NOAH NEXUS TOULOUSE

12/04/2026
Noah Ark Technology — Quantum Aerospace
◈ QUANTUM AEROSPACE INITIATIVE — OCCITANIE, FRANCE

NOAH ARK
TECHNOLOGY

Smart Circular & Traceable Manufacturing for Aeronautics

⚛ W-Seven Dimension 🛡 NNOC Cybersecurity ⬡ Blockchain Traceability 🧬 G-CMC Materials 🤖 Federated AI ♻ Circular Economy
–20% APU Energy Reduction
94.2% RUL Prediction Accuracy
NIST PQC 2024 Compliant
€2.1B ARTES 4.0 Programme
⚛
W-Seven Dimension

A multi-dimensional tensor framework defining 7 interacting physical dimensions governing matter-energy systems at quantum scale. Core theoretical foundation for next-generation propulsion.

🛡
NNOC Alpha Core

Autonomous orbital cybersecurity with TinyML, Post-Quantum Cryptography (NIST FIPS 203/204), and Zero Trust architecture. Protecting satellites against quantum-era threats.

♻
Noah Circular

Additive manufacturing with 99% powder recycling target, G-CMC graphene-enhanced composites, and blockchain-verified circular economy loops for aerospace components.

// SYSTEM ARCHITECTURE

Noah Nexus Platform

A layered manufacturing platform integrating Blockchain traceability, AI-powered Digital Twins, additive manufacturing, and Industry 5.0 human-robot collaboration.

L6 Presentation Layer
Dashboard Analytics Mobile App AR/VR Training API Gateway
L5 AI Intelligence Layer
Predictive Maintenance Generative AI Design Federated Learning
L4 Digital Twin Layer
Component Twins Real-Time Simulation PLM Integration
L3 Blockchain & Web3 Layer
NFT Parts Registry Smart Contracts ERC-721/ERC-1155 IPFS + Filecoin
L2 Manufacturing & Edge Layer
LPBF / DED Additive Mfg Edge AI (NVIDIA Jetson) Cobots
L1 IoT Connectivity Layer
Sensors Mesh 5G/TSN Industrial OPC-UA / MQTT Apache Kafka

TECHNOLOGY STACK

Layer Technology Justification Status
BlockchainHyperledger Fabric / PolygonPermissioned + EVM compatibleACTIVE
StorageIPFS + Filecoin + ArweaveDecentralized + cost-efficientACTIVE
AI/MLPyTorch + HuggingFace + QiskitState-of-the-art 2024-2025IN DEV
Digital TwinSiemens Xcelerator + NVIDIA OmniverseIndustrial leaderIN DEV
EdgeNVIDIA Jetson AGX Orin + Intel OpenVINOPerformance + ecosystemACTIVE
CloudMulti-cloud AWS / Azure / GCPResilience + compliancePLANNED

Core Event Bus: Apache Kafka orchestrates all inter-module communication across NOAH TRACE, NOAH TWIN, NOAH CIRCULAR, and NOAH PREDICT — enabling real-time event streaming at industrial scale with sub-100ms latency across OEMs, MROs, and Suppliers.

// BLOCKCHAIN & WEB3 TRACEABILITY

NFT Hierarchical Registry

Every aerospace component receives a unique NFT with complete lifecycle tracking — from raw material sourcing to end-of-life recycling, compliant with EASA/FAA 2024-2025 standards.

✈ AIRCRAFT DIGITAL PASSPORT — NFT PARENT (ERC-721)
Serial Number · Ownership History · Regulatory Compliance · Carbon Footprint
Engine
Trent XWB
Landing Gear
Main Assembly
Avionics
FMS Systems
Structure
Wings & Frame
Sub-NFTs
Components
Sub-NFTs
Parts
Sub-NFTs
Modules
Sub-NFTs
Panels
// SPDX-License-Identifier: MIT — NoahAeroPartNFT.sol pragma solidity ^0.8.20; struct PartLifecycle { string partNumber; // OEM part number string serialNumber; // Unique serial address manufacturer; // Certified manufacturer uint256 flightHours; // Cumulative flight hours uint256 cycles; // Pressurisation cycles string certificationDocs; // IPFS hash — EASA/FAA docs uint256 carbonFootprint; // kg CO₂e tracking bool isActive; // Active / retired status } event PartManufactured(uint256 indexed tokenId, address manufacturer); event MaintenancePerformed(uint256 indexed tokenId, string maintenanceType); event PartRecycled(uint256 indexed tokenId, uint256 recycleDate);

