Modeling Semantics for Building Deconstruction

Enrico Marino

, Federico Spini

, Alberto Paoluzzi

, Danilo Salvati

, Christian Vadalà

Antonio Bottaro

and Michele Vicentino

Department of Engineering, Roma Tre University, Rome, Italy

Department of Mathematics and Physics, Roma Tre University, Rome, Italy

GEOWEB S.p.A., Rome, Italy

Keywords:

Building Modeling, BIM, Deconstruction Semantics.

Abstract:

In this paper we discuss the motivation, the technology, the design and the use-model of a novel web service

for quantity surveyors, aiming to exploit virtual and augmented reality methods to implement a “zero waste”

model, i.e. a new design paradigm where the waste materials from demolition become resources for recon-

struction. The goal of this project is to provide virtual/augmented reality tools through quick modeling of

buildings and their fast augmentation with semantic content.

1 INTRODUCTION

A tendency to minimize the humanization of new ter-

ritories and to push for reusing already built accom-

modation or accommodation which has fallen into

disuse has become a pressing need in advanced so-

cieties. We have to integrate the “zero energy” model

(each building has to produce the same amount of en-

ergy that it consumes) with the “zero waste” model,

i.e. a new design paradigm where the waste materi-

als from demolition become resources for reconstruc-

tion (Altamura, 2012). Building, contract, and design

processes need to be renewed to take account of envi-

ronmental concerns.

To reduce the impact of construction projects on

the environment, the design needs to take the issue of

building materials into consideration. Public admin-

istrations need suitable tools for the calculation and

the control of reused or disposed materials. The new

tools should handle the digital processing of materi-

als throughout the project life cycle, supporting new

project requirements such as: Design for Deconstruc-

tion, Design for Recycling and Design for Waste.

In particular, a building life cycle, underpinned by

a construction process which envisages cycles aligned

to natural phenomena is the focus of this paper.

In this work

we propose solutions that serve to

close the circle of the building life-cycle, moving

Partially supported by grant from GEOWEB S.p.A., a web

service company owned by Sogei S.p.A. and CNGeGL —

the ICT company of the Italian Ministry of Economy and

away from a traditional linear response with exces-

sively high consumption energy rates (cradle to grave)

and towards the reuse of materials in deconstruc-

tion/reconstruction (cradle to cradle), supported by

computer aided selective demolition process.

All restructuring cycles of buildings should en-

visage de-construction and re-construction steps, tar-

geted towards the replacement of materials in order

to achieve greater efﬁciency. The handling of these

materials requires appropriate encoding both for the

disposal, according to EWC (European Waste Cat-

alogue) codes, and for the planning and design of

new buildings, following BIM (Building Information

Modeling) methodology. For this purpose we need

geo-referenced scenes of augmented reality based on

fast, easily navigable and measurable 3D models.

We already have excellent knowledge about con-

struction costs (from scratch) but little is known about

replacement rates (complete selective demolition). A

modern selective demolition process requires human

intervention, with high insurance costs due to the dan-

ger involved for those working in these activities.

This latter point demands an alternative to human

effort in these process. We suggest that automated

robots could replace human effort; drones could op-

erate in a semantically familiar context and give real-

time updates as the reality contextually changes.

We believe, therefore, that there is a big need

Finance and the Italian National Board of Quantity Sur-

veyors, respectively.

274

Marino E., Spini F., Paoluzzi A., Salvati D., VadalÃ

a C., Bottaro A. and Vicentino M.

Modeling Semantics for Building Deconstruction.

DOI: 10.5220/0006227902740281

In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), pages 274-281

ISBN: 978-989-758-224-0

for modern and easy-to-use modeling frameworks for

building deconstruction in the AEC (Architecture,

Engineering and Construction) industry, to enable an

augmented reality through semantic recognition by

computer vision and by photogrammetric precision

up to centimetric deﬁnition. Such virtual/augmented

reality tools require both fast 3D building modeling

and augmentation with semantic content, in order to

be controlled in almost real time: this real challenge

is also required by the future development of the In-

ternet of Things.

