You will get a Generative AI Wing Shape Optimizer for FreeCAD
Project details
You will get a custom PINN surrogate model for transonic airfoil CFD to accelerate your aerodynamic optimization loops.
Traditional Reynolds-Averaged Navier-Stokes (RANS) simulations for transonic flight regimes are computationally expensive, bottlenecking aerodynamic optimization loops. This project delivers a Physics-Informed Neural Network (PINN) surrogate model that learns the underlying governing equations (Navier-Stokes, continuity, and energy) alongside data constraints.
By embedding fluid physics directly into the neural network's loss function, this surrogate accurately predicts full pressure (P) and skin friction (C_f) distributions over supercritical airfoils across unseen Mach numbers (0.7 \le M \le 0.9), substituting up to 20% of traditional RANS iterations with near-instantaneous inference.
Traditional Reynolds-Averaged Navier-Stokes (RANS) simulations for transonic flight regimes are computationally expensive, bottlenecking aerodynamic optimization loops. This project delivers a Physics-Informed Neural Network (PINN) surrogate model that learns the underlying governing equations (Navier-Stokes, continuity, and energy) alongside data constraints.
By embedding fluid physics directly into the neural network's loss function, this surrogate accurately predicts full pressure (P) and skin friction (C_f) distributions over supercritical airfoils across unseen Mach numbers (0.7 \le M \le 0.9), substituting up to 20% of traditional RANS iterations with near-instantaneous inference.
AI Algorithms
Multimodal Large Language ModelAI Applications
AI Content Creation, AI-Generated Art, AI-Generated VideoAI Development Language
PythonAI Tools
GitHub CopilotAI Models
OpenAI CodexWhat's included
| Service Tiers |
Starter
$2,500
|
Standard
$6,500
|
Advanced
$10,000
|
|---|---|---|---|
| Delivery Time | 7 days | 21 days | 40 days |
Number of Revisions | 0 | 2 | 5 |
AI Model Integration | - | ||
Batch Normalization | - | ||
Database Integration | - | - | |
Detailed Code Comments | - | - | |
Image Upscaling | - | - | |
MLOps | - | - | |
Model Deployment | - | ||
Model Documentation | - | ||
Model Monitoring | - | - | |
Model Testing & Optimization | - | - | |
Model Tuning | - | - | |
Natural Language Processing | |||
NLP Tokenization | |||
Pre-Training | - | ||
Prompt Engineering | |||
Setup File | |||
Source Code |
About Ahmed
General Consultant
Mansourah, Egypt - 12:28 am local time
In Egypt’s rapidly emerging space sector, technical brilliance alone doesn’t open doors — strategic positioning does. As a freelance aerodynamics engineer, SpaceTech Ambassador, and solopreneur, I bridge the gap between fluid dynamics precision and high-growth market access. I help regional satellite integrators, propulsion startups, and aerospace research units turn technical capability into undeniable competitive advantage.
The Impact: Right-Sizing Technical Narratives for 20–30% Faster Trust Building
My mission is to compress the sales cycle by translating low‑TRL concepts into investment‑ready stories. Using predictive modeling honed over years of CFD and design optimization, I pinpoint exactly which technical milestones matter most to funders, agencies, and B2B partners — and build the data-driven proof points to back them.
Why My Technical Approach Wins:
· Aerodynamic Logic Applied to Positioning: Just as I optimize airfoil shapes for maximum lift‑to‑drag, I shape value propositions to maximize investor interest while minimizing communication noise. Root‑cause analysis, sensitivity studies, and design of experiments inform every market message.
· Predictive Opportunity Mapping: I deploy ensemble methods — not just for marketing metrics but for technology trend forecasting. By modeling regional space regulatory shifts and supply‑chain gaps, I position clients where demand will be, not merely where it is.
· Full‑Stack Ambassador Edge: My SpaceTech Ambassador role gives me real‑time insight into agency roadmaps and international collaborations (from the African Space Agency’s agenda to bilateral programs). I translate these signals into actionable growth plays, whether you need a partnership intro or a technical white paper that speaks “engineer.”
· Localised Solopreneur Agility: Based in Egypt, I operate at the intersection of cost‑effective talent and continental ambition. I help international firms localise their technical messaging for the MENA market, and help Egyptian deeptech teams export their innovations with globally credible positioning.
Core Competencies:
· Aerospace Strategy: Market entry roadmapping and differentiation rooted in aerodynamic and system‑engineering rigor.
· Technical Storytelling: Converting CFD results, propulsion specs, and design trade‑offs into persuasive business narratives.
· Ambassador‑Led Business Development: Leveraging pan‑African and European SpaceTech networks to fast‑track credibility.
· Solo Efficiency: Delivering consultancy that scales without overhead — your mission parameters, my engineering mindset.
Let’s Shape Your Trajectory
Whether you’re an Egyptian startup prototyping a cubesat propulsion unit or a European SME navigating the African space landscape, I provide the analytical rigour and regional fluency to transform technical passion into funded, visible, and trusted ventures. In a domain where a single degree of misalignment can cost a contract, I bring the aerodynamic precision your outreach deserves.
Ready to reduce drag and accelerate growth? Let’s run the numbers.
Steps for completing your project
After purchasing the project, send requirements so Ahmed can start the project.
Delivery time starts when Ahmed receives requirements from you.
Ahmed works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Review & Data Onboarding
Review your submitted airfoil geometries, specific operational parameters, and any baseline OpenFOAM computational fluid dynamics (CFD) datasets. Verify the boundary conditions and the targeted transonic Mach number envelope.
Neural Network Architecture & Physics Loss Setup
Construct and configure the core neural network topology using advanced frameworks like DeepXDE or NVIDIA Modulus. Formulate and embed the governing Navier-Stokes partial differential equations (PDEs) directly into the NN's physics loss function.