DECENTRALIZED STORAGE ARCHITECTURE

Data TypeStorageRetention Period
EASA/FAA CertificationsIPFS + Filecoin30 years (aircraft life)
Raw IoT Sensor DataIPFS hot + Filecoin cold10 years
3D Digital Twin ModelsIPFS + ArweavePermanent
Blockchain LogsOn-chain + IPFSPermanent
// AI & DIGITAL TWIN

Predictive Intelligence

Federated learning across OEMs and MROs worldwide — training global models without sharing raw proprietary data. LSTM, Transformers, and Graph Neural Networks for aerospace-specific prediction tasks.

AI MODEL PERFORMANCE

LSTM-Attention · RUL Prediction94.2%
Transformer-XL · Time Series96.5%
Vision Transformer · Visual Inspection98.1%
Graph Neural Network · Systems Analysis91.8%
Federated Learning Architecture

Multi-site learning preserving competitive data confidentiality between Airbus, Boeing, Safran, and global MROs.

ALGORITHM
FedAvg
PRIVACY
ε-DP
ENCRYPTION
HME
SITES
N Global

DIGITAL TWIN — MULTI-SCALE ARCHITECTURE

🛩
Fleet Level

Cross-aircraft comparative analysis, optimized routing and scheduled maintenance, fleet trend prediction across entire commercial fleets.

✈
Aircraft Level

Full 3D aircraft model with real-time flight data integration, what-if scenario simulation, and integrated PLM lifecycle management.

⚙
Component Level

Individual part degradation modeling, material-level monitoring, Remaining Useful Life (RUL) prediction with 94.2% accuracy via LSTM.

// ADDITIVE MANUFACTURING & CIRCULAR ECONOMY

Noah Circular

Closed-loop metal powder recycling, AI-generated topology optimization, and on-demand digital inventory — eliminating physical stock while reducing material waste by 75%.

🔷
LPBF

Laser Powder Bed Fusion for Ti-6Al-4V and Inconel 718. High precision aerospace-grade components with complex internal geometries.

Ti-6Al-4V · Inconel 718
🔶
DED

Directed Energy Deposition for repairs, coatings, and surface finishing. Extends component life cycles and reduces replacement costs.

Repairs · Coatings
🔩
WAAM

Wire Arc Additive Manufacturing for large aluminum structures. Scalable production with dramatically reduced material waste.

Large Structures · Al

CIRCULAR ECONOMY KPIs

MetricCurrent Value2026 Target
Metal Powder Recycling Rate85%99%
Buy-to-Fly Ratio3:1 (vs 20:1 conventional)2:1
Raw Material Reduction60%75%
Energy per kg Produced-40% vs machining-60%
Remanufactured Parts15% of volume30%

G-CMC GRAPHENE-ENHANCED COMPOSITES

Thermal Conductivity
530 W/mK
Density
2.7 g/cm³
Max Temperature
1800 °C
Weight Reduction vs Ti
–25%
Mechanical Strength Gain
+40%
Thermal Conductivity × vs Standard
×10
// CYBERSECURITY — NNOC ALPHA CORE

Zero Trust Orbital Security

NIST Post-Quantum Cryptography standards finalized in August 2024. NNOC implements ML-KEM, ML-DSA, and SLH-DSA — making aerospace systems quantum-resistant for their 15-20 year lifecycle.

HARVEST NOW, DECRYPT LATER: Satellites with 15-20 year lifespans are critically vulnerable. Adversaries may be collecting encrypted communications today for future quantum decryption. Implementing PQC now is not optional — it is a strategic imperative.

NIST PQC STANDARDS 2024 — IMPLEMENTED

FIPS 203
ML-KEM (Kyber)

Key Encapsulation Mechanism for general encryption and key exchange. Applied to satellite ground links and IoT device authentication.