In this section we have discussed the motivation of

the project described in this paper. The remaining sec-

tions are organized as follows. Section 2 introduces

a more technical viewpoint about the state of decon-

struction topics in Europe and in Italy. Section 3 de-

scribes the client application and the proposed work-

ﬂow for quantity surveyors. Section 4 illustrates the

framework architecture. Section 5 shortly recalls the

methodology, programming style and computational

environment of our geometric programming approach

to solid modeling. In the conclusion section we out-

line the work to be done and provide our forecast

about possible developments.

2 DESIGN TO DECONSTRUCT

Waste management is an issue that in recent decades

has become increasingly important, considering its

economic, environmental and energy impact.

2.1 Regulatory Framework

The European Community has deﬁned standards

[EU 98/2008, 1357/2014] and goals (qualitative and

quantitative) that Member States must comply with

through the enactment of national regulations and the

deﬁnition of economic instruments.

Waste disposal, with direct and indirect costs in-

volved, is enforced by Construction and Demolition

activities. In EWC, waste from the demolition of

buildings [955/2014 EU] are identiﬁed as class 17

– Construction And Demolition Wastes. This clas-

siﬁcation allows a correct identiﬁcation of both the

waste generated from adoptable demolition modes,

and the waste produced by actions of re-use, recycling

or landﬁlling.

The regulatory framework for waste management

is far from clear, in particular in the Italian national

context. Despite its direct and indirect costs, the land-

ﬁll is often preferred rather than risking administra-

tive or criminal penalties for failure to comply with

unclear rules.

2.2 Proposed Approach

Given this cumbersome regulatory framework, our

project is promoting the use of simpliﬁed IT tools to

support the deconstruction. In particular, a quick sim-

pliﬁed geometric modeling of the building allows for

integration of a semantic description of component

parts and their materials. Virtual/Augmented Reality

strongly helps overcome the administrative difﬁcul-

ties, provided the correct identiﬁcation of the waste

produced. This approach will increase the adoption

of virtuous actions, namely the recovery and reuse.

In particular, a geometric modeling of the building

allows to identify: (a) cost / income resulting from al-

ternatives of recycling / re-using instead of disposal;

(b) the composition and integration of information

useful to the planning of construction activities; (c)

achievement of the thresholds of reuse / recovery re-

quired by the regulations; (d) ability to economically

compare different options.

We started by considering the SMARTWaste sys-

tem (Hurley, 2002). Their approach allows to derive

estimates of the quantities of materials by providing a

description of the type of building and the area where

it was built. With this information, the forms that pro-

vide an aggregated representation of the data of inter-

est are automatically ﬁlled.

Our approach to deconstruction conversely pro-

vides both a geometric modeling of building subsys-

tems and components and a semantic annotation with

construction materials, like a sort of simpliﬁed BIM.

As a matter of fact, our national construction indus-

try is strongly heterogeneous, so that we need a pretty

detailed modeling to obtain enough accurate informa-

tion. One vantage point of this approach is an incre-

mental iterative character, where each modeling stage

may be followed by validation of partial costs.

A complete report about using BIM as a building

deconstruction approach is provided by (Galic et al.,

2014). A study on the usage of BIM as a support for

Design for Deconstruction is carried on by (Akinade

et al., 2015). In this setup, on the contrary to what

holds for us, deconstruction has to be a major concern

starting from the beginning of the building design.

A large corpus of specialized literature exists

about BIM for existing buildings. A very interest-

ing review paper, discussing hundreds of references

is (Volk et al., 2014). Its abstract states that: “While

BIM processes are established for new buildings, the

majority of existing buildings is not maintained, re-

furbished or deconstructed with BIM yet. Promising

beneﬁts of efﬁcient resource management motivate

research to overcome uncertainties of building condi-

tion and deﬁcient documentation prevalent in existing

buildings.”

Modeling Semantics for Building Deconstruction

275

The Metior (from Latin: to measure or esti-

mate) project, introduced in this paper, is exactly

aiming to overcome such difﬁculties, via (a) the de-

sign and implementation of a web service providing a

strongly simpliﬁed user-interface, designed for quan-

tity surveyors; (b) storing a growing database of tem-

plate plugins for more geometrically complex build-

ing parts; (c) using an extensible geometry engine and

server based on decades of research; (d) offering ﬂex-

ible semantic additions via specialization of IFC (In-

dustry Foundation Classes (ISO, 2013)) classes asso-

ciated to building subsystems and parts.

