Optimizing Specs for Steel Structures


COPENHAGEN—There are many ways to decide on paint specification—and a high-stakes decision it is for large steel structures.

Corrosion protection is expensive, and failures can be catastrophic, risking both lives and ruinous repair costs.

It is therefore surprising to see how often such decisions for new construction are based solely on the lowest cost from the bidding cycle.

This article aims to show a better way to make such decisions for the long-term protection of the structure and the lives that depend on it.

The Power of Simulation

Although most people agree that it is worthwhile to consider maintenance and refurbishment costs over a structure’s expected lifetime, these are not generally taken into account when the coating system is selected.

This article demonstrates a combination of two concepts that can produce more accurate decisions, using simulation software to compare life-cycle costs.

It is impossible to forecast anything over long periods, such as 100 years. Simulation software, however, can compare various corrosion protection strategies over such periods, everything else being equal.

Similarly, surface preparation and paint technologies will progress, and interest rates and inflation rates cannot be accurately predicted.

Simulation, however, can optimize specifications for the best and most economic protection of large steel structures.

Specifications Based on Paint Selection Systems

Several methods are available.

For example, specifications may be based on published standards such as ISO 12944; company standards or those that require acceptance tests such as NORSOK; or recommendations from corrosion societies such as SSPC, NACE or others.

Quite often, the structure’s owner or the contractor rely on specifications put forward by the paint manufacturer; it should have good experience with coating application and performance from similar structures and can normally provide references to that effect.

Official standards and company-specific standards tend to be very detailed or contain complicated tables that take time to study and assimilate. Simple selection programs, however, can make access to the data fast and efficient while reducing mistakes. They can also make it easier to compare alternatives in a short period, because different conditions can be simulated almost instantly.

Simulator Systems

For example, one paint selector for bridges based on ISO 12944 starts with the selection of the corrosion category: C3 (medium), C4 (high), C5I (very high industrial), and C5M (very high marine) are relevant for large steel bridges.

Users then may select the primer type: epoxy (zinc phosphate), zinc epoxy, zinc silicate or waterborne epoxy.

The final stage is selection of the topcoat: typically, polyurethane, polysiloxane, waterborne acrylic or epoxy.

Figure 1 shows a typical decision tree for a bridge in corrosion category C3; Figure 2 shows a screen shot from a decision for C4 with zinc epoxy, epoxy mastic and polyurethane.

It is also possible to insert other fields or links to datasheets, reference lists or other descriptive material in coating selection templates, depending on requirements.


Figure 2: Several parameters define paint-selection decisions for a bridge per ISO 12944 - C4.

Specifications Based on Life-Cycle Calculations (LCC)

Corrosion protection systems for large steel structures may also be based on life-cycle calculations. Thus, one calculates the total life costs and then discounts it back to Net Present Value.

Such calculations consider all costs over the structure's design life, including surface preparation, paint application, maintenance and refurbishment of the corrosion protection system.

A typical detailed system is described below.

Doing the Calculations

In some programs, calculations are carried out in separate modules, such as new construction, maintenance and refurbishment. Surface preparation and other costs can be plugged into a cost module, with that data saved as pdf files or printed out.

This example uses a bridge in China, with a structural area of 100,000 square meters and a design life of 100 years. The user set a maintenance interval of seven years and refurbishment at 30-year intervals.

Typical screen shots illustrate the process.

The Data Screen accepts input about the project. Tabs at the top indicate the possible project parameters.


New Construction takes input such as surface preparation, number of coats, products, film thickness price, solids, VOC, loss factor, and application cost per coat. Including VOC data allows for calculation of a lifetime VOC figure, for projects that demand the lowest environmental impact.


Maintenance and Refurbishment screens (not shown), like their newbuild counterpart, accept information about maintenance intervals, area, and other details.

The Cost Screen allows for surface preparation and application costs as well as additional costs.


Cost Survey displays all cost input and percentages under the three main objects.


Finally, Life Cycle Cost Development details expenses for each event, the discounted net present value, and the VOC.


These values enable comparison of various specifications and coatings.

From Japan, A Coatings Comparison

The calculation can also be used to compare the life-cycle costs of different paint systems.

In Japan, for example, fluoropolymer topcoats are used to extend the life of large steel structures. Thus, comparing the life-cycle cost of a traditional epoxy/polyurethane system with that of an epoxy/fluoropolymer system could be interesting.

Using typical values and prices in the Japanese market, we can see the difference in these two systems when used in new construction.


Based on this narrow comparison, the obvious decision would seem to favour the polyurethane system. However, if the user calculates for the structure’s life cycle—our Chinese bridge again, for example—the result looks very different.


Factoring in lifetime VOC adds still more information.


In summary, then, fluoropolymer system for new construction costs almost 100 million Yen more than the polyurethane system. But over the structure’s lifetime, the polyurethane system costs almost one billion Yen more. Moreover, the fluoropolymer system saves almost 75 tonnes of VOCs over the bridge’s life.

Simulation can also analyse changes to any of the inputs—if, for example, maintenance costs change.


At right, we see that a 10 percent increase in maintenance cost increases the life-cycle cost by just 3.5 percent, due to discounting from Net Present Value.

Simpler simulation programs are also available. These programs may be less flexible and require more user calculation, but they simplify and consolidate the display of simulations and results.


This article has shown how a simple computer program may be used to help select paint specifications, as well as two approaches to life-cycle calculations of corrosion protection for large steel structures.

The examples offer a timely reminder that relying solely on the new-construction cost of the paint is not always the best decision.

About the Author

Svend Johnsen is an independent protective-coatings consultant.


His experience includes a 30-year tenure at Hempel A/S and a coatings selection project with the Japanese government for the oil and gas sector. A chemical engineer, Johnsen also has degrees in marketing and business.



Tagged categories: Asia Pacific; Bridges; Coating selection; Coatings Technology; Consultants; Corrosion protection; EMEA (Europe, Middle East and Africa); Program/Project Management; Protective Coatings; Specification

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