Department of Aerospace Engineering

Department of Aerospace Engineering

ID

aere

Description

The Department of Aerospace Engineering seeks to instruct the design, analysis, testing, and operation of vehicles which operate in air, water, or space, including studies of aerodynamics, structure mechanics, propulsion, and the like.

History
The Department of Aerospace Engineering was organized as the Department of Aeronautical Engineering in 1942. Its name was changed to the Department of Aerospace Engineering in 1961. In 1990, the department absorbed the Department of Engineering Science and Mechanics and became the Department of Aerospace Engineering and Engineering Mechanics. In 2003 the name was changed back to the Department of Aerospace Engineering.

Dates of Existence
1942-present

Historical Names

Department of Aerospace Engineering and Engineering Mechanics (1990-2003)

Related Units

College of Engineering (parent college)
Department of Engineering Science and Mechanics (merged with, 1990)

Full item page

Permanent Link

https://dr.lib.iastate.edu/handle/20.500.12876/98928

Publication Search Results

Now showing 1 - 10 of 1059

Article

Relative Pose Estimation of an Uncooperative Target with Camera Marker Detection

2025-05-10 , Candan, Batu , Servadio, Simone , Department of Aerospace Engineering

Accurate and robust relative pose estimation is the first step in ensuring the success of an active debris removal mission. This paper introduces a novel method to detect structural markers on the European Space Agency’s Environmental Satellite (ENVISAT) for safe de-orbiting using image processing and Convolutional Neural Networks (CNNs). Advanced image preprocessing techniques, including noise addition and blurring, are employed to improve marker detection accuracy and robustness from a chaser spacecraft. Additionally, we address the challenges posed by eclipse periods, during which the satellite’s corners are not visible, preventing measurement updates in the Unscented Kalman Filter (UKF). To maintain estimation quality in these periods of data loss, we propose a covariance-inflating approach in which the process noise covariance matrix is adjusted, reflecting the increased uncertainty in state predictions during the eclipse. This adaptation ensures more accurate state estimation and system stability in the absence of measurements. The initial results show promising potential for autonomous removal of space debris, supporting proactive strategies for space sustainability. The effectiveness of our approach suggests that our estimation method, combined with robust noise adaptation, could significantly enhance the safety and efficiency of debris removal operations by implementing more resilient and autonomous systems in actual space missions.

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Preprint

Dynamical Update Maps for Particle Flow with Differential Algebra

2025-05-02 , Servadio, Simone , Department of Aerospace Engineering

Particle Flow Filters estimate the "a posteriori" probability density function (PDF) by moving an ensemble of particles according to the likelihood. Particles are propagated under the system dynamics until a measurement becomes available when each particle undergoes an additional stochastic differential equation in a pseudo-time that updates the distribution following a homotopy transformation. This flow of particles can be represented as a recursive update step of the filter. In this work, we leverage the Differential Algebra (DA) representation of the solution flow of dynamics to improve the computational burden of particle flow filters. Thanks to this approximation, both the prediction and the update differential equations are solved in the DA framework, creating two sets of polynomial maps: the first propagates particles forward in time while the second updates particles, achieving the flow. The final result is a new particle flow filter that rapidly propagates and updates PDFs using mathematics based on deviation vectors. Numerical applications show the benefits of the proposed technique, especially in reducing computational time, so that small systems such as CubeSats can run the filter for attitude determination.

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Article

Steady states in severe plastic deformations and microstructure at normal and high pressure

2025-03-18 , Levitas, Valery , Mechanical Engineering , Department of Aerospace Engineering

The main fundamental problem in studying plasticity and microstructure evolution is that they depend on five components of the plastic strain tensor εp, its entire path and pressure p and its path p-path, which leaves little hope of finding some general laws, especially at severe plastic straining and high pressures. Here, we review the validity of the following hypothesis for quasi-static material behavior after some critical level of cold severe plastic strain and some straining paths: initially isotropic polycrystalline materials behave like perfectly plastic, isotropic, and strain-path-independent with the corresponding limit surface of perfect plasticity and reach steady values of the crystallite/grain size and dislocation density, which are strain- and strain-path-independent. However, there are multiple steady microstructural states and corresponding limit surfaces of perfect plasticity. The main challenge is to find for which classes of loading paths and p-path material behaves along the same limit surface of perfect plasticity and steady microstructural state and for which loading paths and p-path there is a jump to the different limit surface of perfect plasticity and steady microstructural state. Various experimental, computational, and coupled experimental-computational techniques are analyzed, and some controversies and challenges are summarized.

