Dynamic performance prediction of an annular tensegrity structure based on similitude method

Packing optimization and design of the deployable parabolic rigid antenna based on origami

Structural design and optimization of large cable–rib tension deployable antenna structure with dynamic constraint

Robotic object exploration and identification methods to date have attempted to mimic human Exploratory Procedures (EPs) using complex, rigid robotic hands with multifaceted sensory suites. For applications where the target objects may have different or unknown cross-sectional shapes and sizes (e.g. beam members in truss structures), rigid grippers are not a good option as they are unable to adapt to the target objects. This may make it very difficult to recognise the shape and size of a beam member and the approaching angles which would result in a secure grasp. To best meet the requirements of adaptability and compliancy, a soft robotic gripper with simple exteroceptive force sensors has been designed. This paper experimentally verifies the gripper design by assessing its performance in grasping and adapting to a variety of target beam members in a truss structure. The sensor arrangement is also assessed by verifying that sufficient data is extracted during a grasp to recognise the approaching angle of the gripper. Firstly, the gripper is used to grasp each beam member from various angles of approach and readings from the force sensors are collected. Secondly, the collected sensor data is used to train and then test a range of commonly used classifiers for classification of the angle of approach. Thirdly, the classification results are analysed. Through this process, it is found that the gripper is proficient in grasping the variety of target beam members. Despite the uncertainty in the gripper pose, the sensor data collected from the soft gripper during a grasp is sufficient for classification of the angles of approach.

A digital close range photogrammetric method for space deployable microwave antenna is presented. The planning of multi-camera stations, 3D data connection of images of different view field and the calibration of the cameras are discussed. The procedure of calibration has two steps: direct linear transformation and the bundle adjustment. The measurement error resulted from lens distortion can be corrected. The relative accuracy of 1 part in 1000 can be achieved using on site automatic calibration during measurement. The profile of the space deployable microwave antenna was obtained through the least squares fitting of the adjusted observations.

ABSTRACTLarge deployable space antennas may be exposed to severe thermal environments in future space missions; extreme heat loads will result in considerable thermal stresses and deformations which seriously affects the accuracy of the antenna's parabolic surface. In this study, thermal–structural finite element analysis of a deployable AstroMesh antenna under extreme heat loads was presented. Considering position and orientation with respect to the Sun and Earth, the antenna's temperature changing law under orbital heat fluxes was first evaluated to find the worst condition as loading point. Analyses for the antenna under different levels of extreme heat loads were then performed to obtain the temperature distributions utilizing an equivalent quarter antenna model. Based on the temperature calculation results and prestress designs, structural analyses were finally made to gain the resulting stresses and deformations. The analysis results show that the existing antenna may generate significant performance distortion under extreme thermal environments; so attentions for reliability and safety under such conditions should be taken seriously in future antenna works. Modeling and analysis method proposed in this article was validated to be contributive in antenna's thermal and precompensation designs.

A controlled deployment method for flexible deployable space antennas

Naturally fractured-vuggy carbonate reservoirs in China have some distinctive characteristics: deep buried depth, multi-scale fractures, vugs and caves developed, poor reservoir connectivity and isolated developed reservoirs with small volumetric volume. It is hard to build effective geological models and run reservoir simulation for production forecasting. So how to properly characterize and forecast the performance of this kind of reservoirs is a major challenge. This paper presents an integrated dynamic characterization method to solve this problem. The workflow of the integrated dynamic characterization method are presented. The method mainly involves analytical and numerical production data analysis (PA) and well test analysis. Firstly, based on seismic interpretation and attribute imaging, reservoirs are divided into many different flow units, with reserves and boundaries of each unit determined. Then for each unit, analytical rate transient analysis and analytical pressure transient analysis are applied to calculate original oil in place (OOIP), permeability, etc. After that, numerical production data analysis are used and numerical dynamic model are calibrated with analytical analysis results constrained. Finally, numerical well test analysis models are established and calibrated, which initialized from numerical production data analysis models. This new method has been applied on K fractured-vuggy carbonate reservoir in China. The mid-depth of K reservoir is 6500m with primary depletion currently, and current oil recovery is only around 7% of OOIP with more than 100 producers. Based on seismic modeling study, K reservoir is divided into different flow units, which are thought to be isolated and have no pressure communication from each other. Then how to use the proposed integrated method to characterize flow units are detailed illustrated with the explanation of the application sequence of different analysis method, especially how to combine and constrain these analytical and numerical methods with each other until reliable results generated are detailed presented. Through the dynamic characterization of K reservoir with seismic and geological understanding integrated, reservoir properties of each units are correctly calibrated and evaluated, which includes flow boundary, permeability, well skin, oil in place and so on. Furthermore, the connectivity among different flow units are revised and calibrated based on dynamic characterization. Finally, based on the calibrated numerical dynamic models, performance of each well are predicted. This systematic technique has been successfully applied K fractured-vuggy carbonate reservoir, which properly and correctly evaluate the properties of the reservoir. It also provides a reliable method for remaining oil evaluation and performance prediction, which are helpful for effective development of the reservoir. Furthermore, the systematic method can be used for reservoir evaluation and performance prediction in any other similar oil fields.

