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Connection Design Workflows Using Revit, Robot Structural Analysis, and IDEA StatiCa Connection

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Description

In this session, we'll cover connection design workflows for structural engineers from both the East and West coasts of the United States, as well as other geographical regions in the world. Using Robot Structural Analysis Professional software, Revit software, and IDEA StatiCa Connection, we'll show how information can flow seamlessly from one party to another with no data loss and no data replication using IDEA StatiCA Checkbot. Engineers will finally be able to share their information for connection purposes to create a more efficient workflow. We will show multiple customer success stories from every region.

Key Learnings

  • Learn how IDEA StatiCa eliminates the hurdles to connection design communication.
  • Become familiar with the connection design workflows that affect you the most.
  • Learn how to integrate a solid connection design workflow into your design workflow.

Speakers

  • Ralph Pullinger
    Ralph is a Structural Engineer based in UK and has been working in the software industry the last 15 years. Prior to this he was in consultancy designing structures in steel, concrete, timber and masonry. For ten years prior he was in charge of his company's CAD and analysis requirements. He now works for a Czech company: IDEA StatiCa s.r.o. with offices in the United States, United Kingdom, Germany, Singapore and Benelux providing software for Structural Engineers to design and code check steel connections, steel members, concrete members and specific concrete discontinuity zones. IDEA StatiCa also develops for Autodesk Advance Steel, Autodesk Revit and Autodesk Robot Structural Analysis Professional (as well as many other similar applications).
  • Jason McNeil
    Jason McNeil, PE, has been involved in the steel industry for almost 15 years and has gained a broad range of experience working in steel detailing, structural engineering design, project management of steel construction, and structural software. In his role at IDEA StatiCa, Jason works with engineers and steel detailers to help them safely design and optimize structural details, namely steel connections.
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Transcript

RALPH PULLINGER: Hello and welcome. This is presentation BES2691, Connection, Design, Workflows. This is what we're going to be looking at today. Some brief introductions about myself and the company I work for, a bit about the background, and the problems I and my company have seen over the years. I will introduce a workflow that will work in any situation with practical examples. And last of all, there will be time for questions.

My name is Ralph Pullinger. I've been a structural engineer for over 40 years. I was born in Birmingham, England, hence the strange accent. Following a successful stint in consultancy, I have spent the last 15 years in the software industry helping engineers, detailers, and management realize their potential. My favorite question to ask is why, and you'll find out why later.

I worked for a company called Idea Statica. We are based in Brno, in the Czech Republic. It would be interesting to see how many of you have heard of us. We are a global software company specializing in both steel and concrete solutions with over 100 employees and 40 plus resellers. We are a trusted technology partner with Autodesk, to name but one. Our software is used extensively around the world and our results have been validated and continue to be validated by several renowned international universities at the top of their fields.

A bit about the background of the problem we are looking at today. One size definitely does not fit all. Methodologies for connection design exist that cover most countries. Some processes are more complicated than others. Over on the West Coast of the US and South America, we see what we call the structural bundle or code of standard practice, option one or two.

As we move steadily East, we see what's termed delegated design entering into the Eastern US, or what is known locally as code of standard practice option through A, B, or C. This delegated design even hits the UK, back home.

Over in inland Europe and Australasia, we tend to see an all in one approach. And all of these approaches, I'll go through in greater detail in the coming slides. Some of the gray areas we don't want to know about or have just not been able to assess. The design options that we're going to look at relate primarily to standard contracts. But when we see an IPD contract, things change up a gear or two.

So the first methodology, the structural bundle or cost one or two, can be found on the US West Coast. Although, it might be known locally under different names or even a different name. There is obvious benefit to be had with all of the design being done by one organization. The drawback, however, is that there is little or no fabricator involvement, which can lead to uneconomical use of material and sections.

The second methodology, known as delegated design, is perhaps the one where there is most to gain. Here the fabricator assumes responsibility for the connection design using information gleaned from the global structural design, but provided by the engineer. That is the key differentiator. The potential for over-design grows if valuable design information is not shared adequately.

The third methodology, which we've called, all in one, is very popular on mainland Europe and Australasia. Having seen this first hand over a number of years, I can see the obvious benefits. Coordination being the obvious. However, this workflow could still benefit by moving from an analog to a digital basis, as far too much paper is still being used.

Over the years, we've seen issues arise that relate back to the load effects shared with the designer. These load effects were not based on bona fide combinations, but the maximums or envelope loads. And these loads, again, were factored up by a certain percentage. This approach dates back to when I was starting out as an engineer and is still prevalent today. What this means in reality, is over-design, as connections that should work invariably do not.

