Agent-based Semiology for Simulation and Prediction of Contemporary Spatial Occupation Patters

Mathias Fuchs and Robert R. Neumayr

Abstract. Agent-based semiology is a powerful simulation and prediction environment for pedestrian simulation that allows for accurate balancing of complexity. Here, we describe a framework to simulate increasing behavioural interactivity between agents via agent-based modeling, together with a statistical approach to make the results amenable to a quantitative and automated analysis. That approach borrows ideas from crowd simulation and spatial statistics, notably fitting of Poisson processes, and computer graphics. The described process can simply be thought of as that of approaching an observed pattern by an overlay or additive mixture of grey-scale images each of which are distance transforms of physical objects. Thus, we describe the observed pattern in terms of interactions of spatial features which are akin to traditional BIM tags. We thus arrive at a remarkably concise prediction of the simulation outcome. The benefits of this simulation speedup is, on the one hand, to allow for higher optimization throughput, and on the other hand, to provide designers with quantitative feedback about the impact of their design on the simulation outcome.

Keywords: Parametric Modeling, Simulation, Agent-Based Semiology.

Introduction

Agent-based Semiology aims to investigate, analyze, simulate, and predict contemporary spatial occupation patterns in social spaces in order to understand and develop the performance criteria that interactively link these spaces, their interiors, and their users. The research ambition at hand is to develop a cross-disciplinary method of architectural design that generates spatial environments with high social performativity. 

Architecture channels its social processes through semiological associations as much as through physical separation and connection. It functions through its visual appearance, its legibility and its related capacity to frame its users’ communication. In that way the built environment is not just physically directing bodies, it is orienting socialized agents who have to understand and navigate complex spatial organisations, or  “As a communicative frame, a designed space is itself a premise for all communications that take place within its boundaries.” [21].

In a conventional design process, the designer tends to intuitively adapt and spontaneously intervene within the historically evolving semiological system of his respective cultural environment. The aim of agent-based semiology, however, is to move from this intuitive participation within an evolving semiosis towards a systematic and explicit design process, that understands contemporary spatial organisations as coherent systems of signification without relying on the familiar codes found in the existing built environment.

In today’s networked society and its communication-based working patterns, its increasingly open and dynamic environments, complex spaces and multi-layered social systems of use, the users’ behavioural patterns of interaction cease to be linear and simple to predict but rather start to show emergent and unpredictable properties. This emerging behavioural complexity is no longer a clear function of a number of static spatial occupation patterns, but the result of an iterative process in which the repeated superimposition of a set of comparatively simple interaction patterns of a system’s basic components (its agents) adds up to the complex state of the emergent system. Such nonlinear process, in which small-scale interactions govern a systems overall configuration, is called a “bottom-up” process, as opposed to a “top-down” process, in which the overall form is determined first in order to subsequently organize its constituent parts.

The results of these kind of processes can no longer be calculated or predicted and present serious challenges for predictive algorithms, suggesting the use of extensive computer simulations of its underlying dynamics. They can, however, be simulated using agent-based modeling which is commonly defined as “a computational method that enables a researcher [to] experiment with models composed of agents that interact within an environment.” [7]. In, 1987 Craig Reynolds was the first to successfully set up such a  simulation, reproducing the flocking behaviour of birds with this simulation program “Boids” [19]. Since then agent-based models (ABM) have been developed, refined and commonly used for simulations in the fields of physics, chemistry, biology, or social sciences, mapping the processes that we assume to exist in a real social environment [15].

While other tools and techniques for understanding social spaces, such as for example Space Syntax [10] have gained considerable popularity over the years, architecture has only recently discovered the use of agent-based models for the simulation of life processes. Similar to flocks of birds or schools of fish, human crowds show complex non-linear behaviour and thus constitute emergent systems, that can be successfully simulated by agent-based modeling. Therefore this research proposes their use for the simulation of architecture-related life processes. 

The analysis and prediction of emergent spatial occupation patterns in today’s social spaces, most notably contemporary office environments, has gathered more attention recently, as the economies of developed countries increasingly depend on the free flow of information rather than on the administration and exchange of goods and services. In Western European countries knowledge economy at this point represents about a third of all economic activities [6].

Moving away from long-established Taylorist office space layouts with its traditional linear logics of mono-directional workflow, where the success of different spatial layouts could be easily measured, work patterns in today’s knowledge economy has become increasingly complex, flexible, and interwoven and can therefore no longer be organized and evaluated according to Taylorist principles. Consequently, new methods of assessing the performance of spatial layouts need to be developed.

Designers such as the German Quickborner team with their Bürolandschaft concept, started already in the 1970s to develop novel office layouts that were essentially real-life diagram-spaces based on the optimization of spatial relations between groups of employees. While this design methodology was still relying on the assumption, that there is a linear relationship between a spatial layout’s organisational efficiency and its work output, one of its major innovation was that it focused on the patterns of communication rather than its contents, thus establishing the flow of information as a generative tool. The other key innovation was the abolishment of spatial hierarchies in order to foster informal communication which was considered critical in a cybernetic organisational model [14], or as Quickborner’s Ottomar Gottschalk put it: “Informal conversations are not only useful – in all likelihood  they are actually crucial.” [8].

In knowledge economies employees increase their respective radius of interaction due to the  intrinsically networked nature of contemporary workflow and as a consequence various new types of knowledge work with their particular needs and mobility patterns emerge [9]. The sharing of work, goods or products is less important than information interchange, communication, and human interaction. A space’s performativity therefore largely hinges on its capacity to spatially and semiologically frame the constant informal and formal transfer of knowledge between its users in various different configurations.

Therefore, a design brief of a contemporary office environment acts as an experimental setup in which empirical and statistical knowledge, simulation methodologies, and design ideas are systematically brought together. In order to measure the various emergent patterns that arise from the agents’ continuous interactions with each other, as well as with their environment, the research focuses on the office space’s breakout space, which is its most informal area, where spontaneous communicative encounters and unscheduled opportunities for networking, collaboration and skill exchange can easily occur. At the same time the space’s furniture elements also allow for planned or organized meetings or conferences of various sizes and configurations.

Simulation methods and ACL – scenario matrix 

The research sets up and refines agent based life process simulations, in which the semiological code is defined in terms of the agents’ behavioral rules or scripts being triggered by specific environmental features as well as by the interaction with other agents. The simulation is run in two independent programs in parallel, NetLogo and Unity, with the same setup and variable values, in order to be able to compare results and data.

NetLogo (see Fig. 1) is a program designed for agent-based simulations with built-in processes that already solve typical agent based simulation scripting problems. As it is purely code based it is fast, scalable and data extraction is easy.

Fig. 1. The Netlogo simulation environment.

Unity is a component based software program, that is very popular amongst game developers used to develop multiplayer video games across various platforms. Its complexity allows for sophisticated agent interactions and can also be fully script driven. 

In order to understand, simulate and predict comprehensive life-like office scenarios with complex behavioral patterns within a controlled simulation, a clearly defined small-scale office breakout space is used to script and test relationships between agents and the environment. The task is the development of a population of agents with life‐like individual behavioral rules that allow for the emergence of a simplified, yet overall plausible collective event scenario. For  this, any agent population needs to display two key properties of ‘life‐process modeling’. 

First of all, there needs to be agent differentiation by status, affiliation, or position within the social network, implying behavioral difference as agents interact with each other. Real-life social interactions are complex in nature, as they depend on multiple variables, that have to be effectively weighted to be made operational in a simulation. While this research has been looking into using social network analysis to extract relevant social network features (for example from email databases) to later inform agent-based life process modeling, at this point  agents’ behaviour, such as probability and duration of interaction, is driven by randomly assigned accumulative interaction values. Agent will choose to interact with the agent agent, who has the highest interaction value within a fixed range of values that who is available (i.e. not occupied) within a defined distance.

Secondly there needs to be architectural frame‐dependency, implying different behavioral patterns depending on location and spatial architectural qualities. To that end, architectural features, which are typical for an office break out space, such as different types of tables, a reception desk, or a coffee machine, are added to the simulation environment, once the basic logic is set up. These features are assigned interaction values similar to the agents, that govern the agents’ interaction with them.

Like in other strands of design research, continuously refining the digital processes becomes an important issue once a basic logic is established[16]. Therefore the complexity of the simulation is increased continuously, step by step. While the simplest movement pattern in spatial simulation is the random walk [17], the initial simulation setup is an agent walking around the scene unaware of his surroundings. 

