Meningkatan Hasil Belajar Matematika Materi Volume Bangun Ruang Sisi Lengkung Dengan Model {Pembelajaran Discovery Learning Siswa Kelas IX B SMP Don Bosco Kota Sorong

Tujuan dalam penelitian ini yaitu untuk mengetahui peningkatan hasil belajar matematika materi  Volume Bangun Ruang Sisi Lengkung Siswa Kelas IX B SMP Don Bosco Kota Sorong melalui model pembelajaran Discovery Learning. Jenis penelitian ini adalah penelitian tindakan kelas (Classroom Action Research) yang dilakukan secara kolaboratif antara peneliti dengan guru. Penelitian dilaksanakan dalam dua siklus, masing-masing siklus terdiri dari empat komponen yaitu perencanaan, tindakan, pengamatan dan refleksi. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah wawancara, observasi, dokumentasi dan tes. Analisis yang data dilakukan dalam 3 tahap yaitu reduksi, penyajian data serta menarik kesimpulan. Hasil penelitian menunjukkan bahwa: (a) penggunaan pendekatan saintifik dapat meningkatkan partisipasi belajar siswa. (b) Pemanfaatan model pembelajaran Discovery Learning dapat meningkatkan prestasi belajar siswa. Rata-rata hasil belajar siswa pada siklus I sebesar 69,06  meningkat menjadi 79,06  pada siklus II

Revisiting the assumptions and implementation details of the BAY model for vortex generator flows

Today, Vortex Generators (VGs) are becoming an integral part of a Wind Turbine blade design. However, the challenges involved in the computation of the flow around VGs are yet to be dealt with in a satisfactory manner. A large number of VG models for Reynolds Averaged Navier Stokes (RANS) solvers has been proposed and, among them, the Bender–Anderson–Yagle (BAY) model (ASME Pap. FEDSM99-6919) is one of the most popular, due to its ease of use and relatively low requirements for user input. In the present paper a thorough investigation on the performance and application of the BAY model for aerodynamic VG flows is presented. A fully resolved RANS simulation is validated against experiments and then used as a benchmark for the BAY model simulations. A case relevant to wind turbines is examined, which deals with the flow past a wind turbine airfoil at Reynolds number 0.87e6. When the grid related errors are excluded, it is found that the generated vortices are weaker in the BAY model simulations than in the fully resolved computation. The latter finding is linked to an inherent deficiency of the model, which is first found in this study and which is explained in detail

The CO2 record at the Amazon Tall Tower Observatory : A new opportunity to study processes on seasonal and inter-annual scales

High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2. In this study, we present the first 6 years (2014-2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1 degrees S, 58.9 degrees W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal (Delta CO2obs) that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between Delta CO2obs and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of Delta CO2obs. In addition, we present how the 2015-2016 El Nino-induced drought was captured by our atmospheric record as a positive 2 sigma anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of Delta CO2obs together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.Peer reviewe

Experimental benchmark and code validation for airfoils equipped with passive vortex generators

Experimental results and complimentary computations for airfoils with vortex generators are compared in this paper, as part of an effort within the AVATAR project to develop tools for wind turbine blade control devices. Measurements from two airfoils equipped with passive vortex generators, a 30% thick DU97W300 and an 18% thick NTUA T18 have been used for benchmarking several simulation tools. These tools span low-to-high complexity, ranging from engineering-level integral boundary layer tools to fully-resolved computational fluid dynamics codes. Results indicate that with appropriate calibration, engineering-type tools can capture the effects of vortex generators and outperform more complex tools. Fully resolved CFD comes at a much higher computational cost and does not necessarily capture the increased lift due to the VGs. However, in lieu of the limited experimental data available for calibration, high fidelity tools are still required for assessing the effect of vortex generators on airfoil performance

The CO2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter-annual scales

Abstract High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2. In this study, we present the first 6 years (2014?2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1°S, 58.9°W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal () that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of . In addition, we present how the 2015?2016 El Niño-induced drought was captured by our atmospheric record as a positive 2σ anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales

The CO2 Human Emissions (CHE) Project: First steps towards a European operational capacity to monitor anthropogenic CO2 emissions

