Browse Topic: Scale models
With the deepening of space exploration, deep space exploration missions face formidable challenges. Among these, intense solar radiation and high-temperature environments pose severe threats to precision instruments and equipment in space. Stray light suppression and protection against external heat flow inputs have emerged as critical technical requirements in the design of modern spacecraft over recent years. To address the demand of space applications, this paper proposes a cylindrical deployable sunshield with axial deployment capability. First, drawing on the 6UU/3UPU/3UKU mechanism as a foundational reference, the basic module was defined through in-depth analysis of the multi-layer Kresling origami pattern. Guided by the modular composition principle, these basic modules were further assembled into an integrated deployable support mechanism. Secondly, the overall kinetic and potential energy of the full mechanism system were computed and incorporated into the second-type Lagrange equation. To verify both the correctness of the established dynamic model and the reliability of follow-up simulation studies, an integrated validation strategy was implemented: SolidWorks was used for three-dimensional modeling and kinematic simulation of the mechanism, while Matlab was employed for numerical solving and result analysis of the dynamic model, with consistent outcomes from both tools confirming the model’s correctness.
This study presents a data-driven approach for strengthening aviation safety by integrating human factors assessment with modern predictive modeling techniques. The work focuses on understanding how human performance, operational conditions, and system-level interactions collectively influence safety risk, and how these interactions can be quantified to support improved design and decision-making. Unlike previous studies that address human factors or predictive modeling in isolation, this research offers a unified framework that links causal human factors indicators with statistical modeling, feature extraction, and machine learning based risk estimation. The novelty of this work lies in the structured pipeline that transforms raw categorical and narrative human factors information into measurable predictors that can be analyzed using structural modeling and machine learning. The methodology includes data preparation, dimensionality reduction, latent pattern discovery, dependence modeling, model training, and interpretability analysis. The study demonstrates how this pipeline uncovers hidden relationships among operational errors, environmental influences, maintenance actions, design considerations, and crew behavior. The findings show that the integrated approach improves the accuracy and stability of risk prediction and highlights specific human factors patterns that consistently contribute to elevated risk levels. These insights support targeted mitigation strategies, inform design improvements, and help prioritize safety interventions. The work concludes that a combined human factors and predictive modeling framework enhances the ability of organizations to identify vulnerabilities earlier, allocate resources more effectively, and strengthen system resilience. This approach is adaptable to diverse aviation contexts and offers a practical path for transforming human factors data into actionable safety intelligence.
This paper investigates a sub-scale testing methodology via Froude scaling combined with comprehensive simulation model development to validate Electric Vertical Take-off and Landing (eVTOL) aircraft simulations and disturbance rejection characteristics. Both sub-scale and full-scale quadrotor aircraft were modeled using the Distributed Electric Propulsion Simulation (DEPSim) and the Comprehensive Hierarchical Aeromechanics Rotorcraft Model (CHARM) for simulation analysis. The sub-scale simulation was validated using flight data from the sub-scale model, including frequency sweeps and impulsive gust disturbance tests in the Penn State University (PSU) indoor flight facility. The PX4 control architecture was modeled in DEPSim and implemented in both scale models, using Froude-scaling in the control laws with the limitation that the Electronic Speed Controller (ESC) dynamics were not fully replicated in the simulation. The scaling methodology and control laws were verified through gust response tests and the Hovering turn and hold Handling Qualities Task Element (HQTE) test. The results indicate that the sub-scale flight testing and simulation provide a low-risk and low-cost method to evaluate full-scale flight performance and disturbance rejection properties.
Numerical simulations are essential in the aircraft structures design process to assess safety margins and ensure structural integrity. Safe water landings ("ditching") impose extreme transient fluid-structure interaction (FSI) loads on aircraft. Traditionally, these interactions have been managed using simplified added-mass techniques, which often fail to capture nonlinear effects and free-surface topology changes. This paper showcases the modeling strategy of applying the mesh-free Finite Pointset Method (FPM) coupled two-way with the Virtual Performance Solution (VPS) explicit Finite Element Method structural solver to holistically model external ditching phases (impact, landing, and flotation). Guided high-speed panel tests at flight-representative velocities and legacy model-scale datasets are used to evaluate pressure timing, magnitude, and structural response. We examine gauge-pressure cut-off treatments for robustness during cavitation/ventilation regimes and explore rough-water effects using validated numerical wave generation. Results demonstrate strong correlation on rigid panels, credible multi-phase pressure histories, and highly stable aircraft-scale kinematics. Crucially, FPM's implicit time integration enables practical engineering runtimes where explicit Smoothed Particle Hydrodynamics (SPH) or meshed Arbitrary Lagrangian-Eulerian (ALE) frameworks would be computationally prohibitive.
