Innovation Competitions And Prizes

We are at a critical crossroads for the future of European aviation. The Draghi report highlights three urgent challenges: energy security, European competitiveness, and emissions reduction. The aviation sector is making continuous efforts towards a lower emissions future, with the first year of ReFuelEU SAF mandates now in effect. Amongst the many challenges, one opportunity stands out: European leadership in e-SAF, an alternative aviation fuel produced using clean electricity, which has the potential to begin addressing all three challenges.    Air France-KLM invests heavily in fleet renewal to reduce CO2 emissions, on top of being the largest buyer of SAF amongst all airlines. However, there is an urgent need for alternatives such as e-SAF to further reduce emissions, as we see that global air traffic continues to grow due to increasing demand.     That's why we co-founded Project SkyPower, a coalition of aviation partners, including airlines, e-SAF innovators, and finance houses. We are calling on EU policymakers to urgently facilitate a more enabling policy environment to accelerate corporate action via five key interventions: 1️⃣ Make e-SAF a strategic priority in the Clean Industrial Deal and the Sustainable Transport Investment Plan 2️⃣ Recycle ETS revenues from aviation to capitalise a market intermediary that enters long-term contracts with e-SAF producers and short-term contracts with offtakers 3️⃣ Establish a bridging mechanism in 2025 to support first movers before the intermediary comes online 4️⃣ Provide certainty on mandates, production criteria and penalties 5️⃣ Mitigate project-on-project risk via a government-backed backstop mechanism   The EU has all the ingredients to lead on e-SAF—now it must act.   See the open letter developed by Project SkyPower here: https://lnkd.in/eY26MZTB   #eSAF #ProjectSkyPower #ReFuelEU

Most people think NASA won the early aerospace race because it had smarter engineers. That’s the wrong explanation. Look closely at this ramp at NASA’s Armstrong Flight Research Center (formerly Dryden). It isn’t a lineup of exotic aircraft. It’s a portfolio of probable questions being answered in parallel. • X-31 — thrust vectoring control laws • F-15 ACTIVE — flight control experimentation • SR-71 Blackbird — extreme high-speed envelope knowledge • F-16XL — high-lift and laminar flow research • X-36 — unstable tailless dynamics • X-38 — spacecraft recovery concepts Different vehicles. Different programs. Same institutional capability: Structured flight test. A pattern you see across successful aerospace organizations: Breakthrough capability rarely comes from a single brilliant design. It comes from an organization that can reduce uncertainty faster than everyone else.That requires infrastructure most programs quietly underfund: • Instrumented flight ranges • Chase aircraft • Telemetry and data reduction systems • Flight test engineers • Envelope expansion doctrine • Independent safety boards • Training pipelines for experimental crews These assets compound over decades. Many emerging space programs heavily fund research labs and prototype development but underinvest in test cadence and operational learning systems. Research generates ideas. Testing generates confidence. Training generates judgment. The ramp at Armstrong wasn’t just hardware. It was an institutional learning engine. Fly. Instrument. Analyze. Modify. Repeat. Across aircraft. Across decades. Across generations of engineers. That institutional muscle eventually shows up where it matters most: Launch reliability. Mission assurance. Crew safety margins. Hardware can be reverse engineered. Test culture cannot. If an agency wants to close the gap in aerospace - space capability, the real investment isn’t another prototype. It’s the infrastructure that allows hundreds of experiments to quietly run every year. Curious how others see this balance today especially in emerging space programs trying to build capability quickly. Because in aerospace, the organizations that pull ahead are rarely the ones with the boldest designs. They’re the ones that learn faster than the physics can punish them. Keen about systems-level patterns behind aerospace and space programs that scale and the institutional decisions that determine who leads the next era. #FlightTest #SystemsEngineering #SpacePrograms #MissionAssurance

Over the years working in chemical processing, one of the recurring challenges I’ve faced is with heat exchangers. They are essential for energy efficiency, but even minor issues can create significant downtime and cost. Not long ago, we encountered a serious fouling issue in one of our exchangers. The deposits were reducing heat transfer efficiency, causing higher energy consumption and forcing frequent shutdowns for cleaning. 🔍Instead of treating it as just another maintenance task, we carried out a detailed root cause analysis: • Reviewed process conditions and flow patterns. • Checked velocity and temperature profiles. • Involved both the operations and maintenance teams in the discussion. The findings showed that low fluid velocity was the main driver for fouling. By redesigning the piping layout and adjusting the operating parameters, we were able to: ✅ Increase turbulence and reduce fouling. ✅ Extend cleaning cycles from every 3 months to once a year. ✅ Achieve over 15% improvement in efficiency. For me, the key takeaway is that every technical problem is also an opportunity to innovate and improve reliability. Collaboration and data-driven decisions can transform a recurring issue into a long-term success.

