Lensing 2020 and beyond: 8 megatrends in engineering modeling and simulation

Bruce Jenkins | Ora Research

This second decade of the twenty-first century is witnessing an explosion of invention and innovation in digital engineering technologies unrivaled since the 1980s, when so many foundational tools and methods were either created or brought to practical fruition. Here are eight megatrends that we believe will drive generational leaps forward in engineering modeling and simulation technologies, methods and work processes through 2020 and well beyond:

  • Simulation-led, systems-driven product development.
  • Democratization of engineering modeling and simulation.
  • Simulation app revolution.
  • Design space exploration.
  • Topology, materials and process optimization for additive manufacturing.
  • Simulation for the Industrial IoT and Industry 4.0.
  • Big-data analytics in simulation.
  • Cloud HPC for simulation.

Already, each of these is today the focus of intense development by technology providers—and of investigation, investment and, in many cases, deployment by leading engineering organizations. Much of this work is succeeding in at last transforming long-established, powerful but formerly difficult-to-use, specialist-user-only tools into practical everyday engineering aids. And some of it—rather a lot, actually—is giving engineering organizations capabilities never before possible.

trends in engineering
Naisbitt’s 1972 classic of forecasting and futurology.

Enabling leaps forward are underway in both hardware and software architectures

Hardware—From on-premise to cloud:

  • Universally accessible.
  • Fosters infinitely elastic collaboration among users.
  • Commodity pricing (AWS, Azure, et al.) makes unprecedented computing power available to all.
  • Cloud HPC at last removing longstanding cost barriers to adequate CAE processing power.

Software—From SQL schema-on-write database architectures to NoSQL schema-on-read architectures:

  • Fast.
  • Scalable.
  • Designed to exploit cloud computing resources.
  • “Schema-on-read” allows data to be captured, stored and subsequently acted on with almost limitless freedom, without the application developer having to create a schema for the data in advance.
  • Two key benefits of schema-on-read:

o   “Gives you massive flexibility over how the data can be consumed.”—Tom Deutsch, Solution CTO with IBM.

o   And “your raw/atomic data can be stored for reference and consumption years into the future.”—Deutsch.

Leading NoSQL database MongoDB:

  • Powers eBay, FourSquare, LinkedIn and many other massively participatory sites.
  • In engineering, MongoDB is the database platform used by:
    • Onshape.
    • Frustum.
    • More on the way.

Across the coming months and years we look forward to continuing our investigation and coverage of these and more step-change developments enabling and driving today’s and tomorrow’s revolution in engineering modeling and simulation.

MongoDB

Onshape blog

Frustum

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