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At least 181 records · Page 10

Adhesive-Bonded Composite Joint Analysis with Delaminated Surface Ply Using Strain-Energy Release Rate

This paper presents an analytical model to determine the strain energy release rate due to an interlaminar crack of the surface ply in adhesively bonded composite joints subjected to axial tension. Single-lap shear-joint standard test specimen geometry with thick bondline is followed for model development. The field equations are formulated by using the first-order shear-deformation theory in laminated plates together with kinematics relations and force equilibrium conditions. The stress distributions for the adherends and adhesive are determined after the appropriate boundary and loading conditions are applied and the equations for the field displacements are solved. The system of second-order differential equations is solved to using the symbolic computation tool Maple 9.52 to provide displacements fields. The equivalent forces at the tip of the prescribed interlaminar crack are obtained based on interlaminar stress distributions. The strain energy release rate of the crack is then determined by using the crack closure method. Finite element analyses using the J integral as well as the crack closure method are performed to verify the developed analytical model. It has been shown that the results using the analytical method correlate well with the results from the finite element analyses. An attempt is made to predict the failure loads of the joints based on limited test data from the literature. The effectiveness of the inclusion of bondline thickness is justified when compared with the results obtained from the previous model in which a thin bondline and uniform adhesive stresses through the bondline thickness are assumed.

Chadegani, Alireza↗

The effect of thickness on fatigue crack propagation in 7475-T731 aluminum alloy sheet

Tests were conducted on three thicknesses of 7475-T731 aluminum alloy sheet to investigate the effect of thickness on fatigue crack propagation under constant amplitude loading conditions and on retardation following a single peak overload. Constant amplitude loading tests were performed at stress ratios of 0.05 and 0.75 to obtain data for conditions with crack closure and without crack closure, respectively. At both stress ratios a thickness effect was clearly evident, with thicker specimens exhibiting higher growth rates in the transition from plane strain to plane stress region. The effect of thickness for a stress ratio of 0.05 corresponded well with the fracturing mode transitions observed on the specimens. A model based on the strain energy release rate which accounted for the fracture mode transition was found to correlate the thickness effects well. The specimens tested at the stress ratio of 0.75 did not make the transition from tensile mode to shear mode, indicating that another mechanism besides crack closure or fracture mode transition was active.

Daiuto, R. A.↗

Comprehensive framework for data-driven model form discovery of the closure laws in thermal-hydraulics codes

The two-phase two-fluid model is a basis of many thermal-hydraulics codes used in design, licensing, and safety considerations of nuclear power plants. Thermal-hydraulics codes rely on the closure laws to close the system of conservation equations and describe the interactions between phases. These laws, derived from years of experimental investigations, are semi-empirical correlations that lack generality and have a limited range of applicability. Increase of computational power, availability of new experiments, and development of high-fidelity simulations has increased the number of validation data. The discrepancies between the code predictions and the validation data are a great source of knowledge. Missing physics that are not included in the model but are important for the considered phenomena can be discovered by propagating the information from the experimental results through the model. Furthermore, physics-discovered data-driven model form (P3DM) methodology integrates available integral effect tests and separate effects tests to determine the necessary corrections to the model form of the closure laws. In contrast to existing calibration techniques, the methodology modifies the functional form of the closure laws. Based on the functional form of the correction, the missing physics that were not included in the original model can be discovered. The methodology provides the alternative to the machine learning approach, in which the model is discovered in the form of the intractable black-box relation. In this work, the methodology was applied to the CTF subchannel code to improve the prediction of the two-phase flow phenomena.