You likely know that pyrolysis is the heating of organic material at high temperatures, without oxygen. It sounds straightforward, until you try to run a line every day. Across projects, the same five issues keep showing up. They explain why so many biochar plants underperform or stop entirely. 📌 #Tar: the silent killer Tar isn’t “dirt in the gas.” It condenses, sticks, and builds up in pipes and downstream equipment. If you don’t design for tar from day one (temperature profile, residence time, cleaning), it will become a constant operational headache. 📌 #Feedstock variability = unstable operation Moisture, particle size, ash content, composition… feedstock is never truly constant. Same machine, same settings, different behavior. If you don’t control feedstock, you can’t control your process. 📌 #Temperature control and heat transfer Brochures show a perfect setpoint. Reality is hot spots, cold zones, slow heat transfer. That’s how you can end up with incomplete conversion, tar formation, and inconsistent char quality. For biochar and CDR, a stable temperature profile matters more than peak temperature. 📌 #Gas & emissions management Dirty syngas is both a technical and regulatory problem. Undersized cleaning and unreliable combustion/flaring quickly become operational bottlenecks and permitting risks. 📌 #Mechanical reliability & maintenance Dust and ash abrade. Thermal cycles stress seals. Sticky condensables block moving parts. At scale, the real KPI isn’t nameplate capacity. It’s on-stream time. What does this mean for projects? If you want a factory that actually runs, priorities should look like this: ➡️ Feedstock strategy first, machine second ➡️ Aggressive tar thinking baked into the design ➡️ Serious temperature instrumentation (not one probe and hope) ➡️ Robust gas treatment and reliable combustion/flaring ➡️ Maintenance-ready layout, access, and monitoring Most project decks ignore these points and most failed factories are built exactly like those decks. Designing with these constraints in mind is what separates pyrolysis plants that struggle from plants that run smoothly. 📈 Crystalchain

🚀 #TeachMeTuesday: “Failure is an option (2024)” — Why SpaceX out-innovates traditional aerospace Today I pick up a few papers assessing the overall innovation approach and success of SpaceX, and to generate lessons for overall innovation strategy at the firm and country-level. In reality, SpaceX is operating more like a software company than an old-school aerospace giant: → Fast test loops → Learning-driven innovation → Governance that enables failure and iteration The papers show that its innovation system is built on governance mechanisms that embrace failure. For those aiming to accelerate progress in critical technologies — from advanced manufacturing to climate tech to AI — understanding this model might be key. How does SpaceX deliver over 100 launches a year, while cutting costs and iterating faster than state programs? 👉 A great new paper by Vittori et al. (2024) — "Failure is an option: How failure can lead to disruptive innovations"https://lnkd.in/eE8f2hJR — dives deep into how SpaceX systematically designs failure into its governance: → High test cadence → Failure-tolerant engineering culture → Management insulation from public/political backlash → Reuse and rapid iteration 👉 In parallel, Ansar & Flyvbjerg (2022) — "How to Solve Big Problems: Bespoke Versus Platform Strategies" https://lnkd.in/e9k3XjmH show that SpaceX’s platform-based approach (versus NASA’s bespoke project model) delivers: ✔️ 10x cost savings ✔️ 2x faster development ✔️ Lower systemic risk Some interesting facts that are more recent. 📊 SpaceX 2024–25: The governance-driven innovation system in numbers: Launch cadence: 🛰️ 134 Falcon 9 launches in 2024 — more than 50% of global orbital launches Reuse rate: 🔁 ~80% booster reuse (some boosters with 25+ flights) → AINvest 💰 ~$62 million per Falcon 9 launch — nearly 20x cheaper per kg than the Space Shuttle 🌐 Ecosystem feedback & platform thinking Cai et al. (2024) — "SpaceX’s Network Effects and Innovation Strategy Analysis" — further show how SpaceX’s ecosystem works https://lnkd.in/egh94Bmd Starlink → feeds launch revenue More launches → improve learning → funds Starship A true commercial + technological feedback loop 🚀 Prof. Bent Flyvbjerg SpaceX Elon Musk, Tesla and SpaceX News by Newslines Claire Jolly Marit Undseth dominique guellec Mattia Olivari

