Martin Eriksson
Head of Computational Structural Mechanics
Validus Engineering AB
Martin Eriksson holds a Doctoral degree from Department of Design Sciences at the Faculty of Engineering LTH, Lund University, Sweden. He has 20 years of experience from CAE analysis activities in various industry segments such as; automotive, aerospace and offshore. During the years he has been given the opportunity to be involved in various analysis activities in high-tech projects in technology intensive industry segments involving both product development projects as well as method development projects out of which a few are listed below:
- Development of a method and an in-house tool for prioritization of design proposals in the early turbomachinery blade design work with respect to high cycle fatigue (HCF).
- Development of tools for extraction and visualization of HCF evaluations within offshore industry.
- Development of methodology and performing execution of complex FSI (Fluid structure interaction) problems in e.g. bridge and platform reinforcements of offshore structures (one-way) and Formula 1 racing wing developments (two-way).
- Development of Guideline that gives guidance on how to perform non-linear FE-analyses to determine structural capacity of offshore components forming part of jackets and topsides (tubular joints and members, fabricated sections, bolted connections and fillet welds).
Currently Eriksson acts as Head of Computational Structural Mechanics at Validus Engineering AB, Sweden. He leads a team of design analysts that performs CAE analyses as well as developes in-house as well as customer company methodologies, procedures, tools and standards for advanced CAE analysis.
Abstract
Activities and Factors Essential to the Endorsement of Confidence in Numerical Simulation and Predictions
The rapid development of design analysis tools and methods such as the finite element method, computational fluid dynamics, and multi-body systems, during recent decades has fundamentally changed the way in which products are nowadays designed and developed. This comes, obviously, with challenges such as increasing demands and constraints in planning, executing, controlling and monitoring of design analysis activities as well as in documenting and communicating the results obtained. Furthermore, the circumstances in which the design analysis activities are performed in an actual industrial setting are bounded by factors influencing the design analysis activities and their results. The understanding of uncertainties connected with these factors is important for providing insights to establish confidence in the decisions following the design analysis activity outcome. Moreover, in situations where design analysis is to replace more traditional validation and certification methods as well as being applied in new digital areas, an even greater confidence in the design analysis process and its results is required.
The presentation will discuss around activities and factors essential to the attainment of the increased confidence and the developed Predictive Design Analysis (PDA) methodology that facilitates, at an operational level, the increased confidence will be elaborated on. The PDA methodology is built upon three originally developed constitutive parts:
- The Generic Design Analysis (GDA) process model that provides, at an operational level, an overall approach to planning and execution of design analysis activities as well as for monitoring, communicating and incorporating the obtained findings into the engineering design project.
- Factors (endogenous and exogenous) influencing the design analysis activity emanating from the environment in which the design analysis activity is originated and executed and the
- Confidence Appraisal Activities (CAAs) that provides a foundation for ascertaining the confidence level in the decisions and predictions made when performing a design analysis activity.
The PDA methodology can be successfully adapted to accommodate efficiently and effectively design analysis activities execution in different contexts. The access to such adaptions can also be used as a powerful planning tool as well as it provides the means for supervision and control of design analysis activities. Adhering to the methodology will furthermore give stakeholders insight into what can be expected and what will be required to achieve a given confidence level in prediction. The understanding of confidence level assessment is a vital cornerstone in (and necessity for) assuring endorsement from management to invest in resources and expert knowledge facilitating a continuing extended use of design analysis in an industrial setting.
