Cantilever Overhead Sign Structure (COSS) Application logo, COSS-APP

COSS-APP | Cantilever Overhead Sign Structure Application

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Intuitive Graphic User Interface

Our user interface was created to be easy to use. Whether you’re creating complex cantilever overhead tri-chord or quad-chord truss type structures, or tubular (monotubes), COSS-APP has you covered.

Robust Analysis and Design

COSS-APP features allow you to rapidly create your cantilever overhead sign structure (COSS) analytical models using a wide range of options within a friendly user interface. Easily define your parameters and COSS-APP will setup the model for you in Bentley STAAD.Pro® CONNECT Edition or MIDAS CIVIL NX®, leveraging both platforms’ advanced analysis capabilities.

The features included in COSS-APP are the following:

Comprehensive Model Results

Create models with both graphical and numerical results including robust detailed inputted parameters, giving you and your colleagues full confidence in your design.

Interoperability

COSS-APP integrates with STAAD.Pro’s and MIDAS CIVIL NX® interoperability technology, allowing end-users to access more advanced features, and work collaboratively and collectively thorough the project’s lifecycle.

COSS-APP works with Bentley applications, such as RAM Connection, STAAD.Pro, STAAD Foundation, Adina and iTwin Analytical Synchronizer


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COSS-APP is built to address non-standard, complex tri-chord and quad-chord truss type cantilever sign structures.

COSS-APP Graphic User Interface (GUI) & Features

Designing cantilever overhead sign structures can consume weeks or even months. COSS-APP produces the analytical model in minutes.

COSS-APP Efficiently Design Cantilever Overhead Sign Structures

For engineers tasked with the design of highway structural supports, COSS-APP builds the analytical models for cantilever overhead sign structures in accordance with AASHTO LRFD LTS — leaving more time for design decisions and deliverables.

COSS-APP produces analytical models for cantilever overhead sign structures immediately, so traffic structure designs that fall short of standards get caught at the desk rather than in the field — before they become costly construction issues.

COSS-APP reduces STAAD.Pro modeling time for cantilever overhead sign structures from 200+ hours to a matter of minutes, generating compliant models against FDOT specifications, MDOT requirements, DTOP guidelines, and other major DOT standards.

COSS-APP has been tested against the MIDAS CIVIL NX API, extending platform compatibility beyond STAAD.Pro. Tubular (monotube) cantilever sign structures can be modeled parametrically and analyzed on either platform.

COSS-APP has been tested against the MIDAS CIVIL NX API for the Florida Department of Transportation Cantilever Overhead Tri-Chord Truss Support Structure, Index 700-040 — pairing FDOT-specific compliance with MIDAS finite element analysis.

COSS-APP has been tested against the MIDAS CIVIL API for U.S. Department of Transportation cantilever quad-chord truss support structures, bringing advanced finite element analysis to the more complex DOT truss geometries.

COSS-APP supports dual-chord truss cantilever sign structures — a cost-effective option for medium-span applications, with fewer connection points to fabricate and efficient material use under standard loading conditions. Models generate in minutes rather than hours, follow AASHTO LRFD, and support DOT compliance across multiple state standards.

OpenSTAAD MCP is a Model Context Protocol server that connects AI agents directly to Bentley STAAD.Pro through the OpenSTAAD COM API. Starting from a gantry structure modeled in COSS-APP, the model is restructured by a single natural-language instruction — no scripting and no manual node entry.

The Foundation feature brings Soil-Structure Interaction (SSI) into the STAAD.Pro model from the start. Instead of assuming an idealized fixed base, the model reflects how the foundation and surrounding soil actually respond under load — more realistic stiffness, more representative dynamic behavior, and fewer surprises between analysis and field conditions.