The aim of this research is to determine the effect of coconut and mineral waste of quail as adsorbents on the biogas purity. This research was designed to use the Completely Randomized Design (CRD) method with 6 treatments and 4 replications and the significant influence will be tested using Duncan Test. The result form this research showed that the use of coconut waste and mineral waste of quail as adsorbents gives highly significant influence (P<0,01) to increase the CH4 gas concentration, highly significant influence (P<0,01) to decrease CO 2 gas concentration, highly significant influence (P<0,01) to decrease gas pressure and highly significant influence (P<0,01) to increase gas flow rate on biogas purity. The conclusion of this research is the use of 100% of activated coal from coconut waste, the use of 50% of activated coal from coconut waste and 50% of mineral waste from quail waste as an adsorbent are able to increase the quality of biogas. However, it is lack of effectiveness due to inappropriate application of biogas purification. It is suggested to do physical activation for both adsorbents in order to avoid saturation of the adsorbent so those absorbents be able to adsorb optimally the impurities gases on biogas.
The purposes of this study are (1) to determine the effect of mordan tawas, tunjung, and tannins on the ecoprint dyeing result using Tingi (Ceriops tagal) dye on primisima fabrics (2) to find the best results in ecoprint dyeing using different types of mordan including the pattern clarity, colour sharpness, colour fairness, and colour absorption. The method of this research is experimental. The independent variables are mordan tawas, tunjung and tannins. The dependent variables are the ecoprint dyeing results including the pattern clarity, colour sharpness, colour fairness, and colour absorption. The control variables are Tingi (Ceriops tagal) dye, mordaning technique, and primisima fabric. The data of the study were collected by using observation. There were 5 ecoprint treatment samples used in the design of this study, i.e. sample A - using mordan tawas on the main fabric, Tingi (Ceriops tagal) dye on blanket and mordan tawas in the fixation; sample B - using mordan tawas on the main fabric, Tingi (Ceriops tagal) dye on the blanket, and mordan tunjung in the fixation; sample C - using mordan tunjung on the main fabric, Tingi (Ceriops tagal) dye on the blanket, and mordan tawas in the fixation; sample D - using mordan tunjung on the main fabric, Tingi (Ceriops tagal) dye on the blanket, and mordan tunjung in the fixation; sample E - using mordan tannin on the main fabric, Tingi (Ceriops tagal) dye on the blanket, and mordan tawas in the fixation; and sample F - using mordan tannin on the main fabric, Tingi (Ceriops tagal) dye on the blanket, and mordan tunjung in the fixation. Based on the test of pattern clarity, colour sharpness, colour fairness, and colour absorption, the best ecoprint treatment is shown in sample A, which is the ecoprint treatment using mordan tawas on the main fabric, Tingi (Ceriops tagal) dye on the blanket, and mordan tawas in the fixation.
Determining the reachable set for a given nonlinear control system is crucial for system control and planning. However, computing such a set is impossible if the system’s dynamics are not fully known. This article is motivated by a scenario where a system suffers an adverse event mid-operation, resulting in a substantial change to the system’s dynamics, rendering them largely unknown. Our objective is to conservatively approximate the system’s reachable set solely from its local dynamics at a single point and the bounds on the rate of change of its dynamics. We translate this knowledge about the system dynamics into an ordinary differential inclusion. We then derive an underapproximation of the velocities available to the system at every system state. An inclusion using this approximation can be interpreted as a control system; the trajectories of the derived control system are guaranteed to be the trajectories of the unknown system. To illustrate the practical implementation and consequences of our work, we apply our algorithm to a simplified model of an unmanned aerial vehicle.