Meter-Scale Thin-Walled Structure with Lattice Infill for Fuel Tank Supporting Component of Satellite:Multiscale Design and Experimental Verification

Lightweight thin-walled structures with lattice infill are widely desired in satellite for their high stiffness-to-weight ratio and superior buckling strength resulting fromthe sandwich effect.Such structures can be fabricated bymetallic additive manufacturing technique,such as selective laser melting(SLM).However,the maximum dimensions of actual structures are usually in a sub-meter scale,which results in restrictions on their appliance in aerospace and other fields.In this work,a meter-scale thin-walled structure with lattice infill is designed for the fuel tank supporting component of the satellite by integrating a self-supporting lattice into the thickness optimization of the thin-wall.The designed structure is fabricated by SLM of AlSi10Mg and cold metal transfer welding technique.Quasi-static mechanical tests and vibration tests are both conducted to verify the mechanical strength of the designed large-scale lattice thin-walled structure.The experimental results indicate that themeter-scale thin-walled structure with lattice infill could meet the dimension and lightweight requirements of most spacecrafts.

Vision-based multi-level synthetical evaluation of seismic damage for RC structural components: a multi-task learning approach

Recent studies for computer vision and deep learning-based,post-earthquake inspections on RC structures mainly perform well for specific tasks,while the trained models must be fine-tuned and re-trained when facing new tasks and datasets,which is inevitably time-consuming.This study proposes a multi-task learning approach that simultaneously accomplishes the semantic segmentation of seven-type structural components,three-type seismic damage,and four-type deterioration states.The proposed method contains a CNN-based encoder-decoder backbone subnetwork with skip-connection modules and a multi-head,task-specific recognition subnetwork.The backbone subnetwork is designed to extract multi-level features of post-earthquake RC structures.The multi-head,task-specific recognition subnetwork consists of three individual self-attention pipelines,each of which utilizes extracted multi-level features from the backbone network as a mutual guidance for the individual segmentation task.A synthetical loss function is designed with real-time adaptive coefficients to balance multi-task losses and focus on the most unstably fluctuating one.Ablation experiments and comparative studies are further conducted to demonstrate their effectiveness and necessity.The results show that the proposed method can simultaneously recognize different structural components,seismic damage,and deterioration states,and that the overall performance of the three-task learning models gains general improvement when compared to all single-task and dual-task models.

A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages,such as lightweight and ease of embedding.However,identifying the precise location of damage from the optical fiber signals remains a critical challenge.In this paper,a novel approach which namely Modified Sliding Window Principal Component Analysis(MSWPCA)was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors.The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection.Specifically,we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures.Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding,thereby facilitating reliable and efficient online assessment of the structural health state.

Explicit Topology Optimization Design of Stiffened Plate Structures Based on the Moving Morphable Component(MMC)Method

This paper proposes an explicit method for topology optimization of stiffened plate structures.The present work is devoted to simultaneously optimizing stiffeners’shape,size and layout by seeking the optimal geometry parameters of a series of moving morphable components(MMC).The stiffeners with straight skeletons and the stiffeners with curved skeletons are considered to enhance the modeling and optimization capability of the current approach.All the stiffeners are represented under the Lagrangian-description framework in a fully explicit way,and the adaptive ground structure method,as well as dynamically updated plate/shell elements,is used to obtain optimized designs with more accurate analysis results.Compared with existing works,the proposed approach provides an explicit description of the structure.Thus,a stiffened plate structure with clear stiffener distribution and smooth geometric boundary can be obtained.Several numerical examples provided,including straight and curved stiffeners,hierarchical stiffeners,and a stiffened plate with a cutout,validate the effectiveness and applicability of the proposed approach.

Thermoelastic Structural Topology Optimization Based on Moving Morphable Components Framework

This study investigates structural topology optimization of thermoelastic structures considering two kinds of objectives ofminimumstructural compliance and elastic strain energy with a specified available volume constraint.To explicitly express the configuration evolution in the structural topology optimization under combination of mechanical and thermal load conditions,the moving morphable components(MMC)framework is adopted.Based on the characteristics of the MMC framework,the number of design variables can be reduced substantially.Corresponding optimization formulation in the MMC topology optimization framework and numerical solution procedures are developed for several numerical examples.Different optimization results are obtained with structural compliance and elastic strain energy as objectives,respectively,for thermoelastic problems.The effectiveness of the proposed optimization formulation is validated by the numerical examples.It is revealed that for the optimization design of the thermoelastic structural strength,the objective function with the minimum structural strain energy can achieve a better performance than that from structural compliance design.

