1-10 of 61 results

  • Incorporating ANSYS Simulation Tools Into Engineering Programs at Embry-Riddle Aeronautical University

    PI Fady Barsoum

    CO-I Arka Das

    CO-I Heidi Steinhauer

    CO-I William Engblom

    CO-I Chad Rohrbacher

    This project aims to introduce and implement ANSYS computer modeling and simulation tools into the Engineering Programs at Embry-Riddle.

    This project aims to introduce and implement ANSYS computer modeling and simulation tools into the Engineering Programs at Embry-Riddle. Utilizing ANSYS in the undergraduate curriculum significantly enhances learning outcomes. It allows students to visualize complex physical phenomena, providing clarity on theoretical concepts. Additionally, hands-on experience with the software aligns students with industry standards, preparing them for future careers. Project-based learning fosters essential problem-solving skills. Finally, interactive simulations boost student engagement, making engineering topics more appealing.

    Categories: Faculty-Staff

  • Novel Space Science Test via Adaptive Control and Integral Concurrent Learning Leveraging On-Orbit CubeSat Structural Identification

    PI Riccardo Bevilacqua

    The objective of this work is to create the basic science underpinning the structural testing and evaluation framework and control for deployable large spacecraft.

    The objective of this work is to create the basic science underpinning the structural testing and evaluation framework and control for deployable large spacecraft. Large space structures and those with high dimensional ratio between deployed and stowed configurations are extremely difficult to test on the ground. The AFRL’s Space Vehicle Directorate recently opened the new Deployable Structures Laboratory, or DeSeL, as evidence of a renewed interest towards these systems. DeSeL represents the state-of-the-art technology for on-the-ground experimentation of deployable systems. In particular, an active Gravity Off-Load Follower (GOLF) cart system is being currently developed, intended to have three degrees of freedom (attitude motion) which could foreseeably provide the capability for large low-frequency motions. The real capabilities of the GOLF system are yet to be determined, and this research effort will develop in parallel, assist, support and inform the development of this new facility at AFRL.

    New testing and evaluation science to identify these systems’ behavior and control them, that are robust to large uncertainties in the structural dynamics are then needed, and the first time they deploy on orbit is the ultimate test.

    We propose to obtain the objective by combining novel control and learning theory with ad-hoc experimental activities. The culmination of this effort will be a flight demonstration, where a CubeSat previously designed by the Advanced Autonomous Multiple Spacecraft (ADAMUS) laboratory will be modified in its design and perform autonomous on-orbit structural identification, control, and testing.

    The flight demonstration will be based on measuring the natural frequencies, damping ratios and vibration mode shapes via excitation of the spacecraft, using reaction wheels on the main hub and potentially distributed small thrusters on the flexible bodies, emulating the configuration of the AFRL’s Space Solar Power Incremental Demonstrations and Research Project (SSPIDR).

    Categories: Faculty-Staff

  • GNC Efforts in Support of the University of Floridas Research for the NASA Instrument Incubator

    PI Riccardo Bevilacqua



    The following tasks will be performed by one Ph.D. student and Dr. Bevilacqua (PI at ERAU), in support of the University of Florida’s proposal for the NASA’s Instrument Incubator Program (IIP):

    Year 1:

    • Drag-compensation and test mass control design. Adaptive control combined with integral concurrent learning will be investigated to estimate, in real-time, the effects of drag on the spacecraft, to enable precise control of the test mass inside it. The PI has successfully used this technique for drag-based spacecraft formation flight, where online estimation of the ballistic coefficient of an unknown vehicle is critical.
    • Support for drag-compensation thruster mapping. Lyapunov-based thruster selection principles, previously developed by the PI, will be used to simplify the thruster mapping problem, and prevent the use of any numerical iterations, to ease online implementation. An additional step will involve exploring the possibility to use adaptive + ICL control to also estimate the thrust errors and their misalignment.

