Compaction Density Evaluation Model of Sand-Gravel Dam Based on Elman Neural Network With Modified Particle Swarm Optimization

The compaction density of sand-gravel materials has a strong gradation correlation, mainly affected by some material source parameters such as P5 content (material proportion with particle size greater than 5 mm), maximum particle size and curvature coefficient. When evaluating the compaction density of sand-gravel materials, the existing compaction density evaluation models have poor robustness and adaptability because they do not take into full consideration the impact of material source parameters. To overcome the shortcomings of existing compaction density models, this study comprehensively considers the impact of material source parameters and compaction parameters on compaction density. Firstly, asymmetric data were fused and a multi-source heterogeneous dataset was established for compaction density analysis. Then, the Elman neural network optimized by the adaptive simulated annealing particle swarm optimization algorithm was proposed to establish the compaction density evaluation model. Finally, a case study of the Dashimen water conservancy project in China is employed to demonstrate the effectiveness and feasibility of the proposed method. The results show that this model performs high-precision evaluation of the compaction density at any position of the entire working area which can timely correct the weak area of compaction density on the spot, and reduce the number of test pit tests.

Nutritional value, total dry matter losses, effluent production and pollutant potential in Brachiaria brizantha cv. Paiaguás grass

ABSTRACT The objective of the present study was to evaluate losses, production and polluting potential of the effluent, nutritional value and aerobic stability of silages of Brachiaria brizantha cv. Paiaguás grass, in different particle sizes and compaction density in silage. Three theoretical particle sizes (TTP 5; 8 and 12mm) and three compaction densities (DC 550; 600 and 650kg/m3) were evaluated, distributed in a factorial design (3 x 3), with four repetitions. The highest volume of effluent was found in silages with higher compaction densities (600 and 650kg/m3) and lower TTP (5 and 8mm). The highest chemical oxygen demand and biochemical oxygen demand were registered in the treatment with TTP of 5mm and higher DC (600 and 650kg/m3). Greater in vitro digestibility of DM was verified in the silage chopped at 5 and 8mm. There was no break in aerobic stability for 216 hours. Silage with a low compaction density 550kg/m3 and processing with a theoretical particle size of 12mm reduces effluent losses. In general, the nutritional value of Paiaguás grass was not influenced by the treatments. Different particle sizes and compaction density did not change the aerobic stability of silages.

Kualitas Fisik Pellet dengan Penambahan Level Tepung Daun Ubi Kayu serta Bahan Perekat yang Berbeda

ABSTRACT One alternative that can be used for poultry feed is cassava flour (Manihot esculenta) which can be made into pellets. The purpose of this research was to know the physical quality of water content (KA), specific gravity (BJ), stack angle (ST), stack density (KT), stack compaction density (KPT), and impact resistance (KB) of pellet product with utilization of flour cassava (Manihot esculenta). This research using Completely Randomized Design (RAL) Factorial. Factor A consisting of 3 treatments, that were A0: without adding cassava leaf flour, A1: 5% and A2: 10% in ration formulation and Factor B consisting of 3 treatments binders, that were B0 : basal ration not binders, B1: tapioca starch and B2: wheat flour. The results showed that the interaction between the addition of cassava leaf flour and binders with different levels can be seen from water content, stack angle and stack compaction density, but on specific gravity, stack density and impact resistance did not occur interaction. It can be concluded that the addition of 10% cassava flour with tapioca flour binders gives the best quality of pellet physical properties to moisture content and stack angle, while other treatment combinations have not been able to improve pellet quality based on specific gravity, stack density, stack compaction density and impact resistance. Keywords: Pellet, Cassava Leaf, Flour, Binders