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3D printing and AI reshape nuclear construction in Tennessee
In East Tennessee, engineers have put a robotic 3D-printing arm to work producing detailed molds used to cast concrete shielding columns for the Hermes Low-Power Demonstration Reactor, a project backed by the US Department of Energy. Oak Ridge National Laboratory (ORNL) reports that large segments of the build were completed in just 14 days — a pace that would have taken weeks using traditional construction techniques. The initiative signals a shift toward additive manufacturing and artificial intelligence in nuclear infrastructure.
How the method works
The project uses industrial-scale 3D printing to fabricate precise, complex molds for concrete casting. These molds enable forms and geometries that are difficult or costly to achieve with conventional formwork. AI tools were applied to support design iterations and optimize production workflows, helping reduce manual drafting and accelerating decision-making during fabrication.
Product features: What the technology brings
- High-precision 3D-printed molds for complex concrete components
- AI-assisted design and generative design options to optimize material use
- Faster on-site production cycles — ORNL recorded major work completed within 14 days
- Potential for greater use of domestic materials and a more resilient supply chain
Comparisons: Additive vs. traditional construction
Compared with cast-in-place and modular conventional methods, 3D-printed molds offer superior geometric freedom and faster iteration. Traditional formwork requires more labor and time for complex shapes, while additive manufacturing reduces custom tooling time. However, conventional methods have a long track record for decades-long durability and standardized quality assurance procedures that 3D-printed workflows must match or exceed.
Advantages, challenges and safety considerations
Speed, cost efficiency, and flexibility are clear advantages: additive manufacturing can reduce labor hours, cut material waste, and enable on-demand production for unique shielding geometries. AI can also reduce design errors and automate repetitive checks. Yet heavy reliance on AI raises governance questions: who validates automated design decisions, and how are model errors detected? Equally important is long-term durability — nuclear reactors must operate safely for decades, and novel 3D-printed components require rigorous lifecycle testing, non-destructive evaluation (NDE), and regulatory approval.
Use cases and market relevance
Use cases extend beyond shielding columns: small modular reactors (SMRs), prototype demonstration reactors like Hermes, rapid prototyping, and complex internal structures are prime candidates for additive techniques. Market relevance is driven by rising energy demand from AI systems and hyperscale data centers: nuclear power offers stable baseload supply, and in the future, AI-driven design tools may contribute to reactors that ultimately power those same AI systems — creating an efficient but carefully monitored feedback loop.
What comes next
3D printing and AI represent powerful tools to modernize nuclear construction and strengthen the domestic supply chain. To translate speed gains into safe, deployable technology, the industry will need expanded standards, transparent model validation, enhanced quality assurance, and sustained regulatory oversight. Faster builds are compelling, but safety and longevity must remain paramount as the sector explores this new era of digital-driven nuclear engineering.
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