KEY EXCHANGE
FIPS 204
ML-DSA (Dilithium)

Digital signature algorithm for satellite authentication and software update verification. Prevents unauthorized firmware injection.

DIGITAL SIGNATURES
FIPS 205
SLH-DSA (SPHINCS+)

Hash-based backup signature scheme for long-term documents, critical firmware, and emergency backup authentication.

BACKUP AUTH
# NNOC Alpha Core — Edge Implementation class NNOCCoreLite: def __init__(self): self.anomaly_detector = tf.lite.Interpreter("nnoc_apu.tflite") # 93% AUC self.kem = mlkem.MLKEM512() # NIST FIPS 203 — lightweight edge self.dsa = mldsa.MLDSA65() # NIST FIPS 204 def monitor_system_anomalies(self, sensor_data): input_data = self._preprocess(sensor_data) self.anomaly_detector.invoke() anomaly_score = self.anomaly_detector.get_tensor(0)[0] if anomaly_score > 0.85: self.trigger_incident_response(sensor_data) return anomaly_score def zero_trust_orbital(self, access_request): trust_score = ( self._verify_pqc_identity(access_request.credential) * 0.3 + self._verify_device_integrity(access_request.device_id) * 0.3 + self._verify_orbital_context(access_request.location) * 0.2 + self._verify_behavior_pattern(access_request.history) * 0.2 ) return trust_score > 0.85 # Zero Trust strict threshold

REGULATORY COMPLIANCE MATRIX

RegulationApplicationNoah Nexus Mechanism
EASA Part 21Production certificationAuto-auditing smart contracts
FAA 14 CFR Part 25AirworthinessNFTs with complete history
NIST PQC 2024Quantum-safe cryptoML-KEM + ML-DSA + SLH-DSA
NIS2 DirectiveCybersecurityZero Trust Architecture
EU Taxonomy / CSRDESG reportingReal-time carbon footprint dashboard
// SCAIRA — 3RD OPEN CALL 2024

Interreg SUDOE Application

Noah Ark Technology applies to SCAIRA's third and final open call — presenting a visionary quantum propulsion and orbital cybersecurity framework aligned with Airbus Atlantic, Renault Group, and Soltena challenges.

Total Budget
€1,865,807
Duration
6 Months
Consortium Partners
12 Partners
Services Available
14 Services
Territory
FR · ES · PT
Funding
ERDF / EU

INDUSTRIAL CHALLENGES ADDRESSED

CHALLENGE 01
⚡
Airbus Atlantic
Energy Efficiency in Aerospace Manufacturing

W-Seven Dimension quantum optimization framework applied to APU energy density — targeting 15-20% reduction in manufacturing energy consumption.

CHALLENGE 02
🔬
Airbus Atlantic
Advanced Materials for Lightweight Structures

G-CMC graphene-reinforced composites delivering 25% weight reduction and 40% strength gain over Ti-6Al-4V for aerospace structural components.

CHALLENGE 03
🤖
Renault Group
Smart Systems & Digital Transformation

NNOC Alpha Core — AI-native autonomous cyber defense with TinyML edge inference, federated learning, and NIST PQC 2024 compliance.

CHALLENGE 04
🌿
Soltena
Green Propulsion & Alternative Energy Sources

Noah Ark Core quantum engine concept explores matter-energy flux dynamics for propulsion systems transcending classical energy density limits.

CHALLENGE 05
♻
SCAIRA Consortium
Circular Economy in Aerospace & Automotive

Closed-loop powder recycling, blockchain-verified material traceability, and digital inventory eliminating physical stock requirements globally.

PROGRAMME
🌐
Interreg SUDOE 2021–2027
Noah Ark Eligibility Status

Based in Occitanie, France. Would-be Entrepreneur category. Confirmed SUDOE territory eligibility.

✓ ELIGIBLE

PROGRAMME TIMELINE

SEPTEMBER 2025
3rd Open Call Launch

SCAIRA announces its third and final open call across FR, ES, PT platforms. 15 proposals received in the final call.