42 ENGINEERING↗

Doping a bad metal: Origin of suppression of the metal-insulator transition in nonstoichiometric VO 2

Rutile ( R ) phase VO 2 is a quintessential example of a strongly correlated bad metal, which undergoes a metal-insulator transition (MIT) concomitant with a structural transition to a V-V dimerized monoclinic ( M 1 ) phase below T MIT ~ 340 K . It has been experimentally illustrated that one can control this transition by doping VO 2 . In particular, doping with oxygen vacancies ( V O ) has been shown to completely suppress this MIT without any structural transition. We explain this suppression by elucidating the influence of oxygen vacancies on the electronic structure of the metallic R phase VO 2 , explicitly treating strong electron-electron correlations using dynamical mean-field theory (DMFT) as well as diffusion Monte Carlo (DMC) flavor of quantum Monte Carlo (QMC) techniques. DMC calculations show a gap closure in the M 1 phase when vacancies are present, suggesting that when vacancies are introduced in the high-temperature rutile phase, the dimerized insulating phase cannot be reached when temperature is lowered. Both DMFT and DMC calculations of nonstoichiometric metallic rutile phase shows that this tendency not to dimerize in the presence of vacancies is because V O 's tend to change the V - 3 d filling away from its nominal half-filled value, with the e g π orbitals competing with the otherwise dominant a 1 g orbital. Loss of this near orbital polarization of the a 1 g orbital is associated with a weakening of electron correlations, especially along the V-V dimerization direction. This removes a charge-density wave (CDW) instability along this direction above a critical doping concentration, which further suppresses the metal-insulator transition. Our research further suggests that the MIT is predominantly driven by a correlation-induced CDW instability along the V-V dimerization direction.

36 MATERIALS SCIENCE↗

Correlations of neutron multiplicity and γ -ray multiplicity with fragment mass and total kinetic energy in spontaneous fission of Cf 252

The dependence of correlations of neutron multiplicity ν and γ-ray multiplicity M γ in spontaneous fission of 252 Cf on fragment mass A* and total kinetic energy (TKE) have been investigated by employing the ratio of M γ /ν and the form of M γ (ν). We show for the first time that M γ and ν have a complex correlation for heavy fragment masses, while there is a positive dependence of Mγ for light fragment masses and for near-symmetric mass splits. The ratio M γ /ν exhibits strong shell effects for neutron magic number N=50 and near doubly magic number shell closure at Z=50 and N=82. The γ-ray multiplicity Mγ has a maximum for TKE=165-170 MeV. Above 170 MeV M γ (TKE) is approximately linear, while it deviates significantly from a linear dependence at lower TKE. The correlation between the average neutron and γ-ray multiplicities can be partly reproduced by model calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Laboratory characterization of PM emissions from combustion of wildland biomass fuels

Particle emissions from open burning of southwestern (SW) and southeastern (SE) U.S. 17 fuel types during 77 controlled laboratory burns are presented. The fuels include SW 18 vegetation types: ceanothus, chamise/scrub oak, coastal sage scrub, California sagebrush, 19 manzanita, maritime chaparral, masticated mesquite, oak savanna, and oak woodland as 20 well as SE vegetation types: 1-year, 2-year rough, pocosin, chipped understory, 21 understory hardwood, and pine litter. The SW fuels burned at a higher Modified 22 Combustion Efficiency (MCE) than the SE fuels resulting in lower particulate matter 23 (PM) mass emission factor (EF). Particle size distributions for six fuels and particle 24 number emission or all fuels are reported. Excellent mass closure (slope = 1.00, r2=0.94) 25 between ions, metals, and carbon with total weight was obtained. Organic carbon 26 emission factors inversely correlated (= 0.72) with MCE, while elemental carbon (EC) 27 had little correlation with MCE (=0.10). The EC/total carbon (TC) ratio sharply 28 increased with MCE for MCEs exceeding 0.94. The average levoglucosan and total Poly 29 Aromatic Hydrocarbons (PAH) emissions factors ranged from 25-1272 mg/kg fuel and 30 1790-11300 μg/kg fuel, respectively. No correlation between MCE and emissions of 31 PAHs/levoglucosan was found. Additionally, PAH diagnostic ratios were observed to be 32 poor indicators of biomass burning. Large fuel-type and regional dependency was 33 observed in the emission rates of ammonium, nitrate, fluoride, chloride, sodium, and

Hosseini, SeyedEhsan↗

Revealing complex subsurface dynamics with continuous seismic monitoring: Observations using distributed acoustic sensing and surface orbital vibrators during hydraulic fracturing

