This paper presents the design and numerical validation of a robust fixed-time sliding mode controller (FTSMC) for a thrust-vectored planar vertical takeoff and landing (PVTOL) system with strongly coupled nonlinear dynamics. Unlike conventional PVTOL models assuming aligned thrust, the proposed system explicitly incorporates thrust vectoring, resulting in significant inter-axis coupling. A fixed-time sliding-mode control law with smooth nonlinear terms is developed to ensure practical fixed-time convergence to a predefined boundary layer, independently of initial conditions, while mitigating chattering. Numerical simulations under bounded disturbances demonstrate that the proposed FTSMC outperforms a non-terminal sliding mode controller (NTSMC), achieving a reduction of approximately 38% in settling time, more than 80% reduction in pitch overshoot, and up to 60% decrease in control effort. These results highlight the robustness and efficiency of the proposed control strategy for safety-critical UAV and rocket-based platforms that require rapid, precise maneuvering.

The development of national aerospace technology has aroused interest in different sectors, so there is a long road to transformation where our country must develop the necessary aerospace infrastructure for said technology. The educational sector has been interested in aerospace technology but the use of this type of technology is expensive. That is why, with the support of ICTs, we think about how to solve this problem and this is where augmented reality (AR) comes in, given that today most young people have a cell phone capable of displaying functions of AR through a mobile application. Currently AR in the aerospace industry is used to support the assembly of complex systems such as aircraft or satellites, and perform simulations of the operation of these systems. That is why this project proposes the use of augmented reality so that anyone has access to interaction with a CubeSat-type nanosatellite from their mobile devices.

Reverse time migration (RTM) exploits time-reversal symmetry and adjoint duality to focus wavefields and reconstruct subsurface reflectivity, but large surveys remain limited by the cost of forward and backward propagation. We present a Graphics Processing Unit (GPU)-accelerated adjoint RTM workflow for depth imaging of the Chicxulub impact structure using the marine A0/A1 composite profile (1996). The processed stacked section contains 14,172 traces with 6.25 m Common Depth Point (CDP) spacing, 1 ms sampling, and 18 s record length. Forward and adjoint wavefields are computed with a staggered-grid finite-difference scheme (fourth order in space, second in time) and Convolutional Perfectly Matched Layers (CPMLs), which provide stable finite-domain simulations while introducing controlled symmetry breaking through absorption. The solver is verified with the Lamb half-space analytical benchmark and applied through five interpretation-guided velocity/density updates. The final depth image improves reflector continuity and interpretability of crater-scale elements, including post-impact sedimentary fill, melt and breccia units, terrace fault blocks, and deep uplift-related structure. Compute Unified Device Architecture (CUDA) acceleration reduces runtime from ∼32.36 h on a CPU baseline to ∼34.10 min on an RTX 3070 (≈56.9×), enabling practical, reproducible iterative RTM on accessible hardware.

This study used a Systemic Modeling technique, based on the methodologies of Churchman and Ackoff, to integrate and assess the subsystems regulating the functionality of a Rocket Candy (R-Candy) motor. The nozzle and combustion chamber design was improved using a five-phase systemic architecture to assure the coherent interplay of essential factors, including pressure, temperature, and velocity fields. The principles of experimental rocketry are elucidated through the examination of impulse performance throughout class A to class C engines. A preliminary design was developed in SolidWorks 2024, incorporating the engine’s three main components: the igniter, the combustion chamber, and a convergent–divergent nozzle that enhances the acceleration of the exhaust gases. The system model was validated using simulations in FEATool and verified through experimentation. This allowed for the analysis of fluid behavior, as well as the geometry of the structures, initial parameters, and boundary conditions. The results demonstrate a strong correlation between the simulations and the experimental data, with discrepancies of less than 1.5%, confirming the reliability and feasibility of the nozzle design. The findings indicate that systemic modeling, in conjunction with CFD and experimentation, can provide a strategic framework for iterative refinement, optimization of key performance metrics, and the development of cost-effective, high-performance R-Candy engines for educational and experimental purposes.