The isogeometric methodology has been successfully implemented in one-step inverse analysis of sheet metal stamping processes. However, these models are not capable of analyzing forming processes that require severe d...
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Stinging nettle is a perennial herbaceous plant belonging to the Urticaceae family, In Bali Indonesia called jelatang. This species is considered a weed in intensive agriculture as its fast vegetative growth and high ...
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A flexible treatment for gas- and aerosol-phase chemical processes has been developed for models of diverse scale, from box models up to global models. At the core of this novel framework is an"abstracted aerosol...
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A flexible treatment for gas- and aerosol-phase chemical processes has been developed for models of diverse scale, from box models up to global models. At the core of this novel framework is an"abstracted aerosol representation" that allows a given chemical mechanism to be solved in atmospheric models with different aerosol representations (e.g., sectional, modal, or particle-resolved). This is accomplished by treating aerosols as a collection of condensed phases that are implemented according to the aerosol representation of the host model. The framework also allows multiple chemical processes (e.g., gas- and aerosol-phase chemical reactions, emissions, deposition, photolysis, and mass-transfer) to be solved simultaneously as a single system. The flexibility of the model is achieved by (1) using an object-oriented design that facilitates extensibility to new types of chemical processes and to new ways of representing aerosol systems;(2) runtime model configuration using JSON input files that permits making changes to any part of the chemical mechanism without recompiling the model;this widely used, human-readable format allows entire gas- and aerosol-phase chemical mechanisms to be described with as much complexity as necessary;and (3) automated comprehensive testing that ensures stability of the code as new functionality is introduced. Together, these design choices enable users to build a customized multiphase mechanism, without having to handle pre-processors, solvers or compilers. Removing these hurdles makes this type of modeling accessible to a much wider community, including modelers, experimentalists, and educators. This new treatment compiles as a stand-alone library and has been deployed in the particle-resolved PartMC model and in the MONARCH chemical weather prediction system for use at regional and global scales. Results from the initial deployment to box models of different complexity and MONARCH will be discussed, along with future extension to more
In various mechanical systems, the study of damage processes can be approached from the perspective of continuous phase transition phenomena, a subject typically explored within the framework of statistical physics. T...
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We present a sim-to-real framework that uses dynamics and domain randomized offline reinforcement learning to enhance open-loop gaits for legged robots, allowing them to traverse uneven terrain without sensing foot im...
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It is important for an Unmanned Aerial Vehicle (UAV) to detect any object in its view. This enables the UAV to locate the object with respect to itself and is required for locking and tracking the object. Object detec...
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ISBN:
(数字)9781728149974
ISBN:
(纸本)9781728149981
It is important for an Unmanned Aerial Vehicle (UAV) to detect any object in its view. This enables the UAV to locate the object with respect to itself and is required for locking and tracking the object. Object detection and location estimation makes the UAV capable of manipulating the environment as well as to follow the target. In the present work, object detection has been carried out using You Only Look Once (YOLO) to detect the object in the image stream of the Robot Operating System (ROS) bag file. The GPS information of the UAV is used to further calculate the GPS coordinates of the object. The images are acquired using a single monocular camera.
Motivated by the success of encoding multi-scale contextual information for image analysis, we propose our PointAtrousGraph (PAG) - a deep permutation-invariant hierarchical encoder-decoder for efficiently exploiting ...
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ISBN:
(数字)9781728173955
ISBN:
(纸本)9781728173962
Motivated by the success of encoding multi-scale contextual information for image analysis, we propose our PointAtrousGraph (PAG) - a deep permutation-invariant hierarchical encoder-decoder for efficiently exploiting multi-scale edge features in point clouds. Our PAG is constructed by several novel modules, such as Point Atrous Convolution (PAC), Edgepreserved Pooling (EP) and Edge-preserved Unpooling (EU). Similar with atrous convolution, our PAC can effectively enlarge receptive fields of filters and thus densely learn multi-scale point features. Following the idea of non-overlapping maxpooling operations, we propose our EP to preserve critical edge features during subsampling. Correspondingly, our EU modules gradually recover spatial information for edge features. In addition, we introduce chained skip subsampling/upsampling modules that directly propagate edge features to the final stage. Particularly, our proposed auxiliary loss functions can further improve our performance. Experimental results show that our PAG outperform previous state-of-the-art methods on various 3D semantic perception applications.
Environmental issues are the most critical and urgent factor for the increasing use of biopolymers in broader applications. Research on chitosan as a bioplastic material opens vast opportunities to improve its weak me...
Environmental issues are the most critical and urgent factor for the increasing use of biopolymers in broader applications. Research on chitosan as a bioplastic material opens vast opportunities to improve its weak mechanical properties. These include blending with biopolymer/synthetic polymers as a matrix or incorporating with nanofillers. The use of organic solvents in dissolving chitosan is also interesting for further research. In this study, we synthesized a chitosan/PVA-based biofilm composite in five different ratios (100/0, 80/20, 60/40, 40/60, 0/100) in acetic acid and citric acid with the addition of 10% weight glycerol to get the optimum composition of mechanical properties. This optimum film would be conducted with SiO2 nanoparticles (NPs) and Cellulose Nano Crystals (CNCs) to evaluate the reinforcement effects. Various properties, including surface morphology, functional, mechanical properties, and thermal behavior, were characterized. The experimental result showed that the tensile strength of the composite film in acetic acid was higher than in citric acid. With the addition of 2.5% w/w of SiO2 NPs, the tensile strength of the composite film got its maximum value, 21.01 MPa, and the maximum of 25.77 MPa with 10% w/w of CNCs, which was 115,7% higher than with of the pure chitosan/PVA film in the ratio of 80/20 which was the optimum. The effect of adding CNC and SiO2 NPS has the opposite effect. The addition of filler CNCs will improve mechanical properties, while SiO2 NPs tend to decrease mechanical properties. All film characterizations demonstrated that the physicochemical interaction between CNCs and chitosan/PVA molecules improved their mechanical and thermal properties.
Given a set of 3D-to-2D point correspondences corrupted by outliers, we aim to robustly estimate the absolute camera pose. Existing methods robust to outliers either fail to guarantee high robustness and efficiency si...
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ISBN:
(数字)9781728173955
ISBN:
(纸本)9781728173962
Given a set of 3D-to-2D point correspondences corrupted by outliers, we aim to robustly estimate the absolute camera pose. Existing methods robust to outliers either fail to guarantee high robustness and efficiency simultaneously, or require an appropriate initial pose and thus lack generality. In contrast, we propose a novel approach based on the robust "L 2 -minimizing estimate" (L 2 E) loss. We first define a novel cost function by integrating the projection constraint into the L 2 E loss. Then to efficiently obtain the global minimum of this function, we propose a hybrid strategy of a local optimizer and branch-and-bound. For branch-and-bound, we derive effective function bounds. Our approach can handle high outlier ratios, leading to high robustness. It can run reliably regardless of whether the initial pose is appropriate, providing high generality. Moreover, given a decent initial pose, it is suitable for real-time applications. Experiments on synthetic and real-world datasets showed that our approach outperforms state-of-the-art methods in terms of robustness and/or efficiency.
This paper studies the deflection of a clamped-clamped micro beam actuator subjected to an electric voltage. Two approaches were applied to model the micro beam under study: the first one is analytical and the second ...
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