Bentley Systems announces the general access of SACS Wind Turbine Analysis, an extension of Bentley’s Scenario Services. This new cloud service enables faster, more robust analysis of turbine structures subject to wind and wave loading. Leveraging the power of high performance parallel computing on the cloud, wind turbine structural analysis can now be performed in minutes rather than hours. This dramatically improved turnaround allows engineers to consider many more potential solutions to find the ideal and optimal design.
On typical wind turbine projects, engineers need to make tradeoffs between the number of design iterations they can practically perform in a certain period, the complexity of the idealized model, and the number and scope of wave, wind, and mechanical load conditions. Bentley SACS Wind Turbine Analysis eliminates the need for the engineer to provide crude idealization or reduce the number of load conditions, allowing them instead to consider multiple design alternatives in a fraction of the time it used to take to perform a comprehensive design.
This release comes with a new tiered performance capability that enables users to right size their cloud computing needs. Organizations can better control their analysis costs by selecting a tier that more closely matches the number of load cases, model complexity, and the desired time to complete the analysis.
Bentley’s new SACS Wind Turbine structural cloud analysis capabilities include:
- Practical consideration of multiple design alternatives in parallel
- Analysis and consideration of hundreds of load conditions in parallel on a single design
- Tiered performance levels to fit the scope, cost, and schedule needs of the user
- Transparent compute resource utilization and management controls
Zachary Finucane, P.E, project manager with Keystone Engineering Inc., said, “Bentley’s SACS Wind Turbine module allowed us to streamline the analysis process, thereby reducing the design cycle time, the cost to the client, and the risk of errors managing the tremendous amount of data needed to perform over 3,000 time-domain simulations.”
Raoul Karp, VP of analytical modeling development with Bentley Systems, said, “Performing comprehensive wind turbine analysis has always required significant compromises by engineers on the model complexity, loading completeness, and conservative assumptions. By unlocking the power of almost infinite cloud compute resources, engineers can now finally consider all load conditions and model complexities in far less time than using an in-house desktop solution.”
About SACS Wind Turbine
SACS Wind Turbine Structural Analysis Software allows engineers to explore design alternatives for safe, cost-effective offshore wind farm structures with confidence. Save time with comprehensive, automated capabilities to determine environmental and mechanical loading responses. The application reduces risks with integrated analysis for predicting fatigue and extreme loads for substructures and non-linear foundations. It also reduces runtime for the large number of time history simulations required for fatigue and strength analyses through distribution across multiple processor cores. SACS Wind Turbine improves the design process for offshore wind turbines with both fully coupled and uncoupled analyses.
About the CONNECT Edition
With the SELECT CONNECT Edition, Bentley is introducing SELECTCONNECTservices, new Azure-based services that provide comprehensive learning, mobility, and collaboration benefits to every Bentley application subscriber. Adaptive Learning Services help users master use of Bentley applications through CONNECT Advisor, a new in-application service that provides contextual and personalized learning. Personal Mobility Services provide unlimited access to Bentley apps, ensuring users have access to the right project information when and where they need it. ProjectWise Connection Services allow users to securely share application and project information, to manage and resolve issues, and to create, send, and receive transmittals, submittals, and RFIs.