Simulations gradually increase in complexity and for better systematic comparison are organized in a 2-dimensional matrix system. On the vertical axis we define the agent complexity (agent capacity level – ACL), starting from the simplest possible agent as described above (ACL 1.0). In each subsequent step, the agents’ capabilities are systematically extended (i.e. collision detection, agent interaction, object interaction, etc.), up to a simplified office setup that allows for agent to agent interaction as well as for an interaction with a number of common furniture elements, such as a reception desk, a coffee machine, high tables, low tables, and a meeting table. The result is an accumulative build up of potential agent faculties that allows for direct comparison of individual ACLs and therefor speculation on possible success criteria and relevance of agent capacities. 

On the horizontal axis, each capacity level is tested in four parallel simulation scenarios (A, B, C, D) in order to produce a more robust data set. These scenario differ slightly from each other in terms of their floor pan layout, the location of doors, and the position of interaction objects. The parameters that remain constant are a maximum number of 16 agents per simulation and the total run time of 30 min. During runtime relevant data, such as the agent’s positions, their encounters and interactions, is constantly collected from the simulation and stored for later analysis. For ease of comparison the data is used to create a number of visual quantifiers, such as heat map showing the concentration of occupancy (density) and trail maps tracking the movement of each individual agent. 

The collected simulation data from the first three simulations (A, B, and C) is used to train a prediction algorithm that finally is tested against the empirical data set of the last simulation (D) for accuracy, where the prediction algorithm is confronted with a novel scenario condition.

Statistical description and prediction

Overview and goal

Gaining an approach to a statistical description is necessary for bridging the gap between pedestrian simulations on one side, and 3D modeling. We aim at automating the knowledge transfer in an objective and repeatable way, by deriving a sufficiently general model of the interaction between people and their environment. We emphasise a quantitative, interpretable, easily trained algorithm inspired from statistical learning, that is adaptive and easily extrapolated to new scenarios, in order to leverage the potential of pedestrian simulation for real-world design.

Spatial data analysis [4] deals with regressing observed movement patterns on spatial features. Whereas in a usual linear regression model, the values taken by a single dependent variable are explained by relating them to a linear combination of the independent variables, the so-called features, in a spatial data analysis task an entire spatial field of observations is related to a linear combination of independent feature fields. For instance, the dependent field could be that of successful oil rigs, and the independent fields could be the maps of geographical and geological characteristics. Here, the dependent field is given by the observed pedestrian movement pattern, and the independent feature fields are given by explanatory physical or architectural features of the space. Then, observations of a linear combination of the dependent variables blurred with Gaussian noise. 

Figures 2 and 3 demonstrate the  inspiration visually: to bridge the gap between hard geometrical features and smooth pedestrian behaviours.

Fig. 2. The discrepancy between “hard” geometry and “soft” pedestrian movement patterns can be bridged tentatively by assuming the existence of a guiding principle that steers the pedestrian density according to the proximity to the geometrical pattern. In this work, we are formalising the idea of describing the observed pedestrian density as an overlay of proximities to hard geometrical or physical features of the space.

Fig. 3. A spatial pattern is assumed to be generated by input fields, generated by objects. Typically, doors and tables are the “seed crystals” of these fields.

Development of a statistical model

Therefore, we need to find a way to describe regressors or dependent variables. We used a notion of one-channel image, reflected in a C++ class, to capture the spatial impact of a feature in the form of its distance image [12]. A feature is a user-supplied “explanatory” function. Here, we use the distance fields from objects but in principle any kind of one-channel image can be used for the task.  Such a function can be thought of as an gray-scale image, overlaid onto the 2d rectangle representing the scene’s bounding box in plane view. A typical function could represent the distance to a point of interest such as the central table in a meeting room. Thought of as an image, it consists of radial isolines around the table, getting darker and darker farther away from it. In a first step, one models the impacts of the most apparent spatial features, acting as attractors: doors, tables, toilets, staircases, maybe windows, etc. Their impact is modeled by a function which decreases steadily with higher distance to the object. In general, there is a variety of possible “influence maps”.

In concrete statistical terms, estimating the weights or contributions of each feature is done by fitting a Point Poisson Model to the Data with the Maximum Pseudolikelihood Method [3 and 9]. Fig. 4 shows the central object of study: the pedestrian density represented at as a heatmap. Concretely, the process can be thought of as first computing the empirically observed heatmap and then interpreting it as an overlay as pictured in Fig. 6 of distance images to these spatial features. 

Fig. 4. The building block of statistical reinterpretation of the observed pedestrian occupation pattern is the heatmap. A small number of these is used to approach the observed one. This figure illustrates the complexity inherent in an observed heatmap. Moreover, the dependence of the visual appearance of the heatmap on the bandwidth used for its computation, is often underestimated. This phenomenon corresponds to the ubiquitous property of natural patterns to exhibit structure on every scale from small to large whereas artificial patterns are often constrained to fewer scales.

Attaching features to physical objects and statistical model fitting

The aim of statistical analysis is twofold: fostering the understanding of the spatial process by descriptive processing, and the extrapolation of the learned model to new scenarios in a prediction. In this second step, we derive a way to draw the density of pedestrian activity, as generated in a simulation, onto the design canvas in an adaptive manner. We accomplish that goal by employing techniques and algorithms from point processes. In particular, we show how rudimentary BIM (building information model) tag information gives rise canonically to a set of spatial features. We then go on to describe how a Poisson model fitting gives rise to a statistical model which associates to a design intervention a smooth (“parametric”) adaptation of the predicted pedestrian density. See [20] for an overview of density estimation and its relationship with Gaussian blurring, and the subsection below for the exact description of the fitting method of the features. Fig. 4 shows the central object of study: the pedestrian density represented at as a heatmap.

We validate the generated predictive model by careful separation of the data into disjoint learning and testing sets. A particular benefit of the method is its susceptibility to produce not just predictions — as, for instance, a neural network would — but instead to generate an understanding of how the model works, by yielding concrete and interpretable coefficients associated with the spatial features.See Fig. 7 for an example of prediction results on ACL 4.4.

Fig. 5. The concept of reinterpreting and observed pattern in terms of an overlay of simpler ones is quite powerful. Here, we show how any uniform random point pattern, i.e. a noise pattern, can be described almost perfectly as an overlay of generic heatmaps – sine waves in this case. The approximation principle is closely related to consequences of the theory of Fourier series.

Fig. 6. Each spatial object generates its distance transform. Here, six types of objects – door, window, three standing tables and a desk, each generate a distance function. Finally, these are overlaid additively to generate a statistical re-interpretation of an observed pedestrian pattern. The process of fitting the parameters of a Poisson process described here is the one that determines the contributions or weights of each single such feature image to the overlay.

Fig. 7. Result of the prediction. Learning sets are A to B, true observed pattern is D.

Description of the fitting algorithm

The actual core of the method is the computation of the weights of each single image — typically, a distance image. Each weight gives the image’s relative contribution to the overlay which is intended to be describe the output pattern given by the observed pedestrian locations, as closely as possible. The relevant sub-discipline of statistics is that of spatial data [3], and in particular that of spatial point patterns [5]. To simplify matters, a spatial point pattern can, in that context, just be thought of as a finite collection of two-dimensional points. We use the R system of statistical programming [18], and in particular the popular package “spatstat” for spatial statistics [2].

The translation of our geometrical problem into the language of spatial statistics is very straightforward: The locations immediately define a spatial point process, and each distance image defines a spatial function and thereby a covariate (or independent variable as in the more classical context of usual univariate regression). We interpret the latter locations as a spatial point process and  these weights by fitting a point process model to the observed point pattern with the “ppm” method of the spatstat R package. This function, in turn estimates the weights or contributions of each feature by fitting a Point Poisson Model to the Data with the Maximum Pseudolikelihood Method [1 and 11].The function yields a fitted model, and each covariate’s coefficient is interpreted as the desired weight. Note that this method is superior to the naive way of performing a pixel-wise linear regression because it takes the evident correlations between pixels into account. We use the “Poisson” interaction model [13] of the ppm function which is a simplification because it is the simplest model and  already yields meaningful results. Additionally, we integrate a slight non-linearity into the fitting process by taking interaction terms up to cubic order into account.