Numerical simulation study on monoblock casting process of ultra-slender structural components and experimental validation

Substrate, a typical ultra-slender aluminum alloy structural components with a large aspect ratio and complex internal structure, was traditionally manufactured by re-assembly and sub-welding. In order to realize the monoblock casting of the substrate, the Pro/E software was utilized to carry out three-dimensional(3D) modeling of the substrate casting, and the filling and solidification processes were calculated, as well as the location and types of casting defects were predicted by the casting simulation software Anycasting. Results of the filling process simulation show that the metal liquid is distributed into each gap runner evenly and smoothly. There is no serious vortex phenomenon in the mold cavity, and the trajectory of the virtual particles is clear. Results of the solidification process simulation show that shrinkage cavities mainly appear at the junction of gap runners and the rail surface of the substrate. The average deformation is 0.6 mm in X direction, 3.8 mm in Y direction, and 8.2 mm in Z direction. Based on the simulation results, the casting process of the substrate was optimized, and qualified castings were successfully produced, which will provide a reference for the casting process design of other ultraslender aluminum alloy structural components.

Opportunistic maintenance for multi-component systems considering structural dependence and economic dependence

Although opportunistic maintenance strategies are widely used for multi-component systems, all opportunistic mainte- nance strategies only consider economic dependence and do not take structural dependence into account. An opportunistic main- tenance strategy is presented for a multi-component system that considers both structural dependence and economic dependence. The cost relation and time relation among components based on structural dependence are developed. The maintenance strategy for each component of a multi-component system involves one of five maintenance actions, namely, no-maintenance, a minimal maintenance action, an imperfect maintenance action, a perfect maintenance action, and a replacement action. The maintenance action is determined by the virtual age of the component, the life expectancy of the component, and the age threshold values. Monte Carlo simulation is designed to obtain the optimal oppor- tunistic maintenance strategy of the system over its lifetime. The simulation result reveals that the minimum maintenance cost with a strategy that considers structural dependence is less than that with a strategy that does not consider structural dependence. The availability with a strategy that considers structural dependence is greater than that with a strategy that does not consider structural dependence under the same conditions.

Physicochemical and structural characteristics of the Venn components of wheat gliadin

The aim of this study was to analyze the physicochemical and structural characteristics of the Venn components of wheat gliadin to provide theoretical basis of gliadin for processing in dough and Chinese steamed bread. Eight Venn components, Gli-8, Gli-9, Gli-10, Gli-11, Gli-12, Gli-13, Gli-14, and Gli-15, were extracted from wheat gliadin based on their solubility. The results of physicochemical characteristics showed that the differences in the contents, TDS,electrical conductivity, particle size and zeta potential of Venn components were significant, respectively. The content of Gli-15 in gliadin was the highest, and the content of Gli-9 was the lowest. The TDS value of Gli-9 was the highest(336.0), and the TDS value of Gli-15 was the lowest(52.0). The electrical conductivity of Gli-9 was the highest,which was 7.54 times the lowest value of Gli-11. The zeta potential of Gli-9 was -25.2 mV, and the zeta potential of the Gli-15 was -7.64 mV. However, the difference in the p H values was not significant. The results of UV spectrum and FTIR analysis showed that the secondary structures of the Venn components had significant differences. The results of the XRD patterns indicated that the Venn components might not be a single substance. The results of CLSM images implied that the molecular interactions among the components were varied. Hence, the results could provide research materials and basic data for deep processing and utilization of gliadin.

Knowledge-based System Prototype in Structural Component Design Based on FM

A knowledge-based system in structural component design based on fracture mechanics is developed in this paper. The system consists of several functional parts: a general inference engine, a set of knowledge bases and data-bases, an interpretation engine, a bases administration system and the interface. It can simulate a human expert to make analysis and design scheme mainly for four kinds of typical structural components widely used in shipbuilding industry: pressure vessels, huge rotation constructions, pump-rod and welded structures. It is an open system which may be broadened and perfected to cover a wider range of engineering application through the modification and enlargement of knowledge bases and data-bases. It has a natural and friendly interface that may be easily operated. An on-line help service is also provided.

