BeyondMath

Getting your data into Physics Factory takes about a minute. Sign in, run one command in your AWS account, and your CFD data is copied to your own encrypted workspace. Say what to predict and it trains the model. Watch: Access:

Physics Factory trains an AI model on your CFD and predicts flow on new designs in minutes, not hours. 144 engine intake port cases in, a model out that tests new port designs in 3D, scored against your CFD. Watch: Get access:

RT @ukinchennai: 🇬🇧 Automotive innovation meets 🇮🇳 engineering expertise 🚗 Over 4 days, UK tech companies met @ALIndiaOfficial , @Mahindra_Auto , @boschindia , @ZF_Group, @MadrasChamber & @iitm_respark , exploring everything from electrification & batteries to lightweight materials.

Physics Factory turns your CFD data into an AI model that predicts aero on new designs in seconds. Here it trains on DrivAerML (500 car bodies) and predicts pressure, drag and lift on cars it has never seen. Watch: Get access:

RT @PortalAndForge: Portal & Forge signs partnership with @BeyondMathLtd to give business leaders direct access to physics AI. Board directors and senior executives, inside the laboratory. London, this December. Strictly limited.

Engine teams usually test one cylinder at a few valve lifts. Swirl can differ by 2x between cylinders on the same manifold. Our model predicts intake flow for every cylinder, at any lift, in 15 seconds on a laptop. No mesh, no solver.

Physics Factory is now available to everyone. Turn simulation data into models that predict new designs in seconds. Use it now:

One line brief: "Make an accurate F1 front wing, using circa 2023 era regulations." Cadgen2 reads the regulations, writes 11 parametric parts, builds the assembly, checks every requirement, exports STEP and BREP. Open the example, fork it, carry on.

Physics Factory is open to everyone. Three tools, one platform: Cadgen2: describe a part, get STEP and BREP. Forge: point it at your simulation data, agents train and test the models. Studio: run a released model on new geometry in seconds.

Our work with @Honeywell_Aero is the case study in AI for Aerospace, published by @ATI_UK and @Capgemini. A full unsteady flow field simulated in 90 seconds. The same case took 24 hours on 720 cores. Accuracy within 2% of high fidelity DES. Report:

Heat is the hardest constraint in aerospace components. Each candidate geometry needs thermal proof. Days of simulation each. Across a design space, that is a season. We are compressing it into days for @Honeywell_Aero. Aerothermal optimisation, delivered in days.

Built autonomously by agent crews. 1st place on DrivAerML. Full table below, including the rows we do not win. Best published result on surface and volume pressure. Volume pressure error roughly a third lower than next best. Transolver-3 still leads on volume velocity.

At 40,000 feet, the systems that control cabin air and pressure are not allowed to fail. @Honeywell_Aero builds those systems. BeyondMath's generative physics platform is optimising the additively manufactured components inside the next generation of them.

An AI model built autonomously by agents just took 1st place on DrivAerML. 500 geometries. 160M cells each. ~$1M of CFD compute behind the ground truth. Our hands on time: under 30 mins. No researchers. No consultants. Link:

We've launched the Physics Factory: autonomous agent crews that turn your simulation data into deployed physics AI models and validated designs. Around the clock, no ML team required. A working model the same day. Under 30 minutes of your hands on time.

RT @UKAeroInstitute: Our new joint report with @Capgemini demystifies AI, clarifying the technology suite it includes and where they can create value across the aerospace value chain. Featuring case studies from @BeyondMathLtd, @TeamCloudNC & @RollsRoyce. Read the report:

We're at the Isambard Summit in Bristol this week. We'll be sharing how we scaled our foundational AI model of physics from F1 aerodynamics into automotive, aerospace, and electronics.

Proud to be featured in Jensen Huang's GTC keynote as an AI Native. Our partnership with NVIDIA allows us to leverage the latest GPU infrastructure to power our foundational physics AI models. 1000x faster than traditional CFD and FEA. The physical world is next. #GTC26

The AI revolution conquered the digital world. The physical world? Still waiting. We're at NVIDIA GTC to change that. At @BeyondMath we're building the intelligence layer for the physical world. No more waiting weeks on CFD/FEA. #GTC26 #GenerativePhysics

Surrogate models memorize a geometry set. Change the shape and they break. We're building foundation models trained on the laws of physics. Not locked to a single design. @wasilrezk is speaking at CDFAM Barcelona, April 8-9. Come say hello!