Generalisability

It should be noted the goal of the prediction is not simply to be as accurate as possible. Indeed, greater accuracy can always be achieved at the expense of generalisability: Learning more about a particular constrained design task comes at the cost of giving up the applicability to a more general design language. On the other hand, a general learned model can not adapt to the particularities of a special situation. 

Here, we have chosen to confine the study to a particular space, so that we have been leaning on the side of accuracy. See Fig. 5 for a demonstration of an arbitrarily good fit of the given data. Input fields are sine waves, and  the overlay or superposition corresponds to the terms of a Fourier series converging against a limit in Hilbert space. Here, we generated a random spatial pattern and have demonstrated extreme “overfitting” by approaching that pattern to a stunning degree, taking a large number of terms into account. On the other hand that illustration shows the power and flexibility of the simple overlay approach. Therefore, in an architectural context, the question of overfitting remains salient, imposing a strong trade-off between prediction accuracy and generalisability.

Limitations and drawbacks

While the simulation’s taxonomy, scripts and results as well as the developed prediction algorithms yield very promising results, the office space layout initially chosen for the simulation setup starts to show certain restriction and limitations. Although size and program of the simulation setup were intentionally kept quite confined in the beginning in order to better control the overall simulation and its results, later on this decision proved to be increasingly limiting.

The prediction’s accuracy increases with each additional object and feature included in the simulation, however, the small scale of the simulation space sets a clear limit to the overall number of one-channel images that can be meaningfully implemented. Not only does the intended use as an office breakout space restrict the types of possible objects and features, the size of the chosen office simulation space also sets a physical limit to maximum number of objects such a space can purposively hold. The next stage of this research will therefore seek to expand the scope of the simulation space, adding an additional office program as well as more one-channel images.

Regarding the geometric-statistical method, a possible drawback is that it does not apply immediately to optimization because on the one hand it only predicts densities which are by definition relative (their integral is one). Another drawback is that it is unclear how to determine which classes of layouts a prediction generalizes to. Thus, it would be desirable to identify either geometric, architectural or maybe even socio-cultural traits of a space which should be treated as being within the prediction scope of the algorithm.

Summary

We have described a unique approach borrowing insights and techniques from architecture, agent-based modeling, statistics of point processes, and computer graphics into a novel framework for semiological interpretation and prediction of contemporary spatial occupation patterns. The methodology introduced in this research is tailored towards measuring and simulating the social phenomena that stem from our increasingly complex built environment.

In total, we have shown that a simple process of overlaying spatial features corresponds to the statistical process of fitting the parameters of a Poisson process.

Outlook

The proposed statistical method can be described as “quantitative semiology” and has, as such, a vast field of possible applications in architecture and urbanism.

The first logical step consists in applying an optimization engine like for instance an evolutionary algorithm to exploit the prediction for “machine design”: one extracts from the predicted density a success measure linked to the functionality of the space or the architecturally desired functional outcome.  It could be defined by the amount of conversations, or by their comprehensiveness, or by some measure of the receptiveness of the design, etc. Then, a density prediction leads to a prediction of that particular chosen measure. From that point on, it lends itself to consider a larger number of possible designs or even an entire parametrized family, and to relate the outcome – the success measure – directly to these parameters. There are straightforward parameters such as sizes, distances and other quantities of geometric provenience, as well as well-studied design parameters coming, for instance, from the space syntax grammar [10]. In general, however, it becomes necessary for actual optimisation to assign some “space DNA” quantities to each proposed design. The more insightful these parameters are chosen, the more likely is the success of a machine learning strategy for associating the social functionality. Hence, one will be in a position to ask for prediction and optimization of the success of an entire design family. For this, it would be helpful to have better design measures and fitness criteria. In particular, the question about insightful and parsimonious design parameters that are suited to describe a design’s functionality remains to be answered in an interdisciplinary approach.

There is an ample spectrum of possible future research possibilities. In particular, it will be worthwhile to exploit exploitation of the more realistic 3d features of a Unity simulation, and pose the question how the agents’ behavior is influenced by their field of vision, possibly to be described in combination with an evolutionary algorithm. In the end, one will learn much more about the complexity of pedestrian behavioral patterns and their interaction with the surrounding space.

References

[1] Berman, M. and Turner, T.R. Approximating point process likelihoods with GLIM. Applied Statistics 41 31–38 (1992).

[2] Baddeley, A., Rubak, E. and Turner, R. (2015). Spatial Point Patterns: Methodology and Applications with R. Chapman and Hall/CRC Press (2015)

[3] Cressie, N., Statistics for spatial data. John Wiley and Sons, Inc (1993).

[4] Daley, D.J., Vere-Jones: An Introduction to the Theory of Point Processes. Volume I: Elementary Theory and Methods. Springer (2003).

[5] Diggle, P.J.: Statistical Analysis of Spatial Point Patterns. Arnold, London, second edition (2003)

[6] Eurostat: Science,Technology and Innovation in Europe. Luxembourg: Publication Office of the European Union, p. 115. (2013).

[7] Gilbert, N.: Agent-Based Models. Thousand Oaks: Sage Publications Inc., p. 2. (2008).

[8] Gottschalk, O., Architekt of the Quickborner Teams, Symposium “Bürolandschaft” at the documenta 12 in Kassel. (2007).

[9] Greene, C. and Myerson, J.: Space for Thought: Designing for Knowledge Workers. In Facilities, Vol. 29 Issue: 1/2, pp.19-30, (2011).

[10] Hillier, B. and Hanson, J.: The Social Logic of Space. Cambridge: Cambridge University Press. (2003).

[11] Jensen, J.L. and Moeller, M.: Pseudolikelihood for exponential familymodels of spatial point processes. Annals of Applied Probability 1 445–461 (1991).

[12] R. Kimmel and A.M. Bruckstein, “Distance maps and weighted distance transforms,” in Proceedings SPIE-Geometric Methods in Computer Vision II, San Diego (1996).

[13] Kingman, J. F. C.: Poisson Processes. Clarendon Press (1992)

[14] Kockelkorn, A.: Bürolandschaft – eine vergessene Reformstrategie der deutschen Nachkriegsmoderne. In ARCH+ Zeitschrift für Architektur und Städtebau, Vol. 186/187 (2008).

[15] Macy, M. and Willner, R.: From factors to actors: Computational sociology and agent-based modeling. In Annual Review of Sociology, 28, pp. 143-166. (2002)

[16] Neumayr, R. and Budig, M.: Generative Processes – Script Based Design Research in Contemporary Teaching Practice. In Paoletti, I. (Ed.), Innovative Design and Construction Technologies. Milano: Maggioli S.p.A., p. 172. (2009).

[17] O’Sullivan, D. and Perry, G.: Spatial Simulation. Exploring Pattern and Process. Chichester: Wiley-Blackwell, pp. 97-131. (2013).

[18] R Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.

[19] Reynolds, C.: Flocks, herds, and schools: A distributed behavioral model. In: Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques ACM. 21 (4), pp. 25–34. (1987).

[20] Silverman, B.W.: Density Estimation for Statistics and Data Analysis, In: Monographs on Statistics and Applied Probability, London (1986).

[21] Schumacher, P.: Advanced Social Functionality Via Agent-Based Parametric Semiology. In: Schumacher, P. (Ed.), Parametricism 2.0. AD 02/2016. London: Wiley, p. 110 (2016).

Symbiotic Strategies

Abstract

The concept of symbiosis, particularly parasitism, has been used quite extensively in 20^th century architecture, but mainly on an allegorical or symbolic level. This simplistic approach, however, fails to explore the intricate and multifaceted nature of various symbiotic strategies that one can find in other fields of research, such as biology, from which different symbiotic strategy within the fields of architecture and urbanism can be developed.

This paper investigates into the various forms of symbiosis, that can be found in different natural environments and speculates on how these can be adapted and operationalized as meaningful architectural and urban placement- and co-habitation strategies.

The goal is to computationally derive novel urban occupational models that operate within existing city conditions and that densify, synthesize and complement the urban fabric. Areas of interest encompass distributional logics, structural optimization, deduction of circulation patterns, programmatic distribution etc.

Suitable sites in Vienna serve as hosts for the proposed agents, whether it is an open field condition, voids in between buildings or buildings themselves, always depending on the symbiotic model chosen. Using Rhino’s Grasshopper’s genetic algorithm engine, computational models are derived from architecturally meaningful analogies to biological symbiotic models in order to develop performatively sensible, yet typologically surprising results through the rigorous application of this method. (Proto)architectural symbiotic agents are developed to swarm and infiltrate the existing cityscape (field of existing hosts). In the process of ongoing symbiosis, the symbiotic agents as well as the hosts evolve and undergo considerable changes, resulting in a changing morphogenetic cityscape.