𝗦𝗲𝗮𝘁𝘁𝗹𝗲 𝗧𝗲𝗰𝗵 𝗪𝗲𝗲𝗸 𝟮𝟬𝟮𝟱: 𝟱 𝗟𝗲𝘀𝘀𝗼𝗻𝘀 𝗧𝗵𝗮𝘁 𝗖𝗵𝗮𝗻𝗴𝗲𝗱 𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 Last week running around downtown Seattle, frantically searching for parking, rushing between events with my laptop bag bouncing on my shoulder. The usual startup founder chaos. But one panel discussion stuck with me especially and completely reframed how I think about our NASA SBIR application. The Context: Building real-time monitoring for aerospace additive manufacturing. The problem? 40% of titanium parts fail post-production due to undetected defects that traditional NDT can't catch at printing speeds. The Panel That Changed My Perspective: Austin Link (CEO, Starfish Space), Livingston Holder (CTO, Radian Aerospace), and Cindy C. (CEO, Planetary AI) sharing their biggest technical challenges. 5 Key Lessons: 𝟭. 𝗦𝗽𝗮𝗰𝗲-𝗚𝗿𝗮𝗱𝗲 = 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝗣𝗵𝘆𝘀𝗶𝗰𝘀 Austin Link: "The hardest part isn't building the technology. It's building it to survive what space actually throws at you." - 𝗠𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: Our sensor durability requirements just got 10x more stringent. Space doesn't forgive "good enough." 𝟮. 𝗠𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗗𝗼𝗲𝘀𝗻'𝘁 𝗘𝘅𝗶𝘀𝘁 𝗬𝗲𝘁 Livingston Holder: "Hypersonic vehicles demand manufacturing precision that doesn't exist yet. We're not just building aircraft, we're inventing the processes to build them." - 𝗠𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: We're building infrastructure for an industry that's about to explode. 𝟯. 𝗘𝗱𝗴𝗲 𝗔𝗜 = 𝗠𝗶𝘀𝘀𝗶𝗼𝗻 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹, 𝗡𝗼𝘁 𝗖𝗼𝗻𝘃𝗲𝗻𝗶𝗲𝗻𝘁 Cindy Chin: "AI in space applications isn't about convenience. It's about making split-second decisions when failure isn't an option." - 𝗠𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: Our real-time processing isn't a nice-to-have feature. It's life-or-death reliability. 𝟰. 𝗧𝗵𝗲 𝗥𝗲𝗮𝗹 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗣𝗮𝗶𝗻 𝗣𝗼𝗶𝗻𝘁 All three leaders circled back to the same bottleneck: manufacturing systems that can't keep up with design ambitions. - 𝗠𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: NASA's RAMPT program is just the beginning. Every aerospace company faces this same challenge. 𝟱. 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗗𝗲𝗽𝘁𝗵 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 I'm sitting there with my notebook (yes, I still write things down by hand, old habits from my PhD days), frantically scribbling when I realized: these aren't just business leaders. They're engineers solving problems that didn't exist five years ago. - 𝗠𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: Don't dumb down the physics for investors. Find investors who get excited about heat transfer equations. Hell yeah! My nerdy side jumps up and down! :) Shoutout to the woman at the AI House BBQ who told me, "Your explanation of sensor fusion just made my brain hurt in the best way possible." Sometimes you need that reminder that you're working on something genuinely hard. For fellow deep tech founders, tell me where you are at? #SeattleTechWeek #DeepTech #ManufacturingAI #NASA #StartupLessons #Aerospace #TechFounders

