Leveraging virtual design and construction (VDC) for multi-physics modeling and
multidisciplinary design and optimization (MDO) of sustainable built environments
Engineering or Business Problem
A shift in the management and operation of built infrastructure (buildings, heavy civil
infrastructure, etc.) is underway worldwide. This shift is expanding the scope of management
responsibilities from industry silos to whole lifecycle responsibility. This shift is enabled, in part,
by a number of trends, including (i) the decreasing cost and increasing capability of ubiquitous
monitoring and sensing, (ii) the increasing ability to collect, store, and process large amounts of
data, (iii) a set of improved computational modeling tools that enable high fidelity, predictive
modeling of built infrastructure, (iv) the proliferation of online educational resources, (v) the use
of broader measures of performance that directly relate to user value, and (vi) a growing
acceptance of new forms of financing and governance that blur the boundaries between private
and public investment.1,2,3,4,5,6,7
There are six basic questions that confront managers of the built environment during the often
decades-long operation phase of their facility. The six trends discussed above can be leveraged to
answer these questions with greater speed and accuracy than ever before.
(1) What upcoming projects (i.e., refurbishment, replacement, etc.) will need to be undertaken
(or could be beneficial) on a building or facility?
(2) Where (spatially and financially) on the facility will these projects need to be performed?
(3) When will these projects need to be implemented?
(4) How can these projects be best completed (i.e., traditional versus innovative maintenance)?
(5) Who among the current staff, or what new skill sets, will be needed for the project?
(6) Why is this project needed (e.g. what are the economic, social, or environmental
consequences of delaying or foregoing projects)?
Four of these questions, the “what”, “where”, “when”, and “why”, require the prediction of future
events. Such prediction includes the effects of future environmental exposure (rain, humidity,
temperature, corrosives, etc.), the future failure of built facilities (water leaking through facades,
corroding structural systems, etc.), or the cost and effectiveness of future repair and maintenance.
Currently, the prediction of future conditions or failures of built
infrastructure relies on past experience, rules-of-thumb, statistical
methods (e.g., Markovian models) or empirical models (e.g., Fickian
diffusion of moisture).8,9,10 These rudimentary approaches lead to
unanticipated failures occurring throughout the built environment. One
such example is the current façade corrosion and spalling failure on the J.
Edgar Hoover Building in Washington, DC (Figure 1). The
architecture/engineering/ construction (AEC) community is far behind its
counterparts in the automotive or aerospace industries in leveraging
advanced physics-based modeling tools to computationally design,
optimize, and manage long-lasting capital-intensive investments.11
Theoretical and Practical Points of Departure
CIFE has long been a research leader in the development of
computational models and tools to support the design and construction of
the built environment. This leadership has introduced many
Lepech, Kiremidjian
VDC Multi-physics Modeling
Figure 1. Façade
corrosion and
spalling on the
Hoover Building in
Washington, DC
2
advancements to the AEC community, including Building Information Modeling (BIM), Virtual
Design and Construction (VDC), and most recently multidisciplinary design optimization
(MDO).12 This proposal looks to expand the application of computational modeling tools from
design and construction into the operation and maintenance of built environments through the
first integration of multi-scale multi-physics computational modeling tools, Revit®, and MDO.
