Near infrared spectroscopy has been used to predict the stiffness of radiata pine (Pinus radiata D. Don) veneers. Spectral data obtained from 1.2·2.4 m veneer sheets was corellated against stiffness data obtained from 6-ply mini-LVL panels prepared from the sheet. This paper describes the method used to prepare the mini-LVL test pieces and the results of multivariate regression of NIR spectra with the test piece stiffness. The results show the potential for using NIR spectroscopy for on-line assessment of veneer stiffness prior to layup of plywood or LVL panels. Selection of high stiffness veneers for layup would enable engineered panels of high uniform stiffness to be produced. Zur Vorhersage des Biegeelastizitätsmodul von Sperrholzfurnieren und Preßschichthölzern mit NIR SpektroskopieDie Elastizität von Schichtholzfurnieren aus Montereykiefer (Pinus radiata D. Don.) wurde unter Verwendung von NIR Spektroskopie vorhergesagt. Spektroskopische Daten von 1.2·2.4 m grossen Schichtholzfurnieren wurden korreliert mit der Elastizität von 6-schichtigen mini-Furnierschichtholzplatten, welche aus diesen Schichtholzfurnieren hergestellt worden waren. Dieser Artikel beschreibt die Methode, mit welcher die mini-Furnierschichtholzplatten hergestellt wurden, und die Ergebnisse der multivariaten Regression von NIR Spektren und der Elastizität der Proben. Die Methode zeigt, daß eine prinzipielle Möglickkeiten besteht, NIR Spektroskopie für eine on-line Beurteilung der Furnierelastizität zu verwenden, bevor diese zu einer Sperrholzplatte geschichtet werden. Eine Auswahl von Funieren mit geringer Elastizität vor der Schichtung würde es ermöglichen, Platten mit geringer, einheitlicher Elastizität herzustellen.
Robotic Building implies both physically built robotic environments and robotically supported building processes. Physically built robotic environments consist of reconfigurable, adaptive systems incorporating sensor-actuator mechanisms that enable buildings to interact with their users and surroundings in real-time. These robotic environments require Design-to-Production and-Operation (D2P&O) chains that may be (partially or completely) robotically driven. This chapter describes previous work aiming to integrate D2RP&O processes by linking performance-driven design with robotic production and user-driven building operation. 5.1 Introduction While architecture and architectural production are increasingly incorporating aspects of non-human agency employing data, information, and knowledge contained within the (worldwide) network connecting electronic devices, the question is not whether but how robotic systems can be incorporated into building processes and buildings (Oosterhuis and Bier 2013). This chapter aims to answer this question by reflecting on the achievements of the Robotic Building (RB) team at Technical University Delft (TU Delft) and by identifying future steps. The focus is on an architecture that is robotically enabled to interact with its users and surroundings in real-time and the corresponding Design-to-Production and-Operation (D2P&O) processes that are (in part or as whole) robotically driven. Such modes of production and operation involve agency of both humans and non-humans. Thus agency is not The original version of the book was revised: Open access text has been updated in FM, Chapter
-This paper presents an initial proof-of-concept implementation of a comprehensively intelligent built-environment based on mutually informing Design-to-Robotic-Production and -Operation (D2RP&O) strategies and methods developed at Delft University of Technology (TUD). In this implementation, D2RP is expressed via deliberately differentiated and function-specialized components, while D2RO expressions subsume an extended Ambient Intelligence (AmI) enabled by a CyberPhysical System (CPS). This CPS, in turn, is built on a heterogeneous, scalable, self-healing, and partially meshed Wireless Sensor and Actuator Network (WSAN) whose nodes may be clustered dynamically ad hoc to respond to varying computational needs.Two principal and innovative functionalities are demonstrated in this implementation: (1) costeffective yet robust Human Activity Recognition (HAR) via Support Vector Machine (SVM) and kNearest Neighbor (k-NN) classification models, and (2) appropriate corresponding reactions that promote the occupant's spatial experience and wellbeing via continuous regulation of illumination with respect to colors and intensities to correspond to engaged activities.The present implementation attempts to provide a fundamentally different approach to intelligent built-environments, and to promote a highly sophisticated alternative to existing intelligent solutions whose disconnection between architectural considerations and computational services limits their operational scope and impact.
Hyperbody's materially informed Design-to-Robotic-Production (D2RP) processes for additive and subtractive manufacturing aim to achieve performative porosity in architecture at various scales. An extended series of D2RP experiments aiming to produce prototypes at 1:1 scale wherein design materiality has been approached from both digital and physical perspectives were recently implemented. At digital materiality level, a customized computational design framework for compression only structures has been developed, which was directly linked to the robotic production setup. This has enabled the systematic study of physical materiality, which cannot be fully simulated in the digital medium. The established feedback loop ensured not only the development of an understanding for material properties in relation to their simulated and real behaviours but also allowed to robotically additively deposit and/or subtractively remove material in order to create informed material architectures at 1:1 scale.
Technological and conceptual advances in fields such as artificial intelligence, robotics, and material science have enabled robotic building to be in the last decade prototypically implemented. In this context, robotic building implies both physically built robotic environments and robotically supported building processes, whereas reconfigurable, robotic environments incorporating sensoractuator mechanisms that enable buildings to interact with their users and surroundings in real-time require design to production, assembly, and operation chains that may be (in part or as whole) implemented by robotic means. This paper presents and discusses research and experimental developments in robotic building implemented more recently at Hyperbody.
Minimal interventions that provide various microclimates can stimulate both biodiversity and social accessibility of leftover spaces. New habitats are often developed for different animal and plant species based on studies of the microclimates typical of such residual spaces. By introducing interventions of 0.5-1.0 m diameter ‘planetoids’ placed at various locations, existing and new life is supported. The ‘planetoid’ described in this paper is prototyped by means of Design-to-Robotic-Production and -Operation (D2RP&O). This implies that it is not only produced by robotic means, but that it contains sensor-actuator mechanisms that allow humans to interact with them by establishing a bio-cyber-physical feedback loop.
This paper presents the implementation of a facial-identity and-expression recognition mechanism that confirms or negates physical and/or computational actuations in an intelligent built-environment. Said mechanism is built via Google Brain's TensorFlow (as regards facial identity recognition) and Google Cloud Platform's Cloud Vision API (as regards facial gesture recognition); and it is integrated into the ongoing development of an intelligent built-environment framework, viz., Design-to-Robotic-Production &-Operation (D2RP&O), conceived at Delft University of Technology (TUD). The present work builds on the inherited technological ecosystem and technical functionality of the Design-to-Robotic-Operation (D2RO) component of said framework; and its implementation is validated via two scenarios (physical and computational). In the first scenario-and building on an inherited adaptive mechanism-if building-skin components perceive a rise in interior temperature levels, natural ventilation is promoted by increasing degrees of aperture. This measure is presently confirmed or negated by a corresponding facial expression on the part of the user in response to said reaction, which serves as an intuitive override / feedback mechanism to the intelligent building-skin mechanism's decision-making process. In the second scenario-and building on another inherited mechanism-if an accidental fall is detected and the user remains consciously or unconsciously collapsed, a series of automated emergency notifications (e.g., SMS, email, etc.) are sent to family and/or caretakers by particular mechanisms in the intelligent built-environment. The precision of this measure and its execution are presently confirmed by (a) identity detection of the victim, and (b) recognition of a reflexive facial gesture of pain and/or displeasure. The work presented in this paper promotes a considered relationship between the architecture of the builtenvironment and the Information and Communication Technologies (ICTs) embedded and/or deployed.
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