Jet aircraft intended to exceed Mach 2 (and well above) must operate within aerodynamic regimes defined by transonic shock formation, compressibility effects, and temperature-driven material constraints. LupoTek’s research examines:

NOTE: The following formula are written in LaTeX, the standard markup language used in science and mathematics to format equations cleanly.

• Compressible Flow Dynamics

At Mach numbers M > 1, airflow behaviour follows the compressible Navier–Stokes equations and Prandtl–Glauert compressibility corrections. LupoTek studies shock-wave boundary interactions, wave drag, and thermal boundary layer coupling, using CFD solvers to map:

C_D = C_{D_0} + kC_L^2 + C_{D_{\text{wave}}}(M)

where wave drag rises sharply at supersonic speeds.

• Aerothermal Loads

Airframe temperature rise is governed by stagnation heating:

T_0 = T_{\infty}\left(1 + \frac{\gamma - 1}{2}M^2\right)

requiring materials and coatings capable of resisting high thermal flux without distortion.

• Broadband Low-Observability

LupoTek investigates low-observability concepts that reduce electromagnetic, thermal, and acoustic signatures simultaneously (“broadband signature minimisation”). This includes:

• multi-band surface treatments,

• edge-aligned airframe geometries,

• IR-attenuating exhaust-path shaping,

• and thermal diffusion control using conductive lattice materials.

These are grounded in measurable electromagnetic scattering principles (e.g., bistatic radar cross-section modelling).

Next Generation Systems:

LupoTek’s aircraft incubation program is built on digital engineering and model-based systems design, ensuring the entire airframe, propulsion, structural load paths, and computational architecture are validated through simulation before fabrication.

• Multi-Physics Simulation Stack

Includes CFD, FEA, aeroelastic modelling, thermal analysis, and fatigue prediction using Paris’ Law:

\frac{da}{dN} = C(\Delta K)^m

• Long-Range Structural Efficiency

To achieve ranges exceeding 9,000+ nautical miles, LupoTek studies ultra-efficient lift-to-drag profiles and composite construction methods with stiffness-to-weight optimisation:

\frac{E}{\rho} \rightarrow \max

• Aerodynamic–Computational Co-Design

Airframe geometries are co-developed with sensing and computational systems, ensuring that:

• structural cavities

• surface contours

• airflow channels

• thermal diffusion paths

all match the digital-design predictions fed into the aircraft’s Companion-Intelligence reasoning modules.

• Autonomous Support Systems for Large-Scale Missions

Even in crewed flight, the aircraft relies on autonomous support systems to manage:

• airspace interpretation

• collaborative mapping with winged autonomous partners

• structural-health monitoring

• anomaly detection

• long-distance route optimisation

These systems use online Bayesian learning to refine operational predictions:

p(\theta | x_{1:t}) \propto p(x_t | \theta) p(\theta | x_{1:t-1})

Next-generation propulsion research at LupoTek evaluates variable-cycle engine architectures capable of transitioning between efficient cruise and high-thrust modes. These systems leverage adaptive bypass ratios and adjustable airflow pathways.

• Variable Cycle Modes

Efficiency-driven cycle:

\eta_{\text{cruise}} = \frac{W_{\text{useful}}}{Q_{\text{fuel}}}

High-thrust mode boosts mass flow rate and fan pressure ratio for supersonic acceleration.

This duality enables global ranges exceeding 9,000 nautical miles without compromising high-speed capability.

• Thermal & Structural Modelling

Dynamic turbine temperatures follow the energy balance:

Q_{\text{in}} - Q_{\text{out}} = m c_p \Delta T

driving LupoTek’s materials research into high-strength, creep-resistant alloys and ceramic matrix composites.

• Exhaust Flow Shaping for Reduced IR Signature

Flow-mixing and expansion geometries are modelled to reduce IR plume temperature profiles in compliance with Stefan–Boltzmann radiative principles:

P \propto \epsilon A T^4

Modern aerospace systems operate not as isolated platforms, but as networked vehicles capable of sharing sensing duties, navigation insight, and environmental interpretation.

• Manned–Unmanned Teaming (Collaborative Flight Operations)

LupoTek develops frameworks where a primary aircraft coordinates with multiple smaller autonomous craft, enabling distributed sensing, cooperative mapping, and situational expansion. Coordination algorithms use graph-based multi-agent optimisation:

\min_{\mathbf{u_1},\dots,\mathbf{u_n}} \sum_i J_i(\mathbf{x}_i, \mathbf{u}_i)

• Sensor Fusion & Collective Perception

The primary jet programs integrate:

• multispectral imaging,

• RF sensing,

• inertial–satellite hybrid navigation,

• environmental telemetry from all collaborating craft.

Data fusion uses Bayesian frameworks such as the Extended Kalman Filter and factor-graph optimisation:

x^* = \arg\min_x \sum_i \| z_i - h_i(x)\|_{\Sigma_i^{-1}}^2

• Cyber & Digital Integrity Frameworks

Instead of referencing “cyber warfare,” LupoTek’s research focuses on system-level digital integrity - architecture hardening, intrusion detection through anomaly patterns, and secure inter-vehicle communication channels, with Companion-Intelligence assisting in the detection of statistical irregularities.

LupoTek’s aircraft research prioritises designs that can operate with or without onboard crew.

• Optional Manning Architecture

The airframe is designed to shift between:

• Crewed Mode — with a full human-systems interface

• Remote/Autonomous Mode — where Companion-Intelligence manages navigation, airspace interpretation, and system-health modelling

• Virtual Cockpit & Helmet-Mounted Interfaces

Human-systems integration relies on augmented-visual overlays, using helmet-mounted displays that synthesise:

• fused sensor fields

• navigational predictions

• structural and energy-state models

• environmental hazard mapping

The system uses real-time rendering governed by projected conformal display geometry:

I_{\text{display}}(x, y) = f(I_{\text{sensor}}, \Pi(K, R, t))

where Π represents camera projection matrices.