Understanding hydraulic fracturing is crucial to improving the stimulation of unconventional reservoirs and increasing fluid production. This study develops a novel seismic monitoring technology using distributed acoustic sensing (DAS) and surface orbital vibrators (SOV) to capture fracture seismic response and mechanical properties at high temporal intervals. We analyze continuous time-lapse vertical seismic profiling (VSP) data acquired every hour during the first nine days of treatment of an unconventional reservoir in the Austin Chalk/Eagle Field Laboratory. The VSP data contain clear seismic signals scattered from the activated fractures. The spatiotemporal changes of the fracture reflectivity revealed by the SOV/DAS data correlate well with the observations of fracture locations inferred from low-frequency DAS data. These results capture the fracture opening and closure processes, as well as highlight potential prestage activations of the fractures due to hydraulic connectivity with preexisting fracture systems. Therefore, analysis of the presented data set provides a unique opportunity to understand fracture initiation and subsequent evolution, not only in the context of unconventional resources but also in enhanced geothermal systems.

Correa, Julia↗

Handling properties of diverse automobiles and correlation with full scale response data

Driver/vehicle response and performance of a variety of vehicles in the presence of aerodynamic disturbances are discussed. Steering control is emphasized. The vehicles include full size station wagon, sedan, compact sedan, van, pickup truck/camper, and wagon towing trailer. Driver/vehicle analyses are used to estimate response and performance. These estimates are correlated with full scale data with test drivers and the results are used to refine the driver/vehicle models, control structure, and loop closure criteria. The analyses and data indicate that the driver adjusts his steering control properties (when he can) to achieve roughly the same level of performance despite vehicle variations. For the more disturbance susceptible vehicles, such as the van, the driver tightens up his control. Other vehicles have handling dynamics which cause him to loosen his control response, even though performance degrades.

Hoh, R. H.↗

Comments on the present state and future directions of PDF methods

The one point probability density function (PDF) method is examined in light of its use in actual engineering problems. The PDF method, although relatively complicated, appears to be the only format available to handle the nonlinear stochastic difficulties caused by typical reaction kinetics. Turbulence modeling, if it is to play a central role in combustion modeling, has to be integrated with the chemistry in a way which produces accurate numerical solutions to combustion problems. It is questionable whether the development of turbulent models in isolation from the peculiar statistics of reactant concentrations is a fruitful line of development as far as propulsion is concerned. There are three issues for which additional viewgraphs are prepared: the one point pdf method; the amplitude mapping closure; and a hybrid strategy for replacing a full two point pdf treatment of reacting flows by a single point pdf and correlation functions. An appeal is made for the establishment of an adequate data base for compressible flow with reactions for Mach numbers of unity or higher.

Obrien, E. E.↗

LES, DNS, and RANS for the Analysis of High-Speed Turbulent Reacting Flows

A filtered density function (FDF) method suitable for chemically reactive flows is developed in the context of large eddy simulation. The advantage of the FDF methodology is its inherent ability to resolve subgrid scales (SGS) scalar correlations that otherwise have to be modeled. Because of the lack of robust models to accurately predict these correlations in turbulent reactive flows, simulations involving turbulent combustion are often met with a degree of skepticism. The FDF methodology avoids the closure problem associated with these terms and treats the reaction in an exact manner. The scalar FDF approach is particularly attractive since it can be coupled with existing hydrodynamic computational fluid dynamics (CFD) codes.

