Digital Engineering
It has never been more important for engineers to be competent in the use of digital tools. The capability to exploit data and push the boundaries of what is possible is at the heart of structural engineering. Our industry’s ability to monitor, record, extract, and extrapolate information on structural performance continues to improve, leading to a growing need to better understand how to use big data and AI tools. Digital Engineering is an innovative, integrated approach that uses systems data and models as a continuum across disciplines to support engineering lifecycle activities from concept through disposal.
Structural Analysis
The ability to understand and manipulate information with digital computational tools is transforming structural engineering. Finite element analysis performed with digital computational tools allows engineers to automate the creation of analysis models, leaving more time for actual design work.
Thermal Analysis
Using digital tools to integrate thermal analysis into the design process allows engineers to adjust components earlier in the development cycle. Thermal simulation during design phases is about applying accurate, easy-to-use studies that operate in real-time.
Electrical Design
Simulation-led design empowers engineers to validate models and meet requirements in an accelerated way that creates more time for evaluating alternatives. Electrical engineers can design organically, starting with functional requirements. Component and module details emerge from historically-proven models, allowing specific tasks to be performed automatically, saving everyone time and money.
RF Design
The problem set in RF design includes UL- and FCC-related issues, implementing wireless communication technologies, and the need for robust circuit design and good PCB layout to minimize unintentional radiated emissions and low susceptibility to outside interference. Using system-level models, RF designers can rapidly explore ideas and tradeoffs, optimize system performance, and validate their models with measured data.