Nature has long been a source of inspiration when it comes to tackling engineering challenges. Taking this inspiration from nature, our study aims to emulate the behavior of burrowing animals in order to efficiently dig into granular media. The pacific razor clam utilizes its retractable foot muscle to burrow itself while simultaneously expanding and contracting its shell to fluidize the surrounding sand. Our goal is to create a digging device that approaches the digging efficiency of pacific razor clams of 21 J/m. Our hypothesis is that the interaction of vibration and fluidization is key in burrowing performance. We built a cylindrical robotic model composed of both soft and rigid materials, equipped with a vibrational motor and a downward-facing nozzle. We adjusted the energy devoted to vibration and flow to optimize burrowing efficiency as a function of energy per depth.  Preliminary results suggest that a combination of both local fluidization and vibration improves burrowing efficiency over using them independently. We anticipate that different combinations of flow and vibration are optimal for different burrowing stages. By understanding nature's efficient digging techniques, we can create a reliable anchoring system for sensor arrays and underwater vehicles to aid in the study of our oceanic ecosystem.

Fusion, the process powering the sun, offers a promising solution for deep-space propulsion as it can provide high specific impulse and lightweight fuel. The Flow Z-Pinch lab is exploring the innovative sheared flow stabilized (SFS) Z-pinch technique to mitigate plasma instabilities and enable fusion using axial flows, creating a compact, scalable path to fusion power and space thrusters. Interactions with electrodes often introduce impurities into ZaP-HD plasmas, whose emission can be monitored to measure plasma parameters like electron temperature. However, excessive impurity concentrations can also contribute to radiative losses, degrading fusion performance. Spectroscopy is a key diagnostic tool for analyzing impurities, allowing measurements by examining light emissions from atoms. The ionizations per photon method (S/XB), which correlates emission intensity at a specific carbon line to particle flux using empirical coefficients based on temperature and density, will be used to quantify impurity influx. Our project uses an existing spectrometer and photomultiplier tube (PMT) setup, with initial efforts focusing on absolute calibration to relate pixel intensity to photon flux. This diagnostic is essential for our understanding of impurity dynamics and their migration in ZaP-HD plasmas. The PMT can give us a time-resolved measurement to correlate to other time-resolved diagnostics, especially to characterize the erosion rate of electrode surfaces. Preliminary data analysis will calculate carbon influx using calibrated data and S/XB coefficients, with future work extending the diagnostic system to monitor additional carbon charge states and emissions at varying axial locations. This research provides novel insights into impurity behavior in ZaP-HD, enhancing our understanding of plasma-material interactions and informing us of strategies to minimize impurity influx for improved fusion performance.

This study investigates the interactions between drag and grazing flow over a Helmholtz resonator array under varying resonance conditions, using three-dimensional Particle Image Velocimetry (3DPIV) in a subsonic wind tunnel. By adjusting the resonators’ natural frequencies, we examine how velocity fluctuations influence the local boundary layer in the vicinity of, and downstream from, the resonator orifices. Additionally, we evaluate the effects of resonance tuning on grazing flow to enhance our understanding of fluid–structure interactions in acoustic liner systems. These findings provide insights into drag modulation mechanisms and inform future steps in noise attenuation, aerodynamic efficiency, and both active and passive control strategies.

Robotic movement between waypoints—specific points a robot must travel to—is often perceived as stiff and choppy. This is primarily because paths between these points are typically treated as straight lines. A more effective solution for smoother robotic motion involves forming polynomial curves composed of points–or re-discretizing points–rather than linear segments. The process begins by calculating the diameter of the robot’s orbit, which is determined by computing the maximum distance between any two points. With the orbit dimensions defined, a polynomial trajectory can be fitted to the points and constrained within the robotic arm’s circumference, resulting in a smoother and more fluid movement pattern. The use of this approach of spline trajectories as compared to straight line segments will be demonstrated for a robotic application being used to emulate spacecraft motion for relative proximity operation.

As of 2025, the United States has the highest incarceration rate in the world, with its incarcerated population making up 25% of the incarcerated individuals worldwide. Mass incarceration inflicts the most harm on the most vulnerable populations, disproportionately affecting racial and ethnic minorities and creating insurmountable barriers to reintegrating into society. Prison education programs provide opportunities for growth that help prevent recidivism and support rehabilitation efforts, and with the reinstatement of Pell Grants for incarcerated individuals in 2023, there has never been a better time to expand educational opportunities than now. However, little research has been done on prison education programs, with even less research focusing on enhancing and expanding them to address the specific needs of incarcerated individuals, particularly in digital literacy. In a rapidly evolving digital world, it becomes imperative to ensure that incarcerated people, many of whom have had limited experiences with technology due to extended sentences, have the skills to confidently return to a digital society. This project explores how integrating computer science curricula into correctional facilities can increase rehabilitation, reduce recidivism outcomes for incarcerated individuals, and further support other pre-existing educational programs in prisons. To answer this question, we examined legal documents, performed literature reviews, analyzed previous studies on the incarcerated population, and conducted a comprehensive analysis of outcomes from prior prison education programs. Our findings reveal that computer science education for incarcerated people increases self-efficacy rates, post-employment opportunities, and facilitates a smoother transition back into society. Additionally, integrating computer science through enhanced digital infrastructure can address challenges with current educational programs, such as accessibility, course expansion, and classroom segregation. Collectively, this project represents one of the first studies to explore the possibilities for computer education and prisons, offering valuable insights into the potential to improve rehabilitation, reduce recidivism, and address the digital divide.