    Year 2:

    • Spacecraft acceleration estimation based on S-GRS outputs. The test mass position and orientation are measured inside the sensor and the applied forces and torques on the test mass are known. How to use this information to optimally estimate the spacecraft acceleration and angular acceleration due to atmospheric drag remains a challenge. An approach based on a bank of Kalman (or Extended Kalman) Filters will be explored, possibly in iterative form, as previously done for spacecraft relative motion estimation by Dr. Gurfil at Technion and by the PI and one of his former students.

    Year 3:

    • Support for hardware-in-the-loop testing of the control system at UF. The PI and the PhD student will support experimentation at UF, to implement the above algorithms in hardware systems. The PI has over a decade of experience in on-the-ground testing of spacecraft GNC systems.

    Year 1-3:

    • Support for numerical simulation of the closed-loop system. High-fidelity orbital and attitude propagators will be used to test the algorithms developed. STK and NASA’s Spice will also be candidates for comparison.

    Categories: Faculty-Staff

  • CubeSats Hosting Flexible Appendages for On-Orbit Testing of Advanced Control Algorithms

    PI Riccardo Bevilacqua

    ​The objective of this work is to start the assembly of a CubeSat hosting specialized flexible appendages, taking inspiration from a previously designed spacecraft developed by the Advanced Autonomous Multiple Spacecraft (ADAMUS).

    The objective of this work is to start the assembly of a CubeSat hosting specialized flexible appendages, taking inspiration from a previously designed spacecraft developed by the Advanced Autonomous Multiple Spacecraft (ADAMUS). This CubeSat will eventually enable testing of ADAMUS’ developed spacecraft control algorithms on-orbit.

    Relevance to NASA: The innovation proposed herein lies in the ability to autonomously characterize and control complex space structures. This project will directly support NASA’s TA 4: Robotics and Autonomous Systems

    Categories: Faculty-Staff

  • A Machine Learning Based Transfer to Predict Warhead In-Flight Behavior from Static Arena Test Data

    PI Riccardo Bevilacqua

    The objective of this work is to combine high-fidelity numerical models with unique/ad-hoc experimental activities to strengthen basic science underpinning the test and evaluation framework for warhead fragmentation and fragments fly-out.

    Warhead fragmentation predictions are based on either numerical simulations or static arena tests where detonations occur in unrealistic conditions (not flying). The first methodology presents many shortcomings: there is no agreement on the state of the art for simulations, and many tools ignore important aspects such as gravity, aerodynamic forces and moments, and rigid body motion of different shape fragments. Numerical simulations are also lengthy and cannot be used as online/on-the-battlefield tools. The experimental approach is also extremely limited, as it does not reproduce the real-world conditions of a moving warhead.

    The objective of this work is to combine high-fidelity numerical models with unique/ad-hoc experimental activities to strengthen basic science underpinning the test and evaluation framework for warhead fragmentation and fragments fly-out. In particular, we will aim at combining the most advanced simulation capabilities with static experimental data, to obtain a transfer function predicting lethality and collateral damage of a given warhead in real-life conditions. Artificial neural networks and/or other machine learning tools (e.g., Random Forests) will be used to capture the underlying physics governing fragments dispersion under dynamic conditions, coming from NAVAIR’s Spidy software, and eventually combine this knowledge with real warhead characteristics, coming from the static test. This proposal is of high impact because of the existing gap in analytical tools to define and validate warhead fragmentation testing.

    The broader impact (long term) of this work may be a software tool that the warfighter can use on the field to rapidly assess the effects of the arsenal at his disposal. This tool will be equally beneficial to designers and testers within the Air Force and the DoD in general.

    Categories: Faculty-Staff

  • A Boltzmann Simulator for Porous Media Flows

    PI Leitao Chen

    ​This project develops numerical simulations through parallel development of a Boltzmann model to capture and elucidate multiscale thermos-fluids behaviors in porous media, as well as the fluid-solid interactions.

