Discharge flow of a granular media from a silo: effect of the packing fraction and of the hopper angle

International audienceSilos are widely used in the industry. While empirical predictions of the flow rate, based on scaling laws, have existed for more than a century (Hagen 1852, translated in [1]-Beverloo et al. [2]), recent advances have be made on the understanding of the control parameters of the flow. In particular, using continuous modeling together with a mu(I) granular rheology seem to be successful in predicting the flow rate for large numbers of beads at the aperture (Staron et al.[3], [4]). Moreover Janda et al.[5] have shown that the packing fraction at the outlet plays an important role when the number of beads at the apeture decreases. Based on these considerations, we have studied experimentally the discharge flow of a granular media from a rectangular silo. We have varied two main parameters: the angle of the hopper, and the bulk packing fraction of the granular material by using bidisperse mixtures. We propose a simple physical model to describe the effect of these parameters, considering a continuous granular media with a dilatancy law at the outlet. This model predicts well the dependance of the flow rate on the hopper angle as well as the dependance of the flow rate on the fine mass fraction of a bidisperse mixture

Digital pulse actuated flow control on a centrifugal disc towards multiparameter water quality monitoring

In this paper we present a novel dissolvable film (DF) based valving architecture for use on the centrifugal microfluidic platform. We seal fluidic reservoirs on a disc substrate with a series of these valves such that, by pulsing the spin rate, the next valve in the series is opened. Thus centrifugal flow control advances from ‘analogue’ scheme, where valves are successively opened by incremental steps of the rotational frequency, to a ‘digital pulse’ based method. The performance of these valves is demonstrates through a disc designed towards multi-parameter water quality monitoring

Modest : water heater smart control and management

Recent advances in microcontroller technology have given rise to the Internet of Things (IoT), which has created new opportunities in energy automation and optimization. Smart devices and appliances are able to collect operational data, and combine it with data analytics to facilitate optimized control of household electronics. For example, data collected from a smart thermostat can be combined with third-party data sources such as; 15­min interval electricity usage data collected from a smart meter, weather data from numerous sources, utility billing rate data, and data from other smart appliances in the home to optimize the energy usage of residential heating and cooling system. The goals for this project are: 1) Design a control system that enables collection of temperature, flow rate and power data, 2) implement the control system in an electric water heater for residential use, 3) create a connection between a cloud server and the water heater control system for data collection, and 4) develop an advanced control algorithm for water heater thermal management. The main contribution is meant to be a cloud-based infrastructure for IoT aggregation and control, a kind of artificial intelligence for IoT and energy automation.Electrical and Computer Engineerin

Consideration of the Mechanisms for Tidal Bore Formation in an Idealized Planform Geometry

A tidal bore is a positive wave traveling upstream along the estuary of a river, generated by a relatively rapid rise of the tide, often enhanced by the funneling shape of the estuary. The swell produced by the tide grows and its front steepens as the flooding tide advances inland, promoting the formation of a sharp front wave, i.e., the tidal bore. Because of the many mechanisms and conditions involved in the process, it is difficult to formulate an effective criterion to predict the bore formation. In this preliminary analysis, aimed at bringing out the main processes and parameters that control tidal bore formation, the degrees of freedom of the problem are largely reduced by considering a rectangular channel of constant width with uniform flow, forced downstream by rising the water level at a constant rate. The framework used in this study is extremely simple, yet the problem is still complex and the solution is far from being trivial. From the results of numerical simulations, three distinctive behaviors emerged related to conditions in which a tidal bore forms, a tidal bore does not form, and a weak bore forms; the latter has a weakly steep front and after the bore formed it rapidly vanishes. Based on these behaviors, some criteria to predict the bore formation are proposed and discussed. The more effective criterion, suitably rearranged, is checked against data from real estuaries and the predictions are found to compare favorably with the available data

Adaptive RTT-driven Transport-layer Flow and Error Control Protocol for QoS Guaranteed Image Transmission over Multi-hop Underwater Wireless Networks: Design, Implementation, and Analysis