1. Introduction

1.1 Scope of Research

The concept of symbiosis, and for that particularly parasitism, has been used quite extensively in 20^th century architecture, but mainly on allegorical or symbolic levels, essentially interpreting the relationship of buildings that sit on top of or next to other, older buildings, complimenting or contrasting them in style or material.

This rather simplistic approach, however, fails to explore the intricate and multifaceted nature of various symbiotic strategies that one can find in other fields of research, such as biology.

In contrast, this paper investigates into the various forms of symbiosis, that can be found in different natural environments, on different scales and sizes, and researches how these can be adapted and operationalized as meaningful architectural and urban placement and co-habitation strategies, with the aim to computationally derive novel urban occupational models that operate within existing city conditions in order to densify, synthesize and complement the urban fabric.

It is the working hypothesis of this line of research, that performatively sensible, yet typologically surprising results can be derived by discovering, abstracting and rigorously systematizing biological symbiotic models that show the potential for meaningful architectural or urban application within their own logic and subsequently – after having developed a precise computational growth model – by transferring and applying these abstracted models within the domain of architecture and urbanism.

1.2 Academic Research Environment

The design research documented in this paper was done within the academic environment of the Institute of Architecture at the University of Applied Arts in Vienna by students and staff of editingEIGHT – experimentarium, a design studio run by Jens Mehlan and Robert R. Neumayr, teaching advanced experimental digital design strategies. The two design projects discussed in this paper are the work of groups of students.

2. Background

This research is conducted particularly in light of the recent crucial shift within the architectural paradigm, affecting both – architectural and urban design strategies and architectural theory and education alike. The growing inability of modernism to address or let alone resolve contemporary society’s increasingly complex problems has forced architects, urbanists, theoreticians and scholars to look for radically different approaches.

This lead on the one hand to the re-evaluation of supposedly still hidden potentials of the modernist project within its own logics, a tendency, that Svetlana Boym coined “off modern”, as “[...] it makes us explore slideshadows and backalleys rather than the straight road of progress.” [1].

On the other hand, however, the then recent renunciation of linear and binary systems of perception, which for a long time had been dominating our world view, has opened up totally new areas of scientific research, changing the conception of architecture considerably and propelling the profession into a completely new paradigm. Rather than as a series of independent, absolute objects, architects have come to understand the built environment as a continuous field of interconnected elements, as one spatial organization that is able to negotiate and interpolate between those elements, which are subjected to the changing forces and currents that guide their use. As Stan Allen remarks, “Field conditions move from the one toward the many, from individuals to collectives, from objects to fields.” [2].

Within the paradigm of Parametric Design, the built environment, as we perceive it, can be read as the constructed result of a number of different layers of internal or external forces and parameters, which constantly interact and negotiate with each other in order to form the urban and architectural framework we live in. These layers can be straight forwardly architectural (e.g. functional, programmatic or typological), contextual (e.g. topographical, geographical, or orientation) or more abstract, even pertaining to different systems (e.g. political, economic, or societal). In order to be able to integrate these influences into one coherent digital design process, the aim of contemporary digital design strategies is it, to develop a dynamic, complex, and multi-layered parametric model that as accurately as possible reflects its layers’ intricate connections and relations to produce a set of malleable interconnected geometries, that consequently can be iteratively tested and refined to at some point become architectural and urban organisations.

The strength of this parametric approach lies in its understanding of architecture as a system of correlations and differentiations seeking adequate and complex articulation. As Patrik Schumacher puts it: “Just like natural systems, parametricist compositions are so highly integrated that they cannot be easily decomposed into independent subsystems – a major point of difference in comparison with the modern design paradigm of clear separation of functional subsystems.” [3].

This normally also includes the shift away from traditional platonic shapes, orders and techniques, towards a higher formal complexity, as advanced, spline-driven geometries in general have proven more adaptive to systematic adaptation.

3. Symbiotic Strategies

 3.1 Nature’s Complexity

Architectural organisations in general and urban structures in particular have frequently been described to have an intrinsic complex nature. Manuel de Landa describes them as being organized primarily around currents and lines of exchange where people, services, ideas and goods are collected, organised and redistributed in a multitude of different ways [4]. These dynamics can be analysed and described using models from various other scientific disciplines, such as mathematics, physics or biology. All these systems are to a certain extend characterized by the following properties:

Complexity: the system builds up complexity out of a series of single components. However, their interaction according to a set of simple rules and their initial condition give rise to a high level of complexity.

Emergence: the emergent properties of a system are generated by the recurring iteration and superimposition of interactions of its single components, which add up to the complex state of that system. Consequently, the result of such a non-linear process can – due to its complexity – not be predicted. This is also known as a “bottom-up” process, as opposed to a “top-down” process, in which the overall form is determined first.

Gradient transitions: a field is seen as one continuous organisational unit, which organises and modulates a series of entities, that are subjected to the same set of internal and external rules. As the parameters that drive these sets of rules vary gradually across the field, no binary conditions occur, rather gradient transitions from one state to another.

Coherence: due to their strictly rule-based generative process, resulting field conditions show a high level of coherence, not primarily (or only) in aesthetic terms, but rather in the sense that consistent conceptual and abstract logics necessarily become embedded into the system. A formal or visual coherence needs then to be understood as the result of such a process.

Modulated field conditions: a system is able to create a modulated field of different yet gradually changing densities and/or other properties that are held in a dynamic equilibrium. Emerging and receding patterns (of geometry) resulting from this system are always understood as modulations of an in itself continuous system of changing dependencies, where each modulation becomes an environmental condition (i.e. an agent of change) to their adjacent entities.

All these processes primarily and foremost show an individual capacity to give rise to emergent solutions for specific problems within their own scientific domain, but potentially also in respect to their potential to successfully operate within an architectural or urbanist context.

3.2 Symbiosis in Nature

Within this thread of research the focus lies on the field of biology, in particular on the phenomenon of symbiosis. Various forms of symbiosis can be found in different natural environments, in different scales and sizes. In biology, symbiotic strategies can be differentiated and developed according to different types and parameters [5]. The types of classification are already selected with regards to possible potentials for architectural or urban applications. For the purpose of this exercise a rather general classification as a starting point for further non-biological investigations is more than sufficient:

Differentiation according to physical interaction:

Exosymbiosis: a symbiotic relationship in which the symbiont lives on the body surface of the host (including the inner surfaces).

Endosymbiosis: a symbiotic relationship in which one symbiont lives within the tissues of the other.

Differentiation according to type of (biological) interaction:

Mutualism:a symbiotic relationship between individuals of different species where both individuals benefit.

Comensalism:a symbiotic relationship between two living organisms where one benefits and the other is not significantly harmed or helped.

Parasitism: a symbiotic relationship is one in which one member of the association benefits while the other is harmed.

Amensalism: a symbiotic relationship that exists where one species is inhibited or completely obliterated and one is unaffected.

Synnecrosis: a rare type of symbiosis in which the interaction between species is detrimental to both organisms involved.

Differentiation according to degree of dependency (and duration):

Protocooperation: a (temporary) symbiotic relationship, where two species cooperate with each other with mutual benefit, but without the need to do so.

Obligate Symbiosis: a symbiotic relationship that is vital to at least one of the participants.

3.3 Symbiotic Strategies

These various forms of symbiosis, that can be found within the field of biology, are studied, investigated and exemplified in their natural environments, in order speculate on how these can be adapted and operationalized as meaningful architectural and urban placement and co-habitation strategies. These relationships can be of different nature: conceptual, spatial, typological, programmatic, infrastructural or energy based, but also constructive or structural. They form the starting point of each of the students’ design research projects.

However, as these generic processes in themselves have arguably no capacities to solve problems outside their own domain of biology, they need to be appropriated, enhanced and transferred into the field of architecture and urbanism.

To this end the properties and potentials of a symbiotic process are at first analysed, abstracted and catalogued in order to be able to speculate about their potential to solve architectural and urbanistic problems. In a next step students try to understand and describe the process in a mathematical way, allowing them to simulate and reproduce its results in a scripted or parametric process they set up.

When transferring the process to architecture, students develop an architectural model, indicating which contextual internal and external requirements will then determine the values of the parameters that drive the emergence of these configurations. Results can then be evaluated and optimized in terms of their architectural qualities.

