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Institution

Polytechnic University of Milan

EducationMilan, Italy
About: Polytechnic University of Milan is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Finite element method & Population. The organization has 18231 authors who have published 58416 publications receiving 1229711 citations. The organization is also known as: PoliMi & L-NESS.


Papers
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Journal ArticleDOI
TL;DR: The impact that features have on different phases of the life cycle is discussed, some ideas on how these phases can be improved by fully exploiting the concept of feature are provided, and topics for a research agenda in feature engineering are suggested.

225 citations

Journal ArticleDOI
TL;DR: In this article, a round-robin program has been undertaken to assess the compatibility in the micromechanical techniques used to evaluate the interfacial shear strength of the fiber/matrix bond in composite materials.

225 citations

Journal ArticleDOI
TL;DR: In this paper, the authors propose four different vendor selection systems (VSSs) depending on the time frame (short-term versus long-term) and on the content (logistic versus strategic) of the co-operative customer/supplier relationships.
Abstract: Literature on supply chain management has been recently stressing the need for co‐operation and integration between suppliers and customers, highlighting the critical role played by the supplier in contributing to the overall performance of the purchaser. Consequently supplier selection is one of the purchasing manager’s most critical tasks, as demonstrated by the number of articles that have dealt with vendor selection criteria and techniques in the light of the requirements of the new environment. The paper proposes four different vendor selection systems (VSSs) depending on the time frame (short‐term versus long‐term) and on the content (logistic versus strategic) of the co‐operative customer/supplier relationships. More precisely, the suggested VSSs consider, in an analytic hierarchy process framework, different sets of measures, deriving from a non‐conventional model of the supplier based on the dynamic system and on the resource‐based approach.

225 citations

Journal ArticleDOI
TL;DR: In this paper, the authors combine a process-based crop water model with maps of spatially interpolated yields for 14 major food crops to identify potential differences in food production and water use between current and optimized crop distributions.
Abstract: Growing demand for agricultural commodities for food, fuel and other uses is expected to be met through an intensification of production on lands that are currently under cultivation. Intensification typically entails investments in modern technology — such as irrigation or fertilizers — and increases in cropping frequency in regions suitable for multiple growing seasons. Here we combine a process-based crop water model with maps of spatially interpolated yields for 14 major food crops to identify potential differences in food production and water use between current and optimized crop distributions. We find that the current distribution of crops around the world neither attains maximum production nor minimum water use. We identify possible alternative configurations of the agricultural landscape that, by reshaping the global distribution of crops within current rainfed and irrigated croplands based on total water consumption, would feed an additional 825 million people while reducing the consumptive use of rainwater and irrigation water by 14% and 12%, respectively. Such an optimization process does not entail a loss of crop diversity, cropland expansion or impacts on nutrient and feed availability. It also does not necessarily invoke massive investments in modern technology that in many regions would require a switch from smallholder farming to large-scale commercial agriculture with important impacts on rural livelihoods. The current distribution of crops around the world neither attains maximum production nor minimum water use, according to a crop water model and yield data. An optimized crop distribution could feed an additional 825 million people and substantially reduce water use.

224 citations

Journal ArticleDOI
TL;DR: In this article, the authors consider sinusoidal waves of spanwise velocity which vary in time and are modulated in space along the streamwise direction, so that the phase speed may be null, positive or negative, and the waves may be either stationary or travelling forward or backward in the direction of the mean flow.
Abstract: Waves of spanwise velocity imposed at the walls of a plane turbulent channel flow are studied by direct numerical simulations. We consider sinusoidal waves of spanwise velocity which vary in time and are modulated in space along the streamwise direction. The phase speed may be null, positive or negative, so that the waves may be either stationary or travelling forward or backward in the direction of the mean flow. Such a forcing includes as particular cases two known techniques for reducing friction drag: the oscillating wall technique (a travelling wave with infinite phase speed) and the recently proposed steady distribution of spanwise velocity (a wave with zero phase speed). The travelling waves alter the friction drag significantly. Waves which slowly travel forward produce a large reduction of drag that can relaminarize the flow at low values of the Reynolds number. Faster waves yield a totally different outcome, i.e. drag increase (DI). Even faster waves produce a drag reduction (DR) effect again. Backward-travelling waves instead lead to DR at any speed. The travelling waves, when they reduce drag, operate in similar fashion to the oscillating wall, with an improved energetic efficiency. DI is observed when the waves travel at a speed comparable with that of the convecting near-wall turbulence structures. A diagram illustrating the different flow behaviours is presented.

224 citations


Authors

Showing all 18743 results

NameH-indexPapersCitations
Alex J. Barker132127384746
Pierluigi Zotto128119778259
Andrea C. Ferrari126636124533
Marco Dorigo10565791418
Marcello Giroletti10355841565
Luciano Gattinoni10361048055
Luca Benini101145347862
Alberto Sangiovanni-Vincentelli9993445201
Surendra P. Shah9971032832
X. Sunney Xie9822544104
Peter Nijkamp97240750826
Nicola Neri92112241986
Ursula Keller9293433229
A. Rizzi9165340038
Martin J. Blunt8948529225
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023302
2022811
20214,151
20204,301
20193,831
20183,767