Multi-scale multi-physics modeling
Recent advances in computational performance, material science, and structural engineering
research have enabled interdisciplinary computational linking in the form of “multi-scale multiphysics models” of the built environment. Such models include integrated models of related
physical phenomena. Through multi-scale multi-physics modeling, it is gradually becoming
possible to predict the performance of built environments over time based on fundamental
material characteristics (i.e., concrete diffusion coefficient), environmental loads (i.e.,
temperature profiles, chemical exposures), and mechanical loads (i.e., gravity, wind,
earthquakes). Such models can also relate future performance with physical and chemical
processes taking place on microstructural, to component, to
structural scales. Working with
international collaborators, PIs
Lepech and Kiremidjian have
developed
a
computational
modeling suite for predicting the
deterioration,
corrosion
and
structural
degradation
of
reinforced concrete (Figure 2).13
The programming architecture
is based on multi-physics linking
of
individual,
science-based
models that describe actual
physical phenomena and are
Figure 2. Multi-scale multi-physics reinforced concrete
organized into modules. To
deterioration modeling architecture
establish links between the
individual modules, a backbone data interface module has been created in Matlab that allows for
passing of information from one module to another, thereby allowing for concurrent simulation
of complete building systems. This includes detailed information on micro-scale phenomena up
to structural-scale response. Using an API interface, data translation and easy exchange (“plugand-play”) between individual modules is possible and thereby creates a collaborative platform
for other researchers to test and contribute to the work.
Linking multi-scale multi-physics modeling with Revit®
The multi-physics modeling software used to simulate the “transport and chemical” and the
“material performance” modules shown in Figure 2 is COMSOL. COMSOL is a finite element
package specially formulated for solving coupled, or multi-physics, phenomena (i.e. coupled
transport of heat and moisture). COMSOL currently provides an interface for transferring
element geometries from projects in Revit®. One example application of this link between
Revit® and COMSOL has been the modeling of acoustic pressure levels in a room due to a
Lepech, Kiremidjian
VDC Multi-physics Modeling
3
loudspeaker system (Figure 3). The model geometry
was created in Revit® and modeled using COMSOL.14
Currently missing from this link between COMSOL
and Revit®, however, is a time-dependent modeling
capability.
For problems that have steady-state
boundary conditions that do not change over the
solution time, such as the acoustic pressure distribution
in a room, the existing COMSOL-Revit® software link
is adequate. However, for time-dependent problems, a
solution that advances in time is required. For example,
Figure 3. Multi-physics model of
the movement of moisture through a reinforced concrete
acoustic pressure levels in a room
facade or the formation of rust on reinforcing steel is
14
due to a loudspeaker system
dependent upon both the current conditions (i.e.
temperature, humidity, etc.) and the progression of moisture or corrosion up to that time. Such
modeling of decades-long phenomena is not possible with current software architectures.
Also not supported are links between Revit® and the two software tools which make up the
“mechanical performance” and “structural performance” modules shown in Figure 2. These
software tools are Diana FEM and OpenSees, respectively. By leveraging the existing links
between COMSOL and Revit® and COMSOL, Diana FEM, and OpenSees, an integrated
software suite is proposed that will allow for decades-long modeling of built facilities based on
fundamental material properties, environmental exposure, and mechanical loads.
Multi-objective Optimization based on Long-term Built Environment Performance Models
Multidisciplinary Design Optimization (MDO) involves the formalization of design coordination
and iteration for groups working on complex engineering systems, such as buildings and civil
infrastructure. Computational optimization techniques are applied to systemically search through
a range of design options to find solutions that best meet the objectives and constraints of project
stakeholders. MDO methods were first developed in the aerospace industry in the 1970’s and are
now successfully used in a number of fields including automotive and electronics design.15
Flager et al. have showed that MDO methods can reduce life cycle costs of a commercial
mid-rise building by 5% and environmental impacts by 7%.16 Basbagill et al. applied MDO,
sensitivity analysis, and a novel impact reduction method to show how conceptual design
decisions determining building embodied energy compare with one another.17 Most recently,
Basbagill and Lepech have used MDO methods to show embodied versus operational
environmental impact tradeoffs of building design decisions.18
Never before has MDO been able to consider the long-term tradeoffs of design decisions of
the built environment with such detail as provided by the integration of MDO with multi-physics
modeling and Revit®. Multi-physics models allow designers to predict (deterministically or
stochastically) future performance, and the time of future repairs or maintenance. When
incorporated with previous CIFE work by Flager, Basbagill, and others, multi-physics prediction
enables MDO genetic algorithms to more accurately determine the optimal design parameters of
the built environment at the material science scale, building component scale, or facility scale.