3.4 Microclimatic Growth Patterns

To develop valid growth strategies, that follow computable distribution logics, natural growth patterns of plants, spores, fungi, bacteria, lichens and similar biological systems are analyzed and systematized in respect to their internal logics and external microclimatic conditions. The conditions in question can be of different nature, for example climate, temperature, orientation, etc., but also distribution and/or quality and quantity of existing host elements. These logics are to be adapted for architectural and urban development strategies, focusing on the question, what would constitute favourable microclimatic conditions for distribution and proliferation of the abstracted symbiotic agent in a specific architectural or urban context?

3.5 Morphogenetic City Scapes

Based on the specific type and nature of symbiosis and the individual growth and proliferation patterns chosen by each team of students earlier on, (proto)architectural symbiotic agents and elements are developed that are able to cluster and swarm to build up field-like formations that start infiltrating the existing cityscape (field of existing hosts) or existing building structures. In the process of ongoing symbiosis, the symbiotic agents as well as the hosts might evolve and undergo considerable changes, resulting in a changing morphogenetic cityscape within the logic of diverse local microclimatic urban conditions.

3.6 Methodology

It is the goal of this design research to computationally derive novel occupational models. Apart from the interpretation and development of a specific symbiotic model as described above, a suitable site in Vienna is chosen by each group. Whether that is an open field condition, an existing brown-field, a series voids or spaces in between existing buildings or the buildings themselves largely depends on the symbiotic model chosen. In any case the existing city (or specific parts thereof) will serve as hosts for the proposed symbiotic agents.

After having discovered an architecturally meaningful analogy to the symbiotic model of their choosing, students derive a computational model of the discovered processes. For this step they are required to use Rhino’s Grasshopper’s genetic algorithm engine (i.e. Karamba! or Galapagos).

It is the working hypothesis of this research, that performatively sensible, yet typologically surprising results can be derived through the rigorous application of this method. Areas of interest may encompass distributional logics (based on solar exposure, orientation or other internal or external qualities that can be found throughout a city fabric), structural optimization (by co-relating individual units in favour of volumetric zoning etc.), deduction of circulation patterns, programmatic distribution, etc.

3.7 Structure

The design research is divided into three consecutive phases:

Abstraction:

In a first step a symbiotic process is discovered, that, once translated into architecture, still maintains its performative intelligence. As this is research in architecture, not in biology, an architectural or urban relationship between different parts that exhibit symbiotic properties needs to be extracted. At least two key parameters are identified, that subsequently must be broken down into abstract input in order to be effectively operationalized within the algorithm. Some parameters may prove to be too difficult to implement later on, therefore, it is strongly recommended to rule out those parameters that may well be of interest but will not serve the purpose of this design research exercise.

Application

In this phase the focus lies on establishing a sophisticated computational setup, finalizing the input parameters and clarifying how they can be fed into a genetic algorithm, be it Karamba or Galapagos. The aim is to find an effective way of assessing the exploratory design’s performance in order to evaluate how well it depicts the discovered benefits of the underlying symbiotic model. Adjusting the input parameters and/or starting hypothesis may well be necessary during this stage.

Rationalization

The third phase is dedicated to rationalizing the geometric output towards a credible architectural solution. The resulting geometry is not be considered as a finished architectural piece, but rather as a spatial setup of proto-architectural elements, that are assessed in terms of their performative and transformative capacities rather than in respect to their formal qualities.

4. Projects

4.1 “Siedlung Symbiosis”. Students: A. Fung, S. Ritzer and A. Staskevits

This research investigates the Banyan Tree as a parasitic symbiotic model. The tree’s seeds are dispersed by birds and germinate in the cracks and crevices of a host tree. The Banyan tree starts to grow from the top of the host tree and develops roots as it reaches the ground, finally becoming self sufficient and killing the host tree in this process (fig. 1).

Figure 1. Stages of growth of the Banyan tree

Consequently this work speculates about the spatial, infrastructural and structural implications such a symbiotic strategy can have, when applied to an existing building structure. An existing large-scale social housing block is selected as a testing ground for implementation.

In a first step additional program is distributed within different areas of the existing structure. Then Karamba! is used to simulate the areas of force flows resulting from these additional loads, subsequently culling out the unaffected parts of the structure (fig. 2).

Figure 2. Structural analysis

Superfluous structural elements are eliminated and replaced with three-dimensional continuous parasitic elements, that can serve as structure, circulation and “opportunity spaces” for the residents at the same time. Their growth is defined within void regions dictated by program addition and structural reduction. Load regions and support regions are defined within the host for the support of added program (fig. 3).

Figure 3. Algorithmic development of the parasitic structure

In a next step, following the extracted lines of force flow, a topologically optimized structure is iteratively developed through the use of finite element analysis. Branching from the primary force flow, the symbiotic structure is latched onto the periphery of the void regions, thus establishing a polyvalent connection to the existing building, forming structure, new enclosing surfaces and connection between the new programs, the void ‘oportunity spaces’, and the existing structural grid of the housing block (fig.4, fig. 5).

Figure 4. Topological optimization

Figure 5. Proto-architectural articulation

4.2 “Mycoheterotropism”. Students: M. Giradi, R. Karaivanov and M. Piaseczynska,

Sarcodes is a single springtime flowering plant commonly called the snow plant or snow flower. It is a parasitic plant that derives sustenance and nutrients from fungi that in turn attach to roots of trees. Lacking chlorophyll it is unable to photosynthesize. The snow plant takes advantage of the in itself parasitic relationship between the fungi and the tree by tapping into its network.

The research interest here lies in the phenomenon of a multi-leveled parasitic relationship and its possible implications for innovative urban strategies. The hierarchical parasitic organisation between a host (tree roots), a primary parasite (fungi) and a secondary parasite (flower) serves as the starting point to speculate about the relationship of three interdependent and interconnected urban layers, namely the urban mass, the urban void (understood here as an active agent rather than a passive space) and urban program.

The dense structure of the Viennese urban block becomes a field of experimentation where varying, quasi “micro-climatic” external parameters, such as location within the city fabric, connectivity, orientation, sun exposure and shading, accessibility, privacy and spatial qualities are played against internal parameters, such as increase of population density, transportation needs, and vertical growth strategies, in an iterative optimization process.

In the beginning existing points of transportation become nodes that start to describe the outline of a networked urban void that then in turn is populated with auxiliary programmatic functions (fig. 6).

Figure 6. Basic algorithmic setup

Within the given internal and external parameters the existing urban fabric is subsequently and iteratively altered in a digital optimization process, integrating newly introduced urban elements and resulting a considerably changed volumetric cityscape (fig. 7 and fig. 8).

Figure 7. Iterative optimization process

Figure 8. Computational result compared to initial urban fabric

In this process the current homogeneous urban massing is transformed in order to create an irreducible, smooth and continuous field, that provides higher density and interesting spatial relations between the different interwoven urban layers. The exisiting division between the different separate urban blocks gives way to a continuous mutli-layered urban fabric, that reacts to its environmental conditions (fig. 9 and fig. 10).

Figure 9. Diagram of the resulting interwoven urban layers

Figure 10. Visualization of Result

5. Conclusions

The systematic investigation of the multi-faceted and divers symbiotic relationships that exist in biology, beyond their merely allegorical use, in order to be abstracted, adapted and operationalized as meaningful architectural and urban placement- and co-habitation strategies, produces performatively sensible, and typologically surprising, yet highly experimental architectural and urban results.

Making use of contemporary digital design strategies, such as algorithmic engines, computational models can be developed and tested that operate on different scales, ranging from building scale to urban scale.

Logics derived from biological symbiotic strategies can be transferred into the domain of architecture and urbanism and give rise to solution for a multitude of different fields of interest, such as structural optimization, dynamic spatial configuration or urban distribution logics.

Acknowledgements

This paper documents one semester of design research conducted in editingEIGHT – experimentarium, a design studio run by Jens Mehlan and Robert R. Neumayr, that teaches advanced experimental digital design strategies within the academic environment of the University of Applied Arts in Vienna. All design projects discussed in this paper are the work of groups of students, who successfully completed this course. Project credits therefore also go to A. Fung, S. Ritzer and A. Staskevits, and to M. Giradi, R. Karaivanov and M. Piaseczynska.

