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Wall temperature and high enthalpy effects on hypersonic boundary layer stability and transition
No full textKuehl, Joseph J.The hypersonic boundary layer transition study is crucial for controlled and sustainable flight. Although crucial, the mechanisms underlying the transition are still poorly understood, even in a low-noise environment. Understanding of these extreme environment flow phenomena can lead to significant advances in aerospace flight technologies. Different modes of disturbances present in the hypersonic boundary layer undergo modal growth eventually leading to turbulence. ☐ The objective of this dissertation is to understand the dynamics of modes and their interactions due to wall temperature and high-enthalpy effects on hypersonic boundary layer transition. This research study utilizes computational fluid dynamics (CFD) as well as stability analysis tools such as linear stability theory (LST), linear parabolized stability equations (PSE), and non-linear parabolized stability equations (NPSE). This research combines theoretical understanding of first and second-mode instability with practical application to predict and mitigate turbulent transition in hypersonic boundary layers. The mean flow Lagrangian invariants are introduced to relate it with obliqueness of the first-mode instability. The effects of stream-wise thermal gradients on the growth of second-mode instability are investigated. The computational results for the pattern wall temperature study are compared with experiments conducted in the AFOSR–Notre Dame Large Mach-6 Quiet Tunnel at the University of Notre Dame and show good consistency. The wall thermal configurations proposed in this study significantly delay the laminar-to-turbulent transition that arises due to second-mode instabilities. In addition to that, this research presents unique wall thermal patterns that do not affect the growth of second-mode instabilities. The computational results for high-enthalpy studies are compared with other numerical codes. The sensitivity of high-enthalpy hypersonic boundary layer flows to non-linearity is investigated. A 1D-CNN machine learning model was proposed to predict the critical N-factor. This data-driven model presented in this dissertation is the one that can be used as a preliminary assessment to predict the transition rapidly with minimal computational effort.University of Delaware, Department of Mechanical EngineeringPh.D
DATA FROM: MICROPLASTIC ACCUMULATION AND VERTICAL DISTRIBUTION IN THE DELAWARE ESTUARY ESTUARINE TURBIDITY MAXIMUM
No full text“StationLocationandTime_Figure1_data.csv” is a .csv file containing sampling date, station name, longitude, latitude, net number, net depth category, and time of sampling. These data are presented in Figure 1 of the associated paper.
“ParticleConcentrationsbyType_Figure2_data.csv” is a .csv file containing sampling date, station, net number (1=surface, 2=middle, 3=deep), particle type (fragment, fiber, bead), total particle count, total inorganic particle count, total plastic particle count, and net sample volume (m^3). These data are presented in Figure 2 of the associated paper.
“FTIRPolymerDataandSize_Figure6_7_8_9_data.csv” is a .csv file containing sampling date, station, net number (1=surface, 2=middle, 3=deep), size fraction, particle type, particle ID (an internal record keeping number for each particle), search score (0-1 scale), polymer identification, plastic (yes/no), particle length (microns), particle area (mm^2). These data are presented in Figures 6 - 9 of the associated paper.We sampled microplastics at three depths in the estuarine turbidity maximum region of the Delaware Estuary using an open/close Tucker Trawl net system. Microparticles were isolated and confirmed as microplastic by micro-FTIR spectroscopy. For more details on sampling and instrumentation, see the paper associated with this dataset: Fontana et al. (2026) Marine Pollution Bulletin ##:###-###.This work was supported in part by grants from the National Oceanic and Atmospheric Administration Marine Debris Program (grant numbers NA21NOS9990110, NA19NOS9990084) and the Delaware Sea Grant College Program (R/HCE-31, R/RCE-36)
Two case studies monitoring the soil health of aged biochar installations in Maryland's urban & roadside soils