The Paris Agreement of the United Nations Framework Convention on Climate Change is a binding international treaty signed by 196 nations to limit their greenhouse gas emissions through ever-reducing Nationally Determined Contributions and a system of 5-yearly Global Stocktakes in an Enhanced Transparency Framework. To support this process, the European Commission initiated the design and development of a new Copernicus service element that will use Earth observations mainly to monitor anthropogenic carbon dioxide (CO2) emissions. The CO2 Human Emissions (CHE) project has been successfully coordinating efforts of its 22 consortium partners, to advance the development of a European CO2 monitoring and verification support (CO2MVS) capacity for anthropogenic CO2 emissions. Several project achievements are presented and discussed here as examples. The CHE project has developed an enhanced capability to produce global, regional and local CO2 simulations, with a focus on the representation of anthropogenic sources. The project has achieved advances towards a CO2 global inversion capability at high resolution to connect atmospheric concentrations to surface emissions. CHE has also demonstrated the use of Earth observations (satellite and ground-based) as well as proxy data for human activity to constrain uncertainties and to enhance the timeliness of CO2 monitoring. High-resolution global simulations (at 9 km) covering the whole of 2015 (labelled CHE nature runs) fed regional and local simulations over Europe (at 5 km and 1 km resolution) and supported the generation of synthetic satellite observations simulating the contribution of a future dedicated Copernicus CO2 Monitoring Mission (CO2M

Global Carbon Budget 2020

Accurate assessment of anthropogenic carbon dioxide (CO$_{2}$) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO$_{2}$ emissions (E$_{FOS}$) are based on energy statistics and cement production data, while emissions from land-use change (E$_{LUC}$), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO$_{2}$ concentration is measured directly and its growth rate (G$_{ATM}$) is computed from the annual changes in concentration. The ocean CO$_{2}$ sink (S$_{OCEAN}$) and terrestrial CO$_{2}$ sink (S$_{LAND}$) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B$_{IM}$), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), E$_{FOS}$ was 9.6 ± 0.5 GtC yr$^{-1}$ excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and E$_{LUC}$ was 1.6 ± 0.7 GtC yr$^{-1}$. For the same decade, G$_{ATM}$ was 5.1 ± 0.02 GtC yr$^{-1}$ (2.4 ± 0.01 ppm yr$_{-1}$), S$_{OCEAN}$ 2.5 ±  0.6 GtC yr$^{-1}$, and S$_{LAND}$ 3.4 ± 0.9 GtC yr$^{-1}$, with a budget imbalance B$_{IM}$ of −0.1 GtC yr$^{-1}$ indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in E$_{FOS}$ was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr$^{-1}$ excluding the cement carbonation sink (9.7 ± 0.5 GtC yr$^{-1}$ when cement carbonation sink is included), and E$_{LUC}$ was 1.8 ± 0.7 GtC yr$^{-1}$, for total anthropogenic CO$_{2}$ emissions of 11.5 ± 0.9 GtC yr$^{-1}$ (42.2 ± 3.3 GtCO$_{2}$). Also for 2019, G$_{ATM}$ was 5.4 ± 0.2 GtC yr$^{-1}$ (2.5 ± 0.1 ppm yr$^{-1}$), S$_{OCEAN}$ was 2.6 ± 0.6 GtC yr$^{-1}$, and S$_{LAND}$ was 3.1 ± 1.2 GtC yr$^{-1}$, with a B$_{IM}$ of 0.3 GtC. The global atmospheric CO$_{2}$ concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in E$_{FOS}$ relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr$^{-1}$ persist for the representation of semi-decadal variability in CO$_{2}$ fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO$_{2}$ flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020)

Computing the flow past Vortex Generators: Comparison between RANS Simulations and Experiments

The flow around a wind turbine airfoil equipped with Vortex Generators (VGs) is examined. Predictions from three different Reynolds Averaged Navier Stokes (RANS) solvers with two different turbulence models and two different VG modelling approaches are compared between them and with experimental data. The best results are obtained with the more expensive fully resolved VG approach. The cost efficient BAY model can also provide acceptable results, if grid related numerical diffusion is minimized and only force coefficient polars are considered