Facing rising building demands due to a fast-growing world population and significant environmental challenges at the same time, the building sector urgently requires innovation. The Cluster of Excellence Integrative Computational Design and Construction for Architecture at the University of Stuttgart tackles these challenges through a Co-Design approach for integrating computational design and engineering and robotic construction. Within this research framework, a Holistic Quality Model is developed to ensure the technical, environmental, and social quality of Co-Design processes and products. Up to now, quality models that consider and integrate all these three aspects throughout the life cycle of buildings are still missing. The article outlines the concept of holistic quality assessment based on a Holistic Quality Model for sustainable construction. A key mechanism for sustainable quality assessment in the Holistic Quality Model is the definition of control and decision points in the construction process where critical decisions are made that will affect the quality of the building throughout its entire life-cycle. Firstly, subject-specific quality concepts are defined and their interrelations are conceptualized. Subsequently, these interrelations and their effects on the overall Co-Design construction processes and products are explained using the example of the semi-robotic production of concrete slabs. Examples for control and decision points are given as well. The outline presented here serves as a basis for further advancing and concretizing the Holistic Quality Model and its applications in Co-Design for a functioning, liveable, and sustainable high-quality construction and building culture.
Accepting the ecological necessity of a drastic reduction of resource consumption and greenhouse gas emissions in the building industry, the Institute for Lightweight Structures and Conceptual Design (ILEK) at the University of Stuttgart is developing graded concrete components with integrated concrete hollow spheres. These components weigh a fraction of usual conventional components while exhibiting the same performance. Throughout the production process of a component, the positions of the hollow spheres and the level of the fresh concrete have to be monitored with high accuracy and in close to real-time, so that the quality and structural performance of the component can be guaranteed. In this contribution, effective solutions of multiple sphere detection and concrete surface modeling based on the technology of terrestrial laser scanning (TLS) during the casting process are proposed and realized by the Institute of Engineering Geodesy (IIGS). A complete monitoring concept is presented to acquire the point cloud data fast and with high-quality. The data processing method for multiple sphere segmentation based on the efficient combination of region growing and random sample consensus (RANSAC) exhibits great performance on computational efficiency and robustness. The feasibility and reliability of the proposed methods are verified and evaluated by an experiment monitoring the production of an exemplary graded concrete component. Some suggestions to improve the monitoring performance and relevant future work are given as well.
This paper describes a holistic quality model (HQM) and assessment to support decision-making processes in construction. A graded concrete slab serves as an example to illustrate how to consider technical, environmental, and social quality criteria and their interrelations. The evaluation of the design and production process of the graded concrete component shows that it has advantages compared to a conventional solid slab, especially in terms of environmental performance. At the same time, the holistic quality model identifies potential improvements for the technology of graded concrete. It will be shown that the holistic quality model can be used to (a) consider the whole life cycle in decision-making in the early phases and, thus, make the complexity of construction processes manageable for quality and sustainability assessments and (b) make visible interdependencies between different quality and sustainability criteria, to help designers make better-informed decisions regarding the overall quality. The results show how different quality aspects can be assessed and trade-offs are also possible through the understanding of the relationships among characteristics. For this purpose, in addition to the quality assessment of graded concrete, an overview of the interrelations of different quality characteristics is provided. While this article demonstrates how a HQM can support decision-making in design, the validity of the presented evaluation is limited by the data availability and methodological challenges, specifically regarding the quantification of interrelations.
To prevent terror attacks in which trucks are used as weapons as happened in Nice or Berlin in 2016, the European Project Autonomous Emergency Maneuvering and Movement Monitoring for Road Transport Security (TransSec) was launched in 2018. One crucial point of this project is the development of a map-aiding approach for the localization of vehicles on digital maps, so that the information in digital map data can be used to detect prohibited driving maneuvers, such as off-road or wrong-way drivers. For example, a lane-level map-aiding approach is required for wrong-way driver detection. Navigation Data Standard (NDS) is one of the worldwide map standards developed by several automobile manufacturers. So far, there is no lane-level NDS map covers a large area, therefore, it was decided to use the latest available NDS map without lane level accuracy. In this paper, a lane-level map-aiding approach based on a non-lane-level NDS map is presented. Due to the inaccuracy of vehicle position and digital map the map-aiding does not always provide the correct results, so probabilities of off-road and wrong-way diver detection are estimated to support risk estimation. The performance of the developed map-aiding approach is comprehensively evaluated with both real and simulated trajectories.