Drawing ER diagrams with TikZ

in Ars TeXnica (2013), 15

The paper will illustrate some techniques to represent Entity-Relationship (ER) diagrams with TikZ. In particular, it will focus on the standard internal library \library{er}, on the external package TikZ ... [more ▼]

The paper will illustrate some techniques to represent Entity-Relationship (ER) diagrams with TikZ. In particular, it will focus on the standard internal library \library{er}, on the external package TikZ-er2, on the external tool Graphviz and on the object-oriented approach provided by the er-oo library. [less ▲]

A Dual-Grid Multiscale Approach to CFD-DEM Couplings for Multiphase Flow

Doctoral thesis (2018)

This thesis focuses on a novel dual-grid multiscale approach to CFD- DEM1 couplings, proposes its advantages in terms of numerical proper- ties and performance, and provides examples of engineering ... [more ▼]

This thesis focuses on a novel dual-grid multiscale approach to CFD- DEM1 couplings, proposes its advantages in terms of numerical proper- ties and performance, and provides examples of engineering applications that can benefit from it. In recent years, CFD-DEM couplings are be- coming a more and more adopted solution for the numerical simulation of particle-laden flows. In particular, couplings based on the volume av- eraging technique have become a standard for numerical simulations in chemical and process engineering. Furthermore, they are rapidly spread- ing to civil, geotechnical and mechanical applications due to their ability in dealing with arbitrarily complex mixtures of continuum and granular media. Despite the several advantages that these Eulerian-Lagrangian cou- plings provide, their rigorous application to complex scenarios is currently limited by two main factors. First, the computational traceability of the solutions can become problematic due to the lack of a general theory on the subject. In particular, grid-convergence studies for the solution of the continuous phases are often not feasible due to the averaging procedure that imposes limitations on the grid structure and refinement. Second, the parallel implementation of these numerical schemes holds important disadvantages in terms of memory consumption and inter-physics com- munication load. These disadvantages are significantly limiting the ex- tension of these approaches to large-scale scenarios. This thesis collects some of the most significant works published in the last years on a novel approach that allows solving the two above- mentioned problems, and, therefore, tackling more complex and expen- sive scenarios. I refer to this approach as dual-grid multiscale approach for CFD-DEM couplings. It consists in using two different computational grids, one for the coupling between continuum and discrete entities and one for the solution of the so-obtained continuum equations. The two grids, i.e. the two problems, are in this way resolved on two different scales. The first scale or “bulk” scale is chosen to optimize the averag- ing operation. At this length-scale, the discrete entities are considered as zero-dimensional, and interact with the fluid with local exchanges of momentum, mass, and energy. The second scale or “fluid-fine” scale is identified as the one at which a unique solution for the averaged equa- tions can be provided. In practice, this is chosen as the one at which the solution of the fluid equations becomes grid-independent. An inter-scale communication is adopted by interpolating fields from the fluid-fine scale to the bulk one and vice-versa. The theoretical description of the method is first provided with par- ticular reference to the DEM-VOF coupling. Even in its simplest version, the multiscale approach is shown to generate grid-convergent solutions and significantly higher accuracy than a standard CFD-DEM coupling. This shows how the new approach is able to overcome the first main limitation described above. Then, an optimized parallel implementation of the method is pro- posed to show how this multiscale approach can provide significant ben- efits also for what concerns the execution time. Technically, this is made possible by moving the communication cost of the coupling from the inter-physics communication that characterized the standard CFD-DEM couplings to an optimized inter-scale communication routine. This en- ables the method to overcome a major bottleneck of the parallel execution of CFD-DEM couplings and therefore the second main limitation of those schemes. Finally, the dual-grid multiscale method is applied to approach in- dustrially relevant problems that were till now out-of-reach for standard CFD-DEM couplings, proving how this technique can have direct real- case application and produce immediate benefits for practitioners willing to adopt it. [less ▲]

Dynamic Modal Split Incorporating Trip Chaining: A Parsimonious Approach to Mode-Specific Demand Estimation

in Transportation Research Procedia (2021)

Dynamic modeling of VISSIM's critical gap parameter at unsignalized intersections

in Transportation Research Record: Journal of the Transportation Research Board (2014), 2395

Dynamic neural network approach for atmospheric pollutant prediction: A pulp mill case study

Scientific Conference (2011, May 27)

Dynamic Origin-Destination Matrix Estimation on Large-Scale Congested Networks Using A Hierarchical Decomposition Scheme

in Journal of Intelligent Transportation Systems (2014), 18(1), 51-66

Despite the ever increasing computing power, dynamic Origin-Destination (OD) estimation in congested networks remains troublesome. In previous research, we have shown that an unbiased estimation requires ... [more ▼]

Despite the ever increasing computing power, dynamic Origin-Destination (OD) estimation in congested networks remains troublesome. In previous research, we have shown that an unbiased estimation requires the calculation of the sensitivity of the link flows to all Origin Destination flows, in order to incorporate the effects of congestion spillback. This is however computationally infeasible for large-scale networks. To overcome this issue, we propose a hierarchical approach for off-line application that decomposes the dynamic OD estimation procedure in space. The main idea is to perform a more accurate dynamic OD estimation only on subareas where there is congestion spillback. The output of this estimation is then used as input for the OD estimation on the whole network. This hierarchical approach solves many practical and theoretical limitations of traditional OD estimation methods. The main advantage is that different OD estimation method can be used for different parts of the network as necessary. This allows applying more advanced and accurate, but more time consuming methods only where necessary. The hierarchical approach is tested on a study network and on a real network. In both cases the proposed methodology performs better than traditional OD estimation approaches, indicating its merit. [less ▲]

Dynamic pricing using wavelet neural network under uncertain demands

in Decision Science Letters (2017)

Dynamical differential expression (DyDE) reveals the period control mechanisms of the Arabidopsis circadian oscillator

in PLoS Computational Biology (2019)

The circadian oscillator, an internal time-keeping device found in most organisms, enables timely regulation of daily biological activities by maintaining synchrony with the external environment. The ... [more ▼]

The circadian oscillator, an internal time-keeping device found in most organisms, enables timely regulation of daily biological activities by maintaining synchrony with the external environment. The mechanistic basis underlying the adjustment of circadian rhythms to changing external conditions, however, has yet to be clearly elucidated. We explored the mechanism of action of nicotinamide in Arabidopsis thaliana, a metabolite that lengthens the period of circadian rhythms, to understand the regulation of circadian period. To identify the key mechanisms involved in the circadian response to nicotinamide, we developed a systematic and practical modeling framework based on the identification and comparison of gene regulatory dynamics. Our mathematical predictions, confirmed by experimentation, identified key transcriptional regulatory mechanisms of circadian period and uncovered the role of blue light in the response of the circadian oscillator to nicotinamide. We suggest that our methodology could be adapted to predict mechanisms of drug action in complex biological systems. [less ▲]

Dynamical structure analysis of sparsity and minimality heuristics for reconstruction of biochemical networks

in The proceedings of the 47th IEEE Conference on Decision and Control (2008)

Network reconstruction, i.e. obtaining network structure from input-output information, is a central theme in systems biology. A variety of approaches aim to obtaining structural information from ... [more ▼]

Network reconstruction, i.e. obtaining network structure from input-output information, is a central theme in systems biology. A variety of approaches aim to obtaining structural information from available data. Previous work has introduced dynamical structure functions as a tool for posing and solving the network reconstruction problem. Even for linear time invariant systems, reconstruction requires specific additional information not generated in the typical system identification process. This paper demonstrates that such extra information can be obtained through a limited sequence of system identification experiments on structurally modified systems, analogous to gene silencing and overexpression experiments. In the absence of such extra information, we discuss whether combined assumptions of network sparsity and minimality contribute to the recovery of the network dynamical structure. We provide sufficient conditions for a transfer function to have a completely decoupled minimal realization, and demonstrate that every transfer function is arbitrarily close to one that admits a perfectly decoupled minimal realization. This indicates that the assumptions of sparsity and minimality alone do not lend insight into the network structure. [less ▲]

Dynamical structure functions for the reverse engineering of LTI networks

in Proceedings of the 46th IEEE Conference on Decision and Control (2007)

This research explores the role and representation of network structure for LTI systems with partial state observations. We demonstrate that input-output representations, i.e. transfer functions, contain ... [more ▼]

This research explores the role and representation of network structure for LTI systems with partial state observations. We demonstrate that input-output representations, i.e. transfer functions, contain no internal structural information of the system. We further show that neither the additional knowledge of system order nor minimality of the true realization is generally sufficient to characterize network structure. We then introduce dynamical structure functions as an alternative, graphical-model based representation of LTI systems that contain both dynamical and structural information of the system. The main result uses dynamical structure to precisely characterize the additional information required to obtain network structure from the transfer function of the system. [less ▲]