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FORTRAN 4 program for calculating dynamic Kirchhoff deformation of structural rings subjected to fragment impact
Determining the approximate crushing stress of hexagonal cell structures subject to axial loading
System of three computer programs developed for use with BOPACE finite-element program for analyzing cumulative plastic deformation of structures subject to high thermomechanical load cycles.
This Letter investigates the external deformation on modifying the polymer–nanoparticle (NP) and NP–NP interactions as well as their influences on the macroscopic properties of polymer nanocomposites (PNCs). Specifically, the applied uniaxial extension brings together the NPs along the transverse stretching direction and catalyzes the percolation transition from the initially well-dispersed NPs in the PNCs. The percolated NP network thus increases the strength of PNCs and leads to a strong surge in the elongation viscosity at very low strain rates, exhibiting the unexpected nonmonotonic strain rate dependence on the strain hardening. These results reveal explicitly the unconventional roles of the external deformation on modulating the relative strength of the polymer–NP and the NP–NP interactions, enabling advanced structures and properties control of PNCs.
Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.
Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include 1) diagnostic/detection methodology, 2) prognosis/lifing methodology, 3) diagnostic/prognosis linkage, 4) experimental validation and 5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multi-mechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.
Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.
The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the potential of the combined use of lidar samples and radar imagery for forest biomass mapping. Various issues regarding lidar/radar data synergies for biomass mapping are discussed in the paper.
Excited structures in 104 Mo were populated by β decays of the ground and isomeric states in the neutron-rich nucleus 104 Nb. The beams were produced by the CARIBU facility at Argonne National Laboratory, re-accelerated by the ATLAS accelerator and implanted on a moving-tape system in the middle of the GAMMASPHERE array. Separate decay schemes for the two β-decaying states in 104 Nb were constructed for the first time. The structure of the isomers are discussed in the framework of the deformed Nilsson model and systematics of known quasiparticle structures in neighboring nuclei.
Methods for estimating the deformation of adaptive truss structures are proposed which employ internal displacement sensors to measure changes in the length of selected truss members. Based on the measured data from the instrumented truss member, the total truss deformation pattern can be estimated through direct interpolation. To verify the validity of the methods presented here, numerical simulations are carried out for simple plane trusses, a beam truss, and a tetrahedral truss.
This is a final report as far as our work at University of Minnesota is concerned. The report describes our research progress and accomplishments in development of high performance computing methods and tools for 3D finite element computation of aerodynamic characteristics and fluid-structure interactions (FSI) arising in airdrop systems, namely ram-air parachutes and round parachutes. This class of simulations involves complex geometries, flexible structural components, deforming fluid domains, and unsteady flow patterns. The key components of our simulation toolkit are a stabilized finite element flow solver, a nonlinear structural dynamics solver, an automatic mesh moving scheme, and an interface between the fluid and structural solvers; all of these have been developed within a parallel message-passing paradigm.
Additively manufactured lattice truss structures, often referred to as architected cellular materials, present significant advantages over conventional structures due to their unique characteristics such as high strength-to-weight ratios and surface area-to-volume ratios. These geometrically complex structures, however, come with concomitant challenges for qualification and inspection. In this study, compression testing interrupted with micro-computed tomography inspection was conducted to monitor the evolution of global and local deformation throughout the loading process of 304L stainless steel octet truss lattice structures. Both two- and three-dimensional image analysis techniques were leveraged to characterize geometric heterogeneities resulting from the laser powder bed fusion manufacturing process as well as track the structure throughout deformation. Variations from model-predicted behavior resulting from these heterogeneities are considered relative to the predicted and actual responses of the structures during compression to better understand, model, and predict the octet truss lattice structure compression response.
We present a structure-based numerical analysis of passive scalar mixing in decaying homogeneous isotropic turbulence (DHIT) and shock-turbulence interaction canonical configurations. The analysis focuses on the temporal evolution of ensembles of passive scalar structures, initialized as spheres of different sizes relative to the Taylor microscale. An algorithm is introduced to track the evolution of each individual structure and the interactions with other structures in the ensemble, relating changes in the surface geometry and the underlying physical processes (turbulent transport, scalar dissipation, and shock compression). The tracking algorithm is applied to datasets from shock-capturing direct numerical simulations of DHIT, with Taylor microscale Reynolds number Re λ =40 and turbulence Mach number M t =0.2 , and STI cases in which the turbulence is processed by a shock wave at Mach numbers M = 1.5 and 3.0. Temporal surface convolution increases for initially larger structures, resulting in a higher probability of locally hyperbolic geometries where breakup into smaller structures occurs. Shock-induced deformation of the structures amplifies breakup processes, enhancing mixing, particularly for larger structures. Mixing enhancement by the shock is manifested as an amplification of the surface-averaged scalar gradient, which increases for initially larger structures. The alignment between the scalar gradient and the most extensional strain-rate eigendirection on the scalar isosurfaces also increases across the shock. Larger magnitudes of the scalar gradient and its alignment with the most compressive strain-rate eigendirection correlate with flatter surface regions. Shock-induced structure compression increases the area coverage of flat regions, where the amplification of scalar gradient is localized.
