Inverse Polynomial Based Explicit Guidance for Lunar Soft Landing During Powered Braking

In this paper an explicit guidance law for the powered descent phase of the soft lunar landing is presented. The descent trajectory, expressed in polynomial form is fixed based on the boundary conditions imposed by the precise soft landing mission. Adapting an inverse model based approach, the guidance command is computed from the known spacecraft trajectory. The guidance formulation ensures the vertical orientation of the spacecraft during touchdown. Also a closed form relation for the final flight time is proposed. The final time is expressed as a function of initial position and velocity of the spacecraft ( at the start of descent) and also depends on the desired landing site. To ensure the fuel minimum descent the proposed explicit method is extended to optimal guidance formulation. The effectiveness of the proposed guidance laws are demonstrated with simulation results.

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.

Magnetic properties of sintered sm2fe17ny magnets

Sintered magnets of Sm2Fe17Ny nitrides, with a density of 6.0-7.4 g/cm3, have been prepared by using an explosion technique. Both crystalline structure and the magnetic properties of Sm2Fe17Ny nitrides were retained in the process. The sintered magnet had a remanence B(r)=0.83 T, an intrinsic coercivity mu(0i)H(c)=0.57 T and an energy product (BH)max=88 kJ/m3. The temperature dependence of coercivity and remanence were also measured. The temperature coefficients alpha of remanence and beta of coercivity are -0.076%/degrees-C and -0.51%/degrees-C, respectively.