Research Methods and Work Plan
Task 1 – Computational Linking of Revit® with Multi-Scale Multi-Physics COMSOL, Diana FEM
and OpenSees Models
Lepech, Kiremidjian
VDC Multi-physics Modeling
4
As mentioned previously, a computational link between COMSOL and Revit® currently exists
for some classes of multi-physics problems. Task 1 will enable time-dependent multi-physics
modeling of building materials, components, and structures using Revit® geometries. Matlab is
the computational engine that currently runs the modeling architecture shown in Figure 2.
Building on this architecture, Matlab will be used to call the COMSOL-Revit® interface and
enable time-dependent modeling of Revit®-constructed building elements. A significant part of
this task will be the definition of varying exposure conditions on Revit®-defined object surfaces
(i.e. changing temperature profiles, changing moisture profiles, etc.) This work builds upon years
of research conducted by the PIs and their collaborators in the development of the multi-scale
multi-physics modeling suite shown schematically in Figure 2.
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Task 2 – Modeling of Precast Concrete Building Façade Panels Exposed to Temperature, Sun
Exposure, Moisture, Chloride Exposure and Gravity Load
Precast concrete building façade panels are a common building envelope component. As shown
in Figure 1, a combination of thermal, hygral, chemical, and mechanical loads can lead to serious
deterioration and reduced performance over decades of exposure. Task 2 will model a precast
reinforced concrete panel facade on a building along the San Francisco waterfront that is exposed
to a changing profile of temperatures, moistures, and chlorides (from saltwater spray), along with
a constant gravity load. Previous research performed by the PIs has successfully shown that
multi-physics modeling of reinforced concrete members can accurately capture deterioration at
the materials and structural levels.13
For illustration, Figure 4 shows the results of a multi-physics corrosion simulation of a 1m
long reinforced concrete member exposed to marine salt-water spray and containing two preexisting structural cracks located 0.33m and 0.66m along the member. Figure 4(a) shows the
chloride concentration front (blue line) at an age of 14 years having penetrated into the member
and exceeding the spatially variable critical chloride threshold (red lines). This results in
depassivation of the reinforcing steel. Figures 4(b) and (c) show the corrosion current and
corrosion accumulation (rebar diameter reduction), respectively, modeled along the reinforced
concrete member at 14 years of age. By leveraging the results of Task 1, the results shown in
Figure 4 will be output onto an image of the deteriorating façade panel being modeled.
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Figure 4. Multi-physics corrosion modeling of a 1m cracked reinforced concrete member exposed to
marine salt-water spray at 14 years of age showing (a) chloride front, (b) corrosion current density,
and (c) rebar diameter reduction along the member
Task 3 – Multidisciplinary Design Optimization of Precast Concrete Building Façade Panels
In general, optimization involves systematically choosing variable values from within an allowed
set in order to minimize or maximize a given objective while simultaneously satisfying any
Lepech, Kiremidjian
VDC Multi-physics Modeling
5
constraints that the problem may have. Task 3 will vary façade panel attributes including
geometry (i.e. thickness), concrete material properties (i.e. diffusion coefficient), and maintenance
regimes (i.e. surface washing to remove chlorides from salt water spray). These panel attributes
will be optimized for minimum life cycle cost and minimum life cycle CO2 emissions given an
uncertain set of future exposure conditions to determine the best overall façade panel design. An
appropriate optimization algorithm will be applied to suit the particular problem formulation for
the case study project. This optimization algorithm will be coded in Matlab or Python. The
linking of each of the tasks is shown in Figure 5.
Figure 5. The major components and tasks of the proposed work. Task 1 is the linking of Revit®
with a Matlab controlled time-stepping multi-phyics model. Task 2 is the multi-physics modeling of
a façade element. Task 3 is design optimization based on the results of the multi-physics model.
Expected Results: Findings, Contributions, and Impact on Practice
High fidelity, multi-physics models are at the forefront of engineering modeling research.
