Journal of Civil Engineering and Management

Multi-stakeholder optimal energy supply for multi-family houses under 2021 German market conditions

Lucas Schmeling — 2024-07-04

Especially in the energy supply of multi-family houses, a wide variety of stakeholders are involved, from owners, to users, to energy service providers and society. They usually have different requirements and understandings of optimality, but ultimately have to make joint decisions and thus sensible compromises. In Germany in particular, there are a large number of multi-family houses and, at the same time, many government restrictions and subsidies in terms of energy supply. This makes it difficult to make clear recommendations for the choice of an energy supply concept that takes all stakeholder interests into account. We first identify the relevant stakeholders and define their objectives. In order to relate these with one another, we present a methodology based on energy system simulation and TOPSIS to make energy concepts objectively evaluable. A generic multi-family house with 40 residential units is examined, combining different energy technologies and insulation standards. There is no energy concept that satisfies all stakeholders equally and it is difficult to build coalitions between them. The best results are achieved by air-source heat pumps in combination with photovoltaic.

Technological innovation cooperative behavior analysis for mega construction projects based on TPB

Zhenxu Guo — 2024-07-04

Due to the complex nature of mega construction projects (MCPs), technological innovation risks have significantly increased. Cooperation is widely accepted as a proactive approach to resolving these risks. An in-depth study of technological innovation cooperative behavior (TICB) helps understand the underlying reasons, but studies need to pay more attention to it. This study explored the factors affecting TICB for MCPs and developed a conceptual model based on the Theory of planned behavior (TPB). It established a structural equation model to verify the relationship between influencing factors. An example verified the feasibility of the model. The results show that cooperative attitude, subjective cooperative norm, perceived cooperative behavior control, and cooperative scenarios positively affect cooperative behavior through cooperative intention. Cooperative attitude plays a mediating role between cooperative scenarios and cooperative intention. Perceived cooperative behavior control has no direct effect on cooperative behavior. This study provides a theoretical reference to guide future empirical studies and enriches the knowledge of TICB for MCPs.

Identifying stress and coping behavior factors of ethnic minority workers in the construction industry via a focus group

Khursheed Ahmed — 2024-07-04

The construction industry is notorious for stressful jobs, particularly for ethnic minority construction workers (EM-CWs), who experience complicated issues in the host country. Despite the high-level stress of EM-CWs compared to native construction workers, the particular coping behaviors of EM-CWs is unclear. Due to their cultural differences, religious beliefs, and possible stigma related to sharing feelings, typical stress management strategies may not be effective in relieving the stress of EM-CWs. To manage the stress of EM-CWs and also to benefit organizational productivity, it is important to identify the specific coping behaviors adopted by EM-CWs in response to stress. Therefore, this study aims to explore the stress management factors of EM-CWs. Six focus group discussions were conducted, made up of five EM-CWs groups (three general worker groups and two skilled worker groups) and one group of foremen. Contextual analysis was used to analyze the focus groups’ qualitative data. The study identified 11 items of stress for EM-CWs in two major categories: emotional and physical stress. In addition to problem-focused (i.e., planned problem-solving, seeking instrumental support, and cognitive appraisal) and emotion-focused coping behaviors (i.e., seeking emotional support, emotional discharge, and escapism), the current study also explored religious-focused coping behaviors (i.e., religious practice, service, and meditation) of EM-CWs. The findings advance coping-behavior literature by addressing important features of religious coping behaviors in the construction industry. The study explored the unique stress management factors of EM-CWs, which can be used to manage the stress of EM-CWs, improve their stress management approaches, and design various stress management programs for EM-CWs. Furthermore, several recommendations were made in initiating time management training, encouraging organizations to consider mental health needs in the construction industry, acknowledging the specific cultural context of EM-CWs, striving to reduce the stigma around sharing emotions under stress, facilitating an adequate on-site environment to practice religion, and introducing mindfulness programs to relieve EM-CW stress and improve their performance.

An improved random forest model to predict bond strength of FRP-to-concrete

Li Tao — 2024-07-05

Fiber-reinforced polymer (FRP) is an excellent building material for strengthening concrete structures, but it is difficult to accurately evaluate the bond strength of FRP-to-concrete due to the influence of various parameters. In this study, a novel hybrid model which combines particle swarm optimization (PSO) with random forest (RF) was proposed to predict the bond strength of FRP-to-concrete. The PSO algorithm was used to optimize the hyperparameters of the RF model. A total of 749 specimens collected from the literature were used to develop the proposed PSO-RF model. Each sample contains 11 parameters required for the model. These 11 parameters are (1) the compressive strength of concrete, (2) the tensile strength of concrete, (3) the width of concrete specimen, (4) the maximum aggregate size of concrete, (5) the tensile strength of FRP, (6) the thickness of FRP, (7) the elastic modulus of FRP, (8) the tensile strength of adhesive, (9) the bond length of FRP, (10) the bond width of FRP, and (11) the bond strength of FRP-to-concrete. The proposed PSO-RF model was compared with other machine learning models as well as ten empirical equations. Six statistical indices, namely root mean squared error (RMSE), mean absolute error (MAE), coefficient of determination (R²), Nash-Sutcliffe efficiency coefficient (NSE), Willmott’s Index of Agreement (WIA), and Legates-McCabe’s Index (LM) were used to evaluate the prediction performance of the abovementioned models. The results show that the RMSE, MAE, R², NSE, WIA and LM values of the PSO-RF model are 1.529 kN, 0.942 kN, 0.986, 0.984, 0.996 and 0.892, respectively, for the training datasets and 2.672 kN, 1.967 kN, 0.963, 0.961, 0.989 and 0.761, respectively, for the test datasets. It can be concluded that the proposed PSO-RF model has the best comprehensive performance in predicting the bond strength of FRP-to-concrete. In addition, the sensitivity analysis of the PSO-RF model was also conducted in this study.