No full textImhoff, Paul T.The application of biochar to urban and roadside soils has shown to improve stormwater runoff capture and sorb pollutants from adjacent impervious surfaces. Due to different methods of biochar production, via pyrolysis, and different feedstocks, the physical and chemical properties of produced biochar are likely to be different. Thus it’s vital for road engineers and administrators to understand and predict the effect of biochar when incorporated into to the soil. ☐ Comparing the effects of a commercial biochar with two kiln-produced biochars made from locally sourced materials (invasive plants) on soils treating stormwater runoff showed the two kiln-produced biochars had overall performance similar to that of the commercially produced biochar at the Howard Community College site: penetration resistance in the native compacted soil decreased, and infiltration rates and water retention increased. Commercial biochar showed greater improvements in soil penetration resistance and infiltration rates, with effects that were more consistent in space and over time. The variable particle size of the kiln-produced biochar was likely influential in the results. ☐ Biochar was amended to a sodic soil along an I-95 exit ramp that initially showed hydraulic improvement 5 months after biochar installation but a dramatic decrease in hydraulic function when the soil aged > 12 months. The addition of biochar had no long-term positive on penetration resistance, vegetation growth, or water infiltration. The combination of the site’s mineralogy and accumulation of sodium in the soil via runoff from road salt application over-powered any amelioration of the biochar application.University of Delware, Department of Civil, Construction and Environmental EngineeringM.A.S
A multi-scale numerical study on coastal hydrodynamics, sediment transport, and morphodynamics
No full textHsu, Tian-JianThis dissertation reports studies that advance the scientific understanding of coastal processes by elucidating the coupled dynamics among waves, flows, sediment transport, and morphodynamics across multiple spatiotemporal scales in the coastal environments. Utilizing high-fidelity computational fluid dynamics (CFD) with process-based morphodynamic models, this multi-scale numerical investigation spans three representative scales of coastal dynamics: (1) fine-scale sand particle sorting driven by grain-turbulence interactions, (2) small-scale wave-driven sand ripple evolution and the mobility of underwater munitions, and (3) intermediate-scale storm-induced cross-shore beach profile changes. By integrating insights across these scales, the dissertation seeks to reveal the fundamental coastal processes and underlying physical mechanisms observed in laboratory and field settings. ☐ At the fine scale, simulations using an Eulerian-Lagrangian two-phase model, CFD-DEM, investigate the vertical sorting of polydispersed native sand and denser nonnative particles (e.g., olivine for coastal carbon removal) under oscillatory sheet-flow conditions. Results show that competing upward and downward migration mechanisms control nonnative particle fate, offering insights for deploying the optimum size of nonnative particles that can stay in the active layer to maximize their weathering and carbon capture. ☐ At the small scale, large-eddy simulations (LES) using SedFoam, an Eulerian two-phase model, resolve turbulent coherent structures (TCS) that drive sub-orbital ripple formation from an initially flat sand bed under oscillatory flow. The results demonstrate that TCS are the dominant mechanism initiating the formation of three-dimensional (3D) bed features. At a later stage, when ripples grow sufficiently larger than the integral length scale of turbulence, the wave orbital motion takes over and becomes the dominating driver for the subsequent ripple evolution to equilibrium. These findings elucidate the fundamental coupling between TCS evolution and sediment transport during ripple development. Furthermore, by extending SedFoam to incorporate six-degree-of-freedom for object motion with complete flow-sediment-object interaction coupling, the new model was validated to simulate the onset motion behavior of underwater munitions. The simulation reveals that hydrodynamic forcing and object properties, such as object density, size, and initial burial depth, jointly influence the motion behavior of small objects driven by oscillatory flows. ☐ At the intermediate scale, cross-shore hydrodynamics and morphodynamics in the surf zone are first investigated using the process-based model XBeach-Surfbeat (XB-SB) and large-wave flume data for an erosive event. Simulations of storm-induced berm erosion, sediment transport, and sandbar formation reveal that default model settings overpredict undertow, leading to excessive berm erosion. Systematic calibration produces optimized coefficients that improve morphodynamic predictions based on a well-calibrated undertow. Extending this work to field conditions, XB-SB is applied to two 2023 experiments at the Field Research Facility in Duck, North Carolina, representing an accretive (March 2023) and an erosive event (November 2023). Results indicate that adjusting existing model parameters alone cannot achieve consistent agreement across the shoreline and sandbar regions, highlighting the need to incorporate geotechnical properties into morphodynamic models to represent increased sediment strength in the intertidal zone and to stabilize the foreshore under energetic wave conditions. ☐ Collectively, the findings of this dissertation establish a coherent linkage of physical processes across scales, demonstrating that integrating multi-scale insights yields a more unified understanding of coupled coastal dynamics and enhances the predictive capability of reduced-complexity models.University of Delaware, Department of Civil, Construction and Environmental EngineeringPh.D