Stacked co-rotating rotors offer a mechanically simple alternative to conventional coaxial counter-rotating systems, but their aerodynamic performance is strongly dependent on both axial and azimuthal blade spacing. This study experimentally and numerically investigates the effects of rotor spacing on the performance and wake structure of model-scale stacked rotors in hover. A dedicated test platform was developed to measure thrust, power, and phase-resolved 2D-3C particle image velocimetry flow fields for two-bladed stacked rotors over axial spacings of Δz/c=0.75 to 5 and azimuthal spacings of ϕ = 0° and 90°. Relative to isolated two- and four-bladed baseline rotors, the stacked configurations exhibited measurable variations in total hub loading and induced flow structure as a function of spacing. The flow field results show that changes in axial spacing alter the relative position of the lower rotor within the convected wake of the upper rotor, producing corresponding changes in inflow, effective angle of attack, and total thrust. Azimuthal spacing further modifies these trends by shifting the phase relationship between upper- and lower-rotor blade passages. To interpret these effects, a coupled blade element momentum theory and Blade Interaction Prediction model was developed. The model captures the primary trends in measured thrust and sectional loading, demonstrating that both wake convection and chordwise blade interaction are required to predict the aerodynamic behavior of closely spaced stacked rotors.
This paper introduces an eigenvalue-based whirl flutter prediction method accounting for aerodynamic interactions between a wing and propeller. The linearized unsteady vortex lattice method was utilized to model fixed-wing aerodynamics while the linearized viscous vortex particle method was utilized to model rotary-wing aerodynamics. The complete aerodynamics model was then coupled with computational structural models to demonstrate the capabilities of the model to predict whirl flutter using an eigenvalue-based method. Two computational structural models were used: the first being an analytical propeller model affixed to a rigid wing via root springs and dampers, and the second being the University of Michigan's Nonlinear Aeroelastic Simulation Toolbox. These models demonstrate the capabilities of the linearized aerodynamics model in predicting instability with structural models of different fidelities, both considering and not considering aerodynamic interactions. The linearized aerodynamics model predicts a reasonable aeroelastic solution when coupled with the structural models, but requires more investigation as to whether aerodynamic interactions are being sufficiently captured.
A challenge in establishing rotor performance map for sizing tool during design cycle is the rotor performance uncertainty for full vehicle. Sometimes, simplified tests at different setup/scale are conducted to guide performance map, but this introduces another uncertainty due to configuration difference from full vehicle. To aid insights, validated computational fluid dynamics simulations (using CREATE-AV™ Helios) were carried out to examine hovering rotor performance prediction variations at different design stages, or different modeling/testing setup with identical blade design. Quantitative rotor figure of merit differences has been demonstrated along with descriptions of underlying physical reasons. The examined model setup includes isolated rigid blades with and without flapping, elastic blades, model-scale blades, whirl-tower conditions, blades installed on fuselage, and full-vehicle including tail rotor. Both fully turbulent flow and laminar-turbulence transition flow assumptions were simulated. Rigid blades showed a negative impact on performance due to the lack of nose-down elastic twist. Model scale suffered from lower Reynolds number effects but took advantage of delayed laminar-turbulence transition. Whirl-tower blockage and altered vortex trajectories reduced peak figure of merit but delayed stall. Fuselage installation increased performance with partial in-ground effect. However, the tail rotor disrupted the main rotor vortex system and caused a substantial figure of merit drop. The figure of merit variation summary from current study can provide qualitative trends and rough estimate of the rotor performance change along different analysis or test condition during new design process. Well validated computational fluid dynamics simulations can be used as a risk-reduction approach by comparing with simplified-model results (used during fast design cycle) with the expected full-vehicle model results.
This paper investigates the impact of aerodynamic interactions on the dynamic aeroelastic stability of a wing-propeller configuration, with emphasis on whirl flutter. The wing structural dynamics are modeled using linear Euler-Bernoulli beam finite elements, while the propeller is represented using Reed's two-degree-of-freedom model. Baseline stability analyses neglecting aerodynamic interactions employ strip theory for the wing and the Houbolt-Reed formulation for the propeller. Analyses that account for aerodynamic interactions are then performed by coupling the wing and propeller structural models with the unsteady vortex-lattice method. Whirl flutter points are identified from transient simulations under both thrusting and windmilling conditions. Results show that three-dimensional aerodynamic effects increase the whirl flutter speed, whereas wing-propeller aerodynamic interactions play a slightly destabilizing role. Thrusting conditions produce a lower critical speed than the wind-milling case. The results demonstrate the viability of the unsteady vortex-lattice method as a unified aerodynamic framework for aeroelastic stability analysis of wing-propeller systems with mutual aerodynamic interactions. In addition, they reinforce findings from previous work that highlighted the destabilizing role of wing-propeller aerodynamic interactions.
