Solar energy is a clean energy, renewable, and available for the long term. The tool used to convert the energy generated from the intensity of sunlight into electricity is photovoltaic panels. However, due to the high cost and low efficiency, the use of the energy is still kind small compared to other types of energy sources. Thus, the need for an effective and flexible models, which resemble the characteristics of the actual photovoltaic (PV), so that we can perform simple manipulation of some data to figure out how to get the maximum performance possible. The characteristic of the solar panel output is specific and non-linear, it depend on the solar irradiation and the temperature of the solar panel. Because of it, it makes us difficult to get the Maximum Power Point (or abbreviated MPP) of the solar panels. Approach: Therefore, to solve these problems required the modeling of the solar panel for design and simulate the algorithms of Maximum Power Point Tracking (MPPT) to maintain the working point of solar panels fixed on the MPP. Overall, the designed system results carried are running well. The increase in the average value of the output voltage by 17%, from an average of 11.6 V before installation into 13.94 V after installation MPPT system. It also occurs in output power with an increase of 28%, from an average of 35.13 W before installing system MPPT into 48.9 W after installation MPPT system. The temperature effect on module voltage and output power before and after installation of the MPPT system that after the installation of the MPPT system, the voltage output of photovoltaic modules can be maintained around the desired maximum value that's equal to 12 V. But there was a drop in output power value compared to the prior installation MPPT system. This is caused by the output current value that cannot accommodate the value of the output voltage. So that the value of the output current is enough to produce the maximum output power is needed quantities corresponding load.
Water quality parameters can be indicators of pollution driving riverine, estuarine and coastal resource degradation. This study evaluated water quality in the downstream, estuarine and surrounding coastal waters of 8 major rivers around the western, southern and eastern coasts of South Sulawesi Province, Indonesia. Data on physical and chemical parameters (salinity, temperature, total dissolved solids (TDS), conductivity, turbidity, pH, dissolved oxygen (DO), nitrate and ammonium) were collected during January 2020. These data were interpolated and mapped using the Kriging tool in ArcGIS 9.3 and analysed using the STORET scale and principle component analysis (PCA). STORET values indicate moderate to heavy pollution, with the most severe pollution in Makassar City. Dominant defining parameters based on the PCA were nitrate, ammonium and DO at the Malili and Makassar sites, pH, temperature, TDS and salinity at the Palopo, Bulukumba and Pangkep sites, conductivity at the Takalar site and turbidity at the Pinrang site.
This paper estimated the propulsive power required for Wing in Ground effect (WIG) craft to take-off. The hull form design of the WIG craft incorporates a stepped planing triple hull, since the planing hull is well known to give result and assist in lifting off the water surface effect. In order to determine the power required for WIG craft to take-off, the craft prototype was built into 1 to 6 model scale. In numerical calculation, the required thrust motor of model to take-off was calculated by summation of water drag; aerodynamic drag and the weight of model. The water drag was estimated by Savitsky’s method, and the aerodynamic drag by a MATLAB programming based on Vortex Lattice Method (VLM). In the experiments, the relationship propeller RPM against thrust motor was obtained from the calibration tests. At the flight tests of the model, the propeller RPM of the model was measured to determine the total thrust motor and the propulsive power required to take-off by using the Froude’s Momentum Theory. The required propulsive power for craft scaled model was found to give the total thrusts of 33.85 N, and the effective power estimates required for WIG model to take-off per propeller was 128Watt at the design speed. It was also observed during most of the flight tests, the craft is attempting to enter into ground surface effect at design speed. Kertas kerja ini mengira jumlah kuasa bagi bot Wing in Ground effect (WIG) untuk terbang. Perekabentuk bot WIG menggunakan badan bot planing, yang