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What is VABS?

VABS serves as a popular instrument for conducting cross-sectional analyses, enabling quick and uncomplicated calculations of beam properties and the retrieval of three-dimensional fields in composite beams, commonly utilized in components like helicopter and wind turbine blades. It is unique in its capacity to disentangle a complex 3D slender solid with intricate microstructures into a basic engineering beam model. Developed by AnalySwift, which has its roots in aerospace, tools specifically designed for composite beams, including those used in helicopter rotor blades, propellers, high aspect ratio wings, and various wing section designs, as well as plates, shells, and three-dimensional frameworks, have emerged. VABS has been applied in the wind turbine sector for several years, consistently delivering rapid and accurate modeling results for wind turbine blades. Additionally, SwiftComp broadens its functionality, providing solutions for plates, shells, and 3D composite configurations. As the automotive industry increasingly adopts composite materials in vehicle construction, there is a significant opportunity to apply both SwiftComp and VABS for modeling a wide spectrum of structural forms, including beams, plates, and shells, further enhancing their usability. The adaptability and efficiency of these tools render them essential across various engineering fields, thus fostering innovative designs in multiple industries.

What is ONYX Insight?

ONYX Insight provides comprehensive predictive maintenance solutions specifically designed for wind turbine operators, integrating state-of-the-art sensing technologies, software analytics, and professional engineering consultancy to enhance turbine performance and reduce operational costs. Their versatile, hardware-agnostic platforms, such as fleetMONITOR and AI HUB, merge data from various monitoring systems, including vibration sensors, oil analysis, SCADA, and pitch-bearing diagnostics, into unified dashboards, facilitating effective health assessments across entire fleets and enabling proactive fault detection. The AI HUB platform includes dedicated modules for pitch bearing monitoring, utilizes drone technology for blade inspections, manages case studies, and offers insights on energy losses, significantly improving operational processes and supporting informed maintenance decisions. Additionally, ONYX Insight has developed ecoCMS, an economical condition monitoring system that employs MEMS technology, along with ecoPITCH, a sensor system aimed at the early detection of pitch-bearing failures. This extensive array of resources underscores ONYX Insight's dedication to fostering innovation and efficiency within the wind energy industry, while also paving the way for future advancements in renewable energy technologies. By continuously evolving their offerings, ONYX Insight ensures that wind turbine operators can optimize their operations and contribute to a more sustainable energy landscape.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

AnalySwift

Date Founded

2011

Company Location

United States

Company Website

analyswift.com

Company Facts

Organization Name

ONYX Insight

Date Founded

2008

Company Location

United Kingdom

Company Website

onyxinsight.com

Categories and Features

Simulation

1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Design Analysis
Industry Specific Database
Presentation Tools
Turbulence Modeling

Categories and Features

Wind Farm

Not specified

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