Use of Bamboo in Soft-Ground Engineering and Its Performance Comparison with Geosynthetics: Experimental Studies

The results of the laboratory investigation performed on clay beds reinforced with natural (bamboo) and commercial (geosynthetics) reinforcement materials are reported in this paper. To use bamboo effectively, three-dimensional cells (similar to geocells) and two-dimensional grids (similar to geogrids) are formed using bamboo (termed bamboo cells and bamboo grids, respectively). The performance of clay beds reinforced with bamboo cells and bamboo grids is compared with that of clay beds reinforced with geocells and geogrids. The bearing capacity of the clay bed increased by six times when a combination of geocell and geogrid was used. The ultimate bearing capacity of the clay bed reinforced with bamboo cell and bamboo grid was found to be 1.3 times more than that of clay bed reinforced with geocell and geogrid. In addition, substantial reduction in the footing settlement and the surface deformation was observed. The tensile strength and surface roughness of bamboo were found to be nine times and three times, respectively, higher than geocell materials. The bamboo was treated chemically to increase its durability. Although the performance of bamboo was reduced by 15-20% after the chemical treatment, its performance was better than its commercial counterparts. (C) 2014 American Society of Civil Engineers.

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.