    ​To accurately simulate porous media flow problem, a kinetic model based on the Boltzmann equation (BE) was developed. Two primary reasons justified the choice of a BE-based approach over conventional Navier-Stokes (N-S) computational fluid dynamics (CFD) methods. First, the fluid flow within porous media often occurs in extremely narrow channels, representing high-Knudsen-number flow regimes. The Knudsen number (Kn), defined as the ratio of molecular mean free path to the smallest channel dimension, indicates that traditional N-S equations are physically inadequate for accurately describing these flow conditions. Conversely, BE-based models are well-established to yield physically accurate results for high-Kn flows. Second, from a computational standpoint, the BE inherently involves a simpler mathematical structure due to its linear advection term, substantially reducing computational overhead compared to the nonlinear N-S equations. This simplification significantly improves computational efficiency, especially critical for simulating flow within complex porous structures. To better capture the complex boundaries in porous media, a meshless discretization method of the BE has been developed in this project. This meshless approach entirely eliminates dependency on mesh generation, offering significant advantages in accurately simulating flow through porous media.

    Categories: Faculty-Staff

  • Pure Water Project (PWP)

    PI Marc Compere

    Pure Water Project aims to improve the health and sustainability of individual communities in the Dominican Republic by installing a solar-powered water purification system. Embry-Riddle students design, build, test and deliver a solar water purifier to carefully selected communities in the Dominican Republic and launch water selling businesses to benefit the local community’s health and economy.



    Many in the Dominican Republic either pay for clean water or live with chronic intestinal sickness from contaminated water. Our solar water purifier is designed to provide clean drinking water for 500 adults per day. It generates 1000 gallons of clean water daily, which is enough to bottle and sell to the surrounding community.

    This project is an ideal intersection of humanitarian aid and engineering. Our students design and build Embry-Riddle's solar-powered water purifier for delivery to a carefully selected community each year. Students learn how solar power systems work with batteries, pumps and filters to construct a purifier that runs entirely from the sun. This project provides our students a global perspective and makes them better engineers through their efforts to achieve goals despite the dynamic, fluid environment in a different culture.

    Categories: Faculty-Staff

  • Maritime RobotX Challenge

    PI Eric Coyle

    CO-I Patrick Currier

    CO-I Charles Reinholtz

    CO-I Brian Butka

    The Maritime RobotX Challenge entails the development and demonstration of an autonomous surface vehicle (ASV). Embry-Riddle is one of three U.S. schools selected to compete in the challenge, which is co-sponsored by the Office of Naval Research (ONR) and the Association for Unmanned Vehicle Systems International (AUVSI) Foundation.



    ​The 2014 ERAU platform, named Minion, is a 16-foot fully-autonomous Wave Adaptive Modular Vessel (WAM-V) platform and is registered as an autonomous boat in the state of Florida. Minion's development currently focuses on autonomous tasks of buoy channel navigation, debris avoidance, docking, target identification and sonar localization. To accomplishing these tasks, the team has developed as set of system software nodes including state estimation, object classification, mapping and trajectory planning. These nodes run in parallel across a set of networked computers for distributed processing. Minion's propulsion system is centered around a set rim-driven hubless motors attached to articulated motor pods. This design reduces the risk of entanglement, and provides consistent thrust by maintaining motor depth in rough seas.

    The group is currently developing the 2016 platform for the competition

    Categories: Faculty-Staff

  • Multi-Modal Sensor Fusion for ASV Situational Awareness

    PI Eric Coyle

    CO-I Patrick Currier

    An investigation into strategies and techniques for maritime object detection and classification using visual and spatial data with an emphasis on sensor fusion.

    This project focuses on enhancing autonomous surface vessel (ASV) situational awareness through the fusion of visual and spatial sensing, aiming to improve the detection and classification of objects in the surrounding environment. Such technologies have applications in patrolling test ranges, enhancing harbor security, and using ASVs as support vessels for manned operations. The research is structured around four main objectives: creating and annotating multi-modal maritime data for sensor fusion, developing accurate surface maps for navigation, applying machine learning techniques for robust object identification, and creating sensor fusion strategies for improved robustness. The team uses a custom data acquisition system, which was used to create the open-source ER-Coast dataset. This dataset includes Light Detection and Ranging (LiDAR), high-resolution cameras, infrared cameras, and localization sensors to capture coastal waterways in Florida, both day and night, across 36 sequences. A portion of this data has been made publicly available for future LiDAR semantic segmentation, image segmentation, and object detection studies.

