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Initial release

This repository contains the original source code of the 3D-CMCC-FEM model developed by A. Collalti et al 2013, the model inputs, the model outputs and validation outputs related to the manuscript entitled "Feasibility of enhancing carbon sequestration and stock capacity in temperate and boreal European forests via changes to management regimes" {"references": ["Collalti A, Perugini L, Santini M, Chiti T, Nol\u00e8 A, Matteucci G, Valentini R et al. A process-based model to simulate growth in forests with complex structure: Evaluation and use of 3D-CMCC Forest Ecosystem Model in a deciduous forest in Central Italy. Ecological Modelling,272,362-378,2013"]}

This is the first release of a simple module to plot energy profile diagrams using Python and matplotlib.

The simulation of offshore wind turbines requires the definition of a long-term statistical representation of the environmental conditions in the installation site. To certify a wind turbine for offshore use, a set of design load cases (DLCs) must be simulated. Although international standards [1] define these conditions, finding ready-to-use and complete environmental conditions for such studies can be difficult. This work provides a working example of how to derive environmental conditions for offshore wind turbine simulation using only open-source tools. Data is sourced from the ERA5 reanalysis database [2] and processed using Virocon [3]. Folder contents "01 Derivation of Met-Ocean Conditions for FOWT simulation.py" - Python script to obtain environmental condtions for an offshore site. Example provided for EU site off of Barra Island (Scotland) "02 ERA5_WoB_2000.py" - Python script example to downlod hourly data samples of wind speed at 10 and 100 above sea water level, significant wave height, peak spectral period and mean wave direction from ERA5 reanalysis database for year 2000 "03 MetOcean_WoB_ERA5" - Post-processed ready-to-use environmental conditions for simulation of Offshore (Floating) wind turbines. Data from EU site off of Barra Island (Scotland). "04 arraydescription_pdfWoB.json", "04 arrayvalues_pdfWoB", "04 README_pdfWoB" - 4-D Array containing probability of each wind speed - significan wave height - peak spectral period and wind-wave misalignment bin. The procedure is explained in detail in [4]. {"references": ["International Electrotechnical Commission 2019 IEC 61400-1: Wind energy generation systems. Design requirements Part 1 Part 1", "Hersbach H, et al.,\u00a02020, The ERA5 global reanalysis Q. J. R. Meteorol. Soc. 146 1999\u20132049", "Haselsteiner A F, Lehmkuhl J, Pape T, Windmeier K-L and Thoben K-D 2019 ViroCon: A software to compute multivariate extremes using the environmental contour method SoftwareX 9 95\u2013101", "Papi, F., Perignon, Y., Bianchini, A.,\u00a0Derivation of Met-Ocean Conditions for the Simulation of Floating Wind Turbines: a European case study, IOP Journal of Science: Conference Series, Proceedings of ATI 2022 conference, Bari, 12-15 Sep. 2022"]}

{"references": ["Collalti A, Perugini L, Santini M, Chiti T, Nol\u00e8 A, Matteucci G, Valentini R et al. A process-based model to simulate growth in forests with complex structure: Evaluation and use of 3D-CMCC Forest Ecosystem Model in a deciduous forest in Central Italy. Ecological Modelling,272,362-378,2013"]} This repository contains the original source code of the 3D-CMCC-FEM model developed by A. Collalti et al 2013, the model inputs, the model outputs and validation outputs related to the manuscript entitled "No leeway to enhance carbon sequestration and stock capacity via changes to forest management"

Botoks is a batteryless timekeeping sensor that operates intermittently harvesting ambient energy. Botoks's hardware and software components enable IoT applications that require precise and intermittency-safe timekeeping. The cascaded hierarchical remanence timekeeper (CHRT) embedded on Botoks is a novel remanence timekeeper architecture. In principle, capacitive remanence timekeepers are simple RC circuits whose energy level is converted into time. To know more about them and the CHRT, refer to our paper (to be made public) and the docs.

This study addresses the complex problem of task scheduling and battery management within the context of the Edge-to-Cloud continuum. Our proposed approach incorporates multi-objective optimization, which encompasses power management in addition to real-time processing demands, to ensure both performance and sustainability. Our methodology takes into account the heterogeneity of nodes and dynamically organizes jobs to meet user-specified processing requirements. This is achieved through the utilization of online Reinforcement Learning, a machine learning technique that enables the system to learn and adapt to the dynamic environment in real-time.

Matlab code for simulating the evolution of river alternate bars under different climate change scenarios ->as detailed in the manuscript: Redolfi, M., Carlin, M. & Tubino, M. The impact of climate change on river alternate bars. Geophysical Research Letters. *Originally developed by Mattia Carlin; revised and reorganized by Marco Redolfi *The code is developed using Matlab R2022a under Linux Ubuntu and MS Windows *Please note that this is a research code, not fully tested! *Simply run: ->main.m to perform simulations for the two reaches in all scenarios ->plotting_basic.m to visualize basic results for individual simulations ->change_factors_HYDROCH.m to visualize yearly variation of change factors *For further questions please contact marco.redolfi@unitn.it {"references": ["Redolfi, M., Carlin, M. & Tubino, M. The impact of climate change on river alternate bars. Geophysical Research Letters."]}