Model-Based Granular Flow Estimation Using an Array of Low-Cost Transmitted Light Sensors

Author(s):  
M. Brandner ◽  
A. Fuchs
2007 ◽  
Vol 18 (1) ◽  
pp. 56-79
Author(s):  
Hokey Min ◽  
Hyun-Jeung Ko ◽  
Chin-Soo Lin

With the unprecedented growth of international trade, a growing number of multinational firms have coped with logistical challenges of shipping products to and from unfamiliar territories in many countries. These logistical challenges include the cross-border transportation of products originated from inland port to another inland port isolated from major waterways. In particular, the lack of access to major waterways would not only constrain the intermodal transportation option, but also make door-to-door, containerized delivery services nearly impossible. Such a limited option would eventually lead to increased transportation costs and transit time, and thereby offset low-cost global sourcing advantages. To aid multinational firms in addressing the problem of determining the optimal supply chain link between inland origin and destinations ports, this article proposes a shortest-path model based decision support system. The usefulness of the proposed model-based decision support system was validated by its application to a real problem encountered by a multinational firm that would like to strengthen its foothold in the Chinese market.


2009 ◽  
Vol 3 (1-2) ◽  
pp. 21-38 ◽  
Author(s):  
Yuzuru Isoda ◽  
Akihiro Tsukamoto ◽  
Yoshihiro Kosaka ◽  
Takuya Okumura ◽  
Masakazu Sawai ◽  
...  

This paper explores a method for creating large-scale urban 3D models using Historical GIS data. The method is capable of automatically generating realistic VR models based on GIS data at a low cost. 3D models of houses are created from polygon data, fences from line data, and pedestrians and trees from point data. The method is applied to the Virtual Kyoto Project in which the landscape of the whole city of Kyoto of the early Edo era (ca 17C) is reconstructed.


Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2467 ◽  
Author(s):  
Hery Mwenegoha ◽  
Terry Moore ◽  
James Pinchin ◽  
Mark Jabbal

The dominant navigation system for low-cost, mass-market Unmanned Aerial Vehicles (UAVs) is based on an Inertial Navigation System (INS) coupled with a Global Navigation Satellite System (GNSS). However, problems tend to arise during periods of GNSS outage where the navigation solution degrades rapidly. Therefore, this paper details a model-based integration approach for fixed wing UAVs, using the Vehicle Dynamics Model (VDM) as the main process model aided by low-cost Micro-Electro-Mechanical Systems (MEMS) inertial sensors and GNSS measurements with moment of inertia calibration using an Unscented Kalman Filter (UKF). Results show that the position error does not exceed 14.5 m in all directions after 140 s of GNSS outage. Roll and pitch errors are bounded to 0.06 degrees and the error in yaw grows slowly to 0.65 degrees after 140 s of GNSS outage. The filter is able to estimate model parameters and even the moment of inertia terms even with significant coupling between them. Pitch and yaw moment coefficient terms present significant cross coupling while roll moment terms seem to be decorrelated from all of the other terms, whilst more dynamic manoeuvres could help to improve the overall observability of the parameters.


2020 ◽  
Vol 104 (2) ◽  
pp. 1581-1596
Author(s):  
Thomas Heinze

Abstract Dynamics of snow avalanches or landslides can be described by rapid granular flow. Experimental investigations of granular flow at laboratory scale are often required to analyze flow behaviour and to develop adequate mathematical and numerical models. Most investigations use image-based analysis, and additional sensors such as pressure gauges are not always possible. Testing various scenarios and parameter variations such as different obstacle shapes and positions as well as basal topography and friction usually requires either the construction of a new laboratory setups for each test or a cumbersome reconstruction. In this work, a highly flexible and modular laboratory setup is presented based on LEGO bricks. The flexibility of the model is demonstrated, and possible extensions for future laboratory tests are outlined. The setup is able to reproduce published laboratory experiments addressing current scientific research topics, such as overflow of a rigid reflector, flow on a bumpy surface and against a rigid wall using standard image-based analysis. This makes the setup applicable for quick scenario testing, e.g. for hypothesis testing or for low-cost testing prior to large-scale experiments, and it can contribute to the validation of external results and to benchmarks of numerical models. Small-scale laboratory setups are also very useful for demonstration purposes such as education and public outreach, both crucial in the context of natural hazards. The presented setup enables variation of parameters such as of slope length, channel width, height and shape, inclination, bed friction, obstacle position and shape, as well as density, composition, amount and grain size of flowing mass. Observable quantities are flow type, flow height, flow path and flow velocity, as well as runout distance, size and shape of the deposited material. Additional sensors allow further quantitative assessments, such as local pressure values.


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