This paper is concerned with the vibrational characteristics of rotating flexible structures in the neighborhood of steady rotation. It is assumed that the structure undergoes deformations during the steady rotation, so that the equilibrium is nontrivial. The object of the paper is to formulate the eigenvalue problem associated with small oscillations of the structure about the nontrivial equilibrium and to develop efficient methods to compute the system natural frequencies and modal vectors. A numerical example showing the procedure for the calculation of spacecraft modes is presented.
Papers are presented on the nonlinear dynamic analysis of quasi-symmetric anisotropic structures, the analysis of large deformations of membrane shells by the generalized finite difference method, the vibration of shear-deformable laminated plate structures by the finite strip method, and Coon's surface method for the formulation of finite elements for plates and shells. Other topics include an evaluation of higher-order modal methods for calculating the transient structural response, a nonlinear dynamic analysis of frame structures, and a nonlinear analysis of a truss by energy minimization. Also considered are an incremental Galerkin method for plates and stiffened plates, a comparison of the postbuckling behavior of plates and shells, and a general solution of bending in a cylindrical shell.
The manufacturing of composites typically produces residual stresses that can significantly affect the final shape of the structure. The process of automated fiber placement (AFP) has become a prominent manufacturing technique in developing layups with tailored, variable stiffness morphology. The steered patterns of fiber tows with and without overlaps produce residual deformations that are distinctive from traditional layups. Digital image correlation was used to measure the AFP lamina coefficients of thermal expansion, which were incorporated into finite element analyses (FEA) to model the cooling phase of the cure cycle. The effects of nonlinear analysis and temperature-dependent lamina properties calculated using self-consistent field micromechanics, on the resulting residual deformation of shells, were also modeled. The predicted residual deformation was analyzed by considering out-of-roundness in cylindrical shells and compared to the experimental results. The shell FEA results were well-correlated with the overall deformed shape of the AFP cylinder with overlaps, while the shell FEA model of the AFP cylinder without overlaps did not show as good of qualitative match of the deformation pattern. Analytical correlation with measured results were insensitive to material softening at elevated temperatures, geometric nonlinearities, and variations in measured lamina thermal properties. To improve the accuracy of the residual deformation analysis, these results suggest that the thermo-chemical shrinkages preceding the cooldown should be considered, as well as possible variations in ply level microstructure due to the presence of the embedded fiber tow gaps and overlaps.
A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amid a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results from the symmetry-adapted no-core shell model (SA-NCSM) for light nuclei. We show that the SA-NCSM, which expands ab initio applications up to medium-mass nuclei by using dominant symmetries of nuclear dynamics, can reach heavier nuclei when coupled with the machine learning approach. In particular, we find that a neural network trained on probability amplitudes for s- and p-shell nuclear wave functions not only predicts dominant configurations for heavier nuclei but in addition, when tested for the 20 Ne ground state, accurately reproduces the probability distribution. The non-negligible configurations predicted by the network provide an important input to the SA-NCSM for reducing ultralarge model spaces to manageable sizes that can be, in turn, utilized in SA-NCSM calculations to obtain accurate observables. The neural network is capable of describing nuclear deformation and is used to track the shape evolution along the 20-42 Mg isotopic chain, suggesting a shape coexistence that is more pronounced toward the very neutron-rich isotopes. We provide first descriptions of the structure and deformation of 24 Si and 40 Mg of interest to x-ray burst nucleosynthesis, and even of the extremely heavy nuclei such as 166,168 Er and 236 U, that build on first-principles considerations.
The author discusses structural formations in the northern deformation belt of Venus, studied according to the data of the radar pictures obtained with the Venera 15 and 16 probes. He shows that it consists of regions of compression with submeridional orientation, regions of displacement, extending in the sublatitudinal direction and individual slightly deformed blocks. He puts forward the hypothesis that the formation of these structures is related with horizontal movements in the mantle in the sublatitudinal direction.