Conferência da NAFEMS Américas 2026

Dos dados à decisão: impulsionar a simulação de engenharia inteligente

Open iT joins the NAFEMS Americas Conference 2026 in Saint Charles, Missouri. Heinrich Bartels shows how simulation usage data helps organizations quantify ROI, allocate limited resources, and make better engineering decisions, with lessons from Formula One-style constraints.

27 a 29 de maio de 2026

Centro de Convenções de Saint Charles

Saint Charles, Missouri, EUA

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SESSÃO DE INTERVENÇÕES

Quantificar o retorno do investimento em simulação através de dados de utilização: lições retiradas de restrições ao estilo da Fórmula 1

Esta sessão explora a forma como os dados relativos à utilização da simulação ajudam as organizações a tomar melhores decisões de engenharia, a melhorar a afetação de recursos e a maximizar o retorno do investimento em simulação em ambientes com restrições.

Sessão: Sessão 5 | Modelização e simulação de sistemas

Apresentador: Heinrich Bartels — Consultor Estratégico – Engenharia de Custos e Otimização de Programas

Sexta-feira, 29 de maio de 2026

10h00

Sala 102

Saint Charles, Missouri, EUA
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Entre em contacto com o Heinrich antes do evento ou vá conhecê-lo na NAFEMS Americas 2026.

Heinrich Bartels

Diretor de Engenharia de Custos e Otimização de Programas

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Apresentado e elaborado por

Open iT, Inc.
Heinrich Bartels

Resumo

Formula One engineering represents one of the most constrained simulation environments in modern industry. Aerodynamic performance gains depend heavily on CFD, FEA, and multiphysics simulation, yet teams operate under strict regulatory limits on CFD compute, wind-tunnel usage, and allowable development activity within fixed Aerodynamic Testing Periods. These technical constraints are reinforced by a season-wide financial cost cap that governs software licensing, compute infrastructure, and engineering effort. In such an environment, simulation ROI is defined not by the quantity of analysis performed, but by the quality of engineering decisions enabled by a finite simulation budget.

This presentation examines how simulation usage data can be used to evaluate and improve simulation ROI in environments operating under Formula One-style constraints. The discussion centers on how usage patterns across simulation workflows provide insight into where limited resources are consumed and how effectively they support aerodynamic development objectives. Metrics such as solver execution frequency, geometry iteration rates, feature utilization, license concurrency, and time-based demand reveal how simulation effort is distributed across development phases.

A central challenge addressed is the management of scarcity. Regulatory limits on CFD compute and testing force deliberate trade-offs between model fidelity, simulation frequency, and development focus. Without structured visibility, valuable simulation capacity may be consumed by low-impact or poorly timed analyses, reducing overall return on investment. Usage-based reporting enables engineering teams to identify these inefficiencies and prioritize simulation activity that delivers greater marginal aerodynamic value.

The presentation also explores the relationship between resource utilization and simulation ROI. Understanding patterns of license concurrency, idle capacity, and peak demand supports more effective alignment between engineering demand and available resources, particularly when all simulation activity contributes to regulated budgets. Time-resolved views of usage across Aerodynamic Testing Periods further enable forward planning, allowing teams to allocate simulation effort where it delivers the greatest performance benefit.

Although motivated by the extreme constraints of Formula One, the principles discussed extend to many engineering domains facing similar pressures, including aerospace, automotive, energy, and advanced manufacturing. In these sectors, simulation ROI increasingly depends on governance, prioritization, and decision quality rather than unrestricted computational scale. By treating simulation usage data as an engineering signal rather than an administrative artifact, organizations operating under Formula One-style constraints can maximize the value of simulation, turning limitation into a competitive advantage.

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