Intercampus Marine Science Graduate Program

EAS Doctoral Dissertation Defense by Soolmaz Khoshkalam Date: Friday,December 13, 2024 Time: 9:00 a.m. Topic: Potential of Mean Force-Based Lattice Element: Extension to Dynamic and Nonlinear Analysis of Structures Location: LIB 314 Abstract: The potential-of-mean-force (PMF) approach to the lattice element method (LEM) has recently been adapted to model the response of structural systems. LEM relies on lattice discretization of the domain via a set of particles that interact through prescribed potential functions, representing the mechanical properties of members. The approach offers unique advantages, including robustness to discontinuity and failure without the need for mesh refinement. The overall goal of this research is two-fold: (i) extend the quasi-static PMF-based LEM to model the dynamic behavior of structures (ii) blend the quasi-static PMF-based LEM with Force Analogy method for nonlinear analysis. Such developments provide a means for simulating nonlinear response and failure under dynamic loading that is the nature of most natural hazards and extreme conditions. To accomplish the first goal, integration methods from Molecular Dynamics (MD) are used to estimate of the trajectory of particles in the Lattice Element Method (LEM) and to simulate the dynamic response with a focus on structural (or building) systems. More specifically Verlet-Velocity method is used to estimate the location and momentum of each particle at every time step. To assure accuracy and the numerical stability, we also explore implicit integration techniques such as Hilber-Hughes-Taylor method and midpoint method. Noting that the rotational degrees of freedom have minimal contribution to the kinetic energy of the system we develop an energy-based approach for condensation to reduce the computational cost. Our approach relies on the Euler-Lagrange equations and manifests itself in the form of minimum potential energy theorem for mass-less degrees of freedom. To address another critical aspect of dynamic simulation, the mass matrix, we adopt an energy-based approach and utilize the kinetic energy of the lattice elements to maintain consistency with the kinetic energy of their continuous counterparts. To achieve the second goal, we incorporate the nonlinear behavior of materials under various actions, including bending, torsion, and axial forces, through the introduction of novel potential functions inspired by the Force Analogy Method. These potential functions are calibrated using section properties that represent the nonlinear stress-strain responses of materials, such as nonlinear moment-curvature relationships. The utility of the proposed framework and its and accuracy are validated through its application in quasi-static linear and nonlinear simulations of large-scale buildings subjected to different loading conditions. ADVISOR(S): Dr. Mazdak Tootkaboni, Dept of Civil and Environmental Engineering (Advisor) (mtootkaboni@umassd.edu) Dr. Arghavan Louhghalam, Dept. of Civil and Environmental Engineering (Co-Advisor) (Arghavan_Louhghalam@uml.edu) COMMITTEE MEMBERS: Dr. Alfa Heryudono, Department of Mathematics and Dr. Zheng Chen, Department of Mathematics NOTE: All EAS Students are ENCOURAGED to attend.

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EAS Doctoral Proposal Defense by Zhuoyuan Leng Date: Tuesday, December 17, 2024 Time: 10:00am Topic: Experimental and Numerical Studies on Mixed-mode Fracture of Additively Manufactured Polymer Nanocomposites Location: LIB 314 Zoom Link: https://umassd.zoom.us/j/92967323046?pwd=ppH0sI5z79H46F0rQhSkb2S4Y16mlA.1 Abstract: This study investigates the mixed-mode fracture behavior of ABS nanocomposites fabricated using fused deposition modeling (FDM) for automotive and aerospace applications. The scope includes quasi-static and dynamic mixed-mode fracture scenarios, and cyclic mixed-mode fatigue fracture properties, using experimental and numerical methods, focusing on understanding crack dynamics and enhancing the fracture toughness of ABS composites. It explores fracture criteria under mixed mode loading conditions and assesses the influence of printing direction, loading type, and nanoparticle weight percentage. The experimental methodology is divided into three parts: (1) quasi-static mixed-mode loading of ABS nanocomposites with different printing directions, (2) dynamic mixed-mode loading using a modified Hopkinson pressure bar setup, and (3) cyclic fatigue loading to assess fatigue fracture performance. Scanning electron microscopy (SEM) will be used to analyze fracture surfaces and correlate them to fracture mechanisms under various mode-mixities and loading conditions. Simulation studies focus on crack dynamics using the phase-field method (PF) implemented in COMSOL, with anisotropic material formulations to model different printing directions and dynamic loading scenarios. Comparisons between simulations and experiments will enhance the understanding of fracture mechanisms. The outcome can be used to optimize ABS nanocomposite performance and provide insights for structural applications. ADVISOR(S): Dr. Vijaya Chalivendra, Department of Mechanical Engineering (vchalivendra@umassd.edu) COMMITTEE MEMBERS: Dr. Caiwei Shen, Department of Mechanical Engineering Dr. Jay Wang, Department of Physics Dr. Jun Li, Research Associate Professor, ERAU NOTE: All EAS Students are ENCOURAGED to attend.

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Observatory Open House No moon - lots of planets, Orion Nebula, etc.