Leveraging centuries of fundamental science, and decades of advancing computational methods,
these models can now fundamentally predict the time-to-failure of aircraft components in flight,
automotive vehicles on the road, and manufacturing equipment in use.11 As mentioned, while the
AEC community has matured in the use of BIM and VDC for designing and planning built
environments, it lags in the application of advanced, physics-based models for predicting the
decades-long performance of these facilities. This work will be an initial demonstration of the
power of multi-physics modeling to enable improved design of the built environment.
We expect to uncover a number of challenges through this work. For example, the
assignment of dynamic environmental exposures (i.e. temperature, moisture, sun) to each face of
a BIM element will be challenging in terms of both data collection and object attribute
assignment. Additionally, the assignment of varying material properties (i.e. concrete diffusion
coefficients) throughout a 3-D BIM element may be a challenge. We expect our theoretical
contributions to be the solution to these challenges in the form of new methods for BIM attribute
assignment or smoothing functions for averaging exposure conditions, along with the extension
Lepech, Kiremidjian
VDC Multi-physics Modeling
6
of multi-physics modeling to multidisciplinary design and optimization of the built environment.
When implemented, we expect this research to jumpstart the wider acceptance and use of multiphysics models in the design and operation of built facilities over the next 5–10 years.
Industry Involvement
Two CIFE members have been consulted on this project. Disney Imagineering (B. Schwegler)
continues to support the development of MDO approaches for the built environment. This
proposal looks to use models of fundamental scientific phenomena to predict the future
performance and enable MDO of the built environment. Autodesk (J. Rowe) has also been
contacted and will provide support and knowledge in linking Revit® with multi-physics
simulation. Currently, such linking is not a robust capability in the Autodesk suite of products.
Additionally, we look to reach across CEE and bring in the resources of another research
center. With similar interests in developing multi-physics models for the prediction of building
response to future earthquake hazards, the Blume Earthquake Engineering Center has committed
to fund a 50% RA for one additional quarter to supplement the proposed CIFE budget. The PIs
hope this is the first of numerous future collaborations between these, and other, research centers.
Research Milestones and Risks
Four milestones will be used to measure the progress of this proposed work.
1. Demonstration of Revit® linked to the multi-physics multi-scale modeling suite (August
2015) - This milestone will demonstrate the viability of using Revit® to assign and pass
geometries, material properties, and other input parameters into the modeling suite.
2. Modeling of Precast Concrete Building Façade Panels Exposed to Temperature, Sun
Exposure, Moisture, Chloride Exposure and Gravity Load (December 2015) - This
milestone will require collection of exposure conditions and implementation of the
complete working computer model for a façade panel.
3. Demonstration of MDO for minimizing façade panel life cycle cost and life cycle CO2
emissions (March 2016) - This milestone will require the implementation of MDO
algorithms to select an optimal set of panel geometries and material properties for life
cycle minimization of cost or CO2 emissions.
4. Submission of results to ASCE Journal of Computing in Civil Engineering (April 2016)
As mentioned previously, risks exist in the linking of numerous software suites together in a
single optimization loop. This includes the assignment of exposures and material properties, the
linking of variables across platforms, and the computational demands of multi-physics modeling.
These risks are mitigated through the use of robust integration software (Matlab). However,
additional software, such as Model Center, may also be used to support the MDO process.
Next Steps
Following this work, additional research will be proposed to the National Science Foundation.
Within the new Structural and Architectural Engineering (SAE) program, program manager Dr.
Kishor Mehta has shown significant interest in supporting the integration of fundamental
scientific modeling approaches with structural and architectural design. For instance, Dr. Mehta
has funded PI Lepech’s NSF CAREER award, which focuses on the use of multi-physics
modeling in structural design to mitigate the long-term effects of climate change on built
environments. This CIFE seed grant would set the stage for future projects of that type.
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VDC Multi-physics Modeling
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