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Articles 1 - 3 of 3
Full-Text Articles in Physics
Analyzing The Effects Of Ultrafast Laser Processing On Mechanical Properties Of 3d-Printed Pla Parts, Darshan Pramodbhai Yadav
Analyzing The Effects Of Ultrafast Laser Processing On Mechanical Properties Of 3d-Printed Pla Parts, Darshan Pramodbhai Yadav
Theses and Dissertations
Recent advances in additive manufacturing technologies have already led to wide-scale adoption of 3D-printed parts in various industries. The expansion in choice of materials that can be processed, particularly using Fused Deposition Modeling (FDM), and the steady advancements in dimensional accuracy control have extended the range of applications far beyond rapid prototyping. However, additive manufacturing still has considerable limitations compared to traditional and subtractive manufacturing processes. This work addresses limitations associated with the as-deposited surface roughness of 3D-printed parts. The effects of roughness-induced stress concentrations were studied on ultimate tensile strength and fatigue life. The samples were manufactured using a …
Quantifying Temperature-, Pressure-, And Nuclear Quantum Effects On Hydrophobic And Hydrophilic Water-Mediated Interactions, Justin T. Engstler
Quantifying Temperature-, Pressure-, And Nuclear Quantum Effects On Hydrophobic And Hydrophilic Water-Mediated Interactions, Justin T. Engstler
Dissertations, Theses, and Capstone Projects
Water-mediated interactions (WMIs) are responsible for diverse processes in aqueous solutions, including protein folding and nanoparticle aggregation. WMI may be affected by changes in temperature and pressure, and hence, they can alter chemical/physical processes that occur in aqueous environments. Traditionally, attention has been focused on hydrophobic interactions while, in comparison, the role of hydrophilic and hybrid (hydrophobic–hydrophilic) interactions have been mostly overlooked. Here, we study the role of T and P on the WMI between nanoscale (i) hydrophobic–hydrophobic, (ii) hydrophilic–hydrophilic, and (iii) hydrophilic–hydrophobic pairs of (hydroxylated/non-hydroxylated) graphene-based surfaces. We find that hydrophobic, hydrophilic, and hybrid interactions are all sensitive to …
Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin
All Dissertations
Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …