Projeto de arborização da praça da Torre do Castelo.

Em virtude da comemoração dos 240 anos da cidade de Campinas, a Embrapa Monitoramento por Satélite e o Núcleo de Estudos e Pesquisas Ambientais da Universidade Estadual de Campinas (Nepam/Unicamp) apresentam um projeto para rearborizar a Praça da Torre do Castelo, um dos principais cartões postais da cidade. A partir das informações históricas da vegetação de Campinas e de pesquisas com moradores e frequentadores do local, criou-se um projeto que insere espécies nativas regionais, com coerência de cores e de estilo e respeito a arquitetura do local e a segurança dos transeuntes.bitstream/item/103780/1/DC-105.pd

Greedy kernel methods for accelerating implicit integrators for parametric ODEs

We present a novel acceleration method for the solution of parametric ODEs by single-step implicit solvers by means of greedy kernel-based surrogate models. In an offline phase, a set of trajectories is precomputed with a high-accuracy ODE solver for a selected set of parameter samples, and used to train a kernel model which predicts the next point in the trajectory as a function of the last one. This model is cheap to evaluate, and it is used in an online phase for new parameter samples to provide a good initialization point for the nonlinear solver of the implicit integrator. The accuracy of the surrogate reflects into a reduction of the number of iterations until convergence of the solver, thus providing an overall speedup of the full simulation. Interestingly, in addition to providing an acceleration, the accuracy of the solution is maintained, since the ODE solver is still used to guarantee the required precision. Although the method can be applied to a large variety of solvers and different ODEs, we will present in details its use with the Implicit Euler method for the solution of the Burgers equation, which results to be a meaningful test case to demonstrate the method's features

Interpolation with uncoupled separable matrix-valued kernels

In this paper we consider the problem of approximating vector-valued functions over a domain Ω. For this purpose, we use matrix-valued reproducing kernels, which can be related to Reproducing kernel Hilbert spaces of vectorial functions and which can be viewed as an extension of the scalar-valued case. These spaces seem promising, when modelling correlations between the target function components, as the components are not learned independently of each other. We focus on the interpolation with such matrix-valued kernels. We derive error bounds for the interpolation error in terms of a generalized power-function and we introduce a subclass of matrix-valued kernels whose power-functions can be traced back to the power-function of scalar-valued reproducing kernels. Finally, we apply these kind of kernels to some artificial data to illustrate the benefit of interpolation with matrix-valued kernels in comparison to a componentwise approach

Validation of the GATE Monte Carlo simulation platform for modelling a CsI(Tl) scintillation camera dedicated to small animal imaging

Monte Carlo simulations are increasingly used in scintigraphic imaging to model imaging systems and to develop and assess tomographic reconstruction algorithms and correction methods for improved image quantitation. GATE (GEANT 4 Application for Tomographic Emission) is a new Monte Carlo simulation platform based on GEANT4 dedicated to nuclear imaging applications. This paper describes the GATE simulation of a prototype of scintillation camera dedicated to small animal imaging and consisting of a CsI(Tl) crystal array coupled to a position sensitive photomultiplier tube. The relevance of GATE to model the camera prototype was assessed by comparing simulated 99mTc point spread functions, energy spectra, sensitivities, scatter fractions and image of a capillary phantom with the corresponding experimental measurements. Results showed an excellent agreement between simulated and experimental data: experimental spatial resolutions were predicted with an error less than 100 mu m. The difference between experimental and simulated system sensitivities for different source-to-collimator distances was within 2%. Simulated and experimental scatter fractions in a [98-182 keV] energy window differed by less than 2% for sources located in water. Simulated and experimental energy spectra agreed very well between 40 and 180 keV. These results demonstrate the ability and flexibility of GATE for simulating original detector designs. The main weakness of GATE concerns the long computation time it requires: this issue is currently under investigation by the GEANT4 and the GATE collaboration

Greedy kernel methods for center manifold approximation

For certain dynamical systems it is possible to significantly simplify the study of stability by means of the center manifold theory. This theory allows to isolate the complicated asymptotic behavior of the system close to a non-hyperbolic equilibrium point, and to obtain meaningful predictions of its behavior by analyzing a reduced dimensional problem. Since the manifold is usually not known, approximation methods are of great interest to obtain qualitative estimates. In this work, we use a data-based greedy kernel method to construct a suitable approximation of the manifold close to the equilibrium. The data are collected by repeated numerical simulation of the full system by means of a high-accuracy solver, which generates sets of discrete trajectories that are then used to construct a surrogate model of the manifold. The method is tested on different examples which show promising performance and good accuracy

Feasibility limits of using low-grade industrial waste heat in symbiotic district heating and cooling networks

Abstract: Low-grade waste heat is an underutilized resource in process industries, which may consider investing in urban symbiosis projects that provide heating and cooling to proximal urban areas through district energy networks. A long distance between industrial areas and residential users is a barrier to the feasibility of such projects, given the high capital intensity of infrastructure, and alternative uses of waste heat, such as power generation, may be more profitable, in spite of limited efficiency. This paper introduces a parametric approach to explore the economic feasibility limits of waste heat-based district heating and cooling (DHC) of remote residential buildings depending on network extension. A parametric model for the comparative water\u2013energy\u2013carbon nexus analysis of waste heat-based DHC and Organic Rankine Cycles is also introduced, and applied to an Italian and to an Austrian setting. The results show that, for a generic 4\ua0MW industrial waste heat flow steadily available at 95\ua0\ub0C, district heating and cooling is the best option from an energy\u2013carbon perspective in both countries. Power generation is the best option in terms of water footprint in most scenarios, and is economically preferable to DHC in Italy. Maximum DHC feasibility threshold distances are in line with literature, and may reach up to 30\ua0km for waste heat flows of 30\ua0MW in Austria. However, preferability threshold distances, above which waste heat-to-power outperforms DHC from an economic viewpoint, are shorter, in the order of 20\ua0km in Austria and 10\ua0km in Italy for 30\ua0MW waste heat flows. Graphic abstract: [Figure not available: see fulltext.]