Over the last decades, numerous automated compliance checking (ACC) systems have been developed. However, ACC is still not broadly used in the architecture, engineering, and construction (AEC) industry today; little is known as to how ACC can be better accepted by the end users. This paper reports on a multicase study to learn valuable lessons from recent attempts to adopt ACC systems worldwide. Firstly, 18 semistructured interviews were conducted with 20 experts from eight countries, and supplementary data (e.g., documents, product information, and literature) related to each case were collected. Secondly, the interview and supplementary data were then coded to develop prominent themes. Thirdly, through a cross-case analysis, the 12 most determining variables that could influence the ACC adoption were identified. Three path models that explain the interrelationships between these variables and 10 propositions that can guide future ACC adoption were deduced. The results indicate that the government should play an important role to facilitate ACC adoption through funding, policies, and incentives. This study also provides valuable information to software vendors for delivering ACC systems that meet the needs of the industry, and for innovation managers in the industry to develop appropriate adoption plans for the ACC technology.

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Numerous automated compliance checking (ACC) approaches have been developed over the last half of the twentieth century. However, little is known as to how well the ACC technology has served the off-site manufacturing (OSM) industry from the end users' perspective. This paper aims to measure the New Zealand (NZ) OSM industry's awareness and readiness for ACC and explore a pathway toward wider ACC adoption. It first reports on a survey study in NZ with 44 valid survey responses. It then proposes a high-level roadmap with key actions that can facilitate wider ACC adoption through 16 interviews with international ACC experts and a focus group with nine local OSM stakeholders. The results show that although there is a high demand for automating compliance processes, the OSM industry, especially small and medium enterprises, are not ready to adopt the ACC technology. Suggestions to address this include (1) establish the foundation for broad ACC adoption; (2) boost the development of the ACC technology to expedite its maturity, (3) test the ACC technology under different scenarios and customize it for the NZ context; (4) encourage the government to provide funding and policy support; and (5) promote education and training of both building information modeling (BIM) and ACC to OSM stakeholders. The results can provide software vendors with valuable information about user expectations and requirements to develop ACC products that can better serve NZ OSM projects, and help OSM stakeholders in NZ and countries with similar economic and regulatory structures to understand the technological and nontechnological gaps to better prepare for the ACC technology adoption.

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This research aimed to explore the impact of aging on the molecular structure of asphalts from different crude oils. The elemental composition of five types of original asphalts was measured. The structure changes of the asphalts were analyzed with Fourier transform infrared spectroscopy (FTIR) and nuclear magnetic resonance (1H-NMR) before and after thin-film oven test, ultraviolet light (UV), and pressure aging vessel (PAV). The result of the elemental analysis showed that the hydrogen-carbon ratio (H/C) of asphalts ranges from 1.347 to 1.602 with different contents of sulfur, nitrogen, and oxygen. The FTIR indicated that asphalts with a low H/C had a low rate of change of carbonyl index after aging. Asphalts were more likely to produce an aromatic ring structure and sulfoxide group during the PAV aging process. The aliphatic structure was easier to reduce during the UV aging process. The 1H-NMR analysis showed that the content of aromatic hydrogen (Har) of asphalts is between 0.022 and 0.056, the content of Har decreased after aging, and the asphalt with a low Har content had a smaller change rate of hydrogen atom content. The outlined research results revealed that the asphalt with lower H/C and Har content was prone to have better aging resistance.@en

This research aims to investigate the aging resistance of asphalts from different crude oils based on molecular structure and rheological properties. The average molecular structure of five types of asphalt from different crude oils were analyzed with the element analyzer, nuclear magnetic resonance, gel permeation chromatograph, and the improved Brown–Ladner method. The rheological properties of the asphalts were tested by the dynamic shear rheometer before and after laboratory aging. The antiaging properties of the asphalts were evaluated by the rheological aging index (RAI). The findings indicate that there were significant differences in the molecular structures among the five types of asphalt. The asphalt with the least hydrogen–carbon ratio (H/C), the largest aromatic carbon ratio (f_A), and the largest condensation index (CI) had the lowest rate of decline in rheological properties and therefore, the best antiaging performance. The H/C, f_A, and CI had good correlations with RAI, which indicated that it was feasible to use these molecular structure parameters to evaluate the differences in the aging resistance of various asphalts.

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Rib-to-deck (RD) welded joints in orthotropic steel decks (OSDs) of bridges demonstrates two major fatigue failure models, including the toe-to-deck (TTD) cracking and root-to-deck (RTD) cracking. Generally, the sole failure model is employed in the fatigue assessment of RD joints, causing a hot dispute on the dominant failure model. In this paper, the fatigue crack growth (FCG) in RD joints has been evaluated considering uncertainties and mixed failure models. A probabilistic fatigue crack growth (PFCG) model is at first established for the RD joint, in which two crack-like initial flaws are assumed at the weld toe and root of the RD joint. After that, the gaussian process regression is used to assist and boost the PFCG simulation. Then, the PFCG model is implemented on a typical OSD with the random traffic model. Finally, the result of the PFCG model is discussed in detail, including the failure model, fatigue reliability and life prediction, and crack size evolution. It is revealed that both the TTD and RTD cracking models have a notable contribution to fatigue failure and could not be ignored. More crucial, a remarkable reduction can be observed in the fatigue reliability of RD joints when considering mixed failure models. This study not only highlights the influence of mixed failure models on the fatigue performance of welded joints, but also provide an insight into the application of novel machine learning tools in solving the traditional structural issue.

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