Coriolis-induced instabilities in centrifuge modeling of granular flow

Granular flows are typically studied in laboratory flumes based on common similarity scaling, which create stress fields that only roughly approximate field conditions. The geotechnical centrifuge produces stress conditions that are closer to those observed in the field, but steady conditions can be hardly achieved. Moreover, secondary effects induced by the apparent Coriolis acceleration, which can either dilate or compress the flow, often obscure scaling. This work aims at studying a set of numerical experiments where the effects of the Coriolis acceleration are measured and analyzed. Three flow states are observed: dense, dilute, and unstable. It is found that flows generated under the influence of dilative Coriolis accelerations are likely to become unstable. Nevertheless, a steady dense flow can still be obtained if a large centrifuge is used. A parametric group is proposed to predict the insurgence of instabilities; this parameter can guide experimental designs and could help to avoid damage to the experimental apparatus and model instrumentation. Graphic abstract

Adversarial Optimization-Based Knowledge Transfer of Layer-Wise Dense Flow for Image Classification

A deep-learning technology for knowledge transfer is necessary to advance and optimize efficient knowledge distillation. Here, we aim to develop a new adversarial optimization-based knowledge transfer method involved with a layer-wise dense flow that is distilled from a pre-trained deep neural network (DNN). Knowledge distillation transferred to another target DNN based on adversarial loss functions has multiple flow-based knowledge items that are densely extracted by overlapping them from a pre-trained DNN to enhance the existing knowledge. We propose a semi-supervised learning-based knowledge transfer with multiple items of dense flow-based knowledge extracted from the pre-trained DNN. The proposed loss function would comprise a supervised cross-entropy loss for a typical classification, an adversarial training loss for the target DNN and discriminators, and Euclidean distance-based loss in terms of dense flow. For both pre-trained and target DNNs considered in this study, we adopt a residual network (ResNet) architecture. We propose methods of (1) the adversarial-based knowledge optimization, (2) the extended and flow-based knowledge transfer scheme, and (3) the combined layer-wise dense flow in an adversarial network. The results show that it provides higher accuracy performance in the improved target ResNet compared to the prior knowledge transfer methods.

Unified constitutive model for granular-fluid mixture in quasi-static and dense flow regimes

Most granular materials encountered in nature and industry lie either in the quasi-static regime or the intermediate dense flow regime. Debris materials are a typical granular material with viscous interstitial fluid, and shows solid-like behaviors before failure and fluid-like behaviors after failure. Based on Bagnold’s pioneering work on granular-fluid flows, we propose a framework for constitutive model development, which has an additive form. Based on this framework, a unified constitutive model for granular-fluid material in the quasi-static and dense flow regimes is developed. The main intergranular interactions and granular-fluid interactions controlling the mechanical behaviors are taken into account using the Mohr-Coulomb model and a Bagnold-type relation. Dry granular flows in three simple configurations, i.e., plain shear, vertical chute flow and flow on an inclined plane, are studied. Analytical solutions based on the presented unified model are obtained. Comparisons between results from the presented model and the mu(I) model indicate that the explicit partition of frictional and collisional stress components provides insights in dense granular flows. In addition, the new model is used to predict the stress-strain relations in two annular shear tests. The applicability and advantages of the unified model are discussed.

AvaFrame as a testing and benchmarking environment for avalanche simulations

<p>Testing and benchmarking avalanche models is a crucial step in developing models as well as assessing their applicability. This is not only limited to the representation of physical processes within models, be it via first principles or using empirical relationships, but also concerns their computing environment, including compilers, hardware used, programming language, among others. </p><p>Test, benchmarking, and comparison strategies can aim at different issues, among others: numerics, the implementation thereof, plausibility, verification, or evaluation. However, they always require reference or expected results. References can come from observations, analytical results, comparison to other models, known physical processes or material properties that cannot be changed – e.g., “avalanches cannot fly”. The question is: which characteristics or properties do we test and how to design appropriate tests?  </p><p>To facilitate this, as part of the newly developed opensource avalanche framework - AvaFrame -, we started providing commonly accessible tools to make testing and developing easier. This ranges from tools to import data, generate input parameters to automatic analysis and plotting. Not only do we provide the infrastructure for testing, but we also provide a set of test cases complete with all necessary input data, reference results, and run script examples. These tests so far include idealized (generic) topographies, specific test cases for numerical questions, and 6 real world avalanches with distinct characteristics. </p><p>In this contribution we present this freely available set of tests and benchmarks suitable to assess various aspects and properties of a shallow water model solver for a dense flow avalanche model, one of the core computing modules of AvaFrame (com1DFA). We highlight how we utilize the entire range of tests in our continuous model development to assure the quality and applicability / validity of our development. Showing results from comparison to existing models, but also how to extend and apply our strategies to other models or research questions, we invite other researchers and developers to make full use of these tools.</p>

Making the Desert Bloom?

World War one witnessed the first dense flow of Indian labor into the Persian Gulf. To reconstruct the campaign in Mesopotamia/Iraq after the reverses of 1915-16, the Indian Army demanded non-combatants for dock-work, construction labor and medical and transport services. This chapter explores the Government of India’s anxious deliberations about the choice of legal form in which to meet this demand. The sending of labor for military work overseas had to be distanced conceptually from the stigmatized system of indentured labor migration. There was a danger of disrupting those labor networks across India and around the Bay of Bengal which maintained the supply of material goods for the war. Non-combatant recruitment took the war into new sites and spaces. Regimes of labor servitude were tapped but some form of emancipation had to be promised. The chapter focusses on seven jail- recruited Indian Labor and Porter Corps to explore the work regime in Mesopotamia. Labor units often insisted on fixed engagements rather than ‘duration of war’ agreements, but had to struggle for exit at the conclusion of their contract. After the Armistice, Britain still needed Indian labor and troops in Mesopotamia but sought to prevent the emergence of a settler population.

The Study of Three-Dimensional Granular Stream Flowing through the Test Hopper-Shaped Target

The experiments are carried out in a three-dimensional channel with a screw conveyor, which plays the role of granular drives for the granular flow system and determines the injection of granular in the test target section. The jam-to-dense transition of granular flow is studied with the different inclination angle. The results show that, with a fixed diameter of hopper orifice and initial filling position, there is a change from jam to dense when the inclination angle larger than 22°. Variation of the flow rate with elevated frequency of the screw conveyor is further studied. The flow pattern is changed from dilute to dense with increasing rotation frequency of the screw rod. When the rotation frequency is larger than 5 Hz, the flow is dense. The dynamic balance of the interface between dilute to dense granular is observed in the main target section. We further research the dynamic interface by measuring the highest and lowest location with time and also simulate the gravity flow rate and screw conveyor flow rate with EDEM. From the results, we find that the interface between dilute flow and dense flow is influenced by the combined action of crew conveyor flow and dense gravity flow.