Metior speciﬁcally targets quantity surveyors. In

fact, although large sites to be deconstructed are op-

erated by main contractors, where skills and spe-

ciﬁc tools might be widely available and already

used, most of deconstruction activities, and hence the

largest amount of waste material produced, are man-

aged by quantity surveyors from small or medium

companies — or even by single professionals. Such

kind of ﬁrms may need to be supported with tools

where the complexity, both bureaucratic and techni-

cal, have to be hidden although correctly managed.

3 DECONSTRUCTION APP

A deconstruction oriented to the maximum reuse of

materials must be supported by a workﬂow that guides

the user towards estimating the costs of the process.

The aim is the determination of building demolition

costs, depending also on transportation and disposal

of materials.

3.1 Workﬂow

Project Deﬁnition. The ﬁrst phase of the modeling

process is a gross description of the building, in or-

der to provide basic clues for a correct attribution of

the semantic attributes. In particular, we ask for: the

apparent age, the style of construction, the historic

use register, and the geolocation. The estimated age

and the style of construction are used to determine

the needed data about the used materials; the record

of use destinations allows to reconstruct the hazard

notes of the items to be disposed of; geolocation ﬁ-

nally allows to ﬁnd out the recycling facilities closest

to the site.

Building Modeling. The user describes the con-

struction using some predeﬁned classes of elements,

either instantiating some predeﬁned parametric plug-

ins or through wire-frame input of 2D layouts. First

is deﬁned the building skeleton (backbone), i.e. the

set of beams and columns or load-bearing walls, pro-

viding the structural grid. On its horizontal sections,

the user speciﬁes the exterior and interior walls (ver-

tical enclosure and partitions), on which the ﬁxtures

are positioned (horizontal communications). Ceilings

and ﬂoors (horizontal partitions) are instead automat-

ically generated from the topology (1-boundary) of

the 2-skeleton of the ﬂoors (subsets of 2-cells). Fi-

nally, various elements such as stairs, elevators (ver-

tical communications), foundations and roofs (hori-

zontal enclosures) are placed, using ad-hoc templates

interactively provided by Metior’s plugin server, for

appropriate sizing and part dimensioning.

Semantic Annotations. At this stage (see Figure 1)

the previously inserted elements are annotated seman-

tically by means of references to database of mate-

rials, including densities. The annotation may con-

sists of one or more materials, including percentages.

For disposal control imposed by regulations, the user

should assign one / more EWC codes and degrees of

dangerousness (see Section 2.1). In this stage it is also

assigned a pair of links that refer to the time schedule

for disposal of building components.

Figure 1: Graphical interface for semantics annotation.

Augmented Reality Visualization. After modeling

and attribution of semantics to components, the quan-

tity surveyor can validate the entire model by spatial

merging into a 3D point cloud (see Figure 2) previ-

ously obtained by using ﬂying drones for the exte-

rior, or 3D laser scanners for the interior. In this way

one can assess the adhesion of the modeled building

structure to reality, possibly retracing to some previ-

ous step if the result is still not satisfactory.

3.2 Process Output

Once the work is done and the model geometry is

validated, the application provides a ﬁnal report. In

particular, the ﬁnal report will allow the quantity sur-

veyor and/or the other professionals involved in the

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276

Figure 2: A model inside a point cloud.

deconstruction design team, to determine whether

the decision taken is convenient both economically

and/or environmentally.

The ﬁnal report consists of four documents. (i) An

estimate of volumes and weights of materials, com-

puted by appropriate integration calculations, based

on the geometry of components and annotations de-

ﬁned on them. (ii) An estimate of demolition costs,

including disposal and recovery. Starting from vol-

umes and densities of materials, and from EWC codes

and hence the mode of disposal, it is estimated the

cost of the contribution to landﬁlls. (iii) The trans-

portation costs to move the materials to the closest

landﬁlls, taking into account the geographical posi-

tion of the building, and by calculating the most con-

venient road routes. (iv) An estimate of the expected

time for the complete demolition of the building, lo-

cated on a Gantt chart. Semantic annotations are also

used to generate a schedule of the demolition activi-

ties by means of a PERT program.