This study presents a high-fidelity aeroelastic analysis for lift-offset coaxial rotors based on a three-dimensional (3D) finite element (FE) multibody dynamic analysis. The structural model is based on an updated Lagrangian formulation to capture geometrically nonlinear behavior. The internal aerodynamic model uses lifting line theory with linear inflow model, while the external aerodynamic model employs a panel/vortex particle method to predict aerodynamic loads. The lift-offset coaxial rotor developed by Korea Aerospace Research Institute is employed to investigate the aeroelastic response and the coupling analysis is performed on hover flight condition. The results obtained from the aeromechanics analysis using uniform inflow are compared with CAMRAD II in terms of blade displacement and sectional loads. Furthermore, through high-fidelity aeroelastic analysis using panel/vortex particle method, rotor–rotor aerodynamic interactions and structural loads, and 3D stress and strain distributions are investigated.
A velocity potential-based finite state model (VPBFSM) has been developed to analyze an isolated rotor in ground effect. The model represents the ground using mass source distributions and imposes the non-penetration of flow boundary condition at the ground. In this paper, VPBFSM predictions of the inflow distribution are compared with experimental results for full and inclined ground effect cases using a model-scale rotor. The VPBFSM shows good agreement with the experimental results and captures the expected trend of decreasing inflow as the rotor approaches the ground, with a larger reduction on the side closest to the ground. Differences in magnitude are observed, but remain acceptable and are attributed to reduced-order modeling assumptions in the VPBFSM and uncertainty in the experimentally derived inflow measurements.
With the growing trend of electric vehicles (EVs) incorporating regenerative braking systems, many compact SUVs, including hybrids and EVs, still utilize drum brakes on the rear wheels to strike a balance between cost, performance, and durability. Drum brake squeal remains a complex and persistent challenge in the field of vehicle noise, vibration, and harshness (NVH). This issue stems from dynamic instability caused by time–dependent friction forces. Traditional linear modal analysis has been used to study the mechanisms behind drum brake squeal, focusing on harmonic vibrations in large–scale models. However, these methods often fail to accurately correlate with real world behavior due to the presence of extra, non-physical modes. To address this, time–domain analysis approaches have been explored, incorporating detailed friction models and contact mechanics. These methods consider different root causes for high and low–frequency squeal and have shown promising results in accurately predicting brake squeal behavior when validated against experimental data.
Recent flight tests and simulations have suggested that the outwash from eVTOL air-taxis could be larger than conventional helicopters of equal weight and thus pose greater safety issues for their operation than previously anticipated. This has prompted interest in the analytical and experimental study of the aerodynamics related to multi-rotor aircraft outwash. This paper will describe work investigating some of the related issues, specifically (1) how wake models and wake model parameters impact outwash predictions in comprehensive rotorcraft analyses and (2) considerations when scaling results from model scale to full scale. This work will also compare outwash predictions for conventional and multi-rotor VTOL aircraft obtained with a Lagrangian free-vortex wake model and with an Eulerian velocity-vorticity grid based wake model.
This paper presents the design of a cost-effective fuel injector driver designed for accelerated testing of injectors. The driver simulates injection patterns across a wide range of vehicle operating conditions and can be programmed with injection maps for different engines, test cycles based on drawing specifications, pre-defined engine running profiles, and manual control, where the user defines PWM frequency and duty cycle. It also enables remote operation through a Wi Fi access point. An injector driver-based test setup was developed to study wear and evaluate leakage tendency in an injector design. To simulate extended field usage in a short timeframe, an accelerated operating cycle was derived using telematics data. Injector samples were tested with periodic leak rate measurements. Conducting such tests at vehicle level or on engine test bench would involve significant time and cost. This setup is an effective tool for rapid comparative analysis across supplier design, enabling data driven product selection. It can also be used for quick evaluation of design improvement features introduced in injectors. The flexible architecture and remote operability make it a valuable tool for future injector development and validation.
Endoscopic imaging system development requires coordination between various engineering disciplines, especially for optical illumination and imaging engines, particularly when adding fluorescence imaging capabilities. The optical illumination and imaging engines set the foundation for building intuitive and effective imaging products around and become even more critical when adding fluorescence imaging (FI) capabilities to user needs.