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Article

Virtual melting and cyclic transformations between amorphous Si, Si I, and Si IV in a shear band at room temperature

2025-03-03 , Chen, Hao , Levitas, Valery , Mechanical Engineering , Department of Aerospace Engineering

Virtual melting (VM) as alternative deformation and stress relaxation mechanisms under extreme load is directly validated by molecular dynamics (MD) simulations of the simple shear of single crystal Si I at a temperature 1383 K below the melting temperature. The shear band consisting of liquid Si is formed immediately after the shear instability while stresses drop to zero. This process is independent of the applied shear rate. A new thermodynamic approach is developed, and the thermodynamic criterion for VM, which depends on the ratio of the sample to shear band widths, is derived analytically and confirmed by MD simulations. Since stress-free melt is unstable at 300 K, with further shear, the VM immediately transforms to a mixture of low-density amorphous a-Si, stable Si I, and metastable Si IV. Cyclic transformations between a-Si ↔ Si I, a-Si ↔ Si IV, and Si I ↔ Si IV with volume fraction of all phases mostly between 0.2 and 0.4 and non-repeatable nanostructure evolution are reveled. Such cyclic transformations produce additional important carriers for plastic deformation through transformation strain and transformation-induced plasticity due to volume change, which may occur in shear bands in various material systems but missed in experiments and simulations. The release of shear stresses quenches the microstructure, and shows reasonable qualitative correspondence with existing experiments.

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Article

Analytical and Data-Driven Koopman Operator for the Perturbed Kepler and Circular Restricted Three-Body Problems

2025-05-09 , Hofmann, Christian , Lavezzi, Giovanni , Wu, Di , Servadio, Simone , Linares, Richard , Department of Aerospace Engineering

A modified version of the Extended Dynamic Mode Decomposition (EDMD) approach for the Koopman operator theory is presented, utilizing sparse-grid quadrature nodes and weights to generate the training data. Compared to standard random sampling, this method emphasizes certain regions of the state space and improves the accuracy and convergence rate of the Koopman operator while reducing the amount of required data. Additionally, we propose a QR decomposition and Koopman modes reduction to reduce the computational effort for analytical propagation. Applications in astrodynamics are considered, where atmospheric drag is included as an additional perturbation in a recently developed set of regularized orbital elements. An extensive comparison of the analytical Galerkin method and the data-driven standard and quadrature-based EDMD approaches is provided. Numerical examples for the analytical prediction of perturbed Keplerian motion and periodic orbits in the circular restricted three-body problem, and a comparison with an analytic propagator demonstrate the efficiency of the developed methods.

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Preprint

Advances in Particle Flow Filters with Taylor Expansion Series

2025-05-02 , Servadio, Simone , Department of Aerospace Engineering

Particle Flow Filters perform the measurement update by moving particles to a different location rather than modifying the particles' weight based on the likelihood. Their movement (flow) is dictated by a drift term, which continuously pushes the particle toward the posterior distribution, and a diffusion term, which guarantees the spread of particles. This work presents a novel derivation of these terms based on high-order polynomial expansions, where the common techniques based on linearization reduce to a simpler version of the new methodology. Thanks to differential algebra, the high-order particle flow is derived directly onto the polynomials representation of the distribution, embedded with differentiation and evaluation. The resulting technique proposes two new particle flow filters, whose difference relies on the selection of the expansion center for the Taylor polynomial evaluation. Numerical applications show the improvement gained by the inclusion of high-order terms, especially when comparing performance with the Gromov flow and the "exact" flow.

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Book chapter

Algebraic Tensorial Representations

2025-03-07 , Durbin, Paul , Department of Aerospace Engineering

The scope of this chapter on tensorial representation is constitutive modeling, realizability of eigenvalues, Galilean invariance and tensorial representation of rotation, or streamline curvature. These topics provide a foundation for other chapters on data-driven modeling and uncertainty quantification cation. The constitutive relations are between the Reynolds stress tensor, or the scalar flux vector, and mean flow rate of strain and rate of rotation tensors. Irreducible and algebraically solvable tensor bases are described. Solvable tensor bases suffice for data-driven modeling. Eigenvalue realizability is represented by a triangular domain, into which the eigenvalues must fall. The idea of locating eigenvalues by their barycentric coordinate within this triangle is reviewed. The idea that rotation and curvature might be characterized by the rate of rotation of the principal axes of the rate-of-strain is described. Representations for passive scalar flux are discussed.

