nTop

When you're competing for high-stakes aerospace programs, you don’t get second chances. Losing a program doesn’t just mean missing revenue; it can shut down an entire line of business. And too often, teams are forced to choose between speed and fidelity when both are mission-critical. nTop changes that equation. With implicit modeling and in-the-loop simulation, you can rapidly explore hundreds of high-fidelity design variants in the time it used to take to create just one. nTop helps aerospace engineers improve the scope and speed of what they can achieve in a day. • Create robust parametric models that instantly adapt to any configuration. • Generate high-quality performance data while you design. •Arrive at design reviews with detailed answers, not approximations. Because in a world where billion-dollar contracts are won on technical credibility, low-fidelity insight isn’t good enough. If your team is pushing the limits of conceptual design, we’d like to talk. 👉 Talk to an engineer today to learn what an nTop implementation looks like: https://lnkd.in/g6ZCMZr4

Accelerating Simulation Workflows with NVIDIA 💡 Rishikesh Ranade just showed how they've gone from running one wind tunnel experiment per week to processing orders of magnitude more designs using GPU-accelerated simulations and AI. Key breakthrough: 👏 Physics Nemo → Open-source framework for physics AI applications → New Domino neural operator scales to billions of mesh points → Works with implicit geometry (perfect for nTop workflows) → Includes pre-trained models (NIMs) ready for deployment The combination of NVIDIA's physics AI infrastructure with nTop's implicit modeling is creating new possibilities for rapid, high-fidelity design exploration. The future of engineering isn't just about better tools—it's about the AI infrastructure that makes those tools possible. Check out his presentation here: https://lnkd.in/ey6BjfPk #nTop #AI #PhysicsSimulation #NVIDIA #EngineeringDesign

A big thank you to our partner nTop! Thanks to their powerful computational design solution, we're able to design faster, more precisely, and more efficiently. This collaboration is truly impactful, and we’re excited about what we’re building together. Our sincere thanks to the entire nTop team for their ongoing support! . Un grand merci à notre partenaire nTop ! Grâce à leur puissante solution de conception computationnelle, nous concevons plus rapidement, avec plus de précision et d’efficacité. Cette collaboration a un réel impact, et nous sommes ravis de ce que nous construisons ensemble. Nous remercions chaleureusement toute l’équipe nTop pour son soutien constant ! #Innovation #ComputationalDesign #nTop #Engineering #Partnership

💡 External Aerodynamics for Early Aircraft Concepts 💡 At our nTop Computational Design Summit, Michael Emory, Product Manager at Luminary Cloud, showed what happens when advanced simulation, machine learning, and computational design come together. In collaboration with nTop and NVIDIA, Michael demonstrated a cutting-edge physics-AI workflow that’s transforming how early aircraft concepts are designed, analyzed, and optimized. Here’s what it unlocks: ⚙️ Real-time aerodynamic feedback inside the design environment 🚀 Inverse design workflows that search the output space—not just the input 🧠 Encoded simulation expertise that empowers conceptual designers with high-fidelity results 🔁 Thousands of optimized configurations explored in a fraction of the time This is more than faster meshing or simulation—this is removing workflow barriers entirely, giving design teams the insight they need when it matters most. 🎥 Watch Michael’s full keynote to see how Luminary, nTop, and NVIDIA are shaping the future of co-intelligent design: 👉 https://lnkd.in/ey6BjfPk #ComputationalDesign #PhysicsAI #CFD #LuminaryCloud #nTop #InverseDesign #SimulationDrivenDesign #AircraftDesign #Aerospace 

ML in Computational Design - A Breakthrough in Simulation Efficiency 🔥 What happens when you combine cutting-edge machine learning with complex engineering challenges like heat exchanger design? Carlos Mendez, Staff Opto-Mechanical Engineer at Lockheed Martin, shared the answer in his keynote presentation—highlighting a joint proof-of-concept with nTop that completely reimagines how thermal systems are designed and optimized. Traditionally, CFD-based heat exchanger design is time-intensive and resource-heavy. But with ML surrogate modeling, Carlos and the team: 🚀 Replaced full simulations with fast, accurate neural networks 📈 Used FNOs to predict full pressure and velocity fields 🧠 Enabled inverse design to target optimal performance parameters directly 🕒 Compressed weeks of simulation time into minutes of intelligent iteration This wasn’t just about saving time—it unlocked a new way of designing, one that’s more scalable, flexible, and aligned with Lockheed Martin’s push toward AI-enabled engineering. 🔗 Watch Carlos's full keynote here to see the workflow, results, and what's next for scaling this innovation across Lockheed’s AI infrastructure: 👉 https://lnkd.in/ey6BjfPk #nTop #MachineLearning #EngineeringInnovation #AIinEngineering #SurrogateModeling #LockheedMartin #Thermal

Aircraft designers can lose millions in late-stage redesigns when surface imperfections create drag or manufacturing issues that weren't caught early enough. nTop just launched advanced curvature analysis tools with metallic and zebra visualization styles that let you spot these problems in real-time as you design. With increasing pressure for fuel efficiency and faster development cycles, catching surface discontinuities, sharp edges, and curvature breaks early prevents costly wind tunnel surprises and manufacturing delays. Unlike traditional CAD where surface analysis happens after design freeze, nTop's implicit modeling gives you instant feedback during design iterations - so you maintain aerodynamic quality while exploring more design variants faster. Learn more here: https://lnkd.in/ehvTCY9Y #nTop #UI #productupdate #aerospace #rendering #implicitmodeling #surfaceanalysis