Thermal or infrared signature management simulations of hybrid electric ground vehicles require modeling complex heat sources not present in traditional vehicles. Fast-running multi-physics simulations are necessary for efficiently and accurately capturing the contribution of these electrical drivetrain components to vehicle thermal signature. The infrared signature and heat transfer simulation tool, “Multi-Service Electro-optic Signature” (MuSES), is being updated to address these challenges by expanding its thermal-electrical simulation capabilities, provide a coupling interface to system zero- and one-dimensional modeling tools, and model three-dimensional air flow and its convection effects. These simulation capabilities are used to compare the infrared signatures of a tactical ground vehicle with a traditional powertrain to a hybrid electric version of the same vehicle and demonstrate a reduction in contrast while operating under electrically powered conditions of silent watch and silent mobility.
This paper explores a significant step forward, regarding the further detailed understanding of the Fenestron®. Since its patent in 1968 – for the Gazelle helicopter –, the shrouded tail rotor has been resized, inclined, modulated, etc. and has thus been continuously enhanced on different rotorcraft. Half a century after its invention, Airbus is once again exploring in more detail the magic of the Fenestron®, with the objective of optimizing it even further, for future helicopter applications. To grasp and observe properly some specific phenomena, a model (scaled to one third) capable of both unprecedented functions and modularities, was developed. The present paper will describe in detail the novel model and the related challenges and solutions. This model is capable of high rotor speed and dynamic pitch inputs, delivering power levels high enough to reach stall effects, while allowing the measurement of propulsive efficiency and to differentiate rotor vs fairing thrust. Furthermore, the model had to provide aerodynamic-shape modularity, both in the shroud, on the covers and on the tail gearbox supports. The first test campaign performed on this model allowed us to define design drivers and aerodynamic preferences. And since one idea often leads to another, another challenge is being addressed on this scaled mock-up: Reduction of the tail rotor noise level.
This paper discusses the development of a quantitatively-accurate non-linear hybrid flight dynamics model of a hover-capable Air-Launched Tailsitter Unmanned Aerial System (ALUAS) in order to 1) understand its dynamics during complicated maneuvers, and 2) provide a high-fidelity framework to develop novel control laws. Wind tunnel tests were conducted on a 1:1 scale model of the full aircraft to measure the airloads, which were used in the simulation as a lookup table. Flight tests of the ALUAS were performed in hover, transition, and cruise to collect a large amount of unique state measurements by providing large excitations to induce highly transient motion. The flight dynamics predictions using Rotorcraft Comprehensive Analysis System (RCAS) software were then compared with experimental flight test data. To correct any discrepancies in the RCAS physics-based predictions, a correction was learned from the experimental measurements, making use of the large amount of collected flight test data. Using a neural network to learn this correction, the end result was a quantitatively accurate neural network assisted flight dynamics model. The accuracy of current simulations in complex flight states successfully demonstrates the applicability of the proposed methodology for correcting the dynamics model of novel out-of-the-box aircraft configurations.
Current paper summarizes a correlation study of two flow solvers (CREATETE-AV Helios and Simcenter STAR-CCM+), routinely used at Sikorsky, with multiple model-scale wind-tunnel tests. The Helios modeling approach was aiming for a high-fidelity accurate simulation, whereas the STAR-CCM+ modeling approach was aiming for a fast turn-around time with reasonable solution accuracy with a relatively coarse mesh and simplifications. The two solvers generally agreed well with the test data within reasonable accuracy and captured the airloads and flowfield trends. The calculations presented herein show the impact of the turbulence model on component loads, the aerodynamic interactions among components, and the effect of transition modeling on rotor performance. The Reynolds-Averaged Navier-Stokes CFD model generally delayed separation and resulted in lower drag. By modeling the airframe supporting structure in CFD simulations, an improvement on correlation for inflow on the propeller plane was shown. Additionally, improvements in the rotor system L/De correlation were realized by including a turbulence-transition model, which reduces the rotor drag.
This paper presents an overview of the comprehensive aerodynamic framework developed at ERC for the analysis and simulation of electric vertical takeoff and landing (eVTOL) aircraft. Addressing the challenges inherent to distributed propulsion architectures and the complex transition between hover and forward flight, the methodology integrates multi-fidelity simulation tools ranging from analytical models and low-fidelity simulation to fully-resolved transient CFD. The framework addresses all phases of aircraft design and validation, and includes dedicated insight into aeroacoustics, aeroelasticity, and interactional aerodynamics problems. A modular approach is adopted, where individual phenomena are first studied in isolation before being synthesized into an aircraft model. Experimental validation through wind tunnel testing, full-scale static thrust test stand measurements, and scaled model flight tests is essential to ensuring model accuracy and validity. The paper concludes with an outlook to further enhance data generation, simulation efficiency, and fidelity in future eVTOL development programs.