OCT–NOV 2025
Application Period

Online submission window open. All 15 submissions evaluated against SCAIRA eligibility and quality criteria.

DEC 2025 – FEB 2026
Acceleration Phase

Selected projects enter the 6-month transnational acceleration programme with mentorship from Airbus Atlantic, Renault Group, and Soltena.

FEBRUARY 2026
Final SCAIRA Event · Brussels

Pitch & Connect event. Clean Aviation Call 4. Comet Meetings Louise. Final showcase of accelerated technologies.

END OF 2026
Programme Close

SCAIRA concludes with 45+ startups accelerated across all three calls across the SUDOE region.

// USPTO PROVISIONAL PATENT APPLICATION

Quantum Optimization Algorithm

Provisional patent application for the W-Seven Dimension quantum optimization algorithm — priority date September 30, 2026. No prior public disclosures as of filing date.

US PROVISIONAL PATENT APPLICATION · W-SEVEN DIMENSION OPTIMIZATION ALGORITHM
PRIORITY DATE: 09/30/2026
ApplicantNoah Kouadri Khazar / Noah Ark Technology
InventorNoah Kouadri Khazar
Application TypeProvisional (35 U.S.C. § 111(b))
Filing OfficeUnited States Patent and Trademark Office (USPTO)
Priority DateSeptember 30, 2026
International ExtensionPCT filing within 12 months (Sep 2027)
Technology ClassificationG06N 10/20 (Quantum Computing) · B64D 27/00 (Aircraft Propulsion)

TITLE OF INVENTION

MULTI-DIMENSIONAL TENSOR-BASED QUANTUM OPTIMIZATION SYSTEM FOR ENERGY DENSITY CONTROL IN AEROSPACE PROPULSION USING W-PARAMETER CENTRAL FREQUENCY MODULATION

FIELD OF THE INVENTION

The present invention relates to quantum computing systems for aerospace propulsion optimization, and more particularly to a seven-dimensional tensor framework employing variational quantum eigensolvers for real-time energy density control in aircraft auxiliary power units and propulsion systems.

CLAIMS

Claim 1 (Independent). A quantum optimization system for aerospace energy management comprising: a central frequency parameter W defining a seven-dimensional interaction space; a tensor field H(W) mapping matter-energy flux dynamics across dimensions comprising matter density (D₁), flux dynamics (D₂), volumetric structure (D₃), time evolution (D₄), gravitational modulation (D₅), energetic symmetry (D₆), and wave singularity (D₇); a variational quantum eigensolver (VQE) circuit configured to minimize the expectation value of said tensor field; and a classical control loop translating quantum eigenvalues to physical propulsion parameters.
Claim 2 (Dependent on Claim 1). The system of claim 1 wherein the VQE ansatz comprises a parameterized quantum circuit with depth proportional to the number of active dimensional constraints, enabling real-time optimization with convergence time less than 100 milliseconds on gate-model quantum hardware.
Claim 3 (Dependent on Claim 1). The system of claim 1 further comprising an edge computing module comprising an NVIDIA Jetson AGX processor executing a hybrid classical-quantum optimization loop at latency below 5 milliseconds, interfacing with physical propulsion actuators via OPC-UA industrial protocol.
Claim 4 (Independent). A method for quantum-enhanced energy efficiency in aerospace auxiliary power units (APU) comprising: acquiring real-time sensor telemetry from IoT mesh comprising vibration, thermal, and pressure sensors; encoding said telemetry as initial state vectors for seven-dimensional tensor computation; computing an optimal operating configuration by minimizing the W-Seven Hamiltonain using quantum annealing or VQE; and applying said configuration to fuel mixture ratio and airflow control actuators to achieve energy reduction exceeding 15% relative to classical control baselines.
Claim 5 (Independent). A non-transitory computer-readable medium storing instructions that, when executed by a quantum processor, implement: a W-parameter calibration routine initializing central frequency from operational context; dimensional decomposition of the energy-matter flux state space; gradient-based optimization of a parameterized quantum circuit minimizing eigenvalues of the seven-dimensional Hamiltonian; and blockchain-anchored immutable logging of optimization events for regulatory compliance per EASA Part 21 and FAA 14 CFR Part 25.
# W-Seven Dimension — Core Algorithm (USPTO Claim 1 Implementation) class WSevenQuantumOptimizer: W_DIMENSIONS = [ 'matter_density', # D₁ 'flux_dynamics', # D₂ 'volumetric_struct', # D₃ 'time_evolution', # D₄ 'gravitational_mod', # D₅ 'energetic_symmetry',# D₆ 'wave_singularity' # D₇ ] def build_hamiltonian(self, energy_state: dict) -> SparsePauliOp: H = SparsePauliOp.from_list([("II", 0.0)]) for i, dim in enumerate(self.W_DIMENSIONS): weight = energy_state.get(dim, 1.0) * self.w_central_freq H += SparsePauliOp.from_list([(pauli_string(i), weight)]) return H def optimize(self, constraints: dict) -> dict: H = self.build_hamiltonian(constraints) result = VQE(self._create_ansatz(), COBYLA()).compute_minimum_eigenvalue(H) return { 'fuel_ratio': self._eigenvalue_to_fuel(result.eigenvalue.real), 'airflow_rate': self._eigenvalue_to_airflow(result.eigenvalue.real), 'energy_reduction': self._calculate_savings(result) }
IP Strategy
Provisional → PCT → National Phase
Jurisdictions
US · EU · Japan · Canada
Estimated Grant
2028–2029
// IMPLEMENTATION ROADMAP

