerical models using the ABAQUS finite element program. The outputs of the elastic shear strain and the maximum principal stress were collected in conjunction with MATLAB codes to solve complex matrices. The regression coefficients were determined via the least squares method which are needed to build the regression equations for prediction. The harmonic mean method was applied as a multi-criteria optimization strategy to unify conflicting objectives into a single optimization problem. The reliability of the regression equations was validated by comparing them with the numerical simulation results which resulted in achieving 100% accuracy with R-2 values of 1 for both the maximum principal stress and the elastic shear strain. The results highlight that the shear strength capacity of the reinforced concrete T-beams can be effectively optimized, enabling precise design control.
Engineering (i.e. mechanical, electrical and civil or bridge engineering) unlike science, is concerned not only with knowledge of natural phenomena but also with how knowledge serves the needs and desires of humanity. Variables such as cost, user compatibility, deliverability, safety, and adaptability to different external operating conditions and environments must be taken into account when designing, developing, operationally supporting, and maintaining engineer-created products and services. Therefore, engineering requires the combination of experience, procedures, processes and know-how from multiple fields. In addition, almost all undergraduate research in science and engineering is conducted as part of students' advanced training. The aim of working in industry motivates them to pursue advanced studies, and this will increasingly be the case in the future. For this reason, engineering students' perspectives on research tend to be applied in engineering practice. The main goals of research work are to inform work, gather evidence for theories, and add to the development of expertise in the field of study.
In this paper, we utilize a multi-objective approach with numerical simulations models for the optimization of the flexural strength for a pre-stressed concrete beam. The optimization approach is conducted utilizing five factors that are (concrete Young's modulus, concrete density, steel Young's modulus, steel density, and pre-stressing) which have a limited range. The surrogate model that predicts both the strain and the deflection for the pre-stressed concrete beam is constructed using least square tool in MATLAB. Twenty one numerical simulations are generated using ABAQUS finite element programs using the experimental design method of Latin Hypercube. The surrogate model's reliability has been tested by comparing the outputs from the numerical models with the surrogate models. The coefficient of determination (R-2) value for both (the maximum principal strain and the maximum deflection outputs) was 1 which indicates 100% accuracy. A non-linear multi-objective optimization with constrained factor range was conducted based on the Karush-Kuhn-Tucker (KKT) method for the surrogate models. At first, we scalarized two objectives into single one using harmonic mean, then we used the KKT method which worked very well for optimizing the two surrogate models of prediction.
Trail bridges are vital for improving rural connectivity and living standards. Their construction minimally impacts the environment and causes less disruption. These bridges are crucial for safe river crossing, reducing travel time, and aiding in education, healthcare, and market access. This research aimed to identify best practices by evaluate and compare the design and construction of trail bridges in Ethiopia and Rwanda. The study used data from focus group discussions, expert interviews, and on-site observations in both Rwanda and Ethiopia. Significant distinctions in N-type suspension bridges constrcution noted, particularly in the simplicity of the steel tower, its foundation connections, and main cable anchorage in Rwanda compared to Ethiopia. Ethiopia's bridges, however, were praised for bridge tower and suspenders easely adjustable, maintenable and local material use. The results from the expert questionnaires reveal a strong consensus on the importance of integrating bridge users or community input into the creation of design codes and standards to enhance bridge functionality and user-friendliness. The case study and field observation reveled that, the construction of trail bridges in constrcution practices. The study recommends updating the design manuals by integrating the most effective elements and best practices from each country.
