Comparison of wind turbine tower failure modes under seismic and wind loads

This paper studies the structural responses and failure modes of a 1.5-MW horizontal-axis wind turbine under strong ground motions and wind loading. Ground motions were selected and scaled to match the two design response spectra given by the seismic code, and wind loads were generated considering tropical cyclone scenarios. Nonlinear dynamic time-history analyses were conducted and structural performances under wind loads as well as short- and long-period ground motions compared. The results show that under strong wind loads the collapse of the wind turbine tower is driven by the formation of a plastic hinge at the lower section of the tower. This area is also critical when the tower is subject to most ground motions. However, some short-period earthquakes trigger the collapse of the middle and upper parts of the tower due to the increased contribution of high-order vibration modes. Although long-period ground motions tend to result in greater structural responses, short-period earthquakes may cause brittle failure modes in which the full plastic hinge develops quickly in regions of the tower with only a moderate energy dissipation capacity. Based on these results, recommendations for future turbine designs are proposed

3D-BEVIS: Bird's-Eye-View Instance Segmentation

Recent deep learning models achieve impressive results on 3D scene analysis tasks by operating directly on unstructured point clouds. A lot of progress was made in the field of object classification and semantic segmentation. However, the task of instance segmentation is less explored. In this work, we present 3D-BEVIS, a deep learning framework for 3D semantic instance segmentation on point clouds. Following the idea of previous proposal-free instance segmentation approaches, our model learns a feature embedding and groups the obtained feature space into semantic instances. Current point-based methods scale linearly with the number of points by processing local sub-parts of a scene individually. However, to perform instance segmentation by clustering, globally consistent features are required. Therefore, we propose to combine local point geometry with global context information from an intermediate bird's-eye view representation.Comment: camera-ready version for GCPR '1

Sustainable Campus Community Engagement

Laser metal deposition (LMD) was applied to deposit Inconel 718 metal matrix composites reinforced with TiC particles. The influence of laser energy input per unit length on constitution phases, microstructures, hardness, and wear performance of LMD-processed TiC/Inconel 718 composites was studied. It revealed that the LMD-processed composites consisted of γ Ni-Cr solid solution matrix, the intermetallic precipitation phase γ′, and the TiC reinforcing phase. For the laser energy input per unit length of 80-120 kJ/m, a coherent interfacial layer with the thickness of 0.8-1.4 μm was formed between TiC reinforcing particles and the matrix, which was identified as (Ti,M)C (M=Nb and Mo) layer. Its formation was due to the reaction of the strong carbide-forming elements Nb and Mo of the matrix with the dissolved Ti and C on the surface of TiC particles. The microstructures of the TiC reinforcing phase experienced a successive change as laser energy input per unit length increased: Relatively coarsened poly-angular particles (80 kJ/m) - surface melted, smoothened TiC particles (≥100 kJ/m) - fully melted/precipitated, significantly refined TiC dendrites/particles (160 kJ/m). Using the laser energy input per unit length ≥100 kJ/m produced the fully dense composites having the uniformly dispersed TiC reinforcing particles. Either the formation of reinforcement/matrix interfacial layer or the refinement in TiC dendrites/particles microstructures enhanced the microhardness and wear performance of TiC/Inconel 718 composites

High energy neutrinos from magnetars

Magnetars can accelerate cosmic rays to high energies through the unipolar effect, and are also copious soft photon emitters. We show that young, fast-rotating magnetars whose spin and magnetic moment point in opposite directions emit high energy neutrinos from their polar caps through photomeson interactions. We identify a neutrino cut-off band in the magnetar period-magnetic field strength phase diagram, corresponding to the photomeson interaction threshold. Within uncertainties, we point out four possible neutrino emission candidates among the currently known magnetars, the brightest of which may be detectable for a chance on-beam alignment. Young magnetars in the universe would also contribute to a weak diffuse neutrino background, whose detectability is marginal, depending on the typical neutrino energy.Comment: emulateapj style, 6 pages, 1 figure, ApJ, v595, in press. Important contributions from Dr. Harding added. Major revisions made. More conservative and realistic estimates about the neutrino threshold condition and emission efficiency performed. More realistic typical beaming angle and magnetar birth rate adopte

Simulating the Initial Stage of Phenolic Resin Carbonization via the ReaxFF Reactive Force Field

Pyrolysis of phenolic resins leads to carbon formation. Simulating this resin-to-carbon process atomistically is a daunting task. In this paper, we attempt to model the initial stage of this process by using the ReaxFF reactive force field, which bridges quantum mechanical and molecular mechanical methods. We run molecular dynamics simulations to examine the evolution of small molecules at different temperatures. The main small-molecule products found include H_2O, H_2, CO, and C_2H_2. We find multiple pathways leading to H_2O formation, including a frequent channel via β-H elimination, which has not been proposed before. We determine the reaction barrier for H_2O formation from the reaction rates obtained at different temperatures. We also discuss the relevance of our simulations to previous experimental observations. This work represents a first attempt to model the resin-to-carbon process atomistically

An exactly solvable phase transition model: generalized statistics and generalized Bose-Einstein condensation

In this paper, we present an exactly solvable phase transition model in which the phase transition is purely statistically derived. The phase transition in this model is a generalized Bose-Einstein condensation. The exact expression of the thermodynamic quantity which can simultaneously describe both gas phase and condensed phase is solved with the help of the homogeneous Riemann-Hilbert problem, so one can judge whether there exists a phase transition and determine the phase transition point mathematically rigorously. A generalized statistics in which the maximum occupation numbers of different quantum states can take on different values is introduced, as a generalization of Bose-Einstein and Fermi-Dirac statistics.Comment: 17 pages, 2 figure