Noah Nexus 2025–2030

A phased deployment strategy from single-site POC to global aeronautical manufacturing standard, with escalating investment and growing ecosystem partnerships.

2025 Q1–Q2
PHASE 1
PILOT
  • 1 AM production site
  • Basic NFT traceability
  • Edge computing v1
  • NNOC Alpha prototype
  • 10K parts traced
€2–5M
2025 Q3–Q4
PHASE 2
SCALE
  • 3–5 production sites
  • Federated Learning launch
  • Cobot deployment
  • MRO integration begins
  • 95% uptime SLA
€10–20M
2026
PHASE 3
GLOBAL
  • Multi-OEM integration
  • Full MRO ecosystem
  • Generative AI design
  • 100+ partners
  • ESA ARTES 4.0 demo
€50–100M
2027–2030
PHASE 4
LEADER
  • Complete ecosystem
  • Industry standard
  • 50% aero parts tokenized
  • Quantum propulsion TRL8
  • €45M revenue target
€200M+

REVENUE PROJECTIONS

YearRevenuePrimary DriverGross Margin
2025€1.2MSCAIRA + 1 industrial client72%
2026€4.5M3 major clients + royalties72%
2027€12MSpace market entry68%
2030€45MQuantum propulsion leadership65%

ARTES 4.0 LOI — NNOC-SAT MILESTONES

M3 · JULY 2025
System Architecture Validated

Complete NNOC-SAT architecture reviewed and signed off by ESA technical review board. PQC algorithm selection finalized.

M6 · OCT 2025
TRL4 Prototype — Test Bench

First hardware prototype of NNOC module operating on ground test bench. ML-KEM/ML-DSA demonstrated at full throughput.

M12 · APR 2026
Environmental Qualification

Radiation tolerance (100 krad), thermal cycling (-40°C to +85°C), and vibration qualification completed. TRL5 achieved.

M18 · OCT 2026
TRL6 — PVT Complete

Proto-flight model completed. Performance Verification Testing confirms all specifications. Ready for OPS-SAT-2 flight opportunity.

2027–2028
In-Orbit Demonstration

NNOC-SAT operating on LEO satellite. Commercial contracts with SES, Eutelsat, and Kinéis. TRL8 qualification achieved.

Business Model Revenue Streams
B2B Licenses · Quantum Engine40%
NNOC Subscriptions30%
Data Monetization · W-Seven Vault20%
G-CMC Material Royalties10%
Contact & Application
FOUNDER
Noah Kouadri Khazar
EMAIL
noaharktechnology@gmail.com
LOCATION
France · Occitanie Region
PHONE
+33 6 51 59 00 14
SCAIRA 3RD CALL ARTES 4.0 LOI EUROHPC AI FACTORY
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