Your media diet is impacting your actual diet: The effects of influencer “What I Eat in a Day” YouTube videos on influencer perceptions and nutrition behaviors
No full textThis article was originally published in Digital Health. The version of record is available at: https://doi.org/10.1177/20552076261416379
© The Author(s) 2026
This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).Objective Social media influencers frequently post “What I Eat in a Day” (WIEIAD) vlogs, shaping dietary perceptions and behaviors among young audiences. There is concern that these videos contribute to negative outcomes, such as disordered eating and unhealthy social comparisons. While prior research largely focuses on the effects of short-form content (e.g., from TikTok), this study examines the impact of long-form WIEIAD videos on perceptions about the content creators and nutrition-related behaviors, and measures behavior by asking participants to select an apple or cookie after watching a WIEIAD video.
Methods Using a 2 × 2 experimental design (N = 289), participants viewed WIEIAD YouTube videos varying in the presence and absence of sponsorship (i.e., either a service or product) and physical health benefits of the diet.
Results Results indicate that sponsorship increased perceptions of influencer trustworthiness and attractiveness but decreased authenticity and parasocial interaction. Additionally, exposure to sponsored content increased the likelihood of selecting a cookie, supporting media priming effects in nutrition behavior. However, disclosure of physical health benefits did not influence snack choice. There was also a relationship between intentions to change diet and opting out of the snack.
Conclusions These findings raise important considerations for digital health communication, influencer regulation, and content literacy interventions aimed at mitigating the negative health effects of social comparison and commercial nutrition messaging online.The authors received no financial support for the research, authorship, and/or publication of this article
A Global Ensemble Forecast System (GEFS)-based synthetic event set of U.S. tornado outbreaks
No full textThis article was originally published in Natural Hazards and Earth System Sciences (NHESS). The version of record is available at:https://doi.org/10.5194/nhess-26-433-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License. https://creativecommons.org/licenses/by/4.0/Severe convective storms (SCS) are important drivers of global insured losses, and tornado outbreaks – when many tornadoes occur within a short time span – cause extreme and localized loss of life and property. Tornado outbreak risk estimates from observations, either storm reports or reanalysis environments, are limited by meteorological conditions that have occurred in the historical period. A standard approach of addressing this inadequacy is to construct synthetic event sets that consist of unrealized but plausible events that better represent the full range of possible outcomes. In this study, we constructed and evaluated a synthetic event set of U.S. tornado outbreaks using Global Ensemble Forecast System (GEFS) environments and a tornado outbreak index. With over 800 000 daily maps of environments, over 200 000 synthetic events are generated. In a seamless framework, the synthetic event set includes “daughter events”, constructed from short-lead forecasts and resemble historical events, as well as independent physically plausible events, constructed from longer-lead forecasts. With the GEFS synthetic event set, we estimated that the 1-in-100-year and 1-in-1000-year U.S. tornado outbreak event has 150–250 and 275–400 (F/EF1+) tornadoes per day, respectively. The GEFS synthetic event set also shows robust shifts related to ENSO – higher outbreak activity during La Niña conditions – and trends – increased outbreak activity during 2010–2019 compared to 2000–2009 – consistent with reports. We also developed a subsampling procedure to estimate locally specific tornado outbreak risk, which we illustrate by generating return level curves for grid cells that cover Dallas, Nashville, and Chicago.The authors acknowledge the support of this research by the Willis Research Network (grant no. WILLIS CU15-2366) and NOAA (grant no. NA19OAR4590159). The authors also would like to thank the two anonymous reviewers for their insightful comments
Ecoomic Impact Studies
No full textThe Center for Applied Demography & Survey Research at the University of Delaware conducted this research to measure the economic impact of Delaware’s Brownfield Development Program (BDP).
