Journal of Civil Engineering and Management

BIM and orthogonal test methods to optimize the energy consumption of green buildings

Xiaojuan Li — 2024-09-17

The construction industry’s rapid growth significantly impacts energy consumption and environmental health. It is crucial to develop optimization strategies to enhance green building energy efficiency and encompass comprehensive analysis methods. This study aims to introduce and validate a novel framework for optimizing energy efficiency design in green buildings by integrating Building Information Modeling (BIM) technology, Life Cycle Cost (LCC) analysis, and orthogonal testing methods, focusing on enhancing energy efficiency and reducing life cycle costs. The optimization parameters for the building envelope are identified by analyzing energy consumption components and key green building factors. The orthogonal testing method was applied to streamline design options. Building Energy Consumption Simulation (BECS) software and LCC analysis tools were employed to calculate each optimized option’s total annual energy consumption and the current life cycle costs. Using the efficiency coefficient method, each optimization scheme’s energy consumption and economic indicators were thoroughly analyzed. The framework’s validity and applicability were confirmed through an empirical analysis of a campus green building case in Fujian Province, demonstrating that the optimized framework could reduce energy consumption by 4.85 kWh/m² per year and lower costs by 38.89 Yuan/m² compared to the reference building. The case study highlights the framework’s significant benefits in enhancing environmental performance and economic gains. The results provide critical parameter selection and offer scientific and technological support for the design of building energy efficiency, promoting optimization techniques and sustainable development within the construction industry.

The effect of relative density, granularity and size of geogrid apertures on the shear strength of the soil/geogrid interface

Ali Lakirouhani — 2024-09-25

The increasing use of geogrid in various geotechnical projects has made the evaluation of the shear behavior of soil reinforced with geogrid become particularly important. In this article, a series of large-scale direct shear tests have been performed on sand and gravel samples reinforced with geogrid. The purpose of the experiments was to investigate the impact of the geogrid mesh size and the relative density of the samples on the shear strength coefficient of the interface between soil and geogrid. In this study, 5 geogrids with different mesh sizes and one type of geotextile were used. According to the results, the average shear strength coefficient of sand and gravel samples reinforced with geogrid for different normal stresses and different relative densities was obtained between 0.72 and 0.94. As the relative density increases, the interface shear strength coefficient decreases, this means that the denser the sand, the more the shear strength of the sand/geogrid interface decreases. Based on the results, it was found that the contribution of particle interlocking in the shear resistance of the sand/geogrid interface is particularly important, so that the shear resistance coefficient of the interface increases with the increase in the size of the geogrid mesh.

Planning municipal drainage infrastructure maintenance operations with finite available crews: pragmatic optimization approach

Ali Bayesteh — 2024-10-11

This paper proposes a streamlined approach to addressing the problem of allocating finite crew resources to concurrent jobs in the context of municipal drainage infrastructure maintenance. The problem was defined from the perspective of a project manager involved in planning such operations on a day-by-day basis. The problem statement was then transformed into a simplified Integer Linear Programming optimization model. Performance metrics were devised to evaluate the optimization model’s effectiveness. A heuristic algorithm representing the decision-making process by a seasoned planner in the partner company was also developed. Both methods were applied to a case study and contrasted based on the same performance metrics. The findings underscored substantial optimization benefits in rendering decision support in resource-constrained drainage construction operations planning. In conclusion, this research presents an alternative strategy for navigating the complexities inherent in finite crew resource allocation on multiple concurrent drainage projects; lends a cost-effective optimization solution to improving the utilization of finite available crews while satisfying service demands from multiple clients to the largest extent possible.

Computer vision based early fire-detection and firefighting mobile robots oriented for onsite construction

Liulin Kong — 2024-10-11

Fires are one of the most dangerous hazards and the leading cause of death in construction sites. This paper proposes a video-based firefighting mobile robot (FFMR), which is designed to patrol the desired territory and will constantly observe for fire-related events to make sure the camera without any occlusions. Once a fire is detected, the early warning system will send sound and light signals instantly and the FFMR moves to the right place to fight the fire source using the extinguisher. To improve the accuracy and speed of fire detection, an improved YOLOv3-Tiny (namely as YOLOv3-Tiny-S) model is proposed by optimizing its network structure, introducing a Spatial Pyramid Pooling (SPP) module, and refining the multi-scale anchor mechanism. The experiments show the proposed YOLOv3-Tiny-S model based FFMR can detect a small fire target with relatively higher accuracy and faster speed under the occlusions by outdoor environment. The proposed FFMR can be helpful to disaster management systems, avoiding huge ecological and economic losses, as well as saving a lot of human lives.

Modelling inter-relationships of barriers to smart construction implementation

Beiyu You — 2024-10-15

Smart construction technology offers fresh avenues for advancing the field of civil engineering. It seamlessly integrates across the entire life cycle of civil engineering projects, encompassing planning, design, construction, and maintenance, thereby fundamentally reshaping the landscape of civil engineering development. Nonetheless, it is essential to recognize that, presently, smart construction’s developmental stage remains relatively nascent. Its progression is subject to a myriad of adoption barriers, and the complex dynamics of their interactions remain insufficiently understood. Therefore, this study aims to (1) explore the barriers to the adoption of smart construction; (2) analyze the impact level of each barrier; and the interaction mechanism between the barriers (3) propose effective strategies to promote the development of smart construction. This study commences by identifying 16 major impediments to the adoption of smart construction through a comprehensive synthesis of existing literature and expert interviews. Subsequently, Euclidean similarity analysis is employed to harmonize varying expert assessments. Following this, the Decision-Making Trial and Evaluation Laboratory model is utilized to ascertain the degree of influence associated with each barrier. Further, the Interpretive Structural Model is employed to establish a hierarchical framework that illuminates the interdependencies among these barriers. Additionally, the Matrice d’Impacts Croisés Multiplication Appliqués à un Classement method is invoked to elucidate the roles and statuses of each barrier. Finally, strategies are proposed based on the results of the analysis. This study offers practical strategies for overcoming barriers and driving the adoption of smart construction, filling a critical gap in understanding by identifying key barriers and providing actionable insights, thus significantly advancing the field and empowering stakeholders for successful implementation and dissemination.

Performance-based design of strip foundation considering the full effect of ground improvement

Yang Yu — 2024-10-16

Ground improvement is an effective way to improve the bearing capacity of a shallow foundation. However, the benefit of reducing uncertainties in soil parameters for shallow foundation design is rarely recognized. This study investigated the full effect of rapid impact compaction (RIC) on a strip foundation design. The finite difference method coupled Monte Carlo simulation were used to calculate the failure probability and the required width of the strip foundation, where the friction angle of soil was treated as a random variable. The results show that the foundation width reduces by 48.5% when considering the full effect of RIC, and a significant part of the reduction came from the decrease in the uncertainty of friction angle. Although the adopted relationship between the friction angle and tip resistance of cone penetration test affects the designed width of the foundation, the full effect of ground improvement contributed by the uncertainty reduction of soil parameters is still significant. The implication of the present study provides a basis for the performance-based bearing capacity design of shallow foundations.