The Drivers of Change have been issued twice now. They are collated and published by the Foresight and Innovation team and consist of a series of cards grouped by theme around the STEEP principles covering Social, Technological, Economic, Environmental, or Political drivers.

The cards are often used as a tool for discussion or prompts for workshop events such as the 2009 TED Global workshop in Oxford.

More recently Duncan Wilson has created an interactive tag cloud so the drivers of change most pertinent to any particular group or workshop can be recorded at that event. We’re working with Duncan at the moment to develop a similar tool for the SlimCity workshops we will be conducting in Australia over the next few months. You can see the tag clouds for Melbourne and play with the voting while they are being developed.

SlimCity is a World Economic Forum initiative for which we co-developed three sets of cards (cousins to the Drivers of Change). They can be downloaded here.

I was recently invited to present a short Implementation strategy for using Revit at an AutoDesk Award ceremony for the Building Construction Authority (BCA) here in Singapore. The award was in recognition of the BCA’s continued efforts in promoting the use of Building Information Modelling (BIM) within the Singapore construction industry. This is something that has not been as easy as people first thought but the BCA have continued with their efforts and I think are well on the way to breaking new ground with BIM-based Government submissions.

At Arup in Singapore we have been adopting the process of BIM on all our projects for a fair number of years with many number of successes and only a few doubters (still !!). The support we receive at Arup from our leaders locally, regionally and on a global scale makes it a much easier prospect to implement new ideas and technology but what is clear from my time talking about and discussing BIM with others externally that story is not the norm. So when I get asked to do an implementation presentation I usually try to keep it simple and hopefully funny although I think my humour is lost on most and try and address the main things for people to think about, such as software choice versus project type, training, foresight and planning, support, hardware to name a few. However, the one thing I always stress is the need to start; I still fail to really understand why people do not see and take advantage to this approach to design and documentation.

OK so I am sold, in fact I was sold a long time ago but none the less it still seems blazingly obvious why this  PROCESS of leveraging INFORMATION is the way we all need to work together (forget software for now).  The only reason I can come up with otherwise is risk and responsibility and the way the fear of  it is ingrained into the industry and until we alleviate that mentality its gonna be a long old road for all us but as I say in my presentations, we at Arup are well on that road already.

For the past two years I’ve been part of an Australian Government funded research team exploring the theme of Delivering Digital Architecture in Australia, investigating issues such as architect/engineer communication, data interoperability and lessons from parallel industries.

Early in the research we gathered information about data interoperability experiences from our staff and collated it into an Interoperability Database. This revealed some basic approaches to interoperability problems:

Use an import/export tool written by a software vendor.
Write your own tool to do the data transformation Depending on the particular tool, these approaches can be characterised as either a Scalpel or a Swiss army knife.

Scalpel A tool that links two particular pieces of software (e.g. GSA to Revit)

Pros:
• Specifically designed for the task, often giving the best results.
• Can be optimised to deal with cross-discipline or “geometry + analysis data” transfer.

Cons:
• Can limit the choice of design tools.
• Causes problems as the number of design tools increases.
• Some user written tools prove difficult to share with others.

Swiss Army knife A more general purpose approach, using an exchange file format such as IFC.

Pros:
• Generally industry funded, based on well designed and documented formats.
• Often provided by software vendors as a feature in their products.

Cons:
• Might not meet project data requirements, and may not be easily extendable.
• Currently best suited to “documentation/co-ordination” data rather than “design/analysis” data. As part of our research we are proposing a third possibility, which solves some of these problems but, as with any solution, also has its downsides.

The DesignLink Software Development Kit (SDK) – a meta tool for building tools.

The DesignLink SDK combines a data exchange format with the routines needed to read/write that data to various applications or file formats.

The DesignLink SDK can be used to build tools to solve interoperability problems as well as custom tools to use in the design process. It’s this ability to use the SDK as a platform for building custom design tools that sets it apart from other data exchange toolkits. Since these custom tools share some common DNA, it will be easier for programmers to share useful code. They also benefit from being built on a platform that includes:

• inbuilt testing routines
• easy methods for people to contribute ideas or code, without needing a degree in software development
• a community of programmers and users to review and improve the code

The types of tools that can be built with the SDK include programs to enable designers to connect parametric geometry models to engineering analysis models, allowing them to explore more design options; and custom written programs that perform design processes such as member size optimisation and design code checking.

We recently showcased DesignLink at SmartGeometry 2009 and I’m currently in the process of testing DesignLink on project and planning the next steps, which might involve Collaborative Licensing to further develop the SDK.

The use of custom tools can improve efficiency, especially when handling large structures with thousands of elements. One of the most useful tools I have recently developed is a strength based optimisation program that links with Arup’s in-house structural analysis software Oasys GSA through its API (COM interface).

The COM interface uses Visual Basic (VB) scripting and allows remote access to most of GSA’s functions, enabling the user to drive GSA externally through programs such as Excel. This means the user can automate calculation intensive processes and handle large amounts of data in an efficient manner.

While working on a multi-billion dollar project in Singapore, I was faced with the challenge of analysing and designing several large steel structures with highly complex geometric form and 5000 plus elements in each structural model. I initially developed this tool merely to deal with the sheer number of elements that were required to be analysed, designed and sized.

Later, I saw the potential for expanding its use by incorporating an optimisation routine. This was achieved by running a computer automated numerical algorithm to determine the least steel-weight of the structure while still satisfying the relevant design codes.

The optimisation algorithm will not attempt to modify the geometric form. Instead, through an iterative process, the sizes of the structural elements are continuously substituted (from a user selected pool of sections sizes), analysed, designed and resized based on the results of the analysis, until the structure with the least steel-weight is found.

It is also possible to calibrate the algorithm for different optimisation criteria. For example, an alternative criterion to the least steel-weight solution could be shallowest depth solution, least cost solution or fastest procurement solution, or a combination.

I have used this optimisation tool on two other projects. In these cases it was used for rapid design and member sizing of various scheme options and allowed the design team to quickly assess the most economical design options.

Not only was this an effective and highly efficient method of managing the data from large structural models, it also offered the opportunity to fine tune the steel weight of the structures, resulting in potential cost savings.