Digital Engineering Fundamentals

In This Section

Overview

In this 8-hour course, students will gain an in-depth understanding of Digital Engineering tools, principles, and practices. They will learn to think digitally, not digitized, and to focus on DE to transform lifecycle processes to deliver knowledge enabling better decision making at the speed of relevance.

The course will introduce Digital Engineering strategies and methods to transform system engineering paradigms deploying model-based digital surrogate truth sources, demonstrate the context and value of implementing uncertainty quantification at all levels and phases of decision making under risk, and translating high-volume, high-velocity digital data into better products, processes, and mission effectiveness by delivering essential knowledge to master risk at the speed of need.

SMARTUQ, an uncertainty quantification (UQ) and analytics software tool, will be used for practical illustrations of the context and methods for UQ applications to the creation of digital surrogate truth sources, quantified margins and uncertainties, and support to decision making under risk.

Learning Objectives 

  • Gain an in-depth understanding of Digital Engineering concepts and methods
  • Create, calibrate, and apply authoritative digital surrogates truth sources
  • Implement quantified margins and uncertainties analyses to master risk at critical decision points
  • Discover better systems and test engineering performance metrics to support Test & Evaluation (T&E) and critical decision making under risk
  • Translate the DoD Digital Engineering Strategy into practical actions to create lifecycle value
Who Should Attend
This course is intended for decision makers, program managers, chief engineers, test engineers, engineers, analysts, and data scientists from aerospace or any other industry interested in creating business value.
Outline
Lecture 1: Introduction to Digital Engineering Principles and Practices
  • Digital Engineering History and Terminology
  • DoD Digital Engineering Strategy
  • Digital Engineering Enabled Value
  • Model Based Systems Engineering (MBSE) 
  • Model Based Engineering (MBE)
  • Authoritative Digital Surrogates
  • Mastering Risk
Lecture 2: Uncertainty Quantification
  • Introduction to Uncertainty & Probabilistic Analysis
  • Uncertainty Quantification (UQ) Process Overview
  • Uncertainty Quantification Methods and Benefits
  • Design of Experiments (DOEs)Gaussian Process Emulation
  • Improving Design Space Sampling
  • Sensitivity Analysis
  • Uncertainty Propagation
  • Statistical Calibration
  • Digital Twins
Lecture 3: Transforming Systems Engineering and Test & Evaluation (T&E)
  • Transformation of Systems Engineering Using Digital Engineering
  • Systems Engineering Performance Metrics
  • Digital Critical Decision Making
  • T&E Transformation Using Digital Engineering
  • Optimizing T&E campaigns
  • Digital Test and Evaluation Master Plan
Lecture 4: Authoritative Virtualization and Decisioning
  • Architecture Centric System Development
  • Mission Engineering – Putting It All Together
  • Lifecycle Meta-Model for Authoritative Virtualization
  • Continuous Digital Intelligence for Authoritative Decisioning
Instructors
Dr Edward Kraft has over 48 years’ experience in innovative integration of high-performance computing with ground/flight testing. He is of the early pioneers and principal architects for the AF Digital Thread/Digital Twin and continues working across the A&D Industry advancing concepts for Digital Engineering applications. He is an AIAA fellow and Digital Engineering Integration Committee member.
 
Gavin Jones, SmartUQ Applications Engineering, is responsible for performing simulation and statistical work for clients in aerospace, defense, automotive, gas turbine, and other industries. He is a contributor to SmartUQ’s Digital Thread/Digital Twin initiative.