Colucci, P. J.↗

Turbulence modeling and experiments

The best way of verifying turbulence is to do a direct comparison between the various terms and their models. The success of this approach depends upon the availability of the data for the exact correlations (both experimental and DNS). The other approach involves numerically solving the differential equations and then comparing the results with the data. The results of such a computation will depend upon the accuracy of all the modeled terms and constants. Because of this it is sometimes difficult to find the cause of a poor performance by a model. However, such a calculation is still meaningful in other ways as it shows how a complete Reynolds stress model performs. Thirteen homogeneous flows are numerically computed using the second order closure models. We concentrate only on those models which use a linear (or quasi-linear) model for the rapid term. This, therefore, includes the Launder, Reece and Rodi (LRR) model; the isotropization of production (IP) model; and the Speziale, Sarkar, and Gatski (SSG) model. Which of the three models performs better is examined along with what are their weaknesses, if any. The other work reported deal with the experimental balances of the second moment equations for a buoyant plume. Despite the tremendous amount of activity toward the second order closure modeling of turbulence, very little experimental information is available about the budgets of the second moment equations. Part of the problem stems from our inability to measure the pressure correlations. However, if everything else appearing in these equations is known from the experiment, pressure correlations can be obtained as the closing terms. This is the closest we can come to in obtaining these terms from experiment, and despite the measurement errors which might be present in such balances, the resulting information will be extremely useful for the turbulence modelers. The purpose of this part of the work was to provide such balances of the Reynolds stress and heat flux equations for the buoyant plume.

Shabbir, Aamir↗

A priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence

In the present study, we investigate different data-driven parameterizations for large eddy simulation of two-dimensional turbulence in the a priori settings. These models utilize resolved flow field variables on the coarser grid to estimate the subgrid-scale stresses. We use data-driven closure models based on localized learning that employs a multilayer feedforward artificial neural network with point-to-point mapping and neighboring stencil data mapping, and convolutional neural network fed by data snapshots of the whole domain. The performance of these data-driven closure models is measured through a probability density function and is compared with the dynamic Smagorinksy model (DSM). The quantitative performance is evaluated using the cross-correlation coefficient between the true and predicted stresses. We analyze different frameworks in terms of the amount of training data, selection of input and output features, their characteristics in modeling with accuracy, and training and deployment computational time. We also demonstrate computational gain that can be achieved using the intelligent eddy viscosity model that learns eddy viscosity computed by the DSM instead of subgrid-scale stresses. Here, we detail the hyperparameters optimization of these models using the grid search algorithm.

42 ENGINEERING↗

A second-order closure analysis of turbulent diffusion flames

A complete second-order closure computer program for the investigation of compressible, turbulent, reacting shear layers was developed. The equations for the means and the second order correlations were derived from the time-averaged Navier-Stokes equations and contain third order and higher order correlations, which have to be modeled in terms of the lower-order correlations to close the system of equations. In addition to fluid mechanical turbulence models and parameters used in previous studies of a variety of incompressible and compressible shear flows, a number of additional scalar correlations were modeled for chemically reacting flows, and a typical eddy model developed for the joint probability density function for all the scalars. The program which is capable of handling multi-species, multistep chemical reactions, was used to calculate nonreacting and reacting flows in a hydrogen-air diffusion flame.

Varma, A. K.↗

Analysis of Composite Skin-Stiffener Debond Specimens Using Volume Elements and a Shell/3D Modeling Technique

The debonding of a skin/stringer specimen subjected to tension was studied using three-dimensional volume element modeling and computational fracture mechanics. Mixed mode strain energy release rates were calculated from finite element results using the virtual crack closure technique. The simulations revealed an increase in total energy release rate in the immediate vicinity of the free edges of the specimen. Correlation of the computed mixed-mode strain energy release rates along the delamination front contour with a two-dimensional mixed-mode interlaminar fracture criterion suggested that in spite of peak total energy release rates at the free edge the delamination would not advance at the edges first. The qualitative prediction of the shape of the delamination front was confirmed by X-ray photographs of a specimen taken during testing. The good correlation between prediction based on analysis and experiment demonstrated the efficiency of a mixed-mode failure analysis for the investigation of skin/stiffener separation due to delamination in the adherents. The application of a shell/3D modeling technique for the simulation of skin/stringer debond in a specimen subjected to three-point bending is also demonstrated. The global structure was modeled with shell elements. A local three-dimensional model, extending to about three specimen thicknesses on either side of the delamination front was used to capture the details of the damaged section. Computed total strain energy release rates and mixed-mode ratios obtained from shell/3D simulations were in good agreement with results obtained from full solid models. The good correlations of the results demonstrated the effectiveness of the shell/3D modeling technique for the investigation of skin/stiffener separation due to delamination in the adherents.