    Categories: Faculty-Staff

  • Investigation of an Injection-Jet Self-Powered Fontan Circulation: A Novel Bridge and Destination Therapy for the Failing Fontan

    PI Eduardo Divo

    CO-I Arka Das

    This research effort unifies multiscale computational fluid dynamics (CFD) and mock circulatory loop (MCL) benchtop cross-validations to analyze the hemodynamic impact of an innovative palliative alternative: the Injection-Jet-assisted Fontan circulation.



    A structurally normal heart consists of two separate pumping chambers, or ventricles. One pumps deoxygenated blood from the body to the lungs, while the other delivers oxygenated blood from the lungs to the body. Approximately 8% of all newborns with a congenital heart defect have only a single functioning ventricle (SV). These patients cannot survive without a series of staged palliative operations to ensure adequate blood flow to both the pulmonary and systemic circulations. The final step in this staged reconstruction is the Fontan operation. While lifesaving, this unique physiology directs systemic venous return passively into the pulmonary arteries without the need for a subpulmonary pump. This results in chronically elevated central venous pressure and reduced cardiac output. Over time, this non-physiologic flow leads to significant morbidity, including hepatic fibrosis, protein-losing enteropathy, and Fontan-associated liver disease. A 2018 study of 683 adult Fontan patients from the Australian and New Zealand Fontan Registry reported 20% mortality by age 40, with only 53% free of heart failure symptoms and 41% free of serious adverse events. Similar outcomes have been documented worldwide, with nearly half of the observed morbidity and mortality attributed directly to failure of the unique Fontan circulatory system. To address this growing clinical challenge, our team is developing a novel, surgically implantable Injection-Jet Shunt (IJS) as a passive support strategy for patients with a failing Fontan circulation. This approach challenges the prevailing paradigm that mechanical pumps are the only viable support option for this population. Our proposed mechanism utilizes an intra-corporeal, surgically feasible shunt that harnesses the patient’s own cardiac power to inject a high-velocity jet from the aorta into the Fontan conduit. This jet entrains ambient inferior vena cava (IVC) flow, facilitating momentum transfer into the pulmonary circuit and unloading proximal venous pressure, all without any external power source. Multi-scale CFD simulations have demonstrated that this mechanism can lower Fontan pressure by 3 to 4 mmHg while maintaining clinically acceptable systemic oxygen saturations. These encouraging in-silico findings are currently being cross-validated in-vitro using a dynamically calibrated MCL that replicates Fontan hemodynamics under both resting and simulated exercise conditions. To characterize the flow behavior and jet entrainment dynamics of the Injection-Jet Shunt (IJS), the experimental MCL integrates both Particle Image Velocimetry (PIV) and Light-Induced Fluorometry (LIF) systems. PIV enables high-resolution quantification of velocity fields and shear layers, while LIF captures real-time oxygen transport in benchtop Fontan surrogates, allowing for the assessment of systemic flow distribution and entrained volume fractions. A Proper Orthogonal Decomposition trained Radial Basis Function (POD-RBF) interpolation framework is applied to reconstruct and enhance the spatiotemporal flow fields. This combined optical and data-driven approach enables detailed mapping of jet structure, entrainment efficacy, and pulmonary perfusion, supporting the optimization of IJS configurations for future clinical translation. If successful, the IJS may provide a low-risk, fully passive alternative to conventional mechanical support, potentially delaying or obviating the need for heart transplantation and improving quality of life for children and young adults with single-ventricle physiology.

    Categories: Faculty-Staff

1-10 of 61 results