Hirshfeld Dowd Observatory

Department of Fisheries Oceanography "Modeling Index Selectivity for Fishery Stock Assessments" By: Cole Carrano Advisor Steven X. Cadrin (University of Massachusetts Dartmouth) Committee Members Pingguo He (University of Massachusetts Dartmouth), Gavin Fay (University of Massachusetts Dartmouth), Lisa Kerr (University of Maine) Monday January 6th, 2025 10:00 AM SMAST East 101-103 836 S. Rodney French Blvd, New Bedford and via Zoom Abstract: Abundance indices are crucial components of fishery stock assessments because they provide a time series of relative abundance for estimating absolute stock size, derived from the response of relative indices to the absolute magnitude of fishery removals. Selectivity is the relative vulnerability to a fishery or fishery-independent survey for each species or demographic group within a species (e.g., size or age class). In an age-based assessment model, selectivity parameters are needed to relate observed stock indices to model estimates of abundance at age. Thus, selectivity estimates must be carefully modeled to ensure an accurate depiction of the stock's age structure. The objectives of this research are to improve the accuracy and utilization of indices in fisheries stock assessment models by understanding the effect of alternative approaches to estimating index selectivity. Chapter One provides a general introduction to the topic and a review of the relevant literature. Chapter Two involves splitting a fishery-independent survey into two series to account for vessel and methodological changes by estimating distinct catchability and selectivity parameters for each series. Results indicated improvement in model performance for stocks with sufficient contrast in the new index, and no improvement for stocks with limited years of data or contrast in the recent indices. Chapter Three develops fleet-structured assessment models to improve selectivity estimates for fishery and the fishery-dependent indices. Splitting catch into fleets improves selectivity estimates for respective CPUE indices, but robust catch-at-age data is desirable for fleets that make up a large portion of the total catch. Chapter Four involves simulation cross-testing as a method to evaluate performance of assessments that assume a single index series that is calibrated for changes in survey technology vs. assuming separate indices in stock assessment models. Results from this chapter suggest that the consequences of assuming a split when there truly wasn't one were not severe, but that assuming there wasn't a split when there truly was one can produce significant biases in model results This work examines how decisions about modeling fleet structure or changes in survey systems affect the performance of an assessment model and how sensitive models are to these decisions. This research will emphasize the importance of selectivity estimates to stock assessment and advance our understanding of how to effectively utilize abundance indices in an assessment model. ************ Join Zoom Meeting https://umassd.zoom.us/j/94890073016 Note: Meeting passcode required, email contact below to receive ************** To request the Zoom passcode or for any other questions, please email Callie Rumbut at c.rumbut@umassd.edu

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Department of Fisheries Oceanography "Application of optical and acoustic technologies to improve the understanding of fish behavior, ecology, and stock assessment." By: Christopher Rillahan Advisor: Dr. Pingguo He Committee Members Dr. Kevin D. E. Stokesbury, Dr. Steven X. Cadrin, Dr. Theodore Castro-Santos, and Dr. Kresimir Williams Tuesday January 7th, 2025 11:00 AM SMAST West 204 706 S. Rodney French Blvd, New Bedford and via Zoom Abstract: Marine species inhabit an extensive underwater environment that is largely inaccessible to humans. Consequently, we have relied on various technologies to study and manage the commercial and recreational species we depend on. Over the past century, there have been rapid advancements in optical and acoustic technology, which have coincided with an increased need for effective fisheries management. The ability to observe fish during the capture process has shed light on the role of fish behavior and the potential bias it introduces into fisheries data. Due to insufficient knowledge of most systems, scientific surveys and stock assessment models have traditionally relied on simplified assumptions about fish behavior. While it has been understood that fish have well-developed sensory systems, mobility, and complex life histories, the lack of information has limited their use in gear catchability, survey design, and assumptions about spatial and temporal population dynamics. This dissertation examines the use of optical and acoustic technology to address these limitations, improving the interpretative power of survey data and reducing potential bias. Baited remote underwater video systems (BRUVS) were employed in Chapter II to examine the role of a species' life history in the performance of traditional survey gears (e.g., fish pots and demersal otter trawls). The spatial distribution of black sea bass (Centropristis striata), a structure-oriented species, in Buzzards Bay was observed to vary depending on the survey gear. Conversely, scup (Stenotomus chrysops), a habitat-agnostic species, exhibited similar patterns across survey methods. Video observations of black sea bass documented an increasing affinity for structured habitats during the summer and fall. This shift in the spatial distribution of black sea bass dramatically affected the trawl survey data. Catch data from the spring trawl survey generally corresponded to the video and pot data with respect to the spatial distribution and population structure of both black sea bass and scup. Conversely, the fall trawl survey data starkly contrasted with the two other surveys, with few adult black sea bass catches. The lack of catch is presumably due to the shifting residence of black sea bass to rocky habitats, which are not sampled by the trawl and, therefore, unavailable to the survey. The shifting availability between the spring and fall trawl surveys presents an inaccurate picture of black sea bass abundance in Buzzards Bay....... ************ Join Zoom Meeting https://umassd.zoom.us/j/91787205979 Note: Meeting passcode required, email contact below to receive ************** To request the full abstract, Zoom passcode, or for any other questions, please email Callie Rumbut at c.rumbut@umassd.edu

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