6. References

1. Boym Svetlana. The Future of Nostalgia. First Trade Paper Edition. New York: Basic Books , 2001.

2. Allen Stan. Points + Lines. New York: Princeton Architectural Press, 1999.

3. Schumacher Patrik. Parametricism as a Style – Parametricist Manifesto. 2008. Published on: http://www.patrikschumacher.com/Texts/. Last visited 09.13.2015.

4. de Landa Manuel. A Thousand Years of Non Linear History. New York: Zone Books, 1997.

5. https://en.wikipedia.org/wiki/Symbiosis

Abstract

In a complexly networked society the architect’s core competency is the task of articulation in order to establish the built environment as a communicative frame for its users (Schumacher [9]). A such purposefully designed environment is more legible and navigable than the modernist order of repetition, thus offering a suitable framework for contemporary societal patterns of use.

The adaptation of load bearing structures following different load cases in conjunction with their differentiation according to semiological aspects afford many opportunities for differential tectonic formations, exploiting structural necessities as an instrument of semiotic articulation. Numerous examples of this phenomena can be found in pre-modernist architectural history, from simple structural ornaments and subtle surface articulations to intricately devised surface structures.

Embedded in the studio’s continuous agenda of Parametric Design Research, the project “Parametric Semiology” investigates the semiological capacity of parametrically generated architectural forms and calls for the development of radically innovative and speculative spatial models for the sport venues and their related auxiliary programmes for Rio de Janeiro’s 2016 olympic park.

Buildings are understood as highly integrated complex systems, that are inter-articulated and correlated in order to fulfil urban, architectural, structural, functional, spatial, semiotic and atmospheric criteria.

Using this setup as a testing ground, performance and semiotic aspects become the driving layers of a parametric model in order to test valid tectonic articulations for their semiological potentials. To fully exploit the concept of tectonic articulation the studio closely collaborates with structural engineers, evaluating and orchestrating suitable options. This leads to the development of a series of proto-architectural shell structures, that hold the potential to be organized and differentiated within their own structural logics as well as according to urban and architectural semiological criteria.

Results of this design research and their underlying theories, concepts, logics and strategies are presented and discussed in this paper.

Keywords: design research, parametric design, semiology, semiotics, shell structures, tectonic articulation.

Introduction

Contemporary post-fordist network society is characterized by an unprecedented level of complexity and intensity of communication. Within the context of an ongoing urbanisation process, the ability to navigate dense and complex urban environments is an important aspect of overall societal productivity today. This is facilitated best, if the visual field presents a rich, ordered scene of manifold offerings and also provides clues and anticipations about what lies behind the currently visible layers. The speed and confidence with which one can make new experiences and meaningful connections is decisive. The design of environments that facilitate such hyper-connectivity must be very dense and complex and yet highly ordered and legible. This sets the task set for the semiological project under conditions of variety, density and complexity. (see Schumacher [11])

The core competency of architecture therefore is the task of articulation. Consequently, “The relationship between the technical and the articulatory dimensions leads to the concept of tectonics.” (Schumacher [9]), meaning that technical forms, that are based on engineers’ calculations, are absorbed and further articulated by architects, aiming for increased architectural legibility within the built environment’s framework of social interaction.

At the same time, the development of sophisticated computational design tools – both within architecture and within the engineering disciplines – has opened up the field for nuanced architectonic articulation and multi-layered building configurations. Also, simpler interfaces, common programme platforms and scripting languages make parametric design and engineering technologies alike more tangible for architects, facilitating information interchange and fostering a close collaboration between different disciplines that would have been impossible a few years ago. As a consequence, it has become impossible to conceive architectural design separated from its related disciplines, such as energy design, material science, construction technologies, production techniques, and structural engineering.

In this sense, lately buildings have come to be understood as highly integrated complex systems, sub-systems and components, that are inter-articulated and correlated, complementing each other in order to fulfil architectural, structural, functional, spatial, semiotic and atmospheric criteria. Our built environment is a series of complexly interwoven layers, where a building’s structure is only of them. Functions and programmes can also be integrated by systematic differentiation of one pivotal system, which makes one system work on multiple functional layers, i.e. one series of building components might have structural and atmospheric – or semiotic – properties at the same time.

Within this development, the consequent and strategic adaptation of load bearing structures following different load cases in conjunction with their differentiation according to semiological aspects afford many opportunities for differential tectonic formations, exploiting structural necessities as an instrument of semiotic articulation.

The Structural Ornament

Numerous examples of this phenomena can be found in pre-modernist architectural history, from simple structural ornaments to subtle and intricately devised surface articulations, as structural issues have always had profound impact on a building, not only in terms of its actual form, but also in terms of its ordering elements and surface articulations. Initially facades were ordered and subdivided (and eventually signified) by structural necessities (such as pillars, columns, plinths, beams, or round, pointed or triangular arches) or material formations and patterns (such as stone or ashlar masonry). As a consequence resulting facade articulations were essentially structural.

However, over time most of these elements of ornamentation became part of an historically evolving semiotic system that allowed for an intuitive understanding of the building’s societal functions, its horizontal stratification and the processes and interactions that could take place in them. They were subject to a process of abstraction detaching them from their initial significance and thus becoming mere surface decoration.

This can be exemplified by looking at the ordering principles that were developed for the facades of the typologies of the Italian Renaissance Palazzi. Antique elements were re-contextualized and arranged according to a strict set of abstract rules in order to create a complex system of interwoven semiological elements that enabled contemporaries to unreflectingly understand the buidling’s use and program distribution.

The ground floor’s channeled rustication, for example, alludes to ancient buildings’ massive foundations and suggest a commercial use, the choice of order of columns and the height of each of the subsequent floors hint at the different social strata occupying the respective floors.

Figure 1: Palazzo Rucellai (Source: Wilhelm Lübke, Max Semrau: Grundriß der Kunstgeschichte. Paul Neff Verlag, Esslingen, 14. Auflage 1908)

Alberti’s Palazzo Rucellai was one of the first and most important palazzo types, and the ornamental organization of the Italian palazzi in general remained the dominating model for the composition of all types of representative building typologies throughout the centuries until modernism prepared itself to supersede historicism as the predominant architectural ideology, invalidating its semiological and representational concept of ornament and decoration.

As historicism could no longer find adequate answers to the societal problems of that time, within the wake of the modernist project new and different theories emerged, addressing the very same issue but suggesting totally different solutions. This era of contending ideas might be illustrated best by the famous dispute between Josef Hoffmann and Adolf Loos about the function of the ornament.

Matthias Boeckl points out that during this process “[the] erstwhile comprehensive job description holding the architect to be responsible for the concept, structural design, and form of a building disintegrated into its component parts in the process of moderinsation, which could also be construed to be a process of specialisation; Loos claimed the basic cultural idea, Hoffmann the form – but who was concerned with structural design?” (Boeckl [1]).

Beyond Modernism …

It was precisely this deconstruction of the architectural ideal into its constituent parts on the one hand, and the modernists call for establishing close conceptual connections between architecture and industrially assembled products, like ships, aircrafts or automobiles on the other hand, that gave way to an engineers’ approach to the relationship between form, force and material. First dominated by aesthetic perception (in Le Corbusier’s programmatic book ‘Towards A New Architecture’, a whole chapter ‘Eyes Which Do Not See’ (LC [3]) is dedicated to the description of the aesthetic qualities intrinsic to industrialized products), as industrial objects seemed to be able to transfer a new, much desired machine-like aesthetics to architecture, the adoption of industrial production techniques was soon to give way to a whole range of new powerful materials and technologies that would introduce “more technical beauty” (LC, ibid.) into architecture.

The beginning of the 20^th century also saw the rise of reinforced concrete as one of the most influentual building materials. Initially imitating the structural logic and appearance of the iron- or steel framed buildings of that time, engineers soon started to see the enormous morphological potential of the new material, as new elegant double-curved shell structures, started to emerge. Remo Pedreschi describes this period as being marked by the designers’ ambitions to “[incorporate] a strong desire for structural expression and structural efficiency – to make virtue out of economy. Thus they drew together form, force and architecture.” (Pedreschi [4]).

In relation to the idea of structural semiotics, this early 20^th century development however has some other interesting aspects: These structures were carefully derived from constructed physical models or based on newly developed mathematical concepts (previously structures were designed in empirical ways, mainly relying on tradition, experience and observation) that helped to explain and understand the flow of forces. That lead to an economy of means where structures were optimized according to structural necessities, allowing for an intuitive understanding of the flow of forces through the building. Shell structures allowed the user for the very first time to establish a perceptual relationship between the inside space of a building and its exterior space, as the inner space and the outer form are close to identical. The form could be understood from the inside and the outside alike.