Over the past year, we’ve had the privilege of speaking with dozens of aerospace primes, innovative startups, and expert advisors with decades of experience in airplane design. From this deep well of knowledge, we’ve gathered invaluable insights that are shaping the future of nTop. In Brad’s keynote, we shared how nTop is using these insights to drive key innovations, helping A&D teams cut design cycles, reduce risk, and make better decisions faster. Here’s what we’ve learned: - Design Speed is Non-Negotiable: With shrinking timelines and rising expectations, engineering teams need to accelerate their design cycles without sacrificing performance or accuracy. - Flexibility in Early Design is Key: Too often, early-phase decisions lock teams into rigid paths. There's a pressing need for tools that allow dynamic iteration without getting stuck in the "lock-in trap." - Physics-Driven AI is the Future: Generating thousands of design variants and evaluating them in hours, not months, is no longer a luxury. It's a necessity for teams aiming to stay competitive. In response to these challenges, we’re empowering engineering teams to: - Rapidly explore and iterate on mission-critical designs with real-time insights. - Generate thousands of design variants in hours, not weeks, unlocking previously impossible design spaces. - Leverage physics-informed AI to guide decision-making and accelerate trade studies, allowing for faster, data-driven choices. These innovations are born from direct feedback and collaboration with industry experts, and we’re proud to be working alongside these leaders to push the boundaries of design and engineering. 👉 Watch Brad’s keynote to see how nTop is using these insights to help A&D teams close designs faster, reduce risk, and deliver mission-ready systems on modern timelines: https://lnkd.in/ey6BjfPk #nTop #Aerospace #EngineeringInnovation #ComputationalDesign #AIinEngineering #AerospaceEngineering

Excited to be hosting the team from Specter Aerospace at nTop HQ this week. Specter is carving a bold path in hypersonics, building the digital tools needed to harness today’s massive compute power and turn it into engineering velocity. Their platform is evolving fast to match the scale, performance, and complexity that next-gen propulsion systems demand. This week’s agenda: • Day 1: Modeling foundations • Day 2: OML development of engine + duct + body, and integration with analysis tools • Day 3: DOE setup, hypersonic propulsion optimization, OML detail for VF 3D printing, and present it to the combined leadership of both teams including Jan Vandenbrande and Felipe Gomez del Campo The mission: generate high-performance SCRAMJET variants, fast. They’ll leave with custom nTop blocks (parameterized with performance calcs, design constraints, and mission requirements) so they can create and evaluate radically different engine-body configurations in days, not weeks. They’ll show up to design reviews not just with robust, traceable, manufacturable designs but also with proof that their chosen concept outperforms the rest and the agility to adapt when the mission shifts. My favorite kickoff moment so far? Specter CTO Arun Chundru explained, “They told us only a prime could build a scramjet. We built one. They said only a prime could integrate it. We did that too.” To which George Irving from our team replied, “Wow. I guess you are a prime.” We’ve begun implementing Specter’s proprietary hypersonic design tools into nTop blocks and workflows: • RAMJET OML • Structural sizing • Inlets, isolators, and combustors • Internal packaging + mass buildups • Performance modeling and trade studies Deep exploration of the entire design space becomes possible without the hang-ups from traditional CAD to Sim. These guys are hungry and they are ready to move fast as hell. Great synergies between our teams. Stay tuned.

If you're working on advanced aircraft or spacecraft design and heading to AIAA AVIATION Forum, let me know so we can connect. I’m joining a panel hosted by Fahad Khan (Northrop Grumman) along with Han Park (Northrop Grumman), Peter Lyu (Luminary Cloud), Qiqi Wang (MIT AeroAstro / Flexcompute), Germán Ros (NVIDIA), and Ronal George (MathWorks) this Thursday (July 24, 9:30 am, Room 309) to discuss the Path to Physical AI in Aerospace: Lessons from Aircraft and Spacecraft Design, Simulation Systems, and Autonomous Driving. I’ll be discussing how nTop is enabling design systems that can respond to requirements autonomously, what's needed for that and how far away we are from engineers prompting systems like ours to generate entire design families. This all fits within the inverse design workflows we've been discussing -- and the data / tech stack needed for this. That means: -- CAD that won’t break when parameters change -- High-fidelity simulation workflows that don’t crash mid-run -- Datasets that are clean, versioned, and tied to physical models We’ve seen teams succeed when treating design parameters and performance outputs not as one-off's, but as training data for inverse design. That’s where things get interesting, like -- ML models that predict full flow fields from geometry inputs in milliseconds -- Optimization loops that run 1,000+ design variants guided by mission-level performance goals -- AI-assisted workflows that engineers can inspect, trust, and refine—not black boxes If you're wondering whether your workflow is AI-ready, come to the session. Or shoot me a DM about meeting tomorrow at AIAA -- I’ll share real-world criteria, program-tested examples, and a blueprint for getting started. And if you're already in the thick of it, let’s talk. We’re running workshops and setting up evaluations now to help teams capture and structure the data AI actually needs. Hope to see you there. BTW, Samuel Burns is there today demo'ing nTop running inference on the latest Luminary Cloud Shift-Aero model (screenshot below) -- more to come on this...

✈️ Heading to AIAA Aviation Forum? Come see what’s next in aerospace design! nTop will be at Booth #715 with our friends at Luminary Cloud, showcasing live demos and real-world workflows that are transforming how high-performance aerospace structures are designed. Stop by to explore how implicit modeling + GPU-powered simulation are accelerating innovation—from conceptual design to manufacturing-ready parts. 🤝 Meet members of the nTop team (Bradley Rothenberg, Samuel Burns) 💡 See fast, flexible design workflows in action 🖥️ Learn how nTop + Luminary Cloud integrate seamlessly 📍 Booth 715 | AIAA Aviataion #nTop #Luminarycloud #aerospace #physicsAI