Fuel-optimal G-MPSP Guidance for Powered Descent Phase of Soft Lunar Landing

A fuel optimal nonlinear sub-optimal guidance scheme is presented in this paper for soft landing of a lunar craft during the powered descent phase. The recently developed Generalized Model Predictive Static Programming (G-MPSP) is used to compute the required magnitude and angle of the thrust vector. Both terminal position and velocity vector are imposed as hard constraints, which ensures high position accuracy and facilitates initiation of vertical descent at the end of the powered descent phase. A key feature of the G-MPSP algorithm is that it converts the nonlinear dynamic programming problem into a low-dimensional static optimization problem (of the same dimension as the output vector). The control history update is done in closed form after computing a time-varying weighting matrix through a backward integration process. This feature makes the algorithm computationally efficient, which makes it suitable for on-board applications. The effectiveness of the proposed guidance algorithm is demonstrated through promising simulation results.

Optimal Guidance for Accurate Lunar Soft Landing with Minimum Fuel Consumption using Model Predictive Static Programming

In this paper the soft lunar landing with minimum fuel expenditure is formulated as a nonlinear optimal guidance problem. The realization of pinpoint soft landing with terminal velocity and position constraints is achieved using Model Predictive Static Programming (MPSP). The high accuracy of the terminal conditions is ensured as the formulation of the MPSP inherently poses final conditions as a set of hard constraints. The computational efficiency and fast convergence make the MPSP preferable for fixed final time onboard optimal guidance algorithm. It has also been observed that the minimum fuel requirement strongly depends on the choice of the final time (a critical point that is not given due importance in many literature). Hence, to optimally select the final time, a neural network is used to learn the mapping between various initial conditions in the domain of interest and the corresponding optimal flight time. To generate the training data set, the optimal final time is computed offline using a gradient based optimization technique. The effectiveness of the proposed method is demonstrated with rigorous simulation results.

Tuning Photoluminescence Response by Electric Field in Electrically Soft Ferroelectrics

We show that an electrically soft ferroelectric host can be used to tune the photoluminescence (PL) response of rare-earth emitter ions by external electric field. The proof of this concept is demonstrated by changing the PL response of the Eu3+ ion by electric field on a model system Eu-doped 0.94(Na1/2Bi1/2TiO3)-0.06(BaTiO3). We also show that new channels of radiative transitions, forbidden otherwise, open up due to positional disorder in the system, which can as well be tuned by electric field.

Improved method makes a soft landing of well path

Research and field experience have shown that well-path control is important in many cases, not only to reach the desired coordinates, but also to arrive at the well completion target from the preferred trajectory.

A Generalized Soft-Sphere for Monte Carlo Simulation

A new collision model, called the generalized soft-sphere (GSS) model, is introduced. It has the same total cross section as the generalized hard-sphere model [Phys. Fluids A 5, 738 (1993)], whereas the deflection angle is calculated by the soft-sphere scattering model [Phys. Fluids A 3, 2459 (1991)]. In virtue of a two-term formula given to fit the numerical solutions of the collision integrals for the Lennard-Jones (6-12) potential and for the Stockmayer potential, the parameters involved in the GSS model are determined explicitly that may fully reproduce the transport coefficients under these potentials. Coefficients of viscosity, self-diffusion and diffusion for both polar and nonpolar molecules given by the GSS model and experiment are in excellent agreement over a wide range of temperature from low to high.

Size Dependent Nanoindentation of a Soft Film on a Hard Substrate

Nanoindentation experiments on Al/glass systems show that, as the indentation depth increases, the hardness decreases during a shallow indentation, and increases when the indenter tip approaches the film–substrate interface. We associate the rise in hardness during two stages with the strong strain gradient effects, the first stage is related with the small scale effects and the second stage with the strain gradient between the indenter and the hard substrate. Using the strain gradient theory proposed by Chen and Wang and the classical plasticity theory, the observed nanoindentation behavior is modeled and analyzed by means of the finite element method, and it is found that the classical plasticity cannot explain the experiment results but the strain gradient theory can describe the experiment data at both shallow and deep indentation depths very well. The results prove that both the strain gradient effects and substrate effects exist in the nanoindentation of the film–substrate system.

Propagation of Explosion Wave in Hard-Soft-Hard Layered Media

The paper presents a reasonable analysis for dynamic response and failure process of a plane multi-layered media, which are subjected to a blast loading. This blast loading is induced by a cylindric explosive put on the center of top surface of the layered media. With the help of numerical simulation technique provided by LS-DYNA software, the whole process of explosion wave propagation and attenuation can be revealed. The feature of local failure around the blasting site is also discussed in some detail. Our focus will be on the explosion wave attenuation for the hard-soft-hard sandwich layers. As seen in the paper, the computational results are delivered in a feasible way by comparing with experimental data.