4,598 research outputs found
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Calculation of clearances in twin screw compressors
Clearances between rotating and stationary parts in a screw compressor are set to ensure the efficient operation and allow for thermal deformation without unwanted contacts. The change in clearances is caused by both pressure and temperature changes within the machine. If clearances are too large, the increased leakage flows will reduce efficiency. However, if the nominal clearances are too small, contacts between the rotating and stationary parts can occur as a consequence of rotor and casing deformations. In order to determine the operational clearances, a numerical analysis of deformation of screw compressor rotors and casing has to be performed. This paper discusses how the temperature of rotor and casing surfaces calculated from the one-dimensional chamber model in the SCORG could be used as a boundary conditions for a steady state thermal and structural analysis of a screw compressor solid parts. Deformations of rotors and casing under temperature load were calculated using a commercial Finite Element Analysis code ANSYS. Operational clearance are estimated from these deformations and some recommendations for further work are proposed
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Process Control of 3D Welding as a Droplet-Based Rapid Prototyping Technique
Three-dimensional welding is investigated as a rapid prototyping technique for the production
of real Inetallic parts using gas metal arc welding principles. A high speed machine vision
system is used to study the correlation between droplet transfer parameters and resultant weld
penetration characteristics. Experimental work is conducted to determine how droplet transfer
frequency, droplet size, and number of passes affect the geometrical and Inetallurgical properties
ofthe weld penetration. A finite element analysis is performed in order to study what influence
additional layering has on the cooling characteristics and resultant penetration profile.Mechanical Engineerin
Review of HDI Critiques and Potential Improvements
This paper reviews critiques of the Human Development Report over the last twenty years. The critiques are mostly related to the choice of indicators, to high correlation of HDI components, functional form of the HDI including normalization of component indicators, aggregation vs. multiplication, and issues related to weighting. A thorough analysis of the critiques leads us to a proposal for modification of the HDI.Composite index, well-being, marginal substitutability, equal weighting, aggregation
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Morphing Based Approach for Process Planning for Fabrication of Geometries and the Control of Material Composition
The inherent limitation of most of the solid freeform fabrication is the deposition in form
of layers. Artificial imposition of the process for the desired geometric morphology and
the functional gradience of material limits the accuracy of the workpiece. Mathematical
morphing of geometry and the material gradience allows a smooth variation across the
part geometry and the material composition of the part. The paper describes a framework
for process planning and implementation of fabrication of geometries and control of the
material composition. Simulation results for the suggested approach are described in the
paper.Mechanical Engineerin
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Modeling and Verification of Error Propagation in Integrated Additive/Subtractive Multi-Directional Direct Manufacturing
Integrated additive-subtractive manufacturing, when applied in the framework of SolidFreeform-Fabrication (SFF) allows the fabrication of functional parts on single platform, directly from its computer model. Reduction in process complexity and total processing steps is
ensured by multi-directional material deposition and machining. However, due to shift in the
datum location in reorientation steps and sequential addition of material in the form of layers,
the CAD process intent is not exactly replicated. This leads to inclusion of dimensional errors.
Machining in order to eliminate the errors as frequent as layer deposition is highly expensive
and can be avoided by estimation of errors and varying process parameters, and/or performing
machining after a set of layers are deposited. This paper proposes a state space model for modeling the error propagation due to linear as well as angular variation in the datum. The model
is based on identification of possible sources of error, mechanism of error inclusion and influence
of process parameters. An experiment performed to determine parameters of error modeling
has been reported.Mechanical Engineerin
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An Investigation of Gas-Powder Flow in Laser-Based Direct Metal Deposition
Laser-Based Direct Metal Deposition (LBDMD) is a blown-powder laser deposition process
which can produce fully-dense and metallurgicaly sound parts by a layered manufacturing
method. Since a deposition head equipped with discontinuous radially symmetric nozzles has the
potential to be tilted without influence of the gravity on the powder stream shape, it can be used
for multi-axis deposition. The shape of the gas-powder stream with respect to the shape of laser
beam and the size of the molten pool, have a large influence on the size and shape of the buildup.
They determine the geometrical accuracy and the surface quality of the buildup. This paper
examines gas-powder flow from radially symmetric nozzles using computational fluid dynamics
method. For verification purpose the powder flow was investigated by a visualization method
and powder concentration distribution was analyzed using image processing technique. The
obtained results are in good agreement with numerical model.Mechanical Engineerin
3D Point Cloud Denoising via Deep Neural Network based Local Surface Estimation
We present a neural-network-based architecture for 3D point cloud denoising
called neural projection denoising (NPD). In our previous work, we proposed a
two-stage denoising algorithm, which first estimates reference planes and
follows by projecting noisy points to estimated reference planes. Since the
estimated reference planes are inevitably noisy, multi-projection is applied to
stabilize the denoising performance. NPD algorithm uses a neural network to
estimate reference planes for points in noisy point clouds. With more accurate
estimations of reference planes, we are able to achieve better denoising
performances with only one-time projection. To the best of our knowledge, NPD
is the first work to denoise 3D point clouds with deep learning techniques. To
conduct the experiments, we sample 40000 point clouds from the 3D data in
ShapeNet to train a network and sample 350 point clouds from the 3D data in
ModelNet10 to test. Experimental results show that our algorithm can estimate
normal vectors of points in noisy point clouds. Comparing to five competitive
methods, the proposed algorithm achieves better denoising performance and
produces much smaller variances
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