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Article

Analytical Uncertainty Propagation and Maximum A Posteriori Filtering with the Koopman Operato

2025-05-02 , Servadio, Simone , Department of Aerospace Engineering

This paper proposes a method to propagate uncertainties undergoing nonlinear dynamics using the Koopman Operator (KO). Probability density functions are propagated directly using the Koopman approximation of the solution flow of the system, where the dynamics have been projected on a well-defined set of basis functions. The prediction technique is derived following both the analytical (Galerkin) and numerical (EDMD) derivation of the KO, and a least square reduction algorithm assures the recursivity of the proposed methodology. Furthermore, a complete filtering algorithm is proposed, where the predicted uncertainties are updated analytically using the likelihood function, following Bayes’ formulation. Estimates are provided after optimization according to the Maximum A Posteriori formulation, where a backtracking Newton solver identifies the global most likely posterior state.

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Article

Enhanced Laser-Induced Graphene Microfluidic Integrated Sensors (LIGMIS) for On-Site Biomedical and Environmental Monitoring

2025-04-08 , Johnson, Zachary T. , Ellis, Griffin , Pola, Cicero C. , Banwart, Christopher , McCormick, Abby , Miliao, Gustavo L. , Duong, Duy , Opare-Addo, Jemima , Sista, Harsha , Smith, Emily , Hu, Hui , Gomes, Carmen L. , Claussen, Jonathan , Department of Chemistry , Ames National Laboratory , Department of Aerospace Engineering , Department of Food Science and Human Nutrition (HSS)

The convergence of microfluidic and electrochemical biosensor technologies offers significant potential for rapid, in-field diagnostics in biomedical and environmental applications. Traditional systems face challenges in cost, scalability, and operational complexity, especially in remote settings. Addressing these issues, laser-induced graphene microfluidic integrated sensors (LIGMIS) are presented as an innovative platform that integrates microfluidics and electrochemical sensors both comprised of laser-induced graphene. This study advances the LIGMIS concept by resolving issues of uneven fluid transport, increased hydrophobicity during storage, and sensor biofunctionalization challenges. Key innovations include Y-shaped reservoirs for consistent fluid flow, hydrophilic polyethyleneimine coatings to maintain wettability, and separable microfluidic and electrochemical components enabling isolated electrode nanoparticle metallization and biofunctionalization. Multiplexed electrochemical detection of the neonicotinoid imidacloprid and nitrate ions in environmental water samples yields detection limits of 707 nm and 10−5.4 m with wide sensing ranges of 5–100 µm and 10−5–10−1 m, respectively. Similarly, uric acid and calcium ions are detected in saliva, demonstrating detection limits of 217 nm and 10−5.3 m with sensing ranges of 10–50 µm, and 10−5–10−2.5 m, respectively. Overall, this biosensing demonstrates the capability of the LIGMIS platform for multiplexed detection in biologically complex solutions, with applications in environmental water quality monitoring and oral cancer screening.

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Article

Nondestructive characterization of contaminant-induced material softening in epoxy polymers using nonlinear ultrasonic measurements

2025-03-04 , Pyun, Do-Kyung , Barnard, Daniel J , Bond, Leonard , Department of Aerospace Engineering , Center for Nondestructive Evaluation

Epoxy polymer-based materials are widely used in structural assemblies due to their efficient and robust bonding capabilities. Nondestructive testing tools are needed to assess joint quality, and ideally strength, as contaminants, and some other defects, introduced during the manufacturing process can potentially cause material softening of the epoxy, leading to the degradation of the structural integrity of the bonded components. The application of the nonlinear response with ultrasonic methods used to characterize the epoxy material itself has been underexplored. This study investigates the use of an ultrasonic second-harmonic generation (SHG) method to characterize contaminant-induced material softening in epoxy polymers, with the contaminant being a release agent. The nonlinearity parameter associated with SHG was measured with varying contamination levels. To validate the effectiveness of the SHG method, nonlinear resonant ultrasonic spectroscopy (NRUS) was employed to independently assess the variation in material softening with the increase of contamination levels. Additionally, tensile testing was conducted on contaminated samples to establish a correlation between mechanical strength and the nonlinear parameter related to the degradation due to the material softening. This study demonstrated that the SHG technique is a promising nondestructive evaluation method for detecting contaminant-induced degradation in epoxy materials.

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