Low-contrast high-speed video from rotating detonation rocket engines makes analyzing the detonation wave dynamics difficult. This paper outlines a method to process raw video frames into a filtered time series of brightness measured around a discretized one-dimensional annulus, enabling a frequency-domain extraction of wave frequency and wave number. For low-contrast videos in which the combustion chamber boundaries are not readily detected, an alternative approach uses a full-video singular value decomposition (SVD) followed by a manual selection of the annular region. In addition, a Riemannian gradient descent algorithm for SVD computation is investigated, offering the potential for faster convergence under specific conditions. The uncertainty of the frequency analysis procedure is quantified by comparing results against known pressure sensor (PCD) data, demonstrating the robustness and reliability of this method across a range of experimental conditions.

Biological structures by necessity are often optimized for multi-functionality. Northern gannets (Morus bassanus) have developed the ability to plunge-dive into water at speeds of up to 70 mph in pursuit of fish, surviving high impact loads and yet maintaining maneuverability. Their long, slender, and segmented necks are the opposite of current engineered structures anticipated to resist compressive forces. The goal of the study is to emulate impact survivability afforded by this unconventional design by establishing the mathematical and engineering principles behind observed diving bird morphology. We take inspiration from the musculoskeletal system of the gannets’ necks to examine the effects of muscle connectivity and initial shape on wave propagation in segmented structures. Our study goes beyond previous engineering investigations of water impact that are limited to single segmentation and simple connectivity. We create an experimental setup to systematically evaluate energy distribution with a focus on the initial shape and complex muscle connections. Based on open literature, the findings are the first to show how segmented structures can provide passive control of energy propagation to stabilize structures during impact. Understanding these dynamics allows for engineering of novel multifunctional lightweight structures that passively absorb shock or vibration, allowing maneuverability without compromising performance under compression.

Laser interferometry is a common diagnostic used to measure electron density in plasma experiments. Traditionally, laser interferometers have been employed under the assumption that the scene and reference beams must be equal in length. While this practice maximizes the signal to noise ratio, it provides challenges to experiments requiring multiple laser beams in laboratories with space constraints. Allowing beam paths to be unequal in length would permit increased flexibility in optical setups. In pursuit of this flexibility, some researchers have shown that gas tube laser interferometers with unequal path lengths can produce accurate measurements, provided that the difference in path lengths is equal to some integer multiple of double the cavity length of the gas tube laser. These investigations, however, assumed that the spatial periodicity seen in a homodyne Michelson interferometer configuration will remain constant when employing the same path length differences on a heterodyne Mach-Zehnder interferometer configuration, with which actual plasma density measurements were collected. This work aims to close the gap between proofs of concept and experimental implementations by investigating the signal quality of a Mach-Zehnder heterodyne quadrature helium-neon (HeNe) interferometer over a range of path length differences. Experimental methods and results are given for the benchtop investigation of signal quality. Application of the setup is discussed for measuring plasma density in ZaP-HD, an experimental device at the University of Washington used to demonstrate a sheared-flow-stabilized Z-pinch nuclear fusion space thruster concept.

Controlled fusion would provide clean, abundant energy on Earth and propulsion for space travel. However, we still have much to learn about plasmas, the fusion medium, before we achieve these goals. Simulations play a key role in studying plasmas. Kinetic simulations resolve particles and their collisions individually, so they are computationally expensive. Their alternative, fluid simulations, are less expensive to run  but can't capture as much complexity as kinetic models. This work investigates a hybrid model called Parallel Kinetics Perpendicular Moments (PKPM) that is part of the Princeton code, Gkeyll. PKPM uses kinetic methods parallel to the magnetic field and fluid methods otherwise. Its goal is to get kinetic-like results with lower computational cost. This study investigates how PKPM simulations handle plasma transport compared to fully kinetic simulations. The initial conditions of the two simulation types are identical and consist of an initial sinusoidal perturbation in the temperature of the plasma that is parallel to the magnetic field. The perturbation relaxes over time, leading to a reduction in thermal conductivity. This study compares the reduction in thermal conductivity of the plasma between fully kinetic and PKPM simulations for varying levels of collisionality. The reduction in thermal conductivity is calculated from the change in amplitude of the temperature distribution over time. The PKPM and kinetic results match relatively closely in this case. While more research is needed on how PKPM handles other plasma dynamics, it shows promise as a way to resolve kinetic effects more quickly and with less computational resources.