🚀 Mastering Design Criteria for Chemical Process Engineering 🚀 Designing a chemical process plant is no small feat. It requires a deep understanding of design criteria to ensure safety, efficiency, and cost-effectiveness. Whether you're working on a Conceptual Design,Feasibility Study, getting the design criteria right is crucial for the success of your project. Here are some key insights from the Design Criteria for Chemical Process Engineering that every engineer should know: 1. Risk Management: - Risk = Probability x Impact Understanding risks is at the core of any design. From process safety to environmental protection,risk management ensures that your plant operates safely and efficiently. -Critical Services & Items: Identify operations and equipment that are vital to the process. 2. Operating Life & Time - Operating Life: Most process plants are designed to operate for 20 to 40 years. However, some plants, may have a shorter life. -Operating Time: Understanding the operating time helps in selecting the right equipment and designing for reliability. 3. Design Conditions: -Design Pressure & Temperature: These are critical for ensuring that equipment can withstand normal and abnormal operating conditions. -Pressure-Temperature Ratings: Pipe flanges and fittings have specific pressure-temperature ratings based on materials and applications. 4. Capacity & Quantity: - Capacity: Equipment is typically designed to handle 100% capacity, but sometimes partial capacity is sufficient. - Quantity: The number of equipment units depends on the capacity and operational needs. 5. Materials of Construction: Durability and Cost - Material Selection: The choice of materials depends on factors like corrosion resistance, temperature, and pressure. -Cost Considerations: Materials like titanium or Hastelloy are expensive but necessary for extreme conditions. 6. Utilities & Treatment Media: -Utilities: These include air, water, steam, and power, which are essential for the process. -Treatment Media: Materials like catalysts or absorbents are used to remove undesired components or speed up reactions. 7. Cost Estimation: -Economic Objectives: Every project is an investment. The design must balance cost-effectiveness with performance, and regulatory compliance. -Cost Estimation Models: Use models like the Rule of Six-Tenths or Cost Indices to estimate equipment costs. 📌Key Takeaway:  Design criteria are the backbone of any chemical process engineering project.Understanding these criteria is essential for delivering a successful project. 🔗 Download the full guide to dive deeper into the design criteria for chemical process engineering. 📢 Call to Action:  If you’ve worked on chemical process design, what’s the most challenging aspect of defining design criteria? Share your experiences in the comments below! Let’s learn from each other and grow as professionals. 💪 #ChemicalEngineering #ProcessDesign #DesignCriteria #EngineeringDesign #LinkedInCommunity

A lab experiment can design a factory. Only if the ratios are respected. Nature doesn’t care about size. It doesn’t care about CAD models. It doesn’t care about scaling laws written in reports. It cares about which force dominates. That’s why engineers don’t scale plants by length. We scale them by dimensionless numbers. • Reynolds (Re) → Will flow behave… or turn chaotic? • Prandtl & Nusselt (Pr, Nu) → Will heat actually transfer? • Schmidt & Sherwood (Sc, Sh) → Will mass reach the surface? • Froude & Weber (Fr, We) → Will fluids flow, surge, or atomize? • Mach (Ma) → When does compressibility change everything? Miss just one ratio, and a perfect lab result becomes a plant failure. This is not exam theory. This is scale-up survival. From CFD → pilot → full-scale industry, physics stays honest only when the ratios match. Save this. Every engineer needs it — sooner or later. #ChemicalEngineering #ProcessDesign #ScaleUp #FluidMechanics #HeatTransfer #MassTransfer #CFD #IndustrialEngineering #EngineeringReality #LearnEngineering

WE LOST 3 MONTHS ON A “VALIDATED” PROCESS. Everything was ready. Lab data ✔ Pilot batches ✔ Process locked ✔ The transfer should have been easy. It wasn’t. First batch at the new site: ❌ low yield ❌ unexpected impurity ❌ longer reaction time “Let’s run another batch.” Second batch: Still unstable. Now the pressure starts: Production wants answers R&D defends the process Management wants timelines Weeks turn into months. Root cause analysis begins: Raw materials? → Same Procedure? → Same Temperature profile? → Same Finally… someone asks the right question: “What’s different in the reactor?” And there it was: Different impeller Different diameter Different circulation pattern Same rpm. Completely different mixing. The feed was hitting a different zone. Local concentration spikes appeared. The reaction pathway shifted. Nothing was “wrong.” The process was just… not the same process anymore. That single oversight cost: 3 months multiple failed batches hundreds of thousands in materials and a lot of internal friction Here’s the lesson: Validation at one scale or site doesn’t guarantee transfer. Because chemistry follows physics. And if you don’t reproduce the mixing environment, you’re not repeating success— You’re rerunning an experiment. How many “process failures” are actually transfer failures? #ScaleUp #TechTransfer #Pharma #ChemicalEngineering #ProcessEngineering #Mixing #Manufacturing

Designing rocket engine components is the easy part—manufacturing them to meet all intended design requirements with repeatability and reliability is tough! Additive manufacturing (AM) enables complex geometries, eliminates the specialty skills for brazing or plating, and speeds up prototyping or production, but still has a lot of challenges. One major challenge in AM is surface texture—roughness, waviness, and form—all impacting performance in different ways. This paper represents years of research on laser powder directed energy deposition (LP-DED) for large-scale heat exchangers, such as rocket nozzles with microchannels. We explored surface finishing techniques for internal channels and their effect on friction factors, aiming to tune flow conditions to meet the design requirements. https://lnkd.in/eDxesQFx #additivemanufacturing #3DPrinting #3DPrint #aerospace #rockets #manufacturing #rocket #nasa Piero Angelo NASA - National Aeronautics and Space Administration NASA Marshall Space Flight Center