When it comes to checking, we know that engineers struggle with the information overload that happens in design. But imagine a scenario where calculations are issued together with a 3D model of the connection that can be interrogated and viewed from any angle. Communicating all this to the fabricator efficiently is the next hurdle to overcome. In order to do this, they should be able to receive the design intent to base their detailed modeling on. It should also be easily incorporated into their design. If we are able to create a flexible and reliable workflow, one where information is not duplicated, then our industry can look forward to a bright future. One where risk is lessened and time and cost overruns are a thing of the past.

Some of the reasons why information is not shared is often down to two letters. I and P. Either intellectual property or professional indemnity. The former is often linked with the exchange of whole models, which are not really required by the connection designer. If the relevant load effects from the actual load combinations are published, then there is no need to worry. Indemnity, or insurance, should not be an issue either, if these loads are taken from the same model the global design came from.

If the engineer is not prepared to guarantee these results, then what is the point of the design. Sharing markups, either as PDFs or even as drawings, offers no real benefit. It can be seen as a massive step backwards. Excel schedules, on the other hand, are marginally better if they contain the correct information.

We all know that ours is a complex world with complex products, projects even, involving lots of consultants. Early engineering and fabricator involvement has a proven track record. Just look at ITD. If we were looking at connection checking, how do engineers currently do this? Do they wade through pages and pages of calculations looking for key results? Or do they recreate the connection design? Either way, there should be an easier and more efficient way to do this. If all of the design information could be shared, then checking should be quite straightforward.

The final hurdle to overcome is getting the information to the fabricator for detailing. It's the last thing to be done, but it's always the first thing that is required. Unfortunately, this is the way it's always been done.

We've talked a lot to engineers around the world. We've talked to fabricators, and we've talked to software vendors like Autodesk. We realized very early on that a good workflow allows engineers to work the way they want to with the tools they want to use and the ones they are used to working with. This solution being put forward today could equally apply to other solutions in the same field. We can connect multiple parties to streamline the design process at the end of the day.

On this slide, are the key processes involved in arriving at a successful connection design. We'll go through them one by one. In step one, we are seeing an early structural model that has been constructed in Autodesk Revit. This model contains all the structural information in the form of structural beams, columns, beam systems, slabs, and braces. No connections as yet.

It also takes advantage of the analytical model. That has evolved and developed over a number of years. Hopefully everyone knows that this information is available and can be used downstream by the likes of Autodesk, Robot, structural analysis, professional. However, we all equally know that this is not the case. Most likely the analytical model is being created by a different person, possibly in tandem. The process of transferring the model from Revit to Robot is quite straightforward.

The result of the direct air exchange facility from Revit to Robot is an exact duplication of the Revit model. This model could have been constructed from scratch, but that would have taken a considerable amount of time and duplication of effort. In this model are the same members with the same connectivity as per the Revit model. Loads and load combinations have been added. As you can imagine, modern codes create a lot of combinations. And once we have a good model, we can analyze it and generate an even greater number of results.

Sometimes it's quite hard to visualize what these results mean. But thankfully, Robot allows us to investigate and sense check our inputs. We can check the results by visualizing moments. We can check deflections by choosing the most appropriate load case and enabling the deflections to make it easier to read, we can highlight certain areas of the structure and get a better representation of the results, making sure it is as we expect. The big question is, what comes next.

The next step would be to update the structural model with the results of the structural analysis and design. Using the direct approach, we can integrate the results as well as any geometrical changes, i.e. changes in member section size. This is accomplished very easily by the reverse process, i.e. we're importing the data from Robot rather than exporting it to Robot. And Revit being Revit, any changes to the model will instantly update. However, this is more likely to be accomplished by a series of mark-ups indicating the changes. And I've yet to see this workflow, this digital workflow, in full use. If we can update the Revit model, then the results can also be stored and utilized further downstream. The results are stored in the results package. And we can explore those using the tools within Revit and again, even use these to document the design. We have access to the full scope of the results that we have developed within the Robot model.

So we've now seen what can be undertaken by one organization or even one person. We now have a structural design that is complete with results that have been validated that can be used again. The next step is where it starts to get interesting from the perspective of connection design.

What we can now do is publish the geometry, beams, columns, braces, et cetera, and their load effects to a structured database via solution called Idea Statica Checkbot. With Checkbot, we are able to recreate all of the key information required to design the connections without the massive overhead of the whole structural model.

This means that the connection designer receives the right information at the right time. Furthermore, with today's data sharing solutions, this is a relatively painless exercise. In Checkbot we are able to visualize the load effects and the load connections into design sets. This greatly simplifies the connection design process as we can now focus on key connections rather than all connections.

