BIM pinpoints the best alternative
BIM provides vast scope for accurate evaluation of design alternatives in the event of any changes that may impact the overall performance of the building, says buildSmart ME president TAHIR SHARIF.
01 July 2011
VALUE engineering (VE) is becoming a standard practice in the design of commercial and institutional buildings. Unfortunately, because of the inability to counter cost-cutting arguments with quantitative assessment of their effects on building performance at decision-making time, VE has become synonymous with blunt and sometimes mindless cost-cutting.
The elimination of features and measures designed to make the building more energy efficient exclusively on the basis of their cost typically results in the degradation of the building’s expected energy performance and in unexpected higher operating cost.
Building designers typically consider quite a few design alternatives for buildings they are commissioned to deliver. They also consider the impact of different possible design decisions on the performance of the final products. This is equally true for new building and for retrofit designs. However, design decisions are often made solely on the basis of first cost without quantitative assessment of the overall impact of alternatives on building performance. Design proceeds without understanding if and how decisions to reduce first cost affect the expected eventual performance of building.
If quantitative assessments of performance are sought, they are typically made available days or weeks later. By then, the subject design decisions have already been made and the sought quantitative performance data are largely irrelevant. The true feasibility of possibly preferable design decisions and alternatives thus remains unknown.
Whether quantitative assessments of performance of a design made solely on the basis of first cost become available after a delay or not at all, the result is the same. In either case, what by then have become the “preferable” design alternatives may ultimately not be preferable at all.
Role of BIM
One of the main purposes of building information modeling (BIM) is to serve as the authoritative repository of original building project data (that is, data created by those contractually responsible for their generation). BIM assures that the data it contains are indeed original and are accessed in their original form and format.
It also assures that the same basic original data are available for consistent use in the evaluation of all considered design alternatives, which enables commensurate and fair comparison of them.
Evaluation
Simultaneous consideration of possible first cost reduction and the corresponding quantitative assessment of its effect on building performance allows for accurate and consistent evaluation of design alternatives. The process assimilates the potential impact of any changed parameter on corresponding areas of the design and, consequently, the functioning of the building as a whole. In short, it provides the means to judge if cost reduction is indeed the preferable design decision to make.
The growing attention the architecture, engineering, construction, owner and operator (AECOO) industry is paying to building energy consumption has highlighted the intrinsic relationship between construction cost and energy consumption. However, the two issues are not always dealt with hand-in-hand. By deploying a process to quickly and simultaneously generate construction cost and the corresponding annual operating cost estimates for building designs, it is now possible to quantitatively assess in ‘real time’ the impact of cost-based decisions on building performance.
An integrated process
Outlined in (see Figure 1) is the process to perform cost estimating and building energy performance simulation that deploys various tools (authoring, middleware and analysis), interoperating via IFC (Industry Foundation Classes) and other data formats.
The process starts when IFC-compliant BIM authoring tools populate the IFC-based BIM with building geometry data that describe a specific building. An IFC utility then calculates surface representations that delineate unique energy transmission through a construction (so-called “space boundaries”) and adds them to the representation of building geometry already contained in the BIM.
Building geometry data and data sets must typically be transformed in content and/or format (that is, reduced, simplified, translated or interpreted) before they can be used by analyses tools.
This is the function of the middleware tools. To maintain data integrity, data transformation must be performed per agreed upon rules, which are embedded in the software. Data transformation rules vary depending on the type of analysis tool for which the transformed data are intended.
Data transformation rules for building energy performance simulation would involve reading “space boundaries” and other building geometry data imported from the BIM, performing data transformation per embedded rules, and exporting transformed (as well as unchanged) data.
Data transformation would also involve the creation of thermal zone definitions, linking definitions of construction materials to the library of thermal properties, converting all data to the required syntax (relevant to the analysis tool), defining simulation run control parameters, and generating the initial input file for building performance simulation. With the use of annual weather data that are representative of the weather at the building location, this input file is sufficient to calculate thermal loads generated by the designed building.
HVAC (heating, ventilation and air-conditioning) equipment, systems and plant data, as well as internal loads and all schedules of building use and operation may need to be added manually. Ultimately, the process to import original HVAC-related data from the BIM and transform them as necessary per embedded data transformation rules would be (semi) automated.
Simultaneous to the building performance analysis, a cost estimation tool would import building geometry data from the same BIM and perform quantity take-off calculations. The take-off data can be correlated to predefined unit costs to calculate a detailed construction cost estimate for the building.
