Enabling Mission-Critical Systems in Space with Digital Engineering

Across aerospace and defense, complex systems are no longer just a collection of components. Modern platforms, such as satellites, aircraft, and integrated mission systems, rely on software, system interactions, and real-world operational performance. Traditional engineering approaches, including Model-Based Engineering, are struggling to keep up with this growing complexity. Digital Engineering offers a practical way to understand system behavior earlier, reduce program risk, and support better mission-critical decisions, even before the first prototype is built. By combining system architecture, software behavior, physics-based simulation, and operational scenarios, teams can identify risks, explore trade-offs, and make faster, more informed decisions. This approach helps deliver systems on time, on budget, and with greater confidence.

We spoke with Juan Carlos Vicente Gonzalez, a Digital Engineering expert in aerospace and defense at SciEngineer, to understand how digital engineering is transforming the development of complex systems. From reducing program risks to accelerating delivery, he shared insights into the tools, strategies, and approaches that help aerospace teams build mission-critical systems with confidence.

1. Why are Digital Engineering practices relevant in the space industry?

Digital Engineering practices are increasingly important to organizations who want to engineer the next generation of spacecraft and infrastructure. The primary reason is that the space systems complexity has outgrown traditional practices: even plain Model-Based Engineering is falling behind. Modern spacecraft are reconfigurable, networked and context-aware in autonomous operation. Henceforth, it is possible to deduce that the interactions between systems and elements are even more dominant than any system in isolation.

In this context, Model-Based Engineering must be extended with the capability of optimizing mission-critical decisions through simulation. This is what SciEngineer promotes: exploiting orbital dynamics simulations, thermal modeling, radiation, attitude control, energy systems, etc. to redefine the limits of science before any testing campaign begins.

Another fundamental advantage of Digital Engineering is development speed and mission adaptability. Speed in the development lifecycle means that program managers, architects, and engineering teams must respond rapidly to evolving launch manifests, slots assignments and new opportunities. Keeping up with rapid design iterations, parallel development and modern software practices is now essential for competitive space programs.

Adaptability enables another strategic objective: the development of dual-use technologies. Dual-use refers to designing components and capabilities that can be reused across multiple applications, products, or operational contexts. For example, a control algorithm or embedded processor architecture developed for satellite thrust vectoring could also be adapted for a missile.

Digital Engineering facilitates this reuse by promoting modular, scalable, and interoperable space system architectures, critical for launch providers.

2. How can satellite behavior be understood in real-world conditions?

Understanding complex satellite behavior is one of the core challenges in Digital Engineering. Well-established organizations and agencies have been relying on documents or even models to learn how satellites behave in the different mission stages. This legacy contains a lot of validated engineering knowledge that needs to be selected thoroughly for proper Digital Engineering. It is not possible to just digitize it, as many times development was done in silos and thereafter only put together during AIT (Assembly, Integration and Testing). These silos typically arises a hidden question: Who owns the system interactions and data flows? Organizations with know-how in connecting their models have an edge over their competitors.

The space industry provides a strong illustration of this complexity through the need to operate in a hostile environment while maintaining performance throughout all mission phases. Organizations such as NASA have laid the foundations of modern Systems Engineering, and Ministries of Defense have further evolved these practices to optimize awareness and decision-making. Unsurprisingly, this evolution increasingly relies on simulation as the primary means to evaluate spacecraft behavior before launch.

Leveraging proven space legacy through Digital Engineering practices imply an integration-first approach for the system modeling. Historically, focus was on how to connect the different layers of a system, that is, establishing functional architecture, specifying logical components and determining the fidelity at physics-level simulations (orbital mechanics and link budgets are a good example). Today, satellites, particularly in LEO and software-defined payload markets, need to incorporate mission operations, with very strong focus on reusable, modular software rather than specialized hardware. This trend aligns with broader trends, such as Software-Defined Satellites and Virtual Ground Segments, bringing flexibility through software updates

Therefore, it would be possible to say that approaching the operations phase with good physics notions of the system and modelled scenarios can improve understanding of mission performance. As a result of these simulation-driven practices, constellation trade studies, fault injection for radiation effects or maneuvering experiments can enhance decisions based on integrated digital data.

3. How much of a satellite Digital Twin can be validated before launch?

Provided the Digital Twin’s fidelity is sufficient, a substantial part of it can be validated. In practice, most of all software logic and the overall performance can be deducted in simulations. There is exceptional value in using MathWorks tools as the Digital Engineering ecosystem because of the multiple domains it covers and tool interconnectivity. This enables integration early and allow designs to be tested and inspected, which reduces risks. It is possible to cover satellite communications, the antenna design, the thermal and energy management as well as Hardware-in-the-loop testing of the software with Speedgoat, amongst many options.

Nonetheless, there’s a caveat: Not everything can be done in a digital environment. Some complex behavior in real-world conditions prevail as a challenge. Digital Engineering does not eliminate satellite environmental testing, but it shifts left the verification and validation activities earlier in the lifecycle. The earlier risks can be observed and mitigated with proper requirements-based tests and traceability, the less surprises later when building the physical satellite.

Returning to on-orbit operations, outer space radiation may interact with the avionics, causing Single-Event Upsets, leading to bit flips or memory corruption. Although fault injection for this phenomenon can be simulated, predicting when this will happen or its degradation remains a probabilistic challenge. Thus, running simulations with adequate level of fidelity, redundant parts and following fault-tolerant design practices ensure the robustness, mitigating the risk.

4. What needs to change for organizations to adopt Digital Engineering?

Rather than focusing on which tools or methods to introduce, it’s a change in paradigm that requires a new space engineering culture. Model-Based Engineering initiated the transition from documents to models as source-of-truth, Digital Engineering embraces that change and takes that to the very extreme by treating models as authoritative, interconnected assets. These models are not only descriptive, but also mission-executable and governed decision-making assets.

It is also important to enable cross-collaboration teams, such as Systems Engineering, Operations, Software and Ground. Their challenge lies in connecting tools, workflows and data to build a digital thread (or weave a “digital fabric”) among mission requirements, system models, component tests, pipelines, telemetry data and all other assets. At the same time, regular engineers, developers should upskill in systems thinking and modern software-practices, such as DevSecOps.

This digital transformation must be driven by a strong leadership who clearly understands and advocates the values of Digital Engineering to mitigate risks without compromising mission success. Only those space organizations who align with Digital Engineering core ideas will succeed scaling up and adapting to the market’s demands in the evolving Space economy.