Felix Candela, Heinz Isler, and Eladio Dieste are among the protagonists of this era, as well as Pier Luigi Nervi, whose repetitive, partly precast, yet elegant and delicate rib constructions can be read as first predecessors of today’s differentiated surface articulations.

… and Elegance.

Design research in the wake of new digital design and production strategies with their clear predilection for soft, undulating and malleable architectural forms, has only recently opened up new perspectives for both, the appreciation for shell structures and their potential for optimization and the concept of the ornamental, eventually starting to bring these two strands of research closer together.

Easily accessible software interfaces and ready-to-run scripts as well as the proliferation of advanced fabrication technologies have lead to the widespread generation of sophisticated and differentiated fields of ornamental surface articulations, that due to the increasingly seamless integration of design and production techniques finally start to blur the now long held separation between tectonics and ornamentation. However, while the use of the ornament has become more widespread, there still seems to be a lack of rigor in intellectually pursuing its underlying concepts, or – as Marjan Coletti puts it – based on historic non-figurative ornamentation “[...] a similar generative logic and morphological syntax is nowadays being embraced by parametric and scripted generative techniques to produce myriads of complex, patternised, ornamental topologies, although the endeavour […] usually drifts towards the generic and the dogmatic, and away from the phenomenological and the experimental.” (Coletti [2]).

Almost as if alluding to the inadvertent compartmentalization of the historicist idea of architecture as an all-encompassing effort by Loos and Hoffmann, Coletti identifies two different conceptual strands within the pursuit of the synthesis of digital ornamentation and tectonics, “one [propelling] towards ‘pure form’ through abstraction, [one] towards the purely figural through sensation.” (Coletti, ibid.). Both distinguish the results of contemporary digital form finding processes from representational digital visualizations in the same way a modern painting “[escapes] from the figurative in art.” (Coletti, ibid.). At the same time though, both of them pursue the rationalization of the contemporary ornament as an abstract and theoretical endeavour, that – although intellectually driven – first and foremost speaks to the sensorial and atmospheric qualities of a spatial configuration. While conceptually bridging the gap between tectonic and ornament, it still neglects – following modernism’s threefold distinction – the subject of construction and structure within architectural production. In the context of tectonic articulation it seems to be more productive to develop the underlying logics of surface articulation not as an abstract concept but rather as a goal-oriented process that starts to gradually integrate different systems and subsystems of a building into one coherent and articulate spatial configuration.

The strength of this parametric approach lies in its understanding of architecture as a system of correlations and differentiations seeking adequate and complex articulation. As Patrik Schumacher puts it: “Just like natural systems, parametricist compositions are so highly integrated that they cannot be easily decomposed into independent subsystems – a major point of difference in comparison with the modern design paradigm of clear separation of functional subsystems.” (Schumacher [8]).

The methodical development of these systems aims towards the generation of complex and parametrically controllable geometries, which contain highly adaptive potentials and connectivity (soft patterns). Variation and continuous differentiation of simple elements reflect the changing and mutually influential forces within a system’s different layers in order to eventually articulate a complex architectural system that ties together a spatial organisation, its environment, its inhabitants and their constantly changing patterns of use. This implies controlled and simultaneous development of function, form, structure and material, and requires attention on the associative qualities of all single constituents.

Thus the act of design is no longer framed by “a singular aesthetic end, but by the multiple constraints and ambitions of each project, as negotiated by the architect.” (Rahim A. and Jamelle H. [6]). Nevertheless the result still displays elegance, a contemporary elegance that is supported by articulated complexity rather than by minimalism or simplicity. Successful complex building structures are able to develop a descriptive architectural language that visually reduces the underlying complexity and helps to order, frame and organize the varying patterns of use of their users groups. “An elegant building or urban design should therefore be able to manage considerable complexity without descending into disorder.” (Schumacher [7]).

To design such an ordered architectural and urban environment has become the architect’s core competency in an increasingly complex networked society. Such a clearly articulated environment is more legible and navigable than the modernist order of repetition, thus offering a suitable framework for contemporary societal patterns of use.

Tectonic Articulation

“If we define tectonics as the strategic detournement of an element’s technically induced morphology in order to address substantial functions in the articulatory dimension, then tectonics can be redeemed and integrated within contemporary notions of handling form-function relationships. We might call this strategy of opportunizing on technical details techtonic articulation.” (Schumacher [10]).

If a building’s structure, and consequently its optimization, is understood to be only one layer of its complex and multi-layered organization, then structural expression can not be understood as an end in itself but rather as a means to differentiatedly articulate the substantial social function of the space in question. In this line of thinking, the elegant accentuation of structural elements does not hold any ideological, metaphorical, theoretical, abstract, or sensational value in itself.

Also buildings are not materialized solely to the concerns of technical and structural efficiency, which would be the structural engineer’s approach, but with the clear aim to interarticulate the building’s different systems and subsystems to form one coherent spatial organization, to achieve tectonic articulation, as it is “[the] relationship between the technical and the articulatory dimensions [that] leads to the concept of tectonics” (Schumacher, ibid.)

The Semiological Project

Studio Hadid‘s recent design research project Parametric Semiology – Olympic Park Rio de Janeiro 2016 studies the development of a series of proto-architectural shell structures, that hold the potential to be arranged, clustered, organized and differentiated according to the semiological criteria and that are further articulated within their own structural logics. Semiology and structure become the driving layers of a parametric model in order to test tectonic articulations for their semiological potentials. The Olympic Park’s complex programme, that demands structures of various sizes from large scale stadia to smalll scale auxiliary buildings lends itself to be structurally articulated through a series of related shell structures. At the same time, the vast overall scale of the Olympic Park asks for semiological articulation in order to facilitate orientation, navigation and circulation by meaningfully cohering the builidngs to form a differentiated yet continuous urban field.

In the same way that semiology and a building’s structure become one of the many different interacting layers that all together form what we today consider to be our built environment, “… the architectonic code is one of several fundamental panhuman sign systems which in concert provide individuals and groups with a multi-nodal and multi stereoscopic template for the creation of humanly meaningful realities” (Preziosi [5]).

As a consequence the goal is neither to design a structurally optimised building nor to conduct an exercise in semiological form finding, but the extension of architecture’s formal repertoire through investigation into architecture’s morphogenetic potential within a multi-dimensional solution space that is clearly delineated by previous structural research, which sets the limits for a wide range of possible forms. Parametric design aims towards the exploitation of its generative capacity rather than merely developing a method of discovering inspiring shapes.

Seen from a structural engineer’s point of view on the other hand, these processes might be used to gradually approach “a balance between aesthetic intrigue, innovation and efficiency in new structural forms” as Kristina Shea puts it (Shea [12]).

However, the resulting formal and spatial articulations always remain tectonic, i.e. they remain structurally or technically motivated, rather than being conventionalized and thus becoming ornamental articulations.

Urban and architectural shell prototypes are designed with regards to their semiological readability, based on urban, spatial, programmatic, or social parameters, that were deducted from the specific programme for Rio’s Olympic Park, developing ideas on how semiologic operations can be systematized and intensified in order to be interrelated and tectonically articulated within the framework of the different structural shell systems, that the large span constructions in question require.

Parametric Semiology

During the preparation phase students start to systematically investigate and analyze diffferent structural shell systems, evaluating and cataloguing them according to their architectural, formal, spatial, structural, material, typological, affective and effective properties and their potential to be differentiated according to semiological parameters.

At the same time they try to develop a clear understanding of the project brief and the programmatic and typological components of the Olympic Village in Rio de Janeiro, identifying a series of crucial relations of varying intensities between two or more different components or elements in the brief, that can be described using semiological differentiations.

Subsequently the objective is the development of proto-architectural shell structures, that hold the potential to be arranged, clustered and differentiated according to the semiological relations, that were identified earlier on and that will in turn drive the generation and differentiation of these elements.

During design research phase these proto-architectural shell structures are further developed. Students are required to investigate, if the intended differential qualities actually work in a small scale cluster of buildings. To that end a series of different types in different scales from the list of typologies (i.e. 1 stadium type, 1 housing type, 1 circulation type, …) is selected, arranged and differentiated within the scope of every group’s semiotic concept. The goal of this exercise is a first proof of concept of the group’s architectural hypothesis.