4 DESIGN AND ARCHITECTURE

Workﬂow and requirements described in the previous

section have been received in a prototypal application

serving as proof of concept. With the aim of maxi-

mize accessibility for quantity surveyors, it is strongly

web based and runs in all modern browsers. It is built

using React by Facebook and the unidirectional data

ﬂow design pattern (Abramov, 2016): it ensures the

best code maintainability and debuggability by cen-

tralizing access to the application state in a single con-

troller.

4.1 UI and User Experience

The web application presents itself as a simpliﬁed

CAD software, where the user interface comprises

three main areas of interaction: toolbar, canvas and

sidebar, as shown by Figures 3 and 4.

Figure 3: Metior user interface: 2D canvas.

Figure 4: Metior user interface: 3D canvas.

From the toolbar the user can access functionali-

ties related to: project life cycle (new, save, load);

project editing (show-catalog); view/interaction

mode switching (2D, 3D); interaction mode changing

(selecting, pan, zoom).

The canvas is the area in which the user can in-

teract with actual model data. It supports two dif-

ferent views and interaction modes. In 2D-mode the

model is displayed as a 2D projection from the top,

and the interaction consists of element insertion, se-

lection and editing (according to speciﬁc plugin inter-

action prototype, see Section 4.2). In 3D-mode a 3D

model can be inspected and navigated, respectively

via trackball or ﬁrst-person interaction style, while

object picking allows for element selection.

The sidebar shows the properties of the currently

selected element. In the properties panel it is possible

to view the description of the element, to add/remove

metadata, and to modify any property. The latter is

the interaction mode that allows the user to associate

semantic annotations to every part of the model.

4.2 Plugin-architecture

The application has been designed to provide a small

set of core interaction functionalities and to encapsu-

late the generation logic for architectural components

(from the very basic to the most articulated) into spe-

ciﬁc plugins.

A plugin is a software component that can be

seamlessly integrated into the system in order to ex-

tends its capabilities. In Metior, a plugin represents

an architectural element that extends the Building In-

formation Model design. Technically, a plugin repre-

Modeling Semantics for Building Deconstruction

277

Table 1: Plugin examples according to taxonomy.

inside over / free

linear pipe electrical-conduit

ver. area window, door wall

hor. area light-panel ground, ceil

volume pillar staircase

sents a prototype (namely a “class” in Object Oriented

Programming) of a construction element that can be

inserted (“instantiated”) into the canvas, thus deﬁning

a new element, i.e. a new component of the model.

Plugin Deﬁnition. A plugin is described by the fol-

lowing eight properties: (1) a unique name; (2) a

description; (3) a set of metadata; (4) the occupa-

tion type (one among linear, area or volume); (5) the

placement type (inside or over); (6) a set of speciﬁc

properties mapping the semantic to associate to the

plugin; (7) a generating function that returns the 2D

representation of the element in SVG format, to be

used in the 2D-mode; (8) a generating function that

returns the 3D representation of the element in OBJ

format, to be used in the 3D-mode.

Plugins Taxonomy. The plugins can be organized

according to occupation type and placement type.

In the occupation type three different kind of plu-

gins can be identiﬁed: linear, area or volume plugins.

The linear ones extend in one dimension (unless a ra-

dial thickness) (e.g. hydraulic lines, electrical cables).

The area plugins extend in two dimensions (unless a

linear thickness), (e.g. separation elements). They

can be divided into horizontal area (e.g. ﬂoor and

ceil), and vertical area, (e.g. walls). The volume plu-

gins extend in three dimensions. They can be ﬁxed

volume, (e.g. a piece of furniture) and scalable vol-

ume, that can be scaled (proportionally or not), (eg.

pillars, staircases).

The occupation type determines a different way to

instantiate and to insert the plugins into the canvas.

In particular, in 2D-mode, linear plugins are inserted

drawing lines by mean of a drag&drop interaction; the

area plugins are inserted drawing the bounding-box

of the element by mean of a drag&drop interaction;

the volume plugins are inserted picking the position of

the element by mean of a point&click interaction, and

adjusting their dimensions modifying the bounding-

box by drag&drop.

The placement type determines if the element can

be inserted into the canvas in a speciﬁc point occu-

pied or not by other elements. In other words, the

placement type determines the relationship between a

new instance of a plugin and instances of other plu-

gins previously added to the model. The relationship

can be of two kind: inside or over. Plugins belonging

to the inside category can be added only inside other

element (that can be linear, area or volume); e.g., a

“window” is a “volume inside vertical area” element,

while an “hydraulic line” is a “linear inside horizon-

tal area” element. Plugins of the over category can be

added only over other elements (of any type); e.g., a

“pillar” is a “volume over horizontal area” element,

while an “electric panel” is a “volume over vertical

area” element.

