Research Reports: Aerospace Engineering Research & Innovation

Applied Physics-Informed Neural Networks for Spacecraft Magnetic Testing

Andrew Mentges, Bharat Rawal — Wed, 26 Aug 2026 00:00:00 +0000

Artificial intelligence and machine learning techniques can be used for performing magnetic testing on spacecraft that has historically been difficult and risky to perform. Some of the difficulty arises from the need to take these measurements from within the turbulent nearfield area of the spacecraft. Some methods of testing require the spacecraft to be hoisted in the air and swung while the measurements are being taken so that any magnetic signatures in the test area can be removed. These new artificial intelligence and machine learning techniques can be used to determine the magnetic torque of complex magnetic systems. Here we will describe a test method that collects such data and poses much less risk to the spacecraft. We will also show some combinations of hyper-parameters that can be used to increase the speed and accuracy of the models. Some models were able to achieve over 96.6% accuracy of multipole determination on simulated data and over a 99.99% accuracy of dipole moment determination on simulated data. Applications include attitude control systems (ACS), science instrument locations, and data analysis.

Development of Improved Empirical Landing Equations for Conceptual Design

Timothy T. Takahashi — Wed, 26 Aug 2026 00:00:00 +0000

This paper develops new empirical relationships to estimate FAA/EASA- and MIL-3013Brules-compliant landing-field performance of multi-engine transport aircraft. Widely cited textbooks date from an era when inferior tire and braking capability limited aircraft performance. Today, the use of overly pessimistic conceptual design-level performance estimates may lead concept-design teams to advocate for unnecessary engineering solutions (for example, more complex flaps) to solve “problems” which do not actually exist. Moreover, today’s aircraft designer is likely to face customer-imposed wet and/or contaminated runway performance requirements, where the classic books only discussed dry-weather operations. Taken together, the design community needs a collection of revised empirical equations to estimate landing distances for dry and wet runways. The empirical relationships published here are based upon modern flight-manual data augmented by a calibrated physics-based numerical simulation applied to a wide range of possible vehicle configurations. They offer improved accuracy, compared to earlier methods. The new method, when applied to FAA rules for aircraft operating on dry runways, predicts the substantially shorter “real-world” certified landing distances attainable by modern aircraft.

Retrospective Analysis of Pulse Wave Flattening for G-LOC Detection Using Automatic Computer Algorithm Methods

Janina Sammito, Anthony Schwarz, Michael Nehring, Stefan Sammito — Wed, 26 Aug 2026 00:00:00 +0000

The possibility of G-induced loss of consciousness (G-LOC) is a key concern when flying modern, high-performance aircraft. Currently, there are no identification methods available based on physiological data. This study aimed to determine whether specific pulse wave changes could be reliably identified using automatic computer algorithms to detect impending G-LOC. The pulse waves of 86 people who experienced G-LOC in a human centrifuge were analysed alongside an age-, gender-, nationality-, training-, and anti-Gequipment-matched control group using computer algorithm methods to analyse possible longer reductions in the G-LOC group. Based on this data, the study showed that centrifuge profiles with a gradual “onset run” using AGSM resulted in longer pulse wave flattening around the G-LOC in the G-LOC group than in the matched control group. However, this could not be verified in human centrifuge runs with active flight profiles and higher onset rates. Unfortunately, this means that the method used here would not currently be applicable in actual flight. In the future, the possibility of creating an identification method could be extended by incorporating additional physiological data.

Accelerated Refueling of Type IV Hydrogen Pressure Tanks by Passive Means: Thermal Material Characterization and Evaluation

Nico Liebers, Sven Ropte — Wed, 26 Aug 2026 00:00:00 +0000

The significant heat generated during the refueling of hydrogen pressure tanks may exceed the permissible 85 °C temperature limit for type IV tanks. Common countermeasures such as hydrogen pre-cooling or long filling times are energy- and time-consuming; hence, in this paper, passive means through thermally better-suited materials are examined. State-of-the-art and alternative materials are first characterized and finally compared using a transient heat model. Different material combinations are compared in terms of the maximum temperature and weight in a typical filling scenario. As alternative liner materials, thermoplastics filled with short carbon fibers, minerals, and graphite were selected to improve thermal properties. For the composite overwrap, copper-coated carbon fibers were chosen. The findings show that the liner is the bottleneck while transferring heat from the inner to the outer tank surface. Using graphite-filled thermoplastics as the liner material shows the greatest potential regarding thermal optimization with only a slight weight increase. Using copper-coated carbon fibers additionally further reduces the maximum temperature but results in a significant weight increase.

Potential Field-Based Topology Construction of Structured Grids Around an Aircraft

Hai Zhu, Weiqiang Huang, Taohong Ye, Minming Zhu — Tue, 12 May 2026 00:00:00 +0000

Multi-block structured mesh is widely used for high-precision aerodynamic simulation, but mesh blocking usually requires substantial manual intervention, which is time-consuming and demands a high level of user expertise. In this study, a potential field-based blocking algorithm for mesh generation around an aircraft is proposed, and a corresponding multiblock grid generation workflow is established. First, the hyperbolic partial differential equation (PDE) method is used to march boundary layer grids from the body surface. Next, the potential field is solved on an unstructured background grid, and the grid topology is flexibly designed by adjusting boundary conditions. The gradient lines of the potential field are then determined and employed to partition the external domain into blocks. Finally, the elliptic PDE method is applied to generate structured grids within each sub-block. A low-aspect-ratio flying-wing configuration is adopted as the test case. Structured grids of both H-type and O-type topologies are generated and compared with the benchmark grid released by the China Aerodynamics Research and Development Center (CARDC). The grid quality analysis and aerodynamic calculation results demonstrate that the two generated grids possess good quality, and the computational results show satisfactory agreement with experimental data. The O-type mesh yields more accurate predictions for the lift coefficient and pitching moment coefficients. Furthermore, two test cases, namely a rocket sled and a V-tail aircraft, are presented to demonstrate that the proposed method can flexibly design either O-type or H-type topologies to accommodate different geometric characteristics. In summary, the proposed method enables efficient generation of high-quality multi-block structured grids for the configurations examined in this study.