Freeform surfaces are widely used in advanced optical systems. In order to accurately measure freeform surfaces, an adaptive interferometer with deformable mirror (DM) has been developed for the freeform surface metro...
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Freeform surfaces are widely used in advanced optical systems. In order to accurately measure freeform surfaces, an adaptive interferometer with deformable mirror (DM) has been developed for the freeform surface metrology. To ensure the efficiency, a stochastic parallel gradient descent (SPGD) and newtoniteration mixed algorithm to drive the DM has been proposed, it can achieve the minimum value of the optimization and is suitable for the different interferograms. The simulation and experimental results verify the correctness and feasibility of the proposed DM driving algorithm.
Centrifugal dewatering is a common process used for solid-liquid separation in chemical industry. This process involves the intricate interaction between particles and liquid under centrifugal pressure. Accurate model...
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Centrifugal dewatering is a common process used for solid-liquid separation in chemical industry. This process involves the intricate interaction between particles and liquid under centrifugal pressure. Accurate modeling and simulation of the kinetic process are key to optimizing the dewatering parameters. However, the feeding stage is often disregarded in most of the simulation studies, leading to obvious differences from the actual conditions in the dewatering behavior and initial solid concentration. In this study, a 1D-axisymmetric model is established to simulate the feeding and pre-dewatering stages of an inverting filter centrifuge. The simulation results at different rotating speeds agree with the experimental observations and show a significant difference compared to the model that ignores the feeding stage. Both phenomena demonstrate the method in this study is accurate and reliable. Furthermore, the effects of feeding parameters are investigated using the Sobol global sensitivity analysis method. This study provides crucial assistance for the parameters' optimization and prediction of centrifugal dewatering.
Node localization is an important area in wireless sensor networks (WSNs). Because there are unavoidable measurement errors by the popular distance measurement techniques such as RSSI and TOA, the localization precisi...
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ISBN:
(纸本)9781424462520
Node localization is an important area in wireless sensor networks (WSNs). Because there are unavoidable measurement errors by the popular distance measurement techniques such as RSSI and TOA, the localization precision is the main evaluation criteria for localization algorithms. In this paper, we compare the performances of localization algorithms in different error models by simulation and show that some algorithms are more sensitive to measurement errors than others. The localization errors are more serious when measurement error models are different for distance from various beacon nodes. We give a nonlinear optimal model for this case and employ the newton iteration algorithm to solve this problem. Simulation shows it is better when give different weights to different error models can give a better measurement precision.
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