A Physics-Based Approach to Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems

Given that observational and numerical climate data are being produced at ever more prodigious rates, increasingly sophisticated and automated analysis techniques have become essential. Deep learning is quickly becoming a standard approach for such analyses and, while great progress is being made, major challenges remain. Unlike commercial applications in which deep learning has led to surprising successes, scientific data is highly complex and typically unlabeled. Moreover, interpretability and detecting new mechanisms are key to scientific discovery. To enhance discovery we present a complementary physics-based, data-driven approach that exploits the causal nature of spatiotemporal data sets generated by local dynamics (e.g. hydrodynamic flows). We illustrate how novel patterns and coherent structures can be discovered in cellular automata and outline the path from them to climate data.Comment: 4 pages, 1 figure; http://csc.ucdavis.edu/~cmg/compmech/pubs/ci2017_Rupe_et_al.ht

Computational synthesis of large deformation compliant mechanisms undergoing self and mutual contact

Topologies of large deformation Contact-aided Compliant Mechanisms (CCMs), with self and mutual contact, exemplified via path generation applications, are designed using the continuum synthesis approach. Design domains are parameterized using honeycomb tessellation. Assignment of material to each cell, and generation of rigid contact surfaces, are accomplished via suitably sizing and positioning negative circular masks. To facilitate contact analysis, boundary smoothing is implemented. Mean value coordinates are employed to compute shape functions, as many regular hexagonal cells get degenerated into irregular, concave polygons as a consequence of boundary smoothing. Both, geometric and material nonlinearities are considered in the finite element analysis. The augmented Lagrange multiplier method in association with an active set strategy is employed to incorporate both self and mutual contact. CCMs are evolved using the stochastic hill climber search. Synthesized contact-aided compliant continua trace paths with single and importantly, multiple kinks and experience multiple contact interactions pertaining to both self and mutual contact modes.Comment: 26 pages, 30 figures

On topology optimization of large deformation contact-aided shape morphing compliant mechanisms

A topology optimization approach for designing large deformation contact-aided shape morphing compliant mechanisms is presented. Such mechanisms can be used in varying operating conditions. Design domains are described by regular hexagonal elements. Negative circular masks are employed to perform dual work, i.e., to decide material states of each element and also, to generate rigid contact surfaces. Each mask is characterized by five design variables, which are mutated by a zero-order based hill-climber optimizer. Geometric and material nonlinearities are considered. Continuity in normals to boundaries of the candidate designs is ensured using a boundary resolution and smoothing scheme. The nonlinear mechanical equilibrium equations are solved using the Newton-Raphson method. An updated Lagrange approach in association with segment-to-segment contact method is employed for the contact formulation. Both mutual and self contact modes are permitted. Efficacy of the approach is demonstrated by designing three contact-aided shape morphing compliant mechanisms for different desired curves. The performance of the deformed profiles is verified using a commercial software. The effect of frictional contact surface on the actual profile is also studied.Comment: 16 pages, 11 figure

MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework

We propose MeshfreeFlowNet, a novel deep learning-based super-resolution framework to generate continuous (grid-free) spatio-temporal solutions from the low-resolution inputs. While being computationally efficient, MeshfreeFlowNet accurately recovers the fine-scale quantities of interest. MeshfreeFlowNet allows for: (i) the output to be sampled at all spatio-temporal resolutions, (ii) a set of Partial Differential Equation (PDE) constraints to be imposed, and (iii) training on fixed-size inputs on arbitrarily sized spatio-temporal domains owing to its fully convolutional encoder. We empirically study the performance of MeshfreeFlowNet on the task of super-resolution of turbulent flows in the Rayleigh-Benard convection problem. Across a diverse set of evaluation metrics, we show that MeshfreeFlowNet significantly outperforms existing baselines. Furthermore, we provide a large scale implementation of MeshfreeFlowNet and show that it efficiently scales across large clusters, achieving 96.80% scaling efficiency on up to 128 GPUs and a training time of less than 4 minutes.Comment: Supplementary Video: https://youtu.be/mjqwPch9gDo. Accepted to SC2

Modelling & Simulation of PV Module Connected with Three-Port DC Converter

Of the world’s electricity is being generated through conventional sources of energy like coal and atomic energy. People have realized the dire effect of using these fuels, and the amount of CO2 being released into the environment. There has been a shift in emphasis towards cleaner ways of generating electricity in recent years. Solar energy is abundantly available and the cleanest renewable energy source available in the world and is ready to use for a variety of applications, such as the generation of electricity for residential, commercial, or industrial consumption and have become very competitive solutions. It can be seen that there is trend of solar photovoltaics (PV), which has seen rapid growth over the years. The increasing trend of adopting PV system allows consumers to be known as producers or “Prosumers”. This report evaluates how solar PV can be used in combination with a battery bank along with three port converter to fulfill the requirement. Power production from PV cannot be consistent due to factors like the weather although The main benefits of solar power are that it can be easily installed cost of generation is low as there is no requirement for fuel and require very little maintenance Distributed maximum power point tracking (MPPT) and autonomous are achieved with the proposed configuration. The input-port of each TPC is connected to an independent PV energy source to achieve individual MPPT, and the output-ports of these TPCs are connected with load. Fully modular design is achieved by using Simulink/matlab