Krueger, Ronald↗

Data-Driven Closures and Assimilation for Stiff Multiscale Random Dynamics

Here, we introduce a data-driven and physics-informed framework for propagating uncertainty in stiff, multiscale random ordinary differential equations (RODEs) driven by correlated (colored) noise. Unlike systems subjected to Gaussian white noise, a deterministic equation for the joint probability density function (PDF) of RODE state variables does not exist in closed form. Moreover, such an equation would require as many phase-space variables as there are states in the RODE system. To alleviate this curse of dimensionality, we instead derive exact, albeit unclosed, reduced-order PDF (RoPDF) equations for low-dimensional observables/quantities of interest. The unclosed terms take the form of state-dependent conditional expectations, which are directly estimated from data at sparse observation times. However, for systems exhibiting stiff, multiscale dynamics, data sparsity introduces regression discrepancies that compound during RoPDF evolution. This is overcome by introducing a kinetic-like defect term to the RoPDF equation, which is learned by assimilating in sparse, low-fidelity RoPDF estimates. Two assimilation methods are considered, namely nudging and deep neural networks, which are successfully tested against Monte Carlo simulations.

97 MATHEMATICS AND COMPUTING↗

Direct observations and characterization of crack closure during microstructurally small fatigue crack growth via in-situ high-energy X-ray characterization

This study provides direct observation of the crack closure mechanism of a naturally occurring, tortuous, 3D microstructurally small fatigue crack (SFC) in additively manufactured Inconel 718. In-situ non-destructive characterization is performed using high-energy X-ray diffraction techniques to capture the evolution of the 3D microstructure and micromechanical response in the vicinity of the crack front. Based on the stress state of twelve grains analyzed at the crack tip, the crack closure events of the SFC front was found to be spatially heterogeneous with respect to loading progression governed by the local stress state of the grains (specifically the stress reversal from compression to tension). From this analysis, three grains that displayed different degrees of crack closure were further investigated, based on the orientation of the crack relative to the grains and the associated modality of crack growth. The stress normal to the crack plane and the associated degree of Mode I crack behavior were correlated with events of the crack opening earlier during the loading cycle. This was further corroborated by diffraction spot spreading analysis that quantified the crystallographic lattice distortion caused by the opening crack. Additionally, the detailed characterization of the opening behavior of the grains located at the crack tip and their associated states of stress elucidates the mechanism governing crack closure and will inform future modeling efforts of this phenomenon.

36 MATERIALS SCIENCE↗

Simulating Mixed‐Phase Open Cellular Clouds Observed During COMBLE: Evaluation of Parameterized Turbulence Closure

Marine cold-air outbreaks, or CAOs, are airmass transformations whereby relatively cold boundary layer (BL) air is transported over relatively warm water. To more deeply understand BL and mixed-phase cloud properties during CAO conditions, the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) took place from late 2019 into early 2020. During COMBLE, the U.S. Department of Energy's first Atmospheric Radiation Measurement Mobile Facility (AMF1) was deployed to Andenes, Norway, far downstream (~1,000 km) from the Arctic pack ice. This study examines the two most intense CAOs sampled at the AMF1 site. The observed BL structures are open cellular with high (~3–5 km) and cold (–30 to –50 °C) cloud tops, and they often have pockets of high liquid water paths (LWPs; up to ~1,000 g m –2 ) associated with strong updrafts and enhanced turbulence. We use a high-resolution mesoscale model to explore how well four turbulence closure methods represent open cellular clouds. After applying a radar simulator to model outputs for direct evaluation, cloud top properties agree well with AMF1 observations (within ~10%), but radar reflectivity and LWP agreement is more variable. Results suggest that the turbulent Prandtl number may play an important role for the simulated BL and cloud properties. All simulations produce enhanced precipitation rates that are well-correlated with a cloud transition. Finally, the eddy-diffusivity/mass-flux approach produces the deepest cloud layer and therefore the largest and most coherent cellular structures. Furthermore, we recommend the use of a non-local turbulence closure approach to better capture turbulent processes in intense CAOs.

54 ENVIRONMENTAL SCIENCES↗