Papers by Keyword: Aerospace Applications

Abstract: This study investigates the deployment of adaptive neural network-based control strategies for nonlinear dynamic systems, emphasizing the integration of Echo State Networks (ESNs) into a feedforward-feedback control architecture. Traditional controllers relying on precise mathematical modeling often fail to cope with the complexity of systems exhibiting high nonlinearity, time-varying parameters, and external disturbances. The proposed ESN-based approach harnesses reservoir computing to construct a lightweight, data-driven model capable of accurately capturing system dynamics in real time. The feedforward module provides anticipatory control actions, while the feedback loop compensates for deviations, enabling rapid convergence and robustness against parametric drift. Comparative analysis with conventional PID and LQR controllers reveals superior performance in terms of tracking accuracy, stability, and noise resilience. Preliminary simulations predict reduced steady-state error and improved dynamic response even under uncertain operating conditions. This architecture presents a scalable and efficient alternative for advanced applications in robotics, aerospace, and industrial process control. The findings affirm the viability of ESNs in redefining adaptive control paradigms by combining interpretability, computational efficiency, and real-world adaptability. Reference to this paper should be made as follows:MCE 2025, MCE825. (2025) ‘Adaptive neural network-based feedforward-feedback controller for nonlinear dynamic systems.

Abstract: Shape memory alloys (SMAs) are smart materials that have the ability to recover large strain. The shape memory and superelasticity in these alloys is due to stress induced martensitic transformation that strongly depends upon the phase transformation temperatures. These alloys are being investigated for a number of applications due to their remarkable properties such as improved impact and damage resistance, vibration damping, seismic damping, shape morphing and crack closure properties. In this work, these alloys were integrated in fiber reinforced polymers (FRPs) to develop hybrid composite structures that can benefit from both fiber strength and intrinsic properties of SMAs resulting in weight efficient smart materials with better mechanical properties. The experimental investigation on impact performance of nitinol SMAs wire reinforced glass fiber composites (GFRP) showed 18% increase in toughness, as compared to steel wire reinforced glass fiber composites. In this paper, the effect of shape memory alloys wires in composite materials and their targeted applications especially for aerospace industry is presented.

Abstract: A simple mesoscale model has been developed for discontinuous dynamic recrystallization. Each grain is considered in turn as an inclusion, embedded in a homogeneous equivalent matrix, the properties of which are obtained by averaging over all the grains. The model includes: (i) a grain-boundary migration-equation driving the evolution of grain size via the mobility of grain boundaries, which is coupled with (ii) a single-internal-variable (dislocation density) constitutive model for strain hardening and dynamic recovery, and (iii) a nucleation equation governing the total number of grains by the nucleation of new grains. All the system variables tend to asymptotic values at large strains, in agreement with the experimentally observed steady-state regime.With some assumptions, both steady-state stress and grain-size are derived in closed forms, allowing immediate identification of the mobility of grain boundaries and the rate of nucleation. An application to Ni–Nb-pure-binary model alloys and high-purity 304L stainless steel with Nb addition is presented. More specifically on one hand, from experimental steady-state stresses and grain sizes, variations of the grain boundary mobility and the nucleation rate with niobium content are addressed in order to quantify the solute-drag effect of niobium in nickel. And on the other hand, the Derby exponents were investigated varying separately the strain rate or the temperature.

Abstract: In this paper the important impact of high temperature withstand on performance of electromagnetic actuators for aerospace applications is illustrated. Particular materials enabling high performance and increased reliability in such applications are analysed both through numerical simulations and experimental validation. Specific examples outline advancements in electrical machine technologies for this class of problems.

Abstract: In order to achieve an effective control approach for hypersonic vehicle over a wide flight envelope with uncertainties of structural dynamics and system parameters, a unified modeling and improved switching controller design approach is proposed, and the Adams Customized Development Platform of Flight (ACDPF) has been developed to implement it. The paper firstly discusses the main issues related to the model of the ACDPF, which can be set parameters by several blocks. And it also supports the reuse of modeling among similar missions, thus cutting down the design effort for new model. Then, the improved switching control with baseline controllers and robust adaptive controllers are selected in order to adjust control law to compensate for uncertainty. Finally, the effectiveness of the proposed approach is demonstrated by illustrative case studies and simulation results show that the approach provides a well tracking performance.