Genetic Structure and Indica/Japonica Component Changes in Major Inbred Rice Varieties in China

We used 39 SSR markers to analyze the genetic structure of 304 major Chinese inbred rice varieties, and to compare changes in the indica or japonica components in these varieties that have been widely cultivated from the 1950s to the 1990s in China. The genetic structure analysis showed that these rice varieties were distinctly divided into two populations,＇ indica and japonica. The sub-structure of indica varieties was more complex than that of japonica ones. Among the various lines, late-season indica and early season japonica varieties had simpler genetic backgrounds. The seasonal ecotypes were not quite consistent with the subtypes of genetic structure. Twelve SSR loci with specific differentiation between indica and japonica were used to calculate the indica/japonica components. The differences in indica/japonica components among the five decades were not significant, except for late-season indica varieties in the 1990s, which had a significantly higher japonica component. These results will help to understand the genetic structure of the major Chinese inbred rice varieties and will be useful for indica-japonica hybrid breeding in China.

THREE-DIMENSIONAL STATIC ANALYSES FOR FGM PLATES WITH MEDIUM COMPONENTS AND DIFFERENT NET STRUCTURES

A new microelement method for the analyses of functionally graded structures was proposed. The key of this method is the maneuverable combination of two kinds of elements. Firstly, the macro elements are divided from the functionally graded material structures by the normal finite elements. In order to reflect the functionally graded distributions of materials and the microconstitutions in each macro-element, the microelement method sets up the dense microelements in every macro-element, and translates nodes to the same as the normal finite elements by the degrees of freedom of all microelemental the compatibility conditions. This microelement method can fully reflect the micro constitutions and different components of materials, and its computational elements are the same as the normal finite elements, so it is an effective numerical method for the analyses of the functionally graded material structures. The three-dimensional analyses of functionally graded plates with medium components and different micro net structures are given by using the microelement method in this paper. The differences of the stress contour in the plane of functionally graded plates with different net microstructures are especially given in this paper.

Seismic response of large-span spatial structures under multi-support and multidimensional excitations including rotational components

To achieve rational and precise seismic response predictions of large span spatial structures(LSSSs),the inherent non-uniformity and multidimensionality characteristics of earthquake ground motions should be properly taken into consideration.However,due to the limitations of available earthquake stations to record seismic rotational components,the effects of rocking and torsional earthquake components are commonly neglected in the seismic analyses of LSSSs.In this study,a newly developed method to extract the rocking and torsion components at any point along the area of a deployed dense array from the translational earthquake recordings is applied to obtain the rotational seismic inputs for a LSSS.The numerical model of an actual LSSS,the Dalian International Conference Center(DICC),is developed to study the influences of multi-support and multidimensional excitations on the seismic responses of LSSSs.The numerical results reveal that the non-uniformity and multidimensionality of ground motion input can considerably affect the dynamic response of the DICC.The specific degree of influence on the overall and local structural displacements,deformations and forces are comprehensively investigated and discussed.

gscaLCA in R: Fitting Fuzzy Clustering Analysis Incorporated with Generalized Structured Component Analysis

Clustering analysis identifying unknown heterogenous subgroups of a population(or a sample)has become increasingly popular along with the popularity of machine learning techniques.Although there are many software packages running clustering analysis,there is a lack of packages conducting clustering analysis within a structural equation modeling framework.The package,gscaLCA which is implemented in the R statistical computing environment,was developed for conducting clustering analysis and has been extended to a latent variable modeling.More specifically,by applying both fuzzy clustering(FC)algorithm and generalized structured component analysis(GSCA),the package gscaLCA computes membership prevalence and item response probabilities as posterior probabilities,which is applicable in mixture modeling such as latent class analysis in statistics.As a hybrid model between data clustering in classifications and model-based mixture modeling approach,fuzzy clusterwise GSCA,denoted as gscaLCA,encompasses many advantages from both methods:(1)soft partitioning from FC and(2)efficiency in estimating model parameters with bootstrap method via resolution of global optimization problem from GSCA.The main function,gscaLCA,works for both binary and ordered categorical variables.In addition,gscaLCA can be used for latent class regression as well.Visualization of profiles of latent classes based on the posterior probabilities is also available in the package gscaLCA.This paper contributes to providing a methodological tool,gscaLCA that applied researchers such as social scientists and medical researchers can apply clustering analysis in their research.

