**3.5 Information management**

Once a road network is correctly modeled and parameterized following the above procedure, a number of shared parameters describing the main features of pavement materials can be created to match the information contained in an external database.

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**Figure 8.**

*Materials code creation workflow.*

*BIM Approach for Smart Infrastructure Design and Maintenance Operations*

There are several visual programming tools (VPL) (i.e. Dynamo) that give to users the possibility to visually script and define custom pieces of logic using

The shared parameters imported in the current project as materials features, were the road name, the road administration authority, the year in which the material was layed in place during routine maintenance operations and the physical and mechanical features of the wearing course mixtures, namely bitumen content, air voids percentage calculated with bulk specific gravity determined by means of the dimensional procedure, SSD procedure or sealed specimen procedure and Marshall

Then, the material codes were exported to Excel with the programming flow reported in **Figure 8**, then matched with the materials names in the worksheet and

A worksheet was created using the code block "Data.ExportExcel" (5), whose file path, sheet name and position of the exported data were defined respectively with the code blocks (4A), (4B) and (4C). The worksheet contained a list (4D) of materials identifiers (3A) and names (3B) selected from the list of elements (2) of

The above mentioned operations allowed visualizing and managing the physical and mechanical features of the wearing course model and updating the information once the input worksheet is integrated with different data. The visualization of the imported data is visible in the material parameters interface, as shown in

Then, in the same way, is possible the implementation of a ranking algorithm to evaluate the durability of the wearing course material basing on the material

characterization, according to current Regulation [32]. In the specific:

• Stability>900 (daN) to respond to mechanical problems;

anomalies in the database due to technical errors.

• % bitumen (%B) in the range 4.5 ÷ 6.1% to meet both economic and

• % air voids determined by means of the dimensional procedure >3% to

• The difference between air voids determined by means of the sealed specimen and SSD procedure (Δ) is equal or lower than 1% to ensure that there are no

*DOI: http://dx.doi.org/10.5772/intechopen.94242*

various textual programming languages.

finally imported back into VPL with assigned values.

stability.

**Figure 9**.

the materials category (1).

environmental needs;

improve shear strength;

**Figure 7.** *Modeling corridor. (a) Plan view, (b) 3D view.*

## *BIM Approach for Smart Infrastructure Design and Maintenance Operations DOI: http://dx.doi.org/10.5772/intechopen.94242*

*Models and Technologies for Smart, Sustainable and Safe Transportation Systems*

Once your assembly is built you need to apply this to your alignment using the corridor function and hey presto, you will have a corridor and basic road design.

Before create corridors, you must have existing data, such as existing ground surfaces, alignments (centerlines), profiles (vertical alignments), and typical

All calculations should be finalized before they are applied to the corridor model. Changes in a corridor baseline alignment are not reflected in calculations.

Once a road network is correctly modeled and parameterized following the above procedure, a number of shared parameters describing the main features of pavement materials can be created to match the information contained in an external database.

Changing the design criteria does not update the corridor model.

*Modeling retaining walls using subassembly composer. (a) Workflow, (b) result.*

In **Figure 7** is shown a generic 3D Corridor model.

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**Figure 7.**

*Modeling corridor. (a) Plan view, (b) 3D view.*

**3.4 Corridor modeling**

**Figure 6.**

sections (assemblies).

**3.5 Information management**

There are several visual programming tools (VPL) (i.e. Dynamo) that give to users the possibility to visually script and define custom pieces of logic using various textual programming languages.

The shared parameters imported in the current project as materials features, were the road name, the road administration authority, the year in which the material was layed in place during routine maintenance operations and the physical and mechanical features of the wearing course mixtures, namely bitumen content, air voids percentage calculated with bulk specific gravity determined by means of the dimensional procedure, SSD procedure or sealed specimen procedure and Marshall stability.

Then, the material codes were exported to Excel with the programming flow reported in **Figure 8**, then matched with the materials names in the worksheet and finally imported back into VPL with assigned values.

A worksheet was created using the code block "Data.ExportExcel" (5), whose file path, sheet name and position of the exported data were defined respectively with the code blocks (4A), (4B) and (4C). The worksheet contained a list (4D) of materials identifiers (3A) and names (3B) selected from the list of elements (2) of the materials category (1).

The above mentioned operations allowed visualizing and managing the physical and mechanical features of the wearing course model and updating the information once the input worksheet is integrated with different data. The visualization of the imported data is visible in the material parameters interface, as shown in **Figure 9**.

Then, in the same way, is possible the implementation of a ranking algorithm to evaluate the durability of the wearing course material basing on the material characterization, according to current Regulation [32]. In the specific:


**Figure 8.** *Materials code creation workflow.*

### *Models and Technologies for Smart, Sustainable and Safe Transportation Systems*


#### **Figure 9.**

*Example of material parameters after the association of worksheet data to the model.*

In **Figure 10** is shown the workflow for identifying the road pavements that satisfy the first condition.

In the specific: box 1A answers the question if x (%B) is greater than or equal to y (%B lower-limit equal to 4.5%); box 1B answers the question if x (%B) is less than or equal to y (%B upper limit equal to 6.1%); Box 2 "List.Join" concatenates the two lists into one list; Box 3 "List.AllTrue" determines if all the elements of the list are Boolean values with true value; Box 4 "List.Join" merges all the lists associated to other pavement sections of the road network; box 5 "SelectModelElement" for selecting the pavement sections under analysis; box 6 "ListCreate" for merging all the selected pavements in the previous step in a single list; box 7 "*List. FilterByBoolMask*" to filter the list of elements codes by looking up for corresponding indices in the list of Boolean variables, identifying the sections that comply with the technical specifications.

In the same way, the workflow can be adapted to the remaining Regulation conditions, with the possibility then to create combined filters among the mentioned

#### **Figure 10.**

*Workflow for identifying pavements with bitumen content in the range 4.5%–6.1% by the weight of the mixture.*

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**Figure 12.**

*Example of identification of the critical section.*

**Figure 11.**

*BIM Approach for Smart Infrastructure Design and Maintenance Operations*

pavements with best, worst or intermediate performance.

conditions, for visualizing on the road network map, with different color, the

For example, in **Figure 11**, the list containing the overall scores of the road surfaces under analysis (1) was matched with the list of identification codes of the corresponding elements of the model (3) using again the code block "*List. FilterByBoolMask*" (4). In the present study, the list of Boolean variables was obtained by looking for the road surface with the minimum score (2), obtained from the combination of several physical and mechanical indicators and their upper and lower limit imposed by the Regulation. Lastly, the element code that met condition (2) was emphasized in the model element with the color red (5) by using the

As a simplified application to show the impact of information update on the model output modification, two different road sections were considered with bituminous mixtures for wearing course characterized in terms of bitumen content,

The test results are updated as material parameters in the model and a ranking algorithm is implemented in order to identify the road section with a need for maintenance. As shown in **Figure 12**, the critical road section that requires routine

*DOI: http://dx.doi.org/10.5772/intechopen.94242*

code block "*Element.OverrideColorInView*" (6).

percentage air voids and Marshall stability.

maintenance before the other is highlighted in red.

*Workflow for identifying pavements with best/worst performance on the road network.*
