ParisTech

About: ParisTech is a education organization based out in Paris, France. It is known for research contribution in the topics: Residual stress & Finite element method. The organization has 1888 authors who have published 1965 publications receiving 55532 citations. The organization is also known as: Paris Institute of Technology & ParisTech Développement.

Thermodynamically consistent data-driven computational mechanics

Abstract: In the paradigm of data-intensive science, automated, unsupervised discovering of governing equations for a given physical phenomenon has attracted a lot of attention in several branches of applied sciences. In this work, we propose a method able to avoid the identification of the constitutive equations of complex systems and rather work in a purely numerical manner by employing experimental data. In sharp contrast to most existing techniques, this method does not rely on the assumption on any particular form for the model (other than some fundamental restrictions placed by classical physics such as the second law of thermodynamics, for instance) nor forces the algorithm to find among a predefined set of operators those whose predictions fit best to the available data. Instead, the method is able to identify both the Hamiltonian (conservative) and dissipative parts of the dynamics while satisfying fundamental laws such as energy conservation or positive production of entropy, for instance. The proposed method is tested against some examples of discrete as well as continuum mechanics, whose accurate results demonstrate the validity of the proposed approach.

Precipitation and temperature space–time variability and extremes in the Mediterranean region: evaluation of dynamical and statistical downscaling methods

Abstract: This study evaluates how statistical and dynamical downscaling models as well as combined approach perform in retrieving the space–time variability of near-surface temperature and rainfall, as well as their extremes, over the whole Mediterranean region. The dynamical downscaling model used in this study is the Weather Research and Forecasting (WRF) model with varying land-surface models and resolutions (20 and 50 km) and the statistical tool is the Cumulative Distribution Function-transform (CDF-t). To achieve a spatially resolved downscaling over the Mediterranean basin, the European Climate Assessment and Dataset (ECA&D) gridded dataset is used for calibration and evaluation of the downscaling models. In the frame of HyMeX and MED-CORDEX international programs, the downscaling is performed on ERA-I reanalysis over the 1989–2008 period. The results show that despite local calibration, CDF-t produces more accurate spatial variability of near-surface temperature and rainfall with respect to ECA&D than WRF which solves the three-dimensional equation of conservation. This first suggests that at 20–50 km resolutions, these three-dimensional processes only weakly contribute to the local value of temperature and precipitation with respect to local one-dimensional processes. Calibration of CDF-t at each individual grid point is thus sufficient to reproduce accurately the spatial pattern. A second explanation is the use of gridded data such as ECA&D which smoothes in part the horizontal variability after data interpolation and damps the added value of dynamical downscaling. This explains partly the absence of added-value of the 2-stage downscaling approach which combines statistical and dynamical downscaling models. The temporal variability of statistically downscaled temperature and rainfall is finally strongly driven by the temporal variability of its forcing (here ERA-Interim or WRF simulations). CDF-t is thus efficient as a bias correction tool but does not show any added-value regarding the time variability of the downscaled field. Finally, the quality of the reference observation dataset is a key issue. Comparison of CDF-t calibrated with ECA&D dataset and WRF simulations to local measurements from weather stations not assimilated in ECA&D, shows that the temporal variability of the downscaled data with respect to the local observations is closer to the local measurements than to ECA&D data. This highlights the strong added-value of dynamical downscaling which improves the temporal variability of the atmospheric dynamics with regard to the driving model. This article highlights the benefits and inconveniences emerging from the use of both downscaling techniques for climate research. Our goal is to contribute to the discussion on the use of downscaling tools to assess the impact of climate change on regional scales.

The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight

Abstract: This paper analyzes the transition costs of moving towards a low carbon society when the second-best nature of the economy is accounted for. We emphasize the consequences on mitigation costs of considering the interplay between a) technical systems inertia, including slow infrastructure turnover in transportation and construction; and b) imperfect foresight influencing investment decisions. To this end, the hybrid general equilibrium modeling framework Imaclim-R is employed as it allows for transitory partial adjustments of the economy and captures their impact on the dynamics of economic growth. The modeling exercise quantitatively emphasizes the a) specific risks that the interplay between inertia and imperfect foresight leads to high macroeconomic costs of carbon abatement measures; b) opportunities of co-benefits from climate policies permitted by the correction of sub-optimalities in the reference scenarios. The article draws insights for the framing of future climate architectures by studying the role of measures that act complementarily to carbon pricing in the transport sector. In particular, reallocating public investment towards low-carbon transport infrastructure significantly reduces the overall macroeconomic costs of a given GHG stabilization target and even creates the room for long-term net economic benefits from climate policies.

Ultrasound elastography: Advantages, limitations and artefacts of the different techniques from a study on a phantom

Abstract: Ultrasound elastography is a technique currently under development. Its use in clinical practice is complicated because of the wide range of techniques used by the different manufacturers and the parameters proposed to characterise tissues. A comparative analysis on five ultrasound diagnostic systems has been performed on a calibrated elasticity phantom and demonstrated that: (1) all systems tested are reliable for simple qualitative analysis: is a nodule present and is it harder or softer than neighbouring tissues? (2) the deformation or hardness ratios between two regions are usually, however, not proportional to the theoretical ratios and only a binary analysis greater than 1 (harder) and less than 1 (softer) is reliable and could be used as a negative predictive value (NPV) for malignant lesions, as has been suggested by some authors; (3) finally, quantitative analysis using shear wave techniques performed variably, reliable measurements being obtained with only one of the systems. Measurements produced by these different systems must not be compared in clinical practice to monitor a patient and the threshold values proposed in the literature must only be used in an analysis carried out with the same system and same probe.