Peak earthquake response of structures under multi-component excitations

Accurate estimation of the peak seismic responses of structures is important in earthquake resistant design. The internal force distributions and the seismic responses of structures are quite complex, since ground motions are multidirectional. One key issue is the uncertainty of the incident angle between the directions of ground motion and the reference axes of the structure. Different assumed seismic incidences can result in different peak values within the scope of design spectrum analysis for a given structure and earthquake ground motion record combination. Using time history analysis to determine the maximum structural responses excited by a given earthquake record requires repetitive calculations to determine the critical incident angle. This paper presents a transformation approach for relatively accurate and rapid determination of the maximum peak responses of a linear structure subjected to three-dimensional excitations within all possible seismic incident angles. The responses can be deformations, internal forces, strains and so on. An irregular building structure model is established using SAP2000 program. Several typical earthquake records and an artificial white noise are applied to the structure model to illustrate the variation of the maximum structural responses for different incident angles. Numerical results show that for many structural parameters, the variation can be greater than 100%. This method can be directly applied to time history analysis of structures using existing computer software to determine the peak responses without carrying out the analyses for all possible incident angles. It can also be used to verify and/or modify aseismic designs by using response spectrum analysis.

Mapping crustal S-wave velocity structure with SV-component receiver function method

In this article, we analyze the characters of SV-component receiver function of teleseismic body waves and its advantages in mapping the S-wave velocity structure of crust in detail. Similar to radial receiver function, SV-component receiver function can be obtained by directly deconvolving the P-component from the SV-component of teleseismic recordings. Our analyses indicate that the change of amplitude of SV-component receiver function against the change of epicentral distance is less than that of radial receiver function. Moreover, the waveform of SV-component receiver function is simpler than the radial receiver function and gives prominence to the PS converted phases that are the most sensitive to the shear wave velocity structure in the inversion. The synthetic tests show that the convergence of SV-component receiver function inversion is faster than that of the radial receiver function inversion. As an example, we investigate the S-wave velocity structure beneath HIA sta-tion by using the SV-component receiver function inversion method.

Integrable Coupling of (2+1)-Dimensional Multi-component DLW Integrable Hierarchy and Its Hamiltonian Structure

新多部件谎言代数学被构造，并且新环代数学的一种类型被介绍。A (2+1 ) 维的多部件 DLW integrable 层次被使用获得一(2+1 ) 维零个弯曲方程。而且，循环代数学被扩展进更大的，联合系统和它的相应 Hamiltonian 结构的 integrable 的一种类型被得出。

Design, Analysis and R&D of the EAST In-Vessel Components

In-vessel components are important parts of the EAST superconducting tokamak. They include the plasma facing components, passive plates, cryo-pumps, in-vessel coils, etc. The structural design, analysis and related R＆D have been completed. The divertor is designed in an up-down symmetric configuration to accommodate both double null and single null plasma operation. Passive plates are used for plasma movement control. In-vessel coils are used for the active control of plasma vertical movements. Each cryo-pump can provide an approximately 45 m^3/s pumping rate at a pressure of 10^-1 Pa for particle exhaust. Analysis shows that, when a plasma current of 1 MA disrupts in 3 ms, the EM loads caused by the eddy current and the halo current in a vertical displacement event （VDE） will not generate an unacceptable stress on the divertor structure. The bolted divertor thermal structure with an active cooling system can sustain a load of 2 MW/m^2 up to a 60 s operation if the plasma facing surface temperature is limited to 1500 ℃. Thermal testing and structural optimization testing were conducted to demonstrate the analysis results.

Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks

In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independently of persistence and heteroskedasticity properties, accounting for common deterministic and stochastic factors. Monte Carlo results strongly support the proposed methodology, validating its use also for relatively small cross-sectional and temporal samples.