Hybrid additive manufacturing (AM) and subtractive manufacturing (SM) processes utilize the combination of AM (e.g., LPBF and DED) and SM (e.g., milling and turning operations) to produce the final part. Due to the poor surface roughness resulting from the uneven melting of powders in AM, the subtractive process is a necessary finishing operation to improve the surface roughness of the AM part. The hybrid AM/SM technology combines the benefits of AM and SM processes to create complex geometry while introducing good surface finish and compressive stress to prevent crack initiation. However, the relationship between large process parameter space and the residual stress/distortion in the part is not well understood, which impedes the adoption of hybrid AM/SM to minimize the residual stress in the final product. To expedite the process optimization, we establish a pipeline for the sequential modeling of additive manufacturing (AM) and subtractive manufacturing (SM) processes. Key accomplishments achieved under this study include (1) development of thermal abstraction technique for the AM process to speed up the macroscale level heat transfer analysis based on the manufacturing factors including scanning vector, laser power, dwelling time, etc.; (2) development of the sequentially coupled thermal-mechanical model to predict the residual stress and distortion after AM process by passing the temperature history obtained from heat transfer analysis to the mechanical analysis at each time point; (3) validation of the thermal-mechanical model for AM using thin-wall structure from literature and cantilever beam structure from UNT’s experiments data; (4) conduction of the parametric study on the chamber temperature and part design in the AM process to demonstrate how the temperature gradient and supporting structure affect the residual stress and distortion; (5) exploration of macro and micro scale models to predict the bulk and surface residual stress after cutting; (6) applying the developed modeling framework to tailoring the hybrid AM/SM process. To support model verification and demonstration, we print cantilever beam structure with different supporting structure designs and cutting strategies to study how these factors affect the final part residual stress and distortion. The data collected in the printing and cutting process is used to examine the applicability of the developed simulation tool.
Aeroelastic stability prediction is critical to the successful design, development and flight testing of rotorcraft. As configurations reach higher speeds, new challenges in high Mach number unsteady aerodynamic modeling need to be addressed, especially for higher frequency aeroelastic modes with significant coupling. In this paper, Linear Unsteady aerodynamics and Leishman-Beddoes attached flow models are applied and compared to 2D CFD (airfoil) and 3D CFD/CSD (rotor) analysis for operating conditions of interest. The Leishman-Beddoes model demonstrates improved agreement with CFD data. In the 2D assessment, RCAS is used to model a representative airfoil undergoing prescribed pitch and heave oscillations. CFD results are presented to compare each model (Linear Unsteady and Leishman-Beddoes). In the 3D assessment, a full rotor CFD/CSD test case is evaluated for aeroelastic stability and compared to RCAS standalone analysis. The RCAS rotor structural model is coupled with the HELIOS CFD code and a swashplate cyclic pitch input is used to excite a lightly-damped rotor mode. The transient response based on RCASHELIOS is compared to the standalone RCAS internal aerodynamic result for both Linear Unsteady and Leishman- Beddoes unsteady aerodynamics. This study demonstrates that the Leishman-Beddoes model can produce similar stability results to the computationally expensive coupled CFD/CSD approach of RCAS-HELIOS, but at a lower computational cost, even for critical high-speed conditions.
Electrification in the automotive industry has been steadily rising in popularity for many years, and with any technology there is always a desire to reduce development cost by efficiently iterating designs using accurate simulation models. In the case of rotating machinery and other devices that produce vibrations, an important physical behavior to simulate is Noise Vibration and Harshness (NVH). Efficient workflow to account for NVH was established at Schaeffler for eMotor design. Quantitative prediction is difficult to achieve and is occasionally intended only for faster iterations and trend prediction. A good validated qualitative simulation model would help achieve early NVH risk assessment based on the specified requirement and provide design direction and feasibility guidance across the design process to mitigate NVH concerns. This paper seeks to provide a general approach to validate the simulation model. The correlation methods used in this paper consist of a combination of alignment with structure-borne noise (SBN) and experimental modal analysis (EMA). It is ideal to validate component-level EMA before final assembly, but for more complex components this can be difficult. Many checks must be made for the test including validating magnet temperatures, sensor positions, and boundary conditions. For the permanent magnet synchronous motor (PMSM) drive unit in this case study, predictions of the SBN trend and response magnitude were improved.
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