Dynamic Matrix-Fracture Transfer Behaviour in Dual-Porosity Models

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Morphological properties of mass-spring networks for optimal locomotion learning

Robots have proven very useful in automating industrial processes. Their rigid components and powerful actuators, however, render them unsafe or unfit to work in normal human environments such as schools or hospitals. Robots made of compliant, softer materials may offer a valid alternative. Yet, the dynamics of these compliant robots are much more complicated compared to normal rigid robots of which all components can be accurately controlled. It is often claimed that, by using the concept of morphological computation, the dynamical complexity can become a strength. On the one hand, the use of flexible materials can lead to higher power efficiency and more fluent and robust motions. On the other hand, using embodiment in a closed-loop controller, part of the control task itself can be outsourced to the body dynamics. This can significantly simplify the additional resources required for locomotion control. To this goal, a first step consists in an exploration of the trade-offs between morphology, efficiency of locomotion, and the ability of a mechanical body to serve as a computational resource. In this work, we use a detailed dynamical model of a Mass–Spring–Damper (MSD) network to study these trade-offs. We first investigate the influence of the network size and compliance on locomotion quality and energy efficiency by optimizing an external open-loop controller using evolutionary algorithms. We find that larger networks can lead to more stable gaits and that the system’s optimal compliance to maximize the traveled distance is directly linked to the desired frequency of locomotion. In the last set of experiments, the suitability of MSD bodies for being used in a closed loop is also investigated. Since maximally efficient actuator signals are clearly related to the natural body dynamics, in a sense, the body is tailored for the task of contributing to its own control. Using the same simulation platform, we therefore study how the network states can be successfully used to create a feedback signal and how its accuracy is linked to the body size

Foam EOR Processes

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Flight test evaluation of a separate surface attitude command control system on a Beech 99 airplane

A joint NASA/university/industry program was conducted to flight evaluate a potentially low cost separate surface implementation of attitude command in a Beech 99 airplane. Saturation of the separate surfaces was the primary cause of many problems during development. Six experienced professional pilots who made simulated instrument flight evaluations experienced improvements in airplane handling qualities in the presence of turbulence and a reduction in pilot workload. For ride quality, quantitative data show that the attitude command control system results in all cases of airplane motion being removed from the uncomfortable ride region

Exploring helical dynamos with machine learning

We use ensemble machine learning algorithms to study the evolution of magnetic fields in magnetohydrodynamic (MHD) turbulence that is helically forced. We perform direct numerical simulations of helically forced turbulence using mean field formalism, with electromotive force (EMF) modeled both as a linear and non-linear function of the mean magnetic field and current density. The form of the EMF is determined using regularized linear regression and random forests. We also compare various analytical models to the data using Bayesian inference with Markov Chain Monte Carlo (MCMC) sampling. Our results demonstrate that linear regression is largely successful at predicting the EMF and the use of more sophisticated algorithms (random forests, MCMC) do not lead to significant improvement in the fits. We conclude that the data we are looking at is effectively low dimensional and essentially linear. Finally, to encourage further exploration by the community, we provide all of our simulation data and analysis scripts as open source IPython notebooks.Comment: accepted by A&A, 11 pages, 6 figures, 3 tables, data + IPython notebooks: https://github.com/fnauman/ML_alpha

The application of quadratic optimal cooperative control synthesis to a CH-47 helicopter

A control-system design method, Quadratic Optimal Cooperative Control Synthesis (CCS), is applied to the design of a Stability and Control Augmentation Systems (SCAS). The CCS design method is different from other design methods in that it does not require detailed a priori design criteria, but instead relies on an explicit optimal pilot-model to create desired performance. The design model, which was developed previously for fixed-wing aircraft, is simplified and modified for application to a Boeing Vertol CH-47 helicopter. Two SCAS designs are developed using the CCS design methodology. The resulting CCS designs are then compared with designs obtained using classical/frequency-domain methods and Linear Quadratic Regulator (LQR) theory in a piloted fixed-base simulation. Results indicate that the CCS method, with slight modifications, can be used to produce controller designs which compare favorably with the frequency-domain approach

Asymmetric nuclear matter:the role of the isovector scalar channel

We try to single out some qualitative new effects of the coupling to the $\delta$-isovector-scalar meson introduced in a minimal way in a phenomenological hadronic field theory. Results for the equation of state ($EOS$) and the phase diagram of asymmetric nuclear matter ($ANM$) are discussed. We stress the consistency of the $\delta$-coupling introduction in a relativistic approach. New contributions to the slope and curvature of the symmetry energy and the neutron-proton effective mass splitting appear particularly interesting. A more repulsive $EOS$ for neutron matter at high baryon densities is expected. Effects on new critical properties of warm $ANM$, mixing of mechanical and chemical instabilities and isospin distillation, are also presented. The $\delta$ influence is mostly on the {\it isovectorlike} collective response. The results are largely analytical and this makes the physical meaning quite transparent. Implications for nuclear structure properties of drip-line nuclei and for reaction dynamics with Radioactive Beams are finally pointed out.Comment: 12 pages, 10 Postscript figure

Impact of Compositional Grading and Component Lumping on Ultimate Recovery

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