Concurrent simulation
In concurrent processes, one is able to output the total construction cost for the design and the corresponding annual operating cost that is based on local utility cost schedules (neither cost is compounded). A side-by-side comparison of the two can unambiguously show the relationship between construction and performance costs.
Data transformation rules embedded in the middleware tools are also applicable to the definition of building geometry used by analyses tools that serve other disciplines in the AECOO industry. With an additional modest effort, the diagrammed process could be adapted to simultaneously include other types of building performance, such as structural, acoustical, fire safety, egress, and more. The diagrammed process fits well with the methodology for semi-automated building energy performance simulation (Bazjanac 2008). The use of that methodology prevents human error, omission and contradiction when defining and setting the simulation, and protects data integrity in the reuse of original data. It also dramatically accelerates design decision-making by quickly providing up-to-date quantitative justification, shortening the overall time it takes to design and deliver buildings.
Case study
Simultaneous generation of construction cost and building energy performance estimates was successfully demonstrated in a live, public forum as part of the Open Geospatial Consortium (OGC) AECOO-1 in Washington, DC. The demonstration involved a base case (that is, the “current state”) building and four architectural alternatives. Concurrent simulations for operating and construction costs were undertaken for each of the five scenarios and outputs were provided in less than an hour in each case. The testbed project was the redesign of a four-storey part of the US General Services Administration (GSA) headquarters in Washington, DC. The building included a south-facing four-storey atrium with a three-storey curtain-wall. IFC representations of CAD models of the base case, developed further in BIM authoring tools, formed the initial BIM.
Four architectural alternatives were designed to improve the energy performance of the building and to reduce its annual operating cost. The planned improvement of performance was cumulative (that is, the new features of a new alternative were added to the new features of the previous alternative) and the definition of modifications and additions were added to the BIM, then tested for accuracy.
To enable building energy performance simulation, middleware tools performed the necessary data transformation and semi-automatically created the necessary input files with building geometry and the corresponding construction materials data for the base case and each alternative.
These files were automatically merged with predefined macros, which contained HVAC definitions of a hypothetical district cooling and heating system, internal loads, use, and operating and utility cost schedules. Building energy performance simulations calculated and reported annual summary energy performance and the predicted annual operating cost (Bazjanac 2009). Concurrent to the building energy performance simulation, the cost estimating tool performed automatic quantity take-off from building design data contained in BIM for the base case and each design alternative. The estimating tool then used these quantity take-offs to generate the corresponding construction cost estimates using its database of unit costs.
All simulation and estimating was performed on laptops in the same room, operated by vendors of the tools used in the demonstration. As cost estimating used native CAD definitions and did not require the use of middleware for data transformation, it generated estimates quickly.
The BEP tool took a lot longer to generate its estimates, but it accomplished it in less than one hour in each case (Table 1).
The geometry definition of each alternative was “pre-designed”; it took less than 30 minutes to add even the most complicated additional geometry, such as external shading (the time needed to add additional alternative building geometry to the BIM is not included in Table 1).
All concurrent preparation and execution of the simulation of alternatives, the generation and comparison of construction and operating estimates for a building of similar size can, with some planning and preparation, be accomplished within one hour and a half.
Simultaneous construction and annual operating cost estimating allowed the direct “real-time” comparison of design alternatives (Table 2).
The comparison shows that, for example, alternative 3 (high-performance glass in all windows) was the most energy-efficient alternative, as it reduced the annual building operating cost. It also showed that this was among the most expensive alternatives, and that the necessary long pay-back period may have made this alternative infeasible.
The owner, the design team and project consultants were able to evaluate the feasibility of each alternative using comparable cost data within an hour.
Trying to do the same in the conventional way with conventional tools would have taken days and would have required the convening of at least one additional meeting.
Simultaneous estimation of cost and of building energy performance, based on BIM, provides the ability to confront cost-estimate-based arguments with quantitative counter-arguments that show the annual operating cost before and after cost-cutting action.
With preparatory work done in advance, design decisions based on quantitative comparison and the understanding of the particular cause-and-effect can now be reached in the same meeting – the same afternoon or the same day, depending on estimates’ complexity and building size.
This should result in better decisions, in better buildings delivered sooner and ultimately in more cost-effective building ownership than has often been the case in the past.