Beyond the science and art of the healthy buildings daylighting dynamic control's performance prediction and validation

Modern bridges are monitored by an increasing network of sensors that produce massive data for bridge performance prediction. Reasonably and dynamically predicting with monitored data for the time-variant reliability of the existing bridges has become one of the urgent problems in structural health monitoring (SHM). This study, taking the dynamic measure of structural stress over time as a time series, proposes a data assimilation approach to predicting reliability based on extreme stress data with cyclicity. To this aim, the objectives of this article are to present the following: (a) a Gaussian mixture model-based Bayesian cyclical dynamic linear model (GMM-BCDLM) based on extreme stress data with cyclicity and (b) a dynamic reliability prediction method in the combination of GMM-BCDLM and SHM data via first-order second-moment (FOSM) method. An in-service bridge for providing real-time monitored stress data is applied to illustrate the application and feasibility of the proposed method. Then, the effectiveness and prediction precision of the proposed models are proved to be superior compared to other prediction approaches to extreme stress data with cyclicity.

Despite that theoretical, design and experimental studies connected with the creation of large deployable antenna reflectors have already been carried out for quite a long time, this area still remains of lively interest and has good application prospects. An example is the program of the European Space Agency (ESA) on the creation of a qualified variant of a 15 m deployable space offset reflector. It should be said that by the time the ESA adopted a decision on the implementation of this program, a deployable space reflector 7 m in diameter had already been created in Georgia and, in 1999, this space reflector was successfully tested aboard the orbital station “Mir” according to the joint Georgian–Russian program. Georgian Institute for Space Constructions, continues developing new design principles for large space deployable systems (Transformable Space and Ground Structures (in Russian), A Monograph, Georgia–Germany–Liechtenstein, 1995). In the paper we describe the invention of an absolutely new design of a space antenna for symmetric and nonsymmetric radio telescopes, which has been developed by the team of Georgian designers headed by Professor E. Medzmariashvili. The novelty consists in that new engineering and technological effects we obtained by synthesis of ring-shaped and rib-umbrella type systems. In particular, the central hinge that connects the main levers of the pantograph is arranged asymmetrically. As a result of this asymmetrical arrangement, during deployment the consoles (folded along the package longitudinal axis and connecting the adjacent sections) move in radial directions from the center to the periphery and, simultaneously, deploy in an umbrella-like manner.

It is nearly impossible to carry out prototype experiments of large deployable space antennas because of their large dimensions. To solve this problem, a performance prediction approach is proposed in this paper. The prototype’s working performance is predicted by the scale model of the large deployable antenna. Based on this method, the natural frequency of the ring tension truss deployable antenna working in space is studied. The effect of the structural parameter distortion is taken into consideration by similarity criteria, and a similarity experimental formula of structural natural frequency is obtained. Four finite element models are established to validate the correction of the prediction method. The simulation results show that it’s valid for the prediction method to analyze the prototype in space, and it can be applied to promote the design, and performance prediction of the large deployable antennas.

Dynamics of the orbiter based construction of structural components for space platforms

As sensor monitoring technology continues to evolve, structural online monitoring and health management have found numerous applications across various fields. However, challenges remain concerning the real-time diagnosis of structural damage and the accuracy of dynamic reliability predictions. In this paper, a structural online damage identification and dynamic reliability prediction method based on Unscented Kalman Filter (UKF) is presented. Specifically, in the Wiener degradation process with random effects on structural performance, the structural damage identification is initially realized using UKF. Following that, the EM algorithm is employed for estimating the performance model parameters. Eventually, dynamic reliability prediction is realized based on conditional probability. The simulation results indicate that the method effectively estimates the damage state during the structure’s use while providing accurate, real-time, and dynamic reliability predictions for the system.

To address gear tooth damage and the difficulty of acquiring performance data under high-speed and high-load operating conditions of planetary gearboxes, a digital twin-based system for operational state recognition and performance prediction is proposed, integrating morphological and functional characteristics. Driven by experimental data, the system incorporates finite element analysis, multibody dynamics simulation, artificial intelligence algorithms, and 3D visualization to achieve a virtual mapping of the gearbox’s geometric configuration, structural properties, and dynamic behavior. Structural performance is represented using finite element and dynamic simulation techniques combined with texture mapping, visualized through color gradients; dynamic performance is captured through multibody dynamics simulations and stored in a time-series database, presented as sequential images. The integrated system is constructed by combining a structural performance surrogate model, a system-driven model, and a dynamic performance database, enabling comprehensive functionality. Results demonstrate that the maximum error of the structural performance model is 3%, occurring only under specific working conditions, with negligible impact on the overall meshing performance evaluation of the sun gear. The maximum error in dynamic performance prediction is 1.68%, showing strong consistency with experimental data.

Dynamic blind source separation based on source-direction prediction