Abstract: The paper presents technologies for developing efficient high temperature permanent magnet machines implemented in aerospace drive applications. Selection criteria and experimental investigation of the permanent magnet material is undertaken and design considerations enabling to meet the specifications set are described. The proposed control algorithm for an appropriate PWM inverter is introduced.

Abstract: A simple mesoscale model was developed for discontinuous dynamic recrystallization. The material is described on a grain scale as a set of (variable) spherical grains. Each grain is characterized by two internal variables: its diameter and dislocation density (assumed homogeneous within the grain). Each grain is then considered in turn as an inclusion, embedded in a homogeneous equivalent matrix, the properties of which are obtained by averaging over all the grains. The model includes: (i) a grain boundary migration equation driving the evolution of grain size via the mobility of grain boundaries, which is coupled with (ii) a dislocation-density evolution equation, such as the Yoshie–Laasraoui–Jonas or Kocks–Mecking relationship, involving strain hardening and dynamic recovery, and (iii) an equation governing the total number of grains in the system due to the nucleation of new grains. The model can be used to predict transient and steady-state flow stresses, recrystallized fractions, and grain-size distributions. The effect of the distribution of grain-boundary mobilities has been investigated.

Abstract: A simple mesoscale model was developed for discontinuous dynamic recrystallization. The material is described on a grain scale as a set of (variable) spherical grains. Each grain is characterized by two internal variables: its diameter and dislocation density (assumed homogeneous within the grain). Each grain is then considered in turn as an inclusion, embedded in a homogeneous equivalent matrix, the properties of which are obtained by averaging over all the grains. The model includes: (i) a grain boundary migration equation driving the evolution of grain size via the mobility of grain boundaries, which is coupled with (ii) a dislocation-density evolution equation, such as the Yoshie–Laasraoui–Jonas or Kocks–Mecking relationship, involving strain hardening and dynamic recovery, and (iii) an equation governing the total number of grains in the system due to the nucleation of new grains. The model can be used to predict transient and steady-state flow stresses, recrystallized fractions, and grain-size distributions. A method to fit the model coefficients is also described. The application of the model to pure Ni is presented.

Abstract: Ti–B–C–N and Ti–Si–B–C–N nanocomposite coatings were deposited on AISI 304 stainless steel substrates by DC unbalanced magnetron sputtering from two (80mol% TiB2–20mol% TiC and 40mol% TiB2–60mol% TiC) composite targets in various Si target powers. The relationship among microstructures, mechanical properties, and tribologiacal properties was investigated. The synthesized Ti–B–C–N and Ti–Si–B–C–N coatings were characterized using x–ray diffraction (XRD) and x–ray photoelectron spectroscopy (XPS). These analyses revealed that the Ti–Si–B–C–N coatings are nanocomposites consisting of solid-solution (Ti,C,N)B2 and Ti(C,N) crystallites distributed in an amorphous TiSi2, SiC, and SiB4 matrix including some carbon, BN, CNx, TiO2, and B2O3 components. The addition of Si to the Ti–B–C–N coating led to percolation of amorphous TiSi2, SiC, and SiB4 phases. The Ti–Si–B–C–N coatings exhibited high hardness and H/E values, indicating high fracture toughness, of approximately 35 GPa and 0.098, respectively. Furthermore, the Ti–Si–B–C–N coatings exhibited very low wear rates ranging from ~3×10-7 to ~16×10-7 mm3/(N·m). The minimum friction coefficient of the Ti–Si–B–C–N coatings was approximately 0.15 at low Si target power between 25W and 50W. A systematic investigation on the microstructures, mechanical properties, and tribological properties of Ti–Si–B–C–N coatings prepared from two TiB2–TiC composite targets and one Si target is reported in this paper.