In the design phase, an element that doesn’t meet

the placement constraints deﬁned by the placement

type is notiﬁed by the system as a visual warning,

showing its bounding-box in semi-transparent blinked

red color.

HTML5

WebGL

SVG

Client

PyPlasm

LAR

Server

parameters

JSON + .svg

Plugin - wall

Plugin

pitched-roof

Plugin

...

3Dgf

2Dgf

JSON + .obj

Figure 5: Client/Server architecture for server-side model

generation.

Plugin Speciﬁc Properties. Each plugin has a set

of speciﬁc properties of the building elements it rep-

resents. Each property is deﬁned by (1) a name, (2)

a type, such as “number”, “text”, “boolean”, or “cus-

tom”, and by (3) a value. According to its type, each

property value can be inserted in different ways. For

example, a boolean property value is set through a

checkbox, while a textual property is set through a

text box.

The system is designed to accept custom kinds of

property. A custom property is required to deﬁne the

component of the UI that permits the user to insert its

value. For example, a “color” property can be intro-

duced by deﬁning a UI component composed by three

text boxes (one for each RGB components), while a

“length” property can be introduced by deﬁning a UI

component including a text box for the value and a

drop-down menu for the unit of measure.

The speciﬁc properties of an element can be edited

in the relative panel in the sidebar, once the element

is selected in the canvas.

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278

4.3 Plugin Catalog

It is pivotal to provide the system users with a rich

catalog of plugins, to cover all the basic as well as

the most advanced modeling requirements. Table 1

reports examples of plugins arranged according to the

taxonomy introduced in Section 4.2.

4.4 Server-side Models Generation

Both the 3D and 2D model generations have been

designed as asynchronous. The actual result of the

invocation of a generating function is not the gener-

ated model itself, but rather a promise of the expected

result. Such a design choice is important since the

computation for model generation may require some

while. In the meantime the user must be able to in-

teract with the interface, which in turn must remain

responsive. Relying on this architecture, generation

of the models can be easily delegated to a server (as

shown in Figure 5), thus relieving the client from the

burden of onerous computations. The server exposes

a REST-like HTTP-based JSON API to the client.

The plugins span from the client to the server, since

the 2D and 3D generating functions ( 2Dgf and 3Dgf )

deﬁned by the plugin are actually executed on the

server, as shown in Figure 5.

4.5 Plugin Examples

Figure 6 shows the plugin used to generate concrete

spiral stairs, with steps from coded update of a poly-

hedral approximation of a larSolidHelicoid(),

minor and major radiuses (r and R) and int number

of steps. The nturns ﬂoat is in radians.

Figure 6: (a) The generating function of a strongly parame-

terized spiralStair; (b) default spiralStair.

Figure 7: A spatial concrete frame generated, from a small

.csv ﬁle, by the pyplasm plugin spatialFrame.

The model generated by a plugin for automatic

generation of spatial concrete frames is shown in Fig-

ure 7. In this case the user interface produces a

small .csv ﬁle specifying, for each component pla-

nar frame, the grid-like pattern of members, the 2D

sections of columns and beams, and the proper roto-

translation, i.e. the four numbers α, tx, ty, tz that in-

stantiate each frame in the reference frame of the

previous one. The connecting beams are automati-

cally generated, and the various classes of members

(foots,timbers,columns,linkBeams) are made

available for interactive picking and possible local

modiﬁcation of geometry and/or materials by the sys-

tem user, and of course, for quantity surveying.

5 SOLID MODELING

The server-based geometric core of the modeling ar-

chitecture is based on a set of python libraries, includ-

ing pyopengl, scipy, pyplasm and larlib, that pro-

vide our current implementation of the LAR (Linear

Algebraic Representation) scheme for solid model-

ing, 3D imaging and mesh representation, and which

is brieﬂy described in the following.

