News & Press Releases

Mechanical Engineering (MNE) Senior Design (Capstone) Presentations April 30, 2024 9:00 a.m. - 4:30 p.m. (Poster and prototype preview begins at 8:00 a.m.) Woodland Commons The Mechanical Engineering Department is proud to share this highly anticipated event with students, faculty, staff, family, friends, and any other interested guests! This is a culmination of the Class of 2024's Senior year team project with industry, or UMD research faculty. Attend all day, or come and go as your schedule allows. For more information please contact Dr. Hamed Samandari/Instructor (hsamandari@umassd.edu) or Sue Cunha/Administrative Assistant (scunha@umassd.edu).

Woodland Commons, UMass Dartmouth Campus

Topic: Multi-phase Algorithm Design for Accurate and Efficient Model Fitting Location: Claire T. Carney Library (LIB), Room 314 Zoom Conference Link: https://umassd.zoom.us/j/98963429286 Meeting ID: 989 6342 9286 Passcode: 283650 Abstract: Recent research applies soft computing techniques to fit software reliability growth models. However, runtime performance and the distribution of the distance from an optimal solution over multiple runs must be explicitly considered to justify the practical utility of these approaches, promote comparison, and support reproducible research. This paper presents a meta-optimization framework to design multi-phase algorithms for this purpose. The approach combines initial parameter estimation techniques from statistical algorithms, the global search properties of soft computing, and the rapid convergence of numerical methods. Designs that exhibit the best balance between runtime performance and accuracy are identified. The approach is illustrated through nonhomogeneous Poisson process and covariate software reliability growth models, including a cross-validation step on data sets not used to identify designs. The results indicate the nonhomogeneous Poisson process model considered is too simple to benefit from soft computing because it incurs additional runtime with no increase in accuracy attained. However, a multi-phase design for the covariate software reliability growth model consisting of the bat algorithm followed by a numerical method achieves better performance and converges consistently, compared to a numerical method only. The implementation of a framework-designed algorithm into a software reliability tool is demonstrated. The proposed approach also supports higher-dimensional covariate software reliability growth model fitting suitable for implementation in further tools. Co-Advisor(s): Dr. Lance Fiondella, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth Committee Members: Dr. Hong Liu, Commonwealth Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Ruolin Zhou, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth NOTE: All ECE Graduate Students are ENCOURAGED to attend. All interested parties are invited to attend. Open to the public. *For further information, please contact Dr. Lance Fiondella via email at lfiondella@umassd.edu

Claire T. Carney Library, Room 314

Interested in studying abroad? Do you have a quick question about the opportunities that are available or the overall process? Stop by the International Programs Office's virtual advising session! Students will be seen on a first come, first served basis. Email intl_programs@umassd.edu for the zoom link.

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Topic: 3D Hydrodynamical Simulations of Merging One-CO White Dwarf Binaries Location: SENG 201 Abstract: In 1181, "a guest star", as bright as the planet Saturn was observed in the sky by Chinese and Japanese astronomers. A recent study has identified the star IRAS 00500 + 6713 as the remnant from the 1181 event, surrounded by the nebula "PA 30" and pointing to an unusual scenario where the explosion could have been caused by the merger of two white dwarfs. In this thesis, I will present a 3D hydrodynamical simulation model for SNe Iax in the context of the double-degenerate channel of merging ONe- CO white dwarf binary using the adaptive mesh refinement hydrodynamics code FLASH. I will discuss the explosion mechanism, the characteristics of the remnant, and other implications of this model. ADVISOR(s): Dr. Robert Fisher, Department of Physics (rfisher1@umassd.edu) COMMITTEE MEMBERS: Dr. Jay Wang, Department of Physics Dr. David Kagan, Department of Physics NOTE: All PHY Graduate Students are ENCOURAGED to attend.

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Topic: Assessing the Dynamically Driven Double-Degenerate Double-Detonation (D6) Progenitor Model for Type Ia Supernovae: A Comparison of Dynamic and Adaptive Mesh Simulations Location: SENG 201 Abstract: Type Ia supernovae (SNe Ia) play a crucial role in deciphering cosmological phenomena, including the accelerated expansion of the universe. Despite their significance, the driving mechanisms behind SNe Ia are yet to be fully confirmed. The dynamically driven double-degenerate double-detonation (D6) scenario has gained traction as the most likely explanation for nine hypervelocity galactic white dwarfs discovered by the ESA Gaia space mission. In this thesis, I will present a comparative analysis of hydrodynamical simulations of D6 SNe Ia using two leading hydrodynamical simulation frameworks: AREPO, which utilizes an unstructured, Voronoi tessellation dynamic moving mesh, and FLASH, with its structured adaptive Eulerian mesh. I will briefly describe the impact of our findings on the physical processes which give rise to SNe Ia. ADVISOR(s): Dr. Robert Fisher, Department of Physics (rfisher1@umassd.edu) COMMITTEE MEMBERS: Dr. Jay Wang, Department of Physics Dr. David Kagan, Department of Physics NOTE: All PHY Graduate Students are ENCOURAGED to attend.

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Topic: Study of Interplanetary Optimization between Earth and Mars Location: SENG -201 Abstract: Astrodynamics-based trajectory planning, and optimization are vital in deep space exploration mission design. Interplanetary Trajectories are the orbital paths that a spacecraft takes between a starting and destination celestial body at a certain point in time. Maximum final mass and minimal travel time are two primary parameters that are always targeted to be optimized in Interplanetary trajectory. We focused on the time aspect in our study as it is very crucial when planning any interplanetary space trip. The track between Earth and Mars from 2020 to 2050 is shown using a trajectory optimization tool. The trajectory optimization tool is based on a genetic algorithm and determines trajectories using a patched conics approximation. Time of Flight (TOF), Departure C3 energy, Arrival Velocity, and the orbital elements of the proposed orbit are the tool's output parameters. To select an orbit for Earth to Mars, we focused on getting TOF, C3 Energy, and arrival velocity in the acceptable range. Further, we utilized two open-source libraries, Pykep and PyGMO, to validate the findings achieved using the optimization tool. The outcomes were the journey time, Arrival Vinf, Departure Vinf and Insertion DV. The two approaches were evaluated in terms of trajectory view and travel time. Between the two methods, there is a significant difference in travel duration observed. The best ideal year between 2020 and 2050 will be chosen after comparing the results of the trajectory plotted and TOF obtained from the optimization tool and Pykep library used. Advisor(s): Dr. Sarah Caudill, Physics Department (scaudill@umassd.edu) NOTE: All PHY Graduate Students are ENCOURAGED to attend. Open to the public. All interested parties are invited to attend.

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