terkenal untuk membantu dan mengangkat badan bot ke atas permukaan air. Dalam mendapatkan kuasa bagi bot WIG untuk terbang, model bot dibina dalam skala 1 berbanding 6. Pengiraan kuasa bagi model WIG adalah pengiraan jumlah rintangan model pada setiap halaju, terhadap tambahan rintangan udara, rintangan air dengan jisim model. Kaedah yang digunakan dalam pengiraan jumlah rintangan model adalah dua kaedah iaitu kaedah berangka dan eksperimen. Dari kaedah berangka, rintangan air telah dikira menggunakan simulasi Savitsky, dan rintangan udara telah dikira menggunakan simulasi MATLAB berasaskan kaedah Vortex Lattice Method (VLM). Dari kaedah eksperimen, ujian kalibrasi dilakukan terlebih dahulu untuk mendapatkan hubungan antara RPM melawan daya dorong. Kemudian ujian terbang dilakukan untuk mendapatkan RPM untuk setiap halaju model sebelum terbang. Nilai RPM daripada ujian ini digunakan untuk mendapatkan jumlah daya dorong daripada ujian kalibrasi dan jumlah kuasa didapatkan dengan menggunakan persamaan hukum Froude’s Momentum. Keputusan jumlah daya dorong bagi model diperlukan untuk terbang daripada dua kaedah adalah 33.85 N, dan jumlah kuasa untuk satu kipas iaitu 128Watt. Daripada pengamatan ujian terbang, model WIG telah terbang dalam Ground Effect (GE) di atas permukaan air.
Marine debris is defined as material that is solid, persistent, manufactured or processed, and deliberately or not-deliberately left in the marine environment. Marine debris comes in many shapes and forms, ranging in size from microscopic microplastics to large vessels. Marine debris is a big and growing global problem, pose threats to marine life sustainability. Plastic is a major component of marine debris, and single-use packaging accounts for an increasing part of the global marine debris load. Research on marine debris was conducted on coastal areas and Small Island of South Sulawesi destined for local tourism, i.e., Karama beach, Bodia beach and Mandi beach (Galesong, Takalar District), Tanjung Bayang beach, Akkarena beach and Lae-lae island/also known as Bob beach (Makassar City). This research was aimed at identifying marine debris according to its types, size, and mass. Debris was collected in a 25 x 60 m transect with direction 30 m towards land and waters, respectively, with 3 replication transects at every location, whilst collections of debris were conducted during low and high tides. Current (direction and speed) and waves (incoming direction and height) were also measured as supporting parameters. Surrounding sampling location characteristics were also recorded. The result showed that Karama beach is found with highest total marine debris mass in Takalar (36.44 kg), whilst in Makassar, the Lae-lae island was found to be the highest with debris mass (43.22 kg). Plastic was predominant debris at all sampling locations with percentages of 62.7 – 86.6%. Lastly, the predominant size was macro-debris (25-100 cm).
Phytoplankton are primary producers that can be used as seawater condition indicators. Certain phytoplankton can proliferate, causing harmful algal blooms (HABs). The coastal waters of South Sulawesi, Indonesia are under pressure from land-based processes and activities resulting in inputs of organic and inorganic materials. This study analysed phytoplankton diversity and abundance in coastal waters around South Sulawesi. Phytoplankton were sampled and seawater parameters (salinity, temperature, turbidity, pH, nitrate concentration) measured in-situ at six stations around seven major river estuaries in three seaways (Makassar Strait, Flores Sea, Gulf of Bone). Phytoplankton taxonomic composition, abundance and indices of diversity (H’), evenness (E), and dominance (D) were analysed. Phytoplankton from 31 species and three classes (Bacillariophyceae, Cyanophyceae, Dinophyceae) were identified. Phytoplankton abundance and community structure differed significantly between sites and seaways but were not significantly correlated with water quality parameters although Dinophyceae abundance correlated significantly with observed pollution levels. Phytoplankton abundance was strongly influenced by the Dinophyceae, especially Ceratium furca, a potential HAB species; Cyanophyceae had the strongest influence on species richness but least on community structure. C. furca abundance was strongly correlated negatively with species richness, H’ and E, and positively with D, indicating negative impacts of this species on phytoplankton communities.
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