With the rapid advances in data transmission over various advanced underwater acoustic networks, it is important to develop the efficient protocol to obtain a high data-rate with Quality of Service (QoS) guarantee requirements for acoustic wireless communications. Because of the harsh underwater acoustic environments, such as time-varying network topology and channel conditions, limited bandwidth and constrained underwater signal propagation, we develop and implement a protocol called multi-hop adaptive RTT-driven transport layer flow and error control protocol (ARTFEC) for QoS guaranteed image transmission in underwater wireless networks. ARTFEC is based on the congestion window size control and the Q-learning optimal timeout selection with QoS provisioning. For the congestion window size control, we propose an RTT-based data flow control policy to adapt to the varying acoustic channel environments, aiming to guarantee the reliability and high data rate of data transmission. In addition, we develop a Q-learning based optimal timeout selection algorithm to improve the channel utilization efficiency, which can increase the end-to-end throughput while decreasing the packet loss rate. We implement ARTFEC using our lab testbed, which consists of the Aqua-Net protocol stack and the acoustic OFDM modems. The testbed results obtained show that our developed ARTFEC transport layer protocol outperforms the other existing reliable data transmission schemes, in terms of end-to-end throughput and packet loss rate

Modeling mechanical interactions in growing populations of rod-shaped bacteria

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell's environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps

An Efficient Analytical Solution to Thwart DDoS Attacks in Public Domain

In this paper, an analytical model for DDoS attacks detection is proposed, in which propagation of abrupt traffic changes inside public domain is monitored to detect a wide range of DDoS attacks. Although, various statistical measures can be used to construct profile of the traffic normally seen in the network to identify anomalies whenever traffic goes out of profile, we have selected volume and flow measure. Consideration of varying tolerance factors make proposed detection system scalable to the varying network conditions and attack loads in real time. NS-2 network simulator on Linux platform is used as simulation testbed. Simulation results show that our proposed solution gives a drastic improvement in terms of detection rate and false positive rate. However, the mammoth volume generated by DDoS attacks pose the biggest challenge in terms of memory and computational overheads as far as monitoring and analysis of traffic at single point connecting victim is concerned. To address this problem, a distributed cooperative technique is proposed that distributes memory and computational overheads to all edge routers for detecting a wide range of DDoS attacks at early stage.Comment: arXiv admin note: substantial text overlap with arXiv:1203.240

The integrated use of enterprise and system dynamics modelling techniques in support of business decisions

Enterprise modelling techniques support business process re-engineering by capturing existing processes and based on perceived outputs, support the design of future process models capable of meeting enterprise requirements. System dynamics modelling tools on the other hand are used extensively for policy analysis and modelling aspects of dynamics which impact on businesses. In this paper, the use of enterprise and system dynamics modelling techniques has been integrated to facilitate qualitative and quantitative reasoning about the structures and behaviours of processes and resource systems used by a Manufacturing Enterprise during the production of composite bearings. The case study testing reported has led to the specification of a new modelling methodology for analysing and managing dynamics and complexities in production systems. This methodology is based on a systematic transformation process, which synergises the use of a selection of public domain enterprise modelling, causal loop and continuous simulationmodelling techniques. The success of the modelling process defined relies on the creation of useful CIMOSA process models which are then converted to causal loops. The causal loop models are then structured and translated to equivalent dynamic simulation models using the proprietary continuous simulation modelling tool iThink

Biophysical assay for tethered signaling reactions reveals tether-controlled activity for the phosphatase SHP-1

Tethered enzymatic reactions are ubiquitous in signaling networks but are poorly understood. A previously unreported mathematical analysis is established for tethered signaling reactions in surface plasmon resonance (SPR). Applying the method to the phosphatase SHP-1 interacting with a phosphorylated tether corresponding to an immune receptor cytoplasmic tail provides five biophysical/biochemical constants from a single SPR experiment: two binding rates, two catalytic rates, and a reach parameter. Tether binding increases the activity of SHP-1 by 900-fold through a binding-induced allosteric activation (20-fold) and a more significant increase in local substrate concentration (45-fold). The reach parameter indicates that this local substrate concentration is exquisitely sensitive to receptor clustering. We further show that truncation of the tether leads not only to a lower reach but also to lower binding and catalysis. This work establishes a new framework for studying tethered signaling processes and highlights the tether as a control parameter in clustered receptor signaling