Students are also encouraged to look into the further differentiation of construction, surface articulations, edge conditions, perforations, openings, and ground conditions. Different semiological parameters might affect different components of the shell systems in various ways.

Figure 2: design research phase: devaulting: Testing different column formations.

Figure 3: design research phase: twoFold. Testing different folded surface formations

Figure 4: design research phase: creasedField Testing different surface articulations

During the urban research phase students develop generative strategies to arrange and further differentiate the shell structures according to the urban semiological logics that have been developed through the analysis of site, context and boundary conditions. These strategies might include: aggregation and variation (repeating, multiplying, scaling), packing, flocking, massing, orientation and direction, extremities of scale, hierarchy, sequencing, field conditions, different degrees of transparency, informed grid logics, phenomenological effects, or exploitation of perspective views. In this process organizational and navigational logics, that have been incorporated earlier on, are not discarded but further appropriated and synchronized with the site’s contextual parameters.

Finally all the research and design results are evolved into one coherent semiological design proposal, that simultaneously operates on the urban, architectural, structural, and component level.

The following student projects presented in this paper are selected from design research conducted at Studio Hadid at the Institute of Architecture at the University of Applied Arts in Vienna. Professor: Zaha Hadid. Assistant Professors: Mario Gasser, Christian Kronaus, Jens Mehlan, Robert R. Neumayr, Patrik Schumacher, and Hannes Traupmann.

Selected projects of the studio’s design research were on display at the 13^th Architectural Biennale “Common Ground” in Venice.

Project: devaulting

Students: Tudor Sabau, Jakob Travnik, Matthias Urschler

The project aims at redefining the typology of vaults as a means of creating a complex semiotic system, by which its signified content is expressed through the relationship between two fundamental layers of communication: one layer represented by a unified yet continuously differentiated ground condition based on a strict grid logic, which is working in parallel with a second layer of homogeniously differentiated shell typologies.

The project operates semiotically in various scales. On a global scale the masterplan consists of three parts: a housing zone (grided shells), a non-sport venue zone (full shells) and a sporting venue zone (cracking shells). On a local scale these zones are subdivided into ”islands” on which groups of relevant programs (shell types) are further differentiated according to their intrinsic logics. In between the islands it is the landscape that is subjected to contextual differentiation.

The programs are articulated through systematic shell manipulation, such as cracking logics, structural differentiation, material differentiation, formal operations and the adaption of figure-ground relationships. Ultimately, the resulting hierarchies result in a complex yet clear matrix of semiotic readings, which serves as direct as well as indirect guidance to inform the user of the locally, programmatically and socially relevant use of a particular space.

Figure 5: devaulting: Continuous urban field of differentiated shell structures

Project: Semantic Fields

Students: Elena Krasteva, Emanuele Mozzo, Daniel Zakharyan.

Starting off with the research of shells in nature the team decided to concentrate on mushroom structures as they offer an incredible diversity within a single type of species. Grouping Principles, structural behavior and morphological properties were analyzed, abstracted and translated into proto-architectural shell structures.

Semiologically three different layers of intervention were identified:

On the Grouping Layer the main driving force of differentiation is the application of packing principles. Depending on regulatory parameters and based on behavioural patterns different types of deformed agglomerations and necessary strategies for a controlled shell deformation are developed.

On the Shape Layer different morphogenetic parameters (height, size, inclination, …) are exploited to form a differentiated yet semiotically coherent field of shapes. To that end parametric particle spring simulation systems are used, allowing the students to create physically correct curvatures in real time interaction.

On the Surface Layer the key aspect was the transformation of different natural surface articualtions into architectural yet structurally valid components. Several types of gills (linear, additive, branching) were identified and translated into a structural system that establishes a tectonic connection between a surface’s curvature and its level of detail resolution, thus allowing for a structurally efficient and curvature-dependant distribution throughout the entire system.

Site implementation: As any activity can be defined by two main aspects, the activity itself and the connections it establishes within its surrounding, the project explores these connections and emerging relationships between the program and surrounding field and reflects them through the superimposition of these three layers. It studies how the appearance of a particular program triggers certain behaviors and reactions in the field. It examines how the field can capture programmatic identities, propagate them as a system of visual clues and articulate their presence.

Figure 6: Semantic Fields: Development stages of a proto-architectural shell structure with increasing differentiation.

Figure 7: Semantic Fields: One of the final shell strcutures housing a series of different programmes.

References

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[2] Coletti M., Ornamental Pornamentation, in Exuberance. AD 02/2010 March/April 2010, Coletti M. (ed.), Wiley, 2010. ISSN 0003-8504.

[3] Le Corbusier. Ausblick auf eine Architektur. Braunschweig: Vieweg & Sohn Verlag, 1982. ISBN 3-528-18602-X.

[4] Pedreschi R., Form, Force and Stucture – A Brief History, in Versatility and Vicissitude. AD 02/2008 March/April 2008, Hensel M. and Menges A. (eds.), Wiley, 2008. ISSN 0003-8504.

[5] Preziosi D., Architecture, Language and Meaning – The Origins of the Built World its Semiotic Organisation. Mouton Publishers, The Hague/Paris/New York: 1979.

[6] Rahim A. and Jamelle H., Elegance in the Age of Digital Technique, in Elegance. AD 01/2007 January/February 2007, Rahim A. and Jamelle H. (eds.), Wiley, 2007. ISSN 0003-8504.

[7] Schumacher P., Arguing for Elegance, in Elegance. AD 01/2007 January/February 2007, Rahim A. and Jamelle H. (eds.), Wiley, 2007. ISSN 0003-8504.

[8] Schumacher P., Parametricism as Style – Parametricist Manifesto. London 2008. Presented at 11th Venice Biennale 2008. http://www.patrikschumacher.com/ (last visited 27 04 2015).

[9] Schumacher P., The Autopoiesis of Architecture. A New Framework for Architecture. Wiley & Sons Ltd., Chichester, 2011. ISBN 789-0-470-77298-0.

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[11] Schumacher P., Architecture’s Next Ontological Innovation, in Not Nature, tarp – Architectural Manual, Pratt Institure (ed.), New York, 2012.

[12] Shea K., Directed Randomness, in Leach, Neil et al. (eds.) digital tectonics. Wiley & Sons Ltd., Chichester, 2004. ISBN 0470857293.

fellow lecturers, including antonio petrov, svetlana boym, kai vockler and marko sancanin, offered most interesting readings of past and contemporary architectural practice in eastern and central europe, whereas i myself (speaking about “from flexibility to fluidity“) could rather offer somewhat of an outside reflection on the ongoing discussions.

curator bogdan ghiu has set out to assemble a representative selection of 80 projects in an exhibition called Fluencies to investigate whether “it is possible that [...] the so rich and diverse speciality of the Central, Eastern and South-Eastern Europe represents today [...] a source of resistance to homogenization.” the result is, i think, rather disillusioning.

contemporary east and central european architecture production on the whole seems neither capable of reconstructing a long lost and desired regional identity (as it is totally devoid of any retrospective reasoning), nor of constructively continuing the narrative of regional architectural practice (as it offers no prospective nostalgia). it appears to entirely dissolve within a kind of all-european architectural best practice, unable to provide a critical contribution to what post-socialist modernism could actually mean.

dana vais notes in her essay “Secondary Modernity in Eastern [...] Europe” in the exhibition’s catalogue that “the biggest problem raised by architectural modernity in the East has been the fact that its main ingredient, i.e. technology, has never been completely mastered here.” well, it is safe to say that the east caught up, but interestingly enough  it is precisely the very few projects that still lack this “Euro-American technical titanism” (dana vais quoting peter sloterdijk here), like corvin cristian’s bar Atelier Mecanic in bucharest or alexander brodsky’s Vodka Ceremony Pavilion (which delightfully reminds me of project meganom’s barn project in russia, 2006), that suggest the biggest potentials for a productive re-reading of the regional architectural practice.

footnote: austria is represented by Bauchplan, Dietrich/Untertrifaller, Caramel Architekten,  Franz ZT GmbH, LOVE and Synn Architekten.

Fluencies: east and central european architecture. Zachi, Arpad (ed.). Editura Fundatiei Arhitext Design. Bucuresti, 2011. ISBN 978-606-92734-3-2.

http://www.east-centricarch.eu/