The load effects that we pull in from the Robot model are many. In fact, they are complete. We have algorithms within Checkbot that will reduce these to the most onerous. And we call these the critical load effects. After all, if we've got 163 load cases, we don't really want to be wading through all of those when we can just design on a subset of about eight, say, for instance.

Visualizing the load effects is as simple as selecting the connections that we are interested in, or sets of connections, and drawing those load effects out on the screen. If we were to open a column base with a brace connection, we can see the load effects that have come from the global model.

The load effects, as I mentioned, are many. The load effects have been reduced further to a subset of about eight. And we can see each load combination being applied to the model in turn. So when we design this connection, we don't design on maximums. We design through each and every load case. As a side note to this, once we have a connection, Idea Statica is also able to conduct a stiffness analysis. So the usual engineering, fixed or pinned assumptions can be validated and improved upon for a high level analysis check.

At the same time, fabrication details will start to emerge. Again, we are reverting back to Revit to show how these could be applied. These connection details may or may not be adequate, depending on the skill and expertise of the detailer. If we were to add a series of simple shear tabs to one of the top beam connections, we can visualize those quite easily in Revit. But we really want to be able to check these out in a more substantial manner.

Revit has plenty of tools that will comply different types of connections from simple shear plates to complex moment connections. It can apply these to different cross-sections with different arrangements. But what is relevant is that this model is using the same information that is also in Robot. As an additional step, not shown, it is also possible to export the steel work in its entirety to advance steel.

We've seen how to get the information published from Robot. What we're going to do now is publish a different set of information from Revit. In essence, it's exactly the same process. We use Checkbot to create a database based on, let's call it the fabrication model. And we are lucky in this case, that the load effects are also present in this model, so we don't have to ask for them.

If we were working with our results, say by using another analysis solution or if we were using Advance Steel instead of Revit, then we also have the option to merge geometry and load effects for the same connection across two databases. We can also request one of those intelligent Excel schedules, as we are able to import the data directly from Excel. But the important thing to recognize is that the schedule needs to have the right information.

This is one of the ways that we can break down the silos associated with connection design. If we run this initial connection through our comprehensive checking solution, Idea Statica connection, we will see that it fails, and it fails considerably. These checks that we are doing conform to the AISC code, but there are other codes that we can use in the design of our structural frames and connections associated.

When I said considerably, I meant considerably. If we see red on the overall check, red is bad. Luckily, we are able to investigate these shortcomings and assign a design from over 700,000 valid examples we have on file. When we run this through the check, the results are a lot better. If we see green, we're seeing sections that are being utilized well. If we see gray, they are not being used to their full extent. Luckily, we see no orange, which is bordering on bad, or red, which is bordering on-- which is definitely bad.

Now, unfortunately, we now must communicate these changes to the detailer. And previously this was done by sketches and change requests. Now we have change requests and access to a high fidelity IFC model that can be read into an IFC viewer or indeed read back into Revit. From a checking perspective, we can create an online model that is the same as the one created on the connection designer's desktop. So not only can we issue them the actual calculations but also a link to this 3D viewer.

This functionality can be further enhanced if the checking engineer also has a valid license of Idea Statica. It's as simple as sending an email. If you can type. So what have we just seen?

In step one, we created the initial structural geometrical model. In step two, we created the initial structural analytical model, which we could do either directly or independently. We chose Robot for this task. In step three, we updated the Revit structural geometrical model. And in this case, we also elected to pass the results. In step four, we created a structured database of connections with the geometry and the results from the Revit model.

This is the database that could be shared by connection, by two connection designers. In step five, we carried on and we created those fabrication level details. But imagine a model with many more connection details. How would we go about checking those connections one after the other?

And in step six, we created a database that could be used to design and code check those same connections that we created in Revit. The connections in steps four and six utilized the software. From Idea Statica.

In summary, then, I've shown you how to-- how connections could and should be designed and code checked. By reusing the right information at the right time, by the right people, this process will enhance your workflows. This workflow, or something very similar, can streamline your overall processes, reduce your risks, and create more cost effective designs that, by direct comparison, will also have less embodied carbon. A cheaper design has less carbon.

In reality, we can work with virtually any analysis, solution and any BIM solution. Just look at who we're able to partner with. For ease. I've highlighted the Autodesk Solutions with the red box. The process for many others is almost exactly the same or very similar. And I just go back to what I said in one of the original slides is that we empower engineers to work with solutions that they want to work with.

Thank you for being here.

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We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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