Design and Evaluation of the Key Units in a Rapeseed Direct Seeder Integrated with Plowing-Rotating Combined Tillage

HighlightsThe seeder combined the plowing and rotating tillage to overcome the heavy soil and a large amount of straws.The plow could lift and turn the soil and straw before rotary tillage.The optimal working parameters of the seeder were obtained by orthogonal field experiments.Abstract. Rapeseed, one of the most important oil crops in China, is mainly planted in the mid-lower reaches of the Yangtze River. However, limited by the special long-term rice-rapeseed rotation, rotary tillage is applied in most of the planted areas apply instead of plow tillage, leading to a shallow arable layer. On the other hand, maintaining a high-quality seedbed for rapeseed becomes a challenge because a large amount of straw remains buried in the soil. As a solution, a rapeseed direct seeder that combines plow tillage and rotary tillage was designed. The structure of the plowing unit, whose key components were a lifting-turning plow and symmetrical plow, was analyzed based on the forming principle of the plow. Furthermore, a mechanical soil throwing model of the rotary tillage blade was built to determine the structural parameters. Then, the interaction between the rotary tillage unit and the lift-turning plow was analyzed. Finally, the performance and optimal parameters were evaluated by orthogonal field experiments. The seedbed after the operations indicated that the seeder could achieve the function of turning the soil and straw first and then rotating the soil with good passability, mixing the straw and the soil, flattening the surface of the seed bed, and stabilizing the tillage depth. Orthogonal experiments showed that the optimal working parameters of the seeder were as follows: the tillage depth was 180 mm, the equipment forward speed was 2.1 km/h, and the speed of the rotary tillage blade was 250 r/min. Under the optimal parameter combination, the power consumption of the seeder, the thickness of the tillage layer, the crop residue burial efficiency, the soil breakage efficiency, and the flatness of the seed bed surface were 30.48 kW, 231 mm, 90.88%, 93.26%, and 21.15 mm, respectively. The working performance of the seeder could meet the tillage requirements of rapeseed planting. Keywords: Direct seeder, Evaluation, Plow, Plowing-rotating combined tillage, Rapeseed.

Global analysis of Navier–Stokes and Boussinesq stochastic flows using dynamical orthogonality

We provide a new framework for the study of fluid flows presenting complex uncertain behaviour. Our approach is based on the stochastic reduction and analysis of the governing equations using the dynamically orthogonal field equations. By numerically solving these equations, we evolve in a fully coupled way the mean flow and the statistical and spatial characteristics of the stochastic fluctuations. This set of equations is formulated for the general case of stochastic boundary conditions and allows for the application of projection methods that considerably reduce the computational cost. We analyse the transformation of energy from stochastic modes to mean dynamics, and vice versa, by deriving exact expressions that quantify the interaction among different components of the flow. The developed framework is illustrated through specific flows in unstable regimes. In particular, we consider the flow behind a disk and the Rayleigh–Bénard convection, for which we construct bifurcation diagrams that describe the variation of the response as well as the energy transfers for different parameters associated with the considered flows. We reveal the low dimensionality of the underlying stochastic attractor.

Data Assimilation with Gaussian Mixture Models Using the Dynamically Orthogonal Field Equations. Part II: Applications

The properties and capabilities of the Gaussian Mixture Model–Dynamically Orthogonal filter (GMM-DO) are assessed and exemplified by applications to two dynamical systems: 1) the double well diffusion and 2) sudden expansion flows; both of which admit far-from-Gaussian statistics. The former test case, or twin experiment, validates the use of the Expectation-Maximization (EM) algorithm and Bayesian Information Criterion with GMMs in a filtering context; the latter further exemplifies its ability to efficiently handle state vectors of nontrivial dimensionality and dynamics with jets and eddies. For each test case, qualitative and quantitative comparisons are made with contemporary filters. The sensitivity to input parameters is illustrated and discussed. Properties of the filter are examined and its estimates are described, including the equation-based and adaptive prediction of the probability densities; the evolution of the mean field, stochastic subspace modes, and stochastic coefficients; the fitting of GMMs; and the efficient and analytical Bayesian updates at assimilation times and the corresponding data impacts. The advantages of respecting nonlinear dynamics and preserving non-Gaussian statistics are brought to light. For realistic test cases admitting complex distributions and with sparse or noisy measurements, the GMM-DO filter is shown to fundamentally improve the filtering skill, outperforming simpler schemes invoking the Gaussian parametric distribution.

Interaction of Additive Noise and Nonlinear Dynamics in the Double-Gyre Wind-Driven Ocean Circulation

In this paper the authors study the interactions of additive noise and nonlinear dynamics in a quasigeostrophic model of the double-gyre wind-driven ocean circulation. The recently developed framework of dynamically orthogonal field theory is used to determine the statistics of the flows that arise through successive bifurcations of the system as the ratio of forcing to friction is increased. This study focuses on the understanding of the role of the spatial and temporal coherence of the noise in the wind stress forcing. When the wind stress noise is temporally white, the statistics of the stochastic double-gyre flow does not depend on the spatial structure and amplitude of the noise. This implies that a spatially inhomogeneous noise forcing in the wind stress field only has an effect on the dynamics of the flow when the noise is temporally colored. The latter kind of stochastic forcing may cause more complex or more coherent dynamics depending on its spatial correlation properties.