5.1 Linear Algebraic Representation

LAR is a general-purpose representation scheme (Di-

Carlo et al., 2014) for geometric and solid modeling

introduced recently. The domain of the scheme is pro-

vided by dimension-independent cellular complexes,

while its codomain is that of sparse matrices, stored

using either the CSR (Compressed Sparse Row) or the

CSC (Compressed Sparse Column) scipy’s memory

format. The LAR polyhedral domain coincides with

complexes of connected d-cells, even non-convex

and/or including any number of holes.

The very general shape allowed for cells makes

the LAR scheme notably appropriate for solid model-

ing of buildings and their components. E.g., the whole

frontage of a construction can be described as a sin-

gle 3-cell of its solid model. Also, the algebraic foun-

dation of LAR allows not only for fast queries about

Modeling Semantics for Building Deconstruction

279

incidence and adjacency of cells, but also to resolve—

via fast SpMV computational kernels—the boundary

extraction of any 3D subset of the building model.

It is worth noting that LAR provides a direct

management of all subsets of cells and their physi-

cal properties trough the linear spaces of chains in-

duced by the model partitioning, and their dual spaces

of cochains. The linear operators of boundary and

coboundary between such linear spaces, suitably im-

plemented by sparse matrices, directly provide, de-

pending on the dimension of the mapped spaces, the

discrete differential operators of gradient, curl and di-

vergence, while their product gives the Laplacian (Di-

Carlo et al., 2009).

5.2 Geometric Computing of Shape

Our computational environment is strongly ori-

ented towards the most general parametric model-

ing of component shapes of buildings. This atti-

tude is produced by two Python libraries, that pro-

vide a dimension-independent algebraic calculus with

shapes (pyplasm) and their representation in the LAR

scheme (larlib).

PLaSM (Paoluzzi et al., 1995; Paoluzzi et al.,

2003), which stands for Programming Language for

Solid Modeling, is a geometry-oriented extension of

Backus’ FL language (Backus, 1978; Backus et al.,

1989). PLaSM is a project developed in the nineties in

the framework of Building Technologies Project (“PF

Edilizia”) of the Italian National Research Council.

The pyplasm module (2006) is the C++ porting of

PLaSM to Python via SWIG wrapping.

On top of the Scipy/Pyplasm stack we started

(2012), using literate programming methods, to build

a set of software modules, named larlib, and us-

ing the LAR scheme. This library supports topolog-

ical queries and physical properties of meshes and

complexes, including integration of polynomials over

the boundary of any chain of cells. For interactive

visualization it relies on the pyplasm viewer, based

on OpenGL. A porting of the most engaging parts

of larlib to Julia, the last-generation programming

language for scientiﬁc computing (Bezanson et al.,

2014) started very recently, with the purpose of taking

advantage of the great computational efﬁciency and

parallelism of Julia in more demanding applications.

5.3 Plugin Server Framework

Our building deconstruction framework has a web-

based client-server architecture, discussed in Sec-

tion 4. Metior, the web client application, is illus-

trated in Section 3. The server-side of the framework,

discussed in this section, is a plugin server written in

Python, which capitalizes on the stack of geometric

programming tools described above.

The Metior user quickly develops a 3D hierarchi-

cal assembly of different parts of the building en-

velope, as well as the horizontal and vertical parti-

tions, using very simple 2D drawing tools. The more

geometrically complex parts of the construction are

conversely set up by user picking from context-based

boards of predeﬁned plugin templates, that are Python

scripts (see Figure 6) generating solids models which

are interactively dimensioned, either using 2D draw-

ing tools, or by user’s numeric input from keyboard.

Of course, our list of plugin templates embraces

most of building parts that are not manageable for

quick shape input via 2D interaction. In particular, the

picking boards include templates for planar concrete

frames, spatial building frames, building foundations,

roofs and stairs of different types, attics and dorm-

ers, ﬁreplaces and ﬁtted wardrobes, shover cabins and

sanitary equipments, doors and windows, etc.

It is worth noting that, by virtue of the great

expressiveness of the PLaSM operators and its

functional style of programming and dimension-

independent geometry, the development of a new plu-

gin template is very easy even for non-experienced

programmers, and usually requires a tiny amount of

time and code, that may range between 4-8 hours, and

between 10-100 lines of Python/pyplasm code.

