A fast computational method for the landing footprints of space-to-ground vehicles

Fast computation of the landing footprint of a space-to-ground vehicle is a basic requirement for the deployment of parking orbits, as well as for enabling decision makers to develop real-time programs of transfer trajectories. In order to address the usually slow computational time for the determination of the landing footprint of a space-to-ground vehicle under finite thrust, this work proposes a method that uses polynomial equations to describe the boundaries of the landing footprint and uses back propagation(BP) neural networks to quickly determine the landing footprint of the space-to-ground vehicle. First, given orbital parameters and a manoeuvre moment, the solution model of the landing footprint of a space-to-ground vehicle under finite thrust is established. Second, given arbitrary orbital parameters and an arbitrary manoeuvre moment, a fast computational model for the landing footprint of a space-to-ground vehicle based on BP neural networks is provided.Finally, the simulation results demonstrate that under the premise of ensuring accuracy, the proposed method can quickly determine the landing footprint of a space-to-ground vehicle with arbitrary orbital parameters and arbitrary manoeuvre moments. The proposed fast computational method for determining a landing footprint lays a foundation for the parking-orbit configuration and supports the design of real-time transfer trajectories.

A fast forward computational method for nuclear measurement using volumetric detection constraints

Owing to the complex lithology of unconventional reservoirs,field interpreters usually need to provide a basis for interpretation using logging simulation models.Among the various detection tools that use nuclear sources,the detector response can reflect various types of information of the medium.The Monte Carlo method is one of the primary methods used to obtain nuclear detection responses in complex environments.However,this requires a computational process with extensive random sampling,consumes considerable resources,and does not provide real-time response results.Therefore,a novel fast forward computational method(FFCM)for nuclear measurement that uses volumetric detection constraints to rapidly calculate the detector response in various complex environments is proposed.First,the data library required for the FFCM is built by collecting the detection volume,detector counts,and flux sensitivity functions through a Monte Carlo simulation.Then,based on perturbation theory and the Rytov approximation,a model for the detector response is derived using the flux sensitivity function method and a one-group diffusion model.The environmental perturbation is constrained to optimize the model according to the tool structure and the impact of the formation and borehole within the effective detection volume.Finally,the method is applied to a neutron porosity tool for verification.In various complex simulation environments,the maximum relative error between the calculated porosity results of Monte Carlo and FFCM was 6.80%,with a rootmean-square error of 0.62 p.u.In field well applications,the formation porosity model obtained using FFCM was in good agreement with the model obtained by interpreters,which demonstrates the validity and accuracy of the proposed method.

A fast MPC algorithm for reducing computation burden of MIMO

The computation burden in the model-based predictive control algorithm is heavy when solving QR optimization with a limited sampling step, especially for a complicated system with large dimension. A fast algorithm is proposed in this paper to solve this problem, in which real-time values are modulated to bit streams to simplify the multiplication. In addition, manipulated variables in the prediction horizon are deduced to the current control horizon approximately by a recursive relation to decrease the dimension of QR optimization. The simulation results demonstrate the feasibility of this fast algorithm for MIMO systems.

A fast computing method to distinguish the hyperbolic trajectory of an non-autonomous system

Attempting to find a fast computing method to DHT （distinguished hyperbolic trajectory）, this study first proves that the errors of the stable DHT can be ignored in normal direction when they are computed as the trajectories extend. This conclusion means that the stable flow with perturbation will approach to the real trajectory as it extends over time. Based on this theory and combined with the improved DHT computing method, this paper reports a new fast computing method to DHT, which magnifies the DHT computing speed without decreasing its accuracy.

Computational approaches for fast generation of digital 3D video holograms(Invited Paper)

Several approaches for fast generation of digital holograms of a three-dimensional （3D） object have been discussed. Among them, the novel look-up table （N-LUT） method is analyzed to dramatically reduce the number of pre-calculated fringe patterns required for computation of digital holograms of a 3D object by employing a new concept of principal fringe patterns, so that problems of computational complexity and huge memory size of the conventional ray-tracing and look-up table methods have been considerably alleviated. Meanwhile, as the 3D video images have a lot of temporally or spatially redundant data in their inter- and intra-frames, computation time of the 3D video holograms could be also reduced just by removing these redundant data. Thus, a couple of computational methods for generation of 3D video holograms by combined use of the N-LUT method and data compression algorithms are also presented and discussed. Some experimental results finally reveal that by using this approach a great reduction of computation time of 3D video holograms could be achieved.

An efficient technique for recovering responses of parameterized structural dynamic problems

In this article,an effective technique is developed to efficiently obtain the output responses of parameterized structural dynamic problems.This technique is based on the conception of reduced basis method and the usage of linear interpolation principle.The original problem is projected onto the reduced basis space by linear interpolation projection,and subsequently an associated interpolation matrix is generated.To ensure the largest nonsingularity,the interpolation matrix needs to go through a timenode choosing process,which is developed by applying the angle of vector spaces.As a part of this technique,error estimation is recommended for achieving the computational error bound.To ensure the successful performance of this technique,the offline-online computational procedures are conducted in practical engineering.Two numerical examples demonstrate the accuracy and efficiency of the presented method.

A fast implementation for computing spatial impulse response of ultrasonic transducers

The spatial impulse response（SIR） method is often used as the ＇gold standard5 in simulation of transient acoustic wave fields due to its high accuracy in the linear domain.However, a high sampling frequency is often required in order to achieve the high accuracy. As a result, a large amount of data has to be processed. In this paper a fast approach for computing spatial impulse response is proposed to reduce the computation burden. The proposed approach is developed by employing the relationship of SIRs at observed points and SIRs of the projection points on the transducer surface. Two critical parameters used in the proposed approach, the calculation sampling frequency and the interpolation sampling frequency, are then analyzed.Results show that for a 2.25 MHz rectangular transducer with the size of 5 mm×10 mm,a calculation sampling frequency of 1000 MHz and an interpolation sampling frequency of500 MHz can achieve superior performance while improving the computation efficiency 18 times than the direct solving.