A virtual environment for the design and simulated construction of prefabricated buildings

The construction industry has acknowledged that its current working practices are in need of substantial improvements in quality and efficiency and has identified that computer modelling techniques and the use of prefabricated components can help reduce times, costs, and minimise defects and problems of on-site construction. This paper describes a virtual environment to support the design and construction processes of buildings from prefabricated components and the simulation of their construction sequence according to a project schedule. The design environment can import a library of 3-D models of prefabricated modules that can be used to interactively design a building. Using Microsoft Project, the construction schedule of the designed building can be altered, with this information feeding back to the construction simulation environment. Within this environment the order of construction can be visualised using virtual machines. Novel aspects of the system are that it provides a single 3-D environment where the user can construct their design with minimal user interaction through automatic constraint recognition and view the real-time simulation of the construction process within the environment. This takes this area of research a step forward from other systems that only allow the planner to view the construction at certain stages, and do not provide an animated view of the construction process

Suitability of BIM for enhancing value on PPP projects for the benefit of the public sector

Collaborative integrated working and stakeholder’s interest have been among key drivers that underpin and encourage the use of Building Information Modelling (BIM) within the AEC industry. BIM is becoming a major means to deliver projects with better improved product, and reduced risk within the construction industry. Furthermore, using BIM in areas like buildability, quality assurance, cost and scheduling can be justified through BIM-nD modelling application. What is not so obvious is how the utilisation of BIM visualisation and knowledge embedment will enhance these areas to refine and achieve better value for PPP procurement projects for the long term benefit especially during post-construction phase for the public sector. As of now there is no well-defined guidance with respect to BIM usage incorporating all of the above. Do we really need to revisit the way we specify projects within the contractual framework under PPP? This paper examines the possibility of how BIM can be utilised in the realisation of augmented formal database information management system under the PPP procurement routes with respect to operation and maintenance support. The paper concludes with additional measures that BIM can offer at the post-construction phase for the public sector at learning organisations

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions