A Methodology for Information Flow Experiments

Information flow analysis has largely ignored the setting where the analyst has neither control over nor a complete model of the analyzed system. We formalize such limited information flow analyses and study an instance of it: detecting the usage of data by websites. We prove that these problems are ones of causal inference. Leveraging this connection, we push beyond traditional information flow analysis to provide a systematic methodology based on experimental science and statistical analysis. Our methodology allows us to systematize prior works in the area viewing them as instances of a general approach. Our systematic study leads to practical advice for improving work on detecting data usage, a previously unformalized area. We illustrate these concepts with a series of experiments collecting data on the use of information by websites, which we statistically analyze

CFD Analysis of 2-Stroke Engines

Abstract 1d and 3d CFD simulation is a standard engineering practice on 4-stroke engines. However, the application to the 2-Stroke cycle is not so trivial, in particular the transition from detailed CFD-3d analyses to simplified 1d engine simulations. A first critical issue is the correlation between the instantaneous cylinder gas composition and the composition of the exhaust flow: such a correlation, required by the 1d software, is very difficult to be determined by experiments, so that CFD-3D analyses remain the only reliable source of information. These CFD analyses must be carefully designed, in order to be representative of the actual operating conditions of the engine, and to provide reliable results. Another problem is the characterization of the ports discharge properties. Conventional experiments at a steady flow bench are affected by several approximations: first of all, flow patterns within the cylinder are quite different from the actual ones; moreover, the real flow is fully transient. Finally, a 3-d analysis on a single whole cycle is not sufficient to accurately predict the evolution of the thermodynamic quantities, as the conditions of the charge at exhaust port opening changes from cycle to cycle, affecting all the internal processes. A robust and cost-effective multi-cycle simulation methodology is therefore required. The paper describes a methodology to perform reliable CFD analyses on 2-Stroke engines, with the support of a conventional steady flow bench. This methodology is applied to a 2-Stroke engine prototype, for which a comprehensive set of experimental data is available. The good agreement between simulation and experiments demonstrates the soundness of the proposed approach

Identifying modular flows on multilayer networks reveals highly overlapping organization in social systems

Unveiling the community structure of networks is a powerful methodology to comprehend interconnected systems across the social and natural sciences. To identify different types of functional modules in interaction data aggregated in a single network layer, researchers have developed many powerful methods. For example, flow-based methods have proven useful for identifying modular dynamics in weighted and directed networks that capture constraints on flow in the systems they represent. However, many networked systems consist of agents or components that exhibit multiple layers of interactions. Inevitably, representing this intricate network of networks as a single aggregated network leads to information loss and may obscure the actual organization. Here we propose a method based on compression of network flows that can identify modular flows in non-aggregated multilayer networks. Our numerical experiments on synthetic networks show that the method can accurately identify modules that cannot be identified in aggregated networks or by analyzing the layers separately. We capitalize on our findings and reveal the community structure of two multilayer collaboration networks: scientists affiliated to the Pierre Auger Observatory and scientists publishing works on networks on the arXiv. Compared to conventional aggregated methods, the multilayer method reveals smaller modules with more overlap that better capture the actual organization

Modeling of the interaction of rigid wheels with dry granular media

We analyze the capabilities of various recently developed techniques, namely Resistive Force Theory (RFT) and continuum plasticity implemented with the Material Point Method (MPM), in capturing dynamics of wheel--dry granular media interactions. We compare results to more conventionally accepted methods of modeling wheel locomotion. While RFT is an empirical force model for arbitrarily-shaped bodies moving through granular media, MPM-based continuum modeling allows the simulation of full granular flow and stress fields. RFT allows for rapid evaluation of interaction forces on arbitrary shaped intruders based on a local surface stress formulation depending on depth, orientation, and movement of surface elements. We perform forced-slip experiments for three different wheel types and three different granular materials, and results are compared with RFT, continuum modeling, and a traditional terramechanics semi-empirical method. Results show that for the range of inputs considered, RFT can be reliably used to predict rigid wheel granular media interactions with accuracy exceeding that of traditional terramechanics methodology in several circumstances. Results also indicate that plasticity-based continuum modeling provides an accurate tool for wheel-soil interaction while providing more information to study the physical processes giving rise to resistive stresses in granular media

Analysis of two-phase flow properties of sandstones to evaluate their suitability for geologic storage of CO2

AbstractMore research is needed into the behavior of supercritical CO2 injected for storage in underground rocks at high pressure and temperature as a way of reducing emission of greenhouse gases into the atmosphere. Although many past studies have been based on numerical analyses, most of them considered typical two-phase flow properties in the literature, rather than experimental data, or were based on the properties of fluids other than supercritical CO2 and water. We conducted laboratory experiments on two-phase water- CO2 flow in outcrop and boring core rock samples from formations with potential for use as reservoirs for storage of CO2 to determine the capillary pressure and the relative permeabilities of the two fluids in the two-phase flow system. We developed a water- CO2 separator that allows real-time measurement of water drainage from the two-phase flow system and a procedure for stepwise increases of CO2 injection pressure for quick and efficient drainage of water from the system. We used numerical analysis to simulate injection of CO2 into a water-saturated rock and accurately reproduced the data measured in our laboratory experiments. These results allowed us to determine the relative permeabilities of CO2 and water in the potential reservoir rocks. Our methodology may be useful for evaluating potential reservoirs for subsurface CO2 storage in areas with limited information about rock properties

Advancing Pharmaceutical Dry Milling by Process Analytics and Robustness Testing

The objectives of this work were to implement on-line dynamic image analysis and to introduce a novel at-line flowability analyzer in pharmaceutical dry milling. We used a pilot-scale conical mill and flowability of a placebo granulate was monitored using a powder avalanching analyzer. Experiments were designed and evaluated by means of response surface methodology in conjunction with robustness testing. The process parameters impeller speed and screen size significantly affected the particle size distribution and flow rate of the milled granules. Feeder speed did not affect the particle size, but displayed a statistically significant influence on the flow responses. Robustness testing was able to capture the effect of noise factors on the responses and showed clear differences between different lots of the placebo granulate in addition to temperature-dependent changes in flow behavior. Thus, on-line dynamic image analysis and at-line flowability characterization, together as complementary process analytical tools, provided valuable information. The combined analysis was of particular interest for testing the process and noise factors so that future process development can profit from this advancement in dry millin