Journal of Advanced Research in Aeronautics and Space Science

A Multi-Mode Transportation System: Integrating Land, Air and Water mode

Amit Mithal, Shivanshu Tank, Anuradha, Nikhil Vijay — Thu, 14 May 2026 00:00:00 +0000

The proposed invention is a revolutionary multi-modal vehicle capable of operating on land, water, and air using an advanced vertical take-off and landing (VTOL) system. This research explores its design, technological advancements, and potential applications in transportation, defence, and emergency services. The vehicle incorporates artificial intelligence (AI) for autonomous navigation, safety mechanisms, and adaptive control across different terrains. Additionally, the vehicle is powered by a hybrid energy system utilising both battery and hydrogen fuel cells to overcome range limitations in fully electric systems. The study highlights how the invention addresses existing mobility limitations and enhances efficiency in modern transportation.

DOI: https://doi.org/10.24321/2454.8669.202603

Enhanced Thermal Control in Space Radiators: An SQP-Based Optimization Approach

Thu, 14 May 2026 00:00:00 +0000

Under complex environmental conditions, the cooling process will be significantly enhanced if the detector is kept at an optimal level determined by the thermal index of control. The area and configuration of the detector area in the space ultraviolet imager used in conjunction with the methodology utilised to upgrade the cooling effectiveness of the radiation cooler design are further refined by using successive quadratic algorithms that are aimed towards iterative optimisation of parameters associated with the design. The ultraviolet space imager was associated with a physical model and the thermal simulation model: a defined objective function was detector temperature.

DOI: https://doi.org/10.24321/2454.8669.202602

AI-Driven Intelligent Aerospace Monitoring and Real-Time Update System for Predictive Decision Making

Smith, Sarah L. Johnson — Thu, 12 Mar 2026 00:00:00 +0000

The aerospace industry operates in a highly dynamic and safety-critical environment where real-time decision-making is essential for ensuring operational efficiency and minimizing risks. Traditional monitoring systems often rely on reactive maintenance and limited data integration, leading to inefficiencies and potential safety concerns. This paper presents an AI-driven intelligent aerospace monitoring and real-time update system designed to enhance predictive decision-making capabilities. The proposed system integrates heterogeneous data sources, including aircraft sensors, weather information, and satellite telemetry, into a unified framework. Advanced machine learning algorithms are employed for anomaly detection, predictive maintenance, and operational optimization. A real-time dashboard provides actionable insights and alerts to operators. Experimental evaluation demonstrates improved fault prediction accuracy, reduced downtime, and enhanced situational awareness. The system offers a scalable and efficient solution for modern aerospace operations.

Advanced Aerodynamic Design for Hypersonic Vehicles and Re-Entry Systems

Megha Raut, Jaya Pratap — Thu, 12 Mar 2026 00:00:00 +0000

Hypersonic vehicles and atmospheric re-entry systems represent one of the most challenging domains in aerospace engineering due to extreme aerodynamic heating, shock interactions, and material constraints. This article reviews advanced aerodynamic design methodologies applied to hypersonic flight regimes, focusing on fluid-structure interactions, thermal protection systems, and computational modeling techniques. The study explores key developments in aerodynamics, high-temperature materials, and flight dynamics essential for stable and efficient hypersonic travel. Additionally, the paper highlights ground and flight testing strategies, simulation frameworks, and regulatory considerations for safe deployment. The integration of multidisciplinary approaches is critical for achieving performance optimization and mission reliability in hypersonic and re-entry applications.

A Study on Intelligent Missile Launching, IoT based SightandShoot Capability

Kutubuddin Sayyad Liyakat Kazi — Thu, 12 Mar 2026 00:00:00 +0000

In an era where battlefield decisions are compressed into milliseconds, the fusion of InternetofThings (IoT) paradigms with kinetic weaponry promises a transformative leap in strike precision and operational tempo. This paper introduces the Intelligent Missile a nextgeneration munition endowed with an IoTbased “SightandShoot” architecture that marries edgecomputing, sensorfusion, and adaptive networking into a single, selfcontained strike platform. The missile’s ocular suite—comprising hyperspectral cameras, LIDAR, and lowpower radar—streams compressed situational data to an onboard AI core that performs realtime target classification, threat ranking, and trajectory reoptimization. Simultaneously, a secure mesh link enables bidirectional communication with groundbased command nodes, allied UAVs, and satellite assets, allowing dynamic ruleset updates and cooperative engagement coordination. Empirical trials in a controlled range environment demonstrate a 30 percent reduction in collateral damage and a 45 percent increase in hittokill probability over legacy inertialguided systems, even under contested electromagnetic conditions. The Intelligent Missile thereby exemplifies how IoTcentric design can endow kinetic weapons with the situational awareness, agility, and resilience formerly reserved for pure informationdominance platforms.