Delaware defines brownfields as “any vacant, abandoned or underutilized real property the development or redevelopment of which is hindered by the reasonably held belief that the real property may be environmentally contaminated.” The BDP encourages the remediation and private development on these sites with the assistance of the state. This study looks at 3 economic indicators: the value of the land and improvements to the brownfield site as judged by the assessed value, the amount of assessment taxes that were received from sites, and the employment and associated wages and tax revenues at the sites. We compare those to when the site was either certified or when remediation was complete. Economic modeling estimates the impacts of added employment, as more employment induces other employment and services within the state. A section discussing specific sites describes what is expected in the future.The Delaware Department of Natural Resources and Environmental Contro
Construction of Peptide Amphiphile-Coated Coacervates with Selective Permeability
No full textThis article was originally published in ACS Biomaterials Science & Engineering. The version of record is available at: https://doi.org/10.1021/acsbiomaterials.5c02101
This publication is licensed under
CC-BY 4.0 https://creativecommons.org/licenses/by/4.0/
© 2026 The Authors. Published by American Chemical SocietyThe combination of membranes with coacervates has been regarded as an effective approach to stabilize coacervates and modify their surface properties. Here, we achieved the construction of a functional coacervate system by localizing nanovesicles assembled by elastin-like peptide-block-collagen-like peptides (ELP-CLPs) on the surface of polyelectrolyte coacervates. The formation of the ELP-CLP coating was driven by electrostatic interactions between negatively charged ELP-CLP vesicles and positively charged coacervates. Altering the surface charge of ELP-CLP vesicles or coacervates disrupted the formation of coatings, and the formulation parameters, such as different mixing protocols and the order of adding the components, could be used to control the coating process. The ELP-CLP vesicle coating successfully functionalized the coacervates and presented the ability to control the diffusion of molecules based on their different molecular weights. Our results demonstrated approaches to control the coating process and coating functionality of ELP-CLP vesicle coatings and highlighted their potential application as a novel surface modification to provide selective permeability to current coacervate systems.The research was partially supported by the National Science Foundation (grant number EF-1935049) and through the University of Delaware CHARM Materials Research Science and Engineering Center (DMR-2011824). Additional partial support for the reported studies was also provided by NSF (CBET-2023668). Microscopy equipment employed in the studies was acquired with shared instrumentation grants (S10 RR027273 and S10 OD016361), and access was supported by the NIH-NIGMS (P20 GM103446), the NIGMS (P20 GM139760), and the State of Delaware. Data storage was supported by the University of Delaware Center for Bioinformatics, and Computational Biology Core Facility [RRID: SCR_017696] was made possible by support from an NIH Shared Instrumentation Grant (NIH S10OD028725), Delaware INBRE (NIH P20GM103446), and the Delaware Biotechnology Institute. The views expressed here are the responsibility of the authors and do not necessarily reflect the position of the funding agencies
Mitigating product abuse through privacy-preserving and secure technologies in digital and industrial systems
No full textWang, HainingThe rapid digitalization of modern life has enabled unprecedented convenience and efficiency while simultaneously creating new opportunities for exploitation, misuse, and privacy violations. This dissertation investigates product abuse (the intentional misuse or manipulation of technological systems beyond their intended design) across distinct digital domains to surface its security, privacy, and operational implications. Using real world datasets, deployed prototypes, and empirical vulnerability assessments, it provides a cross domain examination of how abuse emerges and how defenses succeed or fail in practice. ☐ Case Study 1 (Email Tracking) analyzes how embedded tracking beacons in email communication can be repurposed as tools for covert surveillance and behavioral profiling. Through large scale measurement and analysis, the study exposes the privacy risks posed by such mechanisms, highlighting how legitimate business