Two important points we would like to remark

are: (a) the great expressive power of the geo-

metric language, strongly empowered by currying,

i.e. by translating the evaluation of a function—

that takes either multiple arguments or a tuple of

arguments—into evaluating a sequence of functions,

each with a single argument; (b) the ease of devel-

opment. Python/pyplasm is used even to teach ge-

ometric programming to K12 students (Solin, 2016)

(see ??https://nclab.com/3d-gallery/). Sev-

eral plugin templates used by Metior were developed

in class by students, in the framework of the computer

graphics course being taught by one of authors.

6 CONCLUSIONS

In this paper we have introduced a software architec-

ture and framework to be used in design for building

deconstruction. The immediate goal is to provide an

advanced web-service for quantity surveyors, called

to make reliable and accurate estimates of economic

and environmental returns from unused buildings, ac-

cording to new waste material regulations and to poli-

cies for land use control.

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280

The reader may have easily seen that the Metior

framework can be used as a simpliﬁed BIM instru-

ment for renovation projects in existing buildings, and

even for new design projects. Metior, currently in pro-

totype development, is based on advanced technolo-

gies for web services and applications, and on recent

developments in geometric computing. It is worth-

noting that Metior might provide a basis for more

demanding undertakings, in particular in a national

scene in strong need for new large programs of reno-

vation and seismic adaptation of its built heritage.

REFERENCES

Abramov, D. (2016). Redux: predictable state container for

javascript apps. http://redux.js.org/. Accessed: 2016-

11-09.

Akinade, O. O., Oyedele, L. O., Bilal, M., Ajayi, S. O.,

Owolabi, H. A., Alaka, H. A., and Bello, S. A. (2015).

Waste minimisation through deconstruction: A bim

based deconstructability assessment score (bim-das).

Resources, Conservation and Recycling, 105:167–

176.

Altamura, P. (2012). Gestione eco-efﬁcace dei materiali

da costruzione nel ciclo di vita del fabbricato. PhD

thesis, Sapienza Università di Roma. (in Italian).

Backus, J. (1978). Can programming be liberated from the

von Neumann style?: a functional style and its algebra

of programs. Commun. ACM, 21(8):613–641.

Backus, J., Williams, J., Wimmers, E., Lucas, P., and Aiken,

A. (1989). FL language manual, parts 1 and 2. Tech-

nical report, IBM Research Report.

Bezanson, J., Edelman, A., Karpinski, S., and Shah, V. B.

(2014). Julia: A fresh approach to numeric comput-

ing.

DiCarlo, A., Milicchio, F., Paoluzzi, A., and Shapiro, V.

(2009). Chain-based representations for solid and

physical modeling. Automation Science and Engi-

neering, IEEE Transactions on, 6(3):454 –467.

DiCarlo, A., Paoluzzi, A., and Shapiro, V. (2014). Lin-

ear algebraic representation for topological structures.

Comput. Aided Des., 46:269–274.

Galic, M., Dolacek-Alduk, Z., Cerovecki, A., Glick, D.,

and Abramovic, M. (2014). Bim in planning decon-

struction projects. eWork and eBusiness in Architec-

ture, Engineering and Construction: ECPPM 2014,

page 81.

Hurley, J. W. (2002). How to smartwaste the construction

industry. In 10th Symposium Construction Innovation

and Global Competitiveness, Conference Proceedings

for the 10th Syposium Construction Innovation and

Global Competitiveness.

ISO (2013). Industry Foundation Classes, iso 16739:2013.

http://www.iso.org/iso/catalogue_detail.htm?csnum

ber=51622. Accessed: 2016-12-29.

Paoluzzi, A., Pascucci, V., and Vicentino, M. (1995). Geo-

metric programming: a programming approach to ge-

ometric design. ACM Trans. Graph., 14(3):266–306.

Paoluzzi, A., Pascucci, V., Vicentino, M., Baldazzi, C.,

and Portuesi, S. (2003). Geometric Programming for

Computer Aided Design. John Wiley & Sons, Inc.,

New York, NY, USA. 815 pages.

Solin, P. (2016). https://nclab.com/3d-gallery/,Creative

Computing Platform: Learn Coding and 3D Model-

ing! Accessed: 2016-11-12.

Volk, R., Stengel, J., and Schultmann, F. (2014). Build-

ing information modeling (bim) for existing buildings

— literature review and future needs. Automation in

Construction, 38:109 – 127.

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