tools can cross the boundary into privacy abuse. ☐ Case Study 2 (CAPTCHA) surveys 24,000+ web pages from the Alexa Top 50K and correlates implementation patterns with 179 MITRE CVEs (2005–2025). The study finds that most failures stem from implementation errors, weak server-side validation, and supply chain issues, not the intrinsic design of challenges and documents how AI assisted solvers & paid solving economies further erode resilience, with practical hardening recommendations. ☐ Case Study 3 (Industrial IoT / WMS) examines abuse in industrial environments integrating Decision Support Systems, IoT devices, and Warehouse Management Systems. Drawing on a deployed prototype and operational data, it identifies attack surfaces that enable product manipulation, data leakage, and supply chain interference, and proposes blockchain backed audit trails, stronger authentication, and anomaly detection to enhance cyber resilience. ☐ Case Study 4 (Automated Crypto Trading) evaluates Mean Reversion, Arbitrage, Grid Trading, and Mean Deviation strategies as both efficiency enablers and abuse vectors. Experiments highlight how automation, if poorly designed or exploited, can induce market manipulation and systemic instability, motivating transparency, guardrails, and regulation aware algorithmic design. ☐ The dissertation (i) consolidates empirical evidence that product abuse recurs across heterogeneous systems; (ii) maps dominant failure modes from client-side exposure and automation to server-side validation gaps and supply chain weaknesses; (iii) demonstrates deployable countermeasures, privacy preserving email defenses, CAPTCHA hardening practices, IIoT/WMS auditability and access control, and ethics \& compliance aware algorithm design; and (iv) offers a practical threat informed rubric for engineering teams to anticipate misuse, not merely react to incidents. ☐ In conclusion, this dissertation offers both diagnostic and prescriptive perspectives on digital product abuse. It establishes that while product abuse cannot be fully eliminated, it can be systematically reduced through better architecture, stronger accountability, and adaptive security mechanisms that evolve alongside technological progress. By capturing the interplay between innovation, exploitation, and defense, this work contributes to the ongoing discourse on building secure, privacy preserving, and trustworthy digital ecosystems.University of Delaware, Department of Electrical and Computer EngineeringPh.D
Evaluation of source water contribution to tidal marshland using stable isotopes (²H, ¹⁸O, ¹⁷O) of water
No full textJin, YanSea-level rise is increasing saltwater intrusion into coastal marshes, altering porewater chemistry and threatening ecosystem functions such as nutrient cycling and carbon storage. Bulk salinity tracers (e.g., EC, Cl⁻) capture tidal mixing but struggle to distinguish precipitation inputs and evaporative enrichment. This study investigates whether stable water isotopes (δ²H, δ¹⁸O, δ¹⁷O) paired with end-member mixing analysis (EMMA) provide finer resolution of water sources and their biogeochemical impact than salinity alone. Porewater was sampled along a forest-to-channel transect across depths, seasons, and spring/neap tides. This work analyzed isotopes, EC, redox (Eh), and major ions, and compared simple two-endmember models with end-member mixing analysis (EMMA) using (a) isotopes only and (b) isotopes+EC, and the calculation of an Evaporative Enrichment Index (EEI). Direct comparison of isotope- and EC-based models revealed strong agreement at intermediate seawater fractions but divergence in interior zones. The isotope-only EMMA retained clear seasonal and tidal variability tied to recharge and evaporation, while the isotope + EC EMMA collapsed to a conservative, salinity-dominated axis. Incorporating an Evaporative Enrichment Index (EEI) corrected EC-derived estimates by isolating isotopic enrichment from evaporation and transpiration, producing a process-aware mixing framework. Spatial and chemical patterns aligned with marsh zonation: near-channel sites showed rapid flushing and redox oscillation; the transition zone exhibited prolonged residence, evaporative enrichment, and mobilization of Fe, Mn, and P. Isotope and salinity-informed models capture complementary process signals and not interchangeable estimates. Integrating isotopic corrections such as EEI enhances salinity-based models, providing a mechanistic framework for predicting how hydrologic and redox gradients reorganize as marsh zones compress under rising sea levels.University of Delaware, Department of Plant and Soil SciencesM.S